Introduction of International Research Center on Karst under the Auspices of UNESCO

On December 15,2008,the International Research Center on Karst under the Auspices of UNESCO (hereinafter referred as IRCK)was formally established in Guilin,China.It is also the first category Ⅱ center concerning geosciences.Since its foundation,it has organized 11 international symposia, attracted over 200 foreign scientists from more than 40 countries for academic exchange,and signed 16 international cooperation agreements with 14 countries.It has played an active role for international exchange,set firm foundation for cooperative projects.

Big data in support of the Sustainable Development Goals:a celebration of the establishment of the International Research Center of Big Data for Sustainable Development Goals(CBAS)

In the last century the impacts of human activity on natural processes that sustain the Earth’s biosphere,atmosphere,hydrosphere and lithosphere and that provide the bed-rock of human life support systems,have grown to the extent that they pose a credible existential threat to humanity.Today,the biggest challenge for science,technology and innovation(STI)is to contribute to the pursuit of global sustainability as exemplified in the Sustainable Development Goals(SDGs)that were adopted by the United Nations(UN)in 2015.

Big data in support of the sustainable development goals(continued):a celebration of the establishment of the International Research Center of Big Data for Sustainable Development Goals(CBAS)

The rapid development of analytics and concepts in big data enables us to diversify our efforts and enhance opportunities to implement the Sustainable Development Goals(SDGs).Big data improves the extent to which scientific evidence and innova-tive technological solutions can be adopted to meet these goals.However,the tools and methods of big data are still somewhat of a novelty in this respect.

Research progresses on cathode materials of aqueous zinc-ion batteries

Electrochemical energy storage and conversion techniques that exhibit the merits such as high energy density,rapid response kinetics,economical maintenance requirements and expedient installation procedures will hold a pivotal role in the forthcoming energy storage technologies revolution.In recent years,aqueous zinc-ion batteries(AZIBs)have garnered substantial attention as a compelling candidate for large-scale energy storage systems,primarily attributable to their advantageous featu res encompassing cost-effectiveness,environmental sustainability,and robust safety profiles.Currently,one of the primary factors hindering the further development of AZIBs originates from the challenge of cathode materials.Specifically,the three mainstream types of mainstream cathode materials,in terms of manganese-based compounds,vanadium-based compounds and Prussian blue analogues,surfer from the dissolution of Mn~(2+),in the low discharge voltage,and the low specific capacity,respectively.Several strategies have been developed to compensation the above intrinsic defects for these cathode materials,including the ionic doping,defect engineering,and materials match.Accordingly,this review first provides a systematic summarization of the zinc storage mechanism in AZIBs,following by the inherent merit and demerit of three kind of cathode materials during zinc storage analyzed from their structure characteristic,and then the recent development of critical strategies towards the intrinsic insufficiency of these cathode materials.In this review,the methodologies aimed at enhancing the efficacy of manganese-based and vanadium-based compounds are emphasis emphasized.Additionally,the article outlines the future prospective directions as well as strategic proposal for cathode materials in AZIBs.

Efficient Electromagnetic Wave Absorption and Thermal Infrared Stealth in PVTMS@MWCNT Nano‑Aerogel via Abundant Nano‑Sized Cavities and Attenuation Interfaces

Pre-polymerized vinyl trimethoxy silane(PVTMS)@MWCNT nano-aerogel system was constructed via radical polymerization,sol-gel transition and supercritical CO_(2)drying.The fabricated organic-inorganic hybrid PVTMS@MWCNT aerogel structure shows nano-pore size(30-40 nm),high specific surface area(559 m^(2)g^(−1)),high void fraction(91.7%)and enhanced mechanical property:(1)the nano-pore size is beneficial for efficiently blocking thermal conduction and thermal convection via Knudsen effect(beneficial for infrared(IR)stealth);(2)the heterogeneous interface was beneficial for IR reflection(beneficial for IR stealth)and MWCNT polarization loss(beneficial for electromagnetic wave(EMW)attenuation);(3)the high void fraction was beneficial for enhancing thermal insulation(beneficial for IR stealth)and EMW impedance match(beneficial for EMW attenuation).Guided by the above theoretical design strategy,PVTMS@MWCNT nano-aerogel shows superior EMW absorption property(cover all Ku-band)and thermal IR stealth property(ΔT reached 60.7℃).Followed by a facial combination of the above nano-aerogel with graphene film of high electrical conductivity,an extremely high electromagnetic interference shielding material(66.5 dB,2.06 mm thickness)with superior absorption performance of an average absorption-to-reflection(A/R)coefficient ratio of 25.4 and a low reflection bandwidth of 4.1 GHz(A/R ratio more than 10)was experimentally obtained in this work.

Projecting Wintertime Newly Formed Arctic Sea Ice through Weighting CMIP6 Model Performance and Independence

Precipitous Arctic sea-ice decline and the corresponding increase in Arctic open-water areas in summer months give more space for sea-ice growth in the subsequent cold seasons. Compared to the decline of the entire Arctic multiyear sea ice,changes in newly formed sea ice indicate more thermodynamic and dynamic information on Arctic atmosphere–ocean–ice interaction and northern mid–high latitude atmospheric teleconnections. Here, we use a large multimodel ensemble from phase 6 of the Coupled Model Intercomparison Project(CMIP6) to investigate future changes in wintertime newly formed Arctic sea ice. The commonly used model-democracy approach that gives equal weight to each model essentially assumes that all models are independent and equally plausible, which contradicts with the fact that there are large interdependencies in the ensemble and discrepancies in models' performances in reproducing observations. Therefore, instead of using the arithmetic mean of well-performing models or all available models for projections like in previous studies, we employ a newly developed model weighting scheme that weights all models in the ensemble with consideration of their performance and independence to provide more reliable projections. Model democracy leads to evident bias and large intermodel spread in CMIP6 projections of newly formed Arctic sea ice. However, we show that both the bias and the intermodel spread can be effectively reduced by the weighting scheme. Projections from the weighted models indicate that wintertime newly formed Arctic sea ice is likely to increase dramatically until the middle of this century regardless of the emissions scenario.Thereafter, it may decrease(or remain stable) if the Arctic warming crosses a threshold(or is extensively constrained).

A Physics-informed Deep-learning Intensity Prediction Scheme for Tropical Cyclones over the Western North Pacific

Accurate prediction of tropical cyclone(TC)intensity is challenging due to the complex physical processes involved.Here,we introduce a new TC intensity prediction scheme for the western North Pacific(WNP)based on a time-dependent theory of TC intensification,termed the energetically based dynamical system(EBDS)model,together with the use of a long short-term memory(LSTM)neural network.In time-dependent theory,TC intensity change is controlled by both the internal dynamics of the TC system and various environmental factors,expressed as environmental dynamical efficiency.The LSTM neural network is used to predict the environmental dynamical efficiency in the EBDS model trained using besttrack TC data and global reanalysis data during 1982–2017.The transfer learning and ensemble methods are used to retrain the scheme using the environmental factors predicted by the Global Forecast System(GFS)of the National Centers for Environmental Prediction during 2017–21.The predicted environmental dynamical efficiency is finally iterated into the EBDS equations to predict TC intensity.The new scheme is evaluated for TC intensity prediction using both reanalysis data and the GFS prediction data.The intensity prediction by the new scheme shows better skill than the official prediction from the China Meteorological Administration(CMA)and those by other state-of-art statistical and dynamical forecast systems,except for the 72-h forecast.Particularly at the longer lead times of 96 h and 120 h,the new scheme has smaller forecast errors,with a more than 30%improvement over the official forecasts.

Cascade utilization of full spectrum solar energy for achieving simultaneous hydrogen production and all-day thermoelectric conversion

Solar-driven photocatalytic water/seawater splitting holds great potential for green hydrogen production.However,the practical application is hindered by the relatively low conversion efficiency resulting from the inadequate utilization of solar spectrum with significant waste in the form of heat.Moreover,current equipment struggles to maintain all-day operation subjected to the lack of light during nighttime.Herein,a novel hybrid system integrating photothermal catalytic(PTC)reactor,thermoelectric generator(TEG),and phase change materials(PCM)was proposed and designed(named as PTC-TEG-PCM)to address these challenges and enable simultaneous overall seawater splitting and 24-hour power generation.The PTC system effectively maintains in an optimal temperature range to maximize photothermal-assisted photocatalytic hydrogen production.The TEG component recycles the low-grade waste heat for power generation,complementing the shortcoming of photocatalytic conversion and achieving cascade utilization of full-spectrum solar energy.Furthermore,exceptional thermal storage capability of PCM allow for the conversion of released heat into electricity during nighttime,contributing significantly to the overall power output and enabling PTC-TEG-PCM to operate for more than 12 h under the actual condition.Compared to traditional PTC system,the overall energy conversion efficiency of the PTC-TEG-PCM system can be increased by∼500%,while maintaining the solar-to-hydrogen efficiency.The advancement of this novel system demonstrated that recycling waste heat from the PTC system and utilizing heat absorption/release capability of PCM for thermoelectric application are effective strategies to improve solar energy conversion.With flexible parameter designing,PTC-TEG-PCM can be applied in various scenarios,offering high efficiency,stability,and sustainability.

Effect of boundary conditions on shakedown analysis of heterogeneous materials

The determination of the ultimate load-bearing capacity of structures made of elastoplastic heterogeneous materials under varying loads is of great importance for engineering analysis and design. Therefore, it is necessary to accurately predict the shakedown domains of these materials. The static shakedown theorem, also known as Melan's theorem, is a fundamental method used to predict the shakedown domains of structures and materials. Within this method, a key aspect lies in the construction and application of an appropriate self-equilibrium stress field(SSF). In the structural shakedown analysis, the SSF is typically constructed by governing equations that satisfy no external force(NEF) boundary conditions. However, we discover that directly applying these governing equations is not suitable for the shakedown analysis of heterogeneous materials. Researchers must consider the requirements imposed by the Hill-Mandel condition for boundary conditions and the physical significance of representative volume elements(RVEs). This paper addresses this issue and demonstrates that the sizes of SSFs vary under different boundary conditions, such as uniform displacement boundary conditions(DBCs), uniform traction boundary conditions(TBCs), and periodic boundary conditions(PBCs). As a result, significant discrepancies arise in the predicted shakedown domain sizes of heterogeneous materials. Built on the demonstrated relationship between SSFs under different boundary conditions, this study explores the conservative relationships among different shakedown domains, and provides proof of the relationship between the elastic limit(EL) factors and the shakedown loading factors under the loading domain of two load vertices. By utilizing numerical examples, we highlight the conservatism present in certain results reported in the existing literature. Among the investigated boundary conditions, the obtained shakedown domain is the most conservative under TBCs.Conversely, utilizing PBCs to construct an SSF for the shakedown analysis leads to less conservative lower bounds, indicating that PBCs should be employed as the preferred boundary conditions for the shakedown analysis of heterogeneous materials.

Persistent Variations in the East Asian Trough from March to April and the Possible Mechanism

The East Asian trough(EAT)profoundly influences the East Asian spring climate.In this study,the relationship of the EATs among the three spring months is investigated.Correlation analysis shows that the variation in March EAT is closely related to that of April EAT.Extended empirical orthogonal function(EEOF)analysis also confirms the co-variation of the March and April EATs.The positive/negative EEOF1 features the persistent strengthened/weakened EAT from March to April.Further investigation indicates that the variations in EEOF1 are related to a dipole sea surface temperature(SST)pattern over the North Atlantic and the SST anomaly over the tropical Indian Ocean.The dipole SST pattern over the North Atlantic,with one center east of Newfoundland Island and another east of Bermuda,could trigger a Rossby wave train to influence the EAT in March−April.The SST anomaly over the tropical Indian Ocean can change the Walker circulation and influence the atmospheric circulation over the tropical western Pacific,subsequently impacting the southern part of the EAT in March−April.Besides the SST factors,the Northeast Asian snow cover could change the regional thermal conditions and lead to persistent EAT anomalies from March to April.These three impact factors are generally independent of each other,jointly explaining large variations in the EAT EEOF1.Moreover,the signals of the three factors could be traced back to February,consequently providing a potential prediction source for the EAT variation in March and April.

Topology Optimization of Two Fluid Heat Transfer Problems for Heat Exchanger Design

Topology optimization of thermal-fluid coupling problems has received widespread attention.This article proposes a novel topology optimization method for laminar two-fluid heat exchanger design.The proposed method utilizes an artificial density field to create two permeability interpolation functions that exhibit opposing trends,ensuring separation between the two fluid domains.Additionally,a Gaussian function is employed to construct an interpolation function for the thermal conductivity coefficient.Furthermore,a computational program has been developed on the OpenFOAM platform for the topology optimization of two-fluid heat exchangers.This program leverages parallel computing,significantly reducing the time required for the topology optimization process.To enhance computational speed and reduce the number of constraint conditions,we replaced the conventional pressure drop constraint condition in the optimization problem with a pressure inlet/outlet boundary condition.The 3D optimization results demonstrate the characteristic features of a surface structure,providing valuable guidance for designing heat exchangers that achieve high heat exchange efficiency while minimizing excessive pressure loss.At the same time,a new structure appears in large-scale topology optimization,which proves the effectiveness and stability of the topology optimization program written in this paper in large-scale calculation.

SDGSAT-1: Capabilities for Monitoring and Evaluating SDG Indicators

SDGSAT-1,the world's first science satellite dedicated to assisting the United Nations 2030 Sustainable Development Agenda,has been operational for over two and a half years.It provides valuable data to aid in implementing the Sustainable Development Goals internationally.Through its Open Science Program,the satellite has maintained consistent operations and delivered free data to scientific and technological users from 88 countries.This program has produced a wealth of scientific output,with 72 papers,including 28 on data processing methods and 44 on applications for monitoring progress toward SDGs related to sustainable cities,clean energy,life underwater,climate action,and clean water and sanitation.SDGSAT-1 is equipped with three key instruments:a multispectral imager,a thermal infrared spectrometer,and a glimmer imager,which have enabled ground-breaking research in a variety of domains such as water quality analysis,identification of industrial heat sources,assessment of environmental disaster impacts,and detection of forest fires.The precise measurements and ongoing monitoring made possible by this invaluable data significantly advance our understanding of various environmental phenomena.They are essential for making well-informed decisions on a local and global scale.Beyond its application to academic research,SDGSAT-1 promotes global cooperation and strengthens developing countries'capacity to accomplish their sustainable development goals.As the satellite continues to gather and distribute data,it plays a pivotal role in developing strategies for environmental protection,disaster management and relief,and resource allocation.These initiatives highlight the satellite's vital role in fostering international collaboration and technical innovation to advance scientific knowledge and promote a sustainable future.

A Data-driven Model to Reduce Outlet NO_(x)Concentration of SCR System in FCC Unit

Samples(25500)were collected from a selective catalytic reduction(SCR)denitrification system in a fluid catalytic cracking unit and preprocessed using the quartile method and the K-nearest neighbors interpolation method to remove outliers.Using the Pearson correlation coefficient and LightGBM feature score method,13 key operational variables were identified and used to establish a model to predict outlet nitrogen oxide(NO_(x))concentration in an SCR system with backpropagation neural network,long short-term memory(LSTM)and LSTM-attention fully connected(FC)model,respectively.The LSTM-attention FC model showed better accuracy and generalization capability compared with other models.Its mean square error,mean absolute error,and coefficient of determination on the training and test datasets were 11.32 and 12.51,3.65%and 3.97%,and 0.96 and 0.94,respectively.Furthermore,a combination of the LSTM-attention FC model with a genetic algorithm used to optimize four feature variables including ammonia pressure compensation,inlet pressure,gas inlet upper temperature,and outlet ammonia concentration.The outlet NO_(x)concentration could be controlled below 80±3 mg/m^(3),and the ammonia slip concentration could be controlled below 0.1 mg/m^(3),demonstrating that the optimization model can provide effective guidance for reducing NO_(x)emissions and ammonia slip of SCR systems.

Spatial and temporal variation of water clarity in typical reservoirs in the Beijing-Tianjin-Hebei region observed by GF 1-WFV satellite data

Rapidly monitoring regional water quality and the changing trend is of great practical and scientific significance,especially for the Beijing-Tianjin-Hebei(BTH)region of China where water resources are relatively scarce and inland water bodies are generally small.The remote sensing data of the GF 1 satellite launched in 2013 have characteristics of high spatial and temporal resolution,which can be used for the dynamic monitoring of the water environment in small lakes and reservoirs.However,the water quality remote sensing monitoring model based on the GF 1 satellite data for lakes and reservoirs in BTH is still lacking because of the considerable differences in the optical characteristics of the lakes and reservoirs.In this paper,the typical reservoirs in BTH-Guanting Reservoir,Yuqiao Reservoir,Panjiakou Reservoir,and Daheiting Reservoir are taken as the study areas.In the atmospheric correction of GF 1-WFV,the relative radiation normalized atmospheric correction was adopted after comparing it with other methods,such as 6 S and FLAASH.In the water clarity retrieval,a water color hue angle based model was proposed and outperformed other available published models,with the R 2 of 0.74 and MRE of 31.7%.The clarity products of the four typical reservoirs in the BTH region in 2013-2019 were produced using the GF 1-WFV data.Based on the products,temporal and spatial changes in clarity were analyzed,and the main influencing factors for each water body were discussed.It was found that the clarity of Guanting,Daheiting,and Panjiakou reservoirs showed an upward trend during this period,while that of Yuqiao Reservoir showed a downward trend.In the influencing factors,the water level of the water bodies can be an important factor related to the water clarity changes in this region.

New Record Ocean Temperatures and Related Climate Indicators in 2023

The global physical and biogeochemical environment has been substantially altered in response to increased atmospheric greenhouse gases from human activities.In 2023,the sea surface temperature(SST)and upper 2000 m ocean heat content(OHC)reached record highs.The 0–2000 m OHC in 2023 exceeded that of 2022 by 15±10 ZJ(1 Zetta Joules=1021 Joules)(updated IAP/CAS data);9±5 ZJ(NCEI/NOAA data).The Tropical Atlantic Ocean,the Mediterranean Sea,and southern oceans recorded their highest OHC observed since the 1950s.Associated with the onset of a strong El Niño,the global SST reached its record high in 2023 with an annual mean of~0.23℃ higher than 2022 and an astounding>0.3℃ above 2022 values for the second half of 2023.The density stratification and spatial temperature inhomogeneity indexes reached their highest values in 2023.

Preface to the Special Topic on Ocean, Sea Ice and Northern Hemisphere Climate:In Remembrance of Professor Yongqi GAO's Key Contributions

This special issue commemorates the life work of Prof. Yongqi GAO who passed away in July 2021, his time cut short by illness. He had many great achievements, but still much more to contribute. The seven articles in this special issue are from research areas where he contributed, and they illustrate how his close colleagues are continuing his work.

Critical analysis of the ULF power depression as a possible Tohoku earthquake precursor

Among electromagnetic methods of short-term earthquake prediction,an approach is being actively developed based on the phenomenon of magnetic ultra-low-frequency(ULF)power depression occurring a few days before an earthquake.In particular,a nighttime geomagnetic power depression in the band 0.03-0.05 Hz was observed approximately 5 days before the catastrophic Tohoku 2011 earthquake.To verify the reliability of this method,we performed an extended analysis using data from magnetometer arrays JMA,MAGDAS,PWING,and INTERMAGNET.The selected stations included sites close to the epicenter(<300 km)and remote points(~10000 km).The band-integrated spectral power of nighttime magnetic noise decreased significantly from March 6-9,several days before the earthquake.However,such variations occur simultaneously not only at nearby stations but also at distant stations.During this event,the ULF power depression was caused by low global geomagnetic activity,as evidenced by the planetary index SME.Thus,the depression of geomagnetic ULF noise cannot be considered a reliable short-term precursor.

Biomimetic MXene membranes with negatively thermo-responsive switchable 2D nanochannels for graded molecular sieving

Negatively thermo-responsive 2D membranes,which mimic the stomatal opening/closing of plants,have drawn substantial interest for tunable molecular separation processes.However,these membranes are still restricted significantly on account of low water permeability and poor dynamic tunability of 2D nanochannels under temperature stimulation.Here,we present a biomimetic negatively thermo-responsive MXene membrane by covalently grafting poly(N-isopropylacrylamide)(PNIPAm)onto MXene nanosheets.The uniformly grafted PNIPAm polymer chains can enlarge the interlayer spacings for increasing water permeability while also allowing more tunability of 2D nanochannels for enhancing the capability of gradually separating multiple molecules of different sizes.As expected,the constructed membrane exhibits ultrahigh water permeance of 95.6 L m^(-2) h^(-1) bar^(-1) at 25℃,which is eight-fold higher than the state-of-the-art negatively thermoresponsive 2D membranes.Moreover,the highly temperature-tunable 2D nanochannels enable the constructed membrane to perform excellent graded molecular sieving for dye-and antibiotic-based ternary mixtures.This strategy provides new perspectives in engineering smart 2D membrane and expands the scope of temperature-responsive membranes,showing promising applications in micro/nanofluidics and molecular separation.

Network Pharmacology and Experimental Study of MomordicineⅠand MomordicineⅡfrom Bitter Melon Saponins in Inhibiting Fat Accumulation

Bitter melon(Momordica Charania L.),a member of the Cucurbitaceae family,is widely distributed across tropical and subtropical regions.Saponin,an important functional component of bitter melon,has been proven to exert hypoglycemic effects similarly to insulin,and also possesses lipid-lowering properties inhibiting preadipocyte differentiation and fat synthesis^([1]).

Impacts of monsoon break events in the western North Pacific on the cross-equatorial flows over the Maritime Continent

本文利用ERA5逐日再分析资料,探讨了1979-2020年间西北太平洋季风中断事件对海洋性大陆越赤道气流的影响.合成结果表明,西北太平洋季风中断事件会造成高,低空越赤道气流减弱,即高层南风异常,低层北风异常,与此相关的环流异常表现为西北太平洋高层气旋,低层反气旋的斜压结构。特别的是,西北太平洋季风中断对高空越赤道气流的影响更为显著,92%的季风中断事件都导致高空越赤道气流减弱,而只有70%的事件造成低空越赤道气流减弱,这是由于低空越赤道气流同时还受到赤道中东太平洋海温异常的调控.