Showing papers by "Tunis University published in 2015"

The environmental Kuznets curve, economic growth, renewable and non-renewable energy, and trade in Tunisia

Abstract: We use the autoregressive distributed lag (ARDL) b ounds testing approach for cointegration with structural breaks and the ve ctor error correction model (VECM) Granger causality approach in order to investigate relationships between per capita CO 2 emissions, GDP, renewable and non-renewable energy consumption and international trade (exports or imports) for Tunisia during the period 1980-2009. We show the existence of a short-run unidirectional causality running from tra de, GDP, CO 2 emission and non-renewable energy to renewable energy. Our long-run estimates show that non-renewable energy and trade have a positive impact on CO 2 emissions, whereas renewable energy impacts weakly and negatively CO 2 emission when using the model with exports and this impact is statistically insignificant when using the model wi th imports. The inverted U-shaped environmental Kuznets curve (EKC) hypothesis is not supported graphically and analytically in the long-run. This means that Tunisia has not ye t reached the required level of per capita GDP to get an inverted U-shaped EKC. Our main policy recommendations for Tunisia are the following: (i) to radically reform the subsidies system granted b y the Tunisian government for fossil fuels consumption; (ii) to encourage the use of renewable energy and ener gy efficiency by reinforcing actual projects and regulatory frame work; (iii) to locate ports near exporting industrial zones (or vice versa) to reduce emission of pollution caused by the transport of merchandise; (iv) to elaborate a strategy for maximizing its benefit from renewable energy technology transfer occurring when importing capita l goods; (v) to encourage the creation of renewable energy projects for export to the EU with a proportion of production for national consumption.

The environmental Kuznets curve, economic growth, renewable and non-renewable energy, and trade in Tunisia

Abstract: We use the autoregressive distributed lag (ARDL) bounds testing approach for cointegration with structural breaks and the vector error correction model (VECM) Granger causality approach in order to investigate relationships between per capita CO2 emissions, GDP, renewable and non-renewable energy consumption and international trade (exports or imports) for Tunisia during the period 1980-2009. We show the existence of a short-run unidirectional causality running from trade, GDP, CO2 emission and non-renewable energy to renewable energy. Our long-run estimates show that non-renewable energy and trade have a positive impact on CO2 emissions, whereas renewable energy impacts weakly and negatively CO2 emission when using the model with exports and this impact is statistically insignificant when using the model with imports. The inverted U-shaped environmental Kuznets curve (EKC) hypothesis is not supported graphically and analytically in the long-run. This means that Tunisia has not yet reached the required level of per capita GDP to get an inverted U-shaped EKC. Our main policy recommendations for Tunisia are the following: (i) to radically reform the subsidies system granted by the Tunisian government for fossil fuels consumption; (ii) to encourage the use of renewable energy and energy efficiency by reinforcing actual projects and regulatory framework; (iii) to locate ports near exporting industrial zones (or vice versa) to reduce emission of pollution caused by the transport of merchandise; (iv) to elaborate a strategy for maximizing its benefit from renewable energy technology transfer occurring when importing capital goods; (v) to encourage the creation of renewable energy projects for export to the EU with a proportion of production for national consumption.

Multiple Open-Circuit Faults Diagnosis in Back-to-Back Converters of PMSG Drives for Wind Turbine Systems

Abstract: In order to increase the reliability and availability of wind turbines, condition monitoring and fault diagnosis are considered crucial means to achieve these goals. In this context, direct drives wind turbines based on permanent-magnet synchronous generators (PMSGs) with full-scale power converters are an emerging and promising technology. However, several statistical studies point out that power converters are a significant contributor to the overall failure rate of modern wind turbines. Accordingly, this paper presents a new algorithm for multiple open-circuit faults diagnosis in full-scale back-to-back converters, applied in PMSG drives used for wind turbine systems. The proposed method is based on a Luenberger observer and on an adaptive threshold, which can guarantee a reliable diagnosis independently of the drive operating conditions. Several simulation and experimental results using a PMSG drive with a full-scale converter are presented, showing the diagnostic algorithm effectiveness and robustness against false alarms for both generator- and grid-side converters.

Modeling the causal linkages between nuclear energy, renewable energy and economic growth in developed and developing countries

Abstract: This article investigates the causal relationship between two types of energy variables and economic growth using dynamic simultaneous-equation panel data models for 17 developed and developing countries. Our results indicate that there is a unidirectional causality running from nuclear consumption to economic growth in Belgium and Spain, while a unidirectional causality running from economic growth to nuclear consumption is supported in Bulgaria, Canada, Netherlands, and Sweden. A bidirectional relationship appears in Argentina, Brazil, France, Pakistan, and the USA, while no causality exists in Finland, Hungary, India, Japan, Switzerland, and the U.K. Second, the results for the second nexus among renewable energy and economic growth show that there is a unidirectional causality running from renewable consumption to economic growth in Hungary, India, Japan, Netherlands, and Sweden, while there exist a unidirectional running from economic growth to renewable consumption in Argentina, Spain, and Switzerland. A bidirectional relationship is supported in Belgium, Bulgaria, Canada, France, Pakistan, and the USA, while no causality exists in Brazil, Finland, and Switzerland. Third, we find the existence of a bidirectional causality between nuclear consumption and economic; and a unidirectional causality running from economic growth to renewable energy consumption for the global panel.

Application of higher order spectral features and support vector machines for bearing faults classification

Abstract: Condition monitoring and fault diagnosis of rolling element bearings timely and accurately are very important to ensure the reliability of rotating machinery This paper presents a novel pattern classification approach for bearings diagnostics, which combines the higher order spectra analysis features and support vector machine classifier The use of non-linear features motivated by the higher order spectra has been reported to be a promising approach to analyze the non-linear and non-Gaussian characteristics of the mechanical vibration signals The vibration bi-spectrum (third order spectrum) patterns are extracted as the feature vectors presenting different bearing faults The extracted bi-spectrum features are subjected to principal component analysis for dimensionality reduction These principal components were fed to support vector machine to distinguish four kinds of bearing faults covering different levels of severity for each fault type, which were measured in the experimental test bench running under different working conditions In order to find the optimal parameters for the multi-class support vector machine model, a grid-search method in combination with 10-fold cross-validation has been used Based on the correct classification of bearing patterns in the test set, in each fold the performance measures are computed The average of these performance measures is computed to report the overall performance of the support vector machine classifier In addition, in fault detection problems, the performance of a detection algorithm usually depends on the trade-off between robustness and sensitivity The sensitivity and robustness of the proposed method are explored by running a series of experiments A receiver operating characteristic (ROC) curve made the results more convincing The results indicated that the proposed method can reliably identify different fault patterns of rolling element bearings based on vibration signals

The extended clinical phenotype of 64 patients with dedicator of cytokinesis 8 deficiency.

Abstract: Background Mutations in dedicator of cytokinesis 8 (DOCK8) cause a combined immunodeficiency (CID) also classified as autosomal recessive (AR) hyper-IgE syndrome (HIES). Recognizing patients with CID/HIES is of clinical importance because of the difference in prognosis and management. Objectives We sought to define the clinical features that distinguish DOCK8 deficiency from other forms of HIES and CIDs, study the mutational spectrum of DOCK8 deficiency, and report on the frequency of specific clinical findings. Methods Eighty-two patients from 60 families with CID and the phenotype of AR-HIES with (64 patients) and without (18 patients) DOCK8 mutations were studied. Support vector machines were used to compare clinical data from 35 patients with DOCK8 deficiency with those from 10 patients with AR-HIES without a DOCK8 mutation and 64 patients with signal transducer and activator of transcription 3 (STAT3) mutations. Results DOCK8-deficient patients had median IgE levels of 5201 IU, high eosinophil levels of usually at least 800/μL (92% of patients), and low IgM levels (62%). About 20% of patients were lymphopenic, mainly because of low CD4 + and CD8 + T-cell counts. Fewer than half of the patients tested produced normal specific antibody responses to recall antigens. Bacterial (84%), viral (78%), and fungal (70%) infections were frequently observed. Skin abscesses (60%) and allergies (73%) were common clinical problems. In contrast to STAT3 deficiency, there were few pneumatoceles, bone fractures, and teething problems. Mortality was high (34%). A combination of 5 clinical features was helpful in distinguishing patients with DOCK8 mutations from those with STAT3 mutations. Conclusions DOCK8 deficiency is likely in patients with severe viral infections, allergies, and/or low IgM levels who have a diagnosis of HIES plus hypereosinophilia and upper respiratory tract infections in the absence of parenchymal lung abnormalities, retained primary teeth, and minimal trauma fractures.

Chemical composition and antibacterial activities of seven Eucalyptus species essential oils leaves

Abstract: Background: In this paper, we have studied the essential oils chemical composition of the leaves of seven Eucalyptus species developed in Tunisia. Eucalyptus leaves were picked from trees growing in different arboretums in Tunisia. Choucha and Mrifeg arboretums located in Sedjnene, region of Bizerte (Choucha: E. maideni, E. astrengens et E. cinerea; Mrifeg : E. leucoxylon), Korbous arboretums located in the region of Nabeul, North East Tunisia with sub-humid bioclimate, (E. lehmani), Souiniet-Ain Drahem arboretum located in region of Jendouba (E. sideroxylon, E. bicostata). Essential oils were individually tested against a large panel of microorganisms including Staphylococcus aureus (ATCC 6539), Escherichia coli (ATCC 25922), Enterococcus faecalis (ATCC29212), Listeria ivanovii (RBL 30), Bacillus cereus (ATCC11778). Results: The yield of essential oils ranged from 1.2% to 3% (w/w) for the different Eucalyptus species. All essential oils contain α-pinene, 1,8-cineol and pinocarveol-trans for all Eucalyptus species studied. The 1,8-cineol was the major compound in all species (49.07 to 83.59%). Diameter of inhibition zone of essential oils of Eucalyptus species varied from 10 to 29 mm. The largest zone of inhibition was obtained for Bacillus cereus (E. astrengens) and the lowest for Staphylococcus aureus (E. cinerea). The essential oils from E. maideni, E. astrengens, E. cinerea (arboretum of Bizerte), E. bicostata (arboretum of Aindraham) showed the highest antibacterial activity against Listeria ivanovii and Bacillus cereus. Conclusion: The major constituents of Eucalyptus leaves essential oils are 1,8-cineol (49.07 to 83.59%) and α-pinene (1.27 to 26.35%). The essential oils from E. maideni, E. astrengens, E. cinerea, E. bicostata showed the highest antibacterial activity against Listeria ivanovii and Bacillus cereus, they may have potential applications in food and pharmaceutical products.

Reconfigurable Coordination of Distributed Discrete Event Control Systems

Abstract: Dynamic reconfigurability is receiving more and more attention from both academy and industry, which means the ability to flexibly modify system functions by adding/removing hardware/software components, modifying logic relation between components, or updating particular system data at runtime without sacrificing the system performance. A distributed reconfigurable discrete event control system (DRDECS) is composed of several networked reconfigurable subsystems. In order to realize system functions, these reconfigurable subsystems communicate and coordinate with each other, since any casually reconfiguration applied to a subsystem may cause risks to others, or even to the safety of the whole system. This brief proposes a new coordination method for a DRDECS, where each subsystem is modeled by a reconfigurable timed net condition/event system. A virtual coordinator together with a communication protocol between it and subsystems is developed in order to achieve two aims: 1) to coordinate subsystems with an optimal coordination solution using judgement matrices while multiple subsystems require global reconfigurations and 2) to reduce exchanged messages between the coordinator and these subsystems. Furthermore, for the purpose of checking functional and temporal properties of a DRDECS with this virtual coordinator, a computation tree logic-based model checking method is applied. Finally, a hypothetic manufacturing plant is used as a running example to illustrate this brief.

Phenol photocatalytic degradation over anisotropic TiO2 nanomaterials: Kinetic study, adsorption isotherms and formal mechanisms

Abstract: Anisotropic TiO2 nanomaterials (nanotubes, nanorods, nanoplates, nanospheres, and nanoparticles) with controlled structural and textural properties have been evaluated in the photocatalytic degradation of phenol under UV conditions. The kinetic study of phenol adsorption fits well to a quasi-second-order model whereas the adsorption isotherms of phenol over the different TiO2 nanomaterials follow the Langmuir model and the degradation kinetics the Langmuir–Hinshelwood (L–H) model. TiO2 nanomaterials exposing (0 0 1) or (1 0 1) anatase facets are less active than TiO2 P25 for the phenol degradation. This is related to their tendency to degrade faster intermediates products (organic acids) rather than phenol itself. A good compromise between anatase crystallinity, crystallites sizes, and specific surface area can however improve the photocatalytic activity of the TiO2 nanomaterials. Results also showed that the degradation mechanism follows pseudo-first order kinetics. Pseudo-rate constants were therefore determined and formal mechanism schemes proposed.

Financial Development, Bank Efficiency and Economic Growth across the Mediterranean

Abstract: We examine the relationship between FD and economic growth in the SEMC and the EU-MED in 1985–2009 using several variables, taking into account the effects of both quantity and quality. Credit to the private sector and bank deposits are negatively associated with growth, which suggests deficiencies in credit allocation as well as weak financial regulation and supervision. Stock market size and liquidity play a role in growth, especially when accounting for the quality of institutions. Investments, whether domestic or foreign, contribute to economic growth. Stronger institutions and low inflation are growth factors. Initial GDP has a persistently and significantly negative impact on growth, which confirms the catching-up hypothesis.

Parametric study on the dielectric properties of biological tissues

Abstract: A good comprehensive study of the electromagnetic properties of biological layers is important since we cannot discuss an implantable antenna design without investigating the interaction of electromagnetic radiation with the tissue. The human body is not an ideal medium for the transmission of radio waves which can be considered as a barrier degrading the performance of the transmission system that uses the human body as a propagation channel. This paper deals with some notions of electromagnetic characteristics of body tissues and their dependency to the frequency.

A New Equation Relating the Viscosity Arrhenius Temperature and the Activation Energy for Some Newtonian Classical Solvents

Abstract: In transport phenomena, precise knowledge or estimation of fluids properties is necessary, for mass flow and heat transfer computations. Viscosity is one of the important properties which are affected by pressure and temperature. In the present work, based on statistical techniques for nonlinear regression analysis and correlation tests, we propose a novel equation modeling the relationship between the two parameters of viscosity Arrhenius-type equation, such as the energy () and the preexponential factor (). Then, we introduce a third parameter, the Arrhenius temperature (), to enrich the model and the discussion. Empirical validations using 75 data sets of viscosity of pure solvents studied at different temperature ranges are provided from previous works in the literature and give excellent statistical correlations, thus allowing us to rewrite the Arrhenius equation using a single parameter instead of two. In addition, the suggested model is very beneficial for engineering data since it would permit estimating the missing parameter value, if a well-established estimate of the other parameter is readily available.

Chapter Four – Preference Incorporation in Evolutionary Multiobjective Optimization: A Survey of the State-of-the-Art

Abstract: After using Evolutionary Algorithms (EAs) for solving multiobjective optimization problems for more than two decades, the incorporation of the decision maker's (DM’s) preferences within the evolutionary process has finally become an active research area. In fact, EAs have demonstrated their effectiveness and efficiency in providing a well-converged and well-distributed approximation of the Pareto front. However, in reality, the DM is not interested in discovering the whole Pareto front rather than approximating the portion of the front that best matches his/her preferences, i.e., the Region Of Interest. For this reason, many new preference-based Multiobjective Optimization EAs (MOEAs), which are mostly variations of existing methods, have been recently published in the specialized literature. The purpose of this chapter is to summarize and organize the information on these current approaches in an attempt to motivate researchers to further focus on hybridizing between decision making and evolutionary multiobjective optimization research fields; consequently facilitating the DM's task when selecting the final alternative to realize. Hence, a summary of the main preference-based MOEAs is provided together with a brief criticism that includes their pros and cons. Furthermore, we propose a classification of such type of algorithms based on the DM's preference information structure. Finally, the future trends in this research area and some possible paths for future research are outlined.