bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Social Construction of Categorical Data: Mixed Methods Approach to Assessing Data Features in Publicly Available Datasets (Preprint)
Authors: Willem Theresa , Wollek Alessandro , Cheslerean-Boghiu Theodor , Kenney Martha , Buyx Alena 
Published: January 2025

BACKGROUND

In data-sparse areas such as health care, computer scientists aim to leverage as much available information as possible to increase the accuracy of their machine learning models’ outputs. As a standard, categorical data, such as patients’ gender, socioeconomic status, or skin color, are used to train models in fusion with other data types, such as medical images and text-based medical information. However, the effects of including categorical data features for model training in such data-scarce areas are underexamined, particularly regarding models intended to serve individuals equitably in a diverse population.

OBJECTIVE

This study aimed to explore categorical data’s effects on machine learning model outputs, rooted the effects in the data collection and dataset publication processes, and proposed a mixed methods approach to examining datasets’ data categories before using them for machine learning training.

METHODS

Against the theoretical background of the social construction of categories, we suggest a mixed methods approach to assess categorical data’s utility for machine learning model training. As an example, we applied our approach to a Brazilian dermatological dataset (Dermatological and Surgical Assistance Program at the Federal University of Espírito Santo [PAD-UFES] 20). We first present an exploratory, quantitative study that assesses the effects when including or excluding each of the unique categorical data features of the PAD-UFES 20 dataset for training a transformer-based model using a data fusion algorithm. We then pair our quantitative analysis with a qualitative examination of the data categories based on interviews with the dataset authors.

RESULTS

Our quantitative study suggests scattered effects of including categorical data for machine learning model training across predictive classes. Our qualitative analysis gives insights into how the categorical data were collected and why they were published, explaining some of the quantitative effects that we observed. Our findings highlight the social constructedness of categorical data in publicly available datasets, meaning that the data in a category heavily depend on both how these categories are defined by the dataset creators and the sociomedico context in which the data are collected. This reveals relevant limitations of using publicly available datasets in contexts different from those of the collection of their data.

CONCLUSIONS

We caution against using data features of publicly available datasets without reflection on the social construction and context dependency of their categorical data features, particularly in data-sparse areas. We conclude that social scientific, context-dependent analysis of available data features using both quantitative and qualitative methods is helpful in judging the utility of categorical data for the population for which a model is intended.
Beyond point forecasting: Probability density forecasting of corn yield based on quantile regression forest
Authors: Xiong Tao , Xia Meng , Li Gucheng , Li Jian , Xia Weiyi 
Published: January 2025

Abstract
Crop yield forecasting is crucial for global food security. In this paper, we go beyond traditional point forecasting to examine the probability density forecasting of corn yield using a quantile-based machine learning approach. Leveraging 36 years of county-level panel data that cover 1260 counties in China between 1984 and 2019, we develop a quantile regression forest model, enhancing the traditional random forest by integrating quantile regression, for probability density forecasting of corn yield. Quantile regression and quantile regression neural networks are selected as benchmarks. Thirteen meteorological variables are adopted as predictors, and LASSO is used to examine the importance of each variable. Our results show that all quantile-based models produce good point forecasts, prediction intervals, and probability density curves; in general, we find that quantile regression forest with LASSO is best. We also find that the quantile regression neural network does not perform better than the traditional quantile regression, and LASSO doesn’t improve prediction models much in this context. This paper demonstrates that quantile-based machine learning is a promising tool for probability density forecasting of corn yield — but attention must be paid to the selection of machine learning algorithms and their black box properties.
Longitudinal Associations of PFAS Exposure With Insulin Sensitivity and β-Cell Function Among Hispanic Women With Gestational Diabetes Mellitus History
Authors: Kang Ni , Chen Wu , Osazuwa Nosa , Qiu Chenyu , Botelho Julianne Cook , Calafat Antonia M. , Jones Dean , Buchanan Thomas , Xiang Anny H. , Chen Zhanghua 
Published: January 2025

OBJECTIVE
We investigated associations between per- and polyfluoroalkyl substances (PFAS) and changes in diabetes indicators from pregnancy to 12 years after delivery among women with a history of gestational diabetes mellitus (GDM).

RESEARCH DESIGN AND METHODS
Eighty Hispanic women with GDM history were followed from the third trimester of pregnancy to 12 years after delivery. Oral and intravenous glucose tolerance tests were conducted during follow-up. Plasma PFAS concentrations were measured at the third trimester of pregnancy and first postpartum visit. A linear mixed-effects model was used to analyze associations between PFAS and trajectories of diabetes indicators, adjusted for age, breastfeeding status, daily total calorie intake, and body fat percentage.

RESULTS
Increased 2-(N-methyl-perfluorooctane sulfonamido) acetate level was associated with faster increase in concentrations of fasting glucose (P = 0.003). Increased perfluorononanoate (PFNA) and linear perfluorooctanoate (n-PFOA) concentrations were associated with faster increase in fasting insulin concentrations (P = 0.04 for PFNA; P = 0.02 for n-PFOA) and faster decrease in acute insulin response to glucose (P = 0.04 for PFNA; P = 0.02 for n-PFOA).

CONCLUSIONS
PFAS exposure is associated with glucose intolerance, insulin resistance, and β-cell dysfunction, thus increasing type 2 diabetes risk.
Identification of Marine Oil Spills Using Neural Network Technologies
Authors: Sidoryakina V. V. , Solomakha D. A. 
Published: January 2025

Introduction. Detecting oil spills is a critical task in monitoring the marine ecosystem, protecting it, and minimizing the consequences of emergency situations. The development of fast and accurate methods for detecting and mapping oil spills at sea is essential for prompt assessment and response to emergencies. High-resolution aerial photography provides researchers with a tool for remote monitoring of water discoloration. Artificial intelligence technologies contribute to improving and automating the interpretation and analysis of such images. This study aims to develop approaches for identifying oil spilled on water surfaces using neural networks and machine learning techniques.Materials and Methods. Algorithms capable of automatically identifying marine oil spills were developed using computer image analysis and machine learning methods. The U-Net convolutional neural network was employed for image segmentation tasks. The neural network architecture was designed using the PyTorch library implemented in Python. The AdamW optimizer was chosen for training the network. The neural network was trained on a dataset comprising 8,700 images.Results. The performance of oil spill detection on water surfaces was evaluated using metrics such as IoU, Precision, Recall, Accuracy, and F1 score. Calculations based on these metrics demonstrated identification accuracy of approximately 83–88%, confirming the efficiency of the algorithms used.Discussion and Conclusion. The U-Net convolutional network was successfully trained and demonstrated high accuracy in detecting marine oil spills on the given dataset. Future work will focus on developing algorithms using more advanced neural network models and image augmentation methods.
Relationship between deadwood structural diversity and carbon stock along environmental and disturbance gradients in Tropical dry forests
Authors: Masanja Sarafina N. , Shirima Deo D. , Zahabu Eliakimu M. 
Published: January 2025

Abstract
Deadwood is a substantial component of forest ecosystems playing a vital role in maintaining ecosystem health and functioning. However, there is limited information on deadwood stand structure which encompasses attributes such as type, quantities and distribution of deadwood pieces and how it is related to its biomass. This study examined the relationship between deadwood species structural diversity and carbon stock along different environmental and disturbance factors in forest and woodland ecosystems. An agglomerative hierarchical clustering analysis was used to identify species communities, followed by indicator species analysis which was done to determine the species significantly associated with each community. Species richness, evenness and Shannon-Wiener diversity index were calculated to determine deadwood species diversity in both ecosystems. Multimodel inference approach was used to analyse the relationship between deadwood carbon stock and diversity indices, soil properties, climate and proximity to roads and settlements. Three communities were identified from forest ecosystems while four communities were from woodland. Multimodel analysis found a positive significant relationship between deadwood carbon stock and species abundance, Shannon-Wiener diversity, soil moisture and proximity to roads in both ecosystems. These findings provide insights into conservation strategies that prioritize protection and restoration of ecosystems as carbon reservois.
Effect of tree size attributes on fruit production and animal-mediated seed dispersal web in Melia azedarach L. (Chinaberry) in north-west Himalaya, India
Authors: Sukumaran Arun , Sasidharan Sarath , Khanduri Vinod Prasad , Suraj  , Rawat Shweta , Chand Vaisakhy Prem 
Published: January 2025

Abstract
Insights into the relationships between tree species and their potential seed dispersers in a specific region are vital for determining spatial distribution and population dynamics that rely solely on natural regeneration. Several factors influence fruit production in trees, and the fluctuations in fruit output directly affects the population and diversity of frugivores in that area. We examined the trees of Melia azedarach to analyse the impact of tree size attributes (diameter, height and crown length) on fruit yield. Furthermore, we observed the seed dispersers to determine their role in fruit removal and dispersal. The average fruit production among sample trees varied from 1.8 × 103 to 1.18 × 105. Out of the 10 bird species recorded, the Hypsipetes leucocephalus (Himalayan Black Bulbul) and Pycnonotus leucogenys (Himalayan Bulbul) were the most frequent visitors and crucial for seed dispersal of M. azedarach. Psittacula krameri (Rose-ringed Parakeets) dropped a significant quantity of fruits below the parent tree, acting as a pre-dispersal seed predator. There were significant variations among species in total visits and estimated endocarp disbursed. Our findings indicate that the tree-size attributes like diameter, height, and crown length strongly affected fruit yield capacity in trees of Melia azedarach. Large trees are likely to be reproductively matured and are prioritising resources for reproduction rather than growth. Native animals, especially birds are facilitating seed dispersal in M. azedarach. The estimated period of the availability of ripe fruits reflects the status of seed predators and seed dispersal. The results ultimately revealed that the animal plant interactions of this study would be vital for ecosystem functioning, habitat rewilding and conservation of the ecosystem through balancing plant-animal mutualism.
First record of Maconellicoccus hirsutus (Green) (Hemiptera: Pseudococcidae) on Albizia julibrissin - Honeybee foraging on mealybug honeydew
Authors: Tsagkarakis A.E. , Kaydan M.B. , Stathas G.J. , Gastouniotis G. 
Published: January 2025

Summary
In August 2024, the pink hibiscus mealybug, Maconellicoccus hirsutus (Green) (Hemiptera: Coccomorpha: Pseudococcidae), was found in heavy infestations on Albizia julibrissin Durazz. (Fabaceae) and Grevillea robusta A. Cunn. (Proteaceae) in Athens, Greece. This is the first global record of A. julibrissin and the first record on G. robusta in Greece, as hosts of M. hirsutus. All developmental stages: eggs, nymphs, and adult males and females, were present. Honeybees (Apis mellifera L.) were observed actively foraging on the abundant honeydew secreted by the mealybugs. Further research is necessary to assess the potential impact of this invasive pest on host plants in Greece, and the significance of its honeydew as an alternative food resource for honeybees.
Mediation in the Enterprise. A New Approach Needed?
Authors: Broński Włodzimierz , Dąbrowski Marek , Rokosz Marcin , Sławicki Piotr 
Published: January 2025

Abstract
Values set the desired course of action in an enterprise. They are a kind of bonding and expression of the corporate culture, which determines how conflicts are understood, resolved, and managed. A problem that negatively affects the enterprise's productivity is the lack of effective conflict prevention and resolution mechanisms. Thus, mediation as a non-confrontational method of diagnosing and resolving conflicts should be a key element of the corporate culture in the enterprise. Does this mean that a new approach to the institution of mediation is needed? To answer this question, the subject of conflicts in the enterprise is discussed first. Then, the need is indicated to have internal dispute resolution procedures operational in the enterprise, which should also include a system for preventing the occurrence of disputes and dealing with possible court proceedings. In the last part, the issue of the mediator is presented, considering the role that the mediator plays, which is to provide professional assistance in the amicable resolution of disputes arising in the workplace.
Digitalization and Transparency in Cfem Collection: the Use of Technologies to Combat Evasion and Underbilling
Authors: Rocha Alan Pierre Chaves , Nascimento Cleber Augusto do , Luiz Ronilson de Souza 
Published: January 2025

Objective: To investigate the role of digitization and transparency in the process of collecting Financial Compensation for the Exploration of Mineral Resources (CFEM), focusing on the use of technologies to combat tax evasion and underbilling in the mining industry.

Theoretical Framework: It is based on the strategies adopted by the National Mining Agency (ANM) and other control bodies, such as the Federal Revenue and Siscomex, in the implementation of digital systems that promote greater efficiency and clarity in the collection of the CFEM.

Method: Combines literature review with theoretical-empirical research case study with the use of regulatory and legislative content analysis.

Results and Discussion: The results of the work sought the need for greater control and transparency in the mining sector, one of the main sources of tax collection for mining municipalities

Research Implications: The results include the identification of good practices and effective technologies in the collection of CFEM, as well as the proposal of improvements for inspection and tax collection in the mineral sector, focusing on providing greater predictability and fiscal justice, contributing to the sustainable development of mining regions and increasing efficiency in the use of public resources.

Originality/Value: Digitization, when fully implemented and accompanied by effective regulation, can transform the Brazilian mining sector, contributing to greater tax justice and more balanced and sustainable economic growth.
Tax Planning and Decision-Making: a Study in Manufacturing Companies
Authors: Tamayo Galo Hernán García , Sanchez Oscar Lenin Chicaiza , Susana Andrade Arias Mariela , Morales María Gabriela Morales , Valdez Juan Gabriel Villagómez 
Published: January 2025

Objective: The objective of this research is to analyze the relationship between tax planning and decision-making in companies in the manufacturing sector of the city of Quito.

Theoretical Framework: In the development of theories on tax compliance, which constitute the theoretical basis for tax control strategies, the theories of deterrence, behaviorism and signaling are detailed.

Method: This study involves the application of mixed methods through an exhaustive documentary and bibliographic review. The research is classified as descriptive and correlational. In addition, a survey has been structured with a Likert scale.

Results and Discussion: From the data collected, it was concluded that there is a high degree of relationship between tax planning and business decision-making.

Research Implications: The design and implementation of proper tax planning leads to more viable decision-making for a company's economic and financial health. This finding supports the idea that organizations can optimize their bottom line by effectively incorporating tax planning strategies into their decision-making processes.

Originality/Value: The importance of the impact of the tax burden on the results of organizations is recognized, and, therefore, this research is positioned as a valuable contribution for companies to have a meaningful tool when designing strategies aimed at optimizing their economic and financial resources.
Investigation of Factors Associated With Bovine Mastitis in a Compost Barn System and Identification of Microorganisms Involved, Using Maldi-Tof Mass Spectrometry
Authors: Cardoso Bruna Naiara , Santos Eliane Macedo Sobrinho , Santos Franciane Gabrielle dos , Souza Cintya Neves de , Pires Neto Otaviano de Souza , Colen Fernando , Santos Alice Ranielly Chaves , Santos Hercules Otacílio , Santos Wagner Silva dos , Tavares Agueda Maria de França , Marques Mel Suzane Santos , Almeida Anna Christina de 
Published: January 2025

Objective: To investigate factors associated with bovine mastitis in a Compost Barn system and to use MALDI-TOF mass spectrometry to determine the microorganisms involved in the infection.

Theoretical Reference: Mastitis negatively impacts dairy farming. To target control measures efficiently, it is important to assess predisposing factors and identify microorganisms. The MALDI-TOF MS technique can contribute to this.

Method: Subclinical mastitis was diagnosed by the California Mastitis Test (CMT), with milk collected from positive teats for microbiological analysis by Gram staining and subsequent identification by MALDI-TOF mass spectrometry. Teats were classified for hyperkeratosis and dirt according to standardized methodologies. The seasonal influence on mastitis was analyzed based on local climate data.

Results and Discussion: The prevalence of mastitis in the Compost Barn was 35%, with a higher frequency in the warmer, rainier months. There was an association between the occurrence of mastitis and hyperkeratosis (p<0.000001) and dirt (p = 0.02) in the Compost Barn system. Staphylococcus and Bacillus predominated in cases of mastitis. There was no dependence between the type of microorganism and the degree of subclinical mastitis (p = 0.053).

Research implications: The results may contribute to developing efficient strategies to combat and control bovine mastitis in the dairy sector.

Originality/value: This study contributes to the literature by showing the association of factors with the occurrence of bovine mastitis on dairy farms in the north of Minas Gerais. Using the MALDI-TOF MS technique, it also contributes to the libraries of microorganisms involved in cases of mastitis. The relevance and value of this research are evidenced by its influence on the decision-making process of dairy farmers.
أثر القيادة الاستراتيجية في تحسين الأداء للموظفين بمستشفى الملك فهد المركزي في جازان
Authors: مهاجر جبريل عبده 
Published: January 2025

المشكلة: تتلخص مشكلة الراسة في التساؤل الرئيسي "ما أثر القيادة الاستراتيجية في تحسين الأداء للموظفين بمستشفى الملك فهد المركزي في جازان؟" الهدف: تهدف الدراسة الحالية إلى معرفة أثر القيادة الاستراتيجية في تحسين الأداء للموظفين بمستشفى الملك فهد المركزي في جازان. الطريقة والأدوات: استخدمت الدراسة المنهج الوصفي التحليلي ويتمثل مجتمع الدراسة الحالية من جميع الموظفين بمستشفى الملك فهد المركزي في جازان والبالغ عددهم (108) مفردة، وعينة تم اختيار أفراد العينة بطريقة العينة العشوائية البسيطة، وتم تطبيق الدراسة على (40) موظفاً باختلاف أعمارهم ومؤهلاتهم التعليمية ومركزهم الوظيفي، وتم التوزيع عبر الاستبيان وتحليل البيانات عن طريق البرنامج الإحصائي (ٍ Spss). النتائج : أن هناك إصغاء الإدارة العليا في المستشفى لأفكار وآراء ومقترحات عامليها، أن إدارة المستشفى تعمل على متابعة أداء العاملين على نحو منتظم وتقييم مستمر، هناك اهتمام كبير من أدارة المستشفى بمتابعة احتياجات العاملين وتلبيتها، أن إدارة المستشفى تصيغ أهداف واضحة وقابلة للتحقيق باقل تكلفة مما يحقق تقدم العمل ضمنها، اجمع أفراد العينة بقيام تقوم أدارة المستشفى بمراجعة مستمرة للجداول الزمنية والتوقيت النهائي للمهام المنفذة، تسعى الإدارة العليا لأن تقيم علاقات جيدة وطويلة الأمد مع المجتمع الذي تخدمه، تسعى الإدارة العليا إلى أن تتمتع بقدم وظيفي وإداري لمدة طويلة وترويج الإدارة الجيدة من داخل أعضائها. التوصيات: تطوير رؤية واضحة: يجب على الإدارة العليا وضع رؤية استراتيجية واضحة للمستشفى، تُعبر عن الأهداف والطموحات المستقبلية، تعزيز التواصل الفعّال: إنشاء قنوات تواصل مفتوحة بين الإدارة والموظفين لضمان تبادل المعلومات والأفكار والملاحظات.
دور الإدارة الإلكترونية في تطوير بيئة العمل في القطاع الحكومي: دراسة تطبيقية على عينة من المؤسسات بمنطقة عسير
Authors: اليوسي أسماء علي , الشعيبي محمد الصغير قاسم 
Published: January 2025

هدفت الدراسة إلى التعرف على دور الإدارة الإلكترونية في تطوير بيئة العمل بمؤسسات القطاع الحكومي بمنطقة عسير. واستخدم الباحثان المنهج الوصفي التحليلي لتحقيق أهداف الدراسة، وطبَّقت استبانة على عينة عشوائية بسيطة قوامها (٣٥٠) موظفاً من القطاع الحكومي بمنطقة عسير. وتوصلت الدراسة إلى نتائج، من أهمها: أن مؤسسات القطاع الحكومي بمنطقة عسير تطبق الإدارة الإلكترونية بدرجة موافقة كبيرة، وبمتوسط حسابي (4.18)، وجاء مجال التنظيم الإلكتروني في مقدمة المجالات المتحققة، بمتوسط حسابي (4.23)، يليها مجال الرقابة الإلكترونية، بمتوسط حسابي (4.19)، ثم مجال التخطيط الإلكتروني، بمتوسط حسابي (4.15)، وأخيراً مجال التوجيه الإلكتروني، بمتوسط حسابي (4.14). كما أظهرت النتائج موافقة بدرجة كبيرة لدى عينة الدراسة على واقع بيئة العمل في مؤسسات القطاع الحكومي بمنطقة عسير، بمتوسط (4.19)، وجاء مجال البيئة التنظيمية في مقدمة الأبعاد المتحققة، بمتوسط حسابي (4.21)، يليه مجال البيئة المادية، بمتوسط حسابي (4.14). وأظهرت النتائج كذلك وجود علاقة ارتباطية موجبة بين الإدارة الإلكترونية وواقع بيئة العمل، كما افصحت عن وجود أثر ذو دلالة إحصائية للإدارة الإلكترونية بأبعادها المختلفة في تطوير بيئة العمل في مؤسسات القطاع الحكومي بمنطقة عسير. وتوصلت النتائج كذلك عن عدم وجود فروق ذات دلالة إحصائية عند مستوى الدلالة (a≤0.05) بين متوسطات استجابات عينة الدراسة حول دور الإدارة الإلكترونية في تطوير بيئة العمل بمؤسسات القطاع الحكومي بمنطقة عسير، تعزى لاختلاف الجنس، والعمر، والمستوى التعليمي، والمنصب الوظيفي، وعدد سنوات الخبرة. بينما وُجدتْ فروقٌ تعزى لاختلاف جهة العمل في محور الإدارة الإلكترونية، وكانت الفروق في صالح فرع الإدارة العامة للجوازات.