Optimal integration of a hybrid solar-battery power source into smart home nanogrid with plug-in electric vehicle

Hybrid solar-battery power source is essential in the nexus of plug-in electric vehicle (PEV), renewables, and smart building. This paper devises an optimization framework for efficient energy management and components sizing of a single smart home with home battery, PEV, and potovoltatic (PV) arrays. We seek to maximize the home economy, while satisfying home power demand and PEV driving. Based on the structure and system models of the smart home nanogrid, a convex programming (CP) problem is formulated to rapidly and efficiently optimize both the control decision and parameters of the home battery energy storage system (BESS). Considering different time horizons of optimization, home BESS prices, types and control modes of PEVs, the parameters of home BESS and electric cost are systematically investigated. Based on the developed CP control law in home to vehicle (H2V) mode and vehicle to home (V2H) mode, the home with BESS does not buy electric energy from the grid during the electric price's peak periods

Poly(sulfur-random-(1,3-diisopropenylbenzene)) Based Mid-Wavelength Infrared Polarizer: Optical Property Experimental and Theoretical Analysis

Development of polymer based mid-wavelength infrared (MWIR) optics has been limited mainly due to high optical loss of organic polymers used in general optical components. In this study, a MWIR polarization grating based on a sulfuric polymer poly(sulfur-random-(1,3-diisopropenylbenzene)) with a low loss in the MWIR range was fabricated using a simple two-step process: imprint and metal deposition. Fourier-transform infrared (FTIR) spectroscopy measurement showed that this polymeric MWIR polarizer selectively transmitted the polarized IR in transverse magnetic (TM) mode over the transverse electric (TE) mode at normal incidence. The measured extinction ratios (  = The ratio of transmissions in TM and TE) were 208, 176, and 212 at the wavelength of 3, 4, and 5 μm, respectively. The computational simulation and analytical model confirmed that the enhanced TM transmission efficiency and followed a Fabry-Pérot (FP) resonance mode within the created sulfuric polymer film. This polymeric MWIR polarizer demonstrated a great potential for broader applications in IR photonics to realize low-cost and durable optical components

Subtle changes in the flavour and texture of a drink enhance expectations of satiety

Background: The consumption of liquid calories has been implicated in the development of obesity and weight gain. Energy-containing drinks are often reported to have a weak satiety value: one explanation for this is that because of their fluid texture they are not expected to have much nutritional value. It is important to consider what features of these drinks can be manipulated to enhance their expected satiety value. Two studies investigated the perception of subtle changes in a drink’s viscosity, and the extent to which thick texture and creamy flavour contribute to the generation of satiety expectations. Participants in the first study rated the sensory characteristics of 16 fruit yogurt drinks of increasing viscosity. In study two, a new set of participants evaluated eight versions of the fruit yogurt drink, which varied in thick texture, creamy flavour and energy content, for sensory and hedonic characteristics and satiety expectations. Results: In study one, participants were able to perceive small changes in drink viscosity that were strongly related to the actual viscosity of the drinks. In study two, the thick versions of the drink were expected to be more filling and have a greater expected satiety value, independent of the drink’s actual energy content. A creamy flavour enhanced the extent to which the drink was expected to be filling, but did not affect its expected satiety. Conclusions: These results indicate that subtle manipulations of texture and creamy flavour can increase expectations that a fruit yogurt drink will be filling and suppress hunger, irrespective of the drink’s energy content. A thicker texture enhanced expectations of satiety to a greater extent than a creamier flavour, and may be one way to improve the anticipated satiating value of energy-containing beverages

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Experimental study on water pipeline leak using in-pipe acoustic signal analysis and artificial neural network prediction

Water pipeline leakage is a common and significant global problem. In-pipe inspection based on hydrophone is one of the most direct, accurate, and reliable solutions for leak detection and recognition. In this study, a scheme of in-pipe detector was designed to pick up and identify acoustic signal due to leak. To investigate the characteristic of acoustic signal, an experimental platform was built to simulate the leaks and obtain acoustic signals under different leak conditions in an industrial scale water pipeline. Because a decreased pressure as leak has an unstable fluctuation in time domain, the frequency composition of the signal was analyzed in frequency domain, and then the change of frequency amplitude can be referenced to recognize the leaks. Moreover, the effects of leak size, pipeline pressure, and water flow rate on the characteristic of acoustic signal were investigated. The results show that the signal’s intensity under leak conditions are significantly higher than that of no leak case, and it will increase as the increased leak size; the signal intensity under no leak case will increase with the growth of pipeline pressure; the flow velocity has little effect on the signal intensity. To increase the recognition accuracy, an artificial neural network model was developed for the leak prediction, and 18 cases through additional tests were selected to validate the accuracy of model. Comparing experimental and prediction results, maximum relative error is within 10.0%. It indicates that the prediction model has a reasonable accuracy for the leak recognition

New pregnane saponins from Ecdysanthera rosea and their cytotoxicity

National Natural Science Foundation [30860037, 20872148]; Department of Science and Technology in Yunnan Province [20080A007]Two new pregnane saponins elucidated as ecdysantheroside A (1) and ecdysantheroside B (2) and six known compounds (3-8) based on spectral data (MS, IR, 1D and 2D NMR) were isolated from the stem bark of Ecdysanthera rosea. The cytotoxicity against six cell lines of these compounds was tested by MTT assay. The results revealed that compounds 5 and 7 showed cytotoxicity against all the cell lines. Compound 2 showed cytotoxicity against cells A549, MDA435, HepG2, and HUVEC, while compound 4 showed cytotoxicity against cells A549, CEM, and HUVEC. Compound 6 had cytotoxicity against the others except cell HepG2. (C) 2011 Elsevier B.V. All rights reserved