Improving pulmonary perfusion assessment by dynamic contrast-enhanced computed tomography in an experimental lung injury model.

Pulmonary perfusion has been poorly characterized in acute respiratory distress syndrome (ARDS). Optimizing protocols to measure pulmonary blood flow (PBF) via dynamic contrast-enhanced (DCE) computed tomography (CT) could improve understanding of how ARDS alters pulmonary perfusion. In this study, comparative evaluations of injection protocols and tracer-kinetic analysis models were performed based on DCE-CT data measured in ventilated pigs with and without lung injury.

An econometric analysis for the determinants of flight speed in the air transport of passengers.

Accurately determining an aircraft's flight speed is crucial for optimizing airline performance, as it directly impacts factors such as fuel consumption and emissions. Flying at speeds higher than what is recommended by the manufacturer can result in increased fuel burn. However, flying at slower speeds may lead to longer flight times and competitive disadvantages for airlines as passengers typically prefer shorter travel times.

Mixed-integer quadratic programming approach for noninvasive estimation of respiratory effort profile during pressure support ventilation.

Information about respiratory mechanics such as resistance, elastance, and muscular pressure is important to mitigate ventilator-induced lung injury. Particularly during pressure support ventilation, the available options to quantify breathing effort and calculate respiratory system mechanics are often invasive or complex. We herein propose a robust and flexible estimation of respiratory effort better than current methods.

Mathematical modeling and investigation on the role of demography and contact patterns in social distancing measures effectiveness in COVID-19 dissemination.

In this article, we investigate the importance of demography and contact patterns in determining the spread of COVID-19 and to the effectiveness of social distancing policies. We investigate these questions proposing an augmented epidemiological model with an age-structured model, with the population divided into susceptible (S), exposed (E), asymptomatic infectious (A), hospitalized (H), symptomatic infectious (I) and recovered individuals (R), to simulate COVID-19 dissemination. The simulations were carried out using six combinations of four types of isolation policies (work restrictions, isolation of the elderly, community distancing and school closures) and four representative fictitious countries generated over alternative demographic transition stage patterns (aged developed, developed, developing and least developed countries).

Applications of graph theory to the analysis of fNIRS data in hyperscanning paradigms.

Hyperscanning is a promising tool for investigating the neurobiological underpinning of social interactions and affective bonds. Recently, graph theory measures, such as modularity, have been proposed for estimating the global synchronization between brains. This paper proposes the bootstrap modularity test as a way of determining whether a pair of brains is coactivated.

Cancer Inhibition and In Vivo Osteointegration and Compatibility of Gallium-Doped Bioactive Glasses for Osteosarcoma Applications.

Traditional osteosarcoma therapies tend to focus solely on eradicating residual cancer cells and often fail to promote local bone regeneration and even inhibit it due to lack of precise control over target cells, i.e., the treatment affects both normal and cancer cells.

Long-Life and pH-Stable SnO-Coated Au Nanoparticles for SHINERS.

Shell-isolated nanoparticles (SHINs) with a 37 nm gold core and an 11 nm tin dioxide (SnO) coating exhibited long-life Raman enhancement for 3 months and a wide pH stability of pH 2-13 in comparison with conventional SiO-coated SHINs. Herein, Au-SnO is demonstrated as a more durable SHIN for use in the technique Shell-Isolated Nanoparticles for Enhanced Raman Spectroscopy (SHINERS).

Lightweight Design of Variable-Stiffness Cylinders with Reduced Imperfection Sensitivity Enabled by Continuous Tow Shearing and Machine Learning.

The present study investigates how to apply continuous tow shearing (CTS) in a manufacturable design parameterization to obtain reduced imperfection sensitivity in lightweight, cylindrical shell designs. The asymptotic nonlinear method developed by Koiter is applied to predict the post-buckled stiffness, whose index is constrained to be positive in the optimal design, together with a minimum design load. The performance of three machine learning methods, namely, Support Vector Machine, Kriging, and Random Forest, are compared as drivers to the optimization towards lightweight designs.

Testing the differentiated impact of the COVID-19 pandemic on air travel demand considering social inclusion.

The economic downturn and the air travel crisis triggered by the recent coronavirus pandemic pose a substantial threat to the new consumer class of many emerging economies. In Brazil, considerable improvements in social inclusion have fostered the emergence of hundreds of thousands of first-time fliers over the past decades. We apply a two-step regression methodology in which the first step consists of identifying air transport markets characterized by greater social inclusion, using indicators of the local economies' income distribution, credit availability, and access to the Internet.

Applications of Plasma-Activated Water in Dentistry: A Review.

The activation of water by non-thermal plasma creates a liquid with active constituents referred to as plasma-activated water (PAW). Due to its active constituents, PAW may play an important role in different fields, such as agriculture, the food industry and healthcare. Plasma liquid technology has received attention in recent years due to its versatility and good potential, mainly focused on different health care purposes.

Brazilian disaster datasets and real-world instances for optimization and machine learning.

We present comprehensive datasets of Brazilian disasters from January 2003 to February 2021 as well as real-world optimization instances built up from these data. The data were gathered through a series of open available reports obtained from different government and institutional sources. Afterwards, data consolidation and summarization were carried out using Excel and Python.

Identification of Representative Equivalent Volumes on the Microstructure of 3D-Printed Fiber-Reinforced Thermoplastics Based on Statistical Characterization.

The present work describes a methodology to compute equivalent volumes representing the microstructure of 3D-printed continuous fiber-reinforced thermoplastics, based on a statistical characterization of the fiber distribution. In contrast to recent work, the methodology herein presented determines the statistically equivalent fiber distribution directly from cross-section micrographs, instead of generating random fiber arrangements. For this purpose, several regions, with different sizes and from different locations, are cropped from main cross-section micrographs and different spatial descriptor functions are adopted to characterize the microstructures in terms of agglomeration and periodicity of the fibers.

Non-Cooperative SAR Automatic Target Recognition Based on Scattering Centers Models.

This article proposes an Automatic Target Recognition (ATR) algorithm to classify non-cooperative targets in Synthetic Aperture Radar (SAR) images. The scarcity or nonexistence of measured SAR data demands that classification algorithms rely only on synthetic data for training purposes. Based on a model represented by the set of scattering centers extracted from purely synthetic data, the proposed algorithm generates hypotheses for the set of scattering centers extracted from the target under test belonging to each class.

Sequential lateral positioning as a new lung recruitment maneuver: an exploratory study in early mechanically ventilated Covid-19 ARDS patients.

Background: A sequential change in body position from supine-to-both lateral positions under constant ventilatory settings could be used as a postural recruitment maneuver in case of acute respiratory distress syndrome (ARDS), provided that sufficient positive end-expiratory pressure (PEEP) prevents derecruitment. This study aims to evaluate the feasibility and physiological effects of a sequential postural recruitment maneuver in early mechanically ventilated COVID-19 ARDS patients.

Methods: A cohort of 15 patients receiving lung-protective mechanical ventilation in volume-controlled with PEEP based on recruitability were prospectively enrolled and evaluated in five sequentially applied positions for 30 min each: Supine-baseline; Lateral-1st side; 2nd Supine; Lateral-2nd side; Supine-final.

Smooth second-order sliding mode control for fully actuated multirotor aerial vehicles.

The present paper is concerned with the robust and smooth attitude-position tracking control of fully actuated multirotor aerial vehicles equipped with fixed rotors and subject to matched model uncertainties and disturbances. The vehicle coupled dynamic equations representing the translational and rotational motions are thoroughly derived using the multibody approach, considering the external torque and force disturbances as well as the uncertainties in the inertia parameters of the airframe and the rotors. From this model, it is shown that the overall disturbances and uncertainties can be lumped into an additive-matched plant-model discrepancy.

From communities to protein complexes: A local community detection algorithm on PPI networks.

Identifying protein complexes in protein-protein interaction (ppi) networks is often handled as a community detection problem, with algorithms generally relying exclusively on the network topology for discovering a solution. The advancement of experimental techniques on ppi has motivated the generation of many Gene Ontology (go) databases. Incorporating the functionality extracted from go with the topological properties from the underlying ppi network yield a novel approach to identify protein complexes.

Wayset-based guidance of multirotor aerial vehicles using robust tube-based model predictive control.

The present paper is concerned with the wayset-based guidance of underactuated multirotor aerial vehicles (MAVs). A hierarchical guidance and control structure is first established, in which the guidance is realized as a supervisory loop. The lower-level stabilizing attitude and position control laws are assumed to be available.

The Potential Applications of Augmented Reality in Fetoscopic Surgery for Antenatal Treatment of Myelomeningocele.

Objective: To develop a preoperative planning method using augmented reality (AR) of a specific surgical procedure: fetoscopy for myelomeningocele repair.

Methods: Imaging data were acquired of a pregnant woman at 27 weeks of gestation whose fetus was diagnosed with myelomeningocele. The patient was identified as a candidate for fetoscopic repair of the spine defect, and an AR application for mobile device simulation was developed.

An Extended Methodology for Sizing Solar Unmanned Aerial Vehicles: Theory and Development of a Python Framework for Design Assist.

There is a growing interest in using unmanned aerial vehicles (UAVs) in the most diverse application areas from agriculture to remote sensing, that determine the need to project and define mission profiles of the UAVs. In addition, solar photovoltaic energy increases the flight autonomy of this type of aircraft, forming the term Solar UAV. This study proposes an extended methodology for sizing Solar UAVs that take off from a runway.

MoHRiPA-An Architecture for Hybrid Resources Management of Private Cloud Environments.

The high demand for data processing in web applications has grown in recent years due to the increased computing infrastructure supply as a service in a cloud computing ecosystem. This ecosystem offers benefits such as broad network access, elasticity, and resource sharing, among others. However, properly exploiting these benefits requires optimized provisioning of computational resources in the target infrastructure.

Alternative Formulation of Antenna Arrays for DF Systems Considering Active-Element Patterns and Scattering Matrices.

Direction finding (DF) systems are used to determine the direction-of-arrival (DoA) of electromagnetic waves, thus allowing for the tracking of RF sources. In this paper, we present an alternative formulation of antenna arrays for modeling DF systems. To improve the accuracy of the data provided by the DF systems, the effects of mutual coupling in the array, polarization of the received waves, and impedance mismatches in the RF front-end receiver are all taken into account in the steering vectors of the DoA algorithms.

Machine learning predicts treatment sensitivity in multiple myeloma based on molecular and clinical information coupled with drug response.

Providing treatment sensitivity stratification at the time of cancer diagnosis allows better allocation of patients to alternative treatment options. Despite many clinical and biological risk markers having been associated with variable survival in cancer, assessing the interplay of these markers through Machine Learning (ML) algorithms still remains to be fully explored. Here, we present a Multi Learning Training approach (MuLT) combining supervised, unsupervised and self-supervised learning algorithms, to examine the predictive value of heterogeneous treatment outcomes for Multiple Myeloma (MM).

DFT-1/2 method applied to 2D topological insulators: fluorinated and hydrogenated group-IV honeycomb systems.

We present a computationally efficient and accurate methodology to computetopological invariants for systems without inversion symmetry including quasiparticle (QP) effects within the density functional theory (DFT)-1/2 method. The Wannier charge center evolution is applied to compute thetopological invariant and investigate the topological properties of group-IV graphene-like systems, graphene, silicene, germanene and stanene, whose inversion symmetry is broken by simultaneous functionalization with hydrogen and fluorine atoms. Different atomic arrangements are studied.