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An urbanization monitoring dataset for world cultural heritage in the Belt and Road region

Big Earth Data 2022年第1期6卷 127-140页

作者： Da Xiao Linlin Lu Xinyuan Wang Vilas Nitivattananon Huadong Guo Wenhua Hui Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesBeijingChina College of Geological Engineering and Geomatics Chang’an UniversityXi’anChina Urban Environmental Management Program School of EnvironmentResources and DevelopmentAsian Institute of TechnologyBangkokThailand

World cultural heritage refers to properties recognized as having historical, social, and anthropological value. Global urbanization has changed the land cover, land use, transportation, landscape, and local environment in cities, and thus exposed World Heritage sites to risks induced by direct or indirect damaging factors. In this paper, an urbanization intensity index (UII) was developed to quantitatively measure urban dynamics in the vicinity of World Heritage sites. This index is based on three global Earth observation datasets, including a global human settlement layer, a global population grid product, and a global nighttime light imagery. Large UII values represent high urbanization levels and intensive human activities in the study area and vice versa. The assessment results show that the mean UII value at 79 world cultural heritage sites in the Belt and Road region increased from 0.26 in 2000 to 0.29 in 2015. The heritage sites were then classified into four types based on the change rates of UIIs. A total of seven heritage sites were identified as exposed to risks due to urban sprawl and infrastructure expansion. The UII dataset can be combined with UNESCO’s periodic reports and site-specific data to provide valuable information for international communities to develop heritage preservation policies.

关键词： Urban sprawl cultural heritage sustainable development goals nighttime light

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Flow-Population Models for Tracking Non-Stationary Changes in Riparian and Aquatic Ecosystems

Flow-Population Models for Tracking Non-Stationary Changes i...

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作者： Lytle, D. A Olden, J. D Merritt, D. M Oregon State University Corvallis OR STRATEGIC ENVIRONMENTAL RESEARCH AND DEVELOPMENT PROGRAM ALEXANDRIA VA Strategic Environmental Research Development Program Alexandria VA

Climate change is expected to alter temperature and precipitation patterns on military lands throughout the western U.S., and this will alter the timing, frequency, and magnitude of flood and drought events. These changes in streamflow regime will directly affect populations of aquatic organisms (fish, aquatic invertebrates, riparian vegetation)and indirectly affect stream-dependent birds, reptiles, and mammals, including federally threatened and endangered species and other at-risk species. Although climate models as drivers of hydrologic models are becoming increasingly sophisticated in their ability to enable forecasting changes in streamflow regime at small spatial scales (e.g., <144 km2),current species population models do not accommodate the non-stationary effects that shifting flow regimes can exert on population trajectories and viability. Thus, a critical gap remains between our ability to model how climate change will alter streamflow regimes and our ability to predict how these changes will impact management-sensitive aquatic and riparian organisms. The objective of this proposal is to fill this knowledge gap by designing, testing, and implementing flow-population models that integrate nonstationary flow regime dynamics with quantitative population models to forecast potential impacts on aquatic and riparian taxa.

关键词： Fish Habitats Wildlife Birds Eutrophication Fisheries Geography Environmental protection Topography

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The Use of Bromeliads as Biomonitors of Air Quality: A Global Review

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International Journal of Forestry research 2024年第1期2024卷 6677068-6677068页

作者： Benítez, Ángel Montaño, Luis Abas, Azlan Cabrera, Omar Torracchi-Carrasco, Esteban Environmental Management School Technical University of Loja Particular Biodiversity of Tropical Ecosystems BIETROP Research Group Department of Biological and Agricultural Sciences Technical University of Loja Particular Centre for Research in Development Social and Environment (SEEDS) Faculty of Social Sciences and Humanities Universiti Kebangsaan Malaysia Dentistry Program The Center for Research Innovation and Technology Transfer (CIITT) The Catholic University of Cuenca Laboratory of Computational Calculus Modeling and Data Analytics (C2MAD)

Air pollution is a global problem in urban and rural areas, mainly related to vehicular traffic and industrial activities. Bromeliads have been widely used globally for active and passive air quality monitoring. However, a systematic review to facilitate the access and analysis of this information is yet to be made available. The objective of this work was to systematically review the use of bromeliads in biomonitoring of the air quality from articles published between 1990 and 2023 to analyze the progress and impact of the research related to the type of monitoring, species used, pollutants measured, and sampling protocols. The search was carried out in global (Scopus, ISI Web of Science, ScienceDirect, and MDPI) and regional (SciELO and Redalyc) databases with a total of 60 scientific articles, where the neotropical region with 31 articles and the Nearctic region with 11 articles were the most influential regions. In addition, more than 90% of the research has been published in high-impact journals (quartile 1). Passive monitoring registered 25 articles compared to active monitoring with 23, with 23 species of the family Bromeliaceae, predominantly the genus Tillandsia. Tillandsia usneoides was the most common species used in active monitoring, while Tillandsia recurvata was used for passive monitoring. The measurement of heavy metals was the preferred technique (93% of the studies) for air quality monitoring, where Zn, Fe, Pb, Cr, and Mn and the nonessential elements K, Ca, and Na were the most measured. Results obtained by different research groups cannot be compared directly because different methodologies have been used, highlighting the importance of standardized techniques for future work. Thus, as a contribution in this direction, we propose a protocol to facilitate or standardize the selection of the proper methodology for developing air quality monitoring using bromeliads. © 2024 Ángel Benítez et al.

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Correction: Chromatin profile-based identification of a novel ER-positive breast cancer subgroup with reduced ER-responsive element accessibility

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British journal of cancer 2023年第7期128卷 1400-1404页

作者： Kohei Kumegawa Sumito Saeki Yoko Takahashi Liying Yang Tomo Osako Tomoyoshi Nakadai Sayuri Amino Tetsuyo Maeda Chikako Takahata Seiichi Mori Tetsuo Noda Shinji Ohno Takayuki Ueno Reo Maruyama Cancer Cell Diversity Project NEXT-Ganken Program Japanese Foundation for Cancer Research Tokyo Japan. Breast Surgical Oncology Breast Oncology Center Cancer Institute Hospital Japanese Foundation for Cancer Research Tokyo Japan. Project for Cancer Epigenomics Cancer Institute Japanese Foundation for Cancer Research Tokyo Japan. Division of Pathology Cancer Institute Japanese Foundation for Cancer Research Tokyo Japan. Project for Development of Innovative Research on Cancer Therapeutics Cancer Precision Medicine Center Japanese Foundation for Cancer Research Tokyo Japan. Director's room Cancer Institute Japanese Foundation for Cancer Research Tokyo Japan. Breast Oncology Center Cancer Institute Hospital Japanese Foundation for Cancer Research Tokyo Japan. Cancer Cell Diversity Project NEXT-Ganken Program Japanese Foundation for Cancer Research Tokyo Japan. reo.maruyama@jfcr.or.jp. Project for Cancer Epigenomics Cancer Institute Japanese Foundation for Cancer Research Tokyo Japan. reo.maruyama@jfcr.or.jp.

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Learning Multi-cellular Representations of Single-Cell Transcriptomics Data Enables Characterization of Patient-Level Disease States 29th

Learning Multi-cellular Representations of Single-Cell Tran...

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29th International Conference on research in Computational Molecular Biology, RECOMB 2025

作者： Liu, Tianyu De Brouwer, Edward Kuo, Tony Diamant, Nathaniel Missarova, Alsu Wang, Hanchen Hao, Minsheng Bravo, Hector Corrada Scalia, Gabriele Regev, Aviv Heimberg, Graham Research and Early Development Genentech South San FranciscoCA94080 United States Interdepartmental Program in Computational Biology and Bioinformatics Yale University New HavenCT06511 United States Roche Informatics F. Hoffmann-La Roche Ltd. Mississauga Canada Department of Computer Science Stanford University Palo AltoCA94035 United States

ISBN: (纸本)9783031902512

Single-cell RNA-seq (scRNA-seq) has become a prominent tool for studying human biology and disease. The availability of massive scRNA-seq datasets and advanced machine learning techniques has recently driven the development of single-cell foundation models that provide informative and versatile cell representations based on expression profiles. However, to understand disease states, we need to consider entire tissue ecosystems, simultaneously considering many different interacting cells. Here, we tackle this challenge by generating patient-level representations derived from multi-cellular expression context measured with scRNA-seq of tissues. We develop PaSCient, a novel model that employs a multi-level representation learning paradigm and provides importance scores at the individual cell and gene levels for fine-grained analysis across multiple cell types and gene programs characteristic of a given disease. We apply PaSCient to learn a disease model across a large-scale scRNA-seq atlas of 12.5 million cells from over 2,700 patients. Comprehensive and rigorous benchmarking demonstrates the superiority of PaSCient in disease classification and its multiple downstream applications, including dimensionality reduction, gene/cell type prioritization, and patient subgroup discovery. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Biomolecules

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Artificial Intelligence Driven Multivariate Time Series Analysis of Network Traffic Prediction

Artificial Intelligence Driven Multivariate Time Series Anal...

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Innovations in Intelligent Systems and Applications Conference

作者： Gözde Filiz Ayşenur Yıldiz Erkan Kara Suat Altıntaş Tuna Çakar Computer Sci. & Eng. PhD. Program MEF University Istanbul Turkey Research and Development Andromeda TV Digital Plat. Op. Inc. Istanbul Turkey IT Sytems and Network Andromeda TV Digital Plat. Op. Inc. Istanbul Turkey Computer Engineering MEF University Istanbul Turkey

ISBN: (数字)9798350379433

ISBN: (纸本)9798350379440

The primary objective of this research is to employ artificial intelligence, machine learning, and neural networks in order to construct a network traffic prediction model. The analysis of network traffic data obtained from a digital media and entertainment provider operating in Turkey is conducted through the application of multivariate time-series analysis techniques in order to get insights into the temporal patterns and trends. In model development, Vector Autoregression (VAR), Vector Error Correction Model (VECM), Long-Short Term Memory (LSTM), and Gated Recurrent Unit (GRU) algorithms have been utilized. LSTM and GRU models have performed better with low Mean Absolute Percentage Error (MAPE) and high R-squared Score (R 2 ). LSTM model has reached 0.98 R2 and 8.95% MAPE. These results indicate that the models can be utilized in network management optimization as resource allocation, congestion detection, anomaly detection, and quality of service.

关键词： Technological innovation Reactive power Time series analysis Telecommunication traffic Quality of service Predictive models Vectors Resource management Long short term memory Optimization

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The Fate of 17β-Estradiol in Snowmelt from a Field with a History of Manure Application: A Laboratory Simulation and Field Study

SSRN

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SSRN 2024年

作者： Soto, Haven S.J.S. Amarakoon, Inoka D. Casson, Nora J. Kumaragamage, Darshani Wilson, Henry F. Master of Environmental and Social Change Program The University of Winnipeg WinnipegMB Canada Department of Soil Science The University of Manitoba WinnipegMB Canada Department of Geography The University of Winnipeg WinnipegMB Canada Department of Environmental Studies and Sciences The University of Winnipeg Manitoba Canada Agriculture and Agri-Food Canada Brandon Research and Development Centre BrandonMB Canada

17β-estradiol is a naturally occurring estrogen, and livestock manure applied to agricultural fields is a major source of environmental estrogens. Liquid swine manure is widely applied to agricultural fields in the Canadian Prairies, a region where the majority of the annual runoff occurs during a brief snowmelt period over frozen soil. Transport of estrogens during this important hydrological period is not well understood but is critical to mitigating the snowmelt-driven offsite transport of estrogens. This study quantified the concentration and load of 17β-estradiol in snowmelt from an agricultural field with a history of manure application under manure application methods: no manure applied, manure applied on the sub-surface, and on the surface, using a laboratory simulation study with flooded intact soil cores and a field study during snowmelt. A higher concentration of 17β-estradiol was in the laboratory simulation than in the field (mean laboratory pore water = 1.65 ± 1.2 μg/L;mean laboratory flood water = 0.488 ± 0.58 μg/L;and mean field snowmelt = 0.0619 ± 0.048 μg/L). There were no significant differences among manure application methods for 17β-estradiol concentration. Laboratory pore water concentrations significantly increased over time, corresponding with changes in pH. In contrast, there was no significant change in the field snowmelt concentrations of 17β-estradiol over time. However, for both laboratory simulation experiments and field-based snowmelt experiments, mean concentrations of 17β-estradiol were higher with subsurface than surface-applied manure, and the cumulative load of 17β-estradiol was significantly higher in the sub-surface than in surface applied. The mean cumulative load from the field study across all treatments (6.91 ± 3.7 ng/m2) approximates the magnitude of 17β-estradiol that could be mobilized from manured fields. The sub-surface application of manure seems to increase the persistence of 17β-estradiol in soil, thus enhancing the

关键词： Manures

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Thermal Management of Photovoltaic Module Using Affordable Organic Phase Change Material Combined with Nano Metal Oxide Particles Enhancer

SSRN

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SSRN 2024年

作者： Phukaokaew, Wisanu Suksri, Amnart Punyawudho, Konlayutt Wongwuttanasatian, Tanakorn Energy Engineering Program Faculty of Engineering Khon Kaen University Thailand Electrical Engineering Division Faculty of Engineering Khon Kaen University Thailand Department of Mechanical Engineering Faculty of Engineering Chiang Mai University Thailand Mechanical Engineering Division Faculty of Engineering Khon Kaen University Thailand Centre for Alternative Energy Research and Development Khon Kaen University Thailand

The utilization of cooling systems based on phase change materials has experienced a surge in popularity due to their ability to effectively reduce the temperature of photovoltaic (PV) modules. Phase change materials (PCMs) have been widely recognized as a highly efficient medium for thermal energy storage due to their ability to harness latent heat capacity. The low thermal conductivity of the material has been identified in many studies. In the current investigation, we have blended PCM with nanoparticles to enhance its thermal conductivity and electrical efficiency. We produce nanoparticle composited phase change materials (nc-PCMs) by combining lauric acid (LA) with three different nanoparticles: aluminum oxide (Al2O3), copper oxide (CuO), and magnesium oxide (MgO), in an optimal weight proportion of 94: 6. Lauric acid and these nanoparticles are chosen based on their ability to provide a significantly lower cost compared to commercial nanoparticles. research has demonstrated that the incorporation of nanoparticles increases thermal conductivity, resulting in a decrease in the PV module's temperature. The findings indicate that a combination of LA and MgO in a proportion of 94: 6 constitutes the optimal nc-PCM. This composition demonstrated a 5.2 °C reduction in PV module temperature, which resulted in a notable enhancement in the average electrical efficiency of 14.11%. Furthermore, the power output increased significantly to 14.18%. © 2024, The Authors. All rights reserved.

关键词： Aluminum oxide

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Unusual clinical presentation of oral pyogenic granuloma with severe alveolar bone loss:A case report and review of literature

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World Journal of Clinical Cases 2023年第16期11卷 3907-3914页

作者： Sarah Monserrat LomelíMartínez Dennisse Bocanegra Morando Ana Esther Mercado González Juan Ramón Gómez Sandoval Department of Medical and Life Sciences Centro Universitario de la CiénegaUniversidad de GuadalajaraOcotlán 47810Mexico Master of Public Health Department of Wellbeing and Sustainable DevelopmentCentro Universitario del NorteUniversidad de GuadalajaraColotlán 46200Mexico Periodontics Program Department of Integrated Dentistry ClinicsCentro Universitario de Ciencias de la SaludGuadalajara 44340Mexico Antiguo Hospital Civil de Guadalajara“Fray Antonio Alcalde” Guadalajara 44280Mexico Research Institute of Dentistry Department of Integrated Dentistry ClinicsCentro Universitario de Ciencias de la SaludUniversidad de GuadalajaraGuadalajara 44340Mexico

BACKGROUND Pyogenic granuloma(PG)is a localized,reddish and vascularized hyperplastic lesion of the connective tissue which occurs in the oral *** most cases,the presence of this lesion does not show alveolar bone *** pathology is diagnosed clinically with some ***,the diagnosis and treatment are usually corroborated with histopathological *** SUMMARY Three clinical cases of PG associated with bone loss were described in this *** three patients presented tumor-like growth which bled on touch,and were associated with local irritant *** showed bone *** cases were treated with conservative surgical *** scarring was satisfactory,and there was no case of *** diagnoses were based on clinical findings,and were confirmed *** The occurrence of oral PG with bone loss is ***,clinical and radiographic evaluations are important for the diagnosis.

关键词： Hyperplastic lesion Pyogenic granuloma Alveolar bone loss Case report

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Comparison of Lexical Alignment with a Teachable Robot in Human-Robot and Human-Human-Robot Interactions

arXiv

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arXiv 2022年

作者： Asano, Yuya Litman, Diane Yu, Mingzhi Lobczowski, Nikki Nokes-Malach, Timothy Kovashka, Adriana Walker, Erin Intelligent Systems Program University of Pittsburgh United States Department of Computer Science University of Pittsburgh United States Learning Research and Development Center University of Pittsburgh United States Department of Psychology University of Pittsburgh United States

Speakers build rapport in the process of aligning conversational behaviors with each other. Rapport engendered with a teachable agent while instructing domain material has been shown to promote learning. Past work on lexical alignment in the field of education suffers from limitations in both the measures used to quantify alignment and the types of interactions in which alignment with agents has been studied. In this paper, we apply alignment measures based on a data-driven notion of shared expressions (possibly composed of multiple words) and compare alignment in one-on-one human-robot (H-R) interactions with the H-R portions of collaborative human-human-robot (H-H-R) interactions. We find that students in the H-R setting align with a teachable robot more than in the H-H-R setting and that the relationship between lexical alignment and rapport is more complex than what is predicted by previous theoretical and empirical work. © 2022, CC BY.

关键词： Alignment

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