Powerful Mining Research Articles

Integration of Genomics into Rice Breeding

Abstract One of the major challenges in genetics has been to identify the nucleotide polymorphisms responsible for phenotypic variation. Through intensive analysis, several major quantitative trait loci (QTLs) for agronomic traits in rice have been identified and the underlying candidate genes have been delimited. Advanced mapping populations, including chromosome segment substitution lines, have enhanced the power of genetic analysis to detect QTL alleles, even those with minor effects. Recent examples of marker-assisted selection have proven the potential of this strategy for crop improvement. The genome-wide discovery of single nucleotide polymorphisms (SNPs), even among closely related cultivars, has enhanced the power of allele mining in a wide range of rice breeding materials. An array-based SNP genotyping system can be used to visualize pedigree haplotypes in breeding materials, including landraces and modern cultivars. All of these technologies are accelerating the genetic dissection of complex agronomic traits and further improvement of rice.

Lag compensation errors in active power filters based on DSP controllers

The growing problems of harmonic pollution on coal mine power lines caused by high-power DC drive systems has increased the use of active power filters. We analyzed compensation errors caused by the time lag in the detecting circuits of an active power filter based on DSP control. We derived a mathematical model for the compensation error starting from the error estimation when a single distortion frequency is present. This model was then extended to the case where multiple frequencies are present in the distortion. A formula for a general theory of compensation error with fixed load and fixed lag time is presented. The theoretical analysis and experimental results show that the delay time of an active power filter mainly arises from the sampling time. Lower sampling frequencies introduce larger compensation errors in the active power filter reference current.

The effect of quality and reserves uncertainty to production scheduling of a lignite mine feeding a power plant

The effect of uncertainty sources to the stochastic optimization of the combined project of a new surface lignite mine exploitation and power plant operation for electricity generation is investigated. Major sources of uncertainty that were considered are the reserves and the quality of the lignite. Since probability distribution functions for these uncertainties were estimated during the detailed exploration phase of the deposit, the overall goal is then to determine the optimal capacity of the power plant and consequently the optimal production rate of the mine over the time. The optimization objective that was selected is the maximization of the expected net present value of the project. Emphasis is placed on the mathematical analysis applied for the investigation of the effect of the two main parameters in project optimization.

Study on Improved Neural Network PID Control for Coal Mining Power Grid Arc Suppression Coil Compensating System

The paper analyzed arc suppression coil with magnetic bias compensating system with linear system rules. The nonlinear and time-variable performances are considered during model building process. In order to optimize control effect, the paper adopted improved BP neural network PID controller with closed loop control method. Improve BP neural network with the combination of the two strategies, adding momentum method and adaptive learning rate adjustment, can not only effectively suppress the network appearing local minimum but also good to shorten learning time and improve stability of the network furthermore. The results of simulation and experiments indicate that arc suppression coil based on improved neural network with PID control method can quickly and accurately control the compensating capacitive current to an expected value and it has strong robustness. The paper also provided core controller with software and hardware designing scheme based on STM32 microcontroller.

Systematic study of protein sumoylation: Development of a site-specific predictor of SUMOsp 2.0.

Protein sumoylation is an important reversible post-translational modification on proteins, and orchestrates a variety of cellular processes. Recently, computational prediction of sumoylation sites has attracted much attention for its cost-efficiency and power in genomic data mining. In this work, we developed SUMOsp 2.0, an accurate computing program with an improved group-based phosphorylation scoring algorithm. Our analysis demonstrated that SUMOsp 2.0 has greater prediction accuracy than SUMOsp 1.0 and other existing tools, with a sensitivity of 88.17% and a specificity of 92.69% under the medium threshold. Previously, several large-scale experiments have identified a list of potential sumoylated substrates in Saccharomyces cerevisiae and Homo sapiens; however, the exact sumoylation sites in most of these proteins remain elusive. We have predicted potential sumoylation sites in these proteins using SUMOsp 2.0, which provides a great resource for researchers and an outline for further mechanistic studies of sumoylation in cellular plasticity and dynamics. The online service and local packages of SUMOsp 2.0 are freely available at: http://sumosp.biocuckoo.org/.

Industries and lung cancer: A population-based case-control study in British Columbia

An investigation was conducted to identify high-risk industries for histological subtypes of lung cancer based on a large population-based case-control study in British Columbia, Canada. Occupational histories and information on smoking and relevant covariates were collected from 14,755 male incident cancer cases. Industrial risk factors for 2998 lung cancer cases, including histological subtypes were assessed by logistic regression using other cancer cases, excluding smoking-related cancers, as controls. An excess risk of lung cancer was found among workers in mining, metal manufacturing, and electric power systems for all histological-subtypes, and construction, water transport, health services for specific histological subtypes. Industrial associations that are unique to histological subtypes of lung cancer were identified. Future research needs to focus on confirming these histological associations, and identifying the risk from key exposures found within these industries (e.g. medical radiation, electromagnetic fields, and cooking fumes).

From Scotia to Brookwood, fatal US underground coal mine explosions ignited in intake air courses

The National Institute for Occupational Safety and Health, Pittsburgh Research Laboratory, conducted a study of past mine explosions to identify the ignition locations and ignition sources responsible for the most severe explosion events resulting in death. Since the Scotia disaster of 1976, many fatalities from underground coal mine explosions have been linked to nonpermissible electrical equipment ignition sources located in intake air courses. With few exceptions, explosion protected equipment is generally not required in intake air courses of gassy underground coal mines in the US. Cigarette lighters were another prevalent ignition source for fatal explosions ignited in intake air courses. Several mine rescue/recovery teams have encountered electrical ignition hazards. The study provides evidence that intake air courses of gassy underground coal mines fit the description of certain Hazardous (classified) locations described in the US National Electrical Code ®. Class I Division 2 or Zone 2 explosion protection techniques may be used to design intake air equipment so that it does not present an ignition source under normal operation, before mine power is shut down in emergency situations. Nonpermissible circuits in intake air courses that are likely to remain energized during emergencies, e.g. battery powered equipment, should be protected by more stringent Class I Division 1, Zone 1, or Zone 0 techniques, to protect rescue/recovery personnel.

Rapid identification of PAX2/5/8 direct downstream targets in the otic vesicle by combinatorial use of bioinformatics tools

A novel bioinformatics pipeline is used to discover PAX2/5/8 direct downstream targets involved in inner ear development.

Ground-Fault Feeder Detection With Fault-Current and Fault-Resistance Measurement in Mine Power Systems

Many mine power systems operate with a floating neutral or are high-resistance grounded, and earth fault current is no more than a few tens of amperes. Traditional earth-fault-detection methods based on zero-sequence current have poor sensitivity in this case. For improvement, a fault-detection scheme with fault-current and fault-resistance measurement is presented in this paper, which is capable of detecting high-impedance ground faults. The scheme has been verified by electromagnetic-transient-program simulation, and a fault-detection prototype has been developed and tested in the laboratory. Results show that the scheme has high sensitivity and robustness.

Application of grey‐based rough decision‐making approach to suppliers selection

PurposeThis paper aims to resolve the uncertain problem in suppliers selection chain management system through using the proposed multiple attribute decision‐making (MADM) approach.Design/methodology/approachThe approach which combines grey system theory with rough set theory is proposed.FindingsThis proposed approach take advantage of mathematical analysis power of grey system theory and at the same time take advantage of data mining and knowledge discovery power of rough set theory. It will be suitable to decision making under a more uncertain environment.Originality/valueProvides a viewpoint on the attribute values and attribute weights of rough set decision table for all alternatives are decided by grey number based on grey system theory. The best ideal supplier can be decided by grey relational analysis based on grey number.

Simple alignment-free methods for protein classification: A case study from G-protein-coupled receptors

Computational methods of predicting protein functions rely on detecting similarities among proteins. However, sufficient sequence information is not always available for some protein families. For example, proteins of interest may be new members of a divergent protein family. The performance of protein classification methods could vary in such challenging situations. Using the G-protein-coupled receptor superfamily as an example, we investigated the performance of several protein classifiers. Alignment-free classifiers based on support vector machines using simple amino acid compositions were effective in remote-similarity detection even from short fragmented sequences. Although it is computationally expensive, a support vector machine classifier using local pairwise alignment scores showed very good balanced performance. More commonly used profile hidden Markov models were generally highly specific and well suited to classifying well-established protein family members. It is suggested that different types of protein classifiers should be applied to gain the optimal mining power.

A Water Model for Water and Environmental Management at Mae Moh Mine Area in Thailand

It is revealed that the water quality in Mae Moh Reservoir, Thailand, has been deteriorated by lignite mine drainage and power station effluent. This study aims to manipulate water quantity and quality to reduce environmental impacts in Mae Moh area through a model for water management. The model was constructed on the basis of materials balance to predict water flow, which includes concentrations of TDS and SO2–4. Data collected during 1996–2000 were used. Model validation showed that the mean of predicted and actual values of TDS and SO2–4 load were significantly similar at 95% confidence limit. The test result is acceptable and the water model can be used as a tool for water system management in the area. In 2006, Mae Moh mine excess water will be discharged at 10.76 Mm3, with a pH of 7.3, TDS and SO2–4 concentrations of 2,547 and 1,803 mg/l, respectively. Mae Moh power station effluent will be 14.59 Mm3, with pH of 7.1, TDS and SO2–4 concentrations of 610 and 358 mg/l, respectively. Predicted results showed that the outflow of Mae Moh Reservoir will be 83.67 Mm3 and the concentrations of TDS and SO2–4 will be as high as 1,501 and 822 mg/l, respectively. Mine excess water management measures are recommended according to the following strategy. All mine excess water should be stored during dry season. During wet season, 50% of the excess water should be stored and the remaining treated at 90% of TDS removal before being discharged. The end result would be a significant improvement in water quality in the Mae Moh Reservoir over the 4-year period to 2010. Pollutants in terms of TDS would be reduced by 35% from 1,501 mg/l in the beginning of 2006 to 975 mg/l at the end of 2009.

Detrimental Effects of Capacitance on High-Resistance-Grounded Mine Distribution Systems

Modern underground coal mines can be very large, having a total connected load in excess of 15,000 hp. These mines generally have many miles of high-power conveyor belts and IS or more miles of high-voltage power cables at distribution voltages of 12.47, 13.2, 13.8, or 14.4 kV. The shielded cables used in mine power distribution systems have a significant level of capacitance, on the order of 110 pF per ft. This level of capacitance, in an extensive power distribution system at today's voltage levels, can cause significant charging currents during a ground fault. This paper addresses the potential detrimental effects of capacitance charging currents during line-to-ground faults in mine power distribution systems. A representative mine power system is modeled and simulations with faults at various locations are conducted to evaluate the effects of this capacitance on the level of fault current and relay selectivity. The paper also includes results of capacitance measurements made on mine power feeder cables used to validate the simulation model.

Tapping the power of text mining

Sifting through vast collections of unstructured or semistructured data beyond the reach of data mining tools, text mining tracks information sources, links isolated concepts in distant documents, maps relationships between activities, and helps answer questions.

The impact of preprocessing on data mining: An evaluation of classifier sensitivity in direct marketing

Corporate data mining faces the challenge of systematic knowledge discovery in large data streams to support managerial decision making. While research in operations research, direct marketing and machine learning focuses on the analysis and design of data mining algorithms, the interaction of data mining with the preceding phase of data preprocessing has not been investigated in detail. This paper investigates the influence of different preprocessing techniques of attribute scaling, sampling, coding of categorical as well as coding of continuous attributes on the classifier performance of decision trees, neural networks and support vector machines. The impact of different preprocessing choices is assessed on a real world dataset from direct marketing using a multifactorial analysis of variance on various performance metrics and method parameterisations. Our case-based analysis provides empirical evidence that data preprocessing has a significant impact on predictive accuracy, with certain schemes proving inferior to competitive approaches. In addition, it is found that (1) selected methods prove almost as sensitive to different data representations as to method parameterisations, indicating the potential for increased performance through effective preprocessing; (2) the impact of preprocessing schemes varies by method, indicating different ‘best practice’ setups to facilitate superior results of a particular method; (3) algorithmic sensitivity towards preprocessing is consequently an important criterion in method evaluation and selection which needs to be considered together with traditional metrics of predictive power and computational efficiency in predictive data mining.

Structure of Trichamide, a Cyclic Peptide from the Bloom-Forming Cyanobacterium Trichodesmium erythraeum , Predicted from the Genome Sequence

A gene cluster for the biosynthesis of a new small cyclic peptide, dubbed trichamide, was discovered in the genome of the global, bloom-forming marine cyanobacterium Trichodesmium erythraeum ISM101 because of striking similarities to the previously characterized patellamide biosynthesis cluster. The tri cluster consists of a precursor peptide gene containing the amino acid sequence for mature trichamide, a putative heterocyclization gene, an oxidase, two proteases, and hypothetical genes. Based upon detailed sequence analysis, a structure was predicted for trichamide and confirmed by Fourier transform mass spectrometry. Trichamide consists of 11 amino acids, including two cysteine-derived thiazole groups, and is cyclized by an N C terminal amide bond. As the first natural product reported from T. erythraeum, trichamide shows the power of genome mining in the prediction and discovery of new natural products.

An Arabidopsis Oxidosqualene Cyclase Catalyzes Iridal Skeleton Formation by Grob Fragmentation

Mechanistic and phylogenetic surprises: A triterpene synthase (MRN1) from Arabidopsis invokes a Grob fragmentation in the cyclization of oxidosqualene. The enzymatic product is the elusive carbocyclic precursor of iridals, unusual triterpenoids known only in the distant Iris family. The results demonstrate the power of genome mining and exemplify the facile evolution of cyclases to generate diverse triterpene skeletons.

Restoring power in Kosovo

When NATO moved into Kosovo in June 1999 there was no indigenous power generation. UK Royal Engineers were tasked with restoring power within Kosovousing the existing generating capability and distribution system, which were both in a very poor condition. UK industry expertise provided the knowledge to enable the military to reopen a lignite mine, assess and repair power lines and finally restart a single generator thus restoring mains power to much of Kosovo. This paper highlights the interactions between the local labour force, the UK military, various non-government organisations and UK experts.

Global Civil Society and the Local Costs of Belonging: Defining Violence against Women in Russia

Previous articleNext article No AccessGlobal Civil Society and the Local Costs of Belonging: Defining Violence against Women in RussiaJulie HemmentJulie HemmentDepartment of AnthropologyUniversity of Massachusetts, Amherst Search for more articles by this author Department of AnthropologyUniversity of Massachusetts, AmherstPDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by Signs Volume 29, Number 3Spring 2004 Article DOIhttps://doi.org/10.1086/381104 Views: 418Total views on this site Citations: 35Citations are reported from Crossref © 2004 by The University of Chicago. All rights reserved.PDF download Crossref reports the following articles citing this article:Kristians Zalāns, Kārlis Lakševics, Ilze Mileiko Geographical Imagination and Experiences of Violence and Violence Prevention in Post-Soviet Space, Gender, Place & Culture 50 (Jun 2022): 1–22.https://doi.org/10.1080/0966369X.2022.2083588Gesine Fuchs, Eva Maria Hinterhuber Öffentlich und privat in Osteuropa, (Jul 2022): 425–457.https://doi.org/10.1007/978-3-658-35401-5_15Bettina Engels All good things come from below? Scalar constructions of the ‘local’ in conflicts over mining, Political Geography 84 (Jan 2021): 102295.https://doi.org/10.1016/j.polgeo.2020.102295Maria Davidenko An Epistemic Community in Abeyance: The Work of Russian Anti-Violence Organisations in a Restrictive Legal Climate, Europe-Asia Studies 72, no.88 (Oct 2020): 1329–1351.https://doi.org/10.1080/09668136.2020.1817861Bettina Engels, Melanie Müller Northern theories, Southern movements? 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On-site safety evaluation for earth fault in mining power systems

Many mining power systems utilize ineffectively grounded sources to restrict the residual current of single-phase earth fault in order to reduce outage and shock hazard. In practice, with the system expansion, topology changing, and insulation aging, the potential residual current and zero-sequence voltage for earth fault vary dynamically and some arcing earth faults can easily cause over-voltage and induce multiple faults. In order to improve the system safety, on-site condition monitoring, safety evaluation, and preventive maintenance for earth fault are proposed in this paper. Some techniques for online parameters measurement based on resonance-measurement principle are presented. Power system operation states are classified into normal secure state, alert state, incipient fault state, and fault state. Some security enhancement methods (preventive action and remedial action) for each state are implemented. The prototype for safety evaluation has been developed and installed in industry power systems for several years.