Miracle-dz/UniFAR-FTUs huggingface dataset:
Work engagement in the mining industry in South Africa: The role of tasks and relationships

The platinum mining sector in South Africa presents a significant context for the study of work engagement, given the major changes and turmoil experienced by employees in this sector. The aim of this study was to investigate the effects of task and relational factors on work engagement in the platinum mining industry in South Africa. A stratified random sample (N = 564) comprising employees in a platinum mining organisation in South Africa was surveyed (females = 35.1%, blacks = 51.6%, middle managers = 40.8%). The employees completed a biographical questionnaire and several other measures: the Engagement Scale, Supervisory Support Scale, Social Support Scale and Job Diagnostic Survey. The results supported a reliable three-factor structure (consisting of autonomy support, competence support, and relatedness support) for the Supervisory Support Scale. The structural model confirmed that task characteristics (comprising task significance and task identity) were strongly related to work engagement. Supervisor support and co-worker support showed a positive relationship with work engagement, albeit to a lesser extent.
The research on the coupling development between IT policy and industry

The information industry can stimulate economic growth and create enormous social wealth. This paper analysis the integral part of China's information industry. At the same time, this paper researches its development status. Combining the characteristics of information industry, we find out the inadequacies of the information industrial policy. At last, this paper provides kinds of policy to promote the development of information industry.
Critical success factors for eLearning in Saudi Arabian universities

Purpose The purpose of this paper is to offer insights into the development of eLearning systems and the perceptions of key players in the management of eLearning systems in three large universities in Saudi Arabia. It establishes the relative importance of different factors and compares these findings with studies conducted elsewhere in the world. Design/methodology/approach Desk research was conducted to gather a profile of the eLearning initiatives in the participating universities. Structured interviews were conducted with senior managers with responsibility for implementing and promoting eLearning in their universities. The interview protocol prompted discussion of the importance of the following sets of factors in the success and acceptance of eLearning: student characteristics, instructor characteristics, learning environment, instructional design, and support. Interviews were transcribed and analysed using thematic analysis. Findings Supported by the Saudi Government, the three universities in this study have been developing their eLearning services. The two most important groups of critical success factors in this process were regarded as those related to student and instructor characteristics. Further analysis within each group of factors suggested that participants regarded instructor knowledge with learning technologies and student knowledge of computer systems, and technical infrastructure as important facilitators of success. Amongst instructional design factors, clarity of learning objectives and content quality were regarded as important. Insights are offered as to the reasons for these selections. Originality/value This study furthers earlier research on eLearning managers’ views and contributes to understanding of eLearning and its management in the Middle East.
Mitochondrial and Metabolic Dysfunction in Renal Convoluted Tubules of Obese Mice: Protective Role of Melatonin

Obesity is a common and complex health problem, which impacts crucial organs; it is also considered an independent risk factor for chronic kidney disease. Few studies have analyzed the consequence of obesity in the renal proximal convoluted tubules, which are the major tubules involved in reabsorptive processes. For optimal performance of the kidney, energy is primarily provided by mitochondria. Melatonin, an indoleamine and antioxidant, has been identified in mitochondria, and there is considerable evidence regarding its essential role in the prevention of oxidative mitochondrial damage. In this study we evaluated the mechanism(s) of mitochondrial alterations in an animal model of obesity (ob/ob mice) and describe the beneficial effects of melatonin treatment on mitochondrial morphology and dynamics as influenced by mitofusin-2 and the intrinsic apoptotic cascade. Melatonin dissolved in 1% ethanol was added to the drinking water from postnatal week 5–13; the calculated dose of melatonin intake was 100 mg/kg body weight/day. Compared to control mice, obesity-related morphological alterations were apparent in the proximal tubules which contained round mitochondria with irregular, short cristae and cells with elevated apoptotic index. Melatonin supplementation in obese mice changed mitochondria shape and cristae organization of proximal tubules, enhanced mitofusin-2 expression, which in turn modulated the progression of the mitochondria-driven intrinsic apoptotic pathway. These changes possibly aid in reducing renal failure. The melatonin-mediated changes indicate its potential protective use against renal morphological damage and dysfunction associated with obesity and metabolic disease.
Inferring and visualizing topological structures of large-scale complex network

Many information and communications networks are very large and they exhibit extremely complex structures. Here we propose a topology visualisation tool, called the bitmap of sorted adjacency matrix (BOSAM), which illustrates the connectivity information of a network as a bitmap image. We show that by using carefully designed rules to sort network node in specific orders, the produced bitmaps are able to reveal interesting patterns associated with the network structures. This simple tool can facilitate the study on characterising and modelling large-scale complex networks such as the Internet and peer-to-peer (P2P) networks.
A Supervised Learning Approach to Musical Style Recognition

Musical style recognition is somehow intrinsic to human nature: the average layperson can tell the difference between a motet by Josquin and a symphony by Beethoven. But things change when it comes to computers. Musical style and its transformations take place in ways musicology is still unable perfectly to define. Up to now, computer-aided research on style has greatly privileged the rule-based approach (Baroni Dalmonte and Jacoboni, Lerdahl and Jackendoff, Ebcioglu, etc.). In this paper we use a supervised learning approach to create a “style recognizer” which is able to expose genre-attributable differences both within Palestrina’s music (how is a mass different from a motet or a madrigal) and between Palestrina and other composers (either contemporary or younger/older). Our recognizer is implemented using a back-propagation neural network, with a number of innovative techniques to account for the special nature of musical input. Our technique makes no assumptions about the period or style of music being studied, but our experiments have focused on Palestrina. Results are promising: our technique seems to possess those generalization capabilities which are essential when dealing with a matter of such proteiform complexity as musical style.
A compression layer for NAND type flash memory systems

Storage devices of embedded systems must have the characteristics of small size, great capacity, low-power consumption, lightweight, non-volatility, and vibration resistance. The NAND type flash memory, briefly denoted by NandFlash, is one of the more often-used storage devices. In terms of unit price, its cost is several dozen to hundred times more expensive than the traditional hard-disk (HD) since its storage space is limited. Therefore, to increase the storage space of NandFlash is great significance. In this paper, we improved the compression layer for NandFlash, which can be coordinated with the X-RL algorithm, to avoid overhead and reduce the degree of internal fragmentation in the compressed data pages. Hence, our proposed method can improve the compression rate. In the reading phase, we use the consecutive memory allocation method, which can reduce the superfluous time caused by non-consecutive access. Therefore, our architecture is meaningful and practical for embedded system applications.
Imaging with terahertz radiation

Within the last several years, the field of terahertz science and technology has changed dramatically. Many new advances in the technology for generation, manipulation, and detection of terahertz radiation have revolutionized the field. Much of this interest has been inspired by the promise of valuable new applications for terahertz imaging and sensing. Among a long list of proposed uses, one finds compelling needs such as security screening and quality control, as well as whimsical notions such as counting the almonds in a bar of chocolate. This list has grown in parallel with the development of new technologies and new paradigms for imaging and sensing. Many of these proposed applications exploit the unique capabilities of terahertz radiation to penetrate common packaging materials and provide spectroscopic information about the materials within. Several of the techniques used for terahertz imaging have been borrowed from other, more well established fields such as x-ray computed tomography and synthetic aperture radar. Others have been developed exclusively for the terahertz field, and have no analogies in other portions of the spectrum. This review provides a comprehensive description of the various techniques which have been employed for terahertz image formation, as well as discussing numerous examples which illustrate the many exciting potential uses for these emerging technologies.
Inclusion of South American samples reveals new population structuring of the blacktip shark (Carcharhinus limbatus) in the western Atlantic

Carcharhinus limbatus has a cosmopolitan distribution and marked genetic structuring, mainly because of its philopatric behavior. However, analysis of this structuring has not previously included South American populations. In the present study, we analyzed a sample of adult individuals collected on the northern coast of Brazil and compared the sequences of the mitochondrial control region with those of populations already genotyped. Relatively high haplotype diversity (12 haplotypes, genetic diversity of 0.796) was observed, similar to that in other populations but with a much larger number of private alleles. In contrast to populations studied previously, which were represented by neonates, the pronounced allelic variability found in the South American individuals may have resulted from migrations from other populations in the region that have yet to be genotyped. This population was also genetically distinct from the other Atlantic populations (Fst > 0.8), probably because of female philopatry, and apparently separated from the northwestern Atlantic group 1.39 million years ago. These findings indicate that the C. limbatus population from northern Brazil is genetically distinct from all other populations and should be considered as a different management unit for the protection of stocks.
POI recommendation with geographical and multi-tag influences

In this paper, we propose a method for point of interest (POI) recommendation by extracting the multi-tag influence and modeling the geographical influence. First of all, we extract a user-tag matrix from the initial user-POI rating matrix by analyzing the relations between POI and the related bag of tags. Secondly, we use the probabilistic factor model to predict the missing data of the extracted matrix. Thirdly, an effective method to model the geographical influence is proposed by considering the location of user and POI and the related region center. Finally, the multi-tag and geographical influence are fused in the process of making prediction of missing value of every POI. Then we will get a great result for POI recommendation. The experimental analysis on the large dataset Yelp demonstrates that our method outperform the state-of-art methods.
MICROMACHINED HEAT EXCHANGER FOR A CRYOSURGICAL PROBE

This paper describes a lithography-based microfabrication process developed for a recuperative heat exchanger intended for use in a cryosurgical probe. The probe, which uses the Joule-Thomson (JT) cooling cycle, must achieve a temperature < -50°C, with a freeze rate of 25-50°C/min. The heat exchanger must maintain high stream-to-stream thermal conductance while restricting parasitic stream-wise (axial) conduction losses. It has a footprint of 6x1.5cm 2 and 2.5mm thickness, and is fabricated using a five-mask process. Rows of fins composed of high conductivity silicon are bonded onto a 100µm base plate composed of low conductivity Pyrex glass. The fabrication process involves anodic bonding, deep reactive ion dry etching, glass frit bonding, electrochemical drilling and several other steps, along with special features that compensate for manufacturing tolerances. The paper describes the fabrication challenges and how they constrain dimensional variables.
Modeling of a Closed-Loop Maritime Transportation System with Discrete Event Simulation and Multi-Criteria Decision Analysis

The present paper approaches the development and application of a Discrete Event Simulation (DES) model with a Multiple Criteria Decision Analysis (MCDA) tool for the simulation and sizing of a closed-loop maritime transportation system. This system is responsible for the supply of raw materials, especially iron ore, to a steel plant, and its sizing involves the analysis of the transportation fleet and of the storage area for the inputs to the steel making process. This work characterizes the problem, shows the methodology employed and highlights the main results achieved by the simulation. Concomitantly, the choice of the best solution between the simulation results is made based in the application of the MCDA methodology. The main conclusion of the study is that the use of DES combined with MCDA is an efficient way to help decision-making on complex logistics transportations systems.
Measuring Fiscal Sustainability

We propose an index of the fiscal stance that is convenient for practical use. It is based on a finite time horizon, not on an infinite time horizon like most tests. As it employs VAR analysis it is simple to compute and easily automated. We also show how it is possible to analyse a change of policy within a VAR framework. We use this methodology to examine the effect on fiscal sustainability of a change in policy. We then conduct an empirical examination of the fiscal stances of the US, the UK and Germany over the last 25 or more years, and we carry out a counter-factual analysis of the likely consequences for fiscal sustainability of using a Taylor rule to set monetary policy over this period. Among our findings are that the recent fiscal stances of all three countries are not sustainable, and that using a Taylor rule in the past would have improved the fiscal stances of the US and UK, but not that of Germany.
Semantic Lexicon-Based Multi-agent System for Web Resources Markup

A hierarchical multi-agent system that exploits one (or more) Semantic Lexicon for performing semantic markup of Web resources is presented. Semantic Lexicon is considered here as a golden ontology defining taxonomical relations among concepts such as hypernymy, meronymy, holonymy and so forth. The system attempts to annotate Web resources according to the available taxonomical relations using simple annotation schemes. The system is completely autonomous if the chosen golden ontology is provided by linguistic experts as it happens for WordNet. The proposed conceptual architecture has been applied to real-world scenarios for test purposes, obtaining promising results.
The Virtual Mirror: A New Interaction Paradigm for Augmented Reality Environments

Medical augmented reality (AR) has been widely discussed within the medical imaging as well as computer aided surgery communities. Different systems for exemplary medical applications have been proposed. Some of them produced promising results. One major issue still hindering AR technology to be regularly used in medical applications is the interaction between physician and the superimposed 3-D virtual data. Classical interaction paradigms, for instance with keyboard and mouse, to interact with visualized medical 3-D imaging data are not adequate for an AR environment. This paper introduces the concept of a tangible/controllable virtual mirror for medical AR applications. This concept intuitively augments the direct view of the surgeon with all desired views on volumetric medical imaging data registered with the operation site without moving around the operating table or displacing the patient. We selected two medical procedures to demonstrate and evaluate the potentials of the Virtual Mirror for the surgical workflow. Results confirm the intuitiveness of this new paradigm and its perceptive advantages for AR-based computer aided interventions.
Geochemical study of arsenic release mechanisms in the Bengal Basin groundwater

To investigate arsenic mobility in the Bengal Basin groundwater, we sampled water wells and sediments throughout the region. There are strong correlations among high levels of dissolved arsenic and iron, ammonia, and methane, especially in samples from a single site (Laxmipur). No linkage is seen between As and agricultural tracers such as phosphate. The association of As and Fe occurs because arsenic strongly adsorbs onto FeOOH particles in river water. They flocculate with other fine‐grained particles at the freshwater/saltwater transition zone. Subsequent bacterially mediated reduction of FeOOH in the clay releases the adsorbed arsenic. Weathering of As‐bearing mica plays a significant role in the As budget. The “correlated” presence of As, CH4, and NH4 in water supply wells is the result of diffusion out of organic‐rich clay into the more permeable zones. Arsenic is mainly released from recent sediments at <50 m depth deposited in the GBR floodplain as sea level rose throughout the Holocene.
From the 'Digital Divide' to 'Digital Inequality': Studying Internet Use as Penetration Increases

The authors of this paper contend that as Internet penetration increases, students of inequality of access to the new information technologies should shift their attention from the "digital divide" - inequality between "haves" and "have-nots" differentiated by dichotomous measures of access to or use of the new technologies - to digital inequality, by which we refer not just to differences in access, but also to inequality among persons with formal access to the Internet. After reviewing data on Internet penetration, the paper describes five dimensions of digital inequality - in equipment, autonomy of use, skill, social support, and the purposes for which the technology is employed - that deserve additional attention. In each case, hypotheses are developed to guide research, with the goal of developing a testable model of the relationship between individual characteristics, dimensions of inequality, and positive outcomes of technology use. Finally, because the rapidity of organizational as well as technical change means that it is difficult to presume that current patterns of inequality will persist into the future, the authors call on students of digital inequality to study institutional issues in order to understand patterns of inequality as evolving consequences of interactions among firms' strategic choices, consumers' responses, and government policies.
Vitamin D deficiency in minority populations

Abstract Objective Black and Hispanic individuals synthesize less vitamin D per unit of sun exposure than white individuals. The relationship between UV radiation and vitamin D insufficiency in minorities has not been well explored. Design Prospective cohort study. Setting Using the National Health and Nutrition Examination Survey, we obtained serum vitamin D levels for non-Hispanic Whites, Hispanics and non-Hispanic Blacks aged ≥18 years from 2000–2006. We linked these data with the average monthly solar UV index by census tract and data on sun exposure, vitamin D supplementation, health and demographics. We used multivariable regression analyses to assess vitamin D deficiency (<15 ng/ml) and insufficiency (<20 ng/ml) in January (when the UV index was lowest) by race/ethnicity and geography. Subjects Adults (n 14 319) aged ≥18 years. Results A 1-point increase in the UV index was associated with a 0·51 ng/ml increase in vitamin D (95 % CI 0·35, 0·67 ng/ml; P<0·001). Non-Hispanic Black race and Hispanic ethnicity were associated with a 7·47 and 3·41 ng/ml decrease in vitamin D, respectively (both P<0·001). In January, an estimated 65·4 % of non-Hispanic Blacks were deficient in vitamin D, compared with 28·9 % of Hispanics and 14·0 % of non-Hispanic Whites. An estimated 84·2 % of non-Hispanic Blacks were insufficient in vitamin D v. 56·3 % of Hispanics and 34·8 % of non-Hispanic Whites. More non-Hispanic Blacks were estimated to be deficient in vitamin D in January in the highest UV index quartile than were non-Hispanic Whites in the lowest UV index quartile (60·2 % v. 25·7 %). Conclusions Wintertime vitamin D insufficiency is pervasive among minority populations, and not uncommon among non-Hispanic Whites.
Feature Selection and Ranking

This chapter describes a method of feature selection and ranking based on human expert knowledge and training and testing of a neural network. Being computationally efficient, the method is less sensitive to round-off errors and noise in the data than the traditional methods of feature selection and ranking grounded on the sensitivity analysis. The method may lead to a significant reduction of a search space in the tasks of modeling, optimization, and data fusion.
Web Service Reputation-Semantics and Assessment based on Customer Feedback Forecasting Model

In the Service Web, customers’ feedback constitutes a substantial component of Web Service reputation and trustworthiness, which in turn impacts the service uptake by consumers in the future. This paper presents an approach to assess and predict reputation in service-oriented environments. For assessing a Web Service reputation, we define reputation key metrics to aggregate the feedback of different aspects of the ratings. In situations where rating feedback is not available, we propose a Feedback Forecasting Model (FFM), based on Expectation Disconfirmation Theory (EDT), to predict the reputation of a web service in dynamic settings. Then we introduce the semantic concept Reputation Aspect and show how to compute it efficiently. Finally we show how to integrate the Feedback Forecasting Model into Aspect-Based Reputation management framework. To demonstrate the feasibility and effectiveness of our approach, we test the proposed model using our Service Selection Simulation Studio (4S). The empirical results included in this paper show the applicability and performance of the proposed Reputation Assessment based on the Customer Feedback Forecasting Model. We also show how our model is efficient, particularly in dynamic environments.
Asymptotic behavior of solutions of semilinear elliptic equations on an unbounded strip.

(1.3) Zs = ∆t,xZ + f(t+ 2αs, x,Z). In this equation s plays the role of time, ∆t,xZ = Ztt+Zxx is a standard diffusion term and f represents a nonlinear source (reaction term), which travels in the direction of the unbounded variable with the constant speed −2α. Among the solutions of (1.3) of a particular interest are solutions of the form Z(s, t, x) = u(t + 2αs, x) (the travelling waves with velocity −2α). The profile