Separation and Purification of Four Stilbenes from Vitis vinifera L. cv. Cabernet Sauvignon Roots Through High-speed Counter-current Chromatography

A method for preparative separation and purification of trans-resveratrol, δ-viniferin, ε-viniferin and trans-vitisin B from the roots of Vitis vinifera L. cv. Cabernet Sauvignon was successfully established and is reported on in this paper. The four important stilbenes were purified by high-speed counter-current chromatography (HSCCC) with a suitable quaternary solvent system composed of chloroform–methanol–n-butanol–water (4:3:0.05:2, v/v). A total of 7.1 mg ± 0.2 mg of trans-resveratrol, 1.1 mg ± 0.1 mg of δ-viniferin, 18.7 mg ± 0.5 mg of ε-viniferin, and 12.2 mg ± 0.2 mg of trans-vitisin B, with purities of 97.89%, 90.61%, 94.37% and 78.38% respectively, were obtained from 241 mg of crude sample in a one-step HSCCC separation. The chemical structures of trans-resveratrol and δ-viniferin were further confirmed with the retention time using the method of standard addition, while the structural identification of ε-viniferin and trans-vitisin B was performed with LC-ESI/MS, 1H-NMR, and 13C-NMR

Robust Transceiver Design for AF MIMO Relay Systems with Column Correlations

In this paper, we investigate the robust transceiver design for dual-hop amplify-and-forward (AF) MIMO relay systems with Gaussian distributed channel estimation errors. Aiming at maximizing the mutual information under imperfect channel state information (CSI), source precoder at source and forwarding matrix at the relay are jointly optimized. Using some elegant attributes of matrix-monotone functions, the structures of the optimal solutions are derived first. Then based on the derived structure an iterative waterfilling solution is proposed. Several existing algorithms are shown to be special cases of the proposed solution. Finally, the effectiveness of the proposed robust design is demonstrated by simulation results.Comment: 6 Pages, 1 Figur

Modeling Count Outcomes from HIV Risk Reduction Interventions: A Comparison of Competing Statistical Models for Count Responses

Modeling count data from sexual behavioral outcomes involves many challenges, especially when the data exhibit a preponderance of zeros and overdispersion. In particular, the popular Poisson log-linear model is not appropriate for modeling such outcomes. Although alternatives exist for addressing both issues, they are not widely and effectively used in sex health research, especially in HIV prevention intervention and related studies. In this paper, we discuss how to analyze count outcomes distributed with excess of zeros and overdispersion and introduce appropriate model-fit indices for comparing the performance of competing models, using data from a real study on HIV prevention intervention. The in-depth look at these common issues arising from studies involving behavioral outcomes will promote sound statistical analyses and facilitate research in this and other related areas

Design of Sail-Assisted Unmanned Surface Vehicle Intelligent Control System

To achieve the wind sail-assisted function of the unmanned surface vehicle (USV), this work focuses on the design problems of the sail-assisted USV intelligent control systems (SUICS) and illustrates the implementation process of the SUICS. The SUICS consists of the communication system, the sensor system, the PC platform, and the lower machine platform. To make full use of the wind energy, in the SUICS, we propose the sail angle of attack automatic adjustment (Sail_4A) algorithm and present the realization flow for each subsystem of the SUICS. By using the test boat, the design and implementation of the SUICS are fulfilled systematically. Experiments verify the performance and effectiveness of our SUICS. The SUICS enhances the intelligent utility of sustainable wind energy for the sail-assisted USV significantly and plays a vital role in shipping energy-saving emission reduction requirements issued by International Maritime Organization (IMO)

vFitness: a web-based computing tool for improving estimation of in vitro HIV-1 fitness experiments

<p>Abstract</p> <p>Background</p> <p>The replication rate (or fitness) between viral variants has been investigated <it>in vivo </it>and <it>in vitro </it>for human immunodeficiency virus (HIV). HIV fitness plays an important role in the development and persistence of drug resistance. The accurate estimation of viral fitness relies on complicated computations based on statistical methods. This calls for tools that are easy to access and intuitive to use for various experiments of viral fitness.</p> <p>Results</p> <p>Based on a mathematical model and several statistical methods (least-squares approach and measurement error models), a Web-based computing tool has been developed for improving estimation of virus fitness in growth competition assays of human immunodeficiency virus type 1 (HIV-1).</p> <p>Conclusions</p> <p>Unlike the two-point calculation used in previous studies, the estimation here uses linear regression methods with all observed data in the competition experiment to more accurately estimate relative viral fitness parameters. The dilution factor is introduced for making the computational tool more flexible to accommodate various experimental conditions. This Web-based tool is implemented in C# language with Microsoft ASP.NET, and is publicly available on the Web at <url>http://bis.urmc.rochester.edu/vFitness/</url>.</p

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives