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"Bin Wang"
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Dynamic genesis potential index for diagnosing present-day and future global tropical cyclone genesis
Tropical cyclone (TC) genesis potential index (GPI) has been extensively used to understand the processes governing climate variability and future change of TC genesis (TCG). However, the relative roles of the thermodynamic versus dynamic environmental factors in TC genesis remain elusive, especially under a warming world. Here we show that four leading dynamic factors, the 850 hPa absolute vorticity, 500 hPa vertical motion, tropospheric vertical wind shear, and 500 hPa shear vorticity of zonal winds, are objectively identified by the logarithmic stepwise regression analysis from 11 dynamic and thermodynamic candidate factors. We further demonstrate that the model results from a TC-permitting global model ascertain the four leading dynamical factors as the most influential in both the present-day simulation and future projection under global warming. A dynamic GPI, consisting of the four dynamic parameters, provides a diagnostic tool for understanding future change of TC genesis. Meanwhile, it improves skills in representing interannual variations of TCG frequency in the western Pacific and Southern Hemisphere oceans.
Journal Article
Bridging science and policy implication for managing climate extremes
\"Since 1980, the number of climate-related disasters has been greatly increased glocally. Scientific consensus based on the IPCC fifth report suggested that global warming would bring more intense and frequent extreme climate events. These climate-related disasters hinder the achievement of sustainable economic growth and prosperity by disrupting supply chains, impeding production, destroying infrastructure, and necessitating high-cost rebuilding and recovery. To mitigate the climate extreme risks and possible losses, it is essential to maximize the utilization of scientific outputs and to share best practices in disaster risk management. Aligned with such purposes, Asia-Pacific Economic Cooperation (APEC) Climate Center (APCC) hosts the APEC Climate Symposium (APCS) every year. APCS focused on drought predction and management in 2013, climate extremes and hydrological disaster in 2014, and efficient use of climate information for disaster risk management in 2015. This book aims to compile some of the important results from the latest research in climate extreme prediction and services and its application studies with a focus on climate extremes such as typhoons, droughts, and floods based on the APCS presentations during 2013-2015\"-- Page 4 of cover.
Book
Forecasting stock prices with long-short term memory neural network based on attention mechanism
The stock market is known for its extreme complexity and volatility, and people are always looking for an accurate and effective way to guide stock trading. Long short-term memory (LSTM) neural networks are developed by recurrent neural networks (RNN) and have significant application value in many fields. In addition, LSTM avoids long-term dependence issues due to its unique storage unit structure, and it helps predict financial time series. Based on LSTM and an attention mechanism, a wavelet transform is used to denoise historical stock data, extract and train its features, and establish the prediction model of a stock price. We compared the results with the other three models, including the LSTM model, the LSTM model with wavelet denoising and the gated recurrent unit(GRU) neural network model on S&P 500, DJIA, HSI datasets. Results from experiments on the S&P 500 and DJIA datasets show that the coefficient of determination of the attention-based LSTM model is both higher than 0.94, and the mean square error of our model is both lower than 0.05.
Journal Article
تطوير إقتصاد دائري في الصين
هذا العمل الجماعي المشترك، كما يشير عنوانه : (التاريخ المديني الحضري للصين) هو كتاب حضاري بامتياز. كتاب يستعرض جوانب أساسية من حضارة الشعب الصيني القديمة-المتجددة الراسخة، الضاربة جذورها عميقا في تربة التاريخ البشري الشامل. يعد الكتاب سفر حضاري قيم وبحث متصل رصين حول التطور التاريخي العمراني في المدن الصينية وهو إذ يتناول بشكل أساسي، فن العمارة والبناء والتصميم وتخطيط المدن والشوارع والأحياء والأسواق والمقار الحكومية والحدائق والمعابد والساحات ومسالك الملاحة النهرية والري، فإنه لا يغفل في الوقت نفسه عن ما يتصل به هذا الموضوع، من عشرات المواضيع الحضارية والثقافية والمعيشية الأخرى، مثل : العبادات والاعتقادات والتقاليد والعادات والآداب والطقوس والحرف والفنون والنظم الاجتماعية والصراع السياسي والغزو الخارجي والتنظيم الحكومي والقبلي والاجتماعي والطبقي والعسكري والإداري والإنمائي والعمراني والإسكاني والتعليمي والتجاري والأدبي والفني والموسيقي والفولكلوري. إنه كتاب جميل يقدم العديد من اللوحات الرشيقة الرحبة المتقابلة المتلاحقة المتكاملة التي ترحل بنا بين القصور والأنهار والأسوار والأحياء والمعاهد والمعابد وهياكل عبادة الأجداد ومواقع التنقيب والساحات والحدائق والميادين ودواوين الشعر وسجلات التاريخ ولا يخلو كل ذلك من جولات من البحث المقارن في غير أمر من هذه الأمور ولن نطيل عليكم في الإضاءة على مواضيع هذا الكتاب لأكثر من ذلك، آملين لكم سلاسة القراءة ومتعة الاكتشاف.
Book
Antimicrobial Mechanisms and Clinical Application Prospects of Antimicrobial Peptides
Antimicrobial peptides are a type of small-molecule peptide that widely exist in nature and are components of the innate immunity of almost all living things. They play an important role in resisting foreign invading microorganisms. Antimicrobial peptides have a wide range of antibacterial activities against bacteria, fungi, viruses and other microorganisms. They are active against traditional antibiotic-resistant strains and do not easily induce the development of drug resistance. Therefore, they have become a hot spot of medical research and are expected to become a new substitute for fighting microbial infection and represent a new method for treating drug-resistant bacteria. This review briefly introduces the source and structural characteristics of antimicrobial peptides and describes those that have been used against common clinical microorganisms (bacteria, fungi, viruses, and especially coronaviruses), focusing on their antimicrobial mechanism of action and clinical application prospects.
Journal Article
Understanding Future Change of Global Monsoons Projected by CMIP6 Models
Projecting future change of monsoon rainfall is essential for water resource management, food security, disaster mitigation, and infrastructure planning. Here we assess the future change and explore the causes of the changes using 15 models that participated in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The multimodel ensemble projects that, under the shared socioeconomic pathway (SSP) 2–4.5, the total land monsoon rainfall will likely increase in the Northern Hemisphere (NH) by about 2.8% per one degree Celsius of global warming (2.8% °C−1) in contrast to little change in the Southern Hemisphere (SH; −0.3% °C−1). In addition, in the future the Asian–northern African monsoon likely becomes wetter while the North American monsoon becomes drier. Since the humidity increase is nearly uniform in all summer monsoon regions, the dynamic processes must play a fundamental role in shaping the spatial patterns of the global monsoon changes. Greenhouse gas (GHG) radiative forcing induces a “NH-warmer-than-SH” pattern, which favors increasing the NH monsoon rainfall and prolonging the NH monsoon rainy season while reducing the SH monsoon rainfall and shortening the SH monsoon rainy season. The GHG forcing induces a “land-warmer-than-ocean” pattern, which enhances Asian monsoon low pressure and increases Asian and northern African monsoon rainfall, and an El Niño–like warming, which reduces North American monsoon rainfall. The uncertainties in the projected monsoon precipitation changes are significantly related to the models’ projected hemispheric and land–ocean thermal contrasts as well as to the eastern Pacific Ocean warming. The CMIP6 models’ common biases and the processes by which convective heating drives monsoon circulation are also discussed.
Journal Article
Football sports video tracking and detection technology based on YOLOv5 and DeepSORT
Enhancing the analysis of football sports video is of great practical significance and commercial value for tactical analysis, player performance evaluation, tournament broadcasting, and many other aspects. Considering that the current target detection and tracking is characterized by complex scene changes, target occlusion, and obvious external motion interference, the study proposes to improve the YOLOv5 and DeepSORT algorithms for improving the tracking and detection accuracy of sports video to enhance its application performance. First, the model is improved with lightweight network architecture and attention mechanism is introduced to improve feature extraction capability and target detection accuracy. After that, a traceless Kalman filter is introduced into the DeepSORT algorithm to improve the target matching performance and enhance the target tracking. The outcomes indicated that the average accuracy value of the improved YOLOv5 model for target detection was more than 90%, which effectively reduced the number of computational parameters. The detection performance under target overlap and uneven lighting and shadows exceeded 90%, and the difference between the algorithm and other algorithms was at least greater than 2%. When performing target tracking, the AUC values of the research algorithm in different scenarios have exceeded 85%, which is less affected by the overlap threshold and has a high tracking accuracy. It demonstrated the highest successful tracking rate and showed a more stable performance.Article highlightsHighlight 1. Enhanced football video analysis and detection performance for complex scenes and occlusion.Highlight 2. Enhanced tracking capability for complex scenes, facilitating real-time analysis and decision-making.Highlight 3. Balancing lightweight architectural design and real-time computation, broadening the application scenarios.
Journal Article
Neurofilament light chain in blood as a diagnostic and predictive biomarker for multiple sclerosis: A systematic review and meta-analysis
Neurofilament light chain (NfL) in cerebrospinal fluid (CSF) is a biomarker of multiple sclerosis (MS). However, CSF sampling is invasive and has limited the clinical application. With the development of highly sensitive single-molecule assay, the accurate quantification of the very low NfL levels in blood become feasible. As evidence being accumulated, we performed a meta-analysis to evaluate the diagnostic and predictive value of blood NfL in MS patients. We performed literature search on PubMed, EMBASE, Web of Science and Cochrane Library from inception to May 31, 2022. The blood NfL differences between MS vs. controls, MS vs. clinically isolated syndrome (CIS), progressive MS (PMS) vs. relapsing-remitting MS (RRMS), and MS in relapse vs. MS in remission were estimated by standard mean difference (SMD) and corresponding 95% confidence interval (CI). Pooled hazard ratio (HR) and 95%CI were calculated to predict time to reach Expanded Disability Status Scale (EDSS) score[greater than or equal to]4.0 and to relapse. A total of 28 studies comprising 6545 MS patients and 2477 controls were eligible for meta-analysis of diagnosis value, and 5 studies with 4444 patients were synthesized in analysis of predictive value. Blood NfL levels were significantly higher in MS patients vs. age-matched controls (SMD = 0.64, 95%CI 0.44-0.85, P<0.001), vs. non-matched controls (SMD = 0.76, 95%CI 0.56-0.96, P<0.001) and vs. CIS patients (SMD = 0.30, 95%CI 0.18-0.42, P<0.001), in PMS vs. RRMS (SMD = 0.56, 95%CI 0.27-0.85, P<0.001), and in relapsed patients vs. remitted patients (SMD = 0.54, 95%CI 0.16-0.92, P = 0.005). Patients with high blood NfL levels had shorter time to reach EDSS score[greater than or equal to]4.0 (HR = 2.36, 95%CI 1.32-4.21, P = 0.004) but similar time to relapse (HR = 1.32, 95%CI 0.90-1.93, P = 0.155) compared to those with low NfL levels. As far as we know, this is the first meta-analysis evaluating the diagnosis and predictive value of blood NfL in MS. The present study indicates blood NfL may be a useful biomarker in diagnosing MS, distinguishing MS subtypes and predicting disease worsening in the future.
Journal Article