Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technolo...Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.展开更多
On-device Artificial Intelligence(AI)accelerators capable of not only inference but also training neural network models are in increasing demand in the industrial AI field,where frequent retraining is crucial due to f...On-device Artificial Intelligence(AI)accelerators capable of not only inference but also training neural network models are in increasing demand in the industrial AI field,where frequent retraining is crucial due to frequent production changes.Batch normalization(BN)is fundamental to training convolutional neural networks(CNNs),but its implementation in compact accelerator chips remains challenging due to computational complexity,particularly in calculating statistical parameters and gradients across mini-batches.Existing accelerator architectures either compromise the training accuracy of CNNs through approximations or require substantial computational resources,limiting their practical deployment.We present a hardware-optimized BN accelerator that maintains training accuracy while significantly reducing computational overhead through three novel techniques:(1)resourcesharing for efficient resource utilization across forward and backward passes,(2)interleaved buffering for reduced dynamic random-access memory(DRAM)access latencies,and(3)zero-skipping for minimal gradient computation.Implemented on a VCU118 Field Programmable Gate Array(FPGA)on 100 MHz and validated using You Only Look Once version 2-tiny(YOLOv2-tiny)on the PASCALVisualObjectClasses(VOC)dataset,our normalization accelerator achieves a 72%reduction in processing time and 83%lower power consumption compared to a 2.4 GHz Intel Central Processing Unit(CPU)software normalization implementation,while maintaining accuracy(0.51%mean Average Precision(mAP)drop at floating-point 32 bits(FP32),1.35%at brain floating-point 16 bits(bfloat16)).When integrated into a neural processing unit(NPU),the design demonstrates 63%and 97%performance improvements over AMD CPU and Reduced Instruction Set Computing-V(RISC-V)implementations,respectively.These results confirm that our proposed BN hardware design enables efficient,high-accuracy,and power-saving on-device training for modern CNNs.Our results demonstrate that efficient hardware implementation of standard batch normalization is achievable without sacrificing accuracy,enabling practical on-device CNN training with significantly reduced computational and power requirements.展开更多
Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert judgments.Traditional models,such as the Constructive Cost Model(COCOMO II),rely h...Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert judgments.Traditional models,such as the Constructive Cost Model(COCOMO II),rely heavily on historical and accurate data.In addition,expert judgment is required to set many input parameters,which can introduce subjectivity and variability in the estimation process.Consequently,there is a need to improve the current GSD models to mitigate reliance on historical data,subjectivity in expert judgment,inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost overruns.This study introduces a novel hybrid model that synergizes the COCOMO II with Artificial Neural Networks(ANN)to address these challenges.The proposed hybrid model integrates additional GSD-based cost drivers identified through a systematic literature review and further vetted by industry experts.This article compares the effectiveness of the proposedmodelwith state-of-the-artmachine learning-basedmodels for software cost estimation.Evaluating the NASA 93 dataset by adopting twenty-six GSD-based cost drivers reveals that our hybrid model achieves superior accuracy,outperforming existing state-of-the-artmodels.The findings indicate the potential of combining COCOMO II,ANN,and additional GSD-based cost drivers to transform cost estimation in GSD.展开更多
The main aspects that require attention in tunnel design in terms of safety and economy are the precise estimation of probable ground conditions and ground behavior during construction. The variation in rock mass beha...The main aspects that require attention in tunnel design in terms of safety and economy are the precise estimation of probable ground conditions and ground behavior during construction. The variation in rock mass behavior due to tunnel excavation sequence plays an important role during the construction stage.The purpose of this research is to numerically evaluate the effect of excavation sequence on the ground behavior for the Lowari tunnel project, Pakistan. For the tunnel stability, the ground behavior observed during the actual partial face excavation sequence is compared with the top heading and bench excavation sequence. For this purpose, the intact rock parameters are used along with the characterization of rock mass joints related parameters to provide input for numerical modelling via FLAC 2D. The in-situ stresses for the numerical modelling are obtained using empirical equations. From the comparison of the two excavation sequences, it was observed that the actual excavation sequence used for Lowari tunnel construction utilized more support than the top heading and bench method. However, the actual excavation sequence provided good results in terms of stability.展开更多
In view of the accumulation of nanoplastics(NPs)in the food chain of environment and animals,and the good adsorption properties of nano-plastics to toxic substances,it is necessary to explore the influence of NPs in l...In view of the accumulation of nanoplastics(NPs)in the food chain of environment and animals,and the good adsorption properties of nano-plastics to toxic substances,it is necessary to explore the influence of NPs in living organisms.In this study,single and joint toxicological effects of polystyrene nanoplastics(PS-NPs,size 80 nm)and polychlorinated biphenyls(PCBs),were explored in freshwater aquatic animal model zebrafish(Danio rerio).Our study found that exposure to single PS-NPs induced mild acute toxicity,albeit the combined exposure of PS-NPs and polychlorinated biphenyls aggravated the toxicity of PCBs in a dose-dependent manner.Results from gene expression profiling showed that NPs exposure could activate detoxification process,resulting in a slight up-regulation of antioxidant genes(sod1,gstp1),bone development genes(bmp2,bmp4)and cardiac gene(tbx20);while PCBs suppressed the detoxification through down-regulation of these genes,and the addition of NPs will exacerbate the impact of PCBs on gene suppression.Importantly,the results of in vivo purification experiments found that NPs showed prolonged retention in liver,intestine and gills of zebrafish and they might have crossed biological barrier and accumulate in lipid-rich tissues and excretion does not appear as the significant pathway for their elimination.In conclusion,the toxic effects of polychlorinated biphenyls on chorionic protected embryos were not significant as zebrafish chorion plays an important role in resisting the invasion of pollutants;PCBs can seriously damage the bone and heart development of zebrafish,while the presence of NPs significantly enhanced the toxicity of PCBs in zebrafish,which is an alarming concern for growing NPs levels and ecological safety in aquatic environment.展开更多
With recent advancements in imaging modalities and techniques and increased recognition of the long-term impact of several structural heart disease interventions,the number of procedures has significantly increased.Wi...With recent advancements in imaging modalities and techniques and increased recognition of the long-term impact of several structural heart disease interventions,the number of procedures has significantly increased.With the increase in procedures,also comes an increase in cost.In view of this,efficient and cost-effective methods to facilitate and manage structural heart disease interventions are a necessity.Same-day discharge(SDD)after invasive cardiac procedures improves resource utilization and patient satisfaction.SDD in appropriately selected patients has become the standard of care for some invasive cardiac procedures such as percutaneous coronary interventions.This is not the case for the majority of structural heart procedures.With the coronavirus disease 2019 pandemic,safely reducing the duration of time spent within the hospital to prevent unnecessary exposure to pathogens has become a priority.In light of this,it is prudent to assess the feasibility of SDD in several structural heart procedures.In this review we highlight the feasibility of SDD in a carefully selected population,by reviewing and summarizing studies on SDD among patients undergoing left atrial appendage occlusion,patent foramen ovale/atrial septal defect closure,Mitra-clip,and trans-catheter aortic valve replacement procedures.展开更多
Ionosphereic foF2 variations are very sensitive to the seismic effect and results of ionospheric perturbations associated with earthquakes seem to very hopeful for short-term earthquake prediction. On January 18,2011 ...Ionosphereic foF2 variations are very sensitive to the seismic effect and results of ionospheric perturbations associated with earthquakes seem to very hopeful for short-term earthquake prediction. On January 18,2011 at 20: 23 UT a great earthquake( M = 7. 2)occurred in Dalbandin( 28. 73° N,63. 92° E),Pakistan. In this study,we have tried to find out the features of pre-earthquake ionospheric anomalies by using the hourly day time( 08. 00 a. m.- 05. 00 p. m.) data of critical frequency( foF2) obtained by three vertical sounding stations installed in Islamabad( 33. 78°N,73. 06°E),Multan( 32. 26°N,71. 51°E) and Karachi( 24. 89° N,67. 02° E), Pakistan. The results show the significant anomalies of foF2 in the earthquake preparation zone several days prior to the Dalbandin earthquake. It is also observed that the amplitude and frequency of foF2 anomalies are more prominent at the nearest station to the epicenter as compared to those stations near the outer margin of the earthquake preparation zone. The confidence level for ionospheric anomalies regarding the seismic signatures can be enhanced by adding the analysis of some other ionospheic parameters along with critical frequency of the layer F2.展开更多
Distributed denial of service(DDoS)attack is the most common attack that obstructs a network and makes it unavailable for a legitimate user.We proposed a deep neural network(DNN)model for the detection of DDoS attacks...Distributed denial of service(DDoS)attack is the most common attack that obstructs a network and makes it unavailable for a legitimate user.We proposed a deep neural network(DNN)model for the detection of DDoS attacks in the Software-Defined Networking(SDN)paradigm.SDN centralizes the control plane and separates it from the data plane.It simplifies a network and eliminates vendor specification of a device.Because of this open nature and centralized control,SDN can easily become a victim of DDoS attacks.We proposed a supervised Developed Deep Neural Network(DDNN)model that can classify the DDoS attack traffic and legitimate traffic.Our Developed Deep Neural Network(DDNN)model takes a large number of feature values as compared to previously proposed Machine Learning(ML)models.The proposed DNN model scans the data to find the correlated features and delivers high-quality results.The model enhances the security of SDN and has better accuracy as compared to previously proposed models.We choose the latest state-of-the-art dataset which consists of many novel attacks and overcomes all the shortcomings and limitations of the existing datasets.Our model results in a high accuracy rate of 99.76%with a low false-positive rate and 0.065%low loss rate.The accuracy increases to 99.80%as we increase the number of epochs to 100 rounds.Our proposed model classifies anomalous and normal traffic more accurately as compared to the previously proposed models.It can handle a huge amount of structured and unstructured data and can easily solve complex problems.展开更多
With the advancement of technology,shielding for terahertz(THz)electronic and communication equipment is increasingly important.The metamaterial absorption technique is mostly used to shield electromagnetic interferen...With the advancement of technology,shielding for terahertz(THz)electronic and communication equipment is increasingly important.The metamaterial absorption technique is mostly used to shield electromagnetic interference(EMI)in THz sensing technologies.The most widely used THz metamaterial absorbers suffer from their narrowband properties and the involvement of complex fabrication techniques.Materials with multifunctional properties,such as adjustable conductivity,broad bandwidth,high flexibility,and robustness,are driving future development to meet THz shielding applications.In this article,a theoretical simulation approach based on finite difference time domain(FDTD)is utilized to study the absorption and shielding characteristics of a two-dimensional(2D)MXene Ti_(3)C_(2)T_(x) metasurface absorber in the THz band.The proposed metamaterial structure is made up of a square-shaped array of MXene that is 50 nmthick and is placed on top of a silicon substrate.The bottom surface of the silicon is metalized with gold to reduce the transmission and ultimately enhance the absorption at 1–3 THz.The symmetric adjacent space between theMXene array results in a widening of bandwidth.The proposed metasurface achieves 96%absorption under normal illumination of the incident source and acquires an average of 25 dB shielding at 1 THz bandwidth,with the peak shielding reaching 65 dB.The results show that 2D MXene-based stacked metasurfaces can be proven in the realization of low-cost devices for THz shielding and sensing applications.展开更多
Metaheuristic approaches in cloud computing have shown significant results due to theirmulti-objective advantages.These approaches are now considering hybridmetaheuristics combining the relative optimized benefits of ...Metaheuristic approaches in cloud computing have shown significant results due to theirmulti-objective advantages.These approaches are now considering hybridmetaheuristics combining the relative optimized benefits of two or more algorithms resulting in the least tradeoffs among several factors.The critical factors such as execution time,throughput time,response time,energy consumption,SLA violations,communication overhead,makespan,and migration time need careful attention while designing such dynamic algorithms.To improve such factors,an optimizedmulti-objective hybrid algorithm is being proposed that combines the relative advantages of Cat Swarm Optimization(CSO)with machine learning classifiers such as Support Vector Machine(SVM).The adopted approach is based on SVMone to many classification models of machine learning that performs the classifications of various data format types in the cloud with best accuracy.In CSO,grouping phase is used to divide the data files as audio,video,image,and text which is further extended by polynomial Kernel function based on various input features and used for optimized load balancing.Overall,proposed approach works well and achieved performance efficiency in evaluated QoS metrics such as average energy consumption by 12%,migration time by 9%,and optimization time by 10%,in the presence of competitor baselines.展开更多
Effect of different Zinc doses was investigated against Erwinia carotovora ssp. atroseptica, the potato blackleg/soft rot causing organism, during 2009 and 2010 in Department of Plant Pathology and Institute of Biotec...Effect of different Zinc doses was investigated against Erwinia carotovora ssp. atroseptica, the potato blackleg/soft rot causing organism, during 2009 and 2010 in Department of Plant Pathology and Institute of Biotechnology and Genetic Engineering, The University of Agriculture, Peshawar-Pakistan. Out of 200 tested samples, 21 of them were proved to be Eca. However, these tentative Eca isolates showed some characteristics which were unexpected for Eca. We, therefore, decided to perform Polymerase Chain Reaction using Eca-specific primers, Eca1F and Eca2R for confirm identification. For disease management, at the time of sowing, pots containing 5 kg sterilized soil were applied with Zinc in four different treatments i.e. 8 mg, 10 mg, 12 mg and 14 mg along with one control. Results indicated that 12 mg (4.8 kg Zn ha-1) were better doses in controlling the disease up to 73% and increasing the yield up to 117% as compared to control plants.展开更多
Separation and purification technology is becoming increasingly important,especially with the rapid industrial development,which brings huge demands in energy and environment^([1,2]).Nano ltration(NF)membrane technolo...Separation and purification technology is becoming increasingly important,especially with the rapid industrial development,which brings huge demands in energy and environment^([1,2]).Nano ltration(NF)membrane technology is gaining more attention on the scale of ion separation and purification([3,4]),particularly,graphene oxide(GO)nanosheets have gained signi cant interest due to their simple fabrication.展开更多
Environmental issues associated with the aviation industry are getting more attention as air traffic increases.Stringent standards are imposed for fuel consumption and pollution emissions for next-generation aircraft....Environmental issues associated with the aviation industry are getting more attention as air traffic increases.Stringent standards are imposed for fuel consumption and pollution emissions for next-generation aircraft.Superconducting electrical propulsion aircraft(SEPA)have been seen as an efficient way to achieve this goal.High-temperature superconducting(HTS)devices are extensively used in the power system to supply enormous energy.Power is distributed to the different loads via a DC distribution network.However,it will generate an inrush current over ten times higher than the rated current in short-circuit state,which is very harmful to the system.Therefore,it is essential to adopt an appropriate protection scheme.This paper discusses one protection scheme that combines DC vacuum circuit breakers(DC VCB)and resistive superconducting current limiters(RSFCL)for superconducting aircraft applications.Considering problems of cost and loss,the auxiliary capacitor is pre-charged by system voltage,and mechanical elements extinguish the arc.Furthermore,combined with RSFCL,the interrupting environment is fully improved.RSFCL limits fault current,and then the VCB breaks this limited current based on creating an artificial current zero(ACZ).The prospective rated power is 8MW,rated voltage and current are 4 kV and 1 kA,respectively.In this paper,we discuss and simulate switching devices that protect SEPA.The interrupting performance of the circuit breaker is analysed in the DC short-circuit fault that occurs on the transmission line.Finally,the residual energy consumption of different situations is calculated.A comparison is made between using RSFCL with metal oxide varistor(MOV)and just using MOV.The scheme with RSFCL shows a significant advantage in energy consumption.展开更多
With the development of a distributed generation,direct current(DC)load and energy‐storage equipment,voltage‐source‐converter‐based medium‐voltage DC systems(VSC‐MVDC)have attracted more attention due to its low...With the development of a distributed generation,direct current(DC)load and energy‐storage equipment,voltage‐source‐converter‐based medium‐voltage DC systems(VSC‐MVDC)have attracted more attention due to its low power consumption,high reliability,independent power control and so on.However,VSC‐MVDC has the problem of DC fault isolation,which requires the fast‐acting DC circuit‐breakers to isolate faulty lines and ensure low cost.This problem can be solved by coordinating resistive type superconducting‐fault‐current‐limiter(R‐SFCL)and integrated‐gate‐commutated‐thyristor(IGCT)based hybrid circuit breaker.Based on this,IGCT based superconducting DC circuit breaker(SDCCB)is proposed and analysed.Combining R‐SFCL with IGCT could realise large current limiting and interruption and ensure low cost.In addition,the IGCT based hybrid DC circuit breaker(IGCT‐HDCCB)is compared with the traditional insulated gate bipolar transistor(IGBT)based hybrid DC circuit breaker(IGBT‐HDCCB)to evaluate which circuit breaker is more suitable for VSC‐MVDC.The results show that,coordination based on R‐SFCL and SDCCB,the fault current is successfully limited from 17.6 to 2.1 kA,and then inter-rupted within 3.8 ms.In addition,IGCT‐HDCCB overcomes the disadvantage that IGCT has less interrupting capacity than IGBT,retains the advantage of low cost of IGCT and is more suitable for MVDC system.展开更多
Accurate wetting characterization is crucial for the development of next‐generation superhydrophobic surfaces.Traditionally,wetting properties are measured with a contact angle goniometer(CAG)suitable for a broad ran...Accurate wetting characterization is crucial for the development of next‐generation superhydrophobic surfaces.Traditionally,wetting properties are measured with a contact angle goniometer(CAG)suitable for a broad range of surfaces.However,due to optical errors and challenges in baseline positioning,the CAG method suffers from inaccuracies on superhydrophobic surfaces.Here we present an improved version of the oscillating droplet tribometer(ODT),which can reliably assess wetting properties on superhydrophobic surfaces by measuring the frictional forces of a water‐based ferrofluid droplet oscillating in a magnetic field.We demonstrate that ODT has superior accuracy compared to CAG by measuring the wetting properties of four different superhydrophobic surfaces(commercial Glaco and Hydrobead coatings,black silicon coated with fluoropolymer,and nanostructured copper modified with lauric acid).We show that ODT can detect the small but significant changes in wetting properties caused by the thermal restructuring of surfaces that are undetectable by CAG.Even more,unlike any other wetting characterization technique,ODT features an inverse sensitivity:the more repellent the surface,the lower the error of measurement,which was demonstrated by experiments and simulations.展开更多
基金supported by the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI)the Ministry of Health&Welfare,Republic of Korea (HR22C1734)+2 种基金the National Research Foundation (NRF) of Korea (2020R1A6A1A03043539,2020M3A9D8037604,2022R1C1C1004756)(to SBL)the NRF of Korea (2022R1C1C1005741 and RS-2023-00217595)the new faculty research fund of Ajou University School of Medicine (to EJL)。
文摘Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.
基金supported by the National Research Foundation of Korea(NRF)grant for RLRC funded by the Korea government(MSIT)(No.2022R1A5A8026986,RLRC)supported by Institute of Information&Communications Technology Planning&Evaluation(IITP)grant funded by the Korea government(MSIT)(No.2020-0-01304,Development of Self-Learnable Mobile Recursive Neural Network Processor Technology)+3 种基金supported by the MSIT(Ministry of Science and ICT),Republic of Korea,under the Grand Information Technology Research Center support program(IITP-2024-2020-0-01462,Grand-ICT)supervised by the IITP(Institute for Information&Communications Technology Planning&Evaluation)supported by the Korea Technology and Information Promotion Agency for SMEs(TIPA)supported by the Korean government(Ministry of SMEs and Startups)’s Smart Manufacturing Innovation R&D(RS-2024-00434259).
文摘On-device Artificial Intelligence(AI)accelerators capable of not only inference but also training neural network models are in increasing demand in the industrial AI field,where frequent retraining is crucial due to frequent production changes.Batch normalization(BN)is fundamental to training convolutional neural networks(CNNs),but its implementation in compact accelerator chips remains challenging due to computational complexity,particularly in calculating statistical parameters and gradients across mini-batches.Existing accelerator architectures either compromise the training accuracy of CNNs through approximations or require substantial computational resources,limiting their practical deployment.We present a hardware-optimized BN accelerator that maintains training accuracy while significantly reducing computational overhead through three novel techniques:(1)resourcesharing for efficient resource utilization across forward and backward passes,(2)interleaved buffering for reduced dynamic random-access memory(DRAM)access latencies,and(3)zero-skipping for minimal gradient computation.Implemented on a VCU118 Field Programmable Gate Array(FPGA)on 100 MHz and validated using You Only Look Once version 2-tiny(YOLOv2-tiny)on the PASCALVisualObjectClasses(VOC)dataset,our normalization accelerator achieves a 72%reduction in processing time and 83%lower power consumption compared to a 2.4 GHz Intel Central Processing Unit(CPU)software normalization implementation,while maintaining accuracy(0.51%mean Average Precision(mAP)drop at floating-point 32 bits(FP32),1.35%at brain floating-point 16 bits(bfloat16)).When integrated into a neural processing unit(NPU),the design demonstrates 63%and 97%performance improvements over AMD CPU and Reduced Instruction Set Computing-V(RISC-V)implementations,respectively.These results confirm that our proposed BN hardware design enables efficient,high-accuracy,and power-saving on-device training for modern CNNs.Our results demonstrate that efficient hardware implementation of standard batch normalization is achievable without sacrificing accuracy,enabling practical on-device CNN training with significantly reduced computational and power requirements.
文摘Accurate software cost estimation in Global Software Development(GSD)remains challenging due to reliance on historical data and expert judgments.Traditional models,such as the Constructive Cost Model(COCOMO II),rely heavily on historical and accurate data.In addition,expert judgment is required to set many input parameters,which can introduce subjectivity and variability in the estimation process.Consequently,there is a need to improve the current GSD models to mitigate reliance on historical data,subjectivity in expert judgment,inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost overruns.This study introduces a novel hybrid model that synergizes the COCOMO II with Artificial Neural Networks(ANN)to address these challenges.The proposed hybrid model integrates additional GSD-based cost drivers identified through a systematic literature review and further vetted by industry experts.This article compares the effectiveness of the proposedmodelwith state-of-the-artmachine learning-basedmodels for software cost estimation.Evaluating the NASA 93 dataset by adopting twenty-six GSD-based cost drivers reveals that our hybrid model achieves superior accuracy,outperforming existing state-of-the-artmodels.The findings indicate the potential of combining COCOMO II,ANN,and additional GSD-based cost drivers to transform cost estimation in GSD.
基金supported by the National Research Foundation of Korea Grant funded by the Korean Government (NRF-2019R1A2C2003636)
文摘The main aspects that require attention in tunnel design in terms of safety and economy are the precise estimation of probable ground conditions and ground behavior during construction. The variation in rock mass behavior due to tunnel excavation sequence plays an important role during the construction stage.The purpose of this research is to numerically evaluate the effect of excavation sequence on the ground behavior for the Lowari tunnel project, Pakistan. For the tunnel stability, the ground behavior observed during the actual partial face excavation sequence is compared with the top heading and bench excavation sequence. For this purpose, the intact rock parameters are used along with the characterization of rock mass joints related parameters to provide input for numerical modelling via FLAC 2D. The in-situ stresses for the numerical modelling are obtained using empirical equations. From the comparison of the two excavation sequences, it was observed that the actual excavation sequence used for Lowari tunnel construction utilized more support than the top heading and bench method. However, the actual excavation sequence provided good results in terms of stability.
基金funded by National Natural Science Foundation of China (Grant No. 42077364)Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme 2018+2 种基金National Key Research and Development Program of China (Grant No. 2018YFD0900604)Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (Grant No. 311021006)Key Research Projects of Universities in Guangdong Province (Grant Nos. 2019KZDXM003 and 2020KZDZX1040)
文摘In view of the accumulation of nanoplastics(NPs)in the food chain of environment and animals,and the good adsorption properties of nano-plastics to toxic substances,it is necessary to explore the influence of NPs in living organisms.In this study,single and joint toxicological effects of polystyrene nanoplastics(PS-NPs,size 80 nm)and polychlorinated biphenyls(PCBs),were explored in freshwater aquatic animal model zebrafish(Danio rerio).Our study found that exposure to single PS-NPs induced mild acute toxicity,albeit the combined exposure of PS-NPs and polychlorinated biphenyls aggravated the toxicity of PCBs in a dose-dependent manner.Results from gene expression profiling showed that NPs exposure could activate detoxification process,resulting in a slight up-regulation of antioxidant genes(sod1,gstp1),bone development genes(bmp2,bmp4)and cardiac gene(tbx20);while PCBs suppressed the detoxification through down-regulation of these genes,and the addition of NPs will exacerbate the impact of PCBs on gene suppression.Importantly,the results of in vivo purification experiments found that NPs showed prolonged retention in liver,intestine and gills of zebrafish and they might have crossed biological barrier and accumulate in lipid-rich tissues and excretion does not appear as the significant pathway for their elimination.In conclusion,the toxic effects of polychlorinated biphenyls on chorionic protected embryos were not significant as zebrafish chorion plays an important role in resisting the invasion of pollutants;PCBs can seriously damage the bone and heart development of zebrafish,while the presence of NPs significantly enhanced the toxicity of PCBs in zebrafish,which is an alarming concern for growing NPs levels and ecological safety in aquatic environment.
文摘With recent advancements in imaging modalities and techniques and increased recognition of the long-term impact of several structural heart disease interventions,the number of procedures has significantly increased.With the increase in procedures,also comes an increase in cost.In view of this,efficient and cost-effective methods to facilitate and manage structural heart disease interventions are a necessity.Same-day discharge(SDD)after invasive cardiac procedures improves resource utilization and patient satisfaction.SDD in appropriately selected patients has become the standard of care for some invasive cardiac procedures such as percutaneous coronary interventions.This is not the case for the majority of structural heart procedures.With the coronavirus disease 2019 pandemic,safely reducing the duration of time spent within the hospital to prevent unnecessary exposure to pathogens has become a priority.In light of this,it is prudent to assess the feasibility of SDD in several structural heart procedures.In this review we highlight the feasibility of SDD in a carefully selected population,by reviewing and summarizing studies on SDD among patients undergoing left atrial appendage occlusion,patent foramen ovale/atrial septal defect closure,Mitra-clip,and trans-catheter aortic valve replacement procedures.
基金partly supported by the Natural Science Foundation of China,Contract No. 41274061
文摘Ionosphereic foF2 variations are very sensitive to the seismic effect and results of ionospheric perturbations associated with earthquakes seem to very hopeful for short-term earthquake prediction. On January 18,2011 at 20: 23 UT a great earthquake( M = 7. 2)occurred in Dalbandin( 28. 73° N,63. 92° E),Pakistan. In this study,we have tried to find out the features of pre-earthquake ionospheric anomalies by using the hourly day time( 08. 00 a. m.- 05. 00 p. m.) data of critical frequency( foF2) obtained by three vertical sounding stations installed in Islamabad( 33. 78°N,73. 06°E),Multan( 32. 26°N,71. 51°E) and Karachi( 24. 89° N,67. 02° E), Pakistan. The results show the significant anomalies of foF2 in the earthquake preparation zone several days prior to the Dalbandin earthquake. It is also observed that the amplitude and frequency of foF2 anomalies are more prominent at the nearest station to the epicenter as compared to those stations near the outer margin of the earthquake preparation zone. The confidence level for ionospheric anomalies regarding the seismic signatures can be enhanced by adding the analysis of some other ionospheic parameters along with critical frequency of the layer F2.
文摘Distributed denial of service(DDoS)attack is the most common attack that obstructs a network and makes it unavailable for a legitimate user.We proposed a deep neural network(DNN)model for the detection of DDoS attacks in the Software-Defined Networking(SDN)paradigm.SDN centralizes the control plane and separates it from the data plane.It simplifies a network and eliminates vendor specification of a device.Because of this open nature and centralized control,SDN can easily become a victim of DDoS attacks.We proposed a supervised Developed Deep Neural Network(DDNN)model that can classify the DDoS attack traffic and legitimate traffic.Our Developed Deep Neural Network(DDNN)model takes a large number of feature values as compared to previously proposed Machine Learning(ML)models.The proposed DNN model scans the data to find the correlated features and delivers high-quality results.The model enhances the security of SDN and has better accuracy as compared to previously proposed models.We choose the latest state-of-the-art dataset which consists of many novel attacks and overcomes all the shortcomings and limitations of the existing datasets.Our model results in a high accuracy rate of 99.76%with a low false-positive rate and 0.065%low loss rate.The accuracy increases to 99.80%as we increase the number of epochs to 100 rounds.Our proposed model classifies anomalous and normal traffic more accurately as compared to the previously proposed models.It can handle a huge amount of structured and unstructured data and can easily solve complex problems.
基金This research is funded by Abu Dhabi Award for Research Excellence(AARE19-245).
文摘With the advancement of technology,shielding for terahertz(THz)electronic and communication equipment is increasingly important.The metamaterial absorption technique is mostly used to shield electromagnetic interference(EMI)in THz sensing technologies.The most widely used THz metamaterial absorbers suffer from their narrowband properties and the involvement of complex fabrication techniques.Materials with multifunctional properties,such as adjustable conductivity,broad bandwidth,high flexibility,and robustness,are driving future development to meet THz shielding applications.In this article,a theoretical simulation approach based on finite difference time domain(FDTD)is utilized to study the absorption and shielding characteristics of a two-dimensional(2D)MXene Ti_(3)C_(2)T_(x) metasurface absorber in the THz band.The proposed metamaterial structure is made up of a square-shaped array of MXene that is 50 nmthick and is placed on top of a silicon substrate.The bottom surface of the silicon is metalized with gold to reduce the transmission and ultimately enhance the absorption at 1–3 THz.The symmetric adjacent space between theMXene array results in a widening of bandwidth.The proposed metasurface achieves 96%absorption under normal illumination of the incident source and acquires an average of 25 dB shielding at 1 THz bandwidth,with the peak shielding reaching 65 dB.The results show that 2D MXene-based stacked metasurfaces can be proven in the realization of low-cost devices for THz shielding and sensing applications.
基金This work was funded by the University of Jeddah,Saudi Arabia.The authors,therefore,acknowledge with thanks to the University technical support.The authors extend their appreciation to the Deputyship for Research&Innovation,Ministry of Education in Saudi Arabia for funding this research work through the Project Number MoE-IF-20-01.
文摘Metaheuristic approaches in cloud computing have shown significant results due to theirmulti-objective advantages.These approaches are now considering hybridmetaheuristics combining the relative optimized benefits of two or more algorithms resulting in the least tradeoffs among several factors.The critical factors such as execution time,throughput time,response time,energy consumption,SLA violations,communication overhead,makespan,and migration time need careful attention while designing such dynamic algorithms.To improve such factors,an optimizedmulti-objective hybrid algorithm is being proposed that combines the relative advantages of Cat Swarm Optimization(CSO)with machine learning classifiers such as Support Vector Machine(SVM).The adopted approach is based on SVMone to many classification models of machine learning that performs the classifications of various data format types in the cloud with best accuracy.In CSO,grouping phase is used to divide the data files as audio,video,image,and text which is further extended by polynomial Kernel function based on various input features and used for optimized load balancing.Overall,proposed approach works well and achieved performance efficiency in evaluated QoS metrics such as average energy consumption by 12%,migration time by 9%,and optimization time by 10%,in the presence of competitor baselines.
文摘Effect of different Zinc doses was investigated against Erwinia carotovora ssp. atroseptica, the potato blackleg/soft rot causing organism, during 2009 and 2010 in Department of Plant Pathology and Institute of Biotechnology and Genetic Engineering, The University of Agriculture, Peshawar-Pakistan. Out of 200 tested samples, 21 of them were proved to be Eca. However, these tentative Eca isolates showed some characteristics which were unexpected for Eca. We, therefore, decided to perform Polymerase Chain Reaction using Eca-specific primers, Eca1F and Eca2R for confirm identification. For disease management, at the time of sowing, pots containing 5 kg sterilized soil were applied with Zinc in four different treatments i.e. 8 mg, 10 mg, 12 mg and 14 mg along with one control. Results indicated that 12 mg (4.8 kg Zn ha-1) were better doses in controlling the disease up to 73% and increasing the yield up to 117% as compared to control plants.
文摘Separation and purification technology is becoming increasingly important,especially with the rapid industrial development,which brings huge demands in energy and environment^([1,2]).Nano ltration(NF)membrane technology is gaining more attention on the scale of ion separation and purification([3,4]),particularly,graphene oxide(GO)nanosheets have gained signi cant interest due to their simple fabrication.
基金supported by the 2022 Open funding of the State Key Laboratory of Electrical Insulation and Power Equipment(EIPE22211)the National Natural Science Foundation of China,“Research Fund for International Young Scientist(RFIS-1)”,Project:52150410419the 2021 Jiangsu“Shuang-Chuang Doctor(Mass Innovation and Entrepreneurship)Talent Program”,Fund:JSSCBS20211187.
文摘Environmental issues associated with the aviation industry are getting more attention as air traffic increases.Stringent standards are imposed for fuel consumption and pollution emissions for next-generation aircraft.Superconducting electrical propulsion aircraft(SEPA)have been seen as an efficient way to achieve this goal.High-temperature superconducting(HTS)devices are extensively used in the power system to supply enormous energy.Power is distributed to the different loads via a DC distribution network.However,it will generate an inrush current over ten times higher than the rated current in short-circuit state,which is very harmful to the system.Therefore,it is essential to adopt an appropriate protection scheme.This paper discusses one protection scheme that combines DC vacuum circuit breakers(DC VCB)and resistive superconducting current limiters(RSFCL)for superconducting aircraft applications.Considering problems of cost and loss,the auxiliary capacitor is pre-charged by system voltage,and mechanical elements extinguish the arc.Furthermore,combined with RSFCL,the interrupting environment is fully improved.RSFCL limits fault current,and then the VCB breaks this limited current based on creating an artificial current zero(ACZ).The prospective rated power is 8MW,rated voltage and current are 4 kV and 1 kA,respectively.In this paper,we discuss and simulate switching devices that protect SEPA.The interrupting performance of the circuit breaker is analysed in the DC short-circuit fault that occurs on the transmission line.Finally,the residual energy consumption of different situations is calculated.A comparison is made between using RSFCL with metal oxide varistor(MOV)and just using MOV.The scheme with RSFCL shows a significant advantage in energy consumption.
基金supported by the State Key Laboratory of Electrical Insulation and Power Equipment(EIPE22211)the China University of Mining and Technology,‘Science and Technology Fund for the Young Scientist’,Project:2021QN1069.
文摘With the development of a distributed generation,direct current(DC)load and energy‐storage equipment,voltage‐source‐converter‐based medium‐voltage DC systems(VSC‐MVDC)have attracted more attention due to its low power consumption,high reliability,independent power control and so on.However,VSC‐MVDC has the problem of DC fault isolation,which requires the fast‐acting DC circuit‐breakers to isolate faulty lines and ensure low cost.This problem can be solved by coordinating resistive type superconducting‐fault‐current‐limiter(R‐SFCL)and integrated‐gate‐commutated‐thyristor(IGCT)based hybrid circuit breaker.Based on this,IGCT based superconducting DC circuit breaker(SDCCB)is proposed and analysed.Combining R‐SFCL with IGCT could realise large current limiting and interruption and ensure low cost.In addition,the IGCT based hybrid DC circuit breaker(IGCT‐HDCCB)is compared with the traditional insulated gate bipolar transistor(IGBT)based hybrid DC circuit breaker(IGBT‐HDCCB)to evaluate which circuit breaker is more suitable for VSC‐MVDC.The results show that,coordination based on R‐SFCL and SDCCB,the fault current is successfully limited from 17.6 to 2.1 kA,and then inter-rupted within 3.8 ms.In addition,IGCT‐HDCCB overcomes the disadvantage that IGCT has less interrupting capacity than IGBT,retains the advantage of low cost of IGCT and is more suitable for MVDC system.
基金Academy of Finland,Grant/Award Number:346109H2020 European Research Council,Grant/Award Number:725513‐SuperRepel。
文摘Accurate wetting characterization is crucial for the development of next‐generation superhydrophobic surfaces.Traditionally,wetting properties are measured with a contact angle goniometer(CAG)suitable for a broad range of surfaces.However,due to optical errors and challenges in baseline positioning,the CAG method suffers from inaccuracies on superhydrophobic surfaces.Here we present an improved version of the oscillating droplet tribometer(ODT),which can reliably assess wetting properties on superhydrophobic surfaces by measuring the frictional forces of a water‐based ferrofluid droplet oscillating in a magnetic field.We demonstrate that ODT has superior accuracy compared to CAG by measuring the wetting properties of four different superhydrophobic surfaces(commercial Glaco and Hydrobead coatings,black silicon coated with fluoropolymer,and nanostructured copper modified with lauric acid).We show that ODT can detect the small but significant changes in wetting properties caused by the thermal restructuring of surfaces that are undetectable by CAG.Even more,unlike any other wetting characterization technique,ODT features an inverse sensitivity:the more repellent the surface,the lower the error of measurement,which was demonstrated by experiments and simulations.
