This paper aims to study the effects of the long term solar activity on the critical frequencies of ionospheric F1 layer over Baghdad city, during the solar cycle 22, within (1988- 1995). It is found that the critical frequency of this layer is closely related to the sunspots number during the years of the solar cycle 22, at a middle latitude region of the world. The study discussed the effect of sunspot numbers and solar events on the electron densities of F1 layer, which is the most important ionospheric parameter.

The thermal performance of a flat-plate solar collector (FPSC) using novel heat transfer fluids of aqueous colloidal dispersions of covalently functionalized multi-walled carbon nanotubes with β-Alanine (Ala-MWCNTs) has been studied. Multi-walled carbon nanotubes (MWCNTs) with outside diameters of (< 8 nm) and (20–30 nm) having specific surface areas (SSAs) of (500 m2/g) and (110 m2/g), respectively, were utilized. For each Ala-MWCNTs, waterbased nanofluids were synthesized using weight concentrations of 0.025%, 0.05%, 0.075%, and 0.1%. A MATLAB code was built and a test rig was designed and developed. Heat flux intensities of 600, 800, and 1000 W/m2; mass flow rates of 0.6, 1.0, and 1.4 kg/min; and inlet fluid temperatures of 30, 40, an

Investigating the thermal and electrical gains and efficiencies influence the designed photovoltaic thermal hybrid collector (PVT) under different weather conditions. The designed system was manufactured by attaching a fabricated cooling system made of serpentine tubes to a single PV panel and connecting it to an automatic controlling system for measuring, monitoring, and simultaneously collecting the required data. A removable glass cover had been used to study the effects of glazed and unglazed PVT panel situations. The research was conducted in February (winter) and July (summer), and March for daily solar radiation effects on efficiencies. The results indicated that electrical and thermal gains increased by the incre

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

Numerous trace elements, notably metals, are essential for the normal functioning of several biological reactions, especially as enzyme cofactors. Several Trace elements refer to essential micronutrients required in minimal quantities for certain biological functions pertaining to human metabolism, albeit their minimal concentrations in the organism. Nonetheless, our understanding of this topic is considerably restricted, and emerging insights into their metabolic functions necessitate contributions and have implications across various domains, encompassing nutritional chemistry, with a focus on analytical chemistry, biological sciences, medicine, pharmacology, and agricultural sciences. 

Numerous trace elements, notably metals, are essential for the normal functioning of several biological reactions, especially as enzyme cofactors. Several Trace elements refer to essential micronutrients required in minimal quantities for certain biological functions pertaining to human metabolism, albeit their minimal concentrations in the organism. Nonetheless, our understanding of this topic is considerably restricted, and emerging insights into their metabolic functions necessitate contributions and have implications across various domains, encompassing nutritional chemistry, with a focus on analytical chemistry, biological sciences, medicine, pharmacology, and agricultural sciences. 

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