Highly scalable bio-inspired soft elastomeric capacitor for structural health monitoring applications

Over the past few decades, Structural Health Monitoring (SHM) has gained wide popularity as it became essential to integrate monitoring systems into complex structural systems to ensure structural integrity and minimize hazards that may arise from any structural failure or collapse. Current monitoring technologies are capable of monitoring small areas with a priori information about the location of an existing defect, therefore they lack the ability to efficiently monitor large-scale systems such as bridges and wind turbine blades. The objective is to create a system capable of performing real-time online SHM with continuous feedback. This research aims at developing a complete system for structural health monitoring of wind turbine blades, including the sensing element, the data acquisition system, and the damage detection algorithm. The proposal is a network of soft sensors covering large surfaces capable of monitoring global as well as local behavior. The advantages of such a solution include cost efficiency, customizability in size and shape to accommodate the application, simple fabrication and installment and direct feature extraction with simple signal processing and machine learning techniques. The studies conducted to complete this dissertation intended to develop the sensing element (material and fabrication), characterize it and demonstrate applications to real structures. The proposed sensing element is a novel soft elastomeric capacitor (SEC) sensor for monitoring of large surfaces, applicable to composite materials. This soft capacitor is fabricated using a highly sensitive elastomer sandwiched between electrodes. It transduces strain into changes in capacitance. The elastomer is made of a Styrene Ethylene Butylene Styrene (SEBS) polymer doped with high permittivity Titanium dioxide (TiO2) as a filler material to increase the overall composite permittivity and improve the durability. The electrodes are made of a similar polymer doped with carbon black particles. The first study was conducted on optimizing the fabrication process for the sensor. We investigated the influence of processing methods that dictate the performance enhancement in a nanocomposite soft capacitor. The efficiency of ultrasonic probe and high-shear melt mixing methods in dispersing TiO2 nanoparticles in SEBS polymer matrix was studied. The compression-molding method shows highly promising for engineering applications by enhancing fabrication speed, safety, and improving control over the film thickness. The second part investigated the influence of interfacial treatment on the matrix-filler interaction using a melt-mixing process to fabricate robust and highly stretchable elastomers. Silicone oil and silane coupling agent were studied as possible solutions to enhance the compatibility between the inorganic fillers and polymer matrix. Results showed that specimens filled with silicone oil coated particles have promising overall properties. The third part, consisted of several experiments to characterize the functionality and applicability of the SEC to implement SHM to real life structures. The sensor behavior under static and dynamic loads was evaluated. Static test results showed the capability of the sensor to measure strains above 25µε with an almost linear behavior up to 20% strain levels and a gauge factor of 2. Dynamic results showed capability to accurately detect frequency contents and mode shapes. All the characterization tests were verified with one or more method, including commercial strain gauges, accelerometers, and finite element models. Using SECs in a network configuration have a great potential to implement an efficient inexpensive real time SHM on large-scale structures such as wind turbine blades. SEC data can be used to perform damage detection, localization and prognosis based on statistical as well as vibration analysis

The Association between SARS-CoV-2 Infection and Diabetic Ketoacidosis in Patients with New-Onset Diabetes: A Retrospective Study from a Diabetic Center in Saudi Arabia

Background: Various reports described new-onset diabetes during or after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in patients with no previous history of diabetes or glucocorticoid use. Further, SARS-CoV-2 could increase the risk of diabetes, including diabetic ketoacidosis (DKA). However, data on the relationship between new-onset diabetes and COVID-19 are still limited in our region. Thus, we aimed in this study to evaluate the association between new-onset diabetes and DKA in patients with COVID-19. Methods: A retrospective, cross-sectional study was conducted at a diabetic center in Jazan province, Saudi Arabia, between 2020 and 2021. Demographic data, COVID-19 status, and DKA incidence were collected and verified manually from diabetic patients’ medical records. Data were analyzed using a t-test and chi-square test. Results: We included 54 diabetic patients diagnosed during the COVID-19 pandemic, with a median age of 17 years. The majority of patients were females (57.4%). About 38.8% were diagnosed with COVID-19, and 16.6% reported having DKA. About 33.3% of the patients who experienced DKA reported being COVID-19-positive. However, only 6% of patients who denied contracting SARS-CoV-2 developed DKA (p-value = 0.020). Conclusions: Patients with newly diagnosed diabetes due to COVID-19 seem at a higher risk of developing DKA. Further epidemiological and molecular studies are required for a better understanding of the correlation between DKA in patients with diabetes and COVID-19

Knowledge, Attitude and Practices regarding Contraceptive Pill and Its Side Effects among Women in Jazan Region, Saudi Arabia

Contraception is one of the common methods of family planning. The oral contraceptive pill (OCP) is among the most effective methods of contraception. This study aimed to assess the knowledge, attitude, and practice of oral contraception use and its side effects among women in the Jazan region, Saudi Arabia. A cross-sectional study was carried out among adult women 18 years and older in the Jazan region. A pre-tested questionnaire was used to assess their demographic characteristics, knowledge, attitudes, previous experience, and pattern of OCP usage. Descriptive analysis and a logistic regression model were used to analyse data. About 570 questionnaires were distributed and achieved a 98.3% response rate. The majority of women participants were between 18 and 25 years old, and 51.4% of the respondents reported that they had previously used or were using OCP. We found that women had good knowledge and a positive attitude towards OCP, with more than half of the users preferring them over other contraceptive methods. This study indicates that attitude, knowledge, and prior experience of OCP have no significant effect on the usage pattern of OCP among women with relatively high socioeconomic status in the Jazan region, Saudi Arabia

Validation of the 6-Month GRACE Score in Predicting 1-Year Mortality of Patients With Acute Coronary Syndrome Admitted to the Arabian Gulf Hospitals

Acute coronary syndromes (ACS) are the most common cardiovascular diseases and are associated with a significant risk of mortality and morbidity. The Global Registry of Acute Coronary Events (GRACE) risk score postdischarge is a widely used ACS prediction model for risk of mortality (low, intermediate, and high); however, it has not yet been validated in patients from the Arabian Gulf. This prospective multicenter study (second Gulf Registry of Acute Coronary Events) provides detailed information of the GRACE risk score postdischarge in patients from the Arabian Gulf. Its prognostic utility was validated at 1-year follow-up in over 5000 patients with ACS from 65 hospitals in 6 Arabian Gulf countries (Bahrain, Saudi Arabia, Qatar, Oman, United Arab Emirates, and Yemen). Overall, the goodness of fit (Hosmer and Lemeshow statistic P value = .826), calibration, and discrimination (area under the receiver operating characteristic curve = 0.695; 95% confidence interval: 0.668-0.722) were good. The GRACE risk score postdischarge can be used to stratify 1 year mortality risk in the Arabian Gulf population; it does not require further calibration and has a good discriminatory ability.Gulf RACE-2 is a Gulf Heart Association (GHA) project and was financially supported by the GHA, Sanofi-Aventis, and the Deanship of Scientific Research at King Saud University, Riyadh, Saudi Arabia (Research group number: RG-1436-013). L.F.K. is funded by an Endeavour Postgraduate Scholarship (#3781_2014), an Australian National University Higher Degree Scholarship, and a Fondo para la Innovacio´n, Ciencia y Tecnologı´a Scholarship (#095-FINCyTBDE-2014)