bluuebunny/crossref_metadata_2025 huggingface dataset:
The Menzerath-Altmann Law Interpreted through Analysis of Word Structure in Tatar
Authors: Galieva Alfiya , Vavilova Zhanna
Published: January 2025

Validity of the Menzerath-Altmann law has been confirmed in a number of works for lan-guages with different morphology. This research is aimed at disclosure of potential correla-tions between the structure of the Tatar word form and the average length of its constituent syllables; taking into consideration that the Turkic language family is rarely represented in quantitative linguistics, we tested the law using data from ten Tatar texts, both poetry and prose, to interpret the results from the point of view of grammar. To assess the goodness of fit of the model we applied the coefficient of determination R2 which for different texts ranged from 0.676 to 0.999. The study revealed that the examined data in Tatar generally abide by G. Altmann’s formula; the average syllable length depended both on its position in the word and on word length, and joining more affixes provided decrease in the average syl-lable length. For individual texts, while the law as a trend was observed, we discovered cer-tain fluctuations when the average syllable length for sufficiently long words was greater than for relatively short ones. Analyzing the whole corpus data we distinguished between tokens (with frequencies taken into account) and types (unique word forms considered once); the research proved the Menzerath-Altmann law valid in both cases, with better result for types.
Yield and Quality of Onion (Allium cepa L.) as Affected by Integrated Nitrogen Management
Authors: Ahmad Roheela , Mir Aamir Hassan , Mir Shakeel Ahmad , Makhdoomi Mohammad Iqbal , Wani Fehim Jeelani , Baba Zahoor Ahmad , Parray Imtiyaz Ahmad
Published: January 2025

At the Faculty of Agriculture Research Farm in Wadura, a field experiment was carried out for two consecutive Rabi seasons in 2020 and 2021 to determine the impact of integrated nitrogen management on onion (Allium cepa L.) yield and quality. Randomized block design (RBD) was used to set up the experiment, and the treatments were run in triplicate. When compared to other treatments, the onion yield in the plots receiving 50% N through vermicompost and 50% N through urea during Rabi 2020 and 21 was significantly higher (24.29 t ha-1 and 24.43 t ha-1, respectively), although it was comparable to the treatment receiving 50% N through FYM and 50% through urea. The quality parameters such as ascorbic acid, total soluble solids and pyruvic acid were also found higher in treatments receiving 50 per cent nitrogen through organic sources either through farmyard manure or vermicompost.
Effect of Voltage and Electrode gap on cold plasma temperature
Authors: Kumar Abhishek , Gangil Sandip , Bhargav Vinod Kumar
Published: January 2025

The cold plasma reactor was fabricated and was used for the treatment of different lignocellulosic materials such as rice straw. The operating conditions of plasma were determined under the present study, the independent parameters being the DC plasma voltage, electrode gap and reactor pressure (vacuum), whereas the dependent parameters were the plasma temperature and time. The three levels of plasma temperatures obtained and residence times selected were 110, 117 and 128 and 30, 60 and 120 min, respectively. The increase in plasma voltage resulted in increase of plasma temperature whereas reduction in electrode gap increased the plasma temperature. The above obtained parameters will be used for the treatment of lignocellulosic materials and would be environment friendly and non-toxic in nature.
Screening of Brinjal and Tomato Cultivars for Resistance against Fusarium Wilt (Fusarium oxysporum f.sp. lycopersici) before and after Grafting
Authors: D. Saritha  , M. Rajkumar  , R. Sendhilnathan  , Kumar B. Sunil
Published: January 2025

A poly bag experiment was conducted to screen brinjal and tomato cultivars against Fusarium wilt to identify resistant rootstocks before grafting of tomato cultivars to increase production. The experiment was conducted with four Brinjal cultivars (Solanum torvum, Manjusree, Utkarsha and kirti) and ten tomato cultivars (US-440, Abhiman, Sahoo, Sweakar, Ayaan, Arka abhed, Arka samrat, Ansar, JK Ratan, Aryaman). Among the brinjal cultivars, Solanum torvum (score 0.00) was found to be highly resistant, Utkarsha (score 6.67) was found to be resistant and among tomato cultivars, US- 440, Abhiman, Sahoo, Sweakar, Ayaan, Arka abhed were identified as susceptible (per cent disease incidence 33.3 to 46.67) to fusarium wilt. Screened susceptible tomato cultivars were used as scions for grafting on resistant Solanum torvum and Utkarsha rootstocks. Results revealed that susceptible tomato cultivars grafted on Solanum torvum and Utkarsha rootstocks showed defence mechanism against Fusarium wilt because the rootstock produces chemicals and enzymes that break down fungal cells and has more lignified cells in its roots resulting in improved tolerance.
Neglect and Tokenism: Representations of violence against lesbians in textbooks
Authors: Peel Elizabeth
Published: January 2025

‘When they found out I was a lesbian…My parents decided to look for a husband on my behalf so they brought several boys home to meet me but I was not interested so in the end they forced an old man on me. They locked me in a room, and brought him everyday to rape me so I would fall pregnant and be forced to marry him.’(Excerpt fromGALZnewsletter, reproduced in Rosenbloom, 1996, p. xvi)
Examining coach psychophysiological stress responses during Association Football matches: A preliminary study
Authors: Price David , Corbett Jo , Young John S. , Wagstaff Christopher R.D. , Miller-Dicks Matt , Thelwell Richard
Published: January 2025

The aim of this preliminary study was to examine the psychophysiological stress responses of football coaches during competition and in response to ‘in-game’ critical incidents. Participants were 10 male football coaches (mean = 35.3 ± 8.14 age), five professional and five volunteer coaches. Psychophysiological stress responses, characterised by heart rate, respiratory rate, and salivary alpha amylase activity, were collected at non-competition and across two competitions for all coaches. Individual generalized estimating equations were conducted to model the extent to which psychophysiological indices of stress interacted with time (non-competition, pre-game, in-game) and expertise (professionals, volunteers). Results indicated that both heart rate and salivary alpha amylase activity, but not respiratory rate, were significantly higher (p < 0.05) in competition compared to non-competition. Volunteer coaches also had significantly higher (p < 0.05) levels of salivary alpha amylase activity than their professional counterparts. For the second part of the study examining critical incidents, paired samples t-tests revealed no significant difference for psychophysiological stress responses following a critical incident. The results suggest that coaching practice may evoke a modest psychophysiological stress response with volunteer coaches displaying a higher stress response compared to professional coaches. Applied implications and future recommendations are offered.
Structural quality of a Latosol cultivated with oilseed in succession to soybean
Authors: Bergamin Anderson Cristian , Prado Eber Augusto Ferreira do , Vitorino Antonio Carlos Tadeu , Souza Fábio Régis de , Oliveira Renato Ratier Alves de
Published: January 2025

Understanding the changes in soil structure that develop from oilseed crop successions is vital for successful production. The objective of this study was to evaluate the effects of different oleaginous crop successions on the least limiting water range and load-bearing capacity of a clayey Rhodic Hapludox. The following oilseed crops were cultivated under a no-tillage system in autumn-winter: sunflower (Helianthus annuus L.), canola (Brassica napus L. and Brassica rapa), safflower (Carthamus tinctorius L.), crambe (Crambe abyssinica Hochst.) and niger seed (Guizotia abyssinica). They were sown after soybean and soybean/corn (summer/fall-winter). When the autumn-winter crops flowered, soil samples with structure intact were collected at the 0.0–0.5 m and 0.5–0.10 m depths in metal cylinders. It was observed that in terms of water interval, the poorest soil structural quality in the 0.0–0.5 m layer was provided by the corn/safflower and corn/crambe successions. In terms of soil water content, the optimal time for soil management practices varied for the different oilseeds succeeding soybean. Soil load capacity varies inversely with water content and directly with soil density. Niger grown during autumn-winter in succession to soybean improved Rhodic Hapludox structure more than the other crop successions.
A saúde dos povos indígenas na agenda simbólica presidencial
Authors: Cayres Elaine Martins Pinto , Dias Cristiano Araujo , Nunes Selma Aparecida Chaves , Martins Filho Ismar Eduardo , Vilela Alba Benemérita Alves , Silva Temistocles Damasceno
Published: January 2025

O objetivo desta pesquisa foi analisar a atenção dada à saúde dos povos indígenas na agenda simbólica presidencial brasileira no que se refere ao período de 2002 a 2022. Trata-se de uma pesquisa exploratória, documental com abordagem quanti-qualitativa. O estudo foi delineado com base nos pressupostos teóricos da Ciência Política, especificamente, o modelo teórico do Equilíbrio Pontuado. Sendo assim, utilizou-se o descritor “saúde indígena” para coletar dados nas mensagens presidenciais enviadas anualmente ao Congresso Nacional. Os resultados revelaram a presença do tema na agenda retórica presidencial ao longo do tempo. Ao mesmo tempo, constatou-se um ideário multifacetado acerca da saúde indígena com base na premissa da justiça social, direitos humanos e desenvolvimento sustentável na perspectiva da promoção da igualdade e inclusão social. A análise comparativa entre os governos possibilitou a compreensão do processo de seleção e priorização das pautas correlatas ao tema bem como a identificação dos momentos de continuidade e ruptura da atenção à saúde indígena na agenda presidencial brasileira.
Anatomia cardíaca: relato de experiência de dissecação de coração bovino em aula prática de anatomia humana
Authors: Borges Diogo Gontijo , Silva Talia Cristine Rodrigues , Siqueira Maycon da Silva , Latorraca Elder Francisco , Guerreiro Carlos Tostes
Published: January 2025

O presente trabalho propõe relatar a experiência de uma aula prática de anatomia humana do sistema cardiovascular através da dissecação do coração bovino. O principal objetivo da aula foi empregar metodologias ativas no estudo cardíaco, utilizando-se da dissecação de coração bovino, uma vez que esta técnica é um método que auxilia os profissionais em formação na construção do aprendizado e o órgão utilizado possui grande semelhança com o órgão humano. A atividade foi realizada no laboratório da instituição de ensino, e utilizisou-se kits de dissecação, coração bovino doado por frigorífico e materiais de biossegurança. Observou-se e descrevou-se as características das estruturas cardíacas, como os grandes vasos da base cardíaca, as aurículas, pericárdio e válvas cardíacas. Conclui-se que a dissecação do coração, mesmo não de espécie humana, auxilia consideravelmente no aprendizado do estudante da área de saúde humana, principalmente com o uso da metodologia ativa de ensino-aprendizagem, que demonstrou ser um rico meio de estudo anatômico, sendo a metodologia empregada um facilitador para as futuras associações clínicas na formação médica.
Epistemologia: tendências de análise na produção científica
Authors: Santos João Derli de Souza , Silva Edinéia Pereira da , Kormann Eliane , Gripa Sidnei , Bonin Joel Cezar
Published: January 2025

As concepções de epistemologia oportunizam condições para a realização da análise da produção científica e a crítica das ciências. As análises epistemológicas questionam sobre a produção científica, suas condições, seus processos, produtos, aplicação de seus resultados. Para abordar a produção científica nas suas diversas dimensões, é importante o domínio de categorias que possibilitam nos adentrarmos nos seus elementos internos, na sua organização, estrutura e articulação lógica. O presente texto teve por objetivo apresentar concepções de epistemologia e categorias de análise epistemológica da Produção Científica na Educação. Este estudo se caracterizou como uma pesquisa do tipo bibliográfica. Precisamos buscar novas vertentes e estudos que busquem a superação dos modismos, as dificuldades metodológicas e as lacunas teóricas que interferem na construção histórica desse campo científico.
Validez basada en la estructura interna, validez convergente y confiabilidad del Inventario de Dependencia Emocional (IDE) en adultos jóvenes
Authors: Aiquipa-Tello Jesús Joel , Ponce-Díaz Carlos Ramón , Pacheco-Luza Edgard Fernando
Published: January 2025

La dependencia emocional es un constructo que está generando mayor interés por una parte de la comunidad científica. Por ello, es importante disponer de instrumentos que reúnan propiedades psicométricas adecuadas para su medición. El objetivo del estudio fue analizar las evidencias de validez basado en la estructura interna, validez convergente y medida de confiabilidad del Inventario de Dependencia Emocional (IDE). Participaron 1,401 adultos jóvenes (M =21 años, DE = 2.7; 24.2% varones y 75.8% mujeres), residentes en la ciudad de Lima, Perú. Se usó análisis factorial confirmatorio y medidas de asociación bivariada. Los resultados sugieren que el IDE presenta evidencias de validez de estructura interna para un modelo de siete factores oblicuos; dispone de evidencias de validez basado en la relación con violencia de pareja y satisfacción con la vida; y las dimensiones que la conforman presentan medidas de confiabilidad satisfactorias. Estos hallazgos pueden respaldar el uso del IDE en evaluación e investigación.
Variables involved in the long-term alcohol abstinence: Which variables are involved and at what point of time?
Authors: Jurado-Barba Rosa , Espinosa Regina , Marín-Mayor Marta , Sion Ana , Rubio-Valladolid Gabriel
Published: January 2025

Several psychological variables have been associated with the prognosis during alcohol dependence treatment and after discharge. However, we still do not know the role that these variables play in the achievement of abstinence and if they modify throughout time. Method: Longitudinal survey data related to anxiety, depression, impulsivity, coping, meaning in life (MiL) and attendance to mutual-help groups were collected from outpatients with alcohol dependence (N= 159, 66% male, mean age=42.54 years). Assessment points were the following: baseline, at discharge (after 2-years of treatment), and 2-years and 4-years follow-up after discharge. Drinking outcomes were evaluated with the Timeline Followback Method Assessment. Results: At baseline, levels of avoidance coping and impulsivity were associated with months of accumulated abstinence at 4-years-follow-up. However, at discharge and at two-years follow-up, higher scores in MiL were consistently associated with months of accumulated abstinence at 4-years of follow-up. Mediation models showed that MiL increased accumulated abstinence at 4 years-follow-up by increasing avoidance coping and reducing levels of depression. Conclusions: MiL is a determining component in the long-term sustained abstinence. Our results support the key role of MiL and point to a new mechanism through which it influences the maintenance of sobriety. Because mutual-help groups have consistently demonstrated to promote MiL, they should be implemented and recommended as an essential part of an integrated treatment of alcohol dependence.
Efficacy of transcranial direct current stimulation (tDCS) in tobacco use: a PRISMA systematic review
Authors: Quiñonez González Eimy Mariana , Gadea Doménech Marien , Espert Tortajada Raúl
Published: January 2025

Introduction: Transcranial direct current stimulation (tDCS) is an emerging, non-invasive, and safe brain neuromodulation technique intended to relieve symptoms associated with psychiatric disorders, including addiction. Research on tobacco consumption offers promising results; however, at the same time, a lack of replicability is evident among current studies. Objective: To offer an overview of the effectiveness of the tDCS intervention in tobacco consumption over the last 10 years (2014-2024). Method: Systematic review of controlled, double-blind, and randomized empirical studies registered in Science Direct, Scopus, and PubMed between 2014 and 2024. Results: Thirteen empirical studies have been examined that aim to investigate the effects of tDCS stimulation associated with tobacco consumption, highlighting a heterogeneity between the results, since depending on the variable evaluated and the parameters of the stimulation protocol, its effectiveness may vary. Conclusion: The present systematic review shows that tDCS continues to be a promising technique as an alternative for the treatment of tobacco consumption, showing effective results in reducing craving and consumption patterns.
The effect of biological factors on Fusarium oxysporum inhibition causing Fusarium wilt disease on cowpea ( _Vigna unguiculata_ )
Authors: Zainab Asaad Jabr  , Alaa Oudah Manea
Published: January 2025

This study was conducted for the agricultural season 2023-2024 with the aim of evaluating the efficiency of bio agent of Bacillus cereus, Trichoderma Longibrachiatum and Saccharomyces cerevisiae on Cowpea plants infected with Fusarium wilt disease in pots. Three isolates R2, R3 and R7 of Fusarium oxysporum were isolated from the roots of Cowpea plants that showed symptoms of wilt. The isolated fungi were diagnosed morphologically and partially. The results of molecular diagnosis of the fungi showed 100% matching of the isolates. Pathogenicity tests were conducted on cowpea seeds in the laboratory using Petri dishes containing W.A medium as a pathogen for cowpea plants, as the germination percentage of cowpea seeds for all isolates reached 76.66, 66.66 and 63.66% compared to the control treatment which reached 100%. The results of the pot experiment showed that there were no significant differences in the infection severity by the pathogenic fungus in the three isolates, as R2 reached 82.00, R3 82.00 and R7 87.33% respectively compared to the control treatment which reached 0.00%. The results of the pot experiment indicated the effect of bio agent in increasing some plant growth indicators and reducing the infection severity which reached 0.00% in the T. Longibrachiatum, B. cereus and S. cerevisiae treatments. It was also noted from the results that the highest germination rate of cowpea seeds was in the yeast S. cerevisiae treatment, which reached 96.00% compared to the control treatment, which reached 100%. The results of chlorophyll estimation indicated that the treatment of the biological fungus T. Longibrachiatum and the yeast S. cerevisiae was similar to the control treatment, which reached 0.82 mg/g¯¹.
Neutrosophic Burr Distribution for Modeling Health Risk Factors
Authors:   Department of Mathematics, College of Science and Humanities in Al-Kharj, Prince Sattam Bin Abdulaziz University, Al-Kharj, 11942, Saudi Arabia, Zahid Zahid ,   Department of Quantitative Methods, Pannon Egyetem, Veszprem, H-8200, Hungary, Khan Zahid
Published: January 2025

The Burr distribution is one of the most important and commonly used probability distribution in statistical analysis. In this study, a new class of univariate distribution based on the Burr random variable is proposed. Characteristics of the proposed neutrosophic Burr distribution (NBD) are discussed. The neutrosophic form of the proposed distribution is particularly advantageous for handling the imprecise and uncertain information commonly present in real-world problems. The statistical properties and the shapes of corresponding probability density and cumulative density functions are illustrated. Some important functions commonly utilized in survival studies are formulated within neutrosophic structures. General expressions for other distributional properties of the proposed NBD are developed under neutrosophic framework. The inverse cumulative method is used to find random numbers from the suggested model. Maximum likelihood method for estimating the model parameters is described, and the performance of estimated parameters are assessed using a Monte Carlo simulation experiment. Finally, the paper demonstrates the practical use of the proposed model through a real-world application of malaria cases per thousand population at risk.
Instigator of Type 1 Diabetes Mellitus (T1D): Connecting Human Leukocyte Antigen (HLA) with Infant Gut Microbiome
Authors: Li Yujia , Milletich Patricia L.
Published: January 2025

Type 1 Diabetes Mellitus (T1D) is driven by the interplay between genetics and other factors, though the exact relationship between gut microbiome and T1D onset remains unclear. This study aims to investigate the connections between Human Leukocyte Antigen (HLA) genetics, gut microbiome, and their relationships to T1D seroconversion. Data from the Diabimmune website provided stool samples (n=1443) from children aged 16 to 36 months from Finland, Russia, and Estonia, categorized by HLA risk factors and seroconversion status. Statistical analyses using the Wilcoxon rank-sum test measure were conducted. High-risk HLA individuals generally had a lower relative abundance of beneficial bacteria such as Lachnospira. Predicted metabolic pathways PWY.5676 and PWY.7220/7222 had an increased abundance in low-risk HLA infants in multiple age groups. Prevotella was more abundant in seroconverted samples, while Ruminococcus, Hungatella, and Sutterella were more abundant in non-seroconverted samples. Shared pathways between different age groups such as GLYOXYLATE.BYPASS showed higher abundance in non-seroconverted samples, each with similar median abundance across different age groups. The findings suggest that gut microbiome dysbiosis, characterized by a lower abundance of beneficial SCFA-producing bacteria and the prevalence of pathways supporting bacterial persistence and immune stimulation, contributes to T1D onset. Future research should focus on advanced genomic and metabolomic analyses, functional assays, co-culture experiments, and developing predictive models using machine learning to assess autoimmune disease risk based on bacterial strains and HLA haplotypes
Elevated Risk of Preeclampsia in Obese Pregnancies: The Interaction Between Metabolic Dysregulation and Placental Dysfunction
Authors: Zhang Hange
Published: January 2025

Preeclampsia, a hypertension condition during pregnancy, presents considerable dangers to both maternal and fetal well-being. Maternal obesity is becoming acknowledged as a significant modifiable risk factor for preeclampsia; however, the underlying mechanisms are intricate and varied. This paper explores how metabolic dysregulation in obese pregnancies can lead to issues with the placenta. Key problems include insulin resistance, chronic inflammation, oxidative stress, and the role of anti-angiogenic factors like soluble fms-like tyrosine kinase-1 (sFlt-1) based on existing literature and data. Elevated leptin and reduced adiponectin levels, common in obesity, further exacerbate endothelial dysfunction and contribute to systemic inflammation. Additionally, obesity-related dyslipidemia worsens the oxidative and inflammatory processes that drive placental ischemia and vascular complications in preeclampsia. Through a synthesis of current research, this study highlights the intricate relationship between maternal obesity and the heightened risk of preeclampsia, emphasizing the need for targeted interventions in weight management to improve pregnancy outcomes
Machine Learning-Based Financial Big Data Analysis and Forecasting: From Preprocessing to Deep Learning Models
Authors: Zhang Daren , Tang Nyusifan , Dong Wanchen , Zhao Lu
Published: January 2025

Machine learning technology has revolutionized the financial sector by allowing faster and more accurate analysis and forecasting of large-scale financial data. This paper focuses on how machine learning ( ML ), especially deep learning models, can help to deal with high dimensional, noisy, and non-stationary financial data. Essential methodologies such as data preprocessing, feature engineering, and dimensionality reduction are imperative for preparing the raw financial data to ML algorithms. Methods such as outlier detection, normalisation for preprocessing, and feature (variable) selection for dimensionality reduction improve the models accuracy and efficiency. The paper also examines how deep learning models, such as Recurrent Neural Networks ( RNN ) and Long Short-Term Memory ( LSTM ) networks, can overcome the issues of autoregressive integrated moving average ( ARIMA ) models for financial time series prediction. An in-depth comparison of the machine learning models, ranging from supervised to unsupervised methods, is also provided to discuss their pros and cons in the financial domain, including popular applications such as credit scoring, fraud detection, and market risk prediction. The study finally concludes by discussing how optimisation methods such as hyperparameter tuning and cross-validation are imperative for ML models in complex financial scenarios to ensure their generalisation capability and avoid overfitting.
Predicting Employee Turnover in the Financial Company: A Comparative Study of CatBoost and XGBoost Models
Authors: Yin Ziqing , Hu Baojun , Chen Shuhan
Published: January 2025

Employee turnover is a significant issue for financial institutions, impacting productivity, increasing recruitment costs, and disrupting critical operations. In this project, this study aimed to predict employee turnover using a dataset containing attributes such as employee satisfaction, performance, and tenure. By framing the task as a binary classification problem, this study employed CatBoost and XGBoost, two advanced regression-based algorithms, to develop predictive models. This paper's analysis demonstrated that CatBoost outperformed XGBoost across all evaluation metrics, including MAE, MSE, RMSE, and R, making it the more effective model for predicting turnover in the financial sector. The study highlights key factors contributing to employee attrition, such as job satisfaction, tenure, and promotion opportunities, offering actionable insights for retention strategies. Additionally, by predicting probabilities rather than binary outcomes, this study aims to make more detailed decisions about employee retention. This research provides valuable tools for financial institutions to mitigate the risk of turnover, retain critical talent, and ensure operational continuity.
A Review of Current Research and Future Development of Autonomous Driving Technology
Authors: Zhang Kun
Published: January 2025

At present, the automobile industry is undergoing a new round of technological revolution, and autonomous driving technology is also experiencing a period of rapid development, with very active research and technology iteration. Autonomous driving can prevent accidents that occur due to human errors such as inattentiveness and driver fatigue, thereby enhancing road safety. Additionally, autonomous technology helps alleviate traffic congestion and optimize flow by utilizing coordinated driving strategies, such as vehicle-to-vehicle communication (V2V) and vehicle-to-infrastructure communication (V2I), enabling platooning, intelligent rerouting, and other advanced driving techniques. The autonomous driving system can control the vehicle according to the optimal driving strategy, can drive the vehicle in a smoother way, optimize fuel consumption or power use, thereby reducing operating costs and improving travel experience, and has a wide range of application potential and potential social value. This paper summarizes the current research status and development trend of autonomous driving technology, summarizes the current research status of autonomous driving technology from the aspects of environmental perception, machine learning, control execution, etc., while also projecting future directions for the field. Advancements in this technology have the potential to revolutionize transportation, offering significant convenience and transforming daily life. Moreover, it can promote the development of major industries, increase national GDP, affect urban planning and layout, and even improve our living environment and benefit ecological construction.
Comparison of Environmental Benefits between Photovoltaic and Wind Power Based on LCA Method
Authors: Chen Hanye
Published: January 2025

Since the 21st century, climate change is a global issue that affects every corner of the world and extreme weather occurs frequently. The Paris Agreement proposes that countries should strengthen their response to the threat of climate change. Countries around the world are actively seeking energy transition. Photovoltaic power generation and wind power generation are the most important renewable energy generation methods in the world. These two technologies are pollution-free and zero carbon emission during the power generation process. But from the perspective of the full life cycle, there is still some controversy over the environmental benefits of both at present. This article normalizes and analyzes the input-output data of the cradle to grave process using the LCA methodology, and the results indicate that the environmental impact of photovoltaic power generation throughout the full life cycle is significantly greater than that of wind power generation. Based on the above conclusions, several measures are proposed to improve the ecological benefits of both photovoltaic and wind power generation.
Study of Bionic Tactile Sensors in Flexible Robots
Authors: Wang Jian
Published: January 2025

This research investigates the advancement and implementation of bio-inspired tactile and mechanosensory systems, drawing inspiration from sophisticated biological mechanisms found in nature, particularly human sensory networks and the Venus flytrap's rapid response system. The study demonstrates significant progress in developing highly sensitive and precise sensor technologies that effectively mimic natural sensing capabilities. Through innovative material combinations and structural designs, including hybrid graphene-based platforms and advanced piezoelectric tactile arrays, these sensing systems achieve enhanced detection of mechanical forces, subtle vibrations, and environmental fluctuations. The research findings indicate substantial improvements in sensor performance metrics, including response time, sensitivity threshold, and signal-to-noise ratio. Current challenges in manufacturing scalability and cost-effectiveness are addressed, with proposed solutions for large-scale production and seamless system integration. The study outlines promising applications across multiple fields, from advanced prosthetic limbs with enhanced tactile feedback to sophisticated robotic systems capable of precise environmental interaction. Future research directions emphasize the development of more robust and adaptable sensing platforms, focusing on improved durability, reduced power consumption, and enhanced integration capabilities for next-generation biosensing applications.
The Influence of Carbon Nanotube Composites of Precious Metals and Non-precious Metal Oxides on the Electrode Performance of Supercapacitors
Authors: Lyu Yuke
Published: January 2025

As the problems of energy shortage and environmental pollution are increasingly escalating, the development of efficient and sustainable energy storage technologies has become extremely important. Among these technologies, supercapacitors are receiving significant attention due to their relatively high energy density and power density, making them a promising solution for future energy needs. The unique combination of fast charge-discharge capability, long cycle life, and reliability makes supercapacitors attractive in fields such as portable electronic devices, electric vehicles, and renewable energy integration. In particular, composite materials containing carbon nanotubes and metal oxides are of great research interest in improving the performance of supercapacitors. For example, incorporating non-precious metal oxides (such as manganese oxide and nickel oxide) or precious metal oxides (such as ruthenium oxide) into carbon-based materials can significantly enhance electrochemical performance. An appropriate loading quantity of active materials plays a crucial role in achieving high specific capacitance. Furthermore, different composite preparation techniques have a significant impact on the microstructure of the materials, thereby markedly changing the electrochemical characteristics of the electrode and affecting its overall performance in energy storage systems.
Low-Power Optimization Design Strategies for CMOS Digital Integrated Circuits
Authors: Yang Aoqi
Published: January 2025

With the rapid development of digital chip technology, the functions have become increasingly powerful, and processing speeds continue to rise. However, this progress comes at a cost, particularly with the significant increase in chip power consumption. The rise in power consumption directly leads to a continuous growth in chip heat generation, which not only affects the performance stability of the chip but also poses a severe challenge to the battery life and user experience of mobile consumer electronics. Especially in todays context, where consumer reliance on mobile devices is deepening, the demand for low power consumption in digital chips is becoming increasingly stringent. If chip power consumption is too high, its performance will be severely compromised, potentially failing to meet practical application needs. Therefore, optimizing the power consumption of digital integrated circuits has become a hot topic in the industry. While various optimization strategies for digital integrated circuits are emerging, there is a lack of a clear and systematic classification. Based on a thorough analysis of existing optimization strategies, this paper innovatively proposes a new classification framework. This classification framework not only facilitates a more comprehensive understanding of the characteristics and applicable scenarios of various optimization techniques but also provides strong theoretical support and practical guidance for future power optimization research. The article will then provide a detailed introduction to this classification method and discuss its application prospects in the field of power optimization for digital integrated circuits.
Strategies of Building AI Agents for Multimodal Productivity with Contemporary Large Language Models
Authors: Li Xiaotian
Published: January 2025

The past few years have witnessed significant advancements in generative artificial intelligence (AI) led by large language models (LLMs), applications demonstrating capabilities in traditionally unattainable tasks. Numerous efforts are being initiated exploring a prospect all the more exciting, to employ LLMs not just as language processors, but as a starting point toward AI agents that can adapt to diverse tasks and complex scenarios. In this paper, a survey is offered on the state-of-the-art strategies of deploying such models for the generation of both text-based domain-specific contents and multimodal outputs embodied in interactions with web applications, industrial software and ultimately the physical world. Two approaches to implementing multimodality are delineated: Direct embedding of multimodal data, and conversion of multimodal data to text. Both types have seen extensive use in areas of research focus, such as image processing, embodied action and software automation. Representative cases from these categories are reviewed with a focus on their input/output modalities, methods of processing multimodal data and output quality.
User Behavior Analysis and Prediction Based on Differential Evolution Algorithm Optimized Transformer Combined with Bidirectional Long Short-Term Memory Neural Network
Authors: Liu Yuxin , Zhang Yuhan , Hu Minxuan , Tu Yuming , Dong Xinqi
Published: January 2025

This paper discusses a method combining differential evolution algorithm and bidirectional long short-term memory neural network (BiLSTM) to optimize Transformer model, aiming to improve the accuracy of bank customer credit analysis and prediction. By optimizing the parameters of Transformer model through differential evolution algorithm and combining with the powerful time series analysis capability of BiLSTM, an efficient credit prediction model is constructed. In the process of model training, with the increase of the number of iterations, the correct rate of the model steadily improves and eventually becomes stable. Meanwhile, the value of the loss function also gradually decreases, indicating that the performance of the model on the training data is gradually enhanced. In addition, through confusion matrix analysis, we found that the prediction accuracy of the training set reached 86.15%, and that of the test set reached 82.91%, which showed that the model not only performed well on the training data, but also had strong generalization ability on the unseen data. In addition, the F1 score and DAUC values of the model are both positive, which further confirms the superiority of the model's prediction effect. The research results of this paper show that the Transformer model optimized by differential evolution algorithm and BiLSTM has high accuracy and good generalization ability in the analysis and prediction of bank customer credit. This optimization method not only improves the prediction performance of the model, but also enhances the stability and reliability of the model in practical application by reducing overfitting. Through this optimization strategy, banks can more accurately assess the credit risk of customers and make more informed credit decisions. This research provides a new technical means for credit risk assessment in the financial field, which is helpful to improve the efficiency and security of banking business.
УЛУЧШЕНИЕ ОБУЧЕНИЯ С ПОМОЩЬЮ ЧЕЛОВЕКО-ЦЕНТРИРОВАННОГО ДИЗАЙНА: НОВАЯ ПЛАТФОРМА
Authors: Мадениетов М.А.
Published: January 2025

В этой статье рассматривается разработка и эффективность игровой обучающей платформы, предназначенной для повышения вовлеченности студентов и результатов обучения. Традиционные методы обучения в высших учебных заведениях часто не отвечают разнообразным потребностям студентов в обучении, что приводит к снижению вовлеченности и эффективности. Наше исследование направлено на преодоление этого разрыва путем включения элементов из когнитивной науки, геймификации и комиксов в новую платформу электронного обучения. Платформа была разработана с использованием фреймворка Angular и включала различные интерактивные компоненты, такие как видеоуроки, анимации «картинка-текст-текст» (PTT) и комиксы для мотивации студентов. Мы провели эксперимент с 12 студентами, разделенными на четыре группы: одна использовала традиционные методы обучения, а три использовали различные типы контента на игровой платформе. Знания участников оценивались с помощью предварительных и итоговых тестов, а их настроение и уровень вовлеченности измерялись с помощью фанометра. Результаты показали, что студенты, использующие игровую платформу, особенно в группе типа 1 (комиксы, за которыми следовали видео и PTT), показали значительно более высокие результаты в обучении и баллы за настроение по сравнению с теми, кто использовал традиционные методы. Исследование подчеркивает потенциал геймифицированных и ориентированных на человека проектов в улучшении образовательного опыта. В дальнейшем исследования будут сосредоточены на тестировании платформы на разных возрастных группах и предметах, чтобы лучше понять ее более широкую применимость и долгосрочные эффекты на мотивацию и обучение студентов.
Transformation of Kyai's Democratic Leadership in Maintaining the Existence of Ibnul Qoyyim Putri Islamic Boarding School Berbah Sleman Yogyakarta
Authors: Rubini
Published: January 2025

The purpose of this study is to understand the democratic leadership transformation efforts made by Kyai in increasing the existence of the Ibnul Qoyyim Putri Islamic boarding school in Berbah, Sleman Yogyakarta. This research employs a qualitative approach with a case study design, allowing the researcher to explore the context and dynamics of democratic leadership at Ibnul Qoyyim Putri Islamic Boarding School. The research subjects include the chief of the Islamic boarding school (Kyai), the head of the madrasah, teachers, educational staff, employees, students, and parents of students. Data collection techniques involve interviews, observations, and documentation. The analysis is conducted through several steps: data transcription, coding, thematic analysis, and interpretation. To ensure data validity, the researcher will use data triangulation by comparing information from various sources and methods and perform member checking by providing preliminary results to several respondents for confirmation and feedback. The findings indicate that transformation of the democratic leadership of the Kyai in maintaining the existence of the Ibnul Qoyyim Putri Islamic boarding school in Berbah, Sleman, Yogyakarta brings significant benefits to the existence and development of the boarding school. This democratic leadership is characterized by a deliberative system, where the Kyai shares decision-making responsibilities with staff and employees, delegates authority, and facilitates reciprocal communication. Although Kyai is not directly involved in daily operations, the provided guidance and periodic control demonstrate a collaborative and trusting attitude. This leadership style promotes active participation in decision-making and has positive impacts, including increased engagement and motivation, character development, and community strengthening.
Shared Leadership in Schools: Strategies for Improving Teacher Performance
Authors: Rozalinda Kelly , Ali Marzuki Zebua
Published: January 2025

This study explores the implementation of shared leadership in schools: Strategies for improving teacher performance. This qualitative case study found that shared leadership in this school was applied through several key indicators, including effective communication, trust given to teachers, staff involvement in decision-making, and the principal's flexibility in responding to change. The principal regularly engaged teachers through meetings to clarify the school's vision and programs, entrusted them with classroom management, and supported online learning during the pandemic. The results show a significant improvement in teacher performance, with key performance indicators such as planning, implementation, and assessment of learning increasing from 57% in 2021 to over 90% in 2023. In 2022, the teacher performance percentage reached 68%-80%, indicating adaptation and improvement in task execution. The peak of performance improvement was achieved in 2023, with over 90% for most indicators. The implementation of shared leadership has proven to support teachers in creating a productive and inclusive learning environment, contributing to the achievement of better educational outcomes in this school.
Implementation of the Merdeka Belajar Kampus Merdeka (MBKM) Towards Policies at UIN Sunan Kalijaga Yogyakarta
Authors: Mubarok Fatahillah  , Abd Razak Zakaria  , Rika Evania Muslimatun
Published: January 2025

The Merdeka Belajar Kampus Merdeka (MBKM) policy is a strategic initiative by Indonesia's Ministry of Education, Culture, Research, and Technology to create a more flexible, adaptive, and industry-relevant education system. This study explores the implementation of the MBKM policy at UIN Sunan Kalijaga Yogyakarta and its impact on students, faculty, and administrative staff. Using a descriptive qualitative approach, data were collected through observations, in-depth interviews, and documentation. The findings reveal that the MBKM implementation at UIN Sunan Kalijaga has led to significant changes in curriculum, teaching methods, and student engagement in off-campus activities. Additionally, the program encourages students to take a more active role in decision-making regarding their educational pathways, enhances curriculum relevance to industry needs, and strengthens students' skills to face workplace challenges. Overall, the MBKM policy at UIN Sunan Kalijaga positively impacts higher education quality by facilitating the development of skills that are more responsive to global changes.
A multidisciplinaridade da língua portuguesa no processo de ensino – aprendizagem da matemática
Authors: Diogo Gilson Francisco Contreiras , Gáz Domingos de Araújo
Published: January 2025

The article arises from the need to determine the importance of the language of schooling, particularly in the Mathematics teaching-learning process, in a qualitative approach. It is the result of an investigation into the importance of the multidisciplinary nature of the Portuguese language for understanding other subjects in the school context. As far as the supporting theory is concerned, the study was conducted based on Bloom´s Taxonomy theory, which aimed to determine how writing influences understanding in the Mathematics teaching learning. The general objective is to determine how written communication can influence the understanding of Mathematics. In fact, understanding mathematical concepts requires mastery of the language of schooling. To achieve this, one of the specific objectives is to describe how the Portuguese language can contribute to the development of mathematical skills. As for the research model, the study is qualitative in nature, with a descriptive focus. As far as the participants concern, it was possible to count on students from the first circle of the kudyelela school, in Malanje, north of Angola. As for the age range of the participants, it ranges from 12 to 17 years old. For data collection, observation techniques and semi-structured interview were used. The results illustrate that to better learn Mathematics, knowledge or mastery of the language of schooling is crucial. Likewise, the results determine that the comprehension of writing and mathematical symbols is based on knowledge of the language of schooling, in the case, the Portuguese language.