Storming Fortifications

Feel for boulders while crossing the river. ---Deng Xiaoping After a 20-year track record of extraordinary successes, however, China’sleaders now confront the toughest issues since reforms began in 1978. The domes-tic economic growth rate is declining, and the surrounding region is confronting

地面自动气象站数据流式处理设计与实现

针对观测密度和频次日益增加的海量地面自动气象站数据,在气象大数据云平台(天擎)中设计了基于Storm的实时流式处理,利用大规模并行处理的优势提高地面自动气象站数据的处理时效。在流式处理中,设计处理拓扑直接解码标准格式的数据消息;消息确认采用手工确认的方式,将数据解码组件锚定数据接入组件,实现每条数据的可靠处理;数据解码时进行字节校验和时间检查等,过滤异常数据;应用批量加定时的发送策略,解决海量监控信息发送气象综合业务实时监控系统(天镜)的问题;集群部署时保留部分剩余资源,有效应对单节点异常。应用效果表明:国家气象站小时数据的服务时效由全国综合气象信息共享系统(CIMISS)的175 s提高至天擎的78 s,约6×10^(4)个区域气象站小时数据的服务时效由CIMISS的5 min提高至天警的2 min,实况分析系统将数据源切换至天擎后,相同时间检索可获取的站点数量较CIMISS增加1倍。2021年12月基于Storm的流式处理与天擎一同在国省业务化运行,实现了长期稳定运行,为MICAPS4、SWAN2.0、实况分析系统等用户提供高效稳定的地面自动气象站数据。

Storm分布式计算框架下基于知识图谱的快速学习资源推荐

针对在线学习资源推荐存在精度较低或实时性较差的问题,采用知识图谱进行用户及资源的知识表示,并采用长短时间记忆网络对用户资源特征差进行优化,从而将与用户特征差最小的资源推送给用户。首先,在获得在线学习记录样本后,利用知识图谱进行实体特征关系的知识表示,并借助Storm分布式框架生成知识图谱中头尾实体及关系特征向量。接着,建立用户-资源实体的最小特征差目标函数,并采用长短时间记忆网络对最小特征差目标函数进行优化。最后,通过Storm分布式平台进行长短时间记忆网络的参数求解,从而快速生成稳定的相关资源推荐模型。实验结果表明,在Storm分布式框架下采用知识图谱和长短时间记忆网络实现在线资源推荐,可获得较高准确率及运行效率,在应对大规模资源的实时推荐方面具有较强的适应度。

Machine Learning Analysis of Impact of Western US Fires on Central US Hailstorms

Fires,including wildfires,harm air quality and essential public services like transportation,communication,and utilities.These fires can also influence atmospheric conditions,including temperature and aerosols,potentially affecting severe convective storms.Here,we investigate the remote impacts of fires in the western United States(WUS)on the occurrence of large hail(size:≥2.54 cm)in the central US(CUS)over the 20-year period of 2001–20 using the machine learning(ML),Random Forest(RF),and Extreme Gradient Boosting(XGB)methods.The developed RF and XGB models demonstrate high accuracy(>90%)and F1 scores of up to 0.78 in predicting large hail occurrences when WUS fires and CUS hailstorms coincide,particularly in four states(Wyoming,South Dakota,Nebraska,and Kansas).The key contributing variables identified from both ML models include the meteorological variables in the fire region(temperature and moisture),the westerly wind over the plume transport path,and the fire features(i.e.,the maximum fire power and burned area).The results confirm a linkage between WUS fires and severe weather in the CUS,corroborating the findings of our previous modeling study conducted on case simulations with a detailed physics model.

Ecological problems and ecological restoration zoning of the Aral Sea

The Aral Sea was the fourth largest lake in the world but it has shrunk dramatically as a result of irrational human activities, triggering the "Aral Sea ecological crisis". The ecological problems of the Aral Sea have attracted widespread attention, and the alleviation of the Aral Sea ecological crisis has reached a consensus among the five Central Asian countries(Kazakhstan, Uzbekistan, Tajikistan, Kyrgyzstan, and Turkmenistan). In the past decades, many ecological management measures have been implemented for the ecological restoration of the Aral Sea. However, due to the lack of regional planning and zoning, the results are not ideal. In this study, we mapped the ecological zoning of the Aral Sea from the perspective of ecological restoration based on soil type, soil salinity, surface water, groundwater table, Normalized Difference Vegetation Index(NDVI), land cover, and aerosol optical depth(AOD) data. Soil salinization and salt dust are the most prominent ecological problems in the Aral Sea. We divided the Aral Sea into 7 first-level ecological restoration subregions(North Aral Sea catchment area in the downstream of the Syr Darya River(Subregion Ⅰ);artificial flood overflow area in the downstream of the Aral Sea(Subregion Ⅱ);physical/chemical remediation area of the salt dust source area in the eastern part of the South Aral Sea(Subregion Ⅲ);physical/chemical remediation area of severe salinization in the central part of the South Aral Sea(Subregion Ⅳ);existing water surface and potential restoration area of the South Aral Sea(Subregion Ⅴ);Aral Sea vegetation natural recovery area(Subregion Ⅵ);and vegetation planting area with slight salinization in the South Aral Sea(Subregion Ⅶ)) and 14 second-level ecological restoration subregions according to the ecological zoning principles. Implementable measures are proposed for each ecological restoration subregion. For Subregion Ⅰ and Subregion Ⅱ with lower elevations, artificial flooding should be carried out to restore the surface of the Aral Sea. Subregion Ⅲ and Subregion Ⅳ have severe salinization, making it difficult for vegetation to grow. In these subregions, it is recommended to cover and pave the areas with green biomatrix coverings and environmentally sustainable bonding materials. In Subregion Ⅴ located in the central and western parts of the South Aral Sea, surface water recharge should be increased to ensure that this subregion can maintain normal water levels. In Subregion Ⅵ and Subregion Ⅶ where natural conditions are suitable for vegetation growth, measures such as afforestation and buffer zones should be implemented to protect vegetation. This study could provide a reference basis for future comprehensive ecological management and restoration of the Aral Sea.

Potential morphological responses of an artificial beach to a flood in extreme events: field observation and numerical modelling

Conch Island is a typical artificial island at the Tanghe Estuary in Bohai Sea,China.To improve natural environment and boost local tourism,beach nourishment will be applied to its north-western shore.The projected beach is landward and opposite to the Jinmeng Bay Beach.Nowadays,with climate changes,frequent heavy rainfalls in Hebei Province rise flood hazards at the Tanghe Estuary.Under this circumstance,potential influences on the projected beach of a flood are investigated for sustainable managements.A multi-coupled model is established and based on the data from field observations,where wave model,flow model and multifraction sediment transport model are included.In addition,the impacts on the projected beach of different components in extreme events are discussed,including the spring tides,storm winds,storm waves,and sediment inputs.The numerical results indicate the following result.(1)Artificial islands protect the coasts from erosion by obstructing landward waves,but rise the deposition risks along the target shore.(2)Flood brings massive sediment inputs and leads to scours at the estuary,but the currents with high sediment concentration contribute to the accretions along the target shore.(3)The projected beach mitigates flood actions and reduces the maximum mean sediment concentration along the target shore by 20%.(4)The storm winds restrict the flood and decrease the maximum mean sediment concentration by 21%.With the combined actions of storm winds and waves,the maximum value further declines by 38%.(5)A quadratic polynomial relationship between the deposition depths and the maximum sediment inputs with flood is established for estimations on the potential morphological changes after the flood process in extreme events.For the uncertainty of estuarine floods,continuous monitoring on local hydrodynamic variations and sediment characteristics at Tanghe Estuary is necessary.

Comparison of a Spectral Bin and Two Multi-Moment Bulk Microphysics Schemes for Supercell Simulation:Investigation into Key Processes Responsible for Hydrometeor Distributions and Precipitation

There are more uncertainties with ice hydrometeor representations and related processes than liquid hydrometeors within microphysics parameterization(MP)schemes because of their complicated geometries and physical properties.Idealized supercell simulations are produced using the WRF model coupled with“full”Hebrew University spectral bin MP(HU-SBM),and NSSL and Thompson bulk MP(BMP)schemes.HU-SBM downdrafts are typically weaker than those of the NSSL and Thompson simulations,accompanied by less rain evaporation.HU-SBM produces more cloud ice(plates),graupel,and hail than the BMPs,yet precipitates less at the surface.The limiting mass bins(and subsequently,particle size)of rimed ice in HU-SBM and slower rimed ice fall speeds lead to smaller melting-level net rimed ice fluxes than those of the BMPs.Aggregation from plates in HU-SBM,together with snow–graupel collisions,leads to a greater snow contribution to rain than those of the BMPs.Replacing HU-SBM’s fall speeds using the formulations of the BMPs after aggregating the discrete bin values to mass mixing ratios and total number concentrations increases net rain and rimed ice fluxes.Still,they are smaller in magnitude than bulk rain,NSSL hail,and Thompson graupel net fluxes near the surface.Conversely,the melting-layer net rimed ice fluxes are reduced when the fall speeds for the NSSL and Thompson simulations are calculated using HU-SBM fall speed formulations after discretizing the bulk particle size distributions(PSDs)into spectral bins.The results highlight precipitation sensitivity to storm dynamics,fall speed,hydrometeor evolution governed by process rates,and MP PSD design.

Trend of Storm Surge Induced by Typical Landfall Super Typhoons During 1975–2021 in the Eastern China Sea

Climate change affects the activity of global and regional tropical cyclones(TCs).Among all TCs,typical super typhoons(STYs)are particularly devastating because they maintain their intensity when landing on the coast and thus cause casualties,economic losses,and environmental damage.Using a 3D tidal model,we reconstructed the typhoon(TY)wind field to simulate the storm surge induced by typical STYs.The TY activity was then analyzed using historical data.Results showed a downtrend of varying degrees in the annual frequency of STYs and TCs in the Western North Pacific(WNP)Basin,with a significant trend change observed for TCs from 1949 to 2021.A large difference in the interannual change in frequency was found between STYs and TCs in the WNP and Eastern China Sea(ECS).Along the coast of EC,the frequency of landfall TCs showed a weak downtrend,and the typical STYs showed reverse micro growth with peak activity in August.Zhejiang,Fujian,and Taiwan were highly vulnerable to the frontal hits of typical STYs.Affected by climate change,the average lifetime maximum intensity(LMI)locations and landfall locations of typical STYs in the ECS basin showed a significant poleward migration trend.In addition,the annual average LMI and accumulated cyclone energy showed an uptrend,indicating the increasing severity of the disaster risk.Affected by the typical STY activity in the ECS,the maximum storm surge area also showed poleward migration,and the coast of North China faced potential growth in high storm surge risks.

Snow and regolith albedo variations using CRISM data at McMurdo crater,Mars

The cryosphere component provides the most reliable and insightful indications of any planet’s climate dynamics.Using data from the Compact Reconnaissance Imaging Spectrometer for Mars(CRISM),we develop a novel approach to determining the broadband Visible and Near Infrared(VNIR)albedo of the Martian surface.This study focuses on albedo changes in the McMurdo crater,part of Mars’s south polar layer deposits.We compare seasonal and interannual variations of the McMurdo surface albedo before,during,and after the Global Dust Storm(GDS)of Martian Year(MY)34.As the seasons progressed from spring to summer,the mean albedo in MY 32 and 34 plunged by over 40%,by about 35%in MY 33,and by slightly more than 30%in MY 35.Compared interannually,however,mean albedo values within both seasons(spring and summer)exhibited no significant differences in those same years.Notably,interannual albedo difference maps reveal albedo variation of more than±0.3 in certain regions of the crater.Considering only snow-covered pixels,interannual albedo differences suggest that Mars dust had a pervasive impact on Mars’s cryosphere.Variations in maximum and minimum albedo values as high as 0.5 were observed,depending upon differences in the dust levels in Martian snow/ice.The maximum and the minimum snow albedo values were lowest in MY 34,indicating the effect of the intense dust storm event that year.The average snow albedo decreased from 0.45 in MY 32 to 0.40 in MY 33 and to 0.33 in MY 34,and then rose back to 0.40 in MY 35.This trajectory suggests a temporary deposition of dust,partially reversed after the GDS by self-cleaning mechanisms(local aeolian process and CO_(2)sublimation/deposition cycle).

分布式计算中基于机器学习聚类的人力资源管理推荐

由于受到特征维度及数据规模的影响,人力资源精准推荐难度提升。为了提高人力资源管理平台的自适应推荐精准度,采用机器学习聚类推荐策略,将AP聚类算法应用于大规模人力资源推荐,并借助于Storm计算框架提高推荐效率。首先,根据人力资源平台的用户行为记录进行特征提取并初始化,并借助PCA算法进行特征提取,构建求职者和岗位的评分函数。然后,采用AP聚类算法对求职者—岗位特征进行聚类分析,根据聚类结果获得候选岗位推荐序列。AP聚类的所有过程均在Storm分布式节点中完成。通过对4家大型网络招聘平台的仿真分析,分别从不同推荐序列、不同聚类数目及不同特征数的角度下展开人力资源推荐性能分析。结果表明,AP聚类在4家平台的人力资源推荐中获得较高的Recall和F1性能,而分布式计算则有效提升了推荐加速比。

Thermosphere joint observations by TM-1 constellations and Swarm-B during the April 2023 geomagnetic storm

The response of thermosphere density to geomagnetic storms is a complicated physical process.Multi-satellite joint observations at the same altitude but different local times(LTs)are important for understanding this process;however,until now such studies have hardly been done.In this report,we analyze in detail the thermosphere mass density response at 510 km during the April 23−24,2023 geomagnetic storm using data derived from the TM-1(TianMu-1)satellite constellation and Swarm-B satellites.The observations show that there were significant LT differences in the hemispheric asymmetry of the thermosphere mass density during the geomagnetic storm.Densities observed by satellite TM02 at nearly 11.3 and 23.3 LTs were larger in the northern hemisphere than in the southern.The TM04 dayside density observations appear to be almost symmetrical with respect to the equator,though southern hemisphere densities on the nightside were higher.Swarm-B data exhibit near-symmetry between the hemispheres.In addition,the mass density ratio results show that TM04 nightside observations,TM02 data,and Swarm-B data all clearly show stronger effects in the southern hemisphere,except for TM04 on the dayside,which suggest hemispheric near-symmetry.The South-North density enhancement differences in TM02 and TM04 on dayside can reach 130%,and Swarm-B data even achieve 180%difference.From the observations of all three satellites,large-scale traveling atmospheric disturbances(TADs)first appear at high latitudes and propagate to low latitudes,thereby disturbing the atmosphere above the equator and even into the opposite hemisphere.NRLMSISE00 model simulations were also performed on this geomagnetic storm.TADs are absent in the NRLMSISE00 simulations.The satellite data suggest that NRLMSISE00 significantly underestimates the magnitude of the density response of the thermosphere during geomagnetic storms,especially at high latitudes in both hemispheres.Therefore,use of the density simulation of NRLMSISE00 may lead to large errors in satellite drag calculations and orbit predictions.We suggest that the high temporal and spatial resolution of direct density observations by the TM-1 constellation satellites can provide an autonomous and reliable basis for correction and improvement of atmospheric models.

A statistical analysis of the Kappa-type energy spectrum distribution of radiation belt electrons observed by Van Allen Probes

The energy spectrum of energetic electrons is a key factor representing the dynamic variations of Earth’s Van Allen radiation belts.Increased measurements have indicated that the commonly used Maxwellian and Kappa distributions are inadequate for capturing the realistic spectral distributions of radiation belt electrons.Here we adopt the Kappa-type(KT)distribution as the fitting function and perform a statistical analysis to investigate the radiation belt electron flux spectra observed by the Van Allen Probes.By calculating the optimal values of the key KT distribution parameters(i.e.,κandθ2)from the observed spectral shapes,we fit the radiation belt electron fluxes at different L-shells under different geomagnetic conditions.In this manner,we obtain typical values of the KT distribution parameters,which are statistically feasible for modeling the radiation belt electron flux profiles during either geomagnetically quiet or active periods.A comparison of the KT distribution model results with those using the Maxwellian or Kappa distribution reveals the advantage of the KT distribution for studying the overall properties of the radiation belt electron spectral distribution,which has important implications for deepening the current understanding of the radiation belt electron dynamics under evolving geomagnetic conditions.

Explaining the dynamics of the sub-relativistic electron third belt in the Earth's radiation belts by using medium Earth orbit satellite observations

The Earth's electron radiation belts typically exhibit a two-belt structure.However,observations from the Van Allen Probes revealed the existence of a three-belt structure.This structure consists of an inner belt,a slot region,a remnant belt,a“second slot,”and a new outer belt(or the“third belt”).The formation of the structure involves both the partial loss of the original outer belts and the formation of the third belts.These processes are likely associated with radial diffusion induced by ultra-low-frequency(ULF)waves.In this study,we mainly analyzed electron flux data from medium Earth orbit(MEO)navigation satellites M17–M19 to supplement the observational evidence for the sub-relativistic electron(~100–500 keV)three-belt structure.Evidence of substorm injections and ULF waves during the three-belt event was identified,suggesting they played significant roles in the formation and evolution of the third belt.Substorm injections may introduce new electron populations to the third belt,whereas ULF waves may influence the evolution of the third belt through radial diffusion.Toward the end of the three-belt event,the compression of the magnetosphere by shocks may lead to the dropout of the third belt because of the magnetopause shadowing effect and outward radial diffusion,ultimately disrupting the three-belt structure.This study provides more evidence for the presence of a sub-relativistic electron three-belt structure and offers an analysis of the evolutionary mechanisms of the third belt,which may contribute to a comprehensive understanding of the electron three-belt structure in the radiation belts.

Recent geomagnetic storms observed by Macao Science Satellite-1

Geomagnetic storms are rapid disturbances of the Earth’s magnetosphere.They are related to many geophysical phenomena and have large influences on human activities.Observing and studying geomagnetic storms is thus of great significance to both scientific research and geomagnetic hazards prevention.The Macao Science Satellite-1(MSS-1)project includes two high-precision Chinese geomagnetic satellites successfully launched on May 21,2023.The main purpose of MSS-1 is to accurately measure the Earth’s magnetic field.Here,we analyze early MSS-1 geomagnetic field measurements and report observations of two recent geomagnetic storms that occurred on March 24,2024 and May 11,2024.We also calculate the related geoelectric fields as an initial step towards a quantitative assessment of geomagnetic hazards.

A typhoon-induced storm surge numerical model with GPU acceleration based on an unstructured spherical centroidal Voronoi tessellation grid

Storm surge is often the marine disaster that poses the greatest threat to life and property in coastal areas.Accurate and timely issuance of storm surge warnings to take appropriate countermeasures is an important means to reduce storm surge-related losses.Storm surge numerical models are important for storm surge forecasting.To further improve the performance of the storm surge forecast models,we developed a numerical storm surge forecast model based on an unstructured spherical centroidal Voronoi tessellation(SCVT)grid.The model is based on shallow water equations in vector-invariant form,and is discretized by Arakawa C grid.The SCVT grid can not only better describe the coastline information but also avoid rigid transitions,and it has a better global consistency by generating high-resolution grids in the key areas through transition refinement.In addition,the simulation speed of the model is accelerated by using the openACC-based GPU acceleration technology to meet the timeliness requirements of operational ensemble forecast.It only takes 37 s to simulate a day in the coastal waters of China.The newly developed storm surge model was applied to simulate typhoon-induced storm surges in the coastal waters of China.The hindcast experiments on the selected representative typhoon-induced storm surge processes indicate that the model can reasonably simulate the distribution characteristics of storm surges.The simulated maximum storm surges and their occurrence times are consistent with the observed data at the representative tide gauge stations,and the mean absolute errors are 3.5 cm and 0.6 h respectively,showing high accuracy and application prospects.

Current remarks and future directions on the interactions between metabolic dysfunction-associated fatty liver disease and COVID-19

During the outbreak of the coronavirus disease 2019(COVID-19)pandemic,particular interest rose regarding the interaction between metabolic dysfunctionassociated fatty liver disease(MAFLD)and the COVID-19 infection.Several studies highlighted the fact that individuals with MAFLD had higher probability of severe acute respiratory syndrome coronavirus 2 infection and more severe adverse clinical outcomes.One of the proposed mechanisms is the inflammatory response pathway,especially the one involving cytokines,such as interleukin 6,which appeared particularly elevated in those patients and was deemed responsible for additional insult to the already damaged liver.This should increase our vigilance in terms of early detection,close follow up and early treatment for individuals with MAFLD and COVID-19 infection.In the direction of early diagnosis,biomarkers such as cytokeratin-18 and scoring systems such as Fibrosis-4 index score are proposed.COVID-19 is a newly described entity,expected to be of concern for the years to come,and MAFLD is a condition with an ever-increasing impact.Delineating the interaction between these two entities should be brought into the focus of research.Reducing morbidity and mortality of patients with COVID-19 and MAFLD should be the ultimate objective,and the optimal way to achieve this is by designing evidence-based prevention and treatment policies.

Risk assessment of coastal flooding disaster by storm surge based on Elevation-Area method and hydrodynamic models:Taking Bohai Bay as an example

The future inundation by storm surge on coastal areas are currently ill-defined.With increasing global sealevel due to climate change,the coastal flooding by storm surge is more and more frequently,especially in coastal lowland with land subsidence.Therefore,the risk assessment of such inundation for these areas is of great significance for the sustainable socio-economic development.In this paper,the authors use Elevation-Area method and Regional Ocean Model System(ROMS)model to assess the risk of the inundation of Bohai Bay by storm surge.The simulation results of Elevation-Area method show that either a 50-year or 100-year storm surge can inundate coastal areas exceeding 8000 km^(2);the numerical simulation results based on hydrodynamics,considering ground friction and duration of the storm surge high water,show that a 50-year or 100-year storm surge can only inundate an area of over 2000 km^(2),which is far less than 8000 km^(2);while,when taking into account the land subsidence and sea level rise,the very inundation range will rapidly increase by 2050 and 2100.The storm surge will greatly impact the coastal area within about 10-30 km of the Bohai Bay,in where almost all major coastal projects are located.The prompt response to flood disaster due to storm surge is urgently needed,for which five suggestions have been proposed based on the geological background of Bohai Bay.This study may offer insight into the development of the response and adaptive plans for flooding disasters caused by storm surge.

Mesenchymal stem cells and their derived exosomes for the treatment of COVID-19

Coronavirus disease 2019(COVID-19)is an acute respiratory infection caused by severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).SARS-CoV-2 infection typically presents with fever and respiratory symptoms,which can progress to severe respiratory distress syndrome and multiple organ failure.In severe cases,these complications may even lead to death.One of the causes of COVID-19 deaths is the cytokine storm caused by an overactive immune response.Therefore,suppressing the overactive immune response may be an effective strategy for treating COVID-19.Mesenchymal stem cells(MSCs)and their derived exosomes(MSCs-Exo)have potent homing abilities,immunomodulatory functions,regenerative repair,and antifibrotic effects,promising an effective tool in treating COVID-19.In this paper,we review the main mechanisms and potential roles of MSCs and MSCs-Exo in treating COVID-19.We also summarize relevant recent clinical trials,including the source of cells,the dosage and the efficacy,and the clinical value and problems in this field,providing more theoretical references for the clinical use of MSCs and MSCs-Exo in the treatment of COVID-19.

The dawn−dusk asymmetry in mesosphere and lower thermosphere temperature disturbances during geomagnetic storms at high latitude

Utilizing observations by the Sounding of the Atmosphere using Broadband Emission Radiometry(SABER)instrument,we quantitatively assessed the dawn-dusk asymmetry in temperature disturbances within the high-latitude mesosphere and lower thermosphere(MLT)during the main phase of geomagnetic storms in this study.An analysis of five geomagnetic superstorm events indicated that during the main phase,negative temperature disturbances were more prevalent on the dawn side than on the dusk side in the high-latitude MLT region.Results of a statistical analysis of 54 geomagnetic storm events also revealed a notable disparity in temperature disturbances between the dawn and dusk sides.At high latitudes,38.2%of the observational points on the dawn side exhibited negative temperature disturbances(less than−5 K),whereas on the dusk side,this percentage was only 29.5%.In contrast,at mid-latitudes,these proportions were 34.1%and 36.5%,respectively,showing no significant difference.We also conducted a statistical analysis of temperature disturbances at different altitudes,which revealed an increase in the proportion of warming disturbances with altitude.Conversely,the proportion of cooling disturbances initially rose with altitude,reaching a peak around 105 km,and subsequently decreased.These temperature disturbance differences could be explained by the day-night asymmetry in vertical wind disturbances during storm conditions.

Beyond conventional care:The therapeutic potential of hemoperfusion in severe COVID-19

BACKGROUND Hemoperfusion(HP)is an extracorporeal blood purification modality utilized to remove small-to medium-sized molecules,such as toxins and cytokines,that are difficult to remove by conventional hemodialysis.In clinical practice,HP has been successfully used as a salvage therapy for drug overdose and occasionally in patients with liver failure and sepsis.AIM To summarize the clinical outcomes of a series of patients with severe coronavirus disease 2019(COVID-19)who received HP.METHODS Here,we summarize the clinical outcomes of a series of 18 patients with severe COVID-19 who received HP in our institution during the COVID-19 pandemic.A review of the literature was also performed.RESULTS HP was well-tolerated,and after an average of three sessions,respiratory and cardiovascular parameters as well as blood inflammatory markers improved in most patients.Ten patients were discharged alive.Our literature search identified a total of 20 studies(873 patients)in which HP was used for COVID-19.Nine studies reported improvements in respiratory parameters,and 13 studies(438 patients in total)reported better survival rates in patients undergoing HP.CONCLUSION HP was well-tolerated in patients with severe COVID-19,and most studies reported improved clinical parameters,including better survival rates,when HP was used in patients with severe COVID-19.Further research,especially prospective studies,is needed to evaluate the utility of HP as an early and supportive therapy for critically ill patients due to infectious diseases,such as those with COVID-19 or severe sepsis.