Low-Carbon-Economic Collaborative Optimal Dispatching of Microgrid Considering Electricity-Hydrogen Integration by Lingling TAN, Wei TANG, Dongqing CHU, Zihan YU, Xingquan JI, Yumin ZHANG

“…In the low-carbon demand response model, with the saved carbon emission costs by reduced carbon emissions of microgrid users as an incentive signal, a mapping relationship between energy flow and carbon emission flow of microgrid is established to realize the transfer and allocation of carbon emission responsibilities and fine evaluation of carbon emission characteristics of microgrid operations, so as to establish a low-carbon DR model which guides users to participate in carbon emission reduction strategies according to the spatial and temporal differences of load carbon emission intensity, and to deeply explore the synergy between low-carbon and economy of source-load of microgrid. …”
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Local Adaptation and Climate Change Vulnerability of the Relict Tree Species Taiwania cryptomerioides Provide Insights Into Its Conservation and Restoration by Yang Lu, Hao Dong, Saibin Fan, Lu Yuan, Yuhui Wang, Zhuang Zhao, Yong Lai, Shixin Zhu, Jinyong Huang, Caipeng Yue, Yongpeng Ma, Ningning Zhang

“…Here, we applied a landscape genomics approach to investigate the population genetic structure and predict adaptive capacity to climatic change for Taiwania cryptomerioides Hayata, a vulnerable Tertiary relict tree species in China. …”
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Enhancing Breast Cancer Diagnosis With Bidirectional Recurrent Neural Networks: A Novel Approach for Histopathological Image Multi-Classification by Rajendra Babu Chikkala, Chinta Anuradha, Patnala S. R. Chandra Murty, S. Rajeswari, N. Rajeswaran, M. Murugappan, Muhammad E. H. Chowdhury

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Numerical Simulation of Turbopump Inducer Cavitating Behavior by Coutier-Delgosha O., Morel P., Fortes-Patella R., Reboud JL.

“…<p>In the present study a numerical model of 3D cavitating flows is proposed. It is applied to investigate the behavior of a spatial turbopump inducer in noncavitating and cavitating conditions. …”
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A Ship’s Maritime Critical Target Identification Method Based on Lightweight and Triple Attention Mechanisms by Pu Wang, Shenhua Yang, Guoquan Chen, Weijun Wang, Zeyang Huang, Yuanliang Jiang

“…The experimental results show that the average accuracy of this method in identifying seven types of targets—including buoys, bridges, islands and reefs, container ships, bulk carriers, passenger ships, and other ships—reached 92.1%, with a 12% reduction in the number of parameters. This enhancement improves the model’s ability to recognize and distinguish different targets and buoy colors.…”
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Graph-based analysis of histopathological images for lung cancer classification using GLCM features and enhanced graph by Imam Dad, JianFeng He, Zulqarnain Baloch

“…Our methodology leverages Gray-Level Co-occurrence Matrix (GLCM) features to quantify tissue texture, constructs a Sparse Cosine Similarity Matrix (SCSM) to model spatial relationships, and employs DeepWalk embeddings to capture topological patterns. …”
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Pooled error variance and covariance estimation of sparse in situ soil moisture sensor measurements in agricultural fields in Flanders by M. G. A. Hendrickx, M. G. A. Hendrickx, J. Vanderborght, J. Vanderborght, P. Janssens, P. Janssens, P. Janssens, S. Bombeke, E. Matthyssen, A. Waverijn, J. Diels, J. Diels

“…These results demonstrate that the common assumption of uncorrelated random errors to determine parameter and model prediction uncertainty is not valid when measurements from sparse in situ soil moisture sensors are used to parameterize soil hydrological models. …”
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KDM1A epigenetically enhances RAD51 expression to suppress the STING-associated anti-tumor immunity in esophageal squamous cell carcinoma by Qingyuan Yang, Shiyin Wei, Cen Qiu, Chenjie Han, Zunguo Du, Ning Wu

“…Cell growth was assessed by colony formation assays in vitro and subcutaneous xenograft models in vivo. High-throughput transcriptomics and spatial immune proteomics were performed using bulk RNA sequencing and digital spatial profiling techniques, respectively. …”
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Comparison of principal component analysis algorithms for imputation in agrometeorological data in high dimension and reduced sample size. by Valter Cesar de Souza, Sergio Augusto Rodrigues, Luís Roberto Almeida Gabriel Filho

“…Future research should explore the effectiveness of various imputation methods in diverse climatic and geographical contexts, as well as develop new techniques considering the temporal and spatial structure of meteorological data, to advance understanding and climate prediction.…”
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The temporal scale of energy maximization explains allometric variations in movement decisions of large herbivores by Daniel Fortin, Christopher F. Brooke, Hervé Fritz, Jan A. Venter

“…Abstract Empirical testing of energy maximization models has been used to clarify the drivers of resource partitioning among large herbivores. …”
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Long‐term data reveals increase in vehicle collisions of endangered birds in Hokkaido, Japan by Kazuya Kobayashi, Annegret Moto Naito‐Liederbach, Toshio Sadakuni, Yuta Morii

“…These results suggest that long‐term data accumulation over large spatial scales allows us to understand the dynamics of accidents and predict potential factors underlying collision risks.…”
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A meta-analysis for the nighttime light remote sensing data applied in urban research: Key topics, hotspot study areas and new trends by Baiyu Dong, Ruyi Zhang, Sinan Li, Yang Ye, Chenhao Huang

“…Regarding the research methods, we observed an increase in the use of machine learning and index-based evaluation methods, with the former most commonly applied to urban area extraction and environmental variable prediction. We also highlighted emerging trends including: (1) Growing significance of machine learning models; (2) Transition of NTL from a leading role to an auxiliary tool; (3) An increased focus on the physical modelling of NTL, and challenges including: (1) Difficulties faced when applying medium-high resolution NTL imagery; (2) Limited applications of deep learning models; (3) Unable to genuinely reflect the urban artificial light information; (4) Inadequate temporal flexibility and consistency of observations. …”
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Effect of protrusion structure on the performance of an advanced hydrodynamic cavitation reactor: An entropy-based analysis by Gaoju Xia, Sivakumar Manickam, Jingwei Li, Zhiqiang Yin, Wenlong Wang, Xun Sun

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Responsiveness to the Effect of Fluoxetine in Male and Female Rats Exposed to Single Prolonged Stress: A Behavioral, Biochemical, Molecular and Histological Study by Reza Eshaghi-Gorji, Sareh Rashidi, Sakineh Shafia, Fereshteh Talebpour Amiri, Mansoureh Mirzae, Moslem Mohammadi

“…Conclusion: We observed that male and female rats with PTSD, show a reduction of the levels of serum IGF-1, impaired spatial memory in a recognition location memory task and enhanced apoptotic-related factors expression in the hippocampus, and decreased hippocampal dendritic branches. …”
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A lightweight mechanism for vision-transformer-based object detection by Yanming Ye, Qiang Sun, Kailong Cheng, Xingfa Shen, Dongjing Wang

“…This design reduces the computational complexity from quadratic to linear while preserving spatial context awareness. XFCOS enhances the original TSP-FCOS (Transformer-based Set Prediction with FCOS) model by integrating XFA into the transformer encoder, creating a CNN-ViT hybrid architecture, significantly reducing computational costs without sacrificing accuracy. …”
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Individual bacteria in structured environments rely on phenotypic resistance to phage. by Erin L Attrill, Rory Claydon, Urszula Łapińska, Mario Recker, Sean Meaden, Aidan T Brown, Edze R Westra, Sarah V Harding, Stefano Pagliara

“…This survival strategy is in contrast with the emergence of genetic resistance in the absence of ephemeral refuges in well-mixed environments. Predictions generated via a mathematical modelling framework to track bacterial response to phages reveal that the presence of spatial refuges leads to fundamentally different population dynamics that should be considered in order to predict and manipulate the evolutionary and ecological dynamics of bacteria-phage interactions in naturally structured environments.…”
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Spatiotemporal correlation–based adaptive sampling algorithm for clustered wireless sensor networks by Wenyu Cai, Meiyan Zhang

“…Afterwards, each cluster head maintains an autoregressive prediction model for sensory data, which is derived from historical data in the temporal domain. …”
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Spatiotemporal DeepWalk Gated Recurrent Neural Network: A Deep Learning Framework for Traffic Learning and Forecasting by Jian Yang, Jinhong Li, Lu Wei, Lei Gao, Fuqi Mao

“…To address these issues, we propose a spatiotemporal DeepWalk gated recurrent unit model (ST-DWGRU), a deep learning framework that fuses spatial, temporal, and semantic features for traffic speed forecasting. …”
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Evaluation of the pharmacological potential of N-((5-phenyl-6,11-dihydro-[1,2,4]triazolo[1’,5’:1,6]pyrido[3,4-b]indol-2-yl)methyl)benzamides by S. O. Fedotov

“…Advanced molecular docking techniques were employed to identify potential binding sites with model enzymes and to characterize the energetic and spatial features of ligand-target interactions. …”
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Histopathological image based breast cancer diagnosis using deep learning and bio inspired optimization by Venkata Nagaraju Thatha, M. Ganesh Karthik, Venu Gopal Gaddam, D. Pramodh Krishna, S. Venkataramana, Kranthi Kumar Lella, Udayaraju Pamula

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