nils-herrmann/clean_scirepeval huggingface dataset:
Electricity Load and Price Forecasting Using Jaya Long Short Term Memory (JLSTM) in Smart Grids
Venue: Entropy
Year: 2020

In the smart grid (SG) environment, consumers are enabled to alter electricity consumption patterns in response to electricity prices and incentives. This results in prices that may differ from the initial price pattern. Electricity price and demand forecasting play a vital role in the reliability and sustainability of SG. Forecasting using big data has become a new hot research topic as a massive amount of data is being generated and stored in the SG environment. Electricity users, having advanced knowledge of prices and demand of electricity, can manage their load efficiently. In this paper, a recurrent neural network (RNN) long short term memory (LSTM) is used for electricity price and demand forecasting using big data. Researchers are working actively to propose new models of forecasting. These models contain a single input variable as well as multiple variables. From the literature, we observed that the use of multiple variables enhances the forecasting accuracy. Hence, our proposed model uses multiple variables as input and forecasts the future values of electricity demand and price. The hyperparameters of this algorithm are tuned using the Jaya optimization algorithm to improve the forecasting ability and increase the training mechanism of the model. Parameter tuning is necessary because the performance of a forecasting model depends on the values of these parameters. Selection of inappropriate values can result in inaccurate forecasting. So, integration of an optimization method improves the forecasting accuracy with minimum user efforts. For efficient forecasting, data is preprocessed and cleaned from missing values and outliers, using the z score method. Furthermore, data is normalized before forecasting. The forecasting accuracy of the proposed model is evaluated using the root mean square error (RMSE) and mean absolute error (MAE) For a fair comparison, the proposed forecasting model is compared with univariate LSTM and support vector machine (SVM) The values of the performance metrics depict that the proposed model has higher accuracy than SVM and univariate LSTM.
A clinical approach to diagnosis of autoimmune encephalitis
Venue: The Lancet Neurology
Year: 2016

Encephalitis is a severe inflammatory disorder of the brain with many possible causes and a complex differential diagnosis. Advances in autoimmune encephalitis research in the past 10 years have led to the identification of new syndromes and biomarkers that have transformed the diagnostic approach to these disorders. However, existing criteria for autoimmune encephalitis are too reliant on antibody testing and response to immunotherapy, which might delay the diagnosis. We reviewed the literature and gathered the experience of a team of experts with the aims of developing a practical, syndrome based diagnostic approach to autoimmune encephalitis and providing guidelines to navigate through the differential diagnosis. Because autoantibody test results and response to therapy are not available at disease onset, we based the initial diagnostic approach on neurological assessment and conventional tests that are accessible to most clinicians. Through logical differential diagnosis, levels of evidence for autoimmune encephalitis (possible, probable, or definite) are achieved, which can lead to prompt immunotherapy.
The role of JOOP (and other scientific journals) in bridging the practitioner researcher divide in industrial, work and organizational (IWO) psychology
Year: 2006

Reflecting upon recent debates concerning the practitioner researcher divide in the field of industrial, work and organizational (IWO) psychology, Garry Gelade advocates a series of changes to the publication policy of the Journal of Occupational and Organizational Psychology (JOOP) in an attempt to increase its appeal to HR practitioners. While his overall intention the increased application of psychological knowledge, tools and techniques to the enhancement of productivity and well being in workplace settings is to be welcomed, unfortunately, several of his recommendations are misplaced, reflecting a number of misconceptions concerning the nature and role of scientific journals in the science and practice of IWO psychology. Taken as a whole, the package of policy changes he advocates is likely to prove counterproductive. Accordingly, modifications to his recommendations are offered, with a view to ensuring that JOOP continues to meet the needs of its prime constituents.
Helping Mom Help Baby: Nutrition Based Support for the Mother Infant Dyad During Lactation
Venue: Frontiers in Nutrition
Year: 2020

Lactation and breastfeeding support the short and long term health of both mother and infant, yet the success of these processes depend upon individual and combined factors of the pair. Complications during pregnancy and delivery greatly affect the likelihood that a mother will be capable of breastfeeding for at least the recommended 6 months. Guidelines for women regarding postpartum diet and lifestyle management also fail to reflect the diversity of mother infant pairs and their circumstances. In our analysis of the literature, we have identified a categorical deficit in modern scientific discourse regarding human lactation; namely, that postpartum involves full body contribution of resources and thus requires the application of nutrition from a systemic perspective.
End to End Learning of Geometric Deformations of Feature Maps for Virtual Try On
Venue: ArXiv
Year: 2019

The 2D virtual try on task has recently attracted a lot of interest from the research community, for its direct potential applications in online shopping as well as for its inherent and non addressed scientific challenges. This task requires to fit an in shop cloth image on the image of a person. It is highly challenging because it requires to warp the cloth on the target person while preserving its patterns and characteristics, and to compose the item with the person in a realistic manner. Current state of the art models generate images with visible artifacts, due either to a pixel level composition step or to the geometric transformation. In this paper, we propose WUTON: a Warping U net for a Virtual Try On system. It is a siamese U net generator whose skip connections are geometrically transformed by a convolutional geometric matcher. The whole architecture is trained end to end with a multi task loss including an adversarial one. This enables our network to generate and use realistic spatial transformations of the cloth to synthesize images of high visual quality. The proposed architecture can be trained end to end and allows us to advance towards a detail preserving and photo realistic 2D virtual try on system. Our method outperforms the current state of the art with visual results as well as with the Learned Perceptual Image Similarity (LPIPS) metric.
Medical tourism and policy implications for health systems: a conceptual framework from a comparative study of Thailand, Singapore and Malaysia
Venue: Globalization and health
Year: 2011

Medical tourism is a growing phenomenon with policy implications for health systems, particularly of destination countries. Private actors and governments in Southeast Asia are promoting the medical tourist industry, but the potential impact on health systems, particularly in terms of equity in access and availability for local consumers, is unclear. This article presents a conceptual framework that outlines the policy implications of medical tourism's growth for health systems, drawing on the cases of Thailand, Singapore and Malaysia, three regional hubs for medical tourism, via an extensive review of academic and grey literature. Variables for further analysis of the potential impact of medical tourism on health systems are also identified. The framework can provide a basis for empirical, in country studies weighing the benefits and disadvantages of medical tourism for health systems. The policy implications described are of particular relevance for policymakers and industry practitioners in other Southeast Asian countries with similar health systems where governments have expressed interest in facilitating the growth of the medical tourist industry. This article calls for a universal definition of medical tourism and medical tourists to be enunciated, as well as concerted data collection efforts, to be undertaken prior to any meaningful empirical analysis of medical tourism's impact on health systems.
The introduction of amino termination on Ti3C2 MXene surface for its flexible film with excellent property
Venue: Carbon
Year: 2021

The chemical conversion of the surface termination of 2D transition metal carbides/nitrides (MXenes) has opened up a design space that previously had not been extensively explored for this functional material. Herein, via a simple sealed thermal method, the amino terminated groups were successfully introduced on Ti3C2 MXene surface. The substitution reaction of amino group to hydroxyl group was proposed to elucidate this aminated process. As the amination would reduce the carrier density on the surface of MXene, the electrical conductivity of MXene NH2 film decreased, while it still reached a high conductivity of 2.11x104 S m 1. This film also possessed an excellent electromagnetic interference shielding effectiveness of 16160 dB cm2 g 1. Importantly, although the introduction of amino termination altered Zeta potential value, Zeta potential sign remained negative and the MXene NH2 exhibited excellent dispersity in water similar to that of traditional MXenes. Furthermore, the existence of covalent bonds endowed MXene NH2 polymer composite film with improved mechanical properties. Compared with that of traditional CMC/MXene film, the tensile strength and fracture energy of CMC/MXene NH2 increased by 65.5% and 132.7% respectively. These results demonstrated that the introduction of amino terminated group on MXene surface would be an effective strategy to obtain higher performance MXene based films.
Spatially Cohesive Service Discovery and Dynamic Service Handover for Distributed IoT Environments
Venue: ICWE
Year: 2017

The proliferation of the Internet of Things (IoT) enables the provision of diverse services that utilize IoT resources distributed in ad hoc network environments. This has resulted in a new challenge, the issue of how to efficiently and dynamically discover appropriate IoT services that are necessary to accomplish a user task in the vicinity of the user. In this paper, we propose a service discovery method that finds IoT services from a user's surrounding environment in a spatially cohesive manner so that the interactions among the services can be efficiently carried out, and the outcome of service coordination can be effectively delivered to the user. In addition, to ensure a certain Quality of user Experience (QoE) level for the user task, we develop a service handover approach that dynamically switches from one IoT resource to an alternative one to provide services in a stable manner when the degradation of the spatial cohesiveness of the services is monitored. The spatio cohesive service discovery and dynamic service handover algorithms are evaluated by simulating a mobile ad hoc network (MANET) based IoT environment. Then, various service discovery strategies are implemented on this simulation environment, and several options for the service discovery and handover algorithms are tested. The simulation results show that compared to various baseline approaches, the proposed approach results in a significant improvement in the spatial cohesiveness of the services discovered for user tasks. The results also show that the approach efficiently adapts to dynamically changing distributed IoT environments.
Host genetic modifiers of nonproductive angiogenesis inhibit breast cancer
Venue: Breast Cancer Research and Treatment
Year: 2017

PurposeMultiple aspects of the tumor microenvironment (TME) impact breast cancer, yet the genetic modifiers of the TME are largely unknown, including those that modify tumor vascular formation and function.MethodsTo discover host TME modifiers, we developed a system called the Consomic/Congenic Xenograft Model (CXM) In CXM, human breast cancer cells are orthotopically implanted into genetically engineered consomic xenograft host strains that are derived from two parental strains with different susceptibilities to breast cancer. Because the genetic backgrounds of the xenograft host strains differ, whereas the inoculated tumor cells are the same, any phenotypic variation is due to TME specific modifier(s) on the substituted chromosome (consomic) or subchromosomal region (congenic) Here, we assessed TME modifiers of growth, angiogenesis, and vascular function of tumors implanted in the SSIL2Rg and SS.BN3IL2Rg CXM strains.ResultsBreast cancer xenografts implanted in SS.BN3IL2Rg (consomic) had significant tumor growth inhibition compared with SSIL2Rg (parental control) despite a paradoxical increase in the density of blood vessels in the SS.BN3IL2Rg tumors. We hypothesized that decreased growth of SS.BN3IL2Rg tumors might be due to nonproductive angiogenesis. To test this possibility, SSIL2Rg and SS.BN3IL2Rg tumor vascular function was examined by dynamic contrast enhanced magnetic resonance imaging (DCE MRI) micro computed tomography (micro CT) and ex vivo analysis of primary blood endothelial cells, all of which revealed altered vascular function in SS.BN3IL2Rg tumors compared with SSIL2Rg. Gene expression analysis also showed a dysregulated vascular signaling network in SS.BN3IL2Rg tumors, among which DLL4 was differentially expressed and co localized to a host TME modifier locus (Chr3: 95 131 Mb) that was identified by congenic mapping.ConclusionsCollectively, these data suggest that host genetic modifier(s) on RNO3 induce nonproductive angiogenesis that inhibits tumor growth through the DLL4 pathway.
A Human Robot Interaction Perspective on Assistive and Rehabilitation Robotics
Venue: Front. Neurorobot.
Year: 2017

Assistive and rehabilitation devices are a promising and challenging field of recent robotics research. Motivated by societal needs such as aging populations, such devices can support motor functionality and subject training. The design, control, sensing, and assessment of the devices become more sophisticated due to a human in the loop. This paper gives a human robot interaction perspective on current issues and opportunities in the field. On the topic of control and machine learning, approaches that support but do not distract subjects are reviewed. Options to provide sensory user feedback that are currently missing from robotic devices are outlined. Parallels between device acceptance and affective computing are made. Furthermore, requirements for functional assessment protocols that relate to real world tasks are discussed. In all topic areas, the design of human oriented frameworks and methods is dominated by challenges related to the close interaction between the human and robotic device. This paper discusses the aforementioned aspects in order to open up new perspectives for future robotic solutions.
The effectiveness of group training of cognitive behavioral therapy based stress management on anxiety, hardiness and self efficacy in female medical students
Venue: Journal of education and health promotion
Year: 2019

The present study aimed to investigate the effectiveness of cognitive behavioral therapies (CBTs) for anxiety, hardiness, and self efficacy in female students of Birjand University of Medical Sciences.  This was an interventional study. A sample of 30 participants were selected through the available sampling method and randomly assigned into experimental (CBT) and control groups (each group, 15 female student) The data collection instrument was the Beck Depression Inventory questionnaire. The questionnaires of Beck Anxiety Inventory, Ahvaz Hardiness Inventory, and Schwartz's General Self Efficacy Scale were completed by all participants in two stages (pretest and posttest) A 6 session protocol of cognitive behavioral group therapy was performed only on the experimental group. The data were analyzed using Kolmogorov Smirnov, Levene's F, Mbox, analysis of variance, and multivariate analysis of variance tests.  The intervention group showed that the mean of anxiety decreased, whereas (P 0.001) the means of hardiness and self efficacy increased in the posttest for the experimental group (P 0.001)  Based on the obtained results, it can be concluded that CBT is an effective treatment for anxiety, hardiness, and self efficacy. Therefore, through managing anxiety, the levels of hardiness and self efficacy can be increased in students of university to be able to cope with the different challenges in their life.
Effective Demand Forecasting Model Using Business Intelligence Empowered With Machine Learning
Venue: IEEE Access
Year: 2020

In the modern era business intelligence (BI) has a pivotal role in articulating a strategy and taking correct measures based on data. Business intelligence plays a pivotal role in an inevitable decision support system that enables the enterprise to perform analysis on data and throughout the process of business. Machine learning predicts the forecasting of future demands of the enterprises. Demand forecasting is one of the main decision making tasks of enterprise. For demand forecasting first raw sales data is collected from the market, then according to data, the future sale/product demands are forecasted. This prediction is based on collected data that compiles through different sources. The machine learning engine executes data from different modules and determines the weekly, monthly, and quarterly demands of goods/commodities. In demand forecasting, its perfect accuracy is non compromising, the more accurate system model is more efficient. Furthermore, we test the efficiency by comparing the predicted data with actual data and determine the percentage error. Simulation results show that after applying the purposed solution on real time organization data, we get up to 92.38 accuracies for the store in terms of intelligent demand forecasting.
Plastic pollution in Swiss surface waters: nature and concentrations, interaction with pollutants
Year: 2015

Marine microplastic ,5 mm) water pollution has met growing public and scientific interest in the last few years. The situation in freshwater environments remains largely unknown, although it appears that they play an important role as part of the origin of marine pollution. Apart from the physical impacts on biota, chemical effects are to be expected as well, especially with smaller particles. This study aims at assessing plastic abundance in Lakes Geneva, Constance, Neucha^tel, Maggiore, Zurich and Brienz, and identifying the nature of the particles, potential ingestion by birds and fishes, and the associated pollutants. Lake surface transects and a few rivers were sampled using a floating manta net, and beach sediments were analysed. Plastics were sorted by type (fragments, pellets, cosmetic beads, lines, fibres, films, foams) and composition (polypropylene, polyethylene, polystyrene, etc. fish and water birds were dissected to assess their potential exposure, and analyses were conducted on the hydrophobic micropollutants adsorbed to the microplastics as well as some potentially toxic additives they contained. Evidence of this pollution is shown for all lakes, microplastics of all types and diverse composition having been found in all samples. Birds and fish are prone to microplastic ingestion, and all the tested chemicals (both adsorbed micropollutants and contained additives) were found above the detection limit, and often the quantification limit. The sources and their respective contribution need to be confirmed and quantified, and the ecotoxicological effects need further investigation. Other questions remain open, including the transport and fate of plastic particles in the environment.
Motivation and participation in daily and social activities among adults with spinal cord injury: Applying self determination theory.
Venue: Disability and health journal
Year: 2019

Individuals with a spinal cord injury (SCI) report decreased participation in daily and social activities. Self determination theory (SDT) posits that individuals' need satisfaction and frustration predicts participation in health related behaviours and this relationship is mediated by their motivation.  This study explored the role of psychological needs and motivation in relation to participation in daily and social activities among adults with SCI. It was hypothesized that: a) need satisfaction and need frustration were positively associated with autonomous and controlled motivation, respectively, which, positively and negatively predicted participation in daily and social activities; b) autonomous and controlled motivation mediated the need satisfaction/frustration and participation relationship, respectively; and c) need frustration was positively related to amotivation, with no relationship between amotivation and activity participation.  In this cross sectional study, adults with SCI (N 131) completed a questionnaire regarding their need satisfaction/frustration, autonomous and controlled motivation, amotivation, and participation in daily and social activities.  Need satisfaction was positively related to autonomous motivation (b 0.29, 95%bias corrected confidence interval (bCI) [0.04, 0.67] and need frustration to controlled motivation (b 0.28, 95%bCI: [0.09, 0.55] Autonomous motivation was positively associated with six participation categories: autonomous indoor, autonomous outdoor, family role, health, social life, and work/education. Autonomous motivation also mediated the relationship between need satisfaction and all six participation categories; whereas, neither controlled motivation nor amotivation mediated the relationship between need frustration and participation.  This study found that SDT provides a meaningful framework for understanding participation among adults with SCI.
Usos problematicos de Internet y depresion en adolescentes: Meta analisis
Year: 2020

El uso extendido de Internet en la sociedad del siglo XXI no esta exento de riesgos. El presente trabajo estudia la comorbilidad entre los usos problematicos de Internet y la depresion con la finalidad de determinar la existencia de relacion entre ambas. Para ello se ha llevado a cabo un meta analisis, que cuenta con 19 muestras recogidas en 13 investigaciones (n=33.748) con adolescentes de entre 12 y 18 anos (u=15,68) de diferentes culturas y continentes (Europa, Euro Asia, America y Asia) El tamano del efecto obtenido a partir de un modelo de efectos aleatorios (r=0,3, p<0,000) es significativo, positivo y moderado confirmando la existencia de relacion entre usos patologicos de Internet y depresion. Por otra parte, la meta regresion mostro que el 9% (R2=0,09) de la varianza es explicada por el sexo masculino, mientras que la edad y la cultura no son variables significativas. La variabilidad de los estudios es elevada (I2=87,085% siendo fruto de la heterogeneidad y no del sesgo de publicacion, tal y como indico la prueba de regresion de Egger (p value 1 tailed=0,25; p value 2 tailed=0,50 y =1,57) Se advierte la necesidad de comenzar a generar proyectos de intervencion en Educacion Secundaria que traten esta problematica con el objetivo de que no se extienda a la vida adulta.