Classification and Carbon-Stock Estimation of Mangroves in Dongzhaigang Based on Multi-Source Remote Sensing Data Using Google Earth Engine by Ruiwen Zhang, Jianchao Fan

Get full text

Dynamic Risk Assessment System for Power System Based on Multi-source Information of the Ubiquitous Power Internet of Things by Shenhua WANG, Xiangwei HE, Xiaofang FANG, Bingsong CHEN, Chuangxin GUO

“…Finally, based on the architecture, the corresponding software system is designed. The data source, data platform and main function modules of the system are also described. …”
Get full text

A Two-Step Method for Impact Source Localization in Operational Water Pipelines Using Distributed Acoustic Sensing by Haonan Wei, Yi Liu, Zejia Hao

“…STEE is introduced as a stable metric to quantify signal impulsiveness and guides the selection of the relevant intrinsic mode function. …”
Get full text

RQdeltaCT: an open-source R package for relative quantification of gene expression using delta Ct methods by Daniel Zalewski, Anna Bogucka-Kocka

Get full text

Anomaly Usage Behavior Detection Based on Multi-Source Water and Electricity Consumption Information by Wenqing Zhou, Chaoqiang Chen, Qin Yan, Bin Li, Kang Liu, Yingjun Zheng, Hongming Yang, Hui Xiao, Sheng Su

“…Current resident anomaly detection technologies rely on single-source energy data, lacking detailed behavior pattern analysis. …”
Get full text

Nitrogen-functionalized modulation of iron nanoparticles promotes selective hydrogenation of carbon dioxide by Xianbiao Wang, Jun Qian, Zixuan Lu, Jie Huang, Liru Zheng, Yong Jiang, Mengdie Cai, Yuxue Wei, Lisheng Guo, Song Sun

“…Nitrogen-functionalized iron nanoparticles were prepared using a one-pot hydrothermal process. …”
Get full text

Constraining the Faint-end Slope of the Fast Radio Burst Energy Function Using CHIME/FRB Catalog-1 and Local Volume Galaxies by Mohit Bhardwaj, Victoria M. Kaspi, K. W. Masui, B. M. Gaensler, Adaeze L. Ibik, Mawson W. Sammons

Get full text

Identification of resistance sources and genomic regions regulating Septoria tritici blotch resistance in South Asian bread wheat germplasm by Manjeet Kumar, Xinyao He, Sudhir Navathe, Umesh Kamble, Madhu Patial, Pawan Kumar Singh

“…Therefore, dissection of the genetic architecture of adult‐plant resistance with genome‐wide association mapping and selection of resistant sources for adult plant STB resistance were carried out on a panel of South Asian germplasm. …”
Get full text

A Three-Dimensional Complex Measurement Model-Based Avionic Radio-Frequency Power Source Health Assessment Method by Lin Huo, Shiqi Li, Simiao Fei, Chuan Lyu

“…According to the function and structure characteristics of radio-frequency power source, the health characterization parameters are then obtained and the health assessment parameter system is established. …”
Get full text

Insights into the electronic and atomic structures of cerium oxide-based ultrathin films and nanostructures using high-brilliance light sources by Paola Luches, Federico Boscherini

“…High-brilliance light sources, such as synchrotrons and free-electron lasers, allow researchers to probe the structural, electronic, and dynamic properties of functional materials at an unprecedented level of detail. …”
Get full text

Bentayga-I: Development of a Low-Cost and Open-Source Multispectral CubeSat for Marine Environment Monitoring and Prevention by Adrián Rodríguez-Molina, Alejandro Santana, Felipe Machado, Yubal Barrios, Emma Hernández-Suárez, Ámbar Pérez-García, María Díaz, Raúl Santana, Antonio J. Sánchez, José F. López

Get full text

Accelerate Mass Transport of Proton and Carbon Sources by Super‐Hygroscopic and Porous Nanosheets for Continuous CO2‐To‐Ethylene Upgrade by Silong Dong, Guobin Wen, Xinyu Yang, Xiaowen Zhang, Shuxuan Liu, Haoyang Xiong, Yinyi Liu, Kai Zong, Hao Li, Yifan Li, Yi Cui, Bohua Ren, Xin Wang, Mingliang Jin, Zhongwei Chen

“…Inspired by Tillandsia leaves, which efficiently capture H2O and CO2 from the air, copper nanosheets with dual‐functional channels are we designed: the superhygroscopic network enables capillary condensation, converting H2O(g) into H2O(l) to form H2O channels that ensure a stable supply of protons, while the CO2 channels formed by the microporous structure enhance the diffusion of CO2, thus enriching the carbon source. …”
Get full text

MIF-YOLO: An Enhanced YOLO with Multi-Source Image Fusion for Autonomous Dead Chicken Detection by Jiapan Li, Yan Zhang, Yong Zhang, Hongwei Shi, Xianfang Song, Chao Peng

“…Addressing the paucity of automated systems for the detection of dead poultry within large-scale agricultural settings, characterized by the onerous and time-consuming manual inspection processes, this study introduces an enhanced YOLO algorithm with multi-source image fusion (MIF-YOLO) for the autonomous identification of dead chicken. …”
Get full text

Pollination-driven modulation of amino acid biosynthesis in plum: A multi-omics approach by Lijun Deng, Binshu Yuan, Xiaojun Jin, Yingying Xu, Yuhuan Feng, Xuan Zhang, Hui Zhang, Bo Xiong, Xun Wang, Guochao Sun, Mingfei Zhang, Siya He, Ling Liao, Zhihui Wang

“…The findings underscore the potential to improve the nutritional value of plums through the strategic selection of pollination cultivars. In addition, this research provides a foundation for a deeper understanding of the regulatory mechanisms underlying amino acid biosynthesis in plum and supports the development of relevant functional foods.…”
Get full text

The ANFIS-RSM based multi-objective optimization and modelling of ultrasound-assisted extraction of polyphenols from jamun fruit (Syzygium cumini) by Mohammad Ganje, Somayyeh Gharibi, Fatemeh Nejatpour, Maryam Deilamipour, Kimia Goshadehrou, Sahra Saberyan, Gholamreza Abdi

“…For each of the six process-solver conditions, optimal ANFIS models were determined by analyzing the number and type of input membership functions, the output membership function, and the selected optimization and defuzzification methods, based on the highest correlation between actual and predicted data, along with the lowest error rates. …”
Get full text

Sources of uncertainty in DNA metabarcoding of whole communities: Implications for its use in biomonitoring by J. Iwan Jones, Amanda Arnold, Dominik Buchner, John F. Murphy, Jasmine N. Childress, Pedro Beja, Florian Altermatt, Kristian Meissner, Ian Adams, Meri Anderson, Yaisel J. Borrell, Andrew G. Briscoe, Kat Bruce, Cátia Chaves, Chris Conyers, Kristy Deiner, Vasco Elbrecht, Álvaro Fueyo, Tim Goodall, Javier Granero‐Castro, Cristina Hartmann‐Fatu, Eleanor Jones, Elvira Mächler, Filipa M. S. Martins, Sam McGreig, Lyndall Pereira‐da‐Conceicoa, James L. Pretty, Daniel S. Read, Ben Price, Florian Leese, Rosetta C. Blackman

Get full text

QPPLab: A generally applicable software package for detecting, analyzing, and visualizing large-scale quasiperiodic spatiotemporal patterns (QPPs) of brain activity by Nan Xu, Behnaz Yousefi, Nmachi Anumba, Theodore J. LaGrow, Xiaodi Zhang, Shella Keilholz

“…To address these challenges, we present QPPLab, an open-source MATLAB-based toolbox for detecting, analyzing, and visualizing QPPs from fMRI time series. …”
Get full text

A functional selection model explains evolutionary robustness despite plasticity in regulatory networks by Naomi Habib, Ilan Wapinski, Hanah Margalit, Aviv Regev, Nir Friedman

“…We explain these trends using a model with a strong selection to conserve the overall function of a transcription factor, and a much weaker selection over the specific genes it targets. …”
Get full text

Scientific justification for the selection of vegetable crops of the cruciferous family for the design of functional dairy products by Peysakhov Mark, Dunchenko Nina, Yankovskaya Valentina

Get full text

Remote Sensing Extraction of Damaged Buildings in the Shigatse Earthquake, 2025: A Hybrid YOLO-E and SAM2 Approach by Zhimin Wu, Chenyao Qu, Wei Wang, Zelang Miao, Huihui Feng

“…The dataset used for training contained labeled examples of damaged buildings, and the model optimization was carried out using stochastic gradient descent (SGD), with cross-entropy and mean squared error as the selected loss functions. Upon evaluation, the model reached a precision of 0.840, a recall of 0.855, an F1-score of 0.847, and an IoU of 0.735. …”
Get full text