Showing papers by "Tunis University published in 2019"

Guiding Principles for Chronic Total Occlusion Percutaneous Coronary Intervention: A Global Expert Consensus Document

Abstract: Outcomes of chronic total occlusion (CTO) percutaneous coronary intervention (PCI) have improved because of advancements in equipment and techniques. With global collaboration and knowledge sharing, we have identified 7 common principles that are widely accepted as best practices for CTO-PCI. 1. Ischemic symptom improvement is the primary indication for CTO-PCI. 2. Dual coronary angiography and in-depth and structured review of the angiogram (and, if available, coronary computed tomography angiography) are key for planning and safely performing CTO-PCI. 3. Use of a microcatheter is essential for optimal guidewire manipulation and exchanges. 4. Antegrade wiring, antegrade dissection and reentry, and the retrograde approach are all complementary and necessary crossing strategies. Antegrade wiring is the most common initial technique, whereas retrograde and antegrade dissection and reentry are often required for more complex CTOs. 5. If the initially selected crossing strategy fails, efficient change to an alternative crossing technique increases the likelihood of eventual PCI success, shortens procedure time, and lowers radiation and contrast use. 6. Specific CTO-PCI expertise and volume and the availability of specialized equipment will increase the likelihood of crossing success and facilitate prevention and management of complications, such as perforation. 7. Meticulous attention to lesion preparation and stenting technique, often requiring intracoronary imaging, is required to ensure optimum stent expansion and minimize the risk of short- and long-term adverse events. These principles have been widely adopted by experienced CTO-PCI operators and centers currently achieving high success and acceptable complication rates. Outcomes are less optimal at less experienced centers, highlighting the need for broader adoption of the aforementioned 7 guiding principles along with the development of additional simple and safe CTO crossing and revascularization strategies through ongoing research, education, and training.

Analysis of the impact of renewable energy consumption and economic growth on carbon dioxide emissions in 12 MENA countries

Abstract: This paper examines the impact of renewable energy consumption, economic growth, foreign direct investment inflows and trade on carbon dioxide emissions for a panel of 12 Middle East and North Africa countries over the period 1980–2012 using the recent Panel Vector Autoregressive model with multi-domain analysis framework. The results from Granger causality test reveal a bidirectional causality relationship between the candidate variables supporting the feedback hypothesis. The findings show that economic growth leads to environmental degradation while renewable energy, international trade and foreign direct investment inflows lead to decreases carbon dioxide emissions. A serious shift toward using more renewable energy resources, international trade and foreign direct investment inward is recommended to improve the environmental quality and attain the sustainable growth in the region.

Impact of ZnO addition on structural, morphological, optical, dielectric and electrical performances of BaTiO 3 ceramics

Abstract: BaTiO3/(ZnO)x ceramics (x = 0, 2, 5 and 10 wt%) were produced via solid state reaction by using high energy ball milling. The morphological, structural, spectral, optical, electrical and dielectric properties were systematically investigated. X-ray diffraction indicated that all ceramics crystallize in the tetragonal structure. The grains size increases with ZnO additions. The optical band gap energy (Eg) was also evaluated and found to reduce with increasing ZnO concentration. The dielectric and electric properties revealed that an optimal ZnO content lead to obtain ceramic with high dielectric constant and low tangent loss, which are encouraging for radio frequencies and microwaves applications.

Network Anomaly Intrusion Detection Using a Nonparametric Bayesian Approach and Feature Selection

Abstract: Anomaly-based intrusion detection systems (IDSs) have been deployed to monitor network activity and to protect systems and the Internet of Things (IoT) devices from attacks (or intrusions). The problem with these systems is that they generate a huge amount of inappropriate false alarms whenever abnormal activities are detected and they are not too flexible for a complex environment. The high-level rate of the generated false alarms reduces the performance of IDS against cyber-attacks and makes the tasks of the security analyst particularly difficult and the management of intrusion detection process computationally expensive. We study here one of the challenging aspects of computer and network security and we propose to build a detection model for both known and unknown intrusions (or anomaly detection) via a novel nonparametric Bayesian model. The design of our framework can be extended easily to be adequate for IoT technology and notably for intelligent smart city web-based applications. In our method, we learn the patterns of the activities (both normal and anomalous) through a Bayesian-based MCMC inference for infinite bounded generalized Gaussian mixture models. Contrary to classic clustering methods, our approach does not need to specify the number of clusters, takes into consideration the uncertainty via the introduction of prior knowledge for the parameters of the model, and permits to solve problems related to over- and under-fitting. In order to get better clustering performance, feature weights, model's parameters, and the number of clusters are estimated simultaneously and automatically. The developed approach was evaluated using popular data sets. The obtained results demonstrate the efficiency of our approach in detecting various attacks.

Study of tungsten oxide effect on the performance of BaTiO 3 ceramics

Abstract: BaTiO3/(WO3)x ceramics (where x = 0, 0.5, 1, 2 and 5 wt%) were prepared by solid state reaction. X-ray powder diffraction, scanning electron microscope, Fourier transform-infrared spectroscopy and ultraviolet–visible diffuse reflectance spectrophotometry were used to investigate the structure, morphology and optical properties, respectively. The electrical and dielectric properties were also performed for different synthesized ceramics. A pure phase was obtained for x = 0.5 wt% ceramic, nevertheless a secondary phase was detected for x ≥ 1 wt% ceramics. The grains size increases for x = 0.5 wt% ceramic and then reduces abruptly with further increasing WO3 content. The increase of grains size and the absence of impurities were all efficient to enhance the dielectric properties. A suitable WO3 content leads to obtain ceramics having high dielectric constant and low tangent loss, which is encouraging for radio frequencies and microwaves applications.

The Phenolic compound Kaempferol overcomes 5-fluorouracil resistance in human resistant LS174 colon cancer cells

Abstract: Resistance to 5-Fluorouracil chemotherapy is a major cause of therapeutic failure in colon cancer cure. Development of combined therapies constitutes an effective strategy to inhibit cancer cells and prevent the emergence of drug resistance. For this purpose, we investigated the anti-tumoral effect of thirteen phenolic compounds, from the Tunisian quince Cydonia oblonga Miller, alone or combined to 5-FU, on the human 5-FU-resistant LS174-R colon cancer cells in comparison to parental cells. Our results showed that only Kaempferol was able to chemo-sensitize 5-FU-resistant LS174-R cells. This phenolic compound combined with 5-FU exerted synergistic inhibitory effect on cell viability. This combination enhanced the apoptosis and induced cell cycle arrest of both chemo-resistant and sensitive cells through impacting the expression levels of different cellular effectors. Kaempferol also blocked the production of reactive oxygen species (ROS) and modulated the expression of JAK/STAT3, MAPK, PI3K/AKT and NF-κB. In silico docking analysis suggested that the potent anti-tumoral effect of Kaempferol, compared to its two analogs (Kaempferol 3-O-glucoside and Kampferol 3-O-rutinoside), can be explained by the absence of glucosyl groups. Overall, our data propose Kaempferol as a potential chemotherapeutic agent to be used alone or in combination with 5-FU to overcome colon cancer drug resistance.

Application of the GIS based multi-criteria decision analysis and analytical hierarchy process (AHP) in the flood susceptibility mapping (Tunisia)

Abstract: Flooding is considered as the most dangerous natural catastrophe in the world. This paper develops a spatial multi-criteria decision production prototype for the evaluation of flooding susceptibility for the city of Tunis. Eight criterions were considered in order to identify and assess the spatial distribution of hazardous zones and were integrated in the Geographical Information System (ArcGIS). The analytical hierarchy process (AHP) is a mathematical technique for flood hazard modeling and decision support based on the weight and rank of each flood factor in order to calculate Flood Hazard Index (FHI) to generate a flood susceptibility map. This was classified from very low to very high classes flood potential. Five classes are observed: 2.85% (very low), 7.5% (low), 17.95% (moderate), 20.63% (high), and 51.06% (very high). FHI was coupled with a sensitivity analysis to derive the Flood Hazard Index with sensitivity (FHIS). This index evaluates the effect of each criteria which allows for better assessment of the role of each parameter in flood susceptibility. The results of this study provide a basis to limit the impacts of flood and protect urban zone against inundation.

Can economic policy uncertainty, oil prices, and investor sentiment predict Islamic stock returns? A multi-scale perspective

Abstract: This study investigates the causal relationships between economic policy uncertainty, oil prices, investor sentiment, and stock returns of nine Dow Jones Islamic Market Indices. Specifically, this study analyzes the causal effect of these variables on Islamic stock returns at different time scales using the ensemble empirical mode decomposition model. First, we decompose the economic policy uncertainty proxy, oil prices, and investor sentiment into different independent components called intrinsic mode functions (IMFs): short-term IMFs designate the effects of irregular events; medium-term IMFs present the effects of extreme events; and long-term IMFs capture long-term effects. Second, we employ a nonlinear non-parametric causality model to test the causal relationship between different variables and Islamic stock returns at both the original and decomposed levels. We find causal relationships between the underlying variables and Islamic stock returns in several time frequencies rather than in the whole sample period. Our results suggest that the use of lagged economic policy uncertainty, oil prices, and investor sentiment may improve the predictability of Islamic stock returns. A test of forecast accuracy indicated the robustness of our results.

An Adaptive PI Controller Design for DC-Link Voltage Control of Single-Phase Grid-Connected Converters

Abstract: Conventionally, standard proportional and integral (PI) controllers with constant PI gains are commonly used for the dc-link voltage control of single-phase grid-connected converters (GCCs). For such controllers, the selection of the PI gains will lead to a tradeoff between two control objectives: 1) the reduction of the dc-link voltage fluctuations caused by random swings of the active power drawn by the single-phase GCC; and 2) the reduction of the grid current harmonics mainly caused by the 2 f oscillation of the active power in single-phase applications. To solve this tradeoff, this paper presents a systematic approach for the design of an adaptive PI controller for the dc-link voltage control of single-phase GCCs. The proposed design approach is simple and it provides a convenient method to properly determine the adaptive PI controller parameters. Representative simulation and experimental results are presented and discussed in order to show the effectiveness of the proposed dc-link voltage controller.

Modeling and multi-objective optimization for minimizing surface roughness, cutting force, and power, and maximizing productivity for tempered stainless steel AISI 420 in turning operations

Abstract: The present study aims at investigating the influence of the different machining parameters represented by the cutting speed (Vc), the depth of cut (ap), and the feed rate (f) on the output performance parameters expressed through the surface roughness, the cutting force and power, and the material removal rate (i.e., Ra, Fz, Pc, and MRR) during dry hard turning operation of martensitic stainless steel (AISI 420) treated at 59HRC. The machining tests were carried out using the coated mixed ceramic insert (CC6050) according to the Taguchi design (L25). The analysis of the variance (ANOVA) and the Pareto chart analysis led to quantifying the influence of the (Vc, ap, and f) on the output parameters. The response surface methodology (RSM) and the artificial neural networks (ANN) approaches were applied and compared for output parameters modeling. Attempt was further made to optimize the machining parameters using the desirability function (DF). Four objectives were considered including the maximization of the quality and the productivity (through minimizing Ra and maximizing MRR), and reducing the energy consumption over minimizing both (Fz) and (Pc). The results indicated that (Ra) is strongly influenced by the feed rate (in the order of 80.71%), while the depth of cut seems to be the property having the most influence on the cutting force (65.31%), the cutting power (37.56%), and the material removal rate (36.45%). Furthermore, ANN and RSM models were found to predict well experimental results with the former showing higher accuracy. The machining of AISI 420 (59 HRC) steel with coated ceramic led to achieving a quality surface comparable to that found in grinding (i.e., Ra < 0.4 μm).

On The consideration of carbon emissions in modelling-based supply chain literature: the state of the art, relevant features and research gaps

Abstract: This review paper provides the operations management (OM) community with an exhaustive analysis of the mathematical models developed for the problem of low-carbon supply chain management (LCSCM). O...

Diagnosis of Open-Switch and Current Sensor Faults in PMSM Drives Through Stator Current Analysis

Abstract: Fault detection and fault accommodation, as well as fault tolerance, are important issues in closed-loop controlled three-phase converters. For such systems, power semiconductors and sensors are the most affected components by the occurrence of failures. Therefore, fault diagnosis and remedial operating strategies involving such components are highly required. In this paper, a new reliable approach is proposed, which aims to diagnose current sensor faults and power semiconductor open-circuit faults in permanent magnet synchronous motor drives. The proposed fault diagnosis scheme uses only the measured currents, which makes it suitable for real-time implementation. The performance of the proposed technique is analyzed through experiments.

IL-7 receptor influences anti-TNF responsiveness and T cell gut homing in inflammatory bowel disease.

Abstract: It remains unknown what causes inflammatory bowel disease (IBD), including signaling networks perpetuating chronic gastrointestinal inflammation in Crohn's disease (CD) and ulcerative colitis (UC), in humans. According to an analysis of up to 500 patients with IBD and 100 controls, we report that key transcripts of the IL-7 receptor (IL-7R) pathway are accumulated in inflamed colon tissues of severe CD and UC patients not responding to either immunosuppressive/corticosteroid, anti-TNF, or anti-α4β7 therapies. High expression of both IL7R and IL-7R signaling signature in the colon before treatment is strongly associated with nonresponsiveness to anti-TNF therapy. While in mice IL-7 is known to play a role in systemic inflammation, we found that in humans IL-7 also controlled α4β7 integrin expression and imprinted gut-homing specificity on T cells. IL-7R blockade reduced human T cell homing to the gut and colonic inflammation in vivo in humanized mouse models, and altered effector T cells in colon explants from UC patients grown ex vivo. Our findings show that failure of current treatments for CD and UC is strongly associated with an overexpressed IL-7R signaling pathway and point to IL-7R as a relevant therapeutic target and potential biomarker to fill an unmet need in clinical IBD detection and treatment.

BIG DATA for Healthcare: A Survey

Abstract: Recently, the massification of new technologies, which has been adopted by a large majority of the world population, has accumulated a tremendous amount of data, including clinical data. This clinical data have been gathered up and interpreted by medical organizations in order to gain insights and knowledge useful for clinical decisions, drug recommendations, and better diagnoses, among many other uses. This paper highlights the enormous impacts of big data on medical stakeholders, patients, physicians, pharmaceutical and medical operators, and healthcare insurers, and also reviews the different challenges that must be taken into account to get the best benefits from all this big data and the available applications.