bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ecological Suitability Evaluation of Traditional Village Locations in Jiangxi Province Based on Multi-Model Integration Using Artificial Intelligence
Authors: Zhang Cheng , Gong Huimin , Teng Jinlin , Liu PeiLin , Liu Chunqing 
Published: August 2024

Abstract

Traditional villages have evolved over time to adapt to their environmental characteristics, demonstrating high ecological
suitability. Ideal village locations not only provide comfortable living spaces but also ensure safety and sustainability, reflecting
the ancestors’ profound understanding of the natural environment and ecological wisdom. This study employs a multi-model
integration approach using artificial intelligence to evaluate the ecological suitability of 413 traditional village sites in Jiangxi
Province. It identifies key influencing factors and analyzes the ecological wisdom of ancestral site selection, resulting in an
ecological suitability evaluation map for traditional village locations in Jiangxi Province. The study is based on environmental
characteristic data of Jiangxi Province, including topography, climate, habitat quality, land use, air quality, vegetation cover, and
river network density. GIS is used for spatial analysis and result visualization, and raster data are extracted and standardized.
Machine learning methods such as Random Forest, Support Vector Machine, and Gradient Boosting Decision Trees, as well as
deep learning methods such as Convolutional Neural Networks and Multilayer Perceptrons, are applied. Multi-model integration
techniques are used to combine the predictions of various models, enhancing the accuracy and robustness of the ecological
suitability evaluation. Experimental results indicate that elevation, slope, habitat quality, actual distance to water bodies, and
average temperature are the main influencing factors for village site selection. The multi-model integration method performs
excellently in evaluating ecological suitability, effectively identifying key ecological factors. The model’s accuracy and reliability
are verified through confusion matrix, feature importance analysis, and ROC curve. This study evaluates the ecological
suitability of traditional village sites in Jiangxi Province using a multi-model integration approach. By analyzing the impact
weights of various ecological factors, it constructs a Composite Suitability Index (CSI) and generates an ecological suitability
evaluation map, displaying suitability levels. This provides a scientific basis for the protection and rational development of
traditional villages and serves as a reference for ecological site selection studies in other regions.
Rising Prevalence of Parent-Reported Learning Disabilities among U.S. Children and Adolescents Aged 6-17 years: NSCH, 2016-2022
Authors: Xu Chan , Li Yanmei , Yu Huijuan , Li Qishan , Liang Yingyu , Zhou Kefan , Li Qian , Yu Xinping , Zeng Xia , Qu Yabin , Yang Wenhan 
Published: August 2024

Abstract

The prevalence of learning disabilities (LD) among children is a critical public health issue; however, recent LD prevalence estimates among children and adolescents aged 6–17 years, as reported by the National Survey of Children’s Health (NSCH), remain largely unexplored. Data for this population-based cross-sectional study were obtained from NSCH to estimate the prevalence of LD diagnosis among U.S. children at both national and state levels, and to inspect the 7-year trends in these estimates from 2016 to 2022. Among 187,805 U.S. children, 17,379 had a history of LD diagnosis, with a weighted prevalence of 8.80% (95% CI = 8.52–9.08). Of these, 16,221 were currently diagnosed with LD, yielding a weighted prevalence of 8.20% (95% CI = 7.93–8.48). From 2016 to 2022, the prevalence of ever-diagnosed LD increased from 7.86–9.45%, and that of current-diagnosed LD from 7.32–8.80%, indicating a 20% total increase in both types. The state with the highest prevalence (New Hampshire) had twice that of the state with the lowest prevalence (Utah). This study highlights a critical escalation in LD prevalence among US children and adolescents between 2016 and 2022. Comprehensive screening and support programs must be implemented to enhance early identification and intervention.
Assessing the Effects of Long-COVID on Mental Health in the United States: A Population Based Study
Authors: Datta Anusua 
Published: August 2024

Abstract

Background
The term long-COVID is commonly used to refer to protracted symptoms following COVID-19 infection that persist beyond four weeks from onset. Long-COVID conditions have been associated with reduced quality of life. This study estimates the impact of long-COVID on anxiety and depression in the US, using survey data from nearly a million Americans.
Methods
The Household Pulse Survey, provides the first population based nationally representative data on the prevalence of long-COVID, starting with the survey’s June 2022 wave. A population-based survey allows us to conduct counterfactual research using control groups. Difference-in-differences models are applied to predict anxiety and depression in the population that contracted COVID-19 and had symptoms of long-COVID vis-à-vis control groups.
Results
Nearly 51.8% of those surveyed reported testing positive for COVID-19 and of these 27.3% reported suffering from long-COVID. Anxiety and depression rates were twice as high in those with long-COVID. Our sub-group analysis reveals that in general COVID-19 is associated with higher rates of anxiety and depression among younger adults and females, and those on the lower income and education scale. Whites, Blacks and Hispanics had higher odds of anxiety and depression symptoms compared to Asians in both the COVID-19 and long-COVID groups. Interestingly, long-COVID was associated with more negative mental health outcomes among males, where reported mortality rates were higher.
Conclusion
This study fills a significant gap in the literature on the mental health effects of long-COVID. Our results, based on a large population level data, point to a significant association between COVID-19, especially long-COVID, and cognitive impairment and mental health problems
Exploring the trends of Urban Scale and Urban Vitality on S&amp;D Balance in the Yangtze River Delta, China from 2015 to 2025
Authors: Wang Ke , Chen Qiuxiao 
Published: August 2024

Abstract

Analysis of the spatiotemporal trends of urban scale and urban vitality on ecosystem services balance provides an essential basis for regional sustainable development. Based on multi-source big data, the actual levels of urban scale and urban vitality of Yangtze River Delta, China are constructed, solving the previous problem that statistical datasets cannot fully demonstrate the real-time and real scope of the scale and vitality. Moreover, the article develops an integrated quantitative and strategic research system including spatiotemporal correlation, predictive scenario simulation and importance-performance analysis. Results show that urban vitality increases ESs demand without hurting ESs supply, as seen by its favorable impact on the S&D ratio. On the other hand, because cities occupy resources and seize land, they reduce the availability of ESs. Second, the economic priority scenario had the greatest influence on the S&D ratio, reaching -37.5%. This resulted in Zhejiang Province's S&D value approaching 1 (the lowest S&D value being 2.044). In Anhui, Jiangsu Province, and Shanghai, the ecological priority scenario had the most impact on the S&D ratio, raising the S&D value to 0.58~1.057. Third, although urban scale and ecological priority scenarios balance S&D by enhancing ESs supply in northeastern YRD, urban vitality and economic priority scenarios complement each other by improving ESs demand in southwest YRD.
It is safe to use the ulnar length difference to correct the radial length difference in the 3D-planning process of a radius osteotomy in patients with a distal radius malunion
Authors: Smees Camiel J , Nijhuis Koen D Oude , Heide Stein van der , Heuvel Judith olde , Doornberg Job N , Vochteloo Anne J H , Tuijthof Gabriëlle J M 
Published: August 2024

Abstract

Background
A corrective radius osteotomy is often performed in patients with a symptomatic distal radius malunion. In 3D-planned osteotomies, the unaffected radius is mirrored over the malunited radius after adjusting for left-right length differences using both ulnae. This approach assumes that ulnar length differences in a malunion population are similar to those in a healthy population. This study was conducted to analyze the difference in ulnar length in a distal radius malunion population and to assess the potential influence of age, sex, or malunion side on this difference.
Methods
We evaluated 65 adult patients with distal radius malunion using bilateral forearm CT scans. 3D models of both ulnae were constructed, and length differences were determined along a standardized length axis. The results were compared to two populations without a radius malunion.
Results
The average absolute ulnar length difference was 2.57 mm (SD 1.81), which was comparable to the two healthy populations. This difference was not significantly affected by age, sex, or malunion side.
Conclusion
This study demonstrated that using the ulnar length difference to correct for radial length difference in the current 3D planning process, before using the contralateral radius as a template for a corrective osteotomy in patients with radius malunion, is safe.
Construction and characterization of chimeric FcγR T cells for universal T cell therapy
Authors: Zhao Juanjuan , Chen Manling , Li Xudong , Chen Zhaoqi , Li Wei , Guo Rongqun , Wang Min , Jiang Zhongxing , Song Yongping , Wang Jianxiang , Liu Delong 
Published: August 2024

Abstract

Background Several approaches are being explored for engineering off-the-shelf chimeric antigen receptor (CAR) T cells. In this study, we engineered chimeric Fcγ receptor (FcγR) T cells and tested their potential as a versatile platform for universal T cell therapy.
Methods Chimeric FcγR (CFR) constructs were generated using three distinct forms of FcγR, namely CD16A, CD32A, and CD64. The functionality of CFR T cells was evaluated through degranulation assays, specific target lysis experiments, in vitro cytokine production analysis, and assessment of tumor xenograft destruction specificity in mouse models using different monoclonal antibodies (MoAbs).
Results Three types of CFR T cells were engineered, 16s3, 32-8a, 64-8a CFR T cells. In the presence of rituximab (RTX), cytotoxicity of all three types of CFR T cells against CD20+ Raji-wt, K562-CD20+, and primary tumor cells was significantly higher than that of the mock T cells (P < 0.001). When herceptin was used, all three types of CFR T cells exhibited significant cytotoxicity against HER2+ cell lines of SK-BR-3, SK-OV-3, and HCC1954 (P < 0.001). The cytotoxicity of 64-8a CFR T cells was significantly inhibited by free human IgG at a physiological dose (P < 0.001), which was not observed in 16s3, 32-8a CFR T cells. Compared to 32-8a CFR T cells, 16s3 CFR T cells exhibited more prolonged cytotoxicity than 32-8a CFR T cells (P < 0.01).
In in vivo assays using xenograft models, 16s3 CFR T cells significantly prolonged the survival of mice xenografted with Raji-wt cells in the presence of RTX (P < 0.001), and effectively reduced tumor burden in mice xenografted with SK-OV-3 cells in the presence of herceptin (P < 0.05). No significant non-specific cytotoxicity of CFR T cells was found in vivo.
Conclusion The anti-tumor effects of the CFR T cells in vitro and in xenograft mouse models are mediated by specific MoAbs such as RTX and herceptin. The CFR T cells therefore have the features of universal T cells with specificity directed by MoAbs. 16s3 CFR T cells are chosen for clinical trials.
A GFP-GAN based method for improving clarity of license plate images
Authors: Huang Tianyun , Wei Jinxu 
Published: August 2024

Abstract

License plate recognition is a very important component of intelligent transportation system, and its accuracy and speed affect the operation of the entire system. However, it is still difficult to achieve high accuracy in license plate positioning and character recognition for low-quality license plate images. To migrate the GFP-GAN model from blind face reconstruction to license plate image restoration, we made contributions to improve the clarity of license plate images in three aspects: (1). add motion blur present commonly on license plate images rather than facial images; (2). add the license plate recognition loss during training to increase the network's ability to recover correct characters; (3). align the region discriminator to the license plate position to optimize the region recovery effect. As in GFP-GAN, the multi-scale semantic information of low-quality license plate image is extracted by U-Net (extractor), and converted to coding that controls the image content (encoder), then the coding is input to a pre-trained StyleGAN2 network to generate the corresponding high quality license plate image (generator/decoder). The migrated model, datasets requirement and preparation, training process and algorithms are given in detail. As compared with existing methods, the experiments show that our method can significantly improve the accuracy on license plate recognition, with advantages of strong adaptability to various type of blurs, fine and smooth restoration quality, prominent emphasis on license plate area.
The complex kinematics of the young stars orbiting the SMBH in the Galactic center can be explained by an intermediate-mass companion of Sgr A★
Authors: Wang Long , Zheng Xiaochen , Lin Douglas , Burkert Andreas , Mao Shude 
Published: August 2024

Abstract

The inner parsec of the supermassive black hole (SMBH) in the center of the Milky Way, Sgr A★, contains a cluster of several hundred young, massive stars. Their complex, highly structured kinematics poses an intriguing conundrum on their origin within the strong tidal field close to the SMBH. It has been suggested that the encounter of a gas cloud with the SMBH could produce a fast rotating disk of coeval, massive stars. This result however differs strongly from the observed multi-component orbital distribution. We demonstrate that star-star scattering within the disk can only weakly change their orbits and cannot explain the observations, even if one includes the dispersal of an additional gaseous disk component. Including however the gravitational interaction with a putative intermediate-mass companion (IMC) of Sgr A$^\star$, possibly an intermediate mass black hole, naturally scatters the stars into their current kinematic configuration on timescales consistent with their stellar ages.
Impact of Genetic Ancestry on T-cell Acute Lymphoblastic Leukemia Outcomes
Authors: Teachey David , Newman Haley , Lee Shawn , Pölönen Petri , Shraim Rawan , Li Yimei , Liu Hongyan , Aplenc Richard , Bandyopadhyay Shovik , Chen Changya , Chen Zhiguo , Devidas Meenakshi , Diorio Caroline , Dunsmore Kimberly , Elghawy Omar , Elhachimi Amira , Fuller Tori , Gupta Sumit , Hall Junior , Hughes Andrew , Hunger Stephen , Loh Mignon , Martinez Zachary , McCoy Michael , Mullen Cassidy , Pounds Stanley , Raetz Elizabeth , Ryan Theresa , Seffernick Anna , Shi Gongping , Sussman Jonathan , Tan Kai , Uppuluri Lahari , Vincent Tiffaney L , Wang'ondu Ruth , Winestone Lena , Winter Stuart , Wood Brent , Wu Gang , Xu Jason , Yang Wenjian , Mullighan Charles , Yang Jun , Bona Kira 
Published: August 2024

Abstract

The influence of genetic ancestry on biology, survival outcomes, and risk stratification in T-cell Acute Lymphoblastic Leukemia (T-ALL) has not been explored. Genetic ancestry was genomically-derived from DNA-based single nucleotide polymorphisms in children and young adults with T-ALL treated on Children’s Oncology Group trial AALL0434. We determined associations of genetic ancestry, leukemia genomics and survival outcomes; co-primary outcomes were genomic subtype, pathway alteration, overall survival (OS), and event-free survival (EFS). Among 1309 patients, T-ALL molecular subtypes varied significantly by genetic ancestry, including increased frequency of genomically defined ETP-like, MLLT10, and BCL11B-activated subtypes in patients of African ancestry. In multivariable Cox models adjusting for high-risk subtype and pathways, patients of Admixed American ancestry had superior 5-year EFS/OS compared with European; EFS/OS for patients of African and European ancestry were similar. The prognostic value of five commonly altered T-ALL genes varied by ancestry – including NOTCH1, which was associated with superior OS for patients of European and Admixed American ancestry but non-prognostic among patients of African ancestry. Furthermore, a published five-gene risk classifier accurately risk stratified patients of European ancestry, but misclassified patients of African ancestry. We developed a penalized Cox model which successfully risk stratified patients across ancestries. Overall, 80% of patients had a genomic alteration in at least one gene with differential prognostic impact by genetic ancestry. T-ALL genomics and prognostic associations of genomic alterations vary by genetic ancestry. These data demonstrate the importance of incorporating genetic ancestry into analyses of tumor biology for risk classification algorithms.
Sequential Plasmodium Infections in Two Resident Families in Mangalore, India
Authors: MUKHI BENUDHAR 
Published: August 2024

Abstract

Eleven members of two resident families in Mangalore city suffered from Plasmodium falciparum, P. vivax and mixed infections of both parasites in a sequential manner despite using bed nets regularly. Malarial symptoms of febrile illness started with chills and rigors at the schools for children and at work places for adult members. Five members of first family are from the central part of the city, and six members in the second family reside ∼10 km away from the central city, their live locations as well as community health care (CHC) center were mapped using QGIS software, respectively. Interestingly, first infection started with P. falciparum followed by P. vivax in the first family. However, P. vivax appeared first in the second family followed by mixed infection, and the last infection was P. falciparum. Both the families reside in close proximities of construction sites, which correlate with the role of mosquito breeding sites and indoor biting in ongoing malaria transmission in the city.
Pain and sensory disorders after removal of mandibular third molars
Authors: Maximova M. Yu. , Suanova E. T. 
Published: August 2024

Introduction. Extraction of mandibular third molars is one of the most common oral surgical procedures.Aim. To evaluate the efficacy of B Complex Preparation on pain and sensory problems related to inferior alveolar nerve damage after surgical removal of mandibular third molars.Materials and methods. In the open-label comparative trial 86 patients aged 45 to 54 years with sensory disturbances, lasting 72 hours, after surgical removal of mandibular third molar were included. Pain intensity was assessed using a visual analogue scale (VAS). Quantitative sensory testing (QST) was performed with the computer-controlled Thermal Sensory Analyzer (TSA type II, Medoc Ltd., Ramat Yishai, Israel) with contact thermode (30 × 30 mm). Patients with inferior alveolar nerve damage were divided into 2 groups: the first group – 44 patients received the standart therapy in combination with B Complex Preparation for 30 days, in the second group 42 patients received the standart treatment.Results. After a course of treatment in the first group (B Complex Preparation) was determined the relieving of numbness and pain in 90.9% of patients with inferior alveolar nerve damage. The pain intensity in VAS reduced from 6.3 ± 0.9 to 0.8 ± 0.2 points (p = 0.02) in the first group and from 6.1 ± 0.6 to 4.8 ± 0.4 points (p = 0.09) in the second group. Only in the first group there was a decrease of the warm sensation threshold during QST, which additionally confirms the positive therapeutic effect of B Complex Preparation.Conclusion. Effectiveness of therapy with B Complex Preparation was noted in patients with algic manifistations and sensory disorders after the removal of the third molar.
Machine learning models for predicting water quality index: optimization and performance analysis for El Moghra, Egypt
Authors: Kamel Elshaarawy Mohamed , Eltarabily Mohamed Galal 
Published: August 2024

ABSTRACT

Assessing groundwater quality is vital for irrigation, but financial constraints in developing countries often result in infrequent sampling. This study comprehensively analyzes the groundwater quality of the El Moghra aquifer in Egypt's arid Western Desert, for its suitability for irrigation uses. Detailed hydrochemical analysis and advanced machine learning (ML) techniques, including geographic information systems, were employed to enhance spatial analysis and predictive accuracy. Various ML models, such as random forest, adaptive boosting, and extreme gradient boosting (XGBoost), were optimized using Bayesian optimization to predict the irrigation water quality index (IWQI) accurately. The evaluation incorporated visual and quantitative methods, alongside ranking analysis, to validate model effectiveness. Shapley Additive exPlanations feature importance analysis and a graphical user interface (GUI) model were developed based on the best predictive model. The results indicated that the groundwater quality is generally suitable for irrigation, with XGBoost showing the best performance, achieving a root mean square error of 5.602 and a determination coefficient (R²) of 0.872. Sodium concentration was identified as the most significant factor affecting the IWQI. The GUI facilitates easy prediction of IWQI, aiding agricultural water management and resource allocation within the region.