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Supply Chain Management (SCM) requires the alignment of the flow of material, information, and services in a network of suppliers, manufacturers, distributors, and customers. Timing, quantity, and quality should be streamlined by all the stakeholders. The efficiency of SCM operations is especially essential for the growing e-commerce businesses in an era where uncertainties and risks abound and expectations change dynamically. This study initially identifies and prioritizes SCM risk factors for a footwear retailer, which is in both the traditional and e-commerce market, using the Analytical Hierarchy Process (AHP). After the supplier selection risks are found to be the most important risks for the company, a detailed data analysis is conducted to compare the performances of three critical suppliers. Based on historical data, demand forecasting for the year 2021 was made using seasonal factors. Forecasts are then used as requirements in a supply simulation to identify the extent to which the demands will be met and whether there will be any delays in the procurement process. According to the data analysis, forecasting, and simulation results, recommendations for supplier selection and order timing are made.KeywordsSupply chain managementRisk prioritizationAnalytical hierarchy processSupplier selectionData analysisDemand forecasting
Power flow calculations are crucial for the study of power systems, as they can be used to calculate bus voltage magnitudes and phase angles, as well as active and reactive power flows on lines. In this paper, a new approach, the Recycling Newton–Krylov (ReNK) algorithm, is proposed to solve the linear systems of equations in Newton–Raphson iterations. The proposed method uses the Generalized Conjugate Residuals with inner orthogonalization and deflated restarting (GCRO-DR) method within the Newton–Raphson algorithm and reuses the Krylov subspace information generated in previous Newton runs. We evaluate the performance of the proposed method over the traditional direct solver (LU) and iterative solvers (Generalized Minimal Residual Method (GMRES), the Biconjugate Gradient Stabilized Method (Bi-CGSTAB) and Quasi-Minimal Residual Method (QMR)) as the inner linear solver of the Newton–Raphson method. We use different test systems with a number of busses ranging from 300 to 70000 and compare the number of iterations of the inner linear solver (for iterative solvers) and the CPU times (for both direct and iterative solvers). We also test the performance of the ReNK algorithm for contingency analysis and for different load conditions to simulate optimization problems and observe possible performance gains.
The automotive industry is one of the most competitive sectors, and it requires a well-structured logistics system to meet the industry' vital requirements such as just-in-time, lean and agile supply chain operations, productivity and sustainability. Well-located and well-designed warehouses can make reaching these aims for the automotive industry possible and more accessible. Hence, determining a location for a warehouse is a highly critical, tactical, and managerial resolution for the automotive industry, as there is a strong correlation between well-located warehouses and the well-structured logistics network in the automotive industry. Although the WSS is a significant decision-making problem, we observed four critical and severe gaps in the existing literature: (1) the authors preferred to apply traditional objective & subjective frames, and they overlooked existing highly complicated uncertainties. (2) The number of studies focusing on the WSS problem in the automotive industry is surprisingly scarce. (3) It is not sufficiently clear how these factors used in the previous studies were determined, which causes doubts about their reliability. (4) there is no satisfactory evidence of which approaches were used to identify the factors in the previous papers. By considering these gaps, we propose two approaches which can be accepted as a novelty of the paper. First is the extension of the Delphi techniques based on the Fermetean fuzzy sets (FFs) used for identifying the criteria. It also combines the two traditional approaches (i.e., literature review and professionals' evaluations to identify the criteria) with the FF-Delphi technique. The second is the Double Normalized MARCOS approach based on FFs (FF- DN MARCOS) implemented to identify the weights of the criteria and ranking performance of the alternatives. The proposed model was implemented to identify the best warehouse location for the automotive manufacturing company. The results show that the C1 “energy availability & cost” criterion is the most influential criterion and the C5 proximity to port and customs criterion is the second most crucial factor. Then we executed a comprehensive sensitivity analysis, and the results approved the suggested model's validity and robustness despite excessive modifications in the criteria weights.
The seeds of Aframomum melegueta K. Schum (grains of paradise, Zingiberaceae) are used as a common spice in African countries and a fine condiment in the European cuisine. In this study, we evaluated the phytochemical profile of various seed extracts of A. melegueta as well as their antimicrobial, antioxidant and enzyme inhibitory effects. In total, 25 diarylheptanoids, five gingerol derivatives and nine phenolic/organic acids were tentatively annotated in A. melegueta by liquid chromatography hyphenated with high resolution tandem mass spectrometry (LC-HRMS/MS). A. melegueta showed a moderate inhibitory activity against different human pathogenic microbial strains, with H. pylori the most sensitive microorganism. A strong antioxidant and enzyme inhibitory potential was shown in various radical scavenging, reducing and chelating assays as well as in cholinesterase, tyrosinase and glucosidase assays. Several specialized metabolites from A. melegueta (diarylheptanoids, gingerols) were shown to be directly linked with the investigated antioxidant and enzyme inhibitory activities, as evaluated through the correlation analysis. In addition, two diarylheptanoids (one heptan-3-ol and one heptan-3,5-diol) displayed the strongest binding to acetylcholinesterase (AChE) via multiple H-bonds, a couple of π-π interactions and van der Waals interactions all over the catalytic channel of the enzyme, as evidenced by the molecular docking study. Overall, our work brings new contributions to the phyto-complexity and poly-pharmacology of spices from genus Aframomum than can find future applications in pharmaceutical, nutraceutical or cosmeceutical industry.
We introduce the parameter of block elimination distance as a measure of how close a graph is to some particular graph class. Formally, given a graph class G\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {G}}$$\end{document}, the class B(G)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {B}}({\mathcal {G}})$$\end{document} contains all graphs whose blocks belong to G\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {G}}$$\end{document} and the class A(G)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {A}}({\mathcal {G}})$$\end{document} contains all graphs where the removal of a vertex creates a graph in G\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {G}}$$\end{document}. Given a hereditary graph class G\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {G}}$$\end{document}, we recursively define G(k)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${{\mathcal {G}}}^{(k)}$$\end{document} so that G(0)=B(G)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {G}}^{(0)}={\mathcal {B}}({\mathcal {G}})$$\end{document} and, if k≥1\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$k\ge 1$$\end{document}, G(k)=B(A(G(k-1)))\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {G}}^{(k)}={\mathcal {B}}({\mathcal {A}}({\mathcal {G}}^{(k-1)}))$$\end{document}. We show that, for every non-trivial hereditary class G\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {G}}$$\end{document}, the problem of deciding whether G∈G(k)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G\in {\mathcal {G}}^{(k)}$$\end{document} is NP-complete. We focus on the case where G\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {G}}$$\end{document} is minor-closed and we study the minor obstruction set of G(k)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {G}}^{(k)}$$\end{document} i.e., the minor-minimal graphs not in G(k)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {G}}^{(k)}$$\end{document}. We prove that the size of the obstructions of G(k)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {G}}^{(k)}$$\end{document} is upper bounded by some explicit function of k and the maximum size of a minor obstruction of G\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {G}}$$\end{document}. This implies that the problem of deciding whether G∈G(k)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G\in {\mathcal {G}}^{(k)}$$\end{document} is constructively fixed parameter tractable, when parameterized by k. Finally, we give two graph operations that generate members of G(k)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {G}}^{(k)}$$\end{document} from members of G(k-1)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {G}}^{(k-1)}$$\end{document} and we prove that this set of operations is complete for the class O\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\mathcal {O}}$$\end{document} of outerplanar graphs.Please check and confirm if the authors Given and Family names have been correctly identified for author znur YaŸar Diner.All authors names have been identified correctly.Please confirm if the corresponding author is correctly identified. Amend if necessary.This is correct
Proper elucidation of drug-target interaction is one of the most significant steps at the early stages of the drug development research. Computer-aided drug design tools have substantial contribution to this stage. In this chapter, we specifically concentrate on the computational methods widely used to develop reversible inhibitors for monoamine oxidase (MAO) isozymes. In this context, current computational techniques in identifying the best drug candidates showing high potency are discussed. The protocols of structure-based drug design methodologies, namely, molecular docking, in silico screening, and molecular dynamics simulations, are presented. Employing case studies of safinamide binding to MAO B, we demonstrate how to use AutoDock 4.2.6 and NAMD software packages.Key wordsDockingMolecular dynamicsMonoamine oxidaseVirtual screening
Reminiscence bump refers to the increased recall of events from adolescence and early adulthood. It is a robust phenomenon for personal events, while the evidence for the bump has been inconsistent for public events. The present study addressed lifespan distributions of public events in a nationally representative sample of adults ( N = 1200) in Turkey. We demonstrated a robust recency effect in the temporal distribution of public event memories. When we examined the bump in the most frequently reported events, the recency effect persisted. The only exception was the bump for the military coup in 1980, a relatively more distant event among the most frequent events. Findings suggested that high-impact events in Turkey’s recent past may overshadow the past events. Inline, we discuss the role of the context and age distribution of the sample to explain the inconsistency in the evidence for the reminiscence bump in public events.
Internet of Mobile Things (IoMT) have become very popular recently. The routing protocol for low power and lossy networks (RPL) is standardized for static topologies. However, mobility is the nature of IoT. Mobility serves as a promising candidate to harness hand‐off time issues, delay in data transmission, overhead, and low packet delivery rate (PDR) effectively. This study presents a comprehensive account of the mobility‐aware RPL‐based routing protocols to validate and compare the experimental results. Remarkably, classification methods are used in many articles. The aim is to introduce significant research efforts to improve RPL objective functions (OF) performance in hand‐off time, PDR, delay, overhead, and so forth. In this regard, a complete analysis of the existing routing protocols in IoMT has been presented to compare the results. The main focus of this study is on approaches that proposed new OFs for supporting mobility in RPL. Two main categories are considered to study RPL‐based routing protocol mechanisms: The mobile and static sink. The related studies on the mobile sink are divided into three groups: Single metric‐based OF, composite metric OF, and hybrid routing protocols. Also, the related works based on the static sink are categorized into four groups: Fuzzy logic‐based OF, trickle timer‐based OF, composite metrics‐based OF, and modification control messages‐based OF approach. This paper presents a detailed comparison of mechanisms in each category. It also highlights the pros, cons, open issues, and evaluated metrics of each paper. Besides, challenges of mobility in the RPL‐based routing protocol mechanism in IoMT for future studies.
The Internet of Things (IoT) enables intelligent and heterogeneous things to access the Internet and subsequently interact and share info. A service management methodology is required by growing IoT applications and the number of services supplied by various objects. Nevertheless, making decisions, finding, and choosing a service is complex. Therefore, numerous techniques are explored in this regard. This paper employed Flower Pollination Algorithm (FPA) for service discovery and selection in IoT. The FPA is a nature-inspired algorithm that mimics flowering plant pollination behavior. Through a hand-over probability, it is possible to adjust the balance between local and global search properly. The survival of the fittest and the optimal reproducing plants regarding numbers are parts of an optimum plant reproduction strategy. These elements are optimization-oriented and constitute the FPA’s basics. The suggested methodology has an excellent performance in minimizing data access time, energy usage and optimizing cost according to simulation findings.
The current refugee regimes (national/international and EUropean) present significant limitations in the ways they deal with refugee flows. However, both refugees and the host societies are able to develop their own agencies and strategies against such confines. This article pieces together the place-making and reterritorialisation efforts of Syrian refugees, the impact of their arrival on and interaction with the local population in the neighbourhoods of Adana in Turkey that has hosted the largest number of Syrian refugees and have become known as ‘Little Aleppo’. The analysis of Syrians’ experiences that emerge in their new settlements sheds new light on the ways in which urban refugees are able to increase their own agency and choose the solution(s) most appropriate to their own particular circumstances by establishing ‘poor-to-poor, peer-to-peer’ contacts, rather than depending on the few choices offered to them through refugee regimes. The locals, in return, are motivated by the newcomers’ presence to reassess their own socio-economic positions and choices in the land of nation states, even though encounters with the refugees may at times elicit negative feelings.
With the galloping progress of the Internet of Things (IoT) and related technologies in multiple facets of science, distribution environments, namely cloud, edge, fog, Internet of Drones (IoD), and Internet of Vehicles (IoV), carry special attention due to their providing a resilient infrastructure in which users can be sure of a secure connection among smart devices in the network. By considering particular parameters which overshadow the resiliency in distributed environments, we found several gaps in the investigated review papers that did not comprehensively touch on significantly related topics as we did. So, based on the resilient and dependable management approaches, we put forward a beneficial evaluation in this regard. As a novel taxonomy of distributed environments, we presented a well-organized classification of distributed systems. At the terminal stage, we selected 37 papers in the research process. We classified our categories into seven divisions and separately investigated each one their main ideas, advantages, challenges, and strategies, checking whether they involved security issues or not, simulation environments, datasets, and their environments to draw a cohesive taxonomy of reliable methods in terms of qualitative in distributed computing environments. This well-performed comparison enables us to evaluate all papers comprehensively and analyze their advantages and drawbacks. The SLR review indicated that security, latency, and fault tolerance are the most frequent parameters utilized in studied papers that show they play pivotal roles in the resiliency management of distributed environments. Most of the articles reviewed were published in 2020 and 2021. Besides, we proposed several future works based on existing deficiencies that can be considered for further studies.
Abstract Quantum-dot cellular automata (QCA) is a field coupling nano-technology that has drawn significant attention for its low power consumption, low area overhead, and achieving a high speed over the CMOS technology. Majority Voter (MV) and QCA Inverter (INV) are the primitive logic in QCA for implementing any QCA circuit. The performance and cost of a QCA circuit directly depend on the number of QCA primitives and their interconnections. Their optimization plays a crucial role in optimizing the QCA logic circuit synthesis. None of the previous works considered elitism in GA, all the optimization objectives (MV, INV and Level), and the redundancy elimination approach. These profound issues lead us to propose a new methodology based on Genetic algorithm (GA) for the cost-effective synthesis of the QCA circuit of the multi-output boolean functions with an arbitrary number of inputs. The proposed method reduces the delay and gate count, where the worstcase delay is minimized in terms of the level. This methodology adapts elitism to preserve the best solutions throughout the intermediate generations. Here, MV, INV, and levels are optimized according to their relative cost factor in a QCA circuit. Moreover, new methodologies are proposed to create the initial population, maintain the variations, and eliminate redundant gates. Simulation results endorse the superiority of the proposed method.
Bilinguals tend to produce more co-speech hand gestures to compensate for reduced communicative proficiency when speaking in their L2. We here investigated L1-Turkish and L2-English speakers’ gesture use in an emotional context. We specifically asked whether and how (1) speakers gestured differently while retelling L1 vs. L2 and positive vs. negative narratives, and (2) gesture production during retellings was associated with speakers’ later subjective emotional intensity ratings of those narratives. We asked 22 participants to read and then retell eight emotion-laden narratives (half positive, half negative; half Turkish, half English). We analyzed gesture frequency during the entire retelling and during emotional speech only (i.e., gestures that co-occur with emotional phrases such as “happy”). Our results showed that participants produced more representational gestures in L2 than in L1, however, they used more representational gestures during emotional content in L1 than in L2. Participants also produced more co-emotional speech gestures when retelling negative than positive narratives, regardless of language, and more beat gestures co-occurring with emotional speech in negative narratives in L1. Furthermore, using more gestures when retelling a narrative was associated with increased emotional intensity ratings for narratives. Overall, these findings suggest that (1) bilinguals might use representational gestures to compensate for reduced linguistic proficiency in their L2, (2) speakers use more gestures to express negative emotional information, particularly during emotional speech, and (3) gesture production may enhance the encoding of emotional information, which subsequently leads to the intensification of emotion perception.
Hepatocellular carcinoma (HCC) is a highly heterogeneous cancer, and resistant to both conventional and targeted chemotherapy. Recently, nonsteroidal anti-inflammatory drugs (NSAIDs) have been shown to decrease the incidence and mortality of different types of cancers. Here, we investigated the cellular bioactivities of a series of triazolothiadiazine derivatives on HCC, which have been previously reported as potent analgesic/anti-inflammatory compounds. From the initially tested 32 triazolothiadiazine NSAID derivatives, 3 compounds were selected based on their IC50 values for further molecular assays on 9 different HCC cell lines. 7b, which was the most potent compound, induced G2/M phase cell cycle arrest and apoptosis in HCC cells. Cell death was due to oxidative stress-induced JNK protein activation, which involved the dynamic involvement of ASK1, MKK7, and c-Jun proteins. Moreover, 7b treated nude mice had a significantly decreased tumor volume and prolonged disease-free survival. 7b also inhibited the migration of HCC cells and enrichment of liver cancer stem cells (LCSCs) alone or in combination with sorafenib. With its ability to act on proliferation, stemness and the migration of HCC cells, 7b can be considered for the therapeutics of HCC, which has an increased incidence rate of ~ 3% annually.
The broad availability of connected and intelligent devices has increased the demand for Internet of Things (IoT) applications that require more intense data storage and processing. However , cloud-based IoT systems are typically located far from end-users and face several issues, including high cloud server load, slow response times, and a lack of global mobility. Some of these flaws can be addressed with edge computing. In addition, node selection helps avoid common difficulties related to IoT, including network lifespan, allocation of resources, and trust in the acquired data by selecting the correct nodes at a suitable period. On the other hand, the IoT's interconnection of edge and blockchain technologies gives a fresh perspective on access control framework design. This article provides a novel node selection approach for blockchain-enabled edge IoT that provides a quick and dependable node selection. Moreover, fuzzy logic to approximation logic was used to manage numerical and linguistic data simultaneously. In addition, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), a powerful tool for examining Multi-Criteria Decision Making (MCDM) problems, is used. The suggested fuzzy-based technique employs three input criteria to select the correct IoT node for a given mission in IoT-edge situations. The outcomes of the experiments indicate that the proposed framework enhances the parameters under consideration.
Söke Plain (Turkey) is one of the two plains where cotton production is the highest in Turkey, the leading country for cotton production in the Mediterranean Basin. The cropping pattern in Söke Plain is dominated by cotton with a ratio of 97%. The overall irrigation scheme is equipped with conventional systems (i.e., surface, furrow) whose efficiency is approximately 50% due to high evaporation and physical losses. Water efficiency improvement in cotton irrigation necessitates a thorough evaluation of the agricultural water management for Söke Plain, a water-scarce region under drought threat. In this paper, a hybrid multi-criteria decision making (MCDM) method is presented for the evaluation and selection of irrigation methods. This process involves various potentially conflicting qualitative and quantitative criteria, therefore, a hybrid MCDM method such as HF-AHP-PROMETHEE II is needed to make decisions. In HF-AHP-PROMETHEE II, “Hesitant Fuzzy Analytic Hierarchy Process” (HF-AHP) is first implemented to determine importance weights of criteria and then “Hesitant Fuzzy Preference Ranking Organization Method for Enriching Evaluations II” (HF-PROMETHEE II) is utilized to assess and rank the irrigation method alternatives. For comparison analysis, HF-AHP-TOPSIS (HF-AHP-Technique for Order Preference by Similarity to Ideal Solution) method is also implemented to the same problem. A case study is presented where five irrigation method alternatives in Söke Plain are assessed by five expert decision-makers (DMs), based on fifteen evaluation criteria. Sprinkler is found to be the first ranked irrigation method among five alternatives with both HF-AHP-PROMETHEE II and HF-AHP-TOPSIS resulting in the same ranking. The selection of this irrigation technique by the expert DMs is compliant with prevailing regional features related to hydrologic, climatic, environmental conditions and with regard to cotton, one of the highest water-consuming crops.
Human microsomal prostaglandin E synthase (mPGES)-1 is a glutathione-dependent membrane-bound enzyme which is involved in the terminal stage of prostaglandin E2 (PGE2) synthesis. It has been well reported as a key target for the discovery of new anti-inflammatory and anti-cancer drugs. Specific inhibitors of mPGES-1 are anticipated to selectively restrain the generation of PGE2 induced by the inflammatory stimuli, without obstructing of the regular biosynthesis of other homeostatic prostanoids. Therefore, the design of mPGES-1 inhibitors can represent a better choice to take control of PGE2 associated diseases, compared with conventional non-steroidal anti-inflammatory drugs and cyclooxygenase (COX) inhibitors, which are known for their serious side effects. Although there is an intensive effort for the identification of mPGES-1 inhibitors, none of the unveiled molecules so far have reached the clinical market. Therefore, the development of novel mPGES-1 inhibitors with proper drug-like properties is still an unmet medical need. As a continuation of our research for the identification of new chemotypes which might inhibit this enzyme, we now report the design and synthesis of 3-aryloxymethyl-5-[(2-oxo-2-arylethyl)sulfanyl]-1,2,4-triazoles and their oxime derivatives as inhibitors of human mPGES-1. All synthesized compounds were characterized by FTIR, ¹H-NMR, ¹³C-NMR (for compounds 12, 14, 15, 26, 27), HMBC (for compounds 6, 7, 8, 16, 19, 23, 28), and MS data. Twenty-four target compounds 7-30 were screened for their mPGES-1/COX-2 inhibitory activities as well as their cytotoxicity. Of these compounds, 20 and 24 showed potent mPGES-1 inhibition by IC50 values of 0.224±0.070 µM and 1.08±0.35 µM, respectively. These two compounds have also been observed to inhibit angiogenesis in matrigel tube formation assay with no toxicity toward HUVEC cells. In silico studies were also held to understand inhibition mechanisms of the most active compounds using molecular docking, molecular dynamics calculations and ADMET predictions.
In recent years, there have been dramatic changes in manufacturing systems in many industries depending on technological developments. Robotics is one of the essential components of these changes. Today, the usage of robotics in manufacturing processes has become widespread in almost all industries. Also, it has become a very strong desire ever-increasing for even small and medium-sized enterprises at present. Almost all the previous studies emphasized that industrial robot selection is a highly complex decision-making problem as there are many conflicting factors and criteria. Besides, different and advanced specifications of these robotics added by robotic manufacturers have caused to increase the complexities much more. Hence, decision-makers encounter more complicated decision-making problems affected by many uncertainties. Because of that, an integrated fuzzy group MCDM framework can help overcome many ambiguities proposed in the current paper. The proposed fuzzy integrated model consists of the fuzzy SWARA(F-SWARA’B) and the fuzzy CoCoSo (F-CoCoSo'B), which are extended with the help of the Bonferroni function. The model selected the appropriate industrial robotics used in the automotive industry by considering 15 criteria and ten alternatives. According to the result of the study, the three most significant criteria have been determined: Working Accuracy, Reaching Distance, and Performance; and the most suitable option is the A8. The obtained results were validated with the help of a comprehensive sensitivity analysis consisting of different 150 scenarios. The results are also compared with some existing techniques. The sensitivity analysis results approve the validity and applicability of the proposed model.
Advertisements are one of the most important way for companies to access their customers. In this context, televison commercials are gaining significant importance in many sectors daily, and it is crucial for companies to promote their products in the best way. This creates a big rivalry between companies. From this point of view, we have created an IPTV Framework that can automatically detect commercials of rival companies and replace them with desired commercials for companies to help them highlight their products to their customers. We have benefited from monochrome frames to detect the Livestream commercial block and proposed a fingerprint algorithm to create an automatic commercial database. We can easily recognize the commercials, and we can mask the commercials of rival companies with these techniques. We have tested our algorithm in real-time by streaming a recorded broadcast from a server of a specific TV channel. Experimental results show that our algorithm provides high accuracy in real-time commercial recognition.
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