Miracle-dz/UniFAR-FTUs huggingface dataset:
Drivers of the green supply chain initiatives: Evidence from Indonesian automotive industry

Article history: Received July 12, 2019 Received in revised format July 24, 2019 Accepted August 2 2019 Available online August 3 2019 Global warming, resource depletion, rising temperature, air pollution, and other environmental issues have raised several questions regarding the environmental effects of organizations. Thus, the organizations have started to pay attention on their processes. Bearing in mind the importance of ongoing environmental issues, the present study tries to elaborate the role of key drivers due to which the organizations go for adoption of green initiatives. This study considers the supply chain processes as a point of concern. Competitor pressure, customer pressure, regulatory measures (ISO 140001 etc.) and socio-cultural responsibility are the key drivers. Data are collected from the employees who were working in the automotive industry related companies in Indonesia by adopting the simple random sampling. 300 questionnaires are distributed among the employees out of which 200 valid responses are used for data analysis. Smart-PLS is used for data analysis. As per the results of the study the regulatory measures significantly and positively influence the green supply chain initiatives of the automotive car manufacturers. The results of the study also report a positive significant relationship between competitor pressure and green supply chain initiatives. Green supply chain initiatives are also found to be positively influence by the customer pressure. Finally, the study also reports a positive significant influence of socio-cultural responsibility on the green supply chain initiatives. Socio-cultural responsibility is found to be the strongest predictor of green supply chain initiatives. Practical implications and future directions are also provided at the end of the study. by the authors; licensee Growing Science, Canada 20 20 ©
Context-Aware Learning to Rank with Self-Attention

Learning to rank is a key component of many e-commerce search engines. In learning to rank, one is interested in optimising the global ordering of a list of items according to their utility for users.Popular approaches learn a scoring function that scores items individually (i.e. without the context of other items in the list) by optimising a pointwise, pairwise or listwise loss. The list is then sorted in the descending order of the scores. Possible interactions between items present in the same list are taken into account in the training phase at the loss level. However, during inference, items are scored individually, and possible interactions between them are not considered. In this paper, we propose a context-aware neural network model that learns item scores by applying a self-attention mechanism. The relevance of a given item is thus determined in the context of all other items present in the list, both in training and in inference. We empirically demonstrate significant performance gains of self-attention based neural architecture over Multi-LayerPerceptron baselines, in particular on a dataset coming from search logs of a large scale e-commerce marketplace, this http URL. This effect is consistent across popular pointwise, pairwise and listwise losses.Finally, we report new state-of-the-art results on MSLR-WEB30K, the learning to rank benchmark.
Challenges Companies Encounter When Delivering Sustainable Solutions: Research Conducted in the United Arab Emirates

The purpose of this article is to draw attention to the challenges faced by business organizations implementing sustainable solutions in the United Arab Emirates (UAE) and the wider Gulf Coast Countries (GCC) region. To this end, our study examines an academic theory supporting the implementation of responsible solutions to the market. Ultimately, the authors hope to inspire the reader to consider what he or she can do to ameliorate the existing challenges encountered by sustainable businesses. The analysis presented in this article implies that in recent markets, the implementation of the sustainability theory is essential for further development. The research project contributes to the increase of knowledge about corporate and organizational challenges related to running a responsible business, as well as challenges related to the application of environmental, social and economic aspects of sustainable business practices. The research is currently limited to conceptual analysis, literature review and a survey conducted during the Sustainability Week 2019 in Abu Dhabi, United Arab Emirates. Nevertheless, this is the first stage of the research project conducted by the research team in cooperation with enterprises that implement responsible solutions in many global markets, and in UAE market. The scope of the first stage of the study was limited to the analysis of data clarifying the concept of the model specified in the research. To prove the validity of the model it will be implemented and tested in cooperation with organizations participating in the research.
ALGORITHM VISUALIZATION USING THE VIZALGO PLATFORM

Algorithms are central objects of every nontrivial computer application. Every programmer thus should have basic knowledge from the area of algorithm design in order to work more effectively. Simplifying and deepening the understanding of algorithms operation is the main goal of algorithm visualization. There is active research and development in the area of algorithm visualization in the last decades. Solutions of different quality and serving different purposes are available nowadays, but often it is not an easy task to modify or extend the particular solution to meet specific needs exactly. The paper contains concise overview of development in the area of software visualization, as well as a proposal of software visualization platform with the emphasis on its extensibility and portability.
Modeling Homogeneity Detection in Primate Visual Cortex with Spiking Neurons Diplomarbeit

Beginning with the work of Hubel & Wiesel (1962), the representation of retinal input in V1 has mostly been thought of being dominated by luminance-contrastor color-contrast-edges. However, Komatsu et al. (1996) show that some cells in V1 also respond to diffuse illumination of their receptive field, which conflicts with the classical view of receptive fields in V1. Based on these findings, Gewaltig et al. (2002) presented a model for surface detection, which the present work is based on. Surfaces, or homogeneous image areas, are defined as areas with low intensity variance. While the model by Gewaltig et al. inherently uses a rate code, the model presented in this work uses a network of spiking neurons to detect homogeneous areas. Moreover, it uses only one spike per neuron and processing stage, thus fulfilling the timing constraints of rapid feed-forward processing, as postulated by Thorpe et al. (1996). Given the evidence that information about homogeneous image regions is present in the visual cortex, the question arises how the cortex might achieve homogeneity detection, and which thalamic and cortical areas could be involved. The present work provides an hypothesis addressing this question. Further, it is demonstrated what benefits for visual processing can be drawn from information about homogeneous image areas.
Anti-hyperglycemic effect of Vicia ervilia (L.) Willd (Fabaceae) seed extract and its effect on lipid profile, and hepatic and renal biomarkers in streptozotocin-induced diabetic rats

Purpose: To evaluate the impact of Vicia ervilia (L.) Willd (Fabaceae) lyophilized extract on various biomarkers of streptozotocin-induced diabetic rats. Methods: Adult male rats (36) were divided into 6 groups, viz, normal control (NC), diabetes control (DC), and treatment groups. Experimental diabetes was induced with streptozotocin. Blood samples were taken from the tail veins daily for 25 days. Fasting and postprandial blood glucose levels of rats were determined. The rats were sacrificed and blood, kidney and liver were taken for biochemical analysis. Results: Blood glucose decreased in DC groups compared to NC group (p ≤ 0.05). In diabetic extract groups, glycated Hb decreased compared to DC group (p ≤ 0.05). Alpha glucosidase activity was reduced in all treatment groups compared to DC group (p ≤ 0.05). Only triglyceride levels of diabetes extract (400 mg/mL) group decreased compared to DC (p ≤ 0.05). Total cholesterol levels fell compared to NC and DC groups (p ≤ 0.05). Low density lipoprotein was lower compared to NC (p ≤ 0.05), while aspartate aminotransferase and alanine aminotransferase levels rose in diabetic extract groups compared to NC, but fell in some diabetic extract groups compared to DC group (p ≤ 0.05). Lactate dehydrogenase decreased in all diabetic extract groups compared to NC and DC (p ≤ 0.05). Serum urea and creatinine levels were higher in diabetic extract groups compared to NC, but decreased in DC group (p ≤ 0.05). Conclusion: These findings demonstrate that Vicia ervilia lyophilized extract haas positive effects on blood glucose and biochemical parameters in diabetic rats compared to DC of V. ervilia seed extract.
IN SEARCH OF FUNCTIONAL MODELS OF PSYCHOLOGICAL PFJCESS

This paper emphasizes the need to go beyond structural models of personality and intellect to develop sequential models of psychological process, particularly for such complex phenomena of prime concern to theory and application as learning, problem solving, and creativity. It is further argued that factor analysis, in a multitude of studies of cognition and personality over the past fifty years, has already delineated many relevant process variables that might serve as components in these sequential models. Beyond Structure: In Search of Functional Models of Psychological Process 1 Silvan Tomkins (1962) once remarked that it seemed to him. that human personality was "organized as a language is organized, with elements of varying degrees of complexity--from letters, words, phrases, and sentences to styles--and with a set of rules of combination which enable the generation of both endless novelty and the very high order of redundancy which we call style. " He went on to note that "if we had to be blind about one or the other of these types of components, we should sacrifice the elements for the rules," although "factor analysis appears to have made the opposite decision. It would tell what letters, or words, or phrases, or even styles were invariant and characteristic of a personality or of a number of personalities," but by itself it does not and cannot "generate the rules of combination which together with the elements constitute personality" (Tomkins, 1962, p. 287). The use of language as a prototype for psychological functioning is not new. Lashley (1951), for example, pointed to the generality of the problem of syntax. He maintained that most processes of both thought and action were sequential, thereby entailing an essential problem of serial order--not just of elements but of hierarchies of organization (e.g., the order of vocal movements in pronouncing a word, the order of words in a sentence, the order of sentences in a paragraph, the order of paragraphs in a rational discourse). One of the most critical tasks for psych logy is to explicate the syntax of thought and of behavior,
Akdeniz İ.İ.B.F. Dergisi (26) 2013, 55-76 GÖSTERGE FAİZ ORANI, DIŞ TİCARET HACMİ VE İÇ BORÇ STOK İLİŞKİSİ INTERACTIONS OF BENCHMARK INTEREST RATE, FOREIGN TRADE VOLUME, AND DOMESTIC DEBT STOCK

Concerns about the sustainability of public debt reduce efficiency of the transmission mechanism in emerging economies owing to high and volatile risk premiums. Moreover, the interaction between the interest rate and foreign trade volume affects the economy, depending on the valuation of the national currency. This article attempts to identify the longand short-term dynamic relationships among domestic debt stock, foreign trade volume, and benchmark interest rate in Turkey. These dynamic relationships provide information about the economic structure to market participants. This article also explains the impact of these variables on interest rates within the framework of various schools on economic thought.
ONGOING GENETIC CONNECTIVITY

iii Part 1. Project Summary and Discussion . 1 Project Objectives . 1 Primary Contact . 1 Project Background And Rationale . 2 Methods . 6 Results and Discussion . 7 References . Error! Bookmark not defined. Summary of Expenditures . 9 Part 2. Manuscript 1: Population Genetic Diversity and Structure of the Riparian Brush Rabbit (Sylvilagus bachmani riparius) . 10 Introduction . 10 Methods . 12 Results . 14 Discussion.21 Part 3. Manuscript 2: Evaluating the Range-Wide Functional and Structural Connectivity of an Endangered Habitat Specialist, the Riparian Brush Rabbit (Sylvilagus bachmani riparius) . 23 Introduction . 23 Materials and Methods . 24 Results . 26 Discussion.35 Literature Cited . 36 Appendix A. Glossary of Terms . 41
NDT_A_120514 1873..1885

Maëlle Biotteau 1 Jérémy Danna 2 Éloïse Baudou 3 Frédéric Puyjarinet 4 Jean-Luc Velay 2 Jean-Michel Albaret 1,5 Yves Chaix 1,3 1ToNIC, Toulouse NeuroImaging Center, University of Toulouse, Inserm, UPS, Toulouse, France; 2Cognitive Neurosciences Laboratory, CNRS-Aix Marseille University, Marseille, France; 3Pediatric Neurology Unit, Children’s Hospital, Purpan University Hospital, Toulouse, France; 4EuroMov Laboratory, University of Montpellier, Montpellier, France; 5Psychomotor Training Institute, University of Toulouse Paul Sabatier, Toulouse, France Abstract: Developmental coordination disorder (DCD) is a common and well-recognized neurodevelopmental disorder affecting approximately 5 in every 100 individuals worldwide. It has long been included in standard national and international classifications of disorders (especially the Diagnostic and Statistical Manual of Mental Disorders). Children and adults with DCD may come to medical or paramedical attention because of poor motor skills, poor motor coordination, and/or impaired procedural learning affecting activities of daily living. Studies show DCD persistence of 30–70% in adulthood for individuals who were diagnosed with DCD as children, with direct consequences in the academic realm and even beyond. In particular, individuals with DCD are at increased risk of impaired handwriting skills.Medium-term and long-term prognosis depends on the timing of the diagnosis, (possible) comorbid disorders (and their diagnosis), the variability of signs and symptoms (number and intensity), and the nature and frequency of the interventions individuals receive. We therefore chose to investigate the signs and symptoms, diagnosis, and rehabilitation of both DCD and developmental dysgraphia, which continues to receive far too little attention in its own right from researchers and clinicians.
Detection of U.S. Traffic Signs

This paper presents a comprehensive research study of the detection of U.S. traffic signs. Until now, the research in Traffic Sign Recognition systems has been centered on European traffic signs, but signs can look very different across different parts of the world, and a system that works well in Europe may indeed not work in the U.S. We go over the recent advances in traffic sign detection and discuss the differences in signs across the world. Then we present a comprehensive extension to the publicly available LISA-TS traffic sign data set, almost doubling its size, now with high-definition-quality footage. The extension is made with testing of tracking sign detection systems in mind, providing videos of traffic sign passes. We apply the Integral Channel Features and Aggregate Channel Features detection methods to U.S. traffic signs and show performance numbers outperforming all previous research on U.S. signs (while also performing similarly to the state of the art on European signs). Integral Channel Features have previously been used successfully for European signs, whereas Aggregate Channel Features have never been applied to the field of traffic signs. We take a look at the performance differences between the two methods and analyze how they perform on very distinctive signs, as well as white, rectangular signs, which tend to blend into their environment.
Predictive And Prognostic Value Of Hepatic Steatosis In Conversion Therapy For Colorectal Liver-limited Metastases: A Propensity Score Matching Analysis

Purpose To evaluate the role of hepatic steatosis (HS) in patients with synchronous colorectal liver-limited metastases (CLLMs) undergoing conversion therapy. Patients and methods From March 2013 to March 2017, a total of 406 patients with initially unresectable CLLMs accepted conversion therapy in multidisciplinary team (MDT). Before the implementation of conversion therapy, all patients underwent CT scan to assess the presence of hepatic steatosis and divided into the HS group (n = 124) and the non-HS group (n = 282). After using propensity score matching (PSM) to eliminate the potential confounding bias of the two groups, the conversion hepatectomy rate and long-term oncological survival in two groups were compared. Results After 1:1 PSM, no significant difference was observed at baseline between patients in the HS group (n = 119) and the non-HS group (n = 119). Patients in the HS group had higher conversion hepatectomy rate from MDT evaluation (31.1% vs 18.5%, P = 0.029) and actual hepatectomy rate (30.2% vs 18.5%, P = 0.030), when compared with patients in the non-HS group, respectively. In addition, the HS group achieved better progression-free survival (PFS, P = 0.047) and overall survival (OS, P = 0.035) than that of the non-HS group. Multivariate logistic analysis confirmed that pretreatment HS was an independent predictor for conversion hepatectomy rate (OR, 2.393; 95% CI, 1.463–4.315, P = 0.001), and multivariate Cox analysis revealed that HS was an independent prognostic factor for PFS (HR, 0.493, 95% CI 0.281–0.866, P = 0.014) and OS (HR, 0.559, 95% CI 0.398–0.785, P = 0.001). Conclusion For CLLM patients who underwent conversion therapy, hepatic steatosis could be an effective predictor for conversion hepatectomy rate and an independent prognostic factor for PFS and OS.
Intelligent Algorithm for Efficient Use of Energy Using Tackling the Load Uncertainty Method in Smart Grid

In this paper, i am developing a unique optimization based real time inland load management algorithm that takes into account load ambiguity in order to minimize the energy payment for each residential user, as well as reduce the peak to average ratio to overcome the drawbacks in the stability of electrical grid. By categorizing the all residential load in different classes, i.e. must run, interruptible and uninterruptible appliances, i used the real time pricing scheme for load management. However, real time pricing creates the peak profiles when the energy demand is too high, that’s why i used the combination of real time pricing and inclining blocks rates model to improve the grid stability by reducing the peak to average ratio. A simulation results show that the proposed algorithm efficiently and effectively reduced the overall residential energy cost as well as peak to average ratio of our model for data provided.
A narrative inquiry into the induction and mentoring experiences of overseas trained teachers in South Auckland special need schools

i Acknowledgements ii Dedication iii Attestation of Authorship iv Quotation v List of Tables vi List of Abbreviations vii Table of Content viii Chapter Overviews xiii Setting the Scene p. 1 CHAPTER ONE PREAMBLE In the Beginning p. 2 Summary p. 10 CHAPTER TWO INTRODUCTION Overview p. 11 Statement of the problem situation p. 13 Purpose of the study p. 14 Rationale p. 15 Importance of the study p. 17 Summary p. 18
Variations in plasma lipids and lipoproteins among cardiovascular disease patients in South-western Nigerians

This study was designed to assess the changes in plasma lipids and lipoproteins, in particular highdensity lipoprotein (HDLC) in patients suffering from different types of cardiovascular disease (CVD) in Southwestern Nigeria. Patients were drawn from different socioeconomic classes in order to determine the effect of this factor on CVD in Nigeria. One hundred and seventy (74 males, 96 females) CVD patients (hypertensive heart disease (n=48), hypertension (n=59), ischaemic heart disease (n=49), myocardial infarction (n=4)) with a mean age of 45.3±13.2 years were selected. Fifty-eight individuals (31 males and 27 female) with mean age of 44.8±11.7 years were included as controls. Result showed significant increases in mean plasma total cholesterol (TC) (P < 0.05), triglyceride and low density lipoproteins (LDLC) (P < 0.01), LDLC: HDLC (p < 0.001), as well as in systolic and diastolic blood pressures (p < 0.001), while plasma HDLC (p < 0.01) and HDLC:TC (p < 0.001) showed significant decreases when compared with the corresponding mean control values. There were graded decreases in plasma HDLC in the different socioeconomic classes. The lowest mean plasma HDLC was found in IHD patients. This study has uncovered variations in plasma lipids and lipoproteins among patients of CVD within the different socioeconomic classes in South-western Nigeria. Keywords: HDL cholesterol, cardiovascular disease, plasma lipids and lipoproteins, South-western Nigeria.
Leukocyte-Released Mediators in Response to Both Bacterial and Fungal Infections Trigger IFN Pathways, Independent of IL-1 and TNF-α, in Endothelial Cells

In sepsis, dysregulated immune responses to infections cause damage to the host. Previous studies have attempted to capture pathogen-induced leukocyte responses. However, the impact of mediators released after pathogen-leukocyte interaction on endothelial cells, and how endothelial cell responses vary depending on the pathogen-type is lacking. Here, we comprehensively characterized the transcriptomic responses of human leukocytes and endothelial cells to Gram negative-bacteria, Gram positive-bacteria, and fungi. We showed that whole pathogen lysates induced strong activation of leukocytes but not endothelial cells. Interestingly, the common response of leukocytes to various pathogens converges on endothelial activation. By exposing endothelial cells to leukocyte-released mediators, we observed a strong activation of endothelial cells at both transcription and protein levels. By adding IL-1RA and TNF-α antibody in leukocyte-released mediators before exposing to endothelial cells, we identified specific roles for IL-1 and TNF-α in driving the most, but not all, endothelial activation. We also showed for the first time, activation of interferon response by endothelial cells in response to leukocyte-released mediators, independently from IL-1 and TNF-α pathways. Our study therefore, not only provides pathogen-dependent transcriptional changes in leukocytes and endothelial cells during infections, but also reveals a role for IFN, together with IL1 and TNFα signaling, in mediating leukocyte-endothelial interaction in infections.
Transcranial Current Stimulation Alters the Expression of Immune-Mediating Genes

Despite its extensive use in clinical studies, the molecular mechanisms underlying the effects of transcranial direct current stimulation (tDCS) remain to be elucidated. We previously described subacute effects of tDCS on immune- and stem cells in the rat brain. To investigate the more immediate effects of tDCS regulating those cellular responses, we treated rats with a single session of either anodal or cathodal tDCS, and analyzed the gene expression by microarray; sham-stimulated rats served as control. Anodal tDCS increased expression of several genes coding for the major histocompatibility complex I (MHC I), while cathodal tDCS increased the expression of the immunoregulatory protein osteopontin (OPN). We confirmed the effects of gene upregulation by immunohistochemistry at the protein level. Thus, our data show a novel mechanism for the actions of tDCS on immune- and inflammatory processes, providing a target for future therapeutic studies.