Pre-Operative Workup of Cochlear Implant

Hearing loss, an increasing problem across the globe, results in an important solution in the form of cochlear implants, highlighting the critical need for effective interventions. This review involves analyzing 46 relevant publications via databases such as PubMed and Google Scholar, providing current insights into pre-operative issues. Studies through databases such as PubMed and Google Scholar, ensuring contemporary insights into the pre-operative considerations. The pre-operative evaluation encompasses medical history, covering prenatal events and immediate post-natal health, along with physical examinations and complete audiometric assessments. High-Resolution Computed Tomography (HRCT) and Magnetic Resonance Imaging (MRI) emerge as crucial imaging techniques, guiding surgical planning and electrode placement. Brainstem Evoked Response Audiometry (BERA) supplements inconclusive MRI data, while vestibular screening aids in candidate selection. Cochlear duct length determination, often assessed through imaging techniques, contributes to optimal electrode array selection. Models in cochlear implant research, spanning computational, animal, tissue engineering, and physical models, further enhance our understanding and refinement of cochlear implant designs. In conclusion, this comprehensive pre-operative workup plays a significant role in assessing patient health, identifying causes of deafness, and contributing to the overall success of cochlear implantation, a transformative solution for profound hearing impairment

Effect of alloying elements on the compressive mechanical properties of biomedical titanium alloys: A systematic review

Due to problems such as the stress-shielding effect, strength-ductility trade-off dilemma, and use of rare-earth, expensive elements with high melting points in Ti alloys, the need for the design of new Ti alloys for biomedical applications has emerged. This article reports the effect of various alloying elements on the compressive mechanical performance of Ti alloys for biomedical applications for the first time as a systematic review following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines on this subject. The search strategy in this systematic review used Scopus, Web of Science, and PubMed databases and searched the articles using (Beta-type OR β) AND Titanium AND (Mechanical property OR Microstructure) AND Alloying element keywords. Original articles from 2016 to 2022 published in English have been selected for this study as per the inclusion criteria. The results have shown that Nb can be used as the primary alloying element with Ti as it is a strong β-stabilizer element which also reduces the elastic modulus of Ti alloys. The β-eutectic elements (Fe, Cr, and Mn) have also emerged as cost-effective alloying elements that could improve the mechanical performance of Ti alloys. Ti-Nb-Zr-Ta alloyed with Si has shown potential to withstand the strength-ductility trade-off dilemma. The combination of a Ti-Nb binary alloy has emerged as an attractive material for designing low elastic modulus Ti alloys. The mechanical performance of the Ti-Nb alloy can be further improved using the β-eutectic (Fe, Cr, and Mn) and neutral (Zr, Sn) elements to be alloyed with a Ti-Nb binary alloy. The strength-ductility trade-off issue can be overcome using Si as an alloying element in Ti-Nb-Zr-Ta alloys

Analysis of Machine Learning Based Imputation of Missing Data

Data analysis and classification can be affected by the availability of missing data in datasets. To deal with missing data, either deletion-based or imputation-based methods are used that results in the reduction of data records or wrong predicted value imputed by means/median respectively. A significant improvement can be done if missing values are imputed more accurately with less computation cost. In this work, a flow for analysis of machine learning-based algorithms for missing data imputation is proposed. The K-nearest neighbors (KNN) and Sequential KNN (SKNN) algorithms are used to impute missing values in datasets using machine learning. Missing values handled using statistical deletion approach (List-wise Deletion) and ML-based imputation methods (KNN and SKNN) is then tested and compared using different ML classifiers (Support Vector Machine and Decision Tree) to evaluate effectiveness of imputed data. The used algorithms are compared in terms of accuracy, and results yielded that the ML-based imputation method (SKNN) outperforms LD-based approach and KNN method in terms of effectiveness of handling missing data in almost every dataset with both classification algorithms (SVM and DT)

An Adaptive Learning Rate for RBFNN Using Time-Domain Feedback Analysis

Radial basis function neural networks are used in a variety of applications such as pattern recognition, nonlinear identification, control and time series prediction. In this paper, the learning algorithm of radial basis function neural networks is analyzed in a feedback structure. The robustness of the learning algorithm is discussed in the presence of uncertainties that might be due to noisy perturbations at the input or to modeling mismatch. An intelligent adaptation rule is developed for the learning rate of RBFNN which gives faster convergence via an estimate of error energy while giving guarantee to the l2 stability governed by the upper bounding via small gain theorem. Simulation results are presented to support our theoretical development

Factors influencing the use of postoperative bilevel positive airway pressure (BiPAP) in patients undergoing adult cardiac surgery: A retrospective cohort study

Background and aims: Respiratory complications are one of the biggest challenges following cardiac surgery, which can lead to hypoxia and acute respiratory failure (ARF). The aim of this study to identify the factors led to BiPAP application for postoperative respiratory complications and its effectiveness as the main outcome measures after cardiac surgery.Methods: It was a retrospective cohort study with consecutive sampling technique. A total of 335 postcardiac surgery patients medical record was reviewed who were underwent for surgery from November 1, 2018 to November 30, 2019. 265 patients were finalized for the recruitment, five patients were excluded before the final analysis. Data of 260 patients were analyzed for compiling of results.Results: The mean age was 59 years. 196 (75.4%) patients were males and females were 64 (24.6%). Mean weight was 72 kg and mean body mass index (BMI) 26.67 kg/m2 . BiPAP application was in 38 (14.6%) patients and significantly high in with high BMI, (p \u3c 0.05). There are significant associations of BiPAP application patients with COPD (p \u3c 0.05). Patients with positive fluid balance, cardiac dysfunction, and required inotropic support were significantly associated with BiPAP need (p \u3c 0.05), respectively.Conclusion: BiPAP is effective to treat ARF and other respiratory complications after adult cardiac surgeries. High BMI, atelectasis, and pneumonia are also the independent factors causing ARF. BiPAP can be a successful tool for preventing the adverse effects of postoperative pulmonary complications after cardiac surgery

Mentoring and its Effects on Turnover Intensions in Perspective of Pakistan’s Telecom Sector

In today’s era of towering competition the retention of workforce is highly desirable for long term success of any organization. The employees serve as backbone for any organization and are responsible for attaining the laid down objectives of the organization. The ongoing study investigates the effects of mentoring on turnover intensions of employees working in telecom sector of Pakistan. Researchers retrieved data with the help of questionnaires based on five point likert scale from almost 300 employees working in telecom organizations of Pakistan. Multiple regressions were used to analyze the collected data. Result shows that mentoring mostly is negatively associated with turnover intension because employee was not satisfied with mentoring and commitment in employees is only due to experienced learning which helps to develop additional skills in employee

Perovskite Solar Cells: Potentials, Challenges, and Opportunities

Heralded as a major scientific breakthrough of 2013, organic/inorganic lead halide perovskite solar cells have ushered in a new era of renewed efforts at increasing the efficiency and lowering the cost of solar energy. As a potential game changer in the mix of technologies for alternate energy, it has emerged from a modest beginning in 2012 to efficiencies being claimed at 20.1% in a span of just two years. This remarkable progress, encouraging at one end, also points to the possibility that the potential may still be far from being fully realized. With greater insight into the photophysics involved and optimization of materials and methods, this technology stands to match or even exceed the efficiencies for single crystal silicon solar cells. With thin film solution processability, applicability to flexible substrates, and being free of liquid electrolyte, this technology combines the benefits of Dye Sensitized Solar Cells (DSSCs), Organic Photovoltaics (OPVs), and thin film solar cells. In this review we present a brief historic perspective to this development, take a cognizance of the current state of the art, and highlight challenges and the opportunities

Sandwich Generation in Contemporary Indonesia: Determining Responsibility in Caring for Elderly under Islamic Law and Positive Law

The emergence of the term sandwich generation is believed to be a phenomenon that is common in Indonesian society. What's more, the number of baby boomers has become a concern both from a social and economic perspective for the generations below them. Therefore, many dilemmas arise regarding how the Indonesian people respond to sandwich generation, whether this position is a burden or a gift for the perpetrators of sandwich generation. This paper will later answer how the history of the emergence of the term sandwich generation and its development in Indonesia and the perception of sandwich generation on Islamic law perspective. This study uses a qualitative method by collecting library data sourced from related books and journals so as to produce a discussion where the term sandwich generation is a generation that directly supports the generation above and below (the other two generations). The current sandwich generation has actually existed for a long time, even in the era of Prophet Muhammad SAW. The concept of sandwich generation can be interpreted the same as the concept of birrul walidain or devoted to parents. Of course, the concept of birrul walidain is a practice that is highly recommended to be done for every Muslim

Patients\u27 satisfaction and opinions of their experiences during admission in a tertiary care hospital in Pakistan - a cross sectional study

Background: It is often felt that developing countries need to improve their quality of healthcare provision. This study hopes to generate data that can help managers and doctors to improve the standard of care they provide in line with the wishes of the patients.Methods: It was a cross sectional study carried out at a major tertiary care hospital of Karachi. Patients between the ages of 18 and 80 years admitted to the hospital for at least one day were included. Patients in the maternity, psychiatry and chemotherapy wards and those in the ICU/CCU were excluded. A pretested, peer reviewed translation of a validated patient satisfaction scale developed by the Picker Institute of Europe was administered.Results: A total of 173 patients (response rate: 78.6 %) filled the questionnaire. Patient satisfaction was at levels comparable to European surveys for most aspects of hospital care. However, nearly half the patients (48%) felt they had to wait too long to get a bed in the hospital after presenting to the ER. 68.6% of the patients said that they were never asked for views on the quality of care provided. 20% of the patients did not find anyone in the staff to talk to about their worries and fears while 27.6% felt that they were given emotional support to only some extent. Up to one third of the patients said they were not provided enough information regarding their operative procedures beforehand.CONCLUSION: Although several components of patient care equal the quality levels of the west, many sections require considerable improvement in order to improve health care provision. The healthcare team needs to get more involved with the patients, providing them greater support and keeping them informed and involved with their medical treatment. Efforts should be made to get regular feedback from the patients

Current Diagnostic Techniques for Pneumonia:A Scoping Review

Community-acquired pneumonia is one of the most lethal infectious diseases, especially for infants and the elderly. Given the variety of causative agents, the accurate early detection of pneumonia is an active research area. To the best of our knowledge, scoping reviews on diagnostic techniques for pneumonia are lacking. In this scoping review, three major electronic databases were searched and the resulting research was screened. We categorized these diagnostic techniques into four classes (i.e., lab-based methods, imaging-based techniques, acoustic-based techniques, and physiological-measurement-based techniques) and summarized their recent applications. Major research has been skewed towards imaging-based techniques, especially after COVID-19. Currently, chest X-rays and blood tests are the most common tools in the clinical setting to establish a diagnosis; however, there is a need to look for safe, non-invasive, and more rapid techniques for diagnosis. Recently, some non-invasive techniques based on wearable sensors achieved reasonable diagnostic accuracy that could open a new chapter for future applications. Consequently, further research and technology development are still needed for pneumonia diagnosis using non-invasive physiological parameters to attain a better point of care for pneumonia patients