Miracle-dz/UniFAR-FTUs huggingface dataset:
Environmental antecedents of workplace bullying: A multi-design approach

The overall aim of this thesis is to contribute to an increased understanding of why bullying occurs at workplaces. Workplace bullying may be understood as the process of repeated and prolonged mistreatment and abuse of an individual at work who perceive to have little opportunity or recourses to retaliate in kind. Although the reasons for why bullying develops are likely to be both complex and interwoven, and may be related to both characteristics of the target and characteristics of the perpetrator, prevailing explanations all emphasise the role of the employing organisation in this process. In line with Leymann’s (1996) work environment hypothesis, stressful working environments have for long been assumed to create conditions that, directly or indirectly, may lead to the development of workplace bullying. Although an increasing amount of research have investigated the role of the work environment in relation to workplace bullying during the last couple of decades, many empirical as well as theoretical questions regarding why bullying occurs at workplaces are still left unanswered. This thesis comprises four empirical studies that all examine work environment factors as antecedents of workplace bullying by means of different research approaches and analytical designs. Paper 1 reports on data from a cross-sectional representative sample of the Norwegian workforce. The aim of Paper 1 was to simultaneously investigate a broad spectrum of job characteristics as antecedents of exposure to workplace bullying, in order to examine the relative importance of various factors in relation to bullying. The findings showed role conflict, interpersonal conflicts, and tyrannical and laissez-faire leadership behaviour to be strong predictors of exposure to workplace bullying. However, the strength of associations differed for various measures of bullying, with associations between the predictor variables and bullying measured by a behavioural experience measure found to be generally stronger as
FPGA IMPLEMENTATION OF A PSEUDO NOISE SEQUENCE USING CHAOTIC TENT MAP FOR SATELLITE COMMUNICATION

Pseudo Noise (PN) sequences are an integral part of satellite navigation system. In the past few years’ modernization of these systems had led to the addition of new frequency signals or bands such as the L1c and L5 signals thereby necessitating new PN sequences. Chaos based binary PN sequences have been used mainly for cryptographic applications and have not been experimented for other applications. In this paper one such chaos based function namely the Tent map is studied. The Tent map is implemented using shift registers and the output is further modified to obtain optimum correlation values. The correlation properties are studied and compared against Gold sequences. Finally a Verilog hardware description language code is written for implementation on a Field Programmable Gate Array (FPGA) evaluation kit.
The Influence of Teacher Unionization on Educational Outcomes: A Summarization of the Research, Popular Methodologies and Gaps in the Literature

This paper summarizes the research on the relationship between teacher unionization and educational outcomes at the state, district, school, and individual (student) levels. Although teachers are the largest organized professionals in the United States, much of educational policy literature has ignored unionization as a subject of study. An emerging consensus from the literature believes that collective bargaining raises teacher pay, increases district expenditure and reduces class size; however, union influence on student outcomes has not yet been established. The literature is unclear as to whether or not teacher unionization is associated with student graduation rates or standardized test scores.
VERIFICATION OF SHADOW REGION EFFECT ON RADAR CROSS SECTION OF TARGETS USING PHYSICAL OPTICS METHOD

Our method that uses current generator operator assumes the current on the entire surface of conducting scatterers. While, Physical Optics (PO) method assumes that the surface current generates only on the illumination region. The effect of the shadow region on the scattering waves is, therefore, proved by comparing our exact method with PO method. In this regard, radar cross-section (RCS) is calculated for smooth concave-convex contour. We work on numerical calculation of the RCS and analyze its characteristics with different target configurations including complexity and size. Concave illumination region is postulated with considering targets are taking large sizes of about five wavelengths. Here, we assume waves propagation and scattering from targets in free space and horizontal polarization (E-wave incidence).
Moderate Resolution Imaging Spectroradiometer (MODIS) MOD21 Land Surface Temperature and Emissivity Algorithm Theoretical Basis Document

This document outlines the theory and methodology for generating the Moderate Resolution Imaging Spectroradiometer (MODIS) Level-2 daily daytime and nighttime 1-km land surface temperature (LST) and emissivity product using the Temperature Emissivity Separation (TES) algorithm. The MODIS-TES (MOD21_L2) product, will include the LST and emissivity for three MODIS thermal infrared (TIR) bands 29, 31, and 32, and will be generated for data from the NASA-EOS AM and PM platforms. This is version 1.0 of the ATBD and the goal is maintain a 'living' version of this document with changes made when necessary. The current standard baseline MODIS LST products (MOD11*) are derived from the generalized split-window (SW) algorithm (Wan and Dozier 1996), which produces a 1-km LST product and two classification-based emissivities for bands 31 and 32; and a physics-based day/night algorithm (Wan and Li 1997), which produces a 5-km (C4) and 6-km (C5) LST product and emissivity for seven MODIS bands: 20, 22, 23, 29, 31-33.
"Brand building activities in Small Service Firms: A Qualitative Study on Swedish Real Estate Firms"

Brand building is a highly researched phenomenon when it comes to large enterprises in product oriented industries. However, when it comes to small firms and especially the service industry branding is a relatively new topic. This article explores the field of small service firms and their efforts in building their brand. The starting point rests on the creation of an organizational identity which is the values and beliefs that concurrently creates the foundation for the firms internal procedures. The purpose of this study is to get an understanding on how small service firms build their brand. Therefore, this article uses a qualitative approach with multiple cases with responding firms ranging from 2 to 12 employees. This was done in the effort of finding patterns on how brand building is conducted in small service firms. The findings shows that brand building is an important aspect that small service firms place great efforts on and that despite shortages in resources they build their brand by using alternative methods that are less resource intensive. The respondents argue that they have the organization as a base when creating their marketing activities. Important characteristics are consistency, honesty, creativity, integrity and heritage. Together they build a foundation for a unification of the firm that is presented through the brand. A unified organization is then used as a way of branding themselves towards new customers with the help of both reputation gained and word-of-mouth.
A method for calculating means and variances of comparative data for use in a phylogenetic analysis of variance

Question: Is there a general method for applying an analysis of variance (ANOVA) to phylogenetic data sets that allows for the incorporation of any assumption of evolutionary model? Mathematical method: I describe a method that enables the calculation of means and variances of the traits of monophyletically related species. These means and variances are calculated using evolutionary rates derived from estimated nodal values and can thus incorporate any assumption of evolutionary model. Furthermore, calculations of phylogenetically corrected mean squares are described through a worked example to show how these can be implemented into a complete-blocks ANOVA. Key assumptions: The assumptions of this method are, as for all comparable methods, that the phylogeny is known without error and that estimated nodal values are correct. Since the method can utilize nodal values using any evolutionary model, the latter assumption can to a degree be circumvented. Conclusions: I compare the presented method to alternative tests conceptually, but also using an idealized example and an example derived from the real world, to show the utility of the approach described herein.
Relationship Between Trade Openness and Energy Consumption in Oil Importing Asian Countries

The present study intended to examine the impact of trade on energy consumption using data of four oil importing, heavily populated, and developing economies of Asia namely Pakistan, India, China and Bangladesh. The study covers the period of 1972 to 2011. The data was checked for the Cross-sectional Dependency using CD-test, then CIPS panel unit root test, Panel cointegration, and Pooled Mean Group estimates approaches were used. Empirical results confirmed the Long-run relationship between energy consumption and trade openness. This study confirms the influence of trade on energy consumption and that they are positively related. International trade increases the energy demand and economic activities. However, high energy demand causes high energy price which negatively impacts on energy consumption and hence reduces the energy consumption. Therefore, there are many implications for the energy conservation and trade policy makers to consider in all four countries.
VenLA: The LATMOS Venus cloud model

The LATMOS Venus cloud model VenLA (Venus Liquid Aerosols) is based on a terrestrial Polar Strato-spheric Cloud (PSC) model [7]. VenLA models the formation, growth and decay of sulfuric acid-water droplets. The model has undergone several updates. We will present results of reference runs and sensitivity tests based on input profiles from VIRA [5] for temperature and pressure and from occultation data concerning the vapors, as in [8]. We compare the results to the available observations on cloud particle number densities and sizes, and to other modeling studies. The VenLA model will define the baseline for a parallel project on development of a moment method scheme to be used in a global climate model (see abstract Guil-bon et al., this conference [2]).
Exploring Teachers’ and Students’ Attitude Towards Group Work Assignment in English Language Classroom: The Case of Grade 11 at Wolayta Sodo Preparatory Schools in Ethiopia

The purpose of the study was to assess the attitude of English teachers’ and students’ towards group work assignment in English language classroom. The study was conducted in Wolaita Sodo Preparatory School in the case of grade eleven. To attain this objective, Mixed Method Research Design was used. Both quantitative and qualitative analysis methods were used. The participants of the study were seven purposively selected English language teachers from grade eleven. In addition, one hundred forty four grade eleven students were randomly selected for the study. The required data for the study were collected using questionnaire, semi-structured interviews and focus group discussion. Accordingly, the findings of the study indicated that most of the teachers’ and students’ had negative attitude towards group work assignment in English language classroom. Therefore, they did not act according to their attitudes due to students’ lack of interest, students’ lack of motivation and students’ lack of awareness. The results of the study, hence, revealed that a few of teachers gave constructive feedback and grade for students in group work assignment. Based on the findings suitable recommendations were made. Keywords: Group work, attitude, motivation, assignment, awareness
Standalone battery storage unit for PMSG based variable speed wind turbine system

An exercise of power effectively of renewable energy is more important than power generation. This paper proposes stand alone wind energy system (WES) for a rural area with uninterrupted power. Power Point Tracking (PPT) is ordinarily involved in wind systems to maximize the output power from wind generator regardless of the weather changes. Though the sensor less control of tip speed ratio (TSR) is preferred at most, incorporation of the high speed digitized wind gauge replaces the complexity in the closed loop drive of turbine generator. Wind power output capacity, however, is still low and the associated costs still high, so efforts continue to develop WES converter and its controller, aiming for higher power-extracting efficiency and cost effectiveness. For many applications, uninterrupted power is essential. In this proposed system, the Wind energy system with Battery Energy Storage System (BESS) is contributed in the power system for continuous power. Efficient utilization of wind power decides the efficiency of power system. Bidirectional DC-DC converter and Power source selector (PSS) controls the source of power to load. PSS controls charging and discharging of BESS without any wastage of wind power so that the chance of using fossil fuel get reduced. The simulation for switching sequences of PSS is presented.
An Analysis of Perception and Uptake of Insurance Products among Medium-low Income Earners in Kenya

Although the insurance industry in Kenya has been growing in investment, there have been fundamental challenges in the number of new clients being recruited thus low penetration levels have been reported. The fast market growth notwithstanding, penetration rates remain low, at just 3% of GDP in 2013, 2014 and 2015 is still far below other developing economies. The high level of growth along low levels of penetration could lead the Kenyan insurance industry in crises in the near future. Therefore it is necessary to investigate into the trends in insurance uptake and the contributing factors. This study was designed to analyze perception and uptake of insurance products among medium-low income earners in Kenya on the basis that insurance penetration in Kenya is severely limited, which could have been as a result of the insured perception. The study was conducted using the explanatory research design. Primary data was collected using questionnaires administered to teachers using the drop and pick method. Quantitative data analysis was done using multiple response analysis techniques, mean, mode, standard deviation, percentages and frequencies. The study found out that perceptions on insurance played a key role in insurance uptake as the industry was marred by negative perceptions among potential customers hence low penetration. It is recommended that further research be conducted to evaluate customer experiences arising from insurance clients following the view held by majority insurance holders that they would not purchase insurance in the future.
Type IV collagen : characterization of the COL4A5 gene, mutations in Alport syndrome, and autoantibodies in Alport and Goodpasture syndromes

Type IV collagen is only found in basement membranes, where it is the major structural component, providing a framework for the binding of other basement membrane components and a substratum for cells. The type IV collagen molecule is triple-helical and composed of three α chains which exist as six distinct forms (α1 – α6). Abnormalities in this basement membrane collagen structure and function are connected to both inherited and acquired diseases. Alport syndrome is a hereditary kidney disease associated with extrarenal complications, such as sensorineural deafness and eye abnormalities. The disease is caused by mutations in the COL4A3, COL4A4 and COL4A5 genes, coding for the type IV collagen α3, α4 and α5 chain genes, respectively. About 85% of the Alport syndrome cases are X-linked dominant, caused by mutations in the COL4A5 gene. In order to develop a basis for automated mutation analysis of the COL4A5 gene, previously unknown intron sequences flanking exons 2 and 37 were determined. Intron sequences flanking the other 49 exons were expanded from 35 to 190, and additionally, two novel 9 bp exons (exons 41A and 41B) were characterized in the large intron 41. In addition to optimization of the PCR amplification and sequencing conditions for all 51 exons and exon flanking sequences, optimization for the 820 bp promoter region and for the two novel exons was performed as well. Mutations were found in 79 unrelated patients of the 107 studied. This gives a high mutation detection rate of almost 75% in comparison with 50%, at its best, in other extensive mutation analyses of the COL4A5 gene using SSCP analysis. None of the mutations involved the promoter region or exons 41A and 41B. Circulating antibodies against basement membrane components have been recognized in some autoimmune diseases. Goodpasture syndrome is a rare autoimmune disease characterized by progressive glomerulonephritis and pulmonary hemorrhage. The target of the antibodies in this disease has been shown to be the noncollagenous NC1 domain of type IV collagen α3 chain. For unknown reasons, a minority of Alport syndrome patients also develops antibodies against α3 and α5 chains after renal transplantation with manifestation of severe anti-GBM disease. In order to investigate the antibodies both in Goodpasture and Alport syndrome, the NC1 domains of all six type IV collagen chains were produced as recombinant proteins in bacterial and mammalian expression systems, and an ELISA method was developed for antibody detection. Antibodies were found in both syndromes, interestingly also in Alport syndrome patients without the anti-GBM disease. The results of this work have a significant clinical value by providing for the first time complete, effective DNA-based analysis of all exon/intron and promoter regions of the COL4A5 gene in Alport syndrome.
Compressive Sensing in Signal Processing: Algorithms and Transform Domain Formulations

Compressive sensing has emerged as an area that opens new perspectives in signal acquisition and processing. It appears as an alternative to the traditional sampling theory, endeavoring to reduce the required number of samples for successful signal reconstruction. In practice, compressive sensing aims to provide saving in sensing resources, transmission, and storage capacities and to facilitate signal processing in the circumstances when certain data are unavailable. To that end, compressive sensing relies on the mathematical algorithms solving the problem of data reconstruction from a greatly reduced number of measurements by exploring the properties of sparsity and incoherence. Therefore, this concept includes the optimization procedures aiming to provide the sparsest solution in a suitable representation domain. This work, therefore, offers a survey of the compressive sensing idea and prerequisites, together with the commonly used reconstruction methods. Moreover, the compressive sensing problem formulation is considered in signal processing applications assuming some of the commonly used transformation domains, namely, the Fourier transform domain, the polynomial Fourier transform domain, Hermite transform domain, and combined time-frequency domain.
Case Study: ENSO Events, Rainfall Variability and the Potential of SOI for the Seasonal Precipitation Predictions in Iran

The studies in recent decades show that many natural disasters such as tropical severe storms, hurricanes development, torrential rain, river flooding, and landslides in some regions of the world and severe droughts and wildfires in other areas are due to El Nino-Southern Oscillation (ENSO). This research aims to contribute to an improved definition of the relation between ENSO and seasonal (autumn and winter) variability of rainfall over Iran. The results show that during autumn, the positive phase of SOI is associated with decrease in the rainfall amount in most part of the country; negative phase of SOI is associated with a significant increase in the rainfall amount. It is also found that, during the winter time when positive phase of SOI is dominant, winter precipitation increases in most areas of the eastern part of the country while at the same time the decreases in the amount of rainfall in other parts is not significant. Moreover, with negative phase of SOI in winter season the amount of rainfall in most areas except south shores of Caspian Sea in the north decreases, so that the decrease of rainfall amount in the eastern part is statistically significant.
Hope—The Anchor of the Soul: Cultivating Hope and Positive Expectancy

Although hope is a valued construct in psychotherapy, it tends to be viewed as adjunct to more focal interventions or as leverage for other valued goals. We contend that hope needs to be a targeted intervention in many cases. We will highlight issues arising in the acquisition of therapeutic hope. We acknowledge hope's dual nature as both a "gift" from God as well as an attribute that can be cultivated. Our main objectives are to define hope, confirm its essential role in well-being, recognize various hope mechanisms, introduce relevant theory, briefly highlight hope attainment issues, promote a variety of hope interventions, and list some helpful assessments and resources that can aid in nuturing the seeds of hope and optimism. Evidence will be reviewed for the role of hope and optimism in relation to physical and mental health, life success and satisfaction, and resilience during adversity. We advocate for the central role of hope in God's plan for his children as well as fundamental to effective psychotherapy.
Machine learning for identifying botnet network traffic

During the last decade, a great scientific effort has been invested in the development of methods that could provide efficient and effective detection of botnets. As a result, various detection methods based on diverse technical principles and various aspects of botnet phenomena have been defined. Due to promise of non-invasive and resilient detection, botnet detection based on network traffic analysis has drawn a special attention of the research community. Furthermore, many authors have turned their attention to the use of machine learning algorithms as the mean of inferring botnet-related knowledge from the monitored traffic. This paper presents a review of contemporary botnet detection methods that use machine learning as a tool of identifying botnet-related traffic. The main goal of the paper is to provide a comprehensive overview on the field by summarizing current scientific efforts. The contribution of the paper is threefold. First, the paper provides a detailed insight on the existing detection methods by investigating which bot-related heuristic were assumed by the detection systems and how different machine learning techniques were adapted in order to capture botnetrelated knowledge. Second, the paper compares the existing detection methods by outlining their characteristics, performances, and limitations. Special attention is placed on the practice of experimenting with the methods and the methodologies of performance evaluation. Third, the study indicates limitations and challenges of using machine learning for identifying botnet traffic and outlines possibilities for the future development of machine learning-based botnet detection systems. Keywords—Botnet, Botnet detection, State of the art, Traffic analysis, Machine learning