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Objectives : The aim of this study was to evaluate Cu-64 PET phantom image quality using Bayesian Penalized Likelihood (BPL) and Ordered Subset Expectation Maximum with point-spread function modeling (OSEM-PSF) reconstruction algorithms. In the BPL, the regularization parameterβwas varied to identify the optimum value for image quality. In the OSEM-PSF, the effect of acquisition time was evaluated to assess the feasibility of shortened scan duration. Methods : A NEMA IEC PET body phantom was filled with known activities of water soluble Cu-64. The phantom was imaged on a PET/CT scanner and was reconstructed using BPL and OSEM-PSF algorithms. For the BPL reconstruction, variousβvalues (150, 250, 350, 450, and 550) were evaluated. For the OSEM-PSF algorithm, reconstructions were performed using list-mode data intervals ranging from 7.5 to 240 s. Image quality was assessed by evaluating the signal to noise ratio (SNR), contrast to noise ratio (CNR), and background variability (BV). Results : The SNR and CNR were higher in images reconstructed with BPL compared to OSEM-PSF. Both the SNR and CNR increased with increasing β , peaking atβ= 550. The CNR for all β , sphere sizes and tumor-to-background ratios (TBRs) satisfied the Rose criterion for image detectability (CNR > 5). BPL reconstructed images with β = 550 demonstrated the highest improvement in image quality. For OSEM-PSF reconstructed images with list-mode data duration ≥ 120 s, the noise level and CNR were not significantly different from the baseline 240 s list-mode data duration. Conclusions : BPL reconstruction improved Cu-64 PET phantom image quality by increasing SNR and CNR relative to OSEM-PSF reconstruction. Additionally, this study demonstrated scan time can be reduced from 240 to 120 s when using OSEM-PSF reconstruction while maintaining similar image quality. This study provides baseline data that may guide future studies aimed to improve clinical Cu-64 imaging., (© 2024 IOP Publishing Ltd.)

Abstract: This study offers novel progresses for a semianalytical method to simulate 2D propagation of cracks based on linear elastic fracture mechanics. For this purpose, a new algorithm is proposed on the basis of the linear elastic fracture mechanics for crack propagation in single‐mode and mixed mode. Herein, discretization is only performed on the boundaries of the problem by using specific subparametric elements and higher‐order Chebyshev polynomials as mapping functions. Implementing the weighted residual method and by taking Clenshaw‐Curtis numerical quadrature, diagonal Euler's differential equations are obtained. Consequently, once the local coordinate origin is assumed at the tip of the crack, the stress intensity factors can be derived directly. In accordance with the rate of maximum energy release as a propagation criterion and by proposing a new quasi‐automatic remeshing procedure based on domain division, the crack propagation is applied here. Based on the new presented algorithm, application of the new semianalytical method to crack propagation analysis is more flexible and efficient. By taking this advantage, relatively coarse and simple discretization compared with other computational methods may be used. By modelling 4 benchmark problems with a few numbers of degrees of freedom, the validity and accuracy of the current method is illustrated. Results show that the presented algorithm is applicable for efficient and precise prediction of crack trajectories. [ABSTRACT FROM AUTHOR]

Abstract: Flexible job-shop scheduling problem (FJSP) is an extension of the classical job-shop scheduling problem. FJSP is NP-hard and mainly presents two difficulties. The first one is to assign each operation to a machine out of a set of capable machines, and the second one deals with sequencing the assigned operations on the machines. This paper proposes a parallel variable neighborhood search (PVNS) algorithm that solves the FJSP to minimize makespan time. Parallelization in this algorithm is based on the application of multiple independent searches increasing the exploration in the search space. The proposed PVNS uses various neighborhood structures which carry the responsibility of making changes in assignment and sequencing of operations for generating neighboring solutions. The results obtained from the computational study have shown that the proposed algorithm is a viable and effective approach for the FJSP. [Copyright &y& Elsevier]

Abstract: This paper investigates a fixed charge solid transportation problem (FCSTP) under a fuzzy environment, in which the both direct and fixed costs are supposed to be fuzzy numbers. This is one of the primary and most important problems in transportation and network research areas. To solve such a hard problem, three metaheuristics, namely variable neighborhood search (VNS), simulated annealing (SA) and hybrid VNS are employed. To the best of our knowledge, neither SA nor VNS has been considered for any kind of transportation problems. Besides, the novelty of the proposed algorithms is to use various new neighborhood structures related to the nature of the problem, which are proposed and used for the first time. The efficiency of employed parameters is measured by the Taguchi experimental design method that is a useful and new approach to tune the parameters and reduce the possible number of experiments in this research area. To evaluate the performance of the proposed algorithms, an extensive computational study has been conducted and the associated results obtained by the algorithms are compared with each other. Finally, a conclusion and further research areas are presented. [Copyright &y& Elsevier]