Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of Quality of Life and Related Factors in Infertile Women Undergoing Infertility Treatment

Objective: Infertility is an unpleasant emotional experience and is one of the factors that affect the quality of life. Psychological problems caused by infertility can affect fertility success. This study conducted to investigate quality of life and related factors in infertile women. Methods: This cross-sectional study carried out on 80 infertile women referred to the infertility treatment center of Imam Khomeini Hospital in Sari, Iran. Data gathered by World Health Organization Quality of Life (WHOQOL)-BREF questionnaire and analyzed using Pearson’s and Spearman’s correlation coefficient and Kruskal-Wallis test in SPSS version 24 (P < 0.05). Results: Mean age of women was 33 ± 5.70 years. Quality of life of them was good (32.5%), moderate (61.2%), and poor (6.2%). there was a reverse relationship between the duration of trying to conceive and quality of life, meaning that increase of this duration was associated with decreased quality of life (P = 0.05). The increase in duration of cohabitation resulted in a lower number of individuals with a good life quality level and a higher number of subjects with a moderate level of quality of life. In all levels the desire to have a child resulted in moderate life quality in most of the participants. Findings also indicated a significant relationship between quality of life and monthly income, people with lower economic status had lower quality of life (P < 0.05). Conclusion: Because two-thirds of people had a moderate quality of life, awareness of healthcare providers about this issue and their needs will lead to better service provision to this group.
Chapter 21-Disorders of Mineral and Bone Metabolism During Pregnancy and Lactation

l Multiple vertebral crush fractures can occur in association with pregnancy, especially with lactation; pharmacotherapy has an uncertain benefit in these cases. l Physiological hypercalciuria during pregnancy will mask the diagnosis of familial hypocalciuric hypercalcemia (FHH), while physiological hypocalciuria during lactation can mask the diagnosis of primary hyperparathyroidism. l Mild primary hyperparathyroidism can cause a sudden hypercalcemic crisis in the third trimester or puerperium, as well as fetal parathyroid suppression that leads to prolonged neonatal hypocalcemia. l Hypercalcemia can also occur during pregnancy due to excess calcitriol (from 24-hydroxylase deficiency) or excess parathyroid hormone-related protein (PTHrP) arising from the breasts, placenta, or both. l Hypoparathyroidism can improve during pregnancy (requiring less supplemental calcium or calcitriol), but in some instances the condition can worsen (requiring increased doses of supplements). l Lactation improves or normalizes mineral homeostasis in hypoparathyroidism, such that severe hypercalcemia can ensue if supplemental calcium and calcitriol are not reduced or stopped.
AERODYNAMIC SHAPE OPTIMIZATION STUDIES OF THE ADODG

The following study presents single and multipoint aerodynamic shape optimizations of two benchmark problems defined by the Aerodynamic Design Discussion Group (ADODG). Mesh warping and geometry parametrization is accomplished by fitting the multi-block structured grid to a B-spline volumes and performing the mesh movements by using surface control points embedded with free-form deformation (FFD) volumes. The aerodynamic model solves the RANS equations with Spallart-Almaras turbulence model. A gradient based optimization algorithm is used with an adjoint method in order to compute the objectives and constraints derivatives with respect to the design variables. The objective in this work is to minimize the drag of airfoil and wings for transonic regimes taking into account volume and thickness constraint, including aerodynamic coefficients constraint. The first problem solved is RAE2822 airfoil in viscous transonic flow, with a lift constraint. The shock in the upper surface is eliminated and the drag coefficient is reduced by 50%. Also in this problem we started the optimization solution from a circle in order to check the robustness of both the flow solver and the mesh warping algorithm, while reaching a "close" solution as obtained by starting from rae2822 airfoil. The second problem is single and multi-point lift and pitch moment constrained drag minimization of the Common Research Model (CRM) wing in transonic, viscous flow. The CRM design is very challenging due to the tight coupling between aerodynamic performance, trim and stability. Other design challenges include the number of design variables and its effect on the optimized configuration. The single-point optimization reduced the drag coefficient by 7.7% using 192 design variables. The single-point designs are relatively robust to the flight conditions. Further robustness is achieved through a multi-point optimization with nearly 5% drag reduction.
OPTIMISATION OF THE FRONTSHEET ENCASPULANT FOR INCREASED RESISTANCE OF LIGHTWEIGHT GLASS-FREE SOLAR PV MODULES F.Lisco,

The aim of this work is to propose a BIPV module design that is contemporarily lightweight, rigid and resistant to the relevant climatic and mechanical stresses (e.g. exposure to DH, UV, hail impacts, etc), supporting structure and reliability at the same time. Encapsulants represent a key part in the PV structure, acting as the bonding layer between the front or back sheet and the PV cell. Therefore, they need to provide excellent adhesion between these components, which is achieved via lamination. They also have to be transparent and provide outstanding electrical insulation and impact resistance to the module. All these properties must be retained after years of exposure to the UV from the sun or other severe weather conditions. With this work, we want to provide a “recipe” to define and qualify the optimum front sheet encapsulant for the proposed lightweight composite PV modules.
DIFFERENTIAL PRIVACY BY DESIGN: ENSURING COVID-19 DATA PRIVACY ON FEDERATED LEARNING SYSTEMS

To address COVID-19 healthcare challenges, we need frequent sharing of health data, knowledge and resources at a global scale. However, in this digital age, data privacy is a big concern that requires the secure embedding of privacy assurance into the design of all technological solutions that use health data. In this paper, we introduce differential privacy by design (dPbD) framework and discuss its embedding into the federated machine learning system. To limit the scope of our paper, we focus on the problem scenario of COVID-19 imaging data privacy for disease diagnosis by computer vision and deep learning approaches. We discuss the evaluation of the proposed design of federated machine learning systems and discuss how differential privacy by design (dPbD) framework can enhance data privacy in federated learning systems with scalability and robustness. We argue that scalable differentially private federated learning design is a promising solution for building a secure,
THE EFFECT OF CLASSROOM ACOUSTICS ON STUDENTS’ LEARNING PROCESSES: SELECTION OF OBJECTIVE PARAMETERS AND PROVISION OF A MEASUREMENT PROTOCOL / Astolfi,

Despite it is well known that learning experience is affected by classroom acoustics, only a reduced number of studies in this area provides clear information on the acoustic quantities that most influence the academic achievements of students. In this study, the indexes with the greater effect on students' performance have been identified and these were therefore considered on the evaluation of acoustical quality in elementary classrooms through in-field measurements. Noise, room acoustics and intelligibility indices in occupied and unoccupied conditions of 29 first-grade classrooms belonging to 13 school buildings in Turin that differ in location and typology, were gathered in the study. Then, the relationships between objective parameters were assessed through statistical analysis in order to select the minimum number required to best characterize the acoustics of the classroom; furthermore parameter thresholds have been identified so the classrooms have been divided into two groups. In addition to that, new important considerations for the creation of a simplified protocol, that can be universally applied when performing acoustic measurements in classrooms so that comparisons across several environments can be performed, emerged.
Food Security and Coping Strategies Among Farmers Affected by Flood Along River Rima of Sokoto State, Nigeria

The study evaluated the food security and coping strategies of selected villages along River Rima affected by flood in Sokoto State, Nigeria. Eighty respondents were randomly selected across three out of nine local governments affected. Data were collected by the use of interview schedule. Descriptive Statistic, food Security Index and Coping Strategy Index (CSI) were used to analyse data collected. In total sample households, the incidence of food security, average food insecurity gap (depth) and square of food insecurity gap (severity) are 59%, 0.33 and 0.007 respectively. Results further revealed that among the coping strategies adopted by households due to flood, relying on less preferred and less expensive foods was the most common adopted while the least adopted by households was skipping whole days without meals. The study concludes that food insecurity in the study area is high and pronounced thus, a special intervention needs to be put in place either by Government or other donor agencies to reduce food insecurity among the people.
THE EFFECT OF DIVIDEND PAYMENT ON SHARE PRICE OF LISTED OIL AND GAS FIRMS IN NIGERIA

The issue of dividend payment has a long history and some dividend theories are prominent in finance literatures. This study investigates the impact of dividend policy on share price of listed companies in the stock exchange market of the Nigeria economy from 2013 to 2017 on a panel data analysis. Given the crucial impact of the oil and gas sector in Nigeria, it becomes expedient to critically analyze the impact of dividend per share and other variables proxy for dividend that are likely to affect share prices in the oil and gas sector in Nigeria. The study adopted a simple statistical methodology. Some underlining theory of dividend policy in line with the efficient market hypothesis was adopted to practically test the efficacy of the model and if the research hypothesis result corroborates with other studies. Due to the numbers of firms operating in the oil and gas sector in Nigeria, the study uses the Yamane’s formula to derive the appropriate sample size while the Kolmogorov test was used to test for normality under the OLS assumption. The variables in the model are statistically significant and the coefficient of determination is very high, indicating that the total variation in the dependent variable are explained by the independent variables in the model. Therefore, the study found out that dividend per share (DPS) affect share price (SP) in the oil and gas sector in Nigeria.
Deep ConvNet: Non-Random Weight Initialization for Repeatable Determinism, Examined with FSGM †

A repeatable and deterministic non-random weight initialization method in convolutional layers of neural networks examined with the Fast Gradient Sign Method (FSGM). Using the FSGM approach as a technique to measure the initialization effect with controlled distortions in transferred learning, varying the dataset numerical similarity. The focus is on convolutional layers with induced earlier learning through the use of striped forms for image classification. Which provided a higher performing accuracy in the first epoch, with improvements of between 3–5% in a well known benchmark model, and also ~10% in a color image dataset (MTARSI2), using a dissimilar model architecture. The proposed method is robust to limit optimization approaches like Glorot/Xavier and He initialization. Arguably the approach is within a new category of weight initialization methods, as a number sequence substitution of random numbers, without a tether to the dataset. When examined under the FGSM approach with transferred learning, the proposed method when used with higher distortions (numerically dissimilar datasets), is less compromised against the original cross-validation dataset, at ~31% accuracy instead of ~9%. This is an indication of higher retention of the original fitting in transferred learning.
Checklist for a safe intra-hospital transport of critically ill patients: A scoping review

Transporting critically ill patients is has a set of risks that may jeopardize their safety. Knowing the risks associated with intrahospitalar transport of critically ill patients is essential to improving patient safety. For the sake of improving patient safety, was chosen to approach it as an intrahospitalar transport checklist, as the literature describes it as a practical and simple way to increase safety. Objective: Map available scientific evidence regarding aspects of a checklist that ensure the safety of critically ill patients in intrahospitalar transport. Material and Method: A scoping review was performed following the methodology proposed by The Joanna Briggs Institute in databases using the EBSCOhost and B-on search engines. Conducted research in Portuguese, English, and Spanish. Selected free full text articles, with no time limit. Inclusion criteria: adult/elderly critically ill patient, intrahospital transport, a checklist and patient safety. Results: Included 7 articles for analysis. Most verification requests that ensure the safety of critical patients on intrahospitalar transport concern the transport preparation phase, in which patient is monitored was the most mentioned aspect. From the post-transportation phase, checklist aspects are only available in 3 of 7 articles Conclusion: All studies address aspects that improve the safety of critically ill patients in intrahospitalar transport and are likely to be included in the checklist. There is no unanimity as to which aspects to include in the checklist.
Characterisation of potential pollution sources in the quantitative assessment of risk to groundwater resources within the Birmingham aquifers , UK

This work presents a methodological approach where distribution of potential pollution sources and historical frequency of pollution incidents are included in the assessment of risk to groundwater resources. Calibrated flow and transport models were setup, and integrated with a FORTRAN coded risk model. The risk model was run to generate synthetic contaminant source terms that were subsequently transported by the coupled flow and transport models. The ranges of calibrated values obtained for horizontal and vertical hydraulic conductivities are 5.787x10 -6 2.315x10 -5 m/s and 5.787x10 -8 1.157x10 -7 m/s, respectively. Layering within the aquifer is thought to account for the large vertical anisotropy. The corresponding values for the specific yield and specific storage are 0.10 0.12, and 1x10 -4 5x10 -4 , respectively. The estimated historical frequency of pollution occurrence per stress period of 91 days is 35, while the probability of pollution occurring at any of the sources over a period of stress period is calculated as 0.0014. The generated risk maps provide anticipatory capability for risk quantification and show that approximately 55% of the monitoring boreholes have high (i.e. 70 – 100 %) likelihood of having contaminant concentration being less than 0.06 mg/l throughout the simulation.
PR ] 5 J ul 2 02 1 PERCOLATION TRANSITION FOR RANDOM FORESTS IN d > 3

The arboreal gas is the probability measure on (unrooted spanning) forests of a graph in which each forest is weighted by a factor β > 0 per edge. It arises as the q → 0 limit with p = βq of the q-state random cluster model. We prove that in dimensions d > 3 the arboreal gas undergoes a percolation phase transition. This contrasts with the case of d = 2 where all trees are finite for all β > 0. The starting point for our analysis is an exact relationship between the arboreal gas and a fermionic non-linear sigma model with target space H. This latter model can be thought of as the 0-state Potts model, with the arboreal gas being its random cluster representation. Unlike the q > 0 Potts models, the H model has continuous symmetries. By combining a renormalisation group analysis with Ward identities we prove that this symmetry is spontaneously broken at low temperatures. In terms of the arboreal gas, this symmetry breaking translates into the existence of infinite trees in the thermodynamic limit. Our analysis also establishes massless free field correlations at low temperatures and the existence of a macroscopic tree on finite tori.
TRANSACTIONS OF POWDER METALLURGY ASSOCIATION OF INDIA

Nano-sized Cr2AlC powders were synthesized at relatively low temperature by the mechanically assisted synthesis method using a high energy planetary ball mill. The formation of Cr2AlC from chromium carbide (CrCx) and Al powders was monitored by the XRD analysis with progression of ball milling. Synthesis was carried out at three sequential stages: preparation of CrCx powders through reaction synthesis, mechanical activation of synthesized CrCx powder through ball milling for different durations and synthesis of final product by adding Al to the milled CrCx. The nanostructures of the synthesized powder were realized by the FESEM micrograph and XRD analyses. These analytical observations have revealed that the nanocrystalline. Cr2AlC particles were formed just after Al melting when heated with CrCx powder milled for about 15hr. Very high purity Cr2AlC powder with crystallite size smaller than 150 nm and acicular in shape with sharp edges; have been successfully obtained.
Urban Leptospirosis and Rainfall in the City of Rio De Janeiro/RJ, Brazil, 2007 To 2017

The aim of this paper is investigate the effects of rainfall in urban leptospiroses cases in a one the most largest city in the world, Rio de Janeiro/Brazil, in 2007 to 2017 period. Urban Leptospirosis study is relevant to public health because of its severity and mode of dissemination, being its occurrence greater in places with socio-environmental and climatic vulnerability, as Rio de Janeiro city. To evaluate the correlation between the time series of the human leptospirosis cases and rainfall, were used exploratory graphical analyzes and regression models. It was possible to observe that leptopirose cases are significantly associated with the monthly mean rainfall of the previous month (RR = 1.11 [95% CI: 1.08 1.15]), the increases of lepstopirosis cases in this urban setting happens according to rainfall. The monitoring not only of cases of leptospirosis, but also climatic variables, need to be taken into account in epidemiological surveillance. The implementation of public policies for basic sanitation, mainly in urban areas, are necessary for the maintenance and prevention of most neglectable infectious diseases.
Karate as anti-bullying strategy by improvement resilience and self-efficacy in school-age youth

Bullying is characterized by power imbalances in relationships, which can lead to negative social consequences. Youth with higher levels of resilience and self-efficacy are less likely to engage in aggressive behaviours or be victims of bullying. Karate, a martial art emphasizing respect, self-regulation and health promotion, may be an effective alternative to the anti-bullying failing approach of institutions. Therefore, the purpose of this randomized controlled study was to examine the effect of a 12-week karate-based intervention on resilience and self-efficacy. 100 students from 3 high schools, aged 14-16 years, were randomly assigned to experimental group (n=50) that performed technical Shotokan karate practice and psychoeducational activities (90 min., once per week), or wait-list control group (n=50). Before and after intervention, two standardised psychometric instruments were used: CYRM-28 assessed individual capacities and resources, relationship with primary caregiver, contextual factors and total resilience; SEQ-C measured academic, social, emotional and total self-efficacy. Two participants from karate group withdrew during intervention. A significant ‘Time x Group’ interaction was detected for all dependent measures (p<0.05) with moderate to large effect size. Significant increases from baseline were found for all scores on the resilience and self-efficacy scales (p <0.05). The results suggest that psychosocial intervention based on Karate may improve the resilience and self-efficacy of youth and make them less likely to engage in aggressive behaviour or be bullied. Thus, Karate should be considered an effective alternative to the anti-bullying failing approach of the institutions.
Impact of Firm Performance on Changes in Strategic Resource Allocation Decisions

We tested the effect of prior firm performance on changes in strategic resource allocation decisions under the environmental conditions of an economic recession. Results from a study of commercial banks suggest that the effect of firm performance on changes in resource allocation in response to environmental change is curvilinear and nonmonotonic. Firms with middlelevel performance, however, tend to respond to changes in the environment with changes in strategic resource allocations, while both poor-performing firms and high performing firms demonstrate little such changes in response to environmental change.
DeepfakeNet, an Efficient Deepfake Detection Method

Different CNNs models do not perform well in deepfake detection in cross datasets. This paper proposes a deepfake detection model called DeepfakeNet, which consists of 20 network layers. It refers to the stacking idea of ResNet and the split-transform-merge idea of Inception to design the network block structure, That is, the block structure of ResNeXt. The study uses some data of FaceForensics++, Kaggle and TIMIT datasets, and data enhancement technology is used to expand the datasets for training and testing models. The experimental results show that, compared with the current mainstream models including VGG19, ResNet101, ResNeXt50, XceptionNet and GoogleNet, in the same dataset and preset parameters, the proposed detection model not only has higher accuracy and lower error rate in cross dataset detection, but also has a significant improvement in performance. Keywords—DeepfakeNet; deepfake detection; data enhancemen t; CNNs; cross dataset
Electrohydrodynamic atomization (EHDA) of high-conductivity pure solvent

ABSTRACT In this study, the effects of flow rate, liquid conductivity and neutralizer strength on the operating and output characteristics are examined for an Electrohydrodynamic atomization (EHDA)-based aerosol generator system, designed and built in our laboratory. Ethylene glycol is used for generating the droplets. It is seen that stable cone-jet mode could be obtained for solvent conductivity as high as 240 μS/cm. While the output number concentration was found to increase with both flow rate and conductivity, the mean particle diameters decreased with increasing conductivity and increased with flow rate. The mean droplet size and output number concentration are found to be about three times more sensitive to changes in conductivity as compared to that of flow rate in the range of 26–150 μS/cm. It is also observed that throughput from the system is strongly dependent on the strength of the charge neutralizer. In the present setup, 8 μCi 241Am bipolar neutralizer in axisymmetric configuration was found to be sufficient to neutralize the generated droplets.