Developing a Model Based on the Radial Basis Function to Predict the Compressive Strength of Concrete Containing Fly Ash

A supplemental pozzolanic material such as fly ash may result in a reduction in the concrete’s adverse environmental effect by reducing the discharge of carbon dioxide throughout the cement production procedure. This pozzolanic material also enhances the mechanical characteristics as well as the durability of concrete material. Considering the boundless passion for utilizing fly ash and conducting extensive research studies, the extent to which this supplement can be added to concrete has a limitation equal to almost one-third of cement material’s weight. In the current study, a model based on the Radial Basis Function (RBF) is developed to estimate the compressive strength of concrete containing various amounts of fly ash at any arbitrary age. Having parameters used as inputs in ANN modeling such as concrete additives and characteristics of fly ash, the output was compressive strength. It was concluded that the estimated results agree well with the experimental measurements with an MSE of 0.0012 for the compressive strength. Simple and practical equations are proposed to present a simple means to determine the compressive strength of fly ash-based concrete

Prevalence of anxiety and depressive symptoms in ulcerative colitis patients in Jordan and its relationship to patient-reported disease activity

Inflammatory bowel disease is associated with higher rates of anxiety and depression compared to the general population. We aimed to determine the prevalence of anxiety and depressive symptoms among patients with ulcerative colitis and correlation to disease activity. In this cross-sectional study, we collected data from 70 consecutive ulcerative colitis patients over one year at our inflammatory bowel disease outpatient clinic through an interview and a questionnaire containing patient demographics and disease characteristics. Anxiety and depressive symptoms were characterized using the Generalized Anxiety Disorder-7 questionnaire and Patient Health Questionnaire-9, respectively, with ulcerative colitis disease severity assessed by the Partial Mayo scoring system. The majority of our patients were females (68.6%) and the mean age was 39.3 years. Rates of anxiety and depressive symptoms among ulcerative colitis patients were 65.7% and 58.6%, respectively. Depressive symptoms were significantly associated with patient-reported disease activity (r = 0.361; p = 0.010). Significant percentages of ulcerative colitis patients were appreciated to have anxiety and depressive symptoms, and there was a correlation between patient-reported disease activity and depressive symptoms. At this high rate of prevalence, it is justified to screen patients for the presence of psychiatric comorbidities

Increasing the Accuracy and Optimizing the Structure of the Scale Thickness Detection System by Extracting the Optimal Characteristics Using Wavelet Transform

Loss of energy, decrement of efficiency, and decrement of the effective diameter of the oil pipe are among the consequences of scale inside oil condensate transfer pipes. To prevent these incidents and their consequences and take timely action, it is important to detect the amount of scale. One of the accurate diagnosis methods is the use of non-invasive systems based on gamma-ray attenuation. The detection method proposed in this research consists of a detector that receives the radiation sent by the gamma source with dual energy (radioisotopes 241 Am and 133 Ba) after passing through the test pipe with inner scale (in different thicknesses). This structure was simulated by Monte Carlo N Particle code. The simulation performed in the test pipe included a three-phase flow consisting of water, gas, and oil in a stratified flow regime in different volume percentages. The signals received by the detector were processed by wavelet transform, which provided sufficient inputs to design the radial basis function (RBF) neural network. The scale thickness value deposited in the pipe can be predicted with an MSE of 0.02. The use of a detector optimizes the structure, and its high accuracy guarantees the usefulness of its use in practical situations

Application of Artificial Intelligence for Determining the Volume Percentages of a Stratified Regime’s Three-Phase Flow, Independent of the Oil Pipeline’s Scale Thickness

As time passes, scale builds up inside the pipelines that deliver the oil or gas product from the source to processing plants or storage tanks, reducing the inside diameter and ultimately wasting energy and reducing efficiency. A non-invasive system based on gamma-ray attenuation is one of the most accurate diagnostic methods to detect volumetric percentages in different conditions. A system including two NaI detectors and dual-energy gamma sources ( 241 Am and 133 Ba radioisotopes) is the recommended requirement for modeling a volume-percentage detection system using Monte Carlo N particle (MCNP) simulations. Oil, water, and gas form a three-phase flow in a stratified-flow regime in different volume percentages, which flows inside a scaled pipe with different thicknesses. Gamma rays are emitted from one side, and photons are absorbed from the other side of the pipe by two scintillator detectors, and finally, three features with the names of the count under Photopeaks 241 Am and 133 Ba of the first detector and the total count of the second detector were obtained. By designing two MLP neural networks with said inputs, the volumetric percentages can be predicted with an RMSE of less than 1.48 independent of scale thickness. This low error value guarantees the effectiveness of the intended method and the usefulness of using this approach in the petroleum and petrochemical industries

Effect of low-pressure pneumoperitoneum on pain and inflammation in laparoscopic cholecystectomy: a randomized controlled clinical trial

Abstract Objective We aim to assess the effect of low-pressure pneumoperitoneum on post operative pain and ten of the known inflammatory markers. Background The standard of care pneumoperitoneum set pressure in laparoscopic cholecystectomy is set to 12–14 mmHg, but many societies advocate to operate at the lowest pressure allowing adequate exposure of the operative field. Many trials have described the benefits of operating at a low-pressure pneumoperitoneum in terms of lower post operative pain, and better hemodynamic stability. But only few describe the effects on inflammatory markers and cytokines. Methods A prospective, double-blinded, randomised, controlled clinical trial, including patients who underwent elective laparoscopic cholecystectomy. Patients randomised into low-pressure (8–10 mmHg) vs. standard-pressure (12–14 mmHg) with an allocation ratio of 1:1. Perioperative variables were collected and analysed. Results one hundred patients were allocated, 50 patients in each study arm. Low-pressure patients reported lower median pain score 6-hour post operatively (5 vs. 6, p-value = 0.021) in comparison with standard-pressure group. Eight out of 10 inflammatory markers demonstrated better results in low-pressure group in comparison with standard-pressure, but the effect was not statistically significant. Total operative time and surgery difficulty was not significantly different between the two groups even in the hands of inexperienced surgeons. Conclusion low-pressure laparoscopic cholecystectomy is associated with less post operative pain and lower rise of inflammatory markers. It is feasible with comparable complications to the standard of care. Registered on ClinicalTrials.gov (NCT05530564/ September 7th, 2022)

Enhanced functionality of fermented whey protein using water kefir

ABSTRACTThis research is part of an effort to enhance fermented whey proteins’ quality and nutritional value. In this research, we investigated the feasibility of using a natural fermentation approach on whey proteins. We determined the protein digestibility, non-nutritive compounds (including phenolic compounds and saponins), and microbiological quality of water kefir-fermented whey proteins. Due to the water kefir-induced fermentation of whey proteins, the protein digestibility improved from 88.48 to 94.33%. The protein quality of fermented whey proteins has been modified after the water kefir fermentation, as observed with the changes in the secondary protein structure components, especially α-helices (decreased from 10.58 to 8.52%) and random coil (increased from 12.25 to 17.33%). In addition, their water solubility, surface hydrophobicity, and surface charge changed significantly (P < .05) during the fermentation time; 88.44 to 94.11%, 387.23 to 272.7 a.u. and −30.06 to −34.93 mV, respectively. Furthermore, water kefir is an excellent source of fermenting microorganisms, including lactic and acetic acid bacteria and yeast. Thus, the water kefir fermentation approach could be an effective, practical, non-thermal approach for altering whey proteins

Experimental Analysis to Detect Corona COVID-19 Virus Symptoms in Male Patients through Breath Pattern Using Machine Learning Algorithms

In the fourth quarter of the year 2019, the planet became overwhelmed by the pandemic caused by the coronavirus disease (COVID-19). This virus imperiled human life and have affected a considerable percentage of the world population much before its early stage detection mechanisms were discovered and made available at the grassroots level. As there is no specific drug available to treat this infection, the vaccine was intended to serve as the ultimate weapon in the war against this species of coronavirus, but like other viruses, being an RNA virus, this virus also mutates continuously while it passes from one human to the other, making the development of highly potent vaccines even more challenging. This work is being sketched at the juncture when a huge percentage of the human population is already affected by this virus globally. In this work, we are proposing an idea to develop an app to detect coronavirus (COVID-19) symptoms at an early stage by self-diagnosis at home or at the clinical level. An experimental study has been performed on a dummy dataset with 11000 entries of various breadth patterns based on the spirometry analysis, lung volume analysis, and lung capacity analysis of normal male subjects and detailed breath patterns of infected male patients. A logistic regression model is trained after using SMOTE oversampling to balance the data and the predictive accuracy levels of 80%, 78%, and 90%. The results accomplished through this study and experiments may not only aid the clinicians in their medical practice but may also bestow a blue chip to the masterminds engaged in the biomedical research for inventing more evolved, sophisticated, user-friendly, miniaturized, portable, and economical medical app/devices in the future

Monomer Elution from Three Resin Composites at Two Different Time Interval Using High Performance Liquid Chromatography—An In-Vitro Study

Esthetics, improved colour stability and ease of contour have made photo-activated resin based restorative materials being widely used in routine dental clinical practice. Perhaps improper and inadequate polymerization of resin based composite material might lead to elution of monomer. Thus, the aim of the current study was to quantify the monomer elution from three resin composites. The intended analysis was made using high performance liquid chromatography (HPLC) at two different time periods. Three different materials that were investigated in the current study included Swiss Tech resin composite (Group A), Ceram X (Group B) and Beautifil Injectable composite (Group C). Ten cylindrical samples were fabricated in each study group. In 75% wt of ethanol, the samples were ingressed immediately and stored at room temperature. A 0.5 mL of the samples was assessed at pre-defined time intervals at 24 h and 7th day. Later, assessment of the samples was performed with HPLC and the data was analyzed using statistical test. Bisphenol A-glycidyl methacrylate (Bis-GMA), Triethylene glycol dimethacrylate (TEGDMA), 2-hydroxyethyl methacrylate (HEMA) and Urethane dimethacrylate (UDMA) were quantified in the samples. When analyzing the release monomer, it was found that at the end of 24 h Bis-GMA was eluted more in the injectable resin composite whereas, TEGDMA was eluted from Swiss Tech and Ceram X resin composites. At the end of the 7th day it was evident that Bis-GMA was eluted maximum in all the three resin composites. Thus, monomer release was found to be evident among all three resin composites and it is of utmost important to be assessed in routine clinical practice

Nano Drug Delivery Platforms for Dental Application: Infection Control and TMJ Management—A Review

The oral cavity is an intricate environment subjected to various chemical, physical, and thermal injuries. The effectiveness of the local and systemically administered drugs is limited mainly due to their toxicities and poor oral bioavailability that leads to the limited effectiveness of the drugs in the target tissues. To address these issues, nanoparticle drug delivery systems based on metals, liposomes, polymeric particles, and core shells have been developed in recent years. Nano drug delivery systems have applications in the treatment of patients suffering from temporomandibular joint disorders such as preventing degeneration of cartilage in patients suffering from rheumatoid arthritis and osteoarthritis and alleviating the pain along with it. The antibacterial dental applications of nano-drug delivery systems such as silver and copper-based nanoparticles include these agents used to arrest dental caries, multiple steps in root canal treatment, and patients suffering from periodontitis. Nanoparticles have been used in adjunct with antifungals to treat oral fungal infections such as candida albicans in denture wearers. Acyclovir being the most commonly used antiviral has been used in combination with nanoparticles against an array of viral infections such as the herpes simplex virus. Nanoparticles based combination agents offer more favorable drug release in a controlled manner along with efficient delivery at the site of action. This review presents an updated overview of the recently developed nanoparticles delivery systems for the management of temporomandibular joint disorders along with the treatment of different oral infections