Search

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. [ABSTRACT FROM AUTHOR]

Classifying bank accounts by using transaction data is encouraging in cracking down on illegal financial activities. However, few research simultaneously use heterogenous features, which are embedded in the time series data. In this paper, a two route convolution neural network TRHD-CNN model, fed with two types of heterogeneous feature matrices, is proposed for classifying the bank accounts. TRHD-CNN adopts divide and conquer strategy to extract characteristics from two types of data source independently. The strategy is proved able in mining complementary classification characteristics. We firstly transfer the original log data into a directed and dynamic transaction network. On the basis of that, two feature generation methods are devised for extracting information from local topological structure and time series transaction respectively. A DirectedWalk method is developed in this paper to learning the network vector of vertices used for embedding the neighbor relationship of bank account. The extensive experimental results, conducted on a real bank transaction dataset that contains illegal pyramid selling accounts, show the significant advantage of TRHD-CNN over the existing methods. TRHD-CNN can provide recall scores up to 5.15% higher than competing methods. In addition, the two-route architecture of TRHD-CNN is easy to extend to multi-route scenarios and other fields. [ABSTRACT FROM AUTHOR]

Physical inactivity has been identified as a leading risk factor for premature mortality globally, and adolescents, in particular, have low physical activity levels. Schools have been identified as a setting to tackle physical inactivity. Economic evidence of school-based physical activity programmes is limited, and the costs of these programmes are not always collected in full. This paper describes a micro-costing and cost-consequence analysis of the ‘Girls Active’ secondary school-based programme as part of a cluster randomised controlled trial (RCT). Micro-costing and cost-consequence analyses were conducted using bespoke cost diaries and questionnaires to collect programme delivery information. Outcomes for the cost-consequence analysis included health-related quality of life measured by the Child Health Utility-9D (CHU-9D), primary care General Practitioner (GP) and school-based (school nurse and school counsellor) service use as part of a cluster RCT of the ‘Girls Active’ programme. Overall, 1,752 secondary pupils were recruited and a complete case sample of 997 participants (Intervention n = 570, Control n = 427) was used for the cost-consequence analysis. The micro-costing analysis demonstrated that, depending upon how the programme was delivered, ‘Girls Active’ costs ranged from £1,054 (£2 per pupil, per school year) to £3,489 (£7 per pupil, per school year). The least costly option was to absorb ‘Girls Active’ strictly within curriculum hours. The analysis demonstrated no effect for the programme for the three main outcomes of interest (health-related quality of life, physical activity and service use).Micro-costing analyses demonstrated the costs of delivering the ‘Girls Active’ programme, addressing a gap in the United Kingdom (UK) literature regarding economic evidence from school-based physical activity programmes. This paper provides recommendations for those gathering cost and service use data in school settings to supplement validated and objective measures, furthering economic research in this field. Trial registration: -ISRCTN, . [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Determining the distribution of the Yangtze finless porpoise (Neophocaena asiaeorientalis asiaeorientalis, YFP) in the Yangtze River has to date relied on traditional visual and counting methods, but such field surveys are time-consuming and expensive. Analyses using environmental DNA (eDNA) to investigate the presence and range of endangered aquatic species have proven to be more economical and effective detection methods, and are a non-invasive approach to sampling. A challenge of relying on eDNA for YFP monitoring is that the Yangtze River is characterized by high turbidity and a strong current. Here, we used an eDNA-based approach to estimate the presence of YFP at 18 sites in the Yangtze River in August 2017 and at an additional 11 sites in January 2018. At each sampling site, we filtered six 1 L water samples with 5 µm pore size filter paper and quantified the amount of YFP eDNA in each water sample using quantitative real-time polymerase chain reaction (qPCR). In addition, YFP eDNA was successfully detected in locations where we visually observed YFP, as well as in locations where YFP were not observed directly. We found that our eDNA-based method had higher detection rates than traditional field survey methods. Although YFP was visually observed in the Yangtze River in winter, water samples collected during the summer contained significantly higher YFP eDNA than winter water samples. Our results demonstrate the potential effectiveness of eDNA detection methods in determining the distribution of YFP in the Yangtze River. [ABSTRACT FROM AUTHOR]

The use of elasticities of substitution between inputs is a standard method for addressing the effect of a change in the mix of inputs used for production from a technical or cost standpoint. Most estimation methods use parametric production or cost functions or frontiers to estimate these elasticities. A potentially useful nonparametric alternative is data envelopment analysis (DEA). The purpose of this paper is to derive elasticities of input substitution for both technical and cost frontiers using DEA, extending the use of this approach in the field of economics and associated fields. The paper provides derivations for both Hicksian (production and cost frontier) and Morishima (cost frontier) elasticities of input substitution, as well as a parsimonious method for estimating them using DEA. The derivations are presented using an agricultural example form Kansas, USA. [ABSTRACT FROM AUTHOR]

Background: Floating catchment methods have recently been applied to identify priority regions for Automated External Defibrillator (AED) deployment, to aid in improving Out of Hospital Cardiac Arrest (OHCA) survival. This approach models access as a supply-to-demand ratio for each area, targeting areas with high demand and low supply for AED placement. These methods incorporate spatial covariates on OHCA occurrence, but do not provide precise AED locations, which are critical to the initial intent of such location analysis research. Exact AED locations can be determined using optimisation methods, but they do not incorporate known spatial risk factors for OHCA, such as income and demographics. Combining these two approaches would evaluate AED placement impact, describe drivers of OHCA occurrence, and identify areas that may not be appropriately covered by AED placement strategies. There are two aims in this paper. First, to develop geospatial models of OHCA that account for and display uncertainty. Second, to evaluate the AED placement methods using geospatial models of accessibility. We first identify communities with the greatest gap between demand and supply for allocating AEDs. We then use this information to evaluate models for precise AED location deployment. Methods: Case study data set consisted of 2802 OHCA events and 719 AEDs. Spatial OHCA occurrence was described using a geospatial model, with possible spatial correlation accommodated by introducing a conditional autoregressive (CAR) prior on the municipality-level spatial random effect. This model was fit with Integrated Nested Laplacian Approximation (INLA), using covariates for population density, proportion male, proportion over 65 years, financial strength, and the proportion of land used for transport, commercial, buildings, recreation, and urban areas. Optimisation methods for AED locations were applied to find the top 100 AED placement locations. AED access was calculated for current access and 100 AED placements. Priority rankings were then given for each area based on their access score and predicted number of OHCA events. Results: Of the 2802 OHCA events, 64.28% occurred in rural areas, and 35.72% in urban areas. Additionally, over 70% of individuals were aged over 65. Supply of AEDs was less than demand in most areas. Priority regions for AED placement were identified, and access scores were evaluated for AED placement methodology by ranking the access scores and the predicted OHCA count. AED placement methodology placed AEDs in areas with the highest priority, but placed more AEDs in areas with more predicted OHCA events in each grid cell. Conclusion: The methods in this paper incorporate OHCA spatial risk factors and OHCA coverage to identify spatial regions most in need of resources. These methods can be used to help understand how AED allocation methods affect OHCA accessibility, which is of significant practical value for communities when deciding AED placements. [ABSTRACT FROM AUTHOR]

Objectives: Little 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. Methods: We 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. Results: Our 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. Conclusions: Overall, we found that the economic fluctuations caused increased harmful effects in certain population subgroups but also brought some soothing effects to some groups. [ABSTRACT FROM AUTHOR]

Rationale, aims and objective: Substituting outpatient hospital care with primary care is seen as a solution to decrease unnecessary referrals to outpatient hospital care and decrease rising healthcare costs. This systematic review aimed to evaluate the effects on quality of care, health and costs outcomes of substituting outpatient hospital care with primary care-based interventions, which are performed by medical specialists in face-to-face consultations in a primary care setting. Method: The systematic review was performed using the PICO framework. Original papers in which the premise of the intervention was to substitute outpatient hospital care with primary care through the involvement of a medical specialist in a primary care setting were eligible. Results: A total of 14 papers were included. A substitution intervention in general practitioner (GP) practices was described in 11 papers, three described a joint consultation intervention in which GPs see patients together with a medical specialist. This study showed that substitution initiatives result mostly in favourable outcomes compared to outpatient hospital care. The initiatives resulted mostly in shorter waiting lists, shorter clinic waiting times and higher patient satisfaction. Costs for treating one extra patient seemed to be higher in the intervention settings. This was mainly caused by inefficient planning of consultation hours and lower patient numbers. Conclusions: Despite the fact that internationally a lot has been written about the importance of performing substitution interventions in which preventing unnecessary referrals to outpatient hospital care was the aim, only 14 papers were included. Future systematic reviews should focus on the effects on the Triple Aim of substitution initiatives in which other healthcare professions than medical specialists are involved along with new technologies, such as e-consults. Additionally, to gain more insight into the effects of substitution initiatives operating in a dynamic healthcare context, it is important to keep evaluating the interventions in a longitudinal study design. [ABSTRACT FROM AUTHOR]

Open access publication rates have been steadily increasing over time. In spite of this growth, academics in low income settings struggle to gain access to the full canon of research literature. While the vast majority of open access repositories and funding organizations with open access policies are based in high income countries, the geographic patterns of open access publication itself are not well characterized. In this study, we developed a computational approach to better understand the topical and geographical landscape of open access publications in the biomedical research literature. Surprisingly, we found a strong negative correlation between country per capita income and the percentage of open access publication. Open access publication rates were particularly high in sub-Saharan Africa, but vastly lower in the Middle East and North Africa, South Asia, and East Asia and the Pacific. These effects persisted when considering papers only bearing authors from within each region and income group. However, papers resulting from international collaborations did have a higher percentage of OA than single-country papers, and inter-regional collaboration increased OA publication for all world regions. There was no clear relationship between the number of open access policies in a region and the percentage of open access publications in that region. To understand the distribution of open access across topics of biomedical research, we examined keywords that were most enriched and depleted in open access papers. Keywords related to genomics, computational biology, animal models, and infectious disease were enriched in open access publications, while keywords related to the environment, nursing, and surgery were depleted in open access publications. This work identifies geographic regions and fields of research that could be priority areas for open access advocacy. The finding that open access publication rates are highest in sub-Saharan Africa and low income countries suggests that factors other than open access policy strongly influence authors’ decisions to make their work openly accessible. The high proportion of OA resulting from international collaborations indicates yet another benefit of collaborative research. Certain applied fields of medical research, notably nursing, surgery, and environmental fields, appear to have a greater proportion of fee-for-access publications, which presumably creates barriers that prevent researchers and practitioners in low income settings from accessing the literature in those fields. [ABSTRACT FROM AUTHOR]

Executives act based on their experiences, values, personality and personal interpretation of the situations which they face in their companies. Investigations in the field of Behavioral Corporate Finance have determined that there are some relations between CEOs’ personal traits and financial decisions of large companies, but these results are based on indirect personal trait measurements and on public companies. To see whether such relations also exist between CEOs’ personal traits and the financial structure of large private companies, we used psychometric tests to measure their level of optimism, risk attitude and affect heuristic, collected financial data for a period of fourteen years, and considered the economic situation of the country as a key factor in these relations. This paper reports the relationship of executives’ personal traits with the financial structure of large Spanish companies for the period 2001–2014. We observed that executives’ high optimism (and risk aversion attitude) is positively (negatively) related to long-term debt, whilst positive affect is directly associated to the financial leverage and short-term debt. This paper also reports a change of relations when taking into account the country’s economic situation. In effect, by considering this new variable, executives’ risk aversion is seen to be associated to financial leverage and short-term debt, whilst CEOs’ positive affect is linked to long-term debt. These relations are strongly moderated and they become statistically significant in a contracting economic period. In conclusion, the links between CEOs’ personal traits and financial structure of large private Spanish companies make sense when the effect of the economic situation is taken into account. Furthermore, the awareness of these links helps to understand the financial decisions taken within large Spanish companies. [ABSTRACT FROM AUTHOR]

Background: Detection of pulmonary nodules is an important aspect of an automatic detection system. Incomputer-aided diagnosis (CAD) systems, the ability to detect pulmonary nodules is highly important, which plays an important role in the diagnosis and early treatment of lung cancer. Currently, the detection of pulmonary nodules depends mainly on doctor experience, which varies. This paper aims to address the challenge of pulmonary nodule detection more effectively. Methods: A method for detecting pulmonary nodules based on an improved neural network is presented in this paper. Nodules are clusters of tissue with a diameter of 3 mm to 30 mm in the pulmonary parenchyma. Because pulmonary nodules are similar to other lung structures and have a low density, false positive nodules often occur. Thus, our team proposed an improved convolutional neural network (CNN) framework to detect nodules. First, a nonsharpening mask is used to enhance the nodules in computed tomography (CT) images; then, CT images of 512×512 pixels are segmented into smaller images of 96×96 pixels. Second, in the 96×96 pixel images which contain or exclude pulmonary nodules, the plaques corresponding to positive and negative samples are segmented. Third, CT images segmented into 96×96 pixels are down-sampled to 64×64 and 32×32 size respectively. Fourth, an improved fusion neural network structure is constructed that consists of three three-dimensional convolutional neural networks, designated as CNN-1, CNN-2, and CNN-3, to detect false positive pulmonary nodules. The networks’ input sizes are 32×32×32, 64×64×64, and 96×96×96 and include 5, 7, and 9 layers, respectively. Finally, we use the AdaBoost classifier to fuse the results of CNN-1, CNN-2, and CNN-3. We call this new neural network framework the Amalgamated-Convolutional Neural Network (A-CNN) and use it to detect pulmonary nodules. Findings: Our team trained A-CNN using the LUNA16 and Ali Tianchi datasets and evaluated its performance using the LUNA16 dataset. We discarded nodules less than 5mm in diameter. When the average number of false positives per scan was 0.125 and 0.25, the sensitivity of A-CNN reached as high as 81.7% and 85.1%, respectively. [ABSTRACT FROM AUTHOR]

In recent years there has been increased attention to child neurodevelopment in studies on medication safety in pregnancy. Neurodevelopment is a multifactorial outcome that can be assessed by various assessors, using different measures. This has given rise to a debate on the validity of various measures of neurodevelopment. The aim of this review was twofold. Firstly we aimed to give an overview of studies on child neurodevelopment after prenatal exposure to central nervous system acting medications using psychotropics and analgesics as examples, giving special focus on the use and validity of outcome measures. Secondly, we aimed to give guidance on how to conduct and interpret medication safety studies with neurodevelopment outcomes. We conducted a systematic review in the MEDLINE, Embase, PsycINFO, Web of Science, Scopus, and Cochrane databases from inception to April 2019, including controlled studies on prenatal exposure to psychotropics or analgesics and child neurodevelopment, measured with standardised psychometric instruments or by diagnosis of neurodevelopmental disorder. The review management tool Covidence was used for data-extraction. Outcomes were grouped as motor skills, cognition, behaviour, emotionality, or “other”. We identified 110 eligible papers (psychotropics, 82 papers, analgesics, 29 papers). A variety of neurodevelopmental outcome measures were used, including 27 different psychometric instruments administered by health care professionals, 15 different instruments completed by parents, and 13 different diagnostic categories. In 23 papers, no comments were made on the validity of the outcome measure. In conclusion, establishing neurodevelopmental safety includes assessing a wide variety of outcomes important for the child’s daily functioning including motor skills, cognition, behaviour, and emotionality, with valid and reliable measures from infancy through to adolescence. Consensus is needed in the scientific community on how neurodevelopment should be assessed in medication safety in pregnancy studies. Review registration number: CRD42018086101 in the PROSPERO database. [ABSTRACT FROM AUTHOR]

In epidemiology, gerontology, human development and the social sciences, age-period-cohort (APC) models are used to study the variability in trajectories of change over time. A well-known issue exists in simultaneously identifying age, period and birth cohort effects, namely that the three characteristics comprise a perfectly collinear system. That is, since age = period−cohort, only two of these effects are estimable at a time. In this paper, we introduce an alternative framework for considering effects relating to age, period and birth cohort. In particular, instead of directly modeling age in the presence of period and cohort effects, we propose a risk modeling approach to characterize age-related risk (i.e., a hybrid of multiple biological and sociological influences to evaluate phenomena associated with growing older). The properties of this approach, termed risk-period-cohort (RPC), are described in this paper and studied by simulations. We show that, except for pathological circumstances where risk is uniquely determined by age, using such risk indices obviates the problem of collinearity. We also show that the size of the chronological age effect in the risk prediction model associates with the correlation between a risk index and chronological age and that the RPC approach can satisfactorily recover cohort and period effects in most cases. We illustrate the advantages of RPC compared to traditional APC analysis on 27496 individuals from NHANES survey data (2005–2016) to study the longitudinal variability in depression screening over time. Our RPC method has broad implications for examining processes of change over time in longitudinal studies. [ABSTRACT FROM AUTHOR]

Objectives: The main purpose of this paper was to model the process by which patients enter the ED, are seen by physicians, and discharged from the Emergency Department at Nationwide Children’s Hospital, as well as identify modifiable factors that are associated with ED lengths of stay through use of multistate modeling. Methods: In this study, 75,591 patients admitted to the ED from March 1st, 2016 to February 28th, 2017 were analyzed using a multistate model of the ED process. Cox proportional hazards models with transition-specific covariates were used to model each transition in the multistate model and the Aalen-Johansen estimator was used to obtain transition probabilities and state occupation probabilities in the ED process. Results: Acuity level, season, time of day and number of ED physicians had significant and varying associations with the six transitions in the multistate model. Race and ethnicity were significantly associated with transition to left without being seen, but not with the other transitions. Conversely, age and gender were significantly associated with registration to room and subsequent transitions in the model, though the magnitude of association was not strong. Conclusions: The multistate model presented in this paper decomposes the overall ED length of stay into constituent transitions for modeling covariate-specific effects on each transition. This allows physicians to understand the ED process and identify which potentially modifiable covariates would have the greatest impact on reducing the waiting times in each state in the model. [ABSTRACT FROM AUTHOR]

Spots of blood are routinely collected from newborn babies onto filter paper called Guthrie cards and used to screen for metabolic and genetic disorders. The archived dried blood spots are an important and precious resource for genomic research. Whole genome amplification of dried blood spot DNA has been used to provide DNA for genome-wide SNP genotyping. Here we describe a 96 well format procedure to extract DNA from a portion of a dried blood spot that provides sufficient unamplified genomic DNA for genome-wide single nucleotide polymorphism (SNP) genotyping. We show that SNP genotyping of the unamplified DNA is more robust than genotyping amplified dried blood spot DNA, is comparable in cost, and can be done with thousands of samples. This procedure can be used for genome-wide association studies and other large-scale genomic analyses that require robust, high-accuracy genotyping of dried blood spot DNA. [ABSTRACT FROM AUTHOR]

The repellent and contact toxicities of Alpinia officinarum rhizome extract on Lasioderma serricorne adults, and its ability to protect stored wheat flour from L. serricorne adults infestation were investigated. The A. officinarum extract exhibited strong repellent and contact toxicities against L. serricorne adults. The toxicities enhanced significantly with the increasing treatment time and treatment dose. The mean percentage repellency value reached 91.3% at class V at the dose of 0.20 μL/cm2 after 48 h of exposure. The corrected mortality reached over 80.0% at the dose of 0.16 μL/cm2 after 48 h of exposure. The A. officinarum extract could significantly reduce L. serricorne infestation level against stored wheat flour. Particularly, the insect infestation was nil in wheat flour packaged with kraft paper bags coated with the A. officinarum extract at the dose of above 0.05 μL/cm2. The naturally occurring A. officinarum extract could be useful for integrated management of L. serricorne. [ABSTRACT FROM AUTHOR]

Background: Paper mulberry has been used for thousands of years in Asia and Oceania for making paper and bark-cloth, respectively. Museums around the world hold valuable collections of Polynesian bark-cloth. Genetic analysis of the plant fibers from which the textiles were made may answer a number of questions of interest related to provenance, authenticity or species used in the manufacture of these textiles. Recovery of nucleic acids from paper mulberry bark-cloth has not been reported before. Methodology: We describe a simple method for the extraction of PCR-amplifiable DNA from small samples of contemporary Polynesian bark-cloth (tapa) using two types of nuclear markers. We report the amplification of about 300 bp sequences of the ITS1 region and of a microsatellite marker. Conclusions: Sufficient DNA was retrieved from all bark-cloth samples to permit successful PCR amplification. This method shows a means of obtaining useful genetic information from modern bark-cloth samples and opens perspectives for the analyses of small fragments derived from ethnographic materials. [ABSTRACT FROM AUTHOR]

Although interdisciplinarity is often touted as a necessity for modern research, the evidence on the relative impact of sectorial versus to interdisciplinary science is qualitative at best. In this paper we leverage the bibliographic data set of the American Physical Society to quantify the role of interdisciplinarity in physics, and that of talent and luck in achieving success in scientific careers. We analyze a period of 30 years (1980-2009) tagging papers and their authors by means of the Physics and Astronomy Classification Scheme (PACS), to show that some degree of interdisciplinarity is quite helpful to reach success, measured as a proxy of either the number of articles or the citations score. We also propose an agent-based model of the publication-reputation-citation dynamics which reproduces the trends observed in the APS data set. On the one hand, the results highlight the crucial role of randomness and serendipity in real scientific research; on the other, they shed light on a counterintuitive effect indicating that the most talented authors are not necessarily the most successful ones. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Aiming at serving the interdisciplinary demand in network science, this paper introduces a new concept for complex networks, named network stiffness, which is extracted from structural engineering by assuming that a complex network behaves similarly with a structured framework. This analogy allows interpreting that a complex network can resist against any cause attempting to induce deformation changes to the network’s structure, regardless of whether the network is material or not. Within this framework, this paper examines the context of applying the conceptual analogy of stiffness from the field of structural engineering to network science and then it develops computational approaches capturing different aspects of network stiffness so that to be used in complex network analysis. The implementation of these approaches to a real-world network (global inbound tourism network) shows that stiffness can produce interesting insights to complex network analysis about the factors related to changes caused to the structure and the status of a complex network. [ABSTRACT FROM AUTHOR]

This paper aims to demonstrate the impact of coal enterprises’ vertical integration on the performance of innovation corporate social responsibility (ICSR) and to elaborate its specific transmission path through financing structure and market power. This paper takes the data of A-share listed coal company from 2008 to 2017 as samples, uses input-output table method to measure the degree of vertical integration, and explores the relationship between the four factors through multiple linear regression and Bootstrap method. We found that: (1) the vertical integration of coal enterprises has positive incentives for the promotion of ICSR. (2) Financing structure and market power play a chain intermediary role in this process of incentive. (3) In areas with high marketization process, vertical integration has more significant incentive effect on ICSR. The paper extends the research on the relationship between vertical integration and innovation, which provides a reference for the improvement of China’s supply-side reform and corporate social responsibility (CSR) fulfillment policy. It is helpful to promote the sustainable development of the coal industry, stimulate the innovation vitality of enterprises, and improve the fulfillment of CSR. [ABSTRACT FROM AUTHOR]

Social networks influence health-related behavior, such as obesity and smoking. While researchers have studied social networks as a driver for diffusion of influences and behavior, it is less understood how the structure or topology of the network, in itself, impacts an individual's health behavior and wellness state. In this paper, we investigate whether the structure or topology of a social network offers additional insight and predictability on an individual's health and wellness. We develop a method called the Network-Driven health predictor (NetCARE) that leverages features representative of social network structure. Using a large longitudinal data set of students enrolled in the NetHealth study at the University of Notre Dame, we show that the NetCARE method improves the overall prediction performance over the baseline models—that use demographics and physical attributes—by 38%, 65%, 55%, and 54% for the wellness states—stress, happiness, positive attitude, and self-assessed health—considered in this paper. [ABSTRACT FROM AUTHOR]

Tropical tuna support some of the largest and most valuable artisanal and industrial fisheries worldwide, conducted to a large degree with Fish Aggregating Devices (FADs). Yellowfin, bigeye and skipjack are the main tuna species found in mixed aggregations around FADs and they are simultaneously encircled by the purse seining operation. One of the key challenges that purse seine fleets fishing with drifting FADs face in all oceans is to be able to target species in healthy condition such as skipjack, while reducing impacts on bigeye and yellowfin in areas where there is a need to reduce fishing pressure on these species. The present paper explores a technical solution for selective fishing at FADs by means of acoustic equipment used by purse seiners. Acoustic frequency response of skipjack and bigeye tuna were determined at 38, 120 and 200 kHz. Skipjack showed stronger response at higher frequencies. On the contrary, bigeye showed stronger responses at lower frequencies. The robust pattern shown in frequency responses of the two species demonstrates the potential to predict abundance and species proportions based on purely acoustic measures. The paper also addresses the conditions that need to be met to successfully apply this technology for selective fishing as well as other uses of direct acoustic observations to support tuna conservation. [ABSTRACT FROM AUTHOR]

Background: While school-aged children in low- and middle-income countries remain highly exposed to acute infections, programs targeting this age group remain limited in scale and scope. In this paper, we evaluate the impact of a new and comprehensive primary school-based health intervention program on student-reported morbidity and anthropometric outcomes in Lusaka, Zambia. Methods: A prospective matched control study identified 12 classes in 7 schools for the intervention and 12 classes in 7 matched schools as controls. Teachers in intervention schools were trained to deliver health lessons and to refer sick students to care. In addition, vitamin A and deworming medication were biannually administered to intervention students. The primary study outcome was student-reported morbidity. Secondary outcomes were weight, height, health knowledge, and absenteeism. Multivariable linear and logistic regression models were used to estimate program impact. Results: 380 students ages 4–16 were enrolled in the study in 2015, and 97% were followed up at endline in 2016. The intervention decreased the adjusted odds of self-reported acute illnesses by 38% (95% CI: 0.48, 0.77) and the adjusted odds of stunting by 52% (95% CI: 0.26, 0.87). It also increased health knowledge by 0.53 standard deviations (95% CI: 0.24, 0.81). No impact was found on weight (adjusted mean difference β = 0.17, 95% CI: - 1.11, 1.44) and student absenteeism (adjusted odds ratio (aOR) = 0.89, 95% CI: 0.60, 1.33). Conclusion: The results presented in this paper suggest that comprehensive school-based health programs may offer a highly effective way to improve students’ health knowledge as well as their health status. Given their low cost, a more general adoption and implementation of such programs seems recommendable. Trial registration: ClinicalTrials.gov Identifier: . [ABSTRACT FROM AUTHOR]

Accurate Origin-Destination (OD) prediction is significant for effective traffic monitor, which can support operation decision in traffic planning and management field. The enclosed expressway network system like toll gates system in China can collect mounts of trip records which can be gathered for OD prediction. The paper develops a novel neural network, which is named Expressway OD Prediction Neural Network (EODPNN) for toll data-based prediction. The network consists of the following three modules: The Feature Extension Module, the Memory Module, and the Prediction Module. In the process, the attributes data which can reflect the city attribute such as GDP, population, and the number of vehicles are considered to embeded into the notwork to increase the accuracy of the model. For the applicability improvment of the model, we categorize the cities in multiple classes based on their economy and population scales in this paper, which can provide a higher accurate prediction of OD by EODPNN. The results shows that, comparing to the traditional model like ARIMA and SVM, or typical neural networks like Bidirectional Long Short-term Memory, the EODPNN delivers a better prediction performance. The method proposed in this paper has been fully verified and has a potential to transplant to the other OD data-based management systems for a more accurate and flexible prediction. [ABSTRACT FROM AUTHOR]

The paper introduces structural diversity as a new approach to quantify the complexity of technologies. By modeling technologies as combinatorial networks, a measure of technological complexity is derived that represents the diversity of (sub-)network topologies in these networks. It is further argued that this measure can be empirically approximated with the Network Diversity Score (NDS). The paper also presents an application of this approach to European patent data from 1980 to 2015. On this basis, the measure of structural diversity is shown to replicate a number of stylized facts commonly associated with technological complexity: Complexity increases over time and younger technologies are more complex than older technologies. Complex technologies are also associated to larger R&D efforts and require more collaborative R&D activities. Lastly, when controlling for technologies’ size, technologies scoring high on structural diversity are also shown to concentrate in space. [ABSTRACT FROM AUTHOR]

Map-matching technology is a key and difficult technology in the development of vehicle navigation systems. Only by correctly identifying the road segment on which the vehicle is traveling can the navigation system make the right decision. At the same time, the complexity of the road network structure and a variety of error factors have introduced great challenges to map matching and have attracted the attention of many researchers as well. This paper analyzes various map-matching algorithms, determines that the key to the matching performance is the junction matching, performs an in-depth study on the junction-matching problem, and puts forward the junction decision domain model. The model mainly involves information regarding the width of the road segment, the angle between two road segments, the accuracy of GPS and the accuracy of the road network. In this paper, we use this model to improve the map-matching algorithm based on a hidden Markov model (HMM). The experimental results show that the improved matching algorithm can effectively reduce the error rate of junction matching and improve the matching performance of a navigation system. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper proposes a new quantum-like method for the binary classification applied to classical datasets. Inspired by the quantum Helstrom measurement, this innovative approach has enabled us to define a new classifier, called Helstrom Quantum Centroid (HQC). This binary classifier (inspired by the concept of distinguishability between quantum states) acts on density matrices—called density patterns—that are the quantum encoding of classical patterns of a dataset. In this paper we compare the performance of HQC with respect to twelve standard (linear and non-linear) classifiers over fourteen different datasets. The experimental results show that HQC outperforms the other classifiers when compared to the Balanced Accuracy and other statistical measures. Finally, we show that the performance of our classifier is positively correlated to the increase in the number of “quantum copies” of a pattern and the resulting tensor product thereof. [ABSTRACT FROM AUTHOR]

The number of outlaw bikers is growing globally. Despite this, little research exists on these groups and their alleged violent tendencies. To address this, the current paper uses unique data to examine whether gang violence causes outlaw biker violence. The period examined runs from mid-2008 until early 2012 during which violent clashes occurred between outlaw bikers and street gang members involved in an alleged conflict in Copenhagen, Denmark. A precise description of each individual act of violence would make it possible to identify whether specific acts were carried out in furtherance of the alleged conflict. This would allow one to determine whether outlaw bikers commit violence on behalf of their club. However, such knowledge is unavailable. The paper therefore takes a different approach by examining whether acts of violence committed by the two groups are statistically associated. In other words, it considers whether one or more acts can be described as retaliatory during the observation periods. The sample consists of 640 individuals involved with the Hells Angels Motorcycle Club or with non-biker street gangs–both of which are present in Copenhagen. Statistical models are used to predict 143 violent events committed by 196 outlaw bikers. The results suggest that violence committed by gang members predicts violence committed by outlaw bikers. This indicates that violent acts committed by outlaw bikers are at least partly a form of retaliation carried out on behalf of their club. The paper expands the literature on the kinds of inter-group, micro-level processes that can lead to reciprocal violence by including outlaw bikers in a literature that has previously focused on non-biker street gangs. [ABSTRACT FROM AUTHOR]

Animal movement encodes information that is meaningfully interpreted by natural counterparts. This is a behavior that roboticists are trying to replicate in artificial systems but that is not well understood even in natural systems. This paper presents a count on the cardinality of a discretized posture space—an aspect of expressivity—of articulated platforms. The paper uses an information-theoretic measure, Shannon entropy, to create observations analogous to Moore’s Law, providing a measure that complements traditional measures of the capacity of robots. This analysis, applied to a variety of natural and artificial systems, shows trends in increasing capacity in both internal and external complexity for natural systems while artificial, robotic systems have increased significantly in the capacity of computational (internal) states but remained more or less constant in mechanical (external) state capacity. The quantitative measure proposed in this paper provides an additional lens through which to compare natural and artificial systems. [ABSTRACT FROM AUTHOR]

In this paper, we present a method to estimate the market parameters modelled by an asymmetric jump diffusion process. The method proposed is based on Kou’s jump diffusion model while the market parameters refer to the market drift, the market volatility, the jump intensity on market price, and the rate of jump occurrence in a consistent manner throughout the entire paper. The model captures the asymmetric nature of the price fluctuation during up trend markets and down trend markets. The results are compared to conventional options to observe the impact of jump effects. The results from simulation show that the asymmetric jump diffusion model can estimate the fair prices of European call options and annuity better than the Black-Scholes model and the symmetric jump diffusion model proposed by Kou and Merton. [ABSTRACT FROM AUTHOR]

In this paper, we propose an Emotional Trigger System to impart an automatic emotion expression ability within the humanoid robot REN-XIN, in which the Emotional Trigger is an emotion classification model trained from our proposed Word Mover’s Distance(WMD) based algorithm. Due to the long time delay of the WMD-based Emotional Trigger System, we propose an enhanced Emotional Trigger System to enable a smooth interaction with the robot in which the Emotional Trigger is replaced by a conventional convolution neural network and a long short term memory network (CNN_LSTM)-based deep neural network. In our experiments, the CNN_LSTM based model only need 10 milliseconds or less to finish the classification without a decrease in accuracy, while the WMD-based model needed approximately 6-8 seconds to give a result. In this paper, the experiments are conducted based on the same sub-data sets of the Chinese emotional corpus(Ren_CECps) used in former WMD experiments: one comprises 50% data for training and 50% for testing(1v1 experiment), and the other comprises 80% data for training and 20% for testing(4v1 experiment). The experiments are conducted using WMD, CNN_LSTM, CNN and LSTM. The results show that CNN_LSTM obtains the best F1 score (0.35) in the 1v1 experiment and almost the same accuracy of F1 scores (0.366 vs 0.367) achieved by WMD in the 4v1 experiment. Finally, we present demonstration videos with the same scenario to show the performance of robot control driven by CNN_LSTM-based Emotional Trigger System and WMD-based Emotional Trigger System. To improve the comparison, total manual-control performance is also recorded. [ABSTRACT FROM AUTHOR]

This paper aims to investigate the relationship between women’s social class and their levels of self- and other-objectification. Two online studies comprising of multiple questionnaires were conducted: Study 1 examined the association between the social class (both objective and subjective) of 198 non-student British women and their self-objectification levels, while Study 2 turned towards the relationship between social class and other-objectification among 82 non-student British women. Our results indicated no apparent relationship between social class and each of the relevant objectification measures. As the first paper on the topic of class and objectification, it appears that there is no relationship observed between the two. [ABSTRACT FROM AUTHOR]

Scientific research is often thought of as being conducted by individuals and small teams striving for disciplinary advances. Yet as a whole, this endeavor more closely resembles a complex and integrated system of people, papers, and ideas. Studies of co-authorship and citation networks have revealed important structural properties of researchers and articles, but currently the structure of scientific ideas themselves is not well understood. In this study, we posit that topic networks may be a useful framework for revealing the nature of conceptual relationships. Using this framework, we map the landscape of interconnected research topics covered in the multidisciplinary journal PNAS since 2000, constructing networks in which nodes represent topics of study and edges give the extent to which topics occur in the same papers. The network displays small-world architecture, characterized by regions of dense local connectivity with sparse connectivity between them. In this network, dense local connectivity additionally gives rise to distinct clusters of related topics. Yet notably, these clusters tend not to align with assigned article classifications, and instead contain topics from various disciplines. Using a temporal graph, we find that small-worldness has increased over time, suggesting growing efficiency and integration of ideas. Finally, we define two measures of interdisciplinarity, one of which is found to be positively associated with PNAS’s impact factor. Broadly, this work suggests that complex and dynamic patterns of knowledge emerge from scientific research, and that structures reflecting intellectual integration may be beneficial for obtaining scientific insight. [ABSTRACT FROM AUTHOR]

As many countries are now seeking to protect their own markets rather than indulge in global trade, this paper examines whether this type of de-globalization behavior has been having any effect on international investment relationships through a systematic analysis of international investment network (IIN) in 127 economies from 2005 to 2016. Unlike previous studies that only analyzed portfolio investment data, the bilateral international investment data were estimated using a matrix-based iteration approach, and the IIN established using complex network theory. Using bilateral international investment data made the results more reliable and somewhat closer to reality. To analyze the structural properties and evolution of the IIN, complex network indicators including a new one named node similarity were developed. The node similarity is defined as the proportion of common relationships of the current economy between two successive years which is useful to reveal the dynamics of the IIN. This paper finds that there are heterogenous and hierarchal properties in the IIN, several economies had a wide range of international investment partners, while most others had only a small range of investment partners and were more likely to form tight groups within the network. The economies in the IIN were tending towards smaller but closer communities, a new trend of regional financial cooperation was developing. The IIN is divided into more communities over time while the top active and central economies often locate in different communities. These findings imply that the structure of the IIN is changing geographically during the de-globalization rather than independent with regions. The regional cooperation has made positive effect on the international investment. The governments should ensure that they continue to support liberal financial policies and to promote better regional financial cooperation. [ABSTRACT FROM AUTHOR]

A case of intergeneric hybridization in the wild between a female bottlenose dolphin (Tursiops truncatus) and a short-beaked common dolphin (Delphinus delphis), considered members of ‘vulnerable’ and ‘endangered’ subpopulations in the Mediterranean, respectively, by the International Union of Conservation of Nature is described in this paper. The birth of the hybrid was registered in the Bay of Algeciras (southern Spain) in August 2016, and the animal has been tracked on frequent trips aboard dolphin-watching platforms. This unique occurrence is the result of an apparent ongoing interaction (10 years) between a female bottlenose dolphin and common dolphins. The calf has a robust body with length similar to Tursiops, while its lateral striping and coloration are typical of Delphinus. It displays the common dolphin’s ‘criss-cross’ pattern. However, the thoracic patch is lighter than in D. delphis and its dorsal area is light grey, with a ‘V’ shape under the dorsal fin. This paper also provides a comprehensive mini-review of hybridizations of T. truncatus with other species. [ABSTRACT FROM AUTHOR]

Based on electrohysterogram, this paper designed a new method using wavelet-based nonlinear features and stacked sparse autoencoder for preterm birth detection. For each sample, three level wavelet decomposition of a time series was performed. Approximation coefficients at level 3 and detail coefficients at levels 1, 2 and 3 were extracted. Sample entropy of the detail coefficients at levels 1, 2, 3 and approximation coefficients at level 3 were computed as features. The classifier was constructed based on stacked sparse autoencoder. In addition, stacked sparse autoencoder was further compared with extreme learning machine and support vector machine in relation to their classification performance of electrohysterogram. The experiment results reveal that classifier based on stacked sparse autoencoder showed better performance than the other two classifiers with an accuracy of 90%, a sensitivity of 92%, a specificity of 88%. The results indicate that the method proposed in this paper could be effective for detecting preterm birth in electrohysterogram and the framework designed in this work presents higher discriminability than other techniques. [ABSTRACT FROM AUTHOR]

Understanding why parenting programmes work or do not work, and for whom, is crucial for development of more effective parenting interventions. In this paper we focus on a specific component of Mellow Bumps: reflection on one’s own childhood/past/life. We explore how this component was implemented, how participants engaged with it, the facilitating and constraining factors shaping this, whether and how it appeared to work, or not, and for whom. The paper analyses data from the Process Evaluation of the Trial of Healthy Relationships Initiatives for the Very Early years, which is evaluating two antenatal interventions delivered to vulnerable women, one of which is Mellow Bumps. Data were collected from January 2014 to June 2018 for 28 groups, 108 participants and 24 facilitators in a comprehensive and rigorous Process Evaluation designed to complement the Outcome Evaluation. Data were gathered at various time points using multiple methods, and were synthesised to triangulate findings. The reflective component was implemented with fidelity and participants engaged with it to varying degrees, dependent largely on the coherence of the group. Patchy attendance compromised the coherence of some groups, with the development of rapport, which is key to delivering reflective exercises, more difficult when group composition varied from week to week. Where there was a coherent group, powerful mechanisms of change, leading to stress reduction, included: relief through unburdening, empowerment through support given and received, reduced isolation through sharing anxieties, and control through self-care advice. A minority of highly vulnerable mothers seemed not to benefit from the reflective exercises and were marginalised within their groups. In order to minimise potential harmful effects of such exercises, allocation of participants to groups should strive to maximise group homogeneity. More research is needed to explore how very vulnerable parents can be supported in attending parenting interventions from start to finish. [ABSTRACT FROM AUTHOR]

An extreme learning machine (ELM) is a novel training method for single-hidden layer feedforward neural networks (SLFNs) in which the hidden nodes are randomly assigned and fixed without iterative tuning. ELMs have earned widespread global interest due to their fast learning speed, satisfactory generalization ability and ease of implementation. In this paper, we extend this theory to hypercomplex space and attempt to simultaneously consider multisource information using a hypercomplex representation. To illustrate the performance of the proposed hypercomplex extreme learning machine (HELM), we have applied this scheme to the task of multispectral palmprint recognition. Images from different spectral bands are utilized to construct the hypercomplex space. Extensive experiments conducted on the PolyU and CASIA multispectral databases demonstrate that the HELM scheme can achieve competitive results. The source code together with datasets involved in this paper can be available for free download at . [ABSTRACT FROM AUTHOR]

The changing population age structure has a significant influence on the economy, society, and numerous other aspects of a country. This paper has innovatively applied the method of compositional data forecasting for the prediction of population age changes of the young (aged 0–14), the middle-aged (aged 15–64), and the elderly (aged older than 65) in China, India, and Vietnam by 2030 based on data from 1960 to 2016. To select the best-suited forecasting model, an array of data transformation approaches and forecasting models have been extensively employed, and a large number of comparisons have been made between the aforementioned methods. The best-suited model for each country is identified considering the root mean squared error and mean absolute percent error values from the compositional data. As noted in this study, first and foremost, it is predicted that by the year 2030, China will witness the disappearance of population dividend and get mired in an aging problem far more severe than that of India or Vietnam. Second, Vietnam’s trend of change in population age structure resembles that of China, but the country will sustain its good health as a whole. Finally, the working population of India demonstrates a strong rising trend, indicating that the age structure of the Indian population still remains relatively “young”. Meanwhile, the continuous rise in the proportion of elderly population and the gradual leveling off growth of the young population have nevertheless become serious problems in the world. The present paper attempts to offer crucial insights into the Asian population size, labor market and urbanization, and, moreover, provides suggestions for a sustainable global demographic development. [ABSTRACT FROM AUTHOR]

Background: With an estimated 27 million annual incidents of maternal morbidity globally, how they are manifested or experienced is diverse and shaped by societal, cultural and personal influences. Using qualitative research to examine a woman's perception of her pregnancy, its complications, and potential long-term impact on her life can inform public health approaches and complement and inform biomedical classifications of maternal morbidities, historically considered a neglected dimension of safe motherhood. As part of the WHO’s Maternal Morbidity Working Group’s efforts to define and measure maternal morbidity, we carried out a thematic analysis of the qualitative literature published between 1998 and 2017 on how women experience maternal morbidity in low and lower-middle income countries. Results and conclusions: Analysis of the 71 papers included in this study shows that women’s status, their marital relationships, cultural attitudes towards fertility and social responses to infertility and pregnancy trauma are fundamental to determining how they will experience morbidity in the pregnancy and postpartum periods. We explore the physical, economic, psychological and social repercussions pregnancy can produce for women, and how resource disadvantage (systemic, financial and contextual) can exacerbate these problems. In addition to an analysis of ten themes that emerged across the different contexts, this paper presents which morbidities have received attention in different regions and the trends in researching morbidities over time. We observed an increase in qualitative research on this topic, generally undertaken through interviews and focus groups. Our analysis calls for the pursuit of high quality qualitative research that includes repeat interviews, participant observation and triangulation of sources to inform and fuel critical advocacy and programmatic work on maternal morbidities that addresses their prevention and management, as well as the underlying systemic problems for women’s status in society. [ABSTRACT FROM AUTHOR]

This paper reports the impact of a major life event–death–on the physical, psychological and social well-being of the deceased’s close friends. We utilised data from a large longitudinal survey covering a period of 14 years (2002–2015) consisting a cohort of 26,515 individuals in Australia, of whom 9,586 had experienced the death of at least one close friend. This longitudinal cohort dataset comprises responses to the SF-36 (health related quality of life measure) and allowed for analysis of the short and longer-term impacts of bereavement. In order to manage the heterogeneity of the socio-demographics of respondents who did/not experience a death event, we use a new and robust approach known as the Entropy Balancing method to construct a set of weights applied to the bereaved group and the control group (the group that did not experience death). This approach enables us to match the two groups so that the distribution of socio-demographic variables between the two groups are balanced. These variables included gender, age, marital status, ethnicity, personality traits, religion, relative socio-economic disadvantage, economic resources, and education and occupation and where they resided. The data show, for the first time, a range of negative and enduring consequences experienced by people following the death of a close friend. Significant adverse physical and psychological well-being, poorer mental health and social functioning occur up to four years following bereavement. Bereaved females experienced a sharper fall in vitality, suffered greater deterioration in mental health, impaired emotional and social functioning than the male counterparts up to four years after the death. The data show that the level of social connectedness plays an important role in bereavement outcomes. Specifically, we found that less socially active respondents experienced a longer deterioration in physical and psychological health. Finally, we found evidence that the death of a close friend lowered the respondent’s satisfaction with their health. Since death of friends is a universal phenomenon, we conclude the paper by reflecting on the need to recognise the death of a close friend as a substantial experience, and to offer support and services to address this disenfranchised grief. Recognising bereaved friends as a group experiencing adverse outcomes can be used internationally to prompt health and psychological services to assist this specific group, noting that there may be substantial longevity to the negative sequelae of the death of a friend. Facilitating bereaved people’s support networks may be a fruitful approach to minimising these negative outcomes. [ABSTRACT FROM AUTHOR]

In this paper, we aim to establish a mathematical model to design a maximizing social welfare intervention mechanism of healthcare service goods in China. The intervention mechanism is helpful to facilitate the adoption of the healthcare service goods. We consider a research problem that regulates the supply chain system for healthcare service goods by an intervention mechanism, and two intervention strategies composed of demand-growth strategy and subsidy strategy are used to the combination of intervention mechanism. Then this paper presents a new method based on fuzzy set and bilevel programming to design the intervention mechanism. To demonstrate the effectiveness of the proposed model, we conduct a case study for Wudang personalized health package and verify our model by the specific result analysis, the result indicates that our joint intervention mechanism is helpful to achieve the target and increase social welfare. [ABSTRACT FROM AUTHOR]

Computational modeling of engineered gene circuits is an important while challenged task in systems biology. In order to describe and predict the response behaviors of genetic circuits using reliable model parameters, this paper applies an optimal experimental design(OED) method to obtain input signals. In order to obtain informative observations, this study focuses on maximizing Fisher information matrix(FIM)-based optimal criteria and to provide optimal inputs. Furthermore, this paper designs a two-stage optimization with the modified E-optimal criteria and applies harmony search(HS)-based OED algorithm to minimize estimation errors. The proposed optimal identification methodology involves estimation errors and the sample size to pursue a trade-off between estimation accuracy and measurement cost in modeling gene networks. The designed cost function takes two major factors into account, in which experimental costs are proportional to the number of time points. Experiments select two types of synthetic genetic networks to validate the effectiveness of the proposed HS-OED approach. Identification outcomes and analysis indicate the proposed HS-OED method outperforms two candidate OED approaches, with reduced computational effort. [ABSTRACT FROM AUTHOR]

Introduction: Community nursing and midwifery is changing in response to a shift in care from hospital to home, brought about by increasing costs to care because of an aging population and increasing chronicity. Until now, community nursing positions and scope of practice has been dependent on service focus and location, which has led to the role being unclearly defined. Lack of appeal for a career in community practice and a looming workforce shortage necessitates a review into how community nursing and midwifery transition to practice is supported. Methods: This review sought to identify, assess and summarize available evidence relating to transitioning into community nursing and midwifery practice as a speciality. A systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses approach. A narrative synthesis was then undertaken on papers that examined community nursing and midwifery pathway perspectives which define, and enable or inhibit a contemporary pathway. Thematic analysis used a theoretical framework developed for early career and rapid transition to nursing specialty practice. Results: There is a paucity of research that identifies community nursing and midwifery as a discreet scope of practice. Twelve papers were eventually included in the review. Verbatim findings were extracted from the papers and clustered into categories based on the chosen theoretical framework. Major themes were ‘the self’ (professional and personal); ‘transition processes’; and, a ‘sense of belonging’. Sub themes included narrative identifying inhibitors and enablers in each theme. Discussion: No definition of community practice or pathway was identified in nursing, although midwifery was clearly defined. Community nursing practice was described as generalist in nature although specialist knowledge is required. Being part of the community in the professional sense and personal sense was considered important. The importance of transition was identified where pre-entry exposure to community practice was seen as important. Stages in transition to practice were recognised as pre-entry; incomer; insider; and, a sense of belonging. The process of transition should be planned and individualised acknowledging past experience whilst acknowledging the specialist nature of community-based practice. [ABSTRACT FROM AUTHOR]

The University of KwaZulu-Natal has introduced a new language policy requiring all students who have not done Zulu as a first (or second) language at school to complete a six-month course in Zulu as part of their undergraduate curriculum. Given that English is the medium of instruction that is being used for all their other courses, the time that these students have had to spend learning this new language may be adversely affecting the marks that they could be getting for their other courses. Having to do a course in Zulu is also preventing them from being able to take another course in their chosen area of study. If one were able to randomly assign students to the group who have to take the Zulu course, then any difference in performance between the two groups could be directly attributed to the new language policy that is being introduced at the university. Given the context of this paper, however, such a random allocation is not possible. Students who have not done Zulu at school have to eventually complete a course in Zulu before graduating. If this cohort differs (in any other way) from those who do not have to take this course, then any observed difference in overall performance between the two groups may be a result of these group differences rather than the new rule that has been implemented. Methodology: This paper uses regression adjustment and entropy matching to achieve an appropriate balance between the two groups. Having achieved this balance any difference in the overall performance between the two groups can then be attributed directly to the new language policy that has been implemented. Our results indicate, after matching, that a significant difference in performance between the two groups occurs with Black African Zulu home language speakers in particular not performing as well as students from the other race and language groups. The data came from the University of KwaZulu-Natal and the study has been approved by the University Ethics committee and Research committee. Results and conclusions: Using a weighted mean of marks to measure performance, the ATT estimates that result indicate that students in the treated group would all perform significantly better had they been allowed instead to enrol in the non-treated group. Furthermore, Zulu home language speakers, who are not actually forced to take this course, are significantly underperforming whether they have chosen to take this course in Zulu or not. Surprisingly, their underperformance is worse in the treated group. Because one would expect them to be scoring a higher mark for Zulu in this treated group, forfeiting the chance to take another course in their chosen area of study is clearly affecting the type of mark they could be getting for their other courses had they chosen to remain in the non-treated group. With English being the medium of instruction at this university, should the university not also consider introducing a compulsory course in English for these Zulu home language speakers? Females are doing better than males in both groups. The effect being stronger in the treated group suggests that females appear to cope better with the learning of a new language. Significant college effects are also being observed, suggesting that this new language rule possibly needs to be adjusted for the college a student wants to study in. [ABSTRACT FROM AUTHOR]

We used a retrospective cohort study to measure the impact of caring for children on female Australian researchers. Our aim was to see whether caring for children was associated with reduced outputs and collaboration. Women were randomly selected for inclusion if they published a first author paper in one of three Australian journals during 2007 to 2015, women who did not publish during this time were not included. One-hundred and sixty women were approached and 95 (59%) completed a survey on their history of caring for children. Two key outcomes were the women's publication and citation counts, which were accessed from Scopus. We also examined the number of authors, affiliations and countries on their published papers, as a reduction in these numbers could indicate an impaired ability to collaborate. We examined the probability of being first or last author as a measure of esteem. There was a small increase in publication counts after the first child that was reversed after the second child. Average citations counts declined after children, particularly after the second child. There was some evidence of a reduced collaboration with overseas collaborators after the first child. The probability of being the last author increased after the second child. Three women were identified as statistically influential and all three had children and were in the top 10% of overall publications and citations. After removing these women the estimated changes in outcomes were noticeably different for most of the outcomes. The repeated presence of statistically influential women shows that it may be impossible to find an "average impact" of caring for children when considering research output. Adjustments may need to be made individually, with women explaining how caring for children has altered their career. [ABSTRACT FROM AUTHOR]

In this paper, we propose a method that estimates an average delay of frames for each queue and finds an optimal number of aggregated Medium Access Control (MAC) Protocol Data Units (MPDUs) to maximize the system throughput with satisfying the delay requirement of each queue when using the Aggregate MPDU (A-MPDU) aggregation in IEEE 802.11ac. The delay is defined as the sum of the queuing delay and the service delay. If few frames in a queue are aggregated, the frames which remain in the queue for next transmissions may violate the target delay because of the overhead for the next transmissions such as the backoff time, Physical Layer Convergence Procedure (PLCP) preamble, and PLCP header. If many of the frames in the queue are aggregated, the frames of the queue and the other queues may violate their target delays because of a long transmission duration and a long channel occupancy. In this paper, we obtain the average delay for each queue and the optimal number of aggregated MPDUs for the delay requirement of each queue in IEEE 802.11ac. At the last, we evaluate and show the performance of our proposed method through simulations. The simulation results show that the proposed method can estimate the average delay for each queue accurately. The simulation results also show that the proposed method can obtain the violation rates on the target delays less than 0.1. Furthermore, the simulation results show that the proposed method can yield higher system throughput than other conventional methods. [ABSTRACT FROM AUTHOR]