The existing numerical models for nearshore waves are briefly introduced, and the third-generation numerical model for shallow water wave, which makes use of the most advanced productions of wave research and has been...The existing numerical models for nearshore waves are briefly introduced, and the third-generation numerical model for shallow water wave, which makes use of the most advanced productions of wave research and has been adapted well to be used in the environment of seacoast, lake and estuary area, is particularly discussed. The applied model realizes the significant wave height distribution at different wind directions. To integrate the model into the coastal area sediment, sudden deposition mechanism, the distribution of average silt content and the change of sediment sudden deposition thickness over time in the nearshore area are simulated. The academic productions can give some theoretical guidance to the applications of sediment sudden deposition mechanism for stormy waves in the coastal area. And the advancing directions of sediment sudden deposition model are prospected.展开更多
Background:Leptomeningeal metastasis(LM)after third-generation EGFR-TKIs resistance carries a dismal prognosis.Limited blood-brain-barrier penetration rather than secondary EGFR mutations is the dominant resistance me...Background:Leptomeningeal metastasis(LM)after third-generation EGFR-TKIs resistance carries a dismal prognosis.Limited blood-brain-barrier penetration rather than secondary EGFR mutations is the dominant resistance mechanism.We report a case managed with CNS-penetrant EGFR inhibition of zorifertinib.Method:A 53-year-old,never-smoking woman with EGFR L858R-mutant stage IVb non-small-cell lung cancer(NSCLC)developed LM after progression on osimertinib 160 mg and firmonertinib 160 mg.Salvage therapy with zorifertinib(200 mg BID)plus firmonertinib(80 mg qd)was initiated.Results:Within 14 days,the coma resolved.Karnofsky Performance Status improved from 20 to 70.Serial imaging at 3 and 5 months revealed stable disease with shrinkage according to RECIST 1.1.Only grade 1-2 diarrhea,rash,and transaminitis occurred and resolved with symptomatic care.Conclusion:The combination of zorifertinib plus firmonertinib provides durable intracranial control and rapid neurological recovery after third-generation EGFR-TKI failure.Prospective validation is warranted.展开更多
The latest progress in the process optimization and stability improvement of third-generation cephalosporins in recent years was reviewed.The introduction of green chemistry,enzyme catalysis,nanotechnology,lyophilizat...The latest progress in the process optimization and stability improvement of third-generation cephalosporins in recent years was reviewed.The introduction of green chemistry,enzyme catalysis,nanotechnology,lyophilization,and nitrogen-filled packaging technologies can only improve production efficiency and reduce the generation of by-products,but also significantly extend the shelf life of drugs.In the future,process automation and intelligent technology will further optimize the large-scale production process,and the combination of nanotechnology and precision drug delivery will promote the improvement of effect in clinical applications.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
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
Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying ...Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying issues with services,products,or customer experience,resulting in considerable income loss.Prediction of customer churn is a crucial task aimed at retaining customers and maintaining revenue growth.Traditional machine learning(ML)models often struggle to capture complex temporal dependencies in client behavior data.To address this,an optimized deep learning(DL)approach using a Regularized Bidirectional Long Short-Term Memory(RBiLSTM)model is proposed to mitigate overfitting and improve generalization error.The model integrates dropout,L2-regularization,and early stopping to enhance predictive accuracy while preventing over-reliance on specific patterns.Moreover,this study investigates the effect of optimization techniques on boosting the training efficiency of the developed model.Experimental results on a recent public customer churn dataset demonstrate that the trained model outperforms the traditional ML models and some other DL models,such as Long Short-Term Memory(LSTM)and Deep Neural Network(DNN),in churn prediction performance and stability.The proposed approach achieves 96.1%accuracy,compared with LSTM and DNN,which attain 94.5%and 94.1%accuracy,respectively.These results confirm that the proposed approach can be used as a valuable tool for businesses to identify at-risk consumers proactively and implement targeted retention strategies.展开更多
This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to use...This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to user behavior and platform-driven moderation on social media.The proposed methodological framework(1)utilizes large language models for social media post analysis and categorization,(2)employs k-means clustering for content characterization,and(3)incorporates the TODIM(Tomada de Decisão Interativa Multicritério)method to determine moderation strategies based on expert judgments.In general,the fully integrated framework leverages the strengths of these intelligent systems in a more systematic evaluation of large-scale decision problems.When applied in social media moderation,this approach promotes nuanced and context-sensitive self-moderation by taking into account factors such as cultural background and geographic location.The application of this framework is demonstrated within Facebook groups.Eight distinct content clusters encompassing safety,harassment,diversity,and misinformation are identified.Analysis revealed a preference for content removal across all clusters,suggesting a cautious approach towards potentially harmful content.However,the framework also highlights the use of other moderation actions,like account suspension,depending on the content category.These findings contribute to the growing body of research on self-moderation and offer valuable insights for creating safer and more inclusive online spaces within smaller communities.展开更多
The moving morphable component(MMC)topology optimization method,as a typical explicit topology optimization method,has been widely concerned.In the MMC topology optimization framework,the surrogate material model is m...The moving morphable component(MMC)topology optimization method,as a typical explicit topology optimization method,has been widely concerned.In the MMC topology optimization framework,the surrogate material model is mainly used for finite element analysis at present,and the effectiveness of the surrogate material model has been fully confirmed.However,there are some accuracy problems when dealing with boundary elements using the surrogate material model,which will affect the topology optimization results.In this study,a boundary element reconstruction(BER)model is proposed based on the surrogate material model under the MMC topology optimization framework to improve the accuracy of topology optimization.The proposed BER model can reconstruct the boundary elements by refining the local meshes and obtaining new nodes in boundary elements.Then the density of boundary elements is recalculated using the new node information,which is more accurate than the original model.Based on the new density of boundary elements,the material properties and volume information of the boundary elements are updated.Compared with other finite element analysis methods,the BER model is simple and feasible and can improve computational accuracy.Finally,the effectiveness and superiority of the proposed method are verified by comparing it with the optimization results of the original surrogate material model through several numerical examples.展开更多
To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework ba...To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.展开更多
Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frame...Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.展开更多
Noninvasive brain stimulation techniques offer promising therapeutic and regenerative prospects in neurological diseases by modulating brain activity and improving cognitive and motor functions.Given the paucity of kn...Noninvasive brain stimulation techniques offer promising therapeutic and regenerative prospects in neurological diseases by modulating brain activity and improving cognitive and motor functions.Given the paucity of knowledge about the underlying modes of action and optimal treatment modalities,a thorough translational investigation of noninvasive brain stimulation in preclinical animal models is urgently needed.Thus,we reviewed the current literature on the mechanistic underpinnings of noninvasive brain stimulation in models of central nervous system impairment,with a particular emphasis on traumatic brain injury and stroke.Due to the lack of translational models in most noninvasive brain stimulation techniques proposed,we found this review to the most relevant techniques used in humans,i.e.,transcranial magnetic stimulation and transcranial direct current stimulation.We searched the literature in Pub Med,encompassing the MEDLINE and PMC databases,for studies published between January 1,2020 and September 30,2024.Thirty-five studies were eligible.Transcranial magnetic stimulation and transcranial direct current stimulation demonstrated distinct strengths in augmenting rehabilitation post-stroke and traumatic brain injury,with emerging mechanistic evidence.Overall,we identified neuronal,inflammatory,microvascular,and apoptotic pathways highlighted in the literature.This review also highlights a lack of translational surrogate parameters to bridge the gap between preclinical findings and their clinical translation.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 brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cereb...The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cerebral organoids have emerged as valuable tools offering a more complex,versatile,and human-relevant system than traditional animal models,which are often unable to replicate the intricate architecture and functionality of the human brain.Since human cerebral organoids are a state-of-the-art model for the study of neurodevelopment and different pathologies affecting the brain,this field is currently under constant development,and work in this area is abundant.In this review,we give a complete overview of human cerebral organoids technology,starting from the different types of protocols that exist to generate different human cerebral organoids.We continue with the use of brain organoids for the study of brain pathologies,highlighting neurodevelopmental,psychiatric,neurodegenerative,brain tumor,and infectious diseases.Because of the potential value of human cerebral organoids,we describe their use in transplantation,drug screening,and toxicology assays.We also discuss the technologies available to study cell diversity and physiological characteristics of organoids.Finally,we summarize the limitations that currently exist in the field,such as the development of vasculature and microglia,and highlight some of the novel approaches being pursued through bioengineering.展开更多
During the past thirty years, two generations of low alloy steels(ferrite/pearlite followed by bainite/martensite) have been developed and widely used in structural applications. The third-generation of low alloy stee...During the past thirty years, two generations of low alloy steels(ferrite/pearlite followed by bainite/martensite) have been developed and widely used in structural applications. The third-generation of low alloy steels is expected to achieve high strength and improved ductility and toughness, while satisfying the new demands for weight reduction, greenness, and safety. This paper reviews recent progress in the development of third-generation low alloy steels with an M^3 microstructure, namely, microstructures with multi-phase, meta-stable austenite, and multi-scale precipitates. The review summarizes the alloy designs and processing routes of microstructure control, and the mechanical properties of the alloys.The stabilization of retained austenite in low alloy steels is especially emphasized. Multi-scale nano-precipitates, including carbides of microalloying elements and Cu-rich precipitates obtained in third-generation low alloy steels, are then introduced. The structure–property relationships of third-generation alloys are also discussed. Finally, the promises and challenges to future applications are explored.展开更多
The breeding and large-scale application of hybrid rice contribute significantly to the food supply worldwide.Currently,hybrid seed production uses cytoplasmic male sterile(CMS)lines or photoperiod/thermo-sensitive ge...The breeding and large-scale application of hybrid rice contribute significantly to the food supply worldwide.Currently,hybrid seed production uses cytoplasmic male sterile(CMS)lines or photoperiod/thermo-sensitive genic male sterile(PTGMS)lines as female parent.Despite huge successes,both systems have intrinsic problems.CMS systems are mainly restricted by the narrow restorer resources that make it difficult to breed superior hybrids,while PTGMS systems are limited by conditional sterility of the male sterile lines that makes the propagation of both PTGMS seeds and hybrid seeds vulnerable to unpredictable climate changes.Recessive nuclear male sterile(NMS)lines insensitive to environmental conditions are widely distributed and are ideal for hybrid rice breeding and production,but the lack of effective ways to propagate the pure NMS lines in a large scale renders it impossible to use them for hybrid rice production.The development of"the third-generation hybrid rice technology"enables efficient propagation of the pure NMS lines in commercial scale.This paper discusses the establishment of"the thirdgeneration hybrid rice technology"and further innovations.This new technology breaks the limitations of CMS and PTGMS systems and will bring a big leap forward in hybrid rice production.展开更多
Objective:Autosomal recessive bestrophinopathy(ARB),a retinal degenerative disease,is characterized by central visual loss,yellowish multifocal diffuse subretinal deposits,and a dramatic decrease in the light peak on ...Objective:Autosomal recessive bestrophinopathy(ARB),a retinal degenerative disease,is characterized by central visual loss,yellowish multifocal diffuse subretinal deposits,and a dramatic decrease in the light peak on electrooculogram.The potential pathogenic mechanism involves mutations in the BEST1 gene,which encodes Ca2+-activated Cl−channels in the retinal pigment epithelium(RPE),resulting in degeneration of RPE and photoreceptor.In this study,the complete clinical characteristics of two Chinese ARB families were summarized.Methods:Pacific Biosciences(PacBio)single-molecule real-time(SMRT)sequencing was performed on the probands to screen for disease-causing gene mutations,and Sanger sequencing was applied to validate variants in the patients and their family members.Results:Two novel mutations,c.202T>C(chr11:61722628,p.Y68H)and c.867+97G>A,in the BEST1 gene were identified in the two Chinese ARB families.The novel missense mutation BEST1 c.202T>C(p.Y68H)resulted in the substitution of tyrosine with histidine in the N-terminal region of transmembrane domain 2 of bestrophin-1.Another novel variant,BEST1 c.867+97G>A(chr11:61725867),located in intron 7,might be considered a regulatory variant that changes allele-specific binding affinity based on motifs of important transcriptional regulators.Conclusion:Our findings represent the first use of third-generation sequencing(TGS)to identify novel BEST1 mutations in patients with ARB,indicating that TGS can be a more accurate and efficient tool for identifying mutations in specific genes.The novel variants identified further broaden the mutation spectrum of BEST1 in the Chinese population.展开更多
The Third-Generation Poetry of China （namely Post-misty Poetry too） initiated with the introduction of Western modernist poetry, especially sorts of American Post-modernist poetry schools into China. ＂The relation ...The Third-Generation Poetry of China （namely Post-misty Poetry too） initiated with the introduction of Western modernist poetry, especially sorts of American Post-modernist poetry schools into China. ＂The relation between American poetry and Chinese poetry has a long history, which lies in the influences on the creation of the Third-Generation poets. This influence is probably unprecedented in its depth and breadth.＂ ＂Irrational association＂ and ＂leaping images＂ proposed by American Deep Image poets influenced by Freudian and Jungian unconscious perception gained an extraordinary appreciation among the Third-Generation poets who were in pursuit constantly of the experiments on poetic form and language. This paper mainly discusses the influences of American Deep Image on the Third-Generation poets of China through a case study of WANG Yin and CHEN Dongdong＇s poems.展开更多
The development of measurement geometry for medical X-ray computed tomography （CT） scanners was carried out from the first to the fourth-generation. This concept has also been applied for imaging of industrial proce...The development of measurement geometry for medical X-ray computed tomography （CT） scanners was carried out from the first to the fourth-generation. This concept has also been applied for imaging of industrial processes such as pipe flows or for improving design, operation, optimization and troubleshooting. Nowadays, gamma CT permits to visualize failure equipment points in three-dimensional analysis and in sections of chemical and petrochemical industries. The aim of this work is the development of the mechanical system on a third-generation industrial CT scanner to analyze laboratorial process columns which perform highly efficient separation, turning the ^6oCo, ^75Se, ^137Cs and/or ^192Ir sealed gamma-ray source（s） and the NaI（Tl） multidetector array. It also has a translation movement along the column axis to obtain as many slices of the process flow as needed. The mechanical assembly for this third-generation industrial CT scanner is comprised by strength and rigidity structural frame in stainless and carbon steels, rotating table, source shield and collimator with pneumatic exposure system, spur gear system, translator, rotary stage, drives and stepper motors. The use of suitable spur gears has given a good repeatability and high accuracy in the degree of veracity. The data acquisition boards, mechanical control interfaces, software for movement control and image reconstruction were specially development. A multiphase phantom capable to be setting with solid, liquid and gas was testing. The scanner was setting for 90 views and 19 projections for each detector totalizing 11,970 projections. Experiments to determine the linear attenuation coefficients of the phantom were carried out which applied the Lambert-Beer principle. Results showed that it was possible to distinguish between the phases even the polymethylmethacrylate and the water have very similar density and linear attenuation coefficients. It was established that the newly developed third-generation fan-beam arrangement gamma scanner unit has a good spatial resolution acceptable given the size of the used phantom in this study. The tomografic reconstruction algorithm in used 60 ~ 60 pixels images was the Alternative Minimization （AM） technique and was implemented in MATLAB and VB platforms. The mechanical system presented a good performance in terms of strength, rigidity, accuracy and repeatability with great potential to be used for education or program which dedicated to training chemical and petrochemical industry professionals and for industrial process optimization in Brazil.展开更多
文摘The existing numerical models for nearshore waves are briefly introduced, and the third-generation numerical model for shallow water wave, which makes use of the most advanced productions of wave research and has been adapted well to be used in the environment of seacoast, lake and estuary area, is particularly discussed. The applied model realizes the significant wave height distribution at different wind directions. To integrate the model into the coastal area sediment, sudden deposition mechanism, the distribution of average silt content and the change of sediment sudden deposition thickness over time in the nearshore area are simulated. The academic productions can give some theoretical guidance to the applications of sediment sudden deposition mechanism for stormy waves in the coastal area. And the advancing directions of sediment sudden deposition model are prospected.
文摘Background:Leptomeningeal metastasis(LM)after third-generation EGFR-TKIs resistance carries a dismal prognosis.Limited blood-brain-barrier penetration rather than secondary EGFR mutations is the dominant resistance mechanism.We report a case managed with CNS-penetrant EGFR inhibition of zorifertinib.Method:A 53-year-old,never-smoking woman with EGFR L858R-mutant stage IVb non-small-cell lung cancer(NSCLC)developed LM after progression on osimertinib 160 mg and firmonertinib 160 mg.Salvage therapy with zorifertinib(200 mg BID)plus firmonertinib(80 mg qd)was initiated.Results:Within 14 days,the coma resolved.Karnofsky Performance Status improved from 20 to 70.Serial imaging at 3 and 5 months revealed stable disease with shrinkage according to RECIST 1.1.Only grade 1-2 diarrhea,rash,and transaminitis occurred and resolved with symptomatic care.Conclusion:The combination of zorifertinib plus firmonertinib provides durable intracranial control and rapid neurological recovery after third-generation EGFR-TKI failure.Prospective validation is warranted.
基金Supported by the Funds from Central Government for Guiding Local Science and Technology Development(ZY20230102)Planning Project of Scientific Research and Technology Development in Guilin(20220104-4,20210202-1)Science and Technology Planing Project of Guangxi(Guike AB24010263).
文摘The latest progress in the process optimization and stability improvement of third-generation cephalosporins in recent years was reviewed.The introduction of green chemistry,enzyme catalysis,nanotechnology,lyophilization,and nitrogen-filled packaging technologies can only improve production efficiency and reduce the generation of by-products,but also significantly extend the shelf life of drugs.In the future,process automation and intelligent technology will further optimize the large-scale production process,and the combination of nanotechnology and precision drug delivery will promote the improvement of effect in clinical applications.
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.
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)].
文摘Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying issues with services,products,or customer experience,resulting in considerable income loss.Prediction of customer churn is a crucial task aimed at retaining customers and maintaining revenue growth.Traditional machine learning(ML)models often struggle to capture complex temporal dependencies in client behavior data.To address this,an optimized deep learning(DL)approach using a Regularized Bidirectional Long Short-Term Memory(RBiLSTM)model is proposed to mitigate overfitting and improve generalization error.The model integrates dropout,L2-regularization,and early stopping to enhance predictive accuracy while preventing over-reliance on specific patterns.Moreover,this study investigates the effect of optimization techniques on boosting the training efficiency of the developed model.Experimental results on a recent public customer churn dataset demonstrate that the trained model outperforms the traditional ML models and some other DL models,such as Long Short-Term Memory(LSTM)and Deep Neural Network(DNN),in churn prediction performance and stability.The proposed approach achieves 96.1%accuracy,compared with LSTM and DNN,which attain 94.5%and 94.1%accuracy,respectively.These results confirm that the proposed approach can be used as a valuable tool for businesses to identify at-risk consumers proactively and implement targeted retention strategies.
基金funded by the Office of the Vice-President for Research and Development of Cebu Technological University.
文摘This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to user behavior and platform-driven moderation on social media.The proposed methodological framework(1)utilizes large language models for social media post analysis and categorization,(2)employs k-means clustering for content characterization,and(3)incorporates the TODIM(Tomada de Decisão Interativa Multicritério)method to determine moderation strategies based on expert judgments.In general,the fully integrated framework leverages the strengths of these intelligent systems in a more systematic evaluation of large-scale decision problems.When applied in social media moderation,this approach promotes nuanced and context-sensitive self-moderation by taking into account factors such as cultural background and geographic location.The application of this framework is demonstrated within Facebook groups.Eight distinct content clusters encompassing safety,harassment,diversity,and misinformation are identified.Analysis revealed a preference for content removal across all clusters,suggesting a cautious approach towards potentially harmful content.However,the framework also highlights the use of other moderation actions,like account suspension,depending on the content category.These findings contribute to the growing body of research on self-moderation and offer valuable insights for creating safer and more inclusive online spaces within smaller communities.
基金supported by the Science and Technology Research Project of Henan Province(242102241055)the Industry-University-Research Collaborative Innovation Base on Automobile Lightweight of“Science and Technology Innovation in Central Plains”(2024KCZY315)the Opening Fund of State Key Laboratory of Structural Analysis,Optimization and CAE Software for Industrial Equipment(GZ2024A03-ZZU).
文摘The moving morphable component(MMC)topology optimization method,as a typical explicit topology optimization method,has been widely concerned.In the MMC topology optimization framework,the surrogate material model is mainly used for finite element analysis at present,and the effectiveness of the surrogate material model has been fully confirmed.However,there are some accuracy problems when dealing with boundary elements using the surrogate material model,which will affect the topology optimization results.In this study,a boundary element reconstruction(BER)model is proposed based on the surrogate material model under the MMC topology optimization framework to improve the accuracy of topology optimization.The proposed BER model can reconstruct the boundary elements by refining the local meshes and obtaining new nodes in boundary elements.Then the density of boundary elements is recalculated using the new node information,which is more accurate than the original model.Based on the new density of boundary elements,the material properties and volume information of the boundary elements are updated.Compared with other finite element analysis methods,the BER model is simple and feasible and can improve computational accuracy.Finally,the effectiveness and superiority of the proposed method are verified by comparing it with the optimization results of the original surrogate material model through several numerical examples.
基金supported by the confidential research grant No.a8317。
文摘To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.
基金supported by the National Natural Science Foundation of China(Grant No.72161034).
文摘Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.
基金funded by the Deutsche Forschungsgemeinschaft(DFG,German Research Foundation):project ID 431549029-SFB 1451the Marga-und-Walter-Boll-Stiftung(#210-10-15)(to MAR)a stipend from the'Gerok Program'(Faculty of Medicine,University of Cologne,Germany)。
文摘Noninvasive brain stimulation techniques offer promising therapeutic and regenerative prospects in neurological diseases by modulating brain activity and improving cognitive and motor functions.Given the paucity of knowledge about the underlying modes of action and optimal treatment modalities,a thorough translational investigation of noninvasive brain stimulation in preclinical animal models is urgently needed.Thus,we reviewed the current literature on the mechanistic underpinnings of noninvasive brain stimulation in models of central nervous system impairment,with a particular emphasis on traumatic brain injury and stroke.Due to the lack of translational models in most noninvasive brain stimulation techniques proposed,we found this review to the most relevant techniques used in humans,i.e.,transcranial magnetic stimulation and transcranial direct current stimulation.We searched the literature in Pub Med,encompassing the MEDLINE and PMC databases,for studies published between January 1,2020 and September 30,2024.Thirty-five studies were eligible.Transcranial magnetic stimulation and transcranial direct current stimulation demonstrated distinct strengths in augmenting rehabilitation post-stroke and traumatic brain injury,with emerging mechanistic evidence.Overall,we identified neuronal,inflammatory,microvascular,and apoptotic pathways highlighted in the literature.This review also highlights a lack of translational surrogate parameters to bridge the gap between preclinical findings and their clinical translation.
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 Grant PID2021-126715OB-IOO financed by MCIN/AEI/10.13039/501100011033 and"ERDFA way of making Europe"by the Grant PI22CⅢ/00055 funded by Instituto de Salud CarlosⅢ(ISCⅢ)+6 种基金the UFIECPY 398/19(PEJ2018-004965) grant to RGS funded by AEI(Spain)the UFIECPY-396/19(PEJ2018-004961)grant financed by MCIN (Spain)FI23CⅢ/00003 grant funded by ISCⅢ-PFIS Spain) to PMMthe UFIECPY 328/22 (PEJ-2021-TL/BMD-21001) grant to LM financed by CAM (Spain)the grant by CAPES (Coordination for the Improvement of Higher Education Personnel)through the PDSE program (Programa de Doutorado Sanduiche no Exterior)to VSCG financed by MEC (Brazil)
文摘The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cerebral organoids have emerged as valuable tools offering a more complex,versatile,and human-relevant system than traditional animal models,which are often unable to replicate the intricate architecture and functionality of the human brain.Since human cerebral organoids are a state-of-the-art model for the study of neurodevelopment and different pathologies affecting the brain,this field is currently under constant development,and work in this area is abundant.In this review,we give a complete overview of human cerebral organoids technology,starting from the different types of protocols that exist to generate different human cerebral organoids.We continue with the use of brain organoids for the study of brain pathologies,highlighting neurodevelopmental,psychiatric,neurodegenerative,brain tumor,and infectious diseases.Because of the potential value of human cerebral organoids,we describe their use in transplantation,drug screening,and toxicology assays.We also discuss the technologies available to study cell diversity and physiological characteristics of organoids.Finally,we summarize the limitations that currently exist in the field,such as the development of vasculature and microglia,and highlight some of the novel approaches being pursued through bioengineering.
基金financially supported by the National Natural Science Foundation of China (No. 51701012)the National Basic Research Program of China (973 Program: No. 2010CB630801)the Fundamental Research Funds for the Central Universities (No. FRF-TP-17-004A1)
文摘During the past thirty years, two generations of low alloy steels(ferrite/pearlite followed by bainite/martensite) have been developed and widely used in structural applications. The third-generation of low alloy steels is expected to achieve high strength and improved ductility and toughness, while satisfying the new demands for weight reduction, greenness, and safety. This paper reviews recent progress in the development of third-generation low alloy steels with an M^3 microstructure, namely, microstructures with multi-phase, meta-stable austenite, and multi-scale precipitates. The review summarizes the alloy designs and processing routes of microstructure control, and the mechanical properties of the alloys.The stabilization of retained austenite in low alloy steels is especially emphasized. Multi-scale nano-precipitates, including carbides of microalloying elements and Cu-rich precipitates obtained in third-generation low alloy steels, are then introduced. The structure–property relationships of third-generation alloys are also discussed. Finally, the promises and challenges to future applications are explored.
基金supported by the National Natural Science Foundation of China(U1901203)Natural Science Foundation of Guangdong Province(2018B030308008 and 2019A1515110671)+2 种基金Major Program of Guangdong Basic and Applied Research(2019B030302006)Shenzhen Commission on Innovation and Technology Programs(JCYJ20180507181837997)China Postdoctoral Science Foundation(2019M662957)。
文摘The breeding and large-scale application of hybrid rice contribute significantly to the food supply worldwide.Currently,hybrid seed production uses cytoplasmic male sterile(CMS)lines or photoperiod/thermo-sensitive genic male sterile(PTGMS)lines as female parent.Despite huge successes,both systems have intrinsic problems.CMS systems are mainly restricted by the narrow restorer resources that make it difficult to breed superior hybrids,while PTGMS systems are limited by conditional sterility of the male sterile lines that makes the propagation of both PTGMS seeds and hybrid seeds vulnerable to unpredictable climate changes.Recessive nuclear male sterile(NMS)lines insensitive to environmental conditions are widely distributed and are ideal for hybrid rice breeding and production,but the lack of effective ways to propagate the pure NMS lines in a large scale renders it impossible to use them for hybrid rice production.The development of"the third-generation hybrid rice technology"enables efficient propagation of the pure NMS lines in commercial scale.This paper discusses the establishment of"the thirdgeneration hybrid rice technology"and further innovations.This new technology breaks the limitations of CMS and PTGMS systems and will bring a big leap forward in hybrid rice production.
文摘Objective:Autosomal recessive bestrophinopathy(ARB),a retinal degenerative disease,is characterized by central visual loss,yellowish multifocal diffuse subretinal deposits,and a dramatic decrease in the light peak on electrooculogram.The potential pathogenic mechanism involves mutations in the BEST1 gene,which encodes Ca2+-activated Cl−channels in the retinal pigment epithelium(RPE),resulting in degeneration of RPE and photoreceptor.In this study,the complete clinical characteristics of two Chinese ARB families were summarized.Methods:Pacific Biosciences(PacBio)single-molecule real-time(SMRT)sequencing was performed on the probands to screen for disease-causing gene mutations,and Sanger sequencing was applied to validate variants in the patients and their family members.Results:Two novel mutations,c.202T>C(chr11:61722628,p.Y68H)and c.867+97G>A,in the BEST1 gene were identified in the two Chinese ARB families.The novel missense mutation BEST1 c.202T>C(p.Y68H)resulted in the substitution of tyrosine with histidine in the N-terminal region of transmembrane domain 2 of bestrophin-1.Another novel variant,BEST1 c.867+97G>A(chr11:61725867),located in intron 7,might be considered a regulatory variant that changes allele-specific binding affinity based on motifs of important transcriptional regulators.Conclusion:Our findings represent the first use of third-generation sequencing(TGS)to identify novel BEST1 mutations in patients with ARB,indicating that TGS can be a more accurate and efficient tool for identifying mutations in specific genes.The novel variants identified further broaden the mutation spectrum of BEST1 in the Chinese population.
文摘The Third-Generation Poetry of China （namely Post-misty Poetry too） initiated with the introduction of Western modernist poetry, especially sorts of American Post-modernist poetry schools into China. ＂The relation between American poetry and Chinese poetry has a long history, which lies in the influences on the creation of the Third-Generation poets. This influence is probably unprecedented in its depth and breadth.＂ ＂Irrational association＂ and ＂leaping images＂ proposed by American Deep Image poets influenced by Freudian and Jungian unconscious perception gained an extraordinary appreciation among the Third-Generation poets who were in pursuit constantly of the experiments on poetic form and language. This paper mainly discusses the influences of American Deep Image on the Third-Generation poets of China through a case study of WANG Yin and CHEN Dongdong＇s poems.
文摘The development of measurement geometry for medical X-ray computed tomography （CT） scanners was carried out from the first to the fourth-generation. This concept has also been applied for imaging of industrial processes such as pipe flows or for improving design, operation, optimization and troubleshooting. Nowadays, gamma CT permits to visualize failure equipment points in three-dimensional analysis and in sections of chemical and petrochemical industries. The aim of this work is the development of the mechanical system on a third-generation industrial CT scanner to analyze laboratorial process columns which perform highly efficient separation, turning the ^6oCo, ^75Se, ^137Cs and/or ^192Ir sealed gamma-ray source（s） and the NaI（Tl） multidetector array. It also has a translation movement along the column axis to obtain as many slices of the process flow as needed. The mechanical assembly for this third-generation industrial CT scanner is comprised by strength and rigidity structural frame in stainless and carbon steels, rotating table, source shield and collimator with pneumatic exposure system, spur gear system, translator, rotary stage, drives and stepper motors. The use of suitable spur gears has given a good repeatability and high accuracy in the degree of veracity. The data acquisition boards, mechanical control interfaces, software for movement control and image reconstruction were specially development. A multiphase phantom capable to be setting with solid, liquid and gas was testing. The scanner was setting for 90 views and 19 projections for each detector totalizing 11,970 projections. Experiments to determine the linear attenuation coefficients of the phantom were carried out which applied the Lambert-Beer principle. Results showed that it was possible to distinguish between the phases even the polymethylmethacrylate and the water have very similar density and linear attenuation coefficients. It was established that the newly developed third-generation fan-beam arrangement gamma scanner unit has a good spatial resolution acceptable given the size of the used phantom in this study. The tomografic reconstruction algorithm in used 60 ~ 60 pixels images was the Alternative Minimization （AM） technique and was implemented in MATLAB and VB platforms. The mechanical system presented a good performance in terms of strength, rigidity, accuracy and repeatability with great potential to be used for education or program which dedicated to training chemical and petrochemical industry professionals and for industrial process optimization in Brazil.
