Development of a flow-cell bioreactor for immobilized sulfidogenic sludge characterization using electrochemical HS microsensors.

The sulfate-reduction process plays a crucial role in the biological valorization of SO gases. However, a complete understanding of the sulfidogenic process in bioreactors is limited by the lack of technologies for characterizing the sulfate-reducing activity of immobilized biomass. In this work, we propose a flow-cell bioreactor (FCB) for characterizing sulfate-reducing biomass using HS microsensors to monitor HS production in real-time within a biofilm.

Ru-CeZrO as an Anode Catalyst for the Internal Reforming of Dimethyl Ether in Solid Oxide Fuel Cells.

The development of direct dimethyl ether (DME) solid oxide fuel cells (SOFCs) has several drawbacks, due to the low catalytic activity and carbon deposition of conventional Ni-zirconia-based anodes. In the present study, the insertion of 2.0 wt.

What-if nature-based storm buffers on mitigating coastal erosion.

Creating ecosystem buffers in intertidal zones, such as seagrass meadows, has gained increasing attention as a nature-based solution for mitigating storm-driven coastal erosion. This study presents what-if scenarios using an integrated model framework to determine the effectiveness and strategies for planting seagrass to reduce coastal erosion. The framework comprises two levels of simulation packages.

Permutation entropy analysis of EEG signals for distinguishing eyes-open and eyes-closed brain states: Comparison of different approaches.

Developing reliable methodologies to decode brain state information from electroencephalogram (EEG) signals is an open challenge, crucial to implementing EEG-based brain-computer interfaces (BCIs). For example, signal processing methods that identify brain states could allow motor-impaired patients to communicate via non-invasive, EEG-based BCIs. In this work, we focus on the problem of distinguishing between the states of eyes closed (EC) and eyes open (EO), employing quantities based on permutation entropy (PE).

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).

Light-driven dynamical tuning of the thermal conductivity in ferroelectrics.

Dynamical tuning of the thermal conductivity in crystals, , is critical for thermal management applications, as well as for energy harvesting and the development of novel devices able to perform logic operations with phonons. Such a desired control can be achieved in functional materials that experience large structural and phonon variations as a result of field-induced phase transformations. However, this approach is only practical within reduced temperature intervals containing zero-bias phase transition points, since otherwise the necessary driving fields become excessively large and the materials' performances are detrimentally affected.

Combining graph neural networks and computer vision methods for cell nuclei classification in lung tissue.

The detection of tumoural cells from whole slide images is an essential task in medical diagnosis and research. In this article, we propose and analyse a novel approach that combines computer vision-based models with graph neural networks to improve the accuracy of automated tumoural cell detection in lung tissue. Our proposal leverages the inherent structure and relationships between cells in the tissue.

Citizens' willingness to support farmers' adoption of low crude protein diet in pig production.

Livestock farming has a detrimental effect on the environment since it generates a lot of gas emissions. In pig farming, the use of feed is among the substantial sources of animal farm emissions among the European Union. Nevertheless, the use of Low Dietary Crude Protein (LCP) may reduce the environmental impacts of pig farming and provide diverse ecosystem services (ESs).

Concomitant Light-Reversible Magnetic Response in Multiferroic Oxide Heterostructures for Multiphysics Applications.

The concept of multiphysics, where materials respond to diverse external stimuli, such as magnetic fields, electric fields, light irradiation, stress, heat, and chemical reactions, plays a fundamental role in the development of innovative devices. Nanomanufacturing, especially in low-dimensional systems, enhances the synergistic interactions taking place on the nanoscale. Light-matter interaction, rather than electric fields, holds great promise for achieving low-power, wireless control over magnetism, solving two major technological problems: the feasibility of electrical contacts at smaller scales and the undesired heating of the devices.

Measurement of the ^{140}Ce(n,γ) Cross Section at n_TOF and Its Astrophysical Implications for the Chemical Evolution of the Universe.

^{140}Ce(n,γ) is a key reaction for slow neutron-capture (s-process) nucleosynthesis due to being a bottleneck in the reaction flow. For this reason, it was measured with high accuracy (uncertainty ≈5%) at the n_TOF facility, with an unprecedented combination of a high purity sample and low neutron-sensitivity detectors. The measured Maxwellian averaged cross section is up to 40% higher than previously accepted values.

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.

Characterizing the spike timing of a chaotic laser by using ordinal analysis and machine learning.

Semiconductor lasers with optical feedback are well-known nonlinear dynamical systems. Under appropriate feedback conditions, these lasers emit optical pulses that resemble neural spikes. Influenced by feedback delay and various noise sources, including quantum spontaneous emission noise, the dynamics are highly stochastic.

The mediating role of neuroimaging-derived biological brain age in the association between risk factors for dementia and cognitive decline in middle-aged and older individuals without cognitive impairment: a cohort study.

Background: Neuroimaging-based brain-age delta has been shown to be a mediator linking cardiovascular risk factors to cognitive function. We aimed to assess the mediating role of brain-age delta in the association between modifiable risk factors of dementia and longitudinal cognitive decline in middle-aged and older individuals who are asymptomatic, stratified by Alzheimer's disease pathology. We also explored whether the mediation effect is specific to cognitive domain.

Lipidome characterisation and sex-specific differences in type 1 and type 2 diabetes mellitus.

Background: In this study, we evaluated the lipidome alterations caused by type 1 diabetes (T1D) and type 2 diabetes (T2D), by determining lipids significantly associated with diabetes overall and in both sexes, and lipids associated with the glycaemic state.

Methods: An untargeted lipidomic analysis was performed to measure the lipid profiles of 360 subjects (91 T1D, 91 T2D, 74 with prediabetes and 104 controls (CT)) without cardiovascular and/or chronic kidney disease. Ultra-high performance liquid chromatography-electrospray ionization mass spectrometry (UHPLC-ESI-MS) was conducted in two ion modes (positive and negative).

Wireless electrostimulation for cancer treatment: An integrated nanoparticle/coaxial fiber mesh platform.

Cancer, namely breast and prostate cancers, is the leading cause of death in many developed countries. Controlled drug delivery systems are key for the development of new cancer treatment strategies, to improve the effectiveness of chemotherapy and tackle off-target effects. In here, we developed a biomaterials-based wireless electrostimulation system with the potential for controlled and on-demand release of anti-cancer drugs.

Physical and 3D numerical modelling of reinforcements pullout test.

This paper reports results of laboratory and 3D numerical modeled pull-out tests with steel ladders and polymeric strip reinforcements. These types of reinforcement are commonly used in reinforced soil walls constructed with concrete facing elements. Laboratory pull-out tests are required to determine accurate and realistic pull-out strength values considering the interaction of specific reinforcement and backfill materials under different confining pressures (i.

Biobased Imine Vitrimers Obtained by Photo and Thermal Curing Procedures-Promising Materials for 3D Printing.

Imine-based vitrimers were prepared from synthesized diimine-dimethacrylate monomer derived from biobased vanillin. First, a methacrylate derivative starting from vanillin was synthesized. The diimine derivative was synthesized by condensation of the aldehyde groups from two vanillin methacrylate units with the amine groups of hexamethylenediamine (HMDA).

Assessment of Noise of MEMS IMU Sensors of Different Grades for GNSS/IMU Navigation.

Inertial measurement units (IMUs) are key components of various applications including navigation, robotics, aerospace, and automotive systems. IMU sensor characteristics have a significant impact on the accuracy and reliability of these applications. In particular, noise characteristics and bias stability are critical for proper filter settings to perform a combined GNSS/IMU solution.

Embedded Wireless Sensor for In Situ Concrete Internal Relative Humidity Monitoring.

The moisture content within the concrete pore network significantly influences the mechanical, thermal, and durability characteristics of concrete structures. This paper introduces a novel fully embedded wireless temperature and relative humidity sensor connected to an automatic acquisition system designed for continuous concrete monitoring. Relative humidity measurements from this new sensor are compared with those obtained by a commercial system based on the borehole method at different depths (2.

Use of Enzymatically Converted Cell-Free DNA (cfDNA) Data for Copy Number Variation-Linked Fragmentation Analysis Allows for Early Colorectal Cancer Detection.

The use of non-invasive liquid biopsy-based cell-free DNA (cfDNA) analysis is an emerging method of cancer detection and intervention. Different analytical methodologies are used to investigate cfDNA characteristics, resulting in costly and long analysis processes needed for combining different data. This study investigates the possibility of using cfDNA data converted for methylation analysis for combining the cfDNA fragment size with copy number variation (CNV) in the context of early colorectal cancer detection.

Influence of Narrow Titanium Dental Implant Diameter on Fatigue Behavior: A Comparison between Unitary and Splinted Implants.

Scientific literature lacks strong support for using narrow diameter implants (NDI) in high masticatory force areas, especially in molars. Implant splinting in cases of multiple missing teeth reduces lateral forces, improves force distribution, and minimizes stress on implants. However, no studies have evaluated the fatigue load resistance of unitary or splinted implants.

Identification and Clinical Characteristics of Community-Acquired in Patients Hospitalized for Moderate or Severe COVID-19 in Peru.

has been described as a cause of serious community-acquired infections in tropical countries. Currently, its implications when simultaneously identified with other pathogens are not yet adequately understood. A descriptive study was conducted on hospitalized patients with a diagnosis of moderate/severe SARS-CoV-2-induced pneumonia confirmed via real-time RT-PCR.

Decoding emotional responses to AI-generated architectural imagery.

Introduction: The integration of AI in architectural design represents a significant shift toward creating emotionally resonant spaces. This research investigates AI's ability to evoke specific emotional responses through architectural imagery and examines the impact of professional training on emotional interpretation.

Methods: We utilized Midjourney AI software to generate images based on direct and metaphorical prompts across two architectural settings: home interiors and museum exteriors.

A mixture of mobility and meteorological data provides a high correlation with COVID-19 growth in an infection-naive population: a study for Spanish provinces.

Introduction: We use Spanish data from August 2020 to March 2021 as a natural experiment to analyze how a standardized measure of COVID-19 growth correlates with asymmetric meteorological and mobility situations in 48 Spanish provinces. The period of time is selected prior to vaccination so that the level of susceptibility was high, and during geographically asymmetric implementation of non-pharmacological interventions.

Methods: We develop reliable aggregated mobility data from different public sources and also compute the average meteorological time series of temperature, dew point, and UV radiance in each Spanish province from satellite data.