bluuebunny/crossref_metadata_2025 huggingface dataset:
METADATA MANAGEMENT FOR OPEN GOVERNEMENT DATA: A PROPOSE FOR A INDUSTRY OBSERVATORY
Authors: COUTO MARCELO , Salete Trzeciak Dorzeli , Da Silva Dias Júlio
Published: December 2024

The objective of this article is to present a template proposal for metadata cataloging of the databases of a industry Observatory. This is an applied research study with a qualitative, exploratory, and descriptive approach. It employs bibliographic research as a technical procedure. The development of the template considered elements related to metadata repositories, with the FAIR initiative serving as the primary reference, and the FAIR Data Point technology assisting in information retrieval from data repositories. The developed template outlines the basic information necessary for understanding the industry Observatory's databases through metadata that describe their characteristics, location, and the questions they address. The template primarily used metadata proposed by FAIR Data Point technology; however, it was necessary to add some metadata adapted to the Observatory's context to facilitate the information retrieval process from the available data. This study contributes to reducing the time required to search for data on specific topics, knowledge management, and assessing the potential uses of the database for the evolution of the industy Observatory as an intelligence center, meeting demands, and creating products, projects, and services in line with its business objectives.
EMPOWERING LEADERS THROUGH INTENT – BASED LEADERSHIP: A TRANSFORMATIVE APPROACH IN MILITARY EDUCATION
Authors:   “Henri Coandă” Air Force Academy, Braşov, Romania, DRAGOMIR Cristian
Published: December 2024

This article examines the application and potential impact of intent-based
leadership (IBL) in military education, focusing on its ability to enhance decision-making,
autonomy, and responsibility among military cadets and officers. IBL, a leadership model
popularized by the former U.S.. Navy Captain David Marquet shifted authority from a
centralized, top-down approach to a decentralized system that empowers subordinates to make
decisions aligned with the commander’s intent. This study aims to document the existing research
on IBL and analyze its effectiveness in military settings, drawing insights from both case studies
and leadership programs in high-stakes environments. This article reviews documented evidence
from various military academies and allied organizations, focusing on the alignment between IBL
principles and the desired leadership competencies of military personnel. The findings suggest
that IBL can address key gaps in traditional military leadership training by enhancing critical
thinking, adaptability, and accountability among trainees. However, implementing IBL in military
institutions presents challenges, including resistance from entrenched hierarchical structures,
and the need for extensive cultural adaptation. This study provides a foundation for
understanding the potential of IBL in military education, highlighting both the opportunities for
leadership development and the structural considerations necessary for effective implementation.
A VERSES REGÉNY ÉS AZ EMBERISÉGKÖLTEMÉNY DISKURZUSA
Authors: TÖRÖK Gabriella
Published: December 2024

Madách Imre Az ember tragédiája (1862) és Závada Pál Apfelbaum. Nagyvárad, Berlin (2022) című verses regénye több aspektusból vizsgálódva is párhuzamba állítható. A két szerző regényében ellentétek és analógiák sokasága kereszteződik. A dolgozat összehasonlítási alapon, komparatisztikai módszerrel próbál rávilágítani a közöttük lévő azonosságokra, különbségekre, illetve a művek kapcsolódási pontjaira. A kutatás fő célja a művekben megjelenő szereplők vizsgálata, kiváltképp az istenkép megjelenítése, valamint a dolgozat az irodalomban jól ismert toposzt, a női alakok mibenlétét is taglalja.
Prediction of arsenic (III) adsorption from aqueous solution using non-neural network algorithms
Authors: Mirza Nazmul Hassan , Fujino Takeshi
Published: December 2024

Heavy metals such as arsenic can be effectively removed through adsorption. Through material property evaluation and adsorption parameter optimization, machine learning (ML) modeling provides an alternative to lengthy laboratory experimentation. In this work, adsorption data from an earlier study employing a waste-material composite were used. To create prediction models, four non-neural network algorithms - support vector machines (SVM), Gaussian process regression (GPR), linear regression, and ensemble approaches - were used and contrasted with neural network algorithms. Nine predictors were utilized, ranging from adsorbent composition alterations to experimental circumstances. Using principal component analysis (PCA) and feature selection, together with the F-test and minimum redundancy maximum relevance (MRMR) algorithms for feature reduction, optimization was accomplished. With an R-squared of 0.939, mean absolute error (MAE) of 5.778, and root mean squared error (RMSE) of 7.119 for training and an R-squared of 0.942, MAE of 5.450, and RMSE of 6.870 for testing, the optimized GPR method offered the best predictive performance. The best R-squared values found for other algorithms were: SVM (0.922), linear regression (0.925), and ensemble (0.927). The most important variables influencing adsorption efficiency were initial arsenic concentration, time, and the iron salt content. Local interpretable model-agnostic explanations (LIME), partial dependence plot (PDP), and Shapley additive explanations (SHAP) plots were used to explain these results. This work shows that, based on model-derived parameters, non-neural network algorithms may efficiently simulate and optimize arsenic adsorption tests, providing a trustworthy substitute for neural network techniques and markedly increasing adsorption efficiency.
KI AGENG SURYOMENTARAM
Authors: Safei Abdullah
Published: December 2024

For decades, Indonesia’s development has placed more emphasis on physical aspects. Social sciences were abandoned because the government only looked for easy things. Society will surrender when all that is done is physical development, but social science is not developed. Even only given a small portion. In a national context, society needs to have an independent spirit. The government needs to build the soul of citizens by developing and changing the soul of the colonized into an independent soul. Many events that occur in society are caused by humans starting not to understand their true nature. Forgot to fix a pure soul. As a result, humans carry out actions that are not by religious rules or norms. This research is qualitative with a philosophy-praxis-sufism perspective and it can be concluded that Ki Ageng Suryomentaram in his thoughts as outlined in the book “Ilmu Kawruh Jiwa Suryomentaram, History and the Path to Happiness” emphasizes that he invites us as Indonesian people to feel the taste of life, examine every feeling, and reach the true meaning of happiness. True happiness is not out there but within yourself. Free and independent happiness does not depend on time, place, and circumstances. Understanding the soul will make humans understand their nature in life and society. When humans become aware and begin to understand or understand the soul, they will be able to improve themselves, maintain their actions and attitudes, and understand other people.
IBN TAYMIYYAH’S PHILOSOPHICAL CRITIQUE TO IBN ‘ARABĪ’S WAḤDAT AL-WUJŪD THOUGHT
Authors: Hakim Lukmanul , Ahmad Ahmad , Tri Hadi Rahmad
Published: December 2024

This research aims to describe and analyze Ibn Taymiyyah’s philosophical-constructive critique of Ibn ‘Arabī’s waḥdat al-wujūd thought. The method used in this research is descriptive-analytical. The primary data used in this research are the works of Ibn Taymiyyah and Ibn ‘Arabī. Meanwhile, secondary data in this research are books, journal articles, and other websites that discuss the thoughts of Ibn Taymiyyah and Ibn ‘Arabī. The research results show that Ibn Taymiyyah rejected thinking of waḥdat al-wujūd, because of his understanding of the doctrine of waḥdat al-wujūd This is different from the understanding of Ibn ‘Arabī and his followers. According to Ibn Taymiyyah, waḥdat al-wujūd is the equating of God with nature. In modern terms synonymous with pantheism. Ibn Taymiyyah said those who adhere to waḥdat al-wujūd say that existence is one, and wajib al-wujūd what God has is the same as possible waḥdat al-wujūd that a creature has. Ibn Taymiyyah’s criticism emerged because he only saw aspects of tashabbuh (equation of God with his creatures) from understanding waḥdat al-wujūd, and did not see aspects of tanzīh (purification of God from the likeness of his creatures) from the same understanding. These two aspects are combined into one in the teachings of Ibn ‘Arabī. Even according to Ibn Taymiyyah, the understanding that considers God’s existence to be united with the existence of His creatures is a form of disbelief for God, a form of disbelief and shirk in Him.
High density polyethylene microplastics biodegradation by bacteria isolated from a landfill in Cali, Colombia
Authors: Martinez-Delgado Juliana , Benítez-Campo Neyla
Published: December 2024

Microplastics cause pollution problems because they are difficult to degrade and tend to be easily transported and accumulate in the environment. Biodegradation is a promising solution by exploiting the ability of fungi or bacteria to accelerate the degradation process of microplastics, but this is a topic with several knowledge gaps. To evaluate the ability of microorganisms to degrade high-density polyethylene microplastics, four bacterial strains isolated from a sanitary landfill were selected, in a minimal salt medium with microplastics as the sole carbon source. The selected strains were identified as Tsukamurella sp. strain JP3, Tsukamurella sp. strain JP5+, Pseudomonas aeruginosa (JP5–) and Streptomyces sp. strain JP8. The bioassays were performed with single strains and mixed cultures. Biodegradation was determined by calculating the percentage weight loss of the microplastics and observing changes in their surface structure using scanning electron microscopy (SEM). Biodegradation rates between 6.81 and 18.14% were obtained, with JP5+JP8 being the treatment with the highest percentage, but with no significant differences between treatments. However, SEM showed microbial damage and growth on the surface of microplastics. Therefore, the bacterial strains used would have potential for biodegradation of high-density polyethylene, but it is advisable to continue investigations to determine the conditions and appropriate times to improve biodegradation with these strains.
Artificial Intelligence Transformations in Digital Advertising: Historical Progression, Emerging Trends, and Strategic Outlook
Authors: Martin Ava
Published: December 2024

The introduction of Artificial Intelligence (AI) has fundamentally transformed digital advertising, advancing precision, efficiency, and scalability far beyond the capabilities of traditional advertising methods. This paper presents a detailed analysis of AI’s integration into the advertising sector, focusing on critical technologies, including multi-touch attribution (MTA), reinforcement learning (RL), recommendation systems (RS), and large language models (LLMs). We examine the evolution of AI in digital marketing, explore current trends, and assess emerging technologies such as federated learning and transfer learning, emphasizing their role in real-time ad personalization, campaign optimization, and enhanced user engagement. Through an exploration of AI-driven strategies used by major corporations such as Google, IBM, and Coca-Cola, this paper underscores AI’s transformative impact on advertising and anticipates future trends that may further revolutionize the field. Additionally, we address key challenges of deploying AI at scale, including issues of interpretability, ethical considerations, and data privacy, offering potential solutions.
Uncertainty Quantification in CFD Aerodynamics: Methods, Applications, and Future Directions
Authors: García-Gutiérrez Adrián , Domínguez Diego , Delgado Adrián , Rubio Carlos
Published: December 2024

This paper provides a comprehensive review of uncertainty quantification (UQ) methods and their applications in CFD aerodynamics. The review begins by discussing the various sources of uncertainty in CFD simulations, highlighting their impact on aerodynamic predictions. It then explores a range of UQ methods, including non-probabilistic, probabilistic, and Bayesian approaches, detailing their strengths and limitations in the context of aerodynamics. The paper further examines the application of these methods to real-world CFD problems, showcasing their effectiveness in addressing uncertainties inherent in aerodynamic simulations. Additionally, challenges and limitations of applying UQ techniques in CFD aerodynamics are critically evaluated. The review concludes by outlining potential future research directions aimed at advancing UQ methodologies and their integration into CFD-based aerodynamic design and analysis. Key takeaways from the study are presented to provide a foundation for further developments in this important area of research.
Improving Inland Water Quality Predictions Using Machine Learning and Global Dissolved Oxygen Datasets
Authors: Prasad Ayush , Verma Snehal , Khan Mohammad Aatish
Published: December 2024

Dissolved Oxygen (DO) is a crucial parameter for monitoring inland water systems’ health, yet predicting its variability accurately is challenging due to spatial variability across different water bodies. Traditional process-based models lack sufficient accuracy, and while recent data-driven methods and deep learning have shown promise, they are typically site-specific and require retraining for each new location. This limitation is particularly problematic in areas lacking ground observations. In this work, we address these challenges by using deep learning models trained on global water quality datasets. These models were pre-trained on global historical water quality observations and subsequently fine-tuned for specific regions. This approach demonstrated improved results compared to using models trained exclusively on regional data and offered a more robust solution for predicting Dissolved Oxygen levels in diverse inland water systems.
Stroke-SCORE: Personalizing Acute Ischemic Stroke Treatment to Improve Patient Outcomes
Authors: Seetge Jessica , Cséke Balázs , Karádi Zsófia Nozomi , Bosnyák Edit , Szapáry László
Published: December 2024

Background/Objectives: Acute ischemic stroke (AIS) is a leading cause of disability and mortality worldwide. Despite advances in interventions such as thrombolysis (TL) and mechanical thrombectomy (MT), current treatment protocols remain largely standardized, focusing on general eligibility rather than individual patient characteristics. To address this gap, we introduce the Stroke-SCORE (Simplified Clinical Outcome Risk Evaluation), a predictive tool designed to personalize AIS management by providing data-driven, individualized recommendations to optimize treatment strategies and improve patient outcomes. Methods: The Stroke-SCORE was derived using retrospective data from 793 AIS patients admitted to the University of Pécs (February 2023 - September 2024). Logistic regression analysis identified age, National Institutes of Health Stroke Scale (NIHSS) score at admission, and pre-morbid modified Rankin Scale (pre-mRS) score as key predictors of unfavorable outcomes at 90 days (defined as modified Rankin Scale [mRS] score >2). Based on these predictors, a simplified risk score was developed to stratify patients into low, moderate, and high-risk groups, guiding treatment decisions on TL, MT, combination therapy (TL + MT), or standard care (SC). Internal validation was performed to assess the model’s predictive performance via receiver operating characteristic (ROC) analysis and isotonic regression calibration with bootstrapping. Results: The Stroke-SCORE was moderately positively correlated with a 90-day mRS score >2 (correlation coefficient: 0.51, p < 0.001), with an area under the curve (AUC) of 0.86, a sensitivity and specificity of 79% and 81%, respectively, and an overall accuracy of 80%. Simulations indicated that personalized treatment guided by the Stroke-SCORE significantly reduced unfavorable outcomes. Conclusions: The Stroke-SCORE demonstrates strong predictive performance as a practical, data-driven approach for personalizing AIS treatment decisions. In the future, external, multicenter prospective validation is needed to confirm its applicability in real-world settings.
Affordable mRNA Novel Proteins, Recombinant Protein Conversions and “Biosimilars”—Advice to Developers and Regulatory Agencies
Authors: Niazi Sarfaraz K.
Published: December 2024

The mRNA technology can replace the expensive recombinant technology for every type of protein, making biological drugs more affordable. It can also expedite the entry of new biological drugs, and the copies of approved mRNA products can be treated as generic or biosimilar products due to their chemical nature. Hundreds of new protein drugs have been blocked due to the high cost of recombinant development. The low CAPEX and OPEX associated with mRNA technology bring it within the reach of developing countries currently deprived of lifesaving biological drugs. In this paper, we advise developers to introduce novel proteins, switch recombinant manufacturing to mRNA delivery, and further advise the regulatory authorities to allow approval of copies of mRNA products with less testing. We anticipate that mRNA technology will make protein drugs like natural and engineered proteins, monoclonal antibodies, and vaccines accessible to billions of patients worldwide.
Prototype Instrumentation for the Spatial and Temporal Characterization of Voltage Supply Based on Two-Dimensional Higher-Order Statistics
Authors: González-de-la-Rosa Juan-José , Florencias-Oliveros Olivia , Sierra-Fernández José-María , Espinosa-Gavira Manuel-Jesús , Agüera-Pérez Agustín , Palomares-Salas José-Carlos , Pallarés-López Víctor , Real-Calvo Rafael J. , Santiago Isabel
Published: December 2024

Presents a proof-of-concept version of a versatile PQ analyser for tracking the voltage supply in industrial and residential sectors. Implements 2D higher-order statistics to assess power fluctuations based on the sinusoidal waveform. Thus, beyond the second-order parameters and permissible deviations regulated by the norm EN 50160, the two-dimensional traces and probability density functions, along with a previously studied differential index manage to identify different states of the electrical grid. Waveforms have been measured in the point of common coupling of a public building. Being suitable for analysing both power quality and reliability, results convey that incorporating skewness and kurtosis to reports enhance the characterization, as well as extract the customers' supply behavior under normal and anomalous operations, considering both time and location patterns. The principle fosters a robust performance in real-life campaigns, which demonstrate the good behaviour in site characterization. The method is considered as a probabilistic approach for the risk assessment.
Influence of Different Electrode Materials on Bipolar Switching Characteristics for Neodymium Oxide Films Resistance Random Access Memory Devices
Authors: Chen Kai-Huang , Kao Ming Cheng , Chen Hsin-Chin , Wang Yao-Chin
Published: December 2024

The present study observed and discussed the bipolar resistance switching behavior and electrical conduction transport properties of the neodymium oxide films resistive random access memory (RRAM) devices for the different thickness top electrode materials. Especially in ITO (Indium tin oxide) electrode materials, the conduction mechanism of neodymium oxide films RRAM devices for ITO electrode exhibits ohmic conduction behavior with 1 mA and 10 mA compliance currents in the set state for low operating voltages and low/high resistance values. In addition, at elevated operating voltages, the conduction mechanism displays hopping conduction behavior with 1 mA and 10 mA compliance currents. The observed increase in reset voltage indicates that oxygen ions have diffused into the vicinity of the ITO electrode during the set operation. Three hypothetical physical models are proposed, based on the relationship between different ITO electrode thicknesses and the oxygen concentration distribution effect. In conclusion, the neodymium oxide films RRAM devices exhibited high memory window properties, exemplary bipolar resistance switching characteristics, and non-volatile properties, rendering them suitable for incorporation into next-generation non-volatile memory applications.
Formation of Potentially Toxic Metabolites of Polycyclic Aromatic Compounds (PAHs) in Reactions Catalyzed by Human Metabolizing Enzymes
Authors: Rendic Slobodan Petar
Published: December 2024

Data are presented on the formation of potentially toxic metabolites of polycyclic aromatic hydrocarbons (PAHs) and the effects of the structure of the compounds on the human metabolic enzymes that catalyze the reactions and the products formed. The tabular data lists the formation of potentially toxic/reactive products. The data obtained from in vitro experiments showed that the oxidative reactions predominate (67% of the potentially toxic reactions). Sulfating reactions participate in 14%, reductions with 12%, and acetylation reactions with 7%. Of the enzymes, cytochrome P450 (P450, CYP) enzymes catalyzed 58% of the reactions, aldo-keto reductases (AKR) 16%, sulfotransferases (SULT) 15%, N-acetyltransferases (NAT) 6%, cytochrome P450 reductase (NPR) 3%, and a group of minor participating enzymes to the extent of 3%. Within the P450 Superfamily, P450 Family 1 (P450 1A1, 1A2, 1B1) participates to the extent of 75%, P450 3A4 with 8%, P450 2W1 with 4%, and the group of minor participating enzymes with 13%. In the C- and N-atom(s)-containing PAHs (N-PAHs), the P450 enzymes dominated with 66%, followed by NAT (14%), SULT (11%), and the group of minor participating enzymes (9%). The P450 Family 1 dominated with 67%. In the C- atom-containing group of PAHs (C-PAHs), the P450 enzymes participated with 51%. AKR with 28%, SULT with 19%, and COX and EH enzymes with 2%. Of the P450 Family 1 enzymes, P450 1A1 dominated with 41% of the reactions. The data show the dominant participation of the P450 enzymes and the effect of the N-atom presence on the toxication reactions of PAHs and the metabolites formed. Selected examples of the PAHs that are activated or proposed to form toxic species are discussed.
Exploring Vibrotactile Displays to Support Hazard Awareness in Simulated Excavation Tasks
Authors: Hossain S M Ashif , Yin Allen , Ferris Thomas K
Published: December 2024

Safe and effective execution of excavation operations and other high-risk construction tasks requires operators to perform multiple concurrent tasks, including maintaining continuous awareness of coworkers and other hazards in their surroundings. Given the heavy demand on workers’ visual and auditory resources in these contexts, vibrotactile feedback systems offer a potential solution for enhancing awareness without overburdening vision or audition. Aim: This study evaluated the impact of vibrotactile feedback regarding proximity to hazards on multitasking performance and cognitive workload in a simulated excavation task environment. Method: Twenty-four participants performed a joystick-controlled navigation task and a concurrent mental spatial rotation task. Proximity to hazards in the navigation task was conveyed via different encodings of vibrotactile feedback: No Vibration, Intensity Modulation, Pulse Duration, and Pulse Spacing. Performance metrics, including obstacle collisions, target hits, contact time, and accuracy were assessed alongside perceived workload. Results: Intensity-modulated feedback significantly reduced obstacle collisions and contact time compared to No Vibration, and additionally supported the lowest levels of experienced workload. No significant effects were observed for feedback conditions on spatial rotation accuracy, suggesting that vibrotactile feedback can effectively guide navigation and excavation control tasks while supporting general spatial awareness. Conclusions: This study demonstrates the potential for vibrotactile feedback to enhance navigation performance and hazard awareness, providing actionable insights for the development of multimodal safety systems in construction and other high-demand operational environments.
Response Characteristic of Surroundings induced by a Covered Semi-top-down Excavation with Synchronous Construction of Superstructure and Substructure
Authors: Li Liyun , Li Zixuan , Lei Ling , Li Zhuyan , Jiang Haonan , Gao Yunhao
Published: December 2024

Rely on a foundation pit project under covered semi-top-down method with synchronous construction of superstructure and substructure in Beijing, the whole process of construction was simulated by using ABAQUS finite element software. The impact of the whole construction on the surrounding ground, the adjacent building and the retaining structure were studied, and the influence of the existing building, the strength of diaphragm wall and the construction process were carried out. As shown from the results, the foundation pit and the existing building are in a safe state during the whole construction process. The ground settlement shows an obvious groove shape. The deformation of diaphragm wall has obvious spatial effects, which changes from "single peak" to "double peaks". The maximum horizontal displacement of strata behind the diaphragm wall occurs at 22.5m depth, which is 1.4-2.0 times of the top horizontal displacement. The existing buildings reduced the ground settlement between the existing building and the excavation surface. The construction process has little impact on the existing buildings, which can be adjusted appropriately.
Entrepreneurial Fuel for Success: The Influence of Opportunity and Skills on Student Entrepreneurial Motivation
Authors: Aditya Shandy , Berutu Meta Bara , Ramadhan Zidane
Published: December 2024

This research aims to analyze the influence of skills and opportunities on entrepreneurial motivation among Indonesian students. Using quantitative methods, this research collected data from 314 students who were randomly selected through a digital questionnaire. Regression analysis shows that both skills and opportunities have a significant positive influence on entrepreneurial motivation, with skills having a more dominant impact. These results indicate that developing entrepreneurial skills through education or related programs can increase students' entrepreneurial motivation. It is hoped that these findings can contribute to the entrepreneurship literature in the Indonesian context and help develop more effective entrepreneurship programs in higher education.
A DECISION SUPPORT SYSTEM FOR PERFORMANCE ASSESSMENT OF VILLAGE EQUIPMENT USING HYBRID MULTI CRITERIA DECISION MAKING (MCDM) METHOD BETWEEN AHP AND TOPSIS IN BRINGIN VILLAGE,JUWANA PATI
Authors: Maulana Muhdi Maulana
Published: December 2024

ABSTRACTThe Village Apparatus is a staff element that assists the Village Head in policy formulation and coordination, which is organized in the village secretariat and supporting the Village Head's duties in implementing policies, which are organized in the form of technical implementers and territorial elements. However, in reality, the performance of village officials in Bringin Village, Juwana Pati is still lacking and needs to be addressed in order to be optimal. Interviews conducted with the village head of Bringin, Juwana Pati said that the performance of village officials is still not considered optimal and good in a stable manner, so an evaluation is needed in the performance of village officials in Bringin Village, Juwana Pati. Therefore, a system is needed to evaluate, assess, and improve the performance of village officials in Bringin Village, Juwana Pati. The purpose of this study is to determine the results of the implementation of the Hybrid AHP and TOPSIS methods on a decision support system in helping the village head to conduct performance appraisals on village officials in Bringin Village, Juwana Pati. The system development method used is waterfall. The results of the implementation of the two methods concluded that the system built has been able to produce recommendations for determining the performance appraisal of village officials and meet functional needs. This shows that the AHP and TOPSIS methods can be used to solve problems related to determining the performance assessment of village officials by producing the best alternative based on the highest/largest preference value.
DESIGN OF "VERB-ING FOR FUN" LEARNING MEDIA FOR CLASS 4 PRIMARY SCHOOL STUDENTS
Authors: - Raka Arya Pratama
Published: December 2024

Abstract. MI Al-Ihsan Sidoarjo is a madrasa school located in Sidoarjo, East Java. However, the teachers there still rely on textbooks and question sheets for their teaching methods, and do not have projectors to use PowerPoint as another teaching method, which often causes students to not understand the essence of the lessons being delivered, due to the detailed delivery of the material. With these considerations in mind, the researcher solved the problem at MI Al-Ihsan by creating an interactive learning media application called "Verb-ng for Fun" specifically for English lessons which can be accessed using a computer in the lab, so that it can be used by MI English teachers. Al-Ihsan as a supporter for delivering lesson material. In designing it, the researcher studied the English teacher at MI Al-Ihsan and used the material in the textbook as application design material. The researcher aims to use the ADDIE method as a reference for designing interactive learning media applications that will be created. It is hoped that the design of this application can be used to improve students' understanding of English lessons.
A Analysis and Design of WLAN-Based Internet Networks Using the TOP-DOWN Method in RT/RW NET
Authors: AlFaris Muhammad Maulana
Published: December 2024

Penulis mengelola analisis performa jaringan dan rancangan jaringan internet berbasis WLAN pada RT/RW Net di Dusun Gunungsari, Desa Gunungsari, Kecamatan Dawarblandong, Kota Mojokerto. Konektivitas internet yang berkualitas dan handal menjadi kebutuhan penting bagi masyarakat. Namun, sering kali performa jaringan tidak optimal dan mengakibatkan muncul masalah latensi yang tinggi dan throughput yang rendah. Oleh karena itu, analisis menyeluruh dan perancangan jaringan sangat diperlukan untuk meningkatkan layanan dan kebutuhan pengguna. Metode Top-Down digunakan sebagai landasan, dari perencanaan hingga implementasi. Langkah awal pada tahap analisis performa jaringan adalah dengan mengumpulkan informasi terkait parameter yang nantinya digunakan untuk mengevaluasi dan identifikasi terkait masalah yang dapat terjadi. Setelah analisis performa jaringan, perancangan jaringan dilakukan dengan Cisco Packet Tracer sebagai aplikasi yang digunakan untuk melakukan perancangan terkait solusi masalah jaringan nantinya. Kemudian dilakukan evaluasi lagi dalam perancangan jaringan, dengan mempertimbangkan kebutuhan pengguna dan infrastruktur yang ada. Termasuk pada pemilihan perangkat keras, konfigurasi, frekuensi yang optimal, serta cakupan sinyal yang luas.
Arizona Bird Committee Report, 2021–2023 Records
Authors: Rosenberg Gary H. , Core Andrew
Published: December 2024

From 2021 through 2023 the Arizona Bird Committee reviewed 403 reports (several individual records comprise multiple reports) and updated the Arizona bird list through 2023, adding five species—the White-tipped Dove (Leptotila verreauxi), American Woodcock (Scolopax minor), Ringed Kingfisher (Megaceryle torquata—inadvertently left out of the last report), Orange-billed Nightingale-Thrush (Catharus aurantiirostris), and Blue-black Grassquit (Volatinia jacarina)—bringing the Arizona state list to 570 species in good standing.
Developing Prospective Teachers' skills in Supporting Student Reasoning on Quadratic Functions
Authors: Abdelmalak Mariam
Published: December 2024

This study aims to explore how a Teacher Moves for Supporting Student Reasoning (TMSSR)-based intervention influences the development of prospective middle school teachers' use of high potential versus low-potential teacher moves when supporting student reasoning on quadratic functions. Participants (N = 17) engaged with quadratic functions, practiced the TMSSR framework through scriptwriting tasks, received feedback and revised their scripts, compared and contrasted scenarios, and discussed ways to achieve high-potential moves. Data sources included an initial diagnostic task, a post-intervention task, and take-home assignments, all involving scriptwriting. Results showed that prospective teachers successfully transitioned from using low-potential moves to high-potential moves in the areas of eliciting, responding to, facilitating, and extending student mathematical reasoning. Specific areas of improvement included eliciting understanding, promoting error correction, providing guidance, encouraging reflection, and pressing for generalisation. This study offers practical insights for teacher education programs by demonstrating how teacher educators can guide prospective teachers in using high-leverage moves—such as eliciting, responding to, facilitating, and extending student reasoning—thereby contributing to the development of more effective instructional practices in mathematics classrooms.
Sustainable Management of Fusarium Wilt in Cotton through Biological Applications
Authors: Javed Iqra , Khan Muhammad Arslan , Riaz Hasan , Saeed Shafqat , Ali Haider , Bashair Muhammad , Haider Imran
Published: December 2024

Cotton (Gossypium spp.) is an annual shrub that provides valuable vegetable oil and natural fibers. Fusarium wilt, caused by Fusarium oxysporum, is one of the most devastating diseases that threaten sustainable cotton production. The present study was planned to check the response of Trichoderma harzianum formulation against Fusarium cotton wilt. Trichoderma harzianum formulation was prepared in combination with plant defense activators. The pot trials were conducted under a completely randomized design and replicated thrice. Seeds were treated with bio-control agent Trichoderma, chemical fungicide Dynasty® (Azoxystrobin), and Insecticide Cruiser® (Thiamethoxam). The growth and development of cotton plants were studied under different treatments, including control, fungicide, insecticide, and the application of the beneficial fungus Trichoderma harzianum. Results indicated that T. harzianum exhibited notable impacts over other treatments, showing significant growth improvement during the 7th and 8th weeks after sowing. The biocontrol agent effectively inhibited the growth of F. oxysporum mycelium, highlighting its potential as an efficient disease management tool. Furthermore, T. harzianum treatment induced increased activities of peroxidase (POD), hydrogen peroxide (H2O2), and superoxide dismutase (SOD), from 0.6 to 1.2 folds in cotton leaves. This enhancement of antioxidant defense mechanisms protected against oxidative damage and enhanced plant tolerance to pathogen attack. These findings revealed that Trichoderma harzianum has tremendous potential as a sustainable and environmentally friendly method of managing Fusarium wilt in cotton. Implementing this biocontrol method can help the cotton industry remain sustainable and thrive, helping farmers' income and livelihoods. Further research is encouraged to elucidate the underlying mechanisms of T. harzianum's biocontrol activity and explore its implementation on a larger scale in cotton farming.
Dynamic Relevance Learning for Few-Shot Object Detection
Authors: Liu Weijie , Cai Xiaojie , Wang Chong , Li Haohe , Yu Shenghao
Published: December 2024

Expensive bounding-box annotations have limited the development of object detection task. Thus, it is necessary to focus on more challenging task of few-shot object detection. It requires the detector to recognize objects of novel classes with only a few training samples. Nowadays, many existing popular methods adopting training way similar to meta-learning have achieved promising performance, such as Meta R-CNN series. However, support data is only used as the class attention to guide the detecting of query images each time. Their relevance to each other remains unexploited. Moreover, a lot of recent works treat the support data and query images as independent branch without considering the relationship between them. To address this issue, we propose a dynamic relevance learning model, which utilizes the relationship between all support images and Region of Interest (RoI) on the query images to construct a dynamic graph convolutional network (GCN). By adjusting the prediction distribution of the base detector using the output of this GCN, the proposed model serves as a hard auxiliary classification task, which guides the detector to improve the class representation implicitly. Comprehensive experiments have been conducted on Pascal VOC and MS-COCO dataset. The proposed model achieves the best overall performance, which shows its effectiveness of learning more generalized features. Our code is available at https://github.com/liuweijie19980216/DRL-for-FSOD.
Efficacy of the Cross-Union Protocol in the Treatment of Congenital Tibial Pseudarthrosis: A Comparative Study
Authors: Jing Yanhui , Wang Dahui , Zhang zhiqiang , Mo Yueqiang , Ning Bo , Wu Chunxing
Published: December 2024

Background
Congenital Pseudarthrosis of the Tibia (CPT) is a rare pediatric condition presenting substantial challenges for orthopedic surgeons aiming to achieve bone union, with subsequent complications such as refractures being common. The aim of the present study is to evaluate the results of our intentional cross-union protocol and to compare these outcomes with those obtained from our previously used techniques.
Materials and Methods
Sixteen patients, with a mean age of 4.8 years (range: 1-13.3 years), who were treated with the intentional cross-union protocol were included in Group A. Eleven patients, with a mean age of 3.5 years (range: 1.3-7.6 years), who primarily underwent intramedullary rodding with bone graft, were included in Group B. The intentional cross-union protocol involved cross-union of the tibia and fibula, autogenous iliac bone grafting, and the insertion of bone morphogenetic protein 2 (BMP-2) aimed at achieving tibia-fibula cross-union. Retrospective evaluation of serial radiographs was conducted, and the outcomes regarding union and any subsequent complications were analyzed.
Results
A total of 27 patients with CPT were included in the study. All 16 patients (100%) in Group A successfully achieved primary union. Among the 11 patients in Group B, only 4 cases achieved primary union, with a primary healing rate of 36.4%. Seven cases with delayed healing required 2-4 revision surgeries for final healing. The time to union was significantly shorter in Group A (3.37 ± 0.64 months) compared to Group B (8.67 ± 3.0 months). The cross-sectional area of union was also significantly larger in Group A (6.71 ± 0.58 cm²) compared to Group B (1.18 ± 0.19 cm²). In Group A, there were no cases of refracture, whereas in Group B, 7 cases (77.8%) experienced refracture, indicating a statistically significant difference.
Conclusions
Our study demonstrates that the Cross-union protocol is highly effective for achieving union and preventing refracture in CPT. With such significant improvement, it has notably altered the prognosis of this challenging condition.
Level of Evidence: IV
Strategic Model for Integrating Biogas A Framework for Sustainable Energy Integration in Agro-Industries
Authors: Nahwani Ahmad , Soeprijanto Soeprijanto , Widodo Erwin
Published: December 2024

The framework of the methodology presented in this study is an effort to integrate and optimize the agro-industry sector, especially energy in biogas. In this study, the technique of the system in functional analysis is shown systematically to translate various energy requirements in the factory as criteria for performance and functional design to be integrated, optimized, and energy efficient. The case study results indicated that biogas power plants, with a capacity of 1.5 MW, can produce around 13,140 MWh per year. The annual return on investment (ROI) is around 37.13%. With this ROI value, the payback period is 31 months. The overall reduction of greenhouse gases is approximately 77,826 tons CO2 eq/year. The potential value of carbon trading is about USD 3,113,040 per year. This strategic model presents a novel approach by integrating biogas energy production with a customized wastewater treatment system adapted to biodigesters’ effluent characteristics. It offers a sustainable, economically feasible, and scalable solution, combining resource recovery, waste minimization, and potential for carbon trading into a unified system. The novelty of this research lies in maximizing the utility of biogas plants by efficiently treating and reusing wastewater, creating a closed-loop, zero-waste process. Future research on hybrid systems integrating Biogas power plants by focusing on efficiency optimization, economic feasibility, environmental impacts, and innovative approaches like AI and blockchain could make the hybrid system a more robust, scalable, and sustainable solution. Thus, the framework based on the results of this study finds tools that can maximize and integrate energy sources, especially biogas, in the agro-industrial sector.
Rapid Diagnosis of Membranous Nephropathy Based on Kidney Tissue Raman Spectroscopy and Deep Learning
Authors: zhu Guoqiang , shadekejiang halinuer , Zhang Xueqin , Chen Cheng , Su Mingjie , Wu Shuo , Aimaijiang Gulizere , Zhang Li , Wang Shun , Yang Wenjun , Lu Chen
Published: December 2024

Membranous nephropathy (MN) is one of the most common causes of glomerular disease in clinical settings. Renal biopsy is the gold standard for diagnosing MN, but it is invasive and poses risks such as renal hemorrhage, perirenal hematoma, and infection. Furthermore, conventional light and electron microscopy techniques fail to distinguish between primary and secondary MN. The recent identification of autoantibodies against phospholipase A2 receptor (PLA2R) and thrombospondin type-1 domain-containing 7A (THSD7A) antigens has provided key insights into the pathophysiology of MN. Although immunofluorescence assays for detecting serum anti-PLA2R antibodies and glomerular PLA2R antigens are used clinically to diagnose PLA2R-related MN, only 52%-86% of PLA2R-associated MN patients exhibit positive anti-PLA2R antibodies. Recent advances in Raman spectroscopy combined with deep learning methods offer promising non-invasive diagnostic approaches. Our previous studies demonstrated the high diagnostic efficacy of Raman spectroscopy for MN using human serum and urine samples, with excellent sensitivity and specificity. In this study, we present a rapid diagnostic method for MN based on Raman spectroscopy of mouse kidney tissue combined with a CNN-BiLSTM deep learning model. The model achieved 98% accuracy, with specificity and sensitivity of 98.3%, offering a novel supplementary tool for the pathological diagnosis of MN.
Uncovering causal gene-tissue pairs and variants: A multivariable TWAS method controlling for infinitesimal effects
Authors: Zhu Xiaofeng , Yang Yihe , Lorincz-Comi Noah
Published: December 2024

Transcriptome-wide association studies (TWAS) are commonly used to prioritize causal genes underlying associations found in genome-wide association studies (GWAS) and have been extended to identify causal genes through multivariable TWAS methods. However, recent studies have shown that widespread infinitesimal effects due to polygenicity can impair the performance of these methods. In this report, we introduce a multivariable TWAS method named Tissue-Gene pairs, direct causal Variants, and Infinitesimal effects selector (TGVIS) to identify tissue-specific causal genes and direct causal variants while accounting for infinitesimal effects. In simulations, TGVIS maintains an accurate prioritization of causal gene-tissue pairs and variants and demonstrates comparable or superior power to existing approaches, regardless of the presence of infinitesimal effects. In the real data analysis of GWAS summary data of 45 cardiometabolic traits and expression/splicing quantitative trait loci (eQTL/sQTL) from 31 tissues, TGVIS improves causal gene prioritization and enhances the biological interpretability over existing methods.
Epidemiological Characteristics of Infertility, 1990-2021, and 15-Year Forecasts for Global, China, and the United States: An Analysis Based on the Global Burden of Disease Study 2021
Authors: Feng Jiale , Wu Qingguo , Liang Yangbing , Liang Yiwen , Bin Qin
Published: December 2024

Background
Infertility represents a widespread public health challenge. Gaining a thorough understanding of the burden and the epidemiological patterns associated with infertility is essential for evaluating advancements in addressing this epidemic, as well as for informing policy development and program execution. This research aims to elucidate the degree of infertility across various global regions and nations, offering vital insights that can aid in policy-making efforts aimed at mitigating the infertility epidemic.
Methods
The research utilized information gathered from the Global Burden of Disease (GBD) Study conducted in 2021. This dataset encompasses statistics related to prevalence and disability-adjusted life years (DALYs), as well as age-standardized prevalence rate (ASPR) and age-standardized DALYs rate (ASDR) associated with infertility, spanning the years 1990 through 2021. Furthermore, the estimated annual percentage change (EAPC) for these figures was calculated, and provided 95% confidence intervals (CIs) for these estimates as a reference.
Results
In 2021, it was calculated that the global Age-Standardized Prevalence Rate (ASPR) for male infertility stood at 1354.76 cases per 100,000 people, with a 95% Uncertainty Interval ranging from 802.12 to 2174.77 cases per 100,000 individuals. For female infertility, the ASPR was recorded at 2764.62 per 100,000 individuals (95% UI: 1476.33-4862.57 per 100,000 individuals). Between 1990 and 2021, the EAPC in ASPR was observed to be 0.5% (95% CI: 0.36–0.64) for males and 0.7% (95% CI: 0.53–0.87) for females. In that same year, the global ASDR attributed to male infertility was 7.84 per 100,000 individuals (95% UI: 2.85–18.56 per 100,000 individuals), while for female infertility, it amounted to 15.12 per 100,000 individuals (95% UI: 5.35–36.88 per 100,000 individuals). The EAPC for ASDR linked to male and female infertility from 1990 to 2021 was assessed at 0.51% (95% CI: 0.38–0.65) and 0.71% (95% CI: 0.54–0.88), respectively. Among the 204 countries and territories in 2021, India ranked first in both the prevalence of cases and DALYs associated with male and female infertility, followed by China and Indonesia.
Conclusions
Between 1990 and 2021, the worldwide occurrence of infertility has increased, particularly in countries with low to middle incomes. Developing alternative strategies for coping with infertility and creating comprehensive management plans specific to regions experiencing a significant burden is essential.