Enhanced heart sound classification using Mel frequency cepstral coefficients and comparative analysis of single vs. ensemble classifier strategies.

This paper seeks to enhance the performance of Mel Frequency Cepstral Coefficients (MFCCs) for detecting abnormal heart sounds. Heart sounds are first pre-processed to remove noise and then segmented into S1, systole, S2, and diastole intervals, with thirteen MFCCs estimated from each segment, yielding 52 MFCCs per beat. Finally, MFCCs are used for heart sound classification.

ONDL: An optimized Neutrosophic Deep Learning model for classifying waste for sustainability.

Sustainability has become a key factor on our planet. If this concept is applied correctly, our planet will be greener and more eco-friendly. Nowadays, waste classification and management practices have become more evident than ever.

Replication of a local record keeping method for collecting road crash data in low resource settings: lessons from Bangladesh and Nepal.

Background: Police road crash and injury data in low-income and middle-income countries are known to under-report crashes, fatalities and injuries, especially for vulnerable road users. Local record keepers, who are members of the public, can be engaged to provide an additional source of crash and injury data.

Methods: This paper compares the application of a local record keeper method to capture road crash and injury data in Bangladesh and Nepal, assesses the quality of the data collected and evaluates the replicability and value of the methodology using a framework developed to evaluate the impact of being a local record keeper.

A model for skin cancer using combination of ensemble learning and deep learning.

Skin cancer has a significant impact on the lives of many individuals annually and is recognized as the most prevalent type of cancer. In the United States, an estimated annual incidence of approximately 3.5 million people receiving a diagnosis of skin cancer underscores its widespread prevalence.

Enhancing healthcare IoT systems for diabetic patient monitoring: Integration of Harris Hawks and grasshopper optimization algorithms.

The integration of the Internet of Things (IoT) in healthcare, especially for people with diabetes, allows for constant health monitoring. This means that doctors can watch over patients' health more closely, making sure they catch any issues early on. With this technology, healthcare workers can be more accurate and effective when keeping an eye on how patients are doing.

A secure routing approach based on league championship algorithm for wireless body sensor networks in healthcare.

Patients must always communicate with their doctor for checking their health status. In recent years, wireless body sensor networks (WBSNs) has an important contribution in Healthcare. In these applications, energy-efficient and secure routing is really critical because health data of individuals must be forwarded to the destination securely to avoid unauthorized access by malicious nodes.

Formal consensus study on surgery to replace the aortic valve in adults aged 18-60 years.

Objective: There is uncertainty about surgical procedures for adult patients aged 18-60 years undergoing aortic valve replacement (AVR). Options include conventional AVR (mechanical, mAVR; tissue, tAVR), the pulmonary autograft (Ross) and aortic valve neocuspidisation (Ozaki). Transcatheter treatment may be an option for selected patients.

Identifying resistance in wild and ornamental cherry towards bacterial canker caused by .

Bacterial canker is a major disease of stone fruits and is a critical limiting factor to sweet cherry () production worldwide. One important strategy for disease control is the development of resistant varieties. Partial varietal resistance in sweet cherry is discernible using shoot or whole tree inoculations; however, these quantitative differences in resistance are not evident in detached leaf assays.

Chloride Ion Inhibition, Stirring, and Temperature Effects in an Ethylacetoacetate Briggs-Rauscher Oscillator in Phosphoric and Hydrochloric Acids in a Batch Reactor.

Briggs-Rauscher oscillating reaction has been investigated in hydrochloric acid media and in the presence of added chloride ions in phosphoric acid media in a batch reactor using ethylacetoacetate as the organic substrate. The changes in key oscillation parameters, namely, induction period, oscillation period, amplitude, and so forth, have been explained in terms of the steps of the skeleton mechanism proposed by Furrow and Noyes and by de Kepper and Epstein. In spite of several shortcomings as outlined in section 2 in the text, the same mechanistic steps are good enough to explain qualitatively most of the changes in oscillation parameters under different stirring rates and temperatures in phosphoric acid and hydrochloric acid media, particularly stirring effects explained well by the theory of imperfect mixing.

Local Concentration Deviations in a Glycolytic Model of Nonequilibrium Thermodynamics: Emergence of Bistability from Thermodynamic Theories due to Violation of the Lyapunov Stability Theory.

The thermodynamics of nonequilibrium states in the reversible Sel'kov model, a mathematical model of glycolytic oscillations, is reported in terms of the Lyapunov properties of the second differential of its local equilibrium entropy ( S) and that of its entropy production (e.p.) function (σ) per unit volume.

Pathways to "Involved Professionalism": Making Processes of Professional Acculturation Intentional and Transparent.

Context - An increase in managerialism and a decrease in trust of the professions have challenged traditional concepts of professionalism. The market model of professionalism espoused by some critics also poses problems for professions, professionals and recipients of professional services. Professional development is now an important component of medical curricula.