Aggregation Points Research Articles

Salt-assisted microstructure evaluation of hydrophilic block copolymer F98: A thermal and scattering study

The temperature- and salt induced micellization and phase behavior of a very hydrophilic ethylene oxide (EO)-propylene oxide (PO) triblock copolymer Pluronic® F98 (EO118-PO46-EO118, 80% PEO) in aqueous solutions has been investigated by high sensitivity differential scanning calorimetry (HSDSC), viscosity, dynamic light scattering (DLS) and small-angle neutron scattering (SANS) measurements. Data on critical micellization temperature (CMT), cloud point (CP) and thermodynamic parameters for aggregation of F98 in water and salt solution are reported. Both CMT and CP decrease with an increase either in F98 concentration or NaCl concentration. The enthalpy and entropy change of micellization decreased with increasing F98 concentration. The process is related to dehydration of PEO blocks which is dominating factor for positive heat capacity. The solution viscosity of these Newtonian fluids shows significant increase at higher F98 concentration/higher temperature/presence of salt due to intermicellar interaction and is followed by a decrease due to progressive dehydration of PEO shell. SANS and DLS results show that micelles remain spherical with slight increase in size at all temperatures and in the presence of NaCl.

COMPLEX NETWORK SIMULATION OF FOREST NETWORK SPATIAL PATTERN IN PEARL RIVER DELTA

Abstract. Forest network-construction uses for the method and model with the scale-free features of complex network theory based on random graph theory and dynamic network nodes which show a power-law distribution phenomenon. The model is suitable for ecological disturbance by larger ecological landscape Pearl River Delta consistent recovery. Remote sensing and GIS spatial data are available through the latest forest patches. A standard scale-free network node distribution model calculates the area of forest network’s power-law distribution parameter value size; The recent existing forest polygons which are defined as nodes can compute the network nodes decaying index value of the network’s degree distribution. The parameters of forest network are picked up then make a spatial transition to GIS real world models. Hence the connection is automatically generated by minimizing the ecological corridor by the least cost rule between the near nodes. Based on scale-free network node distribution requirements, select the number compared with less, a huge point of aggregation as a future forest planning network’s main node, and put them with the existing node sequence comparison. By this theory, the forest ecological projects in the past avoid being fragmented, scattered disorderly phenomena. The previous regular forest networks can be reduced the required forest planting costs by this method. For ecological restoration of tropical and subtropical in south China areas, it will provide an effective method for the forest entering city project guidance and demonstration with other ecological networks (water, climate network, etc.) for networking a standard and base datum.

Congestion relaxation due to density-dependent junction rules in TASEP network

We now consider a small network module of Totally Asymmetric Simple Exclusion Process with branching and aggregation points, and rules of junctions dependent on the densities of segments of the network module. We also focus on the interaction among junctions which are branching and aggregation. The interaction among junctions with density-dependent rules possesses more complexity than those with density-independent rules studied in the previous papers. In conclusion, we confirm the result that density-dependent rules enable vehicles to move more effectively than the density-independent rules.

CLAP: Component-Level Approximate Processing for Low Tail Latency and High Result Accuracy in Cloud Online Services

Modern latency-critical online services such as search engines often process requests by consulting large input data spanning massive parallel components. Hence the tail latency of these components determines the service latency. To trade off result accuracy for tail latency reduction, existing techniques use the components responding before a specified deadline to produce approximate results. However, they skip a large proportion of components when load gets heavier, thus incurring large accuracy losses. In this paper, we propose CLAP to enable component-level approximate processing of requests for low tail latency and small accuracy losses. CLAP aggregates information of input data to create small aggregated data points. Using these points, CLAP reduces latency variance of parallel components and allows them to produce initial results quickly; CLAP also identifies the parts of input data most related to requests’ result accuracies, thus first using these parts to improve the produced results to minimize accuracy losses. We evaluated CLAP using real services and datasets. The results show: (i) CLAP reduces tail latency by 6.46 times with accuracy losses of 2.2 percent compared to existing exact processing techniques; (ii) when using the same latency, CLAP reduces accuracy losses by 31.58 times compared to existing approximate processing techniques.

Optimal data aggregation tree in wireless sensor networks based on improved river formation dynamics

AbstractThe restricted energy of nodes is one of the most important challenges in wireless sensor networks. Since data transmissions among nodes consume most of the nodes' energy, thus, minimizing the unnecessary transmissions reduces the consumed energy. One of the sources of this problem is the redundancy of raw data that can be eliminated at the aggregation points. As a result, data aggregation can be considered as an effective strategy to tackle the mentioned issue and to optimize the communication energy consumption. In this paper, the sensor nodes are organized in a tree structure, and the data aggregation are done in intermediate nodes at the junction of tree branches. One of the main characteristics of tree protocols is reduction of energy consumption through optimizing the structure of a data aggregation tree. For this, this paper proposes to apply a swarm intelligent algorithm named river formation dynamics. The simulation results show that the proposed algorithm outperforms in comparison to the famous ant colony optimization algorithm in terms of network lifetime. Simulations show that the proposed algorithm makes nearly 4% and 50% improvement in lifetime of wireless sensor networks than ant colony optimization and shortest path routing, respectively.

Convergent mechanisms favor fast amyloid formation in two lambda 6a Ig light chain mutants.

Extracellular deposition as amyloids of immunoglobulin light chains causes light chain amyloidosis. Among the light chain families, lambda 6a is one of the most frequent in light chain amyloidosis patients. Its germline protein, 6aJL2, and point mutants, R24G and P7S, are good models to study fibrillogenesis, because their stability and fibril formation characteristics have been described. Both mutations make the germline protein unstable and speed up its ability to aggregate. To date, there is no molecular mechanism that explains how these differences in amyloidogenesis can arise from a single mutation. To look into the structural and dynamical differences in the native state of these proteins, we carried out molecular dynamics simulations at room temperature. Despite the structural similarity of the germline protein and the mutants, we found differences in their dynamical signatures that explain the mutants' increased tendency to form amyloids. The contact network alterations caused by the mutations, though different, converge in affecting two anti-aggregation motifs present in light chain variable domains, suggesting a different starting point for aggregation in lambda chains compared to kappa chains.

Online stacking of carboxylated magnetite core-shell nanoparticles in capillary electrophoresis.

The stacking effect on carboxylated magnetite core-shell nanoparticles using sodium borate buffer pH 9.5 as the background electrolyte is presented. The ionic strength of the background electrolyte ranged from 5 to 100mM, and the ionic strength of a sample zone ranged from 5 to 100mM. Moreover, water was used as the sample dispersant. Both stacking and de-stacking effects were observed when conductivities of the sample zone and the background electrolyte differed. An explanation of carboxylated magnetic core-shell nanoparticles behavior was suggested based on the Derjaguin-Landau-Verwey-Overbeek theory supposing that the aggregation point is defined by the energetic barrier as the sum of energies given by electrostatic interactions and Van der Waals interactions. Moreover, the stacking conditions were applied for the evaluation of the lowest detectable dilution of magnetic nanoparticles. The carboxylated magnetic nanoparticles were dispersed in 10mM borate/NaOH pH 9.5 and injected for 60s to the background electrolyte composed of 100mM borate/NaOH pH 9.5 that allowed the detection of 100-fold diluted nanoparticles.

Scalable Route Map for Advanced Metering Infrastructure Based on Optimal Routing of Wireless Heterogeneous Networks

This article presents a scalable route map for the least cost deployment of wireless heterogeneous networks that support traffic from the advance metering infrastructure (AMI). We first explore the performance of a common scenario in which a single technology is employed to connect smart meters sending traffic to the utility. Based on simulations with actual city maps, we study the coverage provided to smart meters by an LTE cellular network. In order to improve the coverage, an optimization model that considers network capacity and range is proposed to determine the optimal location of base stations to achieve a target coverage of smart meters. According to these preliminary results with a single access technology, we propose an evolved network architecture that considers several alternatives of wireless heterogeneous networks to guarantee the coverage to smart meters with the least use of resources. We introduce a heuristic model that involves elements from base stations, universal data aggregation points, number of smart meters, and an optimal routing to achieve the desired connectivity from the group of smart meters. We employ geo-referenced models to consider actual characteristics of cities as well as geographical conditions. Results from the evolved model demonstrate that by combining technologies and employing data aggregation points with optimized localizations, the network is able to achieve a target coverage of smart meters with a reduced cost in terms of technological resources.

A combined-alpha-shape-implicit-surface approach to generate 3D random concrete mesostructures via digital image processing, spectral representation, and point cloud

Concrete aggregates have a random and complex shape, which has been shown to affect the mechanical properties of concrete. Commonly, they are approximated as spheres or polyhedra in 3D cases, or further simplified as circles or polygons in 2D cases. This study presents a numerical procedure for the stochastic characterization and representation of the aggregates and microcracks in concrete and the generation of virtual 3D random concrete mesostructures. Central to the proposed simulation method is the generation of realistic 3D aggregate point clouds based on an improved decomposition scheme and the conversion of the point clouds to 3D aggregate microstructures using a hybrid alpha-shape-implicit-surface algorithm. To optimize the simulation results, an image processing procedure and a set of representative aggregates are developed. It is shown that the proposed procedure is capable of reproducing high-quality concrete mesostructures with microcracks, which opens the door to unravelling complex microstructural behaviors of cement-based materials.

Endemic caseous lymphadenitis in a wild Caprinae population

Between 2010 and 2013, an outbreak of caseous lymphadenitis (CLA) occurred in a captive stock of Iberian ibexes (Capra pyrenaica, Schinz 1838) maintained for conservation purposes in the National Game...

An Experimental Evaluation of a Cooperative Communication-Based Smart Metering Data Acquisition System

Smart meters are being deployed globally on a trial basis and are expected to enable remote reading and demand response among other advanced functions, by setting up a two-way communication network. However, it remains to be determined as to how these meters will transmit their data to an aggregation point. An elegant solution to this problem is the use of cooperative communication in a neighborhood area network. This work experimentally compares cooperative networks, deployed in disparate environments, in terms of range extension and energy consumption of the overall network. Data transmissions take place through the universal software radio peripheral platforms. The method has been implemented in both indoor and outdoor environments, with cooperative transmission (CT) taking place over a multihop network, employing the binary phase shift keying scheme. The results indicate that CT can be used to effectively and reliably relay data in a network such as that in a smart grid.

A cross-sectional study to quantify the prevalence of avian influenza viruses in poultry at intervention and non-intervention live bird markets in central Vietnam, 2014.

In Vietnam, live bird markets are found in most populated centres, providing the means by which fresh poultry can be purchased by consumers for immediate consumption. Live bird markets are aggregation points for large numbers of poultry, and therefore, it is common for a range of avian influenza viruses to be mixed within live bird markets as a result of different poultry types and species being brought together from different geographical locations. We conducted a cross-sectional study in seven live bird markets in four districts of Thua Thien Hue Province in August and December, 2014. The aims of this study were to (i) document the prevalence of avian influenza in live bird markets (as measured by virus isolation); and (ii) quantify individual bird-, seller- and market-level characteristics that rendered poultry more likely to be positive for avian influenza virus at the time of sale. A questionnaire soliciting details of knowledge, attitude and avian influenza practices was administered to poultry sellers in study markets. At the same time, swabs and faecal samples were collected from individual poultry and submitted for isolation of avian influenza virus. The final data set comprised samples from 1,629 birds from 83 sellers in the seven live bird markets. A total of 113 birds were positive for virus isolation; a prevalence of 6.9 (95% CI 5.8-8.3) avian influenza virus-positive birds per 100 birds submitted for sale. After adjusting for clustering at the market and individual seller levels, none of the explanatory variables solicited in the questionnaire were significantly associated with avian influenza virus isolation positivity. The proportions of variance at the individual market, seller and individual bird levels were 6%, 48% and 46%, respectively. We conclude that the emphasis of avian influenza control efforts in Vietnam should be at the individual seller level as opposed to the market level.

Estimation of Field Reliability Based on Aggregate Lifetime Data

Because of the exponential distribution assumption, many reliability databases recorded data in an aggregate way. Instead of individual failure times, each aggregate data point is a summation of a series of collective failures representing the cumulative operating time of one component position from system commencement to the last component replacement. The data format is different from traditional lifetime data and the statistical inference is challenging. We first model the individual component lifetime by a gamma distribution. Confidence intervals for the gamma shape parameter can be constructed using a scaled χ2 approximation to a modified ratio of the geometric mean to the arithmetic mean, while confidence intervals for the gamma rate and mean parameters, as well as quantiles, are obtained using the generalized pivotal quantity method. We then fit the data using the inverse Gaussian (IG) distribution, a useful lifetime model for failures caused by degradation. Procedures for point estimation and interval estimation of parameters are developed. We also propose an interval estimation method for the quantiles of an IG distribution based on the generalized pivotal quantity method. An illustrative example demonstrates the proposed inference methods. Supplementary materials for this article are available online.

The False Prometheus: Customer Choice, Smart Devices and Trust

In the information society of today, privacy is a premium service and user-related information a commodity. This development has gone unnoticed for many, but for some it contradicts with their common sense and perception of right and wrong. If we look into user agreements, and the effect Fair Information Practice Principles (FIPPs) seem to have, this development is particularly evident. One-on-one agreements such as End User License Agreements (EULAs) between the providers and users have become ubiquitous to most users who simply scroll through the agreement and click ‘I agree’ without actually understanding or caring what they have accepted.There are various reasons for this kind of behavior ranging from complete indifference, to inadequate internet and technology literacy, and even to peer pressure as certain applications have become a ‘must have’ amongst a group of users. This problem is particularly current as personal mobile devices have become important, for some even inseparable, part of our daily lives. These devices, such as smart phones and tablets, have also become user-centered aggregation points of information that contain personal, even sensitive information about us, and those around us. At the same time, the number of different applications that have practically unrestrained access to the Internet, is on the rise.When combined with ignorance and negligence, the risk of placing personal information into wrong hands is a very real one. In the following, we focus on this well-explored challenge from a novel perspective; informed consent, and argue that one way to address this problem is to develop solutions that not only promote personal choice and awareness, but are also context-dependent. In order to provide a practical insight into our primarily conceptual work, we use one of the most popular applications, the Pokémon GO by Niantic Inc., in highlighting some of the encountered privacy-related issues.

The Scholix Framework for Interoperability in Data-Literature Information Exchange

The Scholix Framework (SCHOlarly LInk eXchange) is a high level interoperability framework for exchanging information about the links between scholarly literature and data, as well as between datasets. Over the past decade, publishers, data centers, and indexing services have agreed on and implemented numerous bilateral agreements to establish bidirectional links between research data and the scholarly literature. However, because of the considerable differences inherent to these many agreements, there is very limited interoperability between the various solutions. This situation is fueling systemic inefficiencies and limiting the value of these, separated, sets of links. Scholix, a framework proposed by the RDA/WDS Publishing Data Services working group, envisions a universal interlinking service and proposes the technical guidelines of a multi-hub interoperability framework. Hubs are natural collection and aggregation points for data-literature information from their respective communities. Relevant hubs for the communities of data centers, repositories, and journals include DataCite, OpenAIRE, and Crossref, respectively. The framework respects existing community-specific practices while enabling interoperability among the hubs through a common conceptual model, an information model and open exchange protocols. The proposed framework will make research data, and the related literature, easier to find and easier to interpret and reuse, and will provide additional incentives for researchers to share their data.

Backward propagation of congestion in TASEP ladder-network

In the network of self-driven particles, aggregation points make velocities of particles smaller and branching points make larger. We consider a ladder-shaped network of totally asymmetric simple exclusion process in order to investigate correlations among multiple junctions by extending our previous results about “critical ellipse” which is the condition where the congestion of particles near the aggregation point propagates to the upstream of the branching point. We have theoretically derived the condition of interactions among the congestion from different aggregation points in the network.

Bridging Gaps: A Framework for Developing Regional Food Systems

Local food research has been generally focused on strengthening the alternative food system by scaling up local agriculture, rather than advancing strategies to bridge gaps between local farmers and conventional food retail businesses. Competitive advantage theory forms the foundation of a frame­work based on Porter’s (1985) firm (business unit) value chain for investigating food system gaps, and a logic model for promoting development by adding value throughout the alternative food supply chain. In the present study, a survey created jointly by local stakeholders investigated factors that food retail businesses consider when sourcing local food. Among the top rated factors, support­ing the local economy (opportunity) and regular delivery (barrier) were seen as significant to the regional food system of the Algoma District in central Canada. Mapping these factors through the firm value chain framework revealed a high degree of interconnectedness to other factors in the survey, including importance of obtaining fresh food, consistency of supply throughout the year, and reducing overall costs of supplying affordable products. Analysis of the survey results from the perspective of a food retail business pointed to information technology and coordinated distribu­tion methods as playing important roles in adding value to the regional food system. In addition to these results, the downtown of the study site has emerged as an aggregation point for local food, and local food may be playing a role in revitalizing the downtown. The value chain framework analysis can be applied to other localities to bridge gaps between local farmers and conventional supply chain actors.

Finding dense locations in symbolic indoor tracking data: modeling, indexing, and processing

Finding the dense locations in large indoor spaces is very useful for many applications such as overloaded area detection, security control, crowd management, indoor navigation, and so on. Indoor tracking data can be enormous and are not immediately ready for finding dense locations. This paper presents two graph-based models for constrained and semi-constrained indoor movement, respectively, and then uses the models to map raw tracking records into mapping records that represent object entry and exit times in particular locations. Subsequently, an efficient indexing structure called Hierarchical Dense Location Time Index (HDLT-Index) is proposed for indexing the time intervals of the mapping table, along with index construction, query processing, and pruning techniques. The HDLT-Index supports very efficient aggregate point, interval, and duration queries as well as dense location queries. A comprehensive experimental study with both real and synthetic data shows that the proposed techniques are efficient and scalable and outperforms RDBMSs significantly.

Conductometric and fluorescence probe analysis on molecular interactions between cationic surfactants in aqueous medium of glycyl dipeptide: Concentration and temperature effect

The effect of cationic micelles of cetyltrimethylammonium bromide (CTAB) and dodecyltrimethylammonium bromide (DTAB) on interactions of glycyl dipeptide in aqueous medium have been studied in varying concentrations (0.001, 0.005 and 0.010mol·kg–1) at different temperatures (293.15K to 293.15K). The conductivity method has been employed to determine critical micelle concentration, CMC i.e. point of aggregation and the results have been discussed in terms of glycylglycine–CTAB/DTAB hydrophobic and electrostatic interactions in aqueous medium. The obtained CMC values reveal the fact that the micellization tendency of the surfactant increases in the presence of glycyl dipeptide. The CMC’s of CTAB and DTAB have been found to decrease from 0.87 to 0.66mmol·kg–1 and 14.2–13.7mmol·kg–1 respectively as the [Glycyl dipeptide] increased from 0.001 to 0.010mol·kg–1. The temperature dependence of the CMC values has been established in terms of ion–ion, ion–polar and hydrophobic–hydrophobic group interactions around the hydrophobic part of surfactants. Furthermore, the standard thermodynamic parameters of micellization have been evaluated and interpreted which enable to grasp fully the ion–ion/ion–hydrophilic interactions existing in the present ternary (surfactant–dipeptide–water) system. In addition, the pyrene fluorescence technique has been used to study the change of micropolarity produced by the interactions of surfactants with glycyl dipeptide and the aggregation behaviour (CMC determination) of surfactants.

Fuzzy-based trusted routing to mitigate packet dropping attack between data aggregation points in smart grid communication network

Providing adequate security measure during data transmission is one of the essential requirements of smart grid communication network (SGCN). In this paper, a novel trust management model is proposed to alleviate packet dropping attack between data aggregation points of SGCN. The concept of probability theory is used to calculate trust of every node in the network before transmitting the packet. Trust evaluation is conducted in four stages viz., Direct, Indirect, Integrated and Overall trust and in each stage, suitable equations are suggested to measure the trust of each node. A novel technique based on fuzzy set theory is used to route the packet through the trusted channel. Hop count, reliability and capacity of the link are the parameters considered for constructing if-then rules and membership function. A qualitative reasoning is performed using inference mechanism and a defuzzication strategy is applied on the calculated trust value to make decision. Simulations are carried out to evaluate the performance of the proposed approach by varying the trust threshold and malicious nodes. From the experiments, it is observed that for all the metrics, the proposed trusted routing using fuzzy theory helps to improve the network performance with much reliable communication and reduced packet loss.