bluuebunny/crossref_metadata_2025 huggingface dataset:
The Role of Educational Institutions in Countering Political Polarization: Building Inclusive Communities and Civic Engagement
Authors: Muhtar Muhtar , Setiyono Budi , Fitriyah Fitriyah , Sardini Nur Hidayat
Published: May 2024

Political polarization has become increasingly prevalent worldwide, posing significant challenges to social cohesion, democratic governance, and civic participation. Various factors, including ideological divisions, socio-economic disparities, and the rise of digital echo chambers, have exacerbated this phenomenon. Amidst this backdrop, educational institutions have emerged as pivotal actors in addressing political polarization by fostering inclusive communities and promoting civic engagement among students and faculty members. This study aims to identify the key challenges and opportunities faced by educational institutions in addressing political polarization, examine the effectiveness of existing interventions and programs, and propose evidence-based recommendations for enhancing the role of educational institutions in building inclusive communities. This study employs a qualitative research design utilizing a literature review as the primary methodological approach. The data for this research are obtained from various scholarly sources, including academic journals, books, reports, and policy documents, accessed through academic databases, institutional repositories, and online libraries. In conclusion, this research sheds light on the crucial role that educational institutions play in combating political polarization by fostering inclusive communities and promoting civic engagement among students. Through an analysis of the various mechanisms and strategies employed, it becomes evident that educational institutions are vital platforms for bridging ideological divides and nurturing a culture of tolerance and respect for diverse perspectives.
Development of an Evangelism-Based Missiology Course Curriculum
Authors: Malau Oloria , Sitompul Sabar Rudi , Sitorus Septina Rumiris , Sirait Sarah
Published: May 2024

This research aims to produce teaching materials that follow the progress of the times. To produce teaching materials that suit the equipment needs of teachers as educators and evangelists. To increase the awareness of students who work as educators and evangelists. To determine the suitability of teaching materials to equip students to become evangelists and educators. The development research uses a questionnaire instrument with a Likert scale with five alternative answer choices. Data analysis was carried out using quantitative descriptive analysis techniques. This development research resulted in a new curriculum for the Missiology course in the PAK Study Program. Curriculum development refers to the 4 D model, namely the Define, Design, Development, and Disseminate Stage. However, this research shows a feasibility assessment only up to stage 3, namely the development stage. According to the Curriculum Expert, the result was 75%, so it was categorized as agreeing or feasible. The results of the curriculum feasibility assessment by the mission practitioner experts were
Utilization of Classroom Reading Corners to Succeed the School Literacy Movement at Malang City, Indonesia
Authors: Sumarni Sumarni , Agus Praseyoningsih Luluk Sri , Iqbal Khurshed
Published: May 2024

Literacy at the elementary school level plays a crucial role in building language skills, understanding texts, and critical thinking. Class reading corners are an effective means of increasing student literacy. This research explains student literacy problems and the use of classroom reading corners to make the School Literacy Movement or Gerakan Literasi Sekolah (GLS) at SDN Lesanpuro 2 Malang City a success. The research approach uses descriptive qualitative with a case study type. The subjects in this research were teaching staff and students in grades IV–VI for the 2022/2023 academic year. Observation, interviews, and documentation were carried out in data collection. The research results show that teachers are important in utilizing the classroom reading corner. Utilizing a classroom reading corner is very effective in making the school literacy movement successful if the arrangement is interesting, the activities are varied, and the circulation of reading materials is carried out continuously. Literacy-based learning using the reading corner at SDN Lesanpuro 2 Malang City is carried out through several processes, namely (1) Planning, (2) Exploration, (3) Fairy Tale Show or Reading Together, (4) Book Discussion, (5) Literacy Competition. Continuous use of classroom reading corners can strengthen literacy culture in schools. This is reflected through an increase in the number of students actively visiting the reading corner and an increase in student academic achievement.
The Role of Innovative Leadership in Driving Educational Management Transformation
Authors: Halimah Halimah , Syafruddin Syafruddin , Earlyanti Novi Indah
Published: May 2024

Through an in-depth literature review, this literature study aims to analyze the role of innovative leadership in supporting educational management transformation. This research is qualitative research that uses a literature study approach. The main data sources are scientific literature, books, journal articles, and academic documents related to the role of innovative leadership in transforming educational management. Library studies collect data through searches for relevant literature using academic databases, digital libraries, and trusted sources. Data analysis in this study involved the synthesis and interpretation of relevant literature. The researcher identified major themes, key concepts, and significant findings from the literature. The analysis process includes compiling data, grouping information, and interpreting the meaning of the literature accessed. The research results state that innovative leadership plays a vital role in shaping and directing the transformation of educational management amidst the dynamics of development and change in the contemporary era. Innovative leadership has a very important role in driving the transformation of educational management. By creating a culture of innovation, developing adaptive management strategies, taking measured risks, motivating those around them, and managing change wisely, innovative leaders shape the future of education that is more dynamic, inclusive, and relevant.
Fama and French Three Factor Model
Authors: Irejeh Enaikpobomene Mina , Aninoritse Lisa Edafiaje
Published: May 2024

This study seeks to investigate the application of FF3FM in the Nigerian stock market. The study examined the behaviour of stock returns in relation to market beta, firm size (market equity), and book-to-market equity (BE/ME) factors. Sixty- eight (68) sample size was selected from all stocks quoted on the Nigerian Stock Exchange (NSE) from 2013 to 2022. Time series regression analysis was adopted. Monthly excess portfolio returns were regressed on firm size, excess market returns and book-to-market-equity ratio. The findings showed a strong correlation between book-to-market equity variables, firm size, and excess stock market returns and predicted portfolio returns. This suggests that the variation in stock returns in the Nigerian stock market can be explained by the FF3FM.
Corporate Social Responsibility Disclosure and Financial Performance of Listed Insurance Firms in Nigeria
Authors: Asemota Ofonime P. , Eddo Zipamone P. , Etale Lyndon M.
Published: May 2024

The backdrop of contending views that CSR is merely façade, just a marketing campaign, and that CSR disclosures among insurance companies in Nigeria are very scanty; whereas organizations desire to be seen as legitimate corporate citizens satisfying various stakeholders, justify this study to examine the relationship between corporate social responsibility disclosure and financial performance of listed insurance companies in Nigeria. Based on the ex-post-facto research design, this study employed secondary data obtained from published financial statements of sampled seven insurance firms between 2015 and 2022. These seven insurance companies are all currently listed in Nigerian Exchange Group. The data gathered was analysed using simple linear regression technique based on the ordinary least square method assisted by E-Views version 9. Three hypotheses were formulated and tested at 0.05 level of significance based on the specific study objectives, using the results of analysis. The findings revealed that corporate social responsibility disclosures have statistically positive significant relationship with earnings per share, net profit margin, and return on assets of listed insurance firms in Nigeria. It was recommended that the management of insurance companies should adopt policies that would favour appropriate increase in corporate social responsibility to enhance performance and peaceful coexistence with their host communities.
A new species of scuttle flies (Diptera, Phoridae) from the genus Menozziola Schmitz that’s a parasitoid of ants (Hymenoptera, Formicidae) Camponotus vagus Scopoli
Authors: Shevchenko Dmitry M. , Dubovikoff Dmitry A. , Disney R. Henry L.
Published: May 2024

A new species of scuttle flies, Menozziola tanaitica sp. n. that’s a parasitoid of ants Camponotus vagus Scopoli was found in the lower reaches of the Don River in the Rostov region, Russia. The new species is similar to Menozziola obscuripes (Schmitz, 1927) but differs in large number of hairs on epandrium and anal tube. This is the first confirmed case of parasitization of scuttle flies on ants in Russia.
Application of Korean Herbal Medicine for Body Fat Loss in Adults with Normal Weight Obesity: A Retrospective Chart Review
Authors:   The Korean Society of Sub-health Medicine, Kim Soohyun , Seok Jungmi , Ok Ji-Myung
Published: May 2024

Objectives Normal weight obesity (NWO) is defined as a normal body weight according to Body Mass Index (BMI) but with a high body fat percentage. NWO is associated with metabolic abnormalities and cardiovascular risk factors, thereby emphasizing the importance of body fat loss. The objective of this study is to evaluate changes in weight and body fat with NWO who were prescribed Korean herbal medicine.
Methods A retrospective chart review was conducted for subjects with NWO, within the normal weight range but with over 30% body fat percentage. These subjects were prescribed herbal medicine for a 12-week between March 2021 and May 2023. Weight (kg), body fat mass (kg), body fat percentage (%) and % Fat Free Mass (FFM) loss/weight loss (%FFML) were assessed before and after the period. Reported adverse events were evaluated for severity, causality, and system-organ classes.
Results A total of 42 subjects were included (mean±SD, weight 57.38±3.45 kg, body fat percentage 33.65±2.12%). The average weight loss rate was 6.99±3.22% with a reduction of 4.08±1.95 kg, while the body fat loss rate averaged 18.00± 0.08% with a decrease of 3.54±1.73 kg. The average of %FFML was 21.89±0.16%. Most adverse events reported were mild (90.9%) in severity, and the likelihood of events being 'Unlikely' increased from 48.8% to 64.3% as the program progressed.
Conclusions The administration of Korean herbal medicine can be considered an appropriate method to alleviate normal weight obesity, without causing serious adverse reactions. Further well-designed controlled trials and clinical studies with the analysis of hematological indicators are needed to validate its efficacy.
Narrative Review on the Safety of Mahuang and Ephedrine in the Treatment of Obesity: Focused on Liver
Authors:   The Korean Society of Sub-health Medicine, Kim Eunjoo , Lee Yun-Jin , Lim Young-Woo
Published: May 2024

Objectives The purpose of this study is to examine whether the use of Ephedrae herba and Ephedrine in obesity treatment is safe for the liver.
Methods Toxicology studies and randomized controlled trials (RCTs) from systematic review (SR), meta-analysis related to Ephedrae herba or Ephedrine, which refer to liver function were collected through Pubmed and RISS databases.
Results There were no findings that hepatotoxicity was induced by Ephedrae herba in the 2-week acute, 4-week subacute, and 13-week repeated administration toxicology studies. In the RCT studies of Ephedrae herba, Ephedrine, or herbal medicine including Ephedrae herba, there were no significant changes in liver function levels.
Conclusions This study suggests that it is difficult to find clear evidence that Ephedrae herba and Ephedrine cause liver injury.
A Literature-Based Framework for Analysing Fall-From-Height Accidents and Safety Preventive Measures in the Construction Industry
Authors: Noratira Abd Samad  , Muhammad Fikri Hasmori  , Nor Haslinda Abas  , Farzaneh Moayedi  , Mustafa Klufallah
Published: May 2024

Fall-from-height accidents are a significant cause of injuries and fatalities in construction industries. The occurrence of this accident may have been caused by any number of contributing factors. In addition, various preventive measures have been proposed to prevent this accident from occurring. To capture the true condition of a fall from height accident, the causes of the accident, the effects of the accident, and the preventive actions should be rendered out. Therefore, it is possible to analyse these accidents in order to determine their fundamental causes and implement effective preventative measures. This article presents a literature-based framework for analysing fall-from-height accidents. A literature review was conducted to examine existing studies and identify similar themes and patterns on fall from height accidents in the construction industry to illustrate the framework. Where the framework outlines the key factors that contribute to the accident. The framework comprises four main components: (1) fall from height accident, (2) causes of accident, (3) effect of accident, and (4) development of safety preventive measures. Along with the literature review that was carried out, an identification and outlining of the factors and subfactors of causes of accidents, effects of accidents, and preventative safety measures was taken out. The proposed framework provides a structured approach for analysing fall-from-height accidents, which can help organizations to identify the underlying causes of such accidents and implement appropriate measures to prevent them. The framework is flexible and can be adapted to suit the needs of other industries and organizations. The paper also discusses the future research directions.
Acceptance of Unified Communications and Collaboration Applications Among Students: A Case Study of University in Sumbawa Island Indonesia
Authors: Rauhil Fahmi  , Nurulhuda Noordin  , Fariza Hanis Abdul Razak  , Wan Abdul Rahim Wan Mohd Isa  , Ahmad Iqbal Hakim Suhaimi
Published: May 2024

Unified Communications and Collaboration (UCC) is a technology that combines conventional communication with computer technology to provide a more efficient communication platform. During the COVID-19 pandemic, UCC applications, such as Microsoft Team, Zoom Meeting, and Google Meet played major roles to support the teaching and learning process. However, the acceptance of UCC applications and their impacts on the future of teaching and learning process, especially for university students in rural areas, are concerned. Based on this, the current study aims to examine the factors that influence the acceptance of UCC applications at the University in Sumbawa Island, Indonesia using adapted theories of Unified Theory of Acceptance and Use of Technology model (UTAUT). In light, survey questionnaire was distributed online to 210 undergraduate students at the University in Sumbawa Island, Indonesia, to test seven factors, Facilitating Condition (FC), Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Motivation (MO), Collaboration (CO), and Behavioural Intention (BI) which were analysed using SPSS software. The findings reveal that PE, EE, SI, FC, MO, CO, and BI are significant factors that influence the acceptance of UCC applications. This finding will be a sound reference to improve the use of UCC applications for teaching and learning as well as help universities strategies their future teaching and learning system.
Optimization Model of Clothing Production Plan using Branch and Bound Method
Authors: Julita Nahar  , Muhammad Sayyid Alqowi  , Sudradjat Supian  , Elis Hertini
Published: May 2024

The increasing number of clothing activities in Indonesia has resulted in companies having to increase their marketing and production activities in order to obtain maximum profit. One of the factors influencing the growth of basic clothing is the price of the middle class in Indonesia. This can be a strong foundation for a long-term clothing consumer base. One of the businesses engaged in the production of clothing is a garment production business. The problem that is often faced by companies is limited resources such as raw materials, capital, time, etc. Production planning is a process to produce goods in a certain period in accordance with those predicted through the organization of resources. Therefore, production optimization is one way to optimize profit and apparel production. This study aims to apply the Integer Linear Programming model and is completed using the Branch and Bound method to obtain the optimal number of clothing production in order to obtain maximum profit. The conclusion obtained from the research is the application of the Branch and Bound method to the problem of optimizing production planning at PT. GM Tactical to obtain more optimal results compared to the actual production carried out by the company.
Assessing the Relationship Between Body Mass Index and Neural Activity of Prefrontal Cortex in Overweight Adults Using EEG-Resting State Data: A Wavelet Transform Analysis
Authors: Mohammed Isam Al-Hiyali  , Asnor Juraiza Ishak  , Maged Saleh Saeed Al-Quraishi  , Sarmad Nozad Mahmood
Published: May 2024

Neuroscientific evidence suggests that weight gain may be associated with changes in brain lobes' volume and function, as well as impulsive behaviour related to eating. However, it remains unclear whether impulsivity behaviour in overweight subjects is linked to abnormal activity in the resting state. To address this question, we propose a novel method to assess the relationship between different levels of body mass index (BMI) and neural activity of the prefrontal cortex (PFC) using electroencephalography (EEG) resting state data. EEG signals recorded during open-eye resting state from 36 subjects were divided into two groups based on BMI: overweight and normal weight subjects. We applied wavelet transform technique to compute the power for decomposed EEG bands and extracted coherence maps to assess the functional connectivity of the PFC. The one-way analysis of variance (ANOVA) was employed to assess the difference in EEG variables between the study groups. The results show a significant increase in the power of the sub-Theta band (4.49-5.34) Hz in overweight subjects compared to normal weight subjects (p-value = 0.001), as well as dysfunctional connectivity between left-right prefrontal sites in the overweight group with decreasing coherence function. These outcomes suggest that the specific PFC-EEG signals observed in overweight individuals are consistent with EEG patterns seen in other impulsivity-related diseases. Therefore, our findings reveal a specific EEG pattern in overweight adults that could be potentially utilized in developing neurotherapy-based treatment methods for overweight management.
Comparative Analysis of Machine Learning Algorithms for Diabetic Disease Identification
Authors: Dhasaradhan Kaveripakam  , Jaichandran Ravichandran
Published: May 2024

This article introduces a comparative analysis of different types of machine learning algorithms (MLAs) used for diabetic disease identification. Today machine learning algorithms are a major role in solving and identifying the different type of diseases in the medical sector. In the early prediction of diabetic to easily treat physicians and protect from other diseases in patients seven types of MLAs such as support vector machine (SVM), decision tree (DT), logistic regression (LGR), Gradient boost method (GDBM), k-nearest neighbour (KNN), XG boost (XGBM) and random forest (RF) are used for diabetic identification. PIMA Indian diabetic dataset (PIMAIDD) is used to train and test the MLAs. Confusion matrix, accuracy (ACR), precision (PCN), recall (RCL), f1-score (FSC), receiver operating curve (ROC) and K-fold cross-validation are the metrics used for performance evaluation of MLAs and experiments are implemented by Jupyter notebook and python sci-kit libraries. Six types of test cases were conducted whereas test case 4 (70%-30%) was well performed in which RF reported better results in diabetic identification that differentiates from other machine learning metric scores.
Single Image Integrated Deblurring Algorithm in Non-Uniform Environment
Authors: Rechard Lee  , Celine Wong
Published: May 2024

Motion blurriness in an image caused by camera shake during exposure is unavoidable. It could lead to information loss and degradation in the image quality. Therefore, many researchers are dedicated to developing image deblurring techniques to recover clear images from blurred images. During the deblurring process, structural edges in images play a vital part in estimating the blur kernels. For images with rich textures, fine-scale edges become more apparent. This will cause vagueness in the image’s structural edges and affect the accuracy of the kernel estimation process. In this study, we propose a single-image motion deblurring by kernel estimation method combined with L0-Regularized Intensity and Gradient Prior, and enhanced Scale Aware Smoothing methods. Two types of non-uniform datasets are used, which are real and synthetic. While synthetic datasets are utilized to assess the consistency in performance across real and synthetic images, real datasets are used to portray the level of detail and variation of actual blurred images. The dataset is divided into five categories (people, nature, manmade, text, and night light). Two image quality metrics were selected: full-reference assessment, including learned perceptual image patch similarity (LPIPS), peak signal-to-noise ratio (PSNR), and structural similarity indexing method (SSIM) for synthetic datasets, and no-reference assessments, including blind/reference-less image spatial quality (BRISQUE), natural image quality evaluator (NIQE) and perception-based image quality evaluator (PIQE) for real datasets. According to the findings, the fusion method performs best in the text category, followed by manmade and in nature, then night light and poor in people. The proposed method not only removes fine-scale edges and preserves the boundary sharpness, but also improved the estimated blur kernel.
Utilizing Immunoglobulin G4 Immunohistochemistry for Risk Stratification in Patients with Papillary Thyroid Carcinoma Associated with Hashimoto Thyroiditis
Authors: Haq Faridul , Park Gyeongsin , Jeon Sora , Hirokawa Mitsuyoshi , Jung Chan Kwon
Published: May 2024

Background: Hashimoto thyroiditis (HT) is suspected to correlate with papillary thyroid carcinoma (PTC) development. While some HT cases exhibit histologic features of immunoglobulin G4 (IgG4)-related disease, the relationship of HT with PTC progression remains unestablished.Methods: This cross-sectional study included 426 adult patients with PTC (≥1 cm) undergoing thyroidectomy at an academic thyroid center. HT was identified based on its typical histologic features. IgG4 and IgG immunohistochemistry were performed. Wholeslide images of immunostained slides were digitalized. Positive plasma cells per 2 mm2 were counted using QuPath and a pre-trained deep learning model. The primary outcome was tumor structural recurrence post-surgery.Results: Among the 426 PTC patients, 79 were diagnosed with HT. With a 40% IgG4 positive/IgG plasma cell ratio as the threshold for diagnosing IgG4-related disease, a cutoff value of >150 IgG4 positive plasma cells per 2 mm2 was established. According to this criterion, 53% (43/79) of HT patients were classified as IgG4-related. The IgG4-related HT subgroup presented a more advanced cancer stage than the IgG4-non-related HT group (P=0.038). The median observation period was 109 months (range, 6 to 142). Initial assessment revealed 43 recurrence cases. Recurrence-free survival periods showed significant (P=0.023) differences, with patients with IgG4 non-related HT showing the longest period, followed by patients without HT and those with IgG4-related HT.Conclusion: This study effectively stratified recurrence risk in PTC patients based on HT status and IgG4-related subtypes. These findings may contribute to better-informed treatment decisions and patient care strategies.
Phytochemical Investigation, Antioxidant, and Enzyme Inhibitory Activities of Blackberry (Rubus fruticosus) Fruit
Authors: Saqee Ali Hasan Saqee , Eruygur Nuraniye
Published: May 2024

This scientific paper explores the phytochemical composition of blackberry (Rubus fruticosus) fruit and investigates its antioxidant and enzyme inhibitory activities. Blackberry is known for its rich nutritional profile and potential health benefits, making it a subject of interest in the field of functional foods and natural medicine. The study aims to provide valuable insights into the bioactive compounds present in blackberry fruit, their antioxidant properties, and their potential as enzyme inhibitors. According to the results, it was determined that the fruit extracts had strong antioxidant and moderate enzyme inhibition activity. HPLC analysis showed that the fruit extract generally contained o-coumaric acid, procatechin, ellagic acid and quercetin as major components.
Prognostic value of fibrinogen/albumin in acute coronary syndrome patients with multiple coronary artery branch lesions
Authors: Doan Chi Thang
Published: May 2024

ABSTRACT Acute coronary syndrome (ACS) comprises a pathophysiological spectrum of cardiovascular diseases related to atherosclerotic coronary plaque erosion. Oxidative stress and inflammation play pivotal roles in the development and progression of atherosclerosis, which affects circulatory proteins, including albumin and fibrinogen, thereby causing an imbalance in albumin-to-globulin and fibrinogen - to - albumin ratios. This study aimed to evaluate the characteristics and prognostic value of fibrinogen/albumin index (FAR) in ACS patients with multiple coronary artery branch lesions after 3 months follow-up. In this cross-sectional description and follow-up study, the major blood proteins in ACS patients were evaluated using standard methods. Out of 76 ACS patients, prognostic indicators such as hs - troponin T, pro - BNP, ejection fraction and GRACE scale were all much higher in high FAR group, the difference was significant (p < 0.05). More major cardiovascular events (MACE) occurred significantly in the high FAR group than in the low FAR group. ROC curve analysis showed that the FAR index can predict events occurring during the 3-month period after discharge from the ACS group (AUC = 0.681; p < 0.05), but the predictability was not high. During the follow-up of MACE, the Kaplan-Meier analysis showed that patients with FAR > 10.3 had a higher risk of MACE than the FAR ≤ 10.3 (p < 0.05). Overall, FAR could be used as a routine prognostic factor in ACS with multiple coronary artery branch lesions with percutaneous coronary artery intervention.
Evaluation of Complete Blood Count Inflammatory Indices in Pregnant Women Diagnosed with Placenta Previa
Authors: Yıldırım Muradiye , Sahin Dilek
Published: May 2024

Aim: To evaluate systemic inflammation in pregnant women diagnosed with placenta previa (PP). First-trimester complete blood count indices of PP patients were assessed.
Materials and Method: This cross-sectional study was conducted with 346 singleton pregnant women, including 115 PP cases (study group) and 231 healthy pregnant women (control group) who were operated on in a tertiary center for one year. The study group was then divided into two subgroups. Those who underwent peripartum hysterectomy due to placenta accreta spectrum (PAS) were determined as PAS-positive, and those without invasion were PAS-negative. Demographic and obstetric characteristics laboratory results were recorded retrospectively. Systemic immune-inflammation index (SII) and systemic inflammatory response index (SIRI) values were calculated. Data were presented as mean and standard deviation using the independent sample t-test.
Results: The mean value of maternal age, body mass index, and gestational weeks at which hemograms were evaluated were similar between the study and control groups. While white blood cell and neutrophil counts were significantly higher in the PP group, red blood cell and hemoglobin counts were lower (p
Is AMH Really Related to Hyperandrogenism and Insulin Resistance? A Study in Young Women With PCOS
Authors: Halilzade İnci , Halilzade Mohammad İbrahim , Kılıçkıran Harun , Kahyaoğlu Serkan
Published: May 2024

Abstract
Aims: Polycystic ovary syndrome (PCOS) is an endocrinological disease associated with hyperandrogenism and insulin resistance. Although the place of AMH in polycystic ovary syndrome has been accepted with the recently published guideline, the underlying mechanisms still remain unclear. The aim of this study is to investigate the relationship between hyperandrogenism and AMH using phenotypes A and D in PCOS and to show the place of AMH in the diagnosis of PCOS phenotype without hyperandrogenism. In addition, to reveal the relationship between insulin resistance and AMH.
Material and Method: One hundred two patients with PCOS were included in this study. The patients were divided into two groups as Phenotype A and D. In addition, the patients were divided into 2 groups; with (HOMA-IR ≥2.5) and without insulin resistance (IR). The primary outcome was to measure the serum AMH levels between two groups. The secondary outcome was to compare demographic and clinical caracterics (age, BMI, laboratory values).
Results: There was no significant difference in AMH values between phenotypes A and D. When patients are divided into 2 groups as PCOS with insulin resistant and without insulin resistant, AMH was found to be significantly lower in the insulin resistant PCOS (p=0.006). The cut-off value for AMH was 6.26 ng/ml, with a sensitivity of 70.4% and a specificity of 62.5%.
Conclusion: As a result of our study, we think that the relationship of AMH with hyperandrogenism is not clear and reliable, as it is not a defining indicator between A and D phenotypes in PCOS, but it could be an indicator in determining insülin resistance in PCOS.
New report and range extension of invasive suckermouth armored catfishes of the genus Pterygoplichthys (Actinopterygii: Siluriformes: Loricariidae) in the Yucatan Peninsula
Authors: Soria-Barreto Miriam , Hinojosa-Garro Demián , García-López Jesús Elías , Góngora Chin Ricardo Efraín
Published: May 2024

Commonly known as suckermouth armored catfishes or pleco, Pterygoplichthys spp. are a group of invasive fishes that are widely distributed in several countries, including Mexico. This paper reports the first records of suckermouth armored catfishes in the Candelaria River, thereby expanding its distribution within the Yucatan Peninsula. Fifteen individuals were collected from three sites in the upper and middle parts of the basin. They represented two phenotypically distinct species of catfishes: (vermiculate) Pterygoplichthys disjunctivus (Weber, 1991) and (spotted) Pterygoplichthys pardalis (Castelnau, 1855). Adults and juveniles were caught in lotic ecosystems in 2023 during the dry and rainy seasons. Results suggest that the invasive process of the Candelaria River is linked to the San Pedro River upper basin, in El Petén, Guatemala, through floodings enhanced by hurricanes, allowing these species to disperse. These records highlight the importance of connectivity between adjacent watersheds for the dispersal and expansion of these invasive fishes, mainly from rivers neighboring Guatemala. However, further research is necessary to explore the dynamics and connectivity between aquatic ecosystems and the possible mechanisms that promote the invasion of these fishes in this region.
Understanding sedimentary dynamics and bottom sediment characteristics in Bons Sinais Estuary – Mozambique: Insights from statistical analysis and Pejrup diagram
Authors: Hoguane Cesar Antonio Mubango , Mativane Jessica , da Cruz Nacir Leitao , Machaieie Helder Arlindo
Published: May 2024

This article addresses the Bons Sinais Estuary sedimentary dynamics and bottom sediment characterization and its implication to pollution, based on bottom sediment grain size and statistical parameters. There were collected 15 bottom sediment samples with a Van veen sampler, which were further analysed by sieve and pipette methods. Sand was the most dominant textural class (51%), followed by silt (25%) and clay (24%). The sedimentary dynamics have varied from moderate to high. Both size of sediments and Pejrup diagram suggests that the hydrodynamics of this Estuary is high. Although the percentage of coarse sediments is higher, the estuary is susceptible to pollution, as the amount of thinner sediments is considerable regarding the values of skewness. These results may be useful to environmental management actions including pollutants tracking.
Modified mildly inertial subgradient extragradient method for solving pseudomonotone equilibrium problems and nonexpansive fixed point problems
Authors: Akutsah Francis , Mebawondu Akindele Adebayo , Ofem Austine Efut , George Reny , Nabwey Hossam A. , Narain Ojen Kumar
Published: May 2024

This paper presents and examines a newly improved linear technique for solving the equilibrium problem of a pseudomonotone operator and the fixed point problem of a nonexpansive mapping within a real Hilbert space framework. The technique relies two modified mildly inertial methods and the subgradient extragradient approach. In addition, it can be viewed as an advancement over the previously known inertial subgradient extragradient approach. Based on common assumptions, the algorithm's weak convergence has been established. Finally, in order to confirm the efficiency and benefit of the proposed algorithm, we present a few numerical experiments.
Two-dimensional array grammars in palindromic languages
Authors: Blasiyus Hannah , Sheena Christy D. K.
Published: May 2024

In this paper, we put forward models that generate two-dimensional palindromic languages with array-rewriting rules. The rewriting rules are of either regular or context-free type with terminals being arrays. The derivation lengths are managed by the array concatenation conditions. These grammars give rise to an extensive variety of palindromic pictures. Different hierarchies that exist between the classes defined are demonstrated. The closure properties have also been evaluated. Applications of these models have been explored by generating a few patterns of kolams.
Numerical investigation of nonlinear extended Fisher-Kolmogorov equation via quintic trigonometric B-spline collocation technique
Authors: Thottoli Shafeeq Rahman , Tamsir Mohammad , Meetei Mutum Zico , Msmali Ahmed H.
Published: May 2024

In this article, a collocation technique based on quintic trigonometric B-spline (QTB-spline) functions was presented for homogeneous as well as the nonhomogeneous extended Fisher-Kolmogorov (F-K) equation. This technique was used for space integration, while the time-derivative was discretized by the usual finite difference method (FDM). To handle the nonlinear term, the process of Rubin-Graves (R-G) type linearization was employed. Three examples of the homogeneous extended F-K equation and one example of the nonhomogeneous extended F-K equation were considered for the analysis. Stability analysis and numerical convergence were also discussed. It was found that the discretized system of the extended F-K equation was unconditionally stable, and the projected technique was second order accurate in space. The consequences were portrayed graphically to verify the accuracy of the outcomes and performance of the projected technique, and a relative investigation was accomplished graphically. The figured results were found to be extremely similar to the existing results.
Exploring Innovative Metrics to Benchmark and Ensure Robustness in AI Systems
Authors: Kuppam Manoj , Godbole Madhavi , Bammidi Tirupathi Rao , Rajest S. Suman , Regin R.
Published: May 2024

In an era where AI systems are increasingly integrated into critical applications, ensuring their robustness and reliability is of paramount importance. This study embarks on a comprehensive exploration of innovative metrics aimed at benchmarking and ensuring the robustness of AI systems. Through extensive research and experimentation, the authors introduce a set of groundbreaking metrics that demonstrate superior performance across diverse AI applications and scenarios. These metrics challenge existing benchmarks and set a new gold standard for the AI community to aspire towards. Robustness and reliability are cornerstones of trustworthy AI systems. Traditional metrics often fall short in assessing the real-world performance and robustness of AI models. To address this gap, this research team has developed a suite of novel metrics that capture nuanced aspects of AI system behavior. These metrics evaluate not only accuracy but also adaptability, resilience to adversarial attacks, and fairness in decision-making. By doing so, the authors provide a more comprehensive view of an AI system's capabilities. This study's significance lies in its potential to drive the AI community towards higher standards of performance and reliability. By adopting these innovative metrics, researchers, developers, and stakeholders can better assess and compare the robustness of AI systems. This, in turn, will lead to the development of more dependable AI solutions across various domains, including healthcare, finance, autonomous vehicles, and more. This research represents a significant step forward in ensuring the robustness and reliability of AI systems. The introduction of innovative metrics challenges the status quo and sets a new performance standard for AI systems, ultimately contributing to the creation of more trustworthy and dependable AI technologies.
New Framework Modeling for Big Data Analysis of the Future
Authors: Ahmad Beig Mirza Tanweer , Kashyap Varun , Walia Megha
Published: May 2024

The area of big data analysis confronts several obstacles in its quest to derive useful insights from the ever-increasing amount and complexity of available data. To cope with the future volume, velocity, and diversity of data, new frameworks and models must be created. In this article, the authors offer a new framework for big data analysis that makes use of a variety of recently developed tools and techniques specifically designed to meet these demands. The three main pillars of our methodology are data acquisition, data processing, and data analysis. To ensure effective and continuous data collection from many sources, the authors make use of recent developments in data streaming and real-time data processing methods. This guarantees that the framework can process large amounts of data quickly enough to allow for timely analysis. The authors do tests using real-world, large-scale data sets to see how well this suggested framework performs in practice. When compared to conventional methods, the results show dramatic enhancements in terms of processing velocity, scalability, and precision. The authors also emphasize the framework's potential for integration with cutting-edge technologies like edge computing and internet of things (IoT) gadgets, as well as its flexibility to accommodate shifting data landscapes. Enhanced decision-making and insights in the age of big data are made possible by the integration of state-of-the-art technology and techniques, which allow for efficient data intake, scalable processing, and sophisticated analytics.
Image Recognition and Extraction on Computerized Vision for Sign Language Decoding
Authors: Gandhi M. , Satheesh C. , Soji Edwin Shalom , Saranya M. , Rajest S. Suman , Kothuru Sudheer Kumar
Published: May 2024

The image recognition method is a significant process in addressing contemporary global issues. Numerous image detection, analysis, and classification strategies are readily available, but the distinctions between these approaches remain somewhat obscure. Therefore, it is essential to clarify the differences between these techniques and subject them to rigorous analysis. This study utilizes a dataset comprising standard American Sign Language (ASL) and Indian Sign Language (ISL) hand gestures captured under various environmental conditions. The primary objective is to accurately recognize and classify these hand gestures based on their meanings, aiming for the highest achievable accuracy. A novel method for achieving this goal is proposed and compared with widely recognized models. Various pre-processing techniques are employed, including principal component analysis and histogram of gradients. The principal model incorporates Canny edge detection, Oriented FAST and Rotated BRIEF (ORB), and the bag of words technique. The dataset includes images of the 26 alphabetical signs captured from different angles. The collected data is subjected to classification using Support Vector Machines to yield valid results. The results indicate that the proposed model exhibits significantly higher efficiency than existing models.
Efficient Student Behaviour Analysis in E-Learning Using Data Mining Approaches
Authors: Ahamed H. Riaz , Hanirex D. Kerana
Published: May 2024

Recognising and assessing how pupils act is essential for customising educational opportunities and enhancing educational results in online learning. In particular, Support Vector Machine (SVM), Decision Tree (DT), and Naive Bayes (NB) are employed in this work to analyse the characteristics of pupil conduct in online educational settings. The main goal is to determine the best strategy for thoroughly comprehending how students communicate in online learning environments. Employing metrics like RMSE (Root Mean Square Error), RSE (Relative Absolute Error), and RRSE (Relative Root Square Error) to evaluate the outcome of DM (Data Mining) methods. The results show that SVM regularly beats DT and NB throughout all criteria, showing that it has a greater capacity to identify complex relationships in pupil activity records with RMSE of 0.02714, RAE of 0.00279 and RRSE of 0.02117, respectively. The tool used for execution is Jupyter Notebook, and the language used is Python.
Southern Boy Blues
Authors: Jackson Anthony , Howard Anissa Kenyatta , White Adrienne D. , Moss Bridget Holyfield
Published: May 2024

This chapter aims to examine issues related to the mental health needs of Black men who sleep with men (BMSM) who reside in southern United States. This chapter examines incidences of clinical symptomology with this population as well as incidences of trauma, and medically exasperated symptoms in the context of post-pandemic America. By presenting a brief synthesis of research pertaining to help-seeking behaviors of this population, the authors aim to broaden perspectives of treatment efficacy when working with BMSM from various age groups. Risk behaviors, internalized homophobia, down low culture, and common misconceptions of gay male sexuality in the Black community will also be explored. Lastly, Cass's sexual orientation identity formation model is used to help the authors exemplify an effective strategy for working with the clinical issues of southern BMSM as well as cultural considerations to enhance therapeutic rapport building at various stages of the counseling process as described by Hill.
Inclusive Education
Authors: Oranga Josephine , Njurai Evelyn W. , Gisore Billiah , Areba George Ngwacho
Published: May 2024

Inclusive education is an approach that promotes diversity and equal educational opportunity among all learners, regardless of any differences they may possess. It is the process of reform in education that embodies modification in structures, content, approaches, teaching methods and strategies in a bid to provide all learners with age-appropriate, participatory, and equitable leaning experiences in environments that best meets and responds to their diverse educational needs. While inclusive education is an extensive concept that encompasses all types of learners, for this chapter, the term will focus on learners with disabilities. This is because, despite the introduction and adoption of the inclusive education approach globally, several barriers still impede its implementation and practice, forming the substance of this chapter. This chapter, thus, delves into the benefits, barriers, and strategies of intervening on barriers to inclusive education.
Navigating Educational Justice in K-12 Schools
Authors: Tsarkos Athanasios
Published: May 2024

This chapter delves into educational justice within K-12 schools, exploring its theoretical underpinnings and practical implications. It examines the impact of educational justice on student outcomes, addressing systemic barriers and policy dilemmas in achieving equity. The chapter proposes solutions emphasizing policy reform and inclusive practices. It concludes by forecasting future trends in educational justice, highlighting the significance of digital literacy, social-emotional learning, personalized education, and community involvement in the dynamic realm of K-12 education.
Systematization of Experiences as a Methodology for Knowledge Production for Educational Practice in Cross-Border Territories
Authors: Pano Fuentes Carolina
Published: May 2024

Among other fields, migratory processes challenge the physiognomy of educational contexts, which can become tense depending on practices and policies designed from a homogeneous perspective. However, one possibility to relax them may be through the participation of teachers in reflection-action processes that allow them to recreate conditions of equity in their own context. In this order of ideas, this chapter shares a reflection on the use of the systematization of experiences as a method for the recovery and production of knowledge to transcend a declarative perspective on what a teacher “should do.” To achieve this, the route proposed is to link an epistemological context in which subjectivity is recovered as an object of knowledge (biographical-narrative approach) to a methodological context anchored to a qualitative and narrative perspective (systematization of experiences).