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Assessing The Monetary Value Of Ecosystem Services Provided By Gaung – Batang Tuaka Peat Hydrological Unit (Khg), Riau Province

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Heliyon 2021年第10期7卷 e08208页

作者： Rossita, Annuri Nurrochmat, Dodik Ridho Boer, Rizaldi Hein, Lars Riqqi, Akhmad Applied Climatology Study Program The Graduate School Of Ipb University Bogor Indonesia Center For Climate Risk And Opportunity Management In South East Asia And Pacific (Ccrom-Seap) Ipb University Bogor Indonesia Department Of Forest Management Faculty Of Forestry And Environment Ipb University Bogor 16680 Indonesia Environmental Science Analysis Group Wageningen University and Research Wageningen Netherlands Faculty of Earth Science and Technology Bandung Institute of Technology (ITB) Indonesia

Peatland Plays A Pivotal Role In Providing Natural Resource Production And Environmental Services For Human Welfare. However, Many Studies Have Mentioned The Impact Of Dryland Cultivation In Peatland On The Shifting Carbon Balance In The Ecosystem That Clearly Will Alter The Interaction Of These Two Ecosystem Services. The Goal Of This Study, Conducted Under The Framework Of The System Of Environmental-Economic Accounting (Seea) Was To Monetary Value The Ecosystem Services (Es) Of Provisioning And Carbon Regulating Services Of The Gaung-Batang Tuaka Peat Hydrological Unit (Khg). We Focused On Khg In Response To Regulation No.57/2016, Which Highlights Ecosystem Boundary As A New Basis For Peatland Management. Under The Seea Framework, Ecosystem Services Become A Benefit When Utilized By Ecosystem Beneficiaries. In This Case, Provisioning Services Will Be Valued Only For Cultivated Land, While Carbon Services Calculated For The Entire Study Area (Global Beneficiaries). Our Study Showed That The Provisioning Services And Carbon Services Are Under The Trade-Off Condition, Where The Monetary Value Of Provisioning Services Increased At A Slower Rate (0.50 Million Usd Annually) Than The Monetary Loss Of The Benefit Of Carbon Services (5.28 Million Usd Annually), Greatly Exceeded The Monetary Value Of Provisioning Services. We Highlight Two Main Strategies To Increase The Monetary Value Of The Khg Towards A Synergy Condition, Namely Increased Value-Added By Reducing The Productivity Gap Among Es Beneficiaries And Large-Scale Adoption Of A Profitable Cultivation System With Minimum Peat Disturbance. The Main Enablers Required Include Financing Access And Incentives (E.G., Reduce Tax) And Disincentives To Allow For Peat-Adaptive Commodities To Compete With Dryland Commodities In The Future Market © 2021 The Authors. Published by Elsevier Ltd

关键词： Ecosystem Services Monetary Value Peat Hydrological Unit Peatland Management Riau

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Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach

arXiv

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arXiv 2020年

作者： Liu, Yi Garg, Sahil Nie, Jiangtian Zhang, Yang Xiong, Zehui Kang, Jiawen Shamim Hossain, M. School of Data Science and Technology Heilongjiang University Harbin China Electrical Engineering Department École de technologie supérieure Uni-versité du Québec Montréal Canada Energy Research Institute Interdisciplinary Graduate Programme School of Computer Science and Engineering Nanyang Technological University Singapore Singapore Hubei Key Laboratory of Transportation Internet of Things School of Computer Science and Technology Wuhan University of Technology China Alibaba-NTU Joint Research Institute School of Computer Science and Engineering NTU Singapore Singapore Energy Research Institute Nanyang Technological University Singapore Department of Software Engineering College of Computer and Information Sciences King Saud University Saudi Arabia

Since edge device failures (i.e., anomalies) seriously affect the production of industrial products in Industrial IoT (IIoT), accurately and timely detecting anomalies is becoming increasingly important. Furthermore, data collected by the edge device may contain the user’s private data, which is challenging the current detection approaches as user privacy is calling for the public concern in recent years. With this focus, this paper proposes a new communication-efficient on-device federated learning (FL)-based deep anomaly detection framework for sensing time-series data in IIoT. Specifically, we first introduce a FL framework to enable decentralized edge devices to collaboratively train an anomaly detection model, which can improve its generalization ability. Second, we propose an Attention Mechanism-based Convolutional Neural Network-Long Short Term Memory (AMCNN-LSTM) model to accurately detect anomalies. The AMCNN-LSTM model uses attention mechanism-based CNN units to capture important fine-grained features, thereby preventing memory loss and gradient dispersion problems. Furthermore, this model retains the advantages of LSTM unit in predicting time series data. Third, to adapt the proposed framework to the timeliness of industrial anomaly detection, we propose a gradient compression mechanism based on Top-k selection to improve communication efficiency. Extensive experiment studies on four real-world datasets demonstrate that the proposed framework can accurately and timely detect anomalies and also reduce the communication overhead by 50% compared to the federated learning framework that does not use gradient compression scheme. Copyright © 2020, The Authors. All rights reserved.

关键词： Anomaly detection

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Effects of galaxy environment on merger fraction?

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Astronomy and Astrophysics 2024年 686卷

作者： Pearson, W.J. Santos, D.J.D. Goto, T. Huang, T.-C. Kim, S.J. Matsuhara, H. Pollo, A. Ho, S.C.-C. Hwang, H.S. Malek, K. Nakagawa, T. Romano, M. Serjeant, S. Suelves, L.E. Shim, H. White, G.J. National Centre for Nuclear Research Pasteura 7 Warszawa02-093 Poland Max Planck Institute for Extraterrestrial Physics Gießenbachstraße 1 Garching85748 Germany Institute of Astronomy National Tsing Hua University 101 Section 2. Kuang-Fu Road Hsinchu30013 Taiwan Department of Space and Astronautical Science Graduate University for Advanced Studies SOKENDAI Shonankokusaimura Hayama Miura District Kanagawa240-0193 Japan Institute of Space and Astronautical Science Japan Aerospace Exploration Agency 3-1-1 Yoshinodai Chuo-ku Kanagawa Sagamihara252-5210 Japan Research School of Astronomy and Astrophysics The Australian National University CanberraACT2611 Australia Centre for Astrophysics and Supercomputing Swinburne University of Technology PO Box 218 HawthornVIC3122 Australia OzGrav The Australian Research Council Centre of Excellence for Gravitational Wave Discovery HawthornVIC3122 Australia ASTRO3D The Australian Research Council Centre of Excellence for All-sky Astrophysics in 3D CanberraACT2611 Australia Astronomy Program Department of Physics and Astronomy Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of SNU Astronomy Research Center Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of INAF – Osservatorio Astronomico di Padova Vicolo dell’Osservatorio 5 Padova35122 Italy School of Physical Sciences The Open University Walton Hall Milton KeynesMK7 6AA United Kingdom Department of Earth Science Education Kyungpook National University 80 Daehak-ro Buk-gu Daegu41566 Korea Republic of Space Science and Technology Division RALSpace STFC Rutherford Appleton Laboratory Chilton DidcotOX11 0QX United Kingdom

Aims. In this work we examine how environment influences the merger fraction, from the low density field environment to higher density groups and clusters. We also study how the properties of a group or cluster, as well as the position of a galaxy in the group or cluster, influences the merger fraction. Methods. We identified galaxy groups and clusters in the North Ecliptic Pole using a friends-of-friends algorithm and the local density. Once identified, we determined the central galaxies, group radii, velocity dispersions, and group masses of these groups and clusters. Merging systems were identified with a neural network as well as visually. With these identifications and properties of groups and clusters and merging galaxy identifications, we examined how the merger fraction changes as the local density changes for all galaxies as well as how the merger fraction changes as the properties of the groups or clusters change. Results. We find that the merger fraction increases as local density increases and decreases as the velocity dispersion increases, as is often found in the literature. A decrease in merger fraction as the group mass increases is also found. We also find that groups with larger radii have higher merger fractions. The number of galaxies in a group does not influence the merger fraction. Conclusions. The decrease in merger fraction as group mass increases is a result of the link between group mass and velocity dispersion. Hence, this decrease in merger fraction with increasing mass is a result of the decrease of merger fraction with velocity dispersion. The increasing relation between group radii and merger fraction may be a result of larger groups having smaller velocity dispersion at a larger distance from the centre or larger groups hosting smaller, infalling groups with more mergers. However, we do not find evidence of smaller groups having higher merger fractions. c The Authors 2024.

关键词： Galaxies

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Developing Feasible Search Approach for Tackling Large Vehicle Routing Problem with Time Window Considering Service Disruption 1

Developing Feasible Search Approach for Tackling Large Vehic...

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1st International Conference on computer science and Applied Mathematic, ICCSAM 2018

作者： Susilawati, Enny Mawengkang, Herman Opim, S. Sitompul Sutarman Graduate School of Mathematics University of Sumatera Utara Medan Indonesia Department of Mathematics University of Sumatera Utara Medan Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

In logistic system, a Vehicle Routing Problem with time windows (VRPTW) is defined as a problem to decide the optimal set of logistic routes used by homogeny vehicles to deliver customers' demand within scheduled service time. The objective is to minimize the total travel cost (related to the travel times or distances) and operational cost (related to the number of vehicles used). In this paper we address a variant of the VRPTW in which the time to deliver and the time departing from a customer are restricted. The problem also include service disruption. We use integer programming model to describe the problem. A feasible neighbourhood approach is proposed to solve the model. © Published under licence by IOP Publishing Ltd.

关键词： Travel time

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A land-neutral expansion of Brazilian renewable fuel production

Research Square

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Research Square 2021年

作者： Camargo, Luis Ramirez Castro, Gabriel Gruber, Katharina Jewell, Jessica Klingler, Michael Turkovska, Olga Wetterlund, Elisabeth Schmidt, Johannes Institute for Sustainable Economic Development University of Natural Resources and Life Science Vienna Austria Department of Electrical Engineering and Energy Technology Vrije Universiteit Brussel Brussels Belgium Flanders Make Heverlee3001 Belgium Energy Planning Program Graduate School of Engineering Federal University of Rio de Janeiro Rio de Janeiro Brazil Department of Space Earth and Environment Chalmers University of Technology Sweden Department of Geography University of Innsbruck Innsbruck Austria Energy Engineering Division of Energy Science Luleå University of Technology Luleå971 87 Sweden LaxenburgA-2361 Austria

Biofuels are currently the only available bulk renewable fuel. They have, however, limited expansion potential due to high land requirements and associated risks for biodiversity, food security, and land conflicts. We therefore propose to increase output from ethanol refineries in a land-neutral methanol pathway: surplus CO2-streams from fermentation are combined with hydrogen from renewably powered electrolysis to synthesize methanol. We illustrate this pathway with the Brazilian sugarcane ethanol industry using a spatio-temporal model. The fuel output of existing ethanol generation facilities can be increased by 42%-49% or ∼100TWh without using additional land. This amount is sufficient to cover projected growth in Brazilian biofuel demand in 2030. We identify a trade-off between renewable energy generation technologies: wind power requires the least amount of land whereas a mix of wind and solar costs the least. In the cheapest scenario, green methanol is competitive to fossil methanol at a carbon price of 80C/tCO2 © 2021, CC BY.

关键词： Methanol

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Optimization Model for a Location-Allocation-Routing in a Periodic Distribution Network 1

Optimization Model for a Location-Allocation-Routing in a Pe...

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1st International Conference on computer science and Applied Mathematic, ICCSAM 2018

作者： Panjaitan, Dedy Juliandri Suwilo, Saib Opim, S. Sitompul Sawaluddin Graduate School of Mathematics Universitas Sumatera Utara Medan Indonesia Department of Mathematics Universitas Sumatera Utara Medan Indonesia Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan Indonesia

The main concern of this paper is to decide the locations and allocations of facilities that impact not only the profitability of an organization but the fast ability to serve customers. Generally the location-routing problem is to minimize the overall cost by simultaneously selecting a subset of candidate facilities and constructing a set of delivery routes that satisfy some restrictions. In this paper we consider the periodic routing of vehicle to be used to distribute goods. Integer programming model is built to solve the problem. A feasible neighbourhood search is developed to solve the result model. © Published under licence by IOP Publishing Ltd.

关键词： Integer programming

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Microendoscopy for periodic intravital end-to-end tumor imaging of cancer cells

Cell reports methods

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Cell reports methods 2025年第6期5卷 101056页

作者： Toshiyuki Goto Masayuki Nakano Sally Danno Chie Ueda Asako Sakaue-Sawano Atsushi Miyawaki Anna Wrabel Ichiro Nakahara Takahito Nishikata Akira Mizoguchi Yasuhisa Tamura Kei Mizuno Yosky Kataoka Kazuo Funabiki RIKEN Center for Biosystems Dynamics Research Kobe Hyogo 650-0047 Japan Frontiers of Innovative Research in Science and Technology (FIRST) Konan University Kobe Hyogo 650-0047 Japan Graduate School of Science Technology and Innovation Kobe University Kobe Hyogo 650-0047 Japan. RIKEN Center for Biosystems Dynamics Research Kobe Hyogo 650-0047 Japan. RIKEN Center for Brain Science Wako Saitama 351-0198 Japan Biotechnological Optics Research Team RIKEN Center for Advanced Photonics Wako Saitama 351-0198 Japan. Frontiers of Innovative Research in Science and Technology (FIRST) Konan University Kobe Hyogo 650-0047 Japan. Graduate School of Medicine Mie University Tsu Mie 514-8507 Japan. Graduate School of Science Technology and Innovation Kobe University Kobe Hyogo 650-0047 Japan RIKEN-JEOL Collaboration Center RIKEN Baton Zone Program Kobe Hyogo 650-0047 Japan. Electronic address: kataokay@person.kobe-u.ac.jp. Foundation for Biomedical Research and Innovation Kobe Hyogo 650-0047 Japan. Electronic address: funabiki@ent.kuhp.kyoto-u.ac.jp.

The spatiotemporal heterogeneity in intratumor proliferative behavior of cancer cells deeply affects tumor environment characteristics and the efficacy of anticancer treatments. Thus, intravital imaging with unlimited imaging depth and cellular-level resolution is greatly desired. We developed an optical-fiber-bundle-based microendoscope with a genetically encoded fluorescent ubiquitination-based cell-cycle indicator (Fucci) system to achieve the intravital, periodic, and multicolor end-to-end imaging of the proliferative activity of cancer cells at a cellular-level resolution. This technique enabled the periodic visualization of spatiotemporal cellular responses, including cell-cycle arrest and resumption, and nuclear enlargement following the administration of anticancer drugs in living mice. It was suggested that proliferating cell ratio and nuclear enlargement in cancer cells at the surface region of tumor characterized by abundant vascular invasion contribute to aggressive tumor regrowth after chemotherapy. The application of this technique can accelerate innovation in cancer biology and therapeutics.

关键词： CP: cancer biology CP: imaging cancer environment chemotherapy in vivo imaging microendoscopy polyploid cancer cells

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PathOrchestra: A Comprehensive Foundation Model for Computational Pathology with Over 100 Diverse Clinical-Grade Tasks

arXiv

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arXiv 2025年

作者： Yan, Fang Wu, Jianfeng Li, Jiawen Wang, Wei Lu, Jiaxuan Chen, Wen Gao, Zizhao Li, Jianan Li, Heng Yan, Hong Ma, Jiabo Chen, Minda Lu, Yang Chen, Qing Wang, Yizhi Ling, Xitong Wang, Xuenian Wang, Zihan Huang, Qiang Hua, Shengyi Liu, Mianxin Ma, Lei Shen, Tian Zhang, Xiaofan He, Yonghong Chen, Hao Zhang, Shaoting Wang, Zhe Shanghai Artificial Intelligence Laboratory Shanghai200030 China State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers Department of Pathology School of Basic Medicine Xijing Hospital Fourth Military Medical University Xi’an710032 China Institute of Biopharmaceutical and Health Engineering Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Department of Pathology The First Affiliated Hospital of USTC Division of Life Sciences and Medicine University of Science and Technology of China Hefei230036 China Intelligent Pathology Institute Division of Life Sciences and Medicine University of Science and Technology of China Hefei230036 China SenseTime Research Shanghai200030 China Department of Computer Science and Engineering Department of Chemical and Biological Engineering Division of Life Science Hong Kong University of Science and Technology 999077 Hong Kong National Biomedical Imaging Center College of Future Technology Peking University Beijing100871 China Shengqiang Technology Co. Ltd. Longgang District Shenzhen518055 China Institute of Materials Research Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Qing Yuan Research Institute Shanghai Jiao Tong University Shanghai200240 China

The complexity and variability inherent in high-resolution pathological images present significant challenges in computational pathology. While pathology foundation models leveraging artificial intelligence (AI) have catalyzed transformative advancements, their development demands large-scale datasets, considerable storage capacity, and substantial computational resources. Furthermore, ensuring their clinical applicability and generalizability requires rigorous validation across a broad spectrum of clinical tasks. In this work, we present PathOrchestra, a versatile pathology foundation model trained via self-supervised learning on a dataset comprising 300K pathological slides (262.5 TB) from 20 tissue and organ types across multiple centers. The model was rigorously evaluated on 112 clinical tasks using a combination of 61 private and 51 public datasets. These tasks encompass digital slide preprocessing, pan-cancer classification, lesion identification, multi-cancer subtype classification, biomarker assessment, gene expression prediction, and the generation of structured reports. PathOrchestra demonstrated exceptional performance across 27,755 whole slide images (WSIs) and 9,415,729 region-of-interest (ROI) images, achieving over 0.950 accuracy in 47 tasks, including pan-cancer classification across various organs, lymphoma subtype diagnosis, and bladder cancer screening. Notably, it is the first model to generate structured reports for high-incidence colorectal cancer and diagnostically complex lymphoma—areas that are infrequently addressed by foundational models but hold immense clinical potential. Overall, PathOrchestra exemplifies the feasibility and efficacy of a large-scale, self-supervised pathology foundation model, validated across a broad range of clinical-grade tasks. Its high accuracy and reduced reliance on extensive data annotation underline its potential for clinical integration, offering a pathway toward more efficient and high-quality medical servic

关键词： Supervised learning

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Why do masked neural language models still need common sense knowledge?

arXiv

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arXiv 2019年

作者： Kwon, Sunjae Kang, Cheongwoong Han, Jiyeon Choi, Jaesik Graduate School of Artificial Intelligence Korea Advanced Institute of Science and Technology School of Electrical & Computer Engineering Ulsan National Institute of Science and Technology

Currently, contextualized word representations are learned by intricate neural network models, such as masked neural language models (MNLMs). The new representations significantly enhanced the performance in automated question answering by reading paragraphs. However, identifying the detailed knowledge trained in the MNLMs is difficult owing to numerous and intermingled parameters. This paper provides empirical but insightful analyses on the pretrained MNLMs with respect to common sense knowledge. First, we propose a test that measures what types of common sense knowledge do pretrained MNLMs understand. From the test, we observed that MNLMs partially understand various types of common sense knowledge but do not accurately understand the semantic meaning of relations. In addition, based on the difficulty of the question answering task problems, we observed that pretrained MLM-based models are still vulnerable to problems that require common sense knowledge. We also experimentally demonstrated that we can elevate existing MNLM-based models by combining knowledge from an external common sense repository. Copyright © 2019, The Authors. All rights reserved.

关键词： Semantics

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Quantum Contextuality Requires Counterfactual Gain

arXiv

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arXiv 2025年

作者： Sagawa, Yuki Hance, Jonte R. Hofmann, Holger F. Ono, Takafumi Program in Advanced Materials Science Faculty of Engineering and Design Kagawa University 2217-20 Hayashi-cho Kagawa Takamatsu761-0396 Japan School of Computing Newcastle University 1 Science Square Newcastle upon TyneNE4 5TG United Kingdom Quantum Engineering Technology Laboratories Department of Electrical and Electronic Engineering University of Bristol Woodland Road BristolBS8 1US United Kingdom Department of Quantum Matter Graduate School of Advanced Science and Engineering Hiroshima University Kagamiyama 1-3-1 Higashi Hiroshima739-8530 Japan

Quantum contextuality, where measurement outcomes depend on the measurement context, implies a failure of classical realism in quantum systems. As recently shown, the transition between measurement contexts can be mapped onto the path that a quantum particle takes through an interferometer. Here, we investigate the relation between contextuality and the counterfactual gain observed in the output ports of such an interferometer when one of the paths is blocked. It is shown that experimental evidence of contextuality can only be obtained when counterfactual gain is observed for a specific combination of blocked path and output port. Using a silicon photonic integrated circuit, we experimentally observe the counterfactual gain for a selection of input states and evaluate the associated evidence for contextuality. The results confirm that contextuality can only be observed in the presence of counterfactual gain. Copyright © 2025, The Authors. All rights reserved.

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