bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of Sense of Community and Civic Engagement on the Well-Being of Student Executive Board Members of Politeknik Negeri Bandung
Authors: Maulana Muhammad Yunus , Bakhrun Akhmad
Published: October 2024

AbstractHigher education institutions are expected to create environments that support positive growth, foster civic engagement, and enhance competencies. Hence, this study is examining the influence of sense of community and civic engagement as the antecedents of psychological aspect of student’s wellbeing. This research employs a quantitative approach using the SEM-PLS method. The questionnaire is completed by 53 respondents from a population of 222 of the Student Executive Board Members of Polban. The results show a significant difference in the influence of sense of community and civic engagement on students' wellbeing. This study presents a new evidence that a sense of community plays a crucial role in fostering civic engagement and student well-being, a connection that has not been previously explored in similar studies within the context of vocational higher education. However, civic engagement has minimal impact, direct or mediated. This study recommends that campuses prioritize community-building to enhance positive student development.---------------AbstrakPerguruan tinggi diharapkan menjadi lingkungan yang mendukung pertumbuhan positif, bangkitnya keterlibatan warga negara serta peningkatan kompetensi sebagai calon profesional. Maka dari itu, penelitian ini menguji pengaruh rasa kebersamaan dan keterlibatan sipil sebagai anteseden dari aspek psikologis kesejahteraan mahasiswa. Penelitian menggunakan pendekatan kuantitatif dengan metode SEM-PLS. Kuesioner penelitian diisi oleh 53 orang sampel dari populasi berjumlah 222 orang pengurus dan anggota BEM Polban kabinet Pilar Impresif. Hasil analisis menampikan adanya signifikansi yang berbeda antara rasa kebersamaan dan keterlibatan sipil terhadap kesejahteraan mahasiswa. Penelitian ini menunjukan bukti baru bahwa rasa memiliki berperan penting dalam mendorong keterlibatan sipil dan kesejahteraan mahasiswa yang belum pernah diungkap dalam kajian serupa pada konteks pendidikan di perguruan tinggi vokasi. Adapun, pengaruh keterlibatan sipil, baik secara langusng maupun sebagai mediator rasa memiliki terhadap kesejahteraan mahasiswa, hasilnya ternyata tidak signifikan. Hasil kajian ini menunjukan bahwa arah kebijakan perlu memprioritaskan internalisasi aspek rasa kebersamaan secara efektif terhadap perkembangan positif mahasiswa.
Football is god and coach is sermon: religious concepts in German football fan communication
Authors: Belyutin Roman Vyacheslavovich
Published: October 2024

The article discusses correlations between sports and religious conceptual frameworks on the example of German football fan discourse. The latter is viewed as peculiar linguo-semiotic space that includes verbal and non-verbal symbols to represent fans' world view, as well as a framework of precedent phenomena (names, situations, sayings) and texts. The study uses such methods as frame analysis and other corresponding research techniques and procedures. Processing and organizing diverse empirical material of different genres which explicitly or implicitly highlight the above mentioned correlations resulted in distinguishing the following (proto)type thematic significative layers of the conceptual framework ‘Religion' in German fan discourse. These significative layers develop new meanings relevant to sports: ‘Lords of the Higher Worlds', ‘Divine Worship', ‘Spiritual Practices', ‘Sacred Sites', ‘Religious and Moral Precepts', ‘Saints and Sinners', ‘Religious Ceremonies', ‘Faith Communities' and others. The paper shows that football fans refer to religious concepts and frames in their discourse not only to represent significant and meaningful culture specific concepts (favourite team, favourite players and coaches, team icons, competition with the fans of other teams, emotional seesaw and others) but also to make their (value) judgment and interpretation. Other ways to study the stated issue are proposed: to compare how sports and religious discourses overlap in two and more languages, to discover the degree of efficiency of mirror mapping, i.e. the frequency of sports concepts in religious discourse.
On the Issue of Personal Socialization in the Information Society
Authors:   Yuri Gagarin State Technical University of Saratov, Naydenova Marina V. , Sytko Vladimir O. ,   Yuri Gagarin State Technical University of Saratov
Published: October 2024

This article discusses the issues related to the theoretical generalization and methodological conceptualization of the problem of formation of the individual’s worldview in the modern information society. The peculiarity of the latter, determined by a high degree of social virtualization, is the active dynamics of the role positions of the subject of social relations in the conditions of publicity. At the empirical level we have revealed that the leading role identification for adolescents are: ethno-national role identification, socio-professional, family and gender. Conclusion dwells upon the fact that in such individuals the general level of information dependence increas-es, associated with both excessive saturation with content, and with the improvement of information and com-munication tools and their availability to the average user. Internet addiction in modern socio-cultural conditions is a kind of information addiction, which, for ordinary participants of the information society, turns into a certain norm of life in the civilized world.
A Review of Research on Bullying and Its Impunity in the School Environment
Authors:   Dorzhi Banzarov Buryat State University, Poselskaya Anastasia N.
Published: October 2024

The article presents the results of a literary review on the impact of impunity on the occurrence of bullying in the educational environment and the creation of a safer and fairer school space in this regard. The aim of this study is to conduct a comprehensive analysis of existing studies on the impact of impunity on the occurrence of bullying in the school environment, as well as to develop recommendations for preventing and solving this problem. The study reveals that the lack of adequate punishment for aggressive actions encourages individu-als to continue bullying specific members of the school community without fear of repercussions. Based on the results of the consideration of the essence of the problem, represented in scientific publications, the author offers recommendations for the prevention and suppression of bullying in modern school conditions. The re-sults of the study can be used to develop effective programs to prevent this negative phenomenon, as well as to raise awareness of the scientific community about the role of impunity in the formation of aggressive behav-ior of schoolchildren.
Comparative Analysis of Data Analytics Approaches in the Context of Business Digital Transformation
Authors: Kuzmin M. A.
Published: October 2024

The article is dedicated to exploring data analytics approaches within the context of business digital transformation. The role of data in enhancing the efficiency of enterprises is highlighted, as data facilitates informed managerial decision–making and strengthens competitive advantages. It is emphasized that the effective use of data requires not only advanced infrastructure and personnel competencies but also a systematic approach that integrates various methods of data analysis and justifies the transition to specific business analytics strategies. A comparative analysis of three primary data analytics approaches – analog, digital, and big data – is conducted. A data analytics model is presented, reflecting the evolution and synergetic integration of these approaches. The study identifies a unified orientation in data analytics, aimed at improving business efficiency through the application and value of business analytics. The distinct characteristics of the transition from analog to digital approaches and from digital to big data analytics are determined, with a focus on changes in infrastructure, personnel competency requirements, and the applicability of data analysis methods. The study concludes with the recognition of the necessity of applying synergetic and systematic approaches to data analytics in the context of digital transformation, which contributes to maximizing the effectiveness of business analytics.
Bernstein polynomials iterative method for weakly singular and fractional Fredholm integral equations
Authors:   University of Oradea, Department of Mathematics and Informatics, Universitatii Street no. 1,
410087 Oradea, Romania
e-mail: abica@uoradea.ro, Bica Alexandru Mihai , Satmari Zoltan ,   University of Oradea, Department of Mathematics and Informatics, Universitatii Street no. 1,
410087 Oradea, Romania
e-mail: zsatmari@yahoo.com
Published: October 2024

Abstract. A novel iterative method based on Picard iterations and Berstein polynomials is proposed for solving weakly singular and fractional Fredholm integral equations. On a uniform mesh, at each iterative step a Bernstein type spline is constructed by using the values computed at the previous step. The error estimates are obtained in terms of the Lipschitz constants and the convergence of the method is proved. Some numerical examples are presented in order to illustrate the accuracy of this iterative method.
Mathematics Subject Classification (2010): 65R20.
Keywords: Weakly singular and fractional Fredholm integral equations, iterative numerical method, piecewise Bernstein polynomials spline, order of convergence.
Prospects, Challenges and Implications of Deploying Artificial Intelligence in Tax Administration in Developing Countries
Authors: MPOFU Favourate Y.
Published: October 2024

Artificial intelligence (AI) can help transform tax administration in developing countries by automating certain functions, pinpointing patterns and irregularities, and forecasting future tax collections. AI can enhance the effectiveness, efficiency, and tax justice in tax administration. This paper discusses the development and deployment of AI in tax administration in developing countries. This paper outlines different AI technologies, the opportunities and challenges of using AI in tax administration, and the possible implications. The paper established that there is an increasing interest in harnessing AI in tax administration in developing countries. The challenges of deploying AI include a lack of quality data, inadequate technical expertise, and a paucity of clear legal and regulatory frameworks to govern the application of AI. The benefits of AI in tax administration were found to encompass increased tax revenue mobilisation and the attainment of sustainable development goals. Reduction in corruption, improved tax compliance, reduced tax avoidance and evasion among other benefits. The paper recommends that policymakers and tax authorities in developing countries improve data quality to support AI adoption, invest in AI research, innovation and development while supporting training in AI as well as the creation of a clear legal and regulatory framework.
JEL classifications: H20, H21, H26, O33, K3
Article History: Received: June 22, 2024; Reviewed: August 29, 2024; Accepted: September 17, 2024; Available online: September 23, 2024.
Socialization on the Role of Islamic Banking in Encouraging the Progress and Development of MSMEs
Authors: Noval  , Abdul Jalil  , Ahmad Haekal  , Fatma  , Khusnul Khatimah  , Muh. Imam Fur’qan  , Moh. Mukhasyaf
Published: October 2024

Micro, Small, and Medium Enterprises (MSMEs) play a vital role in the Indonesian economy, contributing significantly to economic growth, employment, and poverty alleviation. However, limited access to financing sources that suit their needs is a significant obstacle for MSMEs in developing their businesses. This research explores the role of Islamic banking as an alternative solution in supporting the development of MSMEs. Through community service activities at SMA 1 Sidue, we delivered material on Islamic banking and developing MSMEs to 100 student participants. An interactive lecture method was used to improve understanding, followed by a discussion session to encourage active participation of the participants. The evaluation results showed an increase in students' understanding of Islamic banking, including financing products that comply with Sharia principles and the challenges and opportunities faced by MSMEs. This activity is expected to educate MSME players on the benefits of Islamic banking and strengthen their capacity to access more ethical financing. Thus, Islamic banking can be a strategic partner for MSMEs, assisting them in sustainable business growth and development.
Kematangan risiko keamanan informasi layanan TI menggunakan pendekatan NIST dan standar ISO 27001:2013 (Studi kasus: Bapenda Provinsi Jawa Tengah)
Authors: Aminudin Agus , Supriyanto Aji
Published: October 2024

Penerapan Teknologi Informasi (TI) seringkali menimbulkan risiko, seperti salah proses dari aplikasi, pencurian data serta kerusakan data. Dengan semakin besarnya risiko, maka diperlukan pengendalian (kontrol) yang semakin besar pula. Untuk itu perlu dilihat apakah sistem yang berjalan sudah dilengkapi dengan kontrol yang memadai. Badan Pengelola Pendapatan Daerah (BAPENDA) Provinsi Jawa Tengah telah memanfaatkan TI dalam aktivitasnya. Tidak adanya standar keamanan informasi yang memadai, memiliki dampak pada data atau informasi yang kurang terjaga, baik dari sisi kerahasiaan (Confidentially), integritas (Integrity) dan ketersesiaan (Availability). Penelitian ini bertujuan untuk mengukur kematangan risiko Keamanan Informasi (KAMI), seperti melakukan asesmen TI yang di kelola BAPENDA, seperti aplikasi layanan pembayaran pajak kendaraan bermotor, Android (New Sakpole) termasuk infrastruktur TI. Hasil dari Maturity Level KAMI di BAPENDA pada klausul kebijakan keamanan sebesar 0.76, organisasi KAMI 1.24, klasfikasi aset kontrol 0.63, keamanan personel 1.12, manajemen insiden KAMI 1,21, manajemen berlanjutan bisnis 0.51, keamanan fisik dan lingkungan 1.61, pengembangan sistem dan pemeliharaan 2,94, kontrol akses 4,18, manajemen komunikasi dan operasi 4.58 dan, kepatuhan 2.07. Pemetaan identifikasi aset dengan NIST-CSF diperoleh beberapa Aset antara lain Aset Informasi dan data, Aset Pegawai, Aset Hardware dan Aset Software. Hasil yang diperoleh bahwa Aset di BAPENDA memiliki risiko tinggi (High) Risk Avoidance sehingga memerlukan mitigasi dengan menggunakan kontrol NIST dan Annex ISO-IEC 27001:2013.
Computed tomographic features of Morel-Lavallée lesions in 3 cats
Authors: Dziedzic-Nyrka Natalia , Dancer Sumari , Kaipak Emma Fredholm , Nowak Lina , Pinilla Manuel , Carrera Ines , Garcia-Pertierra Sofia , Clements Dylan N. , Schwarz Tobias
Published: October 2024

OBJECTIVE

To describe the CT features of Morel-Lavallée lesions (MLLs) and their association with trauma in cats. This study aimed to investigate whether MLL fluid in cats accumulates between the dermis and deep fascia near superficial trauma, exhibits a vertical attenuation gradient, and shows no or only mild contrast enhancement on CT images.

ANIMALS

3 young cats: a 1-year-old neutered male domestic shorthair cat, a 2-year-old neutered male domestic shorthair cat, and a 3-year-old neutered female British Shorthair cat.

CLINICAL PRESENTATION

The clinical presentation of the 3 cats in the study involved recurrent swelling and fluid accumulation affecting at least 1 pelvic limb following trauma.

RESULTS

In all cases, there was a fluid-filled space deep to the skin and superficial subcutaneous layer but superficial to the deep fascial plane overlying the muscular component of the pelvic limbs. The MLL fluid had a vertical attenuation gradient and no or only mild contrast enhancement.

CLINICAL RELEVANCE

Morel-Lavallée lesions are often initially overlooked, likely due to distraction by concomitant significant bone injuries, and can be mistaken for hematomas, seromas, subcutaneous edema, contusions, or cellulitis, leading to less aggressive treatment. If left untreated, MLLs present a significant risk of extensive skin necrosis compared to other types of subcutaneous swelling.
Describing Adult Heart Failure Patients-Assessment of Real-Life Data in Two Sites
Authors: Petrov I. , Konstantinov V. , Dosev L. , Jekov M. , Penchev D. , Genkova K.
Published: October 2024

Background

There is a lack of local clinical epidemiological data describing the different heart failure (HF) phenotypes in Bulgaria.

Objective

Our goal was to describe the demographic and clinical characteristics of patients with HF in two cardiological hospitals. The primary objective was to describe the demographic and clinical characteristics of patients with HF in two cardiological hospitals. The secondary objective was to further specify the profile of chronic HF patients by describing HF phenotype and the current treatment patterns of hospitalized patients. Primary and secondary outcome measures corresponding to the objectives were descriptive in nature.

Methods

This was a retrospective non-interventional study based on secondary anonymous pooled database analyses on management of patients with HF. The retrospective data was provided by Sqilline's Danny Platform® – analytics AI (Artificial Intelligence) platform for real-world data.

Results

The total number of patients with heart failure as main diagnosis or as comorbidity, or heart failure patients, treated on outpatient basis was 1313 (8%) as of 31th of March, 2019. The number of patients with heart failure as main diagnosis in the inpatient care was 413. The mean age of the patients was 69.77 years and more than 50% of hospitalized patients were males. Ejection fraction was available in 352 HF patients in the inpatient care as follows: 40-49% in 48 patients, less than 40% in 67 patients and more than 50% in 240 patients. The most frequently observed comorbidity in hospitalized patients with two or more comorbidities (66.1%) was as follows: hypertensive heart disease with heart failure (78.0%), atrial fibrillation and flutter (42.1%).

Conclusions

We succeeded in describing the demographic and clinical characteristics of 413 HF patients in Bulgaria. Digitalization in healthcare is an unmet need which should be addressed on a broad societal scale requiring all stakeholders to be involved.
Patients With HIV and Tuberculosis Coinfection, Treated in the Specialized Hospital for Infectious and Parasitic Diseases in Sofia, Bulgaria, for the Period 2017-2019
Authors: Strashimirov D. , Milanov Vl. , Yordanova R. , Tcherveniakova T. , Yancheva-Petrova N.
Published: October 2024

Background

Infection with human immunodeficiency virus (HIV) is the most powerful risk factor known to predispose to Mycobacterium tuberculosis infection and further progression to active disease, which increases the risk of latent TB reactivation. TB is one of the most common opportunistic infections worldwide.

Aim

The objective of the study was to describe the main clinical characteristics of the HIV – positive patients, examined for TB for 2 years (January 2017-January 2019), as well as to delineate the clinical characteristics and treatment of patients with bacteriologically confirmed TB who were treated for it, analyze characteristics of the results from the microbiological tests performed and, further, describe the patients with multidrug – resistant tuberculosis.

Study design

This was a prospective cohort study

Methods

Diagnosis was based on clinical, radiological, and microbiological data, such as smear microscopy, culture, and rapid molecular methods (Xpert MTB/RIF).

Results

The baseline CD4+ count of the patients was significantly lower compared with the other patients without coinfection (86 ± 138 cells/μcl). Acute inflammatory response Syndrome was observed in 9 patients (30%). Multidrug-resistant (MDR) M. tuberculosis was presented in three patients (20%). The predominant localization was pulmonary tuberculosis in 12 patients (80%). Six of them (50%) tested positive for MTB. The extrapulmonary involvement engaged lymph nodes in two patients and the CNS- in one.

Conclusion

TB is a disease of advanced immune suppression. Factors predicting the development of IRIS syndrome included low CD4 count, delay of diagnosis, HIV/ HCV coinfections, infection with MDR Mycobacterium tuberculosis. The principal location was pulmonary; MTB was isolated in 50% of those cases. TB meningitis should be suspected in patients with advanced immune deficiency presented with progressive neurologic deficiency changes of consciousness, and meningeal irritation.
Perception Towards the COVID-19 Vaccine Among the Paramedical Staffs
Authors: Balamanikandan P. , Shetty P. , Shetty U. A.
Published: October 2024

Introduction

Broad access to efficacious immunizations is important for mitigating the COVID-19 pandemie. Healthcare personnel, particularly paramedical workers, may be more susceptible to infection during the covid pandemic due to a variety of causes. The purpose of this research is to assess paramedical staff members' opinions on the COVID-19 vaccine.

Methods and material

A research study was conducted on paramedical personnel at A B Shetty Memorial Institute of Dental Sciences in Mangalore, India, using an online survey and SPSS 21 for data analysis. The survey included questions about vaccination knowledge, type, and dosage based on literature and international recommendations.

Results

The average age of the 61 participants in the research was 45.23 ± 9.66 years, with 43 females and 18 men. While all research participants knew that the COVID-19 vaccine is accessible in India, only 59% were aware of the range of vaccines that are developed and produced in India. Of those surveyed, 42.6% felt comfortable taking the COVID-19 vaccination made in the nation. Participants assessed their likelihood of contracting the illness even after immunization as high (24.6%) and low (39.3%). Of those who have received COVID-19 immunization, 55.7% believe that adverse effects might occur.

Conclusions

The World Health Organisation (WHO) is lowering infection rates and developing a COVID-19 vaccine. Paramedical Staff who worked in the hospital are more vulnerable because of patient interaction and insufficient training on infection prevention.
The Effect of Night Shift Work on Health of Healthcare Workers
Authors: Cekova I. , Stoyanova R. , Marinova E. , Vangelova K.
Published: October 2024

Objectives

Night shift work and long working hours are associated with increased health risk. The aim of the study was to follow the effects of night shift work on morbidity of hospital healthcare workers (HCWs), determinants of ill health and mediating factors.

Materials and methods

A cross-sectional anonymous survey, comprising 2,690 HCWs and including information on individual and behavioral variables, working hours, shift system, and sleep quality was carried out. The health status questionnaire included a list of 13 groups of diseases.

Results

Great proportion of the studied HCWs had night shifts, often 12-hour and long working hours weekly. Cardiovascular diseases (CVDs) were with the highest prevalence, followed by digestive and endocrine diseases. The proportion of chronic diseases was higher with ex-night and night shift workers, reaching statistical significance for CVDs. Odd ratios (OR) showed increased risk of CVDs (OR = 1.98; ρ < 0.01), endocrine, digestive, mental and malignant diseases with night work. Sleep quality index was statistically significantly associated with CVDs, endocrine and digestive diseases and mental illness, and higher BMI – with CVDs and endocrine diseases. In conclusion, our data confirmed the increased health risk in HCWs, working night shifts and long working hours, especially for CVDs, with a mediating effect of their sleep quality.
Exploring Therapeutic Potential of Malcolmia Aegyptiaca Spr. and Matthiola Livida DC. Extracts in Rat Models Using Hot-Plate, Writhing and Carrageenan-Induced Paw Edema Tests
Authors: Chouikh A. , Ben Ali A. , Bousbia Brahim A.
Published: October 2024

Background

Malcolmia aegyptiaca (locally known as El Harra) and Matthiola livida (locally known as Chegara) are medicinal plants traditionally used to relieve pain and reduce inflammation. Little is known about the flavonoid content or the analgesie and anti-inflammatory properties of these plants.

Aims

The aim of the study was to explore the natural therapeutic potential of two xerophytic plants, M. aegyptiaca Spr. and Matthiola livida DC, for analgesic and anti-inflammatory activities using hot-plate, writhing and carrageenan-induced paw edema tests.

Materials and Methods

Flavonoid content was quantified using the AICI3 as reagent. Analgesic activity was assessed using hot-plate (in concentrations of 30 to 80 mg/kg) and writhing tests (20 and 40 mg/kg) in the rats treated. Anti-inflammatory activity was evaluated using the carrageenan-induced paw edema model in rats treated with two doses (25 and 50 mg/kg) of the two plant extracts.

Results

M. livida extract had a higher flavonoid concentration compared to M. aegyptiaca extract. Both the M. aegyptiaca and M. livida extracts exhibited dose-dependent analgesic effects in the hot-plate test, with higher doses inducing a stronger and more sustained analgesia. M. aegyptiaca extract displayed weaker dose-dependent anti-nociceptive effects in the writhing test compared to the standard NSAID indomethacin. The anti-nociceptive effects of the M. livida extract were mainly observed at the higher dose in the writhing test. Both extracts demonstrated dose-dependent anti-inflammatory activity in the carrageenan-induced paw edema model, with higher doses exhibiting greater inhibition at later time points.

Conclusion

The M. aegyptiaca and M. livida methanolic extracts possess analgesic and anti-inflammatory properties, supporting their traditional use for the pain and inflammation management. Further research is needed to elucidate the active components and mechanisms of action responsible for these activities.
Semaphorins: Novel Insights on Their Emerging Multifaceted Roles in the Evolving Landscape of Breast Cancer
Authors: Popov Ts.
Published: October 2024

Semaphorins, initially identified as phylogenetically conserved axon guidance molecules, comprise an extracellular signaling protein family involved in various biological events that regulate the development, tissue homeostasis and cancer progression of many organ systems. In recent years, the focus of research has expanded to investigate the roles of semaphorins in cancer. Semaphorins have emerged as crucial regulators in the pathogenesis of breast cancer (BCa). This review article aims to provide an overview of the contemporary knowledge regarding semaphorins, their diverse tumor-modulating properties, and their clinical application in BCa. Specifically, six semaphorins (SEMA3C, SEMA3E, SEMA4A, SEMA4C, SEMA4D, and SEMA7A) have been demonstrated to promote tumor progression in terms of BCa. Six additional members (SEMA3A, SEMA3B, SEMA3F, SEMA4B, SEMA6B, and SEMA6D) have been associated with tumor suppression. Several semaphorins (SEMA4C and SEMA7A) are considered putative diagnostic and prognostic biomarkers in BCa. Exploring and elucidating the intricate functions of semaphorins and their viability as therapeutic targets is an intriguing avenue of research that can improve BCa outcomes.
Steroid Treatment Focused Management of Graves’ Ophthalmopathy
Authors: Condeng Y. H. , Umar H. , Aman A. M. , Rasyid H. , Bakri S. , Iskandar H.
Published: October 2024

Introduction

Graves' disease (GD) is an autoimmune disease that affects the thyroid and the eyes. Graves' ophthalmopathy (GO), an autoimmune disease, usually appears 18 months after GD diagnosis. Clinical activity and disease severity determine the strategy, with steroid treatment recommended during active disease progression.

Aim

This review aims to provide an overview of steroid therapy in the treatment of Graves' ophthalmopathy, discussing its efficacy, protocols, and considerations.

Materials and Methods

We reviewed the papers focusing on management recommendations and assessed peer-reviewed publications using the following keywords: "Graves' disease", "Graves' ophthalmopathy", "Graves' orbitopathy", "glucocorticoids".

Results and Discussion

Steroid therapy, especially glucocorticoids, is a primary pharmacologic intervention for clinically active GO. Intravenous administration has shown superior outcomes compared to oral administration, with a recommended protocol that uses a cumulative dose of 4.5 grams methylprednisolone. High-dose systemic glucocorticoids possess anti-inflammatory and immunosuppressive characteristics and are efficacious in managing moderate to severe active GO. Second-line therapies, such as methylprednisolone monotherapy or in com-bination with cyclosporine, may be considered.

Conclusion

Graves' ophthalmopathy re-quires intravenous glucocorticoids during the active phase. Intravenous glucocorticoids are more effective and better tolerated than oral glucocorticoids. Patients with Graves' ophthalmopathy require individualized treatment plans that address contraindications and side effects to improve outcomes and quality of life.
Identification and expression of microRNA-34a-3p and its target Rapamycin-insensitive companion of mTOR (RICTOR) in polycystic ovarian syndrome in South Indian population
Authors: Saravanan Manya , P Ameya K , P Ashikha Shirin Usman P , Sekar Durairaj
Published: October 2024

Objectives

Polycystic Ovarian Syndrome (PCOS) is a complex condition affecting 4% to 26% of the world-wide population and is characterized by enlarged ovaries and cysts. These cysts are actually immature ovarian follicles that have failed to mature and release an egg, which is a process known as anovulation. This study aims to explore the potential of miRNA as therapeutic and diagnostic biomarkers for PCOS, focusing on the identification and expression analysis of novel candidates like miR-34a-3p and its target Rapamycin-insensitive companion of mTOR (RICTOR). The objective is to enhance our understanding of the molecular mechanisms associated with PCOS, particularly the roles of miRNAs in its pathogenesis. In future, we plan to test miR-34a-3p mimics/inhibitors and RICTOR downregulation to improve insulin sensitivity and ovarian function. We will also explore combined therapies and conduct trials to assess their efficacy and safety in PCOS patients, aiming to develop practical treatments for PCOS.

Methods

National Centre for Biotechnology Information (NCBI) database, TargetScan, and miRbase were explored to identify the novel miRNA candidates, resulting in the discovery of miR-34a-3p. Secondary structure was constructed using RNA Fold, and Ct and melt curve analysis assessed its statistical expression levels. Additionally, similar research was conducted to analyze the expression levels of RICTOR, a target of miR-34a-3p.

Result

The secondary structure showed miR-34a-3p has a minimum free energy of −47.20 kcal. Additionally shows dysregulation in both miR-34a-3p and RICTOR in individuals with PCOS. Furthermore, overexpression of RICTOR and decrease in miR-34a-3p levels suggest their possible role in the pathogenesis of PCOS.

Conclusion

In PCOS, miR-34a-3p is downregulated, and there’s an inverse relationship between miR-34a-3p and RICTOR levels. qRT-PCR results showed high RICTOR expression in PCOS patients. RICTOR plays a crucial role in the mTOR pathway, affecting insulin signaling, metabolism, and cellular growth, which are all implicated in PCOS.
Predictors of mortality in patients with early versus late onset of septic shock. A prospective, observational and comparative pilot study
Authors: Botoș Ioana Denisa , Pantiș Carmen , Negrău Marcel Ovidiu , Bodolea Constantin , Botea Mihai Octavian , Hirișcău Elisabeta Ioana , Puia Cosmin Ion
Published: October 2024

Introduction

Outcome and predictors of early- and late-onset septic shock are still controversial. The aim of the study was to compare the relevant predictors of 28-day mortality in early- and late-onset septic shock and other non-septic critical illnesses.

Material and Methods

We conducted a prospective, observational, pilot study. A group of 46 patients with early septic shock and 42 nonseptic critically ill patients from the emergency department and 56 patients with late septic shock from the hospital were enrolled. On admission to the ICU, the most important potential predictors of 28-day mortality were assessed.

Results

In terms of predicting 28-day mortality, a higher mNUTRIC score was the only common predictor for all three groups. Multi-drug resistant (MDR) bacterial aetiology was a common predictor in both forms of septic shock. Older age, female gender, increased neutrophilto-lymphocyte ratio (NLR) and increased need for vasoactive agents were common predictors in late septic shock and non-septic critically ill patients. Increased red blood cell distribution width coefficient of variation (RDW-CV) was predictor in early septic shock and non-septic critically ill patients. Central venous-arterial carbon dioxide difference (Pcv-aCO2) was predictor in patients with early septic shock. Inflammatory index and MDR carrier status were predictors in non-septic critically ill patients.

Conclusions

A higher mNUTRIC score is a predictor of 28-day mortality in early and late septic shock and in critically ill non-septic patients. MDR aetiology was predictive of 28-day all-cause mortality in both types of septic shock, and Pcv-aCO2 was predictive in patients with early septic shock.
Analysis and Research on Color Encoding and K-means Clustering Algorithm in Lingnan Landscape Design
Authors: Tan Hongyan
Published: October 2024

As a prominent visual phenomenon, the color environment influences the landscape design of the Lingnan region in three aspects: shape, color, and texture. The purpose of this paper is to examine the landscape nature of color by analyzing the psychological perception characteristics of color and the evolution of Lingnan’s color landscape system. We propose color clustering extraction methods for both single and batch Lingnan landscape images, combining them with color space conversion algorithms like RGB and YIQ to extract colors and segment Lingnan landscape images. We look at the performance parameters of various reconstructed images at various compression ratios. We also draw the performance convergence curves of the clustering algorithm, the JPEG, and the JPEG2000 algorithms to talk about how well they code. Taking the Lingnan region (Guangzhou) as the main object of analysis, we divide the regional color qualities and analyze the evolution and development of landscape color characteristics in the Lingnan region. Most of the Lingnan architectural landscapes have color brightness values in the medium-high range of 5-7. For wall color brightness, most of the brightness class level values are in the high brightness range of 7–10, followed by the medium brightness range of 4–7, and a small portion is in the low brightness range of 1-3.
Research on the Teaching Effect of Virtual Reality Technology in Simulated Vocal Performance Environment
Authors: Yi Heng
Published: October 2024

Traditional teaching methods are often relatively difficult to meet the diverse learning needs of students. For the status quo of vocal music teaching, this paper promotes the development of vocal music teaching in colleges and universities through the use of VR technology. Systematically analyzing the relationship between vocal music and virtual reality technology and its characteristics, the interrelation between the two is summarized. According to the principle of camera imaging to collect samples, after using the SIFT algorithm to detect and match the feature points of the collected samples so as to determine the spatial location of these feature points, realize the camera calibration, and obtain the sparse point cloud. The obtained sparse point cloud model is stored in PLY format files, and the PLY format files are imported into the Unity3D platform for color rendering to complete the construction of the vocal performance scene. The effect of vocal music teaching combined with VR technology was analyzed using statistical methods. The data show that the vocal music teaching mode combined with VR technology (ANOVA value 22.65) is significantly better than the traditional teaching mode (ANOVA value 27.85) in terms of the accuracy of students’ vocal performance speed, in addition to the same in terms of the comparison of the mastery of vocal music knowledge and skills. This study improves the traditional oral teaching method of music and traditional vocal music teaching mode and also breaks the limitations of time and space, providing more practice opportunities for the majority of music learners.
Research on the Integration of Laban Movement Theory and Multimedia Technology to Promote the Cultural Inheritance of Chinese Opera
Authors: Zhang Muchen , Yang Yi
Published: October 2024

In the background of the new era, the rapid development of networking and digitization has played a certain role in promoting the dissemination and development of opera culture. First, we normalize the opera action data of the recorded opera performers. Then, based on Laban’s movement theories, we propose a parallel one-dimensional convolutional network and recurrent neural network model that adds a way for attention to splice, encode, and decode the time sequences in the opera action data. Next, we employ the full connection layer to generate a sequence of Laban opera action symbols, enabling the recognition of Laban opera actions. Ultimately, we integrate the model with virtual reality technology to establish a virtual opera learning system. The model tests show that the suggested Laban opera action recognition and automatic generation method works better than the rule-based and template-matching methods for the same period. There is a significant difference (P<0.05) between the experimental group that used the opera virtual learning system and the control group, which was made up of opera fans who learned the old-fashioned way. This was seen in the post-test of technical quality, which looked at posture and foot movements. This paper’s designed system can enhance the interest and impact of opera enthusiasts in learning opera culture while also offering a reference path for the transmission of opera culture and related fields.
Data-driven decision making and production optimization of higher mathematics in industrial science
Authors: Wen Xiaonan , Dong Liwei
Published: October 2024

Since complex industrial chemical systems contain huge process data, these process data will present the operation characteristics and laws, and the use of appropriate methods to analyze the data is one of the feasible directions for fault diagnosis. In this paper, we analyze data from industrial chemical production processes using the support vector machine algorithm as our decision-making approach. Considering the large amount of data generated in industrial chemical systems and its nonlinear characteristics, this study applies Gaussian and non-Gaussian space to obtain the high-dimensional characteristics of the data before putting it into an SVM model. The rotary drying kiln production simulation experimental process is optimized by applying the fault diagnosis method, with the thermal efficiency shown by several tests being close to each other. The method proposed in this paper has obvious advantages in terms of search efficiency for a feasible global optimal solution.
Cultivation Methods and Effectiveness Assessment in Teaching University Language Courses in the Context of the Artificial Intelligence Era
Authors: He Xi , Huang Mingjie , Zou Hongju , Deng Taiping
Published: October 2024

Aiming at the blind spots of university language course learning in the age of artificial intelligence, this paper builds a technical framework of intelligent cultivation method with a university language intelligent question bank, classroom student behavior recognition model, and intelligent teaching evaluation model as the main modules. The knowledge point mastery model is constructed, the knowledge point test question matrix is composed, and the learner similarity calculation is carried out to design the intelligent question bank. Introduce the YOLO algorithm to solve the problem of occlusion and small target detection of students’ behavioral actions, and propose a student behavior recognition model based on the improved YOLOv5. Intelligent selection of language teaching evaluation indexes, adoption of the recursive goal evaluation method, and establishment of the teaching evaluation model. In the evaluation of the cultivation method, HZ University is used as the research site, and experimental and control classes are set up to conduct comparative experiments. The language score of the experimental class is significantly higher than that of the control class by 4.83 points (P<0.05), and the mean values of all dimensions of learning problem-solving ability are higher than those of the control class, which also show significant differences (P<0.05). The experimental class also outperformed the control class in a number of aspects, including course learning level, cooperative communication, pre-study, and classroom learning status.
Machine Learning-Enhanced ORB Matching Using EfficientPS for Error Reduction
Authors: Li Zhanrong , Su Haosheng , Jiang Chao , Han Jiajie
Published: October 2024

The study comes up with a new way to improve the accuracy of image matching in binocular vision systems, especially those that are mounted on vehicles. It combines machine learning with the ORB (Oriented FAST and Rotated BRIEF) image-matching algorithms. Standard ORB matching frequently encounters mismatches in complex and repetitive environments. To minimize false positives in matches, our strategy utilizes the EfficientPS (Efficient Panoptic Segmentations) algorithm, a panoramic segmentation technique that uses machine learning in conjunction with ORB. The procedure begins with the EfficientPS approach, which delivers fine-grained and efficient segmentation of images, assigning semantic category labels and unique identifiers to each pixel. The ORB feature point matching process is refined using semantic data to filter out mismatches between foreground objects and the background effectively. This machine-learning-augmented method significantly decreases the frequency of erroneous matches in intricate settings. Empirical findings from the KITTI dataset demonstrate that in non-targeted environments, the accuracy of our proposed method (0.978) is marginally less than that of LoFTR (0.983). Still, it surpasses other methods when utilizing 50 ORB parameters. In more intricate situations, such as multi-target scenarios with an increased number of ORB parameters (200), our method maintains a high level of accuracy (0.883), outperforming the conventional ORB (0.732) and rivaling the performance of DL-BDLMR (0.790) and ORB-MFD-FPMC (0.835). Our method’s processing time is competitive and slightly higher than the standard ORB, but it improves accuracy. In scenarios without targets and with single targets, our method’s processing time (0.195 seconds and 0.211 seconds, respectively) is greater than that of ORB and ORB-MFD-FPMC. Yet, it is significantly lower than that of LoFTR. In multi-target scenarios, our method’s processing time (0.226 seconds) is considerably better than LoFTR’s (0.445 seconds), effectively balancing processing speed and accuracy. We highlight the efficacy of incorporating machine learning to enhance the robustness of image-matching algorithms in dynamic and complex environments.
Research on the individualized teaching of Chinese in higher vocational colleges based on cloud computing
Authors: Shang Yuanyuan
Published: October 2024

Whether it is the development trend of education in the whole world or the quality education that is being comprehensively promoted in China, more and more attention is paid to the students’ leading position in the entire education process, respect for students’ differences, and the importance of students’ personality development. This paper uses a distributed cloud computing platform to construct a clustering algorithm based on K-means-CE to categorize language learner characteristics based on language learner characteristics combined with the Felder-Silverman style model. Then, the ItemCF algorithm of collaborative filtering recommendation is studied, and the combined similarity calculation method is proposed to deploy the recommendation algorithm to the Hadoop cloud computing platform to realize parallelized calculation and improve the efficiency of the personalization algorithm. The differences in learner types in the information input, information processing, learning attitude, and learning behavior input dimensions of the learning style analysis model constructed in the study will be expressed in the performance (P<0.05). The total cognitive load of the cloud computing-based personalized teaching group of higher vocational Language (M=65.26, SD=8.58) is lower than that of the conventional teaching group (M=66.23, SD=10.09). The personalized teaching method based on cloud computing is better than the conventional teaching in refining the learners’ knowledge structure. The learners’ achievement rate of the target learning level is higher, and the effect of the personalized teaching is more significant.
Artificial Intelligence Enabled Teaching Optimization for General Studies Elective Courses
Authors: Li Bo
Published: October 2024

Network general knowledge course is a meaningful way to cultivate comprehensive quality talents in Chinese higher education based on the modern information technology environment, and the optimization of network general knowledge course teaching is directly related to whether the network general knowledge course can be effectively implemented, which affects the overall effect of talent cultivation. In this paper, starting from the purpose and goal of humanities general education courses, the optimization direction of teaching general education courses using artificial intelligence is clarified. Skeletal sequence feature extraction is used to obtain students’ general education classroom behavior data, and a stackable multimodal attention module consisting of a self-attention layer and a multimodal co-attention layer is designed for feature fusion and action prediction based on multimodal characteristics. After data integration and processing, the HGCL-LG network model is proposed to complete the diagnosis of students’ general knowledge cognition. The trend of interest assessment and multimodal model calculation value is consistent. In contrast, the student’s interest attention in general knowledge classroom above 0.33 accounts for more than 40% of the overall information, and the interest attention is good. Students’ scores on the objective questions of general knowledge are good; the average score range is between 1.5 and 2 points, the degree of dispersion is small, and the mastery of basic knowledge of general knowledge is good.