Miracle-dz/UniFAR-FTUs huggingface dataset:
Determinants of sickness absence and early retirement intentions and the relationship between sickness absence and the risk of disability retirement or early retirement intentions in the Abu Dhabi Police

Aims: To evaluate the influence of psychological and physical exposures, as well as employees’ perception of occupational health and safety management system, on the risk of sickness absence and early retirement intentions. The thesis also evaluates the relationship between sickness absence and early retirement intentions and disability retirement. Methods: Two systematic literature reviews were conducted; one of studies on sickness absence in the police and the second evaluated all studies examining sickness absence and disability retirement. A case control study investigated the association between sickness absence and disability retirement using data from the Abu Dhabi Police. In a second study, the first Arabic version of the Karasek’s Job Content Questionnaire (the Arabic JCQ) was developed and a linguistic and psychometrical validation was carried out. A cross-sectional survey of 1,317 employees of the Abu Dhabi Police was conducted in a third study. Results: In the case control study, sickness absence, defined using various measures, was a predictor of disability retirement. Psychometric testing of the Arabic JCQ was generally comparable with other studies. The cross-sectional survey was completed by 760 officers (58% response rate). Work factors in general were not associated with sickness absence while officers with low workplace support, unfavourable perception of the health and safety management systems and high exposure to physical work factors had higher risk of early retirement intentions. There was a significant increase in the risk of early retirement intention in officers with ≥4 days of sickness absence compared with those without any sickness absence. Conclusion: Monitoring sickness absence data may help in minimizing disability retirement and early retirement in general (through reducing early retirement intentions). The policing culture may discourage officers from taking sick leave and reporting problems at work which in turn, may result in shifting the consequences of work problems to private life and may encourage presenteeism.
Advective Fluxes in the Martian Regolith as a Mechanism Driving Methane and Other Trace Gas Emissions to the Atmosphere

Advective fluxes influence methane and CO2 soil emissions into the atmosphere on Earth and may drive trace gas emissions in the Mars atmosphere. However, their relevance in the Martian regolith has not been evaluated to date. Our regolith transport simulations show that advective fluxes can be relevant under Martian conditions and may drive the methane abundance detected by Mars Science Laboratory. Trace gas emissions would be highest in regions where winds interact with topography. Emissions in these regions may be further enhanced by time‐varying pressure fields produced by diurnal thermal tides and atmospheric turbulence. Trace gases such as methane should be emitted or produced from the first layers of regolith, or quickly transported to this region from a deeper reservoir through fractured media.
Multisample estimation of bacterial composition matrices in metagenomics data

Metagenomics sequencing is routinely applied to quantify bacterial abundances in microbiome studies, where bacterial composition is estimated based on the sequencing read counts. Due to limited sequencing depth and DNA dropouts, many rare bacterial taxa might not be captured in the final sequencing reads, which results in many zero counts. Naive composition estimation using count normalization leads to many zero proportions, which tend to result in inaccurate estimates of bacterial abundance and diversity. This paper takes a multisample approach to estimation of bacterial abundances in order to borrow information across samples and across species. Empirical results from real datasets suggest that the composition matrix over multiple samples is approximately low rank, which motivates a regularized maximum likelihood estimation with a nuclear norm penalty. An efficient optimization algorithm using the generalized accelerated proximal gradient and Euclidean projection onto simplex space is developed. Theoretical upper bounds and the minimax lower bounds of the estimation errors, measured by the Kullback–Leibler divergence and the Frobenius norm, are established. Simulation studies demonstrate that the proposed estimator outperforms the naive estimators. The method is applied to an analysis of a human gut microbiome dataset.
Variación de la asfericidad corneal en pacientes miopes sometidos a cirugía refractiva LASIK (Laser-Assisted in Situ Keratomileusis) o LASEK (Laser-Assisted Subepithelial Keratomileusis)

Objective : To analyze, through a systematic review of literature, the variation in corneal asphericity in myopic patients corrected with LASIK (laser-assisted in-situ keratomileusis) or LASEK (laser-assisted subepithelial keratomileusis) surgery. Methodology : A literature search for primary studies was performed in PubMed, Scopus, and Science Direct using the Vantage Point software, and 229 publications were collected; 19 of them met the inclusion criteria and were selected. The quality of these 19 articles was assessed using the FLC Web 2.0 platform for critical reading, based on the STROBE statement. The search used keywords such as corneal asphericity, corneal shape factor, Q-value, LASIK (laser-assisted in-situ keratomileusis), LASEK (laser-assisted subepithelial keratomileusis), and refractive surgery. Results : 18 of the evaluated articles had medium quality, and one of them had low quality. The articles agree on that there are changes in corneal asphericity after refractive surgery, from prolate to oblate, significantly affecting visual results. Conclusions : The analysis of these 19 articles evidenced a change in asphericity from prolate to oblate and revealed the factors influencing these variations, as well as the need for improving surgical techniques and deficiencies in research, since 95% of the analyzed articles had average quality.
On real-world patients and real-world outcomes : the Leiden Routine Outcome Monitoring Study in patients with mood, anxiety and somatoform disorders

This thesis focuses on real-world patients and real-world outcomes by using Routine Outcome Monitoring (ROM) in patients with Mood, Anxiety, and Somatoform (MAS) disorders. The primary aims of the series of studies were to investigate correlates of disease characteristics in a large cohort of treatment-seeking patients with MAS disorders, and to discuss these findings in relation to existing data derived from RCTs and general population studies. In addition, using prospective data, we investigated whether baseline characteristics measured with ROM could predict outcomes in real-world or naturalistic treatment settings. The secondary aim was to assess the feasibility of conducting large-scale clinical epidemiological research with ROM data that had been collected in everyday clinical practice, thereby representing the phenotype of ‘real’ patients.
"Goal Recognition Design - Artificial intelligence techniques in surveillance problems”

This thesis focuses on Goal Recognition, an innovative and still developing field of research in Artificial Intelligence, which involves determining an agent's goal by observing its behaviour. Several real-world applications can be modelled in this context, for example, surveillance problems, operations where it is necessary to preserve user privacy, chat-boxes, and human-robot interaction. In this dissertation, we consider an environment in which an intelligent agent, the target, performs actions that can be observed by another intelligent agent, the observer (or by the environment itself). We analyze an evasive or fleeing target that moves in the environment to reach its destination, while the observer tries to find it. An example of this scenario is a surveillance drone that flies over a wide geographical area to discover a criminal who is trying to reach a hideout by car as soon as possible. In this context, the observer runs Goal Recognition algorithms that aim to discover where the target is going. In particular, the observer needs to reason about the target's strategy to obscure its goals. To support this kind of reasoning, we propose a technique to calculate a new measure, the "undisclosing index", that represents the maximal length of the prefix of a path that a fleeing agent may take before its goal becomes apparent to the observer. Moreover, we present methods for the observer to reason about how the target might change its behaviour based on the resources that it has available: the target will take shorter or longer paths based on his total travel budget. We modelled the environment in which the agents move by using a connected graph. For our experiments, we construct the graphs based on data from a real web map provided by OpenStreetMap (OSM). We implemented a web application designed for this purpose. Through it, the user selects and exports an area of interest on the map, identifying the target's possible goals within that area. The web-app provides a viewable version of the graph, implements the algorithms that help the observer reason about the possible paths of the target based on its budget and visualize them. The experimental evaluation shows how the solutions proposed in this thesis are useful tools for solving Goal Recognition problems.
Stability evaluations of three-layered soil slopes based on extreme learning neural network

ABSTRACT Slope stability analysis is one of the most critical and important topics for geotechnical engineers and thus various stability charts have been developed in order to provide quick first assessments of slope stability. However, general chart solutions are often found to be insufficient for purpose when variables to be considered increase. Motivated by that, this study aims to adopt an artificial neural network (ANN) with the extreme learning machine algorithm to develop a convenient and efficient tool for assessing three-layered soil slope stability. The neural network is trained using the obtained solutions from the finite element upper and lower bound limit analysis methods. The proposed tool in this study is capable of providing a quick first assessment of three-layered soil slope stability. The results showed that the slope stability estimation using the proposed ANN-based tool can still maintain good accuracy and convenience.
Edge Computing-Based Tasks Offloading and Block Caching for Mobile Blockchain

Internet of Things (IoT) technology is rapidly evolving, but there is no trusted platform to protect user privacy, protect information between different IoT domains, and promote edge processing. Therefore, we integrate the blockchain technology into constructing trusted IoT platforms. However, the application of blockchain in IoT is hampered by the challenges posed by heavy computing processes. To solve the problem, we put forward a blockchain framework based on mobile edge computing, in which the blockchain mining tasks can be offloaded to nearby nodes or the edge computing service providers and the encrypted hashes of blocks can be cached in the edge computing service providers. Moreover, we model the process of offloading and caching to ensure that both edge nodes and edge computing service providers obtain the maximum profit based on game theory and auction theory. Finally, the proposed mechanism is compared with the centralized mode, mode A (all the miners offload their tasks to the edge computing service providers), and mode B (all the miners offload their tasks to a group of neighbor devices). Simulation results show that under our mechanism, mining networks obtain more profits and consume less time on average.
Climate change and non-infectious fish disorders

Abstract The current volume, entitled Climate Change and Non-infectious Fish Disorders (CCNFD) is the first of the two-volume set, and it focuses on the development, physiology and health of fish. CCNFD has 11 chapters organized into two parts. Chapters 1 and 2 (Part I) are mainly for aquatic biologists including colleagues who study non-infectious fish disorders and infectious fish diseases. These two chapters also set the stage for discussions in the remaining nine chapters. Chapter 1 presents an overview (both historical and current) on climate change while Chapter 2 is focused on abiotic changes in tropical marine and brackish ecosystems. Part II (Chapters 3-11) is on non-infectious disorders such as abnormal development, neoplasms, metabolism, feeding, the immune system, migration and overall health of fish. The principal audience for CCNFD includes research scientists in universities, aquatic biologists and fish health consultants in private or government laboratories. It is also useful to environmentalists and ecologists who monitor changes to the aquatic system. The book may be appropriate for the training of fish health specialists, and for graduate students and senior undergraduates who conduct field studies on fish and/or monitor changes to the aquatic environment.
CARDIOEMBOLIC STROKE IN LATVIA: PREVENTION AND LONG-TERM OUTCOME

INTRODUCTION: Untreated non-valvular atrial fibrillation is one of major causes of stroke. The goal of the study was to evaluate the use of antithrombotic medication stroke prevention and assess long-term stroke outcome. METHODS: This study involved 531 cardio embolic stroke patients of the Paul’s Stradins Clinical University Hospital, Riga, Latvia, in 2014. After discharge the patients or their relatives were interviewed by phone after 30, 90, 180, and 365 days. Standardized questions were asked about the patients’ abilities and use of prescribed secondary prevention medication. The results were compared between patient groups, assigned according to prescribed medications. RESULTS: Of all the patients included in the study, 8.9% were using oral anticoagulants before stroke onset. One year after discharge, 1.44% of patients were not using any preventive medication, 23.56% were using antiplatelet agents, 43.27% warfarin, and 31.73% target-specific oral anticoagulants . The one-year mortality rate was 40.7%. The mortality rate was significantly higher in the patient group using no secondary preventive medication or antiplatelet agents compared to the patient group that used oral anticoagulants. CONCLUSION: Cardio embolic stroke primary and secondary prevention in Latvia is lacking. The study outcomes suggest that action is needed to increase the use of oral anticoagulants in primary stroke prevention in patients with atrial fibrillation. Poor function outcomes, dementia, and patients’ incompliance limits the use of oral anticoagulants in secondary prevention.
Extended Dissipativity-Based Control for Hidden Markov Jump Singularly Perturbed Systems Subject to General Probabilities

This article deals with the extended dissipativity-based control issue for singularly perturbed systems (SPSs) with Markov jump parameters, in which the partial information issues of the Markov chain are fully considered. A comprehensive hidden Markov model (HMM) is established for the partial information issues on Markov chain, in which the transition probabilities of the hidden Markov state and the observation probabilities of the observed state are general, that is, the uncertainty and the unknown peculiarity of them may be encountered simultaneously. By using the HMM with general probabilities, a comprehensive criterion is derived to analyze the extended stochastic dissipativity of the hidden Markov jump SPSs with the different partial information issues on the Markov chain. Based on the derived criterion, an explicit expression to acquire the desired HMM-based controller is presented. An illustrative example and a vehicle active suspension system are, finally, show the validity of the established theoretical results.
PENDULAR MOTION EFFICIENCY DURING VARIOUS WALKING SPEEDS IN ELDERLY WOMEN

In the context of energetics related to a pendular model, the mechanical power (W) and •ependular motion efficiency' (PME) were determined during walking of the subjects who consist of 37 healthy elderly women (65•`85 years) and 21 young women (18•`25 years). Using a force plate, the potential and kinetic energies of the body's centre of mass were measured at various constant speeds. Walking speeds were selected and controlled by a newly devised pace-maker. PME, which is equivalent to •e% recovery' by Cavagna (1976), indicates a sort of efficiency in transforming potential energy into kinetic energy and vice versa. The external power to accelerate the body (Wext ), which is thought to be supplied by muscles, increased with walking speed, and the rate of increase in Wext tended to be greater in the elderly than in the young subjects. It was noted that the maximal PME values at the optimum speed in both age groups were comparable, but PME values in the elderly decreased more markedly than in the young subjects as walking speed deviated from the optimum. This fact suggests that an adaptability to different walking speeds reduced in the elderly population, (Jpn. J. Phys. Fitness Sports Med. 2003, 52 : 621•`630) key word : Walking, Walking speed, Aging, Efficiency
The effects of supplementing yeast fermentation products on gut permeability, hormone concentration, and growth in newborn dairy calves1

Abstract: The objectives of this study were to evaluate the effect of the use of yeast fermentation products (YFP) on growth, hormone concentration, and gut permeability in dairy calves. One hundred and twenty heifers were randomly assigned to one of three treatments: control group with no YFP supplementation (C), Saccharomyces cerevisiae fermentation products (SCFP) supplementation (1 g/head/d of SmartCare [Diamond V] in the milk and 0.7% on dry matter basis of NutriTek [Diamond V] on the starter feed), or Aspergillus oryzae fermentation extracts (AOFE) supplementation (3 g/head/d of LXtract1224 [Biozyme Inc.] in the milk). All calves received 6 L/d of pasteurized milk and had ad libitum access to water and dry feed along the study. Body weight (BW) was recorded at birth and on days 14, 30, and 45 and at weaning. Dry feed (starter) offered was measured daily and refusals twice a week to obtain starter intake (SI). Diarrhea events were recorded daily and fecal scores were classified by using a four-point scale. Blood was sampled on days 7 and 14 for plasma glucose, nonesterified fatty acids (NEFA), insulin, and IL-1β concentrations. Lactulose and D-mannitol were included in the morning feeding of day 14 and blood samples were taken an hour after feeding for assessment of intestinal permeability. On day 14, blood samples were taken for plasma glucagon-like peptide 2 (GLP-2) concentration. On day 30, fecal samples were collected for measurements of Salmonella and Escherichia coli concentration on feces. No treatment differences (P ≥ 0.13) were found for BW or SI. There was a time by treatment difference (P = 0.01) in average daily gain (ADG) on day 45 where C animals had a greater ADG when compared with SCFP and AOFE. Diarrhea incidence did not change between treatments (P = 0.97) and Salmonella and E. coli were not found in feces. There were no differences (P > 0.60) between treatments for plasma GLP-2, glucose, insulin, lactulose, nor D-mannitol concentrations. There was a time by treatment tendency (P = 0.06) for NEFA concentration which tended to be greater on day 7 for C and AOFE when compared with day 14. Plasma IL-1β concentration showed a treatment tendency which tended (P = 0.06) to be greater for SCFP when compared with C. Under the current conditions, supplementation with YFP did not improve performance parameters. Plasma GLP-2 concentration, intestinal permeability, and plasma metabolites did not differ after yeast fermentation products supplementation.
Oportunidades laborais, educacionais e homicídios no Brasil

1 INTRODUÇÃO . 7 2 A TEORIA DA ESCOLHA RACIONAL E A RELAÇÃO COM CRIMES VIOLENTOS . 10 3 MODELO ECONOMÉTRICO . 14 4 CONCLUSÕES . 30 REFERÊNCIAS . 33 APÊNDICE A . 35
Gearbox Fault Diagnosis Using a Deep Learning Model With Limited Data Sample

Massive volumes of data are needed for deep learning (DL) models to provide accurate diagnosis results. Numerous studies of fault diagnosis systems have demonstrated the effectiveness of DL models over shallow machine learning (SL) in terms of feature extraction, feature dimensional reduction and diagnosis performance. Occasionally, during data acquisition, a problem with a sensor renders some of the data potentially unsuitable for further analysis, leaving only a small data sample. To compensate for this deficiency, a DL model based on a stacked sparse autoencoder (SSAE) model is designed to deal with limited sample data. In this article, the fault diagnosis system is developed based on time-frequency image pattern recognition. Therefore, two gearbox datasets are used to evaluate the proposed diagnosis system. The results from the experiments prove that the proposed system is capable of achieving high diagnostic accuracy even with limited sample data. The proposed fault diagnosis system achieved 100% and 99% diagnosis performance on experimental gearbox and wind turbine gearbox datasets, respectively. The proposed diagnosis system increased diagnosis performance between 10% and 20% over the standard SSAE model. In addition, the proposed model achieved higher diagnosis performance compared to deep neural network and convolutional neural networks models.
Pulmonary hypertension syndrome in broiler chickens: a review

Accumulation of fluid in the abdominal cavity, cardiac anomalies, including an enlargement, soft heart as well as right ventricular hypertrophy, are collectively known as ascites syndrome of broilers. Ascites was first noticed as a problem in commercial poultry farms located at high altitude. There are four general factors in ascites fluid buildup, that is: vascular damage that allows capillaries to leak; blockage of the lymphatic system that prevents drainage; decreased plasma oncotic pressure, and increased vascular hydraulic pressure, which can be caused by several types of pathologies, including hepatic, cardiac or right atrioventricular and pulmonary hypertension. Most cases of these metabolic diseases seen in commercial poultry farm are due to pulmonary hypertension. Pulmonary hypertension originates from various causes such as: environmental causes i.e., altitude, cold stress and incubator environment; management causes i.e., feed management, the form of feed, dietary content etc.; developmental causes i.e. growth rate, oxygen requirement, organ size and capacity, hematological parameters. All these factors cause ascites syndrome by inducing hypoxia in commercial birds. Genetic selection has great potential to influence and end ascites syndrome. In the past, genetic selection tools were used for rapid growth, high meat yield and good feed conversion. However, genetic selection may have aggravated the ascites problem and now it is the best solution for eliminating this metabolic disorder. With the advent of molecular genetics research and the development of genetic markers, it is possible to determine the exact genetic basis of ascites; genetic markers may be used to eliminate ascites syndrome from modern commercial broilers.
Emerging Trends In Oral Health Sciences And Dentistry

Complete dentures are most frequently a challenge for practitioners. The complexity of this disease is often associated with general health problems, but also with the physiological ageing phenomenon, that increases the treatment difficulty. Completely edentulous patients, usually elderly, often complain about the functionality of conventional dentures, especially the mandibular ones, claiming their instability, poor retention and discomfort during wear.