Phytochemical Screening and Assays of Phenolic Compounds in Senna occidentalis L. Leaf and Seed Extracts

Phytochemical screening and assay of secondary metabolites, crude extracts with distilled water, aqueous methanol, aqueous acetone and aqueous ethanol of leaves and seeds of Senna occidentalis L. were studied in this work. The aim was to verify the distribution of secondary metabolites according to S. occidentalis organs. Four leaf samples from four different localities (South, East, West and Central Senegal) and a mixed sample of seeds were used. Functional molecules such as polyphenols, flavonoids and tannins were then assessed in the leaves and seeds using various standard methods. The results show that Senna occidentalis L. leaf and seed samples display an identical and homogeneous profile, regardless of locality. They contain secondary metabolites and the polyphenol content of extracts from southern, eastern, western and central leaves is: 0.620 - 0.539 - 0.811 - 0.573 g GAE/100 g DM;flavonoids: 0.064 - 0.074 - 0.130 - 0.101 g CE/100 g DM and tannins: 0.326 - 0.264 - 0.269 - 0.494 g TAE/100 g DM. The efficacy of S. occidentalis L. infusions in therapy is thus justified by the presence of these metabolites, whose biological properties are well known. It is then possible to explore isolation of active principles of Senna occidentalis L. leaves and even seeds for producing medicines.

Stochastic Simulation of Saline Intrusion in the Coastal Aquifer of Saloum, Senegal

In the Saloum region of central-western Senegal, water needs are essentially met by tapping an underground aquifer associated with the sandy-clay formations of the Continental Terminal, in contact with both the ocean to the west and the highly saline waters of the Saloum River to the north. In this estuarine and deltaic zone with its very low relief, the hydraulic loads in the water tables are generally close to zero or even negative, creating a reversal of the natural flow and encouraging saline intrusion into this system, which makes it very vulnerable. This study concerns the implementation of a numerical model of saline intrusion to provide a better understanding of the vulnerability of the water table by analyzing the variability of the freshwater/saltwater interface. The Modflow-2005 code is used to simulate saline intrusion using the SWI2 module, coupled with the GRASS (Geographic Resources Analysis Support System) software under the Linux operating system with the steep interface approach. The probable expansion of the wedge is studied in three scenarios, taking into account its position relative to the bedrock at 1 m, 5 m and 10 m. Simulations carried out under imposed potential and river conditions, based on variations in groundwater reserves using two effective porosity values, 10−1 and 10−2, show that the water table is highly vulnerable in the northwest sector. The probable expansion of the wedge increases as the storage coefficient decreases and is more marked with river conditions in the areas surrounding the Saloum River, reaching 6 km with a probability of 1. The probability of the wedge reaching a certain degree of expansion decreases from 1 to 0.5, and then cancels out as it moves inland. The probable position of the wedge is limited to 500 m or even 1 km depending on the corner around the coast to the southwest and in the southern zone. This modelling, carried out under natural conditions, will be developed further, taking into account climatic parameters and pumping from wells and boreholes.

Cameroon Climate Predictions Using the SARIMA-LSTM Machine Learning Model: Adjustment of a Climate Model for the Sudano-Sahelian Zone of Cameroon

It is acknowledged today within the scientific community that two types of actions must be considered to limit global warming: mitigation actions by reducing GHG emissions, to contain the rate of global warming, and adaptation actions to adapt societies to Climate Change, to limit losses and damages [1] [2]. As far as adaptation actions are concerned, numerical simulation, due to its results, its costs which require less investment than tests carried out on complex mechanical structures, and its implementation facilities, appears to be a major step in the design and prediction of complex mechanical systems. However, despite the quality of the results obtained, biases and inaccuracies related to the structure of the models do exist. Therefore, there is a need to validate the results of this SARIMA-LSTM-digital learning model adjusted by a matching approach, “calculating-test”, in order to assess the quality of the results and the performance of the model. The methodology consists of exploiting two climatic databases (temperature and precipitation), one of which is in-situ and the other spatial, all derived from grid points. Data from the dot grids are processed and stored in specific formats and, through machine learning approaches, complex mathematical equations are worked out and interconnections within the climate system established. Through this mathematical approach, it is possible to predict the future climate of the Sudano-Sahelian zone of Cameroon and to propose adaptation strategies.

Experimental Study of the Anti-Corrosion Performance of Montmorillonite K-10 on Rebar in HCl Environment: Application in Mortar for the Rehabilitation of Reinforced Concrete Degraded by Corrosion

This work first investigates the corrosion-inhibiting behavior of montmorillonite K-10 on reinforcing steel. The corrosion-inhibiting power of the clay (Montmorillonite) is determined in a medium HCl (C = 1N) using free corrosion potential monitoring, Tafel potentiodynamic polarization curves and electrochemical impedance spectroscopy. The results of this study showed a satisfactory corrosion-inhibiting efficiency of around 72.665% for the optimum content of 1%. This is due to the presence of a stable oxide layer that protects the metal against corrosion. To validate the concept of montmorillonite as a corrosion inhibitor in repair mortar, we now turn to the influence of montmorillonite on the mechanical properties of mortars in the hardened state. In this part, montmorillonite K-10 is added to the mortar by partial substitution of the cement by 5% and 10% of the cement mass. The aim of this study is to ensure that the addition of this clay to the mortar composition will not have a negative effect on its compressive and flexural strengths. The results of the compression and flexural tests showed that the presence of montmorillonite in the mortar improved flexural and compressive strengths for the different compositions studied.

The Role and Place of Artificial Neural Network Architectures Structural Redundancy in the Input Data Prototypes and Generalization Development

Neural Networks (NN) are the functional unit of Deep Learning and are known to mimic the behavior of the human brain to solve complex data-driven problems. Whenever we train our own neural networks, we need to take care of something called the generalization of the neural network. The performance of Artificial Neural Networks (ANN) mostly depends upon its generalization capability. In this paper, we propose an innovative approach to enhance the generalization capability of artificial neural networks (ANN) using structural redundancy. A novel perspective on handling input data prototypes and their impact on the development of generalization, which could improve to ANN architectures accuracy and reliability is described.

Dietary Surveys Carried out among Diabetic Patients Hospitalized in the Metabolic and Endocrine Diseases Department of the C.H.U-B

A varied and balanced diet has always been essential in the optimal management of diabetes. The objective of this work was to evaluate dietary surveys among 50 diabetic patients hospitalized in the metabolic and endocrine diseases department of the Brazzaville Hospital and University Center. This survey was carried out using two methods: dietary history and 24-hour recall. The results relating to the dietary history revealed in the patients a dietary imbalance characterized by snacking at meals, non-compliance with a balanced diet and a high frequency of consumption of foods rich in simple sugar. and saturated fats. Regarding the 24-hour recall, the survey showed that the average blood sugar levels of hospitalized patients increased depending on the number of meals. This meant that these hyperglycemias (2 to 5 g/L) observed in these patients exceeded three meals per day and required, among other things, an increase in insulin intake or doses. The age groups of diabetic patients were also divided. These age groups had partly defined the types of diabetes encountered. Regarding body mass index, women had a body mass index greater than 30 kg/m2 compared to men. This increase in body mass index was explained by being overweight or even obese due to excess body fat.