An efficient heuristic for geometric analysis of cell deformations.

Sickle cell disease causes erythrocytes to become sickle-shaped, affecting their movement in the bloodstream and reducing oxygen delivery. It has a high global prevalence and places a significant burden on healthcare systems, especially in resource-limited regions. Automated classification of sickle cells in blood images is crucial, allowing the specialist to reduce the effort required and avoid errors when quantifying the deformed cells and assessing the severity of a crisis.

Outlier detection of clustered functional data with image and signal processing applications by archetype analysis.

In this study, we introduce an innovative methodology for anomaly detection of curves, applicable to both multivariate and multi-argument functions. This approach distinguishes itself from prior methods by its capability to identify outliers within clustered functional data sets. We achieve this by extending the recent AA + kNN technique, originally designed for multivariate analysis, to functional data contexts.

A brief review and guidance on the spatiotemporal sampling designs for disease vector surveillance.

Obtaining a representative sample of disease vectors (mosquitoes, flies, ticks, etc.) is essential for researchers to draw meaningful conclusions about the entire vector population in a target study area and during a specific study period. To achieve this, a carefully chosen surveillance design is required to ensure that the sample captures essential spatial and temporal variations in the target vector population(s) and/or that the study results can be generalized to the entire population.

Urban environment and health: a cross-sectional multiregional project based on population health surveys in Spain (DAS-EP project) - study protocol.

Introduction: The European Environment Agency estimates that 75% of the European population lives in cities. Despite the many advantages of city life, the risks and challenges to health arising from urbanisation need to be addressed in order to tackle the growing burden of disease and health inequalities in cities. This study, (DAS-EP project), aims to investigate the complex association between the urban environmental exposures (UrbEEs) and health.

Electrically Controlled All-Antiferromagnetic Tunnel Junctions on Silicon with Large Room-Temperature Magnetoresistance.

Antiferromagnetic (AFM) materials are a pathway to spintronic memory and computing devices with unprecedented speed, energy efficiency, and bit density. Realizing this potential requires AFM devices with simultaneous electrical writing and reading of information, which are also compatible with established silicon-based manufacturing. Recent experiments have shown tunneling magnetoresistance (TMR) readout in epitaxial AFM tunnel junctions.

White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group.

White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated in the neurobiology of obsessive-compulsive disorder (OCD). However, due to limited sample sizes and the predominance of single-site studies, the generalizability of OCD classification based on diffusion white matter estimates remains unclear. Here, we tested classification accuracy using the largest OCD DTI dataset to date, involving 1336 adult participants (690 OCD patients and 646 healthy controls) and 317 pediatric participants (175 OCD patients and 142 healthy controls) from 18 international sites within the ENIGMA OCD Working Group.

Insights into synaptic functionality and resistive switching in lead iodide flexible memristor devices.

Neuromorphic platforms are gaining popularity due to their superior efficiency, low power consumption, and adaptable parallel signal processing capabilities, overcoming the limitations of traditional von Neumann architecture. We conduct an in-depth investigation into the factors influencing the resistive switching mechanism in memristor devices utilizing lead iodide (PbI). We establish correlations between device performance and morphological features, unveiling synaptic like behaviour of device making it suitable for range of flexible neuromorphic applications.

Solanum lycopersicum heme-binding protein 2 as a potent antimicrobial weapon against plant pathogens.

The rise in antibiotic-resistant bacteria caused by the excessive use of antibiotics has led to the urgent exploration of alternative antimicrobial solutions. Among these alternatives, antimicrobial proteins, and peptides (Apps) have garnered attention due to their wide-ranging antimicrobial effects. This study focuses on evaluating the antimicrobial properties of Solanum lycopersicum heme-binding protein 2 (SlHBP2), an apoplastic protein extracted from tomato plants treated with 1-Methyl tryptophan (1-MT), against Pseudomonas syringae pv.

Neoadjuvant Chemotherapy plus Interval Cytoreductive Surgery with or without Hyperthermic Intraperitoneal Chemotherapy (NIHIPEC) in the Treatment of Advanced Ovarian Cancer: A Multicentric Propensity Score Study.

Introduction: Epithelial ovarian cancer (EOC) is primarily confined to the peritoneal cavity. When primary complete surgery is not possible, neoadjuvant chemotherapy (NACT) is provided; however, the peritoneum-plasma barrier hinders the drug effect. The intraperitoneal administration of chemotherapy could eliminate residual microscopic peritoneal tumor cells and increase this effect by hyperthermia.

Probabilistic computing with voltage-controlled dynamics in magnetic tunnel junctions.

Probabilistic (p-) computing is a physics-based approach to addressing computational problems which are difficult to solve by conventional von Neumann computers. A key requirement for p-computing is the realization of fast, compact, and energy-efficient probabilistic bits. Stochastic magnetic tunnel junctions (MTJs) with low energy barriers, where the relative dwell time in each state is controlled by current, have been proposed as a candidate to implement p-bits.

Cross-sectional evaluation of the association between greenness and cognitive performance in Mexican pre-pubertal boys.

Background: Evidence shows that greenspace exposure benefits children's health and cognitive development. However, evidence assessing this association in young children in low- and middle-income economies is scarce.

Objective: To assess the association between exposure to greenness and cognitive performance in pre-pubertal boys living in Mexico City.

Brain-anatomy image data set for problem solving associated with reversal error: Volumetric data.

Reversal Error (RE) is a common error in algebra problem solving. This error occurs when students recognize the information in the statement but make mistakes when translating some sentences from natural language to algebraic language, reversing the relationship between two variables in comparison word problems. Structural Magnetic Resonance Image (sMRI) data were collected with the purpose of identifying brain anatomical regions related to the RE phenomenon.

Development and Validation of a Meta-Instrument for the Assessment of Functional Capacity, the Risk of Falls and Pressure Injuries in Adult Hospitalization Units (VALENF Instrument) (Part II).

The nursing assessment is the first step of the nursing process and fundamental to detecting patients' care needs and at-risk situations. This article presents the psychometric properties of the VALENF Instrument, a recently developed meta-instrument with only seven items that integrates the assessment of functional capacity, risk of pressure injuries and risk of falls with a more parsimonious approach to nursing assessment in adult hospitalization units. A cross-sectional study based on recorded data in a sample of 1352 nursing assessments was conducted.

COVID-19 transmission risk in Surabaya and Sidoarjo: an inhomogeneous marked Poisson point process approach.

Understanding the spatio-temporal dynamics of COVID-19 transmission is necessary to plan better strategies for controlling the spread of the disease. However, only a few studies explore the COVID-19 transmission risk over a fine spatial resolution while considering relevant spatial and temporal factors. To this aim, we consider an inhomogeneous marked Poisson point process model to assess COVID-19 transmission risk using data of home addresses of confirmed cases, in relation to locations of sources of crowd (enterprise, market, and place of worship) and population density in Surabaya and Sidoarjo, Indonesia.

Ultrafast Loss of Lattice Coherence in the Light-Induced Structural Phase Transition of V_{2}O_{3}.

In solids, the response of the lattice to photoexcitation is often described by the inertial evolution on an impulsively modified potential energy surface which leads to coherent motion. However, it remains unknown if vibrational coherence is sustained through a phase transition, during which coupling between modes can be strong and may lead to rapid loss of coherence. Here we use coherent phonon spectroscopy to track lattice coherence in the structural phase transition of V_{2}O_{3}.

Ethical allocation of scarce vaccine doses: The Priority-Equality protocol.

Background: Whenever vaccines for a new pandemic or widespread epidemic are developed, demand greatly exceeds the available supply of vaccine doses in the crucial, initial phases of vaccination. Rationing protocols must then fulfill a number of ethical principles balancing equal treatment of individuals and prioritization of at-risk and instrumental subpopulations. For COVID-19, actual rationing methods used a territory-based first allocation stage based on proportionality to population size, followed by locally-implemented prioritization rules.

The underlying neural bases of the reversal error while solving algebraic word problems.

Problem solving is a core element in mathematical learning. The reversal error in problem solving occurs when students are able to recognize the information in the statement of comparison word problems, but they reverse the relationship between two variables when building the equations. Functional magnetic resonance images were acquired to identify for the first time the neural bases associated with the reversal error.

Bayesian and network models with covariate effects for predicting heating energy demand.

The spatial effect is an element presented in many geostatistical works and it should be incorporated into studies regarding the heating energy demand of residential building stocks. The most common approaches have been made by simple descriptive statistics or using analyses by Markov random fields. In this work, we propose two different methods.

Development and Validation of a Meta-Instrument for Nursing Assessment in Adult Hospitalization Units (VALENF Instrument) (Part I).

Nursing assessment is the basis for performing interventions that match patient needs, but nurses perceive it as an administrative load. This research aims to develop and validate a meta-instrument that integrates the assessment of functional capacity, risk of pressure ulcers and risk of falling with a more parsimonious approach to nursing assessment in adult hospitalization units. Specifically, this manuscript presents the results of the development of this meta-instrument (VALENF instrument).

A phenomenological model for COVID-19 data taking into account neighboring-provinces effect and random noise.

We model the incidence of the COVID-19 disease during the first wave of the epidemic in Castilla-Leon (Spain). Within-province dynamics may be governed by a generalized logistic map, but this lacks of spatial structure. To couple the provinces, we relate the daily new infections through a density-independent parameter that entails positive spatial correlation.

I am done with this! Women dropping out of engineering majors.

Women are still underrepresented in STEM careers (Science, Technology, Engineering, and Mathematics). One of the possible drivers behind this gender gap in the labour market is the female dropout from STEM education. The causes of the gender differences in the persistence of pursuing STEM studies have been explained by multiple factors related to interest and resolution in this type of career.