Roller Compacted Concrete is a type of concrete that is environmentally friendly and more economical than traditional concrete. Roller Compacted Concrete is typically used for heavy-duty and specialist constructions, such as hydraulic structures and pavements, because of its coarse surface. The main difference between RCC and conventional concrete mixtures is that RCC has a more significant proportion of fine aggregates that allow compaction and tight packing. In recent years, it has been estimated that several million tons of waste demolished material (WDM) produced each year are directed to landfills worldwide without being recycled for disposal. This review aimed to study the literature about creating a Roller-Comp

A direct, sensitive and efficient spectrophotometric method for the determination of nitrofurantoin
drug (NIT) in pure as well as in dosage form (capsules) was described. The suggested method was
based on reduction NIT drug using Zn/HCl and then coupling with 3-methyl-2-benzothiazolinone
hydrazone hydrochloride (MBTH) in the presence of ammonium ceric sulfate. Spectrophotometric
measurement was established by recording the absorbance of the green colored product at 610 nm.
Using the optimized reaction conditions, beer’s law was obeyed in the range of 0.5-30 μg/mL, with
good correlation coefficient of 0.9998 and limits of detection and quantitation of 0.163 and 0.544
μg/mL, respectively. The accuracy and

Brain Fingerprinting (BF) is one of the modern technologies that rely on artificial intelligence in the field of criminal evidence law. Brain information can be obtained accurately and reliably in criminal procedures without resorting to complex and multiple procedures or questions. It is not embarrassing for a person or even violates his human dignity, as well as gives immediate and accurate results. BF is considered one of the advanced techniques related to neuroscientific evidence that relies heavily on artificial intelligence, through which it is possible to recognize whether the suspect or criminal has information about the crime or not. This is done through Magnetic Resonance Imaging (EEG) of the brain and examining

The objectives of the study were to identify the incidence rate and characteristics of adverse drug events (ADEs) in nursing homes (NHs) using the ADE trigger tool and to evaluate the relationships between resident and facility work system factors and incidence of ADEs using the System Engineering Initiative for Patient Safety (SEIPS) model. The study used 2 observational quantitative methods, retrospective resident chart extraction, and surveys. The participating staff included Directors of nursing, registered nurses, certified nurse assistants (CNAs). Data were collected from fall 2016 to spring 2017 from 11 NHs in 9 cities in Iowa. Binary logistic regression with generalized estimated equations was used to measure the association

Over the past decades, several studies have examined the subcellular localization of the cauliflower mosaic virus (CaMV) P6 protein by tagging it with GFP (P6-GFP). These investigations have been essential in the development of models for inclusion body formation, nuclear transport, and microfilament-associated intracellular movement of P6 inclusion bodies for delivery of virions to plasmodesmata. Although it was shown early on that the translational transactivation function of P6-GFP was comparable to wild type P6, it has not been possible to incorporate a P6-GFP gene into an infectious clone of CaMV. Consequently, it has not been possible to formally prove that a P6-GFP fusion is comparable in function to the unmodified P6 protein. Here w

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Reactive oxygen species (ROS) are produced as a result of biochemical processes that are not in balance with the body's antioxidant defense mechanism. This metabolic dysfunction is referred to the oxidative stress (OS).  Metabolic dysfunction-associated diseases are affected by changes in the redox balance. It is now widely recognized that oxidative stress significantly affects diabetes mellitus (DM), particularly type 2 diabetes. The biochemical changes associated with  DM could  disturb the oxidative milieu, leading to several microvascular complications in diabetic patients. Thus, DM is a perfect disease to explore the harmful consequences of oxidative stress and how to treat it. Oxidative stress triggered by hyperglycemia is

Various industrial applications include the dyeing of textiles, paper, leather, and food products, as well as the cosmetics industry. Physic-chemical methods are required to breakdown dyes because they are known to be harmful and persistent in the environment. Many companies' treated effluents contain small amounts of dyes. When it comes to removing dye from wastewater, adsorption has verified to be aneconomical alternative to more traditional treatment procedures. It's important to degrade color impurities in industrial effluents since they constitute a serious health and environmental concern. One way that's been tried is using clay minerals as an adsorbent. Using adsorption for removing

Collaborative learning in class‐based teaching presents a challenge for a tutor to ensure every group and individual student has the best learning experience. We present Group Tagging, a web application that supports reflection on collaborative, group‐based classroom activities. Group Tagging provides students with an opportunity to record important moments within the class‐based group work and enables reflection on and promotion of professional skills such as communication, collaboration and critical thinking. After class, students use the tagged clips to create short videos showcasing their group work activities, which can later be reviewed by the teacher. We report on a deployment of Group Tagging in an undergraduate Computing Scie