Factors Influencing Behavior to Reducing Household Food Waste in Indonesia

The introduction of the determining factor is presumed to be powerful medium to promote a powerful intrusion into household waste management in Indonesia. This study expands the variables theory of planned behavior, the theory of interpersonal characteristics, and a complete model of environmental behavior by using intentions, attitudes, subjective norms, perceived behavioral control, habits, emotions. The sample in this study found 132 people, data processed using SEM Amos version 24. Statistical results and discussion showed that significant factors for behavior to reduce food waste were intentions, habits, attitudes, and perceived behavioral control. And that habits play an essential role in this research, so it is necessary to focus on the importance of the practice to get rid of addictions and be worth emphasizing Keywords: food waste, theory planned behavior, habit

Factors Influencing Behavior to Reducing Household Food Waste in Indonesia

The introduction of the determining factor is presumed to be powerful medium to promote a powerful intrusion into household waste management in Indonesia. This study expands the variables theory of planned behavior, the theory of interpersonal characteristics, and a complete model of environmental behavior by using intentions, attitudes, subjective norms, perceived behavioral control, habits, emotions. The sample in this study found 132 people, data processed using SEM Amos version 24. Statistical results and discussion showed that significant factors for behavior to reduce food waste were intentions, habits, attitudes, and perceived behavioral control. And that habits play an essential role in this research, so it is necessary to focus on the importance of the practice to get rid of addictions and be worth emphasizing Keywords: food waste, theory planned behavior, habit

A stochastic evolutionary model exhibiting power-law behaviour with an exponential cutoff

Recently several authors have proposed stochastic evolutionary models for the growth of complex networks that give rise to power-law distributions. These models are based on the notion of preferential attachment leading to the “rich get richer” phenomenon. Despite the generality of the proposed stochastic models, there are still some unexplained phenomena, which may arise due to the limited size of networks such as protein and e-mail networks. Such networks may in fact exhibit an exponential cutoff in the power-law scaling, although this cutoff may only be observable in the tail of the distribution for extremely large networks. We propose a modification of the basic stochastic evolutionary model, so that after a node is chosen preferentially, say according to the number of its inlinks, there is a small probability that this node will be discarded. We show that as a result of this modification, by viewing the stochastic process in terms of an urn transfer model, we obtain a power-law distribution with an exponential cutoff. Unlike many other models, the current model can capture instances where the exponent of the distribution is less than or equal to two. As a proof of concept, we demonstrate the consistency of our model by analysing a yeast protein interaction network, the distribution of which is known to follow a power law with an exponential cutoff

The Web of Human Sexual Contacts

Many ``real-world'' networks are clearly defined while most ``social'' networks are to some extent subjective. Indeed, the accuracy of empirically-determined social networks is a question of some concern because individuals may have distinct perceptions of what constitutes a social link. One unambiguous type of connection is sexual contact. Here we analyze data on the sexual behavior of a random sample of individuals, and find that the cumulative distributions of the number of sexual partners during the twelve months prior to the survey decays as a power law with similar exponents $\alpha \approx 2.4$ for females and males. The scale-free nature of the web of human sexual contacts suggests that strategic interventions aimed at preventing the spread of sexually-transmitted diseases may be the most efficient approach.Comment: 7 pages with 2 eps figures. Latex file. For more details or for downloading the PDF file of the published article see http://polymer.bu.edu/~amaral/WebofContacts.html . For more results on teh structure of complex networks see http://polymer.bu.edu/~amaral/Networks.htm

Effects of neonatal amygdala or hippocampus lesions on resting brain metabolism in the macaque monkey: A microPET imaging study

Longitudinal analysis of animals with neonatal brain lesions enables the evaluation of behavioral changes during multiple stages of development. Interpretation of such changes, however, carries the caveat that permanent neural injury also yields morphological and neurochemical reorganization elsewhere in the brain that may lead either to functional compensation or to exacerbation of behavioral alterations. We have measured the long-term effects of selective neonatal brain damage on resting cerebral glucose metabolism in nonhuman primates. Sixteen rhesus monkeys (Macaca mulatta) received neurotoxic lesions of either the amygdala (n = 8) or hippocampus (n = 8) when they were two weeks old. Four years later, these animals, along with age- and experience-matched sham-operated control animals (n = 8), were studied with high-resolution positron emission tomography (microPET) and 2-deoxy-2[¹⁸F]fluoro-d-glucose ([¹⁸F]FDG) to detect areas of altered metabolism. The groups were compared using an anatomically-based region of interest analysis. Relative to controls, amygdala-lesioned animals displayed hypometabolism in three frontal lobe regions, as well as in the neostriatum and hippocampus. Hypermetabolism was also evident in the cerebellum of amygdala-lesioned animals. Hippocampal-lesioned animals only showed hypometabolism in the retrosplenial cortex. These results indicate that neonatal amygdala and hippocampus lesions induce very different patterns of long-lasting metabolic changes in distant brain regions. These observations raise the possibility that behavioral alterations in animals with neonatal lesions may be due to the intended damage, to consequent brain reorganization or to a combination of both factors

Do Pareto-Zipf and Gibrat laws hold true? An analysis with European Firms

By employing exhaustive lists of large firms in European countries, we show that the upper-tail of the distribution of firm size can be fitted with a power-law (Pareto-Zipf law), and that in this region the growth rate of each firm is independent of the firm's size (Gibrat's law of proportionate effect). We also find that detailed balance holds in the large-size region for periods we investigated; the empirical probability for a firm to change its size from a value to another is statistically the same as that for its reverse process. We prove several relationships among Pareto-Zipf's law, Gibrat's law and the condition of detailed balance. As a consequence, we show that the distribution of growth rate possesses a non-trivial relation between the positive side of the distribution and the negative side, through the value of Pareto index, as is confirmed empirically

Diagnóstico situacional em saúde: uma ferramenta para o planejamento das ações na estratégia saúde da família do Município de Foz do Iguaçu-PR

A UNILA, a Prefeitura Municipal de Foz do Iguaçu, a Alfândega da Receita Federal em Foz do Iguaçu, a Universidade Estadual do Oeste do Paraná (Unioeste) e o Instituto Federal do Paraná (IFPR) promoverão conjuntamente, este ano, a Semana Integrada do Servidor Público. O evento pretende ser um espaço de análise e discussão sobre o tema “Valorização e integração: contribuições e desafios do servidor público na atualidade”. As atividades serão realizadas entre os dias 22 e 27 de outubro. O lançamento da Semana foi realizado nesta segunda-feira (27), no auditório da UnioesteA Estratégia Saúde da Família (ESF) é considerada um modelo reorganizador do Sistema Único de Saúde (SUS). As equipes de saúde trabalham com o processo de territorialização e deste modo, o diagnóstico situacional é uma ferramenta indispensável para reconhecimento das condições de saúde da população e posterior planejamento das ações. Sendo assim, o objetivo do presente estudo foi identificar o perfil da população, as demandas e as necessidades de atendimento da Equipe Saúde da Família 073 vinculada à Unidade de Saúde São João localizada no Distrito Nordeste do município de Foz do Iguaçu-PR, através de um estudo observacional, documental, do tipo descritivo exploratório com abordagem quantitativa. Constatou-se que a equipe possui um total de 3.578 usuários cadastrados no sistema de informação Saúde Foz e que grande parte destes são acometidos por doenças crônicas como hipertensão e diabetes, também se destaca o grande número de gestantes cadastradas e acompanhadas pela equipe, fazendo-se necessário o acompanhamento desta população de maneira a levar informações que contribuam para a redução de danos e promoção de saúd

A model for collaboration networks giving rise to a power law distribution with exponential cutoff

Recently several authors have proposed stochastic evolutionary models for the growth of complex networks that give rise to power-law distributions. These models are based on the notion of preferential attachment leading to the ``rich get richer'' phenomenon. Despite the generality of the proposed stochastic models, there are still some unexplained phenomena, which may arise due to the limited size of networks such as protein, e-mail, actor and collaboration networks. Such networks may in fact exhibit an exponential cutoff in the power-law scaling, although this cutoff may only be observable in the tail of the distribution for extremely large networks. We propose a modification of the basic stochastic evolutionary model, so that after a node is chosen preferentially, say according to the number of its inlinks, there is a small probability that this node will become inactive. We show that as a result of this modification, by viewing the stochastic process in terms of an urn transfer model, we obtain a power-law distribution with an exponential cutoff. Unlike many other models, the current model can capture instances where the exponent of the distribution is less than or equal to two. As a proof of concept, we demonstrate the consistency of our model empirically by analysing the Mathematical Research collaboration network, the distribution of which is known to follow a power law with an exponential cutoff

Efficiency of Scale-Free Networks: Error and Attack Tolerance

The concept of network efficiency, recently proposed to characterize the properties of small-world networks, is here used to study the effects of errors and attacks on scale-free networks. Two different kinds of scale-free networks, i.e. networks with power law P(k), are considered: 1) scale-free networks with no local clustering produced by the Barabasi-Albert model and 2) scale-free networks with high clustering properties as in the model by Klemm and Eguiluz, and their properties are compared to the properties of random graphs (exponential graphs). By using as mathematical measures the global and the local efficiency we investigate the effects of errors and attacks both on the global and the local properties of the network. We show that the global efficiency is a better measure than the characteristic path length to describe the response of complex networks to external factors. We find that, at variance with random graphs, scale-free networks display, both on a global and on a local scale, a high degree of error tolerance and an extreme vulnerability to attacks. In fact, the global and the local efficiency are unaffected by the failure of some randomly chosen nodes, though they are extremely sensititive to the removal of the few nodes which play a crucial role in maintaining the network's connectivity.Comment: 23 pages, 10 figure

Growing Scale-Free Networks with Small World Behavior

In the context of growing networks, we introduce a simple dynamical model that unifies the generic features of real networks: scale-free distribution of degree and the small world effect. While the average shortest path length increases logartihmically as in random networks, the clustering coefficient assumes a large value independent of system size. We derive expressions for the clustering coefficient in two limiting cases: random (C ~ (ln N)^2 / N) and highly clustered (C = 5/6) scale-free networks.Comment: 4 pages, 4 figure