Exploring Factors Influencing Perceived Quality on Sportswear Fabric

We examine how hedonic and utilitarian motivations have impact on emotions, and in turn, influence perceived quality from Stimulus-Organism-Response (S-O-R) perspectives. Previous studies have been conducted to investigate the effects of different factors on quality of fabrics by considering product related attributes (such as fabric types, touch feelings, price, etc.) and individual characteristics (such as personality) (McCann et al., 2005). They have counted the functional aspects of fabrics but have not convincingly answered how psychological attributes influence consumers’ perceptions about the quality of fabrics; practitioners need this vital information to better understand and conduct business around how consumers formulate their perceptions. For example, our findings can guide emotional design in sportswear fabrics (Hassenzahl, 2006). Also, we develop a more sophisticated theory that investigates what psychological constructs need to be considered. We, therefore, provide initial contributions that are both relevant to practitioners and rigorous to researchers

Compositions and methods for detecting mycobacterium

The present disclosure provides methods of detecting mycobacterium in an individual, generally involving detecting antibody to a mycobacterial lipid in a biological sample obtained from the individual. The present disclosure further provides compositions and kits for carrying out the methodsThe present disclosure provides methods of detecting mycobacterium in an individual, generally involving detecting antibody to a mycobacterial lipid in a biological sample obtained from the individual. The present disclosure further provides compositions and kits for carrying out the method

An advanced prediction method of ship resistance with heterogeneous hull roughness

Despite the ongoing efforts for predicting the effect of hull roughness on ship resistance, the majority of the studies have been treating the hull surfaces as uniformly (i.e., homogeneously) rough. This can be a limiting factor since the real ships' hulls are not uniform due to various reasons such as the heterogeneous accumulation of biofouling. The current study aims to propose a new prediction method for added resistance due to heterogeneous hull roughness. This newly proposed method incorporates the similarity law scaling and the Roughness Impact Factor to consider the relative impacts of hull roughness in different regions. Two separate case studies involving recent Experimental Fluid Dynamics (EFD) and Computational Fluid Dynamics (CFD) results were used to assess the newly proposed method, which showed better prediction performance compared to the conventional method

End-to-end automated microfluidic platform for synthetic biology: from design to functional analysis

DNAConstructor scripts.zip. Zip file containing files gfp_DNAConstructor.txt and rfp_DNAConstructor.txt, input script files for DNA Constructor. (ZIP 1.7 kb

Feature importance measures from random forest regressor using near-infrared spectra for predicting carbonization characteristics of kraft lignin-derived hydrochar

This study investigated the feature importance of near-infrared spectra from random forest regression models constructed to predict the carbonization characteristics of hydrochars produced by hydrothermal carbonization of kraft lignin. The model achieved high coefficients of determination of 0.989, 0.988, and 0.985 with root mean square errors of 0.254, 0.003, and 0.008 when predicting the carbon content, atomic O/C ratio, and H/C ratio, respectively. The random forest models outperformed the multilayer perceptron models for all predictions. In the feature importance analysis, the spectral regions at 1600–1800 nm, the first overtone of C–H stretching vibrations, and 2000–2300 nm, the combination bands, were highly important for predicting the carbon content and O/C predictions, whereas the region at 1250–1711 nm contributed to predicting H/C. The random forest models trained with the high-importance regions achieved better prediction performances than those trained with the entire spectral range, demonstrating the usefulness of the feature importance yielded by the random forest and the feasibility of selective application of the spectral data.This study was supported by the Korea Forestry Promotion Institute through the R&D Program for Forest Science Technology funded by the Korea Forest Service (Project No. 2020215D10-2122-AC01)

Looking for life in the icy crust of Europa

Presented at the Georgia Tech Career, Research, and Innovation Development Conference (CRIDC).Jupiter’s icy moon Europa is of great scientific interest due to its potential for harboring extraterrestrial life. Rather than directly looking for microbial life using optical microscopes and limiting ourselves to life as we know it on Earth, looking for chemical biosignatures is a more holistic approach to search for life. Biosignatures are chemical marks left behind by life systems indicating their presence. For instance, all life on Earth has amino acids as its building blocks and as genetic information storage packets. Similarly, life on Earth seems to be favored by only one type of salts – chloride. Finding biogenic amino acids and chloride salts in the right levels on Europa could be encouraging. To detect amino acids and salts on Europa, we are developing an in-situ sampler, the Icy Moon Penetrator Organic Analyzer (IMPOA), a coke can-sized device. IMPOA is currently capable of sustaining 55,000 G impact force, penetrates deep into the ice crust, collects samples, and analyzes them. IMPOA uses an optical set up to detect the fluorescence of laser-activated amino acids and an embedded contactless electrochemical conductivity sensor for salt detection