In Search of Variables Distinguishing Low and High Achievers in Music Sight Reading Task

The unrehearsed performance of music, called ?sight reading? (SR), is a basic skill for all musicians. Despite the merits of expertise theory, there is no comprehensive model which can classify subjects into high and low performance groups. This study is the first that classifies subjects and is based on an extensive experiment measuring the total SR performance of 52 piano students. Classification methods (cluster analysis, classification tree, linear discriminant analysis) were applied. Results of a linear discriminant analysis revealed a 2-class solution with 4 predictors (predictive error: 15%). --

New gene selection method for classification of cancer subtypes considering within-class variation

AbstractIn this work we propose a new method for finding gene subsets of microarray data that effectively discriminates subtypes of disease. We developed a new criterion for measuring the relevance of individual genes by using mean and standard deviation of distances from each sample to the class centroid in order to treat the well-known problem of gene selection, large within-class variation. Also this approach has the advantage that it is applicable not only to binary classification but also to multiple classification problems. We demonstrated the performance of the method by applying it to the publicly available microarray datasets, leukemia (two classes) and small round blue cell tumors (four classes). The proposed method provides a very small number of genes compared with the previous methods without loss of discriminating power and thus it can effectively facilitate further biological and clinical researches

DeepHealthNet: Adolescent Obesity Prediction System Based on a Deep Learning Framework

Childhood and adolescent obesity rates are a global concern because obesity is associated with chronic diseases and long-term health risks. Artificial intelligence technology has emerged as a promising solution to accurately predict obesity rates and provide personalized feedback to adolescents. This study emphasizes the importance of early identification and prevention of obesity-related health issues. Factors such as height, weight, waist circumference, calorie intake, physical activity levels, and other relevant health information need to be considered for developing robust algorithms for obesity rate prediction and delivering personalized feedback. Hence, by collecting health datasets from 321 adolescents, we proposed an adolescent obesity prediction system that provides personalized predictions and assists individuals in making informed health decisions. Our proposed deep learning framework, DeepHealthNet, effectively trains the model using data augmentation techniques, even when daily health data are limited, resulting in improved prediction accuracy (acc: 0.8842). Additionally, the study revealed variations in the prediction of the obesity rate between boys (acc: 0.9320) and girls (acc: 0.9163), allowing the identification of disparities and the determination of the optimal time to provide feedback. The proposed system shows significant potential in effectively addressing childhood and adolescent obesity

Chirality of a resonance in the absence of backscatterings

Chirality of a resonance localized on an islands chain is studied in a deformed Reuleaux triangular-shaped microcavity, where clockwise and counter clockwise traveling rays are classically separated. A resonance localized on a period-5 islands chain exhibits chiral emission due to the asymmetric cavity shape. Chirality is experimentally proved in a InGaAsP multiquantum-well semiconductor laser by showing that the experimental emission characteristics well coincide with the wave dynamical ones. (C) 2017 Optical Society of America1

Effects of nanofluids containing graphene/graphene-oxide nanosheets on critical heat flux

The superb thermal conduction property of graphene establishes graphene as an excellent material for thermal management. In this paper, we selected graphene/graphene oxide nanosheets as the additives in nanofluids. The authors interestingly found that the highly enhanced critical heat flux (CHF) in the nanofluids containing graphene/graphene-oxide nanosheets (GON) cannot be explained by both the improved surface wettability and the capillarity of the nanoparticles deposition layer. Here we highlights that the GON nanofluid can be exploited to maximize the CHF the most efficiently by building up a characteristically ordered porous surface structure due to its own self-assembly characteristic resulting in a geometrically changed critical instability wavelength.open363

Physical properties and biological effects of mineral trioxide aggregate mixed with methylcellulose and calcium chloride

Objectives: Methylcellulose (MC) is a chemical compound derived from cellulose. MTA mixed with MC reduces setting time and increases plasticity. This study assessed the influence of MC as an anti-washout ingredient and CaCl2 as a setting time accelerator on the physical and biological properties of MTA. Material and Methods: Test materials were divided into 3 groups; Group 1(control): distilled water; Group 2: 1% MC/CaCl2; Group 3: 2% MC/CaCl2. Compressive strength, pH, flowability and cell viability were tested. The gene expression of bone sialoprotein (BSP) was detected by RT-PCR and real­ time PCR. The expression of alkaline phosphatase (ALP) and mineralization behavior were evaluated using an ALP staining and an alizarin red staining. Results: Compressive strength, pH, and cell viability of MTA mixed with MC/CaCl2 were not significantly different compared to the control group. The flowability of MTA with MC/CaCI2 has decreased significantly when compared to the control (