National University of Defense Technology

About: National University of Defense Technology is a education organization based out in Changsha, China. It is known for research contribution in the topics: Computer science & Radar. The organization has 39430 authors who have published 40181 publications receiving 358979 citations. The organization is also known as: Guófáng Kēxuéjìshù Dàxué & NUDT.

A brain network model for depression: From symptom understanding to disease intervention.

Abstract: Understanding the neural substrates of depression is crucial for diagnosis and treatment. Here, we review recent studies of functional and effective connectivity in depression, in terms of functional integration in the brain. Findings from these studies, including our own, point to the involvement of at least four networks in patients with depression. Elevated connectivity of a ventral limbic affective network appears to be associated with excessive negative mood (dysphoria) in the patients; decreased connectivity of a frontal-striatal reward network has been suggested to account for loss of interest, motivation, and pleasure (anhedonia); enhanced default mode network connectivity seems to be associated with depressive rumination; and diminished connectivity of a dorsal cognitive control network is thought to underlie cognitive deficits especially ineffective top-down control of negative thoughts and emotions in depressed patients. Moreover, the restoration of connectivity of these networks-and corresponding symptom improvement-following antidepressant treatment (including medication, psychotherapy, and brain stimulation techniques) serves as evidence for the crucial role of these networks in the pathophysiology of depression.

Assessing spread risk of Wuhan novel coronavirus within and beyond China, January-April 2020: a travel network-based modelling study

Abstract: Objective: To estimate the potential risk and geographic range of Wuhan novel coronavirus (2019-nCoV) spread within and beyond China from January through to April, 2020. Design: Travel network-based modelling study. Setting and participants: General population travelling from Wuhan and other high-risk cities in China. Main outcome measures: Based on de-identified and aggregated mobile phone data, air passenger itinerary data, and case reports, we defined the relative importation risk and internal and international destinations of 2019-nCoV from Wuhan and other high-risk cities in China. Results: The cordon sanitaire of Wuhan is likely to have occurred during the latter stages of peak population numbers leaving the city before Lunar New Year (LNY), with travellers departing into neighbouring cities and other megacities in China, and a high proportion of cases likely travelled with symptoms at the early stage of the outbreak. Should secondary outbreaks occur in 17 high-risk secondary cities, they could contribute to seeding the virus in other highly connected cities within and beyond China after the LNY holiday. We estimated that 59,912 air passengers, of which 834 (95% UI: 478 - 1349) had 2019-nCoV infection, travelled from Wuhan to 382 cities outside of mainland China during the two weeks prior to Wuhan’s lockdown. The majority of these cities were in Asia, but major hubs in Europe, the US and Australia were also prominent, with strong correlation seen between predicted importation risks and reported cases seen. Because significant spread has already occurred, a large number of airline travellers (3.3 million under the scenario of 75% travel reduction from normal volumes) may be required to be screened at origin high-risk cities in China and destinations across the globe for the following three months of February to April, 2020 to effectively limit spread beyond its current extent. Conclusion: Further spread of 2019-nCoV within China and international exportation is likely to occur. All countries, especially vulnerable regions, should be prepared for efforts to contain the 2019-nCoV infection. Keywords: Coronavirus; Epidemiology; Pandemic; Mobile phone; Air travel

A four-band and polarization-independent BDS-based tunable absorber with high refractive index sensitivity.

Abstract: A four-band terahertz tunable narrow-band perfect absorber based on a bulk Dirac semi-metallic (BDS) metamaterial with a microstructure is designed. The three-layer structure of this absorber from top to bottom is the Dirac semi-metallic layer, the dielectric layer and the metal reflector layer. Based on the Finite Element Method (FEM), we use the simulation software CST STUDIO SUITE to simulate the absorption characteristics of the designed absorber. The simulation results show that the absorption rate of the absorber is over 93% at frequencies of 1.22, 1.822, 2.148 and 2.476 THz, and three of them have achieved a perfect absorption rate of more than 95%. We use the localized surface plasmon resonance (LSPR), impedance matching and other theories to analyze its physical mechanism in detail. The influence of the geometric structure parameters of the absorber and the incident angle of electromagnetic waves on the absorption performance has also been studied in detail. Due to the rotational symmetry of the structure, the designed absorber has excellent polarization insensitivity. In addition, the maximum adjustable range of absorption frequency is 0.051 THz, which can be achieved by changing the Fermi energy of BDS. We also define the refractive index sensitivity (S), which is 39.1, 75.4, 119.1 and 122.0 GHz RIU−1 for the four absorption modes when the refractive index varies in the range of 1 to 1.9. This high-performance absorber has a very good development prospect in the frontier fields of bio-chemical sensing and special environmental detection.