Analyzing Thermal Degradation Effects on Devulcanized GTR-Based NR/SBR/NBR Rubber Compounds Reinforced with SiO Particles.

The large number of tires produced annually demands new recycling methods. A key challenge associated with recycling elastomers is their crosslinking structure that prevents fusion. It is possible to reverse crosslinking through a process called devulcanization.

Convergence insufficiency prevalence in attention deficit and hyperactivity disorder children depends on the diagnosis criteria.

Purpose: Attention deficit and hyperactivity disorder (ADHD) is a neurodevelopmental condition commonly seen in children and adolescents, characterised by an increase in distractibility or inattention. Several studies have noted a higher rate of visual problems in this group, especially convergence insufficiency (CI), but when using different diagnostic criteria. The aim of this study was to evaluate visual function in ADHD children and non-ADHD controls to compare the different signs for diagnosis of CI.

AML-DECODER: Advanced Machine Learning for HD-sEMG Signal Classification-Decoding Lateral Epicondylitis in Forearm Muscles.

Background: Innovative algorithms for wearable devices and garments are critical for diagnosing and monitoring disease (such as lateral epicondylitis (LE)) progression. LE affects individuals across various professions and causes daily problems.

Methods: We analyzed signals from the forearm muscles of 14 healthy controls and 14 LE patients using high-density surface electromyography.

BioMOF@cellulose Glycerogel Scaffold with Multifold Bioactivity: Perspective in Bone Tissue Repair.

The development of new biomaterials for musculoskeletal tissue repair is currently an important branch in biomedicine research. The approach presented here is centered around the development of a prototypic synthetic glycerogel scaffold for bone regeneration, which simultaneously features therapeutic activity. The main novelty of this work lies in the combination of an open meso and macroporous nanocrystalline cellulose (NCC)-based glycerogel with a fully biocompatible microporous bioMOF system (CaSyr-1) composed of calcium ions and syringic acid.

Antibacterial and cytocompatible silver coating for titanium Boston Keratoprosthesis.

The Boston Keratoprosthesis (BKPro) serves as a medical solution for restoring vision in complex cases of corneal blindness. Comprising a front plate made of polymethylmethacrylate (PMMA) and a back plate of titanium (Ti), this device utilizes the beneficial biomaterial properties of Ti. While BKPro demonstrates promising retention rates, infection emerges as a significant concern that impacts its long-term efficacy.

Unlocking high-value football fans: unsupervised machine learning for customer segmentation and lifetime value.

Introduction: In the modern competitive landscape of football, clubs are increasingly leveraging data-driven decision-making to strengthen their commercial positions, particularly against rival clubs. The strategic allocation of resources to attract and retain profitable fans who exhibit long-term loyalty is crucial for advancing a club's marketing efforts. While the Recency, Frequency, and Monetary (RFM) customer segmentation technique has seen widespread application in various industries for predicting customer behavior, its adoption within the football industry remains underexplored.

Retigabine increases the conformational stability of the visual photoreceptor rhodopsin.

Rhodopsin is the key photoreceptor protein that mediates vision in low-light conditions. Mutations in rhodopsin are the cause of retinal degenerative diseases such as retinitis pigmentosa. Some of these mutations cause a decreased stability of the receptor.

Use of Beacon v2 for Improving Genomics Based Research in a Clinical Setting.

GA4GH has proposed the Beacon architecture as an interface to retrieve genomic information which also protects the privacy of the individuals. In this paper, we propose to adapt the Beacon Reference Implementation to the use case of a study comparing the susceptibility to the carcinogenic effects of tobacco. This analysis compares the germline of heavy smokers who have either never developed lung cancer or, on the contrary, have developed it at a young age.

Machine learning allows robust classification of visceral fat in women with obesity using common laboratory metrics.

The excessive accumulation and malfunctioning of visceral adipose tissue (VAT) is a major determinant of increased risk of obesity-related comorbidities. Thus, risk stratification of people living with obesity according to their amount of VAT is of clinical interest. Currently, the most common VAT measurement methods include mathematical formulae based on anthropometric dimensions, often biased by human measurement errors, bio-impedance, and image techniques such as X-ray absorptiometry (DXA) analysis, which requires specialized equipment.

Empirical modeling and prediction of neuronal dynamics.

Mathematical modeling of neuronal dynamics has experienced a fast growth in the last decades thanks to the biophysical formalism introduced by Hodgkin and Huxley in the 1950s. Other types of models (for instance, integrate and fire models), although less realistic, have also contributed to understand neuronal dynamics. However, there is still a vast volume of data that have not been associated with a mathematical model, mainly because data are acquired more rapidly than they can be analyzed or because it is difficult to analyze (for instance, if the number of ionic channels involved is huge).

Methodological biases in observational hospital studies of COVID-19 treatment effectiveness: pitfalls and potential.

Introduction: This study aims to discuss and assess the impact of three prevalent methodological biases: competing risks, immortal-time bias, and confounding bias in real-world observational studies evaluating treatment effectiveness. We use a demonstrative observational data example of COVID-19 patients to assess the impact of these biases and propose potential solutions.

Methods: We describe competing risks, immortal-time bias, and time-fixed confounding bias by evaluating treatment effectiveness in hospitalized patients with COVID-19.

Applying a Digital Twin and wastewater analysis for robust validation of COVID-19 pandemic forecasts: insights from Catalonia.

Monitoring SARS-CoV-2 spread is challenging due to asymptomatic infections, numerous variants, and population behavior changes from non-pharmaceutical interventions. We developed a Digital Twin model to simulate SARS-CoV-2 evolution in Catalonia. Continuous validation ensures our model's accuracy.

Effect of Functionalization of Texturized Polypropylene Surface by Silanization and HBII-RGD Attachment on Response of Primary Abdominal and Vaginal Fibroblasts.

Soft tissue defects, such as incisional hernia or pelvic organ prolapse, are prevalent pathologies characterized by a tissue microenvironment rich in fragile and dysfunctional fibroblasts. Precision medicine could improve their surgical repair, currently based on polymeric materials. Nonetheless, biomaterial-triggered interventions need first a better understanding of the cell-material interfaces that truly consider the patients' biology.

The Discovery of inhibitors of the SARS-CoV-2 S protein through computational drug repurposing.

SARS-CoV-2 must bind its principal receptor, ACE2, on the target cell to initiate infection. This interaction is largely driven by the receptor binding domain (RBD) of the viral Spike (S) protein. Accordingly, antiviral compounds that can block RBD/ACE2 interactions can constitute promising antiviral agents.

Robust algorithm for the detection and classification of QRS complexes with different morphologies using the continuous spline wavelet transform with automatic scale detection.

This work presents an algorithm for the detection and classification of QRS complexes based on the continuous wavelet transform (CWT) with splines. This approach can evaluate the CWT at any integer scale and the analysis is not restricted to powers of two. The QRS detector comprises four stages: implementation of CWT with splines, detection of QRS complexes, searching for undetected QRS complexes, and correction of the R wave peak location in detected QRS complexes.

Assessment of the bound conformation of bombesin to the BB1 and BB2 receptors.

Bombesin is an endogenous peptide involved in a wide spectrum of physiological activities ranging from satiety, control of circadian rhythm and thermoregulation in the central nervous system, to stimulation of gastrointestinal hormone release, activation of macrophages and effects on development in peripheral tissues. Actions of the peptide are mediated through the two high affinity G-protein coupled receptors BB1R and BB2R. Under pathophysiological conditions, these receptors are overexpressed in many different types of tumors, such as prostate cancer, breast cancer, small and non-small cell lung cancer and pancreatic cancer.

Low-Power Long-Term Ambulatory Electrocardiography Monitor of Three Leads with Beat-to-Beat Heart Rate Measurement in Real Time.

A low-power long-term ambulatory ECG monitor was developed for the acquisition, storage and processing of three simultaneous leads DI, aVF and V2 with a beat-to-beat heart rate measurement in real time. It provides long-term continuous ECG recordings until 84 h. The monitor uses a QRS complex detection algorithm based on the continuous wavelet transform with splines, which automatically selects the scale for the analysis of ECG records with different sampling frequencies.

Mechanical Properties of Bio-Based Sandwich Composites Containing Recycled Polymer Textiles.

In this paper, sandwich composites were produced by compression moulding techniques, and they consisted of regenerated cellulose fabric (rayon) and bio-based polypropylene (PP) to form facings, while virgin and recycled polyamide (PA) textiles were used as core materials. To compare the mechanical performance between sandwich composites and typical composite designs, a control composite was produced to deliver the same weight and fiber mass fraction from rayon and PP. To evaluate the influence of recycled textile on the mechanical properties of the composites, a series of flexural, low velocity impact (LVI) and tensile tests were performed.

Understanding allochthonous marine litter in a Protected Area in the Amazon Coast.

Studies on international waste on the Amazon coast are lacking, leaving a substantial knowledge gap concerning the socioeconomic, cultural, and environmental repercussion of this issue. In this context, the objective of this study is to comprehensively characterize and trace the origins of allochthonous litter discovered on a beach situated within a Protected Area. Given this, the hypothesis of this study is that the international litters comes from vessels operating in the region.

Target trial emulation with multi-state model analysis to assess treatment effectiveness using clinical COVID-19 data.

Background: Real-world observational data are an important source of evidence on the treatment effectiveness for patients hospitalized with coronavirus disease 2019 (COVID-19). However, observational studies evaluating treatment effectiveness based on longitudinal data are often prone to methodological biases such as immortal time bias, confounding bias, and competing risks.

Methods: For exemplary target trial emulation, we used a cohort of patients hospitalized with COVID-19 (n = 501) in a single centre.

Aging Compensation in a Class-A High-Frequency Amplifier with DC Temperature Measurements.

One of the threats to nanometric CMOS analog circuit reliability is circuit performance degradation due to transistor aging. To extend circuit operating life, the bias of the main devices within the circuit must be adjusted while the aging degradation process affects them by using a monitor circuit that tracks the evolution of the circuit performance. In this paper, we propose the use of DC temperature measurements in the proximity of the circuit to perform the monitoring of circuit performance degradation and as an observable variable to adjust the bias of the main devices to restore the degraded performance to the original values.

Aquatic Ecosystem Risk Assessment Generated by Accidental Silver Nanoparticle Spills in Groundwater.

This paper aims to create a new model for assessing the ecosystem risk in rivers and wetlands that are linked to accidental spills of silver nanoparticles (AgNPs) in soil/groundwater. Due to the uncertainty of the modeling inputs, a combination of two well-known risk assessment methodologies (Monte Carlo and fuzzy logic) were used. To test the new model, two hypothetical, accidental AgNP soil spill case studies were evaluated; both of which were located at the end of the Llobregat River basin within the metropolitan area of Barcelona (NE Spain).