Social and Emotional Skills in at-Risk Adolescents through Participation in Sports.

(1) Background: Adolescents who are under the care of child and youth institutions are vulnerable due to factors that can include disruption to family structure or education and adverse experiences. They often experience poor or unstable support systems, leaving them at risk of delinquency. In this context, sports engagement may provide a stable structure and have positive effects in this population.

Feature analysis for classification of trace fluorescent labeled protein crystallization images.

Background: Large number of features are extracted from protein crystallization trial images to improve the accuracy of classifiers for predicting the presence of crystals or phases of the crystallization process. The excessive number of features and computationally intensive image processing methods to extract these features make utilization of automated classification tools on stand-alone computing systems inconvenient due to the required time to complete the classification tasks. Combinations of image feature sets, feature reduction and classification techniques for crystallization images benefiting from trace fluorescence labeling are investigated.

FocusALL: Focal Stacking of Microscopic Images Using Modified Harris Corner Response Measure.

Automated image analysis of microscopic images such as protein crystallization images and cellular images is one of the important research areas. If objects in a scene appear at different depths with respect to the camera's focal point, objects outside the depth of field usually appear blurred. Therefore, scientists capture a collection of images with different depths of field.

Super-Thresholding: Supervised Thresholding of Protein Crystal Images.

In general, a single thresholding technique is developed or enhanced to separate foreground objects from background for a domain of images. This idea may not generate satisfactory results for all images in a dataset, since different images may require different types of thresholding methods for proper binarization or segmentation. To overcome this limitation, in this study, we propose a novel approach called "super-thresholding" that utilizes a supervised classifier to decide an appropriate thresholding method for a specific image.

Optimizing Associative Experimental Design for Protein Crystallization Screening.

The goal of protein crystallization screening is the determination of the main factors of importance to crystallizing the protein under investigation. One of the major issues about determining these factors is that screening is often expanded to many hundreds or thousands of conditions to maximize combinatorial chemical space coverage for maximizing the chances of a successful (crystalline) outcome. In this paper, we propose an experimental design method called "Associative Experimental Design (AED)" and an optimization method includes eliminating prohibited combinations and prioritizing reagents based on AED analysis of results from protein crystallization experiments.

Evaluation of Normalization and PCA on the Performance of Classifiers for Protein Crystallization Images.

In this paper, we investigate the performance of classification of protein crystallization images captured during protein crystal growth process. We group protein crystallization images into 3 categories: noncrystals, likely leads (conditions that may yield formation of crystals) and crystals. In this research, we only consider the subcategories of noncrystal and likely leads protein crystallization images separately.

Evaluation of Semi-supervised Learning for Classification of Protein Crystallization Imagery.

In this paper, we investigate the performance of two wrapper methods for semi-supervised learning algorithms for classification of protein crystallization images with limited labeled images. Firstly, we evaluate the performance of semi-supervised approach using self-training with naïve Bayesian (NB) and sequential minimum optimization (SMO) as the base classifiers. The confidence values returned by these classifiers are used to select high confident predictions to be used for self-training.

Autofocusing for Microscopic Images using Harris Corner Response Measure.

One of the difficulties for proper imaging in microscopic image analysis is defocusing. Microscopic images such as cellular images, protein images, etc. need properly focused image for image analysis.

Monitoring of some organochlorine pesticide residues of butter in Konya, Turkey.

Some organochlorine pesticide residues were investigated in the samples of all local commercial butter brands sold in the supermarket in Konya (Turkey). Some of the samples were found to have the DDT complex (DDT, DDD, DDE and isomers), total HCH complex (alpha-HCH, beta-HCH, gamma-HCH), aldrin, dieldrin and endosulfan (I and II). Nearly 94% of the butter samples were found to be contaminated.

Monitoring of organochlorine pesticide residues in pikeperch, Stizostedion lucioperca L. in Beysehir Lake (Central Anatolia).

Fishes in Beysehir Lake were analysed to determine organochlorine pesticide residues. The more frequently detected compounds are DDT complex (DDT, DDD, DDE and isomers), total HCH complex (alpha-HCH, beta-HCH and gamma-HCH or lindane), aldrin, dieldrin, endrin and heptachlorine. Eighty five percent of the fish samples were found to be contaminated.