bluuebunny/crossref_metadata_2025_split huggingface dataset:
Europe will struggle to meet the new WHO Air Quality Guidelines
Authors: Im Ulas , Ye Zhuyun , Schuhen Nina , Chowdhury Sourangsu , Christensen Jesper , Geels Camilla , Hänninen Risto , Hodnebrog Øivind , Marelle Louis , Sofiev Mikhail , Brandt Jørgen , Aunan Kristin 
Published: December 2024

Abstract

The World Health Organization (WHO) updated its Global Air Quality Guidelines in 2021 due to growing evidence on adverse health impacts of air pollution even at low concentrations. We used an ensemble of regional atmospheric chemistry models to simulate fine particulate matter (PM2.5) and ozone (O3) levels over Europe in 2015–2050 and assessed the compliance of European countries with the new guidelines under different emission scenarios. The results show that 65% of the EU countries will comply with the PM2.5 target value (5 µg m− 3) by 2050 under ambitious emission reductions (SSP1-2.6). Under less ambitious mitigation scenarios (SSP2-4.5 and SSP3-7.0), the compliance level is only 10%. In addition, none of the EU countries will comply with the O3 target value (60 µg m− 3), while interim values are achieved in most of the EU countries, partly under SSP2-4.5, and to a large extent under SSP1-2.6. These results highlight that reaching the new WHO limit values will be challenging for Europe, however, partly due to natural contribution to PM2.5 reaching up to 50% in some regions. These imply the necessity of more drastic emission reductions to meet the targets.
Design of an Integrated Model for Gait Identification Using DDPG, Sparse Group Lasso, and Stacked Generalization
Authors: Urkude Giridhar , Misal Ashish Kumar , Choubey Abha , Choubey Siddharth 
Published: December 2024

Abstract

Applications in security, healthcare, and human-computer interaction critically require accurate gait identification under complex environmental conditions such as varying lighting and background noise. Current approaches are usually unable to adapt to dynamic, highdimensional environments, with reduced accuracy of feature extraction and classification. This paper bridges the gap by offering an overview of a multi-stage framework that merges the advanced techniques of machine learning with those of reinforcement learning for preemptive optimization. It begins by using Deep Deterministic Policy Gradient for a preprocessing module: environmental parameters are dynamically adjusted so that their real-time data quality is optimized. The module is then followed by a phase in multi-domain feature extraction using Sparse Group Lasso along with KMeans clustering, thereby improving representativeness while reducing dimensionality by 50–60%. We have used a hybrid of stacked generalization, in this case of XGBoost and LightGBM, because this provides a better overall classification accuracy. Refined temporal post-processing at the hidden Markov model and Auto-Regressive Integrated Moving Average (ARIMA) results in enhanced phase transitions that may be gait-based, thus improving the identification accuracy. As the final step, we use Proximal Policy Optimization to implement feedback-driven reinforcement learning, where improvements are incrementally made by updating the model with iterative feedback. This new method enhances the correctness of feature extraction by 12% in complex environments. Overall classification accuracy increases by 5–6% and reaches 95%. False positives in gait phase transitions decrease as well, further increasing the system robustness and reliability in real-world applications.
Strategic Plan Formulation for the Tourism Sector of Bankura District using the SWOT and AHP Techniques
Authors: Raha Shrinwantu , Mondal Madhumita , Gayen Shasanka Kumar 
Published: December 2024

The strategic plan is important for the management of tourism resources in the particular region. However, the strategic planning for the Bankura District is still very far from being accomplished. The study was aimed to formulate the strategic plan for the Bankura District by combining the Analytic Hierarchy Process (AHP) and SWOT (Strength-Weakness-Opportunities-Threats) techniques. The methodology involved a five-step approach, which included the identification of SWOT factors, formulation of pair-wise comparison matrices and the strategy formulation using the TOWS (Threats-Opportunities-Weakness-Strengths) matrix. The data was collected both from the primary and secondary sources. The purposive sampling technique was used to interview the key stakeholders (800 tourists, 120 souvenir people and 87 tourist guides and hotel managers) and the non-participant observation technique were utilized to observe the nature of tourism in the study area. The findings of the research showed that the strength (S) and opportunity (O) factor obtained the highest priorities within the group. Therefore the S-O combination dominates in the strategic planning and management in the study area. The development of tourism may significantly contribute to the community members' feeling of pride in their area and culture by offering a supplemental source of revenue and livelihood with careful planning and implementation.
Indeks Topologi Padmakar Ivan dan Szeged pada Graf Koprima Prima dari Grup Bilangan Bulat Modulo
Authors: Abdurahim Abdurahim , Pratiwi Lia Fitta , Karang Gusti Yogananda , Wardhana I Gede Adhiya Wisnu , Irwansyah Irwansyah , Awanis Zatta Yumni , Romdhini Mamika Ujianita 
Published: December 2024

The Prime Coprime Graph is defined as a graph in which two distinct vertices are adjacent if and only if the greatest common divisor of their orders is 1, indicating that they are coprime. This research focuses on deriving general formulas for the Padmakar-Ivan index and the Szeged index for the coprime prime graph of the modulo integer group with n=p^k, where p is a prime number and k is not less than 2. As a result of this study, explicit formulas for the Padmakar-Ivan and Szeged indices were obtained, along with an analysis of the relationship between these two indices.Keywords: prime coprime graph, Padmakar-Ivan index, Szeged index.
Cuidados de enfermería a adolescente con afrontamiento ineficaz en el contexto académico
Authors: Escobar-Velásquez Katty Dayana , Barajas-Lizarazo Mayra Alejandra , Gómez-Velásquez Alexa Fernanda 
Published: December 2024

Introducción: la valoración del dominio de afrontamiento y tolerancia al estrés y los cuidados ofrecidos por el profesional de enfermería contribuyen a optimizar los recursos internos de las personas y proporcionar mecanismos de enseñanza para afrontar de una mejor manera los problemas de la vida Caso clínico: se presenta caso de un adolescente de 14 años que cursa actualmente noveno grado en un colegio público de Pamplona, Colombia, quien presentaba dificultades para cumplir con actividades académicas a causa del desconocimiento de planificar actividades de forma organizada. Conclusión: las intervenciones de enfermería desde el enfoque de psicosocial favorecen el bienestar mental del adolescente, cuya premisa es reconocer los atributos y recursos propios de cada persona y a partir de allí potenciarlas para resolver de manera asertiva las situaciones estresantes. La adolescente expresó una mayor sensación de control sobre su tiempo y desempeño, lo cual se reflejó en su participación constante y preparación adecuada en clases y actividades grupales.
Post-COVID-19 Syndrome-associated Risk Factors for Acne Exacerbation
Authors: Sun Mingxia , Guo Jing , Li Yuanyuan , Chen Lamei , Meng Yunfang , Wu Jing , Dang Ningning 
Published: December 2024

Introduction:
This study aimed to investigate the impact of coronavirus disease
2019 (COVID-19) syndrome on various aspects of acne exacerbation. Additionally,
we aimed to explore the risk factors for acne exacerbation after COVID-19 syndrome.

Method:
A total of 211 subjects with acne were enrolled, and their key demographic
characteristics and lifestyle factors were recorded. They were asked whether acne exacerbation
occurred after COVID-19 syndrome, as well as the latency of exacerbation, the
exacerbation location, and the form of skin lesions. The risk factors were analyzed using
the Cox proportional hazard regression model. Overall, 41.2% of cases reported exacerbation
of acne after COVID-19 syndrome. Age was found to be a protective factor. Additionally,
sufficient fruit intake may slightly prevent exacerbation. For participants engaging
in daily physical exercise, the likelihood of exacerbation was significantly increased
after COVID-19 syndrome.

Result:
The probability of exacerbation was significantly higher if an acne itch was present.
Patients who experienced exacerbation in the chin area were more likely to develop
acne-induced anxiety. Males had a higher risk of aggravation of the cyst form. Interestingly,
those with lower education levels were more likely to have aggravation in the
right cheek after COVID-19 syndrome. Moreover, physical exercise might prevent aggravation
in the front or back areas.

Conclusion:
Finally, fish intake of ≥240 g per week was related to the aggravation of
the hard nodule form. In conclusion, age and adequate fruit intake may play a protective
role, while acne itch and daily exercise may be risk factors for acne exacerbation.
Fibromyalgia Syndrome among Men and Women: Symptom Identification, Diagnosis, and Concurrence in a Nationally Representative Sample
Authors: Jacobs Molly , Crall Emma , Menzies Victoria 
Published: December 2024

Introduction/Objective
Fibromyalgia Syndrome (FMS) is characterized by chronic musculoskeletal pain and, no reliable biomarkers, diagnosis is difficult. While predominantly identified in women, men are also affected. This study examined FMS prevalence and racial/ethnic differences in clinical characteristics by gender.

Methods
We identified respondents in the 2018 National Health Interview Survey (NHIS) whose symptomology matched the 2016 American College of Rheumatology (ACR) diagnostic criteria. The relative likelihood of having “identified FMS,” “clinically diagnosed FMS”, and “concurrently identified-diagnosed FMS” among men and women reporting pain was compared by demographic, socioeconomic, and geographic characteristic.

Results
Analyses indicated different characteristics were associated with identified, diagnosed, and concurrent FMS among women and men. Among both women and men, the likelihood of identified FMS was comparatively higher among those at older ages, living in the South, and with higher body masses. Both women and men earning less than $100,000 had a higher likelihood of FMS identification compared to higher earners; however, the likelihood of being diagnosed with FMS was not correlated with income. While Black women were significantly more likely than White women to be identified as having FMS, they were less likely to have an FMS diagnosis. Black men were significantly more likely to be identified as having FMS, but less likely to have an FMS diagnosis. Compared to White women, Black and Hispanic women had a lower likelihood of concurrent FMS.

Conclusion
Results showed lower incidence rates of males with FMS. Unexplained racial differences in FMS diagnosis, identification, and concurrence warrant further research.
Prediction of the severity of acute urticaria in children, taking into account the type of autonomic dysfunction
Authors: Averkina L. A. , Posevina A. N. , Maltsev S. V. , Lebedenko A. A. 
Published: December 2024

Objective: to study the features of the inﬂuence of the autonomic nervous system on the severity of acute urticaria in children.Materials and methods: 73 children with acute urticaria were examined. Clinical research methods included an analysis of the life history and illness, an objective examination of the child, and recording of a cardiointervalogram.Results: clinical and anamnestic data made it possible to identify features of the course of the disease that were not previously noted before the development of urticaria, such as complaints of pain in the heart, a feeling of diﬃculty breathing (without the presence of concomitant quincke's edema), dizziness, increased sweating (mainly of the palms and soles); analysis of the initial autonomic tone in children with acute urticaria; in cases of mild disease, a pronounced predominance of eutonia is observed, which indicates a coordinated increase in the activity of both the sympathetic and parasympathetic parts of the autonomic nervous system, and in patients with a pronounced clinical picture, a noticeable predominance of vagotonia is recorded.Conclusion: The created model for predicting the severity of acute urticaria, taking into account clinical and anamnestic parameters, as well as changes in the functioning of the autonomic nervous system, makes it possible to more objectively assess the severity of this pathology.
Artificial Intelligence–Aided Diagnosis System for the Detection and Classification of Private-Part Skin Diseases: Decision Analytical Modeling Study
Authors: Wang Wei , Chen Xiang , Xu Licong , Huang Kai , Zhao Shuang , Wang Yong 
Published: December 2024

Background
Private-part skin diseases (PPSDs) can cause a patient’s stigma, which may hinder the early diagnosis of these diseases. Artificial intelligence (AI) is an effective tool to improve the early diagnosis of PPSDs, especially in preventing the deterioration of skin tumors in private parts such as Paget disease. However, to our knowledge, there is currently no research on using AI to identify PPSDs due to the complex backgrounds of the lesion areas and the challenges in data collection.

Objective
This study aimed to develop and evaluate an AI-aided diagnosis system for the detection and classification of PPSDs: aiding patients in self-screening and supporting dermatologists’ diagnostic enhancement.

Methods
In this decision analytical modeling study, a 2-stage AI-aided diagnosis system was developed to classify PPSDs. In the first stage, a multitask detection network was trained to automatically detect and classify skin lesions (type, color, and shape). In the second stage, we proposed a knowledge graph based on dermatology expertise and constructed a decision network to classify seven PPSDs (condyloma acuminatum, Paget disease, eczema, pearly penile papules, genital herpes, syphilis, and Bowen disease). A reader study with 13 dermatologists of different experience levels was conducted. Dermatologists were asked to classify the testing cohort under reading room conditions, first without and then with system support. This AI-aided diagnostic study used the data of 635 patients from two institutes between July 2019 and April 2022. The data of Institute 1 contained 2701 skin lesion samples from 520 patients, which were used for the training of the multitask detection network in the first stage. In addition, the data of Institute 2 consisted of 115 clinical images and the corresponding medical records, which were used for the test of the whole 2-stage AI-aided diagnosis system.

Results
On the test data of Institute 2, the proposed system achieved the average precision, recall, and F1-score of 0.81, 0.86, and 0.83, respectively, better than existing advanced algorithms. For the reader performance test, our system improved the average F1-score of the junior, intermediate, and senior dermatologists by 16%, 7%, and 4%, respectively.

Conclusions
In this study, we constructed the first skin-lesion–based dataset and developed the first AI-aided diagnosis system for PPSDs. This system provides the final diagnosis result by simulating the diagnostic process of dermatologists. Compared with existing advanced algorithms, this system is more accurate in identifying PPSDs. Overall, our system can not only help patients achieve self-screening and alleviate their stigma but also assist dermatologists in diagnosing PPSDs.
Implementing Findable, Accessible, Interoperable, Reusable (FAIR) Principles in Child and Adolescent Mental Health Research: Mixed Methods Approach
Authors: de Groot Rowdy , van der Graaff Frank , van der Doelen Daniël , Luijten Michiel , De Meyer Ronald , Alrouh Hekmat , van Oers Hedy , Tieskens Jacintha , Zijlmans Josjan , Bartels Meike , Popma Arne , de Keizer Nicolette , Cornet Ronald , Polderman Tinca J C 
Published: December 2024

Abstract

Background
The FAIR (Findable, Accessible, Interoperable, Reusable) data principles are a guideline to improve the reusability of data. However, properly implementing these principles is challenging due to a wide range of barriers.

Objectives
To further the field of FAIR data, this study aimed to systematically identify barriers regarding implementing the FAIR principles in the area of child and adolescent mental health research, define the most challenging barriers, and provide recommendations for these barriers.

Methods
Three sources were used as input to identify barriers: (1) evaluation of the implementation process of the Observational Medical Outcomes Partnership Common Data Model by 3 data managers; (2) interviews with experts on mental health research, reusable health data, and data quality; and (3) a rapid literature review. All barriers were categorized according to type as described previously, the affected FAIR principle, a category to add detail about the origin of the barrier, and whether a barrier was mental health specific. The barriers were assessed and ranked on impact with the data managers using the Delphi method.

Results
Thirteen barriers were identified by the data managers, 7 were identified by the experts, and 30 barriers were extracted from the literature. This resulted in 45 unique barriers. The characteristics that were most assigned to the barriers were, respectively, external type (n=32/45; eg, organizational policy preventing the use of required software), tooling category (n=19/45; ie, software and databases), all FAIR principles (n=15/45), and not mental health specific (n=43/45). Consensus on ranking the scores of the barriers was reached after 2 rounds of the Delphi method. The most important recommendations to overcome the barriers are adding a FAIR data steward to the research team, accessible step-by-step guides, and ensuring sustainable funding for the implementation and long-term use of FAIR data.

Conclusions
By systematically listing these barriers and providing recommendations, we intend to enhance the awareness of researchers and grant providers that making data FAIR demands specific expertise, available tooling, and proper investments.
Potential of Wood Modification Technologies on The Physical and Mechanical Properties of Albizia Falcataria: A Literature Review
Authors: Julian Treza Chandra , Fukuda Hiroatsu 
Published: December 2024

Wood modification treatment has grown in popularity over the last few years and continues to expand as an industrial method for improving certain types of wood. As a result of environmental concerns, the wood sector is under more pressure than ever to develop wood alternatives. Nowadays, fast-growing wood species appear to be increasingly potential as substitute wood sources for bridging the supply-demand gap in the wood industry. Albasia (Albizia falcataria), sometimes known as sengon wood, is a fast-growing wood widely planted in Indonesia. However, specific characteristics of the wood, such as low density, low hardness, and low strength, have been hindering its end-use applications as a building material. Therefore, numerous technologies are utilized to enhance wood's physical and mechanical qualities. This paper summarizes the extensive literature on wood modification of Albizia falcataria and synthesizes the major publications on wood properties, chemical changes, wood uses, and quality control. Acetylation, furfurylation, thermal modification, and impregnation as wood modification technologies have been utilized in Albizia falcataria studies. Based on recent investigations, this article aims to review the current state of knowledge regarding the wood modification technologies for improving physical and mechanical properties of Albizia falcataria. Identifying the gaps in research would also aid in accelerating the research activities for deploying these modification technologies on an industrial scale.
MONITORAMENTO DE IMPACTOS EM TRILHAS: ESTUDO DE CASO DA TRILHA DOS ARENITOS, PARQUE ESTADUAL DE VILA VELHA (PR)
Authors: Farias dos Santos Emerson , Moreira Jasmine Cardozo 
Published: December 2024

A busca por novas rotinas aumentou o interesse pelos atrativos turísticos naturais, fazendo das Unidades de Conservação uma opção para os visitantes em busca de novas experiências de contato com a natureza. O Parque Estadual de Vila Velha é uma Unidade de Conservação localizada em Ponta Grossa que apresenta características geológicas, de fauna e flora únicas, capazes de atrair turistas. Para esta pesquisa a metodologia empregada é a quali-quantitativa do tipo exploratório. Foram realizadas três visitas técnicas para a coleta de dados, entre os meses de novembro de 2021 e fevereiro de 2022. Para a caracterização da trilha foram utilizados dados obtidos anteriormente, tomando como base o roteiro metodológico para manejo de impactos da visitação do ICMBio, e foi realizada a classificação biofísica da trilha segundo a FEMERJ. A trilha dos Arenitos é considerada uma trilha leve com boa acessibilidade e baixa exposição ao risco, contudo apresenta alguns riscos provenientes dos impactos observados (como pisos soltos e erosão das rochas) além de apresentar um alto nível de exposição ao sol em seu percurso. Sugere-se a instalação de novas lixeiras e a intensificação da vistoria pelos monitores, com o intuito de minimizar os impactos ambientais no Parque Estadual de Vila Velha – PR.
Educação e decolonialidade
Authors: Maciel Sandra de Souza 
Published: December 2024

Esta é uma resenha da obra: OLIVEIRA, Luiz Fernandes. Educação e Militância Decolonial. Rio de Janeiro: Editora Selo Novo, 2022. Aborda a crítica ao eurocentrismo e à colonialidade na educação, defendendo práticas decoloniais e a valorização de saberes subalternizados. Foca no papel da militância e na ressignificação do conhecimento.
Pendekatan Sistem Informasi Geografis dan Metode AHP untuk Pemetaan dan Perencanaan Industri Pangan Berbasis Komoditas Utama di Lampung Timur
Authors: Izudin Muhammad Asef , Ridwan Ridwan , Amien Elhamida Rezkia , Asmara Sandi 
Published: December 2024

East Lampung Regency, located in Lampung Province, holds significant potential for the development of agro-industries based on food crops, particularly corn, rice, and cassava. This study aims to identify the most promising and sustainable agro-industrial commodities using the Geographic Information System (GIS) and Analytical Hierarchy Process (AHP) approaches. The analysis was conducted using spatial and non-spatial data, including land surface temperature (LST), rainfall, soil quality, slope, and land use. The results indicate that corn and cassava have very high land suitability (S1), while rice is moderately suitable (S2). Market factors and pricing are key considerations in selecting the priority commodities. The GIS approach provides informative land suitability maps, while AHP helps establish commodity priorities. The combination of these methods offers a strategic guide for planning and developing sustainable agro-industries in East Lampung Regency. Keywords: ArcGIS, Landsat 8 image, Land Suitability, Potential Featured Commodities.