Particulate matter (PM) emitted from diesel engine exhaust have been measured in terms of mass, using
99.98 % pure ethanol blended directly, without additives, with conventional diesel fuel (gas – oil),to
get 10 % , 15 %, 20 % ethanol emulsions . The resulting PM collected has been compared with those
from straight diesel. The engine used is a stationary single cylinder, variable compression ratio Ricardo
E6/US. This engine is fully instrumented and could run as a compression or spark ignition.
Observations showed that particulate matter (PM) emissions decrease with increasing oxygenate
content in the fuel, with some increase of fuel consumption, which is due to the lower heating value of
ethanol. The reduction in

A time series analysis can help to observe the behavior of the system and specify the system faults. In addition, it also helps to explain the various energy flows in the system and further aid in reducing the thermodynamic losses. The intelligent supervisory LabVIEW software can monitor the incoming data from the system by using Arduino microcontroller and calculates the important parameters. Energy, exergy, and anergy analysis present in this paper to investigate the system performance as well as its components. To accomplish this, a 4-ton vertical split air conditioner based on vapor compression refrigeration cycle charged with refrigerant R-22 was modified for experimental analysis. The results showed that during 540

Symmetric cryptography forms the backbone of secure data communication and storage by relying on the strength and randomness of cryptographic keys. This increases complexity, enhances cryptographic systems' overall robustness, and is immune to various attacks. The present work proposes a hybrid model based on the Latin square matrix (LSM) and subtractive random number generator (SRNG) algorithms for producing random keys. The hybrid model enhances the security of the cipher key against different attacks and increases the degree of diffusion. Different key lengths can also be generated based on the algorithm without compromising security. It comprises two phases. The first phase generates a seed value that depends on producing a rand

Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.

Dental clinicians and professionals need an affordable, nontoxic, and effective disinfectant against infectious microorganisms when dealing with the contaminated dental impressions. This study evaluated the efficiency of hypochlorous acid (HOCl) as an antimicrobial disinfectant by spraying technique for the alginate impression materials, compared with sodium hypochlorite, and its effect on dimensional stability and reproduction of details. HOCl with a concentration of 200 ppm for 5 and 10 min was compared with the control group (no treatment) as a negative control and with sodium hypochlorite (% 0.5) as a positive control. Candida albicans, Staphylococcus aureus, and Pseudomonas aeruginosa were selected to assess the antimicrobi

Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

Celiac disease (CD) is an immune-mediated disorder caused by gluten in genetically susceptible individuals characterized by chronic inflammation that essentially affects the small intestine. Objective: this study was designed to measure the potential role of some serological biomarkers including vitamin B12 and homocysteine (HCY) in the progression of CD as well as their relations to global DNA methylation (5mC). Materials and methods. Forty CD patients were enrolled in the study with an average age of (36.60 ± 2.03) years (range between 15 and 60). The diagnosis of the disease was confirmed by serological examinations and intestinal endoscopy in Gastroenterology and Liver Teaching Hospital in the Medical City Hospital in Baghdad