基于个性化推荐系统的视频App的设计

近年来,各类视频应用上内容越来越丰富,页面上与当前用户无关的内容也越来越多。因此,市面上出现了多种不同的推荐算法来进行内容推荐。但是,不是每种推荐算法都能够解决所有的问题。基于个性化推荐系统的视频App,融合了多种推荐方法。首先为了解决推荐系统的冷启动问题,采用了基于统计学的推荐方式,同时,采用基于协同过滤的推荐算法,计算视频和用户间的隐藏特征,最后还有实时推荐模块,能够根据用户近期的行为对推荐内容进行调整。     

Floodplain roughness parameterization using airborne laser scanning and spectral remote sensing

Floodplain roughness parameterization is one of the key elements of hydrodynamic modeling of river flow, which is directly linked to exceedance levels of the embankments of lowland fluvial areas. The present way of roughness mapping is based on manually delineated floodplain vegetation types, schematized as cylindrical elements of which the height (m) and the vertical density (the projected plant area in the direction of the flow per unit volume, m^− 1) have to be assigned using a lookup table. This paper presents a novel method of automated roughness parameterization. It delivers a spatially distributed roughness parameterization in an entire floodplain by fusion of CASI multispectral data with airborne laser scanning (ALS) data. The method consists of three stages: (1) pre-processing of the raw data, (2) image segmentation of the fused data set and classification into the dominant land cover classes (KHAT = 0.78), (3) determination of hydrodynamic roughness characteristics for each land cover class separately. In stage three, a lookup table provides numerical values that enable roughness calculation for the classes water, sand, paved area, meadows and built-up area. For forest and herbaceous vegetation, ALS data enable spatially detailed analysis of vegetation height and density. The hydrodynamic vegetation density of forest is mapped using a calibrated regression model. Herbaceous vegetation cover is further subdivided in single trees and non-woody vegetation. Single trees were delineated using a novel iterative cluster merging method, and their height is predicted (R² = 0.41, rse = 0.84 m). The vegetation density of single trees was determined in an identical way as for forest. Vegetation height and density of non-woody herbaceous vegetation were also determined using calibrated regression models. A 2D hydrodynamic model was applied with the results of this novel method, and compared with a traditional roughness parameterization approach. The modeling results showed that the new method is well able to provide accurate output data. The new method provides a faster, repeatable, and more accurate way of obtaining floodplain roughness, which enables regular updating of river flow models.     

Overview of the potent cyanobacterial neurotoxin β-methylamino-L-alanine (BMAA) and its analytical determination

Blue-green algae are responsible for the production of different types of toxins which can be neurotoxic, hepatotoxic, cytotoxic and dermatotoxic and that can affect both aquatic and terrestrial life. Since its discovery the neurotoxin β-methylamino-L-alanine (BMAA) has been a cause for concern, being associated with the neurodegenerative disease amyotrophic lateral sclerosis/Parkinsonism–dementia complex (ALS/PDC). The initial focus was on Guam where it was observed that a high number of people were affected by the ALS/PDC complex. Subsequently, researchers were surprised to find levels of BMAA in post mortem brains from Canadian patients who also suffered from ALS/PDC. Recent research demonstrates that BMAA has been found at different levels in the aquatic food web in the brackish waters of the Baltic Sea. There is emerging evidence to suggest that sand-borne algae from Qatar can also contain BMAA. Furthermore, there is now concern because BMAA has been found not only in warmer regions of the world but also in temperate regions like Europe. The aim of this review is to focus on the methods of extraction and analysis of the neurotoxic non-protein amino acid BMAA. We also consider the neurotoxicity, aetiology, and diverse sources and routes of exposure to BMAA. In recent years, different methods have been developed for the analysis of BMAA. Some of these use HPLC-FD, UPLC-UV, UPLC-MS and LC-MS/MS using samples that have been derivatised or underivatised. To date the LC-MS/MS approach is the most widely used analytical technique as it is the most selective and sensitive method for BMAA determination.     

Extended HALS algorithm for nonnegative Tucker decomposition and its applications for multiway analysis and classification

Analysis of high dimensional data in modern applications, such as neuroscience, text mining, spectral analysis, chemometrices naturally requires tensor decomposition methods. The Tucker decompositions allow us to extract hidden factors (component matrices) with different dimension in each mode, and investigate interactions among various modalities. The alternating least squares (ALS) algorithms have been confirmed effective and efficient in most of tensor decompositions, especially Tucker with orthogonality constraints. However, for nonnegative Tucker decomposition (NTD), standard ALS algorithms suffer from unstable convergence properties, demand high computational cost for large scale problems due to matrix inverse, and often return suboptimal solutions. Moreover they are quite sensitive with respect to noise, and can be relatively slow in the special case when data are nearly collinear. In this paper, we propose a new algorithm for nonnegative Tucker decomposition based on constrained minimization of a set of local cost functions and hierarchical alternating least squares (HALS). The developed NTD-HALS algorithm sequentially updates components, hence avoids matrix inverse, and is suitable for large-scale problems. The proposed algorithm is also regularized with additional constraint terms such as sparseness, orthogonality, smoothness, and especially discriminant. Extensive experiments confirm the validity and higher performance of the developed algorithm in comparison with other existing algorithms.     

Role of the Ubiquitin System in Stress Granule Metabolism

Eukaryotic cells react to various stress conditions with the rapid formation of membrane-less organelles called stress granules (SGs). SGs form by multivalent interactions between RNAs and RNA-binding proteins and are believed to protect stalled translation initiation complexes from stress-induced degradation. SGs contain hundreds of different mRNAs and proteins, and their assembly and disassembly are tightly controlled by post-translational modifications. The ubiquitin system, which mediates the covalent modification of target proteins with the small protein ubiquitin (‘ubiquitylation’), has been implicated in different aspects of SG metabolism, but specific functions in SG turnover have only recently emerged. Here, we summarize the evidence for the presence of ubiquitylated proteins at SGs, review the functions of different components of the ubiquitin system in SG formation and clearance, and discuss the link between perturbed SG clearance and the pathogenesis of neurodegenerative disorders. We conclude that the ubiquitin system plays an important, medically relevant role in SG biology.     

MPEG-4音频压缩技术的新进展--ALS

在语音信号处理的许多应用中,采用了无损音频压缩的方法.回顾了MPEG-4音频技术的现状,MPEG-4 ALS(Audio Lossless Coding)标准化过程以及编解码技术.详细介绍了编码器中的线性预测、量化、熵编码等模块,展望了MPEG-4 ALS的应用前景.     

高清晰度录像机

高清晰度录像机有希望广泛地应用于高清晰度电视系统。目前，模拟式和数字式高清晰度录像机已经开发出来并被使用。家庭用高清晰度录像机也已开发出来并将商品化。     

甲磺隆对水华鱼腥藻作用机理初探

以水华鱼腥藻的乙酰乳酸合成酶（ALS）比活力作为研究对象,通过在离体和活体条件下比较其对甲磺隆的敏感性,探讨了甲磺隆对水华鱼腥藻的作用机理.结果表明：离体条件下,甲磺隆对水华鱼腥藻ALS抑制强烈,且浓度越高抑制作用越强,其IC50=0.026mg/L;活体条件下,当甲磺隆的浓度为0.001mg/L时,甲磺隆对水华鱼腥藻ALS几乎没有抑制作用,这可能是甲磺隆在水华鱼腥藻体内被降解失活的缘故.当甲磺隆的浓度为0.01～10mg/L时,甲磺隆对水华鱼腥藻ALS抑制与离体条件下的抑制作用基本一样,其IC50=0.714mg/L.     

Cyanobacteria,Cyanotoxins, and Neurodegenerative Diseases: Dangerous Liaisons

The prevalence of neurodegenerative disease (ND) is increasing, partly owing to extensions in lifespan, with a larger percentage of members living to an older age, but the ND aetiology and pathogenesis are not fully understood, and effective treatments are still lacking. Neurodegenerative diseases such as Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis are generally thought to progress as a consequence of genetic susceptibility and environmental influences. Up to now, several environmental triggers have been associated with NDs, and recent studies suggest that some cyanotoxins, produced by cyanobacteria and acting through a variety of molecular mechanisms, are highly neurotoxic, although their roles in neuropathy and particularly in NDs are still controversial. In this review, we summarize the most relevant and recent evidence that points at cyanotoxins as environmental triggers in NDs development.