注浆覆岩离层力学机理及其离层发育分类研究

依据覆岩离层生成的力学机理,结合煤层开采程度的不同,将可注浆层位的离层划分为三类.以岩石的应变为指标,确立了覆岩离层可注浆层位岩梁的断裂步距表达式,理论上证明了划分注浆层位的合理性.根据岩石的全应力应变试验,结合现场实际观测数据,对以应变为指标的岩梁断裂步距表达式做了初步验证.结果表明:可注浆层位的分类和断裂步距表达式的确定对注浆减沉工程具有指导意义.     

Improved customer choice predictions using ensemble methods

In this paper various ensemble learning methods from machine learning and statistics are considered and applied to the customer choice modeling problem. The application of ensemble learning usually improves the prediction quality of flexible models like decision trees and thus leads to improved predictions. We give experimental results for two real-life marketing datasets using decision trees, ensemble versions of decision trees and the logistic regression model, which is a standard approach for this problem. The ensemble models are found to improve upon individual decision trees and outperform logistic regression.     

Design criteria for molecular mimics of fragments of the β-turn. 1. Cα atom analysis

Peptides represent an extensive class of biologically active molecules. They may be used as leads in the development of novel therapeutic agents provided the pharmacophoric information present within them can be translated into non-peptide analogs that lack the peptide backbone and are stable to proteolysis. This is the rationale for peptidomimetic drug design. Frequently, the -turn has been implicated as a conformation important for biological recognition of peptides. Empirical evidence from known peptidomimetics, coupled with a theoretical model of peptide binding and the observation that glycine and proline residues are common within the -turn, has suggested the design of molecules to mimic placement of between two and four of the side-chains. The moderate number of different -turn conformations, combined with the combinatoric nature of side-chain selection complicates the procedure. In this paper, cluster analysis has been used to classify the arrangement of C_{_} atoms about the various fragments of the -turn. Recombination of the observed patterns provides a general model for the -turn which may be used as an effective screen for potential peptidomimetic scaffolds in chemical databases.     

An Analytical Method for the Separation and Determination of As(III) and As(V) in Seepage and Acid Mine Drainage Water

To avoid changes in the original As species distribution in natural water after sampling, a method of immediate separation of As(V) by anion exchange at the sampling site was developed. The procedure consists of two steps. The total concentration of arsenic is determined in one part of the water sample acidified on site. Another part of the water samples is pressed through a column filled with an anion exchanger. The As(III) species that is not redox-stable remains in the effluent of the sorbents column and can be analyzed with conventional methods after stabilization by addition of conc. HNO₃. As(V) is sorbed by the exchanger material. The As(V) concentration can be calculated as the difference between As_sol and As(III), neglecting very low contents of methylated species. Oxidation of Fe(II) by air followed by co-precipitation of arsenic with iron hydroxide was applied in field experiments to minimize the As concentration in seepage and mining water.     

Is Bitcoin’s Carbon Footprint Persistent? Multifractal Evidence and Policy Implications

The Bitcoin mining process is energy intensive, which can hamper the much-desired ecological balance. Given that the persistence of high levels of energy consumption of Bitcoin could have permanent policy implications, we examine the presence of long memory in the daily data of the Bitcoin Energy Consumption Index (BECI) (BECI upper bound, BECI lower bound, and BECI average) covering the period 25 February 2017 to 25 January 2022. Employing fractionally integrated GARCH (FIGARCH) and multifractal detrended fluctuation analysis (MFDFA) models to estimate the order of fractional integrating parameter and compute the Hurst exponent, which measures long memory, this study shows that distant series observations are strongly autocorrelated and long memory exists in most cases, although mean-reversion is observed at the first difference of the data series. Such evidence for the profound presence of long memory suggests the suitability of applying permanent policies regarding the use of alternate energy for mining; otherwise, transitory policy would quickly become obsolete. We also suggest the replacement of ‘proof-of-work’ with ‘proof-of-space’ or ‘proof-of-stake’, although with a trade-off (possible security breach) to reduce the carbon footprint, the implementation of direct tax on mining volume, or the mandatory use of carbon credits to restrict the environmental damage.     

基于模糊评价的学生综合素质挖掘方法

运用数据挖掘思想,运用模糊数学中的综合评判方法对学生信息管理系统中的学生成绩进行挖掘,得到学生综合素质分类,为教育管理中运用数据挖掘这一前沿信息技术提供了示例。     

关联规则增量式更新的改进算法

关联规则是数据挖掘中的重要研究内容之一，对在事务数据库不变，只对最小支持度和最小可信度进行改变的情况下，针对关联规则的维护问题，设计了一个增量式更新的改进算法AIUA。     

ToxML,a data exchange standard with content controlled vocabulary used to build better (Q)SAR models

Development of accurate quantitative structure–activity relationship (QSAR) models requires the availability of high quality validated data. International regulations such as REACH in Europe will now accept (Q)SAR-based evaluations for risk assessment. The number of toxicity datasets available for those wishing to share knowledge, or to use for data mining and modelling, is continually expanding. The challenge is the current use of a multitude of different data formats. The issues of comparing or combining disparate data apply both to public and proprietary sources. The ToxML project addresses the need for a common data exchange standard that allows the representation and communication of these data in a well-structured electronic format. It is an open standard based on Extensible Markup Language (XML). Supporting information for overall toxicity endpoint data can be included within ToxML files. This makes it possible to assess the quality and detail of the data used in a model. The data file model allows the aggregation of experimental data to the compound level in the detail needed to support (Q)SAR work. The standard is published on a website together with tools to view, edit and download it.     

Recent Advances in Discovery of Lead Structures from Microbial Natural Products: Genomics- and Metabolomics-Guided Acceleration

Natural products (NPs) are evolutionarily optimized as drug-like molecules and remain the most consistently successful source of drugs and drug leads. They offer major opportunities for finding novel lead structures that are active against a broad spectrum of assay targets, particularly those from secondary metabolites of microbial origin. Due to traditional discovery approaches’ limitations relying on untargeted screening methods, there is a growing trend to employ unconventional secondary metabolomics techniques. Aided by the more in-depth understanding of different biosynthetic pathways and the technological advancement in analytical instrumentation, the development of new methodologies provides an alternative that can accelerate discoveries of new lead-structures of natural origin. This present mini-review briefly discusses selected examples regarding advancements in bioinformatics and genomics (focusing on genome mining and metagenomics approaches), as well as bioanalytics (mass-spectrometry) towards the microbial NPs-based drug discovery and development. The selected recent discoveries from 2015 to 2020 are featured herein.     

基于MDARM和VxWorks的小型无人机执行器故障检测方法

由于目前在小型无人机执行器故障诊断中存在着智能化程度较低,容易受到人为因素干扰,从而出现故障漏检等问题,难以满足小型无人机对飞行安全的要求。为此,本文提出一种基于多维数据关联规则挖掘(Multidimensional Data Association Rules Mining: MDARM)和VxWorks操作系统的小型无人机执行器故障诊断方法,通过建立执行器内部传感器测量的温度、压力、流速、力矩等相关变量的历史数据库,并对这些数据进行预处理,以避免带来噪声污染,并利用可测量参数与不可测量参数之间的关联性,建立故障诊断知识库,避免了诊断过程中的人为因素干扰,实现小型无人机执行器故障的精准测量。实验结果证明,这种方法能够有效地提高故障准确率64.7%,对小型无人机执行器的智能诊提供有效指导,应用前景广阔。