Miracle-dz/UniFAR-FTUs huggingface dataset:
Corporate Social Responsibility, Organizational Justice and Job Satisfaction: How do They Interrelate, If at All?

Although recent years have seen considerable theoretical attention devoted to corporate social responsibility (CSR), a multi-dimensional construct encompassing commitment to society, employees, customers, and the government, the relationship between CSR and employee attitudes has not been sufficiently studied. This study therefore examines the connections between the macro concept of CSR and micro research in the employee dimensions of organizational justice and job satisfaction. Questionnaires measuring CSR, organizational justice, and job satisfaction were completed by 101 employees. Results show that CSR is positively related to both organizational justice and job satisfaction. In addition, the relationship between CSR and job satisfaction was found to be mediated by organizational justice. The discussion stresses the value of CSR as a business strategy.
International Review of Research in Open and Distributed Learning Defining, Discussing, and Evaluating Mobile Learning: The moving finger writes and having writ....

Since the start of the current millennium, experience and expertise in the development and delivery of mobile learning have blossomed and a community of practice has evolved that is distinct from the established communities of 'tethered' e-Learning. This community is currently visible mainly through dedicated international conference series, of which MLEARN is the most prestigious, rather than through any dedicated journals. So far, these forms of development and delivery have focussed on short-term small-scale pilots and trials in the developed countries of Europe, North America, and the Pacific Rim, and there is a taxonomy emerging from these pilots and trials that suggests tacit and pragmatic conceptualisations of mobile learning. What has, however, developed less confidently within this community is any theoretical conceptualisation of mobile learning and with it any evaluation methodologies specifically aligned to the unique attributes of mobile learning. Some advocates of mobile learning attempt to define and conceptualise it in terms of devices and technologies; other advocates define and conceptualise it in terms of the mobility of learners and the mobility of learning, and in terms of the learners’ experience of learning with mobile devices. The role of theory is, perhaps, a contested topic in a community that encompasses philosophical affiliations from empiricists to post-structuralists, each with different expectations about the scope and legitimacy of theory in their work. The mobile learning community may nevertheless need the authority and credibility of some conceptual base. Such a base would provide the starting point for evaluation methodologies grounded in the unique attributes of mobile learning. Attempts to develop the conceptualisations and evaluation of mobile learning, however, must recognise that mobile learning is essentially personal, contextual, and situated; this means it is 'noisy' and this is problematic both for definition and for evaluation. Furthermore, defining mobile learning can emphasise those unique attributes that position it within informal learning, rather than formal. These attributes place much mobile learning at odds with formal learning with its cohorts, courses, semesters, assessments, and campuses, and with its
Wideband multi-source beamforming with adaptive array location calibration and direction finding

We present a novel adaptive algorithm in the frequency domain with a low order of arithmetic complexity for simultaneously performing beamforming, source direction finding and array shape calibration. The algorithm is proposed for multiple wideband sources, but could be applied to the narrowband case or to a single wideband source. The source signals are first estimated using a set of beamformers. These estimates are processed with the observation signals to track the steering vectors within the signal subspace. The adapted steering vectors are projected over the array manifold, to finally estimate the source directions and sensor positions. Simulations show the efficiency of the algorithm to achieve the proposed tasks.
Stille revolutie, contra-revolutie of cultureel conflict? Veranderingen in de politieke cultuur en hun invloed op het klassengebonden stemgedrag

textabstractIn this paper we investigate the linkage between changes in the political culture on the one hand and changes in class-party alignments on the other. First we investigate how the political culture in Western countries has changed over-time. Three views are tested using data on party-manifestos. The first predicts that only new-leftist issues will increase in salience. The second predicts that both new-leftist and new-rightist issues will emerge at the same time. The third, which is empirically corroborated, predicts that first new-leftist issues will emerge followed by a rise in new right-wing issues. Second, we investigate how the emergence of these new issues has affected the traditional class-party alignments. Using the International Mobility and Stratification File we show that the middle class increasingly votes left-wing as new-leftist issues become more important and that the working class increasingly votes right-wing as new-rightist issues become more important. Next to that, the middle class appears to alienate from the traditional party of their class as new-rightist issues rise in salience. At the end of the paper we discuss the implications of our findings.
The Experiment and Study on the Correlation Between Facial Expression Analysis and Learning Outcomes

The learning state of students in the classroom is closely related to their learning outcomes. The integration of these two aspects enables instructors to promptly and accurately adjust their teaching methods, thereby improving the quality of instruction. This paper presents an experimental study that utilizes facial recognition technology to investigate the correlation between facial expressions and learning effectiveness. We designed a validation system to capture real-time facial expressions of learners during different time intervals and applied it in authentic classroom teaching activities. Through indepth analysis of a substantial volume of reliable data, we unveil the relationship between emotional experiences and expressions during the learning process and instructional content. The research findings offer valuable insights into comprehensively understanding the learning state of students and provide a basis for instructors to adapt their teaching approaches and enhance instructional quality.
INFANT-MOTHER ATTACHMENT: A SOCIAL PSYCHOLOGICAL PERSPECTIVE

This paper examines infant-mother attachment and its alleged significance for personality and social development. There is now a great deal of evidence that the significance given to this attachment is not warranted. Infants normally develop attachments to more than one person. They are active participants in their interactions with other persons. The infant? s and young child's interpersonal world is both broader and more complex than is usually acknowledged. The ideology of motherhood persists to the detriment of fathering, shared parenting in family and cooperative situations, and caretaking in child-care facilities.
Personalized Electronic Program Guides for Digital TV

Although today's world offers us unprecedented access to greater and greater amounts of electronic information, we are faced with significant problems when it comes to finding the right information at the right time -- the essence of the information-overload problem. One of the proposed solutions to this problem is to develop technologies for automatically learning about the implicit and explicit preferences of individual users to customize and personalize the search for relevant information. In this article, we describe the development of the personalized television listings system (PTV),1 which tackles the information-overload problem associated with modern TV listings data by providing an Internet-based personalized TV listings service so that each registered user receives a daily TV guide that has been specially compiled to suit his/her particular viewing preferences.
Style recognition through statistical event models

Abstract The automatic classification of music fragments into style classes is one challenging problem within the music information retrieval (MIR) domain and also for the understanding of music style perception. This has a number of applications, including the indexation and exploration of musical databases. Some technologies employed in text classification can be applied to this problem. The key point here is to establish the music equivalent to the words in texts. A number of works use the combination of intervals and duration ratios for this purpose. In this paper, different statistical text recognition algorithms are applied to style recognition using this kind of melody representation, exploring their performance for different word sizes.
Energy Efficient Distributed Fault Identification Algorithm in Wireless Sensor Networks

A distributed fault identification algorithm is proposed here to find both hard and soft faulty sensor nodes present in wireless sensor networks. The algorithm is distributed, self-detectable, and can detect the most common byzantine faults such as stuck at zero, stuck at one, and random data. In the proposed approach, each sensor node gathered the observed data from the neighbors and computed the mean to check whether faulty sensor node is present or not. If a node found the presence of faulty sensor node, then compares observed data with the data of the neighbors and predict probable fault status. The final fault status is determined by diffusing the fault information from the neighbors. The accuracy and completeness of the algorithm are verified with the help of statistical model of the sensors data. The performance is evaluated in terms of detection accuracy, false alarm rate, detection latency and message complexity.
Angiogenesis around new AB-polymer networks after one week of implantation in mice.

Biomaterials research is expected to forward new materials to be used as, e.g., implant materials or as scaffolds for tissue engineering. It is central for such a scaffold material to create the track on which those cells can inhabit the scaffold needed to rebuild functional tissue substitutes. The tissue engineering concept expects a gradual gain in functionality of the newly created tissues while the scaffold materials are degraded and subsequently eliminated. Not only for the elimination of the degradation products the angiogenesis of new blood vessels is thought to play an important role. In the present study, a new biomaterial, a non-porous polymeric AB-network based on oligo (epsilon-hydroxycaproate) and oligobutylacrylate, was implanted in animals. Male NMRI mice were implanted subcutaneously for one week. Immediately after the explantation, the probes were examined histologically. Already one week after implantation, there was a strong tissue-integration of the polymer. Importantly, blood vessels occurred at the polymer surface. There were also clusters of cells around the vessels, which were phenotypically similar to fat cells. The mechanism of the early integration of the polymer is not clear. The relationship between the new periimplant vessels and the integration of the polymer has to be studied.
MIMO fuzzy control for autonomous mobile robot

This paper addresses the design and implementation of multi-input multi-output (MIMO) fuzzy control for mobile robot. Firstly, MIMO fuzzy control is apply to track different desired trajectories. Secondly, the controller performs on robot for navigation purpose to avoid obstacles and reach defined target. The proposed MIMO fuzzy controller was investigated based on several conducted MATLAB simulation scenarios for mobile robot. The simulation results are presented to demonstrate the effectiveness of our new control algorithm.
The relationship between behaviours exhibited by children with autism and maternal stress

The present study investigated the relationship between behaviours exhibited by children with pervasive developmental disorders, particularly autism, and maternal stress levels. Participants consisted of 60 mothers who had a child diagnosed with a pervasive developmental disorder by an independent practitioner using DSM‐IV criteria. Children were between 2 and 7 years of age. Mothers completed the following self‐report measures: the Parenting Stress Index (short‐form), the Aberrant Behavior Checklist, AAMR Adaptive Behavior Scales and a demographic questionnaire. Two‐thirds of the participants in the sample evidenced stress scores that were significantly elevated. Regression analyses revealed that child maladaptive behaviour and child adaptive behaviour accounted for a significant proportion of the variance in maternal stress. Methodological issues and considerations for future research are discussed.
The prevention of occupational asthma

There is sufficient understanding of the causation of occupational asthma for preventive action to be appropriate. To date, attempts appear to have been largely unsuccessful and this appears to be largely due to nonscientific/technical obstacles. These include the fragmented nature of the disease, its low public and industrial profile, and its comparative rarity in single workplaces. Nonetheless the disease has high individual and societal costs. Prevention strategies should be concentrated on workplace-exposure controls, accompanied by intense educational and managerial improvements. Methods of secondary prevention appear to be successful but require considerable refinement. Screening (out) of potential new employees is inefficient and likely to remain so; and in any case is beset by difficult ethical and legal issues. There are only a handful of published studies reporting evaluations of preventive programmes. None is entirely rigorous but each suggests that primary and secondary prevention are both feasible and highly effective. The evaluation of preventive strategies is difficult, not only because of the low incidence of the disease in individual workplaces but also because of the failure of many epidemiologists to engage in this work. Considerably more cooperation between scientists in the field, regulatory authorities and industry is required.
FGTC Based Remaining Useful Life Prediction with Incomplete Bearing Dataset

Prognostics and health managemen is a vital technology for implementing the health management and predictive maintenance of rotating machinery. However, due to the lack of complete running data set of bearing, the practical application of life prediction is greatly restricted. Therefore, this paper proposes a feature generated time convolutional (FGTC) network framework, including coding layer time-convolutional network (TCN) and prediction layer bidirectional long short term memory attention mechanism (BiLSTM-AM), and decoding layer TCN network. Firstly, physical domain features are extracted from industrial equipment component sensor signals, and light gradient boosting machine is used to select more important features for fusion. The feature data is trend-decomposed using the complete ensemble empirical mode decomposition with adaptive noise to construct a performance degradation feature set. Degradation states and points are determined through reconstruction features, and degradation modes are classified using degradation speed. Secondly, different degradation mode feature data are input to the TCN for encoding and the BiLSTM-AM is trained on the hidden output. Finally, decode the prediction result to realize life prediction and feature data generation. The study uses bearings as an example and compares the proposed FGTC network with commonly used deep learning methods, with the experimental results confirming its superiority and feasibility.
The Development of Successive Approximation Register for SAR ADC

This paper presents a study about successive approximation registers. The study considers and realizes the circuits of fifteen-bit registers and their topologies. In addition, the triggers have been compared to select the most favorable one to be used. The registers are realized based on 180 nm technology, with a supply voltage of 1.8 V. For each of the registers, the influence of technological parameters, parasitic crystal parameters, as well as the evaluation of power consumption and maximum frequency of operation have been verified.
Effect of cohesive behaviour and residual stress on the indentation response of elastoplastic film/substrate structure

In this study, the effects of cohesive behaviour and residual stress on the indentation response of an elastoplastic film/substrate structure were explored. A finite element model was developed by highlighting the contact between the Berkovich rigid indenter and the film/substrate model. The behaviour of the film is defined as the power-law constitutive properties, the substrate is assumed to be perfectly elastic, and the cohesive zone model is employed to evaluate the film/substrate interface interaction. By emphasizing the cohesive behaviour, delamination between the film and the substrate is investigated as an influential factor in the damage of layered device. In addition, the residual stresses generated during the thin film preparation are considered in the finite element model. Predictions of parameters such as Young's modulus, yield strength and hardening exponent were made based upon the curves derived from the finite element analysis. A dimensionless function is derived from the finite element simulation and an algorithm is proposed to reversely solve the intrinsic parameters and residual stresses of the elastoplastic material from the indentation response.
Semi-skyline augmented fillings and non-symmetric Cauchy kernels for stair-type shapes

Using an analogue of the Robinson-Schensted-Knuth (RSK) algorithm for semi-skyline augmented fillings, due to Sarah Mason, we exhibit expansions of non-symmetric Cauchy kernels Q (i;j)2 (1 xiyj) 1 , where the product is over all cell-coordinates (i;j) of the stair-type partition shape , consisting of the cells in a NW-SE diagonal of a rectangle diagram and below it, containing the biggest stair shape. In the spirit of the classical Cauchy kernel expansion for rectangle shapes, this RSK variation provides an interpretation of the kernel for stair-type shapes as a family of pairs of semi-skyline augmented fillings whose key tableaux, determined by their shapes, lead to expansions as a sum of products of two families of key polynomials, the basis of Demazure characters of type A, and the Demazure atoms. A previous expansion of the Cauchy kernel in type A, for the stair shape was given by Alain Lascoux, based on the structure of double crystal graphs, and by Amy M. Fu and Alain Lascoux, relying on Demazure operators, which was also used to recover expansions for Ferrers shapes. R´
Barrier removal in increasing physical activity levels in obese African American women with disabilities.

BACKGROUND This pilot study examined the effectiveness of a telephone-based intervention to increase physical activity in obese African American women with mobility disabilities by targeting the removal of barriers to participation. METHODS Severely obese (mean body mass index [BMI] = 49.1 kg.m²) African American women (n = 33) with mobility disabilities completed a 6-month telephone-based physical activity coaching intervention. RESULTS The major environmental/facility barriers at preintervention were cost of the program (66.7%), lack of transportation (48.5%), not aware of fitness center in the area (45.5%), and lack of accessible facilities (45.5%). The major personal barriers were pain (63.6%), don't know how to exercise (45.5%), health concerns (39.4%), don't know where to exercise (39.4%), and lack of energy (36.4%). Despite only two personal barriers being significantly lower at posttest (don't know where to exercise and don't know how to exercise) (p < 0.01), total exercise time increased from < 6 minutes/day to 27 minutes/day at posttest (p < 0.001), and total physical activity time (structured exercise, leisure, indoor and outdoor household activity) increased from 26 minutes/day to 89 minutes/day at posttest (p < 0.001). CONCLUSIONS Interventions aimed at increasing physical activity participation among obese African American women with mobility disabilities should start with increasing their awareness/knowledge on where and how to exercise. Other reported barriers (e.g., cost, transportation, finding an accessible facility, health concerns, pain) may not be as critical to alter/remove as identifying where participants can exercise (i.e., home, outdoors, gym) and providing them with a variety of routines that can be performed safely in their desired setting.
Smart Environment and Plant Disease Monitoring with Analysis System in Agricultural Field

Agriculture is deemed to be the most significant segment in India. The main objective of this research work is to monitor plant diseases and analyze the system using a smartphone. The remote monitoring framework, including temperature, stickiness and soil humidity sensors, a microcontroller, an ultrasonic sensor, a camera, and a GSM module is validated for effective environment observation. The technology could offer a fresh method for farming to obtain information related to agriculture. In this monitoring system of agricultural diseases, the main aim is to achieve disease monitoring information and collections of the results are detected by Android application through GSM. ARM processor is used for analog to digital converter (ADC) and sends the gathered information to portable through GSM. An IP web camera is occasionally empowered to catch the plant leaf picture for disease checking and an ultrasonic sensor is utilized with the end goal of plant development checking. It uses a soil battery to drive the temperature sensor to foster plant development checking framework and plant infection observation, likewise adaptive android application to screen such circumstances by utilizing this innovation to accomplish a green hardware framework.
Cheese yield as affected by some parameters Review

Cheese yield is defined as the amount of cheese, expressed in kilograms, obtained from 100 kg of milk. It is a very important parameter: the higher the recovered percentage of solids, the greater is the amount of cheese obtained and therefore gains in economic terms. The definition of cheese yield, or how to express yield, is important in two main applications: 1. Economic control of cheesemaking; 2. Expressing the results of cheesemaking experiments. Cheese yield is affected by many factors including milk composition, amount and genetic variants of casein, milk quality, somatic cell count (SCC) in milk, milk pasteurization, coagulant type, vat design, curd firmness at cutting, and manufacturing parameters.