Redes Sociais Pessoais de Idosos, Satisfação com as Relações Interpessoais e Confiança

Objetivos: O presente estudo tem como objetivo geral caracterizar as redes sociais pessoais dos idosos com idade igual ou superior a 65 anos, analisando-as segundo o nível de satisfação com as relações interpessoais e a confiança nos outros. Metodologia: Este é um estudo descritivo e correlacional, privilegiando a análise bivariada. Os dados foram recolhidos através do Instrumento de Análise da Rede Social Pessoal, IARSP-Idosos (Guadalupe, 2009; Guadalupe & Vicente, 2012) e de uma escala de avaliação da Satisfação com as Relações Interpessoais, construída para o efeito, e de uma questão relacionada com a Confiança. Participantes: A amostra é constituída por 446 indivíduos, maioritariamente do sexo feminino (n=285; 63,9%), com idades compreendidas entre os 65 e os 98 anos; a maioria tem filhos (n = 389; 87,2%), e cerca de 80,0% (n = 357) vivem na sua casa, sendo a zona de residência essencialmente rural (61,2%; n = 273). A maioria tem escolaridade (65,9%; n = 294), sobretudo ao nível do quarto ano (n= 226; 50,7%). Resultados: Os resultados demonstram que os idosos do sexo feminino, com ≤ 75 anos, casado/a ou em união de fato, com filhos, que vivem acompanhados, com o 4ª ano de escolaridade e que não registam qualquer corte relacional, são os que mais confiam nos outros. Registam-se diferenças nas características funcionais da rede segundo esta variável, o que não acontece nas estruturais, com a exceção da proporção das relações com técnicos (p = 0,042) e nas relacionais-contextuais. A confiança nas pessoas com quem se relaciona correlaciona-se de forma positiva e estatisticamente significativa com a satisfação com os filhos, com os netos, com outros parentes, com os amigos e com os vizinhos (p<0,001). Conclusões: Numerosas variáveis sociodemográficas não aparentam estar relacionadas com a confiança nas pessoas com quem os idosos se relacionam, nas múltiplas dimensões consideradas. Em contrapartida, as variáveis que aparecem relacionadas com a confiança, são aquelas que, de forma mais ou menos direta, estão igualmente associadas ao domínio pessoal. É de salientar que no que respeita a esta variável se verificam diferenças nas características funcionais da rede o que não acontece nas estruturais e nas relacionais-contextuais. As relações familiares de filhos, netos e outros parentes são as que mais se associam à confiança e ao apoio social percebido pelos idosos, o qual é complementado por outras relações interpessoais, designadamente as que são estabelecidas com amigos e vizinhos. / Objetives: This study has the general objective to characterize the personal social networks of the elderly aged over 65 years, analyzing them according to the level of satisfaction with interpersonal relationships and trust in others. Methodology: This is a descriptive and correlational study, focusing on bivariate analysis. Data were collected through the Personal Social Networks Analysis Tool, IARSP-Elderly (Guadalupe, 2009; Vicente & Guadalupe, 2012) and a scale measuring satisfaction with interpersonal relations, purpose built, and a question related to the trust. Participants: The sample includes 446 individuals, mostly female (n = 285; 63,9%), aged between 65 and 98 years old; most have sons/daughters (n = 389; 87,2%), and about 80,0% (n = 357) are living in their home, mostly in rural areas (61,2%, n = 273). The majority have education (65,9%, n = 294), especially at the level of the fourth year (n = 226; 50,7%). Results: The results show that the elderly female, with <= 75, married, with children, living together, with the 4th grade, and did not record any relational cut, are the ones that rely in the others. We found differences in the functional characteristics of the network according to this variable, what does not happen on the structural variables, with the exception of the proportion of relations with workers in social services (p = 0,042), and on the relational-contextual. The confidence in the people he meets, correlates positively and statistically significant satisfaction with the children, with grandchildren, other relatives, friends and neighbors (p <0,001) Conclusions: Numerous sociodemographic variables do not appear to be related to trust in the interpersonal relationship, in the multiple dimensions considered. In contrast, the variables which appear related to trust are those which are associated with the personal domain. It is noteworthy that we have found differences in the functional characteristics of the network but not in the structural and the relational-contextual. Family relationships of children, grandchildren and other relatives are the most associated to the confidence and social support perceived by the elderly, which is complemented by other interpersonal relationships, including those with established friends and neighbors.

Pathways to emotional closeness in neonatal units - a cross-national qualitative study.

BACKGROUND: Research shows evidence for the importance of physical and emotional closeness for the infant, the parent and the infant-parent dyad. Less is known about how, when and why parents experience emotional closeness to their infants in a neonatal unit (NU), which was the aim of this study. METHODS: A qualitative study using a salutogenic approach to focus on positive health and wellbeing was undertaken in three NUs: one in Sweden, England and Finland. An 'emotional closeness' form was devised, which asked parents to describe moments/situations when, how and why they had felt emotionally close to their infant. Data for 23 parents of preterm infants were analyzed using thematic networks analysis. RESULTS: A global theme of 'pathways for emotional closeness' emerged from the data set. This concept related to how emotional, physical, cognitive and social influences led to feelings of emotional closeness between parents and their infants. The five underpinning organising themes relate to the: Embodied recognition through the power of physical closeness; Reassurance of, and contributing to, infant wellness; Understanding the present and the past; Feeling engaged in the day to day and Spending time and bonding as a family. CONCLUSION: These findings generate important insights into why, how and when parents feel emotionally close. This knowledge contributes to an increased awareness of how to support parents of premature infants to form positive and loving relationships with their infants. Health care staff should create a climate where parents' emotions and their emotional journey are individually supported.

Semantic Mining based on graph theory and ontologies. Case Study: Cell Signaling Pathways

In this paper we use concepts from graph theory and cellular biology represented as ontologies, to carry out semantic mining tasks on signaling pathway networks. Specifically, the paper describes the semantic enrichment of signaling pathway networks. A cell signaling network describes the basic cellular activities and their interactions. The main contribution of this paper is in the signaling pathway research area, it proposes a new technique to analyze and understand how changes in these networks may affect the transmission and flow of information, which produce diseases such as cancer and diabetes. Our approach is based on three concepts from graph theory (modularity, clustering and centrality) frequently used on social networks analysis. Our approach consists into two phases: the first uses the graph theory concepts to determine the cellular groups in the network, which we will call them communities; the second uses ontologies for the semantic enrichment of the cellular communities. The measures used from the graph theory allow us to determine the set of cells that are close (for example, in a disease), and the main cells in each community. We analyze our approach in two cases: TGF-β and the Alzheimer Disease.

Capital social e ações conjuntas: um estudo de caso no arranjo produtivo local de vinhos de altitude catarinense

The general goal of this study was to analyze the relations between the agents’ social capital and joint actions developed by the Cluster of wine produced at the high altitudes of Santa Catarina. This group is made up of 43 agents: one governing agent, 26 support agents and 16 winemakers. This descriptive and exploratory study uses data from qualitative and quantitative approaches. During the exploratory phase, a documental analysis was carried out, as well as semi-structured interviews. The data collection tool used to gather information concerning the social capital and joint actions was the semi-structured questionnaire, and this data gathering was conducted through field research using a structured interview with the selected agents from November 16 to November 26, 2015. The results of this study show a good social capital, which reflects on the joint actions done by the agents. Among the variables of social capital, trust shows a great level among the Cluster agents, followed by good levels concerning commitment and involvement, information share, rules and sanctions, horizontality and authority and improvement. As a result, it has created a nice level of involvement and effectiveness of joint actions, highlighting events organization, joint participation at fairs and events, marketing campaigns, development of products and processes, and human resources improvement. There is a small group of agents who show a strong social capital and a proper environment to expand this capital throughout the network. However, the evaluation concerning reciprocity and density represents only one third of the possibilities of this group, and it happens especially because of the geographical distance between the agents who are part of the Cluster. The main limitation of this study was the trouble trying to map the whole agent group before applying the questionnaires and identifying the responsible people in each of the support agents to inform everything correctly. It is suggested that these questionnaires be carried out with other Clusters as well as in the future in order to have a temporal assessment of this study.

Padrões de comunicação científica nas ciências sociais : a interdisciplinaridade entre economia, ciência política, sociologia e antropologia

Tese (doutorado)—Universidade de Brasília, Faculdade de Ciência da Informação, Programa de Pós-Graduação em Ciência da Informação, 2015.

The intellectual structure of research in hospitality management: A literature review using bibliometric methods of the journal International Journal of Hospitality Management

The purpose of this study is to analyze the existing literature on hospitality management from all the research papers published in The International Journal of Hospitality Management (IJHM) between 2008 and 2014. The authors apply bibliometric methods – in particular, author citation and co-citation analyses (ACA) – to identify the main research lines within this scientific field; in other words, its ‘intellectual structure’. Social network analysis (SNA) is also used to perform a visualization of this structure. The results of the analysis allow us to define the different research lines or fronts which shape the intellectual structure of research on hospitality management.

Design and evaluation of an image analysis platform for low-power, low-bandwidth camera networks

We describe the design and evaluation of a platform for networks of cameras in low-bandwidth, low-power sensor networks. In our work to date we have investigated two different DSP hardware/software platforms for undertaking the tasks of compression and object detection and tracking. We compare the relative merits of each of the hardware and software platforms in terms of both performance and energy consumption. Finally we discuss what we believe are the ongoing research questions for image processing in WSNs.

Sensitivity analysis of voltage imbalance in distribution networks with rooftop PVs

A comprehensive voltage imbalance sensitivity analysis and stochastic evaluation based on the rating and location of single-phase grid-connected rooftop photovoltaic cells (PVs) in a residential low voltage distribution network are presented. The voltage imbalance at different locations along a feeder is investigated. In addition, the sensitivity analysis is performed for voltage imbalance in one feeder when PVs are installed in other feeders of the network. A stochastic evaluation based on Monte Carlo method is carried out to investigate the risk index of the non-standard voltage imbalance in the network in the presence of PVs. The network voltage imbalance characteristic based on different criteria of PV rating and location and network conditions is generalized. Improvement methods are proposed for voltage imbalance reduction and their efficacy is verified by comparing their risk index using Monte Carlo simulations.

Analytical modeling and sensitivity analysis for travel time estimation on signalized urban networks

This paper presents a model for estimation of average travel time and its variability on signalized urban networks using cumulative plots. The plots are generated based on the availability of data: a) case-D, for detector data only; b) case-DS, for detector data and signal timings; and c) case-DSS, for detector data, signal timings and saturation flow rate. The performance of the model for different degrees of saturation and different detector detection intervals is consistent for case-DSS and case-DS whereas, for case-D the performance is inconsistent. The sensitivity analysis of the model for case-D indicates that it is sensitive to detection interval and signal timings within the interval. When detection interval is integral multiple of signal cycle then it has low accuracy and low reliability. Whereas, for detection interval around 1.5 times signal cycle both accuracy and reliability are high.

Performance analysis of IEEE 802.11 DCF based WNCS networks

Wireless network technologies, such as IEEE 802.11 based wireless local area networks (WLANs), have been adopted in wireless networked control systems (WNCS) for real-time applications. Distributed real-time control requires satisfaction of (soft) real-time performance from the underlying networks for delivery of real-time traffic. However, IEEE 802.11 networks are not designed for WNCS applications. They neither inherently provide quality-of-service (QoS) support, nor explicitly consider the characteristics of the real-time traffic on networked control systems (NCS), i.e., periodic round-trip traffic. Therefore, the adoption of 802.11 networks in real-time WNCSs causes challenging problems for network design and performance analysis. Theoretical methodologies are yet to be developed for computing the best achievable WNCS network performance under the constraints of real-time control requirements. Focusing on IEEE 802.11 distributed coordination function (DCF) based WNCSs, this paper analyses several important NCS network performance indices, such as throughput capacity, round trip time and packet loss ratio under the periodic round trip traffic pattern, a unique feature of typical NCSs. Considering periodic round trip traffic, an analytical model based on Markov chain theory is developed for deriving these performance indices under a critical real-time traffic condition, at which the real-time performance constraints are marginally satisfied. Case studies are also carried out to validate the theoretical development.

Multiscale analysis of protein functions and stochastic modelling of gene transcriptional regulatory networks

Genomic and proteomic analyses have attracted a great deal of interests in biological research in recent years. Many methods have been applied to discover useful information contained in the enormous databases of genomic sequences and amino acid sequences. The results of these investigations inspire further research in biological fields in return. These biological sequences, which may be considered as multiscale sequences, have some specific features which need further efforts to characterise using more refined methods. This project aims to study some of these biological challenges with multiscale analysis methods and stochastic modelling approach. The first part of the thesis aims to cluster some unknown proteins, and classify their families as well as their structural classes. A development in proteomic analysis is concerned with the determination of protein functions. The first step in this development is to classify proteins and predict their families. This motives us to study some unknown proteins from specific families, and to cluster them into families and structural classes. We select a large number of proteins from the same families or superfamilies, and link them to simulate some unknown large proteins from these families. We use multifractal analysis and the wavelet method to capture the characteristics of these linked proteins. The simulation results show that the method is valid for the classification of large proteins. The second part of the thesis aims to explore the relationship of proteins based on a layered comparison with their components. Many methods are based on homology of proteins because the resemblance at the protein sequence level normally indicates the similarity of functions and structures. However, some proteins may have similar functions with low sequential identity. We consider protein sequences at detail level to investigate the problem of comparison of proteins. The comparison is based on the empirical mode decomposition (EMD), and protein sequences are detected with the intrinsic mode functions. A measure of similarity is introduced with a new cross-correlation formula. The similarity results show that the EMD is useful for detection of functional relationships of proteins. The third part of the thesis aims to investigate the transcriptional regulatory network of yeast cell cycle via stochastic differential equations. As the investigation of genome-wide gene expressions has become a focus in genomic analysis, researchers have tried to understand the mechanisms of the yeast genome for many years. How cells control gene expressions still needs further investigation. We use a stochastic differential equation to model the expression profile of a target gene. We modify the model with a Gaussian membership function. For each target gene, a transcriptional rate is obtained, and the estimated transcriptional rate is also calculated with the information from five possible transcriptional regulators. Some regulators of these target genes are verified with the related references. With these results, we construct a transcriptional regulatory network for the genes from the yeast Saccharomyces cerevisiae. The construction of transcriptional regulatory network is useful for detecting more mechanisms of the yeast cell cycle.

Aerial image analysis using spiking neural networks with application to power line corridor monitoring

Trees, shrubs and other vegetation are of continued importance to the environment and our daily life. They provide shade around our roads and houses, offer a habitat for birds and wildlife, and absorb air pollutants. However, vegetation touching power lines is a risk to public safety and the environment, and one of the main causes of power supply problems. Vegetation management, which includes tree trimming and vegetation control, is a significant cost component of the maintenance of electrical infrastructure. For example, Ergon Energy, the Australia’s largest geographic footprint energy distributor, currently spends over $80 million a year inspecting and managing vegetation that encroach on power line assets. Currently, most vegetation management programs for distribution systems are calendar-based ground patrol. However, calendar-based inspection by linesman is labour-intensive, time consuming and expensive. It also results in some zones being trimmed more frequently than needed and others not cut often enough. Moreover, it’s seldom practicable to measure all the plants around power line corridors by field methods. Remote sensing data captured from airborne sensors has great potential in assisting vegetation management in power line corridors. This thesis presented a comprehensive study on using spiking neural networks in a specific image analysis application: power line corridor monitoring. Theoretically, the thesis focuses on a biologically inspired spiking cortical model: pulse coupled neural network (PCNN). The original PCNN model was simplified in order to better analyze the pulse dynamics and control the performance. Some new and effective algorithms were developed based on the proposed spiking cortical model for object detection, image segmentation and invariant feature extraction. The developed algorithms were evaluated in a number of experiments using real image data collected from our flight trails. The experimental results demonstrated the effectiveness and advantages of spiking neural networks in image processing tasks. Operationally, the knowledge gained from this research project offers a good reference to our industry partner (i.e. Ergon Energy) and other energy utilities who wants to improve their vegetation management activities. The novel approaches described in this thesis showed the potential of using the cutting edge sensor technologies and intelligent computing techniques in improve power line corridor monitoring. The lessons learnt from this project are also expected to increase the confidence of energy companies to move from traditional vegetation management strategy to a more automated, accurate and cost-effective solution using aerial remote sensing techniques.

Analysis of multiple shared channel cooperative routing in OFDM based wireless networks

Diversity techniques have long been used to combat the channel fading in wireless communications systems. Recently cooperative communications has attracted lot of attention due to many benefits it offers. Thus cooperative routing protocols with diversity transmission can be developed to exploit the random nature of the wireless channels to improve the network efficiency by selecting multiple cooperative nodes to forward data. In this paper we analyze and evaluate the performance of a novel routing protocol with multiple cooperative nodes which share multiple channels. Multiple shared channels cooperative (MSCC) routing protocol achieves diversity advantage by using cooperative transmission. It unites clustering hierarchy with a bandwidth reuse scheme to mitigate the co-channel interference. Theoretical analysis of average packet reception rate and network throughput of the MSCC protocol are presented and compared with simulated results.

Fuzzy methods for analysis of microarrays and networks

Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) clustering of microarrays; (2) identification of disease-associated genes in microarrays; and (3) identification of protein complexes in PPI networks. The first part of the thesis aims to detect, by the fuzzy C-means (FCM) method, clustering structures in DNA microarrays corrupted by noise. Because of the presence of noise, some clustering structures found in random data may not have any biological significance. In this part, we propose to combine the FCM with the empirical mode decomposition (EMD) for clustering microarray data. The purpose of EMD is to reduce, preferably to remove, the effect of noise, resulting in what is known as denoised data. We call this method the fuzzy C-means method with empirical mode decomposition (FCM-EMD). We applied this method on yeast and serum microarrays, and the silhouette values are used for assessment of the quality of clustering. The results indicate that the clustering structures of denoised data are more reasonable, implying that genes have tighter association with their clusters. Furthermore we found that the estimation of the fuzzy parameter m, which is a difficult step, can be avoided to some extent by analysing denoised microarray data. The second part aims to identify disease-associated genes from DNA microarray data which are generated under different conditions, e.g., patients and normal people. We developed a type-2 fuzzy membership (FM) function for identification of diseaseassociated genes. This approach is applied to diabetes and lung cancer data, and a comparison with the original FM test was carried out. Among the ten best-ranked genes of diabetes identified by the type-2 FM test, seven genes have been confirmed as diabetes-associated genes according to gene description information in Gene Bank and the published literature. An additional gene is further identified. Among the ten best-ranked genes identified in lung cancer data, seven are confirmed that they are associated with lung cancer or its treatment. The type-2 FM-d values are significantly different, which makes the identifications more convincing than the original FM test. The third part of the thesis aims to identify protein complexes in large interaction networks. Identification of protein complexes is crucial to understand the principles of cellular organisation and to predict protein functions. In this part, we proposed a novel method which combines the fuzzy clustering method and interaction probability to identify the overlapping and non-overlapping community structures in PPI networks, then to detect protein complexes in these sub-networks. Our method is based on both the fuzzy relation model and the graph model. We applied the method on several PPI networks and compared with a popular protein complex identification method, the clique percolation method. For the same data, we detected more protein complexes. We also applied our method on two social networks. The results showed our method works well for detecting sub-networks and give a reasonable understanding of these communities.