bluuebunny/crossref_metadata_2025_split huggingface dataset:
Sustainable utilization of solid waste byproducts in agricultural amendments as soil conditioner: A state-of-the-art review
Authors: Johnson Jeyaraj Nittin , Sankararajan Vanitha 
Published: January 2025

AbstractRecent advances have enabled solid waste byproducts to effective soil amendment in order to minimize the use of inorganic fertilizers and increase crop yields to provide food for a high-population world. This review aims to summarize the essential nutrients required for crop production, the ability of nutrient supply of solid waste byproducts as soil conditioners, and its impacts on plant growth and soil properties. This paper analyzes the sources of plant nutrients, functions, symptoms of deficiency, and corrective measures. This review analyzed the byproducts of municipal solid waste compost, waste biomass, biochar, farmyard manure, press-mud molasses, vinasses, olive mill waste, spent mushroom compost and fly ash (FA), cow dung vermicomposting with FA, FA mixed with biochar, sewage sludge-FA mixture, fiber sludge, sewage sludge, bauxite residue, poultry waste to determine their ability to supply nutrients, affecting plant growth and soil properties significantly. This review also discusses the challenges associated with solid waste byproducts used in agricultural soil amendment on the environment and human health and possible future strategies to be adopted. Overall, this review provides insights to farmers about the use of solid waste byproducts as soil conditioners for the enrichment of essential nutrients and soil properties in farming soil.
On the 30th anniversary of higher nursing education at Kazan State Medical University — on bachelor's degree program in nursing
Authors: Morozova O. N. , Radchenko O. R. , Tafeeva E. A. , Shulaev A. V. , Gubaeva L. T. 
Published: January 2025

The article presents an overview of publications on higher nursing education in Russia and an analysis of the experience of Kazan State Medical University. In addition, we assessed demand for the faculty and satisfaction with the training and learning process according to student survey data.The analysis of publications showed that higher nursing education was dictated by the healthcare system reform, the integration of Russia into the European educational and scientific space. There is a high competition at Kazan State Medical University over the past 10 years (7,51±3,3 people per place). The increase in the number of full-time students rationaled the opening of a part-time department. Survey results showed that part-time students with experience in health facilities approach study more consciously than students after school.A summary of experience on training medical personnel in the higher nursing education program and an analysis of students' opinions on the educational process at Kazan State Medical University made it possible to propose the main ways to improve the education.
A Sociophilological Account of the Formation and Evolution of the term Língua Geral, with Emphasis on Amazonia
Authors: Finbow Thomas 
Published: January 2025

This chapter critically reevaluates the role of structural change in the development of the concept of Língua Geral, as proposed in Rodrigues (1986,1996, 2010; see also EDELWEISS, 1947, 1969; DIETRICH, 2014). In Rodrigues’s model, two languages, Língua Geral Paulista and Língua Geral Amazônica, emerged from the Tupi and Tupinambá languages spoken by bi- or multilingual ‘Mamluks’ (Luso-Amerindian mestizos) over the 16th and 17th centuries.
However, a socio-philological analysis (WRIGHT, 1982, 1991, 1994, 2002) applied to a broad sample of Luso-Brazilian colonial sources, reveals that contemporaries neither attributed a characteristic variety of Língua Geral to the mamluks nor classified Língua Geral diatopically . Moreover, in 18th c. Amazonia, the linguistically non-Tupi-Guarani Tapuia peoples, rather than the Mamluks, were explicitly identified as agents of linguistic change (Daniel, 2004 [1757-1776]); however, no new name emerged. Thus, although language contact and shift undeniably occurred and undoubtedly contributed to structural change, Rodrigues’ hypothesis regarding the Mamluks’ central role in the formation of the Língua Geral cannot be sustained.
We therefore develop a revised trajectory for Língua Geral in which we propose that perceived changes in function rather than observed structural divergence were responsible the shift from using ‘Língua Brasílica’ in 17th c. Jesuit publications to ‘Língua Geral ‘in the 18th c. Our research highlights the need for a re-assessment of the term Língua Geral, and, in particular, the anachronistic Ausbau of periodizations and varieties on the basis of later perceived structural Abstand (KLOSS, 1967, 1976, 1978) that do not correspond to contemporary usage.
What 25+ Years of “Did You Feel It” Intensities Tell Us About Shaking in California
Authors: Chaffeur Jenna M. , Saunders Jessie K. , Minson Sarah E. , Baltay Annemarie S. , Cochran Elizabeth S. , Hough Susan E. , Quitoriano Vincent , Page Morgan , Blair J. Luke 
Published: January 2025

Abstract
“When will the Big One happen?” is a question that people often have for earthquake scientists. But while waiting for the “Big One” to occur, people will usually experience frightening or damaging shaking from multiple relatively smaller-magnitude earthquakes. Given this context, it raises the question: “Where does most of the damage come from?” Could smaller, yet more frequent, earthquakes account for the majority of reported impactful shaking? To explore this question, we consider reports of earthquake damage and felt shaking experiences from a catalog of community-collected intensity values from the U.S. Geological Survey’s “Did You Feel It?” system. Comparing these intensities to expectations from a ground-motion model, we find that earthquakes of magnitudes smaller than expected are responsible for most reported intensities of community decimal intensities (CDI) 4.5 and above (moderate and higher shaking intensity levels). (Here “expected value” is meant in its mathematical sense of the mean or equivalently median shaking intensity.) We also present a regional analysis of observed earthquake shaking for specific areas, detailing the maximum intensity experienced within a predetermined area. We identify several instances of M &lt; 4.5 events that generated maximum intensities of CDI &gt; 5 in regions in California surrounding the cities of Eureka, San Francisco, Los Angeles, and San Diego. Our results motivate the need to include smaller-magnitude earthquakes in communications about earthquake hazard and risk reduction.
Desenvolvimento de competências empreendedoras em um curso de direito: experiência com “Hackathon”
Authors: De Abreu Barbosa Ricardo , Venelli-Costa Luciano 
Published: January 2025

O presente artigo tem por objetivo apresentar a experiência realizada na Universidade Presbiteriana Mackenzie de aplicação de um modelo de aprendizagem conhecido como “Hackathon” para as turmas do curso de direito. Em 2012, foi instituído na universidade que todos os cursos da graduação deveriam desenvolver competências empreendedoras. Porém, os alunos do curso de direito tinham baixo engajamento e desprezo pelo ensino de empreendedorismo. O método aplicado é de abordagem qualitativa, baseado no estudo de caso da faculdade de direito, em formato de relato de experiência, com resultados antes e depois da aplicação de um “Hackathon” na semana jurídica de 2023. Os resultados revelam aumento significativo no engajamento dos estudantes, com inscrição voluntária de 132 grupos, ou cerca de 500 alunos, além de 1000 visualizações em conta na rede Instagram criada para o desafio, participação em torno de 1500 alunos nas cerimônias de premiação, e alunos escolhendo os professores de empreendedorismo para novos projetos de pesquisa, extensão e orientação de trabalhos de conclusão de curso (TCC). Este artigo expande as técnicas de ensino para professores de empreendedorismo em cursos que não são da área de negócios.
Improved Risk Adjustment for Comorbid Diagnoses in Administrative Claims Analyses of Orthopaedic Surgery
Authors: Koltsov Jayme C.B. , Zhuang Thompson , Hu Serena S. , Kamal Robin N. 
Published: January 2025

Background:
The accurate inclusion of patient comorbidities ensures appropriate risk adjustment in clinical or health services research and payment models. Orthopaedic studies often use only the comorbidities included at the index inpatient admission when quantifying patient risk. The goal of this study was to assess improvements in capture rates and in model fit and discriminatory power when using additional data and best practices for comorbidity capture.

Methods:
Hip fracture care was used as an exemplary case of an inpatient condition in a population typically having multiple comorbidities. Cohorts were built from 3 administrative resources: (1) Medicare, (2) all-payer, and (3) private-payer. Elixhauser comorbidities were calculated first using only the index admission and subsequently by adding inpatient and outpatient data from the previous year. Comorbidities identified on outpatient records required 2 instances occurring ≥30 days apart. Model fit and discriminatory power for in-hospital metrics (death, length of stay, and costs or charges) and post-discharge metrics (90-day readmission and surgical site infection, and 90-day and 1-year death) were compared among capture strategies.

Results:
The index admission missed 9.3% to 65.6% of individual Elixhauser comorbidities for the Medicare cohort, 2.9% to 39.0% for the all-payer cohort, and 14.1% to 57.9% for the private-payer cohort compared with data from the index admission plus the previous year. Using prior inpatient and outpatient data provided substantial improvements in model fit and explanatory power for post-discharge outcomes, whereas information from the index admission was sufficient for in-hospital death and length of stay. The utility of outpatient data was greatest when complete outpatient claims were captured compared with only ambulatory surgery claims.

Conclusions:
The comorbidity capture strategies demonstrated in this study, namely including all available data for post-discharge outcomes, using a 1-year lookback period, and requiring outpatient codes to appear on 2 claims ≥30 days apart, are relevant for improved risk adjustment in orthopaedic clinical or health services research and quality improvement and payment models.

Level of Evidence:
Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.
Evaluation of Specimen Rejection Rates in the Preanalytical Phase and Nurses' Experiences: A Mixed Design Study
Authors: GÜNER Yasemin , GÜNER Elif KILIÇ , ÜÇÜNCÜOĞLU Melek , YÜKSEL Harun 
Published: January 2025

Abstract

Background
Aim of the study was to examine the rejection rates of specimens in the preanalytical phase and to determine the experiences of nurses.
Methods
A mixed design was used in the study, combining retrospective data analysis and individual in-depth interviews. First, data on specimens rejection reported by microbiology and biochemistry laboratories were collected for one year. Then, individual in-depth interviews were conducted with nurses working in the clinics with the highest specimens rejection rates.
Results
As a result of the study, three main themes were determined: the functioning of the preanalytical phase, the causes of medical errors in the preanalytical phase, and the impact of the preanalytical phase on the well-being of nurses.
Conclusion
These results, institutional factors, patient profiles, stakeholders involved in the phase, and the clinical environment all affect the preanalytical phase, potentially leading to medical errors; this phase also affects the attitudes and behaviors of patients and their relatives, and the well-being of nurses, causing emotional fatigue. Despite these difficulties, nurses strive to protect their well-being and provide emotional support to patients and their families. Based on the findings of our study, there is a need for strategies focused on ensuring the well-being of nurses, and reducing emotional fatigue.
Clinical trial number:
Not applicaple.
Information Literacy and Entrepreneurial Innovation in Medical Students: An Empirical Study
Authors: Lixin Gong , Xinming Lv , Zhen Tian , Ya You , Youyou Zhang , Jianzhou Wu , Xiaoyin Niu 
Published: January 2025

Abstract

Background Training in innovation and entrepreneurship (I&E) in medical education has become increasingly prevalentamong medical schools. The information literacy equips innovators with crucial information, facilitates resource integration, and has emerged as a powerful catalyst for driving innovation. Our study explores the current participation of the medical students in innovation and entrepreneurship and provides forwards the suggestions for integrating information literacy into innovation education.
Methods A cross-sectional study was conducted among medical students at Shanghai Jiao Tong University School of Medicine, using a questionnaire to explore the relationship between information literacy and entrepreneurial innovation. The questionnaire comprises five sections, participant background, current involvement in innovation and entrepreneurship activities, satisfaction levels, and perceived needs and suggestions for support in I&E activities.
Results A total of 178 medical students participated in this survey. The results indicate that the medical students primarily face challenges related to time constraints, insufficient energy and inadequate professional knowledge during their engagement in innovation and entrepreneurship activities. Peer-to-peer communication serves as the primary source of information in the initial stage of these activities, while expert consultation is the least used by students. Additionally, the students have a low demand for library resources. Students reported a moderately high level of satisfaction with the innovation and entrepreneurship resources provided by the school, with an average score of 3.63 on a 5-point scale.
Conclusion This study highlights the vital role of information literacy in enhancing the medical students' innovation and entrepreneurship capabilities. By integrating information literacy into education, we can improve students' ability to access, analyze, and utilize information effectively, thus promoting innovation and ethical entrepreneurship. These findings provide valuable insights and a foundation for further research, while emphasizing the necessity of targeted educational strategies to support students' entrepreneurial development.
Overcoming Challenges in Implementation of Competency- Based Medical Education in India: Leveraging Postgraduates for Multiple Choice Item Design for Undergraduate Assessments in Pathology
Authors: Kini Reshma G. , Marla Nisha J , Moras Christol Blanch 
Published: January 2025

Abstract

Background
The implementation of Competency-Based Medical Education (CBME) in India has highlighted significant challenges, including faculty shortages and the need for standardized assessments. Pathology postgraduates, often involved in undergraduate teaching, represent an underutilized resource. Training them in Multiple Choice Item (MCI) development and validation can improve assessment quality while addressing gaps in CBME implementation.
Method
A structured training program was conducted for nine first-year pathology postgraduates at a single institution. The program included nine interactive sessions on CBME principles, Bloom’s taxonomy, MCI construction, identification of technical flaws, validation processes, and blueprinting. Participants’ reactions and self-perceived learning were evaluated using Kirkpatrick Levels 1 and 2 through pre- and post-program surveys and structured feedback forms. Product evaluation analyzed the MCIs for difficulty and discrimination indices, and the need for revalidation by subject matter experts (SMEs). Open-ended feedback was thematically analyzed.
Results
Participants showed significant improvements in knowledge and confidence in MCI development (p < 0.05). Product evaluation revealed that 43.2% of MCIs required revalidation, but most met acceptable thresholds for difficulty (62.5%) and discrimination (75%). Feedback highlighted the program’s structured and practical focus, while suggesting improvements in session pacing and content depth. Multiple choice items predominantly targeted lower order thinking skills, reflecting participants’ novice status and the need for longitudinal support to improve question complexity.
Conclusion
This study demonstrates the feasibility of leveraging pathology postgraduates to address CBME implementation challenges. By equipping postgraduates with assessment design skills, the program improved undergraduate assessment quality while addressing faculty shortages. Future efforts should focus on expanding such programs across institutions, incorporating longitudinal mentorship, and evaluating their long-term impact on medical education outcomes.
Left tracheal diverticulum showing a central airway obstruction pattern in pulmonary function: A case report
Authors: Kodaka Norio , Watanabe Kayo , Nakano Chihiro , Imaizumi Chisato , Niitsuma Kumiko , Shinozawa Saeko , Hirouchi Takatomo , Yoshida Yuto , Takei Hiroaki , Yamada Yuka , Yoshizawa Go , Matsuse Hiroto 
Published: January 2025

Abstract

Background:
Central airway obstruction patterns on the flow–volume curves of pulmonary function tests are commonly caused by upper respiratory tract disease and intratracheal tumors. Here, we describe a rare case in which the central airway obstruction patterns on the flow–volume curves were attributed to the slow progression of tracheal lumen narrowing caused by chronic inflammation in the surrounding area, rather than tracheal diverticulum enlargement.
Case presentation:
A 73-year-old woman diagnosed with a tracheal diverticulum was followed as an outpatient. Although her subjective symptoms did not worsen, her flow–volume curves in the pulmonary function test indicated a central airway obstruction pattern. Annual chest computed tomography imaging showed no significant changes; however, tracheal narrowing due to inflammation around the tracheal diverticulum was suspected. Surgical treatment, including laser therapy, was considered. We report a rare case of a tracheal diverticulum diagnosed >10 years ago that exhibited central airway obstruction patterns on flow–volume curves of pulmonary function tests.
Conclusion:
Pulmonary function tests and flow–volume curves are valuable in monitoring airway obstruction.
Decoding Gender: A Machine Learning Approach for Classifying Indian Names with Advanced Feature Extraction
Authors: Ghate Sudeep D. , H Saishma , D Dhanush Ghate , M Adithya , Alex Anjusha , D’Souza Neevan , Patil Prakash 
Published: January 2025

Abstract

Classifying gender based on Indian names poses a unique challenge due to the nation's immense cultural, linguistic, and regional diversity. Existing methods often struggle to address the complexities of naming conventions shaped by religious, familial, and linguistic influences, resulting in inconsistent and inaccurate classifications. To address these challenges, this study developed a culturally diverse dataset of 31.3 lakh male and female names and leveraged advanced machine learning (ML) and deep learning (DL) techniques for gender classification. These names were sourced from Indian electoral data, synthetic names generated using custom scripts, and publicly available names from websites to ensure diversity. Twelve ML models were evaluated, with the top four - Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Units (GRU), and XGBoost—prioritized for detailed analysis. CNN emerged as the best-performing model, achieving the highest accuracy (96%) and the fastest prediction time (5.61 seconds), highlighting its efficiency and ability to generalize across diverse naming conventions. LSTM and GRU also demonstrated strong performance, achieving accuracies of 95% and 93% respectively, with LSTM offering higher precision but significantly longer prediction times (50 seconds). XGBoost, a traditional ML model, achieved an accuracy of 86% but struggled with female name classification, indicating potential biases in feature representation. All models effectively captured complex naming patterns, though challenges such as the misclassification of unisex names and the underrepresentation of North-East Indian names in the dataset highlighted areas for improvement. This study underscores the advantages of deep learning models, particularly CNN, in leveraging hierarchical and sequential patterns in names for robust gender classification. However, limitations in dataset diversity and model generalizability indicate the need for further refinement. These findings contribute to advancing automated gender classification systems, offering practical applications in healthcare, marketing, and social sciences. Future work should focus on enhancing computational efficiency, expanding datasets to improve cultural inclusivity, and addressing biases to ensure equitable ML innovations.
Optimizing financial success: The synergistic impact of artificial intelligence and R&amp;D investments in U.S. firms
Authors: Kumari Sonia , Shaikh Raja , Bhayo Mujeeb-u-Rehman , Devi Sharmila , Cao Shengjie 
Published: January 2025

Abstract

The use of artificial intelligence (AI) and intellectual machines can support businesses in performing various activities. Therefore, it is necessary to examine the performance outcomes by assessing the concentration of AI technologies. To create a quantifiable score of AI concentration, AI-related terms are identified in the annual reports of all listed firms in the U.S. For analysis purposes, a fixed effects model is employed, using firms’ panel data from 2003 to 2022. The analysis reveals that AI concentration is beneficial for a company’s financial success. Additional analysis examines the moderating role of research and development (R&D). Firms with higher R&D spending experience increased financial benefits from concentrating on AI technologies. The uniqueness of this study lies in analyzing the financial success through the AI and R&D parameters. The findings support a higher concentration on AI, combined with higher R&D spending, to attain greater financial success. The main insights suggest that management must evaluate their existing focus on AI and R&D spending to improve their financial position.
JEL Classification: F65; G30; O32; P33
Studying the effect of concentration on spectral and optical properties of chitosan polymer
Authors: Abdulrazzaq Shaymaa Jabbar 
Published: January 2025

Due to its noteworthy physico-chemical behaviors, the chitosan (CS) biopolymer presents a compelling alter-native to conventional biomaterials. By measuring the emission spectra at a spectrofluorophotometer in differ-ent concentrates (1x10-4, 1x10-5, and 1x10-6) M, the spectral characteristics of the CS polymer were obtained. The crystallinity of the CS polymer was determined by X-ray diffraction (XRD) analysis, which shows only one dominant peak indexed to the orthorhombic structure. With a drop in solution concentration, there was a shift toward the shorter wavelength and a decline in quantum yield. Using a UV-Vis spectrophotometer, the optical properties of the CS polymer, including its refractive index, absorption coefficient, energy band gap, extinction coefficient, and dielectric constant, have been studied. It was observed through the results that the optical parameters are linearly dependent with concentration. In contrast to the optical energy gap, which de-creases with increasing concentration.