Characteristics and Preliminary Causes of Tropical Cyclone Remote Precipitation over China

In this study,the characteristics and preliminary causes of tropical cyclone remote precipitation(TRP)over China during the period from 1979 to 2020 are investigated.Results indicated that approximately 72.42%of tropical cyclones(TCs)in the Western Pacific produce TRP over China.The peak months for TRP are July and August.The four key regions of TRP are the adjacent areas between the Sichuan and Shaanxi Provinces,the northern coast of the Bohai Sea,the coast of the Yellow Sea,and the southern coast area.The typical distance between the station with TRP and the TC center ranges from 1500 to 2500 km.Most of these stations are situated north to 60°west of north of the TC.The south–west water vapor transportation on the west side of the TC is crucial to TRP.TRP has a decreasing trend because of the decrease in the number of TCs that generate TRP.From the perspective of large-scale environmental conditions,a decrease in the integrated horizontal water vapor transport in China' Mainland,the weakening of upward motion at approximately 25°–35°N,which is inconducive to convection,and an increase in low-level vertical wind shear,which is unfavorable for the development of TC in areas with high frequencies of TRP-related TCs,are the factors that result in the decreasing trend of TRP.

Analysis of the causes of primary revision after unicompartmental knee arthroplasty: A case series

BACKGROUND Unicompartmental knee arthroplasty(UKA)has great advantages in the treatment of unicompartmental knee osteoarthritis,but its revision rate is higher than that of total knee arthroplasty.AIM To summarize and analyse the causes of revision after UKA.METHODS This is a retrospective case series study in which the reasons for the first revision after UKA are summarized.We analysed the clinical symptoms,medical histories,laboratory test results,imaging examination results and treatment processes of the patients who underwent revision and summarized the reasons for primary revision after UKA.RESULTS A total of 13 patients,including 3 males and 10 females,underwent revision surgery after UKA.The average age of the included patients was 67.62 years.The prosthesis was used for 3 d to 72 months.The main reasons for revision after UKA were improper suturing of the surgical opening(1 patient),osteophytes(2 patients),intra-articular loose bodies(2 patients),tibial prosthesis loosening(2 patients),rheumatoid arthritis(1 patient),gasket dislocation(3 patients),anterior cruciate ligament injury(1 patient),and medial collateral ligament injury with residual bone cement(1 patient).CONCLUSION The causes of primary revision after UKA were gasket dislocation,osteophytes,intra-articular loose bodies and tibial prosthesis loosening.Avoidance of these factors may greatly reduce the rate of revision after UKA,improve patient satisfaction and reduce medical burden.

Clinical characteristics of acute non-varicose upper gastrointestinal bleeding and the effect of endoscopic hemostasis

BACKGROUND Acute non-variceal upper gastrointestinal bleeding(ANVUGIB)constitutes a prevalent emergency within Gastroenterology,encompassing 80%-90%of all gastrointestinal hemorrhage incidents.This condition is distinguished by its abrupt onset,swift progression,and notably elevated mortality rate.AIM To gather clinical data from patients with ANVUGIB at our hospital in order to elucidate the clinical characteristics specific to our institution and analyze the therapeutic effectiveness of endoscopic hemostasis.METHODS We retrospectively retrieved the records of 532 patients diagnosed with ANVUGIB by endoscopy at our hospital between March 2021 and March 2023,utilizing our medical record system.Data pertaining to general patient information,etiological factors,disease outcomes,and other relevant variables were meticulously collected and analyzed.RESULTS Among the 532 patients diagnosed with ANVUGIB,the male-to-female ratio was 2.91:1,with a higher prevalence among males.Notably,43.6%of patients presented with black stool as their primary complaint,while 27.4%had hematemesis as their initial symptom.Upon admission,17%of patients exhibited both hematemesis and black stool,while most ANVUGIB patients primarily complained of overt gastrointestinal bleeding.Urgent routine blood examinations at admission revealed that 75.8%of patients had anemia,with 63.4%experiencing moderate to severe anemia,and 1.5%having extremely severe anemia(hemoglobin<30 g/L).With regard to etiology,53.2%of patients experienced bleeding without a definitive trigger,24.2%had a history of using gastric mucosa-irritating medications,24.2%developed bleeding after alcohol consumption,2.8%attributed it to improper diet,1.7%to emotional excitement,and 2.3%to fatigue preceding the bleeding episode.Drug-induced ANVUGIB was more prevalent in the elderly than middle-aged and young individuals,while bleeding due to alcohol consumption showed the opposite trend.Additionally,diet-related bleeding was more common among the young age group compared to the middle-aged group.Gastrointestinal endoscopy identified peptic ulcers as the most frequent cause of ANVUGIB(73.3%),followed by gastrointestinal malignancies(10.9%),acute gastric mucous lesions(9.8%),and androgenic upper gastrointestinal bleeding(1.5%)among inpatients with ANVUGIB.Of the 532 patients with gastrointestinal bleeding,68 underwent endoscopic hemostasis,resulting in an endoscopic treatment rate of 12.8%,with a high immediate hemostasis success rate of 94.1%.

Optimised CNN Architectures for Handwritten Arabic Character Recognition

Handwritten character recognition is considered challenging compared with machine-printed characters due to the different human writing styles.Arabic is morphologically rich,and its characters have a high similarity.The Arabic language includes 28 characters.Each character has up to four shapes according to its location in the word(at the beginning,middle,end,and isolated).This paper proposed 12 CNN architectures for recognizing handwritten Arabic characters.The proposed architectures were derived from the popular CNN architectures,such as VGG,ResNet,and Inception,to make them applicable to recognizing character-size images.The experimental results on three well-known datasets showed that the proposed architectures significantly enhanced the recognition rate compared to the baseline models.The experiments showed that data augmentation improved the models’accuracies on all tested datasets.The proposed model outperformed most of the existing approaches.The best achieved results were 93.05%,98.30%,and 96.88%on the HIJJA,AHCD,and AIA9K datasets.

Effect of Co on Solidification Characteristics and Microstructural Transformation of Non-equilibrium Solidified Cu-Ni Alloys

Non-equilibrium solidification structures of Cu55Ni45 and Cu55Ni43Co2 alloys were prepared by the molten glass purification cycle superheating method.The variation of the recalescence phenomenon with the degree of undercooling in the rapid solidification process was investigated using an infrared thermometer.The addition of the Co element affected the evolution of the recalescence phenomenon in Cu-Ni alloys.The images of the solid-liquid interface migration during the rapid solidification of supercooled melts were captured by using a high-speed camera.The solidification rate of Cu-Ni alloys,with the addition of Co elements,was explored.Finally,the grain refinement structure with low supercooling was characterised using electron backscatter diffraction(EBSD).The effect of Co on the microstructural evolution during nonequilibrium solidification of Cu-Ni alloys under conditions of small supercooling is investigated by comparing the microstructures of Cu55Ni45 and Cu55Ni43Co2 alloys.The experimental results show that the addition of a small amount of Co weakens the recalescence behaviour of the Cu55Ni45 alloy and significantly reduces the thermal strain in the rapid solidification phase.In the rapid solidification phase,the thermal strain is greatly reduced,and there is a significant increase in the characteristic undercooling degree.Furthermore,the addition of Co and the reduction of Cu not only result in a lower solidification rate of the alloy,but also contribute to the homogenisation of the grain size.

Prevalence and Causes of Neonatal Mortality at Chu-Mel, Cotonou in 2023

Introduction: Neonatal mortality represents a global health problem that has been at the core of programs developed by the World Health Organization (WHO) for more than 30 years. In our country, it represents a real scourge and remains high despite the efforts made by the Ministry of Health. The goal of this study was to investigate the prevalence and causes of neonatal mortality at CHU-MEL of Cotonou in 2023. Material and Methods: This was a cross-sectional and descriptive study with retrospective data collection, carried out in the neonatology unit of the Mother and Child Teaching Hospital of Lagune (CHU-MEL) in Cotonou over a period of six months from January 1, 2023 to June 30, 2023. All neonates, premature or full-term, born alive and who died during hospitalization in the unit were included. Results: 211 cases of neonatal deaths were recorded among the 2884 neonates hospitalized in the unit during the study period, representing a hospital prevalence of 7.31%. Early neonatal mortality represented 81.5% of cases. The average age at admission was 4.6 days ± 5.3. The average weight of deceased neonates was 1609.08 ± 798.35 g. The most frequent reasons for hospitalization were represented by prematurity (60.66%) and respiratory distress (23.22%), respectively. Prematurity was the leading cause of neonatal mortality (41.7%), followed by neonatal infections (29.4%) and perinatal asphyxia (10.9%). Conclusion: The prevalence of neonatal mortality in the neonatology unit of CHU-MEL is high. Efforts to improve the quality of perinatal care departments must be intensified to reduce this prevalence.

Instance Segmentation of Characters Recognized in Palmyrene Aramaic Inscriptions

This study presents a single-class and multi-class instance segmentation approach applied to ancient Palmyrene inscriptions,employing two state-of-the-art deep learning algorithms,namely YOLOv8 and Roboflow 3.0.The goal is to contribute to the preservation and understanding of historical texts,showcasing the potential of modern deep learning methods in archaeological research.Our research culminates in several key findings and scientific contributions.We comprehensively compare the performance of YOLOv8 and Roboflow 3.0 in the context of Palmyrene character segmentation—this comparative analysis mainly focuses on the strengths and weaknesses of each algorithm in this context.We also created and annotated an extensive dataset of Palmyrene inscriptions,a crucial resource for further research in the field.The dataset serves for training and evaluating the segmentation models.We employ comparative evaluation metrics to quantitatively assess the segmentation results,ensuring the reliability and reproducibility of our findings and we present custom visualization tools for predicted segmentation masks.Our study advances the state of the art in semi-automatic reading of Palmyrene inscriptions and establishes a benchmark for future research.The availability of the Palmyrene dataset and the insights into algorithm performance contribute to the broader understanding of historical text analysis.

Distribution and Formation Causes of PM_(2.5) and O_(3) Double High Pollution Events in China during 2013–20

Fine particulate matter(PM_(2.5))and ozone(O_(3))double high pollution(DHP)events have occurred frequently over China in recent years,but their causes are not completely clear.In this study,the spatiotemporal distribution of DHP events in China during 2013–20 is analyzed.The synoptic types affecting DHP events are identified with the Lamb–Jenkinson circulation classification method.The meteorological and chemical causes of DHP events controlled by the main synoptic types are further investigated.Results show that DHP events(1655 in total for China during 2013–20)mainly occur over the North China Plain,Yangtze River Delta,Pearl River Delta,Sichuan Basin,and Central China.The occurrence frequency increases by 5.1%during 2013–15,and then decreases by 56.1%during 2015–20.The main circulation types of DHP events are“cyclone”and“anticyclone”,accounting for over 40%of all DHP events over five main polluted regions in China,followed by southerly or easterly flat airflow types,like“southeast”,“southwest”,and“east”.Compared with non-DHP events,DHP events are characterized by static or weak wind,high temperature(20.9℃ versus 23.1℃)and low humidity(70.0%versus 64.9%).The diurnal cycles of meteorological conditions cause PM_(2.5)(0300–1200 LST,Local Standard Time=UTC+8 hours)and O_(3)(1500–2100 LST)to exceed the national standards at different periods of the DHP day.Three pollutant conversion indices further indicate the rapid secondary conversions during DHP events,and thus the concentrations of NO_(2),SO_(2) and volatile organic compounds decrease by 13.1%,4.7%and 4.4%,respectively.The results of this study can be informative for future decisions on the management of DHP events.

A Method for Detecting and Recognizing Yi Character Based on Deep Learning

Aiming at the challenges associated with the absence of a labeled dataset for Yi characters and the complexity of Yi character detection and recognition,we present a deep learning-based approach for Yi character detection and recognition.In the detection stage,an improved Differentiable Binarization Network(DBNet)framework is introduced to detect Yi characters,in which the Omni-dimensional Dynamic Convolution(ODConv)is combined with the ResNet-18 feature extraction module to obtain multi-dimensional complementary features,thereby improving the accuracy of Yi character detection.Then,the feature pyramid network fusion module is used to further extract Yi character image features,improving target recognition at different scales.Further,the previously generated feature map is passed through a head network to produce two maps:a probability map and an adaptive threshold map of the same size as the original map.These maps are then subjected to a differentiable binarization process,resulting in an approximate binarization map.This map helps to identify the boundaries of the text boxes.Finally,the text detection box is generated after the post-processing stage.In the recognition stage,an improved lightweight MobileNetV3 framework is used to recognize the detect character regions,where the original Squeeze-and-Excitation(SE)block is replaced by the efficient Shuffle Attention(SA)that integrates spatial and channel attention,improving the accuracy of Yi characters recognition.Meanwhile,the use of depth separable convolution and reversible residual structure can reduce the number of parameters and computation of the model,so that the model can better understand the contextual information and improve the accuracy of text recognition.The experimental results illustrate that the proposed method achieves good results in detecting and recognizing Yi characters,with detection and recognition accuracy rates of 97.5%and 96.8%,respectively.And also,we have compared the detection and recognition algorithms proposed in this paper with other typical algorithms.In these comparisons,the proposed model achieves better detection and recognition results with a certain reliability.

The Impacts and Causes of Land Fragmentation on Farm Productivity: Case Review of East African Countries

This report provides an overall assessment of land fragmentation problems in East Africa. Many parts of East Africa have become highly fragmented, putting development systems and activities in these areas at risk of complete collapse. Land fragmentation occurs when land gets converted for agriculture, industrialization, or urbanization, invaded by non-local plants, or enclosed for individual use and by subdividing farmlands into subsequent smaller units called parcels with varying average farm sizes. Fragmentation results from inappropriate agricultural development processes and ineffective land use planning that fails to recognize how farmland is used, and the importance of its interconnected areas. Insecurity of tenure and resource rights are key factors in making this possible. Land fragmentation is one of the key reasons why the ability of most resources in East Africa becomes scarcer, and those remaining become “privatized” by more powerful community members—keen to maintain their access to them. Such individualistic attitudes are new and disadvantage the poorest even further by affecting the traditional customary safety nets and agricultural outputs. Neither the government nor customary governance systems effectively protect resource access for the poorest. This review summary report identifies the key causes, measures, and implications, government interventions, and the common remedies to land fragmentation problems in the East African Countries of Kenya, Uganda, Rwanda, and Tanzania including neighboring Ethiopia, and the Sudan. The findings indicated from 2005 to 2015, the population kept increasing for all the named countries in East Africa with Rwanda and Uganda having a substantial increase in population density. The study review further explores the trend in the performance of agriculture by average farm sizes within the intervals of five years by highlighting their strong linkages and found that the average farm size has declined drastically, especially for Kenya. This can only mean that small farms kept becoming smaller and smaller and that there were more small-scale farmers. The results further depicted that the major and commonly cultivated food crops among the East African countries include maize, sorghum, rice, cassava, sweet potatoes, bananas, Irish potatoes, beans, peas, etc., with maize yields (Mt/ha) in 2003 for Uganda being the highest (1.79 Mt/ha) and the lowest in Rwanda (0.77 Mt/ha) respectively. Therefore, from the review results, recommendations are being made as to how the negative impacts of land fragmentation on agricultural productivity can be reduced or mitigated. One way is by community sensitization and awareness about the importance of land consolidation and its proposition on farm productivity.

Fireworks Optimization with Deep Learning-Based Arabic Handwritten Characters RecognitionModel

Handwritten character recognition becomes one of the challenging research matters.More studies were presented for recognizing letters of various languages.The availability of Arabic handwritten characters databases was confined.Almost a quarter of a billion people worldwide write and speak Arabic.More historical books and files indicate a vital data set for many Arab nationswritten in Arabic.Recently,Arabic handwritten character recognition(AHCR)has grabbed the attention and has become a difficult topic for pattern recognition and computer vision(CV).Therefore,this study develops fireworks optimizationwith the deep learning-based AHCR(FWODL-AHCR)technique.Themajor intention of the FWODL-AHCR technique is to recognize the distinct handwritten characters in the Arabic language.It initially pre-processes the handwritten images to improve their quality of them.Then,the RetinaNet-based deep convolutional neural network is applied as a feature extractor to produce feature vectors.Next,the deep echo state network(DESN)model is utilized to classify handwritten characters.Finally,the FWO algorithm is exploited as a hyperparameter tuning strategy to boost recognition performance.Various simulations in series were performed to exhibit the enhanced performance of the FWODL-AHCR technique.The comparison study portrayed the supremacy of the FWODL-AHCR technique over other approaches,with 99.91%and 98.94%on Hijja and AHCD datasets,respectively.

Audio2AB:Audio-driven collaborative generation of virtual character animation

Background Considerable research has been conducted in the areas of audio-driven virtual character gestures and facial animation with some degree of success.However,few methods exist for generating full-body animations,and the portability of virtual character gestures and facial animations has not received sufficient attention.Methods Therefore,we propose a deep-learning-based audio-to-animation-and-blendshape(Audio2AB)network that generates gesture animations and ARK it's 52 facial expression parameter blendshape weights based on audio,audio-corresponding text,emotion labels,and semantic relevance labels to generate parametric data for full-body animations.This parameterization method can be used to drive full-body animations of virtual characters and improve their portability.In the experiment,we first downsampled the gesture and facial data to achieve the same temporal resolution for the input,output,and facial data.The Audio2AB network then encoded the audio,audio-corresponding text,emotion labels,and semantic relevance labels,and then fused the text,emotion labels,and semantic relevance labels into the audio to obtain better audio features.Finally,we established links between the body,gestures,and facial decoders and generated the corresponding animation sequences through our proposed GAN-GF loss function.Results By using audio,audio-corresponding text,and emotional and semantic relevance labels as input,the trained Audio2AB network could generate gesture animation data containing blendshape weights.Therefore,different 3D virtual character animations could be created through parameterization.Conclusions The experimental results showed that the proposed method could generate significant gestures and facial animations.

A Novel 6G Scalable Blockchain Clustering-Based Computer Vision Character Detection for Mobile Images

6G is envisioned as the next generation of wireless communication technology,promising unprecedented data speeds,ultra-low Latency,and ubiquitous Connectivity.In tandem with these advancements,blockchain technology is leveraged to enhance computer vision applications’security,trustworthiness,and transparency.With the widespread use of mobile devices equipped with cameras,the ability to capture and recognize Chinese characters in natural scenes has become increasingly important.Blockchain can facilitate privacy-preserving mechanisms in applications where privacy is paramount,such as facial recognition or personal healthcare monitoring.Users can control their visual data and grant or revoke access as needed.Recognizing Chinese characters from images can provide convenience in various aspects of people’s lives.However,traditional Chinese character text recognition methods often need higher accuracy,leading to recognition failures or incorrect character identification.In contrast,computer vision technologies have significantly improved image recognition accuracy.This paper proposed a Secure end-to-end recognition system(SE2ERS)for Chinese characters in natural scenes based on convolutional neural networks(CNN)using 6G technology.The proposed SE2ERS model uses the Weighted Hyperbolic Curve Cryptograph(WHCC)of the secure data transmission in the 6G network with the blockchain model.The data transmission within the computer vision system,with a 6G gradient directional histogram(GDH),is employed for character estimation.With the deployment of WHCC and GDH in the constructed SE2ERS model,secure communication is achieved for the data transmission with the 6G network.The proposed SE2ERS compares the performance of traditional Chinese text recognition methods and data transmission environment with 6G communication.Experimental results demonstrate that SE2ERS achieves an average recognition accuracy of 88%for simple Chinese characters,compared to 81.2%with traditional methods.For complex Chinese characters,the average recognition accuracy improves to 84.4%with our system,compared to 72.8%with traditional methods.Additionally,deploying the WHCC model improves data security with the increased data encryption rate complexity of∼12&higher than the traditional techniques.

Frontier Progress of Landscape Character Assessment in China

The role of Landscape Character Assessment(LCA)at the level of territorial landscape governance spans both natural and social sciences.By analyzing the development history,research distribution,methods and applications of cutting-edge cases of LCA in China,the following conclusions are drawn:①the LCA research in China originated earlier than that in Europe,but has not yet been systematically applied to the implementation of urban and rural planning at all levels;②the fundamental theory of LCA in China has been well constructed,with three main research directions:technologyled,assessment-led,and assessment combined with other theories;③the development of LCA in rural areas is more mature than in urban areas,but the progress of research is uneven across regions;④the current research presents significant“bottom-up”academic characteristics,and there is an urgent need for government decision-making authorities and academia to jointly promote a“top-down”standardized governance mechanism to comprehensively promote the modernization of territorial landscape governance.

Eternal Climate Change Patterns and the Causes and Countermeasures of Global Climate Change

It is an objective fact that the weather is unpredictable.Even the famous meteorologist,Academician Chu Ko Chen,has only a partial understanding of the changing laws of wind and rain.Even though ancient people summarized the 24 solar terms by observing the annual activities of the sun for a long time,because they ignored the impact of the activities of the moon on the Earth’s climate change on a small scale,the 24 solar terms they summarized often could not accurately predict the change of the Earth’s climate.Therefore,the author studied the influence of lunar activities on the Earth’s climate change,finds out the law of the influence of lunar activities on the Earth’s climate change on a small scale,and summarizes the eternal climate change pattern determined by the activities of the sun and the moon.In addition,the author also reveals the causes and countermeasures of global warming and the frequent occurrence of extreme weather as well as environmental change.

Progress in the evaluation tool of Character Strengths and its application in nursing staff

Character Strengths is a group of positive personality traits reflected through cognition,behavior,and emotion,which play a positive role in improving happiness,alleviating negative emotions,and maintaining physical and mental health.This article reviews the concept,content,methods,evaluation tools,and application progress of Character Strengths in nurses,so as to provide a reference for clinical managers and improve the quality of life,mental health,and professional satisfaction of n urses.

Chip Surface Character Recognition Based on OpenCV

Chip surface character recognition is an important part of quality inspection in the field of microelectronics manufacturing.By recognizing the character information on the chip,automated production,quality control,and data collection and analysis can be achieved.This article studies a chip surface character recognition method based on the OpenCV vision library.Firstly,the obtained chip images are preprocessed.Secondly,the template matching method is used to locate the chip position.In addition,the surface characters on the chip are individually segmented,and each character image is extracted separately.Finally,a Support Vector Machine(SVM)is used to classify and recognize characters.The results show that this method can accurately recognize the surface characters of chips and meet the requirements of chip quality inspection.

Characteristics and Preliminary Causes of Tropical Cyclone Extreme Rainfall Events over Hainan Island

The characteristics of tropical cyclone（TC） extreme rainfall events over Hainan Island from 1969 to 2014 are analyzed from the viewpoint of the TC maximum daily rainfall（TMDR） using daily station precipitation data from the Meteorological Information Center of the China Meteorological Administration, TC best-track data from the Shanghai Typhoon Institute,and NCEP/NCAR reanalysis data. The frequencies of the TMDR reaching 50, 100 and 250 mm show a decreasing trend[-0.7（10 yr）^（-1）], a weak decreasing trend [-0.2（10 yr）^（-1）] and a weak increasing trend [0.1（10 yr）^（-1）], respectively. For seasonal variations, the TMDR of all intensity grades mainly occurs from July to October, with the frequencies of TMDR 50 mm and 100 mm peaking in September and the frequency of TMDR 250 mm [TC extreme rainstorm（TCER） events]peaking in August and September. The western region（Changjiang） of the Island is always the rainfall center, independent of the intensity or frequencies of different intensity grades. The causes of TCERs are also explored and the results show that topography plays a key role in the characteristics of the rainfall events. TCERs are easily induced on the windward slopes of Wuzhi Mountain, with the coordination of TC tracks and TC wind structure. A slower speed of movement, a stronger TC intensity and a farther westward track are all conducive to extreme rainfall events. A weaker northwestern Pacific subtropical high is likely to make the 500-h Pa steering flow weaker and results in slower TC movement, whereas a stronger South China Sea summer monsoon can carry a higher moisture flux. These two environmental factors are both favorable for TCERs.

On the Causes of Scarlet's Character in Gone with the Wind

Gone With the Wind is a historical fiction novel with vivid descriptions of the Old South,the Civil War and the Recon struction.This is an incredibly well written book about the death of old civilization and the struggles to survive in the new era.It is ultimately the story of one person,Scarlet O'Hara.Scarlet is keeping on changing during the three periods of the novel—her girlhood,the period of the Civil War and the Reconstruction.Through the analysis of the formation and changing of Scarlet’s characters,this paper will make a further elaboration on the Darwinian concept of"survival of the fittest"and feminism.

Characteristics,Causes and Mitigation of Catastrophic Debris Flow Hazard on 21 July 2011 at the Longda Watershed of Songpan County,China

Debris flow is a common natural hazard in the mountain areas of Western China due to favorable natural conditions, and also exacerbated by mountainous exploitation activities. This paper concentrated on the characteristics, causes and mitigation of a catastrophic mine debris flow hazard at Longda Watershed in Songpan County, Sichuan Province, on 21 July 2011. This debris flow deposited in the front of the No.1 dam, silted the drainage channel for flood and then rushed into tailing sediment reservoir in the main channel and made the No.2 dam breached. The outburst debris flow blocked Fu River, formed dammed lake and generated outburst flood, which delivered heavy metals into the lower reaches of Fu River, polluted the drink water source of the population of over 1 million. The debris flow was characterized with a density of 1.87～2.15 t/m3 and a clay content of less than 1.63%. The peak velocity and flux at Longda Gully was over l0.0～10.9 m/s and 429.o～446.o m3/s, respectively, and the flux was about 700 m3/s in main channel, equaling to the flux of the probability of 1%. About 33o,ooorn3 solid materials was transported by debris flow and deposited in the drainage tunnel （120,000～130,000 m3）, the front of No.1 dam （100,000 m3） and the mouth of the watershed （l00,000～110,000 m3）, respectively. When the peak flux and magnitude of debris flow was more than 462 m3/s and 7,423 m3, respectively, it would block Fu River and produce a hazard chain which was composed of debris flow, dammed lake and outburst flood. Furthermore, the 21 July large-scale debris flow was triggered by rainstorm with an intensity of 21.2 mm/0.5 h and the solid materials of debris flow were provided by landslides, slope deposits, mining wastes and tailing sediments. The property losses were mainly originated from the silting of the drainage tunnel for flash flood but not for debris flow and the irrational location of tailing sediment reservoir. Therefore, the mitigation measures for mine debris flows were presented： （1） The disastrous debris flow watershed should be identified in planning period and prohibited from being taken as the site of mining factories; （2） The mining facilities are constructed at the safe areas or watersheds; （3） Scoria plots, concentrator factory and tailing sediment reservoir are constructed in safe areas where the protection measures be easily made against debris flows; （4） The appropriate system and plan of debris flow mitigation including monitoring, remote monitoring and early-warning and emergency plan is established; （5） The stability of waste dump and tailing sediment reservoir are monitored continuously to prevent mining debris flows.