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تحقيق الحماية الكاملة لحقوق الإنسان كان ولا يزال الغاية الأساس التي عمل الشعب الصيني والحكومة الصينية من أجلها منذ فترات طويلة، فضلا عن كونه من التطلعات العامة التي يشترك فيها الشعب الصيني مع جميع شعوب العالم. وقد قام (تشانغ بينغ تشون)، بصفته أول ممثل للصين لدى الأمم المتحدة ونائب رئيس لجنة الأمم المتحدة لحقوق الإنسان، بصياغة الإعلان العالمي لحقوق الإنسان مع السيدة رزفلت وممثلين عن باقي دول العالم، وقدموا إسهاما أشاد به العالم أجمع. وتقر الحكومة الصينية بالمبادئ والقيم الخاصة بحقوق الإنسان واعتمدتها، كما حرصت أشد الحرص على استيفاء الواجبات المنصوص عليها في هذه الاتفاقيات، باذلة في الوقت نفسه، ومن واقع ظروفها الوطنية الخاصة، قصارى جهودها لاستكشاف مسار تنمية حقوق الإنسان الذي يتلاءم مع طبيعتها، وذلك لضمان تحقيق إصلاحات مستمرة لحماية حقوق الإنسان جنبا إلى جنب مع التنمية الاقتصادية والاجتماعية، وتحقيق التنسيق والتوازن في حقوق الإنسان، كما أنشأت الصين مجموعة كاملة من أنظمة الحماية الفعالة لحقوق الإنسان، فأصبح مبدأ «احترام الدولة لحقوق الإنسان وصونها» مبدأ دستوريا أساسيا للصين سطره دستور الحزب الشيوعي الصيني الحاكم ليكون المحدد الأساسي لخطط الصين نحو التنمية الاقتصادية والاجتماعية الوطنية قبل أن يصبح أحد المبادئ الرئيسة التي يلتزم بها الحزب والحكومة الصينية في حكم البلاد، ويشكل تطوير خطتي العمل الوطنيتين لحقوق الإنسان في الصين وتنفيذهما بداية مرحلة جديدة لقضية حقوق الإنسان في الصين التي تعرض التنمية المخطط لها والمستمرة والمطردة والتقدم الشامل.

The study is focused on the ecological-fragile and water-shortage region in Northwest China (NWC). A drought-heatwave cluster projection (DHCP) approach is developed based on Stepwise Cluster Analysis (SCA) and multi-level factor analysis (MFA). A multi-model ensemble consisting of 5 global climate models (GCMs) under two shared socioeconomic pathways (i.e., SSPs) is used in the approach. It could investigate the spatiotemporal characteristics of heatwaves, drought, and compound drought-heatwave events (CDHEs) in NWC. A precise projection is given by SCA in 48 stations and four indicators of CDHEs (i.e., CEN, CEDU, CEI, and CEM) are thus calculated. Finally, the individual and interactive effects of uncertainties (i.e., period, SSP, and GCM) are analyzed by MFA. Results show the SCA method can effectively reproduce precise projections for temperature and precipitation for NWC. The frequency, intensity, and duration of heatwaves increase significantly under SSP5-8.5. Drought will ease and then intensify projected by all SSPs. The long-term intensification trend of drought is more pronounced under SSP5-8.5. CDHEs will increase, especially under SSP5-8.5 by the 2090s. These parameters will increase to 4.59 events, 2.86 days per event, 16.7°C per event, and 4.69 days, respectively. Higher increases are found in southeastern Qinghai, northwestern Gansu, and northern Xinjiang. Period affects CDHEs projection mostly. The GCM selection and its interaction with period also affect the projection significantly. DHCP provides a comprehensive analysis of heatwaves and droughts. It is equally applicable to other water shortage areas and is expected to help better manage water resources.

Tibetan medicine has historically engaged in extensive exchanges with the three traditional medicines. These interactions peaked during the Tubo Dynasty (7th-9th century AD). Numerous scholars have acknowledged the close medical and cultural exchanges between Tibetan medicine and the three traditional medicines, but studies offering quantitative and objective comparative results are lacking. This study quantitatively analyzes the above problems from the perspective of medicinal materials and discusses the general use of medicinal materials in Tibetan medicine, the three traditional medical systems, and the exchange of co-used medicinal materials among them. It provides a preliminary analysis of the source composition of Tibetan medicinal materials. Firstly, Data mining: Data were extracted from 20 classical texts on Tibetan medicine, traditional Chinese medicine, Ayurveda and Arabic medicine dating from the 6th century AD to the 10th century AD. Information on medical properties, namely, medicinal taste, distribution, medicinal parts, efficacy, therapeutic use, and usage and dosage of medicinal materials, were systematically compiled to establish the datasets. Secondly, Analysis and comparison: Similarities and differences among medicinal materials used in Tibetan medicine, traditional Chinese medicine, Ayurveda, and Arabic medicine between the 6th and 10th centuries AD were analyzed using the Mann-Whitney test (a non-parametric method) and an intuitive comparison method. The total numbers of medicinal materials in Tibetan medicine, traditional Chinese medicine, Ayurveda, and Arabic medicine were 1229, 2184, 760, and 511, respectively. The overall comparison showed that Tibetan medicine, traditional Chinese Medicine, Ayurveda, and Arabic medicine all used plants as the main source of medicinal materials, accounting for 81.2%, 84.5%, 87.3%, and 79.8%, respectively. There were significant differences in medicinal parts, therapeutic uses, and medicinal taste among them (p < 0.05). In terms of medicinal parts, traditional Chinese medicine mostly used whole herbs and rhizomes, whereas Tibetan medicine, Ayurveda, and Arabic medicine were more inclined to use renewable fruits, seeds, and leaves. Regarding treatment, although the four traditional medicines were generally used to treat digestive diseases, traditional Chinese medicine was more commonly used to treat skin diseases, whereas Ayurveda and Arabic medicine were more commonly used to treat respiratory and urogenital diseases. The comparison of co-used medicinal materials showed that Tibetan medicine had 248 kinds of co-used medicinal materials with Traditional Chinese Medicine, 140 with Ayurveda, and 128 with Arabic medicine. These co-used medicinal materials exhibited similarities and differences in terms of medicinal parts, therapeutic applications, and dose specifications. This study found differences and similarities in the use of medicinal materials across the four traditional medicines. Significant differences in medicinal parts, therapeutic uses, and dosage forms were found, which were attributed to the combined influence of multiple factors, such as medical theory and cultural customs. In addition, a partial overlap was found between the medicinal materials used in Tibetan medicine and the three medical systems. This finding indicates that although grounded in locally available resources, Tibetan medicine has incorporated medicinal material information from traditional Chinese medicine (20.18%), Ayurveda (11.19%), and Arabic medicine (10.41%). Overall, these findings provide an empirical basis for understanding similarities and differences between Tibetan medicine and the three major medical systems and offer a novel perspective for comparative research in traditional medicine.

The aerobic biodegradation of dimethyl phthalate (DMP) is initiated with two hydrolysis reactions that generate an intermediate, phthalic acid (PA), that is further biodegraded through a two-step di-oxygenation reaction. DMP biodegradation is inhibited when PA accumulates, but DMP’s biodegradation can be enhanced by adding an exogenous electron donor. We evaluated the effect of adding succinate, acetate, or formate as an exogenous electron donor. PA removal rates were increased by 15 and 30% for initial PA concentrations of 0.3 and 0.6 mM when 0.15 and 0.30 mM succinate, respectively, were added as exogenous electron donor. The same electron-equivalent additions of acetate and formate had the same acceleration impacts on PA removal. Consequently, the DMP-removal rate, even PA coexisting with DMP simultaneously, was accelerated by 37% by simultaneous addition of 0.3 mM succinate. Thus, lowering the accumulation of PA by addition of an electron increased the rate of DMP biodegradation.

Pyridine and its heterocyclic derivatives are widely encountered in industrial wastewaters, and they are relatively recalcitrant to biodegradation. Pyridine biodegradation is initiated by two mono-oxygenation reactions that compete for intracellular electron donor (2H). In our experiments, UV photolysis of pyridine generated succinate, whose oxidation augmented the intracellular electron donor and accelerated pyridine biodegradation and mineralization. The first mono-oxygenation reaction always was faster than the second one, because electrons provided by intracellular electron donors were preferentially utilized by the first mono-oxygenase; this was true even when the concentration of 2HP was greater than the concentration of pyridine. In addition, the first mono-oxygenation had faster kinetics because it had higher affinity for its substrate (pyridine), along with less substrate self-inhibition.

An internal circulation baffled bioreactor was employed to realize simultaneous di-oxygenation of phthalic acid (PA) and denitrification of nitrate, which require aerobic and anoxic conditions, respectively. Adding a small concentration of succinate as an exogenous electron donor stimulated PA di-oxygenation, which produced readily oxidizable downstream products whose oxidation also enhanced denitrification of nitrate; succinate addition also stimulated denitrification. Depending on the concentration of PA, addition of 0.17 mM succinate increased the PA removal rate by 25 and 42%, while the corresponding nitrate removal rate was increased by 73 and 51%. UV/H 2 O 2 advanced oxidation of PA had the same effects as adding succinate, since succinate is generated by UV/H 2 O 2 ; this acceleration effect was approximately equivalent to adding 0.17 mM succinate.

Multivariate time series classification is of great importance in practical applications and is a challenging task. However, deep neural network models such as Transformers exhibit high accuracy in multivariate time series classification but lack interpretability and fail to provide insights into the decision-making process. On the other hand, traditional approaches based on decision tree classifiers offer clear decision processes but relatively lower accuracy. Swin Transformer (ST) addresses these issues by leveraging self-attention mechanisms to capture both fine-grained local patterns and global patterns. It can also model multi-scale feature representation learning, thereby providing a more comprehensive representation of time series features. To tackle the aforementioned challenges, we propose ST-Tree with interpretability for multivariate time series classification. Specifically, the ST-Tree model combines ST as the backbone network with an additional neural tree model. This integration allows us to fully leverage the advantages of ST in learning time series context while providing interpretable decision processes through the neural tree. This enables researchers to gain clear insights into the model's decision-making process and extract meaningful interpretations. Through experimental evaluations on 10 UEA datasets, we demonstrate that the ST-Tree model improves accuracy in multivariate time series classification tasks and provides interpretability through visualizing the decision-making process across different datasets.

Obesity is a risk factor for asthma in adolescents. \"Although body mass index (BMI) is the most widely used metric for assessing obesity, it has several limitations. The weight-adjusted waist index (WWI) is a novel central obesity indicator and accurately reflects body composition. We aimed to explore the association of WWI with asthma in adolescents using NHANES 1999-2020 data. WWI was calculated based on waist circumference (cm) divided by the square root of weight (kg). Current asthma status in adolescents was determined based on participants' self-reports. Multivariate logistic regression analysis, restricted cubic spline (RCS) analysis, mediation analysis, and stratified analysis were used to comprehensively explore this association. A total of 15,796 adolescents were included. In the fully adjusted model, WWI was positively associated with current asthma in adolescents (odds ratio 1.252, 95% confidence interval 1.125-1.392, p = 0.0001). Participants in the highest WWI quartile (Q4) showed a 54.5% higher prevalence of asthma compared to Q1 (p for trend = 0.0007).. RCS modeling indicated that the association was linear. Mediation analyses indicated that blood eosinophil percentage (EOS%), total cholesterol (TC), and high-density lipoprotein cholesterol (HDL-C) partially mediated this association by 9.89% (p < 0.0001), 7.47% (p = 0.048), and 8.24% (p = 0.044), respectively. This association was independent of BMI, and BMI also did not significantly interact with this association (p for interaction = 0.682). WWI was linearly and positively associated with the prevalence of current asthma among U.S. adolescents, independently of BMI. EOS%, TC, and HDL-C partially mediated this association.

ObjectiveThis study aims to evaluate the correlation between viral clearance and blood biochemical index of 94 discharged patients with COVID-19 infection in Shenzhen Third People’s Hospital, enrolled from Jan 5 to Feb 13, 2020.MethodsThe clinical and laboratory findings were extracted from the electronic medical records of the patients. The data were analysed and reviewed by a trained team of physicians. Information on clinical signs and symptoms, medical treatment, virus clearance, and laboratory parameters including interleukin 6 (IL-6) and C-reactive protein were collected.ResultsCOVID-19 mRNA clearance ratio was identified significantly correlated with the decline of serum creatine kinase (CK) and lactate dehydrogenase (LDH) levels. Furthermore, COVID-19 mRNA clearance time was positively correlated with the length of hospital stay in patients treated with either IFN-α + lopinavir/ritonavir or IFN-α + lopinavir/ritonavir + ribavirin.ConclusionsTherapeutic regimens of IFN-α + lopinavir/ritonavir and IFN-α + lopinavir/ritonavir + ribavirin might be beneficial for treatment of COVID-19. Serum LDH or CK decline may predict a favorable response to treatment of COVID-19 infection.