Geographical Distribution Characteristics Research Articles

Bibliometric and visual analysis of machine learning-based research in acute kidney injury worldwide.

Acute kidney injury (AKI) is a serious clinical complication associated with adverse short-term and long-term outcomes. In recent years, with the rapid popularization of electronic health records and artificial intelligence machine learning technology, the detection rate and treatment of AKI have been greatly improved. At present, there are many studies in this field, and a large number of articles have been published, but we do not know much about the quality of research production in this field, as well as the focus and trend of current research. Based on the Web of Science Core Collection, studies reporting machine learning-based AKI research that were published from 2013 to 2022 were retrieved and collected after manual review. VOSviewer and other software were used for bibliometric visualization analysis, including publication trends, geographical distribution characteristics, journal distribution characteristics, author contributions, citations, funding source characteristics, and keyword clustering. A total of 336 documents were analyzed. Since 2018, publications and citations have increased dramatically, with the United States (143) and China (101) as the main contributors. Regarding authors, Bihorac, A and Ozrazgat-Baslanti, T from the Kansas City Medical Center have published 10 articles. Regarding institutions, the University of California (18) had the most publications. Approximately 1/3 of the publications were published in Q1 and Q2 journals, of which Scientific Reports (19) was the most prolific journal. Tomašev et al.'s study that was published in 2019 has been widely cited by researchers. The results of cluster analysis of co-occurrence keywords suggest that the construction of AKI prediction model related to critical patients and sepsis patients is the research frontier, and XGBoost algorithm is also popular. This study first provides an updated perspective on machine learning-based AKI research, which may be beneficial for subsequent researchers to choose suitable journals and collaborators and may provide a more convenient and in-depth understanding of the research basis, hotspots and frontiers.

Carbon Fiber Composites for Large-Scale Wind Turbine Blades: Applicability Study and Comprehensive Evaluation in China

Wind energy is a type of clean energy that can address global energy shortages and environmental issues. Wind turbine blades are a critical component in capturing wind energy. Carbon fiber composites have been widely recognized for their excellent overall performance in large-scale wind turbine blades. However, in China, the wide application of carbon fiber composites in wind turbine blades still faces many problems and challenges. This paper examines the current state of carbon fiber composites for wind turbine blades and the geographical distribution characteristics of wind resources in China. The economic revenues from increasing the length of wind turbine blades in four typical wind farms, including offshore wind farms, are compared. Using a mathematical model, the energy efficiency of carbon fiber composites in the application of large wind turbine blades is evaluated from the aspects of cost, embedded energy, and carbon footprint. Further, the current relationship between supply and demand for the industrial structure of carbon fiber in China is revealed. The manufacturing technologies for carbon fiber composite wind turbine blades are analyzed, and corresponding countermeasures are proposed. Finally, the incentive policy for applying carbon fiber composites to wind turbine blades is explained, and the development prospects are explored. In this paper, the economics and energy efficiency of the application of carbon fiber composite materials in large wind turbine blades are analyzed and comprehensively evaluated by using mathematical models, which will provide a valuable reference for China’s wind turbine blade industry.

Large-Scale Populus euphratica Distribution Mapping Using Time-Series Sentinel-1/2 Data in Google Earth Engine

Accurate and efficient large-scale mapping of P. euphratica distribution is of great importance for managing and protecting P. euphratica forests, policy making, and realizing sustainable development goals in the ecological environments of desert areas. In large regions, numerous types of vegetation exhibit spectral characteristics that closely resemble those of P. euphratica, such as Tamarix, artificial forests, and allée trees, posing challenges for the accurate identification of P. euphratica. To solve this issue, this paper presents a method for large-scale P. euphratica distribution mapping. The geographical distribution characteristics of P. euphratica were first utilized to rapidly locate the appropriate region of interest and to further reduce background complexity and interference from other similar objects. Spectral features, indices, phenological features, and backscattering features extracted from all the available Sentinel-2 MSI and Sentinel-1 SAR data from 2021 were regarded as the input for a random forest model used to classify P. euphratica in the GEE platform. The results were then compared with the results from the method using only spectral features and index features, the results from the method that only added phenological features, and the results from the method that added phenological features and backscattering features by visually and quantitatively referencing field-surveyed samples, UAV data, and high-spatial-resolution data from Google Earth Data and Map World. The comparison indicated that the proposed method, which adds both phenological and time-series backscattering features, could correctly distinguish P. euphratica from other types of vegetation that have spectral information similar to P. euphratica. The rates of omission errors (OEs), commission errors (CEs), and overall accuracy (OA) for the proposed method were 12.53%, 11.01%, and 89.32%, respectively, representing increases of approximately 9%, 17%, and 13% in comparison with the method using only spectral and index features. The proposed method significantly improved the accuracy of P. euphratica classification in terms of both omission and, especially, commission.

Research on the Heterogeneity Threshold Effect of Foreign Direct Investment and Corporate Social Responsibility on Haze Pollution

Carrying out environmental protection and governance in the process of using foreign capital to develop the economy is a realistic problem that China needs to solve urgently. In order to reduce environmental pollution, all enterprises are called upon by the local government to fulfil CSR and improve the quality of FDI use. However, previous studies have rarely explored the threshold effect of FDI and CSR on haze pollution. This paper employs the threshold effect model to explore the above problem based on panel data of 30 provinces in China from 2009 to 2018. The empirical study found the following: (1) FDI has a significantly positive double-threshold effect on haze pollution. Meanwhile, the promotion effect of FDI on haze pollution is the strongest in the two threshold ranges. (2) CSR has a significantly negative single-threshold effect on haze pollution; that is, the increase in CSR intensity inhibits haze pollution. Such a negative effect shows the characteristics of increasing marginal efficiency. (3) In addition, the provinces in different thresholds display obvious geographical distribution characteristics. Through the above analysis, it can be observed that FDI and CSR have distinct impacts on haze pollution. Thus, the country and the government can reduce haze pollution by improving the investment structure, using environmentally friendly technology, guiding enterprises to abide by business ethics and promoting social responsibilities fulfilment.

Changes in Ecotourism Flow in Hunan Province of China in the Context of COVID-19

This study analyzed the changes in ecotourism flow in Hunan Province before and after the COVID-19 epidemic by obtaining the ecotourism route data for 2019 and 2020 from online tourism platforms such as wasp nest, poor travel, Ctrip, tuniu and qunar, and determining geographical distribution characteristics, node characteristics and network characteristics with the help of software such as UCINET, Netdraw and ArcGIS. The results revealed major changes in spatial distribution, the roles of nodes, and the structure and composition of the flow network. (1) COVID-19 has changed the spatial distribution pattern of ecotourism flows in Hunan Province. Under the influence of the epidemic, the spatial geographical concentration trend in Hunan Province decreased from 30.42 in 2019 to 28.94 in 2020, the flow in the North weakened, and the hot spots shifted to the south. In order to promote the development of global tourism in Hunan Province, we should focus on how to correctly handle the differences in tourism resources and the imbalance in tourism development between the Xiangxi region and other tourism regions. (2) The COVID-19 epidemic triggered changes of the roles of some nodes in the ecotourism flow network in Hunan Province. The comprehensive efficiency value of the node decreased from 266 to 222, indicating that crisis events such as the epidemic have caused damage to the ecotourism flow in Hunan Province, and the surrounding low-density ecotourism sites with good natural scenery have become more favored by tourists after the COVID-19 epidemic. (3) The COVID-19 situation has affected the structure and composition of the ecotourism flow network in Hunan Province. The overall network density of ecotourism flow in Hunan Province increased from 0.18 to 0.14, the degree of separation between ecotourism destinations increased, and tourists' demand for health and safety has driven the development of ecotourism flow in Hunan Province towards multinode and multiregional characteristics.

A review of the indigenous coffee resources of Uganda and their potential for coffee sector sustainability and development.

Uganda is a major global coffee exporter and home to key indigenous (wild) coffee resources. A comprehensive survey of Uganda's wild coffee species was undertaken more than 80 years ago (in 1938) and thus a contemporary evaluation is required, which is provided here. We enumerate four indigenous coffee species for Uganda: Coffea canephora, C. eugenioides, C. liberica (var. dewevrei) and C. neoleroyi. Based on ground point data from various sources, survey of natural forests, and literature reviews we summarise taxonomy, geographical distribution, ecology, conservation, and basic climate characteristics, for each species. Using literature review and farm survey we also provide information on the prior and exiting uses of Uganda's wild coffee resources for coffee production. Three of the indigenous species (excluding C. neoleroyi) represent useful genetic resources for coffee crop development (e.g. via breeding, or selection), including: adaptation to a changing climate, pest and disease resistance, improved agronomic performance, and market differentiation. Indigenous C. canephora has already been pivotal in the establishment and sustainability of the robusta coffee sector in Uganda and worldwide, and has further potential for the development of this crop species. Coffea liberica var. dewevrei (excelsa coffee) is emerging as a commercially viable coffee crop plant in its own right, and may offer substantial potential for lowland coffee farmers, i.e. in robusta coffee growing areas. It may also provide useful stock material for the grafting of robusta and Arabica coffee, and possibly other species. Preliminary conservation assessments indicate that C. liberica var. dewevrei and C. neoleroyi are at risk of extinction at the country-level (Uganda). Adequate protection of Uganda's humid forests, and thus its coffee natural capital, is identified as a conservation priority for Uganda and the coffee sector in general.

Latitudinal transition of epipelagic mesozooplankton in the northwestern Pacific in winter

The northwestern Pacific (NWP) is a hotspot of marine biodiversity study, and zooplankton is a crucial secondary producer in the marine ecosystem. It is of utmost importance to do extensive study on the distribution of zooplankton community in the NWP. The distribution of epipelagic zooplankton community in the 143–146°E section between the equator and 36°N in winter was examined in this study. The findings indicated that the Kuroshio extension, the North Pacific Subtropical Gyre, the North Equatorial Current and the North Equatorial Countercurrent were the four main ocean currents in the NWP that regulated the latitudinal transition of epipelagic mesozooplankton and split the sample section into four station groups. The key factors influencing zooplankton's geographic distribution were temperature, primary productivity, and current movement. In general, as latitude increased, zooplankton abundance and biomass first decreased and subsequently flourished in the NWP. Diversity indexes and indicator species also revealed the difference across the communities in four station groups. The body length of zooplankton declined gradually from north to south under the combined influence of temperature and primary production, with the minimum in the oligotrophic subtropical zone and a sub-peak in the high primary production area near the equator. Additionally, the abundance of zooplankton was higher in the winter than in the summer due to seasonal fluctuations in the properties of the ocean currents. This study elucidated the control effects of ocean currents on the latitudinal distribution of zooplankton, supplemented records of the geographic distribution and body length characteristics of zooplankton communities in the NWP, and provided the basis for further research on the ecological role of zooplankton communities and the global changes of marine ecosystems.

Biogeographic Distribution Patterns and Ecological Mechanisms of Benthic Eukaryotic Microorganisms in Jinsha River

Eukaryotic microbial communities play an important role in biogeochemical cycling and maintaining the health and stability of ecosystems. However, little is known about the geographical distribution patterns, key driving mechanisms, and interspecific interactions of eukaryotic microorganisms in large rivers. This study investigated the geographical distribution characteristics, influencing factors, and interspecific interactions of eukaryotic microorganisms in sediments from the Jinsha River, a cascade hydropower development river in southwest China. The results showed that the α-diversity indices of benthic eukaryotic microorganisms in the Jinsha River increased first and then decreased. The community structure and relative abundance of dominant genera of benthic eukaryotic microorganisms differed significantly among different reaches. The results of distance decay analysis showed that the community assembly of benthic eukaryotic microorganisms in the Jinsha River was influenced by environmental selection and dispersal limitation. The results of variance partitioning analysis and neutral model further demonstrated that the geographical distribution pattern was mainly driven by dispersal limitation. The co-occurrence network analysis revealed that the interspecific competition and network connectivity of the cascade dam reach were weaker than those of the upstream natural reach, indicating that the interactions of benthic eukaryotic microorganisms were stronger in the upstream natural reach. This study supplemented the lack of data on the diversity and geographical distribution of benthic eukaryotic microorganisms in the river of southwest China and provided data support for the ecological response of benthic eukaryotic microorganisms in the river of cascade hydropower development.

Access to Pediatric Ophthalmological Care by Geographic Distribution and US Population Demographic Characteristics in 2022

The geographic distribution of pediatric ophthalmological care has not been reported on since 2007; understanding this distribution could shed light on potential avenues to increase access, which is a necessary first step in addressing the pediatric ophthalmological needs of underserved areas. To analyze the number and location (ie, geographic distribution) of pediatric ophthalmologists in relation to US population demographic characteristics. In this cross-sectional study, public databases from the American Academy of Ophthalmology and American Association for Pediatric Ophthalmology and Strabismus were used to identify pediatric ophthalmologists in the US as of March 2022. Geographic distribution of pediatric ophthalmologists listed in public databases and any association between pediatric ophthalmologist distribution and US population demographic characteristics. Addresses were geocoded using ArcGIS Pro (Esri). A total of 1056 pediatric ophthalmologists (611 men [57.9%]) were identified. States with the most pediatric ophthalmologists were California (n = 116 [11.0%]), New York (n = 97 [9.2%]), Florida (n = 69 [6.5%]), and Texas (n = 62 [5.9%]), the 4 most populous states. A total of 2828 of 3142 counties (90.0%) and 4 of 50 states (8.0%) had 0 pediatric ophthalmologists. In 314 counties (10.0%) with 1 or more pediatric ophthalmologists, the mean (range) pediatric ophthalmologists per million persons was 7.7 (0.4-185.5). The range of practitioner to million persons has increased since 2007. Counties with 1 or more pediatric ophthalmologists had a higher median (SD) household income compared with counties with 0 pediatric ophthalmologists ($70 230.59 [$18 945.05] vs $53 263.62 [$12 786.07]; difference, -$16 966.97; 95% CI, -$18 544.57 to -$14 389.37; P < .001). Additionally, the proportion of families in each county without internet service (8.0% vs 4.7%; difference, 3.4%; 95% CI, 3.0%-3.7%; P < .001), the proportion of persons younger than 19 years without health insurance (5.7% vs 4.1%; difference, 1.6%; 95% CI, 1.1%-2.2%; P < .001), and the proportion of households without vehicle access (2.1% vs 1.8%; difference, 0.3%; 95% CI, 0.6%-5.2%; P = .001) were greater in counties with 0 compared with counties with 1 or more pediatric ophthalmologists. This cross-sectional study found that disparities in access to pediatric ophthalmological care have increased over the past 15 years and are associated with lower socioeconomic status. As patients may rely on online sources to identify the nearest pediatric ophthalmologist, accurate publicly available databases are important.

Meloidogyne graminicola Population Structure in China Suggests a South-to-North Expansion.

The distribution range of root-knot nematode Meloidogyne graminicola is rapidly expanding, posing a severe threat to rice production. In this study, the sequences of cytochrome oxidase subunit I (COI) genes of rice M. graminicola populations from all reported provinces in China were amplified and sequenced by PCR. The distribution pattern and phylogenetic tree showed that all 54 M. graminicola populations in China have distinct geographical distribution characteristics; specifically, cluster 1 (southern China), cluster 2 (central south and southwest China), and cluster 3 (central and eastern China). The high haplotype diversity (Hd = 0.646) and low nucleotide diversity (π = 0.00682), combined with the negative value of Tajima's D (-1.252) and Fu's Fs (-3.06764), suggested that all nematode populations were expanding. The existence of high genetic differentiation (Fst = 0.5933) and low gene flow (Nm = 0.3333) indicated that there was a block of gene exchange between most populations. Mutation accumulation with population expansion might be directly responsible for the high genetic differentiation; therefore, the tested nematode population showed high within-group genetic variation (96.30%). The haplotype Hap8 was located at the bottom of the network topology, with the widest distribution and the highest frequency (59.26%), indicating that it was the ancestral haplotype. The populations in cluster 3 were newly invasive according to the lowest frequency of occurrence of Hap8, the highest number of endemic haplotypes, and the highest total haplotype frequency (60%). In contrast, cluster 1 having the highest genetic diversity (Hd = 0.772, π = 0.01127) indicated that it was the most primitive. Interestingly, the highest gene flow (Nm > 1), lowest genetic differentiation (Fst ≤ 0.33), and closest genetic distance (0.000) only occurred between the Guangdong/Hainan population and others, which suggested that there might be channels for gene exchange between them and that long-distance dispersal occurred. This suggestion is further confirmed by the weak correlation between genetic distance and geographical distance. Based on these data, a hypothesis can be drawn that M. graminicola populations in China were spreading from south to north, specifically from Guangdong and Hainan Provinces to other regions. Natural selection (including anthropogenic) and genetic drift were the main drivers of their evolution. Coincidentally, this hypothesis was consistent with the gradual warming trend and the chronological order of reporting these populations. The main factors influencing current M. graminicola population expansion and distribution patterns might be geography, climate, long-distance seedling transport, interregional operations of agricultural machinery, and rotation mode. It reminds human beings of the necessity to be vigilant about preventing nematode disease according to local conditions all year round.

Trade network characteristics, competitive patterns, and potential risk shock propagation in global aluminum ore trade

Aluminum is an essential strategic mineral resource. The geographical space distribution characteristics make the aluminum ore trade relationship more complicated. This paper analyzes the evolution characteristics, spatial migration, and trade competition of aluminum ore trade from 2011 to 2020. This paper constructs the aluminum supply risk propagation network Aluminum Supply Risk Spread Network to analyze the propagation path, impact scope, and potential impact of different risk outbreak sources. The results show that a few countries control more aluminum ore resources, and the trade community and center of trade gravity have changed significantly. Trade competition gradually intensifies, mainly concentrated in Asia and Europe. When supply risk occurs, the threat spreads rapidly. This paper selects four major trading countries Brazil, Guinea, Australia, and China, as risk outbreak countries. Risk outbreak mainly shows three typical characteristics. Meanwhile, indirect infections account for a large proportion, and China plays an essential role in trade. Finally, based on these findings, some suggestions to maintain the stability of the aluminum resource trade and improve its ability to resist risks for China.

Reevaluación del riesgo de extinción de la pata de elefante Beaucarnea inermis

Abstract Beaucarnea inermis is an endemic species from Northeast Mexico, in the states of San Luis Potosí and Tamaulipas. It is appreciated as an ornamental plant, so its populations are subject to the poaching of individuals for illegal trade. Previous studies determined that their populations have been affected due to the disturbance since the incidence of anthropogenic activities affects the viability of the species. Here we determine the current conservation status of B. inermis and identify their main risk factor by performing an extinction risk assessment based on the Annex II “Method for Evaluation of Risk of Extinction of Plants in Mexico”. We studied 10 populations of B. inermis from protected and non-protected areas in San Luis Potosí and Tamaulipas. We considered the MER criteria: A) geographical distribution characteristics, B) habitat characteristics, C) intrinsic biological vulnerability, and D) impact of human activity. Using field and analyzed data, the MER assessment gives 1.91 points that confirm B. inermis is correctly classified as an Endangered species. The natural protected areas where the species occurs represent cores for its protection; however, the surface of these areas may not be sufficient without biological corridors that connect them.

The Genus &lt;i&gt;Iris&lt;/i&gt; (Iridaceae) in Russia: Phytochemistry, Biological Activity and Application in Traditional Medicine

The genus Iris in Russia is represented by 41 species, of which 4 species are endemic, 11 are included in the Red Book of the Russian Federation and 30 have various regional conservation status. The review provides information on the phytochemical compounds, biological activity and medicinal properties of 16 species growing in Russia, and on their use in traditional medicine of different peoples. The analysis of available data shows that studying the component composition, biological activity levels, and medicinal use of Iris L. species requires their correct identification and the knowledge concerning their geographical distribution, ecology, and morphological characteristics. The use of Iris species in traditional medicine is described. The extracts and compounds isolated from the most of the studied species exhibit analgesic, antioxidative, antipyretic, anti-inflammatory, antibacterial and antimicrobial activity. Some species also have cytotoxic, antitumor, antidiabetic, anti-influenza, neuroprotective, antihyperglycemic, antiallergic, antifeedant and other properties. Most of the isolated metabolites were flavonoids, isoflavonoids, anthocyanes, terpenoids, xantgones, quinones, phenolic and fatty acids. In official and traditional medicine in Asia and Europe, the underground and aboveground parts of Iris aphylla, I. lactea, I. pseudacorus, I. ruthenica, I. sanguinea and other species of the genus are used. The article results from the long-term studies of irises in situ and in the collections of two botanical gardens, as well as extensive examination of literature on the component composition and medicinal properties of the studied species.

New method for morphological identification and simultaneous quantification of multiple tetracyclines by a white fluorescent probe.

The threat of tetracycline antibiotics to the environment and human health is attracting widespread attention. The development of morphological analysis and quantitative techniques of multiple tetracyclines is of great significance for the evaluation of biochemical toxicity, wide-spectrum antibacterial property and degradation cycle between different tetracyclines. In this study, the white fluorescent Eu/Tb@CDs was synthesized and applied successfully to the identification and detection of the most widely used tetracycline antibiotics (tetracycline (TC), oxytetracycline (OC), chlortetracycline (CC) and doxycycline (DC)) with detection limits all below 1nM. For the actual water samples with coexistence of the above 4 tetracyclines, their simultaneous morphology identification and accurate quantitative detection can also be realized through simple spectrometric measurement. In addition, the selective and competitive experiments have been carried out on the pollutants widely present in water, and the results have also confirmed that other pollutants could not interfere with the detection of the above 4 tetracyclines. It is undeniable that this work will conveniently and visually reveal the existence information and geographical distribution characteristics of different tetracycline antibiotics in the environment and their action mechanism on organisms.

Distribution of β-lactamases and emergence of carbapenemases co-occurring Enterobacterales isolates with high-level antibiotic resistance identified from patients with intra-abdominal infection in the Asia-Pacific region, 2015-2018.

In this study, we aimed to assess the geographic distribution and molecular characteristics of β-lactamases among Enterobacterales isolates causing intra-abdominal infections (IAIs) from 2015 to 2018 in the Asia-Pacific region. Isolates were investigated for extended-spectrum β-lactamases (ESBLs), AmpC β-lactamases, and carbapenemases using multiplex PCR assays and full-gene DNA sequencing. A total of 832 Enterobacterales isolates from 8 different countries with β-lactamase genes were analysed. Plasmid-mediated ESBLs and AmpC β-lactamases were encoded in 598 (71.9%) and 314 (37.7%) isolates, respectively. In 710 (85.3%) carbapenemase-negative isolates, positivity for both AmpC β-lactamases and ESBLs was identified in 51 (8.5%) Escherichia coli and 24 (3.4%) Klebsiella pneumoniae isolates. The most prevalent countries were Taiwan and Vietnam, and the co-occurrence of CMY/CTX-M in E. coli and DHA-1/ESBLs in K. pneumoniae was predominant. All isolates showed high susceptibility to colistin, but susceptibility to carbapenems varied among different resistance mechanism combinations. Among 122 (14.7%) isolates encoding carbapenemase, NDM (n=67, including 64.2% NDM-1) was the most common, followed by the OXA-48-type (n=49), KPC (n=24) and IMP (n=4). The most prevalent country was Thailand (n=44), followed by Vietnam (n=35) and the Philippines (n=21). Twenty-two isolates were found to encode multiple carbapenemases, 16 of which were collected from Thailand and harbored NDM-1, OXA-232 and CTX-M-15. Despite high susceptibility to amikacin, susceptibility to colistin was only 56%. The emergence of carbapenem-non-susceptible AmpC/ESBL co-occurring Enterobacterales and colistin non-susceptible carbapenemases co-occurring K. pneumoniae highlights potential therapeutic challenges in the Asia-Pacific region.

Cancer situation in China: what does the China cancer map indicate from the first national death survey to the latest cancer registration?

Over the past four decades, the Chinese government has conducted three surveys on the distribution of causes of death and built cancer registration. In order to shine a new light on better cancer prevention strategies in China, we evaluated the profile of cancer mortality over the forty years and analyzed the policies that have been implemented. We described spatial and temporal changes in both cancer mortality and the ranking of major cancer types in China based on the data collected from three national surveys during 1973-1975, 1990-1992, 2004-2005, and the latest cancer registration data published by National Central Cancer Registry of China. The mortality data were compared after conversion to age-standardized mortality rates based on the world standard population (Segi's population). The geographical distribution characteristics were explored by marking hot spots of different cancers on the map of China. From 1973 to 2016, China witnessed an evident decrease in mortality rate of stomach, esophageal, and cervical cancer, while a gradual increase was recorded in lung, colorectal, and female breast cancer. A slight decrease of mortality rate has been observed in liver cancer since 2004. Lung and liver cancer, however, have become the top two leading causes of cancer death for the last twenty years. From the three national surveys, similar profiles of leading causes of cancer death were observed among both urban and rural areas. Lower mortality rates from esophageal and stomach cancer, however, have been demonstrated in urban than in rural areas. Rural areas had similar mortality rates of the five leading causes of cancer death with the small urban areas in 1973-1975. Additionally, rural areas in 2016 also had approximate mortality rates of the five leading causes with urban areas in 2004-2005. Moreover, stomach, esophageal, and liver cancer showed specific geographical distributions. Although mortality rates have decreased at most of the hotspots of these cancers, they were still higher than the national average levels during the same time periods. Building up a strong primary public health system especially among rural areas may be one critical step to reduce cancer burden in China.

Genetic characterization of Marek's disease virus in chickens in Thailand reveals a high genetic diversity of circulating strains.

Marek's disease (MD) is a highly contagious lymphoproliferative disease of chickens caused by Gallid alphaherpesvirus 2, commonly known as serotype 1 Marek's disease virus (MDV-1). Despite widespread vaccination, MD-related cases have been frequently observed worldwide, including in Thailand. However, no information is available on the genetic characteristics of MDV-1 field strains circulating in chickens in Thailand. This study investigated the geographic distribution and genetic characteristics of MDV-1 field strains circulating in chickens in Thailand between 2013 and 2021 by analysing the Meq and pp38 genes. Out of a total of the 286 clinical samples obtained from 70 chicken farms located in major chicken raising areas of Thailand, 138 samples (48.25%) from 46 chicken farms (65.71%) tested positive for MDV-1 field strains. Results demonstrated that MDV-1 field strains were extensively distributed in major chicken raising areas. Phylogenetic analyses based on the Meq gene revealed that four clusters of MDV-1 circulated in chickens in Thailand between 2013 and 2021. Among these clusters, cluster 1 was the predominant cluster circulating in chickens in Thailand. Additionally, our findings based on molecular characteristics of Meq and pp38 gene/protein suggested that most of the Thai MDV-1 field strains were potentially highly virulent. In conclusion, our data demonstrated the circulation of different clusters of MDV-1 with virulence characteristics in chickens in Thailand, indicating high genetic diversity of MDV-1 in Thailand. This study highlights the importance of more effective vaccine development and routine MDV-1 surveillance for early detection and control of highly virulent MDV-1.

First report of Porcine respirovirus 1 in South Korea.

Porcine respirovirus 1 (PRV1) is a recently emerging porcine respiratory virus that belongs to the genus Respirovirus of the Paramyxoviridae family. Since its first detection in Hong Kong, China in 2009, PRV1 has been subsequently identified in several American and European countries, suggesting that the emerging virus may have been globally distributed. However, in Asia, the virus has been reported only in China. Here, we report that PRV1 was first detected in pigs from 16 farms located in seven provinces across Korea, with a prevalence of 71.4% based on the tested oral fluid samples, suggesting that the virus is already widespread in Korean pig herds. For further genetic characterization of the Korean PRV1 strains, a complete genome and two F gene sequences were obtained from PRV1-positive samples collected from three different pig farms. Phylogenetic analysis based on the complete genome and F gene sequences showed that all three Korean PRV1 strains were grouped into European lineage 1 and were closely related to strains from Hong Kong (China), Germany and Poland. We could not obtain evidence for the origin of Korean PRV1 because of the limited availability of PRV1 sequences. In conclusion, PRV1 was first identified in Korean pig herds and genetically characterized in the present study. These results contribute to a better understanding of the global geographical distribution and genetic characteristics of PRV1.

Long-Term Spatiotemporal Characteristics and Impact Factors of Land Surface Temperature of Inhabited Islands with Different Urbanization Levels

Surface thermal environment (STE) is closely related to the comfort and health of residents, affecting regional livability, and its spatial and temporal changes are deeply affected by the urbanization process. Considering there is a lack of effective comparative analysis on STE in different urbanized inhabited islands, the special geographical unit and vital human settlement environment, long-term spatiotemporal characteristics and impact factor quantitative analyses were performed in two inhabited islands via the RS and GIS methods. The results suggest that the surface heat amplitude of the highly urbanized Xiamen Island decreases, with the surface heat intensity continuing to increase from 2000 to 2020, while that of the lowly urbanized Kinmen Island is reversed. Although the land surface temperature (LST) of the two inhabited islands shows similar spatial distribution characteristics with evident cold/hot spots, the geographical distribution characteristics of high LST zones are significantly different, and the thermal landscape of Xiamen Island is more fragmented, discrete, and simple in shape, as revealed by the landscape metrics. We demonstrate that the area proportion between cooling land (water body and greenland) and warming land (bare land and impervious surface) is the most influential factor of LST in the two islands while the marine environment is a unique contributor to STE of inhabited islands compared with inland cities, where the seawater around the island can reduce LST over a range of distances, and the influence of elevation on LST is mostly indirect. These results provide a scientific basis and case support for understanding the STE situation of inhabited islands with different urbanization levels.

Measuring the Green Total Factor Productivity in Chinese Aquaculture: A Zofio Index Decomposition

Aquatic products are important sources of protein and food consumption, which are pivotal to solving the problem of food shortage. As the world’s largest producer of aquatic products, China’s aquaculture has developed rapidly. However, a large quantity of pollutants has also been generated in the fish farming process, which is detrimental to the sustainable development of China’s aquaculture. Therefore, under double constraints with regard to resources and the environment, fishery development must achieve cleaner production. Measuring green total factor productivity in aquaculture is fundamental to improving aquaculture production efficiency and reducing pollution emissions. This paper investigated the green total factor productivity in China using the SBM-ML method and analyzed the dynamic evolution of fish farming, measuring its change characteristics with regard to time and spatial differences. The results indicated that the total factor productivity indexes of mariculture and freshwater aquaculture in China are 1.050 and 1.060, respectively. Regionally, mariculture in the East China Sea region has the highest green total factor productivity of 1.072, followed by the South China Sea region with 1.056, and the green total factor productivity in the Yellow Sea region is the lowest—only 1.030. The results of the freshwater aquaculture calculations showed the opposite geographical distribution characteristics in China, with the highest in the western region (1.098), followed by the central region (1.046), with the lowest being in the eastern region (1.038). Evidently, both mariculture and freshwater aquaculture have noticeable spatiotemporal heterogeneity. Relevant policy recommendations are provided to improve the green production efficiency of fishery.