CaRLO

Description: Current methods for estimating heat vulnerability of young athletes use a heat index (HI) or a wet bulb globe thermometer (WBGT), neither of which fully include the environmental or physiological characteristics that can affect a person’s heat budget, particularly where activity occurs on a synthetic surface. This study analyzed and compared the standard methods, HI and WBGT, with a novel and more comprehensive method termed COMFA-Kid (CK) which is based on an energy budget model explicitly designed for youth. The COMFA model was presented at the same time to demonstrate the difference between a child and an adult during activity. Micrometeorological measurements were taken at a synthetic-surfaced football field during mid-day in hot environmental conditions. Standard methods (HI and WBGT) indicated that conditions on the field were relatively safe for youth to engage in activities related to football practice or games, whereas the CK method indicated that conditions were dangerously hot and could lead to exertional heat illness. Estimates using the CK method also indicated that coaches and staff standing on the sidelines, and parents sitting in the stands, would not only be safe from heat but would be thermally comfortable. The difference in thermal comfort experienced by coaches and staff off the field, versus that experienced by young players on the field, could affect decision making regarding the duration and intensity of practices and time in the game. The CK method, which is easy to use and available for modification for specific conditions, would lead to more accurate estimates of heat safety on outdoor synthetic surfaces in particular, and in sports with a high prevalence of heat illness such as football, and should be considered as a complementary or alternative preventive measure against heat.

Description: Exome sequencing has been commonly used to characterize rare diseases by selecting multiplex families or singletons with an extreme phenotype (EP) and searching for rare variants in coding regions. The EP strategy covers both extreme ends of a disease spectrum and it has been also used to investigate the contribution of rare variants to the heritability of complex clinical traits. We conducted a systematic review to find evidence supporting the use of EP strategies in the search for rare variants in genetic studies of complex diseases and highlight the contribution of rare variations to the genetic structure of polygenic conditions. After assessing the quality of the retrieved records, we selected 19 genetic studies considering EPs to demonstrate genetic association. All studies successfully identified several rare or de novo variants, and many novel candidate genes were also identified by selecting an EP. There is enough evidence to support that the EP approach for patients with an early onset of a disease can contribute to the identification of rare variants in candidate genes or pathways involved in complex diseases. EP patients may contribute to a better understanding of the underlying genetic architecture of common heterogeneous disorders such as tinnitus or age-related hearing loss.

Description: Herein we investigate the usage of principal component analysis (PCA) and canonical variate analysis (CVA), in combination with the F factor clustering metric, for the a priori tailored selection of the optimal sensor array for a given electronic tongue (ET) application. The former allows us to visually compare the performance of the different sensors, while the latter allows us to numerically assess the impact that the inclusion/removal of the different sensors has on the discrimination ability of the ET. The proposed methodology is based on the measurement of a pure stock solution of each of the compounds under study, and the posterior analysis by PCA/CVA with stepwise iterative removal of the sensors that demote the clustering when retained as part of the array. To illustrate and assess the potential of such an approach, the quantification of paracetamol, ascorbic acid, and uric acid mixtures were chosen as the study case. Initially, an array of eight different electrodes was considered, from which an optimal array of four sensors was derived to build the quantitative ANN model. Finally, the performance of the optimized ET was benchmarked against the results previously reported for the analysis of the same mixtures, showing improved performance.

Description: This study develops an eye tracking method for autostereoscopic three-dimensional (3D) display systems for use in various environments. The eye tracking-based autostereoscopic 3D display provides low crosstalk and high-resolution 3D image experience seamlessly without 3D eyeglasses by overcoming the viewing position restriction. However, accurate and fast eye position detection and tracking are still challenging, owing to the various light conditions, camera control, thick eyeglasses, eyeglass sunlight reflection, and limited system resources. This study presents a robust, automated algorithm and relevant systems for accurate and fast detection and tracking of eye pupil centers in 3D with a single visual camera and near-infrared (NIR) light emitting diodes (LEDs). Our proposed eye tracker consists of eye–nose detection, eye–nose shape keypoint alignment, a tracker checker, and tracking with NIR LED on/off control. Eye–nose detection generates facial subregion boxes, including the eyes and nose, which utilize an Error-Based Learning (EBL) method for the selection of the best learnt database (DB). After detection, the eye–nose shape alignment is processed by the Supervised Descent Method (SDM) with Scale-invariant Feature Transform (SIFT). The aligner is content-aware in the sense that corresponding designated aligners are applied based on image content classification, such as the various light conditions and wearing eyeglasses. The conducted experiments on real image DBs yield promising eye detection and tracking outcomes, even in the presence of challenging conditions.

Description: This review critically summarizes the recent advances of the microcantilever-based force sensors for atomic force microscope (AFM) applications. They are one the most common mechanical spring–mass systems and are extremely sensitive to changes in the resonant frequency, thus finding numerous applications especially for molecular sensing. Specifically, we comment on the latest progress in research on the deflection detection systems, fabrication, coating and functionalization of the microcantilevers and their application as bio- and chemical sensors. A trend on the recent breakthroughs on the study of biological samples using high-speed atomic force microscope is also reported in this review.

Description: Obesity is currently becoming a serious global public health problem due to its high prevalence and continuous increase. This condition is associated with different physical and mental health problems. The presence of emotional disorders (anxiety, depression and related disorders) among candidates for bariatric surgery is very high and predicts worse physical and psychological results. The present study aims to explore the feasibility and clinical usefulness of the Unified Protocol, a transdiagnostic emotion regulation-based intervention, delivered in an online group format to patients with emotional disorder diagnosis or symptoms, who are waiting for bariatric surgery. We will conduct a pilot study with a repeated single-case experimental design (multiple baseline design) in a public mental health service. The sample will consist of 60 participants, who will be randomized to three baseline conditions: 8, 12 or 15 evaluation days before the intervention. Diagnostic criteria, symptomatology and body mass index are the primary outcome measures, and we will include affectivity, personality, quality of life, body image, eating behavior and surgical complications like secondary measures. An analysis of treatment satisfaction will be also performed. Assessment points will include pre-treatment, baseline, treatment, post-treatment, and follow-ups every three months until two years after post-treatment. The results obtained in this study may have important clinical, social and economic implications for public mental health.

Description: Dogs develop osteosarcoma (OSA) and the disease process closely resembles that of human OSA. OSA has a poor prognosis in both species and disease-free intervals and cure rates have not improved in recent years. Gene expression in canine OSAs was compared with non-tumor tissue utilising RNA sequencing, validated by qRT-PCR and immunohistochemistry (n = 16). Polymorphic polyglutamine (polyQ) tracts in the androgen receptor (AR/NR3C4) and nuclear receptor coactivator 3 (NCOA3) genes were investigated in control and OSA patients using polymerase chain reaction (PCR), Sanger sequencing and fragment analysis (n = 1019 Rottweilers, 379 Irish Wolfhounds). Our analysis identified 1281 significantly differentially expressed genes (〉2 fold change, p 〈 0.05), specifically 839 lower and 442 elevated gene expression in osteosarcoma (n = 3) samples relative to non-malignant (n = 4) bone. Enriched pathways and gene ontologies were identified, which provide insight into the molecular pathways implicated in canine OSA. Expression of a subset of these genes (SLC2A1, DKK3, MMP3, POSTN, RBP4, ASPN) was validated by qRTPCR and immunohistochemistry (MMP3, DKK3, SLC2A1) respectively. While little variation was found in the NCOA3 polyQ tract, greater variation was present in both polyQ tracts in the AR, but no significant associations in length were made with OSA. The data provides novel insights into the molecular mechanisms of OSA in high risk breeds. This knowledge may inform development of new prevention strategies and treatments for OSA in dogs and supports utilising spontaneous OSA in dogs to improve understanding of the disease in people.

Description: Oncobiotic transformation of the gut microbiome may contribute to the risk of breast cancer. Recent studies have provided evidence that the microbiome secretes cytostatic metabolites that inhibit the proliferation, movement, and metastasis formation of cancer cells. In this study, we show that indolepropionic acid (IPA), a bacterial tryptophan metabolite, has cytostatic properties. IPA selectively targeted breast cancer cells, but it had no effects on non-transformed, primary fibroblasts. In cell-based and animal experiments, we showed that IPA supplementation reduced the proportions of cancer stem cells and the proliferation, movement, and metastasis formation of cancer cells. These were achieved through inhibiting epithelial-to-mesenchymal transition, inducing oxidative and nitrosative stress, and boosting antitumor immune response. Increased oxidative/nitrosative stress was due to the IPA-mediated downregulation of nuclear factor erythroid 2-related factor 2 (NRF2), upregulation of inducible nitric oxide synthase (iNOS), and enhanced mitochondrial reactive species production. Increased oxidative/nitrosative stress led to cytostasis and reductions in cancer cell stem-ness. IPA exerted its effects through aryl hydrocarbon receptor (AHR) and pregnane X receptor (PXR) receptors. A higher expression of PXR and AHR supported better survival in human breast cancer patients, highlighting the importance of IPA-elicited pathways in cytostasis in breast cancer. Furthermore, AHR activation and PXR expression related inversely to cancer cell proliferation level and to the stage and grade of the tumor. The fecal microbiome’s capacity for IPA biosynthesis was suppressed in women newly diagnosed with breast cancer, especially with stage 0. Bacterial indole biosynthesis showed correlation with lymphocyte infiltration to tumors in humans. Taken together, we found that IPA is a cytostatic bacterial metabolite, the production of which is suppressed in human breast cancer. Bacterial metabolites, among them, IPA, have a pivotal role in regulating the progression but not the initiation of the disease.

Description: Svalbard is a singular region to study biodiversity. Located at a high latitude and geographically isolated, the archipelago possesses widely varying environmental conditions and unique flora and fauna communities. It is also here where particularly rapid environmental changes are occurring, having amongst the fastest increases in mean air temperature in the Arctic. One of the most common and species-rich invertebrate groups in Svalbard is the mites (Acari). We here describe the characteristics of the Svalbard acarofauna, and, as a baseline, an updated inventory of 178 species (one Ixodida, 36 Mesostigmata, 43 Trombidiformes, and 98 Sarcoptiformes) along with their occurrences. In contrast to the Trombidiformes and Sarcoptiformes, which are dominated in Svalbard by species with wide geographical distributions, the Mesostigmata include many Arctic species (39%); it would thus be an interesting future study to determine if mesostigmatid communities are more affected by global warming then other mite groups. A large number of new species (42 spp.) have been described from Svalbard, including 15 that have so far been found exclusively there. It is yet uncertain if any of these latter species are endemic: six are recent findings, the others are old records and, in most cases, impossible to verify. That the Arctic is still insufficiently sampled also limits conclusions concerning endemicity.

Description: It is acknowledged that construction safety is pivotal to the project management objectives. Meanwhile, the concept of resilience provides an effective and pragmatic countermeasure to improve the safety management level of construction projects. However, the “resilience” has not gained considerable attention in the construction safety management system. In this context, the paper aims to develop the key safety management factors for construction projects from the resilience perspective. Firstly, the theoretical framework and key safety management factors of construction safety management system based on the resilience theory are proposed. The importance of each factor is then obtained by using the method of structural equation modeling (SEM). The results indicate that information management, material and technology management, organization management and personnel management would improve the safety and resilience of the project. Specifically, improving the resilience of information flow to strengthen the interaction among elements of the system can enhance the safety management level. These findings can be used as references for construction safety managers to improve the abilities of preventing safety accidents and recovering after safety accidents.

Description: Among peritumoral cells, cancer-associated fibroblasts (CAFs) are major facilitators of tumor progression. This study describes the effects of two urokinase-derived, novel decapeptides, denoted as Pep 1 and its cyclic derivative Pep 2. In a mouse model of tumor dissemination, using HT1080 fibrosarcoma cells, Pep 2 reduced the number and size of lung metastases. Specific binding of fluoresceinated Pep 2 to HT1080 and telomerase immortalised fibroblasts (TIF) cell surfaces was enhanced by αv overexpression or abolished by excess vitronectin, anti-αv antibodies or silencing of ITGAV αv gene, identifying αv-integrin as the Pep 2 molecular target. In 3D-organotypic assays, peptide-exposed TIFs and primary CAFs from breast carcinoma patients both exhibited a markedly reduced pro-invasive ability of either HT1080 fibrosarcoma or MDA-MB-231 mammary carcinoma cells, respectively. Furthermore, TIFs, either exposed to Pep 2, or silenced for αv integrin, were impaired in their ability to chemoattract cancer cells and to contract collagen matrices, exhibiting reduced α-smooth muscle actin (α-SMA) levels. Finally, peptide exposure of αv-expressing primary CAFs led to the downregulation of α-SMA protein and to a dramatic reduction of their pro-invasive capability. In conclusion, the ability of the novel decapeptides to interfere with tumor cell invasion directly and through the down-modulation of CAF phenotype suggests their use as lead compounds for co-targeting anti-cancer strategies.

Description: DNA replication is the fundamental process for accurate duplication and transfer of genetic information. Its fidelity is under constant stress from endogenous and exogenous factors which can cause perturbations that lead to DNA damage and defective replication. This can compromise genomic stability and integrity. Genomic instability is considered as one of the hallmarks of cancer. In normal cells, various checkpoints could either activate DNA repair or induce cell death/senescence. Cancer cells on the other hand potentiate DNA replicative stress, due to defective DNA damage repair mechanism and unchecked growth signaling. Though replicative stress can lead to mutagenesis and tumorigenesis, it can be harnessed paradoxically for cancer treatment. Herein, we review the mechanism and rationale to exploit replication stress for cancer therapy. We discuss both established and new approaches targeting DNA replication stress including chemotherapy, radiation, and small molecule inhibitors targeting pathways including ATR, Chk1, PARP, WEE1, MELK, NAE, TLK etc. Finally, we review combination treatments, biomarkers, and we suggest potential novel methods to target DNA replication stress to treat cancer.

Description: This paper presents closed-form optimal cooperative guidance laws for two UAVs under information constraints that achieve the required relative approach angle. Two UAVs cooperate to optimize a common cost function under a coupled constraint on terminal velocity vectors and the information constraint which defines the sensor information availability. To handle the information constraint, a general two-player partially nested decentralized optimal control problem is considered in the continuous finite-horizon time domain. It is shown that under the state-separation principle the optimal solution of the decentralized control problem can be obtained by solving two centralized subproblems which cover the prediction problem for the information-deficient player and the prediction error minimization problem for the player with full information. Based on the solution of the decentralized optimal control problem, the explicit closed-form cooperative guidance laws that can be efficiently implemented on conventional guidance computers are derived. The performance of the proposed guidance laws is investigated on both centralized and decentralized cooperative scenarios with nonlinear engagement kinematics of networked two-UAV systems.

Description: Hajdu–Cheney syndrome (HCS) is a rare genetic disease that causes acroosteolysis and generalized osteoporosis, accompanied by a series of developmental skeletal disorders and multiple clinical and radiological manifestations. It has an autosomal dominant inheritance, although there are several sporadic non-hereditary cases. The gene that has been associated with Hajdu-Cheney syndrome is NOTCH2. The described phenotype and clinical signs and symptoms are many, varied, and evolve over time. As few as 50 cases of this disease, for which there is currently no curative treatment, have been reported to date. The main objective of this systematic review was to evaluate the results obtained in research regarding Hajdu–Cheney Syndrome. The findings are reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines and were registered on the web PROSPERO under the registration number CRD42020164377. A bibliographic search was carried out using the online databases Orphanet, PubMed, and Scielo; articles from other open access sources were also considered. Finally, 76 articles were included, and after their analysis, we have obtained a series of hypotheses as results that will support further studies on this matter.

Description: Until recently, air quality impacts from wildfires were predominantly determined based on data from permanent stationary regulatory air pollution monitors. However, low-cost particulate matter (PM) sensors are now widely used by the public as a source of air quality information during wildfires, although their performance during smoke impacted conditions has not been thoroughly evaluated. We collocated three types of low-cost fine PM (PM2.5) sensors with reference instruments near multiple fires in the western and eastern United States (maximum hourly PM2.5 = 295 µg/m3). Sensors were moderately to strongly correlated with reference instruments (hourly averaged r2 = 0.52–0.95), but overpredicted PM2.5 concentrations (normalized root mean square errors, NRMSE = 80–167%). We developed a correction equation for wildfire smoke that reduced the NRMSE to less than 27%. Correction equations were specific to each sensor package, demonstrating the impact of the physical configuration and the algorithm used to translate the size and count information into PM2.5 concentrations. These results suggest the low-cost sensors can fill in the large spatial gaps in monitoring networks near wildfires with mean absolute errors of less than 10 µg/m3 in the hourly PM2.5 concentrations when using a sensor-specific smoke correction equation.

Description: Electricity demand is rising due to industrialisation, population growth and economic development. To meet this rising electricity demand, towns are renovated by smart cities, where the internet of things enabled devices, communication technologies, dynamic pricing servers and renewable energy sources are integrated. Internet of things (IoT) refers to scenarios where network connectivity and computing capability is extended to objects, sensors and other items not normally considered computers. IoT allows these devices to generate, exchange and consume data without or with minimum human intervention. This integrated environment of smart cities maintains a balance between demand and supply. In this work, we proposed a closed-loop super twisting sliding mode controller (STSMC) to handle the uncertain and fluctuating load to maintain the balance between demand and supply persistently. Demand-side load management (DSLM) consists of agents-based demand response (DR) programs that are designed to control, change and shift the load usage pattern according to the price of the energy of a smart grid community. In smart grids, evolved DR programs are implemented which facilitate controlling of consumer demand by effective regulation services. The DSLM under price-based DR programs perform load shifting, peak clipping and valley filling to maintain the balance between demand and supply. We demonstrate a theoretical control approach for persistent demand control by dynamic price-based closed-loop STSMC. A renewable energy integrated microgrid scenario is discussed numerically to show that the demand of consumers can be controlled through STSMC, which regulates the electricity price to the DSLM agents of the smart grid community. The overall demand elasticity of the current study is represented by a first-order dynamic price generation model having a piece-wise linear price-based DR program. The simulation environment for this whole scenario is developed in MATLAB/Simulink. The simulations validate that the closed-loop price-based elastic demand control technique can trace down the generation of a renewable energy integrated microgrid.

Description: This article describes a refinement of recurrence analysis to determine the delay in the causal influence between a driver and a target, in the presence of additional perturbations affecting the time series of the response observable. The methodology is based on the definition of a new type of recurrence plots, the Conditional Joint Recurrence plot. The potential of the proposed approach resides in the great flexibility of recurrence plots themselves, which allows extending the technique to more than three quantities. Autoregressive time series, both linear and nonlinear, with different couplings and percentage of additive Gaussian noise have been investigated in detail, with and without outliers. The approach has also been applied to the case of synthetic periodic signals, representing realistic situations of synchronization experiments in thermonuclear fusion. The results obtained have been very positive; the proposed Conditional Joint Recurrence plots have always managed to identify the right interval of the causal influences and are very competitive with alternative techniques such as the Conditional Transfer Entropy.

Description: Background/objectives: The longitudinal effect of abdominal weight status (AWS) defined by waist circumference (WC) on healthy aging has not yet been comprehensively examined. Therefore, the purpose of the present study was to examine the temporal association between WC-defined AWS and a comprehensive assessment for healthy aging. Subjects/methods: This study utilized data from 5211 respondents aged 65+ who participated in the National Health and Aging Trends Study from 2011 to 2018. Mixed effects regression models were used to examine the association between baseline AWS and the annual change rate in healthy aging score (HAS) via interaction terms (AWS*round) adjusting for confounding effects. Further multiple mixed models examined the relationship of AWS and HAS over an 8-year period. Results: There were no annual change rate differences in HAS by baseline AWS, regardless of sex. However, males with abdominal obesity were more likely to have a lower HAS than males with normal AWS (β = −0.20, 95% CI: −0.30, −0.10, p 〈 0.001) but no difference in HAS was observed between males with overweight and normal AWS. A similar pattern was observed among females. Conclusions: Study results indicate that AWS was associated with HAS but it did not modify annual HAS change rate over time.

Description: A healthy lifestyle and regular physical activity are highly recommended for older adults. However, there has been limited research into testing lifestyle intervention effects on physical activity in older adults with hypertension. The purpose of this study was to assess the association of lifestyle intervention effects with physical activity and blood pressure in older adults with hypertension, accounting for social support and perceived stress as control variables. This study performed a secondary analysis of a two-arm randomized controlled trial. A total of 196 participants were randomly assigned to a six-month lifestyle intervention group or a control group. Hierarchical multiple regression analyses demonstrated that lifestyle intervention effects were not significantly associated with improvements in physical activity and blood pressure, but the final regression models were statistically significant (all p 〈 0.001). The result revealed that only physical activity frequency at baseline was significantly related to improvement in physical activity. Systolic blood pressure (SBP) at baseline and monthly income were significantly associated with change in SBP, while age and diastolic blood pressure (DBP) at baseline were significantly related to change in DBP. The findings provide empirical evidence for developing and optimizing lifestyle interventions for future research and clinical practice in this population.

Description: Social connectedness in later life is an important dimension of an age-friendly community, with associated implications for individual health and wellbeing. In contrast with prior efforts focusing on connections at a distance or online communities where the digital technology is the interface, we explore the design opportunities and role of technology for connectedness within a geographically local community context. We present findings from interviews with 22 older adults and a linked ideation workshop. Our analysis identified shared concerns and negative perceptions around local relationships, connections and characteristics of the geographical area. However, local connectedness through technology was largely absent from day-to-day life and even perceived as contributing to disconnection. By uncovering how older adults use and perceive technology in their social lives and combining these findings with their ideas for improving local connections, we highlight the need for thoughtful consideration of the role of technology in optimising social connections within communities. Our research highlights a need for design work to understand the specifics of the local context and reduce emphasis on technology as the interface between people. We introduce an amended definition—‘underpinned by a commitment to respect and social inclusion, an age-friendly community is engaged in a strategic and ongoing process to facilitate active ageing by optimising the community’s physical, social and digital environments and its supporting infrastructure’—to conceptualise our approach. We conclude by suggesting areas for future work in developing digitally connected age-friendly communities.

Description: Synthetic antigens based on consensus sequences that represent circulating viral isolates are sensitive, time saving and cost-effective tools for in vitro immune monitoring and to guide immunogen design. When based on a representative sequence database, such consensus sequences can effectively be used to test immune responses in exposed and infected individuals at the population level. To accelerate immune studies in SARS-CoV-2 infection, we here describe a SARS-CoV-2 2020 consensus sequence (CoV-2-cons) which is based on more than 1700 viral genome entries in NCBI and encompasses all described SARS-CoV-2 open reading frames (ORF), including recently described frame-shifted and length variant ORF. Based on these sequences, we created curated overlapping peptide (OLP) lists containing between 1500 to 3000 peptides of 15 and 18 amino acids in length, overlapping by 10 or 11 residues, as ideal tools for the assessment of SARS-CoV-2-specific T cell immunity. In addition, CoV-2-cons sequence entropy values are presented along with variant sequences to provide increased coverage of the most variable sections of the viral genome. The identification of conserved protein fragments across the coronavirus family and the corresponding OLP facilitate the identification of T cells potentially cross-reactive with related viruses. This new CoV-2-cons sequence, together with the peptides sets, should provide the basis for SARS-CoV-2 antigen synthesis to facilitate comparability between ex-vivo immune analyses and help to accelerate research on SARS-CoV-2 immunity and vaccine development.

Description: The effectiveness of counsellor support in addition to physical activity on prescription (PAP) from health care professionals has rarely been evaluated. This observational follow-up study investigated differences in physical activity levels and health-related quality of life (HRQoL) one year after PAP regarding patients’ use of counsellor support in addition to PAP in routine care. The study was conducted in a Swedish health care region in which all patients receiving PAP from health care professionals were offered counsellor support. Data were collected from medical records and questionnaires (baseline and follow-up). Of the 400 study participants, 37% used counsellor support. The group of counsellor users attained a higher level of physical activity one year after receiving PAP compared to the group of non-users (p 〈 0.001). The level of physical activity was measured by a validated index (score 3–19) calculated from weekly everyday activity and exercise training. Comparison of the change in scores between baseline and follow-up showed a significant difference between the two groups, (p 〈 0.001). The median difference in the PAP + C group was 2.0 (interquartile range, 7.0) and 0.0. among non-users (interquartile range, 4.0). Significant differences in HRQoL were due to positive improvements among counsellor users, with the main improvement in general health. The conclusion is that patients using counsellor support after receiving PAP from health care professionals had higher physical activity and better HRQoL one year after compared with patients who did not use this support.

Description: Since current key management schemes are mainly designed for static and planar networks, they are not very suitable for the layer-cluster wireless sensor networks (WSNs), a WSN layer-cluster key management scheme based on quadratic polynomial and Lagrange interpolation polynomial is proposed, in which the main idea of this scheme along the research line of broadcast identity authentication, session key, group key, network key and personal key. Specifically, authentication key can be established on the basis of Fourier series for identity authentication; session key is established by a multiple asymmetric quadratic polynomial, in which session key information is encrypted by the authentication key to ensure the security of intermediate interactive information; based on the former two keys, group key is established on the basis of Lagrange interpolation polynomial, in which the nodes of the cluster are not directly involved; the generation and management of network key is similar to the group key, in which the establishment idea is to regard the BS and all cluster heads as a group; the generation and management of personal key is also similar to the group key, the difference is that the personal key can be obtained by cluster nodes through getting the Lagrange interpolation polynomial coefficients based on their own random key information. It is analyzed that the proposed layer-cluster key management scheme can guarantee the identity of network nodes firstly through forward authentication and reverse authentication, and session key, group key and network key will guarantee the independence of the keys’ management and avoids the problem of single point failure compared with LEAP protocol, and personal key will guarantee the privacy of network.

Description: This article describes research that investigated the ability of a carbon nanotube (CNT) sensor to detect and monitor fatigue crack initiation and propagation in metal structures. The sensor consists of a nonwoven carrier fabric with a thin film of CNT that is bonded to the surface of a structure using an epoxy adhesive. The carrier fabric enables the sensor to be easily applied over large areas with complex geometries. Furthermore, the distributed nature of the sensor improves the probability of detecting crack initiation and enables monitoring of crack propagation over time. Piezoresistivity of the sensor enables strains to be monitored in real time and the sensor, which is designed to fragment as fatigue cracks propagate, directly measures crack growth through permanent changes in resistance. The following laboratory tests were conducted to evaluate the performance of the sensor: (1) continuous crack propagation monitoring, (2) potential false positive evaluation under near-threshold crack propagation conditions, and (3) crack re-initiation detection at a crack-stop hole, which is a commonly used technique to arrest fatigue cracks. Real-time sensor measurements and post-mortem fractography show that a distinguishable resistance change of the sensor occurs due to fatigue crack propagation that can be quantitatively related to crack length. The sensor does not show false positive responses when the crack does not propagate, which is a drawback of many other fatigue sensors. The sensor is also shown to be remarkably sensitive to detecting crack re-initiation.

Description: Biliary tract cancers (BTCs) are a group of rare cancers that account for up to 3–5% of cancer patients worldwide. BTCs include cholangiocarcinoma (CCA), gallbladder cancer (GBC), and ampulla of Vater cancer (AVC). They are frequently diagnosed at an advanced stage when the disease is often found disseminated. A late diagnosis highly compromises surgery, the only potentially curative option. Current treatment regimens include a combination of chemotherapeutic drugs gemcitabine with cisplatin that have a limited efficiency since more than 50% of patients relapse in the first year. More recently, an inhibitor of fibroblast growth factor receptor 2 (FGFR2) was approved as a second-line treatment, based on the promising results from the NCT02924376 clinical trial. However, novel secondary treatment options are urgently needed. Recent molecular characterization of CCA and GBC highlighted the molecular heterogeneity, etiology, and epidemiology in BTC development and lead to the classification of the extrahepatic CCA into four types: metabolic, proliferating, mesenchymal, and immune type. Differences in the immune infiltration and tumor microenvironment (TME) have been described as well, showing that only a small subset of BTCs could be classified as an immune “hot” and targeted with the immunotherapeutic drugs. This recent evidence has opened a way to new clinical trials for BTCs, and new drug approvals are highly expected by the medical community.

Description: Cervical, anogenital, and some head and neck cancers (HNC) are etiologically associated with high-risk human papillomavirus (HR-HPV) infection, even though additional cofactors are necessary. Epidemiological studies have established that tobacco smoke (TS) is a cofactor for cervical carcinogenesis because women who smoke are more susceptible to cervical cancer when compared to non-smokers. Even though such a relationship has not been established in HPV-related HNC, a group of HPV positive patients with this malignancy are smokers. TS is a complex mixture of more than 4500 chemical compounds and approximately 60 of them show oncogenic properties such as benzo[α]pyrene (BaP) and nitrosamines, among others. Some of these compounds have been evaluated for carcinogenesis through experimental settings in collaboration with HR-HPV. Here, we conducted a comprehensive review of the suggested molecular mechanisms involved in cooperation with both HR-HPV and TS for epithelial carcinogenesis. Furthermore, we propose interaction models in which TS collaborates with HR-HPV to promote epithelial cancer initiation, promotion, and progression. More studies are warranted to clarify interactions between oncogenic viruses and chemical or physical environmental factors for epithelial carcinogenesis.

Description: The Internet of Things (IoT) brings plenty of opportunities to enhance society’s activities, from improving a factory’s production chain to facilitating people’s household tasks. However, it has also brought new security breaches, compromising privacy and authenticity. IoT devices are vulnerable to being accessed from the Internet; they lack sufficient resources to face cyber-attack threats. Keeping a balance between access control and the devices’ resource consumption has become one of the highest priorities of IoT research. In this paper, we evaluate an access control architecture based on the IAACaaS (IoT application-Scoped Access Control as a Service) model with the aim of protecting IoT devices that communicate using the Publish/Subscribe pattern. IAACaaS is based on the OAuth 2.0 authorization framework, which externalizes the identity and access control infrastructure of applications. In our evaluation, we implement the model using FIWARE Generic Enablers and deploy them for a smart buildings use case with a wireless communication. Then, we compare the performance of two different approaches in the data-sharing between sensors and the Publish/Subscribe broker, using Constrained Application Protocol (CoAP) and Hypertext Transfer Protocol (HTTP) protocols. We conclude that the integration of Publish/Subscribe IoT deployments with IAACaaS adds an extra layer of security and access control without compromising the system’s performance.

Description: Cell migration is an essential systemic behavior, tightly regulated, of all living cells endowed with directional motility that is involved in the major developmental stages of all complex organisms such as morphogenesis, embryogenesis, organogenesis, adult tissue remodeling, wound healing, immunological cell activities, angiogenesis, tissue repair, cell differentiation, tissue regeneration as well as in a myriad of pathological conditions. However, how cells efficiently regulate their locomotion movements is still unclear. Since migration is also a crucial issue in cancer development, the goal of this narrative is to show the connection between basic findings in cell locomotion of unicellular eukaryotic organisms and the regulatory mechanisms of cell migration necessary for tumor invasion and metastases. More specifically, the review focuses on three main issues, (i) the regulation of the locomotion system in unicellular eukaryotic organisms and human cells, (ii) how the nucleus does not significantly affect the migratory trajectories of cells in two-dimension (2D) surfaces and (iii) the conditioned behavior detected in single cells as a primitive form of learning and adaptation to different contexts during cell migration. New findings in the control of cell motility both in unicellular organisms and mammalian cells open up a new framework in the understanding of the complex processes involved in systemic cellular locomotion and adaptation of a wide spectrum of diseases with high impact in the society such as cancer.

Description: Data charts are widely used in our daily lives, being present in regular media, such as newspapers, magazines, web pages, books, and many others. In general, a well-constructed data chart leads to an intuitive understanding of its underlying data. In the same way, when data charts have wrong design choices, a redesign of these representations might be needed. However, in most cases, these charts are shown as a static image, which means that the original data are not usually available. Therefore, automatic methods could be applied to extract the underlying data from the chart images to allow these changes. The task of recognizing charts and extracting data from them is complex, largely due to the variety of chart types and their visual characteristics. Other features in real-world images that can make this task difficult are photo distortions, noise, alignment, etc. Two computer vision techniques that can assist this task and have been little explored in this context are perspective detection and correction. These methods transform a distorted and noisy chart in a clear chart, with its type ready for data extraction or other uses. This paper proposes a classification, detection, and perspective correction process that is suitable for real-world usage, when considering the data used for training a state-of-the-art model for the extraction of a chart in real-world photography. The results showed that, with slight changes, chart recognition methods are now ready for real-world charts, when taking time and accuracy into consideration.

Description: Cell fate decisions regulating survival and death are essential for maintaining tissue homeostasis; dysregulation thereof can lead to tumor development. In some cases, survival and death are triggered by the same receptor, e.g., tumor necrosis factor (TNF)-receptor 1 (TNFR1). We identified a prominent role for the cold shock Y-box binding protein-1 (YB-1) in the TNF-induced activation and nuclear translocation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) p65. In the absence of YB-1, the expression of TNF receptor-associated factor 2 (TRAF2), a central component of the TNF receptor signaling complex required for NF-κB activation, is significantly reduced. Therefore, we hypothesized that the loss of YB-1 results in a destabilization of TRAF2. Consistent with this hypothesis, we observed that YB-1-deficient cells were more prone to TNF-induced apoptotic cell death. We observed enhanced effector caspase-3 activation and could successfully rescue the cells using the pan-caspase inhibitor zVAD-fmk, but not necrostatin-1. Taken together, our results indicate that YB-1 plays a central role in promoting cell survival through NF-κB activation and identifies a novel mechanism by which enhanced YB-1 expression may contribute to tumor development.

Description: Porous titanium is a metallic biomaterial with good properties for the clinical repair of cortical bone tissue, although the presence of pores can compromise its mechanical behavior and clinical use. It is therefore necessary to characterize the implant pore size and distribution in a suitable way. In this work, we explore the new use of electrical impedance spectroscopy for the characterization and monitoring of titanium bone implants. Electrical impedance spectroscopy has been used as a non-invasive route to characterize the volumetric porosity percentage (30%, 40%, 50% and 60%) and the range of pore size (100–200 and 355–500 mm) of porous titanium samples obtained with the space-holder technique. Impedance spectroscopy is proved to be an appropriate technique to characterize the level of porosity of the titanium samples and pore size, in an affordable and non-invasive way. The technique could also be used in smart implants to detect changes in the service life of the material, such as the appearance of fractures, the adhesion of osteoblasts and bacteria, or the formation of bone tissue.

Description: In patients with Parkinson’s disease (PD), arm swing changes are common, even in the early stages, and these changes are usually evaluated subjectively by an expert. In this article, hypothesize that arm swing changes can be detected using a low-cost, cloud-based, wearable, sensor system that incorporates triaxial accelerometers. The aim of this work is to develop a low-cost, assistive diagnostic tool for use in quantifying the arm swing kinematics of patients with PD. Ten patients with PD and 11 age-matched, healthy subjects are included in the study. Four feature extraction techniques were applied: (i) Asymmetry estimation based on root mean square (RMS) differences between arm movements; (ii) posterior–anterior phase and cycle regularity through autocorrelation; (iii) tremor energy, established using Fourier transform analysis; and (iv) signal complexity through the fractal dimension by wavelet analysis. The PD group showed significant (p 〈 0.05) reductions in arm swing RMS values, higher arm swing asymmetry, higher anterior–posterior phase regularities, greater “high energy frequency” signals, and higher complexity in their XZ plane signals. Therefore, the novel, portable system provides a reliable means to support clinical practice in PD assessment.

Description: Optimization of tool life is required to tune the machining parameters and achieve the desired surface roughness of the machined components in a wide range of engineering applications. There are many machining input variables which can influence surface roughness and tool life during any machining process, such as cutting speed, feed rate and depth of cut. These parameters can be optimized to reduce surface roughness and increase tool life. The present study investigates the optimization of five different sensorial criteria, additional to tool wear (VB) and surface roughness (Ra), via the Tool Condition Monitoring System (TCMS) for the first time in the open literature. Based on the Taguchi L9 orthogonal design principle, the basic machining parameters cutting speed (vc), feed rate (f) and depth of cut (ap) were adopted for the turning of AISI 5140 steel. For this purpose, an optimization approach was used implementing five different sensors, namely dynamometer, vibration, AE (Acoustic Emission), temperature and motor current sensors, to a lathe. In this context, VB, Ra and sensorial data were evaluated to observe the effects of machining parameters. After that, an RSM (Response Surface Methodology)-based optimization approach was applied to the measured variables. Cutting force (97.8%) represented the most reliable sensor data, followed by the AE (95.7%), temperature (92.9%), vibration (81.3%) and current (74.6%) sensors, respectively. RSM provided the optimum cutting conditions (at vc = 150 m/min, f = 0.09 mm/rev, ap = 1 mm) to obtain the best results for VB, Ra and the sensorial data, with a high success rate (82.5%).

Description: The incidence of thyroid cancer is rapidly increasing, mostly due to the overdiagnosis and overtreatment of differentiated thyroid cancer (TC). The increasing use of potent preclinical models, high throughput molecular technologies, and gene expression microarrays have provided a deeper understanding of molecular characteristics in cancer. Hence, molecular markers have become a potent tool also in TC management to distinguish benign from malignant lesions, predict aggressive biology, prognosis, recurrence, as well as for identification of novel therapeutic targets. In differentiated TC, molecular markers are mainly used as an adjunct to guide management of indeterminate nodules on fine needle aspiration biopsies. In contrast, in advanced thyroid cancer, molecular markers enable targeted treatments of affected signalling pathways. Identification of the driver mutation of targetable kinases in advanced TC can select treatment with mutation targeted tyrosine kinase inhibitors (TKI) to slow growth and reverse adverse effects of the mutations, when traditional treatments fail. This review will outline the molecular landscape and discuss the impact of molecular markers on diagnosis, surveillance and treatment of differentiated, poorly differentiated and anaplastic follicular TC.

Description: Zn-Co-S ball-in-ball hollow sphere (BHS) was successfully prepared by solvothermal sulfurization method. An efficient strategy to synthesize Zn-Co-S BHS consisted of multilevel structures by controlling the ionic exchange reaction was applied to obtain great performance electrode material. Carbon nanotubes (CNTs) as a conductive agent were uniformly introduced with Zn-Co-S BHS to form Zn-Co-S BHS/CNTs and expedited the considerable electrocatalytic behavior toward glucose electro-oxidation in alkaline medium. In this study, characterization with scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD) was used for investigating the morphological and physical/chemical properties and further evaluating the feasibility of Zn-Co-S BHS/CNTs in non-enzymatic glucose sensing. Electrochemical methods (cyclic voltammetry (CV) and chronoamperometry (CA)) were performed to investigate the glucose sensing performance of Zn-Co-S BHS/CNTs. The synergistic effect of Faradaic redox couple species of Zn-Co-S BHS and unique conductive network of CNTs exhibited excellent electrochemical catalytic ability towards the glucose electro-oxidation, which revealed linear range from 5 to 100 μM with high sensitivity of 2734.4 μA mM−1 cm−2, excellent detection limit of 2.98 μM, and great selectivity in the presence of dopamine, uric acid, ascorbic acid, and fructose. Thus, Zn-Co-S BHS/CNTs would be expected to be a promising material for non-enzymatic glucose sensing.

Description: How to predict the evolution of ecosystems is one of the numerous questions asked of ecologists by managers and politicians. To answer this we will need to give a scientific definition to concepts like sustainability, integrity, resilience and ecosystem health. This is not an easy task, as modern ecosystem theory exemplifies. Ecosystems show a high degree of complexity, based upon a high number of compartments, interactions and regulations. The last two decades have offered proposals for interpretation of ecosystems within a framework of thermodynamics. The entrance point of such an understanding of ecosystems was delivered more than 50 years ago through Schrödinger’s and Prigogine’s interpretations of living systems as “negentropy feeders” and “dissipative structures”, respectively. Combining these views from the far from equilibrium thermodynamics to traditional classical thermodynamics, and ecology is obviously not going to happen without problems. There seems little reason to doubt that far from equilibrium systems, such as organisms or ecosystems, also have to obey fundamental physical principles such as mass conservation, first and second law of thermodynamics. Both have been applied in ecology since the 1950s and lately the concepts of exergy and entropy have been introduced. Exergy has recently been proposed, from several directions, as a useful indicator of the state, structure and function of the ecosystem. The proposals take two main directions, one concerned with the exergy stored in the ecosystem, the other with the exergy degraded and entropy formation. The implementation of exergy in ecology has often been explained as a translation of the Darwinian principle of “survival of the fittest” into thermodynamics. The fittest ecosystem, being the one able to use and store fluxes of energy and materials in the most efficient manner. The major problem in the transfer to ecology is that thermodynamic properties can only be calculated and not measured. Most of the supportive evidence comes from aquatic ecosystems. Results show that natural and culturally induced changes in the ecosystems, are accompanied by a variations in exergy. In brief, ecological succession is followed by an increase of exergy. This paper aims to describe the state-of-the-art in implementation of thermodynamics into ecology. This includes a brief outline of the history and the derivation of the thermodynamic functions used today. Examples of applications and results achieved up to now are given, and the importance to management laid out. Some suggestions for essential future research agendas of issues that needs resolution are given.

Description: In 1980, Ruff and Kanamori (RK) published an article on seismicity and the subduction zones where they reported that the largest characteristic earthquake (Mw) of a subduction zone is correlated with two geophysical quantities: the rate of convergence between the oceanic and continental plates (V) and the age of the corresponding subducting oceanic lithosphere (T). This proposal was synthetized by using an empirical graph (RK-diagram) that includes the variables Mw, V and T. We have recently published an article that reports that there are some common characteristics between real seismicity, sandpaper experiments and a critically self-organized spring-block model. In that paper, among several results we qualitatively recovered a RK-diagram type constructed with equivalent synthetic quantities corresponding to Mw, V and T. In the present paper, we improve that synthetic RK-diagram by means of a simple model relating the elastic ratio γ of a critically self-organized spring-block model with the age of a lithospheric downgoing plate. In addition, we extend the RK-diagram by including some large subduction earthquakes occurred after 1980. Similar behavior to the former RK-diagram is observed and its SOC synthetic counterpart is obtained.

Description: The paper presents the Rr matrix form of Kedem–Katchalsky–Peusner equations for membrane transport of the non-homogeneous ternary non-electrolyte solutions. Peusner’s coefficients Rijr and det [Rr] (i, j ∈ {1, 2, 3}, r = A, B) occurring in these equations, were calculated for Nephrophan biomembrane, glucose in aqueous ethanol solutions and two different settings of the solutions relative to the horizontally oriented membrane for concentration polarization conditions or homogeneity of solutions. Kedem–Katchalsky coefficients, measured for homogeneous and non-homogeneous solutions, were used for the calculations. The calculated Peusner’s coefficients for homogeneous solutions depend linearly, and for non-homogeneous solutions non-linearly on the concentrations of solutes. The concentration dependences of the coefficients Rijr and det [Rr] indicate a characteristic glucose concentration of 9.24 mol/m3 (at a fixed ethanol concentration) in which the obtained curves for Configurations A and B intersect. At this point, the density of solutions in the upper and lower membrane chamber are the same. Peusner’s coefficients were used to assess the effect of concentration polarization and free convection on membrane transport (the ξij coefficient), determine the degree of coupling (the rijr coefficient) and coupling parameter (the QRr coefficient) and energy conversion efficiency (the (eijr)r coefficient).

Description: The deposition of layers of different polycations (synthetic or derived from natural, renewable resources) onto oppositely charged surfaces has been studied using ellipsometry and quartz crystal microbalance with dissipation monitoring (QCM-D). Information about the thickness of the deposited layers and their water content was ascertained. The adsorption of the different polycations onto negatively charged surfaces was found to be a complex process, which is influenced by the chemical nature of the polymer chains, ionic strength, polymer concentration and the addition of additives such as surfactants. The experimental picture shows a good agreement with theoretical calculations performed using the Self-Consistent Mean Field (SCF) approach. The results show that the electrostatically-driven deposition can be tuned by modifying the physico-chemical properties of the solutions and the chemical nature of the adsorbed polymer. This versatile approach is a big step forward in aiding the design of new polymers for many industrial applications and, in particular, the design of sustainable washing formulations for cosmetic applications.

Description: Diarrhea is responsible for killing around 525,000 children every year, even though it is preventable and treatable. This research focuses on both houseflies’ roles and humans’ roles in carrying pathogens causing diarrhea as multiple disease carriers. Both human and fly compartmental models are simulated with five diseases control strategies in order to identify the epidemic dynamics. The framework considers the life cycle of flies modeled into eggs, larvae, pupae, susceptible flies, and carrier flies, while the human system follows a compartment model as susceptible, infected, recovered, and back to susceptible again (SIRS). The relationships are modeled into an ordinary differential equation-based compartmental system. Then, the control parameters of the compartmental framework are analyzed. In order to propose effective control methods, five control strategies are considered: (1) elimination of flies’ breeding site, (2) sanitation, (3) installation of UV light trap, (4) good personal and food hygiene, and (5) water purification. Then, overall, ten control scenarios using the five control strategies are analyzed. Among them, effective control solutions considering various dynamic epidemiology are provided with the simulations and analyses. The proposed framework contributes to an effective control strategy in reducing the number of both flies and infected humans, since it minimizes the spread of the disease and considers cost-effectiveness.

Description: Exposure to greenspace has been related to improved mental health, but the available evidence is limited and findings are heterogeneous across different areas. We aimed to evaluate the associations between residential exposure to greenspace and specific psychopathological and psychosomatic symptoms related to mental health among mothers from a Spanish birth cohort. Our study was based on data from 1171 women participating in two follow-ups of a population-based cohort in Valencia, Sabadell, and Gipuzkoa (2004–2012). For each participant, residential surrounding greenspace was estimated as the average of the satellite-based Normalized Difference Vegetation Index (NDVI) across different buffers around the residential address at the time of delivery and at the 4-year follow-up. The Symptom Checklist 90 Revised (SCL-90-R) was applied to characterize mental health at the 4-year follow-up. We developed mixed-effects logistic regression models controlled for relevant covariates to evaluate the associations. Higher residential surrounding greenspace was associated with a lower risk of somatization and anxiety symptoms. For General Severity Index (GSI), obsessive–compulsive, interpersonal sensitivity, depression, hostility, phobic anxiety, paranoid ideation, and psychoticism symptoms, we generally observed protective associations, but none attained statistical significance. Findings from this study suggested a potential positive impactof greenspace on mental health.

Description: Studies on the pattern of heatwave mortality using nationwide data that include rural areas are limited. This study aimed to assess the risk of heatwave-related mortality and evaluate the health risk-based definition of heatwave. We collected data on daily temperature and mortality from 229 districts in South Korea in 2011–2017. District-specific heatwave-related mortality risks were calculated using a distributed lag model. The estimates were pooled in the total areas and for each urban and rural area using meta-regression. In the total areas, the threshold point of heatwave mortality risk was estimated at the 93rd percentile of temperature, and it was lower in urban areas than in rural areas (92nd percentile vs. 95th percentile). The maximum risk of heatwave-related mortality in the total area was 1.11 (95% CI: 1.01–1.22), and it was slightly greater in rural areas than in the urban areas (RR: 1.23, 95% CI: 0.99–1.53 vs. RR: 1.10, 95% CI: 1.01–1.20). The results differ by age- and cause-specific deaths. In conclusion, the patterns of heatwave-related mortality risk vary by area and sub-population in Korea. Thus, more target-specific heatwave definitions and action plans should be established according to different areas and populations.

Description: Active Kids is a government-led, universal voucher program that aims to reduce the cost of participation in structured physical activity for all school-enrolled children in New South Wales (NSW), Australia. As part of the Active Kids program evaluation, this cross-sectional study examined the Active Kids’ program’s reach to children in NSW and their physical activity behaviors, before voucher use. Demographic registration data from all children (4.5–18 years old) who registered for an Active Kids voucher in 2018 (n = 671,375) were compared with Census data. Binary and multinomial regression models assessed which correlates were associated with meeting physical activity guidelines and participation in the sessions of structured physical activity. The Active Kids program attracted more than half (53%) of all eligible children in NSW. Children who spoke a primary language other than English at home, were aged 15–18 years old, lived in the most disadvantaged areas, and girls, were less likely to register. Of the registered children, 70% had attended structured physical activity sessions at least once a week during the previous 12 months, whilst 19% achieved physical activity guidelines. Active Kids achieved substantial population reach and has the potential to improve children’s physical activity behaviors.

Description: The goal of the training is to enable the body to perform prolonged physical effort without reducing its effectiveness while maintaining the body’s homeostasis. Homeostasis is the ability of the system to maintain, in dynamic balance, the stability of the internal environment. Equally as important as monitoring the body’s thermoregulation phenomena during exercise seems to be the evaluation of these mechanisms after physical effort, when the athlete’s body returns to physiological homeostasis. Restoring homeostasis is an important factor in body regeneration and has a significant impact on preventing overtraining. In this work we present a training protocol using a rowing ergometer, which was planned to be carried out in a short time and which involves working the majority of the athlete’s muscles, allowing a full assessment of the body’s thermal parameters after stopping exercise and during the body’s return to thermal equilibrium and homeostasis. The significant differences between normalized mean body surface temperature obtained for the cyclist before the training period and strength group as well as before and 10 min after training were obtained. Such observation seems to bring indirectly some information about the sportsperson’s efficiency due to differences in body temperature in the first 10 min of training when sweat does not play a main role in surface temperature. Nearly 1 °C drop of mean body temperature has been measured due to the period of training. It is concluded that thermovision not only allows you to monitor changes in body temperature due to sports activity, but also allows you to determine which of the athletes has a high level of body efficiency. The average maximum body temperature of such an athlete is higher (32.5 °C) than that of an athlete who has not trained regularly (30.9 °C) and whose body probably requires further training.

Description: Fibroblast growth factor receptor 4 (FGFR4) is involved in multiple physiological and pathological processes. Several genetic variants of FGFR4 have been shown to be associated with tumor progression in many cancers. However, its association, such as genetic variants and expression levels, with lung cancer is controversial. The present study examined the relationship between four single-nucleotide polymorphisms (SNPs; rs2011077 T/C, rs351855 G/A, rs7708357 G/A, and rs1966265 A/G) of FGFR4 and the risk of lung adenocarcinoma with the epidermal growth factor receptor (EGFR) mutation status in a Taiwanese cohort. The results demonstrated that FGFR4 rs2011077 (odds ratio (OR) = 0.348, 95% confidence interval (CI) = 0.136–0.891, p = 0.024), and rs351855 (OR = 0.296, 95% CI = 0.116–0.751, p = 0.008) showed an inverse association with distant metastasis in wild-type EGFR lung adenocarcinoma. Furthermore, a database analysis using The Cancer Genome Atlas revealed that the higher FGFR4 expression level was correlated with poor survival rates in wild-type EGFR lung adenocarcinoma. In conclusion, the data suggest that FGFR4 SNPs may help in identifying patient subgroups at low-risk for tumor metastasis, among carriers of lung adenocarcinoma bearing wild-type EGFR.

Description: With the current extensive availability of synthetic-aperture radar (SAR) datasets with high temporal (e.g., a repeat cycle of a few or a dozen days) and spatial resolution (e.g., in the order of ∼1 m), radar remote sensing possesses an increasing potential for the monitoring of glacier surface motion thanks to the nearly weather and time-independent advantages. This paper proposes a robust subpixel frequency-based image correlation method for dense matching and integrates the improved matching into a workflow of glacier surface motion estimation using SAR intensity images with specific pre-processing and post-processing steps. The proposed matching method combines complex edge maps and local upsampling in the frequency domain for subpixel intensity tracking, which ensure the accuracy and robustness of glacier surface motion estimation. Experiments were carried out with TerraSAR-X and Sentinel-1 images covering two glacier areas in pole and alpine regions. The results of the monitoring and investigation of glacier motion validate the feasibility and reliability of the presented motion estimation method based on subpixel gradient correlation. The comparative results using both simulated and real SAR data indicate that the proposed matching method outperforms commonly used correlation-based matching methods in terms of matching accuracy and the ability to obtain correct matches.

Description: We propose a deep neural network model that recognizes the position and velocity of a fast-moving object in a video sequence and predicts the object’s future motion. When filming a fast-moving subject using a regular camera rather than a super-high-speed camera, there is often severe motion blur, making it difficult to recognize the exact location and speed of the object in the video. Additionally, because the fast moving object usually moves rapidly out of the camera’s field of view, the number of captured frames used as input for future-motion predictions should be minimized. Our model can capture a short video sequence of two frames with a high-speed moving object as input, use motion blur as additional information to recognize the position and velocity of the object, and predict the video frame containing the future motion of the object. Experiments show that our model has significantly better performance than existing future-frame prediction models in determining the future position and velocity of an object in two physical scenarios where a fast-moving two-dimensional object appears.

Description: In this study, the adsorption of Fe(III) from aqueous solution on zeolite and bentonite was investigated by combining batch adsorption technique, Atomic adsorption spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy analyses. Although iron is commonly found in water and is an essential bioelement, many industrial processes require efficient removal of iron from water. Two types of zeolite and two types of bentonite were used. The results showed that the maximum adsorption capacities for removal of Fe (III) by Zeolite Micro 20, Zeolite Micro 50, blue bentonite, and brown bentonite were 10.19, 9.73, 11.64, and 16.65 mg.g−1, respectively. Based on the X-ray photoelectron spectroscopy (XPS) and X-ray fluorescence (XRF) analyses of the raw samples and the solid residues after sorption at low and high initial Fe concentrations, the Fe content is different in the surface layer and in the bulk of the material. In the case of lower initial Fe concentration (200 mg.dm−3), more than 95% of Fe is adsorbed in the surface layer. In the case of higher initial Fe concentration (4000 mg.dm−3), only about 45% and 61% of Fe is adsorbent in the surface layer of zeolite and bentonite, respectively; the rest is adsorbed in deeper layers.

Description: This study examined the cross-sectional and longitudinal association of sleep timing with weight status in 14- to 19-year-old adolescents in Wuhan, China. A prospective school-based study was conducted in Wuhan, China between 28 May and 29 September 2019. Data on sociodemographic information, academic performance, diet, mental health status, physical activity, sleep characteristics, body weight, and height were collected. A linear regression model and binary logistic regression model were performed. A total of 1194 adolescents were included in the analysis. Adolescents who woke up before 05:45 had higher body mass index (BMI) Z-score (odds ratio (OR) with 95% confidence interval (CI) = 1.28 (1.05, 1.57), p = 0.02) and higher odds of overweight/obesity (odds ratio (OR) with 95% confidence interval (CI) = 1.74 (1.10, 2.76), p = 0.02) at baseline after fully adjustment for covariates, compared with those who woke up after 05:45. Longitudinal data showed a nonsignificant association between waking up time and change in BMI Z-score (p = 0.18). No association of bedtime with weight status was observed in this sample after full adjustment (p 〉 0.1). Earlier waking up time might contribute to overweight and obesity in adolescents; however, more data are needed to test and elucidate this relationship.

Description: The tone-mapping algorithm compresses the high dynamic range (HDR) information into the standard dynamic range for regular devices. An ideal tone-mapping algorithm reproduces the HDR image without losing any vital information. The usual tone-mapping algorithms mostly deal with detail layer enhancement and gradient-domain manipulation with the help of a smoothing operator. However, these approaches often have to face challenges with over enhancement, halo effects, and over-saturation effects. To address these challenges, we propose a two-step solution to perform a tone-mapping operation using contrast enhancement. Our method improves the performance of the camera response model by utilizing the improved adaptive parameter selection and weight matrix extraction. Experiments show that our method performs reasonably well for overexposed and underexposed HDR images without producing any ringing or halo effects.

Description: There is a growing interest in preventing cyberbullying in youth. However, multiple questions remain as to the relationship between cyberbullying and psychosocial variables. This study examines the relationship between personality traits, aggression and cyberbullying (victims, bullies, victimized bullies and not involved) in 548 Spanish students aged 10 to 13 (50.2% boys). To do so, the Screening of Peer Harassment, the Big Five Questionnaire for Children and the Aggression Questionnaire were used. Logistic regression analyses indicated that the extraversion trait is an explanatory factor for being a victim and openness is a protective factor against being a cyberbully. Agreeableness was found to be a positive predictor of being a cyberbullying victim. Only verbal aggression and anger were included as explanatory factors of being a victim and a victimized bully, respectively. The results are discussed, suggesting their potential implications in the development of preventive programs.

Description: Ammonia can be produced by the respiration and excretion of fish during the farming process, which can affect the life of fish. In this paper, to research the behavior of fish under different ammonia concentration and make the corresponding judgment and early warning for the abnormal behavior of fish, the different ammonia environments are simulated by adding the ammonium chloride into the water. Different from the existing methods of directly artificial observation or artificial marking, this paper proposed a recognition and analysis of behavior trajectory approach based on deep learning. Firstly, the three-dimensional spatial trajectories of fish are drawn by three-dimensional reconstruction. Then, the influence of different concentrations of ammonia on fish is analyzed according to the behavior trajectory of fish in different concentrations of ammonia. The results of comparative experiments show that the movement of fish and vitality decrease significantly, and the fish often stagnates in the water of containing ammonium chloride. The proposed approach can provide a new idea for the behavior analysis of animal.

Description: Internet of Things is advancing, and the augmented role of smart navigation in automating processes is at its vanguard. Smart navigation and location tracking systems are finding increasing use in the area of the mission-critical indoor scenario, logistics, medicine, and security. A demanding emerging area is an Indoor Localization due to the increased fascination towards location-based services. Numerous inertial assessments unit-based indoor localization mechanisms have been suggested in this regard. However, these methods have many shortcomings pertaining to accuracy and consistency. In this study, we propose a novel position estimation system based on learning to the prediction model to address the above challenges. The designed system consists of two modules; learning to prediction module and position estimation using sensor fusion in an indoor environment. The prediction algorithm is attached to the learning module. Moreover, the learning module continuously controls, observes, and enhances the efficiency of the prediction algorithm by evaluating the output and taking into account the exogenous factors that may have an impact on its outcome. On top of that, we reckon a situation where the prediction algorithm can be applied to anticipate the accurate gyroscope and accelerometer reading from the noisy sensor readings. In the designed system, we consider a scenario where the learning module, based on Artificial Neural Network, and Kalman filter are used as a prediction algorithm to predict the actual accelerometer and gyroscope reading from the noisy sensor reading. Moreover, to acquire data, we use the next-generation inertial measurement unit, which contains a 3-axis accelerometer and gyroscope data. Finally, for the performance and accuracy of the proposed system, we carried out numbers of experiments, and we observed that the proposed Kalman filter with learning module performed better than the traditional Kalman filter algorithm in terms of root mean square error metric.

Description: The occlusion problem is very common in pedestrian retrieval scenarios. When persons are occluded by various obstacles, the noise caused by the occluded area greatly affects the retrieval results. However, many previous pedestrian re-identification (Re-ID) methods ignore this problem. To solve it, we propose a semantic-guided alignment model that uses image semantic information to separate useful information from occlusion noise. In the image preprocessing phase, we use a human semantic parsing network to generate probability maps. These maps show which regions of images are occluded, and the model automatically crops images to preserve the visible parts. In the construction phase, we fuse the probability maps with the global features of the image, and semantic information guides the model to focus on visible human regions and extract local features. During the matching process, we propose a measurement strategy that only calculates the distance of public areas (visible human areas on both images) between images, thereby suppressing the spatial misalignment caused by non-public areas. Experimental results on a series of public datasets confirm that our method outperforms previous occluded Re-ID methods, and it achieves top performance in the holistic Re-ID problem.

Description: Owing to its versatility, optical refractive index (RI) sensors with compact size and high chemical stability are very suitable for a wide range of the applications in the internet of things (IoT), such as immunosensor, disease detection, and blood mapping. In this study, a RI sensor with very simple system and high chemical stability was developed using GaN-based high-contrast grating (HCG). The designed HCG pattern was fabricated on GaN-film grown on c-plane sapphire substrate. The fabricated GaN-HCG sensor can detect minuscule RI change of 1.71 × 10–3 with extreme simple surface normal irradiation system. The light behavior inside the GaN-HCG was discussed using numerical electromagnetic field calculation, and the deep understand of the sensing mechanism was provided. The simple system and very high chemical stability of our sensor exploit RI sensing applications in IoT society.

Description: The process parameters of selective laser melting (SLM) significantly influence molten pool formation. A comprehensive understanding and analysis, from a macroscopic viewpoint, of the mechanisms underlying these technological parameters and how they affect the evolution of molten pools are presently lacking. In this study, we established a dynamic finite element simulation method for the process of molten pool formation by SLM using a dynamic moving heat source. The molten pool was generated, and the dynamic growth process of the molten pool belt and the evolution process of the thermal field of the SLM molten pool were simulated. Then, a deposition experiment that implemented a new measurement method for online monitoring involving laser supplementary light was conducted using the same process parameters as the simulation, in which high-speed images of the molten pool were acquired, including images of the pool surface and cross-section images of the deposited samples. The obtained experimental results show a good agreement with the simulation results, demonstrating the effectiveness of the proposed algorithm.

Description: This paper presents a procedure to analyse the effects of radiation in an IEEE 802.15.4 RF receiver for wireless sensor networks (WSNs). Specifically, single-event transients (SETs) represent one of the greatest threats to the adequate performance of electronic communication devices in high-radiation environments. The proposed procedure consists in injecting current pulses in sensitive nodes of the receiver and analysing how they propagate through the different circuits that form the receiver. In order to perform this analysis, a Complementary Metal Oxide Semiconductor (CMOS) low-IF receiver has been designed using a 0.18 μm technology from the foundry UMC. In order to analyse the effect of single-event transients in this receiver, it has been studied how current pulses generated in the low-noise amplifier propagate down the receiver chain. The effect of the different circuits that form the receiver on this kind of pulse has been studied prior to the analysis of the complete receiver. First, the effect of SETs in low-noise amplifiers was analysed. Then, the propagation of pulses through mixers was studied. The effect of filters in the analysed current pulses has also been studied. Regarding the analysis of the designed RF receiver, an amplitude and phase shift was observed under the presence of SETs.

Description: In the field of cultural heritage, applied dyes on textiles are studied to explore their great artistic and historic values. Dye analysis is essential and important to plan correct restoration, preservation and display strategy in museums and art galleries. However, most of the existing diagnostic technologies are destructive to the historical objects. In contrast to that, spectral reflectance imaging is potential as a non-destructive and spatially resolved technique. There have been hardly any studies in classification of dyes in textile fibers using spectral imaging. In this study, we show that spectral imaging with machine learning technique is capable in preliminary screening of dyes into the natural or synthetic class. At first, sparse logistic regression algorithm is applied on reflectance data of dyed fibers to determine some discriminating bands. Then support vector machine algorithm (SVM) is applied for classification considering the reflectance of the selected spectral bands. The results show nine selected bands in short wave infrared region (SWIR, 1000–2500 nm) classify dyes with 97.4% accuracy (kappa 0.94). Interestingly, the results show that fairly accurate dye classification can be achieved using the bands at 1480nm, 1640 nm, and 2330 nm. This indicates possibilities to build an inexpensive handheld screening device for field studies.

Description: As a spontaneous facial expression, a micro-expression can reveal the psychological responses of human beings. Thus, micro-expression recognition can be widely studied and applied for its potentiality in clinical diagnosis, psychological research, and security. However, micro-expression recognition is a formidable challenge due to the short-lived time frame and low-intensity of the facial actions. In this paper, a sparse spatiotemporal descriptor for micro-expression recognition is developed by using the Enhanced Local Cube Binary Pattern (Enhanced LCBP). The proposed Enhanced LCBP is composed of three complementary binary features containing Spatial Difference Local Cube Binary Patterns (Spatial Difference LCBP), Temporal Direction Local Cube Binary Patterns (Temporal Direction LCBP), and Temporal Gradient Local Cube Binary Patterns (Temporal Gradient LCBP). With the application of Enhanced LCBP, it would no longer be a problem to provide binary features with spatiotemporal domain complementarity to capture subtle facial changes. In addition, due to the redundant information existing among the division grids, which affects the ability of descriptors to distinguish micro-expressions, the Multi-Regional Joint Sparse Learning is designed to perform feature selection for the division grids, thus paying more attention to the critical local regions. Finally, the Multi-kernel Support Vector Machine (SVM) is employed to fuse the selected features for the final classification. The proposed method exhibits great advantage and achieves promising results on four spontaneous micro-expression datasets. Through further observation of parameter evaluation and confusion matrix, the sufficiency and effectiveness of the proposed method are proved.

Description: Given the growing concerns of problematic Internet use and online safety, it is critical to address parental self-efficacy in managing adolescent Internet use and to examine associated factors, especially in parents of adolescents with attention-deficit/hyperactivity disorder (ADHD). We examined the roles of adolescents’ hyperactivity/impulsivity, inattention and oppositional defiant disorder (ODD) symptoms, parents’ depressive symptoms, parenting behavior (parental care and indifference), and child behavior (Internet addiction) in relation to parental self-efficacy in managing adolescent Internet use. We recruited 237 Taiwanese parents of adolescents with ADHD (ages 11–18). Hierarchical linear regression was performed in four steps to test the study hypotheses. The results indicated that child’s age, ODD symptoms, and Internet addiction of adolescents were negatively associated, and parental care was positively associated with parental self-efficacy in managing adolescent Internet use. The final model was significant and explained 43% of the variance. The present study demonstrated that parenting and child behaviors contribute to parental self-efficacy in managing adolescent Internet use. Moreover, children’s ODD symptoms were identified as the risk factor for reduced parental self-efficacy.

Description: With the deepening of industrialization and urbanization in China, air pollution has become the most serious environmental issue due to huge energy consumption, which threatens the health of residents and the sustainable development of the country. Increasing attention has been paid to the efficiency evaluation of industrial system due to its fast development and severe air pollution emissions, but the efficiency evaluation on China’s industrial waste gas still has scope for improvement. This paper proposes a global non-radial Network Data Envelopment Analysis (NDEA) model from the perspective of pollution prevention (PP) and end-of-pipe treatment (ET), to explore the potential reduction of generation and emission of air pollutants in China’s industrial system. Given the differences of different air pollution treatment capacities, the ET stage is further subdivided into three parallel sub-stages, corresponding to SO2, NOX, and soot and dust (SD), respectively. Then, grey relation analysis (GRA) is adopted to figure out the key factor affecting the unified efficiency. The main findings are summarized as follows: firstly, the unified efficiency of China’s industrial waste gas underperformed nationwide, and most provinces had the potential to reduce the generation and emission of industrial waste gas. Secondly, the PP efficiency outperformed the ET efficiency in many provinces and the efficiency gap between two stages increasingly narrowed except in 2014. Thirdly, the unified efficiency in the eastern area performed well, while the area disparities increased significantly after 2012. Fourthly, significant differences were found in three ET efficiencies and the ET efficiency of NOX was higher than that of SO2 and SD in the sample period. Finally, the results of GRA indicated that different air pollutants had distinct influence on the improvement of the unified efficiency in three areas. To promote the unified efficiency of industrial waste gas, some pertinent policy suggestions are put forward from the perspectives of sub-stages, air pollutants and areas.

Description: Significant variation in impedance under a wide range of loads increases the difficulty of frequency tracking and vibration control in high-power piezoelectric systems (HPPSs). This paper proposed a wide operating range driving and control scheme for HPPSs. We systematically analyzed the impedance characteristics and deduced the load optimization frequency. In order to provide sufficient drive capability, the inverter combined with an LC matching circuit is configured. With the aid of a transformer ratio arm bridge (TRAB) combined with a proposed pulse-based phase detector (PBPD), the proposed scheme can control the vibration amplitude and keep parallel resonance status under a wide range of loads. Experiments conducted under actual operating conditions verify the feasibility of the proposed scheme under the modal resistance range from 7.40 to 500 Ω and the vibration range from 20% to 100%. Moreover, with the aid of a laser displacement sensor, our scheme is verified to have a vibration amplitude control accuracy better than 2% over a tenfold load variation. This research could be helpful for the driving and control of HPPSs operating in a wide range.

Description: In this article, regression and classification models are compared for stress detection. Both personal and user-independent models are experimented. The article is based on publicly open dataset called AffectiveROAD, which contains data gathered using Empatica E4 sensor and unlike most of the other stress detection datasets, it contains continuous target variables. The used classification model is Random Forest and the regression model is Bagged tree based ensemble. Based on experiments, regression models outperform classification models, when classifying observations as stressed or not-stressed. The best user-independent results are obtained using a combination of blood volume pulse and skin temperature features, and using these the average balanced accuracy was 74.1% with classification model and 82.3% using regression model. In addition, regression models can be used to estimate the level of the stress. Moreover, the results based on models trained using personal data are not encouraging showing that biosignals have a lot of variation not only between the study subjects but also between the session gathered from the same person. On the other hand, it is shown that with subject-wise feature selection for user-independent model, it is possible to improve recognition models more than by using personal training data to build personal models. In fact, it is shown that with subject-wise feature selection, the average detection rate can be improved as much as 4%-units, and it is especially useful to reduce the variance in the recognition rates between the study subjects.

Description: As the use of technology becomes further integrated into the daily lives of all persons, including older adults, it is important to investigate how the perceptions and use of technology intersect with intergenerational relationships. Based on the international multi-centered study Technology In Later Life (TILL), this paper emphasizes the perceptions of older adults and the interconnection between technology and intergenerational relationships are integral to social connectedness with others. Participants from rural and urban sites in Canada and the UK (n = 37) completed an online survey and attended a focus group. Descriptive and thematic analyses suggest that older adults are not technologically adverse and leverage intergenerational relationships with family and friends to adjust to new technologies and to remain connected to adult children and grandchildren, especially when there is high geographic separation between them. Participants referenced younger family members as having introduced them to, and having taught them how to use, technologies such as digital devices, computers, and social networking sites. The intergenerational support in the adoption of new technologies has important implications for helping older persons to remain independent and to age in place, in both age-friendly cities and in rural communities. The findings contribute to the growing literature in the fields of gerontology and gerontechnology on intergenerational influences and the impacts of technology use in later life and suggest the flexibility and willingness of older persons to adopt to new technologies as well as the value of intergenerational relationships for overcoming barriers to technology adoption.

Description: The rate and characteristics of prostate-specific antigen (PSA) bounce post-radiotherapy remain unclear. To address this issue, we performed a meta-analysis. Reports of PSA bounce post-radiotherapy with a cutoff of 0.2 ng/mL were searched by using Medline and Web of Science. The primary endpoint was the occurrence rate, and the secondary endpoints were bounce characteristics such as amplitude, time to occurrence, nadir value, and time to nadir. Radiotherapy modality, age, risk classification, androgen deprivation therapy, and the follow-up period were extracted as clinical variables. Meta-analysis and univariate meta-regression were performed with random-effect modeling. Among 290 search-positive studies, 50 reports including 26,258 patients were identified. The rate of bounce was 31%; amplitude was 1.3 ng/mL; time to occurrence was 18 months; nadir value was 0.5 ng/mL; time to nadir was 33 months. Univariate meta-regression analysis showed that radiotherapy modality (29.7%), age (20.2%), and risk classification (12.2%) were the major causes of heterogeneity in the rate of bounce. This is the first meta-analysis of PSA bounce post-radiotherapy. The results are useful for post-radiotherapy surveillance of prostate cancer patients.

Description: Alternative lengthening of telomeres (ALT) is a telomerase-independent mechanism that extends telomeres in cancer cells. It influences tumorigenesis and patient survival. Despite the clinical significance of ALT in tumors, the manner in which ALT is activated and influences prognostic outcomes in distinct cancer types is unclear. In this work, we profiled distinct telomere maintenance mechanisms (TMMs) using 8953 transcriptomes of 31 different cancer types from The Cancer Genome Atlas (TCGA). Our results demonstrated that approximately 29% of cancer types display high ALT activity with low telomerase activity in the telomere-lengthening group. Among the distinct ALT mechanisms, homologous recombination was frequently observed in sarcoma, adrenocortical carcinoma, and kidney chromophobe. Five cancer types showed a significant difference in survival in the presence of high ALT activity. Sarcoma patients with elevated ALT had unfavorable risks (p 〈 0.038) coupled with a high expression of TOP2A, suggesting this as a potential drug target. On the contrary, glioblastoma patients had favorable risks (p 〈 0.02), and showed low levels of antigen-presenting cells. Together, our analyses highlight cancer type-dependent TMM activities and ALT-associated genes as potential therapeutic targets.

Description: This study aimed to evaluate the impact of co-inoculation Rhizobium sp. and Azospirillum sp. on plant (Trifolium pratense L.) growth in the presence of polycyclic aromatic hydrocarbon (PAH) contamination (anthracene, phenanthrene, and pyrene). Eight strains from the genus Rhizobium leguminosarum bv. trifolii were selected for biotest analysis. Two methods of inoculation were used in the chamber experiment: (1) R. leguminosarum alone and (2) a combined inoculant (R. leguminosarum and Azospirillum brasilense). For comparison, non-contaminated controls were also used. The results demonstrated that co-inoculation of plants with Rhizobium and Azospirillum resulted in more root and shoot biomass than in plants inoculated with R. leguminosarum alone. The results indicated that application of a co-inoculation of bacteria from Rhizobium and Azospirillum species had a positive effect on clover nodulation and growth under the condition of PAH contamination.

Description: Face recognition is a crucial subject for public health, as socialization is one of the main characteristics for full citizenship. However, good recognizers would be distinguished, not only by the number of faces they discriminate but also by the number of rejected stimuli as unfamiliar. When it comes to face recognition, it is important to remember that position, to some extent, would not entail a high cognitive cost, unlike other processes in similar areas of the brain. The aim of this paper was to examine participant’s recognition profiles according to face position. For this reason, a recognition task was carried out by employing the Karolinska Directed Emotional Faces. Reaction times and accuracy were employed as dependent variables and a cluster analysis was carried out. A total of two profiles were identified in participants’ performance, which differ in position in terms of reaction times but not accuracy. The results can be described as follows: first, it is possible to identify performance profiles in visual recognition of faces that differ in position in terms of reaction times, not accuracy; secondly, results suggest a bias towards the left. At the applied level, this could be of interest with a view to conducting training programs in face recognition.

Description: The quality and safety of healthcare facility (HCF) services are critical to achieving universal health coverage (UHC) and yet the WHO/UNICEF joint monitoring program for water supply, sanitation and hygiene report indicates that only 51% and 23% of HCF in Sub-Saharan Africa have basic access to water and sanitation, respectively. Global commitments on improving access to water, sanitation, hygiene, waste management and environmental cleaning (WaSH) in HCF as part of implementing UHC have surged since 2015. Guided by political ecology of health theory, we explored the country level commitment to ensuring access to WaSH in HCFs as part of piloting UHC in Kisumu, Kenya. Through content analysis, 17 relevant policy documents were systematically reviewed using NVIVO. None of the national documents mentioned all the component of WaSH in healthcare facilities. Furthermore, these WaSH components are not measured as part of the universal health coverage pilot. Comprehensively incorporating WaSH measurement and monitoring in HCFs in the context of UHC policies creates a foundation for achieving SDG 6.