Article
Chemistry, Analytical
Athos Agapiou, Vasiliki Lysandrou
Summary: This study utilizes satellite observation, cloud platforms, and GIS technology to investigate the thermal conditions of two historic clusters in Cyprus at a macro-scale level. It explores land surface temperature and potential land cover changes in these areas.
Article
Computer Science, Information Systems
Chouaib Bourahla, Ramdane Maamri, Said Brahimi
Summary: In this paper, a system is proposed to reduce the computation time of the Skyline after updating the data by using the Skyline computation history. The system achieves this by introducing a new data representation and algorithms for handling Skyline queries and update queries. Experimental results show that the proposed system outperforms existing approaches in terms of execution time and keeping the Skyline up to date.
INFORMATION SYSTEMS
(2023)
Article
Geochemistry & Geophysics
Chen Xu, Xiaoping Du, Xiangtao Fan, Zhenzhen Yan, Xujie Kang, Junjie Zhu, Zhongyang Hu
Summary: This research analyzed the processing flow of remote sensing big data from the perspective of computer science and remote sensing science, proposing a modular framework. By introducing computation ready data as a dynamic data type to connect key modules of the framework, it significantly reduces experimental costs for remote sensing researchers.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Computer Science, Artificial Intelligence
Yansheng Li, Jiayi Ma, Yongjun Zhang
Summary: The paper discusses the importance of image retrieval in RS big data, as well as related applications and challenges, and provides publicly open datasets, evaluation metrics, and mainstream methods. The authors also point out future research directions for RS big data mining.
INFORMATION FUSION
(2021)
Article
Engineering, Electrical & Electronic
Yang Liu, Lanxue Dang, Shenshen Li, Kun Cai, Xianyu Zuo
Summary: This article summarizes the data type and processing theory model of RS-STBD, high-performance algorithm design, and architecture design of complex remote sensing application systems. It also analyzes current research problems and prospects the future development trends of RS-STBD.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Geochemistry & Geophysics
Yinyi Cheng, Kefa Zhou, Jinlin Wang, Shichao Cui, Jining Yan, Philippe De Maeyer, Tim Van de Voorde
Summary: This letter proposes an optimized strategy for Earth observation data management by designing different horizontal scaling strategies to achieve the optimal distribution of data. The experimental results demonstrate that this strategy contributes to efficient organization and management of data.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2022)
Article
Environmental Sciences
Arno Keppens, Steven Compernolle, Daan Hubert, Tijl Verhoelst, Jose Granville, Jean-Christopher Lambert
Summary: A method is developed to remove a priori information from remotely sensed atmospheric state profiles. This method utilizes Wiener deconvolution and an iterative process to obtain profile-specific deconvolution matrices. The resulting prior-free atmospheric state representations are achieved by asserting that the deconvoluted averaging kernel matrix should equal the unit matrix. The method is successfully applied to ozone profile retrievals, producing accurate results after spatiotemporal averaging.
Article
Biotechnology & Applied Microbiology
Jingyi Zhang, Tong Zhao, Xiangyang Zhai
Summary: The article introduces the application of satellite remote sensing technology in monitoring and analyzing atmospheric pollutants, as well as the detection of spatial distribution and concentration changes of small-scale pollutants in the air through inversion algorithms.
ENVIRONMENTAL TECHNOLOGY & INNOVATION
(2021)
Article
Chemistry, Multidisciplinary
Gloria Pietropolli, Luca Manzoni, Gianpiero Cossarini
Summary: Our work aims to develop an improved deep-learning technique for predicting the relationships between high-frequency and low-frequency sampled variables, in order to enhance the predictive capabilities of ocean observation data.
APPLIED SCIENCES-BASEL
(2023)
Article
Environmental Sciences
Rolf Simoes, Gilberto Camara, Gilberto Queiroz, Felipe Souza, Pedro R. Andrade, Lorena Santos, Alexandre Carvalho, Karine Ferreira
Summary: This paper introduces an open-source R package sits for satellite image time series analysis using machine learning, which adopts a time-first, space-later approach and supports the complete cycle of data analysis for land classification. The software provides a simple but powerful set of functions and works in different cloud computing environments. It includes methods for quality assessment of training data and provides validation and accuracy measurement methods.
Article
Computer Science, Information Systems
Xuan Song, Haoran Zhang, Rajendra Akerkar, Huawei Huang, Song Guo, Lei Zhong, Yusheng Ji, Andreas L. Opdahl, Hemant Purohit, Andre Skupin, Akshay Pottathil, Aron Culotta
Summary: In recent decades, the frequency, intensity, and impact of natural disasters and emergencies have increased significantly, making emergency response and disaster management national priorities for governments worldwide. Leveraging big data and technological advances offers more effective approaches to humanitarian relief, logistical coordination, overall disaster management, and long-term recovery. However, aligning and defining interdisciplinary terminologies and methodologies is necessary for the desired merging of big data and emergency management.
IEEE TRANSACTIONS ON BIG DATA
(2022)
Article
Environmental Sciences
Yanqiong Zhou, Zhuowei Hu, Qianqian Geng, Jiarong Ma, Jiayan Liu, Mi Wang, Yongcai Wang
Summary: Desertification is a critical ecological environmental problem worldwide, and monitoring its spatiotemporal dynamics is essential for its control. This study used Google Earth Engine to collect satellite images from 2000 to 2020 and developed a remote sensing monitoring model for desertification. The results showed that the desertification status in the region around Qinghai Lake has improved, likely due to natural and human factors.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Biochemical Research Methods
Fahimeh Motamedi, Horacio Perez-Sanchez, Alireza Mehridehnavi, Afshin Fassihi, Fahimeh Ghasemi
Summary: This article discusses two approaches for quantitative structure-activity prediction studies, focusing on identifying appropriate molecular descriptors and predicting the biological activities of designed compounds. The use of LASSO-random forest algorithm is shown to significantly improve output correlation, reduce implementation time and model complexity, while maintaining prediction accuracy.
Article
Environmental Sciences
Elisa Castelli, Enzo Papandrea, Alessio Di Roma, Ilaria Bloise, Mattia Varile, Hamid Tabani, Jean-Philippe Gastellu-Etchegorry, Lorenzo Feruglio
Summary: Recent technological advancements have greatly increased the amount of satellite data available, leading to the development of fast and efficient retrieval algorithms. While deep learning techniques have been applied to satellite data for target retrievals, their application to radiative transfer simulations remains underexplored. The DeepLIM project aims to test the feasibility of using deep learning techniques in the design of retrieval chains for satellite missions.
Article
Computer Science, Theory & Methods
Kun Zhang, Kai Chen, Binghui Fan
Summary: This paper designs a massive picture retrieval system using big data image mining technology, running through three steps of data segmentation, mining, and merging to efficiently improve the accuracy and recall of picture retrieval.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Dentistry, Oral Surgery & Medicine
Lingxiao Wang, Chao Liang, Xiao Lin, Changying Liu, Jun Li
Summary: This study elucidated the role of miR-491-5p in osteogenic differentiation, particularly in patients with type 2 diabetes. The downregulation of miR-491-5p was found to be a major factor contributing to decreased osteogenic differentiation. Regulation of miR-491-5p expression has the potential to improve osteogenic differentiation in patients with type 2 diabetes.
Article
Metallurgy & Metallurgical Engineering
Xinxiu Wang, Ruirun Chen, Qi Wang, Shu Wang, Yili Li, Yuan Xia, Guoping Zhou, Guanglong Li, Yingdong Qu
Summary: In this paper, the effects of rotation speed and filling time on the casting process of super large cylinder liners during centrifugal casting were investigated using numerical simulation. The results showed that higher or slower rotation speeds can negatively impact casting performance. Meanwhile, an appropriate rotation speed and filling time can ensure a uniform and steady filling process.
INTERNATIONAL JOURNAL OF METALCASTING
(2023)
Article
Multidisciplinary Sciences
Youlong Zhan, Changlin Liu, Xiao Xiao, Qianbao Tan, Xiaolan Fu
Summary: The risk-taking tendency in human decision-making can be positive and pro-social when it benefits others or society. Recent research has explored the mechanisms of individual negative risk and positive prosocial behaviors and introduced the concept of prosocial risky behavior, which involves risk-taking for the benefit of others. This behavior is dangerous yet prosocial, and understanding it can contribute to a better understanding of human development.
CHINESE SCIENCE BULLETIN-CHINESE
(2023)
Article
Chemistry, Multidisciplinary
Hao Yan, Qian Wang, Jingyun Wang, Wenting Shang, Zhiyuan Xiong, Lingyun Zhao, Xiaodan Sun, Jie Tian, Feiyu Kang, Seok-Hyun Yun
Summary: By using a bottom-up molecular approach, graphene quantum dots (GQDs) can be planted in the poly(ethylene glycol) (PEG) layer of PEGylated nanoparticles to form NPs-GQDs-PEG nanocomposite, allowing for sustainable and multimodality tumor bioimaging in vivo. The planted GQDs show prolonged blood circulation and increased tumor accumulation compared to typical GQDs, and also enable long-term real-time visualization of the local pharmacokinetics of nanoparticles in vivo.
ADVANCED MATERIALS
(2023)
Article
Materials Science, Multidisciplinary
Ji Cheng Ding, Yang Cheng, Shihong Zhang, Qimin Wang, Teng Fei Zhang
Summary: Ti doped ta-C films were deposited using a hybrid coating system and the microstructure, mechanical, and tribological properties of the films were investigated. The Ti content in the films increased linearly with increasing Ti target current, leading to the formation of TiC phase and a transformation of the microstructure to a nanocomposite structure. The Ti doping significantly affected the hardness, residual stress, and adhesion force of the films, resulting in improved friction coefficients and wear rates at different temperatures.
DIAMOND AND RELATED MATERIALS
(2023)
Article
Microbiology
Yibei Zhang, Xiao Wu, Jingxiao Cai, Mo Chen, Jun Zhang, Shuai Shao, Yuanxing Zhang, Yue Ma, Qiyao Wang
Summary: Vibrio alginolyticus is a significant conditional pathogen in marine aquaculture, causing economic losses. Temperature affects its quorum sensing (QS) system, and novel regulatory factors influencing LuxR expression have been identified. These regulators have temperature-dependent or temperature-independent effects on QS-associated phenotypes, such as Asp yields and biofilm formation, indicating their importance in population phenotype modifications. Further investigation is needed to understand their role in opportunistic outbreaks of vibriosis.
MICROBIOLOGICAL RESEARCH
(2023)
Article
Engineering, Mechanical
Xuejie Zhang, Wei Wang, Tong Zhang, Xiaojun Liu, Kun Liu
Summary: Discrete element method simulations are used to analyze the contributions of strong and weak subnetworks to the shear strength of dense granular inertial flow. It was found that all the anisotropy parameters of the subnetworks contribute positively, except for the normal contact force of the weak subnetwork. The contribution weight of the strong subnetwork is significantly greater than that of the weak subnetwork and slightly decreases with increasing shear velocity.
TRIBOLOGY INTERNATIONAL
(2023)
Article
Optics
Teng Fei, Shenqiang Zhai, Jinchuan Zhang, Quanyong Lu, Ning Zhuo, Junqi Liu, Lijun Wang, Shuman Liu, Zhiwei Jia, Kun Li, Yongqiang Sun, Kai Guo, Fengqi Liu
Summary: In this article, a high-performance quantum cascade laser similar to 4.6 μm is reported, which is grown by metal-organic chemical vapor deposition. The coated laser with a length of 8 mm and width of 7.5 μm achieved a continuous wave power of 3 W at a temperature of 285 K. The maximum pulsed and CW wall-plug efficiency reached 15.4% and 10.4%, respectively. The device performance demonstrates the significant potential of metal-organic chemical vapor deposition growth for quantum cascade materials and devices.
Article
Linguistics
Olga Tararova, Martha Black, Qiyao Wang, Katrina Blong
Summary: This study investigates the acquisition of Spanish gender agreement by Russian or Mandarin speakers of English, and compares the results with English speakers of Spanish. The results suggest that beginner learners are influenced by the grammatical gender system of their L1s when identifying gender in Spanish.
Article
Geography, Physical
Jinwen Xu, Yi Qiang, Heng Cai, Lei Zou
Summary: The increasing intensity of extreme weather events highlights the importance of the electrical power system as a crucial component of our infrastructure. However, a lack of household-level power outage data impedes timely and accurate assessments. To address this challenge, we introduced an analytical workflow using NASA's Black Marble nighttime light images to detect power outages during the 2021 Winter Storm Uri. The results demonstrate environmental justice concerns, with Latino/Hispanic communities suffering more from power outages at both the county and census tract levels.
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2023)
Article
Gastroenterology & Hepatology
Li-Ting Mao, Wei-Cui Chen, Jian-Ye Lu, Han-Liang Zhang, Yong-Song Ye, Yu Zhang, Bo Liu, Wei-Wei Deng, Xian Liu
Summary: The study found that the quantitative parameters based on DLSDCT can distinguish the expression status of Ki-67 in gastric cancer. These spectral parameters may have potential clinical applications in evaluating Ki-67 expression.
WORLD JOURNAL OF GASTROENTEROLOGY
(2023)
Article
Geochemistry & Geophysics
Zhuoyi Zhao, Xiang Xu, Jun Li, Shutao Li, Antonio Plaza
Summary: Nowadays, CNN-based DL models have gained popularity in HSIC and achieved high accuracy due to their hierarchical and nonlinear feature learning patterns. However, deeper network structures may demand more parameters and training samples. To overcome these problems, we propose a lightweight network model using the GSC module, which reduces parameters and is suitable for HSI data. Experimental results show that our model has low training cost and achieves competitive accuracy with fewer samples compared to existing models.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Geochemistry & Geophysics
Zhiyong Lv, Haitao Huang, Weiwei Sun, Tao Lei, Jon Atli Benediktsson, Junhuai Li
Summary: This paper proposes a novel approach, E-UNet, for land cover change detection with multimodal remote sensing images (MRSIs). Experimental results demonstrate the feasibility and advantages of the proposed method in terms of visual observations and quantitative evaluations.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Geochemistry & Geophysics
Peng Zheng, Jin Sun, Yang Xu, Yi Zhang, Zhihui Wei, Javier Plaza, Antonio Plaza, Zebin Wu
Summary: This letter introduces a nonlocal hierarchical Tucker decomposition model for hyperspectral and multispectral image fusion. By clustering similar nonlocal patch tensors and employing the alternating direction method of multipliers for solving, the high-resolution HSI can be obtained. Furthermore, an efficient distributed and parallel method is proposed to accelerate the fusion process.
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
(2023)
Article
Environmental Sciences
Mingdong Jiang, Yumeng Huang, Yang Bai, Qi Wang
Summary: By analyzing the impact of Beijing and Shanghai on global carbon emissions, it is found that they are net carbon consumers and play important roles in international trade. Structural adjustment has become the main factor in reducing carbon emissions, rather than technological progress. Beijing's carbon emissions continue to increase, while Shanghai's carbon emissions have declined. Both cities have stable and hub roles in the global carbon network. The heterogeneous structural characteristics of carbon emissions in these two metropolises highlight the need for different carbon mitigation strategies.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
