Trends in surface air temperature (SAT) are a critical indicator for climate change at varied spatial scales. Because of urbanization effects, however, the current SAT records of many urban stations can hardly meet the demands of the studies. Evaluation and adjustment of the urbanization effects on the SAT trends are needed, which requires an objective selection of reference (rural) stations. Based on the station history information from all meteorological stations with long-term records in mainland China, an integrated procedure for determining the reference SAT stations has been developed and is applied in forming a network of reference SAT stations. Historical data from the network are used to assess the urbanization effects on the long-term SAT trends of the stations of the national Reference Climate Network and Basic Meteorological Network (RCN+BMN or national stations), which had been used most frequently in studies of regional climate change throughout the country. This paper describes in d...

An Integrated Procedure to Determine a Reference Station Network for Evaluating and Adjusting Urban Bias in Surface Air Temperature Data

There has been significant effort devoted to investigating long-term trends in land surface air temperature over mainland China by Chinese scientists over the past 50 years, and much progress has been made in understanding dynamics of the changes. This review highlights research conducted by early Chinese climatologists, and particularly Professor Shaowu Wang from Peking University, with special focus on systematic work that has been conducted since the mid to late 1970s. We also discuss major issues that remain unresolved in past and current studies. The most recent analyses indicate that the country-average annual mean surface air temperature rose by 1.12°C over the past 115 years (1901–2015), with a rate of increase of about 0.10°C decade–1. Temperatures have risen more rapidly since the 1950s, with the rate of increase of more than 0.25°C decade-1. However, the recent increase in temperatures is in large part due to contamination by systematically biased data. These data are influenced by unprecedented urbanization in China, with a contribution of urbanization to the overall increase of annual mean temperatures in mainland China of about one third over the past half a century. If the bias is corrected, the rate of increase for the country-average annual mean surface air temperature is 0.17°C decade–1 over the last 50–60 years, which is approximately the same as global and Northern Hemispheric averages in recent decades. Future efforts should be focused towards the recovery and digitization of early-year observational records, the homogenization of observational data, the evaluation and adjustment of urbanization bias in temperature data series from urban stations, the analysis of extreme temperatures over longer periods including the first half of the 20th century, and the investigation of the observed surface air temperature change mechanisms in mainland China.

An overview of mainland China temperature change research

Land use and land cover (LULC) in the Beijing–Tianjin–Hebei region has changed significantly since 1990. To comprehensively understand its impact on meteorology, this paper uses an LULC transfer matrix to discuss changes 10 years before the millennium (BM) and 10 years after the millennium (AM). The Weather Research and Forecasting (WRF) model is used to simulate air temperature, precipitation, and wind speed in January and July using 1990, 2000, and 2010 LULC data. The temperature increase in the AM period (0.118 °C) was greater than that in the BM period (0.042 °C) and increased by 0.36 °C in response to the transformation from croplands to urban and built-up lands (UBL). The change in precipitation showed an obvious seasonal difference, where the trend decreased in winter and increased in summer. There was a small band of precipitation change that extended from Beijing to Shijiazhuang. The wind speed at 10 m decreased by 0.04 m/s in winter and 0.017 m/s in summer. Simultaneously, the impact on meteorology from different classification transformations was quantified. The region where land was transformed into UBL had the largest reduction in wind speed, and was later transformed into woodlands. A comprehensive discussion on the impact of LULC changes on climate should support the future development of more environmentally compatible and sustainable land planning.

Impact of land-use and land-cover change on meteorology in the Beijing-Tianjin-Hebei region from 1990 to 2010

Based on combined thresholds of daily maximum and minimum temperatures, a compound heat wave is defined, and then changes in multiple aspects of such heat waves in China are estimated between 1961 and 2015. Our results intriguingly indicate that severe compound heat waves in northern China are characterized by excessively high intensity within short duration, while long duration determines great disaster-causing potential of severe events in the south. In the past few decades, large areas of China have experienced longer, stronger, and more frequent compound heat waves. Northern China has witnessed dramatic intensity increases, with a maximum amplification over 5°C decade–1; while remarkable lengthening in duration has been mostly recorded in the south, with a maximum trend over 1 day decade–1. The spatial extent affected by compound heat waves has significantly expanded since the 1960s, with the largest expanding rate over 6% decade–1 detected in North China and Northeast China. These systematic assessments serve to deepen our understanding of observed changes in compound heat waves across China, and may further shed some light on future adaptations and mitigations against an increasingly warming climate.

Observed Trends in Various Aspects of Compound Heat Waves across China from 1961 to 2015

Identifying and separating the signal of urbanization effects in current temperature data series is essential for accurately detecting, attributing, and projecting mean and extreme temperature change on varied spatial scales. This paper proposes a new method based on machine learning to classify the observational stations into rural stations and urban stations. Based on the classification of rural and urban stations, the global and regional land annual mean and extreme temperature indices series over 1951–2018 for all stations and rural stations were calculated, and the urbanization effects and the urbanization contribution of global land annual mean and extreme temperature indices series are quantitatively evaluated using the difference series between all stations and the rural stations. The results showed that the global land annual mean time series for mean temperature and most extreme temperature indices experienced statistically significant urbanization effects. The urbanization effects in the mean and extreme temperature indices series generally occurred after the mid-1980s, and there were significant differences of the magnitudes of urbanization effects among different regions. The urbanization effect on the trends of annual mean and extreme temperature indices series in East Asia is generally the strongest, which is consistent with the rapidly urbanization process in the region over the past decades, but it is generally small in Europe during the recent decades.

Urbanization Effects on Estimates of Global Trends in Mean and Extreme Air Temperature

Based on daily temperature data from an urban station and four rural stations of Shijiazhuang area in Hebei Province, North China, we analyzed the trends of extreme temperature indices series of the urban station (Shijiazhuang station) and rural stations during 1962–2011 and the urbanization effect on the extreme temperature indices of the urban station. The results showed that the trends of annual extreme temperature indices of the urban station and the rural stations are significantly different in the recent 50 years. Urbanization effect on the long-term trends of hot days, cold days, frost days, diurnal temperature range (DTR), extreme maximum temperature, and extreme minimum temperature at the urban station were all statistically significant, reaching 1.10 days/10 years, −2.30 days/10 years, −2.55 days/10 years, −0.20 °C/10 years, 0.16 °C/10 years, and 0.70 °C/10 years, respectively, with the urbanization contributions to the overall trends reaching 100, 38.0, 42.2, 40.0, 94.1, and 47.0 %, respectively. The urbanization effect on trend of ice days was also significant, reaching −0.47 days/10 years. However, no significant urbanization effect on trends of minimum values of maximum temperature and maximum values of minimum temperature had been detected. The urbanization effects in the DTR and extreme minimum temperature series of Shijiazhuang station in wintertime were highly significant.

Urbanization effect on long-term trends of extreme temperature indices at Shijiazhuang station, North China

Objective This study aimed to establish a pediatric lower respiratory tract infections (PLRTIs) database based on the structured electronic medical records (SEMRs), to provide a brief overview and the usage process of the SEMRs and the database. Methods All the medical information is recorded by a clinical information system developed by Eureka Systems Company. A plugin of the software was used to set the properties of items of the SEMR. Children with lower respiratory tract infections (LRTIs) who were admitted to the department of respiratory medicine of our hospital from May 2020 were included. PostgreSQL 13.1 software was used to construct the PLRTIs database. Results Seven kinds of SEMRs were established, and the admission record was the most important and complex among them. It was mainly composed of 10 parts, i.e., basic information, history of present illness, past history (without respiratory disease), past history of respiratory diseases, personal history, family history, physical examination, the score of LRTIs, auxiliary examination, and diagnosis. With the three-level doctor ward round, the recorded information of the SEMR would be checked repeatedly, thus guaranteeing the correctness of the information. The data of the SEMR and laboratory tests could be extracted directly from the hospital information system (HIS) by PostgreSQL 13.1 software with the specific structured query language (SQL) code. After manually checking the original records, the datasets were imported into PostgreSQL 13.1 software, and a simple PLRTIs database was constructed. According to the inclusion criteria of this study, a total of 1,184 children with LRTIs were included in this database from 1 May 2020 to 30 April 2021. Conclusion A series of SEMRs for PLRTIs were designed and used during the hospitalization. A simple PLRTIs database was established based on the SEMR. The SEMRs will provide complete and high-quality data on LRTIs in children.

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Establishment of a Simple Pediatric Lower Respiratory Tract Infections Database Based on the Structured Electronic Medical Records

The purpose of participating in sports is to enhance physical fitness and promote physical and mental health. The occurrence of sports injuries will cause physical and mental injuries to athletes, especially the ankle joint injuries that often occur. Therefore, it is particularly important to understand the causes, symptoms, treatment, and prevention of athletes' ankle injuries. This article aims at studying the significance of comprehensive rehabilitation nursing for the rehabilitation of sports-induced ankle joint injuries and introduces the concepts of comprehensive rehabilitation nursing and ankle joint injuries. This article proposes how to use comprehensive rehabilitation nursing to recover ankle injuries caused by sports based on smart medical care. In the experiment of this article, it can be seen from Table 5 that the recovery speed of 5 athletes with ankle joint injuries before rehabilitation training was 8% (lowest) and 14% (highest). The recovery rate after rehabilitation care is up to 25%. It can be seen that comprehensive rehabilitation care is of great help to athletes with ankle injuries. As can be seen from Table 4, the number of ankle injuries in acute secondary injuries is 25, accounting for 33%, which is the highest; the number of contusions is 15, accounting for 21%, which is the lowest ratio, so it can be seen that the ankle joint injury in sports is the most serious. Therefore, the application of comprehensive rehabilitation care needs to be popularized, which is of great significance to ankle joint injuries. The ankle joint is one of the most easily sprained joints in the human body, not only because of the flexibility of the ankle joint, but also because of the anatomical characteristics of the ankle joint. The main cause of ankle injuries is inappropriate behavior in sports.

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The Effect of Comprehensive Rehabilitation Nursing on the Rehabilitation of Sports-Induced Ankle Joint Injuries

With the development of artificial intelligence technology in the medical field, clinical trials using artificial intelligence as an intervention method are constantly emerging. This article mainly introduces the intervention of artificial intelligence and emotional intelligence on the rehabilitation of athletes' muscle strains. Among them, artificial intelligence and emotional intelligence are a brand-new nursing intervention method. This article compares conventional rehabilitation therapy with these two new types of intelligent interventions to explore the effects of artificial intelligence intervention and emotional intelligence intervention in the rehabilitation of athletes. The experimental results show that the average number of muscle restrains under the intervention of artificial intelligence is 4.1 times, the average restrain rate of muscles is 27.7%, and the average recovery degree of athletes is 94.7%. The average SPB score under emotional intelligence intervention was 56 points. Artificial intelligence interventions can enhance rehabilitation through advanced technology, and emotional intelligence interventions can provide emotional support to effectively improve treatment outcomes and quality of life.

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Rehabilitation Treatment of Muscle Strain in Athlete Training under Intelligent Intervention

Apple geminivirus 1 (AGV) in the genus Maldovirus of the family Geminiviridae was first identified infecting apple trees in the year 2015 in China. In this work, we characterized three isolates of the AGV in the Chinese pearleaf crabapple (Malus asiatica) in Inner Mongolia Autonomous Region. The viruses were detected by Illumina sequencing and its existence was confirmed by reverse transcription-polymerase chain reaction (RT-PCR) amplification of an AGV fragment. Between the three AGV isolates and the initially characterized AGV isolate PL2015, the nucleotide sequence identities of the complete genome ranged from 91.2 to 91.7%, of the coat protein gene (V1) ranged from 95.4% to 97.3%, and of the replicase gene (C1) ranged from 87.3% to 88.0%. Phylogenetic analysis indicated that the three isolates formed a monophyletic group together with the AGV, separated from the current genera in the family Geminiviridae. This is the first description of the AGV infecting crabapples.

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Bingxiang Zhang

Papers

Urbanization effect on long-term trends of extreme temperature indices at Shijiazhuang station, North China

Establishment of a Simple Pediatric Lower Respiratory Tract Infections Database Based on the Structured Electronic Medical Records

The Effect of Comprehensive Rehabilitation Nursing on the Rehabilitation of Sports-Induced Ankle Joint Injuries

Rehabilitation Treatment of Muscle Strain in Athlete Training under Intelligent Intervention

Molecular Characterization of Three Apple Geminivirus Isolates in Crabapples Detected in Inner Mongolia, China