137 research outputs found

    Flow-Induced Voltage Generation Over Monolayer Graphene in the Presence of Herringbone Grooves

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    While flow-induced voltage over a graphene layer has been reported, its origin remains unclear. In our previous study, we suggested different mechanisms for different experimental configurations: phonon dragging effect for the parallel alignment and an enhanced out-of-plane phonon mode for the perpendicular alignment (Appl. Phys. Lett. 102:063116, 2011). In order to further examine the origin of flow-induced voltage, we introduced a transverse flow component by integrating staggered herringbone grooves in the microchannel. We found that the flow-induced voltage decreased significantly in the presence of herringbone grooves in both parallel and perpendicular alignments. These results support our previous interpretation

    Age-of-Information Aware Contents Caching and Distribution for Connected Vehicles

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    To support rapid and accurate autonomous driving services, road environment information, which is difficult to obtain through vehicle sensors themselves, is collected and utilized through communication with surrounding infrastructure in connected vehicle networks. For this reason, we consider a scenario that utilizes infrastructure such as road side units (RSUs) and macro base station (MBS) in situations where caching of road environment information is required. Due to the rapidly changed road environment, a concept which represents a freshness of the road content, age of information (AoI), is important. Based on the AoI value, in the connected vehicle system, it is essential to keep appropriate content in the RSUs in advance, update it before the content is expired, and send the content to the vehicles which want to use it. However, too frequent content transmission for the minimum AoI leads to indiscriminate use of network resources. Furthermore, a transmission control, that content AoI and service delay are not properly considered adversely, affects user service. Therefore, it is important to find an appropriate compromise. For these reasons, the objective of this paper is about to reduce the system cost used for content delivery through the proposed system while minimizing the content AoI presented in MBS, RSUs and UVs. The transmission process, which is able to be divided into two states, i.e., content caching and service, is approached using Markov decision process (MDP) and Lyapunov optimization framework, respectively, which guarantee optimal solutions, as verified via data-intensive performance evaluation

    Workload-Aware Scheduling using Markov Decision Process for Infrastructure-Assisted Learning-Based Multi-UAV Surveillance Networks

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    In modern networking research, infrastructure-assisted unmanned autonomous vehicles (UAVs) are actively considered for real-time learning-based surveillance and aerial data-delivery under unexpected 3D free mobility and coordination. In this system model, it is essential to consider the power limitation in UAVs and autonomous object recognition (for abnormal behavior detection) deep learning performance in infrastructure/towers. To overcome the power limitation of UAVs, this paper proposes a novel aerial scheduling algorithm between multi-UAVs and multi-towers where the towers conduct wireless power transfer toward UAVs. In addition, to take care of the high-performance learning model training in towers, we also propose a data delivery scheme which makes UAVs deliver the training data to the towers fairly to prevent problems due to data imbalance (e.g., huge computation overhead caused by larger data delivery or overfitting from less data delivery). Therefore, this paper proposes a novel workload-aware scheduling algorithm between multi-towers and multi-UAVs for joint power-charging from towers to their associated UAVs and training data delivery from UAVs to their associated towers. To compute the workload-aware optimal scheduling decisions in each unit time, our solution approach for the given scheduling problem is designed based on Markov decision process (MDP) to deal with (i) time-varying low-complexity computation and (ii) pseudo-polynomial optimality. As shown in performance evaluation results, our proposed algorithm ensures (i) sufficient times for resource exchanges between towers and UAVs, (ii) the most even and uniform data collection during the processes compared to the other algorithms, and (iii) the performance of all towers convergence to optimal levels.Comment: 15 pages, 10 figure

    Experimental observation of hidden Berry curvature in inversion-symmetric bulk 2H-WSe2

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    We investigate the hidden Berry curvature in bulk 2H-WSe2 by utilizing the surface sensitivity of angle resolved photoemission (ARPES). The symmetry in the electronic structure of transition metal dichalcogenides is used to uniquely determine the local orbital angular momentum (OAM) contribution to the circular dichroism (CD) in ARPES. The extracted CD signals for the K and K' valleys are almost identical but their signs, which should be determined by the valley index, are opposite. In addition, the sign is found to be the same for the two spin-split bands, indicating that it is independent of spin state. These observed CD behaviors are what are expected from Berry curvature of a monolayer of WSe2. In order to see if CD-ARPES is indeed representative of hidden Berry curvature within a layer, we use tight binding analysis as well as density functional calculation to calculate the Berry curvature and local OAM of a monolayer WSe2. We find that measured CD-ARPES is approximately proportional to the calculated Berry curvature as well as local OAM, further supporting our interpretation.Comment: 6 pages, 3 figure

    Multi-Agent Deep Reinforcement Learning for Efficient Passenger Delivery in Urban Air Mobility

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    It has been considered that urban air mobility (UAM), also known as drone-taxi or electrical vertical takeoff and landing (eVTOL), will play a key role in future transportation. By putting UAM into practical future transportation, several benefits can be realized, i.e., (i) the total travel time of passengers can be reduced compared to traditional transportation and (ii) there is no environmental pollution and no special labor costs to operate the system because electric batteries will be used in UAM system. However, there are various dynamic and uncertain factors in the flight environment, i.e., passenger sudden service requests, battery discharge, and collision among UAMs. Therefore, this paper proposes a novel cooperative MADRL algorithm based on centralized training and distributed execution (CTDE) concepts for reliable and efficient passenger delivery in UAM networks. According to the performance evaluation results, we confirm that the proposed algorithm outperforms other existing algorithms in terms of the number of serviced passengers increase (30%) and the waiting time per serviced passenger decrease (26%).Comment: 6 pages, 5 figure

    Open-top axially swept light-sheet microscopy

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    Open-top light-sheet microscopy (OT-LSM) is a specialized microscopic technique for high throughput cellular imaging of large tissue specimens including optically cleared tissues by having the entire optical setup below the sample stage. Current OT-LSM systems had relatively low axial resolutions by using weakly focused light sheets to cover the imaging field of view (FOV). In this report, open-top axially swept LSM (OTAS-LSM) was developed for high-throughput cellular imaging with improved axial resolution. OTAS-LSM swept a tightly focused excitation light sheet across the imaging FOV using an electro tunable lens (ETL) and collected emission light at the focus of the light sheet with a camera in the rolling shutter mode. OTAS-LSM was developed by using air objective lenses and a liquid prism and it had on-axis optical aberration associated with the mismatch of refractive indices between air and immersion medium. The effects of optical aberration were analyzed by both simulation and experiment, and the image resolutions were under 1.6 & micro;m in all directions. The newly developed OTAS-LSM was applied to the imaging of optically cleared mouse brain and small intestine, and it demonstrated the single-cell resolution imaging of neuronal networks. OTAS-LSM might be useful for the high-throughput cellular examination of optically cleared large tissues

    Comprehensive Analysis of Transcription Factor-Based Molecular Subtypes and Their Correlation to Clinical Outcomes in Small-Cell Lung Cancer

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    BACKGROUND: Recent studies have reported the predictive and prognostic value of novel transcriptional factor-based molecular subtypes in small-cell lung cancer (SCLC). We conducted an in-depth analysis pairing multi-omics data with immunohistochemistry (IHC) to elucidate the underlying characteristics associated with differences in clinical outcomes between subtypes. METHODS: IHC (n = 252), target exome sequencing (n = 422), and whole transcriptome sequencing (WTS, n = 189) data generated from 427 patients (86.4% males, 13.6% females) with SCLC were comprehensively analysed. The differences in the mutation profile, gene expression profile, and inflammed signatures were analysed according to the IHC-based molecular subtype. FINDINGS: IHC-based molecular subtyping, comprised of 90 limited-disease (35.7%) and 162 extensive-disease (64.3%), revealed a high incidence of ASCL1 subtype (IHC-A, 56.3%) followed by ASCL1/NEUROD1 co-expressed (IHC-AN, 17.9%), NEUROD1 (IHC-N, 12.3%), POU2F3 (IHC-P, 9.1%), triple-negative (IHC-TN, 4.4%) subtypes. IHC-based subtype showing high concordance with WTS-based subtyping and non-negative matrix factorization (NMF) clusterization method. IHC-AN subtype resembled IHC-A (rather than IHC-N) in terms of both gene expression profiles and clinical outcomes. Favourable median overall survival was observed in IHC-A (15.2 months) compared to IHC-N (8.0 months, adjusted HR 2.3, 95% CI 1.4-3.9, p = 0.002) and IHC-P (8.3 months, adjusted HR 1.7, 95% CI 0.9-3.2, p = 0.076). Inflamed tumours made up 25% of cases (including 53% of IHC-P, 26% of IHC-A, 17% of IHC-AN, but only 11% of IHC-N). Consistent with recent findings, inflamed tumours were more likely to benefit from first-line immunotherapy treatment than non-inflamed phenotype (p = 0.002). INTERPRETATION: This study provides fundamental data, including the incidence and basic demographics of molecular subtypes of SCLC using both IHC and WTS from a comparably large, real-world Asian/non-Western patient cohort, showing high concordance with the previous NMF-based SCLC model. In addition, we revealed underlying biological pathway activities, immunogenicity, and treatment outcomes based on molecular subtype, possibly related to the difference in clinical outcomes, including immunotherapy response

    Systematic functional analysis of kinases in the fungal pathogen Cryptococcus neoformans

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    Cryptococcus neoformans is the leading cause of death by fungal meningoencephalitis; however, treatment options remain limited. Here we report the construction of 264 signature-tagged gene-deletion strains for 129 putative kinases, and examine their phenotypic traits under 30 distinct in vitro growth conditions and in two different hosts (insect larvae and mice). Clustering analysis of in vitro phenotypic traits indicates that several of these kinases have roles in known signalling pathways, and identifies hitherto uncharacterized signalling cascades. Virulence assays in the insect and mouse models provide evidence of pathogenicity-related roles for 63 kinases involved in the following biological categories: growth and cell cycle, nutrient metabolism, stress response and adaptation, cell signalling, cell polarity and morphology, vacuole trafficking, transfer RNA (tRNA) modification and other functions. Our study provides insights into the pathobiological signalling circuitry of C. neoformans and identifies potential anticryptococcal or antifungal drug targets.OAIID:RECH_ACHV_DSTSH_NO:T201615370RECH_ACHV_FG:RR00200001ADJUST_YN:EMP_ID:A003535CITE_RATE:11.329FILENAME:4. ncomms12766.pdfDEPT_NM:๋†์ƒ๋ช…๊ณตํ•™๋ถ€EMAIL:[email protected]_YN:YFILEURL:https://srnd.snu.ac.kr/eXrepEIR/fws/file/fce63c4a-7de7-4741-996f-d8d24af38905/linkCONFIRM:
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