Characteristics of ABL during active and weak phases of monsoon

Understanding of the Atmospheric Boundary Layer (ABL) is imperative in the arena of the monsoon field. Here, the features of the ABL are studied employing Conserved Variable Analysis (CVA) using equivalent potential temperature and humidity. In addition, virtual potential temperature and wind are used during active and weak phases of monsoon. The analysis is carried out utilising the radiosonde observations during the monsoon months for two stations situated in the west coast of India. All these parameters show considerable variations during active and weak monsoon phases in both the stations. The core speed and core height vary with these epochs. The core speed is found to be more than 38 knots in the active monsoon phase around 1.2 km over Trivandrum and around 2 km over Mangalore. But during weak monsoon phase the core wind speed is decreased and core height is elevated over both stations. The wind direction shows an additional along shore component during weak monsoon period. The Convective Boundary Layer (CBL) height shows increase during weak monsoon phase over both stations due to less cloudiness and subsequent insolation. The CBL height during the southwest monsoon is more over Mangalore and is attributed by the orographic lifting in the windward side of the Western Ghats while the influence of the Ghats is less over Trivandrum.

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

A hybrid commodity price-forecasting model applied to the sugar-alcohol sector

Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.

Fragmentation of a Neotropical migratory fish population by a century-old dam

Loss of connectivity in impounded rivers is among the impacts imposed by dams, and mitigation measures such as fish passages might not accomplish their purpose of reestablishing an efficient bi-directional gene flow in the fish populations affected. As a consequence, fish populations remain fragmented, and a new interpopulational structure may develop, with increased risk of reduced genetic diversity and stochastic extinction. In order to evaluate the effects of the Gavio Peixoto Dam, which was constructed almost a century ago on the Jacar,-Gua double dagger u River in the Upper Parana River basin, Brazil, a comparative morphometric study was undertaken on the populations of the Neotropical migratory characid fish Salminus hilarii living up- and downstream of this dam. Population dynamics, spatial segregation, and habitat use by different age classes were monitored for 2 years. We found that segregation caused by the dam and long periods with no efficient connection by fish passages have led to fragmentation and interpopulational structuring of S. hilarii, as revealed by canonical variable analysis of morphometric features. The fish populations occupying the up- and downstream sections have succeeded in performing short-distance reproductive migrations in the main river and tributaries, have found suitable habitats for completing their life cycle, and have been able to maintain distinct small-sized populations so far.

Implications of the Intervention Program for Physical Activity (IPPA) in the perception of illness and wellbeing in people with Multiple Sclerosis (MS)

The aim of this study is to examine the implications of the IPPA in the perception of illness and wellbeing in MS patients. Methods - This is a quasi experimental study non-randomized study with 24 MS patients diagnosed at least 1 year before, and with an EDSS score of under 7. We used the IPPA in 3 groups of eight people in 3 Portuguese hospitals (Lisbon, Coimbra, and Porto). The sessions were held once a week for 90 minutes, over a period of 7 weeks. The instruments used were: We asked the subjects the question “Please classify the severity of your disease?” and used the Personal Wellbeing Scale (PWS) at the beginning (time A) and end (time B) of the IPPA. We used the SPSS version 20. A non-parametric statistical hypothesis test (Wilcoxon test) was used for the variable analysis. The intervention followed the recommendations of the Helsinki Declaration. Results – The results suggest that there are differences between time A and B, the perception of illness decreased (p<0.08), while wellbeing increased (p<0.01). Conclusions: The IPPA can play an important role in modifying the perception of disease severity and personal wellbeing.

Understanding sources of the change in international business cycles

Macroeconomic activity has become less volatile over the past three decades in most G7 economies. Current literature focuses on the characterization of the volatility reduction and explanations for this so called "moderation" in each G7 economy separately. In opposed to individual country analysis and individual variable analysis, this paper focuses on common characteristics of the reduction and common explanations for the moderation in G7 countries. In particular, we study three explanations: structural changes in the economy, changes in common international shocks and changes in domestic shocks. We study these explanations in a unified model structure. To this end, we propose a Bayesian factor structural vector autoregressive model. Using the proposed model, we investigate whether we can find common explanations for all G7 economies when information is pooled from multiple domestic and international sources. Our empirical analysis suggests that volatility reductions can largely be attributed to the decline in the magnitudes of the shocks in most G7 countries while only for the U.K., the U.S. and Italy they can partially be attributed to structural changes in the economy. Analyzing the components of the volatility, we also find that domestic shocks rather than common international shocks can account for a large part of the volatility reduction in most of the G7 countries. Finally, we find that after mid-1980s the structure of the economy changes substantially in five of the G7 countries: Germany, Italy, Japan, the U.K. and the U.S..

Characterization of a genomic signature of pregnancy identified in the breast.

The objective of this study was to comprehensively compare the genomic profiles in the breast of parous and nulliparous postmenopausal women to identify genes that permanently change their expression following pregnancy. The study was designed as a two-phase approach. In the discovery phase, we compared breast genomic profiles of 37 parous with 18 nulliparous postmenopausal women. In the validation phase, confirmation of the genomic patterns observed in the discovery phase was sought in an independent set of 30 parous and 22 nulliparous postmenopausal women. RNA was hybridized to Affymetrix HG_U133 Plus 2.0 oligonucleotide arrays containing probes to 54,675 transcripts, scanned and the images analyzed using Affymetrix GCOS software. Surrogate variable analysis, logistic regression, and significance analysis of microarrays were used to identify statistically significant differences in expression of genes. The false discovery rate (FDR) approach was used to control for multiple comparisons. We found that 208 genes (305 probe sets) were differentially expressed between parous and nulliparous women in both discovery and validation phases of the study at an FDR of 10% and with at least a 1.25-fold change. These genes are involved in regulation of transcription, centrosome organization, RNA splicing, cell-cycle control, adhesion, and differentiation. The results provide initial evidence that full-term pregnancy induces long-term genomic changes in the breast. The genomic signature of pregnancy could be used as an intermediate marker to assess potential chemopreventive interventions with hormones mimicking the effects of pregnancy for prevention of breast cancer.

Relationship between obesity and the risk of clinically significant depression: Mendelian randomisation study.

BACKGROUND: Obesity has been shown to be associated with depression and it has been suggested that higher body mass index (BMI) increases the risk of depression and other common mental disorders. However, the causal relationship remains unclear and Mendelian randomisation, a form of instrumental variable analysis, has recently been employed to attempt to resolve this issue. AIMS: To investigate whether higher BMI increases the risk of major depression. METHOD: Two instrumental variable analyses were conducted to test the causal relationship between obesity and major depression in RADIANT, a large case-control study of major depression. We used a single nucleotide polymorphism (SNP) in FTO and a genetic risk score (GRS) based on 32 SNPs with well-established associations with BMI. RESULTS: Linear regression analysis, as expected, showed that individuals carrying more risk alleles of FTO or having higher score of GRS had a higher BMI. Probit regression suggested that higher BMI is associated with increased risk of major depression. However, our two instrumental variable analyses did not support a causal relationship between higher BMI and major depression (FTO genotype: coefficient -0.03, 95% CI -0.18 to 0.13, P = 0.73; GRS: coefficient -0.02, 95% CI -0.11 to 0.07, P = 0.62). CONCLUSIONS: Our instrumental variable analyses did not support a causal relationship between higher BMI and major depression. The positive associations of higher BMI with major depression in probit regression analyses might be explained by reverse causality and/or residual confounding.

Un análisis del discurso político en el Perú contemporáneo : el caso de Alan García y la cortesía positiva

Alan Garcia, l’actuel président du Pérou, est un des politiciens les plus controversés dans l’histoire péruvienne. Le succès de sa carrière comme candidat est fort opposé aux résultats catastrophiques de sa première gestion présidentielle. Dans la culture populaire, les compétences discursives de Garcia, ainsi que le contraste entre son succès et ses pauvres performances en tant que président, l’ont élevé au rang de mythe. Ce travail de recherche présente une analyse pragmatique linguistique des stratégies discursives utilisées par le président Garcia dans son deuxième mandat (2001-2006). L’analyse sera centrée sur le rapport établi par Steven Pinker (2007) entre politesse positive et solidarité communale. Les travaux de Brown et Levinson (1978, 1987) et d’Alan Fiske (1991) sont notre base théorique. L’exclusion sociale d’une partie de la population électorale péruvienne, selon le point de vue de Vergara (2007), est l’élément clé pour mieux comprendre le succès de la stratégie discursive de Garcia. Vegara présente une analyse diachronique multi-variable de la situation politique péruvienne pour expliquer la rationalité de la population électorale péruvienne. À partir de cet encadrement théorique, nous procéderons à l’analyse lexicométrique qui nous permettra d’identifier les stratégies discursives utilisées dans le corpus des discours de Garcia qui a été choisi pour l’analyse. D’après le schéma de Pinker, les données obtenues seront classifiées selon la définition de politesse positive de Brown et Levinson. Finalement, nous évaluerons le rapport entre les résultats classifiés et le modèle de solidarité communale de Fiske. L’objectif est de démontrer que le style discursif de Garcia est structuré à partir d’une rationalité dont l’objet est de fermer la brèche sociale entre le politicien et l’électorat.

Plan Exportador para Improquisa S.A. de tapas poly guard en el mercado latinoamericano 2011-2012

A través del uso de distintas metodologías para la elaboración de un plan exportador, y con la ayuda y guía de nuestro director Andrés Castro, se ha elaborado un análisis integral que le permitirá a la empresa Improquisa S.A., tener algunos elementos clave a su disposición en el momento en que deseen aprobar su plan de exportación o elaborar uno propio. Se inicia entonces con un análisis del sector de plásticos en Colombia, identificando las empresas que hacen parte del sector y que se destacan por tener ingresos operacionales por encima del nivel de las otras empresas. Así se encuentra que hay pocas empresas en pocos lugares de Colombia que conservan estas características. De la misma manera se identifican cuales son las empresas que exportan y hacia que destinos en años anteriores. Luego, pasamos a observar la empresa en su totalidad, pasando desde un planteamiento de su estrategia competitiva hasta un análisis financiero, pasando por todas las áreas de la empresa puesto que una exportación, al ser una actividad integral, involucra a la empresa en su totalidad y por esto se debía analizar completamente. El siguiente paso es entonces decidir a qué mercado exportar y las razones por las cuales se le da prioridad a ese destino por encima de los demás. Dicho ejercicio es realizado con la metodología de Andrés Castro en la que se toman tres potenciales mercados y, a través de la calificación y análisis de variables, se identifica cuál se adapta mejor a las necesidades y capacidades de la empresa. Finalmente se identifican clientes potenciales en el mercado objetivo y se mencionan estrategias claves que pueden ser utilizadas por la empresa para la consecución del plan exportador. Esperamos entonces que este ejercicio sea de gran utilidad para la empresa Improquisa S.A.

Perfil competencial de los responsables de direcci??n en el Ayuntamiento de Palma

Este art??culo presenta los resultados de un estudio realizado entre los funcionarios del Ayuntamiento de Palma de Mallorca. Tiene por objeto conocer las caracter??sticas de los cargos de direcci??n, as?? como de los mandos intermedios en una administraci??n p??blica local de grandes dimensiones, y obtener grupos homog??neos de profesionales con responsabilidades de direcci??n a partir de las competencias autoevaluadas. Para ello se ha realizado un estudio transversal descriptivo, basado en encuesta autoadministrada. Se seleccionaron las 126 personas que cumpl??an las condiciones de tener responsabilidades de direcci??n. Se analiza un amplio conjunto de variables centradas en las competencias profesionales y se realizan an??lisis descriptivos diversos, entre ellos un an??lisis factorial de las competencias autoevaluadas, preparatorios del an??lisis de clusters no jer??rquicos. Los resultados indican la existencia de tres clusters diferentes y consistentes atendiendo al g??nero, edad y procedimiento de acceso a la funci??n directiva.

ms1, a novel stress-responsive, muscle-specific gene that is up-regulated in the early stages of pressure overload-induced left ventricular hypertrophy

We have identified and characterised a cDNA encoding a novel gene, designated myocyte stress 1 (ms1), that is up-regulated within 1 h in the left ventricle following the application of pressure overload by aortic banding in the rat. The deduced ms1 protein of 317 amino acids contains several putative functional motifs, including a region that is evolutionarily conserved. Distribution analysis indicates that rat ms1 mRNA expression is predominantly expressed in striated muscle and progressively increases in the left ventricle from embryo to adulthood. These findings suggest that rust may be important in striated muscle biology and the development of pressure-induced left ventricular hypertrophy. (C) 2002 Published by Elsevier Science B.V. on behalf of the Federation of European Biochemical Societies.

A critical revision of the estimation of the latent heat flux from two-wavelength scintillometry

Simultaneous scintillometer measurements at multiple wavelengths (pairing visible or infrared with millimetre or radio waves) have the potential to provide estimates of path-averaged surface fluxes of sensible and latent heat. Traditionally, the equations to deduce fluxes from measurements of the refractive index structure parameter at the two wavelengths have been formulated in terms of absolute humidity. Here, it is shown that formulation in terms of specific humidity has several advantages. Specific humidity satisfies the requirement for a conserved variable in similarity theory and inherently accounts for density effects misapportioned through the use of absolute humidity. The validity and interpretation of both formulations are assessed and the analogy with open-path infrared gas analyser density corrections is discussed. Original derivations using absolute humidity to represent the influence of water vapour are shown to misrepresent the latent heat flux. The errors in the flux, which depend on the Bowen ratio (larger for drier conditions), may be of the order of 10%. The sensible heat flux is shown to remain unchanged. It is also verified that use of a single scintillometer at optical wavelengths is essentially unaffected by these new formulations. Where it may not be possible to reprocess two-wavelength results, a density correction to the latent heat flux is proposed for scintillometry, which can be applied retrospectively to reduce the error.

Association of vitamin D status with arterial blood pressure and hypertension risk: a mendelian randomisation study

BACKGROUND: Low plasma 25-hydroxyvitamin D (25[OH]D) concentration is associated with high arterial blood pressure and hypertension risk, but whether this association is causal is unknown. We used a mendelian randomisation approach to test whether 25(OH)D concentration is causally associated with blood pressure and hypertension risk. METHODS: In this mendelian randomisation study, we generated an allele score (25[OH]D synthesis score) based on variants of genes that affect 25(OH)D synthesis or substrate availability (CYP2R1 and DHCR7), which we used as a proxy for 25(OH)D concentration. We meta-analysed data for up to 108 173 individuals from 35 studies in the D-CarDia collaboration to investigate associations between the allele score and blood pressure measurements. We complemented these analyses with previously published summary statistics from the International Consortium on Blood Pressure (ICBP), the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and the Global Blood Pressure Genetics (Global BPGen) consortium. FINDINGS: In phenotypic analyses (up to n=49 363), increased 25(OH)D concentration was associated with decreased systolic blood pressure (β per 10% increase, -0·12 mm Hg, 95% CI -0·20 to -0·04; p=0·003) and reduced odds of hypertension (odds ratio [OR] 0·98, 95% CI 0·97-0·99; p=0·0003), but not with decreased diastolic blood pressure (β per 10% increase, -0·02 mm Hg, -0·08 to 0·03; p=0·37). In meta-analyses in which we combined data from D-CarDia and the ICBP (n=146 581, after exclusion of overlapping studies), each 25(OH)D-increasing allele of the synthesis score was associated with a change of -0·10 mm Hg in systolic blood pressure (-0·21 to -0·0001; p=0·0498) and a change of -0·08 mm Hg in diastolic blood pressure (-0·15 to -0·02; p=0·01). When D-CarDia and consortia data for hypertension were meta-analysed together (n=142 255), the synthesis score was associated with a reduced odds of hypertension (OR per allele, 0·98, 0·96-0·99; p=0·001). In instrumental variable analysis, each 10% increase in genetically instrumented 25(OH)D concentration was associated with a change of -0·29 mm Hg in diastolic blood pressure (-0·52 to -0·07; p=0·01), a change of -0·37 mm Hg in systolic blood pressure (-0·73 to 0·003; p=0·052), and an 8·1% decreased odds of hypertension (OR 0·92, 0·87-0·97; p=0·002). INTERPRETATION: Increased plasma concentrations of 25(OH)D might reduce the risk of hypertension. This finding warrants further investigation in an independent, similarly powered study.