bluuebunny/crossref_metadata_2025 huggingface dataset:
Efficacy and Safety of Intrapleural Fibrinolytic Therapy in Empyema Thoracis: A Meta-Analysis of Clinical Outcomes
Authors: Aldo Yulian  , Oea Khairsyaf  , Fenty Anggrainy
Published: October 2024

Background: Empyema thoracis is a severe pulmonary condition characterized by pus accumulation in the pleural space. Intrapleural fibrinolytic therapy is used adjunctively to break down loculations and facilitate lung re-expansion. This meta-analysis evaluated the efficacy and safety of this treatment in adults with empyema thoracis.
Methods: A systematic search of PubMed, Embase, and Cochrane Central Register of Controlled Trials was conducted (January 2013 - December 2023) for randomized controlled trials (RCTs) comparing intrapleural fibrinolytics with placebo or no fibrinolytic therapy in adults with empyema. Primary outcomes were treatment success (radiographic improvement and/or clinical resolution), duration of hospital stay, and mortality. Secondary outcomes included major bleeding and bronchopleural fistula. Data were pooled using a random-effects model, and risk ratios (RR) or mean differences (MD) with 95% confidence intervals (CI) were calculated.
Results: Six RCTs (n=623 patients) met the inclusion criteria. Intrapleural fibrinolytic therapy showed a significantly higher treatment success rate than the control (RR 1.42, 95% CI 1.18-1.72, p=0.001) and significantly reduced hospital stay (MD -2.84 days, 95% CI -3.36 to -2.33, p<0.001). No significant difference in mortality was found (RR 0.95, 95% CI 0.46-1.93, p=0.93). The incidence of major bleeding and bronchopleural fistula was similar between the groups.
Conclusion: Intrapleural fibrinolytic therapy significantly improves treatment success and reduces hospital stays without increasing mortality or major complications. These findings support its use as an adjunctive therapy for drainage in managing empyema thoracis in adults.
PENGEMBANGAN KOMPETENSI MAHASISWA MELALUI WORKSHOP BEBASIS POM QM FOR WINDOWS UNTUK ANALISIS QUALITY CONTROL
Authors: Suseno Pangki , Junianto Dwi , Mahariani Yeni Roha , Suwignyo Fahrul Afiyas
Published: October 2024

Indonesia saat ini berada dalam era Industri 4.0 yang merupakan era digitalisasi industri yang menjadi acuan utama dalam membawa perubahan besar, termasuk pengendalian kualitas. Kualitas telah menjadi salah satu variabel pilihan utama perusahaan dalam memahami dan mengembangkan kualitas lebih lanjut untuk mendorong pencapaian dalam bisnis. Untuk mengembangkan kualitas tersebut sumber daya manusia dituntut memiliki keterampilan. Program POM-QM merupakan sebuah program komputer yang digunakan sebagai alternatif aplikasi yang bisa digunakan untuk membantu pengambilan keputusan. Tujuan dari kegiatan pengabdian ini adalah untuk memberikan tambahan pengalaman, keterampilan dan pengetahuan kepada mahasiswa dalam berinteraksi dengan teknologi secara umum dan menggunakan POM-QM for windows sebagai alat analisis kualitas. Pelaksanaan pengabdian dilakukan pada tanggal 21 Februari 2024 dengan jalan ceramah dan praktik, serta evaluasi pemahaman mahasiswa sebelum dan setelah pelatihan. Pelaksanaan pelatihan antara lain: instalasi software POM-QM for windows; penggunaan software; dan praktik analisis kualitas dengan POM-QM for Windows. Hasil dari kegiatan PKM ini menunjukkan bahwa mahasiswa sudah memahami instalasinya dan 57,9% peserta sudah memahami penggunaan software POM-QM for windows untuk menyelesaikan permasalahan kualitas dan memberikan solusinya. Dan dari hasil evaluasi diketahui bahwa pelatihan tersebut bermanfaat bagi mahasiswa untuk menyelesaikan masalah kualitas dengan cepat.
An Enhanced Edge Computing Technique for Detection of Voltage Fluctuation in Grid-tied Renewable Energy
Authors: Ibitoye Oladapo T. , Onibonoje Moses O. , Dada Joseph O. , Ikumapayi Omolayo M. , Laseinde Opeyeolu T.
Published: October 2024

Renewable energy sources (RES) such as solar photovoltaic and wind are becoming the most attractive power generation options in many nations. Even while high penetration seems likely, power quality anomalies such as voltage fluctuation, harmonics, and frequency fluctuation associated with RES hinder seamless integration. The variability and unpredictability of these sources create the most oddities. In grid-tied renewable energy, monitoring power quality efficiently is crucial. Power grid monitoring solutions in related literature use sensor-based cloud and edge computing techniques. The existing systems struggle with excessive latency when delivering large amounts of generated data to the cloud. To fill this gap, a new approach for the detection and localization of voltage fluctuation is proposed in this study. The approach integrated three techniques namely; feed-forward neural network (FFNN), Stockwell transform, and anomaly-aware edge computing to detect and locate voltage fluctuation in a GtRE. Using MATLAB/Simulink, virtual emulation of a modified IEEE 33 Bus and a GtRE representing a section of Ado Ekiti (in Nigeria) low-voltage distribution grid are carried out for data generation and system evaluation. Feature extraction was carried out in a Python IDE using Stockwell transform. The voltage fluctuation events are detected and localized based on the extracted features using the trained FFNN model deployed and evaluated within three microcontroller-based computing devices. The proposed approach integrated anomaly-aware with edge computing to send only voltage data that are considered abnormal to a dedicated data center for visualization and storage. Performance evaluation of the proposed technique on the simulated GtRE demonstrates a significant decrease of 98% and 90% in latency when compared to cloud computing and conventional edge computing respectively. Comparison of the proposed approach to two closely related solutions in literature also demonstrates a 50% and 92.5 % reduction in latency. The contribution of the study is the reduced latency and minimal bandwidth utilization achieved by the implementation of the developed technique.
On Numerical Radius Inequalities for Hilbert Space Operators
Authors: Al-Hawari M. , Alazzam Mahmoud
Published: October 2024

This paper aims to find special cases of some inequalities for numerical radii and spectral radii of a bounded linear operator on a Hil-bert space, we focus on numerical radii inequalities for restricted linear operators on complex Hil-bert spaces for the case of one and two operators, and study the numerical range of an operator K on a complex Hil-bert space H, after that we present some inequalities for numerical radii and spectral radii and studied it to find new results. At the end of this paper we find several inequalities for numerical radii by using the spectral norm, this study is necessary to find other bound for zeros of polynomials and this study is necessary to find new bounds for the zeros of polynomials by a playing the new results to the companion matrix.
Dee J. Kelly Law Library By the Numbers, 2021-2022
Authors:   Dee J. Kelly Law Library
Published: October 2024

A compilation of data and statistics highlighting the activities and services of the Dee J. Kelly Law Library at Texas A&M University School of Law
Legal Status of Doctoral Students and Scientific Consultants: Problems and Possible Solutions
Authors:   Saratov State Law Academy, Rukavishnikov S. M.
Published: October 2024

Introduction. The article studies the issue of assessing the effectiveness of modern domestic doctoral studies through the prism of the legal status of doctoral students and scientific consultants. Taking into account the critical role of doctoral studies in the training of researchers of the highest level of qualifications who have an academic degree of Doctor of Science, as well as the current regulations and the specifics of training in doctoral studies, the totality of rights, responsibilities and guarantees provided to doctoral students and scientific consultants requires consideration and critical assessment. Materials and Methods. The use of methods of formal legal analysis, coupled with consideration of the positions of researchers on the issues of improving the system of state scientific certification, made it possible to identify a number of positions that require clarification in regulatory legal acts, or are not regulated at all, despite their high importance in creating conditions for the preparation of research in doctoral studies. Analysis. The current regulation of material guarantees ensuring the activities of doctoral students and scientific consultants is considered, and the insufficiency and uncertainty regarding certain regulations in this matter is identified. The issue of the responsibility of a scientific consultant for the dishonest performance of their duties is also touched upon, the scope of which is currently determined by the parties independently, which is subject to motivated criticism. A separate aspect of providing conditions for the implementation of research work by doctoral students is the issue of providing them with long-term leave, which is currently covered only by general regulations tied to the ten-year experience of the relevant specialist, which has been criticized in the context of the need to reduce the average age of scientific and scientific-pedagogical personnel. Results. The set of measures proposed by the author is aimed at increasing the efficiency of the doctoral education institute, which is an important element of the state scientific certification system, the potential of which is currently not revealed and requires development.
Public law and private law principles in the regulation of digital currency
Authors:   North-Caucasus Federal University, Sagalaeva E. S. , Botasheva L. E. ,   North-Caucasus Federal University
Published: October 2024

Introduction. The article discusses issues of interdisciplinary regulation of centralized digital currencies issued by central banks. Attention is paid to the public legal and fair principles of digital currency of the Central Bank. Materials and Methods. The theoretical basis was formed by scientific publications of domestic and foreign authors on research issues. The study is based on the analysis of legal provisions of financial and civil legislation that determine the legal regime of the digital ruble. The formal legal method, as the main method of the research, made it possible to reveal the content of the intersectoral legal nature of digital currency. Analysis. The issues of the legal nature of the Central Bank digital currency are explored. Close attention is paid to the provisions “On the Digital Ruble”, concentrated in the norms of public and private law. It is noted that the lack of a clear conceptual apparatus causes difficulties in the interpretation of basic categories. The dual legal nature of the digital ruble is substantiated. This duality is manifested in the fact that the digital ruble is an object of financial law, as a national digital currency issued by the Bank of Russia, on the other hand, the obligatory nature of the digital ruble, reflected in the provisions of private law and the Federal Law “On the National Payment System”. Results. Central bank digital currencies (CBDCs) are being considered or are in the process of being implemented by many central banks around the world. Despite the importance and potential consequences of such dramatic changes in national currencies, many uncertainties remain.
Impact of self-restraint by COVID-19 pandemic on mental health in college students-COVID-19 Longitudinal survey of the 2nd and 3rd waves
Authors: Ohue Takashi
Published: October 2024

[Purpose] The purpose of this study was to investigate the effects of the COVID-19 pandemic on mental health in students at university.
[Method] 1880 students from university were surveyed. Survey period: July-August 2020
Demographic factors were used department, grade, gender, age. Mental health factors (PHQ-9 Japanese version, GAD-7 Japanese version, IES-R) were used. Decreased motivation to learn, loneliness: Japanese version UCLA loneliness scale was used.
[Results] As a result of the survey, in (July-August), 737 patients (123 males and 614 females) were recovered (recovery rate 40.9%). As a result, in terms of gender difference, males had a higher total of "loneliness" than females and had a higher total of PTSD and "invasive symptoms". Students whose parents corresponded to corona had high "anxiety" and "depression". Students who felt rumors had high scores for "PTSD," "depression," "anxiety," and "loneliness." Students "seeking support" also scored higher on PTSD, depression, anxiety, and loneliness. Those who were "not very careful" about infection control were more likely to be depressed than those who were "careful", and those who were "quite careful" were less motivated to learn. Family structure and parental profession have no effect. In addition, the relationship between each psychiatric symptom (PTSD, depression, anxiety disorder) and "loneliness" and "motivation to learn" was examined using covariance structure analysis. When the model was examined, the models of "loneliness" ⇒ "decreased learning motivation" ⇒ "PTSD" ⇒ "depression" and "anxiety" were verified. In other words, it was shown that it is important to deal with "loneliness" to improve mental health and learning motivation during the COVID 19 pandemic.
[Conclusion] At the time of the COVID-19 pandemic, college students may be high-risk persons with mental health problems.
МЕЖДУНАРОДНАЯ КООПЕРАЦИЯ-ВАЖНЕЙШИЙ ВИД ЗАРУБЕЖНОЙ ДЕЯТЕЛЬНОСТИ
Authors: Александрова Е.В. , Иншаков А.А.
Published: October 2024

Расширение партнерских отношений. Задачи исследования- обеспечение занятости на рынке труда, Целью доклада является повышение осведомленности о кооперативах. Новизна состоит в особом подходе к развитию международного кооперативного движения. Для написания доклада изучались литературные источники в период НЭПа, проведен архивный поиск. Сделан анализ трудов современных ученых.
ENHANCING LEXICAL PROFICIENCY IN ASPIRING FOREIGN LANGUAGE EDUCATORS THROUGH MOTIVATIONALLY-DRIVEN PEDAGOGICAL STRATEGIES
Authors:   Tashkent State Pedagogical University Uzbekistan, Shavkatovna Yarieva Zarrina
Published: October 2024

This article investigates the implementation of motivationally-driven pedagogical strategies to enhance the lexical proficiency of aspiring foreign language educators. Recognizing the crucial role of vocabulary in language acquisition and teaching, this paper explores innovative approaches to motivate future teachers in developing their lexical competencies. Drawing upon theoretical frameworks and practical insights, this article proposes a comprehensive plan to integrate motivational techniques into pedagogical practices, aiming to empower educators with the lexical expertise necessary for effective language instruction.
IMPORTANCE OF INNOVATIVE TECHNOLOGIES IN MATHEMATICS
Authors:   Student Of Gulistan State University Uzbekistan, Qizi Habibullayeva Shoira Farhod
Published: October 2024

In this article, scientific opinions about the importance of innovative technologies in mathematics are presented and their role in improving the methodological work of mathematics education is revealed. Interactive strategies of mathematics education based on modern pedagogical technologies facilitate the educational process, clarify it, and cover a wide community. intended.
Risk management technology in the public sector: challenges and opportunities
Authors: BUTENKO Hlib
Published: October 2024

The paper examines the importance of using effective risk management methods in the public sector, emphasizing the need for an integrated approach to this problem. The author emphasizes that public management mechanisms must be supported by appropriate technologies to ensure sustainable functioning. The use of ISO 31000 and ISSAI 9100 standards helps structure the risk management process and increase its effectiveness. Risk management should be based on the identification, assessment and response to risks and take into account the influence of various factors on the risk management process.
The author also notes that risk management in the public sector is complicated by certain factors (frequent management changes, division of operating budgets and programs, lack of clear risk indicators, etc.).
The analysis of the issue demonstrates that the system of assessment, management and risk reduction should play a key role in public administration. The main task of risk management as an element of public management is to make effective decisions, create the necessary conditions and plan actions taking risks into account to minimize their negative impact on planned results.
As a result of the use of risk management technologies, it is possible to identify risks, determine factors and sources of risk, assess the degree and probability of occurrence of hazards and, ultimately, develop an optimal plan of management actions. The results of the study demonstrate that the issue of forming a risk management mechanism in the public sector requires further scientific research on the application of theoretical developments in the practical activities of public management and administration bodies of Ukraine.
The paper also focuses on the issue of risk management in public sector organizations, and concludes that in order to assess the value, type and impact of risk, it is necessary to review the internal part of the organization and its management processes, as well as its environment. Such a review of risks should be complemented by increased risk awareness at each level of the management hierarchy and in the day-to-day activities of all employees of the organization.
Thus, the need to use modern risk management technologies in the public sector is outlined in order to increase the effectiveness of the decisions made and minimize the negative impact of potential risks on the results of the work of management bodies.
Economic outcomes and evaluation of market power of enterprises
Authors: TYTARENKO Valerii
Published: October 2024

Equitable distribution of society's resources is impossible without controlling monopolies. This is especially true of state-owned enterprises, which, in addition to inflated prices, often have the ability to use the resources received inefficiently. In order to control the market power of enterprises, scientists have already developed many approaches to analysing the market structure and assessing the level of its concentration. At the same time, the problem of formal numerical assessment of the degree of market power of enterprises remains insufficiently resolved. One of the most important areas of assessing the market power of an enterprise is the analysis of its economic results. The essence of this assumption is quite simple: the higher the level of market power an enterprise has, the more independent it is in setting higher prices, which lead to excessive profits. This paper does not consider possible sources and causes of market power related to product uniqueness, cross elasticity of demand or market structure. The purpose of the paper is to find a way to assess market power according to performance indicators that are derived from and result from the use of market power by an enterprise. However, a study of the existing methods of assessing the level of market power of an enterprise has shown that there is no single approach to determining the degree of market power of an enterprise, despite the unambiguous dependence. Most methods propose to use profitability as a basis, but there is a variety of views on how to calculate this indicator. While the first component of profit, revenue or the price of goods, is a fairly objective indicator, the greatest difficulties are found in understanding and applying cost elements to calculate profitability as a measure of market power.
Impact of green human resource management on employees’ green behavior in hotels
Authors: Hong Nguyen Thi , Hieu Le Trung , Huong Dang Thi , Phuong Tran Thi Minh
Published: October 2024

The purpose of this study is to examine the influence of green human resource management (GHRM) on employees’ green behavior (EGB) in hotels in Vietnam. To fulfill social responsibility towards the environment, many organizations have been paying more attention to GHRM, thereby forming EGB. Especially in today's situation where global warming is increasing, “green” practices should be adopted by organizations, starting from the core of organizations—their human resources. The success of an organization's initiative to sustain environmental sustainability largely depends on promoting green behavior among employees. The study used a mixed method, incorporating qualitative feedback from previous studies, experts, and quantitative data from 556 employees working in hotels in Vietnam. Filtering was performed on the data to remove outliers and demonstrate statistical, confirmatory factor analysis, and structural equation modeling. The results show that GHRM activities such as green recruitment, green training and development, green job performance management and appraisal, and providing green compensation strongly influence EGB. Additionally, the study also indicates that EGB varies based on work experience and the type of hotel where they are employed. Hotels operating in the tourism industry have been paying more attention to GHRM, thereby forming EGB. In the tourism industry, hotels must ensure environmental protection goals more than ever. Developers and managers can utilize more development tactics to enhance GHRM and EGB.
ДИНАМИКА СОРНОЙ РАСТИТЕЛЬНОСТИ В ПОСЕВАХ ЯРОВОЙ ТРИТИКАЛЕ ВОЗДЕЛЫВАЕМОЙ В ОРГАНИЧЕСКОМ ЗЕМЛЕДЕЛИИ
Authors: Назарова Перизат , Наздрачев Яков , Мамыкин Евгений
Published: October 2024

В органическом земледелии одним из основных факторов, снижающих продуктивность сельскохозяйственных культур, является сорная растительность. Методов борьбы с сорной растительностью в органическом сельском хозяйстве крайне мало. Авторами статьи был выбран комплексный метод борьбы с сорняками - подбор культур для возделывания, севооборот и различные способы обработки почвы. В качестве культуры для возделывания в условиях Северного Казахстана была выбрана – яровая тритикале. Исследования проводились в ТОО «НПЦЗХ им. А. И. Бараева» с 2018 по 2023 гг. Благодаря комплексному методу борьбы с сорной растительностью удалось значительно снизить численность таких сорных растений, как щирица запрокинутая (Amaranthus retroflexus L.), гречиха татарская (Fagopirum tataricum L. Gaertn.), марь белая (Chenopodium album L.), просо сорнополевое (Panicum miliaceum L.), овсюг обыкновенный (Avena fatua L.) и бодяк полевой (Cirsium arvense L.). Единственным сорным растением, численность которого слабо контролируется, был вьюнок полевой (Convolvulus arvensis L.), его количество в опытах с каждым годом увеличивалась с 8 шт./м2 (в 2018 году) до 13-20 шт./м2 (в 2023 году).
The Effect of Company Performance, Company Complexity, Company Size on the Board of Commissioners Structure Moderated by Managerial Ownership
Authors: Carlos Pangestu Juan , Whittleliang Hakki Tandry , Naftalia Elisa Marta
Published: October 2024

The role of the Board of Commissioners is very important to minimize agency problems so that shareholder wealth maximization can be achieved. Under one board, a number of studies have investigated the effect of the effectiveness of the Board of Directors on their company's performance. In Indonesia, existing research related to the effectiveness of the Board of Commissioners investigates the effectiveness of the Board of Commissioners as one of the determining factors for the possibility of financial distress and investigates effectiveness. This study aims to examine the effect of Company Performance, Company Complexity, Company Size on the Structure of the Board of Commissioners and examine whether there is a role of Managerial Ownership as a moderation in the influence of Company Performance, Company Complexity, Company Size on the Structure of the Board of Commissioners carried out by the company. This study took the research population from financial sector companies listed on the Indonesia Stock Exchange for the period 2019-2022. The type of data used in this study is secondary data in the form of company financial reports that are used as samples. The research method used in this study is a quantitative research method. The sample was selected using the purposive sampling method. For hypothesis testing, this study uses multiple linear regression analysis. Based on the results of the study, it shows that company performance has a significant effect on the Board of Commissioners Structure, then Company Complexity and Company Size do not have a significant effect on the Board of Commissioners structure. Managerial Ownership strengthens the influence of Company Performance on the Board of Commissioners Structure. Managerial Ownership does not strengthen the influence of Company Complexity and Company Size on the Board of Commissioners Structure.
The Antecedents of Carbon Emission Disclosure With Carbon Knowledge as Moderation
Authors: Setiawan Temy , Ahalik Ahalik , Hakki Tandry Whittleliang , Novanto Yosan
Published: October 2024

Climate change is one of the main problems faced by humans in this decade. Several environmental research institutions state that climate change in the next ten years is considered the most threatening long-term risk. Developed countries contribute 65-70% while poor and developing countries contribute the remaining 30%-35%. One of Indonesia's commitments as a country that is a member of the United Nations Framework Convention on Climate Change. The UNFCCC CoP (Climate Change Conference) is an annual world climate conference, where governments meet to discuss plans to address the climate crisis. This will be the 26th meeting. Where this convention is attended by 195 countries that are members of the United Nations (UN). This study aims to analyze the factors that influence the level of carbon emission disclosure, namely to test and analyze: The Influence of Corporate Environmental Awareness, Corporate Carbon Strategy, Green Corporate Business Strategy and Green Supply Chain on Carbon Emission Disclosure. In addition, this study also tests and analyzes the Role of Carbon Knowledge as a moderating variable for the influence of Corporate Environmental Awareness, Corporate Carbon Strategy and Green Supply Chain on Carbon Emission Disclosure. The analytical method used in this study is path analysis with the pattern of relationships between independent variables in this study being correlative and causal. Based on the results of this study, it shows that Environmental Performance has a significant effect on carbon emission disclosure. Carbon management strategy does not have an effect on carbon emission disclosure. Competitive Business Strategy has a significant effect on carbon emission disclosure. And green supply chain management has an effect on carbon emission disclosure. Carbon Knowledge does not strengthen the effect of environmental performance on carbon emission disclosure, Carbon Knowledge does not strengthen the effect of Carbon Management Strategy on carbon emission disclosure. Carbon Knowledge strengthens the effect of Corporate Business Strategy on carbon emission disclosure. Carbon Knowledge strengthens the effect of Green Supply Chain Management on carbon emission disclosure
Determination of Competency, Work Discipline and Motivation on employee performance at Universities in Indonesia
Authors: Muhajirin Adi , Ali Hapzi , Widyastuti Tri , Suroso Sugeng
Published: October 2024

How to accept educational staff who lack competence with the level of job satisfaction of staff due to lack of competence and measure the level of motivation that has continued to decline since entering the staff, that the level of staff discipline has decreased. Quantitative research, which is a type of research emphasizing the testing of theoretical theories through measuring research variables with numbers and requiring data analysis with statistical procedures. The measuring instrument for this research is a questionnaire, the data obtained is in the form of answers from staff to the questions asked. based on the research objectives that have been set, this type of research is explanatory. The statistical t value of the effect of competence (KO) on motivation (MO) is 5.29 with a positive structural equation coefficient, that competence has a positive and significant effect on motivation. The more competence of university staff, it will increase employee motivation, otherwise the less competence the university staff has, it will reduce work motivation and can even transmit decreased motivation to other staff so that motivation becomes the main thing that must be owned by university staff. For universities, it is better when recruiting educational staff to have basic competencies so that they can increase the motivation of the staff themselves and form an academic culture that is in accordance with academic rules
Analysis of Annual Spt Reporting Article 21 Before and After the Implementation of the E-Filling System at PT Surya Toto Indonesia, Tbk
Authors: Wahyuni Efa , Kuncara Tommy
Published: October 2024

The purpose of this research is to understand and gather information on how the employees of PT. Surya Toto Indonesia fulfill their obligations as taxpayers in reporting their Annual Income Tax Return (SPT) for PPh 21, to identify the advantages and disadvantages of the e-filing system, and to explore several efforts to overcome the challenges associated with this system. It also aims to examine the differences in reporting the Annual Income Tax Return (SPT) for PPh 21 before and after the implementation of the e-filing system. The data processed in this research is sourced from primary data, which includes qualitative data from interviews and the company profile of PT. Surya Toto Indonesia, Tbk, and quantitative data related to the calculation of PPh 21 on irregular income for employees. The findings of this study indicate that the employees of PT. Surya Toto Indonesia have fulfilled their obligations as taxpayers in reporting the Annual Income Tax Return for PPh 21. In the implementation of the e-filing system, there are both advantages and disadvantages. Differences have been noted before and after the implementation of the e-filing system in terms of the Notification Letter Form (SPT), tax calculation procedures, time/place effectiveness, efficiency, archiving, data submission of the SPT, and taxpayer compliance.
The role of artificial intelligence in decolonising academic writing for inclusive knowledge production
Authors: Omodan Bunmi Isaiah , Marongwe Newlin
Published: October 2024

This conceptual article delves into the integration of Artificial Intelligence (AI) in academia, focusing on its potential to decolonise academic writing for inclusive knowledge production. The paper begins with an overview of decolonisation in academic discourse and introduces AI's emerging role in this field. It then reviews the literature on decolonial perspectives in academia, the challenges faced by non-native English speakers in academic writing, and previous AI research in education, highlighting gaps that necessitate a decolonial and critical approach. The theoretical framework combines decoloniality and critical theory, linking these to empower non-native English-speaking academics. Using a theory synthesis design, the discussion explores this group's unique challenges in academic writing and how AI, specifically applications like ChatGPT, can be a transformative tool for inclusivity in publication spaces. It critically examines how AI can contribute to decolonising academic knowledge writing. However, it also addresses potential challenges and ethical considerations in merging AI with decolonial perspectives. The article forecasts future AI developments and their implications for decolonising academic experiences, emphasising the need for inclusive technological advancements. In conclusion, the article stresses AI's potential role in decolonising academic practices and calls for further interdisciplinary dialogue and exploration. Recommendations for universities, academics, policymakers, and curriculum designers, as well as implications for decolonial and critical discourses, are provided.
A New Hope in The Treatment of Rett Syndrome: Trofinetide
Authors: Sönmez Doğancan
Published: October 2024

Trofinetide is a medication used to treat Rett Syndrome. It was approved by the United States in March 2023 for the treatment of Rett Syndrome in adults and children ages 2 and older. The drug is an N-terminal tripeptide derivative of insulin-like growth factor-1 (IGF-1) and is an oral, small molecule, synthetic analogue. The FDA's approval of trophinetide marks the first authorized treatment for Rett Syndrome.
GOODS & SERVICES TAX (GST) AND ITS IMPLICATIONS FOR SMALL BUSINESSES: A DHULE DISTRICT PERSPECTIVE
Authors: Pandit Palve Dr. Vijay
Published: October 2024

The present study examines the implications of the Goods and Services Tax (GST) on small businesses in Dhule district, with a focus on comparing businesses with turnovers up to 1 Crore and those between 1 to 5 Crores. The primary objective is to explore whether there are significant differences in perceptions of GST's impact across various business aspects. A structured questionnaire based on a 7- point Likert scale was used to collect primary data from 100 small businesses. The responses were analyzed using independent samples t-tests to test the hypothesis that businesses with different turnover levels perceive the impact of GST differently. The results showed no significant differences in the perceptions of GST between the two groups for any of the variables. Key business aspects assessed included the simplification of the tax process, administrative burden, cash flow, input tax credits, and overall costs. The findings suggest that small businesses, irrespective of their turnover size, share similar views on GST's effects on their operations. Consequently, the study concludes that GST has a uniform impact on small businesses within the turnover categories analyzed.
UNVEILING FARMERS’ PERSPECTIVES: A COMPREHENSIVE EXAMINATION OF PRADHAN MANTRI FASAL BIMA YOJANA (PMFBY) IN TIRUCHIRAPPALLI DISTRICT OF TAMIL NADU
Authors: Iniya V  , Padma S R
Published: October 2024

Agriculture’s inherent uncertainties threaten farmers' income and food security. The government introduced Pradhan Mantri Fasal Bima Yojana (PMFBY) in 2016 to mitigate risks, aligning with the “One Nation-One Plan” initiative for farmers’ protection. The current investigation aimed to gauge farmers’ perceptions of the Pradhan Mantri Fasal Bima Yojana (PMFBY). Conducted in the year 2022-23, the study focused on deliberately chosen blocks namely Thuraiyur and Uppiliyapuram in Tiruchirappalli district of Tamil Nadu. Respondents, totaling 120, were chosen from three villages in each selected block using a proportionate random sampling method. A thoroughly designed interview schedule, formulated based on expert opinions and literature reviews, was employed for data collection. Subsequently, the acquired data underwent coding, quantification, classification, tabulation and analysis, employing frequency, percentage and mean score ranking techniques to derive meaningful insights. The study's results indicated that a significant proportion of farmers (70.83%) held medium level perception, while 20.00 per cent had low perception, and 9.17 per cent expressed high perception regarding the Pradhan Mantri Fasal Bima Yojana (PMFBY). The assessment revealed that statements such as the enhancement of individual farmers' knowledge and skills under PMFBY (Mean Score - 2.59) ranked highest, followed by its role in enhancing yields and crop protection (Mean Score - 2.58) and improving resource-poor farmers’ access to better crop production (Mean Score - 2.48), which were ranked second and third, respectively. Crop insurance shields farmers from uncertainties like natural disasters. It is deemed essential for all types of farmers due to its significance.
THE EXPLORATION OF THE BUSINESS FINTECH LENDING SECTOR REVEALS SIGNIFICANT IMPACTS ON THE FINANCIAL LANDSCAPE
Authors: Tri Agusta Levani , Aurora Sylvira Krystalicia , Susilo Wilhelmus Hary
Published: October 2024

The investigation into the FinTech lending industry uncovers substantial effects on the overall financial environment. The objective of this research is to investigate various fundamental elements of existing literature, with a particular emphasis on financial technology (FinTech), regulatory structures, competitive approaches, and the broader financial sector. This sector, characterized by the integration of technology into financial services, has transformed traditional lending practices, enhancing accessibility and efficiency for both borrowers and lenders. The emergence of innovative platforms has facilitated a more streamlined application process, reduced costs, and expanded the range of financing options available to businesses. As a result, the FinTech lending sector not only contributes to the growth of small and medium-sized enterprises but also challenges conventional banking models, prompting a re-evaluation of regulatory frameworks and competitive strategies within the financial industry.
Predicting the Energetic Proton Flux with a Machine Learning Regression Algorithm
Authors: Stumpo Mirko , Laurenza Monica , Benella Simone , Marcucci Maria Federica
Published: October 2024

The need for real-time monitoring and alerting systems for space weather hazards has grown significantly in the last two decades. One of the most important challenges for space mission operations and planning is the prediction of solar proton events (SPEs). In this context, artificial intelligence and machine learning techniques have opened a new frontier, providing a new paradigm for statistical forecasting algorithms. The great majority of these models aim to predict the occurrence of an SPE, i.e., they are based on the classification approach. This work is oriented toward the successful implementation of onboard prediction systems, which is essential for the future of space exploration. We present a simple and efficient machine learning regression algorithm that is able to forecast the energetic proton flux up to 1 hr ahead by exploiting features derived from the electron flux only. This approach could be helpful in improving monitoring systems of the radiation risk in both deep space and near-Earth environments. The model is very relevant for mission operations and planning, especially when flare characteristics and source location are not available in real time, as at Mars distance.
AM3: An Open-source Tool for Time-dependent Lepto-hadronic Modeling of Astrophysical Sources
Authors: Klinger Marc , Rudolph Annika , Rodrigues Xavier , Yuan 袁 Chengchao 成超 , Fichet de Clairfontaine Gaëtan , Fedynitch Anatoli , Winter Walter , Pohl Martin , Gao Shan
Published: October 2024

We present the Astrophysical Multimessenger Modeling (AM

3
) software. AM

3
is a documented open-source software (source code at https://gitlab.desy.de/am3/am3; user guide and documentation at https://am3.readthedocs.io/en/latest/) that efficiently solves the coupled integro-differential equations describing the temporal evolution of the spectral densities of particles interacting in astrophysical environments, including photons, electrons, positrons, protons, neutrons, pions, muons, and neutrinos. The software has been extensively used to simulate the multiwavelength and neutrino emission from active galactic nuclei (including blazars), gamma-ray bursts, and tidal disruption events. The simulations include all relevant nonthermal processes, namely synchrotron emission, inverse Compton scattering, photon–photon annihilation, proton–proton and proton–photon pion production, and photo-pair production. The software self-consistently calculates the full cascade of primary and secondary particles, including nonlinear feedback processes and predictions in the time domain. It also allows the user to track separately the particle densities produced by means of each distinct interaction process, including the different hadronic channels. With its efficient hybrid solver combining analytical and numerical techniques, AM

3
combines efficiency and accuracy at a user-adjustable level. We describe the technical details of the numerical framework and present three examples of applications to different astrophysical environments.
3D Radiation-hydrodynamical Simulations of Shadows on Transition Disks
Authors: Zhang Shangjia , Zhu Zhaohuan
Published: October 2024

Shadows are often observed in transition disks, which can result from obscuring by materials closer to the star, such as a misaligned inner disk. While shadows leave apparent darkened emission as observational signatures, they have significant dynamical impact on the disk. We carry out 3D radiation-hydrodynamical simulations to study shadows in transition disks and find that the temperature drop due to the shadow acts as an asymmetric driving force, leading to spirals in the cavity. These spirals have zero pattern speed following the fixed shadow. The pitch angle is given by tan−1(c

s
/v

ϕ
) (6° if h/r = 0.1). These spirals transport mass through the cavity efficiently, with α ∼ 10−2 in our simulation. Besides spirals, the cavity edge can also form vortices and flocculent streamers. When present, these features could disturb the shadow-induced spirals. By carrying out Monte Carlo radiative transfer simulations, we show that these features resemble those observed in near-infrared scattered light images. In the vertical direction, the vertical gravity is no longer balanced by the pressure gradient alone. Instead, an azimuthal convective acceleration term balances the gravity–pressure difference, leading to azimuthally periodic upward and downward gas motion reaching 10% of the sound speed, which can be probed by Atacama Large Millimeter/submillimeter Array line observations.
2019 UO14: A Transient Trojan of Saturn
Authors: Hui 許 Man-To 文韜 , Wiegert Paul A. , Weryk Robert , Micheli Marco , Tholen David J. , Deen Sam , Walker Andrew J. , Wainscoat Richard
Published: October 2024

Saturn has long been the only giant planet in our solar system without any known Trojan members. In this Letter, with serendipitous archival observations and refined orbit determination, we report that 2019 UO14 is a Trojan of the gas giant. However, the object is only a transient Trojan currently librating around the leading Lagrange point L
4 of the Sun–Saturn system in a period of ∼0.7 kyr. Our N-body numerical simulation shows that 2019 UO14 was likely captured as a Centaur and became trapped around L
4 ∼ 2 kyr ago from a horseshoe co-orbital. The current Trojan state will be maintained for another millennium or thereabouts before transitioning back to a horseshoe state. Additionally, we characterize the physical properties of 2019 UO14. Assuming a linear phase slope of 0.06 ± 0.01 mag deg−1, the mean r-band absolute magnitude of the object was determined to be H

r
= 13.11 ± 0.07, with its color measured to be consistent with that of Jupiter and Neptune Trojans and not statistically different from Centaurs. Although the short-lived Saturn Trojan exhibited no compelling evidence of activity in the observations, we favor the possibility that it could be an active Trojan. If confirmed, 2019 UO14 would be marked as the first active Trojan in our solar system. We conservatively determine the optical depth of dust within our photometric aperture to be ≲10−7, corresponding to a dust mass-loss rate to be ≲1 kg s−1, provided that the physical properties of dust grains resemble Centaur 29P/Schwassmann–Wachmann 1.
Multi-Step-Ahead Time Series Forecasting using Deep Learning and Fuzzy Time Series-based Error Correction Method
Authors: Bhanja Samit , Ghose Banani , Das Abhishek
Published: October 2024

Recently time series forecasting has become one of the prime application areas of climatology, economics and industries. Many research works are conducted to forecast the time series more accurately. But few of them are concentrated on predicting the time series over an extended future horizon, and there is also a scope to improve their forecasting accuracy. This work proposes a multi-step-ahead foresting method to produce a stable and accurate forecasting result for the extended future horizon. Firstly, a deep learning-based forecasting model is proposed to predict the time series. Secondly, a fuzzy time series-based error correction model is implemented to enhance the prediction performance of the deep learning model. Here to optimize all the fuzzy time series (FTS) parameters in an integrated way, an integrated butterfly optimization (FTS-IBO) algorithm is proposed. In this study, two different types of real-world multivariate time series datasets are used to analyze the forecasting performance of the proposed model. The performance of the proposed FTS-IBO algorithm is compared with the traditional butterfly optimization (FTS-BO) algorithm. The experimental results show that the FTS-IBO technique is superior to the FTS-BO technique. The forecasting performance of the proposed model has also compared the other state-of-the-art models, and the simulation results exhibit that the proposed model produces a more accurate prediction performance for multi-step-ahead time series forecasting problems compared to other models.
Editorial
Authors: Gütl Christian
Published: October 2024

Dear Readers,

It gives me great pleasure to announce the tenth regular issue of 2024. I would like to thank all the authors for their sound research papers and the editorial board and our guest reviewers for their extremely valuable reviews and suggestions for improvement. These contributions and the generous support of the consortium members enable us to run our journal and maintain its quality. I would also like to thank our broader community for reading and incorporating sound J.UCS papers into their research.

Still, I would like to expand our editorial board: If you are a tenured associate professor or above with a good publication record, please apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and emerging trends.

In this regular issue, I am very pleased to introduce six accepted papers involving 17 authors from six different countries (Argentina, Brazil, Ecuador, Hong Kong, India, Saudi Arabia).

Álex dos Santos Moura, Fábio Gomes Rocha, and Michel S. Soares from Brazil propose in their research a recommendation tool based on information retrieval to assist developers in choosing the suitable microservices pattern to solve a given problem. In a collaborative research effort between Ecuador and Argentina, Gonzalo P. Espinel-Mena, José L. Carrillo-Medina, Eddie E. Galarza, and Mario Matias Urbieta discuss a systematic mapping of configuration management activities in software product line. Edward Kai Fung Dang, Robert Wing Pong Luk, and Qing Li from Hong Kong contribute to the forum for negative results with their study on word bigrams for pseudo-relevance feedback in information retrieval. Prateek Thakral and Yugal Kumar from India present in their work an improved water flow optimizer (IWFO) algorithm for cluster analysis that can address the issues of traditional and heuristic algorithms. Samit Bhanja, Banani Ghose, and Abhishek Das from India highlight their findings on multi-step-ahead time series forecasting using a deep learning and fuzzy time series-based error correction method. And last but not least, Abdullilah A. Alotaibi and Salman A. AlQahtani from Saudi Arabia present in their research an intelligent distributed channel selection framework with hybrid mode selection for interference mitigation in D2D based 5G networks. 

Enjoy Reading!

Best regards, 

Christian Gütl, Managing Editor

Graz University of Technology, Graz, Austria