Research Progress on Information Model of Urban Green Space by Wei ZHANG, Yahan YAN

“…In terms of assessment and analysis, given the increasingly complex development trends of urban fabric, traditional two-dimensional assessment methods cannot meet the needs of complex green space evaluation. By establishing evaluation methods, green space information models can be applied to different practical needs: Calculation of three-dimensional green volume indicators, analysis of three-dimensional landscape patterns, and evaluation of three-dimensional spatial ecosystem services.ConclusionBased on the requirements for green space information modeling, a corresponding construction framework can be established, including data acquisition, composition structure, detail level, spatial scale, sharing platform and analysis application of green space information models. …”
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Understanding discrepancies in soil moisture from SMAP and AMSR2: insights into performance and dry-down behavior by Zhiqing Peng, Tianjie Zhao, Jiancheng Shi, Lu Hu, Thomas J. Jackson, Michael H. Cosh, Hui Lu, Xiaodong Gao, Jingyao Zheng, Panpan Yao, Qian Cui, Peng Guo, Peilin Song, Zushuai Wei, Mengjia Wang, Anmin Fu

“…The satellite-derived SM data are evaluated and compared using 40 globally distributed SM observation networks at both regional (dense network) and grid scales. …”
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Woody legacies of railroad ties from the Southern Atacama Desert used to strengthen Nothofagus obliqua tree-ring chronologies from Northern Patagonia by Isadora Schneider-Valenzuela, Ariel A. Muñoz, Duncan A. Christie, Karin Klock-Barría, María Eugenia Solari, Marcelo Madariaga-Burgos, Rocío Urrutia-Jalabert, Isabella Aguilera-Betti, Santiago Ancapichún, Alejandro Venegas-González, Mauro E. González

“…The large-scale manufacturing of railroad ties distributed across Chile drove part of this exploitation. This study evaluated the use of this cultural material from abandoned tracks preserved in the southern Atacama Desert to strengthen the existing N. obliqua tree-ring network in Patagonia. …”
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Psychometric properties of the Dating Violence Questionnaire for Victimization and Perpetration (DVQ-VP) in Ecuadorian population by Andrés Ramírez, Luis Burgos-Benavides, Javier Herrero Díez, Hugo Sinchi-Sinchi, Alhena L. Alfaro-Urquiola, Venus Medina-Maldonado, Francisco Javier Rodríguez-Díaz

“…Additionally, a network analysis was conducted with the DVQ-VP items. …”
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TOM40 as a prognostic oncogene for oral squamous cell carcinoma prognosis by Lifei Deng, Hong Ran, Dunhui Yang, Zhen Wang, Peng Zhao, Hengjie Huang, Yongjin Wu, Peng Zhang

“…The immune infiltration pattern in OSCC was analyzed in the TCGA-OSCC cohort using the CIBERSORT algorithm. …”
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Expression of pathogenesis-related proteins in potato brown rot plants confers resistance to filamentous pathogens under field trials by Hanaa S. Omar, Mohamed H. Hagag, Dina El-Khishin, Mona Hashem

“…The DGGE uses 16 srRNA primers that were used to compare two extreme patterns for identifying the microbial population detected in environmental samples. …”
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Deep learning helps discriminate between autoimmune hepatitis and primary biliary cholangitis by Alessio Gerussi, Oliver Lester Saldanha, Giorgio Cazzaniga, Damiano Verda, Zunamys I. Carrero, Bastian Engel, Richard Taubert, Francesca Bolis, Laura Cristoferi, Federica Malinverno, Francesca Colapietro, Reha Akpinar, Luca Di Tommaso, Luigi Terracciano, Ana Lleo, Mauro Viganó, Cristina Rigamonti, Daniela Cabibi, Vincenza Calvaruso, Fabio Gibilisco, Nicoló Caldonazzi, Alessandro Valentino, Stefano Ceola, Valentina Canini, Eugenia Nofit, Marco Muselli, Julien Calderaro, Dina Tiniakos, Vincenzo L’Imperio, Fabio Pagni, Nicola Zucchini, Pietro Invernizzi, Marco Carbone, Jakob Nikolas Kather

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Mouse SPAG6L, a Key Cytoskeleton Modulator Essential for Male Germ Cell Development, Is Not Required for Sertoli Cell Function by Tao Li, Wei Li, Cheng Zheng, Jannette M. Dufour, William H. Walker, Shuiqiao Yuan, Zhibing Zhang

“…Since SPAG6L decorates microtubules and modulates cytoskeleton function, and Sertoli cells have a well-developed microtubule transport network, the potential function of SPAG6L in Sertoli cells was evaluated. …”
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Kidney Ensemble-Net: Enhancing Renal Carcinoma Detection Through Probabilistic Feature Selection and Ensemble Learning by Zaib Akram, Kashif Munir, Muhammad Usama Tanveer, Atiq Ur Rehman, Amine Bermak

“…Our approach begins by acquiring spatial features from contrast-enhanced images using a Convolutional Neural Network (CNN) effectively capturing intricate patterns and structures characteristic of different carcinoma subtypes. …”
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Hybrid deep learning framework for real-time DO prediction in aquaculture by Longqin Xu, Wenjun Liu, Cai Chengqing, Tonglai Liu, Xuekai Gao, Ferdous Sohel, Murtaza Hasan, Mansour Ghorbanpour, Shahbaz Gul Hassan, Shuangyin Liu

“…However, off-the-shelf models, such as Random Forest (RF) and Back Propagation (BP) have demonstrated poor performance due to intricate interactions in aquatic ecosystems, which leads to complex data patterns. This study proposes a water quality estimation model by combining a convolutional neural network (CNN), self-attention (SA), and bidirectional simple recurrent unit (BiSRU). …”
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AudioProtoPNet: An interpretable deep learning model for bird sound classification by René Heinrich, Lukas Rauch, Bernhard Sick, Christoph Scholz

“…The classifier learns prototypical patterns of each bird species’ vocalizations from spectrograms of instances in the training data. …”
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SmartTrust: a hybrid deep learning framework for real-time threat detection in cloud environments using Zero-Trust Architecture by Umesh Kumar Lilhore, Sarita Simaiya, Roobaea Alroobaea, Abdullah M. Baqasah, Majed Alsafyani, Afnan Alhazmi, Md Monish Khan

“…SmartTrust integrates CNN, LSTM, and Transformer models to analyze spatial and temporal patterns in network traffic and user behaviours. Unlike conventional models, it leverages Reinforcement Learning to enable adaptive decision-making, allowing it to adjust responses based on real-time contextual signals dynamically. …”
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DeepGuard: real-time threat recognition using Golden Jackal optimization with deep learning model by Fatma S. Alrayes, Hamed Alqahtani, Wahida Mansouri, Asma Alshuhail, Wafa Sulaiman Almukadi, Ahmed Mahmud

“…The DeepGuard model uses long short-term memory neural networks (LSTM-NNs) for violence detection. The performance evaluation of the DeepGuard model takes place using benchmark datasets. …”
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ZO-1 boosts the in vitro self-renewal of pre-haematopoietic stem cells from OCT4-reprogrammed human hair follicle mesenchymal stem cells through cytoskeleton remodeling by Yingchun Ruan, Xingang Huang, Pengpeng Sun, Xiaozhen Yu, Xiaohua Tan, Yaolin Song, Hua Chen, Zhijing Liu

“…These intermediate cells exhibit gene expression patterns similar to pre-HSCs, making them promising for artificial haematopoiesis. …”
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In Silico Analysis of Dysregulated Genes and Drug Resistance in Epstein-Barr Virus Associated Gastric Cancer by Tabassom Sedaghat Anbouhi, Hossein Sazegar, Ebrahim Rahimi

“…Recognizing its complex and diverse nature, the cancer genome atlas (TCGA) research network has identified four distinct subtypes of GC. …”
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An IoT intrusion detection framework based on feature selection and large language models fine-tuning by Huan Ma, Wan Zhang, Dalong Zhang, Baozhan Chen

“…Abstract The rapid proliferation of Internet of Things (IoT) devices has significantly expanded the network attack surface, necessitating the deployment of advanced AI (artificial intelligence)-based intrusion detection systems (IDS) to bolster IoT security. …”
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BRD4 as the key lactylation related gene in heart failure identified through bioinformatics analysis by Kaiyuan Li, Lingyu Han, Xiaowen Wang, Zhipeng Zheng, Min Sha, Jun Ye, Li Zhu

“…Key LRGs implicated in HF were selected using the Least Absolute Shrinkage and Selection Operator (LASSO) and Weighted Gene Co-Expression Network Analysis (WGCNA). The diagnostic efficacy and biological significance of these genes were evaluated through receiver operating characteristic (ROC) curve analysis, Gene Set Enrichment Analysis, and immune cell infiltration analysis. …”
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Performance Prediction of the Gearbox Elastic Support Structure Based on Multi-Task Learning by Chengshun Zhu, Zhizhou Lu, Jie Qi, Meng Xiang, Shilong Yuan, Hui Zhang

“…Neural networks offer a powerful means of capturing and interpreting the intricate associations linking structural parameters with performance metrics. …”
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Estimating chlorophyll content in tea leaves using spectral reflectance and deep learning methods by Yuta Tsuchiya, Yuhei Hirono, Rei Sonobe

“…These findings demonstrate that SSL is particularly effective for capturing subtle spectral patterns and improving prediction performance, especially when labeled data are scarce. …”
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Identification of the Wheat Protein Disulfide Isomerase-like Gene Family and Its Impact on the Structure and Properties of Gluten by JIANG Lanfang, TAN Xiaodi, LIU Xinyu, HAO Jianyu, MA Xiaofei, WANG Min, LI Xiaoli, JI Hutai, ZHANG Dingyi, ZHANG Yang

“…A total of 21 members of the TaPDIL gene family were identified and named TaPDIL1A to TaPDIL8D according to their chromosomal positions, and the length of their coding sequences, the physicochemical properties and secondary structure of the encoded proteins and their subcellular localization were evaluated as well as their expression patterns during grain development in high-gluten (Yaomai 36) and all-purpose (Pinyu 8155) wheat cultivars. …”
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