Miracle-dz/UniFAR-FTUs huggingface dataset:
Dimensional latent structure of ICD-11 posttraumatic stress disorder, complex PTSD, and adjustment disorder: Evidence from Ghana, Kenya, and Nigeria.

With the release of ICD-11 in 2018, there has been a surge in studies examining the nosology of mental disorders, including disorders associated with stress, namely, posttraumatic stress disorder (PTSD), complex PTSD (CPTSD), and adjustment disorder (AjD). Few studies have examined the same in lowand middle-income countries that have disproportionate levels of exposure to trauma and stressors and are under-resourced in mental health services. The present study examined the latent factor structure of a joint model comprising PTSD, CPTSD, and AjD symptoms and their association with stressful and traumatic life events to assess the degree of distinctiveness between these disorders. Participants were 2,524 adults in the age range of 18-71 years (M/SDage = 30.44/8.67) from Ghana, (n = 500; 50% female), Kenya (n = 1,006; 49.8% female), and Nigeria (n = 1,018; 50% female). Findings obtained through confirmatory factor analyses indicated that a dimensional and hierarchical secondorder model comprising correlated latent factors of PTSD, DSO, and AjD provided the best goodness-of-fit indices. Furthermore, it was found that stressors were positively associated with AjD and PTSD, and traumatic life events largely with PTSD. Findings support the ICD11 classification of related-although distinct stress-related disorders in adults from three African nations.
Relationship of Related Party Transactions and Earnings Management

This study aimed to examine the relationship between related party transactions and earnings management. The sample of this study was companies listed on the Indonesia Stock Exchange for the 2017 and 2018 period. The result shows that related party transaction (sales and expense) has a negative effect on accrual earnings management. It indicates that firms use related party transactions (sales and expense) as substitutes for earnings management especially accrual earnings management.
Effects of an integrative neuromuscular training protocol vs. FIFA 11+ on sprint, change of direction performance and inter-limb asymmetries in young soccer players

This study compared the effects of integrative neuromuscular training (INT) versus FIFA 11+ protocols on sprint, change of direction performance and inter-limb asymmetries. Thirty young (U-11) male soccer players (age: 11.2 ± 0.7 years; height: 145.6 ± 6.8 cm; body mass: 72.5 ± 3.0 kg) were randomly assigned to each training group, which consisted of two sessions/week for a period of 6-weeks. The INT consisted of play-based tasks designed according to structured training principles, whereas the FIFA 11+ followed standard procedures. Before and after the intervention, 0-20 sprint time and double 180° change of direction test were measured from which change of direction deficit and inter-limb asymmetries were also computed. Significant improvements were found in double 180° change of direction test and deficit for both legs in both groups (all p < 0.01). A significant decrease was observed in 0-20 sprint time (p < 0.05), and inter-limb asymmetries for FIFA 11+ group. A significant group-by-time effect, which favored the FIFA 11+ group, was observed on double 180° change of direction in right leg (F = 15.08, p < 0.01, η 2 p = 0.35), but also in change of direction deficit in right (F = 214.19, p < 0.01, η 2 p = 0.88), and left legs (F = 126.79, p < 0.01, η 2 p = 0.82). These findings suggest youth soccer practitioners should select the FIFA 11+ program to improve inter-limb asymmetries and 0-20 sprint time, and that both training methods are suitable to improve 180° change of direction performance.
Testing power system protections utilizing hardware-in-the-loop simulations on real-time Linux

The complexity of power system phenomena challenges power system protection testing to obtain the required adequacy of the testing environment. Hardware-in-the-loop simulation in real-time substantially increases testing capabilities. However, there is still the question of the availability of commercial solutions. To address the challenges, a new hardware-in-the loop system has been designed and implemented utilizing the easily available Matlab/Simulink environment and Linux RT Preempt OS. The custom software part prepared for the presented system is based on the Matlab/Simulink s-function mechanism, Embedded Coder toolbox and Advantech biodaq library as the interface for the utilized I/O cards. The simulator’s real-time performance limits on Linux RT Preempt have been verified, and it was shown that its performance is sufficient to conduct successful tests of protection relays. Consequently, a simple power system protection relay testing example is provided, including a discussion of results. Finally, it has been proven that the presented system can be utilized as a simpler and more accessible hard-ware-in-the-loop testing alternative to commercial simulators.
Prognostic significance of N-Terminal Pro-BNP in patients with COVID-19 pneumonia without previous history of heart failure

Introduction: The objective of the present research was to evaluate the possible association between the N-terminal pro-brain type natriuretic peptide (NT-proBNP) levels and in-hospital mortality in coronavirus disease 2019 (COVID-19) pneumonia patients who did not have pre-existing heart failure (HF). Methods: A total of 137 consecutive patients without pre-existing HF and hospitalized due to COVID-19 pneumonia were enrolled into the current research. The main outcome of the research was the in-hospital death. The independent parameters linked with the in-hospital death were determined by multivariable analysis. Results: A total of 26 deaths with an in-hospital mortality rate of 18.9% was noted. Those who died were older with an increased frequency of co-morbidities such as hypertension, chronic kidney disease, coronary artery disease, stroke and dementia. They had also increased white blood cell (WBC) counts and had elevated glucose, creatinine, troponin I, and NT-pro-BNP levels but had decreased levels of hemoglobin. By multivariable analysis; age, NT-pro-BNP, WBC, troponin I, and creatinine levels were independently linked with the in-hospital mortality. After ROC evaluation, the ideal value of the NT-pro-BNP to predict the in-hospital mortality was found as 260 ng/L reflecting a sensitivity of 82% and a specificity of 93% (AUC:0.86; 95%CI:0.76-0.97). Conclusion: The current research clearly shows that the NT-proBNP levels are independently linked with the in-hospital mortality rates in subjects with COVID-19 pneumonia and without HF. Thus, we believe that this biomarker can be used as a valuable prognostic parameter in such cases.
THE DEVELOPMENT OF THE IMPLEMENTATION OF SPACE TECHNOLOGIES: A CASE STUDY OF THE FERGANA VALLEY (UZBEKISTAN)

The paper presents an overview of automated methods for interpretation lineament and ring structures from satellite imagery data. The methods are presented to analyze lineament and ring structures in the Fergana Valley (Uzbekistan). As a result of automated processing, it is planned to obtain separate maps of lineament and ring structures, the distribution density of lineaments, spatial orientation of lineament structures, rose-diagrams, etc., which will be entered into the GIS for constructing a thematic map of the distribution of lineament and ring structures in the Fergana Valley.
Phytochemical screening, antimalarial and histopathological studies of Allophylus africanus and Tragia benthamii

[ABSTRACT] The anti-malarial potential of different parts of Allophylus africanus P. Beauv and Tragia benthamii Baker were determined in vivo for suppressive, curative and cytotoxic activities in mice receiving 0.2 mL of a standard inoculum size of 1 × 10 infected erythrocytes of Plasmodium berghei (NK-65) intraperitoneally. The A. africanus extracts suppressed parasitaemia following administration to infected mice by 92.82%−97.81% on day 7 post-infection against 96.81% for chloroquine. The infected extract-treated animals had significantly moderate (P < 0.05) packed cell volume (PCV) compared with the infected, untreated animals. Phytochemical screening revealed a predominance of tannins, saponins, flavonoids and carbohydrates in all parts of A. africanus, and alkaloids instead of flavonoids in the extract of T. benthamii. The results suggest that the extract possesses considerable antimalarial activity. These results support further studies on A. africanus. [KEY WORDS] A. africanus; Tragia benthamii; Plasmodium berghei; Antimalarial; Parasitaemia
Effectiveness of Four Lytic Phages Against Biofilm-Producing and Multidrug-Resistant Escherichia Coli

Multi-drug-resistant (MDR) strains of biofilm-producing Escherichia coli are being reported worldwide and are threatening the health of human beings. These species are seen as the highest priority for the development of new phage biocontrol agents. Therefore, we isolated and characterized new and effective lytic phages as biocontrol agents against MDR E. coli. Bacteriophages (phages) were isolated from different wastewater samples, whilst E. coli strain was isolated from Sausage with accession number MN493640; it was resistant to 66.6% of tested common antibiotics with strong biofilm production. Phages designated ΦEcp1, ΦEcp2, ΦEcp3, ΦEcp4 and they were classified as being in the order Caudovirales, ΦEcp1 and ΦEcp2 belong to families Siphoviridae and Myoviridae respectively while ΦEcp3, ΦEcp4 belonging to family Podoviridae. The four phages and its cocktail showed polyvalent infectivity. All phages are stable at pH values range from 7–9; exhibited remarkable temperature stability (55-65oC). They were stable in different concentrations of sodium chloride and did not lose their infectivity after exposure to Ultraviolet (UV) radiation for 30 min. One-step growth curve analysis showed short latent period (10 min) and large burst sizes (295, 117, 102 .and 127 PFU/mL) for ΦEcp1, ΦEcp2, ΦEcp3, ΦEcp4 respectively. Phages cocktail completely inhibited the growth of MDR E. coli in 8 h in vitro and also significantly (p<0.05) eradicated the development of 24 h old biofilms. This study suggests that these four new phages can be characterized even farther as antimicrobial agents against biofilm-producing MDR E. coli.
Effects of nest boxes on the most important population of red-footed falcon Falco vespertinus in Italy

The red-footed falcon is a near threatened species, which breeds mainly in agricultural landscapes, typically nesting in empty corvid nests on trees. In Europe, this species is declining due to habitat degradation and agriculture intensification. The aim of our study was to determine the reproductive success and the increase in the number of nesting pairs after the installation of nest boxes. This study took place in the Italian province of Parma, the southernmost part of the red-footed falcon’s breeding range. Nest boxes were provided in four locations, where falcons were already breeding in corvid nests, to assess if this action could increase the falcon population and breeding success in the study area. After the deployment of 117 nest boxes from 2010 to 2018 the Parma population increased from 25 to 82 pairs, occupying up to 50% of available boxes in 2018. The breeding success remained unvaried over the study period with an average of 2.06 and 2.37 chicks fledged per pair in corvid nests and nest boxes respectively. It also did not differ between the two nest categories. These results could indicate that a lack of suitable nesting sites is a major limiting factor for the falcon population in the Parma province rather than lack of food.
Facial Action Unit Detection with Convolutional Neural Networks

—We propose a novel deep convolutional neural network architecture to study the problem of action unit detection. We leverage recent gains in large-scale object recognition by formulating the task of predicting the presence of a speciﬁc action unit in a still image as simple image-level binary classiﬁcation. We ﬁrst train a convolutional encoder on the problem of multi-view emotion recognition as a high-level representation of facial expressions. We show that our architecture generalizes across views, ethnicity, gender and age by merging and training jointly on three standard emotion recognition datasets: CK+, Bosphorus and RafD. Our system is the ﬁrst fully multi-view emotion recognizer proposed in the literature. We then extend this shared learned representation with fully-connected layers trained to detect individual action units. Our approach is conceptually simpler and yet signiﬁcantly more accurate than the best methods based on the dominant paradigm for the study of this problem, which relies on facial landmark detection as an intermediate task. We conduct experiments on the BP4D dataset, the largest and most challenging benchmark currently available for action unit detection, and report an absolute improvement of 16% over the previous state-of-the-art.
Cyber Vulnerability Assessment of a Digital Secondary System in an Electrical Substation

— Modern digital secondary system (DSS) technology uses digital communications among relays and remote digital sensors over high-speed fiber connections to perform fault detection and trip circuit control. A cyber vulnerability assessment of each proposed communications design is essential to evaluate the energy control system’s reliability. Many cybersecurity technologies from numerous industries are promoted for use in DSS communications with unknown impacts. This paper introduces appropriate metrics and a cyber vulnerability assessment framework, using the attack tree method, to compare the cyber risk of available technologies to determine the dependability and security of digital control and protective trip circuits.
THE INFLUENCE OF ACCOUNTING KNOWLEDGE IN MODERATING RELATIONSHIP BETWEEN UNDERSTANDING AND SOCIALIZATION OF TAX TO MSMEs TAX COMPLIANCE APRIANI KARTIKA RAHAYU ICUK RANGGA BAWONO (icuk.bawono@unsoed.ac.id) YUDHA ARYO SUDIBYO

This research aims to analyze the understanding and socialization of taxation on tax compliance of MSMEs. This research also aims to analyze the influence of understanding of accounting in moderating the relationship of understanding and socialization of taxation on tax compliance of MSMEs. Samples were determined by the stratified cluster sampling method. The number of respondents is 151 MSMEs owners/managers/actors in sectors of the trade, hotel, and restaurant. This study uses the Structural Equation Model (SEM) to analyze the purposes of this research. Effect size analysis is used to determine how big is the moderation effect from the variable of accounting knowledge. Through path analysis, this research states that taxation understanding and socialization have a significant positive effect on tax compliance of MSMEs. Then, accounting knowledge has a significant and weakening effect on moderating the relationship between taxation understanding and tax compliance of MSMEs. Meanwhile, accounting knowledge has not been proven to moderate the relationship between tax socialization on tax compliance of MSMEs.
A Big Data Analytics System Based on a High Level Query Language Using Apache Spark

Big data analytics is one of the most active research areas today with a lot of challenges, both theoretical and practical. This thesis makes a contribution to the area of big data analytics by implementing the HIFUN language using the Apache Spark framework. HIFUN is a high level query language, proposed for expressing analytic queries over big data sets. This language makes a clear separation between the conceptual and the physical level. An analytic query and its answer are de ned at the conceptual level independently of the nature and location of data. The abstract de nitions are then mapped to lower level evaluation mechanisms, taking into account the nature and location of data, as well as other related aspects. In this thesis, we leverage this language to design and implement a system which allows a user to analyse, visualize and discover information useful for decision making, which is "hidden" in large-scale data sets. In the physical level, HIFUN queries are mapped to lower level evaluation mechanisms of the Apache Spark framework following the conceptual evaluation scheme proposed by HIFUN and supporting a big range of data set formats. In the conceptual level, we apply the query rewriting rules and create query execution plans, proposed by HIFUN. Our work shows that the HIFUN formal model is useful in practice and the experimental evaluation of the system proves that the model's approach to query rewriting and to the generation of query execution plans succeeds in reducing the computational costs regardless of the nature of the data.
The Impact of Ascorbic Acid and Some Additives in the Rheological Properties of Doughs in Pasta from Agimi, Apache and Anchor Wheat

This study is a report about the latest researches in dough technology. Results are valid for Balkan countries. In recent years, a high temperature drying system has been established in high quality pasta production. Continuous increase in pasta production has brought an increase in demand for processed materials such as flour from wheat processing. The production with only flour is not enough to recover the major part of pasta consumption. For this reason new methods to improve the quality of pasta production with Tricitum aestivum flour are being investigated. We have been studying the usage of L-Ascorbic acid in the industrial level experimented in 2 types of pasta where in the first type is used only the wheat with high “glassness” and in the second type is used the flour by soft wheats with extra additives. Before the experiment in the industrial level, prior researches were made in the laboratory of “Miell Tirana” Company in Albania. Here a mixture of flour by soft wheats with extra ascorbic acid and wheats only with high “glassness” are used for the pasta production. These systems facilitate the use of processing techniques using high temperature drying systems. Pasta quality depends on too many factors like water temperature, dough, product itself, added methods of LAA, the first material and working conditions.
Wheat Grain Development’

The pattern of endoproteolytic activities occurring during wheat (Triticum aestivum, cultivar Chinese Spring) grain development was investigated. Total endoprotease activity, assayed in solution with azocasein as a substrate, increased during the early stages of grain development to reach a maximum at 15 d postanthesis that was maintained until the grain was mature. Endoprotease activity was also assayed in gradient polyacrylamide gels co-polymerized with gelatin. The increase in endoproteolytic activity was due to the appearance of up to 18 endoproteolytic bands that were arbitrarily classified into five groups (A, B, C, D, and E). l h e presence of serine, aspartic, metallo, and, to a lesser extent, thiol proteases in developing wheat grains was demonstrated by the use of class-specific protease inhibitors. lhe appearance of the different classes of endoproteases during seed development was subject to temporal control; serine proteases were more abundant at early stages and aspartic and metallo proteases were more abundant at later stages. At intermediate stages of development (1 5-20 d postanthesis), most of the endoproteases were localized in the aleurone, testa, and embryo. l h e content of acidic thiol proteases was low in the developing starchy endosperm.
Factors Associated with Personal Protective Measures Utilization among Community Dwelling Older Adults during COVID-19 Pandemic in Alexandria , Egypt

Introduction: The world’s population is aging. Elderly faces various physiological and pathological changes make them at higher risk to be infected with COVID-19 and to suffer more from its complications. Therefore, this study aimed to identify the factors associated with personal protective measures utilization among community dwelling older adults during COVID-19 Pandemic in Alexandria, Egypt. Setting: The study was conducted at El-Wafaa club in Mohram Bec, which is affiliated to the Ministry of Social Solidarity in Alexandria, Egypt. Subjects: 190 eligible older adult participants, have neither cognitive impairment nor depression, able to read and write and have access to the internet. Tools: three tools were applied for data collection. Results: This study revealed that more than one third of the studied elderly had fair practice level toward COVID prevention (36.8 %), all the studied elderly had unsatisfactory level regrading social distancing, more than one half (56.8 %) of the studied elderly had negative attitude toward Covid-19, and more one half (55.8%) of the study subjects had good knowledge level. Conclusion: This study concluded that, the study elders have personal, psychological, and environmental factors that hinder their utilization of the protective measures against COVID-19, and the level of practices is affected significantly by sex, different educational level, and living alone or with others, (P = 0.010, 0.045, 0.005 respectively). Recommendations: The current study recommended designing of interventions targeted at improving older adults’ practices , knowledge and attitudes regarding coronavirus and the usage of its preventive measures .
University of Birmingham Dense connection and depthwise separable convolution based CNN for polarimetric SAR image classification

—Convolution neural networks (CNN) have achieved great success in natural image processing where large amounts of training data are available. However, for the polarimetric synthetic aperture radar (PolSAR) image classification problem, the number of labeled training samples is typically limited. To improve the performance of CNN on limited training data, we propose a new network, the densely connected and depthwise separable convolutional neural network (DSNet). According to characteristics of PolSAR data, DSNet uses depthwise separable convolution to replace standard convolution, to independently extract features over each channel in PolSAR images. DSNet also introduces dense connections to directly connect non-adjacent layers. With the depthwise separable convolution and dense connections, DSNet can avoid extracting redundant features, reuse the hierarchical feature maps of PolSAR images and reduce the number of training parameters. Compared with normal CNN, DSNet is more lightweight and its training parameters decrease to less than 1/9. We compare DSNet against several popular algorithms on three different data sets, and show that DSNet achieves better results while using less training samples.
Applying AHP in Evaluation the Distribution Science of Suppliers for Retails in Vietnam: Case of Saigon Co-op Mart

Purpose: Retailing is a very special sector because it demonstrates the effectiveness of combined products and services to create business values. In this study, the author wants to investigate particular areas in the distribution sciences of the purchasing process in Coopmart (Saigon Coop-Vietnam), which is about sauces and seasoning. Research design, data and methodology: The data were collected by experts of Saigon coop, which first went through the Delphi method to choose criteria and sub-criteria for the Analytic Hierarchical Process (AHP). Results: After a long process of calculation based on AHP, the final supplier is chosen according to experts‟ interview; Masan is the most potential candidate to be the main supplier of sauces and seasoning to Coop mart. Therefore, it is necessary to apply the typical methods such as quantitative analysis of this process AHP. With the aim of increasing the computational content of the evaluation process suppliers, especially the comparison of suppliers in the same industry as AHP has shown. This enables analyses of all the providers to be more scientific. Conclusions: Thus, this paper would help the facility managers ensure objectives to the reasonable decision, which can be based on AHP to get more information, implement plans and get strategic collaboration with