Search results for: real number sequences

Authors: Lidia Lombardi

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Waste management in Europe and North America is evolving towards sustainable materials management, intended as a systemic approach to using and reusing materials more productively over their entire life cycles. Various waste management strategies are prioritized and ranked from the most to the least environmentally preferred, placing emphasis on reducing, reusing, and recycling as key to sustainable materials management. However, non-recyclable materials must also be appropriately addressed, and waste-to-energy (WtE) offers a solution to manage them, especially when a WtE plant is integrated within a complex system of waste and wastewater treatment plants and potential users of the output flows. To evaluate the environmental effects of such system integration, Life Cycle Assessment (LCA) is a helpful and powerful tool. LCA has been largely applied to the waste management sector, dating back to the late 1990s, producing a large number of theoretical studies and applications to the real world as support to waste management planning. However, LCA still has a fundamental role in helping the development of waste management systems supporting decisions. Thus, LCA was applied to evaluate the environmental performances of a Municipal Solid Waste (MSW) management system, with improved separate material collection and recycling and an integrated network of treatment plants including WtE, anaerobic digestion (AD) and also wastewater treatment plant (WWTP), for a reference study case area. The proposed system was compared to the actual situation, characterized by poor recycling, large landfilling and absence of WtE. The LCA results showed that the increased recycling significantly increases the environmental performances, but there is still room for improvement through the introduction of energy recovery (especially by WtE) and through its use within the system, for instance, by feeding the heat to the AD, to sludge recovery processes and supporting the water reuse practice. WtE offers a solution to manage non-recyclable MSW and allows saving important resources (such as landfill volumes and non-renewable energy), reducing the contribution to global warming, and providing an essential contribution to fulfill the goals of really sustainable waste management.

Keywords: anaerobic digestion, life cycle assessment, waste-to-energy, municipal solid waste

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Authors: Muhammad Umer, Aishwariya Giri, Umaiyma Rakha

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Mimicked from the humpback whale flippers, the application of tubercle technology is seen to be particularly advantageous at high angles of attack. This particular advantage is of paramount importance when it comes to structures producing lift at high angles of attack. This characteristic of the technology makes it ideal for horizontal stabilizers and selecting the same as the subject of study to identify and exploit the advantage highlighted by researchers on airfoils, this project aims in establishing a foundation for the application of the bio-mimicked technology on an existing aircraft. Using a baseline and 2 tubercle configuration integrated models, the project targets to achieve the twin aim of highlighting the possibility and merits over the base model and also choosing the right configuration in providing the best characteristic suitable for high angles of attack. To facilitate this study, the required models are generated using Solidworks followed by trials in a virtual aerodynamic environment using Fluent in Ansys for resolving the project objectives. Following a structured plan, the aim is to initially identify the advantages mathematically and then selecting the optimal configuration, simulate the end configuration at angles mimicking the actual operation envelope for the particular structure. Upon simulating the baseline configuration at various angles of attack, the stall angle was determined to be 22 degrees. Thus, the tubercle configurations will be simulated and compared at 4 different angles of attacks: 0, 10, 20, and 24. Further, after providing the optimum configuration of horizontal stabilizers, this study aims at the integration of aircraft structure so that the results better imply the end deliverables of real life application. This draws the project scope closer at this point into longitudinal static stability considerations and improvements in the manoeuvrability characteristics. The objective of the study is to achieve a complete overview ready for real life application with marked benefits obtainable from bio morphing of the tubercle technology.

Keywords: flow simulation, horizontal stabilizer, stability enhancement, tubercle

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Authors: Annet Namusoke, Annet Namayanja, Peter Wasswa, Shakirah Nampijja

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Common bean cultivar G2333 which offers broad resistance for anthracnose has been widely used as a source of resistance in breeding for anthracnose resistance. The cultivar is pyramided with three genes namely CO-4, CO-5 and CO-7 and of these three genes, the CO-4 gene has been found to offer the broadest resistance. The main aim of this work was to identify and validate easily assayable PCR based co-dominant molecular markers for selection of the CO-4 gene in segregating populations derived from crosses of G2333 with RWR 1946 and RWR 2075, two commercial Andean cultivars highly susceptible to anthracnose. Marker sequences for the study were obtained by blasting the sequence of the COK-4 gene in the Phaseolus gene database. Primer sequence pairs that were not provided from the Phaseolus gene database were designed by the use of Primer3 software. PCR conditions were optimized and the PCR products were run on 6% HPAGE gel. Results of the polymorphism test indicated that out of 18 identified markers, only two markers namely BM588 and BM211 behaved co-dominantly. Phenotypic evaluation for reaction to anthracnose disease was done by inoculating 21days old seedlings of three parents, F1 and F2 populations with race 7 of Colletotrichum lindemuthianum in the humid chamber. DNA testing of the BM588 marker onto the F2 segregating population of the crosses RWR 1946 x G 2333 and RWR 2075 x G2333 further revealed that the marker BM588 co-segregated with disease resistance with co-dominance of two alleles of 200bp and 400bp, fitting the expected segregation ratio of 1:2:1. The BM588 marker was significantly associated with disease resistance and gave promising results for marker assisted selection of the CO-4 gene in the breeding lines. Activities to validate the BM211 marker are also underway.

Keywords: codominant, Colletotrichum lindemuthianum, MAS, Phaseolus vulgaris

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Authors: Walaa Diab, Baher Atlam, Nadia El Nimer

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Egypt faces many obvious economic challenges, and it is so clear that a real economic transformation is needed to address those problems, especially after the recent decisions of floating the Egyptian pound and the gradual subsidy cuts that are trying to meet the needed conditions to get the IMF support of (a £12bn loan) for its economic reform program. Following the post-2008 revival of the interest in the fiscal policy and its vital role in speeding up or slowing down the economic growth. Here comes the value of this paper as it seeks to analyze the macroeconomic effects of fiscal policy in Egypt by applying A Bayesian SVAR Approach. The study uses the Bayesian method because it includes the prior information and no relevant information is omitted and so it is well suited for rational, evidence-based decision-making. Since the study aims to define the effects of fiscal policy shocks in Egypt to help the decision-makers in determining the proper means to correct the structural problems in the Egyptian economy, it has to study the period of 1990s economic reform, but unfortunately; the available data is on an annual frequency. Thus, it uses annual time series to study the period 1991: 2005 And quarterly data over the period 2006–2016. It uses a set of six main variables includes government expenditure and net tax revenues as fiscal policy arms affecting real GDP, unemployment, inflation and the interest rate. The study also tries to assess the 'crowding out' effects by considering the effects of government spending and government revenue shocks on the composition of GDP, namely, on private consumption and private investment. Last but not least the study provides its policy implications regarding the needed role of fiscal policy in Egypt in the upcoming economic reform building on the results it concludes from the previous reform program.

Keywords: fiscal policy, government spending, structural vector autoregression, taxation

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Authors: Salma Parvin, M. A. Alim

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The convective and radiative heat transfer performance and entropy generation on forced convection through a direct absorption solar collector (DASC) is investigated numerically. Four different fluids, including Cu-water nanofluid, Al₂O₃-waternanofluid, TiO₂-waternanofluid, and pure water are used as the working fluid. Entropy production has been taken into account in addition to the collector efficiency and heat transfer enhancement. Penalty finite element method with Galerkin’s weighted residual technique is used to solve the governing non-linear partial differential equations. Numerical simulations are performed for the variation of mass flow rate. The outcomes are presented in the form of isotherms, average output temperature, the average Nusselt number, collector efficiency, average entropy generation, and Bejan number. The results present that the rate of heat transfer and collector efficiency enhance significantly for raising the values of m up to a certain range.

Keywords: DASC, forced convection, mass flow rate, nanofluid

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Authors: Jean Berger, Mohamed Barkaoui

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Discrete search path planning in time-constrained uncertain environment relying upon imperfect sensors is known to be hard, and current problem-solving techniques proposed so far to compute near real-time efficient path plans are mainly bounded to provide a few move solutions. A new information-theoretic –based open-loop decision model explicitly incorporating false alarm sensor readings, to solve a single agent military logistics search-and-delivery path planning problem with anticipated feedback is presented. The decision model consists in minimizing expected entropy considering anticipated possible observation outcomes over a given time horizon. The model captures uncertainty associated with observation events for all possible scenarios. Entropy represents a measure of uncertainty about the searched target location. Feedback information resulting from possible sensor observations outcomes along the projected path plan is exploited to update anticipated unit target occupancy beliefs. For the first time, a compact belief update formulation is generalized to explicitly include false positive observation events that may occur during plan execution. A novel genetic algorithm is then proposed to efficiently solve search path planning, providing near-optimal solutions for practical realistic problem instances. Given the run-time performance of the algorithm, natural extension to a closed-loop environment to progressively integrate real visit outcomes on a rolling time horizon can be easily envisioned. Computational results show the value of the approach in comparison to alternate heuristics.

Keywords: search path planning, false alarm, search-and-delivery, entropy, genetic algorithm

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Authors: Navneet Kaur, Amarpreet Singh

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In Vehicular Adhoc Networks, Data Dissemination is a challenging task. There are number of techniques, types and protocols available for disseminating the data but in order to preserve limited bandwidth and to disseminate maximum data over networks makes it more challenging. There are broadcasting, multicasting and geocasting based protocols. Multicasting based protocols are found to be best for conserving the bandwidth. One such protocol named BEAM exists that improves the performance of Vehicular Adhoc Networks by reducing the number of in-network message transactions and thereby efficiently utilizing the bandwidth during an emergency situation. But this protocol may result in multicar chain collision as there was no V2V communication. So, this paper proposes a new protocol named Enhanced Bandwidth Efficient Cluster Based Multicasting Protocol (EBECM) that will overcome the limitations of existing BEAM protocol. And Simulation results will show the improved performance of EBECM in terms of Routing overhead, throughput and PDR when compared with BEAM protocol.

Keywords: BEAM, data dissemination, emergency situation, vehicular adhoc network

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Authors: C. W. F. Che Wan Putra, M. Alshawi, M. S. Al Ahbabi, M. Jabakhanji

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The construction industry is a multi-disciplinary and multi-national industry, which has an important role to play within the overall economy of any country. There are major challenges to an improved performance within the industry. Particularly lacking is, the ability to capture the large amounts of information generated during the life-cycle of projects and to make these available, in the right format, so that professionals can then evaluate alternative solutions based on life-cycle analysis. The fragmented nature of the industry is the main reason behind the unavailability and ill utilisation of project information. The lack of adequately engaging clients and managing their requirements contributes adversely to construction budget and schedule overruns. This is a difficult task to achieve, particularly if clients are not continuously and formally involved in the design and construction process, which means that the design intent is left to designers that may not always satisfy clients’ requirements. Client lead is strongly recognised in bringing change through better collaboration between project stakeholders. However, one of the major challenges is that collaboration is operated under conventional procurement methods, which hugely limit the stakeholders’ roles and responsibilities to bring about the required level of collaboration. A research has been conducted with a typical project in the UAE. A qualitative research work was conducted including semi-structured interviews with project partners to discover the real reasons behind this delay. The case study also investigated the real causes of the problems and if they can be adequately addressed by BIM and IPD. Special focus was also placed on the Client leadership and the role the Client can play to eliminate/minimize these problems. It was found that part of the ‘key elements’ from which the problems exist can be attributed to the client leadership and the collaborative environment and BIM.

Keywords: client leadership, building information modelling (BIM), integrated project delivery (IPD), case study

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Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

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Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

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Authors: Junfeng Yan, Wenkui Hou

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Prognostics and Health Management (PHM) is a technology to monitor the equipment status and predict impending faults. It is used to predict the potential fault and provide fault information and track trends of system degradation by capturing characteristics signals. So how to detect characteristics signals is very important. The select of test point plays a very important role in detecting characteristics signal. Traditionally, we use dependency model to select the test point containing the most detecting information. But, facing the large complicated system, the dependency model is not built so easily sometimes and the greater trouble is how to calculate the matrix. Rely on this premise, the paper provide a highly effective method to select test point without dependency model. Because signal flow model is a diagnosis model based on failure mode, which focuses on system’s failure mode and the dependency relationship between the test points and faults. In the signal flow model, a fault information can flow from the beginning to the end. According to the signal flow model, we can find out location and structure information of every test point and module. We break the signal flow model up into serial and parallel parts to obtain the final relationship function between the system’s testability or prediction metrics and test points. Further, through the partial derivatives operation, we can obtain every test point’s importance degree in determining the testability metrics, such as undetected rate, false alarm rate, untrusted rate. This contributes to installing the test point according to the real requirement and also provides a solid foundation for the Prognostics and Health Management. According to the real effect of the practical engineering application, the method is very efficient.

Keywords: false alarm rate, importance degree, signal flow model, undetected rate, untrusted rate

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Authors: Titis Indah Adi Rahayu

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Angiogenesis is the process of generating new capillary from pre-existing blood vessels. VEGFA is a major regulator in angiogenesis that binds and activates two tyrosine kinase receptors, VEGFR1 (Flt-1) and VEGFR2 (Flk-1/KDR) which regulate pathological and physiological angiogenesis. Disruption of VEGFA and VEGFR2 regulation lead to many diseases. The study of α-Mangostin (derivate of xanthone) as anti-oxidant and anti inflammation has been explored recently and both of them have relation to vasculature however the effect of α-Mangostin in blood vessel formation in healthy tissue in vivo has not been studied. Zebrafish is a powerful model in studying angiogenesis and shared many advantages that is a viable whole animal model for screening small molecules that affect blood vessel formation. Therefore the aim of this study is to evaluate angiogenic activity of α-Mangostin in healthy tissue in vivo in zebrafish embryo in relation of patterning blood vessel. Blood vessel patterning is highly characteristic in the developing of zebrafish embryo and the subintestinal vessel (SIV) can be stained and visualized microscopically as a primary screen for α-Mangostin that effect angiogenesis. The zebrafish embryos are divided into 2 groups. Group one consists of the zebrafish embryos at 1 dpf for 4 days which are tested to α-Mangostin in several concentration 2 µM, 4 µM, 6 µM, 8 µM and 10 µM whereas in group two the zebrafish larva at 4 dpf are exposed to α-Mangostin 1,75 µM, 2,3 µM, 2,9 µM, 3,8 µM dan 5 µM for 2 days. DMSO is served as a control for each group. The level expression of vegfa and vegfr2 are observed quantitatively using real time q-PCR and patterning of SIV are then analized via alkaline phospatase staining. Result shows that the level expression of vegfa and vegfr2 is repressed quantitatively as shown in real time q-PCR in the group of 1-4 days of α-Mangostin exposure where it is increased in the group of 4-6 days of α-Mangostin exposure. The result is then compared to alkaline phospatase staining of SIV using stereo microscope. It indicates that α-Mangostin does not disturb the patterning of SIV formation in zebrafish.

Keywords: angiogenesis, Danio rerio, α-Mangostin, SIV, vegfa, vegfr2

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Authors: Mahesh M. Patil, K. A. Anu-Appaiah

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Overweight and obesity is a serious medical problem, increasing in prevalence, and affecting millions worldwide. Investigators have been trying from decades to articulate the burden of obesity and related risk factors. To answer this problem, we suggest a new therapeutic anti-obesity compounds from Garcinia xanthochymus fruit. However, there is little published scientific information on non-hydroxycitric acid Garcinia species. Our findings include biochemical characterization of the fruit; in vivo toxicity and bio-efficacy study of G. xanthochymus in high fat diet wistar rat model. We observed that Garcinia pericarp is a rich source of organic acids, polyphenols, mono- (40.63%) and poly-unsaturated fatty acids (16.45%; omega-3: 10.02%). Toxicological studies have showed that Garcinia is safe and had no observed adverse effect level up to 400 mg/kg/day. Body weight and food intake was significantly (P<0.05) reduced in oral gavage treated rats (sonicated Garcinia powder) in 13 weeks. Subcutaneous fat was significantly (P<0.05) reduced in Garcinia treated rats. Hepatocytes significantly (p<0.05) overexpressed sterol regulatory element binding protein 2, liver X receptor- α, liver X receptor- β, lipoprotein lipase and monoacylglycerol lipase. Fatty acid binding protein 1 and peroxisome proliferator activated receptor- α were down regulated as assessed by real time qPCR. Currently our research is focused on the adipocyte obesity related gene expressions, effect of Garcinia on 3T3-adipocyte cell lines and high fat diet induced mice model. This in vivo pre-clinical data suggests that G. xanthochymus may have clinical utility for the treatment of obesity. However, further studies are required to establish its potency.

Keywords: Garcinia xanthochymus, anti-obesity, high fat diet, real time qPCR

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Authors: Pamita Awasthi, Kirna, Shilpa Dogra, Manu Vatsal, Ritu Barthwal

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Doxorubicin, also known as adriamycin, is an anthracycline class of drug used in cancer chemotherapy. It is used in the treatment of non-Hodgkin’s lymphoma, multiple myeloma, acute leukemias, breast cancer, lung cancer, endometrium cancer and ovary cancers. It functions via intercalating DNA and ultimately killing cancer cells. The major side effects of doxorubicin are hair loss, myelosuppression, nausea & vomiting, oesophagitis, diarrhoea, heart damage and liver dysfunction. The minor modifications in the structure of compound exhibit large variation in the biological activity, has prompted us to carry out the synthesis of sulfonamide derivatives. Sulfonamide is an important feature with broad spectrum of biological activity such as antiviral, antifungal, diuretics, anti-inflammatory, antibacterial and anticancer activities. Structure of the synthesized compound N-(1-methyl-2-oxo-2-N-methyl anilino-ethyl)benzene sulfonamide confirmed by proton nuclear magnetic resonance (1H NMR),13C NMR, Mass and FTIR spectroscopic tools to assure the position of all protons and hence stereochemistry of the molecule. Further we have reported the binding potential of synthesized sulfonamide analogues in comparison to doxorubicin drug using Auto Dock 4.2 software. Computational binding energy (B.E.) and inhibitory constant (Ki) has been evaluated for the synthesized compound in comparison of doxorubicin against Poly (dA-dT).Poly (dA-dT) and Poly (dG-dC).Poly (dG-dC) sequences. The in vitro cytotoxic study against human breast cancer cell lines confirms the better anticancer activity of the synthesized compound over currently in use anticancer drug doxorubicin. The IC50 value of the synthesized compound is 7.12 µM where as for doxorubicin is 7.2 µ.

Keywords: Doxorubicin, auto dock, in silco, in vitro

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Authors: S. Fahiminiya, J. Nadaf, F. Rauch, L. Jerome-Majewska, J. Majewski

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Background: Sequencing of protein coding regions of human genome (Whole Exome Sequencing; WES), has demonstrated a great success in the identification of causal mutations for several rare genetic disorders in human. Generally, most of WES studies have focused on rare variants in coding exons and splicing-sites where missense substitutions lead to the alternation of protein product. Although focusing on this category of variants has revealed the mystery behind many inherited genetic diseases in recent years, a subset of them remained still inconclusive. Here, we present the result of our WES studies where analyzing only rare variants in coding regions was not conclusive but further investigation revealed the involvement of non-coding variants and copy number variations (CNV) in etiology of the diseases. Methods: Whole exome sequencing was performed using our standard protocols at Genome Quebec Innovation Center, Montreal, Canada. All bioinformatics analyses were done using in-house WES pipeline. Results: To date, we successfully identified several disease causing mutations within gene coding regions (e.g. SCARF2: Van den Ende-Gupta syndrome and SNAP29: 22q11.2 deletion syndrome) by using WES. In addition, we showed that variants in non-coding regions and CNV have also important value and should not be ignored and/or filtered out along the way of bioinformatics analysis on WES data. For instance, in patients with osteogenesis imperfecta type V and in patients with glucocorticoid deficiency, we identified variants in 5'UTR, resulting in the production of longer or truncating non-functional proteins. Furthermore, CNVs were identified as the main cause of the diseases in patients with metaphyseal dysplasia with maxillary hypoplasia and brachydactyly and in patients with osteogenesis imperfecta type VII. Conclusions: Our study highlights the importance of considering non-coding variants and CNVs during interpretation of WES data, as they can be the only cause of disease under investigation.

Keywords: whole exome sequencing data, non-coding variants, copy number variations, rare diseases

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Authors: Claire Williams

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Randomised controlled Trials (RCTs) of efficacy are still perceived as the gold standard for the generation of evidence, and whilst advances in data collection methods are well developed, this progress has not been matched for the reporting of adverse events (AEs). Assessment and reporting of AEs in clinical trials are fraught with human error and inefficiency and are extremely time and resource intensive. Recent research conducted into the quality of reporting of AEs during clinical trials concluded it is substandard and reporting is inconsistent. Investigators commonly send reports to sponsors who are incorrectly categorised and lacking in critical information, which can complicate the detection of valid safety signals. In our presentation, we will describe an electronic data capture system, which has been designed to support clinical trial processes by reducing the resource burden on investigators, improving overall trial efficiencies, and making trials safer for patients. This proprietary technology was developed using expertise proven in the delivery of the world’s first prospective, phase 3b real-world trial, ‘The Salford Lung Study, ’ which enabled robust safety monitoring and reporting processes to be accomplished by the remote monitoring of patients’ EHRs. This technology enables safety alerts that are pre-defined by the protocol to be detected from the data extracted directly from the patients EHR. Based on study-specific criteria, which are created from the standard definition of a serious adverse event (SAE) and the safety profile of the medicinal product, the system alerts the investigator or study team to the safety alert. Each safety alert will require a clinical review by the investigator or delegate; examples of the types of alerts include hospital admission, death, hepatotoxicity, neutropenia, and acute renal failure. This is achieved in near real-time; safety alerts can be reviewed along with any additional information available to determine whether they meet the protocol-defined criteria for reporting or withdrawal. This active surveillance technology helps reduce the resource burden of the more traditional methods of AE detection for the investigators and study teams and can help eliminate reporting bias. Integration of multiple healthcare data sources enables much more complete and accurate safety data to be collected as part of a trial and can also provide an opportunity to evaluate a drug’s safety profile long-term, in post-trial follow-up. By utilising this robust and proven method for safety monitoring and reporting, a much higher risk of patient cohorts can be enrolled into trials, thus promoting inclusivity and diversity. Broadening eligibility criteria and adopting more inclusive recruitment practices in the later stages of drug development will increase the ability to understand the medicinal products risk-benefit profile across the patient population that is likely to use the product in clinical practice. Furthermore, this ground-breaking approach to AE detection not only provides sponsors with better-quality safety data for their products, but it reduces the resource burden on the investigator and study teams. With the data taken directly from the source, trial costs are reduced, with minimal data validation required and near real-time reporting enables safety concerns and signals to be detected more quickly than in a traditional RCT.

Keywords: more comprehensive and accurate safety data, near real-time safety alerts, reduced resource burden, safer trials

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Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

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The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

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Authors: Israa Sh. Tawfic, Sema Koc Kayhan

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Given a large sparse signal, great wishes are to reconstruct the signal precisely and accurately from lease number of measurements as possible as it could. Although this seems possible by theory, the difficulty is in built an algorithm to perform the accuracy and efficiency of reconstructing. This paper proposes a new proved method to reconstruct sparse signal depend on using new method called Least Support Matching Pursuit (LS-OMP) merge it with the theory of Partial Knowing Support (PSK) given new method called Partially Knowing of Least Support Orthogonal Matching Pursuit (PKLS-OMP). The new methods depend on the greedy algorithm to compute the support which depends on the number of iterations. So to make it faster, the PKLS-OMP adds the idea of partial knowing support of its algorithm. It shows the efficiency, simplicity, and accuracy to get back the original signal if the sampling matrix satisfies the Restricted Isometry Property (RIP). Simulation results also show that it outperforms many algorithms especially for compressible signals.

Keywords: compressed sensing, lest support orthogonal matching pursuit, partial knowing support, restricted isometry property, signal reconstruction

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Authors: Tobias Strübing, Fatemeh Ziaeetabar

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Humans usually manipulate objects with their hands. To represent these actions in a simple and understandable way, we need to use a semantic framework. For this purpose, the Semantic Event Chain (SEC) method has already been presented which is done by consideration of touching and non-touching relations between manipulated objects in a scene. This method was improved by a computational model, the so-called enriched Semantic Event Chain (eSEC), which incorporates the information of static (e.g. top, bottom) and dynamic spatial relations (e.g. moving apart, getting closer) between objects in an action scene. This leads to a better action prediction as well as the ability to distinguish between more actions. Each eSEC manipulation descriptor is a huge matrix with thirty rows and a massive set of the spatial relations between each pair of manipulated objects. The current eSEC framework has so far only been used in the category of manipulation actions, which eventually involve two hands. Here, we would like to extend this approach to a whole body action descriptor and make a conjoint activity representation structure. For this purpose, we need to do a statistical analysis to modify the current eSEC by summarizing while preserving its features, and introduce a new version called Enhanced eSEC or (e2SEC). This summarization can be done from two points of the view: 1) reducing the number of rows in an eSEC matrix, 2) shrinking the set of possible semantic spatial relations. To achieve these, we computed the importance of each matrix row in an statistical way, to see if it is possible to remove a particular one while all manipulations are still distinguishable from each other. On the other hand, we examined which semantic spatial relations can be merged without compromising the unity of the predefined manipulation actions. Therefore by performing the above analyses, we made the new e2SEC framework which has 20% fewer rows, 16.7% less static spatial and 11.1% less dynamic spatial relations. This simplification, while preserving the salient features of a semantic structure in representing actions, has a tremendous impact on the recognition and prediction of complex actions, as well as the interactions between humans and robots. It also creates a comprehensive platform to integrate with the body limbs descriptors and dramatically increases system performance, especially in complex real time applications such as human-robot interaction prediction.

Keywords: enriched semantic event chain, semantic action representation, spatial relations, statistical analysis

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Authors: Youcef Serhane, Abdelkrim Bouzaza, Dominique Wolbert, Aymen Amin Assadi

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Throughout history, the use of chemical weapons is not exclusive to combats between army corps; some of these weapons are also found in very targeted intelligence operations (political assassinations), organized crime, and terrorist organizations. To improve the speed of action, important technological devices have been developed in recent years, in particular in the field of protection and decontamination techniques to better protect and neutralize a chemical threat. In order to assess certain protective, decontaminating technologies or to improve medical countermeasures, tests must be conducted. In view of the great toxicity of toxic chemical agents from (real) wars, simulants can be used, chosen according to the desired application. Here, we present an investigation about using a photocatalytic filtering reactor (PFR) for highly contaminated environments containing diethyl sulfide (DES). This target pollutant is used as a simulant of CWA, namely of Yperite (Mustard Gas). The influence of the inlet concentration (until high concentrations of DES (1200 ppmv, i.e., 5 g/m³ of air) has been studied. Also, the conversion rate was monitored under different relative humidity and different flow rates (respiratory flow - standards: ISO / DIS 8996 and NF EN 14387 + A1). In order to understand the efficacity of pollutant neutralization by PFR, a kinetic model based on the Langmuir–Hinshelwood (L–H) approach and taking into account the mass transfer step was developed. This allows us to determine the adsorption and kinetic degradation constants with no influence of mass transfer. The obtained results confirm that this small configuration of reactor presents an extremely promising way for the use of photocatalysis for treatment to deal with highly contaminated environments containing real chemical warfare agents. Also, they can give birth to an individual protection device (an autonomous cartridge for a gas mask).

Keywords: photocatalysis, photocatalytic filtering reactor, diethylsulfide, chemical warfare agents

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Authors: M. Kouyate, M. Sangare, S. Samake, S. Keita, H. G. Kim, D. H. Geschwind

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Background & Objectives: Human genetic studies can be expensive, even unaffordable, in developing countries, partly due to the sequencing costs. Our aim is to pilot the use of bioinformatics tools to guide scientifically valid, locally relevant, and economically sound autism genetic research in Mali. Methods: The following databases, NCBI, HGMD, and LSDB, were used to identify hot point mutations. Phenotype, transmission pattern, theoretical protein expression in the brain, the impact of the mutation on the 3D structure of the protein) were used to prioritize selected autism genes. We used the protein database, Modeller, and clustal W. Results: We found Mef2c (Gly27Ala/Leu38Gln), Pten (Thr131IIle), Prodh (Leu289Met), Nme1 (Ser120Gly), and Dhcr7 (Pro227Thr/Glu224Lys). These mutations were associated with endonucleases BseRI, NspI, PfrJS2IV, BspGI, BsaBI, and SpoDI, respectively. Gly27Ala/Leu38Gln mutations impacted the 3D structure of the Mef2c protein. Mef2c protein sequences across species showed a high percentage of similarity with a highly conserved MADS domain. Discussion: Mef2c, Pten, Prodh, Nme1, and Dhcr 7 gene mutation frequencies in the Malian population will be very informative. PCR coupled with restriction enzyme digestion can be used to screen the targeted gene mutations. Sanger sequencing will be used for confirmation only. This will cut down considerably the sequencing cost for gene-to-gene mutation screening. The knowledge of the 3D structure and potential impact of the mutations on Mef2c protein informed the protein family and altered function (ex. Leu38Gln). Conclusion & Future Work: Bio-informatics will positively impact autism research in Mali. Our approach can be applied to another neuropsychiatric disorder.

Keywords: bioinformatics, endonucleases, autism, Sanger sequencing, point mutations

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Authors: Ziyue Zeng

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Bacteriophages are viruses which infect bacteria specifically. Over the past decades, phage λ has been extensively studied, especially its interaction with the Escherichia coli LamB (EcLamB) protein receptor. Nonetheless, despite the enormous numbers and near-ubiquity of environmental phages, aside from phage λ, there is a paucity of information on other phages which target EcLamB as a receptor. In this study, to answer the question of whether there are other EcLamB-targeting phages in the natural environment, a simple and convenient method was developed and used for isolating environmental phages which target a particular surface structure of a particular bacterium; in this case, the EcLamB outer membrane protein. From the enrichments with the engineered bacterial hosts, a collection of EcLamB-targeting phages (ΦZZ phages) were easily isolated. Intriguingly, unlike phage λ, an obligate EcLamB-dependent phage in the Siphoviridae family, the newly isolated ΦZZ phages alternatively recognised EcLamB or E. coli OmpC (EcOmpC) as a receptor when infecting E. coli. Furthermore, ΦZZ phages were suggested to represent new species in the Tequatrovirus genus in the Myoviridae family, based on phage morphology and genomic sequences. Most phages are thought to have a narrow host range due to their exquisite specificity in receptor recognition. With the ability to optionally recognise two receptors, ΦZZ phages were considered relatively promiscuous. Via the heterologous expression of EcLamB on the bacterial cell surface, the host range of ΦZZ phages was further extended to three different enterobacterial genera. Besides, an interesting selection of evolved phage mutants with a broader host range was isolated, and the key mutations involved in their evolution to adapt to new hosts were investigated by genomic analysis. Finally, and importantly, two ΦZZ phages were found to be putative generalised transducers, which could be exploited as tools for DNA manipulations.

Keywords: environmental microbiology, phage, microbe-host interactions, microbial ecology

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Authors: H. A. Jawan

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This review describes the models of environmental-related crack propagation of aluminum alloys (7xxx) during the last few decades. Acknowledge on effects of different factors on the susceptibility to SCC permits to propose valuable mechanisms on crack advancement. The reliable mechanism of cracking give a possibility to propose the optimum chemical composition and thermal treatment conditions resulting in microstructure the most suitable for real environmental condition and stress state.

Keywords: microstructure, environmental, propagation, mechanism

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Authors: Andrey V. Khromov, Antonida V. Makhotenko, Ekaterina A. Snigir, Svetlana S. Makarova, Natalia O. Kalinina, Valentin V. Makarov, Mikhail E. Taliansky

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Due to its simplicity, CRISPR/Cas9 has become widely used and capable of inducing mutations in the genes of organisms of various kingdoms. The aim of this work was to develop applications for the efficient modification of DNA coding sequences of phytoene desaturase (PDS), coilin and vacuolar invertase (Solanum tuberosum) genes, and to develop a new nanoparticles carrier efficient technology to deliver the CRISPR/Cas9 system for editing the plant genome. For each of the genes - coilin, PDS and vacuolar invertase, five single RNA guide (sgRNAs) were synthesized. To determine the most suitable nanoplatform, two types of NP platforms were used: magnetic NPs (MNPS) and gold NPs (AuNPs). To test the penetration efficiency, they were functionalized with fluorescent agents - BSA * FITS and GFP, as well as labeled Cy3 small-sized RNA. To measure the efficiency, a fluorescence and confocal microscopy were used. It was shown that the best of these options were AuNP - both in the case of proteins and in the case of RNA. The next step was to check the possibility of delivering components of the CRISPR/Cas9 system to plant cells for editing target genes. AuNPs were functionalized with a ribonucleoprotein complex consisting of Cas9 and corresponding to target genes sgRNAs, and they were biolistically bombarded to axillary buds and apical meristems of potato plants. After the treatment by the best NP carrier, potato meristems were grown to adult plants. DNA isolated from this plants was sent to a preliminary fragment of the analysis to screen out the non-transformed samples, and then to the NGS. The present work was carried out with the financial support from the Russian Science Foundation (grant No. 16-16-04019).

Keywords: biobombardment, coilin, CRISPR/Cas9, nanoparticles, NPs, PDS, sgRNA, vacuolar invertase

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Authors: Abdon Choque-Rivero

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The Jacobi system with the Dirichlet boundary condition is considered on a half-line lattice when the coefficients are real valued. The inverse problem of recovery of the coefficients from various data sets containing the so-called transmission eigenvalues is analyzed. The Marchenko method is utilized to solve the corresponding inverse problem.

Keywords: inverse scattering, discrete system, transmission eigenvalues, Marchenko method

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Authors: Rui Wu

Abstract:

In the volatile modern manufacturing environment, new orders randomly occur at any time, while the pre-emptive methods are infeasible. This leads to a real-time scheduling method that can produce a reasonably good schedule quickly. The dynamic Flexible Job Shop problem is an NP-hard scheduling problem that hybrid the dynamic Job Shop problem with the Parallel Machine problem. A Flexible Job Shop contains different work centres. Each work centre contains parallel machines that can process certain operations. Many algorithms, such as genetic algorithms or simulated annealing, have been proposed to solve the static Flexible Job Shop problems. However, the time efficiency of these methods is low, and these methods are not feasible in a dynamic scheduling problem. Therefore, a dynamic rule selection scheduling system based on the reinforcement learning method is proposed in this research, in which the dynamic Flexible Job Shop problem is divided into several parallel machine problems to decrease the complexity of the dynamic Flexible Job Shop problem. Firstly, the features of jobs, machines, work centres, and flexible job shops are selected to describe the status of the dynamic Flexible Job Shop problem at each decision point in each work centre. Secondly, a framework of reinforcement learning algorithm using a double-layer deep Q-learning network is applied to select proper composite dispatching rules based on the status of each work centre. Then, based on the selected composite dispatching rule, an available operation is selected from the waiting buffer and assigned to an available machine in each work centre. Finally, the proposed algorithm will be compared with well-known dispatching rules on objectives of mean tardiness, mean flow time, mean waiting time, or mean percentage of waiting time in the real-time Flexible Job Shop problem. The result of the simulations proved that the proposed framework has reasonable performance and time efficiency.

Keywords: dynamic scheduling problem, flexible job shop, dispatching rules, deep reinforcement learning

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Authors: Ezgi Kaya, A. Dilek Maden

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A topological index is a number related to graph which is invariant under graph isomorphism. In theoretical chemistry, molecular structure descriptors (also called topological indices) are used for modeling physicochemical, pharmacologic, toxicologic, biological and other properties of chemical compounds. Let G be a graph with n vertices and m edges. For a given edge uv, the quantity nu(e) denotes the number of vertices closer to u than v, the quantity nv(e) is defined analogously. The vertex PI index defined as the sum of the nu(e) and nv(e). Here the sum is taken over all edges of G. The energy of a graph is defined as the sum of the eigenvalues of adjacency matrix of G and the Laplacian energy of a graph is defined as the sum of the absolute value of difference of laplacian eigenvalues and average degree of G. In theoretical chemistry, the π-electron energy of a conjugated carbon molecule, computed using the Hückel theory, coincides with the energy. Hence results on graph energy assume special significance. The Laplacian matrix of a graph G weighted by the vertex PI weighting is the Laplacian vertex PI matrix and the Laplacian vertex PI eigenvalues of a connected graph G are the eigenvalues of its Laplacian vertex PI matrix. In this study, Laplacian vertex PI energy of a graph is defined of G. We also give some bounds for the Laplacian vertex PI energy of graphs in terms of vertex PI index, the sum of the squares of entries in the Laplacian vertex PI matrix and the absolute value of the determinant of the Laplacian vertex PI matrix.

Keywords: energy, Laplacian energy, laplacian vertex PI eigenvalues, Laplacian vertex PI energy, vertex PI index

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Authors: Guram Esakia, Giorgi Goguadze

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The following paper is written due to overview the concept of R2P, this new dimension in International Relations field. Paper contains the general description of previously mentioned concept, its advantages and disadvantages. We also compare each other R2P and“humanitarian intervention“, trying to make clear division between these two approaches in conflict solution. There is also discussed R2P in real action, successful one in Libya and yet failed in Syria. Essay doesn’t claim to be the part of scientific chain and is based only on personal subjection as well on information gathered from various scholars and UN resolutions.

Keywords: the concept of R2P, humanitarian intervention, Libya, Syria

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Authors: Guillaume Craveur

Abstract:

This study shows the opportunity to use numerical tools dedicated to Fire Safety Engineering for the Rolling Stock. Indeed, some lawful requirements can now be demonstrated by using numerical tools. The first part of this study presents the use of modelling evacuation tool to satisfy the criteria of evacuation time for the rolling stock. The buildingEXODUS software is used to model and simulate the evacuation of rolling stock. Firstly, in order to demonstrate the reliability of this tool to calculate the complete evacuation time, a comparative study was achieved between a real test and simulations done with buildingEXODUS. Multiple simulations are performed to capture the stochastic variations in egress times. Then, a new study is done to calculate the complete evacuation time of a train with the same geometry but with a different interior architecture. The second part of this study shows some applications of Computational Fluid Dynamics. This work presents the approach of a multi scales validation of numerical simulations of standardized tests with Fire Dynamics Simulations software developed by the National Institute of Standards and Technology (NIST). This work highlights in first the cone calorimeter test, described in the standard ISO 5660, in order to characterize the fire reaction of materials. The aim of this process is to readjust measurement results from the cone calorimeter test in order to create a data set usable at the seat scale. In the second step, the modelisation concerns the fire seat test described in the standard EN 45545-2. The data set obtained thanks to the validation of the cone calorimeter test was set up in the fire seat test. To conclude with the third step, after controlled the data obtained for the seat from the cone calorimeter test, a larger scale simulation with a real part of train is achieved.

Keywords: fire safety engineering, numerical tools, rolling stock, multi-scales validation

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Authors: Muhammad Naveed Tahir, Wang Yingkuan, Huang Wenjiang, Raheel Osman

Abstract:

Numerous models used in prediction and decision-making process but most of them are linear in natural environment, and linear models reach their limitations with non-linearity in data. Therefore accurate estimation is difficult. Artificial Neural Networks (ANN) found extensive acceptance to address the modeling of the complex real world for the non-linear environment. ANN’s have more general and flexible functional forms than traditional statistical methods can effectively deal with. The link between information technology and agriculture will become more firm in the near future. Monitoring crop biophysical properties non-destructively can provide a rapid and accurate understanding of its response to various environmental influences. Crop chlorophyll content is an important indicator of crop health and therefore the estimation of crop yield. In recent years, remote sensing has been accepted as a robust tool for site-specific management by detecting crop parameters at both local and large scales. The present research combined the ANN model with satellite-derived chlorophyll indices from LANDSAT 8 imagery for predicting real-time wheat chlorophyll estimation. The cloud-free scenes of LANDSAT 8 were acquired (Feb-March 2016-17) at the same time when ground-truthing campaign was performed for chlorophyll estimation by using SPAD-502. Different vegetation indices were derived from LANDSAT 8 imagery using ERADAS Imagine (v.2014) software for chlorophyll determination. The vegetation indices were including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Absorbed Ratio Index (CARI), Modified Chlorophyll Absorbed Ratio Index (MCARI) and Transformed Chlorophyll Absorbed Ratio index (TCARI). For ANN modeling, MATLAB and SPSS (ANN) tools were used. Multilayer Perceptron (MLP) in MATLAB provided very satisfactory results. For training purpose of MLP 61.7% of the data, for validation purpose 28.3% of data and rest 10% of data were used to evaluate and validate the ANN model results. For error evaluation, sum of squares error and relative error were used. ANN model summery showed that sum of squares error of 10.786, the average overall relative error was .099. The MCARI and NDVI were revealed to be more sensitive indices for assessing wheat chlorophyll content with the highest coefficient of determination R²=0.93 and 0.90 respectively. The results suggested that use of high spatial resolution satellite imagery for the retrieval of crop chlorophyll content by using ANN model provides accurate, reliable assessment of crop health status at a larger scale which can help in managing crop nutrition requirement in real time.

Keywords: ANN, chlorophyll content, chlorophyll indices, satellite images, wheat

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Authors: L. Joseph, B. Farid, F. Ravelet

Abstract:

Fundamental studies were performed on bifurcation, instabilities and turbulence in Taylor-Couette flow and applied to many engineering applications like astrophysics models in the accretion disks, shrouded fans, and electric motors. Such rotating machinery performances need to have a better understanding of the fluid flow distribution to quantify the power losses and the heat transfer distribution. The present investigation is focused on high gap ratio of Taylor-Couette flow with high rotational speeds, for smooth and grooved surfaces. So far, few works has been done in a very narrow gap and with very high rotation rates and, to the best of our knowledge, not with this combination with grooved surface. We study numerically the turbulent flow between two coaxial cylinders where R1 and R2 are the inner and outer radii respectively, where only the inner is rotating. The gap between the rotor and the stator varies between 0.5 and 2 mm, which corresponds to a radius ratio η = R1/R2 between 0.96 and 0.99 and an aspect ratio Γ= L/d between 50 and 200, where L is the length of the rotor and d being the gap between the two cylinders. The scaling of the torque with the Reynolds number is determined at different gaps for different smooth and grooved surfaces (and also with different number of grooves). The fluid in the gap is air. Re varies between 8000 and 30000. Another dimensionless parameter that plays an important role in the distinction of the regime of the flow is the Taylor number that corresponds to the ratio between the centrifugal forces and the viscous forces (from 6.7 X 105 to 4.2 X 107). The torque will be first evaluated with RANS and U-RANS models, and compared to empirical models and experimental results. A mesh convergence study has been done for each rotor-stator combination. The results of the torque are compared to different meshes in 2D dimensions. For the smooth surfaces, the models used overestimate the torque compared to the empirical equations that exist in the bibliography. The closest models to the empirical models are those solving the equations near to the wall. The greatest torque achieved with grooved surface. The tangential velocity in the gap was always higher in between the rotor and the stator and not on the wall of rotor. Also the greater one was in the groove in the recirculation zones. In order to avoid endwall effects, long cylinders are used in our setup (100 mm), torque is measured by a co-rotating torquemeter. The rotor is driven by an air turbine of an automotive turbo-compressor for high angular velocities. The results of the experimental measurements are at rotational speed of up to 50 000 rpm. The first experimental results are in agreement with numerical ones. Currently, quantitative study is performed on grooved surface, to determine the effect of number of grooves on the torque, experimentally and numerically.

Keywords: Taylor-Couette flow, high gap ratio, grooved surface, high speed

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