Mind-body skills groups for posttraumatic stress disorder and depression symptoms in Palestinian children and adolescents in Gaza.

A mind-body skills group program was evaluated to determine its effects on symptoms of posttraumatic stress disorder (PTSD) and depression, and on hopelessness in children and adolescents in Gaza. The 10-session mind-body skills groups included meditation, guided imagery, breathing techniques, autogenic training, biofeedback, genograms, and self-expression through words, drawings, and movement. Data were analyzed from 129 children and adolescents meeting criteria for PTSD. Significant improvements in PTSD and depression symptoms and a significant decrease in a sense of hopelessness were observed immediately following participation in the program. At 7-month follow-up, the improvements in the total PTSD and depression scores were largely maintained and the decreased sense of hopelessness was fully maintained despite ongoing violent conflict and economic hardship. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

USGS Streamflow Data and Modeling Sand-Bed Rivers

United States Geological Survey streamflow data are commonly used for hydraulic model calibration and boundary conditions. The transitory nature of sand-bed rivers’ bathymetry is problematic for the traditional automated stream gauging methods used by the USGS. This note seeks to assess the limitations of streamflow measurements for use in hydraulic models. An overview of USGS rating-curve development and use is presented with a focus on the specific challenges of sand-bed rivers. Measurements from three consecutive USGS gauges for a storm event on the Rio Grande in Albuquerque, New Mexico, illustrate the outlined problems with rating curves. These gauges are utilized to study the impact of uncertainty in rating-curve discharges on hydraulic model results. A one dimensional hydraulic model of the study reach indicates up to 25% reduction in the calculated flow depth if questionable rating-curve discharges are used as model input. Recommendations for using USGS streamflow data in hydraulic models are outlined.     

Regularized Pre-image Estimation for Kernel PCA De-noising

The main challenge in de-noising by kernel Principal Component Analysis (PCA) is the mapping of de-noised feature space points back into input space, also referred to as “the pre-image problem”. Since the feature space mapping is typically not bijective, pre-image estimation is inherently illposed. As a consequence the most widely used estimation schemes lack stability. A common way to stabilize such estimates is by augmenting the cost function by a suitable constraint on the solution values. For de-noising applications we here propose Tikhonov input space distance regularization as a stabilizer for pre-image estimation, or sparse reconstruction by Lasso regularization in cases where the main objective is to improve the visual simplicity. We perform extensive experiments on the USPS digit modeling problem to evaluate the stability of three widely used pre-image estimators. We show that the previous methods lack stability in the is non-linear regime, however, by applying our proposed input space distance regularizer the estimates are stabilized with a limited sacrifice in terms of de-noising efficiency. Furthermore, we show how sparse reconstruction can lead to improved visual quality of the estimated pre-image.     

Changes in structural aspects of mood during 39–66 h of sleep loss using matched controls

A number of studies have described mood change during sleep loss in the laboratory, however, an understanding of fluctuations in structural aspects of mood under such conditions is lacking. Sixty-two healthy young adults completed one of three possible conditions: one (n = 20) or two (n = 23) nights of sleep loss or the control condition which consisted of one (n = 9) or two (n = 10) nights of 9 h time in bed. The Mood Scale II was completed every two waking hours and data were analysed in terms of the frequency and intensity of mood reports. Overall, sleep loss conditions were associated with significantly less frequent happiness and activation and more frequent fatigue reports (p < 0.001). Intensity was also significantly reduced for activation and happiness, and increased for depression, anger and fatigue (p < 0.05). Interestingly, there were no significant differences in anger following two nights in the laboratory with or without sleep. Further, two nights in the lab with normal sleep was associated with significant increases in depression intensity (p < 0.05). Findings support the hypothesis of a mood regulatory function of sleep and highlight the relative independence of frequency and intensity and of positive and negative mood dimensions. Findings also suggest that the laboratory environment, in the absence of sleep loss, may have a significant negative impact on mood.     

Nitrogen fixation and productivity of winter annual legume cover crops in Upper Midwest organic cropping systems

Nutrient Cycling in Agroecosystems - Legume cover crops can play a valuable role in maintaining and increasing soil quality and nitrogen availability, but are infrequently grown in the Upper...     

Healthy Snacks: Using Nutrient Profiling to Evaluate the Nutrient‐Density of Common Snacks in the United States

Objective: To quantify and compare the nutrient‐density of commonly consumed snacks using two nutrient‐density measures, Nutrient Rich Foods Indices 9.3 (NRF 9.3) and 15.3 (NRF 15.3). Design: Identify commonly consumed categories of snacks and individual snack foods, calculate NRF 9.3 and 15.3 scores, rank snacks by category and by individual food based on nutrient density, compare and contrast scores generated by the two NRF Indices. Main Outcome Measures: NRF 9.3 and 15.3 scores. Analysis: Averages and standard deviations of nutrient‐density scores for each snack category. Results: Vegetables and coffee/tea received the highest category scores on both indices. Cakes/cookies/pastries and sweets had the lowest category scores. NRF 9.3 scores for individual snacks ranged from –46 (soda) to 524 (coffee). NRF 15.3 scores ranged from –45 (soda) to 736 (coffee). Conclusions and Implications: If added to food labels, NRF scores could help consumers identify more nutritious choices. The differences between NRF 9.3 and 15.3 scores generated for the same foods and the limitations of these indices highlight the need for careful consideration of which nutrient‐density measure to include on food labels as well as consumer education.