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%.

     

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.     

Harnessing irreversible thermal strain for shape memory in polymer additive manufacturing

Shape transformation upon annealing of fused filament fabrication additively manufacturing structures is investigated as a one-way shape memory strategy using commodity thermoplastics. Irreversible thermal strain, which is a measurement of shape transformation upon annealing, is shown to depend on both raster angle and layer thickness, both of which are parameters than can be easily adjusted on most FFF printers. We present an algorithm based on our understanding of the underlying micromechanics of the system that allows for input of desired final dimensions and output the necessary print parameters. We also demonstrate that this approach is extensible to other materials and report more complex shape memory geometries. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48239.     

Investigation of nanosized alumina-binder feedstock rheology for ceramics injection molding (CIM) and survey spark plasma sintering of output green body to obtain transparent alumina

The purpose of this work is to optimize the feed containing alumina-binder nanoparticles for ceramics injection molding to create transparent alumina parts. In this research, two Alumina with and without MgO as sintering aid fabricated via the spark plasma sintering method. Feed fluidity, fracture toughness, density, IR, and visible transmission of SPSed bodies of the sintered pieces were measured. Furthermore, a pin on the disc test was used on the disk to examine the alumina friction coefficient. The results of feed rheology showed that the sample prepared at 90°C had the best conditions as a pseudoplastic fluid for the ceramic injection molding (CIM) method. The results showed that a combination of CIM and spark plasma sintering (SPS) methods cause more visible transmission than conventional SPS of alumina nanopowder. Also, the fracture toughness and hardness of as-obtained transparent alumina were in the range of 3.6 MPa m^0.5 and 20.1 MPa, respectively. The wear rate of the as-obtained transparent sample (4.5 × 10⁻⁷ mm³/N m) was proportional to the alumina grain size (1–4 μm).     

siRNA nanotherapeutics: a promising strategy for anti‐HBV therapy

Chronic hepatitis B (CHB) is the most common cause of hepatocellular carcinoma (HCC) and liver cirrhosis worldwide. In spite of the numerous advances in the treatment of CHB, drugs and vaccines have failed because of many factors like complexity, resistance, toxicity, and heavy cost. New RNA interference (RNAi)‐based technologies have developed innovative strategies to target Achilles'' heel of the several hazardous diseases involving cancer, some genetic disease, autoimmune illnesses, and viral disorders particularly hepatitis B virus (HBV) infections. Naked siRNA delivery has serious challenges including failure to cross the cell membrane, susceptibility to the enzymatic digestion, and excretion by renal filtration, which ideally can be addressed by nanoparticle‐mediated delivery systems. cccDNA formation is a significant problem in obtaining HBV infections complete cure because of strength, durability, and lack of proper immune response. Nano‐siRNA drugs have a great potential to address this problem by silencing specific genes which are involved in cccDNA formation. In this article, the authors describe siRNA nanocarrier‐mediated delivery systems as a promising new strategy for HBV infections therapy. Simultaneously, the authors completely represent the clinical trials which use these strategies for treatment of the HBV infections.Inspec keywords: tumours, drugs, genetics, cellular biophysics, RNA, nanomedicine, diseases, molecular biophysics, microorganisms, cancer, liver, nanoparticles, patient treatmentOther keywords: siRNA nanotherapeutics, anti‐HBV therapy, chronic hepatitis B, CHB, HCC, hazardous diseases, cancer, genetic disease, autoimmune illnesses, viral disorders, hepatitis B virus infections, naked siRNA delivery, cell membrane, enzymatic digestion, renal filtration, nanoparticle‐mediated delivery systems, cccDNA formation, HBV infections complete cure, nanosiRNA drugs, siRNA nanocarrier‐mediated delivery systems, HBV infections therapy, liver cirrhosis, RNA interference, immune response, hepatocellular carcinoma     

Tracking Structural Phase Transitions in Lead‐Halide Perovskites by Means of Thermal Expansion

The extraordinary properties of lead‐halide perovskite materials have spurred intense research, as they have a realistic perspective to play an important role in future photovoltaic devices. It is known that these materials undergo a number of structural phase transitions as a function of temperature that markedly alter their optical and electronic properties. The precise phase transition temperature and exact crystal structure in each phase, however, are controversially discussed in the literature. The linear thermal expansion of single crystals of APbX₃ (A = methylammonium (MA), formamidinium (FA); X = I, Br) below room temperature is measured using a high‐resolution capacitive dilatometer to determine the phase transition temperatures. For δ‐FAPbI₃, two wide regions of negative thermal expansion below 173 and 54 K, and a cascade of sharp transitions for FAPbBr₃ that have not previously been reported are uncovered. Their respective crystal phases are identified via powder X‐ray diffraction. Moreover, it is demonstrated that transport under steady‐state illumination is considerably altered at the structural phase transition in the MA compounds. The results provide advanced insights into the evolution of the crystal structure with decreasing temperature that are essential to interpret the growing interest in investigating the electronic, optical, and photonic properties of lead‐halide perovskite materials.     

Fabrication and characterization of gold nanoparticle-doped electrospun PCL/chitosan nanofibrous scaffolds for nerve tissue engineering

In the field of nerve tissue engineering, nanofibrous scaffolds could be a promising candidate when they are incorporated with electrical cues. Unique physico-chemical properties of gold nanoparticles (AuNPs) make them an appropriate component for increasing the conductivity of scaffolds to enhance the electrical signal transfer between neural cells. The aim of this study was fabrication of AuNPs-doped nanofibrous scaffolds for peripheral nerve tissue engineering. Polycaprolactone (PCL)/chitosan mixtures with different concentrations of chitosan (0.5, 1 and 1.5) were electrospun to obtain nanofibrous scaffolds. AuNPs were synthesized by the reduction of HAuCl₄ using chitosan as a reducing/stabilizing agent. A uniform distribution of AuNPs with spherical shape was achieved throughout the PCL/chitosan matrix. The UV–Vis spectrum revealed that the amount of gold ions absorbed by nanofibrous scaffolds is in direct relationship with their chitosan content. Evaluation of electrical property showed that inclusion of AuNPs significantly enhanced the conductivity of scaffolds. Finally, after 5 days of culture, biological response of Schwann cells on the AuNPs-doped scaffolds was superior to that on as-prepared scaffolds in terms of improved cell attachment and higher proliferation. It can be concluded that the prepared AuNPs-doped scaffolds can be used to promote peripheral nerve regeneration.

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Nanodiamonds for In Vivo Applications

Due to their unique optical properties, diamonds are the most valued gemstones. However, beyond the sparkle, diamonds have a number of unique properties. Their extreme hardness gives them outstanding performance as abrasives and cutting tools. Similar to many materials, their nanometer‐sized form has yet other unique properties. Nanodiamonds are very inert but still can be functionalized on the surface. Additionally, they can be made in very small sizes and a narrow size distribution. Nanodiamonds can also host very stable fluorescent defects. Since they are protected in the crystal lattice, they never bleach. These defects can also be utilized for nanoscale sensing since they change their optical properties, for example, based on temperature or magnetic fields in their surroundings. In this Review, in vivo applications are focused upon. To this end, how different diamond materials are made and how this affects their properties are discussed first. Next, in vivo biocompatibility studies are reviewed. Finally, the reader is introduced to in vivo applications of diamonds. These include drug delivery, aiding radiology, labeling, and use in cosmetics. The field is critically reviewed and a perspective on future developments is provided.     

Multi-criteria evolutionary optimization of a traffic light using genetics algorithm and teaching-learning based optimization

Today, the development of urbanization and increasing the number of vehicles has resulted in displeased consequences like traffic congestion and vehicle queuing. The vast majority of countries in the world encounter the challenge of the explosive rise in traffic demand. In this regard, it is necessary to meet traffic demand in transport networks, especially in metropolitans. In traffic management and shortening the trip duration, traffic lights on the signalized intersections play an essential role in urban pathways. This work provides a multi-criteria decision-making method for optimum traffic light control in an isolated corner. The main idea involves establishing a set of sub-optimal solutions for traffic light timing and selecting the best one among the diverse solutions. We have mathematically modelled the problem as an optimization problem to achieve an optimal solution with less waiting time for vehicles in intersections and the lowest cost. Genetic algorithm (GA) and Teaching-Learning-based Optimization (TLBO) are utilized for each phase to create a set of suitable timing scenarios. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to identify the best scenario, considering both waiting vehicles and traffic capacity as decision criteria. Its efficiency has been demonstrated over three different traffic volumes. Also, in a real-world implementation, its practical capability has been approved at a crossroads in Mashhad, Iran. The simulations indicate the improvement in the number of vehicles waiting behind the crossroad and the traffic capacity by 10% and 6.76% compared to the existing signal timing of the studied intersection, respectively.