bluuebunny/crossref_metadata_2025_split huggingface dataset:
Peri-urbanisasi dan Perubahan Struktur Ruang Perkotaan di Kawasan Solo Baru
Authors: Wibowo Binandhita Rizky Genta , Rahayu Paramita , Kusumastuti Kusumastuti 
Published: June 2024

<p class="Abstract"><em><span lang="IN">Solo Baru merupakan kawasan fungsional yang secara administratif berada di Kecamatan Grogol, Kabupaten Sukoharjo. Perkembangan Solo Baru merupakan proses pemekaran dari Kota Surakarta ke wilayah peri-urbannya. Pembangunan Solo Baru digagas oleh developer yang dipengaruhi oleh keterbatasan lahan di Kota Surakarta. Rencana pengembangan Solo Baru sebagai kota satelit dimulai sejak tahun 1980. Solo Baru kemudian berkembang sebagai pusat bisnis ditandai dengan tumbuhnya aktivitas perdagangan jasa seperti supermarket, hotel, mal, dan aktivitas ekonomi lainnya, yang kemudian membentuk suatu konsentrasi kegiatan baru yang mengarah pada perubahan struktur ruang di kawasan tersebut. Tujuan penelitian ini adalah untuk mengetahui bagaimana perubahan struktur ruang perkotaan pada proses peri-urbanisasi di Solo Baru. Penelitian ini menggunakan data time series yang terdiri dari tiga titik tahun data yaitu tahun 2000, 2011, dan 2020. Pendekatan yang digunakan dalam penelitian ini adalah pendekatan kuantitatif dengan jenis penelitian deskriptif menggunakan teknik analisis statistika deskriptif, dan analisis spasial dengan Sistem Informasi Geografis (SIG). Hasil analisis menunjukkan bahwa secara keseluruhan proses peri-urbanisasi di Solo Baru menyebabkan perubahan secara fisik maupun nonfisik yang merubah struktur ruang di kawasan. Struktur ruang di kawasan Solo Baru menunjukkan perubahan sejak tahun 2000-2020 meskipun pada dasarnya berbentuk pusat kegiatan banyak. Pada tahun 2000, model struktur ruang di kawasan Solo Baru berbentuk noncentered yang terdiri dari pusat-pusat kecil yang saling berhubungan satu sama lain. Pada tahun 2011, model struktur ruang di kawasan Solo Baru berubah menjadi memiliki satu pusat utama dan beberapa subpusat pelayanan. Pada tahun 2020, satu pusat utama tersebut semakin berkembang, diikuti oleh adanya beberapa pusat dan subpusat pelayanan yang saling terhubung satu sama lain. Selain itu, pengaruh aksesibilitas kawasan Solo Baru dengan Kota Surakarta terlihat mempengaruhi terbentuknya pusat dominan tersebut.</span></em></p>
Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning
Authors: Chang Chia-en , Ruzmetov Talant , Hung Ta I , Jonnalagedda Saisri Padmaja , Chen Si-han , Fasihianifard Parisa , Guo Zhefeng , Bhanu Bir 
Published: June 2024

Abstract

Proteins are inherently dynamic, and their conformational ensembles are functionally important in biology. Large-scale motions may govern protein structure–function relationship, and numerous transient but stable conformations of intrinsically disordered proteins (IDPs) can play a crucial role in biological function. Investigating conformational ensembles to understand regulations and disease-related aggregations of IDPs is challenging both experimentally and computationally. In this paper first an unsupervised deep learning-based model, termed Internal Coordinate Net (ICoN), is developed that learns the physical principles of conformational changes from molecular dynamics (MD) simulation data. Second, interpolating data points in the learned latent space are selected that rapidly identify novel synthetic conformations with sophisticated and large-scale sidechains and backbone arrangements. Third, with the highly dynamic amyloid-β1-42 (Aβ42) monomer, our deep learning model provided a comprehensive sampling of Aβ42’s conformational landscape. Analysis of these synthetic conformations revealed conformational clusters that can be used to rationalize experimental findings. Additionally, the method can identify novel conformations with important interactions in atomistic details that are not included in the training data. New synthetic conformations showed distinct sidechain rearrangements that are probed by our EPR and amino acid substitution studies. The proposed approach is highly transferable and can be used for any available data for training. The work also demonstrated the ability for deep learning to utilize learned natural atomistic motions in protein conformation sampling.
Structural Pattern of Emotional Schemas with Adolescents' Self-Injury Behavior Based on Mediating Role of Cognitive Emotion Regulation Strategies
Authors: Manesh Soudabeh Ershadi , Nejad Farzaneh Ghorbani , Moosivand Mahboobeh , Zaremohzzabieh Zeinab , Kulemarzi Mohammad Javad Bagian 
Published: June 2024

Abstract

Non-suicidal self-injury is a common mental health threat among adolescents. This study aimed to investigate the structural relationships between emotional schemas and adolescents' self-injury behavior based on the mediating role of cognitive emotion regulation strategies. The study employed a cross-sectional design, with the statistical population consisting of second high school students in Tehran during the school year of 2022–2023. In this study, 316 students were selected through multistage cluster sampling. Data were collected using a non-suicidal self-injury behavior questionnaire, emotional schemas, and cognitive emotion regulation strategies. Structural Equation Modeling (SEM) in AMOS version 26 was utilized to evaluate the proposed model. The findings indicate that the proposed model fits the data. The results of SEM showed that adaptive emotional schemas have a direct and negative effect on adolescents' self-injury. Additionally, adaptive emotional schemas have an indirect positive effect through maladaptive cognitive emotion regulation and a negative indirect effect through adaptive cognitive emotion regulation on adolescents' self-injury. Moving forward, this study provides an account of cumulative knowledge for addressing the issue of non-suicidal self-injury in Iranian adolescents and may inform future prevention and intervention strategies.
Increased chemosensitivity of IDH1-mutated gliomas due to impairment of RPA1-mediated DNA repair
Authors: Li Zhiqiang , Wang Danwen , Yu Donghu , Li Xinyi , Tang Feng , Wang Zefen 
Published: June 2024

Abstract

Isocitrate dehydrogenase 1 (IDH1) mutation, resulting in the expression of mutant IDH1 (mIDH1), is the most common genetic abnormality in low-grade gliomas and is recognized as a biological marker for better patient prognosis and a robust response to temozolomide (TMZ). To investigate the possible mechanisms of chemosensitivity differences between wild-type (WT) IDH1 and IDH1-mutated gliomas, we conducted immunoprecipitation–mass spectrometry (IP-MS) and coimmunoprecipitation (co-IP) in glioma cells expressing wild-type IDH1 and mIDH1 to identify the specific protein that directly interacts with mIDH1, namely, replication protein A1 (RPA1). Increased expression of RPA1 was significantly associated with low TMZ responsiveness and worse prognosis. Subsequently, we demonstrated that overexpression of RPA1, an essential functional factor in DNA damage repair (DDR), increased TMZ resistance in glioma cells, while treatment with an RPA1 inhibitor (HAMNO) sensitized glioma cells to TMZ both in vitro and in vivo. Moreover, TMZ induced a greater degree of general DNA damage in glioma cells coexpressing mIDH1 and RPA1 than in those coexpressing wild-type IDH1 and RPA1, indicating RPA1 dysfunction in IDH1-mutant glioma cells. Further, mIDH1 directly bound to the DNA binding domain (DBD-A) of RPA1 and then suppressed its binding to single-stranded DNA (ssDNA), consequently leading to blockade of the downstream ATR/CHK1 DNA repair signalling pathway, failure of DNA repair and apoptosis. Taken together, our findings reveal a novel molecular mechanism involved in the chemosensitivity of IDH-mutated gliomas and suggest that targeting RPA1-related DNA repair is a promising therapeutic strategy to increase the TMZ response of IDH1-mutant gliomas. Moreover, the combination of TMZ and (1Z)-1-[(2-hydroxyanilino)methylidene] naphthalen-2-one (HAMNO) may be a clinically effective treatment strategy.
Investigation of the quality characteristics of two varieties of aromatic tobacco leaves utilizing metagenomics and non-targeted metabolomics methodologies
Authors: Wei Jinbin , Zhang Jiandong , Song Kai , Zang Zhipeng , Yang Hongjing , Gao Yuzhen , Wang Zhen , Liu Chen 
Published: June 2024

Abstract

Background
During the fermentation process of tobacco leaves, microorganisms play a vital role in producing various aroma components that significantly influence the flavor of tobacco. Different types of microorganisms with specific functions contribute distinct aroma characteristics to tobacco leaves.
Methods
This study investigates the microbial profiles of light-flavored and strong-flavored tobacco leaves, utilizing Yuxi in Yunnan Province as a representative of light-flavored leaves and Yongzhou in Hunan Province for strong-flavored leaves. Using metagenomic technology, we aim to identify the core functional microorganisms present in these representative tobacco leaf types. In addition, non-targeted metabolomics is employed to identify metabolic differences between the two types of tobacco leaves.
Results
The predominant microorganisms in tobacco leaves consist of Pseudomonas, Sphingomonas, Methylobacterium, Pantoea, Methylorubrum, Aureimonas, Acinetobacter, Enterobacter, Stenotrophomonas, and Xanthomonas. Species difference analysis revealed significant divergences at the genus level between Yunnan (YN) and Hunan (HN) samples, implying that these microbial variances may influence the development of distinct flavors. Examination of the tobacco leaf microbiome through KEGG and CAZymes functional annotations exposed carbohydrate and amino acid metabolism as primary features, with glycoside hydrolases (GH), glycosyl transferases (GT), and carbohydrate esterases (CE) as the key enzymes. Correlation analysis between species and functions in the two tobacco leaf samples showed a notable positive relationship among Pseudomonas, Pantoea, Sphingomonas, and Methylobacterium genera in KEGG carbohydrate and amino acid metabolism functions, and CAZymes GH, CE, and AA annotations, suggesting their significant involvement in the chemical breakdown of tobacco leaves and their potential role in enhancing tobacco quality. Non-targeted metabolomic analysis identified 157 volatile and 648 non-volatile metabolites that differ between Yunnan (YN) and Hunan (HN) samples, indicating potential differences in tobacco styles.
Conclusion
This study provides a theoretical basis for guiding tobacco fermentation and has certain enlightening effects on reducing harmful substances during the fermentation process of tobacco leaves. Therefore, further research on tobacco microbiota will focus on these genera.
Study on finite element modeling method of oral soft and hard tissues based on CBCT images and digital scanning technology
Authors: Tang Ruize , Cui Qing , Ren Shuo , Unurjargal Khadbaatar , Li Jingxu 
Published: June 2024

Abstract

Objective
To study an accurate, efficient, and fast method for creating a three-dimensional finite element model using a combination of oral soft and hard tissue images obtained from various field of view CBCT scans and intra-oral 3D scan.
METHODS
An adult female volunteer was selected, and the mandible was scanned using two different field of view CBCT scans, the resulting images were imported into Mimics, Blue Sky Bio, and 3-Matic software using DICOM format, then it was used to create models of the teeth, periodontal ligament, and mandible bone, respectively. The oral soft tissues and dental arch were scanned using an intra-oral digital scanner. The obtained scans were processed using Geomagic and 3-Matic software to create a gingival model. The created model was meshed, and a three-dimensional finite element model consisting of a tetrahedral mesh was generated.
RESULTS
A comprehensive finite element model consisting of the mandible, dental arch, periodontal ligament, and gingiva was established. The model comprised a total of 222,873 nodes, with the following distribution: 892,871, 40,358, 405,043 and 234,224 for the mandible bone, periodontal ligament, teeth and gingiva, respectively.
CONCLUSION
The modeling method based on different field of view CBCT scans and Intra-oral scan can establish a comprehensive finite element model of the mandible bone and gingiva, which is more accurate, faster, and has a wide range of applicability.
Spatiotemporal prediction of landslide deformation based on temporal graph convolutional networks
Authors: Ma Juan , Yao Leihua , Deng Lizheng , Yang Qiang , Chen Yao , Ouyang Chengyu 
Published: June 2024

Abstract

The displacement-time curves of landslides accurately reflect their movement status. Precise prediction of landslide deformation is the key to successful early warning. Machine-learning techniques have been used to predict the deformation of individual landslide monitoring points with desirable results. However, previous studies have not considered the spatial correlation between the monitoring points arranged in the horizontal and vertical profiles. Based on the deep learning model of a temporal graph convolutional network (T-GCN), a feasible solution was provided to accurately predict the overall deformation of landslides. To capture spatial and temporal correlations simultaneously, this study proposed a T-GCN spatiotemporal prediction method that considers the temporal correlation effects of the external factors inducing landslide deformation and generates comprehensive prediction results. The model combines the characteristics of a graph convolutional network (GCN) and gated recurrent unit (GRU). The GCN was used to determine the spatial correlations between landslide monitoring points, whereas the GRU was used to capture dynamic changes in displacement over time. The T-GCN model was then applied to predict the spatiotemporal deformation of the Dawuchang landslide in the Three Gorges Reservoir area. The experimental results demonstrate that the T-GCN model provides a novel solution for spatiotemporal deformation prediction of landslides and can effectively predict the overall displacement of landslides.
Neural Phase Picker Trained on the Japan Meteorological Agency Unified Earthquake Catalog
Authors: Naoi Makoto , Tamaribuchi Koji , Shimojo Kengo , Katoh Shinya , Ohyanagi Shukei 
Published: June 2024

Abstract

In Japan, one of the most seismically active nations, seismic data from various institutions are shared in real-time and made accessible via the web, which facilitates research by numerous scholars. The Japan Meteorological Agency (JMA), in collaboration with the Ministry of Education, Culture, Sports, Science, and Technology (MEXT), processes these data to compile a “unified earthquake catalog.” This catalog is crucial for developing disaster prevention strategies and significantly enhances societal safety. To facilitate the efficient development of high-quality seismic catalogs from this data, we retrained a deep-learning phase picker, known as a neural phase picker, which has gained prominence in recent years. This retraining was based on manual arrival time measurements provided by the JMA. We utilized the PhaseNet architecture for our model and trained it using 6.1 million three-component seismic waveforms collected between 2014 and 2021. When the original PhaseNet model, which was trained with data from California, was applied to routine Japanese data, its performance was suboptimal, especially with ocean-bottom seismometer records. However, retraining the model with the JMA-unified catalogs and corresponding waveforms significantly enhanced its performance in reading arrival times of natural and low-frequency earthquakes. The retrained model reduced its dependency on the types of stations that were monitored when applying the original PhaseNet and displayed improved performance for waveforms even from stations not included in the training dataset. The performance of the model varied with earthquake magnitude, which highlights the reliance on extensive data on small events in the training set. When integrated into the automatic processing used in the routine operation of the JMA, the model identified a larger number of events, especially smaller ones with undetermined magnitudes, compared to the events recorded by the conventional procedure. Furthermore, leveraging approximately ten times more training data than the California study, we developed and trained PhaseNetWC, which is a model with greater expressiveness than the original PhaseNet. This new model surpassed the performance of its predecessor. The publication and dissemination of these models are anticipated to enhance the analysis of routine observational datasets in Japan.
Development of a framework for comprehensive oral health services provision to the Iranian older people
Authors: Azami-Aghdash Saber , Rastkar-Gharamaleki Shima , Pournaghi-Azar Fatemeh , Poorhashemi-Ardakani SM Hossein 
Published: June 2024

Abstract

Background: The older people faces many Oral Health (OH) problems which have wide range of detrimental effects on their life from different aspects. Countries need to have an effective framework to deal with these problems. Therefore, the aim of this study was to develop an effective framework to provide Comprehensive Oral Health Services (COHS) for the Iranian older people.
Methods: First, a scoping review was done. In the second phase of the study, the viewpoints of 11 experts and service providers were collected through semi-structured interviews. Afterward, a panel of experts was held for designing COHS framework. Finally, a modified Delphi method was used to validate the designed framework.
Results: The designed framework including seven main areas 1) the necessity of COHS 2) the process of providing COHS at different levels of service provision 3) the service package in each level of service provision and the composition of human resources required for them; 4) financing; 5) services providing assessment; 6) the role of organizations and communications to improve the OH and 7) Structures, policies and strategies for improving the OH older people.
Conclusion: The designed framework in this study can be used as an effective policy/approach to policymakers so as to provide a roadmap for improving the OH status of the older people.
Competitive Demands during International Sprint-Distance Triathlon Races according to the Circuit Type: Cycling Influence on the Subsequent Running Performance.
Authors: Espejo Raúl , Martínez-Sobrino Jesús , Veiga Santiago 
Published: June 2024

Abstract

Background. Despite the quantitative importance of the cycling segment in Sprint-Distance Triathlon (SDT), very few studies reported the power output of elite triathletes during races. The aim of this study was to analyse the competitive demands of elite triathletes during the cycling segment of SDT races and their influence on the subsequent running segment performance, considering the different types of race circuits.
Methods. Power variables during the cycling segment as well as the running performance metrics during 82 SDT races organised by World Triathlon (68 Continental Cups and Championships, 12 World Cups and 2 World Triathlon Series) were analysed in 10 male and 7 female U23 participants.
Results. The mean power output (MP) values for males, the number of power peaks (Peak 1 for males and Peak 2 for both genders) and the % of race time spent in high power bands increased as circuits presented a greater technical difficulty. Males spent more % of race time in the low (< 2W/kg) and high (> 6W/kg) but less % of time in the medium (2–6 W/kg) relative power bands than females (p < 0.05). Time spent in medium-high power bands showed large correlation with running ranking, both for males on rolling (r = 0.62) and technical (r = 0.55) courses and for females on rolling courses (r = 0.52).
Conclusions. The competitive demands of the cycling segment during SDT races seem to be dependent on the circuit type and should be taken into account to optimise the subsequent running performance.
Valence or semantic: The role of ambivalence on subjective well- being between cultures and within cultures
Authors: Chen Dian , Liu Ying , Guo Yiting , Zhang Yulin 
Published: June 2024

Abstract

This study explores the impact of two types of self-concept ambivalence—valence ambivalence and semantic ambivalence—on individuals’ subjective well-being. It aims to address why individuals in Eastern cultures, despite their tolerance for inconsistencies and contradictions in their self-concept, often report lower levels of subjective well-being. The results show a significant negative correlation between valence ambivalent self-concept and subjective well-being, while semantic ambivalent self-concept is associated with cognitive flexibility and positively predict subjective well-being. Additionally, the study finds that Chinese participants generally score higher on valence ambivalent self-concept than American participants, but no significant differences are observed in semantic ambivalent self-concept. The research emphasizes the importance of understanding and resolving ambivalent self-concepts for enhancing individuals’ subjective well-being and reveals the role of cultural differences in the relationship between ambivalent self-concept and subjective well-being.
Characteristics of the Integration Sites and Structures of the Tn916 and Its Family
Authors: Song Lei , Duan Jingxiu , Liu Tianren , Sun Jiaojiao 
Published: June 2024

Abstract

Tn916, the most typical conjugative transposon carrying the tetM resistance gene, has been identified in a wide range of genomes. This study utilized the sequence identity of the Tn916 internal integrase in Enterococcus faecalis DS16 to recognize Tn916 (with an identity of > 90%) and Tn916 family members (with identity between 60%-90%) in all currently complete genomes and chromosomes, naming them Tn916.1- Tn916.9, respectively. Tn916 and its family members have similar structures: AT-rich inverted repeats (IRs), with boundaries being AT-rich stem-loop structures; the coupling sequences in the middle are often 5 bp AT-rich regions, and their conserved base being the first base A or the last base T; the stem sequence from the host often matches or complement part of the IR (4 or 5bp). Most Tn916 family members have the ABC gene cluster as their resistance marker gene, and Tn916.7 has vancomycin resistance. Tn916 and its family integrate into genomes which have lower GC% more frequently. Our research revealed the flanking structure characteristics of Tn916 and its family, laying a molecular foundation for further determining their deletion and integration mechanisms, and aiding in controlling the spread of such antibiotic resistance in these conjugative transposons.