Miracle-dz/UniFAR-FTUs huggingface dataset:
The role of education and income as protective factors against intimate partner violence and HIV exposure among Kenyan women

Abstract Introduction Intimate partner violence (IPV) is a public health problem that impacts approximately one in three women worldwide in their lifetime. The purpose of the study was to explore the lived experiences of women teachers and violence in Kenya. It also explores the intersection between intimate partner violence, HIV risk, and gender inequality. Method Data were collected through two focus groups of a total of 15 women teachers. We recruited women ages 21–44 from two geographically diverse urban and rural schools. The data were analyzed using a thematic analysis method to identify text themes and meaning patterns. Results Three contextual experiences emerged: socio-cultural influences of gender norms, masculinity and patriarchy; uneven power dynamics; and institutionalized gender inequality. Discussion Findings suggest that education alone is not sufficient to end GBV. Comprehensive and gender transformative governmental policy approaches are needed to mitigate GBV in Kenya.
Calibrating Manure Spreaders

Department of Crop and Soil Sciences 1 College of Agriculture and Life Sciences Manure spreader calibration is an important step in nutrient management planning. With proper calibration, a producer can eliminate application rate guesswork, allowing for better use of manure nutrients and hence reduction in the risk of environmental pollution. There are three basic methods of calibrating manure spreaders: (1) using truck scales to weigh loads; (2) using plastic sheets in the field, and (3) counting loads of known volume or weight. In this fact sheet the three methods will be described.
Guidelines' Parametrization to Assess AAL Ecosystems' Usability

: With the aging of the population, healthcare services worldwide are faced with new economic, technical, and demographic challenges. Indeed, an effort has been made to develop viable alternatives capable of mitigating current services’ bottlenecks and of assisting/improving end-user’s life quality. Through a combination of information and communication technologies, specialized ecosystems have been developed; however, multiple challenges (ecosystems autonomy, robustness, security, integration, human-computer interactions and usability) have arisen, compromising their adoption and acceptance among the main stakeholders. Dealing with the technical related flaws has led to a shift in the focus of the development process from the end-user towards the ecosystem’s technological impairments. Although many issues, namely usability, have been reported, solutions are still lacking. This article proposes a set of metrics based on the parametrization of literature guidelines, with the aim of providing a consistent and accurate way of using the heuristic methodology not only to evaluate the ecosystem’s usability compliance level, but also to create the building blocks required to include automation mechanisms.
New Insights on the Radiative Impacts of Ozone‐Depleting Substances

The global warming potential of Ozone‐depleting substances (ODS) has long been known to be thousands of times larger than the one of CO2, but their climate impacts as greenhouse gases, i.e. unmediated ozone depletion, has received relatively little attention. Focusing on the period 1955–2005, we here present results from offline radiative forcing (RF) calculations from a global chemistry climate model. Using realistic distributions of ODS and consistent stratospheric ozone, we show that ODS dominate the adjusted stratospheric warming of the lower stratosphere, where CO2 has little radiative impact. We also show that the global mean RF of stratospheric ozone only cancels a fraction of the RF of ODS, leaving an important ODS contribution to anthropogenic forcing. Finally we show that the RF of ODS opposes Arctic amplification, its equator‐to‐pole gradient being larger than the one of CO2.
Návrh řízení problem managementu podle metodiky ITIL ve vybrané organizaci

ITIL představuje v soucasne době silně rozsiřenou metodiku pro řizeni ICT služeb v korporatnim prostředi. Cela metodika obsahuje 26 procesů v celkem 5 knihach popisujici životni cyklus ICT služby. Jednim z procesů je take problem management zařazený do knihy Service operation. Tato diplomova prace si klade za cil navrhnout komplexni model řizeni problem managementu ve spolecnosti Vodafone Czech Republic a.s. V uvodu teto prace je definovan kontext ICT služeb v podnikovem prostředi. Dale jsou uvedeny zakladni informace, ktere poskytuje samotna metodika. Nicmeně je zřejme, že tyto informace jsou nedostacujici pro realne využiti v podnikovem prostředi. Prolnutim znalosti ziskaných z metodiky se znalostmi ostatnich ICT podnikových služeb a podnikoveho prostředi doslo k vytvořeni samotneho modelu. Pote byla kratce představena vybrana spolecnost a definovany klicove aspekty řizeni ICT služeb. Byla take identifikovana slaba mista soucasneho stavu. Tyto informace byly použity při navrhu modelu. Prvni prvek modelu tvoři vize a strategie problem managementu. Nasledně byla provedena analýza zainteresovaných stran z pohledu role problem manažera. Strucně byly představeny take nastroje pro podporu prace problem manažera. Definovany zodpovědnosti jednotlivých roli a urceno co je problem a co už nikoli. Tim model předchazi možným nedorozuměnim a snižuje třeci plochy. Stěžejni casti celeho modelu je samotný proces u něhož byly identifikovany ctyři zakladni faze. Pro ucely předavani informaci z procesu a do něj byl take navržen způsob komunikace a eskalacni matice. Navrh modelu uzavira skupina klicových ukazatelů výkonnosti. V posledni casti prace byla navržena databaze znamých chyb a diskutovany aktualni výzvy v oblasti problem managementu. Autor je problem manažerem ve vybrane spolecnosti a tudiž teměř v každe casti noveho modelu byl schopen vložit doporuceni z praxe a take přicinne vysvětleni.
Warm-Up Intensity and Time-Course Effects on Jump Height under Cold Conditions

With this study, we aimed to investigate the effects of different warm-up intensities on counter-movement jump (CMJ) performance over time under cold conditions. Eleven male collegiate athletes volunteered. The participants performed high-intensity warm-up (HWU) at 80% VO2max and moderate-intensity warm-up (MWU) at 60% VO2max for 15 min on a bicycle ergometer in a laboratory room at 10 °C. CMJ height, vastus lateralis muscle temperature, heart rate, and perceived fatigue were measured before warm-up (Pre), immediately after (Post 0), 10 min after (Post 10), and 20 min after (Post 20). Significant main effects and interactions were found for CMJ height (time, p < 0.001 and ηp2 = 0.859; interaction, p = 0.007 and ηp2 = 0.327). HWU significantly increased CMJ height at Post 0 to Post 20 compared to that at Pre (p < 0.01), whereas MWU increased CMJ height at Post 0 only compared to that at Pre (p < 0.001). The results indicate that HWU achieved an increase in CMJ height for 20 min. MWU changed CMJ height instantly, but the change did not last compared to HWU in a cold environment.
Creativity, exploration and control in musical parameter spaces

This thesis investigates the use of multidimensional control of synthesis parameters in electronic music, and the impact of controller mapping techniques on creativity. The theoretical contribution of this work, the EARS model, provides a rigorous application of creative cognition research to this topic. EARS provides a cognitive model of creative interaction with technology, retrodicting numerous prior findings in musical interaction research. The model proposes four interaction modes, and characterises them in terms of parameter-space traversal mechanisms. Recommendations for properties of controller-synthesiser mappings that support each of the modes are given. This thesis proposes a generalisation of Fitts’ law that enables throughput-based evaluation of multi-dimensional control devices. Three experiments were run that studied musicians performing sound design tasks with various interfaces. Mappings suited to three of the four EARS modes were quantitatively evaluated. Experiment one investigated the notion of a ‘divergent interface’. A mapping geometry that caters to early-stage exploratory creativity was developed, and evaluated via a publicly available tablet application. Dimension reduction of a 10D synthesiser parameter space to 2D surface was achieved using Hilbert space-filling curves. Interaction data indicated that this divergent mapping was used for early-stage creativity, and that the traditional sliders were used for late-stage fine tuning. Experiment two established a ‘minimal experimental paradigm’ for sound design interface evaluation. This experiment showed that multidimensional controllers were faster than 1D sliders for locating a target sound in two and three timbre dimensions.
Optimized Fault Diagnosis Algorithm under GAN and CNN Hybrid Model

The network fault diagnosis algorithm is one of the most important algorithms to solve network transmission problems. In traditional network fault diagnosis, it mainly analyzes and troubleshoots the fault manually by comparing the alarm information of the network performance index with the expert experience database. Diagnosis methods based on manpower analysis will take up much material resources and manpower and increase maintenance costs. Therefore, there is an urgent need for a more efficient and intelligent fault diagnosis technology. In addition, as the current network is becoming more and more complex, and based on this consideration, a semi-supervised fault diagnosis algorithm is studied in this paper. It is a combination of the GAN and CNN models. Meanwhile, the method of combining relief and mutual information is applied to reducing the dimensionality of network feature parameters, and the optimal feature combination is selected. The fluctuations in the convergence of the generated confrontation network model are stabilized. Moreover, the simulation software is used to build the heterogeneous wireless network scenario studied. Meanwhile, an improved fault diagnosis model is constructed to verify that in the case of both GAN and CNN models, the accuracy of fault diagnosis algorithm can reach 98.6%, which is significantly higher than other comparative analysis methods. It has contributed to ensuring the user’s service experience and reducing the cost of network maintenance and operation.
Pyrazoles and pyrazolines as anti-inflammatory agents

The five-membered heterocyclic group of pyrazoles/pyrazolines plays important role in drug discovery. Pyrazoles and pyrazolines present a wide range of biological activities. The synthesis of the pyrazolines and pyrazole derivatives was accomplished via the condensation of the appropriate substituted aldehydes and acetophenones, suitable chalcones and hydrazine hydrate in absolute ethanol in the presence of drops of glacial acetic acid. The compounds are obtained in good yields 68–99% and their structure was confirmed using IR, 1H-NMR, 13C-NMR and elemental analysis. The novel derivatives were studied in vitro for their antioxidant, anti-lipid peroxidation (AAPH) activities and inhibitory activity of lipoxygenase. Both classes strongly inhibit lipid peroxidation. Compound 2g was the most potent lipoxygenase inhibitor (IC50 = 80 µM.) The inhibition of the carrageenin-induced paw edema (CPE) and nociception was also determined, with compounds 2d and 2e being the most potent. Compound 2e inhibited nociception higher than 2d. Pyrazoline 2d was found to be active in a preliminary test, for the investigation of anti-adjuvant-induced disease (AID) activity. Pyrazoline derivatives were found to be more potent than pyrazoles.
Virginia School Bus Driver Training: Does Training Program Adequacy Affect school Bus Accident Rates?

i Acknowledgements. iv Dedication. v List of Tables. x List of Figures. xii Chapter I Introduction. 1 Organization of the Study . 4 Statement of the Problem . 5 Purpose of the Study . 6 Significance of the Study . 7 Definitions . 7 Limitations. 10 Chapter II Literature Review. 12 Introduction. 12 National History. 15 National Legislation Effecting Transportation/Driver Training . 17 Standard No. 17 . 18 Virginia Pupil Transportation History . 19 Virginia Legislation. 21 School Bus Driver Training in Virginia . 22 Virginia’s School Bus Driver Training Program . 23 Introduction. 23 Pre-service. 23 Behind-The-Wheel Instruction . 25 In-Service Instruction. 25 Legal Aspects of Training . 26 Court Cases . 26 Driver Liability . 27 Behavioral Aspects of Safety Training . 28 Introduction. 28 Program Establishment . 29 Program Success . 30 Reducing Risks. 30 Summary. 32 Industry Accident Reduction . 32 Accident Reduction of Truck Drivers . 33 Studies Verifying the Validity and Cost Effectiveness of School Bus Driver Training . 34
A distributed control system for multirotor aerial platforms

In a variety of microavionics systems for multirotor flying platforms, only a few are designed as open hardware and software solutions, suitable for scientific research. In this paper, we present our own approach – a modular, distributed control system. The developed solution is adaptive for new tasks, unified between each module and designed in an innovative hardware manner. The presented solution has been already developed in various designs of multirotor platforms intended for different applications.
Feature Selection with Hybrid Bio-inspired Approach for Classifying Multi-idiom Social Media Sentiment Analysis

: Social media sentiment analysis consists on extracting information from users’ comments. It can assist the decision-making process of companies, aid public health and security and even identify intentions and opinions about candidates in elections. However, such data come from an environment with big data characteristics, which can make traditional and manual analysis impracticable because of the high dimensionality. The implications on the analysis are high computational cost and low quality of results. Up to date research focuses on how to analyse feelings of users with machine learning and inspired by nature methods. To analyse such data effectively, a feature selection through cuckoo search and genetic algorithm is proposed. Machine learning with lexical analysis has become an attractive alternative to overcome this challenge. This paper aims to present a hybrid bio-inspired approach to realize feature selection and improve sentiment classification quality. The scientific contribution is the improvement of a classification model considering pre-processing of the data with different languages and contexts. The results prove that the developed method enriches the predictive model. There is an improvement of around 13% in accuracy with a 45% average usage of attributes related to traditional analysis.
Development of a low-cost iot platform for data collection

Precision agriculture in the Internet of Things (IoT) integrates different technologies able to raise crop productivity, optimize resource efficiency, and accelerate decision making. However, the adoption of this technology is usually costly, affecting the acquisition by the farmers. Thus, the objective of this work was to develop and evaluate low-cost hardware to obtain data in a hydroponic system via IoT. The experiment was conducted at the Pici Campus of the Federal University of Ceará and split into three distinct stages. Firstly, the DS18B20 temperature sensors were calibrated in water, using the KR380 infrared thermometer as a comparison method. For the second step, when the hydroponic system was installed, the water temperature was monitored in the channel and not in the solution reservoir. In this same phase, the quality of data sending and receiving was investigated. In the third step, the sensory data were analyzed with those obtained by the local Meteorological Station. The calibration results revealed that the DS18B20 sensor has reasonable accuracy and excellent agreement and reliability between data. As for receiving and storing, only 6% of the total data was lost.
Prevalence, complications and factors associated with severely elevated blood pressure in patients with hypertension: a cross-sectional study in two hospitals in Yaoundé, Cameroon

Introduction severely elevated blood pressure significantly increases cardiovascular morbidity and mortality in hypertensive Black patients. The objective of this study was to determine the prevalence, complications and factors associated with severe high blood pressure in hypertensive patients in Yaoundé, Cameroon. Methods we conducted a cross-sectional study in the outpatient and cardiology units of two teaching hospitals in Yaoundé. We included consenting hypertensive patients aged over 18 years. We first measured their blood pressure (BP), then we collected their sociodemographic data, cardiovascular risk factors, follow-up data, and ended with a complete physical examination. We performed a regression analysis to assess correlates of severe hypertension. Results we included a total of 153 patients with 33 (21.6%) of them having severe hypertension. Among the 33 patients, 16 (48.5%) were male and 17 (51.5%) were female. Their mean age was 60.52 ± 12.83 years. Chronic kidney disease (78.8%), hypertensive retinopathy (69.7%) and left ventricular hypertrophy (48.5%) were the most common complications. On multiple logistic regression analysis, inadequate follow-up was independently associated with severe hypertension (adjusted OR=7.09; 95% CI [2.29-21.9]). Conclusion severely elevated BP is common among hypertensive patients in our setting with important physical and economic consequences. Increased patients awareness and improving access to primary care physicians and cardiologists, through health insurance or other means, may be an effective strategy for reducing cardiovascular morbidity and mortality among hypertensive Black patients.
UAV-Mounted Cloudlet Systems for Emergency Response in Industrial Areas

The advancements in Internet of Things (IoT) and embedded systems, 5G networks and next-generation wireless systems, and embedded and distributed artificial intelligence are empowering Industry 4.0. In this new industrial era, smart autonomous and connected systems will improve efficiency, reduce cost and pollution, and increase productivity and safety in industrial 4.0 based applications. Nevertheless, the new generation technologies mentioned above have not been explored to improve safety in multiplant and industrial zones. In this article, we shed light on the design of unmanned aerial vehicles (UAVs)-assisted systems for emergence response in multiplant and industrial zones. We discuss the important contributions of UAV-mounted cloudlet systems to support SAR missions by providing computation, communication, and storage resources to first responders, surveillance of the affected area, real-time monitoring of SAR members and victims, and caching nodes to improve content delivery among SAR teams. Besides, we design an envisioned UAV-cloudlet reference system for emergency response in industrial areas. Moreover, we highlight the current challenges that are being addressed in the literature aimed at making possible the efficient use of the designed UAV-mounted cloudlet systems for emergency response. Finally, we point out some future research directions that require further investigation.
Performance comparison of 60 GHz printed patch antennas with different geometrical shapes using miniature hybrid microwave integrated circuits technology

This study presents a comparative study of several printed antennas having different shapes of the patch (rectangular, square, triangular, trapezoidal, circular, elliptical, and annular ring), suitable for 60 GHz wireless applications. All these microstrip patch antennas have been designed and fabricated on a very thin ceramic substrate to enable a high level of integration with other integrated circuits including passive circuits (such as power dividers, hybrid couplers, and passive filters), and active circuits (such as low noise amplifier (LNA), radio frequency (RF) mixers, and frequency multipliers). In that event, all of those circuits will be incorporated on a single and very small planar substrate to reduce overall size, and to avoid lossy millimetre-wave connectors. To analyse and compare the performances, advanced design system of Keysight Technologies was used for circuits design and simulation. This comparison is based on the obtained results particularly in radiation characteristics and inputs return loss, by determining the main associated parameters such as the bandwidth, voltage standing wave ratio, gain, directivity, efficiency, and cross-polarisation level. This comparative study would be very helpful for RF design engineers to select suitable antenna geometry while designing microstrip patch antenna arrays at 60 GHz millimetre-wave band.
Performance Improvement of Turbid Underwater Wireless Optical Communication Link Using Ratiometric Signal Processing

This article introduces a technique of improving the link performance of the underwater wireless optical communication (UWOC) system in terms of signal-to-noise ratio (SNR) by incorporating a novel ratiometric signal processing (RSP) scheme at the receiver node. In addition, the temporal fluctuations in the attenuation coefficient information (ACI) of the UWOC channel in the nonuniform turbulent regime are analyzed, and the corresponding distribution function is analytically derived. The consistency of the obtained statistical distribution of the ACI parameter is analyzed by simulating the experimental data in a UWOC prototype link within a laboratory-controlled turbulent regime. The experimental outcomes indicate a relative improvement in the SNR by 1.70 to 3.23 dB in the nonuniform turbulent conditions upon incorporating the proposed RSP technique at the receiver node. It is also observed that the mean square error and an average difference of the received images that are processed by incorporating the RSP technique are lower as compared to that of the images without processing at the receiver node in the UWOC prototype link. The approach of implementing the proposed RSP technique is observed to improve the performance of the UWOC link.
Asymptotic Normality of the Robust Equivariant Estimator for Functional Nonparametric Models

As in parametric regression, nonparametric kernel regression is essential for examining the relationship between response variables and covariates. In both methods, outliers may affect the estimators, and hence robustness is essential to deal with practical issues. This paper proposes a family of robust nonparametric estimators with unknown scale parameters for regression function based on the kernel method. In addition, we establish the asymptotic normality of the estimator under the concentration properties on small balls of probability measure of the functional explanatory variables. The superiority of the proposed methods is shown through numerical and real data studies to compare the sensitivity to outliers between the classical and robust regression (fixed and unknown scale parameter). Such a new proposed method will be useful in the future for analyzing data and making decisions.