Miracle-dz/UniFAR-FTUs huggingface dataset:
Theory Assessment and Agenda Setting in Political CSR: A Critical Theory Perspective

Frynas and Stephens (Political corporate social responsibility: reviewing theories and setting new agendas. International Journal of Management Reviews, 17, pp. 483–509, 2015) reviewed the literature on political corporate social responsibility (CSR). They described existing trends and suggested an agenda for future research. They attempted to develop ‘a more inclusive pluralist research agenda in political CSR, which can integrate different perspectives on political CSR in order to account for different phenomena, including global governance changes at macro level, instrumental concerns at organizational level or cognitive dimensions at individual level, in both descriptive and normative terms’. This was an ambitious endeavour, given the rapid growth of the literature and the extensive heterogeneity of the field. There is much to like in Frynas and Stephens’ paper, as it spans a broad range of perspectives and links together discrete research topics. In the present review, however, the author focuses on a number of critical aspects in their argument. Frynas and Stephens failed to define core concepts, to reveal their normative stance on CSR and their paradigmatic position, or to address the inherent conflict of values in political CSR. And they were too optimistic about the possibilities and benefits of ‘integration’. The author suspects that their approach, when adopted in practice, will impede rather than promote social welfare. This paper starts with a brief summary of the field and continues by emphasizing critical issues in Frynas and Stephens’ analysis. It concludes with an alternative agenda for research in political CSR.
Weight Loss and Germination Failure Caused by Psocids in Different Wheat Varieties

ABSTRACT We investigated weight loss caused by Liposcelis entomophila (Enderlein) feeding in damaged (cracked) and intact kernels of ‘Jagger’ variety of hard red winter wheat over a 90-d period at 30 ± LC and 75 ± 5% relative humidity. L. entomophila caused 8.5% weight loss in damaged wheat kernels, which was significantly greater than the weight loss found in intact wheat kernels (0.2%). We also evaluated the suitability of six wheat varieties commonly grown in Oklahoma, namely, Jagger, ‘Endurance,’ ‘Overley,’ ‘Jagalene,’ ‘OK Bullet,’ and ‘Deliver’ to support populations of four psocid species, namely, Liposcelis bostrychophila Badonnel, L. decolor (Pearman), L. entomophila, and L. paeta Pearman over a 30-d period. The greatest population increase was observed in L. bostrychophila followed by L. paeta. Subsequently, weight loss of damaged and intact wheat kernels and germination of intact kernels infested by L. paeta over a 45-d period were assessed in OK Bullet variety. L. paeta caused weight loss of 3.3% in damaged kernels, which was significantly greater than the weight loss found in intact kernels (0.4%). Based on our data, 40% of infested intact kernels failed to germinate after 45 d of infestation by L. paeta, but this decreased to 32% when adjusted using germination failure of uninfested kernels. Our data show that psocid infestations do not only cause considerable loss in weight of wheat, but also result in significant germination failure. These data call for the formulation of effective integrated psocid management strategies for stored wheat to mitigate the negative impacts of psocid pests.
Detecting Software Faults in Distrubted Systems

We are concerned with the problem of detecting faults in distributed software, rapidly and accurately. We assume that the software is characterized by events or attributes, which determine operational modes; some of these modes may be identified as failures. We assume that these events are known and that their probabilistic structure, in their chronological evolution, is also known, for a finite set of different operational modes. We propose and analyze a sequential algorithm that detects changes in operational modes rapidly and reliably. Further more, a threshold operational parameter of the algorithm controls effectively the induced speed versus correct detection versus false detection tradeoff.
Assessing the Financialization Hypothesis

The main objectives of this paper are to assess whether financialization can impact oil market behaviour over and above structural fundamental changes, and whether these changes affect final consumers’ welfare. We build a calibrated macro-finance model of the oil market that solves for the term structure of spot prices and the futures price, as well as consumer welfare. While shifts arising in financial investors’ preferences and wealth can explain the rise in participation of purely financial investors, they fail to explain key features such as the movements in the basis. Instead, anticipated changes in the physical layer of the oil market can better explain many of the features often attributed to financialization. We also find that greater financialization has no harmful effects on consumer welfare. Our paper shows that from a regulatory point of view, it is crucial in the first instance to identify the channels through which financialization can result in market failure and then design policies accordingly. JEL-Classification: C63, G12, G13, G17, Q43
The erudite humility of the historian: the ‘critical epistemology’ of Georges Lantéri-Laura

This paper analyses the historical and epistemological work of the French psychiatrist Georges Lantéri-Laura (1930–2004) within the context of the French ‘tradition’ of history and philosophy of sciences, with special reference to Georges Canguilhem and Michel Foucault. After an introduction devoted to a critical survey of the most recent works on the history and historiography of psychiatry in French, the paper outlines Lantéri-Laura’s approach by focusing especially on the role played by the methodological concept of ‘semiology’ as regards the relation between medicine and psychiatry. The last part of the paper draws attention to the relation between the history and philosophy of psychiatry in light of Lantéri-Laura’s ‘critical epistemology’.
Query recommendation based on irrelevant feedback analysis

Similarity computation among queries is a central step of query recommendation based on click information in search log. In this step, weights of clicked URLs or clicked document terms, which may have a large influence on similarity computation results, are mostly counted based on co-occurrence. However, counting weights based on co-occurrence are unusually disturbed by irrelevant feedbacks in search log, which may decrease the precision of query similarity computation. This paper proposes a method that computes similarity among queries based on "Query - Clicked Sequence" model, which counts weight of clicked document term by density of documents containing this term on clicked sequence, and filters content of irrelevant documents during similarity computation. A series of experiment results show that this method can precisely count the weights of terms, and increase the precision of query similarity computation, accordingly increase the precision of query recommendation.
Language and Framework Requirements for Adaptation Models

Approaches to self-adaptive software systems use models at runtime to leverage beneﬁts of model-driven engineering (MDE) for providing views on running systems and for engineering feedback loops. Most of these approaches focus on causally connecting runtime models and running systems, and just apply typical MDE techniques, like model transformation, or well-known techniques, like event-condition-action rules, from other ﬁelds than MDE to realize a feedback loop. However, elaborating requirements for feedback loop activities for the speciﬁc case of runtime models is rather neglected. Therefore, we investigate requirements for Adaptation Models that specify the analysis, decision-making, and planning of adaptation as part of a feedback loop. In particular, we consider requirements for a modeling language of adaptation models, and for a framework as the execution environment of adaptation models. Moreover, we discuss patterns for using adaptation models within the feedback loop regarding the structuring of loop activities. The patterns and the requirements for adaptation models inﬂuence each other, which impacts the design of the feedback loop.
Simulation of Multi-Agent Approach in Multi-Cloud Environment Using Matlab

These days, cloud computing is growing more popular, as users are becoming more interested in migrating their tasks on these ubiquitous systems. However, due to the large number of providers and services available, selecting the best option would be a very time-consuming process. This paper presents a multi-agent approach to assist the selection and provisioning of resources in a multi-cloud environment for incoming requests. This framework allows automated monitoring and resource provisioning. This research has demonstrated and implemented this approach in a simulated multi-cloud environment created in Matlab, also represent an example of two resource provisioning algorithms considering users benefit.
Fitness Function Approximation by Neural Networks in the Optimization of MGP-FIR Filters

In this paper we introduce a neural network based method for speeding up the fitness function calculations in a genetic algorithm (GA)-driven optimization process of multiplicative general parameter finite impulse response (MGP-FIR) filters. In this case, calculating the fitness of a candidate solution is an extensive and time-consuming task. However, our results show that it is possible to approximate the fitness function components with neural networks up to sufficient degree, thus enabling the genetic algorithm to perform the fitness calculations considerably faster. This allows the algorithm to evaluate larger number of generations in a given time. Our results suggest that it is possible to decrease the approximation error of the neural network so that the NN-assisted GA eventually offers competitive performance compared to a reference GA
Hybridization of heuristic approach with variable neighborhood descent search to solve nurse Rostering problem at Universiti Kebangsaan Malaysia Medical Centre (UKMMC)

Nurse Rostering problem (NRP) represents a subclass of scheduling problems that are difficult to solve for optimality. It deals with assigning shifts to staff nurses subject to satisfying required workload and other constraints. The constraints are classified into hard constraints (compulsory) and soft constraints (should be satisfied as much as possible). A feasible solution is a solution that satisfies all hard constraints. However, the quality of the duty roster is measured based on satisfying the soft constraints. This study is an attempt to solve a real world scenario from Universiti Kebangsaan Malaysia Medical Center (UKMMC). Currently, the duty roster is constructed manually by head nurses in different wards. So, the main goal of our work is to generate good duty roster that satisfied all the hard constraints which are required by (UKMMC). A constructive heuristic is introduced to solve (UKMMC) nurse rostering problem. This heuristic is a hybridization of cycling schedule with non-cycling schedule (random order). If the solution is not feasible, we apply a repairing mechanism to produce feasible solution. Then, the initial solution is improved by applying variable neighborhood descent search. Computational results are presented to demonstrate the effectiveness of the proposed approach.
Model-Based Analysis of Sensor-Noise in Predictive Passive Safety Algorithms

The introduction of environment perception sensors into the automotive world enables further improvement of the already highly optimized passive safety systems. Such sensors facilitate the development of safety applications that can act in a context sensitive manner concerning the protection of vehicle occupants. Hereby the quality of the provided information is decisive for the usability and effective range of such sensors within integrated safety systems. In this paper noise effects in sensors and their implications on the prediction of collision parameters are analyzed. The focus lies on sensors that can measure distances but not velocities or accelerations of the objects surrounding the car. For such sensors a noise model is presented as well as a tracking algorithm aiming to estimate the velocities and to compensate the effects of noise. This information is used by a trajectory-based algorithm to predict relevant collision parameters like time-to-collision, relative velocity at collision time etc. Monte Carlo simulations show the influence of noise on the accuracy of the predicted collision parameters. The described model-based study allows the systematic deduction of sensor requirements and represents a new way for the evaluation of the robustness of predictive passive safety systems.
Cryptography Algorithms and approaches used for data security

used systems, the computers are exposed to the other users. To keep the data secured from different users various encryption algorithms are entered. As computer systems become more pervasive and complex, security is increasingly important. Cryptographic algorithms and protocols constitute the central component of systems that protect network transmissions and store data. Encryption is the translation of data to a secret code. Apart from its uses in Military and Government to facilitate secret communication, Encryption is used in protecting many kinds of civilian systems such as Internet e-commerce, Mobile networks, automatic teller machine transactions, copy protection (especially protection against reverse Engineering and Software piracy), and many more. The Encrypted data can only be deciphered if one has the password or the Key. The Encryption algorithm is a set of well defined steps to transform data from a readable format to an encoded format using the Key. This set of well defined steps is also called cipher.
The development of a human resource management (HRM) professional competence model: A pilot study

This study sought to develop and test a diagnostic tool for the measurement of professional human resource management (HRM) competencies in the South African context. Data on HRM competencies were collected from South African human resource (HR) practitioners (N = 189; females = 49.2%, blacks = 91.2%). Exploratory factor analyses resulted in three distinguishable HR competency dimensions: Professional behaviour and leadership (i.e. leadership-personal credibility, organisational capability, solution creation, interpersonal communication, and citizenship); Service orientation and execution (i.e. talent management, HR governance, analytics and measurement, and HR service delivery); and Business intelligence (i.e. strategic contribution, HR business knowledge, and HR technology).
Three-phase Induction Motor Operation Trend Prediction Using Support Vector Regression for Condition-based Maintenance

Due to the broad employment and large amount of electricity consumption of induction motor, their efficient operation has been a focus for engineering research. The paper proposes a new integrated approach performing the motor condition prediction for the maintenance of low cost and high quality. Studies were done on nonlinear data analysis techniques, including particle filters for state estimates and support vector regression for condition prediction. Laboratory studies support the condition-based maintenance for motor systems
Nutrient Control of Yeast PKA Activity Involves Opposing Effects on Phosphorylation of the Bcy1 Regulatory Subunit

Kelch repeat proteins Gpb1 and Gpb2 control yeast PKA activity in response to nutrients by stimulating phosphorylation of the Bcy1 regulatory subunit. Gpb1 and Gpb2 function by blocking inhibition of Bcy1 phosphorylation by PKA catalytic subunits. Phosphorylated Bcy1 is more stable and is a more effective inhibitor of PKA activity.
Direct Pulse Transit Time measurement from an electronic weighing scale

A novel method to measure Pulse Transit Time (PTT) from the force sensors of a modified electronic weighing scale is presented. The method relies on the relation between PTT and the interval between I and J waves of the ballistocardiogram (BCG). The IJ interval and the PTT derived from a carotid and a femoral pressure-pulse waveform were simultaneously obtained from three subjects during paced respiration, which induces periodic hemodynamic changes. The correlation between the IJ interval and this PTT is 0.69 and the difference between measurements is −5.2±16.4 ms, which are values similar to those of commercial devices based on more invasive methods that can be applied only to subjects in supine position. The simplicity of the method and the cost-effectiveness of the device to implement it offer new perspectives for the ambulatory assessment of arterial stiffness.
THE INFLUENCE OF PRESENTATION ON THE INTERPRETATION OF INFERENTIAL RESULTS

Confidence intervals (CIs) have frequently been presented as an alternative for null-hypothesis significance testing (NHST). Earlier, it was shown that the frequency of misinterpretations for results presented by means of CIs are lower than those for data presented by means of NHST outcomes. Little is known, however, about whether the subjective estimates that arguably play an implicit role in most interpretations of results differ for results presented by means of CIs or NHST outcomes. In the present study, participants were asked to interpret outcomes of fictitious studies. For significant outcomes, participants tend to be more certain about the existence of a population effect and about replicability of their results when the results are presented by means of NHST than by means of CIs. Such a difference could not be found for clearly non-significant findings. Apparently, a significant finding presented by means of a p-value is more convincing than the same effect presented by means of a CI. Null-hypothesis significance testing (NHST) has been heavily criticized for decades for not being a useful inferential technique. CIs are believed to offer a solution for many problems associated with the use of NHST. In addition to combining information on location and precision, CIs convey information on effect size (Schmidt, 1996), and should thus reduce binary thinking (Wilkinson & Task Force on Statistical Inference, 1999). We define binary thinking in the NHST context as an exaggerated focus on whether or not the result is significant, with little or no attention for the size of the effect. Furthermore, it has been argued that CIs make meta-analysis easier and less problematic (Cumming & Finch, 2001).
Iterative estimation of phase using complex cepstrum representation

This paper presents a method to iteratively estimate phase information from speech in the cepstrum domain. It assumes that correct markings of pitch periods, which may not correspond to glottal closure instants (GCI), are available and can be used to extract the smooth spectral envelope of speech. By using this information, the minimum-phase cepstrum is derived and used as prior information in a modified version of a previously proposed scheme of complex cepstrum analysis based on the mean squared error. Experiments with an emotional database show that the proposed method achieves better performance in terms of continuous phase spectrum estimation, when compared with approaches that rely on accurate GCI markings and high-resolution phase unwrapping mechanisms. In addition, similar results to the full optimization of the complex cepstrum vector are reached, at a lower computational complexity.
Creencias y percepciones del éxito en futbolistas adolescentes. Diferencias entre categorías deportivas y posición clasificatoria (Beliefs and perceptions of footballers on success. The differences between sporting categories and their qualifying rank)

El objetivo del trabajo fue analizar la relacion entre creencias y percepciones de exito en futbolistas adolescentes de categorias Cadete (14-16 anos) y Juvenil (16-18 anos) asi como atender a posibles diferencias entre las categorias deportivas y posicion clasificatoria de sus equipos. La muestra fue de 512 sujetos pertenecientes a 12 clubs de la ciudad de Zaragoza (M=16,01; DT: 1,465). Los instrumentos utilizados fueron Perception of Success Questionnaire (POSQ) traducida al castellano por Cervello, Escarti y Balaguer (1999) asi como Beliefs About the Causes of Sport Success Questionnaire (BACSSQ) validada por Castillo, Balaguer y Duda (2002). Los resultados mostraron correlaciones de orientaciones hacia la tarea con creencias de exito basadas en el esfuerzo y motivacion y de orientaciones hacia el ego con la habilidad normativa y utilizacion de tecnicas de engano. Ademas, se denoto la influencia de la percepcion de exito hacia la tarea y habilidad normativa segun aumenta el nivel competitivo en jugadores cadetes y juveniles siguiendo una misma tendencia en las creencias de exito basadas en la utilizacion de tecnicas enganosas con los primeros. Se desprenden implicaciones practicas a tener en cuenta por entrenadores y monitores para con sus deportistas orientadas hacia conductas de logro adaptativas y autodeterminadas en la consecucion de resultados deportivos. Abstract. The aim of this research was to analyse the relationship between beliefs and perceptions held by adolescent footballers on success in the categories of U16 (under 16) and U18 (under18) leagues, as well as exploring the possible differences between sporting categories and their team’s ranking. The sample included 512 individuals belonging to 12 clubs in the city of Zaragoza (M=16,01; DT: 1,465). The main means used were Perception of Success Questionnaire (POSQ) translated into Spanish by Cervello, Escarti y Balaguer (1999) as well as Beliefs About the Causes of Sport Success Questionnaire (BACSSQ), created by Castillo, Balaguer y Duda (2002). The results showed a correlation, on the one hand, between attitudes towards the task and beliefs in success based on effort and motivation, and on the other hand, of attitudes towards oneself and both the accurate self-assessment of performance and the use of cheating methods, taking into account significant differences between the competitive level and the qualifying rank. Some practical implications can be deduced for coaches and instructors to bear in mind for their athletes who aim to acquire a more adaptive and self-determined behaviour in the attainment of sporting results.
Predicting Rodent Carcinogenicity By Learning Bayesian Classifiers

The National Toxicology Program (NTP) uses the results of various experiments to determine if test agents are carcinogenic. Because these experiments are costly and time consuming, the rate at which test agents can be tested is limited. The ability to predict the outcome of the analysis at various points in the process would facilitate informed decisions about the allocation of testing resources. In addition, it is hoped that models resulting from attempting to make such predictions will augment expert insight into the biological pathways associated with cancers. This paper describes an approach to making such predictions which is based on learning Bayesian Classifiers. This method builds predictive models by gleaning information from a training set containing data from test agents which have previously been classified by NTP. We will focus on the structure of the training sets and the intuitiveness and cross-validated accuracy of the models learned. As the data is available, these models are being used to predict the classifications of a set of thirty test agents currently being bioassayed by NTP.