Issues related to the impact of ChatGPT-like artificial intelligence generated content (AIGC) and artificial general intelligence (AGI) technologies on medicine and medicare have been presented and ...discussed. We believe that advances in medical foundation models, scenarios engineering, and medical operations with operating systems would lead to parallel doctors in parallel hospitals, i.e., digital, robotic, and human doctors working in parallel within cyber-physical-social spaces under three modes: autonomous, parallel, and expert/emergency operations. Under decentralized/distributed autonomous organizations/operations (DAO) and DeSci, as well as DeMed and DeHospitals, the vision for individual patients with her/his personalized digital hospital could be a reality in the future.
This paper proposes the concept of digital doctors and their roles in parallel healthcare for the digital transformation of medical services based on atificial intelligence and intelligent ...technology. By integrating complexity medicine, transdisciplinary medicine, and systematized intelligent medicine, we outline an ACP-based parallel healthcare and federated hospitals for preventive, proactive, precise, and personalized medical services.
A Security and Privacy Review of VANETs Qu, Fengzhong; Wu, Zhihui; Wang, Feiyue ...
IEEE transactions on intelligent transportation systems,
12/2015, Volume:
16, Issue:
6
Journal Article
Peer reviewed
Vehicular ad hoc networks (VANETs) have stimulated interest in both academic and industry settings because, once deployed, they would bring a new driving experience to drivers. However, communicating ...in an open-access environment makes security and privacy issues a real challenge, which may affect the large-scale deployment of VANETs. Researchers have proposed many solutions to these issues. We start this paper by providing background information of VANETs and classifying security threats that challenge VANETs. After clarifying the requirements that the proposed solutions to security and privacy problems in VANETs should meet, on the one hand, we present the general secure process and point out authentication methods involved in these processes. Detailed survey of these authentication algorithms followed by discussions comes afterward. On the other hand, privacy preserving methods are reviewed, and the tradeoff between security and privacy is discussed. Finally, we provide an outlook on how to detect and revoke malicious nodes more efficiently and challenges that have yet been solved.
Due to the advantages of small size, lightweight, and simple operation, the unmanned aerial vehicle (UAV) has been widely used, and it is also becoming increasingly convenient to capture ...high-resolution aerial images in a variety of environments. Existing target-detection methods for UAV aerial images lack outstanding performance in the face of challenges such as small targets, dense arrangement, sparse distribution, and a complex background. In response to the above problems, some improvements on the basis of YOLOv5l have been made by us. Specifically, three feature-extraction modules are proposed, using asymmetric convolutions. They are named the Asymmetric ResNet (ASResNet) module, Asymmetric Enhanced Feature Extraction (AEFE) module, and Asymmetric Res2Net (ASRes2Net) module, respectively. According to the respective characteristics of the above three modules, the residual blocks in different positions in the backbone of YOLOv5 were replaced accordingly. An Improved Efficient Channel Attention (IECA) module was added after Focus, and Group Spatial Pyramid Pooling (GSPP) was used to replace the Spatial Pyramid Pooling (SPP) module. In addition, the K-Means++ algorithm was used to obtain more accurate anchor boxes, and the new EIOU-NMS method was used to improve the postprocessing ability of the model. Finally, ablation experiments, comparative experiments, and visualization of results were performed on five datasets, namely CIFAR-10, PASCAL VOC, VEDAI, VisDrone 2019, and Forklift. The effectiveness of the improved strategies and the superiority of the proposed method (YOLO-UAV) were verified. Compared with YOLOv5l, the backbone of the proposed method increased the top-one accuracy of the classification task by 7.20% on the CIFAR-10 dataset. The mean average precision (mAP) of the proposed method on the four object-detection datasets was improved by 5.39%, 5.79%, 4.46%, and 8.90%, respectively.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
•Index system for evaluating multiscale comprehensive carrying capacity is built.•Multiscale assessment is applied in China’s YREB region.•Multiscale disparity of comprehensive carrying capacity is ...quantified.•Specific contributions to the total disparity are investigated.•Spatial pattern of urban comprehensive carrying capacity is analyzed.
Exploring and revealing the comprehensive carrying capacity is a critical barometer and benchmark for multiregional sustainable development. Using a typical multiscale region moving forward on a green development demonstration belt (China’ s Yangtze River Economic Belt) as a case study, the multiscale disparity of comprehensive carrying capacity during the period 2005–2019 is presented after a comprehensive assessment of multiscale carrying capacity level. Some convergence models, covering δ-convergence, absolute β-convergence, and conditional β-convergence, are constructed to test the disparity of urban comprehensive carrying capacity. Furthermore, the multiscale disparity of comprehensive carrying capacity is quantified when the decomposition model is used to determine the specific contributions to total disparity (from inter-urban agglomerations or intra-urban agglomeration), and then the spatial aggregation effect of urban comprehensive carrying capacity is analyzed. The results highlight that: YREB’s comprehensive carrying capacity is gradually improving whether at the scale of upper, middle, lower reaches, or the whole; there is an obvious inter-city disparity of comprehensive carrying capacity from the results of conditional β-convergence; the further conditional β-convergence tells that urban ecological and sustainable management and its stakeholder engagements should begin with the sufficient eco-environment endowment, good transportation system, well-reconstructed market environment, and the healthy economic structure or benefit; the disparity from the lower reaches is greater than that from the middle and upper reaches when the specific disparity from intra-low reaches plays a significant role, and there is a spatial aggregation effect of urban carrying capacity in the study area. Future policies and regulatory decisions must address such multiregional disparities to foster sustainable development based on the “equity and efficiency” philosophy.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Sediment contamination remains a global problem, particularly in transitional waters such as estuaries and coastal lagoons, which are the recipients of chemicals from multiple near- and far-field ...sources. Although transitional waters are highly productive ecosystems, approaches for assessing and managing their sediment contamination are not as well developed as in marine and fresh waters. Further, although transitional waters remain defined by their variable and unique natural water quality characteristics, particularly salinity, the biota inhabiting such ecosystems, once thought to be defined by Remane's “paradox of brackish water”, are being redefined. The purpose of the present paper is to build on an earlier but now dated (>12years old) review of methods to assess sediment contamination in estuaries, extending this to all transitional waters, including information on integrative assessments and on management decision-making. The following are specifically discussed: chemical assessments; bioindicators; biomarkers; and, biological surveys. Assessment and management of sediment contamination in transitional waters need to be focused on ecosystem services and, where appropriate and possible, be proactive rather than reactive when uncertainty has been suitably reduced.
•Transitional waters (estuaries, lagoons) are highly productive ecosystems.•Sediment contamination from direct and indirect sources is a continuing issue.•We review the state-of-the art of transitional-water-specific assessment and management of sediment contamination.•We focus on chemical assessments, bioindicators, biomarkers, and biological surveys.•We emphasize the importance of integrative assessments and ecosystem services.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Volcanism is a potentially important natural source of mercury (Hg) to the environment. However, its impact on the global Hg cycle remains poorly understood despite advances over the last five ...decades. This represents a major uncertainty in our understanding of the relative contributions of natural and anthropogenic Hg sources to the global atmosphere. This uncertainty, in turn, impacts evaluation of the effectiveness of policies to mitigate the impact of anthropogenic Hg on the environment. Here we critically review recent progress in volcanic Hg emission research, including advances in sampling methods and understanding of the post-emission behavior of Hg in the atmosphere. Our statistical analysis of the limited available data shows that the plumes of non-arc volcanoes exhibit significantly higher Hg concentrations than arc volcanoes, yet the latter emit 3-fold higher Hg fluxes on average. Arc volcanism also dominates volcanic gas emissions globally, indicating that arc volcanoes should be a priority for future Hg emission research. We explore several methodological challenges that continue to hinder progress in quantifying global volcanic Hg emissions, and discuss the importance of longer time-frame data collection to capture temporal variations in emissions. Recommendations are proposed for working toward a more accurate assessment of the global volcanic Hg flux. A detailed summary of all published volcanic Hg emissions data worldwide is also presented as a reference tool for future work.
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•Volcanic degassing is a potentially large but poorly constrained source of mercury.•Key knowledge gaps exist in processes and temporal variability of mercury emissions.•Arc volcanoes have a three-fold higher average mercury flux than non-arc systems.•Arc volcanoes should be prioritized for further study of volcanic mercury.•Further measurements are needed globally, particularly in Indonesia and Melanesia.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Mercury is a potent neurotoxin that poses health risks to the global population. Anthropogenic mercury emissions to the atmosphere are projected to decrease in the future due to enhanced policy ...efforts such as the Minamata Convention, a legally-binding international treaty entered into force in 2017. Here, we report the development of a comprehensive climate-atmosphere-land-ocean-ecosystem and exposure-risk model framework for mercury and its application to project the health effects of future atmospheric emissions. Our results show that the accumulated health effects associated with mercury exposure during 2010-2050 are $19 (95% confidence interval: 4.7-54) trillion (2020 USD) realized to 2050 (3% discount rate) for the current policy scenario. Our results suggest a substantial increase in global human health cost if emission reduction actions are delayed. This comprehensive modeling approach provides a much-needed tool to help parties to evaluate the effectiveness of Hg emission controls as required by the Minamata Convention.
The Minamata Convention to reduce anthropogenic mercury (Hg) emissions entered into force in 2017, and attention is now focused on how to best monitor its effectiveness at reducing Hg exposure to ...humans. A key question is how closely Hg concentrations in the human food chain, especially in fish and other aquatic wildlife, will track the changes in atmospheric Hg that are expected to occur following anthropogenic emission reductions. We investigated this question by evaluating several regional groups of case studies where Hg concentrations in aquatic biota have been monitored continuously or intermittently for several decades. Our analysis shows that in most cases Hg time trends in biota did not agree with concurrent Hg trends in atmospheric deposition or concentrations, and the divergence between the two trends has become more apparent over the past two decades. An over-arching general explanation for these results is that the impact of changing atmospheric inputs on biotic Hg is masked by two factors: 1) The aquatic environment contains a large inventory of legacy emitted Hg that remains available for bio-uptake leading to a substantial lag in biotic response time to a change in external inputs; and 2) Biotic Hg trends reflect the dominant effects of changes in multi-causal, local and regional processes (e.g., aquatic or terrestrial biogeochemical processes, feeding ecology, climate) that control the speciation, bioavailability, and bio-uptake of both present-day and legacy emitted Hg. Globally, climate change has become the most prevalent contributor to the divergence. A wide range of biotic Hg outcomes can thus be expected as anthropogenic atmospheric Hg emissions decline, depending on how these processes operate on specific regions and specific organisms. Therefore, evaluating the effectiveness of the Minamata Convention will require biomonitoring of multiple species that represent different trophic and ecological niches in multiple regions of the world.
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•Mercury time-trends in aquatic biota often do not agree with atmospheric trends.•Divergence between the two trends has become more apparent in the past two decades.•The divergence is due to legacy mercury and changing biogeochemical processes.•Globally climate change has become the most prevalent contributor to the divergence.•Thus, the efforts of the Minamata Convention may be countered by climate change.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Language models have contributed to breakthroughs in interdisciplinary research, such as protein design and molecular dynamics understanding. In this study, we reveal that beyond language, ...representations of other entities, such as human behaviors, that are mappable to learnable sequences can be learned by language models. One compelling example is the real-world delivery route optimization problem. We here propose a novel approach based on the language model to optimize delivery routes on the basis of drivers’ historical experiences. Although a broad range of optimization-based approaches have been designed to optimize delivery routes, they do not capture the implicit knowledge of complex delivery operating environments. The model we propose integrates this knowledge in the route optimization process by learning from driving behaviors in experienced drivers. A real-world delivery route that preserves drivers’ implicit behavioral patterns is first analogized to a sentence in natural language. Through unsupervised learning, we then learn the vector representations of words and infer the drivers’ delivery chains on the basis of the tailored chain-reaction-based algorithm. We also provide insights into the fusion of language models and operations research methods. In our approach, language models are applied to learn drivers’ delivery behaviors and infer new deliveries at the delivery zone level, while the classic traveling salesman problem (TSP) model is embedded into the hybrid framework for intra-zone optimization. Numerical experiments performed on real-world data from Amazon’s delivery service demonstrate that the proposed approach outperforms pure optimization, supporting the effectiveness, efficiency, and extensibility of our model. As a versatile approach, the proposed framework can easily be extended to various disciplines in which the data follow certain grammar rules. We anticipate that our work will serve as a stepping stone toward the understanding and application of language models in tackling interdisciplinary research problems.
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•Revealing that language models can learn human behavioral sequences.•Integrating the implicit knowledge of drivers in the route optimization process.•A novel algorithm to optimize delivery routes emulating real-world driving behaviors.•Broadening the scope of language models to diverse domains with certain grammar rules.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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