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Cancer is one of the leading causes of death all over the world. Among the strategies that are used for cancer treatment, the effectiveness of chemotherapy is often hindered by factors such as irregular and non-uniform uptake of drugs inside tumor. Thus, accurate prediction of drug transport and deposition inside tumor is crucial for increasing the effectiveness of chemotherapeutic treatment. In this study, a computational model of human brain tumor is developed that incorporates dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) data into a voxelized porous media model. The model takes into account realistic transport and perfusion kinetics parameters together with realistic heterogeneous tumor vasculature and accurate arterial input function (AIF), which makes it patient specific. The computational results for interstitial fluid pressure (IFP), interstitial fluid velocity (IFV) and tracer concentration show good agreement with the experimental results. The computational model can be extended further for predicting the deposition of chemotherapeutic drugs in tumor environment as well as selection of the best chemotherapeutic drug for a specific patient.

An intermediate fluid vaporizer (IFV) is a typical vaporizer of liquefied natural gas (LNG), which is used in a large number of LNG terminals. Since it requires a large supply of seawater during its operation, it generates a lot of energy consumption. In this study, to reduce the seawater consumption in the regasification system, the heat transfer process was first numerically calculated, and the heat transfer coefficient of the IFV was determined for different seawater inlet temperatures, seawater flow rates, and LNG flow rates. The calculation results of the heat transfer coefficient were integrated into the numerical model in HYSYS, and the minimum seawater flow of the IFV under different working conditions was obtained. For receiving terminals using multiple IFVs, this study programmed calculations based on optimization software. The operating configuration of the IFVs under different operating conditions was optimized to reduce the consumption of seawater in the regasification system of the LNG terminals.

Background Gynecologic oncologists should be aware of the option of conception through IVF/PGT-M for families with high BRCA related morbidity or mortality. Our objective was to investigate the cost-effectiveness of preimplantation genetic testing for selection and transfer of BRCA negative embryo in BRCA mutation carriers compared to natural conception. Methods Cost-effectiveness of two strategies, conception through IVF/PGT-M and BRCA negative embryo transfer versus natural conception with a 50% chance of BRCA positive newborn for BRCA mutation carriers was compared using a Markovian process decision analysis model. Costs of the two strategies were compared using quality adjusted life years (QALYs’). All costs were discounted at 3%. Incremental cost effectiveness ratio (ICER) compared to willingness to pay threshold was used for cost-effectiveness analysis. Results IVF/ PGT-M is cost-effective with an ICER of 150,219 new Israeli Shekels, per QALY gained (equivalent to 44,480 USD), at a 3% discount rate. Conclusions IVF/ PGT-M and BRCA negative embryo transfer compared to natural conception among BRCA positive parents is cost effective and may be offered for selected couples with high BRCA mutation related morbidity or mortality. Our results could impact decisions regarding conception among BRCA positive couples and health care providers.

This benchmarking study aims to examine and discuss the current state-of-the-art techniques for in-video violence detection, and also provide benchmarking results as a reference for the future accuracy baseline of violence detection systems. In this paper, the authors review 11 techniques for in-video violence detection. They re-implement five carefully chosen state-of-the-art techniques over three different and publicly available violence datasets, using several classifiers, all in the same conditions. The main contribution of this work is to compare feature-based violence detection techniques and modern deep-learning techniques, such as Inception V3.

During the uncertain information processing on Atanassov’s intuitionistic fuzzy sets, the ranking for intuitionistic fuzzy values (IFVs) is an important and omnipresent issue. Even though many orders used to compare any two IFVs have been proposed, some shortcomings, such as inadmissibility, nonrobustness, and nondeterminacy, may exist when these orders are utilized. Inspired by the Euclidean approach for ranking IFVs, we present a novel order that can overcome the aforementioned shortcomings using the notion of relative geometric distance. With the help of graphic representation of an IFV, we analyze the existing popular approaches for ranking IFVs and point out their drawbacks. Taking into account these three distances between an IFV and the ideal negative point, ideal positive point and most uncertain point, respectively, we present a relative-distance-based mensuration for describing the favorable degree of the IFV. Accordingly, the boundaries used in the existing ranking approaches for IFVs are replaced by a novel curve. We prove that the proposed method satisfies the admissibility, robustness, and determinacy requirements. Finally, we extend the presented ranking method for IFVs by introducing human attitudes and compare the proposed approach with the existing ones, which indicates its availability and rationality. We then can obtain the conclusion that the relative distance is an effective and reasonable approach for ranking IFVs.

With respect to dynamic multi-attribute group decision-making (DMAGDM) problems, where attribute values take the form of intuitionistic fuzzy values (IFVs) and the weights (including expert, attribute and time weights) are unknown, the dynamic intuitionistic fuzzy power geometric weighted average (DIFPGWA) operator and the improved IFVs’ GM(1,1) prediction model (IFVs-GM(1,1)-PM) are proposed. First, the concept of IFVs, the operational rules, the distance between IFVs, and the comparing method of IFVs are defined. Second, the DIFPGWA operator and the improved IFVs-GM(1,1)-PM are defined in detail. Third, corresponding decision-making (D-M) steps are proposed. Three kinds of weights are given by the proposed determination method. Finally, an example is given to prove the effectiveness and superiority of the proposed decision-making method.

In this paper, a well known problem called the Shortest Path Problem (SPP) has been considered in an uncertain environment. The cost parameters for traveling each arc have been considered as Intuitionistic Fuzzy Numbers (IFNs) which are the more generalized form of fuzzy numbers involving a degree of acceptance and a degree of rejection. A heuristic methodology for solving the SPP has been developed, which aim to exploit tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low cost solution corresponding to the minimum-cost path or the shortest path. The Modified Intuitionistic Fuzzy Dijkstra's Algorithm (MIFDA) has been proposed in this paper for solving Intuitionistic Fuzzy Shortest Path Problem (IFSPP) using the Intuitionistic Fuzzy Hybrid Geometric (IFHG) operator. A numerical example illustrates the effectiveness of the proposed method. [PUBLICATION ABSTRACT]