Analysis on the spatial ecological distribution model of landscape plant community

Because the spatial pattern of plant communities in garden landscapes usually exhibits highly non-random distribution characteristics, the accuracy of the analysis results is not high. For this purpose, a spatial ecological distribution model of landscape landform plant communities is designed. Based on the remote sensing images of landscape plant communities, the study area was obtained. The grassland communities in this area were classified and calculated by geostatistics, and the semi variogram values of typical samples of different vegetation types were obtained. According to the calculation results, the spatial terrain factors of landscape plant community are extracted, and the annual NDVI value is taken as the ecological vitality index of landscape green vegetation, the NDVI level is divided, the spatial ecological distribution model of landscape plant community is constructed, and the evaluation index system is generated, so as to complete the spatial ecological distribution model analysis of landscape plant community. The results show that the method of this study accurately analyzes the area of coniferous and broad-leaved mixed forest, mountain meadow, road, construction land, water area land and slope grade, which is slightly different from the actual value, indicating that the method has certain reliability.     

Paradigm and performance analysis of distributed frequent itemset mining algorithms based on Mapreduce

FrequentItemsetMining (FIM) is one of the most important data mining tasks and is the foundation of many data mining tasks. In Big Data era, centralized FIM algorithms cannot meet the needs of FIM for big data in terms of time and space, so Distributed Frequent Itemset Mining (DFIM) algorithms have been designed to meet the above challenges. In this paper, LocalGlobal and RedistributionMining which are two main paradigms of DFIM algorithm are discussed; Two algorithms of these paradigms on MapReduce named LG and RM are proposed while MapReduce is a popular distributed computing model, and also the related work is discussed. The experimental results show that the RM algorithm has better performance in terms of computation and scalability of sites, and can be used as the basis for designing the DFIM algorithm based on MapReduce. This paper also discusses the main ideas of improving the DFIM algorithms based on MapReduce.     

Government ecological governance management based on heterogeneous multi-processors and dynamic image sampling

With the advent of the governance economy era, traditional government governance models face enormous challenges. Governance management is the source of power to enter the era of the knowledge economy. This is a profound change that governments have needed to implement innovative government governance models, methods of social organization, and management. Governments in many countries are now adopting the construction of e-government as a strategy and response to demonstrate their priority development competitive advantage over the international competition and the challenges of the knowledge economy that spreads around the world. Therefore, the establishment of a new model of government governance has great theoretical and practical significance for impulse and government management innovation. The Dynamic Image Classification Algorithm (DICA) system is introduced in the implementation of the image processing technology and global disaster detection proposed here, and of this dynamic image classification algorithm (DICA) of the government, sector to extract more effectively. DICA is the most important task, or it is a strong shadow, proper access to the characteristics of the disaster area, and a false impact on the impact of the disaster, overcoming false alarms. It creates patches of post-disaster aerial image data from pre-tailoring and pre-adjustment training and satellite imagery. DICA training, all patches to government-managed data modified without delay or image data extraction. Two types of proposed systems are high-speed operation and accuracy (96.6%) and detection of earth disasters.     

First macrocyclic oxamide Cu(II)–Co(II) complex: synthesis,crystal structure and magnetic properties

A oxamido-bridged binuclear complex, [Cu(L)Co(bpy)₂](ClO₄)₂·0.5C₂H₅OH·H₂O has been synthesized, and structurally and magnetically characterized, where L = 1,4,8,11- tetraazacyclotradecanne-2,3-dione and bpy = 2,2^′-bipyridine. In the complex, the copper atom from the macrocyclic oxamido-copper(II) precursor in a square-planar and cobalt atoms in a distorted octahedral environment is bridged by the oxamidate group, Cu⋯Co separation of 5.359 Å. The metal–metal separations are consistent with the sequence of decrease of the ion radius of the metal ion. The magnetic properties of the complex have been investigated. The χ_MT versus T plots is typical of antiferromagnetically coupled Cu(II)–Co(II).     

Green and ecological interior design based on network processor and embedded system

With the growing demand for interior design solutions that are friendly to the green environment, there is a growing awareness of interior designers around the world to the sustainability strategy. Most of the traditional interior design and construction process consumes many natural resources in the manufacturing and installation process. This will harm the environment. Interior designers adopted a sustainable design technology, the opportunity to improve the healthy indoor air quality. To achieve sustainable solutions, materials, construction methods, furniture by selecting the lighting design options. Despite much sustainable design research, discussion of the interior design of sustainability criteria there little. Essential for sustainable standard interior design solutions to support the responsible interior designer. Therefore, this study aims to propose a set of criteria for selecting based on sustainable indoor network processors and embedded system design solutions to ensure a sustainable and consistent product mix of 3DWeb representation of interior design solutions thing. Finally, to enhance its functionality, come to an end because of the importance of effective standards.     

Construction of an impedimetric immunosensor for label-free detecting carbofuran residual in agricultural and environmental samples

In this paper, a label-free electrochemical impedance immunosensor for the detection of carbofuran was prepared by immobilizing l-cysteine on a gold electrode. The carbofuran antibodies were immobilized on the electrode by the using glutaraldehyde as a cross linker. The stepwise assembly of the electrode surface was confirmed by atomic force microscope (AFM), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). Under the optimized conditions, a linear relationship between the resistance change and the logarithm value of carbofuran concentration was obtained in the carbofuran concentration range of 1.0 × 10⁻¹ – 1.0 × 10³ ng/mL, with a detection limit of 1.0 × 10⁻¹ ng/mL. The immunosensor performed good reproducibility and stability. Additionally, the proposed method can be applied for monitoring carbofuran residual in agricultural and environmental samples.     

多条件多样本RNA-Seq数据的剪切异构体表达水平估计

当处理多条件多样本RNA-Seq测序数据时,现有方法忽略了读段分布样本之间存在高度相似性的特点。本文提出了一个基于多条件多样本RNA-Seq测序数据剪切异构体表达水平估计方法MCMS-Seq。该方法建立了一个联合偏差估计模型来提取读段分布在样本之间的相似性特征,同时考虑读段分布受全局偏差和局部偏差的影响。此外,增加了 ${{{L_2}} / {{L_1}}}$ 组稀疏约束和 ${L_1}$ 稀疏约束两个正则化项,用来体现基因和剪切异构体之间存在稀疏特性,以及消除技术性误差和数据噪声的影响。通过多个真实数据集的验证,MCMS-Seq方法能获得更为准确的剪切异构体表达水平,同时也能提供更有意义的生物性解释。     

Research on security technology of automobile electronic communication based on genetic assessment

In the techno world, the Internet of Things (IoT) is a growing and advanced technology that has become an enormous base for employing in various applications of different genres, including smart vehicle infrastructure, by facilitating Internet connections. Because of the developing nature and the salient features of ensuring high-level road safety and security to optimize traffic management, vehicle networks have become a significant research field in the Intelligent Transportation System (ITS). With various benefits of ITS and IoT, the wireless device transfer connectivity raises the possibility of privacy violations, which may result in surveillance, deflection of identification, and the hijacking of virtual vehicles. Therefore, avoiding data security disputes for computing in the IoT-ITS remains a significant challenge. The IoT supported with Multiple-Objective Genetic Assessment (IoT-MOGA) helps to tackle this problem. The security of knowledge transparency for ITS is suggested in this article. The communication-based vehicle routing method is then configured to retrieve the vehicles from the initial automobile, where the device assignment is placed at the vehicle location. The goal is to improve the consumption of time and energy MOGA to decrease the accomplishing time and avoid conflicts in computer tasks’ privacy. Eventually, investigational assessments are required to demonstrate IoT-MOGA's performance and competitiveness.     

Autoinducer-2 associated inhibition by Lactobacillus sakei NR28 reduces virulence of enterohaemorrhagic Escherichia coli O157:H7

Bacteria use quorum sensing (QS) to regulate the expression of certain target genes for social behaviour. A LuxS/AI-2 signalling system serves to control the virulence of some pathogenic bacteria by mechanisms such as motility, biofilm formation and attachment, and is typical of the enterohaemorrhagic Escherichia coli O157:H7 (EHEC) associated with infections of the human intestine. The LuxS/AI-2 signalling system presents an interesting potential as antimicrobial target for appropriate AI-2 inhibitors, and thus widens the scope for treatment or prevention of infections by pathogens such as EHEC. Probiotic lactic acid bacteria (LAB) are primary candidates for this approach because of their general acceptability, safety and adaptation to the intestinal and/or food ecosystem. In this paper, we report on Lactobacillus sakei NR28 as a new candidate strain for AI-2 related quorum quenching. It is considered to be a putative probiotic strain and was originally isolated from kimchi, a traditional Korean fermented food known for its special health features. This study has shown that AI-2 activity and the associated virulence factors of the EHEC ‘wild-type’ strain E. coli ATCC 43894, were significantly reduced by L. sakei NR28, while, at the same time, the cell viability of the EHEC strain was not affected. In addition, the purified AI-2 molecule, a luxS-deficient mutant of EHEC strain ATCC 43894, and an AI-2 independent EHEC mimicking strain of Citrobacter rodentium were used to determine the relationship between the virulence reducing effect of L. sakei NR28 and its AI-2 inhibiting ability. Our results showed that L. sakei NR28 has a reducing effect on the pathogenicity of the ‘wild-type’ EHEC strain ATCC 43894 by AI-2 signalling inhibition.