Wuhan University

About: Wuhan University is a education organization based out in Wuhan, China. It is known for research contribution in the topics: Computer science & Population. The organization has 92849 authors who have published 92882 publications receiving 1691049 citations. The organization is also known as: WHU & Wuhan College.

Hyperspectral Image Denoising Employing a Spectral–Spatial Adaptive Total Variation Model

Abstract: The amount of noise included in a hyperspectral image limits its application and has a negative impact on hyperspectral image classification, unmixing, target detection, and so on In hyperspectral images, because the noise intensity in different bands is different, to better suppress the noise in the high-noise-intensity bands and preserve the detailed information in the low-noise-intensity bands, the denoising strength should be adaptively adjusted with the noise intensity in the different bands Meanwhile, in the same band, there exist different spatial property regions, such as homogeneous regions and edge or texture regions; to better reduce the noise in the homogeneous regions and preserve the edge and texture information, the denoising strength applied to pixels in different spatial property regions should also be different Therefore, in this paper, we propose a hyperspectral image denoising algorithm employing a spectral-spatial adaptive total variation (TV) model, in which the spectral noise differences and spatial information differences are both considered in the process of noise reduction To reduce the computational load in the denoising process, the split Bregman iteration algorithm is employed to optimize the spectral-spatial hyperspectral TV model and accelerate the speed of hyperspectral image denoising A number of experiments illustrate that the proposed approach can satisfactorily realize the spectral-spatial adaptive mechanism in the denoising process, and superior denoising results are produced

Survey of Insomnia and Related Social Psychological Factors Among Medical Staff Involved in the 2019 Novel Coronavirus Disease Outbreak

Abstract: Objective: The outbreak of the 2019 novel coronavirus disease (COVID-19) caused not only extraordinary public health concerns but also tremendous psychological distress, particularly among medical staff. We aimed to investigate the prevalence rate of insomnia and confirm the related social psychological factors among medical staff in hospitals during the COVID-19 outbreak. Method: Medical staff members in China were recruited, including frontline medical workers. The questionnaire, administered through the WeChat program, obtained demographic data and asked self-design questions related to the COVID-19 outbreak, insomnia/depressive/anxiety symptoms, and stress-related symptoms. We used logistic regression analysis to examine the associations between sociodemographic factors and insomnia symptoms. Result: There were 1,563 participants in our study. Five hundred and sixty-four (36.1%) participants had insomnia symptoms according to the Insomnia Severity Index (ISI) (total score ≥ 8). A multiple binary logistic regression model revealed that insomnia symptoms were associated with the education level of high school or below (OR = 2.69, p = 0.042, 95% CI = 1.0–7.0), occupation of doctor (OR = 0.44, p = 0.007, 95% CI = 0.2–0.8), currently working in an isolation unit (OR = 1.71, p = 0.038, 95% CI = 1.0–2.8), worry about being infected (OR = 2.30, p < 0.001, 95% CI = 1.6–3.4), perceived lack of helpfulness in terms of psychological support from news or social media with regard to COVID-19 (OR = 2.10, p = 0.001, 95% CI = 1.3–3.3), and having very strong uncertainty regarding effective disease control (OR = 3.30, p = 0.013, 95% CI = 1.3–8.5). Conclusion: Our study found that more than one-third of the medical staff suffered from insomnia symptoms during the COVID-19 outbreak. The related factors included education level, an isolation environment, psychological worries about the COVID-19 outbreak, and occupation of doctor. Interventions for insomnia among medical staff are needed considering the different sociopsychological factors.

Accuracy and reliability of multi-GNSS real-time precise positioning: GPS, GLONASS, BeiDou, and Galileo

Abstract: In this contribution, we present a GPS+GLONASS+BeiDou+Galileo four-system model to fully exploit the observations of all these four navigation satellite systems for real-time precise orbit determination, clock estimation and positioning. A rigorous multi-GNSS analysis is performed to achieve the best possible consistency by processing the observations from different GNSS together in one common parameter estimation procedure. Meanwhile, an efficient multi-GNSS real-time precise positioning service system is designed and demonstrated by using the multi-GNSS Experiment, BeiDou Experimental Tracking Network, and International GNSS Service networks including stations all over the world. The statistical analysis of the 6-h predicted orbits show that the radial and cross root mean square (RMS) values are smaller than 10 cm for BeiDou and Galileo, and smaller than 5 cm for both GLONASS and GPS satellites, respectively. The RMS values of the clock differences between real-time and batch-processed solutions for GPS satellites are about 0.10 ns, while the RMS values for BeiDou, Galileo and GLONASS are 0.13, 0.13 and 0.14 ns, respectively. The addition of the BeiDou, Galileo and GLONASS systems to the standard GPS-only processing, reduces the convergence time almost by 70 %, while the positioning accuracy is improved by about 25 %. Some outliers in the GPS-only solutions vanish when multi-GNSS observations are processed simultaneous. The availability and reliability of GPS precise positioning decrease dramatically as the elevation cutoff increases. However, the accuracy of multi-GNSS precise point positioning (PPP) is hardly decreased and few centimeter are still achievable in the horizontal components even with 40 $$^{\circ }$$ elevation cutoff. At 30 $$^{\circ }$$ and 40 $$^{\circ }$$ elevation cutoffs, the availability rates of GPS-only solution drop significantly to only around 70 and 40 %, respectively. However, multi-GNSS PPP can provide precise position estimates continuously (availability rate is more than 99.5 %) even up to 40 $$^{\circ }$$ elevation cutoff (e.g., in urban canyons).

A genome-wide association study of cleft lip with and without cleft palate identifies risk variants near MAFB and ABCA4

Abstract: Case-parent trios were used in a genome-wide association study of cleft lip with and without cleft palate. SNPs near two genes not previously associated with cleft lip with and without cleft palate (MAFB, most significant SNP rs13041247, with odds ratio (OR) per minor allele = 0.704, 95% CI 0.635-0.778, P = 1.44 x 10(-11); and ABCA4, most significant SNP rs560426, with OR = 1.432, 95% CI 1.292-1.587, P = 5.01 x 10(-12)) and two previously identified regions (at chromosome 8q24 and IRF6) attained genome-wide significance. Stratifying trios into European and Asian ancestry groups revealed differences in statistical significance, although estimated effect sizes remained similar. Replication studies from several populations showed confirming evidence, with families of European ancestry giving stronger evidence for markers in 8q24, whereas Asian families showed stronger evidence for association with MAFB and ABCA4. Expression studies support a role for MAFB in palatal development.