BACKGROUND The mortality rate for severe cases of acute pancreatitis(AP),a common gastrointestinal emergency,is as high as 30%.Our previous study has shown that rutaecarpine(Rut)has a therapeutic effect on AP.AIM To i...BACKGROUND The mortality rate for severe cases of acute pancreatitis(AP),a common gastrointestinal emergency,is as high as 30%.Our previous study has shown that rutaecarpine(Rut)has a therapeutic effect on AP.AIM To investigate the role of F-box and WD repeat domain containing 11(FBXW11)in AP models and to assess whether Rut mitigates AP by regulating FBXW11.METHODS AP rat model was established and treated with Rut,followed by biochemical analysis of serum amylase and lipase,hematoxylin and eosin staining of pancreatic tissue,and immunohistochemistry detection of pancreatic Ly6G,CD11b,and myeloperoxidase.Assay kits were used to detect oxidative stress-related indicators in pancreatic tissue and inflammatory factors in serum.AR42J cells were treated with cerulein to model AP and subjected to Cell Counting Kit-8 viability assay,flow cytometry apoptosis assay,and immunofluorescence detection of reactive oxygen species to elucidate the mechanistic involvement of the enhancer of zeste homolog 2(EZH2)-FBXW11 axis in Rut-mediated protection against AP.The EZH2-histone H3 binding and H3 methylation were evaluated using co-immunoprecipitation.RESULTS Rut treatment ameliorated AP severity,as evidenced by reduced serum levels of pancreatic enzymes(amylase and lipase)and attenuated histological damage.Rut also decreased inflammatory markers(interleukin-1 beta,interleukin-6,and tumor necrosis factor alpha),tissue oxidative stress(malondialdehyde),and neutrophil infiltration(Ly6G,CD11b,and myeloperoxidase)levels in rats with AP.Moreover,Rut restored pancreatic antioxidant capacity(glutathione and superoxide dismutase).In vitro,Rut pre-incubation enhanced cell viability and suppressed cerulein-induced apoptosis and oxidative stress.Rut increased EZH2 expression while decreasing FBXW11 expression.FBXW11 overexpression eliminated the protective effect of Rut against AP.Further analysis revealed that EZH2 binds to H3 and upregulates H3 methylation levels,thereby inhibiting FBXW11 expression.CONCLUSION Collectively,our findings demonstrate that Rut ameliorates AP by upregulating EZH2,thereby enhancing H3 methylation and suppressing FBXW11 expression.展开更多
The viscosity of refining slags plays a critical role in metallurgical processes.However,obtaining accurate viscosity data remains challenging due to the complexities of high-temperature experiments,often relying on e...The viscosity of refining slags plays a critical role in metallurgical processes.However,obtaining accurate viscosity data remains challenging due to the complexities of high-temperature experiments,often relying on empirical models with limited predictive capabilities.This study focuses on the influence of optical basicity on viscosity in CaO-Al_(2)O_(3)-based refining slags,leveraging machine learning to address data scarcity and improve prediction accuracy.An automated framework for algorithm integration,parameter tuning,and evaluation ranking framework(Auto-APE)is employed to develop customized data-driven models for various slag systems,including CaO-Al_(2)O_(3)-SiO_(2),CaO-Al_(2)O_(3)-CaF_(2),CaO-Al_(2)O_(3)-SiO_(2)-MgO,and CaO-Al_(2)O_(3)-SiO_(2)-MgO-CaF_(2).By incorporating optical basicity as a key feature,the models achieve an average validation error of 8.0%to 15.1%,significantly outperforming traditional empirical models.Additionally,symbolic regression is introduced to rapidly construct domain-specific features,such as optical basicity-like descriptors,offering a potential breakthrough in performance prediction for small datasets.This work highlights the critical role of domain-specific knowledge in understanding and predicting viscosity,providing a robust machine learning-based approach for optimizing refining slag properties.展开更多
Objectives This study aimed to explore the research trends,thematic structures,and core competency domains in the field of nursing-related digital and artificial intelligence(AI)technologies.Methods A bibliometric ana...Objectives This study aimed to explore the research trends,thematic structures,and core competency domains in the field of nursing-related digital and artificial intelligence(AI)technologies.Methods A bibliometric analysis was conducted in accordance with the PRISMA 2020 statement.Peer-reviewed articles published in English from 2015 to 2025 were retrieved from Scopus,Web of Science,and PubMed.Thematic clustering was conducted using the Louvain algorithm and cosine similarity.A subset of 66 frequently cited articles was then qualitatively synthesized to capture core competencies across clusters.Results A total of 83,807 articles were included for bibliometric analysis.Of these,66 articles were chosen for thematic analysis.Five major thematic clusters were identified:remote care in primary settings,oncology and palliative care,nurse education and training,safety and quality in nursing practice,and geriatric and dementia care.Additionally,four competency domains were identified:telehealth and remote communication,health systems and informatics,digital tools in practice,and AI-powered decision support.A clear shift in research focus was observed,with the emphasis transitioning from foundational digital skills before the COVID-19 pandemic to more advanced competencies during the post-pandemic digital transformation,encompassing ethical reasoning,immersive technology use,and AI integration.Conclusions Integrating digital and AI technologies is reshaping nursing practice across various thematic areas and competency domains,highlighting a transition from foundational digital tasks to AI-supported decision-making and ethically informed technology use.This study provides a structured overview of evolving competencies in digital nursing and synthesizes evidence to support future research,curriculum design,and policy planning.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
The precise tuning of magnetic nanoparticle size and magnetic domains,thereby shaping magnetic properties.However,the dynamic evolution mechanisms of magnetic domain configurations in relation to electromagnetic(EM)at...The precise tuning of magnetic nanoparticle size and magnetic domains,thereby shaping magnetic properties.However,the dynamic evolution mechanisms of magnetic domain configurations in relation to electromagnetic(EM)attenuation behavior remain poorly understood.To address this gap,a thermodynamically controlled periodic coordination strategy is proposed to achieve precise modulation of magnetic nanoparticle spacing.This approach unveils the evolution of magnetic domain configurations,progressing from individual to coupled and ultimately to crosslinked domain configurations.A unique magnetic coupling phenomenon surpasses the Snoek limit in low-frequency range,which is observed through micromagnetic simulation.The crosslinked magnetic configuration achieves effective low-frequency EM wave absorption at 3.68 GHz,encompassing nearly the entire C-band.This exceptional magnetic interaction significantly enhances radar camouflage and thermal insulation properties.Additionally,a robust gradient metamaterial design extends coverage across the full band(2–40 GHz),effectively mitigating the impact of EM pollution on human health and environment.This comprehensive study elucidates the evolution mechanisms of magnetic domain configurations,addresses gaps in dynamic magnetic modulation,and provides novel insights for the development of high-performance,low-frequency EM wave absorption materials.展开更多
Lithium niobate(LN)has remained at the forefront of academic research and industrial applications due to its rich material properties,which include second-order nonlinear optic,electro-optic,and piezoelectric properti...Lithium niobate(LN)has remained at the forefront of academic research and industrial applications due to its rich material properties,which include second-order nonlinear optic,electro-optic,and piezoelectric properties.A further aspect of LN’s versatility stems from the ability to engineer ferroelectric domains with micro and even nano-scale precision in LN,which provides an additional degree of freedom to design acoustic and optical devices with improved performance and is only possible in a handful of other materials.In this review paper,we provide an overview of the domain engineering techniques developed for LN,their principles,and the typical domain size and pattern uniformity they provide,which is important for devices that require high-resolution domain patterns with good reproducibility.It also highlights each technique's benefits,limitations,and adaptability for an application,along with possible improvements and future advancement prospects.Further,the review provides a brief overview of domain visualization methods,which is crucial to gain insights into domain quality/shape and explores the adaptability of the proposed domain engineering methodologies for the emerging thin-film lithium niobate on an insulator platform,which creates opportunities for developing the next generation of compact and scalable photonic integrated circuits and high frequency acoustic devices.展开更多
To avoid the laborious annotation process for dense prediction tasks like semantic segmentation,unsupervised domain adaptation(UDA)methods have been proposed to leverage the abundant annotations from a source domain,s...To avoid the laborious annotation process for dense prediction tasks like semantic segmentation,unsupervised domain adaptation(UDA)methods have been proposed to leverage the abundant annotations from a source domain,such as virtual world(e.g.,3D games),and adapt models to the target domain(the real world)by narrowing the domain discrepancies.However,because of the large domain gap,directly aligning two distinct domains without considering the intermediates leads to inefficient alignment and inferior adaptation.To address this issue,we propose a novel learnable evolutionary Category Intermediates(CIs)guided UDA model named Leci,which enables the information transfer between the two domains via two processes,i.e.,Distilling and Blending.Starting from a random initialization,the CIs learn shared category-wise semantics automatically from two domains in the Distilling process.Then,the learned semantics in the CIs are sent back to blend the domain features through a residual attentive fusion(RAF)module,such that the categorywise features of both domains shift towards each other.As the CIs progressively and consistently learn from the varying feature distributions during training,they are evolutionary to guide the model to achieve category-wise feature alignment.Experiments on both GTA5 and SYNTHIA datasets demonstrate Leci's superiority over prior representative methods.展开更多
In this paper,we give a complete characterization of all self-adjoint domains of odd order differential operators on two intervals.These two intervals with all four endpoints are singular(one endpoint of each interval...In this paper,we give a complete characterization of all self-adjoint domains of odd order differential operators on two intervals.These two intervals with all four endpoints are singular(one endpoint of each interval is singular or all four endpoints are regulars are the special cases).And these extensions yield"new"self-adjoint operators,which involve interactions between the two intervals.展开更多
In this paper,the Paley-Wiener theorem is extended to the analytic function spaces with general weights.We first generalize the theorem to weighted Hardy spaces Hp(0<p<∞)on tube domains by constructing a sequen...In this paper,the Paley-Wiener theorem is extended to the analytic function spaces with general weights.We first generalize the theorem to weighted Hardy spaces Hp(0<p<∞)on tube domains by constructing a sequence of L^(1)functions converging to the given function and verifying their representation in the form of Fourier transform to establish the desired result of the given function.Applying this main result,we further generalize the Paley-Wiener theorem for band-limited functions to the analytic function spaces L^(p)(0<p<∞)with general weights.展开更多
The mitogen-activated protein kinase kinase kinase kinases(MAP4Ks)signaling pathway plays a pivotal role in axonal regrowth and neuronal degeneration following insults.Whether targeting this pathway is beneficial to b...The mitogen-activated protein kinase kinase kinase kinases(MAP4Ks)signaling pathway plays a pivotal role in axonal regrowth and neuronal degeneration following insults.Whether targeting this pathway is beneficial to brain injury remains unclear.In this study,we showed that adeno-associated virus-delivery of the Citron homology domain of MAP4Ks effectively reduces traumatic brain injury-induced reactive gliosis,tauopathy,lesion size,and behavioral deficits.Pharmacological inhibition of MAP4Ks replicated the ameliorative effects observed with expression of the Citron homology domain.Mechanistically,the Citron homology domain acted as a dominant-negative mutant,impeding MAP4K-mediated phosphorylation of the dishevelled proteins and thereby controlling the Wnt/β-catenin pathway.These findings implicate a therapeutic potential of targeting MAP4Ks to alleviate the detrimental effects of traumatic brain injury.展开更多
Pb(Zr,Ti)O_(3)-Pb(Zn_(1/3)Nb_(2/3))O_(3) (PZT-PZN) based ceramics, as important piezoelectric materials, have a wide range of applications in fields such as sensors and actuators, thus the optimization of their piezoe...Pb(Zr,Ti)O_(3)-Pb(Zn_(1/3)Nb_(2/3))O_(3) (PZT-PZN) based ceramics, as important piezoelectric materials, have a wide range of applications in fields such as sensors and actuators, thus the optimization of their piezoelectric properties has been a hot research topic. This study investigated the effects of phase boundary engineering and domain engineering on (1-x)[0.8Pb(Zr_(0.5)Ti_(0.5))O_(3)-0.2Pb(Zn_(1/3)Nb_(2/3))O_(3)]-xBi(Zn_(0.5)Ti_(0.5))O_(3) ((1-x)(0.8PZT-0.2PZN)- xBZT) ceramic to obtain excellent piezoelectric properties. The crystal phase structure and microstructure of ceramic samples were characterized. The results showed that all samples had a pure perovskite structure, and the addition of BZT gradually increased the grain size. The addition of BZT caused a phase transition in ceramic samples from the morphotropic phase boundary (MPB) towards the tetragonal phase region, which is crucial for optimizing piezoelectric properties. By adjusting content of BZT and precisely controlling position of the phase boundary, the piezoelectric performance can be optimized. Domain structure is one of the key factors affecting piezoelectric performance. By using domain engineering techniques to optimize grain size and domain size, piezoelectric properties of ceramic samples have been significantly improved. Specifically, excellent piezoelectric properties (piezoelectric constant d_(33)=320 pC/N, electromechanical coupling factor kp=0.44) were obtained simultaneously for x=0.08. Based on experimental results and theoretical analysis, influence mechanisms of phase boundary engineering and domain engineering on piezoelectric properties were explored. The study shows that addition of BZT not only promotes grain growth, but also optimizes the domain structure, enabling the polarization reversal process easier, thereby improving piezoelectric properties. These research results not only provide new ideas for the design of high-performance piezoelectric ceramics, but also lay a theoretical foundation for development of related electronic devices.展开更多
To enable proper diagnosis of a patient,medical images must demonstrate no presence of noise and artifacts.The major hurdle lies in acquiring these images in such a manner that extraneous variables,causing distortions...To enable proper diagnosis of a patient,medical images must demonstrate no presence of noise and artifacts.The major hurdle lies in acquiring these images in such a manner that extraneous variables,causing distortions in the form of noise and artifacts,are kept to a bare minimum.The unexpected change realized during the acquisition process specifically attacks the integrity of the image’s quality,while indirectly attacking the effectiveness of the diagnostic process.It is thus crucial that this is attended to with maximum efficiency at the level of pertinent expertise.The solution to these challenges presents a complex dilemma at the acquisition stage,where image processing techniques must be adopted.The necessity of this mandatory image pre-processing step underpins the implementation of traditional state-of-the-art methods to create functional and robust denoising or recovery devices.This article hereby provides an extensive systematic review of the above techniques,with the purpose of presenting a systematic evaluation of their effect on medical images under three different distributions of noise,i.e.,Gaussian,Poisson,and Rician.A thorough analysis of these methods is conducted using eight evaluation parameters to highlight the unique features of each method.The covered denoising methods are essential in actual clinical scenarios where the preservation of anatomical details is crucial for accurate and safe diagnosis,such as tumor detection in MRI and vascular imaging in CT.展开更多
BACKGROUND Colon cancer represents a significant malignant neoplasm within the digestive system,characterized by a high incidence rate and substantial disease burden.The F-box protein 22(FBXO22)plays a role in forming...BACKGROUND Colon cancer represents a significant malignant neoplasm within the digestive system,characterized by a high incidence rate and substantial disease burden.The F-box protein 22(FBXO22)plays a role in forming a specific type of ubiquitin ligase subunit,which is expressed abnormally in various malignant neoplasms and shows a notable relationship with prognosis in patients with cancer.Never-theless,the function of FBXO22 in the context of colon cancer remains inade-quately elucidated.AIM To explore the role of FBXO22 in colon cancer by examining FBXO22 expression patterns and analyzing how the protein affects the prognosis in patients who have undergone surgery.METHODS Samples of cancerous and nearby normal tissues from patients with colon cancer were gathered,along with pertinent clinical data.Expression levels of the FBXO22 gene in both cancerous and paracancerous tissues were assessed through immu-nohistochemistry.The median H score served as a criterion for categorizing FBXO22 gene expression into high and low levels in cancerous tissues,and the relationship between these expression levels and various pathologic character-istics of patients,such as age,sex,and clinical stage,was analyzed.Colon cancer cell lines HCT116 and DLD-1 were used and divided into three groups:A blank control group,a negative control group,and a si-FBXO22 group.FBXO22 gene mRNA and protein expression were measured 24 hours post-transfection using real-time fluorescence quantitative polymerase chain reaction and western blotting.The proliferation capabilities of the cells in each group were assessed using the Cell Counting Kit-8 assay and 5-ethynyl-2’-deoxyuridine assay,while cellular migration and invasion abilities were evaluated using scratch healing and Transwell assays.Various online platforms,including the Timer Immune Estimation Resource,were used to analyze pan-cancer expression,promoter methylation levels,and mutation frequencies of the FBXO22 gene in colon cancer patients.Additionally,the correlation between FBXO22 gene expression,patient prognosis,immune cell infiltration,and the expression of immune molecules in the colon cancer microenvironment was investigated.The relationship between FBXO22 gene expression and chemotherapy resistance,along with the potential mechanisms of action of the FBXO22 gene,were analyzed using The Cancer Genome Atlas dataset and the Genomics of Drug Sensitivity in Cancer drug training set via R software.RESULTS Compared with normal colonic tissues,the FBXO22 gene was highly expressed in colon cancer tissues.Post-operative patients with colon cancer elevated FBXO22 reduced survival and exhibited resistance to various chemotherapeutic agents.FBXO22 expression suppresses the infiltration of anti-tumor immune cells.In vitro,FBXO22 knockdown inhibited the proliferation and migration of colon cancer cells.CONCLUSION The FBXO22 gene is a biomarker of poor prognosis in patients with colon cancer and has potential as a target for immunotherapy and overcoming chemotherapy resistance.展开更多
The functional and structural integrity of the blood-brain barrier is crucial in maintaining homeostasis in the brain microenvironment;however,the molecular mechanisms underlying the formation and function of the bloo...The functional and structural integrity of the blood-brain barrier is crucial in maintaining homeostasis in the brain microenvironment;however,the molecular mechanisms underlying the formation and function of the blood-brain barrier remain poorly understood.The major facilitator superfamily domain containing 2A has been identified as a key regulator of blood-brain barrier function.It plays a critical role in promoting and maintaining the formation and functional stability of the blood-brain barrier,in addition to the transport of lipids,such as docosahexaenoic acid,across the blood-brain barrier.Furthermore,an increasing number of studies have suggested that major facilitator superfamily domain containing 2A is involved in the molecular mechanisms of blood-brain barrier dysfunction in a variety of neurological diseases;however,little is known regarding the mechanisms by which major facilitator superfamily domain containing 2A affects the blood-brain barrier.This paper provides a comprehensive and systematic review of the close relationship between major facilitator superfamily domain containing 2A proteins and the blood-brain barrier,including their basic structures and functions,cross-linking between major facilitator superfamily domain containing 2A and the blood-brain barrier,and the in-depth studies on lipid transport and the regulation of blood-brain barrier permeability.This comprehensive systematic review contributes to an in-depth understanding of the important role of major facilitator superfamily domain containing 2A proteins in maintaining the structure and function of the blood-brain barrier and the research progress to date.This will not only help to elucidate the pathogenesis of neurological diseases,improve the accuracy of laboratory diagnosis,and optimize clinical treatment strategies,but it may also play an important role in prognostic monitoring.In addition,the effects of major facilitator superfamily domain containing 2A on blood-brain barrier leakage in various diseases and the research progress on cross-blood-brain barrier drug delivery are summarized.This review may contribute to the development of new approaches for the treatment of neurological diseases.展开更多
Domain Generation Algorithms(DGAs)continue to pose a significant threat inmodernmalware infrastructures by enabling resilient and evasive communication with Command and Control(C&C)servers.Traditional detection me...Domain Generation Algorithms(DGAs)continue to pose a significant threat inmodernmalware infrastructures by enabling resilient and evasive communication with Command and Control(C&C)servers.Traditional detection methods-rooted in statistical heuristics,feature engineering,and shallow machine learning-struggle to adapt to the increasing sophistication,linguistic mimicry,and adversarial variability of DGA variants.The emergence of Large Language Models(LLMs)marks a transformative shift in this landscape.Leveraging deep contextual understanding,semantic generalization,and few-shot learning capabilities,LLMs such as BERT,GPT,and T5 have shown promising results in detecting both character-based and dictionary-based DGAs,including previously unseen(zeroday)variants.This paper provides a comprehensive and critical review of LLM-driven DGA detection,introducing a structured taxonomy of LLM architectures,evaluating the linguistic and behavioral properties of benchmark datasets,and comparing recent detection frameworks across accuracy,latency,robustness,and multilingual performance.We also highlight key limitations,including challenges in adversarial resilience,model interpretability,deployment scalability,and privacy risks.To address these gaps,we present a forward-looking research roadmap encompassing adversarial training,model compression,cross-lingual benchmarking,and real-time integration with SIEM/SOAR platforms.This survey aims to serve as a foundational resource for advancing the development of scalable,explainable,and operationally viable LLM-based DGA detection systems.展开更多
基金Supported by Hunan Provincial Natural Science Foundation of China,No.2022JJ40836the Key Project of Research and Development Plan of Hunan Province,No.2023DK2002the Postdoctoral Fellowship Program of China Postdoctoral Science Foundation,No.GZC20242045.
文摘BACKGROUND The mortality rate for severe cases of acute pancreatitis(AP),a common gastrointestinal emergency,is as high as 30%.Our previous study has shown that rutaecarpine(Rut)has a therapeutic effect on AP.AIM To investigate the role of F-box and WD repeat domain containing 11(FBXW11)in AP models and to assess whether Rut mitigates AP by regulating FBXW11.METHODS AP rat model was established and treated with Rut,followed by biochemical analysis of serum amylase and lipase,hematoxylin and eosin staining of pancreatic tissue,and immunohistochemistry detection of pancreatic Ly6G,CD11b,and myeloperoxidase.Assay kits were used to detect oxidative stress-related indicators in pancreatic tissue and inflammatory factors in serum.AR42J cells were treated with cerulein to model AP and subjected to Cell Counting Kit-8 viability assay,flow cytometry apoptosis assay,and immunofluorescence detection of reactive oxygen species to elucidate the mechanistic involvement of the enhancer of zeste homolog 2(EZH2)-FBXW11 axis in Rut-mediated protection against AP.The EZH2-histone H3 binding and H3 methylation were evaluated using co-immunoprecipitation.RESULTS Rut treatment ameliorated AP severity,as evidenced by reduced serum levels of pancreatic enzymes(amylase and lipase)and attenuated histological damage.Rut also decreased inflammatory markers(interleukin-1 beta,interleukin-6,and tumor necrosis factor alpha),tissue oxidative stress(malondialdehyde),and neutrophil infiltration(Ly6G,CD11b,and myeloperoxidase)levels in rats with AP.Moreover,Rut restored pancreatic antioxidant capacity(glutathione and superoxide dismutase).In vitro,Rut pre-incubation enhanced cell viability and suppressed cerulein-induced apoptosis and oxidative stress.Rut increased EZH2 expression while decreasing FBXW11 expression.FBXW11 overexpression eliminated the protective effect of Rut against AP.Further analysis revealed that EZH2 binds to H3 and upregulates H3 methylation levels,thereby inhibiting FBXW11 expression.CONCLUSION Collectively,our findings demonstrate that Rut ameliorates AP by upregulating EZH2,thereby enhancing H3 methylation and suppressing FBXW11 expression.
基金supported by the National Key Research and Development Program of China(No.2023YFB3712401),the National Natural Science Foundation of China(No.52274301)the Aeronautical Science Foundation of China(No.2023Z0530S6005)the Ningbo Yongjiang Talent-Introduction Programme(No.2022A-023-C).
文摘The viscosity of refining slags plays a critical role in metallurgical processes.However,obtaining accurate viscosity data remains challenging due to the complexities of high-temperature experiments,often relying on empirical models with limited predictive capabilities.This study focuses on the influence of optical basicity on viscosity in CaO-Al_(2)O_(3)-based refining slags,leveraging machine learning to address data scarcity and improve prediction accuracy.An automated framework for algorithm integration,parameter tuning,and evaluation ranking framework(Auto-APE)is employed to develop customized data-driven models for various slag systems,including CaO-Al_(2)O_(3)-SiO_(2),CaO-Al_(2)O_(3)-CaF_(2),CaO-Al_(2)O_(3)-SiO_(2)-MgO,and CaO-Al_(2)O_(3)-SiO_(2)-MgO-CaF_(2).By incorporating optical basicity as a key feature,the models achieve an average validation error of 8.0%to 15.1%,significantly outperforming traditional empirical models.Additionally,symbolic regression is introduced to rapidly construct domain-specific features,such as optical basicity-like descriptors,offering a potential breakthrough in performance prediction for small datasets.This work highlights the critical role of domain-specific knowledge in understanding and predicting viscosity,providing a robust machine learning-based approach for optimizing refining slag properties.
基金supported by grants for development of new faculty staff,Ratchadaphiseksomphot Fund,Chulalongkorn University,Thailand.
文摘Objectives This study aimed to explore the research trends,thematic structures,and core competency domains in the field of nursing-related digital and artificial intelligence(AI)technologies.Methods A bibliometric analysis was conducted in accordance with the PRISMA 2020 statement.Peer-reviewed articles published in English from 2015 to 2025 were retrieved from Scopus,Web of Science,and PubMed.Thematic clustering was conducted using the Louvain algorithm and cosine similarity.A subset of 66 frequently cited articles was then qualitatively synthesized to capture core competencies across clusters.Results A total of 83,807 articles were included for bibliometric analysis.Of these,66 articles were chosen for thematic analysis.Five major thematic clusters were identified:remote care in primary settings,oncology and palliative care,nurse education and training,safety and quality in nursing practice,and geriatric and dementia care.Additionally,four competency domains were identified:telehealth and remote communication,health systems and informatics,digital tools in practice,and AI-powered decision support.A clear shift in research focus was observed,with the emphasis transitioning from foundational digital skills before the COVID-19 pandemic to more advanced competencies during the post-pandemic digital transformation,encompassing ethical reasoning,immersive technology use,and AI integration.Conclusions Integrating digital and AI technologies is reshaping nursing practice across various thematic areas and competency domains,highlighting a transition from foundational digital tasks to AI-supported decision-making and ethically informed technology use.This study provides a structured overview of evolving competencies in digital nursing and synthesizes evidence to support future research,curriculum design,and policy planning.
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supported by the National Natural Science Foundation of China(22265021,52231007,and 12327804)the Aeronautical Science Foundation of China(2020Z056056003)Jiangxi Provincial Natural Science Foundation(20232BAB212004).
文摘The precise tuning of magnetic nanoparticle size and magnetic domains,thereby shaping magnetic properties.However,the dynamic evolution mechanisms of magnetic domain configurations in relation to electromagnetic(EM)attenuation behavior remain poorly understood.To address this gap,a thermodynamically controlled periodic coordination strategy is proposed to achieve precise modulation of magnetic nanoparticle spacing.This approach unveils the evolution of magnetic domain configurations,progressing from individual to coupled and ultimately to crosslinked domain configurations.A unique magnetic coupling phenomenon surpasses the Snoek limit in low-frequency range,which is observed through micromagnetic simulation.The crosslinked magnetic configuration achieves effective low-frequency EM wave absorption at 3.68 GHz,encompassing nearly the entire C-band.This exceptional magnetic interaction significantly enhances radar camouflage and thermal insulation properties.Additionally,a robust gradient metamaterial design extends coverage across the full band(2–40 GHz),effectively mitigating the impact of EM pollution on human health and environment.This comprehensive study elucidates the evolution mechanisms of magnetic domain configurations,addresses gaps in dynamic magnetic modulation,and provides novel insights for the development of high-performance,low-frequency EM wave absorption materials.
基金supported by the Australian Research Council Centre of Excellence in Optical Microcombs for Breakthrough Science COMBS(CE230100006)the Australian Research Council grants DP220100488 and DE230100964funded by the Australian Government.
文摘Lithium niobate(LN)has remained at the forefront of academic research and industrial applications due to its rich material properties,which include second-order nonlinear optic,electro-optic,and piezoelectric properties.A further aspect of LN’s versatility stems from the ability to engineer ferroelectric domains with micro and even nano-scale precision in LN,which provides an additional degree of freedom to design acoustic and optical devices with improved performance and is only possible in a handful of other materials.In this review paper,we provide an overview of the domain engineering techniques developed for LN,their principles,and the typical domain size and pattern uniformity they provide,which is important for devices that require high-resolution domain patterns with good reproducibility.It also highlights each technique's benefits,limitations,and adaptability for an application,along with possible improvements and future advancement prospects.Further,the review provides a brief overview of domain visualization methods,which is crucial to gain insights into domain quality/shape and explores the adaptability of the proposed domain engineering methodologies for the emerging thin-film lithium niobate on an insulator platform,which creates opportunities for developing the next generation of compact and scalable photonic integrated circuits and high frequency acoustic devices.
基金Australian Research Council Project(FL-170100117).
文摘To avoid the laborious annotation process for dense prediction tasks like semantic segmentation,unsupervised domain adaptation(UDA)methods have been proposed to leverage the abundant annotations from a source domain,such as virtual world(e.g.,3D games),and adapt models to the target domain(the real world)by narrowing the domain discrepancies.However,because of the large domain gap,directly aligning two distinct domains without considering the intermediates leads to inefficient alignment and inferior adaptation.To address this issue,we propose a novel learnable evolutionary Category Intermediates(CIs)guided UDA model named Leci,which enables the information transfer between the two domains via two processes,i.e.,Distilling and Blending.Starting from a random initialization,the CIs learn shared category-wise semantics automatically from two domains in the Distilling process.Then,the learned semantics in the CIs are sent back to blend the domain features through a residual attentive fusion(RAF)module,such that the categorywise features of both domains shift towards each other.As the CIs progressively and consistently learn from the varying feature distributions during training,they are evolutionary to guide the model to achieve category-wise feature alignment.Experiments on both GTA5 and SYNTHIA datasets demonstrate Leci's superiority over prior representative methods.
基金Supported by NSFC (No.12361027)NSF of Inner Mongolia (No.2018MS01021)+1 种基金NSF of Shandong Province (No.ZR2020QA009)Science and Technology Innovation Program for Higher Education Institutions of Shanxi Province (No.2024L533)。
文摘In this paper,we give a complete characterization of all self-adjoint domains of odd order differential operators on two intervals.These two intervals with all four endpoints are singular(one endpoint of each interval is singular or all four endpoints are regulars are the special cases).And these extensions yield"new"self-adjoint operators,which involve interactions between the two intervals.
基金Supported by the National Natural Science Foundation of China(12301101)the Guangdong Basic and Applied Basic Research Foundation(2022A1515110019 and 2020A1515110585)。
文摘In this paper,the Paley-Wiener theorem is extended to the analytic function spaces with general weights.We first generalize the theorem to weighted Hardy spaces Hp(0<p<∞)on tube domains by constructing a sequence of L^(1)functions converging to the given function and verifying their representation in the form of Fourier transform to establish the desired result of the given function.Applying this main result,we further generalize the Paley-Wiener theorem for band-limited functions to the analytic function spaces L^(p)(0<p<∞)with general weights.
基金supported by the TARCC,Welch Foundation Award(I-1724)the Decherd Foundationthe Pape Adams Foundation,NIH grants NS092616,NS127375,NS117065,NS111776。
文摘The mitogen-activated protein kinase kinase kinase kinases(MAP4Ks)signaling pathway plays a pivotal role in axonal regrowth and neuronal degeneration following insults.Whether targeting this pathway is beneficial to brain injury remains unclear.In this study,we showed that adeno-associated virus-delivery of the Citron homology domain of MAP4Ks effectively reduces traumatic brain injury-induced reactive gliosis,tauopathy,lesion size,and behavioral deficits.Pharmacological inhibition of MAP4Ks replicated the ameliorative effects observed with expression of the Citron homology domain.Mechanistically,the Citron homology domain acted as a dominant-negative mutant,impeding MAP4K-mediated phosphorylation of the dishevelled proteins and thereby controlling the Wnt/β-catenin pathway.These findings implicate a therapeutic potential of targeting MAP4Ks to alleviate the detrimental effects of traumatic brain injury.
基金National Natural Science Foundation of China (52202139, 52072178)。
文摘Pb(Zr,Ti)O_(3)-Pb(Zn_(1/3)Nb_(2/3))O_(3) (PZT-PZN) based ceramics, as important piezoelectric materials, have a wide range of applications in fields such as sensors and actuators, thus the optimization of their piezoelectric properties has been a hot research topic. This study investigated the effects of phase boundary engineering and domain engineering on (1-x)[0.8Pb(Zr_(0.5)Ti_(0.5))O_(3)-0.2Pb(Zn_(1/3)Nb_(2/3))O_(3)]-xBi(Zn_(0.5)Ti_(0.5))O_(3) ((1-x)(0.8PZT-0.2PZN)- xBZT) ceramic to obtain excellent piezoelectric properties. The crystal phase structure and microstructure of ceramic samples were characterized. The results showed that all samples had a pure perovskite structure, and the addition of BZT gradually increased the grain size. The addition of BZT caused a phase transition in ceramic samples from the morphotropic phase boundary (MPB) towards the tetragonal phase region, which is crucial for optimizing piezoelectric properties. By adjusting content of BZT and precisely controlling position of the phase boundary, the piezoelectric performance can be optimized. Domain structure is one of the key factors affecting piezoelectric performance. By using domain engineering techniques to optimize grain size and domain size, piezoelectric properties of ceramic samples have been significantly improved. Specifically, excellent piezoelectric properties (piezoelectric constant d_(33)=320 pC/N, electromechanical coupling factor kp=0.44) were obtained simultaneously for x=0.08. Based on experimental results and theoretical analysis, influence mechanisms of phase boundary engineering and domain engineering on piezoelectric properties were explored. The study shows that addition of BZT not only promotes grain growth, but also optimizes the domain structure, enabling the polarization reversal process easier, thereby improving piezoelectric properties. These research results not only provide new ideas for the design of high-performance piezoelectric ceramics, but also lay a theoretical foundation for development of related electronic devices.
文摘To enable proper diagnosis of a patient,medical images must demonstrate no presence of noise and artifacts.The major hurdle lies in acquiring these images in such a manner that extraneous variables,causing distortions in the form of noise and artifacts,are kept to a bare minimum.The unexpected change realized during the acquisition process specifically attacks the integrity of the image’s quality,while indirectly attacking the effectiveness of the diagnostic process.It is thus crucial that this is attended to with maximum efficiency at the level of pertinent expertise.The solution to these challenges presents a complex dilemma at the acquisition stage,where image processing techniques must be adopted.The necessity of this mandatory image pre-processing step underpins the implementation of traditional state-of-the-art methods to create functional and robust denoising or recovery devices.This article hereby provides an extensive systematic review of the above techniques,with the purpose of presenting a systematic evaluation of their effect on medical images under three different distributions of noise,i.e.,Gaussian,Poisson,and Rician.A thorough analysis of these methods is conducted using eight evaluation parameters to highlight the unique features of each method.The covered denoising methods are essential in actual clinical scenarios where the preservation of anatomical details is crucial for accurate and safe diagnosis,such as tumor detection in MRI and vascular imaging in CT.
基金The study was reviewed and approved by institutional ethics board of Affiliated Hospital of Hebei Engineering University(No.:2024[K]005-01).
文摘BACKGROUND Colon cancer represents a significant malignant neoplasm within the digestive system,characterized by a high incidence rate and substantial disease burden.The F-box protein 22(FBXO22)plays a role in forming a specific type of ubiquitin ligase subunit,which is expressed abnormally in various malignant neoplasms and shows a notable relationship with prognosis in patients with cancer.Never-theless,the function of FBXO22 in the context of colon cancer remains inade-quately elucidated.AIM To explore the role of FBXO22 in colon cancer by examining FBXO22 expression patterns and analyzing how the protein affects the prognosis in patients who have undergone surgery.METHODS Samples of cancerous and nearby normal tissues from patients with colon cancer were gathered,along with pertinent clinical data.Expression levels of the FBXO22 gene in both cancerous and paracancerous tissues were assessed through immu-nohistochemistry.The median H score served as a criterion for categorizing FBXO22 gene expression into high and low levels in cancerous tissues,and the relationship between these expression levels and various pathologic character-istics of patients,such as age,sex,and clinical stage,was analyzed.Colon cancer cell lines HCT116 and DLD-1 were used and divided into three groups:A blank control group,a negative control group,and a si-FBXO22 group.FBXO22 gene mRNA and protein expression were measured 24 hours post-transfection using real-time fluorescence quantitative polymerase chain reaction and western blotting.The proliferation capabilities of the cells in each group were assessed using the Cell Counting Kit-8 assay and 5-ethynyl-2’-deoxyuridine assay,while cellular migration and invasion abilities were evaluated using scratch healing and Transwell assays.Various online platforms,including the Timer Immune Estimation Resource,were used to analyze pan-cancer expression,promoter methylation levels,and mutation frequencies of the FBXO22 gene in colon cancer patients.Additionally,the correlation between FBXO22 gene expression,patient prognosis,immune cell infiltration,and the expression of immune molecules in the colon cancer microenvironment was investigated.The relationship between FBXO22 gene expression and chemotherapy resistance,along with the potential mechanisms of action of the FBXO22 gene,were analyzed using The Cancer Genome Atlas dataset and the Genomics of Drug Sensitivity in Cancer drug training set via R software.RESULTS Compared with normal colonic tissues,the FBXO22 gene was highly expressed in colon cancer tissues.Post-operative patients with colon cancer elevated FBXO22 reduced survival and exhibited resistance to various chemotherapeutic agents.FBXO22 expression suppresses the infiltration of anti-tumor immune cells.In vitro,FBXO22 knockdown inhibited the proliferation and migration of colon cancer cells.CONCLUSION The FBXO22 gene is a biomarker of poor prognosis in patients with colon cancer and has potential as a target for immunotherapy and overcoming chemotherapy resistance.
基金supported by the National Natural Science Foundation of China,No.82104412(to TD)Shaanxi Provincial Key R&D Program,No.2023-YBSF-165(to TD)+1 种基金the Natural Science Foundation of Shaanxi Department of Science and Technology,No.2018JM7022(to FM)Shaanxi Provincial Key Industry Chain Project,No.2021ZDLSF04-11(to PW)。
文摘The functional and structural integrity of the blood-brain barrier is crucial in maintaining homeostasis in the brain microenvironment;however,the molecular mechanisms underlying the formation and function of the blood-brain barrier remain poorly understood.The major facilitator superfamily domain containing 2A has been identified as a key regulator of blood-brain barrier function.It plays a critical role in promoting and maintaining the formation and functional stability of the blood-brain barrier,in addition to the transport of lipids,such as docosahexaenoic acid,across the blood-brain barrier.Furthermore,an increasing number of studies have suggested that major facilitator superfamily domain containing 2A is involved in the molecular mechanisms of blood-brain barrier dysfunction in a variety of neurological diseases;however,little is known regarding the mechanisms by which major facilitator superfamily domain containing 2A affects the blood-brain barrier.This paper provides a comprehensive and systematic review of the close relationship between major facilitator superfamily domain containing 2A proteins and the blood-brain barrier,including their basic structures and functions,cross-linking between major facilitator superfamily domain containing 2A and the blood-brain barrier,and the in-depth studies on lipid transport and the regulation of blood-brain barrier permeability.This comprehensive systematic review contributes to an in-depth understanding of the important role of major facilitator superfamily domain containing 2A proteins in maintaining the structure and function of the blood-brain barrier and the research progress to date.This will not only help to elucidate the pathogenesis of neurological diseases,improve the accuracy of laboratory diagnosis,and optimize clinical treatment strategies,but it may also play an important role in prognostic monitoring.In addition,the effects of major facilitator superfamily domain containing 2A on blood-brain barrier leakage in various diseases and the research progress on cross-blood-brain barrier drug delivery are summarized.This review may contribute to the development of new approaches for the treatment of neurological diseases.
基金the Deanship of Scientific Research at King Khalid University for funding this work through large group under grant number(GRP.2/663/46).
文摘Domain Generation Algorithms(DGAs)continue to pose a significant threat inmodernmalware infrastructures by enabling resilient and evasive communication with Command and Control(C&C)servers.Traditional detection methods-rooted in statistical heuristics,feature engineering,and shallow machine learning-struggle to adapt to the increasing sophistication,linguistic mimicry,and adversarial variability of DGA variants.The emergence of Large Language Models(LLMs)marks a transformative shift in this landscape.Leveraging deep contextual understanding,semantic generalization,and few-shot learning capabilities,LLMs such as BERT,GPT,and T5 have shown promising results in detecting both character-based and dictionary-based DGAs,including previously unseen(zeroday)variants.This paper provides a comprehensive and critical review of LLM-driven DGA detection,introducing a structured taxonomy of LLM architectures,evaluating the linguistic and behavioral properties of benchmark datasets,and comparing recent detection frameworks across accuracy,latency,robustness,and multilingual performance.We also highlight key limitations,including challenges in adversarial resilience,model interpretability,deployment scalability,and privacy risks.To address these gaps,we present a forward-looking research roadmap encompassing adversarial training,model compression,cross-lingual benchmarking,and real-time integration with SIEM/SOAR platforms.This survey aims to serve as a foundational resource for advancing the development of scalable,explainable,and operationally viable LLM-based DGA detection systems.
