Machine-learning models for Alzheimer’s disease diagnosis using neuroimaging data: survey, reproducibility, and generalizability evaluation by Maryam Akhavan Aghdam, Serdar Bozdag, Fahad Saeed, Alzheimer’s Disease Neuroimaging Initiative

“…To better understand the landscape, we surveyed the major preprocessing, data management, traditional machine-learning (ML), and deep learning (DL) techniques used for diagnosing AD using neuroimaging data such as structural magnetic resonance imaging (sMRI), functional magnetic resonance imaging (fMRI), and positron emission tomography (PET). …”
Get full text

Efficient Virus-Induced Gene Silencing (VIGS) Method for Discovery of Resistance Genes in Soybean by Kelin Deng, Zihua Lu, Hongli Yang, Shuilian Chen, Chao Li, Dong Cao, Hongwei Wang, Qingnan Hao, Haifeng Chen, Zhihui Shan

“…While stable genetic transformation is a common approach for studying gene function, virus-induced gene silencing (VIGS) offers a rapid and powerful alternative for functional genomics, enabling efficient screening of candidate genes. …”
Get full text

Integrating PROSPECT-D physics and adversarial domain adaptation resnet for robust cross-ecosystem plant traits estimation by Hui Zhang, Haoxuan Su, Tie Shen, Guangyao Sun, Qi Wang

“…Plant functional traits, including chlorophyll content (CHL), equivalent water thickness (EWT), and leaf mass per area (LMA), are critical indicators for assessing ecosystem functioning, functional diversity, and their roles in the Earth system. …”
Get full text

On some conceptual sources of the wealth maximization theory by Richard Posner: Adam Smith and Jeremy Bentham by V. S. Dorokhin, A. V. Polyakov

Get full text

Pseudomonas sp. as a Source of Medium Chain Length Polyhydroxyalkanoates for Controlled Drug Delivery: Perspective by Sujatha Kabilan, Mahalakshmi Ayyasamy, Sridhar Jayavel, Gunasekaran Paramasamy

Get full text

Multi-Source Rainfall Data Assimilation based on Broad Learning System over Yunnan Province by Yuanyuan ZHOU, Xiaohui YANG, Tiangui XIAO

“…The accurate estimation of rainfall is always a topic of concern， given its pivotal role in accurately predicting rainfall-related disasters.This study proposed a multi-source rainfall assimilation technology based on a broad learning system （BLS） to improve the accuracy of rainfall estimation.Yunnan Province， located in China's low-latitude plateau， was chosen as the geographical area of interest to establish a multi-source rainfall assimilation model within this region.In particular， the model utilizes five satellite-derived rainfall datasets （3B42V7， IMERG， GSMaP， CMORPH， PERSIANN） and the latitude and longitude information as the source data， and the ground-based rainfall gauge data serves as the reference data.The time span of all the datasets is from April 2014 to December 2017.A leave-one-year-out cross-validation （LOYOCV） method was applied to verify the performance of the established assimilation model， where statistical indicators including Pearson’s correlation coefficient （CC）， root-mean square error （RMSE）， mean absolute error （MAE）， Nash efficiency coefficient （NSE） and Kling-Gupta efficiency （KGE） were used to quantify the accuracy of assimilation rainfall at different spatiotemporal scales.Concurrently， assimilation models based on support vector machine （SVM） and deep neural network （DNN） were established to highlight the accuracy and efficiency of the BLS， respectively.Additionally， the effectiveness of the latitude and longitude information within the proposed assimilation model was examined.The results show that the daily average statistical index of assimilation rainfall based on BLS is better than that of the other five satellite-based products in LOYOCV.At the temporal scale， the proposed assimilation technique effectively reflects the temporal variations observed in gauge-recorded rainfall.Moreover， it can accurately estimate the rainfall amounts during rainstorms in Yunnan Province throughout 2017.It is worth noting that the rainfall data generated through the BLS method outperforms the CMORPH product （the most accurate one among the five satellite-derived rainfall products） in both rainy and dry seasons （May to October and November to April of next year， respectively）.At the spatial scale， BLS-based rainfall results in most areas of Yunnan Province showed higher CC and NSE as well as smaller RMSE and MAE than the satellite-based products.The evaluation of the assimilation models based on BLS， SVM， and DNN highlights that the BLS exhibits superior functional mapping capabilities compared to SVM and demands fewer computational resources than DNN.It is reasonable to conclude that the multi-source rainfall assimilation approach utilizing the BLS while incorporating latitude and longitude information can enhance the precision of rainfall estimates in Yunnan Province.The proposed method presents practical significance in multi-source rainfall data assimilation.…”
Get full text

Environmental adaptations in metagenomes revealed by deep learning by Johanna C. Winder, Simon Poulton, Taoyang Wu, Thomas Mock, Cock van Oosterhout

“…In this study, we applied a transfer learning approach using the ESM-2 protein structure prediction model and our own smaller ANN to classify proteins containing the domain of unknown function 3494 (DUF3494) by their source environments. …”
Get full text

A Global Attention Mechanism-Based EfficientNet Model for Road Pavement-Type Identification by Zhe-Yuan Ni, Jun-Cheng Wang

Get full text

Cropland non-agriculturization and agricultural green development: Evidence from the Yangtze River Economic Belt, China by Chunxia Zhu, Yangyang Sun, Haolun Xu

“…Employing the biennial non-radial directional distance function and Luenberger index, the agricultural green total factor productivity (AGTFP) has been measured under the dual constraints of “carbon source” and “carbon sink”. …”
Get full text

Model-assisted analysis on the response of tomato fruit growth to source-sink ratio regulated by water and nitrogen by Huiping Zhou, Jinliang Chen, Shaozhong Kang

Get full text

Measurement and optimization of sustainable urban form elements in New Urban districts using multi-source data by Yanfeng Zhang, Xiaohui Wang, Longsheng Wang, Guangyu Li, Yige Zhang, Yu Ye, Hongqiang Jiang, Shaoyun Zhong, Junxi Song

Get full text

Microgrid Energy Management Considering Energy Storage Degradation Cost by Yiming Zhao, Hongrui Li, Changsheng Wan, Dong Du, Bo Chen

Get full text

Deep Defense Against Mal-Doc: Utilizing Transformer and SeqGAN for Detecting and Classifying Document Type Malware by Gati Lother Martin, Sang-Min Lee, Jong-Hyun Kim, Young-Seob Jeong, Ah Reum Kang, Jiyoung Woo

“…The proposed model will solve this gap by detecting and classifying document-type malware families using script codes, including tags, to write documents and script languages to execute malicious functions. These script codes offer insights into how the malware was constructed and operates on the victim’s system. …”
Get full text

Estimation of Above-Ground Biomass for <italic>Dendrocalamus Giganteus</italic> Utilizing Spaceborne LiDAR GEDI Data by Huanfen Yang, Zhen Qin, Qingtai Shu, Li Xu, Jinge Yu, Shaolong Luo, Zaikun Wu, Cuifen Xia, Zhengdao Yang

Get full text

Methodological characterization of X-ray absorption Spectroscopy in small molecule conversion processes utilizing energy catalytic nanomaterials by Rui Ren, Sitan Li, Yulan Gu, Guifen Li, Dongdong Xue, Nuo Liu, Yali Zhang, Li An, Jiangwei Zhang

“…While many catalysts have demonstrated excellent catalytic performance in reactions such as nitrogen reduction, carbon dioxide reduction, water splitting, and biomass conversion, numerous questions regarding catalyst structure, active site functionality, and catalytic mechanisms remain unanswered. …”
Get full text

Simulation study on the dosimetric parameters of domestically produced high-dose-rate brachytherapy 192Ir source by HAN Jinpeng, AN Xingtao, WANG Ji, YANG Zhijun, WANG Peiwei, WU Jinjie, WANG Kun

“…Furthermore, the dosimetric parameters for the radial dose function and anisotropy function obtained in this study show a high degree of consistency with corresponding data from existing literature.ConclusionsThe domestically produced 192Ir source model established using the Monte Carlo software demonstrates good consistent dosimetric parameters with the literature-reported dosimetric parameters, indicating that this model can be used for clinical practice applications of domestically produced 192Ir sources and has certain guiding significance.…”
Get full text

Bias‐Independent True Random Number Generator Circuit using Memristor Noise Signals as Entropy Source by Jinwoo Park, Hyunjoong Kim, Hyungjin Kim

“…Herein, a bias‐independent TRNG circuit is presented, utilizing the random telegraph noise (RTN) signal of the memristor as a random entropy source. …”
Get full text

pH shift extraction technique for plant proteins: A promising technique for sustainable development by Zainab Sultan, Alweera Ashfaq, Kausar Jahan, Ovais Shafiq Qadri, Kaiser Younis, Owais Yousuf

“…Plant proteins offer versatile functional and dietary benefits, making them suitable for various food applications. …”
Get full text

Flow Allocation Algorithm Based on Potential Game in Multi-Source Multi-Hop Wireless Sensor Network by Wei Zhang, Linghua Zhang

“…The scheme adjusts the traffic based on the utility function to increase the number of coding opportunities. …”
Get full text

Strategies for efficient utilization of heavy rare-earth Tb in high-performance Ce magnets with high Ce content by Xiaolong Song, Qisong Sun, Minggang Zhu, Dongmin Zhang, Yifei Xiao, Yikun Fang, Qiang Wang, Wei Li

Get full text