bluuebunny/crossref_metadata_2025_split huggingface dataset:
Normative values of motor performance and their relationship with BMI status in Hong Kong preschoolers
Authors: Yip Ka-Man , So Hung-Kwan , Tung Keith , Wong Rosa , Tso Winnie , Wong Ian , Yam Jason , Kwan Mike , Louie Lobo , Lee Albert , Wong Wilfred , Hui Lai-Ling , Nelson E.A.S. , Ip Patrick 
Published: December 2023

Abstract
This study aimed to establish sex- and age-specific reference values for motor performance (MP) in Hong Kong preschoolers aged 3–5 years old and examine the relationship between MP and BMI status. A cross-sectional study was conducted among 5,579 preschoolers in Hong Kong. Three MP tests were administered, and height and weight information were collected. GAMLSS was used to compute the normative values of the motor tests. Boys outperformed girls in activities requiring muscle strength and power, while girls outperformed boys in activities requiring balance and coordination. The MP scores increased with age for both overarm beanbag throw and standing long jump for both sexes, while the one-leg balance scores showed larger differences between P50 and P95 in older preschoolers. Children with excessive weight performed worse in standing long jump and one-leg balance compared to their healthy weight peers. This study provides valuable information on the MP of preschoolers in Hong Kong, including sex- and age-specific reference values and the association between BMI status and MP scores. These findings can serve as a reference for future studies and clinical practice and highlight the importance of promoting motor skill development in preschoolers, particularly those who are overweight or obese.
Urbanization Trends and Challenges: A Case Study in the Asan Watershed of Uttarakhand on Urban Growth Patterns and Sustainable Land Use Planning
Authors: Sharma Ankita , Nikam Bhaskar , Bagri Dhirendra Singh 
Published: December 2023

Abstract

Historical evidence suggests that urbanization is an inevitable and universal process, all over the world. Notably, urbanization has outpaced the average population growth rate, indicating the rapid pace of urban expansion. The case study focuses on the Asan watershed of Uttarakhand, one of India's highly urbanized states, where urban population growth is remarkable. The paper discusses the significance of raising urban diameter within the region based on specific criteria like decadal Census statistics and Land cover dynamics. It highlights the importance of accurate urban mapping and monitoring, using advanced technologies like remote sensing and GIS, to assess urban growth patterns and inform effective urban planning. Through the use of statistical techniques, remote sensing, and GIS, the study enables cost-effective and comprehensive urban studies to enhance decision-making. It also includes a comparative analysis of population statistics for India and its selective regions. The LULC changes exert substantial impacts on natural resources, socioeconomic factors, and environmental hydrological processes. The associate study requires the creation of decadal Land Use/Land Cover maps, areal analysis, validation through accuracy assessment, and the generation of urban growth pattern maps along with the direction of growth expansion. The analysis revealed a concerning trend of rapid urban expansion in the study area, which increased nearly four times over almost four decades, while the percentage of forest, plantations, cropland, and water bodies decreased significantly. The findings also highlighted the dominant directions of urban expansion over time. The study predicts that the eastern portion of the area is likely to continue dominating urban expansion in the future. Overall, the study provides valuable insights into the changing landscape and urbanization patterns within the region, emphasizing the importance of sustainable land use planning and environmental conservation efforts to address the challenges posed by rapid urban growth and its impact on natural resources.
Comprehensive Insights into Health Services Accessibility and Quality of Life of Families with Individuals with 22q11.2 Deletion Syndrome in Brazil
Authors: Silva Isabela Mayá Wayhs , Gil-da-Silva-Lopes Vera Lúcia 
Published: December 2023

Abstract

Background
The 22q11.2 Deletion Syndrome (22q11.2 DS) presents unique healthcare challenges for affected individuals, families, and healthcare systems. Despite its rarity, 22q11.2 DS is the most common microdeletion syndrome in humans, emphasizing the need to understand and address the distinctive healthcare requirements of those affected. This paper examines the multifaceted issue of health service access and caregivers’ quality of life in the context of 22q11.2 DS in Brazil, a condition with diverse signs and symptoms demanding multidisciplinary care. This study employs a comprehensive approach to evaluate health service accessibility and the quality of life of caregivers of individuals with 22q11.2 DS. It utilizes a structured Survey and the WHOQOL-bref questionnaire for data collection.
Results
Individuals with 22q11.2 DS continue to receive incomplete clinical management after obtaining the diagnosis, even in the face of conditions that enabled an average age of diagnosis that precedes that found in sample groups that are more representative of the Brazilian population (mean of 3.2 versus 10, respectively). In turn, caring for individuals with 22q11.2 DS who face difficulty accessing health services impacts the perception of quality of life associated with the caregivers' environment of residence.
Conclusions
Results obtained help bridge the research gap in understanding how caring for individuals with multisystem clinical conditions such as 22q11.2 DS and difficulties in accessing health are intertwined with aspects of quality of life in Brazil. This research paves the way for more inclusive healthcare policies and interventions to enhance the quality of life for families affected by this syndrome.
The Administrative Data Cystectomy Model and its Impact on Misclassification Bias
Authors: Ross James , Lavallee Luke T. , Hickling Duane , Walraven Carl van 
Published: December 2023

Abstract
Background:
Misclassification bias (MB) is the deviation of measured from true values due to incorrect case assignment. This study compared MB when cystectomy status was determined using administrative database codes vs. predicted cystectomy probability.
Methods:
We identified every primary cystectomy-diversion type at a single hospital 2009-2019. We linked to claims data to measure true association of cystectomy with 30 patient-hospitalization factors. Associations were also measured when cystectomy status was assigned using billing codes and cystectomy probability from multivariate logistic regression model with covariates from administrative data. MB was the difference between measured and true associations.
Results:
500 people underwent cystectomy (0.12% of 428 677 hospitalizations). Sensitivity and positive predictive values for cystectomy codes were 97.1% and 58.6% for incontinent diversions and 100.0% and 48.4% for continent diversions, respectively. The model accurately predicted cystectomy-incontinent diversion (c-statistic [C] 0.999, Integrated Calibration Index [ICI] 0.000) and cystectomy-continent diversion (C:1.000, ICI 0.000) probabilities. MB was significantly lower with imputed cystectomy-diversion type status using model-based predictions for both incontinent cystectomy (F=12.75; p<.0001) and continent cystectomy (F=11.25; p<.0001).
Conclusions:
A model using administrative data accurately returned the probability that cystectomy by diversion type occurred during a hospitalization. Using this model to impute cystectomy status minimized MB. Accuracy of administrative database research can be increased by using probabilistic imputation to determine case status instead of individual codes.
Long COVID and recovery from Long COVID: Quality of life impairments and subjective cognitive decline at a median of 2 years after initial infection
Authors: Szewczyk Warren , Fitzpatrick Annette L , Fossou Herve , Gentile Nicole L , Sotoodehnia Nona , Vora Surabhi , West T Eoin , Bertolli Jeanne , Cope Jennifer R , Lin Jin-Mann , Unger Elizabeth , Vu Quan M 
Published: December 2023

Abstract

Background:Quality of life (QoL) and cognition for those with Long COVID is not well-characterized, but existing research suggests impairments in both persist beyond 12 months after initial illness.
Methods:In this cross-sectional study, 435 participants with SARS-CoV-2 infection, confirmed with laboratory test or physician diagnosis, between March 2020 and December 2021 completed self-report surveys between March 2022 and September 2022 (n=7305 sent surveys; response rate=6.0%). Multi-domain QoL and cognitive concerns were evaluated using PROMIS-29 and the Cognitive Change Index-12. Those not recovered from COVID-19 at time of survey (“Current Long COVID”; n=181) and those who recovered from COVID-19 in >3 months (“Recovered Long COVID”; n=34), were combined to form a Long COVID group (n=215) and were compared with those who recovered from COVID in ≤3 months (“Without Long COVID”; n=220).
Results: Nearly half the participants (47.7%) were surveyed more than 2 years from initial infection (median=23.3 months; IQR=18.6, 26.7). The Long COVID group showed significantly greater proportion of moderate-to-severe impairment in all health domains assessed compared to those Without Long COVID (all p<0.05). The Recovered Long COVID group showed significantly lower prevalence of fatigue, pain, depression, and physical and social function impairment compared to those with Current Long COVID (all p<0.05). However, compared to patients Without Long COVID, the Recovered Long COVID group had greater prevalences of fatigue, pain (P≤0.06) and subjective cognitive decline (61.8% vs 29.1%; p<0.01).
Multivariate relative risk (RR) regression indicated Long COVID risk was greater for older age groups (RR range 1.46-1.52; all p≤0.05), those without a bachelor’s degree (RR=1.33; 95% CI=1.03-1.71; p=0.03), and those with 3 or more comorbidities prior to SARS-CoV-2 infection (RR=1.45; 95% CI=1.11-1.90; p<0.01). Each additional symptom experienced during acute COVID-19 was associated with a 14% greater Long COVID risk (RR=1.14, 95% CI=1.10-1.18; p<0.01).
Conclusions: Long COVID is associated with long-term cognitive complaints and diminished quality of life. Older age, not having a bachelor’s degree, and pre-existing comorbidities are risk factors for prolonged or non-recovery from COVID-19. Recovery from Long COVID was reported by a subset of those with Long COVID, though clinically significant cognitive complaints, fatigue, and pain persisted.
Methylene Blue (MB) removal from Aqueous Solution by Alum; Catalytic Ozonation Process
Authors: Ikhlaq Amir , Parveen Sehrish , Masood Zafar , Rizvi Osama Shaheen , Johani Eng. Thamer Abdulhameed Al , Ahsan Muffakir , Amjad Hadeeqa , Qi Fei 
Published: December 2023

Abstract
The Textile wastewater is among the most polluted types of industrial waste. Wastewater treatment in the textile industries is notoriously difficult because of the use of complex chemicals, Dyes in the textile production steps and conventional methods are not enough to treat these chemicals. Textile wastewater, known for its high pollution levels, poses challenges for treatment due to complex chemicals and dyes. A comparative study was conducted on simple ozonation and catalytic ozonation using alum as a catalyst for degrading methylene blue. Various factors like time, pH, catalyic and ozone dosage were analyzed. Results showed that catalytic activity in ozonation is pH and ozone flow dependent. pH 6.6 and 200V ozone flow achieved maximum methylene blue elimination. Scanning electron microscopy (SEM) was used to characterize surface morphology of catalyst, (FTIR) Fourier transform infrared spectroscopy was used to identify the important functional groups, and energy dispersive X-ray spectroscopy (EDS) was used to characterize the catalyst's elemental composition. Compared to simple ozonation, catalytic ozonation showed higher removal in the initial phase. Real textile wastewater analysis confirmed the effectiveness of alum catalyst in achieving significant removal of methylene blue (87%) through this novel cost-efficient process.
Development of new microplastic reference particles for usage in pre-defined numbers
Authors: Oster Simon D.J. , Bräumer Paul E. , Wagner Daniel , Rösch Max , Fried Martina , Narayana Vinay K.B. , Hausinger Eva , Metko Helena , Vizsolyi Eva C. , Schott Matthias , Laforsch Christian , Löder Martin G.J. 
Published: December 2023

Abstract
For almost two decades now, scientists have increasingly focused on the occurrence of microplastics in the environment and their impact on environmental and human health. Currently, the variety of analytical methods used in microplastic research result in data of different quality and resolution. This largely hampers comparability between data sets and consequently prevents a reliable risk assessment. In this context, the lack of suitable reference microplastic particles that can be added as internal standard in an exactly known number further prevents quality assessment of, and harmonization in terms of comparability between different analytical methods. Although this lack has widely been recognized, currently only reference microplastic particles in form of micro-beads or -fragments (powders) are commercially available. Manual addition of such reference microplastic particles to samples in a precisely defined number as an internal standard is inefficient and the alternative use of microplastic particle suspensions does not allow for the addition of an exactly defined particle number. The optimum solution to solve this issue would be reference microplastic particles embedded in an easy-to-use soluble matrix in exact numbers. This would allow for evaluating analytical quality during microplastic analysis as well as establishing harmonization in terms of comparability between different methods. In the present study we focused on the development of such reference microplastic particles. We used CNC milling for the production of small diameter plastic columns followed by gelatine embedment and subsequent cryosectioning. This results in gelatin slices containing an exactly defined number of reference microplastic particles with well-defined size, shape and polymer type / chemical composition that can be added to a sample easily with the dissolution of the gelatine. We successfully produced square shaped reference microplastic particles in a size range of 125–1000 µm of five different polymers. The overall size-deviation of the reference microplastic particles never exceeded ± 11.2% from the mean value of a set of particles. The highest percentage weight-deviation was 25.5% from the mean value of a set of 125 x 125 x 20 µm PS reference microplastic particles. Our approach allows for the production of reference microplastic particles tailored to specific needs of all different analytical methods used in current microplastic research. Beyond analytical method validation, these reference microplastic particles furthermore open possibilities for experiments on microplastics ranging from organismic uptake to environmental distribution.
Changes in physical properties with varying impregnation temperatures and compression times during fabrication of carbon blocks using needle cokes and pitch
Authors: Youn U-Sang , Lee Sang-Hye , Kim Jong-Bok , Roh Jae-Seung 
Published: December 2023

Abstract
Impregnation was conducted to decrease the pores formed during the carbonization process after manufacturing carbon blocks using needle cokes and coal tar pitch. This was carried out in the order of heating, subjecting to vacuum, and compression, and changes in mechanical and electrical properties before and after impregnation were analyzed with impregnation temperature and compression time as variables. The impregnation temperatures were 150, 200, and 250°C, and compression times were 30, 60, and 90 min. The optimal impregnation temperature was 200°C, resulting in a 12.5% increase in bulk density and a 26.0% decrease in porosity after impregnation of the carbon blocks. The optimal compression time was 60 min, leading to a 14.3% increase in bulk density and a 24.0% decrease in porosity after impregnation. Under the selected optimal conditions, after three impregnation cycles, the bulk density increased by 33.8% compared to the initial state (0 cycles 1.259 g/cm³ → 3 cycles 1.685 g/cm³), and porosity decreased by 56.8% (0 cycles 39.1% → 3 cycles 16.9%). According to the performance evaluation of carbon blocks, electrical resistivity decreased by 52.0% (72.5 µΩm → 34.8 µΩm) and flexural strength increased by 368.3% (6.0 MPa → 28.1 MPa). The substantial increase in flexural strength was attributed to the reduction in porosity.
Technological Vanguard: The Outstanding Performance of the LTY-CNN Model for the Early Prediction of Epileptic Seizures
Authors: yang yang , Luan Tianyun , Yu Zhangjun , Zhang Min , Li Fengtian , Chen Xing , Gao Fei , Zhang Zhijun 
Published: December 2023

Abstract
Background: Epilepsy is a common neurological disorder that affects approximately 60 million people worldwide. Characterized by unpredictable neural electrical activity abnormalities, it results in seizures with varying intensity levels. Electroencephalography (EEG), as a crucial technology for monitoring and predicting epileptic seizures, plays an essential role in improving the quality of life for people with epilepsy.
Method: This study introduces an innovative deep learning model, a lightweight triscale yielding convolutional neural network” (LTY-CNN), that is specifically designed for EEG signal analysis. The model integrates a parallel convolutional structure with a multihead attention mechanism to capture complex EEG signal features across multiple scales and enhance the efficiency achieved when processing time series data. The lightweight design of the LTY-CNN enables it to maintain high performance in environments with limited computational resources while preserving the interpretability and maintainability of the model.
Results: In tests conducted on the SWEC-ETHZ and CHB-MIT datasets, the LTY-CNN demonstrated outstanding performance. On the SWEC-ETHZ dataset, the LTY-CNN achieved an accuracy of 99.9%, an area under the receiver operating characteristic curve (AUROC) of 0.99, a sensitivity of 99.9%, and a specificity of 99.8%. Furthermore, on the CHB-MIT dataset, it recorded an accuracy of 99%, an AUROC of 0.932, a sensitivity of 99.1%, and a specificity of 93.2%. These results signify the remarkable ability of the LTY-CNN to distinguish between epileptic seizures and nonseizure events. Compared to other existing epilepsy detection classifiers, the LTY-CNN attained higher accuracy and sensitivity.
Conclusion: The high accuracy and sensitivity of the LTY-CNN model demonstrate its significant potential for epilepsy management, particularly in terms of predicting and mitigating epileptic seizures. Its value in personalized treatments and widespread clinical applications reflects the broad prospects of deep learning in the health care sector. This also highlights the crucial role of technological innovation in enhancing the quality of life experienced by patients.
Development of Respiratory Motion-Resolved Hepatobiliary Phase Cine-Magnetic Resonance Imaging for Stereotactic Body Radiotherapy in Liver Tumor
Authors: Shimada Ryuji , Sofue Keitaro , Tianyuan Wang , Ishihara Takeaki , Ueshima Eisuke , Ueno Yoshiko , Kusaka Akiko , Murakami Takamichi 
Published: December 2023

Abstract

Cine-magnetic resonance imaging (MRI) has been used to track respiratory-induced motion of the liver and tumor and assist in the accurate delineation of tumor volume. Recent developments in compressed sensitivity encoding (SENSE;CS) have accelerated temporal resolution while maintaining contrast resolution. This study aimed to develop and assess hepatobiliary phase (HBP) cine-MRI scans using CS. Phantom was imaged using cine-MRI and signal intensity (SI) and contrast ratio (CR) measured to determine the optimal flip-angle turbo field echo (TFE) prepulse delay. Twenty patients underwent HBP cine MRI after injecting gadoxetic acid every 0.5 s for 1 min. Acquired images had three different acceleration factors (SENSE, CS without denoising [CS-no], and CS with strong denoising [CS-strong]). The image quality of the HBP cine MRI was quantitatively and qualitatively analyzed. In the phantom study, a flip angle of 30 °and TFE prepulse delay of 150 ms were optimal for clinical imaging. In a clinical study, CS-strong showed the highest signal-to-noise ratio and comparable contrast ratio among the three sequences. The CS-strong group showed a significantly higher image quality (P < 0.01), except for motion smoothness (P = 0.11). CS with denoising improved the tumor-to-liver contrast and image quality in high-temporal-resolution HBP cine MRI.
Participants in a tourism city's environmental protection behavior: a game analysis
Authors: Zhu Linlin 
Published: December 2023

Abstract
The way that tourists behave when making decisions has a big impact on both the growth of tourism and the preservation of the environment. This paper builds a tripartite dynamic game analysis model of tourism development and environmental protection behavior from the perspectives of tourism city government, community, and tourism enterprises. It then computes the equilibrium solution of tripartite benefit maximization based on the dynamic game model. Based on this, the action plan for environmental protection during the development of tourism is presented in accordance with the three parties' best decision.The governments of tourist cities can increase the punishment for some behaviors that may damage the environment by establishing environmental protection regulations. At the same time, the role of the community in the development of the tourism city is played, and the participation of the community is helped in innovative ways. Tourism enterprises can actively introduce tourism professionals to enhance the overall service awareness of the tourism industry.
Synthesis of NaAlSiO4 Hollow Microspheres as Absorbents for the Removal of Heavy Metal ions in Environmental Remediation
Authors: Ouyang Zhiyuan , Meng Lihui , Hu Yanru , Li Wenchao , Zhu Fang , Xie Bin , Zhou Zilin , Cui Shuojie , Wang Meng , Wu Qingzhi 
Published: December 2023

Abstract
The harm of heavy metal ions to the environment has attracted increasing attention. Adsorption has been proven to be one of the best choices for controlling water pollution. Hollow microspheres with a high surface area and large internal space have been considered ideal adsorbents. In this work, NaAlSiO4 hollow microspheres were synthesized through a solvothermal method combined with calcination treatment. The removal ability of the hollow microspheres to heavy metal ions was evaluated using Ni(II) and Cd(II) as the models under different conditions, including different pH values, metal ion concentrations, and adsorption times. SEM and TEM images show that the average diameter of the hollow microspheres was approximately 2 ± 0.5 µm, and the average pore size was approximately 20 ~ 60 nm. The peak near 707°C in the DSC curve indicates the crystal transformation from an amorphous state to a well-crystallized state, and well-crystallized NaAlSiO4 microspheres can be obtained after calcination at 850℃. The maximum adsorption capacity of the hollow microspheres was 115.15 ± 1.68 mg·g− 1 for Ni(II) and 106.03 ± 0.97 mg·g− 1 for Cd(II). The adsorption of the NaAlSiO4 hollow microspheres depends on the surface area and content of CTAB for Ni(II) and Cd(II), respectively. The Ni(II) adsorption efficiency of the NaAlSiO4 hollow microspheres was still more than 95% after 4 cycles. This study provides an effective absorbent for removing heavy metal ions in wastewater treatment and environmental remediation.