Gudermannian neural network procedure for the nonlinear prey-predator dynamical system.

The present study performs the design of a novel Gudermannian neural networks (GNNs) for the nonlinear dynamics of prey-predator system (NDPPS). The process of GNNs is applied using the global and local search approaches named as genetic algorithm and interior-point algorithms, i.e., GNNs-GA-IPA. An error-based merit function is constructed using the NDPPS and its initial conditions and then optimized by the hybrid of GA-IPA. Six cases of the NDPPS using the variable coefficients have been presented and the correctness is observed through the overlapping of the obtained and Runge-Kutta reference results. The results of the NDPPS have been performed between 0 and 5 using the step size 0.02. The graph of absolute error are performed around 10-06 to 10-08 to check the consistency of the proposed GNNs-GA-IPA. The statistical analysis based minimum, median and semi-interquartile ranges have been performed for both predator and prey dynamics of the model. Moreover, the investigations through the statistical operators are performed to validate the reliability of the obtained outcomes based on multiple trials.

Bio inspired heuristic computing scheme for the human liver nonlinear model.

In this research, a bio-inspired heuristic computing approach has been developed to solve the nonlinear behavior of the human liver, which is categorized into the liver and blood. The solutions of the human liver model are presented by using the stochastic computation procedure based on the artificial neural network (ANN) along with the optimization of genetic algorithm (GA) and interior-point (IP). A fitness function is designed through the differential form of the nonlinear human liver model and then optimized by using the hybrid competency of GAIP scheme. The correctness and exactness of the proposed approach are observed through the overlapping of the obtained (GAIP) and reference (Adams scheme) solutions, while the calculated absolute error values in good order enhance the worth of the proposed solver. The log-sigmoid transfer function together with ten numbers of neurons is executed to perform the solutions of the human liver nonlinear model. Furthermore, the statistical approaches have been applied in order to observe the reliability of the designed approach for solving the nonlinear human liver model.

An artificial neural network approach for the language learning model.

The current study provides the numerical solutions of the language-based model through the artificial intelligence (AI) procedure based on the scale conjugate gradient neural network (SCJGNN). The mathematical learning language differential model is characterized into three classes, named as unknown, familiar, and mastered. A dataset is generalized by using the performance of the Adam scheme, which is used to reduce to mean square error. The AI based SCJGNN procedure works by taking the data with the ratio of testing (12%), validation (13%), and training (75%). An activation log-sigmoid function, twelve numbers of neurons, SCJG optimization, hidden and output layers are presented in this stochastic computing work for solving the learning language model. The correctness of AI based SCJGNN is noted through the overlapping of the results along with the small calculated absolute error that are around 10-06 to 10-08 for each class of the model. Moreover, the regression performances for each case of the model is performed as one that shows the perfect model. Additionally, the dependability of AI based SCJGNN is approved using the histogram, and function fitness.

Heuristic computing with active set method for the nonlinear Rabinovich-Fabrikant model.

The current study shows a reliable stochastic computing heuristic approach for solving the nonlinear Rabinovich-Fabrikant model. This nonlinear model contains three ordinary differential equations. The process of stochastic computing artificial neural networks (ANNs) has been applied along with the competences of global heuristic genetic algorithm (GA) and local search active set (AS) methodologies, i.e., ANNs-GAAS. The construction of merit function is performed through the differential Rabinovich-Fabrikant model. The results obtained through this scheme are simple, reliable, and accurate, which have been calculated to optimize the merit function by using the GAAS method. The comparison of the obtained results through this scheme and the conventional reference solutions strengthens the correctness of the proposed method. Ten numbers of neurons along with the log-sigmoid transfer function in the neural network structure have been used to solve the model. The values of the absolute error are performed around 10-07 and 10-08 for each class of the Rabinovich-Fabrikant model. Moreover, the reliability of the ANNs-GAAS approach is observed by using different statistical approaches for solving the Rabinovich-Fabrikant model.

Hybridization of the swarming and interior point algorithms to solve the Rabinovich-Fabrikant system.

In this study, a trustworthy swarming computing procedure is demonstrated for solving the nonlinear dynamics of the Rabinovich-Fabrikant system. The nonlinear system's dynamic depends upon the three differential equations. The computational stochastic structure based on the artificial neural networks (ANNs) along with the optimization of global search swarming particle swarm optimization (PSO) and local interior point (IP) algorithms, i.e., ANNs-PSOIP is presented to solve the Rabinovich-Fabrikant system. An objective function based on the differential form of the model is optimized through the local and global search methods. The correctness of the ANNs-PSOIP scheme is observed through the performances of achieved and source solutions, while the negligible absolute error that is around 10-05-10-07 also represent the worth of the ANNs-PSOIP algorithm. Furthermore, the consistency of the ANNs-PSOIP scheme is examined by applying different statistical procedures to solve the Rabinovich-Fabrikant system.

A fractional order nonlinear model of the love story of Layla and Majnun.

In this study, a fractional order mathematical model using the romantic relations of the Layla and Majnun is numerically simulated by the Levenberg-Marquardt backpropagation neural networks. The fractional order derivatives provide more realistic solutions as compared to integer order derivatives of the mathematical model based on the romantic relationship of the Layla and Majnun. The mathematical formulation of this model has four categories that are based on the system of nonlinear equations. The exactness of the stochastic scheme is observed for solving the romantic mathematical system using the comparison of attained and Adam results. The data for testing, authorization, and training is provided as 15%, 75% and 10%, along with the twelve numbers of hidden neurons. Furthermore, the reducible value of the absolute error improves the accuracy of the designed stochastic solver. To prove the reliability of scheme, the numerical measures are presented using correlations, error histograms, state transitions, and regression.

A neuro swarm procedure to solve the novel second order perturbed delay Lane-Emden model arising in astrophysics.

The current work provides a mathematical second order perturbed singular delay differential model (SO-PSDDM) by using the standard form of the Lane-Emden model. The inclusive structures based on the delay terms, singular-point and perturbation factor and shape forms of the SO-PSDDM are provided. The novel form of the SO-PSDDM is numerically solved by using the procedures of artificial neural networks (ANNs) along with the optimization measures based on the swarming procedures (PSO) and interior-point algorithm (IPA). An error function is optimized through the swarming PSO procedure along with the IPA to solve the SO-PSDDM. The precision, substantiation and validation are observed for three problems of the SO-PSDDM. The exactness of the novel SO-PSDDM is observed by comparing the obtained and exact solutions. The reliability, stability and convergence of the proposed stochastic algorithms are observed for 30 independent trials to solve the novel SO-PSDDM.

Phylogenetic analysis and growth profiles of Fusarium incarnatum-equiseti species complex strains isolated from Tunisian cereals.

The Fusarium incarnatum-equiseti species complex (FIESC) is a phylogenetically rich complex. It includes more than 30 cryptic phylogenetic species, making morphological identification problematic. FIESC has previously been detected in Tunisian cereals, but knowledge on the phylogeny and the ecophysiology of their species is lacking. In this work a phylogenetic analysis was performed using partial sequences of the translation elongation factor 1a gene (EF1a) of three FIESC strains isolated from barley and wheat from Tunisia, situated south in the Mediterranean basin, and additional strains from other countries. The results indicated that all Tunisian strains clustered with FIESC 5 group (F. clavum) together with other Spanish FIESC 5 strains also isolated from cereals. Growth rate profiles of the Tunisian strains were also determined on wheat and sorghum based media at a range of temperatures (15, 20, 25, 30, 35 and 40 °C) and water potential values (-0.7, -2.8, -7.0, and -9.8 MPa, corresponding to 0.995, 0.98, 0.95 and 0.93 aw values). Optimal growth was observed at 20-30 °C and between -0.7 and -7.0 MPa on both substrates (wheat and sorghum). The highest growth rate for the three strains was seen at 25 °C combined with -2.8 MPa. The comparison between the growth profiles of Tunisian and Spanish FIESC 5 strains showed similar trends with some interesting differences regarding temperature and water potential factors. Tunisian strains seem to perform better between 15 and 30 °C and, notably, at even lower water potentials included -9.8 Mpa. This might suggest that tolerance to low water potentials might be for Tunisian strains a more important selective clue than to higher temperatures. These results appeared to be consistent with a population well adapted to the present climatic conditions and predicted scenarios for North Africa.

Contamination of Wheat, Barley, and Maize Seeds with Toxigenic Fusarium Species and Their Mycotoxins in Tunisia.

BACKGROUND: Fusarium is a worldwide distributed fungal genus. It includes different species pathogenic to cereals among others crops. Some of these species can also produce toxic compounds toward animals and humans. OBJECTIVE: In this work, occurrence of fumonisins B1+B2, zearalenone, type A trichothecenes (T-2 and HT-2 toxins), and type B trichothecenes (deoxynivalenol[DON] and nivalenol[NIV]) was studied in 65 samples of stored and freshly harvested wheat, barley, and maize collected in Tunisia. METHODS: Mycotoxins analyses were performed by using gas chromatography for type B trichothecenes and HPLC for other mycotoxins. Obtained results were compared with the presence of mycotoxigenic species considered responsible for their synthesis by using species-specific polymerase chain reaction (PCR). RESULTS: Fumonisins occurred in 20.83% of wheat, 40% of barley, and 57.14% of maize samples, at levels exceeding European limits and suggesting a risk in Tunisian cereals, especially maize. Zearalenone, DON, NIV, and T-2+HT-2 toxins were detected at lower values in only wheat and barley samples. PCR protocols showed the predominance of F. verticillioides especially in maize, and occurrence of F. equiseti and F. graminearum in wheat and barley, and F. proliferatum in only two maize samples. A very consistent correlation was found between the detection of F. verticillioides and the contamination by fumonisins, as well as between the presence of F. graminearum and the contamination by zearalenone, DON, and NIV in the analyzed cereals. CONCLUSIONS: Consequently, the detection of Fusarium species with the current PCR assays strategy in wheat, barley, and maize grains may be considered predictive of their potential mycotoxin risk in these matrices. HIGHLIGHTS: This work is the first to report information on the occurrence of fumonisins, trichothecene, and ZEN, together with their potentially producing Fusarium species in wheat, barley, and maize in Tunisia. The high level of fumonisins in cereals, especially maize, stresses the importance of the control and the regularization of these mycotoxins for food safety.

Mycoflora isolation and molecular characterization of Aspergillus and Fusarium species in Tunisian cereals.

Wheat, barley and maize are the mainly consumed cereals in Tunisia. This study aimed to determine the mycoflora of these cereals with special focus on the mycotoxigenic Aspergillus and Fusarium species. Freshly harvested samples and other stored samples of each type of cereal (31 and 34 samples, respectively) were collected in Tunisia and cultured for fungal isolation and identification. Identification of fungal genera was based on morphological features. Aspergillus and Fusarium species were identified by species specific PCR assays complemented with DNA sequencing. Alternaria (70.83%), Eurotium (62.50%), Aspergillus (54.17%) and Penicillium (41.67%) were the most frequent fungi isolated from wheat. Penicillium (75%), Aspergillus (70%), Eurotium (65%) and Alternaria (65%) were the most frequently recovered genera from barley. The predominant genera in maize were Aspergillus (76.19%), Eurotium (42.86%), and Penicillium (38.09%). Aspergilllus, Penicillium, Fusarium and Alternaria were detected in both stored and freshly harvested grain samples. The frequencies of contamination with Aspergillus, Fusarium and Alternaria were higher in freshly harvested samples, whereas Penicillium species were more frequent in stored samples. The predominant Aspergillus species detected were A. flavus and A. niger. The Fusarium species detected were F. equiseti, F. verticillioides, F. nygamai, and F. oxysporum. This study suggested the potential risk for Aflatoxins and, to a lesser extent, for Ochratoxin A in Tunisian cereals. This is the first survey about mycoflora associated with wheat, barley and maize in Tunisia.

Aflatoxin B1, ochratoxin A and zearalenone in sorghum grains marketed in Tunisia.

A total of 64 samples of sorghum (37 Tunisian sorghum samples and 27 Egyptian sorghum samples) were collected during 2011-2012 from markets in Tunisia. Samples were analysed for contamination with aflatoxin B1, ochratoxin A and zearalenone by High-Performance Liquid Chromatography Coupled with Fluorescence Detection (HPLC-FLD). Aflatoxin B1 was found in 38 samples in the range 0.03-31.7 µg kg-1. Ochratoxin A was detected in 24 samples with concentrations ranging from 1.04 to 27.8 µg kg-1. Zearalenone was detected in 21 samples and the concentration varied between 3.7 and 64.5 µg kg-1. ANOVA analysis of the influence of the country of origin on the incidence and concentration of mycotoxins in the samples studied showed no significant difference (P > 0.05) between the two batches of samples for each of the three mycotoxins studied. The studied mycotoxins contaminate sorghum and may also co-exist because of the diversity of the mycobiota in this cereal.

Transfer Learning: A Riemannian Geometry Framework With Applications to Brain-Computer Interfaces.

OBJECTIVE: This paper tackles the problem of transfer learning in the context of electroencephalogram (EEG)-based brain-computer interface (BCI) classification. In particular, the problems of cross-session and cross-subject classification are considered. These problems concern the ability to use data from previous sessions or from a database of past users to calibrate and initialize the classifier, allowing a calibration-less BCI mode of operation. METHODS: Data are represented using spatial covariance matrices of the EEG signals, exploiting the recent successful techniques based on the Riemannian geometry of the manifold of symmetric positive definite (SPD) matrices. Cross-session and cross-subject classification can be difficult, due to the many changes intervening between sessions and between subjects, including physiological, environmental, as well as instrumental changes. Here, we propose to affine transform the covariance matrices of every session/subject in order to center them with respect to a reference covariance matrix, making data from different sessions/subjects comparable. Then, classification is performed both using a standard minimum distance to mean classifier, and through a probabilistic classifier recently developed in the literature, based on a density function (mixture of Riemannian Gaussian distributions) defined on the SPD manifold. RESULTS: The improvements in terms of classification performances achieved by introducing the affine transformation are documented with the analysis of two BCI datasets. CONCLUSION AND SIGNIFICANCE: Hence, we make, through the affine transformation proposed, data from different sessions and subject comparable, providing a significant improvement in the BCI transfer learning problem.

Modulatory effect of curcumin against genotoxicity and oxidative stress induced by cisplatin and methotrexate in male mice.

The use of dietary antioxidants to modulate the toxic side effects induced by the anticancer drugs used in chemotherapy is currently eliciting considerable interest. This study was undertaken to investigate the possible protective role of the antioxidant curcumin (CMN) against genotoxicity, cytotoxicity and oxidative stress induced by cisplatin and methotrexate. Male mice were administered CMN orally in the dosages of 60, 90, and 120 mg/kg for three consecutive days before a single intraperitoneal injection of either cisplatin (6.5 mg/kg) or methotrexate (10 mg/kg). Animals were sacrificed 24 h after treatment with the used anticancer drugs. The protective role of CMN against the genotoxic and cytotoxic effects of the tested anticancer drugs was evaluated by using micronucleus and comet assay. The oxidative stress induced by the two anticancer drugs was assessed by determining malondialdehyde and reduced glutathione levels in kidney tissues. The results indicated that CMN pretreatment at the tested doses reduced the incidence of micronuclei and DNA damage induced by cisplatin and methotrexate. Moreover, malondialdhyde level was significantly decreased while glutathione level was significantly increased in CMN pretreated groups compared with cisplatin- and methotrexate-treated groups. This protective effect of CMN could be attributed to its ability to scavenge reactive oxygen species.

Aflatoxins and ochratoxin A and their Aspergillus causal species in Tunisian cereals.

Occurrence of aflatoxins (AFs) AFB1, AFB2, AFG1, AFG2 and ochra toxin A (OTA) was studied in 65 samples of stored and freshly harvested wheat, barley and maize collected in Tunisia. The mycotoxins were simultaneously extracted and quantified by high performance liquid chromatography. Determination of AF-producing (section Flavi) and OTA-producing Aspergillus species (sections Nigri and Circumdati) was conducted in these samples by species-specific polymerase chain reaction (PCR). Results showed that most of maize samples were contaminated with AFs, data after storage showing lower values than those collected at harvest. All contaminated maize samples contained AFG1 and AFG2, among which 27.78% also had AFB1 and AFB2. This AFs pattern was consistent with the A. parasiticus toxin profile. A. flavus however showed the highest frequency in maize but was also found in barley and wheat where no AFs were detected. In contrast, OTA was neither found in maize nor in barley and only one wheat sample contained OTA. A. niger was the only OTA-producing species detected.

Influence of temperature, water activity and incubation time on fungal growth and production of ochratoxin A and zearalenone by toxigenic Aspergillus tubingensis and Fusarium incarnatum isolates in sorghum seeds.

The major objective of this study was to describe the effect of water activity and temperature on radial growth and production of ochratoxin A (OTA) and zearalenone (ZEA) on sorghum grains of three Aspergillus tubingensis and three Fusarium incarnatum isolates. The water activity range was 0.91-0.99 aw for F. incarnatum isolates and 0.88-0.99 aw for A. tubingensis isolates. Temperatures of incubation were 15, 25 and 37°C for both species. Mycotoxin production was determined after 7, 14, 21 and 28days depending on the growth rate of the six isolates. Maximum growth rates (mm/day) were observed at 37°C and 0.99 aw for A. tubingensis isolates and at 0.99 aw and 25°C for F. incarnatum isolates. A. tubingensis was able to grow at 15°C only at the highest aw levels (0.97 and 0.99 aw). However, at this temperature F. incarnatum grew at 0.94 aw. Optimum ochratoxin A production was observed at 0.97 aw×37°C whereas optimal conditions for ZEA production varied from one isolate to another. Moreover, isolates of F. incarnatum from Tunisia do not require high aw and temperature levels to yield maximum levels of ZEA. In general, our results showed that there is no correlation between the growth and production of ZEA in the case of F. incarnatum. This is the first study on the water activity and temperature effect on growth rate and ZEA production of F. incarnatum. Our results show that sorghum grains not only support growth but also OTA and ZEA production by A. tubingensis and F. incarnatum, respectively.

Efectos de la temperatura, la actividad de agua y el tiempo de incubación en el crecimiento fúngico y la producción de aflatoxina B1 por aislados toxicogénicos de Aspergillus flavus en sorgo / Effects of temperature, water activity and incubation time on fungal growth and aflatoxin B1 production by toxinogenic Aspergillus flavus isolates on sorghum seeds

Sorghum, which is consumed in Tunisia as human food, suffers from severe colonization by several toxigenic fungi and contamination by mycotoxins. The Tunisian climate is characterized by high temperature and humidity that stimulates mold proliferation and mycotoxin accumulation in foodstuffs. This study investigated the effects of temperature (15, 25 and 37 °C), water activity (a w, between 0.85 and 0.99) and incubation time (7, 14, 21 and 28 d) on fungal growth and aflatoxin B1 (AFB1) production by three Aspergillus flavus isolates (8, 10 and 14) inoculated on sorghum grains. The Baranyi model was applied to identify the limits of growth and mycotoxin production. Maximum diameter growth rates were observed at 0.99 a w at 37 °C for two of the isolates. The minimum a w needed for mycelial growth was 0.91 at 25 and 37 °C. At 15 °C, only isolate 8 grew at 0.99 a w. Aflatoxin B1 accumulation could be avoided by storing sorghum at low water activity levels (≤0.91 a w). Aflatoxin production was not observed at 15 °C. This is the first work on the effects of water activity and temperature on A. flavus growth and AFB1 production by A. flavus isolates on sorghum grains.

El sorgo, que se consume en Túnez como alimento humano, puede sufrir la colonización severa de varios hongos toxicogénicos, con la consiguiente bioacumulación de micotoxinas. Además, el clima de Túnez, caracterizado por las altas temperaturas y humedad, estimula el crecimiento fúngico y la acumulación de micotoxinas en los productos alimenticios. Este estudio investigó los efectos de la temperatura (15, 25 y 37 °C), la actividad de agua (a w) (entre 0,85 y 0,99) y el tiempo de incubación (7, 14, 21 y 28 días) sobre el crecimiento y la producción de aflatoxina B1 (AFB1) de 3 aislados de Aspergillus flavus (designados como 8, 10 y 14) que se inocularon sobre granos de sorgo. El modelo Baranyi se aplicó para identificar los límites del crecimiento y la producción de micotoxinas. Las tasas máximas de crecimiento para 2 de los aislados se observaron en la combinación 0,99 a w y 37 °C. La a w mínima necesaria para el crecimiento del micelio fue de 0,91 a 25 °C y 37 °C. A 15 °C, solo el aislado 8 creció a 0,99 a w, pero fue incapaz de producir la aflatoxina B1. Es posible evitar la acumulación de aflatoxina B1 en el sorgo almacenándolo a baja actividad de agua (≤ 0,91 a w). Este es el primer trabajo que ha estudiado el efecto de la actividad del agua y la temperatura sobre el crecimiento de aislados de A. flavus y su producción de aflatoxina B1 en granos de sorgo.

Effects of temperature, water activity and incubation time on fungal growth and aflatoxin B1 production by toxinogenic Aspergillus flavus isolates on sorghum seeds.

Sorghum, which is consumed in Tunisia as human food, suffers from severe colonization by several toxigenic fungi and contamination by mycotoxins. The Tunisian climate is characterized by high temperature and humidity that stimulates mold proliferation and mycotoxin accumulation in foodstuffs. This study investigated the effects of temperature (15, 25 and 37°C), water activity (aw, between 0.85 and 0.99) and incubation time (7, 14, 21 and 28 d) on fungal growth and aflatoxin B1 (AFB1) production by three Aspergillus flavus isolates (8, 10 and 14) inoculated on sorghum grains. The Baranyi model was applied to identify the limits of growth and mycotoxin production. Maximum diameter growth rates were observed at 0.99 a(w) at 37°C for two of the isolates. The minimum aw needed for mycelial growth was 0.91 at 25 and 37°C. At 15°C, only isolate 8 grew at 0.99 a(w). Aflatoxin B1 accumulation could be avoided by storing sorghum at low water activity levels (≤0.91 a(w)). Aflatoxin production was not observed at 15°C. This is the first work on the effects of water activity and temperature on A. flavus growth and AFB1 production by A. flavus isolates on sorghum grains.

1,4,8,11-Tetra-azonia-cyclo-tetra-decane tetra-kis-(hydrogensulfate).

In the title salt, C10H28N4 (4+)·4HSO4 (-), the cation lies about an inversion center. In the crystal, O-H⋯O and N-H⋯O hydrogen bonds connect the anions and cations, forming a three-dimensional network.

A more accurate detection of codon 72 polymorphism and LOH of the TP53 gene.

The polymorphism at codon 72 of the TP53 gene has been extensively studied for its involvement in cancerogenesis and loss of heterozygosity (LOH) detection. Usually, the exon 4 of the TP53 gene is amplified by polymerase chain reaction (PCR) on DNA extracted from blood and tumor tissues, then digested by AccII. In the case of heterozygosity, the comparison of AccII profile from blood and tumor DNA PCR products allowed the identification of a potential LOH in the TP53 locus. This method can be hindered by a partial AccII digestion and/or DNA contamination of non-tumor cells. To circumvent these problems, we have developed a new approach by using the AccII restriction site between exon 4 and exon 6. The PCR amplification of exon 4-6, followed by AccII digestion allowed us to detect without ambiguity any LOH case.