Scientific Advances and Weather Services of the China Meteorological Administration’s National Forecasting Systems during the Beijing 2022 Winter Olympics

Since the Beijing 2022 Winter Olympics was the first Winter Olympics in history held in continental winter monsoon climate conditions across complex terrain areas,there is a deficiency of relevant research,operational techniques,and experience.This made providing meteorological services for this event particularly challenging.The China Meteorological Administration(CMA)Earth System Modeling and Prediction Centre,achieved breakthroughs in research on short-and medium-term deterministic and ensemble numerical predictions.Several key technologies crucial for precise winter weather services during the Winter Olympics were developed.A comprehensive framework,known as the Operational System for High-Precision Weather Forecasting for the Winter Olympics,was established.Some of these advancements represent the highest level of capabilities currently available in China.The meteorological service provided to the Beijing 2022 Games also exceeded previous Winter Olympic Games in both variety and quality.This included achievements such as the“100-meter level,minute level”downscaled spatiotemporal resolution and forecasts spanning 1 to 15 days.Around 30 new technologies and over 60 kinds of products that align with the requirements of the Winter Olympics Organizing Committee were developed,and many of these techniques have since been integrated into the CMA’s operational national forecasting systems.These accomplishments were facilitated by a dedicated weather forecasting and research initiative,in conjunction with the preexisting real-time operational forecasting systems of the CMA.This program represents one of the five subprograms of the WMO’s high-impact weather forecasting demonstration project(SMART2022),and continues to play an important role in their Regional Association(RA)II Research Development Project(Hangzhou RDP).Therefore,the research accomplishments and meteorological service experiences from this program will be carried forward into forthcoming highimpact weather forecasting activities.This article provides an overview and assessment of this program and the operational national forecasting systems.

A Novel Method for Cross-Subject Human Activity Recognition with Wearable Sensors

Human Activity Recognition (HAR) is an important way for lower limb exoskeleton robots to implement human-computer collaboration with users. Most of the existing methods in this field focus on a simple scenario recognizing activities for specific users, which does not consider the individual differences among users and cannot adapt to new users. In order to improve the generalization ability of HAR model, this paper proposes a novel method that combines the theories in transfer learning and active learning to mitigate the cross-subject issue, so that it can enable lower limb exoskeleton robots being used in more complex scenarios. First, a neural network based on convolutional neural networks (CNN) is designed, which can extract temporal and spatial features from sensor signals collected from different parts of human body. It can recognize human activities with high accuracy after trained by labeled data. Second, in order to improve the cross-subject adaptation ability of the pre-trained model, we design a cross-subject HAR algorithm based on sparse interrogation and label propagation. Through leave-one-subject-out validation on two widely-used public datasets with existing methods, our method achieves average accuracies of 91.77% on DSAD and 80.97% on PAMAP2, respectively. The experimental results demonstrate the potential of implementing cross-subject HAR for lower limb exoskeleton robots.

Research and Analysis of Grammatical Error Correction Technology for Chinese Documents

With the widespread use of Chinese globally, the number of Chinese learners has been increasing, leading to various grammatical errors among beginners. Additionally, as domestic efforts to develop industrial information grow, electronic documents have also proliferated. When dealing with numerous electronic documents and texts written by Chinese beginners, manually written texts often contain hidden grammatical errors, posing a significant challenge to traditional manual proofreading. Correcting these grammatical errors is crucial to ensure fluency and readability. However, certain special types of text grammar or logical errors can have a huge impact, and manually proofreading a large number of texts individually is clearly impractical. Consequently, research on text error correction techniques has garnered significant attention in recent years. The advent and advancement of deep learning have paved the way for sequence-to-sequence learning methods to be extensively applied to the task of text error correction. This paper presents a comprehensive analysis of Chinese text grammar error correction technology, elaborates on its current research status, discusses existing problems, proposes preliminary solutions, and conducts experiments using judicial documents as an example. The aim is to provide a feasible research approach for Chinese text error correction technology.

CPG Human Motion Phase Recognition Algorithm for a Hip Exoskeleton with VSA Actuator

Due to the dynamic stiffness characteristics of human joints, it is easy to cause impact and disturbance on normal movements during exoskeleton assistance. This not only brings strict requirements for exoskeleton control design, but also makes it difficult to improve assistive level. The Variable Stiffness Actuator (VSA), as a physical variable stiffness mechanism, has the characteristics of dynamic stiffness adjustment and high stiffness control bandwidth, which is in line with the stiffness matching experiment. However, there are still few works exploring the assistive human stiffness matching experiment based on VSA. Therefore, this paper designs a hip exoskeleton based on VSA actuator and studies CPG human motion phase recognition algorithm. Firstly, this paper puts forward the requirements of variable stiffness experimental design and the output torque and variable stiffness dynamic response standards based on human lower limb motion parameters. Plate springs are used as elastic elements to establish the mechanical principle of variable stiffness, and a small variable stiffness actuator is designed based on the plate spring. Then the corresponding theoretical dynamic model is established and analyzed. Starting from the CPG phase recognition algorithm, this paper uses perturbation theory to expand the first-order CPG unit, obtains the phase convergence equation and verifies the phase convergence when using hip joint angle as the input signal with the same frequency, and then expands the second-order CPG unit under the premise of circular limit cycle and analyzes the frequency convergence criterion. Afterwards, this paper extracts the plate spring modal from Abaqus and generates the neutral file of the flexible body model to import into Adams, and conducts torque-stiffness one-way loading and reciprocating loading experiments on the variable stiffness mechanism. After that, Simulink is used to verify the validity of the criterion. Finally, based on the above criterions, the signal mean value is removed using feedback structure to complete the phase recognition algorithm for the human hip joint angle signal, and the convergence is verified using actual human walking data on flat ground.

Adaptive Robust Control with Leakage-Type Control Law for Trajectory Tracking of Exoskeleton Robots

This paper investigates the trajectory following problem of exoskeleton robots with numerous constraints. However, as a typical nonlinear system with variability and parameter uncertainty, it is difficult to accurately achieve the trajectory tracking control for exoskeletons. In this paper, we present a robust control of trajectory tracking control based on servo constraints. Firstly, we consider the uncertainties (e.g., modelling errors, initial condition deviations, structural vibrations, and other unknown external disturbances) in the exoskeleton system, which are time-varying and bounded. Secondly, we establish the dynamic model and formulate a close-loop connection between the dynamic model and the real world. Then, the trajectory tracking issue is regarded as a servo constraint problem, and an adaptive robust control with leakage-type adaptive law is proposed with the guaranteed Lyapunov stability. Finally, we conduct numerical simulations to verify the performance of the proposed controller.

Effects of pyrite on the spontaneous combustion of coal

Abstract Pyrite has a significant effect on the spontaneous combustion of coal. The presence of pyrite can change the propensity of coal towards spontaneous combustion. The influences of various pyrite contents on the parameters of spontaneous combustion, such as index gases, temperature and released heat etc., were investigated in this study, Coal samples with different pyrite contents （0 %, 3 %, 5 %, 7 % and 9 %） were made by mixing coal and pyrite. The oxidation experiments under temperature-programmed condition were carried out to test the release rate of gaseous oxidation products at different temperatures. Differential scanning calorimeter （DSC） was employed to measure the intensity of heat release during coal oxidation for various pyrite contents. The results indicate that pyrite can nonlinearly accelerate the process of spontaneous combustion. The coal sample with a pyrite content of 5 % has the largest CO release rate and oxygen adsorption as well. However, the coal sample with a pyrite content of ？ % has the largest rate of heat flow according to the results from the DSC tests. Pyrite contents of 5 %-7 % in coal has the most significant effects on spontaneous combustion within the range of this study. The conclusions are conducive to the evaluation and control for the spontaneous combustion of coal.

Spatial distribution pattern of Picea schrenkiana population in the Middle Tianshan Mountains and the relationship with topographic attributes

The spatial distribution of plant populations is an important feature of population structure and it de- termines the population＇s ecological preferences, biological characteristics and relationships with environmental factors. The point pattern analysis method was adopted to study the distribution pattern of Picea schrenkiana indi- viduals of different size classes and the correlations between two size classes as well as the impact of topog- raphical attributes on the population distribution. With increasing diameter at breast height, the plant density of the P. schrenkiana population showed a declining trend. Old trees showed a random distribution at a small spatial scale （0-12 m）, whereas saplings, small trees and big trees all had an aggregated distribution at all scales. With the increase of tree age, the scales at which maximal aggregation occurred gradually increased and the aggregation strength decreased. At a small scale （0-16 m）, all size classes showed a negative correlation and the larger the difference between tree size, the more significant the negative correlation. The number of medium, big and old trees had a significantly positive correlation with elevations, whereas the number of saplings and small trees was not significantly correlated with elevations. The numbers of saplings, small and medium trees showed a significant positive correlation with slope gradient, whereas the number of big trees was not significantly correlated, and the number of old trees was negatively correlated with gradient. With the exception of old trees, saplings, small, me- dium and big trees showed negative correlations with convexity index. The study provides a theoretical basis for the conservation, rehabilitation and sustainable management of forest ecosystems in the Tianshan Mountains.

Quantitative Precipitation Forecast Experiment Based on Basic NWP Variables Using Deep Learning

The quantitative precipitation forecast(QPF)performance by numerical weather prediction(NWP)methods depends fundamentally on the adopted physical parameterization schemes(PS).However,due to the complexity of the physical mechanisms of precipitation processes,the uncertainties of PSs result in a lower QPF performance than their prediction of the basic meteorological variables such as air temperature,wind,geopotential height,and humidity.This study proposes a deep learning model named QPFNet,which uses basic meteorological variables in the ERA5 dataset by fitting a non-linear mapping relationship between the basic variables and precipitation.Basic variables forecasted by the highest-resolution model(HRES)of the European Centre for Medium-Range Weather Forecasts(ECMWF)were fed into QPFNet to forecast precipitation.Evaluation results show that QPFNet achieved better QPF performance than ECMWF HRES itself.The threat score for 3-h accumulated precipitation with depths of 0.1,3,10,and 20 mm increased by 19.7%,15.2%,43.2%,and 87.1%,respectively,indicating the proposed performance QPFNet improved with increasing levels of precipitation.The sensitivities of these meteorological variables for QPF in different pressure layers were analyzed based on the output of the QPFNet,and its performance limitations are also discussed.Using DL to extract features from basic meteorological variables can provide an important reference for QPF,and avoid some uncertainties of PSs.

Degradation Dynamics of Triadimefon and Difenoconazole Residues in Strawberry and Soil

A field experiment was employed to study the degradation of triadimefon and difenoconazole residues in strawberry and soil. The results showed that the degradation of both the two kinds of pesticides was in accordance with the first order kinetic equation. The half-lives of difenoconazole in strawberry fruit, strawberry stem leaf and soil were 4.09, 8.21 and 13.38 d, respectively; and the half-lives of triadimefon in strawberry fruit, strawberry stem and leaf and soil were 3.38, 5.31 and 15.64 d, respectively. The maximum residue limit （MRL） of difenoconazole in strawberry was recommended as 0.5 mg/kg, and 10% difenoconazole WG and 20% triadimefon EC should be applied four times with a safety interval of 7 d according to the amounts of 100 and 60 g a. i./hm2,respectively.

Application of the fractal theory for evaluating effects of coal comminution by waterjet

Comminution of coal to ultrafine sizes by high-pressure waterjet provides a novel method for preparation of coal-water fuels for next generation,near-zero emission electric power generation.The particle size distribution(PSD)of ground coal is a key parameter in the preparation of slurries as it determines the settling behavior of the particles and viscosity of the coal-water mixture.There are several methods available for representation and evaluation of particle size analysis data.However,fractal theory provides a means by which the entire PSD of comminuted materials can be quantified by using of a specific and exact value.In this paper,a volume-based fractal model was deduced to characterize the PSD of the coal which is ground in a specially designed comminution cell.During the size reduction process,the inlet pressures up to 276 MPa were used.

Acid Value Determination and Pre-Esterification of Crude Euphorbia lathyris L. Oil

There were various problems in the determination of oil acid value of the national standard method, and this paper developed a low cost, simple and effective way to determine the acid value of oil and grease. Furthermore, the esterification of high acid Euphorbia lathyris L. oil (ELO) with methanol could be efficiently catalyzed by hydrochloric acid to produce biodiesel, and the influencing factors such as the amount of catalyst, reaction time, reaction temperature and molar ratio of oil to methanol were also studied. Under the optimized conditions with the oil to methanol molar ratio of 1:30 and a reaction temperature of 70℃, 95.8% oil conversion was obtained within 40 min in the presence of only 2.0 wt% of catalyst. Therefore, the low-cost non-edible Euphorbia lathyris L. oil as a raw material had good potential for the synthesis of biodiesel in industry.

后腹腔镜下输尿管中上段切开取石50例报告

目的探讨后腹腔镜下输尿管中上段切开取石的操作要点和经验。方法 2015年5月~2016年5月对术前经B超、腹部平片、静脉泌尿系造影或CT确诊为输尿管中上段结石患者50例,采用后腹腔镜行输尿管切开取石,患者术前均有体外冲击波碎石或输尿管镜碎石治疗失败史,结石直径0.8~2.5 cm。结果 50例均获成功,手术时间25~73 m in,平均48min;术中出血量5~40 ml,平均20ml;平均6个月后随访,未发现结石残余、结石复发、输尿管狭窄及肾积液等并发症。结论后腹腔镜输尿管切开取石治疗输尿管中上段结石是安全有效的手术方式。

Mushroom Poisoning Outbreaks—China,2023

What is already known about this topic?Mushroom poisoning poses a significant food safety concern in China,with a total of 196 species identified in poisoning incidents by the end of 2022.What is added by this report?In 2023,the China CDC conducted an investigation into 505 cases of mushroom poisoning spanning 24 provincial-level administrative divisions.This investigation resulted in 1,303 patients and 16 deaths,yielding a case fatality rate of 1.23%.A total of 97 mushrooms were identified as the cause of 6 distinct clinical disease types,with 12 species newly documented as poisonous mushrooms in China.What are the implications for public health practice?Close collaboration among CDC staff,physicians,and mycologists remains crucial for the control and prevention of mushroom poisoning in the future.

Food-Borne Poisoning Accident from Amanitin Toxin in Wild Mushrooms—Xingtai City,Hebei Province,China,2023

What is already known about this topic?Fatal poisonings caused by wild mushrooms containing amanita toxins pose a significant threat in the southern regions of China.These toxins primarily induce gastrointestinal symptoms initially,which are then followed by potentially life-threatening acute liver damage.What is added by this report?This report contributes to the existing knowledge on these cases of poisoning by documenting the second occurrences in Hebei Province and the first occurrences in Xingtai City.Five individuals reported consuming wild mushrooms from the same origin,and laboratory tests confirmed the presence ofα-amanitin in their blood samples.What are the implications for public health practice?This underscores the risk associated with the collection and consumption of amanita toxin-containing mushrooms in Hebei.It is important to note that the identification of toxic and non-toxic mushrooms should not solely rely on personal experience or appearance.

Mushroom Poisoning Outbreaks -China, 2022

Mushroom poisoning has become a serious food safety issue in China.With the support of the government,over the past decade,China has gradually established a mushroom poisoning prevention and treatment system involving experts in disease prevention and control,clinical diagnosis and treatment,fungal classification,and basic medicine(1–3).

精神分裂症患者骤停氯氮平治疗后发生严重窦性心动过缓1例

本文报道1例精神分裂症患者骤停氯氮平治疗后发生严重窦性心动过缓(39次/min)的病例, 在服用茶碱缓释片联合心宝丸后, 心率恢复正常。

回转窑热解废塑料过程中固体颗粒的运动与传热模拟

废塑料在回转窑反应器中经热解工艺可以转化成热解气、热解油和热解炭.回转窑中热载体的加载量对颗粒的运动和传热有着非常重要的影响,进而可以影响热解气、热解油和热解炭的三相产物分布.本研究采用石英砂作为热解废塑料的热载体,热载体的加载量从5%增加到15%.随着热载体的增加,热解油和热解炭产量增加,而热解气的产量减少.通过离散元方法对颗粒运动和换热过程分析发现,加载更多的热载体提高了回转窑内颗粒的平动速度和转动速度,增强了颗粒间的相互碰撞,从而加快了石英砂热载体向废塑料颗粒的传热效率.热载体的增加有助于挥发分的释放,并缩短了挥发分的停留时间,这导致了产油量的增加和产气量的减少.另外,增加热载体使用量可以使床层保持更高的温度,强化挥发分在床层内的碳化反应,增加焦炭产量.

Mushroom Poisoning Outbreaks--China,2019

What is already known about this topic?Mushroom poisoning is becoming one of the most serious food safety issues in China,which is responsible for nearly a half of all oral poisoning deaths.What is added by this report?In China,many mushrooms were previously“recorded”as poisonous.In this study,about 70 species obtained from mushroom poisoning incidents including several new records were confirmed accurately by morphological and molecular evidence in 2019,and spatial and temporal distribution characters of 13 lethal mushrooms were summarized systematically.What are the implications for public health practice?Precise and timely species identification is of pivotal importance in mushroom incidents.More efforts and cooperation are continued to be needed urgently for the governments,CDC staff,doctors and mycologists in future.

AMiner:Search and Mining of Academic Social Networks

AMiner is a novel online academic search and mining system,and it aims to provide a systematic modeling approach to help researchers and scientists gain a deeper understanding of the large and heterogeneous networks formed by authors,papers,conferences,journals and organizations.The system is subsequently able to extract researchers’profiles automatically from the Web and integrates them with published papers by a way of a process that first performs name disambiguation.Then a generative probabilistic model is devised to simultaneously model the different entities while providing a topic-level expertise search.In addition,AMiner offers a set of researcher-centered functions,including social influence analysis,relationship mining,collaboration recommendation,similarity analysis and community evolution.The system has been in operation since 2006 and has been accessed from more than 8 million independent IP addresses residing in more than 200 countries and regions.

Effect of dissolved organic matter on mercury release from water body

Dissolved organic matter（DOM） plays an important role in the process of mercury release from water body.In this study,the influence of DOM from different sources（DOMR,DOMS and DOMH,extracted from rice straw,compost and humic soil respectively） on mercury reduction was investigated.The molecular weight distribution and chemical composition of DOM from each source were determined using ultrafiltration membrane technique and elemental analysis respectively.The result showed that mercury release from DOM-added samples was much lower than the control;the lowest mercury release flux was observed in the treatment of DOMH,25.02% of the control,followed by DOMS and DOMR,62.46% and 64.95% of the control,respectively.The higher saturation degree and lower molecular weight of DOMH was responsible for the highest inhibition degree on the mercury release.The link between DOMH,concentration and mercury flux was also estimated and the result showed that mercury flux was increased with DOMH at lower concentration,while decreased with DOMH at higher concentration.Different mechanism dominated the influence of DOM on mercury release with variation of DOM concentration.