Evaluation of driver drowsiness using respiration analysis by thermal imaging on a driving simulator

In this paper, a new non-intrusive driver drowsiness detection method is introduced based on respiration analysis using facial thermal imaging. Drowsiness is the cause of many driving accidents all over the world. Drivers’ respiration system undergoes significant changes from wakefulness to drowsiness and can be used to detect drowsiness. Current respiration measurement methods are intrusive and uncomfortable making respiration the least measured vital sign during driving. In this paper, a new method is presented based on facial thermal imaging to analyze drivers’ respiration signal non-intrusively. Thirty subjects are tested in a car simulator. They are fully awake at the beginning and experience drowsiness during the tests. The mean and the standard deviation of the respiration rate and the inspiration-to-expiration time ratio are extracted from the subjects’ respiration signal. To detect drowsiness, the Support Vector Machine (SVM) and the K-Nearest Neighbor (KNN) classifiers are used. The Observer Rating of Drowsiness method is used for scoring the drowsiness level and validating the proposed method. The performance and the results of both methods are presented and compared. The results indicate that drowsiness can be detected with the accuracy of 90%, sensitivity of 92%, specificity of 85%, and precision of 91%.

     

Effect of surface area of nanosilica particles on the cure kinetics parameters of an epoxy resin system

Knowing of thermoset curing kinetics is essential for process development, quality control, and achieving desirable products. Hence, in this article, cure kinetics of an EPON 828 epoxy resin/dicyandiamide curing agent/diuron accelerator system is investigated. This resin system is usually used for the production of epoxy/glass fiber prepregs used in wind turbine blades. For this, differential scanning calorimetry analysis is used and the effect of temperature, weight percentage, and size of nanosilica is studied by conducting isothermal tests at several temperatures for samples with and without nanoparticles. An autocatalytic curing model is applied to describe the cure kinetic of system and then the variations in model parameters calculated by curve fitting using the MATLAB software. The results show that the increase in temperature, weight percentage of nanosilica from 0 to 6%, and surface area of nanosilica particles lead to the increase in curing rate, whereas the increase in the percentage and surface area of nanosilica particles significantly decreases total heat of reaction. At the end, the relation between each of model parameters and the total surface area of nanosilica particles, calculated by mathematical equations, is obtained. The allowable maximum surface area of nanosilica used in the mathematical equations is 12 m² g⁻¹. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47958.     

Commercial lignosulfonates from different sulfite processes as partial phenol replacement in PF resole resins

Four commercial spruce lignosulfonates representing the most common acidic, neutral, and alkaline sulfite pulping processes and varying significantly in molecular weight characteristics were tested as partial (40 wt %) phenol substitute materials for the manufacture of lignosulfonate‐phenol‐formaldehyde (LPF) resole resins. Similar as recently reported for technical lignins from nonsulfite pulping processes (kraft, soda, organosolv), all lignosulfonates of this study effectuated a faster viscosity gain during resole cooking compared to the lignin‐free reference resin (1000 mPa s after 120 min vs. 250 min to reach 1000 mPa s). Sodium lignosulfonate featuring the lowest weight average molecular weight (M_w 5780 g mol^?1) and dispersity (Ð 6.1) turned out to be superior to the other lignosulfonates with regard to curing rate (B‐time; 3:37 min vs. 6:41–9:08 min) and tensile shear strength development under hot pressing (120 °C; T_S,max = 5.64 N mm^?2 after 8 min) for beech veneer strips glued together with the respective LPF resins. Calcium and magnesium lignosulfonates are less suited with regard to phenol replacement due to the poor performance of the respective LPF adhesives in terms of tensile shear strength (T_S,max = 3.29–3.49 N mm^?2 after 12 min) most likely caused by considerable amounts of side products formed in the course of formose‐type reactions. Phenolation of the two promising lignosulfonates, that is, sodium and ammonium lignosulfonate, did neither considerably increase the rate of PF network formation during resin cooking and curing nor improve tensile strength development during hot pressing. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 45893.     

Multi‐“Color” Delineation of Bone Microdamages Using Ligand‐Directed Sub‐5 nm Hafnia Nanodots and Photon Counting CT Imaging

The early detection of bone microdamages is crucial to make informed decisions about the therapy and taking precautionary treatments to avoid catastrophic fractures. Conventional computed tomography (CT) imaging faces obstacles in detecting bone microdamages due to the strong self‐attenuation of photons from bone and poor spatial resolution. Recent advances in CT technology as well as novel imaging probes can address this problem effectively. Herein, the bone microdamage imaging is demonstrated using ligand‐directed nanoparticles in conjunction with photon counting spectral CT. For the first time, Gram‐scale synthesis of hafnia (HfO₂) nanoparticles is reported with surface modification by a chelator moiety. The feasibility of delineating these nanoparticles from bone and soft tissue of muscle is demonstrated with photon counting spectral CT equipped with advanced detector technology. The ex vivo and in vivo studies point to the accumulation of hafnia nanoparticles at microdamage site featuring distinct spectral signal. Due to their small sub‐5 nm size, hafnia nanoparticles are excreted through reticuloendothelial system organs without noticeable aggregation while not triggering any adverse side effects based on histological and liver enzyme function assessments. These preclinical studies highlight the potential of HfO₂‐based nanoparticle contrast agents for skeletal system diseases due to their well‐placed K‐edge binding energy.     

Risk-Based Design of Flood Control Systems Considering Multiple Dependent Uncertainties

Due to random behavior of flood events and inaccuracies in measurements, design, analysis, and operation of flood control systems are subjected to several uncertainties. An important aspect in developing stochastic models for evaluating and analyzing more than one uncertainty is the dependence or independence of them. In flood control projects, hydrologic, hydraulic, geotechnical, and economic uncertainties are important considerations. In this paper, a stochastic Monte-Carlo simulation – optimization modeling approach is described for risk-based design of flood control levees (as a common structural flood control measure): considering multiple dependent uncertainties. It has been applied to the Leaf River reach in Hattiesburg, Mississippi for testing and evaluation of modeling results. Unlike a deterministic model that yields just one set of values for system dimensions, the stochastic model solution gives a range of values for each of them. One of the major reasons for limited field application of uncertainty analysis is difficulties in performing the modeling results in real world contexts. For closing the gap between theory and reality, design charts are developed in this study. This helps decision makers in identifying design values with desired and accepted risks.     

Optimization of arsenite removal by adsorption onto organically modified montmorillonite clay: Experimental & theoretical approaches

Arsenic is a critical contaminant for aqueous environments as it poses harmful health risks. To meet the stringent regulations regarding the presence of arsenic in aqueous solutions, the feasibility of montmorillonite clay modified with hexadecyltrimethyl ammonium chloride as the adsorbent was tested for the removal of arsenic ions from aqueous solutions. A scanning electron microscopy (SEM) study confirmed that the organically modified nanoclay (ONC) adsorbent had a porous structure with a vast adsorbent surface.The x-ray fluorescence (XRF) analysis proved the presence of carbon in the structure of the modified nanoclay that can be evidence for the creation of ONC. The x-ray diffraction (XRD) analysis results confirm the existence of four main groups of minerals, carbonate (Calcite), clay (Askmtyt and Kandyt), silicate (Quartz), and phyllosilicate (Kaolinite), in the ONC structure.The influence of various parameters such as solution pH, adsorbent dosage, initial arsenite concentration, and contact time on arsenic adsorption onto ONC was investigated. A 2⁵ full factorial central composite experimental design was applied. A central composite design under response surface methodology (RSM) was employed to investigate the effects of independent variables on arsenite removal and to determine the optimum condition. The experimental values were in a good fit with the ones predicted by the model. The optimal operating points (adsorbent dosage: 3.7 g L^?1, surfactant dosage: 3 g L^?1 and the contact time: 37.2min) giving maximum arsenite removal (95.95%) were found using Solver “Add-ins” in Microsoft Excel 2010.