Leontief Model Analysis with Fuzzy Parameters by Basic Matrixes Method

The basic matrixes method is suggested for the Leontief model analysis (LM) with some of its components indistinctly given. LM can be construed as a forecast task of product’s expenses-output on the basis of the known statistic information at indistinctly given several elements’ meanings of technological matrix, restriction vector and variables’ limits. Elements of technological matrix, right parts of restriction vector LM can occur as functions of some arguments. In this case the task’s dynamic analog occurs. LM essential complication lies in inclusion of variables restriction and criterion function in it.

?Qu? impacto cognitivo, medido por el model analysis, tiene el uso de un libro de texto refutacional como recurso did?ctico en la ense?anza de la primera ley de newton en los estudiantes de d?cimo grado de un colegio de Cali?

Se incorpor? un texto expositivo refutacional (TER), en el programa de un curso de f?sica durante los primeros dos periodos acad?micos a finales del a?o 2012, en cuatro grupos de d?cimo grado de un colegio del sur de Cali. Aplicando la propuesta de Uribe (2010), para ense?ar el modelo newtoniano del movimiento de la part?cula, haciendo ?nfasis en la comprensi?n de los conceptos, trascendiendo de la ense?anza de la mera resoluci?n de problemas t?picos con el andamiaje matem?tico que implican, propuesta materializada en un texto expositivo refutacional (TER). Se identific? el modelo que predomina en la mente de los estudiantes a trav?s del FCI analizando la informaci?n con la metodolog?a de an?lisis del estado de conocimiento de un grupo-clase respecto a un concepto cient?fico denominada Model Analysis (Bao & Redish, 2006). Los resultados de la intervenci?n se compararon con un quinto grupo de la misma instituci?n que sigui? un programa de ense?anza tradicional.

An Integrated Framework To Improve The Concept Of Resource Specialisation.

Resource specialisation, although a fundamental component of ecological theory, is employed in disparate ways. Most definitions derive from simple counts of resource species. We build on recent advances in ecophylogenetics and null model analysis to propose a concept of specialisation that comprises affinities among resources as well as their co-occurrence with consumers. In the distance-based specialisation index (DSI), specialisation is measured as relatedness (phylogenetic or otherwise) of resources, scaled by the null expectation of random use of locally available resources. Thus, specialists use significantly clustered sets of resources, whereas generalists use over-dispersed resources. Intermediate species are classed as indiscriminate consumers. The effectiveness of this approach was assessed with differentially restricted null models, applied to a data set of 168 herbivorous insect species and their hosts. Incorporation of plant relatedness and relative abundance greatly improved specialisation measures compared to taxon counts or simpler null models, which overestimate the fraction of specialists, a problem compounded by insufficient sampling effort. This framework disambiguates the concept of specialisation with an explicit measure applicable to any mode of affinity among resource classes, and is also linked to ecological and evolutionary processes. This will enable a more rigorous deployment of ecological specialisation in empirical and theoretical studies.

Hyper abundant mesopredators and bird extinction in an Atlantic forest island

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

Spatial and temporal distribution of tadpole assemblages (Amphibia, Anura) in a seasonal dry tropical forest of southeastern Brazil

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

Ecologia de comunidades e comportamento reprodutivo de anfíbios anuros em savana amazônica

The Amazon savannas occur as isolated patches throughout extensive areas of forest in the states of Amapá, Amazonas, Pará, and Roraima. There is a considerable variation in the composition of anuran assemblages in the localities and phytophysiognomies of Amazon savannas and given the absence of studies on reproductive behavior, a systematic and geographically wide sampling has been carried out in the Amapá savanna, located in the Eastern Amazon. The study was conducted in a savanna area in the state of Amapá to examine the composition, ecology, and reproductive behavior of anuran amphibians. We carried out 24 field trips in each phytophysiognomy (gramineous-woody savana, gramineous-herbaceous-woody savana, park savana, and arboreal savanna); for analysis of reproductive behavior observations were made during the period January to December 2013, lasting four consecutive days. Samples were collected by active and acoustic search along 20 plots of 100x50 meters. Twenty-one anuran species were recorded, of which four are new records for the state of Amapá: Dendropsophus walfordi, Scinax fuscomarginatus, Pseudopaludicola boliviana e Elachistocleis helianneae. The KruskalWallis ANOVA revealed significant differences between richness and species diversity in the phytophysiognomies (p < 0.05). The Bray-Curtis similarity coefficient divided the phytophysiognomies into three groups: arboreal savana, gramineous-woody savanna and gramineous-herbaceous-woody savanna, and park savanna. According to the non-metric multidimensional scaling, the structure of the anuran community resulted in a separation into three phytophysiognomies, with significant differences in the structure of communities (ANOSIM, R = 0.823; p < 0.001). In the study of community ecology, the results obtained for spatial, temporal, and trophic niche breadth suggest that the assemblage of anurans of the Amapá savanna is not composed of predominantly generalist species. Also, the presence of other specialist anurans may explain the processes of speciation associated with the isolation of habitats, resulting in heterogeneity and spatial discontinuity in the phytophysiognomies with open formations. The null model analysis revealed that the community is structured based on temporal and trophic niche, indicating a significant influence of contemporary ecological factors on the assemblage. The absence of structure based on spatial niche might be explained by the spatial segregation in the distribution and occupation of anurans in the different phytophysiognomies of the Amapá savanna. Regarding the reproductive behavior of anurans, 11 species were classified as having a long breeding season, intrinsically associated with the rainy season and the reproductive mode of most species that lay egg clutches in lentic water bodies. Six reproductive modes were recorded and parental care was observed in Leptodactylus macrosternum and L. podicipinus, whose reproductive mode is characterized by foam nests. Regarding behavioral reproductive strategies, calling males were observed in all species of anurans, satellite males were recorded only for D. walfordi, Hypsiboas multifasciatus, S. nebulosus and S. fuscomarginatus; active search for females was observed for Phyllomedusa hypochondrialis and L. fuscus, and male displacement was recorded only for Rhinella major and R. margaritifera. Of the reproductive behaviors observed, throat and vocal sac display is associated with courtship and territorial behavior exhibited by males. In addition to courtship behavior, visual signals associated with courtship strategies were recorded for the anurans of the Amapá savanna.

A landscape-scale test of the predictive ability of a spatially explicit model for population viability analysis

1. Although population viability analysis (PVA) is widely employed, forecasts from PVA models are rarely tested. This study in a fragmented forest in southern Australia contrasted field data on patch occupancy and abundance for the arboreal marsupial greater glider Petauroides volans with predictions from a generic spatially explicit PVA model. This work represents one of the first landscape-scale tests of its type. 2. Initially we contrasted field data from a set of eucalypt forest patches totalling 437 ha with a naive null model in which forecasts of patch occupancy were made, assuming no fragmentation effects and based simply on remnant area and measured densities derived from nearby unfragmented forest. The naive null model predicted an average total of approximately 170 greater gliders, considerably greater than the true count (n = 81). 3. Congruence was examined between field data and predictions from PVA under several metapopulation modelling scenarios. The metapopulation models performed better than the naive null model. Logistic regression showed highly significant positive relationships between predicted and actual patch occupancy for the four scenarios (P = 0.001-0.006). When the model-derived probability of patch occupancy was high (0.50-0.75, 0.75-1.00), there was greater congruence between actual patch occupancy and the predicted probability of occupancy. 4. For many patches, probability distribution functions indicated that model predictions for animal abundance in a given patch were not outside those expected by chance. However, for some patches the model either substantially over-predicted or under-predicted actual abundance. Some important processes, such as inter-patch dispersal, that influence the distribution and abundance of the greater glider may not have been adequately modelled. 5. Additional landscape-scale tests of PVA models, on a wider range of species, are required to assess further predictions made using these tools. This will help determine those taxa for which predictions are and are not accurate and give insights for improving models for applied conservation management.

A scaled difference chi-square test statistic for moment structure analysis

A family of scaling corrections aimed to improve the chi-square approximation of goodness-of-fit test statistics in small samples, large models, and nonnormal data was proposed in Satorra and Bentler (1994). For structural equations models, Satorra-Bentler's (SB) scaling corrections are available in standard computer software. Often, however, the interest is not on the overall fit of a model, but on a test of the restrictions that a null model say ${\cal M}_0$ implies on a less restricted one ${\cal M}_1$. If $T_0$ and $T_1$ denote the goodness-of-fit test statistics associated to ${\cal M}_0$ and ${\cal M}_1$, respectively, then typically the difference $T_d = T_0 - T_1$ is used as a chi-square test statistic with degrees of freedom equal to the difference on the number of independent parameters estimated under the models ${\cal M}_0$ and ${\cal M}_1$. As in the case of the goodness-of-fit test, it is of interest to scale the statistic $T_d$ in order to improve its chi-square approximation in realistic, i.e., nonasymptotic and nonnormal, applications. In a recent paper, Satorra (1999) shows that the difference between two Satorra-Bentler scaled test statistics for overall model fit does not yield the correct SB scaled difference test statistic. Satorra developed an expression that permits scaling the difference test statistic, but his formula has some practical limitations, since it requires heavy computations that are notavailable in standard computer software. The purpose of the present paper is to provide an easy way to compute the scaled difference chi-square statistic from the scaled goodness-of-fit test statistics of models ${\cal M}_0$ and ${\cal M}_1$. A Monte Carlo study is provided to illustrate the performance of the competing statistics.

Type-1 error inflation in the traditional by-participant analysis to metamemory accuracy: a generalized mixed-effects model perspective

In order to examine metacognitive accuracy (i.e., the relationship between metacognitive judgment and memory performance), researchers often rely on by-participant analysis, where metacognitive accuracy (e.g., resolution, as measured by the gamma coefficient or signal detection measures) is computed for each participant and the computed values are entered into group-level statistical tests such as the t-test. In the current work, we argue that the by-participant analysis, regardless of the accuracy measurements used, would produce a substantial inflation of Type-1 error rates, when a random item effect is present. A mixed-effects model is proposed as a way to effectively address the issue, and our simulation studies examining Type-1 error rates indeed showed superior performance of mixed-effects model analysis as compared to the conventional by-participant analysis. We also present real data applications to illustrate further strengths of mixed-effects model analysis. Our findings imply that caution is needed when using the by-participant analysis, and recommend the mixed-effects model analysis.

Analysis of peptides in prohormone convertase 1/3 null mouse brain using quantitative peptidomics

P>Neuropeptides are produced from larger precursors by limited proteolysis, first by endopeptidases and then by carboxypeptidases. Major endopeptidases required for these cleavages include prohormone convertase (PC) 1/3 and PC2. In this study, quantitative peptidomics analysis was used to characterize the specific role PC1/3 plays in this process. Peptides isolated from hypothalamus, amygdala, and striatum of PC1/3 null mice were compared with those from heterozygous and wild-type mice. Extracts were labeled with stable isotopic tags and fractionated by HPLC, after which relative peptide levels were determined using tandem mass spectrometry. In total, 92 peptides were found, of which 35 were known neuropeptides or related peptides derived from 15 distinct secretory pathway proteins: 7B2, chromogranin A and B, cocaine- and amphetamine-regulated transcript, procholecystokinin, proenkephalin, promelanin concentrating hormone, proneurotensin, propituitary adenylate cyclase-activating peptide, proSAAS, prosomatosatin, provasoactive intestinal peptide, provasopressin, secretogranin III, and VGF. Among the peptides derived from these proteins, similar to 1/3 were decreased in the PC1/3 null mice relative to wild-type mice, similar to 1/3 showed no change, and similar to 1/3 increased in PC1/3 null. Cleavage sites were analyzed in peptides that showed no change or that decreased in PC1/3 mice, and these results were compared with peptides that showed no change or decreased in previous peptidomic studies with PC2 null mice. Analysis of these sites showed that while PC1/3 and PC2 have overlapping substrate preferences, there are particular cleavage site residues that distinguish peptides preferred by each PC.

Multilevel Analysis in Household Survey: An Application to Health Condition Data

The aim of this thesis is to apply multilevel regression model in context of household surveys. Hierarchical structure in this type of data is characterized by many small groups. In last years comparative and multilevel analysis in the field of perceived health have grown in size. The purpose of this thesis is to develop a multilevel analysis with three level of hierarchy for Physical Component Summary outcome to: evaluate magnitude of within and between variance at each level (individual, household and municipality); explore which covariates affect on perceived physical health at each level; compare model-based and design-based approach in order to establish informativeness of sampling design; estimate a quantile regression for hierarchical data. The target population are the Italian residents aged 18 years and older. Our study shows a high degree of homogeneity within level 1 units belonging from the same group, with an intraclass correlation of 27% in a level-2 null model. Almost all variance is explained by level 1 covariates. In fact, in our model the explanatory variables having more impact on the outcome are disability, unable to work, age and chronic diseases (18 pathologies). An additional analysis are performed by using novel procedure of analysis :"Linear Quantile Mixed Model", named "Multilevel Linear Quantile Regression", estimate. This give us the possibility to describe more generally the conditional distribution of the response through the estimation of its quantiles, while accounting for the dependence among the observations. This has represented a great advantage of our models with respect to classic multilevel regression. The median regression with random effects reveals to be more efficient than the mean regression in representation of the outcome central tendency. A more detailed analysis of the conditional distribution of the response on other quantiles highlighted a differential effect of some covariate along the distribution.

A methodology for analysis of sugarcane productivity trends - I. Analysis across districts

Historically, few articles have addressed the use of district level mill production data for analysing the effect of varietal change on sugarcane productivity trends. This appears to be due to lack of compiled district data sets and appropriate methods by which to analyse these data. Recently, varietal data on tonnes of sugarcane per hectare (TCH), sugar content (CCS), and their product, tonnes of sugar content per hectare (TSH) on a district basis, have been compiled. This study was conducted to develop a methodology for regular analysis of such data from mill districts to assess productivity trends over time, accounting for variety and variety x environment interaction effects for 3 mill districts (Mulgrave, Babinda, and Tully) from 1958 to 1995. Restricted maximum likelihood methodology was used to analyse the district level data and best linear unbiased predictors for random effects, and best linear unbiased estimates for fixed effects were computed in a mixed model analysis. In the combined analysis over districts, Q124 was the top ranking variety for TCH, and Q120 was top ranking for both CCS and TSH. Overall production for TCH increased over the 38-year period investigated. Some of this increase can be attributed to varietal improvement, although the predictors for TCH have shown little progress since the introduction of Q99 in 1976. Although smaller gains have been made in varietal improvement for CCS, overall production for CCS decreased over the 38 years due to non-varietal factors. Varietal improvement in TSH appears to have peaked in the mid-1980s. Overall production for TSH remained stable over time due to the varietal increase in TCH and the non-varietal decrease in CCS.

Fuzzy clustering applied to a demand response model in a smart grid contingency scenario

This paper focus on a demand response model analysis in a smart grid context considering a contingency scenario. A fuzzy clustering technique is applied on the developed demand response model and an analysis is performed for the contingency scenario. Model considerations and architecture are described. The demand response developed model aims to support consumers decisions regarding their consumption needs and possible economic benefits.