bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative toxicity study of aqueous, ethanol and methanol leaf extracts of Simarouba glauca on hematological indices in adult normotensive male Wistar rats
Authors: Osagie-Eweka SammyDavies E. , Orhue Noghayin E.J. , Moke Emuesiri G. , Omogbai Eric K.I.
Published: February 2023

Background
The study focused on the toxicological evaluation of leaf extracts of S. glauca on some hematological indices of male Wistar rats.
Methods
Thirty (30) male Wistar rats were divided into ten groups of three rats each. Test rats were given AESG, EESG or MESG at doses of 500, 1000 and 2000 mg/kg body weight respectively; the control group was provided with food and water ad libitum daily for thirty (30) days. At the end of the study, the fasted rats were sacrificed and haematological assessment was conducted.
Results
The data obtained indicates elevated (P ˂ 0.05) RBC levels of experimental rat administered EESG and MESG at 500, 1000 and 2000 mg respectively. Reduced (P ˂ 0.05) haemoglobin concentration at AESG and MESG 500 mg, AESG, EESG and MESG 1000 mg; EESG 2000 mg. The haematocrit/PCV levels where only slightly reduced (P ˂ 0.05) and elevated (P ˂ 0.05) at EESG 1000 and 2000 mg respectively. Platelets count was elevated (P ˂ 0.05) at MESG 500 mg, lowered at AESG 1000 mg and EESG 2000 mg. The WBC count was elevated (P ˂ 0.05) at AESG and EESG 1000 mg; elevated (P ˂ 0.05) at EESG and MESG 2000 mg. The lymphocytes count was elevated (P ˂ 0.05) at EESG 500, 1000 & 2000 mg; at AESG 1000 mg. The monocytes count was elevated (P ˂ 0.05) at AESG 500, 1000 & 2000 mg, elevated (P ˂ 0.05) AESG and EESG 1000 & 2000 mg respectively, and elevated (P ˂ 0.05) at MESG 2000 mg.
Conclusion
Oral administration of leaf extracts of S. glauca, especially at higher doses elicit disturbances in haematological indices.
Psychometric Properties of Maslach Burnout Inventory-EFL (MBI-EFL) among Foreign Language Students of Pakistan
Authors: Tian Mao , Mohsin Muhammad , Ashraf Rabbia
Published: February 2023

Students participate in and manage structured activities like attending classes, doing projects by the deadline, and taking tests. The goal-oriented nature of these activities might make students anxious, stressed, and exhausted, demanding the use of coping mechanisms on their behalf to maintain their learning thus, experiencing academic burnout. Particularly in Pakistan, where students' admittance to institutions or prospects are determined by intensely competitive, high-stakes exams This study was intended to explore the psychometric properties of the modified 10- item Maslach Burnout Inventory-EFL Student survey among (N = 1750) foreign language students of Pakistan. A cross-sectional validation survey design was used in the current study. A modified version of the Maslach Burnout Inventory-Student Survey (MBI-SS) was designed and assessed in 1718 Pakistani students in China. Based on the findings of several reliability and validity tests, a final 10-item Maslach Burnout Inventory-EFL Student Survey was created to meet the context of learning English as a foreign language (EFL). CFA extracted three factors comprising Reduced Efficacy, Cynicism, and Exhaustion, demonstrating the MBI-original SS's tri-factorial structure's invariance. The Cronbach's alphas for Exhaustion, Cynicism, and Reduced Efficacy were 0.78, 0.82, and 0.86, respectively, demonstrating good internal consistency reliability for the subscales. Pearson coefficients between 10 items and the scale varied from 0.55–0.81. An acceptable model fit (χ2 = 345.23, RMSEA = 0.05, TLI = 0.92, GFI = 0.93, SRMR = 0.03) was achieved. Thus, results demonstrate adequate validity and reliability of MBI-EFL student survey for measuring burnout among English as a foreign language student.
Approximation algorithms for covering vertices by long paths
Authors: Gong Mingyang , Edgar Brett , Fan Jing , Lin Guohui , Miyano Eiji
Published: February 2023

Given a graph, the general problem to cover the maximum number of vertices by a collection of vertex-disjoint long paths seemingly escapes from the literature. A path containing at least k vertices is considered long. When k ≤ 3, the problem is polynomial time solvable; when k is the total number of vertices, the problem reduces to the Hamiltonian path problem, which is NP-complete. For a fixed k ≥ 4, the problem is NP-hard and the best known approximation algorithm for the weighted set packing problem implies a k-approximation algorithm. To the best of our knowledge, there is no approximation algorithm directly designed for the general problem; when k = 4, the problem admits a 4-approximation algorithm which was presented recently. We propose the first (0.4394k +O(1))-approximation algorithm for the general problem and an improved 2-approximation algorithm when k = 4. Both algorithms are based on local improvement, and their theoretical performance analyses are done via amortization and their practical performance is examined through simulation studies.
2012 ACM Subject Classi cation Theory of computation ! Packing and covering problems
Enhanced visual multi-modal fusion framework for dense video captioning
Authors: Zhong Ruizhe , Zhang Qingchuan , Zuo Min
Published: February 2023

Dense video captioning is a machine translation task that aims to localize events from full video and describe them separately. Human observers who parse the video are also impressed by frames containing a high amount of information and duplication, but video often appears unrelated frames in the subject. However, existing works have largely ignored these details. To fully incorporate human visual perception into the process of understanding video, we propose an enhanced visual multi-modal fusion framework (Evmff), which utilizes the captions of video keyframes to improve dense video captioning performance. We first extract video keyframes through time stamps and then apply the recently proposed image captioning method DLCT to obtain a temporally aligned caption of the keyframe. Evmff fuses the textual information of speech, the caption of image keyframes, video features, and audio features, applying transformer architecture to convert the data into text descriptions. The performance of our model is verified using the ActivityNet Captions dataset with four different indicators, Bleu@N, METEOR, Rouge_L, and CIDEr-D. Ablation experiments show that employing the video keyframe description as the input of the multi-modal model compensates for the deficiency in visual information understanding. Our code will be released.
Effects of Savings on Depressive Symptoms among Homeless People in Korea: Using Propensity Score Matching
Authors: Choi Jungtae , Han Chang-Keun , Kang Sion
Published: February 2023

OBJECTIVE:In Korea, the financial crisis that occurred in 1997 increased the homeless population. Since then, mental health issues, particularly depressive symptoms, among the homeless have become a substantial social issue. Prior research documented that asset ownership positively influenced people’s mental health. However, the largely under-researched area is whether asset accumulation has an impact on depressive symptoms along with homeless persons.METHODS:This study investigates the relationship between the saving status and depressive symptoms of homeless people using the 2016 National Survey on Homeless People. To reduce the selection bias, this study employed the propensity score matching method. Further, multivariate logistic regression was performed to determine how the savings level affected depressive symptoms.RESULTS:This study found a negative relationship between the savings level and depressive symptoms after controlling for covariates.CONCLUSION:Our findings suggest that an asset-based policy targeting the homeless may play a crucial role in reducing depressive symptoms and facilitating their self-reliance.
Offline Kurdish Character Handwritten Recognition (OKCHR) Using CNN With Various Preprocessing Techniques
Authors: Majeed Hamssa D. , Nariman Goran Saman
Published: February 2023

Offline optical-character-recognition is considered part of the significant pattern-recognition applications. Handwriting recognition though is an active and challenging area of research in this field. Nowadays, many algorithms are introduced with the aim of achieving the highest accuracy. To achieve a better recognition result, the input character images must have good quality. That is why the preprocessing step becomes essential for any image identification task. As for the classification phase, some researchers focused their research on the utilization of CNN (Convolutional Neural Networks). CNN algorithm is equipped with various learning architectures, enabling researchers to choose the most effective architecture for classification. However, this study suggests that the preprocessing mechanism is also another important factor that should be considered in order to increase the accuracy of classification. This study utilized seven stages for preprocessing mechanisms applied to the selected dataset and the measurement of the accuracy as the result of the utilization of the CNN for the classification was acquired. The study exposed that the utilization of using preprocessing steps indicated the most heightened accuracy with Barbarized-KDS as an input achieving training, testing, and validation accuracy of 0.992, 0.97, and 0.972 respectively after only 35 iterations. Furthermore, another significant finding is that using different steps in the processing of input images to trian the recognition model affects the recognition-rate within the same classifiers. Besides, the outcome reveals that each technique applied with the specific classifier may require a certain preprocess to obtain its optimal accuracy recognition rate.
Water, climate change and uncertainty in the Great Lakes and Rio Grande/Bravo Regions
Authors: Bassone-Quashie Yena , VanNijnatten Debora , Johns Carolyn
Published: February 2023

Uncertainty is inherent in transboundary water governance, yet climate change is deepening the uncertainties faced by those who manage shared water resources. This paper identifies and assesses uncertainties in the transboundary water governance context by applying an analytical framework which integrates insights from the uncertainty, adaptive governance, and public policy literatures to analyze policy documents in two complex transboundary cases: the Great Lakes and Rio Grande/Bravo basins. Findings from the analysis indicate that: first, deep uncertainties exist in both cases but the two basins face different combinations of, and interactions between, uncertainties; second, the system of scarcity assessed in this analysis (the Rio Grande/Bravo Basin) indicates more conflict-based uncertainties which aggravate natural and technical system uncertainties; and third, the governance system itself is a significant source of uncertainty, or exacerbates existing uncertainties, in both basins. The case studies reveal that governance systems need to focus on different sources, types and levels of uncertainty, and that policy responses need to be designed to move to a ‘monitor-and-adapt’ governance approach to reflect different uncertainties across systems of abundance and scarcity. An analysis of the preparedness of governance systems to respond and adapt to uncertainties is also needed and highly recommended.
A survey on applications of machine learning algorithms in water quality assessment and water supply and management
Authors: Oğuz Abdulhalık , Ertuğrul Ömer Faruk
Published: February 2023

Managing water resources and determining the quality of surface and groundwater is one of the most significant issues fundamental to human and societal well-being. The process of maintaining water quality and managing water resources well involves complications due to human-induced errors. Therefore, applications that facilitate and enhance these processes have gained importance. In recent years, machine learning techniques have been applied successfully in the preservation of water quality and the management and planning of water resources. Water researchers have effectively used these techniques to integrate them into public management systems. In this study, data sources, pre-processing, and machine learning methods used in water research are briefly mentioned, and algorithms are categorized. Then, a general summary of the literature is presented on water quality determination and applications in water resources management. Lastly, the study was detailed using machine learning investigations on two publicly shared datasets.
Kierkegaard e a transformação do sujeito em si mesmo entre a vertigem da liberdade e o paradoxo absoluto da fé
Authors: Mariano da Rosa Luiz Carlos
Published: February 2023

Atribuindo à ironia a possibilidade de exercício e desenvolvimento da liberdade subjetiva, Kierkegaard sublinha a negatividade absoluta como característica do referido processo em Sócrates, convergindo para assinalar o absoluto e irredutível valor do indivíduo em um movimento que implica o início absoluto da vida pessoal entre criar-se (poeticamente) e deixar-se criar (poeticamente). Dessa forma, contrapondo-se à dissolução da existência humana nas fronteiras da pura conceituação intelectual, Kierkegaard assinala a tensão inaplacável entre existência e transcendência em um movimento que implica a interioridade e guarda correspondência com a necessidade de tornar-se subjetivo, tendo em vista a perspectiva que defende que a verdade consiste na transformação do sujeito em si mesmo entre a vertigem da liberdade e o paradoxo da fé em um processo que encerra angústia e desespero e converge para a transição do ético ao religioso.
Applying conditional optimization to determine the allowable loads on flexurally rigid threads
Authors: Tarasov D. A.
Published: February 2023

Objective.Development of a methodology for determining the allowable loads on existing structural elements, the design model of which is a flexural-rigid thread, based on the requirements of strength and rigidity due to the changed operating conditions of structures.

Method.This study is based on mathematical modeling of the problem of conditional optimization. The objective function is the total potential energy of deformation of a thread with some flexural rigidity. In this case, restrictions are imposed on strength, rigidity, and the condition of continuity of deformations. At the same time, to achieve this goal, the provisions of the strength of materials, as well as the apparatus of integral and differential calculation of functions of one or more variables, were used.

Result.An assessment of the adequacy of the results obtained using the developed methodology was carried out. A numerical experiment was performed to determine the value of the allowable uniformly distributed load and the corresponding distribution of stresses and strains along the length of a thread of finite stiffness with given physical and geometric parameters. It has been established that the discrepancies in the values of the results obtained using the proposed modeling technology and the commercial computer-aided design and calculation system LIRA 10.8, implemented on the generally recognized finite element method, are no more than 5%.

Conclusion.The developed technique allows setting and solving problems of determining the ultimate loads on flexural-rigid threads, based on the allowable stresses and strains, in contrast to existing commercial computer simulation systems that solve exclusively direct problems of determining the stress-strain state of various types of structures. It can be used at the stage of inspection of large-span coatings in the reconstruction of public buildings and engineering structures.
Protection against attacks using social engineering tools and methods
Authors: Repenko V. A. , Reznichenko S. A.
Published: February 2023

Objective.  In the modern world, innovative technologies are actively developing, communications are moving into the Internet space. Nevertheless, new technologies turned out to be in demand in the segment of organizations, individuals, cyber fraudsters and hackers. The purpose of the study is to analyze the essence and structure of modern social engineering, including reverse social engineering in the context of the digitalization of society.

Method. Adapting the study to the current moment, it is clarified that technologies, developments and manipulative sociological tactics are picked up not just by hackers, but also by followers of radical ideas.

Result. The optimal definition of the term "social engineering" is proposed - the identification and exploitation of incompetence, insufficient professional level or negligence of employees of an organization or individuals to obtain unauthorized access to confidential data; a set of technologies based on the use of the psychological specifics of a person.

Conclusion. The novelty of the study lies in an in-depth study of the classification of types of attacks using social engineering methods and recommendations for countering and preventing them.
Methods for obtaining polarized xenon for magnetic resonance imaging. Review
Authors: Grigoriev G Y  , Lagutin A S
Published: February 2023

A review of experimental studies and design developments of devices for obtaining nuclear-spin hyperpolarized 129Xe by optical pumping of rubidium vapor with subsequent spin exchange with noble gas isotope atoms is presented. Hyperpolarized 129Xe atom is an excellent probe in magnetic resonance imaging in studies of lung structure and function, and biomarkers based on it are applicable for the diagnosis of a wide range of both pulmonary and other diseases. The principles of operation, advantages and disadvantages of polarizer design options are outlined. The main attention is paid to new approaches and technical solutions that determine the trends in the development of the methodology. Keywords: hyperpolarized xenon, lasers, optical pumping, nuclear magnetic resonance, magnetic resonance imaging.
Radiation from a Moving Bunch of Particles with a Variable Charge
Authors: Tyukhtin A.V.  , Fan X.
Published: February 2023

We study the electromagnetic radiation of a charged particle bunch with small size moving at a constant velocity and having a variable charge. The environment medium is considered to be isotropic and homogeneous, and it may have frequency dispersion, but not spatial dispersion. The general solution of the problem is obtained. The main attention is paid to the case when the bunch charge, starting from a certain moment, decreases exponentially with time. The saddle point method is used to obtain the approximate expressions for the field components that are valid in the wave zone. The energy characteristics of the excited spherical wave are studied and compared with the case of a decelerating charge. In the case of excitation of Vavilov-Cherenkov radiation, we obtain the asymptotics which are valid in the entire wave zone, including the region in which the field cannot be divided into the spherical and cylindrical waves. Keywords: Charged particle bunch, spherical wave, cylindrical wave, Vavilov-Cherenkov radiation.
The Impact of Social Media Interventions on Weight Reduction and Physical Activity Improvement Among Healthy Adults: Systematic Review
Authors: Shiyab Wa'ed , Halcomb Elizabeth , Rolls Kaye , Ferguson Caleb
Published: February 2023

Background

A sedentary lifestyle and being overweight or obese are well-established cardiovascular risk factors and contribute substantially to the global burden of disease. Changing such behavior is complex and requires support. Social media interventions show promise in supporting health behavior change, but their impact is unclear. Moreover, previous reviews have reported contradictory evidence regarding the relationship between engagement with social media interventions and the efficacy of these interventions.

Objective

This review aimed to critically synthesize available evidence regarding the impact of social media interventions on physical activity and weight among healthy adults. In addition, this review examined the effect of engagement with social media interventions on their efficacy.

Methods

CINAHL and MEDLINE were searched for relevant randomized trials that were conducted to investigate the impact of social media interventions on weight and physical activity and were published between 2011 and 2021 in the English language. Studies were included if the intervention used social media tools that provided explicit interactions between the participants. Studies were excluded if the intervention was passively delivered through an app website or if the participants had a known chronic disease. Eligible studies were appraised for quality and synthesized using narrative synthesis.

Results

A total of 17 papers reporting 16 studies from 4 countries, with 7372 participants, were identified. Overall, 56% (9/16) of studies explored the effect of social media interventions on physical activity; 38% (6/16) of studies investigated weight reduction; and 6% (1/16) of studies assessed the effect on both physical activity and weight reduction. Evidence of the effects of social media interventions on physical activity and weight loss was mixed across the included studies. There were no standard metrics for measuring engagement with social media, and the relationship between participant engagement with the intervention and subsequent behavior change was also mixed. Although 35% (6/16) of studies reported that engagement was not a predictor of behavior change, engagement with social media interventions was found to be related to behavior change in 29% (5/16) of studies.

Conclusions

Despite the promise of social media interventions, evidence regarding their effectiveness is mixed. Further robust studies are needed to elucidate the components of social media interventions that lead to successful behavior change. Furthermore, the effect of engagement with social media interventions on behavior change needs to be clearly understood.

Trial Registration

PROSPERO International Prospective Register of Systematic Reviews CRD42022311430; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=311430
Perceived Risk of Diabetes Among Vietnamese Americans With Prediabetes: Mixed Methods Study
Authors: Nguyen Angelina , McEwen Marylyn Morris , Loescher Lois J
Published: February 2023

Background

Vietnamese Americans have a relatively high risk of developing diabetes at younger ages, yet there are no published studies exploring their risk perceptions.

Objective

This mixed methods study describes perceived diabetes risk in the context of an underserved population.

Methods

This study was guided by the Common-Sense Model of Self-Regulation. Snowball sampling was used to recruit 10 Vietnamese Americans with prediabetes and achieve data saturation. Qualitative and quantitative descriptive methodologies with data transformation were used to analyze data from semistructured interviews and questionnaires to explore the dimensions of perceived diabetes risk.

Results

Participants were between the ages of 30 and 75 years with diversity also noted in diabetes risk factors. The 3 risk perception domains from qualitative data were risk factors, disease severity, and preventing diabetes. The main perceived diabetes risk factors were eating habits (including cultural influences), sedentary lifestyle, and family history of diabetes. Quantitative data supported qualitative findings of a low-to-moderate level of perceived diabetes risk. Despite the lower levels of perceived diabetes risk, Vietnamese Americans do believe that the severity of diabetes is a “big concern.”

Conclusions

Vietnamese Americans with prediabetes have a low-to-moderate level of perceived diabetes risk. Understanding the perceived diabetes risk in this population provides a foundation for diabetes prevention interventions that consider cultural influences on diet and exercise.
Evolving Face Mask Guidance During a Pandemic and Potential Harm to Public Perception: Infodemiology Study of Sentiment and Emotion on Twitter
Authors: Ramjee Divya , Pollack Catherine C , Charpignon Marie-Laure , Gupta Shagun , Rivera Jessica Malaty , El Hayek Ghinwa , Dunn Adam G , Desai Angel N , Majumder Maimuna S
Published: February 2023

Background

Throughout the COVID-19 pandemic, US Centers for Disease Control and Prevention policies on face mask use fluctuated. Understanding how public health communications evolve around key policy decisions may inform future decisions on preventative measures by aiding the design of communication strategies (eg, wording, timing, and channel) that ensure rapid dissemination and maximize both widespread adoption and sustained adherence.

Objective

We aimed to assess how sentiment on masks evolved surrounding 2 changes to mask guidelines: (1) the recommendation for mask use on April 3, 2020, and (2) the relaxation of mask use on May 13, 2021.

Methods

We applied an interrupted time series method to US Twitter data surrounding each guideline change. Outcomes were changes in the (1) proportion of positive, negative, and neutral tweets and (2) number of words within a tweet tagged with a given emotion (eg, trust). Results were compared to COVID-19 Twitter data without mask keywords for the same period.

Results

There were fewer neutral mask-related tweets in 2020 (β=–3.94 percentage points, 95% CI –4.68 to –3.21; P<.001) and 2021 (β=–8.74, 95% CI –9.31 to –8.17; P<.001). Following the April 3 recommendation (β=.51, 95% CI .43-.59; P<.001) and May 13 relaxation (β=3.43, 95% CI 1.61-5.26; P<.001), the percent of negative mask-related tweets increased. The quantity of trust-related terms decreased following the policy change on April 3 (β=–.004, 95% CI –.004 to –.003; P<.001) and May 13 (β=–.001, 95% CI –.002 to 0; P=.008).

Conclusions

The US Twitter population responded negatively and with less trust following guideline shifts related to masking, regardless of whether the guidelines recommended or relaxed mask usage. Federal agencies should ensure that changes in public health recommendations are communicated concisely and rapidly.
Data-Efficient Computational Pathology Platform for Faster and Cheaper Breast Cancer Subtype Identifications: Development of a Deep Learning Model (Preprint)
Authors: Bae Kideog , Jeon Young Seok , Hwangbo Yul , Yoo Chong Woo , Han Nayoung , Feng Mengling
Published: February 2023

BACKGROUND

Breast cancer subtyping is a crucial step in determining therapeutic options, but the molecular examination based on immunohistochemical staining is expensive and time-consuming. Deep learning opens up the possibility to predict the subtypes based on the morphological information from hematoxylin and eosin staining, a much cheaper and faster alternative. However, training the predictive model conventionally requires a large number of histology images, which is challenging to collect by a single institute.

OBJECTIVE

We aimed to develop a data-efficient computational pathology platform, 3DHistoNet, which is capable of learning from z-stacked histology images to accurately predict breast cancer subtypes with a small sample size.

METHODS

We retrospectively examined 401 cases of patients with primary breast carcinoma diagnosed between 2018 and 2020 at the Department of Pathology, National Cancer Center, South Korea. Pathology slides of the patients with breast carcinoma were prepared according to the standard protocols. Age, gender, histologic grade, hormone receptor (estrogen receptor [ER], progesterone receptor [PR], and androgen receptor [AR]) status, erb-B2 receptor tyrosine kinase 2 (HER2) status, and Ki-67 index were evaluated by reviewing medical charts and pathological records.

RESULTS

The area under the receiver operating characteristic curve and decision curve were analyzed to evaluate the performance of our 3DHistoNet platform for predicting the ER, PR, AR, HER2, and Ki67 subtype biomarkers with 5-fold cross-validation. We demonstrated that 3DHistoNet can predict all clinically important biomarkers (ER, PR, AR, HER2, and Ki67) with performance exceeding the conventional multiple instance learning models by a considerable margin (area under the receiver operating characteristic curve: 0.75-0.91 vs 0.67-0.8). We further showed that our z-stack histology scanning method can make up for insufficient training data sets without any additional cost incurred. Finally, 3DHistoNet offered an additional capability to generate attention maps that reveal correlations between Ki67 and histomorphological features, which renders the hematoxylin and eosin image in higher fidelity to the pathologist.

CONCLUSIONS

Our stand-alone, data-efficient pathology platform that can both generate z-stacked images and predict key biomarkers is an appealing tool for breast cancer diagnosis. Its development would encourage morphology-based diagnosis, which is faster, cheaper, and less error-prone compared to the protein quantification method based on immunohistochemical staining.
Modeling Suicidality with Multimodal Impulsivity Characterization in Participants with Mental Health Disorder (Preprint)
Authors: Moukaddam Nidal , Lamichhane Bishal , Salas Ramiro , Goodman Wayne , Sabharwal Ashutosh
Published: February 2023

BACKGROUND

Suicide is one of the leading causes of death across different age groups. Impulsivity, the tendency to act on urges with low temporal latency and little forethought to the consequences of one's actions, is implicated in several clinical conditions including suicidality. Impulsivity can make a difference in the persistence of suicidal ideation and the progression of suicidal ideations to action. Currently, there are no validated markers for intent to act in suicidality and no objective measures that allow the prediction of suicidality possibly leading to suicide attempts. Impulsivity quantification could be the missing link in risk assessments of ideation-to-action suicidality frameworks.

OBJECTIVE

We aimed to assess the impulsivity differences in participant groups with different suicidality and develop a suicidality prediction model using multimodal impulsivity measures.

METHODS

We obtained questionnaires, behavioral tests, heart rate variability (HRV), and resting state fMRI (rsfMRI) measurements from a cohort of 34 well-characterized participants with mood disorders. The participants were categorized into three groups based on the suicidality stratification from their Mini International Neuropsychiatric Interview (MINI): none, low, and moderate-severe. Group differences in impulsivity and a suicidality prediction classifier using different impulsivity measures were investigated.

RESULTS

Questionnaire-based impulsivity measures, particularly the motor and attentional impulsivity, were significantly different between the suicidality groups with higher subscales of impulsivity associated with higher suicidality. HRV-based impulsivity measures were also significantly different between the groups. A multimodal system to characterize impulsivity outperformed the unimodal system in the three-class suicidality group prediction task, resulting in a classification accuracy of 96.77% when using all objective impulsivity measures.

CONCLUSIONS

Our work is the first reported attempt to elucidate the relative sensitivity of different impulsivity measures in relation to suicidality and employ multimodal impulsivity markers to predict suicidality. Impulsivity quantification could differentiate participants with suicidality and predict suicidality with high accuracy using a multimodal characterization. Suicidality prediction could potentially help tailor mental health interventions for an at-risk individual while the impulsivity characterization for suicidality prediction could be additionally helpful to deter progression from suicidal thoughts to acts of self-harm.
Difficulties in diagnosing gastrointestinal allergy in paediatric practice: a clinical case
Authors: Kryuchko T.O. , Bubyr L.M. , Poda O.A. , Nesina I.M. , Kovalenko L.A. , Matiazh D.S.
Published: February 2023

Since allergy pathology in the structure of general somatic diseases occupies a significant niche in both adult and child populations and is accompanied by a number of unresolved issues, it represents a major medical and social problem. The use of modern diagnostic techniques has made it possible to broaden scientists’ knowledge of the in-depth mechanisms of the pathogenesis of allergic diseases with the subsequent development and implementation of new diagnostic, therapeutic and prophylactic recommendations. However, the multidisciplinary aspects of paediatric allergy continue to be studied; among them, the problems of specific diagnosis of food allergy are of particular importance. Recently, the study of allergic lesions in the various parts of the gastrointestinal tract has received increasing attention in paediatric practice. Since in most cases the mucosa of the digestive system is the first to contact with allergens of various nature, the gastrointestinal form ranks second in the overall structure of clinical symptoms of food allergy. Gastrointestinal symptoms of food allergy are characterized by polymorphic manifestations, making timely verification of the diagnosis difficult. This leads to prolonged differential analysis and requires the exclusion of concomitant organic and functional gastrointestinal pathology, which delays early diagnosis and timely therapeutic recommendations for patients with food allergy. The relevance of the above-mentioned problem is highlighted by the following clinical case.
FINANCIAL SECTOR DEVELOPMENT AND REAL SECTOR GROWTH – ASSOCIATION, SPILLOVER AND CAUSALITY DURING PRE COVID AND COVID REGIMES
Authors: Chaudhuri Tamal Datta , Ghosh Indranil
Published: February 2023

In this paper, we propose an alternative approach to understanding the relationship between financial sector development and real sector growth in India. We use stock market sectoral indices available on National Stock Exchange (NSE) like Capital Goods Index, FMCG Index, Energy Index, Infra Index, Metal Index, Realty Index, and Auto Index to represent the real sector. To represent the financial sector, we consider Bank Index and Financial Services Index separately. The proposed framework examines the relationships at a granular level to understand the extent of association, spillover, and causality. We also analyze the relationship between the financial sector and the real sector in Pre COVID and COVID periods separately. Our research methodology includes the use of Detrended Cross-Correlation Analysis (DCCA), Wavelet Multiple Correlation (WMC), Wavelet Multiple Cross Correlation (WMCC), Diebold-Yilmaz spillover Framework, and Non-Linear Causality Test. Our granular approach has enabled us to examine the relationships in different periods and we observe that the results change. The intensity of the relationships also is different during the COVID period as compared to Pre COVID period.
CHANGES IN FISCAL DEFICIT AND PUBLIC DEBT OF THE REPUBLIC OF SERBIA DURING THE COVID-19 PANDEMIC PERIOD
Authors: Milovanović Goran , Radisavljević Goran , Milanović Sandra
Published: February 2023

The aim of this paper is to consider the nature of changes in the fiscal deficit and public debt of the Republic of Serbia and propose measures to reduce them, based on the analysis of selected statistical and academic sources. The fiscal deficit and the public debt of the Republic of Serbia constitute the subject determination of the paper. After presenting certain effects of the COVID-19 pandemic, the authors investigate: the causes of the change in the fiscal deficit and public debt of the Republic of Serbia; the impact of the COVID-19 crisis on the fiscal deficit and public debt of the Republic of Serbia; and the activity of the government in terms of reducing the fiscal deficit and public debt of the Republic of Serbia. The knowledge that is the result of this research should: contribute to the improvement of fiscal discipline; enable the determination of factors that make public debt and GDP growth sustainable taking into account fiscal constraints and risks.
THE IMPACT OF DEMOGRAPHIC DIFFERENCES ON EMPLOYEE SATISFACTION WITH BENEFITS AND PERKS: EVIDENCE FROM SERBIAN FINANCIAL SECTOR
Authors: Lazarević Anđela , Marinović Matović Ivana
Published: February 2023

After the downfall of socialist regimes, human resource management systems in transition countries like Serbia were transformed, establishing entirely new employee compensation system. In this paper, the most common benefits and perks in the Serbian financial sector, as well as their significance for the employee satisfaction are explored, with the focus on the effectiveness of its structure. The investigation of differences in impact of benefits and perks on employee satisfaction is performed with respect to gender, education, age, and job position of the respondents. The empirical research is conducted by a survey questionnaire. Results suggest that there are no differences in employee satisfaction between respondents of different genders, and education, while partial differences in employee satisfaction are confirmed with respect to age, and job position. The results indicate that benefits and perks in Serbian financial sector should be better structured, and provide guidelines for the investigation of more favorable total compensation package.
CARBON ACCOUNTING IN THE PUBLIC SECTOR – CHALLENGES, APPROACHES AND PERSPECTIVES FOR MUNICIPALITIES
Authors: Stojanović-Blab Maja , Lutter Milena , Blab Daniel
Published: February 2023

Nowadays, combating climate change and its effects due to the anthropogenic greenhouse effect is one of the central challenges for society and politics in order to prevent  further increase of greenhouse gases in the atmosphere and thus become climate neutral. An indispensable prerequisite for the selection, implementation and monitoring of the effectiveness of measures to reduce greenhouse gas emissions is the measurement and accounting of emissions through the implementation of a carbon accounting system. Compared to companies, the topic of carbon accounting at the municipality level has so far received less public attention. Therefore, this paper deals with the specific challenges, the approaches and the perspectives of municipal carbon accounting.
Virtual tour-based digital batik village as a place for promotion of Bekasi city batik in the industry 4.0 era: Study on batik tiara
Authors: Sudjatmoko Agung , Sari Azani Cempaka , Maryani M.
Published: February 2023

The development of digital technology and virtual reality has also given birth to virtual tourism innovations that impact improving the community's economy through training. This program is carried out to create virtual tourist villages, mainly based on virtual batik tourism so that batik artisans have more time to promote their products and the tourist aspect. The virtual tour-based batik village aims to make the batik artisan community more active in utilizing digital application platforms to market their products and produce practical marketing applications. This digital application makes it easier for buyers to find out the promotions being carried out by Bekasi batik by utilizing gadgets and taking advantage of the digital world. The training method uses a case study approach, discussion, and lecture and ends with a training evaluation. The results of the study are based on the review of the user experience of Bekasi city batik artisans; out of 50 respondents, it is found that 55% strongly agree that training materials and virtual tour systems that are socialized are easy to access, can develop digital village web-based virtual tours as well as a forum for urban batik promotion Bekasi. In the aspect of the desired goals of the Bekasi city batik artisans participants, out of 50 respondents, the result was that 65% strongly agreed that the learning objectives of the training and virtual tour system met the expectations of the respondents. It is the hope of the training participants that the problem of marketing the virtual tour system will be a solution to expand the marketing of batik in the City of Bekasi.
PELATIHAN PENGGUNAAN VIRTUAL REALITY DALAM PENGAJARAN KOSA KATA BAHASA INGGRIS PADA GURU SEKOLAH DASAR DI KECAMATAN CIPANAS
Authors: Kurniawati Nia , Sofarini Anisa , Handayani Trini , Kamilah Anita , Mulyana Aji
Published: February 2023

Tujuan pelaksanaan  pelatihan penggunaan virtual reality dalam pengajaran kosa kata Bahasa Inggris pada guru Sekolah Dasar di Kecamatan Cipanas ini untuk membuka wawasan dan pengetahuan guru terkait media pembelajaran berbasis teknologi. Metode pelaksanaan kegiatan menggunakan pendekatan yang digunakan dalam pelatihan adalah pendekatan klasikal. Terdapat 5 tahapan dalam kegiatan pengabdian ini, yakni sebagai berikut: Identifikasi Masalah, Proses Informasi dan Solusi yang Ditawarkan, Penyusunan Materi Pelatihan, Pelaksanaan Pelatihan, Evaluasi. Perlu adanya peningkatan dalam metode pembelajaran Bahasa Inggris yang semula masih manual sekarang bergeser kepada penggunaan alat teknologi, solusi yang ditawarkan adalah memberikan penguatan kepada guru peserta pelatihan bahwa pembelajaran berbasis kolaboratif dapat diterapkan ketika VR digunakan sebagai media pembelajaran.
The premature expiration of arbitration litigation in investment disputes
Authors: Kandeel Moustafa Elmetwaly , Abouahmed Alaa , Zakaria Aliaa
Published: February 2023

Arbitration litigation shall be completed by the issuance of an arbitral award ending the dispute (Al Tarawneh & Al-Qhaiwi, 2020). This type of legal litigation may also end due to a contingency that occurs before the issuance of this arbitral award. The problem of this paper is to determine the cases in which the arbitration dispute can end without the issuance of an arbitral award. To study this topic, we follow the analytical approach in light of the provisions of the United Arab Emirates (UAE) Arbitration Law promulgated by Federal Law No. (6) of 2018. At the end of this paper, we conclude that the arbitration dispute may end without the issuance of an arbitral award for many reasons. This termination may be ordered by the president of the competent court, by a decision from the arbitral tribunal, by the litigant’s reconciliation, by the expiry of the arbitration deadline, or by ruling the invalidity of the arbitration agreement. In such cases, the arbitration litigation is considered expired without an arbitral decision based on the legal grounds of fulfilling one of the procedural reasons that could lead to cessation of litigation before adjudication (Zamzam, 2020)
Improved Efficiency and Stability of Organic Solar Cells by Interface Modification Using Atomic Layer Deposition of Ultrathin Aluminum Oxide
Authors: Lan Ai , Li Yiqun , Zhu Huiwen , Zhu Jintao , Lu Hong , Do Hainam , Lv Yifan , Chen Yonghua , Chen Zhikuan , Chen Fei , Huang Wei
Published: February 2023

The interfacial contacts between the electron transporting layers (ETLs)
and the photoactive layers are crucial to device performance and
stability for OSCs with inverted architecture. Herein, atomic layer
deposition (ALD) fabricated ultrathin Al2O3 layers are applied to modify
the ETLs/active blends (PM6:BTP-BO-4F) interfaces of OSCs, thus
improving device performance. The ALD-Al2O3 thin layers on ZnO
significantly improved its surface morphology, which led to the
decreased work function of ZnO and reduced recombination losses in
devices. The simultaneous increase in open-circuit voltage (),
short-circuit current density () and fill factor (FF) were achieved for
the OSCs incorporated with ALD-Al2O3 interlayers of a certain thickness,
which produced a maximum PCE of 16.61%. Moreover, the ALD-Al2O3
interlayers had significantly enhanced device stability by suppressing
degradation of the photoactive layers induced by the photocatalytic
activity of ZnO and passivating surface defects of ZnO that may play the
role of active sites for the adsorption of oxygen and moisture.
Student motivational profiles in science: TIMSS 2019 in Serbia
Authors: Sevkusic Slavica , Mirkov Snezana , Lalic-Vucetic Natasa
Published: February 2023

Understanding motivation for learning as a complex construct allows for
education to be tailored to students? individual characteristics and needs.
Although different combinations of motivational factors lead to different
outcomes, there is still a remarkable scarcity of research on students?
motivational profiles in science. To identify groups of fourth-graders
characterized by different levels of intrinsic motivation and self-efficacy
in science, we applied the person-centered approach. By conducting secondary
analyses of data obtained via student questionnaires and science knowledge
tests in TIMSS 2019 in Serbia, we examined motivational profiles? structure
and relations to achievement as well as the membership of students of
different genders and profile stability across two research cycles. The
cluster analysis revealed four profiles characterized by different levels of
intrinsic motivation, self-efficacy, and achievement. Students who reported
higher levels of motivation and self-efficacy were more successful than
students with lower scores on these variables. Students who reported the
highest levels of self-efficacy and moderate levels of motivation
demonstrated the highest achievement levels. This finding indicates that
teachers need to use strategies for improving competencies and enhancing
students? self-efficacy. It is necessary to examine contextual factors that
might have contributed to the increase in the number of students who
demonstrated low levels of intrinsic motivation and self-efficacy, and the
lowest levels of achievement.
University education in Serbia during the COVID-19 pandemic - students’ perspective
Authors: Osmanovic-Zajic Jelena , Maksimovic Jelena , Lazic Natalija
Published: February 2023

The COVID-19 pandemic forced the transition to online teaching and learning
in Serbian higher education. Therefore, this paper studies the results
achieved at Serbian universities during the Covid-19 pandemic. The methods
used are the descriptive method together with the scaling technique and the
Likert scale. The sample included 400 tertiary-level students from Serbia.
The obtained results showed both advantages and disadvantages of online
university teaching and learning during the pandemic from the students?
perspective, which might contribute to the improvement of this mode of
teaching. (SOUV). Factor analysis was applied to determine the main
variables that were used for further statistical data processing: the manner
in which lectures and tutorials were held, the predominant teaching
platforms used, the mode of examination and students? academic achievements
during the pandemic. The results proved that online teaching could not
replace the traditional mode of teaching. Moreover, the results showed that
the predominant teaching platforms used were Google Meet, Zoom and Google
Classroom. The majority of the students claimed that the main advantage of
taking examinations online was saving time and money, whreas its main
disadvantage was technical issues that could impede the process of
examination. Also, this research proved that studying in time of the
pandemic stimulated their digital literacy. The fact that the respondents
stated both advantages and disadvantages of virtual teaching may contribute
to the improvement of this manner of teaching. Thus, this paper aims to
stimulate future research that will provide an indepth analysis of
tertiary-level teaching during the pandemic.