Exploring Sensory Phenotypes in Autistic Children and Children with ADHD

Autistic children and children with attention-deficit/hyperactivity disorder (ADHD) often experience sensory processing difficulties, which are highly heterogeneous. Researchers have identified sensory phenotypes that co-occur within autistic individuals. However, sensory phenotypes have not been examined in children with ADHD. The aim of this research is to identify whether these sensory phenotypes exist in children with ADHD, and whether these phenotypes are similar to those observed in autism. A secondary aim of this study is to determine whether these sensory phenotypes are related to autism, ADHD, and obsessive-compulsive (OCD) traits. Short Sensory Profile data from 495 autistic children and 461 children with ADHD were subjected to a K-means cluster analysis to determine whether meaningful sensory phenotypes could be modelled. Follow up ANOVAs were used to compare autism, ADHD, and OCD traits across the resultant phenotypes. Overall, autistic children and children with ADHD demonstrated highly similar patterns of sensory phenotypes. Autism, ADHD, and OCD traits differed across the five phenotypes (ps \u3c .001), but these patterns were very similar across the diagnostic groups. Although highly heterogeneous, sensory processing difficulties in both autistic children and children with ADHD can be classified into one of five sensory phenotypes. These sensory phenotypes help to parse the heterogeneity in sensory processing and help to explain variance in behavioural difficulties often observed in these diagnostic groups. Further, these results suggest that transdiagnostic etiologies may underlie sensory difficulties in these groups

The Limerick bubbly flow rig: design, performance, hold-up and mixing pattern

peer-reviewedAs Euler-Euler CFD simulations of bubbly flows suffer from uncertainties due to the many underpinning models, there is an obvious need of accurate experimental data for validation. With this in mind, a new bubbly flow test rig was built to be operated with and without liquid co-flow, with bubble size as uniform as possible in the range 4–7 mm, and with a very even horizontal bubble distribution. We designed the gas sparging system such that we can also produce an essentially bi-modal bubble size distribution. The column consists of two square sections to allow for studying the mixing of two originally separated bubbly flows with either the same or a different bubble size. The bubbles are produced from 2 × 196 needles, bubble sizes are determined with high-speed imaging and with a simple acoustical method, overall volume fractions in the column by means of air chamber pressure measurements. Overall volume fractions are presented as a function of gas and liquid flow rates, with slip velocity mostly increasing with increasing void fraction. First results are obtained on (a) producing bi-model bubble size distributions and the pertinent volume fractions in the column, and (b) flow patterns in the case of unequal aeration

Simulation of particle motion in incompressible fluid by lattice boltzmann MRT model

As far as these days developing simulation fluid flow in different geometries are one the main concern of thermo fluid researchers , This study are going to employ Lattice Boltzmann Method as a computational method to solve some different geometries. This approach tends to demonstrate different accuracy and stability in two Relaxation time for Lattice Boltzmann Method(LBM) in lid driven cavity .Velocity field for different Reynolds number and aspect ratio in channel fluid flow are systematically presented to interpret developed vortex in different time. In this geometries multi particles are simulated for different Reynolds number and it is found that the percentage of removal particles in different time after stability is decreased by growing aspect ratio . In final section Multi-relaxation-time based on Lattice Boltzmann method is applied for simulation of backward-facing step .The obtained results shows position and length of the vortex. The numerical results obtained in this paper are in good agreement with the published experimental and numerical results

Prediction of particle dynamics in lid-driven cavity flow

The prediction of the flow of solid particle through fluid has been an important research topic in the past decades. The difficulties arise to understand the interaction between the particle and surrounding fluid. Therefore, in the present study, the Cubic Interpolated Pseudo- Particle Navier Stokes equation (CIPNSE) was applied to investigate the two-dimensional square lid driven cavity flow of water at wide range of Reynolds numbers. The CIPNSE scheme was used to solve hyperbolic term of the vorticity transport equation. In the CIPNSE scheme, the gradient and the value of the vorticity at the nodes are determined and the stream function is then determined using the vorticity equation. It is discovered that the numerical simulation of CIPNSE provided a very good agreement with the established benchmark results by previous researchers. Then, in order to predict the velocity and position of the particle in the fluid flow, we applied the 4th order Runge-Kutta method to solve the effect from the drag and gravitational forces on the particle

CFD modelling and anfis development for the hydrodynamics prediction of bubble column reactor ring sparger / Mohammad Pourtousi

A detailed understanding of the interactions between gas bubbles and the liquid phases in bubble column reactors (BCR), which enhance the heat and mass transfer and chemical reactions, will greatly assist in the design and optimization of the reactor. Despite of wide researches on industrial BCRs, there are still many design aspects of the reactor and sparger (e.g., sparger types, position and velocity, as well as orifice size of the sparger) that require further investigation. A proper selection of BCR and spargers for different industries would greatly improve BCR efficiency and productivity. In addition, an accurate prediction of BCR hydrodynamics with less computational efforts is a major concern in the design and optimization process. In this study, the effect of ring sparger diameters, superficial gas velocities and number of sparger holes on the flow pattern and gas dynamics in BCR have been investigated. The two-phase Eulerian-Eulerian method embedded in the Commercial Computational Fluid Dynamic software, ANSYS CFX, V14 has been adopted to study the macroscopic hydrodynamics inside a cylindrical BCR. Relevant literature on experimental and numerical results and empirical correlations has been used for validation. Changing the ring sparger diameter and the superficial velocity has a significant effect on the results in comparison to that of the case of the different number of sparger holes. The influence of microscopic parameters such as orifice size, inlet gas velocity, distance between orifices and number of orifices on a single bubble formation, rising, as well as bubble coalescence process are studied using the Volume of Fluid (VOF) method which is embedded in ANSYS FLUENT, V14. In addition, an experimental work has been carried out to validate some of the CFD cases investigated and also to study the effect of inlet flowrate and orifice size on bubble detachment from an orifice. iv An increase in the number of orifices (more than two) resulted in faster bubble detachment from the orifices. This also lead to the production of large bubbles with non-uniform shapes. By determining the specific distance between orifices resulted in bubble formation without coalescence and a uniform size and shape of bubbles. For the first time, the Adaptive Neuro Fuzzy Inference System (ANFIS) model has been developed to predict the microscopic and macroscopic parameters of BCR hydrodynamics. Some of the CFD results from the previous chapters have been used for the development, training, testing and validation of the ANFIS model. The developed ANFIS model is used to predict the liquid flow pattern and gas dynamics for different ring sparger diameters and BCR heights. ANFIS model is also developed for the prediction of the bubble formation from an orifice and to investigate the bubble rise characteristics. Some limitations are found in ANFIS model and this is discussed. As a conclusion, ANFIS method can be employed to predict microscopic and macroscopic results for various operational conditions of BCRs. Unlike the CFD implementation process, ANFIS model has the capability to predict the required results fast and requires less computational effort in providing a non-discrete (continuous) result

Ability of neural network cells in learning teacher motivation scale and prediction of motivation with fuzzy logic system

We employed a new approach in the field of social sciences or psychological aspects of teaching besides using a very common software package that is Statistical Package for the Social Sciences (SPSS). Artificial intelligence (AI) is a new domain that the methods of its data analysis could provide the researchers with new insights for their research studies and more innovative ways to analyze their data or verify the data with this method. Also, a very significant element in teaching is teacher motivation that is the trigger that pushes the teachers forward, depending on some internal and external factors. In the current study, seven research questions were designed to explore different aspects of teacher motivation, and they were analyzed via SPSS. The current study also compared the results by using an adaptive neuro-fuzzy inference system (ANFIS). Due to the similarity of ANFIS to humans' brain intelligence, the results of the current study could be similar to humans regarding what happens in reality. To do so, the researchers used the validated teacher motivation scale (TMS) and asked participants to fill the questionnaire, and analyzed the results. When the inputs were added to the ANFIS system, the model indicated a high accuracy and prediction capability. The findings also illustrated the importance of the tuning model parameters for the ANFIS method to build up the AI model with a high repeatability level. The differences between the results and conclusions are discussed in detail in the article