Dynamic Ride-Matching for Large-Scale Transportation Systems

Efficient dynamic ride-matching (DRM) in large-scale transportation systems is a key driver in transport simulations to yield answers to challenging problems. Although the DRM problem is simple to solve, it quickly becomes a computationally challenging problem in large-scale transportation system simulations. Therefore, this study thoroughly examines the DRM problem dynamics and proposes an optimization-based solution framework to solve the problem efficiently. To benefit from parallel computing and reduce computational times, the problem’s network is divided into clusters utilizing a commonly used unsupervised machine learning algorithm along with a linear programming model. Then, these sub-problems are solved using another linear program to finalize the ride-matching. At the clustering level, the framework allows users adjusting cluster sizes to balance the trade-off between the computational time savings and the solution quality deviation. A case study in the Chicago Metropolitan Area, U.S., illustrates that the framework can reduce the average computational time by 58% at the cost of increasing the average pick up time by 26% compared with a system optimum, that is, non-clustered, approach. Another case study in a relatively small city, Bloomington, Illinois, U.S., shows that the framework provides quite similar results to the system-optimum approach in approximately 62% less computational time.

A Bayesian-based framework for advanced nature-based tourism model

PurposeNature-based tourism (NBT) blossoming requires sound monitoring models to maximize its potential in the tourism industry. Cooperation of different segments from nature to economy will lead to a sustainable NBT. Therefore, the qualitative and quantitative relation between these subdivisions has to be investigated.Design/methodology/approachThis paper proposes an advanced NBT model for the design of an optimum tourism system. To this end, Bayesian network (BN) has been implemented to characterize the impact of each subsector on NBT.FindingsThe outcomes of this study can help the tourism managers, policymakers and related organizations to find the optimum approach to achieve a continuous improvement in the system. To demonstrate the applicability of the methodology, two cases of observations are considered.Originality/valueThe originality of the work is well demonstrated in the literature review of the paper.

Groundwater Single- and Multiobjective Optimization Using Harris Hawks and Multiobjective Billiards-Inspired Algorithm

This is the first attempt to combine the Multiobjective Billiards-Inspired Optimization Algorithm (MOBOA) with groundwater modelling to determine pumping rates within a well-distributed range of Pareto options. In this study, in order to determine an optimum solution for groundwater drawdown, pumping rates were selected accompanied by three minimization objectives: minimizing shortage influenced by inability to supply, adjusted shortage index, and minimizing the degree of drawdown within predefined areas. To optimize hydraulic conductivity and specific yield parameters of a modular three-dimensional finite-difference (MODFLOW) groundwater model, the Harris Hawks optimization algorithm was used to minimize the sum of absolute deviation between observed and simulated water-table levels. MOBOA was then utilized to optimize pumping rate variables for an Iranian arid to semiarid groundwater environment using these parameters. As the study results, when the maximum and minimum aquifer drawdown was specified in the range of −40 to +40 cm/year, the Pareto parameter sets produced satisfactory results. Overall, the “Simulation-Optimization-Modelling” protocol was able to generate a series of optimal solutions that were shown on a Pareto front. The study concluded to an optimum approach that provides policy makers in the Iranian water stressed zones with safe groundwater management alternatives.

Global genomic pathogen surveillance to inform vaccine strategies: a decade-long expedition in pneumococcal genomics

Vaccines are powerful agents in infectious disease prevention but often designed to protect against some strains that are most likely to spread and cause diseases. Most vaccines do not succeed in eradicating the pathogen and thus allow the potential emergence of vaccine evading strains. As with most evolutionary processes, being able to capture all variations across the entire genome gives us the best chance of monitoring and understanding the processes of vaccine evasion. Genomics is being widely adopted as the optimum approach for pathogen surveillance with the potential for early and precise identification of high-risk strains. Given sufficient longitudinal data, genomics also has the potential to forecast the emergence of such strains enabling immediate or pre-emptive intervention. In this review, we consider the strengths and challenges for pathogen genomic surveillance using the experience of the Global Pneumococcal Sequencing (GPS) project as an early example. We highlight the multifaceted nature of genome data and recent advances in genome-based tools to extract useful information relevant to inform vaccine strategies and treatment options. We conclude with future perspectives for genomic pathogen surveillance.

Excellent Mechanical Properties of the Silicate Glasses Modified by CeO2 and TiO2: A New Choice for High-Strength and High-Modulus Glass Fibers

As is well known, silicate glass has a stable glass-forming region and mature drawing processes into fibers. In this study, to obtain enhanced mechanical properties, glasses with a composition of SiO2-Al2O3-MgO-CaO-B2O3-Fe2O3 were synthesized using TiO2 and CeO2. When the amount of TiO2 and CeO2 is less than 2 wt%, the mechanical properties increase with increases in the TiO2 and CeO2. However, as the amount of TiO2 and CeO2 increases from 2 to 3.5 wt%, the mechanical properties decrease. Co-doping with 1 wt% TiO2 and 1 wt% CeO2 was found to be the optimum approach, with a density, bending strength, compression strength, and compression modulus of 2.626 g/cm3, 108.36 MPa, 240.18 MPa, and 115.03 GPa, respectively. The optical band gap and Raman spectroscopy proved that, as long as the content of oxygen bonds reaches the maximum level, a kind of best structural stability and mechanical properties will be achieved. Hence, this type of high-strength silicate glass can be used in optical fibers for military defense, wind power generation, and transportation.

Therapeutic Approaches for COVID-19 Based on the Interferon-mediated Immune Responses

Background: As the outbreak of COVID-19 has accelerated, an urgent need for finding strategies to combat the virus is growing. Thus, gaining more knowledge on the pathogenicity mechanism of SARS-CoV-2, the causing agent of COVID-19, and its interaction with the immune system is of utmost importance. Although this novel virus is not well known yet, its structural and genetic similarity with SARS-CoV as well as the comparable pattern of age-mortality relations suggest that some previous findings on SARS could be applicable for COVID-19. Objective: The aim of this study was to investigate the most important signaling pathways activated by coronaviruses to better understand the viral pathogenesis and host immune responses. Method: Here, a systems biology study was conducted on a SARS database. It was followed by a literature review on the cognate subject. Results: It was proved that interferons may possess a crucial role in the defense against coronavirus diseases. The literature supported the validity of the employed approach and the notion that interferon induction could play a key role in the body defense against coronavirus infections. Conclusion: Altogether, administration of interferons or interferon-inducing agents in a prophylactic manner or at early stages of the disease, could mimic the effective antiviral responses against SARS-CoV-2 and reduce the disease severity. At later stages of the disease, however, the balance of the immune reactions would be disrupted and the responses would shift toward immunopathogenic over-reactions, which could be exacerbated by interferon usage. Moderating the activity of the immune system by anti-inflammatory agents, might be the optimum approach in such conditions.

A Study on the Numerical Performances of Diffuse Interface Methods for Simulation of Melting and Their Practical Consequences

This work is the final one in a series of three papers devoted to shedding light on the performance of fixed grid methods, also known as enthalpy methods, for the modeling and the simulation of solid/liquid phase transition. After a detailed analysis of five of the most common enthalpy methods for conductive-dominated and conductive-convective problems and then a study concerning the formulation of the advective term in the energy balance equation, the aim of the present paper is to extend the above-mentioned studies by an investigation of the numerical performance. Such a goal is achieved by comparing the required iterations and, even if it is shown to be only a rough guide, the simulation time of each method, for a great variety of parameter variations. In terms of contribution, the main conclusions of this overall work are to demonstrate that almost all solvers give similar results when stable. However, there are still distinctive deviations with the experiments, highlighting the need for a proper validation experiment. The second important assessment concerns resilience: almost all solvers work well, with only the applied apparent heat capacity method being the major exception as it often leads to unrealistic results. As a rule of thumb, models are more resilient when only the sensible enthalpy is advected. As far as the average of the required iterations is concerned, the so-called optimum approach needs the least. The order of the other solvers depends on the advective formulation, whereas source-based methods perform averagely and the tested apparent heat capacity method poorly. Cases with only sensible enthalpy advected need fewer iterations for four of the five solvers and less computational time for all solvers.

Theoretical study of the band structure of 2H-SiC and 4H-SiC of silicon carbide polytypes

We have studied the electronic band properties of 2H-SiC and 4H-SiC silicon carbide polytypes. The structures of the electronic bands and density of state (DOS) using ab initio Density Functional Theory (DFT) were calculated for the first Brillouin zone both in the generalized gradient approximation and taking into account quasiparticle effects according to the GW scheme. The calculated bandgaps obtained using the GW approximation Eg2H-SiC = 3.17 eV and Eg4H-SiC = 3.26 eV agree well with experimental values. The shape and values of total DOS are within agreement with calculations performed by other authors. The calculated total energy values for 2H-SiC and 4H-SiC were close, but they satisfy the condition E2H > E4H, which implies that the 4H-SiC structure is more stable than 2H-SiC. Our calculations of the band structure and DOS of 2H-SiC and 4H-SiC by the DFT method showed that the application of the GW approximation is an optimum approach to the study of the electronic structure of 2H-SiC and 4H-SiC polytypes.