With the evolution of next-generation communication networks,ensuring robust Core Network(CN)architecture and data security has become paramount.This paper addresses critical vulnerabilities in the architecture of CN ...With the evolution of next-generation communication networks,ensuring robust Core Network(CN)architecture and data security has become paramount.This paper addresses critical vulnerabilities in the architecture of CN and data security by proposing a novel framework based on blockchain technology that is specifically designed for communication networks.Traditional centralized network architectures are vulnerable to Distributed Denial of Service(DDoS)attacks,particularly in roaming scenarios where there is also a risk of private data leakage,which imposes significant operational demands.To address these issues,we introduce the Blockchain-Enhanced Core Network Architecture(BECNA)and the Secure Decentralized Identity Authentication Scheme(SDIDAS).The BECNA utilizes blockchain technology to decentralize data storage,enhancing network security,stability,and reliability by mitigating Single Points of Failure(SPoF).The SDIDAS utilizes Decentralized Identity(DID)technology to secure user identity data and streamline authentication in roaming scenarios,significantly reducing the risk of data breaches during cross-network transmissions.Our framework employs Ethereum,free5GC,Wireshark,and UERANSIM tools to create a robust,tamper-evident system model.A comprehensive security analysis confirms substantial improvements in user privacy and network security.Simulation results indicate that our approach enhances communication CNs security and reliability,while also ensuring data security.展开更多
Recently,a novel type of neural networks,known as liquid neural networks(LNNs),has been designed from first principles to address robustness and interpretability challenges facing artificial intelligence(AI)solutions....Recently,a novel type of neural networks,known as liquid neural networks(LNNs),has been designed from first principles to address robustness and interpretability challenges facing artificial intelligence(AI)solutions.The potential of LNNs in telecommunications is explored in this paper.First,we illustrate the mechanisms of LNNs and highlight their unique advantages over traditional networks.Then we explore the opportunities that LNNs bring to future wireless networks.Furthermore,we discuss the challenges and design directions for the implementation of LNNs.Finally,we summarize the performance of LNNs in two case studies.展开更多
Propelled by the rise of artificial intelligence,cloud services,and data center applications,next-generation,low-power,local-oscillator-less,digital signal processing(DSP)-free,and short-reach coherent optical communi...Propelled by the rise of artificial intelligence,cloud services,and data center applications,next-generation,low-power,local-oscillator-less,digital signal processing(DSP)-free,and short-reach coherent optical communication has evolved into an increasingly prominent area of research in recent years.Here,we demonstrate DSP-free coherent optical transmission by analog signal processing in frequency synchronous optical network(FSON)architecture,which supports polarization multiplexing and higher-order modulation formats.The FSON architecture that allows the numerous laser sources of optical transceivers within a data center can be quasi-synchronized by means of a tree-distributed homology architecture.In conjunction with our proposed pilot-tone assisted Costas loop for an analog coherent receiver,we achieve a record dual-polarization 224-Gb/s 16-QAM 5-km mismatch transmission with reset-free carrier phase recovery in the optical domain.Our proposed DSP-free analog coherent detection system based on the FSON makes it a promising solution for next-generation,low-power,and high-capacity coherent data center interconnects.展开更多
Meteor Burst Communication(MBC),a niche yet revolutionary wireless communication paradigm,exploits the transient ionized trails generated by meteors ablating in Earth’s atmosphere to enable sporadic yet resilient lon...Meteor Burst Communication(MBC),a niche yet revolutionary wireless communication paradigm,exploits the transient ionized trails generated by meteors ablating in Earth’s atmosphere to enable sporadic yet resilient long-distance radio links.Known for its exceptional resilience,robustness,and sustained connectivity,MBC holds significant promise for applications in emergency communications,remote area connectivity,military/defense systems,and environmental monitoring.However,the scientific exploration and application of MBC have long been highly challenging.In particular,under the combined influence of multiple physical field factors,the channel experiences superimposed multiple random fading effects,exhibiting bursty,highly time-varying,and strongly random characteristics.This persistent technical challenge has resulted in the absence of a practical statistical channel model for MBC to date.展开更多
The hardware and software architectures of core service platforms for next-generation networks were analyzed to compute the minimum cost hardware configuration of a core service platform. This method gives a closed fo...The hardware and software architectures of core service platforms for next-generation networks were analyzed to compute the minimum cost hardware configuration of a core service platform. This method gives a closed form expression for the optimized hardware cost configuration based on the service requirements, the processing features of the computers running the core service platform software, and the processing capabilities of the common object request broker architecture middleware. Three simulation scenarios were used to evaluate the model. The input includes the number of servers for the protocol mapping （PM）, Parlay gateway （PG）, application sever （AS）, and communication handling （CH） functions. The simulation results show that the mean delay meets requirements. When the number of servers for PM, PG, AS, and CH functions were not properly selected, the mean delay was excessive. Simulation results show that the model is valid and can be used to optimize investments in core service platforms.展开更多
The convenience of availing quality services at affordable costs anytime and anywhere makes mobile technology very popular among users.Due to this popularity,there has been a huge rise in mobile data volume,applicatio...The convenience of availing quality services at affordable costs anytime and anywhere makes mobile technology very popular among users.Due to this popularity,there has been a huge rise in mobile data volume,applications,types of services,and number of customers.Furthermore,due to the COVID-19 pandemic,the worldwide lockdown has added fuel to this increase as most of our professional and commercial activities are being done online from home.This massive increase in demand for multi-class services has posed numerous challenges to wireless network frameworks.The services offered through wireless networks are required to support this huge volume of data and multiple types of traffic,such as real-time live streaming of videos,audios,text,images etc.,at a very high bit rate with a negligible delay in transmission and permissible vehicular speed of the customers.Next-generation wireless networks(NGWNs,i.e.5G networks and beyond)are being developed to accommodate the service qualities mentioned above and many more.However,achieving all the desired service qualities to be incorporated into the design of the 5G network infrastructure imposes large challenges for designers and engineers.It requires the analysis of a huge volume of network data(structured and unstructured)received or collected from heterogeneous devices,applications,services,and customers and the effective and dynamic management of network parameters based on this analysis in real time.In the ever-increasing network heterogeneity and complexity,machine learning(ML)techniques may become an efficient tool for effectively managing these issues.In recent days,the progress of artificial intelligence and ML techniques has grown interest in their application in the networking domain.This study discusses current wireless network research,brief discussions on ML methods that can be effectively applied to the wireless networking domain,some tools available to support and customise efficient mobile system design,and some unresolved issues for future research directions.展开更多
The security of the seed industry is crucial for ensuring national food security.Currently,developed countries in Europe and America,along with international seed industry giants,have entered the Breeding 4.0 era.This...The security of the seed industry is crucial for ensuring national food security.Currently,developed countries in Europe and America,along with international seed industry giants,have entered the Breeding 4.0 era.This era integrates biotechnology,artificial intelligence(AI),and big data information technology.In contrast,China is still in a transition period between stages 2.0 and 3.0,which primarily relies on conventional selection and molecular breeding.In the context of increasingly complex international situations,accurately identifying core issues in China's seed industry innovation and seizing the frontier of international seed technology are strategically important.These efforts are essential for ensuring food security and revitalizing the seed industry.This paper systematically analyzes the characteristics of crop breeding data from artificial selection to intelligent design breeding.It explores the applications and development trends of AI and big data in modern crop breeding from several key perspectives.These include highthroughput phenotype acquisition and analysis,multiomics big data database and management system construction,AI-based multiomics integrated analysis,and the development of intelligent breeding software tools based on biological big data and AI technology.Based on an in-depth analysis of the current status and challenges of China's seed industry technology development,we propose strategic goals and key tasks for China's new generation of AI and big data-driven intelligent design breeding.These suggestions aim to accelerate the development of an intelligent-driven crop breeding engineering system that features large-scale gene mining,efficient gene manipulation,engineered variety design,and systematized biobreeding.This study provides a theoretical basis and practical guidance for the development of China's seed industry technology.展开更多
Atmospheric instability information derived from satellites plays an important role in short-term weather forecasting, especially the forecasting of severe convective storms. For the next generation of weather satelli...Atmospheric instability information derived from satellites plays an important role in short-term weather forecasting, especially the forecasting of severe convective storms. For the next generation of weather satellites for Korea＇s multi-purpose geostationary satellite program, a new imaging instrument has been developed. Although this imaging instrument is not de- signed to perform full sounding missions and its capability is limited, its multi-spectral infrared channels provide information on vertical sounding. To take full advantage of the observation data from the much improved spatiotemporal resolution of the imager, the feasibility of an artificial neural network approach for the derivation of the atmospheric instability is investigated. The multi-layer perceptron model with a feed-forward and back-propagation training algorithm shows quite a sensitive re- sponse to the selection of the training dataset and model architecture. Through an extensive performance test with a carefully selected training dataset of 7197 independent profiles, the model architectures are selected to be 12, 5000, and 0.3 for the number of hidden nodes, number of epochs, and learning rate, respectively. The selected model gives a mean absolute error, RMSE, and correlation coefficient of 330 J kg-1, 420 J kg-1, and 0.9, respectively. The feasibility is further demonstrated via application of the model to real observation data from a similar instrument that has comparable observation channels with the planned imager.展开更多
16 September 2013, Shenzhen--ZTE today unveiled the world＇s first flexible, reconfigurable terabit router that allows customers to build the highest-performance broadband networks. The terabit router supports the de...16 September 2013, Shenzhen--ZTE today unveiled the world＇s first flexible, reconfigurable terabit router that allows customers to build the highest-performance broadband networks. The terabit router supports the deployment of multiple line cards with processing capabilities of 10 Gbps to 1 Tbps. It also supports the deployment of modules that can scale throughput from 200 Gbps to 18 Tbps. For easy installation in a range of environments, the router interfaces are flexible and the component design is loose-coupled. This allows customers to customize networks to their needs and promotes adaptability, consistency, and continuity.展开更多
BACKGROUND Pepsinogen(PG)and the PG I/II ratio(PGR)are critical indicators for diagnosing Helicobacter pylori infection and chronic atrophic gastritis,and assessing gastric cancer risk.Existing reference intervals(RIs...BACKGROUND Pepsinogen(PG)and the PG I/II ratio(PGR)are critical indicators for diagnosing Helicobacter pylori infection and chronic atrophic gastritis,and assessing gastric cancer risk.Existing reference intervals(RIs)often overlook age,sex,and demographic variations.Partitioned RIs,while considering these factors,fail to capture the gradual age-related physiological changes.Next-generation RIs offer a solution to this limitation.AIM To investigate age-and sex-specific dynamics of PG and establish next-generation RIs for adults and the elderly in northern China.METHODS After screening,708 healthy individuals were included in this observational study.Serum PG was measured using chemiluminescence immunoassay.Age-and sex-related effects on PG were analyzed with a two-way analysis of variance.RI partitioning was determined by the standard deviation ratio(SDR).Traditional RIs were established using a non-parametric approach.Generalized Additive Models for Location,Scale,and Shape(GAMLSS)modeled age-related trends and continuous reference percentiles for PG I and PG II.Reference limit flagging rates for both RI types were compared.RESULTS PG I and PG II levels were influenced by age(P<0.001)and sex(P<0.001),while PGR remained stable.Age-specific RIs were required for PG I(SDR=0.366)and PG II(SDR=0.424).Partitioned RIs were established for PG I and PG II,with a single RI for PGR.GAMLSS modeling revealed distinct age-dependent trajectories:PG I increased from a median of 39.75μg/L at age 20 years to 49.75μg/L at age 60 years,a 25.16%increase,after which it plateaued through age 80 years.In contrast,PG II showed a continuous rise throughout the age range,with the median value increasing from 5.07μg/L at age 20 years to 8.36μg/L at age 80 years,corresponding to a 64.89%increase.Continuous reference percentiles intuitively reflected these trends and were detailed in this study.Next-generation RIs demonstrated superior accuracy compared to partitioned RIs when applied to specific age subgroups.CONCLUSION This study elucidates the age-and sex-specific dynamics of PG and,to our knowledge,is the first to establish next-generation RIs for PG,supporting more individualized interpretation in laboratory medicine.展开更多
BACKGROUND Leuconostoc garlicum is commonly found in fermented foods and very few infected patients have been reported,who typically present symptoms such as fever and fatigue.Conventional clinical examinations often ...BACKGROUND Leuconostoc garlicum is commonly found in fermented foods and very few infected patients have been reported,who typically present symptoms such as fever and fatigue.Conventional clinical examinations often struggle to identify this bacterium,and routine anti-infective treatments are generally ineffective.Both diagnostic challenges and therapeutic limitations pose significant difficulties for clinicians.CASE SUMMARY We report a patient ultimately diagnosed with Leuconostoc garlicum infection.The primary manifestations included persistent fever,cough and fatigue.These symptoms lasted for 2 months.He received anti-infective treatment at a community hospital,but this was ineffective.After inquiring about the patient's medical history and conducting a physical examination,the patient underwent laboratory tests.Complete blood count tests revealed that the patient had a high proportion of neutrophils,C-reactive protein level was 235.9 mg/L,erythrocyte sedimentation rate was 67 mm/h,respiratory pathogen testing was negative,and he was then thought to have an infectious disease.However,conventional anti-infective treatments were ineffective.After excluding infectious neurological diseases,urologic diseases and digestive problems,we ultimately focused our attention on the lungs.A lung computed tomography scan indicated pulmonary inflammation.Bronchoalveolar lavage fluid for next-generation sequencing suggested lung infection with Leuconostoc garlicum.The patient's symptoms gradually improved following treatment with piperacillin tazobactam and linezolid.During the follow-up period,the patient's temperature remained normal.CONCLUSION For patients with suspected bacterial infection and experiencing fever,conventional anti-infective treatment can be ineffective in controlling their symptoms,and an infection due to rare bacteria or drug-resistant bacteria should be considered.Next-generation sequencing enables rapid and precise identification of infection-related pathogens in febrile patients.展开更多
In rice fields,rice plants usually grow alongside wild weeds and are attacked by various invertebrate species.Viruses are abundant in plants and invertebrates,playing crucial ecological roles in controlling microbial ...In rice fields,rice plants usually grow alongside wild weeds and are attacked by various invertebrate species.Viruses are abundant in plants and invertebrates,playing crucial ecological roles in controlling microbial abundance and maintaining community structures.To date,only 16 rice viruses have been documented in rice-growing regions.These viruses pose serious threats to rice production and have traditionally been identified only from rice plants and insect vectors by isolation techniques.Advances in next-generation sequencing(NGS)have made it feasible to discover viruses on a global scale.Recently,numerous viruses have been identified in plants and invertebrates using NGS technologies.In this review,we discuss viral studies in rice plants,invertebrate species,and weeds in rice fields.Many novel viruses have been discovered in rice ecosystems through NGS technologies,with some also detected using metatranscriptomic and small RNA sequencing.These analyses greatly expand our understanding of viruses in rice fields and provide valuable insights for developing efficient strategies to manage insect pests and virus-mediated rice diseases.展开更多
This study investigates the diversity of gut microbiota in Metaphire peguana,an earthworm species commonly found in agricultural areas of Thailand.Earthworms play a critical role in soil ecosystems by supporting nutri...This study investigates the diversity of gut microbiota in Metaphire peguana,an earthworm species commonly found in agricultural areas of Thailand.Earthworms play a critical role in soil ecosystems by supporting nutrient cycling and breaking down organic matter.Understanding the microbial diversity in their gut is essential for exploring their ecological contributions.Using Next Generation Sequencing(NGS),we analyzed the mycobiome in the gut of M.peguana.Our findings revealed a high diversity of fungal species,primarily belonging to two major phyla:Ascomycota and Basidiomycota.Ascomycota was the most abundant phylum,comprising 40.1% of the total fungal species identified.A total of 33 distinct fungal species were identified,which underscores the richness of microbial life within the earthworm gut.This study successfully created the first genetic database of the microbial community in M.peguana,providing a foundation for future research in agricultural applications.The microbial species identified,particularly siderophoreproducing fungi,could have significant implications for improving soil fertility and promoting sustainable agricultural practices.The use of NGS technology has enabled comprehensive profiling of microbial communities,allowing for precise identification of fungi that may play essential roles in soil health.Furthermore,the study paves the way for future studies on the potential applications of earthworm gut microbiomes in biotechnology,especially in enhancing soil nutrient availability and plant growth.The findings of this research contribute to the broader understanding of the ecological roles of earthworms and their microbiomes in soil ecosystems.展开更多
Objective and Background Early and accurate diagnosis of spinal infections,including spinal tuberculosis,is pivotal for effective treatment but remains challenging.This study aims to assess the diagnostic yield of met...Objective and Background Early and accurate diagnosis of spinal infections,including spinal tuberculosis,is pivotal for effective treatment but remains challenging.This study aims to assess the diagnostic yield of metagenomic next-generation sequencing(mNGS)compared with that of conventional microbiological tests(CMTs)in identifying pathogens associated with spinal pathologies,with a special focus on infections leading to surgical interventions.Methods We enrolled 85 patients who underwent spinal surgery,comprising 63 patients with clinically diagnosed spinal infections,including patients with spinal tuberculosis,and 22 patients with noninfectious spinal conditions.The procedures involved irrigation and debridement for persistent wound drainage,with subsequent DNA extraction from plasma and joint fluid for mNGS and CMT analysis.Results Significantly increased C-reactive protein(CRP)levels were observed in patients with infections.The mNGS approach showed greater diagnostic sensitivity(92.06%)for detecting pathogens,including Mycobacterium tuberculosis,than did CMTs(36.51%).Despite its low specificity,mNGS had considerable negative predictive value(70.59%),underscoring its utility in ruling out infections.Conclusions The mNGS offers superior sensitivity over CMTs in the diagnosis of a variety of spinal infections,notably spinal tuberculosis.This study highlights the potential of mNGS in enhancing the diagnosis of complex spinal infections,thereby informing targeted treatment strategies.展开更多
In this study,an amine-reactive poly(pentafluorophenyl acrylate)(PPFPA)platform was developed for advanced surface engineering of next-generation sequencing(NGS)chips.Through post-polymerization modification,PPFPA was...In this study,an amine-reactive poly(pentafluorophenyl acrylate)(PPFPA)platform was developed for advanced surface engineering of next-generation sequencing(NGS)chips.Through post-polymerization modification,PPFPA was functionalized with dual moieties:azide groups for covalent immobilization of DBCO-modified DNA primers via click chemistry and tunable hydrophilic side chains to optimize biocompatibility and surface properties.Systematic screening revealed that hydrophobic azide carriers combined with neutral hydroxyl groups maximized the DNA immobilization efficacy,approaching the performance of commercial polyacrylamide-based polymers.The negatively charged carboxyl groups severely impede DNA primer attachment.Higher molecular weight derivatives further enhance the efficacy of DNA immobilization.In NGS validation,optimized surface modification polymers achieved robust surface density of clustered DNA and high sequencing accuracy,surpassing quality benchmarks and comparable to those of conventional analogs.This platform demonstrates significant potential for tailoring high-sensitivity surfaces for genomic applications,advancing clinical diagnostics,and personalized medicine.展开更多
Cystic echinococcosis (CE) is a prevalent zoonotic disease caused by Echinococcus granulosus, with a cosmopolitan distribution. The parasite is transmitted cyclically between canines and numerous intermediate herbivor...Cystic echinococcosis (CE) is a prevalent zoonotic disease caused by Echinococcus granulosus, with a cosmopolitan distribution. The parasite is transmitted cyclically between canines and numerous intermediate herbivorous livestock animals. Also, other Taeniid tapeworms could infect domestic dogs and they pose significant veterinary and public health concerns worldwide. This study aimed to develop a sensitive molecular method for detecting Echinococcus spp. DNA in dog fecal samples using next-generation sequencing (NGS). A set of PCR primers targeting conserved regions of Taeniid tapeworms’ 18s rRNA genes was designed and tested for amplifying genomic DNA from various tapeworm species. The PCR system demonstrated high sensitivity, amplifying DNA from all tested tapeworm species, with differences observed in amplified band sizes. The primers were adapted for NGS analysis by adding forward and reverse adapters, enabling the sequencing of amplified DNA fragments. Application of the developed PCR system to dog fecal samples collected from Yatta town, Palestine, revealed the presence of E. granulosus DNA in five out of 50 samples. NGS analysis confirmed the specificity of the amplified DNA fragments, showing 98% - 99% similarity with the 18s rDNA gene of E. granulosus. This study demonstrates the utility of NGS-based molecular methods for accurate and sensitive detection of Echinococcus spp. in dog fecal samples, providing valuable insights for epidemiological surveillance and control programs of echinococcosis in endemic regions.展开更多
The improvement of soybean seed carotenoid contents is very important due to the beneficial role of carotenoids in human health and nutrition. However, the genetic architecture underlying soybean carotenoid biosynthes...The improvement of soybean seed carotenoid contents is very important due to the beneficial role of carotenoids in human health and nutrition. However, the genetic architecture underlying soybean carotenoid biosynthesis remains largely unknown. In the present study, we employed next generation sequencing-based bulked-segregant analysis to identify new genomic regions governing seed carotenoids in 1,551 natural soybean accessions. The genomic DNA samples of individual plants with extreme phenotypes were pooled to form two bulks with high(50 accessions) and low(50 accessions) carotenoid contents for Illumina sequencing. A total of 125.09 Gb of clean bases and 89.82% of Q30 were obtained, and the average alignment efficiency was 99.45% with an average coverage depth of 62.20× and 99.75% genome coverage. Based on the G prime statistic algorithm(G') method analysis, 16 candidate genomic loci with a total length 20.41 Mb were found to be related to the trait. Of these loci, the most significant regions displaying the highest elevated G' values were found in chromosome 06 at a position of 18.53–22.67 Mb, and chromosome 19 at genomic region intervals of 8.36–10.94, 12.06–13.79 and 18.45–20.26 Mb. These regions were then used to identify the key candidate genes. In these regions, 250 predicted genes were found and analyzed to obtain 90 significantly enriched(P<0.05) Gene Ontology(GO) terms. Based on ANNOVAR analysis, 50 genes with non-synonymous and stopgained mutations were preferentially selected as potential candidate genes. Of those 50 genes, following their gene annotation functions and high significant haplotype variations in various environments,five genes were identified as the most promising candidate genes regulating soybean seed carotenoid accumulation, and they should be investigated in further functional validation studies. Collectively, understanding the genetic basis of carotenoid pigments and identifying genes underpinning carotenoid accumulation via a bulked-segregant analysis-based sequencing(BSA-seq) approach provide new insights for exploring future molecular breeding efforts to produce soybean cultivars with high carotenoid content.展开更多
The main aim of this research is to get a better knowledge and understanding of the micro-scale oscillatory networks behavior in the solid propellants reactionary zones. Fundamental understanding of the micro-and nano...The main aim of this research is to get a better knowledge and understanding of the micro-scale oscillatory networks behavior in the solid propellants reactionary zones. Fundamental understanding of the micro-and nano-scale combustion mechanisms is essential to the development and further improvement of the next-generation technologies for extreme control of the solid propellant thrust. Both experiments and theory confirm that the micro-and nano-scale oscillatory networks excitation in the solid propellants reactionary zones is a rather universal phenomenon. In accordance with our concept,the micro-and nano-scale structures form both the fractal and self-organized wave patterns in the solid propellants reactionary zones. Control by the shape, the sizes and spacial orientation of the wave patterns allows manipulate by the energy exchange and release in the reactionary zones. A novel strategy for enhanced extreme thrust control in solid propulsion systems are based on manipulation by selforganization of the micro-and nano-scale oscillatory networks and self-organized patterns formation in the reactionary zones with use of the system of acoustic waves and electro-magnetic fields, generated by special kind of ring-shaped electric discharges along with resonance laser radiation. Application of special kind of the ring-shaped electric discharges demands the minimum expenses of energy and opens prospects for almost inertia-free control by combustion processes. Nano-sized additives will enhance self-organizing and self-synchronization of the micro-and nano-scale oscillatory networks on the nanometer scale. Suggested novel strategy opens the door for completely new ways for enhanced extreme thrust control of the solid propulsion systems.展开更多
The Internet subscribers are expected to increase up to 69.7%(6 billion)from 45.3%and 25 billion Internet-of-things connections by 2025.Thus,the ubiquitous availability of data-hungry smart multimedia devices urges re...The Internet subscribers are expected to increase up to 69.7%(6 billion)from 45.3%and 25 billion Internet-of-things connections by 2025.Thus,the ubiquitous availability of data-hungry smart multimedia devices urges research attention to reduce the energy consumption in the fifthgeneration cloud radio access network to meet the future traffic demand of high data rates.We propose a new cell zooming paradigm based on joint transmission(JT)coordinated multipoint to optimize user connection by controlling the cell coverage in the downlink communications with a hybrid power supply.The endeavoring cell zooming technique adjusts the coverage area in a given cluster based on five different JT schemes,which will help in reducing the overall power consumption with minimum inter-cell interference.We provide heuristic solutions to assess wireless network performances in terms of aggregate throughput,energy efficiency index(EEI),and energy consumption gain under a different scale of network settings.The suggested algorithm allows efficient allocation of resource block and increases energy and spectral efficiency over the conventional location-centric cell zooming mechanism.Extensive system-level simulations show that the proposed framework reduces energy consumption yielding up to 17.5%and increases EEI by 14%.Subsequently,a thorough comparison among different JT-based load shifting schemes is pledged for further validation of varying system bandwidths.展开更多
Recommending personalized travel routes from sparse,implicit feedback poses a significant challenge,as conventional systems often struggle with information overload and fail to capture the complex,sequential nature of...Recommending personalized travel routes from sparse,implicit feedback poses a significant challenge,as conventional systems often struggle with information overload and fail to capture the complex,sequential nature of user preferences.To address this,we propose a Conditional Generative Adversarial Network(CGAN)that generates diverse and highly relevant itineraries.Our approach begins by constructing a conditional vector that encapsulates a user’s profile.This vector uniquely fuses embeddings from a Heterogeneous Information Network(HIN)to model complex user-place-route relationships,a Recurrent Neural Network(RNN)to capture sequential path dynamics,and Neural Collaborative Filtering(NCF)to incorporate collaborative signals from the wider user base.This comprehensive condition,further enhanced with features representing user interaction confidence and uncertainty,steers a CGAN stabilized by spectral normalization to generate high-fidelity latent route representations,effectively mitigating the data sparsity problem.Recommendations are then formulated using an Anchor-and-Expand algorithm,which selects relevant starting Points of Interest(POI)based on user history,then expands routes through latent similarity matching and geographic coherence optimization,culminating in Traveling Salesman Problem(TSP)-based route optimization for practical travel distances.Experiments on a real-world check-in dataset validate our model’s unique generative capability,achieving F1 scores ranging from 0.163 to 0.305,and near-zero pairs−F1 scores between 0.002 and 0.022.These results confirm the model’s success in generating novel travel routes by recommending new locations and sequences rather than replicating users’past itineraries.This work provides a robust solution for personalized travel planning,capable of generating novel and compelling routes for both new and existing users by learning from collective travel intelligence.展开更多
基金supported by the Beijing Natural Science Foundation(L223025,4242003)Qin Xin Talents Cultivation Program of Beijing Information Science&Technology University(QXTCP B202405)。
文摘With the evolution of next-generation communication networks,ensuring robust Core Network(CN)architecture and data security has become paramount.This paper addresses critical vulnerabilities in the architecture of CN and data security by proposing a novel framework based on blockchain technology that is specifically designed for communication networks.Traditional centralized network architectures are vulnerable to Distributed Denial of Service(DDoS)attacks,particularly in roaming scenarios where there is also a risk of private data leakage,which imposes significant operational demands.To address these issues,we introduce the Blockchain-Enhanced Core Network Architecture(BECNA)and the Secure Decentralized Identity Authentication Scheme(SDIDAS).The BECNA utilizes blockchain technology to decentralize data storage,enhancing network security,stability,and reliability by mitigating Single Points of Failure(SPoF).The SDIDAS utilizes Decentralized Identity(DID)technology to secure user identity data and streamline authentication in roaming scenarios,significantly reducing the risk of data breaches during cross-network transmissions.Our framework employs Ethereum,free5GC,Wireshark,and UERANSIM tools to create a robust,tamper-evident system model.A comprehensive security analysis confirms substantial improvements in user privacy and network security.Simulation results indicate that our approach enhances communication CNs security and reliability,while also ensuring data security.
基金supported by the China National Key R&D Program under Grant Nos.2021YFA1000500 and 2023YFB2904804National Natural Science Foundation of China under Grant Nos.62331023,62101492,62394292 and U20A20158+1 种基金Zhejiang Provincial Natural Science Foundation of China under Grant No.LR22F010002Zhejiang Provincial Science and Technology Plan Project under Grant No.2024C01033。
文摘Recently,a novel type of neural networks,known as liquid neural networks(LNNs),has been designed from first principles to address robustness and interpretability challenges facing artificial intelligence(AI)solutions.The potential of LNNs in telecommunications is explored in this paper.First,we illustrate the mechanisms of LNNs and highlight their unique advantages over traditional networks.Then we explore the opportunities that LNNs bring to future wireless networks.Furthermore,we discuss the challenges and design directions for the implementation of LNNs.Finally,we summarize the performance of LNNs in two case studies.
基金supported by the National Natural Science Foundation of China(Grant Nos.62405250 and 62471404)the China Postdoctoral Science Foundation(Grant No.2024M762955)+1 种基金the Key Project of Westlake Institute for Optoelectronics(Grant No.2023GD003)the Optical Com-munication and Sensing Laboratory,School of Engineering,Westlake University.
文摘Propelled by the rise of artificial intelligence,cloud services,and data center applications,next-generation,low-power,local-oscillator-less,digital signal processing(DSP)-free,and short-reach coherent optical communication has evolved into an increasingly prominent area of research in recent years.Here,we demonstrate DSP-free coherent optical transmission by analog signal processing in frequency synchronous optical network(FSON)architecture,which supports polarization multiplexing and higher-order modulation formats.The FSON architecture that allows the numerous laser sources of optical transceivers within a data center can be quasi-synchronized by means of a tree-distributed homology architecture.In conjunction with our proposed pilot-tone assisted Costas loop for an analog coherent receiver,we achieve a record dual-polarization 224-Gb/s 16-QAM 5-km mismatch transmission with reset-free carrier phase recovery in the optical domain.Our proposed DSP-free analog coherent detection system based on the FSON makes it a promising solution for next-generation,low-power,and high-capacity coherent data center interconnects.
文摘Meteor Burst Communication(MBC),a niche yet revolutionary wireless communication paradigm,exploits the transient ionized trails generated by meteors ablating in Earth’s atmosphere to enable sporadic yet resilient long-distance radio links.Known for its exceptional resilience,robustness,and sustained connectivity,MBC holds significant promise for applications in emergency communications,remote area connectivity,military/defense systems,and environmental monitoring.However,the scientific exploration and application of MBC have long been highly challenging.In particular,under the combined influence of multiple physical field factors,the channel experiences superimposed multiple random fading effects,exhibiting bursty,highly time-varying,and strongly random characteristics.This persistent technical challenge has resulted in the absence of a practical statistical channel model for MBC to date.
基金the China Postdoctoral Science Foundation (No. 20060390463)the Basic Research Foundation of Tsinghua National Laboratory for Information Science and Technology
文摘The hardware and software architectures of core service platforms for next-generation networks were analyzed to compute the minimum cost hardware configuration of a core service platform. This method gives a closed form expression for the optimized hardware cost configuration based on the service requirements, the processing features of the computers running the core service platform software, and the processing capabilities of the common object request broker architecture middleware. Three simulation scenarios were used to evaluate the model. The input includes the number of servers for the protocol mapping （PM）, Parlay gateway （PG）, application sever （AS）, and communication handling （CH） functions. The simulation results show that the mean delay meets requirements. When the number of servers for PM, PG, AS, and CH functions were not properly selected, the mean delay was excessive. Simulation results show that the model is valid and can be used to optimize investments in core service platforms.
文摘The convenience of availing quality services at affordable costs anytime and anywhere makes mobile technology very popular among users.Due to this popularity,there has been a huge rise in mobile data volume,applications,types of services,and number of customers.Furthermore,due to the COVID-19 pandemic,the worldwide lockdown has added fuel to this increase as most of our professional and commercial activities are being done online from home.This massive increase in demand for multi-class services has posed numerous challenges to wireless network frameworks.The services offered through wireless networks are required to support this huge volume of data and multiple types of traffic,such as real-time live streaming of videos,audios,text,images etc.,at a very high bit rate with a negligible delay in transmission and permissible vehicular speed of the customers.Next-generation wireless networks(NGWNs,i.e.5G networks and beyond)are being developed to accommodate the service qualities mentioned above and many more.However,achieving all the desired service qualities to be incorporated into the design of the 5G network infrastructure imposes large challenges for designers and engineers.It requires the analysis of a huge volume of network data(structured and unstructured)received or collected from heterogeneous devices,applications,services,and customers and the effective and dynamic management of network parameters based on this analysis in real time.In the ever-increasing network heterogeneity and complexity,machine learning(ML)techniques may become an efficient tool for effectively managing these issues.In recent days,the progress of artificial intelligence and ML techniques has grown interest in their application in the networking domain.This study discusses current wireless network research,brief discussions on ML methods that can be effectively applied to the wireless networking domain,some tools available to support and customise efficient mobile system design,and some unresolved issues for future research directions.
基金partially supported by the Construction of Collaborative Innovation Center of Beijing Academy of Agricultural and Forestry Sciences(KJCX20240406)the Beijing Natural Science Foundation(JQ24037)+1 种基金the National Natural Science Foundation of China(32330075)the Earmarked Fund for China Agriculture Research System(CARS-02 and CARS-54)。
文摘The security of the seed industry is crucial for ensuring national food security.Currently,developed countries in Europe and America,along with international seed industry giants,have entered the Breeding 4.0 era.This era integrates biotechnology,artificial intelligence(AI),and big data information technology.In contrast,China is still in a transition period between stages 2.0 and 3.0,which primarily relies on conventional selection and molecular breeding.In the context of increasingly complex international situations,accurately identifying core issues in China's seed industry innovation and seizing the frontier of international seed technology are strategically important.These efforts are essential for ensuring food security and revitalizing the seed industry.This paper systematically analyzes the characteristics of crop breeding data from artificial selection to intelligent design breeding.It explores the applications and development trends of AI and big data in modern crop breeding from several key perspectives.These include highthroughput phenotype acquisition and analysis,multiomics big data database and management system construction,AI-based multiomics integrated analysis,and the development of intelligent breeding software tools based on biological big data and AI technology.Based on an in-depth analysis of the current status and challenges of China's seed industry technology development,we propose strategic goals and key tasks for China's new generation of AI and big data-driven intelligent design breeding.These suggestions aim to accelerate the development of an intelligent-driven crop breeding engineering system that features large-scale gene mining,efficient gene manipulation,engineered variety design,and systematized biobreeding.This study provides a theoretical basis and practical guidance for the development of China's seed industry technology.
基金supported by the National Meteorological Satellite Center(NMSC) of the Korea Meteorological Administration,entitled "Development of Geostationary Meteorological Ground Segment"
文摘Atmospheric instability information derived from satellites plays an important role in short-term weather forecasting, especially the forecasting of severe convective storms. For the next generation of weather satellites for Korea＇s multi-purpose geostationary satellite program, a new imaging instrument has been developed. Although this imaging instrument is not de- signed to perform full sounding missions and its capability is limited, its multi-spectral infrared channels provide information on vertical sounding. To take full advantage of the observation data from the much improved spatiotemporal resolution of the imager, the feasibility of an artificial neural network approach for the derivation of the atmospheric instability is investigated. The multi-layer perceptron model with a feed-forward and back-propagation training algorithm shows quite a sensitive re- sponse to the selection of the training dataset and model architecture. Through an extensive performance test with a carefully selected training dataset of 7197 independent profiles, the model architectures are selected to be 12, 5000, and 0.3 for the number of hidden nodes, number of epochs, and learning rate, respectively. The selected model gives a mean absolute error, RMSE, and correlation coefficient of 330 J kg-1, 420 J kg-1, and 0.9, respectively. The feasibility is further demonstrated via application of the model to real observation data from a similar instrument that has comparable observation channels with the planned imager.
文摘16 September 2013, Shenzhen--ZTE today unveiled the world＇s first flexible, reconfigurable terabit router that allows customers to build the highest-performance broadband networks. The terabit router supports the deployment of multiple line cards with processing capabilities of 10 Gbps to 1 Tbps. It also supports the deployment of modules that can scale throughput from 200 Gbps to 18 Tbps. For easy installation in a range of environments, the router interfaces are flexible and the component design is loose-coupled. This allows customers to customize networks to their needs and promotes adaptability, consistency, and continuity.
文摘BACKGROUND Pepsinogen(PG)and the PG I/II ratio(PGR)are critical indicators for diagnosing Helicobacter pylori infection and chronic atrophic gastritis,and assessing gastric cancer risk.Existing reference intervals(RIs)often overlook age,sex,and demographic variations.Partitioned RIs,while considering these factors,fail to capture the gradual age-related physiological changes.Next-generation RIs offer a solution to this limitation.AIM To investigate age-and sex-specific dynamics of PG and establish next-generation RIs for adults and the elderly in northern China.METHODS After screening,708 healthy individuals were included in this observational study.Serum PG was measured using chemiluminescence immunoassay.Age-and sex-related effects on PG were analyzed with a two-way analysis of variance.RI partitioning was determined by the standard deviation ratio(SDR).Traditional RIs were established using a non-parametric approach.Generalized Additive Models for Location,Scale,and Shape(GAMLSS)modeled age-related trends and continuous reference percentiles for PG I and PG II.Reference limit flagging rates for both RI types were compared.RESULTS PG I and PG II levels were influenced by age(P<0.001)and sex(P<0.001),while PGR remained stable.Age-specific RIs were required for PG I(SDR=0.366)and PG II(SDR=0.424).Partitioned RIs were established for PG I and PG II,with a single RI for PGR.GAMLSS modeling revealed distinct age-dependent trajectories:PG I increased from a median of 39.75μg/L at age 20 years to 49.75μg/L at age 60 years,a 25.16%increase,after which it plateaued through age 80 years.In contrast,PG II showed a continuous rise throughout the age range,with the median value increasing from 5.07μg/L at age 20 years to 8.36μg/L at age 80 years,corresponding to a 64.89%increase.Continuous reference percentiles intuitively reflected these trends and were detailed in this study.Next-generation RIs demonstrated superior accuracy compared to partitioned RIs when applied to specific age subgroups.CONCLUSION This study elucidates the age-and sex-specific dynamics of PG and,to our knowledge,is the first to establish next-generation RIs for PG,supporting more individualized interpretation in laboratory medicine.
文摘BACKGROUND Leuconostoc garlicum is commonly found in fermented foods and very few infected patients have been reported,who typically present symptoms such as fever and fatigue.Conventional clinical examinations often struggle to identify this bacterium,and routine anti-infective treatments are generally ineffective.Both diagnostic challenges and therapeutic limitations pose significant difficulties for clinicians.CASE SUMMARY We report a patient ultimately diagnosed with Leuconostoc garlicum infection.The primary manifestations included persistent fever,cough and fatigue.These symptoms lasted for 2 months.He received anti-infective treatment at a community hospital,but this was ineffective.After inquiring about the patient's medical history and conducting a physical examination,the patient underwent laboratory tests.Complete blood count tests revealed that the patient had a high proportion of neutrophils,C-reactive protein level was 235.9 mg/L,erythrocyte sedimentation rate was 67 mm/h,respiratory pathogen testing was negative,and he was then thought to have an infectious disease.However,conventional anti-infective treatments were ineffective.After excluding infectious neurological diseases,urologic diseases and digestive problems,we ultimately focused our attention on the lungs.A lung computed tomography scan indicated pulmonary inflammation.Bronchoalveolar lavage fluid for next-generation sequencing suggested lung infection with Leuconostoc garlicum.The patient's symptoms gradually improved following treatment with piperacillin tazobactam and linezolid.During the follow-up period,the patient's temperature remained normal.CONCLUSION For patients with suspected bacterial infection and experiencing fever,conventional anti-infective treatment can be ineffective in controlling their symptoms,and an infection due to rare bacteria or drug-resistant bacteria should be considered.Next-generation sequencing enables rapid and precise identification of infection-related pathogens in febrile patients.
基金supported by the National Natural Science Foundation of China(Grant Nos.31972983 and 32072487)the Key Technology R&D Program of Zhejiang Province,China(Grant No.2021C02006)the Zhejiang Provincial Natural Science Foundation of China(Grant No.LY23C140001).
文摘In rice fields,rice plants usually grow alongside wild weeds and are attacked by various invertebrate species.Viruses are abundant in plants and invertebrates,playing crucial ecological roles in controlling microbial abundance and maintaining community structures.To date,only 16 rice viruses have been documented in rice-growing regions.These viruses pose serious threats to rice production and have traditionally been identified only from rice plants and insect vectors by isolation techniques.Advances in next-generation sequencing(NGS)have made it feasible to discover viruses on a global scale.Recently,numerous viruses have been identified in plants and invertebrates using NGS technologies.In this review,we discuss viral studies in rice plants,invertebrate species,and weeds in rice fields.Many novel viruses have been discovered in rice ecosystems through NGS technologies,with some also detected using metatranscriptomic and small RNA sequencing.These analyses greatly expand our understanding of viruses in rice fields and provide valuable insights for developing efficient strategies to manage insect pests and virus-mediated rice diseases.
文摘This study investigates the diversity of gut microbiota in Metaphire peguana,an earthworm species commonly found in agricultural areas of Thailand.Earthworms play a critical role in soil ecosystems by supporting nutrient cycling and breaking down organic matter.Understanding the microbial diversity in their gut is essential for exploring their ecological contributions.Using Next Generation Sequencing(NGS),we analyzed the mycobiome in the gut of M.peguana.Our findings revealed a high diversity of fungal species,primarily belonging to two major phyla:Ascomycota and Basidiomycota.Ascomycota was the most abundant phylum,comprising 40.1% of the total fungal species identified.A total of 33 distinct fungal species were identified,which underscores the richness of microbial life within the earthworm gut.This study successfully created the first genetic database of the microbial community in M.peguana,providing a foundation for future research in agricultural applications.The microbial species identified,particularly siderophoreproducing fungi,could have significant implications for improving soil fertility and promoting sustainable agricultural practices.The use of NGS technology has enabled comprehensive profiling of microbial communities,allowing for precise identification of fungi that may play essential roles in soil health.Furthermore,the study paves the way for future studies on the potential applications of earthworm gut microbiomes in biotechnology,especially in enhancing soil nutrient availability and plant growth.The findings of this research contribute to the broader understanding of the ecological roles of earthworms and their microbiomes in soil ecosystems.
基金supported by the Hubei Provincial Natural Science Foundation of China(No.2023AFB646)Knowledge Innovation Program of Wuhan(No.2023020201010155)Educational Research Program of Huazhong University of Science and Technology(No.2022135).
文摘Objective and Background Early and accurate diagnosis of spinal infections,including spinal tuberculosis,is pivotal for effective treatment but remains challenging.This study aims to assess the diagnostic yield of metagenomic next-generation sequencing(mNGS)compared with that of conventional microbiological tests(CMTs)in identifying pathogens associated with spinal pathologies,with a special focus on infections leading to surgical interventions.Methods We enrolled 85 patients who underwent spinal surgery,comprising 63 patients with clinically diagnosed spinal infections,including patients with spinal tuberculosis,and 22 patients with noninfectious spinal conditions.The procedures involved irrigation and debridement for persistent wound drainage,with subsequent DNA extraction from plasma and joint fluid for mNGS and CMT analysis.Results Significantly increased C-reactive protein(CRP)levels were observed in patients with infections.The mNGS approach showed greater diagnostic sensitivity(92.06%)for detecting pathogens,including Mycobacterium tuberculosis,than did CMTs(36.51%).Despite its low specificity,mNGS had considerable negative predictive value(70.59%),underscoring its utility in ruling out infections.Conclusions The mNGS offers superior sensitivity over CMTs in the diagnosis of a variety of spinal infections,notably spinal tuberculosis.This study highlights the potential of mNGS in enhancing the diagnosis of complex spinal infections,thereby informing targeted treatment strategies.
基金financially supported by the Science and Technology Commission of Shanghai Municipality(No.24ZR1401400)Shenzhen Salus Bio Med Company for their strong support in this study。
文摘In this study,an amine-reactive poly(pentafluorophenyl acrylate)(PPFPA)platform was developed for advanced surface engineering of next-generation sequencing(NGS)chips.Through post-polymerization modification,PPFPA was functionalized with dual moieties:azide groups for covalent immobilization of DBCO-modified DNA primers via click chemistry and tunable hydrophilic side chains to optimize biocompatibility and surface properties.Systematic screening revealed that hydrophobic azide carriers combined with neutral hydroxyl groups maximized the DNA immobilization efficacy,approaching the performance of commercial polyacrylamide-based polymers.The negatively charged carboxyl groups severely impede DNA primer attachment.Higher molecular weight derivatives further enhance the efficacy of DNA immobilization.In NGS validation,optimized surface modification polymers achieved robust surface density of clustered DNA and high sequencing accuracy,surpassing quality benchmarks and comparable to those of conventional analogs.This platform demonstrates significant potential for tailoring high-sensitivity surfaces for genomic applications,advancing clinical diagnostics,and personalized medicine.
文摘Cystic echinococcosis (CE) is a prevalent zoonotic disease caused by Echinococcus granulosus, with a cosmopolitan distribution. The parasite is transmitted cyclically between canines and numerous intermediate herbivorous livestock animals. Also, other Taeniid tapeworms could infect domestic dogs and they pose significant veterinary and public health concerns worldwide. This study aimed to develop a sensitive molecular method for detecting Echinococcus spp. DNA in dog fecal samples using next-generation sequencing (NGS). A set of PCR primers targeting conserved regions of Taeniid tapeworms’ 18s rRNA genes was designed and tested for amplifying genomic DNA from various tapeworm species. The PCR system demonstrated high sensitivity, amplifying DNA from all tested tapeworm species, with differences observed in amplified band sizes. The primers were adapted for NGS analysis by adding forward and reverse adapters, enabling the sequencing of amplified DNA fragments. Application of the developed PCR system to dog fecal samples collected from Yatta town, Palestine, revealed the presence of E. granulosus DNA in five out of 50 samples. NGS analysis confirmed the specificity of the amplified DNA fragments, showing 98% - 99% similarity with the 18s rDNA gene of E. granulosus. This study demonstrates the utility of NGS-based molecular methods for accurate and sensitive detection of Echinococcus spp. in dog fecal samples, providing valuable insights for epidemiological surveillance and control programs of echinococcosis in endemic regions.
基金financially supported by the National Natural Science Foundation of China (32161143033, 32272178, and 32001574)National Key Research and Development Program of China (2021YFD1201605)the Agricultural Science and Technology Innovation Project of CAAS。
文摘The improvement of soybean seed carotenoid contents is very important due to the beneficial role of carotenoids in human health and nutrition. However, the genetic architecture underlying soybean carotenoid biosynthesis remains largely unknown. In the present study, we employed next generation sequencing-based bulked-segregant analysis to identify new genomic regions governing seed carotenoids in 1,551 natural soybean accessions. The genomic DNA samples of individual plants with extreme phenotypes were pooled to form two bulks with high(50 accessions) and low(50 accessions) carotenoid contents for Illumina sequencing. A total of 125.09 Gb of clean bases and 89.82% of Q30 were obtained, and the average alignment efficiency was 99.45% with an average coverage depth of 62.20× and 99.75% genome coverage. Based on the G prime statistic algorithm(G') method analysis, 16 candidate genomic loci with a total length 20.41 Mb were found to be related to the trait. Of these loci, the most significant regions displaying the highest elevated G' values were found in chromosome 06 at a position of 18.53–22.67 Mb, and chromosome 19 at genomic region intervals of 8.36–10.94, 12.06–13.79 and 18.45–20.26 Mb. These regions were then used to identify the key candidate genes. In these regions, 250 predicted genes were found and analyzed to obtain 90 significantly enriched(P<0.05) Gene Ontology(GO) terms. Based on ANNOVAR analysis, 50 genes with non-synonymous and stopgained mutations were preferentially selected as potential candidate genes. Of those 50 genes, following their gene annotation functions and high significant haplotype variations in various environments,five genes were identified as the most promising candidate genes regulating soybean seed carotenoid accumulation, and they should be investigated in further functional validation studies. Collectively, understanding the genetic basis of carotenoid pigments and identifying genes underpinning carotenoid accumulation via a bulked-segregant analysis-based sequencing(BSA-seq) approach provide new insights for exploring future molecular breeding efforts to produce soybean cultivars with high carotenoid content.
基金supported by the Western-Caucasus Research Center
文摘The main aim of this research is to get a better knowledge and understanding of the micro-scale oscillatory networks behavior in the solid propellants reactionary zones. Fundamental understanding of the micro-and nano-scale combustion mechanisms is essential to the development and further improvement of the next-generation technologies for extreme control of the solid propellant thrust. Both experiments and theory confirm that the micro-and nano-scale oscillatory networks excitation in the solid propellants reactionary zones is a rather universal phenomenon. In accordance with our concept,the micro-and nano-scale structures form both the fractal and self-organized wave patterns in the solid propellants reactionary zones. Control by the shape, the sizes and spacial orientation of the wave patterns allows manipulate by the energy exchange and release in the reactionary zones. A novel strategy for enhanced extreme thrust control in solid propulsion systems are based on manipulation by selforganization of the micro-and nano-scale oscillatory networks and self-organized patterns formation in the reactionary zones with use of the system of acoustic waves and electro-magnetic fields, generated by special kind of ring-shaped electric discharges along with resonance laser radiation. Application of special kind of the ring-shaped electric discharges demands the minimum expenses of energy and opens prospects for almost inertia-free control by combustion processes. Nano-sized additives will enhance self-organizing and self-synchronization of the micro-and nano-scale oscillatory networks on the nanometer scale. Suggested novel strategy opens the door for completely new ways for enhanced extreme thrust control of the solid propulsion systems.
基金This work was supported by SUT Research and Development Funds and by Thailand Science Research and Innovation(TSRI)Also,this work was supported by the Deanship of Scientific Research at Prince Sattam bin Abdulaziz University,Saudi ArabiaIn addition,support by the Taif University Researchers Supporting Project Number(TURSP-2020/77),Taif University,Taif,Saudi Arabia.
文摘The Internet subscribers are expected to increase up to 69.7%(6 billion)from 45.3%and 25 billion Internet-of-things connections by 2025.Thus,the ubiquitous availability of data-hungry smart multimedia devices urges research attention to reduce the energy consumption in the fifthgeneration cloud radio access network to meet the future traffic demand of high data rates.We propose a new cell zooming paradigm based on joint transmission(JT)coordinated multipoint to optimize user connection by controlling the cell coverage in the downlink communications with a hybrid power supply.The endeavoring cell zooming technique adjusts the coverage area in a given cluster based on five different JT schemes,which will help in reducing the overall power consumption with minimum inter-cell interference.We provide heuristic solutions to assess wireless network performances in terms of aggregate throughput,energy efficiency index(EEI),and energy consumption gain under a different scale of network settings.The suggested algorithm allows efficient allocation of resource block and increases energy and spectral efficiency over the conventional location-centric cell zooming mechanism.Extensive system-level simulations show that the proposed framework reduces energy consumption yielding up to 17.5%and increases EEI by 14%.Subsequently,a thorough comparison among different JT-based load shifting schemes is pledged for further validation of varying system bandwidths.
基金supported by the Chung-Ang University Research Grants in 2023.Alsothe work is supported by the ELLIIT Excellence Center at Linköping–Lund in Information Technology in Sweden.
文摘Recommending personalized travel routes from sparse,implicit feedback poses a significant challenge,as conventional systems often struggle with information overload and fail to capture the complex,sequential nature of user preferences.To address this,we propose a Conditional Generative Adversarial Network(CGAN)that generates diverse and highly relevant itineraries.Our approach begins by constructing a conditional vector that encapsulates a user’s profile.This vector uniquely fuses embeddings from a Heterogeneous Information Network(HIN)to model complex user-place-route relationships,a Recurrent Neural Network(RNN)to capture sequential path dynamics,and Neural Collaborative Filtering(NCF)to incorporate collaborative signals from the wider user base.This comprehensive condition,further enhanced with features representing user interaction confidence and uncertainty,steers a CGAN stabilized by spectral normalization to generate high-fidelity latent route representations,effectively mitigating the data sparsity problem.Recommendations are then formulated using an Anchor-and-Expand algorithm,which selects relevant starting Points of Interest(POI)based on user history,then expands routes through latent similarity matching and geographic coherence optimization,culminating in Traveling Salesman Problem(TSP)-based route optimization for practical travel distances.Experiments on a real-world check-in dataset validate our model’s unique generative capability,achieving F1 scores ranging from 0.163 to 0.305,and near-zero pairs−F1 scores between 0.002 and 0.022.These results confirm the model’s success in generating novel travel routes by recommending new locations and sequences rather than replicating users’past itineraries.This work provides a robust solution for personalized travel planning,capable of generating novel and compelling routes for both new and existing users by learning from collective travel intelligence.
