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In this paper, we propose a hierarchical statistical model for a single repairable system subject to several failure modes (competing risks). The paper describes how complex engineered systems may be modelled hierarchically by use of Bayesian methods. It is also assumed that repairs are minimal and each failure mode has a power-law intensity. Our proposed model generalizes another one already presented in the literature and continues the study initiated by us in another published paper. Some properties of the new model are discussed. We conduct statistical inference under an objective Bayesian framework. A simulation study is carried out to investigate the efficiency of the proposed methods. Finally, our methodology is illustrated by two practical situations currently addressed in a project under development arising from a partnership between Petrobras and six research institutes.

Background During uncertainties associated with the COVID-19 pandemic, effectively improving people’s health literacy is more important than ever. Drawing knowledge maps of health literacy research through data mining and visualized measurement technology helps systematically present the research status and development trends in global academic circles. Methods This paper uses CiteSpace to carry out a metric analysis of 9,492 health literacy papers included in Web of Science through mapping knowledge domains. First, based on the production theory of scientific knowledge and the data mining of citations, the main bodies (country, institution and author) that produce health literacy knowledge as well as their mutual cooperation (collaboration network) are both clarified. Additionally, based on the quantitative framework of cocitation analysis, this paper introduces the interdisciplinary features, development trends and hot topics of the field. Finally, by using burst detection technology in the literature, it further reveals the research frontiers of health literacy. Results The results of the BC measures of the global health literacy research collaboration network show that the United States, Australia and the United Kingdom are the major forces in the current international collaboration network on health literacy. There are still relatively very few transnational collaborations between Eastern and Western research institutions. Collaborations in public environmental occupational health, health care science services, nursing and health policy services have been active in the past five years. Research topics in health literacy research evolve over time, mental health has been the most active research field in recent years. Conclusions A systematic approach is needed to address the challenges of health literacy, and the network framework of cooperation on health literacy at regional, national and global levels should be strengthened to further promote the application of health literacy research. In the future, we anticipate that this research field will expand in two directions, namely, mental health literacy and eHealth literacy, both of which are closely linked to social development and issues. The results of this study provide references for future applied research in health literacy.

In this paper, we describe a novel approach to the development of a reference standard for the quality control of complex natural products, which will assist in the assessment of their authenticity and purity. The proposed method provides a template for the selection of samples, which can be pooled to obtain a reference standard. A shortfall of such an approach is, however, that the pooled sample is static in nature and therefore unable to capture difference in processing conditions or natural variations triggered by geographical or climatic impacts over time. To address this, the paper also outlines the development of a dynamic reference standard, which allows for ongoing adjustments to future variations. The method employs High-Performance Thin Layer Chromatography (HPTLC) derived extract profiles processed by multivariate analysis. The development of the dynamic reference standard is illustrated using honey, a complex natural matrix, as an example.

Background Cognitive performances on neuropsychological paper-and-pencil tests are generally evaluated quantitatively by examining a final score (e.g., total duration). Digital tests allow for a quantitative evaluation of “how” a patient attained a final score, which opens the possibility to assess more subtle cognitive impairment even when final scores are evaluated as normal. We assessed performance stability (i.e., the number of fluctuations in test performance) to investigate (1) differences in performance stability between patients with acquired brain injury (ABI) and healthy controls; (2) the added value of performance stability measures in patients with ABI; and (3) the relation between performance stability and cognitive complaints in daily life in patients with ABI. Methods We administered three digital neuropsychological tests (Rey Auditory Verbal Learning Test, Trail Making Test, Stroop Colour and Word Test) and the Cognitive Complaints—Participation (CoCo-P) inventory in patients with ABI (n = 161) and healthy controls (n = 91). Results Patients with ABI fluctuated more in their performance on all tests, when compared to healthy controls. Furthermore, 4–15% of patients who performed inside normal range on the conventional final scores were outside normal range on the performance stability measures. The performance stability measures, nor the conventional final scores, were associated with cognitive complaints in daily life. Conclusions Stability in test performance of patients was clearly dissociable from healthy controls, and may assess additional cognitive weaknesses which might not be observed or objectified with paper-and-pencil tests. More research is needed for developing measures better associated with cognitive complaints.

Since the financial system has illustrated an increasingly prominent characteristic of inextricable connections, information theory is gradually utilized to study the financial system. By collecting the daily data of industry index (2005-2020) and region index (2012-2020) listed in China as samples, this paper applies an innovative measure named partial mutual information on mixed embedding to generate directed networks. Based on the analysis of nonlinear relationships among sectors, this paper realizes the accurate construction of “time-varying” financial network from the perspective of risk spillover. The results are presented as follow: (1) interactions can be better understood through the nonlinear networks among distinct sectors, and sectors in the networks could be classified into different types according to their topological properties connected to risk spillover; (2) in the rising stage, information is transmitted rapidly in the network, so the risk is fast diffused and absorbed; (3) in the declining stage, the network topology is more complex and panic sentiments have long term impact leading to more connections; (4) The US market, Japan market and Hongkong market have significant affect on China’s market. The results suggest that this nonlinear measure is an effective approach to develop financial networks and explore the mechanism of risk spillover.

This paper establishes a fully automatic real-time image segmentation and recognition system for breast ultrasound intervention robots. It adopts the basic architecture of a U-shaped convolutional network (U-Net), analyses the actual application scenarios of semantic segmentation of breast ultrasound images, and adds dropout layers to the U-Net architecture to reduce the redundancy in texture details and prevent overfitting. The main innovation of this paper is proposing an expanded training approach to obtain an expanded of U-Net. The output map of the expanded U-Net can retain texture details and edge features of breast tumours. Using the grey-level probability labels to train the U-Net is faster than using ordinary labels. The average Dice coefficient (standard deviation) and the average IOU coefficient (standard deviation) are 90.5% (±0.02) and 82.7% (±0.02), respectively, when using the expanded training approach. The Dice coefficient of the expanded U-Net is 7.6 larger than that of a general U-Net, and the IOU coefficient of the expanded U-Net is 11 larger than that of the general U-Net. The context of breast ultrasound images can be extracted, and texture details and edge features of tumours can be retained by the expanded U-Net. Using an expanded U-Net can quickly and automatically achieve precise segmentation and multi-class recognition of breast ultrasound images.

Objective Some researchers have studied about early prediction and diagnosis of major adverse cardiovascular events (MACE), but their accuracies were not high. Therefore, this paper proposes a soft voting ensemble classifier (SVE) using machine learning (ML) algorithms. Methods We used the Korea Acute Myocardial Infarction Registry dataset and selected 11,189 subjects among 13,104 with the 2-year follow-up. It was subdivided into two groups (ST-segment elevation myocardial infarction (STEMI), non ST-segment elevation myocardial infarction NSTEMI), and then subdivided into training (70%) and test dataset (30%). Third, we selected the ranges of hyper-parameters to find the best prediction model from random forest (RF), extra tree (ET), gradient boosting machine (GBM), and SVE. We generated each ML-based model with the best hyper-parameters, evaluated by 5-fold stratified cross-validation, and then verified by test dataset. Lastly, we compared the performance in the area under the ROC curve (AUC), accuracy, precision, recall, and F-score. Results The accuracies for RF, ET, GBM, and SVE were (88.85%, 88.94%, 87.84%, 90.93%) for complete dataset, (84.81%, 85.00%, 83.70%, 89.07%) STEMI, (88.81%, 88.05%, 91.23%, 91.38%) NSTEMI. The AUC values in RF were (98.96%, 98.15%, 98.81%), ET (99.54%, 99.02%, 99.00%), GBM (98.92%, 99.33%, 99.41%), and SVE (99.61%, 99.49%, 99.42%) for complete dataset, STEMI, and NSTEMI, respectively. Consequently, the accuracy and AUC in SVE outperformed other ML models. Conclusions The performance of our SVE was significantly higher than other machine learning models (RF, ET, GBM) and its major prognostic factors were different. This paper will lead to the development of early risk prediction and diagnosis tool of MACE in ACS patients.

The SARS-CoV-2 pandemic has emerged as one of the most dramatic health crises of recent decades. This paper treats mainstream news about the current pandemic as a valuable entry point for analyzing the relationship between science and politics in the public sphere, where the outbreak must be both understood and confronted through appropriate public-health policy decisions. In doing so, the paper aims to examine which actors, institutions, and experts dominate the SARS-CoV-2 media narratives, with particular attention to the roles of political, medical, and scientific actors and institutions within the pandemic crisis. The study relies on a large dataset consisting of all SARS-CoV-2 articles published by eight major Italian national newspapers between January 1, 2020 and June 15, 2020. These articles underwent a quantitative analysis based on a topic modeling technique. The topic modeling outputs were further analyzed by innovatively combining ad-hoc metrics and a classifier based on the stacking ensemble method (combining regularized logistic regression and linear stochastic gradient descent) for quantifying scientific salience. This enabled the identification of relevant topics and the analysis of the roles that different actors and institutions engaged in making sense of the pandemic. The results show how the health emergency has been addressed primarily in terms of political regulation and concerns and only marginally as a scientific matter. Hence, science has been overwhelmed by politics, which, in media narratives, exerts a moral as well as regulatory authority. Media narratives exclude neither scientific issues nor scientific experts; rather, they configure them as a subsidiary body of knowledge and expertise to be mobilized as an ancillary, impersonal institution useful for legitimizing the expansion of political jurisdiction over the governance of the emergency.

The inference of gene regulatory networks (GRNs) from expression data is a challenging problem in systems biology. The stochasticity or fluctuations in the biochemical processes that regulate the transcription process poses as one of the major challenges. In this paper, we propose a novel GRN inference approach, named the Probabilistic Extended Petri Net for Gene Regulatory Network (PEPN-GRN), for the inference of gene regulatory networks from noisy expression data. The proposed inference approach makes use of transition of discrete gene expression levels across adjacent time points as different evidence types that relate to the production or decay of genes. The paper examines three variants of the PEPN-GRN method, which mainly differ by the way the scores of network edges are computed using evidence types. The proposed method is evaluated on the benchmark DREAM4 in silico data sets and a real time series data set of E. coli from the DREAM5 challenge. The PEPN-GRN_v3 variant (the third variant of the PEPN-GRN approach) sought to learn the weights of evidence types in accordance with their contribution to the activation and inhibition gene regulation process. The learned weights help understand the time-shifted and inverted time-shifted relationship between regulator and target gene. Thus, PEPN-GRN_v3, along with the inference of network edges, also provides a functional understanding of the gene regulation process.

We consider a proposed system that would place sensors in a number of wastewater manholes in a community in order to detect genetic remnants of SARS-Cov-2 found in the excreted stool of infected persons. These sensors would continually monitor the manhole’s wastewater, and whenever virus remnants are detected, transmit an alert signal. In a recent paper, we described two new algorithms, each sequentially opening and testing successive manholes for genetic remnants, each algorithm homing in on a neighborhood where the infected person or persons are located. This paper extends that work in six important ways: (1) we introduce the concept of in-manhole sensors, as these sensors will reduce the number of manholes requiring on-site testing; (2) we present a realistic tree network depicting the topology of the sewer pipeline network; (3) for simulations, we present a method to create random tree networks exhibiting key attributes of a given community; (4) using the simulations, we empirically demonstrate that the mean and median number of manholes to be opened in a search follows a well-known logarithmic function; (5) we develop procedures for determining the number of sensors to deploy; (6) we formulate the sensor location problem as an integer nonlinear optimization and develop heuristics to solve it. Our sensor-manhole system, to be implemented, would require at least three additional steps in R&D: (a) an accurate, inexpensive and fast SARS-Cov-2 genetic-remnants test that can be done at the manhole; (b) design, test and manufacture of the sensors; (c) in-the-field testing and fine tuning of an implemented system.

During the Covid-19 pandemic, the Vietnamese government has actively implemented various policies to achieve dual objectives: (i) to minimize the loss of life due to the infection; and (ii) to support economic growth. This paper is conducted to examine the effect of the government’s containment and closure policy on the stock market quality in Vietnam. Unlike other papers, we focus exclusively on market quality during the pandemic. We find that the policies appear to positively affect the market quality, except for closing-school policy (negative effect) and international travel (no effect). We argue that the government should sustain the policies until the wide availability of the vaccine to support the stock market quality in the near future.

The ‘long tail’ nature of rural special education (RSE) suggests that it simultaneously possesses the private nature of discreteness and the public nature of externalities, which can easily cause provision insufficiency. However, this mismatch may have a dynamic intertemporal correction mechanism impacted by different expenditures of supply sectors (governments and other social sectors). This paper uses different models and data from 30 provinces in China from 2003–2014 to analyze this dynamic correction mechanism. This research finds that different kinds of expenditures from different suppliers have divergent effects on this correction. Capital expenses (especially infrastructure construction) have significantly positive effects on the correction, but administrative expenses have significant dual effects on the correction. These effects may be caused by the various governance efficiencies and motivations of all stakeholders in RSE. This paper concludes that we should pay more attention to the accurate recognition and effective satisfaction of RSE affected by the governance efficiency and motivation of different suppliers to achieve this dynamic correction.

This research paper aims to understand the effects of time spent in domestic work, including childcare, on women’s mental health in Ghana. The paper adopted a triangulation convergence mixed methods approach. The quantitative information was sourced from two waves (2009/ 2014) of the Ghana Socioeconomic Panel Survey (GSEPS) while qualitative information was obtained from in-depth interviews with couples and key informants from five (5) regions, representing diverse ethnic backgrounds, in Ghana. Employing fixed effects regressions and a multinomial logistic regression model with fixed effects, we find that domestic work contributes to poorer mental health outcomes among women. These results are consistent, even when we correct for potential self-selectivity of women into domestic work. We also examine whether the relationship is differentiated between women of higher and lower socioeconomic status. We find that women from wealthier households who spend increasing time in domestic work have higher odds of mental distress. These results are supported by the qualitative data- women indicate increasing stress levels from domestic work and while some husbands acknowledge the situation of their overburdened wives and make attempts, however minor, to help, others cite social norms and cultural expectations that act as a deterrent to men’s assistance with domestic work. Efforts should be made to lessen the effects of social and cultural norms which continue to encourage gendered distributions of domestic work. This may be done through increased education, sensitization and general re-socialization of both men and women about the need for more egalitarian divisions of household work.

The number of COVID-19 infections is key for accurately monitoring the pandemics. However, due to differential testing policies, asymptomatic individuals and limited large-scale testing availability, it is challenging to detect all cases. Seroprevalence studies aim to address this gap by retrospectively assessing the number of infections, but they can be expensive and time-intensive, limiting their use to specific population subgroups. In this paper, we propose a complementary approach that combines estimated (1) infection fatality rates (IFR) using a Bayesian melding SEIR model with (2) reported case-fatality rates (CFR) in order to indirectly estimate the fraction of people ever infected (from the total population) and detected (from the ever infected). We apply the technique to the U.S. due to their remarkable regional diversity and because they count with almost a quarter of all global confirmed cases and deaths. We obtain that the IFR varies from 1.25% (0.39–2.16%, 90% CI) in Florida, the most aged population, to 0.69% in Utah (0.21–1.30%, 90% CI), the youngest population. By September 8, 2020, we estimate that at least five states have already a fraction of people ever infected between 10% and 20% (New Jersey, New York, Massachussets, Connecticut, and District of Columbia). The state with the highest estimated fraction of people ever infected is New Jersey with 17.3% (10.0, 55.8, 90% CI). Moreover, our results indicate that with a probability of 90 percent the fraction of detected people among the ever infected since the beginning of the epidemic has been less than 50% in 15 out of the 20 states analyzed in this paper. Our approach can be a valuable tool that complements seroprevalence studies and indicates how efficient have testing policies been since the beginning of the outbreak.

Sexual violence against women and girls is a major public health problem globally and in South Africa. Although young men have been identified as an important risk group for prevention interventions, scant attention have been given to this age cohort in low and middle-income countries. There is strong evidence that perpetration starts early and increasing attention is being drawn to Higher Education Institutions (HEIs) as settings for prevention interventions. The main objective of this study was to adapt the One Man Can Intervention for use with male university students in residences and develop materials for implementation. This paper presents the qualitative findings of the adaptation process of the One Man Can Intervention with 15 young male student leaders at a HEI in South Africa. The same participants who started in the study, participated throughout. Only five of the 15 participants were located and participated in the interviews six months post intervention. The results show the emergence of a six-hour session adapted intervention that addresses key drivers of violence against women and girls (VAWG). Critical engagement and dialogue on sexual violence is shown to shift key norms on gender equality, on being a man and reflection on their role in preventing sexual violence. This paper contributes to the field where much learning, refining and improvement of prevention interventions for VAWG are ongoing.

BackgroundThis study examines the relationship between experiencing intimate partner violence (IPV), exposure to prior childhood adversity, lifetime adverse experiences, drug-related relationship dependencies with intimate partners and overdose, hospitalization for drug use, friends and family members who overdosed and witnessing overdose.MethodologyThis paper included a sample of 201 women who use drugs in heterosexual relationships with criminal justice-involved men in New York City. We included measures of experiencing overdose, hospitalization for drug use, witnessing overdose, and having friends and family who overdosed. Intimate partner violence consisted of either 1) none/verbal only, 2) moderate and 3) severe abuse. Dichotomous indicators of drug-related relationship dependencies included financial support, drug procurement, splitting and pooling drugs. A scale measured cumulative exposure to childhood adversity and lifetime exposures to adverse events. This paper hypothesized that experiencing moderate and severe IPV, drug-related dependencies and exposure to prior childhood and lifetime adversity would be associated with a greater risk of experiencing overdose, hospitalization for drug use, witnessing overdose and having friends and family members who overdosed. Generalized linear modeling with robust variance estimated relative risk ratios that accounted for potential bias in confidence intervals and adjusted for race, ethnicity, education and marital status.ResultsWe found experiencing moderate or severe IPV was associated with ever being hospitalized for drug use and having a family member who experienced overdose. Experiencing moderate IPV was associated with increased risk of witnessing overdose, Partner drug dependencies were associated with overdose, ever being hospitalized for drug use, witnessing overdose, and having a family member or friend who experienced overdose. Childhood and lifetime adversity exposures were significantly associated with increased risk of overdose, ever being hospitalized for drug use, ever witnessing overdose and having a friend and family member who overdosed.ConclusionFindings underscore the intersection of experiencing IPV and drug-related relationship dependencies, childhood adversity and lifetime adversity in shaping experiences of and witnessing overdose among women who use drugs. They highlight the urgent need to address IPV, adversity experiences and drug-related relationship dependencies in overdose prevention for women who use drugs.

Currently, many ischemic stroke patients worldwide suffer from physical and mental impairments, and thus have a low quality of life. However, although rehabilitation is acknowledged as an effective way to recover patients' health, there does not exist yet an adaptive training platform for animal tests so far. For this sake, this paper aims to develop an adaptive escalator (AE) for rehabilitation of rats with cerebral ischemia. Rats were observed to climb upward spontaneously, and a motor-driven escalator, equipped with a position detection feature and an acceleration/deceleration mechanism, was constructed accordingly as an adaptive training platform. The rehabilitation performance was subsequently rated using an incline test, a rotarod test, the infarction volume, the lesion volume, the number of MAP2 positive cells and the level of cortisol. This paper is presented in 3 parts as follows. Part 1 refers to the escalator mechanism design, part 2 describes the adaptive ladder-climbing rehabilitation mechanism, and part 3 discusses the validation of an ischemic stroke model. As it turned out, a rehabilitated group using this training platform, designated as the AE group, significantly outperformed a control counterpart in terms of a rotarod test. After the sacrifice of the rats, the AE group gave an average infarction volume of (34.36 ± 3.8)%, while the control group gave (66.41 ± 3.1)%, validating the outperformance of the escalator-based rehabilitation platform in a sense. An obvious difference between the presented training platform and conventional counterparts is the platform mechanism, and for the first time in the literature rats can be well and voluntarily rehabilitated at full capacity using an adaptive escalator. Taking into account the physical diversity among rats, the training strength provided was made adaptive as a reliable way to eliminate workout or secondary injury. Accordingly, more convincing arguments can be made using this mental stress-free training platform.

Personal motivation is a key factor in the service of foster care, impending both on the welfare of the child and on the satisfaction of the carer. This paper explores the benefits, challenges and dilemmas involved in the job of professional (i.e. state-supported) foster carer in Romania-a country where the issue of child protection has drawn a great deal of international attention over the last thirty years. The principal hypothesis concerns whether the benefits, challenges and dilemmas identified by foster carers are influenced by the factors that led to their taking up this kind of work. Quantitative research was conducted using a questionnaire as the main tool. The paper takes a descriptive, cross-sectional and multifactorial approach. Sampling was carried out by self-selecting method, and the study involved 51 participants. The research project identified a statistically significant variation in the challenges and dilemmas reported by foster carers. Thus, the results of the study show that the majority of the carers indicate a primarily intrinsic motivation for their work. By way of conclusion, it is argued that social workers, operating in collaboration with multidisciplinary teams, can offer carers support in managing more difficult periods in the child-carer relationship, thus enhancing the sustainability of the foster care service.

As the root cause of illegal cyber activities, botnets are evolving continuously over the last two decades. Current researches on botnet command and control mechanism based on blockchain network suffer from high economic cost, single point of failure, and limited scalability. In this paper, we present DUSTBot, a novel P2P botnet model based on Bitcoin transactions to prepare for new cyber threats. Specifically, a covert, duplex, and low-cost command and control (C&C) channel in the Bitcoin network is presented in our work. DUSTBot uses the Bitcoin main network as the downstream channel while using the Bitcoin testnet as the upstream channel. Furthermore, the peer list exchange algorithm based on the Ethereum block hash proposed in this paper is effective against routing table poisoning attack and P2P botnet crawling. The robustness of DUSTBot against node removal is studied through constructing the botnet with a P2P simulator. We deploy the implementation of DUSTBot on cloud platforms to test its feasibility and performance. Moreover, the stealthiness of DUSTBot and the effectiveness of the proposed peer list exchange algorithm are evaluated. The results demonstrate the feasibility, performance, stealthiness, and robustness of DUSTBot. In the end, possible countermeasures are discussed to mitigate similar threats in the future.

While diaspora communities have become more critical of Female Genital Cutting (FGC), there are also trends of continuity. To explore the interplay between continuity and change, I designed a study among Somali migrants in Norway. A team of six Somali research assistants collected data from 72 male and female research participants between 16 and 57 years of age through in-depth interviews and focus group discussions. The aim of the study was to gather knowledge that could improve interventions among migrant populations. The study findings indicate that the experience of FGC as a practice in transition implies that people have to maneuver between different and partly contradictory social norms. The paper first discusses the contradiction between a strong negative attitude toward FGC and very low engagement. The lack of engagement is explained by the increased privatization of FGC and insecurities due to the transition and disempowerment with regard to challenging the FGC practices of relatives based in countries of origin. Second, the paper explores the contradiction between perceptions of FGC as a disappearing practice and the recognition of trends of continuation. Trends of continuation include those related to perceptions of risk during travel to countries of origin, resistance to defibulation, support for sunna circumcision and insecurities regarding the significance of FGC for marriageability. Thus, despite an almost universally negative attitude toward FGC in the form of infibulation, ongoing changes can, to some extent, hamper further change. This suggests that to ensure further progress in the abandonment of the practice, these complex and interconnected expectations must be addressed.

This paper examines the levels of health system efficiency and their possible determinants across Latin American and Caribbean (LAC) countries using national-level data for those countries, as well as for other emerging and developed countries. The data are analyzed using data envelopment analyses and econometric advances that yield reliable estimations of the relationship between system efficiency and its potential determinants. We find that there is substantial room for efficiency improvements in the health system of most LAC countries. For example, LAC countries could improve life expectancy at birth by about five years on average at current public spending levels if they followed best practices. Furthermore, the paper assesses what factors amenable to policy act as the main possible levers for some countries to be able to translate a given level of health financing into better performance on access to care and health outcomes. Our econometric analyses suggest that efforts to increase health system efficiency could be focused in a few key policy areas associated with broader access to health services and better outcomes. These areas include general governance aspects, in addition to improvements in specific dimensions of the quality of health system institutions, notably stronger reliance on results-based management in the production of healthcare goods and services.

Background Epidemiological studies have shown that gastrointestinal Helicobacter pylori (H. pylori) infection is the main cause of chronic gastritis, but the relation between oral H. pylori and chronic periodontitis (CP) remains uncertain. A meta-analysis of published papers was performed to elucidate the correlation between oral H. pylori and CP. Method To perform this meta-analysis, we searched papers published from 2000 to 2018 on PubMed, OVID, Springer Link, Chinese National Knowledge Infrastructure (CNKI) and Chinese Biology Medicine search engines. Pooled odds ratios (ORs) and 95% confidence intervals (CIs) for the correlation between H. pylori and CP were estimated. Heterogeneity, publication bias and subgroup analyses were also conducted. Results A total of 918 papers on oral H. pylori and CP were collected, and 11 papers were in accordance with the inclusion criteria. Oral H. pylori was suggested to be correlated with CP. The results indicated that a H. pylori-positive state significantly increased the risk of CP 3.42 times (OR = 3.42; 95% CI = 2.71–4.31). A diagnostic test using polymerase chain reaction (PCR) showed a higher prevalence of H. pylori (OR = 3.70; 95% CI = 2.66–5.14) than did that using the rapid urease test (RUT) (OR = 3.13; 95% CI = 2.26–4.34). Conclusions This paper demonstrated that CP was potentially correlated with oral H. pylori in adults and that oral H. pylori may be a possible risk factor for CP.

By utilizing cognitive mapping and leveraging georeferenced text data, this paper aims to suggest a new visualization method that combines the advantages of both conventional and state-of-the-art research techniques to depict the collective identity of place in a single image. The study addressed two research questions: (1) Can crowd-sourced text data be utilized in representing place identity? (2) Can collective place identity be expressed in the form of a cognitive map? By confirming that text data gathered from social media effectively demonstrate people’s behaviors and perceptions related to places, we propose a novel method to create a visual representation of urban identity–a “crowd-sourced cognitive map”. In particular, to improve the conventional cognitive mapping method to depict the collective identity of a city, we draw cognitive maps of Bundang and Ilsan developed in the 1990s, as well as Songdo and Dongtan developed in the 2000s, just outside of the administrative boundaries of Seoul in Korea, through a computational method based on crowd-sourced opinions collected from social media. We open the possibility for the use of social media text data to capture the identity of cities and suggest a graphical image through which people without prior information could also easily apprehend the overall image of a city. The work in this paper is expected to provide a methodological technique for appropriate decision-making and the evaluation of urban identity to shape a more unique and imageable city.

Many crashes occur around freeway exit ramp areas in China due to excessive speeds and large speed variances. Traditionally, a single posted ramp speed limit sign is installed around the physical gore area to manage the speed. To address this issue, the study presented in this paper proposes the use of an advisory exit speed sign (AESS), which is an additional exit speed limit sign positioned along the deceleration lane to accommodate the speed changes ahead of the physical gore. The study selected three sites with similar exit ramp configurations and two scenarios (with AESS/without AESS) to quantify the influences of the AESS on the speed of exiting vehicles. The speed profiles of 480 vehicles were obtained based on 12 hours of data collection. A t-test was applied to verify the reduction in mean speed between the two scenarios. The results show that the AESS in this study was effective in reducing the mean speed and 85th percentile speed, especially in the taper and deceleration lane. It was clearly seen that drivers began to decelerate in advance when the AESS was installed, which led to a smooth deceleration process, especially on the segment between the theoretical gore and the physical gore. The AESS was also helpful in reducing speeding to some extent. Although the effects of the AESS on speed reduction at curved ramps were not ideal, the speed fluctuation range tended to be more contracted when the AESS was installed. This paper provides useful information for researchers, managers, and engineers when considering the implementation of AESS.

International audience; Lower back pain is a major public health problem. Despite claims that lumbar belts change spinal posture due to applied pressure on the trunk, no mechanical model has yet been published to prove this treatment. This paper describes a first model for belt design, based on the one hand on the mechanical properties of the fabrics and the belt geometry, and on the other hand on the trunk geometrical and mechanical description. The model provides the estimation of the pressure applied to the trunk, and a unique indicator of the belt mechanical efficiency is proposed: pressure is integrated into a bending moment characterizing the belt delordosing action on the spine. A first in-silico clinical study of belt efficiency for 15 patients with 2 different belts was conducted. Results are very dependent on the body shape: in the case of high BMI patients, the belt effect is significantly decreased, and can be even inverted, increasing the lordosis. The belt stiffness proportionally increases the pressure applied to the trunk, but the influence of the design itself on the bending moment is clearly outlined. Moreover, the belt/trunk interaction, modeled as sticking contact and the specific way patients lock their belts, dramatically modifies the belt action. Finally, even if further developments and tests are still necessary, the model presented in this paper seems suitable for in-silico pre-clinical trials on real body shapes at a design stage.

Backward-moving kinematic waves (KWs) (e.g., stop-and-go traffic conditions and a shock wave) cause unsafe driving conditions, decreases in the capacities of freeways, and increased travel time. In this paper, a sequential filtering method is proposed to detect KWs using data collected in a connected environment, which can aid in developing a traffic control strategy for connected vehicles to stop or dampen the propagation of these KWs. The proposed method filters out random fluctuation in the data using ensemble empirical mode decomposition that considers the spectral features of KWs. Then, the spatial movements of KWs are considered using cross-correlation to identify potential candidate KWs. Asynchronous changes in the denoised flow and speed are used to evaluate candidate KWs using logistic regression to identify the KWs from localized reductions in speed that are not propagated upstream. The findings from an empirical evaluation of the proposed method showed strong promise for detecting KWs using data in a connected environment, even at 30% of the market penetration rates. This paper also addresses how data resolution of the connected environment affects the performance in detecting KWs.

We sought to develop a smooth and low cost sample preparation and DNA extraction protocol, streamlined with a ready-to-use qPCR in a portable instrument to overcome some of the existing hurdles. Several solutions were evaluated as to their ability to liquefy a mucin-based matrix. Each liquefied matrix, supplemented with either Mycobacterium tuberculosis (MTB) H37Rv strain DNA or intact cells, was aliquoted onto a filter paper embedded with solubilizing agents, and was subsequently dried up. Most of the nucleic acids, including genomic DNA from the bacilli and the host, binds to the filter paper. Next, several protocols were evaluated to elute the DNA from the paper, using qPCR to detect the insertion sequence IS6110, a M. tuberculosis complex genomic marker. The limit of detection (LOD) of the best protocol was then evaluated using parallel seeding and colony counting. The protocol was also evaluated using seventeen sputum samples, previously characterized by the GeneXpert or culture. Two instruments (the ABI7500 Standard and the Q3-Plus system) and two reagents storage formats (frozen or ready-to-use) were evaluated. Solutions containing guanidine isothiocyanate exerted the best liquefying effect on the mucin-based matrix extracted from one 6-mm punches, followed by a brief incubation at 95°C. The resulting DNA contained impurities, but a simple 1:10 dilution elicited the detection of MTB and human genomic targets. The described protocol presented an apparent LOD of 02 CFU/mL of MTB. Challenging the protocol with previously characterized samples showed substantial agreement with GeneXpert MTB/RIF results (sensitivity of 90%, agreement of 88.9%, kappa coefficient of 0.77), and moderate agreement with culture results (sensitivity of 100%, agreement of 78.9%, kappa coefficient of 0.58). This work presents a sensitive proof–of-concept protocol for sputum liquefaction and decontamination followed by a simple DNA extraction procedure, in which the extraction steps are streamlined with a ready-to-use qPCR in a portable instrument that can be employed in low infrastructure settings.

Background Access to healthcare services, from diagnosis through end of life (EOL), is important among persons living with Human Immunodeficiency Syndrome (HIV) and Acquired Immunodeficiency Syndrome (AIDS) (PLWHA). However, little is known about the availability of hospice services in Appalachian areas. Therefore, the objective of this study is to describe the geographic distribution of hospice, homecare and nursing home facilities in order to demonstrate current existence of and access to resources for EOL care among PLWHA in the Appalachian regions of Tennessee and Alabama. Methods This paper reports on the second aim of a larger sequential, mixed methods qualitative-quantitative (qual→quan) study. Data from advance care planning (ACP) surveys were collected by both electronic (n = 28) and paper copies (n = 201) and, among other things, obtained information on zip codes of residence of PLWHA. This enabled assessment of the geographic distribution of residences of PLWHA in relation to the distribution of healthcare services such as hospice and home healthcare services. Hospice and Home Healthcare data were obtained from the Tennessee and Alabama Departments of Health. The street addresses of these facilities were used to geocode and map the geographic distributions of the facilities using Street Map USA. Travel times to Hospice and Home Healthcare facilities were computed and mapped using ArcGIS 10.3. Results We identified a total of 32 hospice and 69 home healthcare facilities in the Tennessee Appalachian region, while the Alabama Appalachian region had a total of 110 hospice and 86 home healthcare facilities. Most care facilities were located in urban centers. The distribution of care facilities was worse in Tennessee with many counties having no facilities, requiring up to an hour drive time to reach patients. A total of 86% of the PLWHA indicated preference to die at home. Conclusions Persons living with HIV/AIDS in Appalachia face a number of challenges at the end of life that make access to EOL services difficult. Although respondents indicated a preference to die at home, the hospice/homecare infrastructure and resources are overwhelmingly inadequate to meet this need. There is need to improve access to EOL care in the Appalachian regions of both Tennessee and Alabama although the need is greater in Tennessee.

Gram-negative bacteria, as well as some Gram-positive bacteria, possess hair-like appendages known as fimbriae, which play an important role in adhesion of the bacteria to surfaces or to other bacteria. Unlike the sex pili or flagellum, the fimbriae are quite numerous, with of order 1000 fimbriae appendages per bacterial cell. In this paper, a recently developed hybrid model for bacterial biofilms is used to examine the role of fimbriae tension force on the mechanics of bacterial biofilms. Each bacterial cell is represented in this model by a spherocylindrical particle, which interact with each other through collision, adhesion, lubrication force, and fimbrial force. The bacterial cells absorb water and nutrients and produce extracellular polymeric substance (EPS). The flow of water and EPS, and nutrient diffusion within these substances, is computed using a continuum model that accounts for important effects such as osmotic pressure gradient, drag force on the bacterial cells, and viscous shear. The fimbrial force is modeled using an outer spherocylinder capsule around each cell, which can transmit tensile forces to neighboring cells with which the fimbriae capsule collides. We find that the biofilm structure during the growth process is dominated by a balance between outward drag force on the cells due to the EPS flow away from the bacterial colony and the inward tensile fimbrial force acting on chains of cells connected by adhesive fimbriae appendages. The fimbrial force also introduces a large rotational motion of the cells and disrupts cell alignment caused by viscous torque imposed by the EPS flow. The current paper characterizes the competing effects of EPS drag and fimbrial force using a series of computations with different values of the ratio of EPS to bacterial cell production rate and different numbers of fimbriae per cell.

Background Neuroergonomics combines neuroscience with ergonomics to study human performance using recorded brain signals. Such neural signatures of performance can be measured using a variety of neuroimaging techniques, including functional magnetic resonance imaging (fMRI), functional near-infrared spectroscopy (fNIRS), and electroencephalography (EEG). EEG has an excellent temporal resolution, and EEG indices are highly sensitive to human brain activity fluctuations. Objective The focus of this systematic review was to explore the applications of EEG indices for quantifying human performance in a variety of cognitive tasks at the macro and micro scales. To identify trends and the state of the field, we examined global patterns among selected articles, such as journal contributions, highly cited papers, affiliations, and high-frequency keywords. Moreover, we discussed the most frequently used EEG indices and synthesized current knowledge regarding the EEG signatures of associated human performance measurements. Methods In this systematic review, we analyzed articles published in English (from peer-reviewed journals, proceedings, and conference papers), Ph.D. dissertations, textbooks, and reference books. All articles reviewed herein included exclusively EEG-based experimental studies in healthy participants. We searched Web-of-Science and Scopus databases using specific sets of keywords. Results Out of 143 papers, a considerable number of cognitive studies focused on quantifying human performance with respect to mental fatigue, mental workload, mental effort, visual fatigue, emotion, and stress. An increasing trend for publication in this area was observed, with the highest number of publications in 2017. Most studies applied linear methods (e.g., EEG power spectral density and the amplitude of event-related potentials) to evaluate human cognitive performance. A few papers utilized nonlinear methods, such as fractal dimension, largest Lyapunov exponent, and signal entropy. More than 50% of the studies focused on evaluating an individual’s mental states while operating a vehicle. Several different methods of artifact removal have also been noted. Based on the reviewed articles, research gaps, trends, and potential directions for future research were explored. Conclusion This systematic review synthesized current knowledge regarding the application of EEG indices for quantifying human performance in a wide variety of cognitive tasks. This knowledge is useful for understanding the global patterns of applications of EEG indices for the analysis and design of cognitive tasks.

Aim To review evidence about the experience of being the recipient of a donated heart, lungs, or heart and lungs. Design A systematic review (registered with PROSPERO: CRD42017067218), in accordance with PRISMA guidelines. Data sources Seven databases and Google Scholar were searched in May 2017 and July 2019 for papers reporting English-language research that had used qualitative methods to investigate experiences of adult recipients. Review methods Quality was assessed and results were analysed thematically. Results 24 papers (reporting 20 studies) were eligible and included. Their results were organised into three chronological periods: pre-transplant (encompassing the themes of ‘dynamic psychosocial impact’, ‘resources and support’), transplant (‘The Call’, ‘intensive care unit’), and post-transplant (‘dynamic psychosocial impact’, ‘management’, ‘rejection’). Sub-themes were also identified. It was evident that contemplating and accepting listing for transplantation entailed or amplified realisation of the precipitating illness’s existential threat. The period surrounding transplantation surgery was marked by profound, often surreal, experiences. Thereafter, although life usually improved, it incorporated unforeseen challenges. The transplantation clinic remained important to the recipient. The meaning of the clinic and its staff could be both reassuring (providing care and support) and threatening (representing onerous medical requirements and potential organ rejection). Conclusion This review has implications for the psychosocial care of transplant recipients and indicates the need for further research to gain insight into the experience of receiving a donated heart and/or lung. Impact Medical consequences of heart and lung transplantation are well documented; this is the first systematic review of research using qualitative methods to investigate the experience of heart, lung, and heart-and-lung transplantation. The psychosocial impact of transplantation was found to be dynamic and complex, with notable features evident before, during, and after transplantation. Clinic staff remained significant to recipients. It is clear that recipients need continuing psychosocial as well as medical support.

BackgroundThe 2013–15 Ebola epidemic in West Africa was the largest so far recorded, and mainly affected three adjacent countries, Guinea, Liberia and Sierra Leone. The worst affected country (in terms of confirmed cases) was Sierra Leone. The present paper looks at the epidemic in Sierra Leone. The epidemic in this country was a concatenation of local outbreaks. These local outbreaks are not well characterized through analysis using standard numerical techniques. In part, this reflects difficulties in record collection at the height of the epidemic. This paper offers a different approach, based on application of field-based techniques of social investigation that provide a richer understanding of the epidemic.MethodsIn a post-epidemic study (2016–18) of two districts (Bo and Moyamba) we use ethnographic data to reconstruct local infection pathways from evidence provided by affected communities, cross-referenced to records of the epidemic retained by the National Ebola Response Commission, now lodged in the Ebola Museum and Archive at Njala University. Our study documents and discusses local social and contextual factors largely missing from previously published studies.ResultsOur major finding is that the epidemic in Sierra Leone was a series of local outbreaks, some of which were better contained than others. In those that were not well contained, a number of contingent factors helps explain loss of control. Several numerical studies have drawn attention to the importance of local heterogeneities in the Sierra Leone Ebola epidemic. Our qualitative study throws specific light on a number of elements that explain these heterogeneities: the role of externalities, health system deficiencies, cultural considerations and local coping capacities.ConclusionsSocial issues and local contingencies explain the spread of Ebola in Sierra Leone and are key to understanding heterogeneities in epidemiological data. Integrating ethnographic research into epidemic-response is critical to properly understand the patterns of spread and the opportunities to intervene. This conclusion has significant implications for future interdisciplinary research and interpretation of standard numerical data, and consequently for control of epidemic outbreaks.

An MSK model of care for hip and knee patients integrated with an electronic referral solution (eReferral) has been deployed within four subregions across Ontario. Referrals are sent from primary care offices to a central intake (CI), where the referral forms are reviewed and forwarded, if appropriate, to a rapid access clinic (RAC) where patients are assessed by an advanced practice clinician (APC). The pragmatic design of eReferral allows for a seamless flow of electronic orthopedic referrals from primary care to CI. It also enables CI to process and transcribe faxed referrals into the eReferral system for a smooth flow of data electronically to the RACs. In general, wait time is the time interval between receiving the patient’s referral at CI or the surgeon’s office until receiving the orthopedic surgeon's first consultation. Wait time is further broken down into wait 1 a and wait 1 b. Wait 1 a is the time between the receipt of the referral at CI until the date of the first initial assessment at the RAC. This study aimed at: a) assessing the processing time of orthopedic referrals at central intakes (CI) to be forwarded to the RAC, b) assessing the wait time (wait 1 a) of orthopedic referrals processed through the eReferral system to receive an initial assessment at the RACs. c) comparing the ability of the RACs to meet the target wait time for assessment (four weeks) by the method of referral (eReferrals vs. fax). d) evaluating patients’ satisfaction with the length of time they waited to receive care at the RACs with eReferral. We used Ocean eReferral database to access MSK hip and knee referral data processed through the system. Patients whose referrals were initiated electronically through the system and opted to receive email notification of their referral status had the opportunity to take an online satisfaction survey embedded in the booked appointment notification message. There were 1,723 patients initially referred electronically for hip, and knee pain consults, while 13,780 referrals started as paper-based and transcribed into the system to be forwarded later electronically by CI to a RAC. Higher mean processing time at CI by 21.76 days for paper-based referral was detected as opposed to referrals received electronically (p

BackgroundThe development of deep learning (DL) algorithms is a three-step process-training, tuning, and testing. Studies are inconsistent in the use of the term "validation", with some using it to refer to tuning and others testing, which hinders accurate delivery of information and may inadvertently exaggerate the performance of DL algorithms. We investigated the extent of inconsistency in usage of the term "validation" in studies on the accuracy of DL algorithms in providing diagnosis from medical imaging.Methods and findingsWe analyzed the full texts of research papers cited in two recent systematic reviews. The papers were categorized according to whether the term "validation" was used to refer to tuning alone, both tuning and testing, or testing alone. We analyzed whether paper characteristics (i.e., journal category, field of study, year of print publication, journal impact factor [JIF], and nature of test data) were associated with the usage of the terminology using multivariable logistic regression analysis with generalized estimating equations. Of 201 papers published in 125 journals, 118 (58.7%), 9 (4.5%), and 74 (36.8%) used the term to refer to tuning alone, both tuning and testing, and testing alone, respectively. A weak association was noted between higher JIF and using the term to refer to testing (i.e., testing alone or both tuning and testing) instead of tuning alone (vs. JIF 10: adjusted odds ratio 2.41, P = 0.089). Journal category, field of study, year of print publication, and nature of test data were not significantly associated with the terminology usage.ConclusionsExisting literature has a significant degree of inconsistency in using the term "validation" when referring to the steps in DL algorithm development. Efforts are needed to improve the accuracy and clarity in the terminology usage.

Piano is a complex instrument, which humans learn to play after many years of practice. This paper investigates the complex dynamics of the embodied interactions between a human and piano, in order to gain insights into the nature of humans’ physical dexterity and adaptability. In this context, the dynamic interactions become particularly crucial for delicate expressions, often present in advanced music pieces, which is the main focus of this paper. This paper hypothesises that the relationship between motor control for key-pressing and the generated sound is a manifold problem, with high-degrees of non-linearity in nature. We employ a minimalistic experimental platform based on a robotic arm equipped with a single elastic finger in order to systematically investigate the motor control and resulting outcome of piano sounds. The robot was programmed to run 3125 key-presses on a physical digital piano with varied control parameters. The obtained data was applied to a Gaussian Process (GP) inference modelling method, to train a network in terms of 10 playing styles, corresponding to different expressions generated by a Musical Instrument Digital Interface (MIDI). By analysing the robot control parameters and the output sounds, the relationship was confirmed to be highly nonlinear, especially when the rich expressions (such as a broad range of sound dynamics) were necessary. Furthermore this relationship was difficult and time consuming to learn with linear regression models, compared to the developed GP-based approach. The performance of the robot controller was also compared to that of an experienced human player. The analysis shows that the robot is able to generate sounds closer to humans’ in some expressions, but requires additional investigations for others.

Although the peer review system of academic journals is seen as fundamental to scientific achievement, a major threat to the validity of the system is a potential evaluation bias resulting from constraints at the journal level. In this study, we examine how the time pressure to maintain a fixed periodical quota for journal publication can influence a journal editor’s decision to accept or reject a paper at any given point in time. We find that an increase in publication backlog, proxied as the average delay between paper acceptance and print publication, is correlated with an increase in the subsequent rejection rates of new submissions. Our findings suggest that time pressures inherent in the peer review system may be a source of potential evaluator bias, calling for a need to reconsider the current quota system.

We aimed to assess whether Nobel prizes (widely considered the most prestigious award in science) are clustering in work done in a few specific disciplines. We mapped the key Nobel prize-related publication of each laureate awarded the Nobel Prize in Medicine, Physics, and Chemistry (1995-2017). These key papers mapped in only narrow sub-regions of a 91,726-cluster map of science created from 63 million Scopus-indexed published items. For each key Nobel paper, a median of 435 (range 0 to 88383) other Scopus-indexed items were published within one year and were more heavily cited than the Nobel paper. Of the 114 high-level domains that science can be divided into, only 36 have had a Nobel prize. Five of the 114 domains (particle physics [14%], cell biology [12.1%], atomic physics [10.9%], neuroscience [10.1%], molecular chemistry [5.3%]) have the lion's share, accounting in total for 52.4% of the Nobel prizes. Using a more granular classification with 849 sub-domains shows that only 71 of these sub-domains (8.3%) have at least one Nobel-related paper. Similar clustering was seen when we mapped all the 40,819 Scopus-indexed publications representing the career-long output of all the Nobel laureates. In conclusion, work resulting in Nobel prizes is concentrated in a small minority of scientific disciplines.

BackgroundSurveying the scientific literature is an important part of early drug discovery; and with the ever-increasing amount of biomedical publications it is imperative to focus on the most interesting articles. Here we present a project that highlights new understanding (e.g. recently discovered modes of action) and identifies potential drug targets, via a novel, data-driven text mining approach to score type 2 diabetes (T2D) relevance. We focused on monitoring trends and jumps in T2D relevance to help us be timely informed of important breakthroughs.MethodsWe extracted over 7 million n-grams from PubMed abstracts and then clustered around 240,000 linked to T2D into almost 50,000 T2D relevant 'semantic concepts'. To score papers, we weighted the concepts based on co-mentioning with core T2D proteins. A protein's T2D relevance was determined by combining the scores of the papers mentioning it in the five preceding years. Each week all proteins were ranked according to their T2D relevance. Furthermore, the historical distribution of changes in rank from one week to the next was used to calculate the significance of a change in rank by T2D relevance for each protein.ResultsWe show that T2D relevant papers, even those not mentioning T2D explicitly, were prioritised by relevant semantic concepts. Well known T2D proteins were therefore enriched among the top scoring proteins. Our 'high jumpers' identified important past developments in the apprehension of how certain key proteins relate to T2D, indicating that our method will make us aware of future breakthroughs. In summary, this project facilitated keeping up with current T2D research by repeatedly providing short lists of potential novel targets into our early drug discovery pipeline.

Background and objectives: Population ageing has rapidly increased the number of people requiring end-of-life care across the globe. Governments have responded by promoting end-of-life in the community. Partly as a consequence, older spouses are frequently providing for their partner’s end-of-life care at home, despite potentially facing their own health issues. While there is an emerging literature on young-old caregivers, less is known about spouse carers over 75 who are likely to face specific challenges associated with their advanced age and relationship status. The aim of this review, therefore, is to identify and synthesise the literature concerning the experiences of caregiver’s aged 75 and over whose partner is approaching end-of-life. We conducted a mixed-method systematic review and narrative synthesis of the empirical literature published between 1985 and May 2019, identified from six databases: Medline, PsychINFO, Cumulative Index to Nursing and Allied Health Literature, Embase, Sociological Abstracts and Social Service Abstracts. Hand searching and reference checking were also conducted. Gough’s Weight of Evidence and Morgan’s Feminist Quality Appraisal tool used to determine the quality of papers. From the initial 7819 titles, 10 qualitative studies and 9 quantitative studies were included. We identified three themes: 1) “Embodied impact of care” whereby caring was found to negatively impact carers physical and psychological health, with adverse effects continuing into bereavement; 2) “Caregiving spouse’s conceptualisation of their role” in which caregiver’s navigated their self and marriage identities in relation to their partner’s condition and expectations about gender and place; 3) “Learning to care” which involved learning new skills and ways of coping to remain able to provide care. We identified a recent up-surge in published papers about very old spousal caregivers, which now comprise a small, medium-quality evidence base. This review outlines a range of potential lines of inquiry for future research including further clarification of the impact of caregiving on the likelihood of mortality, the incidence of men and women providing end-of-life care amongst this age group, and the role of anticipatory grief in shaping their perceptions of their relationship and their own longevity.

Background This paper investigates actions that combine nutrition and physical activity which hold potential for ‘double duty action’ to tackle multiple forms of malnutrition simultaneously. Expanding on previous research on single component actions, we assessed the state of the literature to map integrated interventions across the life course to analyse potential double duty effects, and identify knowledge gaps and needs for future design, implementation, evaluation and research for effective double duty action. Methods A scoping review of peer-reviewed and grey literature was conducted to explore the pathways that extend from combined physical activity and nutrition promotion interventions, with potential synergistic effects on outcomes other than obesity. Electronic databases were searched for studies published between 1 January 2010 and 31 January 2020. Out of 359 articles retrieved, 31 peer-reviewed and 5 grey literature sources met inclusion criteria. Findings from 36 papers reporting on 34 interventions/initiatives were organised into 6 categories, based on implementation across multiple stages of the life course. Double-duty potential was assessed through a further stage of analysis. Findings This review has identified actions that hold potential for tackling not only obesity, but healthy diets, sedentary behaviour and quality of life more generally, as well as actions that explicitly tackle multiple forms of malnutrition. Importantly, it has identified crucial gaps in current methods and praxis that call for further practice-oriented research, in order to better understand and exploit the synergistic effects of integrated interventions on outcomes other than obesity. Conclusions Findings from across implementation settings suggest that even in situations where interventions are aimed at, or framed in terms of, obesity prevention and control, there are unexploited pathways for broader outcomes of relevance to nutrition and health and wellbeing more generally. Future design and evaluation of multisectoral approaches will benefit from an explicit framing of interventions as double-duty oriented.

Background\ud Health care workers (HCWs) are essential for the delivery of health care services in conflict areas and in rebuilding health systems post-conflict.\ud Objective\ud The aim of this study was to systematically identify and map the published evidence on HCWs in conflict and post-conflict settings. Our ultimate aim is to inform researchers and funders on research gap on this subject and support relevant stakeholders by providing them with a comprehensive resource of evidence about HCWs in conflict and post-conflict settings on a global scale.\ud Methods\ud We conducted a systematic mapping of the literature. We included a wide range of study designs, addressing any type of personnel providing health services in either conflict or post-conflict settings. We conducted a descriptive analysis of the general characteristics of the included papers and built two interactive systematic maps organized by country, study design and theme.\ud Results\ud Out of 13,863 identified citations, we included a total of 474 studies: 304 on conflict settings, 149 on post-conflict settings, and 21 on both conflict and post-conflict settings. For conflict settings, the most studied counties were Iraq (15%), Syria (15%), Israel (10%), and the State of Palestine (9%). The most common types of publication were opinion pieces in conflict settings (39%), and primary studies (33%) in post-conflict settings. In addition, most of the first and corresponding authors were affiliated with countries different from the country focus of the paper. Violence against health workers was the most tackled theme of papers reporting on conflict settings, while workforce performance was the most addressed theme by papers reporting on post-conflict settings. The majority of papers in both conflict and post-conflict settings did not report funding sources (81% and 53%) or conflicts of interest of authors (73% and 62%), and around half of primary studies did not report on ethical approvals (45% and 41%).\ud Conclusions\ud This systematic mapping provides a comprehensive database of evidence about HCWs in conflict and post-conflict settings on a global scale that is often needed to inform policies and strategies on effective workforce planning and management and in reducing emigration. It can also be used to identify evidence for policy-relevant questions, knowledge gaps to direct future primary research, and knowledge clusters.

Introduction Since its initial recognition, HIV has been responsible for around 35 million deaths globally. The introduction of Antiretroviral Therapy has helped to reduce mortality from HIV. However, the resulting increased longevity has influenced the experience of people living with HIV, which now manifests as a chronic condition requiring effective self-management. This review aimed to identify and evaluate the effectiveness of interventions to improve self-management of adults living with HIV on Antiretroviral therapy. Methods The review included published experimental studies addressing interventions to improve self-management of adults living with HIV on Antiretroviral Therapy. Studies were included if they addressed two or more outcomes of self-management, as defined by the Theory of Individual and Family Self-Management. The search covered four databases and was limited to papers published in the English language from 2001 to March 30, 2019. The reference lists of included studies were further searched for additional studies. Two independent reviewers using the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument (JBI SUMARI) assessed the methodological quality of the reviewed papers. Data extraction was undertaken using the JBI SUMARI standardized data extraction tool. As the included papers were not homogeneous, it was not possible to conduct a meta-analysis. A narrative synthesis was undertaken to synthesize the findings of the included studies. Results The search identified 337 articles from which 10 experimental and 2 quasi-experimental studies were included. The total participant sample in the included studies was 1661 adults living with HIV. The overall evidence quality of the findings was considered moderate. Many of the studies included in this review comprised multi-component interventions to improve self-management. Skills training, in conjunction with other forms of interventions, particularly phone counseling, was commonly employed and generally effective in improving self-management outcomes. Counseling with a symptom management manual was another employed and effective intervention, followed by technology-assisted self-management interventions. The most common outcomes measured were maintaining medication adherence and quality of life, followed by symptom management, self-efficacy, coping, and social support. Conclusions Interventions to improve self-management varied across studies. However, promising outcomes achieved in the majority of studies through interventions comprising a combination of skills training, phone counseling, counseling with symptom management manuals, and technology-assisted interventions.

ObjectivesDespite the rising risk factor exposure and non-communicable disease (NCD) mortality across the Middle East and the North African (MENA) region, public health policy responses have been slow and appear discordant with the social, economic and political circumstances in each country. Good health policy and outcomes are intimately linked to a research-active culture, particularly in NCD. In this study we present the results of a comprehensive analysis of NCD research with particular a focus on cancer, diabetes and cardiovascular disease in 10 key countries that represent a spectrum across MENA between 1991 and 2018.MethodsThe study uses a well validated bibliometric approach to undertake a quantitative analysis of research output in the ten leading countries in biomedical research in the MENA region on the basis of articles and reviews in the Web of Science database. We used filters for each of the three NCDs and biomedical research to identify relevant papers in the WoS. The countries selected for the analyses were based on the volume of research outputs during the period of analysis and stability, included Egypt, Iran, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, Turkey and the United Arab Emirates.ResultsA total of 495,108 biomedical papers were found in 12,341 journals for the ten MENA countries (here we consider Turkey in the context of MENA). For all three NCDs, Turkey's output is consistently the highest. Iran has had considerable growth in research output to occupy second place across all three NCDs. It appears that, relative to their wealth (measured by GDP), some MENA countries, particularly Oman, Qatar, Kuwait and the United Arab Emirates, are substantially under-investing in biomedical research. In terms of investment on particular NCDs, we note the relatively greater commitment on cancer research compared with diabetes or cardiovascular disease in most MENA countries, despite cardiovascular disease causing the greatest health-related burden. When considering the citation impact of research outputs, there have been marked rises in citation scores in Qatar, Lebanon, United Arab Emirates and Oman. However, Turkey, which has the largest biomedical research output in the Middle East has the lowest citation scores overall. The level of intra-regional collaboration in NCD research is highly variable. Saudi Arabia and Egypt are the dominant research collaborators across the MENA region. However, Turkey and Iran, which are amongst the leading research-active countries in the area, show little evidence of collaboration. With respect to international collaboration, the United States and United Kingdom are the dominant research partners across the region followed by Germany and France.ConclusionThe increase in research activity in NCDs across the MENA region countries during the time period of analysis may signal both an increasing focus on NCDs which reflects general global trends, and greater investment in research in some countries. However, there are several risks to the sustainability of these improvements that have been identified in particular countries within the region. For example, a lack of suitably trained researchers, low political commitment and poor financial support, and minimal international collaboration which is essential for wider global impact.

Background Antimicrobial resistance (AMR) has become an emerging issue in the developing countries as well as in Bangladesh. AMR is aggravated by irrational use of antimicrobials in a largely unregulated pluralistic health system. This review presents a ‘snap shot’ of the current situation including existing policies and practices to address AMR, and the challenges and barriers associated with their implementation. Methods A systematic approach was adopted for identifying, screening, and selecting relevant literature on AMR situation in Bangladesh. We used Google Scholar, Pubmed, and Biomed Central databases for searching peer-reviewed literature in human, animal and environment sectors during January 2010-August 2019, and Google for grey materials from the institutional and journal websites. Two members of the study team independently reviewed these documents for inclusion in the analysis. We used a ‘mixed studies review’ method for synthesizing evidences from different studies. Result Of the final 47 articles, 35 were primary research, nine laboratory-based research, two review papers and one situation analysis report. Nineteen articles on human health dealt with prescribing and/or use of antimicrobials, five on self-medication, two on non-compliance of dosage, and 10 on the sensitivity and resistance patterns of antibiotics. Four papers focused on the use of antimicrobials in food animals and seven on environmental contamination. Findings reveal widespread availability of antimicrobials without prescription in the country including rise in its irrational use across sectors and consequent contamination of environment and spread of resistance. The development and transmission of AMR is deep-rooted in various supply and demand side factors. Implementation of existing policies and strategies remains a challenge due to poor awareness, inadequate resources and absence of national surveillance. Conclusion AMR is a multi-dimensional problem involving different sectors, disciplines and stakeholders requiring a One Health comprehensive approach for containment.

Poor visual conditions in tunnels can easily cause traffic accidents, and it is difficult for emergency services to reach these areas. As an economical and effective visual guiding device, delineators have attracted wide attention. Based on the actual alignment of the Qinling Mountain No.1, No.2 and No.3 tunnels of the G5 Expressway in Xi’an City (Shaanxi Province, China), this paper designs a simulation experiment. Through a simulator study and a questionnaire survey, this paper discusses how delineators affect drivers’ visual characteristics (including fixation area and pupil size) in different settings and with different road alignments. Twenty-five subjects participated in this research. The results show that setting delineators in tunnels can continuously guide drivers’ vision and attract their attention to focus on the pavement. Compared with setting only pavement delineators, setting wall delineators and pavement delineators together can provide better guiding effects and ensure driving safety in both straight and curved sections. In addition, when driving in tunnels equipped with delineators, especially tunnels with both wall delineators and pavement delineators, the participants exhibited a smaller pupil diameter and lower pupil diameter change rate. In terms of the relationship between pupil size and road alignment, the results indicated that regardless of what type of delineator was used, the drivers exhibited the smallest pupil size and lowest pupil change rate when driving on the straight section compared with the curved sections.

The overflow of the flame plume from the window is the main cause of the vertical spread of the fire on the facade of the building. This paper considers the geometry of the window by taking measures to prevent the flame from propagating along the vertical wall. In this paper, a residential building is taken as an example to evaluate the flame plume characteristics through experimental tests and numerical simulations. The objective of the present study is to study the flame plume characteristics under the air blow on the outer window side of the building. The theoretical equations of the flame tilt angle, non-dimensional temperature and non-dimensional velocity are derived. A series of experimental tests were carried out in a reduced-scale building model corresponding to the changes of lateral blow ventilation velocity. Reduced scale numerical simulations were conducted to verify the experiments. Results showed that the flame tilt angle increases with ventilation velocity increases. Meanwhile, the experimental results were compared with the reduced-scale tests and numerical simulations. These showed a good agreement between experimental results and numerical simulations. All these findings provide theoretical basis for building fire prevention outside window.

Background"Horizontal strokes should be level and vertical strokes should be straight" is a common guideline in the teaching of Chinese handwriting. Measuring deviations in level horizontal and straight vertical strokes in students' Chinese handwriting is usually assessed manually. However, this task is time-consuming and may have inconsistent outcomes when judged by different people. In this paper, we aim to formulate a method to automatically evaluate the tilt and slant degrees of students' Chinese handwriting using digital handwriting tablets. Furthermore, we analyze the relationship between the tilt and slant features of students' Chinese handwriting and other demographic and handwriting features.MethodsFive hundred and ninety-one primary school students from grades 1 to 6 were recruited in Hong Kong. Before the assessment, a grid paper was attached to a digital handwriting tablet. The participants were then asked to copy 90 Chinese characters from a template to the grid paper. Their handwriting processes were recorded as two-dimensional points and then analyzed. The tilt and slant of the students' handwriting were calculated based on the inclination level of their horizontal and vertical strokes. Linear regressions between slant/tilt degree of the manuscripts and other handwriting features were performed. The students' demographic information was also explored.ResultsSlant was found to be significantly correlated to Gender (p < 0.001) and tilt×standard deviation of pen pressure (p < 0.001). Tilt was found to be significantly correlated to ground time (p < 0.001), slant (p < 0.001) and slant×special education need (p = 0.021).ConclusionsOur results demonstrate the relationship between slant, tilt and Chinese handwriting performance in primary school children. Slant and tilt can be adopted as an indicator in students' special education need diagnosis, as tilt level in the students' Chinese handwriting was related to ground time and slant× special education need, while slant is related to tilt×standard deviation of pen pressure and female students. These findings may also inspire ways to increase special education need students' writing speed.

Despite the large amount of human and experimental studies no effective (prophylactic) treatment exists for chemotherapy induced peripheral neuropathy (CIPN), a disabling side effect of many cancer treatments. One of the underlying reasons for this could be that often the preclinical animal models used are not the best representation of the clinical situation. We therefore present a systematic summary and comparison of all animal models currently described in literature for CIPN focusing on stimulus evoked pain-like behaviour and neurophysiological alterations in nerve function (650 included papers, and a comparison of 183 models), that resulted in a clear overview of the most effective and robust CIPN models using an administration route used in clinical practice. Using our three-step approach (step 1: efficacy; step; 2 robustness and step 3: mimicking the clinical situation) we show that all mice CIPN models treated with either paclitaxel or cisplatin using an administration route used in clinical practice seem suitable models. Three specific models using paclitaxel or cisplatin that stand out are 1) C57BL/6 female mice receiving paclitaxel and 2) CD1 male mice receiving paclitaxel and 3) C57BL/6 male mice receiving cisplatin. This overview may help scientists selecting suitable CIPN models for their research. We hypothesize that by using effective and robust animal models that mimic the clinical situation as much as possible, the translational value of preclinical study results with respect to the potential of identifying promising treatments for CIPN in the future, will prove. The methodology described in this paper, aimed at comparing animal models, is novel and can be used by scientist in other research fields as well.

Complex network theory has been successful at unveiling the topology of the brain and showing alterations to the network structure due to brain disease, cognitive function and behavior. Functional connectivity networks (FCNs) represent different brain regions as the nodes and the connectivity between them as the edges of a graph. Graph theoretic measures provide a way to extract features from these networks enabling subsequent characterization and discrimination of networks across conditions. However, these measures are constrained mostly to binary networks and highly dependent on the network size. In this paper, we propose a novel graph-to-signal transform that overcomes these shortcomings to extract features from functional connectivity networks. The proposed transformation is based on classical multidimensional scaling (CMDS) theory and transforms a graph into signals such that the Euclidean distance between the nodes of the network is preserved. In this paper, we propose to use the resistance distance matrix for transforming weighted functional connectivity networks into signals. Our results illustrate how well-known network structures transform into distinct signals using the proposed graph-to-signal transformation. We then compute well-known signal features on the extracted graph signals to discriminate between FCNs constructed across different experimental conditions. Based on our results, the signals obtained from the graph-to-signal transformation allow for the characterization of functional connectivity networks, and the corresponding features are more discriminative compared to graph theoretic measures.

ObjectivesLittle is known about the gender and age differences associated with the effects of economic fluctuations on hospitalization for cardiovascular diseases. This paper investigates the impact of economic fluctuations on hospitalization for ischemic heart disease (IHD), stroke, and hypertension by age and gender between January 1996 and December 2012 in Taiwan.MethodsWe adopted a multiple-input time series analysis to examine the strength of the immediate and latent effects of the 17-year quarterly unemployment rates (UR), air pollution exposure (APE), gross domestic product (GDP), per capita consumption expenditure in cigarette and alcohol (ECA), and per capita healthcare expenditure (HE) on the adjusted quarterly incidence rate of hospitalization. The data used in this paper were retrieved from the National Health Insurance Research Database and the website of the Directorate-General of Budget, Accounting and Statistics (DGBAS), Executive Yuan.ResultsOur findings indicate that higher UR increased IHD hospitalization in young men and women and middle-aged women but reduced stroke hospitalization in young men. Higher APE increased IHD hospitalization in young men but reduced it for young women, increased stroke hospitalization in old men and middle-aged women but reduced it for young men, and increased hypertension hospitalization in middle-aged men and young women. Higher ECA reduced IHD hospitalization in middle-aged men, increased stoke hospitalization in middle-aged and old men and middle-aged women. Higher HE reduced IHD hospitalization in old men, young and old women, reduced stroke hospitalization in old women, and reduced hypertension hospitalization in young and middle-aged women.ConclusionsOverall, we found that the economic fluctuations caused increased harmful effects in certain population subgroups but also brought some soothing effects to some groups.