In this work,we proposed a strategy for the hydrolysis of native corn starch after the treatment of corn starch in an ionic liquid aqueous solution,and it is an awfully“green”and simple means to obtain starch with l...In this work,we proposed a strategy for the hydrolysis of native corn starch after the treatment of corn starch in an ionic liquid aqueous solution,and it is an awfully“green”and simple means to obtain starch with low molecular weight and amorphous state.X-ray diffraction results revealed that the natural starch crystalline region was largely disrupted by ionic liquid owing to the broken intermolecular and intramolecular hydrogen bonds.After hydrolysis,the morphology of starch changed from particles of native corn starch into little pieces,and their molecular weight could be effectively regulated during the hydrolysis process,and also the hydrolyzed starch samples exhibited decreased thermal stability with the extension of hydrolysis time.This work would counsel as a powerful tool for the development of native starch in realistic applications.展开更多
Roaming in 5G networks enables seamless global mobility but also introduces significant security risks due to legacy protocol dependencies,uneven Security Edge Protection Proxy(SEPP)deployment,and the dynamic nature o...Roaming in 5G networks enables seamless global mobility but also introduces significant security risks due to legacy protocol dependencies,uneven Security Edge Protection Proxy(SEPP)deployment,and the dynamic nature of inter-Public Land Mobile Network(inter-PLMN)signaling.Traditional rule-based defenses are inadequate for protecting cloud-native 5G core networks,particularly as roaming expands into enterprise and Internet of Things(IoT)domains.This work addresses these challenges by designing a scalable 5G Standalone testbed,generating the first intrusion detection dataset specifically tailored to roaming threats,and proposing a deep learning based intrusion detection framework for cloud-native environments.Six deep learning models including Multilayer Perceptron(MLP),one-dimensional Convolutional Neural Network(1D CNN),Autoencoder(AE),Recurrent Neural Network(RNN),Gated Recurrent Unit(GRU),and Long Short-Term Memory(LSTM)were evaluated on the dataset using both weighted and balanced metrics to account for strong class imbalance.While all models achieved over 99%accuracy,recurrent architectures such as GRU and LSTM outperformed others in balanced accuracy and macro-level evaluation,demonstrating superior effectiveness in detecting rare but high-impact attacks.These results confirm the importance of sequence-aware Artificial Intelligence(AI)models for securing roaming scenarios,where transient and contextdependent threats are common.The proposed framework provides a foundation for intelligent,adaptive intrusion detection in 5G and offers a path toward resilient security in Beyond 5G and 6G networks.展开更多
生物氧化是生物化学代谢部分的重要内容,因其复杂性和抽象性不易被学生理解。采用非变性聚丙烯酰胺凝胶电泳(Native polyacrylamide gel electrophoresis, Native-PAGE)构建了适用于本科实验教学的“线粒体复合体酶I活性方法”。从锥虫...生物氧化是生物化学代谢部分的重要内容,因其复杂性和抽象性不易被学生理解。采用非变性聚丙烯酰胺凝胶电泳(Native polyacrylamide gel electrophoresis, Native-PAGE)构建了适用于本科实验教学的“线粒体复合体酶I活性方法”。从锥虫中提取线粒体粗体物,以10μg/孔样品蛋白上样量,进行非变性聚丙烯酰胺凝胶电泳, NADH脱氢酶酶促反应时间为30分钟,可得到分辨率高、条带清晰的特异性酶活性条带。将Native-PAGE方法应用到本科生化实验中,可有效拓展教学内容,有助于教学紧密联系科研,对本科生化实验教学的开展有借鉴意义。展开更多
Tree endophytic fungi play an important role in reducing insect herbivory,either by repelling them or kill-ing them directly.Identifying which fungi show such activ-ity could lead to new environmentally friendly pesti...Tree endophytic fungi play an important role in reducing insect herbivory,either by repelling them or kill-ing them directly.Identifying which fungi show such activ-ity could lead to new environmentally friendly pesticides.In this study,the Mediterranean basin climate conditions are projected to harshen in the next decades,will increase vulnerability of tree species to pest invasions.Endophytic fungi were isolated from wood and leaves of Quercus pyr-enaica,Q.ilex and Q.suber and tested for virulence against adults of the mealworm beetle,Tenebrio molitor L.using a direct contact method.Only 3 of 111 sporulating isolates had entomopathogenic activity,all identified as Lecanicillium lecanii.The pathogenicity of L.lecanii on T.molitor resulted in a median lethal time(TL50)of 14-16 d.Compared with commercial products,L.lecanii caused faster insect death than the nematode Steinernema carpocapsae and nuclear polyhedrosis virus(no effect on T.molitor survival),and slower than Beauveria bassiana(TL50=5),Beauveria pseu-dobassiana(TL50=8d)and Bacillus thuriengensis(80%mortality first day after inoculation).Mortality was also accelerated under water stress,reducing TL50 by an addi-tional 33%.Remarkably,water stress alone had a comparable effect on mortality to that of L.lecanii isolates.This study confirms T.molitor as a good model insect for pathogenicity testing and agrees with management policies proposed in the EU Green Deal.展开更多
Exotic tree species,though widely used in forestry and restoration projects,pose great threats to local ecosystems.They need to be replaced with native species from natural forests.We hypothesized that natural forests...Exotic tree species,though widely used in forestry and restoration projects,pose great threats to local ecosystems.They need to be replaced with native species from natural forests.We hypothesized that natural forests contain large,fast-growing,dominant native tree species that are suitable for specific topographic conditions in forestry.We tested this hypothesis using data from a 50-ha forest dynamics plot in subtropical China.We classified the plot into the ridge,slope,and valley habitats and found that 34/87 species had significant associations with at least one topographic habitat.There were 90 tree species with a maximum diameter≥30 cm,and their abundances varied widely in all habitat types.In all habitat types,for most species,rate of biomass gain due to recruitment was<1%of its original biomass,and rate of biomass gain due to tree growth was between 1 and 5%of its original biomass.For most species,biomass loss due to tree mortality was not significantly different than biomass gain due to recruitment,but the resulting net biomass increment rates did not significantly differ from zero.The time required to reach a diameter of 30 cm from 1 cm diameter for Altingia chinensis in the slope habitat,for Quercus chungii and Morella rubra in the ridge habitat and for Castanopsis carlesii in all habitats could be as short as 30 years in our simulations based on actual distributions of tree growth observed in the forest.Principal component analyses of maximum diameter,abundance and net biomass increment rates suggested several species were worthy of further tests for use in forestry.Our study provides an example for screening native tree species from natural forests for forestry.Because native tree species are better for local ecosystems,our study will also contribute to biodiversity conservation in plantations.展开更多
N-methyl-D-aspartate receptors(NMDARs)play crucial roles in neuronal plasticity and brain function by sensing key neurotransmitters,such as glutamate and glycine.In a tour-de-force,Zhang et al.[1]provide the first ima...N-methyl-D-aspartate receptors(NMDARs)play crucial roles in neuronal plasticity and brain function by sensing key neurotransmitters,such as glutamate and glycine.In a tour-de-force,Zhang et al.[1]provide the first images of native NMDARs directly extracted from rat brains,revealing key aspects of NMDAR assembly and diversity.展开更多
Although mollusks represent Earth’s second most diverse invertebrate group,their natural history and ecology are still scarcely known.The compilation of non-traditional data,such as those from citizen science,represe...Although mollusks represent Earth’s second most diverse invertebrate group,their natural history and ecology are still scarcely known.The compilation of non-traditional data,such as those from citizen science,represents an alternative to fill these gaps,particularly on striking land snail species such as Macrocyclis peruvianus.Based on long-term citizen science,we aimed to update and describe some basic ecological aspects,such as the distribution and protected area types used by M.peruvianus.We performed pairwise comparisons to test potential changes in occurrence and occupancy among administrative regions,forest types,and protected area types using chi-squared tests.The citizen scientists were also asked to provide the number of M.peruvianus individuals observed and the tree species that dominated their habitat.Thus,we tested if the number of land snails found by citizen scientists could be related to forest and protected area types using a generalized linear mixed model.We expanded the northern distributional limit,with Nothofagus,evergreen,and mixed forests far the most frequented by M.peruvianus.Parallelly,the occurrence of M.peruvianus in official protected areas(65.73%)was significantly higher than in privately owned areas.Moreover,we did not find associations between forest and protected area types with the number of M.peruvianus recorded.Although citizen science is a helpful method for obtaining novel information regarding the ecology of neglected species such as M.peruvianus,it also introduces spatial and occurrence biases explained by the access and attractiveness of the officially protected areas compared to privately owned patches of native forest.展开更多
3D laser scanning technology is widely used in underground openings for high-precision,rapid,and nondestructive structural evaluations.Segmenting large 3D point cloud datasets,particularly in coal mine roadways with m...3D laser scanning technology is widely used in underground openings for high-precision,rapid,and nondestructive structural evaluations.Segmenting large 3D point cloud datasets,particularly in coal mine roadways with multi-scale targets,remains challenging.This paper proposes an enhanced segmentation method integrating improved PointNet++with a coverage-voted strategy.The coverage-voted strategy reduces data while preserving multi-scale target topology.The segmentation is achieved using an enhanced PointNet++algorithm with a normalization preprocessing head,resulting in a 94%accuracy for common supporting components.Ablation experiments show that the preprocessing head and coverage strategies increase segmentation accuracy by 20%and 2%,respectively,and improve Intersection over Union(IoU)for bearing plate segmentation by 58%and 20%.The accuracy of the current pretraining segmentation model may be affected by variations in surface support components,but it can be readily enhanced through re-optimization with additional labeled point cloud data.This proposed method,combined with a previously developed machine learning model that links rock bolt load and the deformation field of its bearing plate,provides a robust technique for simultaneously measuring the load of multiple rock bolts in a single laser scan.展开更多
Non-typhoid Salmonella is a common foodborne infection.[1]In the setting of immunosuppression,the classical symptom of diarrhea,that is an immune defense mechanism,may be absent,[2,3]allowing the bacteria to hematogen...Non-typhoid Salmonella is a common foodborne infection.[1]In the setting of immunosuppression,the classical symptom of diarrhea,that is an immune defense mechanism,may be absent,[2,3]allowing the bacteria to hematogenous spread and settle in other organs.[4,5]As a result,in the setting of acute pericarditis in immunosuppressed patients,a bacterial etiology must always be considered,which requires pericardiocentesis to complete drainage and pathogen identification.展开更多
Group B Streptococcus(GBS;Streptococcus agalactiae)is a gram-positive coccus that colonizes the gastrointestinal and genital tracts in adults,as well as the upper respiratory tract in infants.While it has been thought...Group B Streptococcus(GBS;Streptococcus agalactiae)is a gram-positive coccus that colonizes the gastrointestinal and genital tracts in adults,as well as the upper respiratory tract in infants.While it has been thought that GBS only results in invasive disease in pregnant females and neonates,recent literature has suggested an increasing incidence of invasive GBS among non-pregnant individuals within the United States.展开更多
The goal of this project is to use the Semantic Web Technologies and Data Mining for disease diagnosis to assist health care professionals regarding the possible medication and drug to prescribe (Drug recommendation) ...The goal of this project is to use the Semantic Web Technologies and Data Mining for disease diagnosis to assist health care professionals regarding the possible medication and drug to prescribe (Drug recommendation) according to the features of the patient. Numerous Decision Support Systems (DSS) and Expert Systems allow medical collaboration, like in the differential diagnosis specific or general. But, a medical recommendation system using both Semantic Web technologies and Data mining has not yet been developed which initiated this work. However, it should be mentioned that there are several system references about medicine or active ingredient interactions, but their final goal is not the Drug recommendation which uses above technologies. With this project we try to provide an assistant to the doctor for better recommendations. The patient will also able to use this system for explanation of drugs, food interaction and side effects of corresponding drugs.展开更多
With the rapid expansion of the Internet of Things(IoT),user data has experienced exponential growth,leading to increasing concerns about the security and integrity of data stored in the cloud.Traditional schemes rely...With the rapid expansion of the Internet of Things(IoT),user data has experienced exponential growth,leading to increasing concerns about the security and integrity of data stored in the cloud.Traditional schemes relying on untrusted third-party auditors suffer from both security and efficiency issues,while existing decentralized blockchain-based auditing solutions still face shortcomings in correctness and security.This paper proposes an improved blockchain-based cloud auditing scheme,with the following core contributions:Identifying critical logical contradictions in the original scheme,thereby establishing the foundation for the correctness of cloud auditing;Designing an enhanced mechanism that integrates multiple hashing with dynamic aggregate signatures,binding encrypted blocks through bilinear pairings and BLS signatures,and improving the scheme by setting parameters based on the Computational Diffie-Hellman(CDH)problem,significantly strengthening data integrity protection and anti-forgery capabilities;Introducing a random challenge mechanism and dynamic parameter adjustment strategy,effectively resisting various attacks such as forgery,tampering,and deletion,significantly improving the detection probability of malicious Cloud Service Providers(CSPs),and significantly reducing the proof generation overhead for CSPswhilemaintaining the same computational cost forDataOwners.Theoretical analysis and performance evaluation experiments demonstrate that the proposed scheme achieves significant improvements in both security and efficiency.Finally,the paper explores potential applications of the Enhanced Security Scheme in fields such as healthcare,drone swarms,and government office attendance systems,providing an effective approach for building secure,efficient,and decentralized cloud auditing systems.展开更多
文摘In this work,we proposed a strategy for the hydrolysis of native corn starch after the treatment of corn starch in an ionic liquid aqueous solution,and it is an awfully“green”and simple means to obtain starch with low molecular weight and amorphous state.X-ray diffraction results revealed that the natural starch crystalline region was largely disrupted by ionic liquid owing to the broken intermolecular and intramolecular hydrogen bonds.After hydrolysis,the morphology of starch changed from particles of native corn starch into little pieces,and their molecular weight could be effectively regulated during the hydrolysis process,and also the hydrolyzed starch samples exhibited decreased thermal stability with the extension of hydrolysis time.This work would counsel as a powerful tool for the development of native starch in realistic applications.
基金supported by Institute of Information&communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(RS-2024-00441484,Development of Open Roaming Technology for Private 5G Network)。
文摘Roaming in 5G networks enables seamless global mobility but also introduces significant security risks due to legacy protocol dependencies,uneven Security Edge Protection Proxy(SEPP)deployment,and the dynamic nature of inter-Public Land Mobile Network(inter-PLMN)signaling.Traditional rule-based defenses are inadequate for protecting cloud-native 5G core networks,particularly as roaming expands into enterprise and Internet of Things(IoT)domains.This work addresses these challenges by designing a scalable 5G Standalone testbed,generating the first intrusion detection dataset specifically tailored to roaming threats,and proposing a deep learning based intrusion detection framework for cloud-native environments.Six deep learning models including Multilayer Perceptron(MLP),one-dimensional Convolutional Neural Network(1D CNN),Autoencoder(AE),Recurrent Neural Network(RNN),Gated Recurrent Unit(GRU),and Long Short-Term Memory(LSTM)were evaluated on the dataset using both weighted and balanced metrics to account for strong class imbalance.While all models achieved over 99%accuracy,recurrent architectures such as GRU and LSTM outperformed others in balanced accuracy and macro-level evaluation,demonstrating superior effectiveness in detecting rare but high-impact attacks.These results confirm the importance of sequence-aware Artificial Intelligence(AI)models for securing roaming scenarios,where transient and contextdependent threats are common.The proposed framework provides a foundation for intelligent,adaptive intrusion detection in 5G and offers a path toward resilient security in Beyond 5G and 6G networks.
基金supported by LIFE project MYCORESTORE“Innovative use of mycological resources for resilient and productive Mediterranean forests threatened by climate change,LIFE18 CCA/ES/001110”projects VA178P23 and VA208P20 funded by JCYL(Spain),both co-financed by FEDER(UE)budget.
文摘Tree endophytic fungi play an important role in reducing insect herbivory,either by repelling them or kill-ing them directly.Identifying which fungi show such activ-ity could lead to new environmentally friendly pesticides.In this study,the Mediterranean basin climate conditions are projected to harshen in the next decades,will increase vulnerability of tree species to pest invasions.Endophytic fungi were isolated from wood and leaves of Quercus pyr-enaica,Q.ilex and Q.suber and tested for virulence against adults of the mealworm beetle,Tenebrio molitor L.using a direct contact method.Only 3 of 111 sporulating isolates had entomopathogenic activity,all identified as Lecanicillium lecanii.The pathogenicity of L.lecanii on T.molitor resulted in a median lethal time(TL50)of 14-16 d.Compared with commercial products,L.lecanii caused faster insect death than the nematode Steinernema carpocapsae and nuclear polyhedrosis virus(no effect on T.molitor survival),and slower than Beauveria bassiana(TL50=5),Beauveria pseu-dobassiana(TL50=8d)and Bacillus thuriengensis(80%mortality first day after inoculation).Mortality was also accelerated under water stress,reducing TL50 by an addi-tional 33%.Remarkably,water stress alone had a comparable effect on mortality to that of L.lecanii isolates.This study confirms T.molitor as a good model insect for pathogenicity testing and agrees with management policies proposed in the EU Green Deal.
基金supported by the National Natural Science Foundation of China(31925027,31300455).
文摘Exotic tree species,though widely used in forestry and restoration projects,pose great threats to local ecosystems.They need to be replaced with native species from natural forests.We hypothesized that natural forests contain large,fast-growing,dominant native tree species that are suitable for specific topographic conditions in forestry.We tested this hypothesis using data from a 50-ha forest dynamics plot in subtropical China.We classified the plot into the ridge,slope,and valley habitats and found that 34/87 species had significant associations with at least one topographic habitat.There were 90 tree species with a maximum diameter≥30 cm,and their abundances varied widely in all habitat types.In all habitat types,for most species,rate of biomass gain due to recruitment was<1%of its original biomass,and rate of biomass gain due to tree growth was between 1 and 5%of its original biomass.For most species,biomass loss due to tree mortality was not significantly different than biomass gain due to recruitment,but the resulting net biomass increment rates did not significantly differ from zero.The time required to reach a diameter of 30 cm from 1 cm diameter for Altingia chinensis in the slope habitat,for Quercus chungii and Morella rubra in the ridge habitat and for Castanopsis carlesii in all habitats could be as short as 30 years in our simulations based on actual distributions of tree growth observed in the forest.Principal component analyses of maximum diameter,abundance and net biomass increment rates suggested several species were worthy of further tests for use in forestry.Our study provides an example for screening native tree species from natural forests for forestry.Because native tree species are better for local ecosystems,our study will also contribute to biodiversity conservation in plantations.
文摘N-methyl-D-aspartate receptors(NMDARs)play crucial roles in neuronal plasticity and brain function by sensing key neurotransmitters,such as glutamate and glycine.In a tour-de-force,Zhang et al.[1]provide the first images of native NMDARs directly extracted from rat brains,revealing key aspects of NMDAR assembly and diversity.
基金supported by the Agencia Nacional de Investigacion y Desarrollo(ANID)with the ANID grant[SIA 85220045].
文摘Although mollusks represent Earth’s second most diverse invertebrate group,their natural history and ecology are still scarcely known.The compilation of non-traditional data,such as those from citizen science,represents an alternative to fill these gaps,particularly on striking land snail species such as Macrocyclis peruvianus.Based on long-term citizen science,we aimed to update and describe some basic ecological aspects,such as the distribution and protected area types used by M.peruvianus.We performed pairwise comparisons to test potential changes in occurrence and occupancy among administrative regions,forest types,and protected area types using chi-squared tests.The citizen scientists were also asked to provide the number of M.peruvianus individuals observed and the tree species that dominated their habitat.Thus,we tested if the number of land snails found by citizen scientists could be related to forest and protected area types using a generalized linear mixed model.We expanded the northern distributional limit,with Nothofagus,evergreen,and mixed forests far the most frequented by M.peruvianus.Parallelly,the occurrence of M.peruvianus in official protected areas(65.73%)was significantly higher than in privately owned areas.Moreover,we did not find associations between forest and protected area types with the number of M.peruvianus recorded.Although citizen science is a helpful method for obtaining novel information regarding the ecology of neglected species such as M.peruvianus,it also introduces spatial and occurrence biases explained by the access and attractiveness of the officially protected areas compared to privately owned patches of native forest.
基金supported by the National Natural Science Foundation of China(Grant Nos.52304139,52325403)the CCTEG Coal Mining Research Institute funding(Grant No.KCYJY-2024-MS-10).
文摘3D laser scanning technology is widely used in underground openings for high-precision,rapid,and nondestructive structural evaluations.Segmenting large 3D point cloud datasets,particularly in coal mine roadways with multi-scale targets,remains challenging.This paper proposes an enhanced segmentation method integrating improved PointNet++with a coverage-voted strategy.The coverage-voted strategy reduces data while preserving multi-scale target topology.The segmentation is achieved using an enhanced PointNet++algorithm with a normalization preprocessing head,resulting in a 94%accuracy for common supporting components.Ablation experiments show that the preprocessing head and coverage strategies increase segmentation accuracy by 20%and 2%,respectively,and improve Intersection over Union(IoU)for bearing plate segmentation by 58%and 20%.The accuracy of the current pretraining segmentation model may be affected by variations in surface support components,but it can be readily enhanced through re-optimization with additional labeled point cloud data.This proposed method,combined with a previously developed machine learning model that links rock bolt load and the deformation field of its bearing plate,provides a robust technique for simultaneously measuring the load of multiple rock bolts in a single laser scan.
文摘Non-typhoid Salmonella is a common foodborne infection.[1]In the setting of immunosuppression,the classical symptom of diarrhea,that is an immune defense mechanism,may be absent,[2,3]allowing the bacteria to hematogenous spread and settle in other organs.[4,5]As a result,in the setting of acute pericarditis in immunosuppressed patients,a bacterial etiology must always be considered,which requires pericardiocentesis to complete drainage and pathogen identification.
文摘Group B Streptococcus(GBS;Streptococcus agalactiae)is a gram-positive coccus that colonizes the gastrointestinal and genital tracts in adults,as well as the upper respiratory tract in infants.While it has been thought that GBS only results in invasive disease in pregnant females and neonates,recent literature has suggested an increasing incidence of invasive GBS among non-pregnant individuals within the United States.
文摘The goal of this project is to use the Semantic Web Technologies and Data Mining for disease diagnosis to assist health care professionals regarding the possible medication and drug to prescribe (Drug recommendation) according to the features of the patient. Numerous Decision Support Systems (DSS) and Expert Systems allow medical collaboration, like in the differential diagnosis specific or general. But, a medical recommendation system using both Semantic Web technologies and Data mining has not yet been developed which initiated this work. However, it should be mentioned that there are several system references about medicine or active ingredient interactions, but their final goal is not the Drug recommendation which uses above technologies. With this project we try to provide an assistant to the doctor for better recommendations. The patient will also able to use this system for explanation of drugs, food interaction and side effects of corresponding drugs.
基金funded by the National Natural Science Foundation of China(New Design and Analysis of Fully Homomorphic Signatures,Grant No.62172436).
文摘With the rapid expansion of the Internet of Things(IoT),user data has experienced exponential growth,leading to increasing concerns about the security and integrity of data stored in the cloud.Traditional schemes relying on untrusted third-party auditors suffer from both security and efficiency issues,while existing decentralized blockchain-based auditing solutions still face shortcomings in correctness and security.This paper proposes an improved blockchain-based cloud auditing scheme,with the following core contributions:Identifying critical logical contradictions in the original scheme,thereby establishing the foundation for the correctness of cloud auditing;Designing an enhanced mechanism that integrates multiple hashing with dynamic aggregate signatures,binding encrypted blocks through bilinear pairings and BLS signatures,and improving the scheme by setting parameters based on the Computational Diffie-Hellman(CDH)problem,significantly strengthening data integrity protection and anti-forgery capabilities;Introducing a random challenge mechanism and dynamic parameter adjustment strategy,effectively resisting various attacks such as forgery,tampering,and deletion,significantly improving the detection probability of malicious Cloud Service Providers(CSPs),and significantly reducing the proof generation overhead for CSPswhilemaintaining the same computational cost forDataOwners.Theoretical analysis and performance evaluation experiments demonstrate that the proposed scheme achieves significant improvements in both security and efficiency.Finally,the paper explores potential applications of the Enhanced Security Scheme in fields such as healthcare,drone swarms,and government office attendance systems,providing an effective approach for building secure,efficient,and decentralized cloud auditing systems.
