Search Results (35)

Purpose/Objective(s): Peritoneal carcinosis can occur in several gastrointestinal or gynecological malignancies and its prognosis is usually poor. With the advent of more effective systemic agents, the overall survival of metastatic patients has been revolutionized and isolated peritoneal or abdominal wall metastases might benefit from local treatments; Stereotactic Body Radiotherapy (SBRT) might be considered in selected patients with oligometastatic presentation. Materials/Methods: Oligometastases were defined according to recent ESTRO/EORTC consensus. Inclusion criteria were as follows: ECOG PS ≤ 2, written informed consent, up to five lesions to be treated at the same time, patients treated with radiotherapy schedules applying minimum 6 Gy per fraction. The primary endpoint of the study was local control (LC); acute and late toxicity, distant progression-free survival (DPFS), time-to-next systemic treatment (TNST), polymetastatic-free survival (PMFS) and overall survival (OS) were secondary endpoints. Toxicity was assessed according to CTCAE criteria v5.0. Statistical associations between clinical variables and outcomes were assessed using Fisher’s exact test, and Kruskal–Wallis test, as appropriate. Survival outcomes were estimated using the Kaplan–Meier method and compared using the log-rank test. Results: Between April 2020 and September 2024 a total of 26 oligometastatic lesions located in the peritoneum or in the abdominal wall detected in 20 patients received SBRT with Helical Tomotherapy. All cases have been assessed by a multidisciplinary team. Only in three patients out of twenty did more than one lesion receive SBRT: two lesions in two patients, and five lesions in a single case of colorectal cancer with ongoing third-line systemic treatment. Median total dose was 30 Gy (27–35 Gy) in five fractions (3–5). The most frequent primary neoplasm was ovarian cancer in 14/20, endometrial in 2/20, while the remaining were colorectal, vaginal, pancreatic and non-small cell lung cancer. Four lesions were located in the abdominal wall, while the remaining twenty-two were located in the peritoneum. Concurrent systemic therapy was administered in 18/20 patients. With a median follow-up of 15 months (range, 6–59), our 1-year LC was 100%, while 1-year DPFS, PMFS, TNTS and OS rates were 54%, 69%, 61% and 83%, respectively. Abdominal wall location and treatment of a subsequent oligometastatic recurrence with a second course of SBRT were both significantly associated with improved OS (p = 0.03 and p = 0.04, respectively). No G ≥ 3 adverse events occurred. Conclusion: Our preliminary data support the use of SBRT in selected cases of oligometastatic disease located in the peritoneum or in the abdominal wall with excellent results in terms of tolerability and promising clinical outcomes. Full article

This paper proposes a comprehensive Mixed-Integer Linear Programming (MILP) formulation for the simultaneous scheduling of machines and Automated Guided Vehicles (AGVs) within a partitioned Flexible Manufacturing System (FMS). The main objective is to numerically optimize the simultaneous scheduling of machines and AGVs while considering various workshop layouts and operational constraints. Three different workshop layouts are analyzed, with varying numbers of machines in partitioned workshop areas A and B, to evaluate the performance and effectiveness of the proposed model. The model is tested in multiple scenarios that combine different layouts with varying numbers of workpieces, followed by an extension to consider dynamic initial conditions in a more generalized MILP framework. Results demonstrate that the proposed MILP formulation efficiently generates globally optimal solutions and consistently outperforms a greedy algorithm enhanced by A*-inspired heuristics. Although computationally intensive for large scenarios, the MILP’s optimal results serve as an exact benchmark for evaluating faster heuristic methods. In addition, the study provides practical insight into the integration of AGVs in modern manufacturing systems, paving the way for more flexible and efficient production planning. The findings of this research are expected to contribute to the development of advanced scheduling strategies in automated manufacturing systems. Full article

Background/Objectives: Vitiligo is an autoimmune condition causing melanocyte destruction and skin depigmentation. First-line treatments for vitiligo include topical medications and phototherapy; however, access and utilization of these treatments vary, particularly in pediatric patients. This study evaluates nbUVB use in pediatric versus adult vitiligo patients to better understand utilization in the pediatric population. Methods: A retrospective chart review study was conducted, collecting demographics and treatment characteristics for 102 adults and 19 children with vitiligo treated with nbUVB phototherapy at one institution. Statistical analysis included comparisons for categorical variables made using Chi-squared test or Fisher’s exact test, as appropriate, and using a non-parametric Mann–Whitney U test for continuous variables. Results: On average, adults underwent nbUVB for 23.8 months (range 0.5–418, median 9), while children had an average duration of 14.8 months (range 2–60, median 8). The average number of nbUVB sessions for adults was 83.8, whereas children had an average of 33.5 sessions. Overall, 59.6% of adults and 60.0% of children experienced repigmentation with nbUVB. Conclusions: Retrospective analysis indicated that the duration and frequency of nbUVB sessions varied widely among both adults and children. While the average duration of treatment was comparable between the groups, children underwent fewer sessions on average. This may reflect differences in physician recommendation, scheduling constraints, or treatment adherence. Despite this variability, most pediatric patients exhibited repigmentation, supporting nbUVB efficacy. Our results suggest nbUVB is underutilized in pediatric vitiligo. Addressing obstacles to access is crucial for improving treatment outcomes and quality of life. Full article

The Mixed No-Idle Permutation Flow Shop Scheduling Problem (MNPFSSP) represents a specific case within regular flow scheduling problems. In this problem, some machines allow idle times between consecutive jobs or operations while other machines do not. Traditionally, the MNPFSSP has been addressed using the metaheuristics and exact methods. This work proposes an Evolutionary Strategy Based on the Generalized Mallows Model (ES-GMM) to solve the issue. Additionally, its advanced version, ES-GMMc, is developed, incorporating operating conditions to improve execution times without compromising solution quality. The proposed approaches are compared with algorithms previously used for the problem under study. Statistical tests of the experimental results show that the ES-GMMc achieved reductions in execution time, especially standing out in large instances, where the shortest computing times were obtained in 23 of 30 instances, without affecting the quality of the solutions. Full article

In this paper, we develop an exact schedulability test and sufficient infeasibility test for fixed-priority scheduling on multiprocessor platforms. We base our tests on presenting real-time systems as a Kripke model for dynamic real-time systems with sporadic non-preemptible tasks running on a multiprocessor platform and an online scheduler using global fixed priorities. This model includes states and transitions between these states, allows us to formally justify a polynomial-time algorithm for an exact schedulability test using the idea of backward reachability. Using this algorithm, we perform the exact schedulability test for the above real-time systems, in which there is one more task than the processors. The main advantage of this algorithm is its polynomial complexity, while, in general, the problem of the exact schedulability testing of real-time systems on multiprocessor platforms is NP-hard. The infeasibility test uses the same algorithm for an arbitrary task-to-processor ratio, providing a sufficient infeasibility condition: if the real-time system under test is not schedulable in some cases, the algorithm detects this. We conduct an experimental study of our algorithms on the datasets generated with different utilization values and compare them to several state-of-the-art schedulability tests. The experiments show that the performance of our algorithm exceeds the performance of its analogues while its accuracy is similar. Full article

Against the backdrop of developing metro-based passenger and freight co-transportation plans, this study addresses the integrated optimization problem of train scheduling and flow control for a co-transportation metro line, where passengers and freight can share the same trains. Given a set of time-dependent passenger and freight demands, the problem involves determining the space-time trajectories and passenger (or freight) capacities of trains while simultaneously assigning these demands to the trains. To tackle this, train selection variables, carriage arrangement variables, and flow assignment variables are introduced, and the problem is formulated as an integer linear programming model. The objective is to minimize the weighted sum of the number of freight carriages, the total waiting time of all passengers, and the total delay of all freight. The proposed model is equivalent to a mixed-integer linear programming model, which allows a commercial solver to efficiently find the exact solution. To validate the effectiveness of the proposed method, several numerical examples of varying scales are tested. The results demonstrate that integrating the optimization of train schedules and co-transportation plans significantly enhances the efficiency of the entire co-transportation system. Full article

Introduction: Radiation therapy plays an important role in the treatment of localized breast cancer. Hypofractionated (HF) radiation therapy has emerged as a promising alternative to conventional fractionation (CF) schedules, offering comparable efficacy with reduced treatment duration and costs. However, concerns remain regarding its safety and rate of toxicity, particularly in patients undergoing mastectomy with breast reconstruction. This study aimed to assess the implant-related complications in breast cancer patients receiving HF post-mastectomy radiation therapy (PMRT) and reconstruction compared to CF PMRT. Methods: A retrospective study was conducted on 59 breast cancer patients who underwent mastectomy and breast reconstruction between 2013 and 2021 and received adjuvant PMRT. Patient demographics, treatment characteristics, and implant-related complications were analyzed. Statistical tests including chi-square, Fischer’s exact test, and multivariable Cox regression were employed for analysis. Results: Of the 59 patients, 29 received HF PMRT and 30 received CF PMRT. At a median follow-up of 23.4 months, there was no significant difference in major implant-related complications between the two groups (24.1% in HF vs. 33.3% in CF, p = 0.436). Most complications in the HF group occurred within the first two years post-radiation. Age over 40 was identified as a significant predictor for higher implant-related complications (p = 0.029). Conclusions: Our findings indicate that HF PMRT and reconstruction does not increase the risk of major implant-related complications compared to CF PMRT. These results align with the existing literature, supporting the safety of HF radiation in breast cancer patients who underwent mastectomy with reconstruction. Full article

In recent years, twin stacker crane units have been increasingly integrated into large automated storage and retrieval systems (AS/RSs) in shipyards to enhance operational efficiency. These common rail units often encounter conflicts, and the additional time costs incurred during collision avoidance significantly diminish AS/RS efficiency. Therefore, addressing the twin stacker cranes’ scheduling problem (TSSP) with a collision-free constraint is essential. This paper presents a novel approach to identifying and avoiding collisions by approximating the stacker crane’s trip trajectory as a triangular envelope. Utilizing the collision identification equation derived from this method, we express the collision-free constraint within the TSSP and formulate a mixed-integer programming model. Recognizing the multimodal characteristics of the TSSP objective function, we introduce the dung beetle optimizer (DBO), which excels in multimodal test functions, as the foundational framework for a heuristic optimizer aimed at large-scale TSSPs that are challenging for exact algorithms. To adapt the optimizer for bi-level programming problems like TSSPs, we propose a double-layer code mechanism and innovatively design a binary DBO for the binary layer. Additionally, we incorporate several components, including a hybrid initialization strategy, a Cauchy–Gaussian mixture distribution neighborhood search strategy, and a velocity revision strategy based on continuous space discretization, into the improved dung beetle optimizer (IDBO) to further enhance its performance. To validate the efficacy of the IDBO, we established a numerical experimental environment and generated a series of instances based on actual environmental parameters and operational conditions from an advanced AS/RS in southeastern China. Extensive comparative experiments on various scales and distributions demonstrate that the components of the IDBO significantly improve algorithm performance, yielding stable advantages over classical algorithms in solving TSSPs, with improvements exceeding 10%. Full article

Background: Social Communication Disorder (SCD), introduced in the DSM-5, is distinguished from Autism Spectrum Disorder (ASD) by the absence of restricted and repetitive behaviors or interests (RRBIs). Aim: To compare the adaptive, sensory, communication, and cognitive profiles of children with ASD and SCD. Methods: The assessments of nine children with SCD and ten with ASD were compared with either Fisher’s Exact Test or the Mann–Whitney Test. Assessments included the Vineland Adaptive Behavior Scales, the Autism Diagnostic Observation Schedule (ADOS), the Short Sensory Profile, Bishop’s Children’s Communication Checklist, a pragmatics evaluation, and the Wechsler Intelligence Scale for Children IV. Results: The total ADOS score and the second subtotal “Restricted and Repetitive Behaviors” were significantly higher (p = 0.022) in the ASD group than in the SCD group. The Vineland standard score for the “Socialization” domain was significantly lower (p = 0.037) in the ASD group (mean: 51 +/− 19) than in the SCD group (mean: 80 +/− 28). The working memory index score was also significantly lower (p = 0.013) in the ASD group compared to the SCD group. Conclusions: While ASD and SCD share similarities in communication and pragmatic difficulties, some distinctions have been identified, e.g. in executive functioning and the impact on socialization, which may be linked to the absence of RRBIs in SCD. These findings highlight the challenges posed by this nosographic separation during diagnostic evaluations due to the scarcity of discriminative tools. Full article

This paper presents a novel, multi-objective scatter search algorithm (MOSS) for a bi-objective, dynamic, multiprocessor open-shop scheduling problem (Bi-DMOSP). The considered objectives are the minimization of the maximum completion time (makespan) and the minimization of the mean weighted flow time. Both are particularly important for improving machines’ utilization and customer satisfaction level in maintenance and healthcare diagnostic systems, in which the studied Bi-DMOSP is mostly encountered. Since the studied problem is NP-hard for both objectives, fast algorithms are needed to fulfill the requirements of real-life circumstances. Previous attempts have included the development of an exact algorithm and two metaheuristic approaches based on the non-dominated sorting genetic algorithm (NSGA-II) and the multi-objective gray wolf optimizer (MOGWO). The exact algorithm is limited to small-sized instances; meanwhile, NSGA-II was found to produce better results compared to MOGWO in both small- and large-sized test instances. The proposed MOSS in this paper attempts to provide more efficient non-dominated solutions for the studied Bi-DMOSP. This is achievable via its hybridization with a novel, bi-objective tabu search approach that utilizes a set of efficient neighborhood search functions. Parameter tuning experiments are conducted first using a subset of small-sized benchmark instances for which the optimal Pareto front solutions are known. Then, detailed computational experiments on small- and large-sized instances are conducted. Comparisons with the previously developed NSGA-II metaheuristic demonstrate the superiority of the proposed MOSS approach for small-sized instances. For large-sized instances, it proves its capability of producing competitive results for instances with low and medium density. Full article

The water pump scheduling problem is an optimisation model that determines which water pumps will be turned on or off at each time period over a given time horizon for a given water supply system. This problem has received considerable attention in mining and desalination due to the high power consumption of water pumps and desalination plants and the complicated dynamics of water flows and the power market. Motivated by this, in this paper we solve the optimal operation of a desalinated water supply system consisting of interconnected tanks and pumps that transport water to high-altitude reservoirs. The optimisation of this process encounters several difficulties arising from (i) the nonlinearities of the equations for the frictional losses along the pipes and pumps, which makes the problem a nonlinear mixed-integer model, and (ii) many possible combinations of pressure head and flow rates, which quickly leads to high computational costs. These limitations prevent the problem from being solved in a reasonable computational time in high-altitude water supply systems with more than six pumps and reservoirs, as in many networks worldwide. Therefore, in this work we develop new exact methods for the optimal pump scheduling problem that use a binary expansion approach to efficiently account for the existing nonlinearities by reducing the computational difficulties of the original problem while keeping an excellent representation of the physical phenomena involved. We also extensively tested the proposed approach in different network topologies and a case study for a real-world copper mine water network, and we conclude that the binary expansion approach significantly reduces the computational time for solving the problem with high precision, which can be very relevant for the practical daily operation of real-world water supply systems. Full article

Scheduling and optimization have a central place in the research area of computing because it is increasingly important to achieve fully automated production processes to adjust manufacturing systems to the requirements of Industry 4.0. In this paper, we demonstrate how an automated wet-etch scheduling problem for the semiconductor industry can be solved by constraint answer set programming (CASP) and its solver called clingcon. A successful solution to this problem is achieved, and we found that for all tested problems, CASP is faster and obtains smaller makespan values for seven of the eight problems tested than the solutions based on mixed integer linear programming and constraint paradigms. The considered scheduling problem includes a robot for lot transfers between baths. CASP is a hybrid approach in automated reasoning that combines different research areas such as answer set programming, constraint processing, and Satisfiability Modulo Theories. For a long time, exact methods such as constraint programming have displayed difficulties in solving real large-scale problem instances. Currently, the performance of state-of-the-art constraint solvers is comparatively better than a decade ago, and some complex combinatorial problems can be better solved. These theoretical and technical achievements open new horizons for declarative programming applications such as logistics. Full article

During acute respiratory infections, women may concurrently receive human papillomavirus (HPV) and respiratory vaccines, as observed during the coronavirus disease 2019 (COVID-19) pandemic in China. However, few studies have assessed the safety of such concurrent administration, which could impact HPV vaccination schedules. This study analyzes the safety and optimal sequence of concurrent HPV and COVID-19 vaccinations. For this purpose, we surveyed women with both vaccines from January to October 2023 in Fujian Province, China. During this process, we collected vaccination history and adverse event (AE) data via telephone or interviews. Participants were grouped as Before, Concurrent, or After based on their vaccination sequence. A Chi-squared test, exact Fisher tests, and logistic regression were used to analyze the incidence of AEs and factors influencing vaccine safety. Overall, 1416 eligible participants were included. Although overall AE risk with the HPV vaccine was unaffected by vaccination sequence, individual AEs varied statistically between groups, including pain at the vaccination site (p < 0.001) and prolonged menstruation duration (p = 0.003). Based on the results, the optimal sequence would be to receive the HPV vaccine after the COVID-19 vaccine (After group). This insight may guide future emergency vaccination sequences for HPV and other respiratory infectious diseases. Full article

Large language models (LLMs) excel in providing natural language responses that sound authoritative, reflect knowledge of the context area, and can present from a range of varied perspectives. Agent-based models and simulations consist of simulated agents that interact within a simulated environment to explore societal, social, and ethical, among other, problems. Simulated agents generate large volumes of data and discerning useful and relevant content is an onerous task. LLMs can help in communicating agents’ perspectives on key life events by providing natural language narratives. However, these narratives should be factual, transparent, and reproducible. Therefore, we present a structured narrative prompt for sending queries to LLMs, we experiment with the narrative generation process using OpenAI’s ChatGPT, and we assess statistically significant differences across 11 Positive and Negative Affect Schedule (PANAS) sentiment levels between the generated narratives and real tweets using chi-squared tests and Fisher’s exact tests. The narrative prompt structure effectively yields narratives with the desired components from ChatGPT. In four out of forty-four categories, ChatGPT generated narratives which have sentiment scores that were not discernibly different, in terms of statistical significance (alpha level $\alpha =0.05$), from the sentiment expressed in real tweets. Three outcomes are provided: (1) a list of benefits and challenges for LLMs in narrative generation; (2) a structured prompt for requesting narratives of an LLM chatbot based on simulated agents’ information; (3) an assessment of statistical significance in the sentiment prevalence of the generated narratives compared to real tweets. This indicates significant promise in the utilization of LLMs for helping to connect a simulated agent’s experiences with real people. Full article

This paper presents the performance analysis of a three-phase squirrel cage induction motor (SCIM) with a double–triple-layer (DTL) stator winding configuration operating with broken rotor bar (BRB) faults. The effects of BRB faults on the performance of specific parameters are analyzed under a steady-state regime. The SCIM is modeled using the two-dimensional finite element method (FEM) to study electromagnetic performance under healthy and BRB faulty conditions. To validate the finite element analysis (FEA) results, a prototype of an SCIM with a DTL stator winding configuration is tested for performance evaluation under healthy and BRB faulty conditions. The FEA and experimental (EXP) results of the SCIM with a DTL stator winding arrangement are compared with the results of the SCIM with a conventional double-layer (CDL) stator winding configuration. FEA and EXP results evidenced that the SCIM with a DTL stator winding configuration mitigates some of the adverse effects introduced by the BRB faults compared to the SCIM with a CDL stator winding of the exact specifications. Under loaded conditions, the SCIM with a DTL stator winding configuration reduced the magnitudes of the twice slip frequency sidebands caused by BRB faults from ±1.2 Hz for the SCIM with a CDL stator winding arrangement down to ±0.2 Hz and ±0.36 Hz when operating with 3BRB and 6BRB faults, respectively. The results also indicate that the SCIM with a DTL stator winding configuration has reduced the decibel sideband magnitude by 7.5 dB and 8 dB for unloaded and loaded conditions, respectively. This premise has positioned the SCIM with a DTL stator winding configuration as a strong candidate in applications where BRB faults are frequent, and the motor may be required to continue operating with a BRB fault until scheduled maintenance is in effect. Full article