1. A disease occurring among Chinese in Malaya is described. The main complaints are weakness and numbness of the legs ; and the main signs absent tendon reflexes, sensory loss and ataxia.
2. The aetiology is discussed and the disease is thought to be a form of pellagra modified by other factors in the diet or circumstances of those affected.
In 2020, coronavirus disease (COVID-19) left around 81% of the global workforce, nearly 2.7 billion workers, affected. Employment in China was the first to be hit by COVID-19. The Regional Comprehensive Economic Partnership (RCEP) is expected to bring dynamism to China's employment market in an era of long COVID-19. This study aims to examine the number of sectoral jobs that the RCEP will create in China, with the number of skilled or unskilled labour employed in each sector. The exogenous shocks to the RCEP can be reflected in the number of jobs created through multipliers based on a social accounting matrix compiled from China's input-output tables in 2017, combined with the employment satellite accounts compiled. The results show that the RCEP is expected to create over 17 million potential jobs in China, with unskilled labour accounting for 10.44 million and skilled labour for 6.77 million. It is even expected that there will be job losses in the metalworking machinery sector. The contribution of this paper can serve as a reference for policies to protect vulnerable sectors, further open up trade markets and strengthen cooperation among RCEP members as important measures to address the employment impact of long COVID-19.
Music streaming platforms have recently become one of the latest innovative music devices used to replace traditional music sets. In order to examine users' behavior on music streaming platforms, this study proposes an extended research model based on flow theory and investigates the relationship between flow experience and co-creation behavior. A partial least square methodology was employed to test the proposed model and corresponding hypotheses on data collected from 390 survey samples. The results showed that flow experience has a significant influence on users' co-creation behavior. Among the three antecedents, only perceived skill and perceived interactivity have the strongest effects on flow experience, while perceived control has little effect on flow experience. This study discusses some valuable theoretical implications and offers insights useful for both researchers and practitioners.
The genus Airapus Stebnicka Howden, 1996 currently comprises 26 extant species distributed in the Australian and Oriental zoogeographical regions (Stebnicka Howden 1996; Stebnicka 1998, 2009; Rakovič et al. 2019; Král et al. 2019; Minkina 2020) and one fossil species from the Eocene Baltic amber (Tamutis et al. 2017). Of the continental Southeast Asia, only three species have been known so far: Airapus cechovskyi Král, Mencl Rakovič, 2019 (mainland Malaysia: Kelantan), A. tyri Král, Mencl Rakovič, 2019 (Central Thailand: Phetchaburi Province) and A. sicardi ( Paulian, 1945) (Laos: "Cochinchine: Long Xuyen" and South Vietnam: "Annam: Tanh Hoa") (Paulian 1945; Balthasar 1964; Král et al. 2019). Examination of the material housed in the collections of the Institute of Zoology, Chinese Academy of Sciences, Beijing, China, revealed Airapus material belonging to an undescribed species. Its formal description is presented in this paper. This new species is another, fourth species occurring in mainland Southeast Asia. It is also the first country record from China. The geographical distribution of the genus is now known to the north as far as Fujian Province.
Oliparisca menglaensis sp. nov. (Hemiptera: Fulgoromorpha: Cixiidae: Pentastirini) is described and illustrated from Yunnan Province of China. This represents the first record of the genus Oliparisca from China. The new taxon extends the distribution range of the genus Oliparisca, previously known only from Indonesia, Malaysia, Philippines and Sri Lanka. A key of identification to all known species of this genus and a map of their geographic distributions are provided.
Sediment is the ultimate reservoir of effluent from landmasses. This includes octylphenol (OP) and nonylphenol (NP), two chemical compounds which are known with the ability to disrupt the normal functions of hormones in the organism. To our knowledge, no study of these compounds in the marine sediment of Malaysia has been published to date. Hence, this study presents the level of OP and NP in the sediment of the South China Sea and Malacca Strait, Malaysia. The extraction of compounds was done using the liquid-liquid extraction method and followed by clean-up using solid-phase extraction cartridges. The range of OP in Malacca Strait (1.00-27.16 ng/g dw) was greater than in the South China Sea (5.12-14.16 ng/g dw) whereas a similar range of NP was found in the South China Sea (1.32-23.76 ng/g dw) and Malacca Strait (0.79-27.59 ng/g dw). The concentration of both compounds was consistently high near Redang Island (E2A) and Penang (W32 and W43) suggesting continuous input of these chemicals from this nearby land. Risk quotient (RQ) values of OP showed the potential risk to benthic communities in 4/7 and 21/47 sampling points of the respective South China Sea and Malacca Strait. Both water bodies are located far from the wastewater effluent and yet able to retain these chemicals in their sediment. This suggests that the wastewater treatment system as well as dilution effects do not prevent these chemicals to be ended up in the marine environment.
Today's rule of law construction in China is walking between the conflict and coordination of factors such as reality and ideals, tradition and modernity, local and foreign, and local knowledge and universal principles, all while continuing to strengthen the unification of the legal system and advance the modernization of the rule of law. Traditional customary law, which is the most representative local resource culture, is unquestionably one of the most important themes in the formation of the rule of law. It has far-reaching significance for the development of ethnic jurisprudence, the reunderstanding of traditional culture, and the construction of ethnic unity and harmonious society. Based on this background, this paper uses big data technology to collect relevant experimental data and proposes a traditional customary law value assessment based on BPNN. The completed work is as follows: (1) this paper clarifies the concept of customary law and the difference between it and related concepts and introduces the domestic relevant research on traditional customary law and the interactive relationship between customary law and national law in dynamic legal practice and puts forward the status and influence of customary law in contemporary legal practice. (2) The related technologies of neural network are introduced, and a traditional customary value evaluation system that can be used for experiments is constructed. (3) Experiment with the designed data set to see if the BP model is feasible. The experimental results suggest that the model proposed in this study has a low error rate and performs well while evaluating traditional common law values.
The construction of low-carbon cities is an essential component of sustainable urban development. However, there is a lack of a comprehensive low-carbon city design and evaluation system that incorporates "carbon sink accounting-remote sensing monitoring-numerical modelling-design and application" in an all-around linkage, multi-scale coupling, and localized effects. This paper utilizes the Citespace tool to evaluate low-carbon city design applications by analyzing literature in the Web of Science (WOS) core collection database. The results reveal that low-carbon cities undergo four stages: "measurement-implementation-regulation - management." The research themes are divided into three core clustering evolutionary pathways: "extension of carbon sink functions," "spatialisation of carbon sink systems," and "full-cycle, full-dimensional decarbonisation." Applications include "Utility studies of multi-scale carbon sink assessments," "Correlation analysis of carbon sink influencing factors," "Predictive characterisation of multiple planning scenarios," and "Spatial planning applications of urban sink enhancement." Future low-carbon city construction should incorporate intelligent algorithm technology in real-time to provide a strong design basis for multi-scale urban spatial design with the features of "high-precision accounting, full-cycle assessment and low-energy concept."
Rapid global urbanization has made brownfield reuse a vital issue for sustainable urban development. However, the regeneration of brownfield landscapes is a complex and lengthy process that requires a combination of factors to be considered. Their landscape regeneration must be planned and prioritized to utilize brownfield sites and achieve positive social benefits. Therefore, an urgent need must be established to establish an assessment framework and system for various types of brownfield landscape regeneration dominant factors to find different brownfield landscape regeneration dominant factors. This research developed an assessment model using the Analytic Hierarchy Process (AHP), covering five brownfield types: industrial, mining, military, transportation, and landfill in Xi'an, China. The potential assessment factors in three levels were analyzed for weighting to explore the dominant factors for the potential regeneration of brownfield landscapes in Xi'an. The results showed that, firstly, among the five first-level assessment factors, the physicality factor was the most important. Secondly, among the 16 second-level factors, the spatial and physical features of the visual landscape were the most critical. Finally, among the 40 three-level factors, spatial features were the primary factor. Therefore, the purpose of this research is to provide a specific assessment system and data analysis methods and ideas for the dominant factors of urban brownfield landscape regeneration in China and other regions based on the assessment framework with strong adaptability proposed by the AHP method, which can be flexibly adapted in the different areas and countries, to realize the sustainable development of cities in various regions.
Agricultural carbon emission is an important cause of climate change, and the carbon transfer caused by agricultural trade is a key area related to carbon emissions of all countries. Based on the Eora database, this paper aims to constructs a multi-region input-output database of 185 countries or regions, analyzes a spatial correlation network of embodied net carbon transfer in global agricultural trade by using UCINET, selects multi-dimensional network measurement indicators, and comprehensively studies the global evolution characteristics and functional features of network plate role of embodied carbon transfer in the global agricultural trade. The result shows that the embodied net carbon transfer network of global agricultural trade is densely connected, the spatial correlation spillover effect is significant, and the edge of the network core structure is clear. On the one hand, the top four countries or regions in terms of embodied carbon outflow in agricultural trade are the USA, Australia, Vietnam, and China. On the other hand, the top four countries or regions of embodied carbon inflow are Malaysia, Central Africa, Singapore, and Serbia. From the perspective of outdegree, indegree, proximity centrality, and intermediary centrality, Cambodia, the Netherlands, Vietnam, Ghana, and South Africa, with the high frequency of the shortest path of the globally embodied net carbon transfer network, have a strong influence and linking facility in spatial correlation and have a strong control ability to the spatial correlation of other countries or regions. The embodied carbon emission network of global agricultural trade can be divided into four sectors: main spillover, two-way spillover, broker, and main benefit. The main spillover segment, constituted by the USA, India, Germany, and China, has significant embodied carbon spillover effects on the internal segment and other segments. It is the main embodied carbon spillover sector of embodied net carbon transfer of global agricultural trade. Countries should reasonably allocate the responsibility of carbon reduction according to the trading embodied carbon transfer and made efforts to optimize the export structure of agricultural products.
Insufficient and low public service quality in China has resulted in unfulfilled resident needs, necessitating an examination to improve public service quality. Thus, this study constructs a public service quality index for 29 provinces covering 2004-2020 to explore the relationship between expenditure decentralization and public service quality. Using Fixed effects model, OLS and System Generalized Method of Moments (SYS-GMM) technique, this study reveals that expenditure decentralization has a significantly positive effect on public service quality, with a 1 % increase in expenditure decentralization leading to a 0.287 % improvement in public service quality. Additionally, the impact of expenditure decentralization on public service quality in the eastern and central regions is positively significant, while in the western region, expenditure decentralization does not positively affect public service quality. Furthermore, based on the public service quality theory, this study finds that FDI and fiscal self-sufficiency can enhance the relationship between expenditure decentralization and public service quality. The study provides evidence-based recommendations for policymakers to prioritize expenditure decentralization as a strategy to enhance public service quality, especially when considering attracting FDI and promoting fiscal self-sufficiency.
Urban infrastructure, particularly in ageing cities, faces significant challenges in maintaining building aesthetics and structural integrity. Traditional methods for detecting diseases on building exteriors, such as manual inspections, are often inefficient, costly, and prone to errors, leading to incomplete assessments and delayed maintenance actions. This study explores the application of advanced deep learning techniques to accurately detect diseases on the exterior surfaces of buildings in urban environments, aiming to enhance detection efficiency and accuracy while providing a real-time monitoring solution that can be widely implemented in infrastructure health management. The research implemented a deep learning model that improves feature extraction and accuracy by integrating DenseNet blocks and Swin-Transformer prediction heads, trained and validated using a dataset of 289 high-resolution images collected from diverse urban environments in China. Data augmentation techniques improved the model's robustness against varying conditions. The proposed model achieved a high accuracy rate of 84.42%, a recall of 77.83%, and an F1 score of 0.81, with a detection speed of 55 frames per second. These metrics demonstrate the model's effectiveness in accurately identifying complex damage patterns, such as minute cracks, even within noisy urban environments, significantly outperforming traditional methods. This study highlights the potential of deep learning to transform urban maintenance strategies by offering a practical solution for the real-time detection of diseases on building exteriors, ultimately enhancing the efficiency and accuracy of urban infrastructure monitoring and contributing to improved maintenance practices and timely interventions.