天津市正常人全血和血清微量元素含量分析

人体内微量元素含量平衡与否与人体健康状态有着密切关系已为大量实践所证实。人体血液中微量元素的正常值测定是研究人体健康与微量元素关系的一项基础性工作,本文提供了天津市正常人全血及血清中几种微量元素含量的数据。     

Synthesis and biological activities of phenyl piperazine-based peptidomimetic growth hormone secretagogues

A new class of potent, orally active phenyl piperazine-based GH secretagogues have been discovered from attempts to mimic the arrangement of the phenyl substituent in the spiroindanyl piperidine and spiroindoline sulfonamide privileged structures of 4 and 1, respectively. The best of these compounds, 18 (EC50 = 2.8 nM) is nearly as potent as MK-0677 for releasing GH from rat pituitary cells.     

Calcium-sensitive fluorescent dyes can report increases in intracellular free zinc concentration in cultured forebrain neurons

High concentrations of Zn2+ are found in presynaptic terminals of excitatory neurons in the CNS. Zn2+ can be released during synaptic activity and modulate postsynaptic receptors, but little is known about the possibility that Zn2+ may enter postsynaptic cells and produce dynamic changes in the intracellular Zn2+ concentration ([Zn2+]i). We used fura-2 and magfura-2 to detect the consequences of Zn2+ influx in cultured neurons under conditions that restrict changes in intracellular Ca2+ and Mg2+ concentrations. The resulting ratio changes for both dyes were reversed completely by the Zn2+ chelator, N,N,N',N'-tetrakis(2-pyridylmethyl)ethylenediamine, indicating that these dyes are measuring changes in [Zn2+]i. We found that fura-2 was useful in measuring small increases in [Zn2+]i associated with exposure to Zn2+ alone that may be mediated by a Na+/Ca2+ exchanger. Magfura-2, which has a lower affinity for Zn2+, was more useful in measuring larger agonist-stimulated increases in [Zn2+]i. The coapplication of 300 microM Zn2+ and 100 microM glutamate/10 microM glycine resulted in a [Zn2+]i increase that was approximately 40-100 nM in magnitude and could be inhibited by the NMDA receptor antagonist, MK-801 (30 microM), or extracellular Na+. This suggests that Zn2+ influx can occur through at least two different pathways, leading to varying increases in [Zn2+]i. These findings demonstrate the feasibility of measuring changes in [Zn2+]i in neurons.     

Pre-bainitic Transformation in Fe-Ni Alloy

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Characterization of arylamine N-acetyltransferase in Enterobacter aerogenes

N-acetyltransferase (NAT) activity was determined by incubation of purified Enterobacter aerogenes enzyme with 2-aminofluorene (2-AF) as the substrate, followed by high pressure liquid chromatography assays. The NAT activity from E. aerogenes was 0.58 +/- 0.08 nmol/min/mg protein for 2-AF. The values of apparent K(m) and Vmax were 0.72 +/- 0.14 mM and 2.45 +/- 0.29 nmol/min/mg protein, respectively, for 2-AF. The optimal pH value for the enzyme activity was 7.5 for the 2-AF tested. The optimal temperature for enzyme activity was 37 degrees C for the 2-AF substrate. The molecular weight of NAT from E. aerogenes was 44.9 kD. Among a series of divalent cations and salts, Zn2+, Ca2+, and Fe2+ were demonstrated to be the most potent protease inhibitors, and only ethylenediaminetetraacetic acid significantly protected the NAT. Iodoacetamide, in contrast to other agents, markedly inhibited NAT.     

基于仿人足球机器人协作定位技术研究

本文综述多机器人协作定位的研究现状,分析比较当前该领域的主要研究方向,介绍实现机器人协作定位的主要研究方法和关键技术,并总结多机器人协作定位面临的挑战和发展趋势.     

HAR-sEMG: A Dataset for Human Activity Recognition on Lower-Limb sEMG

Knowledge and Information Systems - In the past decade, human activity recognition (HAR) has grown in popularity due to its applications in security and entertainment. As recent years have...     

CoGCN: Combining co‐attention with graph convolutional network for entity linking with knowledge graphs

Entity linking is a fundamental task in natural language processing. The task of entity linking with knowledge graphs aims at linking mentions in text to their correct entities in a knowledge graph like DBpedia or YAGO2. Most of existing methods rely on hand‐designed features to model the contexts of mentions and entities, which are sparse and hard to calibrate. In this paper, we present a neural model that first combines co‐attention mechanism with graph convolutional network for entity linking with knowledge graphs, which extracts features of mentions and entities from their contexts automatically. Specifically, given the context of a mention and one of its candidate entities' context, we introduce the co‐attention mechanism to learn the relatedness between the mention context and the candidate entity context, and build the mention representation in consideration of such relatedness. Moreover, we propose a context‐aware graph convolutional network for entity representation, which takes both the graph structure of the candidate entity and its relatedness with the mention context into consideration. Experimental results show that our model consistently outperforms the baseline methods on five widely used datasets.     

Differential Evolution Algorithm Based Self-adaptive Control Strategy for Fed-batch Cultivation of Yeast

In the fed-batch cultivation of Saccharomyces cerevisiae, excessive glucose addition leads to increased ethanol accumulation, which will reduce the efficiency of glucose utilization and inhibit product synthesis. Insufficient glucose addition limits cell growth. To properly regulate glucose feed, a different evolution algorithm based on self-adaptive control strategy was proposed, consisting of three modules (PID, system identification and parameter optimization). Performance of the proposed and conventional PID controllers was validated and compared in simulated and experimental cultivations. In the simulation, cultivation with the self-adaptive control strategy had a more stable glucose feed rate and concentration, more stable ethanol concentration around the set-point (1.0 g•L^-1), and final biomass concentration of 34.5 g-DCW•L^-1, 29.2% higher than that with a conventional PID control strategy. In the experiment, the cultivation with the self-adaptive control strategy also had more stable glucose and ethanol concentrations, as well as a final biomass concentration that was 37.4% higher than that using the conventional strategy.     

Scheduling Optimization Modelling: A Case Study of a Woven Label Manufacturing Company

Production scheduling involves all activities of building production schedules, including coordinating and assigning activities to each person, group of people, or machine and arranging work orders in each workplace. Production scheduling must solve all problems such as minimizing customer wait time, storage costs, and production time; and effectively using the enterprise’s human resources. This paper studies the application of flexible job shop modelling on scheduling a woven labelling process. The labelling process includes several steps which are handled in different work-stations. Each workstation is also comprised of several identical parallel machines. In this study, job splitting is allowed so that the power of work stations can be utilized better. The final objective is to minimize the total completion time of all jobs. The results show a significant improvement since the new planning may save more than 60% of lead time compared to the current schedule. The contribution of this research is to propose a flexible job shop model for scheduling a woven labelling process. The proposed approach can also be applied to support complex production scheduling processes under fuzzy environments in different industries. A practical case study demonstrates the effectiveness of the proposed model.