Functional Analysis of the Genotypic Differences in Response of Pea (Pisum sativum L.) to Calcareous-Induced Iron Deficiency

Lime-induced iron chlorosis is a major nutritional disorder causing severe plant growth and yield reduction in the calcareous soils of Tunisia.The understanding the behavior of key metabolic functions of peas on calcareous soils,the identification of useful traits of tolerance,and the exploration of the genotypic differences in response to this constraint remain the most efficient approaches due to their coast,environmental benefits,and sustainability.For this purpose,a greenhouse experiment was conducted on three pea genotypes(Alexandra:Alex,Douce de provence:DP,and Merveille de Kelvedon:MK)cultivated on calcareous soil(Fe-deficient)and fertile soil(control).Plant growth,SPAD index,iron nutrition and distribution,photosynthesis,and antioxidant enzymes were deeply analyzed to discriminate genotypic differences.Calcareous-induced iron deficiency reduced SPAD index,plant growth,net photosynthesis,and tissue Fe content against a significant stimulation of the oxidative stress indicators,H2O2 and Malondialdehyde(MDA).Moreover,we reported a significant induction of SOD and CAT activity in shoots and roots of the Alexandra genotype.Fe use efficiency increased on calcareous soil and clearly discriminated the studied genotypes.Alexandra genotype was found to be the most tolerant to lime-induced iron chlorosis.This genotype protects its tissues against oxidative stress by stimulating enzyme activities(SOD and CAT)and develops significant efficiency of Fe uptake,translocation to shoots and use when cultivated on calcareous soil.

Automatic Detection of COVID-19 Using a Stacked Denoising Convolutional Autoencoder

The exponential increase in new coronavirus disease 2019(COVID-19)cases and deaths has made COVID-19 the leading cause of death in many countries.Thus,in this study,we propose an efficient technique for the automatic detection of COVID-19 and pneumonia based on X-ray images.A stacked denoising convolutional autoencoder(SDCA)model was proposed to classify X-ray images into three classes:normal,pneumonia,and COVID-19.The SDCA model was used to obtain a good representation of the input data and extract the relevant features from noisy images.The proposed model’s architecture mainly composed of eight autoencoders,which were fed to two dense layers and SoftMax classifiers.The proposed model was evaluated with 6356 images from the datasets from different sources.The experiments and evaluation of the proposed model were applied to an 80/20 training/validation split and for five cross-validation data splitting,respectively.The metrics used for the SDCA model were the classification accuracy,precision,sensitivity,and specificity for both schemes.Our results demonstrated the superiority of the proposed model in classifying X-ray images with high accuracy of 96.8%.Therefore,this model can help physicians accelerate COVID-19 diagnosis.

Automatic Migration of a Software Task to Hardware Component in MPSoC Systems

The authors will focus on the study of the design of Multiprocessor Systems on Chip （MPSoC）, specifically in the context of improving the performance of applications located on the MPSoC architecture. The objective of this research is to study the problems of transition from a pure software implementation for an embodiment admitting one or more hardware components and to develop a methodology for automatic generation of migration of a software task into a hardware component in MPSoC. The transformation of a software task into a hardware task led to many changes, hardware part （connection, the requirement of an interrupt controller...）, software part （at least one task, I/O （I/O）, synchronization...） and an architectural point of view, the remarkable aspects of data storage. The experiment is done on the MJPEG decoder to illustrate the effectiveness of the authors＇ tool for automatic generation of migration.

The Physiological Mechanisms Underlying N_(2)-Fixing Common Bean(Phaseolus vulgaris L.)Tolerance to Iron Deficiency

Iron is an essential element for plants as well as all living organisms,functioning in various physiological and biochemical processes such as photosynthesis,respiration,DNA synthesis,and N2 fixation.In the soil,Fe bioavailability is extremely low,especially under aerobic conditions and at high pH ranges.In contrast,plants with nodules on their roots that fix atmospheric nitrogen need much more iron.To highlight the physiological traits underlying the tolerance of N2-fixing common bean to iron deficiency,two genotypes were hydroponically cultivated in a greenhouse:Coco nain(CN)and Coco blanc(CB).Plants were inoculated with an efficient strain of Rhizobium tropici,CIAT899,and received a nutrient solution added with 0μM Fe(severe Fe deficiency,SFeD),5μM Fe(moderate Fe deficiency,MFeD)or 45μM Fe(control,C).Several physiological parameters related to photosynthesis and symbiotic nitrogen fixation were then analyzed.Iron deficiency significantly reduced whole plant and nodule growth,chlorophyll biosynthesis,photosynthesis,leghemoglobin(LgHb),nitrogenase(N2ase)activity,nitrogen,and Fe nutrition,with some genotypic differences.As compared to CB,CN maintained better Fe allocation to shoots and nodules,allowing it to preserve the integrity of its photosynthetic and symbiotic apparatus,thus maintaining the key functional traits of the plant metabolism(chlorophyll biosynthesis and photosynthesis in shoots,leghemoglobin accumulation,and nitrogenase activity in root nodules).Plant growth depends on photosynthesis,which needs to be supplied with sufficient iron and nitrogen.Fe deficiency stress index(FeD-SI)and Fe use efficiency(FeUE)are two physiological traits of tolerance that discriminated the studied genotypes.

Hybrid Evolutionary Algorithm Based Relevance Feedback Approach for Image Retrieval

Searching images fromthe large image databases is one of the potential research areas of multimedia research.The most challenging task for nay CBIR system is to capture the high level semantic of user.The researchers of multimedia domain are trying to fix this issue with the help of Relevance Feedback(RF).However existing RF based approaches needs a number of iteration to fulfill user’s requirements.This paper proposed a novel methodology to achieve better results in early iteration to reduce the user interaction with the system.In previous research work it is reported that SVM based RF approach generating better results for CBIR.Therefore,this paper focused on SVM based RF approach.To enhance the performance of SVM based RF approach this research work applied Particle Swarm Optimization(PSO)and Genetic Algorithm(GA)before applying SVM on user feedback.The main objective of using thesemeta-heuristic was to increase the positive image sample size from SVM.Firstly steps PSO is applied by incorporating the user feedback and secondly GA is applied on the result generated through PSO,finally SVM is applied using the positive sample generated through GA.The proposed technique is named as Particle Swarm Optimization Genetic Algorithm-Support Vector Machine Relevance Feedback(PSO-G A-SVMRF).Precisions,recall and F-score are used as performance metrics for the assessment and validation of PSO-GA-SVM-RF approach and experiments are conducted on coral image dataset having 10908 images.From experimental results it is proved that PSO-GA-SVM-RF approach outperformed then various well known CBIR approaches.

Application of Response Surface Methodology for Optimization of Cadmium Ion Removal from an Aqueous Solution by Eggshell Powder

The removal of cadmium（Cd） from synthetic solutions by batch adsorption process was performed using eggshell powder, which is mainly composed of calcite（CaCO3）. In order to optimize the adsorption process, a re- sponse surface methodology（RSM） based on Central Composite Design（CCD） was applied. Developed model for Cd removal yields（R, %） response was statistically validated by variance analysis（ANOVA） which showed a high de- termination coefficient value（R2=0.9889）. According to Minitab software, the optimal conditions were found at tem- perature of 44℃, eggshell adsorbent dose of 2.98 g, initial Cd concentration of 36.74 mg/L and initial pH of 7. Under these conditions, the Cd removal yield was 98.76%. The deviation value of 1.24% confirms the validity of the model for the adsorption process optimization. The adsorption isotherm has been described by a Freundlich model. In addition, the predominant sorption mechanisms are the chemisorptions or precipitation（non-reversible） and ion ex- change（reversible）.

Study of a Generalized Nonlinear Euler-Poisson-Darboux System:Numerical and Bessel Based Solutions

In this paper a nonlinear Euler-Poisson-Darboux system is considered.In a first part,we proved the genericity of the hypergeometric functions in the development of exact solutions for such a system in some special cases leading to Bessel type differential equations.Next,a finite difference scheme in two-dimensional case has been developed.The continuous system is transformed into an algebraic quasi linear discrete one leading to generalized Lyapunov-Sylvester operators.The discrete algebraic system is proved to be uniquely solvable,stable and convergent based on Lyapunov criterion of stability and Lax-Richtmyer equivalence theorem for the convergence.A numerical example has been provided at the end to illustrate the efficiency of the numerical scheme developed in section 3.The present method is thus proved to be more accurate than existing ones and lead to faster algorithms.

Stochastic Nicholson's blowflies model with delays

In this research work,we introduce a new concept of double measure ergodic processes to identify the space of double measure pseudo almost periodic(or pap)processes in the pth mean sense.We display some findings regarding the completeness as well as the composition theorems and the invariance of the space consisting in double measure pap processes.Motivated by the above-mentioned results,the Banach fixed point theorem and the stochastic analysis techniques,we prove the existence,uniqueness and the global exponential stability of doubly measure pseudo almost periodic mild solution for a class of stochastic Nicholson's blowflies model with mixed delays in a separable real Hilbert space.The concluding part of the work is crowned with an example to confirm the reliability and feasibility of our findings.

New results for a Lasota-Wazewska model

In nature there is no phenomenon that is purely periodic,and this gives the idea to consider the measure pseudo almost periodic oscillation.In this paper,by employing a suitable fixed point theorem,the proper ties of the measure pseudo almost periodic functions and differential inequality,we investigate the existence and uniqueness of the measure pseudo almost periodic solutions for some models of Lasota-Wazewska equation with measure pseudo almost periodic coefficients and mixed delays.We suppose that the linear part has almost periodic and the nonlinear part is assumed to be measure pseudo almost periodic.Moreover,the global attractivity and the exponential stability of the measure pseudo almost periodic solutions are also considered for the system.As application,an illustrative numerical example is given to demonstrate the effectiveness of the obtained results.