Detection of Borreliae in Archived Sera from Patients with Clinically Suspect Lyme Disease

The diagnoses of Lyme disease based on clinical manifestations, serological findings and detection of infectious agents often contradict each other. We tested 52 blind-coded serum samples, including 20 pre-treatment and 12 post-treatment sera from clinically suspect Lyme disease patients, for the presence of residual Lyme disease infectious agents, using nested PCR amplification of a signature segment of the borrelial 16S ribosomal RNA gene for detection and direct DNA sequencing of the PCR amplicon for molecular validation. These archived sera were split from the samples drawn for the 2-tier serology tests performed by a CDC-approved laboratory, and are used as reference materials for evaluating new diagnostic reagents. Of the 12 post-treatment serum samples, we found DNA evidence of a novel borrelia of uncertain significance in one, which was also positive for the 2-tier serology test. The rest of the post-treatment sera and all 20 control sera were PCR-negative. Of the 20 pre-treatment sera from clinically suspect early Lyme disease patients, we found Borrelia miyamotoi in one which was 2-tier serology-negative, and a Borrelia burgdorferi in two—one negative and one positive for 2-tier serology. We conclude that a sensitive and reliable DNA-based test is needed to support the diagnosis of Lyme disease and Lyme disease-like borreliosis.     

Advances in photobioreactors for intensive microalgal production: configurations,operating strategies and applications

Over the past ten years a great deal of literature has focused on the biotechnological potential of microalgal commercial applications, mainly in the field of biofuel production. However, the biofuel production is not yet competitive, mainly due to the incidence of the photobioreactor technology on the process cost. Besides, major advances in classic photobioreactor design, several novel configurations have been proposed in the last 20 years to improve their performance expressed in terms of light absorption, biomass productivity, light to biomass yield and photosynthetic efficiency. This review aims at analyzing and classifying the most recent advances and the several novel approaches to the design, development, control and modeling of photobioreactors. The diverse approaches are grouped considering irradiance strategies, multiphase hydrodynamics, mass transfer mechanisms, modeling approaches and control strategies. Some innovative applications of the photobioreactor technology are also reported. © 2013 Society of Chemical Industry     

多特征融合的兴趣点推荐算法

基于位置社交网络的兴趣点推荐越来越受到工业界和学术界的关注。由于用户签到数据集的稀疏性以及签到地理位置的聚集性，使得目前的推荐算法效率普遍不高，特别是当用户外出到新的地点时，推荐效果更是急剧下降。因此本文提出了一种基于用户-区域-内容主题的多特征联合推荐算法（UCRTM），以隐主题模型为基础，在统一的框架下利用隐含因子关联性融合了用户的偏好、兴趣点的内容以及兴趣点所属地理区域主题等信息来进行推荐，使得用户无论身处何地，都能获得理想的推荐服务。本文在两种真实的数据集上进行了实验，结果表明该方法不仅能够克服数据的稀疏性以及弱语义性等问题，而且与其他方法相比具有更高的推荐准确率。     

A New Time-Aware Collaborative Filtering Intelligent Recommendation System

Aiming at the problem that the traditional collaborative filtering recommendation algorithm does not fully consider the influence of correlation between projects on recommendation accuracy, this paper introduces project attribute fuzzy matrix, measures the project relevance through fuzzy clustering method, and classifies all project attributes. Then, the weight of the project relevance is introduced in the user similarity calculation, so that the nearest neighbor search is more accurate. In the prediction scoring section, considering the change of user interest with time, it is proposed to use the time weighting function to improve the influence of the time effect of the evaluation, so that the newer evaluation information in the system has a relatively large weight. The experimental results show that the improved algorithm improves the recommendation accuracy and improves the recommendation quality.     

BGNN: Behavior-aware graph neural network for heterogeneous session-based recommendation

Session-based recommendation (SBR) and multi-behavior recommendation (MBR) are both important problems and have attracted the attention of many researchers and practitioners. Different from SBR that solely uses one single type of behavior sequences and MBR that neglects sequential dynamics, heterogeneous SBR (HSBR) that exploits different types of behavioral information (e.g., examinations like clicks or browses, purchases, adds-to-carts and adds-to-favorites) in sequences is more consistent with real-world recommendation scenarios, but it is rarely studied. Early efforts towards HSBR focus on distinguishing different types of behaviors or exploiting homogeneous behavior transitions in a sequence with the same type of behaviors. However, all the existing solutions for HSBR do not exploit the rich heterogeneous behavior transitions in an explicit way and thus may fail to capture the semantic relations between different types of behaviors. However, all the existing solutions for HSBR do not model the rich heterogeneous behavior transitions in the form of graphs and thus may fail to capture the semantic relations between different types of behaviors. The limitation hinders the development of HSBR and results in unsatisfactory performance. As a response, we propose a novel behavior-aware graph neural network (BGNN) for HSBR. Our BGNN adopts a dual-channel learning strategy for differentiated modeling of two different types of behavior sequences in a session. Moreover, our BGNN integrates the information of both homogeneous behavior transitions and heterogeneous behavior transitions in a unified way. We then conduct extensive empirical studies on three real-world datasets, and find that our BGNN outperforms the best baseline by 21.87%, 18.49%, and 37.16% on average correspondingly. A series of further experiments and visualization studies demonstrate the rationality and effectiveness of our BGNN. An exploratory study on extending our BGNN to handle more than two types of behaviors show that our BGNN can easily and effectively be extended to multi-behavior scenarios.     

基于广义Choquet积分的职位推荐算法

为解决传统职位推荐算法推荐结果范围小,无法对跨行就业率高的人群进行有效推荐的问题,提出基于人口统计学数据及广义Choquet积分的职位推荐算法。利用层次分析法构建用户信息层次结构模型,结合广义Shapley函数与离散Choquet积分,通过计算最优相似人群进行职位推荐。与传统模型实验对比,推荐模型在雷达招聘网站提供的数据集上准确率提高了8.35%,有效验证了其可行性和有效性。     

Bitumen cracking using liquid injection

Uniform distribution of liquid feed on fluidzed bed increase yield on valuable of products and improves operability in the process of fluid coking, and it is of crucial improtance to optimize the contact between the injected liquid and the bed solids. The moisture in fluidized bed is divided into three groups: (a) free moisture, (b) microagglomerates, and (c) macroagglomerates. The goal of this study was to develop a rapid and reliable experimental technique to assess the liquid-solid contact efficiency resulting from the injection of gas-atomized liquid feed. Immediately after the injection of liquid through an atomization nozzle, the triboelectric charges accumulated on the particles migrated to a grounded electrode through the paths offered by the conductive liquid. The methods based on the in situ measurements of the bed conductance varies with time, therefore, use to detect the liquid distribution on different agglomerates, and the air-liquid ratio effect of nozzle is also presented.     

Nutrient Recommendations for Growing-up Milk: A Report of an Expert Panel

Utilization of expert recommendations in the development of food and beverage nutritional profiles represents an opportunity to merge science and food manufacturing to deliver nutritionally optimized products into the marketplace. This report details expert panel guidelines for the design of a nutritional product for children one to six years of age. This interaction demonstrates the essential synergy between academia and food manufacturers in translating nutrient recommendations to food for their delivery to a population. Important factors for such translation are the identification of applicable nutrient recommendations and selection of an appropriate delivery matrix. This report demonstrates the translation of expert nutritional recommendations to a milk-based product for children—one to six years of age.     

Suitability,efficiency and microbiological safety of novel physical technologies for the processing of ready‐to‐eat meals,meats and pumpable products

Consumer studies and market reports show an increase in consumption of ready‐to‐eat (RTE) foods. Although conventional processing technologies can in most cases produce safe products, they can also lead to the degradation of nutritional compounds and negatively affect quality characteristics. Consumers strongly prefer food that is minimally processed with the maximum amount of health‐promoting substances. Novel processing technologies as pre‐ or post‐treatment decontamination methods or as substitutes of conventional technologies have the potential to produce foods that are safe, rich in nutrient content and with superior organoleptic properties. Combining novel with conventional processes can eliminate potential drawbacks of novel technologies. This review examines available scientific information and critically evaluates the suitability and efficiency of various novel thermal and nonthermal technologies in terms of microbial safety, quality as well as nutrient content on the production of RTE meals, meats and pumpable products.     

Novel Bi-Doped Amorphous SnOx Nanoshells for Efficient Electrochemical CO2 Reduction into Formate at Low Overpotentials

Engineering novel Sn-based bimetallic materials could provide intriguing catalytic properties to boost the electrochemical CO₂ reduction. Herein, the first synthesis of homogeneous Sn_1−xBi_x alloy nanoparticles (x up to 0.20) with native Bi-doped amorphous SnO_x shells for efficient CO₂ reduction is reported. The Bi-SnO_x nanoshells boost the production of formate with high Faradaic efficiencies (>90%) over a wide potential window (−0.67 to −0.92 V vs RHE) with low overpotentials, outperforming current tin oxide catalysts. The state-of-the-art Bi-SnO_x nanoshells derived from Sn_0.80Bi_0.20 alloy nanoparticles exhibit a great partial current density of 74.6 mA cm⁻² and high Faradaic efficiency of 95.8%. The detailed electrocatalytic analyses and corresponding density functional theory calculations simultaneously reveal that the incorporation of Bi atoms into Sn species facilitates formate production by suppressing the formation of H₂ and CO.