Application of data mining for assessment of material properties : creep behavior of high-temperature steels

Magdeburg, Univ., Fak. für Maschinenbau, Diss., 2009

On utilising change over time in data mining

Magdeburg, Univ., Fak. für Informatik, Diss., 2013

Malaria entomological inoculation rates in gold mining areas of Southern Venezuela

A longitudinal study of malaria vectors aiming to describe the intensity of transmission was carried out in five villages of Southern Venezuela between January 1999-April 2000. The man-biting, sporozoite and entomological inoculation rates (EIR) were calculated based on 121 all-night collections of anophelines landing on humans, CDC light traps and ultra violet up-draft traps. A total of 6,027 female mosquitoes representing seven species were collected. The most abundant species were Anopheles marajoara Galvão & Damasceno (56.7%) and Anopheles darlingi Root (33%), which together accounted for 89.7% of the total anophelines collected. The mean biting rate for An. marajoara was 1.27 (SD + 0.81); it was 0.74 (SD + 0.91) for An. darlingand 0.11 (SD + 0.10) for Anopheles neomaculipalpus Curry and the overall biting rate was 2.29 (SD + 1.06). A total of 5,886 mosquitoes collected by all three methods were assayed by ELISA and 28 pools, equivalent to 28 mosquitoes, yielded positive results for Plasmodium spp. CS protein. An. neomaculipalpus had the highest sporozoite rate 0.84% (3/356), followed by An. darlingi 0.82% (16/1,948) and An. marajoara 0.27% (9/3,332). The overall sporozoite rate was 0.48% (28/5,886). The rates of infection by Plasmodium species in mosquitoes were 0.37% (22/5,886) for Plasmodium vivax(Grassi & Feletti) and 0.10% (6/5,886) for Plasmodium falciparum (Welch). The estimated overall EIR for An. darling was 2.21 infective bites/person/year, 1.25 for An. marajoara and 0.34 for An. neomaculipalpus. The overall EIR was four infective bites/person/year. The biting rate, the sporozoite rate and the EIR are too low to be indicators of the efficacy of control campaigns in this area.

Inferences about the global scenario of human T-cell lymphotropic virus type 1 infection using data mining of viral sequences

Human T-cell lymphotropic virus type 1 (HTLV-1) is mainly associated with two diseases: tropical spastic paraparesis/HTLV-1-associated myelopathy (TSP/HAM) and adult T-cell leukaemia/lymphoma. This retrovirus infects five-10 million individuals throughout the world. Previously, we developed a database that annotates sequence data from GenBank and the present study aimed to describe the clinical, molecular and epidemiological scenarios of HTLV-1 infection through the stored sequences in this database. A total of 2,545 registered complete and partial sequences of HTLV-1 were collected and 1,967 (77.3%) of those sequences represented unique isolates. Among these isolates, 93% contained geographic origin information and only 39% were related to any clinical status. A total of 1,091 sequences contained information about the geographic origin and viral subtype and 93% of these sequences were identified as subtype “a”. Ethnicity data are very scarce. Regarding clinical status data, 29% of the sequences were generated from TSP/HAM and 67.8% from healthy carrier individuals. Although the data mining enabled some inferences about specific aspects of HTLV-1 infection to be made, due to the relative scarcity of data of available sequences, it was not possible to delineate a global scenario of HTLV-1 infection.

Malaria in gold-mining areas in Colombia

Gold-mining may play an important role in the maintenance of malaria worldwide. Gold-mining, mostly illegal, has significantly expanded in Colombia during the last decade in areas with limited health care and disease prevention. We report a descriptive study that was carried out to determine the malaria prevalence in gold-mining areas of Colombia, using data from the public health surveillance system (National Health Institute) during the period 2010-2013. Gold-mining was more prevalent in the departments of Antioquia, Córdoba, Bolívar, Chocó, Nariño, Cauca, and Valle, which contributed 89.3% (270,753 cases) of the national malaria incidence from 2010-2013 and 31.6% of malaria cases were from mining areas. Mining regions, such as El Bagre, Zaragoza, and Segovia, in Antioquia, Puerto Libertador and Montelíbano, in Córdoba, and Buenaventura, in Valle del Cauca, were the most endemic areas. The annual parasite index (API) correlated with gold production (R2 0.82, p < 0.0001); for every 100 kg of gold produced, the API increased by 0.54 cases per 1,000 inhabitants. Lack of malaria control activities, together with high migration and proliferation of mosquito breeding sites, contribute to malaria in gold-mining regions. Specific control activities must be introduced to control this significant source of malaria in Colombia.

Tannery and coal mining waste disposal on soil

Tannery residues and coal mine waste are heavily polluting sources in Brazil, mainly in the Southern States of Rio Grande do Sul and Santa Catarina. In order to study the effects of residues of chrome leather tanning (sludge and leather shavings) and coal waste on soybean and maize crops, a field experiment is in progress since 1996, at the Federal University of Rio Grande do Sul Experimental Station, county of Eldorado do Sul, Brazil. The residues were applied twice (growing seasons 1996/97 and 1999/00). The amounts of tannery residues were applied according to their neutralizing value, at rates of up to 86.8 t ha-1, supplying from 671 to 1.342 kg ha-1 Cr(III); coal waste was applied at a total rate of 164 t ha-1. Crop yield and dry matter production were evaluated, as well as the nutrients (N, P, K, Ca, Mg, Cu and Zn) and Cr contents. Crop yields with tannery sludge application were similar to those obtained with N and lime supplied with mineral amendments. Plant Cr absorption did not increase significantly with the residue application. Tannery sludge can be used also to neutralize the high acidity developed in the soil by coal mine waste.

Community Policing in Switzerland's Major Urban Areas: An Observational Study of the Implementation and Impact Using Geospatial Data Mining

La présente étude est à la fois une évaluation du processus de la mise en oeuvre et des impacts de la police de proximité dans les cinq plus grandes zones urbaines de Suisse - Bâle, Berne, Genève, Lausanne et Zurich. La police de proximité (community policing) est à la fois une philosophie et une stratégie organisationnelle qui favorise un partenariat renouvelé entre la police et les communautés locales dans le but de résoudre les problèmes relatifs à la sécurité et à l'ordre public. L'évaluation de processus a analysé des données relatives aux réformes internes de la police qui ont été obtenues par l'intermédiaire d'entretiens semi-structurés avec des administrateurs clés des cinq départements de police, ainsi que dans des documents écrits de la police et d'autres sources publiques. L'évaluation des impacts, quant à elle, s'est basée sur des variables contextuelles telles que des statistiques policières et des données de recensement, ainsi que sur des indicateurs d'impacts construit à partir des données du Swiss Crime Survey (SCS) relatives au sentiment d'insécurité, à la perception du désordre public et à la satisfaction de la population à l'égard de la police. Le SCS est un sondage régulier qui a permis d'interroger des habitants des cinq grandes zones urbaines à plusieurs reprises depuis le milieu des années 1980. L'évaluation de processus a abouti à un « Calendrier des activités » visant à créer des données de panel permettant de mesurer les progrès réalisés dans la mise en oeuvre de la police de proximité à l'aide d'une grille d'évaluation à six dimensions à des intervalles de cinq ans entre 1990 et 2010. L'évaluation des impacts, effectuée ex post facto, a utilisé un concept de recherche non-expérimental (observational design) dans le but d'analyser les impacts de différents modèles de police de proximité dans des zones comparables à travers les cinq villes étudiées. Les quartiers urbains, délimités par zone de code postal, ont ainsi été regroupés par l'intermédiaire d'une typologie réalisée à l'aide d'algorithmes d'apprentissage automatique (machine learning). Des algorithmes supervisés et non supervisés ont été utilisés sur les données à haute dimensionnalité relatives à la criminalité, à la structure socio-économique et démographique et au cadre bâti dans le but de regrouper les quartiers urbains les plus similaires dans des clusters. D'abord, les cartes auto-organisatrices (self-organizing maps) ont été utilisées dans le but de réduire la variance intra-cluster des variables contextuelles et de maximiser simultanément la variance inter-cluster des réponses au sondage. Ensuite, l'algorithme des forêts d'arbres décisionnels (random forests) a permis à la fois d'évaluer la pertinence de la typologie de quartier élaborée et de sélectionner les variables contextuelles clés afin de construire un modèle parcimonieux faisant un minimum d'erreurs de classification. Enfin, pour l'analyse des impacts, la méthode des appariements des coefficients de propension (propensity score matching) a été utilisée pour équilibrer les échantillons prétest-posttest en termes d'âge, de sexe et de niveau d'éducation des répondants au sein de chaque type de quartier ainsi identifié dans chacune des villes, avant d'effectuer un test statistique de la différence observée dans les indicateurs d'impacts. De plus, tous les résultats statistiquement significatifs ont été soumis à une analyse de sensibilité (sensitivity analysis) afin d'évaluer leur robustesse face à un biais potentiel dû à des covariables non observées. L'étude relève qu'au cours des quinze dernières années, les cinq services de police ont entamé des réformes majeures de leur organisation ainsi que de leurs stratégies opérationnelles et qu'ils ont noué des partenariats stratégiques afin de mettre en oeuvre la police de proximité. La typologie de quartier développée a abouti à une réduction de la variance intra-cluster des variables contextuelles et permet d'expliquer une partie significative de la variance inter-cluster des indicateurs d'impacts avant la mise en oeuvre du traitement. Ceci semble suggérer que les méthodes de géocomputation aident à équilibrer les covariables observées et donc à réduire les menaces relatives à la validité interne d'un concept de recherche non-expérimental. Enfin, l'analyse des impacts a révélé que le sentiment d'insécurité a diminué de manière significative pendant la période 2000-2005 dans les quartiers se trouvant à l'intérieur et autour des centres-villes de Berne et de Zurich. Ces améliorations sont assez robustes face à des biais dus à des covariables inobservées et covarient dans le temps et l'espace avec la mise en oeuvre de la police de proximité. L'hypothèse alternative envisageant que les diminutions observées dans le sentiment d'insécurité soient, partiellement, un résultat des interventions policières de proximité semble donc être aussi plausible que l'hypothèse nulle considérant l'absence absolue d'effet. Ceci, même si le concept de recherche non-expérimental mis en oeuvre ne peut pas complètement exclure la sélection et la régression à la moyenne comme explications alternatives. The current research project is both a process and impact evaluation of community policing in Switzerland's five major urban areas - Basel, Bern, Geneva, Lausanne, and Zurich. Community policing is both a philosophy and an organizational strategy that promotes a renewed partnership between the police and the community to solve problems of crime and disorder. The process evaluation data on police internal reforms were obtained through semi-structured interviews with key administrators from the five police departments as well as from police internal documents and additional public sources. The impact evaluation uses official crime records and census statistics as contextual variables as well as Swiss Crime Survey (SCS) data on fear of crime, perceptions of disorder, and public attitudes towards the police as outcome measures. The SCS is a standing survey instrument that has polled residents of the five urban areas repeatedly since the mid-1980s. The process evaluation produced a "Calendar of Action" to create panel data to measure community policing implementation progress over six evaluative dimensions in intervals of five years between 1990 and 2010. The impact evaluation, carried out ex post facto, uses an observational design that analyzes the impact of the different community policing models between matched comparison areas across the five cities. Using ZIP code districts as proxies for urban neighborhoods, geospatial data mining algorithms serve to develop a neighborhood typology in order to match the comparison areas. To this end, both unsupervised and supervised algorithms are used to analyze high-dimensional data on crime, the socio-economic and demographic structure, and the built environment in order to classify urban neighborhoods into clusters of similar type. In a first step, self-organizing maps serve as tools to develop a clustering algorithm that reduces the within-cluster variance in the contextual variables and simultaneously maximizes the between-cluster variance in survey responses. The random forests algorithm then serves to assess the appropriateness of the resulting neighborhood typology and to select the key contextual variables in order to build a parsimonious model that makes a minimum of classification errors. Finally, for the impact analysis, propensity score matching methods are used to match the survey respondents of the pretest and posttest samples on age, gender, and their level of education for each neighborhood type identified within each city, before conducting a statistical test of the observed difference in the outcome measures. Moreover, all significant results were subjected to a sensitivity analysis to assess the robustness of these findings in the face of potential bias due to some unobserved covariates. The study finds that over the last fifteen years, all five police departments have undertaken major reforms of their internal organization and operating strategies and forged strategic partnerships in order to implement community policing. The resulting neighborhood typology reduced the within-cluster variance of the contextual variables and accounted for a significant share of the between-cluster variance in the outcome measures prior to treatment, suggesting that geocomputational methods help to balance the observed covariates and hence to reduce threats to the internal validity of an observational design. Finally, the impact analysis revealed that fear of crime dropped significantly over the 2000-2005 period in the neighborhoods in and around the urban centers of Bern and Zurich. These improvements are fairly robust in the face of bias due to some unobserved covariate and covary temporally and spatially with the implementation of community policing. The alternative hypothesis that the observed reductions in fear of crime were at least in part a result of community policing interventions thus appears at least as plausible as the null hypothesis of absolutely no effect, even if the observational design cannot completely rule out selection and regression to the mean as alternative explanations.

Replication of an ivg protocol to estimate bioaccessible arsenic in materials from a gold mining area in Brazil

Tests for bioaccessibility are useful in human health risk assessment. No research data with the objective of determining bioaccessible arsenic (As) in areas affected by gold mining and smelting activities have been published so far in Brazil. Samples were collected from four areas: a private natural land reserve of Cerrado; mine tailings; overburden; and refuse from gold smelting of a mining company in Paracatu, Minas Gerais. The total, bioaccessible and Mehlich-1-extractable As levels were determined. Based on the reproducibility and the accuracy/precision of the in vitro gastrointestinal (IVG) determination method of bioaccessible As in the reference material NIST 2710, it was concluded that this procedure is adequate to determine bioaccessible As in soil and tailing samples from gold mining areas in Brazil. All samples from the studied mining area contained low percentages of bioaccessible As.

Perennial grasses for recovery of the aggregation capacity of a reconstructed soil in a coal mining area in southern Brazil

The construction of a soil after surface coal mining involves heavy machinery traffic during the topographic regeneration of the area, resulting in compaction of the relocated soil layers. This leads to problems with water infiltration and redistribution along the new profile, causing water erosion and consequently hampering the revegetation of the reconstructed soil. The planting of species useful in the process of soil decompaction is a promising strategy for the recovery of the soil structural quality. This study investigated the influence of different perennial grasses on the recovery of reconstructed soil aggregation in a coal mining area of the Companhia Riograndense de Mineração, located in Candiota-RS, which were planted in September/October 2007. The treatments consisted of planting: T1- Cynodon dactylon cv vaquero; T2 - Urochloa brizantha; T3 - Panicum maximun; T4 - Urochloa humidicola; T5 - Hemarthria altissima; T6 - Cynodon dactylon cv tifton 85. Bare reconstructed soil, adjacent to the experimental area, was used as control treatment (T7) and natural soil adjacent to the mining area covered with native vegetation was used as reference area (T8). Disturbed and undisturbed soil samples were collected in October/2009 (layers 0.00-0.05 and 0.10-0.15 m) to determine the percentage of macro- and microaggregates, mean weight diameter (MWD) of aggregates, organic matter content, bulk density, and macro- and microporosity. The lower values of macroaggregates and MWD in the surface than in the subsurface layer of the reconstructed soil resulted from the high degree of compaction caused by the traffic of heavy machinery on the clay material. After 24 months, all experimental grass treatments showed improvements in soil aggregation compared to the bare reconstructed soil (control), mainly in the 0.00-0.05 m layer, particularly in the two Urochloa treatments (T2 and T4) and Hemarthria altissima (T5). However, the great differences between the treatments with grasses and natural soil (reference) indicate that the recovery of the pre-mining soil structure could take decades.

Organic Matter Fractions and Quality of the Surface Layer of a Constructed and Vegetated Soil After Coal Mining. I - Humic Substances and Chemical Characterization

After open coal mining, soils are “constructed”, which usually contain low levels and quality of organic matter (OM). Therefore, the use of plant species for revegetation and reclamation of degraded areas is essential. This study evaluated the distribution of carbon (C) in the chemical fractions as well as the chemical characteristics and humification degree of OM in a soil constructed after coal mining under cultivation of perennial grasses. The experiment was established in 2003 with the following treatments: Hemarthria altissima (T1), Paspalum notatum (T2), Cynodon dactilon (T3), Urochloa brizantha (T4), bare constructed soil (T5), and natural soil (T6). In 2009, soil samples were collected from the 0.00-0.03 m layer and the total organic carbon stock (TOC) and C stock in the chemical fractions: acid extract (CHCl), fulvic acid (CFA), humic acid (CHA), and humin (CHU) were determined. The humic acid (HA) fraction was characterized by infrared spectroscopy and the laser-induced fluorescence index (ILIF) of OM was also calculated. After six years, differences were only observed in the CHA stocks, which were highest in T1 (0.89 Mg ha-1) and T4 (1.06 Mg ha-1). The infrared spectra of HA in T1, T2 and T4 were similar to T6, with greater contribution of aliphatic organic compounds than in the other treatments. In this way, ILIF decreased in the sequence T5>T3>T4>T1>T2>T6, indicating higher OM humification in T3 and T5 and more labile OM in the other treatments. Consequently, the potential of OM quality recovery in the constructed soil was greatest in treatments T1 and T4.

Organic Matter Fractions and Quality of the Surface Layer of a Constructed and Vegetated Soil After Coal Mining. II - Physical Compartments and Carbon Management Index

Soils constructed after mining often have low carbon (C) stocks and low quality of organic matter (OM). Cover crops are decisive for the recovery process of these stocks, improving the quality of constructed soils. Therefore, the goal of this study was to evaluate the effect of cover crops on total organic C (TOC) stocks, C distribution in physical fractions of OM and the C management index (CMI) of a soil constructed after coal mining. The experiment was initiated in 2003 with six treatments: Hemarthria altissima (T1), Paspalum notatum (T2), Cynodon dactylon (T3), Urochloa brizantha (T4), bare constructed soil (T5), and natural soil (T6). Soil samples were collected in 2009 from the 0.00-0.03 m layer, and the TOC and C stocks in the physical particle size fractions (carbon in the coarse fraction - CCF, and mineral-associated carbon - MAC) and density fractions (free light fraction - FLF; occluded light fraction - OLF, and heavy fraction - HF) of OM were determined. The CMI components: carbon pool index (CPI), lability (L) and lability index (LI) were estimated by both fractionation methods. No differences were observed between TOC, CCF and MAC stocks. The lowest C stocks in FLF and OLF fractions were presented by T2, 0.86 and 0.61 Mg ha-1, respectively. The values of TOC stock, C stock in physical fractions and CMI were intermediate, greater than T5 and lower than T6 in all treatments, indicating the partial recovery of soil quality. As a result of the better adaptation of the species Hemarthria and Brizantha, resulting in greater accumulation of labile organic material, the CPI, L, LI and CMI values were higher in these treatments, suggesting a greater potential of these species for recovery of constructed soils.

Rhizobia Isolated from Coal Mining Areas in the Nodulation and Growth of Leguminous Trees

ABSTRACT An alternative for recovery of areas degraded by coal mining is revegetation with rapidly growing leguminous trees, which often do not establish in low fertility soils. The objective of this study was to evaluate the efficiency of native rhizobia isolated from coal mining areas in the nodulation and growth of leguminous trees. We isolated 19 strains of rhizobia from a degraded soil near Criciúma, SC, Brazil, and evaluated the nodulation and growth-promoting capacity of the inoculated isolates for bracatinga (Mimosa scabrella), maricá (M. bimucronata) and angico-vermelho (Parapiptadenia rigida). Isolates UFSC-B2, B6, B8, B9, B11 and B16 were able to nodulate bracatinga, providing average increases of 165 % in shoot dry matter, with a significant contribution to N accumulation. Isolates UFSC-B5, B12, and M8 favored nodulation and growth of maricá, especially isolate UFSC-B12, which promoted increases of 370 % in N accumulation compared to treatment with N fertilizer. All strains were inefficient in promoting growth and N uptake by angico-vermelho. In conclusion, isolation and use of selected rhizobia for bracatinga and maricá plant inoculation can contribute to the growth and accumulation of N, with prospects for use in programs for revegetation of degraded soils in coal mining areas.

A process for mining science & technology documents databases, illustrated for the case of "knowledge discovery and data mining"

This paper presents a process of mining research & development abstract databases to profile current status and to project potential developments for target technologies, The process is called "technology opportunities analysis." This article steps through the process using a sample data set of abstracts from the INSPEC database on the topic o "knowledge discovery and data mining." The paper offers a set of specific indicators suitable for mining such databases to understand innovation prospects. In illustrating the uses of such indicators, it offers some insights into the status of knowledge discovery research*.

Inteligência obtida pela aplicação de data mining em base de teses francesas sobre o Brasil

O assunto Brasil foi analisado na base de teses francesas DocThèses, compreendendo os anos de 1969 a 1999. Utilizou-se a técnica de Data Mining como ferramenta para obter inteligência e conhecimento. O software utilizado para a limpeza da base DocThèses foi o Infotrans, e, para a preparação dos dados, empregou-se o Dataview. Os resultados da análise foram ilustrados com a aplicação dos pressupostos da Lei de Zipf, classificando-se as informações em trivial, interessante e ruído, conforme a distribuição de freqüência. Conclui-se que a técnica do Data Mining associada a softwares especialistas é uma poderosa aliada no emprego de inteligência no processo decisório em todos os níveis, inclusive o nível macro, pois oferece subsídios para a consolidação, investimento e desenvolvimento de ações e políticas.

Mercury in soils and sediments from gold mining liabilities in Southern Amazonia

The 1980-1990 Amazonian gold rush left an enormous liability that increasingly has been substituted by developing fish aquaculture. This work aimed at the identification of the mercury levels in the environment, associated with fish farms located in the North of Mato Grosso State, Southern Amazon. Sediment and soil samples were analyzed for total organic carbon and total mercury. Results indicate that the chemical characteristics of the sediment largely depend on the management procedures of the fish pond (liming, fish food used and fish population). The soils presented relatively low concentrations when compared with other data from the literature.