Introducing the GEV Activation Function for Highly Unbalanced Data to Develop COVID-19 Diagnostic Models

Fast and accurate diagnosis is essential for the efficient and effective control of the COVID-19 pandemic that is currently disrupting the whole world. Despite the prevalence of the COVID-19 outbreak, relatively few diagnostic images are openly available to develop automatic diagnosis algorithms. Traditional deep learning methods often struggle when data is highly unbalanced with many cases in one class and only a few cases in another; new methods must be developed to overcome this challenge. We propose a novel activation function based on the generalized extreme value (GEV) distribution from extreme value theory, which improves performance over the traditional sigmoid activation function when one class significantly outweighs the other. We demonstrate the proposed activation function on a publicly available dataset and externally validate on a dataset consisting of 1,909 healthy chest X-rays and 84 COVID-19 X-rays. The proposed method achieves an improved area under the receiver operating characteristic (DeLong's p-value < 0.05) compared to the sigmoid activation. Our method is also demonstrated on a dataset of healthy and pneumonia vs. COVID-19 X-rays and a set of computerized tomography images, achieving improved sensitivity. The proposed GEV activation function significantly improves upon the previously used sigmoid activation for binary classification. This new paradigm is expected to play a significant role in the fight against COVID-19 and other diseases, with relatively few training cases available

Analysis of occupational identity among family doctor teams and its influencing factors in Chengdu

BackgroundThe contracted family doctor services are the embodiment of the implementation of the new medical reform policy, and the transformation of the grass-roots health service mode. Studies have proved that the occupational stress in medical staff was at a high level. The enhancement of professional identity will contribute to strengthen team building，alleviate job burnout, and reduce turnover intention of family doctors. ObjectiveTo investigate the current situation of occupational identity among family doctor teams in Chengdu, to examine potential influencing factors of occupational identity, and to provide a reference for promoting career development and team building of family doctor teams. MethodsMulti-stage random cluster sampling was adopted to enroll study participants form 46 primary healthcare centers where family doctor contract services were implemented among 23 districts and counties in Chengdu between March 4 and 26, 2021. A total of 2 681 family doctors participated in this survey. A self-reported survey was conducted to collect participants' demographic and occupational data. The Effort-Reward Imbalance (ERI）questionnaire was implemented to assess occupational stress. The Professional Identity Scale was used to appraise occupational identity. ResultsA total of 2 327 valid questionnaires were collected, with a valid recovery rate of 86.80%, involving 1 715 females (73.7%) and 612 males (26.3%), with dominant age groups of 26−35 years (43.3%) and 36−45 years (30.4%), a high proportion of being married (82.8%), having college (36.0%) and undergraduate (47.3%) education, a high proportion of primary titles (66.0%) and informal work contract (66.1%). About 88.7% of family doctor team workers reported occupational stress. The average score of occupational identity was (3.68±0.62) points. There were significant differences in occupational identity scores among different professional title, work contract, working years in medical institutions, income, and effort/reward ratio (EER) groups (P < 0.05). ERR was negatively correlated with occupational identity (rs=−0.495, P<0.05）. The multiple regression model showed that occupational identity score in the non-staffed participants was lower than the score in the staffed ones (OR=0.429, 95%CI: 0.299−0.825). The occupational identity score in the participants having associate senior title or above was higher than in without professional title (OR=1.424, 95%CI: 1.194−2.328). The longer the working years, the higher the occupational identity score among the participants. The score of the more than 20 working years group was 1.820 times that of the less than 5 working years group (95%CI: 1.342−2.543). The higher the income, the higher the occupational identity score. The score of the 9001−12000 yuan per month group was 1.977 times that of the 1000−3000 yuan per month group (95%CI: 0.811−9.696) , and the score of the more than 12000 yuan per month group was 2.283 times that of the 1000−3000 yuan per month group (95%CI: 1.199−10.267）. ConclusionThe family doctor team workers generally report occupational stress, and their occupational identity is at a medium level in Chengdu. Relevant managers should implement intervention measures against the main influencing factors to reduce their work tension and improve their occupational identity

The Transcriptomic Responses of Pinus massoniana to Drought Stress

Masson pine (Pinus massoniana) is a major fast-growing timber species planted in southern China, a region of seasonal drought. Using a drought-tolerance genotype of Masson pine, we conducted large-scale transcriptome sequencing using Illumina technology. This work aimed to evaluate the transcriptomic responses of Masson pine to different levels of drought stress. First, 3397, 1695 and 1550 unigenes with differential expression were identified by comparing plants subjected to light, moderate or severe drought with control plants. Second, several gene ontology (GO) categories (oxidation-reduction and metabolism) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways (plant hormone signal transduction and metabolic pathways) were enriched, indicating that the expression levels of some genes in these enriched GO terms and pathways were altered under drought stress. Third, several transcription factors (TFs) associated with circadian rhythms (HY5 and LHY), signal transduction (ERF), and defense responses (WRKY) were identified, and these TFs may play key roles in adapting to drought stress. Drought also caused significant changes in the expression of certain functional genes linked to osmotic adjustment (P5CS), abscisic acid (ABA) responses (NCED, PYL, PP2C and SnRK), and reactive oxygen species (ROS) scavenging (GPX, GST and GSR). These transcriptomic results provide insight into the molecular mechanisms of drought stress adaptation in Masson pine

A Comparative Study of Contemporary Color Tongue Image Extraction Methods Based on HSI

Tongue image with coating is of important clinical diagnostic meaning, but traditional tongue image extraction method is not competent for extraction of tongue image with thick coating. In this paper, a novel method is suggested, which applies multiobjective greedy rules and makes fusion of color and space information in order to extract tongue image accurately. A comparative study of several contemporary tongue image extraction methods is also made from the aspects of accuracy and efficiency. As the experimental results show, geodesic active contour is quite slow and not accurate, the other 3 methods achieve fairly good segmentation results except in the case of the tongue with thick coating, our method achieves ideal segmentation results whatever types of tongue images are, and efficiency of our method is acceptable for the application of quantitative check of tongue image

A Comparative Study of Contemporary Color Tongue Image Extraction Methods Based on HSI

Tongue image with coating is of important clinical diagnostic meaning, but traditional tongue image extraction method is not competent for extraction of tongue image with thick coating. In this paper, a novel method is suggested, which applies multiobjective greedy rules and makes fusion of color and space information in order to extract tongue image accurately. A comparative study of several contemporary tongue image extraction methods is also made from the aspects of accuracy and efficiency. As the experimental results show, geodesic active contour is quite slow and not accurate, the other 3 methods achieve fairly good segmentation results except in the case of the tongue with thick coating, our method achieves ideal segmentation results whatever types of tongue images are, and efficiency of our method is acceptable for the application of quantitative check of tongue image

A Joint Channel Estimation and Compression Method Based on GAN in 6G Communication Systems

Due to the increasing popularity of communication devices and vehicles, the channel environment becomes more and more complex, which makes conventional channel estimation methods further increase the pilot overhead to maintain estimation performance. However, it declines the throughput of communication networks. In this paper, we provide a novel two-stage based channel estimation method by using generative adversarial networks (GANs) to handle this problem in orthogonal frequency division multiplexing (OFDM) systems. Specifically, the first stage aims to learn the mapping from a low-dimensional latent variable to the real channel sample. During the second stage, an iterative algorithm method is designed to find the optimal latent variable by matching the pilot channels of a real channel and generated channel. Then, the data channels are recovered based on the learned mapping relationship between the latent variable and the real channel sample. The simulation results show that our proposed method can achieve a performance gain of more than 2 dB with a pilot reduction by 75% when SNR is 10 dB, by comparing with the widely used Wiener filter interpolation method. In addition, as the low-dimensional latent variable can be obtained simultaneously, it can also be used for reducing the feedback overhead

Nanocellulose-Based Composite Materials Used in Drug Delivery Systems

Nanocellulose has lately emerged as one of the most promising &ldquo;green&rdquo; materials due to its unique properties. Nanocellulose can be mainly divided into three types, i.e., cellulose nanocrystals (CNCs), cellulose nanofibrils (CNFs), and bacterial cellulose (BC). With the rapid development of technology, nanocellulose has been designed into multidimensional structures, including 1D (nanofibers, microparticles), 2D (films), and 3D (hydrogels, aerogels) materials. Due to its adaptable surface chemistry, high surface area, biocompatibility, and biodegradability, nanocellulose-based composite materials can be further transformed as drug delivery carriers. Herein, nanocellulose-based composite material used for drug delivery was reviewed. The typical drug release behaviors and the drug release mechanisms of nanocellulose-based composite materials were further summarized, and the potential application of nanocellulose-based composite materials was prospected as well

A Mesoscale CFD Simulation Study of Basic Wind Pressure in Complex Terrain—A Case Study of Taizhou City

The basic wind pressure or the reference wind pressure for structural design varies greatly across complex terrain. Since only a few meteorological stations can provide adequate extreme wind speed records, it is very difficult to appropriately determine the basic wind pressure for a specific site without a long history of meteorological records. To solve this problem, a mesoscale CFD model was developed and optimized based on geographic information data for Taizhou and suitable turbulence models were selected for CFD simulation. The mean extreme wind speed and the corresponding direction at five main weather stations with long observation histories in Taizhou were used as the verification conditions to perform the CFD simulation of the extreme wind field. The maximum wind speeds of the rural areas, cities, and streets of Taizhou were obtained from the results of the mesoscale CFD simulations. Then, the 50-year return period reference wind pressures were calculated and could be used for the wind-resistant structural design of buildings for sites without a long history of meteorological records. The reliability of the results was verified by comparing the simulation results with the observation data at five main stations with a long history