The Impact of Sea Level Rise on Roadway Design and Evacuation Routes in Delaware

As the global temperature continues to increase, the sea level continues to rise at a rapid rate that has never been seen before. This becomes an issue for many facets of life but one of the most impacted is the transportation infrastructure. Many people living in low elevation coastal areas can become trapped by flooding with no way in or out. With Delaware being a coastal state, this would affect a large portion of the population and will have detrimental effects over time if nothing is done to combat sea level rise. The issue with sea level rise in transportation is that once the roads become flooded, they become virtually unusable and detour routes would be needed. If all the roads in a coastal area were to be affected by sea level rise, the options for detours would become limited. This article looks at direct solutions to combat sea level rise and indirect solutions that would specifically help transportation infrastructure and evacuation routes in Delaware. There is not one solution that can fix every problem, so many solutions are laid out to see what is applicable to each affected area. Some solutions include defense structures that would be put close to the coast, raising the elevation of vulnerable roads throughout the state and including pumping stations to drain the water on the surface of the road. With an understanding of all these solutions around the world, the ultimate conclusion came in the form of a six-step plan that Delaware should take in order to best design against sea level rise in these coastal areas.

Stage at diagnosis of colorectal cancer through diagnostic route:Who should be screened?

BACKGROUND Colorectal cancer(CRC)is a global health concern,with advanced-stage diagnoses contributing to poor prognoses.The efficacy of CRC screening has been well-established;nevertheless,a significant proportion of patients remain unscreened,with>70%of cases diagnosed outside screening.Although identifying specific subgroups for whom CRC screening should be particularly recommended is crucial owing to limited resources,the association between the diagnostic routes and identification of these subgroups has been less appreciated.In the Japanese cancer registry,the diagnostic routes for groups discovered outside of screening are primarily categorized into those with comorbidities found during hospital visits and those with CRC-related symptoms.AIM To clarify the stage at CRC diagnosis based on diagnostic routes.METHODS We conducted a retrospective observational study using a cancer registry of patients with CRC between January 2016 and December 2019 at two hospitals.The diagnostic routes were primarily classified into three groups:Cancer screening,follow-up,and symptomatic.The early-stage was defined as Stages 0 or I.Multivariate and univariate logistic regressions were exploited to determine the odds of early-stage diagnosis in the symptomatic and cancer screening groups,referencing the follow-up group.The adjusted covariates were age,sex,and tumor location.RESULTS Of the 2083 patients,715(34.4%),1064(51.1%),and 304(14.6%)belonged to the follow-up,symptomatic,and cancer screening groups,respectively.Among the 2083 patients,CRCs diagnosed at an early stage were 57.3%(410 of 715),23.9%(254 of 1064),and 59.5%(181 of 304)in the follow-up,symptomatic,and cancer screening groups,respectively.The symptomatic group exhibited a lower likelihood of early-stage diagnosis than the follow-up group[P<0.001,adjusted odds ratio(aOR),0.23;95%confidence interval(95%CI):0.19-0.29].The likelihood of diagnosis at an early stage was similar between the follow-up and cancer screening groups(P=0.493,aOR for early-stage diagnosis in the cancer screening group vs follow-up group=1.11;95%CI=0.82-1.49).CONCLUSION CRCs detected during hospital visits for comorbidities were diagnosed earlier,similar to cancer screening.CRC screening should be recommended,particularly for patients without periodical hospital visits for comorbidities.

Therapeutic Routes of a Group of Heart Failure Patients Followed in a Cameroonian Urban Setting

Background: Heart failure (HF) is a rising global health problem. Patients with HF tend to use several therapies obtained via different treatment routes to relieve their symptoms. It is rampant in sub-Saharan Africa (SSA), leading to poor health-seeking behaviours and worsened HF health outcomes. We aimed to describe the different therapeutic routes of HF patients from the onset of their first symptom until treatment in a specialised cardiology centre to identify and rebuke harmful therapeutic routes. Materials and Methods: This was a cross-sectional study at the Yaoundé Central Hospital in Cameroon between December 2018 to July 2019. Patients were recruited by consecutive convenient sampling. Adult patients aged above 18 years with confirmed HF were included using the Framingham criteria. Variables relating to socio-demographic and clinical data and the health-seeking behaviours of HF patients were studied. Results: We included 132 patients with a mean age of 62.90 years (62.88% women). Very few patients (0.90%) followed an ideal route;60.71% of subjects had a pseudo-ideal route, 19.64% accessed a specialised facility directly, and 21.42% used an erratic route. At the arrival time in a cardiology unit, 49.24% and 35.61% of our subjects were in NYHA stage III and IV HF compared to 15.15% for stage II. None of them was in Stage I. Conclusion: Most heart failure patients in Cameroon have resorted to non-specialised care, which worsens their clinical presentation. There is an urgent need for health education of HF patients in our context.

Migration routes and differences in migration strategies of Whooper Swans between spring and autumn

Long-distance migratory birds travel more rapidly in spring than in autumn,as they face temporal breeding constraints.However,several species travel slower in spring owing to environmental influences,such as food availability and wind conditions.GPS trackers were attached to 17 Whooper Swans(Cygnus cygnus) inhabiting northeastern Mongolia,to determine their migration routes and stopover sites in spring and autumn.Differences between spring and autumn migrations,migration-influencing parameters,and the effect of spring stopover site temperatures were analyzed.Six swans completed perfect tours between their wintering and breeding sites,and these data were used for analysis.Spring migration lasted 57 days,with 49.2 days spent at 3.7 stopover sites.Autumn migration lasted 21.5 days,with 17.5 days spent at 1.0 stopover sites.Thus,the swans traveled more rapidly in autumn than in spring.Migration distance,number of stopovers,migration speed,and straightness were important migration determinants in both spring and autumn.Migration distance,stopover duration,number of stopovers,daily travel speed,travel duration,and migration speed differed significantly between spring and autumn.During spring migration,the temperature at the current stopover sites and that at the future stopover sites displayed significant variations(t=1585.8,df=631.6,p <0.001).These findings are critical for the conservation and management of Whooper Swans and their key habitats in East Asian regions,and the data are anticipated to make a particularly significant contribution toward developing detailed management plans for the conservation of their key habitats.

Regional variation in routes to diagnosis of cholangiocarcinoma in England from 2006 to 2017

BACKGROUND Incidence of cholangiocarcinoma(CCA)is rising,with overall prognosis remaining very poor.Reasons for the high mortality of CCA include its late presentation in most patients,when curative options are no longer feasible,and poor response to systemic therapies for advanced disease.Late presentation presents a large barrier to improving outcomes and is often associated with diagnosis via mergency presentation(EP).Earlier diagnoses may be made by Two Week Wait(TWW)referrals through General practitioner(GP).We hypothesise that TWW referrals and EP routes to diagnosis differ across regions in England.AIM To investigate routes to diagnosis of CCA over time,regional variation and influencing factors.METHODS We linked patient records from the National Cancer Registration Dataset to Hospital Episode Statistics,Cancer Waiting Times and Cancer Screening Programme datasets to define routes to diagnosis and certain patient characteristics for patients diagnosed 2006-2017 in England.We used linear probability models to investigate geographic variation by assessing the proportions of patients diagnosed via TWW referral or EP across Cancer Alliances in England,adjusting for potential confounders.Correlation between the proportion of people diagnosed by TWW referral and EP was investigated with Spearman’s correlation coefficient.RESULTS Of 23632 patients diagnosed between 2006-2017 in England,the most common route to diagnosis was EP(49.6%).Non-TWW GP referrals accounted for 20.5%of diagnosis routes,13.8%were diagnosed by TWW referral,and the remainder 16.2%were diagnosed via an‘other’or Unknown route.The proportion diagnosed via a TWW referral doubled between 2006-2017 rising from 9.9%to 19.8%,conversely EP diagnosis route declined,falling from 51.3%to 46.0%.Statistically significant variation in both the TWW referral and EP proportions was found across Cancer Alliances.Age,presence of comorbidity and underlying liver disease were independently associated with both a lower proportion of patients diagnosed via TWW referral,and a higher proportion diagnosed by EP after adjusting for other potential confounders.CONCLUSION There is significant geographic and socio-demographic variation in routes to diagnosis of CCA in England.Knowledge sharing of best practice may improve diagnostic pathways and reduce unwarranted variation.

MTCR-CR Routing Strategy for Connection-Oriented Routing over Satellite Networks

The high-speed movement of satellites makes it not feasible to directly apply the mature routing scheme on the ground to the satellite network.DT-DVTR in the snapshot-based connectionoriented routing strategy is one of the representative solutions,but it still has room for improvement in terms of routing stability.In this paper,we propose an improved scheme for connection-oriented routing strategy named the Minimal Topology Change Routing based on Collaborative Rules(MTCR-CR).The MTCR-CR uses continuous time static topology snapshots based on satellite status to search for intersatellite link(ISL)construction solutions that meet the minimum number of topology changes to avoid route oscillations.The simulation results in Beidou-3 show that compared with DT-DVTR,MTCR-CR reduces the number of routing changes by about 92%,the number of path changes caused by routing changes is about38%,and the rerouting time is reduced by approximately 47%.At the same time,in order to show our algorithm more comprehensively,the same experimental index test was also carried out on the Globalstar satellite constellation.

Efficient Route Planning for Real-Time Demand-Responsive Transit

Demand Responsive Transit (DRT) responds to the dynamic users’ requests without any fixed routes and timetablesand determines the stop and the start according to the demands. This study explores the optimization of dynamicvehicle scheduling and real-time route planning in urban public transportation systems, with a focus on busservices. It addresses the limitations of current shared mobility routing algorithms, which are primarily designedfor simpler, single origin/destination scenarios, and do not meet the complex demands of bus transit systems. Theresearch introduces an route planning algorithm designed to dynamically accommodate passenger travel needsand enable real-time route modifications. Unlike traditional methods, this algorithm leverages a queue-based,multi-objective heuristic A∗ approach, offering a solution to the inflexibility and limited coverage of suburbanbus routes. Also, this study conducts a comparative analysis of the proposed algorithm with solutions based onGenetic Algorithm (GA) and Ant Colony Optimization Algorithm (ACO), focusing on calculation time, routelength, passenger waiting time, boarding time, and detour rate. The findings demonstrate that the proposedalgorithmsignificantly enhances route planning speed, achieving an 80–100-fold increase in efficiency over existingmodels, thereby supporting the real-time demands of Demand-Responsive Transportation (DRT) systems. Thestudy concludes that this algorithm not only optimizes route planning in bus transit but also presents a scalablesolution for improving urban mobility.

Significant lake expansion has accelerated permafrost degradation on the Qinghai-Tibet Plateau

In recent years, lakes on the Qinghai-Tibet Plateau have become more responsive to climate change. In September 2011, Zonag Lake in Hoh Xil experienced sudden drainage, the water eventually flowed into Yanhu Lake, which caused Yanhu Lake to continue to expand. The potential collapse of Yanhu Lake could directly threaten the operational safety of the adjacent Qinghai-Tibet Highway, Qinghai-Tibet Railway. To explore the implications of expanding lakes on the surrounding permafrost, we selected Hoh Xil Yanhu Lake on the Qinghai-Tibet Plateau to study the effect of lake expansion on permafrost degradation. The permafrost degradation in the Yanhu Lake basin from October 2017 to December 2022 was inverted using Sentinel-1 satellite image data and small baseline subset interferometry synthetic aperture radar(SBAS-In SAR) technology. Additionally, permafrost degradation from February 2007 and February 2010 was analyzed using advanced land observing satellite phased array-type L-band synthetic aperture radar(ALOS PALSAR) satellite images and differential interferometric synthetic aperture radar(D-In SAR) technique. The results showed that the permafrost around Yanhu Lake experienced accelerated degradation. Prior to the expansion of Yanhu Lake, the average annual deformation rate along the line of sight(LOS) direction was 6.7 mm/yr. After the expansion, the rate increased to 20.9 mm/yr. The integration of spatial-temporal distribution maps of surface subsidence, Wudaoliang borehole geothermal data, meteorological data, Yanhu Lake surface area changes, and water level changes supports the assertion that the intensified permafrost degradation could be attributed to lake expansion rather than the rising air temperature. Furthermore, permafrost degradation around Yanhu Lake could impact vital infrastructure such as the adjacent Qinghai-Tibet Highway and Qinghai-Tibet Railway.

Cryptic diversity and rampant hybridization in annual gentians on the Qinghai-Tibet Plateau revealed by population genomic analysis

Understanding the evolutionary and ecological processes involved in population differentiation and speciation provides critical insights into biodiversity formation. In this study, we employed 29,865 single nucleotide polymorphisms(SNPs) and complete plastomes to examine genomic divergence and hybridization in Gentiana aristata, which is endemic to the Qinghai-Tibet Plateau(QTP) region. Genetic clustering revealed that G. aristata is characterized by geographic genetic structures with five clusters(West, East, Central, South and North). The West cluster has a specific morphological character(i.e., blue corolla) and higher values of FSTcompared to the remaining clusters, likely the result of the geological barrier formed by the Yangtze River. The West cluster diverged from the other clusters in the Early Pliocene;these remaining clusters diverged from one another in the Early Quaternary. Phylogenetic reconstructions based on SNPs and plastid data revealed substantial cyto-nuclear conflicts. Genetic clustering and D-statistics demonstrated rampant hybridization between the Central and North clusters,along the Bayankala Mountains, which form the geological barrier between the Central and North clusters. Species distribution modeling demonstrated the range of G. aristata expanded since the Last Interglacial period. Our findings provide genetic and morphological evidence of cryptic diversity in G. aristata, and identified rampant hybridization between genetic clusters along a geological barrier.These findings suggest that geological barriers and climatic fluctuations have an important role in triggering diversification as well as hybridization, indicating that cryptic diversity and hybridization are essential factors in biodiversity formation within the QTP region.

CoopAI-Route: DRL Empowered Multi-Agent Cooperative System for Efficient QoS-Aware Routing for Network Slicing in Multi-Domain SDN

The emergence of beyond 5G networks has the potential for seamless and intelligent connectivity on a global scale.Network slicing is crucial in delivering services for different,demanding vertical applications in this context.Next-generation applications have time-sensitive requirements and depend on the most efficient routing path to ensure packets reach their intended destinations.However,the existing IP(Internet Protocol)over a multi-domain network faces challenges in enforcing network slicing due to minimal collaboration and information sharing among network operators.Conventional inter-domain routing methods,like Border Gateway Protocol(BGP),cannot make routing decisions based on performance,which frequently results in traffic flowing across congested paths that are never optimal.To address these issues,we propose CoopAI-Route,a multi-agent cooperative deep reinforcement learning(DRL)system utilizing hierarchical software-defined networks(SDN).This framework enforces network slicing in multi-domain networks and cooperative communication with various administrators to find performance-based routes in intra-and inter-domain.CoopAI-Route employs the Distributed Global Topology(DGT)algorithm to define inter-domain Quality of Service(QoS)paths.CoopAI-Route uses a DRL agent with a message-passing multi-agent Twin-Delayed Deep Deterministic Policy Gradient method to ensure optimal end-to-end routes adapted to the specific requirements of network slicing applications.Our evaluation demonstrates CoopAI-Route’s commendable performance in scalability,link failure handling,and adaptability to evolving topologies compared to state-of-the-art methods.

Unveiling evapotranspiration patterns and energy balance in a subalpine forest of the Qinghai-Tibet Plateau:observations and analysis from an eddy covariance system

Evapotranspiration is an important parameter used to characterize the water cycle of ecosystems.To under-stand the properties of the evapotranspiration and energy balance of a subalpine forest in the southeastern Qinghai-Tibet Plateau,an open-path eddy covariance system was set up to monitor the forest from November 2020 to October 2021 in a core area of the Three Parallel Rivers in the Qing-hai-Tibet Plateau.The results show that the evapotranspira-tion peaked daily,the maximum occurring between 11:00 and 15:00.Environmental factors had significant effects on evapotranspiration,among them,net radiation the greatest(R^(2)=0.487),and relative humidity the least(R^(2)=0.001).The energy flux varied considerably in different seasons and sensible heat flux accounted for the main part of turbulent energy.The energy balance ratio in the dormant season was less than that in the growing season,and there is an energy imbalance at the site on an annual time scale.

Enhancing Network Design through Statistical Evaluation of MANET Routing Protocols

This paper contributes a sophisticated statistical method for the assessment of performance in routing protocols salient Mobile Ad Hoc Network(MANET)routing protocols:Destination Sequenced Distance Vector(DSDV),Ad hoc On-Demand Distance Vector(AODV),Dynamic Source Routing(DSR),and Zone Routing Protocol(ZRP).In this paper,the evaluation will be carried out using complete sets of statistical tests such as Kruskal-Wallis,Mann-Whitney,and Friedman.It articulates a systematic evaluation of how the performance of the previous protocols varies with the number of nodes and the mobility patterns.The study is premised upon the Quality of Service(QoS)metrics of throughput,packet delivery ratio,and end-to-end delay to gain an adequate understanding of the operational efficiency of each protocol under different network scenarios.The findings explained significant differences in the performance of different routing protocols;as a result,decisions for the selection and optimization of routing protocols can be taken effectively according to different network requirements.This paper is a step forward in the general understanding of the routing dynamics of MANETs and contributes significantly to the strategic deployment of robust and efficient network infrastructures.

Dynamic Routing of Multiple QoS-Required Flows in Cloud-Edge Autonomous Multi-Domain Data Center Networks

The 6th generation mobile networks(6G)network is a kind of multi-network interconnection and multi-scenario coexistence network,where multiple network domains break the original fixed boundaries to form connections and convergence.In this paper,with the optimization objective of maximizing network utility while ensuring flows performance-centric weighted fairness,this paper designs a reinforcement learning-based cloud-edge autonomous multi-domain data center network architecture that achieves single-domain autonomy and multi-domain collaboration.Due to the conflict between the utility of different flows,the bandwidth fairness allocation problem for various types of flows is formulated by considering different defined reward functions.Regarding the tradeoff between fairness and utility,this paper deals with the corresponding reward functions for the cases where the flows undergo abrupt changes and smooth changes in the flows.In addition,to accommodate the Quality of Service(QoS)requirements for multiple types of flows,this paper proposes a multi-domain autonomous routing algorithm called LSTM+MADDPG.Introducing a Long Short-Term Memory(LSTM)layer in the actor and critic networks,more information about temporal continuity is added,further enhancing the adaptive ability changes in the dynamic network environment.The LSTM+MADDPG algorithm is compared with the latest reinforcement learning algorithm by conducting experiments on real network topology and traffic traces,and the experimental results show that LSTM+MADDPG improves the delay convergence speed by 14.6%and delays the start moment of packet loss by 18.2%compared with other algorithms.

Frequency-tunable single-photon router based on a microresonator containing a driven three-level emitter

We propose a frequency-tunable router of single photons with high routing efficiency, which is constructed by two waveguides mediately linked by a single-mode whispering gallery resonator with a driven three-level emitter. Quantum routing probability in the output port is obtained via the real-space Hamiltonian. By adjusting the resonator–emitter coupling and the drive, the desired continuous central frequencies for the resonance peaks of routing photons can be manipulated nearly linearly, with the assistance of Rabi splitting effect and optical Stark shift. The proposed routing system may provide potential applications in designing other frequency-modulation quantum optical devices, such as multiplexers,filters, and so on.

Design Strategies of Expressway Routes and Interchanges

Road traffic conditions can have an important impact on the economic development of various regions.Under the background of rapid social and economic development,more and more expressway construction projects are initiated in various regions,including both new expressways and expansion of old expressways,and interchange design plays an important role.Scientific and reasonable interchange design can not only realize energy saving and low carbon footprint,but also be people-oriented and promote regional economic development.Therefore,this paper mainly analyzes the highway route and its interchange design strategy for reference.

An Energy-Efficient Routing Algorithm for UAV Formation Based on Time-Aggregated Graph

The limited energy and high mobility of unmanned aerial vehicles(UAVs)lead to drastic topology changes in UAV formation.The existing routing protocols necessitate a large number of messages for route discovery and maintenance,greatly increasing network delay and control overhead.A energyefficient routing method based on the discrete timeaggregated graph(TAG)theory is proposed since UAV formation is a defined time-varying network.The network is characterized using the TAG,which utilizes the prior knowledge in UAV formation.An energyefficient routing algorithm is designed based on TAG,considering the link delay,relative mobility,and residual energy of UAVs.The routing path is determined with global network information before requesting communication.Simulation results demonstrate that the routing method can improve the end-to-end delay,packet delivery ratio,routing control overhead,and residual energy.Consequently,introducing timevarying graphs to design routing algorithms is more effective for UAV formation.

QoS Routing Optimization Based on Deep Reinforcement Learning in SDN

To enhance the efficiency and expediency of issuing e-licenses within the power sector, we must confront thechallenge of managing the surging demand for data traffic. Within this realm, the network imposes stringentQuality of Service (QoS) requirements, revealing the inadequacies of traditional routing allocation mechanismsin accommodating such extensive data flows. In response to the imperative of handling a substantial influx of datarequests promptly and alleviating the constraints of existing technologies and network congestion, we present anarchitecture forQoS routing optimizationwith in SoftwareDefinedNetwork (SDN), leveraging deep reinforcementlearning. This innovative approach entails the separation of SDN control and transmission functionalities, centralizingcontrol over data forwardingwhile integrating deep reinforcement learning for informed routing decisions. Byfactoring in considerations such as delay, bandwidth, jitter rate, and packet loss rate, we design a reward function toguide theDeepDeterministic PolicyGradient (DDPG) algorithmin learning the optimal routing strategy to furnishsuperior QoS provision. In our empirical investigations, we juxtapose the performance of Deep ReinforcementLearning (DRL) against that of Shortest Path (SP) algorithms in terms of data packet transmission delay. Theexperimental simulation results show that our proposed algorithm has significant efficacy in reducing networkdelay and improving the overall transmission efficiency, which is superior to the traditional methods.

Bacterial communities and enzyme activities during litter decomposition of Elymus nutans leaf on the Qinghai-Tibet Plateau

The dominant plant litter plays a crucial role in carbon(C)and nutrients cycling as well as ecosystem functions maintenance on the Qinghai-Tibet Plateau(QTP).The impact of litter decomposition of dominant plants on edaphic parameters and grassland productivity has been extensively studied,while its decomposition processes and relevant mechanisms in this area remain poorly understood.We conducted a three-year litter decomposition experiment in the Gansu Gannan Grassland Ecosystem National Observation and Research Station,an alpine meadow ecosystem on the QTP,to investigate changes in litter enzyme activities and bacterial and fungal communities,and clarify how these critical factors regulated the decomposition of dominant plant Elymus nutans(E.nutans)litter.The results showed that cellulose and hemicellulose,which accounted for 95%of the initial lignocellulose content,were the main components in E.nutans litter decomposition.The litter enzyme activities ofβ-1,4-glucosidase(BG),β-1,4-xylosidase(BX),andβ-D-cellobiosidase(CBH)decreased with decomposition while acid phosphatase,leucine aminopeptidase,and phenol oxidase increased with decomposition.We found that both litter bacterial and fungal communities changed significantly with decomposition.Furthermore,bacterial communities shifted from copiotrophic-dominated to oligotrophic-dominated in the late stage of litter decomposition.Partial least squares path model revealed that the decomposition of E.nutans litter was mainly driven by bacterial communities and their secreted enzymes.Bacteroidota and Proteobacteria were important producers of enzymes BG,BX,and CBH,and their relative abundances were tightly positively related to the content of cellulose and hemicellulose,indicating that Bacteroidota and Proteobacteria are the main bacterial taxa of the decomposition of E.nutans litter.In conclusion,this study demonstrates that bacterial communities are the main driving forces behind the decomposition of E.nutans litter,highlighting the vital roles of bacterial communities in affecting the ecosystem functions of the QTP by regulating dominant plant litter decomposition.

A phylogenetic approach identifies patterns of beta diversity and floristic subregions of the Qinghai-Tibet Plateau

Patterns of taxonomic and phylogenetic beta diversity and their relationships with environmental correlates can help reveal the origin and evolutionary history of regional biota.The Qinghai-Tibet Plateau(QTP)harbors an exceptionally diverse flora,however,a phylogenetic perspective has rarely been used to investigate its beta diversity and floristic regions.In this study,we used a phylogenetic approach to identify patterns of beta diversity and quantitatively delimit floristic regions on the Qinghai-Tibet Plateau.We also examined the relationships between multifaceted beta diversity,geographical distance,and climatic difference,and evaluated the relative importance of various factors(i.e.,climate,topography and history)in shaping patterns of beta diversity.Sørensen dissimilarity indices indicated that patterns of species turnover among sites dominated the QTP.We also found that patterns of both taxonomic and phylogenetic beta diversity were significantly related to geographical distance and climatic difference.The environmental factors that contributed most to these patterns of beta diversity include annual precipitation,mean annual temperature,climatic gradients and climatic instability.Hierarchical dendrograms of dissimilarity and non-metric multidimensional scaling ordination based on phylogenetic beta diversity data identified ten floristic subregions in the QTP.Our results suggest that the contemporary environment and historical climate changes have filtered species composition among sites and eventually determined beta diversity patterns of plants in the QTP.

An SDN-Based Algorithm for Caching,Routing,and Load Balancing in ICN

One of the challenges of Informationcentric Networking(ICN)is finding the optimal location for caching content and processing users’requests.In this paper,we address this challenge by leveraging Software-defined Networking(SDN)for efficient ICN management.To achieve this,we formulate the problem as a mixed-integer nonlinear programming(MINLP)model,incorporating caching,routing,and load balancing decisions.We explore two distinct scenarios to tackle the problem.Firstly,we solve the problem in an offline mode using the GAMS environment,assuming a stable network state to demonstrate the superior performance of the cacheenabled network compared to non-cache networks.Subsequently,we investigate the problem in an online mode where the network state dynamically changes over time.Given the computational complexity associated with MINLP,we propose the software-defined caching,routing,and load balancing(SDCRL)algorithm as an efficient and scalable solution.Our evaluation demonstrates that the SDCRL algorithm significantly reduces computational time while maintaining results that closely resemble those achieved by GAMS.