Miracle-dz/UniFAR-FTUs huggingface dataset:
Opportunities and challenges in the development and implementation of a national research strategy in adult learning & work

The confluence of increasing pressures on researchers to demonstrate the impact of their work with a growing interest in research informed practice and policy creates both opportunities and challenges for dialogue and partnership between researchers, policy makers and practitioners in adult, vocational and lifelong education and training. The Research Division of the Institute for Adult Learning in Singapore, part of the Singapore Workforce Development Agency, has attempted to grasp these opportunities, and address the challenges, through the development of a research strategy shaped by consultation with key stakeholders, from Workforce Skills Qualification (WSQ) course participants to senior policy makers. The implementation of this strategy has involved both the design of a programme of policy and practice relevant research and the development of a range of research capacity and capability development initiatives. In this paper we will explore the process of facilitating the creation of a research community in Continuing Education and Training (CET). In particular, we will examine the ways in which specific research studies in key areas of adult learning, skills utilisation and innovation in CET have acted both to inform practice and policy and act as a medium for research capability building. We will relate this work to the development of a framework for monitoring and evaluation of the impact of CET initiatives and, ultimately, investment in Singapore. From this we will explore the ways in which such a framework can assist in establishing coherence in and the credibility of a research and development programme that aims to maximise impact on practice. (Theme: Policy studies, work and learning).
Gaggle: Visual Analytics for Model Space Navigation

Recent visual analytics systems make use of multiple machine learning models to better fit the data as opposed to traditional single, pre-defined model systems. However, while multi-model visual analytic systems can be effective, their added complexity poses usability concerns, as users are required to interact with the parameters of multiple models. Further, the advent of various model algorithms and associated hyperparameters creates an exhaustive model space to sample models from. This poses complexity to navigate this model space to find the right model for the data and the task. In this paper, we present Gaggle, a multi-model visual analytic system that enables users to interactively navigate the model space. Further translating user interactions into inferences, Gaggle simplifies working with multiple models by automatically finding the best model from the high-dimensional model space to support various user tasks. Through a qualitative user study, we show how our approach helps users to find a best model for a classification and ranking task. The study results confirm that Gaggle is intuitive and easy to use, supporting interactive model space navigation and auPaste the appropriate copyright statement here. ACM now supports three different copyright statements: • ACM copyright: ACM holds the copyright on the work. This is the historical approach. • License: The author(s) retain copyright, but ACM receives an exclusive publication license. • Open Access: The author(s) wish to pay for the work to be open access. The additional fee must be paid to ACM. This text field is large enough to hold the appropriate release statement assuming it is
Systematic Review of Glass Ceiling Effect in

As women started to take an active role in business life, the problems faced by women in organizational life attracted the attention of researchers. The concept of glass ceiling effect, which is popular in recent years, has been studied in many business areas. This study was held with the aim of reviewing studies published between January 2000 and May 2019 in Turkey about glass ceiling effect perception of women working in academia and systematically reviewing data obtained from the studies. A total 168 publications were reached, and 3 of them were evaluated as part of the study according to inclusion criteria. Results were obtained by focusing on variables affecting ceiling glass effect perception, assessment tools used in studies and solutions suggested to break glass ceilings in academia. In general, it was found that very less known according glass ceiling effect perception in academia. Main findings show that main factors that are related to glass ceiling effect perception are opinion of women duties in family and business life, organisational policies, power distance and organisational factors that impede the rise of women in hierarchy. Systematic review of related studies has put forth scientific evidence on the importance of the problem. Since the academy is an area where women work intensively, the problem of ceiling glass effect perception of women working in academia should be studied in-depth
ICLR 2020 Higher-level Capsules Lower-level Capsules pose ... ... Agreement by Dot-Product Attention multiplication ∑ LayerNorm ( ⋅ ) routing   coefficients Pose UpdateRouting Coefficients as Normalized Agreement agreement weight matrix multiplication reshape ⋅ dot product ⊤

We introduce a new routing algorithm for capsule networks, in which a child capsule is routed to a parent based only on agreement between the parent’s state and the child’s vote. Unlike previously proposed routing algorithms, the parent’s ability to reconstruct the child is not explicitly taken into account to update the routing probabilities. This simplifies the routing procedure and improves performance on benchmark datasets such as CIFAR-10 and CIFAR-100. The new mechanism 1) designs routing via inverted dot-product attention; 2) imposes Layer Normalization as normalization; and 3) replaces sequential iterative routing with concurrent iterative routing. Besides outperforming existing capsule networks, our model performs at-par with a powerful CNN (ResNet-18), using less than 25% of the parameters. On a different task of recognizing digits from overlayed digit images, the proposed capsule model performs favorably against CNNs given the same number of layers and neurons per layer. We believe that our work raises the possibility of applying capsule networks to complex real-world tasks.
PROCRASTINATION AND FUTURE DISCOUNTING

Many studies examine delay discounting and procrastination independently in literature. The current study investigates for the relationship between procrastination and future discounting, unlike others. A difference between procrastinators and non-procrastinators in terms of their tendency to discount is also expected. Further, the response times of participants are expected to differ according to discount values (k values) that derived from each preference. Research was conducted with 104 undergraduates. The expected relations and differences were found to be statistically significant. The results shed light on the psychological correlations of participants’ discount rates and procrastination scores.
Transportation Research Record DATA DRIVEN REAL-TIME PLATFORM CROWDING PREDICTION USING AUTOMATED FARE COLLECTION AND VEHICLE LOCATION DATA IN URBAN RAILWAY SYSTEMS

Growing urbanization causes increase in crowding in many urban railway systems. Providing real-time crowding information would enable informed travel decisions and encourage cooperative behavior of passengers, as well as improve operating efficiency and safety. However, the problem of real-time crowding prediction is not trivial due to the unavailability of ground-truth crowding data. This paper proposes a data-driven approach for real-time platform crowding prediction in urban railway systems using automated fare collection (AFC) and automated vehicle location (AVL) data. The methodology aims to use the existing data-driven denied boarding estimation method to generate ground truth information and thus, extending the denied boarding framework into having predictive capabilities. The distribution of denied boarding probability is estimated by adopting the structured mixture model proposed in Ma et.al (19) using AFC and AVL data. Using these estimates, the real-time crowding prediction is formulated as a supervised learning problem with the denied boarding estimate as the response variable and explanatory variables extracted from AFC and AVL data, including characteristics of demand, operations, and disruptions. A Case study using Mass Transit Railway (MTR) data in Hong Kong is conducted to illustrate the effectiveness of the proposed methodology. The model is able to provide accurate platform crowding prediction in short-term using explanatory variables such as transfer demands and headways. Manuscript Classifications: Data and Information Technology; Urban Tranportation Big Data ABJ30SC; Big Data; Transformative Transit Data AP000; Smartcard; Transit Capacity and Quality of Service AP015; Capacity; Customer; Measuring; Service; Public Transportation; Rail Transit Systems (not Light, Freight, Commuter, or Highspeed) AP065; Passenger Information; Subway; Performance
Managerial Performance and Team Composition in International Soccer: Evidence from Jamaica

This paper uses data from 188 international matches played by the Jamaica national senior soccer team between 1995 and 2014 to examine the role of a variety of different factors on match performance. The econometric analysis is conducted using two match performance variables – goal difference and match result – and the regression models control for the identity of the coach, the composition of the national team, the quality of the Jamaica and opposition teams, disciplinary sanctions, the venue of the match as well as the fixture type. The results provide evidence of a variation in team performance across different national coaches however the presence of domestic league players in the national side exerts no independent effect on match outcome. In addition, the issuing of a red card to an opponent improves both goal difference and match outcome in Jamaica’s favour, as does playing lower ranked opponents on the basis of FIFA’s country rankings.
Social Behaviour in Games: Dynamic Identity in NPCs

The increasing use of virtual worlds in diverse areas such as entertainment, simulations and education, has not gone unnoticed by researchers and academics. With their wide application adding to the advancements in computational power, comes the interest to offer richer virtual environments that populated with agents allow a great variety of interesting social phenomena to be simulated. One of the current focal points to achieve that goal has been the agent’s identity. Due to its impact in human thoughts, feelings and behaviours, researchers have been focusing on identity and on the way it can contribute to believable and socially intelligent agents. However, many of these works do not assume identity as being dynamic, when in fact identity is known to have a great dependence on the social situation the individual is in. For that reason, we believe that a dynamic identity is especially important if the aim is to build socially believable agents with the ability to adjust their identity and decisions to the situation they are in. Thus, we present the Dynamic Identity Model for Agents.
⊙ Invert ⊙ = hadamard ⊙ ⊙ Invert BGNet Pose Encoder Appearance Encoder Foreground Decoder Apply color jittering Sample future frame 1 st Layer Feature maps Fit Gaussian Fit GaussianPose Encoder

Unsupervised landmark learning is the task of learning semantic keypoint-like representations without the use of expensive input keypoint-level annotations. A popular approach is to factorize an image into a pose and appearance data stream, then to reconstruct the image from the factorized components. The pose representation should capture a set of consistent and tightly localized landmarks in order to facilitate reconstruction of the input image. Ultimately, we wish for our learned landmarks to focus on the foreground object of interest. However, the reconstruction task of the entire image forces the model to allocate landmarks to model the background. This work explores the effects of factorizing the reconstruction task into separate foreground and background reconstructions, conditioning only the foreground reconstruction on the unsupervised landmarks. Our experiments demonstrate that the proposed factorization results in landmarks that are focused on the foreground object of interest. Furthermore, the rendered background quality is also improved, as the background rendering pipeline no longer requires the ill-suited landmarks to model its pose and appearance. We demonstrate this improvement in the context of the video-prediction task.
EXPLOITING SEMANTIC COHERENCE TO IMPROVE PREDICTION IN SATELLITE SCENE IMAGE ANALYSIS: APPLICATION TO DISEASE DENSITY ESTIMATION

High intra-class diversity and inter-class similarity is a characteristic of remote sensing scene image data sets currently posing significant difficulty for deep learning algorithms on classification tasks. To improve accuracy, post-classification methods have been proposed for smoothing results of model predictions. However, those approaches require an additional neural network to perform the smoothing operation, which adds overhead to the task. We propose an approach that involves learning deep features directly over neighboring scene images without requiring use of a cleanup model. Our approach utilizes a siamese network to improve the discriminative power of convolutional neural networks on a pair of neighboring scene images. It then exploits semantic coherence between this pair to enrich the feature vector of the image for which we want to predict a label. Empirical results show that this approach provides a viable alternative to existing methods. For example, our model improved prediction accuracy by 1 percentage point and dropped the mean squared error value by 0.02 over the baseline, on a disease density estimation task. These performance gains are comparable with results from existing post-classification methods, moreover without implementation overheads.
Transcriptomic, proteomic and phenotypic analysis of the Vibrio campbellii stationary phase alternative sigma factors RpoS1 and RpoS2

1 Center for Bio/Molecular Science & Engineering, Naval Research Laboratory, Washington DC 20375 (gary.vora@nrl.navy.mil) 2 Department of Mathematics, Whittier College, Whittier, CA 90608 (brubin698@gmail.com) 3 Center for Strategic Scientific Initiatives, National Institutes of Health, Bethesda, MD 20892 (rahbaram@mail.nih.gov) 4 National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892 (thachdc@niaid.nih.gov)
A MODIFIED THEORY OF COMPOSITE MECHANICS TO PREDICT TENSILE MODULUS OF RESINATED WOOD

In this work, a modified theory (model) of composite mechanics was developed to predict the tensile modulus of elasticity (MOE) of resinated wood with the consideration of glue penetration. Variables built into the model included species, glue solids spread (GS), wood thickness and compression ratio (CR). The results showed that the effect of glue on the wood tensile MOE differed from species to species. With the increase of glue dosage, thOE first increased linearly and then leveled off at a threshold level of GS. Further increase of glue dosage made the MOE exhibit either a small increase or a decrease depending on the wood and glue properties. With a normal range of GS (50 to 90 g.m-2), the effect of glue on the wood tensile MOE became negligible if wood thickness was larger than 1.4 mm. Also, an increase in CR resulted in a predictable increase of the wood MOE. The model prediction showed a good agreement with the published experimental results. Further validation of the model is underway.
OP-EUPA180177 1..27

the management of antithrombotic therapy in atrial fibrillation patients presenting with acute coronary syndrome and/or undergoing percutaneous cardiovascular interventions: a joint consensus document of the European Heart Rhythm Association (EHRA), European Society of Cardiology Working Group on Thrombosis, European Association of Percutaneous Cardiovascular Interventions (EAPCI), and European Association of Acute Cardiac Care (ACCA) endorsed by the Heart Rhythm Society (HRS), Asia-Pacific Heart Rhythm Society (APHRS), Latin America Heart Rhythm Society (LAHRS), and Cardiac Arrhythmia Society of Southern Africa (CASSA) Gregory Y.H. Lip (Chair)*, Jean-Phillippe Collet (Co-Chair), Michael Haude (Co-Chair), Robert Byrne, Eugene H. Chung, Laurent Fauchier, Sigrun Halvorsen, Dennis Lau, Nestor Lopez-Cabanillas, Maddalena Lettino, Francisco Marin, Israel Obel, Andrea Rubboli, Robert F. Storey, Marco Valgimigli, and Kurt Huber (Co-Chair)
Nanoscale science and nanotechnology education in Africa: importance and challenges

Nanoscale science and nanotechnology is a rapidly growing and multidisciplinary field with its footing in chemistry, physics, molecular biology and engineering. It has led to breakthroughs in energy, environmental science, agriculture, biotechnology and several others. it is also capable of making a positive and significant impact on the African continent. However, nanotechnology training and education in Africa appears to be scarce even within its contributory fields like chemistry and physics. A thorough, relevant and comprehensive nanotechnology education across informal and formal lines and at all levels of education is required to develop human capacity and assist the continent respond appropriately to career/business/development opportunities, risks and policy challenges that would arise from present and emerging nanotechnologies.
The relationship between the farmer, researcher and the extension advisor / La relación entre el agricultor, el investigador y el asesor de extensión

The philosophy of extension is to: “Help farmers to help themselves”. Extension approaches have evolved from linear to advisory models, which focused mainly on transfer of technology with limited interaction between role players. Modern extension approaches include facilitation and participatory models that encourage interaction amongst all role players. Previously the South African Avocado Growers Association’s (SAAGA) extension advisors served their members according to an advisory extension approach. During 2006, the Subtrop amalgamation took place, which is an umbrella organization that manages the affairs of SAAGA, SAMAC (SA Macadamia Growers Association), SAMGA (SA Mango Growers Association) and SALGA (SA Litchi Growers Association). In 2010, after the Subtrop amalgamation, a farmer satisfaction survey on extension services and research coordination functions was conducted. A structured questionnaire was developed with open and closed questions using Likert-Type scale response anchors. Survey participants had to indicate their perception and utilization of the following main extension services: farm visits, newsletters, study groups and relevant websites. Avocado farmer were also asked a) what their expectations were from the extension advisors, b) the relevance of advisors as well as the interaction and role of and between extension advisors, researchers and farmers. Suggestions to improve extension services are suggested and the role of the farmer in the research environment is highlighted.
Effects of Eye Acupuncture on Learning Disorder and Dysmnesia,and Blood Rheologic Characteristics in the Rats with Vascular Dementia

Objective:To investigate the effects of eye acupuncture on learning disorder and dysmnesia,and blood rheologic characteristics in rats with vascular dementia.Methods:A rat model of vascular dementia was made by 4–vessel occulusion.The liver,heart and kidney areas were selected for eye acupuncture.The treatment lasted 30 days.Western medicine Nimoton was used as a control.A Y type maze test and the blood rheologic characteristics was performed before and after the experiment.Results:Learning disorder and dysmnesia were obvious in the model group as compared with the control group as compared with the control group.In the eye acupuncture and medication group of vascular dementia rats,learning disorder and dysmnesia were significantly abated as compared with the model group(P0.01). Compared with the rheologic characteristics of model and control group,the modeling group's blood became densier and sticker(P0.01). In the eye acupuncture and medication groups of vascular dementia rats,the blood became fluencier,and the changes of the blood rheologic characteristics were significantly abated as compared with model group(P0.01～0.05). Conclusion:Eye acupuncture can produce an improving effect on learning disorder and dysmnesia,and changes the blood rheologic characteristics in experimental vascular dementia rats.
Psychosocial Risk Factors: its Relation with Social Cognition, Emotional Regulation and Well-Being

Abstract. In Colombia, an increase of suicidal behavior in adolescents caused by personal and environmental factors is evidenced. This quantitative, descriptive, correlational research aimed to establish the existing relationship between social cognition, perception of the quality of relationships and emotional regulation with the variables of psychosocial risk, suicide risk and level of psychological well-being in adolescents in contexts of high socioeconomic vulnerability of Bogotá. A total of 155 adolescents were selected through non-probabilistic sampling at convenience, with ages between 13 and 17 years (M = 14.47 and DE = 1.03). The results allowed observing the existence of significant relationships between the study variables. From a linear regression analysis, the emotional bond and emotional self-regulation had a higher level of explanation about the perception of well-being and the psychosocial risk associated with suicide. Finally, the results and implications of a greater participation of the emotional bond in comparison to that of social cognition in adolescence are discussed, in order to formulate programs that promote well-being and prevent risk.
Multiconcept Methods to Enhance Photovoltaic System Efficiency

The main goal of this paper is to review the most important methods previously developed to enhance the efficiency and increase the lifetime of photovoltaic panels. The methods to increase the solar radiation incident on photovoltaic panels, as well as the cooling and the maximum power point tracker methods, are concisely presented in this paper. The pros and cons analysis reveals that the methods to enhance the power generated by the photovoltaic panels are strongly dependent on geographical location, climatic conditions, and the materials used. This review paper is also of interest for engineers who attempt to identify the most adequate solutions to maximize the energy output of photovoltaic systems for each location.
Aalborg Universitet Electromyography Evaluation of Bodyweight Exercise Progression in a Validated Anterior Cruciate Ligament Injury Rehabilitation Program A Cross-Sectional Study

Citation for published version (APA): Zebis, M. K. , Sørensen, M. H. , Lauridsen, H. B. , Bencke, J., Andersen, C. H. , Carlsbæk, J. B. , . Andersen, L. L. (2019). Electromyography Evaluation of Bodyweight Exercise Progression in a Validated Anterior Cruciate Ligament Injury Rehabilitation Program: A Cross-Sectional Study. American Journal of Physical Medicine and Rehabilitation, 98(11), 998-1004. https://doi.org/10.1097/PHM.0000000000001232