Multi-Objective Message Routing in Electric and Flying Vehicles Using a Genetics Algorithm.

With progressive technological advancements, the time for electric vehicles (EVs) and unmanned aerial vehicles (UAVs) has finally arrived for the masses. However, intelligent transportation systems need to develop appropriate protocols that enable swift predictive communication among these battery-powered devices. In this paper, we highlight the challenges in message routing in a unified paradigm of electric and flying vehicles (EnFVs). We innovate over the existing routing scheme by considering multi-objective EnFVs message routing using a novel modified genetics algorithm. The proposed scheme identifies all possible solutions, outlines the Pareto-front, and considers the optimal solution for the best route. Moreover, the reliability, data rate, and residual energy of vehicles are considered to achieve high communication gains. An exhaustive evaluation of the proposed and three existing schemes using a New York City real geographical trace shows that the proposed scheme outperforms existing solutions and achieves a 90%+ packet delivery ratio, longer connectivity time, shortest average hop distance, and efficient energy consumption.

Boosting cuckoo optimization algorithm via Gaussian mixture model for optimal power flow problem in a hybrid power system with solar and wind renewable energies.

This paper presents a novel approach, the Gaussian Mixture Method-enhanced Cuckoo Optimization Algorithm (GMMCOA), designed to optimize power flow decision parameters, with a specific focus on minimizing fuel cost, emissions, network loss, and voltage deviation. GMMCOA integrates the strengths of COA and GMM while mitigating their individual limitations. While COA offers robust search capabilities, it suffers from initial parameter dependency and the risk of getting trapped in local optima. Conversely, GMM delivers high-speed performance but requires guidance to identify the best solution. By combining these methods, GMMCOA achieves an intelligent approach characterized by reduced parameter dependence and enhanced convergence speed. The effectiveness of GMMCOA is demonstrated through extensive testing on both the IEEE 30-bus and the large-scale 118-bus test systems. Notably, for the 118-bus test system, GMMCOA achieved a minimum cost of $129,534.7529 per hour and $103,382.9225 per hour in cases with and without the consideration of renewable energies, respectively, surpassing outcomes produced by alternative algorithms. Furthermore, the proposed method is benchmarked against the CEC 2017 test functions. Comparative analysis with state-of-the-art algorithms, under consistent conditions, highlights the superior performance of GMMCOA across various optimization functions. Remarkably, GMMCOA consistently outperforms its competitors, as evidenced by simulation results and Friedman examination outcomes. With its remarkable performance across diverse functions, GMMCOA emerges as the preferred choice for solving optimization problems, emphasizing its potential for real-world applications.

Routine extensive dissection of the cystic duct during laparoscopic cholecystectomy to reduce the risk of residual choledocholithiasis: an unnecessary step and a potentially hazardous concept.

Introduction: Post-cholecystectomy choledocholithiasis can occur from retained stones at the cystic duct stump remnant; however, most surgeons would not proceed with extensive dissection of the cystic duct during routine cholecystectomy, mainly in fear of inadvertent bile duct injuries, given the frequent anatomical variations of the extrahepatic biliary tree. Aim: To determine the need and feasibility of extensive dissection of the cystic duct during laparoscopic cholecystectomy, to reduce the risk of post-cholecystectomy choledocholithiasis. Material and methods: We performed a retrospective review of our institutional database of all patients who had magnetic resonance cholangiopancreatography (MRCP) prior to cholecystectomy over a 3-year period (03/2016-04/2019), assessing the anatomical variations of the cystic duct and the incidence of cystic duct stones. Results: During the study period, from a total of 763 patients who underwent cholecystectomy for symptomatic gallstones, 284 had undergone pre-operative MRCP and were all included in the final analysis. The typical right lateral insertion of the cystic duct in the midpoint between the confluence of the main hepatic ducts and the ampulla of Vater was identified in less than 50% of the patients. In our series, cystic duct stones were present only in 1.8% of our patients. Conclusions: The presence of significant anatomical variations and the low likelihood of incidental cystic duct stones render prophylactic extensive dissection of the cystic duct during standard laparoscopic cholecystectomy a rather unnecessary and probably hazardous step.

An accurate model of polyglutamine.

Polyglutamine repeats in proteins are highly correlated with amyloid formation and neurological disease. To better understand the molecular basis of glutamine repeat diseases, structural analysis of polyglutamine peptides as soluble monomers, oligomers, and insoluble amyloid fibrils is necessary. In this study, fluorescence resonance energy transfer (FRET) experiments and molecular dynamics simulations using different theoretical models of polyglutamine were conducted. This study demonstrates that a previously proposed simple C(α)C(ß) model of polyglutamine, denoted as FCO, accurately reproduced the present FRET results and the results of previously published FRET, triplet-state quenching, and fluorescence correlation studies. Other simple C(α)C(ß) models with random coil and extended ß-strand parameters, and all-atom models with parm96 and parm99SB force fields, did not match the FRET result well. The FCO is an intrinsically disordered model with a high-effective persistence length producing extended peptides at short lengths (Q(N) < 10). Because of an increasing number of attractive Q-Q interactions at longer lengths, the FCO model becomes increasingly more compact at lengths between Q(N) ∼ 10-16 and is as compact as many folded proteins at Q(N) > 16.

Single-centre experience of emergency hernia surgery during COVID-19 pandemic: a comparative study of the operative activity and outcomes before and after the outbreak.

Aim The outbreak of COVID-19 pandemic in January 2020 affected largely the elective operating for non-urgent surgical pathologies, such as hernias, due to periodical cancellations of the operating lists on a worldwide scale. To the best of our knowledge, the long-term impact of the COVID-19 pandemic in relation to the emergency hernia surgery operative workload and postoperative outcomes remains largely unknown. Methods Retrospective research of admission, operation and inpatient records of all patients who underwent emergency surgery over a 2-year period (2019-2020) was done. Results An 18% increase in terms of emergency hernia surgery operating volume, with a 23% increase of visceral resections due to unsalvageable herniated content strangulation was found. Overall morbidity did not increase during the pandemic period and there was no postoperative mortality or occurrence of COVID-19 related complications. Conclusion Emergency operative management of acutely symptomatic hernias can be safely performed even during the COVID-19 infection peak waves; hernia taxis should be reserved only for patients unfit or unwilling to undergo upfront surgery.

Robust quadratic stabilization applied to design of continuous-time and discrete-time observers.

In this paper, an application of a robust quadratic stabilization algorithm (RQSA) to continuous-time and discrete-time observers is presented. The RQSA is based on checking end points of a bounding hyperpolyhedron. The RQSA applied to observers is introduced, and implemented for a simplified car model, in both continuous-time and discrete-time case. The paper concludes that the RQSA is feasible to estimate unavailable states, even though there are structured uncertainties in the system matrix and in the measurement matrix.

Parameter estimation from experimental laboratory data of HSV-1 by using alternative regression method.

In this paper, an estimation of model parameters is performed by using the Alternative Regression (AR) approach on an experimental data set of Herpes Simplex Virus type-1 (HSV-1) infection with innate immune response. Throughout the specified course of time, the measurements of monocytes, neutrophils, and viral load were obtained from the corneas of infected mice. C57BL/6 (B6) mice were used at Oakland University, Department of Biological Sciences, and the outcome measurements were divided into training and testing data sets. The HSV-1 nonlinear dynamic model is proposed based on the observed data patterns and biological system information. The simulation results of the proposed model showed that they consistently fit the experimental data set. In addition, the sensitivity test and model validation diagnostics are considered to determine the most significant key parameters that affect the dynamics of the HSV-1 system.