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Metrology for Automotive (MetroAutomotive), IEEE international Workshop on

作者： Giovanni Cappello Antonio Angrisano Silvia Ascione Silvio Del Pizzo Ciro Gioia Gabriele Portelli Melania Susi Salvatore Gaglione Department of Science and Technology International PhD Programme / UNESCO Chair "Environment Resources and Sustainable Development" Parthenope University of Naples Naples Italy Department of Engineering Messina University Messina Italy Department of Science and Technology International PhD Programme/"Environmental Phenomena and Risks (EnPheR)" Parthenope University of Naples Naples Italy Department of Science and Technology Parthenope University of Naples Naples Italy Independert Researcher Ispra Italy Joint Research Centre Italy

The importance of an accurate PNT (Position, Navigation, Timing) information is nowadays consolidated in the navigation field. Easy of use and robustness make Single Point Positioning (SPP) one of the most used techniques to compute navigation information, on the other hand, employing SPP may not lead to the achievement of the required performance, especially in challenging scenario. Different techniques or services could be used in order to achieve the target performance; in particular, the recent Galileo High Accuracy Service (HAS) could enhance the position accuracy. Several applications can benefit of HAS in particular geomatics, automotive, aviation, and maritime. This novel service provides corrections for orbits, code, phase, and satellite clock for Galileo and GPS (Global Positioning System) systems. Corrections are broadcast through the Galileo E6-B signal or other means (i.e., internet), and they have a global coverage. Even if HAS corrections are meant for the PPP (Precise Point Positioning) technique, in this study, they are applied to the SPP technique in order to assess the possible improvements in solution accuracy.

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POST-CLASSIFICATION ENHANCEMENT IN THE RESULT OF DEEP LEARNING LAND COVER CLASSIFICATION USING VERY-HIGH RESOLUTION SATELLITE IMAGERY 44

POST-CLASSIFICATION ENHANCEMENT IN THE RESULT OF DEEP LEARNI...

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44th Asian Conference on Remote Sensing, ACRS 2023

作者： Hakim, Yofri Furqani Tsai, Fuan International Ph.D. Program in Environmental Science and Technology National Central University No. 300 Zhongda Rd. Zhongli District Taoyuan City32001 Taiwan Center for Space and Remote Sensing Research National Central University No. 300 Zhongda Rd. Zhongli District Taoyuan City32001 Taiwan

ISBN: (纸本)9781713893646

Land cover is one of the fundamental data utilized in spatial analysis for a range of applications, including climate, environment, natural resources, agriculture, forestry, planning, health, and even social issues. The demand for land cover data is diverse, ranging from global scale, regional scale, and detailed scale. Furthermore, data updates also become a necessity for users. The current trend is the requirement for more accurate and up-to-date land cover data. The growing demand for accurate and up-to-date land cover data is in sync with improvements in satellite imagery data acquisition technology, which now offers improved spatial resolution and more effective satellite imagery data processing. Satellite imagery data processing technology is also growing rapidly with the advance of artificial intelligence for semantic classification or segmentation. This research uses a deep learning approach to classify land cover on Pleiades very high-resolution satellite imagery. A post-classification enhancement is also carried out to improve the consistency and accuracy of the deep learning classification results. The preliminary research results show that post-classification enhancement with the algorithms proposed in this study can increase the accuracy of classification results using deep learning-based approaches by approximately 2%. The original Overall Accuracy and Kappa of the deep learning classification results were 0.84 and 0.79. After the post-classification enhancement process, the Overall Accuracy and Kappa values increased to 0.86 and 0.81. © 2023 ACRS. All Rights Reserved.

关键词： Deep Learning Image Morphology Land Cover Classification Post-Classification Enhancement Semantic Segmentation U-Net

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INTEGRATING SENTINEL-1 SYNTHETIC APERTURE RADAR AND CHIRPS DATA FOR UNDERSTANDING HEAVY PRECIPITATION AND FLOODING IN AN GIANG PROVINCE, VIET NAM 44

INTEGRATING SENTINEL-1 SYNTHETIC APERTURE RADAR AND CHIRPS D...

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44th Asian Conference on Remote Sensing, ACRS 2023

作者： Minh, Ton Binh Chiang, Shou-Hao International Ph.D Program in Environmental Science and Technology University System of Taiwan No. 300 Zhongda Rd. Zhongli District Taoyuan City32001 Taiwan Center for Space and Remote Sensing Research National Central University No. 300 Zhongda Rd. Zhongli District Taoyuan City32001 Taiwan

ISBN: (纸本)9781713893646

Understanding the mechanisms of heavy precipitation and flooding is essential for effective climate change adaptation and response. The cloud-penetrating ability of microwaves makes Synthetic Aperture Radar (SAR) an ideal tool for providing weather-independent images for flood mapping. Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) is a land-only rainfall dataset that incorporates 0.05° resolution satellite imagery with in-situ station data to create gridded rainfall time series for various analysis applications. This study employs intensity images from Sentinel-1 satellites to generate flood maps and utilizes CHIRPS to derive heavy rainfall frequency. The segmentation technique is applied to distinguish between pre-existing standing water, recently flooded areas, and non-flooded regions within the study area. By combining SAR and CHIRPS data, this research yields valuable insights into the relationship between heavy rainfall and flood occurrences in An Giang province, Viet Nam. The escalating frequency of heavy precipitation correlates with an augmentation in local rainfall amounts, and a positive correlation emerges between heavy rainfall and the extension of flood-prone areas. While recognizing that flooding influences water flow from the upstream of the Mekong River, flooding discharges from neighboring areas, and tidal levels, the accelerated trend of urbanization has also played a significant role. The expansion of impervious surfaces contributes to the severity of deep floods and elevates flood potential in the region. Furthermore, this research affirms the effectiveness of SAR intensity image mapping for flood detection, and the integration of SAR and CHIRPS data furthers our understanding of heavy precipitation mechanisms. As the implications of climate change persist, the findings are crucial for developing sustainable flood management strategies, as well as enhancing resilience to climate-induced challenges in the Mekong River Del

关键词： CHIRPS climate change Flood Mekong River Delta Sentinel-1

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Anchorene,a carotenoid-derived growth regulator,modulates auxin homeostasis by suppressing GH3-mediated auxin conjugation

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Journal of Integrative Plant Biology 2024年第11期66卷 2490-2504页

作者： Danping Ke Yinpeng Xie Haipeng Li Liqun Hu Yi He Chao Guo Yahui Zhai Jinggong Guo Kun Li Zongyan Chu Junli Zhang Xuebin Zhang Salim Al-Babili Kai Jiang Yuchen Miao Kun-Peng Jia National Key Laboratory of Cotton Bio-breeding and Integrated Utilization State Key Laboratory of Crop Stress Adaptation and ImprovementHenan Joint International Laboratory for Crop Multi-Omics ResearchSchool of Life SciencesHenan UniversityKaifeng 450046China Sanya Institute of Henan University Sanya 572025China State Key Laboratory for Crop Stress Resistance and High-Eﬁciency Production/Shaanxi Key Laboratory of Apple College of HorticultureNorthwest A&F UniversityYangling 712100China Institute of Plant and Food Science Department of BiologySchool of Life SciencesSouthern University of Science and Technology(SUSTech)Shenzhen 518055China The BioActives Lab Center for Desert AgricultureKing Abdullah University of Science and TechnologyThuwal 23955-6900Kingdom of Saudi Arabia Plant Science Program Biological and Environmental Science and Engineering(BESE)DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Laboratory of Cell Metabolism and Diseases State Key Laboratory of Conservation and Utilization of Bio-Resources in YunnanCenter for Life SciencesSchool of Life SciencesYunnan UniversityKunming 650500China

Anchorene,identified as an endogenous bioactive carotenoid-derived dialdehyde and diapocarotenoid,affects root development by modulating auxin ***,the precise interaction between anchorene and auxin,as well as the mechanisms by which anchorene modulates auxin levels,remain largely *** this study,we conducted a comparative analysis of anchorene's bioactivities alongside auxin and observed that anchorene induces multifaceted auxin-like *** genetic and pharmacological examinations,we revealed that anchorene's auxin-like activities depend on the indole-3-pyruvate-dependent auxin biosynthesis pathway,as well as the auxin inactivation pathway mediated by Group II Gretchen Hagen 3(GH3)proteins that mainly facilitate the conjugation of indole-3-acetic acid(IAA)to amino acids,leading to the formation of inactivated storage *** measurements indicated that anchorene treatment elevates IAA levels while reducing the quantities of inactivated IAA–amino acid conjugates and ox *** sequencing further revealed that anchorene triggers the expression of numerous auxin-responsive genes in a manner reliant on Group II ***,our in vitro enzymatic assays and biolayer interferometry(BLI)assay demonstrated anchorene's robust suppression of GH3.17-mediated IAA conjugation with ***,our findings highlight the significant role of carotenoid-derived metabolite anchorene in modulating auxin homeostasis,primarily through the repression of GH3-mediated IAA conjugation and inactivation pathways,offering novel insights into the regulatory mechanisms of plant bioactive apocarotenoids.

关键词： Anchorene auxin conjugation carotenoid-derived bioactive apocarotenoid Gretchen Hagen 3 root development

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Application of machine learning algorithms to screen potential biomarkers under cadmium exposure based on human urine metabolic profiles

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Chinese Chemical Letters 2022年第12期33卷 5184-5188页

作者： Ting Zeng Yanshan Liang Qingyuan Dai Jinglin Tian Jinyao Chen Bo Lei Zhu Yang Zongwei Cai Food Science and Technology Program Beijing Normal University-Hong Kong Baptist University United International CollegeZhuhai 519087China State Key Laboratory of Environmental and Biological Analysis Department of ChemistryHong Kong Baptist UniversityHong KongChina Department of Nutrition Food Safety and ToxicologyWest China School of Public HealthSichuan UniversityChengdu 610041China

Exposure to environmental cadmium increases the health risk of *** urine metabolic detection using high-resolution mass spectrometry and machine learning algorithms would be advantageous to predict the adverse health ***,we conducted machine learning approaches to screen potential biomarkers under cadmium exposure in 403 urine *** positive and negative ionization mode,4207 and 3558 features were extracted,*** compared seven machine learning algorithms and found that the extreme gradient boosting(XGBoost)and random forest(RF)classifiers showed better accuracy and predictive performance than *** 5-fold cross-validation,the value of area under curve(AUC)was both 0.93 for positive and negative ionization modes in XGBoost *** the RF classifier,AUC were 0.80 and 0.84 for positive and negative ionization modes,*** then identified a biomarker panel based on XGBoost and RF *** incorporation of machine learning models into urine analysis using high-resolution mass spectrometry could allow a convenient assessment of cadmium exposure.

关键词： Human urine High-resolution mass spectrometry Cadmium exposure Metabolic profiles Machine learning

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Pentacenequinone-Modulated 2D GdSn-PQ Nanosheets as a Fluorescent Probe for the Detection of Enrofloxacin in Biological and environmental Samples

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ACS Applied Materials and Interfaces 2024年第21期16卷 27028-27039页

作者： Dabur, Deepak Rana, Priyanka Wu, Hui-Fen International PhD Program for Science National Sun Yat-Sen University Kaohsiung80424 Taiwan Department of Chemistry National Sun Yat-Sen University Kaohsiung 70 Lien-Hai Road Kaohsiung80424 Taiwan School of Pharmacy College of Pharmacy Kaohsiung Medical University Kaohsiung807 Taiwan Institute of Medical Science and Technology College of Medicine National Sun Yat-Sen University Kaohsiung80424 Taiwan Institute of Precision Medicine College of Medicine National Sun Yat-Sen University Kaohsiung80424 Taiwan School of Medicine College of Medicine National Sun Yat-Sen University Kaohsiung80424 Taiwan Institute of BioPharmaceutical Science National Sun Yat-Sen University Kaohsiung80424 Taiwan

The fate and effects of fluoroquinolone antibacterial (FQ) on the environment are important since there appears to be a surge in FQ resistance like enrofloxacin (ENR) in both environmental and clinical organisms. Numerous reports indicate that the sensing capabilities of these antibiotics need to be improved. Here, we have investigated the interaction of ENR with our synthesized pentacenequinone-modulated gadolinium-tin (GdSn-PQ) nanosheets and the formation of intermolecular interactions that caused the occurrence of aggregation-induced emission enhancement. The concept for designing hybrid metallic nanosheets comes from the unique features inherited from the parent organic precursor. Due to the distinct interaction between ENR and GdSn-PQ, the interstate conversion (ISC) between GdSn-PQ and ENR induces a significant wavelength shift in photoluminescence (PL), improving reliability, selectivity, and visibility compared to quenching- or AIEE-based methods without peak shifts, allowing for highly sensitive and visually detectable analyses. The fluorescence signal of GdSn-PQ exhibited a linear relationship (R2 = 0.9911), with the added ENR concentrations ranging from 5 to 90 nM, with a detection limit of 0.10 nM. We have demonstrated its potential and wide use in the detection of ENR in biological samples (human urine and blood serum) and environmental samples (tap water and seawater) with a recovery rate of 98- 108%. The current approach has demonstrated that the 2D GdSn-PQ nanosheet is a novel and powerful platform for future biological and environmental studies. © 2024 The Authors. Published by American Chemical Society.

关键词： Nanosheets

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Exposure to trace levels of metals and fluoroquinolones increases inflammation and tumorigenesis risk of zebrafish embryos

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environmental science and Ecotechnology 2022年第2期10卷 12-22页

作者： Dantong Jia Ruijie Zhang Jian Shao Wei Zhang Leilei Cai Weiling Sun College of Environmental Sciences and Engineering Peking UniversityThe Key Laboratory of Water and Sediment SciencesMinistry of EducationBeijing100871China State Environmental Protection Key Laboratory of All Material Fluxes in River Ecosystems International Joint Laboratory for Regional Pollution ControlMinistry of EducationBeijing100871China College of Animal Science Guizhou UniversityThe Key Laboratory of Animal GeneticsBreeding and Reproduction in the Plateau Mountainous RegionMinistry of EducationGuiyangGuizhou550025China Department of Plant Soil and Microbial SciencesEnvironmental Science and Policy ProgramMichigan State UniversityEast LansingMI48824United States College of Safety and Environmental Engineering Shandong University of Science and TechnologyQingdaoShandong266590China

Exposure to trace-level heavy metals and antibiotics may elicit metabolic disorder,alter protein expression,and then induce pathological changes in zebrafish embryos,despite negligible physiological and developmental *** study investigated the single and combined developmental toxicity of fluoroquinolones(enrofloxacin[ENR]and ciprofloxacin[CIP])(0.5 mM)and heavy metals(Cu and Cd)(0.5 mM)to zebrafish embryos,and molecular responses of zebrafish larvae upon exposure to the single pollutant(0.2 mM)or a binary metal-fluoroquinolone mixture(0.2 mM).In all single and mixture exposure groups,no developmental toxicity was observed,but oxidative stress,inflammation,and lipid depletion were found in zebrafish embryos,which was more severe in the mixture exposure groups than in the single exposure groups,probably due to increased metal bioaccumulation in the presence of ENR or *** analysis revealed the up-regulation of amino acids and down-regulation of fatty acids,corresponding to an active response to oxidative stress and the occurrence of *** up-regulation of antioxidase and immune proteins revealed by proteomics analysis further confirmed the occurrence of oxidative stress and ***,the KEGG pathway enrichment analysis showed a significant disturbance of pathways related to immunity and tumor,indicating the potential risk of tumorigenesis in zebrafish *** findings provide molecular-level insights into the adverse effects of heavy metals and antibiotics(especially in chemical mixtures)on zebrafish embryos,and highlight the potential ecotoxicological risks of trace-level heavy metals and antibiotics in the environment.

关键词： Fluoroquinolone Metal Inflammation Tumor Oxidative stress

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Enhanced removal of viral aerosols using nanosilver/TiO2-chitosan filters combined with a negative air ionizer

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Journal of environmental Chemical Engineering 2024年第3期12卷

作者： Dlamini, Wonder Nathi Yao, Ting-Ching Lee, Hsin-Jui Berekute, Abiyu Kerebo Sallah-Ud-Din, Rasham Siregar, Sepridawati Yu, Kuo-Pin Institute of Environmental and Occupational Health Sciences National Yang-Ming Chiao-Tung University Taipei Taiwan Department of International Ph.D. Program in Environmental Sciences and Technology University System of Taiwan Taipei Taiwan Department of Chemistry College of Natural and Computational Sciences Arba Minch University Arbaminch Ethiopia Faculty of Mineral Technology AKPRIND Institute of Science & Technology Yogyakarta Indonesia

The presence of airborne viruses in bioaerosols is a significant and ongoing public health concern. In this context, this study aimed to develop a new filter that integrates nanosilver into a TiO2-chitosan matrix (nano-Ag/TiO2-CS) to inactivate the non-enveloped bacteriophage MS2 as a viral aerosol surrogate. The materials were characterized using various techniques, such as X-ray diffraction (XRD), scanning electron microscopy (SEM), high-resolution transmission electron microscopy (HR-TEM), and X-ray photoelectron spectroscopy (XPS). The SEM images showed that the nano-Ag particles were spheres with a high surface area for virus interactions and that the fiber surfaces were covered by nano-Ag, which enhanced contact with viruses. The optimal 5 wt% nano-Ag/TiO2-CS filter combined with a negative air ionizer (NAI) showed the highest viral aerosol removal efficiency, which reached 97 %. The use of an NAI during filtration enhanced the inactivation of the viral aerosols. A long-term antiviral efficacy assessment showed that the nano-Ag/TiO2-CS filter demonstrated robust durability, which is vital for real-world applications. The nanofilter proposed in this work is simple, safe, and cost-effective for inactivating viral aerosols to improve indoor air quality. © 2024 Elsevier Ltd

关键词： Aerosols

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Customer Segment Classification Prediction in the Australian Retail Based on Machine Learning Algorithms 23

Customer Segment Classification Prediction in the Australian...

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Proceedings of the 2023 4th international Conference on Machine Learning and Computer Application

作者： Yiming Luo Rui Zhang Fei Wang Tao Wei Business Schoo The University of Sydney Austialia Computer and information sciences program Harrisburg University of Science and Technology United States Faculty of Science and Technology Beijing Normal University-Hong Kong Baptist University United International College China School of Chemical and Environmental Engineering Sichuan University of Science & Engineering China

ISBN: (纸本)9798400709449

Customer segmentation is an essential area of business analytics today. Accurate customer segmentation is access to improves the efficiency of marketing campaigns and customer satisfaction. This study employs multiple machine learning methods to classify Australian Retail company BIGW's customer segments and first to apply multiple model explanation methods to find insights related to customer segmentation identification. After rigorous comparison and hyperparameter fine-tuning, XGBoost is the most adept for this dataset. We derive three key insights through the model results and model interpretive methods. First, BIGW's primary clientele comprises young families in urban areas who prefer cost-effective products, establishing the foundation of their consumer base. Second, the model result indicates a notable gap in BIGW's understanding of its high-end customers, suggesting an area for immediate attention. Third, a specific customer segment emerges from the data: individuals favoring online shopping, demonstrating high total expenditure but low interest in promotions, representing a high-value segment.

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Comprehensive assessment of water and sediment quality to support sustainable management practices and mitigate potential risks of trace metal pollution in the Johor River Basin, South Peninsular Malaysia

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Ecohydrology and Hydrobiology 2025年第2期25卷 315-329页

作者： Mazilamani, Lelavathy S. Annammala, Kogila V. Martin, Patrick Qi, Liang Y. Sugumaran, Dhinesh Ling, Yong E. Reynard, P.S. Nurhidayat, Agus Syawal, Muhamad S. Sutapa, Ignasius D.A. Department of Water & Environmental Engineering Faculty of Civil Engineering Universiti Teknologi Malaysia Johor Bahru Malaysia Disaster Preparedness and Prevention Centre Universiti Teknologi Malaysia Kuala Lumpur Malaysia Asian School of the Environment Nanyang Technological University Singapore Centre of Environmental Sustainability & Water Security (IPASA) Research Institute for Sustainable Environment (RISE) Universiti Teknologi Malaysia Johor Bahru Malaysia Faculty of Engineering – Industrial Engineering International Study Program University of Indonesia Indonesia Asia Pacific Centre for Ecohydrology (APCE) – UNESCO C2C Indonesia Research Centre for Limnology and Water Resources – NRIA Indonesia Faculty of Environmental Science and Technology – Soegijapranata Catholic University (SCU) Semarang Indonesia

Human activities have caused concerns over the contamination of trace elements in aquatic systems due to their toxicity, long-lasting nature, and ability to accumulate in living organisms. This study evaluated the spatial pattern, environmental hazard, and potential health hazard of 13 trace metals in water and sediment samples collected from the Johor River basin using multivariate statistical techniques in order to identify the impact of both natural and human-related factors on the presence of trace metals in the area. The increased levels of metals in Station S1 indicated a significant impact from municipal, domestic, and industrial waste. The Geo-accumulation Index (I_geo) values for pollution and ecological indices in the sediment of the Johor River Basin ranged from -9.44 to 6.27. The Pollution Load Index (PLI) values ranged from 0.05 to 0.18, and the Potential Ecological Risk Assessment (RI) values ranged from 2.15 to 11.18. These results indicate that the sediments in the Johor River Basin have a low risk of contamination from trace metals. The water's hazard quotient (HQ) had an average value of 0.0001, while the hazard index (HI) had an average value of 0.0003. It is important to increase stakeholders' understanding and concerns regarding the potential long-term human health and ecological implications associated with trace metals in Johor River water. The results of this study offer essential initial information for government entities to implement sustainable management strategies, reducing the likelihood of future trace metal contamination issues in the Johor River basin and similar regions. © 2024 European Regional Centre for Ecohydrology of the Polish Academy of sciences

关键词： Health assessment Johor river basin Multivariate analysis Sediment quality Trace metals Water quality

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