FraudMiner: a novel credit card fraud detection model based on frequent itemset mining.

PubMed

Seeja, K R; Zareapoor, Masoumeh

2014-01-01

This paper proposes an intelligent credit card fraud detection model for detecting fraud from highly imbalanced and anonymous credit card transaction datasets. The class imbalance problem is handled by finding legal as well as fraud transaction patterns for each customer by using frequent itemset mining. A matching algorithm is also proposed to find to which pattern (legal or fraud) the incoming transaction of a particular customer is closer and a decision is made accordingly. In order to handle the anonymous nature of the data, no preference is given to any of the attributes and each attribute is considered equally for finding the patterns. The performance evaluation of the proposed model is done on UCSD Data Mining Contest 2009 Dataset (anonymous and imbalanced) and it is found that the proposed model has very high fraud detection rate, balanced classification rate, Matthews correlation coefficient, and very less false alarm rate than other state-of-the-art classifiers.

Large-Scale Constraint-Based Pattern Mining

ERIC Educational Resources Information Center

Zhu, Feida

2009-01-01

We studied the problem of constraint-based pattern mining for three different data formats, item-set, sequence and graph, and focused on mining patterns of large sizes. Colossal patterns in each data formats are studied to discover pruning properties that are useful for direct mining of these patterns. For item-set data, we observed robustness of…

Reducing side effects of hiding sensitive itemsets in privacy preserving data mining.

PubMed

Lin, Chun-Wei; Hong, Tzung-Pei; Hsu, Hung-Chuan

2014-01-01

Data mining is traditionally adopted to retrieve and analyze knowledge from large amounts of data. Private or confidential data may be sanitized or suppressed before it is shared or published in public. Privacy preserving data mining (PPDM) has thus become an important issue in recent years. The most general way of PPDM is to sanitize the database to hide the sensitive information. In this paper, a novel hiding-missing-artificial utility (HMAU) algorithm is proposed to hide sensitive itemsets through transaction deletion. The transaction with the maximal ratio of sensitive to nonsensitive one is thus selected to be entirely deleted. Three side effects of hiding failures, missing itemsets, and artificial itemsets are considered to evaluate whether the transactions are required to be deleted for hiding sensitive itemsets. Three weights are also assigned as the importance to three factors, which can be set according to the requirement of users. Experiments are then conducted to show the performance of the proposed algorithm in execution time, number of deleted transactions, and number of side effects.

Reducing Side Effects of Hiding Sensitive Itemsets in Privacy Preserving Data Mining

PubMed Central

Lin, Chun-Wei; Hong, Tzung-Pei; Hsu, Hung-Chuan

2014-01-01

Data mining is traditionally adopted to retrieve and analyze knowledge from large amounts of data. Private or confidential data may be sanitized or suppressed before it is shared or published in public. Privacy preserving data mining (PPDM) has thus become an important issue in recent years. The most general way of PPDM is to sanitize the database to hide the sensitive information. In this paper, a novel hiding-missing-artificial utility (HMAU) algorithm is proposed to hide sensitive itemsets through transaction deletion. The transaction with the maximal ratio of sensitive to nonsensitive one is thus selected to be entirely deleted. Three side effects of hiding failures, missing itemsets, and artificial itemsets are considered to evaluate whether the transactions are required to be deleted for hiding sensitive itemsets. Three weights are also assigned as the importance to three factors, which can be set according to the requirement of users. Experiments are then conducted to show the performance of the proposed algorithm in execution time, number of deleted transactions, and number of side effects. PMID:24982932

Apriori Versions Based on MapReduce for Mining Frequent Patterns on Big Data.

PubMed

Luna, Jose Maria; Padillo, Francisco; Pechenizkiy, Mykola; Ventura, Sebastian

2017-09-27

Pattern mining is one of the most important tasks to extract meaningful and useful information from raw data. This task aims to extract item-sets that represent any type of homogeneity and regularity in data. Although many efficient algorithms have been developed in this regard, the growing interest in data has caused the performance of existing pattern mining techniques to be dropped. The goal of this paper is to propose new efficient pattern mining algorithms to work in big data. To this aim, a series of algorithms based on the MapReduce framework and the Hadoop open-source implementation have been proposed. The proposed algorithms can be divided into three main groups. First, two algorithms [Apriori MapReduce (AprioriMR) and iterative AprioriMR] with no pruning strategy are proposed, which extract any existing item-set in data. Second, two algorithms (space pruning AprioriMR and top AprioriMR) that prune the search space by means of the well-known anti-monotone property are proposed. Finally, a last algorithm (maximal AprioriMR) is also proposed for mining condensed representations of frequent patterns. To test the performance of the proposed algorithms, a varied collection of big data datasets have been considered, comprising up to 3 · 10#x00B9;⁸ transactions and more than 5 million of distinct single-items. The experimental stage includes comparisons against highly efficient and well-known pattern mining algorithms. Results reveal the interest of applying MapReduce versions when complex problems are considered, and also the unsuitability of this paradigm when dealing with small data.

Frequent Itemset Mining for Query Expansion in Microblog Ad-hoc Search

DTIC Science & Technology

2012-11-01

captin, @rayhattersley, #rhythm, almond, #lift, #white, rhythm, #blues, #sci- ence, loss*, you, #eating, #beauty, ambria, #with, weight*, diets , white...puwisdom, sci- ence, #and, @pulistbook, lift, dingle, @mir- acleweight, @tweettraffic4u, # diets , oranges, #of, @aase25, and*, berries*, #no...and, it, is, daily* MB055 benefits, with, acai, their, diet , on, of, wt, health, plans, ber, for, first, how, are, loss*, you, this, mt, lose, weight

Mining subspace clusters from DNA microarray data using large itemset techniques.

PubMed

Chang, Ye-In; Chen, Jiun-Rung; Tsai, Yueh-Chi

2009-05-01

Mining subspace clusters from the DNA microarrays could help researchers identify those genes which commonly contribute to a disease, where a subspace cluster indicates a subset of genes whose expression levels are similar under a subset of conditions. Since in a DNA microarray, the number of genes is far larger than the number of conditions, those previous proposed algorithms which compute the maximum dimension sets (MDSs) for any two genes will take a long time to mine subspace clusters. In this article, we propose the Large Itemset-Based Clustering (LISC) algorithm for mining subspace clusters. Instead of constructing MDSs for any two genes, we construct only MDSs for any two conditions. Then, we transform the task of finding the maximal possible gene sets into the problem of mining large itemsets from the condition-pair MDSs. Since we are only interested in those subspace clusters with gene sets as large as possible, it is desirable to pay attention to those gene sets which have reasonable large support values in the condition-pair MDSs. From our simulation results, we show that the proposed algorithm needs shorter processing time than those previous proposed algorithms which need to construct gene-pair MDSs.

CisMiner: Genome-Wide In-Silico Cis-Regulatory Module Prediction by Fuzzy Itemset Mining

PubMed Central

Navarro, Carmen; Lopez, Francisco J.; Cano, Carlos; Garcia-Alcalde, Fernando; Blanco, Armando

2014-01-01

Eukaryotic gene control regions are known to be spread throughout non-coding DNA sequences which may appear distant from the gene promoter. Transcription factors are proteins that coordinately bind to these regions at transcription factor binding sites to regulate gene expression. Several tools allow to detect significant co-occurrences of closely located binding sites (cis-regulatory modules, CRMs). However, these tools present at least one of the following limitations: 1) scope limited to promoter or conserved regions of the genome; 2) do not allow to identify combinations involving more than two motifs; 3) require prior information about target motifs. In this work we present CisMiner, a novel methodology to detect putative CRMs by means of a fuzzy itemset mining approach able to operate at genome-wide scale. CisMiner allows to perform a blind search of CRMs without any prior information about target CRMs nor limitation in the number of motifs. CisMiner tackles the combinatorial complexity of genome-wide cis-regulatory module extraction using a natural representation of motif combinations as itemsets and applying the Top-Down Fuzzy Frequent- Pattern Tree algorithm to identify significant itemsets. Fuzzy technology allows CisMiner to better handle the imprecision and noise inherent to regulatory processes. Results obtained for a set of well-known binding sites in the S. cerevisiae genome show that our method yields highly reliable predictions. Furthermore, CisMiner was also applied to putative in-silico predicted transcription factor binding sites to identify significant combinations in S. cerevisiae and D. melanogaster, proving that our approach can be further applied genome-wide to more complex genomes. CisMiner is freely accesible at: http://genome2.ugr.es/cisminer. CisMiner can be queried for the results presented in this work and can also perform a customized cis-regulatory module prediction on a query set of transcription factor binding sites provided by the user. PMID:25268582

The association rules search of Indonesian university graduate’s data using FP-growth algorithm

NASA Astrophysics Data System (ADS)

Faza, S.; Rahmat, R. F.; Nababan, E. B.; Arisandi, D.; Effendi, S.

2018-02-01

The attribute varieties in university graduates data have caused frustrations to the institution in finding the combinations of attributes that often emerge and have high integration between attributes. Association rules mining is a data mining technique to determine the integration of the data or the way of a data set affects another set of data. By way of explanation, there are possibilities in finding the integration of data on a large scale. Frequent Pattern-Growth (FP-Growth) algorithm is one of the association rules mining technique to determine a frequent itemset in an FP-Tree data set. From the research on the search of university graduate’s association rules, it can be concluded that the most common attributes that have high integration between them are in the combination of State-owned High School outside Medan, regular university entrance exam, GPA of 3.00 to 3.49 and over 4-year-long study duration.

Efficiently hiding sensitive itemsets with transaction deletion based on genetic algorithms.

PubMed

Lin, Chun-Wei; Zhang, Binbin; Yang, Kuo-Tung; Hong, Tzung-Pei

2014-01-01

Data mining is used to mine meaningful and useful information or knowledge from a very large database. Some secure or private information can be discovered by data mining techniques, thus resulting in an inherent risk of threats to privacy. Privacy-preserving data mining (PPDM) has thus arisen in recent years to sanitize the original database for hiding sensitive information, which can be concerned as an NP-hard problem in sanitization process. In this paper, a compact prelarge GA-based (cpGA2DT) algorithm to delete transactions for hiding sensitive itemsets is thus proposed. It solves the limitations of the evolutionary process by adopting both the compact GA-based (cGA) mechanism and the prelarge concept. A flexible fitness function with three adjustable weights is thus designed to find the appropriate transactions to be deleted in order to hide sensitive itemsets with minimal side effects of hiding failure, missing cost, and artificial cost. Experiments are conducted to show the performance of the proposed cpGA2DT algorithm compared to the simple GA-based (sGA2DT) algorithm and the greedy approach in terms of execution time and three side effects.

Boosting association rule mining in large datasets via Gibbs sampling.

PubMed

Qian, Guoqi; Rao, Calyampudi Radhakrishna; Sun, Xiaoying; Wu, Yuehua

2016-05-03

Current algorithms for association rule mining from transaction data are mostly deterministic and enumerative. They can be computationally intractable even for mining a dataset containing just a few hundred transaction items, if no action is taken to constrain the search space. In this paper, we develop a Gibbs-sampling-induced stochastic search procedure to randomly sample association rules from the itemset space, and perform rule mining from the reduced transaction dataset generated by the sample. Also a general rule importance measure is proposed to direct the stochastic search so that, as a result of the randomly generated association rules constituting an ergodic Markov chain, the overall most important rules in the itemset space can be uncovered from the reduced dataset with probability 1 in the limit. In the simulation study and a real genomic data example, we show how to boost association rule mining by an integrated use of the stochastic search and the Apriori algorithm.

Genetic Programming and Frequent Itemset Mining to Identify Feature Selection Patterns of iEEG and fMRI Epilepsy Data

PubMed Central

Smart, Otis; Burrell, Lauren

2014-01-01

Pattern classification for intracranial electroencephalogram (iEEG) and functional magnetic resonance imaging (fMRI) signals has furthered epilepsy research toward understanding the origin of epileptic seizures and localizing dysfunctional brain tissue for treatment. Prior research has demonstrated that implicitly selecting features with a genetic programming (GP) algorithm more effectively determined the proper features to discern biomarker and non-biomarker interictal iEEG and fMRI activity than conventional feature selection approaches. However for each the iEEG and fMRI modalities, it is still uncertain whether the stochastic properties of indirect feature selection with a GP yield (a) consistent results within a patient data set and (b) features that are specific or universal across multiple patient data sets. We examined the reproducibility of implicitly selecting features to classify interictal activity using a GP algorithm by performing several selection trials and subsequent frequent itemset mining (FIM) for separate iEEG and fMRI epilepsy patient data. We observed within-subject consistency and across-subject variability with some small similarity for selected features, indicating a clear need for patient-specific features and possible need for patient-specific feature selection or/and classification. For the fMRI, using nearest-neighbor classification and 30 GP generations, we obtained over 60% median sensitivity and over 60% median selectivity. For the iEEG, using nearest-neighbor classification and 30 GP generations, we obtained over 65% median sensitivity and over 65% median selectivity except one patient. PMID:25580059

An Incremental High-Utility Mining Algorithm with Transaction Insertion

PubMed Central

Gan, Wensheng; Zhang, Binbin

2015-01-01

Association-rule mining is commonly used to discover useful and meaningful patterns from a very large database. It only considers the occurrence frequencies of items to reveal the relationships among itemsets. Traditional association-rule mining is, however, not suitable in real-world applications since the purchased items from a customer may have various factors, such as profit or quantity. High-utility mining was designed to solve the limitations of association-rule mining by considering both the quantity and profit measures. Most algorithms of high-utility mining are designed to handle the static database. Fewer researches handle the dynamic high-utility mining with transaction insertion, thus requiring the computations of database rescan and combination explosion of pattern-growth mechanism. In this paper, an efficient incremental algorithm with transaction insertion is designed to reduce computations without candidate generation based on the utility-list structures. The enumeration tree and the relationships between 2-itemsets are also adopted in the proposed algorithm to speed up the computations. Several experiments are conducted to show the performance of the proposed algorithm in terms of runtime, memory consumption, and number of generated patterns. PMID:25811038

Application of Frequent Itemsets Mining to Analyze Patterns of One-Stop Visits in Taiwan

PubMed Central

Tu, Chun-Yi; Chen, Tzeng-Ji; Chou, Li-Fang

2011-01-01

Background The free choice of health care facilities without limitations on frequency of visits within the National Health Insurance in Taiwan gives rise to not only a high number of annual ambulatory visits per capita but also a unique “one-stop shopping”phenomenon, which refers to a patient' visits to several specialties of the same healthcare facility in one day. The visits to multiple physicians would increase the potential risk of polypharmacy. The aim of this study was to analyze the frequency and patterns of one-stop visits in Taiwan. Methodology/Principal Findings The claims datasets of 1 million nationally representative people within Taiwan's National Health Insurance in 2005 were used to calculate the number of patients with one-stop visits. The frequent itemsets mining was applied to compute the combination patterns of specialties in the one-stop visits. Among the total 13,682,469 ambulatory care visits in 2005, one-stop visits occurred 144,132 times and involved 296,822 visits (2.2% of all visits) by 66,294 (6.6%) persons. People tended to have this behavior with age and the percentage reached 27.5% (5,662 in 20,579) in the age group ≥80 years. In general, women were more likely to have one-stop visits than men (7.2% vs. 6.0%). Internal medicine plus ophthalmology was the most frequent combination with a visited frequency of 3,552 times (2.5%), followed by cardiology plus neurology with 3,183 times (2.2%). The most frequent three-specialty combination, cardiology plus neurology and gastroenterology, occurred only 111 times. Conclusions/Significance Without the novel computational technique, it would be hardly possible to analyze the extremely diverse combination patterns of specialties in one-stop visits. The results of the study could provide useful information either for the hospital manager to set up integrated services or for the policymaker to rebuild the health care system. PMID:21747926

Mining on Big Data Using Hadoop MapReduce Model

NASA Astrophysics Data System (ADS)

Salman Ahmed, G.; Bhattacharya, Sweta

2017-11-01

Customary parallel calculations for mining nonstop item create opportunity to adjust stack of similar data among hubs. The paper aims to review this process by analyzing the critical execution downside of the common parallel recurrent item-set mining calculations. Given a larger than average dataset, data apportioning strategies inside the current arrangements endure high correspondence and mining overhead evoked by repetitive exchanges transmitted among registering hubs. We tend to address this downside by building up a learning apportioning approach referred as Hadoop abuse using the map-reduce programming model. All objectives of Hadoop are to zest up the execution of parallel recurrent item-set mining on Hadoop bunches. Fusing the comparability metric and furthermore the locality-sensitive hashing procedure, Hadoop puts to a great degree comparative exchanges into an information segment to lift neighborhood while not making AN exorbitant assortment of excess exchanges. We tend to execute Hadoop on a 34-hub Hadoop bunch, driven by a decent change of datasets made by IBM quest market-basket manufactured data generator. Trial uncovers the fact that Hadoop contributes towards lessening system and processing masses by the uprightness of dispensing with excess exchanges on Hadoop hubs. Hadoop impressively outperforms and enhances the other models considerably.

RANWAR: rank-based weighted association rule mining from gene expression and methylation data.

PubMed

Mallik, Saurav; Mukhopadhyay, Anirban; Maulik, Ujjwal

2015-01-01

Ranking of association rules is currently an interesting topic in data mining and bioinformatics. The huge number of evolved rules of items (or, genes) by association rule mining (ARM) algorithms makes confusion to the decision maker. In this article, we propose a weighted rule-mining technique (say, RANWAR or rank-based weighted association rule-mining) to rank the rules using two novel rule-interestingness measures, viz., rank-based weighted condensed support (wcs) and weighted condensed confidence (wcc) measures to bypass the problem. These measures are basically depended on the rank of items (genes). Using the rank, we assign weight to each item. RANWAR generates much less number of frequent itemsets than the state-of-the-art association rule mining algorithms. Thus, it saves time of execution of the algorithm. We run RANWAR on gene expression and methylation datasets. The genes of the top rules are biologically validated by Gene Ontologies (GOs) and KEGG pathway analyses. Many top ranked rules extracted from RANWAR that hold poor ranks in traditional Apriori, are highly biologically significant to the related diseases. Finally, the top rules evolved from RANWAR, that are not in Apriori, are reported.

Association mining of mutated cancer genes in different clinical stages across 11 cancer types.

PubMed

Hu, Wangxiong; Li, Xiaofen; Wang, Tingzhang; Zheng, Shu

2016-10-18

Many studies have demonstrated that some genes (e.g. APC, BRAF, KRAS, PTEN, TP53) are frequently mutated in cancer, however, underlying mechanism that contributes to their high mutation frequency remains unclear. Here we used Apriori algorithm to find the frequent mutational gene sets (FMGSs) from 4,904 tumors across 11 cancer types as part of the TCGA Pan-Cancer effort and then mined the hidden association rules (ARs) within these FMGSs. Intriguingly, we found that well-known cancer driver genes such as BRAF, KRAS, PTEN, and TP53 were often co-occurred with other driver genes and FMGSs size peaked at an itemset size of 3~4 genes. Besides, the number and constitution of FMGS and ARs differed greatly among different cancers and stages. In addition, FMGS and ARs were rare in endocrine-related cancers such as breast carcinoma, ovarian cystadenocarcinoma, and thyroid carcinoma, but abundant in cancers contact directly with external environments such as skin melanoma and stomach adenocarcinoma. Furthermore, we observed more rules in stage IV than in other stages, indicating that distant metastasis needed more sophisticated gene regulatory network.

Knowledge discovery in traditional Chinese medicine: state of the art and perspectives.

PubMed

Feng, Yi; Wu, Zhaohui; Zhou, Xuezhong; Zhou, Zhongmei; Fan, Weiyu

2006-11-01

As a complementary medical system to Western medicine, traditional Chinese medicine (TCM) provides a unique theoretical and practical approach to the treatment of diseases over thousands of years. Confronted with the increasing popularity of TCM and the huge volume of TCM data, historically accumulated and recently obtained, there is an urgent need to explore these resources effectively by the techniques of knowledge discovery in database (KDD). This paper aims at providing an overview of recent KDD studies in TCM field. A literature search was conducted in both English and Chinese publications, and major studies of knowledge discovery in TCM (KDTCM) reported in these materials were identified. Based on an introduction to the state of the art of TCM data resources, a review of four subfields of KDTCM research was presented, including KDD for the research of Chinese medical formula, KDD for the research of Chinese herbal medicine, KDD for TCM syndrome research, and KDD for TCM clinical diagnosis. Furthermore, the current state and main problems in each subfield were summarized based on a discussion of existing studies, and future directions for each subfield were also proposed accordingly. A series of KDD methods are used in existing KDTCM researches, ranging from conventional frequent itemset mining to state of the art latent structure model. Considerable interesting discoveries are obtained by these methods, such as novel TCM paired drugs discovered by frequent itemset analysis, functional community of related genes discovered under syndrome perspective by text mining, the high proportion of toxic plants in the botanical family Ranunculaceae disclosed by statistical analysis, the association between M-cholinoceptor blocking drug and Solanaceae revealed by association rule mining, etc. It is particularly inspiring to see some studies connecting TCM with biomedicine, which provide a novel top-down view for functional genomics research. However, further developments of KDD methods are still expected to better adapt to the features of TCM. Existing studies demonstrate that KDTCM is effective in obtaining medical discoveries. However, much more work needs to be done in order to discover real diamonds from TCM domain. The usage and development of KDTCM in the future will substantially contribute to the TCM community, as well as modern life science.

Multiagent data warehousing and multiagent data mining for cerebrum/cerebellum modeling

NASA Astrophysics Data System (ADS)

Zhang, Wen-Ran

2002-03-01

An algorithm named Neighbor-Miner is outlined for multiagent data warehousing and multiagent data mining. The algorithm is defined in an evolving dynamic environment with autonomous or semiautonomous agents. Instead of mining frequent itemsets from customer transactions, the new algorithm discovers new agents and mining agent associations in first-order logic from agent attributes and actions. While the Apriori algorithm uses frequency as a priory threshold, the new algorithm uses agent similarity as priory knowledge. The concept of agent similarity leads to the notions of agent cuboid, orthogonal multiagent data warehousing (MADWH), and multiagent data mining (MADM). Based on agent similarities and action similarities, Neighbor-Miner is proposed and illustrated in a MADWH/MADM approach to cerebrum/cerebellum modeling. It is shown that (1) semiautonomous neurofuzzy agents can be identified for uniped locomotion and gymnastic training based on attribute relevance analysis; (2) new agents can be discovered and agent cuboids can be dynamically constructed in an orthogonal MADWH, which resembles an evolving cerebrum/cerebellum system; and (3) dynamic motion laws can be discovered as association rules in first order logic. Although examples in legged robot gymnastics are used to illustrate the basic ideas, the new approach is generally suitable for a broad category of data mining tasks where knowledge can be discovered collectively by a set of agents from a geographically or geometrically distributed but relevant environment, especially in scientific and engineering data environments.

Long-range prediction of Indian summer monsoon rainfall using data mining and statistical approaches

NASA Astrophysics Data System (ADS)

H, Vathsala; Koolagudi, Shashidhar G.

2017-10-01

This paper presents a hybrid model to better predict Indian summer monsoon rainfall. The algorithm considers suitable techniques for processing dense datasets. The proposed three-step algorithm comprises closed itemset generation-based association rule mining for feature selection, cluster membership for dimensionality reduction, and simple logistic function for prediction. The application of predicting rainfall into flood, excess, normal, deficit, and drought based on 36 predictors consisting of land and ocean variables is presented. Results show good accuracy in the considered study period of 37years (1969-2005).

SiBIC: a web server for generating gene set networks based on biclusters obtained by maximal frequent itemset mining.

PubMed

Takahashi, Kei-ichiro; Takigawa, Ichigaku; Mamitsuka, Hiroshi

2013-01-01

Detecting biclusters from expression data is useful, since biclusters are coexpressed genes under only part of all given experimental conditions. We present a software called SiBIC, which from a given expression dataset, first exhaustively enumerates biclusters, which are then merged into rather independent biclusters, which finally are used to generate gene set networks, in which a gene set assigned to one node has coexpressed genes. We evaluated each step of this procedure: 1) significance of the generated biclusters biologically and statistically, 2) biological quality of merged biclusters, and 3) biological significance of gene set networks. We emphasize that gene set networks, in which nodes are not genes but gene sets, can be more compact than usual gene networks, meaning that gene set networks are more comprehensible. SiBIC is available at http://utrecht.kuicr.kyoto-u.ac.jp:8080/miami/faces/index.jsp.

Statistical evaluation of synchronous spike patterns extracted by frequent item set mining

PubMed Central

Torre, Emiliano; Picado-Muiño, David; Denker, Michael; Borgelt, Christian; Grün, Sonja

2013-01-01

We recently proposed frequent itemset mining (FIM) as a method to perform an optimized search for patterns of synchronous spikes (item sets) in massively parallel spike trains. This search outputs the occurrence count (support) of individual patterns that are not trivially explained by the counts of any superset (closed frequent item sets). The number of patterns found by FIM makes direct statistical tests infeasible due to severe multiple testing. To overcome this issue, we proposed to test the significance not of individual patterns, but instead of their signatures, defined as the pairs of pattern size z and support c. Here, we derive in detail a statistical test for the significance of the signatures under the null hypothesis of full independence (pattern spectrum filtering, PSF) by means of surrogate data. As a result, injected spike patterns that mimic assembly activity are well detected, yielding a low false negative rate. However, this approach is prone to additionally classify patterns resulting from chance overlap of real assembly activity and background spiking as significant. These patterns represent false positives with respect to the null hypothesis of having one assembly of given signature embedded in otherwise independent spiking activity. We propose the additional method of pattern set reduction (PSR) to remove these false positives by conditional filtering. By employing stochastic simulations of parallel spike trains with correlated activity in form of injected spike synchrony in subsets of the neurons, we demonstrate for a range of parameter settings that the analysis scheme composed of FIM, PSF and PSR allows to reliably detect active assemblies in massively parallel spike trains. PMID:24167487

An Integrative data mining approach to identifying Adverse ...

EPA Pesticide Factsheets

The Adverse Outcome Pathway (AOP) framework is a tool for making biological connections and summarizing key information across different levels of biological organization to connect biological perturbations at the molecular level to adverse outcomes for an individual or population. Computational approaches to explore and determine these connections can accelerate the assembly of AOPs. By leveraging the wealth of publicly available data covering chemical effects on biological systems, computationally-predicted AOPs (cpAOPs) were assembled via data mining of high-throughput screening (HTS) in vitro data, in vivo data and other disease phenotype information. Frequent Itemset Mining (FIM) was used to find associations between the gene targets of ToxCast HTS assays and disease data from Comparative Toxicogenomics Database (CTD) by using the chemicals as the common aggregators between datasets. The method was also used to map gene expression data to disease data from CTD. A cpAOP network was defined by considering genes and diseases as nodes and FIM associations as edges. This network contained 18,283 gene to disease associations for the ToxCast data and 110,253 for CTD gene expression. Two case studies show the value of the cpAOP network by extracting subnetworks focused either on fatty liver disease or the Aryl Hydrocarbon Receptor (AHR). The subnetwork surrounding fatty liver disease included many genes known to play a role in this disease. When querying the cpAOP

Data mining and frequency analysis for licorice as a "Two-Face" herb in Chinese Formulae based on Chinese Formulae Database.

PubMed

Guo, Jianming; Shang, Erxin; Zhao, Jinlong; Fan, Xinsheng; Duan, Jinao; Qian, Dawei; Tao, Weiwei; Tang, Yuping

2014-09-25

Liquorice is the root of Glycyrrhiza uralensis Fisch. or Glycyrrhiza glabra L., Leguminosae. Licorice is described as 'National Venerable Master' in Chinese medicine and plays paradoxical roles, i.e. detoxification/strengthen efficacy and inducing/enhancing toxicity. Therefore, licorice was called "Two-Face" herb in this paper. The aim of this study is to discuss the paradoxical roles and the perspective usage of this "Two-Face" herb using data mining and frequency analysis. More than 96,000 prescriptions from Chinese Formulae Database were selected. The frequency and the prescription patterns were analyzed using Microsoft SQL Server 2000. Data mining methods (frequent itemsets) were used to analyze the regular patterns and compatibility laws of the constituent herbs in the selected prescriptions. The result showed that licorice (Radix glycyrrhizae) was the most frequently used herb in Chinese Formulae Database, other frequently used herbs including Radix Angelicae Sinensis (Dang gui), Radix et rhizoma ginseng (Ren shen), etc. Toxic herbs such as Radix aconiti lateralis praeparata (Fu zi), Rhizoma pinelliae (Ban xia) and Cinnabaris (Zhu sha) are top 3 herbs that most frequently used in combination with licorice. Radix et rhizoma ginseng (Ren shen), Poria (Fu ling), Radix Angelicae Sinensis (Dang gui) are top 3 nontoxic herbs that most frequently used in combination with licorice. Moreover, Licorice was seldom used with sargassum (Hai Zao), Herba Cirsii Japonici (Da Ji), Euphorbia kansui (Gan Sui) and Flos genkwa (Yuan Hua), which proved the description of contradictory effect of Radix glycyrrhizae and these herbs as recorded in Chinese medicine theory. This study showed the principle pattern of Chinese herbal drugs used in combination with licorice or not. The principle patterns and special compatibility laws reported here could be useful and instructive for scientific usage of licorice in clinic application. Further pharmacological and chemical researches are needed to evaluate the efficacy and the combination pattern of these Chinese herbs. The mechanism of the combination pattern of these prescriptions should also be investigated whether additive, synergistic or antagonistic effect exist using in vitro or in vivo models. Copyright © 2014 Elsevier GmbH. All rights reserved.

Prediction model for peninsular Indian summer monsoon rainfall using data mining and statistical approaches

NASA Astrophysics Data System (ADS)

Vathsala, H.; Koolagudi, Shashidhar G.

2017-01-01

In this paper we discuss a data mining application for predicting peninsular Indian summer monsoon rainfall, and propose an algorithm that combine data mining and statistical techniques. We select likely predictors based on association rules that have the highest confidence levels. We then cluster the selected predictors to reduce their dimensions and use cluster membership values for classification. We derive the predictors from local conditions in southern India, including mean sea level pressure, wind speed, and maximum and minimum temperatures. The global condition variables include southern oscillation and Indian Ocean dipole conditions. The algorithm predicts rainfall in five categories: Flood, Excess, Normal, Deficit and Drought. We use closed itemset mining, cluster membership calculations and a multilayer perceptron function in the algorithm to predict monsoon rainfall in peninsular India. Using Indian Institute of Tropical Meteorology data, we found the prediction accuracy of our proposed approach to be exceptionally good.

Study of the distribution patterns of the constituent herbs in classical Chinese medicine prescriptions treating respiratory disease by data mining methods.

PubMed

Fu, Xian-Jun; Song, Xu-Xia; Wei, Lin-Bo; Wang, Zhen-Guo

2013-08-01

To provide the distribution pattern and compatibility laws of the constituent herbs in prescriptions, for doctor's convenience to make decision in choosing correct herbs and prescriptions for treating respiratory disease. Classical prescriptions treating respiratory disease were selected from authoritative prescription books. Data mining methods (frequent itemsets and association rules) were used to analyze the regular patterns and compatibility laws of the constituent herbs in the selected prescriptions. A total of 562 prescriptions were selected to be studied. The result exhibited that, Radix glycyrrhizae was the most frequently used in 47.2% prescriptions, other frequently used were Semen armeniacae amarum, Fructus schisandrae Chinese, Herba ephedrae, and Radix ginseng. Herbal ephedrae was always coupled with Semen armeniacae amarum with the confidence of 73.3%, and many herbs were always accompanied by Radix glycyrrhizae with high confidence. More over, Fructus schisandrae Chinese, Herba ephedrae and Rhizoma pinelliae was most commonly used to treat cough, dyspnoea and associated sputum respectively besides Radix glycyrrhizae and Semen armeniacae amarum. The prescriptions treating dyspnoea often used double herb group of Herba ephedrae & Radix glycyrrhizae, while prescriptions treating sputum often used double herb group of Rhizoma pinelliae & Radix glycyrrhizae and Rhizoma pinelliae & Semen armeniacae amarum, triple herb groups of Rhizoma pinelliae & Semen armeniacae amarum & Radix glycyrrhizae and Pericarpium citri reticulatae & Rhizoma pinelliae & Radix glycyrrhizae. The prescriptions treating respiratory disease showed common compatibility laws in using herbs and special compatibility laws for treating different respiratory symptoms. These principle patterns and special compatibility laws reported here could be useful for doctors to choose correct herbs and prescriptions in treating respiratory disease.

Efficient Algorithms for Segmentation of Item-Set Time Series

NASA Astrophysics Data System (ADS)

Chundi, Parvathi; Rosenkrantz, Daniel J.

We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.

Information mining over heterogeneous and high-dimensional time-series data in clinical trials databases.

PubMed

Altiparmak, Fatih; Ferhatosmanoglu, Hakan; Erdal, Selnur; Trost, Donald C

2006-04-01

An effective analysis of clinical trials data involves analyzing different types of data such as heterogeneous and high dimensional time series data. The current time series analysis methods generally assume that the series at hand have sufficient length to apply statistical techniques to them. Other ideal case assumptions are that data are collected in equal length intervals, and while comparing time series, the lengths are usually expected to be equal to each other. However, these assumptions are not valid for many real data sets, especially for the clinical trials data sets. An addition, the data sources are different from each other, the data are heterogeneous, and the sensitivity of the experiments varies by the source. Approaches for mining time series data need to be revisited, keeping the wide range of requirements in mind. In this paper, we propose a novel approach for information mining that involves two major steps: applying a data mining algorithm over homogeneous subsets of data, and identifying common or distinct patterns over the information gathered in the first step. Our approach is implemented specifically for heterogeneous and high dimensional time series clinical trials data. Using this framework, we propose a new way of utilizing frequent itemset mining, as well as clustering and declustering techniques with novel distance metrics for measuring similarity between time series data. By clustering the data, we find groups of analytes (substances in blood) that are most strongly correlated. Most of these relationships already known are verified by the clinical panels, and, in addition, we identify novel groups that need further biomedical analysis. A slight modification to our algorithm results an effective declustering of high dimensional time series data, which is then used for "feature selection." Using industry-sponsored clinical trials data sets, we are able to identify a small set of analytes that effectively models the state of normal health.

The Network Structure Underlying the Earth Observation Assessment

NASA Astrophysics Data System (ADS)

Vitkin, S.; Doane, W. E. J.; Mary, J. C.

2017-12-01

The Earth Observations Assessment (EOA 2016) is a multiyear project designed to assess the effectiveness of civil earth observation data sources (instruments, sensors, models, etc.) on societal benefit areas (SBAs) for the United States. Subject matter experts (SMEs) provided input and scored how data sources inform products, product groups, key objectives, SBA sub-areas, and SBAs in an attempt to quantify the relationships between data sources and SBAs. The resulting data were processed by Integrated Applications Incorporated (IAI) using MITRE's PALMA software to create normalized relative impact scores for each of these relationships. However, PALMA processing obscures the natural network representation of the data. Any network analysis that might identify patterns of interaction among data sources, products, and SBAs is therefore impossible. Collaborating with IAI, we cleaned and recreated a network from the original dataset. Using R and Python we explore the underlying structure of the network and apply frequent itemset mining algorithms to identify groups of data sources and products that interact. We reveal interesting patterns and relationships in the EOA dataset that were not immediately observable from the EOA 2016 report and provide a basis for further exploration of the EOA network dataset.

A Market-Basket Approach to Predict the Acute Aquatic Toxicity of Munitions and Energetic Materials.

PubMed

Burgoon, Lyle D

2016-06-01

An ongoing challenge in chemical production, including the production of insensitive munitions and energetics, is the ability to make predictions about potential environmental hazards early in the process. To address this challenge, a quantitative structure activity relationship model was developed to predict acute fathead minnow toxicity of insensitive munitions and energetic materials. Computational predictive toxicology models like this one may be used to identify and prioritize environmentally safer materials early in their development. The developed model is based on the Apriori market-basket/frequent itemset mining approach to identify probabilistic prediction rules using chemical atom-pairs and the lethality data for 57 compounds from a fathead minnow acute toxicity assay. Lethality data were discretized into four categories based on the Globally Harmonized System of Classification and Labelling of Chemicals. Apriori identified toxicophores for categories two and three. The model classified 32 of the 57 compounds correctly, with a fivefold cross-validation classification rate of 74 %. A structure-based surrogate approach classified the remaining 25 chemicals correctly at 48 %. This result is unsurprising as these 25 chemicals were fairly unique within the larger set.

Item-Based Top-N Recommendation Algorithms

DTIC Science & Technology

2003-01-20

basket of items, utilized by many e-commerce sites, cannot take advantage of pre-computed user-to-user similarities. Finally, even though the...not discriminate between items that are present in frequent itemsets and items that are not, while still maintaining the computational advantages of...453219 0.02% 7.74 ccard 42629 68793 398619 0.01% 9.35 ecommerce 6667 17491 91222 0.08% 13.68 em 8002 1648 769311 5.83% 96.14 ml 943 1682 100000 6.31

A Method for Identifying Prevalent Chemical Combinations in the U.S. Population

PubMed Central

Wambaugh, John F.; Ring, Caroline L.; Tornero-Velez, Rogelio; Setzer, R. Woodrow

2017-01-01

Background: Through the food and water they ingest, the air they breathe, and the consumer products with which they interact at home and at work, humans are exposed to tens of thousands of chemicals, many of which have not been evaluated to determine their potential toxicities. Furthermore, while current chemical testing tends to focus on individual chemicals, the exposures that people actually experience involve mixtures of chemicals. Unfortunately, the number of mixtures that can be formed from the thousands of environmental chemicals is enormous, and testing all of them would be impossible. Objectives: We seek to develop and demonstrate a method for identifying those mixtures that are most prevalent in humans. Methods: We applied frequent itemset mining, a technique traditionally used for market basket analysis, to biomonitoring data from the 2009–2010 cycle of the continuous National Health and Nutrition Examination Survey (NHANES) to identify combinations of chemicals that frequently co-occur in people. Results: We identified 90 chemical combinations consisting of relatively few chemicals that occur in at least 30% of the U.S. population, as well as three supercombinations consisting of relatively many chemicals that occur in a small but nonnegligible proportion of the U.S. population. Conclusions: We demonstrated how FIM can be used in conjunction with biomonitoring data to narrow a large number of possible chemical combinations down to a smaller set of prevalent chemical combinations. https://doi.org/10.1289/EHP1265 PMID:28858827

Identification and Prioritization of Relationships between Environmental Stressors and Adverse Human Health Impacts.

PubMed

Bell, Shannon M; Edwards, Stephen W

2015-11-01

There are > 80,000 chemicals in commerce with few data available describing their impacts on human health. Biomonitoring surveys, such as the NHANES (National Health and Nutrition Examination Survey), offer one route to identifying possible relationships between environmental chemicals and health impacts, but sparse data and the complexity of traditional models make it difficult to leverage effectively. We describe a workflow to efficiently and comprehensively evaluate and prioritize chemical-health impact relationships from the NHANES biomonitoring survey studies. Using a frequent itemset mining (FIM) approach, we identified relationships between chemicals and health biomarkers and diseases. The FIM method identified 7,848 relationships between 219 chemicals and 93 health outcomes/biomarkers. Two case studies used to evaluate the FIM rankings demonstrate that the FIM approach is able to identify published relationships. Because the relationships are derived from the vast majority of the chemicals monitored by NHANES, the resulting list of associations is appropriate for evaluating results from targeted data mining or identifying novel candidate relationships for more detailed investigation. Because of the computational efficiency of the FIM method, all chemicals and health effects can be considered in a single analysis. The resulting list provides a comprehensive summary of the chemical/health co-occurrences from NHANES that are higher than expected by chance. This information enables ranking and prioritization on chemicals or health effects of interest for evaluation of published results and design of future studies. Bell SM, Edwards SW. 2015. Identification and prioritization of relationships between environmental stressors and adverse human health impacts. Environ Health Perspect 123:1193-1199; http://dx.doi.org/10.1289/ehp.1409138.

Frequency and pattern of Chinese herbal medicine prescriptions for urticaria in Taiwan during 2009: analysis of the national health insurance database

PubMed Central

2013-01-01

Background Large-scale pharmaco-epidemiological studies of Chinese herbal medicine (CHM) for treatment of urticaria are few, even though clinical trials showed some CHM are effective. The purpose of this study was to explore the frequencies and patterns of CHM prescriptions for urticaria by analysing the population-based CHM database in Taiwan. Methods This study was linked to and processed through the complete traditional CHM database of the National Health Insurance Research Database in Taiwan during 2009. We calculated the frequencies and patterns of CHM prescriptions used for treatment of urticaria, of which the diagnosis was defined as the single ICD-9 Code of 708. Frequent itemset mining, as applied to data mining, was used to analyse co-prescription of CHM for patients with urticaria. Results There were 37,386 subjects who visited traditional Chinese Medicine clinics for urticaria in Taiwan during 2009 and received a total of 95,765 CHM prescriptions. Subjects between 18 and 35 years of age comprised the largest number of those treated (32.76%). In addition, women used CHM for urticaria more frequently than men (female:male = 1.94:1). There was an average of 5.54 items prescribed in the form of either individual Chinese herbs or a formula in a single CHM prescription for urticaria. Bai-Xian-Pi (Dictamnus dasycarpus Turcz) was the most commonly prescribed single Chinese herb while Xiao-Feng San was the most commonly prescribed Chinese herbal formula. The most commonly prescribed CHM drug combination was Xiao-Feng San plus Bai-Xian-Pi while the most commonly prescribed triple drug combination was Xiao-Feng San, Bai-Xian-Pi, and Di-Fu Zi (Kochia scoparia). Conclusions In view of the popularity of CHM such as Xiao-Feng San prescribed for the wind-heat pattern of urticaria in this study, a large-scale, randomized clinical trial is warranted to research their efficacy and safety. PMID:23947955

Frequency and pattern of Chinese herbal medicine prescriptions for urticaria in Taiwan during 2009: analysis of the national health insurance database.

PubMed

Chien, Pei-Shan; Tseng, Yu-Fang; Hsu, Yao-Chin; Lai, Yu-Kai; Weng, Shih-Feng

2013-08-15

Large-scale pharmaco-epidemiological studies of Chinese herbal medicine (CHM) for treatment of urticaria are few, even though clinical trials showed some CHM are effective. The purpose of this study was to explore the frequencies and patterns of CHM prescriptions for urticaria by analysing the population-based CHM database in Taiwan. This study was linked to and processed through the complete traditional CHM database of the National Health Insurance Research Database in Taiwan during 2009. We calculated the frequencies and patterns of CHM prescriptions used for treatment of urticaria, of which the diagnosis was defined as the single ICD-9 Code of 708. Frequent itemset mining, as applied to data mining, was used to analyse co-prescription of CHM for patients with urticaria. There were 37,386 subjects who visited traditional Chinese Medicine clinics for urticaria in Taiwan during 2009 and received a total of 95,765 CHM prescriptions. Subjects between 18 and 35 years of age comprised the largest number of those treated (32.76%). In addition, women used CHM for urticaria more frequently than men (female:male = 1.94:1). There was an average of 5.54 items prescribed in the form of either individual Chinese herbs or a formula in a single CHM prescription for urticaria. Bai-Xian-Pi (Dictamnus dasycarpus Turcz) was the most commonly prescribed single Chinese herb while Xiao-Feng San was the most commonly prescribed Chinese herbal formula. The most commonly prescribed CHM drug combination was Xiao-Feng San plus Bai-Xian-Pi while the most commonly prescribed triple drug combination was Xiao-Feng San, Bai-Xian-Pi, and Di-Fu Zi (Kochia scoparia). In view of the popularity of CHM such as Xiao-Feng San prescribed for the wind-heat pattern of urticaria in this study, a large-scale, randomized clinical trial is warranted to research their efficacy and safety.

Integrating publicly-available data to generate computationally ...

EPA Pesticide Factsheets

The adverse outcome pathway (AOP) framework provides a way of organizing knowledge related to the key biological events that result in a particular health outcome. For the majority of environmental chemicals, the availability of curated pathways characterizing potential toxicity is limited. Methods are needed to assimilate large amounts of available molecular data and quickly generate putative AOPs for further testing and use in hazard assessment. A graph-based workflow was used to facilitate the integration of multiple data types to generate computationally-predicted (cp) AOPs. Edges between graph entities were identified through direct experimental or literature information or computationally inferred using frequent itemset mining. Data from the TG-GATEs and ToxCast programs were used to channel large-scale toxicogenomics information into a cpAOP network (cpAOPnet) of over 20,000 relationships describing connections between chemical treatments, phenotypes, and perturbed pathways measured by differential gene expression and high-throughput screening targets. Sub-networks of cpAOPs for a reference chemical (carbon tetrachloride, CCl4) and outcome (hepatic steatosis) were extracted using the network topology. Comparison of the cpAOP subnetworks to published mechanistic descriptions for both CCl4 toxicity and hepatic steatosis demonstrate that computational approaches can be used to replicate manually curated AOPs and identify pathway targets that lack genomic mar

A Novel Biclustering Approach to Association Rule Mining for Predicting HIV-1–Human Protein Interactions

PubMed Central

Mukhopadhyay, Anirban; Maulik, Ujjwal; Bandyopadhyay, Sanghamitra

2012-01-01

Identification of potential viral-host protein interactions is a vital and useful approach towards development of new drugs targeting those interactions. In recent days, computational tools are being utilized for predicting viral-host interactions. Recently a database containing records of experimentally validated interactions between a set of HIV-1 proteins and a set of human proteins has been published. The problem of predicting new interactions based on this database is usually posed as a classification problem. However, posing the problem as a classification one suffers from the lack of biologically validated negative interactions. Therefore it will be beneficial to use the existing database for predicting new viral-host interactions without the need of negative samples. Motivated by this, in this article, the HIV-1–human protein interaction database has been analyzed using association rule mining. The main objective is to identify a set of association rules both among the HIV-1 proteins and among the human proteins, and use these rules for predicting new interactions. In this regard, a novel association rule mining technique based on biclustering has been proposed for discovering frequent closed itemsets followed by the association rules from the adjacency matrix of the HIV-1–human interaction network. Novel HIV-1–human interactions have been predicted based on the discovered association rules and tested for biological significance. For validation of the predicted new interactions, gene ontology-based and pathway-based studies have been performed. These studies show that the human proteins which are predicted to interact with a particular viral protein share many common biological activities. Moreover, literature survey has been used for validation purpose to identify some predicted interactions that are already validated experimentally but not present in the database. Comparison with other prediction methods is also discussed. PMID:22539940

An integrative data mining approach to identifying adverse outcome pathway signatures.

PubMed

Oki, Noffisat O; Edwards, Stephen W

2016-03-28

The Adverse Outcome Pathway (AOP) framework is a tool for making biological connections and summarizing key information across different levels of biological organization to connect biological perturbations at the molecular level to adverse outcomes for an individual or population. Computational approaches to explore and determine these connections can accelerate the assembly of AOPs. By leveraging the wealth of publicly available data covering chemical effects on biological systems, computationally-predicted AOPs (cpAOPs) were assembled via data mining of high-throughput screening (HTS) in vitro data, in vivo data and other disease phenotype information. Frequent Itemset Mining (FIM) was used to find associations between the gene targets of ToxCast HTS assays and disease data from Comparative Toxicogenomics Database (CTD) by using the chemicals as the common aggregators between datasets. The method was also used to map gene expression data to disease data from CTD. A cpAOP network was defined by considering genes and diseases as nodes and FIM associations as edges. This network contained 18,283 gene to disease associations for the ToxCast data and 110,253 for CTD gene expression. Two case studies show the value of the cpAOP network by extracting subnetworks focused either on fatty liver disease or the Aryl Hydrocarbon Receptor (AHR). The subnetwork surrounding fatty liver disease included many genes known to play a role in this disease. When querying the cpAOP network with the AHR gene, an interesting subnetwork including glaucoma was identified. While substantial literature exists to support the potential for AHR ligands to elicit glaucoma, it was not explicitly captured in the public annotation information in CTD. The subnetwork from this analysis suggests a cpAOP that includes changes in CYP1B1 expression, which has been previously established in the literature as a primary cause of glaucoma. These case studies highlight the value in integrating multiple data sources when defining cpAOPs for HTS data. Copyright © 2016. Published by Elsevier Ireland Ltd.

Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming.

PubMed

Luna, Jose Maria; Pechenizkiy, Mykola; Del Jesus, Maria Jose; Ventura, Sebastian

2017-09-25

Real-world data usually comprise features whose interpretation depends on some contextual information. Such contextual-sensitive features and patterns are of high interest to be discovered and analyzed in order to obtain the right meaning. This paper formulates the problem of mining context-aware association rules, which refers to the search for associations between itemsets such that the strength of their implication depends on a contextual feature. For the discovery of this type of associations, a model that restricts the search space and includes syntax constraints by means of a grammar-based genetic programming methodology is proposed. Grammars can be considered as a useful way of introducing subjective knowledge to the pattern mining process as they are highly related to the background knowledge of the user. The performance and usefulness of the proposed approach is examined by considering synthetically generated datasets. A posteriori analysis on different domains is also carried out to demonstrate the utility of this kind of associations. For example, in educational domains, it is essential to identify and understand contextual and context-sensitive factors that affect overall and individual student behavior and performance. The results of the experiments suggest that the approach is feasible and it automatically identifies interesting context-aware associations from real-world datasets.

DMET-Miner: Efficient discovery of association rules from pharmacogenomic data.

PubMed

Agapito, Giuseppe; Guzzi, Pietro H; Cannataro, Mario

2015-08-01

Microarray platforms enable the investigation of allelic variants that may be correlated to phenotypes. Among those, the Affymetrix DMET (Drug Metabolism Enzymes and Transporters) platform enables the simultaneous investigation of all the genes that are related to drug absorption, distribution, metabolism and excretion (ADME). Although recent studies demonstrated the effectiveness of the use of DMET data for studying drug response or toxicity in clinical studies, there is a lack of tools for the automatic analysis of DMET data. In a previous work we developed DMET-Analyzer, a methodology and a supporting platform able to automatize the statistical study of allelic variants, that has been validated in several clinical studies. Although DMET-Analyzer is able to correlate a single variant for each probe (related to a portion of a gene) through the use of the Fisher test, it is unable to discover multiple associations among allelic variants, due to its underlying statistic analysis strategy that focuses on a single variant for each time. To overcome those limitations, here we propose a new analysis methodology for DMET data based on Association Rules mining, and an efficient implementation of this methodology, named DMET-Miner. DMET-Miner extends the DMET-Analyzer tool with data mining capabilities and correlates the presence of a set of allelic variants with the conditions of patient's samples by exploiting association rules. To face the high number of frequent itemsets generated when considering large clinical studies based on DMET data, DMET-Miner uses an efficient data structure and implements an optimized search strategy that reduces the search space and the execution time. Preliminary experiments on synthetic DMET datasets, show how DMET-Miner outperforms off-the-shelf data mining suites such as the FP-Growth algorithms available in Weka and RapidMiner. To demonstrate the biological relevance of the extracted association rules and the effectiveness of the proposed approach from a medical point of view, some preliminary studies on a real clinical dataset are currently under medical investigation. Copyright © 2015 Elsevier Inc. All rights reserved.

AprioriGWAS, a new pattern mining strategy for detecting genetic variants associated with disease through interaction effects.

PubMed

Zhang, Qingrun; Long, Quan; Ott, Jurg

2014-06-01

Identifying gene-gene interaction is a hot topic in genome wide association studies. Two fundamental challenges are: (1) how to smartly identify combinations of variants that may be associated with the trait from astronomical number of all possible combinations; and (2) how to test epistatic interaction when all potential combinations are available. We developed AprioriGWAS, which brings two innovations. (1) Based on Apriori, a successful method in field of Frequent Itemset Mining (FIM) in which a pattern growth strategy is leveraged to effectively and accurately reduce search space, AprioriGWAS can efficiently identify genetically associated genotype patterns. (2) To test the hypotheses of epistasis, we adopt a new conditional permutation procedure to obtain reliable statistical inference of Pearson's chi-square test for the [Formula: see text] contingency table generated by associated variants. By applying AprioriGWAS to age-related macular degeneration (AMD) data, we found that: (1) angiopoietin 1 (ANGPT1) and four retinal genes interact with Complement Factor H (CFH). (2) GO term "glycosaminoglycan biosynthetic process" was enriched in AMD interacting genes. The epistatic interactions newly found by AprioriGWAS on AMD data are likely true interactions, since genes interacting with CFH are retinal genes, and GO term enrichment also verified that interaction between glycosaminoglycans (GAGs) and CFH plays an important role in disease pathology of AMD. By applying AprioriGWAS on Bipolar disorder in WTCCC data, we found variants without marginal effect show significant interactions. For example, multiple-SNP genotype patterns inside gene GABRB2 and GRIA1 (AMPA subunit 1 receptor gene). AMPARs are found in many parts of the brain and are the most commonly found receptor in the nervous system. The GABRB2 mediates the fastest inhibitory synaptic transmission in the central nervous system. GRIA1 and GABRB2 are relevant to mental disorders supported by multiple evidences.

DTFP-Growth: Dynamic Threshold-Based FP-Growth Rule Mining Algorithm Through Integrating Gene Expression, Methylation, and Protein-Protein Interaction Profiles.

PubMed

Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan; Mallik, Saurav; Bhadra, Tapas; Mukherji, Ayan

2018-04-01

Association rule mining is an important technique for identifying interesting relationships between gene pairs in a biological data set. Earlier methods basically work for a single biological data set, and, in maximum cases, a single minimum support cutoff can be applied globally, i.e., across all genesets/itemsets. To overcome this limitation, in this paper, we propose dynamic threshold-based FP-growth rule mining algorithm that integrates gene expression, methylation and protein-protein interaction profiles based on weighted shortest distance to find the novel associations among different pairs of genes in multi-view data sets. For this purpose, we introduce three new thresholds, namely, Distance-based Variable/Dynamic Supports (DVS), Distance-based Variable Confidences (DVC), and Distance-based Variable Lifts (DVL) for each rule by integrating co-expression, co-methylation, and protein-protein interactions existed in the multi-omics data set. We develop the proposed algorithm utilizing these three novel multiple threshold measures. In the proposed algorithm, the values of , , and are computed for each rule separately, and subsequently it is verified whether the support, confidence, and lift of each evolved rule are greater than or equal to the corresponding individual , , and values, respectively, or not. If all these three conditions for a rule are found to be true, the rule is treated as a resultant rule. One of the major advantages of the proposed method compared with other related state-of-the-art methods is that it considers both the quantitative and interactive significance among all pairwise genes belonging to each rule. Moreover, the proposed method generates fewer rules, takes less running time, and provides greater biological significance for the resultant top-ranking rules compared to previous methods.

Refining adverse drug reaction signals by incorporating interaction variables identified using emergent pattern mining.

PubMed

Reps, Jenna M; Aickelin, Uwe; Hubbard, Richard B

2016-02-01

To develop a framework for identifying and incorporating candidate confounding interaction terms into a regularised cox regression analysis to refine adverse drug reaction signals obtained via longitudinal observational data. We considered six drug families that are commonly associated with myocardial infarction in observational healthcare data, but where the causal relationship ground truth is known (adverse drug reaction or not). We applied emergent pattern mining to find itemsets of drugs and medical events that are associated with the development of myocardial infarction. These are the candidate confounding interaction terms. We then implemented a cohort study design using regularised cox regression that incorporated and accounted for the candidate confounding interaction terms. The methodology was able to account for signals generated due to confounding and a cox regression with elastic net regularisation correctly ranking the drug families known to be true adverse drug reactions above those that are not. This was not the case without the inclusion of the candidate confounding interaction terms, where confounding leads to a non-adverse drug reaction being ranked highest. The methodology is efficient, can identify high-order confounding interactions and does not require expert input to specify outcome specific confounders, so it can be applied for any outcome of interest to quickly refine its signals. The proposed method shows excellent potential to overcome some forms of confounding and therefore reduce the false positive rate for signal analysis using longitudinal data. Copyright © 2015 Elsevier Ltd. All rights reserved.

Handling Dynamic Weights in Weighted Frequent Pattern Mining

NASA Astrophysics Data System (ADS)

Ahmed, Chowdhury Farhan; Tanbeer, Syed Khairuzzaman; Jeong, Byeong-Soo; Lee, Young-Koo

Even though weighted frequent pattern (WFP) mining is more effective than traditional frequent pattern mining because it can consider different semantic significances (weights) of items, existing WFP algorithms assume that each item has a fixed weight. But in real world scenarios, the weight (price or significance) of an item can vary with time. Reflecting these changes in item weight is necessary in several mining applications, such as retail market data analysis and web click stream analysis. In this paper, we introduce the concept of a dynamic weight for each item, and propose an algorithm, DWFPM (dynamic weighted frequent pattern mining), that makes use of this concept. Our algorithm can address situations where the weight (price or significance) of an item varies dynamically. It exploits a pattern growth mining technique to avoid the level-wise candidate set generation-and-test methodology. Furthermore, it requires only one database scan, so it is eligible for use in stream data mining. An extensive performance analysis shows that our algorithm is efficient and scalable for WFP mining using dynamic weights.

Differentially Private Frequent Subgraph Mining

PubMed Central

Xu, Shengzhi; Xiong, Li; Cheng, Xiang; Xiao, Ke

2016-01-01

Mining frequent subgraphs from a collection of input graphs is an important topic in data mining research. However, if the input graphs contain sensitive information, releasing frequent subgraphs may pose considerable threats to individual's privacy. In this paper, we study the problem of frequent subgraph mining (FGM) under the rigorous differential privacy model. We introduce a novel differentially private FGM algorithm, which is referred to as DFG. In this algorithm, we first privately identify frequent subgraphs from input graphs, and then compute the noisy support of each identified frequent subgraph. In particular, to privately identify frequent subgraphs, we present a frequent subgraph identification approach which can improve the utility of frequent subgraph identifications through candidates pruning. Moreover, to compute the noisy support of each identified frequent subgraph, we devise a lattice-based noisy support derivation approach, where a series of methods has been proposed to improve the accuracy of the noisy supports. Through formal privacy analysis, we prove that our DFG algorithm satisfies ε-differential privacy. Extensive experimental results on real datasets show that the DFG algorithm can privately find frequent subgraphs with high data utility. PMID:27616876

Healthcare information systems: data mining methods in the creation of a clinical recommender system

NASA Astrophysics Data System (ADS)

Duan, L.; Street, W. N.; Xu, E.

2011-05-01

Recommender systems have been extensively studied to present items, such as movies, music and books that are likely of interest to the user. Researchers have indicated that integrated medical information systems are becoming an essential part of the modern healthcare systems. Such systems have evolved to an integrated enterprise-wide system. In particular, such systems are considered as a type of enterprise information systems or ERP system addressing healthcare industry sector needs. As part of efforts, nursing care plan recommender systems can provide clinical decision support, nursing education, clinical quality control, and serve as a complement to existing practice guidelines. We propose to use correlations among nursing diagnoses, outcomes and interventions to create a recommender system for constructing nursing care plans. In the current study, we used nursing diagnosis data to develop the methodology. Our system utilises a prefix-tree structure common in itemset mining to construct a ranked list of suggested care plan items based on previously-entered items. Unlike common commercial systems, our system makes sequential recommendations based on user interaction, modifying a ranked list of suggested items at each step in care plan construction. We rank items based on traditional association-rule measures such as support and confidence, as well as a novel measure that anticipates which selections might improve the quality of future rankings. Since the multi-step nature of our recommendations presents problems for traditional evaluation measures, we also present a new evaluation method based on average ranking position and use it to test the effectiveness of different recommendation strategies.

A construction scheme of web page comment information extraction system based on frequent subtree mining

NASA Astrophysics Data System (ADS)

Zhang, Xiaowen; Chen, Bingfeng

2017-08-01

Based on the frequent sub-tree mining algorithm, this paper proposes a construction scheme of web page comment information extraction system based on frequent subtree mining, referred to as FSM system. The entire system architecture and the various modules to do a brief introduction, and then the core of the system to do a detailed description, and finally give the system prototype.

Research on parallel algorithm for sequential pattern mining

NASA Astrophysics Data System (ADS)

Zhou, Lijuan; Qin, Bai; Wang, Yu; Hao, Zhongxiao

2008-03-01

Sequential pattern mining is the mining of frequent sequences related to time or other orders from the sequence database. Its initial motivation is to discover the laws of customer purchasing in a time section by finding the frequent sequences. In recent years, sequential pattern mining has become an important direction of data mining, and its application field has not been confined to the business database and has extended to new data sources such as Web and advanced science fields such as DNA analysis. The data of sequential pattern mining has characteristics as follows: mass data amount and distributed storage. Most existing sequential pattern mining algorithms haven't considered the above-mentioned characteristics synthetically. According to the traits mentioned above and combining the parallel theory, this paper puts forward a new distributed parallel algorithm SPP(Sequential Pattern Parallel). The algorithm abides by the principal of pattern reduction and utilizes the divide-and-conquer strategy for parallelization. The first parallel task is to construct frequent item sets applying frequent concept and search space partition theory and the second task is to structure frequent sequences using the depth-first search method at each processor. The algorithm only needs to access the database twice and doesn't generate the candidated sequences, which abates the access time and improves the mining efficiency. Based on the random data generation procedure and different information structure designed, this paper simulated the SPP algorithm in a concrete parallel environment and implemented the AprioriAll algorithm. The experiments demonstrate that compared with AprioriAll, the SPP algorithm had excellent speedup factor and efficiency.

Mining algorithm for association rules in big data based on Hadoop

NASA Astrophysics Data System (ADS)

Fu, Chunhua; Wang, Xiaojing; Zhang, Lijun; Qiao, Liying

2018-04-01

In order to solve the problem that the traditional association rules mining algorithm has been unable to meet the mining needs of large amount of data in the aspect of efficiency and scalability, take FP-Growth as an example, the algorithm is realized in the parallelization based on Hadoop framework and Map Reduce model. On the basis, it is improved using the transaction reduce method for further enhancement of the algorithm's mining efficiency. The experiment, which consists of verification of parallel mining results, comparison on efficiency between serials and parallel, variable relationship between mining time and node number and between mining time and data amount, is carried out in the mining results and efficiency by Hadoop clustering. Experiments show that the paralleled FP-Growth algorithm implemented is able to accurately mine frequent item sets, with a better performance and scalability. It can be better to meet the requirements of big data mining and efficiently mine frequent item sets and association rules from large dataset.

Association mining of dependency between time series

NASA Astrophysics Data System (ADS)

Hafez, Alaaeldin

2001-03-01

Time series analysis is considered as a crucial component of strategic control over a broad variety of disciplines in business, science and engineering. Time series data is a sequence of observations collected over intervals of time. Each time series describes a phenomenon as a function of time. Analysis on time series data includes discovering trends (or patterns) in a time series sequence. In the last few years, data mining has emerged and been recognized as a new technology for data analysis. Data Mining is the process of discovering potentially valuable patterns, associations, trends, sequences and dependencies in data. Data mining techniques can discover information that many traditional business analysis and statistical techniques fail to deliver. In this paper, we adapt and innovate data mining techniques to analyze time series data. By using data mining techniques, maximal frequent patterns are discovered and used in predicting future sequences or trends, where trends describe the behavior of a sequence. In order to include different types of time series (e.g. irregular and non- systematic), we consider past frequent patterns of the same time sequences (local patterns) and of other dependent time sequences (global patterns). We use the word 'dependent' instead of the word 'similar' for emphasis on real life time series where two time series sequences could be completely different (in values, shapes, etc.), but they still react to the same conditions in a dependent way. In this paper, we propose the Dependence Mining Technique that could be used in predicting time series sequences. The proposed technique consists of three phases: (a) for all time series sequences, generate their trend sequences, (b) discover maximal frequent trend patterns, generate pattern vectors (to keep information of frequent trend patterns), use trend pattern vectors to predict future time series sequences.

Supporting Solar Physics Research via Data Mining

NASA Astrophysics Data System (ADS)

Angryk, Rafal; Banda, J.; Schuh, M.; Ganesan Pillai, K.; Tosun, H.; Martens, P.

2012-05-01

In this talk we will briefly introduce three pillars of data mining (i.e. frequent patterns discovery, classification, and clustering), and discuss some possible applications of known data mining techniques which can directly benefit solar physics research. In particular, we plan to demonstrate applicability of frequent patterns discovery methods for the verification of hypotheses about co-occurrence (in space and time) of filaments and sigmoids. We will also show how classification/machine learning algorithms can be utilized to verify human-created software modules to discover individual types of solar phenomena. Finally, we will discuss applicability of clustering techniques to image data processing.

Customizing FP-growth algorithm to parallel mining with Charm++ library

NASA Astrophysics Data System (ADS)

Puścian, Marek

2017-08-01

This paper presents a frequent item mining algorithm that was customized to handle growing data repositories. The proposed solution applies Master Slave scheme to frequent pattern growth technique. Efficient utilization of available computation units is achieved by dynamic reallocation of tasks. Conditional frequent trees are assigned to parallel workers basing on their workload. Proposed enhancements have been successfully implemented using Charm++ library. This paper discusses results of the performance of parallelized FP-growth algorithm against different datasets. The approach has been illustrated with many experiments and measurements performed using multiprocessor and multithreaded computer.

Data Mining in Social Media

NASA Astrophysics Data System (ADS)

Barbier, Geoffrey; Liu, Huan

The rise of online social media is providing a wealth of social network data. Data mining techniques provide researchers and practitioners the tools needed to analyze large, complex, and frequently changing social media data. This chapter introduces the basics of data mining, reviews social media, discusses how to mine social media data, and highlights some illustrative examples with an emphasis on social networking sites and blogs.

Combined mining: discovering informative knowledge in complex data.

PubMed

Cao, Longbing; Zhang, Huaifeng; Zhao, Yanchang; Luo, Dan; Zhang, Chengqi

2011-06-01

Enterprise data mining applications often involve complex data such as multiple large heterogeneous data sources, user preferences, and business impact. In such situations, a single method or one-step mining is often limited in discovering informative knowledge. It would also be very time and space consuming, if not impossible, to join relevant large data sources for mining patterns consisting of multiple aspects of information. It is crucial to develop effective approaches for mining patterns combining necessary information from multiple relevant business lines, catering for real business settings and decision-making actions rather than just providing a single line of patterns. The recent years have seen increasing efforts on mining more informative patterns, e.g., integrating frequent pattern mining with classifications to generate frequent pattern-based classifiers. Rather than presenting a specific algorithm, this paper builds on our existing works and proposes combined mining as a general approach to mining for informative patterns combining components from either multiple data sets or multiple features or by multiple methods on demand. We summarize general frameworks, paradigms, and basic processes for multifeature combined mining, multisource combined mining, and multimethod combined mining. Novel types of combined patterns, such as incremental cluster patterns, can result from such frameworks, which cannot be directly produced by the existing methods. A set of real-world case studies has been conducted to test the frameworks, with some of them briefed in this paper. They identify combined patterns for informing government debt prevention and improving government service objectives, which show the flexibility and instantiation capability of combined mining in discovering informative knowledge in complex data.

Integrative relational machine-learning for understanding drug side-effect profiles

PubMed Central

2013-01-01

Background Drug side effects represent a common reason for stopping drug development during clinical trials. Improving our ability to understand drug side effects is necessary to reduce attrition rates during drug development as well as the risk of discovering novel side effects in available drugs. Today, most investigations deal with isolated side effects and overlook possible redundancy and their frequent co-occurrence. Results In this work, drug annotations are collected from SIDER and DrugBank databases. Terms describing individual side effects reported in SIDER are clustered with a semantic similarity measure into term clusters (TCs). Maximal frequent itemsets are extracted from the resulting drug x TC binary table, leading to the identification of what we call side-effect profiles (SEPs). A SEP is defined as the longest combination of TCs which are shared by a significant number of drugs. Frequent SEPs are explored on the basis of integrated drug and target descriptors using two machine learning methods: decision-trees and inductive-logic programming. Although both methods yield explicit models, inductive-logic programming method performs relational learning and is able to exploit not only drug properties but also background knowledge. Learning efficiency is evaluated by cross-validation and direct testing with new molecules. Comparison of the two machine-learning methods shows that the inductive-logic-programming method displays a greater sensitivity than decision trees and successfully exploit background knowledge such as functional annotations and pathways of drug targets, thereby producing rich and expressive rules. All models and theories are available on a dedicated web site. Conclusions Side effect profiles covering significant number of drugs have been extracted from a drug ×side-effect association table. Integration of background knowledge concerning both chemical and biological spaces has been combined with a relational learning method for discovering rules which explicitly characterize drug-SEP associations. These rules are successfully used for predicting SEPs associated with new drugs. PMID:23802887

Integrative relational machine-learning for understanding drug side-effect profiles.

PubMed

Bresso, Emmanuel; Grisoni, Renaud; Marchetti, Gino; Karaboga, Arnaud Sinan; Souchet, Michel; Devignes, Marie-Dominique; Smaïl-Tabbone, Malika

2013-06-26

Drug side effects represent a common reason for stopping drug development during clinical trials. Improving our ability to understand drug side effects is necessary to reduce attrition rates during drug development as well as the risk of discovering novel side effects in available drugs. Today, most investigations deal with isolated side effects and overlook possible redundancy and their frequent co-occurrence. In this work, drug annotations are collected from SIDER and DrugBank databases. Terms describing individual side effects reported in SIDER are clustered with a semantic similarity measure into term clusters (TCs). Maximal frequent itemsets are extracted from the resulting drug x TC binary table, leading to the identification of what we call side-effect profiles (SEPs). A SEP is defined as the longest combination of TCs which are shared by a significant number of drugs. Frequent SEPs are explored on the basis of integrated drug and target descriptors using two machine learning methods: decision-trees and inductive-logic programming. Although both methods yield explicit models, inductive-logic programming method performs relational learning and is able to exploit not only drug properties but also background knowledge. Learning efficiency is evaluated by cross-validation and direct testing with new molecules. Comparison of the two machine-learning methods shows that the inductive-logic-programming method displays a greater sensitivity than decision trees and successfully exploit background knowledge such as functional annotations and pathways of drug targets, thereby producing rich and expressive rules. All models and theories are available on a dedicated web site. Side effect profiles covering significant number of drugs have been extracted from a drug ×side-effect association table. Integration of background knowledge concerning both chemical and biological spaces has been combined with a relational learning method for discovering rules which explicitly characterize drug-SEP associations. These rules are successfully used for predicting SEPs associated with new drugs.

Recommending Learning Activities in Social Network Using Data Mining Algorithms

ERIC Educational Resources Information Center

Mahnane, Lamia

2017-01-01

In this paper, we show how data mining algorithms (e.g. Apriori Algorithm (AP) and Collaborative Filtering (CF)) is useful in New Social Network (NSN-AP-CF). "NSN-AP-CF" processes the clusters based on different learning styles. Next, it analyzes the habits and the interests of the users through mining the frequent episodes by the…

An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks.

PubMed

He, Jieyue; Wang, Chunyan; Qiu, Kunpu; Zhong, Wei

2014-01-01

Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. The algorithm of probability graph isomorphism evaluation based on circuit simulation method excludes most of subgraphs which are not probability isomorphism and reduces the search space of the probability isomorphism subgraphs using the mismatch values in the node voltage set. It is an innovative way to find the frequent probability patterns, which can be efficiently applied to probability motif discovery problems in the further studies.

An novel frequent probability pattern mining algorithm based on circuit simulation method in uncertain biological networks

PubMed Central

2014-01-01

Background Motif mining has always been a hot research topic in bioinformatics. Most of current research on biological networks focuses on exact motif mining. However, due to the inevitable experimental error and noisy data, biological network data represented as the probability model could better reflect the authenticity and biological significance, therefore, it is more biological meaningful to discover probability motif in uncertain biological networks. One of the key steps in probability motif mining is frequent pattern discovery which is usually based on the possible world model having a relatively high computational complexity. Methods In this paper, we present a novel method for detecting frequent probability patterns based on circuit simulation in the uncertain biological networks. First, the partition based efficient search is applied to the non-tree like subgraph mining where the probability of occurrence in random networks is small. Then, an algorithm of probability isomorphic based on circuit simulation is proposed. The probability isomorphic combines the analysis of circuit topology structure with related physical properties of voltage in order to evaluate the probability isomorphism between probability subgraphs. The circuit simulation based probability isomorphic can avoid using traditional possible world model. Finally, based on the algorithm of probability subgraph isomorphism, two-step hierarchical clustering method is used to cluster subgraphs, and discover frequent probability patterns from the clusters. Results The experiment results on data sets of the Protein-Protein Interaction (PPI) networks and the transcriptional regulatory networks of E. coli and S. cerevisiae show that the proposed method can efficiently discover the frequent probability subgraphs. The discovered subgraphs in our study contain all probability motifs reported in the experiments published in other related papers. Conclusions The algorithm of probability graph isomorphism evaluation based on circuit simulation method excludes most of subgraphs which are not probability isomorphism and reduces the search space of the probability isomorphism subgraphs using the mismatch values in the node voltage set. It is an innovative way to find the frequent probability patterns, which can be efficiently applied to probability motif discovery problems in the further studies. PMID:25350277

Discovery of spatio-temporal patterns from location-based social networks

NASA Astrophysics Data System (ADS)

Béjar, J.; Álvarez, S.; García, D.; Gómez, I.; Oliva, L.; Tejeda, A.; Vázquez-Salceda, J.

2016-03-01

Location-based social networks (LBSNs) such as Twitter or Instagram are a good source for user spatio-temporal behaviour. These networks collect data from users in such a way that they can be seen as a set of collective and distributed sensors of a geographical area. A low rate sampling of user's location information can be obtained during large intervals of time that can be used to discover complex patterns, including mobility profiles, points of interest or unusual events. These patterns can be used as the elements of a knowledge base for different applications in different domains such as mobility route planning, touristic recommendation systems or city planning. The aim of this paper is twofold, first to analyse the frequent spatio-temporal patterns that users share when living and visiting a city. This behaviour is studied by means of frequent itemsets algorithms in order to establish some associations among visits that can be interpreted as interesting routes or spatio-temporal connections. Second, to analyse how the spatio-temporal behaviour of a large number of users can be segmented in different profiles. These behavioural profiles are obtained by means of clustering algorithms that show the different patterns of behaviour of visitors and citizens. The data analysed were obtained from the public data feeds of Twitter and Instagram within an area surrounding the cities of Barcelona and Milan for a period of several months. The analysis of these data shows that these kinds of algorithms can be successfully applied to data from any city (or general area) to discover useful patterns that can be interpreted on terms of singular places and areas and their temporal relationships.

Nurse staffing levels and outcomes - mining the UK national data sets for insight.

PubMed

Leary, Alison; Tomai, Barbara; Swift, Adrian; Woodward, Andrew; Hurst, Keith

2017-04-18

Purpose Despite the generation of mass data by the nursing workforce, determining the impact of the contribution to patient safety remains challenging. Several cross-sectional studies have indicated a relationship between staffing and safety. The purpose of this paper is to uncover possible associations and explore if a deeper understanding of relationships between staffing and other factors such as safety could be revealed within routinely collected national data sets. Design/methodology/approach Two longitudinal routinely collected data sets consisting of 30 years of UK nurse staffing data and seven years of National Health Service (NHS) benchmark data such as survey results, safety and other indicators were used. A correlation matrix was built and a linear correlation operation was applied (Pearson product-moment correlation coefficient). Findings A number of associations were revealed within both the UK staffing data set and the NHS benchmarking data set. However, the challenges of using these data sets soon became apparent. Practical implications Staff time and effort are required to collect these data. The limitations of these data sets include inconsistent data collection and quality. The mode of data collection and the itemset collected should be reviewed to generate a data set with robust clinical application. Originality/value This paper revealed that relationships are likely to be complex and non-linear; however, the main contribution of the paper is the identification of the limitations of routinely collected data. Much time and effort is expended in collecting this data; however, its validity, usefulness and method of routine national data collection appear to require re-examination.

Mining with Rare Cases

NASA Astrophysics Data System (ADS)

Weiss, Gary M.

Rare cases are often the most interesting cases. For example, in medical diagnosis one is typically interested in identifying relatively rare diseases, such as cancer, rather than more frequently occurring ones, such as the common cold. In this chapter we discuss the role of rare cases in Data Mining. Specific problems associated with mining rare cases are discussed, followed by a description of methods for addressing these problems.

Differentially Private Frequent Sequence Mining via Sampling-based Candidate Pruning

PubMed Central

Xu, Shengzhi; Cheng, Xiang; Li, Zhengyi; Xiong, Li

2016-01-01

In this paper, we study the problem of mining frequent sequences under the rigorous differential privacy model. We explore the possibility of designing a differentially private frequent sequence mining (FSM) algorithm which can achieve both high data utility and a high degree of privacy. We found, in differentially private FSM, the amount of required noise is proportionate to the number of candidate sequences. If we could effectively reduce the number of unpromising candidate sequences, the utility and privacy tradeoff can be significantly improved. To this end, by leveraging a sampling-based candidate pruning technique, we propose a novel differentially private FSM algorithm, which is referred to as PFS2. The core of our algorithm is to utilize sample databases to further prune the candidate sequences generated based on the downward closure property. In particular, we use the noisy local support of candidate sequences in the sample databases to estimate which sequences are potentially frequent. To improve the accuracy of such private estimations, a sequence shrinking method is proposed to enforce the length constraint on the sample databases. Moreover, to decrease the probability of misestimating frequent sequences as infrequent, a threshold relaxation method is proposed to relax the user-specified threshold for the sample databases. Through formal privacy analysis, we show that our PFS2 algorithm is ε-differentially private. Extensive experiments on real datasets illustrate that our PFS2 algorithm can privately find frequent sequences with high accuracy. PMID:26973430

Quantifying Associations between Environmental Stressors and Demographic Factors

EPA Science Inventory

Association rule mining (ARM) [1-3], also known as frequent item set mining [4] or market basket analysis [1], has been widely applied in many different areas, such as business product portfolio planning [5], intrusion detection infrastructure design [6], gene expression analysis...

The prevalence of selected potentially hazardous workplace exposures in the US: findings from the 2010 National Health Interview Survey.

PubMed

Calvert, Geoffrey M; Luckhaupt, Sara E; Sussell, Aaron; Dahlhamer, James M; Ward, Brian W

2013-06-01

Assess the national prevalence of current workplace exposure to potential skin hazards, secondhand smoke (SHS), and outdoor work among various industry and occupation groups. Also, assess the national prevalence of chronic workplace exposure to vapors, gas, dust, and fumes (VGDF) among these groups. Data were obtained from the 2010 National Health Interview Survey (NHIS). NHIS is a multistage probability sample survey of the civilian non-institutionalized population of the US. Prevalence rates and their variances were calculated using SUDAAN to account for the complex NHIS sample design. The data for 2010 were available for 17,524 adults who worked in the 12 months that preceded interview. The highest prevalence rates of hazardous workplace exposures were typically in agriculture, mining, and construction. The prevalence rate of frequent handling of or skin contact with chemicals, and of non-smokers frequently exposed to SHS at work was highest in mining and construction. Outdoor work was most common in agriculture (85%), construction (73%), and mining (65%). Finally, frequent occupational exposure to VGDF was most common among mining (67%), agriculture (53%), and construction workers (51%). We identified industries and occupations with the highest prevalence of potentially hazardous workplace exposures, and provided targets for investigation and intervention activities. Copyright © 2012 Wiley Periodicals, Inc.

The Prevalence of Selected Potentially Hazardous Workplace Exposures in the US: Findings From the 2010 National Health Interview Survey

PubMed Central

Calvert, Geoffrey M.; Luckhaupt, Sara E.; Sussell, Aaron; Dahlhamer, James M.; Ward, Brian W.

2015-01-01

Objective Assess the national prevalence of current workplace exposure to potential skin hazards, secondhand smoke (SHS), and outdoor work among various industry and occupation groups. Also, assess the national prevalence of chronic workplace exposure to vapors, gas, dust, and fumes (VGDF) among these groups. Methods Data were obtained from the 2010 National Health Interview Survey (NHIS). NHIS is a multistage probability sample survey of the civilian non-institutionalized population of the US. Prevalence rates and their variances were calculated using SUDAAN to account for the complex NHIS sample design. Results The data for 2010 were available for 17,524 adults who worked in the 12 months that preceded interview. The highest prevalence rates of hazardous workplace exposures were typically in agriculture, mining, and construction. The prevalence rate of frequent handling of or skin contact with chemicals, and of non-smokers frequently exposed to SHS at work was highest in mining and construction. Outdoor work was most common in agriculture (85%), construction (73%), and mining (65%). Finally, frequent occupational exposure to VGDF was most common among mining (67%), agriculture (53%), and construction workers (51%). Conclusion We identified industries and occupations with the highest prevalence of potentially hazardous workplace exposures, and provided targets for investigation and intervention activities. PMID:22821700

General health status of residents of the Selebi Phikwe Ni-Cu mine area, Botswana.

PubMed

Ekosse, Georges

2005-10-01

Residents of the Selebi Phikwe area, Botswana where nickel-copper (Ni-Cu) is being exploited often exhibit symptoms of varied degrees of ailments, sicknesses and diseases. A need to investigate their general health status was therefore eminent. Primary data was obtained by means of a questionnaire and structured interviews conducted with individuals, health service providers, business enterprises and educational Institutions. The generated data revealed common ailments, sicknesses and diseases in the area with the four most frequent health complaints being frequent coughing headaches, influenza/common colds and rampant chest pains. Research findings indicated that residents had respiratory tract-related problems, suspected to be linked to the effects of air pollution caused by the emission of sulphur dioxide (SO2) from mining and smelting activities. Residents were frequently in contact with SO2 and related gases and fumes, mineral and silica dust generated from the mining processes. No clearly demarcating differences were noticed in the health status of residents living in the control site from those in the main study area. However, sites most affected were those close to where Ni-Cu is exploited. Environmental factors resulting from mining and smelting activities, among others, could be contributory to the negative health effects occurring at Selebi Phikwe.

Risky Business: Factor Analysis of Survey Data – Assessing the Probability of Incorrect Dimensionalisation

PubMed Central

van der Eijk, Cees; Rose, Jonathan

2015-01-01

This paper undertakes a systematic assessment of the extent to which factor analysis the correct number of latent dimensions (factors) when applied to ordered-categorical survey items (so-called Likert items). We simulate 2400 data sets of uni-dimensional Likert items that vary systematically over a range of conditions such as the underlying population distribution, the number of items, the level of random error, and characteristics of items and item-sets. Each of these datasets is factor analysed in a variety of ways that are frequently used in the extant literature, or that are recommended in current methodological texts. These include exploratory factor retention heuristics such as Kaiser’s criterion, Parallel Analysis and a non-graphical scree test, and (for exploratory and confirmatory analyses) evaluations of model fit. These analyses are conducted on the basis of Pearson and polychoric correlations. We find that, irrespective of the particular mode of analysis, factor analysis applied to ordered-categorical survey data very often leads to over-dimensionalisation. The magnitude of this risk depends on the specific way in which factor analysis is conducted, the number of items, the properties of the set of items, and the underlying population distribution. The paper concludes with a discussion of the consequences of over-dimensionalisation, and a brief mention of alternative modes of analysis that are much less prone to such problems. PMID:25789992

Mining High-Dimensional Data

NASA Astrophysics Data System (ADS)

Wang, Wei; Yang, Jiong

With the rapid growth of computational biology and e-commerce applications, high-dimensional data becomes very common. Thus, mining high-dimensional data is an urgent problem of great practical importance. However, there are some unique challenges for mining data of high dimensions, including (1) the curse of dimensionality and more crucial (2) the meaningfulness of the similarity measure in the high dimension space. In this chapter, we present several state-of-art techniques for analyzing high-dimensional data, e.g., frequent pattern mining, clustering, and classification. We will discuss how these methods deal with the challenges of high dimensionality.

30 CFR 57.5002 - Exposure monitoring.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Exposure monitoring. 57.5002 Section 57.5002 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE... monitoring. Dust, gas, mist, and fume surveys shall be conducted as frequently as necessary to determine the...

Analyzing Teaching Performance of Instructors Using Data Mining Techniques

ERIC Educational Resources Information Center

Mardikyan, Sona; Badur, Bertain

2011-01-01

Student evaluations to measure the teaching effectiveness of instructor's are very frequently applied in higher education for many years. This study investigates the factors associated with the assessment of instructors teaching performance using two different data mining techniques; stepwise regression and decision trees. The data collected…

Identification of Work-Related Musculoskeletal Disorders in Mining

PubMed Central

Weston, Eric; Pollard, Jonisha P.

2016-01-01

Work-related musculoskeletal disorder (WMSD) prevention measures have been studied in great depth throughout various industries. While the nature and causes of these disorders have been characterized in many industries, WMSDs occurring in the U.S. mining sector have not been characterized for several years. In this report, MSHA accident/injury/illness data from 2009 to 2013 were characterized to determine the most frequently reported WMSDs in the U.S. mining sector. WMSDs were most frequently reported in workers with less than 5 years or more than 20 years of mining experience. The number of days lost from work was the highest for shoulder and knee injuries and was found to increase with worker age. Underground and surface coal, surface stone and stone processing plants experienced the greatest number of WMSDs over the period studied. WMSDs were most commonly caused by an employee suffering from an overexertion, falls or being struck by an object while performing materials handling, maintenance and repair tasks, getting on or off equipment or machines, and walking or running. The injury trends presented should be used to help determine the focus of future WMSD prevention research in mining. PMID:27294012

Comparative Data Mining Analysis for Information Retrieval of MODIS Images: Monitoring Lake Turbidity Changes at Lake Okeechobee, Florida

EPA Science Inventory

In the remote sensing field, a frequently recurring question is: Which computational intelligence or data mining algorithms are most suitable for the retrieval of essential information given that most natural systems exhibit very high non-linearity. Among potential candidates mig...

Binary Coded Web Access Pattern Tree in Education Domain

ERIC Educational Resources Information Center

Gomathi, C.; Moorthi, M.; Duraiswamy, K.

2008-01-01

Web Access Pattern (WAP), which is the sequence of accesses pursued by users frequently, is a kind of interesting and useful knowledge in practice. Sequential Pattern mining is the process of applying data mining techniques to a sequential database for the purposes of discovering the correlation relationships that exist among an ordered list of…

An Adaptive Sensor Mining Framework for Pervasive Computing Applications

NASA Astrophysics Data System (ADS)

Rashidi, Parisa; Cook, Diane J.

Analyzing sensor data in pervasive computing applications brings unique challenges to the KDD community. The challenge is heightened when the underlying data source is dynamic and the patterns change. We introduce a new adaptive mining framework that detects patterns in sensor data, and more importantly, adapts to the changes in the underlying model. In our framework, the frequent and periodic patterns of data are first discovered by the Frequent and Periodic Pattern Miner (FPPM) algorithm; and then any changes in the discovered patterns over the lifetime of the system are discovered by the Pattern Adaptation Miner (PAM) algorithm, in order to adapt to the changing environment. This framework also captures vital context information present in pervasive computing applications, such as the startup triggers and temporal information. In this paper, we present a description of our mining framework and validate the approach using data collected in the CASAS smart home testbed.

Application-Specific Graph Sampling for Frequent Subgraph Mining and Community Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Purohit, Sumit; Choudhury, Sutanay; Holder, Lawrence B.

Graph mining is an important data analysis methodology, but struggles as the input graph size increases. The scalability and usability challenges posed by such large graphs make it imperative to sample the input graph and reduce its size. The critical challenge in sampling is to identify the appropriate algorithm to insure the resulting analysis does not suffer heavily from the data reduction. Predicting the expected performance degradation for a given graph and sampling algorithm is also useful. In this paper, we present different sampling approaches for graph mining applications such as Frequent Subgrpah Mining (FSM), and Community Detection (CD). Wemore » explore graph metrics such as PageRank, Triangles, and Diversity to sample a graph and conclude that for heterogeneous graphs Triangles and Diversity perform better than degree based metrics. We also present two new sampling variations for targeted graph mining applications. We present empirical results to show that knowledge of the target application, along with input graph properties can be used to select the best sampling algorithm. We also conclude that performance degradation is an abrupt, rather than gradual phenomena, as the sample size decreases. We present the empirical results to show that the performance degradation follows a logistic function.« less

Integrated field and laboratory tests to evaluate effects of metals-impacted wetlands on amphibians: A case study from Montana

USGS Publications Warehouse

Linder, G.; ,

2003-01-01

Mining activities frequently impact wildlife habitats, and a wide range of habitats may require evaluations of the linkages between wildlife and environmental stressors common to mining activities (e.g., physical alteration of habitat, releases of chemicals such as metals and other inorganic constituents as part of the mining operation). Wetlands, for example, are frequently impacted by mining activities. Within an ecological assessment for a wetland, toxicity evaluations for representative species may be advantageous to the site evaluation, since these species could be exposed to complex chemical mixtures potentially released from the site. Amphibian species common to these transition zones between terrestrial and aquatic habitats are one key biological indicator of exposure, and integrated approaches which involve both field and laboratory methods focused on amphibians are critical to the assessment process. The laboratory and field evaluations of a wetland in western Montana illustrates the integrated approach to risk assessment and causal analysis. Here, amphibians were used to evaluate the potential toxicity associated with heavy metal-laden sediments deposited in a reservoir. Field and laboratory methods were applied to a toxicity assessment for metals characteristic of mine tailings to reduce potential "lab to field" extrapolation errors and provide adaptive management programs with critical site-specific information targeted on remediation.

Determination of Abutment Pressure in Coal Mines with Extremely Thick Alluvium Stratum: A Typical Kind of Rockburst Mines in China

NASA Astrophysics Data System (ADS)

Zhu, Sitao; Feng, Yu; Jiang, Fuxing

2016-05-01

This paper investigates the abutment pressure distribution in coal mines with extremely thick alluvium stratum (ETAS), which is a typical kind of mines encountering frequent intense rockbursts in China. This occurs due to poor understanding to abutment pressure distribution pattern and the consequent inappropriate mine design. In this study, a theoretical computational model of abutment pressure for ETAS longwall panels is proposed based on the analysis of load transfer mechanisms of key stratum (KS) and ETAS. The model was applied to determine the abutment pressure distribution of LW2302S in Xinjulong Coal Mine; the results of stress and microseismic monitoring verified the rationality of this model. The calculated abutment pressure of LW2302S was also used in the terminal mining line design of LW2301N for rockburst prevention, successfully protecting the main roadway from the adverse influence of the abutment pressure.

Safety Psychology Applicating on Coal Mine Safety Management Based on Information System

NASA Astrophysics Data System (ADS)

Hou, Baoyue; Chen, Fei

In recent years, with the increase of intensity of coal mining, a great number of major accidents happen frequently, the reason mostly due to human factors, but human's unsafely behavior are affected by insecurity mental control. In order to reduce accidents, and to improve safety management, with the help of application security psychology, we analyse the cause of insecurity psychological factors from human perception, from personality development, from motivation incentive, from reward and punishment mechanism, and from security aspects of mental training , and put forward countermeasures to promote coal mine safety production,and to provide information for coal mining to improve the level of safety management.

Integrating Entropy and Closed Frequent Pattern Mining for Social Network Modelling and Analysis

NASA Astrophysics Data System (ADS)

Adnan, Muhaimenul; Alhajj, Reda; Rokne, Jon

The recent increase in the explicitly available social networks has attracted the attention of the research community to investigate how it would be possible to benefit from such a powerful model in producing effective solutions for problems in other domains where the social network is implicit; we argue that social networks do exist around us but the key issue is how to realize and analyze them. This chapter presents a novel approach for constructing a social network model by an integrated framework that first preparing the data to be analyzed and then applies entropy and frequent closed patterns mining for network construction. For a given problem, we first prepare the data by identifying items and transactions, which arc the basic ingredients for frequent closed patterns mining. Items arc main objects in the problem and a transaction is a set of items that could exist together at one time (e.g., items purchased in one visit to the supermarket). Transactions could be analyzed to discover frequent closed patterns using any of the well-known techniques. Frequent closed patterns have the advantage that they successfully grab the inherent information content of the dataset and is applicable to a broader set of domains. Entropies of the frequent closed patterns arc used to keep the dimensionality of the feature vectors to a reasonable size; it is a kind of feature reduction process. Finally, we analyze the dynamic behavior of the constructed social network. Experiments were conducted on a synthetic dataset and on the Enron corpus email dataset. The results presented in the chapter show that social networks extracted from a feature set as frequent closed patterns successfully carry the community structure information. Moreover, for the Enron email dataset, we present an analysis to dynamically indicate the deviations from each user's individual and community profile. These indications of deviations can be very useful to identify unusual events.

Preliminary evidence for good psychometric properties of the Norwegian version of the Brief Problems Monitor (BPM).

PubMed

Richter, Jörg

2015-04-01

Methods to assess intervention progress and outcome for frequent use are needed. To provide preliminary information about psychometric properties for the Norwegian version of the Brief Problems Monitor. Cronbach's alpha scores and intra-class correlation coefficients as indicators for internal consistency (reliability) and Pearson correlation coefficients between corresponding subscales of the long and short ASEBA form versions as well as multiple regression coefficients to explore the predictive power of the reduced item-set related to the corresponding scale-scores of the long version were calculated in large, representative data sets of Norwegian children and adolescents. Cronbach's alpha scores of the Norwegian version of the BPM subscales varied between 0.67 (attention BPM-youth) and 0.88 (attention BPM-teacher) and between 0.90 (BPM-youth) and 0.96 (BPM-teacher) for its total problem score. Corresponding subscales from the long versions and the BPM as well as the total problems scores were closely correlated with coefficients of high effect size (all r > 0.80). The variance of the items of the BPM explained about three-quarters or more of the variance in the corresponding subscales of the long version. The Norwegian BPM has good psychometric properties in terms of 1) being acceptable to good internal consistency and in terms of 2) regression coefficients of high effect size from the BPM items to the problem-scale scores of the long versions as validity indicators. Its use in clinical practice and research can be recommended.

Estimating the Importance of Terrorists in a Terror Network

NASA Astrophysics Data System (ADS)

Elhajj, Ahmed; Elsheikh, Abdallah; Addam, Omar; Alzohbi, Mohamad; Zarour, Omar; Aksaç, Alper; Öztürk, Orkun; Özyer, Tansel; Ridley, Mick; Alhajj, Reda

While criminals may start their activities at individual level, the same is in general not true for terrorists who are mostly organized in well established networks. The effectiveness of a terror network could be realized by watching many factors, including the volume of activities accomplished by its members, the capabilities of its members to hide, and the ability of the network to grow and to maintain its influence even after the loss of some members, even leaders. Social network analysis, data mining and machine learning techniques could play important role in measuring the effectiveness of a network in general and in particular a terror network in support of the work presented in this chapter. We present a framework that employs clustering, frequent pattern mining and some social network analysis measures to determine the effectiveness of a network. The clustering and frequent pattern mining techniques start with the adjacency matrix of the network. For clustering, we utilize entries in the table by considering each row as an object and each column as a feature. Thus features of a network member are his/her direct neighbors. We maintain the weight of links in case of weighted network links. For frequent pattern mining, we consider each row of the adjacency matrix as a transaction and each column as an item. Further, we map entries into a 0/1 scale such that every entry whose value is greater than zero is assigned the value one; entries keep the value zero otherwise. This way we can apply frequent pattern mining algorithms to determine the most influential members in a network as well as the effect of removing some members or even links between members of a network. We also investigate the effect of adding some links between members. The target is to study how the various members in the network change role as the network evolves. This is measured by applying some social network analysis measures on the network at each stage during the development. We report some interesting results related to two benchmark networks: the first is 9/11 and the second is Madrid bombing.

Careflow Mining Techniques to Explore Type 2 Diabetes Evolution.

PubMed

Dagliati, Arianna; Tibollo, Valentina; Cogni, Giulia; Chiovato, Luca; Bellazzi, Riccardo; Sacchi, Lucia

2018-03-01

In this work we describe the application of a careflow mining algorithm to detect the most frequent patterns of care in a type 2 diabetes patients cohort. The applied method enriches the detected patterns with clinical data to define temporal phenotypes across the studied population. Novel phenotypes are discovered from heterogeneous data of 424 Italian patients, and compared in terms of metabolic control and complications. Results show that careflow mining can help to summarize the complex evolution of the disease into meaningful patterns, which are also significant from a clinical point of view.

A New Approach for Mining Order-Preserving Submatrices Based on All Common Subsequences.

PubMed

Xue, Yun; Liao, Zhengling; Li, Meihang; Luo, Jie; Kuang, Qiuhua; Hu, Xiaohui; Li, Tiechen

2015-01-01

Order-preserving submatrices (OPSMs) have been applied in many fields, such as DNA microarray data analysis, automatic recommendation systems, and target marketing systems, as an important unsupervised learning model. Unfortunately, most existing methods are heuristic algorithms which are unable to reveal OPSMs entirely in NP-complete problem. In particular, deep OPSMs, corresponding to long patterns with few supporting sequences, incur explosive computational costs and are completely pruned by most popular methods. In this paper, we propose an exact method to discover all OPSMs based on frequent sequential pattern mining. First, an existing algorithm was adjusted to disclose all common subsequence (ACS) between every two row sequences, and therefore all deep OPSMs will not be missed. Then, an improved data structure for prefix tree was used to store and traverse ACS, and Apriori principle was employed to efficiently mine the frequent sequential pattern. Finally, experiments were implemented on gene and synthetic datasets. Results demonstrated the effectiveness and efficiency of this method.

SPMBR: a scalable algorithm for mining sequential patterns based on bitmaps

NASA Astrophysics Data System (ADS)

Xu, Xiwei; Zhang, Changhai

2013-12-01

Now some sequential patterns mining algorithms generate too many candidate sequences, and increase the processing cost of support counting. Therefore, we present an effective and scalable algorithm called SPMBR (Sequential Patterns Mining based on Bitmap Representation) to solve the problem of mining the sequential patterns for large databases. Our method differs from previous related works of mining sequential patterns. The main difference is that the database of sequential patterns is represented by bitmaps, and a simplified bitmap structure is presented firstly. In this paper, First the algorithm generate candidate sequences by SE(Sequence Extension) and IE(Item Extension), and then obtain all frequent sequences by comparing the original bitmap and the extended item bitmap .This method could simplify the problem of mining the sequential patterns and avoid the high processing cost of support counting. Both theories and experiments indicate that the performance of SPMBR is predominant for large transaction databases, the required memory size for storing temporal data is much less during mining process, and all sequential patterns can be mined with feasibility.

Data Mining and Homeland Security: An Overview

DTIC Science & Technology

2007-01-18

originally collected. A fourth issue is privacy. Questions that may be considered include the degree to which government agencies should use and mix...commercial data with government data, whether data sources are being used for purposes other than those for which they were originally designed, and...unique or frequently represented. For example, a hardware CRS-2 3 John Makulowich, “ Government Data Mining Systems Defy Definition,” Washington

Surface Mining and Reclamation Effects on Flood Response of Watersheds in the Central Appalachian Plateau Region

NASA Technical Reports Server (NTRS)

Ferrari, J. R.; Lookingbill, T. R.; McCormick, B.; Townsend, P. A.; Eshleman, K. N.

2009-01-01

Surface mining of coal and subsequent reclamation represent the dominant land use change in the central Appalachian Plateau (CAP) region of the United States. Hydrologic impacts of surface mining have been studied at the plot scale, but effects at broader scales have not been explored adequately. Broad-scale classification of reclaimed sites is difficult because standing vegetation makes them nearly indistinguishable from alternate land uses. We used a land cover data set that accurately maps surface mines for a 187-km2 watershed within the CAP. These land cover data, as well as plot-level data from within the watershed, are used with HSPF (Hydrologic Simulation Program-Fortran) to estimate changes in flood response as a function of increased mining. Results show that the rate at which flood magnitude increases due to increased mining is linear, with greater rates observed for less frequent return intervals. These findings indicate that mine reclamation leaves the landscape in a condition more similar to urban areas rather than does simple deforestation, and call into question the effectiveness of reclamation in terms of returning mined areas to the hydrological state that existed before mining.

Application of remote-sensing techniques to hydrologic studies in selected coal-mine areas of southeastern Kansas

USGS Publications Warehouse

Kenny, J.F.; McCauley, J.R.

1983-01-01

Disturbances resulting from intensive coal mining in the Cherry Creek basin of southeastern Kansas were investigated using color and color-infrared aerial photography in conjunction with water-quality data from simultaneously acquired samples. Imagery was used to identify the type and extent of vegetative cover on strip-mined lands and the extent and success of reclamation practices. Drainage patterns, point sources of acid mine drainage, and recharge areas for underground mines were located for onsite inspection. Comparison of these interpretations with water-quality data illustrated differences between the eastern and western parts of the Cherry Creek basin. Contamination in the eastern part is due largely to circulation of water from unreclaimed strip mines and collapse features through the network of underground mines and subsequent discharge of acidic drainage through seeps. Contamination in the western part is primarily caused by runoff and seepage from strip-mined lands in which surfaces have frequently been graded and limed but are generally devoid of mature stands of soil-anchoring vegetation. The successful use of aerial photography in the study of Cherry Creek basin indicates the potential of using remote-sensing techniques in studies of other coal-mined regions. (USGS)

Pattern Discovery and Change Detection of Online Music Query Streams

NASA Astrophysics Data System (ADS)

Li, Hua-Fu

In this paper, an efficient stream mining algorithm, called FTP-stream (Frequent Temporal Pattern mining of streams), is proposed to find the frequent temporal patterns over melody sequence streams. In the framework of our proposed algorithm, an effective bit-sequence representation is used to reduce the time and memory needed to slide the windows. The FTP-stream algorithm can calculate the support threshold in only a single pass based on the concept of bit-sequence representation. It takes the advantage of "left" and "and" operations of the representation. Experiments show that the proposed algorithm only scans the music query stream once, and runs significant faster and consumes less memory than existing algorithms, such as SWFI-stream and Moment.

Data Mining and Homeland Security: An Overview

DTIC Science & Technology

2007-03-28

originally collected. A fourth issue is privacy. Questions that may be considered include the degree to which government agencies should use and mix...commercial data with government data, whether data sources are being used for purposes other than those for which they were originally designed, and...frequently represented. For example, a hardware CRS-2 3 John Makulowich, “ Government Data Mining Systems Defy Definition,” Washington Technology, 22 February

Assertions of Japanese Websites for and Against Cancer Screening: a Text Mining Analysis

PubMed

Okuhara, Tsuyoshi; Ishikawa, Hirono; Okada, Masahumi; Kato, Mio; Kiuchi, Takahiro

2017-04-01

Background: Cancer screening rates are lower in Japan than in Western countries such as the United States and the United Kingdom. While health professionals publish pro-cancer-screening messages online to encourage proactive seeking for screening, anti-screening activists use the same medium to warn readers against following guidelines. Contents of pro- and anti-cancer-screening sites may contribute to readers’ acceptance of one or the other position. We aimed to use a text-mining method to examine frequently appearing contents on sites for and against cancer screening. Methods: We conducted online searches in December 2016 using two major search engines in Japan (Google Japan and Yahoo! Japan). Targeted websites were classified as “pro”, “anti”, or “neutral” depending on their claims, with the author(s) classified as “health professional”, “mass media”, or “layperson”. Text-mining analyses were conducted, and statistical analysis was performed using the chi-square test. Results: Of the 169 websites analyzed, the top-three most frequently appearing content topics in pro sites were reducing mortality via cancer screening, benefits of early detection, and recommendations for obtaining detailed examination. The top three most frequent in anti-sites were harm from radiation exposure, non-efficacy of cancer screening, and lack of necessity of early detection. Anti-sites also frequently referred to a well-known Japanese radiologist, Makoto Kondo, who rejects the standard forms of cancer care. Conclusion: Our findings should enable authors of pro-cancer-screening sites to write to counter misleading anti-cancer-screening messages and facilitate dissemination of accurate information. Creative Commons Attribution License

Privacy Preserving Nearest Neighbor Search

NASA Astrophysics Data System (ADS)

Shaneck, Mark; Kim, Yongdae; Kumar, Vipin

Data mining is frequently obstructed by privacy concerns. In many cases data is distributed, and bringing the data together in one place for analysis is not possible due to privacy laws (e.g. HIPAA) or policies. Privacy preserving data mining techniques have been developed to address this issue by providing mechanisms to mine the data while giving certain privacy guarantees. In this chapter we address the issue of privacy preserving nearest neighbor search, which forms the kernel of many data mining applications. To this end, we present a novel algorithm based on secure multiparty computation primitives to compute the nearest neighbors of records in horizontally distributed data. We show how this algorithm can be used in three important data mining algorithms, namely LOF outlier detection, SNN clustering, and kNN classification. We prove the security of these algorithms under the semi-honest adversarial model, and describe methods that can be used to optimize their performance. Keywords: Privacy Preserving Data Mining, Nearest Neighbor Search, Outlier Detection, Clustering, Classification, Secure Multiparty Computation

Large Scale Frequent Pattern Mining using MPI One-Sided Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vishnu, Abhinav; Agarwal, Khushbu

In this paper, we propose a work-stealing runtime --- Library for Work Stealing LibWS --- using MPI one-sided model for designing scalable FP-Growth --- {\\em de facto} frequent pattern mining algorithm --- on large scale systems. LibWS provides locality efficient and highly scalable work-stealing techniques for load balancing on a variety of data distributions. We also propose a novel communication algorithm for FP-growth data exchange phase, which reduces the communication complexity from state-of-the-art O(p) to O(f + p/f) for p processes and f frequent attributed-ids. FP-Growth is implemented using LibWS and evaluated on several work distributions and support counts. Anmore » experimental evaluation of the FP-Growth on LibWS using 4096 processes on an InfiniBand Cluster demonstrates excellent efficiency for several work distributions (87\\% efficiency for Power-law and 91% for Poisson). The proposed distributed FP-Tree merging algorithm provides 38x communication speedup on 4096 cores.« less

Japanese anti- versus pro-influenza vaccination websites: a text-mining analysis.

PubMed

Okuhara, Tsuyoshi; Ishikawa, Hirono; Okada, Masafumi; Kato, Mio; Kiuchi, Takahiro

2018-03-23

Anti-vaccination sentiment exists worldwide and Japan is no exception. Health professionals publish pro-influenza vaccination messages online to encourage proactive seeking of influenza vaccination. However, influenza vaccine coverage among the Japanese population is less than optimal. The contents of pro- and anti-influenza vaccination websites may contribute to readers' acceptance of one or the other position. We aimed to use a text-mining method to examine frequently appearing content on websites for and against influenza vaccination. We conducted online searches in January 2017 using two major Japanese search engines (Google Japan and Yahoo! Japan). Targeted websites were classified as 'pro', 'anti' or 'neutral' depending on their claims, with author(s) classified as 'health professionals', 'mass media' or 'laypersons'. Text-mining analysis was conducted, and statistical analysis was performed using a chi-squared test. Of the 334 websites analyzed, 13 content topics were identified. The three most frequently appearing content topics on pro-vaccination websites were vaccination effect for preventing serious cases of influenza, side effects of vaccination, and efficacy rate of vaccination. The three most frequent topics on anti-vaccination websites were ineffectiveness of influenza vaccination, toxicity of vaccination, and side effects of vaccination. The main disseminators of each topic, by author classification, were also revealed. We discuss possible tactics of online influenza vaccination promotion to counter anti-vaccination websites.

Discovering amino acid patterns on binding sites in protein complexes

PubMed Central

Kuo, Huang-Cheng; Ong, Ping-Lin; Lin, Jung-Chang; Huang, Jen-Peng

2011-01-01

Discovering amino acid (AA) patterns on protein binding sites has recently become popular. We propose a method to discover the association relationship among AAs on binding sites. Such knowledge of binding sites is very helpful in predicting protein-protein interactions. In this paper, we focus on protein complexes which have protein-protein recognition. The association rule mining technique is used to discover geographically adjacent amino acids on a binding site of a protein complex. When mining, instead of treating all AAs of binding sites as a transaction, we geographically partition AAs of binding sites in a protein complex. AAs in a partition are treated as a transaction. For the partition process, AAs on a binding site are projected from three-dimensional to two-dimensional. And then, assisted with a circular grid, AAs on the binding site are placed into grid cells. A circular grid has ten rings: a central ring, the second ring with 6 sectors, the third ring with 12 sectors, and later rings are added to four sectors in order. As for the radius of each ring, we examined the complexes and found that 10Å is a suitable range, which can be set by the user. After placing these recognition complexes on the circular grid, we obtain mining records (i.e. transactions) from each sector. A sector is regarded as a record. Finally, we use the association rule to mine these records for frequent AA patterns. If the support of an AA pattern is larger than the predetermined minimum support (i.e. threshold), it is called a frequent pattern. With these discovered patterns, we offer the biologists a novel point of view, which will improve the prediction accuracy of protein-protein recognition. In our experiments, we produced the AA patterns by data mining. As a result, we found that arginine (arg) most frequently appears on the binding sites of two proteins in the recognition protein complexes, while cysteine (cys) appears the fewest. In addition, if we discriminate the shape of binding sites between concave and convex further, we discover that patterns {arg, glu, asp} and {arg, ser, asp} on the concave shape of binding sites in a protein more frequently (i.e. higher probability) make contact with {lys} or {arg} on the convex shape of binding sites in another protein. Thus, we can confidently achieve a rate of at least 78%. On the other hand {val, gly, lys} on the convex surface of binding sites in proteins is more frequently in contact with {asp} on the concave site of another protein, and the confidence achieved is over 81%. Applying data mining in biology can reveal more facts that may otherwise be ignored or not easily discovered by the naked eye. Furthermore, we can discover more relationships among AAs on binding sites by appropriately rotating these residues on binding sites from a three-dimension to two-dimension perspective. We designed a circular grid to deposit the data, which total to 463 records consisting of AAs. Then we used the association rules to mine these records for discovering relationships. The proposed method in this paper provides an insight into the characteristics of binding sites for recognition complexes. PMID:21464838

Assessing Lightning and Wildfire Hazard by Land Properties and Cloud to Ground Lightning Data with Association Rule Mining in Alberta, Canada

PubMed Central

Cha, DongHwan; Wang, Xin; Kim, Jeong Woo

2017-01-01

Hotspot analysis was implemented to find regions in the province of Alberta (Canada) with high frequency Cloud to Ground (CG) lightning strikes clustered together. Generally, hotspot regions are located in the central, central east, and south central regions of the study region. About 94% of annual lightning occurred during warm months (June to August) and the daily lightning frequency was influenced by the diurnal heating cycle. The association rule mining technique was used to investigate frequent CG lightning patterns, which were verified by similarity measurement to check the patterns’ consistency. The similarity coefficient values indicated that there were high correlations throughout the entire study period. Most wildfires (about 93%) in Alberta occurred in forests, wetland forests, and wetland shrub areas. It was also found that lightning and wildfires occur in two distinct areas: frequent wildfire regions with a high frequency of lightning, and frequent wild-fire regions with a low frequency of lightning. Further, the preference index (PI) revealed locations where the wildfires occurred more frequently than in other class regions. The wildfire hazard area was estimated with the CG lightning hazard map and specific land use types. PMID:29065564

Assessing Lightning and Wildfire Hazard by Land Properties and Cloud to Ground Lightning Data with Association Rule Mining in Alberta, Canada.

PubMed

Cha, DongHwan; Wang, Xin; Kim, Jeong Woo

2017-10-23

Hotspot analysis was implemented to find regions in the province of Alberta (Canada) with high frequency Cloud to Ground (CG) lightning strikes clustered together. Generally, hotspot regions are located in the central, central east, and south central regions of the study region. About 94% of annual lightning occurred during warm months (June to August) and the daily lightning frequency was influenced by the diurnal heating cycle. The association rule mining technique was used to investigate frequent CG lightning patterns, which were verified by similarity measurement to check the patterns' consistency. The similarity coefficient values indicated that there were high correlations throughout the entire study period. Most wildfires (about 93%) in Alberta occurred in forests, wetland forests, and wetland shrub areas. It was also found that lightning and wildfires occur in two distinct areas: frequent wildfire regions with a high frequency of lightning, and frequent wild-fire regions with a low frequency of lightning. Further, the preference index (PI) revealed locations where the wildfires occurred more frequently than in other class regions. The wildfire hazard area was estimated with the CG lightning hazard map and specific land use types.

Comparison between BIDE, PrefixSpan, and TRuleGrowth for Mining of Indonesian Text

NASA Astrophysics Data System (ADS)

Sa'adillah Maylawati, Dian; Irfan, Mohamad; Budiawan Zulfikar, Wildan

2017-01-01

Mining proscess for Indonesian language still be an interesting research. Multiple of words representation was claimed can keep the meaning of text better than bag of words. In this paper, we compare several sequential pattern algortihm, among others BIDE (BIDirectional Extention), PrefixSpan, and TRuleGrowth. All of those algorithm produce frequent word sequence to keep the meaning of text. However, the experiment result, with 14.006 of Indonesian tweet from Twitter, shows that BIDE can produce more efficient frequent word sequence than PrefixSpan and TRuleGrowth without missing the meaning of text. Then, the average of time process of PrefixSpan is faster than BIDE and TRuleGrowth. In the other hand, PrefixSpan and TRuleGrowth is more efficient in using memory than BIDE.

[Basic Regularities and Characteristics of Compound Reinforcing--reducing Manipulation of Acu- puncture Revealed by Data Mining].

PubMed

Yang, Qing-qing; Jia, Chun-sheng; Wang, Jian-ling; Li, Jun-lei; Feng, Xin-xin; Tan, Zhan-na; Li, Bo-ying; Zhu, Xue-liang; Shi, Jing; Sun, Yan-hui; Li, Xiao-feng; Xu, Jing; Zhang, Xuan-ping; Zhang, Xin; Du, Yu-zhu; Bao, Na; Wang, Qiong

2016-04-01

To explore the regularities and features of compound reinforcing-reducing manipulation of acupuncture filiform needles in the treatment of clinical conditions or diseases by using data mining technique, so as to guide clinical practice. At first, the data base about the reinforcing-reducing manipulation (CRRM) of filiform needles for different clinical problems was established by collection, sorting, screening, recording, collation, data extraction of the related original papers published in journals and conferences and related academic dissertations from Jan. 1 of 1950 to Jan. 31 of 2015 by using key words of "acupuncture" "moxibustion" "needling" "filiform needle", and according to the included and excluded standards. A total of 130 835 papers met the included standards were collected. Outcomes of data mining in the present study showed that (1) the ORRM is most frequently applied in the internal medicine, followed by surgery, gynecology, ophthalmology and otorhinolaryngology, dermatology, and pediatrics, successively, mostly for lumbago and leg pain; (2) the heat-producing needling manipulation is the most frequently applied technique, followed by cool-producing needling, dragon-tiger warring, yang occluding in yin, yin occluding in yang techniques; (3) the highest effective rate of CRRM is for problems of the pediatrics, followed by those of the internal medicine, surgery, ophthalmology and otorhinolaryngology, dermatology, and gynecology; (4) the most fre- quently used acupoints are Zusanli (ST 36), then Sanyinjiao (SP 6), stimulated by heat-producing needling, and Zusanli (ST 36), then Quchi (LI 11), stimulated by cool-producing needling, and Huantiao (GB 30), stimulated by dragon-tiger warring needling. The compound reinforcing-reducing manipulation of acupuncture is most frequently applied to problems in the inter- nal medicine, predominately for lumbago and leg pain, and the best effectiveness is for pediatric conditions. The heat-producing needling and cool-producing needling are most frequently applied at Zusanli (ST 36) and the dragon-tiger warring manipulation is most frequently applied at Huantiao (GB 30).

The Distribution and Status of Bats at Fort Irwin National Training Center

DTIC Science & Technology

2012-12-01

the Avawatz Mountains (Table 9) in the vicinity of Goat Mountain are more human accessible due to their close proximity to roads. Troops are currently...altitudinally, (Grinnell 1918, Krutzsch 1948, Cryan 2003) and are often the species most frequently killed at wind farms . For southern California...As noted in the results section, the current level of bat use was similar at the Desert King Mine and the Avawatz mines near Goat Mountain as was

Microbial diversity at the moderate acidic stage in three different sulfidic mine tailings dumps generating acid mine drainage.

PubMed

Korehi, Hananeh; Blöthe, Marco; Schippers, Axel

2014-11-01

In freshly deposited sulfidic mine tailings the pH is alkaline or circumneutral. Due to pyrite or pyrrhotite oxidation the pH is dropping over time to pH values <3 at which acidophilic iron- and sulfur-oxidizing prokaryotes prevail and accelerate the oxidation processes, well described for several mine waste sites. The microbial communities at the moderate acidic stage in mine tailings are only scarcely studied. Here we investigated the microbial diversity via 16S rRNA gene sequence analysis in eight samples (pH range 3.2-6.5) from three different sulfidic mine tailings dumps in Botswana, Germany and Sweden. In total 701 partial 16S rRNA gene sequences revealed a divergent microbial community between the three sites and at different tailings depths. Proteobacteria and Firmicutes were overall the most abundant phyla in the clone libraries. Acidobacteria, Actinobacteria, Bacteroidetes, and Nitrospira occurred less frequently. The found microbial communities were completely different to microbial communities in tailings at

Mining Productive-Associated Periodic-Frequent Patterns in Body Sensor Data for Smart Home Care

PubMed Central

Ismail, Walaa N.; Hassan, Mohammad Mehedi

2017-01-01

The understanding of various health-oriented vital sign data generated from body sensor networks (BSNs) and discovery of the associations between the generated parameters is an important task that may assist and promote important decision making in healthcare. For example, in a smart home scenario where occupants’ health status is continuously monitored remotely, it is essential to provide the required assistance when an unusual or critical situation is detected in their vital sign data. In this paper, we present an efficient approach for mining the periodic patterns obtained from BSN data. In addition, we employ a correlation test on the generated patterns and introduce productive-associated periodic-frequent patterns as the set of correlated periodic-frequent items. The combination of these measures has the advantage of empowering healthcare providers and patients to raise the quality of diagnosis as well as improve treatment and smart care, especially for elderly people in smart homes. We develop an efficient algorithm named PPFP-growth (Productive Periodic-Frequent Pattern-growth) to discover all productive-associated periodic frequent patterns using these measures. PPFP-growth is efficient and the productiveness measure removes uncorrelated periodic items. An experimental evaluation on synthetic and real datasets shows the efficiency of the proposed PPFP-growth algorithm, which can filter a huge number of periodic patterns to reveal only the correlated ones. PMID:28445441

Mining Productive-Associated Periodic-Frequent Patterns in Body Sensor Data for Smart Home Care.

PubMed

Ismail, Walaa N; Hassan, Mohammad Mehedi

2017-04-26

The understanding of various health-oriented vital sign data generated from body sensor networks (BSNs) and discovery of the associations between the generated parameters is an important task that may assist and promote important decision making in healthcare. For example, in a smart home scenario where occupants' health status is continuously monitored remotely, it is essential to provide the required assistance when an unusual or critical situation is detected in their vital sign data. In this paper, we present an efficient approach for mining the periodic patterns obtained from BSN data. In addition, we employ a correlation test on the generated patterns and introduce productive-associated periodic-frequent patterns as the set of correlated periodic-frequent items. The combination of these measures has the advantage of empowering healthcare providers and patients to raise the quality of diagnosis as well as improve treatment and smart care, especially for elderly people in smart homes. We develop an efficient algorithm named PPFP-growth (Productive Periodic-Frequent Pattern-growth) to discover all productive-associated periodic frequent patterns using these measures. PPFP-growth is efficient and the productiveness measure removes uncorrelated periodic items. An experimental evaluation on synthetic and real datasets shows the efficiency of the proposed PPFP-growth algorithm, which can filter a huge number of periodic patterns to reveal only the correlated ones.

Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis.

PubMed

Alonzo, Michael; Van Den Hoek, Jamon; Ahmed, Nabil

2016-10-11

The socio-ecological impacts of large scale resource extraction are frequently underreported in underdeveloped regions. The open-pit Grasberg mine in Papua, Indonesia, is one of the world's largest copper and gold extraction operations. Grasberg mine tailings are discharged into the lowland Ajkwa River deposition area (ADA) leading to forest inundation and degradation of water bodies critical to indigenous peoples. The extent of the changes and temporal linkages with mining activities are difficult to establish given restricted access to the region and persistent cloud cover. Here, we introduce remote sensing methods to "peer through" atmospheric contamination using a dense Landsat time series to simultaneously quantify forest loss and increases in estuarial suspended particulate matter (SPM) concentration. We identified 138 km 2 of forest loss between 1987 and 2014, an area >42 times larger than the mine itself. Between 1987 and 1998, the rate of disturbance was highly correlated (Pearson's r = 0.96) with mining activity. Following mine expansion and levee construction along the ADA in the mid-1990s, we recorded significantly (p < 0.05) higher SPM in the Ajkwa Estuary compared to neighboring estuaries. This research provides a means to quantify multiple modes of ecological damage from mine waste disposal or other disturbance events.

Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis

PubMed Central

Alonzo, Michael; Van Den Hoek, Jamon; Ahmed, Nabil

2016-01-01

The socio-ecological impacts of large scale resource extraction are frequently underreported in underdeveloped regions. The open-pit Grasberg mine in Papua, Indonesia, is one of the world’s largest copper and gold extraction operations. Grasberg mine tailings are discharged into the lowland Ajkwa River deposition area (ADA) leading to forest inundation and degradation of water bodies critical to indigenous peoples. The extent of the changes and temporal linkages with mining activities are difficult to establish given restricted access to the region and persistent cloud cover. Here, we introduce remote sensing methods to “peer through” atmospheric contamination using a dense Landsat time series to simultaneously quantify forest loss and increases in estuarial suspended particulate matter (SPM) concentration. We identified 138 km2 of forest loss between 1987 and 2014, an area >42 times larger than the mine itself. Between 1987 and 1998, the rate of disturbance was highly correlated (Pearson’s r = 0.96) with mining activity. Following mine expansion and levee construction along the ADA in the mid-1990s, we recorded significantly (p < 0.05) higher SPM in the Ajkwa Estuary compared to neighboring estuaries. This research provides a means to quantify multiple modes of ecological damage from mine waste disposal or other disturbance events. PMID:27725748

Capturing coupled riparian and coastal disturbance from industrial mining using cloud-resilient satellite time series analysis

NASA Astrophysics Data System (ADS)

Alonzo, Michael; van den Hoek, Jamon; Ahmed, Nabil

2016-10-01

The socio-ecological impacts of large scale resource extraction are frequently underreported in underdeveloped regions. The open-pit Grasberg mine in Papua, Indonesia, is one of the world’s largest copper and gold extraction operations. Grasberg mine tailings are discharged into the lowland Ajkwa River deposition area (ADA) leading to forest inundation and degradation of water bodies critical to indigenous peoples. The extent of the changes and temporal linkages with mining activities are difficult to establish given restricted access to the region and persistent cloud cover. Here, we introduce remote sensing methods to “peer through” atmospheric contamination using a dense Landsat time series to simultaneously quantify forest loss and increases in estuarial suspended particulate matter (SPM) concentration. We identified 138 km2 of forest loss between 1987 and 2014, an area >42 times larger than the mine itself. Between 1987 and 1998, the rate of disturbance was highly correlated (Pearson’s r = 0.96) with mining activity. Following mine expansion and levee construction along the ADA in the mid-1990s, we recorded significantly (p < 0.05) higher SPM in the Ajkwa Estuary compared to neighboring estuaries. This research provides a means to quantify multiple modes of ecological damage from mine waste disposal or other disturbance events.

Adaptive semantic tag mining from heterogeneous clinical research texts.

PubMed

Hao, T; Weng, C

2015-01-01

To develop an adaptive approach to mine frequent semantic tags (FSTs) from heterogeneous clinical research texts. We develop a "plug-n-play" framework that integrates replaceable unsupervised kernel algorithms with formatting, functional, and utility wrappers for FST mining. Temporal information identification and semantic equivalence detection were two example functional wrappers. We first compared this approach's recall and efficiency for mining FSTs from ClinicalTrials.gov to that of a recently published tag-mining algorithm. Then we assessed this approach's adaptability to two other types of clinical research texts: clinical data requests and clinical trial protocols, by comparing the prevalence trends of FSTs across three texts. Our approach increased the average recall and speed by 12.8% and 47.02% respectively upon the baseline when mining FSTs from ClinicalTrials.gov, and maintained an overlap in relevant FSTs with the base- line ranging between 76.9% and 100% for varying FST frequency thresholds. The FSTs saturated when the data size reached 200 documents. Consistent trends in the prevalence of FST were observed across the three texts as the data size or frequency threshold changed. This paper contributes an adaptive tag-mining framework that is scalable and adaptable without sacrificing its recall. This component-based architectural design can be potentially generalizable to improve the adaptability of other clinical text mining methods.

Remote mineral mapping using AVIRIS data at Summitville, Colorado and the adjacent San Juan Mountains

NASA Technical Reports Server (NTRS)

King, Trude V. V.; Clark, Roger N.; Ager, Cathy; Swayze, Gregg A.

1995-01-01

We have demonstrated the unique utility of imaging spectroscopy in mapping mineral distribution. In the Summitville mining region we have shown that the mine site does not contribute clay minerals to the Alamosa River, but does contribute Fe-bearing minerals. Such minerals have the potential to carry heavy metals. This application illustrates only one specific environmental application of imaging spectroscopy data. For instance, the types of minerals we can map with confidence are those frequently associated with environmental problems related to active and abandoned mine lands. Thus, the potential utility of this technology to the field of environmental science has yet to be fully explored.

Natural thorium resources and recovery: Options and impacts

USGS Publications Warehouse

Ault, Timothy; Van Gosen, Bradley S.; Krahn, Steven; Croff, Allen

2016-01-01

This paper reviews the front end of the thorium fuel cycle, including the extent and variety of thorium deposits, the potential sources of thorium production, and the physical and chemical technologies required to isolate and purify thorium. Thorium is frequently found within rare earth element–bearing minerals that exist in diverse types of mineral deposits, often in conjunction with other minerals mined for their commercial value. It may be possible to recover substantial quantities of thorium as a by-product from active titanium, uranium, tin, iron, and rare earth mines. Incremental physical and chemical processing is required to obtain a purified thorium product from thorium minerals, but documented experience with these processes is extensive, and incorporating thorium recovery should not be overly challenging. The anticipated environmental impacts of by-product thorium recovery are small relative to those of uranium recovery since existing mining infrastructure utilization avoids the opening and operation of new mines and thorium recovery removes radionuclides from the mining tailings.

Dietary patterns analysis using data mining method. An application to data from the CYKIDS study.

PubMed

Lazarou, Chrystalleni; Karaolis, Minas; Matalas, Antonia-Leda; Panagiotakos, Demosthenes B

2012-11-01

Data mining is a computational method that permits the extraction of patterns from large databases. We applied the data mining approach in data from 1140 children (9-13 years), in order to derive dietary habits related to children's obesity status. Rules emerged via data mining approach revealed the detrimental influence of the increased consumption of soft dinks, delicatessen meat, sweets, fried and junk food. For example, frequent (3-5 times/week) consumption of all these foods increases the risk for being obese by 75%, whereas in children who have a similar dietary pattern, but eat >2 times/week fish and seafood the risk for obesity is reduced by 33%. In conclusion patterns revealed from data mining technique refer to specific groups of children and demonstrate the effect on the risk associated with obesity status when a single dietary habit might be modified. Thus, a more individualized approach when translating public health messages could be achieved. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Moving Equipment and Workers to Mine Construction Site at a Logistically Challenged Area

NASA Astrophysics Data System (ADS)

Tikasz, Laszlo; Biroscak, Dennis; Pentiah, Scheale Duvah; McCulloch, Robert I.

Social sensitivity of habitants, minimal impact on the environment, low-grade infrastructure, high altitude, frequent rock slides combined with expectations for the timely moving of equipment and workers are some of the challenges emerging from the current construction of a mine. Starting with traditional planning, and experiencing issues in the early phase of the construction, a traffic simulator was requested by the Procurement Department in order to validate daily-weekly schedules and predict likely delays or blockages on the long-term.

Contents of Japanese pro- and anti-HPV vaccination websites: A text mining analysis.

PubMed

Okuhara, Tsuyoshi; Ishikawa, Hirono; Okada, Masahumi; Kato, Mio; Kiuchi, Takahiro

2018-03-01

In Japan, the human papillomavirus (HPV) vaccination rate has sharply fallen to nearly 0% due to sensational media reports of adverse events. Online anti-HPV-vaccination activists often warn readers of the vaccine's dangers. Here, we aimed to examine frequently appearing contents on pro- and anti-HPV vaccination websites. We conducted online searches via two major search engines (Google Japan and Yahoo! Japan). Targeted websites were classified as "pro," "anti," or "neutral" according to their claims, with the author(s) classified as "health professionals," "mass media," or "laypersons." We then conducted a text mining analysis. Of the 270 sites analyzed, 16 contents were identified. The most frequently appearing contents on pro websites were vaccine side effects, preventable effect of vaccination, and cause of cervical cancer. The most frequently appearing contents on anti websites were vaccine side effects, vaccine toxicity, and girls who suffer from vaccine side effects. Main disseminators of each content according to the author's expertise were also revealed. Pro-HPV vaccination websites should supplement deficient contents and respond to frequent contents on anti-HPV websites. Effective tactics are needed to better communicate susceptibility to cervical cancer, frequency of side effects, and responses to vaccine toxicity and conspiracy theories. Copyright © 2017 Elsevier B.V. All rights reserved.

Tree-based approach for exploring marine spatial patterns with raster datasets.

PubMed

Liao, Xiaohan; Xue, Cunjin; Su, Fenzhen

2017-01-01

From multiple raster datasets to spatial association patterns, the data-mining technique is divided into three subtasks, i.e., raster dataset pretreatment, mining algorithm design, and spatial pattern exploration from the mining results. Comparison with the former two subtasks reveals that the latter remains unresolved. Confronted with the interrelated marine environmental parameters, we propose a Tree-based Approach for eXploring Marine Spatial Patterns with multiple raster datasets called TAXMarSP, which includes two models. One is the Tree-based Cascading Organization Model (TCOM), and the other is the Spatial Neighborhood-based CAlculation Model (SNCAM). TCOM designs the "Spatial node→Pattern node" from top to bottom layers to store the table-formatted frequent patterns. Together with TCOM, SNCAM considers the spatial neighborhood contributions to calculate the pattern-matching degree between the specified marine parameters and the table-formatted frequent patterns and then explores the marine spatial patterns. Using the prevalent quantification Apriori algorithm and a real remote sensing dataset from January 1998 to December 2014, a successful application of TAXMarSP to marine spatial patterns in the Pacific Ocean is described, and the obtained marine spatial patterns present not only the well-known but also new patterns to Earth scientists.

A Comparative Study of Frequent and Maximal Periodic Pattern Mining Algorithms in Spatiotemporal Databases

NASA Astrophysics Data System (ADS)

Obulesu, O.; Rama Mohan Reddy, A., Dr; Mahendra, M.

2017-08-01

Detecting regular and efficient cyclic models is the demanding activity for data analysts due to unstructured, vigorous and enormous raw information produced from web. Many existing approaches generate large candidate patterns in the occurrence of huge and complex databases. In this work, two novel algorithms are proposed and a comparative examination is performed by considering scalability and performance parameters. The first algorithm is, EFPMA (Extended Regular Model Detection Algorithm) used to find frequent sequential patterns from the spatiotemporal dataset and the second one is, ETMA (Enhanced Tree-based Mining Algorithm) for detecting effective cyclic models with symbolic database representation. EFPMA is an algorithm grows models from both ends (prefixes and suffixes) of detected patterns, which results in faster pattern growth because of less levels of database projection compared to existing approaches such as Prefixspan and SPADE. ETMA uses distinct notions to store and manage transactions data horizontally such as segment, sequence and individual symbols. ETMA exploits a partition-and-conquer method to find maximal patterns by using symbolic notations. Using this algorithm, we can mine cyclic models in full-series sequential patterns including subsection series also. ETMA reduces the memory consumption and makes use of the efficient symbolic operation. Furthermore, ETMA only records time-series instances dynamically, in terms of character, series and section approaches respectively. The extent of the pattern and proving efficiency of the reducing and retrieval techniques from synthetic and actual datasets is a really open & challenging mining problem. These techniques are useful in data streams, traffic risk analysis, medical diagnosis, DNA sequence Mining, Earthquake prediction applications. Extensive investigational outcomes illustrates that the algorithms outperforms well towards efficiency and scalability than ECLAT, STNR and MAFIA approaches.

[Analysis of on medication rules for Qi-deficiency and blood-stasis syndrome of chronic heart failure based on data mining technology].

PubMed

Wang, Qian; Yao, Geng-Zhen; Pan, Guang-Ming; Huang, Jing-Yi; An, Yi-Pei; Zou, Xu

2017-01-01

To analyze the medication features and the regularity of prescriptions of traditional Chinese medicine in treating patients with Qi-deficiency and blood-stasis syndrome of chronic heart failure based on modern literature. In this article, CNKI Chinese academic journal database, Wanfang Chinese academic journal database and VIP Chinese periodical database were all searched from January 2000 to December 2015 for the relevant literature on traditional Chinese medicine treatment for Qi-deficiency and blood-stasis syndrome of chronic heart failure. Then a normalized database was established for further data mining and analysis. Subsequently, the medication features and the regularity of prescriptions were mined by using traditional Chinese medicine inheritance support system(V2.5), association rules, improved mutual information algorithm, complex system entropy clustering and other mining methods. Finally, a total of 171 articles were included, involving 171 prescriptions, 140 kinds of herbs, with a total frequency of 1 772 for the herbs. As a result, 19 core prescriptions and 7 new prescriptions were mined. The most frequently used herbs included Huangqi(Astragali Radix), Danshen(Salviae Miltiorrhizae Radix et Rhizoma), Fuling(Poria), Renshen(Ginseng Radix et Rhizoma), Tinglizi(Semen Lepidii), Baizhu(Atractylodis Macrocephalae Rhizoma), and Guizhi(Cinnamomum Ramulus). The core prescriptions were composed of Huangqi(Astragali Radix), Danshen(Salviae Miltiorrhizae Radix et Rhizoma) and Fuling(Poria), etc. The high frequent herbs and core prescriptions not only highlight the medication features of Qi-invigorating and blood-circulating therapy, but also reflect the regularity of prescriptions of blood-circulating, Yang-warming, and urination-promoting therapy based on syndrome differentiation. Moreover, the mining of the new prescriptions provide new reference and inspiration for clinical treatment of various accompanying symptoms of chronic heart failure. In conclusion, this article provides new reference for traditional Chinese medicine in the treatment of chronic heart failure. Copyright© by the Chinese Pharmaceutical Association.

Mining in low coal. Volume 1. Biomechanics and work physiology. Open file report 15 Jun 78-15 Sep 81

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ayoub, M.M.; Bethea, N.J.; Bobo, M.

1981-11-01

The objectives of this research were (1) to evaluate the job demands associated with low coal mining, (2) to survey the anthropometry, strength, and aerobic capacity of low coal miners to determine if they differ from the U.S. population, and (3) to recommend, on the basis of available information, optimal job and work station design for low coal mining. The male and female anthropometry, except for weight and circumferential dimensions, was quite similar to the comparison populations. Back strength for male and female miners was significantly lower than the industrial worker population. This can be one of the contributing factorsmore » of low back problems in mining. Shoveling, timbering, and helpers tasks were physiologically demanding activities. However, because of the frequent stoppage of work, adequate rest was usually available. If work stoppage is corrected, then better work and rest schedules are essential.« less

Subnetwork mining on functional connectivity network for classification of minimal hepatic encephalopathy.

PubMed

Zhang, Daoqiang; Tu, Liyang; Zhang, Long-Jiang; Jie, Biao; Lu, Guang-Ming

2018-06-01

Hepatic encephalopathy (HE), as a complication of cirrhosis, is a serious brain disease, which may lead to death. Accurate diagnosis of HE and its intermediate stage, i.e., minimal HE (MHE), is very important for possibly early diagnosis and treatment. Brain connectivity network, as a simple representation of brain interaction, has been widely used for the brain disease (e.g., HE and MHE) analysis. However, those studies mainly focus on finding disease-related abnormal connectivity between brain regions, although a large number of studies have indicated that some brain diseases are usually related to local structure of brain connectivity network (i.e., subnetwork), rather than solely on some single brain regions or connectivities. Also, mining such disease-related subnetwork is a challenging task because of the complexity of brain network. To address this problem, we proposed a novel frequent-subnetwork-based method to mine disease-related subnetworks for MHE classification. Specifically, we first mine frequent subnetworks from both groups, i.e., MHE patients and non-HE (NHE) patients, respectively. Then we used the graph-kernel based method to select the most discriminative subnetworks for subsequent classification. We evaluate our proposed method on a MHE dataset with 77 cirrhosis patients, including 38 MHE patients and 39 NHE patients. The results demonstrate that our proposed method can not only obtain the improved classification performance in comparison with state-of-the-art network-based methods, but also identify disease-related subnetworks which can help us better understand the pathology of the brain diseases.

Mining of Business-Oriented Conversations at a Call Center

NASA Astrophysics Data System (ADS)

Takeuchi, Hironori; Nasukawa, Tetsuya; Watanabe, Hideo

Recently it has become feasible to transcribe textual records from telephone conversations at call centers by using automatic speech recognition. In this research, we extended a text mining system for call summary records and constructed a conversation mining system for the business-oriented conversations at the call center. To acquire useful business insights from the conversational data through the text mining system, it is critical to identify appropriate textual segments and expressions as the viewpoints to focus on. In the analysis of call summary data using a text mining system, some experts defined the viewpoints for the analysis by looking at some sample records and by preparing the dictionaries based on frequent keywords in the sample dataset. However with conversations it is difficult to identify such viewpoints manually and in advance because the target data consists of complete transcripts that are often lengthy and redundant. In this research, we defined a model of the business-oriented conversations and proposed a mining method to identify segments that have impacts on the outcomes of the conversations and can then extract useful expressions in each of these identified segments. In the experiment, we processed the real datasets from a car rental service center and constructed a mining system. With this system, we show the effectiveness of the method based on the defined conversation model.

A systems approach to accident causation in mining: an application of the HFACS method.

PubMed

Lenné, Michael G; Salmon, Paul M; Liu, Charles C; Trotter, Margaret

2012-09-01

This project aimed to provide a greater understanding of the systemic factors involved in mining accidents, and to examine those organisational and supervisory failures that are predictive of sub-standard performance at operator level. A sample of 263 significant mining incidents in Australia across 2007-2008 were analysed using the Human Factors Analysis and Classification System (HFACS). Two human factors specialists independently undertook the analysis. Incidents occurred more frequently in operations concerning the use of surface mobile equipment (38%) and working at heights (21%), however injury was more frequently associated with electrical operations and vehicles and machinery. Several HFACS categories appeared frequently: skill-based errors (64%) and violations (57%), issues with the physical environment (56%), and organisational processes (65%). Focussing on the overall system, several factors were found to predict the presence of failures in other parts of the system, including planned inappropriate operations and team resource management; inadequate supervision and team resource management; and organisational climate and inadequate supervision. It is recommended that these associations deserve greater attention in future attempts to develop accident countermeasures, although other significant associations should not be ignored. In accordance with findings from previous HFACS-based analyses of aviation and medical incidents, efforts to reduce the frequency of unsafe acts or operations should be directed to a few critical HFACS categories at the higher levels: organisational climate, planned inadequate operations, and inadequate supervision. While remedial strategies are proposed it is important that future efforts evaluate the utility of the measures proposed in studies of system safety. Copyright © 2011. Published by Elsevier Ltd.

The Development of Novel Chemical Fragment-Based Descriptors Using Frequent Common Subgraph Mining Approach and Their Application in QSAR Modeling.

PubMed

Khashan, Raed; Zheng, Weifan; Tropsha, Alexander

2014-03-01

We present a novel approach to generating fragment-based molecular descriptors. The molecules are represented by labeled undirected chemical graph. Fast Frequent Subgraph Mining (FFSM) is used to find chemical-fragments (subgraphs) that occur in at least a subset of all molecules in a dataset. The collection of frequent subgraphs (FSG) forms a dataset-specific descriptors whose values for each molecule are defined by the number of times each frequent fragment occurs in this molecule. We have employed the FSG descriptors to develop variable selection k Nearest Neighbor (kNN) QSAR models of several datasets with binary target property including Maximum Recommended Therapeutic Dose (MRTD), Salmonella Mutagenicity (Ames Genotoxicity), and P-Glycoprotein (PGP) data. Each dataset was divided into training, test, and validation sets to establish the statistical figures of merit reflecting the model validated predictive power. The classification accuracies of models for both training and test sets for all datasets exceeded 75 %, and the accuracy for the external validation sets exceeded 72 %. The model accuracies were comparable or better than those reported earlier in the literature for the same datasets. Furthermore, the use of fragment-based descriptors affords mechanistic interpretation of validated QSAR models in terms of essential chemical fragments responsible for the compounds' target property. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mineral resource of the month: barite

USGS Publications Warehouse

Miller, M. Michael

2006-01-01

Also called barytes, barite forms in various geologic environments and is frequently found with both metallic and nonmetallic minerals. Most barite is produced by open-pit mining techniques, and most crude barite requires some upgrading to meet minimum purity or specific gravity levels.

A review on the mechanism, risk evaluation, and prevention of coal spontaneous combustion in China.

PubMed

Kong, Biao; Li, Zenghua; Yang, Yongliang; Liu, Zhen; Yan, Daocheng

2017-10-01

In recent years, the ecology, security, and sustainable development of modern mines have become the theme of coal mine development worldwide. However, spontaneous combustion of coal under conditions of oxygen supply and automatic exothermic heating during coal mining lead to coalfield fires. Coal spontaneous combustion (CSC) causes huge economic losses and casualties, with the toxic and harmful gases produced during coal combustion not only polluting the working environment, but also causing great damage to the ecological environment. China is the world's largest coal producer and consumer; however, coal production in Chinese mines is seriously threatened by the CSC risk. Because deep underground mining methods are commonly adopted in Chinese coal mines, coupling disasters are frequent in these mines with the coalfield fires becoming increasingly serious. Therefore, in this study, we analyzed the development mechanism of CSC. The CSC risk assessment was performed from the aspects of prediction, detection, and determination of the "dangerous area" in a coal mine (i.e., the area most susceptible to fire hazards). A new geophysical method for CSC determination is proposed and analyzed. Furthermore, the main methods for CSC fire prevention and control and their advantages and disadvantages are analyzed. To eventually construct CSC prevention and control integration system, future developmental direction of CSC was given from five aspects. Our results can present a reference for the development of CSC fire prevention and control technology and promote the protection of ecological environment in China.

Correlating microbial community profiles with geochemical conditions in a watershed heavily contaminated by an antimony tailing pond.

PubMed

Xiao, Enzong; Krumins, Valdis; Tang, Song; Xiao, Tangfu; Ning, Zengping; Lan, Xiaolong; Sun, Weimin

2016-08-01

Mining activities have introduced various pollutants to surrounding aquatic and terrestrial environments, causing adverse impacts to the environment. Indigenous microbial communities are responsible for the biogeochemical cycling of pollutants in diverse environments, indicating the potential for bioremediation of such pollutants. Antimony (Sb) has been extensively mined in China and Sb contamination in mining areas has been frequently encountered. To date, however, the microbial composition and structure in response to Sb contamination has remained overlooked. Sb and As frequently co-occur in sulfide-rich ores, and co-contamination of Sb and As is observed in some mining areas. We characterized, for the first time, the microbial community profiles and their responses to Sb and As pollution from a watershed heavily contaminated by Sb tailing pond in Southwest China. The indigenous microbial communities were profiled by high-throughput sequencing from 16 sediment samples (535,390 valid reads). The comprehensive geochemical data (specifically, physical-chemical properties and different Sb and As extraction fractions) were obtained from river water and sediments at different depths as well. Canonical correspondence analysis (CCA) demonstrated that a suite of in situ geochemical and physical factors significantly structured the overall microbial community compositions. Further, we found significant correlations between individual phylotypes (bacterial genera) and the geochemical fractions of Sb and As by Spearman rank correlation. A number of taxonomic groups were positively correlated with the Sb and As extractable fractions and various Sb and As species in sediment, suggesting potential roles of these phylotypes in Sb biogeochemical cycling. Copyright © 2016 Elsevier Ltd. All rights reserved.

Discovering significant evolution patterns from satellite image time series.

PubMed

Petitjean, François; Masseglia, Florent; Gançarski, Pierre; Forestier, Germain

2011-12-01

Satellite Image Time Series (SITS) provide us with precious information on land cover evolution. By studying these series of images we can both understand the changes of specific areas and discover global phenomena that spread over larger areas. Changes that can occur throughout the sensing time can spread over very long periods and may have different start time and end time depending on the location, which complicates the mining and the analysis of series of images. This work focuses on frequent sequential pattern mining (FSPM) methods, since this family of methods fits the above-mentioned issues. This family of methods consists of finding the most frequent evolution behaviors, and is actually able to extract long-term changes as well as short term ones, whenever the change may start and end. However, applying FSPM methods to SITS implies confronting two main challenges, related to the characteristics of SITS and the domain's constraints. First, satellite images associate multiple measures with a single pixel (the radiometric levels of different wavelengths corresponding to infra-red, red, etc.), which makes the search space multi-dimensional and thus requires specific mining algorithms. Furthermore, the non evolving regions, which are the vast majority and overwhelm the evolving ones, challenge the discovery of these patterns. We propose a SITS mining framework that enables discovery of these patterns despite these constraints and characteristics. Our proposal is inspired from FSPM and provides a relevant visualization principle. Experiments carried out on 35 images sensed over 20 years show the proposed approach makes it possible to extract relevant evolution behaviors.

Biomedical text mining and its applications in cancer research.

PubMed

Zhu, Fei; Patumcharoenpol, Preecha; Zhang, Cheng; Yang, Yang; Chan, Jonathan; Meechai, Asawin; Vongsangnak, Wanwipa; Shen, Bairong

2013-04-01

Cancer is a malignant disease that has caused millions of human deaths. Its study has a long history of well over 100years. There have been an enormous number of publications on cancer research. This integrated but unstructured biomedical text is of great value for cancer diagnostics, treatment, and prevention. The immense body and rapid growth of biomedical text on cancer has led to the appearance of a large number of text mining techniques aimed at extracting novel knowledge from scientific text. Biomedical text mining on cancer research is computationally automatic and high-throughput in nature. However, it is error-prone due to the complexity of natural language processing. In this review, we introduce the basic concepts underlying text mining and examine some frequently used algorithms, tools, and data sets, as well as assessing how much these algorithms have been utilized. We then discuss the current state-of-the-art text mining applications in cancer research and we also provide some resources for cancer text mining. With the development of systems biology, researchers tend to understand complex biomedical systems from a systems biology viewpoint. Thus, the full utilization of text mining to facilitate cancer systems biology research is fast becoming a major concern. To address this issue, we describe the general workflow of text mining in cancer systems biology and each phase of the workflow. We hope that this review can (i) provide a useful overview of the current work of this field; (ii) help researchers to choose text mining tools and datasets; and (iii) highlight how to apply text mining to assist cancer systems biology research. Copyright © 2012 Elsevier Inc. All rights reserved.

Mining Co-Location Patterns with Clustering Items from Spatial Data Sets

NASA Astrophysics Data System (ADS)

Zhou, G.; Li, Q.; Deng, G.; Yue, T.; Zhou, X.

2018-05-01

The explosive growth of spatial data and widespread use of spatial databases emphasize the need for the spatial data mining. Co-location patterns discovery is an important branch in spatial data mining. Spatial co-locations represent the subsets of features which are frequently located together in geographic space. However, the appearance of a spatial feature C is often not determined by a single spatial feature A or B but by the two spatial features A and B, that is to say where A and B appear together, C often appears. We note that this co-location pattern is different from the traditional co-location pattern. Thus, this paper presents a new concept called clustering terms, and this co-location pattern is called co-location patterns with clustering items. And the traditional algorithm cannot mine this co-location pattern, so we introduce the related concept in detail and propose a novel algorithm. This algorithm is extended by join-based approach proposed by Huang. Finally, we evaluate the performance of this algorithm.

Using association rule mining to identify risk factors for early childhood caries.

PubMed

Ivančević, Vladimir; Tušek, Ivan; Tušek, Jasmina; Knežević, Marko; Elheshk, Salaheddin; Luković, Ivan

2015-11-01

Early childhood caries (ECC) is a potentially severe disease affecting children all over the world. The available findings are mostly based on a logistic regression model, but data mining, in particular association rule mining, could be used to extract more information from the same data set. ECC data was collected in a cross-sectional analytical study of the 10% sample of preschool children in the South Bačka area (Vojvodina, Serbia). Association rules were extracted from the data by association rule mining. Risk factors were extracted from the highly ranked association rules. Discovered dominant risk factors include male gender, frequent breastfeeding (with other risk factors), high birth order, language, and low body weight at birth. Low health awareness of parents was significantly associated to ECC only in male children. The discovered risk factors are mostly confirmed by the literature, which corroborates the value of the methods. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Riparian plants on mine runoff in Zimapan, Hidalgo, Mexico: Useful for phytoremediation?

PubMed

Carmona-Chit, Eréndira; Carrillo-González, Rogelio; González-Chávez, Ma Del Carmen A; Vibrans, Heike; Yáñez-Espinosa, Laura; Delgado-Alvarado, Adriana

2016-09-01

Dispersion and runoff of mine tailings have serious implications for human and ecosystem health in the surroundings of mines. Water, soils and plants were sampled in transects perpendicular to the Santiago stream in Zimapan, Hidalgo, which receives runoff sediments from two acidic and one alkaline mine tailing. Concentrations of potentially toxic elements (PTE) were measured in water, soils (rhizosphere and non-rhizosphere) and plants. Using diethylenetriaminepentaacetic acid (DTPA) extractable concentrations of Cu, Zn, Ni, Cd and Pb in rhizosphere soil, the bioconcentration and translocation factors were calculated. Ruderal annuals formed the principal element of the herbaceous vegetation. Accumulation was the most frequent strategy to deal with high concentrations of Zn, Cu, Ni, Cd and Pb. The order of concentration in plant tissue was Zn>Pb>Cu>Ni>Cd. Most plants contained concentrations of PTE considered as phytotoxic and behaved as metal tolerant species. Rorippa nasturtium-aquaticum accumulated particularly high concentrations of Cu. Parietaria pensylvanica and Commelina diffusa, common tropical weeds, behaved as Zn hyperaccumulators and should be studied further.

Study of Internal Dump Stability of Dudhichua Open Cast Project, Northern Coalfields Limited, India

NASA Astrophysics Data System (ADS)

Sengupta, S.; Roy, I.

2015-04-01

Dudhichua Open Cast Project is one of the prestigious projects of Northern Coalfields Limited, India; with total mineable coal reserves of approximately 400 million tonnes and corresponding 1,700 million m3 volume of waste rock i.e. overburden material. Accommodating this waste dump masses in the limited space of the de-coaled portion of the quarry is considered as one of the major challenges to the mine operators. It has been reported that this mine is facing frequent slope failures of waste rock dumps which is of great concern to the mine management in view of unsafe working condition. To tackle the above problem, a detailed investigation was carried out to propose a stable dump profile which will cater to the land economics and safety aspects of the mine. A detailed investigation along with recommendation of optimum design for dragline dump profile along with shovel-dumper-dump profile is presented in this paper.

The role of conflict minerals, artisanal mining, and informal trading networks in African intrastate and regional conflicts

USGS Publications Warehouse

Chirico, Peter G.; Malpeli, Katherine C.

2014-01-01

The relationship between natural resources and armed conflict gained public and political attention in the 1990s, when it became evident that the mining and trading of diamonds were connected with brutal rebellions in several African nations. Easily extracted resources such as alluvial diamonds and gold have been and continue to be exploited by rebel groups to fund their activities. Artisanal and small-scale miners operating under a quasi-legal status often mine these mineral deposits. While many African countries have legalized artisanal mining and established flow chains through which production is intended to travel, informal trading networks frequently emerge in which miners seek to evade taxes and fees by selling to unauthorized buyers. These networks have the potential to become international in scope, with actors operating in multiple countries. The lack of government control over the artisanal mining sector and the prominence of informal trade networks can have severe social, political, and economic consequences. In the past, mineral extraction fuelled violent civil wars in Sierra Leone, Liberia, and Angola, and it continues to do so today in several other countries. The significant influence of the informal network that surrounds artisanal mining is therefore an important security concern that can extend across borders and have far-reaching impacts.

A cross-sectional survey on knowledge and perceptions of health risks associated with arsenic and mercury contamination from artisanal gold mining in Tanzania

PubMed Central

2013-01-01

Background An estimated 0.5 to 1.5 million informal miners, of whom 30-50% are women, rely on artisanal mining for their livelihood in Tanzania. Mercury, used in the processing gold ore, and arsenic, which is a constituent of some ores, are common occupational exposures that frequently result in widespread environmental contamination. Frequently, the mining activities are conducted haphazardly without regard for environmental, occupational, or community exposure. The primary objective of this study was to assess community risk knowledge and perception of potential mercury and arsenic toxicity and/or exposure from artisanal gold mining in Rwamagasa in northwestern Tanzania. Methods A cross-sectional survey of respondents in five sub-villages in the Rwamagasa Village located in Geita District in northwestern Tanzania near Lake Victoria was conducted. This area has a history of artisanal gold mining and many of the population continue to work as miners. Using a clustered random selection approach for recruitment, a total of 160 individuals over 18 years of age completed a structured interview. Results The interviews revealed wide variations in knowledge and risk perceptions concerning mercury and arsenic exposure, with 40.6% (n=65) and 89.4% (n=143) not aware of the health effects of mercury and arsenic exposure respectively. Males were significantly more knowledgeable (n=59, 36.9%) than females (n=36, 22.5%) with regard to mercury (x2=3.99, p<0.05). An individual’s occupation category was associated with level of knowledge (x2=22.82, p=<0.001). Individuals involved in mining (n=63, 73.2%) were more knowledgeable about the negative health effects of mercury than individuals in other occupations. Of the few individuals (n=17, 10.6%) who knew about arsenic toxicity, the majority (n=10, 58.8%) were miners. Conclusions The knowledge of individuals living in Rwamagasa, Tanzania, an area with a history of artisanal gold mining, varied widely with regard to the health hazards of mercury and arsenic. In these communities there was limited awareness of the threats to health associated with exposure to mercury and arsenic. This lack of knowledge, combined with minimal environmental monitoring and controlled waste management practices, highlights the need for health education, surveillance, and policy changes. PMID:23351708

A cross-sectional survey on knowledge and perceptions of health risks associated with arsenic and mercury contamination from artisanal gold mining in Tanzania.

PubMed

Charles, Elias; Thomas, Deborah S K; Dewey, Deborah; Davey, Mark; Ngallaba, Sospatro E; Konje, Eveline

2013-01-25

An estimated 0.5 to 1.5 million informal miners, of whom 30-50% are women, rely on artisanal mining for their livelihood in Tanzania. Mercury, used in the processing gold ore, and arsenic, which is a constituent of some ores, are common occupational exposures that frequently result in widespread environmental contamination. Frequently, the mining activities are conducted haphazardly without regard for environmental, occupational, or community exposure. The primary objective of this study was to assess community risk knowledge and perception of potential mercury and arsenic toxicity and/or exposure from artisanal gold mining in Rwamagasa in northwestern Tanzania. A cross-sectional survey of respondents in five sub-villages in the Rwamagasa Village located in Geita District in northwestern Tanzania near Lake Victoria was conducted. This area has a history of artisanal gold mining and many of the population continue to work as miners. Using a clustered random selection approach for recruitment, a total of 160 individuals over 18 years of age completed a structured interview. The interviews revealed wide variations in knowledge and risk perceptions concerning mercury and arsenic exposure, with 40.6% (n=65) and 89.4% (n=143) not aware of the health effects of mercury and arsenic exposure respectively. Males were significantly more knowledgeable (n=59, 36.9%) than females (n=36, 22.5%) with regard to mercury (x²=3.99, p<0.05). An individual's occupation category was associated with level of knowledge (x²=22.82, p=<0.001). Individuals involved in mining (n=63, 73.2%) were more knowledgeable about the negative health effects of mercury than individuals in other occupations. Of the few individuals (n=17, 10.6%) who knew about arsenic toxicity, the majority (n=10, 58.8%) were miners. The knowledge of individuals living in Rwamagasa, Tanzania, an area with a history of artisanal gold mining, varied widely with regard to the health hazards of mercury and arsenic. In these communities there was limited awareness of the threats to health associated with exposure to mercury and arsenic. This lack of knowledge, combined with minimal environmental monitoring and controlled waste management practices, highlights the need for health education, surveillance, and policy changes.

FREQUENT SUBGRAPH MINING OF PERSONALIZED SIGNALING PATHWAY NETWORKS GROUPS PATIENTS WITH FREQUENTLY DYSREGULATED DISEASE PATHWAYS AND PREDICTS PROGNOSIS.

PubMed

Durmaz, Arda; Henderson, Tim A D; Brubaker, Douglas; Bebek, Gurkan

2017-01-01

Large scale genomics studies have generated comprehensive molecular characterization of numerous cancer types. Subtypes for many tumor types have been established; however, these classifications are based on molecular characteristics of a small gene sets with limited power to detect dysregulation at the patient level. We hypothesize that frequent graph mining of pathways to gather pathways functionally relevant to tumors can characterize tumor types and provide opportunities for personalized therapies. In this study we present an integrative omics approach to group patients based on their altered pathway characteristics and show prognostic differences within breast cancer (p < 9:57E - 10) and glioblastoma multiforme (p < 0:05) patients. We were able validate this approach in secondary RNA-Seq datasets with p < 0:05 and p < 0:01 respectively. We also performed pathway enrichment analysis to further investigate the biological relevance of dysregulated pathways. We compared our approach with network-based classifier algorithms and showed that our unsupervised approach generates more robust and biologically relevant clustering whereas previous approaches failed to report specific functions for similar patient groups or classify patients into prognostic groups. These results could serve as a means to improve prognosis for future cancer patients, and to provide opportunities for improved treatment options and personalized interventions. The proposed novel graph mining approach is able to integrate PPI networks with gene expression in a biologically sound approach and cluster patients in to clinically distinct groups. We have utilized breast cancer and glioblastoma multiforme datasets from microarray and RNA-Seq platforms and identified disease mechanisms differentiating samples. Supplementary methods, figures, tables and code are available at https://github.com/bebeklab/dysprog.

EMRlog method for computer security for electronic medical records with logic and data mining.

PubMed

Martínez Monterrubio, Sergio Mauricio; Frausto Solis, Juan; Monroy Borja, Raúl

2015-01-01

The proper functioning of a hospital computer system is an arduous work for managers and staff. However, inconsistent policies are frequent and can produce enormous problems, such as stolen information, frequent failures, and loss of the entire or part of the hospital data. This paper presents a new method named EMRlog for computer security systems in hospitals. EMRlog is focused on two kinds of security policies: directive and implemented policies. Security policies are applied to computer systems that handle huge amounts of information such as databases, applications, and medical records. Firstly, a syntactic verification step is applied by using predicate logic. Then data mining techniques are used to detect which security policies have really been implemented by the computer systems staff. Subsequently, consistency is verified in both kinds of policies; in addition these subsets are contrasted and validated. This is performed by an automatic theorem prover. Thus, many kinds of vulnerabilities can be removed for achieving a safer computer system.

EMRlog Method for Computer Security for Electronic Medical Records with Logic and Data Mining

PubMed Central

Frausto Solis, Juan; Monroy Borja, Raúl

2015-01-01

The proper functioning of a hospital computer system is an arduous work for managers and staff. However, inconsistent policies are frequent and can produce enormous problems, such as stolen information, frequent failures, and loss of the entire or part of the hospital data. This paper presents a new method named EMRlog for computer security systems in hospitals. EMRlog is focused on two kinds of security policies: directive and implemented policies. Security policies are applied to computer systems that handle huge amounts of information such as databases, applications, and medical records. Firstly, a syntactic verification step is applied by using predicate logic. Then data mining techniques are used to detect which security policies have really been implemented by the computer systems staff. Subsequently, consistency is verified in both kinds of policies; in addition these subsets are contrasted and validated. This is performed by an automatic theorem prover. Thus, many kinds of vulnerabilities can be removed for achieving a safer computer system. PMID:26495300

Autumn olive (Elaeagnus umbellata) presence and proliferation on former surface coal mines in Eastern USA

USGS Publications Warehouse

Oliphant, Adam J.; Wynne, R.H.; Zipper, Carl E.; Ford, W. Mark; Donovan, P. F.; Li, Jing

2017-01-01

Invasive plants threaten native plant communities. Surface coal mines in the Appalachian Mountains are among the most disturbed landscapes in North America, but information about land cover characteristics of Appalachian mined lands is lacking. The invasive shrub autumn olive (Elaeagnus umbellata) occurs on these sites and interferes with ecosystem recovery by outcompeting native trees, thus inhibiting re-establishment of the native woody-plant community. We analyzed Landsat 8 satellite imagery to describe autumn olive’s distribution on post-mined lands in southwestern Virginia within the Appalachian coalfield. Eight images from April 2013 through January 2015 served as input data. Calibration and validation data obtained from high-resolution aerial imagery were used to develop a land cover classification model that identified areas where autumn olive was a primary component of land cover. Results indicate that autumn olive cover was sufficiently dense to enable detection on approximately 12.6 % of post-mined lands within the study area. The classified map had user’s and producer’s accuracies of 85.3 and 78.6 %, respectively, for the autumn olive coverage class. Overall accuracy was assessed in reference to an independent validation dataset at 96.8 %. Autumn olive was detected more frequently on mines disturbed prior to 2003, the last year of known plantings, than on lands disturbed by more recent mining. These results indicate that autumn olive growing on reclaimed coal mines in Virginia and elsewhere in eastern USA can be mapped using Landsat 8 Operational Land Imager imagery; and that autumn olive occurrence is a significant landscape vegetation feature on former surface coal mines in the southwestern Virginia segment of the Appalachian coalfield.

Examining health and well-being outcomes associated with mining activity in rural communities of high-income countries: A systematic review.

PubMed

Mactaggart, Fiona; McDermott, Liane; Tynan, Anna; Gericke, Christian

2016-08-01

It is recognised internationally that rural communities often experience greater barriers to accessing services and have poorer health outcomes compared to urban communities. In some settings, health disparities may be further exacerbated by mining activity, which can affect the social, physical and economic environment in which rural communities reside. Direct environmental health impacts are often associated with mining activity and are frequently investigated. However, there is evidence of broader, indirect health and well-being implications emerging in the literature. This systematic review examines these health and well-being outcomes in communities living in proximity to mining in high-income countries, and, in doing so, discusses their possible determinants. Four databases were systematically searched. Articles were selected if adult residents in mining communities were studied and outcomes were related to health or individual or community-level well-being. A narrative synthesis was conducted. Sixteen publications were included. Evidence of increased prevalence of chronic diseases and poor self-reported health status was reported in the mining communities. Relationship breakdown and poor family health, lack of social connectedness and decreased access to health services were also reported. Changes to the physical landscape; risky health behaviours; shift work of partners in the mine industry; social isolation and cyclical nature of 'boom and bust' activity contributed to poorer outcomes in the communities. This review highlights the broader health and well-being outcomes associated with mining activity that should be monitored and addressed in addition to environmental health impacts to support co-existence of mining activities and rural communities. © 2016 National Rural Health Alliance Inc.

Proceedings: Fourth Workshop on Mining Scientific Datasets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kamath, C

Commercial applications of data mining in areas such as e-commerce, market-basket analysis, text-mining, and web-mining have taken on a central focus in the JCDD community. However, there is a significant amount of innovative data mining work taking place in the context of scientific and engineering applications that is not well represented in the mainstream KDD conferences. For example, scientific data mining techniques are being developed and applied to diverse fields such as remote sensing, physics, chemistry, biology, astronomy, structural mechanics, computational fluid dynamics etc. In these areas, data mining frequently complements and enhances existing analysis methods based on statistics, exploratorymore » data analysis, and domain-specific approaches. On the surface, it may appear that data from one scientific field, say genomics, is very different from another field, such as physics. However, despite their diversity, there is much that is common across the mining of scientific and engineering data. For example, techniques used to identify objects in images are very similar, regardless of whether the images came from a remote sensing application, a physics experiment, an astronomy observation, or a medical study. Further, with data mining being applied to new types of data, such as mesh data from scientific simulations, there is the opportunity to apply and extend data mining to new scientific domains. This one-day workshop brings together data miners analyzing science data and scientists from diverse fields to share their experiences, learn how techniques developed in one field can be applied in another, and better understand some of the newer techniques being developed in the KDD community. This is the fourth workshop on the topic of Mining Scientific Data sets; for information on earlier workshops, see http://www.ahpcrc.org/conferences/. This workshop continues the tradition of addressing challenging problems in a field where the diversity of applications is matched only by the opportunities that await a practitioner.« less

Mining and harnessing natural variation - a little MAGIC

USDA-ARS?s Scientific Manuscript database

As has been frequently noted, exotic germplasm ( lines unadapted to local conditions) can be sources of very beneficial genes. The trouble is that it's often difficult to identify these genes. We propose an approach in which mutations can be used to uncover useful variants of natural genes....

The requirements for implementing Sustainable Development Goals (SDGs) and for planning and implementing Integrated Territorial Investments (ITI) in mining areas

NASA Astrophysics Data System (ADS)

Florkowska, Lucyna; Bryt-Nitarska, Izabela

2018-04-01

The notion of Integrated Territorial Investments (ITI) appears more and more frequently in contemporary regional development strategies. Formulating the main assumptions of ITI is a response to a growing need for a co-ordinated, multi-dimensional regional development suitable for the characteristics of a given area. Activities are mainly aimed at improving people's quality of life with their significant participation. These activities include implementing the Sustainable development Goals (SDGs). Territorial investments include, among others, projects in areas where land and building use is governed not only by general regulations (Spatial Planning and Land Development Act) but also by separate legal acts. This issue also concerns areas with active mines and post-mining areas undergoing revitalization. For the areas specified above land development and in particular making building investments is subject to the requirements set forth in the Geological and Mining Law and in the general regulations. In practice this means that factors connected with the present and future mining impacts must be taken into consideration in planning the investment process. This article discusses the role of proper assessment of local geological conditions as well as the current and future mining situation in the context of proper planning and performance of the Integrated Territorial Investment programme and also in the context of implementing the SDGs. It also describes the technical and legislative factors which need to be taken into consideration in areas where mining is planned or where it took place in the past.

HC StratoMineR: A Web-Based Tool for the Rapid Analysis of High-Content Datasets.

PubMed

Omta, Wienand A; van Heesbeen, Roy G; Pagliero, Romina J; van der Velden, Lieke M; Lelieveld, Daphne; Nellen, Mehdi; Kramer, Maik; Yeong, Marley; Saeidi, Amir M; Medema, Rene H; Spruit, Marco; Brinkkemper, Sjaak; Klumperman, Judith; Egan, David A

2016-10-01

High-content screening (HCS) can generate large multidimensional datasets and when aligned with the appropriate data mining tools, it can yield valuable insights into the mechanism of action of bioactive molecules. However, easy-to-use data mining tools are not widely available, with the result that these datasets are frequently underutilized. Here, we present HC StratoMineR, a web-based tool for high-content data analysis. It is a decision-supportive platform that guides even non-expert users through a high-content data analysis workflow. HC StratoMineR is built by using My Structured Query Language for storage and querying, PHP: Hypertext Preprocessor as the main programming language, and jQuery for additional user interface functionality. R is used for statistical calculations, logic and data visualizations. Furthermore, C++ and graphical processor unit power is diffusely embedded in R by using the rcpp and rpud libraries for operations that are computationally highly intensive. We show that we can use HC StratoMineR for the analysis of multivariate data from a high-content siRNA knock-down screen and a small-molecule screen. It can be used to rapidly filter out undesirable data; to select relevant data; and to perform quality control, data reduction, data exploration, morphological hit picking, and data clustering. Our results demonstrate that HC StratoMineR can be used to functionally categorize HCS hits and, thus, provide valuable information for hit prioritization.

Effects of coal mining, forestry, and road construction on southern Appalachian stream invertebrates and habitats.

PubMed

Gangloff, Michael M; Perkins, Michael; Blum, Peter W; Walker, Craig

2015-03-01

Coal has been extracted via surface and sub-surface mining for decades throughout the Appalachian Mountains. New interest in ridge-top mining has raised concerns about possible waterway impacts. We examined effects of forestry, mining, and road construction-based disturbance on physico-chemistry and macroinvertebrate communities in east-central Tennessee headwater streams. Although 11 of 30 sites failed Tennessee's biocriteria scoring system, invertebrate richness was moderately high and we did not find significant differences in any water chemistry or habitat parameters between sites with passing and failing scores. However, conductivity and dissolved solid concentrations appeared elevated in the majority of study streams. Principal components (PCs) analysis indicated that six PCs accounted for ~77 % of among-site habitat variability. One PC associated with dissolved oxygen and specific conductance explained the second highest proportion of among-site variability after catchment area. Specific conductance was not correlated with catchment area but was strongly correlated with mining activity. Composition and success of multivariate models using habitat PCs to predict macroinvertebrate metrics was highly variable. PC scores associated with water chemistry and substrate composition were most frequently included in significant models. These results suggest that impacts of historical and current coal mining remain a source of water quality and macroinvertebrate community impairment in this region, but effects are subtle. Our results suggest that surface mining may have chronic and system-wide effects on habitat conditions and invertebrate communities in Cumberland Plateau streams.

Assembler: Efficient Discovery of Spatial Co-evolving Patterns in Massive Geo-sensory Data.

PubMed

Zhang, Chao; Zheng, Yu; Ma, Xiuli; Han, Jiawei

2015-08-01

Recent years have witnessed the wide proliferation of geo-sensory applications wherein a bundle of sensors are deployed at different locations to cooperatively monitor the target condition. Given massive geo-sensory data, we study the problem of mining spatial co-evolving patterns (SCPs), i.e ., groups of sensors that are spatially correlated and co-evolve frequently in their readings. SCP mining is of great importance to various real-world applications, yet it is challenging because (1) the truly interesting evolutions are often flooded by numerous trivial fluctuations in the geo-sensory time series; and (2) the pattern search space is extremely large due to the spatiotemporal combinatorial nature of SCP. In this paper, we propose a two-stage method called Assembler. In the first stage, Assembler filters trivial fluctuations using wavelet transform and detects frequent evolutions for individual sensors via a segment-and-group approach. In the second stage, Assembler generates SCPs by assembling the frequent evolutions of individual sensors. Leveraging the spatial constraint, it conceptually organizes all the SCPs into a novel structure called the SCP search tree, which facilitates the effective pruning of the search space to generate SCPs efficiently. Our experiments on both real and synthetic data sets show that Assembler is effective, efficient, and scalable.

Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jin, R; McCallen, S; Almaas, E

2007-05-28

Complex networks have been used successfully in scientific disciplines ranging from sociology to microbiology to describe systems of interacting units. Until recently, studies of complex networks have mainly focused on their network topology. However, in many real world applications, the edges and vertices have associated attributes that are frequently represented as vertex or edge weights. Furthermore, these weights are often not static, instead changing with time and forming a time series. Hence, to fully understand the dynamics of the complex network, we have to consider both network topology and related time series data. In this work, we propose a motifmore » mining approach to identify trend motifs for such purposes. Simply stated, a trend motif describes a recurring subgraph where each of its vertices or edges displays similar dynamics over a userdefined period. Given this, each trend motif occurrence can help reveal significant events in a complex system; frequent trend motifs may aid in uncovering dynamic rules of change for the system, and the distribution of trend motifs may characterize the global dynamics of the system. Here, we have developed efficient mining algorithms to extract trend motifs. Our experimental validation using three disparate empirical datasets, ranging from the stock market, world trade, to a protein interaction network, has demonstrated the efficiency and effectiveness of our approach.« less

[Features of Professor Ma Kun's medication in treating ovulatory infertility].

PubMed

Tong, Ya-Jing; Zhang, Hui-Xian; Chen, Yan-Xia; Dong, Mei-Ling; Ma, Kun

2017-12-01

In order to analyze Professor Ma Kun's medication in treating anovulatory infertility, her prescriptions for treating anovulatory infertility in 2012-2015 were collected. The medication features and the regularity of prescriptions were mined by using traditional Chinese medicine inheritance support system, association rules, complex system entropy clustering and other mining methods. Finally, a total of 684 prescriptions and 300 kinds of herbs were screened out, with a total frequency of 11 156 times; And 68 core combinations and 8 new prescriptions were mined. The top three frequently used herbs by effect were respectively tonic herb, blood circulation promoting herb, and Qi-circulation promoting herb. The top three tastes were sweetness, bitterness and pungent flavor. The results showed 28 herbs with a high frequency of ≥100.The top 10 frequently used herbs were respectively Angelica Sinensis Radix, Cyperi Rhizoma, Chuanxiong Rhizome, Paeoniae Radix Rubra, Cyathulae Radix, Taxilli Herba, Cuscutae Semen, Codonopsis Radix, Ligustri Lucidi Fructus, Paeoniae Albaand Paeoniae Radix Alba. The association rules analysis showed commonly used herbal pairs, including Rehmanniae Radix Preparata-Chuanxiong Rhizome, Rehmanniae Radix Preparata-Angelica Sinensis Radix, Cuscutae Semen-Dipsaci Radix. In conclusion, Professor Ma has treated anovulatory infertility by nourishing the kidney and activating blood throughout the treatment course, and attached the importance to the relationship between Qi and blood and there gulation of liver, spleen and kidney in treating anovulatory infertility. Copyright© by the Chinese Pharmaceutical Association.

Prodromal signs and symptoms of serious infections with tocilizumab treatment for rheumatoid arthritis: Text mining of the Japanese postmarketing adverse event-reporting database.

PubMed

Atsumi, Tatsuya; Ando, Yoshiaki; Matsuda, Shinichi; Tomizawa, Shiho; Tanaka, Riwa; Takagi, Nobuhiro; Nakasone, Ayako

2018-05-01

To search for signs and symptoms before serious infection (SI) occurs in tocilizumab (TCZ)-treated rheumatoid arthritis (RA) patients. Individual case safety reports, including structured (age, sex, adverse event [AE]) and unstructured (clinical narratives) data, were analyzed by automated text mining from a Japanese post-marketing AE-reporting database (16 April 2008-10 April 2015) assuming the following: treated in Japan; TCZ RA treatment; ≥1 SI; unable to exclude causality between TCZ and SIs. The database included 7653 RA patients; 1221 reports met four criteria, encompassing 1591 SIs. Frequent SIs were pneumonia (15.9%), cellulitis (9.9%), and sepsis (5.0%). Reports for 782 patients included SI onset date; 60.7% of patients had signs/symptoms ≤28 days before SI diagnosis, 32.7% had signs/symptoms with date unidentified, 1.7% were asymptomatic, and 4.9% had unknown signs/symptoms. The most frequent signs/symptoms were for skin (swelling and pain) and respiratory (cough and pyrexia) infections. Among 68 patients who had normal laboratory results for C-reactive protein, body temperature, and white blood cell count, 94.1% had signs or symptoms of infection. This study identified prodromal signs and symptoms of SIs in RA patients receiving TCZ. Data mining clinical narratives from post-marketing AE databases may be beneficial in characterizing SIs.

Occurrence and variability of mining-related lead and zinc in the Spring River flood plain and tributary flood plains, Cherokee County, Kansas, 2009--11

USGS Publications Warehouse

Juracek, Kyle E.

2013-01-01

Historical mining activity in the Tri-State Mining District (TSMD), located in parts of southeast Kansas, southwest Missouri, and northeast Oklahoma, has resulted in a substantial ongoing input of cadmium, lead, and zinc to the environment. To provide some of the information needed to support remediation efforts in the Cherokee County, Kansas, superfund site, a 4-year study was begun in 2009 by the U.S. Geological Survey that was requested and funded by the U.S. Environmental Protection Agency. A combination of surficial-soil sampling and coring was used to investigate the occurrence and variability of mining-related lead and zinc in the flood plains of the Spring River and several tributaries within the superfund site. Lead- and zinc-contaminated flood plains are a concern, in part, because they represent a long-term source of contamination to the fluvial environment. Lead and zinc contamination was assessed with reference to probable-effect concentrations (PECs), which represent the concentrations above which adverse aquatic biological effects are likely to occur. The general PECs for lead and zinc were 128 and 459 milligrams per kilogram, respectively. The TSMD-specific PECs for lead and zinc were 150 and 2,083 milligrams per kilogram, respectively. Typically, surficial soils in the Spring River flood plain had lead and zinc concentrations that were less than the general PECs. Lead and zinc concentrations in the surficial-soil samples were variable with distance downstream and with distance from the Spring River channel, and the largest lead and zinc concentrations usually were located near the channel. Lead and zinc concentrations larger than the general or TSMD-specific PECs, or both, were infrequent at depth in the Spring River flood plain. When present, such contamination typically was confined to the upper 2 feet of the core and frequently was confined to the upper 6 inches. Tributaries with few or no lead- and zinc-mined areas in the basin—Brush Creek, Cow Creek, and Shawnee Creek—generally had flood-plain lead and zinc concentrations (surficial soil, 6- and 12-inch depth) that were substantially less than the general PECs. Tributaries with extensive lead- and zinc-mined areas in the basin—Shoal Creek, Short Creek, Spring Branch, Tar Creek, Turkey Creek, and Willow Creek—had flood-plain lead concentrations (surficial soil, 6- and 12-inch depth) that frequently or typically exceeded the general and TSMD-specific PECs. Likewise, the tributaries with extensive lead- and zinc-mined areas in the basin had flood-plain zinc concentrations (surficial soil, 6- and 12-inch depth) that frequently or typically exceeded the general PEC. With the exception of Shoal and Willow Creeks, zinc concentrations typically exceeded the TSMD-specific PEC. The largest flood-plain lead and zinc concentrations (surficial soil, 6- and 12-inch depth) were measured for Short and Tar Creeks. Lead and zinc concentrations in the surficial-soil samples collected from the tributary flood plains varied longitudinally in relation to sources of mining-contaminated sediment in the basins. Lead and zinc concentrations also varied with distance from the channel; however, no consistent spatial trend was evident. For the surficial-soil samples collected from the Spring River flood plain and tributary flood plains, both the coarse (larger than 63 micrometers) and fine particles (less than 63 micrometers) contained substantial lead and zinc concentrations.

Discovering interesting molecular substructures for molecular classification.

PubMed

Lam, Winnie W M; Chan, Keith C C

2010-06-01

Given a set of molecular structure data preclassified into a number of classes, the molecular classification problem is concerned with the discovering of interesting structural patterns in the data so that "unseen" molecules not originally in the dataset can be accurately classified. To tackle the problem, interesting molecular substructures have to be discovered and this is done typically by first representing molecular structures in molecular graphs, and then, using graph-mining algorithms to discover frequently occurring subgraphs in them. These subgraphs are then used to characterize different classes for molecular classification. While such an approach can be very effective, it should be noted that a substructure that occurs frequently in one class may also does occur in another. The discovering of frequent subgraphs for molecular classification may, therefore, not always be the most effective. In this paper, we propose a novel technique called mining interesting substructures in molecular data for classification (MISMOC) that can discover interesting frequent subgraphs not just for the characterization of a molecular class but also for the distinguishing of it from the others. Using a test statistic, MISMOC screens each frequent subgraph to determine if they are interesting. For those that are interesting, their degrees of interestingness are determined using an information-theoretic measure. When classifying an unseen molecule, its structure is then matched against the interesting subgraphs in each class and a total interestingness measure for the unseen molecule to be classified into a particular class is determined, which is based on the interestingness of each matched subgraphs. The performance of MISMOC is evaluated using both artificial and real datasets, and the results show that it can be an effective approach for molecular classification.

Introducing Artificial Neural Networks through a Spreadsheet Model

ERIC Educational Resources Information Center

Rienzo, Thomas F.; Athappilly, Kuriakose K.

2012-01-01

Business students taking data mining classes are often introduced to artificial neural networks (ANN) through point and click navigation exercises in application software. Even if correct outcomes are obtained, students frequently do not obtain a thorough understanding of ANN processes. This spreadsheet model was created to illuminate the roles of…

Semi-Supervised Clustering for High-Dimensional and Sparse Features

ERIC Educational Resources Information Center

Yan, Su

2010-01-01

Clustering is one of the most common data mining tasks, used frequently for data organization and analysis in various application domains. Traditional machine learning approaches to clustering are fully automated and unsupervised where class labels are unknown a priori. In real application domains, however, some "weak" form of side…

Big Data: You Are Adding to . . . and Using It

ERIC Educational Resources Information Center

Makela, Carole J.

2016-01-01

"Big data" prompts a whole lexicon of terms--data flow; analytics; data mining; data science; smart you name it (cars, houses, cities, wearables, etc.); algorithms; learning analytics; predictive analytics; data aggregation; data dashboards; digital tracks; and big data brokers. New terms are being coined frequently. Are we paying…

Spatio-Temporal Mining of PolSAR Satellite Image Time Series

NASA Astrophysics Data System (ADS)

Julea, A.; Meger, N.; Trouve, E.; Bolon, Ph.; Rigotti, C.; Fallourd, R.; Nicolas, J.-M.; Vasile, G.; Gay, M.; Harant, O.; Ferro-Famil, L.

2010-12-01

This paper presents an original data mining approach for describing Satellite Image Time Series (SITS) spatially and temporally. It relies on pixel-based evolution and sub-evolution extraction. These evolutions, namely the frequent grouped sequential patterns, are required to cover a minimum surface and to affect pixels that are sufficiently connected. These spatial constraints are actively used to face large data volumes and to select evolutions making sense for end-users. In this paper, a specific application to fully polarimetric SAR image time series is presented. Preliminary experiments performed on a RADARSAT-2 SITS covering the Chamonix Mont-Blanc test-site are used to illustrate the proposed approach.

Is Blast Injury a Modern Phenomenon?: Early Historical Descriptions of Mining and Volcanic Traumatic Brain Injury With Relevance to Modern Terrorist Attacks and Military Warfare.

PubMed

Bowen, Lauren N; Moore, David F; Okun, Michael S

2016-03-01

Given the recent interest in blast injury spurred by returning soldiers from overseas conflicts, we sought to research the early historical descriptions of blast injuries and their treatments. Consideration was given to specific descriptions of survivors of closed head injury and their treatment. A review of the medical and nonmedical literature was undertaken, with particular emphasis on pre-1800 descriptions of volcanic eruptions and mining accidents. Compilations of accounts of the Etna eruptions dating from 126 BC were translated into English, and early mining texts from the 1600s and 1700s were reviewed. Accumulations of flammable gases were recorded in many medieval sources and this knowledge of toxic gas which could lead to blast injury was known in the mining community by 1316. No direct attribution of injuries to blast forces was present in the historical record examined before the 1300s, although mining accounts in the 1600s detail deaths due to blast. No specific descriptions of survivors of a closed head injury were found in the mining and volcanic eruption literature. Descriptions and warnings of blast forces were commonly written about in the medieval and Renaissance mining communities. Personal narratives as early as 1316 recognize the traumatic effects of blast injury. No mining or volcanic blast descriptions before 1800 detailed severe closed head injury survivors, suggesting greater mortality than morbidity from blast injury in the premodern era. This review also uncovered that there was no historical treatment or remedy recommended to survivors of blast injury. Blast explosions resulting in injury or death were frequently described, although in simplistic terminology.

Controls on the Mobility of Antimony in Mine Waste from Three Deposit Types

NASA Astrophysics Data System (ADS)

Jamieson, H.; Radková, A. B.; Fawcett, S.

2017-12-01

Antimony can be considered both a critical metal and an environmental hazard, with a toxicity similar to arsenic. It is concentrated in stibnite deposits, but also present in polymetallic and precious metal ores, frequently accompanied by arsenic. We have studied the mineralogical controls on the mobility of antimony in three types of mine waste: stibnite tailings from an antimony mine, tetrahedrite-bearing waste rock from copper mining, and gold mine tailings and ore roaster waste. Our results demonstrate that the tendency of antimony to leach into the aqueous environment or remain sequestered in solid phases depends on the primary host minerals and conditions governing the precipitation of secondary antimony-hosting phases. In tailings at the Beaver Brook antimony mine in Newfoundland, Canada, stibnite oxidizes rapidly, and secondary minerals such as the relatively insoluble Sb-Fe tripuhyite-like phase and Sb-bearing goethite. However, under dry conditions, the most important secondary Sb host is the Mg-Sb hydroxide brandholzite, but this easily soluble mineral disappears when it rains. Antimony that was originally hosted in tetrahedrite, a complex multi-element sulfosalt, in the historic waste rock piles at Špania Dolina-Piesky, Slovakia, is not as mobile as Cu and As during weathering but reprecipiates to a mixture of tripuhyite and romeite. Finally, the original antimony-hosting minerals, both stibnite and sulphosalts, in the gold ore at Giant Mine, Yellowknife, Canada were completely destroyed during ore roasting. In tailings-contaminated sediments, antimony persists in roaster-generated iron oxide phases, except under reducing conditions where some of the antimony forms a Sb-S phase. The combined presence of antimony and arsenic in mine waste complicates risk assessment but in general, our findings suggest that antimony is less mobile than arsenic in the environment.

Clustering XML Documents Using Frequent Subtrees

NASA Astrophysics Data System (ADS)

Kutty, Sangeetha; Tran, Tien; Nayak, Richi; Li, Yuefeng

This paper presents an experimental study conducted over the INEX 2008 Document Mining Challenge corpus using both the structure and the content of XML documents for clustering them. The concise common substructures known as the closed frequent subtrees are generated using the structural information of the XML documents. The closed frequent subtrees are then used to extract the constrained content from the documents. A matrix containing the term distribution of the documents in the dataset is developed using the extracted constrained content. The k-way clustering algorithm is applied to the matrix to obtain the required clusters. In spite of the large number of documents in the INEX 2008 Wikipedia dataset, the proposed frequent subtree-based clustering approach was successful in clustering the documents. This approach significantly reduces the dimensionality of the terms used for clustering without much loss in accuracy.

PDBj Mine: design and implementation of relational database interface for Protein Data Bank Japan

PubMed Central

Kinjo, Akira R.; Yamashita, Reiko; Nakamura, Haruki

2010-01-01

This article is a tutorial for PDBj Mine, a new database and its interface for Protein Data Bank Japan (PDBj). In PDBj Mine, data are loaded from files in the PDBMLplus format (an extension of PDBML, PDB's canonical XML format, enriched with annotations), which are then served for the user of PDBj via the worldwide web (WWW). We describe the basic design of the relational database (RDB) and web interfaces of PDBj Mine. The contents of PDBMLplus files are first broken into XPath entities, and these paths and data are indexed in the way that reflects the hierarchical structure of the XML files. The data for each XPath type are saved into the corresponding relational table that is named as the XPath itself. The generation of table definitions from the PDBMLplus XML schema is fully automated. For efficient search, frequently queried terms are compiled into a brief summary table. Casual users can perform simple keyword search, and 'Advanced Search' which can specify various conditions on the entries. More experienced users can query the database using SQL statements which can be constructed in a uniform manner. Thus, PDBj Mine achieves a combination of the flexibility of XML documents and the robustness of the RDB. Database URL: http://www.pdbj.org/ PMID:20798081

Mining the Temporal Dimension of the Information Propagation

NASA Astrophysics Data System (ADS)

Berlingerio, Michele; Coscia, Michele; Giannotti, Fosca

In the last decade, Social Network Analysis has been a field in which the effort devoted from several researchers in the Data Mining area has increased very fast. Among the possible related topics, the study of the information propagation in a network attracted the interest of many researchers, also from the industrial world. However, only a few answers to the questions “How does the information propagates over a network, why and how fast?” have been discovered so far. On the other hand, these answers are of large interest, since they help in the tasks of finding experts in a network, assessing viral marketing strategies, identifying fast or slow paths of the information inside a collaborative network. In this paper we study the problem of finding frequent patterns in a network with the help of two different techniques: TAS (Temporally Annotated Sequences) mining, aimed at extracting sequential patterns where each transition between two events is annotated with a typical transition time that emerges from input data, and Graph Mining, which is helpful for locally analyzing the nodes of the networks with their properties. Finally we show preliminary results done in the direction of mining the information propagation over a network, performed on two well known email datasets, that show the power of the combination of these two approaches.

PDBj Mine: design and implementation of relational database interface for Protein Data Bank Japan.

PubMed

Kinjo, Akira R; Yamashita, Reiko; Nakamura, Haruki

2010-08-25

This article is a tutorial for PDBj Mine, a new database and its interface for Protein Data Bank Japan (PDBj). In PDBj Mine, data are loaded from files in the PDBMLplus format (an extension of PDBML, PDB's canonical XML format, enriched with annotations), which are then served for the user of PDBj via the worldwide web (WWW). We describe the basic design of the relational database (RDB) and web interfaces of PDBj Mine. The contents of PDBMLplus files are first broken into XPath entities, and these paths and data are indexed in the way that reflects the hierarchical structure of the XML files. The data for each XPath type are saved into the corresponding relational table that is named as the XPath itself. The generation of table definitions from the PDBMLplus XML schema is fully automated. For efficient search, frequently queried terms are compiled into a brief summary table. Casual users can perform simple keyword search, and 'Advanced Search' which can specify various conditions on the entries. More experienced users can query the database using SQL statements which can be constructed in a uniform manner. Thus, PDBj Mine achieves a combination of the flexibility of XML documents and the robustness of the RDB. Database URL: http://www.pdbj.org/

Trace Metal Content of Sediments Close to Mine Sites in the Andean Region

PubMed Central

Yacoub, Cristina; Pérez-Foguet, Agustí; Miralles, Nuria

2012-01-01

This study is a preliminary examination of heavy metal pollution in sediments close to two mine sites in the upper part of the Jequetepeque River Basin, Peru. Sediment concentrations of Al, As, Cd, Cu, Cr, Fe, Hg, Ni, Pb, Sb, Sn, and Zn were analyzed. A comparative study of the trace metal content of sediments shows that the highest concentrations are found at the closest points to the mine sites in both cases. The sediment quality analysis was performed using the threshold effect level of the Canadian guidelines (TEL). The sediment samples analyzed show that potential ecological risk is caused frequently at both sites by As, Cd, Cu, Hg, Pb, and Zn. The long-term influence of sediment metals in the environment is also assessed by sequential extraction scheme analysis (SES). The availability of metals in sediments is assessed, and it is considered a significant threat to the environment for As, Cd, and Sb close to one mine site and Cr and Hg close to the other mine site. Statistical analysis of sediment samples provides a characterization of both subbasins, showing low concentrations of a specific set of metals and identifies the main characteristics of the different pollution sources. A tentative relationship between pollution sources and possible ecological risk is established. PMID:22606058

Mining moving object trajectories in location-based services for spatio-temporal database update

NASA Astrophysics Data System (ADS)

Guo, Danhuai; Cui, Weihong

2008-10-01

Advances in wireless transmission and mobile technology applied to LBS (Location-based Services) flood us with amounts of moving objects data. Vast amounts of gathered data from position sensors of mobile phones, PDAs, or vehicles hide interesting and valuable knowledge and describe the behavior of moving objects. The correlation between temporal moving patterns of moving objects and geo-feature spatio-temporal attribute was ignored, and the value of spatio-temporal trajectory data was not fully exploited too. Urban expanding or frequent town plan change bring about a large amount of outdated or imprecise data in spatial database of LBS, and they cannot be updated timely and efficiently by manual processing. In this paper we introduce a data mining approach to movement pattern extraction of moving objects, build a model to describe the relationship between movement patterns of LBS mobile objects and their environment, and put up with a spatio-temporal database update strategy in LBS database based on trajectories spatiotemporal mining. Experimental evaluation reveals excellent performance of the proposed model and strategy. Our original contribution include formulation of model of interaction between trajectory and its environment, design of spatio-temporal database update strategy based on moving objects data mining, and the experimental application of spatio-temporal database update by mining moving objects trajectories.

Potential synergy: the thorium fuel cycle and rare earths processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ault, T.; Wymer, R.; Croff, A.

2013-07-01

The use of thorium in nuclear power programs has been evaluated on a recurring basis. A concern often raised is the lack of 'thorium infrastructure'; however, for at least a part of a potential thorium fuel cycle, this may less of a problem than previously thought. Thorium is frequently encountered in association with rare earth elements and, since the U.S. last systematically evaluated the large-scale use of thorium (the 1970's,) the use of rare earth elements has increased ten-fold to approximately 200,000 metric tons per year. Integration of thorium extraction with rare earth processing has been previously described and top-levelmore » estimates have been done on thorium resource availability; however, since ores and mining operations differ markedly, what is needed is process flowsheet analysis to determine whether a specific mining operation can feasibly produce thorium as a by-product. Also, the collocation of thorium with rare earths means that, even if a thorium product stream is not developed, its presence in mining waste streams needs to be addressed and there are previous instances where this has caused issues. This study analyzes several operational mines, estimates the mines' ability to produce a thorium by-product stream, and discusses some waste management implications of recovering thorium. (authors)« less

Development and implementation of the Good Neighbor Agreement (GNA) practice in the USA sustainable mining development.

NASA Astrophysics Data System (ADS)

Masaitis, Alexandra

2014-05-01

New economic, environmental and social challenges for the mining industry in the USA show the need to implement "responsible" mining practices that include improved community involvement. Conflicts which occur in the US territory and with US mining companies around the world are now common between the mining proponents, NGO's and communities. These conflicts can sometimes be alleviated by early development of modes of communication, and a formal discussion format that allows airing of concerns and potential resolution of problems. One of the methods that can formalize this process is to establish a Good Neighbor Agreement (GNA), which deals specifically with challenges in relationships between mining operations and the local communities. It is a new practice related to mining operations that are oriented toward social needs and concerns of local communities that arise during the normal life of a mine, which can achieve sustainable mining practices. The GNA project being currently developed at the University of Nevada, USA in cooperation with the Newmont Mining Corporation has a goal of creating an open company/community dialog that will help identify and address sociological and environmental concerns associated with mining. Discussion: The Good Neighbor Agreement currently evolving will address the following: 1. Identify spheres of possible cooperation between mining companies, government organizations, and NGO's. 2. Provide an economically viable mechanism for developing a partnership between mining operations and the local communities that will increase mining industry's accountability and provide higher levels of confidence for the community that a mine is operated in a safe and sustainable manner. Implementation of the GNA can help identify and evaluate conflict criteria in mining/community relationships; determine the status of concerns; determine the role and responsibilities of stakeholders; analyze problem resolution feasibility; maintain the community involvement and support through economic benefits and environmental safeguards; develop options for the concerns resolution. Difficulties in establishing the GNA standards include lack of insurance/bonding policies, and by the lack of audit and monitoring that could determine the level of exposure of the local community and the environment to the contaminants released at the mine sites. Since many problems of mines can occur during closure and post-closure, GNA's should address those issues also. The goal of the GNA is to have open access for the public to the safety, health, and environmental information pertaining to the mining operation, as well as to educate the local communities about mining practices that promote mutual acknowledgment of the need to build a relationship amenable to each other's needs. Frequent conflicts between mining companies and surrounding communities lead to work disruptions or even mine closures and show the necessity of a less confrontational approach to environmental and social justice. The Good Neighbor Agreement is a unique way to provide the benefits for the both mining operations and local community to provide a mechanism for risk redaction and communication that offer the potential to protect both mining and community interests.

A Method of Cross-Level Frequent Pattern Mining for Web-Based Instruction

ERIC Educational Resources Information Center

Huang, Yueh-Min; Chen, Juei-Nan; Cheng, Shu-Chen

2007-01-01

Due to the rise of e-Learning, more and more useful learning materials are open to public access. Therefore, an appropriate learning suggestion mechanism is an important tool to enable learners to work more efficiently. A smoother learning process increases the learning effect, avoiding unnecessarily difficult concepts and disorientation during…

Improving the Scalability of an Exact Approach for Frequent Item Set Hiding

ERIC Educational Resources Information Center

LaMacchia, Carolyn

2013-01-01

Technological advances have led to the generation of large databases of organizational data recognized as an information-rich, strategic asset for internal analysis and sharing with trading partners. Data mining techniques can discover patterns in large databases including relationships considered strategically relevant to the owner of the data.…

Development of rapid methods for measuring stream ecosystem functions in the Appalachian coal mining region: preliminary results

EPA Science Inventory

Headwater streams represent the majority of U.S. stream miles. As a consequence of being abundant and widespread, the alteration and loss of headwater streams may have impacts on downstream waterbodies. These streams are frequently the subject of proposed dredge and fill projects...

Mycobacteria in water used for personal hygiene in heavy industry and collieries: a potential risk for employees.

PubMed

Ulmann, Vit; Kracalikova, Anna; Dziedzinska, Radka

2015-03-04

Environmental mycobacteria (EM) constitute a health risk, particularly for immunocompromised people. Workers in heavy industry and in collieries represent an at-risk group of people as their immunity is often weakened by long-term employment in dusty environments, frequent smoking and an increased occurrence of pulmonary diseases. This study was concerned with the presence of EM in non-drinking water used for the hygiene of employees in six large industrial companies and collieries. Over a period of ten years, 1096 samples of surface water treated for hygiene purposes (treated surface water) and treated surface water diluted with mining water were examined. EM were detected in 63.4 and 41.5% samples of treated surface water and treated surface water diluted with mining water, respectively. Mycobacterium gordonae, M. avium-intracellulare and M. kansasii were the most frequently detected species. Adoption of suitable precautions should be enforced to reduce the incidence of mycobacteria in shower water and to decrease the infectious pressure on employees belonging to an at-risk group of people.

Social cost of land mines in four countries: Afghanistan, Bosnia, Cambodia, and Mozambique.

PubMed Central

Andersson, N.; da Sousa, C. P.; Paredes, S.

1995-01-01

OBJECTIVES--To document the effects of land mines on the health and social conditions of communities in four affected countries. DESIGN--A cross design of cluster survey and rapid appraisal methods including a household questionnaire and qualitative data from key informants, institutional reviews, and focus groups of survivors of land mines from the same communities. SETTING--206 communities, 37 in Afghanistan, 66 in Bosnia, 38 in Cambodia, and 65 in Mozambique. SUBJECTS--174,489 people living in 32,904 households in the selected communities. MAIN OUTCOME MEASURES--Effects of land mines on food security, residence, livestock, and land use; risk factors: extent of individual land mine injuries; physical, psychological, social, and economic costs of injuries during medical care and rehabilitation. RESULTS--Between 25% and 87% of households had daily activities affected by land mines. Based on expected production without the mines, agricultural production could increase by 88-200% in different regions of Afghanistan, 11% in Bosnia, 135% in Cambodia, and 3.6% in Mozambique. A total of 54,554 animals was lost because of land mines, with a minimum cash value of $6.5m, or nearly $200 per household. Overall, 6% of households (1964) reported a land mine victim; a third of victims died in the blast. One in 10 of the victims was a child. The most frequent activities associated with land mine incidents were agricultural or pastoral, except in Bosnia where more than half resulted from military activities, usually during patrols. Incidences have more than doubled between 1980-3 and 1990-3, excluding the incidents in Bosnia. Some 22% of victims (455/2100) were from households reporting attempts to remove land mines; in these households there was a greatly increased risk of injury (odds ratio 4.2 and risk difference 19% across the four countries). Lethality of the mines varied; in Bosnia each blast killed an average of 0.54 people and injured 1.4, whereas in Mozambique each blast killed 1.45 people and wounded 1.27. Households with a land mine victim were 40% more likely to experience difficulty in providing food for the family. Family relationships were affected for around one in every four victims and relationships with colleagues in 40%. CONCLUSIONS--Land mines seriously undermine the economy and food security in affected countries; they kill and maim civilians at an increasing rate. The expense of medical care and rehabilitation add economic disability to the physical burden. Awareness of land mines can be targeted at high risk attitudes, such as those associated with tampering with mines. PMID:7549685

Social cost of land mines in four countries: Afghanistan, Bosnia, Cambodia, and Mozambique.

PubMed

Andersson, N; da Sousa, C P; Paredes, S

1995-09-16

To document the effects of land mines on the health and social conditions of communities in four affected countries. A cross design of cluster survey and rapid appraisal methods including a household questionnaire and qualitative data from key informants, institutional reviews, and focus groups of survivors of land mines from the same communities. 206 communities, 37 in Afghanistan, 66 in Bosnia, 38 in Cambodia, and 65 in Mozambique. 174,489 people living in 32,904 households in the selected communities. Effects of land mines on food security, residence, livestock, and land use; risk factors: extent of individual land mine injuries; physical, psychological, social, and economic costs of injuries during medical care and rehabilitation. Between 25% and 87% of households had daily activities affected by land mines. Based on expected production without the mines, agricultural production could increase by 88-200% in different regions of Afghanistan, 11% in Bosnia, 135% in Cambodia, and 3.6% in Mozambique. A total of 54,554 animals was lost because of land mines, with a minimum cash value of $6.5m, or nearly $200 per household. Overall, 6% of households (1964) reported a land mine victim; a third of victims died in the blast. One in 10 of the victims was a child. The most frequent activities associated with land mine incidents were agricultural or pastoral, except in Bosnia where more than half resulted from military activities, usually during patrols. Incidences have more than doubled between 1980-3 and 1990-3, excluding the incidents in Bosnia. Some 22% of victims (455/2100) were from households reporting attempts to remove land mines; in these households there was a greatly increased risk of injury (odds ratio 4.2 and risk difference 19% across the four countries). Lethality of the mines varied; in Bosnia each blast killed an average of 0.54 people and injured 1.4, whereas in Mozambique each blast killed 1.45 people and wounded 1.27. Households with a land mine victim were 40% more likely to experience difficulty in providing food for the family. Family relationships were affected for around one in every four victims and relationships with colleagues in 40%. Land mines seriously undermine the economy and food security in affected countries; they kill and maim civilians at an increasing rate. The expense of medical care and rehabilitation add economic disability to the physical burden. Awareness of land mines can be targeted at high risk attitudes, such as those associated with tampering with mines.

An efficient, versatile and scalable pattern growth approach to mine frequent patterns in unaligned protein sequences.

PubMed

Ye, Kai; Kosters, Walter A; Ijzerman, Adriaan P

2007-03-15

Pattern discovery in protein sequences is often based on multiple sequence alignments (MSA). The procedure can be computationally intensive and often requires manual adjustment, which may be particularly difficult for a set of deviating sequences. In contrast, two algorithms, PRATT2 (http//www.ebi.ac.uk/pratt/) and TEIRESIAS (http://cbcsrv.watson.ibm.com/) are used to directly identify frequent patterns from unaligned biological sequences without an attempt to align them. Here we propose a new algorithm with more efficiency and more functionality than both PRATT2 and TEIRESIAS, and discuss some of its applications to G protein-coupled receptors, a protein family of important drug targets. In this study, we designed and implemented six algorithms to mine three different pattern types from either one or two datasets using a pattern growth approach. We compared our approach to PRATT2 and TEIRESIAS in efficiency, completeness and the diversity of pattern types. Compared to PRATT2, our approach is faster, capable of processing large datasets and able to identify the so-called type III patterns. Our approach is comparable to TEIRESIAS in the discovery of the so-called type I patterns but has additional functionality such as mining the so-called type II and type III patterns and finding discriminating patterns between two datasets. The source code for pattern growth algorithms and their pseudo-code are available at http://www.liacs.nl/home/kosters/pg/.

Reclamation technology development for western Arkansas coal refuse waste materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

King, J.R.; Veith, D.L.

Coal mining has been an important industry in the Arkansas River Valley Major Land Resource Area (MLRA) of western Arkansas for more than 100 yr., most of it with little regard for environmental concerns. Almost 3,640 ha. of land affected by surface coal mines cover the seven-county area, with less than 1,200 ha. currently in various stages of operation or reclamation. Since only the active mining sites must now be reclaimed by law, the remaining 2,440 ha. of abandoned land remains at the mercy of natural forces. Little topsoil exists on these sites and the coal wastes are generally acidicmore » with a pH in the 4.0-5.5 range. Revegetation attempts under these conditions generally require continued maintenance and retreatment until an acceptable cover is achieved. If and when an acceptable vegetative cover is established, the cost frequently approaches $7,400/ha. ($3,000/acre). In an effort to resolve these issues and provide some direction for stabilizing coal waste lands, the US Department of Agriculture through its Soil Conservation Service Plant Materials Center at Boonville, Arkansas, received a Congressional Pass through administered by the US Bureau of Mines, to support a 5-yr. revegetation study on the coal mine spoils of western Arkansas. This paper reports the results through the spring of 1994 on that portion of the study dealing with the establishment of blackberries as a cash crop on coal mine spoils.« less

Systematic Review of Data Mining Applications in Patient-Centered Mobile-Based Information Systems.

PubMed

Fallah, Mina; Niakan Kalhori, Sharareh R

2017-10-01

Smartphones represent a promising technology for patient-centered healthcare. It is claimed that data mining techniques have improved mobile apps to address patients' needs at subgroup and individual levels. This study reviewed the current literature regarding data mining applications in patient-centered mobile-based information systems. We systematically searched PubMed, Scopus, and Web of Science for original studies reported from 2014 to 2016. After screening 226 records at the title/abstract level, the full texts of 92 relevant papers were retrieved and checked against inclusion criteria. Finally, 30 papers were included in this study and reviewed. Data mining techniques have been reported in development of mobile health apps for three main purposes: data analysis for follow-up and monitoring, early diagnosis and detection for screening purpose, classification/prediction of outcomes, and risk calculation (n = 27); data collection (n = 3); and provision of recommendations (n = 2). The most accurate and frequently applied data mining method was support vector machine; however, decision tree has shown superior performance to enhance mobile apps applied for patients' self-management. Embedded data-mining-based feature in mobile apps, such as case detection, prediction/classification, risk estimation, or collection of patient data, particularly during self-management, would save, apply, and analyze patient data during and after care. More intelligent methods, such as artificial neural networks, fuzzy logic, and genetic algorithms, and even the hybrid methods may result in more patients-centered recommendations, providing education, guidance, alerts, and awareness of personalized output.

Optimising post-mining soil conditions to maximise restoration success in a biodiverse semiarid environment

NASA Astrophysics Data System (ADS)

Muñoz-Rojas, Miriam; Erickson, Todd; Merritt, David; Dixon, Kingsley

2014-05-01

The original topsoil of mine degraded areas is frequently lost or damaged, which together with the absence of soil forming materials is a major constraint for seed germination and establishment in post-mining restoration. Thus, management of the available topsoil and the use of alternative growth media are critical to improve restoration areas disturbed through mining. Here we are developing laboratory and field trials to define the optimal range for physical and chemical properties of potentially suitable natural and 're-made' soil substrates and growth medium for 20 selected native plant species from the mining intensive Pilbara region of Western Australia. In this semiarid area, water is a limiting factor for seedling establishment, which is compounded by the lack of organic matter of post-disturbance soils. Therefore, particular attention is given to indicators of soil biological activity such as soil respiration, and hydrological soil properties such as water holding capacity, infiltration, hydraulic conductivity and soil water repellence. This research is part of a broader multi-study approach, the Restoration Seedbank Initiative project, a partnership between The University of Western Australia, BHP Billiton Iron Ore, and Kings Park and Botanic Garden to develop the science and underpinning knowledge to achieve biodiverse restoration in the Pilbara region, where land areas disturbed by mining exceed 40,000 ha. Achieving restoration success is critical as the Pilbara region is an ancient landscape with diverse geology and high levels of regional and local endemism in plants and animals.

Forming artificial soils from waste materials for mine site rehabilitation

NASA Astrophysics Data System (ADS)

Yellishetty, Mohan; Wong, Vanessa; Taylor, Michael; Li, Johnson

2014-05-01

Surface mining activities often produce large volumes of solid wastes which invariably requires the removal of significant quantities of waste rock (overburden). As mines expand, larger volumes of waste rock need to be moved which also require extensive areas for their safe disposal and containment. The erosion of these dumps may result in landform instability, which in turn may result in exposure of contaminants such as trace metals, elevated sediment delivery in adjacent waterways, and the subsequent degradation of downstream water quality. The management of solid waste materials from industrial operations is also a key component for a sustainable economy. For example, in addition to overburden, coal mines produce large amounts of waste in the form of fly ash while sewage treatment plants require disposal of large amounts of compost. Similarly, paper mills produce large volumes of alkaline rejected wood chip waste which is usually disposed of in landfill. These materials, therefore, presents a challenge in their use, and re-use in the rehabilitation of mine sites and provides a number of opportunities for innovative waste disposal. The combination of solid wastes sourced from mines, which are frequently nutrient poor and acidic, with nutrient-rich composted material produced from sewage treatment and alkaline wood chip waste has the potential to lead to a soil suitable for mine rehabilitation and successful seed germination and plant growth. This paper presents findings from two pilot projects which investigated the potential of artificial soils to support plant growth for mine site rehabilitation. We found that pH increased in all the artificial soil mixtures and were able to support plant establishment. Plant growth was greatest in those soils with the greatest proportion of compost due to the higher nutrient content. These pot trials suggest that the use of different waste streams to form an artificial soil can potentially be used in mine site rehabilitation where there is a nutrient-rich source of waste.

Metal contamination and post-remediation recovery in the Boulder River watershed, Jefferson County, Montana

USGS Publications Warehouse

Unruh, Daniel M.; Church, Stanley E; Nimick, David A.; Fey, David L.

2009-01-01

The legacy of acid mine drainage and toxic trace metals left in streams by historical mining is being addressed by many important yet costly remediation efforts. Monitoring of environmental conditions frequently is not performed but is essential to evaluate remediation effectiveness, determine whether clean-up goals have been met, and assess which remediation strategies are most effective. Extensive pre- and post-remediation data for water and sediment quality for the Boulder River watershed in southwestern Montana provide an unusual opportunity to demonstrate the importance of monitoring. The most extensive restoration in the watershed occurred at the Comet mine on High Ore Creek and resulted in the most dramatic improvement in aquatic habitat. Removal of contaminated sediment and tailings, and stream-channel reconstruction reduced Cd and Zn concentrations in water such that fish are now present, and reduced metal concentrations in streambed sediment by a factor of c. 10, the largest improvement in the district. Waste removals at the Buckeye/Enterprise and Bullion mine sites produced limited or no improvement in water and sediment quality, and acidic drainage from mine adits continues to degrade stream aquatic habitat. Recontouring of hillslopes that had funnelled runoff into the workings of the Crystal mine substantially reduced metal concentrations in Uncle Sam Gulch, but did not eliminate all of the acidic adit drainage. Lead isotopic evidence suggests that the Crystal mine rather than the Comet mine is now the largest source of metals in streambed sediment of the Boulder River. The completed removal actions prevent additional contaminants from entering the stream, but it may take many years for erosional processes to diminish the effects of contaminated sediment already in streams. Although significant strides have been made, additional efforts to seal draining adits or treat the adit effluent at the Bullion and Crystal mines would need to be completed to achieve the desired restoration.

Suspended sediment load below open-cast mines for ungauged river basin

NASA Astrophysics Data System (ADS)

Kuksina, L.

2011-12-01

Placer mines are located in river valleys along river benches or river ancient channels. Frequently the existing mining sites are characterized by low contribution of the environmental technologies. Therefore open-pit mining alters stream hydrology and sediment processes and enhances sediment transport. The most serious environmental consequences of the sediment yield increase occur in the rivers populated by salmon fish community because salmon species prefer clean water with low turbidity. For instance, placer mining located in Kamchatka peninsula (Far East of Russia) which is regarded to be the last global gene pool of wild salmon Oncorhynchus threatens rivers ecosystems significantly. Impact assessment is limited by the hydrological observations scarcity. Gauging network is rare and in many cases whole basins up to 200 km length miss any hydrological data. The main purpose of the work is elaboration of methods for sediment yield estimation in rivers under mining impact and implementation of corresponding calculations. Subjects of the study are rivers of the Vivenka river basin where open-cast platinum mine is situated. It's one of the largest platinum mines in Russian Federation and in the world. This mine is the most well-studied in Kamchatka (research covers a period from 2003 to 2011). Empirical - analytical model of suspended sediment yield estimation was elaborated for rivers draining mine's territories. Sediment delivery at the open-cast mine happens due to the following sediment processes: - erosion in the channel diversions; - soil erosion on the exposed hillsides; - effluent from settling ponds; - mine waste water inflow; - accident mine waste water escape into rivers. Sediment washout caused by erosion was estimated by repeated measurements of the channel profiles in 2003, 2006 and 2008. Estimation of horizontal deformation rates was carried out on the basis of erosion dependence on water discharge rates, slopes and composition of sediments. Soil erosion on the exposed hillsides was estimated taking into account precipitation of various intensity and solid material washout during this period. Effluent from settling ponds was calculated on the basis of minimum anthropogenic turbidity. Its value is difference in background turbidity and minimal turbidity caused by effluent and waste water overflow. Mine waste water inflow was estimated due to actual data on water balance of purification system. Accident mine waste water escape into rivers was estimated by duration and material washout during accidents data measured during observation period. Total suspended sediment yield of rivers draining mine's territory is the sum of its components. Total sediment supply from mining site is 24.7 % from the Vivenka sediment yield. Polluted placer-mined rivers contribute about 35.4 % of the whole sediment yield of the Vivenka river. At the same time the catchment area of these rivers is less than 0.2 % from the whole Vivenka catchment area.

Efficient Mining of Interesting Patterns in Large Biological Sequences

PubMed Central

Rashid, Md. Mamunur; Karim, Md. Rezaul; Jeong, Byeong-Soo

2012-01-01

Pattern discovery in biological sequences (e.g., DNA sequences) is one of the most challenging tasks in computational biology and bioinformatics. So far, in most approaches, the number of occurrences is a major measure of determining whether a pattern is interesting or not. In computational biology, however, a pattern that is not frequent may still be considered very informative if its actual support frequency exceeds the prior expectation by a large margin. In this paper, we propose a new interesting measure that can provide meaningful biological information. We also propose an efficient index-based method for mining such interesting patterns. Experimental results show that our approach can find interesting patterns within an acceptable computation time. PMID:23105928

Efficient mining of interesting patterns in large biological sequences.

PubMed

Rashid, Md Mamunur; Karim, Md Rezaul; Jeong, Byeong-Soo; Choi, Ho-Jin

2012-03-01

Pattern discovery in biological sequences (e.g., DNA sequences) is one of the most challenging tasks in computational biology and bioinformatics. So far, in most approaches, the number of occurrences is a major measure of determining whether a pattern is interesting or not. In computational biology, however, a pattern that is not frequent may still be considered very informative if its actual support frequency exceeds the prior expectation by a large margin. In this paper, we propose a new interesting measure that can provide meaningful biological information. We also propose an efficient index-based method for mining such interesting patterns. Experimental results show that our approach can find interesting patterns within an acceptable computation time.

The numerical simulation on the stability of steep rock slope by DDA

NASA Astrophysics Data System (ADS)

Zhu, Jianye; Xue, Yiguo; Tao, Yufan; Zhang, Kai; Li, Zhiqiang; Zhang, Xuedong; Yang, Ying

2017-05-01

China is a mountainous country, especially in the southwest area. Recently, the variety of geological disasters such as landslides caused by roadway excavation has become a growing concern for our society. Blindly pursuing mining interests without regard for either the environment or residents in the surrounding areas has created a dangerous situation. In recent years, frequent collapses have occurred at Zengzi Rock in Chongqing, especially after torrential rains [1]. This landslide site is a typical example of collapse caused by mine roadway excavations. To study the mechanism of mining slope stability, we conducted a numerical simulation by DDA based on Zengzi Rock in Chongqing, China. The numerical simulation analyzes the slopes under different engineering conditions and rainfall conditions. The results show that the slope has already been changed under the action of its own joints and fissures. After the excavation of the roadway and the rainfall action, this change is drastically increased and the effect is obvious. Through the result graph, we can find that the change of the displacement and stress distribution is obvious, and the simulation results can be great significance to the mining and support of similar mountain conditions.

Mineral saturation states in natural waters and their sensitivity to thermodynamic and analytical errors

USGS Publications Warehouse

Nordstrom, D. Kirk; Ball, James W.

1989-01-01

Saturation indices computed with WATEQ4F chemical analyses from a groundwater in crystalline bedrock and a surface water receiving acid mine drainage are frequently at or above saturation with respect to calcite, fluorite, barite, gibbsite and ferrihydrite. Deep granitic groundwaters from Stripa, Sweden, are supersaturated with respect to calcite and fluorite. Acid mine waters from the Leviathan Mine drainage basin in California are supersaturated with respect to barite by about a factor of three. These mine waters also are 10 times supersaturated with respect to the most soluble form of ferric hydroxide but are near saturation with respect to microcrystalline gibbsite. A sensitivity analysis has been performed by varying the analytic and thermodynamic parameters for which the saturation indices are most sensitive. For calcite, fluorite and barite, the supersaturation effect appears to be real because it is only slightly decreased by sources of uncertainty. Apparent supersaturation for gibbsite is most likely caused by the degree of crystallinity on solubility behavior. Apparent supersaturation for ferric hydroxide is likely caused by small colloidal particles (< 0.1 µm) in the water sample that cannot be removed by standard field filtration, although several other possible explanations cannot be easily excluded.

Effects of host-plant population size and plant sex on a specialist leaf-miner

NASA Astrophysics Data System (ADS)

Bañuelos, María-José; Kollmann, Johannes

2011-03-01

Animal population density has been related to resource patch size through various hypotheses such as those derived from island biogeography and resource concentration theory. This theoretical framework can be also applied to plant-herbivore interactions, and it can be modified by the sex of the host-plant, and density-dependent relationships. Leaf-miners are specialised herbivores that leave distinct traces on infested leaves in the form of egg scars, mines, signs of predation and emergence holes. This allows the life cycle of the insect to be reconstructed and the success at the different stages to be estimated. The main stages of the leaf-miner Phytomyza ilicis were recorded in eleven populations of the evergreen host Ilex aquifolium in Denmark. Survival rates were calculated and related to population size, sex of the host plant, and egg and mine densities. Host population size was negatively related to leaf-miner prevalence, with larger egg and mine densities in small populations. Percentage of eggs hatching and developing into mines, and percentage of adult flies emerging from mines also differed among host populations, but were not related to population size or host cover. Feeding punctures left by adults were marginally more frequent on male plants, whereas egg scars and mines were more common on females. Overall survival rate from egg stage to adult emergence was higher on female plants. Egg density was negatively correlated with hatching, while mine density was positively correlated with emergence of the larvae. The inverse effects of host population size were not in line with predictions based on island biogeography and resource concentration theory. We discuss how a thorough knowledge of the immigration behaviour of this fly might help to understand the patterns found.

The ACODEA Framework: Developing Segmentation and Classification Schemes for Fully Automatic Analysis of Online Discussions

ERIC Educational Resources Information Center

Mu, Jin; Stegmann, Karsten; Mayfield, Elijah; Rose, Carolyn; Fischer, Frank

2012-01-01

Research related to online discussions frequently faces the problem of analyzing huge corpora. Natural Language Processing (NLP) technologies may allow automating this analysis. However, the state-of-the-art in machine learning and text mining approaches yields models that do not transfer well between corpora related to different topics. Also,…

The canary in the coal mine: Sprouts as a rapid indicator of browse impact in managed forests

Treesearch

Alex Royo; David W. Kramer; Karl V. Miller; Nathan P. Nibbelink; Susan L. Stout

2016-01-01

Forest managers are frequently confronted with sustaining vegetation diversity and structure in land-scapes experiencing high ungulate browsing pressure. Often, managers monitor browse damage and risk to plant communities using vegetation as indicators (i.e., phytoindicators). Although useful, the efficacy of traditional phytoindicators is sometimes hampered by limited...

Data mining for the identification of metabolic syndrome status

PubMed Central

Worachartcheewan, Apilak; Schaduangrat, Nalini; Prachayasittikul, Virapong; Nantasenamat, Chanin

2018-01-01

Metabolic syndrome (MS) is a condition associated with metabolic abnormalities that are characterized by central obesity (e.g. waist circumference or body mass index), hypertension (e.g. systolic or diastolic blood pressure), hyperglycemia (e.g. fasting plasma glucose) and dyslipidemia (e.g. triglyceride and high-density lipoprotein cholesterol). It is also associated with the development of diabetes mellitus (DM) type 2 and cardiovascular disease (CVD). Therefore, the rapid identification of MS is required to prevent the occurrence of such diseases. Herein, we review the utilization of data mining approaches for MS identification. Furthermore, the concept of quantitative population-health relationship (QPHR) is also presented, which can be defined as the elucidation/understanding of the relationship that exists between health parameters and health status. The QPHR modeling uses data mining techniques such as artificial neural network (ANN), support vector machine (SVM), principal component analysis (PCA), decision tree (DT), random forest (RF) and association analysis (AA) for modeling and construction of predictive models for MS characterization. The DT method has been found to outperform other data mining techniques in the identification of MS status. Moreover, the AA technique has proved useful in the discovery of in-depth as well as frequently occurring health parameters that can be used for revealing the rules of MS development. This review presents the potential benefits on the applications of data mining as a rapid identification tool for classifying MS. PMID:29383020

Data mining for the identification of metabolic syndrome status.

PubMed

Worachartcheewan, Apilak; Schaduangrat, Nalini; Prachayasittikul, Virapong; Nantasenamat, Chanin

2018-01-01

Metabolic syndrome (MS) is a condition associated with metabolic abnormalities that are characterized by central obesity (e.g. waist circumference or body mass index), hypertension (e.g. systolic or diastolic blood pressure), hyperglycemia (e.g. fasting plasma glucose) and dyslipidemia (e.g. triglyceride and high-density lipoprotein cholesterol). It is also associated with the development of diabetes mellitus (DM) type 2 and cardiovascular disease (CVD). Therefore, the rapid identification of MS is required to prevent the occurrence of such diseases. Herein, we review the utilization of data mining approaches for MS identification. Furthermore, the concept of quantitative population-health relationship (QPHR) is also presented, which can be defined as the elucidation/understanding of the relationship that exists between health parameters and health status. The QPHR modeling uses data mining techniques such as artificial neural network (ANN), support vector machine (SVM), principal component analysis (PCA), decision tree (DT), random forest (RF) and association analysis (AA) for modeling and construction of predictive models for MS characterization. The DT method has been found to outperform other data mining techniques in the identification of MS status. Moreover, the AA technique has proved useful in the discovery of in-depth as well as frequently occurring health parameters that can be used for revealing the rules of MS development. This review presents the potential benefits on the applications of data mining as a rapid identification tool for classifying MS.

Post-mining deterioration of bauxite overburdens in Jamaica: storage methods or subsoil dilution?

NASA Astrophysics Data System (ADS)

Harris, Mark A.; Omoregie, Samson N.

2008-03-01

Rapid degradation of disturbed soil from a karst bauxite mine in Jamaica was recorded. Substantial macronutrient losses were incurred during a short (1 month) or a long (12 months) storage of the replaced topsoils during frequent wet/dry changes. The results suggested very high rates (>70% in the first year) of soil degradation from storage, alongside moderate rates (30%) within the same storage dump. However, higher levels of soil organic matter (SOM) were indicated just below the surface, compared with the surface horizons. It was unlikely that under a high leaching humid tropical rainfall regime, natural degradation processes could have re-emplaced such material firmly intact in the 15-30 cm zone. It was therefore concluded that these SOM anomalies were due to mechanical dilution of surface soil with subsoil material during overburden removal and emplacement rather than from long storage. Increasing the soil organic content during storage could be one corrective approach. However, it is far less costly to exercise greater care to apply more precise overburden removal and emplacement techniques initially, than it is to correct the results of topsoil contamination with subsoil. Although this study was limited to one mine, in the context of imminent large-scale mining expansion and current practices, further investigations are needed to accurately ascertain the proportion of similar subsoil contamination in other bauxite-mined sites.

Possibilities of Effective Inertisation of Self-Heating Places in Goaf of Longwall in Hard Coal Mines

NASA Astrophysics Data System (ADS)

Szlązak, Nikodem; Piergies, Kazimierz

2016-12-01

Underground fires in coal mines belong to the most common hazards, the exposure to which frequently requires long term and costly rescue operations. It is mainly connected with the specific character of underground excavations which have limited volume. This makes the maximum permissible concentration of harmful gases rapidly exceeded and may also cause changes in air flow direction. The most certain way of improving a safety situation in Polish coal mining industry is taking early prevention steps. One of the prevention methods is inertisation of the atmosphere in longwall goaf. These activities rely on partial or total replacement of air or combustible atmosphere by inert gas. Thanks to them the risk of spontaneous fires hazard and gas explosion decreases. The main reason for the use of inert gases is to reduce the oxygen content to a limit which prevents further development of fire. This article presents methods for assessing inert gas to replace oxygen in the atmosphere in goaf.

Reduction of Conflicts in Mining Development Using "Good Neighbor Agreements"

NASA Astrophysics Data System (ADS)

Masaitis, A.

2013-05-01

New environmental and social challenges for the mining industry in both developed and developing countries show the obvious need to implement "responsible" mining practices that include improved community involvement. Good Neighbor Agreements (GNA's) are a relatively new mechanism for improving communication and trust between a mining company and the community. The focus of a GNA will be to provide a written and enforceable agreement, negotiated between the concerned public and the respective mining company to respond to concerns from the public, and also provide a mechanism for conflict resolution, when there is mutual benefit to maintain a working relationship. Development of GNA's, a recently evolving process that promotes environmentally sound relationships between mines and the surrounding communities. Modify and apply the resulting GNA formulas to the developing countries and countries with transitional economies. This is particularly important for countries that have poorly functioning regulatory systems that cannot guarantee a healthy and safe environment for the communities. The fundamental questions addressed by this research. 1. This is a three-year research project started in August 2012 at the University of Nevada, Reno (UNR) to develop a Good Neighbor Agreements standards as well as to investigate the details of mine development. 2. Identify spheres of possible cooperation between mining companies, government organizations, and the Non-Governmental Organizations (NGO's). Use this cooperation to develop international standards for the GNA, to promote exchange of environmental information, and exchange of successful environmental, health, and safety practices between mining operations from different countries. Discussion: The Good Neighbor Agreement currently evolving will address the following: 1. Provide an economically viable mechanism for developing a partnership between mining operations and the local communities that will increase mining industry's accountability and provide higher levels of confidence for the community that a mine is operated in a safe and sustainable manner. 2. Increase the diversity of people benefiting from the results of this research by providing standards that could be adopted in developing countries. The goal of the GNA is to have open access for the public to the safety, health, and environmental information pertaining to the mining operation, as well as to educate the local communities about safe and sustainable mining practices that promote mutual acknowledgment of the need to build a relationship amenable to each other's needs. Frequent conflicts between mining companies and surrounding communities lead to work disruptions or even mine closures and show the necessity of a less confrontational approach to environmental and social justice. Because of the higher quality environmental standards already in place, this new approach perhaps should first be established in developed countries and then applied to other countries with less developed economies. The Good Neighbor Agreement is a unique way to provide the benefits for the both mining operations and local community to provide a mechanism for development of trust and communication that offer the potential to protect both mining and community interests, and can possibly reduce conflicts in resource development projects.

Thinking Like a Social Worker: Examining the Meaning of Critical Thinking in Social Work

ERIC Educational Resources Information Center

Mathias, John

2015-01-01

"Critical thinking" is frequently used to describe how social workers ought to reason. But how well has this concept helped us to develop a normative description of what it means to think like a social worker? This critical review mines the literature on critical thinking for insight into the kinds of thinking social work scholars…

Fault Tolerant Frequent Pattern Mining

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shohdy, Sameh; Vishnu, Abhinav; Agrawal, Gagan

FP-Growth algorithm is a Frequent Pattern Mining (FPM) algorithm that has been extensively used to study correlations and patterns in large scale datasets. While several researchers have designed distributed memory FP-Growth algorithms, it is pivotal to consider fault tolerant FP-Growth, which can address the increasing fault rates in large scale systems. In this work, we propose a novel parallel, algorithm-level fault-tolerant FP-Growth algorithm. We leverage algorithmic properties and MPI advanced features to guarantee an O(1) space complexity, achieved by using the dataset memory space itself for checkpointing. We also propose a recovery algorithm that can use in-memory and disk-based checkpointing,more » though in many cases the recovery can be completed without any disk access, and incurring no memory overhead for checkpointing. We evaluate our FT algorithm on a large scale InfiniBand cluster with several large datasets using up to 2K cores. Our evaluation demonstrates excellent efficiency for checkpointing and recovery in comparison to the disk-based approach. We have also observed 20x average speed-up in comparison to Spark, establishing that a well designed algorithm can easily outperform a solution based on a general fault-tolerant programming model.« less

Injuries among Artisanal and Small-Scale Gold Miners in Ghana

PubMed Central

Kyeremateng-Amoah, E.; Clarke, Edith E.

2015-01-01

Artisanal and small-scale gold miners are confronted with numerous hazards often resulting in varying degrees of injuries and fatalities. In Ghana, like many developing countries, there is paucity of information on the causes and nature of the accidents that result in the injuries. The study was a retrospective, cross sectional type that examined the records of injuries of artisanal and small-scale gold miners presented to the emergency department of a district hospital in the Eastern Region of Ghana from 2006 to 2013. The causes, types, and outcomes of reported injuries were analyzed for 72 cases. Occurrences of mining accidents reported in selected Ghanaian media during the year 2007–2012 were also analyzed to corroborate the causes of the accidents. Fractures and contusions constituted the most frequently occurring injuries, with collapse of the mine pits and falls being the most frequent cause of accidents reported both by the hospital and media records. This study shows that though varied degrees of injuries occur among the miners, the potential for serious injuries is substantial. Measures to reduce the incidence of injuries and fatalities should include education and training on the use of safe working tools and means of creating a safe working environment. PMID:26404345

[Lung Cancer as an Occupational Disease].

PubMed

Baur, X; Woitowitz, H-J

2016-08-01

Lung cancer is one of the most frequently encountered cancer types. According to the latest WHO data, about 10 % of this disease are due to occupational exposure to cancerogens. Asbestos is still the number one carcinogen. Further frequent causes include quarz and ionizing radiation (uranium mining). Probable causes of the disease can be identified only with the help of detailed occupational history taken by a medical specialist and qualified exposure assessment. Without clarifying the cause of the disease, there is neither a correct insurance procedure nor compensation for the victim, and furthermore, required preventive measures cannot be initiated. © Georg Thieme Verlag KG Stuttgart · New York.

Sodium cyanide hazards to fish and other wildlife from gold mining operations

USGS Publications Warehouse

Eisler, R.; Clark, D.R.; Wiemeyer, Stanley N.; Henny, C.J.; Azcue, Jose M.

1999-01-01

Highly toxic sodium cyanide (NaCN) is used increasingly by the international mining community to extract gold and other precious metals through milling of high grade ores and heap leaching of low grade ores. Of the 98 million kg cyanide (CN) consumed in North America in 1989, about 80% was used in gold mining (Knudson 1990). In Canada, more than 90% of the mined gold is extracted from ores with the cyanidation process. This process consists of leaching gold from the ore as a gold-cyanide complex, and gold being recovered by precipitation (Simovic and Snodgrass 1985). Milling and heap leaching require cycling of millions of liters of alkaline water containing high concentrations of potentially toxic NaCN, free cyanide, and metal cyanide complexes that are frequently accessible to wildlife. Some milling operations result in tailings ponds of 150 ha and larger. Heap leach operations that spray or drip cyanide solution onto the flattened top of the ore heap require solution processing ponds of about 1 ha in surface area. Although not intentional or desired, puddles of various sizes may occur on the top of heaps where the highest concentrations of NaCN are found. Exposed solution recovery channels are usually constructed at the base of leach heaps. All of these cyanidecontaining water bodies are hazardous to wildlife if not properly managed (Henny et al. 1994). In this account we emphasize hazards of cyanide from mining operations to fish and wildlife species and proposed mitigation to protect them.

A case in support of implementing innovative bio-processes in the metal mining industry.

PubMed

Sánchez-Andrea, Irene; Stams, Alfons J M; Weijma, Jan; Gonzalez Contreras, Paula; Dijkman, Henk; Rozendal, Rene A; Johnson, D Barrie

2016-06-01

The metal mining industry faces many large challenges in future years, among which is the increasing need to process low-grade ores as accessible higher grade ores become depleted. This is against a backdrop of increasing global demands for base and precious metals, and rare earth elements. Typically about 99% of solid material hauled to, and ground at, the land surface currently ends up as waste (rock dumps and mineral tailings). Exposure of these to air and water frequently leads to the formation of acidic, metal-contaminated run-off waters, referred to as acid mine drainage, which constitutes a severe threat to the environment. Formation of acid drainage is a natural phenomenon involving various species of lithotrophic (literally 'rock-eating') bacteria and archaea, which oxidize reduced forms of iron and/or sulfur. However, other microorganisms that reduce inorganic sulfur compounds can essentially reverse this process. These microorganisms can be applied on industrial scale to precipitate metals from industrial mineral leachates and acid mine drainage streams, resulting in a net improvement in metal recovery, while minimizing the amounts of leachable metals to the tailings storage dams. Here, we advocate that more extensive exploitation of microorganisms in metal mining operations could be an important way to green up the industry, reducing environmental risks and improving the efficiency and the economy of metal recovery. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Trace elements and organic compounds in streambed sediment and aquatic biota from the Sacramento River Basin, California, October and November 1995

USGS Publications Warehouse

MacCoy, Dorene E.; Domagalski, Joseph L.

1999-01-01

Elevated levels of trace elements and hydrophobic organic compounds were detected in streambed sediments and aquatic biota [Asiatic clam (Corbicula fluminea) or bottom-feeding fish] of the Sacramento River Basin, California, during October and November 1995. Trace elements detected included cadmium, copper, mercury, lead, and zinc. Elevated levels of cadmium, copper, and zinc in the upper Sacramento River are attributed to a mining land use, and elevated levels of zinc and lead in an urban stream, and possibly in the lower Sacramento River, are attributed to urban runoff processes. Elevated levels of mercury in streambed sediment are attributed to either past mercury mining or to the use of mercury in past gold mining operations. Mercury mining was an important land use within the Coast Ranges in the past and gold mining was an important land use of the Sierra Nevada in the past. Mercury was the only trace element found in elevated levels in the tissue of aquatic biota, and those levels also could be attributed to either mining or urban runoff. Hydrophobic organic compounds also were detected in streambed sediments and aquatic biota. The most frequently detected compounds were DDT and its breakdown products, dieldrin, oxychlordane, and toxaphene. Differences were found in the types of compounds detected at agricultural sites and the urban site. Although both types of sites had measurable concentrations of DDT or its breakdown products, the urban site also had measurable concentrations of pesticides used for household pest control. Few semivolatile compounds were detected in the streambed sediments of any site. The semivolatile compound p-cresol, a coal-tar derivative associated with road maintenance, was found in the highest concentration.

Predicting missing values in a home care database using an adaptive uncertainty rule method.

PubMed

Konias, S; Gogou, G; Bamidis, P D; Vlahavas, I; Maglaveras, N

2005-01-01

Contemporary literature illustrates an abundance of adaptive algorithms for mining association rules. However, most literature is unable to deal with the peculiarities, such as missing values and dynamic data creation, that are frequently encountered in fields like medicine. This paper proposes an uncertainty rule method that uses an adaptive threshold for filling missing values in newly added records. A new approach for mining uncertainty rules and filling missing values is proposed, which is in turn particularly suitable for dynamic databases, like the ones used in home care systems. In this study, a new data mining method named FiMV (Filling Missing Values) is illustrated based on the mined uncertainty rules. Uncertainty rules have quite a similar structure to association rules and are extracted by an algorithm proposed in previous work, namely AURG (Adaptive Uncertainty Rule Generation). The main target was to implement an appropriate method for recovering missing values in a dynamic database, where new records are continuously added, without needing to specify any kind of thresholds beforehand. The method was applied to a home care monitoring system database. Randomly, multiple missing values for each record's attributes (rate 5-20% by 5% increments) were introduced in the initial dataset. FiMV demonstrated 100% completion rates with over 90% success in each case, while usual approaches, where all records with missing values are ignored or thresholds are required, experienced significantly reduced completion and success rates. It is concluded that the proposed method is appropriate for the data-cleaning step of the Knowledge Discovery process in databases. The latter, containing much significance for the output efficiency of any data mining technique, can improve the quality of the mined information.

Near-field postseismic deformation associated with the 1992 Landers and 1999 Hector Mine, California, earthquakes

USGS Publications Warehouse

Savage, J.C.; Svarc, J.L.; Prescott, W.H.

2003-01-01

After the Landers earthquake (Mw = 7.3, 1992.489) a linear array of 10 monuments extending about 30 km N50??E on either side of the earthquake rupture plus a nearby offtrend reference monument were surveyed frequently by GPS until 2003.2. The array also spans the rupture of the subsequent Hector Mine earthquake (Mw = 7.1, 1999.792 . The pre-Landers velocities of monuments in the array relative to interior North America were estimated from earlier trilateration and very long baseline interferometry measurements. Except at the reference monument, the post-Landers velocities of the individual monuments in the array relaxed to their preseismic values within 4 years. Following the Hector Mine earthquake the velocities of the monuments relaxed to steady rates within 1 year. Those steady rates for the east components are about equal to the pre-Landers rates as is the steady rate for the north component of the one monument east of the Hector Mine rupture. However, the steady rates for the north components of the 10 monuments west of the rupture are systematically ???10 mm yr1 larger than the pre-Landers rates. The relaxation to a steady rate is approximately exponential with decay times of 0.50 ?? 0.10 year following the Landers earthquake and 0.32 ?? 0.18 year following the Hector Mine earthquake. The postearthquake motions of the Landers array following the Landers earthquake are not well approximated by the viscoelastic-coupling model of Pollitz et al. [2000]. A similar viscoelastic-coupling model [Pollitz et al., 2001] is more successful in representing the deformation after the Hector Mine earthquake.

Association Rule Based Feature Extraction for Character Recognition

NASA Astrophysics Data System (ADS)

Dua, Sumeet; Singh, Harpreet

Association rules that represent isomorphisms among data have gained importance in exploratory data analysis because they can find inherent, implicit, and interesting relationships among data. They are also commonly used in data mining to extract the conditions among attribute values that occur together frequently in a dataset [1]. These rules have wide range of applications, namely in the financial and retail sectors of marketing, sales, and medicine.

Informatic innovations in glycobiology: relevance to drug discovery.

PubMed

Mamitsuka, Hiroshi

2008-02-01

The recent development and applications of tree-based informatics on glycans have accelerated the biological analysis on glycans, particularly from structural viewpoints. We review three major aspects of recent informatics innovations on glycan structures: maturity of well-organized databases on glycan structures linking with other biological information, implementation of glycan structure matching algorithms and extensive development of methods for mining frequent patterns from glycan structures.

Selection of Dogs for Land Mine and Booby Trap Detection Training. Volume I

DTIC Science & Technology

1976-09-01

Such discharges are frequently of diagnostic significance, being associated with various specific diseases, e.g., canine distemper (14). The condition...in some forms of distemper , in acute gastritis, and in acute forms of intestinal toxaemia (14). Clinical examination of the abdomen involves...current (canine distemper , infectious canine hepatitis, leptospirosis,.I rabies). A certification of vaccination signed and dated by a licensed

Evaluating relationships between natural resource management, land use changes, and flooding in the Appalachian region

Treesearch

Nicolas P. Zegre; Samuel J. Lamont

2013-01-01

Th e Appalachian Region has a long history of natural resource management and recurrent history of frequent and large-scale floods. Land use activities such as urbanization, mining, forest harvesting, and agriculture can have a noticeable effect on the volume, magnitude, timing, and frequency of floods. Determining the effects of land use on flooding is difficult for...

Mining level of control in medical organizations.

PubMed

Çalimli, Olgu; Türkeli, Serkan; Eken, Emir Gökberk; Gönen, Halil Emre

2014-01-01

In literature of strategic management, there are three layers of control defined in organizational structures. These layers are strategic, tactical and operational, in which resides senior, medium level and low level managers respectively. In strategic level, institutional strategies are determined according to senior managers' perceived state of organization. In tactical level, this strategy is processed into methods and activities of a business management plan. Operational level embodies actions and functions to sustain specified business management plan. An acknowledged lead organization in Turkish medical area is examined using case study and data mining method in the scope of this paper. The level of decisions regarded in managerial purposes evaluated through chosen organization's business intelligence event logs report. Hence specification of management level importance of medical organizations is made. Case study, data mining and descriptive statistical method of taken case's reports present that positions of "Chief Executive Officer", "Outpatient Center Manager", "General Manager", monitored and analyzed functions of operational level management more frequently than strategic and tactical level. Absence of strategic management decision level research in medical area distinguishes this paper and consequently substantiates its significant contribution.

Mining Bug Databases for Unidentified Software Vulnerabilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dumidu Wijayasekara; Milos Manic; Jason Wright

2012-06-01

Identifying software vulnerabilities is becoming more important as critical and sensitive systems increasingly rely on complex software systems. It has been suggested in previous work that some bugs are only identified as vulnerabilities long after the bug has been made public. These vulnerabilities are known as hidden impact vulnerabilities. This paper discusses the feasibility and necessity to mine common publicly available bug databases for vulnerabilities that are yet to be identified. We present bug database analysis of two well known and frequently used software packages, namely Linux kernel and MySQL. It is shown that for both Linux and MySQL, amore » significant portion of vulnerabilities that were discovered for the time period from January 2006 to April 2011 were hidden impact vulnerabilities. It is also shown that the percentage of hidden impact vulnerabilities has increased in the last two years, for both software packages. We then propose an improved hidden impact vulnerability identification methodology based on text mining bug databases, and conclude by discussing a few potential problems faced by such a classifier.« less

Hydroponics as a valid tool to assess arsenic availability in mine soils.

PubMed

Moreno-Jiménez, E; Esteban, E; Fresno, T; de Egea, C López; Peñalosa, J M

2010-04-01

The low solubility of As in mine soils limits its phytoavailability. This makes the extrapolation of data obtained under hydroponic conditions unrealistic because the concentration in nutrient solution frequently overexposes plants to this metalloid. This work evaluates whether As supply in hydroponics resembles, to some extent, the As phytoavailable fraction in soils and the implications for phytoremediation. Phytotoxicity of As, in terms of biomass production, chlorophyll levels, and As concentrations in plants, was estimated and compared in both soils and hydroponics. In order for hydroponic conditions to be compared to soil conditions, plant exposure levels were measured in both cultures. Hydroponic As concentration ranging from 2-8microM equated to the same plant organ concentrations from soils with 700-3000mgkg(-1). Total and extractable As fractions exceeded those values, but As concentrations in pore water were bellow them. According to our results (i) hydroponics should include doses in the range 0-10microM As to allow the extrapolation of the results to As-polluted soils, and (ii) phytoextraction of As in mining sites will be limited by low As phytoavailability.

Opinion Summarizationof CustomerComments

NASA Astrophysics Data System (ADS)

Fan, Miao; Wu, Guoshi

Web 2.0 technologies have enabled more and more customers to freely comment on different kinds of entities, such as sellers, products and services. The large scale of information poses the need and challenge of automatic summarization. In many cases, each of the user-generated short comments implies the opinions which rate the target entity. In this paper, we aim to mine and to summarize all the customer comments of a product. The algorithm proposed in this researchis more reliable on opinion identification because it is unsupervised and the accuracy of the result improves as the number of comments increases. Our research is performed in four steps: (1) mining the frequent aspects of a product that have been commented on by customers; (2) mining the infrequent aspects of a product which have been commented by customers (3) identifying opinion words in each comment and deciding whether each opinion word is positive, negative or neutral; (4) summarizing the comments. This paper proposes several novel techniques to perform these tasks. Our experimental results using comments of a number of products sold online demonstrate the effectiveness of the techniques.

COPS: Detecting Co-Occurrence and Spatial Arrangement of Transcription Factor Binding Motifs in Genome-Wide Datasets

PubMed Central

Lohmann, Ingrid

2012-01-01

In multi-cellular organisms, spatiotemporal activity of cis-regulatory DNA elements depends on their occupancy by different transcription factors (TFs). In recent years, genome-wide ChIP-on-Chip, ChIP-Seq and DamID assays have been extensively used to unravel the combinatorial interaction of TFs with cis-regulatory modules (CRMs) in the genome. Even though genome-wide binding profiles are increasingly becoming available for different TFs, single TF binding profiles are in most cases not sufficient for dissecting complex regulatory networks. Thus, potent computational tools detecting statistically significant and biologically relevant TF-motif co-occurrences in genome-wide datasets are essential for analyzing context-dependent transcriptional regulation. We have developed COPS (Co-Occurrence Pattern Search), a new bioinformatics tool based on a combination of association rules and Markov chain models, which detects co-occurring TF binding sites (BSs) on genomic regions of interest. COPS scans DNA sequences for frequent motif patterns using a Frequent-Pattern tree based data mining approach, which allows efficient performance of the software with respect to both data structure and implementation speed, in particular when mining large datasets. Since transcriptional gene regulation very often relies on the formation of regulatory protein complexes mediated by closely adjoining TF binding sites on CRMs, COPS additionally detects preferred short distance between co-occurring TF motifs. The performance of our software with respect to biological significance was evaluated using three published datasets containing genomic regions that are independently bound by several TFs involved in a defined biological process. In sum, COPS is a fast, efficient and user-friendly tool mining statistically and biologically significant TFBS co-occurrences and therefore allows the identification of TFs that combinatorially regulate gene expression. PMID:23272209

Rising floodwaters: mapping impacts and perceptions of flooding in Indonesian Borneo

NASA Astrophysics Data System (ADS)

Wells, Jessie A.; Wilson, Kerrie A.; Abram, Nicola K.; Nunn, Malcolm; Gaveau, David L. A.; Runting, Rebecca K.; Tarniati, Nina; Mengersen, Kerrie L.; Meijaard, Erik

2016-06-01

The roles of forest and wetland ecosystems in regulating flooding have drawn increasing attention in the contexts of climate change adaptation and disaster risk reduction. However, data on floods are scarce in many of the countries where people are most exposed and vulnerable to their impacts. Here, our separate analyses of village interview surveys (364 villages) and news archives (16 sources) show that floods have major impacts on lives and livelihoods in Indonesian Borneo, and flooding risks are associated with features of the local climate and landscape, particularly land uses that have seen rapid expansions over the past 30 years. In contrast with government assessments, we find that flooding is far more widespread, and that frequent, local, events can have large cumulative impacts. Over three years, local news agencies reported floods that affected 868 settlements, 966 times (including 89 in urban areas), inundated at least 197 000 houses, and displaced more than 776 000 people, possibly as many as 1.5 million (i.e. 5%-10% of the total population). Spatial analyses based on surveys in 364 villages show that flood frequency is associated with land use in catchment areas, including forest cover and condition, and the area of wetlands, mines (open-cut coal or gold mines), and oil palm. The probability that floods have become more frequent over the past 30 years was higher for villages closer to mines, and in watersheds with more extensive oil palm, but lower in watersheds with greater cover of selectively-logged or intact forests. We demonstrate that in data-poor regions, multiple sources of information can be integrated to gain insights into the hydrological services provided by forest and wetland ecosystems, and motivate more comprehensive assessment of flooding risks and options for ecosystem-based adaptation.

Understanding Human Motion Skill with Peak Timing Synergy

NASA Astrophysics Data System (ADS)

Ueno, Ken; Furukawa, Koichi

The careful observation of motion phenomena is important in understanding the skillful human motion. However, this is a difficult task due to the complexities in timing when dealing with the skilful control of anatomical structures. To investigate the dexterity of human motion, we decided to concentrate on timing with respect to motion, and we have proposed a method to extract the peak timing synergy from multivariate motion data. The peak timing synergy is defined as a frequent ordered graph with time stamps, which has nodes consisting of turning points in motion waveforms. A proposed algorithm, PRESTO automatically extracts the peak timing synergy. PRESTO comprises the following 3 processes: (1) detecting peak sequences with polygonal approximation; (2) generating peak-event sequences; and (3) finding frequent peak-event sequences using a sequential pattern mining method, generalized sequential patterns (GSP). Here, we measured right arm motion during the task of cello bowing and prepared a data set of the right shoulder and arm motion. We successfully extracted the peak timing synergy on cello bowing data set using the PRESTO algorithm, which consisted of common skills among cellists and personal skill differences. To evaluate the sequential pattern mining algorithm GSP in PRESTO, we compared the peak timing synergy by using GSP algorithm and the one by using filtering by reciprocal voting (FRV) algorithm as a non time-series method. We found that the support is 95 - 100% in GSP, while 83 - 96% in FRV and that the results by GSP are better than the one by FRV in the reproducibility of human motion. Therefore we show that sequential pattern mining approach is more effective to extract the peak timing synergy than non-time series analysis approach.

Tools for Large Graph Mining

DTIC Science & Technology

2005-06-01

regarding criminals among many police departments. The criminal graph links suspects, crimes , locations, previous case histories, etc. These linkages...rebroadcast rate is high enough that dying out is not a concern. With the rise of sensor and peer to peer networks characterized by high churn, theory that...document groups (say, science fiction novels and thrillers ), based on the word groups that occur most frequently in them. A user who prefers one

Fire Safety Aspects of Polymeric Materials. Volume 10. Mines and Bunkers

DTIC Science & Technology

1980-01-01

Formaldehyde and Melamine / Formaldehyde Resins The basic chemistry, properties, and applications of urea / formaldehyde and melamine / formaldehyde resins ... Formaldehyde and Melamine Formaldehyde Rosins 71 4.2.3.3 Unsaturated Polyester Resins 71 4.2.3.4 Epoxy Resins 72 4.2.3.5 Furan Resins 72 4.2.3.6 Amine...aldehyde — most frequently formaldehyde . Urea is often used as a modifying agent. The

Crime Pattern Analysis: A Spatial Frequent Pattern Mining Approach

DTIC Science & Technology

2012-05-10

econometrics. A companion to theoretical econometrics, pages 310-330, 1988. [5] L. Anselin, J. Cohen, D. Cook, W. Gorr, and G. Tita . Spatial analyses...52] G. Mohler, M. Short, P. Brantingham, F. Schoenberg, and G. Tita . Self-exciting point process modeling of crime. Journal of the American...Systems, 9:462, 2010. [69] M. Short, P. Brantingham, A. Bertozzi, and G. Tita . Dissipation and displacement of hotspots in reaction-diffusion models

JPRS Report, Soviet Union, Political Affairs.

DTIC Science & Technology

1989-11-30

was before. Shag robes are hung in the bathrooms. On the shelves are shampoo and tooth- brushes in cellophane. One gets the impression that the old...the actual organizational and technical working con- ditions of judges, court secretaries, and other personnel. A survey , conducted by the author, of...There were frequent instances of drunkenness even at the work place. As a result, the volume of strip mining and also geological survey of reserves

Conservation Beyond Park Boundaries: The Impact of Buffer Zones on Deforestation and Mining Concessions in the Peruvian Amazon.

PubMed

Weisse, Mikaela J; Naughton-Treves, Lisa C

2016-08-01

Many researchers have tested whether protected areas save tropical forest, but generally focus on parks and reserves, management units that have internationally recognized standing and clear objectives. Buffer zones have received considerably less attention because of their ambiguous rules and often informal status. Although buffer zones are frequently dismissed as ineffective, they warrant attention given the need for landscape-level approaches to conservation and their prevalence around the world-in Peru, buffer zones cover >10 % of the country. This study examines the effectiveness of buffer zones in the Peruvian Amazon to (a) prevent deforestation and (b) limit the extent of mining concessions. We employ covariate matching to determine the impact of 13 buffer zones on deforestation and mining concessions from 2007 to 2012. Despite variation between sites, these 13 buffer zones have prevented ~320 km(2) of forest loss within their borders during the study period and ~1739 km(2) of mining concessions, an outcome associated with the special approval process for granting formal concessions in these areas. However, a closer look at the buffer zone around the Tambopata National Reserve reveals the difficulties of controlling illegal and informal activities. According to interviews with NGO employees, government officials, and community leaders, enforcement of conservation is limited by uncertain institutional responsibilities, inadequate budgets, and corruption, although formal and community-based efforts to block illicit mining are on the rise. Landscape-level conservation not only requires clear legal protocol for addressing large-scale, formal extractive activities, but there must also be strategies and coordination to combat illegal activities.

Text mining to decipher free-response consumer complaints: insights from the NHTSA vehicle owner's complaint database.

PubMed

Ghazizadeh, Mahtab; McDonald, Anthony D; Lee, John D

2014-09-01

This study applies text mining to extract clusters of vehicle problems and associated trends from free-response data in the National Highway Traffic Safety Administration's vehicle owner's complaint database. As the automotive industry adopts new technologies, it is important to systematically assess the effect of these changes on traffic safety. Driving simulators, naturalistic driving data, and crash databases all contribute to a better understanding of how drivers respond to changing vehicle technology, but other approaches, such as automated analysis of incident reports, are needed. Free-response data from incidents representing two severity levels (fatal incidents and incidents involving injury) were analyzed using a text mining approach: latent semantic analysis (LSA). LSA and hierarchical clustering identified clusters of complaints for each severity level, which were compared and analyzed across time. Cluster analysis identified eight clusters of fatal incidents and six clusters of incidents involving injury. Comparisons showed that although the airbag clusters across the two severity levels have the same most frequent terms, the circumstances around the incidents differ. The time trends show clear increases in complaints surrounding the Ford/Firestone tire recall and the Toyota unintended acceleration recall. Increases in complaints may be partially driven by these recall announcements and the associated media attention. Text mining can reveal useful information from free-response databases that would otherwise be prohibitively time-consuming and difficult to summarize manually. Text mining can extend human analysis capabilities for large free-response databases to support earlier detection of problems and more timely safety interventions.

Conservation Beyond Park Boundaries: The Impact of Buffer Zones on Deforestation and Mining Concessions in the Peruvian Amazon

NASA Astrophysics Data System (ADS)

Weisse, Mikaela J.; Naughton-Treves, Lisa C.

2016-08-01

Many researchers have tested whether protected areas save tropical forest, but generally focus on parks and reserves, management units that have internationally recognized standing and clear objectives. Buffer zones have received considerably less attention because of their ambiguous rules and often informal status. Although buffer zones are frequently dismissed as ineffective, they warrant attention given the need for landscape-level approaches to conservation and their prevalence around the world—in Peru, buffer zones cover >10 % of the country. This study examines the effectiveness of buffer zones in the Peruvian Amazon to (a) prevent deforestation and (b) limit the extent of mining concessions. We employ covariate matching to determine the impact of 13 buffer zones on deforestation and mining concessions from 2007 to 2012. Despite variation between sites, these 13 buffer zones have prevented ~320 km2 of forest loss within their borders during the study period and ~1739 km2 of mining concessions, an outcome associated with the special approval process for granting formal concessions in these areas. However, a closer look at the buffer zone around the Tambopata National Reserve reveals the difficulties of controlling illegal and informal activities. According to interviews with NGO employees, government officials, and community leaders, enforcement of conservation is limited by uncertain institutional responsibilities, inadequate budgets, and corruption, although formal and community-based efforts to block illicit mining are on the rise. Landscape-level conservation not only requires clear legal protocol for addressing large-scale, formal extractive activities, but there must also be strategies and coordination to combat illegal activities.

Pattern mining of user interaction logs for a post-deployment usability evaluation of a radiology PACS client.

PubMed

Jorritsma, Wiard; Cnossen, Fokie; Dierckx, Rudi A; Oudkerk, Matthijs; van Ooijen, Peter M A

2016-01-01

To perform a post-deployment usability evaluation of a radiology Picture Archiving and Communication System (PACS) client based on pattern mining of user interaction log data, and to assess the usefulness of this approach compared to a field study. All user actions performed on the PACS client were logged for four months. A data mining technique called closed sequential pattern mining was used to automatically extract frequently occurring interaction patterns from the log data. These patterns were used to identify usability issues with the PACS. The results of this evaluation were compared to the results of a field study based usability evaluation of the same PACS client. The interaction patterns revealed four usability issues: (1) the display protocols do not function properly, (2) the line measurement tool stays active until another tool is selected, rather than being deactivated after one use, (3) the PACS's built-in 3D functionality does not allow users to effectively perform certain 3D-related tasks, (4) users underuse the PACS's customization possibilities. All usability issues identified based on the log data were also found in the field study, which identified 48 issues in total. Post-deployment usability evaluation based on pattern mining of user interaction log data provides useful insights into the way users interact with the radiology PACS client. However, it reveals few usability issues compared to a field study and should therefore not be used as the sole method of usability evaluation. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Blast from the Past: Pervasive Impact and Landscape-Scale Modification from Historical Mining Over 1000 Years in Central Sweden

NASA Astrophysics Data System (ADS)

Hansson, S.; Bindler, R.

2011-12-01

In the public consciousness Sweden is often viewed as a largely natural landscape. However, many parts of the landscape have undergone substantial changes. For example, in the historically and culturally important Bergslagen region in central Sweden, which played an important role in the economic development of Sweden since the medieval period, agriculture and mining have greatly transformed the landscape over the past 1000 years. Bergslagen is an ore-rich region characterized as a granite-porphyr belt formed 1900 Ma ago, with thousands of mines and mine pits, hundreds of furnaces, smelters and forges distributed throughout the area. Drawing on data from selected lake sediment records from different historical mining districts in Central Sweden (e.g. Norberg mining district - iron ores and Falun mining district - copper ores) the aim of this presentation is to show how small-scale but pervasively widespread mining and metallurgy, along with associated settlement, have transformed the surrounding landscape. These anthropogenic activities led to changes in sedimentation and erosion rates, forest structure, and also causing large-scale metal pollution and ecological changes in recipient watercourses and lakes. This historical pollution was oftentimes on a scale we associate with modern mining pollution. Our research is based on analyses of lake sediment records, which include multi-element analyses of minor and trace elements using XRF, mercury, carbon, and in some lakes also pollen and diatoms. In two lakes in Norberg, recent catastrophic failure (1991) of a sand magazine below a now closed mine led to significant contamination of the two downstream lakes, with Cu and Hg concentrations up to 1800 ppm and 1400 ppb, respectively. These concentrations are 50 and 20 times greater than natural background values. However, such elevated concentrations are also frequently found in sediments dated to the 16th-18th centuries. For example, in one lake in the Norberg iron mining district, Hg concentrations were as high as 1100 ppb in sediments from the 16th century - about 40 times greater than background level. Although the total concentrations of metals in the lake sediments in these areas have decreased since the peak in the 16th-17th centuries, due to declines in mining and metallurgy, and the complete cessation of activities since the mid-20th century, metal concentrations have remained elevated for more than 500 years. Already 500 years ago land use and mining in some cases led to cultural alkalization of lakes, but ultimately acidification of soils and lakes in areas where sulfide ores were mined and processed. Land use and mining pollution also altered biogeochemical conditions in downstream lakes, which have not returned to natural baseline levels although mining and metallurgy have ceased over the last two centuries. Seeing that these results are symptomatic of changes that potentially affected thousands of lakes in this large region of Sweden, we believe that this has important implications for other environmental and also archaeological studies in the area, particularly those aimed at establishing reference conditions for potential future exploitation of ores.

Computational systems biology analysis of biomarkers in lung cancer; unravelling genomic regions which frequently encode biomarkers, enriched pathways, and new candidates.

PubMed

Alanazi, Ibrahim O; AlYahya, Sami A; Ebrahimie, Esmaeil; Mohammadi-Dehcheshmeh, Manijeh

2018-06-15

Exponentially growing scientific knowledge in scientific publications has resulted in the emergence of a new interdisciplinary science of literature mining. In text mining, the machine reads the published literature and transfers the discovered knowledge to mathematical-like formulas. In an integrative approach in this study, we used text mining in combination with network discovery, pathway analysis, and enrichment analysis of genomic regions for better understanding of biomarkers in lung cancer. Particular attention was paid to non-coding biomarkers. In total, 60 MicroRNA biomarkers were reported for lung cancer, including some prognostic biomarkers. MIR21, MIR155, MALAT1, and MIR31 were the top non-coding RNA biomarkers of lung cancer. Text mining identified 447 proteins which have been studied as biomarkers in lung cancer. EGFR (receptor), TP53 (transcription factor), KRAS, CDKN2A, ENO2, KRT19, RASSF1, GRP (ligand), SHOX2 (transcription factor), and ERBB2 (receptor) were the most studied proteins. Within small molecules, thymosin-a1, oestrogen, and 8-OHdG have received more attention. We found some chromosomal bands, such as 7q32.2, 18q12.1, 6p12, 11p15.5, and 3p21.3 that are highly involved in deriving lung cancer biomarkers. Copyright © 2018 Elsevier B.V. All rights reserved.

Stopping Antidepressants and Anxiolytics as Major Concerns Reported in Online Health Communities: A Text Mining Approach.

PubMed

Abbe, Adeline; Falissard, Bruno

2017-10-23

Internet is a particularly dynamic way to quickly capture the perceptions of a population in real time. Complementary to traditional face-to-face communication, online social networks help patients to improve self-esteem and self-help. The aim of this study was to use text mining on material from an online forum exploring patients' concerns about treatment (antidepressants and anxiolytics). Concerns about treatment were collected from discussion titles in patients' online community related to antidepressants and anxiolytics. To examine the content of these titles automatically, we used text mining methods, such as word frequency in a document-term matrix and co-occurrence of words using a network analysis. It was thus possible to identify topics discussed on the forum. The forum included 2415 discussions on antidepressants and anxiolytics over a period of 3 years. After a preprocessing step, the text mining algorithm identified the 99 most frequently occurring words in titles, among which were escitalopram, withdrawal, antidepressant, venlafaxine, paroxetine, and effect. Patients' concerns were related to antidepressant withdrawal, the need to share experience about symptoms, effects, and questions on weight gain with some drugs. Patients' expression on the Internet is a potential additional resource in addressing patients' concerns about treatment. Patient profiles are close to that of patients treated in psychiatry. ©Adeline Abbe, Bruno Falissard. Originally published in JMIR Mental Health (http://mental.jmir.org), 23.10.2017.

[Exploring the clinical characters of Shugan Jieyu capsule through text mining].

PubMed

Pu, Zheng-Ping; Xia, Jiang-Ming; Xie, Wei; He, Jin-Cai

2017-09-01

The study was main to explore the clinical characters of Shugan Jieyu capsule through text mining. The data sets of Shugan Jieyu capsule were downloaded from CMCC database by the method of literature retrieved from May 2009 to Jan 2016. Rules of Chinese medical patterns, diseases, symptoms and combination treatment were mined out by data slicing algorithm, and they were demonstrated in frequency tables and two dimension based network. Then totally 190 literature were recruited. The outcomess suggested that SC was most frequently correlated with liver Qi stagnation. Primary depression, depression due to brain disease, concomitant depression followed by physical diseases, concomitant depression followed by schizophrenia and functional dyspepsia were main diseases treated by Shugan Jieyu capsule. Symptoms like low mood, psychic anxiety, somatic anxiety and dysfunction of automatic nerve were mainy relieved bv Shugan Jieyu capsule.For combination treatment. Shugan Jieyu capsule was most commonly used with paroxetine, sertraline and fluoxetine. The research suggested that syndrome types and mining results of Shugan Jieyu capsule were almost the same as its instructions. Syndrome of malnutrition of heart spirit was the potential Chinese medical pattern of Shugan Jieyu capsule. Primary comorbid anxiety and depression, concomitant comorbid anxiety and depression followed by physical diseases, and postpartum depression were potential diseases treated by Shugan Jieyu capsule.For combination treatment, Shugan Jieyu capsule was most commonly used with paroxetine, sertraline and fluoxetine. Copyright© by the Chinese Pharmaceutical Association.

Chemical Sensing for Buried Landmines - Fundamental Processes Influencing Trace Chemical Detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

PHELAN, JAMES M.

2002-05-01

Mine detection dogs have a demonstrated capability to locate hidden objects by trace chemical detection. Because of this capability, demining activities frequently employ mine detection dogs to locate individual buried landmines or for area reduction. The conditions appropriate for use of mine detection dogs are only beginning to emerge through diligent research that combines dog selection/training, the environmental conditions that impact landmine signature chemical vapors, and vapor sensing performance capability and reliability. This report seeks to address the fundamental soil-chemical interactions, driven by local weather history, that influence the availability of chemical for trace chemical detection. The processes evaluated include:more » landmine chemical emissions to the soil, chemical distribution in soils, chemical degradation in soils, and weather and chemical transport in soils. Simulation modeling is presented as a method to evaluate the complex interdependencies among these various processes and to establish conditions appropriate for trace chemical detection. Results from chemical analyses on soil samples obtained adjacent to landmines are presented and demonstrate the ultra-trace nature of these residues. Lastly, initial measurements of the vapor sensing performance of mine detection dogs demonstrates the extreme sensitivity of dogs in sensing landmine signature chemicals; however, reliability at these ultra-trace vapor concentrations still needs to be determined. Through this compilation, additional work is suggested that will fill in data gaps to improve the utility of trace chemical detection.« less

A three-step approach to minimise the impact of a mining site on vicuña (Vicugna vicugna) and to restore landscape connectivity.

PubMed

Mata, Cristina; Malo, Juan E; Galaz, José Luis; Cadorzo, César; Lagunas, Héctor

2016-07-01

Resource extraction projects generate a diversity of negative effects on the environment that are difficult to predict and mitigate. Consequently, adaptive management approaches have been advocated to develop effective responses to impacts that were not predicted. Mammal populations living in or around mine sites are frequently of management concern; yet, there is a dearth of published information on how to minimise the negative effects of different phases of mining operations on them. Here, we present the case study of a copper mine in the Chilean Altiplano, which caused roadkills of the protected vicuña (Vicugna vicugna). This issue led to a three-step solution being implemented: (1) the initial identification of the problem and implementation of an emergency response, (2) the scientific analysis for decision making and (3) the planning and informed implementation of responses for different future scenarios and timescales. The measures taken under each of these steps provide examples of environmental management approaches that make use of scientific information to develop integrated management responses. In brief, our case study showed how (1) the timescale and the necessity/urgency of the case were addressed, (2) the various stakeholders involved were taken into account and (3) changes were included into the physical, human and organisational elements of the company to achieve the stated objectives.

Resource-Saving Cleaning Technologies for Power Plant Waste-Water Cooling Ponds

NASA Astrophysics Data System (ADS)

Zakonnova, Lyudmila; Nikishkin, Igor; Rostovzev, Alexandr

2017-11-01

One of the frequently encountered problems of power plant small cooling ponds is rapid eutrophication and related intensified development of phytoplankton ("hyperflow") and overgrowing of ponds by higher aquatic vegetation. As a result of hyper-flowering, an enormous amount of detritus settles on the condenser tubes, reducing the efficiency of the power plant operation. The development of higher aquatic vegetation contributes to the appearing of the shoals. As a result the volume, area and other characteristics of the cooling ponds are getting changed. The article describes the environmental problems of small manmade ponds of power plants and coal mines in mining regions. Two approaches to the problem of eutrophication are considered: technological and ecological. The negative effects of herbicides application to aquatic organisms are experimentally proved. An ecological approach to solving the problem by fish-land reclamation method is shown.

Multi - party Game Analysis of Coal Industry and Industry Regulation Policy Optimization

NASA Astrophysics Data System (ADS)

Jiang, Tianqi

2018-01-01

In the face of the frequent occurrence of coal mine safety accidents, this paper analyses the relationship between central and local governments, coal mining enterprises and miners from the perspective of multi - group game. In the actual production, the decision of one of the three groups can affect the game strategy of the other of the three, so we should assume the corresponding game order. In this order, the game analysis of the income and decision of the three is carried out, and the game decision of the government, the enterprise and the workers is obtained through the establishment of the benefit matrix and so on. And then on the existing system to optimize the coal industry regulation proposed practical recommendations to reduce the frequency of industry safety accidents, optimize the industry production environment.

Advantages and difficulties of implementation of the international GNA standards in sustainable mining development. (Invited)

NASA Astrophysics Data System (ADS)

Masaitis, A.

2013-12-01

Conflicts in the development of mining projects are now common between the mining proponents, NGO's and communities. These conflicts can sometimes be alleviated by early development of modes of communication, and a formal discussion format that allows airing of concerns and potential resolution of problems. One of the methods that can formalize this process is to establish a Good Neighbor Agreement (GNA), which deals specifically with challenges in relationships between mining operations and the local communities. It is a new practice related to mining operations that are oriented toward social needs and concerns of local communities that arise during the normal life of a mine, which can achieve sustainable mining practices in both developing and developed countries. The GNA project being currently developed at the University of Nevada, Reno in cooperation with the Newmont Mining Corporation has a goal to create an open company/community dialog that is based on the international standards and that will help identify and address sociological and environmental concerns associated with mining, as well as find methods for communication and conflict resolution. GNA standards should be based on trust doctrine, open information access, and community involvement in the decision making process. It should include the following components: emergency response and community communications; environmental issues, including air and water quality standards; reclamation and recultivation; socio-economic issues: transportation, safety, training, and local hiring; and financial issues, particularly related to mitigation offsets and community needs. The GNA standards help identify and evaluate conflict criteria in mining/community relationships; determine the status of concerns; focus on the local political and government systems; separate the acute and the chronic concerns; determine the role and responsibilities of stakeholders; analyze problem resolution feasibility; maintain the community involvement and support through economic benefits and environmental safeguards; develop options for the concerns resolution; develop and manage short and long-term plans. Difficulties in establishing the GNA standards include identification of the full list of stakeholders, lack of responsible environmental protection practices, dependence on the government and political system, lack of will to disclose full information to the public. It is further complicated by the lack of insurance/bonding policies, and by the lack of audit and monitoring that could determine the level of exposure of the local community and the environment to the contaminants released at the mine sites. Since many problems of mines can occur during closure and post-closure, GNA's should address those issues also. Determined the process for the GNA implementation as a conflict prevention/resolution tool, analyzed conflict/concerns criteria associated with mining operations, determined the role of the stakeholders, worked out the process of stakeholders monitoring, carried out the sociological survey of the stakeholders and the community. Frequent conflicts between mining companies and surrounding communities that lead to work disruptions or even mine closures show the necessity of a less confrontational approach to environmental and social justice. Establishment of GNA standards for use in both developed and developing nations can decrease these conflicts.

Set of Frequent Word Item sets as Feature Representation for Text with Indonesian Slang

NASA Astrophysics Data System (ADS)

Sa'adillah Maylawati, Dian; Putri Saptawati, G. A.

2017-01-01

Indonesian slang are commonly used in social media. Due to their unstructured syntax, it is difficult to extract their features based on Indonesian grammar for text mining. To do so, we propose Set of Frequent Word Item sets (SFWI) as text representation which is considered match for Indonesian slang. Besides, SFWI is able to keep the meaning of Indonesian slang with regard to the order of appearance sentence. We use FP-Growth algorithm with adding separation sentence function into the algorithm to extract the feature of SFWI. The experiments is done with text data from social media such as Facebook, Twitter, and personal website. The result of experiments shows that Indonesian slang were more correctly interpreted based on SFWI.

New method for the direct determination of dissolved Fe(III) concentration in acid mine waters

USGS Publications Warehouse

To, T.B.; Nordstrom, D. Kirk; Cunningham, K.M.; Ball, J.W.; McCleskey, R. Blaine

1999-01-01

A new method for direct determination of dissolved Fe(III) in acid mine water has been developed. In most present methods, Fe(III) is determined by computing the difference between total dissolved Fe and dissolved Fe(II). For acid mine waters, frequently Fe(II) >> Fe(III); thus, accuracy and precision are considerably improved by determining Fe(III) concentration directly. The new method utilizes two selective ligands to stabilize Fe(III) and Fe(II), thereby preventing changes in Fe reduction-oxidation distribution. Complexed Fe(II) is cleanly removed using a silica-based, reversed-phase adsorbent, yielding excellent isolation of the Fe(III) complex. Iron(III) concentration is measured colorimetrically or by graphite furnace atomic absorption spectrometry (GFAAS). The method requires inexpensive commercial reagents and simple procedures that can be used in the field. Calcium(II), Ni(II), Pb(II), AI(III), Zn(II), and Cd(II) cause insignificant colorimetric interferences for most acid mine waters. Waters containing >20 mg of Cu/L could cause a colorimetric interference and should be measured by GFAAS. Cobalt(II) and Cr(III) interfere if their molar ratios to Fe(III) exceed 24 and 5, respectively. Iron(II) interferes when its concentration exceeds the capacity of the complexing ligand (14 mg/L). Because of the GFAAS elemental specificity, only Fe(II) is a potential interferent in the GFAAS technique. The method detection limit is 2 ??g/L (40 nM) using GFAAS and 20 ??g/L (0.4 ??M) by colorimetry.A new method for direct determination of dissolved Fe(III) in acid mine water has been developed. In most present methods, Fe(III) is determined by computing the difference between total dissolved Fe and dissolved Fe(II). For acid mine waters, frequently Fe(II)???Fe(III); thus, accuracy and precision are considerably improved by determining Fe(III) concentration directly. The new method utilizes two selective ligands to stabilize Fe(III) and Fe(II), thereby preventing changes in Fe reduction-oxidation distribution. Complexed Fe(II) is cleanly removed using a silica-based, reversed-phase adsorbent, yielding excellent isolation of the Fe(III) complex. Iron(III) concentration is measured colorimetrically or by graphite furnace atomic absorption spectrometry (GFAAS). The method requires inexpensive commercial reagents and simple procedures that can be used in the field. Calcium(II), Ni(II), Pb(II), Al(III), Zn(II), and Cd(II) cause insignificant colorimetric interferences for most acid mine waters. Waters containing >20 mg of Cu/L could cause a colorimetric interference and should be measured by GFAAS. Cobalt(II) and Cr(III) interfere if their molar ratios to Fe(III) exceed 24 and 5, respectively. Iron(II) interferes when its concentration exceeds the capacity of the complexing ligand (14 mg/L). Because of the GFAAS elemental specificity, only Fe(II) is a potential interferent in the GFAAS technique. The method detection limit is 2/??g/L (40 nM) using GFAAS and 20 ??g/L (0.4 ??M) by colorimetry.

Whole-body vibration exposure of haul truck drivers at a surface coal mine.

PubMed

Wolfgang, Rebecca; Burgess-Limerick, Robin

2014-11-01

Haul truck drivers at surface mines are exposed to whole-body vibration for extended periods. Thirty-two whole-body vibration measurements were gathered from haul trucks under a range of normal operating conditions. Measurements taken from 30 of the 32 trucks fell within the health guidance caution zone defined by ISO2631-1 for an 8 h daily exposure suggesting, according to ISO2631-1, that "caution with respect to potential health risks is indicated". Maintained roadways were associated with substantially lower vibration amplitudes. Larger trucks were associated with lower vibration levels than small trucks. The descriptive nature of the research, and small sample size, prevents any strong conclusion regarding causal links. Further investigation of the variables associated with elevated vibration levels is justified. The operators of mining equipment such as haul trucks are exposed to whole-body vibration amplitudes which have potential to lead to long term health effects. Systematic whole-body vibration measurements taken at frequent intervals are required to provide an understanding of the causes of elevated vibration levels and hence determine appropriate control measures. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Towards comprehensive structural motif mining for better fold annotation in the "twilight zone" of sequence dissimilarity

PubMed Central

Jia, Yi; Huan, Jun; Buhr, Vincent; Zhang, Jintao; Carayannopoulos, Leonidas N

2009-01-01

Background Automatic identification of structure fingerprints from a group of diverse protein structures is challenging, especially for proteins whose divergent amino acid sequences may fall into the "twilight-" or "midnight-" zones where pair-wise sequence identities to known sequences fall below 25% and sequence-based functional annotations often fail. Results Here we report a novel graph database mining method and demonstrate its application to protein structure pattern identification and structure classification. The biologic motivation of our study is to recognize common structure patterns in "immunoevasins", proteins mediating virus evasion of host immune defense. Our experimental study, using both viral and non-viral proteins, demonstrates the efficiency and efficacy of the proposed method. Conclusion We present a theoretic framework, offer a practical software implementation for incorporating prior domain knowledge, such as substitution matrices as studied here, and devise an efficient algorithm to identify approximate matched frequent subgraphs. By doing so, we significantly expanded the analytical power of sophisticated data mining algorithms in dealing with large volume of complicated and noisy protein structure data. And without loss of generality, choice of appropriate compatibility matrices allows our method to be easily employed in domains where subgraph labels have some uncertainty. PMID:19208148

Automated data mining: an innovative and efficient web-based approach to maintaining resident case logs.

PubMed

Bhattacharya, Pratik; Van Stavern, Renee; Madhavan, Ramesh

2010-12-01

Use of resident case logs has been considered by the Residency Review Committee for Neurology of the Accreditation Council for Graduate Medical Education (ACGME). This study explores the effectiveness of a data-mining program for creating resident logs and compares the results to a manual data-entry system. Other potential applications of data mining to enhancing resident education are also explored. Patient notes dictated by residents were extracted from the Hospital Information System and analyzed using an unstructured mining program. History, examination and ICD codes were obtained and compared to the existing manual log. The automated data History, examination, and ICD codes were gathered for a 30-day period and compared to manual case logs. The automated method extracted all resident dictations with the dates of encounter and transcription. The automated data-miner processed information from all 19 residents, while only 4 residents logged manually. The manual method identified only broad categories of diseases; the major categories were stroke or vascular disorder 53 (27.6%), epilepsy 28 (14.7%), and pain syndromes 26 (13.5%). In the automated method, epilepsy 114 (21.1%), cerebral atherosclerosis 114 (21.1%), and headache 105 (19.4%) were the most frequent primary diagnoses, and headache 89 (16.5%), seizures 94 (17.4%), and low back pain 47 (9%) were the most common chief complaints. More detailed patient information such as tobacco use 227 (42%), alcohol use 205 (38%), and drug use 38 (7%) were extracted by the data-mining method. Manual case logs are time-consuming, provide limited information, and may be unpopular with residents. Data mining is a time-effective tool that may aid in the assessment of resident experience or the ACGME core competencies or in resident clinical research. More study of this method in larger numbers of residency programs is needed.

Geo-products of urban areas: Silesian Metropolis, Southern Poland

NASA Astrophysics Data System (ADS)

Chybiorz, Ryszard; Abramowicz, Anna

2017-04-01

Silesian Metropolis is located in the Silesian Voivodeship, in the most important industrial region in Poland. It consist of 14 cities with powiat rights, which create the largest urban center in Poland and one of the largest in Central and Eastern Europe. Almost 2 million people live in its territory. A large concentration of the population is associated with industrialization and especially with the development of the mining industry (Upper Silesian Coal Basin) and the processing industry (steelworks, textile industry) at the end of 19th century. One hundred years later, during the creation of the modern sectors of the economy, processes of metallurgy and mining restructuring have been started. Created mechanisms and conditions for development of post-industrial areas were consistent with the principles of sustainable development and had many new features, including cultural and touristic features. The Industrial Monuments Route was opened for the inhabitants and visitors in October 2006. The route joined the European Route of Industrial Heritage (ERIH) in 2010. Its most interesting mining attractions are located in Silesian Metropolis, and the most frequently visited object on the route is the Guido Historical Coal Mine in Zabrze and the Historical Silver Mine in Tarnowskie Góry. The project, which is realized in Zabrze, will provide for tourists a system of underground corridors, which were used for coal transportation in the 19th century. Visitors will be able to actively explore the work of miners, moving by underground boats, railway and suspension railway. Surface mines are also available for geotourists. The Ecological and Geological Education Center GEOsfera was created in a former Triassic quarry in Jaworzno. Although the area of the Silesian Metropolis is characterized by a very large devastation of the environment, the following objects were created (and are still created) on the basis of inanimate nature and they have a touristic value for the region and the country. Some of them already provide for the implementation of geotouristic purposes.

Morphological and molecular diversity of arbuscular mycorrhizal fungi in revegetated iron-mining site has the same magnitude of adjacent pristine ecosystems.

PubMed

Vieira, Caroline Krug; Marascalchi, Matheus Nicoletti; Rodrigues, Arthur Vinicius; de Armas, Rafael Dutra; Stürmer, Sidney Luiz

2018-05-01

Arbuscular mycorrhizal fungi (AMF) are important during revegetation of mining sites, but few studies compared AMF community in revegetated sites with pristine adjacent ecosystems. The aim of this study was to assess AMF species richness in a revegetated iron-mining site and adjacent ecosystems and to relate AMF occurrence to soil chemical parameters. Soil samples were collected in dry and rainy seasons in a revegetated iron-mining site (RA) and compared with pristine ecosystems of forest (FL), canga (NG), and Cerrado (CE). AMF species were identified by spore morphology from field and trap cultures and by LSU rDNA sequencing using Illumina. A total of 62 AMF species were recovered, pertaining to 18 genera and nine families of Glomeromycota. The largest number of species and families were detected in RA, and Acaulospora mellea and Glomus sp1 were the most frequent species. Species belonging to Glomeraceae and Acaulosporaceae accounted for 42%-48% of total species richness. Total number of spores and mycorrhizal inoculum potential tended to be higher in the dry than in the rainy season, except in RA. Sequences of uncultured Glomerales were dominant in all sites and seasons and five species were detected exclusively by DNA-based identification. Redundancy analysis evidenced soil pH, organic matter, aluminum, and iron as main factors influencing AMF presence. In conclusion, revegetation of the iron-mining site seems to be effective in maintaining a diverse AMF community and different approaches are complementary to reveal AMF species, despite the larger number of species being identified by traditional identification of field spores. Copyright © 2017. Published by Elsevier B.V.

Comparison of MERV 16 and HEPA filters for cab filtration of underground mining equipment.

PubMed

Cecala, A B; Organiscak, J A; Noll, J D; Zimmer, J A

2016-08-01

Significant strides have been made in optimizing the design of filtration and pressurization systems used on the enclosed cabs of mobile mining equipment to reduce respirable dust and provide the best air quality to the equipment operators. Considering all of the advances made in this area, one aspect that still needed to be evaluated was a comparison of the efficiencies of the different filters used in these systems. As high-efficiency particulate arrestance (HEPA) filters provide the highest filtering efficiency, the general assumption would be that they would also provide the greatest level of protection to workers. Researchers for the U.S. National Institute for Occupational Safety and Health (NIOSH) speculated, based upon a previous laboratory study, that filters with minimum efficiency reporting value, or MERV rating, of 16 may be a more appropriate choice than HEPA filters in most cases for the mining industry. A study was therefore performed comparing HEPA and MERV 16 filters on two kinds of underground limestone mining equipment, a roof bolter and a face drill, to evaluate this theory. Testing showed that, at the 95-percent confidence level, there was no statistical difference between the efficiencies of the two types of filters on the two kinds of mining equipment. As the MERV 16 filters were less restrictive, provided greater airflow and cab pressurization, cost less and required less-frequent replacement than the HEPA filters, the MERV 16 filters were concluded to be the optimal choice for both the roof bolter and the face drill in this comparative-analysis case study. Another key finding of this study is the substantial improvement in the effectiveness of filtration and pressurization systems when using a final filter design.

Comparison of MERV 16 and HEPA filters for cab filtration of underground mining equipment

PubMed Central

Cecala, A.B.; Organiscak, J.A.; Noll, J.D.; Zimmer, J.A.

2016-01-01

Significant strides have been made in optimizing the design of filtration and pressurization systems used on the enclosed cabs of mobile mining equipment to reduce respirable dust and provide the best air quality to the equipment operators. Considering all of the advances made in this area, one aspect that still needed to be evaluated was a comparison of the efficiencies of the different filters used in these systems. As high-efficiency particulate arrestance (HEPA) filters provide the highest filtering efficiency, the general assumption would be that they would also provide the greatest level of protection to workers. Researchers for the U.S. National Institute for Occupational Safety and Health (NIOSH) speculated, based upon a previous laboratory study, that filters with minimum efficiency reporting value, or MERV rating, of 16 may be a more appropriate choice than HEPA filters in most cases for the mining industry. A study was therefore performed comparing HEPA and MERV 16 filters on two kinds of underground limestone mining equipment, a roof bolter and a face drill, to evaluate this theory. Testing showed that, at the 95-percent confidence level, there was no statistical difference between the efficiencies of the two types of filters on the two kinds of mining equipment. As the MERV 16 filters were less restrictive, provided greater airflow and cab pressurization, cost less and required less-frequent replacement than the HEPA filters, the MERV 16 filters were concluded to be the optimal choice for both the roof bolter and the face drill in this comparative-analysis case study. Another key finding of this study is the substantial improvement in the effectiveness of filtration and pressurization systems when using a final filter design. PMID:27524838

Accumulation of heavy metals and As in liver, hair, femur, and lung of Persian jird (Meriones persicus) in Darreh Zereshk copper mine, Iran.

PubMed

Khazaee, Manoochehr; Hamidian, Amir Hossein; Alizadeh Shabani, Afshin; Ashrafi, Sohrab; Mirjalili, Seyyed Ali Ashghar; Esmaeilzadeh, Esmat

2016-02-01

Rodents frequently serve as bioindicator to monitor the quality of the environment. Concentrations of 11 elements (Cd, Co, Ti, Fe, Mn, Cu, Sb, As, Sr, Ni, and Cr) were investigated and compared in liver, hair, femur, and lung of the Persian jird (Meriones persicus) from Darreh Zereshk copper mine, Iran. Metals were determined in different tissues of 39 individuals of Persian jird, collected by snap trap in 2014 from five areas of Darreh Zereshk copper mine. Samples were prepared by wet digestion method, and the contents of elements were analyzed with ICP-OES (VARIAN, 725-ES) instrument. Cadmium, Sb, and Co were below the limit of detection, and Mn and As were found only in hair and liver tissues. We detected the highest concentration of Cu, As, Ti, Fe, Mn, Cr, and Ni in hair in comparison with other tissues. Significant higher levels of Ti in femur and hair; Fe in liver and hair; Mn in liver; As in hair; Sr in lung; Cr in lung, hair, femur, and liver; Cu in femur; and Ni in liver and lung tissues were observed in females. Nearly all element concentrations in the tissues of Persian jird from flotation site, Darreh Zereshk and Hasan Abad villages and leaching site (mining areas) were higher than those from tailing dump site (reference site). We found the highest concentrations of As in liver and hair; Ni and Cr in liver, hair, and lung; and Sr in lung and hair tissues of Persian jird in leaching site. We tried to specify the status of elements before fully exploitation of Darreh Zereshk copper mine by using bioindicator species. Based on our achievements, initial activities did not strongly pollute the surrounded environment of the mine. The high abundance of Persian jird as well as their several proper features makes them a suitable species for biomonitoring programs especially for further studies will be performed after full exploitation of Darreh Zereshk copper mine.

Analysis of ingredient lists of commercially available gluten-free and gluten-containing food products using the text mining technique.

PubMed

do Nascimento, Amanda Bagolin; Fiates, Giovanna Medeiros Rataichesck; Dos Anjos, Adilson; Teixeira, Evanilda

2013-03-01

Ingredients mentioned on the labels of commercially available packaged gluten-free and similar gluten-containing food products were analyzed and compared, using the text mining technique. A total of 324 products' labels were analyzed for content (162 from gluten-free products), and ingredient diversity in gluten-free products was 28% lower. Raw materials used as ingredients of gluten-free products were limited to five varieties: rice, cassava, corn, soy, and potato. Sugar was the most frequently mentioned ingredient on both types of products' labels. Salt and sodium also were among these ingredients. Presence of hydrocolloids, enzymes or raw materials of high nutritional content such as pseudocereals, suggested by academic studies as alternatives to improve nutritional and sensorial quality of gluten-free food products, was not identified in the present study. Nutritional quality of gluten-free diets and health of celiac patients may be compromised.

Assessing genotoxic effects in fish from a marine protected area influenced by former mining activities and other stressors.

PubMed

Gusso-Choueri, Paloma Kachel; Choueri, Rodrigo Brasil; Santos, Gustavo Souza; de Araújo, Giuliana Seraphim; Cruz, Ana Carolina Feitosa; Stremel, Tatiana; de Campos, Sandro Xavier; Cestari, Marta Margarete; Ribeiro, Ciro Alberto Oliveira; Abessa, Denis Moledo de Sousa

2016-03-15

The goal of the current study was to evaluate different genotoxicity tools in order to assess a marine protected area (MPA) affected by former mining activities and urban settlements. A catfish (Cathorops spixii) was analyzed for genotoxic effects at the (i) molecular and at the (ii) chromosomal levels. Through factor analysis, genotoxicity was found to be linked to levels of metals bioaccumulated and PAH metabolites in the bile. Micronucleus and nuclear alteration were less vulnerable to the effects of confounding factors in mildly contaminated areas since they were more frequently associated with bioaccumulated metals than the DNA analysis. The different genotoxicity responses allowed for the identification of sources of pollution in the MPA. This approach was important for detecting environmental risks related to genotoxic contaminants in a mildly contaminated MPA. Copyright © 2016 Elsevier Ltd. All rights reserved.

Template for preparation of papers for IEEE sponsored conferences & symposia.

PubMed

Sacchi, L; Dagliati, A; Tibollo, V; Leporati, P; De Cata, P; Cerra, C; Chiovato, L; Bellazzi, R

2015-01-01

To improve the access to medical information is necessary to design and implement integrated informatics techniques aimed to gather data from different and heterogeneous sources. This paper describes the technologies used to integrate data coming from the electronic medical record of the IRCCS Fondazione Maugeri (FSM) hospital of Pavia, Italy, and combines them with administrative, pharmacy drugs purchase coming from the local healthcare agency (ASL) of the Pavia area and environmental open data of the same region. The integration process is focused on data coming from a cohort of one thousand patients diagnosed with Type 2 Diabetes Mellitus (T2DM). Data analysis and temporal data mining techniques have been integrated to enhance the initial dataset allowing the possibility to stratify patients using further information coming from the mined data like behavioral patterns of prescription-related drug purchases and other frequent clinical temporal patterns, through the use of an intuitive dashboard controlled system.

Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

PubMed

Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

2015-01-01

Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these interaction types and their associated gene-gene pairs uncovered many scientific insights. INO provides a novel approach for defining hierarchical interaction types and related keywords for literature mining. The ontology-based literature mining, in combination with an INO-based statistical interaction enrichment test, provides a new platform for efficient mining and analysis of topic-specific gene interaction networks.

Prevalence of Heart Failure Signs and Symptoms in a Large Primary Care Population Identified Through the Use of Text and Data Mining of the Electronic Health Record

PubMed Central

Vijayakrishnan, Rajakrishnan; Steinhubl, Steven R.; Ng, Kenney; Sun, Jimeng; Byrd, Roy J.; Daar, Zahra; Williams, Brent A.; deFilippi, Christopher; Ebadollahi, Shahram; Stewart, Walter F.

2014-01-01

Background The electronic health record contains a tremendous amount of data that if appropriately detected can lead to earlier identification of disease states such as heart failure (HF). Using a novel text and data analytic tool we explored the longitudinal EHR of over 50,000 primary care patients to identify the documentation of the signs and symptoms of HF in the years preceding its diagnosis. Methods and Results Retrospective analysis consisting of 4,644 incident HF cases and 45,981 group-matched controls. Documentation of Framingham HF signs and symptoms within encounter notes were carried out using a previously validated natural language processing procedure. A total of 892,805 affirmed criteria were documented over an average observation period of 3.4 years. Among eventual HF cases, 85% had at least one criterion within a year prior to their HF diagnosis (as did 55% of controls). Substantial variability in the prevalence of individual signs and symptoms were found in both cases and controls. Conclusions HF signs and symptoms are frequently documented in a primary care population as identified through automated text and data mining of EHRs. Their frequent identification demonstrates the rich data available within EHRs that will allow for future work on automated criterion identification to help develop predictive models for HF. PMID:24709663

[Application of text mining approach to pre-education prior to clinical practice].

PubMed

Koinuma, Masayoshi; Koike, Katsuya; Nakamura, Hitoshi

2008-06-01

We developed a new survey analysis technique to understand students' actual aims for effective pretraining prior to clinical practice. We asked third-year undergraduate students to write fixed-style complete and free sentences on "preparation of drug dispensing." Then, we converted their sentence data in to text style and performed Japanese-language morphologic analysis on the data using language analysis software. We classified key words, which were created on the basis of the word class information of the Japanese language morphologic analysis, into categories based on causes and characteristics. In addition to this, we classified the characteristics into six categories consisting of those concepts including "knowledge," "skill and attitude," "image," etc. with the KJ method technique. The results showed that the awareness of students of "preparation of drug dispensing" tended to be approximately three-fold more frequent in "skill and attitude," "risk," etc. than in "knowledge." Regarding the characteristics in the category of the "image," words like "hard," "challenging," "responsibility," "life," etc. frequently occurred. The results of corresponding analysis showed that the characteristics of the words "knowledge" and "skills and attitude" were independent. As the result of developing a cause-and-effect diagram, it was demonstrated that the phase "hanging tough" described most of the various factors. We thus could understand students' actual feelings by applying text-mining as a new survey analysis technique.

Metal mobilization by iron- and sulfur-oxidizing bacteria in a multiple extreme mine tailings in the Atacama Desert, Chile.

PubMed

Korehi, H; Blöthe, M; Sitnikova, M A; Dold, B; Schippers, A

2013-03-05

The marine shore sulfidic mine tailings dump at the Chañaral Bay in the Atacama Desert, northern Chile, is characterized by extreme acidity, high salinity, and high heavy metals concentrations. Due to pyrite oxidation, metals (especially copper) are mobilized under acidic conditions and transported toward the tailings surface and precipitate as secondary minerals (Dold, Environ. Sci. Technol. 2006, 40, 752-758.). Depth profiles of total cell counts in this almost organic-carbon free multiple extreme environment showed variable numbers with up to 10(8) cells g(-1) dry weight for 50 samples at four sites. Real-time PCR quantification and bacterial 16S rRNA gene diversity analysis via clone libraries revealed a dominance of Bacteria over Archaea and the frequent occurrence of the acidophilic iron(II)- and sulfur-oxidizing and iron(III)-reducing genera Acidithiobacillus, Alicyclobacillus, and Sulfobacillus. Acidophilic chemolithoautotrophic iron(II)-oxidizing bacteria were also frequently found via most-probable-number (MPN) cultivation. Halotolerant iron(II)-oxidizers in enrichment cultures were active at NaCl concentrations up to 1 M. Maximal microcalorimetrically determined pyrite oxidation rates coincided with maxima of the pyrite content, total cell counts, and MPN of iron(II)-oxidizers. These findings indicate that microbial pyrite oxidation and metal mobilization preferentially occur in distinct tailings layers at high salinity. Microorganisms for biomining with seawater salt concentrations obviously exist in nature.

Dietary habits among persons hired on shift work.

PubMed

Strzemecka, Joanna; Bojar, Iwona; Strzemecka, Ewa; Owoc, Alfred

2014-01-01

Shift-work determinates irregular nutrition habits. The quality as well as the quantity of meals consumed by shift-workers can significantly affects their health. The aim of this study was to evaluate the dietary habits of people performing shift work in the Bogdanka mine. The study was carried out in the Bogdanka mine in Leczna. The questionnaire, which was designed by the author of this dissertation, was conducted among 700 shift-workers, working underground. The results were subjected to statistical analysis based on STATISTICA v. 7.1 (StatSoft, Poland) software. Nearly half of respondents reported regular consumption of meals (40.0%) Interviewees admitted having warm meals during the day (81.4%). The most frequently consumed meal during the day was the hot one (50.9%), three meals and more were consumed the least frequently (8.1%). Almost half of respondents considered their eating habits as inappropriate (46.3%). Among those, nearly half (68.2%) stated that shift - work is the reason for their nutrition habits. More than half of respondents (66.0%) admitted that shift work hampers regular consumption of meals. Shift work makes nourishment and regular consumption difficult. It contributes to the limited amount of warm meals eaten during the day. In order to maintain preventive health care and the improvement of quality of life, shift workers should be provided with an easier access to meals (including warm one) at specified times of the day.

Statistically significant performance results of a mine detector and fusion algorithm from an x-band high-resolution SAR

NASA Astrophysics Data System (ADS)

Williams, Arnold C.; Pachowicz, Peter W.

2004-09-01

Current mine detection research indicates that no single sensor or single look from a sensor will detect mines/minefields in a real-time manner at a performance level suitable for a forward maneuver unit. Hence, the integrated development of detectors and fusion algorithms are of primary importance. A problem in this development process has been the evaluation of these algorithms with relatively small data sets, leading to anecdotal and frequently over trained results. These anecdotal results are often unreliable and conflicting among various sensors and algorithms. Consequently, the physical phenomena that ought to be exploited and the performance benefits of this exploitation are often ambiguous. The Army RDECOM CERDEC Night Vision Laboratory and Electron Sensors Directorate has collected large amounts of multisensor data such that statistically significant evaluations of detection and fusion algorithms can be obtained. Even with these large data sets care must be taken in algorithm design and data processing to achieve statistically significant performance results for combined detectors and fusion algorithms. This paper discusses statistically significant detection and combined multilook fusion results for the Ellipse Detector (ED) and the Piecewise Level Fusion Algorithm (PLFA). These statistically significant performance results are characterized by ROC curves that have been obtained through processing this multilook data for the high resolution SAR data of the Veridian X-Band radar. We discuss the implications of these results on mine detection and the importance of statistical significance, sample size, ground truth, and algorithm design in performance evaluation.

Twenty-one-year experience with land mine injuries.

PubMed

Adams, D B; Schwab, C W

1988-01-01

Land mines produce devastating injuries which are usually fatal. In Guantanamo Bay, there have been no survivors from close range, functioning antipersonnel mines of the M-16 series. All 15 antipersonnel mine fatalities suffered extremity amputation. Seven of the 15 patients suffered immediately fatal head, neck, or truncal injuries (Type I injury). The three patients who underwent hospital resuscitation had extremity amputation but were spared major head, neck, or truncal injury. It is in this group of injured that potentially salvageable patients can be identified; for them aggressive rescue and resuscitation must be performed. Those with Type II injuries are the highest priority in any triage plan. In a mass casualty or combat casualty scenario, Type II patients, in particular those with high bilateral above-the-knee amputations, may be reassigned to an expectant treatment category so as to allow the main focus on more salvageable patients. The prehospital management plan emphasizes rapid assessment and triage of patients, use of tourniquets to control extremity hemorrhage, supplemental oxygen or endotracheal intubation if possible, neck immobilization, use of the extremity section of the pneumatic antishock garment if applicable, and rapid transport to a hospital. Hospital management of these patients emphasizes aggressive resuscitation, early endotracheal intubation, and rapid volume replacement with simultaneous balanced salt solution and blood. Operative debridement with broad-spectrum antibiotic coverage and tetanus prophylaxis is performed; wounds are managed in an open fashion and frequently examined at subsequent dates in the operating room.

Process monitoring and control with CHEMIN, a miniaturized CCD-based instrument for simultaneous XRD/XRF analysis

NASA Astrophysics Data System (ADS)

Vaniman, David T.; Bish, D.; Guthrie, G.; Chipera, S.; Blake, David E.; Collins, S. Andy; Elliott, S. T.; Sarrazin, P.

1999-10-01

There is a large variety of mining and manufacturing operations where process monitoring and control can benefit from on-site analysis of both chemical and mineralogic constituents. CHEMIN is a CCD-based instrument capable of both X-ray fluorescence (XRF; chemical) and X-ray diffraction (XRD; mineralogic) analysis. Monitoring and control with an instrument like CHEMIN can be applied to feedstocks, intermediate materials, and final products to optimize production. Examples include control of cement feedstock, of ore for smelting, and of minerals that pose inhalation hazards in the workplace. The combined XRD/XRF capability of CHEMIN can be used wherever a desired commodity is associated with unwanted constituents that may be similar in chemistry or structure but not both (e.g., Ca in both gypsum and feldspar, where only the gypsum is desired to make wallboard). In the mining industry, CHEMIN can determine mineral abundances on the spot and enable more economical mining by providing the means to assay when is being mined, quickly and frequently, at minimal cost. In manufacturing, CHEMIN could be used to spot-check the chemical composition and crystalline makeup of a product at any stage of production. Analysis by CHEMIN can be used as feedback in manufacturing processes where rates of heating, process temperature, mixture of feedstocks, and other variables must be adjusted in real time to correct structure and/or chemistry of the product (e.g., prevention of periclase and alkali sulfate coproduction in cement manufacture).

PIPE: a protein–protein interaction passage extraction module for BioCreative challenge

PubMed Central

Chu, Chun-Han; Su, Yu-Chen; Chen, Chien Chin; Hsu, Wen-Lian

2016-01-01

Identifying the interactions between proteins mentioned in biomedical literatures is one of the frequently discussed topics of text mining in the life science field. In this article, we propose PIPE, an interaction pattern generation module used in the Collaborative Biocurator Assistant Task at BioCreative V (http://www.biocreative.org/) to capture frequent protein-protein interaction (PPI) patterns within text. We also present an interaction pattern tree (IPT) kernel method that integrates the PPI patterns with convolution tree kernel (CTK) to extract PPIs. Methods were evaluated on LLL, IEPA, HPRD50, AIMed and BioInfer corpora using cross-validation, cross-learning and cross-corpus evaluation. Empirical evaluations demonstrate that our method is effective and outperforms several well-known PPI extraction methods. Database URL: PMID:27524807

Sediment processes modelling below hydraulic mining: towards environmental impact mitigation

NASA Astrophysics Data System (ADS)

Chalov, Sergey R.

2010-05-01

Placer mining sites are located in the river valleys so the rivers are influenced by mining operations. Frequently the existing mining sites are characterized by low contribution to the environmental technologies. Therefore hydraulic mining alters stream hydrology and sediment processes and increases water turbidity. The most serious environmental sequences of the sediment yield increase occur in the rivers populated by salmon fish community because salmon species prefer clean water with low turbidity. For instance, the placer mining in Kamchatka peninsula (Far East of Russia) which is regarded to be the last global gene pool of wild salmon Oncorhynchus threatens the rivers ecosystems. System of man-made impact mitigation could be done through the exact recognition of the human role in hydrological processes and sediment transport especially. Sediment budget of rivers below mining sites is transformed according to the appearance of the man-made non-point and point sediment sources. Non-point source pollution occurs due to soil erosion on the exposed hillsides and erosion in the channel diversions. Slope wash on the hillsides is absent during summer days without rainfalls and is many times increased during rainfalls and snow melting. The nearness of the sources of material and the rivers leads to the small time of suspended load increase after rainfalls. The average time of material intake from exposed hillsides to the rivers is less than 1 hour. The main reason of the incision in the channel diversion is river-channel straightening. The increase of channel slopes and transport capacity leads to the intensive incision of flow. Point source pollution is performed by effluents both from mining site (mainly brief effluents) and from settling ponds (permanent effluents), groundwater seepage from tailing pits or from quarries. High rate of groundwater runoff is the main reason of the technological ponds overfilling. Intensive filtration from channel to ponds because of their nearness determines the water mass increase inside mining site. The predictive models were suggested to assess each of the mane-made processes contribution into the total sediment budget of the rivers below mining sites. The empirical data and theoretical and laboratory-derived correlations were used to obtain the predictive models for each processes of sediment supply. It was challenging to estimate specific erosion rate of washed exposed hillsides, channel incision, water supply conditions. Climatic and anthropogenic changes of water runoff also were simulated to decrease uncertainty of the proposed model. Application of the given approach to the hydraulic platinum-mining located in the Kamchatka peninsula (Koryak plateau, tributaries of the Vivenka River) gave the sediment budget of the placer-mined rivers and the total sediment yield supplied into the ocean from river basin. Polluted placer-mined rivers contribute about 30 % of the whole sediment yield of the Vivenka River. At the same time the catchment area of these rivers is less than 0,03 % from the whole Vivenka catchment area. Based on the sediment transport modeling the decision making system for controlling water pollution and stream community preservation was developed. Due to exposed hillside erosion prevention and settling pond system optimization the total decrease of sediment yield was up to 75 %.

Engineer: The Professional Bulletin of Army Engineers. Volume 41. January-April 2011

DTIC Science & Technology

2011-04-01

American, French and German. These were unfolded, and then ensued a long conference which included general in- structions and details for the...These maps, both Ger- man and French , would, in some cases, show traps and mines which did not exist but, more frequently, whole series of traps...Ignition Devices The staff officer had under his ar a great roll of aps, A erican, French and er an. These ere unfolded, and then ensued a long

Data: Mining with a Mission- Data-Driven Decision Making Is the Buzz Phrase of Choice for the New Decade. but Once We've Got the Information, How Do We Use It to Yield Results?

ERIC Educational Resources Information Center

Salpeter, Judy

2004-01-01

For some districts, the current obsession with data grows out of the need to comply with No Child Left Behind and additional accountability-related mandates. For others, it dates way back before the phrase "data-driven decision making" rolled so frequently off the tongues of educators. In either case, there is no denying that an integral…

Tour Recommendation Guide- Personalized travel sequence recommendation

NASA Astrophysics Data System (ADS)

Sivakumar, Akshitha; Prabadevi, B.

2017-11-01

Presents a personalized travel sequence for the given area the individual wants to visit. It not only helps to personalize the travel but also recommend a travel sequence based on the area mentioned. Firstly the frequently visited routes are ranked then top ranked routes are chosen based on previous travel records. The data is being collected using data mining and the famous routes are ranked based on user and the route. It helps in bridging the gap between user travel preference and routes.

Suitability of ponds formed by strip mining in eastern Oklahoma for public water supply, aquatic life, waterfowl habitat, livestock watering, irrigation, and recreation

USGS Publications Warehouse

Parkhurst, Renee S.

1994-01-01

A study of coal ponds formed by strip mining in eastern Oklahoma included 25 ponds formed by strip mining from the Croweburg, McAlester, and Iron Post coal seams and 6 noncoal-mine ponds in the coal-mining area. Water-quality samples were collected in the spring and summer of 1985 to determine the suitability of the ponds for public water supply, aquatic life, waterfowl habitat, livestock watering, irrigation, and recreation. The rationale for water-quality criteria and the criteria used for each proposed use are discussed. The ponds were grouped by the coal seam mined or as noncoal-mine ponds, and the number of ponds from each group containing water that exceeded a given criterion is noted. Water in many of the ponds can be used for public water supplies if other sources are not available. Water in most of these ponds exceeds one or more secondary standards, but meets all primary standards. Water samples from the epilimnion (shallow strata as determined by temperature) of six ponds exceeded one or more primary standards, which are criteria protective of human health. Water samples from five of eight Iron Post ponds exceeded the selenium criterion. Water samples from all 31 ponds exceeded one or more secondary standards, which are for the protection of human welfare. The criteria most often exceeded were iron, manganese, dissolved solids, and sulfate, which are secondary standards. The criteria for iron and manganese were exceeded more frequently in the noncoal-mine ponds, whereas ponds formed by strip mining were more likely to exceed the criteria for dissolved solids and sulfate. The ponds are marginally suited for aquatic life. Water samples from the epilimnion of 18 ponds exceeded criteria protective of aquatic life. The criteria for mercury and iron were exceeded most often. Little difference was detected between mine ponds and noncoal-mine ponds. Dissolved oxygen concentrations in the hypolimnion (deepest strata) of all the ponds were less than the minimum criterion during the summer. This decreases available fish habitat and affects the type and number of benthic invertebrates. The ponds are generally well suited for use by wintering and migrating waterfowl. Thirteen of the ponds contained water that exceeded the pH, alkalinity, and selenium criteria. The noncoal-mine ponds had the largest percentage of ponds exceeding pH and alkalinity criteria. Water samples from five of eight Iron Post ponds exceeded the selenium criterion. All ponds are generally unsuitable as waterfowl habitat during the summer because of high temperatures and low dissolved oxygen. Most of the ponds are well suited for livestock watering. Water samples from the epilimnion of 29 ponds met all chemical and physical criteria. Water samples from five ponds exceeded the criteria in the hypolimnion. Mine ponds exceeded chemical and physical criteria more often than noncoal-mine ponds. All the ponds contained phytoplankton species potentially toxic to livestock. Water from most of the ponds is marginally suitable for irrigation of sensitive crops, but is more suitable for irrigation of semitolerant and tolerant crops. Most major cash crops grown in eastern Oklahoma are semitolerant and tolerant crops. Water from the epilimnion of 14 ponds was suitable for irrigation under almost all conditions. Water from the epilimnion of 20 ponds was suitable for irrigation of semitolerant crops, and water from the epilimnion of 25 ponds is suitable for irrigation of tolerant crops. The dissolved solids criterion was exceeded the most often. Most of the ponds would not be suitable for swimming. The pH criterion was exceeded in 17 ponds and turbidity restricts visibility needed for diving in 23 ponds. Little difference was detected between mine ponds and noncoal-mine ponds. Many of the ponds formed by strip mining have steep banks that may be dangerous to swimmers.

Analysis of Human Mobility Based on Cellular Data

NASA Astrophysics Data System (ADS)

Arifiansyah, F.; Saptawati, G. A. P.

2017-01-01

Nowadays not only adult but even teenager and children have then own mobile phones. This phenomena indicates that the mobile phone becomes an important part of everyday’s life. Based on these indication, the amount of cellular data also increased rapidly. Cellular data defined as the data that records communication among mobile phone users. Cellular data is easy to obtain because the telecommunications company had made a record of the data for the billing system of the company. Billing data keeps a log of the users cellular data usage each time. We can obtained information from the data about communication between users. Through data visualization process, an interesting pattern can be seen in the raw cellular data, so that users can obtain prior knowledge to perform data analysis. Cellular data processing can be done using data mining to find out human mobility patterns and on the existing data. In this paper, we use frequent pattern mining and finding association rules to observe the relation between attributes in cellular data and then visualize them. We used weka tools for finding the rules in stage of data mining. Generally, the utilization of cellular data can provide supporting information for the decision making process and become a data support to provide solutions and information needed by the decision makers.

Sediment storage and severity of contamination in a shallow reservoir affected by historical lead and zinc mining

USGS Publications Warehouse

Juracek, K.E.

2008-01-01

A combination of sediment-thickness measurement and bottom-sediment coring was used to investigate sediment storage and severity of contamination in Empire Lake (Kansas), a shallow reservoir affected by historical Pb and Zn mining. Cd, Pb, and Zn concentrations in the contaminated bottom sediment typically exceeded baseline concentrations by at least an order of magnitude. Moreover, the concentrations of Cd, Pb, and Zn typically far exceeded probable-effects guidelines, which represent the concentrations above which toxic biological effects usually or frequently occur. Despite a pre-1954 decrease in sediment concentrations likely related to the end of major mining activity upstream by about 1920, concentrations have remained relatively stable and persistently greater than the probable-effects guidelines for at least the last 50 years. Cesium-137 evidence from sediment cores indicated that most of the bottom sediment in the reservoir was deposited prior to 1954. Thus, the ability of the reservoir to store the contaminated sediment has declined over time. Because of the limited storage capacity, Empire Lake likely is a net source of contaminated sediment during high-inflow periods. The contaminated sediment that passes through, or originates from, Empire Lake will be deposited in downstream environments likely as far as Grand Lake O' the Cherokees (Oklahoma). ?? 2007 Springer-Verlag.

Growth of Quailbush in Acidic, Metalliferous Desert Mine Tailings: Effect of Azospirillum brasilense Sp6 on Biomass Production and Rhizosphere Community Structure

PubMed Central

de-Bashan, Luz E.; Hernandez, Juan-Pablo; Nelson, Karis N.; Bashan, Yoav

2010-01-01

Mine tailing deposits in semiarid and arid environments frequently remain devoid of vegetation due to the toxicity of the substrate and the absence of a diverse soil microbial community capable of supporting seed germination and plant growth. The contribution of the plant growth promoting bacterium (PGPB) Azospirillum brasilense Sp6 to the growth of quailbush in compost-amended, moderately acidic, high-metal content mine tailings using an irrigation-based reclamation strategy was examined along with its influence on the rhizosphere bacterial community. Sp6 inoculation resulted in a significant (2.2-fold) increase in plant biomass production. The data suggest that the inoculum successfully colonized the root surface and persisted throughout the 60-day experiment in both the rhizosphere, as demonstrated by excision and sequencing of the appropriate denaturing gradient gel electrophoresis (DGGE) band, and the rhizoplane, as indicated by fluorescent in situ hybridization of root surfaces. Changes in rhizosphere community structure in response to Sp6 inoculation were evaluated after 15, 30, and 60 days using DGGE analysis of 16S rRNA polymerase chain reaction amplicons. A comparison of DGGE profiles using canonical correspondence analysis revealed a significant treatment effect (Sp6-inoculated vs. uninoculated plants vs. unplanted) on bacterial community structure at 15, 30, and 60 days (p<0.05). These data indicate that in an extremely stressed environment such as acid mine tailings, an inoculated plant growth promoting bacterium not only can persist and stimulate plant growth but also can directly or indirectly influence rhizobacterial community development. PMID:20632001

Comparative data mining analysis for information retrieval of MODIS images: monitoring lake turbidity changes at Lake Okeechobee, Florida

NASA Astrophysics Data System (ADS)

Chang, Ni-Bin; Daranpob, Ammarin; Yang, Y. Jeffrey; Jin, Kang-Ren

2009-09-01

In the remote sensing field, a frequently recurring question is: Which computational intelligence or data mining algorithms are most suitable for the retrieval of essential information given that most natural systems exhibit very high non-linearity. Among potential candidates might be empirical regression, neural network model, support vector machine, genetic algorithm/genetic programming, analytical equation, etc. This paper compares three types of data mining techniques, including multiple non-linear regression, artificial neural networks, and genetic programming, for estimating multi-temporal turbidity changes following hurricane events at Lake Okeechobee, Florida. This retrospective analysis aims to identify how the major hurricanes impacted the water quality management in 2003-2004. The Moderate Resolution Imaging Spectroradiometer (MODIS) Terra 8-day composite imageries were used to retrieve the spatial patterns of turbidity distributions for comparison against the visual patterns discernible in the in-situ observations. By evaluating four statistical parameters, the genetic programming model was finally selected as the most suitable data mining tool for classification in which the MODIS band 1 image and wind speed were recognized as the major determinants by the model. The multi-temporal turbidity maps generated before and after the major hurricane events in 2003-2004 showed that turbidity levels were substantially higher after hurricane episodes. The spatial patterns of turbidity confirm that sediment-laden water travels to the shore where it reduces the intensity of the light necessary to submerged plants for photosynthesis. This reduction results in substantial loss of biomass during the post-hurricane period.

Quality of water and sediment in streams affected by historical mining, and quality of Mine Tailings, in the Rio Grande/Rio Bravo Basin, Big Bend Area of the United States and Mexico, August 2002

USGS Publications Warehouse

Lambert, Rebecca B.; Kolbe, Christine M.; Belzer, Wayne

2008-01-01

The U.S. Geological Survey, in cooperation with the International Boundary and Water Commission - U.S. and Mexican Sections, the National Park Service, the Texas Commission on Environmental Quality, the Secretaria de Medio Ambiente y Recursos Naturales in Mexico, the Area de Proteccion de Flora y Fauna Canon de Santa Elena in Mexico, and the Area de Proteccion de Flora y Fauna Maderas del Carmen in Mexico, collected samples of stream water, streambed sediment, and mine tailings during August 2002 for a study to determine whether trace elements from abandoned mines in the area in and around Big Bend National Park have affected the water and sediment quality in the Rio Grande/Rio Bravo Basin of the United States and Mexico. Samples were collected from eight sites on the main stem of the Rio Grande/Rio Bravo, four Rio Grande/Rio Bravo tributary sites downstream from abandoned mines or mine-tailing sites, and 11 mine-tailing sites. Mines in the area were operated to produce fluorite, germanium, iron, lead, mercury, silver, and zinc during the late 1800s through at least the late 1970s. Moderate (relatively neutral) pHs in stream-water samples collected at the 12 Rio Grande/Rio Bravo main-stem and tributary sites indicate that water is well mixed, diluted, and buffered with respect to the solubility of trace elements. The highest sulfate concentrations were in water samples from tributaries draining the Terlingua mining district. Only the sample from the Rough Run Draw site exceeded the Texas Surface Water Quality Standards general-use protection criterion for sulfate. All chloride and dissolved solids concentrations in water samples were less than the general-use protection criteria. Aluminum, copper, mercury, nickel, selenium, and zinc were detected in all water samples for which each element was analyzed. Cadmium, chromium, and lead were detected in samples less frequently, and silver was not detected in any of the samples. None of the sample concentrations of aluminum, cadmium, chromium, nickel, selenium, and zinc exceeded the Texas Surface Water Quality Standards criteria for aquatic life-use protection or human health. The only trace elements detected in the water samples at concentrations exceeding the Texas Surface Water Quality Standards criterion for human health (fish consumption use) was lead at one site and mercury at 10 of 12 sites. Relatively high mercury concentrations distributed throughout the area might indicate sources of mercury in addition to abandoned mining areas. Streambed-sediment samples were collected from 12 sites and analyzed for 44 major and trace elements. In general, the trace elements detected in streambed-sediment samples were low in concentration, interpreted as consistent with background concentrations. Concentrations at two sites, however, were elevated compared to Texas Commission on Environmental Quality criteria. Concentrations of antimony, arsenic, cadmium, lead, silver, and zinc in the sample from San Carlos Creek downstream from La Esperanza (San Carlos) Mine exceeded the Texas Commission on Environmental Quality screening levels for sediment. The sample from Rough Run Draw, downstream from the Study Butte Mine, also showed elevated concentrations of arsenic, cadmium, and lead, but these concentrations were much lower than those in the San Carlos Creek sample and did not exceed screening levels. Elevated concentrations of multiple trace elements in streambed-sediment samples from San Carlos Creek and Rough Run Draw indicate that San Carlos Creek, and probably Rough Run Draw, have been adversely affected by mining activities. Fourteen mine-tailing samples from 11 mines were analyzed for 25 major and trace elements. All trace elements except selenium and thallium were detected in one or more samples. The highest lead concentrations were detected in tailings samples from the Boquillas, Puerto Rico, La Esperanza (San Carlos), and Tres Marias Mines, as might be expected because the tailings ar

Deposits of Large-scale Mass Movements in the Sediments of Hallstätter See (Austria) - Recurrent Natural Hazards at a UNESCO World Cultural Heritage Site

NASA Astrophysics Data System (ADS)

Lauterbach, S.; Strasser, M.; Tjallingii, R.; Kowarik, K.; Reschreiter, H.; Spatl, C.; Brauer, A.

2017-12-01

The cultural importance of underground salt mining in Hallstatt (Austria), which is documented since the Middle Bronze Age, has been recognized already 20 years ago by assigning the status of a UNESCO World Cultural Heritage Site to the Hallstatt area, particularly because of the wealth of archaeological artefacts from the Early Iron Age. Local mining activity is well documented for prehistoric times and known to have been repeatedly affected by large-scale mass movements, for example at the end of the Bronze Age and during the Late Iron Age. In contrast, evidence of mining activity between the 5th and late 13th century AD is scarce, which could be related to socio-economic changes but also to continued mass movement activity, possibly biasing the archaeological record. Within the present study, a 15.63-m-long 14C-dated sediment core from Hallstätter See has been investigated with respect to the deposits of large-scale mass movements. Most of the lake sediment sequence consists of cm- to sub-mm-scale laminated carbonate mud with frequently intercalated small-scale turbidites, reflecting seasonally variable detrital input from the tributaries, but two major event layers clearly stand out. The upper one comprises a 2.45-m-thick basal mass transport deposit (containing folded laminated sediments, homogenized sediments with liquefaction structures, and coarse gravel) and an overlying 1.45-m-thick co-genetic turbidite. From the lower event layer only the topmost part of the turbiditic sequence with a (minimum) thickness of 1.49 m was recovered. Based on their sedimentological characteristics, both event layers are interpreted as the subaqueous continuation of large-scale mass movements, which occurred at ca. 1050 and 2300 cal. years BP and possibly originated from the rock walls along the western lake shore where also the salt mining area is located. This indicates that mass movement activity not only threatened prehistoric salt mining, but occurred also repeatedly during the Common Era, possibly explaining the lack of archaeological evidence of mining activity between the 5th and late 13th century AD. However, a direct spatial and temporal relationship between documented mass movements in the mining area and those recorded in the lake sediments cannot be proven at present and requires further investigations.

Knowledge discovery in cardiology: A systematic literature review.

PubMed

Kadi, I; Idri, A; Fernandez-Aleman, J L

2017-01-01

Data mining (DM) provides the methodology and technology needed to transform huge amounts of data into useful information for decision making. It is a powerful process employed to extract knowledge and discover new patterns embedded in large data sets. Data mining has been increasingly used in medicine, particularly in cardiology. In fact, DM applications can greatly benefit all those involved in cardiology, such as patients, cardiologists and nurses. The purpose of this paper is to review papers concerning the application of DM techniques in cardiology so as to summarize and analyze evidence regarding: (1) the DM techniques most frequently used in cardiology; (2) the performance of DM models in cardiology; (3) comparisons of the performance of different DM models in cardiology. We performed a systematic literature review of empirical studies on the application of DM techniques in cardiology published in the period between 1 January 2000 and 31 December 2015. A total of 149 articles published between 2000 and 2015 were selected, studied and analyzed according to the following criteria: DM techniques and performance of the approaches developed. The results obtained showed that a significant number of the studies selected used classification and prediction techniques when developing DM models. Neural networks, decision trees and support vector machines were identified as being the techniques most frequently employed when developing DM models in cardiology. Moreover, neural networks and support vector machines achieved the highest accuracy rates and were proved to be more efficient than other techniques. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Spatial Data Mining for Estimating Cover Management Factor of Universal Soil Loss Equation

NASA Astrophysics Data System (ADS)

Tsai, F.; Lin, T. C.; Chiang, S. H.; Chen, W. W.

2016-12-01

Universal Soil Loss Equation (USLE) is a widely used mathematical model that describes long-term soil erosion processes. Among the six different soil erosion risk factors of USLE, the cover-management factor (C-factor) is related to land-cover/land-use. The value of C-factor ranges from 0.001 to 1, so it alone might cause a thousandfold difference in a soil erosion analysis using USLE. The traditional methods for the estimation of USLE C-factor include in situ experiments, soil physical parameter models, USLE look-up tables with land use maps, and regression models between vegetation indices and C-factors. However, these methods are either difficult or too expensive to implement in large areas. In addition, the values of C-factor obtained using these methods can not be updated frequently, either. To address this issue, this research developed a spatial data mining approach to estimate the values of C-factor with assorted spatial datasets for a multi-temporal (2004 to 2008) annual soil loss analysis of a reservoir watershed in northern Taiwan. The idea is to establish the relationship between the USLE C-factor and spatial data consisting of vegetation indices and texture features extracted from satellite images, soil and geology attributes, digital elevation model, road and river distribution etc. A decision tree classifier was used to rank influential conditional attributes in the preliminary data mining. Then, factor simplification and separation were considered to optimize the model and the random forest classifier was used to analyze 9 simplified factor groups. Experimental results indicate that the overall accuracy of the data mining model is about 79% with a kappa value of 0.76. The estimated soil erosion amounts in 2004-2008 according to the data mining results are about 50.39 - 74.57 ton/ha-year after applying the sediment delivery ratio and correction coefficient. Comparing with estimations calculated with C-factors from look-up tables, the soil erosion values estimated with C-factors generated from spatial data mining results are more in agreement with the values published by the watershed administration authority.

Application of electrical resistivity tomography techniques for mapping man-made sinkholes

NASA Astrophysics Data System (ADS)

Rey, J.; Martínez, J.; Hidalgo, C.; Dueñas, J.

2012-04-01

The suitability of the geophysical prospecting by electrical resistivity tomography to detect and map man-made subsurface cavities and related sinkholes has been studied in the Linares abandoned mining district (Spain). We have selected for this study four mined sectors constituted of different lithologies: granite and phyllites of Paleozoic age, and Triassic shales and sandstones. In three of these sectors, detail underground topographic surveys were carried out to chart the position and dimensions of the mining voids (galleries and chamber), in order to analyze the resolution of this methodology to characterize these cavities by using different electrode arrays. The results are variable, depending on the depth and diameter of the void, the selected electrode array, the spacing between electrodes, geological complexity and data density. These results also indicate that when the cavity is empty, an anomaly with a steep gradient and high resistivity values is registered, because the air that fills the mining void is dielectric, while when the cavities are filled with fine grain sediments, frequently saturated in water, the electrical resistance is lower. In relation with the three different multi-electrode arrays tested, the Wenner-Schlumberger array has resulted to offer the maximum resolution in all these cases, with lower and more stable values for the RMS than the other arrays. Therefore, this electrode array has been applied in the fourth studied sector, a former mine near the city centre of Linares, in an area of urban expansion in which there are problems of subsidence. Two sets of four electrical tomography profiles have been carried out, perpendicular to each other, and which have allowed reaching depths of research between 30-35 m. This net-array allowed the identification of two shallow anomalies of low resistivity values, interpreted as old mining galleries filled with fine material saturated in water. It also allows detecting two fractures, correlated in the profiles and which can be mapped to more than 25 m in depth. As showed by this case study, electrical resistivity tomography can be a suitable tool in sub-surface cavities detection and man-made sinkhole investigations.

A Study on Environmental Research Trends Using Text-Mining Method - Focus on Spatial information and ICT -

NASA Astrophysics Data System (ADS)

Lee, M. J.; Oh, K. Y.; Joung-ho, L.

2016-12-01

Recently there are many research about analysing the interaction between entities by text-mining analysis in various fields. In this paper, we aimed to quantitatively analyse research-trends in the area of environmental research relating either spatial information or ICT (Information and Communications Technology) by Text-mining analysis. To do this, we applied low-dimensional embedding method, clustering analysis, and association rule to find meaningful associative patterns of key words frequently appeared in the articles. As the authors suppose that KCI (Korea Citation Index) articles reflect academic demands, total 1228 KCI articles that have been published from 1996 to 2015 were reviewed and analysed by Text-mining method. First, we derived KCI articles from NDSL(National Discovery for Science Leaders) site. And then we pre-processed their key-words elected from abstract and then classified those in separable sectors. We investigated the appearance rates and association rule of key-words for articles in the two fields: spatial-information and ICT. In order to detect historic trends, analysis was conducted separately for the four periods: 1996-2000, 2001-2005, 2006-2010, 2011-2015. These analysis were conducted with the usage of R-software. As a result, we conformed that environmental research relating spatial information mainly focused upon such fields as `GIS(35%)', `Remote-Sensing(25%)', `environmental theme map(15.7%)'. Next, `ICT technology(23.6%)', `ICT service(5.4%)', `mobile(24%)', `big data(10%)', `AI(7%)' are primarily emerging from environmental research relating ICT. Thus, from the analysis results, this paper asserts that research trends and academic progresses are well-structured to review recent spatial information and ICT technology and the outcomes of the analysis can be an adequate guidelines to establish environment policies and strategies. KEY WORDS: Big data, Test-mining, Environmental research, Spatial-information, ICT Acknowledgements: The authors appreciate the support that this study has received from `Building application frame of environmental issues, to respond to the latest ICT trends'.

Potentials of marginal lands - sponateous ecosystem development

NASA Astrophysics Data System (ADS)

Gerwin, Werner; Schaaf, Wolfgang

2017-04-01

Marginal lands are often considered as unfertile and not productive. They are widely excluded from modern land use by conventional agriculture. Assessment of soil fertility usually shows very low productivity potentials at least for growing traditional crops. However, it can be frequently observed that natural succession at different types of marginal lands leads to very diverse and nonetheless productive ecosystems. Examples can be found at abandoned former industrial or transportation sites which were set aside and not further maintained - and also in post-mining landscapes. In one of the lignite open cast mines of the State of Brandenburg in Eastern Germany a landscape observatory was established in 2005 for observing this natural ecosystem development under marginal site conditions. The site of 6 ha is part of the post-mining landscapes of Lusatia which are often characterized by poor soil conditions and clearly reduced soil fertility. It is named "Hühnerwasser-Quellgebiet" (Chicken Creek Catchment) after a small stream that is restored again after destruction by the mining operations. It is planned to serve as the headwater of this stream and was left to an unrestricted primary succession. A comprehensive scientific monitoring program is carried out since the start of ecosystem development in 2005. The results offer exemplary insights into the establishment of interaction networks between the developing ecosystem compartments. After 10 years a large biodiversity, expressed by a high number of species, can be found at this site as the result of natural recovery processes. A large number of both tree species and individuals have settled here. Even if no economic use of the site and of the woody biomass produced by these trees is planned, an overall assessment of the biomass production was carried out. The results showed that the biomass production from natural succession without any application of fertilizers etc. is directly comparable with yields from adjacent post-mining sites where trees are grown in agroforestry systems for bioenergy production. This reflects the general potentials of marginal lands with regard to biomass production.

Population exposure to trace elements in the Kilembe copper mine area, Western Uganda: A pilot study.

PubMed

Mwesigye, Abraham R; Young, Scott D; Bailey, Elizabeth H; Tumwebaze, Susan B

2016-12-15

The mining and processing of copper in Kilembe, Western Uganda, from 1956 to 1982 left over 15 Mt. of tailings containing cupriferous and cobaltiferous pyrite dumped within a mountain river valley. This pilot study was conducted to assess the nature and extent of risk to local populations from metal contamination arising from those mining activities. We determined trace element concentrations in mine tailings, soils, locally cultivated foods, house dust, drinking water and human biomarkers (toenails) using ICP-MS analysis of acid digested samples. The results showed that tailings, containing higher concentrations of Co, Cu, Ni and As compared with world average crust values had eroded and contaminated local soils. Pollution load indices revealed that 51% of agricultural soils sampled were contaminated with trace elements. Local water supplies were contaminated, with Co concentrations that exceeded Wisconsin (US) thresholds in 25% of domestic water supplies and 40% of Nyamwamba river water samples. Zinc exceeded WHO/FAO thresholds of 99.4mgkg -1 in 36% of Amaranthus vegetable samples, Cu exceeded EC thresholds of 20mgkg -1 in 19% of Amaranthus while Pb exceeded WHO thresholds of 0.3mgkg -1 in 47% of Amaranthus vegetables. In bananas, 20% of samples contained Pb concentrations that exceeded the WHO/FAO recommended threshold of 0.3mgkg -1 . However, risk assessment of local foods and water, based on hazard quotients (HQ values) revealed no potential health effects. The high external contamination of volunteers' toenails with some elements (even after a washing process) calls into question their use as a biomarker for metal exposure in human populations where feet are frequently exposed to soil dust. Any mitigation of Kilembe mine impacts should be aimed at remediation of agricultural soils, regulating the discharge of underground contaminated water but also containment of tailing erosion. Copyright © 2016 Elsevier B.V. All rights reserved.

Psychological distress in remote mining and construction workers in Australia.

PubMed

Bowers, Jennifer; Lo, Johnny; Miller, Peta; Mawren, Daveena; Jones, Brooklyn

2018-05-21

To assess the prevalence and correlates of psychological distress in a sample of remote mining and construction workers in Australia. Design, setting: A cross-sectional, anonymous Wellbeing and Lifestyle Survey at ten mining sites in South Australia and Western Australia, administered at meetings held during 2013-2015. 1124 employees at remote construction, and open cut and underground mining sites completed the survey. General psychological distress (Kessler Psychological Distress Scale, K10) and self-reported overall mental health status; work, lifestyle and family factors correlated with level of psychological distress. The final sample comprised 1124 workers; 93.5% were men, 63% were aged 25-44 years. 311 respondents (28%) had K10 scores indicating high/very high psychological distress, compared with 10.8% for Australia overall. The most frequently reported stressors were missing special events (86%), relationship problems with partners (68%), financial stress (62%), shift rosters (62%), and social isolation (60%). High psychological distress was significantly more likely in workers aged 25-34 years (v ≥ 55 years: odds ratio [OR], 3.2; P = 0.001) and workers on a 2 weeks on/1 week off roster (v 4 weeks on/1 week off: OR, 2.4; P < 0.001). Workers who were very or extremely stressed by their assigned tasks or job (OR, 6.2; P = 0.004), their current relationship (OR, 8.2; P < 0.001), or their financial situation (OR, 6.0; P < 0.001) were significantly more likely to have high/very high K10 scores than those not stressed by these factors. Workers who reported stress related to stigmatisation of mental health problems were at the greatest risk of high/very high psychological distress (v not stressed: OR, 23.5; P < 0.001). Psychological distress is significantly more prevalent in the remote mining and construction workforce than in the overall Australian population. The factors that contribute to mental ill health in these workers need to be addressed, and the stigma associated with mental health problems reduced.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Taylor, Mark Patrick, E-mail: mark.taylor@mq.edu.au; Mould, Simon Anthony; Kristensen, Louise Jane

Although blood lead values in children are predominantly falling globally, there are locations where lead exposure remains a persistent problem. One such location is Broken Hill, Australia, where the percentage of blood lead values >10 μg/dL in children aged 1–4 years has risen from 12.6% (2010), to 13% (2011) to 21% (2012). The purpose of this study was to determine the extent of metal contamination in places accessible to children. This study examines contemporary exposure risks from arsenic, cadmium, lead, silver and zinc in surface soil and dust, and in pre- and post-play hand wipes at six playgrounds across Brokenmore » Hill over a 5-day period in September 2013. Soil lead (mean 2,450 mg/kg) and zinc (mean 3,710 mg/kg) were the most elevated metals in playgrounds. Surface dust lead concentrations were consistently elevated (mean 27,500 μg/m{sup 2}) with the highest lead in surface dust (59,900 μg/m{sup 2}) and post-play hand wipes (60,900 μg/m{sup 2}) recorded close to existing mining operations. Surface and post-play hand wipe dust values exceeded national guidelines for lead and international benchmarks for arsenic, cadmium and lead. Lead isotopic compositions ({sup 206}Pb/{sup 207}Pb, {sup 208}Pb/{sup 207}Pb) of surface dust wipes from the playgrounds revealed the source of lead contamination to be indistinct from the local Broken Hill ore body. The data suggest frequent, cumulative and ongoing mine-derived dust metal contamination poses a serious risk of harm to children. - Highlights: 1.Playground soils and surface dust in a mining town have high metal concentrations. 2.Elevated levels of As, Cd, Pb and Zn dust are found on playground users′ hands. 3.Pb isotope analysis shows that the source of playground dust is ore body Pb. 4.Surface mine operations must be contained to reduce childhood lead exposure risks. 5.Mine environmental licences need to set trigger values for As, Cd, Pb and Zn dust.« less

Content-Aware DataGuide with Incremental Index Update using Frequently Used Paths

NASA Astrophysics Data System (ADS)

Sharma, A. K.; Duhan, Neelam; Khattar, Priyanka

2010-11-01

Size of the WWW is increasing day by day. Due to the absence of structured data on the Web, it becomes very difficult for information retrieval tools to fully utilize the Web information. As a solution to this problem, XML pages come into play, which provide structural information to the users to some extent. Without efficient indexes, query processing can be quite inefficient due to an exhaustive traversal on XML data. In this paper an improved content-centric approach of Content-Aware DataGuide, which is an indexing technique for XML databases, is being proposed that uses frequently used paths from historical query logs to improve query performance. The index can be updated incrementally according to the changes in query workload and thus, the overhead of reconstruction can be minimized. Frequently used paths are extracted using any Sequential Pattern mining algorithm on subsequent queries in the query workload. After this, the data structures are incrementally updated. This indexing technique proves to be efficient as partial matching queries can be executed efficiently and users can now get the more relevant documents in results.

Post-licensure surveillance of quadrivalent inactivated influenza (IIV4) vaccine in the United States, Vaccine Adverse Event Reporting System (VAERS), July 1, 2013-May 31, 2015.

PubMed

Haber, Penina; Moro, Pedro L; Lewis, Paige; Woo, Emily Jane; Jankosky, Christopher; Cano, Maria

2016-05-11

Quadrivalent inactivated influenza vaccines (IIV4) were first available for use during 2013-14 influenza season for individuals aged ≥6 months. IIV4 is designed to protect against four different flu viruses; two influenza A viruses and two influenza B viruses. We searched the Vaccine Adverse Event Reporting System (VAERS) for US reports after IIV4 and trivalent inactivated influenza vaccine (IIV3) from 7/1/2013-5/31/2015. Medical records were requested for non-manufacturer reports classified as serious (i.e. death, hospitalization, prolonged hospitalization, life-threatening illness, permanent disability). The review included automated data analysis, clinical review of all serious reports, reports of special interest, and empirical Bayesian data mining. VAERS received 1,838 IIV4 reports; 512 (28%) in persons aged 6 months-17 years of which 42 (8.2%) were serious reports; 1,265 (69%) in persons aged >18 years of which 84 (6.6%) were serious reports; two in children <6 months and 59 in persons of unknown age. Injection site erythema (24%), fever (14%) and injection site swelling (17%) were the most frequent adverse events among persons aged 6 months-17 years, while injection site pain (16%), pain (15%) and pain in extremity (13%) were the most frequent among persons aged 18-64 years given the vaccine alone. Among non-death serious reports, injection site reactions, constitutional symptoms, Guillain-Barré syndrome, seizures, and anaphylaxis were the most frequently reported adverse events. Data mining detected disproportional reporting for incorrect vaccine administration with no associated adverse events. Adverse events following IIV4 reported to VAERS were similar to those following IIV3. In our review of VAERS reports, IIV4 had a similar safety profile to IIV3. Most of the reported AEs were non-serious. Our findings are consistent with data from pre-licensure studies of IIV4. Published by Elsevier Ltd.

Post-licensure surveillance of 13-valent pneumococcal conjugate vaccine (PCV13) in adults aged ⩾19years old in the United States, Vaccine Adverse Event Reporting System (VAERS), June 1, 2012-December 31, 2015.

PubMed

Haber, Penina; Arana, Jorge; Pilishvili, Tamara; Lewis, Paige; Moro, Pedro L; Cano, Maria

2016-12-07

The 13-valent pneumococcal conjugate vaccine (PCV13) was first recommended for use in adults aged ⩾19years with immunocompromising conditions in June 2012. On August 2014, the Advisory Committee on Immunization Practices (ACIP) recommended routine use of PCV13 among adults aged ⩾65years. We assessed adverse events (AEs) reports following PCV13 in adults aged ⩾19years reported to the Vaccine Adverse Event Reporting System (VAERS) from June 2012 to December 2015. VAERS is a national spontaneous reporting system for monitoring AEs following vaccination. Our assessment included automated data analysis, clinical review of all serious reports and reports of special interest. We conducted empirical Bayesian data mining to assess for disproportionate reporting. VAERS received 2976 US PCV13 adult reports; 2103 (71%) of these reports were from PCV13 administered alone. Fourteen percent were in persons aged 19-64years and 86% were in persons aged ⩾65years. Injection site erythema (28%), injection site pain (24%) and fever (22%) were the most frequent AEs among persons aged 19-64years; injection site erythema (30%), erythema (20%) and injection site swelling (18%) were the most frequent among persons aged ⩾65years who were given the vaccine alone. The most frequently reported AEs among non-death serious reports were injection site reactions and general malaise among persons 19-64years old; injection site reactions, general malaise and Guillain-Barré syndrome among those ⩾65years (Table 2). Data mining did not detect disproportional reporting for any unexpected AE. The results of this study were consistent with safety data from pre-licensure studies of PCV13. We did not detect any new or unexpected AEs. Published by Elsevier Ltd.

Text feature extraction based on deep learning: a review.

PubMed

Liang, Hong; Sun, Xiao; Sun, Yunlei; Gao, Yuan

2017-01-01

Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep learning has made achievements in text mining. The major difference between deep learning and conventional methods is that deep learning automatically learns features from big data, instead of adopting handcrafted features, which mainly depends on priori knowledge of designers and is highly impossible to take the advantage of big data. Deep learning can automatically learn feature representation from big data, including millions of parameters. This thesis outlines the common methods used in text feature extraction first, and then expands frequently used deep learning methods in text feature extraction and its applications, and forecasts the application of deep learning in feature extraction.

Natural products for chronic cough: Text mining the East Asian historical literature for future therapeutics.

PubMed

Shergis, Johannah Linda; Wu, Lei; May, Brian H; Zhang, Anthony Lin; Guo, Xinfeng; Lu, Chuanjian; Xue, Charlie Changli

2015-08-01

Chronic cough is a significant health burden. Patients experience variable benefits from over the counter and prescribed products, but there is an unmet need to provide more effective treatments. Natural products have been used to treat cough and some plant compounds such as pseudoephedrine from ephedra and codeine from opium poppy have been developed into drugs. Text mining historical literature may offer new insight for future therapeutic development. We identified natural products used in the East Asian historical literature to treat chronic cough. Evaluation of the historical literature revealed 331 natural products used to treat chronic cough. Products included plants, minerals and animal substances. These natural products were found in 75 different books published between AD 363 and 1911. Of the 331 products, the 10 most frequently and continually used products were examined, taking into consideration findings from contemporary experimental studies. The natural products identified are promising and offer new directions in therapeutic development for treating chronic cough. © The Author(s) 2015.

Toxic and heavy metals as a cause of crayfish mass mortality from acidified headwater streams.

PubMed

Svobodová, Jitka; Douda, Karel; Fischer, David; Lapšanská, Natalia; Vlach, Pavel

2017-03-01

Mining activities are responsible for high concentrations of metals in river networks in many parts of the world. Mining activities and the resulting high loads of heavy metals interact with intensive acid rain, and often have great consequences for biodiversity. However, considering the frequently episodic nature of these heavy acid rains, there is little detailed evidence of direct impacts. In 2011 we observed a massive mortality of noble crayfish and stone crayfish in Padrťsko Special Area of Conservation (SAC) in the Brdy Mountain region of the Czech Republic. Based on concentrations of metals (Al, Fe, As, Cd, Pb, Cu, Zn and Hg) in various tissues (gills, hepatopancreas, muscle) of both dead and live crayfish in this locality compared to reference populations, these crayfish had experienced long-term exposure to increased levels of these metals. Here we give detailed documentation of crayfish mortality associated with high metal concentrations in the gills and other tissues of these endangered invertebrates.

David and Goliath: chemical perturbation of eukaryotes by bacteria.

PubMed

Ho, Louis K; Nodwell, Justin R

2016-03-01

Environmental microbes produce biologically active small molecules that have been mined extensively as antibiotics and a smaller number of drugs that act on eukaryotic cells. It is known that there are additional bioactives to be discovered from this source. While the discovery of new antibiotics is challenged by the frequent discovery of known compounds, we contend that the eukaryote-active compounds may be less saturated. Indeed, despite there being far fewer eukaryotic-active natural products these molecules interact with a far richer diversity of molecular and cellular targets.

Rehabilitation of landmine victims--the ultimate challenge.

PubMed Central

Walsh, Nicolas E.; Walsh, Wendy S.

2003-01-01

Antipersonnel landmines are often used indiscriminately and frequently result in injury or death of non-combatants. In the last 65 years, over 110 million mines have been spread throughout the world into an estimated 70 countries. Landmine victims use a disproportionately high amount of medical resources; the vast majority of incidents occur in regions and countries without a sophisticated medical infrastructure and with limited resources, where rehabilitation is difficult in the best of circumstances. It is suggested that only a quarter of the patients with amputation secondary to landmines receive appropriate care. PMID:14710508

A tutorial on information retrieval: basic terms and concepts

PubMed Central

Zhou, Wei; Smalheiser, Neil R; Yu, Clement

2006-01-01

This informal tutorial is intended for investigators and students who would like to understand the workings of information retrieval systems, including the most frequently used search engines: PubMed and Google. Having a basic knowledge of the terms and concepts of information retrieval should improve the efficiency and productivity of searches. As well, this knowledge is needed in order to follow current research efforts in biomedical information retrieval and text mining that are developing new systems not only for finding documents on a given topic, but extracting and integrating knowledge across documents. PMID:16722601

Applied Graph-Mining Algorithms to Study Biomolecular Interaction Networks

PubMed Central

2014-01-01

Protein-protein interaction (PPI) networks carry vital information on the organization of molecular interactions in cellular systems. The identification of functionally relevant modules in PPI networks is one of the most important applications of biological network analysis. Computational analysis is becoming an indispensable tool to understand large-scale biomolecular interaction networks. Several types of computational methods have been developed and employed for the analysis of PPI networks. Of these computational methods, graph comparison and module detection are the two most commonly used strategies. This review summarizes current literature on graph kernel and graph alignment methods for graph comparison strategies, as well as module detection approaches including seed-and-extend, hierarchical clustering, optimization-based, probabilistic, and frequent subgraph methods. Herein, we provide a comprehensive review of the major algorithms employed under each theme, including our recently published frequent subgraph method, for detecting functional modules commonly shared across multiple cancer PPI networks. PMID:24800226

Residential Mobility and Lung Cancer Risk: Data-Driven Exploration Using Internet Sources

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yoon, Hong-Jun; Tourassi, Georgia; Xu, Songhua

2015-01-01

Frequent relocation has been linked to health decline, particularly with respect to emotional and psychological wellbeing. In this paper we investigate whether there is an association between frequent relocation and lung cancer risk. For the initial investigation we leverage two online data sources to collect cancer and control subjects using web crawling and tailored text mining. The two data sources share different strengths and weaknesses in terms of the amount of detail, population representation, and sample size. One data source includes online obituaries. The second data source includes augmented LinkedIn profiles. For each data source, the subjects spatiotemporal history ismore » reconstructed from the available information provided in the obituaries and from the education and work experience provided in the LinkedIn profiles. The study shows that lung cancer subjects have higher mobility frequency than the control group. This trend is consistent for both data sources.« less

Treatment impacts on temporal microbial community dynamics during phytostabilization of acid-generating mine tailings in semiarid regions.

PubMed

Valentín-Vargas, Alexis; Neilson, Julia W; Root, Robert A; Chorover, Jon; Maier, Raina M

2018-03-15

Direct revegetation, or phytostabilization, is a containment strategy for contaminant metals associated with mine tailings in semiarid regions. The weathering of sulfide ore-derived tailings frequently drives acidification that inhibits plant establishment resulting in materials prone to wind and water dispersal. The specific objective of this study was to associate pyritic mine waste acidification, characterized through pore-water chemistry analysis, with dynamic changes in microbial community diversity and phylogenetic composition, and to evaluate the influence of different treatment strategies on the control of acidification dynamics. Samples were collected from a highly instrumented one-year mesocosm study that included the following treatments: 1) unamended tailings control; 2) tailings amended with 15% compost; and 3) the 15% compost-amended tailings planted with Atriplex lentiformis. Tailings samples were collected at 0, 3, 6 and 12months and pore water chemistry was monitored as an indicator of acidification and weathering processes. Results confirmed that the acidification process for pyritic mine tailings is associated with a temporal progression of bacterial and archaeal phylotypes from pH sensitive Thiobacillus and Thiomonas to communities dominated by Leptospirillum and Ferroplasma. Pore-water chemistry indicated that weathering rates were highest when Leptospirillum was most abundant. The planted treatment was most successful in disrupting the successional evolution of the Fe/S-oxidizing community. Plant establishment stimulated growth of plant-growth-promoting heterotrophic phylotypes and controlled the proliferation of lithoautotrophic Fe/S-oxidizers. The results suggest the potential for eco-engineering a microbial inoculum to stimulate plant establishment and inhibit proliferation of the most efficient Fe/S-oxidizing phylotypes. Copyright © 2017 Elsevier B.V. All rights reserved.

Using methods from the data mining and machine learning literature for disease classification and prediction: A case study examining classification of heart failure sub-types

PubMed Central

Austin, Peter C.; Tu, Jack V.; Ho, Jennifer E.; Levy, Daniel; Lee, Douglas S.

2014-01-01

Objective Physicians classify patients into those with or without a specific disease. Furthermore, there is often interest in classifying patients according to disease etiology or subtype. Classification trees are frequently used to classify patients according to the presence or absence of a disease. However, classification trees can suffer from limited accuracy. In the data-mining and machine learning literature, alternate classification schemes have been developed. These include bootstrap aggregation (bagging), boosting, random forests, and support vector machines. Study design and Setting We compared the performance of these classification methods with those of conventional classification trees to classify patients with heart failure according to the following sub-types: heart failure with preserved ejection fraction (HFPEF) vs. heart failure with reduced ejection fraction (HFREF). We also compared the ability of these methods to predict the probability of the presence of HFPEF with that of conventional logistic regression. Results We found that modern, flexible tree-based methods from the data mining literature offer substantial improvement in prediction and classification of heart failure sub-type compared to conventional classification and regression trees. However, conventional logistic regression had superior performance for predicting the probability of the presence of HFPEF compared to the methods proposed in the data mining literature. Conclusion The use of tree-based methods offers superior performance over conventional classification and regression trees for predicting and classifying heart failure subtypes in a population-based sample of patients from Ontario. However, these methods do not offer substantial improvements over logistic regression for predicting the presence of HFPEF. PMID:23384592

The systematic assessment of traditional evidence from the premodern Chinese medical literature: a text-mining approach.

PubMed

May, Brian H; Zhang, Anthony; Lu, Yubo; Lu, Chuanjian; Xue, Charlie C L

2014-12-01

This project aimed to develop an approach to evaluating information contained in the premodern Traditional Chinese Medicine (TCM) literature that was (1) comprehensive, systematic, and replicable and (2) able to produce quantifiable output that could be used to answer specific research questions in order to identify natural products for clinical and experimental research. The project involved two stages. In stage 1, 14 TCM collections and compendia were evaluated for suitability as sources for searching; 8 of these were compared in detail. The results were published in the Journal of Alternative and Complementary Medicine. Stage 2 developed a text-mining approach for two of these sources. The text-mining approach was developed for Zhong Hua Yi Dian; Encyclopaedia of Traditional Chinese Medicine, 4th edition) and Zhong Yi Fang Ji Da Ci Dian; Great Compendium of Chinese Medical Formulae). This approach developed procedures for search term selection; methods for screening, classifying, and scoring data; procedures for systematic searching and data extraction; data checking procedures; and approaches for analyzing results. Examples are provided for studies of memory impairment and diabetic nephropathy, and issues relating to data interpretation are discussed. This approach to the analysis of large collections of the premodern TCM literature uses widely available sources and provides a text-mining approach that is systematic, replicable, and adaptable to the requirements of the particular project. Researchers can use these methods to explore changes in the names and conceptions of a disease over time, to identify which therapeutic methods have been more or less frequently used in different eras for particular disorders, and to assist in the selection of natural products for research efforts.

Aerial gamma ray and magnetic survey: Powder River II Project, Gillette Quadrangle, Wyoming. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1979-04-01

The Gillette quadrangle in northeastern Wyoming and western South Dakota contains approximately equal portions of the Powder River Basin and the Black Hills Uplift. In these two structures, a relatively thick sequence of Paleozoic and Mesozoic strata represent nearly continuous deposition over the Precambrian basement complex. The Powder River Basin also contains a thick sequence of early Tertiary rocks which cover about 50% of the surface. A stratigraphic sequence from Upper Cretaceous to Precambrian is exposed in the Black Hills Uplift to the east. Magnetic data apparently illustrate the relative depth to the Precambrian crystalline rocks, but only weakly definemore » the boundary between the Powder River Basin and the Black Hills Uplift. The positions of some small isolated Tertiary intrusive bodies in the Black Hills Uplift are relatively well expressed. The Gillette quadrangle has been productive in terms of uranium mining, but its current status is uncertain. The producing uranium deposits occur within the Lower Cretaceous Inyan Kara Group and the Jurassic Morrison Formation in the Black Hills Uplift. Other prospects occur within the Tertiary Wasatch and Fort Union Formations in the Pumpkin Buttes - Turnercrest district, where it extends into the quadrangle from the Newcastle quadrangle to the south. These four formations, all predominantly nonmarine, contain all known uranium deposits in the Gillette quadrangle. A total of 108 groups of sample responses in the uranium window constitute anomalies as defined in Volume I. The anomalies are most frequently found in the Inyan Kara-Morrison, Wasatch and Fort Union Formations. Many anomalies occur over known mines or prospects. Others may result from unmapped uranium mines or areas where material other than uranium is mined. The remainder may relate to natural geologic features.« less

Exposing ecological and economic costs of the research-implementation gap and compromises in decision making.

PubMed

Kareksela, Santtu; Moilanen, Atte; Ristaniemi, Olli; Välivaara, Reima; Kotiaho, Janne S

2018-02-01

The frequently discussed gap between conservation science and practice is manifest in the gap between spatial conservation prioritization plans and their implementation. We analyzed the research-implementation gap of one zoning case by comparing results of a spatial prioritization analysis aimed at avoiding ecological impact of peat mining in a regional zoning process with the final zoning plan. We examined the relatively complex planning process to determine the gaps among research, zoning, and decision making. We quantified the ecological costs of the differing trade-offs between ecological and socioeconomic factors included in the different zoning suggestions by comparing the landscape-level loss of ecological features (species occurrences, habitat area, etc.) between the different solutions for spatial allocation of peat mining. We also discussed with the scientists and planners the reasons for differing zoning suggestions. The implemented plan differed from the scientists suggestion in that its focus was individual ecological features rather than all the ecological features for which there were data; planners and decision makers considered effects of peat mining on areas not included in the prioritization analysis; zoning was not truly seen as a resource-allocation process and not emphasized in general minimizing ecological losses while satisfying economic needs (peat-mining potential); and decision makers based their prioritization of sites on site-level information showing high ecological value and on single legislative factors instead of finding a cost-effective landscape-level solution. We believe that if the zoning and decision-making processes are very complex, then the usefulness of science-based prioritization tools is likely to be reduced. Nevertheless, we found that high-end tools were useful in clearly exposing trade-offs between conservation and resource utilization. © 2017 Society for Conservation Biology.

Three-dimensional hydrogeological modeling to assess the elevated-water-table technique for controlling acid generation from an abandoned tailings site in Quebec, Canada

NASA Astrophysics Data System (ADS)

Ethier, Marie-Pier; Bussière, Bruno; Broda, Stefan; Aubertin, Michel

2018-01-01

The Manitou Mine sulphidic-tailings storage facility No. 2, near Val D'Or, Canada, was reclaimed in 2009 by elevating the water table and applying a monolayer cover made of tailings from nearby Goldex Mine. Previous studies showed that production of acid mine drainage can be controlled by lowering the oxygen flux through Manitou tailings with a water table maintained at the interface between the cover and reactive tailings. Simulations of different scenarios were performed using numerical hydrogeological modeling to evaluate the capacity of the reclamation works to maintain the phreatic surface at this interface. A large-scale numerical model was constructed and calibrated using 3 years of field measurements. This model reproduced the field measurements, including the existence of a western zone on the site where the phreatic level targeted is not always met during the summer. A sensitivity analysis was performed to assess the response of the model to varying saturated hydraulic conductivities, porosities, and grain-size distributions. Higher variations of the hydraulic heads, with respect to the calibrated scenario results, were observed when simulating a looser or coarser cover material. Long-term responses were simulated using: the normal climatic data, data for a normal climate with a 2-month dry spell, and a simplified climate-change case. Environmental quality targets were reached less frequently during summer for the dry spell simulation as well as for the simplified climate-change scenario. This study illustrates how numerical simulations can be used as a key tool to assess the eventual performance of various mine-site reclamation scenarios.

Multi-target screening mines hesperidin as a multi-potent inhibitor: Implication in Alzheimer's disease therapeutics.

PubMed

Chakraborty, Sandipan; Bandyopadhyay, Jaya; Chakraborty, Sourav; Basu, Soumalee

2016-10-04

Alzheimer's disease (AD) is the most frequent form of neurodegenerative disorder in elderly people. Involvement of several pathogenic events and their interconnections make this disease a complex disorder. Therefore, designing compounds that can inhibit multiple toxic pathways is the most attractive therapeutic strategy in complex disorders like AD. Here, we have designed a multi-tier screening protocol combining ensemble docking to mine BACE1 inhibitor, as well as 2-D QSAR models for anti-amyloidogenic and antioxidant activities. An in house developed phytochemical library of 200 phytochemicals has been screened through this multi-target procedure which mine hesperidin, a flavanone glycoside commonly found in citrus food items, as a multi-potent phytochemical in AD therapeutics. Steady-state and time-resolved fluorescence spectroscopy reveal that binding of hesperidin to the active site of BACE1 induces a conformational transition of the protein from open to closed form. Hesperidin docks close to the catalytic aspartate residues and orients itself in a way that blocks the cavity opening thereby precluding substrate binding. Hesperidin is a high affinity BACE1 inhibitor and only 500 nM of the compound shows complete inhibition of the enzyme activity. Furthermore, ANS and Thioflavin-T binding assay show that hesperidin completely inhibits the amyloid fibril formation which is further supported by atomic force microscopy. Hesperidin exhibits moderate ABTS(+) radical scavenging assay but strong hydroxyl radical scavenging ability, as evident from DNA nicking assay. Present study demonstrates the applicability of a novel multi-target screening procedure to mine multi-potent agents from natural origin for AD therapeutics. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Three-dimensional hydrogeological modeling to assess the elevated-water-table technique for controlling acid generation from an abandoned tailings site in Quebec, Canada

NASA Astrophysics Data System (ADS)

Ethier, Marie-Pier; Bussière, Bruno; Broda, Stefan; Aubertin, Michel

2018-06-01

The Manitou Mine sulphidic-tailings storage facility No. 2, near Val D'Or, Canada, was reclaimed in 2009 by elevating the water table and applying a monolayer cover made of tailings from nearby Goldex Mine. Previous studies showed that production of acid mine drainage can be controlled by lowering the oxygen flux through Manitou tailings with a water table maintained at the interface between the cover and reactive tailings. Simulations of different scenarios were performed using numerical hydrogeological modeling to evaluate the capacity of the reclamation works to maintain the phreatic surface at this interface. A large-scale numerical model was constructed and calibrated using 3 years of field measurements. This model reproduced the field measurements, including the existence of a western zone on the site where the phreatic level targeted is not always met during the summer. A sensitivity analysis was performed to assess the response of the model to varying saturated hydraulic conductivities, porosities, and grain-size distributions. Higher variations of the hydraulic heads, with respect to the calibrated scenario results, were observed when simulating a looser or coarser cover material. Long-term responses were simulated using: the normal climatic data, data for a normal climate with a 2-month dry spell, and a simplified climate-change case. Environmental quality targets were reached less frequently during summer for the dry spell simulation as well as for the simplified climate-change scenario. This study illustrates how numerical simulations can be used as a key tool to assess the eventual performance of various mine-site reclamation scenarios.

[Characterization of severe acute occupational poisoning accidents related to asphyxiating gases in China between 1989 and 2003].

PubMed

Zhang, Min; Li, Tao; Wang, Huan-Qiang; Wang, Hong-Fei; Chen, Shu-Yang; Du, Xie-Yi; Qin, Jian; Zhang, Shuang; Ji, Li-Ying

2006-12-01

To analyze severe acute occupational poisoning accidents related to asphyxiating gases reported in China between 1989 and 2003, and to study the characteristics of severe acute occupational poisoning accidents and provide scientific evidences for prevention and control strategies. The data from the national occupational poisoning case reporting system were analyzed with descriptive methods. (1) There were 273 severe acute occupational poisoning accidents related to asphyxiating gases for 15 years with 1638 workers poisoned and 600 workers died, which accounted for 53.95% in total accidents and 35.17% of workers poisoned and 78.64% of workers died of all severe acute occupational poisoning accidents. The average poisoning age was (33.8 +/- 9.7) years old and the average death age was (36.6 +/- 10.0) years old. (2) Most of the accidents were caused by hydrogen sulfide, carbon monoxide and carbon dioxide respectively, and mainly occurred in chemical industry, mining, water disposal industry, paper making industry and brewing industry. The risk was higher in some jobs than others, such as cleanout, machine maintenance and repair, production, mine and digging. The poisoning accidents occurred more frequently from April to September each year and occurred in the confined space, in the basement and the mine, and workers died of poisoning mostly were men. (1) The severe acute occupational poisoning accidents related to asphyxiating gases are more dangerous than others. (2) The control of poisoning accidents related to hydrogen sulfide, carbon monoxide and carbon dioxide, which occurred easily in the confined space, should be paid more attention to, and good work practice should be developed on some posts, such as digging, cleanout, dredge, machine maintenance and repair and mine.

Organic petrology of Paleocene Marcelina Formation coals, Paso Diablo mine, western Venezuela: Tectonic controls on coal type

USGS Publications Warehouse

Hackley, P.C.; Martinez, M.

2007-01-01

About 7??Mt of high volatile bituminous coal are produced annually from the four coal zones of the Upper Paleocene Marcelina Formation at the Paso Diablo open-pit mine of western Venezuela. As part of an ongoing coal quality study, we have characterized twenty-two coal channel samples from the mine using organic petrology techniques. Samples also were analyzed for proximate-ultimate parameters, forms of sulfur, free swelling index, ash fusion temperatures, and calorific value. Six of the samples represent incremental benches across the 12-13??m thick No. 4 bed, the stratigraphically lowest mined coal, which is also mined at the 10??km distant Mina Norte open-pit. Organic content of the No. 4 bed indicates an upward increase of woody vegetation and/or greater preservation of organic material throughout the life of the original mire(s). An upward increase in telovitrinite and corresponding decrease in detrovitrinite and inertinite illustrate this trend. In contrast, stratigraphically higher coal groups generally exhibit a 'dulling upward' trend. The generally high inertinite content, and low ash yield and sulfur content, suggest that the Paso Diablo coals were deposited in rain-fed raised mires, protected from clastic input and subjected to frequent oxidation and/or moisture stress. However, the two thinnest coal beds (both 0.7??m thick) are each characterized by lower inertinite and higher telovitrinite content relative to the rest of Paso Diablo coal beds, indicative of less well-established raised mire environments prior to drowning. Foreland basin Paleocene coals of western Venezuela, including the Paso Diablo deposit and time-correlative coal deposits of the Ta??chira and Me??rida Andes, are characterized by high inertinite and consistently lower ash and sulfur relative to Eocene and younger coals of the area. We interpret these age-delimited coal quality characteristics to be due to water availability as a function of the tectonic control of subsidence rate. It is postulated that slower subsidence rates dominated during the Paleocene while greater foreland basin subsidence rates during the Eocene-Miocene resulted from the loading of nappe thrust sheets as part of the main construction phases of the Andean orogen. South-southeastward advance and emplacement of the Lara nappes during the oblique transpressive collision of the Caribbean and South American tectonic plates in the Paleocene was further removed from the sites of peat deposition, resulting in slower subsidence rates. Slower subsidence in the Paleocene may have favored the growth of raised mires, generating higher inertinite concentrations through more frequent moisture stress. Consistently low ash yield and sulfur content would be due to the protection from clastic input in raised mires, in addition to the leaching of mineral matter by rainfall and the development of acidic conditions preventing fixation of sulfur. In contrast, peat mires of Eocene-Miocene age encountered rapid subsidence due to the proximity of nappe emplacement, resulting in lower inertinite content, higher and more variable sulfur content, and higher ash yield.

Data mining of space heating system performance in affordable housing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ren, Xiaoxin; Yan, Da; Hong, Tianzhen

The space heating in residential buildings accounts for a considerable amount of the primary energy use. Therefore, understanding the operation and performance of space heating systems becomes crucial in improving occupant comfort while reducing energy use. This study investigated the behavior of occupants adjusting their thermostat settings and heating system operations in a 62-unit affordable housing complex in Revere, Massachusetts, USA. The data mining methods, including clustering approach and decision trees, were used to ascertain occupant behavior patterns. Data tabulating ON/OFF space heating states was assessed, to provide a better understanding of the intermittent operation of space heating systems inmore » terms of system cycling frequency and the duration of each operation. The decision tree was used to verify the link between room temperature settings, house and heating system characteristics and the heating energy use. The results suggest that the majority of apartments show fairly constant room temperature profiles with limited variations during a day or between weekday and weekend. Data clustering results revealed six typical patterns of room temperature profiles during the heating season. Space heating systems cycled more frequently than anticipated due to a tight range of room thermostat settings and potentially oversized heating capacities. In conclusion, from this study affirm data mining techniques are an effective method to analyze large datasets and extract hidden patterns to inform design and improve operations.« less

Data mining of space heating system performance in affordable housing

DOE PAGES

Ren, Xiaoxin; Yan, Da; Hong, Tianzhen

2015-02-16

The space heating in residential buildings accounts for a considerable amount of the primary energy use. Therefore, understanding the operation and performance of space heating systems becomes crucial in improving occupant comfort while reducing energy use. This study investigated the behavior of occupants adjusting their thermostat settings and heating system operations in a 62-unit affordable housing complex in Revere, Massachusetts, USA. The data mining methods, including clustering approach and decision trees, were used to ascertain occupant behavior patterns. Data tabulating ON/OFF space heating states was assessed, to provide a better understanding of the intermittent operation of space heating systems inmore » terms of system cycling frequency and the duration of each operation. The decision tree was used to verify the link between room temperature settings, house and heating system characteristics and the heating energy use. The results suggest that the majority of apartments show fairly constant room temperature profiles with limited variations during a day or between weekday and weekend. Data clustering results revealed six typical patterns of room temperature profiles during the heating season. Space heating systems cycled more frequently than anticipated due to a tight range of room thermostat settings and potentially oversized heating capacities. In conclusion, from this study affirm data mining techniques are an effective method to analyze large datasets and extract hidden patterns to inform design and improve operations.« less

Combining QSAR Modeling and Text-Mining Techniques to Link Chemical Structures and Carcinogenic Modes of Action.

PubMed

Papamokos, George; Silins, Ilona

2016-01-01

There is an increasing need for new reliable non-animal based methods to predict and test toxicity of chemicals. Quantitative structure-activity relationship (QSAR), a computer-based method linking chemical structures with biological activities, is used in predictive toxicology. In this study, we tested the approach to combine QSAR data with literature profiles of carcinogenic modes of action automatically generated by a text-mining tool. The aim was to generate data patterns to identify associations between chemical structures and biological mechanisms related to carcinogenesis. Using these two methods, individually and combined, we evaluated 96 rat carcinogens of the hematopoietic system, liver, lung, and skin. We found that skin and lung rat carcinogens were mainly mutagenic, while the group of carcinogens affecting the hematopoietic system and the liver also included a large proportion of non-mutagens. The automatic literature analysis showed that mutagenicity was a frequently reported endpoint in the literature of these carcinogens, however, less common endpoints such as immunosuppression and hormonal receptor-mediated effects were also found in connection with some of the carcinogens, results of potential importance for certain target organs. The combined approach, using QSAR and text-mining techniques, could be useful for identifying more detailed information on biological mechanisms and the relation with chemical structures. The method can be particularly useful in increasing the understanding of structure and activity relationships for non-mutagens.

Removal of arsenic from synthetic acid mine drainage by electrochemical pH adjustment and coprecipitation with iron hydroxide.

PubMed

Wang, Jenny Weijun; Bejan, Dorin; Bunce, Nigel J

2003-10-01

Acid mine drainage (AMD), which is caused by the biological oxidation of sulfidic materials, frequently contains arsenic in the form of arsenite, As(III), and/or arsenate, As(V), along with much higher concentrations of dissolved iron. The present work is directed toward the removal of arsenic from synthetic AMD by raising the pH of the solution by electrochemical reduction of H+ to elemental hydrogen and coprecipitation of arsenic with iron(III) hydroxide, following aeration of the catholyte. Electrolysis was carried out at constant current using two-compartment cells separated with a cation exchange membrane. Four different AMD model systems were studied: Fe(III)/As(V), Fe(III)/As(III), Fe(II)/As(V), and Fe(II)/As(III) with the initial concentrations for Fe(III) 260 mg/L, Fe(II) 300 mg/L, As(V), and As(III) 8 mg/L. Essentially quantitative removal of arsenic and iron was achieved in all four systems, and the results were independent of whether the pH was adjusted electrochemically or by the addition of NaOH. Current efficiencies were approximately 85% when the pH of the effluent was 4-7. Residual concentrations of arsenic were close to the drinking water standard proposed by the World Health Organization (10 microg/L), far below the mine waste effluent standard (500 microg/L).

Combining QSAR Modeling and Text-Mining Techniques to Link Chemical Structures and Carcinogenic Modes of Action

PubMed Central

Papamokos, George; Silins, Ilona

2016-01-01

There is an increasing need for new reliable non-animal based methods to predict and test toxicity of chemicals. Quantitative structure-activity relationship (QSAR), a computer-based method linking chemical structures with biological activities, is used in predictive toxicology. In this study, we tested the approach to combine QSAR data with literature profiles of carcinogenic modes of action automatically generated by a text-mining tool. The aim was to generate data patterns to identify associations between chemical structures and biological mechanisms related to carcinogenesis. Using these two methods, individually and combined, we evaluated 96 rat carcinogens of the hematopoietic system, liver, lung, and skin. We found that skin and lung rat carcinogens were mainly mutagenic, while the group of carcinogens affecting the hematopoietic system and the liver also included a large proportion of non-mutagens. The automatic literature analysis showed that mutagenicity was a frequently reported endpoint in the literature of these carcinogens, however, less common endpoints such as immunosuppression and hormonal receptor-mediated effects were also found in connection with some of the carcinogens, results of potential importance for certain target organs. The combined approach, using QSAR and text-mining techniques, could be useful for identifying more detailed information on biological mechanisms and the relation with chemical structures. The method can be particularly useful in increasing the understanding of structure and activity relationships for non-mutagens. PMID:27625608

Mining co-occurrence and sequence patterns from cancer diagnoses in New York State.

PubMed

Wang, Yu; Hou, Wei; Wang, Fusheng

2018-01-01

The goal of this study is to discover disease co-occurrence and sequence patterns from large scale cancer diagnosis histories in New York State. In particular, we want to identify disparities among different patient groups. Our study will provide essential knowledge for clinical researchers to further investigate comorbidities and disease progression for improving the management of multiple diseases. We used inpatient discharge and outpatient visit records from the New York State Statewide Planning and Research Cooperative System (SPARCS) from 2011-2015. We grouped each patient's visit history to generate diagnosis sequences for seven most popular cancer types. We performed frequent disease co-occurrence mining using the Apriori algorithm, and frequent disease sequence patterns discovery using the cSPADE algorithm. Different types of cancer demonstrated distinct patterns. Disparities of both disease co-occurrence and sequence patterns were observed from patients within different age groups. There were also considerable disparities in disease co-occurrence patterns with respect to different claim types (i.e., inpatient, outpatient, emergency department and ambulatory surgery). Disparities regarding genders were mostly found where the cancer types were gender specific. Supports of most patterns were usually higher for males than for females. Compared with secondary diagnosis codes, primary diagnosis codes can convey more stable results. Two disease sequences consisting of the same diagnoses but in different orders were usually with different supports. Our results suggest that the methods adopted can generate potentially interesting and clinically meaningful disease co-occurrence and sequence patterns, and identify disparities among various patient groups. These patterns could imply comorbidities and disease progressions.

[Mining analysis on composition and medication of menstruation prescriptions in Fu Qingzhu's Obstetrics and Gynecology].

PubMed

Zhu, Jia-qing; Che, Yu-xia

2015-04-01

In this paper, menstruation prescriptions were selected from "Fu Qingzhu's Obstetrics and Gynecology" and analyzed by using GRI algorithm, correlation analysis, hierarchical clustering method through SPSS, Clementine and traditional Chinese medicine (TCM) inheritance auxiliary systems, in order to screen out 15 menopathy prescriptions, which involve 45 traditional Chinese medicine herbs. In the study, blood-tonifying and qi-tonifying herbs were found to be frequent in the prescriptions. The most frequent single herb was white paeony root, accounting for 9.6% in the total number of prescriptions; The most frequent herb pairs were white paeony root-radix rehmanniae preparata and paeony root-angelica sinensis. Among Fu Shan's menopathy prescriptions, 61 herbal pairs showed a correlation coefficient exceeding 0.05, which evolved into 16 pairs of core combinations. The analysis showed that menopathy prescriptions in volume 1 of "Fu Qingzhu's Obstetrics and Gynecology" focused on tonic traditional Chinese medicines involving liver, spleen and kidney and were adjusted according to changes in qi, blood, cold, hot and wet, which could provide a specific reference for further studies on Fu Shan's academic thoughts and traditional Chinese medicine clinical treatment of menopathy.

Constrained clusters of gene expression profiles with pathological features.

PubMed

Sese, Jun; Kurokawa, Yukinori; Monden, Morito; Kato, Kikuya; Morishita, Shinichi

2004-11-22

Gene expression profiles should be useful in distinguishing variations in disease, since they reflect accurately the status of cells. The primary clustering of gene expression reveals the genotypes that are responsible for the proximity of members within each cluster, while further clustering elucidates the pathological features of the individual members of each cluster. However, since the first clustering process and the second classification step, in which the features are associated with clusters, are performed independently, the initial set of clusters may omit genes that are associated with pathologically meaningful features. Therefore, it is important to devise a way of identifying gene expression clusters that are associated with pathological features. We present the novel technique of 'itemset constrained clustering' (IC-Clustering), which computes the optimal cluster that maximizes the interclass variance of gene expression between groups, which are divided according to the restriction that only divisions that can be expressed using common features are allowed. This constraint automatically labels each cluster with a set of pathological features which characterize that cluster. When applied to liver cancer datasets, IC-Clustering revealed informative gene expression clusters, which could be annotated with various pathological features, such as 'tumor' and 'man', or 'except tumor' and 'normal liver function'. In contrast, the k-means method overlooked these clusters.

Visualizing frequent patterns in large multivariate time series

NASA Astrophysics Data System (ADS)

Hao, M.; Marwah, M.; Janetzko, H.; Sharma, R.; Keim, D. A.; Dayal, U.; Patnaik, D.; Ramakrishnan, N.

2011-01-01

The detection of previously unknown, frequently occurring patterns in time series, often called motifs, has been recognized as an important task. However, it is difficult to discover and visualize these motifs as their numbers increase, especially in large multivariate time series. To find frequent motifs, we use several temporal data mining and event encoding techniques to cluster and convert a multivariate time series to a sequence of events. Then we quantify the efficiency of the discovered motifs by linking them with a performance metric. To visualize frequent patterns in a large time series with potentially hundreds of nested motifs on a single display, we introduce three novel visual analytics methods: (1) motif layout, using colored rectangles for visualizing the occurrences and hierarchical relationships of motifs in a multivariate time series, (2) motif distortion, for enlarging or shrinking motifs as appropriate for easy analysis and (3) motif merging, to combine a number of identical adjacent motif instances without cluttering the display. Analysts can interactively optimize the degree of distortion and merging to get the best possible view. A specific motif (e.g., the most efficient or least efficient motif) can be quickly detected from a large time series for further investigation. We have applied these methods to two real-world data sets: data center cooling and oil well production. The results provide important new insights into the recurring patterns.

CDR3 analysis of TCR Vβ repertoire of CD8⁺ T cells from chickens infected with Eimeria maxima.

PubMed

Ren, Chao; Yin, Guangwen; Qin, Mei; Suo, Jingxia; Lv, Qiyao; Xie, Li; Wang, Yunzhou; Huang, Xiaoxi; Chen, Yuchen; Liu, Xianyong; Suo, Xun

2014-08-01

CD8(+) T cells play a major role in the immune protection of host against the reinfection of Eimeria maxima, the most immunogenic species of eimerian parasites in chickens. To explore the dominant complementarity-determining regions 3 (CDR3) of CD8(+) T cell populations induced by the infection of this parasite, sequence analysis was performed in this study for CDR3 of CD8(+) T cells from E. maxima infected chickens. After 5 days post the third or forth infection, intraepithelial lymphocytes were isolated from the jejunum of bird. CD3(+)CD8(+) T cells were sorted and subjected to total RNA isolation and cDNA preparation. PCR amplification and cloning of the loci between Vβ1 and Cβ was conducted for the subsequent sequencing of CDR3 of T cell receptor (TCR). After the forth infection, 2 birds exhibited two same frequent TCR CDR3 sequences, i.e., AKQDWGTGGYSNMI and AGRVLNIQY; while the third bird showed two different frequent TCR CDR3 sequences, AKQGARGHTPLN and AKQDIEVRGPNTPLN. No frequent CDR3 sequence was detected from uninfected birds, though AGRVLNIQY was also found in two uninfected birds. Our result preliminarily demonstrates that frequent CDR3 sequences may exist in E. maxima immunized chickens, encouraging the mining of the immunodominant CD8(+) T cells against E. maxima infection. Copyright © 2014 Elsevier Inc. All rights reserved.

Data from deployment of temporary seismic stations in northern Norway and Finland

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maercklin, N; Mykkeltveit, S; Schweitzer, J

2005-02-11

This short contribution is a description of data now available in NORSAR's data archives from a temporary deployment during 2002-2004 of six seismic stations in northern Norway and Finland. Explosions in underground as well as open-pit mines in the Khibiny massif of the Kola Peninsula of northwestern Russia are conducted on a frequent and relatively regular basis. It was decided to supplement the network of permanent stations in northern Fennoscandia and northwest Russia with temporarily deployed stations, in order to record these explosions, as well as other mining explosions and natural events occurring in this general area. As shown inmore » Fig. 6.4.1, the six temporary stations were deployed along two profile lines, extending westwards from the Khibini massif. The rationale for this deployment was to collect data to examine distance as well as azimuthal dependence of seismic discriminants. As can be seen from Fig. 6.4.1 the southernmost of the two profile lines runs through the permanent seismic array ARCES in northern Norway.« less

Techniques of Acceleration for Association Rule Induction with Pseudo Artificial Life Algorithm

NASA Astrophysics Data System (ADS)

Kanakubo, Masaaki; Hagiwara, Masafumi

Frequent patterns mining is one of the important problems in data mining. Generally, the number of potential rules grows rapidly as the size of database increases. It is therefore hard for a user to extract the association rules. To avoid such a difficulty, we propose a new method for association rule induction with pseudo artificial life approach. The proposed method is to decide whether there exists an item set which contains N or more items in two transactions. If it exists, a series of item sets which are contained in the part of transactions will be recorded. The iteration of this step contributes to the extraction of association rules. It is not necessary to calculate the huge number of candidate rules. In the evaluation test, we compared the extracted association rules using our method with the rules using other algorithms like Apriori algorithm. As a result of the evaluation using huge retail market basket data, our method is approximately 10 and 20 times faster than the Apriori algorithm and many its variants.

Mining Twitter to Assess the Public Perception of the “Internet of Things”

PubMed Central

Yoshigoe, Kenji; Hicks, Amanda; Yuan, Jiawei; He, Zhe; Xie, Mengjun; Guo, Yi; Prosperi, Mattia; Salloum, Ramzi; Modave, François

2016-01-01

Social media analysis has shown tremendous potential to understand public's opinion on a wide variety of topics. In this paper, we have mined Twitter to understand the public's perception of the Internet of Things (IoT). We first generated the discussion trends of the IoT from multiple Twitter data sources and validated these trends with Google Trends. We then performed sentiment analysis to gain insights of the public’s attitude towards the IoT. As anticipated, our analysis indicates that the public's perception of the IoT is predominantly positive. Further, through topic modeling, we learned that public tweets discussing the IoT were often focused on business and technology. However, the public has great concerns about privacy and security issues toward the IoT based on the frequent appearance of related terms. Nevertheless, no unexpected perceptions were identified through our analysis. Our analysis was challenged by the limited fraction of tweets relevant to our study. Also, the user demographics of Twitter users may not be strongly representative of the population of the general public. PMID:27391760

Mining Twitter to Assess the Public Perception of the "Internet of Things".

PubMed

Bian, Jiang; Yoshigoe, Kenji; Hicks, Amanda; Yuan, Jiawei; He, Zhe; Xie, Mengjun; Guo, Yi; Prosperi, Mattia; Salloum, Ramzi; Modave, François

2016-01-01

Social media analysis has shown tremendous potential to understand public's opinion on a wide variety of topics. In this paper, we have mined Twitter to understand the public's perception of the Internet of Things (IoT). We first generated the discussion trends of the IoT from multiple Twitter data sources and validated these trends with Google Trends. We then performed sentiment analysis to gain insights of the public's attitude towards the IoT. As anticipated, our analysis indicates that the public's perception of the IoT is predominantly positive. Further, through topic modeling, we learned that public tweets discussing the IoT were often focused on business and technology. However, the public has great concerns about privacy and security issues toward the IoT based on the frequent appearance of related terms. Nevertheless, no unexpected perceptions were identified through our analysis. Our analysis was challenged by the limited fraction of tweets relevant to our study. Also, the user demographics of Twitter users may not be strongly representative of the population of the general public.

The psychosocial effects of living in an isolated community. A community health study.

PubMed

Michalowsky, A M; Wicht, C L; Möller, A T

1989-06-03

Doctors working in isolated mining towns frequently remark on the number of psychosocial problems they encounter, particularly among women. A test was designed to study psychosocial well-being in three such towns. The results were compared with those from a diamond-mining town 30 km from a large city. There were 1,239 respondents. The results showed that, according to Goldberg's General Health Questionnaire, the number of people 'clinically disturbed' varied from 14.1% to 23.8%. On the Carroll Rating Scale for Depression, the number of depressed respondents varied from 21.9% to 37.6%. Of the respondents, 23.2 - 31.2% drank alcohol at least once a day, a much higher percentage than that found in the general population. Women suffered more than men from psychosocial illness. Isolation as a risk factor could not be proved, since all 4 towns were affected. Causal factors could be the personality type of the people drawn to such towns or the transient nature of life there or the effect of the towns being company owned.

Unique Approach to Hydraulic Characterization at an Underground Lab

NASA Astrophysics Data System (ADS)

Jones, T. L.; Wang, J. S.

2009-12-01

The Sanford Underground Laboratory is the interim lab for the future federally funded DUSEL (Deep Underground Science and Engineering Lab). The Sanford Lab took over the abandoned Homestake mine in Lead, SD. Over three hundred miles of drift, extending 8,000 feet below the surface, are now being used to house experiments in disciplines including physics, geology, and biology. The lab is situated in Precambrian metamorphic rocks intersected by Tertiary dike swarms. Three relevant geologic units are defined within the Precambrian rock system; all of which are interpreted to be metamorphosed igneous and sedimentary deposits. The Sanford Lab provides a unique environment to study several aspects of hydrogeology and hydrology; including geochemistry, hydraulic systems in fractured aquifers, and fluvial activity within mine workings. Aquifer characteristics housing the mine workings’ is important to define for future and present research at the underground lab. Outlined here is a unique approach to defining the matrix porosity within the fractured aquifer system. The Homestake mine was abandoned and the pump system keeping the mine dry was turned off in 2003. Over the course of the next five years the water level rose 3470 feet. Oxidation of iron from the water left a red staining on the submerged rocks. Hydrological observations are conducted on different levels throughout the Homestake facility as the water levels are lowered. Isolated air pockets and long stretches of unstained areas along the roof of drifts have been observed, together with less frequent occurrences of seepages. These observations are documented to supplement hydrological monitoring and testing with sensors. The sizes and widths of the trapped air pockets are indications of low permeability values and can be used to estimate the degree of heterogeneity along drifts. It is noted that sections of long stretches of trapped air have more delayed drainages, consistent with low effective permeability values for the metamorphic rocks. The air pockets reveal a distinctive difference in size between the geologic units; the average size of the air pockets associated with different geologic units differs by an order of magnitude. The infrequent seepage observations are also consistent with the hydrological setting of this facility with low inflow rates.

Bioremediation of contaminated mixtures of desert mining soil and sawdust with fuel oil by aerated in-vessel composting in the Atacama Region (Chile).

PubMed

Godoy-Faúndez, Alex; Antizar-Ladislao, Blanca; Reyes-Bozo, Lorenzo; Camaño, Andrés; Sáez-Navarrete, César

2008-03-01

Since early 1900s, with the beginning of mining operations and especially in the last decade, small, although repetitive spills of fuel oil had occurred frequently in the Chilean mining desert industry during reparation and maintenance of machinery, as well as casual accidents. Normally, soils and sawdust had been used as cheap readily available sorbent materials of spills of fuel oil, consisting of complex mixtures of aliphatic and aromatic hydrocarbons. Chilean legislation considers these fuel oil contaminated mixtures of soil and sawdust as hazardous wastes, and thus they must be contained. It remains unknown whether it would be feasible to clean-up Chilean desert soils with high salinity and metal content, historically polluted with different commercial fuel oil, and contained during years. Thus, this study evaluated the feasibility of aerated in-vessel composting at a laboratory scale as a bioremediation technology to clean-up contaminated desert mining soils (fuel concentration>50,000 mg kg(-1)) and sawdust (fuel concentration>225,000 mg kg(-1)) in the Atacama Region. The composting reactors were operated using five soil to sawdust ratios (S:SD, 1:0, 3:1, 1:1, 1:3, 0:1, on a dry weight basis) under mesophilic temperatures (30-40 degrees C), constant moisture content (MC, 50%) and continuous aeration (16 l min(-1)) during 56 days. Fuel oil concentration and physico-chemical changes in the composting reactors were monitored following standard procedures. The highest (59%) and the lowest (35%) contaminant removals were observed in the contaminated sawdust and contaminated soil reactors after 56 days of treatment, respectively. The S:SD ratio, time of treatment and interaction between both factors had a significant effect (p<0.050) on the contaminant removal. The results of this research indicate that bioremediation of an aged contaminated mixture of desert mining soil and sawdust with fuel oil is feasible. This study recommends a S:SD ratio 1:3 and a correct nutrient balance in order to achieve a maximum overall hydrocarbon removal of fuel oil in the weathered and aged contaminated wastes.

Application of granular ferric hydroxides for removal elevated concentrations of arsenic from mine waters

NASA Astrophysics Data System (ADS)

Szlachta, Małgorzata; Włodarczyk, Paweł; Wójtowicz, Patryk

2015-04-01

Arsenic is naturally occurring element in the environment. Over three hundred minerals are known to contain some form of arsenic and among them arsenopyrite is the most common one. Arsenic-bearing minerals are frequently associated with ores containing mined metals such as copper, tin, nickel, lead, uranium, zinc, cobalt, platinum and gold. In the aquatic environment arsenic is typically present in inorganic forms, mainly in two oxidation states (+5, +3). As(III) is dominant in more reduced conditions, whereas As(V) is mostly present in an oxidizing environment. However, due to certain human activities the elevated arsenic levels in aquatic ecosystems are arising to a serious environmental problem. High arsenic concentrations found in surface and groundwaters, in some regions originate from mining activities and ore processing. Therefore, the major concern of mining industry is to maintain a good quality of effluents discharged in large volumes. This requires constant monitoring of effluents quality that guarantee the efficient protection of the receiving waters and reacting to possible negative impact of contamination on local communities. A number of proven technologies are available for arsenic removal from waters and wastewaters. In the presented work special attention is given to the adsorption method as a technically feasible, commonly applied and effective technique for the treatment of arsenic rich mine effluents. It is know that arsenic has a strong affinity towards iron rich materials. Thus, in this study the granular ferric hydroxides (CFH 12, provided by Kemira Oyj, Finland) was applied to remove As(III) and As(V) from aqueous solutions. The batch adsorption experiments were carried out to assess the efficiency of the tested Fe-based material under various operating parameters, including composition of treated water, solution pH and temperature. The results obtained from the fixed bed adsorption tests demonstrated the benefits of applying granular ferric hydroxides for treatment As-contaminated waters. This research is a part of the study supported by the National Centre for Research and Development grant (2014-2017) "Sustainable and responsible supply of primary resources - SUSMIN" (http://projects.gtk.fi/susmin), within the EU ERA-NET ERA-MIN program.

Site-specific climate analysis elucidates revegetation challenges for post-mining landscapes in eastern Australia

NASA Astrophysics Data System (ADS)

Audet, P.; Arnold, S.; Lechner, A. M.; Baumgartl, T.

2013-10-01

In eastern Australia, the availability of water is critical for the successful rehabilitation of post-mining landscapes and climatic characteristics of this diverse geographical region are closely defined by factors such as erratic rainfall and periods of drought and flooding. Despite this, specific metrics of climate patterning are seldom incorporated into the initial design of current post-mining land rehabilitation strategies. Our study proposes that a few common rainfall parameters can be combined and rated using arbitrary rainfall thresholds to characterise bioregional climate sensitivity relevant to the rehabilitation these landscapes. This approach included assessments of annual rainfall depth, average recurrence interval of prolonged low intensity rainfall, average recurrence intervals of short or prolonged high intensity events, median period without rain (or water-deficit) and standard deviation for this period in order to address climatic factors such as total water availability, seasonality and intensity - which were selected as potential proxies of both short- and long-term biological sensitivity to climate within the context of post-disturbance ecological development and recovery. Following our survey of available climate data, we derived site "climate sensitivity" indexes and compared the performance of 9 ongoing mine sites: Weipa, Mt. Isa and Cloncurry, Eromanga, Kidston, the Bowen Basin (Curragh), Tarong, North Stradbroke Island, and the Newnes Plateau. The sites were then ranked from most-to-least sensitive and compared with natural bioregional patterns of vegetation density using mean NDVI. It was determined that regular rainfall and relatively short periods of water-deficit were key characteristics of sites having less sensitivity to climate - as found among the relatively more temperate inland mining locations. Whereas, high rainfall variability, frequently occurring high intensity events, and (or) prolonged seasonal drought were primary indicators of sites having greater sensitivity to climate - as found among the semi-arid central-inland sites. Overall, the manner in which these climatic factors are identified and ultimately addressed by land managers and rehabilitation practitioners could be a key determinant of achievable success at given locations at the planning stages of rehabilitation design.

The Interaction Network Ontology-supported modeling and mining of complex interactions represented with multiple keywords in biomedical literature.

PubMed

Özgür, Arzucan; Hur, Junguk; He, Yongqun

2016-01-01

The Interaction Network Ontology (INO) logically represents biological interactions, pathways, and networks. INO has been demonstrated to be valuable in providing a set of structured ontological terms and associated keywords to support literature mining of gene-gene interactions from biomedical literature. However, previous work using INO focused on single keyword matching, while many interactions are represented with two or more interaction keywords used in combination. This paper reports our extension of INO to include combinatory patterns of two or more literature mining keywords co-existing in one sentence to represent specific INO interaction classes. Such keyword combinations and related INO interaction type information could be automatically obtained via SPARQL queries, formatted in Excel format, and used in an INO-supported SciMiner, an in-house literature mining program. We studied the gene interaction sentences from the commonly used benchmark Learning Logic in Language (LLL) dataset and one internally generated vaccine-related dataset to identify and analyze interaction types containing multiple keywords. Patterns obtained from the dependency parse trees of the sentences were used to identify the interaction keywords that are related to each other and collectively represent an interaction type. The INO ontology currently has 575 terms including 202 terms under the interaction branch. The relations between the INO interaction types and associated keywords are represented using the INO annotation relations: 'has literature mining keywords' and 'has keyword dependency pattern'. The keyword dependency patterns were generated via running the Stanford Parser to obtain dependency relation types. Out of the 107 interactions in the LLL dataset represented with two-keyword interaction types, 86 were identified by using the direct dependency relations. The LLL dataset contained 34 gene regulation interaction types, each of which associated with multiple keywords. A hierarchical display of these 34 interaction types and their ancestor terms in INO resulted in the identification of specific gene-gene interaction patterns from the LLL dataset. The phenomenon of having multi-keyword interaction types was also frequently observed in the vaccine dataset. By modeling and representing multiple textual keywords for interaction types, the extended INO enabled the identification of complex biological gene-gene interactions represented with multiple keywords.

A Segment-Based Trajectory Similarity Measure in the Urban Transportation Systems.

PubMed

Mao, Yingchi; Zhong, Haishi; Xiao, Xianjian; Li, Xiaofang

2017-03-06

With the rapid spread of built-in GPS handheld smart devices, the trajectory data from GPS sensors has grown explosively. Trajectory data has spatio-temporal characteristics and rich information. Using trajectory data processing techniques can mine the patterns of human activities and the moving patterns of vehicles in the intelligent transportation systems. A trajectory similarity measure is one of the most important issues in trajectory data mining (clustering, classification, frequent pattern mining, etc.). Unfortunately, the main similarity measure algorithms with the trajectory data have been found to be inaccurate, highly sensitive of sampling methods, and have low robustness for the noise data. To solve the above problems, three distances and their corresponding computation methods are proposed in this paper. The point-segment distance can decrease the sensitivity of the point sampling methods. The prediction distance optimizes the temporal distance with the features of trajectory data. The segment-segment distance introduces the trajectory shape factor into the similarity measurement to improve the accuracy. The three kinds of distance are integrated with the traditional dynamic time warping algorithm (DTW) algorithm to propose a new segment-based dynamic time warping algorithm (SDTW). The experimental results show that the SDTW algorithm can exhibit about 57%, 86%, and 31% better accuracy than the longest common subsequence algorithm (LCSS), and edit distance on real sequence algorithm (EDR) , and DTW, respectively, and that the sensitivity to the noise data is lower than that those algorithms.

Dietary human exposure to mercury in two artisanal small-scale gold mining communities of northwestern Colombia.

PubMed

Salazar-Camacho, Carlos; Salas-Moreno, Manuel; Marrugo-Madrid, Siday; Marrugo-Negrete, José; Díez, Sergi

2017-10-01

Artisanal and small-scale gold mining (ASGM) is the largest anthropogenic source of mercury pollution worldwide, posing a grave threat to human health. The present study identifies current levels of mercury in the human population from mining areas of the Chocó Department, Colombia, through total mercury (THg) and methylmercury (MeHg) measurements in human hair. Mercury exposure of the local population was assessed in two towns affected by ASGM and was related to different variables of interest. Concentrations of THg in human hair ranged from 0.06 to 17.54ppm and the mean value for the subjects under study was 2.48ppm. Men had significantly higher levels than women in both towns (3.29ppm vs. 0.77ppm). Fish consumption was related to a marked increase of THg in hair, with mean values close to five times higher in frequent fish consumers (5-7 times/week) than in non-fish consumers (4.80ppm vs. 0.90ppm). A multiple linear regression model was fitted successfully (R=0.671) and reveals that gender, fish consumption and location of residence were significant indicators of Hg levels in hair, while no significant relationship was found for age. Approximately 60% of subjects tested had THg levels that exceeded the U.S. Environmental Protection Agency reference dose of 1.0ppm, while 25% surpassed that of the World Health Organization (2.2ppm). Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of copper resistant bacteria from vineyard soils and mining waste for copper biosorption

PubMed Central

Andreazza, R.; Pieniz, S.; Okeke, B.C.; Camargo, F.A.O

2011-01-01

Vineyard soils are frequently polluted with high concentrations of copper due application of copper sulfate in order to control fungal diseases. Bioremediation is an efficient process for the treatment of contaminated sites. Efficient copper sorption bacteria can be used for bioremoval of copper from contaminated sites. In this study, a total of 106 copper resistant bacteria were examined for resistance to copper toxicity and biosorption of copper. Eighty isolates (45 from vineyard Mollisol, 35 from Inceptisol) were obtained from EMBRAPA (Empresa Brasileira de Pesquisa Agropecuária) experimental station, Bento Gonçalves, RS, Brazil (29°09′53.92″S and 51°31′39.40″W) and 26 were obtained from copper mining waste from Caçapava do Sul, RS, Brazil (30°29′43.48″S and 53′32′37.87W). Based on resistance to copper toxicity and biosorption, 15 isolates were identified by 16S rRNA gene sequencing. Maximal copper resistance and biosorption at high copper concentration were observed with isolate N2 which removed 80 mg L−1 in 24 h. Contrarily isolate N11 (Bacillus pumilus) displayed the highest specific copper biosorption (121.82 mg/L/OD unit in 24 h). GenBank MEGABLAST analysis revealed that isolate N2 is 99% similar to Staphylococcus pasteuri. Results indicate that several of our isolates have potential use for bioremediation treatment of vineyards soils and mining waste contaminated with high copper concentration. PMID:24031606

[Characteristics of acupoint selection of acupuncture-moxibustion for vertigo in history: a data mining research].

PubMed

Li, Xiang; Shou, Yi-Xia; Ren, Yu-Lan; Liang, Fan-Rong

2014-05-01

The data mining technique is adopted to analyze characteristics and rules of acupoint and meridian selection of acupuncture-moxibustion for treatment of vertigo at different time periods in the ancient. The data is collected from literature regarding acupuncture-moxibustion from the pre-Qin period to the end of Qing Dynasty, so as to establish a clinical literature database of ancient acupuncture-moxibustion for treatment of vertigo. Data mining method is applied to analyze the commonly used meridians, acupoints and special acupoints in different dynasties, also possible rules are explored. Totally 82 pieces of prescription of acupuncture-moxibustion for treatment of vertigo are included. In the history the leading selection of acupoitns are Fengchi (GB 20), Hegu (LI 4), Shangxing (GV 23) and Jiexi (ST 41) while that of meridians are mainly three yang meridians of foot and the Governor Vessel, especially the acupoints on the Bladder Meridian of foot yangming had the highest utilization rate, accounting for 23.04%. The acupoint selection is characterized by special acupoint, accounting for 80.6%, among which the crossing points are the most common choice. Distal-proximal acupoints combination is the most frequent method. The results indicate that the ancient acupuncture-moxibustion for treatment of vertigo focused on acupoints in the yang meridians, and the specific acupoints play an essential role in prescription; also the principle of syndrome differentiation and selecting acupoints along the meridians could be seen.

Analysis of Nature of Science Included in Recent Popular Writing Using Text Mining Techniques

NASA Astrophysics Data System (ADS)

Jiang, Feng; McComas, William F.

2014-09-01

This study examined the inclusion of nature of science (NOS) in popular science writing to determine whether it could serve supplementary resource for teaching NOS and to evaluate the accuracy of text mining and classification as a viable research tool in science education research. Four groups of documents published from 2001 to 2010 were analyzed: Scientific American, Discover magazine, winners of the Royal Society Winton Prize for Science Books, and books from NSTA's list of Outstanding Science Trade Books. Computer analysis categorized passages in the selected documents based on their inclusions of NOS. Human analysis assessed the frequency, context, coverage, and accuracy of the inclusions of NOS within computer identified NOS passages. NOS was rarely addressed in selected document sets but somewhat more frequently addressed in the letters section of the two magazines. This result suggests that readers seem interested in the discussion of NOS-related themes. In the popular science books analyzed, NOS presentations were found more likely to be aggregated in the beginning and the end of the book, rather than scattered throughout. The most commonly addressed NOS elements in the analyzed documents are science and society and empiricism in science. Only one inaccurate presentation of NOS were identified in all analyzed documents. The text mining technique demonstrated exciting performance, which invites more applications of the technique to analyze other aspects of science textbooks, popular science writing, or other materials involved in science teaching and learning.

Low Cost Remediation of Mining Sites with Biosolids

NASA Astrophysics Data System (ADS)

Daniels, Walter; Evanylo, Gregory; Stuczynski, Tomasz

2010-05-01

This paper will present collective results of 25 years of research by the authors into the use of municipal biosolids (sewage sludge) and other residuals to reclaim sites disturbed by a range of mining and construction activities. Loading rate experiments and demonstrations have been conducted on areas drastically disturbed by coal mining, sand mining, heavy mineral mining, urbanization, airport construction and heavy metal processing. At all sites, the post-mining soils were devoid of organic matter, very low in nutrients and frequently quite acidic. At all sites, addition of biosolids at higher than agronomic rates resulted in complete stabilization of the resultant mine soils and vigorous stable vegetation that persisted for > 5 years and has allowed enhanced invasion of native herbaceous species. Application of higher rates is not compatible with establishment of certain native tree species (e.g. Pinus sp.), however, due to adverse effects of soluble salts, nutrient enrichment and enhanced competition by grasses. An underlying goal of this program has been to develop approaches that use higher than agronomic rates of biosolids while simultaneously minimizing losses of N and P to local ground- and surface-waters. In the early 1980's, working on USA coal mining spoils, we determined that that approximately 100 Mg/ha of secondary cake biosolids was optimal for revegetation with herbaceous species, but water quality monitoring was not a concern at that time. This finding raised concerns, however, that the large amounts of total N applied (> 2500 kg/ha) would lead to nitrate-N contamination of local waters. Subsequent work in the early 1990's indicated that similar rates of biosolids could be mixed with woodchips (high palatable C source) and land-applied to large (> 100 ha) coal mining sites with no losses of nitrate-N to surface or ground-water due to microbial immobilization of the applied N. Follow-up work at three sand mining (sand & gravel and mineral sands) sites in eastern Virginia indicated that non C-amended biosolids could be applied at loading rates of up to 75 Mg/ha without significant local ground-water effects, but that significant elevation of nitrate-N in shallow root-zone (75 cm) percolates was observed the first winter after application. Addition of palatable C (as sawdust) to adjust the applied biosolids C:N ratio to 25:1 significantly reduced nitrate-N in root-zone percolates and would allow for higher loading rates where indicated. Lime-stabilized biosolids (100 Mg/ha; 15 to 25% CCE) have also been used to permanently stabilize and revegetate large areas (> 100 ha) acid-sulfate (pH < 3.5) soils disturbed by construction in eastern Virginia with minimal local water quality effects. Parallel studies at our sites in the USA have indicated no significant heavy metal leaching or plant uptake risks as long as sludge quality and soil pH are controlled. Finally, long-term (10 yr) results from Katowice, Poland, indicate that high rates (> 250 Mg/ha) of biosolids co-applied with waste limes can be utilized to permanently stabilize and revegetate a wide range of phytotoxic and heavily contaminated Pb/Zn smelter slags and processing tailings. Biosolids are generally available at very low cost for land rehabilitation since their cost of transport and application is usually born by the producer or source municipality. Their use is particularly cost-effective when lime-stabilized materials are applied to strongly acidic or metalliferous sites.

Application of Long Expansion Rock Bolt Support in the Underground Mines of Legnica-Głogów Copper District

NASA Astrophysics Data System (ADS)

Skrzypkowski, Krzysztof; Korzeniowski, Waldemar; Zagórski, Krzysztof; Dudek, Piotr

2017-09-01

In the underground mines of the Legnica-Głogów Copper District (LGOM) the main way to protect the room excavation is the use of a rock bolt support. For many years, it has proven to be an efficient security measure in excavations which met all safety standards and requirements. The article presents the consumption of the rock bolt support in the Mining Department "Polkowice-Sieroszowice" in the years 2010-2015 as well as the number of bolt supports that were used to secure the excavations. In addition, it shows the percentage of bolt supports that were used to conduct rebuilding work and cover the surface of exposed roofs. One of the factors contributing to the loss of the functionality of bolt supports is corrosion whose occurrence may lead directly to a reduction in the diameter of rock bolt support parts, in particular rods, bearing plates and nuts. The phenomenon of the corrosion of the bolt support and its elements in underground mining is an extremely common phenomenon due to the favorable conditions for its development in mines, namely high temperature and humidity, as well as the presence of highly aggressive water. This involves primarily a decrease in the capacity of bolt support construction, which entails the need for its strengthening, and often the need to perform the reconstruction of the excavation. The article presents an alternative for steel bearing plates, namely plates made using the spatial 3D printing technology. Prototype bearing plates were printed on a 3D printer Formiga P100 using the "Precymit" material. The used printing technology was SLS (Selective Laser Sintering), which is one of the most widely used technologies among all the methods of 3D printing for the short series production of the technical parts of the final product. The article presents the stress-strain characteristic of the long expansion connected rock bolt support OB25 with a length of 3.65 m. A rock bolt support longer than 2.6 m is an additional bolt support in excavations, and it is increasingly frequently used to reinforce roofs and in rebuilding the underground mines of KGHM Polish Copper S.A. In order to conduct the laboratory tests that are most suitable for the mine conditions, and yet are carried out on a laboratory test facility, the Authors used a steel cylinder with an external diameter of 102 mm and a length of 600 mm, which was filled with a core of rock (dolomite) from the roofs of the mine workings. In addition the maximum load that took over the bolt support made of rods and connected with sleeves was determined. For the initial tension, the elastic and plastic range of the maximal displacements, which were measured by the rope encoder, were determined. The statical tests of the expansion rock bolt support were carried out at the laboratory of the Department of Underground Mining in simulated mine conditions. The test facility enables the study of the long bolt rods on a geometric scale of 1:1 for the different ways of fixing. The aim of the laboratory research was to obtain the stress-strain characteristics, of the long expansion rock bolt support with a steel bearing plate and a plate printed on a 3D printer.

Soil propagule banks of ectomycorrhizal fungi along forest development stages after mining.

PubMed

Huang, Jian; Nara, Kazuhide; Zong, Kun; Lian, Chunlan

2015-05-01

Ectomycorrhizal fungal (EMF) propagules play an important role in seedling establishment following disturbance. However, little is known about how the EMF propagule community changes with forest development. In this study, EMF propagules were examined using seedling bioassays in rhizosphere soils collected from a recently closed Pb-Zn tailing (Taolin Pb-Zn tailing (TLT)), a Cu tailing (Dexing Cu No. 2 tailing (DXT)) that had undergone 21 years of restoration, and a mature Masson pine (Pinus massoniana) forest (DXC) outside the Cu mining areas. The corresponding EMF communities colonizing Masson pine at each site were also investigated for comparison. After 8 months of running bioassays, ectomycorrhizal colonization was poor for seedlings grown in TLT (9.0 % ± 14.9 %) and DXT soils (22.4 % ± 17.7 %), while DXC seedlings were well colonized (47.5 % ± 24.9 %). Internal transcribed spacer sequencing revealed that EMF species richness increased with forest development in both the propagule bank (TLT, 6; DXT, 7; DXC, 12) and in the field (TLT, 8; DXT, 14; DXC, 26), though richness was lower in propagule banks. Several lineages, such as Cenococcum, Rhizopogon, Inocybe, Suillus, and Atheliaceae, were frequently encountered in propagule communities, but species assemblages were different among the three sites. Canonical correspondence analysis revealed that several soil parameters, i.e., N, EC, Cu, Pb, Zn, etc., were responsible for the distribution of EMF in the field and bioassay seedlings. The highest overlap in EMF species composition between the propagule bank and the field community was observed at the recently closed tailing (Morisita-Horn similarity = 0.71 for TLT), whereas the lowest overlap occurred at the mature forest (0.26 for DXC). These results indicate that EMF propagules in soil are less frequent and diverse in early primary succession and become more frequent and diverse along forest development, due mainly to the accumulation of dormant spores of Rhizopogon spp. and sclerotia of Cenococcum spp. Thus, EMF propagule communities in soil may diverge from those root-colonizing EMF communities along a gradient of forest development.

FIFS: A data mining method for informative marker selection in high dimensional population genomic data.

PubMed

Kavakiotis, Ioannis; Samaras, Patroklos; Triantafyllidis, Alexandros; Vlahavas, Ioannis

2017-11-01

Single Nucleotide Polymorphism (SNPs) are, nowadays, becoming the marker of choice for biological analyses involving a wide range of applications with great medical, biological, economic and environmental interest. Classification tasks i.e. the assignment of individuals to groups of origin based on their (multi-locus) genotypes, are performed in many fields such as forensic investigations, discrimination between wild and/or farmed populations and others. Τhese tasks, should be performed with a small number of loci, for computational as well as biological reasons. Thus, feature selection should precede classification tasks, especially for Single Nucleotide Polymorphism (SNP) datasets, where the number of features can amount to hundreds of thousands or millions. In this paper, we present a novel data mining approach, called FIFS - Frequent Item Feature Selection, based on the use of frequent items for selection of the most informative markers from population genomic data. It is a modular method, consisting of two main components. The first one identifies the most frequent and unique genotypes for each sampled population. The second one selects the most appropriate among them, in order to create the informative SNP subsets to be returned. The proposed method (FIFS) was tested on a real dataset, which comprised of a comprehensive coverage of pig breed types present in Britain. This dataset consisted of 446 individuals divided in 14 sub-populations, genotyped at 59,436 SNPs. Our method outperforms the state-of-the-art and baseline methods in every case. More specifically, our method surpassed the assignment accuracy threshold of 95% needing only half the number of SNPs selected by other methods (FIFS: 28 SNPs, Delta: 70 SNPs Pairwise FST: 70 SNPs, In: 100 SNPs.) CONCLUSION: Our approach successfully deals with the problem of informative marker selection in high dimensional genomic datasets. It offers better results compared to existing approaches and can aid biologists in selecting the most informative markers with maximum discrimination power for optimization of cost-effective panels with applications related to e.g. species identification, wildlife management, and forensics. Copyright © 2017 Elsevier Ltd. All rights reserved.

A framework for periodic outlier pattern detection in time-series sequences.

PubMed

Rasheed, Faraz; Alhajj, Reda

2014-05-01

Periodic pattern detection in time-ordered sequences is an important data mining task, which discovers in the time series all patterns that exhibit temporal regularities. Periodic pattern mining has a large number of applications in real life; it helps understanding the regular trend of the data along time, and enables the forecast and prediction of future events. An interesting related and vital problem that has not received enough attention is to discover outlier periodic patterns in a time series. Outlier patterns are defined as those which are different from the rest of the patterns; outliers are not noise. While noise does not belong to the data and it is mostly eliminated by preprocessing, outliers are actual instances in the data but have exceptional characteristics compared with the majority of the other instances. Outliers are unusual patterns that rarely occur, and, thus, have lesser support (frequency of appearance) in the data. Outlier patterns may hint toward discrepancy in the data such as fraudulent transactions, network intrusion, change in customer behavior, recession in the economy, epidemic and disease biomarkers, severe weather conditions like tornados, etc. We argue that detecting the periodicity of outlier patterns might be more important in many sequences than the periodicity of regular, more frequent patterns. In this paper, we present a robust and time efficient suffix tree-based algorithm capable of detecting the periodicity of outlier patterns in a time series by giving more significance to less frequent yet periodic patterns. Several experiments have been conducted using both real and synthetic data; all aspects of the proposed approach are compared with the existing algorithm InfoMiner; the reported results demonstrate the effectiveness and applicability of the proposed approach.

Expanding the Scope of an Automated Radiology Recommendation-Tracking Engine: Initial Experiences and Lessons Learned.

PubMed

Licurse, Mindy Y; Lalevic, Darco; Zafar, Hanna M; Schnall, Mitchell D; Cook, Tessa S

2017-04-01

An automated radiology recommendation-tracking engine for incidental focal masses in the liver, pancreas, kidneys, and adrenal glands was launched within our institution in July 2013. For 2 years, the majority of CT, MR, and US examination reports generated within our health system were mined by the engine. However, the need to expand the system beyond the initial four organs was soon identified. In July 2015, the second phase of the system was implemented and expanded to include additional anatomic structures in the abdomen and pelvis, as well as to provide non-radiology and non-imaging options for follow-up. The most frequent organs with incidental findings, outside of the original four, included the ovaries and the endometrium, which also correlated to the most frequently ordered imaging follow-up study of pelvic ultrasound and non-imaging follow-up study of endometrial biopsies, respectively. The second phase expansion has demonstrated new venues for augmenting and improving radiologist roles in optimal communication and management of incidental findings.

Remote sensing supported surveillance and characterization of tailings behavior at a gold mine site, Finland.

NASA Astrophysics Data System (ADS)

Rauhala, Anssi; Tuomela, Anne; Rossi, Pekka M.; Davids, Corine

2017-04-01

The management of vast amounts of tailings produced is one of the key issues in mining operations. The effective and economic disposal of the waste requires knowledge concerning both basic physical properties of the tailings as well as more complex aspects such as consolidation behavior. The behavior of tailings in itself is a very complex issue that can be affected by flocculation, sedimentation, consolidation, segregation, deposition, freeze-thaw, and desiccation phenomena. The utilization of remote sensing in an impoundment-scale monitoring of tailings could benefit the management of tailings, and improve our knowledge on tailings behavior. In order to gain better knowledge of tailings behavior in cold climate, we have utilized both modern remote sensing techniques and more traditional in situ and laboratory measurements in characterizing thickened gold tailings behavior at a Finnish gold mine site, where the production has been halted due to low gold prices. The remote sensing measurements consisted of elevation datasets collected from unmanned aerial vehicles during summers 2015 and 2016, and a further campaign is planned for the summer 2017. The ongoing traditional measurements include for example particle-size distribution, frost heave, frost depth, water retention, temperature profile, and rheological measurements. Initial results from the remote sensing indicated larger than expected settlements on parts of the tailings impoundment, and also highlighted some of the complexities related to data processing. The interpretation of the results and characterization of the behavior is in this case complicated by possible freeze-thaw effects and potential settlement of the impoundment bottom structure consisting of natural peat. Experiments with remote sensing and unmanned aerial vehicles indicate that they could offer potential benefits in frequent mine site monitoring, but there is a need towards more robust and streamlined data acquisition and processing. The gathered data and obtained results form the basis for further modelling efforts which aim at better management of tailings storage facilities.

Lead (II) detection and contamination routes in environmental sources, cookware and home-prepared foods from Zimatlán, Oaxaca, Mexico.

PubMed

Villalobos, M; Merino-Sánchez, C; Hall, C; Grieshop, J; Gutiérrez-Ruiz, M E; Handley, M A

2009-04-01

An interdisciplinary investigation, involving environmental geochemists, epidemiologists, nurses, and anthropologists, was undertaken to determine the contamination source and pathway of an on-going outbreak of lead poisoning among migrants originating from Zimatlán, Oaxaca, Mexico and living in Seaside, California, and among their US-born children. An initial investigation in Seaside identified grasshopper foodstuff ("chapulines") imported from Mexico and consumed as snacks, as containing alarmingly high lead concentrations (up to 2300 mg/kg). The focus in the present work concentrates on the Oaxacan area of origin of the problem in Mexico, and two potential sources of contamination were investigated: wind-borne dusts from existing mine residues as potential contaminants of soil, plant, and fauna; and food preparation practices using lead-glazed ceramic cookware. Over a three year period, sampling was conducted in Oaxaca using community-level sampling and also targeted sampling with families of cases with lead poisoning in California. In addition to fresh field chapulines, we analyzed for total lead: soil, water, mine residues, and plant materials, both from areas adjacent to or at an abandoned waste site containing mine tailings, and from fields where chapulines are collected; foodstuffs gathered in community markets or in a food transport business; and foodstuffs and cookware gathered from relatives of case families in California. Also, selected new and used lead-glazed clay cookware was extracted for lead, using 0.02 M citric acid and with 4% acetic acid. The results indicated significant presence of lead in mine wastes, in specific foodstuffs, and in glazed cookware, but no extensive soil contamination was identified. In-situ experiments demonstrated that lead incorporation in food is made very efficient through grinding of spices in glazed cookware, with the combination of a harsh mechanical action and the frequent presence of acidic lime juice, but without heating, resulting in high but variable levels of contamination.

Ion-dipole interactions and their functions in proteins.

PubMed

Sippel, Katherine H; Quiocho, Florante A

2015-07-01

Ion-dipole interactions in biological macromolecules are formed between atomic or molecular ions and neutral protein dipolar groups through either hydrogen bond or coordination. Since their discovery 30 years ago, these interactions have proven to be a frequent occurrence in protein structures, appearing in everything from transporters and ion channels to enzyme active sites to protein-protein interfaces. However, their significance and roles in protein functions are largely underappreciated. We performed PDB data mining to identify a sampling of proteins that possess these interactions. In this review, we will define the ion-dipole interaction and discuss several prominent examples of their functional roles in nature. © 2015 The Protein Society.

Using Google Blogs and Discussions to Recommend Biomedical Resources: A Case Study

PubMed Central

Reed, Robyn B.; Chattopadhyay, Ansuman; Iwema, Carrie L.

2013-01-01

This case study investigated whether data gathered from discussions within the social media provide a reliable basis for a biomedical resources recommendation system. Using a search query to mine text from Google Blogs and Discussions, a ranking of biomedical resources was determined based on those most frequently mentioned. To establish quality, these results were compared to rankings by subject experts. An overall agreement between the frequency of social media discussions and subject expert recommendations was observed when identifying key bioinformatics and consumer health resources. Testing the method in more than one biomedical area implies this procedure could be employed across different subjects. PMID:24180648

Estimating procedure times for surgeries by determining location parameters for the lognormal model.

PubMed

Spangler, William E; Strum, David P; Vargas, Luis G; May, Jerrold H

2004-05-01

We present an empirical study of methods for estimating the location parameter of the lognormal distribution. Our results identify the best order statistic to use, and indicate that using the best order statistic instead of the median may lead to less frequent incorrect rejection of the lognormal model, more accurate critical value estimates, and higher goodness-of-fit. Using simulation data, we constructed and compared two models for identifying the best order statistic, one based on conventional nonlinear regression and the other using a data mining/machine learning technique. Better surgical procedure time estimates may lead to improved surgical operations.

ChloroSSRdb: a repository of perfect and imperfect chloroplastic simple sequence repeats (cpSSRs) of green plants

PubMed Central

Kapil, Aditi; Rai, Piyush Kant; Shanker, Asheesh

2014-01-01

Simple sequence repeats (SSRs) are regions in DNA sequence that contain repeating motifs of length 1–6 nucleotides. These repeats are ubiquitously present and are found in both coding and non-coding regions of genome. A total of 534 complete chloroplast genome sequences (as on 18 September 2014) of Viridiplantae are available at NCBI organelle genome resource. It provides opportunity to mine these genomes for the detection of SSRs and store them in the form of a database. In an attempt to properly manage and retrieve chloroplastic SSRs, we designed ChloroSSRdb which is a relational database developed using SQL server 2008 and accessed through ASP.NET. It provides information of all the three types (perfect, imperfect and compound) of SSRs. At present, ChloroSSRdb contains 124 430 mined SSRs, with majority lying in non-coding region. Out of these, PCR primers were designed for 118 249 SSRs. Tetranucleotide repeats (47 079) were found to be the most frequent repeat type, whereas hexanucleotide repeats (6414) being the least abundant. Additionally, in each species statistical analyses were performed to calculate relative frequency, correlation coefficient and chi-square statistics of perfect and imperfect SSRs. In accordance with the growing interest in SSR studies, ChloroSSRdb will prove to be a useful resource in developing genetic markers, phylogenetic analysis, genetic mapping, etc. Moreover, it will serve as a ready reference for mined SSRs in available chloroplast genomes of green plants. Database URL: www.compubio.in/chlorossrdb/ PMID:25380781

ChloroSSRdb: a repository of perfect and imperfect chloroplastic simple sequence repeats (cpSSRs) of green plants.

PubMed

Kapil, Aditi; Rai, Piyush Kant; Shanker, Asheesh

2014-01-01

Simple sequence repeats (SSRs) are regions in DNA sequence that contain repeating motifs of length 1-6 nucleotides. These repeats are ubiquitously present and are found in both coding and non-coding regions of genome. A total of 534 complete chloroplast genome sequences (as on 18 September 2014) of Viridiplantae are available at NCBI organelle genome resource. It provides opportunity to mine these genomes for the detection of SSRs and store them in the form of a database. In an attempt to properly manage and retrieve chloroplastic SSRs, we designed ChloroSSRdb which is a relational database developed using SQL server 2008 and accessed through ASP.NET. It provides information of all the three types (perfect, imperfect and compound) of SSRs. At present, ChloroSSRdb contains 124 430 mined SSRs, with majority lying in non-coding region. Out of these, PCR primers were designed for 118 249 SSRs. Tetranucleotide repeats (47 079) were found to be the most frequent repeat type, whereas hexanucleotide repeats (6414) being the least abundant. Additionally, in each species statistical analyses were performed to calculate relative frequency, correlation coefficient and chi-square statistics of perfect and imperfect SSRs. In accordance with the growing interest in SSR studies, ChloroSSRdb will prove to be a useful resource in developing genetic markers, phylogenetic analysis, genetic mapping, etc. Moreover, it will serve as a ready reference for mined SSRs in available chloroplast genomes of green plants. Database URL: www.compubio.in/chlorossrdb/ © The Author(s) 2014. Published by Oxford University Press.

Conflict translates environmental and social risk into business costs

PubMed Central

Franks, Daniel M.; Davis, Rachel; Bebbington, Anthony J.; Ali, Saleem H.; Kemp, Deanna; Scurrah, Martin

2014-01-01

Sustainability science has grown as a field of inquiry, but has said little about the role of large-scale private sector actors in socio-ecological systems change. However, the shaping of global trends and transitions depends greatly on the private sector and its development impact. Market-based and command-and-control policy instruments have, along with corporate citizenship, been the predominant means for bringing sustainable development priorities into private sector decision-making. This research identifies conflict as a further means through which environmental and social risks are translated into business costs and decision making. Through in-depth interviews with finance, legal, and sustainability professionals in the extractive industries, and empirical case analysis of 50 projects worldwide, this research reports on the financial value at stake when conflict erupts with local communities. Over the past decade, high commodity prices have fueled the expansion of mining and hydrocarbon extraction. These developments profoundly transform environments, communities, and economies, and frequently generate social conflict. Our analysis shows that mining and hydrocarbon companies fail to factor in the full scale of the costs of conflict. For example, as a result of conflict, a major, world-class mining project with capital expenditure of between US$3 and US$5 billion was reported to suffer roughly US$20 million per week of delayed production in net present value terms. Clear analysis of the costs of conflict provides sustainability professionals with a strengthened basis to influence corporate decision making, particularly when linked to corporate values. Perverse outcomes of overemphasizing a cost analysis are also discussed. PMID:24821758

Conflict translates environmental and social risk into business costs.

PubMed

Franks, Daniel M; Davis, Rachel; Bebbington, Anthony J; Ali, Saleem H; Kemp, Deanna; Scurrah, Martin

2014-05-27

Sustainability science has grown as a field of inquiry, but has said little about the role of large-scale private sector actors in socio-ecological systems change. However, the shaping of global trends and transitions depends greatly on the private sector and its development impact. Market-based and command-and-control policy instruments have, along with corporate citizenship, been the predominant means for bringing sustainable development priorities into private sector decision-making. This research identifies conflict as a further means through which environmental and social risks are translated into business costs and decision making. Through in-depth interviews with finance, legal, and sustainability professionals in the extractive industries, and empirical case analysis of 50 projects worldwide, this research reports on the financial value at stake when conflict erupts with local communities. Over the past decade, high commodity prices have fueled the expansion of mining and hydrocarbon extraction. These developments profoundly transform environments, communities, and economies, and frequently generate social conflict. Our analysis shows that mining and hydrocarbon companies fail to factor in the full scale of the costs of conflict. For example, as a result of conflict, a major, world-class mining project with capital expenditure of between US$3 and US$5 billion was reported to suffer roughly US$20 million per week of delayed production in net present value terms. Clear analysis of the costs of conflict provides sustainability professionals with a strengthened basis to influence corporate decision making, particularly when linked to corporate values. Perverse outcomes of overemphasizing a cost analysis are also discussed.

Epidemiological profile of suicide in the Santa Catarina Coal Mining Region from 1980 to 2007.

PubMed

Portella, Carolina H; Moretti, Gustavo P; Panatto, Ana P; Rosa, Maria I; Quevedo, João; Simões, Priscyla W T A

2013-01-01

Suicide is a public health problem worldwide. Estimates have indicated that over 1 million people commit suicide every year all over the world. Brazil has a moderate suicide death rate (4.1 per 100,000 inhabitants), but the fact that it is a large country leads to the coexistence of diverse characteristics and levels of development across the different Brazilian regions. In this sense, the South region has been shown to present suicide rates above the national average. To estimate the profile of suicide in municipalities comprising the Santa Catarina Coal Mining Region from 1980 to 2007. This ecological, time-series, descriptive study sought to characterize epidemiological aspects related to suicide method, marital status, sex, age, and occupation in the municipalities of the region in the years 1980 to 2007. A total of 474 suicides occurred in the period, yielding a mean death rate of 10.83 per 100,000 inhabitants. There was a predominance of males, at a 5:1 ratio, and a peak rate in the 55-64-year age group (11.31 per 100,000 inhabitants). The suicide method most commonly used was hanging (72%) and the most frequent occupation was hard labor work (11.60%); in relation to marital status, married subjects (48%) were the ones with the highest rates of suicide. The Santa Catarina Coal Mining Region has suicide mortality rates above the national average. This study highlights specific characteristics of suicide in the region and may contribute to the development of preventive measures.

Leptospirosis Seroprevalence among Blue Metal Mine Workers of Tamil Nadu, India

PubMed Central

Parveen, Sakkarai Mohamed Asha; Suganyaa, Baskar; Sathya, Muthu Sri; Margreat, Alphonse Asirvatham Princy; Sivasankari, Karikalacholan; Shanmughapriya, Santhanam; Hoffman, Nicholas E.; Natarajaseenivasan, Kalimuthusamy

2016-01-01

Leptospirosis is mainly considered an occupational disease, prevalent among agriculture, sewage works, forestry, and animal slaughtering populations. However, putative risk to miners and their inclusion in the high-risk leptospirosis group remain in need of rigorous analysis. Therefore, a study was conducted with the objective to assess the leptospirosis seroprevalence among miners of two districts of Tamil Nadu, India. A total of 244 sera samples from Pudukkottai miners (124) and Karur miners (120) were analyzed by microscopic agglutination test. Antibodies to leptospires were detected in 94 samples giving an overall seroprevalence of 38.5%. The seroprevalence was higher among Pudukkottai miners (65.3%) when compared with Karur miners (10.8%). Seroprevalence among control population (13%) was significantly less than that of the Pudukkottai miners marking a possible high-risk population group distinction. Subject sera most commonly reacted with organisms of the serogroup Autumnalis, and the pattern was similar in carrier animals of the study areas. Two leptospires were isolated from kidney samples of rats. The prevalence of Autumnalis among rodents and humans source tracked human leptospirosis among the miners. The study also determined that Pudukkottai miners are subjected to high-risk challenges such as exposure to water bodies on the way to the mines (odds ratio [OR] = 10.6), wet mine areas (OR = 10.6), rat infestation (OR = 4.6), and cattle rearing (OR = 10.4) and are thus frequently exposed to leptospirosis compared with Karur miners. Hence, control strategies targeting these populations will likely to prove to be effective remediation strategies benefiting Pudukkottai miners and workers in similar environments across occupations. PMID:27044567

Recent applications of multivariate data analysis methods in the authentication of rice and the most analyzed parameters: A review.

PubMed

Maione, Camila; Barbosa, Rommel Melgaço

2018-01-24

Rice is one of the most important staple foods around the world. Authentication of rice is one of the most addressed concerns in the present literature, which includes recognition of its geographical origin and variety, certification of organic rice and many other issues. Good results have been achieved by multivariate data analysis and data mining techniques when combined with specific parameters for ascertaining authenticity and many other useful characteristics of rice, such as quality, yield and others. This paper brings a review of the recent research projects on discrimination and authentication of rice using multivariate data analysis and data mining techniques. We found that data obtained from image processing, molecular and atomic spectroscopy, elemental fingerprinting, genetic markers, molecular content and others are promising sources of information regarding geographical origin, variety and other aspects of rice, being widely used combined with multivariate data analysis techniques. Principal component analysis and linear discriminant analysis are the preferred methods, but several other data classification techniques such as support vector machines, artificial neural networks and others are also frequently present in some studies and show high performance for discrimination of rice.

Trace metal accumulation and fish pathologies in areas affected by mining and metallurgical enterprises in the Kola Region, Russia.

PubMed

Moiseenko, T I; Kudryavtseva, L P

2001-01-01

Throughout the Kola region of Russia there has been a substantial increase of metal concentrations in water, which are related to local discharges from metallurgical and mining industry, transboundary transmissions as well as indirect leaching of elements by acid precipitation. This study presents data on the levels of Ni, Cu, Sr, Al, Zn, Co, Mn, Pb, Cd, Hg in the organs and tissues of fish, and evaluates relationships with water chemistry. Special attention is paid to fish pathologies, whose aetiology is related to the accumulation of metals and the associated changes of the elementary ratios within the organism. Ecotoxicological assessment of the copper nickel, strontium and acidification regimes also is considered in this article. In general we observed a large number of lakes that are heavily contaminated by Ni and Cu. Fish in these lakes contain high concentrations of Ni and Cu and display frequent pathologies, mostly associated with the kidneys. In lakes contaminated with Sr, there also are high Sr levels in fish and pathologies associated with skeletal tissues. Exposure to acidified water appears to increase the transport of metals (including Al, Ni and Cu) into fish and hence the toxic effects.

Data mining for blood glucose prediction and knowledge discovery in diabetic patients: the METABO diabetes modeling and management system.

PubMed

Georga, Eleni; Protopappas, Vasilios; Guillen, Alejandra; Fico, Giuseppe; Ardigo, Diego; Arredondo, Maria Teresa; Exarchos, Themis P; Polyzos, Demosthenes; Fotiadis, Dimitrios I

2009-01-01

METABO is a diabetes monitoring and management system which aims at recording and interpreting patient's context, as well as, at providing decision support to both the patient and the doctor. The METABO system consists of (a) a Patient's Mobile Device (PMD), (b) different types of unobtrusive biosensors, (c) a Central Subsystem (CS) located remotely at the hospital and (d) the Control Panel (CP) from which physicians can follow-up their patients and gain also access to the CS. METABO provides a multi-parametric monitoring system which facilitates the efficient and systematic recording of dietary, physical activity, medication and medical information (continuous and discontinuous glucose measurements). Based on all recorded contextual information, data mining schemes that run in the PMD are responsible to model patients' metabolism, predict hypo/hyper-glycaemic events, and provide the patient with short and long-term alerts. In addition, all past and recently-recorded data are analyzed to extract patterns of behavior, discover new knowledge and provide explanations to the physician through the CP. Advanced tools in the CP allow the physician to prescribe personalized treatment plans and frequently quantify patient's adherence to treatment.

Integrated Text Mining and Chemoinformatics Analysis Associates Diet to Health Benefit at Molecular Level

PubMed Central

Jensen, Kasper; Panagiotou, Gianni; Kouskoumvekaki, Irene

2014-01-01

Awareness that disease susceptibility is not only dependent on genetic make up, but can be affected by lifestyle decisions, has brought more attention to the role of diet. However, food is often treated as a black box, or the focus is limited to few, well-studied compounds, such as polyphenols, lipids and nutrients. In this work, we applied text mining and Naïve Bayes classification to assemble the knowledge space of food-phytochemical and food-disease associations, where we distinguish between disease prevention/amelioration and disease progression. We subsequently searched for frequently occurring phytochemical-disease pairs and we identified 20,654 phytochemicals from 16,102 plants associated to 1,592 human disease phenotypes. We selected colon cancer as a case study and analyzed our results in three directions; i) one stop legacy knowledge-shop for the effect of food on disease, ii) discovery of novel bioactive compounds with drug-like properties, and iii) discovery of novel health benefits from foods. This works represents a systematized approach to the association of food with health effect, and provides the phytochemical layer of information for nutritional systems biology research. PMID:24453957

Occurrence and transport of total mercury and methyl mercury in the Sacramento River Basin, California

USGS Publications Warehouse

Domagalski, Joseph L.

1999-01-01

Mercury poses a water-quality problem for California's Sacramento River, a large river with a mean annual discharge of over 650 m3/s. This river discharges into the San Francisco Bay, and numerous fish species of the bay and river contain mercury levels high enough to affect human health if consumed. Two possible sources of mercury are the mercury mines in the Coast Ranges and the gold mines in the Sierra Nevada. Mercury was once mined in the Coast Ranges, west of the Sacramento River, and used to process gold in the Sierra Nevada, east of the river. The mineralogy of the Coast Ranges mercury deposits is mainly cinnabar (HgS), but elemental mercury was used to process gold in the Sierra Nevada. Residual mercury from mineral processing in the Sierra Nevada is mainly in elemental form or in association with oxide particles or organic matter and is biologically available. Recent bed-sediment sampling, at sites below large reservoirs, showed elevated levels of total mercury (median concentration 0.28 ??g/g) in every large river (the Feather, Yuba, Bear, and American rivers) draining the Sierra Nevada gold region. Monthly sampling for mercury in unfiltered water shows relatively low concentrations during the nonrainy season in samples collected throughout the Sacramento River Basin, but significantly higher concentrations following storm-water runoff. Measured concentrations, following storm-water runoff, frequently exceeded the state of California standards for the protection of aquatic life. Results from the first year of a 2-year program of sampling for methyl mercury in unfiltered water showed similar median concentrations (0.1 ng/l) at all sampling locations, but with apparent high seasonal concentrations measured during autumn and winter. Methyl mercury concentrations were not significantly higher in rice field runoff water, even though rice production involves the creation of seasonal wetlands: higher rates of methylation are known to occur in stagnant wetland environments that have high dissolved carbon.Mercury poses a water-quality problem for California's Sacramento River, a large river with a mean annual discharge of over 650 m3/s. This river discharges into the San Francisco Bay, and numerous fish species of the bay and river contain mercury levels high enough to affect human health if consumed. Two possible sources of mercury are the mercury mines in the Coast Ranges and the gold mines in the Sierra Nevada. Mercury was once mined in the Coast Ranges, west of the Sacramento River, and used to process gold in the Sierra Nevada east of the river. The mineralogy of the Coast Ranges mercury deposits is mainly cinnabar (HgS), but elemental mercury was used to process gold in the Sierra Nevada. Residual mercury from mineral processing in the Sierra Nevada is mainly in elemental form or in association with oxide particles or organic matter and is biologically available. Recent bed-sediment sampling, at sites below large reservoirs, showed elevated levels of total mercury (median concentration 0.28 ??g/g) in every large river (the Feather, Yuba, Bear, and American rivers) draining the Sierra Nevada gold region. Monthly sampling for mercury in unfiltered water shows relatively low concentrations during the nonrainy season in samples collected throughout the Sacramento River Basin, but significantly higher concentrations following storm-water runoff. Measured concentrations, following storm-water runoff, frequently exceeded the state of California standards for the protection of aquatic life. Results from the first year of a 2-year program of sampling for methyl mercury in unfiltered water showed similar median concentrations (0.1 ng/l) at all sampling locations, but with apparent high seasonal concentrations measured during autumn and winter. Methyl mercury concentrations were not significantly higher in rice field runoff water, even though rice production involves the creation of seasonal wetlands: higher rates of methylation a

Illegal gold miners in French Guiana: a neglected population with poor health.

PubMed

Douine, Maylis; Mosnier, Emilie; Le Hingrat, Quentin; Charpentier, Charlotte; Corlin, Florine; Hureau, Louise; Adenis, Antoine; Lazrek, Yassamine; Niemetsky, Florence; Aucouturier, Anne-Laure; Demar, Magalie; Musset, Lise; Nacher, Mathieu

2017-07-17

In French Guiana, a French overseas territory in South America, 6 to 10 thousands undocumented persons work illegally in gold mining sites in the Amazonian forest. Precarious life conditions lead to poor health but few data exist on the health status of illegal gold miners in French Guiana. The objective of this article was to describe the sociodemographic and health status of this vulnerable population. A prospective cross-sectional survey was conducted in 2015 on gold mine supply sites at the border between French Guiana and Suriname. Health status was assessed through medical examination, past medical history, haemoglobin concentration, and HIV and malaria testing. A questionnaire was used to collect data about the migration itinerary and life conditions on mining sites. Among the 421 adults included in the study, 93.8% (395/421) were Brazilian, mainly from Maranhão (55.7%, 220/395), the poorest Brazilian state. The sex ratio was 2.4. Overall, 48% of persons never went to school or beyond the primary level. The median time spent in gold mining was quite long (10 years), with a high turn-over. One third of the surveyed population (37.1%, 156/421) had high blood pressure, and only two had a medical follow-up. Most persons had experienced malaria (89.3%, 376/421). They declared frequent arboviroses and digestive disorders. Active leishmaniasis was observed in 8.3% of gold miners. Among women, 28.5% were anemic. Concerning HIV, 36.6% (154/421) of persons, mainly men, never got tested before and 6 were tested positive, which represented an HIV prevalence of 1.43% (95%CI =0.29-2.5). These findings support the hypothesis that mining in remote areas is linked to several specific illnesses. Theoretically, gold miners would be presumed to start their economical migration to French Guiana as a healthy group. However, their strenuous working and living conditions there lead to poor health caused by infectious and non infectious diseases. This description of their health status is precious for health policy planners in French Guiana given the importance of controlling communicable disease, and the severity and range of specific illnesses acquired by this neglected population. Clinical trial registration PRS N° NCT02903706 . Retrospectively registered 09/13/2016.

A history of mining activity in Celtic Aeduan territory, and its environmental impact (Morvan, France)

NASA Astrophysics Data System (ADS)

Monna, F.; Petit, C.; Guillaumet, J.-P.; Jouffroy, I.; Blanchot, C.; Dominik, J.; Losno, R.; Richard, H.; Lévêque, J.

2003-04-01

Described by Caesar in "de Bello Gallico" in 58 BC as one of the greatest and richest oppida of Gaul, Bibracte was the capital of the vast Aeduan territory. It was strategically located at the top of Mount Beuvray, which is also one of the highest points of the granitic Morvan. Geomorphological anomalies, such as wide trenches and gullies, have recently been discovered and interpreted as mining excavations. On this basis, some archaeologists have assumed that early settlers were attracted by the abundance of mineral resources. However, this assumption is not yet an established fact, because of the lack of clear field evidence. Proof of early local mining exploitation may have been destroyed, buried or masked when the city of Bibracte was built. As a consequence, we searched for indirect evidence, such as any impact of these metallurgical activities on the surrounding environment. Elemental and lead isotopic compositions were therefore measured in a 2m peat core sampled around Mount Beuvray (Glux, Port-des-Lamberts) recording the last four millennia of atmospheric deposition. Pollen analysis was also performed to verify the impact of local mining on nearby vegetation, if any. Pb isotopic and concentration profiles show anthropogenic inputs starting from ca 1300 BC, and intensifying during Aeduan occupation (ca 200 BC - 20 BC). After a long phase of recession, inputs start again during the 11th century, and finally increase exponentially from the Industrial Revolution to present times. Compared to Zn, Cu and Sb, which do not present clear trends, the integrity of the lead signal is demonstrated by frequent and spectacular changes in the isotopic feature of the anthropogenic component, so that the isotopic profile cannot be explained by post-deposition migration processes. The origin of the pollution is local. Each phase of activity comes with a drastic fall of fagus taxa, interpreted as a selective deforestation consequent to the increase in energy demands. Atmospheric long range transportation from Rio Tinto, often invoked as the major lead source during Antiquity, is obliterated here by local emissions. These findings tend to confirm the archaeological hypothesis concerning the attractive role of mineral resources. For the first time, evidence of mining and/or smelting activities from the Bronze Age onwards has been established on this site.

Capturing pre-failure signs of slope instability using multi-temporal interferometry and Sentinel-1 data

NASA Astrophysics Data System (ADS)

Wasowski, Janusz; Bovenga, Fabio; Nitti, Davide Oscar; Tijani, Khalid; Morea, Alberto; Nutricato, Raffaele; Chiaradia, Maria Teresa

2017-04-01

The shorter repeat cycle (6 days since October 2016) and regularity of acquisitions of Sentinel-1A/B with respect to earlier European Space Agency (ESA) satellites with C-band sensors (ERS1/2, ENVISAT) represent the key advantages for the research-oriented and practical applications of multi-temporal interferometry (MTI). The applicability of the Interferometric Wide Swath acquisition mode of Sentinel-1 (images covering a 250 km swath on the ground) to regional scale slope instability detection through MTI has already been demonstrated, e.g., via studies of landslide-prone areas in Italy. Here we focus on the potential of Sentinel-1 data for local (site-specific), MTI-based monitoring and capturing pre-failure signs of slope instability, by exploiting the Persistent and Distributed Scatterers processing capability of the SPINUA algorithm. In particular, we present an example of a retrospective study of a large (over 2 km long) landslide, which took place in 2016 in an active open-cast coal mine in central Europe. This seemingly sudden failure caused destruction of the mining equipment, blocked the mining operations thereby resulting in significant economic losses. For the study, we exploited over 60 Sentinel-1A/B images acquired since November 2014. The MTI results furnished a valuable overview of the ground instability/stability conditions within and around the active mine, even though considerable spatial gaps in information were encountered due to surface disturbance by mining operations. Significantly, the ground surface displacement time series revealed that the 2016 slope failure was preceded by very slow (generally 1-3 cm/yr) creep-like deformations, already present in 2014. The MTI results also indicated that the slope experienced a phase of accelerated movement several weeks prior to the landslide event. Furthermore, the spatio-temporal analysis of interferometric coherence changes in the unstable area (mapped on Sentinel-2 Bottom Of Atmosphere reflectance images processed by using the ESA Sen2Cor processor), indicated a sharp coherence loss in the last few weeks before the slope collapse. The availability of more frequent measurements represents a key improvement for MTI-based ground surface displacement monitoring and this will better support research on slope destabilization processes over time and, ultimately, on slope failure forecasting. Acknowledgments We thank ESA for Sentinel-1 & Sentinel-2 images.

The Necessity of Public Relations for Sustainable Mining Activities

NASA Astrophysics Data System (ADS)

Lee, Hyunbock; Ji, Sangwoo

2015-04-01

This paper reports research about the necessity of image making for sustainable mine developments in the Republic of Korea. One of the big risks in mining activities is mining area residents opposing mine developments and operations. Analysis of the media reports on disputes between mining companies and residents can determine causes of opposing mine developments, dispute process, and influences of disputes on processes of mining projects. To do this, civil complaints from 2009 to 2012 and 24 media reports since 2000 on opposing mining activities are analyzed. And, to analyze difficulties of mining companies, the survey is conducted to target to mining companies. 57 representatives of mining companies are participated in the survey. The result of analysis cited that the major reasons of anti-mining activities are environmental degradation and reduced agricultural productivity. And specifically because of water pollution (50%), crop damages (33%), and mining dust pollution (21%), communities of mining area are against mine developments and operations. However, 25% of residents have experience of the damage caused by mining activities and the remaining 75% of residents opposing mining activities simply have anxiety about mining pollution. In the past, construction-oriented, environment-unfriendly mining projects had lasted. And while mine reclamation had been postponed in abandoned mines, mining area residents had suffered from mining pollution. So, mining area residents are highly influenced by the prejudice that mining activities are harmful to mining area communities. Current mining projects in South Korea, unlike the past mining activity, focus on minimizing environmental damage and contributing to mining area communities financially. But, in many case of disputes between mining companies and mining area residents, the both cannot reach an agreements because of the negative prejudice. Moreover, some communities categorically refuse any mining activity. On the other hand, in the survey to determine what the greatest difficulties of the current mining activities, 54% of mining companies chose environmental regulations, 26% of mining companies chose conflicts between mine area residents and mining companies. Environmental regulations are may defined as the greatest difficulty of current mining activities. But most of environmental regulation's problems are caused by frictions with residents, because all of South Korean mines are very close to villages. So, the biggest difficulty of mining activities can be defined conflicts between residents and mining companies. Moreover, general people in South Korea including some mining engineers recognize the mining industry as a declined and pollution industry. Without clear understanding of mining activities, any mine developments and policies related to mining activities cannot be made by rational discussions. And, if their recognition is not formed in a rational way, it will be turned to extreme fear or blind hatred. Therefore, to understand mining activities correctly, the effective public relations strategy is necessary such as corporate advertisements or public advertisements.

Measuring radon concentrations and estimating dose in tourist caves.

PubMed

Martín Sánchez, A; de la Torre Pérez, J; Ruano Sánchez, A B; Naranjo Correa, F L

2015-11-01

Caves and mines are considered to be places of especial risk of exposure to (222)Rn. This is particularly important for guides and workers, but also for visitors. In the Extremadura region (Spain), there are two cave systems in which there are workers carrying out their normal everyday tasks. In one, visits have been reduced to maintain the conditions of temperature and humidity. The other comprises several caves frequently visited by school groups. The caves were radiologically characterised in order to estimate the dose received by workers or possible hazards for visitors. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Security and Correctness Analysis on Privacy-Preserving k-Means Clustering Schemes

NASA Astrophysics Data System (ADS)

Su, Chunhua; Bao, Feng; Zhou, Jianying; Takagi, Tsuyoshi; Sakurai, Kouichi

Due to the fast development of Internet and the related IT technologies, it becomes more and more easier to access a large amount of data. k-means clustering is a powerful and frequently used technique in data mining. Many research papers about privacy-preserving k-means clustering were published. In this paper, we analyze the existing privacy-preserving k-means clustering schemes based on the cryptographic techniques. We show those schemes will cause the privacy breach and cannot output the correct results due to the faults in the protocol construction. Furthermore, we analyze our proposal as an option to improve such problems but with intermediate information breach during the computation.

Algorithm to Identify Frequent Coupled Modules from Two-Layered Network Series: Application to Study Transcription and Splicing Coupling

PubMed Central

Li, Wenyuan; Dai, Chao; Liu, Chun-Chi

2012-01-01

Abstract Current network analysis methods all focus on one or multiple networks of the same type. However, cells are organized by multi-layer networks (e.g., transcriptional regulatory networks, splicing regulatory networks, protein-protein interaction networks), which interact and influence each other. Elucidating the coupling mechanisms among those different types of networks is essential in understanding the functions and mechanisms of cellular activities. In this article, we developed the first computational method for pattern mining across many two-layered graphs, with the two layers representing different types yet coupled biological networks. We formulated the problem of identifying frequent coupled clusters between the two layers of networks into a tensor-based computation problem, and proposed an efficient solution to solve the problem. We applied the method to 38 two-layered co-transcription and co-splicing networks, derived from 38 RNA-seq datasets. With the identified atlas of coupled transcription-splicing modules, we explored to what extent, for which cellular functions, and by what mechanisms transcription-splicing coupling takes place. PMID:22697243

A prospective cohort study among new Chinese coal miners: the early pattern of lung function change.

PubMed

Wang, M-L; Wu, Z-E; Du, Q-G; Petsonk, E L; Peng, K-L; Li, Y-D; Li, S-K; Han, G-H; Atffield, M D

2005-11-01

To investigate the early pattern of longitudinal change in forced expiratory volume in 1 second (FEV1) among new Chinese coal miners, and the relation between coal mine dust exposure and the decline of lung function. The early pattern of lung function changes in 317 newly hired Chinese underground coal miners was compared to 132 referents. This three year prospective cohort study involved a pre-employment and 15 follow up health surveys, including a questionnaire and spirometry tests. Twice a month, total and respirable dust area sampling was done. The authors used a two stage analysis and a linear mixed effects model approach to analyse the longitudinal spirometry data, and to investigate the changes in FEV1 over time, controlling for age, height, pack years of smoking, mean respirable dust concentration, the room temperature during testing, and the groupxtime interaction terms. FEV1 change over time in new miners is non-linear. New miners experience initial rapid FEV1 declines, primarily during the first year of mining, little change during the second year, and partial recovery during the third year. Both linear and quadratic time trends in FEV1 change are highly significant. Smoking miners lost more FEV1 than non-smokers. Referents, all age less than 20 years, showed continued lung growth, whereas the miners who were under age 20 exhibited a decline in FEV1. Dust and smoking affect lung function in young, newly hired Chinese coal miners. FEV1 change over the first three years of employment is non-linear. The findings have implications for both methods and interpretation of medical screening in coal mining and other dusty work: during the first several years of employment more frequent testing may be desirable, and caution is required in interpreting early FEV1 declines.

Cancer incidence in the Western Australian mining industry (1996-2013).

PubMed

Sodhi-Berry, Nita; Reid, Alison; Fritschi, Lin; Musk, Aw Bill; Vermeulen, Roel; de Klerk, Nicholas; Peters, Susan

2017-08-01

Miners are frequently exposed to established and potential carcinogens. We aimed to assess cancer incidence in miners relative to the general population and identify high-risk subgroups. Incident cancers in Western Australian miners (n=153,922; 86% male) during 1996-2013 were identified. Indirectly standardised incidence ratios (SIRs) were calculated and mixed-effects Poisson models were used to calculate Incidence Rate Ratios (IRRs) to identify high-risk within-cohort subgroups. Compared with the general population, the overall cancer incidence in miners (n=4194 cases) was lower for both females (SIR:0.83, 95%CI:0.74-0.92) and males (SIR:0.96, 95%CI:0.93-0.99). Overall, cancer incidence did not differ by employment duration or employment commencement time. Ever-underground work was associated with lung cancer (IRR:1.81, 95%CI:1.11-2.93). Relative to multi-ore miners, IRRs for specific cancers were significantly different when exclusively mining: iron (prostate:0.73, 95%CI:0.56-0.94); gold (lung:1.77, 95%CI:1.04-3.01 and colorectum:1.70, 95%CI:1.16-2.51); and other metals (urinary tract:1.85, 95%CI:1.03-3.31 and leukaemia:0.36, 95%CI:0.14-0.96). Working underground emerged as a significant determinant of lung cancer risk in our contemporary mining cohort. Increased risks of lung, prostate, colorectal and urinary tract cancers and leukaemia were identified in miners of specific ores. These findings underline the importance of continued surveillance of the health and exposures of this relatively young cohort of miners. Copyright © 2017 Elsevier Ltd. All rights reserved.

Herbal compatibility of traditional Chinese medical formulas for acquired immunodeficiency syndrome.

PubMed

Cui, Meng; Li, Jinghua; Li, Haiyan; Song, Chunxin

2012-09-01

Because herbal compatibility is one of the most important reasons why Traditional Chinese Medcine (TCM) formulas are effective for acquired immunodeficiency syndrome (AIDS), our study aimed to determine the compatibility of herbs based on published AIDS clinical research in Chinese periodicals. To achieve this aim, we designed a new data-mining algorithm according to TCM data characteristics. We found 25 clinical AIDS studies, all using Chinese herbs for treatment, in the Traditional Chinese Medicine Database System, and information on diagnosis and treatment was extracted. To find out herbal compatibility, especially the formulae for herbal combinations, we proposed an improved association rule algorithm based on the frequency of combinations. In this algorithm, all the compatibility relationships were displayed in a tree structure, by which the relationship between formulas and their derivation could be clearly inferred. Data analysis showed that approximately 100 herbs have been used for treating AIDS. Based on the whole herb compatibility tree, we calculated a basic formula for AIDS: Huang Qi combined with Ren Shen, Fu Ling, Bai Zhu, Bai Zhu, Dang Gui, and Bai Shao. This formula, deriving from most of clinical prescriptions, and was chosed by most of clinicians for AIDS treatment. From data mining we found that Qi replenishment and detoxification were the main treatment principles, which coincided with the AIDS pathological mechanism in which immune function is destroyed by human immunodeficiency virus (HIV). Our data-mining results suggest that the core TCM treatment of AIDS is replenishing Qi and detoxification, by which AIDS patients' immune system may be enhanced. Compatibility of Huang Qi with some frequently-used herbs have shown real efficacy in clinical practice, which warrants pharmacological research in the future.

Text-mining as a methodology to assess eating disorder-relevant factors: Comparing mentions of fitness tracking technology across online communities.

PubMed

McCaig, Duncan; Bhatia, Sudeep; Elliott, Mark T; Walasek, Lukasz; Meyer, Caroline

2018-05-07

Text-mining offers a technique to identify and extract information from a large corpus of textual data. As an example, this study presents the application of text-mining to assess and compare interest in fitness tracking technology across eating disorder and health-related online communities. A list of fitness tracking technology terms was developed, and communities (i.e., 'subreddits') on a large online discussion platform (Reddit) were compared regarding the frequency with which these terms occurred. The corpus used in this study comprised all comments posted between May 2015 and January 2018 (inclusive) on six subreddits-three eating disorder-related, and three relating to either fitness, weight-management, or nutrition. All comments relating to the same 'thread' (i.e., conversation) were concatenated, and formed the cases used in this study (N = 377,276). Within the eating disorder-related subreddits, the findings indicated that a 'pro-eating disorder' subreddit, which is less recovery focused than the other eating disorder subreddits, had the highest frequency of fitness tracker terms. Across all subreddits, the weight-management subreddit had the highest frequency of the fitness tracker terms' occurrence, and MyFitnessPal was the most frequently mentioned fitness tracker. The technique exemplified here can potentially be used to assess group differences to identify at-risk populations, generate and explore clinically relevant research questions in populations who are difficult to recruit, and scope an area for which there is little extant literature. The technique also facilitates methodological triangulation of research findings obtained through more 'traditional' techniques, such as surveys or interviews. © 2018 Wiley Periodicals, Inc.

Effect of sewage sludge on formation of acidic ground water at a reclaimed coal mine

USGS Publications Warehouse

Cravotta, C.A.

1998-01-01

Data on rock, ground water, vadose water, and vadose gas chemistry were collected for two years after sewage sludge was applied at a reclaimed surface coal mine in Pennsylvania to determine if surface-applied sludge is an effective barrier to oxygen influx, contributes metals and nutrients to ground water, and promotes the acidification of ground water. Acidity, sulfate, and metals concentrations were elevated in the ground water (6- to 21-m depth) from spoil relative to unmined rock because of active oxidation of pyrite and dissolution of aluminosilicate, carbonate, and Mn-Fe-oxide minerals in the spoil. Concentrations of acidity, sulfate, metals (Fe, Mn, Al, Cd, Cu, Cr, Ni, Zn), and nitrate, and abundances of iron-oxidizing bacteria were elevated in the ground water from sludge-treated spoil relative to untreated spoil having a similar mineral composition; however, gaseous and dissolved oxygen concentrations did not differ between the treatments. Abundances of iron-oxidizing bacteria in the ground water samples were positively correlated with concentrations of ammonia, nitrate, acidity, metals, and sulfate. Concentrations of metals in vadose water samples (<5-m depth) from sludge-treated spoil (pH 5.9) were not elevated relative to untreated spoil (pH 4.4). In contrast, concentrations of nitrate were elevated in vadose water samples from sludge-treated spoil, frequently exceeding 10 mg/L. Downgradient decreases in nitrate to less than 3 mg/L and increases in sulfate concentrations in underlying ground water could result from oxidation of pyrite by nitrate. Thus, sewage sludge added to pyritic spoil can increase the growth of iron-oxidizing bacteria, the oxidation of pyrite, and the acidification of ground water. Nevertheless, the overall effects on ground water chemistry from the sludge were small and probably short-lived relative to the effects from mining only.

CT Characteristics of Pleural Plaques Related to Occupational or Environmental Asbestos Exposure from South Korean Asbestos Mines.

PubMed

Kim, Yookyung; Myong, Jun-Pyo; Lee, Jeong Kyong; Kim, Jeung Sook; Kim, Yoon Kyung; Jung, Soon-Hee

2015-01-01

This study evaluated the CT characteristics of pleural plaques in asbestos-exposed individuals and compared occupational versus environmental exposure groups. This study enrolled 181 subjects with occupational exposure and 98 with environmental exposure from chrysotile asbestos mines, who had pleural plaques confirmed by a chest CT. The CT scans were analyzed for morphological characteristics, the number and distribution of pleural plaques and combined pulmonary fibrosis. Furthermore, the CT findings were compared between the occupational and environmental exposure groups. Concerning the 279 subjects, the pleural plaques were single in 2.2% and unilateral in 3.6%, and showed variable widths (range, 1-20 mm; mean, 5.4 ± 2.7 mm) and lengths (5-310 mm; 72.6 ± 54.8 mm). The chest wall was the most commonly involved (98.6%), with an upper predominance on the ventral side (upper, 77.8% vs. lower, 55.9%, p < 0.001) and a lower predominance on the dorsal side (upper, 74.9% vs. lower, 91.8%, p = 0.02). Diaphragmatic involvement (78.1%) showed a right-side predominance (right, 73.8% vs. left, 55.6%, p < 0.001), whereas mediastinal plaques (42.7%) were more frequent on the left (right, 17.6% vs. left, 39.4%, p < 0.001). The extent and maximum length of plaques, and presence and severity of combined asbestosis, were significantly higher in the occupational exposure group (p < 0.05). Pleural plaques in asbestos-exposed individuals are variable in number and size; and show a predominant distribution in the upper ventral and lower dorsal chest walls, right diaphragm, and left mediastinum. Asbestos mine workers have a higher extent of plaques and pulmonary fibrosis versus environmentally exposed individuals.

Temperatures and locations used by hibernating bats, including Myotis sodalis (Indiana bat), in a limestone mine: implications for conservation and management.

PubMed

Brack, Virgil

2007-11-01

Understanding temperatures used by hibernating bats will aid conservation and management efforts for many species. A limestone mine with 71 km of passages, used as a hibernaculum by approximately 30,000 bats, was visited four times during a 6-year period. The mine had been surveyed and mapped; therefore, bats could be precisely located and temperatures (T (s)) of the entire hibernaculum ceiling accurately mapped. It was predicted that bats should hibernate between 5 and 10 degrees C to (1) use temperatures that allow a near minimal metabolic rate, (2) maximize the duration of hibernation bouts, (3) avoid more frequent and prolonged arousal at higher temperatures, (4) avoid cold and freezing temperatures that require an increase in metabolism and a decrease in duration of hibernation bouts or that could cause death, and (5) balance benefits of a reduced metabolic rate and costs of metabolic depression. The distribution of each species was not random for location (P < 0.000) or T (s) (P < 0.000). Myotis sodalis (Indiana bat) was most restricted in areas occupied, hibernating in thermally stable yet cold areas (X = 8.4 +/- 1.7 degrees C); 99% associated with cement block walls and sheltered alcoves, which perhaps dampened air movement and temperature fluctuations. Myotis lucifugus (little brown myotis) hibernated in colder, more variable areas (X = 7.2 +/- 2.6 degrees C). Myotis septentrionalis (northern myotis), Pipistrellus subflavus (eastern pipistrelle), and Eptesicus fuscus (big brown bat) typically hibernated in warm, thermally stable areas (X = 9.1 +/- 0.2 degrees C, X = 9.6 +/- 1.9 degrees C, and X = 9.5 +/- 1.5 degrees C, respectively). These data do not indicate that hibernacula for M. sodalis, an endangered species, should be manipulated to cool below 5 degrees C.

Design pattern mining using distributed learning automata and DNA sequence alignment.

PubMed

Esmaeilpour, Mansour; Naderifar, Vahideh; Shukur, Zarina

2014-01-01

Over the last decade, design patterns have been used extensively to generate reusable solutions to frequently encountered problems in software engineering and object oriented programming. A design pattern is a repeatable software design solution that provides a template for solving various instances of a general problem. This paper describes a new method for pattern mining, isolating design patterns and relationship between them; and a related tool, DLA-DNA for all implemented pattern and all projects used for evaluation. DLA-DNA achieves acceptable precision and recall instead of other evaluated tools based on distributed learning automata (DLA) and deoxyribonucleic acid (DNA) sequences alignment. The proposed method mines structural design patterns in the object oriented source code and extracts the strong and weak relationships between them, enabling analyzers and programmers to determine the dependency rate of each object, component, and other section of the code for parameter passing and modular programming. The proposed model can detect design patterns better that available other tools those are Pinot, PTIDEJ and DPJF; and the strengths of their relationships. The result demonstrate that whenever the source code is build standard and non-standard, based on the design patterns, then the result of the proposed method is near to DPJF and better that Pinot and PTIDEJ. The proposed model is tested on the several source codes and is compared with other related models and available tools those the results show the precision and recall of the proposed method, averagely 20% and 9.6% are more than Pinot, 27% and 31% are more than PTIDEJ and 3.3% and 2% are more than DPJF respectively. The primary idea of the proposed method is organized in two following steps: the first step, elemental design patterns are identified, while at the second step, is composed to recognize actual design patterns.

Data mining with iPlant: a meeting report from the 2013 GARNet workshop, Data mining with iPlant.

PubMed

Martin, Lisa; Cook, Charis; Matasci, Naim; Williams, Jason; Bastow, Ruth

2015-01-01

High-throughput sequencing technologies have rapidly moved from large international sequencing centres to individual laboratory benchtops. These changes have driven the 'data deluge' of modern biology. Submissions of nucleotide sequences to GenBank, for example, have doubled in size every year since 1982, and individual data sets now frequently reach terabytes in size. While 'big data' present exciting opportunities for scientific discovery, data analysis skills are not part of the typical wet bench biologist's experience. Knowing what to do with data, how to visualize and analyse them, make predictions, and test hypotheses are important barriers to success. Many researchers also lack adequate capacity to store and share these data, creating further bottlenecks to effective collaboration between groups and institutes. The US National Science Foundation-funded iPlant Collaborative was established in 2008 to form part of the data collection and analysis pipeline and help alleviate the bottlenecks associated with the big data challenge in plant science. Leveraging the power of high-performance computing facilities, iPlant provides free-to-use cyberinfrastructure to enable terabytes of data storage, improve analysis, and facilitate collaborations. To help train UK plant science researchers to use the iPlant platform and understand how it can be exploited to further research, GARNet organized a four-day Data mining with iPlant workshop at Warwick University in September 2013. This report provides an overview of the workshop, and highlights the power of the iPlant environment for lowering barriers to using complex bioinformatics resources, furthering discoveries in plant science research and providing a platform for education and outreach programmes. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Quantifying the contribution of airborne lead (Pb) to surface waters in northeastern Oklahoma

NASA Astrophysics Data System (ADS)

Li, J. J.; McDonald, J.; Curtis, H.

2017-12-01

The northeastern Oklahoma, home to a number of Native American Tribes, is part of the well-known Tri-State Mining District (TSMD). One hundred years of mining production in this area has left numerous, large chat piles on the surrounding environment, directly affecting the town of Picher and many other tribe communities. Byproducts of the mining, including lead (Pb)-contain dust have been transported to the atmosphere and seeped into groundwater, lakes, ponds and rivers. Due to this contamination, many children in the area have elevated levels of Pb in their bodies. Despite a substantial number of studies and efforts on the restoration of heavy metal contamination in this area (e.g. The Tar Creek Superfund Site, EPA), no studies have attempted to distinguish the contributions of different sources, particularly from the atmospheric deposition, of heavy metals to the aquatic environment. In this study, we analyzed the atmospheric deposition of Pb from 4 sites located close to the chat piles for the period of 2010 to 2016. Our preliminary analysis showed that atmospheric Pb has a strong seasonal pattern with two peak times in early spring and late fall, which largely correspond with the dry periods in the this area. Atmospheric concentrations of Pb monitored at these sites frequently exceeded 0.15 μg/m3, the National Ambient Air Quality Standards (NAAQS) standard for ambient air Pb, and was generally 10 times higher than atmospheric Pb monitored in Tulsa, OK, a major metropolitan area 150 km southwest of the monitoring sites. With the known Pb flux to the sediments of the water bodies, we estimated that the contribution of Pb from the atmospheric deposition to the surface waters is up to 25%, depending on the distance of the water bodies to concentrated distribution of the chat piles.

Leptospirosis Seroprevalence Among Blue Metal Mine Workers of Tamil Nadu, India.

PubMed

Parveen, Sakkarai Mohamed Asha; Suganyaa, Baskar; Sathya, Muthu Sri; Margreat, Alphonse Asirvatham Princy; Sivasankari, Karikalacholan; Shanmughapriya, Santhanam; Hoffman, Nicholas E; Natarajaseenivasan, Kalimuthusamy

2016-07-06

Leptospirosis is mainly considered an occupational disease, prevalent among agriculture, sewage works, forestry, and animal slaughtering populations. However, putative risk to miners and their inclusion in the high-risk leptospirosis group remain in need of rigorous analysis. Therefore, a study was conducted with the objective to assess the leptospirosis seroprevalence among miners of two districts of Tamil Nadu, India. A total of 244 sera samples from Pudukkottai miners (124) and Karur miners (120) were analyzed by microscopic agglutination test. Antibodies to leptospires were detected in 94 samples giving an overall seroprevalence of 38.5%. The seroprevalence was higher among Pudukkottai miners (65.3%) when compared with Karur miners (10.8%). Seroprevalence among control population (13%) was significantly less than that of the Pudukkottai miners marking a possible high-risk population group distinction. Subject sera most commonly reacted with organisms of the serogroup Autumnalis, and the pattern was similar in carrier animals of the study areas. Two leptospires were isolated from kidney samples of rats. The prevalence of Autumnalis among rodents and humans source tracked human leptospirosis among the miners. The study also determined that Pudukkottai miners are subjected to high-risk challenges such as exposure to water bodies on the way to the mines (odds ratio [OR] = 10.6), wet mine areas (OR = 10.6), rat infestation (OR = 4.6), and cattle rearing (OR = 10.4) and are thus frequently exposed to leptospirosis compared with Karur miners. Hence, control strategies targeting these populations will likely to prove to be effective remediation strategies benefiting Pudukkottai miners and workers in similar environments across occupations. © The American Society of Tropical Medicine and Hygiene.

Large Mine Permitting - Div. of Mining, Land, and Water

Science.gov Websites

Pebble Project Pogo Mine Red Dog Mine Rock Creek Project True North Mine OPMP Canadian Large Projects Pebble Project Pogo Mine Red Dog Mine Rock Creek Project True North Mine Contact: Kyle Moselle Large Mine

A screening-level assessment of lead, cadmium, and zinc in fish and crayfish from northeastern Oklahoma, USA

USGS Publications Warehouse

Schmitt, C.J.; Brumbaugh, W.G.; Linder, G.L.; Hinck, J.E.

2006-01-01

The objective of this study was to evaluate potential human and ecological risks associated with metals in fish and crayfish from mining in the Tri-States Mining District (TSMD). Crayfish (Orconectes spp.) and fish of six frequently consumed species (common carp, Cyprinus carpio; channel catfish, Ictalurus punctatus; flathead catfish, Pylodictis olivaris; largemouth bass, Micropterus salmoides; spotted bass, M. punctulatus; and white crappie, Pomoxis annularis) were collected in 2001-2002 from the Oklahoma waters of the Spring River (SR) and Neosho River (NR), which drain the TSMD. Samples from a mining-contaminated site in eastern Missouri and from reference sites were also analyzed. Individual fish were prepared for human consumption in the manner used locally by Native Americans (headed, eviscerated, and scaled) and analyzed for lead, cadmium, and zinc. Whole crayfish were analyzed as composite samples of 5-60 animals. Metals concentrations were typically higher in samples from sites most heavily affected by mining and lowest in reference samples. Within the TSMD, most metals concentrations were higher at sites on the SR than on the NR and were typically highest in common carp and crayfish than in other taxa. Higher concentrations and greater risk were associated with fish and crayfish from heavily contaminated SR tributaries than the SR or NR mainstems. Based on the results of this and previous studies, the human consumption of carp and crayfish could be restricted based on current criteria for lead, cadmium, and zinc, and the consumption of channel catfish could be restricted due to lead. Metals concentrations were uniformly low in Micropterus spp. and crappie and would not warrant restriction, however. Some risk to carnivorous avian wildlife from lead and zinc in TSMD fish and invertebrates was also indicated, as was risk to the fish themselves. Overall, the wildlife assessment is consistent with previously reported biological effects attributed to metals from the TSMD. The results demonstrate the potential for adverse effects in fish, wildlife, and humans and indicate that further investigation of human health and ecological risks, to include additional exposure pathways and endpoints, is warranted. ?? Springer Science+Business Media B.V. 2006.

Twelve years of succession on sandy substrates in a post-mining landscape: a Markov chain analysis.

PubMed

Baasch, Annett; Tischew, Sabine; Bruelheide, Helge

2010-06-01

Knowledge of succession rates and pathways is crucial for devising restoration strategies for highly disturbed ecosystems such as surface-mined land. As these processes have often only been described in qualitative terms, we used Markov models to quantify transitions between successional stages. However, Markov models are often considered not attractive for some reasons, such as model assumptions (e.g., stationarity in space and time, or the high expenditure of time required to estimate successional transitions in the field). Here we present a solution for converting multivariate ecological time series into transition matrices and demonstrate the applicability of this approach for a data set that resulted from monitoring the succession of sandy dry grassland in a post-mining landscape. We analyzed five transition matrices, four one-step matrices referring to specific periods of transition (1995-1998, 1998-2001, 2001-2004, 2004-2007), and one matrix for the whole study period (stationary model, 1995-2007). Finally, the stationary model was enhanced to a partly time-variable model. Applying the stationary and the time-variable models, we started a prediction well outside our calibration period, beginning with 100% bare soil in 1974 as the known start of the succession, and generated the coverage of 12 predefined vegetation types in three-year intervals. Transitions among vegetation types changed significantly in space and over time. While the probability of colonization was almost constant over time, the replacement rate tended to increase, indicating that the speed of succession accelerated with time or fluctuations became stronger. The predictions of both models agreed surprisingly well with the vegetation data observed more than two decades later. This shows that our dry grassland succession in a post-mining landscape can be adequately described by comparably simple types of Markov models, although some model assumptions have not been fulfilled and within-plot transitions have not been observed with point exactness. The major achievement of our proposed way to convert vegetation time series into transition matrices is the estimation of probability of events--a strength not provided by other frequently used statistical methods in vegetation science.

Temporal variation and the effect of rainfall on metals flux from the historic Beatson mine, Prince William Sound, Alaska, USA

USGS Publications Warehouse

Stillings, L.L.; Foster, A.L.; Koski, R.A.; Munk, L.; Shanks, Wayne C.

2008-01-01

Several abandoned Cu mines are located along the shore of Prince William Sound, AK, where the effect of mining-related discharge upon shoreline ecosystems is unknown. To determine the magnitude of this effect at the former Beatson mine, the largest Cu mine in the region and a Besshi-type massive sulfide ore deposit, trace metal concentration and flux were measured in surface run-off from remnant, mineralized workings and waste. Samples were collected from seepage waters; a remnant glory hole which is now a pit lake; a braided stream draining an area of mineralized rock, underground mine workings, and waste piles; and a background location upstream of the mine workings and mineralized rock. In the background stream pH averaged ???7.3, specific conductivity (SC) was ???40 ??S/cm, and the aqueous components indicative of sulfide mineral weathering, SO4 and trace metals, were at detection limits or lower. In the braided stream below the mine workings and waste piles, pH usually varied from 6.7 to 7.1, SC varied from 40 to 120 ??S/cm, SO4 had maximum concentrations of 32 mg/L, and the trace metals Cu, Ni, Pb, and Zn showed maximum total acid extractable concentrations of 186, 5.9, 6.2 and 343 ??g/L, respectively. With an annual rainfall of ???340 cm (estimated from the 2006 water year) it was expected that rain water would have a large effect on the chemistry of the braided stream draining the mine site. A linear mixing model with two end members, seepage water from mineralized rock and background water, estimated that the braided stream contained 10-35% mine drainage. After rain events the braided stream showed a decrease in pH, SC, Ca + Mg, SO4, and alkalinity, due to dilution. The trace metals Ni and Zn followed this same pattern. Sodium + K and Cl did not vary between the background and braided stream, nor did they vary with rainfall. At approximately 2 and 3 mg/L, respectively, these concentrations are similar to concentrations found in rainfall on the coasts of North America. High concentrations of total acid extractable Al and Fe were found at near-neutral pH in most of the waters collected at the site. Equilibrium solubility simulations, performed with PHREEQC, show that the stream waters are saturated with respect to Al, Fe and SiO2 solid phases. Because the "dissolved" sample fractions (acid preserved and filtered to 0.45 ??m) show significant concentrations of Al and Fe it is presumed that these are present as colloids. The relationship between concentrations of Al and Fe, and rainfall was the opposite of that observed for the major ions Ca + Mg, SO4, and alkalinity, in that Al and Fe concentrations increased with increasing rainfall. Concentrations of Cu and Pb followed the same pattern. Adsorption calculations were performed with Visual MINTEQ, using the diffuse double layer electrostatic model and surface complexation constants for the ferrihydrite surface. These results suggest that 30-93% of Cu and 58-97% of Pb was adsorbed to ferrihydrite precipitates in the stream waters. Ni and Zn showed little adsorption in this pH range. Flux calculations show that the total mass of trace metals transported from the mine site, during the 60 day study period, was ranked as Zn (196 kg) > Cu (87 kg) > Pb(1.9 kg) ??? Ni(1.9 kg). Nickel and Zn were transported mostly as dissolved species while Cu and Pb were transported mostly as adsorbed species. pH control on adsorption was evident when Cu and Pb isotherms were normalized by ferrihydrite flux. Decreased stream water pH due to periods of frequent and high volume rain events would cause desorption of Cu and Pb from the ferrihydrite surface, thus changing not only their speciation in solution but also their mechanism of transport. ?? 2007 Elsevier Ltd. All rights reserved.

The three-dimensional shapes of underground coal miners' feet do not match the internal dimensions of their work boots.

PubMed

Dobson, Jessica A; Riddiford-Harland, Diane L; Bell, Alison F; Steele, Julie R

2018-04-01

Mining work boots provide an interface between the foot and the ground, protecting and supporting miners' feet during lengthy coal mining shifts. Although underground coal miners report the fit of their work boots as reasonable to good, they frequently rate their boots as uncomfortable, suggesting that there is a mismatch between the shape of their feet and their boots. This study aimed to identify whether dimensions derived from the three-dimensional scans of 208 underground coal miners' feet (age 38.3 ± 9.8 years) differed from the internal dimensions of their work boots. The results revealed underground coal miners wore boots that were substantially longer than their feet, possibly because boots available in their correct length were too narrow. It is recommended boot manufacturers reassess the algorithms used to create boot lasts, focusing on adjusting boot circumference at the instep and heel relative to increases in foot length. Practitioner Summary: Fit and comfort ratings suggest a mismatch between the shape of underground coal miners' feet and their boots exists. This study examined whether three-dimensional scans of 208 miners' feet differed from their boot internal dimensions. Miners wore boots substantially longer than their feet, possibly due to inadequate width.

Arbuscular mycorrhizal fungi in arsenic-contaminated areas in Brazil.

PubMed

Schneider, Jerusa; Stürmer, Sidney Luiz; Guilherme, Luiz Roberto Guimarães; de Souza Moreira, Fatima Maria; Soares, Claudio Roberto Fonsêca de Sousa

2013-11-15

Arbuscular mycorrhizal fungi (AMF) are ubiquitous and establish important symbiotic relationships with the majority of the plants, even in soils contaminated with arsenic (As). In order to better understand the ecological relationships of these fungi with excess As in soils and their effects on plants in tropical conditions, occurrence and diversity of AMF were evaluated in areas affected by gold mining activity in Minas Gerais State, Brazil. Soils of four areas with different As concentrations (mg dm(-3)) were sampled: reference Area (10); B1 (subsuperficial layer) (396); barren material (573), and mine waste (1046). Soil sampling was carried out in rainy and dry seasons, including six composite samples per area (n = 24). AMF occurred widespread in all areas, being influenced by As concentrations and sampling periods. A total of 23 species were identified, belonging to the following genus: Acaulospora (10 species), Scutellospora (4 species), Racocetra (3 species), Glomus (4 species), Gigaspora (1 species) and Paraglomus (1 species). The most frequent species occurring in all areas were Paraglomus occultum, Acaulospora morrowiae and Glomus clarum. The predominance of these species indicates their high tolerance to excess As. Although arsenic contamination reduced AMF species richness, presence of host plants tended to counterbalance this reduction. Copyright © 2012 Elsevier B.V. All rights reserved.

[Disorders of locomotor system and effectiveness of physiotherapy in coal miners].

PubMed

Bilski, Bartosz; Bednarek, Agata

2003-01-01

The aim of the survey was to analyze the efficacy of physiotherapy applied in coal miners as well as to assess their locomotor system load and the effects of working conditions in mines. The questionnaire survey covered a group of 51 miners, aged 28-76 years (mean, 54 years), undergoing physiotherapeutic procedures in the mine out-patient clinic during the first quarter of 2003. The survey revealed that lumbosacral disorders were the most frequent locomotor system complaints reported by miners, especially those who work in a bending down position. According to the clinical data, spondylosis and allied disorders were the main reasons for pain in this part of the body. Having analyzed the relationship between age and occurrence of back pains, the majority of complaints were found in the 46-55 age group (two complaints per one respondent). The analysis of the association between back pains and duration of employment revealed that the complaints for the locomotor system occurred already after a five-year employment. The survey showed that the application of physiotherapeutic procedures diminished the back pain in the study group by 2.83 on average on the 0-10 scale. It was also found that magnetotherapy proved to be the most effective method in treating the spinal degenerative changes.

Implementation of Paste Backfill Mining Technology in Chinese Coal Mines

PubMed Central

Chang, Qingliang; Zhou, Huaqiang; Bai, Jianbiao

2014-01-01

Implementation of clean mining technology at coal mines is crucial to protect the environment and maintain balance among energy resources, consumption, and ecology. After reviewing present coal clean mining technology, we introduce the technology principles and technological process of paste backfill mining in coal mines and discuss the components and features of backfill materials, the constitution of the backfill system, and the backfill process. Specific implementation of this technology and its application are analyzed for paste backfill mining in Daizhuang Coal Mine; a practical implementation shows that paste backfill mining can improve the safety and excavation rate of coal mining, which can effectively resolve surface subsidence problems caused by underground mining activities, by utilizing solid waste such as coal gangues as a resource. Therefore, paste backfill mining is an effective clean coal mining technology, which has widespread application. PMID:25258737

Implementation of paste backfill mining technology in Chinese coal mines.

PubMed

Chang, Qingliang; Chen, Jianhang; Zhou, Huaqiang; Bai, Jianbiao

2014-01-01

Implementation of clean mining technology at coal mines is crucial to protect the environment and maintain balance among energy resources, consumption, and ecology. After reviewing present coal clean mining technology, we introduce the technology principles and technological process of paste backfill mining in coal mines and discuss the components and features of backfill materials, the constitution of the backfill system, and the backfill process. Specific implementation of this technology and its application are analyzed for paste backfill mining in Daizhuang Coal Mine; a practical implementation shows that paste backfill mining can improve the safety and excavation rate of coal mining, which can effectively resolve surface subsidence problems caused by underground mining activities, by utilizing solid waste such as coal gangues as a resource. Therefore, paste backfill mining is an effective clean coal mining technology, which has widespread application.

76 FR 70075 - Proximity Detection Systems for Continuous Mining Machines in Underground Coal Mines

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-10

... Detection Systems for Continuous Mining Machines in Underground Coal Mines AGENCY: Mine Safety and Health... proposed rule addressing Proximity Detection Systems for Continuous Mining Machines in Underground Coal... Detection Systems for Continuous Mining Machines in Underground Coal Mines. MSHA conducted hearings on...

Poker Flats Mine - Div. of Mining, Land, and Water

Science.gov Websites

Lands Coal Regulatory Program Large Mine Permits Mineral Property and Rights Mining Index Land Fishery Water Resources Factsheets Forms banner image of landscape Poker Flats Mine Home Mining Coal Regulatory Program Poker Flats Mine Mining Coal Regulatory Program Info Chickaloon Chuit Watershed Chuitna

76 FR 63238 - Proximity Detection Systems for Continuous Mining Machines in Underground Coal Mines

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-12

... Detection Systems for Continuous Mining Machines in Underground Coal Mines AGENCY: Mine Safety and Health... Agency's proposed rule addressing Proximity Detection Systems for Continuous Mining Machines in... proposed rule for Proximity Detection Systems on Continuous Mining Machines in Underground Coal Mines. Due...

30 CFR 77.1712 - Reopening mines; notification; inspection prior to mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... to mining. 77.1712 Section 77.1712 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION... prior to mining. Prior to reopening any surface coal mine after it has been abandoned or declared... an authorized representative of the Secretary before any mining operations in such mine are...

30 CFR 77.1712 - Reopening mines; notification; inspection prior to mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... to mining. 77.1712 Section 77.1712 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION... prior to mining. Prior to reopening any surface coal mine after it has been abandoned or declared... an authorized representative of the Secretary before any mining operations in such mine are...

30 CFR 819.21 - Auger mining: Protection of underground mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Auger mining: Protection of underground mining. 819.21 Section 819.21 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT... STANDARDS-AUGER MINING § 819.21 Auger mining: Protection of underground mining. Auger holes shall not extend...

Mining (except Oil and Gas) Sector (NAICS 212)

EPA Pesticide Factsheets

EPA Regulatory and enforcement information for the mining sector, including metal mining & nonmetallic mineral mining and quarrying. Includes information about asbestos, coal mining, mountaintop mining, Clean Water Act section 404, and abandoned mine lands

Mine Water Treatment in Hongai Coal Mines

NASA Astrophysics Data System (ADS)

Dang, Phuong Thao; Dang, Vu Chi

2018-03-01

Acid mine drainage (AMD) is recognized as one of the most serious environmental problem associated with mining industry. Acid water, also known as acid mine drainage forms when iron sulfide minerals found in the rock of coal seams are exposed to oxidizing conditions in coal mining. Until 2009, mine drainage in Hongai coal mines was not treated, leading to harmful effects on humans, animals and aquatic ecosystem. This report has examined acid mine drainage problem and techniques for acid mine drainage treatment in Hongai coal mines. In addition, selection and criteria for the design of the treatment systems have been presented.

Mercury Levels in Human Hair and Farmed Fish near Artisanal and Small-Scale Gold Mining Communities in the Madre de Dios River Basin, Peru

PubMed Central

Langeland, Aubrey L.; Hardin, Rebecca D.; Neitzel, Richard L.

2017-01-01

Artisanal and small-scale gold mining (ASGM) has been an important source of income for communities in the Madre de Dios River Basin in Peru for hundreds of years. However, in recent decades, the scale of ASGM activities in the region has increased dramatically, and exposures to a variety of occupational and environmental hazards related to ASGM, including mercury, are becoming more widespread. The aims of our study were to: (1) examine patterns in the total hair mercury level of human participants in several communities in the region and compare these results to the 2.2 µg/g total hair mercury level equivalent to the World Health Organization (WHO) Expert Committee of Food Additives (JECFA)’s Provisional Tolerable Weekly Intake (PTWI); and (2), to measure the mercury levels of paco (Piaractus brachypomus) fish raised in local aquaculture ponds, in order to compare these levels to the EPA Fish Tissue Residue Criterion of 0.3 µg Hg/g fish (wet weight). We collected hair samples from 80 participants in four communities (one control and three where ASGM activities occurred) in the region, and collected 111 samples from fish raised in 24 local aquaculture farms. We then analyzed the samples for total mercury. Total mercury levels in hair were statistically significantly higher in the mining communities than in the control community, and increased with increasing geodesic distance from the Madre de Dios headwaters, did not differ by sex, and frequently exceeded the reference level. Regression analyses indicated that higher hair mercury levels were associated with residence in ASGM communities. The analysis of paco fish samples found no samples that exceeded the EPA tissue residue criterion. Collectively, these results align with other recent studies showing that ASGM activities are associated with elevated human mercury exposure. The fish farmed through the relatively new process of aquaculture in ASGM areas appeared to have little potential to contribute to human mercury exposure. More research is needed on human health risks associated with ASGM to discern occupational, residential, and nutritional exposure, especially through tracking temporal changes in mercury levels as fish ponds age, and assessing levels in different farmed fish species. Additionally, research is needed to definitively determine that elevated mercury levels in humans and fish result from the elemental mercury from mining, rather than from a different source, such as the mercury released from soil erosion during deforestation events from mining or other activities. PMID:28335439

Mercury Levels in Human Hair and Farmed Fish near Artisanal and Small-Scale Gold Mining Communities in the Madre de Dios River Basin, Peru.

PubMed

Langeland, Aubrey L; Hardin, Rebecca D; Neitzel, Richard L

2017-03-14

Artisanal and small-scale gold mining (ASGM) has been an important source of income for communities in the Madre de Dios River Basin in Peru for hundreds of years. However, in recent decades, the scale of ASGM activities in the region has increased dramatically, and exposures to a variety of occupational and environmental hazards related to ASGM, including mercury, are becoming more widespread. The aims of our study were to: (1) examine patterns in the total hair mercury level of human participants in several communities in the region and compare these results to the 2.2 µg/g total hair mercury level equivalent to the World Health Organization (WHO) Expert Committee of Food Additives (JECFA)'s Provisional Tolerable Weekly Intake (PTWI); and (2), to measure the mercury levels of paco ( Piaractus brachypomus ) fish raised in local aquaculture ponds, in order to compare these levels to the EPA Fish Tissue Residue Criterion of 0.3 µg Hg/g fish (wet weight). We collected hair samples from 80 participants in four communities (one control and three where ASGM activities occurred) in the region, and collected 111 samples from fish raised in 24 local aquaculture farms. We then analyzed the samples for total mercury. Total mercury levels in hair were statistically significantly higher in the mining communities than in the control community, and increased with increasing geodesic distance from the Madre de Dios headwaters, did not differ by sex, and frequently exceeded the reference level. Regression analyses indicated that higher hair mercury levels were associated with residence in ASGM communities. The analysis of paco fish samples found no samples that exceeded the EPA tissue residue criterion. Collectively, these results align with other recent studies showing that ASGM activities are associated with elevated human mercury exposure. The fish farmed through the relatively new process of aquaculture in ASGM areas appeared to have little potential to contribute to human mercury exposure. More research is needed on human health risks associated with ASGM to discern occupational, residential, and nutritional exposure, especially through tracking temporal changes in mercury levels as fish ponds age, and assessing levels in different farmed fish species. Additionally, research is needed to definitively determine that elevated mercury levels in humans and fish result from the elemental mercury from mining, rather than from a different source, such as the mercury released from soil erosion during deforestation events from mining or other activities.

Frequent loss of lineages and deficient duplications accounted for low copy number of disease resistance genes in Cucurbitaceae

PubMed Central

2013-01-01

Background The sequenced genomes of cucumber, melon and watermelon have relatively few R-genes, with 70, 75 and 55 copies only, respectively. The mechanism for low copy number of R-genes in Cucurbitaceae genomes remains unknown. Results Manual annotation of R-genes in the sequenced genomes of Cucurbitaceae species showed that approximately half of them are pseudogenes. Comparative analysis of R-genes showed frequent loss of R-gene loci in different Cucurbitaceae species. Phylogenetic analysis, data mining and PCR cloning using degenerate primers indicated that Cucurbitaceae has limited number of R-gene lineages (subfamilies). Comparison between R-genes from Cucurbitaceae and those from poplar and soybean suggested frequent loss of R-gene lineages in Cucurbitaceae. Furthermore, the average number of R-genes per lineage in Cucurbitaceae species is approximately 1/3 that in soybean or poplar. Therefore, both loss of lineages and deficient duplications in extant lineages accounted for the low copy number of R-genes in Cucurbitaceae. No extensive chimeras of R-genes were found in any of the sequenced Cucurbitaceae genomes. Nevertheless, one lineage of R-genes from Trichosanthes kirilowii, a wild Cucurbitaceae species, exhibits chimeric structures caused by gene conversions, and may contain a large number of distinct R-genes in natural populations. Conclusions Cucurbitaceae species have limited number of R-gene lineages and each genome harbors relatively few R-genes. The scarcity of R-genes in Cucurbitaceae species was due to frequent loss of R-gene lineages and infrequent duplications in extant lineages. The evolutionary mechanisms for large variation of copy number of R-genes in different plant species were discussed. PMID:23682795

30 CFR 49.50 - Certification of coal mine rescue teams.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Certification of coal mine rescue teams. 49.50... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.50 Certification of coal mine... coal mine, the mine operator shall send the District Manager an annual statement certifying that each...

30 CFR 49.50 - Certification of coal mine rescue teams.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Certification of coal mine rescue teams. 49.50... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.50 Certification of coal mine... coal mine, the mine operator shall send the District Manager an annual statement certifying that each...

30 CFR 49.50 - Certification of coal mine rescue teams.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Certification of coal mine rescue teams. 49.50... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.50 Certification of coal mine... coal mine, the mine operator shall send the District Manager an annual statement certifying that each...

30 CFR 49.20 - Requirements for all coal mines.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Requirements for all coal mines. 49.20 Section... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.20 Requirements for all coal mines. (a) The operator of each underground coal mine shall make available two certified mine rescue...

30 CFR 49.20 - Requirements for all coal mines.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Requirements for all coal mines. 49.20 Section... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.20 Requirements for all coal mines. (a) The operator of each underground coal mine shall make available two certified mine rescue...

30 CFR 49.50 - Certification of coal mine rescue teams.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Certification of coal mine rescue teams. 49.50... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.50 Certification of coal mine... coal mine, the mine operator shall send the District Manager an annual statement certifying that each...

30 CFR 49.20 - Requirements for all coal mines.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Requirements for all coal mines. 49.20 Section... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.20 Requirements for all coal mines. (a) The operator of each underground coal mine shall make available two certified mine rescue...

30 CFR 49.20 - Requirements for all coal mines.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Requirements for all coal mines. 49.20 Section... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.20 Requirements for all coal mines. (a) The operator of each underground coal mine shall make available two certified mine rescue...

30 CFR 49.50 - Certification of coal mine rescue teams.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Certification of coal mine rescue teams. 49.50... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.50 Certification of coal mine... coal mine, the mine operator shall send the District Manager an annual statement certifying that each...

30 CFR 49.20 - Requirements for all coal mines.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Requirements for all coal mines. 49.20 Section... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.20 Requirements for all coal mines. (a) The operator of each underground coal mine shall make available two certified mine rescue...

The improved Apriori algorithm based on matrix pruning and weight analysis

NASA Astrophysics Data System (ADS)

Lang, Zhenhong

2018-04-01

This paper uses the matrix compression algorithm and weight analysis algorithm for reference and proposes an improved matrix pruning and weight analysis Apriori algorithm. After the transactional database is scanned for only once, the algorithm will construct the boolean transaction matrix. Through the calculation of one figure in the rows and columns of the matrix, the infrequent item set is pruned, and a new candidate item set is formed. Then, the item's weight and the transaction's weight as well as the weight support for items are calculated, thus the frequent item sets are gained. The experimental result shows that the improved Apriori algorithm not only reduces the number of repeated scans of the database, but also improves the efficiency of data correlation mining.

Survey of nine surface mines in North America. [Nine different mines in USA and Canada

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hayes, L.G.; Brackett, R.D.; Floyd, F.D.

This report presents the information gathered by three mining engineers in a 1980 survey of nine surface mines in the United States and Canada. The mines visited included seven coal mines, one copper mine, and one tar sands mine selected as representative of present state of the art in open pit, strip, and terrace pit mining. The purpose of the survey was to investigate mining methods, equipment requirements, operating costs, reclamation procedures and costs, and other aspects of current surface mining practices in order to acquire basic data for a study comparing conventional and terrace pit mining methods, particularly inmore » deeper overburdens. The survey was conducted as part of a project under DOE Contract No. DE-AC01-79ET10023 titled The Development of Optimal Terrace Pit Coal Mining Systems.« less

Using stable isotopes (δD, δ18O, δ34S and 87Sr/86Sr) to identify sources of water in abandoned mines in the Fengfeng coal mining district, northern China

NASA Astrophysics Data System (ADS)

Qu, Shen; Wang, Guangcai; Shi, Zheming; Xu, Qingyu; Guo, Yuying; Ma, Luan; Sheng, Yizhi

2018-05-01

With depleted coal resources or deteriorating mining geological conditions, some coal mines have been abandoned in the Fengfeng mining district, China. Water that accumulates in an abandoned underground mine (goaf water) may be a hazard to neighboring mines and impact the groundwater environment. Groundwater samples at three abandoned mines (Yi, Er and Quantou mines) in the Fengfeng mining district and the underlying Ordovician limestone aquifer were collected to characterize their chemical and isotopic compositions and identify the sources of the mine water. The water was HCO3·SO4-Ca·Mg type in Er mine and the auxiliary shaft of Yi mine, and HCO3·SO4-Na type in the main shaft of Quantou mine. The isotopic compositions (δD and δ18O) of water in the three abandoned mines were close to that of Ordovician limestone groundwater. Faults in the abandoned mines were developmental, possibly facilitating inflows of groundwater from the underlying Ordovician limestone aquifers into the coal mines. Although the Sr2+ concentrations differed considerably, the ratios of Sr2+/Ca2+ and 87Sr/86Sr and the 34S content of SO4 2- were similar for all three mine waters and Ordovician limestone groundwater, indicating that a close hydraulic connection may exist. Geochemical and isotopic indicators suggest that (1) the mine waters may originate mainly from the Ordovician limestone groundwater inflows, and (2) the upward hydraulic gradient in the limestone aquifer may prevent its contamination by the overlying abandoned mine water. The results of this study could be useful for water resources management in this area and other similar mining areas.

North American Bats and Mines Project: A cooperative approach for integrating bat conservation and mine-land reclamation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ducummon, S.L.

Inactive underground mines now provide essential habitat for more than half of North America`s 44 bat species, including some of the largest remaining populations. Thousands of abandoned mines have already been closed or are slated for safety closures, and many are destroyed during renewed mining in historic districts. The available evidence suggests that millions of bats have already been lost due to these closures. Bats are primary predators of night-flying insects that cost American farmers and foresters billions of dollars annually, therefore, threats to bat survival are cause for serious concern. Fortunately, mine closure methods exist that protect both batsmore » and humans. Bat Conservation International (BCI) and the USDI-Bureau of Land Management founded the North American Bats and Mines Project to provide national leadership and coordination to minimize the loss of mine-roosting bats. This partnership has involved federal and state mine-land and wildlife managers and the mining industry. BCI has trained hundreds of mine-land and wildlife managers nationwide in mine assessment techniques for bats and bat-compatible closure methods, published technical information on bats and mine-land management, presented papers on bats and mines at national mining and wildlife conferences, and collaborated with numerous federal, state, and private partners to protect some of the most important mine-roosting bat populations. Our new mining industry initiative, Mining for Habitat, is designed to develop bat habitat conservation and enhancement plans for active mining operations. It includes the creation of cost-effective artificial underground bat roosts using surplus mining materials such as old mine-truck tires and culverts buried beneath waste rock.« less

Atmospheric particulate matter size distribution and concentration in West Virginia coal mining and non-mining areas.

PubMed

Kurth, Laura M; McCawley, Michael; Hendryx, Michael; Lusk, Stephanie

2014-07-01

People who live in Appalachian areas where coal mining is prominent have increased health problems compared with people in non-mining areas of Appalachia. Coal mines and related mining activities result in the production of atmospheric particulate matter (PM) that is associated with human health effects. There is a gap in research regarding particle size concentration and distribution to determine respiratory dose around coal mining and non-mining areas. Mass- and number-based size distributions were determined with an Aerodynamic Particle Size and Scanning Mobility Particle Sizer to calculate lung deposition around mining and non-mining areas of West Virginia. Particle number concentrations and deposited lung dose were significantly greater around mining areas compared with non-mining areas, demonstrating elevated risks to humans. The greater dose was correlated with elevated disease rates in the West Virginia mining areas. Number concentrations in the mining areas were comparable to a previously documented urban area where number concentration was associated with respiratory and cardiovascular disease.

Evaluation of mine seals constructed in 1967 at Elkins, Randolph County, West Virginia. Report of investigations/1984

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adams, L.M.; Lipscomb, J.R.

1984-01-01

In 1980, the Bureau of Mines surveyed a group of mine seals in Randolph County, WV, to evaluate their effectiveness for reducing toxic pollutants in mine water discharges. The survey focused on 11 block wet mine seals, but mine seals of several other types were also examined. The seals were designed to prevent air from entering the mine portals while allowing mine water to flow out. It was believed that by preventing air from entering inactive or abandoned mines, the formation of toxic pollutants and acid mine drainage (AMD) could be reduced.

POST-MINING DEVELOPMENT USING RESOURCES FROM FLOODED UNDERGROUND MINE WORKINGS

EPA Science Inventory

Post-mining issues of land and surface utilization now serve to accentuate how important it is to incorporate sustainable development aspects into hard rock mining. In an effort to revitalize lands degraded by historic mining, 10 acres of mine tailings near the Belmont Mine have...

75 FR 17511 - Coal Mine Dust Sampling Devices

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-06

... Part III Department of Labor Mine Safety and Health Adminisration 30 CFR Parts 18, 74, and 75 Coal Mine Dust Sampling Devices; High-Voltage Continuous Mining Machine Standard for Underground Coal Mines...-AB61 Coal Mine Dust Sampling Devices AGENCY: Mine Safety and Health Administration, Labor. ACTION...

Publications - SR 68 | Alaska Division of Geological & Geophysical Surveys

Science.gov Websites

Mining District; Base Metals; Bethel Mining District; Bismuth; Black Mining District; Bluff (Place ; Livengood Mining District; Lode; Marshall Mining District; Massive Sulfide Deposit; Massive Sulfide Occurrence; Massive Sulfide Prospect; Massive Sulfides; McGrath Mining District; Melozitna Mining District

78 FR 79010 - Criteria to Certify Coal Mine Rescue Teams

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-27

... to Certify Coal Mine Rescue Teams AGENCY: Mine Safety and Health Administration, Labor. ACTION... updated the coal mine rescue team certification criteria. The Mine Improvement and New Emergency Response... mine operator to certify the qualifications of a coal mine rescue team is that team members are...

77 FR 16863 - Proposed Extension of Existing Information Collection; Mine Mapping and Records of Opening...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-03-22

... DEPARTMENT OF LABOR Mine Safety and Health Administration Proposed Extension of Existing Information Collection; Mine Mapping and Records of Opening, Closing, and Reopening of Mines (Formerly, Record of Mine Closures, Opening & Reopening of Mines) AGENCY: Mine Safety and Health Administration, Labor...

30 CFR 49.5 - Mine rescue station.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Mine rescue station. 49.5 Section 49.5 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and Nonmetal Mines § 49.5 Mine rescue station. (a) Except...

30 CFR 49.15 - Mine rescue station.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Mine rescue station. 49.15 Section 49.15 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.15 Mine rescue station. (a) Every operator...

78 FR 35974 - Proposed Information Collection; Comment Request; Coal Mine Rescue Teams; Arrangements for...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-14

... Request; Coal Mine Rescue Teams; Arrangements for Emergency Medical Assistance and Transportation for... Part 49, Mine Rescue Teams, Subpart B--Mine Rescue Teams for Underground Coal Mines, sets standards related to the availability of mine rescue teams; alternate mine rescue capability for small and remote...

30 CFR 49.15 - Mine rescue station.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Mine rescue station. 49.15 Section 49.15 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.15 Mine rescue station. (a) Every operator...

30 CFR 49.4 - Alternative mine rescue capability for special mining conditions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Alternative mine rescue capability for special mining conditions. 49.4 Section 49.4 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and...

30 CFR 49.5 - Mine rescue station.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Mine rescue station. 49.5 Section 49.5 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and Nonmetal Mines § 49.5 Mine rescue station. (a) Except...

30 CFR 49.15 - Mine rescue station.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Mine rescue station. 49.15 Section 49.15 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.15 Mine rescue station. (a) Every operator...

30 CFR 49.5 - Mine rescue station.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Mine rescue station. 49.5 Section 49.5 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and Nonmetal Mines § 49.5 Mine rescue station. (a) Except...

30 CFR 49.15 - Mine rescue station.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Mine rescue station. 49.15 Section 49.15 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.15 Mine rescue station. (a) Every operator...

30 CFR 49.4 - Alternative mine rescue capability for special mining conditions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Alternative mine rescue capability for special mining conditions. 49.4 Section 49.4 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and...

30 CFR 49.4 - Alternative mine rescue capability for special mining conditions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Alternative mine rescue capability for special mining conditions. 49.4 Section 49.4 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and...

30 CFR 49.15 - Mine rescue station.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Mine rescue station. 49.15 Section 49.15 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.15 Mine rescue station. (a) Every operator...

30 CFR 49.9 - Mine emergency notification plan.

Code of Federal Regulations, 2011 CFR

2011-07-01

... TRAINING MINE RESCUE TEAMS § 49.9 Mine emergency notification plan. (a) Each underground mine shall have a mine rescue notification plan outlining the procedures to follow in notifying the mine rescue teams...

30 CFR 49.9 - Mine emergency notification plan.

Code of Federal Regulations, 2010 CFR

2010-07-01

... TRAINING MINE RESCUE TEAMS § 49.9 Mine emergency notification plan. (a) Each underground mine shall have a mine rescue notification plan outlining the procedures to follow in notifying the mine rescue teams...

Long Term Analysis of Deformations in Salt Mines: Kłodawa Salt Mine Case Study, Central Poland

NASA Astrophysics Data System (ADS)

Cała, Marek; Tajduś, Antoni; Andrusikiewicz, Wacław; Kowalski, Michał; Kolano, Malwina; Stopkowicz, Agnieszka; Cyran, Katarzyna; Jakóbczyk, Joanna

2017-09-01

Located in central Poland, the Kłodawa salt dome is 26 km long and about 2 km wide. Exploitation of the dome started in 1956, currently rock salt extraction is carried out in 7 mining fields and the 12 mining levels at the depth from 322 to 625 meters below sea level (m.b.s.l.). It is planned to maintain the mining activity till 2052 and extend rock salt extraction to deeper levels. The dome is characterised by complex geological structure resulted from halokinetic and tectonic processes. Projection of the 3D numerical analysis took into account the following factors: mine working distribution within the Kłodawa mine (about 1000 rooms, 350 km of galleries), complex geological structure of the salt dome, complicated structure and geometry of mine workings and distinction in rocks mechanical properties e.g. rock salt and anhydrite. Analysis of past mine workings deformation and prediction of future rock mass behaviour was divided into four stages: building of the 3D model (state of mine workings in year 2014), model extension of the future mine workings planned for extraction in years 2015-2052, the 3D model calibration and stability analysis of all mine workings. The 3D numerical model of Kłodawa salt mine included extracted and planned mine workings in 7 mining fields and 14 mining levels (about 2000 mine workings). The dimensions of the model were 4200 m × 4700 m × 1200 m what was simulated by 33 million elements. The 3D model was calibrated on the grounds of convergence measurements and laboratory tests. Stability assessment of mine workings was based on analysis of the strength/stress ratio and vertical stress. The strength/stress ratio analysis enabled to indicate endangered area in mine workings and can be defined as the factor of safety. Mine workings in state close to collapse are indicated by the strength/stress ratio equals 1. Analysis of the vertical stress in mine workings produced the estimation of current state of stress in comparison to initial (pre-mining) conditions. The long-term deformation analysis of the Kłodawa salt mine for year 2014 revealed that stability conditions were fulfilled. Local disturbances indicated in the numerical analysis were connected with high chambers included in the mining field no 1 and complex geological structure in the vicinity of mine workings located in the mining fields no 2 and 3. Moreover, numerical simulations that projected the future extraction progress (till year 2052) showed positive performance. Local weakness zones in the mining field no 7 are associated with occurrence of carnallite layers and intensive mining which are planned in the mining field no 6 at the end of rock salt extraction.

Mine Improvement and New Emergency Response Act of 2006. Public Law 109-236, S2803

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

2006-06-15

This Act may be cited as the 'Mine Improvement and New Emergency Response Act of 2006' or the 'MINER Act'. It amends the Federal Mine Safety and Health Act of 1977 to improve the safety of mines and mining. The Act requires operators of underground coal mines to improve accident preparedness. The legislation requires mining companies to develop an emergency response plan specific to each mine they operate, and requires that every mine has at least two rescue teams located within one hour. S. 2803 also limits the legal liability of rescue team members and the companies that employ them.more » The act increases both civil and criminal penalties for violations of federal mining safety standards and gives the Mine Safety and Health Administration (MSHA) the ability to temporarily close a mine that fails to pay the penalties or fines. In addition, the act calls for several studies into ways to enhance mine safety, as well as the establishment of a new office within the National Institute for Occupational Safety and Health devoted to improving mine safety. Finally, the legislation establishes new scholarship and grant programs devoted to training individuals with respect to mine safety.« less

30 CFR 49.19 - Mine emergency notification plan.

Code of Federal Regulations, 2012 CFR

2012-07-01

... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.19 Mine emergency notification... follow in notifying the mine rescue teams when there is an emergency that requires their services. (b) A...

30 CFR 49.9 - Mine emergency notification plan.

Code of Federal Regulations, 2012 CFR

2012-07-01

... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and Nonmetal Mines § 49.9 Mine emergency... procedures to follow in notifying the mine rescue teams when there is an emergency that requires their...

30 CFR 49.9 - Mine emergency notification plan.

Code of Federal Regulations, 2014 CFR

2014-07-01

... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and Nonmetal Mines § 49.9 Mine emergency... procedures to follow in notifying the mine rescue teams when there is an emergency that requires their...

30 CFR 49.9 - Mine emergency notification plan.

Code of Federal Regulations, 2013 CFR

2013-07-01

... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and Nonmetal Mines § 49.9 Mine emergency... procedures to follow in notifying the mine rescue teams when there is an emergency that requires their...

30 CFR 49.19 - Mine emergency notification plan.

Code of Federal Regulations, 2014 CFR

2014-07-01

... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.19 Mine emergency notification... follow in notifying the mine rescue teams when there is an emergency that requires their services. (b) A...

30 CFR 49.19 - Mine emergency notification plan.

Code of Federal Regulations, 2011 CFR

2011-07-01

... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.19 Mine emergency notification... follow in notifying the mine rescue teams when there is an emergency that requires their services. (b) A...

30 CFR 49.19 - Mine emergency notification plan.

Code of Federal Regulations, 2010 CFR

2010-07-01

... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.19 Mine emergency notification... follow in notifying the mine rescue teams when there is an emergency that requires their services. (b) A...

30 CFR 49.19 - Mine emergency notification plan.

Code of Federal Regulations, 2013 CFR

2013-07-01

... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.19 Mine emergency notification... follow in notifying the mine rescue teams when there is an emergency that requires their services. (b) A...

30 CFR 49.4 - Alternative mine rescue capability for special mining conditions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Alternative mine rescue capability for special mining conditions. 49.4 Section 49.4 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS § 49.4 Alternative mine rescue capability for...

30 CFR 49.7 - Physical requirements for mine rescue team.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Physical requirements for mine rescue team. 49... EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and Nonmetal Mines § 49.7 Physical requirements for mine rescue team. (a) Each member of a mine rescue team shall be examined...

30 CFR 49.12 - Availability of mine rescue teams.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Availability of mine rescue teams. 49.12... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.12 Availability of mine rescue teams. (a) Except where alternative compliance is permitted for small and remote mines (§ 49.13), every...

30 CFR 49.2 - Availability of mine rescue teams.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Availability of mine rescue teams. 49.2 Section... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and Nonmetal Mines § 49.2 Availability of mine rescue teams. (a) Except where alternative compliance is permitted for small and remote mines...

30 CFR 49.12 - Availability of mine rescue teams.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Availability of mine rescue teams. 49.12... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.12 Availability of mine rescue teams. (a) Except where alternative compliance is permitted for small and remote mines (§ 49.13), every...

30 CFR 49.12 - Availability of mine rescue teams.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Availability of mine rescue teams. 49.12... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.12 Availability of mine rescue teams. (a) Except where alternative compliance is permitted for small and remote mines (§ 49.13), every...

30 CFR 49.7 - Physical requirements for mine rescue team.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Physical requirements for mine rescue team. 49... EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and Nonmetal Mines § 49.7 Physical requirements for mine rescue team. (a) Each member of a mine rescue team shall be examined...

30 CFR 49.12 - Availability of mine rescue teams.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Availability of mine rescue teams. 49.12... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.12 Availability of mine rescue teams. (a) Except where alternative compliance is permitted for small and remote mines (§ 49.13), every...

30 CFR 49.4 - Alternative mine rescue capability for special mining conditions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Alternative mine rescue capability for special mining conditions. 49.4 Section 49.4 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS § 49.4 Alternative mine rescue capability for...

30 CFR 49.12 - Availability of mine rescue teams.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Availability of mine rescue teams. 49.12... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.12 Availability of mine rescue teams. (a) Except where alternative compliance is permitted for small and remote mines (§ 49.13), every...

30 CFR 49.2 - Availability of mine rescue teams.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Availability of mine rescue teams. 49.2 Section... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and Nonmetal Mines § 49.2 Availability of mine rescue teams. (a) Except where alternative compliance is permitted for small and remote mines...

30 CFR 49.7 - Physical requirements for mine rescue team.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Physical requirements for mine rescue team. 49... EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and Nonmetal Mines § 49.7 Physical requirements for mine rescue team. (a) Each member of a mine rescue team shall be examined...

30 CFR 49.2 - Availability of mine rescue teams.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Availability of mine rescue teams. 49.2 Section... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and Nonmetal Mines § 49.2 Availability of mine rescue teams. (a) Except where alternative compliance is permitted for small and remote mines...

Application of Modern Tools and Techniques for Mine Safety & Disaster Management

NASA Astrophysics Data System (ADS)

Kumar, Dheeraj

2016-04-01

The implementation of novel systems and adoption of improvised equipment in mines help mining companies in two important ways: enhanced mine productivity and improved worker safety. There is a substantial need for adoption of state-of-the-art automation technologies in the mines to ensure the safety and to protect health of mine workers. With the advent of new autonomous equipment used in the mine, the inefficiencies are reduced by limiting human inconsistencies and error. The desired increase in productivity at a mine can sometimes be achieved by changing only a few simple variables. Significant developments have been made in the areas of surface and underground communication, robotics, smart sensors, tracking systems, mine gas monitoring systems and ground movements etc. Advancement in information technology in the form of internet, GIS, remote sensing, satellite communication, etc. have proved to be important tools for hazard reduction and disaster management. This paper is mainly focused on issues pertaining to mine safety and disaster management and some of the recent innovations in the mine automations that could be deployed in mines for safe mining operations and for avoiding any unforeseen mine disaster.

The Data Gap in the EHR for Clinical Research Eligibility Screening.

PubMed

Butler, Alex; Wei, Wei; Yuan, Chi; Kang, Tian; Si, Yuqi; Weng, Chunhua

2018-01-01

Much effort has been devoted to leverage EHR data for matching patients into clinical trials. However, EHRs may not contain all important data elements for clinical research eligibility screening. To better design research-friendly EHRs, an important step is to identify data elements frequently used for eligibility screening but not yet available in EHRs. This study fills this knowledge gap. Using the Alzheimer's disease domain as an example, we performed text mining on the eligibility criteria text in Clinicaltrials.gov to identify frequently used eligibility criteria concepts. We compared them to the EHR data elements of a cohort of Alzheimer's Disease patients to assess the data gap by usingthe OMOP Common Data Model to standardize the representations for both criteria concepts and EHR data elements. We identified the most common SNOMED CT concepts used in Alzheimer 's Disease trials, andfound 40% of common eligibility criteria concepts were not even defined in the concept space in the EHR dataset for a cohort of Alzheimer 'sDisease patients, indicating a significant data gap may impede EHR-based eligibility screening. The results of this study can be useful for designing targeted research data collection forms to help fill the data gap in the EHR.

Pattern extraction for high-risk accidents in the construction industry: a data-mining approach.

PubMed

Amiri, Mehran; Ardeshir, Abdollah; Fazel Zarandi, Mohammad Hossein; Soltanaghaei, Elahe

2016-09-01

Accidents involving falls and falling objects (group I) are highly frequent accidents in the construction industry. While being hit by a vehicle, electric shock, collapse in the excavation and fire or explosion accidents (group II) are much less frequent, they make up a considerable proportion of severe accidents. In this study, multiple-correspondence analysis, decision tree, ensembles of decision tree and association rules methods are employed to analyse a database of construction accidents throughout Iran between 2007 and 2011. The findings indicate that in group I, there is a significant correspondence among these variables: time of accident, place of accident, body part affected, final consequence of accident and lost workdays. Moreover, the frequency of accidents in the night shift is less than others, and the frequency of injury to the head, back, spine and limbs are more. In group II, the variables time of accident and body part affected are mostly related and the frequency of accidents among married and older workers is more than single and young workers. There was a higher frequency in the evening, night shifts and weekends. The results of this study are totally in line with the previous research.

Numerical Study on 4-1 Coal Seam of Xiaoming Mine in Ascending Mining

PubMed Central

Tianwei, Lan; Hongwei, Zhang; Sheng, Li; Weihua, Song; Batugin, A. C.; Guoshui, Tang

2015-01-01

Coal seams ascending mining technology is very significant, since it influences the safety production and the liberation of dull coal, speeds up the construction of energy, improves the stability of stope, and reduces or avoids deep hard rock mining induced mine disaster. Combined with the Xiaoming ascending mining mine 4-1, by numerical calculation, the paper analyses ascending mining 4-1 factors, determines the feasibility of ascending mining 4-1 coalbed, and proposes roadway layout program about working face, which has broad economic and social benefits. PMID:25866840

Orapa Diamond Mine, Botswana

NASA Image and Video Library

2015-11-16

This image from NASA Terra spacecraft shows the Orapa diamond mine, the world largest diamond mine by area. The mine is located in Botswana. It is the oldest of four mines operated by the same company, having begun operations in 1971. Orapa is an open pit style of mine, located on two kimberlite pipes. Currently, the Orapa mine annually produces approximately 11 million carats (2200 kg) of diamonds. The Letlhakane diamond mine is also an open pit construction. In 2003, the Letlhakane mine produced 1.06 million carats of diamonds. The Damtshaa diamond mine is the newest of four mines, located on top of four distinct kimberlite pipes of varying ore grade. The mine is forecast to produce about 5 million carats of diamond over the projected 31 year life of the mine. The image was acquired October 5, 2014, covers an area of 28 by 45 km, and is located at 21.3 degrees south, 25.4 degrees east. http://photojournal.jpl.nasa.gov/catalog/PIA20104

Modes and Experience of Green Mine Construction in Yunnan, China: Case Studies

NASA Astrophysics Data System (ADS)

Cheng, Xianfeng; Huang, Qianrui; Yang, Shuran; Xu, Jun; Fan, Youcai; Xu, Gang; Yang, Jiaqing; Yuan, Jia; Qi, Wufu

2017-12-01

Yunnan is one of most important provinces with mineral resources and exploration in China. Meanwhile, Yunnan is Chinese ecological protective screen and try to be Pacesetter of ecological civilization. However, mining industry always disturbs ecological environment seriously. So green mine construction is inevitable and the best choice for Yunnan. In this paper, achievement of green mine construction in Yunnan was summarized. Then the paper takes two mines from Dahongshan and 4 mines from Yunnan Phosphate Chemical Group Co., Ltd (YPC for short) as case studies. Technological innovation in Dahongshan Fe Mine and Dahongshan Cu Mine guarantees their success of green mine construction. Land rehabilitation and harmonious community are highlights of 4 mines from YPC. These modes and experience could be referential to construct green mine.

30 CFR 49.17 - Physical requirements for mine rescue team.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Physical requirements for mine rescue team. 49... EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.17 Physical requirements for mine rescue team. (a) Each member of a mine rescue team shall be examined annually by a...

30 CFR 49.17 - Physical requirements for mine rescue team.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Physical requirements for mine rescue team. 49... EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.17 Physical requirements for mine rescue team. (a) Each member of a mine rescue team shall be examined annually by a...

30 CFR 49.18 - Training for mine rescue teams.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Training for mine rescue teams. 49.18 Section... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.18 Training for mine rescue teams. (a) Prior to serving on a mine rescue team each member shall complete, at a minimum, an initial...

30 CFR 49.8 - Training for mine rescue teams.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Training for mine rescue teams. 49.8 Section 49... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and Nonmetal Mines § 49.8 Training for mine rescue teams. (a) Prior to serving on a mine rescue team each member shall complete, at a minimum...

30 CFR 49.17 - Physical requirements for mine rescue team.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Physical requirements for mine rescue team. 49... EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.17 Physical requirements for mine rescue team. (a) Each member of a mine rescue team shall be examined annually by a...

30 CFR 49.8 - Training for mine rescue teams.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Training for mine rescue teams. 49.8 Section 49... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and Nonmetal Mines § 49.8 Training for mine rescue teams. (a) Prior to serving on a mine rescue team each member shall complete, at a minimum...

30 CFR 49.18 - Training for mine rescue teams.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Training for mine rescue teams. 49.18 Section... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.18 Training for mine rescue teams. (a) Prior to serving on a mine rescue team each member shall complete, at a minimum, an initial...

30 CFR 49.17 - Physical requirements for mine rescue team.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Physical requirements for mine rescue team. 49... EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.17 Physical requirements for mine rescue team. (a) Each member of a mine rescue team shall be examined annually by a...

30 CFR 49.17 - Physical requirements for mine rescue team.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Physical requirements for mine rescue team. 49... EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.17 Physical requirements for mine rescue team. (a) Each member of a mine rescue team shall be examined annually by a...

30 CFR 49.18 - Training for mine rescue teams.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Training for mine rescue teams. 49.18 Section... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.18 Training for mine rescue teams. (a) Prior to serving on a mine rescue team each member shall complete, at a minimum, an initial...

30 CFR 49.18 - Training for mine rescue teams.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Training for mine rescue teams. 49.18 Section... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.18 Training for mine rescue teams. (a) Prior to serving on a mine rescue team each member shall complete, at a minimum, an initial...

30 CFR 49.8 - Training for mine rescue teams.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Training for mine rescue teams. 49.8 Section 49... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and Nonmetal Mines § 49.8 Training for mine rescue teams. (a) Prior to serving on a mine rescue team each member shall complete, at a minimum...

30 CFR 49.18 - Training for mine rescue teams.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Training for mine rescue teams. 49.18 Section... TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines § 49.18 Training for mine rescue teams. (a) Prior to serving on a mine rescue team each member shall complete, at a minimum, an initial...

The Mechanization of Mining.

ERIC Educational Resources Information Center

Marovelli, Robert L.; Karhnak, John M.

1982-01-01

Mechanization of mining is explained in terms of its effect on the mining of coal, focusing on, among others, types of mining, productivity, machinery, benefits to retired miners, fatality rate in underground coal mines, and output of U.S. mining industry. (Author/JN)

Abandoned Uranium Mine (AUM) Trust Mine Points, Navajo Nation, 2016, US EPA Region 9

EPA Pesticide Factsheets

This GIS dataset contains point features that represent mines included in the Navajo Environmental Response Trust. This mine category also includes Priority mines. USEPA and NNEPA prioritized mines based on gamma radiation levels, proximity to homes and potential for water contamination identified in the preliminary assessments. Attributes include mine names, reclaimed status, links to US EPA AUM reports, and the region in which the mine is located. This dataset contains 19 features.

Identifying Catchment-Scale Predictors of Coal Mining Impacts on New Zealand Stream Communities.

PubMed

Clapcott, Joanne E; Goodwin, Eric O; Harding, Jon S

2016-03-01

Coal mining activities can have severe and long-term impacts on freshwater ecosystems. At the individual stream scale, these impacts have been well studied; however, few attempts have been made to determine the predictors of mine impacts at a regional scale. We investigated whether catchment-scale measures of mining impacts could be used to predict biological responses. We collated data from multiple studies and analyzed algae, benthic invertebrate, and fish community data from 186 stream sites, including un-mined streams, and those associated with 620 mines on the West Coast of the South Island, New Zealand. Algal, invertebrate, and fish richness responded to mine impacts and were significantly higher in un-mined compared to mine-impacted streams. Changes in community composition toward more acid- and metal-tolerant species were evident for algae and invertebrates, whereas changes in fish communities were significant and driven by a loss of nonmigratory native species. Consistent catchment-scale predictors of mining activities affecting biota included the time post mining (years), mining density (the number of mines upstream per catchment area), and mining intensity (tons of coal production per catchment area). Mining was associated with a decline in stream biodiversity irrespective of catchment size, and recovery was not evident until at least 30 years after mining activities have ceased. These catchment-scale predictors can provide managers and regulators with practical metrics to focus on management and remediation decisions.

Identifying Catchment-Scale Predictors of Coal Mining Impacts on New Zealand Stream Communities

NASA Astrophysics Data System (ADS)

Clapcott, Joanne E.; Goodwin, Eric O.; Harding, Jon S.

2016-03-01

Coal mining activities can have severe and long-term impacts on freshwater ecosystems. At the individual stream scale, these impacts have been well studied; however, few attempts have been made to determine the predictors of mine impacts at a regional scale. We investigated whether catchment-scale measures of mining impacts could be used to predict biological responses. We collated data from multiple studies and analyzed algae, benthic invertebrate, and fish community data from 186 stream sites, including un-mined streams, and those associated with 620 mines on the West Coast of the South Island, New Zealand. Algal, invertebrate, and fish richness responded to mine impacts and were significantly higher in un-mined compared to mine-impacted streams. Changes in community composition toward more acid- and metal-tolerant species were evident for algae and invertebrates, whereas changes in fish communities were significant and driven by a loss of nonmigratory native species. Consistent catchment-scale predictors of mining activities affecting biota included the time post mining (years), mining density (the number of mines upstream per catchment area), and mining intensity (tons of coal production per catchment area). Mining was associated with a decline in stream biodiversity irrespective of catchment size, and recovery was not evident until at least 30 years after mining activities have ceased. These catchment-scale predictors can provide managers and regulators with practical metrics to focus on management and remediation decisions.

30 CFR 49.13 - Alternative mine rescue capability for small and remote mines.

Code of Federal Regulations, 2011 CFR

2011-07-01

..., DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines... the operator as to the number of miners willing to serve on a mine rescue team; (8) The operator's...

30 CFR 49.13 - Alternative mine rescue capability for small and remote mines.

Code of Federal Regulations, 2014 CFR

2014-07-01

..., DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines... the operator as to the number of miners willing to serve on a mine rescue team; (8) The operator's...

30 CFR 49.13 - Alternative mine rescue capability for small and remote mines.

Code of Federal Regulations, 2012 CFR

2012-07-01

..., DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines... the operator as to the number of miners willing to serve on a mine rescue team; (8) The operator's...

30 CFR 49.13 - Alternative mine rescue capability for small and remote mines.

Code of Federal Regulations, 2010 CFR

2010-07-01

..., DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines... the operator as to the number of miners willing to serve on a mine rescue team; (8) The operator's...

30 CFR 49.13 - Alternative mine rescue capability for small and remote mines.

Code of Federal Regulations, 2013 CFR

2013-07-01

..., DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Coal Mines... the operator as to the number of miners willing to serve on a mine rescue team; (8) The operator's...

Applications of Geomatics in Surface Mining

NASA Astrophysics Data System (ADS)

Blachowski, Jan; Górniak-Zimroz, Justyna; Milczarek, Wojciech; Pactwa, Katarzyna

2017-12-01

In terms of method of extracting mineral from deposit, mining can be classified into: surface, underground, and borehole mining. Surface mining is a form of mining, in which the soil and the rock covering the mineral deposits are removed. Types of surface mining include mainly strip and open-cast methods, as well as quarrying. Tasks associated with surface mining of minerals include: resource estimation and deposit documentation, mine planning and deposit access, mine plant development, extraction of minerals from deposits, mineral and waste processing, reclamation and reclamation of former mining grounds. At each stage of mining, geodata describing changes occurring in space during the entire life cycle of surface mining project should be taken into consideration, i.e. collected, analysed, processed, examined, distributed. These data result from direct (e.g. geodetic) and indirect (i.e. remote or relative) measurements and observations including airborne and satellite methods, geotechnical, geological and hydrogeological data, and data from other types of sensors, e.g. located on mining equipment and infrastructure, mine plans and maps. Management of such vast sources and sets of geodata, as well as information resulting from processing, integrated analysis and examining such data can be facilitated with geomatic solutions. Geomatics is a discipline of gathering, processing, interpreting, storing and delivering spatially referenced information. Thus, geomatics integrates methods and technologies used for collecting, management, processing, visualizing and distributing spatial data. In other words, its meaning covers practically every method and tool from spatial data acquisition to distribution. In this work examples of application of geomatic solutions in surface mining on representative case studies in various stages of mine operation have been presented. These applications include: prospecting and documenting mineral deposits, assessment of land accessibility for a potential large-scale surface mining project, modelling mineral deposit (granite) management, concept of a system for management of conveyor belt network technical condition, project of a geoinformation system of former mining terrains and objects, and monitoring and control of impact of surface mining on mine surroundings with satellite radar interferometry.

Overview of bureau research directed towards surface powered haulage safety

DOE Office of Scientific and Technical Information (OSTI.GOV)

May, J.P.; Aldinger, J.A.

1995-12-31

Surface mining operations, including mills and preparation plants, employ over 260,000 people. This represents a significant contribution to our nation`s economy and an important source of skilled and well-paying jobs. As mine production has shifted from underground to surface, and with continuing advances in underground mine safety, surface mining has unfortunately become the leader in mine fatalities. In 1994 surface mining accidents accounted for 49% of all mine fatalities, followed by underground mining with 37% and mills and preparation plants with 14%. The U.S. Bureau of Mines (USBM) has targeted surface mining as an important research priority to reduce themore » social and economic costs associated with fatalities and lost-work-time injuries. USBM safety research focuses on the development of technologies that can enhance productivity and reduce mining costs through a reduction in the number and severity of mining accidents. This report summarizes a number of completed and ongoing research programs directed towards surface powered haulage--the single largest category of fatalities in surface mining and a major cause of lost workdays. Research products designed for industry are highlighted and future USBM surface mining safety research is discussed.« less

Decision support from local data: creating adaptive order menus from past clinician behavior.

PubMed

Klann, Jeffrey G; Szolovits, Peter; Downs, Stephen M; Schadow, Gunther

2014-04-01

Reducing care variability through guidelines has significantly benefited patients. Nonetheless, guideline-based Clinical Decision Support (CDS) systems are not widely implemented or used, are frequently out-of-date, and cannot address complex care for which guidelines do not exist. Here, we develop and evaluate a complementary approach - using Bayesian Network (BN) learning to generate adaptive, context-specific treatment menus based on local order-entry data. These menus can be used as a draft for expert review, in order to minimize development time for local decision support content. This is in keeping with the vision outlined in the US Health Information Technology Strategic Plan, which describes a healthcare system that learns from itself. We used the Greedy Equivalence Search algorithm to learn four 50-node domain-specific BNs from 11,344 encounters: abdominal pain in the emergency department, inpatient pregnancy, hypertension in the Urgent Visit Clinic, and altered mental state in the intensive care unit. We developed a system to produce situation-specific, rank-ordered treatment menus from these networks. We evaluated this system with a hospital-simulation methodology and computed Area Under the Receiver-Operator Curve (AUC) and average menu position at time of selection. We also compared this system with a similar association-rule-mining approach. A short order menu on average contained the next order (weighted average length 3.91-5.83 items). Overall predictive ability was good: average AUC above 0.9 for 25% of order types and overall average AUC .714-.844 (depending on domain). However, AUC had high variance (.50-.99). Higher AUC correlated with tighter clusters and more connections in the graphs, indicating importance of appropriate contextual data. Comparison with an Association Rule Mining approach showed similar performance for only the most common orders with dramatic divergence as orders are less frequent. This study demonstrates that local clinical knowledge can be extracted from treatment data for decision support. This approach is appealing because: it reflects local standards; it uses data already being captured; and it produces human-readable treatment-diagnosis networks that could be curated by a human expert to reduce workload in developing localized CDS content. The BN methodology captured transitive associations and co-varying relationships, which existing approaches do not. It also performs better as orders become less frequent and require more context. This system is a step forward in harnessing local, empirical data to enhance decision support. Copyright © 2013 Elsevier Inc. All rights reserved.

Decision Support from Local Data: Creating Adaptive Order Menus from Past Clinician Behavior

PubMed Central

Klann, Jeffrey G.; Szolovits, Peter; Downs, Stephen; Schadow, Gunther

2014-01-01

Objective Reducing care variability through guidelines has significantly benefited patients. Nonetheless, guideline-based clinical decision support (CDS) systems are not widely implemented or used, are frequently out-of-date, and cannot address complex care for which guidelines do not exist. Here, we develop and evaluate a complementary approach - using Bayesian network (BN) learning to generate adaptive, context-specific treatment menus based on local order-entry data. These menus can be used as a draft for expert review, in order to minimize development time for local decision support content. This is in keeping with the vision outlined in the US Health Information Technology Strategic Plan, which describes a healthcare system that learns from itself. Materials and Methods We used the Greedy Equivalence Search algorithm to learn four 50-node domain-specific BNs from 11,344 encounters: abdominal pain in the emergency department, inpatient pregnancy, hypertension in the urgent visit clinic, and altered mental state in the intensive care unit. We developed a system to produce situation-specific, rank-ordered treatment menus from these networks. We evaluated this system with a hospital-simulation methodology and computed Area Under the Receiver-Operator Curve (AUC) and average menu position at time of selection. We also compared this system with a similar association-rule-mining approach. Results A short order menu on average contained the next order (weighted average length 3.91–5.83 items). Overall predictive ability was good: average AUC above 0.9 for 25% of order types and overall average AUC .714–.844 (depending on domain). However, AUC had high variance (.50–.99). Higher AUC correlated with tighter clusters and more connections in the graphs, indicating importance of appropriate contextual data. Comparison with an association rule mining approach showed similar performance for only the most common orders with dramatic divergence as orders are less frequent. Discussion and Conclusion This study demonstrates that local clinical knowledge can be extracted from treatment data for decision support. This approach is appealing because: it reflects local standards; it uses data already being captured; and it produces human-readable treatment-diagnosis networks that could be curated by a human expert to reduce workload in developing localized CDS content. The BN methodology captured transitive associations and co-varying relationships, which existing approaches do not. It also performs better as orders become less frequent and require more context. This system is a step forward in harnessing local, empirical data to enhance decision support. PMID:24355978

Factors influencing mine rescue team behaviors.

PubMed

Jansky, Jacqueline H; Kowalski-Trakofler, K M; Brnich, M J; Vaught, C

2016-01-01

A focus group study of the first moments in an underground mine emergency response was conducted by the National Institute for Occupational Safety and Health (NIOSH), Office for Mine Safety and Health Research. Participants in the study included mine rescue team members, team trainers, mine officials, state mining personnel, and individual mine managers. A subset of the data consists of responses from participants with mine rescue backgrounds. These responses were noticeably different from those given by on-site emergency personnel who were at the mine and involved with decisions made during the first moments of an event. As a result, mine rescue team behavior data were separated in the analysis and are reported in this article. By considering the responses from mine rescue team members and trainers, it was possible to sort the data and identify seven key areas of importance to them. On the basis of the responses from the focus group participants with a mine rescue background, the authors concluded that accurate and complete information and a unity of purpose among all command center personnel are two of the key conditions needed for an effective mine rescue operation.

Lunar vertical-shaft mining system

NASA Technical Reports Server (NTRS)

Introne, Steven D. (Editor); Krause, Roy; Williams, Erik; Baskette, Keith; Martich, Frederick; Weaver, Brad; Meve, Jeff; Alexander, Kyle; Dailey, Ron; White, Matt

1994-01-01

This report proposes a method that will allow lunar vertical-shaft mining. Lunar mining allows the exploitation of mineral resources imbedded within the surface. The proposed lunar vertical-shaft mining system is comprised of five subsystems: structure, materials handling, drilling, mining, and planning. The structure provides support for the exploration and mining equipment in the lunar environment. The materials handling subsystem moves mined material outside the structure and mining and drilling equipment inside the structure. The drilling process bores into the surface for the purpose of collecting soil samples, inserting transducer probes, or locating ore deposits. Once the ore deposits are discovered and pinpointed, mining operations bring the ore to the surface. The final subsystem is planning, which involves the construction of the mining structure.

New perspectives on a 140-year legacy of mining and abandoned mine cleanup in the San Juan Mountains, Colorado

USGS Publications Warehouse

Yager, Douglas B.; Fey, David L.; Chapin, Thomas; Johnson, Raymond H.

2016-01-01

The Gold King mine water release that occurred on 5 August 2015 near the historical mining community of Silverton, Colorado, highlights the environmental legacy that abandoned mines have on the environment. During reclamation efforts, a breach of collapsed workings at the Gold King mine sent 3 million gallons of acidic and metal-rich mine water into the upper Animas River, a tributary to the Colorado River basin. The Gold King mine is located in the scenic, western San Juan Mountains, a region renowned for its volcano-tectonic and gold-silver-base metal mineralization history. Prior to mining, acidic drainage from hydrothermally altered areas was a major source of metals and acidity to streams, and it continues to be so. In addition to abandoned hard rock metal mines, uranium mine waste poses a long-term storage and immobilization challenge in this area. Uranium resources are mined in the Colorado Plateau, which borders the San Juan Mountains on the west. Uranium processing and repository sites along the Animas River near Durango, Colorado, are a prime example of how the legacy of mining must be managed for the health and well-being of future generations. The San Juan Mountains are part of a geoenvironmental nexus where geology, mining, agriculture, recreation, and community issues converge. This trip will explore the geology, mining, and mine cleanup history in which a community-driven, watershed-based stakeholder process is an integral part. Research tools and historical data useful for understanding complex watersheds impacted by natural sources of metals and acidity overprinted by mining will also be discussed.

Nome Offshore Mining Information

Science.gov Websites

Lands Coal Regulatory Program Large Mine Permits Mineral Property and Rights Mining Index Land potential safety concerns, prevent overcrowding, and provide for efficient processing of the permits and Regulatory Program Large Mine Permitting Mineral Property Management Mining Fact Sheets Mining Forms APMA

Mine wastes and human health

USGS Publications Warehouse

Plumlee, Geoffrey S.; Morman, Suzette A.

2011-01-01

Historical mining and mineral processing have been linked definitively to health problems resulting from occupational and environmental exposures to mine wastes. Modern mining and processing methods, when properly designed and implemented, prevent or greatly reduce potential environmental health impacts. However, particularly in developing countries, there are examples of health problems linked to recent mining. In other cases, recent mining has been blamed for health problems but no clear links have been found. The types and abundances of potential toxicants in mine wastes are predictably influenced by the geologic characteristics of the deposit being mined. Hence, Earth scientists can help understand, anticipate, and mitigate potential health issues associated with mining and mineral processing.

Coal mine bumps as related to geologic features in the northern part of the Sunnyside District, Carbon County, Utah

USGS Publications Warehouse

Osterwald, Frank W.; Dunrud, C. Richard; Collins, Donley S.

1993-01-01

Coal mine bumps, which are violent, spontaneous, and often catastrophic disruptions of coal and rock, were common in the Sunnyside coal mining district, Utah, before the introduction of protective-engineering methods, modern room-and-pillar retreat mining with continuous mining machines, and particularly modern longwall mining. The coal at Sunnyside, when stressed during mining, fails continuously with many popping, snapping, and banging noises. Although most of the bumps are beneficial because they make mining easier, many of the large ones are dangerous and in the past caused injuries and fatalities, particularly with room- and-pillar mining methods used in the early mining operations. Geologic mapping of underground mine openings revealed many types of deformational features, some pre-mine and some post-mine in age. Stresses resulting from mining are concentrated near the mine openings; if openings are driven at large angles to small pre-mine deformational features, particularly shatter zones in coal, abnormal stress buildups may occur and violent bumps may result. Other geologic features, such as ripple marks, oriented sand grains, intertongued rock contacts, trace fossils, and load casts, also influence the occurrence of bumps by impeding slip of coal and rocks along bedding planes. The stress field in the coal also varies markedly because of the rough ridge and canyon topography. These features may allow excessively large stress components to accumulate. At many places, the stresses that contribute to deformation and failures of mine openings are oriented horizontally. The stratigraphy of the rocks immediately above and below the mined coal bed strongly influences the deformation of the mine openings in response to stress accumulations. Triaxial compressive testing of coal from the Sunnyside No.1 and No.3 Mines indicates that the strength of the coal increases several times as the confining (lateral) stress is increased. Strengths of cores cut from single large blocks of coal vary widely. Although the strengths of coal cores increase slowly at high levels of confining stress, the coal in Sunnyside No. 1 Mine is slightly stronger in laboratory tests than coal in Sunnyside No.3 Mine. The coal in No.1 Mine probably can store larger amounts of stress than coal in the No.3 Mine, which may account for the apparently greater number of violent bumps in No.1 Mine. The strength of coal, and its ability to store stress before failure, may correlate in part with chemical composition, particularly with the amounts of benzene ring compounds in vitrain; coal with relatively large amounts of benzene ring compounds is stronger than coal with lesser amounts of these compounds. Alternatively, the chemical composition of coal may affect its response to stress. Increasing contents of kaolinite in coal appear to reduce its compressive strength at low confining stresses, resulting in easy failures of pillars and ribs in mine openings. Applications of the geologic factors outlined in this report, carefully coupled with advanced modern engineering methods, have markedly reduced the hazards from coal mine bumps and related failures of mine openings at Sunnyside. Similar studies probably could aid in reducing bump-related hazards in other coal mining areas.

Underground gas storage in the Leyden lignite mine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meddles, R.M.

1978-01-01

Underground gas storage in the Leyden lignite mine by Public Service Co. of Colorado was preceded by careful studies of mine records with respect to geologic conditions and investigation of the gas-sealing potential of the rocks surrounding the cavern. The water level in shaft No. 3 in Sept. 1958 was about 100 ft above the coal seam at that point. Wells were drilled into the mine up-dip (east) of the structurally highest point that a mine shaft intersected the coal seams, and gas was injected into the mine, using the mine water as a seal. At least the up-dip partmore » of the mine was gas-tight, and tests were expanded to the rest of the mine, which also proved to be gas-tight. All that remained to complete the preparation of the mine for permanent gas storage was sealing of the old mine shafts.« less

Closedure - Mine Closure Technologies Resource

NASA Astrophysics Data System (ADS)

Kauppila, Päivi; Kauppila, Tommi; Pasanen, Antti; Backnäs, Soile; Liisa Räisänen, Marja; Turunen, Kaisa; Karlsson, Teemu; Solismaa, Lauri; Hentinen, Kimmo

2015-04-01

Closure of mining operations is an essential part of the development of eco-efficient mining and the Green Mining concept in Finland to reduce the environmental footprint of mining. Closedure is a 2-year joint research project between Geological Survey of Finland and Technical Research Centre of Finland that aims at developing accessible tools and resources for planning, executing and monitoring mine closure. The main outcome of the Closedure project is an updatable wiki technology-based internet platform (http://mineclosure.gtk.fi) in which comprehensive guidance on the mine closure is provided and main methods and technologies related to mine closure are evaluated. Closedure also provides new data on the key issues of mine closure, such as performance of passive water treatment in Finland, applicability of test methods for evaluating cover structures for mining wastes, prediction of water effluents from mine wastes, and isotopic and geophysical methods to recognize contaminant transport paths in crystalline bedrock.

Mine Waste at The Kherzet Youcef Mine : Environmental Characterization

NASA Astrophysics Data System (ADS)

Issaad, Mouloud; Boutaleb, Abdelhak; Kolli, Omar

2017-04-01

Mining activity in Algeria has existed since antiquity. But it was very important since the 20th century. This activity has virtually ceased since the beginning of the 1990s, leaving many mine sites abandoned (so-called orphan mines). The abandonment of mining today poses many environmental problems (soil pollution, contamination of surface water, mining collapses...). The mining wastes often occupy large volumes that can be hazardous to the environment and human health, often neglected in the past: Faulting geotechnical implementation, acid mine drainage (AMD), alkalinity, presence of pollutants and toxic substances (heavy metals, cyanide...). The study started already six years ago and it covers all mines located in NE Algeria, almost are stopped for more than thirty years. So the most important is to have an overview of all the study area. After the inventory job of the abandoned mines, the rock drainage prediction will help us to classify sites according to their acid generating potential.

THE EPA/DOE MINE WASTE TECHNOLOGY PROGRAM

EPA Science Inventory

Mining activities in the US (not counting coal) produce between 1-2B tons of mine waste annually. Since many of the ore mines involve sulfide minerals, the production of acid mine drainage (AMD) is a common problem from these abandoned mine sites. The combination of acidity, heav...

30 CFR 57.22102 - Smoking (I-C mines).

Code of Federal Regulations, 2010 CFR

2010-07-01

... Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR METAL AND NONMETAL MINE SAFETY AND HEALTH SAFETY AND HEALTH STANDARDS-UNDERGROUND METAL AND NONMETAL MINES Safety Standards for Methane in Metal and Nonmetal Mines Fire Prevention and Control § 57.22102 Smoking (I-C mines). (a...

PREVENTION OF ACID MINE DRAINAGE GENERATION FROM OPEN-PIT MINE HIGHWALLS

EPA Science Inventory

Exposed, open pit mine highwalls contribute significantly to the production of acid mine

drainage (AMD) thus causing environmental concerns upon closure of an operating mine. Available information on the generation of AMD from open-pit mine highwalls is very limit...

30 CFR 75.389 - Mining into inaccessible areas.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Mining into inaccessible areas. 75.389 Section 75.389 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.389 Mining into...

30 CFR 75.389 - Mining into inaccessible areas.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Mining into inaccessible areas. 75.389 Section 75.389 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES Ventilation § 75.389 Mining into...

Automation and robotics technology for intelligent mining systems

NASA Technical Reports Server (NTRS)

Welsh, Jeffrey H.

1989-01-01

The U.S. Bureau of Mines is approaching the problems of accidents and efficiency in the mining industry through the application of automation and robotics to mining systems. This technology can increase safety by removing workers from hazardous areas of the mines or from performing hazardous tasks. The short-term goal of the Automation and Robotics program is to develop technology that can be implemented in the form of an autonomous mining machine using current continuous mining machine equipment. In the longer term, the goal is to conduct research that will lead to new intelligent mining systems that capitalize on the capabilities of robotics. The Bureau of Mines Automation and Robotics program has been structured to produce the technology required for the short- and long-term goals. The short-term goal of application of automation and robotics to an existing mining machine, resulting in autonomous operation, is expected to be accomplished within five years. Key technology elements required for an autonomous continuous mining machine are well underway and include machine navigation systems, coal-rock interface detectors, machine condition monitoring, and intelligent computer systems. The Bureau of Mines program is described, including status of key technology elements for an autonomous continuous mining machine, the program schedule, and future work. Although the program is directed toward underground mining, much of the technology being developed may have applications for space systems or mining on the Moon or other planets.

Spectral methods to detect surface mines

NASA Astrophysics Data System (ADS)

Winter, Edwin M.; Schatten Silvious, Miranda

2008-04-01

Over the past five years, advances have been made in the spectral detection of surface mines under minefield detection programs at the U. S. Army RDECOM CERDEC Night Vision and Electronic Sensors Directorate (NVESD). The problem of detecting surface land mines ranges from the relatively simple, the detection of large anti-vehicle mines on bare soil, to the very difficult, the detection of anti-personnel mines in thick vegetation. While spatial and spectral approaches can be applied to the detection of surface mines, spatial-only detection requires many pixels-on-target such that the mine is actually imaged and shape-based features can be exploited. This method is unreliable in vegetated areas because only part of the mine may be exposed, while spectral detection is possible without the mine being resolved. At NVESD, hyperspectral and multi-spectral sensors throughout the reflection and thermal spectral regimes have been applied to the mine detection problem. Data has been collected on mines in forest and desert regions and algorithms have been developed both to detect the mines as anomalies and to detect the mines based on their spectral signature. In addition to the detection of individual mines, algorithms have been developed to exploit the similarities of mines in a minefield to improve their detection probability. In this paper, the types of spectral data collected over the past five years will be summarized along with the advances in algorithm development.

Selenium and mining in the Powder River Basin, Wyoming: Phase III - a preliminary survey of selenium concentrations in deer mice (Peromyscus maniculatus) livers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raisbeck, M.L.; Vance, G.F.; Steward, D.G.

1995-09-01

Samples of liver tissue from deer mice trapped on not-yet-mined areas and reclaimed areas at five surface coal mines in the Powder River Basin of northeastern Wyoming were analyzed for selenium. The overall mean concentration of selenium in wet weight liver tissue was 1.685 ppm. The mean value from not-yet-mined areas was 1.437 ppm; the mean value from reclaimed areas was 1.910 ppm (significant at p<0.1016). When one not-yet-mined outlier was removed, significance rose to p<0.0004. Mine-to-mine comparison of samples stratified by type (that is, by not-yet-mined or reclaimed), showed average tissue concentrations from the reclaimed area of Mine 1more » were also higher (p<0.0143) then not-yet-mined area samples at Mine 1. No statistically significant differences were found between mines for samples from not-yet-mined areas, and no statistically significant differences were found between Mines 2, 3, 4, and 5 for samples from reclaimed areas. Multiple analysis of variance using the factors: site (mine) and type (not-yet-mined or reclaimed) was not significantly significant (p<0.2115). Simple linear regression showed that selenium concentrations in dry tissue could easily be predicted from wet tissue selenium (r2=0.9775), demonstrating that percent water in the samples was relatively constant. Animal body weight in general was not a predictor for either wet or dry tissue selenium concentrations, but was related to body weight at the higher tissue concentrations of selenium encountered in samples from the reclaimed area at Mine 1. Mouse body weights at Mine 1 were higher on the reclaimed area than mouse body weights from the not-yet-mined area.« less

78 FR 68783 - Refuge Alternatives for Underground Coal Mines

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-15

... Alternatives for Underground Coal Mines AGENCY: Mine Safety and Health Administration, Labor. ACTION: Reopen... coal mines. The U.S. Court of Appeals for the District of Columbia Circuit remanded a training... for refuge alternatives in underground coal mines. On January 13, 2009, the United Mine Workers of...

30 CFR 780.27 - Reclamation plan: Surface mining near underground mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... RECLAMATION AND OPERATION PLAN § 780.27 Reclamation plan: Surface mining near underground mining. For surface... 30 Mineral Resources 3 2010-07-01 2010-07-01 false Reclamation plan: Surface mining near... ENFORCEMENT, DEPARTMENT OF THE INTERIOR SURFACE COAL MINING AND RECLAMATION OPERATIONS PERMITS AND COAL...