Extraction of Saponins from Soapnut (Sapindus Mukorossi) and Their Antimicrobial Properties

In this study optimization of extraction conditions for saponin from Sapindus mukorossi was investigated. Results showed that polarity of the extraction solvent affects the yield percentage of the extraction process. Best yield percentage was obtained as 78.1 % at 1:10 solid-liquid ratio in aqueous ethanol solution (50% v/v). The antimicrobial properties of extracts containing saponins were investigated for different microorganisms. Minimum inhibition concentrations of extract were obtained against Escherichia coli, Staphylococcus aureus and Candida albicans. Minimum inhibition concentrations (MIC) of saponin extract ranged between 12.5 mg/mL to 25 mg/mL.nbs

Vortex Images and q-Elementary Functions

In the present paper problem of vortex images in annular domain between two coaxial cylinders is solved by the q-elementary functions. We show that all images are determined completely as poles of the q-logarithmic function, where dimensionless parameter $q = r^2_2/r^2_1$ is given by square ratio of the cylinder radii. Resulting solution for the complex potential is represented in terms of the Jackson q-exponential function. By composing pairs of q-exponents to the first Jacobi theta function and conformal mapping to a rectangular domain we link our solution with result of Johnson and McDonald. We found that one vortex cannot remain at rest except at the geometric mean distance, but must orbit the cylinders with constant angular velocity related to q-harmonic series. Vortex images in two particular geometries in the $q \to \infty$ limit are studied.Comment: 17 page

Experimental study of a TLP offshore floating wind turbine

Tank testing in a wind and wave environment is a key part of the design process for the development of an offshore floating wind turbine. The current paper describes an extensive experiment campaign carried out at the Kelvin Hydrodynamics Laboratory at the University of Strathclyde to determine the hydrodynamic performance of the Iberdrola TLPWIND offshore floating wind turbine with the NREL 5MW reference turbine over a range of environmental conditions. Tests were carried out for 70m water depth and the deployment area selected as off Aberdeen, North Sea. The campaign included free oscillation tests, tests in regular waves and irregular waves, and additionally examined failure and accidental load cases

Myocardial contractile function in survived neonatal piglets after cardiopulmonary bypass

<p>Abstract</p> <p>Background</p> <p>Hemodynamic function may be depressed in the early postoperative stages after cardiac surgery. The aim of this study was the analysis of the myocardial contractility in neonates after cardiopulmonary bypass (CPB) and mild hypothermia.</p> <p>Methods</p> <p>Three indices of left ventricular myocardial contractile function (dP/dt, (dP/dt)/P, and wall thickening) were studied up to 6 hours after CPB in neonatal piglets (CPB group; n = 4). The contractility data were analysed and then compared to the data of newborn piglets who also underwent median thoracotomy and instrumentation for the same time intervals but without CPB (non-CPB group; n = 3).</p> <p>Results</p> <p>Left ventricular dP/dt_maxand (dP/dt_max)/P remained stable in CPB group, while dP/dt_maxdecreased in non-CPB group 5 hours postoperatively (1761 ± 205 mmHg/s at baseline vs. 1170 ± 205 mmHg/s after 5 h; p < 0.05). However, with regard to dP/dt_maxand (dP/dt_max)/P there were no statistically significant differences between the two groups. Comparably, although myocardial thickening decreased in the non-CPB group the differences between the two groups were not statistically significant.</p> <p>Conclusions</p> <p>The myocardial contractile function in survived neonatal piglets remained stable 6 hours after cardiopulmonary bypass and mild hypothermia probably due to regional hypercontractility.</p

Evaluation of cancer outcome assessment using MRI: A review of deep-learning methods

Accurate evaluation of tumor response to treatment is critical to allow personalized treatment regimens according to the predicted response and to support clinical trials investigating new therapeutic agents by providing them with an accurate response indicator. Recent advances in medical imaging, computer hardware, and machine-learning algorithms have resulted in the increased use of these tools in the field of medicine as a whole and specifically in cancer imaging for detection and characterization of malignant lesions, prognosis, and assessment of treatment response. Among the currently available imaging techniques, magnetic resonance imaging (MRI) plays an important role in the evaluation of treatment assessment of many cancers, given its superior soft-tissue contrast and its ability to allow multiplanar imaging and functional evaluation. In recent years, deep learning (DL) has become an active area of research, paving the way for computer-assisted clinical and radiological decision support. DL can uncover associations between imaging features that cannot be visually identified by the naked eye and pertinent clinical outcomes. The aim of this review is to highlight the use of DL in the evaluation of tumor response assessed on MRI. In this review, we will first provide an overview of common DL architectures used in medical imaging research in general. Then, we will review the studies to date that have applied DL to magnetic resonance imaging for the task of treatment response assessment. Finally, we will discuss the challenges and opportunities of using DL within the clinical workflow

Modeling dissolved oxygen dynamics and hypoxia

Abstract. Hypoxia conditions are increasing throughout the world, influencing biogeochemical cycles of elements and marine life. Hypoxia results from complex interactions between physical and biogeochemical processes, which can not be understood by observations alone. Models are invaluable tools at studying system dynamics, generalizing discrete observations and predicting future states. They are also useful as management tools for evaluating site-specific responses to management scenarios. Here we review oxygen dynamics models that have significantly contributed to a better understanding of the effects of natural processes and human perturbations on the development of hypoxia, factors controlling the extent and temporal variability of coastal hypoxia, and the effects of oxygen depletion on biogeochemical cycles. Because hypoxia occurs in a variety of environments and can be persistent, periodic or episodic, models differ significantly in their complexity and temporal and spatial resolution. We discuss the progress in developing hypoxia models for benthic and pelagic systems that range from simple box models to three dimensional circulation models. Applications of these models in five major hypoxia regions are presented. In the last decades, substantial progress has been made towards the parameterization of biogeochemical processes in both hypoxic water columns and sediments. In coastal regions, semi-empirical models have been used more frequently than mechanistic models to study nutrient enrichment and hypoxia relationships. Recent advances in three-dimensional coupled physical-ecological-biogeochemical models have allowed a better representation of physical-biological interactions in these systems. We discuss the remaining gaps in process descriptions and suggest directions for improvement. Better process representations in models will help us answer several important questions, such as those about the causes of the observed worldwide increase in hypoxic conditions, and future changes in the intensity and spread of coastal hypoxia. At the same time, quantitative model intercomparison studies suggest that the predictive ability of our models may be adversely affected by their increasing complexity, unless the models are properly constrained by observations. Natural and Human-Induced Hypoxia and Consequences for Coastal AreasPublisher's Versio

Improving emerging European NMIs’ capabilities in humidity measurement

The control and measurement of humidity is important for many industrial applications and to ensure the appropriate storage of materials and products. Humidity measurement techniques are diverse and each presents different challenges for use and calibration for a range of pressures and gases. Over the past few years, the development of humidity sensors and apparatus has matured to a level where traceable calibration is beneficial to all industries in which humidity and moisture measurement and control are important. This paper deals with a European project in which the overall objective is to develop or extend the measurement and research capabilities of the participating emerging NMI/DIs’ countries in the field of humidity measurements, where access to these types of facilities is currently limited