Influence of bearing ball recirculation on error motions of linear axes

For positioning systems utilizing linear guides and trucks with recirculating balls, a method is presented that uses the measured total error motions and the measured phase of ball loops within trucks to determine the influence of each ball loop on the error motions. The influence of ball recirculation on the error motions is estimated a priori via a least-squares solution based on data collected from a multitude of motion tests in which varying phases were measured by sensors integrated into the trucks. This method enables real-time estimation of performance degradations and identification of their sources.     

Neuroscience and architecture: What does the brain tell to an emotional experience of architecture via a functional MR study?

Environment psychologically affects individuals. According to the base of cognitive psychology, there is a direct relationship between human behavior, environment, and emotional process. Assuming that pleasantness and unpleasantness are associated with peripheral nervous system activation, the current study aims to explore if the pleasant or unpleasant architectural places can stimulate the brain regions engaged in emotions or not. As the main contribution, we used functional magnetic resonance imaging (fMRI) measuring blood oxygenation level-dependent (BOLD) changes to effectively detect the brain's region that mainly responds to the emotional-perceptual processes. Based on the results of examining the emotional assessment model of “Pleasure-Arousal” applied to 140 students, 30 most-rated images representing 15 pleasant and 15 unpleasant places were shown to 32 participants in a 1.5-T MRI scanner. After applying standard preprocessing steps (re-alignment, slice-timing, co-registration, segmentation, normalization, and smoothing) to functional MR images, first-level analysis was applied to each subject. The results were evaluated using statistical corrections at different levels for female and male participants with the second-level analysis. In conclusion, it has been shown that there is a significant linkage between environmental experience and brain activation so that the architectural qualities can change blood flow in specific brain regions.     

Integration of machine learning and first principles models

Model building and parameter estimation are traditional concepts widely used in chemical, biological, metallurgical, and manufacturing industries. Early modeling methodologies focused on mathematically capturing the process knowledge and domain expertise of the modeler. The models thus developed are termed first principles models (or white-box models). Over time, computational power became cheaper, and massive amounts of data became available for modeling. This led to the development of cutting edge machine learning models (black-box models) and artificial intelligence (AI) techniques. Hybrid models (gray-box models) are a combination of first principles and machine learning models. The development of hybrid models has captured the attention of researchers as this combines the best of both modeling paradigms. Recent attention to this field stems from the interest in explainable AI (XAI), a critical requirement as AI systems become more pervasive. This work aims at identifying and categorizing various hybrid models available in the literature that integrate machine-learning models with different forms of domain knowledge. Benefits such as enhanced predictive power, extrapolation capabilities, and other advantages of combining the two approaches are summarized. The goal of this article is to consolidate the published corpus in the area of hybrid modeling and develop a comprehensive framework to understand the various techniques presented. This framework can further be used as the foundation to explore rational associations between several models.     

Preparation of poly(methyl methacrylate-co-ethylene glycol dimethacrylate-co-glycidyl methacrylate) walled thermochromic microcapsules and their application to cotton fabrics

This study focused on fabrication of the thermochromic microcapsules and their application to the cotton fabric. In this study, thermochromic systems composed of crystal violet lactone, bisphenol A, and 1-tetradecanol were prepared and microencapsulated by emulsion polymerization method in poly(methyl methacrylate-co-ethylene glycol dimethacrylate-co-glycidyl methacrylate) wall. The microcapsules were analyzed by Fourier transform infrared spectroscopy, scanning electron microscope, transmission electron microscope, differential scanning calorimetry, and thermogravimetric analysis. Their thermoregulating property was tested by T-history test. The results revealed that microcapsules with smooth surfaces, core–shell structured, and spherical shape were successfully produced. The latent heat storage capacity of the microcapsules decreased from 202 J g⁻¹ to 167 J g⁻¹ when their shell/core ratio changed from 0.5/1 to 2/1. Microcapsules were adequately had sufficient thermal resistance to the temperatures they will encounter during their application to textile products and their usage. According to the UV–visible spectroscopy analysis and color measurements, the microcapsules exhibited reversible color change from blue to colorless and vice versa. Besides, the microcapsule impregnated fabric was able to absorb latent heat energy of 21.79 J g⁻¹ at around 35 °C and had cooling effect. According to the colorimetric parameters, the fabric was at blue color at room temperature and became colorless when heated to the temperature above the melting point of thermochromic system. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48815.     

Deliberately Losing Control of C−H Activation Processes in the Design of Small-Molecule-Fragment Arrays Targeting Peroxisomal Metabolism

Combined photochemical arylation, “nuisance effect” (S_NAr) reaction sequences have been employed in the design of small arrays for immediate deployment in medium-throughput X-ray protein–ligand structure determination. Reactions were deliberately allowed to run “out of control” in terms of selectivity; for example the ortho-arylation of 2-phenylpyridine gave five products resulting from mono- and bisarylations combined with S_NAr processes. As a result, a number of crystallographic hits against NUDT7, a key peroxisomal CoA ester hydrolase, have been identified.     

Use of Endostemon tereticaulis (Pear.) M.Ashby and Hyptis spicigera Lam. Plant Extracts as Corrosion Green Inhibitors for Mild Steel in 1M HCl: Electrochemical and Surface Morphological Studies

Protection of Metals and Physical Chemistry of Surfaces - In the present study, we evaluated the effect of corrosion inhibition of ethanol extracts from Endostemon tereticaulis and Hyptis spicigera...     

Evaluation of chemical indicators for tracking and apportionment of phosphorus sources to Table Rock Lake in Southwest Missouri, USA

This work evaluated the suitability of selected chemical species as indicators for tracking and apportionment of point and non-point phosphorus sources within the Table Rock Lake watershed in Southwest Missouri, USA. The species were evaluated with respect to their uniqueness to specific source types, their ability to be detected in both sources and receiving waters, and the consistency of their concentration ratios to phosphorus. Four sampling events were conducted at 15 sample locations in one year to collect water samples for measuring the concentrations of total and dissolved phosphorus, seven anions, and 19 major and trace elements. Current analytical methods were sensitive enough for quantification of most of the chemical species in both sources and the receiving waterbody. Due to the high seasonal variation of phosphorus concentrations in source samples, no chemical species had consistent concentration ratios to phosphorus across source types. However, several chemicals were found to be unique to specific sources; bromide ion can be used as a unique indicator for the effluent of the largest wastewater treatment plant in the watershed.     

Constructing porous ZnO/SnO2 nanocomposites for the detection of methane at low operating temperature

Journal of Porous Materials - Aimed at detecting methane (CH4) gas at low operating temperature, porous ZnO/SnO2 nanocomposites were constructed through a simple two-step method. Pure SnO2 with a...     

Characterization of Thermal-Sprayed HAP and HAP/TiO<Subscript>2</Subscript> Coatings for Biomedical Applications

In the present study, hydroxyapatite (HAP) coating along with HAP/TiO₂ coating has been deposited by high-velocity flame spray (HVFS) technique onto 316LSS. Titania was used as a bond coat and HAP as top coat in HAP/TiO₂ coating. The main aim of the study is to investigate the corrosion behavior of thermal spray coating of HAP and HAP/TiO₂ on steel. Electrochemical corrosion testing was carried out using potentiodynamic polarization test. The corrosion behavior of bare and as-sprayed specimens was analyzed in simulated body fluid known as Hank’s solution. As-sprayed specimens along with corroded specimens were further characterized by XRD, SEM/EDS, and x-ray mapping analysis. It was observed that the HAP/TiO₂ coating possessed higher microhardness (280 Hv) as compared to HAP coating (254 Hv). Surface roughness also got enhanced in case of HAP/TiO₂ coating (9.35 μm) as compared to pure HAP coating (7.37 μm). The porosity of the HAP coating was found to be higher than the bond coating. It was observed that the Ca/P ratio almost resembled that of the natural bone composition. The corrosion resistance of steel increased after the deposition of HAP and HAP/TiO₂ coatings. The maximum corrosion resistance was exhibited by HAP/TiO₂ coating.     

A scalable sparse Cholesky based approach for learning high-dimensional covariance matrices in ordered data

Machine Learning - Covariance estimation for high-dimensional datasets is a fundamental problem in machine learning, and has numerous applications. In these high-dimensional settings the number of...