Do eating behaviours (restraint, uncontrolled and emotional eating) and the general use of emotion regulation strategies (cognitive reappraisal and expressive suppression) predict state body dissatisfaction?

Young girls comparing themselves with thinner women (upward comparison) in social media experience Body Dissatisfaction (BD), which is associated with Disordered Eating Behaviours (DEBs), like Restraint Eating (RE), in an effort to fulfil the thin beauty standards. Recent studies suggest that maladaptive Emotion Regulation Strategies (ERSs) increase BD and DEBS in contrast to the adaptive ones, which can effectively reduce them. However, the researchers in most of these studies instruct ERSs and more recently, researchers who utilised self-report measures have demonstrated controversial results in both studies. Thus, this study adopting a social comparison paradigm, will explore whether the general use of the adaptive Cognitive Reappraisal (CR) and the maladaptive Expressive Suppression and the DEBs of Restraint, Uncontrolled (UE) and Emotional Eating would predict state BD. In addition, the relationships between the predictors will be also explored

A critical discussion of how psychological and biological factors influence the development of anxiety disorders.

Anxiety disorders are becoming a common symptom, with the number of people affected by them rapidly multiplying. Numerous studies try to explain their nature, yet there are no clear answer so far as to what exactly causes them. Up to date bibliography on psychological and biological factors possibly correlating with anxiety disorders, with a focus on genes, chromosomes, proteins, HPA axis, serotonin, the environment and even maternal care are critically discussed

Selection and Modelling of a New Single-Domain Intrabody Against TDP-43

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder associated to deteriorating motor and cognitive functions, and short survival. The disease is caused by neuronal death which results in progressive muscle wasting and weakness, ultimately leading to lethal respiratory failure. The misbehaviour of a specific protein, TDP-43, which aggregates and becomes toxic in ALS patient’s neurons, is supposed to be one of the causes. TDP-43 is a DNA/RNA-binding protein involved in several functions related to nucleic acid metabolism. Sequestration of TDP-43 aggregates is a possible therapeutic strategy that could alleviate or block pathology. Here, we describe the selection and characterization of a new intracellular antibody (intrabody) against TDP-43 from a llama nanobody library. The structure of the selected intrabody was predicted in silico and the model was used to suggest mutations that enabled to improve its expression yield, facilitating its experimental validation. We showed how coupling experimental methodologies with in silico design may allow us to obtain an antibody able to recognize the RNA binding regions of TDP-43. Our findings illustrate a strategy for the mitigation of TDP-43 proteinopathy in ALS and provide a potential new tool for diagnostics

Improvements in wind speed forecasts for wind power prediction purposes using Kalman filtering

International audienceThis paper studies the application of Kalman filtering as a post-processing method in numerical predictions of wind speed. Two limited-area atmospheric models have been employed, with different options/capabilities of horizontal resolution, to provide wind speed forecasts. The application of Kalman filter to these data leads to the elimination of any possible systematic errors, even in the lower resolution cases, contributing further to the significant reduction of the required CPU time. The potential of this method in wind power applications is also exploited. In particular, in the case of wind power prediction, the results obtained showed a remarkable improvement in the model forecasting skill

Spatial and temporal variability of the concentration field from localized releases in a regular building array

Spatial and temporal fluctuations in the concentration field from an ensemble of continuous point-source releases in a regular building array are analyzed from data generated by direct numerical simulations. The release is of a passive scalar under conditions of neutral stability. Results are related to the underlying flow structure by contrasting data for an imposed wind direction of 0 deg and 45 deg relative to the buildings. Furthermore, the effects of distance from the source and vicinity to the plume centreline on the spatial and temporal variability are documented. The general picture that emerges is that this particular geometry splits the flow domain into segments (e.g. “streets” and “intersections”) in each of which the air is, to a first approximation, well mixed. Notable exceptions to this general rule include regions close to the source, near the plume edge, and in unobstructed channels when the flow is aligned. In the oblique (45 deg) case the strongly three-dimensional nature of the flow enhances mixing of a scalar within the canopy leading to reduced temporal and spatial concentration fluctuations within the plume core. These fluctuations are in general larger for the parallel flow (0 deg) case, especially so in the long unobstructed channels. Due to the more complex flow structure in the canyon-type streets behind buildings, fluctuations are lower than in the open channels, though still substantially larger than for oblique flow. These results are relevant to the formulation of simple models for dispersion in urban areas and to the quantification of the uncertainties in their predictions

The Treatment of Uncertainties in Reactive Pollution Dispersion Models at Urban Scales

The ability to predict NO2 concentrations ([NO¬2]) within urban street networks is important for the evaluation of strategies to reduce exposure to NO2. However, models aiming to make such predictions involve the coupling of several complex processes: traffic emissions under different levels of congestion; dispersion via turbulent mixing; chemical processes of relevance at the street-scale. Parameterisations of these processes are challenging to quantify with precision. Predictions are therefore subject to uncertainties which should be taken into account when using models within decision making. This paper presents an analysis of mean [NO¬2] predictions from such a complex modelling system applied to a street canyon within the city of York, UK including the treatment of model uncertainties and their causes. The model system consists of a micro-scale traffic simulation and emissions model, a Reynolds Averaged turbulent flow model coupled to a reactive Lagrangian particle dispersion model. The analysis focuses on the sensitivity of predicted in-street increments of [NO¬2] at different locations in the street to uncertainties in the model inputs. These include physical characteristics such as background wind direction, temperature and background ozone concentrations; traffic parameters such as overall demand and primary NO2 fraction; as well as model parameterisations such as roughness lengths, turbulent time- and length-scales and chemical reaction rate coefficients. Predicted [NO¬2] is shown to be relatively robust with respect to model parameterisations, although there are significant sensitivities to the activation energy for the reaction NO+O3 as well as the canyon wall roughness length. Under off-peak traffic conditions, demand is the key traffic parameter. Under peak conditions where the network saturates, road-side [NO¬2] is relatively insensitive to changes in demand and more sensitive to the primary NO2 fraction. The most important physical parameter was found to be the background wind direction. The study highlights the key parameters required for reliable [NO¬2] estimations suggesting that accurate reference measurements for wind direction should be a critical part of air quality assessments for in-street locations. It also highlights the importance of street scale chemical processes in forming road-side [NO¬2], particularly for regions of high NOx emissions such as close to traffic queues

Next Generation Short-Term Forecasting of Wind Power – Overview of the ANEMOS Project.

International audienceThe aim of the European Project ANEMOS is to develop accurate and robust models that substantially outperform current state-of-the-art methods, for onshore and offshore wind power forecasting. Advanced statistical, physical and combined modelling approaches were developed for this purpose. Priority was given to methods for on-line uncertainty and prediction risk assessment. An integrated software platform, 'ANEMOS', was developed to host the various models. This system is installed by several end-users for on-line operation and evaluation at a local, regional and national scale. Finally, the project demonstrates the value of wind forecasts for the power system management and market integration of wind power. Keywords: Wind power, short-term forecasting, numerical weather predictions, on-line software, tools for wind integration

The Grizzly, October 1, 1991

Whittaker Relates Gulf Experience • Sorority Pledging Underway • U.S.E.A.C. Conference a Success • Ursinus Students Feel the Excitement of Habitat • College Tutorial Project Thrives • U.C. Welcomes New Instructors • Leadershop 1991 • U.S.G.A. Finds a Home • A Plea for Help • GN\u27R: Illusion ... of Good Music • State Museum Exhibits Berman Sculptures • Jane Ira Bloom Jazzes It Up • Sky Sands Strikes Ursinus • Aerobics Attack • The Tempting Temple • Field Hockey Faces Tough Times • Bears Terrorized by Western Maryland • Lady Bears Finish 4th • Bears Tee Off • Runners Get Recognition • Soccer Splits Two • Cross Country Cruises to 3rd Place • Gift to Give • Alcohol Policy Enforcement Tightens • Intellect Over Image • Wismer Whine • Healing the Wounds of the Gulf War • The Search For the Chemical Promisehttps://digitalcommons.ursinus.edu/grizzlynews/1278/thumbnail.jp