Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Nurses' Knowledge and Practice Regarding Pre- Marital Counseling in Primary Health Care Services

Background:Premarital counseling is a worldwide activity aiming to diagnose, treat unrecognized disorders, and reduce transmission of diseases to couples to prevent any risk of transmitting any disease to their children which may affect the quality of marriage and the health of future generations. The aim of this study: isto assess knowledge and practice of nurses working in premarital counseling in primary health care services. Design: descriptive design was used. Setting: This study was conducted at primary health care services at Menuofia Governorate. Sample: purposive sample of 61 nurseswasrecruited. Tools: two tools were used for data collection, tool I: nurses' structured interviewing questionnaire who working in primary health care services it includes; demographic characteristics of nurses and their knowledge regarding pre-marital counseling. tool II: pre-marital counseling observation checklist for nurses working in primary health care services to assess nurses' practice.Results:findings of the present study revealed that, there were poor of nurses' knowledge and practice regarding pre-marital counseling (70%)of studied sample had poor knowledge, (15%) fair and 15% had good knowledge. Also, (80%)of studied sample had negative performance and (20%) of them had positive performance regarding pre-marital counseling.Conclusion:there was poor of nurses' knowledge and practice of pre-marital counseling in primary health care services. Recommendation:There is an important need to devloptraning program about pre-marital counseling for all nurses working in primary health care services to increase knowledge and practice.
FATE AND EFFECTS OF CADMIUM IN NEAR SHORE ENVIRONMENTS-INTERACTIONS BETWEEN CD AND THE LUGWORM, ARENICOLA MARINA

Damk Skaebne og effekter af partikel-reaktive forurenende stoffer som for eksempel tungmetallet Cd er vigtige emneomrader i okotoksikologien. Dette er saxlig vigtigt for estuarine omrider hvor Cd akkumuleres i sedimenter (Campbell & Tessier 1996) og udgerr en fare for den estuarine biota (Viarengo 1985). Estuarier kan karakteriseres ved salinitetsamdringer der influerer Cd’s speciering Mantoura et al. 1978) og dermed Cd’s skaabne og okotoksikologi (Rainbow 1995). Desuden vi1 bioturberende infauna pivirke optagelse og fordeling af Cd i sediment og dermed tilgamgeligheden af Cd, for infauna (Everaarts & SaralaDeG 1996). Omvendt kan metaleksponering p5virke bioturbationen (Miron et al. 1994). Slutteligt kan de osmo-regulerings/-adapterings mekanismer, estuarine invertebrater anvender til at klare salinitetssendringer, pivirkes af Cd (Rasmussen et al. 1995). For&let med denne afhandling var at underwgejlere relaterede spnrgsm61: Hvordan vi1 salinitet og den bioturberende organisme Arenicola marina p&irke fordelingen of Cd mellem vand og sediment? Er der andre vigtige estuarine faktorer der kan pavirke denne fordeling? Kan eksponering til Cd pavirke sandonnens bioturbation? Effekteme af salinitetsaxdringer modvirkes af A. marina ved hjselp af volumenregulering. Kan Cd pavirke denne regulering? Er dette toksisk for dyret? De vigtigste resultater af underwgelseme var: i) Sandormens bioturbation ogede s&e1 sedimentets Cd-optagelse som den vertikale fordeling af Cd i sedimentet r& Cd blev tilsat vandfasen (I). Dette blev underbygget af et mindre in situ eksperiment (IV). Denne kraftige omfordeling af Cd i sedimentssjlen blev ogsi observeret hvis et tyndt Cd-mserket sedimentlag blev placeret overst pa sedimentet eller hvis hele sedimetsojlen blev ,. ~, homogent mssrket med Cd (IL). Det menes at bioturbation generelt oger mobiliseringen af Cd fra sediment til vand. Ikke desto mindre peger resultateme pi en netto Cd-fluks fra vand til sediment da sandormens stserke irrigation pumper det overliggende vand dybt ned i sedimentet hvor oplost Cd bindes (II). Selv om en salinitetsstigning fra 12 til 18 og 24% resulterede i en oget Cd frigivelse
Effects of Pouring Temperature and Squeeze Pressure on Al-8%Si Alloy Squeeze Cast Parts

This study investigated the effects of squeeze parameters on the properties of squeeze castings and the optimum parameters for producing squeeze castings from Al-Si alloy. It also compared the properties of the squeeze castings with those of chill castings. Squeeze castings were made from Al-8%Si alloy using pressures of 25150MPa with the alloy poured at 650, 700 and 750C into a die preheated to 250C. Squeeze time was 30s. It was found that for a specific pouring temperature, the microstructure of squeeze castings became finer; density and the mechanical properties were increased with increase in pressure to their maximum values while further increase in pressure did not yield any meaningful change in the properties. Compared with chill casting process, squeeze casting enhanced the mechanical properties; it increased the hardness, UTS, 0.2% proof stress and elongation of the alloy to optimum values of HRF58.0, 232MPa, 156MPa and 3.8% respectively at squeeze pressure of 125MPa and pouring temperature of 700C. The study concluded, among other things, that optimum pouring temperature of 700C and squeeze pressure of 125MPa are suitable for obtaining sound Al-8%Si alloy squeeze castings with aspect ratio not greater than 2.5:1.
Characteristic of Demography and Pulmonary Fuction Value Maximal Voluntary Ventilation (MVV) of Cronic Obstructif Pulmonary Disease (COPD) patients in Medan

COPD (Chronic Obstructive Pulmonary Disease) causes of death worldwide. Patients experiencing a decrease in the work function of the respiratory muscles can be measured by spirometry, interpretasi spirometry results can be obtained by value Maximal Voluntary Ventilation (MVV), which provide databasic abnormalities in lung function. Descriptive method that describes the demographic data and lung function MVV value. The study was conducted in July s / d August 2018, the sample size of 56 respondents using purposive sampling technique. The results of the study describes the demographics and valuesMaximal Voluntary Ventilation (MVV) ranging from age, education, occupation, body mass index, smoking a long history, the sheer number of cigarettes smoked, and duration of pain COPD. There are demographic data linkage with MVV value in COPD patients.
Work Engagement and Proactive Behavior A Concept

This article discusses the concept of proactive behavior and work engagement and summarizes relevant research. On the basis of Broaden and Build Theory (Fredrickson, 2001), this study explores the role of work engagement in predicting proactive behavior. Despite the growing concern on the increasingly crucial aspects of proactive behavior, little is known on how work engagement can propose linkage to proactive behavior. In this article, I review sets of literature to propose possible linkage on such relationship. To offer explanatory device, this article review and discuss related theory and concepts to provide direction and sense of the possible linkage.
Correlations Between Textual Features and Grades on The Swedish National Exam in English: A Coh-Metrix Analysis

Researchers and educators do not always have a clear idea about how evaluators actually go about assessing student texts. On the one hand, grading criteria are often vague and differ across locations and age groups. On the other hand, the underlying issues of how evaluators make judgments about student texts, and how various textual and linguistic features are related to grades, are not completely understood. The current study addresses the latter issue by analysing links between textual features and grades in L2 writing, using the computational tool Coh-Metrix. The textual features addressed concern linguistic sophistication and cohesion. Previous research on these issues has been conducted both with and without computational aids. Early research, for example Engber (1995), showed that there are correlations between lexical variation and high grades. Engber (1995), also, found correlations between error-free lexical variation and grades. More recent research has been conducted with tools such as Coh-Metrix. Crossley and McNamara’s (2010) research indicates that high proficiency L2 writers write more sophisticatedly, but with less cohesiveness than low proficiency writers. This study aims to test Crossley and McNamara’s (2010) results using the same computational tool, Coh-Metrix, in another setting. Thirty student essays were collected from the Swedish National Exam in English. Five essays for each grade (A F) were selected. The texts were analysed in Coh-Metrix 3.0 and correlations between grades and linguistic features were calculated. The result was compared to Crossley and McNamara’s (2010) study and correlations stronger than 0.4 and –0.4 were analysed. The results indicate that the more sophistically advanced texts did receive higher grades. Rather surprisingly, only weak correlations were found between grades and cohesion.
Applying SFA and DEA in Measuring Banks Cost Efficiency in Relation to Lending Activities: The Case of Vietnamese Commercial Banks

Vietnam's economy heavily relies on credit from the banking sector in the absence of other sources, which requires the state bank need to closely monitor lending to minimize bad debts. Loans play an important role in earning profit and efficiency of the bank. However, a bigger amount of loans may cause higher cost spent to monitor loans and manage the bigger loan portfolio. It is obvious that problem loans negatively affect both profit efficiency and cost efficiency of the bank. This study is, therefore, examining the impact of loans on cost efficiency in the context of Vietnamese commercial banks. Data of 25 Vietnamese commercial bank from 2010 to 2017 were collected and analyzed. In first step Stochastic frontier analysis (SFA) was used to measure cost efficiency. Following, we examine if the bank loan has any effect on cost efficiency by using regression and finally, Data envelopment analysis (DEA) window model was applied to evaluate bank cost efficiency and make a comparison. The results found in this paper indicated that during 2010-2017, 25 sample Vietnamese commercial banks perform well in term of cost efficiency with an average efficiency score range from 0.8 to 0.9. In addition, results also found a strong consistency between SFA and DEA Window in measuring cost efficiency. Our results also indicated that bank loans found to have a significantly negative effect on bank cost efficiency. Findings of this study can provide important insights for bankers in managing their cost efficiency. Moreover, findings of this study also suggested that results obtained from SFA and DEA are consistent, which enables researchers to have greater confidence in choosing the method measuring bank efficiency. Furthermore, this study is expected to be the first empirical study on the relationship between loans and cost efficiency of the bank; therefore, it shed a light on literature for the new aspect of bank efficiency.
Effect of Infection Control Guideline on Practice of Health Care Workers Caring for Patients with Hepatitis C

Background:The disease of a major influence is hepatitis C. The serious, advanced, and possibly lifethreatening infection is Chronic HCV infection. Objectives: the purpose of this study was to value the outcome of applying infection control instruction on health care workers' practice. Design: quasi-investigationalstudydesignwas done in this study. Setting: The study directed at the Egyptian Liver Institute in Sherbein Dakahlia. Sample: A conveniencesection of 61 health care workers was designated. Tools of the study: Two tools were used to gather the requiredstatistics for this study: Tool I: Health care workerspracticeworksheet. Tool II: Infection control instruction. Result: There was a statistically significantamongtotalpractice and ageingimmediateapplicationstage were (p=.038). Conclusion: There was progress in health care workers' practice in direct and next 3 months of application of infection control instruction. Recommendation: Intermittentstimulatingpreparation courses should be delivered to bring up the health care workers to datepracticeconcerningworldwide infection control protections.
Nature of science understanding level of science colleges’ graduates at Najran University and its relationship to their teaching performance

-The study aimed to investigate the understanding level of science college graduates at Najran University of the nature of science and its relationship with their teaching performance and other demographic variables such as specialty, university rating, and methodology course. To achieve this, a test for the understanding of the nature of science was carried out (SUSSI). Observation card was also used for the sample of the study which consisted of (30) female students of physics and chemistry departments at the college of science who were enrolled the practicum course at public schools. The findings illustrated that the understanding level of science nature was low. It is significantly different from the standard criterion in education (80%). There was no statistically significant relationship between the science nature understanding and teaching performance. The nature of science understanding does not vary in accordance to variation in specialty, university rating and the course in methodology.
Adaptive Scatter Search to Solve the Minimum Connected Dominating Set Problem for Efficient Management of Wireless Networks

An efficient routing using a virtual backbone (VB) network is one of the most significant improvements in the wireless sensor network (WSN). One promising method for selecting this subset of network nodes is by finding the minimum connected dominating set (MCDS), where the searching space for finding a route is restricted to nodes in this MCDS. Thus, finding MCDS in a WSN provides a flexible low-cost solution for the problem of event monitoring, particularly in places with limited or dangerous access to humans as is the case for most WSN deployments. In this paper, we proposed an adaptive scatter search (ASS-MCDS) algorithm that finds the near-optimal solution to this problem. The proposed method invokes a composite fitness function that aims to maximize the solution coverness and connectivity and minimize its cardinality. Moreover, the ASS-MCDS methods modified the scatter search framework through new local search and solution update procedures that maintain the search objectives. We tested the performance of our proposed algorithm using different benchmark-test-graph sets available in the literature. Experiments results show that our proposed algorithm gave good results in terms of solution quality.
Effect of corporate governance on financial performance of Nepalese commercial banks

This study examines the impact of corporate governance on financial performance of Nepalese commercial banks. The return on assets (ROA) and return on equity (ROE) are the dependent variables. Women on board of director (WD), audit committee size (AS), firm size (FS), board size (BS), board independence (BI), foreign ownership (FO) and credit deposit ratio (CD) are the independent variables. The data are collected from the annual reports of selected commercial banks. Total of 23 commercial banks of Nepal are included in this study from 2012/13 to 2016/17 leading to a total of 115 observations. The regression and correlation models were estimated to test the significance and importance of corporate governance and performance of Nepalese commercial banks. The findings shows that board independence has a significant negative relation on return on assets but insignificant negative impact on the return on equity. The credit deposit ratio also shows a significant negative impact on return on equity but insignificant negative relation with return on assets. Lastly, the firm size has insignificant positive impact on return on assets but a significant positive impact on return on equity.
The Roots of Agricultural Innovation: Patent Evidence of Knowledge Spillovers

This chapter investigates the extent to which agricultural innovations draw on ideas originating outside of agriculture. We identify a large set of US patents for agricultural technologies granted between 1976 and 2018. To measure knowledge spillovers to these patents, we rely on three proxies: patent citations to other patents, patent citations to the scientific literature, and a novel text analysis to identify and track new ideas in the patent text. We find that more than half of knowledge flows originate outside of agriculture. The majority of these knowledge inflows, however, still originate in domains that are close to agriculture.
Moments of (De)Valuation. Confirmation and Devaluation of Ideas in Creative Processes

In recent years contexts for fostering creativity were and still are a chief aim in the field of economic geography. Despite the sophisticated examination of the time-spatial constellation for fostering creativity in clusters, in projects or at events, economic geography concentrated mainly on the aspect of generating new ideas. In general, creativity does not only include the aspect of generation but also the aspect of valuation. However, the problematic of valuating ideas has so far been neglected in economic geography. In order to explore the relation between generation and valuation of new ideas within creative processes this paper seeks to push beyond the prevailing focus in economic geography and analyze the question to what extend the generation and valuation of new ideas are influencing each other. For this purpose, a process perspective on creativity and a pragmatic view on valuation are chosen. Accordingly, creativity is understood as a collective process, while valuation is characterized by multiple valuation criteria and situations of value uncertainty. Using the example of pharmaceutical 2 R&D projects to explore the relation between generation and valuation of new ideas within a creative process, this paper introduces an example of a scientific-analytic creative process. Based on the empirical data, it is shown that the relation between generation and valuation of new ideas within pharmaceutical R&D projects can be understood as a loop of mutual influence, where moments of valuation are crucial for the creative process. Furthermore, it is shown that particularly negative value judgements are essential for the generation aspect of creativity and that positive value judgements lead to path dependencies.
Educational Tool for Testing Emotion Recognition Abilities in Adolescents

Emotion recognition represents an important predictor for the development of social interactions. Previous studies have shown that the ability to recognize emotions, the speed, and accuracy, with which individuals process emotions, is an ability that develops with age, starting from early childhood. Children with autism spectrum disorder (ASD) show reduced attention to faces and they have difficulties in identifying emotions. Our goal was to investigate the effectiveness of a technology-based educational tool for assessing emotion recognition skills in individuals with ASD and typical developing children. 51 children aged between 12 and 14 years were enrolled in our study, out of which 11 have a diagnosis of ASD. Our results reveal that adolescents perceive emotions differently depending on the type of stimuli that we use and on their ages.
Calibrating Deep Neural Networks using Focal Loss

Miscalibration - a mismatch between a model's confidence and its correctness - of Deep Neural Networks (DNNs) makes their predictions hard to rely on. Ideally, we want networks to be accurate, calibrated and confident. We show that, as opposed to the standard cross-entropy loss, focal loss [Lin et. al., 2017] allows us to learn models that are already very well calibrated. When combined with temperature scaling, whilst preserving accuracy, it yields state-of-the-art calibrated models. We provide a thorough analysis of the factors causing miscalibration, and use the insights we glean from this to justify the empirically excellent performance of focal loss. To facilitate the use of focal loss in practice, we also provide a principled approach to automatically select the hyperparameter involved in the loss function. We perform extensive experiments on a variety of computer vision and NLP datasets, and with a wide variety of network architectures, and show that our approach achieves state-of-the-art calibration without compromising on accuracy in almost all cases. Code is available at this https URL
MaxUp: A Simple Way to Improve Generalization of Neural Network Training

We propose \emph{MaxUp}, an embarrassingly simple, highly effective technique for improving the generalization performance of machine learning models, especially deep neural networks. The idea is to generate a set of augmented data with some random perturbations or transforms and minimize the maximum, or worst case loss over the augmented data. By doing so, we implicitly introduce a smoothness or robustness regularization against the random perturbations, and hence improve the generation performance. For example, in the case of Gaussian perturbation, \emph{MaxUp} is asymptotically equivalent to using the gradient norm of the loss as a penalty to encourage smoothness. We test \emph{MaxUp} on a range of tasks, including image classification, language modeling, and adversarial certification, on which \emph{MaxUp} consistently outperforms the existing best baseline methods, without introducing substantial computational overhead. In particular, we improve ImageNet classification from the state-of-the-art top-1 accuracy $85.5\%$ without extra data to $85.8\%$. Code will be released soon.
Convolutional Tensor-Train LSTM for Spatio-temporal Learning

Learning from spatio-temporal data has numerous applications such as human-behavior analysis, object tracking, video compression, and physics simulation.However, existing methods still perform poorly on challenging video tasks such as long-term forecasting. This is because these kinds of challenging tasks require learning long-term spatio-temporal correlations in the video sequence. In this paper, we propose a higher-order convolutional LSTM model that can efficiently learn these correlations, along with a succinct representations of the history. This is accomplished through a novel tensor train module that performs prediction by combining convolutional features across time. To make this feasible in terms of computation and memory requirements, we propose a novel convolutional tensor-train decomposition of the higher-order model. This decomposition reduces the model complexity by jointly approximating a sequence of convolutional kernels asa low-rank tensor-train factorization. As a result, our model outperforms existing approaches, but uses only a fraction of parameters, including the baseline models.Our results achieve state-of-the-art performance in a wide range of applications and datasets, including the multi-steps video prediction on the Moving-MNIST-2and KTH action datasets as well as early activity recognition on the Something-Something V2 dataset.