Characterisation and modelling of the elastic properties of poly(lactic acid) nanofibre scaffolds

The aim of this study is to predict the elastic response of poly(lactic acid) (PLA) electrospun nanofibre scaffolds through mathematical models based on homogenisation and the differential replacement method (DRM). These models principally seek to determine and analyse the effects of the internal morphology of the nanofibres on the effective Young’s modulus of polymer nanofibre scaffolds. The microstructure of the nanofibres was first characterised by SEM, XRD, DSC, AFM, and TEM techniques. From this characterisation, strong evidence of a hierarchical core–shell structure was found. With the experimental data, it was possible to design and validate better models than those currently used. In addition, the effects of the electrospinning parameters, such as take-up velocity and thermal treatment, were analysed and correlated with the morphology and the elastic properties of the nanofibres and their scaffolds. To validate the models’ results, we conducted a series of uniaxial tensile tests on the PLA nanofibre scaffolds. Using the data from the nanofibre measurements, the homogenisation approximations and the model based on the DRM predicted an effective Young’s modulus of 667 and 835 MPa, respectively. The predicted data were in excellent agreement with the experimental results (685–880 MPa). These models will be useful in understanding and evaluating the structure–property relationships of oriented nanofibre scaffolds for medical or biological applications.     

Adaptive local learning techniques for multiple-step-ahead wind speed forecasting

A massive deployment of wind energy in power systems is expected in the near future. However, a still open issue is how to integrate wind generators into existing electrical grids by limiting their side effects on network operations and control. In order to attain this objective, accurate short and medium-term wind speed forecasting is required.This paper discusses and compares a physical (white-box) model (namely a limited-area non hydrostatic model developed by the European consortium for small-scale modeling) with a family of local learning techniques (black-box) for short and medium term forecasting. Also, an original model integrating machine learning techniques with physical knowledge modeling (grey-box) is proposed.A set of experiments on real data collected from a set of meteorological sensors located in the south of Italy supports the methodological analysis and assesses the potential of the different forecasting approaches.     

Geometric Parameterization Technique for Continuation Power Flow Based on Quadratic Curve

The electricity sector, especially in emerging countries, has experienced several transformations, mainly resulting from the increase of electricity demand. This encourages more investment in the generation sector and causes increasing concerns with the development and improvement of tools for static voltage stability analysis of electrical power systems. This paper presents a new geometric parameterization technique for continuation power flow (CPF) that works based on the addition of a parabola that passes through three points in the plane formed by the variables of total real power losses and loading factor. This technique eliminates the Jacobian matrix singularity at the maximum loading point, which allows obtaining the solution trajectory (P–V curve) without any need to change the parameter, which is a very common procedure in the currently available CPFs. Intending to define a simple and efficient step size control procedure, the total real power losses values are normalized by its base case value. The results obtained by applying the proposed technique to the IEEE-300 bus system and two real large systems of 638 and 787 buses show its effectiveness.     

Sarcopenia: Molecular Pathways and Potential Targets for Intervention

Aging is associated with sarcopenia. The loss of strength results in decreased muscle mass and motor function. This process accelerates the progressive muscle deterioration observed in older adults, favoring the presence of debilitating pathologies. In addition, sarcopenia leads to a decrease in quality of life, significantly affecting self-sufficiency. Altogether, these results in an increase in economic resources from the National Health Systems devoted to mitigating this problem in the elderly, particularly in developed countries. Different etiological determinants are involved in the progression of the disease, including: neurological factors, endocrine alterations, as well as nutritional and lifestyle changes related to the adoption of more sedentary habits. Molecular and cellular mechanisms have not been clearly characterized, resulting in the absence of an effective treatment for sarcopenia. Nevertheless, physical activity seems to be the sole strategy to delay sarcopenia and its symptoms. The present review intends to bring together the data explaining how physical activity modulates at a molecular and cellular level all factors that predispose or favor the progression of this deteriorating pathology.     

Energy requirements and production cost of the spray drying process of cheese whey

The influence of spray drying conditions on the energy required, production cost, and physicochemical characteristics of cheese whey was researched. The factors investigated were the inlet air temperature (180–220°C), outlet air temperature (80–100°C), and silica and maltodextrin (DE-10) as additives at 2 and 5% (w/w), respectively. Analysis of variance revealed that the inlet and outlet air temperatures, and the addition of additives had significant effects (p?T_inlet of 180°C, T_outlet of 80°C, and the addition of 5% additive material. Under these conditions, 0.2165?kg/h of dried product was obtained, with a moisture content of 2.08% and water activity of 0.125, and the product cost was $17.06?kg with an energy consumption of 2.0490?kW?·?h/kg of dry product.     

Assessment of a Cylindrical and a Rectangular Plate Differential Mobility Analyzer for Size Fractionation of Nanoparticles at High-Aerosol Flow Rates

An existing differential mobility analyzer (DMA) of cylindrical electrodes and a novel DMA of rectangular plate electrodes are demonstrated for size fractionation of nanoparticles at high-aerosol flow rates in this work. The two DMAs are capable of delivering monodisperse size selected nanoparticles (SMPS σ_g < 1.1) at gas flow rates ranging from 200 slm to 500 slm. At an aerosol flow rate of 200 slm, the maximum attainable particle mean size is of about 20 nm for the cylindrical DMA and of nearly 50 nm for the rectangular plate DMA. The number concentration of the monodisperse nanoparticles delivered by the high-flow DMAs spans from 10⁴ cm^?3 to 10⁶ cm^?3 depending upon the particle mean size and particle size dispersion.

Copyright 2014 American Association for Aerosol Research     

Metformin Reduces Lipogenesis Markers in Obese Mice Fed a Low-Carbohydrate and High-Fat Diet

Lipogenesis is the process by which fatty acids are synthesized. In metabolic syndrome, an insulin resistant state along with high plasma levels of free fatty acids (FFA) and hyperglycemia may contribute to the lipogenic process. The aim of the present study was to investigate the effects of oral administration of metformin on the expression of lipogenic genes and glycemic profile in mice fed with low‐carbohydrate high‐fat diet by evaluating their metabolic profile. SWISS male mice were divided into 4 groups (N = 7) that were fed with standard (ST), standard plus metformin (ST + MET), low‐carbohydrate high‐fat diet (LCHFD) and low‐carbohydrate high‐fat diet plus metformin (LCHFD + MET) (100 mg kg^?1 diet) diets respectively. Food intake, body weight and blood parameters, such as glucose tolerance, insulin sensitivity, glucose, HDL‐c, total cholesterol, triglycerides, ASL and ALT levels were assessed. Histological analyses were performed on hematoxylin and eosin‐stained epididymal adipose tissue histological specimens. The expression levels of peroxisome proliferator‐activated receptor (PPARγ), sterol regulatory element‐binding protein 1 (SREBP1), fatty acid synthase (FAS) and acetyl‐CoA carboxylase (ACC), were assessed by RT‐PCR. This study showed that metformin decreased adipocyte area, body weight and food consumption in obese animals when compared to the standard group. Furthermore, the expression of lipogenic markers in adipose tissue were diminished in obese animals treated with metformin. This data showed that oral administration of metformin improved glucose and lipid metabolic parameters in white adipose tissue by reducing the expression of lipogenesis markers, suggesting an important clinical application of MET in treating obesity‐related diseases in metabolic syndrome.