This study was included the isolation of four strains from two species of lactic acid bacteria which as Lactococcus lactis subsp. diacetylactis; Lactococcus lactis subsp. lactis; Leuconostoc mesenteroides subsp. mesenteroides and Leuconostoc mesenteroides subsp. cremoris, were isolated from locally fermented diary products. The isolated were identified by using morphological, cultural and biochemical tests. Their abilities to producing flavor compounds as each Diacetyl and Acetoin after cultured on MRS broth media and incubation at 30 °c for 24 hours. The results indicated that’s all strains were produced the acetoin significantly (P<0.05) more than diacetyl compound. The production of Lactococcus lactis subsp. diacetylactis from Diacety

Scheduling considered being one of the most fundamental and essential bases of the project management. Several methods are used for project scheduling such as CPM, PERT and GERT. Since too many uncertainties are involved in methods for estimating the duration and cost of activities, these methods lack the capability of modeling practical projects. Although schedules can be developed for construction projects at early stage, there is always a possibility for unexpected material or technical shortages during construction stage. The objective of this research is to build a fuzzy mathematical model including time cost tradeoff and resource constraints analysis to be applied concurrently. The proposed model has been formulated using fuzzy the

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

Malaysia's growing population and industrialisation have increased solid waste accumulation in landfills, leading to a rise in leachate production. Leachate, a highly contaminated liquid from landfills, poses environmental risks and affects water quality. Conventional leachate treatments are costly and time-consuming due to the need for additional chemicals. Therefore, the Electrocoagulation process could be used as an alternative method. Electrocoagulation is an electrochemical method of treating water by eliminating impurities by applying an electric current. In the present study, the optimisation of contaminant removal was investigated using Response Surface Methodology. Three parameters were considered for optimisation: the curr

In this study, mean free path and positron elastic-inelastic scattering are modeled for the elements hydrogen (H), carbon (C), nitrogen (N), oxygen (O), phosphorus (P), sulfur (S), chlorine (Cl), potassium (K) and iodine (I). Despite the enormous amounts of data required, the Monte Carlo (MC) method was applied, allowing for a very accurate simulation of positron interaction collisions in live cells. Here, the MC simulation of the interaction of positrons was reported with breast, liver, and thyroid at normal incidence angles, with energies ranging from 45 eV to 0.2 MeV. The model provides a straightforward analytic formula for the random sampling of positron scattering. ICRU44 was used to compile the elemental composition data. In this

The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample

Pregnancy- including hypertension(PIH), also known as preeclampsia, is one of the major causes of maternal and fetal death. This study was carried out on 30 pregnant women with preeclampsia and 30 healthy pregnant women as control ranging in age mean ±SD (28.84±3.55) years , BMI (76.80±9.78) Kg/m2 and gestation age(30.82±0.75)week. The aim of this research was studied the plasma Metanephrine level and other biochemical parameters such as Hemoglobin(Hb), serum Protein, S. Albumin, Globulin, Albumin/Globulin ratio (Alb/Glu. ratio), S.Glutamate Pyruvate aminotransferase (GPT), S.Glutamate Oxaloacetate aminotransferase(GOT). The obtained results have been compared with 30 healthy pregnant women as control group. The result showed that ther

Background: Periodontal diseases (PD) are inflammatory conditions of the tissues supporting the teeth, most often gingivitis and periodontitis. Maxillary chronic rhinosinusitis (MCRS) is the inflammation of the maxillary sinuses which is last for at least 12 consecutive weeks duration. Aims of study: Distribution of periodontal diseases among patients with Maxillary chronic rhinosinusitis according to gender and age. Materials and methods: Males and females subjects (25-45 years), divided into two groups; 150 patients suffer from MCRS and 130 subjects without MCRS. Clinical periodontal parameters; Plaque Index (PL.I), Gingival Index (G.I), Probing Pocket Depth (PPD), Clinical Attachment Level (CAL) and Bleeding On Probing (BOP) recorded f