Interference cancellation in two-path successive relay system with network coding

This paper proposes a novel interference cancellation algorithm for the two-path successive relay system using network coding. The two-path successive relay scheme was proposed recently to achieve full date rate transmission with half-duplex relays. Due to the simultaneous data transmission at the relay and source nodes, the two-path relay suffers from the so-called inter-relay interference (IRI) which may significantly degrade the system performance. In this paper, we propose to use the network coding to remove the IRI such that the interference is first encoded with the network coding at the relay nodes and later removed at the destination. The network coding has low complexity and can well suppress the IRI. Numerical simulations show that the proposed algorithm has better performance than existing approaches.

Adaptive noise cancellation with fast tunable RBF network

This paper describes a novel adaptive noise cancellation system with fast tunable radial basis function (RBF). The weight coefficients of the RBF network are adapted by the multi-innovation recursive least square (MRLS) algorithm. If the RBF network performs poorly despite of the weight adaptation, an insignificant node with little contribution to the overall performance is replaced with a new node without changing the model size. Otherwise, the RBF network structure remains unchanged and only the weight vector is adapted. The simulation results show that the proposed approach can well cancel the noise in both stationary and nonstationary ANC systems.

Bridging the gap between research and practice in organizational network analysis: a conversation between Rob Cross and Martin Kilduff

The article features a conversation between Rob Cross and Martin Kilduff about organizational network analysis in research and practice. It demonstrates the value of using social network perspectives in HRM. Drawing on the discussion about managing personal networks; managing the networks of others; the impact of social networking sites on perceptions of relationships; and ethical issues in organizational network analysis, we propose specific suggestions to bring social network perspectives closer to HRM researchers and practitioners and rebalance our attention to people and to their relationships.

Activities related with electricity consumption in the Spanish residential sector: variations between days of the week, Autonomous Communities and size of towns

Nowadays the electricity consumption in the residential sector attracts policy and research efforts, in order to propose saving strategies and to attain a better balance between production and consumption, by integrating renewable energy production and proposing suitable demand side management methods. To achieve these objectives it is essential to have real information about household electricity demand profiles in dwellings, highly correlated, among other aspects, with the active occupancy of the homes and to the personal activities carried out in homes by their occupants. Due to the limited information related to these aspects, in this paper, behavioral factors of the Spanish household residents, related to the electricity consumption, have been determined and analyzed, based on data from the Spanish Time Use Surveys, differentiating among the Autonomous Communities and the size of municipalities, or the type of days, weekdays or weekends. Activities involving a larger number of houses are those related to Personal Care, Food Preparation and Washing Dishes. The activity of greater realization at homes is Watching TV, which together with Using PC, results in a high energy demand in an aggregate level. Results obtained enable identify prospective targets for load control and for efficiency energy reduction recommendations to residential consumers.

Competitive fitness in coronaviruses is not correlated with size or number of double-membrane vesicles under reduced-temperature growth conditions

Positive-stranded viruses synthesize their RNA in membrane-bound organelles, but it is not clear how this benefits the virus or the host. For coronaviruses, these organelles take the form of double-membrane vesicles (DMVs) interconnected by a convoluted membrane network. We used electron microscopy to identify murine coronaviruses with mutations in nsp3 and nsp14 that replicated normally while producing only half the normal amount of DMVs. Viruses with mutations in nsp5 and nsp16 produced small DMVs but also replicated normally. Quantitative RT-PCR confirmed that the most strongly affected of these, the nsp3 mutant, produced more viral RNA than wild-type virus. Competitive growth assays were carried out in both continuous and primary cells to better understand the contribution of DMVs to viral fitness. Surprisingly, several viruses that produced fewer or smaller DMVs showed a higher relative fitness compared to wild-type virus, suggesting that larger and more numerous DMVs do not necessarily confer a competitive advantage in primary or continuous cell culture. For the first time, this directly demonstrates that replication and organelle formation may be, at least in part, studied separately during positive-stranded RNA virus infection.

A fast adaptive tunable RBF network for nonstationary systems

This paper describes a novel on-line learning approach for radial basis function (RBF) neural network. Based on an RBF network with individually tunable nodes and a fixed small model size, the weight vector is adjusted using the multi-innovation recursive least square algorithm on-line. When the residual error of the RBF network becomes large despite of the weight adaptation, an insignificant node with little contribution to the overall system is replaced by a new node. Structural parameters of the new node are optimized by proposed fast algorithms in order to significantly improve the modeling performance. The proposed scheme describes a novel, flexible, and fast way for on-line system identification problems. Simulation results show that the proposed approach can significantly outperform existing ones for nonstationary systems in particular.

Percolation in a network with long-range connections: Implications for cytoskeletal structure and function

Cell shape, signaling, and integrity depend on cytoskeletal organization. In this study we describe the cytoskeleton as a simple network of filamentary proteins (links) anchored by complex protein structures (nodes). The structure of this network is regulated by a distance-dependent probability of link formation as P = p/d(s), where p regulates the network density and s controls how fast the probability for link formation decays with node distance (d). It was previously shown that the regulation of the link lengths is crucial for the mechanical behavior of the cells. Here we examined the ability of the two-dimensional network to percolate (i.e. to have end-to-end connectivity), and found that the percolation threshold depends strongly on s. The system undergoes a transition around s = 2. The percolation threshold of networks with s < 2 decreases with increasing system size L, while the percolation threshold for networks with s > 2 converges to a finite value. We speculate that s < 2 may represent a condition in which cells can accommodate deformation while still preserving their mechanical integrity. Additionally, we measured the length distribution of F-actin filaments from publicly available images of a variety of cell types. In agreement with model predictions, cells originating from more deformable tissues show longer F-actin cytoskeletal filaments. (C) 2008 Elsevier B.V. All rights reserved.

Vård i livets slut av personer med demens. Personal och anhörigas upplevelse av given vård : En metasyntes

Palliativt förhållningssätt kännetecknas av helhetssyn av människan och uppnås genom stöttning av individen att leva med värdighet och största möjliga välbefinnande till livets slut oavsett diagnos eller ålder. Demens är en sjukdom som är svårt handikappande för den som drabbas och för de anhöriga är sjukdomen förödande. Den palliativa vården av personer med demens är inte optimerad. Studier visar att det dels beror på demenssjukdomen som är svår att vårda och dels för att stöd till de personer som vårdar sina anhöriga och det sociala kommunala nätverket har brister. Syfte: Att analysera upplevelsen av given vård i livets slutskede hos personer med demensdiagnos ur personalens och anhörigas perspektiv. Metod: Metasyntes utförd med Howell Major och Savin-Badins analysmodell, Qualitative Research Synthesis. Resultat: Kunskap och personcentrering var de två begrepp som blev produkten av syntesen. Begreppen fungerar som motsatser, om det finns kunskap och personcentrering så finns en bra upplevelse av given vård hos personal och anhöriga och om det brister i kunskap och personcentrering blir upplevelsen sämre. Diskussion: Kunskap om demens bland personal har i syntesen visats vara en indikator för god vård vid livets slut. Utbildning i demenssjukdom bör ske kontinuerligt och på olika nivåer beroende på vilken personalkategori som utbildas. Konklusion: Palliativ vård och demens måste få utrymme i utbildningarna av all personal, från undersköterska till specialistläkare.

Student Thesis Level: Master’s Thesis in Business Administration Corporate Social Responsibility (CSR) networking : A case study on why members join CSR network and why are they sharing their knowledge

Purpose – This research focuses on finding the reasons, why members from different sectors join a cross-sector/multi-stakeholder CSR network and what motivates them to share (or not to share) their knowledge of CSR and their best practices. Design/methodology/approach – Semi-structured interviews were conducted with members of the largest cross-sector CSR network in Sweden. The sample base of 15 people was chosen to be able to represent a wider variety of members from each participating sectors. As well as the CEO of the intermediary organization was interviewed. The interviews were conducted via email and telephone. Findings – The findings include several reasons linked to the business case of CSR such as stakeholder pressure, competitive advantage, legitimacy and reputation as well as new reasons like the importance of CSR, and the access of further knowledge in the field. Further reasons are in line with members wanting to join a network, such as access to contact or having personal contacts. As to why members are sharing their CSR knowledge, the findings indicate to inspire others, to show CSR commitment, to be visible, it leads to business opportunity and the access of others knowledge, and because it was requested. Reasons for not sharing their knowledge would be the lack of opportunity, lack of time and the lack of experience to do so. Originality/value – The research contributes to existing studies, which focused on Corporate Social Responsibility and cross-sector networking as well as to inter-organizational knowledge sharing in the field of CSR.

How does data quality in a network affect heuristic solutions?

To have good data quality with high complexity is often seen to be important. Intuition says that the higher accuracy and complexity the data have the better the analytic solutions becomes if it is possible to handle the increasing computing time. However, for most of the practical computational problems, high complexity data means that computational times become too long or that heuristics used to solve the problem have difficulties to reach good solutions. This is even further stressed when the size of the combinatorial problem increases. Consequently, we often need a simplified data to deal with complex combinatorial problems. In this study we stress the question of how the complexity and accuracy in a network affect the quality of the heuristic solutions for different sizes of the combinatorial problem. We evaluate this question by applying the commonly used p-median model, which is used to find optimal locations in a network of p supply points that serve n demand points. To evaluate this, we vary both the accuracy (the number of nodes) of the network and the size of the combinatorial problem (p). The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 supply points we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000 (which is aggregated from the 1.5 million nodes). To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when the accuracy in the road network increase and the combinatorial problem (low p) is simple. When the combinatorial problem is complex (large p) the improvements of increasing the accuracy in the road network are much larger. The results also show that choice of the best accuracy of the network depends on the complexity of the combinatorial (varying p) problem.

A sociometric analysis for the creation of an integrated multicultural work team

This research aimed to apply the sociometric theory and its methodology to create an integrated multicultural work team. The study focused on the application of the sociometry theory, developed by Jacob L. Moreno in 1934, to analyze the small multicultural group. In the beginning, a review of the literature was done to have a better understanding of Sociometric Theory as well as the modern tools and software developed to analyze and map the social networks. After this part of the study, the qualitative study was done, in which 26 students from 12 countries, which studied together in a Corporate International Master (2014-2015), developed by Georgetown University’s McDonough School of Business, Corporate Master of Business Administration from ESADE Business School and FGV/EBAPE, were surveyed and asked them to choose people, among the selected group, who they attracted, rejected or they were neutral towards, in 4 different scenarios: work team, leadership, trip (leisure time) and personal problem. Additionally, there were, two questions asked about how they felt when they answered the survey and which question(s) was/were difficult to answer and why. The focus on these two questions was to understand the emotional state of the respondents when they answered the survey and related this emotional state to the Sociometric Theory. The sociometric matrix, using Microsoft Excel, was created using the answers and the total of the positive, negative and neutral choices were analyzed for each scenario as well as the mutualities and incongruences of the choices. Furthermore, the software Kumu was used to analyze the connections between the people in the selected group using three metrics: size, degree centrality and indegree. Also Kumu was used to draw the social maps or sociometric maps. Using the relationship level analyses of the sociometric matrix and maps, it was possible to create an integrated multicultural work team. In the end, the results obtained suggest that it is possible to apply the sociometric methodology to study the relationships inside companies, project teams and work teams and identify the best work team based on the interrelationship between the people as well as the lack of communication among the team members, project team or inside the company as a whole.

Wear Particle Classifier System Based on an Artificial Neural Network

This paper describes a method of identifying morphological attributes that classify wear particles in relation to the wear process from which they originate and permit the automatic identification without human expertise. The method is based on the use of Multi Layer Perceptron (MLP) for analysis of specific types of microscopic wear particles. The classification of the wear particles was performed according to their morphological attributes of size and aspect ratio, among others. (C) 2010 Journal of Mechanical Engineering. All rights reserved.

The size of excavators within a polymorphic termite species governs tunnel topology

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fight versus flight: the interaction of temperature and body size determines antipredator behaviour in tegu lizards

Ectotherm antipredator behaviour might be strongly affected both by body temperature and size: when environmental temperatures do not favour maximal locomotor performance, large individuals may confront predators, whereas small animals may flee, simply because they have no other option. However, integration of body size and temperature effects is rarely approached in the study of antipredator behaviour in vertebrate ectotherms. In the present study we investigated whether temperature affects antipredator responses of tegu lizards, Tupinambis merianae, with distinct body sizes, testing the hypothesis that small tegus (juveniles) run away from predators regardless of the environmental temperature, because defensive aggression may not be an effective predator deterrent, whereas adults, which are larger, use aggressive defence at low temperatures, when running performance might be suboptimal. We recorded responses of juvenile (small) and adult (large) tegu lizards to a simulated predatory attack at five environmental temperatures in the laboratory. Most differences between the two size classes were observed at low temperatures: large tegus were more aggressive overall than were small tegus at all temperatures tested, but at lower temperatures, the small lizards often used escape responses whereas the large ones either adopted a defensive posture or remained inactive. These results provide strong evidence that body size and temperature affect the antipredator responses of vertebrate ectotherms. We discuss the complex and intricate network of evolutionary and ecological parameters that are likely to be involved in the evolution of such interactions. (C) 2009 The Association for the Study of Animal Behaviour. Published by Elsevier Ltd. All rights reserved.

Short term hydroelectric scheduling combining network flow and interior point approaches

In this paper, short term hydroelectric scheduling is formulated as a network flow optimization model and solved by interior point methods. The primal-dual and predictor-corrector versions of such interior point methods are developed and the resulting matrix structure is explored. This structure leads to very fast iterations since it avoids computation and factorization of impedance matrices. For each time interval, the linear algebra reduces to the solution of two linear systems, either to the number of buses or to the number of independent loops. Either matrix is invariant and can be factored off-line. As a consequence of such matrix manipulations, a linear system which changes at each iteration has to be solved, although its size is reduced to the number of generating units and is not a function of time intervals. These methods were applied to IEEE and Brazilian power systems, and numerical results were obtained using a MATLAB implementation. Both interior point methods proved to be robust and achieved fast convergence for all instances tested. (C) 2004 Elsevier Ltd. All rights reserved.