Simultaneous determination of the stroke volume and the left ventricular residual fraction with the fiberoptic- and thermodilution method

Simultaneous measurements of the concentration of dye by a fiberoptic catheter and of the temperature by a thermistor catheter were obtained in dogs. No significant difference for cardiac output and stroke volume was found. The slightly but significant higher residual fraction by thermodilution than by fiberoptic technique is caused by cold transfer between ventricular myocardium and cavity. It becomes evident after the fifth bea

Screening for overweight using mid-upper arm circumference (MUAC) among children younger than two years in the Eastern Cape, South Africa

Background: The relationship between overweight and under-nutrition, particularly in resource-poor settings, poses practical challenges for targeting nutrition interventions. Current anthropometric indicators including weight for length (WLZ) recommended by the WHO may be challenging in community settings. Objectives: The aim of this study was to assess whether MUAC can accurately identify children aged younger than two years with overweight and obesity. Method: A descriptive, cross-sectional study was used to collect data from a non-probability sample of 397 young South African children from October 2015 to February 2016. MUAC cut-off values were tested using a receiver operating characteristic and area under the curve (AUC). Results: The prevalence of overweight (WLZ > +2) and obesity (WLZ > +3) was 11% (n = 44) and 5% (21) respectively. A MUAC cut-off value for identifying male children 6 to 24 months old with overweight was determined at 16.5 cm (85% sensitivity, 71.4% specificity, AUC = 0.821) and female children at 16.5 cm (100% sensitivity, 76.6% specificity, AUC = 0.938). Conclusions: MUAC may be an appropriate tool for identifying children younger than two years old with overweight and obesity. The predicted MUAC cut-off values were able to identify infants and young children with overweight accurately

State-Dependent Computation Using Coupled Recurrent Networks

Although conditional branching between possible behavioral states is a hallmark of intelligent behavior, very little is known about the neuronal mechanisms that support this processing. In a step toward solving this problem, we demonstrate by theoretical analysis and simulation how networks of richly interconnected neurons, such as those observed in the superficial layers of the neocortex, can embed reliable, robust finite state machines. We show how a multistable neuronal network containing a number of states can be created very simply by coupling two recurrent networks whose synaptic weights have been configured for soft winner-take-all (sWTA) performance. These two sWTAs have simple, homogeneous, locally recurrent connectivity except for a small fraction of recurrent cross-connections between them, which are used to embed the required states. This coupling between the maps allows the network to continue to express the current state even after the input that elicited that state iswithdrawn. In addition, a small number of transition neurons implement the necessary input-driven transitions between the embedded states. We provide simple rules to systematically design and construct neuronal state machines of this kind. The significance of our finding is that it offers a method whereby the cortex could construct networks supporting a broad range of sophisticated processing by applying only small specializations to the same generic neuronal circuit

Experimental and analytical studies of advanced air cushion landing systems

Several concepts are developed for air cushion landing systems (ACLS) which have the potential for improving performance characteristics (roll stiffness, heave damping, and trunk flutter), and reducing fabrication cost and complexity. After an initial screening, the following five concepts were evaluated in detail: damped trunk, filled trunk, compartmented trunk, segmented trunk, and roll feedback control. The evaluation was based on tests performed on scale models. An ACLS dynamic simulation developed earlier is updated so that it can be used to predict the performance of full-scale ACLS incorporating these refinements. The simulation was validated through scale-model tests. A full-scale ACLS based on the segmented trunk concept was fabricated and installed on the NASA ACLS test vehicle, where it is used to support advanced system development. A geometrically-scaled model (one third full scale) of the NASA test vehicle was fabricated and tested. This model, evaluated by means of a series of static and dynamic tests, is used to investigate scaling relationships between reduced and full-scale models. The analytical model developed earlier is applied to simulate both the one third scale and the full scale response

Inferring brain-wide interactions using data-constrained recurrent neural network models

Behavior arises from the coordinated activity of numerous anatomically and functionally distinct brain regions. Modern experimental tools allow unprecedented access to large neural populations spanning many interacting regions brain-wide. Yet, understanding such large-scale datasets necessitates both scalable computational models to extract meaningful features of inter-region communication and principled theories to interpret those features. Here, we introduce Current-Based Decomposition (CURBD), an approach for inferring brain-wide interactions using data-constrained recurrent neural network models that directly reproduce experimentally-obtained neural data. CURBD leverages the functional interactions inferred by such models to reveal directional currents between multiple brain regions. We first show that CURBD accurately isolates inter-region currents in simulated networks with known dynamics. We then apply CURBD to multi-region neural recordings obtained from mice during running, macaques during Pavlovian conditioning, and humans during memory retrieval to demonstrate the widespread applicability of CURBD to untangle brain-wide interactions underlying behavior from a variety of neural datasets

Biological response of an in vitro human 3D lung cell model exposed to brake wear debris varies based on brake pad formulation

Wear particles from automotive friction brake pads of various sizes, morphology, and chemical composition are significant contributors towards particulate matter. Knowledge concerning the potential adverse effects following inhalation exposure to brake wear debris is limited. Our aim was, therefore, to generate brake wear particles released from commercial low-metallic and non-asbestos organic automotive brake pads used in mid-size passenger cars by a full-scale brake dynamometer with an environmental chamber simulating urban driving and to deduce their potential hazard in vitro. The collected fractions were analysed using scanning electron microscopy via energy-dispersive X-ray spectroscopy (SEM-EDS) and Raman microspectroscopy. The biological impact of the samples was investigated using a human 3D multicellular model consisting of human epithelial cells (A549) and human primary immune cells (macrophages and dendritic cells) mimicking the human epithelial tissue barrier. The viability, morphology, oxidative stress, and (pro-)inflammatory response of the cells were assessed following 24 h exposure to similar to 12, similar to 24, and similar to 48 A mu g/cm(2) of non-airborne samples and to similar to 3.7 A mu g/cm(2) of different brake wear size fractions (2-4, 1-2, and 0.25-1 A mu m) applying a pseudo-air-liquid interface approach. Brake wear debris with low-metallic formula does not induce any adverse biological effects to the in vitro lung multicellular model. Brake wear particles from non-asbestos organic formulated pads, however, induced increased (pro-)inflammatory mediator release from the same in vitro system. The latter finding can be attributed to the different particle compositions, specifically the presence of anatase.Web of Science9272351233