Challenging Behaviors in Children with Comorbid Autism Spectrum Disorder and Attention-Deficit/Hyperactivity Disorder

Challenging behaviors, such as aggression, destruction, self-injurious behaviors, or stereotypic movements, affect the majority of individuals with Autism Spectrum Disorder. One factor that is known to influence the frequency at which challenging behaviors occur is the presence of a comorbid disorder. Attention-deficit/hyperactivity disorder (ADHD) is thought to be one such disorder. This study aimed to compare the prevalence rates of challenging behaviors, according to the Autism Spectrum Disorder-Behavior Problems, Child Version (ASD-BPC), in children ages 6-16 with parent reported symptoms of ASD, ADHD, comorbid ASD/ADHD, and no diagnosis. Differences existing overall were examined as well as differences on the ASD-BPC’s two factors, behaviors directed towards self and behaviors directed towards others. Results indicate that individuals with symptoms of ASD/ADHD display significantly higher rates of challenging behavior than those with symptoms of ADHD only and no diagnosis. They also indicate that those with symptoms of ADHD displayed higher rates of challenging behavior than those with no diagnosis. A better understanding of challenging behaviors in individuals with comorbid ASD/ADHD will assist in more accurate differential diagnoses

Autonomous analysis to identify bijels from two-dimensional images

Bicontinuous interfacially jammed emulsion gels (bijels) are novel composite materials that can be challenging to manufacture. As a step towards automating production, we have developed a machine learning tool to classify fabrication attempts. We use training and testing data in the form of confocal images from both successful and unsuccessful attempts at bijel fabrication. We then apply machine learning techniques to this data in order to classify whether an image is a bijel or a non-bijel. Our principal approach is to process the images to find their autocorrelation function and structure factor, and from these functions we identify variables that can be used for training a supervised machine learning model to identify a bijel image. We are able to categorise images with reasonable accuracies of 85.4% and 87.5% for two different approaches. We find that using both the liquid and particle channels helps to achieve optimal performance and that successful classification relies on the bijel samples sharing a characteristic length scale. Our second approach is to classify the shapes of the liquid domains directly; the shape descriptors are then used to classify fabrication attempts via a decision tree. We have used an adaptive design approach to find an image pre-processing step that yields the optimal classification results. Again, we find that the characteristic length scale of the images is crucial in performing the classification

Rheological Behavior and in Situ Confocal Imaging of Bijels Made by Mixing

International audienc

Nanostructured, Fluid-Bicontinuous Gels for Continuous-Flow Liquid–Liquid Extraction

Fluid-bicontinuous gels are unique materials that allow two distinct fluids to interact through a percolating, rigid scaffold. Current restrictions for their use are the large fluid-channel sizes (>5 µm), limiting the fluid–fluid interaction surface-area, and the inability to flow liquids through the channels. In this work a scalable synthesis route of nanoparticle stabilized fluid-bicontinuous gels with channels sizes below 500 nm and specific surface areas of 2 m2 cm−3 is introduced. Moreover, it is demonstrated that liquids can be pumped through the fluid-bicontinuous gels via electroosmosis. The fast liquid flow in the fluid-bicontinuous gel facilitates their use for molecular separations in continuous-flow liquid–liquid extraction. Together with the high surface areas, liquid flow through fluid-bicontinuous gels enhances their potential as highly permeable porous materials with possible uses as microreaction media, fuel-cell components, and separation membranes

Landscape and Residential Variables Associated with Plague-Endemic Villages in the West Nile Region of Uganda

Plague, caused by the bacteria Yersinia pestis , is a severe, often fatal disease. This study focuses on the plagueendemic West Nile region of Uganda, where limited information is available regarding environmental and behavioral risk factors associated with plague infection. We conducted observational surveys of 10 randomly selected huts within historically classified case and control villages (four each) two times during the dry season of 2006 ( N = 78 case huts and N = 80 control huts), which immediately preceded a large plague outbreak. By coupling a previously published landscape-level statistical model of plague risk with this observational survey, we were able to identify potential residence-based risk factors for plague associated with huts within historic case or control villages (e.g., distance to neighboring homestead and presence of pigs near the home) and huts within areas previously predicted as elevated risk or low risk (e.g., corn and other annual crops grown near the home, water storage in the home, and processed commercial foods stored in the home). The identified variables are consistent with current ecologic theories on plague transmission dynamics. This preliminary study serves as a foundation for future case control studies in the area

Fabrication of bijels with sub-micron domains via a single-channel flow device

Particle-stabilized bicontinuous emulsions (bijels) are made of two interwoven liquid channel systems. In contrast to emulsion droplets, the liquid-liquid interface of bijels curves both towards the oil and the water phases. Thus, particles with equal wettability for both oil and water are needed to stabilize the interface. In this research paper, we enhance the understanding of nanoparticle functionalization by a surfactant for controlling the particle wettability. To this end, we develop a novel, single-channel, continuous flow method, enabling the rapid synthesis and analysis of bijels formed via solvent transfer induced phase separation (STrIPS). Silica nanoparticles are functionalized with the positively charged surfactant (cetyltrimethylammonium+, CTA+). Zeta-potential and colloidal stability analysis are employed to characterize the CTA+ functionalization. Confocal and electron microscopy are used to visualize the resulting bijel structures. Bijels with nearly uniform, sub-micrometer channels are obtained when the particle functionalization by CTA+ is regulated. To this end, the initial negative zeta-potential of the particles needs to be low enough to prevent excessive CTA+ adsorption. The adsorption is further controlled by adjusting the concentrations of CTA+, salt and glycerol additive. This report shows that the nanoparticle surfactant modification depends on multiple parameters, providing guidance for future bijel synthesis approaches