Large language models(LLMs)have demonstrated significant capabilities in semantic understanding and code generation.However,cybersecurity tasks often require prompting the adaptation of open-source models to this doma...Large language models(LLMs)have demonstrated significant capabilities in semantic understanding and code generation.However,cybersecurity tasks often require prompting the adaptation of open-source models to this domain.Despite their effectiveness,large-parameter LLMs incur substantial memory usage and runtime costs during task inference and downstreamfine-tuning for cybersecurity applications.In this study,we fine-tuned six LLMs with parameters under 4 billion using LoRA(Low-Rank Adaptation)on specific cybersecurity instruction datasets,employing evaluation metrics similar to Hackmentor.Results indicate that post-fine-tuning,smaller models achieved victory or parity rates up to 85%against larger models like Qwen-1.5-14B on cybersecurity test datasets,with the best model reaching a 90%win or tie rate compared to SecGPT.Additionally,these smaller models required significantly less computational resources,reducing fine-tuning times by up to 53%and enhancing efficiency in downstream tasks.Further validation showed that withminimal fine-tuning,our models achieved a performance gain of 21.66%to 31.32%in tactical extraction and 30.69%to 40.42%in technical extraction tasks,significantly outperforming ChatGPT.These findings highlight the potential of smaller parameter LLMs for optimizing performance and resource utilization in cybersecurity applications including methods such as technique and tactic extraction.It will facilitate future research on the application of small-parameter large language models in the cybersecurity domain.展开更多
Message structure reconstruction is a critical task in protocol reverse engineering,aiming to recover protocol field structures without access to source code.It enables important applications in network security,inclu...Message structure reconstruction is a critical task in protocol reverse engineering,aiming to recover protocol field structures without access to source code.It enables important applications in network security,including malware analysis and protocol fuzzing.However,existing methods suffer from inaccurate field boundary delineation and lack hierarchical relationship recovery,resulting in imprecise and incomplete reconstructions.In this paper,we propose ProRE,a novel method for reconstructing protocol field structures based on program execution slice embedding.ProRE extracts code slices from protocol parsing at runtime,converts them into embedding vectors using a data flow-sensitive assembly language model,and performs hierarchical clustering to recover complete protocol field structures.Evaluation on two datasets containing 12 protocols shows that ProRE achieves an average F1 score of 0.85 and a cophenetic correlation coefficient of 0.189,improving by 19%and 0.126%respectively over state-of-the-art methods(including BinPRE,Tupni,Netlifter,and QwQ-32B-preview),demonstrating significant superiority in both accuracy and completeness of field structure recovery.Case studies further validate the effectiveness of ProRE in practical malware analysis scenarios.展开更多
Structural health monitoring is important to ensuring the health and safety of dams.An inverse analysis method based on a novel hybrid fireworks algorithm (FWA) and the radial basis function (RBF) model is proposed to...Structural health monitoring is important to ensuring the health and safety of dams.An inverse analysis method based on a novel hybrid fireworks algorithm (FWA) and the radial basis function (RBF) model is proposed to diagnose the health condition of concrete dams.The damage of concrete dams is diagnosed by identifying the elastic modulus of materials using the displacement changes at different reservoir water levels.FWA is a global optimization intelligent algorithm.The proposed hybrid algorithm combines the FWA with the pattern search algorithm, which has a high capability for local optimization.Examples of benchmark functions and pseudo-experiment examples of concrete dams illustrate that the hybrid FWA improves the convergence speed and robustness of the original algorithm.To address the time consumption problem, an RBF-based surrogate model was established to replace part of the finite element method in inverse analysis.Numerical examples of concrete dams illustrate that the use of an RBF-based surrogate model significantly reduces the computation time of inverse analysis with little influence on identification accuracy.The presented hybrid FWA combined with the RBF network can quickly and accurately determine the elastic modulus of materials, and then determine the health status of the concrete dam.展开更多
Soil acidification is a major threat to agricultural sustainability in tropical and subtropical regions.Biodegradable and environmentally friendly materials,such as calcium lignosulfonate(CaLS),calcium poly(aspartic a...Soil acidification is a major threat to agricultural sustainability in tropical and subtropical regions.Biodegradable and environmentally friendly materials,such as calcium lignosulfonate(CaLS),calcium poly(aspartic acid)(PASP-Ca),and calcium polyγ-glutamic acid(γ-PGA-Ca),are known to effectively ameliorate soil acidity.However,their effectiveness in inhibiting soil acidification has not been studied.This study aimed to evaluate the effect of CaLS,PASP-Ca,andγ-PGA-Ca on the resistance of soil toward acidification as directly and indirectly(i.e.,via nitrification)caused by the application of HNO_(3)and urea,respectively.For comparison,Ca(OH)_(2)and lignin were used as the inorganic and organic controls,respectively.Among the materials,γ-PGA-Ca drove the substantial improvements in the pH buffering capacity(pHBC)of the soil and exhibited the greatest potential in inhibiting HNO_(3)-induced soil acidification via protonation of carboxyl,complexing with Al~(3+),and cation exchange processes.Under acidification induced by urea,CaLS was the optimal one in inhibiting acidification and increasing exchangeable acidity during incubation.Furthermore,the sharp reduction in the population sizes of ammonia-oxidizing bacteria(AOB)and ammonia-oxidizing archaea(AOA)confirmed the inhibition of nitrification via CaLS application.Therefore,compared to improving soil pHBC,CaLS may play a more important role in suppressing indirect acidification.Overall,γ-PGA-Ca was superior to PASP-Ca and CaLS in enhancing the soil pHBC and the its resistance to acidification induced by HNO_(3) addition,whereas CaLS was the best at suppressing urea-driven soil acidification by inhibiting nitrification.In conclusion,these results provide a reference for inhibiting soil re-acidification in intensive agricultural systems.展开更多
With widely availed clinically used radionuclides,Cer enkov luminescence imaging(CLI)has become a potential tool in the field of optical molecular imaging.However,the impulse noises introduced by high-energy gamma ray...With widely availed clinically used radionuclides,Cer enkov luminescence imaging(CLI)has become a potential tool in the field of optical molecular imaging.However,the impulse noises introduced by high-energy gamma rays that are generated during the decay of radionuclide reduce the image quality significantly,which affects the acauracy of quantitative analysis,as well as the three dimensional reconstruction.In this work,a novel denoising framework based on fuzzy dlustering and curvat ure driven difusion(CDD)is proposed to remove this kind of impulse noises.To improve the accuracy,the F u1zzy Local Information C-Means algorithm,where spatial information is evolved,is used.We evaluate the per formance of the proposed framework sys-tematically with a series of experiments,and the corresponding results demonstrate a better denoising effect than those from the commonly used median filter method.We hope this work may provide a useful data pre processing tool for CLI and its following studies.展开更多
Brown adipose tissue(BAT)is a kind of adipose tissue engaging in thermoregulatory thermogenesis,metaboloregulatory thermogenesis,and secretory.Current studies have revealed that BAT activity is negatively correlated w...Brown adipose tissue(BAT)is a kind of adipose tissue engaging in thermoregulatory thermogenesis,metaboloregulatory thermogenesis,and secretory.Current studies have revealed that BAT activity is negatively correlated with adult body weight and is considered a target tissue for the treatment of obesity and other metabolic-related diseases.Additionally,the activity of BAT presents certain differences between different ages and genders.Clinically,BAT segmentation based on PET/CT data is a reliable method for brown fat research.However,most of the current BAT segmentation methods rely on the experience of doctors.In this paper,an improved U-net network,ICA-Unet,is proposed to achieve automatic and precise segmentation of BAT.First,the traditional 2D convolution layer in the encoder is replaced with a depth-wise overparameterized convolutional(Do-Conv)layer.Second,the channel attention block is introduced between the double-layer convolution.Finally,the image information entropy(IIE)block is added in the skip connections to strengthen the edge features.Furthermore,the performance of this method is evaluated on the dataset of PET/CT images from 368 patients.The results demonstrate a strong agreement between the automatic segmentation of BAT and manual annotation by experts.The average DICE coeffcient(DSC)is 0.9057,and the average Hausdorff distance is 7.2810.Experimental results suggest that the method proposed in this paper can achieve effcient and accurate automatic BAT segmentation and satisfy the clinical requirements of BAT.展开更多
Survey of nuclear medicine To monitor the evolving landscape of nuclear medicine in China and guide the formulation of effective development strategies,the Chinese Society of Nuclear Medicine(CSNM)has been conducting ...Survey of nuclear medicine To monitor the evolving landscape of nuclear medicine in China and guide the formulation of effective development strategies,the Chinese Society of Nuclear Medicine(CSNM)has been conducting national surveys since the 1980s.Beginning in 2009,these surveys have been carried out biennially,except in 2021 due to the COVID-19 pandemic.The most recent census was completed in 2024 and collected comprehensive data for 2023 on nuclear medicine departments,personnel,equipment,and the number of patients for both diagnostic imaging and therapeutic procedures,etc.展开更多
A 68-year-old female patient was clinically diagnosed with Parkinson's disease(PD)presenting with symptoms including resting tremor in the hands(attenuated by voluntary movement),accompanied by bradykinesia,hyposm...A 68-year-old female patient was clinically diagnosed with Parkinson's disease(PD)presenting with symptoms including resting tremor in the hands(attenuated by voluntary movement),accompanied by bradykinesia,hyposmia,and excessive sweating for one year.Her symptoms showed significant improvement following Medopar administration.To further evaluate iron deposition and presynaptic dopaminergic function in the nigrostriatal system,a simultaneous positron emission tomography/magnetic resonance imaging(PET/MRI)study using quantitative susceptibility mapping(QSM)and ^(18)F-2-carbomethoxy-8-(3-fluoropropyl)-3-(4-iodophenyl)tropane(^(18)F-FP-CIT)PET,which targets dopamine transporters(DAT),was performed.This integrated PET/MRI approach demonstrated an association between increased iron deposition and dopaminergic dysfunction within the nigrostriatal system in PD.This study underscores the value of simultaneous multimodal imaging in elucidating the concurrent pathological processes of iron dyshomeostasis and dopaminergic degeneration in PD,potentially offering insights for diagnosis and mechanistic understanding.展开更多
Osteoporosis is caused by an osteoclast activation mechanism.People suffering from osteoporosis are prone to bone defects.Increasing evidence indicates that scavenging reactive oxygen species(ROS)can inhibit receptor ...Osteoporosis is caused by an osteoclast activation mechanism.People suffering from osteoporosis are prone to bone defects.Increasing evidence indicates that scavenging reactive oxygen species(ROS)can inhibit receptor activator of nuclear factorκB ligand(RANKL)-induced osteoclastogenesis and suppress ovariectomy-induced osteoporosis.It is critical to develop biomaterials with antioxidant properties to modulate osteoclast activity for treating osteoporotic bone defects.Previous studies have shown that manganese(Mn)can improve bone regeneration,and Mn supplementation may treat osteoporosis.However,the effect of Mn on osteoclasts and the role of Mn in osteoporotic bone defects remain unclear.In present research,a model bioceramic,Mn-containedβ-tricalcium phosphate(Mn-TCP)was prepared by introducing Mn intoβ-TCP.The introduction of Mn intoβ-TCP significantly improved the scavenging of oxygen radicals and nitrogen radicals,demonstrating that Mn-TCP bioceramics might have antioxidant properties.The in vitro and in vivo findings revealed that Mn^(2+)ions released from Mn-TCP bioceramics could distinctly inhibit the formation and function of osteoclasts,promote the differentiation of osteoblasts,and accelerate bone regeneration under osteoporotic conditions in vivo.Mechanistically,Mn-TCP bioceramics inhibited osteoclastogenesis and promoted the regeneration of osteoporotic bone defects by scavenging ROS via Nrf2 activation.These results suggest that Mn-containing bioceramics with osteoconductivity,ROS scavenging and bone resorption inhibition abilities may be an ideal biomaterial for the treatment of osteoporotic bone defect.展开更多
文摘Large language models(LLMs)have demonstrated significant capabilities in semantic understanding and code generation.However,cybersecurity tasks often require prompting the adaptation of open-source models to this domain.Despite their effectiveness,large-parameter LLMs incur substantial memory usage and runtime costs during task inference and downstreamfine-tuning for cybersecurity applications.In this study,we fine-tuned six LLMs with parameters under 4 billion using LoRA(Low-Rank Adaptation)on specific cybersecurity instruction datasets,employing evaluation metrics similar to Hackmentor.Results indicate that post-fine-tuning,smaller models achieved victory or parity rates up to 85%against larger models like Qwen-1.5-14B on cybersecurity test datasets,with the best model reaching a 90%win or tie rate compared to SecGPT.Additionally,these smaller models required significantly less computational resources,reducing fine-tuning times by up to 53%and enhancing efficiency in downstream tasks.Further validation showed that withminimal fine-tuning,our models achieved a performance gain of 21.66%to 31.32%in tactical extraction and 30.69%to 40.42%in technical extraction tasks,significantly outperforming ChatGPT.These findings highlight the potential of smaller parameter LLMs for optimizing performance and resource utilization in cybersecurity applications including methods such as technique and tactic extraction.It will facilitate future research on the application of small-parameter large language models in the cybersecurity domain.
文摘Message structure reconstruction is a critical task in protocol reverse engineering,aiming to recover protocol field structures without access to source code.It enables important applications in network security,including malware analysis and protocol fuzzing.However,existing methods suffer from inaccurate field boundary delineation and lack hierarchical relationship recovery,resulting in imprecise and incomplete reconstructions.In this paper,we propose ProRE,a novel method for reconstructing protocol field structures based on program execution slice embedding.ProRE extracts code slices from protocol parsing at runtime,converts them into embedding vectors using a data flow-sensitive assembly language model,and performs hierarchical clustering to recover complete protocol field structures.Evaluation on two datasets containing 12 protocols shows that ProRE achieves an average F1 score of 0.85 and a cophenetic correlation coefficient of 0.189,improving by 19%and 0.126%respectively over state-of-the-art methods(including BinPRE,Tupni,Netlifter,and QwQ-32B-preview),demonstrating significant superiority in both accuracy and completeness of field structure recovery.Case studies further validate the effectiveness of ProRE in practical malware analysis scenarios.
基金supported by the National Key Research and Development Program of China(Grants No.2016YFC0401600 and 2017YFC0404906)the National Natural Science Foundation of China(Grants No.51769033 and 51779035)the Fundamental Research Funds for the Central Universities(Grants No.DUT17ZD205 and DUT19LK14)
文摘Structural health monitoring is important to ensuring the health and safety of dams.An inverse analysis method based on a novel hybrid fireworks algorithm (FWA) and the radial basis function (RBF) model is proposed to diagnose the health condition of concrete dams.The damage of concrete dams is diagnosed by identifying the elastic modulus of materials using the displacement changes at different reservoir water levels.FWA is a global optimization intelligent algorithm.The proposed hybrid algorithm combines the FWA with the pattern search algorithm, which has a high capability for local optimization.Examples of benchmark functions and pseudo-experiment examples of concrete dams illustrate that the hybrid FWA improves the convergence speed and robustness of the original algorithm.To address the time consumption problem, an RBF-based surrogate model was established to replace part of the finite element method in inverse analysis.Numerical examples of concrete dams illustrate that the use of an RBF-based surrogate model significantly reduces the computation time of inverse analysis with little influence on identification accuracy.The presented hybrid FWA combined with the RBF network can quickly and accurately determine the elastic modulus of materials, and then determine the health status of the concrete dam.
基金supported by the Major project of Ministry of Agriculture and Rural Affairs of the People’s Republic of China(No.NK2022180401)the major project of Ministry of Agriculture and Rural Affairs of the People’s Republic of China(No.NK2022180404)。
文摘Soil acidification is a major threat to agricultural sustainability in tropical and subtropical regions.Biodegradable and environmentally friendly materials,such as calcium lignosulfonate(CaLS),calcium poly(aspartic acid)(PASP-Ca),and calcium polyγ-glutamic acid(γ-PGA-Ca),are known to effectively ameliorate soil acidity.However,their effectiveness in inhibiting soil acidification has not been studied.This study aimed to evaluate the effect of CaLS,PASP-Ca,andγ-PGA-Ca on the resistance of soil toward acidification as directly and indirectly(i.e.,via nitrification)caused by the application of HNO_(3)and urea,respectively.For comparison,Ca(OH)_(2)and lignin were used as the inorganic and organic controls,respectively.Among the materials,γ-PGA-Ca drove the substantial improvements in the pH buffering capacity(pHBC)of the soil and exhibited the greatest potential in inhibiting HNO_(3)-induced soil acidification via protonation of carboxyl,complexing with Al~(3+),and cation exchange processes.Under acidification induced by urea,CaLS was the optimal one in inhibiting acidification and increasing exchangeable acidity during incubation.Furthermore,the sharp reduction in the population sizes of ammonia-oxidizing bacteria(AOB)and ammonia-oxidizing archaea(AOA)confirmed the inhibition of nitrification via CaLS application.Therefore,compared to improving soil pHBC,CaLS may play a more important role in suppressing indirect acidification.Overall,γ-PGA-Ca was superior to PASP-Ca and CaLS in enhancing the soil pHBC and the its resistance to acidification induced by HNO_(3) addition,whereas CaLS was the best at suppressing urea-driven soil acidification by inhibiting nitrification.In conclusion,these results provide a reference for inhibiting soil re-acidification in intensive agricultural systems.
基金the Program of the National Natural Science Foundation of China under Grant Nos.61701403,61601363,11571012,61372046 and 61640418the Natural Science Basic Research Plan in Shaanxi Province of China under Grant Nos.2017JQ6006 and 2017JQ6017.
文摘With widely availed clinically used radionuclides,Cer enkov luminescence imaging(CLI)has become a potential tool in the field of optical molecular imaging.However,the impulse noises introduced by high-energy gamma rays that are generated during the decay of radionuclide reduce the image quality significantly,which affects the acauracy of quantitative analysis,as well as the three dimensional reconstruction.In this work,a novel denoising framework based on fuzzy dlustering and curvat ure driven difusion(CDD)is proposed to remove this kind of impulse noises.To improve the accuracy,the F u1zzy Local Information C-Means algorithm,where spatial information is evolved,is used.We evaluate the per formance of the proposed framework sys-tematically with a series of experiments,and the corresponding results demonstrate a better denoising effect than those from the commonly used median filter method.We hope this work may provide a useful data pre processing tool for CLI and its following studies.
基金supported in part by the National Natural Science Foundation of China(61701403,82122033,81871379)National Key Research and Development Program of China(2016YFC0103804,2019YFC1521103,2020YFC1523301,2019YFC-1521102)+3 种基金Key R&D Projects in Shaanxi Province(2019ZDLSF07-02,2019ZDLGY10-01)Key R&D Projects in Qinghai Province(2020-SF-143)China Post-doctoral Science Foundation(2018M643719)Young Talent Support Program of the Shaanxi Association for Science and Technology(20190107).
文摘Brown adipose tissue(BAT)is a kind of adipose tissue engaging in thermoregulatory thermogenesis,metaboloregulatory thermogenesis,and secretory.Current studies have revealed that BAT activity is negatively correlated with adult body weight and is considered a target tissue for the treatment of obesity and other metabolic-related diseases.Additionally,the activity of BAT presents certain differences between different ages and genders.Clinically,BAT segmentation based on PET/CT data is a reliable method for brown fat research.However,most of the current BAT segmentation methods rely on the experience of doctors.In this paper,an improved U-net network,ICA-Unet,is proposed to achieve automatic and precise segmentation of BAT.First,the traditional 2D convolution layer in the encoder is replaced with a depth-wise overparameterized convolutional(Do-Conv)layer.Second,the channel attention block is introduced between the double-layer convolution.Finally,the image information entropy(IIE)block is added in the skip connections to strengthen the edge features.Furthermore,the performance of this method is evaluated on the dataset of PET/CT images from 368 patients.The results demonstrate a strong agreement between the automatic segmentation of BAT and manual annotation by experts.The average DICE coeffcient(DSC)is 0.9057,and the average Hausdorff distance is 7.2810.Experimental results suggest that the method proposed in this paper can achieve effcient and accurate automatic BAT segmentation and satisfy the clinical requirements of BAT.
文摘Survey of nuclear medicine To monitor the evolving landscape of nuclear medicine in China and guide the formulation of effective development strategies,the Chinese Society of Nuclear Medicine(CSNM)has been conducting national surveys since the 1980s.Beginning in 2009,these surveys have been carried out biennially,except in 2021 due to the COVID-19 pandemic.The most recent census was completed in 2024 and collected comprehensive data for 2023 on nuclear medicine departments,personnel,equipment,and the number of patients for both diagnostic imaging and therapeutic procedures,etc.
文摘A 68-year-old female patient was clinically diagnosed with Parkinson's disease(PD)presenting with symptoms including resting tremor in the hands(attenuated by voluntary movement),accompanied by bradykinesia,hyposmia,and excessive sweating for one year.Her symptoms showed significant improvement following Medopar administration.To further evaluate iron deposition and presynaptic dopaminergic function in the nigrostriatal system,a simultaneous positron emission tomography/magnetic resonance imaging(PET/MRI)study using quantitative susceptibility mapping(QSM)and ^(18)F-2-carbomethoxy-8-(3-fluoropropyl)-3-(4-iodophenyl)tropane(^(18)F-FP-CIT)PET,which targets dopamine transporters(DAT),was performed.This integrated PET/MRI approach demonstrated an association between increased iron deposition and dopaminergic dysfunction within the nigrostriatal system in PD.This study underscores the value of simultaneous multimodal imaging in elucidating the concurrent pathological processes of iron dyshomeostasis and dopaminergic degeneration in PD,potentially offering insights for diagnosis and mechanistic understanding.
基金the Key Program of National Natural Science Foundation of China(81930067)the Youth Program of National Natural Science Foundation of China(grant number 82002316)+1 种基金the Youth Cultivation Project of Army Medical University(2020XQN08)General Program of Natural Science Foundation of Chongqing(cstc2019jcyj-msxmX0176).
文摘Osteoporosis is caused by an osteoclast activation mechanism.People suffering from osteoporosis are prone to bone defects.Increasing evidence indicates that scavenging reactive oxygen species(ROS)can inhibit receptor activator of nuclear factorκB ligand(RANKL)-induced osteoclastogenesis and suppress ovariectomy-induced osteoporosis.It is critical to develop biomaterials with antioxidant properties to modulate osteoclast activity for treating osteoporotic bone defects.Previous studies have shown that manganese(Mn)can improve bone regeneration,and Mn supplementation may treat osteoporosis.However,the effect of Mn on osteoclasts and the role of Mn in osteoporotic bone defects remain unclear.In present research,a model bioceramic,Mn-containedβ-tricalcium phosphate(Mn-TCP)was prepared by introducing Mn intoβ-TCP.The introduction of Mn intoβ-TCP significantly improved the scavenging of oxygen radicals and nitrogen radicals,demonstrating that Mn-TCP bioceramics might have antioxidant properties.The in vitro and in vivo findings revealed that Mn^(2+)ions released from Mn-TCP bioceramics could distinctly inhibit the formation and function of osteoclasts,promote the differentiation of osteoblasts,and accelerate bone regeneration under osteoporotic conditions in vivo.Mechanistically,Mn-TCP bioceramics inhibited osteoclastogenesis and promoted the regeneration of osteoporotic bone defects by scavenging ROS via Nrf2 activation.These results suggest that Mn-containing bioceramics with osteoconductivity,ROS scavenging and bone resorption inhibition abilities may be an ideal biomaterial for the treatment of osteoporotic bone defect.
