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In our planned study, we shall empirically study the assessment of cited papers within the framework of the anchoring-and-adjustment heuristic. We are interested in the question whether citation decisions are (mainly) driven by the quality of cited references. The design of our study is oriented towards the study by Teplitskiy, Duede [10]. We shall undertake a survey of corresponding authors with an available email address in the Web of Science database. The authors are asked to assess the quality of papers that they cited in previous papers. Some authors will be assigned to three treatment groups that receive further information alongside the cited paper: citation information, information on the publishing journal (journal impact factor), or a numerical access code to enter the survey. The control group will not receive any further numerical information. In the statistical analyses, we estimate how (strongly) the quality assessments of the cited papers are adjusted by the respondents to the anchor value (citation, journal, or access code). Thus, we are interested in whether possible adjustments in the assessments can not only be produced by quality-related information (citation or journal), but also by numbers that are not related to quality, i.e. the access code. The results of the study may have important implications for quality assessments of papers by researchers and the role of numbers, citations, and journal metrics in assessment processes.

Objective To survey the knowledge, attitude, and practices of Vietnamese pharmacists regarding the COVID-19 pandemic. Method This cross-sectional, paper-based study was conducted from June to August 2020. A validated questionnaire (Cronbach’s alpha = 0.84) was used to interview 1,023 pharmacists in nine provinces of Vietnam. Analysis of covariance was employed to identify factors associated with the knowledge of pharmacists. The best model was chosen by using the Bayesian Model Averaging method in R software version 4.0.4. Results The mean knowledge score was 12.02 ± 1.64 (range: 6–15), which indicated that 93.4% of pharmacists had good knowledge of COVID-19. There was no difference in the average score between males and females (p > 0.05). The multivariate linear regression model revealed that the knowledge was significantly associated with pharmacists’ age, education level, and residence (p < 0.001). About attitude and practices, pharmacists daily sought and updated information on the COVID-19 pandemic through mass media and the internet (social network and online newspapers). Nearly 48% of them conceded that they communicated with customers when at least one person did not wear a face mask at the time of the COVID-19 outbreak. At medicine outlets, many measures were applied to protect pharmacists and customers, such as equipping pharmacists with face masks and hand sanitizers (95.0%), using glass shields (83.0%), and maintaining at least one-meter distance between two people (85.2%). Conclusion The pharmacists’ knowledge of COVID-19 transmission, symptoms, and prevention was good. Many useful measures against the spread of this perilous virus were applied in medicine outlets. However, pharmacists should restrict forgetting to wear face masks in communication with medicine purchasers. The government and health agencies should have practical remedies to reduce the significant differences in the COVID-19 knowledge of pharmacists among provinces and education-level groups.

The highly contagious nature of SARS-CoV-2 has led to several studies on the transmission of the virus. A little studied potential fomite of great concern in the community is currency, which has been shown to harbor microbial pathogens in several studies. Since the onset of the COVID-19 pandemic, many businesses in the United States have limited the use of banknotes in favor of credit cards. However, SARS-CoV-2 has shown greater stability on plastic in several studies. Herein, the stability of SARS-CoV-2 at room temperature on banknotes, money cards and coins was investigated. In vitro studies with live virus suggested SARS-CoV-2 was highly unstable on banknotes, showing an initial rapid reduction in viable virus and no viral detection by 24 hours. In contrast, SARS-CoV-2 displayed increased stability on money cards with live virus detected after 48 hours. Environmental swabbing of currency and money cards on and near the campus of Brigham Young University supported these results, with no detection of SARS-CoV-2 RNA on banknotes, and a low level on money cards. However, no viable virus was detected on either. These preliminary results suggest that the use of money cards over banknotes in order to slow the spread of this virus may be ill-advised. These findings should be investigated further through larger environmental studies involving more locations.

This study, based in San Bernardino County, Southern California, collected and examined tap water samples within the area to explore the feasibility of adopting non-industrial equipment and methods to reduce water hardness and total dissolved solids(TDS). We investigated how water quality could be improved by utilizing water boiling, activated carbon and sodium bicarbonate additives, as well as electrolysis methods. The results show that heating is effective at lower temperatures rather than long boils, as none of the boiling tests were lower than the original value. Activated carbon is unable to lower TDS, because it is unable to bind to any impurities present in the water. This resulted in an overall TDS increase of 3.5%. However, adding small amounts of sodium bicarbonate(NaHCO3) will further eliminate water hardness by reacting with magnesium ions and improve taste, while increasing the pH. When added to room temperature tap water, there is a continuous increase in TDS of 24.8% at the 30 mg/L mark. The new findings presented in this study showed that electrolysis was the most successful method in eliminating TDS, showing an inverse proportion where an increasing electrical current and duration of electrical lowers more amounts of solids. This method created a maximum decrease in TDS by a maximum of 22.7%, with 3 tests resulting in 15.3–16.6% decreases. Furthermore, when water is heated to a temperature around 50°C (122°F), a decrease in TDS of around 16% was also shown. The reduction of these solids will help lower water hardness and improve the taste of tap water. These results will help direct residents to drink more tap water rather than bottled water with similar taste and health benefits for a cheaper price as well as a reduction on plastic usage.

Synthetic fibers are increasingly seen to dominate microplastic pollution profiles in aquatic environments, with evidence pointing to textiles as a potentially important source. However, the loss of microfibers from textiles during laundry is poorly understood. We evaluated microfiber release from a variety of synthetic and natural consumer apparel textile samples (n = 37), with different material types, constructions, and treatments during five consecutive domestic laundry cycles. Microfiber loss ranged from 9.6 mg to 1,240 mg kg-1 of textile per wash, or an estimated 8,809 to > 6,877,000 microfibers. Mechanically-treated polyester samples, dominated by fleeces and jerseys, released six times more microfibers (161 ± 173 mg kg-1 per wash) than did nylon samples with woven construction and filamentous yarns (27 ± 14 mg kg-1 per wash). Fiber shedding was positively correlated with fabric thickness for nylon and polyester. Interestingly, cotton and wool textiles also shed large amounts of microfibers (165 ± 44 mg kg-1 per wash). The similarity between the average width of textile fibers here (12.4 ± 4.5 μm) and those found in ocean samples provides support for the notion that home laundry is an important source of microfiber pollution. Evaluation of two marketed laundry lint traps provided insight into intervention options for the home, with retention of up to 90% for polyester fibers and 46% for nylon fibers. Our observation of a > 850-fold difference in the number of microfibers lost between low and high shedding textiles illustrates the strong potential for intervention, including more sustainable clothing design.

Since the innovation of our new half-piece elastometric respirator, this type of filtering facepiece respirator (FFR) has been used widely in Thailand. Decontamination methods including ultraviolet C (UVC) germicidal irradiation and 70% alcohol have been implemented to decontaminate these respirators. We then examined the inactivation potential of different decontamination processes on porcine epidemic diarrhea virus (PEDV) and numerous bacterial strains, most of which were skin-derived. To enable rigorous integrity of the masks after repeated decontamination processes, fit tests by the Bitrex test, tensile strength and elongation at break were also evaluated. Our results showed that UVC irradiation at a dose of 3 J/cm2 can eradicate bacteria after 60 min and viruses after 10 min. No fungi were found on the mask surface before decontamination. The good fit test results, tensile strength and elongation at break were still maintained after multiple cycles of decontamination. No evidence of physical degradation was found by gross visual inspection. Alcohol (70%) is also an easy and effective way to eradicate microorganisms on respirators. As the current pandemic is expected to continue for months to years, the need to supply adequate reserves of personnel protective equipment (PPE) and develop effective PPE reprocessing methods is crucial. Our studies demonstrated that the novel silicone mask can be safely reprocessed and decontaminated for many cycles by UVC irradiation, which will help ameliorate the shortage of important protective devices in the COVID-19 pandemic era.

Extensive research shows that residential segregation has severe health consequences for racial and ethnic minorities. Most research to date has operationalized segregation in terms of either poverty or race/ethnicity rather than a synergy of these factors. A novel version of the Index of Concentration at the Extremes (ICERace-Income) specifically assesses racialized economic segregation in terms of spatial concentrations of racial and economic privilege (e.g., wealthy white people) versus disadvantage (e.g., poor Black people) within a given area. This multidimensional measure advances a more comprehensive understanding of residential segregation and its consequences for racial and ethnic minorities. The aim of this paper is to critically review the evidence on the association between ICERace-Income and health outcomes. We implemented the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to conduct a rigorous search of academic databases for papers linking ICERace-Income with health. Twenty articles were included in the review. Studies focused on the association of ICERace-Income with adverse birth outcomes, cancer, premature and all-cause mortality, and communicable diseases. Most of the evidence indicates a strong association between ICERace-Income and each health outcome, underscoring income as a key mechanism by which segregation produces health inequality along racial and ethnic lines. Two of the reviewed studies examined racial disparities in comorbidities and health care access as potential explanatory factors underlying this relationship. We discuss our findings in the context of the extant literature on segregation and health and propose new directions for future research and applications of the ICERace-Income measure.

To better prevent the potential risks in Internet-based Supply Chain Financing (SCF) products, this paper optimizes and evaluates the Internet-based SCF-oriented Credit Risk Evaluation (CRE) method. Firstly, this paper summarizes 12 risk factors of SCF business, establishes a Risk Assessment Index System (RAIS) with good consistency and stability; then, the principles of Backpropagation (BP) Neural Network (NN) is expounded together with Support Vector Machines (SVM) and Genetic Algorithm (GA) model. Consequently, a CRE model is implemented by the NN tools in MATLAB based on the collection of multiple groups of SCF-oriented risk assessment samples. Subsequently, the assessment samples are trained and tested. Finally, the SCF-oriented CRE model is proposed and verified. The results show that the BP-GA model has presented high prediction consistency with the actual classification. According to the comparison of classification results of SVM, BP model, and BP-GA model, the classification accuracy of test samples of the proposed Internet-based SCF-oriented CRE system using BP-GA model reaches 97.19%; the Type I and Type II error rate of the CRE system based on BP-GA model is 7.2% and 14.21%, respectively. Therefore, a suitable SCF-oriented CRE method is put forward for China’s commercial banks along with scientific and feasible suggestions to manage SCF-oriented credit risks more reasonably and effectively.

Background The ligaments in the knee are prone to injury especially during dynamic activities. The resulting instability can have a profound impact on a patient’s daily activities and functional capacity. Musculoskeletal knee modelling provides a non-invasive tool for investigating ligament force-strain behaviour in various dynamic scenarios, as well as potentially complementing existing pre-planning tools to optimise surgical reconstructions. However, despite the development and validation of many musculoskeletal knee models, the effect of modelling parameters on ligament mechanics has not yet been systematically reviewed. Objectives This systematic review aimed to investigate the results of the most recent studies using musculoskeletal modelling techniques to create models of the native knee joint, focusing on ligament mechanics and modelling parameters in various simulated movements. Data sources PubMed, ScienceDirect, Google Scholar, and IEEE Xplore. Eligibility criteria for selecting studies Databases were searched for articles containing any numerical ligament strain or force data on the intact, ACL-deficient, PCL-deficient, or lateral extra-articular reconstructed (LER) knee joints. The studies had to derive these results from musculoskeletal modelling methods. The dates of the publications were between 1 January 1995 and 30 November 2021. Method A customised data extraction form was created to extract each selected study’s critical musculoskeletal model development parameters. Specific parameters of the musculoskeletal knee model development used in each eligible study were independently extracted, including the (1) musculoskeletal model definition (i.e., software used for modelling, knee type, source of geometry, the inclusion of cartilage and menisci, and articulating joints and joint boundary conditions (i.e., number of degrees of freedom (DoF), subjects, type of activity, collected data and type of simulation)), (2) specifically ligaments modelling techniques (i.e., ligament bundles, attachment points, pathway, wrapping surfaces and ligament material properties such as stiffness and reference length), (3) sensitivity analysis, (4) validation approaches, (5) predicted ligament mechanics (i.e., force, length or strain) and (6) clinical applications if available. The eligible papers were then discussed quantitatively and qualitatively with respect to the above parameters. Results and discussion From the 1004 articles retrieved by the initial electronic search, only 25 met all inclusion criteria. The results obtained by aggregating data reported in the eligible studies indicate that considerable variability in the predicted ligament mechanics is caused by differences in geometry, boundary conditions and ligament modelling parameters. Conclusion This systematic review revealed that there is currently a lack of consensus on knee ligament mechanics. Despite this lack of consensus, some papers highlight the potential of developing translational tools using musculoskeletal modelling. Greater consistency in model design, incorporation of sensitivity assessment of the model outcomes and more rigorous validation methods should lead to better agreement in predictions for ligament mechanics between studies. The resulting confidence in the musculoskeletal model outputs may lead to the development of clinical tools that could be used for patient-specific treatments.

This study assesses the practices and views of Scottish dairy farmers relating to pasture-based and indoor systems. There are the debates about the environmental, economic and animal welfare implications of these systems. Indoor dairy farming is a contentious practice among the public. While this controversy is sometimes represented as a lack of public understanding, there is a need for more research on farmers’ views to facilitate discussion in the industry. A survey was posted to 909 dairy farmers in Scotland with questions about their grazing practices and attitudes to grazing and indoor systems. 254 surveys were completed, online and in paper form. There was a 26% response rate to the paper version of the survey. The results showed that 19% of respondents housed some or all the cows all year-round. 68% agreed or strongly agreed that cows should graze for part of the year and 51% agreed or strongly agreed that welfare was better if cows grazed for part of the year. These views coexisted with the view that management was more important than the type of system for determining profitability or welfare outcomes (83% and 82% strongly agree or agree respectively). Respondents whose system involved grazing and respondents who had spent longer in farming were moderately more likely to agree that cows should have access to pasture, and slightly less likely to agree that management was more important than system for determining welfare outcomes. The results indicate that the picture is more complicated than the public rejecting indoor dairy farming and those in the industry accepting it. The results showed that a majority preference for cows to graze co-existed with the view that management was more important than system. In terms of industry and policy recommendations, the research suggests that measures should be taken to safeguard farmers’ ability to graze through for instance research and advisory support on grazing; ensuring different systems are not penalised in the development of dairy sector environmental measures and recommendations; and potentially supply chains that financially rewards farmers for grazing.

Ecosystem markets are proliferating around the world in response to increasing demand for climate change mitigation and provision of other public goods. However, this may lead to perverse outcomes, for example where public funding crowds out private investment or different schemes create trade-offs between the ecosystem services they each target. The integration of ecosystem markets could address some of these issues but to date there have been few attempts to do this, and there is limited understanding of either the opportunities or barriers to such integration. This paper reports on a comparative analysis of eleven ecosystem markets in operation or close to market in Europe, based on qualitative analysis of 25 interviews, scheme documentation and two focus groups. Our results indicate three distinct types of markets operating from the regional to national scale, with different modes of operation, funding and outcomes: regional ecosystem markets, national carbon markets and green finance. The typology provides new insights into the operation of ecosystem markets in practice, which may challenge traditionally held notions of Payment for Ecosystem Services. Regional ecosystem markets, in particular, represent a departure from traditional models, by using a risk-based funding model and aggregating both supply and demand to overcome issues of free-riding, ecosystem service trade-offs and land manager engagement. Central to all types of market were trusted intermediaries, brokers and platforms to aggregate supply and demand, build trust and lower transaction costs. The paper outlines six options for blending public and private funding for the provision of ecosystem services and proposes a framework for integrating national carbon markets and green finance with regional ecosystem markets. Such integration may significantly increase funding for regenerative agriculture and conservation across multiple habitats and services, whilst addressing issues of additionality and ecosystem service trade-offs between multiple schemes.

The symport of lactose and H+ is an important physiological process in E. coli, for it is closely related to cellular energy supply. In this paper, the symport of H+ and lactose by E. coli LacY protein is computationally simulated using a newly proposed cotransport model that takes the "leakage" phenomenon (uncoupled sugar translocation) into account and also satisfies the static head equilibrium condition. Then, we study the equilibrium properties of this cotransport process including equilibrium solution and the time required to reach equilibrium state, when varying the parameters of the initial state of cotransport system. It can be found that in the presence of leakage, H+ and lactose will reach their equilibrium state separately, but the intensity of "leakage" has almost no effect on the equilibrium solution, while the stronger leakage is, the shorter the time required for H+ and lactose to reach equilibrium. For E. coli cells with different periplasm and cytoplasm volumes, when cotransport is performed at constant initial particle concentration, the time for cytoplasm pH to be stabilized increases monotonically with the periplasm to cytoplasm volume ratio. For a certain E. coli cell, as it continues to lose water and contract, the time for cytoplasm pH to be stabilized by cotransport also increases monotonically when the cell survives. The above phenomena and other findings in this paper may help us to not only further validate or improve the model, but also deepen our understanding of the cotransport process of E. coli LacY protein., 10 figures

Background Coronavirus (COVID-19) has severely impacted lifestyles worldwide. Responses to COVID-19 have intentionally restricted the factors that encourage regular and frequent PA; opportunity, capability and motivation. However, the effects of these restrictions are likely to have differed by gender and age and different intensities of PA. This rapid review builds on previous evidence by synthesising the global impact of COVID-19 on adult PA through specific intensities and types of PA and evaluating this by gender and age. Methods A rapid systematic search of seven electronic databases (PubMed, MEDLINE, CINAHL, SPORTDiscus, Academic Search Complete, APA PsycInfo, and APA PsycArticles) was performed from December 2019 to January 2021. Studies investigating adult change in PA, exercise or sedentary behaviour due to COVID-19 were included. Results From an initial database search identifying 3,863 articles, 66 remained for synthesis after applying eligibility criteria. Results demonstrate decreases among all intensities and types of PA—walking (6 out of 7 papers), moderate-only (5 out of 6 papers), vigorous-only (5 out of 6 papers) and MVPA (4 out of 5 papers); as well as overall PA (14–72% participants reported a decrease). Reflecting that COVID-19 responses were designed to have universal effects, they also achieved whole-society decreases in PA behaviour, accented in older age groups. Conclusion There is a universal need to address the low levels of PA post-COVID-19. The consequences of decreased PA across all intensities has powerful, potentially recoverable, impacts. Universal declines have implications for public health officials and PA advocates for post-COVID-19 initiatives to promote PA.

The analysis of brain-imaging data requires complex and often non-linear transformations to support findings on brain function or pathologies. And yet, recent work has shown that variability in the choices that one makes when analyzing data can lead to quantitatively and qualitatively different results, endangering the trust in conclusions1–3. Even within a given method or analytical technique, numerical instabilities could compromise findings4–7. We instrumented a structural-connectome estimation pipeline with Monte Carlo Arithmetic8, 9, a technique to introduce random noise in floating-point computations, and evaluated the stability of the derived connectomes, their features10, 11, and the impact on a downstream analysis12, 13. The stability of results was found to be highly dependent upon which features of the connectomes were evaluated, and ranged from perfectly stable (i.e. no observed variability across executions) to highly unstable (i.e. the results contained no trustworthy significant information). While the extreme range and variability in results presented here could severely hamper our understanding of brain organization in brain-imaging studies, it also leads to an increase in the reliability of datasets. This paper highlights the potential of leveraging the induced variance in estimates of brain connectivity to reduce the bias in networks alongside increasing the robustness of their applications in the detection or classification of individual differences. This paper demonstrates that stability evaluations are necessary for understanding error and bias inherent to scientific computing, and that they should be a component of typical analytical workflows.

Distracted driving behavior is one of the main factors of road accidents. Accurately predicting the risk of driving behavior is of great significance to the active safety of road transportation. The large amount of information collected by the sensors installed on the vehicle can be identified by the algorithm to obtain the distracted driving behavior data, which can be used to predict the driving behavior risk of the vehicle and the area. In this paper, a new neural network named Driving Behavior Risk Prediction Neural Network (DBRPNN) is developed for prediction based on the distracted driving behavior data. The network consists of three modules: the Feature Processing Module, the Memory Module, and the Prediction Module. In this process, attribute data (time in a day, daily driving time, and daily driving mileage) that can reflect external factors and driver statuses, are added to the network to increase the accuracy of the model. We predicted the driving behavior risk of different objects (Vehicle and Area). For the applicability improvement of the model, we further classify the distracted driving behavior categories, and DBRPNN can provide more accurate risk prediction. The results show that compared with traditional models (Classification and Regression Tree, Support Vector Machines, Recurrent Neural Network, and Long Short-Term Memory), DBRPNN has better prediction performance. The method proposed in this paper has been fully verified and may be transplanted into active safety early warning system for more accurate and flexible application.

The prevalence of dyslexia identification has increased significantly over the last two decades. Yet there is debate over whether there are distinct biological and cognitive differences between those with literacy difficulties and the subgroup of people identified as dyslexic. This is the first paper that provides evidence for this ongoing debate by investigating the socio-demographic factors, outside biology and cognition, that predict whether a child is identified as dyslexic in the UK. Using secondary data from the UK’s Millennium Cohort Study, this paper examines the socio-demographic factors that predict whether a child’s teacher identifies them as dyslexic at age 11. Gender, season of birth, socio-economic class and parental income are found to be significant predictors of the dyslexia label. Therefore, factors seemingly unrelated to the clinical aspects of dyslexia influence whether a child is identified as dyslexic in England and Wales. This suggests that label may not be evenly distributed across a population; furthermore, it may also indicate that resources for support may not be fairly allocated. The findings further support the argument that a ‘dyslexic sub-group’ within poor readers is created due to the impact of environmental factors. The results from this national-scale study thus questions the reliability, validity and moral integrity of the allocation of the dyslexia label across current education systems in the UK.

In recent decades, animal welfare science has evolved to utilize a multidisciplinary approach to assess the welfare of animals in accredited zoos and aquariums. Science-based animal welfare assessments have become an essential component of management programs and widespread application is expected by animal care professionals. Management practices for bottlenose dolphins in accredited facilities incorporate several programs that potentially impact animal welfare including environmental enrichment and animal training. Additionally, habitat characteristics, such as the dimensions of the habitat, have been proposed to affect welfare. While accredited facilities are required to meet high standards of care, habitat characteristics and management practices are not standardized across locations. Knowledge and subsequent application of these practices and habitat characteristics can enhance our understanding of factors associated with positive welfare. As part of a larger study of dolphin welfare titled “Towards understanding the welfare of cetaceans in zoos and aquariums” (colloquially called the Cetacean Welfare Study), survey data were collected from 86 bottlenose dolphins in 40 habitats at 38 facilities in seven countries. The major aims of this paper are to provide general descriptive information regarding dolphin management in accredited zoos and aquariums and to provide supplemental context to the other research published from the Cetacean Welfare Study data set. This paper provides a review of current habitat characteristics and management practices at those 38 accredited zoos and aquariums. These data enabled the identification and quantification of how cetacean management practices differed between participating facilities accredited by the Alliance for Marine Mammal Parks and Aquariums and the Association of Zoos & Aquariums. Variables were selected based on their potential association with welfare including the physical habitat, environmental enrichment, and training programs. The variables were also used for subsequent research in this collection of related papers to investigate important connections between potential indicators of welfare and habitat characteristics, environmental enrichment, and training programs.

This paper introduces anenhanced MSM(Mutual Subspace Method) methodology for gait recognition, to provide robustness to variations in walking speed. Theenhanced MSM (eMSM)methodology expands and adapts the MSM, commonly used for face recognition, which is a static/physiological biometric, to gait recognition, which is a dynamic/behavioral biometrics. To address the loss of accuracy during calculation of the covariance matrix in the PCA step of MSM, we use a 2D PCA-based mutual subspace. Furhtermore, to enhance the discrimination capability, we rotate images over a number of angles, which enables us to extract richer gait features to then be fused by a boosting method. The eMSM methodology is evaluated on existing data sets which provide variable walking speed, i.e. CASIA-C and OU-ISIR gait databases, and it is shown to outperform state-of-the art methods. While the enhancement to MSM discussed in this paper uses combinations of 2D-PCA, rotation, boosting, other combinations of operations may also be advantageous.

Depending on the strategy of "Healthy China", more and more people pay attention to health issues. The integration and development of sports industry and health service industry is an inevitable outcome of industrial transformation and upgrading and healthy life in the new era. Through constructing the evaluation index system of the coupling and coordination development degree between sports industry and health service industry, using entropy evaluation method and coupling and coordination degree model, this paper explore the comprehensive level and coupling and coordination development status of sports industry and health service industry in thirty-one provinces, municipality cities and autonomous regions of China from 2013 to 2017. The results of this paper show that the comprehensive China’s sports industry and health service industry both present an incremental development trend year by year, and are characterized by the distribution of "high in the east and low in the west" in space. The government’s policy support provides superior industrial supporting conditions for the development of sports industry. However, it is not conducive to the promotion of industrial economic benefits. In the health service industry, the rapid development of health insurance is beneficial to the integration of industrial resources and the perfection of industrial chain. Whereas as the core content of health service industry, health service has greater space for development; the coupling and coordination degree between the two industries rises from mild maladjustment to basic coordination, which is characterized by the distribution of "high in the east and low in the west" in space; among provinces, with Beijing, the Yangtze River Delta and Guangdong as the three development center points, it shows the spatial evolutionary process from "dispersion-type plaques" to "gathering type scattered surfaces".

Construction of not in my back yard (NIMBY) facility Public Private Partnership (PPP) projects are feasible measures to realize sustainable urbanization. In order to ensure the smooth development of the NIMBY facility PPP projects, the problem of choosing the most suitable operation mode among many PPP modes is still scarce and unscientific. In order to select the operation mode of the PPP projects that best fits the characteristics of the project, this paper constructs the operation mode selection of the NIMBY facility PPP project. Firstly, the index system of operation mode selection of the NIMBY facility PPP project is determined. G1 subjective weighting method and information entropy objective weighting method are introduced to solve the optimal weight of each index. Grey correlation theory is used to improve TOPSIS method, and the calculation form of relative proximity degree is optimized to determine the most suitable operation mode for the project. In this paper, combined weighting and TOPSIS method are applied to the research of NIMBY facility PPP project, and the operation mode selection of NIMBY facility PPP project is established, which makes up the blank of this part. Finally, a PPP project in Qingdao, Shandong Province, China, is taken as an example to verify the applicability of the model. The effectiveness of this model was tested by comparing the results of TOPSIS method, Grey target model, Extended matter-element mode and GRA-TOPSIS. It is hoped to provide useful reference for the operation mode selection of NIMBY facility PPP project.

Background Cambodia is widely credited for its successful HIV epidemic control. However, in recent years there have been signs of increasing HIV prevalence among men who have sex with men (MSM) and transgender women (TGW). This paper reviews HIV epidemiological, social science and HIV program implementation studies conducted over the past 20 years to explore possible reasons for the rising HIV prevalence among these groups and to formulate recommendations for improved policies, HIV programmatic interventions and further research. Methods For this scoping review, we searched the PubMed and Google Scholar databases for scientific publications related to HIV and MSM and TGW in Cambodia published since 1999. From each of the returned citations we subsequently studied reference lists to find additional data sources. We also searched websites for reports commissioned by national and international governmental and non-governmental organizations. Results Twenty-seven relevant studies and papers were found and reviewed; most were epidemiological in nature. Recent epidemiological studies and reports show an increase in HIV prevalence among Cambodian MSM and TGW. The epidemiology of HIV infection in these groups has been relatively well-described and analyzed. While initially MSM and TGW were grouped together, in more recent years they have been studied in their own right, recognizing their specific HIV and other prevention needs. Few studies were found investigating Cambodian same-sex cultures and social and cultural contexts in which HIV transmission among MSM and TGW occurs. A few evaluation studies were found, but it remains unknown how effective current HIV service implementation modalities are, or how successful strategies to increase access to essential HIV prevention, testing and treatment services have been employed for MSM and TGW in Cambodia. Conclusions Research about Cambodian MSM and TGW in the context of HIV primarily concerns bio-behavioral knowledge generation. Cambodia is unlikely to achieve control of the HIV epidemic among MSM and TGW without doing better in-depth social science research on its multiple sexual- and gender minority cultures, and without understanding what differentiated implementation modalities, strategies and approaches are most effective to address HIV among its increasingly diverse MSM and TGW populations.

The humans of modern society are enjoying the luxuries and comforts today but future generations will be facing a more polluted environment and scarcity of natural resources. So the effects of global warming and climatic changes are a major policy concern nowadays around the world. The majority of the literature treats the Carbon Dioxide emissions as an indicator of environmental deterioration but this paper considers the environmental performance index as an indicator of environment. This paper addresses the role of institutional reforms for environmental performance that is hardly discussed in the earlier literature. It is argued that a novel approach of institutional reforms can provide some useful insights for environmental performance in developing countries. There is wide agreement that institutional quality is crucial for economic sustainability but rarely focused to explore the impacts of institutional reforms on environmental performance. The institutional reforms are generally divided into two categories; economic and political reforms. This paper investigated the impact of each category of institutional reforms for environmental performance by using panel data of 122 developing economies for a period of 1996–2020. Difference in differences technique is applied to determine the impact of each category of reforms on the environment. It is found that economic and political reforms significantly contribute to protecting the environment in developing countries, and it will be a good policy option to reform the economic and political institutions to preserve the environment in these countries along with sustainable development.

Cosegmentation is a newly emerging computer vision technique used to segment an object from the background by processing multiple images at the same time. Traditional plant phenotyping analysis uses thresholding segmentation methods which result in high segmentation accuracy. Although there are proposed machine learning and deep learning algorithms for plant segmentation, predictions rely on the specific features being present in the training set. The need for a multi-featured dataset and analytics for cosegmentation becomes critical to better understand and predict plants’ responses to the environment. High-throughput phenotyping produces an abundance of data that can be leveraged to improve segmentation accuracy and plant phenotyping. This paper introduces four datasets consisting of two plant species, Buckwheat and Sunflower, each split into control and drought conditions. Each dataset has three modalities (Fluorescence, Infrared, and Visible) with 7 to 14 temporal images that are collected in a high-throughput facility at the University of Nebraska-Lincoln. The four datasets (which will be collected under the CosegPP data repository in this paper) are evaluated using three cosegmentation algorithms: Markov random fields-based, Clustering-based, and Deep learning-based cosegmentation, and one commonly used segmentation approach in plant phenotyping. The integration of CosegPP with advanced cosegmentation methods will be the latest benchmark in comparing segmentation accuracy and finding areas of improvement for cosegmentation methodology.

The rapid development of urbanization has had a dramatic impact on the economy, society and environment in China. In this context, the coordination relationship between population urbanization and land urbanization is essential for achieving sustainable urbanization. Based on the statistical data from 2007–2017 in the Yangtze River Economic Belt (YEB), this paper established the multi-dimensional coordination evaluation (MDCE) model by using the speed coordination evaluation (SCE) model, the level consistency evaluation (LCE) model, the entropy method and the space matching evaluation (SME) model to evaluate the coordination relationship between population urbanization and land urbanization from the speed-level-space perspective. The results showed that from 2007 to 2017: 1) the development speed of population urbanization and land urbanization in the YEB were more and more coordinated, and the speed of population urbanization lagged behind that of land urbanization. In addition, the overall development speed of the 11 provinces declined, and most of them were characterized by excessive development of land urbanization. 2) the development level of population urbanization and land urbanization in the YEB were all high, but the development level of population urbanization was lower than that of land urbanization. Further, the development level of the 11 provinces remained stable and high, and continuously improved. 3) the space matching of population urbanization and land urbanization in the YEB had a high degree of coordination, and the space matching degree of population urbanization was higher than that of land urbanization. Moreover, the space matching of most provinces in the region had declined, but the change was small. Finally, this paper proposes the policy recommendations on the coordinated development of population and land urbanization at the institutional, market and management levels to achieve coordinated and sustainable urbanization.

Overweight and obesity has reach pandemic levels, with two-thirds (67%) of adult Australians classified as overweight or obese. As two of the most significant behavioral risk factors for obesity are modifiable (diet and exercise), there exists an opportunity for treatment through workplace health promotion initiatives. As one of Australia’s largest industries with its own unique workplace factors, the mining industry has previously reported higher than population levels of overweight and obesity. This represented an opportune setting to test the RESHAPE workplace wellness program. RESHAPE is an eight-step framework (based on the WHO ‘Health Workplace Framework and Model’) which aims to provide a sustained approach to wellness in the workplace. This paper presents baseline findings from a pilot study that aimed to implement RESHAPE at three mine sites in NSW, Australia, and investigates the issue of overweight and obesity in the coal mining industry. Across three mine sites, 949 coal miners were examined cross-sectionally on a range of workplace, wellness, health, diet, and exercise factors using a paper-based survey. This was a predominantly male sample (90.4%) with the majority (59.2%) of participants aged 25–44 years. Self-reported height and weight measures indicated that less than 20 percent (18.9%) of participants were in a healthy BMI range, while there were effectively equal numbers of overweight (40.9%) and obese (39.1%) participants. Only 3.5% of participants met the daily recommendation for vegetables (5 serves) and shift-workers had greater association with elevated BMI compared to non-shift workers (B = 1.21, 95% CI: 0.23, 2.20, p = 0.016). Poor nutrition is likely to be a key component in elevated levels of overweight and obesity within this industry, with workplace factors compounding challenges workers face in implementing health behavior change. Future studies would benefit from assessing diet and physical activity knowledge in relation to recommendations and serving sizes.

The Sustainable Development Goals include a target on eliminating child marriage, a human rights abuse. Yet, the indicator used in the SDG framework is a summary statistic and does not provide a full picture of the incidence of marriage at different ages. This paper aims to address this limitation by providing an alternative method of measuring child marriage. The paper reviews recent data on nuptiality and captures evidence of changes in the proportion married and in the age at marriage, in 98 low- and middle-income countries (LMICs). Using data collected from nationally representative Demographic and Health Surveys and Multiple Indicator Cluster Surveys, survival analysis is applied to estimate (a) age-specific marriage hazard rates among girls before age 18; and (b) the number of girls that were married before age 18 in 2020. Results show that the vast majority of girls remain unmarried until age 10. Child marriage rates increase gradually until age 14 and accelerate significantly thereafter at ages 15–17. By accounting for both single-year-age-specific child marriage hazard rates and the age structure of the population with a survival analysis approach, lower estimates in countries with a rapid decrease in child marriage and higher estimates in countries with constant or slightly rising child marriage rates relative to the direct approach are obtained.

As natural backwater structures, landslide dams both threaten downstream human settlement or infrastructure and contain abundant hydro-energy and tourism resources, so research on their development feasibility is of great significance for permanently remedying them and effectively turning disasters into benefits. Through an analysis of the factors influencing landslide dam development and utilization, an index system (consisting of target, rule, and index layers) for evaluating development feasibility was constructed in this paper. Considering uncertainty and randomness in development feasibility evaluation, a cloud model-improved evaluation method was proposed to determine membership and score clouds based on the uncertainty reasoning of cloud model, and a cloud model-improved analytic hierarchy process (AHP-Cloud Model) was introduced to obtain weights. Final evaluation results were obtained using a hierarchical weighted summary. The improved method was applied to evaluate the Hongshiyan and Tangjiashan landslide dams and the results were compared with the maximum membership principle results. The results showed that the cloud model depicted the fuzziness and uncertainty in the evaluation process. The improved method proposed in this paper overcame the loss of fuzziness in the maximum membership principle evaluation results, and was capable of more directly presenting evaluation results. The development feasibility of the Hongshiyan landslide dam was relatively high, while that of the Tangjiashan landslide dam was relatively low. As suggested by these results, the evaluation model proposed in this paper has great significance for preparing a long-term management scheme for landslide dams.

Background As the world’s largest coal producer, China was accounted for about 46% of global coal production. Among present coal mining risks, methane gas (called gas in this paper) explosion or ignition in an underground mine remains ever-present. Although many techniques have been used, gas accidents associated with the complex elements of underground gassy mines need more robust monitoring or warning systems to identify risks. This paper aimed to determine which single method between the PCA and Entropy methods better establishes a responsive weighted indexing measurement to improve coal mining safety. Methods Qualitative and quantitative mixed research methodologies were adopted for this research, including analysis of two case studies, correlation analysis, and comparative analysis. The literature reviewed the most-used multi-criteria decision making (MCDM) methods, including subjective methods and objective methods. The advantages and disadvantages of each MCDM method were briefly discussed. One more round literature review was conducted to search publications between 2017 and 2019 in CNKI. Followed two case studies, correlation analysis and comparative analysis were then conducted. Research ethics was approved by the Shanxi Coking Coal Group Research Committee. Results The literature searched a total of 25,831publications and found that the PCA method was the predominant method adopted, and the Entropy method was the second most widely adopted method. Two weighting methods were compared using two case studies. For the comparative analysis of Case Study 1, the PCA method appeared to be more responsive than the Entropy. For Case Study 2, the Entropy method is more responsive than the PCA. As a result, both methods were adopted for different cases in the case study mine and finally deployed for user acceptance testing on 5 November 2020. Conclusions The findings and suggestions were provided as further scopes for further research. This research indicated that no single method could be adopted as the better option for establishing indexing measurement in all cases. The practical implication suggests that comparative analysis should always be conducted on each case and determine the appropriate weighting method to the relevant case. This research recommended that the PCA method was a dimension reduction technique that could be handy for identifying the critical variables or factors and effectively used in hazard, risk, and emergency assessment. The PCA method might also be well-applied for developing predicting and forecasting systems as it was sensitive to outliers. The Entropy method might be suitable for all the cases requiring the MCDM. There is also a need to conduct further research to probe the causal reasons why the PCA and Entropy methods were applied to each case and not the other way round. This research found that the Entropy method provides higher accuracy than the PCA method. This research also found that the Entropy method demonstrated to assess the weights of the higher dimension dataset was higher sensitivity than the lower dimensions. Finally, the comprehensive analysis indicates a need to explore a more responsive method for establishing a weighted indexing measurement for warning applications in hazard, risk, and emergency assessments.

Three-dimensional landscape patterns are an effective means to study the relationship between landscape pattern evolution and eco-environmental effects. This paper selects six districts in Xi’an as the study area to examine the spatial distribution characteristics of the three-dimensional architectural landscape in the city’s main urban area using three-dimensional information on the buildings in 2020 with the support of GIS. In this study, two new architectural landscape indices—landscape height variable coefficient and building rugosity index—were employed in landscape pattern analysis, whilst a system of rigorous and comprehensive three-dimensional architectural landscape metrics was established using principal component analysis. A mathematical model of weighted change of landscape metrics based on the objective weighting method was applied to carry out scale analysis of the landscape patterns. Spatial statistical analysis and spatial autocorrelation analysis were conducted to comprehensively study the differentiation of three-dimensional architectural landscape spatial patterns. The results show that the characteristic scale of the three-dimensional landscape pattern in Xi’an’s main urban area is around 8 km. Moreover, the three-dimensional landscape of the buildings in this area is spatially positively correlated, exhibiting a high degree of spatial autocorrelation whilst only showing small spatial differences. The layout of the architectural landscape pattern is disorderly and chaotic within the second ring, whilst the clustering of patch types occurs near the third ring. Moreover, the building density in the Beilin, Lianhu, and Xincheng districts is large, the building height types are rich, and the roughness of the underlying surface is high, such that these are key areas to be improved through urban renewal. The height, volume, density, morphological heterogeneity, and vertical roughness of the architectural landscape vary amongst functional areas within the study area. This paper is the first to apply the study of spatial heterogeneity of three-dimensional landscape patterns to Xi’an. It does so in order to provide a quantitative basis for urban landscape ecological design for urban renewal and the rational planning of built-up areas, which will promote the sustainable development of the city’s urban environment.

Background Pragmatic challenges remain in the monitoring and return to play (RTP) decisions following suspected Sports Related Concussion (SRC). Reliance on traditional approaches (pen and paper) means players readiness for RTP is often based on self-reported symptom recognition as a marker for full physiological recovery. Non-digital approaches also limit opportunity for robust data analysis which may hinder understanding of the interconnected nature and relationships in deficit recovery. Digital approaches may provide more objectivity to measure and monitor impairments in SRC. Crucially, there is dearth of protocols for SRC assessment and digital devices have yet to be tested concurrently (multimodal) in SRC rugby union assessment. Here we propose a multimodal protocol for digital assessment in SRC, which could be used to enhance traditional sports concussion assessment approaches. Methods We aim to use a repeated measures observational study utilising a battery of multimodal assessment tools (symptom, cognitive, visual, motor). We aim to recruit 200 rugby players (male n≈100 and female n≈100) from University Rugby Union teams and local amateur rugby clubs in the North East of England. The multimodal battery assessment used in this study will compare metrics between digital methods and against traditional assessment. Conclusion This paper outlines a protocol for a multimodal approach for the use of digital technologies to augment traditional approaches to SRC, which may better inform RTP in rugby union. Findings may shed light on new ways of working with digital tools in SRC. Multimodal approaches may enhance understanding of the interconnected nature of impairments and provide insightful, more objective assessment and RTP in SRC. Clinical trial registration NCT04938570. https://clinicaltrials.gov/ct2/results?cond=NCT04938570&term=&cntry=&state=&city=&dist=

With the increase of patients with retinopathy, retinopathy recognition has become a research hotspot. In this article, we describe the etiology and symptoms of three kinds of retinal diseases, including drusen(DRUSEN), choroidal neovascularization(CNV) and diabetic macular edema(DME). In addition, we also propose a hybrid attention mechanism to classify and recognize different types of retinopathy images. In particular, the hybrid attention mechanism proposed in this paper includes parallel spatial attention mechanism and channel attention mechanism. It can extract the key features in the channel dimension and spatial dimension of retinopathy images, and reduce the negative impact of background information on classification results. The experimental results show that the hybrid attention mechanism proposed in this paper can better assist the network to focus on extracting thr fetures of the retinopathy area and enhance the adaptability to the differences of different data sets. Finally, the hybrid attention mechanism achieved 96.5% and 99.76% classification accuracy on two public OCT data sets of retinopathy, respectively.

In this paper, the algebraic topological characteristics of brain networks composed of electroencephalogram(EEG) signals induced by different quality images were studied, and on that basis, a neurophysiological image quality assessment approach was proposed. Our approach acquired quality perception-related neural information via integrating the EEG collection with conventional image assessment procedures, and the physiologically meaningful brain responses to different distortion-level images were obtained by topological data analysis. According to the validation experiment results, statistically significant discrepancies of the algebraic topological characteristics of EEG data evoked by a clear image compared to that of an unclear image are observed in several frequency bands, especially in the beta band. Furthermore, the phase transition difference of brain network caused by JPEG compression is more significant, indicating that humans are more sensitive to JPEG compression other than Gaussian blur. In general, the algebraic topological characteristics of EEG signals evoked by distorted images were investigated in this paper, which contributes to the study of neurophysiological assessment of image quality.

An unbiased, widely accepted estimate of the rate of occurrence of new cases of autism over time would facilitate progress in understanding the causes of autism. The same may also apply to other disorders. While incidence is a widely used measure of occurrence, birth prevalence—the proportion of each birth year cohort with the disorder—is the appropriate measure for disorders and diseases of early childhood. Studies of autism epidemiology commonly speculate that estimates showing strong increases in rate of autism cases result from an increase in diagnosis rates rather than a true increase in cases. Unfortunately, current methods are not sufficient to provide a definitive resolution to this controversy. Prominent experts have written that it is virtually impossible to solve.This paper presents a novel method, time-to-event birth prevalence estimation (TTEPE), to provide accurate estimates of birth prevalence properly adjusted for changing diagnostic factors. It addresses the shortcomings of prior methods. TTEPE is based on well-known time-to-event (survival) analysis techniques. A discrete survival process models the rates of incident diagnoses by birth year and age. Diagnostic factors drive the probability of diagnosis as a function of the year of diagnosis. TTEPE models changes in diagnostic criteria, which can modify the effective birth prevalence when new criteria take effect. TTEPE incorporates the development of diagnosable symptoms with age. General-purpose optimization software estimates all parameters, forming a non-linear regression. The paper specifies all assumptions underlying the analysis and explores potential deviations from assumptions and optional additional analyses.A simulation study shows that TTEPE produces accurate parameter estimates, including trends in both birth prevalence and the probability of diagnosis in the presence of sampling effects from finite populations. TTEPE provides high power to resolve small differences in parameter values by utilizing all available data points.

Background Self-management is a promising approach to improve quality of life after stroke. However, evidence for the appropriateness and effectiveness of self-management for stroke survivors with aphasia is limited. This article reports on the process used to develop a supported self-management intervention for stroke survivors with aphasia (SSWA) using co-production and behaviour change theory. Preparatory research included systematic reviews, and qualitative interviews and focus groups with SSWA, family members and speech and language therapists (SLTs). Materials and methods We conducted six, 2 hour long intervention development workshops with key stakeholders. The workshops were informed by principles of co-production and the intervention development process outlined by the Behaviour Change Wheel (BCW). We also incorporated the findings of our preparatory research within workshops. Each workshop included an introduction, 1–2 co-production tasks and time for feedback at the end of the session. Data were analysed on an ongoing basis so that findings could be used to feed in to subsequent workshops and intervention development. Results Workshop participants (n = 12) included; SSWA (n = 5), family members (n = 3) and SLTs (n = 4). Together, participants engaged with accessible and participatory co-production tasks which aligned with the BCW framework. Participants engaged in discussion to define self-management in behavioural terms (behavioural diagnosis) and to identify what needed to change to support self-management. Participant’s co-produced solutions for supporting self-management and discussed options to implement these in practice. Prototype materials were generated by the research team and evaluated by participants. Intervention functions and behaviour change techniques (BCTs) were mapped to the solutions generated by participants by the research team, after the final workshop. A supported self-management intervention for SSWA was developed which will be delivered by SLTs through community stroke services. Conclusions This paper reports the process we used to integrate co-production work with behaviour change theory to develop a complex self-management intervention. This is of relevance for researchers looking to harness the strengths of co-production methods and theory in intervention design. Future research will feasibility test the supported self-management intervention developed. This paper provides transparency to our intervention development process which will help others to better interpret the findings of our feasibility work.

The objective of the paper is to diagnose organisational culture of selected universities and analyse its impact on the innovation processes within them. The subject matter of the study was organisational culture and innovation at universities. The subjects were four selected universities in Poland, Austria, Germany, and Ukraine. The paper provided a definition of organisational culture and its typology. It further discussed the organisational culture of universities and the relationships between organisational culture and innovativeness. The literature review provided foundations for building a model for the formation of a type of organisational culture at universities that is innovation-friendly, which is the added value of the paper. It offers actions worth taking to shape innovation-friendly culture at universities. It is particularly important during difficult time of changing labour market, when universities greatly impact the attitudes of young people. The knowledge of how to shape innovation-friendly organisational culture at universities is necessary for academia to profile future employees in times of continuous changes. To investigate the relationship between organisational culture and the innovativeness of universities, we designed an original survey questionnaire [S1 File]. Organisational culture was diagnosed with the Organizational Culture Assessment Instrument by K.S. Cameron and R.E. Quinn. The analyses were conducted in Dell Statistica v. 13.1 (StatSoft Polska). We normalised data from the Likert rating scale using Kaufman’s and Rousseeuw’s formula. We used Spearman’s correlation coefficient and Kendall’s W to calculate correlations. The research shows that the investigated Polish and Austrian universities are dominated by hierarchy and market cultures. On the other hand, the German and Ukrainian universities host all cultures, but clan and adhocracy dominate there. Moreover, the analyses demonstrated that although the adhocracy culture was the least visible in the investigated organisations, it contributes to university innovativeness the most. The conclusions were used to build a model for promoting innovation-friendly organisational culture at universities. The model contains answers to the research questions. In addition, it offers guidelines for shaping organisational culture to bolster innovation at universities. The research identified relationships between organisational culture and university innovativeness and components that create innovation opportunities at universities as its contribution to management theory. When applied in practice, the guidelines can help form the university’s organisational culture bottom-up.

Selecting a target journal is a universal decision faced by authors of scientific papers. Components of the decision, including expected turnaround time, journal acceptance rate, and journal impact factor, vary in terms of accessibility. In this study, I collated recent turnaround times and impact factors for 82 journals that publish papers in the field of fisheries sciences. In addition, I gathered acceptance rates for the same journals when possible. Findings indicated clear among-journal differences in turnaround time, with median times-to-publication ranging from 79 to 323 days. There was no clear correlation between turnaround time and acceptance rate nor between turnaround time and impact factor; however, acceptance rate and impact factor were negatively correlated. I found no field-wide differences in turnaround time since the beginning of the COVID-19 pandemic, though some individual journals took significantly longer or significantly shorter to publish during the pandemic. Depending on their priorities, authors choosing a target journal should use the results of this study as guidance toward a more informed decision.

The purpose of this paper is to analyse the global Sales and Operations Planning (S&OP) process and investigate the steps to support consolidated business planning in worldwide operations and large-scale supply chains. The paper conducts a case study at a multinational manufacturing company applying an abductive approach. It combines the deductive logic from theory and the inductive logic from field observation in an attempt to elaborate further on theory on global S&OP. The analysis is structured and guided by a novel framework for global S&OP, which is developed based on the theoretical background and the case study findings. The research findings characterise the S&OP process for global operations and identify challenges related to the need to synchronise the subsidiaries’ S&OP efforts worldwide to deal with different contingencies of these subsidiaries, and to manage and analyse a large amount of information gathered. The research reveals how the subsidiaries’ performance is analysed by top executives along the global S&OP process, feeding strategic initiatives in the organisation and identifying business opportunities like benchmarking among subsidiaries, synergies with other management practices, and global gains. This paper offers a novel investigation of the global steps on S&OP in a real-life setting, offering a well-documented characterisation of the process that goes beyond the traditional local approach. Moreover, it is the first study to reveal challenges and expected outcomes of such a global perspective for S&OP. The theoretical advancements of S&OP research offered herein aid scholars, opening avenues for middle-range theorising, highlighting the cross-disciplinary nature of the domain, and discussing the use of concepts from related disciplines like Economics, Psychology, and Information Systems. The research findings can also assist executives, especially from multinational manufacturers, in their efforts to consolidate global planning.

Fake news is a complex problem that leads to different approaches used to identify them. In our paper, we focus on identifying fake news using its content. The used dataset containing fake and real news was pre-processed using syntactic analysis. Dependency grammar methods were used for the sentences of the dataset and based on them the importance of each word within the sentence was determined. This information about the importance of words in sentences was utilized to create the input vectors for classifications. The paper aims to find out whether it is possible to use the dependency grammar to improve the classification of fake news. We compared these methods with the TfIdf method. The results show that it is possible to use the dependency grammar information with acceptable accuracy for the classification of fake news. An important finding is that the dependency grammar can improve existing techniques. We have improved the traditional TfIdf technique in our experiment.

In the case of a fire, the choice of exit in the highway tunnel is strictly limited by fire location, which seriously affects the evacuation time. A spontaneous or disorderly exit choice might result in a decreased evacuation efficiency and utilization rate of exits. In this paper, we propose a strategy to obtain the optimal exit choice based on fire location during highway tunnel evacuations. In our strategy, first, the vehicle distributions and locations of evacuating occupants are determined in the traffic simulation program VISSIM. The evacuation simulation software BuildingEXODUS is employed to obtain the corresponding parameters of the evacuation process and analyze the impacts of different fire locations on the evacuation time. During the analysis, the optimal productivity statistics (OPS) is selected as the evaluation index. Then, the feature points of the crowding occupants are captured by the fuzzy c-means (FCM) cluster algorithm. Next, based on the feature points, the relationship between the location of the fire and boundary of the optimal exit choice under the optimal OPS is obtained through the polynomial regression model. It is found that the R-squared(R2) and sum of squares for error (SSE) of the polynomial regression model, reflecting the accuracy estimation, are 98.02% and 2.79×10−4, respectively. Moreover, different fire locations impact the evacuation time of tunnel entrance and evacuation passageway. This paper shows that the location of the fire and boundary of optimal exit choice have a negative linear correlation. Taking the fire 110 m away from the evacuation passageway as an example, the OPS of our strategy can be decreased by 35.6% when compared with no strategies. Our proposed strategy could be applied to determine the location of variable evacuation signs to help evacuating occupants make optimal exit choices.

Drowning is a global public health problem, but accurately estimating drowning risk remains a challenge. Coastal drowning comprises a significant proportion of the drowning burden in Australia and is influenced by a range of behavioural factors (e.g. risk perception, knowledge, attitudes and behaviours) that are poorly understood. These factors, along with those that impact exposure (e.g. coastal visitation and activity participation) all impact on drowning risk. While excellent mortality and morbidity data exists in Australia, a lack of coastal participation data presents challenges to identifying high-risk groups or activities and prioritising prevention efforts. This methods paper describes the development and evolution of an ongoing, annual, nationally representative online survey as an effective tool used to capture valuable data about the Australian population’s relationship with the coast. This paper explores how the survey is structured (12–14 sections spanning multiple topics and themes), the different question types used (including open text, 4-digit responses and categorical questions), the sample size (1400–1600 respondents), sampling strategy (using demographic quota sampling which can then be post-weighted to the population if required) and how topics and themes have changed over time to enhance the quality of data collected (i.e., wording changes to enhance participant comprehension or data usability and changing issue-specific ‘feature’ topics of interest such as campaign evaluation). How the survey is implemented online is described, both practically through to third-party recruitment processes and ethically to maximise anonymity of respondents and ensure data quality. Interim analyses indicate the impact of considering exposure when calculating fatal drowning rates, especially by activity (e.g., crude boating drowning rate 0.12 per 100,000 population vs 0.95 per 100,000 exposed population [relative risk = 8.01; 95% confidence interval: 4.55–14.10]). This study highlights lessons learned in the process of conducting a nationally representative coastal participation survey as well as the strengths and limitations of adopting this approach. Data collected will provide more detailed information on the skills, behaviours, knowledge and attitudes of coastal activity participants. Analyses of this unique dataset will inform research that will underpin development and evaluation of coastal drowning prevention initiatives prioritising those most at risk. It is hoped that the methods detailed within this study may be useful for other countries to develop similar approaches to understanding their own population.

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.

Eggs contain the essential cholesterol and protein for the human body, which plays an irreplaceable role in human survival, production and life. There are significant differences in the development of laying hens feeding in different regions. It is of great significance to improve egg production and reduce pollution emission for China’s laying hens industry. Based on the SBM model, this paper constructs MML index, considering unexpected output under common frontier, to comprehensively evaluate the green total factor productivity on Chinese laying hens (GTCL). The results show that: (1) GTCL shows a large spatial and temporal differentiation under both the common frontier and the regional frontier. Compared with the eastern region and central region, the western region has obvious advantages in GTCL. (2) GTCL overall shows a downward trend, however, it emerges an upward trend in recent years. (3) Compared with small-scale and large-scale, middle-scale GTCL has advantages. According to the above empirical results, combined with the China’s actual national situation, this paper finally puts forward some policy recommendations to improve GTCL.

Peer-to-Peer (P2P) lending provides convenient and efficient financing channels for small and medium-sized enterprises and individuals, and therefore it has developed rapidly since entering the market. However, due to the imperfection of the credit system and the influence of cyberspace restrictions, P2P network lending faces frequent borrower credit risk crises during the transaction process, with a high proportion of borrowers default. This paper first analyzes the basic development of China’s P2P online lending and the credit risks of borrowers in the industry. Then according to the characteristics of P2P network lending and previous studies, a credit risk assessment indicators system for borrowers in P2P lending is formulated with 29 indicators. Finally, on the basis of the credit risk assessment indicators system constructed in this paper, BP neural network is built based on the BP algorithm, which is trained by the LM algorithm (Levenberg-Marquardt), Scaled Conjugate Gradient, and Bayesian Regularization respectively, to complete the credit risk assessment model. By comparing the results of three mentioned training methodologies, the BP neural network trained by the LM algorithm is finally adopted to construct the credit risk assessment model of borrowers in P2P lending, in which the input layer node is 9, the hidden layer node is 11 and output layer node is 1. The model can provide practical guidance for China and other countries’ P2P lending platforms, and therefore to establish and improve an accurate and effective borrower credit risk management system.

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.

Supply chain integration plays an important role in the development of the vegetable industry in terms of vegetable quality, vegetable safety, and vegetable security in rural China. This paper explores how agricultural cooperatives integrate the vegetable supply chain by taking a trinity cooperative as an example in China. It explains the translation concatenation of supply chain integration for this cooperative by constructing actor networks in four development stages, including the seed stage, start-up stage, development stage, and mature stage. The findings show that supply chain integration in production cooperation, supply & sales cooperation, and credit cooperation is a useful trinity cooperative model of supply chain integration for investigating vegetable supply chain integration through internal integration and external integration. This paper suggests that cooperatives in the vegetable supply chain should facilitate close coordination among different shareholders and further improve the efficiency of supply chain integration. The government should provide training opportunities and funding to encourage cooperatives to participate in supply chain integration within the vegetable industry.

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.

In this paper the author proposes an approach in the form of an active wave generator for ground surface vibration reduction. The idea is compared to classic and innovative vibration mitigation techniques. The solution is mainly addressed to prevent people and structures against the destructive effects of anthropogenic vibrations. The efficiency of the presented idea is verified in the paper for two types of excitation–harmonic and impact loads, for points located on the ground surface and below it. The vibration reduction effect for structures is presented in the paper in the case of a three-story building. The advantages and disadvantages of the presented solutions are summarized. Moreover, this paper presents a wide and up-to-date literature review on the vibration control of the ground surface. Classical well-known technologies in the form of ground obstacles are compared with innovative ideas such as metamaterials.

Scaling is a ubiquitous concept in agricultural research in the global south as donors require their research grantees to prove that their results can be scaled to impact upon the livelihoods of a large number of beneficiaries. Recent studies on scaling have brought critical perspectives to the rather technocratic tendencies in the agricultural innovations scaling literature. Drawing on theoretical debates on spatial strategies and practical experience of agricultural innovation scaling in Ethiopia, this paper adds to the current debate on what constitutes scaling and how to overcome critical scaling constraints. The data for the paper came from a qualitative assessment using focus group discussions, key informant interviews, and document analysis on scaling work done in Ethiopia by a USAID-funded research for development project. The paper concludes with four broad lessons for the current understating of agricultural innovation scaling. First, scaling of agricultural innovations requires a balanced focus on technical requirements and associated social dynamics surrounding scaling targets, actors involved and their social relations. Second, appreciating the social dynamics of scaling emphasizes the fact that scaling is more complex than a linear rolling out of innovations towards diffusion. Third, scaling may not be strictly planned; instead, it might be an extension of the innovation generation process that relies heavily on both new and long-term relationships with key partners, trust, and continuous reflection and learning. Fourth, the overall implication of the above three conclusions is that scaling strategies need to be flexible, stepwise, and reflective. Despite the promises of flourishing scaling frameworks, scaling strategies it would appear from the Africa RISING experience that, if real impact is to be achieved, approaches will be required to be flexible enough to manage the social, processual and emergent nature of the practice of scaling.

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.