Optimal Distance Threshold Research Articles

Optimizing an Urban Green Space Ecological Network by Coupling Structural and Functional Connectivity: A Case for Biodiversity Conservation Planning

Strengthening and optimizing the spatial structure and functional connectivity of green space ecological networks can not only relieve the tight urban space and provide biodiversity protection but also promote the virtuous cycle of the urban ecosystem and provide a new method for the resilient development of the urban landscape. In this study, the central area of Chengdu was taken as the study area; Morphological Spatial Pattern Analysis (MSPA) with landscape metrics were combined to determine the optimal distance threshold and identify the ecological sources. Graph theory and circuit theory were applied to construct and optimize the green space ecological network with structural or functional connectivity, respectively. Based on the coupling effect, the optimization of the ecological network was put forward, and the network analysis method was used to evaluate the connectivity of three different types of ecological networks. The results were as follows: (1) The ecological network with structural connectivity was composed of 74 stepping stones, 43 protective sources, and 315 ecological corridors. The connectivity of green space structures gradually decreased from west to east and from periphery to center. (2) In the optimal ecological network with functional connectivity, 176 important ecological corridors were protected, and 40 pinch points and 48 protective sources were identified. The number of important corridors in the east and south was the largest, and the network structure was relatively complex. The barriers were divided into three different levels of ecological restoration areas. (3) The green ecological network with structural and functional connectivity has the best network connectivity. A green space ring network optimization pattern of one center, two belts, multi-points, multi-corridors, and multi-zones connected in a series was proposed. It was suggested to build a multi-level forest ecosystem in Longquan Mountain, develop eco-fruit agriculture and eco-tourism, enrich the biodiversity of the ecological source, and improve its anti-interference ability to the external environment. It is also important to increase ecological strategic points and stepping stones to strengthen the links between different ecological restoration areas, properly handle the use of cultivated land in different regions, strictly observe the red line of cultivated land, and maintain the integrity and diversity of ecological sources. Therefore, the optimization method of the green space ecological network in this study provides technical support for the effective determination of ecological protection areas, the accurate implementation of green space ecological networks, and a scientific planning strategy for decision-makers.

A risk source identification model for network security of power CPS system (CPS) based on fuzzy artificial neural network

In order to improve the effect and accuracy of risk source identification, this paper studied the network security risk source identification model of power CPS system based on fuzzy artificial neural network. The network security risk source index system of power CPS system was constructed, and the dimension of index data was reduced by principal component analysis. Fuzzy theory is used to process the index data after dimension reduction, and the comprehensive membership vector of each index is obtained. The dynamic clustering algorithm is used to determine the number of hidden layer units of radial basis function neural network, and the network security risk source identification model is established. Finally, the quantitative value of risk source identification is output. The experimental results show that the model can effectively reduce the dimension of the network security risk source index data of the power CPS system. The optimal distance threshold of the hidden layer is 4.2, and the optimal number of units is 6. In the final identification results, four severe risk sources and five moderate risk sources were obtained, and the quantitative values of risk source identification of each index were 63, 70, 71, 77, 65, 89 and 96, respectively, indicating that the model can effectively identify network security risk sources of power CPS systems. With the increase of the proportion of communication nodes removed, when there are various types of security vulnerability information, the mean square error value of the model is always lower than the set threshold, indicating that the model has high recognition accuracy.

Inferring potential non-disclosed men who have sex with men among self-reported heterosexual men with HIV in Southwest China: A genetic network study.

In Guangxi province of China, there is a high prevalence of HIV in the general population and in men who have sex with men (MSM). However, there is still a low proportion of MSM among people living with HIV. This apparent contradiction could be due to the high proportion of potential non-disclosed MSM (pnMSM) among reported heterosexual men. We analyzed the genetic linkage of HIV specimens to address this problem aiming to (1) identify the optimal genetic distance threshold, which gave the highest number of genetic clusters, (2) document the proportion of potential non-disclosed MSM (pnMSM) among self-reported heterosexual men, and (3) determine predictors for pnMSM. Pairwise genetic distances were computed among all samples. The genetic distance threshold giving the highest number of genetic clusters was identified. Self-reported heterosexual men were identified as belonging to the pnMSM group if they could be linked to any MSM in their cluster. Multinomial logistic regression was used to determine associated factors of being pnMSM. The optimal genetic distance threshold was 0.75% substitutions/site. Among 896 self-reported heterosexual men, the frequency (percentage and 95% confidence interval) was 62 (6.9%, 5.2-8.6%) for pnMSM, 779 (86.9%, 84.7-89.1%) for indeterminate men and 55 (6.1%, 4.5-7.7%) for potential heterosexual men, respectively. Self-reported heterosexual men who were younger, single and more educated were more likely to be pnMSM. Based on these findings, there is a need to pay more attention to sexually active, young and educated self-reported heterosexual men and provide them with voluntary counselling and testing and specific HIV prevention services.

Physical Urban Area Identification Based on Geographical Data and Quantitative Attribution of Identification Threshold: A Case Study in Chongqing Municipality, Southwestern China

Although some methods have identified the physical urban area to a certain extent, the driving factors for the identification threshold have not been studied deeply. In this paper, vector building data and road intersection data are used for comparative validation based on the urban expansion curve method to identify the physical urban area using the meso-city scale. The geographical detector technique is used to detect how and to what extent the urban spatial structure factors, geographical environment factors and social economic factors affect the optimal distance threshold of 22 administrative districts in the Chongqing municipality. The results based on the vector buildings are more precise and show the characteristics of the physical urban area of core-periphery distribution and the distribution along the water corridor. From the results of quantitative attribution, it was found that the road network density, building density, urbanization rate and urban population density, and their interaction with regional GDP, play a critical role in the optimal distance threshold, with the index value of influence degree ≥0.79. Under the influence of different factors, the optimal distance thresholds of 22 administrative districts show adaptive characteristics. Looking forward to the future, this study provides ideas for further research on the morphological characteristics and distribution laws of multi-spatial scale cities.

Density peaks clustering based on local fair density and fuzzy k-nearest neighbors membership allocation strategy

The density peaks clustering algorithm (DPC) has been widely concerned since it was proposed in 2014. There is no need to specify in advance and only one parameter required. However, some disadvantages are still witnessed in DPC: (1) Requiring repeated experiments for choosing a suitable calculation method of the local density due to the variations in the scale of the dataset, which will lead to additional time cost. (2) Difficulty in finding an optimal cutoff distance threshold, since different parameters not only impact the selection of cluster centers but also directly affect the quality of clusters. (3) Poor fault tolerance of the allocation strategy, especially in manifold datasets or datasets with uneven density distribution. Targetting solutions to these problems, a density peaks clustering based on local fair density and fuzzy k-nearest neighbors membership allocation strategy (LF-DPC) is proposed in this paper. First, to obtain a more balanced local density, two classic local density calculation methods are combined in the algorithm to calculate the local fair density through the optimization function with the smallest local density difference. Second, a robust two stage remaining points allocation strategy is designed. In the first stage, k-nearest neighbors are used to quickly and accurately allocate points from the cluster center. In the second stage, to further improve the accuracy of allocation, a fuzzy k-nearest neighbors membership method is designed to allocate the remaining points. Finally, the LF-DPC algorithm has been experimented based on several synthetic and real-world datasets. The results prove that the proposed algorithm has obvious advantages compared with the other five ones.

A method for data density reduction in overlapped airborne LiDAR strips

A partial overlap between adjacent strips during airborne Light Detection And Ranging (LiDAR) data scanning is required to ensure data integrity. The overlap area is observed two times and contains richer target details. To reduce data density yet retaining target details in the overlap area, a method based on reducing the influence of repeated observation data is presented. The proposed method defines the repeated observation data as the multiple samples of the same location from two adjacent strips, identifies them by locating the pairwise closest points from two adjacent strips with their distance below a distance threshold, and eliminates unimportant points inside the repeated observation data according to the criterion that LiDAR points with low curvature or high incidence angle can be removed without affecting the sharp features and the overall quality of data representation of the overlap area. The optimal distance threshold is adaptively determined using a Gaussian fitting model by modeling the mean distance between all the nearest neighbors in one original LiDAR strips. Finally, reduction rate and information entropy metric are put forward to quantitatively evaluate the effectiveness of the proposed method. The developed method is applied to two real airborne LiDAR datasets with urban and forestry scenes for experimental testing. The quantitative accuracy evaluation results show that reduction rate in urban and forestry area can reach to 25.1% and 12.8%, respectively. Furthermore, the data density of the overlap area could be reduced while the information entropy and DTM accuracy still can be maintained.

Building Plane Segmentation Based on Point Clouds

Planes are essential features to describe the shapes of buildings. The segmentation of a plane is significant when reconstructing a building in three dimensions. However, there is a concern about the accuracy in segmenting plane from point cloud data. The objective of this paper was to develop an effective segmentation algorithm for building planes that combines the region growing algorithm with the distance algorithm based on boundary points. The method was tested on point cloud data from a cottage and pantry as scanned using a Faro Focus 3D laser range scanner and Matterport Camera, respectively. A coarse extraction of the building plane was obtained from the region growing algorithm. The coplanar points where two planes intersect were obtained from the distance algorithm. The building plane’s optimal segmentation was then obtained by combining the coarse extraction plane points and the corresponding coplanar points. The results show that the proposed method successfully segmented the plane points of the cottage and pantry. The optimal distance thresholds using the proposed method from the uncoarse extraction plane points to each plane boundary point of cottage and pantry were 0.025 m and 0.030 m, respectively. The highest correct rate and the highest error rate of the cottage’s (pantry’s) plane segmentations using the proposed method under the optimal distance threshold were 99.93% and 2.30% (98.55% and 2.44%), respectively. The F1 score value of the cottage’s and pantry’s plane segmentations using the proposed method under the optimal distance threshold reached 97.56% and 95.75%, respectively. This method can segment different objects on the same plane, while the random sample consensus (RANSAC) algorithm causes the plane to become over-segmented. The proposed method can also extract the coplanar points at the intersection of two planes, which cannot be separated using the region growing algorithm. Although the RANSAC-RG method combining the RANSAC algorithm and the region growing algorithm can optimize the segmentation results of the RANSAC (region growing) algorithm and has little difference in segmentation effect (especially for cottage data) with the proposed method, the method still loses coplanar points at some intersection of the two planes.

Improvement and Performance Evaluation When Implementing a Distance-Based Registration

An efficient location registration scheme is essential to continuously accommodate the increasing number of mobile subscribers and to offer a variety of multimedia services with good quality. The objective of this study was to analyze the optimal size for the location area of a distance-based registration (DBR) scheme by varying the number of location areas on a cell-by-cell basis, not on a ring-by-ring basis. Using our proposed cell-by-cell distance-based registration scheme with a random walk mobility model, a variety of circumstances were analyzed to obtain the optimal number of cells for location area for minimizing the total signaling cost on radio channels. Analysis results showed that the optimal number of cells for location area was between 4 and 7 in most cases. Our cell-by-cell distance-based location registration scheme had less signaling cost than an optimal ring-by-ring distance-based location registration scheme with an optimal distance threshold of 2 (the optimal number of cells for location area was 7). Therefore, when DBR is adopted, it must be implemented with an LA increasing on a cell-by-cell basis to achieve optimal performance.

长江下游平原区生态网络识别与优化——以常州市金坛区为例

生态网络识别与优化是保障区域生态安全格局，开展国土空间生态保护修复的重要研究手段。立足图论和景观生态学理论方法，以长江下游平原区的金坛区为例，利用遥感影像、土地利用数据、POI数据等，通过最小面积阈值、最佳距离阈值分析，识别了区域现状生态网络，开展了生态盲区指导下的生态网络优化，并对优化前后的生态网络性能、区域生境斑块重要性进行评价，取得以下研究结果：①开展生态盲区指导下生态网络优化，可显著提升区域景观连接度，且在生态水网区域具有较强适用性；②研究区存在生态景观断裂，生态网络布局亟待优化，经优化Harary指数增加了10.92倍，整体连接度指数提升了43.45%，可能性连接度指数提升了99.58%；③国土空间生态保护修复应重点关注关键区域整治，可采取重点斑块生态保护、关键节点生态修复、特殊区域生态建设等差异化生态网络修复策略。;Identification and optimization of ecological networks is an important research method to ensure the regional ecological security pattern and carry out the ecological protection and restoration of national land space. Based on theories of graph and landscape ecology, this paper took Jintan District in the lower reaches of the Yangtze River as an example, and used the remote sensing images, land use data, POI data, etc. Through the minimum area threshold and the optimal distance threshold analysis, the current ecological network of the region was identified, the ecological network under the guidance of the ecological blind zone was carried out, and the ecological network performance before and after optimization the importance of regional habitat patches was evaluated. This paper obtained the following results:① under the guidance of the ecological blind zone, ecological network optimization can significantly improve the connectivity of regional landscape and has strong applicability in ecological water network areas. ② There are ecological landscape fractures in some areas of research area, and the ecological network layout needs to be optimized. The optimized Harary index increased by 10.92 times. The overall connectivity index increased by 43.45%, and the possibility connectivity index increased by 99.58%. ③ National land space ecological protection and restoration should focus on key areas, and adopt the strategies of important patches ecological protection, key nodes ecological restoration, and special regions ecological construction for ecological network restoration.

Deep manifold clustering based optimal pseudo pose representation (DMC-OPPR) for unsupervised person re-identification

Person re-identification (re-ID) is highly complex in a diverse surveillance environment. The existing person re-ID methods are evaluated as a closed set problem with limited environmental variation. It is highly challenging to estimate the diverse poses of a dynamically crowded environment using the traditional unsupervised person re-ID methods. To resolve this issue of handling complex diverse poses and camera angles, a contextual incremental multi-clustering based unsupervised person re-ID method have been proposed. Cam-pose based optimal similarity distance threshold is determined to label the unlabeled person re-ID images efficiently. Frequent intra and inter-camera pseudo pose sequences are represented with optimal distance threshold. This resolves the over-fitting issue created by the dominant samples of an identity and reduces the source-target domain gap. The experimental results show the supremacy of our proposed method over the existing unsupervised person re-ID methods in handling complex poses and camera angles in an incremental self-learning diverse surveillance environment.

Analysis on the transmission characteristics of newly reported human immunodeficiency virus/acquired immunodeficiency syndrome cases based on the molecular transmission network in Huzhou, Zhejiang, 2017

Objective: Using field epidemiological investigation and molecular analysis to construct the molecular transmission network of human immunodeficiency virus/acquired immunodeficiency syndrome cases (HIV/AIDS) newly diagnosed in Huzhou in 2017, Zhejiang Province. Methods: A total of 160 participants were obtained through a web-based system from Chinese Center for Disease Control and Prevention (CCDC) with the features of diagnosed in Huzhou in 2017 who also had been collected samples for the first follow-up. The basic information of demographic characteristics and risk factors was extracted from the website. RNA was extracted from plasma samples of untreated cases, followed by RT-PCR and nest-PCR for pol gene amplification, sequencing. Phylogenetic tree was constructed by MEGA software for HIV gene subtyping. TN93 model was used for calculating the distance between two sequences. Cytoscape software was used for drawing molecular transmission network. And then an epidemiological survey was conducted to cases in the primary cluster. Results: A total of 138 sequenced individuals (86.3%) were acquired from 160 individuals. Among which, 123 (89.1%) were male. The highest proportion of subtype was CRF07_BC (60, 43.5%), followed by CRF01_AE (46, 33.3%), and with four cases of Unique Recombinant Form (URF, CRF01_AE and CRF07_BC) and one case of URF (subtype B and C). A total of 18 molecular clusters included 56 individuals (40.6%) were found in the transmission network under the optimal genetic distance threshold (1.0%). The clustering proportion of CRF07_BC (66.1%, 37 cases) was higher than that of CRF01_AE. There were 9 clusters formed among CRF07_BC, including 37 cases (accounting for 61.7%, 37/60). The primary transmission cluster contained 11 cases, among which 9 cases were transmitted by homosexual sex. The first time of the cases to have homosexual behavior is range from 2010 to 2016, whose media number (P(25), P(75)) of partners was 6 (3.5, 8.5). Most of the cases come from Anhui Province and engaged in garment industry (5 cases), between which there were 8 cases used Blued software to seek for casual partners, 1 case seeking for casual partners in garden. Conclusion: With CRF07_BC and CRF01_AE predominantly circulating, HIV genetic diversity had been noticed in this area. The primary cluster was consisted of high proportion of locally new infections, and a specific population aggregation in limited place existed.

The Optimal Distance Threshold for Fractional Frequency Reuse in Size-Scalable Networks

In the fractional frequency reuse (FFR) system, the bandwidth is partitioned into orthogonal subbands such that users in the cell-center region use the subbands of a frequency reuse factor (FR factor) equal to 1, whereas users in the cell-edge region exploit the subbands of an FR factor larger than 1. The distance threshold, which is used to distinguish the cell-edge region from the cell-center region, is an important factor in FFR system performance. In this paper, we study the optimal distance threshold to maximize system throughput in the downlink cellular networks, including aerial base stations. Subject to the constraint that a given target outage probability is satisfied, the optimal distance threshold is analyzed as a function of the cell size. It is proven that when the sizes of all cells in the network are scaled at the same rate, the optimal distance threshold normalized by the cell size is nondecreasing in the cell size. The analytical results in this paper provide a system design guideline for initial planning of FFR cellular networks of different sizes, including macro, pico, and femto systems. In particular, for size-scalable aerial networks comprising base stations in the sky, such as balloons or unmanned aerial vehicles, our analysis offers insight into the design of the distance threshold with regard to the cell size.

天津滨海新区湿地景观连接度距离阈值研究

PDF HTML阅读 XML下载 导出引用 引用提醒 天津滨海新区湿地景观连接度距离阈值研究 DOI: 10.5846/stxb201804190897 作者: 作者单位: 南开大学环境科学与工程学院,天津师范大学城市与环境科学学院,南开大学环境科学与工程学院 作者简介: 通讯作者: 中图分类号: 基金项目: 天津市自然科学基金科技特派员项目（16JCTPJC53900） Distance thresholds of wetland landscape connectivity in Tianjin Binhai New Area Author: Affiliation: College of Environmental Science and Engineering, Nankai University,,College of Environmental Science and Engineering, Nankai University Fund Project: Science and technology special project of Tianjin Natural Science Foundation 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:在应用景观连接度研究景观格局变化时，选择适宜的距离阈值是关键。适宜的距离阈值有利于识别景观中的关键斑块并及时发现连接脆弱的区域，对景观格局动态分析、生态恢复研究等均具有重要意义。以天津市滨海新区湿地生态系统为研究对象，将研究区域划分为不同的焦点景观，焦点景观是依据研究区域栖息候鸟的生境面积而划分的面积大小相同的区域，并通过ArcGIS中的泰森多边形分析实现，焦点景观分析可为面积更大、结构更加复杂的景观分析提供新的思路。文章选取斑块间链接数（NL）、组分数（NC）、等效连接面积指数（ECA）、景观巧合概率指数（LCP）来表征景观连接度，设定100、200、400、600、800、1000、1500、2000、3000、5000、8000 m共11个距离阈值，探讨不同距离阈值下各指数的变化规律，对比分析研究区域整体景观斑块和焦点景观内各斑块的连接度指数随距离阈值变化的异同，最终确定研究区域最佳距离阈值。结果表明：（1）各焦点景观内斑块的景观连接度指数随距离阈值的变化趋势与研究区域整体景观斑块相似且对应的最佳距离阈值相同；（2）天津市滨海新区湿地景观连接度距离阈值的适宜范围是400-800 m，该区间内进行景观格局分析研究能够较为真实的反映出研究区域实际景观状况；（3）通过进一步研究，最终确定400 m为天津滨海新区湿地景观连接度最佳距离阈值。研究结果可为天津市滨海新区湿地景观研究提供参考，在实际研究中距离阈值的选择可根据具体研究目标、研究层次需求等进行适当调整。 Abstract:When applying landscape connectivity to the study of landscape pattern changes, it is important to choose the appropriate distance threshold, which affects the analysis of landscape connectivity in the study area. If the distance threshold is set too low, the patches in the area will remain unconnected, and fragmentation will be severe, whereas if the distance threshold is set too high, the patches in the area are interconnected and grouped together. However, neither of these scenarios is likely to truly reflect the actual condition of the landscape in the study area. Using an appropriate distance threshold will facilitate the identification of key patches in the landscape and the discovery of vulnerable areas, both of which are important for the dynamic analysis of landscape patterns and ecological restoration studies. The present study investigated this principle using Landsat 8-OLI remote sensing images of a wetland ecosystem of the Tianjin Binhai New Area, taken on April 14, 2017. The research area was divided into different focal landscapes, in order to prevent software stalling and reductions in data processing speed that could have resulted from the large study area and provide a new analytical idea for this field. The focal landscape was the same size area, based on the habitat area of the migratory birds in the study area, and was analysed by Thiessen polygon analysis in ArcGIS. The number of links, number of components, equivalent connectivity area, and landscape coincidence probability were selected to characterize the landscape connectivity, and a total of 11 distance thresholds (100, 200, 400, 600, 800, 1000, 1500, 2000, 3000, 5000, and 8000 m) were selected to draw the ‘Landscape Connectivity Index-Distance Threshold’ curve, which was used to study the trend of each index under different distance thresholds. By comparing the overall landscape patch and the focal landscape connectivity index with distance thresholds, the optimal distance threshold for the study area was determined. (1) The optimal distance thresholds selected by the two methods of focal landscape and overall landscape patch were the same, and the proposed method provides new ideas for future regional landscape analysis and more complex ecological landscape pattern research. (2) The range of 400-800 m can be used as suitable distance threshold ranges for the dynamic change of landscape pattern and restoration of ecosystems in the Binhai New Area. In this interval, the connectivity of the habitat patch in the study area was relatively stable, which clearly illustrates the distribution of the patches and helps to identify the important patches in the landscape. (3) Through further research, 400 m was finally selected as the optimal distance threshold for the connectivity of the wetland ecosystem in Tianjin Binhai New Area. These findings provide a reference for studying wetland landscapes in the Tianjin Binhai New Area. In addition, the selection of the distance threshold in practical research can be adjusted according to specific research objectives and research level requirements. 参考文献 相似文献 引证文献

DNABarcoding as useful tool to identify crop pest flea beetles of Turkey

AbstractFlea beetles (Chrysomelidae: Galerucinae: Alticini), with ~8,000 species worldwide, include pest species causing substantial economic damage to crops. The generaPhyllotretaandChaetocnemainclude both pest and non‐pest species. An accurate and fast taxonomic identification approach is required for discriminating among taxa for non‐expert taxonomists; moreover, the utility of this approach spans from biodiversity conservation to the monitoring of pest species.DNAbarcoding represents a reliable and easy identification tool based on the use of shortDNAsequences. In this study, 45 newCOIsequences of 13Phyllotretaand fiveChaetocnemaspecies, representing ~30% and ~20% of the Turkish species belonging to these genera, were provided. These sequences increased by ~18% and ~25% the number of species of these genera whose sequences are available inBOLD. In order to testDNAbarcoding efficiency inPhyllotretaandChaetocnemaspecies identification, we created a data set consisting of sequences belonging to species present in the Middle East and available inBOLDplus the sequences developed in this study (36 species). The efficiency of species identification, estimated using best close match analysis (with the ad hoc calculated optimal distance threshold of 1.5%), was 99%. The overall intraspecific and interspecific mean nucleotide divergences were 1.4% and 20%, respectively. Interestingly,COIsequences ofPhyllotreta nigripesclustered into two well‐separated groups with a high value of the between‐group nucleotide distance (11.4%), which suggests the presence of cryptic species. In addition, information was provided on the crops exploited by the collected organisms and the observed damage.

Pilot contamination mitigation by fractional pilot reuse with threshold optimization in massive MIMO systems

In this paper, we propose a fractional pilot reuse (FPR) scheme to mitigate pilot contamination in massive multiple-input multiple-output (MIMO) system. In FPR, users are classified into the cell-center and the cell-edge ones according to their signal-to-interference-plus-noise ratios (SINRs) at the receiver side. Then, the cell-edge users with low SINRs in different cells use different pilots or orthogonal pilots to avoid strong interference from adjacent cells while the cell-center users with high SINRs in different cells reuse the same pilots to improve the pilot efficiency. In order to identify the cell-center users and the cell-edge ones, we first approximate the SINR as a function of the distance between the user and the base station (BS) and then find the relationship between the network throughput and the distance threshold. The optimal distance threshold is found to maximize the network throughput. The analytical and simulation results demonstrate advantages of the proposed scheme compared with the conventional schemes.

Identifying Transmission Clusters with Cluster Picker and HIV-TRACE.

We compared the behavior of two approaches (Cluster Picker and HIV-TRACE) at varying genetic distances to identify transmission clusters. We used three HIV gp41 sequence datasets originating from the Rakai Community Cohort Study: (1) next-generation sequence (NGS) data from nine linked couples; (2) NGS data from longitudinal sampling of 14 individuals; and (3) Sanger consensus sequences from a cross-sectional dataset (n = 1,022) containing 91 epidemiologically linked heterosexual couples. We calculated the optimal genetic distance threshold to separate linked versus unlinked NGS datasets using a receiver operating curve analysis. We evaluated the number, size, and composition of clusters detected by Cluster Picker and HIV-TRACE at six genetic distance thresholds (1%-5.3%) on all three datasets. We further tested the effect of using all NGS, versus only a single variant for each patient/time point, for datasets (1) and (2). The optimal gp41 genetic distance threshold to distinguish linked and unlinked couples and individuals was 5.3% and 4%, respectively. HIV-TRACE tended to detect larger and fewer clusters, whereas Cluster Picker detected more clusters containing only two sequences. For NGS datasets (1) and (2), HIV-TRACE and Cluster Picker detected all linked pairs at 3% and 4% genetic distances, respectively. However, at 5.3% genetic distance, 20% of couples in dataset (3) did not cluster using either program, and for >1/3 of couples cluster assignment were discordant. We suggest caution in choosing thresholds for clustering analyses in a generalized epidemic.

Optimal estimation of recurrence structures from time series

Recurrent temporal dynamics is a phenomenon observed frequently in high-dimensional complex systems and its detection is a challenging task. Recurrence quantification analysis utilizing recurrence plots may extract such dynamics, however it still encounters an unsolved pertinent problem: the optimal selection of distance thresholds for estimating the recurrence structure of dynamical systems. The present work proposes a stochastic Markov model for the recurrent dynamics that allows for the analytical derivation of a criterion for the optimal distance threshold. The goodness of fit is assessed by a utility function which assumes a local maximum for that threshold reflecting the optimal estimate of the system's recurrence structure. We validate our approach by means of the nonlinear Lorenz system and its linearized stochastic surrogates. The final application to neurophysiological time series obtained from anesthetized animals illustrates the method and reveals novel dynamic features of the underlying system. We propose the number of optimal recurrence domains as a statistic for classifying an animals' state of consciousness.

An Enhanced Energy Balanced Data Transmission Protocol for Underwater Acoustic Sensor Networks.

This paper presents two new energy balanced routing protocols for Underwater Acoustic Sensor Networks (UASNs); Efficient and Balanced Energy consumption Technique (EBET) and Enhanced EBET (EEBET). The first proposed protocol avoids direct transmission over long distance to save sufficient amount of energy consumed in the routing process. The second protocol overcomes the deficiencies in both Balanced Transmission Mechanism (BTM) and EBET techniques. EBET selects relay node on the basis of optimal distance threshold which leads to network lifetime prolongation. The initial energy of each sensor node is divided into energy levels for balanced energy consumption. Selection of high energy level node within transmission range avoids long distance direct data transmission. The EEBET incorporates depth threshold to minimize the number of hops between source node and sink while eradicating backward data transmissions. The EBET technique balances energy consumption within successive ring sectors, while, EEBET balances energy consumption of the entire network. In EEBET, optimum number of energy levels are also calculated to further enhance the network lifetime. Effectiveness of the proposed schemes is validated through simulations where these are compared with two existing routing protocols in terms of network lifetime, transmission loss, and throughput. The simulations are conducted under different network radii and varied number of nodes.

基于生境斑块的滇金丝猴景观连接度分析

PDF HTML阅读 XML下载 导出引用 引用提醒 基于生境斑块的滇金丝猴景观连接度分析 DOI: 10.5846/stxb201408191641 作者: 作者单位: 昆明理工大学环境科学与工程学院,云南财经大学野生动植物管理与生态系统健康研究中心,云南财经大学野生动植物管理与生态系统健康研究中心,云南财经大学野生动植物管理与生态系统健康研究中心,云南师范大学旅游与地理科学学院,云南财经大学野生动植物管理与生态系统健康研究中心 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目(31100351) Analysis of landscape connectivity of the Yunnan snub-nosed monkeys (Rhinopithecus bieti) based on habitat patches Author: Affiliation: Faculty of Environmental Science and Engineering, Kunming University of Science and Technology,Wildlife Management and Ecosystem Health center, Yunnan University of Finance and Economics,,,, Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:基于生境斑块,结合最小费用距离并运用图论法对滇金丝猴分布区进行栖息地连接度分析,研究利用猴群的现实分布结合Logistic回归模型确定了景观功能连接的最佳距离阈值,对于功能畅通的组分,以景观指数BC定量识别出作为"踏脚石"的优先保护区域;对于功能不连接的组分,绘制出最小费用路径,确定了该路径中优先恢复区域。结果表明:最佳的最小费用距离阈值为1400,该阈值下猴群主要存在于5个组分中,所有组分中猴群间的连接度优劣排序为组分3 > 组分1 > 组分5 > 组分4,龙马山猴群(G15)没有"踏脚石"斑块使其与同一组分内的其他猴群相连接,应考虑优先恢复该区域的植被,研究成果对于该物种的保护和其他濒危物种的类似研究具有较强的参考价值和借鉴意义。 Abstract:Habitat fragmentation is a major cause of biodiversity loss; it impedes gene flow between populations and interrupts the network of habitat patches. Populations are faced with a high risk of extinction owing to their small and isolated habitat patches. The maintenance of landscape connectivity can promote population movement between habitat patches, and this is extremely important to maintain gene flow and biological dispersal in fragmented landscapes. Using current habitat patches, the least-cost distance method and graph theory were implemented to study the habitat connectivity across the distribution of the Yunnan snub-nosed monkeys, and the optimal distance threshold of landscape functional connectivity was identified. Priority protected areas referred to as "stepping stones" were quantitatively identified based on highly connected functional components. The least-cost path was estimated to determine restoration priority areas for less connected functional components. This study had the following aims: (1) to explore new methods for identifying the optimal distance threshold, (2) to analyze the connectivity between monkey groups, and (3) to quantitatively analyze priority protected areas among monkey groups. The best resistance assignment for each habitat type was determined by a landscape genetics approach that combines the relationship between the least-cost-distance and gene flow, and reflects the promotion and impediment of the landscape matrix on species movement. The optimal threshold distance of least cost comprehensively reflected landscape features and species distribution characteristics; it incorporated the habitat area of each connected component into the monkey distribution. The priority conservation area was quantified using the landscape index. Based on the results, the optimal threshold distance of least cost was 1400 cost units. Monkey groups were mainly classified into five components that did not exceed this threshold, and the connectivity scores for monkey groups within components was Component 3 > Component 1 > Component 5 > Component 4. "Stepping-stone" patches do not exist in the Longma mountain group, resulting in a disconnect between that group and other monkey groups. This connection should first be restored. The results of this study can facilitate the protection of this and other species. 参考文献 相似文献 引证文献

Analysis of Distance-Based Location Management in Wireless Communication Networks

The performance of dynamic distance-based location management schemes (DBLMS) in wireless communication networks is analyzed. A Markov chain is developed as a mobility model to describe the movement of a mobile terminal in 2D cellular structures. The paging area residence time is characterized for arbitrary cell residence time by using the Markov chain. The expected number of paging area boundary crossings and the cost of the distance-based location update method are analyzed by using the classical renewal theory for two different call handling models. For the call plus location update model, two cases are considered. In the first case, the intercall time has an arbitrary distribution and the cell residence time has an exponential distribution. In the second case, the intercall time has a hyper-Erlang distribution and the cell residence time has an arbitrary distribution. For the call without location update model, both intercall time and cell residence time can have arbitrary distributions. Our analysis makes it possible to find the optimal distance threshold that minimizes the total cost of location management in a DBLMS.