Caves and subsurface voids on Mars and other bodies can provide significant advantages when used for human habitat and operational space. They are also targets for significant scientific investigations. We have develo...
Caves and subsurface voids on Mars and other bodies can provide significant advantages when used for human habitat and operational space. They are also targets for significant scientific investigations. We have developed a suite of technology concepts to make utilization of extraterrestrial caves feasible. Our goal is to provide a solid foundation of information and options so that mission planners may realistically consider the subsurface option in development of mission scenarios. We have concentrated on identifying the primary challenges to human operation in the extraterrestrial cave environment. Employing concepts like inflatable cave liner habitats, foamed‐in‐place airlock technologies, and micro‐robotic self‐deploying communication, mapping, and data transmission networks, we are developing solutions to meet those challenges and demonstrate the feasibility of cave use on Mars. We present the results of field trials of an incave mission simulation in several Earth caves as a proof‐of‐concept demonstration. These trials during the summer and fall of 2003 culminate in a high fidelity simulation scheduled for January 2004. Concepts and prototypes were developed during a completed Phase I and on‐going Phase II NASA Institute for Advanced Concepts (NIAC) study.
The rapid development of computer vision technology for detecting anomalies in industrial products has received unprecedented attention. In this paper, we propose a dual teacher–student-based discrimination model (DT...
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The rapid development of computer vision technology for detecting anomalies in industrial products has received unprecedented attention. In this paper, we propose a dual teacher–student-based discrimination model (DTSD) for anomaly detection, which combines the advantages of both embedding-based and reconstruction-based methods. First, the DTSD builds a dual teacher-student architecture consisting of a pretrained teacher encoder with frozen parameters, a student encoder and a student decoder. By distillation of knowledge from the teacher encoder, the two teacher-student modules acquire the ability to capture both local and global anomaly patterns. Second, to address the issue of poor reconstruction quality faced by previous reconstruction-based approaches in some challenging cases, the model employs a feature bank that stores encoded features of normal samples. By incorporating template features from the feature bank, the student decoder receives explicit guidance to enhance the quality of reconstruction. Finally, a segmentation network is utilized to adaptively integrate multiscale anomaly information from the two teacher–student modules, thereby improving segmentation accuracy. Extensive experiments demonstrate that our method outperforms existing state-of-the-art approaches. The code of DTSD is publicly available on https://***/Math-Computer/DTSD.
We have developed a novel method for co-adding multiple under-sampled images that combines the iteratively reweighted least squares and divide-and-conquer algorithms. Our approach not only allows for the anti-aliasing...
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This study investigated the dynamic changes in NiFe (hydr)oxide and identified the role of high-valent Fe in the oxygen-evolution reaction (OER) within alkaline media via in situ techniques. Several high-valent Fe ion...
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This study investigated the dynamic changes in NiFe (hydr)oxide and identified the role of high-valent Fe in the oxygen-evolution reaction (OER) within alkaline media via in situ techniques. Several high-valent Fe ions were found to remain considerably stable in the absence of potential in NiFe (hydr)oxide, even 96 hours after the OER. For Ni 2+ hydroxide treated with 57 Fe ions, where Fe sites are introduced onto the surface of Ni 2+ hydroxide, no Fe 4+ species were detected at the rate-determining step (RDS). The findings of this study suggested that the oxidation of bulk Fe ions, similar to Ni ions, to high valent forms, is charge accumulation without a direct role in OER; these results offered a novel perspective on manipulating Fe states to optimize OER efficacy. The prevailing hypothesis suggested that trace amounts of high-valent Fe ions, notably those on the surface, directly participate in OER.
Electrocardiogram (ECG) has emerged as a widely accepted diagnostic instrument for cardiovascular diseases (CVD). The standard clinical 12-lead ECG configuration causes considerable inconvenience and discomfort, while...
Electrocardiogram (ECG) has emerged as a widely accepted diagnostic instrument for cardiovascular diseases (CVD). The standard clinical 12-lead ECG configuration causes considerable inconvenience and discomfort, while wearable devices offers a more practical alternative. To reduce information gap between 12-lead ECG and single-lead ECG, this study proposes a multi-channel masked autoencoder (MCMA) for reconstructing 12-Lead ECG from arbitrary single-lead ECG, and a comprehensive evaluation benchmark, ECGGenEval, encompass the signal-level, feature-level, and diagnostic-level evaluations. MCMA can achieve the state-of-the-art performance. In the signal-level evaluation, the mean square errors of 0.0175 and 0.0654, Pearson correlation coefficients of 0.7772 and 0.7287. In the feature-level evaluation, the average standard deviation of the mean heart rate across the generated 12-lead ECG is 1.0481, the coefficient of variation is 1.58%, and the range is 3.2874. In the diagnostic-level evaluation, the average F1-score with two generated 12-lead ECG from different single-lead ECG are 0.8233 and 0.8410.
Aim The urgency for remote, reliable and scalable biodiversity monitoring amidst mounting human pressures on ecosystems has sparked worldwide interest in Passive Acoustic Monitoring (PAM), which can track life underwa...
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Aim The urgency for remote, reliable and scalable biodiversity monitoring amidst mounting human pressures on ecosystems has sparked worldwide interest in Passive Acoustic Monitoring (PAM), which can track life underwater and on land. However, we lack a unified methodology to report this sampling effort and a comprehensive overview of PAM coverage to gauge its potential as a global research and monitoring tool. To address this gap, we created the Worldwide Soundscapes project, a collaborative network and growing database comprising metadata from 416 datasets across all realms (terrestrial, marine, freshwater and subterranean). Location Worldwide, 12,343 sites, all ecosystem types. Time Period 1991 to present. Major Taxa Studied All soniferous taxa. Methods We synthesise sampling coverage across spatial, temporal and ecological scales using metadata describing sampling locations, deployment schedules, focal taxa and audio recording parameters. We explore global trends in biological, anthropogenic and geophysical sounds based on 168 selected recordings from 12 ecosystems across all realms. Results Terrestrial sampling is spatially denser (46 sites per million square kilometre—Mkm 2 ) than aquatic sampling (0.3 and 1.8 sites/Mkm 2 in oceans and fresh water) with only two subterranean datasets. Although diel and lunar cycles are well sampled across realms, only marine datasets (55%) comprehensively sample all seasons. Across the 12 ecosystems selected for exploring global acoustic trends, biological sounds showed contrasting diel patterns across ecosystems, declined with distance from the Equator, and were negatively correlated with anthropogenic sounds. Main Conclusions PAM can inform macroecological studies as well as global conservation and phenology syntheses, but representation can be improved by expanding terrestrial taxonomic scope, sampling coverage in the high seas and subterranean ecosystems, and spatio-temporal replication in freshwater habitats. Overall, this
W-CDF-S, ELAIS-S1, and XMM-LSS will be three Deep-Drilling Fields (DDFs) of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), but their extensive multi-wavelength data have not been fully utilized ...
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Cardiac magnetic resonance imaging (MRI) provides detailed and quantitative evaluation of the heart’s structure, function, and tissue characteristics with high-resolution spatial-temporal imaging. However, its slow i...
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Cardiac magnetic resonance imaging (MRI) provides detailed and quantitative evaluation of the heart’s structure, function, and tissue characteristics with high-resolution spatial-temporal imaging. However, its slow imaging speed and motion artifacts are notable limitations. Undersampling reconstruction, especially data-driven algorithms, has emerged as a promising solution to accelerate scans and enhance imaging performance using highly under-sampled data. Nevertheless, the scarcity of publicly available cardiac k-space datasets and evaluation platform hinder the development of data-driven reconstruction algorithms. To address this issue, we organized the Cardiac MRI Reconstruction Challenge (CMRxRecon) in 2023, in collaboration with the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI). CMRxRecon presented an extensive k-space dataset comprising cine and mapping raw data, accompanied by detailed annotations of cardiac anatomical structures. With overwhelming participation, the challenge attracted more than 285 teams and over 600 participants. Among them, 22 teams successfully submitted Docker containers for the testing phase, with 7 teams submitted for both cine and mapping tasks. All teams use deep learning based approaches, indicating that deep learning has predominately become a promising solution for the problem. The first-place winner of both tasks utilizes the E2E-VarNet architecture as backbones. In contrast, U-Net is still the most popular backbone for both multi-coil and single-coil reconstructions. This paper provides a comprehensive overview of the challenge design, presents a summary of the submitted results, reviews the employed methods, and offers an in-depth discussion that aims to inspire future advancements in cardiac MRI reconstruction models. The summary emphasizes the effective strategies observed in Cardiac MRI reconstruction, including backbone architecture, loss function, pre-processing techn
Side-chain engineering with heteroatoms is not only effective in tuning frontier molecular orbitals, but also possible for forming secondary bonds which can be utilized to planarize the molecular backbone, hence, impr...
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Side-chain engineering with heteroatoms is not only effective in tuning frontier molecular orbitals, but also possible for forming secondary bonds which can be utilized to planarize the molecular backbone, hence, improving the photon absorption as well as charge-transport abilities of polymer solar-cell (PSC) materials. Herein, two types of unconventional side chains, namely carboxylate and carbamate, containing various heteroatoms are introduced to the thiophene bridges in high performance benzodithiophene (BDT) based donor polymers to from the novel polymers PTzTz-C and PTzTz-N, respectively. In these polymers, non-covalent O⋅⋅⋅S and N⋅⋅⋅H interactions induce a high tendency to aggregation. In a ternary-blend PSC with PTzTz-N added to the high-performance D18 : BTP-eC9 blend, complimentary absorption and improved thin-film morphology were observed with a top power conversion efficiency of 18.76 %, which is an improvement of almost 5 % over the D18 : BTP-eC9 binary blends.
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