Spinal and bulbar muscular atrophy is a neurodegenerative disease caused by extended CAG trinucleotide repeats in the androgen receptor gene,which encodes a ligand-dependent transcription facto r.The mutant androgen r...Spinal and bulbar muscular atrophy is a neurodegenerative disease caused by extended CAG trinucleotide repeats in the androgen receptor gene,which encodes a ligand-dependent transcription facto r.The mutant androgen receptor protein,characterized by polyglutamine expansion,is prone to misfolding and forms aggregates in both the nucleus and cytoplasm in the brain in spinal and bulbar muscular atrophy patients.These aggregates alter protein-protein interactions and compromise transcriptional activity.In this study,we reported that in both cultured N2a cells and mouse brain,mutant androgen receptor with polyglutamine expansion causes reduced expression of mesencephalic astrocyte-de rived neurotrophic factor.Overexpressio n of mesencephalic astrocyte-derived neurotrophic factor amelio rated the neurotoxicity of mutant androgen receptor through the inhibition of mutant androgen receptor aggregation.Conversely.knocking down endogenous mesencephalic astrocyte-derived neurotrophic factor in the mouse brain exacerbated neuronal damage and mutant androgen receptor aggregation.Our findings suggest that inhibition of mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor is a potential mechanism underlying neurodegeneration in spinal and bulbar muscular atrophy.展开更多
Microglial functions are linked to Ca2+signaling,with endoplasmic reticulum(ER)calcium stores playing a crucial role.Microglial abnormality is a hallmark of Alzheimer’s disease(AD),but how ER Ca2+receptors regulate m...Microglial functions are linked to Ca2+signaling,with endoplasmic reticulum(ER)calcium stores playing a crucial role.Microglial abnormality is a hallmark of Alzheimer’s disease(AD),but how ER Ca2+receptors regulate microglial functions under physiological and AD conditions remains unclear.We found reduced ryanodine receptor 2(Ryr2)expression in microglia from an AD mouse model.Modulation of RyR2 using S107,a RyR-Calstabin stabilizer,blunted spontaneous Ca2+transients in controls and normalized Ca2+transients in AD mice.S107 enhanced ATP-induced migration and phagocytosis while reducing ramification in control microglia;however,these effects were absent in AD microglia.Our findings indicate that RyR2 stabilization promotes an activation state shift in control microglia,a mechanism impaired in AD.These results highlight the role of ER Ca2+receptors in both homeostatic and AD microglia,providing insights into microglial Ca2+malfunctions in AD.展开更多
Myasthenia gravis is a chronic autoimmune disorder that affects the neuromuscular junction leading to fluctuating skeletal muscle fatigability. The majority of myasthenia gravis patients have detectable antibodies in ...Myasthenia gravis is a chronic autoimmune disorder that affects the neuromuscular junction leading to fluctuating skeletal muscle fatigability. The majority of myasthenia gravis patients have detectable antibodies in their serum, targeting acetylcholine receptor, muscle-specific kinase, or related proteins. Current treatment for myasthenia gravis involves symptomatic therapy, immunosuppressive drugs such as corticosteroids, azathioprine, and mycophenolate mofetil, and thymectomy, which is primarily indicated in patients with thymoma or thymic hyperplasia. However, this condition continues to pose significant challenges including an unpredictable and variable disease progression, differing response to individual therapies, and substantial longterm side effects associated with standard treatments(including an increased risk of infections, osteoporosis, and diabetes), underscoring the necessity for a more personalized approach to treatment. Furthermore, about fifteen percent of patients, called “refractory myasthenia gravis patients”, do not respond adequately to standard therapies. In this context, the introduction of molecular therapies has marked a significant advance in myasthenia gravis management. Advances in understanding myasthenia gravis pathogenesis, especially the role of pathogenic antibodies, have driven the development of these biological drugs, which offer more selective, rapid, and safer alternatives to traditional immunosuppressants. This review aims to provide a comprehensive overview of emerging therapeutic strategies targeting specific immune pathways in myasthenia gravis, with a particular focus on preclinical evidence, therapeutic rationale, and clinical translation of B-cell depletion therapies, neonatal Fc receptor inhibitors, and complement inhibitors.展开更多
The accuracy of genomic annotation is crucial for subsequent functional investigations;however,computational protocols used in high-throughput annotation of open reading frames(ORFs)can introduce inconsistencies.These...The accuracy of genomic annotation is crucial for subsequent functional investigations;however,computational protocols used in high-throughput annotation of open reading frames(ORFs)can introduce inconsistencies.These inconsistencies,which lead to non-uniform extension or truncation of sequence ends,pose challenges for downstream analyses.Existing strategies to rectify these inconsistencies are time-consuming and labor-intensive,lacking specific approaches.To address this gap,we developed to GC,a tool that integrates genomic annotation with RNA-seq datasets to rectify annotation inconsistencies.Using to GC,we achieved an accuracy of nearly 100%accuracy in correcting inconsistencies in published Phytophthora sojae ORFs.We applied this innovative pipeline to the GPCR-bigrams gene family,which was predicted to have 42 members in the P.sojae genome but lacked experimental validation.By employing to GC,we identified 32 GPCR-bigram ORFs with inconsistencies between previous annotations and to GC-corrected sequences.Notably,among these were 5 genes(GPCR-TKL9,GPCR-TKL15,GPCR-PDE3,GPCR-AC3,and GPCR-AC4)showed substantial inconsistencies.Experimental gene annotation confirmed the effectiveness of to GC,as sequences obtained through cloning matched those annotated by to GC.Importantly,we discovered two novel GPCRs(GPCR-AC3 and GPCR-AC4),which were previously mispredicted as a single gene.CRISPR/Cas9-mediated knockout experiments revealed the involvement of GPCR-AC4 but not GPCR-AC3 in oospore production,further confirming their status as two separate genes.In addition to P.sojae,the reliability of the to GC pipeline in Phytophthora capsici and Pythium ultimum further emphasizes the robustness of this pipeline.Our findings highlight the utility of to GC for reliable gene model correction,facilitating investigations into biological functions and offering potential applications in diverse species analyses.展开更多
BACKGROUND Chronic pancreatitis(CP)accompanied with persistent abdominal pain represents a major clinical challenge for the symptom management in patients.Although with clear involvement of neuropathy,the detailed mec...BACKGROUND Chronic pancreatitis(CP)accompanied with persistent abdominal pain represents a major clinical challenge for the symptom management in patients.Although with clear involvement of neuropathy,the detailed mechanisms underlying pain hypersensitivity associated with CP are not totally clear.The endothelin system has been reported to contribute to chronic pain and chronic inflammatory settings,and is a potential therapeutic target for the treatment of chronic pain.AIM To evaluate the role of nociceptor-specific endothelin A receptor(ETAR)in pain hypersensitivity in a CP mouse model and its potential contributing mechanisms.METHODS Oral gavage delivery of dibutyltin dichloride(DBTC)was used to induce CP in mice.A conditional knockout(CKO)strain which specifically delete ETAR in dorsal root ganglion(DRG)nociceptive neurons was generated.Abdominal pain hypersensitivity associated with CP and other behaviors were evaluated.The size of mouse gallbladder was measured and pancreatic histopathology was examined to validate the CP model.Calcitonin gene-related peptide expression and immune cells in the innervated DRGs and spinal cord were also examined.Calcium imaging in dissociated DRG neurons was performed to investigate the excitability of affected nociceptive neurons.RESULTS Specific deletion of endothelin receptor type A gene in nociceptive DRG neurons did not affect basal abdominal thermal and mechanical pain threshold in mice.Abdominal mechanical pain hypersensitivity was persistent in DBTC-treated WT mice but was significantly reduced in DBTC-treated CKO mice.DBTC treatment did not affect mouse nociceptive responses to heat and cold stimuli,as well as motor functions and anxiety-like behaviors of mice.DBTC treatment induced severe pancreatic inflammation and obvious gallbladder enlargement in wild type(WT)mice,but less in CKO mice.DBTC-induced increase of calcitonin gene-related peptide-and induction of brown adipocytes 1-positive signals in the DRG and spinal cord in WT mice were remarkably attenuated in CKO mice.DRG neurons from CKO mice exhibited less excitability and sensitivity in response to endothelin-1 exposure than those from WT mice.CONCLUSION DBTC intragastric administration in mice produced a convenient and reliable animal model for studying abdominal pain associated with CP.ETAR-dependent endothelin signaling in nociceptors is important for the development of persistent abdominal mechanical hypersensitivity in mice.展开更多
Background:In recent decades,the global incidence of dengue fever has been stead-ily increasing,with continuous geographical expansion.Researchers have successfully modeled most clinical symptoms of human dengue fever...Background:In recent decades,the global incidence of dengue fever has been stead-ily increasing,with continuous geographical expansion.Researchers have successfully modeled most clinical symptoms of human dengue fever using interferon type I(IFN-I)or combined IFN-I/II receptor knockout mice infected with dengue virus(DENV).However,this model requires further optimization to better support related studies.Methods:This study aimed to establish a stable dengue infection model by evaluating the effects of different genetic backgrounds and injection routes on DENV infection in interferon receptor knockout mice.We first infected various strains of interferon receptor-deficient mice with DENV and compared their susceptibility based on clini-cal symptoms,viremia levels,organ indices,histopathological findings,and vascular leakage markers.Subsequently,we selected the most susceptible strain to further investigate the impact of different injection methods on infection outcomes.Results:We found that BALB/c background mice with type 1 interferon recep-tor knockout(IFNAR)had the most obvious symptoms.Subsequently,we selected IFNAR−/−BALB/c mice to further explore the effects of different injection methods on dengue virus infection.The results showed that the intraperitoneal injection group had the most severe clinical symptoms,the longest duration of viremia,and the most obvious degree of organ damage.Conclusion:Through systematic screening and optimization,we established a robust animal model of dengue virus infection via intraperitoneal injection in IFNAR−/−BALB/c mice.This model offers a valuable tool for future dengue research.展开更多
Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLM...Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.展开更多
In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asy...In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.展开更多
In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation ...In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade.展开更多
In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and cha...In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.展开更多
Brassinosteroids(BRs)are essential phytohormones that broadly regulate plant growth,development,and adaptation to biotic and abiotic stresses.In Arabidopsis,apoplastic BR molecules are perceived by a plasma membrane-l...Brassinosteroids(BRs)are essential phytohormones that broadly regulate plant growth,development,and adaptation to biotic and abiotic stresses.In Arabidopsis,apoplastic BR molecules are perceived by a plasma membrane-localized receptor complex comprising the ligand-binding receptor BRI1 and the co-receptor BAK1.While negative regulators of the BR receptor complex,such as BKI1,BIR3,and PUB12/13,have been well characterized,how BRI1 and BAK1 are positively modulated in the BR pathway remains largely unknown.In this study,a genetic screen involving overexpression of RLP genes in the bak1-3 bkk1-1 double mutant reveals that enhanced RLP51 expression partially suppresses the BR-deficient phenotypes of bak1-3 bkk1-1.RLP51 overexpression also partially rescues the weak bri1 mutant allele,bri1-301.Although the rlp51 single mutant exhibits wild-type-like phenotypes,it enhances BR-defective phenotypes in bri1-301 and bak1 serk1 mutants.RLP51 is next found to interact with both BRI1 and BAK1 without affecting BRI1–BAK1 interaction.Critically,co-expression of RLP51 with BRI1 or BAK1 significantly increases BRI1 and BAK1 protein abundances.RLP51 appears to promote protein synthesis rather than stabilize BRI1 and BAK1 proteins.Thus,our study identifies RLP51 as a positive regulator of BR signaling that enhances the protein levels of BRI1 and BAK1.展开更多
Background:Large language models(LLMs)have shown considerable promise in supporting clinical decision-making.However,their adoption and evaluation in dermatology remains limited.This study aimed to explore the prefere...Background:Large language models(LLMs)have shown considerable promise in supporting clinical decision-making.However,their adoption and evaluation in dermatology remains limited.This study aimed to explore the preferences of Chinese dermatologists regarding LLM-generated responses in clinical psoriasis scenarios and to assess how they prioritize key quality dimensions,including accuracy,traceability,and logicality.Methods:A cross-sectional,web-based survey was conducted between December 25,2024,and January 22,2025,following the Checklist for Reporting Results of Internet E-Surveys guidelines.A total of 1247 valid responses were collected from practicing dermatologists across 33 of China's provincial-level administrative divisions.Participants evaluated responses to five categories of clinical questions(etiology,clinical presentation,differential diagnosis,treatment,and case study)generated by five LLMs:ChatGPT-4o,Kimi.ai,Doubao,ZuoYiGPT,and Lingyi-agent.Statistical associations between participant characteristics and model preferences were examined using chi-square tests.Results:ChatGPT-4o(Model 1)emerged as the most preferred model across all clinical tasks,consistently receiving the highest number of votes in case study(n=740),clinical presentation(n=666),differential diagnosis(n=707),etiology(n=602),and treatment(n=656).Significant variation in model preference by professional title was observed only for the differential diagnosis task(χ^(2)=21.13,df=12,p=0.0485),while no significant differences were found across hospital tiers(p>0.05).In terms of evaluation dimensions,accuracy was most frequently rated as“very important”(n=635).A significant association existed between hospital tier and the most valued dimension(χ^(2)=27.667,df=9,p=0.0011),with dermatologists in primary hospitals prioritizing traceability more than their peers in higher-tier hospitals.No significant associations were found across professional titles(p=0.127).Conclusions:Chinese dermatologists suggest a strong preference for ChatGPT-4o over domestic LLMs in psoriasis-related clinical tasks.While accuracy remains the primary criterion,traceability and logicality are also critical,particularly for clinicians in lower-tier hospitals.These findings suggest that future clinical LLMs should prioritize not only content accuracy but also source transparency and structural clarity to meet the diverse needs of different clinical settings.展开更多
The Reynolds-averaged Navier-Stokes(RANS)technique enables critical engineering predictions and is widely adopted.However,since this iterative computation relies on the fixed-point iteration,it may converge to unexpec...The Reynolds-averaged Navier-Stokes(RANS)technique enables critical engineering predictions and is widely adopted.However,since this iterative computation relies on the fixed-point iteration,it may converge to unexpected non-physical phase points in practice.We conduct an analysis on the phase-space characteristics and the fixed-point theory underlying the k-ε turbulence model,and employ the classical Kolmogorov flow as a framework,leveraging its direct numerical simulation(DNS)data to construct a one-dimensional(1D)system under periodic/fixed boundary conditions.The RANS results demonstrate that under periodic boundary conditions,the k-ε model exhibits only a unique trivial fixed point,with asymptotes capturing the phase portraits.The stability of this trivial fixed point is determined by a mathematically derived stability phase diagram,indicating the fact that the k-ε model will never converge to correct values under periodic conditions.In contrast,under fixed boundary conditions,the model can yield a stable non-trivial fixed point.The evolutionary mechanisms and their relationship with boundary condition settings systematically explain the inherent limitations of the k-ε model,i.e.,its deficiency in computing the flow field under periodic boundary conditions and sensitivity to boundary-value specifications under fixed boundary conditions.These conclusions are finally validated with the open-source code OpenFOAM.展开更多
Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is empl...Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.展开更多
Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interact...Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interactions to predict future items of interest.However,many current methods rely on unique user and item IDs,limiting their ability to represent users and items effectively,especially in zero-shot learning scenarios where training data is scarce.With the rapid development of Large Language Models(LLMs),researchers are exploring their potential to enhance recommendation systems.However,there is a semantic gap between the linguistic semantics of LLMs and the collaborative semantics of recommendation systems,where items are typically indexed by IDs.Moreover,most research focuses on item representations,neglecting personalized user modeling.To address these issues,we propose a sequential recommendation framework using LLMs,called CIT-Rec,a model that integrates Collaborative semantics for user representation and Image and Text information for item representation to enhance Recommendations.Specifically,by aligning intuitive image information with text containing semantic features,we can more accurately represent items,improving item representation quality.We focus not only on item representations but also on user representations.To more precisely capture users’personalized preferences,we use traditional sequential recommendation models to train on users’historical interaction data,effectively capturing behavioral patterns.Finally,by combining LLMs and traditional sequential recommendation models,we allow the LLM to understand linguistic semantics while capturing collaborative semantics.Extensive evaluations on real-world datasets show that our model outperforms baseline methods,effectively combining user interaction history with item visual and textual modalities to provide personalized recommendations.展开更多
The National Geophysical Data Center(NGDC)of the United States has collected aeromagnetic data for input into a series of geomagnetic models to improve model resolution;however,in the Tibetan Plateau region,ground-bas...The National Geophysical Data Center(NGDC)of the United States has collected aeromagnetic data for input into a series of geomagnetic models to improve model resolution;however,in the Tibetan Plateau region,ground-based observations remain insufficient to clearly reflect the characteristics of the region’s lithospheric magnetism.In this study,we evaluate the lithospheric magnetism of the Tibetan Plateau by using a 3D surface spline model based on observations from>200 newly constructed repeat stations(portable stations)to determine the spatial distribution of plateau geomagnetism,as well as its correlation with the tectonic features of the region.We analyze the relationships between M≥5 earthquakes and lithospheric magnetic field variations on the Tibetan Plateau and identify regions susceptible to strong earthquakes.We compare the geomagnetic results with those from an enhanced magnetic model(EMM2015)developed by the NGDC and provide insights into improving lithospheric magnetic field calculations in the Tibetan Plateau region.Further research reveals that these magnetic anomalies exhibit distinct differences from the magnetic-seismic correlation mechanisms observed in other tectonic settings;here,they are governed primarily by the combined effects of compressional magnetism,thermal magnetism,and deep thermal stress.This study provides new evidence of geomagnetic anomalies on the Tibetan Plateau,interprets them physically,and demonstrates their potential for identifying seismic hazard zones on the Plateau.展开更多
(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbi...(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.展开更多
Effective management of mining areas in the Luo River Basin,located in the eastern Qinling Mountains,is vital for the integrated protection and restoration needed to support the high-quality development of the Yellow ...Effective management of mining areas in the Luo River Basin,located in the eastern Qinling Mountains,is vital for the integrated protection and restoration needed to support the high-quality development of the Yellow River Basin.Using the‘cupball'model,this study analyzes the limiting factors and restoration characteristics across four mining areas and proposes a conceptual model for selecting appropriate restoration approaches.A second conceptual model is then introduced to address regional development needs,incorporating ecological conservation,safety protection,and people's wellbeing.The applicability of the integrated model selection framework is demonstrated through a case study on the south bank of the Qinglongjian River.The results indicate that:(1)The key limiting factors are similar across cases,but the degree of ecological degradation varies.(2)Mildly degraded areas are represented by a shallower and narrower‘cup',where natural recovery is the preferred approach,whereas moderately and severely degraded systems call for assisted regeneration and ecological reconstruction,respectively.(3)When the restoration models determined based on limiting factors and development needs are consistent,the model is directly applicable;if they differ,the option involving less artificial intervention is preferred;(4)Monitoring of the restored mining area on the Qinglongjian River's south bank confirms significant improvements in soil erosion control and vegetation coverage.This study provides a transferable methodology for balancing resource extraction with ecosystem conservation,offering practical insights for other ecologically vulnerable mining regions.展开更多
Accurate forecasting of tropical cyclone(TC)tracks and intensities is essential.Although the TianXing large weather model,a six-hourly forecasting model surpassing operational forecasts,exhibits superior performance,i...Accurate forecasting of tropical cyclone(TC)tracks and intensities is essential.Although the TianXing large weather model,a six-hourly forecasting model surpassing operational forecasts,exhibits superior performance,its TC forecasts still require enhancement.Prediction errors persist due to biases in the training data and smoothing effects in data-driven methods.To address this,we introduce CycloneBCNet,a deep-learning model designed to correct TianXing’s TC forecast biases by leveraging spatial and temporal data.CycloneBCNet utilizes the SimVP(simpler yet better video prediction)framework with spatial attention to highlight cyclone core regions in forecast fields.It also incorporates TC trend information(center position,maximum wind speed,and minimum sea level pressure)via an LSTM(long short-term memory)module.These TC vectors are derived from post-processed TianXing forecasts.By fusing features from forecast fields and TC vectors,CycloneBCNet corrects biases across multiple lead times.At a 96-h lead time,the track error reduces from 162.4 to 86.4 km,the wind speed error from 17.2 to 6.69 m s^(-1),and the pressure error from 22.2 to 9.36 hPa.Interpretability analysis shows that CycloneBCNet adjusts its attention across forecast lead times.Intensity corrections prioritize inner-core dynamics,particularly the eye and eyewall,while track corrections shift from lower-level variables and the cyclone’s core to broader environmental factors and mid-to upper-level features as the forecast duration increases.These findings demonstrate that CycloneBCNet effectively captures key TC dynamics consistent with meteorological principles,including the dominance of near-surface conditions for intensity and the increasing influence of steering currents on track prediction.展开更多
Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(...Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].展开更多
基金supported by the National Key R&D Program of China,No.2021YFA0805200(to SY)the National Natural Science Foundation of China,No.31970954(to SY)two grants from the Department of Science and Technology of Guangdong Province,Nos.2021ZT09Y007,2020B121201006(both to XJL)。
文摘Spinal and bulbar muscular atrophy is a neurodegenerative disease caused by extended CAG trinucleotide repeats in the androgen receptor gene,which encodes a ligand-dependent transcription facto r.The mutant androgen receptor protein,characterized by polyglutamine expansion,is prone to misfolding and forms aggregates in both the nucleus and cytoplasm in the brain in spinal and bulbar muscular atrophy patients.These aggregates alter protein-protein interactions and compromise transcriptional activity.In this study,we reported that in both cultured N2a cells and mouse brain,mutant androgen receptor with polyglutamine expansion causes reduced expression of mesencephalic astrocyte-de rived neurotrophic factor.Overexpressio n of mesencephalic astrocyte-derived neurotrophic factor amelio rated the neurotoxicity of mutant androgen receptor through the inhibition of mutant androgen receptor aggregation.Conversely.knocking down endogenous mesencephalic astrocyte-derived neurotrophic factor in the mouse brain exacerbated neuronal damage and mutant androgen receptor aggregation.Our findings suggest that inhibition of mesencephalic astrocyte-derived neurotrophic factor expression by mutant androgen receptor is a potential mechanism underlying neurodegeneration in spinal and bulbar muscular atrophy.
基金supported by grants from the Guangdong Basic and Applied Basic Research Foundation(2021A1515110912)Guangdong Provincial Key Laboratory of Brain Connectome and Behavior(2017B030301017)Shenzhen Key Laboratory of Translational Research for Brain Diseases(ZDSYS20200828154800001).
文摘Microglial functions are linked to Ca2+signaling,with endoplasmic reticulum(ER)calcium stores playing a crucial role.Microglial abnormality is a hallmark of Alzheimer’s disease(AD),but how ER Ca2+receptors regulate microglial functions under physiological and AD conditions remains unclear.We found reduced ryanodine receptor 2(Ryr2)expression in microglia from an AD mouse model.Modulation of RyR2 using S107,a RyR-Calstabin stabilizer,blunted spontaneous Ca2+transients in controls and normalized Ca2+transients in AD mice.S107 enhanced ATP-induced migration and phagocytosis while reducing ramification in control microglia;however,these effects were absent in AD microglia.Our findings indicate that RyR2 stabilization promotes an activation state shift in control microglia,a mechanism impaired in AD.These results highlight the role of ER Ca2+receptors in both homeostatic and AD microglia,providing insights into microglial Ca2+malfunctions in AD.
文摘Myasthenia gravis is a chronic autoimmune disorder that affects the neuromuscular junction leading to fluctuating skeletal muscle fatigability. The majority of myasthenia gravis patients have detectable antibodies in their serum, targeting acetylcholine receptor, muscle-specific kinase, or related proteins. Current treatment for myasthenia gravis involves symptomatic therapy, immunosuppressive drugs such as corticosteroids, azathioprine, and mycophenolate mofetil, and thymectomy, which is primarily indicated in patients with thymoma or thymic hyperplasia. However, this condition continues to pose significant challenges including an unpredictable and variable disease progression, differing response to individual therapies, and substantial longterm side effects associated with standard treatments(including an increased risk of infections, osteoporosis, and diabetes), underscoring the necessity for a more personalized approach to treatment. Furthermore, about fifteen percent of patients, called “refractory myasthenia gravis patients”, do not respond adequately to standard therapies. In this context, the introduction of molecular therapies has marked a significant advance in myasthenia gravis management. Advances in understanding myasthenia gravis pathogenesis, especially the role of pathogenic antibodies, have driven the development of these biological drugs, which offer more selective, rapid, and safer alternatives to traditional immunosuppressants. This review aims to provide a comprehensive overview of emerging therapeutic strategies targeting specific immune pathways in myasthenia gravis, with a particular focus on preclinical evidence, therapeutic rationale, and clinical translation of B-cell depletion therapies, neonatal Fc receptor inhibitors, and complement inhibitors.
基金supported by the grants to Min Qiu and Ming Wang from the National Natural Science Foundation of China(32100160 and 32100044)the grants to Ming Wang from the Jiangsu“Innovative and Entrepreneurial Talent”Program,China(JSSCRC2021510)the grants to Yuanchao Wang from the Chinese Modern Agricultural Industry Technology System(CARS-004-PS14)。
文摘The accuracy of genomic annotation is crucial for subsequent functional investigations;however,computational protocols used in high-throughput annotation of open reading frames(ORFs)can introduce inconsistencies.These inconsistencies,which lead to non-uniform extension or truncation of sequence ends,pose challenges for downstream analyses.Existing strategies to rectify these inconsistencies are time-consuming and labor-intensive,lacking specific approaches.To address this gap,we developed to GC,a tool that integrates genomic annotation with RNA-seq datasets to rectify annotation inconsistencies.Using to GC,we achieved an accuracy of nearly 100%accuracy in correcting inconsistencies in published Phytophthora sojae ORFs.We applied this innovative pipeline to the GPCR-bigrams gene family,which was predicted to have 42 members in the P.sojae genome but lacked experimental validation.By employing to GC,we identified 32 GPCR-bigram ORFs with inconsistencies between previous annotations and to GC-corrected sequences.Notably,among these were 5 genes(GPCR-TKL9,GPCR-TKL15,GPCR-PDE3,GPCR-AC3,and GPCR-AC4)showed substantial inconsistencies.Experimental gene annotation confirmed the effectiveness of to GC,as sequences obtained through cloning matched those annotated by to GC.Importantly,we discovered two novel GPCRs(GPCR-AC3 and GPCR-AC4),which were previously mispredicted as a single gene.CRISPR/Cas9-mediated knockout experiments revealed the involvement of GPCR-AC4 but not GPCR-AC3 in oospore production,further confirming their status as two separate genes.In addition to P.sojae,the reliability of the to GC pipeline in Phytophthora capsici and Pythium ultimum further emphasizes the robustness of this pipeline.Our findings highlight the utility of to GC for reliable gene model correction,facilitating investigations into biological functions and offering potential applications in diverse species analyses.
基金Supported by Hansoh Foundation of Lianyungang,No.QN1913.
文摘BACKGROUND Chronic pancreatitis(CP)accompanied with persistent abdominal pain represents a major clinical challenge for the symptom management in patients.Although with clear involvement of neuropathy,the detailed mechanisms underlying pain hypersensitivity associated with CP are not totally clear.The endothelin system has been reported to contribute to chronic pain and chronic inflammatory settings,and is a potential therapeutic target for the treatment of chronic pain.AIM To evaluate the role of nociceptor-specific endothelin A receptor(ETAR)in pain hypersensitivity in a CP mouse model and its potential contributing mechanisms.METHODS Oral gavage delivery of dibutyltin dichloride(DBTC)was used to induce CP in mice.A conditional knockout(CKO)strain which specifically delete ETAR in dorsal root ganglion(DRG)nociceptive neurons was generated.Abdominal pain hypersensitivity associated with CP and other behaviors were evaluated.The size of mouse gallbladder was measured and pancreatic histopathology was examined to validate the CP model.Calcitonin gene-related peptide expression and immune cells in the innervated DRGs and spinal cord were also examined.Calcium imaging in dissociated DRG neurons was performed to investigate the excitability of affected nociceptive neurons.RESULTS Specific deletion of endothelin receptor type A gene in nociceptive DRG neurons did not affect basal abdominal thermal and mechanical pain threshold in mice.Abdominal mechanical pain hypersensitivity was persistent in DBTC-treated WT mice but was significantly reduced in DBTC-treated CKO mice.DBTC treatment did not affect mouse nociceptive responses to heat and cold stimuli,as well as motor functions and anxiety-like behaviors of mice.DBTC treatment induced severe pancreatic inflammation and obvious gallbladder enlargement in wild type(WT)mice,but less in CKO mice.DBTC-induced increase of calcitonin gene-related peptide-and induction of brown adipocytes 1-positive signals in the DRG and spinal cord in WT mice were remarkably attenuated in CKO mice.DRG neurons from CKO mice exhibited less excitability and sensitivity in response to endothelin-1 exposure than those from WT mice.CONCLUSION DBTC intragastric administration in mice produced a convenient and reliable animal model for studying abdominal pain associated with CP.ETAR-dependent endothelin signaling in nociceptors is important for the development of persistent abdominal mechanical hypersensitivity in mice.
基金Guangdong Province Medical Research Fund Project,Grant/Award Number:B2024112The Scientific Research Special Project of the Joint Construction Project of High-level Hospitals between Guangzhou University of Chinese Medicine and the Scientific Research Fund Project,Grant/Award Number:GZYZS2024G09+2 种基金Special Project of the Research Platform of Guangdong Provincial Department of Traditional Chinese Medicine,Grant/Award Number:20254040the Project of the Incubation Program for the Science and Technology Development of Chinese Medicine Guangdong Laboratory/Hengqin Laboratory,Grant/Award Number:HQL2024PZ043Guangdong Province Natural Science Foundation-Guangzhou-South China Joint Youth Fund Project,Grant/Award Number:2023A1515110849。
文摘Background:In recent decades,the global incidence of dengue fever has been stead-ily increasing,with continuous geographical expansion.Researchers have successfully modeled most clinical symptoms of human dengue fever using interferon type I(IFN-I)or combined IFN-I/II receptor knockout mice infected with dengue virus(DENV).However,this model requires further optimization to better support related studies.Methods:This study aimed to establish a stable dengue infection model by evaluating the effects of different genetic backgrounds and injection routes on DENV infection in interferon receptor knockout mice.We first infected various strains of interferon receptor-deficient mice with DENV and compared their susceptibility based on clini-cal symptoms,viremia levels,organ indices,histopathological findings,and vascular leakage markers.Subsequently,we selected the most susceptible strain to further investigate the impact of different injection methods on infection outcomes.Results:We found that BALB/c background mice with type 1 interferon recep-tor knockout(IFNAR)had the most obvious symptoms.Subsequently,we selected IFNAR−/−BALB/c mice to further explore the effects of different injection methods on dengue virus infection.The results showed that the intraperitoneal injection group had the most severe clinical symptoms,the longest duration of viremia,and the most obvious degree of organ damage.Conclusion:Through systematic screening and optimization,we established a robust animal model of dengue virus infection via intraperitoneal injection in IFNAR−/−BALB/c mice.This model offers a valuable tool for future dengue research.
文摘Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.
基金Supported by the National Natural Science Foundation of China(12261018)Universities Key Laboratory of Mathematical Modeling and Data Mining in Guizhou Province(2023013)。
文摘In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.
文摘In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade.
基金the World Climate Research Programme(WCRP),Climate Variability and Predictability(CLIVAR),and Global Energy and Water Exchanges(GEWEX)for facilitating the coordination of African monsoon researchsupport from the Center for Earth System Modeling,Analysis,and Data at the Pennsylvania State Universitythe support of the Office of Science of the U.S.Department of Energy Biological and Environmental Research as part of the Regional&Global Model Analysis(RGMA)program area。
文摘In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.
基金supported by the National Natural Science Foundation of China(32370295 and 32170280 to K.H.)Foundation of Science and Technology of Gansu Province(22ZD6NA049)+3 种基金the Fundamental Research Funds for the Central Universities(lzujbky-2021-kb05 to Y.F.and lzujbky-2023-kb05 to P.L.)the Science and Technology Department of Gansu Province(24JRRA392 to K.H.and 23JRRA1132 to C.X.)China Postdoctoral Science Foundation(2024M751259 and GZB20240285 to B.L.)Science and Technology Program of Gansu Province(25JRRA718 to B.L.).
文摘Brassinosteroids(BRs)are essential phytohormones that broadly regulate plant growth,development,and adaptation to biotic and abiotic stresses.In Arabidopsis,apoplastic BR molecules are perceived by a plasma membrane-localized receptor complex comprising the ligand-binding receptor BRI1 and the co-receptor BAK1.While negative regulators of the BR receptor complex,such as BKI1,BIR3,and PUB12/13,have been well characterized,how BRI1 and BAK1 are positively modulated in the BR pathway remains largely unknown.In this study,a genetic screen involving overexpression of RLP genes in the bak1-3 bkk1-1 double mutant reveals that enhanced RLP51 expression partially suppresses the BR-deficient phenotypes of bak1-3 bkk1-1.RLP51 overexpression also partially rescues the weak bri1 mutant allele,bri1-301.Although the rlp51 single mutant exhibits wild-type-like phenotypes,it enhances BR-defective phenotypes in bri1-301 and bak1 serk1 mutants.RLP51 is next found to interact with both BRI1 and BAK1 without affecting BRI1–BAK1 interaction.Critically,co-expression of RLP51 with BRI1 or BAK1 significantly increases BRI1 and BAK1 protein abundances.RLP51 appears to promote protein synthesis rather than stabilize BRI1 and BAK1 proteins.Thus,our study identifies RLP51 as a positive regulator of BR signaling that enhances the protein levels of BRI1 and BAK1.
基金National Key Research and Development Program of China,Grant/Award Number:2024YFF0507404Special Clinical Business Fund for High-Level Hospitals of China-Japan Friendship Hospital,Grant/Award Number:2024-NHLHCRF-TS-01。
文摘Background:Large language models(LLMs)have shown considerable promise in supporting clinical decision-making.However,their adoption and evaluation in dermatology remains limited.This study aimed to explore the preferences of Chinese dermatologists regarding LLM-generated responses in clinical psoriasis scenarios and to assess how they prioritize key quality dimensions,including accuracy,traceability,and logicality.Methods:A cross-sectional,web-based survey was conducted between December 25,2024,and January 22,2025,following the Checklist for Reporting Results of Internet E-Surveys guidelines.A total of 1247 valid responses were collected from practicing dermatologists across 33 of China's provincial-level administrative divisions.Participants evaluated responses to five categories of clinical questions(etiology,clinical presentation,differential diagnosis,treatment,and case study)generated by five LLMs:ChatGPT-4o,Kimi.ai,Doubao,ZuoYiGPT,and Lingyi-agent.Statistical associations between participant characteristics and model preferences were examined using chi-square tests.Results:ChatGPT-4o(Model 1)emerged as the most preferred model across all clinical tasks,consistently receiving the highest number of votes in case study(n=740),clinical presentation(n=666),differential diagnosis(n=707),etiology(n=602),and treatment(n=656).Significant variation in model preference by professional title was observed only for the differential diagnosis task(χ^(2)=21.13,df=12,p=0.0485),while no significant differences were found across hospital tiers(p>0.05).In terms of evaluation dimensions,accuracy was most frequently rated as“very important”(n=635).A significant association existed between hospital tier and the most valued dimension(χ^(2)=27.667,df=9,p=0.0011),with dermatologists in primary hospitals prioritizing traceability more than their peers in higher-tier hospitals.No significant associations were found across professional titles(p=0.127).Conclusions:Chinese dermatologists suggest a strong preference for ChatGPT-4o over domestic LLMs in psoriasis-related clinical tasks.While accuracy remains the primary criterion,traceability and logicality are also critical,particularly for clinicians in lower-tier hospitals.These findings suggest that future clinical LLMs should prioritize not only content accuracy but also source transparency and structural clarity to meet the diverse needs of different clinical settings.
基金Project supported by the National Natural Science Foundation of China(Nos.12372214 and U2341231)。
文摘The Reynolds-averaged Navier-Stokes(RANS)technique enables critical engineering predictions and is widely adopted.However,since this iterative computation relies on the fixed-point iteration,it may converge to unexpected non-physical phase points in practice.We conduct an analysis on the phase-space characteristics and the fixed-point theory underlying the k-ε turbulence model,and employ the classical Kolmogorov flow as a framework,leveraging its direct numerical simulation(DNS)data to construct a one-dimensional(1D)system under periodic/fixed boundary conditions.The RANS results demonstrate that under periodic boundary conditions,the k-ε model exhibits only a unique trivial fixed point,with asymptotes capturing the phase portraits.The stability of this trivial fixed point is determined by a mathematically derived stability phase diagram,indicating the fact that the k-ε model will never converge to correct values under periodic conditions.In contrast,under fixed boundary conditions,the model can yield a stable non-trivial fixed point.The evolutionary mechanisms and their relationship with boundary condition settings systematically explain the inherent limitations of the k-ε model,i.e.,its deficiency in computing the flow field under periodic boundary conditions and sensitivity to boundary-value specifications under fixed boundary conditions.These conclusions are finally validated with the open-source code OpenFOAM.
文摘Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.
基金supported by the National Key R&D Program of China[2022YFF0902703]the State Administration for Market Regulation Science and Technology Plan Project(2024MK033).
文摘Recommendation systems are key to boosting user engagement,satisfaction,and retention,particularly on media platforms where personalized content is vital.Sequential recommendation systems learn from user-item interactions to predict future items of interest.However,many current methods rely on unique user and item IDs,limiting their ability to represent users and items effectively,especially in zero-shot learning scenarios where training data is scarce.With the rapid development of Large Language Models(LLMs),researchers are exploring their potential to enhance recommendation systems.However,there is a semantic gap between the linguistic semantics of LLMs and the collaborative semantics of recommendation systems,where items are typically indexed by IDs.Moreover,most research focuses on item representations,neglecting personalized user modeling.To address these issues,we propose a sequential recommendation framework using LLMs,called CIT-Rec,a model that integrates Collaborative semantics for user representation and Image and Text information for item representation to enhance Recommendations.Specifically,by aligning intuitive image information with text containing semantic features,we can more accurately represent items,improving item representation quality.We focus not only on item representations but also on user representations.To more precisely capture users’personalized preferences,we use traditional sequential recommendation models to train on users’historical interaction data,effectively capturing behavioral patterns.Finally,by combining LLMs and traditional sequential recommendation models,we allow the LLM to understand linguistic semantics while capturing collaborative semantics.Extensive evaluations on real-world datasets show that our model outperforms baseline methods,effectively combining user interaction history with item visual and textual modalities to provide personalized recommendations.
基金supported by the CAS Pioneer Hundred Talents Program and Second Tibetan Plateau Scientific Expedition Research Program(2019QZKK0708)as well as the Basic Research Program of Qinghai Province:Lithospheric Geomagnetic Field of the Qinghai-Tibet Plateau and the Relationship with Strong Earthquakes(2021-ZJ-969Q).
文摘The National Geophysical Data Center(NGDC)of the United States has collected aeromagnetic data for input into a series of geomagnetic models to improve model resolution;however,in the Tibetan Plateau region,ground-based observations remain insufficient to clearly reflect the characteristics of the region’s lithospheric magnetism.In this study,we evaluate the lithospheric magnetism of the Tibetan Plateau by using a 3D surface spline model based on observations from>200 newly constructed repeat stations(portable stations)to determine the spatial distribution of plateau geomagnetism,as well as its correlation with the tectonic features of the region.We analyze the relationships between M≥5 earthquakes and lithospheric magnetic field variations on the Tibetan Plateau and identify regions susceptible to strong earthquakes.We compare the geomagnetic results with those from an enhanced magnetic model(EMM2015)developed by the NGDC and provide insights into improving lithospheric magnetic field calculations in the Tibetan Plateau region.Further research reveals that these magnetic anomalies exhibit distinct differences from the magnetic-seismic correlation mechanisms observed in other tectonic settings;here,they are governed primarily by the combined effects of compressional magnetism,thermal magnetism,and deep thermal stress.This study provides new evidence of geomagnetic anomalies on the Tibetan Plateau,interprets them physically,and demonstrates their potential for identifying seismic hazard zones on the Plateau.
基金supported in part by the National Key Research and Development Program of China(2021YFB2900501)in part by the Shaanxi Science and Technology Innovation Team(2023-CX-TD-03)+3 种基金in part by the Science and Technology Program of Shaanxi Province(2021GXLH-Z-038)in part by the Natural Science Foundation of Hunan Province(2023JJ40607 and 2023JJ50045)in part by the Scientific Research Foundation of Hunan Provincial Education Department(23B0713 and 24B0603)in part by the National Natural Science Foundation of China(62401371,62101275,and 62372070).
文摘(Quasi-)closed-form results for the statistical properties of unmanned aerial vehicle(UAV)airto-ground channels are derived for the first time using a novel spatial-vector-based method from a threedimensional(3-D)arbitrary-elevation one-cylinder model.The derived results include a closed-form expression for the space-time correlation function and some quasi-closed-form ones for the space-Doppler power spectrum density,the level crossing rate,and the average fading duration,which are shown to be the generalizations of those previously obtained from the two-dimensional(2-D)one-ring model and the 3-D low-elevation one-cylinder model for terrestrial mobile-to-mobile channels.The close agreements between the theoretical results and the simulations as well as the measurements validate the utility of the derived channel statistics.Based on the derived expressions,the impacts of some parameters on the channel characteristics are investigated in an effective,efficient,and explicable way,which leads to a general guideline on the manual parameter estimation from the measurement description.
基金supported by Special major projects for research and development of Henan Provincial(Science and Technology Research Project)(No.252102321104)Humanities and Social Sciences Youth Foundation,Ministry of Education(24YJCZH410)。
文摘Effective management of mining areas in the Luo River Basin,located in the eastern Qinling Mountains,is vital for the integrated protection and restoration needed to support the high-quality development of the Yellow River Basin.Using the‘cupball'model,this study analyzes the limiting factors and restoration characteristics across four mining areas and proposes a conceptual model for selecting appropriate restoration approaches.A second conceptual model is then introduced to address regional development needs,incorporating ecological conservation,safety protection,and people's wellbeing.The applicability of the integrated model selection framework is demonstrated through a case study on the south bank of the Qinglongjian River.The results indicate that:(1)The key limiting factors are similar across cases,but the degree of ecological degradation varies.(2)Mildly degraded areas are represented by a shallower and narrower‘cup',where natural recovery is the preferred approach,whereas moderately and severely degraded systems call for assisted regeneration and ecological reconstruction,respectively.(3)When the restoration models determined based on limiting factors and development needs are consistent,the model is directly applicable;if they differ,the option involving less artificial intervention is preferred;(4)Monitoring of the restored mining area on the Qinglongjian River's south bank confirms significant improvements in soil erosion control and vegetation coverage.This study provides a transferable methodology for balancing resource extraction with ecosystem conservation,offering practical insights for other ecologically vulnerable mining regions.
基金supported by the Meteorological Joint Funds of the National Natural Science Foundation of China(Grant No.U2142211)the National Natural Science Foundation of China(Grant Nos.42075141,42341202 and 62088101)+1 种基金the National Key Research and Development Program of China(Grant No.2020YFA0608000)the Shanghai Municipal Science and Technology Major Project(Grant No.2021SHZDZX0100).
文摘Accurate forecasting of tropical cyclone(TC)tracks and intensities is essential.Although the TianXing large weather model,a six-hourly forecasting model surpassing operational forecasts,exhibits superior performance,its TC forecasts still require enhancement.Prediction errors persist due to biases in the training data and smoothing effects in data-driven methods.To address this,we introduce CycloneBCNet,a deep-learning model designed to correct TianXing’s TC forecast biases by leveraging spatial and temporal data.CycloneBCNet utilizes the SimVP(simpler yet better video prediction)framework with spatial attention to highlight cyclone core regions in forecast fields.It also incorporates TC trend information(center position,maximum wind speed,and minimum sea level pressure)via an LSTM(long short-term memory)module.These TC vectors are derived from post-processed TianXing forecasts.By fusing features from forecast fields and TC vectors,CycloneBCNet corrects biases across multiple lead times.At a 96-h lead time,the track error reduces from 162.4 to 86.4 km,the wind speed error from 17.2 to 6.69 m s^(-1),and the pressure error from 22.2 to 9.36 hPa.Interpretability analysis shows that CycloneBCNet adjusts its attention across forecast lead times.Intensity corrections prioritize inner-core dynamics,particularly the eye and eyewall,while track corrections shift from lower-level variables and the cyclone’s core to broader environmental factors and mid-to upper-level features as the forecast duration increases.These findings demonstrate that CycloneBCNet effectively captures key TC dynamics consistent with meteorological principles,including the dominance of near-surface conditions for intensity and the increasing influence of steering currents on track prediction.
文摘Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].
