bluuebunny/crossref_metadata_2025 huggingface dataset:
Machine Learning for the Diagnosis and Prognosis of Chronic Illnesses
Authors: Kajal  , Kanchan Saini  , Dr. Nikhat Akhtar  , Prof. (Dr.) Devendra Agarwal  , Ms. Sana Rabbani  , Dr. Yusuf Perwej
Published: May 2024

An essential part of healthcare is disease prediction, which seeks to identify people who are at risk of getting certain diseases. Because of their superior capacity to sift through massive datasets in search of intricate patterns, machine learning algorithms have recently become useful instruments in the fight against illness prediction. The goal of this project is to make it easier for people to diagnose their own health problems using just their symptoms and precise vital signs. Due to excessive medical expenditures, many people put off taking care of their health, which can result in worsening symptoms or even death. Medical expenses can be overwhelming for people without health insurance. Using machine learning methods like ExtRa Trees, the suggested system provides a general illness forecast based on patients' symptoms. The algorithm provides a possible diagnosis based on the user's age, gender, and symptoms, suggesting that the user may be experiencing a certain illness. The system also suggests healthy eating and exercise routines to help lessen the impact of the condition, depending on how bad it is. Lastly, this article has shown a comparison examination of the suggested system using several algorithms including logistic regression, decision tree, and Naïve Bayes. The efficiency and accuracy of illness prediction are both enhanced by the suggested model.
Employee Attrition Prediction in the USA: A Machine Learning Approach for HR Analytics and Talent Retention Strategies
Authors: Md Sumon Gazi  , Md Nasiruddin  , Shuvo Dutta  , Rajesh Sikder  , Chowdhury Badrul Huda  , Md Zahidul Islam
Published: May 2024

In the dynamic business domain in the USA, human capital is one of the most instrumental assets for companies. Maintaining high performance and reducing employee attrition has become an utmost priority in the USA since the costs related to employee attrition can be significant. The chief objective of this study was to explore the application of machine learning in terms of forecasting employee attrition and its ramifications for HR analytics and talent retention strategies. In this study, the investigator used Jupyter Notebook, an interactive platform for Python users, to design machine learning algorithms. The dataset utilized in this research was attained from the IBM Human Resource workforce attrition survey dataset. In the current research, the investigator proposed an array of machine learning models, most notably, Decision Tree, Ada-boost classifier, Random Forest, and gradient-boosted classifier. By referring to the model’s performance evaluation, it was apparent that the Random Forest algorithm had the highest accuracy, followed by Gradient Boosting and Decision Tree respectively. AdaBoost had the lowest accuracy. Concerning precision, the Random Forest algorithm again had the highest precision followed by Gradient Boosting and AdaBoost accordingly. By implementing the proposed models’ organizations in the USA can identify high-performing employees at risk of quitting, and subsequently take proactive steps to retain them, saving significant organizational resources. Ultimately, the proposed machine learning techniques can assist the government in maintaining high-performing employees, reducing the impact of labor shortages, and maintaining business continuity.
Sudoku Puzzle Difficulty Rating based on Fuzzy Logic
Authors: Naji Areen , Salous Saleh
Published: May 2024

In this document, we propose a new fuzzy logic-based rating technique for Sudoku difficulty, which takes into account Sudoku instance parameters such as the number of filled cells as well as parameters relating to the distribution of filled numbers on the cells. This new technique is validated using historical data from a certificate paper [Mantere, 2008], which includes 45 Sudoku instances of all rank levels, three of each level, and the average/max time consumed in 100 runs using different algorithms for each instance. First and foremost, these instances were analyzed and parameterized, and their parameters were quantitatively analyzed to be considered in fuzzy logic. The instance parameters' correlation with their solving time is studied, and dimensionality reduction was performed on these as variables to ensure that no unnecessary variable was included in the study. As solving time parameters, the number of filled cells in the instance, the minimum number of filled cells in rows and columns, and the number of empty sub-squares (3*3) in the instance are all accepted. Because there should be a functional relationship between the Sudoku rank and the time required to solve it, a linear regression model was performed on the historical data between the old rank and the solving time, and the same regression model was performed on the new rank to validate it. As a result, a new clear and simple ranking technique that outputs more correlated ranks with the time required to solve Sudoku puzzles is validated.
Attitudes and Performance of Grade 11 Students in Pre-Calculus Using Strategic Intervention Material
Authors: Etcuban Jonathan , Daculara, Jr. Cirilo , Cutab Mayette , Lapiña Suzette , Campanilla Bell
Published: May 2024

Strategic Intervention Material (SIM) served as instructional support to help students review key ideas and techniques to help them master a competency-based ability they could not achieve during routine class discussions. This study aimed to determine the attitudes and the performance of Grade 11 students in Pre-Calculus using SIM at the three-identified public national high schools in Cebu, Philippines. It employed the descriptive-correlational method to collect data from 97 samples using two questionnaires (A standardized Attitudinal Test by Fennema-Sherman and researchers-made Performance Test in Equations of Circles). The Chi-square test, t-test, frequency, simple percentage, mean, standard deviation, and attitude toward success were used to analyze the respondents' attitudes about pre-calculus regarding confidence in learning, attitude toward success, mathematics as a male domain, and usefulness. The findings demonstrated that SIMs were appropriate for the respondents' needs, with more excellent knowledge gained from the SIM leading to a better understanding of Pre-Calculus, specifically Equations of Circles, which is beneficial when SIM is used as a teaching tool. The study concluded that using SIM in Pre-Calculus as instructional support significantly affected the student's performance in Pre-Calculus, which is effective in learning the subject. The proposed intervention plan was recommended to be implemented, monitored, and evaluated to boost the math performance of the Grade 11 senior high schools.
A PRELIMINARY SURVEY OF TREE SPECIES DIVERSITY: A CASE STUDY OF FEDERAL UNIVERSITY WUKARI
Authors: Anongo M'ember Catherine , Yerima Mercy joseph
Published: May 2024

The impact of anthropogenic activities on tree species diversity of a selected sub-sample of the Federal University Wukari Campus comprising of four sampling Sites (A, B, C and D) was investigated using the Shannon-Wiener, Margalefs and Menhinik diversity indices. Tree felling is the commonest human activity. The infrastructural developments and anthropogenic activities among the four sampling sites ranges from low to high. A total of 203 individual tree species of 20 species from 15 families was encountered in the study area. The dominant families were Arecaceace, Fabaceae, Anacardiaceae, Lamiaceae and Moraceae. Elaies guineensis (80) was the most dominant tree species with the highest relative density (RD) of 39.4% at Site D while the lowest RD of 0.49 were encountered at Sites A, B and C. The most abundant tree species were Elaies guineensis and Mangifera indica due to their economic importance. About 35% of the trees were exotic while 65% were native. A high Shannon-Wiener index value of 0.78 and Margalefs index value of 14.869 were observed. Analysis of the diversity indices of the 20 species reveals the sensitivity of the Shannon-Wiener index than the Margalefs index, though the two indices shows relative diversity of tree species according to their ranges. The high population size of the indigenous trees with higher economic uses is a strong indicator of loss of tree genetic resources that play critical roles in local diversification of the ecosystems to make them more resilient for what is to come with respect to climate change regulation.
Level of knowledge and awareness among parents regarding the care of children with thalassaemia
Authors: Makajil Johari Daud , Taising Zerah , Thomas Deena Clare , Nain Rose A
Published: May 2024

Background This study assessed parental knowledge and awareness of children with thalassemia. Thalassemia care among 65 parents at a Kota Kinabalu hospital focuses on parental knowledge and awareness of children with thalassemia. The objectives were to identify parents' level of knowledge of thalassemia care and assess their awareness of specific care needs.
Methods: This was a descriptive, cross-sectional study of the thalassemia families of patients at Likas Women and Children's Hospital, Kota Kinabalu, Sabah. Using random sampling. The study involved 65 respondents from Sabah Women and Children in Kota Kinabalu, Sabah. Data from questionnaires and tests were processed using SPSS version 24, with descriptive statistics analysing frequency and percentage, expressed as mean ± standard deviation.
 Results Most respondents had a high level of knowledge about thalassemia, an inherited disease caused by insufficient red blood cell supply. They understood that untreated conditions could deteriorate thalassemia patients but could lead normal lives with proper therapy. They also knew that thalassemia could be detected through blood tests and that blood donation could be beneficial. However, they had moderate knowledge of the connection between thalassemia and anaemia, blood transfusions as the only treatment, and their ability to identify and avoid thalassemia during pregnancy.
Conclusion This study emphasises the need for education, community engagement, and healthcare involvement to enhance the understanding and support of individuals with thalassemia, suggesting that comprehensive strategies, including education programs and collaborations with local organisations, can be implemented.
Not all that glitters is gold: Glitter causes acute toxicity to nauplii of Artemia sp.
Authors: Abessa Denis Moledo de Souza , Gonçalves Alexandre Rodrigo Nascimento , Ueda de Carvalho Maysa , Spanghero Natalie , Sales Soares do Nascimento Nathalia , Fornari Milene , Perina Fernando Cesar , Cruz Ana Carolina Feitosa
Published: May 2024

Glitter has been reported as a relevant pollutant, as it is widely used in cosmetic and textile products and craftwork, and often associated with domestic sewage. The particular glitter is composed of thin layers of plastic and metal. This study assessed the acute toxicity of glitter dispersions in the brine shrimp Artemia sp. Nauplii of Artemia sp. that were exposed to glitter dispersions (0.01, 0.1, 1, 10, and 100 mg/L), obtained by diluting a stock solution in seawater; the control consisted of filtered seawater only. Three replicates were used per treatment and consisted of glass tubes filled with 10 mL of the test solution, and ten nauplii aging over 48 h. After 48 h, the survivors were counted and examined under a microscope. The mean size of glitter particles was 3.94 (±0.98) µm; approximately 44 % of particles were in the range of very fine sand, and 27 % coarse silt. Significant lethal effects (p < 0.05) occurred from 0.1 mg/L (Lowest Observed Effect Concentration - LOEC); the lethal concentration to 50 % organisms (LC50-48h) was 0.350 (0.348 - 0.351) mg/L. The exposed organisms also exhibited patches in their digestive tracts, and particles were stranded in their appendices. The results indicate the toxic potential of glitter to brine shrimp. This investigation indicates the need for further studies on the toxicity of glitter to marine invertebrates.
Highlights

Glitter includes particles of sizes similar to those of marine microalgae
Exposure to glitter suspensions caused toxicity in brine shrimps from 0.1 mg/L
The nauplii of Artemia were more sensitive to glitter than echinoderm embryos
Metallic parts of the glitter were observed in the digestive tract of the brine shrimp nauplii
Ready, steady, chop! Investigating the impact of chop size on zoo food nutritional quality
Authors: Brereton James Edward
Published: May 2024

It is common for animal keepers to chop food up for their animals into small pieces, yet there is limited information as to why this practice is done. Anecdotally, many collections also prepare their zoo animal diets the day before feeding and store them in the fridge overnight. The potential impact of these food preparation and storage methods on food nutritional quality is unknown. To address this, this study investigated the impact of preparing six types of produce into four sizes (0.5, 2, and 4 cm3 cubes, or whole) on the desiccation, browning and pH scores. Samples were stored either under ambient, room temperatures, or stored in a fridge and analysis was conducted over a 24-hour period. The most severe desiccation levels occurred in finely chopped feeds, for both ambient and fridge-stored samples. Time significantly affected the rate of desiccation and browning, and food chop size was a significant predictor of both browning and pH. These results suggest that serious nutritional changes occur in chopped feeds, especially when they are finely chopped and especially when food is stored for more than a couple of hours prior to feeding. Practitioners who care for animals should consider whether their animals benefit from finely chopped feeds and should avoid the practice of storing chopped food overnight.
The Natural History of Post-Chikungunya Viral Arthritis Disease Activity and T-cell Immunology: A Cohort Study
Authors: Chang Aileen Yu-hen , Hernández Alfonso Sucerquia , Forero-Mejía Jose , Tritsch Sarah Renee , Mendoza-Torres Evelyn , Encinales Liliana , Bonfanti Andres Cadena , Proctor Abigale Marie , Simon Gary Leonard , Simmens Samuel Joseph , Firestein Gary Steven
Published: May 2024

Background: Chikungunya virus (CHIKV) is an alphavirus spread by mosquitos that causes arthralgias and arthritis that may last for years. The objective of this study was to describe the arthritis progression and T cell immunology over a two-year period.

Methods: A cohort of 40 cases of serologically confirmed CHIKV from Magdalena and Atlántico, Colombia were followed in 2019 and again in 2021. Arthritis disease severity, disability, pain, stiffness, physical function, mobility, fatigue, anxiety, sleep disturbances and depression were assessed. Serum cytokines and T-cell subsets were measured and tested for change. Correlations within each of the 2 time periods for laboratory parameters were also examined.

Results: Although, arthritis disease severity, as measured by the Disease Activity Score-28 (DAS-28) did not change significantly over a two-year period, a new metric- the Chikungunya Disease Activity Score (CHIK-DAS)- was more sensitive to detect changes in disease severity than the Disease Activity Score-28 (DAS-28) and showed some improvement in average disease severity from moderate to mild over two years. Cases were characterized by moderate disability, pain, and stiffness with mild alterations of physical function, mobility, fatigue, anxiety, sleep disturbances and depression that did not change significantly over time. Small joints including the fingers and wrists were most affected without significant change over time. The percentage of effector T cells (Teffs) and regulatory T cells (Tregs) of CD4+ T cells both decreased over time. Teff percentages decreased more significantly resulting in a halving of the Teff/Treg ratio two years later. Furthermore, markers of Treg immunosuppressive function such as CTLA4, Helios, CD28, CD45RA and 41bb decreased over time. Cytokines did not change significantly over time.

Conclusions: The presented data suggest that arthritis persists almost seven years after chikungunya infection in some patients with waning Teff and Treg numbers and activation markers over time. Treg activation may be a promising therapeutic target for further investigation.
A Natural Metabolite and Inhibitor of the NLRP3 Inflammasome: 4-hydroxynonenal
Authors: Zhang Jinmin , Berk Bradford C. , Hsu Chia George
Published: May 2024

The NOD-, LRR-, and pyrin domain-containing protein 3 (NLRP3) inflammasome, crucial in the innate immune response, is linked to various human diseases. However, the effect of endogenous metabolites, like 4-hydroxynonenal (HNE), on NLRP3 inflammasome activity remains underexplored. Recent research highlights HNE's inhibitory role in NLRP3 inflammasome activation, shedding light on its potential as an endogenous regulator of inflammatory responses. Studies demonstrate that HNE blocks NLRP3 inflammasome-mediated pyroptosis and IL-1β secretion. Additionally, covalent targeting emerges as a common mechanism for inhibiting NLRP3 inflammasome assembly, offering promising avenues for therapeutic intervention. Further investigation is needed to understand the impact of endogenous HNE on NLRP3 inflammasome activation, especially in settings where lipid peroxidation byproducts like HNE are produced. Understanding the intricate interplay between HNE and the NLRP3 inflammasome holds significant potential for unraveling novel therapeutic strategies for inflammatory disorders.
Abd al-Rahman al-Kawākibī dan Visi Politik Islam
Authors: Nabil Amir Ahmad , Rahman Tasnim Abdul
Published: May 2024

The paper address the political view of ‘Abd al-Rahmān b. Ahmad al-Kawākibī (1855- 1902) in the context of historical tradition and political structure of the Ottoman caliphate in the late 19th century. It looks into his critics of dictatorial rule and oppressive system of the caliphate and its call for the dismantling of the unjust and tyrannical framework. The study is based on qualitative method and documentary approach. The data obtained from reliable library material and source in the form of manuscript, dissertation, book, newspaper and magazine. The information derived is analysed using descriptive, analytical, comparative, and historical method. The finding shows that al-Kawakibi’s underlying philosophy and movement has largely influenced the Arab consciousness of the Middle East in the late 19th century, inspiring revolutionary ideas and movement in the East Mediterranean toward meaningful political liberation and the formation of nation state, bringing the spirit of nationalism and enlightenment throughout the Arab world.
Perlindungan Hak Konsumen Pada Penggunaaan E-Commerce: Perspektif Hukum Syariah Islam
Authors: Thorik Achmad , Putri Suryan Widaningrum , Kirana Putri Al-Zahra , Tri Andini Lulu
Published: May 2024

In Indonesia , there is a Consumer Protection Law as an effort to guarantee consumer protection in online transactions, especially in e-commerce. This research aims to examine muamalah's legal views regarding consumer rights amidst the widespread use of e-commerce. This research is normative legal research which includes a statutory approach (statue approach) and a case approach, which in obtaining legal materials is carried out through literature study. Based on the research results, it is known that the practice of e-commerce in the business world is seen as a form of digitalization of buying and selling which according to Islamic sharia is permitted provided that it follows sharia principles and applicable legal regulations, especially in fulfilling consumer rights and protection. Researchers will examine Islamic legal views on e-commerce transactions and find out how consumer rights are fulfilled in the e-commerce system.
Shape from dots: a window into abstraction processes in visual perception
Authors: Baker Nicholas , Kellman Philip J.
Published: May 2024

Introduction

A remarkable phenomenon in perception is that the visual system spontaneously organizes sets of discrete elements into abstract shape representations. We studied perceptual performance with dot displays to discover what spatial relationships support shape perception.

Methods

In Experiment 1, we tested conditions that lead dot arrays to be perceived as smooth contours vs. having vertices. We found that the perception of a smooth contour vs. a vertex was influenced by spatial relations between dots beyond the three points that define the angle of the point in question. However, there appeared to be a hard boundary around 90° such that any angle 90° or less was perceived as a vertex regardless of the spatial relations of ancillary dots. We hypothesized that dot arrays whose triplets were perceived as smooth curves would be more readily perceived as a unitary object because they can be encoded more economically. In Experiment 2, we generated dot arrays with and without such “vertex triplets” and compared participants’ phenomenological reports of a unified shape with smooth curves vs. shapes with angular corners. Observers gave higher shape ratings for dot arrays from curvilinear shapes. In Experiment 3, we tested shape encoding using a mental rotation task. Participants judged whether two dot arrays were the same or different at five angular differences. Subjects responded reliably faster for displays without vertex triplets, suggesting economical encoding of smooth displays. We followed this up in Experiment 4 using a visual search task. Shapes with and without vertex triplets were embedded in arrays with 25 distractor dots. Participants were asked to detect which display in a 2IFC paradigm contained a shape against a distractor with random dots. Performance was better when the dots were sampled from a smooth shape than when they were sampled from a shape with vertex triplets.

Results and discussion

These results suggest that the visual system processes dot arrangements as coherent shapes automatically using precise smoothness constraints. This ability may be a consequence of processes that extract curvature in defining object shape and is consistent with recent theory and evidence suggesting that 2D contour representations are composed of constant curvature primitives.
Development and application of a machine learning-based predictive model for obstructive sleep apnea screening
Authors: Liu Kang , Geng Shi , Shen Ping , Zhao Lei , Zhou Peng , Liu Wen
Published: May 2024

Objective

To develop a robust machine learning prediction model for the automatic screening and diagnosis of obstructive sleep apnea (OSA) using five advanced algorithms, namely Extreme Gradient Boosting (XGBoost), Logistic Regression (LR), Support Vector Machine (SVM), Light Gradient Boosting Machine (LightGBM), and Random Forest (RF) to provide substantial support for early clinical diagnosis and intervention.

Methods

We conducted a retrospective analysis of clinical data from 439 patients who underwent polysomnography at the Affiliated Hospital of Xuzhou Medical University between October 2019 and October 2022. Predictor variables such as demographic information [age, sex, height, weight, body mass index (BMI)], medical history, and Epworth Sleepiness Scale (ESS) were used. Univariate analysis was used to identify variables with significant differences, and the dataset was then divided into training and validation sets in a 4:1 ratio. The training set was established to predict OSA severity grading. The validation set was used to assess model performance using the area under the curve (AUC). Additionally, a separate analysis was conducted, categorizing the normal population as one group and patients with moderate-to-severe OSA as another. The same univariate analysis was applied, and the dataset was divided into training and validation sets in a 4:1 ratio. The training set was used to build a prediction model for screening moderate-to-severe OSA, while the validation set was used to verify the model's performance.

Results

Among the four groups, the LightGBM model outperformed others, with the top five feature importance rankings of ESS total score, BMI, sex, hypertension, and gastroesophageal reflux (GERD), where Age, ESS total score and BMI played the most significant roles. In the dichotomous model, RF is the best performer of the five models respectively. The top five ranked feature importance of the best-performing RF models were ESS total score, BMI, GERD, age and Dry mouth, with ESS total score and BMI being particularly pivotal.

Conclusion

Machine learning-based prediction models for OSA disease grading and screening prove instrumental in the early identification of patients with moderate-to-severe OSA, revealing pertinent risk factors and facilitating timely interventions to counter pathological changes induced by OSA. Notably, ESS total score and BMI emerge as the most critical features for predicting OSA, emphasizing their significance in clinical assessments. The dataset will be publicly available on my Github.
Causal effects and metabolites mediators between immune cell and risk of breast cancer: a Mendelian randomization study
Authors: Ming Ruijie , Wu Huan , Liu Hong , Zhan Fangbiao , Qiu Xingan , Ji Ming
Published: May 2024

Introduction: The incidence and mortality of female breast cancer remain high, and the immune microenvironment of breast cancer has undergone significant alterations. However, the impact of blood immune cell levels on the risk of breast cancer is not fully understood. Therefor this study aims to investigate the causal relationship between blood immune cell levels and the risk of breast cancer.

Methods: A Mendelian randomization (MR) analysis was employed to assess the causal relationship between immune cells and the risk of breast cancer, as along with their potential mediating factors. Genetic statistics of metabolites breast cancer and immune cells were obtained from the GWAS Catalog, while the genome-wide association study (GWAS) statistics of breast cancer were extracted from the UK biobank. Two-sample MR analysis were performed using inverse-variance weighted (IVW) to ascertain the causal association between immune cells and the risk of breast cancer. Furthermore, 1,400 metabolites were analyzed for their mediating role between immune cells and the risk of breast cancer.

Results: MR analysis through IVW method revealed that genetically predicted CD24+ CD27+ B cells were associated with a decreased risk of breast cancer (OR = 0.9978, 95% CI: 0.996–0.999, p = 0.001), while IgD- CD38+ B cells were linked to an increased risk of breast cancer (OR = 1.002, 95% CI: 1.001–1.004, p = 0.005). Additional CD14+ CD16+ monocytes were associated with an increased risk of breast cancer (OR = 1.000, 95% CI: 1.000–1.001, p = 0.005). Mediation analysis revealed a positive causal relationship between IgD- CD38+ B cells and Glycerate levels, with the latter also exhibiting a positive causal relationship with the risk of breast cancer (p < 0.05). Conversely, IgD- CD38+ B cells displayed a negative causal relationship with Succinoyltaurine levels, and the latter also demonstrated a negative causal relationship with the risk of breast cancer (p < 0.05).

Conclusion: This MR study provides novel genetic evidence supporting a causal relationship between IgD- CD38+ B cells and the risk of BC. Moreover, it is identified that IgD- CD38+ B cells contribute to an increased risk of BC through both positive and negative mediation effects involving Glycerate and Succinoyltaurine.
Sentiment Analysis of COVID-19 Tweets using Neural Network in Pakistan
Authors: Mazhar Syed Tayyab Ul , Khan Hasnain , Usmani Shazia , Afzal Uzma
Published: May 2024

Covid-19 is a respiratory infectious disease that spreads from person to person. World Health Organization declared it a pandemic in March 2020. Social distancing and lockdowns during the pandemic affected the lives, sentiments, and mental health of people. They are mentally, physically, and emotionally disturbed. It was observed that the verification of the very first Covid case increased the precariousness and fear in Pakistan because people had no information about the state policies. In this paper, Covid-related tweets from Pakistan for the year 2021 are collected. Pakistan faced two Covid waves in 2021. Dataset is preprocessed and a neural network-based model is applied to analyze the sentiment of the tweet. Sentiments of people are analyzed separately for each Covid wave, moreover, a comparative analysis is presented to discuss the change in people's sentiments with the passage of time. Results show a reduction in the number of tweets from third to fourth wave. Moreover, the %decrease in negative and positive sentiments are 6 and 1 respectively which show that by the passage of time, people started living with the environment and time healed the wounds of fears and uncertainty in their lives.
MEREC-WISP(S) Integration Extended with Fermatean Fuzzy Set for Requirement Prioritization
Authors: Rahman Ateeque
Published: May 2024

Software projects need efficient requirement prioritization. Time, budget, and quality often limit these projects. MCDM techniques help balance conflicting criteria. However, they struggle to rank options due to multiple parties. Current MCDM methods have drawbacks, like poor uncertainty management. This thesis presents a new technique, WISP-S, for requirement prioritization in software development. The dynamic WISP(S) approach and the MEREC method are merged. Fermatean fuzzy numbers manage qualitative data and uncertainty. This technique surpasses the restrictions of current MCDM methods. It offers an effective way to rank software requirements within limits. The research consists of two separate stages. The first phase introduces an enhanced MEREC technique. It’s designed to compute the objective weights of each criteria within Fermatean Fuzzy Sets (FFS). By leveraging FFS features, this expansion improves the current MEREC technique. It allows a more thorough examination of criteria weights. The second phase integrates the WISP(S) method with the suggested generalized weighted Fermatean fuzzy aggregated operator and MEREC technology. This integration allows ranking and evaluating alternatives in a prioritization context. The study offers a robust strategy to prioritize alternatives. It considers both qualitative and uncertain data by integrating two novel methods. The approach’s validity and robustness are confirmed through comparisons with existing models and sensitivity analysis. A real-world case study demonstrates the proposed approach. The WISP-S approach is a novel technique for integrated Fermatean fuzzy information-based decision-making. It can handle complex decision-making problems in software development. This approach could improve the success of software projects. It addresses the shortcomings of existing MCDM methods.
Strategic Analysis of Feature Selection Methods for Enhanced Dental Therapy Recognition in Machine Learning Applications
Authors: Noor Shaheena , Saleem Muhammad Imran , Ismat Najma , Minhas Humera Noor , Rukaiya Rukaiya , Siddiqui Aneeta
Published: May 2024

The popularity of smart clinics has increased significantly as a result of technical developments in fields like computer vision. At the heart of such systems is the ability to recognize objects and activities as well as perceive the environment as a whole. This is crucial for both eco-independent systems and human-machine interaction, especially in settings with constrained workspaces, like dental care. Our study delves into an extensive analysis of multiple machine learning models designed to robustly predict dental treatments. These models encompass Lazy Instance-based Learning, Sequential Minimal Optimization, Hoeffding Tree, and Random Tree. Leveraging object-oriented input sourced from gaze-guided wearable cameras, we scrutinize intricate attributes such as material properties, patients' dental conditions, and the array of instruments in use. Notably, we exploit the insight that identifying visual cues during an activity holds the potential to address the specific therapy identification challenge. Utilizing a dental data set that we gathered in the real world, we conducted our experiments and discovered that combining multiple criteria enhances accuracy in comparison to using each one alone. We did see, nevertheless, that in certain circumstances employing the symptoms alone produced superior outcomes. Additionally, symptoms demonstrated to have lesser error than combination in terms of RMS error convergence. Finally, we observed that the machine learning models' build and test durations increased as a result of the combined method. This demonstrates that adding additional parameters does not necessarily result in better outcomes in machine learning applications generally and in medical/dental applications in particular. Instead, it relies on the machine learning tool used, the settings taken into account and the input data provided. The versatility of our approach extends beyond dental contexts. It has been systematically validated across diverse domains, including the recognition of kitchen activities within smart home environments. This methodology holds relevance for various outdoor scenarios where the focal point of attention guides ongoing activities.
Potential of Large Language Models (LLMs) as Supplementary Tools for Historical Learning: Users’ Interaction and Knowledge Acquisition
Authors: Hasnain Muhammad , Usman Sardar
Published: May 2024

This study explores the strengths and limits of large language models (LLMs) in exploring the information on history, an area unexplored in the existing literature. ChatGPT and Gemini, as LLMs, have demonstrated superior performance in education, healthcare, and business. This study proposes utilizing the ChatGPT (ver. 3.5) and Gemini applications to acquire information on historical figures like Sher Shah Suri and Mughal Emperors and Sikhs in the subcontinent. To evaluate the proposed study, this study used two data sets: the first data set comprised a set of questions (n = 26) and the second data set contained questions (n = 35). The results indicate that ChatGPT provides concise answers to the questions of both datasets compared to the Gemini application. However, Gemini exhibited a higher accuracy (92.30%) than ChatGPT with accuracy (76.92%) for dataset 1. For the dataset 2, ChatGPT showed better accuracy (68.57%) than Gemini with accuracy (65.71%). Further research could expand on this study by employing additional artificial intelligence (AI) tools on large-scale datasets from diverse domains.
PERAN INCREMENTAL VALIDITY SEBAGAI PEMEDIASI PADA PENGARUH PROTEAN CAREER TERHADAP CAREER OUTCOME (Studi Kasus Mahasiswa Fakultas Ekonomi dan Bisnis Universitas Muhammadiyah Surakarta)
Authors: Chusna Maulida Purwani , Waskito Jati
Published: May 2024

Individual orientations can differ due to personal tendencies in navigating careers and attitudes. Through this research, it was determined to set objectives to measure the influence of the role of incremental validity as a mediator on the influence of protean career on career outcomes. In the research, it was found through partial least square analysis measurements with a quantitative approach that a number of 100 students from the economics and business faculty at Muhammadiyah University of Surakarta were found as a sample of respondents who were then analyzed to obtain the results, namely Protean career had a positive and significant influence on incremental validity, Protean career had a positive influence and significant on career outcomes and Incremental validity as a mediator has a positive effect on protean career on career outcomes.

Key words: Protean Career, Incremental Validity, Career Outcome, Student
THE STRUCTURE OF PUBLIC SPACE
Authors: Evdokimov V. A.
Published: May 2024

The article examines the structure of public space. Public space is characterized
from the point of view of scale and from the point of view of the spheres of
communicative ties. Interactions in terms of scale take place in the public space of the
world, continental, national, regional, local, in terms of the spheres of reflection of
communicative relations - in the urban, extraurban, Internet environment. Public space
is considered to be a vast system, not limited to the urban environment, which includes
in terms of spheres of expression such segments as political, cultural, economic, ethnic
space. Political space is at the top of this system. The political actors coordinate
people’s interactions in the economic, cultural and ethnic space. At the same time,
interactions in the economic, cultural, ethnic space can influence events and processes
in the political environment. An element of cultural space is the media. Mass media
improves interactive communication with the audience, but not all messages disseminated
by journalists become part of the public space, unless readers, viewers, listeners
participate in the discussion of topical topics. Both constructive discussions
reflecting different viewpoints and simulated discussions that do not represent the
plurality of opinions of free citizens are common in public spaces.
THE LEXICON OF NEW YOUTH SUBCULTURES: INTERNET COMMUNITY OF INFORMAL ARTISTS
Authors: Kochelaeva I. S.
Published: May 2024

The article analyzes the thematic dominants and replenishment sources of the
lexicon of a new youth subculture – informal artists. Author gives the reasons to
consider it virtual, shows its specificity, reflected in vocabulary and phraseology,
groups the lexicon units thematically – the names of the community itself; its
representatives – artists; drawing and stages of its creation; materials and tools used.
Much attention is paid to subcultural names related to the main artistic techniques –
digital and "traditional" drawing. Both neutral (mostly borrowed from English)
and emotionally marked slangisms are shown. Phraseological combinations are also grouped
according to their correlation with the acting subject, the drawing process and the
result evaluation. The definitions of lexical and phraseological units are given,
alongside the examples of their functioning in speech. The thematic parallels of the
lexicon of artists and other creative subcultures are elicitated. The results of this
study can be used to explore the dynamics of youth language and the functioning and
evolution of youth subcultures.
LINGUISTIC REPRESENTATION OF «ECO-ANXIETY» IN BRITISH MEDIA DISCOURSE (A CASE-STUDY
OF THE GUARDIAN)
Authors: Ryzhkova E. V. , Kokkonen E. I.
Published: May 2024

The article provides the results of an analysis of the discursive realization of
the linguocultural concept of «eco-anxiety». The analysis was carried out based on
publications in the Guardian for the years 2015–2023. Within the framework of the
thematic discourse of eco-anxiety, actional subdiscourses are considered: informative,
regulatory, subjective-expressive and prognostic. Based on the linguistic means and
speech strategies presented in the aforementioned subdiscourses, we construct the
conceptual, associative, figurative and value components of the concept of
«eco-anxiety». Eco-anxiety is viewed as associated with the affects of grief, anger,
loneliness, guilt and helplessness. The findings show that the structure of the concept
includes the components “source of anxiety” and «object of accusation». The article also
consideres the apocalyptic modality of the eco-anxiety discourse. Discourse participants
in their speech acts construct a cultural trauma and either take responsibility for
existing problems and their solution or deny them. The results of discourse and content
analysis showed that the significant penetration of eco-anxiety into British linguistic
culture not only determines the emotional background of subjects, but also regulates and
predicts their actions.
MOTIVES OF SPIRITUAL ASCETICISM IN THE KIEVO-PECHERSKY PATERIKON
Authors: Dorofeeva L. G. , Makarova O. F.
Published: May 2024

The article examines examples of the internal struggle of the heroes of the
Kiev-Pechersk paterik with their passions. The texts of the short stories are examined
in a hermeneutical way in their relation to the religious and didactic goals of the work
and with the Evangelical context of the narrative. The short stories of the
Kievo-Pechersk Paterik reflect Christian ideas about sin, among which are avarice, envy,
voluptuousness and others. In the depiction of the spiritual struggle of a monk in the
Paterica, emphasis is placed on the freedom of his choice and the orientation of his
will to the will of God. Following the Gospel commandments of Christ, monks achieve the
main goal of monastic life – victory over passions and assimilation to Christ. The
author comes to the conclusion that the "invisible battle" becomes the
dominant image of the heroes of the Paterican novels, and the motives of spiritual
asceticism are the main ones in the system of toposes of the Kievo-Pechersk pateric,
organizing the compositional structure of the novels and performing an agiological
function.
Influence of Steam Curing Temperature on the Characteristic of Self-Compacting Concrete Incorporating Palm Shell Ash
Authors: Nurjannah Siti Aisyah , Muliawan Sutanto , Nurazizah Ervi Tri Romayni , Asmarani Dwi
Published: May 2024

Self-Compacting Concrete (SCC) is proven as durable concrete and applied to constructions. In this paper, a study was conducted to analyze the influence of variations of steam curing temperature (SCT) and water/binder (w/b) ratio on the characteristics of SCC incorporating 10% Palm Shell Ash (PSA) as a partial substitution for cement mass. The SCT was arranged from 25  C to 80  C. The variation of w/b in the compositions of SCC was 0.325, 0.350, and 0.375. The results showed that using PSA, the variation of SCT and the w/b ratio influenced the workability of the fresh concrete. The PSA, SCT, and the w/b ratio affected the concrete compressive strength and mass density. The increased SCT caused a lighter density and greater compressive strength. However, the decreased compressive strength occurred due to an excessive SCT of 70  C and above. The SCT of 60  C, 10% PSA, and w/b ratio of 0.350 in the mixture produced the greatest compressive strength of 36.27 MPa at 28 days of age, while without SCT, the greatest compressive strength of 36.78 MPa was achieved at the age of 28 days containing 10% PSA and w/b ratio of 0.325. It indicated that the w/b ratio was more influential than the SCT on the increase of the SCC compressive strength.
Analisis Produktivitas Alat Berat dalam Pengelolaan Sampah di Kecamatan Sukarami Kota Palembang
Authors: Firda Ani , Akhirini  , Permatasari Rosmalinda
Published: May 2024

In Indonesia, solid waste has become a problem for municipalities, which could result in hygienic and aesthetically unpleasant issues. The high rate of population growth will have an impact on waste generation since it will change the needs and lifestyles of city dwellers. The collection, transportation, and final disposal of urban solid waste (TPA) require suitable facilities and infrastructure, particularly hefty equipment. Heavy equipment, specifically waste trucks, and heavy digging equipment, plays a significant part in supporting waste management activities. In particular, the Palembang City region is covered in this study's discussion of the productivity of heavy machinery used in waste management, which might begin with the collecting system, transportation system, and heavy equipment employed at the landfill. The study was conducted in Palembang City's Sukarami District, and data was collected by surveying and observing the current condition of the heavy equipment that was already in place, namely in terms of cycle time variables and the volume of waste that was served. The findings of the study indicate that direct communal and direct individual patterns characterize the region's waste-collecting practices. Dump trucks, which are used to transport waste, had a productivity range of 609.98 to 1266.13 kilograms per hour, while bulldozers and excavators had a range of 759.42 to 1166.17 kilograms per hour. This heavy equipment repair recommendation is targeted at bulldozers and excavators since a field investigation reveals that there are now only 2 pieces of bulldozer heavy equipment and 1 unit of excavator heavy equipment available.
Penelusuran Debit Anak Sungai Musi Berdasarkan Pengukuran Curah Hujan Kota Palembang
Authors: Permatasari Rosmalinda , Andayani Reni , Umari Zuul Fitriana
Published: May 2024

The hydrological cycle of the South Sumatra region is influenced by the potential flow produced by the Musi River and its tributaries. The quantity of water that is accessible at any given place is never constant and varies with time. The primary input to the river basin simulation model is flow and discharge data, which must be a time series that completely captures the variability of river flow and discharge data in order to accurately depict water availability. Because the Sekanak River is one of the tributaries of the Musi River, the research built a hydrological model that combines rainfall and river discharge to determine the discharge. The monthly rainfall data is processed to obtain the average rainfall during the data analysis step. The modified Penman method is then used to calculate evapotranspiration. The FJ Mock model was used to examine the mainstay discharge. Results of the discharge analysis for the period of 2018 to 2022 using the FJ Mock method show that the largest discharge occurred between March and June, ranging from 0.203 to 0.241 m3/sec. When the calculated discharge and the actual discharge are compared, it can be seen that the minimum discharge happens in August and the maximum discharge typically occurs in March in the actual discharge data.
A Review of Recent Developments on Modeling Low Impact Development (LID) Technique
Authors: Al Amin Muhammad Baitullah , Sujono Joko , Triatmadja Radianta
Published: May 2024

Urban areas are more susceptible to flooding and water body contamination due to the detrimental effects of urbanization. As a result, a sustainable urban drainage system, also known as low impact development (LID) technique, is required. Although this technique can be extensively applied, the planning and design processes are multi-dimensional, multi-variable, and site-specific, which must consider various local conditions and factors. Consequently, these processes can be very complicated and time-consuming for professionals, necessitating support from computer modeling. This study intends to thoroughly explore the idea of LID modeling, various available computer models, and other tools for its optimization and decision-making processes. The most recent trustworthy journal publications that addressed the subjects under discussion were reviewed. This paper used the descriptive and comparative approaches as the analytical methods. According to the findings of the review, Storm Water Management Model (SWMM) is the computer model in LID modeling that is most frequently employed. This model is a fundamental package for dynamic urban rainfall-runoff modeling, and it has the benefits of being lightweight, simple to use, and an intuitive user interface. Besides, this model is public domain (free to use), open source, and interoperable with many hydro modeling applications. A specific LID editor module is also included in this model for modeling different LID units. To acquire the best LID planning and design from multiple criteria and alternatives, it is also necessary to use metaheuristic algorithms as an optimization model and a multi-criteria decision-making (MCDM) model in addition to the rainfall-runoff model. The authors believe combining the hydrologic and hydraulics models integrated with geographical information systems (GIS), metaheuristic algorithms, and MCDM is the most comprehensive and appropriate method for LID modeling in urban watersheds.