Animal models to study hepatitis C virus infection

With more than 71 million chronically infected people, the hepatitis C virus (HCV) is a major global health concern. Although new direct acting antivirals have significantly improved the rate of HCV cure, high therapy cost, potential emergence of drug-resistant viral variants, and unavailability of a protective vaccine represent challenges for complete HCV eradication. Relevant animal models are required, and additional development remains necessary, to effectively study HCV biology, virus-host interactions and for the evaluation of new antiviral approaches and prophylactic vaccines. The chimpanzee, the only non-human primate susceptible to experimental HCV infection, has been used extensively to study HCV infection, particularly to analyze the innate and adaptive immune response upon infection. However, financial, practical, and especially ethical constraints have urged the exploration of alternative small animal models. These include different types of transgenic mice, immunodeficient mice of which the liver is engrafted with human hepatocytes (humanized mice) and, more recently, immunocompetent rodents that are susceptible to infection with viruses that are closely related to HCV. In this review, we provide an overview of the currently available animal models that have proven valuable for the study of HCV, and discuss their main benefits and weaknesses

EXPLORING THE ECONOMIC AND COMMERCIAL RELATIONS BETWEEN LIBYA AND THE EU: A PERCEPTION ANALYSIS OF LIBYAN BUSINESSMEN

Abstract The Libyan economy is highly dependent on oil export revenues, which allied to a small population, makes Libya one of the richest countries in Africa. In order to diversify its sources of income, the government undertook measures to liberalise its economy and foreign trade. The central strategy of enhancing trade and developing the Libyan economy is to integrate with the EU by taking a pro-active part in EU-initiated economic cooperation and integration programmes and treaties, such as the Barcelona Process. This process constitutes an important step towards enhancing the openness of Libya’s economy and creating convergence towards EU economies. The research explores the perceptions of Libyan businessmen on the economic and trade relationship between Libya and the EU by focusing directly on trends, developments, problems and prospects. The research also aims to explore problems encountered between Libya and the EU with the objective of establishing ways in which to lessen the adverse effects. It suggests policy measures to be adopted to improve Libya’s trade and economic relations with the EU. To fulfil its aims and objectives, this study utilised both primary and secondary data. The primary data were collected through a survey questionnaire conducted in Libya, which explored the opinions, perceptions and attitudes of Libyan businessmen towards trade-related issues with the EU. In addition, the secondary data were in the form of published statistical data relating to trade between Libya and the EU. The findings of this study demonstrated that the majority of Libyan businessmen have positive attitude towards economic cooperation and the integration process between Libya and the EU within the EU-Mediterranean Partnership (Barcelona Process) in general, and towards the establishment of FTA in particular. In addition, the majority of Libyan businessmen think that achievements in the economic field were the most successful policy aims within the Euro-Mediterranean Partnership, while perceiving the political and military and security fields to be of a minor role. However, the majority consider that trade between Libya and EU still faces a number of obstacles, despite Libya joining the Barcelona Process. These include the high price of EU products, the difference in terms of quality, and the adoption of high customs duties on EU products by the Libyan authorities and the lack of information about the opportunities available in EU markets. The study, also, finds that the majority of Libyan businessmen see the future of Libyan economy tied closely to the EU, rather than in an African, Arab or Islamic Union, in which they show little interest

Hybrid Approach for Botnet Detection Using K-Means and K-Medoids with Hopfield Neural Network

In the last few years, a number of attacks and malicious activities have been attributed to common channels between users. A botnet is considered as an important carrier of malicious and undesirable briskness. In this paper, we propose a support vector machine to classify botnet activities according to k-means, k-medoids, and neural network clusters. The proposed approach is based on the features of transfer control protocol packets. System performance and accuracy are evaluated using a predefined data set. Results show the ability of the proposed approach to detect botnet activities with high accuracy and performance in a short execution time. The proposed system provides 95.7% accuracy rate with a false positive rate less than or equal to 3%

A Modular Platform for Adaptive Heterogeneous Many-Core Architectures

Multi-/many-core heterogeneous architectures are shaping current and upcoming generations of compute-centric platforms which are widely used starting from mobile and wearable devices to high-performance cloud computing servers. Heterogeneous many-core architectures sought to achieve an order of magnitude higher energy efficiency as well as computing performance scaling by replacing homogeneous and power-hungry general-purpose processors with multiple heterogeneous compute units supporting multiple core types and domain-specific accelerators. Drifting from homogeneous architectures to complex heterogeneous systems is heavily adopted by chip designers and the silicon industry for more than a decade. Recent silicon chips are based on a heterogeneous SoC which combines a scalable number of heterogeneous processing units from different types (e.g. CPU, GPU, custom accelerator). This shifting in computing paradigm is associated with several system-level design challenges related to the integration and communication between a highly scalable number of heterogeneous compute units as well as SoC peripherals and storage units. Moreover, the increasing design complexities make the production of heterogeneous SoC chips a monopoly for only big market players due to the increasing development and design costs. Accordingly, recent initiatives towards agile hardware development open-source tools and microarchitecture aim to democratize silicon chip production for academic and commercial usage. Agile hardware development aims to reduce development costs by providing an ecosystem for open-source hardware microarchitectures and hardware design processes. Therefore, heterogeneous many-core development and customization will be relatively less complex and less time-consuming than conventional design process methods. In order to provide a modular and agile many-core development approach, this dissertation proposes a development platform for heterogeneous and self-adaptive many-core architectures consisting of a scalable number of heterogeneous tiles that maintain design regularity features while supporting heterogeneity. The proposed platform hides the integration complexities by supporting modular tile architectures for general-purpose processing cores supporting multi-instruction set architectures (multi-ISAs) and custom hardware accelerators. By leveraging field-programmable-gate-arrays (FPGAs), the self-adaptive feature of the many-core platform can be achieved by using dynamic and partial reconfiguration (DPR) techniques. This dissertation realizes the proposed modular and adaptive heterogeneous many-core platform through three main contributions. The first contribution proposes and realizes a many-core architecture for heterogeneous ISAs. It provides a modular and reusable tilebased architecture for several heterogeneous ISAs based on open-source RISC-V ISA. The modular tile-based architecture features a configurable number of processing cores with different RISC-V ISAs and different memory hierarchies. To increase the level of heterogeneity to support the integration of custom hardware accelerators, a novel hybrid memory/accelerator tile architecture is developed and realized as the second contribution. The hybrid tile is a modular and reusable tile that can be configured at run-time to operate as a scratchpad shared memory between compute tiles or as an accelerator tile hosting a local hardware accelerator logic. The hybrid tile is designed and implemented to be seamlessly integrated into the proposed tile-based platform. The third contribution deals with the self-adaptation features by providing a reconfiguration management approach to internally control the DPR process through processing cores (RISC-V based). The internal reconfiguration process relies on a novel DPR controller targeting FPGA design flow for RISC-V-based SoC to change the types and functionalities of compute tiles at run-time

Managers' and auditors' perceptions of intellectual capital disclosure

Purpose– This paper aims to explore managers' and auditors' perceptions of intellectual capital (IC) measurement and reporting in Egyptian companies. Design/methodology/approach– The paper draws on a questionnaire survey sent to managers and external auditors who were asked to provide their opinion about IC measurement and reporting for companies listed on the Egyptian Stock Exchange. Findings– The paper finds significant differences between respondents' rates on IC indicators. These differences are due to different industry sectors involved in our sample. Further, it finds that Egyptian listed firms neither measure nor report IC indicators in their annual reports. In addition, it finds that auditors' responsibilities on IC reporting are ambiguous. Finally, the paper finds that work experience is the main determinant of managers' perceptions of IC indicators, while professional education is the main determinant of external auditors' perceptions of IC indicators. Originality/value– Prior research on IC used the content analysis approach to measure levels of IC disclosure in annual reports. This paper adds to the existing literature by using the results of a survey questionnaire distributed to managers working in (and auditors specialised in) Egyptian companies to explore their perceptions on IC measurement and reporting. Since prior research has focused on developed economies, we strongly believe that this paper contributes to the existing literature, as we are the first to examine this issue in Egypt as an example of a developing economy

Pearl millet forage productivity under sprinkler irrigation system in sandy soil

A field experiment was conducted in a private farm (30o40' N latitude, 32o15' E longitude, and 10.0 m above mean sea level), Ismailia Governorate, Egypt, during the 2020 and 2021 summer growing seasons. The aim was to study the effect of four irrigation treatments (125, 100, 75% ETo, and farmer practice) on pearl millet forage yield. Average amounts of applied irrigation water under 125, 100, 75% ETo and farmer practice were 4637, 3710, 2782, and 5950 m3/ha, respectively with respective average water consumption values of 4130, 3308, 2482, and 5302 m3/ha. Compared to the farmer practice, the saved water was 22, 38, and 53 % for the 125, 100, and 75% ETo treatments. Average water use efficiency values were 7.91, 7.55, 6.96 and 4.59 kg/m3, and average water productivity values were 7.04, 6.73, 6.21, and 4.08 kg/m3 for 125, 100, 75% ETo and farmer treatments, respectively. The Ky factor was 1.17 indicating that the pearl millet crop is moderately sensitive to water stress. Irrigating pearl millet in sandy soils with 100% ETo will save 38% of applied irrigation water, achieve water use efficiency of 7.55 green yield/m3 of water consumed, and water productivity of 6.73 kg green yield/m3 of water applied. Keywords: Pearl millet, BIS model, sprinkler system, sandy soil, water use efficiency and water productivit

Internal Audit Function in Tunisian Listed Companies: An Explanatory Study

Purpose – The aim of this paper is to explore the attributes and activities of the internal audit function in Tunisian listed firms and evaluate its capacity to fulfill its role in corporate governance process. Design/methodology/approach – The study has been carried out through a questionnaire survey that aims to analyze internal audit function (IAF) characteristics’ in Tunisian listed firms.  The main aspects of this study were: insourcing versus outsourcing arrangements of the internal audit function; organizational statue; internal audit activities and internal audit interaction with external auditors.Findings – The findings of the study show that despite its changing role within the organization, the internal audit function suffers from some limitations that impair its independence and limit its intervention field. Also, internal audit function in Tunisian listed companies is focused on financial audit, internal controls and risk management assessment. Further analysis reveals a considerable level of coordination between internal and external auditors. Research implications – The paper’s findings are of interest to several different parties, primarily the professional internal audit body, chief audit executive (CAE), audit committee and senior management.Originality/value – The paper describes an empirical study, conducted on a sample of Tunisian listed companies, which provides a better understanding of the internal audit function attributes and activities. The paper is also a meaningful contribution to the internal audit literature, as it examines an interesting subject that has not yet been largely investigated in the context of emerging market. Keywords - Internal audit function - Corporate governance - Listed companies - Tunisi

Improvement of mechanical properties of railway track concrete sleepers using ultra high performance concrete (UHPC)

In recent times, the shape of the beams evolved from wooden sleepers and then to steel sleepers until they reached concrete sleepers. These sleepers play a very important role in transferring the loads from the train wheels to the subgrade layers fixed by the railway. This development took place in concrete sleepers until we reached mono-block concrete sleepers. This paper discusses, through laboratory experiments, the effect of ultra-high performance concrete mixtures on the behavior of mono-block concrete sleeper B70. The ability of these new sleepers to resist train loads was also studied, compared to its conventional concrete sleepers. This research aimed to determine through experiment if these sleepers' behavior fulfilled the European requirements standers for prestressed concrete sleepers, and make comparisons between the UHPC sleepers and conventional concrete sleepers. All these sleepers were tested under static load tests at the rail seat and center section and pull-out tests for cast-in fastening components. These initial results suggest that a new generation of Ultra-high performance concrete sleepers can be created; the long-term efficiency of this category of sleeper will need to be confirmed by dynamic and fatigue tests and practical use

Deep Learning for UAV Imagery Segmentation: The Detection of Elymus Athericus Spread in The Hallig Nordstrandischmoor

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesIt has been observed that Athyrics Elymus engulfs smaller species in low marsh habitats in different areas of Europe. To obtain automated segmentation of the Athurics Elymus in Hallig Nordstrandischmoor, a deep learning model based on the transfer learning technique presented in the VGG16 was implemented with a U-Net deep learning architecture and the data augmentation algorithm. In conclusion, the final results were good, and had been grouped into three levels of accuracy. These groups are also characterized by varying levels of diversity in their environments. The wildrye covers the majority of these single images, with a low percentage of other habitats in the first group with an accuracy greater than 96%. In the second group, the accuracy ranged between 91-95%, which included more elements of variation; however, wildrye was still included. Moreover, the third group, with an accuracy rate between 80-90%, did not seem to include wildrye very often, while at the same time including elements not found in the training dataset, such as surface water and dirt roads. Due to this, time and effort are significantly reduced while high accuracy is achieved