Aggregation Points Research Articles

Human γS-Crystallin-Copper Binding Helps Buffer against Aggregation Caused by Oxidative Damage.

Divalent metal cations can play a role in protein aggregation diseases, including cataract. Here we compare the aggregation of human γS-crystallin, a key structural protein of the eye lens, via mutagenesis, ultraviolet light damage, and the addition of metal ions. All three aggregation pathways result in globular, amorphous-looking structures that do not elongate into fibers. We also investigate the molecular mechanism underlying copper(II)-induced aggregation. This work was motivated by the observation that zinc(II)-induced aggregation of γS-crystallin is driven by intermolecular bridging of solvent-accessible cysteine residues, while in contrast, copper(II)-induced aggregation of this protein is exacerbated by the removal of solvent-accessible cysteines via mutation. Here we find that copper(II)-induced aggregation results from a complex mechanism involving multiple interactions with the protein. The initial protein-metal interactions result in the reduction of Cu(II) to Cu(I) with concomitant oxidation of γS-crystallin. In addition to the intermolecular disulfides that represent a starting point for aggregation, intramolecular disulfides also occur in the cysteine loop, a region of the N-terminal domain that was previously found to mediate the early stages of cataract formation. This previously unobserved ability of γS-crystallin to transfer disulfides intramolecularly suggests that it may serve as an oxidation sink for the lens after glutathione levels have become depleted during aging. γS-Crystallin thus serves as the last line of defense against oxidation in the eye lens, a result that underscores the chemical functionality of this protein, which is generally considered to play a purely structural role.

Long-Term Determinants of Tuberculosis in the Ungulate Host Community of Doñana National Park.

Animal tuberculosis (TB) is endemic in wild boar (Sus scrofa), red deer (Cervus elaphus), fallow deer (Dama dama) and cattle in south and central Spain. In order to clarify the processes that operate in the medium and long-term, we studied TB at the wildlife–livestock interface in Doñana National Park for 14 years (2006–2018) in relation to host density, stochastic factors (rainfall) and environmental features (e.g., aggregation points such as waterholes). Wild boar showed the highest prevalence of TB (76.7%), followed by red deer (42.5%), fallow deer (14.4%) and cattle (10.7%). We found evidence of relevant epidemiological processes which operate over the long-term and interact with host and community ecology. Interestingly, the effect of high wild boar population density on increased TB rates was mediated by sows, which could determine high incidence in young individuals already in maternal groups. Rainfall significantly determined a higher risk of TB in male red deer, probably mediated by sex-related differences in life history traits that determined more susceptibility and/or exposure in comparison to females. The positive association between the prevalence of TB in fallow deer and cattle may indicate significant interspecies transmission (in either direction) and/or similar exposure to risk factors mediated by ecological overlapping of grazing species. The identification of long-term drivers of TB provided evidence that its control in extensive pastoral systems can only be achieved by targeting all relevant hosts and integrating measures related to all the factors involved, such as: population abundance and the aggregation of wild and domestic ungulates, environmental exposure to mycobacteria, cattle testing and culling campaigns and adjustments of appropriate densities.

SIMPLIFIED ANALYSIS OF BUILDING SEISMIC STABILITY USING PRINCIPLES OF SPECTRUM CAPACITY METHOD

According to the current DBN, it is possible to apply the nonlinear static analysis based on the load-bearing capacity spectrum method. This analysis is allocated by essential simplicity in comparison with the direct dynamic method and also possibility of application as its alternative, considering necessity of application of a direct dynamic method also for buildings (constructions) of the responsibility class SS2. At the same time the complete nonlinear static analysis is also enough complex and sensitive to possible errors in modelling, after all it needs creation of nonlinear model of entire building. Aggregate points of analysis on seismic influences by the spectral method and the nonlinear static analysis (on the basis of the method of bearing capacity spectrum) according to the current DBN allow to execute the last (nonlinear static analysis) with proved simplifications regarding creation of spectrum load-bearing capacity diagram for constructive system on the basis of results conditionally linear spectral analysis.

Quantifying wildlife-livestock interactions and their spatio-temporal patterns: Is regular grid camera trapping a suitable approach?

Abstract Camera trapping use has increased significantly in ecological studies in recent decades due to its ability to register information about cryptic and/or elusive species and, more recently, due to its ability to derive population parameters, such as population abundance or density. For these latter applications, camera traps set in a regular grid pattern (CT-RG) are required to obtain representative information of the study area. The present work aims to assess the usefulness of the information collected through CT-RG to study interspecific interactions between animals, in terms of frequency of interaction and their spatiotemporal pattern. The results from CT-RG were compared with those obtained from GPS collars. For this latter methodology, 31 individuals were monitored with GPS-GSM collars (9 red deer [Cervus elaphus], 7 fallow deer [Dama dama], 6 wild boar [Sus scrofa] and 9 cows). The results showed that all the types of interactions recorded by GPS devices were also recorded by CT-RG. However, the relative frequency of each type of interspecific interaction was not precisely estimated using CT-RG. Nor did we observe an overlap between methodologies in the temporality of the interactions. These results are possibly due to most of the interactions tending to occur at aggregation points, which cannot be sufficiently represented by a regular grid. Finally, the spatial pattern obtained from CT-RG correlated with those obtained with GPS collars. Nowadays, camera trapping is being established as an affordable and effective tool to study different population parameters and, therefore, a huge amount of area is monitored with these devices using regular grids. Our results suggest that the information obtained through CT-RG can also be used to study the patterns of interaction between species.

A Novel Framework for Fog Computing: Lattice-Based Secured Framework for Cloud Interface

Interconnection and intercommunication between people, processes, and things have been enhanced with the development of the Internet of Things (IoT) and extended with fog computing for better efficiency. Fog computing improves the network services and circumvents the problem of escalated data management as an interface between cloud and terminal with the requirement of secure data transmission. In this article, a novel security framework is designed for fog computing intended for improving the security of IoT. This framework uses single point of aggregation from fog interface and lattice cryptographic approach to establish the security for the services. Azure cloud platform and Sage lattice cryptographic base have been employed to evaluate the performance of the framework. It is noticed that the Level 1-Level 2 (L1–L2) cache implementation in the system significantly improves the efficiency of the framework. The results show that the proposed framework is robust in preventing attacks on fog nodes and additionally provides an advantage for low communication overhead.

Microstructural analysis of the effects of compaction on fatigue properties of asphalt mixtures

ABSTRACT In the current approaches to structural analysis for asphalt pavements, the entire pavement material is usually treated to identical material, which disregards the distinct heterogeneity of asphalt mixture. Asphalt mixture is actually a multi-phase heterogeneous material that is composed of air voids, aggregate and asphalt binder. In this study, asphalt specimens were drilled from a test track and the indirect tensile fatigue test was conducted to study the fatigue properties. Digital Image Processing (DIP) was used to investigate the microstructural changes of the asphalt specimens based on X-ray Computed Tomography (X-ray CT) images. The aggregate orientation and number of aggregate contact points were determined. The distribution of the air-voids content and shape index of air voids before and after the fatigue tests were comprehensively discussed. According to the results, the microscopic analysis can effectively predict the evolutions of the internal structures of asphalt mixtures during fatigue damage. The heterogeneity due to different degrees of compaction significantly affects the fatigue properties of the asphalt mixtures. This study not only provides support for the further research on the relationship between the microstructural characteristics and mechanical damages of asphalt mixture but also provides implications for conducting the structural mechanical analysis of asphalt pavement.

Are Roadkill Hotspots in the Cerrado Equal Among Groups of Vertebrates?

Understand the spatial distribution of wildlife roadkill is necessary to design mitigation measures minimizing damage to the fauna and the human population. Thus, we aimed to analyze the spatial distribution of wildlife roadkill in the Brazilian savanna ("Cerrado") to test whether roadkill hotspots match between the studied animal groups. We collected data of wildlife roadkill over a year in the southwest region of the state of Goiás, Brazil. To understand the distribution of roadkill on highways and to identify the aggregation hotspots, we used the modified two-dimensional Ripley K test and the two-dimensional hotspot identification analysis. We detected that birds and mammals have different aggregation points. These points may vary when the two groups are analyzed together or when species with greater abundance are removed from the analyses. Hence, we concluded that using generalist approaches including several species, are not enough, and can lead to erroneous conclusions. Therefore, it is necessary that the analyses be done in groups.

Dynamic Network of Interactions in the Wildlife-Livestock Interface in Mediterranean Spain: An Epidemiological Point of View.

The correct management of diseases that are transmitted between wildlife and livestock requires a reliable estimate of the pathogen transmission rate. The calculation of this parameter is a challenge for epidemiologists, since transmission can occur through multiple pathways. The social network analysis is a widely used tool in epidemiology due to its capacity to identify individuals and communities with relevant roles for pathogen transmission. In the present work, we studied the dynamic network of interactions in a complex epidemiological scenario using information from different methodologies. In 2015, nine red deer, seven fallow deer, six wild boar and nine cattle were simultaneously monitored using GPS-GSM-Proximity collars in Doñana National Park. In addition, 16 proximity loggers were set in aggregation points. Using the social network analysis, we studied the dynamic network of interactions, including direct and indirect interactions, between individuals of different species and the potential transmission of pathogens within this network. The results show a high connection between species through indirect interactions, with a marked seasonality in the conformation of new interactions. Within the network, we differentiated four communities that included individuals of all the species. Regarding the transmission of pathogens, we observed the important role that fallow deer could be playing in the maintenance and transmission of pathogens to livestock. The present work shows the need to consider different types of methodologies in order to understand the complete functioning of the network of interactions at the wildlife/livestock interface. It also provides a methodological approach applicable to the management of shared diseases.

Scheduling Optimization of Time-Triggered Cyber-Physical Systems Based on Fuzzy-Controlled QPSO and SMT Solver

The time-triggered communication paradigm is a cost-efficient way to meet the real-time requirements of cyber-physical systems. It is a non-deterministic polynomial NP-complete problem for multi-hop networks and non-strictly periodic traffic. A two-level scheduling approach is proposed to simplify the complexity during optimization. In the first level, a fuzzy-controlled quantum-behaved particle swarm optimization (FQPSO) algorithm is proposed to optimize the scheduling performance by assigning time-triggered frame instances to the basic periods of each link. In order to prevent population from high aggregation, a random mutation mechanism is used to disturb particles at the aggregation point and enhance the diversity at later stages. Fuzzy logic is introduced and well designed to realize a dynamic adaptive adjustment of the contraction–expansion coefficient and mutation rate in FQPSO. In the second level, we use an improved Satisfiability Modulo Theories (SMT) scheduling algorithm to solve the collision-free and temporal constraints. A schedulability ranking method is proposed to accelerate the computation of the SMT-based incremental scheduler. Our approach can co-optimize the jitter and load balance of communication for an off-line schedule. The experiments show that the proposed approach can improve the performance of the scheduling table, reduce the optimization time, and reserve space for incremental messages.

Abstract TP373: Developing a Pre-Arrival Report Card

Background and Purpose: Hospitals’ communication with EMS on pre-arrival evidence based measures is essential in ensuring the best care for stroke patients in their community. To assist in assessing EMS pre-hospital care, the Wisconsin Coverdell Stroke Program (Coverdell) developed a quarterly report card for each of our participating hospitals. Coverdell’s 66 participating hospitals represent 78% of annual stroke admissions to Wisconsin hospitals. Coverdell utilizes the data entered into Get With The Guidelines® (GWTGs) - Special Initiatives tab. The data in the report card can be used to identify gaps in quality stroke care, followed by identifying performance improvement opportunities which can be initiated to address these gaps in care. Methods: Coverdell hospitals participate in the quarterly Coverdell Learning Collaborative (CLC) where they review several aggregated data points. CLC recognized a report card would provide an opportunity for participating hospitals to discuss the pre-arrival quality measures with their EMS providers and assist in developing a trusting relationship. To develop the report card, Coverdell’s Epidemiologist and Stroke Project Specialist analyzed the data measures from the GWTGs- Special Initiatives tab. We determined the need to provide benchmark groups for comparison, and to have established goals for each measure to assist in motivating and gauging progress of quality improvement initiatives. Findings: Coverdell released the pilot quarterly report card in Q3 2018. We then met with Stroke Coordinators whose hospitals were entering into the GWTGs Special Initiatives tab to discuss the goals, measures, and the need for modifications. The Q4 2018 report card incorporated the identified edits. Conclusion: Providing quarterly report cards with EMS pre-arrival measures will assist hospitals and their EMS providers in jointly identifying, planning, and implementing performance improvement initiatives in efforts to ensure seamless transitions of care for stroke patients in their community.

Abstract TP258: Increasing Emergency Medical Services Pre-Notification Results in Faster Alteplase Administration and Increased Thrombectomy Therapy

Background and Purpose: EMS pre-notification of a suspected acute stroke patient assists the hospital in mobilizing the appropriate personnel and resources before the patient arrives. The pre-notification by EMS and mobilization of the hospitals stroke team will increase the probability of the appropriately screened acute stroke patient receiving thrombolytic therapy. The Wisconsin Coverdell Stroke Program (Coverdell) performed a multi-quarter analysis of the successes and barriers hospitals were experiencing with EMS pre-notifying, with an overarching goal to increase this percentage to >80%. Methods: Coverdell’s 66 participating hospitals represent 78% of annual stroke admissions to Wisconsin hospitals. Coverdell hospitals participate in the quarterly Coverdell Learning Collaborative (CLC) where they review several aggregated data points. Of these, EMS pre-notification times are analyzed and discussed. Stroke Coordinators at hospitals’ performing at a high level shared with the CLC their performance improvement activities and best practices related to EMS pre-notification. Methods used consisted of, educating and training EMS caregivers on improving pre-arrival notification by communicating in plain language stroke symptoms or verbalizing a “possible stroke”; educating and training emergency department caregivers on where to document the EMS pre-arrival report in the EHR; and educating the stroke data abstractor on where the EMS pre-hospital report is located in the EHR. Findings: In analyzing quarterly data from Q1 2017 to Q1 2019, our multi-disciplinary approach demonstrates impressive results. EMS pre-notification rose from 68.1% to 77.0%, with 82% reached in Q2 2018. Associated with this the median DTN time for those arriving by EMS decreased from 49 to 44 minutes, with the lowest median time in Q2 2018 of 42.5 minutes. Furthermore, thrombectomy therapy (alteplase and mechanical thrombectomy) administration rates increased from 21.5% to the highest in Q2 2018 at 26.8%. Conclusion: A multi-faceted approach focused on improving communication between EMS and hospitals by pre-notifying of a suspected stroke patients arrival, has led to remarkable improvements in Coverdell’s outcome data.

Commercial viability of lunar In-Situ Resource Utilization (ISRU)

In this paper, we propose an architecture for lunar in-situ resource utilization (ISRU) which can provide propellant, typically cryogenic hydrogen and oxygen, to a cislunar aggregation point in support of future space missions to the Moon, Mars, and beyond at a price competitive with commercial delivery from Earth. This architecture is premised on maximizing the non-linear scaling laws of key system components: the ISRU plant, the nuclear reactor, and the reusable lunar lander. Engineering and cost models were developed to evaluate the impact of non-linear scaling laws on a reference architecture. The scaling laws applicable to each key system component were evaluated and incorporated in our model. We also provide sensitivity analysis showing how the model is impacted by commercial delivery costs to the cislunar aggregation point. This study showed that the cost of propellant sourced from lunar ISRU production can be lower than that delivered from Earth when maximal scale is utilized in sizing the key system components.

A Stochastic Aggregate Harmonic Load Model

This article presents a stochastic aggregate harmonic load model that can be used to accurately replicate the stochastic behavior of the network impedance downstream of a point of aggregation. The method has been applied to three low voltage networks and the results show that it is able to accurately represent their stochastic behavior while significantly reducing the computational burden compared to modelling the downstream network in detail.

Scalable Graph Convolutional Networks With Fast Localized Spectral Filter for Directed Graphs

Graph convolutional neural netwoks (GCNNs) have been emerged to handle graph-structured data in recent years. Most existing GCNNs are either spatial approaches working on neighborhood of each node, or spectral approaches based on graph Laplacian. Compared with spatial-based GCNNs, spectral-based GCNNs are capable of highly exploiting graph structure information, but always regard graphs undiredcted. Actually, there are many scenarios where the graph structures are directed, such as social networks, citation networks, etc. Treating graphs undirected may lose important information, which is helpful for graph learning tasks. This motivate us to construct a spectral-based GCNN for directed graphs. In this paper, we propose a scalable graph convolutional neural network with fast localized convolution operators derived from directed graph Laplacian, which is called fast directed graph convolutional network (FDGCN). FDGCN can directly work on directed graphs and can scale to large graphs as the convolution operation is linear with the number of edges. Furthermore, we find that FDGCN can unify the graph convolutional network (GCN), which is a classic spectral-based GCNN. The mechanism of FDGCN is thoroughly analyzed from spatial aggregation point of view. Since previous work has confirmed that considering uncertainty of graph could promote GCN a lot, the proposed FDGCN is further enhanced through extra training epochs on random graphs generated by mixed membership stochastic block model (MMSBM). Experiments are conducted for semi-supervised node classification tasks to evaluate the performance of FDGCN. Results show that our model can outperform or match state-of-the-art models in most cases.

Wormhole Detection Mechanism in Wireless Sensor Networks

A Wireless Sensor Network (WSN) is a component with sensor nodes that continuously observes environmental circumstances. Sensor nodes accomplish different key operations like sensing temperature and distance. It has been used in many applications like computing, signal processing, and network selfconfiguration to expand network coverage and build up its scalability. The Unit of all these sensors that exhibit sensing and transmitting information will offer more information than those offered by autonomously operating sensors. Usually, the transmitting task is somewhat critical as there is a huge amount of data and sensors devices are restricted. Being the limited number of sensor devices the network is exposed to different types of attacks. The Traditional security mechanisms are not suitable for WSN as they are generally heavy and having limited number of nodes and also these mechanisms will not eliminate the risk of other attacks. WSN are most useful in different crucial domains such as health care, environment, industry, and security, military. For example, in a military operation, a wireless sensor network monitors various activities. If an event is detected, these sensor nodes sense that and report the data to the primary (base) station (called sink) by making communication with other nodes. To collect data from WSN base Stations are commonly used. Base stations have more resources (e.g. computation power and energy) compared to normal sensor nodes which include more or less such limitations. Aggregation points will gather the data from neighboring sensor nodes to combine the data and forward to master (base) stations, where the data will be further forwarded or processed to a processing center. In this manner, the energy can be preserved in WSN and the lifetime of network is expanded.

Availability and Fade Margin Calculations for 5G Microwave and Millimeter-Wave Anyhaul Links

The deployment of new radio access technologies always provides a good opportunity and timing to optimize the existing mobile front- and backhaul (commonly called “anyhaul”). The legacy systems (Long-Term Evolution (LTE), High-Speed Packet Access (HSPA), third-generation mobile (3G), second-generation mobile (2G)) already extensively utilize the transmission and transport capacities of the mobile anyhaul. With the current launch of 5G (fifth-generation mobile) and recent LTE-A (Advanced Long-Term Evolution), additional new transmission capacities are required again. Depending on the traffic and network topology, additional cell sites are built, and even more locations are connected with fiber optics. The existing microwave and millimeter-wave links are rotated toward those aggregation points that already have optical-fiber access. Due to the increased cell-site density, the average distance of the radio access links can be reduced by network and topology optimization. The reduced hop lengths combined with adaptive modulation and automatic power control bring an opportunity for capacity increase in shortened radio links. Links newly deployed for 5G find a wide spectrum in the millimetric V, E, W, and D frequency bands. This paper discusses the availability and hop-length targets of the anyhaul links that should be carefully kept by proper planning and monitoring.

Research on Population Spatiotemporal Aggregation Characteristics of a Small City: A Case Study on Shehong County Based on Baidu Heat Maps

Baidu heat maps can be used to explore the pattern of individual citizens conducting their activities and their agglomeration effects at the city scale. To investigate the spatiotemporal pattern of population aggregation and its relationship with land parcel attributes in small cities, we collected Baidu heat map data for a weekday and a weekend day in Shehong County and used Getis–Ord general G and the raster overlay methods to analyze population aggregation spatiotemporal characteristics. Chi-squared and Pearson correlation tests were used to analyze the correlation between population aggregation and land parcel attributes against three types of land parcel divisions: land use parcels, road network blocks, and grids. The results showed that, (1) for most hours of the workday, the degree of population aggregation was greater than on the weekend, and the fluctuation magnitude on the workday was higher as well. (2) On the weekday, people clustered and dispersed faster than on the weekend. (3) On the weekday and weekend, the spatial position of people aggregation was highly overlapping. (4) The correlation between the degree of population aggregation and the type of parcel was not significant. (5) Regarding different parcel unit sizes, the correlations between population aggregation degree and point of interest (POI) density, floor area ratio, and building density were significant and positively correlated, and the correlation coefficients increased as the grid size increased.

Product Service Platform to improve care systems for elderly living at home

BackgroundPopulation aging is inducing governments to redesign their healthcare models. One policy measure aimed at reducing healthcare expenditures and improving services is to encourage people to age-in-place. Scientific research has been trying to find ICT-enabled solutions to the growing problem of elderly home care. However, such research is often technology-oriented and neglects the end-user perspective. It does not consider the real needs of older people and all stakeholders involved in their healthcare. MethodA user-centered design approach was adopted with the involvement of older people, experts dealing with the aging population, and the whole stakeholders’ chain. Through surveys, focus groups, and brainstorming sessions, it was possible to determine the main features of the product service platform. ResultsStarting from a large-scale survey of elderly people living in Italy, this paper presents the requirements and the architecture of a product service platform aimed at improving the independence and elderly quality of life. This work proposes an elderly-centered platform that works as an aggregation point of an articulated social health system, provides multiple tailored services, and optimizes the use of local resources. ConclusionsThe involvement of the end-user and all the stakeholders allowed for the consideration of different perspectives and the creation of a value network that aggregates existing services, resources, and information with new opportunities to achieve common benefits. This work provides guidelines on how to develop this type of platform by exploiting the potential of each stakeholder without creating new barriers. Technology, caregivers, and society are combined synergistically to provide tailored services able to satisfy specific users’ needs.

Cost-efficient approximation algorithm for aggregation points planning in smart grid communications

Smart grid is in need of an efficient communication network to guarantee reliable two-way data transmission between the control center and smart meters (SMs). In this work, a software-defined networking (SDN) based smart grid communication (SGC) scheme is introduced to fulfill the information transmission requirement, where the control plane is separated from the data plane to support diverse services flexibly in the smart grid. In such an SDN-based SGC system, to guarantee effective data processing and forwarding between the SMs and the control center, aggregation points (APs) are introduced. These APs should be deployed in an optimal way so as to cut down the total capital expenditure of the SGC system. The total cost generally includes the transmission cost between APs and the control center as well as APs and SMs. The construction and maintenance cost of the APs is also included. An approximation algorithm is introduced in this paper. The algorithm can deal with the formulated intractable APs planning task and produce performance-guaranteed solutions with reasonable complexity. Experiments indicate that the proposed algorithm works well for geographical areas with different densities of SMs. Our proposal yields cost-efficient APs deployment scheme and sheds insight into the reduction of the capital expenditure of the SGC system.

Geostatistical Assessment of Frankliniella schultzei (Thysanoptera: Thripidae) Spatial Distribution in Commercial Watermelon Crops.

Spatial distribution studies of insect pests make it possible to determine their colonization and dispersal patterns. Watermelon (Citrullus lanatus (Thunb.) Matsum. et Nakai) is among the most frequently consumed fruits in the world, and the common blossom thrips, Frankliniella schultzei (Trybom) (Thysanoptera: Thripidae), is one of the most important insect pests of this plant. The objective of this study was to determine the spatial distribution of F. schultzei in commercial watermelon crops using geostatistics. The studied F. schultzei populations presented an aggregated distribution. The colonization of thrips began at the borders of the crops, especially in the areas located in the opposite direction to that of the prevailing winds. The highest densities of thrips occurred in crops that had cucurbits in the surrounding areas. When monitoring for F. schultzei populations, greater attention should be given to sampling that part of the crop located in the opposite direction to that of the prevailing winds because this is where colonization begins. Even at low densities, the aggregation points of thrips in the crop should be located and controlled so that they do not cause damage. In sampling programs for F. schultzei, samples should be taken at distances greater than 9 m apart because this is the distance up to which densities of this species show spatial dependence. Planting watermelon crops close to other cucurbits should be avoided, as these alternate hosts may act as a source of infestation by this pest.