Evaluation and Improvement of Nuclear Security Measures at a Radiological Facility in Morocco

Nuclear security combines both concepts of physical security and security culture within a nuclear facility to protect people, property, society and the environment from harmful effects of ionization radiation. Physical security means prevention, detection, and response to unauthorized removal, sabotage, and/or illegal transfer involving radioactive sources and nuclear material. Nuclear security culture is the human factor within the nuclear field which is considered a principal means to support and enhance nuclear security system. This paper presents a study of nuclear security system already established within a radiological facility considering concepts such as: deter, detect, delay, and response layers. This study focuses on nuclear security culture in order to assess, improve, and complement existing nuclear security practices

Numerical Study of Internal Radius Effect on Mechanical Behavior of P265GH Material

In metallic structures, cracks are mostly initiated at geometric discontinuities of notches or defects. The geometric parameters and discontinuities govern cracks initiation or propagation and therefore affect the resistance of structures during their use. In industry, for economic or security reasons it is seek to know the degree of defects harmfulness and residual life time of structures; This requires the development of models based on fracture mechanics.The objective of this paper is to establish a numerical finite element modeling for a bent specimen using CASTEM2013 computer code. The studied material is P265GH steel commonly used in sheet form in boilers and pressure vessels.The results show that the propagation velocity of crack and stress concentration coefficient increases by increasing the length of the crack and the diameter of the structure

A Numerical Study of the Damage Mechanisms for CT Tensile Specimens of P265GH Steel Material

The aim of this paper is to determine the damage mechanisms of P265GH steel, commonly used for pressure equipment. First, an experimental study using tensile and Charpy tests allowed us to determine the mechanical properties (Young modulus E = 200 GPa, elongation ε = 35%, yield se = 320 MPa, ultimate stress su = 470 MPa, and KIC = 96 MP√m). Then, numerical finite element modeling on a CT specimen using the CASTEM calculation code allowed us to determine the damage of the material when the notch depth varies. The analysis of the results shows that the numerical values of the stress concentration coefficient Kt and the stress intensity factor KI are comparable with the analytically calculated values, thus validating our numerical study. The numerical results obtained revealed that the maximum stress σmax is located in the vicinity of the notch bottom and the high probability density corresponds to a high loading level

Analyzing the Global Big Data Maturity Model Domains for Better Adoption of Big Data Projects

For many years now, big data has revolutionized the world. Today, companies know that creating the most value from their data is essential for their growth. However, not all big data projects are successful; in fact, it is fundamental for companies to make the correct assessment of their capabilities and identify the potential problems to address before the starting point, and this is through maturity models. In previous work, we proposed a new Maturity Model and its framework to track companies’ progress toward successful big data implementation. We identified and categorized the factors influencing big data projects into six categories: strategy alignment, data, people, governance, technology, and methodology. The model provided a final score representing the readiness level for an organization to start its big data implementation. In this paper, we focus specifically on the Global Big Data Maturity assessment tool results. We analyze the importance of maturity domains and detail the final score calculation method using the AHP technique. For this research, we reached out to nineteen North African companies’ big data experts to give us input about their ongoing projects, and the steps are: (1) Collect nineteen big data expert’s ranks for each maturity domain using online forms; (2) Use these ranks alongside the Analytic Hierarchy Process method to have the domain’s weights, which were [0.173, 0.278, 0.128; 0.190; 0.064; 0.166], respectively for the domains [strategy alignment, data, people, governance, technology, and methodology]; Then (3) use the domain’s weights alongside assessment inputs, to calculate accurate weighted scores. As a result, AHP ranks show that the data dimension has the most impact on big data projects’ success, followed by strategy, methodology, governance, people, and, last but not least, technology. The framework dashboards show that most interviewed North African companies have great big data maturity levels

Case Study of Bacterial Decontamination of an Aromatic and Medicinal Plant: Decontamination of Thymus Satureioides by Gamma Radiation at Low Doses and Impact on Hygienic and Physicochemical Quality

The purpose of our study is to verify the usefulness of gamma irradiation treatment at low doses (0.25, 0.5 and 1 kGy) combined to vacuum packaging on commercial teas of Thymus satureioides deliberately contaminated with Escherichia coli. The efficiency and the influence of the process on contamination level and the shelf life of the product were studied. The phenolic composition and concentration were identified in the unirradiated and irradiated thyme. The total phenolic content (TPC) was assayed by the Folin-Ciocalteu method, the individual phenolic compounds were determined by high liquid chromatography (HPLC) and the essential oil was characterized by gas chromatography coupled to mass spectroscopy (GC-MS). The plant was observed by scanning electrons microscopy and the radioactivity effect was analyzed. The results show a complete decontamination of thyme depending to the dose and the storage time. Privileged hygienic quality was found in the irradiated thyme with the highest concentrations of polyphenols. The process showed the conservation of thyme quality without any alteration of its characteristics or radioactivity effect

Native incorporation of outer membrane proteins into vesicles suitable for high resolution NMR spectroscopy

Nuclear Magnetic Resonance spectroscopy is a powerful tool for studying the structure and dynamics of membrane proteins. The method has mainly been used for membrane proteins solubilized in detergent or embedded in membrane mimetic systems. Detergents/membrane mimetics do not ensure glycolipid polarity and native lipid distribution, resulting in the questionable biological relevance of data. Therefore, the aim of this project was to develop a method for collection of Nuclear Magnetic Resonance data from membrane proteins in a native lipid architecture. To achieve this, we use a special Escherichia coli strain that was engineered to shed off its outer membrane at a high rate. The protein of interest is designed with a translocation-tag that takes it to the outer membrane and is concomitantly shed-off during growth and expression. The vesicle-membrane is then precipitated directly from bacterial culture media, resuspended in buffer and concentrated. Nuclear Magnetic Resonance spectroscopy can be directly performed on the sample or it can be stored for later use. We could show the success of the method using a model protein (OmpW) by measuring Nuclear Magnetic Resonance spectra from OmpW containing vesicles as well as from OmpW in detergent micelles. This method has the potential to significantly shape future structural and dynamic studies of membrane proteins and is likely going to have a huge impact on our understanding of host-pathogen interactions and drug development at a molecular level

Native incorporation of outer membrane proteins into vesicles suitable for high resolution NMR spectroscopy

Nuclear Magnetic Resonance spectroscopy is a powerful tool for studying the structure and dynamics of membrane proteins. The method has mainly been used for membrane proteins solubilized in detergent or embedded in membrane mimetic systems. Detergents/membrane mimetics do not ensure glycolipid polarity and native lipid distribution, resulting in the questionable biological relevance of data. Therefore, the aim of this project was to develop a method for collection of Nuclear Magnetic Resonance data from membrane proteins in a native lipid architecture. To achieve this, we use a special Escherichia coli strain that was engineered to shed off its outer membrane at a high rate. The protein of interest is designed with a translocation-tag that takes it to the outer membrane and is concomitantly shed-off during growth and expression. The vesicle-membrane is then precipitated directly from bacterial culture media, resuspended in buffer and concentrated. Nuclear Magnetic Resonance spectroscopy can be directly performed on the sample or it can be stored for later use. We could show the success of the method using a model protein (OmpW) by measuring Nuclear Magnetic Resonance spectra from OmpW containing vesicles as well as from OmpW in detergent micelles. This method has the potential to significantly shape future structural and dynamic studies of membrane proteins and is likely going to have a huge impact on our understanding of host-pathogen interactions and drug development at a molecular level

Solution nuclear magnetic resonance spectroscopy of bacterial outer membrane proteins in natively excreted vesicles using engineered Escherichia coli

Gaining structural information on membrane proteins in their native lipid environment is a long-standing challenge in molecular biology. Instead, it is common to employ membrane mimetics, which has been shown to affect protein structure, dynamics, and function severely. Here, we describe the incorporation of a bacterial outer membrane protein (OmpW) into natively excreted membrane vesicles for solution nuclear magnetic resonance (NMR) spectroscopy using a mutant Escherichia coli strain with a high outer membrane vesicle (OMV) production rate. We collected NMR spectra from both vesicles containing overexpressed OmpW and vesicles from a control strain to account for the presence of physiologically relevant outer membrane proteins in vesicles and observed distinct resonance signals from OmpW. Due to the increased production of OMVs and the use of non-uniform sampling techniques we were able to obtain high-resolution 2D (HSQC) and 3D (HNCO) NMR spectra of our target protein inside its native lipid environment. While this workflow is not yet sufficient to achieve in situ structure determination, our results pave the way for further research on vesicle-based solution NMR spectroscopy

An End-to-End Reliability Framework of the Internet of Things

The Internet of Things (IoT) paradigm feeds from many scientific and engineering fields. This involves a diversity and heterogeneity of its underlying systems. When considering End-to-End IoT systems, we can identify the emergence of new classes of problems. The best-known ones are those associated to standardization for better interoperability and compatibility of those systems, and those who gave birth of new paradigms like that of Fog Computing. Predicting the reliability of an End-to-End IoT system is a problem belonging to this category. On one hand, predicting reliability can be mandatory, most times, before the deployment stage. On another hand, it may help engineers at the design and the operational stages to establish effective maintenance policies and may provide the various stakeholders and decision-makers a means to take the relevant actions. We can find in the literature works which consider only fragments of End-to-End IoT systems such as those assessing reliability for Wireless Sensors Networks (WSN) or Cloud subsystems, to cite just a few. Some other works are specific to well-defined industries, like those targeting reliability study of E-health and Smart-Grid infrastructures. Works that aims to assess reliability for an End-to-End IoT system are remarkably rare and particularly restrained in terms of expressiveness, flexibility, and in their implementation time complexity. In this paper, we apply the Reliability Block Diagram (RBD) paradigm to set up a framework for End-to-End IoT system reliability modeling and analysis. Our contribution is four-fold: we propose an IoT network-based layered architecture, we model in depth each layer of the proposed architecture, we suggest a flow chart to deploy the proposed framework, and we perform a numerical investigation of simplified scenarios. We affirm that the proposed framework is expressive, flexible, and scalable. The numerical study reveals mission time intervals which characterize the behavior of an IoT system from the point of view of its reliability

Influence of Detergent and Lipid Composition on Reconstituted Membrane Proteins for Structural Studies

Membrane proteins are frequently reconstituted in different detergents as a prerequisite to create a phospholipid environment reminiscent of their native environment. Different detergent characteristics such as their chain length and bond types could affect the structure and function of proteins. Yet, they are seldom taken into account when choosing a detergent for structural studies. Here, we explore the effect of different detergents and lipids with varying degrees of double- or single-bond composition on H-1-N-15 transverse relaxation optimized spectroscopy spectra of the outer membrane protein W (OmpW). We observed changes in nuclear magnetic resonance chemical shifts for OmpW reconstituted in micelles, bicelles, and nanodiscs, depending on their detergent/lipid composition. These results suggest that a careful evaluation of detergents is necessary, so as not to jeopardize the structure and function of the protein