Miracle-dz/UniFAR-FTUs huggingface dataset:
Socio-cultural Factors and Practices Affecting the Girl Child among the Annang People of Akwa Ibom State

Household discriminatory practices on the girl-child have drawn attention worldwide due to deep-rooted socio-cultural beliefs, values and practices. Despite extensive empirical evidence in literature there is a dearth of studies in Nigeria in particular. This study examined the socio-cultural factors and practices affecting the girl-child among the Annang, an ethnic group in Akwa-Ibom State-Nigeria. The study adopted the Weber’s social action theory as theoretical framework to provide theoretical orientation to the issue investigated. A multi-methodological approach was adopted in generating data. A household survey was conducted among 100 respondents which comprised of pairs of fathers/male-children and mothers/female-children. A four-staged sampling technique was used to purposively select 3 Enumeration Areas (EAs). Structured questionnaires elicited information on cultural construction of girlhood, familial roles and household practices from both adults and boy and girl-children. Four Focus Group Discussions (FGDs) and IDIs which centred on gender socialization, gender relations, household practices, and socio-cultural factors were conducted among adults males and females as well as male and female-children. Indepth interviews were also conducted with religious leaders, traditional rulers, as well as male and female community leaders. Quantitative data were analyzed using descriptive statistics. The qualitative data employed content analysis as well as thematic narratives of participants and key informants views and responses. Adult respondents’ mean age was 40.3±10.0 years, 98.1% were married, and 81.7% were farmers. The mean age for boys and girl-children was 13.5±3.2 years. Majority of the respondents were rural dwellers (82.0%). Majority of respondents (97.1%) opined that the status of the girl-child was very low relative to the boy-child. About 99% affirmed that girl-children were disadvantaged with regard to opportunities and privileges. The girl-child faced household discriminatory practices in domestic work assignment (79.0%), education (78.4%) and restrictive food taboos (32.2%). Significant others approved such practices. About 67% of girl-children perceived the practices as acceptable to the Annang people. The qualitative data identified socio-cultural factors such as conception of gender roles, gender socialization, son preference, cultural construction of girlhood, and valuation of the girl-child, decision-making, gender stereotyping among others engendered these practices. Cultural construction of girlhood was largely defined by the respondents’ societal notions on femininity. Household discriminatory practices among the Annang people, was largely due to socio-cultural factors and practices. Therefore, serious attention should be given to community mobilization and sensitization to address the socio-cultural factors and harmful practices which limit the empowerment of the girl-child.
Approximate Value Iteration Based on Numerical Quadrature

Learning control policies has become an appealing alternative to the derivation of control laws based on classic control theory. Value iteration approaches have proven an outstanding flexibility, while maintaining high data efficiency when combined with probabilistic models to eliminate model bias. However, a major difficulty for these methods is that the state and action spaces must typically be discretized and often the value function update is analytically intractable. In this letter, we propose a projection based approximate value iteration approach, that employs numerical quadrature for the value function update step. It can handle continuous state and action spaces and noisy measurements of the system dynamics while learning globally optimal control from scratch. In addition, the proposed approximation technique allows for upper bounds on the approximation error, which can be used to guarantee convergence of the proposed approach to an optimal policy under some assumptions. Empirical evaluations on the mountain benchmark problem show the efficiency of the proposed approach and support our theoretical results.
Latency aware mobile task assignment and load balancing for edge cloudlets

With the various technological advances, mobile devices are not just being used as a means to make voice calls; but are being used to accomplish a variety of tasks. Mobile devices are being envisioned to practically accomplish any task which could be done on a computer. This is hurdled by the limited computational resources available with the mobile devices due to their portable size. With the mobile devices being connected to the Internet, leveraging cloud services is being seen as a promising solution to overcome this hurdle. Computationally intensive tasks can be offloaded to the Cloud servers. However, owing to the latency and cost associated with using cloud services, edge devices (termed cloudlets) stationed near the mobile devices are being seen as a prospective alternative to replace/assist the Cloud services. The mobile devices have an easier access to the cloudlets being situated in their vicinity and can offload their task requests to them to be served at a lower cost. This paper considers a network of such connected cloudlets which provide service to the mobile devices in a given area. We address the issue of task assignment in such a scenario (i.e. which cloudlet serves which mobile device) aimed towards improving the quality of service experienced by the mobile devices in terms of minimizing the latency. Through numerical simulations we demonstrate the performance gains of the proposed task assignment scheme showing lower latency as compared to the traditional scheme for task assignment.
Impact of intramammary tilmicosin infusion as a dry cow therapy

Three hundred subclinically infected quarters of 259 Holstein cows infected with gram-positive bacteria were selected via quota sampling based on the California Mastitis Test (CMT) result and were divided randomly and equally into treatment and test groups. Quarters of test group (n = 150 in 128 cows) were treated with an intramammary infusion of tilmicosin, and quarters of the control group (n = 150 in 131 cows) were treated with cloxacillin as a traditional intramammary infusion of dry cow (DC) ointment. Cows with more than one infected quarter were randomly assigned to the same group, and adjacent quarters were treated the same. The milk samples of all quarters were obtained, and bacterial cultures and somatic cell count (SCC) were tested before dry cow therapy (DCT) (50 ± 15 days before parturition), and finally on day 2 of the next lactation. Results have shown that total bacteriological cure rates on day 2 of the next lactation were 45% and 78%, (p = .01), new infection rates were 43.3% and 56.6%, and SCC was (6.732 × 105 ± 3.124 × 105 ) and (5.025 × 105 ± 2.935 × 105 ), (p > .05) in test and control groups, respectively. Tilmicosin had less effect on reducing IMI due to Corynebacterium bovis, and had no effect on Streptococcus agalactiae, but had a potent effect against Staphylococcus aureus. It was concluded that tilmicosin alone should not be infused as an alternative to conventional dry cow therapy. However, it had a significant effect against S. aureus, and the potential of tilmicosin to treat S. aureus IMI should be confirmed in further studies.
Evaluating the role of the Hippo pathway in the onset and disease progression of the SOD1 mouse model of Amyotrophic Lateral Sclerosis

The Hippo pathway is a cell signaling pathway involved in organ size regulation and tumorigenesis in mammals. This pathway regulates the activity of Yes-associated protein (YAP), a transcriptional coactivator which binds to the transcription factor TEAD to promote expression of genes controlling growth and proliferation of tissues, as well as inhibition of apoptosis. The Hippo pathway has recently been implicated as a pathogenic mechanism in neurodegenerative disorders. Specifically, mammalian sterile 20 (Ste20)like kinase 1 (MST1), a protein kinase in the Hippo pathway, has been found to promote neuronal death under conditions of oxidative stress. Moreover, homozygous deletion of MST1 in a mouse model of Amyotrophic Lateral Sclerosis (ALS) significantly delayed onset of neurodegenerative symptoms. We examined the expression levels of key Hippo pathway components in cortex, lumbar spinal cord, and gastrocnemius muscle samples of male and female G39A SOD1 mice using western blots. Our results revealed a significant increase in phosphorylated MST1 (pMST1) in lumbar spinal cord of presymptomatic transgenic animals, and found this increase to be sex and gene copy number dependent. These results suggest that the Hippo pathway is dysregulated in the SOD1 mouse model and that MST1 may play a critical role in pathogenesis and disease progression in ALS.
The Psychosocial Health of Shan Children in Northwest Thailand

We administered the Strengths and Difficulties Questionnaire (SDQ) to 51 Shan refugee children from Burma who are living in northern Thailand, and collected life histories from 11 of their families. Of the sample, 63% of the children were stateless, and none were Thai citizens. About 30% of the children had normal peer relationship subscores—a number well below Thai norms after correcting for multiple comparisons (p < .001). However, thier overall functioning was not different from the Thai population as a whole.
Survey of a Rule Based Expert System for Gas Price Forecasting

The difficulty in gas price forecasting has attracted much attention of academic researchers and business practitioners. Various methods have been tried to solve the problem of forecasting gas prices however, all of the existing models of prediction cannot meet practical needs. In this paper, a novel hybrid intelligent framework is developed by applying a systematic integration of GMDH neural networks with GA and Rule-based Exert System (RES) employs for gas price forecasting. In this paper we use a new method for extract the rules. Our research reveals that during the recent financial crisis period by employing hybrid intelligent framework for gas price forecasting, we obtain better forecasting results compared to the GMDH neural networks and results will be so better when we employ hybrid intelligent system with GARCH (1, 1) for gas price volatility forecasting.
Training a Log-Linear Parser with Loss Functions via Softmax-Margin

Log-linear parsing models are often trained by optimizing likelihood, but we would prefer to optimise for a task-specific metric like F-measure. Softmax-margin is a convex objective for such models that minimises a bound on expected risk for a given loss function, but its naive application requires the loss to decompose over the predicted structure, which is not true of F-measure. We use softmax-margin to optimise a log-linear CCG parser for a variety of loss functions, and demonstrate a novel dynamic programming algorithm that enables us to use it with F-measure, leading to substantial gains in accuracy on CCG-Bank. When we embed our loss-trained parser into a larger model that includes supertagging features incorporated via belief propagation, we obtain further improvements and achieve a labelled/unlabelled dependency F-measure of 89.3%/94.0% on gold part-of-speech tags, and 87.2%/92.8% on automatic part-of-speech tags, the best reported results for this task.
Surface light field from video acquired in uncontrolled settings

This paper presents an algorithm for the estimation of the Surface Light Field using video sequences acquired moving the camera around the object. Unlike other state of the art methods, it does not require a uniform sampling density of the view directions, but it is able to build an approximation of the Surface Light Field starting from a biased video acquisition: dense along the camera path and completely missing in the other directions. The main idea is to separate the estimation of two components: the diffuse color, computed using statistical operations that allow the estimation of a rough approximation of the direction of the main light sources in the acquisition environment; the other residual Surface Light Field effects, modeled as linear combination of spherical functions. From qualitative and numerical evaluations, the final rendering results show a high fidelity and similarity with the input video frames, without ringing and banding effects.
Motor coordination and emotional–behavioral problems in children

Purpose of review To summarize recent research on developmental coordination disorder (DCD), with particular attention to comorbidity and related questions of etiology. Recent findings Although a general consensus on the disorder definition exists, case identification in research studies remains problematic. Despite this, recent research has reported high levels of attention deficit/hyperactivity disorder and internalizing disorders among children with poor motor coordination. These findings offer some support for the longstanding view that DCD may be one facet of a broader syndrome that includes learning difficulties and deficits in attention. ‘Pure’ cases are common, however, and other work suggests that DCD and attention deficit/hyperactivity disorder have distinct causes. There is also some evidence that internalizing disorder may be a consequence of DCD. Summary Measurement issues in DCD persist, whereas findings on comorbidity have both illuminated the nature of the disorder and heightened debate on its usefulness as a distinct diagnostic entity.
A Detailed Protocol to Enable Safe-Handling, Preemptive Detection, and Systematic Surveillance of Rat-Vectored Pathogens in the Urban Environment

We detail a five-stage protocol to address physical barriers and experimental limitations that have hindered routine pathogen monitoring of wild rats in urban settings. New York City potentially harbors from 2 to 32 million rats among its 8-million people. However, at a time, when people are most vulnerable to disease from over-crowdedness brought on by increased urbanization of society, the difficulty of studying wild rats has led to a paucity of ecological and epidemiological research. Challenges of safely handling animals and the difficulties of identifying individual animals and the emergence of their respective pathogen loads (timing of infection) have impeded progress. We previously reported a method using radio frequency identification paired with load cell and camera traps to enable the identification of individual animals and subsequent monitoring of the animals’ weights (an indicator of health). However, efficient pathogen surveillance requires repeated captures of the same individual in order to isolate and document the emergence of new pathogens, or variations in pathogen load, over time. Most of these barriers are now addressed in our protocol, which is aided by the use of a mobile, outdoor laboratory, followed by incorporation of pheromone-based lures to attract individuals back to active sensors, within a camera trap. This approach allows for the assessment of individual animal health, behaviors under camera, and changing pathogen loads and weights in most urban environments (e.g., financial district, docks, sewers, and residential). Five phases are described and presented: (1) site selection and urban trapping, (2) anesthetization, (3) serological and ectoparasite collection, (4) microchip implantation, and (5) retrapping and luring animals back to active remote sensors. In order to fulfill the unmet call for preemptive pathogen surveillance, public health officials and researchers may wish to adapt, or modify, similar protocols to ensure early detection and monitoring of rat-borne zoonoses, before they become problematic.
Perturbative corrections for approximate inference in Gaussian latent variable models

Expectation Propagation (EP) provides a framework for approximate inference. When the model under consideration is over a latent Gaussian field, with the approximation being Gaussian, we show how these approximations can systematically be corrected. A perturbative expansion is made of the exact but intractable correction, and can be applied to the model's partition function and other moments of interest. The correction is expressed over the higher-order cumulants which are neglected by EP's local matching of moments. Through the expansion, we see that EP is correct to first order. By considering higher orders, corrections of increasing polynomial complexity can be applied to the approximation. The second order provides a correction in quadratic time, which we apply to an array of Gaussian process and Ising models. The corrections generalize to arbitrarily complex approximating families, which we illustrate on tree-structured Ising model approximations. Furthermore, they provide a polynomial-time assessment of the approximation error. We also provide both theoretical and practical insights on the exactness of the EP solution.
PRÁCTICAS DEL ANÁLISIS FACTORIAL EXPLORATORIO (AFE) EN LA INVESTIGACIÓN SOBRE CONDUCTA DEL CONSUMIDOR Y MARKETING

El Analisis Factorial Exploratorio (AFE) es una de las tecnicas estadisticas mas utilizadas en la investigacion social. El principal objetivo de este trabajo es describir las practicas mas utilizadas por los investigadores en el area de la conducta del consumidor y el marketing. Mediante una metodologia de revision documental se analizan las practicas de AFE en cinco revistas espanolas dedicadas a dicha tematica (2000-2010). Se analizan las elecciones de los investigadores relacionadas con el modelo factorial, el criterio de retencion, la rotacion, la interpretacion de los factores y otras cuestiones relevantes para el analisis factorial. Los resultados sugieren que los investigadores ejecutan los analisis utilizando metodos cuestionables. Se presentan sugerencias para mejorar el uso del analisis factorial y el informe de resultados y se proporciona un protocolo (Protocolo de Analisis Factorial Exploratorio, PAFE) para ayudar a editores, revisores y autores a mejorar sus informes de analisis factorial exploratorio.
Hepatitis C Viremia Patterns in Incident Hepatitis C Infection and One Year Later in 150 Prospectively Tested Persons Who Inject Drugs

Objectives To assess HCV viremia levels just before, during and one year after anti-HCV seroconversion in people who inject drugs (PWID). Methods PWID enrolling into a needle exchange program in Malmö, Sweden, 1997–2005 constituted the source population. Sera were obtained at enrolment and at approximately 3–4 monthly intervals afterwards, and were initially tested for anti-HIV, HBsAg/anti-HBc and anti-HCV and thereafter for markers previously negative. Seroconversion to anti-HCV had occurred during the study period in 186 out of 332 seronegative subjects. In these anti-HCV seroconverters, quantitative HCV RNA PCR was retrospectively performed on frozen sera to determine viremia levels in the last anti-HCV negative, the first anti-HCV positive and in one year follow-up samples. Results Among 150 subjects seroconverting to anti-HCV with samples available from all three defined time-points, eight different patterns of viremia were observed. Spontaneous clearance at one year was noted in 48 cases (32%) and was associated with female gender (p = 0.03, CI 0.17–1.00). In 13 cases HCV-RNA was not detected in any study sample. Among 61 subjects with pre-seroconversion viremia, viral load was significantly higher in the pre-seroconversion samples compared to subsequent samples. For the whole group, viral load declined to undetectable levels at seroconversion in 28% of cases (but with recurrent viremia in 15%). Conclusions Different patterns of HCV RNA kinetics were observed among PWID with documented seroconversion to anti-HCV. The frequently observed absence of detectable HCV RNA in the first anti-HCV positive sample (irrespective of subsequent viremia) demonstrates the importance of repeated sampling and RNA testing for determination of the outcome of acute infection.
A two-step approach for event factuality identification

This paper focuses on identifying event factuality. Different from pervious rule-based method, this paper proposes a novel two-step approach of combining machine learning and rule-based approach. Firstly, a maximum entropy model is constructed to determine whether the informant's degree of certainty of events is expressed. Then, a set of rules containing cue and scope detection is introduced to further identify various event factuality values. Experimental results manifest that our two-step approach achieves a higher performance than that of the state-of-the-art rule-based system.
Individual differences in white matter integrity: Linking brain structure to cognition in children and adults

For disparate brain regions to communicate efficiently action potentials must be transmitted relatively long distances along myelinated axons, which make up the brain's white matter . These connections are fundamental for the generation of complex cognition. A single cortical region is not sufficient--the human brain must work as a network, with the billions of neurons interacting together to perform the necessary computations. In my graduate work, presented in this dissertation, I sought to explain the variability in cognitive behavior with individual differences in white matter microstructure. The overarching goal was to further our understanding of the mechanisms through which structural connections in the brain underlie complex cognition in children and adults.I used diffusion tensor imaging, a type of magnetic resonance imaging that is sensitive to white matter microstructure, to quantify in vivo the maturation of white matter in children and adults. I first motivate the need to study the individual differences in white matter integrity and their predictive value on cognitive behavior in chapter one. I then describe four experiments that investigate various aspects of this connection. In chapter two, I first describe the age related changes in brain and behavior through childhood and adolescence, and then use longitudinal data to highlight the additional explanatory power of how within-person measures of change (in brain and cognitive ability) over time are linked. In chapter three, I demonstrate the mediation of the relationship between white matter integrity (WMI) and reasoning ability by cognitive processing speed in typically developing children. In chapter four, I show the WMI differences between two groups of adults who have experienced different perceptual environments through development (synesthetes and non-synesthetes) and demonstrate a correlation between vividness of visual imagery and the WMI of the synesthetic brain. Finally, in chapter five, I explain the effects of short term cognitive training on WMI . After only three months of undergoing an intensive reasoning training program we saw evidence of cellular reorganization in the white matter of healthy young adults. I conclude by summarizing the major contributions of the work in this dissertation and discuss possible future directions based on the results of my graduate research.
Quantification of teaching behavior in physical education : a methodological study

Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva. nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible.