Design of a Water Environment Monitoring System Based on Wireless Sensor Networks

A water environmental monitoring system based on a wireless sensor network is proposed. It consists of three parts: data monitoring nodes, data base station and remote monitoring center. This system is suitable for the complex and large-scale water environment monitoring, such as for reservoirs, lakes, rivers, swamps, and shallow or deep groundwaters. This paper is devoted to the explanation and illustration for our new water environment monitoring system design. The system had successfully accomplished the online auto-monitoring of the water temperature and pH value environment of an artificial lake. The system's measurement capacity ranges from 0 to 80 °C for water temperature, with an accuracy of ±0.5 °C; from 0 to 14 on pH value, with an accuracy of ±0.05 pH units. Sensors applicable to different water quality scenarios should be installed at the nodes to meet the monitoring demands for a variety of water environments and to obtain different parameters. The monitoring system thus promises broad applicability prospects

Photoactivation of Cu Centers in Metal-Organic Frameworks for Selective CO2 Conversion to Ethanol.

CO2 hydrogenation to ethanol is of practical importance but poses a significant challenge due to the need of forming one C-C bond while keeping one C-O bond intact. CuI centers could selectively catalyze CO2-to-ethanol conversion, but the CuI catalytic sites were unstable under reaction conditions. Here we report the use of low-intensity light to generate CuI species in the cavities of a metal-organic framework (MOF) for catalytic CO2 hydrogenation to ethanol. X-ray photoelectron and transient absorption spectroscopies indicate the generation of CuI species via single-electron transfer from photoexcited [Ru(bpy)3]2+-based ligands on the MOF to CuII centers in the cavities and from Cu0 centers to the photoexcited [Ru(bpy)3]2+-based ligands. Upon light activation, this Cu-Ru-MOF hybrid selectively hydrogenates CO2 to EtOH with an activity of 9650 μmol gCu-1 h-1 under 2 MPa of H2/CO2 = 3:1 at 150 °C. Low-intensity light thus generates and stabilizes CuI species for sustained EtOH production

The role of genetic predisposition in cardiovascular risk after cancer diagnosis : a matched cohort study of the UK Biobank

Funding Information: This work is supported by the National Natural Science Foundation of China (No. 81971262 to HS), 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University (No. ZYYC21005 to HS), the Swedish Cancer Society (No. 20 0846 PjF to FF), and the EU Horizon2020 Research and Innovation Action Grant (No. 847776 to UV and FF). Publisher Copyright: © 2022, The Author(s).Background: Evidence is scarce regarding the potential modifying role of disease susceptibility on the association between a prior cancer diagnosis and cardiovascular disease (CVD). Methods: We conducted a matched cohort study of UK Biobank including 78,860 individuals with a cancer diagnosis between January 1997 and January 2020, and 394,300 birth year and sex individually matched unexposed individuals. We used Cox model to assess the subsequent relative risk of CVD, which was further stratified by individual genetic predisposition. Results: During nearly 23 years of follow-up, an elevated risk of CVD was constantly observed among cancer patients, compared to their matched unexposed individuals. Such excess risk was most pronounced (hazard ratio [HR] = 5.28, 95% confidence interval [CI] 4.90–5.69) within 3 months after a cancer diagnosis, which then decreased rapidly and stabilised for >6 months (HR = 1.22, 95% CI 1.19–1.24). For all the studied time periods, stratification analyses by both levels of polygenic risk score for CVD and by family history of CVD revealed higher estimates among individuals with lower genetic risk predisposition. Conclusions: Our findings suggest that patients with a recent cancer diagnosis were at an increased risk of multiple types of CVD and the excess CVD risk was higher among individuals with lower genetic susceptibility to CVD, highlighting a general need for enhanced psychological assistance and clinical surveillance of CVD among newly diagnosed cancer patients.Peer reviewe

Pre-pandemic psychiatric disorders and risk of COVID-19 : a UK Biobank cohort analysis

This work is supported by the National Natural Science Foundation of China (81971262 to HS), West China Hospital COVID-19 Epidemic Science and Technology Project (HX-2019-nCoV-014 to HS), Sichuan University Emergency Grant (2020scunCoVyingji10002 to HS), and EU Horizon 2020 Research and Innovation Action Grant (847776 to UAV and FF). We thank the team members involved in West China Biomedical Big Data Center for Disease Control and Prevention for their support. Publisher Copyright: © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 licenseBackground: Psychiatric morbidities have been associated with a risk of severe infections through compromised immunity, health behaviours, or both. However, data are scarce on the association between multiple types of pre-pandemic psychiatric disorders and COVID-19. We aimed to assess the association between pre-pandemic psychiatric disorders and the subsequent risk of COVID-19 using UK Biobank. Methods: For this cohort analysis, we included participants from UK Biobank who were registered in England and excluded individuals who died before Jan 31, 2020, (the start of the COVID-19 outbreak in the UK) or had withdrawn from UK Biobank. Participants diagnosed with a psychiatric disorder before Jan 31 were included in the group of individuals with pre-pandemic psychiatric disorders, whereas participants without a diagnosis before the outbreak were included in the group of individuals without pre-pandemic psychiatric disorders. We used the Public Health England dataset, UK Biobank hospital data, and death registers to collect data on COVID-19 cases. To examine the relationship between pre-pandemic psychiatric disorders and susceptibility to COVID-19, we used logistic regression models to estimate odds ratios (ORs), controlling for multiple confounders and somatic comorbidities. Key outcomes were all COVID-19, COVID-19 specifically diagnosed in inpatient care, and COVID-19-related deaths. ORs were also estimated separately for each psychiatric disorder and on the basis of the number of pre-pandemic psychiatric disorders. As a positive disease control, we repeated analyses for hospitalisation for other infections. Findings: We included 421 014 UK Biobank participants in our study and assessed their COVID-19 status between Jan 31 and July 26, 2020. 50 809 participants were diagnosed with psychiatric disorders before the outbreak, while 370 205 participants had no psychiatric disorders. The mean age at outbreak was 67·80 years (SD 8·12). We observed an elevated risk of COVID-19 among individuals with pre-pandemic psychiatric disorders compared with that of individuals without such conditions. The fully adjusted ORs were 1·44 (95% CI 1·28–1·62) for All COVID-19 cases, 1·55 (1·34–1·78) for Inpatient COVID-19 cases, and 2·03 (1·59–2·59) for COVID-19-related deaths. We observed excess risk, defined as risk that increased with the number of pre-pandemic psychiatric disorders, across all diagnostic categories of pre-pandemic psychiatric disorders. We also observed an association between psychiatric disorders and elevated risk of hospitalisation due to other infections (OR 1·74, 95% CI 1·58–1·93). Interpretation: Our findings suggest that pre-existing psychiatric disorders are associated with an increased risk of COVID-19. These findings underscore the need for surveillance of and care for populations with pre-existing psychiatric disorders during the COVID-19 pandemic. Funding: National Natural Science Foundation of China.Peer reviewe

Public awareness, emotional reactions and human mobility in response to the COVID-19 outbreak in China- A population-based ecological study

This work is supported by the West China Hospital COVID-19 Epidemic Science and Technology Project (No. HX-2019-nCoV-014 to Dr Song, No. HX-2019-nCoV-019 to Dr Zhang), Sichuan University Emergency Grant (No. 2020scunCoVyingji1002 to Dr Song, No. 2020scunCoVyingji1005 to Dr Zhang), and Emergency Grant form Science & Technology Department of Sichuan Providence (No. 2020YFS0007 to Dr Zhang). Publisher Copyright: © 2020 Cambridge University Press. All rights reserved.Background: The outbreak of COVID-19 generated severe emotional reactions, and restricted mobility was a crucial measure to reduce the spread of the virus. This study describes the changes in public emotional reactions and mobility patterns in the Chinese population during the COVID-19 outbreak. Methods: We collected data on public emotional reactions in response to the outbreak through Weibo, the Chinese Twitter, between January 1st and March 31st, 2020. Using anonymized location-tracking information, we analyzed the daily mobility patterns of approximately 90% of Sichuan residents. Results: There were three distinct phases of the emotional and behavioral reactions to the COVID-19 outbreak. The alarm phase (January 19th�26th) was a restriction-free period, characterized by few new daily cases, but enormous public negative emotions (the number of negative comments per Weibo post increased by 246.9 per day, 95%CI: 122.5�371.3), and a substantial increase in self-limiting mobility (from 45.6% to 54.5%, changing by 1.5% per day, 95%CI: 0.7%�2.3%). The epidemic phase (January 27th�February 15th) exhibited rapidly increasing numbers of new daily cases, decreasing expression of negative emotions (a decrease of 27.3 negative comments per post per day, 95%CI:-40.4�-14.2), and a stabilized level of self-limiting mobility. The relief phase (February 16th�March 31st) had a steady decline in new daily cases and decreasing levels of negative emotion and self-limiting mobility. Conclusions: During the COVID-19 outbreak in China, the public�s emotional reaction was strongest before the actual peak of the outbreak and declined thereafter. The change in human mobility patterns occurred before the implementation of restriction orders, suggesting a possible link between emotion and behavior.Peer reviewe

Adverse health consequences of undiagnosed hearing loss at middle age : A prospective cohort study with the UK Biobank

Funding Information: 1.3.5 Project for Disciplines of Excellence, West China Hospital, Sichuan University (grant no. ZYYC21005 to HS) and National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University (grant no. Z20201013 to HS). Funding Information: This research has been conducted using the UK Biobank Resource under Application 54803. This work uses data provided by patients and collected by the NHS as part of their care and support. This research used data assets made available by National Safe Haven as part of the Data and Connectivity National Core Study, led by Health Data Research UK in partnership with the Office for National Statistics and funded by UK Research and Innovation. We thank the team members involved in West China Biomedical Big Data Center for their support. Publisher Copyright: © 2023 The Author(s)Objectives: Hearing impairment is common in the middle-aged population but remains largely undiagnosed and untreated. The knowledge about to what extent and how hearing impairment matters for health is currently lacking. Thus, we aimed to comprehensively examine the adverse health consequences as well as the comorbidity patterns of undiagnosed hearing loss. Study design: Based on the prospective cohort of the UK Biobank, we included 14,620 individuals (median age 61 years) with audiometry-determined (i.e., speech-in-noise test) objective hearing loss and 38,479 individuals with subjective hearing loss (i.e., tested negative but with self-reported hearing problems; median age 58 years) at recruitment (2006–2010), together with 29,240 and 38,479 matched unexposed individuals respectively. Main outcome measures: Cox regression was used to determine the associations of both hearing-loss exposures with the risk of 499 medical conditions and 14 cause-specific deaths, adjusting for ethnicity, annual household income, smoking and alcohol intake, exposure to working noise, and BMI. Comorbidity patterns following both exposures were visualized by comorbidity modules (i.e., sets of connected diseases) identified in the comorbidity network analyses. Results: During a median follow-up of 9 years, 28 medical conditions and mortality related to nervous system disease showed significant associations with prior objective hearing loss. Subsequently, the comorbidity network identified four comorbidity modules (i.e., neurodegenerative, respiratory, psychiatric, and cardiometabolic diseases), with the most pronounced association noted for the module related to neurodegenerative diseases (meta-hazard ratio [HR] = 2.00, 95%confidence interval [CI] 1.67–2.39). For subjective hearing loss, we found 57 associated medical conditions, which were partitioned into four modules (i.e., diseases related to the digestive, psychiatric, inflammatory, and cardiometabolic systems), with meta-HRs varying from 1.17 to 1.25. Conclusions: Undiagnosed hearing loss captured by screening could identify individuals with at greater risk of multiple adverse health consequences, highlighting the importance of screening for speech-in-noise hearing impairment in the middle-aged population, for potential early diagnosis and intervention.Peer reviewe