Contrairement à l’abstention-surveillance, la surveillance active est une modalité de prise en charge curative. Elle vise à retarder le traitement d’une tumeur peu agressive jusqu’au moment où elle le deviendra tout en restant dans la fenêtre de curabilité de la maladie. À travers une lecture de littératures, nous allons essayer de maitre la lumière sur la place et les modalités de la surveillance active, dans les groupes favorables des cancers de la prostate et de répondre aux questions suivantes : Pourquoi la surveillance active ? Pour qui ? Comment l’instauré ? et quand doit-on l’arrêter ? La majorité des essais, cliniques publiés s’accordent à dire, que la surveillance active est une attitude parfaitement adaptée aux patients du groupe favorable d’AMICO, voire même une partie du groupe intermédiaire bas risque. Les résultats en matière de survie globale et d’évènement métastatiques, sont similaires à ceux des patients traités d’emblée par chirurgie et ou radiothérapie, avec en plus moins de toxicité. La surveillance est basée essentiellement sur le dosage périodique du PSA, rebiopsie selon des protocoles propres à chaque équipe. La décision du passage aux traitements invasifs, sera conditionnée par la progression du score Gleason, selon des algorithmes dont certains, sont déjà validés à l’international. La surveillance active, doit faire partie intégrante des décisions de prise en charge des adénocarcinomes prostatiques localisés favorables. Cette attitude nous permet, d’éviter de surtraiter un grand nombre, de petites lésions non évolutives, tout en ayant la possibilité et les moyens, de rattraper les lésions qui progressent.
Image classification has been one of the most widely topic in artificial intelligence, deep models need larger datasets and powerful hardware to improve the highperformance classification. ImageNet Challenge was started in 2010 to classify 100,000 test images into 1000 different classes. Tiny ImageNet challenge is similar to ImageNet challenge, where images are taken from the standard ImageNet and resized to be 64x64. In this paper a fine-tuned Xception to classify images into the 200 classes is presented using the standard Tiny ImageNet dataset, the down-sampling (64x64) of images and the low similarity inter-class makes feature extraction and classification difficult and more challenging. We used a transfer learning algorithm to fine-tune the Xception architecture using the Extreme version of the Inception module to achieve a high validation accuracy of 65.14%.
The novel coronavirus outbreak (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents the actual greatest global public health crisis. The lack of efficacious drugs and vaccines against this viral infection created a challenge for scientific researchers in order to find effective solutions. One of the promising therapeutic approaches is the search for bioactive molecules with few side effects that display antiviral properties in natural sources like medicinal plants and vegetables. Several computational and experimental studies indicated that flavonoids especially flavonols and their derivatives constitute effective viral enzyme inhibitors and possess interesting antiviral activities. In this context, the present study reviews the efficacy of many dietary flavonols as potential antiviral drugs targeting the SARS-CoV-2 enzymes and proteins including Chymotrypsin-Like Protease (3CLpro), Papain Like protease (PLpro), Spike protein (S protein) and RNA-dependent RNA polymerase (RdRp), and also their ability to interact with the angiotensin-converting enzyme II (ACE2) receptor. The relationship between flavonol structures and their SARS-CoV-2 antiviral effects were discussed. On the other hand, the immunomodulatory, the anti-inflammatory and the antiviral effects of secondary metabolites from this class of flavonoids were reported. Also, their bioavailability limitations and toxicity were predicted.
Floods become major concerns in most gobe regions due to socio-economic and environmental consequences caused by these phenomena in recent decades. Most Algerian cities are exposed to flood risks and suffered from its consequences. The purpose of this paper is the spatialization of flood hazard in the city of Chemora (Algeria) by hydraulic modelling in a GIS environment whose objective is prevention, which requires a set of hydrological and hydraulic informations in order to achieve a comprehensive and effective management.
Floods become major concerns in most gobe regions due to socio-economic and environmental consequences caused by these phenomena in recent decades. Most Algerian cities are exposed to flood risks and suffered from its consequences. The purpose of this paper is the spatialization of flood hazard in the city of Chemora (Algeria) by hydraulic modelling in a GIS environment whose objective is prevention, which requires a set of hydrological and hydraulic informations in order to achieve a comprehensive and effective management.
As renewable energy elucidation, the solar refrigeration of fruits such as date palm is a storage alternate to preserve food in healthy parameters of conditioning. This statistical and numeric study investigates the energy gain cost case around the diverse dimensions’ models of positive cold stores (02, 04, and 06 cold rooms), concerning energetic disparity and numerous financial fluctuations of the applied systems. The results of computation and analysis regarding panels of construction, equipment, consumption, and maintenance for classic, absorption, and adsorption refrigeration systems that conserve dates palm into these three cold stores. In the end, the comparison of technical and economic elements in tables and figures by enumerating their advantages and inconveniences. Classic Bitzer, Absorption WFC SC 5, and Adsorption AG ACS 15 and 08 are models in which their evaluation is relating to their costs. In Biskra, these results mean that adsorption chiller termed AG ACS (15 plus 08) is illustrious by its parameters of simplicity, lifespan, safety, and security, valued to 1147.5 €/m² and median cost up ten years of using is 92972 €
Nanometric YSi2 − x yttrium silicides layers have been formed onto a Si(111) single-crystal substrate by implantation at room temperature (RT) of Y ions using an energy of 195 keV and a dose of 2 × 1017 Y+/cm2 followed by a thermal annealing in a nitrogen atmosphere. The process of the silicidation has been investigated at a function of the annealing temperatures ranging from 600 to 1000 °C for duration of one hour. The characterization of the samples has been performed using X-ray diffraction (XRD), Rutherford backscattering spectrometry (RBS), and scanning electron microscopy combined with energy dispersive X-ray spectrometer (SEM-EDS) techniques. Studies have shown that the YSi2 − x layer is epitaxially grown on the Si (111) surface, and after thermal annealing at a temperature of 600–1000 °C, no change in the properties of the formed phase is found.
Today’s, and near future, communication networks rely heavily on capacity expansion to keep pace with the massive number of mobile devices and ever-increasing mobile traffic. This expansion can be achieved through three major ingredients, namely, adding more wireless-spectrum, efficient usage of this spectrum, and adequate networks’ architectures. In this paper, a proposition for integrating these three ingredients in a cognitive-radio-inspired framework is presented. The focus is on the integration of the idle spectrum resources of different wireless networks into a single mobile heterogeneous wireless network. This framework is based on a conceptual network-architecture articulated with a generic and cooperative spectrum-harvesting scheme. The former brings the necessary agility for such heterogeneous environments, the latter keeps the network supplied with the vital spectrum resources. In our proposal, we make use of cross-correlated sequences (CCSs) for context-aware events’ signaling purposes. This choice is motivated by the particularly interesting characteristics of CCSs, namely, duration shortness, robustness to bad radio conditions, detection rather than decoding, and low probability of collision. As an illustration, we propose a reporting and detection scheme, in the context of OFDMA systems, and provide performance results from simulations to validate our proposal.
In this paper, first we show that the analytical solutions obtained in the literature for the new coupled Konno-Oono system can be immediately presented via the Weierstrass elliptic function or Jacobi elliptic functions. Next, we present a new general real dark-type of soliton and a complex bright-type of envelope soliton to this system in terms of the solutions of the sine-Gordon and sinh-Gordon equations involving an arbitrary function via two new different transformations.
This paper deals with the integration of a photovoltaic energy conversion system (PVECS) into a distribution network and cater for the energy needs of buildings. The main goals of this work are the reduction of the grid dependence, minimization of the energy cost and increasing the autonomy of the building’s energy. Two stages converters are used to ensure the maximum power point tracking (MPPT) and to control the power flow. A fuzzy MPPT control is proposed to maintain the power of the Photovoltaic panel at its optimal value despite climatic condition variations and building’s load changes. The grid side inverter is controlled by hysteresis regulators to transfer the total produced energy, with the aim to partially or completely replace energy provided from the Grid. The DC link voltage is also stabilized in order to improve the energy quality. The complete PVECS system is modelled and simulated in Matlab/Simulink, the controllers used are simple to implement and the simulation results show that the building’s energy demand can be satisfied, and the energy exceed is injected into the grid. The results confirm the good effectiveness of the proposed control.
The direct power control of the doubly fed induction generator using conventional controllers is characterized by unsatisfactory performance: high ripples of stator powers and sensitivity to parametric variations. Among the most evoked control strategies adopted in this field to overcome these drawbacks presented in classical drive, it is worth mentioning the use of the higher law sliding mode developed on the super twisting algorithm associated with the fuzzy logic control in order to realize optimal command performance, Finally, the efficiency of the envisaged control scheme, is investigated against. The proposed regulation scheme is efficient in reducing the powers ripples; successfully suppress chatter and the effects of parametric variations that do not affect the performance of the regulation.
The direct power control of the doubly fed induction generator using conventional controllers is characterized by unsatisfactory performance: high ripples of stator powers and sensitivity to parametric variations. Among the most evoked control strategies adopted in this field to overcome these drawbacks presented in classical drive, it is worth mentioning the use of the higher law sliding mode developed on the super twisting algorithm associated with the fuzzy logic control in order to realize optimal command performance, Finally, the efficiency of the envisaged control scheme, is investigated against. The proposed regulation scheme is efficient in reducing the powers ripples; successfully suppress chatter and the effects of parametric variations that do not affect the performance of the regulation.
This paper proposes the fundamental aspects of hybrid nonlinear control which is composed of the super twisting algorithm (STA) based second order sliding mode control applying fuzzy logic method (FSOSMC), with pertinent simulation results for a doubly fed induction machine (DFIM) drive. To minimize chattering effect phenomenon due to Signum function employed in sliding mode algorithm, a new method is proposed. This technique consists in replacing the signum function by fuzzy switching function in the SOSMC to minimize flux and torque ripples. This FSOSMC is associated to the double direct torque control DDTC of the doubly fed induction machine (DFIM) by combining the advantages of fuzzy logic (FL) and the advantages of super-twisting sliding mode. The FSOSMC-DDTC strategy is compared with a PI-DDTC and SOSMC-DDTC. Simulation results demonstrate good efficiency and excellent robustness of the hybrid nonlinear controller.
This paper proposes the fundamental aspects of hybrid nonlinear control which is composed of the super twisting algorithm (STA) based second order sliding mode control applying fuzzy logic method (FSOSMC), with pertinent simulation results for a doubly fed induction machine (DFIM) drive. To minimize chattering effect phenomenon due to Signum function employed in sliding mode algorithm, a new method is proposed. This technique consists in replacing the signum function by fuzzy switching function in the SOSMC to minimize flux and torque ripples. This FSOSMC is associated to the double direct torque control DDTC of the doubly fed induction machine (DFIM) by combining the advantages of fuzzy logic (FL) and the advantages of super-twisting sliding mode. The FSOSMC-DDTC strategy is compared with a PI-DDTC and SOSMC-DDTC. Simulation results demonstrate good efficiency and excellent robustness of the hybrid nonlinear controller.
This article investigates a non-equilibrium chaotic system in view of commensurate and incommensurate fractional orders and with only one signum function. By varying some values of the fractional-order derivative together with some parameter values of the proposed system, different dynamical behaviors of the system are explored and discussed via several numerical simulations. This system displays complex hidden dynamics such as inversion property, chaotic bursting oscillation, multistabilty, and coexisting attractors. Besides, by means of adapting certain controlled constants, it is shown that this system possesses a three-variable offset boosting system. In conformity with the performed simulations, it also turns out that the resultant hidden attractors can be distributively ordered in a grid of three dimensions, a lattice of two dimensions, a line of one dimension, and even arbitrariness in the phase space. Through considering the Caputo fractional-order operator in all performed simulations, phase portraits in two- and three-dimensional projections, Lyapunov exponents, and the bifurcation diagrams are numerically reported in this work as beneficial exit results.
In this work, we propose a new algorithm to improve existing techniques used in the field of spectroscopic data regression analysis. In particular, it combines the power of nonlinear kernel regressors (kernel ridge regression [KRR], kernel principal component regression [KPCR], and Gaussian process regression [GPR]) with an optimization based on nondominated sorting multi-objective genetic algorithm (NSGAII) to filter the residual outliers in the prediction space and leverage points in the features space. The proposed algorithm, contrary to most existing robust algorithms, simultaneously optimizes many complementary objectives for an automatic adaptation and thus a better outliers detection. It is well known that the elimination of outliers greatly improves the regression model. It is thus the aim of this work to develop a new robust regression algorithm. It has been applied on five different datasets, and the results are compared to both classical nonlinear regression methods and the commonly used robust regression methods robust continuum regression (RCR), partial robust M-regression (PRM), robust principal component regression (RPCR), robust PLSR (RSIMPLS), and locally weighted regression (LWR). They show that the proposed algorithm outperforms the classical nonlinear regression methods and is a promising competitor to the robust methods outperforming most of them. Even though the results obtained are only from five datasets, this algorithm can be considered an interesting contribution for improving data analysis in the field of chemometrics.
In this paper, the role of introducing Germanium (Ge)/IGZO heterostructure in enhancing the Infrared (IR) photodetection properties of thin-film phototransistor (Photo- TFT) is presented. Numerical models for the investigated device are developed using ATLAS device simulator. The influence of Ge photosensitive layer thickness on the sensor IR photoresponse is carried out. It is revealed that the optimized IR Photo-TFT based on p-Ge/IGZO heterojunction can offer improved IR responsivity of 4.1×10(exp2) A/W, and over 10(exp6) of sensitivity. These improvements are attributed to the role of the introduced p-Ge/IGZO heterostructure in promoting IR photodetection ability and improved separation and transfer mechanisms of photo-exited electron/hole pairs. The photosensor is then implemented in an optical inverter gate circuit in order to assess its switching capabilities. It is found that the proposed phototransistor shows an improved optical gain thus indicating its excellent performance. Therefore, providing high IR responsivity and low dark noise effects, the optimized Ge/IGZO IR Photo-TFT can be a potential alternative photosensor for designing optoelectronic systems with high-performance and ultralow power consumption.
