Miracle-dz/UniFAR-FTUs huggingface dataset:
Mannoheptulose has differential effects on fasting and postprandial energy expenditure and respiratory quotient in adult Beagle dogs fed diets of different macronutrient contents

The present study aimed to determine the effects of mannoheptulose (MH) (8 mg/kg) on energy expenditure (EE), respiratory quotient (RQ) and glycaemic response in healthy adult Beagle dogs (n 8; 9·62 (sem 0·31) kg; body condition score 4·5). The study was designed as replicated 4 × 4 Latin squares with a 2 × 2 factorial treatment structure. The dietary treatments were low carbohydrate (CHO) relative to fat diet (LC; 31 % CHO, 28 % fat) with placebo (0 mg/kg) or MH supplement and high CHO relative to fat diet (HC; 54 % CHO, 11 % fat) with placebo (0 mg/kg) or MH supplement. Dogs were fed to maintain body weight (HC and HC+MH 3625 (sem 295) kJ and LC and LC+MH 3542 (sem 284) kJ). Resting and postprandial (0–4 h; 5–10 h; 11–17 h; 18–23 h) EE and RQ were determined by indirect calorimetry (days 12 or 14). Glycaemic response to a meal (24 h) and plasma MH concentrations were determined on days 12 or 14. Plasma MH followed first-order kinetics, confirming that MH is absorbed and available to the animal. In the presence of high dietary CHO, MH increased postprandial EE (5–10 h only), suggesting MH increased dietary induced thermogenesis. In contrast to earlier reports, MH did not affect serum glucose or insulin in the present study. Irrespective of MH, dogs adapted RQ to diet composition and dogs consuming the LC diet had a greater incremental AUC for glucose, but not insulin, than dogs consuming the HC diet.
The validation of a workplace boredom scale within the South African context

Orientation: Boredom at work has been shown to be a concern for individuals and organisations. At the time of this research, no validated scale was available to measure and investigate workplace boredom within the South African context. Research purpose: To determine whether the Dutch Boredom scale (DUBS) is valid and reliable for use within the South African context. Motivation for the study: No reliable and valid scale for workplace boredom was available in South Africa at the time of the current research. Boredom at work has been found to affect organisations negatively in other countries. Insight into workplace boredom and how it affects the performance of organisations needed to be gained. Research design, approach and method: A cross-sectional research approach was utilised. A random convenience sample (N = 490) was used from organisations within the manufacturing and logistics sector. In order to validate the DUBS, the reliability, factorial validity, convergent validity, predictive validity and discriminant validity for the scale were investigated. Main findings: Results showed that the DUBS could be confirmed as a one-factor structure, and that this factor has acceptable reliability. Relationships between workplace boredom and dissimilar theoretical constructs were negatively and practically significantly correlated. Workplace boredom showed significant negative regressions to work engagement, job satisfaction and organisational commitment. No significant relationship was found between workplace boredom and gender. Practical/Managerial implications: Management should not neglect workplace boredom as results showed how it affects work engagement, job satisfaction and organisational commitment levels within the South African context. Therefore, workplace boredom is a concern for overall organisational performance. Contribution/Value-add: This study contributes to the limited research available on workplace boredom for both the individual and the organisation with regard to organisational outcomes in South Africa by providing a reliable and valid scale.
Improving the accuracy of Search Engine based anti-phishing solutions using lightweight features

A drawback of the Search Engine (SE) based anti-phishing technique is that authentic websites that are newly launched over the web are classified as phishing websites due to their low ranking. This causes a noticeable reduction in the True Negative Rate (TNR) of such schemes. Some SE based techniques use other complex anti-phishing techniques or features in combination to increase the TNR which results in higher accuracy. However, such an addition dilutes the importance of SE based techniques, which are intended to make anti-phishing lightweight, client side implementable and efficient. In this paper, we study a set of lightweight features including https, digits in domain name and Google Safe Browsing (GSB) API check, and the effect of their addition to the results of a SE based solution. An eventual effect on the accuracy of the existing SE based schemes is also reflected in this paper. A total shift of nearly 96% from False Positive Rate (FPR) to TNR is recorded with a slight decrease of 0.1% in True Positive Rate (TPR), thus increasing the accuracy by 3.28%.
Using SVM for classification in datasets with ambiguous data

One of the challenges in machine learning is the classification of datasets with ambiguous instances. In this paper we study specifically datasets with examples that have overlapping feature values for different classes. In these circumstances there is a bound on the classification performance. While there seems to be a race for accuracy, very little has been done to understand and solve the issues related to ambiguous data where the possible classification performance is limited. We discuss the use of SVMs in a proposed scheme to handle classification in such problem domains. A new approach is offered that tries to separate ambiguous data from the data that are much simpler to classify in order to prevent their influence on the classification process. We demonstrate that by separating the ambiguous data, although we lose some data, the performance of the classification increases significantly. In contrast to previous findings with some other classifiers, our experimental results show that the performance of SVM classifiers on cleaned data is not affected significantly when there are some atypical points in the training data.
Enhancing success in higher education by measuring student engagement in South Africa

Improving student success and throughput rates are key challenges facing South African higher education. International research shows that a focus on student engagement can help to enhance student learning and other desired outcomes as well as the efficiency and effectiveness of higher education systems. The paper documents the psychometric properties of the South African Survey of Student Engagement (SASSE), providing a sound basis on which to promote large scale studies of student engagement-related interventions. Using this contextualized measure will allow South African institutions to engage in national, as well as international benchmarking with countries such as the United States, Canada and Australia. Opsomming Die verbetering van sukses en deurvloeikoerse is een van die sleutel uitdagings wat Suid-Afrikaanse hoer onderwys in die gesig staar. Internasionale navorsing toon dat student betrokkenheid ŉ kragtige instrument kan wees om student sukses en die effektiwiteit en doeltreffendheid van die hoer onderwys stelsel te verbeter. Die psigometriese eienskappe van die Suid-Afrikaanse Opname vir Studente Betrokkenheid (SAOSB) word bespreek en daar word geargumenteer dat die eienskappe ŉ goeie basis lewer vir die studie van studente betrokkenheid. Die gebruik van ŉ gekontekstualiseerde instrument sal Suid-Afrikaanse instellings in staat stel om nasionale afsnypunte (benchmarks) te ontwikkel wat internasionaal vergelyk kan word met die Verenigde State, Kanada en Australie.
Abusive Supervision and Employee Performance:Mechanisms of Traditionality and Trust

Abusive supervision has attracted increasing attention in Western academy of management.In mainland China,there is no such academic investigation though,in practice,abusive supervision is prevailing due to Chinese cultural root that is characterized by hierarchy and high level of power distance.To fill the gap,the study aims to address:within the context of Chinese organizations,what are the major mediating and moderation mechanisms linking abusive supervision and employee performance? Drawing on the social exchange theory,we propose that employee's trust in the supervisor will mediate the relationship between abusive supervision and employee outcomes.We also propose that employee traditionality will moderate the process that abusive supervision exerts negative influence on employee outcomes.Theoretically,this echoes the call for examining the role of followers in the process of leadership(Howell Shamir,2005). In total,338 employees and 128 their supervisors from 6 electronic manufacturing enterprises located in Beijing were sampled.To avoid the common method variance problem,two waves as well as two sources of survey were administrated.In the first wave,employees were asked to provide ratings of abusive supervision and self-reported traditionality.In the second wave,employees provided ratings of trust in supervisors.In both waves,supervisors provided ratings of employee performance including task and organizational citizenship behaviors.Time 1 performance data was controlled when predicting Time 2 performance,which was the outcome of the study.The final matched sample included 283 employees and 112 direct supervisors,resulting valid response rates 83.7% and 87.5% for employees and supervisors,respectively.Among the major measures,the 15-item abusive supervision scale was adopted from Tepper(2000)study;trust in supervisor was measured via 6 items that was adopted from Wong et al.(2002)study.The 5-item task performance scale and the 14-item organizational citizenship behavior(OCB)scale were adapted from Williams and Anderson(1991). Cronbach's alpha coefficients for above measures were from 0.85 to 0.95,indicating acceptable measurement reliabilities.Hierarchical Regression Modeling(HRM)was employed to analyze the data.Results show that:in the Chinese organizational context,trust in supervisor mediates the relationship between abusive supervision and employee performance,demonstrating that social exchange is a unique angle for explaining how abusive supervision leads to negative employee outcomes.Comparing to non-traditional ones,traditional employees will more likely comply with abusive supervisors.They will respond less distrust in abusive supervisors.This finding could,to a large extent,offer insights why abusive supervisor is prevailing in Chinese organizations.
PASD1: A Promising Target for the Immunotherapy of Haematological

In general, there is a lack of good immunotherapy targets within the spectrum of haematological malignancies. However haematopoietic stem cell transplants and continuing antigen discovery have allowed further insight into how further improvements in outcomes for patients might be achieved. Most patients with haematological malignancies can be treated with conventional therapies such as radio- and chemotherapy and will attain first remission. However the removal of residual diseased cells is essential to prevent relapse and its associated high mortality. PASD1 is one of the most tissue restricted cancer-testis (CT) antigens with expression limited to primary spermatagonia in healthy tissue. However, characterisation of PASD1 expression in cancers has been predominantly focussed on haematological malignancies where the inappropriate expression of PASD1 was first identified. PASD1 has one of the highest frequencies of expression of all CT antigens in acute myeloid leukaemia, with some suggestion of its role as a biomarker in diffuse large B-cell lymphoma. Here we describe the characterisation of the function and expression patterns of PASD1 in cell lines and primary tissues. Development of DNA vaccines targeting PASD1 epitopes demonstrate effective ex vivo T-cell responses in terms of IFNγ secretion and tumour cell killing. Of particular note these vaccines have led to the destruction of cells which process and present endogenous PASD1 indicating that effectively primed CTLs could kill PASD1-positive tumour cells.
Likelihood Cross-Validation Versus Least Squares Cross-Validation for Choosing the Smoothing Parameter in Kernel Home-Range Analysis

Abstract Fixed kernel density analysis with least squares cross-validation (LSCVh) choice of the smoothing parameter is currently recommended for home-range estimation. However, LSCVh has several drawbacks, including high variability, a tendency to undersmooth data, and multiple local minima in the LSCVh function. An alternative to LSCVh is likelihood cross-validation (CVh). We used computer simulations to compare estimated home ranges using fixed kernel density with CVh and LSCVh to true underlying distributions. Likelihood cross-validation generally performed better than LSCVh, producing estimates with better fit and less variability, and it was especially beneficial at sample sizes <˜50. Because CVh is based on minimizing the Kullback-Leibler distance and LSCVh the integrated squared error, for each of these measures of discrepancy, we discussed their foundation and general use, statistical properties as they relate to home-range analysis, and the biological or practical interpretation of these statistical properties. We found 2 important problems related to computation of kernel home-range estimates, including multiple minima in the LSCVh and CVh functions and discrepancies among estimates from current home-range software. Choosing an appropriate smoothing parameter is critical when using kernel methods to estimate animal home ranges, and our study provides useful guidelines when making this decision.
Geneland: a computer package for landscape genetics

Geneland is a computer package that allows to make use of georeferenced individual multilocus genotypes for the inference of the number of populations and of the spatial location of genetic discontinuities between those populations. Main assumptions of the method are: (i) the number of populations is unknown and all values are considered a priori equally likely, (ii) populations are spread over areas given by a union of some polygons of unknown location in the spatial domain, (iii) Hardy-Weinberg equilibrium is assumed within each population and (iv) allele frequencies in each population are unknown and treated as random variable either following the so-called Dirichlet model or Falush model. Different algorithms implemented in Geneland to perform inferences are first briefly presented. Then major running steps and outputs (i.e. histogram of number of populations and map of posterior probabilities of population membership) are illustrated from the analysis of a simulated data set, which was also produced by Geneland. (Resume d'auteur)
Evolution and Learning: Evolving Sensors in a Simple MDP Environment

Natural intelligence and autonomous agents face difficulties when acting in information-dense environments. Assailed by a multitude of stimuli they have to make sense of the inflow of information, filtering and processing what is necessary, but discarding that which is unimportant. This paper aims at investigating the interactions between evolution of the sensorial channel extracting the information from the environment and the simultaneous individual adaptation of agent-control. Our particular goal is to study the influence of learning on the evolution of sensors, with learning duration being the tunable parameter. A genetic algorithm governs the evolution of sensors appropriate for the agent solving a simple grid world task. The performance of the agent is taken as fitness; ‘sensors’ are conceived as a map from environmental states to agent observations, and individual adaptation is modeled by Q-learning. Our experimental results show that due to the principles of cognitive economy learning and varying the degree thereof actually transforms the fitness landscape. In particular we identify a trade-off between learning speed (load) and sensor accuracy (error). These results are further reinforced by theoretical analysis: we derive an analytical measure for the quality of sensors based on the mutual entropy between the system of states and the selection of an optimal action, a concept recently proposed by Polani, Martinetz, and Kim.
Presented at Satnav 2003 the 6 Th International Symposium on Satellite Navigation Technology including Mobile Positioning & Location Services Locata: the Positioning Technology of the Future?

Locata Corporation has invented a new positioning technology called Locata, which is designed to overcome severe limitations in other positioning systems currently available. Part of the " Locata technology " consists of a time-synchronised pseudolite transceiver called a LocataLite. A network of LocataLites forms a LocataNet, which transmits GPS-like signals that allow single-point positioning using carrier-phase measurements for a mobile device (a Locata). The SNAP group at UNSW has assisted in the development of a Locata and testing of the new technology. In this paper, the prototype " Locata technology " is described, and the results of a performance test experiment are presented. The test experiment demonstrates proof-of-concept for the " Locata technology " and shows that carrier point positioning (without radio modem data-links) is possible with sub-centimetre precision.
Different Issues in the Design of a Lemmatizer/Tagger for Basque

This paper presents relevant issues that have been considered in the design of a general purpose lemmatizer/tagger for Basque (EUSLEM). The lemmatizer/tagger is conceived as a basic tool necessary for other linguistic applications. It uses the lexical data base and the morphological analyzer previously developed and implemented. Due to the characteristics of the language, the tagset here proposed in structured in for levels, so that each level is a refinement of the previous one in the sense that it adds more detailed information. We will focus on the problems found in designing this tagset and on the strategies for morphological disambiguation that will be used.
A Data Collection Protocol for Local Mobile Sensor Network

In future pervasive computing environments, applications should be able to automatically adapt to their changing context such as environment status and system conditions. Therefore, context information collection is an ignored yet significant research area. An efficient sensor data collection protocol is studied in this paper for a sensor header (collector) to continuously collect data from mobile nodes in its local access area, where the mobile node refers to a relatively tiny sensor often fixed on a mobile object without high precision antenna to sense carriers emitted by other nodes. The protocol consists of registration phase when one-to-many access model is used to identify the local nodes and data collection phase when the efficient one-to-one access model can be incorporated based on the result of first phase. Furthermore, the critical performance parameters are derived to analyze and control the runtime execution of the protocol. Simulation results show that the protocol performance improves in a wide mobility range by appropriately controlling the system parameters.
Optimal control and numerical optimization applied to epidemiological models

The relationship between epidemiology, mathematical modeling and computational tools allows to build and test theories on the development and battling of a disease. This PhD thesis is motivated by the study of epidemiological models applied to infectious diseases in an Optimal Control perspective, giving particular relevance to Dengue. Dengue is a subtropical and tropical disease transmitted by mosquitoes, that affects about 100 million people per year and is considered by the World Health Organization a major concern for public health. The mathematical models developed and tested in this work, are based on ordinary differential equations that describe the dynamics underlying the disease, including the interaction between humans and mosquitoes. An analytical study is made related to equilibrium points, their stability and basic reproduction number. The spreading of Dengue can be attenuated through measures to control the transmission vector, such as the use of specific insecticides and educational campaigns. Since the development of a potential vaccine has been a recent global bet, models based on the simulation of a hypothetical vaccination process in a population are proposed. Based on Optimal Control theory, we have analyzed the optimal strategies for using these controls, and respective impact on the reduction/eradication of the disease during an outbreak in the population, considering a bioeconomic approach. The formulated problems are numerically solved using direct and indirect methods. The first discretize the problem turning it into a nonlinear optimization problem. Indirect methods use the Pontryagin Maximum Principle as a necessary condition to find the optimal curve for the respective control. In these two strategies several numerical software packages are used.
Antiepileptic drugs for the treatment of neuropathic pain: A systematic review

Many therapies have been proposed for the management of neuropathic pain, and they include the use of different antiepileptic drugs. However, the lack of high quality studies indicates that results on the different neuropathic disorders under study do not recommend a particular drug treatment. This study makes a systematic review of the published literature on the use of several antiepileptic drugs to treat neuropathic pain, and has the objective of considering both its clinical characteristics and pharmacological use, which will depend on their level of scientific evidence and will follow the principles of evidence-based dentistry. The articles were stratified according to their scientific evidence using the SORT criteria (Strength of Recommendation Taxonomy), and it included those articles that only have level 1 or 2. Randomized clinical trials were stratified according to their level of quality using the JADAD scale, an instrument described by Jadad et al. (7). to assess the quality of clinical trials, while studies with a level below 3 were discarded. Recently, type A or B recommendations are given in favor or against the use of antiepileptic drugs to treat neuropathic pain on the basis of their scientific quality. Key words:Neuropathic pain, antiepileptic drugs (AEDs), trigeminal neuralgia, glossopharyngeal neuralgia, post- herpetic neuralgia, burning mouth syndrome, persistent idiopathic facial pain.