INVESTIGATING THE CHANGE IN PREFERENCE OF LIVING AND TRANSPORT DURING COVID-19

The COVID-19 pandemic meant that people had to perform most of their daily activities from home. This study intends to investigate if a period of working from home has changed living preferences concerning housing size and location. The data was collected through a web-based survey. The literature is divided regarding the potential benefits of reduced commuting due to increased home office utilization. There is a prevalent risk of rebound effects as saved travel time might lead to increased travel on leisure, which could counterweight the benefits of reduced daily commuting in cities. Most of the respondents in this study want to work from home 2–3 days a week. The respondents that desire to move to a less central location state the lower square meter price as one important reason. Analyses in prevailing research did not investigate the preference for larger homes combined with increased home office use. Future studies should also investigate the desire for larger homes to achieve a holistic evaluation of the emissions related to telecommuting. © 2022 The Author(s). Licensed under a CC-BY 4.0 licence.

Clinical Guidelines for Dentistry in China During the Coronavirus Disease 2019 Pandemic

Preventing the spread of Coronavirus Disease 2019 (COVID-19) has become the focus of epidemiologists as the highly infectious respiratory disease spreads primarily by close, person-to-person contact via droplets or the skin. Aerosol dissemination may occur in a closed, high-aerosol environment. The aerosols generated in dental procedures can pollute surrounding air and device surfaces. In this paper, we summarize prevention and control measures relating to dentistry. We focus on the relationship between COVID-19 and dental disease prevention and control in dental treatment procedures and imaging examinations, oral health education and perspectives, and guidance for the practice of dentistry during the COVID-19 pandemic to provide a consistent and broadly endorsed standard for dental hospital and clinics. Copyright © 2021 Luo, Wang, Tang, Peng, Ma and Wu.

Preparation of PLA-based SMS nonwoven composites and its applications in protective apparel

The global COVID-19 pandemic has triggered a huge demand for the protective nonwovens. However, the main raw material of nonwovens comes from petroleum, and the massive consumption of petroleum-based polymers brings great pressure to ecosystem. Therefore, it is significant to develop biodegradable protective barrier products. In this work, a polylactic-based composite (a tri-layer nonwovens composed of spunbond, meltblown and spunbond, SMS) was prepared and applied for protective apparel. The surface morphology and chemical changes of the fibers were characterized and analyzed by scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FTIR) and energy dispersive spectroscopy (EDS). The liquid contact angle and permeability, breathability and moisture permeability, frictional charge and mechanical strength of the samples were evaluated and compared. The samples degradability was also recorded. The results demonstrate that the optimum formula for anti-fouling treatment on SMS is F-30. The treated fabric possesses superior liquid repellency and anti-permeability, with contact angles of water and alcohol at 128° and 115° respectively, while the alcohol repellent grade reaches level 7. The treated sample has less strength loss but exhibits favorable breathability, moisture permeability and anti-static properties, which can meet the requirements of protective apparels. After fluorine resin coating, the composite still provide excellent degradation performance, and the weight loss rate reaches more than 80% after 10 days water degradation. These results provide new insights for the application of PLA-based SMS in biodegradable protective apparel. © 2023 The Textile Institute.

Design of service robot control system for epidemic prevention and control

In view of the fact that Covid-19 is highly contagious, which poses great threat and inconvenience to people's production and life, a multifunctional robot control system with single-chip microcomputer as the control core is designed, aiming at the problems of centralized isolation points in communities, complicated situation and difficult management. Firstly, Gmapping algorithm is used to realize the robot's autonomous positioning and avoidance. Secondly, a three-degree-of-freedom robot arm is designed to disinfect any indoor space. Finally, Gmapping algorithm is used to recognize and measure the temperature of human face. Through the simulation experiment, this method can improve the efficiency of searching the shortest path and carry out disinfection work while reducing human contact, improving public safety and has practical value. © 2023 IEEE.

Global Stability of a MERS-CoV Infection Model with CTL Immune Response and Intracellular Delay

In this paper, we propose and study a Middle East respiratory syndrome coronavirus (MERS-CoV) infection model with cytotoxic T lymphocyte (CTL) immune response and intracellular delay. This model includes five compartments: uninfected cells, infected cells, viruses, dipeptidyl peptidase 4 (DPP4), and CTL immune cells. We obtained an immunity-inactivated reproduction number (Formula presented.) and an immunity-activated reproduction number (Formula presented.). By analyzing the distributions of roots of the corresponding characteristic equations, the local stability results of the infection-free equilibrium, the immunity-inactivated equilibrium, and the immunity-activated equilibrium were obtained. Moreover, by constructing suitable Lyapunov functionals and combining LaSalle's invariance principle and Barbalat's lemma, some sufficient conditions for the global stability of the three types of equilibria were obtained. It was found that the infection-free equilibrium is globally asymptotically stable if (Formula presented.) and unstable if (Formula presented.) ;the immunity-inactivated equilibrium is locally asymptotically stable if (Formula presented.) and globally asymptotically stable if (Formula presented.) and condition (H1) holds, but unstable if (Formula presented.) ;and the immunity-activated equilibrium is locally asymptotically stable if (Formula presented.) and is globally asymptotically stable if (Formula presented.) and condition (H1) holds. © 2023 by the authors.

The Psychological Impacts of COVID-19 on Breast Cancer Patients in China

Background: Approximately 30% to 50% of breast cancer patients experienced mental distress prior to the advent of COVID.The delayed access to cancer treatment due to the outbreak of COVID -19 pandemic posed a unique challenge to breast cancer patients and caused a significant level of mental distress among them. In the current research, we examined the psychological impacts of COVID on breast cancer patients in China using Symptom Checklist-90-R (SCL-90-R). Method(s): Participants were breast cancer patients at the outpatient clinic of Xijing hospital. The study was conducted virtually, and the questionnaires were distributed via Wenjuanxing, the Chinese alternative of Qualtrics. The researchers were healthcare workers affiliated with Xijing hospital, and the survey was sent to a breast cancer patient support group which included 1399 cancer patients and 6 healthcare workers. The initial sample consisted of 199 participants who signed an informed consent form to participate in the study. The inclusion criteria were as follows: 1) diagnosed with breast cancer, 2) aged 18 years or above, and 3) had no history of cognitive impairment or previous diagnosis of psychiatric disorders. The validated Mandarin version of the SCL-90-R (Wang, 1984) was then given to the participants to evaluate their psychological status.Categorical variables were summarized as numbers and percentages;continuous variables were described as mean (M) +/- standard deviation (SD). Data were analyzed using IBM SPSS Statistics Version 26. Result(s): Participants (N = 195) filled out the SCL-90 questionnaire in February, 2020. All participants were female breast cancer patients treated at Xijing hospital, among which 16.41%, 36.41%, 19.49%, and 28.21% had respectively received treatment for less than a year, 1-3 years, 3-5 years, and 5 years or more. 64.62% of the patients were at stage I;0.77% were at stage II and III;4.62% were at stage IV according to TNM classification. The molecular type of participants is as follows: 47.2% of ER+ HER2-, 31.8% of HER2+, and 21.0% of Triple negative.Participants whose treatments continued to be delayed, on average, reported an elevated general psychopathology score (M = 1.48, SD = 0.47) compared to participants whose treatments were resumed (M = 1.30, SD = 0.34), and the difference was statistically significant, t(193) = 2.96, p = .003, d = 0.44, 95%Cl [0.06, 0.30]. The one-way ANOVA revealed a marginally significant effect of length of treatment delay on general psychopathology score, F(4, 190) = 2.09, p = .08, eta2 = .04. Follow-up multiple comparison analysis showed that participants who had their treatment delayed for 3 weeks to 1 month (M = 1.70, SD = 0.70) reported significantly higher general psychopathology scores than participants whose delay in treatment was less than 1 week (M = 1.34, SD = 0.40), p = .05. General health status (p < .001) and current treatment status (p = .02) are the only two variables that were statistically associated with general psychopathology score.Poorer perceived health status and current delay in treatment were associated with higher general psychopathology score, Additionally, younger age was associated with higher interpersonal sensitivity (p = .01) and hostility (p = .006). Conclusion(s): We found that breast cancer patients at an advanced stage were more likely to experience psychological symptoms with longer treatment delay, and whose treatments continued to be delayed reported elevated psychological symptoms than individuals whose treatment were resumed, regardless of treatment type. Additionally, a treatment delay of more than three weeks might have exacerbated breast cancer patients' psychological symptoms, whereas a short-term delay of less than three weeks was less likely to have a significant effect on one's mental wellbeing.

Analysing the factors affecting medical waste generation in China

Medical waste deserves particular attention due to its potential for causing serious damage to people and the environment. Although the factors influencing the generation of medical waste are critical for designing policies aimed at effectively reducing medical waste and improving medical waste management, they have not been extensively studied. The rapid development of China's medical and health services and the sudden outbreak of Covid-19 have brought significant challenges to managing medical waste in China. Therefore, based on panel data from eight cities in China from 2013 to 2019, this study used a fixed-effects model to investigate the influencing factors of medical waste generation (MWG) in China, and tested the environmental Kuznets curve (EKC) hypothesis. The results show that there is a non-linear N-shaped curve relationship between MWG and per capita gross domestic product (GDP);MWG will continue to increase with economic growth, but the growth rate will slow down from fast to slow, and then from slow to fast with economic growth. The analysis also reveals that implementing a tiered diagnosis and treatment policy may negatively affect MWG by reducing the waste of medical resources and thus reducing the generation of medical waste. The positive effect of population size on MWG is also highly significant, so when the aging of the population increases, the generation of medical waste also increases. The three policy suggestions are provided: 1) improve the disposal capacity and efficiency of medical waste;2) give full play to the advantages of hierarchical diagnosis and treatment policy;3) improve the management level of medical waste in primary medical institutions. © 2023

Implementation of Mask Wearing Recognition

Because of the pandemic of COVID-19 since 2020, it seriously affects people's daily life and causes huge economic loss. Recently, the international community has mostly adopted an attitude of coexisting with Covid-19. We cannot ignore the harm the virus can bring to us. In order to effectively protect everyone from the virus, the most basic and effective way is to wear a mask to keep you away from exposure to the virus when going to public areas. Vision intelligence can play an important role in public health issues. In this paper, we utilize the object detection method to implement an actual mask wearing recognition system which can detect if people have a face mask on their face, and send a warning message if not wearing a mask. YOLOv3 is the basic framework for our implementation. After training and fine-tuning processes, the implemented model can perform effectively and correctly. © 2022 IEEE.

An immobilization-based, loop-mediated isothermal amplification device for nucleic acid detection of SARS-CoV-2 N gene

Confronting the global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), simple, fast and specific non-laboratory SARS-CoV-2 diagnostic tests are urgently required. However, the current nucleic acid assays generally rely on the diagnostic laboratory, trained staff and specialized equipment for execution and analysis, presenting clear limitations in the field detection. Here, we describe a portable and reliable immobilization-based loop-mediated isothermal amplification (LAMP) device which is mobile, without the requirement of any complicated instrument and appropriate for high-throughput testing. This device was constructed by utilizing the interaction between a carboxyl-tagged primer and an amino-tagged substrate, and capable of catching the target sequence in SARS-CoV-2 produced via the immobilization-based LAMP. In this study, the immobilization conditions and immobilized primer structure were explored and optimized. With this proposed device, the analysis result can be obtained rapidly in 30 min with excellent specificity, even if the template is extracted from a complex sample containing pharyngeal swab or human blood. In addition, the device can be applied to detect the nucleic acid of SARS-CoV-2 and various other pathogens, showing attractive potential for rapid and high-throughput detection at airports, railway stations, cold-chain transportations, community hospitals and so on. Therefore, we believe that the immobilization-based LAMP device is an advanced approach to developing a portable, specific, low-cost and high-throughput diagnostic platform.

Test-Time Adaptation with Calibration of Medical Image Classification Nets for Label Distribution Shift

Class distribution plays an important role in learning deep classifiers. When the proportion of each class in the test set differs from the training set, the performance of classification nets usually degrades. Such a label distribution shift problem is common in medical diagnosis since the prevalence of disease vary over location and time. In this paper, we propose the first method to tackle label shift for medical image classification, which effectively adapt the model learned from a single training label distribution to arbitrary unknown test label distribution. Our approach innovates distribution calibration to learn multiple representative classifiers, which are capable of handling different one-dominating-class distributions. When given a test image, the diverse classifiers are dynamically aggregated via the consistency-driven test-time adaptation, to deal with the unknown test label distribution. We validate our method on two important medical image classification tasks including liver fibrosis staging and COVID-19 severity prediction. Our experiments clearly show the decreased model performance under label shift. With our method, model performance significantly improves on all the test datasets with different label shifts for both medical image diagnosis tasks. Code is available at https://github.com/med-air/TTADC. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Research on the impact of artificial intelligence on international specialization status in textile industry

With the continuous iteration of digital technologies Artificial Intelligence AI is emerging as a core strength leading the technological revolution and industrial transformation. Furthermore since the outbreak of COVID-19 epidemic AI has been promoted to a new high. To build new international competitiveness AI has been undoubtedly seen as an important avenue to improve the status of international specializations. Under the opportunity of global value chain GVC reconstruction the traditional comparative advantages such as labor cost are gradually weakened. The textile industry urgently needs to improve the core competitiveness of products through intelligent manufacturing and upgrade from the processing and manufacturing link with the lowest added value to the textile machinery production and product design link with higher added value. Does the current development level of AI have an obvious driving effect on the international specializations status of textile industry in various countries What is the specific mechanism The discussion of these problems has theoretical value and important practical significance for the formulation of AI-related policies the transformation of textile industry and the promotion path selection of the international specializations status. This paper measures the comprehensive development index of AI in 28 countries from 2010 to 2017. Based on the world input-output table a global value chain position index is constructed to measure a country's status of international specializations. The two indicators are connected within a unified framework and the multi-dimensional panel fixed effect model is used for empirical test of textile industry. Then using the intermediary effect model this paper analyzes the influence mechanism of AI on the status of international specializations from three channels technological innovation production efficiency and human capital. There are three possible marginal contributions of this paper First the research on integrated evaluation systems for AI development in 28 economies from 2010 to 2017 allowing for the international comparison and dynamic tracking from multiple dimensions could be initial efforts to break up the one-fold measurement of AI. Second it is the first time to use AI as an emerging influencing factor of the international specializations status in the textile industry. Third through connecting the AI index with international specializations status of the textile industry within the unified accounting framework our study provides a better understanding of mechanisms for AI influence on international specializations from three channels technological innovation production efficiency and human capital. The main conclusions are as follows First AI has significantly improved the position of a country's textile industry in the global value chain. Second through the mechanism test it is confirmed that AI has improved the international specializations status of the textile industry through three channels technological innovation production efficiency and human capital. Among them the kinetic energy of promoting the textile industry to move up the value chain through production efficiency needs to be further stimulated. Therefore in order to seize the opportunity of technological revolution the textile industry should actively develop intelligent manufacturing and use AI technology to help enterprises complete the transformation of automation intelligence and digitization so as to improve the added value and technical content of export products. Meanwhile enterprises and governments should increase R&D research and development investment vigorously promote the transformation of innovative achievements of AI technology in the textile industry and make it gradually occupy the core position of global value chain in international competition. Finally in order to solve the key problems of textile industry such as the over-dependence on low-end labor force administrative departments should speed up the construction of high-end talent team of AI. The emer ing technology represented by AI provides a new path choice for the international specializations status of the textile industry which can not only further promote the AI sustainable development and the effective integration of all links of the textile industry but also break through the dilemma of "low-end locking" of the global value chain so as to achieve the goal of promoting the digital transformation of the textile industry and improving the status of international specializations. It provides a theoretical and factual basis for AI to cultivate new digital kinetic energy in the upgrading of textile industry and to participate in the positioning of a new round of international competition. © 2022 China Silk Association. All rights reserved.

A Reflection Case to Covid-19 Pandemic: Online Learning Experience

The covid-19 pandemic spread throughout the world by 2020. Millions were infected, and thousands died as a result of this. Many institutions were shut down, and physical access to campuses was halted. Institutions switched to online instruction, and students took online classes at home. The purpose of this study was to better understand the shift to online learning during the coronavirus epidemic. It also attempted to identify roadblocks and hurdles in the process so that ideas for the future of learning could be proposed. Between February and May 2020, teaching staff and students at a local applied degree institute in Hong Kong were asked about their online learning experiences. There were six major themes identified: (1) online learning experience;(2) support;(3) engagement;(4) group work;(5) time;and (6) assessment. These were examined in light of past literature, and recommendations for further learning were made. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

[Characteristics of SARS-CoV-2 Omicron infection in children imported from Hong Kong].

Objective: To understand the clinical characteristics of children with SARS-CoV-2 Omicron infection imported from Hong Kong Special Administrative Region. Methods: This retrospective study was conducted to collect the data including clinical manifestations, outcomes and vaccination of 107 children with SARS-CoV-2 Omicron infection imported from Hong Kong Special Administrative Region to be admitted to the designated referral hospital in Shanghai from February to March 2022. According to the occurrence of clinical symptoms, the cases were divided into asymptomatic group and symptomatic group. According to the age of diagnosis, the cases were divided into <3 years group, 3-<6 years group and 6-<18 years group, and the clinical manifestations in different age group were analyzed with t-test and Mann-Whitney rank-sum test. Besides, to analyze the effectiveness of vaccination against SARS-CoV-2 Omicron infection in different age group, the cases aged 3-<18 years were also subdivided into unvaccinated group, 1-dose group and 2-dose group, and the relative risk (RR) was used to demonstrate the effectiveness. Results: Among the 107 cases, 66 were male and 41 were female, with infection age of 10 (5, 14) years. There were 29 cases in the asymptomatic group, and 78 cases in the symptomatic group, and no significant difference in the age of infection was observed between the 2 groups (11 (6, 14) vs. 10 (5, 14) years, Z=0.49, P>0.05). And there were no severe cases in symptomatic group. The length of hospitalization was (18±6) days, and was longer in symptomatic group than that in asymptomatic group ((19±6) vs. (16±7) d, t=0.17, P=0.030). Eight-two cases (76.6%) had a history of epidemiological exposure and, among whom, 81 cases (75.7%) were associated with household transmission. Among symptomatic group, 57 cases (73.1%) had fever and 20 cases (25.6%) had cough. Of the 74 cases undergoing chest CT examination, 17 cases (23.0%) showed mild abnormalities. Of the 83 cases who received the lab tests, 23 cases (27.7%) had white blood cell counts<4×109/L, 3 cases (3.6%) had C-reaction protein >8.0 mg/L, and 6 cases (7.2%) had slightly elevated aspartate transaminase and alanine aminotransferase. Among the 92 children aged 3-<18 years, 31 cases were unvaccinated, 34 cases received 1 dose, and 27 cases received 2 doses. The interval between the last vaccination and infection was 2.2 (0.6, 6.0) months; the interval between the last vaccination and infection in the 2-dose group was longer than that in 1-dose group (6.0 (4.5, 7.3) vs. 0.7 (0.3,2.0) months, Z=3.59, P<0.001).The risk of symptomatic infection was reduced by 45% (RR=0.55, 95% CI 0.35-0.87) with two-dose vaccination compared to non-vaccination in cases aged 3-<18 years. All these cases recovered completely. Conclusions: Children infected with SARS-CoV-2 Omicron are usually mild or asymptomatic. Household transmission is the main pattern of infection with SARS-CoV-2 Omicron in children. Two-dose SARS-CoV-2 vaccination in children aged 3-<18 years can provide partial protection against disease caused by SARS-CoV-2 Omicron.

Real-Time Detection of COVID-19 Events From Twitter: A Spatial-Temporally Bursty-Aware Method

In the last two years, the outbreak of COVID-19 has significantly affected human life, society, and the economy worldwide. To prevent people from contracting COVID-19 and mitigate its spread, it is crucial to timely distribute complete, accurate, and up-to-date information about the pandemic to the public. In this article, we propose a spatial-temporally bursty-aware method called STBA for real-time detection of COVID-19 events from Twitter. STBA has three consecutive stages. In the first stage, STBA identifies a set of keywords that represent COVID-19 events according to the spatiotemporally bursty characteristics of words using Ripley's K function. STBA will also filter out tweets that do not contain the keywords to reduce the interference of noise tweets on event detection. In the second stage, STBA uses online density-based spatial clustering of applications with noise clustering to aggregate tweets that describe the same event as much as possible, which provides more information for event identification. In the third stage, STBA further utilizes the temporal bursty characteristic of event location information in the clusters to identify real-world COVID-19 events. Each stage of STBA can be regarded as a noise filter. It gradually filters out COVID-19-related events from noisy tweet streams. To evaluate the performance of STBA, we collected over 116 million Twitter posts from 36 consecutive days (from March 22, 2020 to April 26, 2020) and labeled 501 real events in this dataset. We compared STBA with three state-of-the-art methods, EvenTweet, event detection via microblog cliques (EDMC), and GeoBurst+ in the evaluation. The experimental results suggest that STBA outperforms GeoBurst+ by 13.8%, 12.7%, and 13.3% in terms of precision, recall, and F ₁score. STBA achieved even more improvements compared with EvenTweet and EDMC.

Comparation and Sentiment Analysis Method of Chinese and Western Media's COVID-19 Reports on Various Countries

Media plays an important role in the information society and therefore, it should be fair, just, and objective. Media has been influencing the public's cognition of COVID-19 and their views of the actions taken by the government of different countries in 2020. After analyzing more than 260 thousand reports collected from search engines and published by both the Chinese and Western media about 10 countries, we found that Western media has prejudice when reporting the epidemic in China, and there exist obvious abnormal features when they reporting the epidemic in the United States. In addition, compared to Western media, Chinese media are more consistent and objective with the actual development of the epidemic in different countries. © 2022, Science Press. All right reserved.

[Epidemiological characteristics of local COVID-19 epidemics and control experience in routine prevention and control phase in China].

The COVID-19 pandemic is still ongoing in the world, the risk of COVID-19 spread from other countries or in the country will exist for a long term in China. In the routine prevention and control phase, a number of local COVID-19 epidemics have occurred in China, most COVID-19 cases were sporadic ones, but a few case clusters or outbreaks were reported. Winter and spring were the seasons with high incidences of the epidemics; border and port cities had higher risk for outbreaks. Active surveillance in key populations was an effective way for the early detection of the epidemics. Through a series of comprehensive prevention and control measures, including mass nucleic acid screening, close contact tracing and isolation, classified management of areas and groups at risk, wider social distancing and strict travel management, the local COVID-19 epidemics have been quickly and effectively controlled. The experiences obtained in the control of the local epidemics would benefit the routine prevention and control of COVID-19 in China. The occurrence of a series of COVID-19 case clusters or outbreaks has revealed the weakness or deficiencies in the COVID-19 prevention and control in China, so this paper suggests some measures for the improvement of the future prevention and control of COVID-19.

Comparison of disinfection effects of different methods for nucleic acid pollution in 2019-nCoV

Objective: To evaluate the ability of different disinfection methods to remove nucleic acid pollution in 2019-nCoV so as to obtain the best removal scheme. Methods: 2019-nCoV positive quality control nucleic acid of 50 μL was applied to plastic, metal and glass with medical cotton swabs, respectively. After drying, we dropped 50 μL of 750 mL/L alcohol (ethanol), chlorine-containing disinfectant (2 000 mg/L and 5 500 mg/L), and PCR Cleaner, respectively. After 1 min, the contaminated area was wiped with medical cotton swabs and soaked in 300 μL of pure water. After shaking and mixing, 5 μL was taken as a template. The Ct values of ORF1ab and N genes and IC genes of internal standard fragment in the amplified target area of 2019-nCoV after wiping with different disinfection methods were compared to evaluate the effect of eliminating nucleic acid pollution, and each experiment was repeated for three times. Similarly, the effects of ultraviolet irradiation for 0, 1, 2, 3, 4, and 5 hours on the removal of nucleic acid pollution were compared. Results: After 2 000 mg/L and 5 500 mg/L chlorine-containing disinfectant wiped the contaminated area, the Ct values of ORF1ab and N genes and IC genes of internal standard fragment in the amplified target area in 2019-nCoV were all 0, and the Ct values of all genes in the contaminated area in groups 3, 4 and 5 h after UV irradiation were all 0, which completely cleared the pollution and had a strong effect. The effect of PCR Cleaner was second, and 750 mL/L ethanol was the worst. Conclusion: 2 000 mg/L and 5 500 mg/L chlorine-containing disinfectant and ultraviolet irradiation for 3 hours have the best effect of eliminating nucleic acid pollution, which is worth popularizing under appropriate conditions.

A Lightweight Face Verification Based on Adaptive Cascade Network and Triplet Loss Function

In the past few years, with the continuous breakthrough of technology in various fields, artificial intelligence has been considered as a revolutionary technology. One of the most important and useful applications of artificial intelligence is face detection. The outbreak of COVID-19 has promoted the development of the noncontact identity authentication system. Face detection is also one of the key techniques in this kind of authentication system. However, the current real-time face detection is computationally expensive which hinders the application of face recognition. To address this issue, we propose a face verification framework based on adaptive cascade network and triplet loss. The framework is simple in network architecture and has light-weighted parameters. The training network is made of three stages with an adaptive cascade network and utilizes a novel image pyramid based on scales with different sizes. We train the face verification model and complete the verification within 0.15 second for processing one image which shows the computation efficiency of our proposed framework. In addition, the experimental results also show the competitive accuracy of our proposed framework which is around 98.6%. Using dynamic semihard triplet strategy for training, our network achieves a classification accuracy of 99.2% on the dataset of Labeled Faces in the Wild. © 2022 Jianhong Lin et al.

Location-specific health impacts of climate change require location-specific responses

Left unmitigated, climate change poses a catastrophic risk to human health, demanding an urgent and concerted response from every country. The 2015 Lancet Commission on Health and Climate Change and The Lancet Countdown: Tracking Progress on Health and Climate Change have been initiated to map out the impacts of climate change and the necessary policy responses. To meet these challenges, Tsinghua University, partnering with the University College London and 17 Chinese and international institutions, has prepared the Chinese Lancet Countdown report, which has a national focus and builds on the work of the global Lancet Countdown: Tracking Progress on Health and Climate Change. Drawing on international methodologies and frameworks, this report aims to deepen the understanding of the links between public health and climate change at the national level and track them with 23 indicators. This work is part of the Lancet's Countdown broader efforts to develop regional expertise on this topic, and coincides with the launch of the Lancet Countdown Regional Centre in Asia, based at Tsinghua University. The data and results of this report are presented at the provincial level, where possible, to facilitate targeted response strategies for local decision-makers. Based on the data and findings of the 2020 Chinese Lancet Countdown report, five recommendations are proposed to key stakeholders in health and climate change in China: (1) Enhance inter-departmental cooperation. Climate change is a challenge that demands an integrated response from all sectors, urgently requiring substantial inter-departmental cooperation among health, environment, energy, economic, financial, and education authorities. (2) Strengthen health emergency preparedness. Knowledge and findings on current and future climate-related health threats still lack the required attention and should be fully integrated into the emergency preparedness and response system. (3) Support research and raise awareness. Additional financial support should be allocated to health and climate change research in China to enhance health system adaptation, mitigation measures, and their health benefits. At the same time, media and academia should be fully motivated to raise the public and politicians' awareness of this topic. (4) Increase climate change mitigation. Speeding up the phasing out of coal is necessary to be consistent with China's pledge to be carbon neutral by 2060 and to continue to reduce air pollution. Fossil fuel subsidies must also be phased out. (5) Ensure the recovery from COVID-19 to protect health now and in the future. China's efforts to recover from COVID-19 will shape public health for years to come. Climate change should be a priority in these interventions. © 2021, Science Press. All right reserved.