For businesses that provide delivery services, the efficiency of the delivery process in terms of punctuality is very important. In addition to increasing customer trust, efficient route management, and selection are required to reduce vehicle fuel costs and expedite delivery. Some small and medium businesses still use conventional methods to manage delivery routes. Decisions to manage delivery schedules and routes do not use any specific methods to expedite the delivery settlement process. This process is inefficient, takes a long time, increases costs and is prone to errors. Therefore, the Dijkstra algorithm has been used to improve the delivery management process. A delivery management system was developed to help managers and drivers schedule efficient ways to deliver product orders to recipients. Based on testing, the Dijkstra algorithm that has been included in the nearest route search function for the delivery process has worked well. This system is expected to improve the efficient management and delivery of orders.
Background: Preterm labor and related prematurity are predisposing factors that increase perinatal morbidity and mortality. Acute phase reactants are inflammatory markers which are positive and negative reactants explained by the reaction of reactants to the subclinical infection that are commonly associated with preterm labor. Objectives: To assess the role of acute phase reactants in pregnant women with preterm delivery. Patients and method: A case control study conducted in Gynecological Department of Baghdad Teaching Hospital from 1st February 2021 to 30th October 2021, on one hundred pregnant women with gestational age (28weeks - 36weeks+6days) who attended outpatient clinic; fifty pregnant women with established preterm labor
... Show MoreImproved oral bioavailability of lipophilic substances can be achieved using self-emulsifying drug delivery systems. However, because the properties of self-emulsifying are greatly influenced by surfactant amount and type, type of oil used, droplet size, charge, cosolvents, and physiological variables, the synthesis of self-emulsifying is highly complex; consequently, only a small number of excipient self-emulsifying formulations has been developed so far for clinical use. This study reports a highly effective procedure for developing self-emulsifying formulations using a novel approach based on the hydrophilic-lipophilic difference theory. Microemulsion characteristics, such as the constituents and amounts of oil and surfactant electrolyte
... Show MoreDelivering therapeutic agents to the brain remains a major challenge due to the restrictive nature of the blood–brain barrier (BBB). Intranasal administration has emerged as a promising, non-invasive approach that bypasses the BBB and facilitates direct nose-to-brain transport via the olfactory and trigeminal pathways. In this study, we developed a nanostructured lipid carrier (NLC) system for the intranasal delivery of dolutegravir sodium, a potent integrase inhibitor, with the goal of enhancing brain bioavailability for the treatment of neuroHIV and related central nervous system (CNS) complications. The NLCs were optimized for particle size, polydispersity index (PDI), and drug incorporation efficiency. The optimized formulation exhibi
... Show MoreBackground: Frovatriptan succinate (FVT) is an effective medication used to treat migraines; however, available oral formulations suffer from low permeability; accordingly, several formulations of FVT were prepared. Objective: Prepare, optimize, and evaluate FVT-BE formulation to develop enhanced intranasal binary nano-ethosome gel. Methods: Binary ethosomes were prepared using different concentrations of phospholipid PLH90, ethanol, propylene glycol, and cholesterol by thin film hydration and characterized by particle size, zeta potential, and entrapment efficiency. Furthermore, in-vitro, in-vivo, ex-vivo, pharmacokinetics, and histopathological studies were done. Results: Regarding FVT-loaded BE, formula (F9) demonstrated the best paramet
... Show MoreAbstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.
In this study, a fast block matching search algorithm based on blocks' descriptors and multilevel blocks filtering is introduced. The used descriptors are the mean and a set of centralized low order moments. Hierarchal filtering and MAE similarity measure were adopted to nominate the best similar blocks lay within the pool of neighbor blocks. As next step to blocks nomination the similarity of the mean and moments is used to classify the nominated blocks and put them in one of three sub-pools, each one represents certain nomination priority level (i.e., most, less & least level). The main reason of the introducing nomination and classification steps is a significant reduction in the number of matching instances of the pixels belong to the c
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