Optimal Biocompatible Solvent Design by Mixed-integer Hybrid Differential Evolution

In this study, a flexible optimization approach is introduced to design an optimal biocompatible solvent for an extractive fermentation process with cell-recycling. The optimal process/solvent design problem is formulated as a mixed-integer nonlinear programming model in which performance requirements of the compounds are reflected in the objectives and the constraints. A flexible or fuzzy optimization approach is applied to soften the rigid requirement for maximization of the production rate, extraction efficiency and to consider the solvent utilization rate as the softened inequality constraint to the process/solvent design problem. Such a trade-off problem is then converted to the goal attainment problem, which is described as the constrained mixed-integer nonlinear programming (MINLP) problem. Mixed-integer hybrid differential evolution with multiplier updating method is introduced to solve the constrained MINLP problem. The adaptive penalty updating scheme is more efficient to achieve a global design

Modeling User Equilibrium in Microscopic Transportation Simulation

User equilibrium refers to the network-wide state where individual travelers cannot gain improvement by unilaterally changing their behaviors. The Wardropian Equilibrium has been the focus of a transportation equilibrium study. This paper modifies the dynamic traffic assignment method through utilizing the TRANSIMS system to reach the dynamic user equilibrium state in a microscopic model. The focus of research is developing three heuristics in a Routing-Microsimulation-Equilibrating order for reaching system-wide equilibrium while simultaneously minimizing the computing burden and execution. The heuristics are implemented to a TRANSIMS model to simulate a subarea of Houston, TX

Structured Meta-Mirrors for Beam Spatial Filtering

The work presents optical spatial filtering in reflection based on translationally invariant meta-mirrors. The meta-structure is generated by a thin grating presenting a transverse modulation of the refraction index on the sub-micron scale located in front of a mirror. We analyze the angular spectrum of the reflected waves for different types of structured meta-mirrors as well as the filtering effects of these meta-structures in reflected beams. The comparison between FDTD simulations of full Maxwell equations and different approximated models allows to determine the filtering contribution from the structured cavity and from Mie resonances associated to elements generating the grating.Peer ReviewedPostprint (author's final draft

Leveling Maintenance Mechanism by Using the Fabry-Perot Interferometer with Machine Learning Technology

This study proposes a method for maintaining parallelism of the optical cavity of a laser interferometer using machine learning. The Fabry-Perot interferometer is utilized as an experimental optical structure in this research due to its advantage of having a brief optical structure. The supervised machine learning method is used to train algorithms to accurately classify and predict the tilt angle of the plane mirror using labeled interference images. Based on the predicted results, stepper motors are fixed on a plane mirror that can automatically adjust the pitch and yaw angles. According to the experimental results, the average correction error and standard deviation in 17-grid classification experiment are 32.38 and 11.21 arcseconds, respectively. In 25-grid classification experiment, the average correction error and standard deviation are 19.44 and 7.86 arcseconds, respectively. The results show that this parallelism maintenance technology has essential for the semiconductor industry and precision positioning technology

Team Quotients, Resilience, and Performance of Software Development Projects

Past studies have examined actions and strategies that software project teams can take to reduce the negative impact of uncertainties, such as changing requirements. Software development project teams often have to be flexible to follow the pre-defined plans and strive to meet project goals. Sometimes uncertainty may go extreme to temporarily slow projects down and set project teams into reduced productivity. Project teams should be resilient to recover from the reduce productivity condition and move forward toward predefined goals. This study focuses on understanding the importance of team resilience for software project teams and exploring the antecedents of team resilience. Specifically, we investigate the impacts of intelligence and emotional quotient on team resilience capability, the extent to which project team can recover from the impediment and move forward. This is a research-in-progress work. A future empirical test plan has been discussed at the end

Gate-induced insulator to band-like transport transition in organolead halide perovskite

Understanding the intrinsic charge transport in organolead halide perovskites is essential for the development of high-efficiency photovoltaics and other optoelectronic devices. Despite the rapid advancement of the organolead halide perovskite in photovoltaic and optoelectronic applications, the intrinsic charge carrier transport in these materials remains elusive partly due to the difficulty of fabricating electrical devices and obtaining good electrical contact. Here, we report the fabrication of organolead halide perovskite microplates with monolayer graphene as low barrier electrical contact. A systematic charge transport studies reveal an insulator to band-like transport transition. Our studies indicate that the insulator to band-like transport transition depends on the orthorhombic-to-tetragonal phase transition temperature and defect densities of the organolead halide perovskite microplates. Our findings are not only important for the fundamental understanding of charge transport behavior but also offer valuable practical implications for photovoltaics and optoelectronic applications based on the organolead halide perovskite.Comment: 18 pages, 5 figure

Age as a predisposing factor of respiratory alkalosis in accidental carbon monoxide poisoning

AbstractAimsThe purpose of this study was to determine the frequency of and identify the predisposing factors for respiratory alkalosis in patients with accidental carbon monoxide (CO) poisoning.MethodsPatients presenting to the emergency department with accidental CO poisoning were retrospectively identified and divided into Group A (no respiratory alkalosis) and Group B (respiratory alkalosis). Charts were reviewed for neurologic status, various demographic factors, and laboratory data.ResultsA total 96 patients, 37 (38.5%) men and 59 (61.5%) women, were identified. Of these, the 58 (60.4%) patients without respiratory alkalosis were placed in Group A and the 38 (39.6%) patients with respiratory alkalosis were placed in Group B. Independent multivariate predictors of CO poisoning presenting with respiratory alkalosis were age [odds ratio (OR), 1.04; 95% confidence interval (CI), 1.01–1.08] and respiratory rate (OR, 1.16; 95% CI, 1.01–1.33). The rates of respiratory alkalosis in patients younger than 15 years, 15–29 years, 30–44 years, 45–59 years, and older than 59 years were 17.4%, 32.4%, 51.9%, 75%, and 75%, respectively (p<0.01).ConclusionsRespiratory alkalosis in the patients with CO poisoning is not an uncommon finding, and as age increases, the percentage becomes higher. When emergency physicians are faced with patients presenting with respiratory alkalosis of undetermined cause, CO poisoning should be taken into consideration, especially in the elderly