Integrated Intermodal Network Design with Nonlinear Inter-Hub Movement Costs

In this research, transportation mode and load route selection problems are integrated with the hub location problem in a single mathematical formulation to find the optimal design of intermodal transportation networks. Economies of scale are modeled utilizing a stepwise function that relates the per container transportation cost to the amount of flow between two nodes. A heuristic method combining a genetic algorithm and the shortest path algorithm was developed to solve this integrated planning problem. Computational experiments were completed to evaluate the performance of the proposed heuristic for different problem instances. At the end, conclusions are presented and future research directions are discussed

Integrated Intermodal Logistics Network Design

Intermodal freight transportation uses at least two different transportation modes (e.g., truck, rail, ship, air) to move freight loads that are in the same transportation unit (e.g., a shipping container) from origin to destination without handling the goods themselves. The increasing shift to intermodal transportation and the growth of freight transportation demand have resulted in a higher demand for intermodal freight transportation that has been projected to grow even faster in the next few decades. Satisfying this emerging demand will require enhancing the capacity of current intermodal facilities or even the construction of new intermodal facilities. This research addresses the intermodal logistics network design problem which is one of the key strategic planning decisions related to intermodal transportation. To obtain the maximum performance of the intermodal logistics network, two relevant decisions corresponding to the route and mode selection for freight loads were integrated with the facility location problem within the integrated intermodal logistics network design (IILND) problem. To address the IILND problem, two mathematical formulations were developed. One considered making decisions about arcs of the network while the other considered making decisions about routes for origin-destination flows in the network. The arc-based formulation modeled the effect of consolidating freight loads at intermodal terminals on the transportation cost by a stepwise function that relates the per container transportation cost to the amount of flow between two nodes. A heuristic approach that combines a genetic algorithm and the shortest path algorithm was developed to efficiently obtain high quality solutions for the arc-based formulation. Unlike the arc-based formulation, the route-based formulation modeled the effect of consolidating different loads at intermodal terminals on the transportation cost and time using constant discount and delay factors, respectively. Moreover, a composite variable formulation was used for the route-based formulation to incorporate route feasibility constraints within the definition of the composites and avoid explicitly adding them to the model. These modifications reduced the number of variables and constraints significantly when compared to the arc-based formulation. Two solution approaches were developed to find optimal solutions for the route-based formulation, namely a decomposition-based search algorithm and an accelerated Bender’s decomposition method. Several sets of computational experiments were completed to evaluate the performance of the proposed mathematical formulations and solutions approaches. Finally, several general insights about the effects of design parameters on solution characteristics were obtained from the computational experiments and directions for future research were identified

Evaluation of Radicular Dentin Thickness of Danger Zone in Mandibular First Molars

Objective: Better understanding of the furcation anatomy may serve to decrease the risk of root perforation. The purpose of this study was to measure the thickness of root walls in the danger zone in mandibular first molars.Materials and Methods: The roots of 53 extracted human mandibular first molars were sectioned in the horizontal plane 4 mm below the orifice of the mesial and distal root canals.For each cut surface buccal, lingual, mesial, and distal thickness of the root wall wasmeasured. Mean values of the thickness at each location were calculated and compared by ANOVA and t-test.Results: The results showed that the mean thickness in the distal portion of the mesial root was smaller in comparison to all other portions of the roots (P<0.05) and this difference was statistically significant except for the mesial portion of the distal root (P=0.463). The mean thickness of radicular dentin at the distal aspect of mesial roots was 1.2 millimeter.Conclusion: Our study suggests that knowledge of the root dentin thickness in the danger zone is essential for preventing endodontic mishaps leading to failure

New insight in severe acute respiratory syndrome coronavirus 2 consideration: Applied machine learning for nutrition quality, microbiome and microbial food poisoning concerns

Although almost two years have passed since the beginning of the coronavirus disease 2019 (COVID-19) pandemic in the world, there is still a threat to the health of people at risk and patients. Specialists in various sciences conduct various researches in order to eliminate or reduce the problems caused by this disease. Nutrition is one of the sciences that plays a very important supportive role in this regard. It is important for patients to pay attention to the potential of different diets in preventing or accelerating the healing process. The relationship between nutrition and microbiome regulation or the occurrence of food microbial poisoning is one of the factors that can directly or indirectly play a key role in the body's resilience to COVID-19. In this article, we introduce a link between nutrition, the microbiome, and the incidence of food microbial poisoning that may have great potential in preventing, treating COVID-19, or preventing deterioration in patients. In linking the components of this network, artificial intelligence (AI), machine learning (ML) and data mining (DM) can be important strategies and lead to the creation of a conceptual model called "Balance square", which we will introduce

Clinico-pathological Features and Survival Time of Papillary Thyroid Carcinoma in Patients With and Without Hashimoto’s Thyroiditis: A Cross-sectional Study

Objectives: Researchers have reported different results regarding the association between Hashimoto’s disease and papillary thyroid carcinoma (PTC). Some believe that the coexistence of these diseases can lead to fewer tumor invasion and recurrence rates. This study evaluated the clinico-pathological features and survival time of PTC in patients with and without Hashimoto’s thyroiditis. Materials and Methods: In this cross-sectional study, medical records of 251 participants who underwent total or subtotal thyroidectomy due to PTC from 2012 to 2019 were reviewed. The clinico-pathological features of participants, such as age, gender, tumor stage, tumor size, lymph node involvement, metastasis, capsular invasion, single or multi-focal tumor status, and survival time were recorded from their medical records and pathology report and compared in two groups with and without Hashimoto’s thyroiditis. Results: From 251 participants, 92 (36.6%) had Hashimoto’s thyroiditis, whereas 159 (63.4%) did not show any signs of this disease. Fifteen participants in the Hashimoto group and 46 in the non-Hashimoto group had a recurrence. Although there were no significant differences between the two groups in the term of recurrence rate (P = 0.08), the mean survival time was significantly difference between the two groups (69.03 and 58.78, respectively; P = 0.038) Conclusions: Results of the study revealed that Hashimoto’s thyroiditis could increase the survival time of patients with PTC

Anticipatory freight selection in intermodal long-haul round-trips

We consider the planning problem faced by Logistic Service Providers (LSPs) transporting freights periodically, using long-haul round-trips. In each round-trip, freights are delivered and picked up at different locations within one region. Freights have time-windows and become known gradually over time. Using probabilistic knowledge about future freights, the LSP’s objective is to minimize costs over a multi-period horizon. We propose a look-ahead planning method using Approximate Dynamic Programming. Experiments show that our approach reduces costs up to 25.5% compared to a single-period optimization approach. We provide managerial insights for several intermodal long-haul round-trips settings and provide directions for further research

Design, synthesis and SAR exploration of tri-substituted 1,2,4-triazoles as inhibitors of the annexin A2–S100A10 protein interaction

Recent target validation studies have shown that inhibition of the protein interaction between annexin A2 and the S100A10 protein may have potential therapeutic benefits in cancer. Virtual screening identified certain 3,4,5-trisubstituted 4H-1,2,4-triazoles as moderately potent inhibitors of this interaction. A series of analogues were synthesized based on the 1,2,4-triazole scaffold and were evaluated for inhibition of the annexin A2–S100A10 protein interaction in competitive binding assays. 2-[(5-{[(4,6-Dimethylpyrimidin-2-yl)sulfanyl]methyl}-4-(furan-2-ylmethyl)-4H-1,2,4-triazol-3-yl)sulfanyl]-N-[4-(propan-2-yl)phenyl]acetamide (36) showed improved potency and was shown to disrupt the native complex between annexin A2 and S100A10