bluuebunny/crossref_metadata_2025_split huggingface dataset:
To be, or not to be an intron evidence from entropy-based machine learning
Authors: Mancini Alessio , Merelli Emanuela , Piangerelli Marco , Pucciarelli Sandra , Vito Leonardo 
Published: February 2025

Abstract

Alternative splicing (AS) of introns is a key mechanism contributing to proteomic diversity. It enables the generation of multiple mRNAs variants from a single gene sequence, which are subsequently translated into the distinct protein isoforms. Intron retention (IR) is a specific type of AS in which introns remain unspliced in the mature mRNA. The process of intron splicing is regulated by cis-regulatory elements that recruit small non-coding RNAs and heterogeneous nuclear ribonucleoproteins (hnRNP), collectively forming the spliceosome. However, the precise mechanism or “code” governing the splicing pattern of any primary transcript remains not completely understood. In this study, we present the use of explainable Machine Learning (xML) models to investigate the mecahnism underlying intron retention in mature mRNA. Intronic sequences obtained were analyzed from species within the ciliate genus Tetrahymena, providing unique insights into the IR process that are biased by tissue-specific factors. Various features of the intronic sequences were examined, including the absence of repetitive nucleotide motifs-quantified as “entropy”-the GC content, and the complexity of the secondary structures as estimated by the Lempel-Ziv (LZ) measure. Our findings indicate that the key distinguishing features of retained introns (RIs) compared to constitutively spliced introns include the reduced presence of repetitive nucleotide motifs within the intronic sequences and the compactness of secondary structures near the 3’ splice sites. These features appear to weaken splicing signals, impairing the recognition of intronic sequences and resulting in IR. In conclusion, our work offers insights into the regulatory code underlying intron retention in other organisms and highlights its potential role in modulating phenotypic plasticity. This supports a framework for understanding the epigenetic mechanisms of stress response and environmental adaptation, aligning with the “Lamarckian” perspective of evolutionary biology.
Synergistic effect of ammonium polyphosphate and silicone macromolecular charring agent on improving flame retardancy and mechanical properties of ethylene-butyl acrylate copolymer composites
Authors: Huo Xuan , Wu Bingcheng , Lou Yuanmeng , Zhu Junlin , Li Cui , Ma Lili , Hao Chuncheng , Wen Xin 
Published: February 2025

Abstract

It is still a challenge to achieve a good balance on flame retardancy and mechanical properties of polymer/intumescent flame retardants (polymer/IFRs) composites. In this work, a novel IFR system containing ammonium polyphosphate (APP) and silicone-containing macromolecular charring agent (Si-MCA) was constructed to synergistically improve the flame retardancy and mechanical properties of ethylene-butyl acrylate copolymer (EBA) composites. The optimal mass ratio of APP/Si-MCA was 3/1 in EBA composites (EBA/APP-Si-31), corresponding to the best flame retardancy with 31.2% of limited oxygen index (LOI), V0 rating in UL-94 test and 76.4% reduction on the peak of heat release rate (PHRR) in cone calorimeter test. The enhancement mechanism was ascribed to the synergistic effect of APP/Si-MCA during combustion, including the trapping radical effect, diluting effect of non-flammable gases, and the barrier effect of intumescent char layer. Meanwhile, tensile test indicated that EBA/APP-Si-31 also exhibited good mechanical properties with the addition of maleic anhydride-grafted polyethylene as compatibilizer. Thus, the APP/Si-MCA combination is an effective IFRs to prepare high-performance EBA composites, and will promote their applications as cable sheath materials.
An L1 norm regularization model for signal extraction from GNSS coordinate time series
Authors: Wang Zhuofan , Chen Gang , Li Hongwei , Bian Jiawen 
Published: February 2025

Abstract

Accurate signal extraction from Global Navigation Satellite System (GNSS) coordinate time series is crucial for geophysical studies. Primary focus of this paper lies in the recovery of trend and seasonal signals from observed GNSS coordinate time series. To achieve this, this paper presents a novel Modified L1-norm Regularization Rank-1 Matrix Completion (ML1MC) method, ML1MC leverages the low-rank property of Hankel matrices and incorporates automatic rank estimation and Block Coordinate Descent (BCD) to effectively handle noise and avoid overfitting, which provides a more comprehensive rank-1 matrix representation than Singular Value Decomposition (SVD) based low-rank matrix recovery methods. Extensive experiments on simulated and real GNSS datasets demonstrate ML1MC's superior performance in comparison to several State-Of-The-Art (SOTA) methods. Specifically, compared to the SOTA methods, ML1MC achieves over 7.8\% misfit reduction and reduces trend uncertainty error by more than 45.9\% under normal noise conditions.
The Impact of Perforation Presence, Preparation Design, and Prosthetic Treatment Options on Crack Propagation: A Finite Element Analysis Study
Authors: Güntekin Neslihan , Mutlu Şerefnur , Mohammadi Reza , Demirel Mehmet Gökberkkaan , Erdoğdu Meryem 
Published: February 2025

Abstract

Background: The aim of this study is to investigate the impact of restoration type and material on stress distribution in molar teeth with furcal perforations, as well as to evaluate the prognosis of cracks originating from the perforation site.
Methods: The molar tooth with a furcal perforation was restored using post-core restorations containing 1, 2, and 3 posts, as well as two different endocrown designs with and without a ferrule. Lithium disilicate (LDS) and polymer-infiltrated ceramic network (PICN) materials were used as the restoration materials. After modeling, von Mises values generated in the components were recorded using XFEM, and the progression of cracks originating from the perforation site was also examined. Fatigue values for dentin and crown were predicted.
Results: The investigations revealed that the LDS material exhibited better fatigue performance in all groups. Increasing the number of posts showed positive results for the perforation prognosis. Additionally, the presence of a ferrule in endocrown restorations improved the restoration's success.
Conclusion: In the presence of perforation, increasing the number of posts in post-core applications, when combined with ceramic restorations, is likely to result in a more successful prognosis in terms of survival. If endocrown restorations are to be chosen, the presence of a ferrule positively influences the success.
Data-driven multi-criteria decision making for cell performance detection in 5G and B5G networks
Authors: Yami Reza Moammer , Khazaei Ali Akbar , Quchani Saeed Rahati 
Published: February 2025

Abstract

Self-organizing communication networks in 5G and B5G automatically optimize and improve without human intervention, reducing OPEX and CAPEX. One of the critical features is self-healing, which predicts and resolves anomalies, optimizes performance, and adapts to changing cell density. This is managed through cell outage management (COM), which includes cell outage detection (COD) and cell outage compensation (COC). Timely prediction of cell state enhances network performance. This research uses machine learning techniques combined with multi-criteria decision making (MCDM) methods to rank and estimate defective cells. Using the TOPSIS method, an unsupervised dataset was transformed into a two-class supervised dataset. The results show that the TOPSIS-Adaboost combination outperforms other methods and improves the capabilities of cell outage detection in 5G and B5G networks.
Induction of Lewy-like aggregates perturbs the firing dynamics of midbrain dopaminergic neurons in vivo
Authors: Magill Peter J , Schaffran Barbara T , Wolff Amy R , Threlfell Sarah , Doig Natalie M , Dinneen David , Yona Guy , Sharott Andrew , Luc Kelvin C , Cragg Stephanie J , Dodson Paul D 
Published: February 2025

Abstract

Lewy-bodies are protein aggregates that are thought to lead to neurodegeneration in Parkinson’s disease. However, little is known about the contributions of these aggregates to the symptomatology of the disease. We injected alpha-synuclein pre-formed fibrils (PFFs) into dorsolateral striatum to induce Lewy-like aggregates in substantia nigra dopamine neurons and examined the effects 1- and 3-months post-injection, stages that are prior to overt cell loss. Aggregate-bearing dopamine neurons exhibited an increase in burst-firing in vivo and their firing became synchronized with cortical activity. Aggregates had a progressive effect on dopamine neuron activity, with a decrease in firing rate observed 3-months after PFF injection. In addition to altered neuronal firing, PFFs caused a reduction in evoked dopamine release and in the rate of dopamine uptake measured in striatal slices. Furthermore, alpha-synuclein aggregates were detected in dopaminergic axons in striatum and a loss of these axons was observed prior to cell body degeneration. These findings suggest that at early stages of disease, Lewy-like aggregates cause loss of dopaminergic axons and alter both the rate and pattern of dopamine neuron firing. Thus, aggregates may not only be instrumental in neurodegeneration, but may also play a role in the symptoms of Parkinson’s disease.
Impact of Lesson Studies in development of Pedagogical Content Knowledge in Physical Education Preservice Teachers
Authors: Santinha Fernanda Marques , Onofre Marcos , Martins Maria 
Published: February 2025

Abstract

Purpose – To analyze the impact of Lesson Studies in development of pedagogical content knowledge in Physical Education preservice teachers.
Methodology – This project was developed by carrying out a Lesson Study, collecting data during the process and studying the perspectives of participating preservice teachers.
Findings – The participation in Lesson Study promoted development in Physical Education prospective teachers’ knowledge in goal setting, lesson planning, task design, knowledge of students’ difficulties, solving strategies, class discussion and observation of student learning. Our results are in line with other studies addressing the relationship between Lesson Studies and the development of pedagogical content knowledge in preservice teachers, and with the general conclusion that Lesson Study helps teachers to better support student learning. Due to the importance of developing teacher’s pedagogical content knowledge, also in Physical Education, these results suggest that Lesson Studies can be advantageously used in initial teacher training.
Originality – We couldn’t find studies about the relationship between Lesson Studies and the development of pedagogical content knowledge in initial teacher training in Physical Education, and the research reported on the use of Lesson Studies in training of Physical Education teachers is very limited.
A surrogate model for the variable infiltration capacity model using physics-informed machine learning
Authors: Gu Haiting , Liang Xiao , Liu Li , Wang Lu , Guo Yuxue , Pan Suli , Xu Yue-Ping 
Published: February 2025

ABSTRACT

In this study, a physics-informed machine learning-based surrogate model (SM) for the variable infiltration capacity (VIC) model was developed to improve simulation efficiency in the Yarlung Tsangpo River basin. The approach combines the empirical orthogonal function decomposition of low-fidelity VIC models to extract spatial and temporal features, with machine learning techniques applied to refine temporal feature series. This allows for accurate reconstruction of high-fidelity spatial simulations from the results of the low-fidelity model. Using the SM built from the 1.0°-resolution VIC model as an example, the study highlights the challenges and solutions associated with low-fidelity simulations. The SM significantly improves accuracy, achieving a Kling–Gupta efficiency of 0.88, an Nash–Sutcliffe efficiency of 0.97, and a PBIAS value of −6.21% with reduced computational demands. Additionally, different machine learning methods impact the performance of the SM, with the support vector machine regression model performing best in these methods. SMs from varying low-fidelity resolutions maintain similar accuracy, but higher resolutions notably enhance computational efficiency, reducing time by 86.31% when compared to the high-fidelity VIC model. These findings demonstrate the potential of the SM to enhance VIC model simulations while reducing computational requirements.
Traditional techniques in Rajata Shodhana: A comprehensive review of classical methods
Authors: Kirtesh Agey  , Poorvi Mahabdi  , Dilip Prajapati  
Published: February 2025

Introduction: The traditional Ayurvedic process of Rajata Shodhana (silver processing) is essential in preparing silver for therapeutic applications, transforming it from a raw metal into a safe, bio available from known as Bhasma. This review comprehensively examines classical methods of Rajata Shodhana, focusing on techniques that involve various herbal, mineral, and heating processes to detoxify and enhance the metal’s medicinal properties. By analyzing these traditional practices, the review aims to highlight their scientific underpinnings and relevance. Material and Methods: A detailed analysis of the following 14 classical Ayurvedic texts on were undertaken for this study: Anandakanda, Rasendra Chudamani, Rasarnava, Rasa Paddhati, Sharangdhara Samhita, Rasaprakash Sudhakara, Rasa Ratna Samucchaya, Rasendra Chintamani, Rasendra Sara Sangraha, Rasa Manjiri, Ayurveda Prakash, Rasa Jala Nidhi, Rasa Tarangini, and Rasamrita. Results & Discussion: The primary techniques employed in the Shodhana of Rajata include Nirvapa, Dravana, Dhalana, Dhamapana, and Swedana, with Nirvapa being the most frequently used. The quenching process ranges from a minimum of 3 to a maximum of 21 repetitions. Various Shodhana media are detailed in Rasashastra classics, with Naga (lead) being the most commonly used, appearing 14 times in the reviewed texts. The processes of Dhmapana or Dravana often incorporate Naga, along with Kharpara and Tankana, as purifying media. Conclusion: These varied media illustrate a comprehensive approach to metal processing, combining chemical reactions, traditional practices, and therapeutic properties to achieve the desired processing of Rajata. The choice of media depends on the specific requirements of the processing of the traditional knowledge embedded in the practice.
Effect of Yoga on Mental Health: An Overview
Authors: Komal Kumari  , Sweta Pathak  
Published: February 2025

Self as well as community development depends on mental health, which is a fundamental human right. Mental health problems can affect our thought pattern, mood states and different types of behaviors at every stage of life. A state of mental well-being is known as mental health which enables individuals to fulfill their potential, learn new skills and work productively, overcome obstacles of the life, and contribute back to their communities. This review assessed the effectiveness of Yoga as an intervention for improving mental health and its different aspects. The present review carried out from databases including Google scholar and PubMed using key terms Yoga, mental health, and well-being. Only randomized control trials and experimental studies were included based on their relevance. Inappropriate and qualitative studies were excluded from the present review. On the basis of inclusion and exclusion criteria, only seven studies published between 2014 and 2024 have been included for this review. Overall, the studies showed that comprehensive Yoga program is an effective tool to manage different aspects of mental health. The review suggests that Yoga and its various techniques shows considerable improvement in mental health and its various aspects. Yoga is the key to accomplishing both emotional and physical well-being.
Silajathu Rasayana in management of Ankylosing Spondylitis - A Case Report
Authors: Hariharan MK  , Giri PV  
Published: February 2025

Ankylosing Spondylitis is a chronic seronegative inflammatory condition that primarily impacts the sacroiliac joint and spine, potentially leading to the fusion of spinal bones. The exact cause of this condition remains unknown. A 50-year-ojoints andatient was admitted to the Kayachikitsa inpatient department of Vaidyaratnam Ayurveda College, Ollur, presenting with both knee pain and swelling, pain in both elbow joints, and generalized back pain. She was treated by following the Amavatha management protocol, which included internal administration of Ayurvedic formulations such as Amrithotharam Kashaya, Indukantham Kashaya, Yogaraja Guggulu, Punarnavasam, and Rasnapanchakam Kashaya. External therapies such as Churna Pinda Sweda, Snehapana, Sarvanga Taila Dhara and Virechana. Silajathu Rasayana were administered in the final stage of the treatment. After six weeks of treatment, the patient experienced significant relief from upper and lower back pain, reduced elbow pain, and noticeable improvement in knee joint swelling and discomfort. This case study emphasizes the efficacy of Ayurvedic management especially Rasayana chikitsa in achieving substantial symptom improvement within a short duration.
When Infodemic Meets Epidemic: Systematic Literature Review
Authors: Asaad Chaimae , Khaouja Imane , Ghogho Mounir , Baïna Karim 
Published: February 2025

Background
Epidemics and outbreaks present arduous challenges, requiring both individual and communal efforts. The significant medical, emotional, and financial burden associated with epidemics creates feelings of distrust, fear, and loss of control, making vulnerable populations prone to exploitation and manipulation through misinformation, rumors, and conspiracies. The use of social media sites has increased in the last decade. As a result, significant amounts of public data can be leveraged for biosurveillance. Social media sites can also provide a platform to quickly and efficiently reach a sizable percentage of the population; therefore, they have a potential role in various aspects of epidemic mitigation.

Objective
This systematic literature review aimed to provide a methodical overview of the integration of social media in 3 epidemic-related contexts: epidemic monitoring, misinformation detection, and the relationship with mental health. The aim is to understand how social media has been used efficiently in these contexts, and which gaps need further research efforts.

Methods
Three research questions, related to epidemic monitoring, misinformation, and mental health, were conceptualized for this review. In the first PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) stage, 13,522 publications were collected from several digital libraries (PubMed, IEEE Xplore, ScienceDirect, SpringerLink, MDPI, ACM, and ACL) and gray literature sources (arXiv and ProQuest), spanning from 2010 to 2022. A total of 242 (1.79%) papers were selected for inclusion and were synthesized to identify themes, methods, epidemics studied, and social media sites used.

Results
Five main themes were identified in the literature, as follows: epidemic forecasting and surveillance, public opinion understanding, fake news identification and characterization, mental health assessment, and association of social media use with psychological outcomes. Social media data were found to be an efficient tool to gauge public response, monitor discourse, identify misleading and fake news, and estimate the mental health toll of epidemics. Findings uncovered a need for more robust applications of lessons learned from epidemic “postmortem documentation.” A vast gap exists between retrospective analysis of epidemic management and result integration in prospective studies.

Conclusions
Harnessing the full potential of social media in epidemic-related tasks requires streamlining the results of epidemic forecasting, public opinion understanding, and misinformation detection, all while keeping abreast of potential mental health implications. Proactive prevention has thus become vital for epidemic curtailment and containment.
Inteligência artificial no ensino superior:
Authors: Bottentuit Junior João Batista , Mariz Ester Avelar dos Santos Rios , Costa Jéssica Silva , Albuquerque Odla Cristianne Patriota 
Published: February 2025

Este artigo discorre sobre a Inteligência Artificial (IA) no ensino superior, problematizando como essa tecnologia se apresenta no contexto acadêmico. O seu objetivo principal é refletir sobre como a IA tem sido integrada à academia, analisando as estratégias de uso, as concepções relativas à IA, e os desafios e possibilidades dessa integração. A metodologia empregada é uma revisão sistemática de literatura, com levantamento de produções científicas entre janeiro de 2021 e junho de 2024, em dois bancos de dados: AcademiaEdu e Google Acadêmico. Os tópicos apresentados incluem breve histórico da IA, sua definição, como também discussões sobre a IA no ensino superior a partir de Nascimento et al. (2023), Rodrigues (2023), Peres (2024), entre outros. Os resultados apontam a IA como um recurso valioso para personalizar o aprendizado e apoiar decisões pedagógicas no ensino superior. Entretanto, também destacam desafios éticos, legais e a necessidade de formação dos professores nessa tecnologia.
Estudos decoloniais e a educação inclusiva
Authors: Maranhão Caldas Renata , Navarrete Tolomei Cristiane 
Published: February 2025

Este texto propõe refletir metodologias inovadoras que contemplem os estudos decoloniais como uma práxis de oposição ao sistema-mundo moderno/colonial na educação inclusiva. Para isso, verificamos como uma ontologia centralizadora invisibiliza e subalterniza pessoas com deficiência, resultando em um modelo social capacitista e excludente na educação inclusiva no Brasil. Diante disso, discorremos sobre as implicações da colonialidade no domínio da educação inclusiva para, em seguida, a partir de uma perspectiva decolonial, apresentar os elementos que circundam uma pedagogia decolonial para promover uma educação inclusiva, especialmente, no que diz respeito à educação e inclusão das pessoas com deficiência.
Llegar al lugar correcto
Authors: Bárcena Fernando 
Published: February 2025

Llegamos al lugar correcto cuando nos encontramos con alguien que, como ocurre con los maestros, nos descubre quiénes somos y nos ayuda a crecer; no se limita a enseñar lo que en la sociedad ya hay, sino que nos lo pone delante para que lo estudiemos con atención y precisión. Cuando enseña, el maestro se hace signo y voz, y lo que transmite no es simplemente un cuerpo unívoco de información. Su enseñanza es el acto mismo destinado a movilizar el deseo (de saber) en otro, para hacerlo crecer, y llevarlo hacia sí mismo, desplazándolo, conmoviéndolo, abriendo mundos. El maestro transmite, sobre todo, lo que no dice. Su comunicación es indirecta, y a menudo parece que en la transmisión del saber hay una clase de engaño que adopta la forma de la ironía, un juego de ocultamiento y exhibición. Cuando el maestro transmite, convoca, como exigencia imperiosa, la necesidad de traducción de sus lecciones, que son siempre modos de dar a leer. Sin embargo, en la escuela de nuestros días parece impedirse cada vez más a los maestros ser tales –es decir, estudiantes y estudiosos-. Es interesante volver a pensar, en tal sentido, la relación con lo que se estudia, y que luego es transmitido, como el centro que instituye la figura humana del maestro, en general el oficio docente, lo que hace del adulto que eligió tal oficio un cierto ejemplo de humanidad para sus alumnos, tal vez para la ciudad.