Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the relationship between depressive symptoms and attainment at school

Rates of depressive symptoms and disorder increase during adolescence and these are associated with a range of negative outcomes both in adolescence and adulthood. One possible pathway to poor outcomes is via low attainment at school. However the association between depressive symptoms and attainment is poorly understood. This thesis explored this association. First, a meta-analysis was conducted on associations between depressive symptoms and subsequent attainment (chapter 2). This found small but significant associations, as well as significant heterogeneity of effect sizes between studies. Second, the temporal direction of this association was investigated using a cross-lagged design (chapter 4). This found depressive symptoms to be associated with a decline in attainment over time. Third, possible mediators of this association were investigated in a 3-stage study design (chapter 5). Low school connectedness, concentration problems, and stressful life events were found to mediate associations between depressive symptoms at baseline and low attainment at follow-up. These studies identified gender, co-occurring conduct problems, and cognitive ability as sources of heterogeneity in the association between depressive symptoms and subsequent low attainment. These sources of heterogeneity were then further investigated. First, latent profile analysis was used to investigate depressive subgroups based on co-occurring conduct problems and symptom severity. Subgroups were identified and there was some evidence of differing associations with attainment and in aetiology. Second, higher cognitive ability was found to buffer the effects of stress on depressive symptoms and disorder in girls (chapter 7) as well as the effects of stress on attainment (chapter 5). Taken together, these findings advance understanding of the association between depressive symptoms and attainment at school. They also suggest specific groups with depressive symptoms that may merit special consideration (e.g. pupils with conduct problems or low cognitive ability) and pathways of importance (e.g. school connectedness).
Fuzzy characterization of Kernel-based neural Networks

In Neural Networks models the knowledge synthesized from the training process is represented in a subsymbolic fashion (weights, kernels, combination of numerical descriptions) that makes difficult its interpretation. The interpretation of the internal representation of a successful Neural Network can be useful to understand the nature of the problem and its solution, to use the Neural "model" as a tool that gives insights about the problem solved and not just as a solving mechanism treated as a black box. The internal representation used by the family of kernel-based Neural Networks (including Radial Basis Functions, Support Vector machines, Coulomb potential methods, and some probabilistic Neural Networks) can be seen as a set of positive instances of classification and, thereafter, used to derive fuzzy rules suitable for explanation or inference processes. The probabilistic nature of the kernel-based Neural Networks is captured by the membership functions associated to the components of the rules extracted. In this work we propose a method to extract fuzzy rules from trained Neural Networks of the family mentioned; comparing the quality of the knowledge extracted by different methods using known machine learning benchmarks.
Best Effort SRLG Failure Protection for Optical WDM Networks

With the increase in the size and number of shared risk link groups (SRLGs) in optical wavelength-division multiplexing (WDM) networks, the capacity efficiency of shared-path protection becomes much poorer due to the SRLG-disjoint constraint, and thus the blocking probability becomes much higher. Furthermore, due to severe traps caused by SRLGs, it becomes more difficult to find an SRLG-disjoint backup path with trap avoidance within reasonable computational complexity. As a result, in a mesh WDM network with a large number of SRLGs or a large SRLG size, 100% SRLG failure protection is no longer a practical protection scheme. To solve this problem, we present a new protection scheme called best effort SRLG failure protection, in which we try to provide an SRLG-disjoint backup path by choosing the backup path sharing the least number of SRLGs with the working path; this is to make the impact of SRLG failures as low as possible and accept as many as possible connection requests. As a result, the proposed best effort SRLG failure protection scheme manages to make a trade-off between blocking probability and survivability. 100% SRLG failure protection becomes a special case of best effort SRLG failure protection when the working path and backup path share zero SRLG. Due to the NP-completeness of this problem, we propose a heuristic to find the optimal result of the best effort SRLG-disjoint backup path under dynamic traffic. We formulate the connection survivability against SRLG failures and analyze the possibility of backup sharing under best effort SRLG failure protection. Analytical and extensive simulation results with various network topology and SRLG parameters demonstrate that, compared with 100% SRLG failure protection, the proposed best effort SRLG failure protection scheme offers much better capacity efficiency and much lower blocking probability while keeping survivability as high as possible. This can be explained by the fact that by slightly loosing the SRLG-disjoint constraint, shared-path protection will become more capacity efficient and more efficient in overcoming traps.
Predictive gaze stabilization during periodic locomotion based on Adaptive Frequency Oscillators

In this paper we present an approach to the problem of stabilizating the gaze of legged robots using Adaptive Frequency Oscillators to learn the frequency, phase and amplitude of the optical flow and generate compensatory commands during robot locomotion. Assuming periodic and nearly sine shaped motion of the head of the robot, the system successfully stabilizes the gaze of the robot, whether the robot itself is moving, or an external object is moving relative to the robot. We present experiments in simulation and, for object tracking, with a real robotics setup, the Hoap 3, showing that the system can be successfully applied to gaze stabilization during locomotion, even when the feedback loop is very slow and noisy.
Psychosocial and Economic Status of the Parents with Children with and without Tooth Trauma.

BACKGROUND The main goal of this research is to try and understand influence of psychological and social factors in children with tendencies to repeat tooth trauma. SUBJECTS AND METHODS Research included 147 patients, children of preschool and school age (88 boys and 59 girls). In the research patients were divided in two age groups: 5-8 and 9-12 years. In both groups there were 49 patients with no experience of dental trauma and 69 patients with experience of one dental trauma and 29 patients with repeated dental trauma. All patients that were involved in the study had previous experience with dental and medical treatment. Study included evaluation of dental anxiety and also factors that caused dental phobia previous their visit to the office in the children with no dental trauma compared to repeat dental trauma patients. On the whole study group differences considering sex, age and psychosocial status in the level of dental anxiety and dental fear were also measured. RESULTS Categories of children without trauma and with one or multiple trauma showed that it is a similar sex division in the categories. In the no trauma group participation of the boys is lower (46.9%) while in the group with repeated trauma their participation is significantly higher (79.3%). Based on that the risk of repeated dental trauma is characteristic of boys. CONCLUSIONS Results of this study show that tested psychosocial variables do not differentiate participants according to the tested groups or in other words there is no difference between tested groups in their psychosocial standing.
Design and Analysis of User Identification for Graphical Password

Authentication is necessary in multi-user systems. User name and password are used to authenticate a user. Textual passwords are the most common method used for authentication. But textual passwords are vulnerable to eves dropping, dictionary attacks, social engineering and shoulder surfing. Graphical passwords are introduced as alternative techniques to textual passwords. Most of the graphical schemes are vulnerable to shoulder surfing. To address this problem, text can be combined with images or colors to generate session passwords for authentication. Session passwords can be used only once and every time a new password is generated. This project proposes two techniques to generate session passwords using text and colors which are resistant to shoulder surfing. These methods are suitable for Personal Digital Assistants. Keywords— Authentication, session passwords, shoulder surfing.
Pericentric heterochromatin reprogramming by new histone variants during mouse spermiogenesis

During male germ cell postmeiotic maturation, dramatic chromatin reorganization occurs, which is driven by completely unknown mechanisms. For the first time, we describe a specific reprogramming of mouse pericentric heterochromatin. Initiated when histones undergo global acetylation in early elongating spermatids, this process leads to the establishment of new DNA packaging structures organizing the pericentric regions in condensing spermatids. Five new histone variants were discovered, which are expressed in late spermiogenic cells. Two of them, which we named H2AL1 and H2AL2, specifically mark the pericentric regions in condensing spermatids and participate in the formation of new nucleoprotein structures. Moreover, our investigations also suggest that TH2B, an already identified testis-specific H2B variant of unknown function, could provide a platform for the structural transitions accompanying the incorporation of these new histone variants.
Joint detection and estimation fusion in distributed multiple sensor systems

In this paper, we address the problem of the joint detection and estimation fusion in distributed multiple sensor systems. The objective is to decide between two hypotheses and make the corresponding estimates if the decided hypothesis has unknown parameters at the same time. The fusion system comprises N independent sensors, and each one sends a binary decision to the fusion center for integration. The traditional approaches treat the detection and estimation separately, and tend to place the primary emphasis on the detection part through maximizing detection probability and then treat the estimation part as suboptimal. The proposed approach treats these two parts simultaneously in a jointly optimal manner. The average estimated cost concerning about the random decision rule is minimized subject to the corresponding constraints with respect to the false alarm probability and the probability of missed detection. The resulting scheme shows that a trade-off between detection and estimation performance can be achieved. A hypothesis test example with unknown parameters based on multi-sensor quantized measurements is given, which demonstrates the flexibility and the superiority of the proposed approach compared with the classical Neyman-Pearson and the GLRT.
Quantity and quality of motivational regulation among university students

Abstract Effective regulation of motivation can be theoretically explained by both the extent of motivational regulation strategies used (quantity) and their optimal implementation (quality). Researchers have not yet analysed the significance of both aspects for learning success simultaneously. In the present study, 188 students were presented with different descriptions of prototypical learning situations paired with specific causes for poor motivation and were asked to report both the quantity and key aspects of the quality of motivational regulation strategies they would implement. Regression analyses revealed that the quantity of strategy use was a moderate positive predictor of both self-reported regulatory effectiveness and self-reported effort while studying. These two dependent variables were significantly better predicted by including the quality of strategy use. Moreover, only the quality of strategy use correlated with academic achievement. Structural equation modelling indicated that the effect of strategy quality on academic performance was mediated by regulatory effectiveness and effort.
Symposium "recovery from Brain Damage: Behavioral and Neurochemical Approaches" Prostacyclin Reduces Early Ischemic Changes in Central Nervous System

The authors made a study of the effect of prostacyclin (PG12) on ischemic morphological changes in the brain, extracellular calcium concentration (Ca2+e) and the blood-brain barrier (BBB) per-meability. This was combined with physiological and neurophysiological measurements. Complete cerebral ischemia (CCI) lasting 15 or 20 min wag produced by the ligation of the brachiocephalic trunk, the left sub-clavian and both internal thoracic arteries. The experiments with PGI, were carried out in two groups. In group I, the rabbits received PGIz 3 min before CCI, during it and for 15 min after it. In group I1 PGIz was infused in the last 3 min of CCI and for 40 min after it. Control animals with CCI of the same duration were not given PGI, medication. The rabbits treated with PGI, were found to have recovery of the bioelec-tric activity of the brain in half the t i n ~ e that its return took in the untreated cases. PGI, was noted to have a positive effect on some parameters of the peripheral blood system after CCI. Application of PGI, reduced the depth of ischemia-evoked drop of Ca2 ' e by 50°/a without accelerating recovery d ~ ~ r i n g recirculation; the post-ischemic increase of BBB permeability to iluorescein was also diminished. PGI, reduced edema and the spectrum of neuronal changes and decreased the number of pathologically changed neurons in the brain. In the group that received PGIa ischemic ultrastructural changes in the cytoplasm of neurons were abolished, but PGIz did not prevent pathological changes in the neuronal nuclei after CCI. Those changes were manifested in numerous vesicular structures and nuclear inclusions. Hence, the described data indicate that the beneficial action of PGIz is directed only to early changes in the neuronal cytoplasm and reflects a transient facilitation of functional recovery rather than permanent brain protection after complete cerebral ischemia.
Background Information on our Neural Network – Based System of Leading Indicators

Neurons are arranged in several layers called input, hidden, and output layers (Chart 2). Simply put, the input layer is similar to a matrix of independent variables in a regression while the output layer is the dependent variable. The hidden layer is the series of relationships calculated in the network’s training process. There is no theoretical limit on the number of hidden layers in a given network. Typically there will be one or two. CIBCWM leading indicators of economic activity and inflation are designed to signal any notable change in trends in overall GDP growth and inflation. The indicators are based on Artificial Intelligence -Neural Network technology. Neural networks have been used in various fields such as medicine and robotics for several years, but only recently have they made an impact as a serious business tool. In the financial sector, neural networks are mainly used for stock selection, stock ranking, credit analysis, risk assessment and asset allocation. Neural networks can be also utilized in both macroand microeconomic analysis, with clear potential to improve the timeliness and quality of economic forecasting. This is especially true in cases where there is a significant non-linear relationship between the dependent and independent variables
People living with HIV travel farther to access healthcare: a population-based geographic analysis from rural Uganda

The availability of specialized HIV services is limited in rural areas of sub‐Saharan Africa where the need is the greatest. Where HIV services are available, people living with HIV (PLHIV) must overcome large geographic, economic and social barriers to access healthcare. The objective of this study was to understand the unique barriers PLHIV face when accessing healthcare compared with those not living with HIV in a rural area of sub‐Saharan Africa with limited availability of healthcare infrastructure.
Inoculation of Goats, Sheep, and Horses with MERS-CoV Does Not Result in Productive Viral Shedding

The Middle East respiratory syndrome coronavirus (MERS-CoV) was first recognized in 2012 and can cause severe disease in infected humans. Dromedary camels are the reservoir for the virus, although, other than nasal discharge, these animals do not display any overt clinical disease. Data from in vitro experiments suggest that other livestock such as sheep, goats, and horses might also contribute to viral transmission, although field data has not identified any seropositive animals. In order to understand if these animals could be infected, we challenged young goats and horses and adult sheep with MERS-CoV by intranasal inoculation. Minimal or no virus shedding was detected in all of the animals. During the four weeks following inoculation, neutralizing antibodies were detected in the young goats, but not in sheep or horses.
A Gate-Width Scalable Method of Parasitic Parameter Determination for Distributed HEMT Small-Signal Equivalent Circuit

We propose a gate-width scalable method for extracting the reliable parasitic elements of the 0.1- μm GaAs metamorphic high electron-mobility transistors. This method utilizes the de-embedding scheme for coplanar waveguide (CPW) feeding structure by considering the distributed extrinsic parasitic elements in our small-signal model. The parasitic capacitances are determined based on estimation of the sub-model (the model after de-embedding the contribution of the CPW feeding structure). We perform the parameter extraction at four different gate widths of the devices to examine the scaling effect. The model shows the best S-parameter effective fitting error of 9.85% among four different extraction methods evaluated in this study over the entire gate-width variation and in a frequency range of 0.5-110 GHz.
Léčba pokročilého stadia Parkinsonovy nemoci intraduodenálními infuzemi levodopy

L-DOPA je stale považovana za nejucinnějsi lek v terapii Parkinsonovy nemoci. Jeji dlouhodobe podavani je vsak spojeno s rozvojem pozdnich hybných komplikaci, za jejichž přicinu se považuje nefyziologicke intermitentni podavani L-DOPA. Eliminace pulzatilni stimulace dopaminových receptorů nastavenim stabilnějsi hladiny koncentrace dopaminergnich preparatů v plazmě a v oblasti striata tak může vest k výrazne redukci těchto motorických komplikaci. Předkladame kazuistiku pacienta v pokrocile fazi Parkinsonovy nemoci, u ktereho vedlo zavedeni kontinualnich intestinalnich infuzi L-DOPY ke zmirněni přiznaků onemocněni a významně tak zlepsilo kvalitu života pacienta.
CUIDADOR DE CRIANÇA COM CÂNCER: RELIGIOSIDADE E ESPIRITUALIDADE COMO MECANISMOS DE ENFRENTAMENTO CUIDADOR DEL NIÑO CON CÁNCER: RELIGIOSIDAD Y ESPIRITUALIDAD COMO MECANISMOS DE AFRONTAMIENTO CHILDREN CAREGIVER WITH CANCER: RELIGIOSITY AND SPIRITUALITY AS COPING MECHANISMS

Introduction: Although there have been great advances in oncologic therapy, cancer still presents itself as a diagnostic disease related to the fear of death, which causes pain in the affected child and her family. In any case, caregivers experience drastic changes in their routines and suffer during the treatment of children with cancer, so seek support strategies that helps them to confront this adverse situation. Objective: To investigate the role of religion and spirituality as a coping mechanism used by family caregivers front of childhood cancer. Materials and Methods: The place where the research was conducted was the Institute for the Support of Children with Cancer in the municipality of Barbalha (CE). The subjects were family caregivers and the instrument for data collection was one semi-structured interview. Data were analyzed by a Thematic Analysis. Results: Data were crowded into two themes: faith as a source of support in delicate moments of treatment and expectations for the end of treatment. Discussion: Reports showed the use of religion and spirituality as components inherent in coping with childhood cancer by family caregivers. Conclusions: The search for the religion and the use of spirituality by caregivers is very present during the confrontation of childhood cancer. Thus, health professionals should be a source of respect and support the beliefs, religion and values of family caregivers. Keywords:�Neoplasms, Child, Caregivers, Religion, Spirituality. (Source: DeCS BIREME).
Face recognition and computer graphics for modelling expressive faces in 3D

This thesis addresses the problem of the lack of verisimilitude in animation. Since computer vision has been aimed at creating photo-realistic representations of environments and face recognition creates replicas of faces for recognition purposes, we research face recognition techniques to produce photo-realistic models of expressive faces that could be further developed and applied in animation. We use two methods that are commonly used in face recognition to gather information about the subject: 3D scanners and multiple 2D images. For the latter method, Maya is used for modeling. Both methods produced accurate 3D models for a neutral face, but Maya allowed us to manually build 3D models and was therefore more successful in creating exaggerated facial expressions.
Crystal structure of the flavoenzyme PA4991 from Pseudomonas aeruginosa

PA4991 is a FAD-dependent oxidoreductase from the pathogen P. aeruginosa that is essential for virulence and survival in the infected host. The structure of this enzyme, determined to 2.4 Å resolution, reveals that PA4991 belongs to the GR2 family of flavoenzymes.
Impact of channel models on simulation of large scale wireless networks

Accurate simulation of wireless networks requires realistic models of the channel propagation medium. The commonly used free space model is computationally efficient but ignores many losses that are common in wireless signal propagation. This paper describes the impact of the wireless channel models on the accuracy and execution time of large-scale simulation models. The paper also demonstrates the impact of using parallel execution in reducing the execution time of the model sufficiently such that a model with 10,000 wireless nodes can be simulated with 6 processors in less time than a network with half as many nodes using sequential execution.