The comprehensive nonlinear flow behaviors of a ductile alloy play a significant role in the numerical analysis of its forming process. The accurate characterization of as-forged Ti-13 Nb-13 Zr alloy was conducted by ...The comprehensive nonlinear flow behaviors of a ductile alloy play a significant role in the numerical analysis of its forming process. The accurate characterization of as-forged Ti-13 Nb-13 Zr alloy was conducted by an improved intelligent algorithm, GA-SVR, the combination of genetic algorithm(GA) and support vector regression(SVR). The GA-SVR model learns from a training dataset and then is verified by a test dataset. As for the generalization ability of the solved GA-SVR model, no matter in β phase temperature range or(α+β) phase temperature range, the correlation coefficient R-values are always larger than 0.9999, and the AARE-values are always lower than 0.18%. The solved GA-SVR model accurately tracks the highly-nonlinear flow behaviors of Ti-13 Nb-13 Zr alloy. The stress-strain data expanded by this model are input into finite element solver, and the computation accuracy is improved.展开更多
AIM: To evaluate the role of the 13C-methacetin breath test(13C-MBT) in the assessment of acute liver injury in a rat model.METHODS: Acute liver injury in rats was induced by a single intraperitoneal injection of D-ga...AIM: To evaluate the role of the 13C-methacetin breath test(13C-MBT) in the assessment of acute liver injury in a rat model.METHODS: Acute liver injury in rats was induced by a single intraperitoneal injection of D-galactosamine(D-GalN). Forty-eight male Sprague-Dawley rats were randomly assigned to a control group(n = 8) and five model groups(each n = 8), and acute liver injury was assessed at different time points(6, 12, 24, 48 and 72 h) after D-GalN injection. The 13C-MBT, biochemical tests, 15-min retention rate of indocyanine green(ICGR15), and liver biopsy were performed and compared between the control and model groups. Correlations between parameters of the 13C-MBT(Tmax, MVmax, CUM120 and DOBmax), biochemical tests, ICGR15 and liver necrosis score were also analyzed using Spearman'scorrelation analysis.RESULTS: Tmax, MVmax, CUM120 and DOBmax, as well as most of the traditional methods, correlated with the liver necrosis score(r = 0.493, P < 0.05; r =-0.731, P < 0.01; r =-0.618, P < 0.01; r =-0.592, P < 0.01, respectively). MVmax, CUM120 and DOBmax rapidly decreased and were lower than those in the controls as early as 6 h after D-GalN injection(3.84 ± 0.84 vs 5.06 ± 0.78, P < 0.01; 3.35 ± 0.72 vs 4.21 ± 1.44, P < 0.05; 52.3 ± 20.58 vs 75.1 ± 9.57, P < 0.05, respectively) and reached the lowest point 24 h after D-GalN injection. MVmax, CUM120 and DOBmax returned to normal levels 72 h after D-GalN injection and preceded most of the traditional methods, including liver biopsy.CONCLUSION: The 13C-MBT is a sensitive tool for the timely detection of acute liver injury and early prediction of recovery in a rat model. Further clinical studies are warranted to validate its role in patients with acute liver injury.展开更多
An approach is presented to characterize the stress response of workpiece in hard machining, accounted for the effect of the initial workpiece hardness, temperature, strain and strain rate on flow stress. AISI H13 wor...An approach is presented to characterize the stress response of workpiece in hard machining, accounted for the effect of the initial workpiece hardness, temperature, strain and strain rate on flow stress. AISI H13 work tool steel was chosen to verify this methodology. The proposed flow stress model demonstrates a good agreement with data collected from published experiments. Therefore, the proposed model can be used to predict the corresponding flow stress-strain response of AISI H13 work tool steel with variation of the initial workpiece hardness in hard machining.展开更多
Sets of cold-filled SMA-13 asphalt mixture were designed by means of orthogonal design method. The bending and low temperature creep tests of the cold-filled SMA-13 asphalt mixture were carried out. The related models...Sets of cold-filled SMA-13 asphalt mixture were designed by means of orthogonal design method. The bending and low temperature creep tests of the cold-filled SMA-13 asphalt mixture were carried out. The related models of the fractal dimension and the road performance evaluation index including low temperature bending failure strain εB and bending strength RB are established by using fractal theory. The model can be used to predict the low temperature performance of cold-filled SMA-13 asphalt mixture according to the design gradation, which can reduce the test workload and improve the working efficiency, so as to provide the reference for engineering design.展开更多
Mesopelagic fish,the most important daily vertically migrating community in the oceans,are characterized by high lipid content which may obscure the interpretation of stable isotopes analysis.Demersal fish,which are i...Mesopelagic fish,the most important daily vertically migrating community in the oceans,are characterized by high lipid content which may obscure the interpretation of stable isotopes analysis.Demersal fish,which are important consumers in the food web dominated by mesopelagic fish,also have a high lipid content.Here we collected 127 fish samples from the South China Sea and evaluated the effect of lipid contents on△δ^(13)C of mesopelagic and demersal fish.In lipid-extracted mesopelagic fish,the C/N content ratio(<5.5)shows a clear correlation withΔδ^(13)C(the offset of bulk and lipid-extractedδ^(13)C values),especially in non-migratory and semi-migratory species;these values were less correlation in demersal fish.Based on our results,we suggest that mesopelagic and demersal fish in different regions of the South China Sea should be studied separately using appropriate correction models and less fit for the traditional model.Moreover,the C/N content ratio should be used cautiously for establishing the lipid normalization model,especially for the fish in migratory mesopelagic fish and demersal fish.Our results also reveal that mesopelagic fish across nearby regions could be analyzed together.The new models described here can be applied in future studies of mesopelagic and demersal fish in the South China Sea.展开更多
With the rapid development of Internet of Things technology,the sharp increase in network devices and their inherent security vulnerabilities present a stark contrast,bringing unprecedented challenges to the field of ...With the rapid development of Internet of Things technology,the sharp increase in network devices and their inherent security vulnerabilities present a stark contrast,bringing unprecedented challenges to the field of network security,especially in identifying malicious attacks.However,due to the uneven distribution of network traffic data,particularly the imbalance between attack traffic and normal traffic,as well as the imbalance between minority class attacks and majority class attacks,traditional machine learning detection algorithms have significant limitations when dealing with sparse network traffic data.To effectively tackle this challenge,we have designed a lightweight intrusion detection model based on diffusion mechanisms,named Diff-IDS,with the core objective of enhancing the model’s efficiency in parsing complex network traffic features,thereby significantly improving its detection speed and training efficiency.The model begins by finely filtering network traffic features and converting them into grayscale images,while also employing image-flipping techniques for data augmentation.Subsequently,these preprocessed images are fed into a diffusion model based on the Unet architecture for training.Once the model is trained,we fix the weights of the Unet network and propose a feature enhancement algorithm based on feature masking to further boost the model’s expressiveness.Finally,we devise an end-to-end lightweight detection strategy to streamline the model,enabling efficient lightweight detection of imbalanced samples.Our method has been subjected to multiple experimental tests on renowned network intrusion detection benchmarks,including CICIDS 2017,KDD 99,and NSL-KDD.The experimental results indicate that Diff-IDS leads in terms of detection accuracy,training efficiency,and lightweight metrics compared to the current state-of-the-art models,demonstrating exceptional detection capabilities and robustness.展开更多
基金Project(cstc2018jcyjAX0459) supported by Chongqing Basic Research and Frontier Exploration Program,ChinaProjects(2019CDQYTM027,2019CDJGFCL003,2018CDPTCG0001-6,2019CDXYCL0031) supported by the Fundamental Research Funds for the Central Universities,China
文摘The comprehensive nonlinear flow behaviors of a ductile alloy play a significant role in the numerical analysis of its forming process. The accurate characterization of as-forged Ti-13 Nb-13 Zr alloy was conducted by an improved intelligent algorithm, GA-SVR, the combination of genetic algorithm(GA) and support vector regression(SVR). The GA-SVR model learns from a training dataset and then is verified by a test dataset. As for the generalization ability of the solved GA-SVR model, no matter in β phase temperature range or(α+β) phase temperature range, the correlation coefficient R-values are always larger than 0.9999, and the AARE-values are always lower than 0.18%. The solved GA-SVR model accurately tracks the highly-nonlinear flow behaviors of Ti-13 Nb-13 Zr alloy. The stress-strain data expanded by this model are input into finite element solver, and the computation accuracy is improved.
基金Supported by Beijing Health System Advanced Health Technology Talent Cultivation Plan,No.2011-2-08
文摘AIM: To evaluate the role of the 13C-methacetin breath test(13C-MBT) in the assessment of acute liver injury in a rat model.METHODS: Acute liver injury in rats was induced by a single intraperitoneal injection of D-galactosamine(D-GalN). Forty-eight male Sprague-Dawley rats were randomly assigned to a control group(n = 8) and five model groups(each n = 8), and acute liver injury was assessed at different time points(6, 12, 24, 48 and 72 h) after D-GalN injection. The 13C-MBT, biochemical tests, 15-min retention rate of indocyanine green(ICGR15), and liver biopsy were performed and compared between the control and model groups. Correlations between parameters of the 13C-MBT(Tmax, MVmax, CUM120 and DOBmax), biochemical tests, ICGR15 and liver necrosis score were also analyzed using Spearman'scorrelation analysis.RESULTS: Tmax, MVmax, CUM120 and DOBmax, as well as most of the traditional methods, correlated with the liver necrosis score(r = 0.493, P < 0.05; r =-0.731, P < 0.01; r =-0.618, P < 0.01; r =-0.592, P < 0.01, respectively). MVmax, CUM120 and DOBmax rapidly decreased and were lower than those in the controls as early as 6 h after D-GalN injection(3.84 ± 0.84 vs 5.06 ± 0.78, P < 0.01; 3.35 ± 0.72 vs 4.21 ± 1.44, P < 0.05; 52.3 ± 20.58 vs 75.1 ± 9.57, P < 0.05, respectively) and reached the lowest point 24 h after D-GalN injection. MVmax, CUM120 and DOBmax returned to normal levels 72 h after D-GalN injection and preceded most of the traditional methods, including liver biopsy.CONCLUSION: The 13C-MBT is a sensitive tool for the timely detection of acute liver injury and early prediction of recovery in a rat model. Further clinical studies are warranted to validate its role in patients with acute liver injury.
基金supported by the Jiangxi Provincial Natural Science Foundation of China(No.550067)Jiangxi Provincial Education Commission Foundation(No.2005-26).
文摘An approach is presented to characterize the stress response of workpiece in hard machining, accounted for the effect of the initial workpiece hardness, temperature, strain and strain rate on flow stress. AISI H13 work tool steel was chosen to verify this methodology. The proposed flow stress model demonstrates a good agreement with data collected from published experiments. Therefore, the proposed model can be used to predict the corresponding flow stress-strain response of AISI H13 work tool steel with variation of the initial workpiece hardness in hard machining.
文摘Sets of cold-filled SMA-13 asphalt mixture were designed by means of orthogonal design method. The bending and low temperature creep tests of the cold-filled SMA-13 asphalt mixture were carried out. The related models of the fractal dimension and the road performance evaluation index including low temperature bending failure strain εB and bending strength RB are established by using fractal theory. The model can be used to predict the low temperature performance of cold-filled SMA-13 asphalt mixture according to the design gradation, which can reduce the test workload and improve the working efficiency, so as to provide the reference for engineering design.
基金the National Natural Science Foundation of China under contract Nos 42090043 and 41876074the National Basic Research Program(973 Program)of China under contract No.2014CB441502.
文摘Mesopelagic fish,the most important daily vertically migrating community in the oceans,are characterized by high lipid content which may obscure the interpretation of stable isotopes analysis.Demersal fish,which are important consumers in the food web dominated by mesopelagic fish,also have a high lipid content.Here we collected 127 fish samples from the South China Sea and evaluated the effect of lipid contents on△δ^(13)C of mesopelagic and demersal fish.In lipid-extracted mesopelagic fish,the C/N content ratio(<5.5)shows a clear correlation withΔδ^(13)C(the offset of bulk and lipid-extractedδ^(13)C values),especially in non-migratory and semi-migratory species;these values were less correlation in demersal fish.Based on our results,we suggest that mesopelagic and demersal fish in different regions of the South China Sea should be studied separately using appropriate correction models and less fit for the traditional model.Moreover,the C/N content ratio should be used cautiously for establishing the lipid normalization model,especially for the fish in migratory mesopelagic fish and demersal fish.Our results also reveal that mesopelagic fish across nearby regions could be analyzed together.The new models described here can be applied in future studies of mesopelagic and demersal fish in the South China Sea.
基金supported by the Key Research and Development Program of Hainan Province(Grant Nos.ZDYF2024GXJS014,ZDYF2023GXJS163)the National Natural Science Foundation of China(NSFC)(Grant Nos.62162022,62162024)Collaborative Innovation Project of Hainan University(XTCX2022XXB02).
文摘With the rapid development of Internet of Things technology,the sharp increase in network devices and their inherent security vulnerabilities present a stark contrast,bringing unprecedented challenges to the field of network security,especially in identifying malicious attacks.However,due to the uneven distribution of network traffic data,particularly the imbalance between attack traffic and normal traffic,as well as the imbalance between minority class attacks and majority class attacks,traditional machine learning detection algorithms have significant limitations when dealing with sparse network traffic data.To effectively tackle this challenge,we have designed a lightweight intrusion detection model based on diffusion mechanisms,named Diff-IDS,with the core objective of enhancing the model’s efficiency in parsing complex network traffic features,thereby significantly improving its detection speed and training efficiency.The model begins by finely filtering network traffic features and converting them into grayscale images,while also employing image-flipping techniques for data augmentation.Subsequently,these preprocessed images are fed into a diffusion model based on the Unet architecture for training.Once the model is trained,we fix the weights of the Unet network and propose a feature enhancement algorithm based on feature masking to further boost the model’s expressiveness.Finally,we devise an end-to-end lightweight detection strategy to streamline the model,enabling efficient lightweight detection of imbalanced samples.Our method has been subjected to multiple experimental tests on renowned network intrusion detection benchmarks,including CICIDS 2017,KDD 99,and NSL-KDD.The experimental results indicate that Diff-IDS leads in terms of detection accuracy,training efficiency,and lightweight metrics compared to the current state-of-the-art models,demonstrating exceptional detection capabilities and robustness.
