Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

This study was perform to defined the effect of fungus Metarhizium anisopliae Sorokin with concentrations 5x101, 5x103 and 5x105 spore/ ml and Actelic insecticide with concentration 0.001% in pupa stages of Callosobruchus maculatus in pupa ages of 24 and 120 hours the results of the study showed the following: the highest killing rate of treated pupa in age 120 hours 100% at concentration 105 spore/ ml. observation for distortions in the adult insects from the pupa that treated with fungal concentration like wings and abdominal distortion , the concentration of fungal effect on the number of eggs that production from adults and percentage of hatching.

Autorías: Hadeer Idan Ghanim, Ishraq Mahmood. Localización: Revista iberoamericana de psicología del ejercicio y el deporte. Nº. 3, 2021. Artículo de Revista en Dialnet.

Flavonoids were extracted from Zizyphus spina-christi leaves by Ethyl acetate after acid digested and used as antioxidant. The dried extract was added separately to each sample of fat extracted from hallow cow and sheep bones as follows: T1 cow fat, T2 control for cow fat, T3 sheep fat and T4 control for sheep fat (the control T2 and T4 reffered to samples without added antioxidant).
Samples were stored at -18, 5, 25 and 55 °C for 28 days. The storage trials were conducted at -18, 5 and 25 °C for 28 days for T1, T2, T3 and T4. The chemical indices examined initially and at the end of storage period. PVs was 1.46, 1.46, 1.8 and 1.8 meq/ Kg oil respectively, FFA values were 0.245, 0.245, 0.244 and 0.244% respectively and TBA va

The physical, mechanical, electrical and thermal properties containing (Viscosity, curing, adhesion force, Tensile strength, Lap shear strength, Resistively, Electrical conductivity and flammability) of adhesive material that prepared from Nitrocellulose reinforced with graphite particles and aluminum streat. A comparison is made between the properties of adhesive material with varying percentage of graphite powder (0%, 25%, 30%, 35%, 40%) to find out the effect of reinforcement on the adhesive material. The ability of property an electrical was studied through the measurement of conductivity a function of temperature varying. The results of comparison have clearly shown that the increasing of conten

Heterocyclic systems, which are essential in medicinal chemistry due to their promising cytotoxic activity, are one of the most important families of organic molecules found in nature or produced in the laboratory. As a result of coupling N-(4-nitrophenyl)-3-oxo-butanamide (3) using thiourea, indole-3-carboxaldehyde, or piperonal, the pyrimidine derivatives (5a and 5b) were produced. Furthermore, pyrimidine 9 was synthesized by reacting thiophene-2-carboxaldehyde with ethyl cyanoacetate and urea with potassium carbonate as a catalyst. The chalcones 11a and 11b were synthesized by reacting equal molar quantities of 1-naphthaldehy

        Peroxidase is a class of oxidation-reduction reaction enzyme that is useful for accelerating many oxidative reactions that protect cells from the harmful effects of free radicals. Peroxidase is found in many common sources like plants, animals and microbes and have extensive uses in numerous industries such as industrial, medical and food processing. In this study, P. aeruginosa was harvested to utilize and study its peroxidases. P. aeruginosa was isolated from a burn patient, and the isolate was verified as P. aeruginosa using staining techniques, biochemical assay, morphological, and a sensitivity test. The gram stain and biochemical test result show rod pink gram-ne

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod