According to the famous saying of the medieval physician Paracelsus, "There is no substance without poison. Only the dose determines the extent of the toxic effect." Here, the effect of monosodium glutamate (MSG) on human health and the risks to the health of its frequent use in the short term was addressed and the long term was evaluated according to the studies of several researchers specializing in this regard. Monosodium glutamate (MSG) is known as one of the most popular food additives that classified as a flavor enhancer. Parts of the evidence were reviewed from the literature explaining its effect on immune system cells in addition to metabolic disorders by exposing individuals to obesity and what is known as metabolic syndrome, as well as reviewing a lot of evidence indicating the effect of MSG intake on the health of the kidney, liver and other parts of the body through Practical application to laboratory rats and clinical studies in humans.
The consumption of fresh fruits has increased nowadays due to the lifestyle of the consumers. Maintaining the quality and nutritional value of cut fruits during storage is difficult compared to whole fruits. Deterioration of internal and external quality usually occurs in freshly harvested fruits. It is necessary to use different techniques to maintain the quality and increase the shelf life of the freshly cut product. This research studied the effect of treating apple slices with cold plasma once and with filtered water again on quality characteristics (hardness, moisture content, sugar content, carbohydrate content, and color) after being stored for five days. The best treatment was determined using two different pressures of the plasma j
... Show MoreIn this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images. So, this study aimed at testing the system performance at poo
... Show MoreIn this research, a study is introduced on the effect of several environmental factors on the performance of an already constructed quality inspection system, which was designed using a transfer learning approach based on convolutional neural networks. The system comprised two sets of layers, transferred layers set from an already trained model (DenseNet121) and a custom classification layers set. It was designed to discriminate between damaged and undamaged helical gears according to the configuration of the gear regardless to its dimensions, and the model showed good performance discriminating between the two products at ideal conditions of high-resolution images.
So, this study aimed at testing the system performance at poor s
... Show MoreBackground: This study was conducted among diabetic persons to assess the sweet and salty taste sensitivity with its effect on gingival health in relation to salivary serotonin levels. Materials and methods: A cross-sectional comparative study design was used. All patients with diabetes aged 12-14 years that attend the Paediatric hospital at Baghdad medical city with specific inclusion criteria were involved in the sample of the present study (patients group 50 patients) compared with non-diabetic persons matched in age and gender of the study sample (control group 70 patients) who were attending dental unit in the college of dentistry/university of Baghdad. A two-alternative forced choice question including each component presented at f
... Show MoreThis paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar
... Show MoreThis paper is specifically a detailed review of the Spatial Quantile Autoregressive (SARQR) model that refers to the incorporation of quantile regression models into spatial autoregressive models to facilitate an improved analysis of the characteristics of spatially dependent data. The relevance of SARQR is emphasized in most applications, including but not limited to the fields that might need the study of spatial variation and dependencies. In particular, it looks at literature dated from 1971 and 2024 and shows the extent to which SARQR had already been applied previously in other disciplines such as economics, real estate, environmental science, and epidemiology. Accordingly, evidence indicates SARQR has numerous benefits compar
... Show MoreTesting is a vital phase in software development, and having the right amount of test data is an important aspect in speeding up the process. As a result of the integrationist optimization challenge, extensive testing may not always be practicable. There is also a shortage of resources, expenses, and schedules that impede the testing process. One way to explain combinational testing (CT) is as a basic strategy for creating new test cases. CT has been discussed by several scholars while establishing alternative tactics depending on the interactions between parameters. Thus, an investigation into current CT methods was started in order to better understand their capabilities and limitations. In this study, 97 publications were evalua
... Show MoreBlockchain technology relies on cryptographic techniques that provide various advantages, such as trustworthiness, collaboration, organization, identification, integrity, and transparency. Meanwhile, data analytics refers to the process of utilizing techniques to analyze big data and comprehend the relationships between data points to draw meaningful conclusions. The field of data analytics in Blockchain is relatively new, and few studies have been conducted to examine the challenges involved in Blockchain data analytics. This article presents a systematic analysis of how data analytics affects Blockchain performance, with the aim of investigating the current state of Blockchain-based data analytics techniques in research fields and
... Show MoreTransdermal drug delivery has made an important contribution to medical practice but has yet to fully achieve its potential as an alternative to oral delivery and hypodermic injections. Transdermal therapeutic systems have been designed to provide controlled continuous delivery of drugs through the skin to the systemic circulation. A transdermal patch is an adhesive patch that has a coating of drug; the patch is placed on the skin to deliver particular amount of drug into the systemic circulation over a period of time. The transdermal drug delivery systems (TDDS) review articles provide information regarding the transdermal drug delivery systems and its evaluation process as a ready reference for the research scientist who is involved
... Show MoreWith the high usage of computers and networks in the current time, the amount of security threats is increased. The study of intrusion detection systems (IDS) has received much attention throughout the computer science field. The main objective of this study is to examine the existing literature on various approaches for Intrusion Detection. This paper presents an overview of different intrusion detection systems and a detailed analysis of multiple techniques for these systems, including their advantages and disadvantages. These techniques include artificial neural networks, bio-inspired computing, evolutionary techniques, machine learning, and pattern recognition.