15,125 research outputs found

    Highly Efficient Midinfrared On-Chip Electrical Generation of Graphene Plasmons by Inelastic Electron Tunneling Excitation

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    Inelastic electron tunneling provides a low-energy pathway for the excitation of surface plasmons and light emission. We theoretically investigate tunnel junctions based on metals and graphene. We show that graphene is potentially a highly efficient material for tunneling excitation of plasmons because of its narrow plasmon linewidths, strong emission, and large tunability in the midinfrared wavelength regime. Compared to gold and silver, the enhancement can be up to 10 times for similar wavelengths and up to 5 orders at their respective plasmon operating wavelengths. Tunneling excitation of graphene plasmons promises an efficient technology for on-chip electrical generation and manipulation of plasmons for graphene-based optoelectronics and nanophotonic integrated circuits.Comment: 12 pages, 7 figure

    Photon-number-solving Decoy State Quantum Key Distribution

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    In this paper, a photon-number-resolving decoy state quantum key distribution scheme is presented based on recent experimental advancements. A new upper bound on the fraction of counts caused by multiphoton pulses is given. This upper bound is independent of intensity of the decoy source, so that both the signal pulses and the decoy pulses can be used to generate the raw key after verified the security of the communication. This upper bound is also the lower bound on the fraction of counts caused by multiphoton pulses as long as faint coherent sources and high lossy channels are used. We show that Eve's coherent multiphoton pulse (CMP) attack is more efficient than symmetric individual (SI) attack when quantum bit error rate is small, so that CMP attack should be considered to ensure the security of the final key. finally, optimal intensity of laser source is presented which provides 23.9 km increase in the transmission distance. 03.67.DdComment: This is a detailed and extended version of quant-ph/0504221. In this paper, a detailed discussion of photon-number-resolving QKD scheme is presented. Moreover, the detailed discussion of coherent multiphoton pulse attack (CMP) is presented. 2 figures and some discussions are added. A detailed cauculation of the "new" upper bound 'is presente

    Toxicological evaluation of precocene II isolated from Ageratum conyzoides L. (Asteraceae) in Sprague Dawley rats

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    Precocene II (6,7-dimethoxy-2,2-dimethyl-2-chromene) was the main constituent isolated from Ageratum conyzoides L. and reportedly possessed antifungal activity. The study investigated the isolation, purification and toxicological effects of precocene II from A. conyzoides in Sprague Dawley rats. Precocene II was isolated from the petroleum ether fraction of the plant and the structure was determined by 1H-,13C-,DEPT-NMR and MS spectral techniques. Three groups of eight rats per group were used for the study. While groups B and C were respectively administered with 25 and 50 mg/kg of precocene II in 0.25% CMC-Na for 11 days by gastric intubation, group A was administered with 0.25% CMC-Na and served as the control group. After the last treatment, animals were fasted overnight and on the 12th day, they were injected intravenously with 0.2 ml/kg body weight of phenobarbital. Animals were subsequently dissected from the abdominal region; blood was collected from the pulmonary vein into EDTA anti-coagulated and non anti-coagulated tubes. The liver, kidney and spleen tissues were extracted into separate bottles for histopathological examinations. Results from hematological study indicated that the white blood cell (WBC), red blood cell (RBC), plateletcrit (PCT) and mean corpuscular hemoglobin count (MCHC) were significantly higher across the treated groups. Biochemical result showed that serum glucose level was significantly reduced in the treated groups. No apparent damage was noticed in the liver, kidney and spleen tissues. The result therefore suggests that precocene II possesses hypoglycemic property and could alter some hematopoietic elements but was not toxic to the liver, kidney and spleen tissues

    Evolution and maintenance of cooperation via inheritance of spatial neighbourhood

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    Duration of untreated bipolar disorder: A multicenter study

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    Little is known about the demographic and clinical differences between short and long duration of untreated bipolar disorder (DUB) in Chinese patients. This study examined the demographic and clinical features of short (≤2 years) and long DUB (\u3e2 years) in China. A consecutively recruited sample of 555 patients with bipolar disorder (BD) was examined in 7 psychiatric hospitals and general hospital psychiatric units across China. Patients’ demographic and clinical characteristics were collected using a standardized protocol and data collection procedure. The mean DUB was 3.2 ± 6.0 years; long DUB accounted for 31.0% of the sample. Multivariate analyses revealed that longer duration of illness, diagnosis of BD type II, and earlier misdiagnosis of BD for major depressive disorder or schizophrenia were independently associated with long DUB. The mean DUB in Chinese BD patients was shorter than the reported figures from Western countries. The long-term impact of DUB on the outcome of BD is warranted

    DeepTrace: Learning to Optimize Contact Tracing in Epidemic Networks with Graph Neural Networks

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    The goal of digital contact tracing is to diminish the spread of an epidemic or pandemic by detecting and mitigating public health emergencies using digital technologies. Since the start of the COVID-1919 pandemic, a wide variety of mobile digital apps have been deployed to identify people exposed to the SARS-CoV-2 coronavirus and to stop onward transmission. Tracing sources of spreading (i.e., backward contact tracing), as has been used in Japan and Australia, has proven crucial as going backwards can pick up infections that might otherwise be missed at superspreading events. How should robust backward contact tracing automated by mobile computing and network analytics be designed? In this paper, we formulate the forward and backward contact tracing problem for epidemic source inference as maximum-likelihood (ML) estimation subject to subgraph sampling. Besides its restricted case (inspired by the seminal work of Zaman and Shah in 2011) when the full infection topology is known, the general problem is more challenging due to its sheer combinatorial complexity, problem scale and the fact that the full infection topology is rarely accurately known. We propose a Graph Neural Network (GNN) framework, named DeepTrace, to compute the ML estimator by leveraging the likelihood structure to configure the training set with topological features of smaller epidemic networks as training sets. We demonstrate that the performance of our GNN approach improves over prior heuristics in the literature and serves as a basis to design robust contact tracing analytics to combat pandemics
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