Hybrid Evolutionary Metaheuristics for Concurrent Multi-Objective Design of Urban Road and Public Transit Networks

This paper addresses a bi-modal multi-objective discrete urban road network design problem with automobile and bus flow interaction. The problem considers the concurrent urban road and bus network design in which the authorities play a major role in designing bus network topology. The road network design deals with the decision making for new street constructions, lane additions to existing streets, lane allocations for two-way streets, and the orientations and locations of one-way streets. The bus network design is performed by keeping the terminal stations of the existing bus lines unchanged and redesigning the forth and back routes of each line. Four measures, namely user benefit, the demand coverage of the bus network, the demand share of the bus mode, and the average travel generalized cost of bus passengers, are used to evaluate the network design scenarios. The problem is formulated as a multi-objective optimization model in which a modal-split/assignment model is included to depict the mode and route choice behaviors of travelers. The model is solved by the hybrid genetic algorithm and the hybrid clonal selection algorithm. The performance of these algorithms is presented and investigated by solving a number of test networks.     

Extraction of inulin from Burdock root (Arctium lappa) using high intensity ultrasound

Burdock root could be a source of inulin, but scarce studies about its extraction exist. To optimise conventional and ultrasound‐assisted extraction of inulin, various combinations were used. The independent variables for ultrasound extraction were sonication amplitude (20–100%), sonication temperature (20–60 °C) and sonication time (5–25 min) while for conventional extraction the following variables were water to solid ratio (5–15 v/w), temperature (40–90 °C) and time (5–40 min). For each response, a second‐order polynomial model was developed using multiple linear regression analysis. The use of high intensity ultrasound significantly improves the extraction of inulin contained within the body of Burdock root. It was shown that increasing the amplitude (from 20% to 85%) and extraction time increased the extraction yield; however, the effect of temperature was minor. Optimum extraction condition was found to be sonication time: 25 min, sonication amplitude 83.22% and temperature: 36.76 °C.     

Antimicrobial and anti‐biofilm activities of Bi subnitrate and BiNPs produced by Delftia sp. SFG against clinical isolates of Staphylococcus aureus,Pseudomonas aeruginosa,and Proteus mirabilis

In the present study Delftia sp. Shakibaie, Forootanfar, and Ghazanfari (SFG), was applied for preparation of biogenic Bi nanoparticles (BiNPs) and antibacterial and anti‐biofilm activities of the purified BiNPs were investigated by microdilution and disc diffusion methods. Transmission electron micrographs showed that the produced nanostructures were spherical with a size range of 40–120 nm. The measured minimum inhibitory concentration of both the Bi subnitrate and BiNPs against three biofilms producing bacterial pathogens of Staphylococcus aureus, Pseudomonas aeruginosa, and Proteus mirabilis were found to be above 1280 µg/ml. Addition of BiNPs (1000 µg/disc) to antibiotic discs containing tobramycin, nalidixic acid, ceftriaxone, bacitracin, cefalexin, amoxicillin, and cefixime significantly increased the antibacterial effects against methicillin‐resistant S. aureus (MRSA) in comparison with Bi subnitrate (p  < 0.05). Furthermore, the biogenic BiNPs decreased the biofilm formation of S. aureus, P. aeruginosa, and P. mirabilis to 55, 85, and 15%, respectively. In comparison to Bi subnitrate, BiNPs indicated significant anti‐biofilm activity against P. aeruginosa (p  < 0.05) while the anti‐biofilm activity of BiNPs against S. aureus and P. mirabilis was similar to that of Bi subnitrate. To sum up, the attained results showed that combination of biogenic BiNPs with commonly used antibiotics relatively enhanced their antibacterial effects against MRSA.Inspec keywords: nanoparticles, bismuth, nanofabrication, antibacterial activity, microorganisms, biomedical materials, toxicology, nanomedicine, transmission electron microscopy, biochemistry, drugsOther keywords: Bi, size 40.0 nm to 120.0 nm, mass 1000.0 mug, Delftia sp. SFG, Staphylococcus aureus, antibiofilm mechanisms, antibiofilm effect, antibiofilm activity, Proteus mirabilis, Pseudomonas aeruginosa, purified biogenic BiNPs, antibacterial biofilm mechanisms, Bi subnitrate, antibacterial effects     

Peanut and cardiovascular disease risk factors: A systematic review and meta-analysis

Abstract

Several studies have been conducted on the effects of peanut consumption on cardiovascular diseases (CVD) risk factors. However, the findings are conflicting and appear inconsistent. The aim of this review is to summarize the findings on the effect of peanut consumption on the risk factors of CVDs. We used relevant keywords and searched through PubMed, Scopus and Web of Science for articles published studies up to November 2018. Randomized controlled trials (RCTs) were included in this meta-analysis. Random or fixed-effects meta-analysis method depending on the results of heterogeneity tests was used to estimate the effect size. Between-study heterogeneity was assessed by Q test and I² index. Subgroup analysis was conducted to find any excess relationship. Publication bias was checked by Egger’s test and funnel plot. Quality of studies was assessed by the Cochrane criteria. According to the results of 13 RCTs, peanuts has no significant effect on weight (WMD: ?0.11?kg, P?=?0.773), waist circumference (WMD: ?1.41?cm, P?=?0.139), body mass index (WMD: ?0.14?kg/m², P?=?0.428), systolic and diastolic blood pressure (WMD: ?0.09?mmHg, P?=?0.939 and WMD: 0.60?mmHg, P?=?0.652, respectively), low-density lipoprotein cholesterol (WMD: ?3.31?mg/dl, P?=?0.472), triglyceride (WMD: ?7.59?mg/dl, P?=?0.180), total cholesterol (WMD: 3.15?mg/dl, P?=?0.171), fasting blood sugar (WMD: 0.57?mg/dl, P?=?0.604) and serum insulin (WMD: ?0.40, P?=?0.582). Also, this meta-analysis showed that peanut had a positive significant effect on high-density lipoprotein cholesterol (HDL) (WMD: 2.72?mg/dl, P?=?0.001). Peanuts consumption has a positive significant effect on HDL especially at the type of peanut oil, high-oleic peanut and peanut sprout and in healthy subjects and for consumption more than 12?weeks, while has no significant effect on other CVD risk factors.     

Analytical investigation of superior gas sensor based on phosphorene

Microsystem Technologies - The recent discovery of phosphorene, a 2D allotrope of semiconducting black phosphorus has aroused significant interest for future electronic device applications....     

Combination of neural network and wavelet transform for islanding detection of distributed generation in a small-scale network

In this paper, an optimum and intelligent method is proposed for islanding detection using wavelet transform. The suggested relay is based on neural network (NN) in which different heuristic algorithms are used for training the NN. In the proposed method, the appropriate signals for detection procedure as well as mother wavelet are selected optimally, based on the mean square error (MSE) concept. Lately, the desired relay is trained by the optimally selected signals using four different algorithms and the optimum condition of the fault detector is identified. Simulation results approved that non detection zone (NDZ) has a significant reduction utilising the proposed intelligent technique. The contributions of the proposed method include presenting an appropriate signal selection method based on MSE, selecting optimum number of relay input signals using the proposed technique, fast training of intelligent relay by using least information, solving threshold selection problem and reduction of NDZ approximately to zero.     

Probabilistic and Multi-Objective Placement of D-STATCOM in Distribution Systems Considering Load Uncertainty

Advanced technologies such as distribution static compensator (D-STATCOM) are broadly deployed in distribution systems (DSs) to tackle different issues. Successful deployment of such technologies requires their adaption to stochastic nature of DS. This paper proposes a new method for allocation of D-STATCOM in DSs considering load uncertainty. Monte Carlo simulation (MCS) technique is utilized to cope with uncertain attribute of loads. To do so, output of MCS is considered as a deterministic case which is solved by backward-forward sweep power flow approach. The objective functions of the proposed model include total voltage deviation, total active losses, and voltage stability metrics. These metrics are combined in a multi-objective optimization formulation and solved by non-dominated sorting genetic algorithm-II (NSGA-II). Lastly, the best compromise solution is determined by Pareto front technique taking advantage of fuzzy decision making (FDM) engine. Comprehensive simulation studies are carried out on IEEE 33-bus standard distribution system as well as on Portuguese 94-bus real-world distribution system. Simulation studies confirm the accuracy of the proposed method in determining proper location of D-STATCOM in DSs by fulfilling the objectives.     

Effect of the spin-line temperature profile on the mechanical properties of melt electrospun polyethylene fibers

The covid-19 pandemic has revealed the need for alternative production approaches with low startup costs like electrospinning for filter needs, the most imperative element of the personal protective equipment (PPE). Current attempts in advancing melt electrospinning deal with developing strategies for fiber diameter attenuation toward sub-micron scale. Here, the attunement in the spinning-zone temperature known as ''spin-line temperature profile'' was utilized as a baseline for fiber diameter reduction. The mechanical performance of the melt-electrospun linear low-density polyethylene (LLDPE) fibers is reported to characterize their structural transformation with respect to various spin-line temperature profiles. With an increase in the spin-line temperature to above 100°C in the area of cone formation, an increased tensile and yield strength along with fiber diameter reduction by four-folds was demonstrated. A significant increase in toughness, by almost three times, without compromising the stiffness and Young's modulus was observed. The dynamic mechanical analysis revealed that spinning in high temperatures produces changes in the alpha (α) relaxation, contributing to the significant increase in strain at break. These results are significant because polyolefin fibers are an imperative element of medical textiles and PPE. Therefore, developing a correlation for process-structure-properties for emerging production techniques like melt electrospinning becomes critical.