Miracle-dz/UniFAR-FTUs huggingface dataset:
AN EMPIRICAL STUDY ON THE EFFECT OF LEADERSHIP STYLES ON EMPLOYEE WELLBEING AND ORGANIZATIONAL OUTCOMES WITHIN AN AUSTRALIAN REGIONAL UNIVERSITY

Leadership has increasingly become a major research focus in the corporate sector as well as in the higher education sector (HES). Previous studies have shown that different leadership styles play a significant role in promoting both employee wellbeing and organizational outcomes. However, there is a lack of clear understanding of how leadership, employee wellbeing and organizational outcome such as job satisfaction, organizational commitment and turnover intention interact together in the HES context, particularly within Australian regional university settings. The HES has two distinct staff cohorts, academic and professional, who have a stake in tertiary education leadership and management that further add to the complexities of leadership within the sector. Moreover, research into HES leadership uses many different leadership theories with results primarily focused on academic leadership. More expansive and pluralist approaches are necessary if we are to better understand the contextual complexities of leadership in the current HES. A review of leadership studies literature also suggests that researchers have either focused on the relationship between a specific leadership style and wellbeing; leadership styles and organizational outcomes‟ or the relationship between wellbeing and organizational outcomes, but rarely do empirical studies examine all three concurrently. For a complex organization such as a university, an effective way of examining leadership may be by applying leadership theories that examine a diverse range of leadership styles concurrently. The Full Range of Leadership Theory (FLRT) examines transformational, transactional and laissez-faire leadership styles within a single continuum that may provide a way to concurrently examine how these differing leadership styles may impact on leadership effectiveness in the HES context. The proposed PhD research project that this paper draws upon aims to examine the lived experiences of leadership amongst both academic and professional staff working in an Australian regional university by exploring the relationships between leadership style, employee wellbeing and organizational outcomes. The proposed project takes a mixed method approach using both qualitative and quantitative methods and analysis. Given the timing of the project, the focus of the paper and presentation for the Australasian Conference on Business and Social Sciences 2015 will be a position paper exploring the literature review and research design for this project.
Question 1 Is There a Significant Relationship Between Components of WM and Reading Growth , and Is Such a Relationship Dependent on the Type of Reading Task ?

This cohort-sequential study explored the components of working memory (WM) that underlie second language (L2) reading growth in 450 children at risk and not at risk for reading disabilities (RD) whose first language is Spanish. English language learners designated as balanced and nonbalanced bilinguals with and without risk for RD in Grades 1, 2, and 3 at Wave 1 were administered a battery of cognitive (short-term memory, WM, naming speed, and inhibition), vocabulary, and reading measures in Spanish and English. These same measures were administered 1 and 2 years later. Two important findings occurred: First, growth in the WM executive component was significantly related to growth in English word identification and passage comprehension when competing measures (phonological processing, naming speed, inhibition, and fluid intelligence) were entered into the multilevel growth model. Second, children defined as at risk for RD in Wave 1 had lower intercepts than children not at risk at Wave 3 across several measures of cognition, language, and achievement. However, except on measures of the executive component of WM, no significant group differences in linear growth emerged. These findings suggest that growth in L2 reading was tied to growth in the executive system of WM.
E. PAKOCI, B. POPOVIĆ, D. PEKAR IMPROVEMENTS IN SERBIAN SPEECH RECOGNITION USING SEQUENCE-TRAINED DEEP NEURAL NETWORKS

Pakoci E. , Popović B. , Pekar D. Improvements in Serbian Speech Recognition using Sequence-Trained Deep Neural Networks. Abstract. This paper presents the recent improvements in Serbian speech recognition that were obtained by using contemporary deep neural networks based on sequence-discriminative training to train robust acoustic models. More specifically, several variants of the new large vocabulary continuous speech recognition (LVCSR) system are described, all based on the lattice-free version of the maximum mutual information (LF-MMI) training criterion. The parameters of the system were varied to achieve best possible word error rate (WER) and character error rate (CER), using the largest speech database for Serbian in existence and the best n-gram based language model made for general purposes. In addition to tuning the neural network itself (its layers, complexity, layer splicing etc.) other language-specific optimizations were explored, such as the usage of accent-specific vowel phoneme models, and its combination with pitch features to produce the best possible results. Finally, speech database tuning was tested as well. Artificial database expansion was made by modifying speech speed in utterances, as well as volume scaling in an attempt to improve speech variability. The results showed that 8-layer deep neural network with 625-neuron layers works best in the given environment, without the need for speech database augmentation or volume adjustments, and that pitch features in combination with the introduction of accented vowel models provide the best performance out of all experiments.
Reproductive biology of the swordfish Xiphias gladius in the Straits of Florida and adjacent waters

The swordfish Xiphias gladius Linnaeus inhabits all tropical, subtropical, and temperate oceans of the world, including the Mediterranean Sea and the Gulf of Mexico. In the western Atlantic, it is found from Newfoundland to Argentina (Palko et al. 1981, Nakamura 1985). Swordfish occur in the Florida Straits at all times of the year. Prior to 1970, swordfish were pursued primarily by recreational fishermen. During the 1970s, the fishery in Florida attracted displaced Cuban-Americans and New England longline fishermen, and by 1980 commercial landings from the east coast of Florida had reached nearly 1500mt (Berkeley and Irby 1982). Little is known about the reproductive biology of swordfish in the western Atlantic. Ovchinnikov (1970) and Berkeley and Houde (1980) reported contradictory findings on male and female sizes-at-maturity. Wilson (1984) reported that males mature at younger ages than do females in the U.S. south Atlantic. Descriptions of swordfish spawning season and spawning grounds have been based on the temporal and areal distribution of infrequentlycollected larvae and juveniles (Arata 1954, Tibbo and Lauzier 1969 Markle 1974, Grall et al. 1983). Ou; research objectives were to determine t? e sizeand age-at-maturity, spawmng season, and approximate spawning grounds of swordfish in the Straits of Florida and adjacent waters. Data were collected as part of a joint Florida Marine Research Institute and University of Miami investigation of the fishery and biology of the swordfish. Samples gathered during this research have been used to develop a method to determine the ages of swordfish and to describe their growth (Berkeley and Houde 1984).
Determination of the strain-optical parameters for a polarimetric optical sensor embedded in a composite laminate

Abstract Polarimetric fibre optical sensors embedded in composite laminates are capable of detecting damage in the form of matrix cracking. To interpret the behaviour of the sensors when damage develops, it is first necessary to determine the strain-optical parameters of the sensor itself. In this work, the sensitivity of a bare polarimetric sensor manufactured from Hi-Bi PANDA fibre has been measured experimentally and a phase-strain model available in the literature has been used to determine the characteristic parameters of the optical fibre. The results suggest that a polarimetric sensor based on the PANDA fibre embedded in a composite laminate will be less sensitive to damage development than an equivalent sensor based on Bow-tie fibre.
Attacks on Distributed Sequential Control in Manufacturing Automation

Industrial Internet of Things (IIoT) represents a backbone of modern reconfigurable manufacturing systems (RMS), which enable manufacturing of a high product variety through rapid and easy reconfiguration of manufacturing equipment. In IIoT-enabled RMS, modular equipment is built from smart devices, each performing its own tasks, whereas the global functioning is achieved through their networking and intensive communication. Although device communication contributes to the system reconfigurability, it also opens up new security challenges due to potential vulnerability of communication links. In this article, we present security analysis for a major part of RMS in which manufacturing equipment is sequentially controlled and can be modeled as discrete event systems (DES). Control distribution within DES implies communication of certain events between smart modules. Specifically, in this work, we focus on attacks on communication of these events. In particular, we develop a method for modeling such attacks, including event insertion and removal attacks, in distributed sequential control; the method is based on the supervisory control theory framework. We show how the modeled attacks can be detected and provide a method for identification of communication links that require protection to avoid catastrophic damage of the system. Finally, we illustrate and experimentally validate applicability of our methodology on a real-world industrial case study with reconfigurable manufacturing equipment.
Aggregate Liquidity for Malaysian Stock Market : New Indicators and Time Series Properties

This study constructs two liquidity indicators, “Closing Percent Quoted Spread” and “Closing Percent Quoted Spread Impact”, for all publicly listed firms on Bursa Malaysia over the 2000-2014 sample period. The raw firm-level daily liquidity values are averaged across months and then aggregated using equaland value-weighted schemes to provide two Malaysian monthly aggregate liquidity indicators. Tracking the level of market liquidity over the last 15 years, all indicators consistently show that there is an obvious dry-up in liquidity in year 2008 when the bankruptcy of Lehman Brothers shattered confidence in the financial markets. Unlike the U.S. stock exchanges, there is no conclusive evidence to suggest that liquidity in the Malaysian market has improved over the sample period. However, in the short-term, there is evidence of seasonality in which the market is less liquid at year end as compared to the beginning of the year. Further structural break analysis indicates that the sharp liquidity changes in the Malaysian stock market are mainly driven by reactions to international events. When comparing with other commonly used liquidity proxies, the correlation analysis provides evidence in the Malaysian context that the turnover ratio is a poor indicator of liquidity. JEL Classification: C10, G12, G20
Pyruvate attenuate lipid metabolic disorders and insulin resistance in obesity induced in rats

This study was designed to evaluate the effect of prolonged intake of Pyruvate on insulin resistance, leptin and lipid metabolism in obesity -induced in female rats by feeding high fat diet. Fifty female albino rats were divided into five equal groups of 10 rats each. Group Ι :( Control negative group): rats fed normal diet. Group II: (Control positive group): rats fed high fat diet (HFD) and administered no drugs. Group III: rats fed HFD and administered pyruvate (270 mg/kg b. wt. /day, orally) for 8 weeks. Group IV: rats received HFD and administered pyruvate (540 mg/kg b. wt. /day, orally). Group V: rats received the control normal diet and administered pyruvate once daily (540 mg/kg b. wt., orally) for 8 weeks. Blood samples were collected at 2, 6, 8 weeks from the onset of pyruvate administration for determination of serum glucose, insulin, insulin resistance, leptin, total cholesterol (TC), triacylglycerol (TAG), phospholipids, Low density lipoprotein-cholesterol (LDL-c), Very low density lipoprotein-cholesterol (VLDL-c) and High density lipoprotein-cholesterol (HDL-c) levels in addition to serum transaminases enzymes (AST, ALT) and creatine kinase-MB (CK-MB) activities. The obtained results revealed that, rats fed HFD exhibited marked hyperglycemia, significant elevation of serum leptin, insulin and insulin resistance, AST, ALT and CK-MB, lipids profile (TC, TAG,LDL-C, VLDL-c) with marked decreased in serum HDL-c concentrations compared to rats fed normal diet. Meanwhile, administration of pyruvate to HFD-fed rats tended to prevent hyperglycemia, improve dyslipidemia and other changes relevant to cardiovascular disease mainly through improving leptin and insulin resistance. These results suggest that, pyruvate is effective in improving the obesity with its associated many important complications such as diabetes mellitus and coronary heart
PREVALENCE OF DENTAL DISORDERS IN WORKING DONKEYS IN EGYPT

A total of 100 working donkeys of subjected to field clinical dental examinations. A modified flexible low costed industrial endoscope, attached to a laptop facilitated detailed examination of the oc teeth. All of the presented donkeys were found suffering from different varieties of dental disorders despite their owners' histories devoid of any dental complaints. The recorded prevalent dental disorders were den overgrowth (10%),
the Mitigating Effect of Communication Climate on Organizational Identification and The Influence of Followership

Today’s workplaces are in need of followers who are proactively engaged in leadership process and bring fresh ideas to organizations. The study aims to empirically investigate to how does followership interact with leadership and explore the factors which influence the impact of followership on organizational outcome. The two behavioral dimensions of Kelley’s (1992) followership scale was adapted for analyses. The active engagement dimension of followership has positive impact on organizational identification, and communication climate was discovered as a critical element to mediate the influence. The paper suggests new insights on organizational management and provides a foundation for further followership research.
Agricultural Academy SEMEN PARAMETERS AND THEIR SEASONAL VARIATIONS OF LOCAL ARBIA BREED BUCKS IN WESTERN ALGERIA

Belhamiti, T.B. , A. Ait Amrane, S.M. Hammoudi, S.M.A. Selles, A.R. Benia, E.A. Mammeri and R. Kaidi, 2018. Semen parameters and their seasonal variations of local Arbia breed bucks in Western Algeria. Bulg. J. Agric. Sci.,
EUCLID Located Strokes to the Gaisberg Tower – Accuracy of Location and its assigned Confidence Ellipse

In this paper we analyze LLS located discharges (return strokes and superimposed ICC pulses) to the Gaisberg Tower (GBT) in terms of their location accuracy and assigned confidence ellipse (often also called error-ellipse). From 2000 to 2013 EUCLID (ALDIS) located 681 return strokes and 779 ICC pulses in upward initiated flashes from the GBT. We found that for 49 % of the return strokes and for 48 % of the ICC pulses the true tower location was inside the 50% confidence ellipse assigned by the LLS to the LLS estimated striking point. After implementation of several improvements in the location algorithm median location accuracy for strokes to the GBT is in the range of 100 m. For the most recent years (GBT data since 2010) we observe a significantly higher than expected percentage of GBT location being included in the assigned confidence ellipse. Most likely this is a result of the discretization of the length of the semi-major axis of confidence ellipse in 100 m steps, which is in the same range as the median location accuracy. Keywords— lightning, confidence ellipse, location accuracy
Volume 19, Coastal Atmosphere and Sea Time Series (CoASTS), Part 1: A Tower-Based, Long-Term Measurement Program

The Coastal Atmosphere and Sea Time Series (CoASTS) Project, aimed at supporting ocean color research and applications, from 1995 up to the time of publication of this document, has ensured the collection of a comprehensive atmospheric and marine data set from an oceanographic tower located in the northern Adriatic Sea. The instruments and the measurement methodologies used to gather quantities relevant for bio-optical modeling and for the calibration and validation of ocean color sensors, are described. Particular emphasis is placed on four items: 1) the evaluation of perturbation effects in radiometric data (i.e., tower-shading, instrument self-shading, and bottom effects); 2) the intercomparison of seawater absorption coefficients from in situ measurements and from laboratory spectrometric analysis on discrete samples; 3) the intercomparison of two filter techniques for in vivo measurement of particulate absorption coefficients; and 4) the analysis of repeatability and reproducibility of the most relevant laboratory measurements carried out on seawater samples (i.e., particulate and yellow substance absorption coefficients, and pigment and total suspended matter concentrations). Sample data are also presented and discussed to illustrate the typical features characterizing the CoASTS measurement site in view of supporting the suitability of the CoASTS data set for bio-optical modeling and ocean color calibration and validation.
An analysis of the magnetic behavior of olivine and garnet substitutional solid solutions

Abstract The low-temperature magnetic properties and Néel temperature, TN, behavior of four silicate substitutional solid solutions containing paramagnetic ions are analyzed. The four systems are: fayalite-forsterite olivine [Fe22+SiO4-Mg2SiO4], and the garnet series, grossular-andradite [Ca3(Alx,Fe31+ –x)2Si3O12], grossular-spessartine [(Cax,Mn21+ –x)3Al2Si3O12], and almandine-spessartine [(Fex2+,Mn21+ –x)3Al2Si3O12]. Local magnetic behavior of the transition-metal-bearing end-members is taken from published neutron diffraction results and computational studies. TN values are from calorimetric heat capacity, C P, and magnetic susceptibility measurements. These end-members, along with more transition-metal-rich solid solutions, show a paramagnetic to antiferromagnetic phase transition. It is marked by a C P l-anomaly that decreases in temperature and magnitude with increasing substitution of the diamagnetic component. For olivines, TN varies between 65 and 18 K and TN for the various garnets is less than 12 K. Local magnetic behavior can involve one or more superexchange interactions mediated through oxygen atoms. TN behavior shows a quasi-plateau-like effect for the systems fayalite-forsterite, grossular-andradite, and grossular-spessartine. More transition-metal-rich crystals show a stronger TN dependence compared to transition-metal-poor ones. The latter may possibly show superparamagnetic behavior. (Fex2+,Mn21+ –x)3Al2Si3O12 garnets show fundamentally different magnetic behavior. End-member almandine and spessartine have different and complex interacting local superexchange mechanisms and intermediate compositions show a double-exchange magnetic mechanism. For the latter, TN values show negative deviations from linear interpolated TN values between the end-members. Double exchange seldom occurs in oxides, and this may be the first documentation of this magnetic mechanism in a silicate. TN behavior may possibly be used to better understand the nature of macroscopic thermodynamic functions, C P and S °, of both end-member and substitutional solid-solution phases.
Bacteriological diagnosis of bovine tuberculosis in bovines positive to the tuberculin test

Mycobacterium bovis is the causative agent of bovine tuberculosis (BTB), considered a zoonotic disease. In our country, the diagnosis is based on the application of the tuberculin skin test (TST). Conventional culture, from various biological samples, can complement the TST test results. Regarding this, it is possible to perform sampling and subsequent analysis of nasal discharge, milk and tissues. The latter allows the observation of macroscopic lesions, the anatomical location in addition to collect biological samples to be analyzed by bacteriology and histopathology. The aim of this study was to evaluate the presence of M. bovis in samples of nasal secretions, milk and tissues in cattle PAC-positive and characterize gross and microscopic lesions compatible with BTB. A total of 744 samples belonging to 572 cattle from dairy herds in the provinces of Córdoba, Santa Fe and Buenos Aires, were processed. All of them were, during this study, in stage of control of BTB showing a low prevalence (between 0.5 to 4%). About 12.4% (71/572) M. bovis isolations from cattle examined was obtained. These isolations were from tissue samples 36.5% (38/104), followed by milk 10.7% (23/214) and nasal secretions 3.9% (10/254). Bacteriology from milk samples and nasal secretions were of limited effectiveness. On the other hand, tissue analysis was more useful as complementary diagnostic, allowing confirmation of suspected cases of BTB.
Improving Robustness to Attacks Against Vertex Classification

Vertex classification—the problem of identifying the class labels of nodes in a graph—has applicability in a wide variety of domains. Examples include classifying subject areas of papers in citation networks or roles of machines in a computer network. Recent work has demonstrated that vertex classification using graph convolutional networks is susceptible to targeted poisoning attacks, in which both graph structure and node attributes can be changed in an attempt to misclassify a target node. This vulnerability decreases users’ confidence in the learning method and can prevent adoption in high-stakes contexts. This paper presents work in progress aiming to make vertex classification robust to these types of attacks. We investigate two aspects of this problem: (1) the classification model and (2) the method for selecting training data. Our alternative classifier is a support vector machine (with a radial basis function kernel), which is applied to an augmented node feature-vector obtained by appending the node’s attributes to a Euclidean vector representing the node based on the graph structure. Our alternative methods of selecting training data are (1) to select the highest-degree nodes in each class and (2) to iteratively select the node with the most neighbors minimally connected to the training set. In the datasets on which the original attack was demonstrated, we show that changing the training set can make the network much harder to attack. To maintain a given probability of attack success, the adversary must use far more perturbations; often a factor of 2–4 over the random training baseline. Even in cases where success is relatively easy for the attacker, we show that the classification and training alternatives allow classification performance to degrade much more gradually, with weaker incorrect predictions for the attacked nodes