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An algorithm for a family of self-starting high-order implicit time integration schemes with controllable numerical dissipation is proposed for both linear and nonlinear transient problems. This work builds on the previous works of the authors on elastodynamics by presenting a new algorithm that eliminates the need for factorization of the mass matrix providing benefit for the solution of nonlinear problems. The improved algorithm directly obtains the acceleration at the same order of accuracy of the displacement and velocity using vector operations (without additional equation solutions). The nonlinearity is handled by numerical integration within a time step to achieve the desired order of accuracy. The new algorithm fully retains the desirable features of the previous works: 1. The order of accuracy is not affected by the presence of external forces and physical damping; 2. numerical dissipation in the algorithm is controlled by a user-specified parameter, leading to schemes ranging from perfectly nondissipative A-stable to L-stable; 3. The effective stiffness matrix is a linear combination of the mass, damping, and stiffness matrices as in the trapezoidal rule. The proposed algorithm is shown to replicate the numerical results demonstrated on linear problems in previous works. Additional numerical examples of linear and nonlinear vibration and wave propagation are presented herein. Notably, the proposed algorithms show the same convergence rates for nonlinear problems as linear problems, and very high accuracy. Second-order time integration methods commonly used in commercial software produce significantly polluted acceleration responses for a common class of wave propagation problems. The high-order time integration schemes presented here perform noticably better at suppressing spurious high-frequency oscillations and producing reliable and useable acceleration responses., Comment: 50 pages, 31 figures, 93 equations. Source code available at https://github.com/ChongminSong/HighOrderTimeIngt_PartialFraction.git

Bus electrification accelerates the transition towards sustainable urban transportation. Battery-Electric Buses (BEBs) often require periodic recharging intervals between service trips. The strategic placement and allocation of charging equipment are crucial in facilitating operations, optimizing costs, and minimizing downtime. In this study, we develop an optimization framework to address the optimal placement of various charger types at candidate locations under the stochastic charging demand of BEBs. The framework aims to minimize long-term system costs while balancing considerations among station, charger, and value of time expenses. Leveraging existing stochastic location literature, we develop a mixed-integer non-linear program (MINLP) to model the problem. We design an exact solution method to address this computationally challenging problem. The program optimizes the generalized costs associated with building charging stations, allocating charger types, traveling to charging stations, and average queueing and charging times. Queueing dynamics are modeled using an M/M/s queue, with the number of servers as a decision variable at each candidate location and each charger type. The linearization process, which excludes queueing variables, is succeeded by introducing associated constraints through cutting planes. This step guarantees global optimality due to the convexity properties of the problem. To enhance scalability, we implement a genetic algorithm and a simulated annealing metaheuristic and devise heuristic clustering strategies, facilitating the effective resolution of real-world, large-scale instances. Then, we conduct comparative analyses across garage-only, other-only, and mixed-location scenarios.

Evaporation of blood droplets and diluted blood samples is a topic of intensive research, as it is seen as a possible low-cost tool for diagnosis. So far, samples with volume fraction down to a few percents of Red Blood Cells (RBCs) have been studied, and those were reportedly dominated by a ``coffee-ring'' deposit. In this study, samples with lower volume fractions have been used in order to study the growth of the evaporative deposit from sessile droplets more in details. We observed that blood samples and salt solutions with less than 1\% volume fraction of RBCs are dominated by a central deposit. We characterized the growth process of this central deposit by evaporating elongated drops, and determined that it is consistent with the Kardar-Parisi-Zhang process in the presence of quenched disorder. Our results showed a sensitivity of this deposit size to the fibrinogen concentration and shape of the RBCs, meaning that this parameter could be used to develop a new and cost-effective clinical marker for inflammation and RBC deformation., Comment: 27 pages, 11 Figures

The $r$-edge bootstrap percolation on a graph is an activation process of the edges. The process starts with some initially activated edges and then, in each round, any inactive edge whose one of endpoints is incident to at least $r$ active edges becomes activated. A set of initially activated edges leading to the activation of all edges is said to be a percolating set. Denote the minimum size of a percolating set in the $r$-edge bootstrap percolation process on a graph $G$ by $m_e(G, r)$. The importance of the $r$-edge bootstrap percolation relies on the fact that $m_e(G, r)$ provides bounds on $m(G, r)$, that is, the minimum size of a percolating set in the $r$-neighbor bootstrap percolation process on $G$. In this paper, we explicitly determine $m_e(K_n^d, r)$, where $K_n^d$ is the Cartesian product of $d$ copies of the complete graph on $n$ vertices which is referred as Hamming graph. Using this, we show that $m(K_n^d, r)=(1+o(1))\frac{d^{r-1}}{r!}$ when $n, r$ are fixed and $d$ goes to infinity which extends a known result on hypercubes.

Two skew Hadamard matrices are considered {\sf SH}-equivalent if they are similar by a signed permutation matrix. This paper determines the number of {\sf SH}-inequivalent skew Hadamard matrices of order $36$ for some types. We also study ternary self-dual codes and association schemes constructed from the skew Hadamard matrices of order $36$.

The adoption of electric vehicles (EVs), including electric taxis and buses, as a mode of transportation, is rapidly increasing in cities. In addition to providing economic and environmental benefits, these fleets can potentially participate in the energy arbitrage market by leveraging their mobile energy storage capabilities. This presents an opportunity for EV owners to contribute to a more sustainable and efficient energy system while also reducing their operational costs. The present study introduces deterministic and single-stage stochastic optimization frameworks that aim to maximize revenue by optimizing the charging, discharging, and travel of a fleet of electric vehicles in the context of uncertainty surrounding both spatial and temporal energy prices. The simulations are performed on a fleet of electric delivery trucks, which have to make deliveries to certain locations on specific dates. The findings indicate the promising potential of bidirectional electric vehicle charging as a mobile grid asset. However, it is important to note that significant revenue is only realized in scenarios where there is substantial variation in prices between different areas, and when these price variations can be accurately forecasted with a high level of confidence.

In this paper, we describe an experimental investigation into the effect of passivation layer thickness on heat dissipation between a quartz substrate and liquid helium. We have observed that by depositing SiN from 0 to 240 nm, the Kapitza resistance increases by 0.0365 m^2.K/W per nanometer more than for an unpassivated semiconductor. We hypothesize that this increase in Kapitza resistance represents an additional barrier to the cooling of semiconductor devices in liquid helium., Comment: 7 pages

What happens if we encounter a suitable font for our design work but do not know its name? Visual Font Recognition (VFR) systems are used to identify the font typeface in an image. These systems can assist graphic designers in identifying fonts used in images. A VFR system also aids in improving the speed and accuracy of Optical Character Recognition (OCR) systems. In this paper, we introduce the first publicly available datasets in the field of Persian font recognition and employ Convolutional Neural Networks (CNN) to address this problem. The results show that the proposed pipeline obtained 78.0% top-1 accuracy on our new datasets, 89.1% on the IDPL-PFOD dataset, and 94.5% on the KAFD dataset. Furthermore, the average time spent in the entire pipeline for one sample of our proposed datasets is 0.54 and 0.017 seconds for CPU and GPU, respectively. We conclude that CNN methods can be used to recognize Persian fonts without the need for additional pre-processing steps such as feature extraction, binarization, normalization, etc.

Cooling electronic devices to cryogenic temperatures (< 77 K) is crucial in various scientific and engineering domains. Efficient cooling involves the removal of heat generated from these devices through thermal contact with either a liquid cryogen or a dry cryostat cold stage. However, as these devices cool, thermal boundary resistance, also known as Kapitza resistance, hinders the heat flow across thermal interfaces, resulting in elevated device temperatures. In transistors, the presence of passivation layers like Silicon Nitride (SiN) introduces additional interfaces that further impede heat dissipation. This paper investigates the impact of passivation layer thickness on Kapitza resistance at the interface between a solid device and liquid nitrogen. The Kapitza resistance is measured using a capacitance thermometer that has been passivated with SiN layers ranging from 0 to 240 nm. We observe that Kapitza resistance increases with increasing passivation thickness., Comment: 6 pages, 5 Figures

This study focuses on the single depot electric vehicle scheduling problem (SDEVSP) within the broader context of the vehicle scheduling problem (VSP). By developing an effective scheduling model using mixed-integer linear programming, we generate bus blocks that accommodate electric vehicles (EVs), ensuring successful completion of each block while considering recharging requirements between blocks and during off-hours. Next day operability constraints are also incorporated, allowing for seamless repetition of blocks on subsequent days. The SDEVSP is known to be computationally complex, deriving optimal solutions unattainable for large-scale problems within reasonable timeframes. To address this, we propose a two-step solution approach: first solving the single depot VSP, and then addressing the block chaining problem (BCP) using the blocks generated in the first step. The BCP focuses on optimizing block combinations to facilitate recharging between consecutive blocks, considering operational constraints. A case study conducted reveals that nearly 100% electrification for Chicago, IL and Austin, TX transit buses is viable yet requires 1.6 EVs at 150-mile range per diesel vehicle., Comment: 23 pages

A sustainable solution to negative externalities imposed by road transportation is replacing internal combustion vehicles with electric vehicles (EVs), especially plug-in EV (PEV) encompassing plug-in hybrid EV (PHEV) and battery EV (BEV). However, EV market share is still low and is forecast to remain low and uncertain. This shows a research need for an in-depth understanding of EV adoption behavior with a focus on one of the main barriers to the mass EV adoption, which is the limited electric driving range. The present study extends the existing literature in two directions; First, the influence of the psychological aspect of driving range, which is referred to as range anxiety, is explored on EV adoption behavior by presenting a nested logit (NL) model with a latent construct. Second, the two-level NL model captures individuals' decision on EV adoption behavior distinguished by vehicle transaction type and EV type, where the upper level yields the vehicle transaction type selected from the set of alternatives including no-transaction, sell, trade, and add. The fuel type of the vehicles decided to be acquired, either as traded-for or added vehicles, is simultaneously determined at the lower level from a set including conventional vehicle, hybrid EV, PHEV, and BEV. The model is empirically estimated using a stated preferences dataset collected in the State of California. A notable finding is that anxiety about driving range influences the preference for BEV, especially as an added than traded-for vehicle, but not the decision on PHEV adoption., Comment: 27 pages, 3 figures, 5 tables

For two given graphs $G$ and $F$, a graph $ H$ is said to be weakly $ (G, F) $-saturated if $H$ is a spanning subgraph of $ G$ which has no copy of $F$ as a subgraph and one can add all edges in $ E(G)\setminus E(H)$ to $ H$ in some order so that a new copy of $F$ is created at each step. The weak saturation number $ wsat(G, F)$ is the minimum number of edges of a weakly $(G, F)$-saturated graph. In this paper, we deal with the relation between $ wsat(G(n,p), F)$ and $ wsat(K_n, F)$, where $G(n,p)$ denotes the Erd\H{o}s--R\'enyi random graph and $ K_n$ denotes the complete graph on $ n$ vertices. For every graph $ F$ and constant $ p$, we prove that $ wsat( G(n,p),F)= wsat(K_n,F)(1+o(1))$ with high probability. Also, for some graphs $ F$ including complete graphs, complete bipartite graphs, and connected graphs with minimum degree $ 1$ or $ 2$, it is shown that there exists an $ \varepsilon(F)>0$ such that, for any $ p\geqslant n^{-\varepsilon(F)}\log n$, $ wsat( G(n,p),F)= wsat(K_n,F)$ with high probability., Comment: The only difference with the previous file is here that the grant number of the first author was wrong and is corrected now

Electric vehicle (EV) supply equipment location and allocation (EVSELCA) problems for freight vehicles are becoming more important because of the trending electrification shift. Some previous works address EV charger location and vehicle routing problems simultaneously by generating vehicle routes from scratch. Although such routes can be efficient, introducing new routes may violate practical constraints, such as drive schedules, and satisfying electrification requirements can require dramatically altering existing routes. To address the challenges in the prevailing adoption scheme, we approach the problem from a fixed-route perspective. We develop a mixed-integer linear program, a clustering approach, and a metaheuristic solution method using a genetic algorithm (GA) to solve the EVSELCA problem. The clustering approach simplifies the problem by grouping customers into clusters, while the GA generates solutions that are shown to be nearly optimal for small problem cases. A case study examines how charger costs, energy costs, the value of time (VOT), and battery capacity impact the cost of the EVSELCA. Charger equipment costs were found to be the most significant component in the objective function, leading to a substantial reduction in cost when decreased. VOT costs exhibited a significant decrease with rising energy costs. An increase in VOT resulted in a notable rise in the number of fast chargers. Longer EV ranges decrease total costs up to a certain point, beyond which the decrease in total costs is negligible.

For a given graph $F$, the $F$-saturation number of a graph $G$, denoted by $ {sat}(G, F)$, is the minimum number of edges in an edge-maximal $F$-free subgraph of $G$. In 2017, Kor\'andi and Sudakov determined $ {sat}({G}(n, p), K_r)$ asymptotically, where ${G}(n, p) $ denotes the Erd\H{o}s-R\'enyi random graph and $ K_r$ is the complete graph on $r$ vertices. In this paper, among other results, we present an asymptotic upper bound on ${sat}({G}(n, p), F)$ for any bipartite graph $F$ and also an asymptotic lower bound on ${sat}({G}(n, p), F)$ for any complete bipartite graph $F$.