The future of artificial hibernation medicine:protection of nerves and organs after spinal cord injury

Spinal cord injury is a serious disease of the central nervous system involving irreversible nerve injury and various organ system injuries.At present,no effective clinical treatment exists.As one of the artificial hibernation techniques,mild hypothermia has preliminarily confirmed its clinical effect on spinal cord injury.However,its technical defects and barriers,along with serious clinical side effects,restrict its clinical application for spinal cord injury.Artificial hibernation is a futureoriented disruptive technology for human life support.It involves endogenous hibernation inducers and hibernation-related central neuromodulation that activate particular neurons,reduce the central constant temperature setting point,disrupt the normal constant body temperature,make the body adapt"to the external cold environment,and reduce the physiological resistance to cold stimulation.Thus,studying the artificial hibernation mechanism may help develop new treatment strategies more suitable for clinical use than the cooling method of mild hypothermia technology.This review introduces artificial hibernation technologies,including mild hypothermia technology,hibernation inducers,and hibernation-related central neuromodulation technology.It summarizes the relevant research on hypothermia and hibernation for organ and nerve protection.These studies show that artificial hibernation technologies have therapeutic significance on nerve injury after spinal co rd injury through inflammatory inhibition,immunosuppression,oxidative defense,and possible central protection.It also promotes the repair and protection of res pirato ry and digestive,cardiovascular,locomoto r,urinary,and endocrine systems.This review provides new insights for the clinical treatment of nerve and multiple organ protection after spinal cord injury thanks to artificial hibernation.At present,artificial hibernation technology is not mature,and research fa ces various challenges.Neve rtheless,the effort is wo rthwhile for the future development of medicine.

Preparation of a high-performance synthetic pitch from aromatic hydrocarbons containing N/Cl

The preparation of a synthetic pitch from aromatic monomers could easily regulate structure orientation at the molecu-lar level,which would be useful in fabrication.An isotropic synthetic pitch was prepared by a chlorine-and/or nitrogen-induced sub-stitution polymerization reaction method using aromatic hydrocarbon precursors containing Cl and N,which for this study were chloromethyl naphthalene and quinoline.This method was verified by investigating the structural changes under different synthesis conditions,and the synthesis mechanism induced by aromatics containing Cl was also probed.The result shows that the pyridinic N in quinoline contains a lone pair of electrons,and is an effective active site to induce the polymerization reaction by coupling with aromatic hydrocarbons containing Cl.The reaction between such free radicals causes strong homopolymerization and oligomeriza-tion.A higher reaction temperature and longer reaction time significantly increased the degree of polymerization and thus increased the softening point of the pitch.A linear molecular structure was formed by the Cl substitution reaction,which produced a highly spinnable pitch with a softening point of 258.6℃,and carbon fibers with a tensile strength of 1163.82 MPa were obtained.This study provides a relatively simple and safe method for the preparation of high-quality spinnable pitch.

Chemico-biological conversion of carbon dioxide

The unabated carbon dioxide(CO_(2))emission into the atmosphere has exacerbated global climate change,resulting in extreme weather events,biodiversity loss,and an intensified greenhouse effect.To address these challenges and work toward carbon(C)neutrality and reduced CO_(2)emissions,the capture and utilization of CO_(2)have become imperative in both scientific research and industry.One cutting-edge approach to achieving efficient catalytic performance involves integrating green bioconversion and chemical conversion.This innovative strategy offers several advantages,including environmental friendliness,high efficiency,and multi-selectivity.This study provides a comprehensive review of existing technical routes for carbon sequestration(CS)and introduces two novel CS pathways:the electrochemicalbiological hybrid and artificial photosynthesis systems.It also thoroughly examines the synthesis of valuable Cnproducts from the two CS systems employing different catalysts and biocatalysts.As both systems heavily rely on electron transfer,direct and mediated electron transfer has been discussed and summarized in detail.Additionally,this study explores the conditions suitable for different catalysts and assesses the strengths and weaknesses of biocatalysts.We also explored the biocompatibility of the electrode materials and developed novel materials.These materials were specifically engineered to combine with enzymes or microbial cells to solve the biocompatibility problem,while improving the electron transfer efficiency of both.Furthermore,this review summarizes the relevant systems developed in recent years for manufacturing different products,along with their respective production efficiencies,providing a solid database for development in this direction.The novel chemical-biological combination proposed herein holds great promise for the future conversion of CO_(2)into advanced organic compounds.Additionally,it offers exciting prospects for utilizing CO_(2)in synthesizing a wide range of industrial products.Ultimately,the present study provides a unique perspective for achieving the vital goals of“peak shaving”and C-neutrality,contributing significantly to our collective efforts to combat climate change and its associated challenges.

Improvement in Tol2 transposon for efficient large-cargo capacity transgene applications in cultured cells and zebrafish(Danio rerio)

Most viruses and transposons serve as effective carriers for the introduction of foreign DNA up to 11 kb into vertebrate genomes.However,their activity markedly diminishes with payloads exceeding 11 kb.Expanding the payload capacity of transposons could facilitate more sophisticated cargo designs,improving the regulation of expression and minimizing mutagenic risks associated with molecular therapeutics,metabolic engineering,and transgenic animal production.In this study,we improved the Tol2 transposon by increasing protein expression levels using a translational enhancer(QBI SP163,ST)and enhanced the nuclear targeting ability using the nuclear localization protein H2B(SHT).The modified Tol2 and ST transposon efficiently integrated large DNA cargos into human cell cultures(H1299),comparable to the well-established super PiggyBac system.Furthermore,mRNA from ST and SHT showed a significant increase in transgene delivery efficiency of large DNA payloads(8 kb,14 kb,and 24 kb)into zebrafish(Danio rerio).This study presents a modified Tol2 transposon as an enhanced nonviral vector for the delivery of large DNA payloads in transgenic applications.

Synthetic polymers:A review of applications in drilling fluids

With the growth of deep drilling and the complexity of the well profile,the requirements for a more complete and efficient exploitation of productive formations increase,which increases the risk of various complications.Currently,reagents based on modified natural polymers(which are naturally occurring compounds)and synthetic polymers(SPs)which are polymeric compounds created industrially,are widely used to prevent emerging complications in the drilling process.However,compared to modified natural polymers,SPs form a family of high-molecular-weight compounds that are fully synthesized by undergoing chemical polymerization reactions.SPs provide substantial flexibility in their design.Moreover,their size and chemical composition can be adjusted to provide properties for nearly all the functional objectives of drilling fluids.They can be classified based on chemical ingredients,type of reaction,and their responses to heating.However,some of SPs,due to their structural characteristics,have a high cost,a poor temperature and salt resistance in drilling fluids,and degradation begins when the temperature reaches 130℃.These drawbacks prevent SP use in some medium and deep wells.Thus,this review addresses the historical development,the characteristics,manufacturing methods,classification,and the applications of SPs in drilling fluids.The contributions of SPs as additives to drilling fluids to enhance rheology,filtrate generation,carrying of cuttings,fluid lubricity,and clay/shale stability are explained in detail.The mechanisms,impacts,and advances achieved when SPs are added to drilling fluids are also described.The typical challenges encountered by SPs when deployed in drilling fluids and their advantages and drawbacks are also discussed.Economic issues also impact the applications of SPs in drilling fluids.Consequently,the cost of the most relevant SPs,and the monomers used in their synthesis,are assessed.Environmental impacts of SPs when deployed in drilling fluids,and their manufacturing processes are identified,together with advances in SP-treatment methods aimed at reducing those impacts.Recommendations for required future research addressing SP property and performance gaps are provided.

深低温保存下高效抗冻多肽的合理设计和机理探讨

The development of effective antifreeze peptides to control ice growth has attracted a significant amount of attention yet still remains a great challenge.Here,we propose a novel design method based on in-depth investigation of repetitive motifs in various ice-binding proteins(IBPs)with evolution analysis.In this way,several peptides with notable antifreeze activity were developed.In particular,a designed antifreeze peptide named AVD exhibits ideal ice recrystallization inhibition(IRI),solubility,and biocompatibility,making it suitable for use as a cryoprotective agent(CPA).A mutation analysis and molecular dynamics(MD)simulations indicated that the Thr6 and Asn8 residues of the AVD peptide are fundamental to its ice-binding capacity,while the Ser18 residue can synergistically enhance their interaction with ice,revealing the antifreeze mechanism of AVD.Furthermore,to evaluate the cryoprotection potential of AVD,the peptide was successfully employed for the cryopreservation of various cells,which demonstrated significant post-freezing cell recovery.This work opens up a new avenue for designing antifreeze materials and provides peptide-based functional modules for synthetic biology.

Mapping soil organic matter in cultivated land based on multi-year composite images on monthly time scales

Rapid and accurate acquisition of soil organic matter(SOM)information in cultivated land is important for sustainable agricultural development and carbon balance management.This study proposed a novel approach to predict SOM with high accuracy using multiyear synthetic remote sensing variables on a monthly scale.We obtained 12 monthly synthetic Sentinel-2 images covering the study area from 2016 to 2021 through the Google Earth Engine(GEE)platform,and reflectance bands and vegetation indices were extracted from these composite images.Then the random forest(RF),support vector machine(SVM)and gradient boosting regression tree(GBRT)models were tested to investigate the difference in SOM prediction accuracy under different combinations of monthly synthetic variables.Results showed that firstly,all monthly synthetic spectral bands of Sentinel-2 showed a significant correlation with SOM(P<0.05)for the months of January,March,April,October,and November.Secondly,in terms of single-monthly composite variables,the prediction accuracy was relatively poor,with the highest R^(2)value of 0.36 being observed in January.When monthly synthetic environmental variables were grouped in accordance with the four quarters of the year,the first quarter and the fourth quarter showed good performance,and any combination of three quarters was similar in estimation accuracy.The overall best performance was observed when all monthly synthetic variables were incorporated into the models.Thirdly,among the three models compared,the RF model was consistently more accurate than the SVM and GBRT models,achieving an R^(2)value of 0.56.Except for band 12 in December,the importance of the remaining bands did not exhibit significant differences.This research offers a new attempt to map SOM with high accuracy and fine spatial resolution based on monthly synthetic Sentinel-2 images.

Numerical analysis on the factors affecting post-peak characteristics of coal under uniaxial compression

The post-peak characteristics of coal serve as a direct reflection of its failure process and are essential parameters for evaluating brittleness and bursting liability.Understanding the significant factors that influence post-peak characteristics can offer valuable insights for the prevention of coal bursts.In this study,the Synthetic Rock Mass method is employed to establish a numerical model,and the factors affecting coal post-peak characteristics are analyzed from four perspectives:coal matrix mechanical parameters,structural weak surface properties,height-to-width ratio,and loading rate.The research identifies four significant influencing factors:deformation modulus,density of discrete fracture networks,height-to-width ratio,and loading rate.The response and sensitivity of post-peak characteristics to single-factor and multi-factor interactions are assessed.The result suggested that feasible prevention and control measures for coal bursts can be formulated through four approaches:weakening the mechanical properties of coal pillars,increasing the number of structural weak surfaces in coal pillars,reducing the width of coal pillars,and optimizing mining and excavation speed.The efficacy of measures aimed at weakening the mechanical properties of coal is successfully demonstrated through a case study on coal burst prevention using large-diameter borehole drilling.

Scientific Elegance in NIDS: Unveiling Cardinality Reduction, Box-Cox Transformation, and ADASYN for Enhanced Intrusion Detection

The emergence of digital networks and the wide adoption of information on internet platforms have given rise to threats against users’private information.Many intruders actively seek such private data either for sale or other inappropriate purposes.Similarly,national and international organizations have country-level and company-level private information that could be accessed by different network attacks.Therefore,the need for a Network Intruder Detection System(NIDS)becomes essential for protecting these networks and organizations.In the evolution of NIDS,Artificial Intelligence(AI)assisted tools and methods have been widely adopted to provide effective solutions.However,the development of NIDS still faces challenges at the dataset and machine learning levels,such as large deviations in numeric features,the presence of numerous irrelevant categorical features resulting in reduced cardinality,and class imbalance in multiclass-level data.To address these challenges and offer a unified solution to NIDS development,this study proposes a novel framework that preprocesses datasets and applies a box-cox transformation to linearly transform the numeric features and bring them into closer alignment.Cardinality reduction was applied to categorical features through the binning method.Subsequently,the class imbalance dataset was addressed using the adaptive synthetic sampling data generation method.Finally,the preprocessed,refined,and oversampled feature set was divided into training and test sets with an 80–20 ratio,and two experiments were conducted.In Experiment 1,the binary classification was executed using four machine learning classifiers,with the extra trees classifier achieving the highest accuracy of 97.23%and an AUC of 0.9961.In Experiment 2,multiclass classification was performed,and the extra trees classifier emerged as the most effective,achieving an accuracy of 81.27%and an AUC of 0.97.The results were evaluated based on training,testing,and total time,and a comparative analysis with state-of-the-art studies proved the robustness and significance of the applied methods in developing a timely and precision-efficient solution to NIDS.

The occurrence,inheritance,and segregation of complex genomic structural variation in synthetic Brassica napus

"Synthetic"allopolyploids recreated by interspecific hybridization play an important role in providing novel genomic variation for crop improvement.Such synthetic allopolyploids often undergo rapid genomic structural variation(SV).However,how such SV arises,is inherited and fixed,and how it affects important traits,has rarely been comprehensively and quantitively studied in advanced generation synthetic lines.A better understanding of these processes will aid breeders in knowing how to best utilize synthetic allopolyploids in breeding programs.Here,we analyzed three genetic mapping populations(735 DH lines)derived from crosses between advanced synthetic and conventional Brassica napus(rapeseed)lines,using whole-genome sequencing to determine genome composition.We observed high tolerance of large structural variants,particularly toward the telomeres,and preferential selection for balanced homoeologous exchanges(duplication/deletion events between the A and C genomes resulting in retention of gene/chromosome dosage between homoeologous chromosome pairs),including stable events involving whole chromosomes("pseudoeuploidy").Given the experimental design(all three populations shared a common parent),we were able to observe that parental SV was regularly inherited,showed genetic hitchhiking effects on segregation,and was one of the major factors inducing adjacent novel and larger SV.Surprisingly,novel SV occurred at low frequencies with no significant impacts on observed fertility and yield-related traits in the advanced generation synthetic lines.However,incorporating genome-wide SV in linkage mapping explained significantly more genetic variance for traits.Our results provide a framework for detecting and understanding the occurrence and inheritance of genomic SV in breeding programs,and support the use of synthetic parents as an important source of novel trait variation.

A synthetic diagnostics platform for microwave imaging diagnostics in tokamaks

Interpreting experimental diagnostics data in tokamaks,while considering non-ideal effects,is challenging due to the complexity of plasmas.To address this challenge,a general synthetic diagnostics(GSD)platform has been established that facilitates microwave imaging reflectometry and electron cyclotron emission imaging.This platform utilizes plasma profiles as input and incorporates the finite-difference time domain,ray tracing and the radiative transfer equation to calculate the propagation of plasma spontaneous radiation and the external electromagnetic field in plasmas.Benchmark tests for classical cases have been conducted to verify the accuracy of every core module in the GSD platform.Finally,2D imaging of a typical electron temperature distribution is reproduced by this platform and the results are consistent with the given real experimental data.This platform also has the potential to be extended to 3D electromagnetic field simulations and other microwave diagnostics such as cross-polarization scattering.

CO_(2)capture costs of chemical looping combustion of biomass:A comparison of natural and synthetic oxygen carrier

Chemical looping combustion has the potential to be an efficient and low-cost technology capable of contributing to the reduction of the atmospheric concentration of CO_(2) in order to reach the 1.5/2°C goal and mitigate climate change.In this process,a metal oxide is used as oxygen carrier in a dual fluidized bed to generate clean CO_(2) via combustion of biomass.Most commonly,natural ores or synthetic materials are used as oxygen carrier whereas both must meet special requirements for the conversion of solid fuels.Synthetic oxygen carriers are characterized by higher reactivity at the expense of higher costs versus the lower-cost natural ores.To determine the viability of both possibilities,a techno-economic comparison of a synthetic material based on manganese,iron,and copper to the natural ore ilmenite was conducted.The synthetic oxygen carrier was characterized and tested in a pilot plant,where high combustion efficiencies up to 98.4%and carbon capture rates up to 98.5%were reached.The techno-economic assessment resulted in CO_(2) capture costs of 75 and 40€/tCO_(2) for the synthetic and natural ore route respectively,whereas a sensitivity analysis showed the high impact of production costs and attrition rates of the synthetic material.The synthetic oxygen carrier could break even with the natural ore in case of lower production costs and attrition rates,which could be reached by adapting the production process and recycling material.By comparison to state-of-the-art technologies,it is demonstrated that both routes are viable and the capture cost of CO_(2) could be reduced by implementing the chemical looping combustion technology.

Plant Nitrogen Metabolism: Balancing Resilience to Nutritional Stress andAbiotic Challenges

Plant growth and resilience to abiotic stresses,such as soil salinity and drought,depend intricately on nitrogen metabolism.This review explores nitrogen’s regulatory role in plant responses to these challenges,unveiling a dynamic interplay between nitrogen availability and abiotic stress.In the context of soil salinity,a nuanced rela-tionship emerges,featuring both antagonistic and synergistic interactions between salinity and nitrogen levels.Salinity-induced chlorophyll depletion in plants can be alleviated by optimal nitrogen supplementation;however,excessive nitrogen can exacerbate salinity stress.We delve into the complexities of this interaction and its agri-cultural implications.Nitrogen,a vital element within essential plant structures like chloroplasts,elicits diverse responses based on its availability.This review comprehensively examines manifestations of nitrogen deficiency and toxicity across various crop types,including cereals,vegetables,legumes,and fruits.Furthermore,we explore the broader consequences of nitrogen products,such as N_(2)O,NO_(2),and ammonia,on human health.Understand-ing the intricate relationship between nitrogen and salinity,especially chloride accumulation in nitrate-fed plants and sodium buildup in ammonium-fed plants,is pivotal for optimizing crop nitrogen management.However,prudent nitrogen use is essential,as overapplication can exacerbate nitrogen-related issues.Nitrogen Use Effi-ciency(NUE)is of paramount importance in addressing salinity challenges and enhancing sustainable crop productivity.Achieving this goal requires advancements in crop varieties with efficient nitrogen utilization,pre-cise timing and placement of nitrogen fertilizer application,and thoughtful nitrogen source selection to mitigate losses,particularly urea-based fertilizer volatilization.This review article delves into the multifaceted world of plant nitrogen metabolism and its pivotal role in enabling plant resilience to nutritional stress and abiotic challenges.It offers insights into future directions for sustainable agriculture.

The 2023 M_(w)6.8 Adassil Earthquake(Chichaoua,Morocco)on a steep reverse fault in the deep crust and its geodynamic implications

The Mw 6.8 Adassil earthquake that occurred in the High Atlas on September 8,2023,was a catastrophic event that provided a rare opportunity to study the mechanics of deep crustal seismicity.This research aimed to decipher the rupture characteristics of the Adassil earthquake by analyzing teleseismic waveform data in conjunction with interferometric synthetic aperture radar(InSAR)observations from both ascending and descending orbits.Our analysis revealed a reverse fault mechanism with a centroid depth of approximately 28 km,exceeding the typical range for crustal earthquakes.This result suggests the presence of cooler temperatures in the lower crust,which facilitates the accumulation of tectonic stress.The earthquake exhibited a steep reverse mechanism,dipping at 70°,accompanied by minor strike-slip motion.Within the geotectonic framework of the High Atlas,known for its volcanic legacy and resulting thermal irregularities,we investigated the potential contributions of these factors to the initiation of the Adassil earthquake.Deep seismicity within the lower crust,away from plate boundaries,calls for extensive research to elucidate its implications for regional seismic hazard assessment.Our findings highlight the critical importance of studying and preparing for significant seismic events in similar geological settings,which would provide valuable insights into regional seismic hazard assessments and geodynamic paradigms.

Synthetic Aperture Positioning: A Review

Obtaining precise position of interested emitters passively has wide applications in both civilian and military fields.Different from traditional parameter measurement and direct position determination(DPD)method,recently a new passive localization method based on synthetic aper-ture technique,named synthetic aperture positioning(SAP),has been proposed.The method com-pensates for the nonlinear phase produced by relative motion between the moving platform and the emitter,achieving coherent summation of intercepted signals.The SAP can obtain high-resolution and high-precision localization results at a low signal-to-noise ratio.This paper summarizes the research progress of SAP,including localization principles,spaceborne applications,and application scope analysis.Besides,the possible future outlook of SAP is considered.

Predictive modeling for postoperative delirium in elderly patients with abdominal malignancies using synthetic minority oversampling technique

BACKGROUND Postoperative delirium,particularly prevalent in elderly patients after abdominal cancer surgery,presents significant challenges in clinical management.AIM To develop a synthetic minority oversampling technique(SMOTE)-based model for predicting postoperative delirium in elderly abdominal cancer patients.METHODS In this retrospective cohort study,we analyzed data from 611 elderly patients who underwent abdominal malignant tumor surgery at our hospital between September 2020 and October 2022.The incidence of postoperative delirium was recorded for 7 d post-surgery.Patients were divided into delirium and non-delirium groups based on the occurrence of postoperative delirium or not.A multivariate logistic regression model was used to identify risk factors and develop a predictive model for postoperative delirium.The SMOTE technique was applied to enhance the model by oversampling the delirium cases.The model’s predictive accuracy was then validated.RESULTS In our study involving 611 elderly patients with abdominal malignant tumors,multivariate logistic regression analysis identified significant risk factors for postoperative delirium.These included the Charlson comorbidity index,American Society of Anesthesiologists classification,history of cerebrovascular disease,surgical duration,perioperative blood transfusion,and postoperative pain score.The incidence rate of postoperative delirium in our study was 22.91%.The original predictive model(P1)exhibited an area under the receiver operating characteristic curve of 0.862.In comparison,the SMOTE-based logistic early warning model(P2),which utilized the SMOTE oversampling algorithm,showed a slightly lower but comparable area under the curve of 0.856,suggesting no significant difference in performance between the two predictive approaches.CONCLUSION This study confirms that the SMOTE-enhanced predictive model for postoperative delirium in elderly abdominal tumor patients shows performance equivalent to that of traditional methods,effectively addressing data imbalance.

Epigenetic silencing schlafen-11 sensitizes esophageal cancer to ATM inhibitor

BACKGROUND Targeting DNA damage response(DDR)pathway is a cutting-edge strategy.It has been reported that Schlafen-11(SLFN11)contributes to increase chemosensitivity by participating in DDR.However,the detailed mechanism is unclear.AIM To investigate the role of SLFN11 in DDR and the application of synthetic lethal in esophageal cancer with SLFN11 defects.METHODS To reach the purpose,eight esophageal squamous carcinoma cell lines,142 esophageal dysplasia(ED)and 1007 primary esophageal squamous cell carcinoma(ESCC)samples and various techniques were utilized,including methylationspecific polymerase chain reaction,CRISPR/Cas9 technique,Western blot,colony formation assay,and xenograft mouse model.RESULTS Methylation of SLFN11 was exhibited in 9.15%of(13/142)ED and 25.62%of primary(258/1007)ESCC cases,and its expression was regulated by promoter region methylation.SLFN11 methylation was significantly associated with tumor differentiation and tumor size(both P<0.05).However,no significant associations were observed between promoter region methylation and age,gender,smoking,alcohol consumption,TNM stage,or lymph node metastasis.Utilizing DNA damaged model induced by low dose cisplatin,SLFN11 was found to activate non-homologous end-joining and ATR/CHK1 signaling pathways,while inhibiting the ATM/CHK2 signaling pathway.Epigenetic silencing of SLFN11 was found to sensitize the ESCC cells to ATM inhibitor(AZD0156),both in vitro and in vivo.CONCLUSION SLFN11 is frequently methylated in human ESCC.Methylation of SLFN11 is sensitive marker of ATM inhibitor in ESCC.

An empirical method for joint inversion of wave and wind parameters based on SAR and wave spectrometer data

Synthetic aperture radar(SAR)and wave spectrometers,crucial in microwave remote sensing,play an essential role in monitoring sea surface wind and wave conditions.However,they face inherent limitations in observing sea surface phenomena.SAR systems,for instance,are hindered by an azimuth cut-off phenomenon in sea surface wind field observation.Wave spectrometers,while unaffected by the azimuth cutoff phenomenon,struggle with low azimuth resolution,impacting the capture of detailed wave and wind field data.This study utilizes SAR and surface wave investigation and monitoring(SWIM)data to initially extract key feature parameters,which are then prioritized using the extreme gradient boosting(XGBoost)algorithm.The research further addresses feature collinearity through a combined analysis of feature importance and correlation,leading to the development of an inversion model for wave and wind parameters based on XGBoost.A comparative analysis of this model with ERA5 reanalysis and buoy data for of significant wave height,mean wave period,wind direction,and wind speed reveals root mean square errors of 0.212 m,0.525 s,27.446°,and 1.092 m/s,compared to 0.314 m,0.888 s,27.698°,and 1.315 m/s from buoy data,respectively.These results demonstrate the model’s effective retrieval of wave and wind parameters.Finally,the model,incorporating altimeter and scatterometer data,is evaluated against SAR/SWIM single and dual payload inversion methods across different wind speeds.This comparison highlights the model’s superior inversion accuracy over other methods.

SAR regional all-azimuth observation orbit design for target 3D reconstruction

Three-dimensional(3D) synthetic aperture radar(SAR)extends the conventional 2D images into 3D features by several acquisitions in different aspects. Compared with 3D techniques via multiple observations in elevation, e.g. SAR interferometry(InSAR) and SAR tomography(TomoSAR), holographic SAR can retrieve 3D structure by observations in azimuth. This paper focuses on designing a novel type of orbit to achieve SAR regional all-azimuth observation(AAO) for embedded targets detection and holographic 3D reconstruction. The ground tracks of the AAO orbit separate the earth surface into grids. Target in these grids can be accessed with an azimuth angle span of360°, which is similar to the flight path of airborne circular SAR(CSAR). Inspired from the successive coverage orbits of optical sensors, several optimizations are made in the proposed method to ensure favorable grazing angles, the performance of 3D reconstruction, and long-term supervision for SAR sensors. Simulation experiments show the regional AAO can be completed within five hours. In addition, a second AAO of the same area can be duplicated in two days. Finally, an airborne SAR data process result is presented to illustrate the significance of AAO in 3D reconstruction.

An envelope-based machine learning workflow for locating earthquakes in the southern Sichuan Basin

The development of machine learning technology enables more robust real-time earthquake monitoring through automated implementations. However, the application of machine learning to earthquake location problems faces challenges in regions with limited available training data. To address the issues of sparse event distribution and inaccurate ground truth in historical seismic datasets, we expand the training dataset by using a large number of synthetic envelopes that closely resemble real data and build an earthquake location model named ENVloc. We propose an envelope-based machine learning workflow for simultaneously determining earthquake location and origin time. The method eliminates the need for phase picking and avoids the accumulation of location errors resulting from inaccurate picking results. In practical application, ENVloc is applied to several data intercepted at different starting points. We take the starting point of the time window corresponding to the highest prediction probability value as the origin time and save the predicted result as the earthquake location. We apply ENVloc to observed data acquired in the southern Sichuan Basin, China, between September 2018 and March 2019. The results show that the average difference with the catalog in latitude, longitude, depth, and origin time is 0.02°,0.02°, 2 km, and 1.25 s, respectively. These suggest that our envelope-based method provides an efficient and robust way to locate earthquakes without phase picking, and can be used in earthquake monitoring in near-real time.