Class of correlated random networks with hidden variables

We study a class of models of correlated random networks in which vertices are characterized by hidden variables controlling the establishment of edges between pairs of vertices. We find analytical expressions for the main topological properties of these models as a function of the distribution of hidden variables and the probability of connecting vertices. The expressions obtained are checked by means of numerical simulations in a particular example. The general model is extended to describe a practical algorithm to generate random networks with an a priori specified correlation structure. We also present an extension of the class, to map nonequilibrium growing networks to networks with hidden variables that represent the time at which each vertex was introduced in the system.

Stability and robustness of blood variables in an antidoping context.

Introduction:  With the setting up of the newly Athlete's Biological Passport antidoping programme, novel guidelines have been introduced to guarantee results beyond reproach. We investigated in this context, the effect of storage time on the variables commonly measured for the haematological passport. We also wanted to assess for these variables, the within and between analyzer variations. Methods:  Blood samples were obtained from top level male professional cyclists (27 samples for the first part of the study and 102 for the second part) taking part to major stage races. After collection, they were transported under refrigerated conditions (2 °C < T < 12 °C), delivered to the antidoping laboratory, analysed and then stored at approximately 4 °C to conduct analysis at different time points up to 72 h after delivery. A mixed-model procedure was used to determine the stability of the different variables. Results:  As expected haemoglobin concentration was not affected by storage and showed stability for at least 72 h. Under the conditions of our investigation, the reticulocytes percentage showed a much better stability than previous published data (> 48 h) and the technical comparison of the haematology analyzer demonstrated excellent results. Conclusion:  In conclusion, our data clearly demonstrate that as long as the World Anti-Doping Agency's guidelines are followed rigorously, all blood results reach the quality level required in the antidoping context.

Las relaciones actitud-conducta y'otras variables' a partir de la teoría de Fishbein y Ajzena y del modelo LISREL: Estudio empírico

A través de la investigación presentada en este articulo se ha pretendido operacionalizar la parte predictiva de la Teoria de Acción Razonada, propuesta por Fishbein y Ajzen. Para ello, se ha utilizado la reciente metodologia de 10s modelos de ecuaciones estructurales lineales con variables latentes desarrollados por Joreskog y Sorbom, entre otros. Como dominio se ha delimitado el consumo de tabaco en distintas situaciones sociales. Después de estimar y valorar el modelo predictivo especificado desde la Teoria de Fishbein y Ajzen, se estimo y valoro el modelo generalizado propuesto por Bentler y Speckart y se asumió como mas coherente este modelo generalizado. En el trabajo también se plantean una serie de observaciones para optimizar, sobre todo, la parte metodológica de recogida de datos asociados a estos modelos y se presenta una propuesta para operacionalizar todo el sistema teórico de predicción y explicación de las conductas desde la Teoria de Fishbein y Ajzen.

Retaining principal components for discrete variables

The present study discusses retention criteria for principal components analysis (PCA) applied to Likert scale items typical in psychological questionnaires. The main aim is to recommend applied researchers to restrain from relying only on the eigenvalue-than-one criterion; alternative procedures are suggested for adjusting for sampling error. An additional objective is to add evidence on the consequences of applying this rule when PCA is used with discrete variables. The experimental conditions were studied by means of Monte Carlo sampling including several sample sizes, different number of variables and answer alternatives, and four non-normal distributions. The results suggest that even when all the items and thus the underlying dimensions are independent, eigenvalues greater than one are frequent and they can explain up to 80% of the variance in data, meeting the empirical criterion. The consequences of using Kaiser"s rule are illustrated with a clinical psychology example. The size of the eigenvalues resulted to be a function of the sample size and the number of variables, which is also the case for parallel analysis as previous research shows. To enhance the application of alternative criteria, an R package was developed for deciding the number of principal components to retain by means of confidence intervals constructed about the eigenvalues corresponding to lack of relationship between discrete variables.

School burnout in adolescents : Differences in background variables and exploration of school-related stress at the end of compulsory schooling

The aim of this study is to contribute to a better understanding of the risk factors associated with school burnout, which has recently been described as a syndrome of emotional exhaustion due to school demands, cynical and detached attitude towards school and feelings of inadequacy as a student (Salmela-Aro, Kiuru, Pietikainen & Jokela, 2008a). The research focuses on students in the last years of compulsory schooling, period in which burnout has not received much attention yet. A total of 342 adolescents (Mean age = 14.84) were asked to complete questionnaires about school burnout, school-related stress and background variables. The results showed differences in school burnout by gender, grade level and school track, with girls, last grade of compulsory school and high-track classes, showing the highest scores. No difference was observed with respect to grade retention. Several types of school stress were identified, with stress type Success related to pressures to succeed and concerns about the academic future being the highest. Finally, stress and burnout were strongly and positively correlated, and the type of stress Success was the best predictor of overall Burnout, Exhaustion and Inadequacy dimension scores. The results are discussed in relation to their theoretical relevance and implications for the prevention of school burnout in adolescents.

Family burden related to clinical and functional variables of people with intellectual disability with and without a mental disorder

Few studies have been found that to assess the factors that explain higher levels of familyburden in adults with intellectualdisability (ID) and intellectualdisability and mental disorders (ID-MD). The aims of this study were to assess familyburden in people with ID and ID-MD and to determine which sociodemographic, clinical and functionaldisabilityvariables account for familyburden. The sample is composed of pairs of 203 participants with disability and their caregivers, of which 33.5% are caregivers of people with ID and 66.5% of ID-MD. Assessments were performed using scales of clinical and functionaldisability as the following instruments: Weschler Adult Intelligence Scale-III (WAIS-III), Inventory for Client and Agency Planning (ICAP), Psychiatric Assessment Schedule for Adults with Development Disability (PAS-ADD checklist), Disability Assessment Schedule of the World Health Organization (WHO-DAS-II) and familyburden (Subjective and Objective FamilyBurden Inventory - SOFBI/ECFOS-II). People with ID-MD presented higher levels of functionaldisability than those with ID only. Higher levels of familyburden were related to higher functionaldisability in all the areas (p < 0.006-0.001), lower intelligence quotient (p < 0.001), diagnosis of ID-MD (p < 0.001) and presence of organic, affective, psychotic and behavioral disorders (p < 0.001). Stepwise multiple regression showed that behavioral problems, affective and psychotic disorder, disability in participation in society, disability in personal care and presence of ID-MD explained more than 61% of the variance in familyburden. An integrated approach using effective multidimensional interventions is essential for both people with ID and ID-MD and their caregivers in order to reduce familyburden.

Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.

Balance nutricional y número de hojas como variables de predicción del rendimiento del plátano Hartón

El objetivo de este trabajo fue desarrollar una ecuación de regresión que permitiese estimar el rendimiento (Y) del plátano Hartón (Musa AAB subgrupo plátano cv. Hartón), con la relación entre el Índice de Balance de Nutrientes DRIS (IBN-DRIS) (X1) y el número de hojas de la planta madre (X2). Usando un muestreo completamente al azar, se colectaron 398 muestras de tejido foliar. Se obtuvo la ecuación: Y = 30,351** - 8,644** log X1 + 0,27502*X2, con R² de 0,6206***, con distribución normal de los residuos. Pudo demostrarse que con la misma se puede predecir el rendimiento potencial de cualquier plantación del plátano Hartón en el área de estudio.

Optimization of Snow Drifting Mitigation and Control Methods for Iowa Conditions Part II, TR-626, 2015

Blowing and drifting of snow is a major concern for transportation efficiency and road safety in regions where their development is common. One common way to mitigate snow drift on roadways is to install plastic snow fences. Correct design of snow fences is critical for road safety and maintaining the roads open during winter in the US Midwest and other states affected by large snow events during the winter season and to maintain costs related to accumulation of snow on the roads and repair of roads to minimum levels. Of critical importance for road safety is the protection against snow drifting in regions with narrow rights of way, where standard fences cannot be deployed at the recommended distance from the road. Designing snow fences requires sound engineering judgment and a thorough evaluation of the potential for snow blowing and drifting at the construction site. The evaluation includes site-specific design parameters typically obtained with semi-empirical relations characterizing the local transport conditions. Among the critical parameters involved in fence design and assessment of their post-construction efficiency is the quantification of the snow accumulation at fence sites. The present study proposes a joint experimental and numerical approach to monitor snow deposits around snow fences, quantitatively estimate snow deposits in the field, asses the efficiency and improve the design of snow fences. Snow deposit profiles were mapped using GPS based real-time kinematic surveys (RTK) conducted at the monitored field site during and after snow storms. The monitored site allowed testing different snow fence designs under close to identical conditions over four winter seasons. The study also discusses the detailed monitoring system and analysis of weather forecast and meteorological conditions at the monitored sites. A main goal of the present study was to assess the performance of lightweight plastic snow fences with a lower porosity than the typical 50% porosity used in standard designs of such fences. The field data collected during the first winter was used to identify the best design for snow fences with a porosity of 50%. Flow fields obtained from numerical simulations showed that the fence design that worked the best during the first winter induced the formation of an elongated area of small velocity magnitude close to the ground. This information was used to identify other candidates for optimum design of fences with a lower porosity. Two of the designs with a fence porosity of 30% that were found to perform well based on results of numerical simulations were tested in the field during the second winter along with the best performing design for fences with a porosity of 50%. Field data showed that the length of the snow deposit away from the fence was reduced by about 30% for the two proposed lower-porosity (30%) fence designs compared to the best design identified for fences with a porosity of 50%. Moreover, one of the lower-porosity designs tested in the field showed no significant snow deposition within the bottom gap region beneath the fence. Thus, a major outcome of this study is to recommend using plastic snow fences with a porosity of 30%. It is expected that this lower-porosity design will continue to work well for even more severe snow events or for successive snow events occurring during the same winter. The approach advocated in the present study allowed making general recommendations for optimizing the design of lower-porosity plastic snow fences. This approach can be extended to improve the design of other types of snow fences. Some preliminary work for living snow fences is also discussed. Another major contribution of this study is to propose, develop protocols and test a novel technique based on close range photogrammetry (CRP) to quantify the snow deposits trapped snow fences. As image data can be acquired continuously, the time evolution of the volume of snow retained by a snow fence during a storm or during a whole winter season can, in principle, be obtained. Moreover, CRP is a non-intrusive method that eliminates the need to perform man-made measurements during the storms, which are difficult and sometimes dangerous to perform. Presently, there is lots of empiricism in the design of snow fences due to lack of data on fence storage capacity on how snow deposits change with the fence design and snow storm characteristics and in the estimation of the main parameters used by the state DOTs to design snow fences at a given site. The availability of such information from CRP measurements should provide critical data for the evaluation of the performance of a certain snow fence design that is tested by the IDOT. As part of the present study, the novel CRP method is tested at several sites. The present study also discusses some attempts and preliminary work to determine the snow relocation coefficient which is one of the main variables that has to be estimated by IDOT engineers when using the standard snow fence design software (Snow Drift Profiler, Tabler, 2006). Our analysis showed that standard empirical formulas did not produce reasonable values when applied at the Iowa test sites monitored as part of the present study and that simple methods to estimate this variable are not reliable. The present study makes recommendations for the development of a new methodology based on Large Scale Particle Image Velocimetry that can directly measure the snow drift fluxes and the amount of snow relocated by the fence.

Increasing stair climbing in a train station: effects of contextual variables and visibility

Accumulation of physical activity during daily living is a current public health target that is influenced by the layout of the built environment. This study reports how the layout of the environment may influence responsiveness to an intervention. Pedestrian choices (n = 41 717) between stairs and the adjacent escalators were monitored for seven weeks in a train station (Birmingham, UK). After a 3.5 week baseline period, a stair riser banner intervention to increase stair climbing was installed on two staircases adjacent to escalators and monitoring continued for a further 3.5 weeks. Logistic regression analyses revealed that the visibility of the intervention, defined as the area of visibility in the horizontal plane opposite to the direction of travel (termed the isovist) had a major effect on success of the intervention. Only the largest isovist produced an increase in stair climbing (isovist=77.6 m2, OR = 1.10, CIs 1.02-1.19; isovist=40.7 m2, OR = 0.98, CIs 0.91-1.06; isovist=53.2 m2, OR = 1.00, CIs 0.95-1.06). Additionally, stair climbing was more common during the morning rush hour (OR = 1.56, CIs 1.80-2.59) and at higher levels of pedestrian traffic volume (OR = 1.92, CIs 1.68-2.21). The layout of the intervention site can influence responsiveness to point-of-choice interventions. Changes to the design of train stations may maximize the choice of the stairs at the expense of the escalator by pedestrians leaving the station.

Proposal of three thermodynamic variables to discriminate between storms associated with hail and storms with intense rainfall in Catalonia (Proposta de tres variables termodinàmiques per discriminar entre tempestes amb pedregades i tempestes amb pluges intenses)

Between late spring and early fall, the development of storms is common in Catalonia. Despite the fact that they usually produce heavy showers of short duration, they can also involve severe weather with ice pellets or hail. While the latter usually affect inland regions, and there are numerous publications on these cases; the analysis of events affecting the coast and causing damage to public and private properties is not so well developed. The aim of this study is to provide additional thermodynamic indicators that help differentiate storms with hail from storms without hail, considering cases that have affected various regions of Catalonia, mainly coastal areas. The aim is to give more information to improve prognosis and the ability to detail information in these situations. The procedure developed involved the study of several episodes of heavy rainfall and hail that hit Catalonia during the 2003-2009 period, mainly in the province of Girona, and validated the proposal during the campaign of late summer and fall of 2009, as well as 2012. For each case, several variables related to temperature, humidity and wind were analyzed at different levels of the atmosphere, while the information provided by the radio sounding in Barcelona was also taken into account. From this study, it can be concluded that the temperature difference between 500 hPa and 850 hPa, the humidity in the lower layers of the atmosphere and the LI index are good indicators for the detection of storms with associated hail.

Introduction of snow and geomorphic disturbance variables into predictive models of alpine plant distribution in the Western Swiss Alps

Indirect topographic variables have been used successfully as surrogates for disturbance processes in plant species distribution models (SDM) in mountain environments. However, no SDM studies have directly tested the performance of disturbance variables. In this study, we developed two disturbance variables: a geomorphic index (GEO) and an index of snow redistribution by wind (SNOW). These were developed in order to assess how they improved both the fit and predictive power of presenceabsence SDM based on commonly used topoclimatic (TC) variables for 91 plants in the Western Swiss Alps. The individual contribution of the disturbance variables was compared to TC variables. Maps of models were prepared to spatially test the effect of disturbance variables. On average, disturbance variables significantly improved the fit but not the predictive power of the TC models and their individual contribution was weak (5.6% for GEO and 3.3% for SNOW). However their maximum individual contribution was important (24.7% and 20.7%). Finally, maps including disturbance variables (i) were significantly divergent from TC models in terms of predicted suitable surfaces and connectivity between potential habitats, and (ii) were interpreted as more ecologically relevant. Disturbance variables did not improve the transferability of models at the local scale in a complex mountain system, and the performance and contribution of these variables were highly species-specific. However, improved spatial projections and change in connectivity are important issues when preparing projections under climate change because the future range size of the species will determine the sensitivity to changing conditions.

Variation in biomass related variables of reed canary grass

Selostus: Ruokohelven biomassan tuotantoon vaikuttavien ominaisuuksien vaihtelu