Studies on removal of metal ions and sulphate reduction using rice husk and Desulfotomaculum nigrificans with reference to remediation of acid mine drainage

The utility of rice husk as an adsorbent for metal ions such as iron, zinc and copper from acid mine water was assessed. The adsorption isotherms exhibited Langmuirian behavior and were endothermic in nature. The free energy values for adsorption of the chosen metal ions onto rice husk were found to be highly negative attesting to favorable interaction. Over 99% Fe3+, 98% of Fe2+ and Zn2+ and 95% Cu2+ uptake was achieved from acid mine water, with a concomitant increase in the pH value by two units using rice husk. The remediation studies carried out on acid mine water and simulated acid mine water pretreated with rice husk indicated successful growth of Desulfotomaculum nigrificans (D. nigrificans). The amount of sulphate bioreduction in acid mine water at an initial pH of 5.3 was enhanced by D. nigrificans from 21% to 40% in the presence of rice husk filtrate supplemented with carbon and nitrogen. In simulated acid mine water with fortified husk filtrate, the sulphate reduction was even more extensive, with an enhancement to 73%. Concurrently, almost 90% Fe2+, 89% Zn2+ and 75% Cu2+ bioremoval was attained from simulated acid mine water. Metal adsorption by rice husk was confirmed in desorption experiments in which almost complete removal of metal ions from the rice husk was achieved after two elutions using 1 M HCl. The possible mechanisms of metal ion adsorption onto rice husk and sulphate reduction using D. nigrificans are discussed.

A thermodynamic interpretation of the zonal arrangement of minerals in the bedded manganese deposits of the Noda tamagawa mine, Japan

Calculated phase relations in the system MnOSi02-C02-02 were used to propose a thermodynamic explanation for the thermal metamorphism of rhodochrosite beds lying between chert strata. The metamorphic MnOS i 0 2 minerals are arranged in order quartz(chert), rhodonite. tephroite and manganosite-hausmannite-pyrochroite rhodonite across the ore bed. The calculation covered temperatures up to 1000 K and pressures up to 5 kb. The zoning was interpreted as the result of a continuous rise in metamorphic temperature. The equilibrium partner of rhodochrosite changed from rhodonite through manganosite. Across the ore bed there are gradients in the chemical potential of MnO and SiO2 but fugacities of volatlle components such as C02. 02 and H20 were probably uniform at any given time and location during formation of the zones. Assuming that the total pressure and the fugacity of C02 were at 1.4 kb and 1.0 1 b. respectively. rhodonite. tephroite and manganosite would have formed at 472. 478 and 629 K.

Performance Evaluation of Underground Mine Communication and Monitoring Devices: Case Studies

Communication and environmental monitoring play a major role in underground mining both from production and safety point of view. However, underground mining communication as well as monitoring devices encounter several challenges because of the nature of underground features and characteristics. Lack of real time information from underground workings may hamper production and create serious safety risks. Proper communication and monitoring devices are inevitable requirements for better production and improved safety. Communication and environmental monitoring devices are basic element of underground mine infrastructure. This paper describes the performance of communication and monitoring devices being used in underground mines. An attempt has been made to assess the safety risks by these devices which may dictate future research directions.

Binding of DNA Nucleobases and Nucleosides with Graphene

Interaction of two different samples of graphene with DNA nucleobases and nucleosides is investigated by isothermal titration calorimetry. The relative interaction energies of the nucleobases decrease in the order guanine (G) > adenine (A) > cytosine (C) > thy mine (T) in aqueous solutions, although the positions of C and T seem to be interchangeable. The same trend is found with the nucleosides. Interaction energies of the A-T and G-C pairs are somewhere between those of the constituent bases. Theoretical calculations including van der Wools interaction and solvation energies give the trend G > A similar to T > C. The magnitudes of the interaction energies of the nucleobases with graphene are similar to those found with single-walled carbon nonotubes.

Development of temperature-tolerant strains of Thiobacillus ferrooxidans to improve bioleaching kinetics

An isolate of Thiobacillus ferrooxidans derived from gold mine water samples was repeatedly subcultured at increasing temperatures (from 30 degrees to 42 degrees C) in 9K medium. The temperature-adapted strain was found to be more efficient in the bioleaching of pyrite mineral than the wild type. When temperature-tolerant strains were cultured repeatedly in 9K medium at 30 degrees C, the temperature tolerance was completely lost, These results indicate that the temperature tolerance was stress-dependent and not a permanent trait of the adapted strain, The potential utility of such temperature-tolerant strains of Thiobacillus ferrooxidans in sulphide mineral dissolution is demonstrated.

Microbial aspects of acid generation and bioremediation with relevance to indian mining

The role of Acidithiobacillus group of bacteria in acid generation and heavy metal dissolution was studied with relevance to some Indian mines. Microorganisms implicated in acid generation such as Acidithiobacillus Acidithicibacillus thiooxidans and Leptospirillum ferrooxidans were isolated from abandoned mines, waste rocks and tailing dumps. Arsenite oxidizing Thiomonas and Bacillus group of bacteria were isolated and their ability to oxidize As (111) to As (V) established. Mine isolated Sulfate reducing bacteria were used to remove dissolved copper, zinc, iron and arsenic from solutions.

Dendritic Poly(ether imine) Based Gene Delivery Vector

The nonviral vector based gene delivery approach is attractive due to advantages associated with molecular-level modifications suitable for optimization of vector properties. In a new class of nonviral gene delivery systems, we herein report the potential of poly(ether Mine) (PETIM) dendrimers to mediate an effective gene delivery function. PETIM dendrimer, constituted with tertiary amine branch points, n-propyl ether linkers and primary amines at their peripheries, exhibits significantly reduced toxicities, over a broad concentration range. The dendrimer complexes pDNA effectively, protects DNA from endosomal damages, and delivers to the cell nucleus. Gene transfection studies, utilizing a reporter plasmid pEGFP-C1 and upon complexation with dendrimer, showed a robust expression of the encoded protein. The study shows that PETIM dendrimers are hitherto unknown novel gene delivery vectors, combining features of poly(ethylene imine)-based polymers and dendrimers, yet are relatively nontoxic and structurally precise.

Enhanced lithium-ion transport in PEG-based composite polymer electrolyte with Mn0.03Zn0.97Al2O4 nanoparticles

The ion conduction and thermal properties of composite solid polymer electrolyte (SPE) comprising Poly(ethylene) Glycol (PEG, mol wt. 2000), lithium perchlorate (LiClO4) and insulating Mn0.03Zn0.97Al2O4 nanoparticle fillers were studied by complex impedance analysis and DSC techniques. The average size of the nanoparticles was determined by powder X-ray diffraction (XRD) using Scherrer's equation and was found to be similar to 8 nm. The same was also determined by TEM imaging and found to be similar to 12 nm. The glass transition temperature T, as measured by differential scanning calorimeter (DSC), showed a minimum at 5 mol% of narroparticles. Fractional crystallinity was determined using DSC. NMR was used to deter-mine crystallinity of a pure PEG sample, which was then used as the standard. Fractional crystallinity X. was the lowest for 5 mol% and beyond. The ionic conductivity of the composite polymer electrolyte containing 5 mol% Mn0.03Zn0.97Al2O4 nanoparticles was found to be 1.82 x 10(-5) S/cm, while for the pristine one, it was 7.27 x 10(-7) S/cm at room temperature. As a function of nanoparticle content, conductivity was observed to go through two maxima, one at around 5 mol% and another shallower one at around 12 mol%. The temperature dependence of conductivity could be divided into two regions, one consistent with Arrhenius behaviour and the other with VTF. We conclude that the enhancement of ionic conductivity on the addition of Mn0.03Zn0.97Al2O4 nanoparticles is a result of reduction in both the T, and the crystallinity. (C) 2002 Elsevier Science B.V. All rights reserved.

Stream-Close: Fast mining of Closed Frequent Itemsets in high speed data streams

With the emergence of large-volume and high-speed streaming data, the recent techniques for stream mining of CFIpsilas (closed frequent itemsets) will become inefficient. When concept drift occurs at a slow rate in high speed data streams, the rate of change of information across different sliding windows will be negligible. So, the user wonpsilat be devoid of change in information if we slide window by multiple transactions at a time. Therefore, we propose a novel approach for mining CFIpsilas cumulatively by making sliding width(ges1) over high speed data streams. However, it is nontrivial to mine CFIpsilas cumulatively over stream, because such growth may lead to the generation of exponential number of candidates for closure checking. In this study, we develop an efficient algorithm, stream-close, for mining CFIpsilas over stream by exploring some interesting properties. Our performance study reveals that stream-close achieves good scalability and has promising results.

Biosorption of heavy metal ions from aqueous and cyanide solutions using fungal biomass

A waste fungal biomass containing killed cells of Aspergillus niger was efficiently used in the removal of toxic metal ions such as nickel, calcium, iron and chromium from aqueous solutions. The role of different parameters such as initial metal ion concentration, solution pH and biomass concentration on biosorption capacity was established. The maximum metal uptake was found to be dependent on solution pH and increased with biomass loading upto 10g/L. The adsorption densities for various metal ions could be arranged as Ca>Cr (III)>Ni>Fe>Cr (VI). The effect of the presence of various metal ions in binary, ternary and quaternary combinations on biosorption was also assessed. Ni uptake was significantly affected, while that of Cr (VI) the least, in the presence of other metal ions. Uptake of base metals from an industrial cyanide effluent was studied using different species of fungi such as Aspergillus niger, Aspergillus terreus and Penicillium funiculosum and yeast such as Saccharomyces cerevisiae which were isolated from a gold mine. Traces of gold present in the cyanide effluent could be efficiently recovered. Among the four base metal contaminants present in the cyanide effluent, zinc was found to be most efficiently biosorbed, followed by iron, copper and lead. The role of both living and dead biomass on biosorption was distinguished and probable mechanisms illustrated.

Mining sentiments from songs using latent dirichlet allocation

Song-selection and mood are interdependent. If we capture a song’s sentiment, we can determine the mood of the listener, which can serve as a basis for recommendation systems. Songs are generally classified according to genres, which don’t entirely reflect sentiments. Thus, we require an unsupervised scheme to mine them. Sentiments are classified into either two (positive/negative) or multiple (happy/angry/sad/...) classes, depending on the application. We are interested in analyzing the feelings invoked by a song, involving multi-class sentiments. To mine the hidden sentimental structure behind a song, in terms of “topics”, we consider its lyrics and use Latent Dirichlet Allocation (LDA). Each song is a mixture of moods. Topics mined by LDA can represent moods. Thus we get a scheme of collecting similar-mood songs. For validation, we use a dataset of songs containing 6 moods annotated by users of a particular website.

Discovering Math APIs by Mining Unit Tests

In today's API-rich world, programmer productivity depends heavily on the programmer's ability to discover the required APIs. In this paper, we present a technique and tool, called MATHFINDER, to discover APIs for mathematical computations by mining unit tests of API methods. Given a math expression, MATHFINDER synthesizes pseudo-code to compute the expression by mapping its subexpressions to API method calls. For each subexpression, MATHFINDER searches for a method such that there is a mapping between method inputs and variables of the subexpression. The subexpression, when evaluated on the test inputs of the method under this mapping, should produce results that match the method output on a large number of tests. We implemented MATHFINDER as an Eclipse plugin for discovery of third-party Java APIs and performed a user study to evaluate its effectiveness. In the study, the use of MATHFINDER resulted in a 2x improvement in programmer productivity. In 96% of the subexpressions queried for in the study, MATHFINDER retrieved the desired API methods as the top-most result. The top-most pseudo-code snippet to implement the entire expression was correct in 93% of the cases. Since the number of methods and unit tests to mine could be large in practice, we also implement MATHFINDER in a MapReduce framework and evaluate its scalability and response time.

Association Rule Sharing Model for Privacy Preservation and Collaborative Data Mining Efficiency

The disclosure of information and its misuse in Privacy Preserving Data Mining (PPDM) systems is a concern to the parties involved. In PPDM systems data is available amongst multiple parties collaborating to achieve cumulative mining accuracy. The vertically partitioned data available with the parties involved cannot provide accurate mining results when compared to the collaborative mining results. To overcome the privacy issue in data disclosure this paper describes a Key Distribution-Less Privacy Preserving Data Mining (KDLPPDM) system in which the publication of local association rules generated by the parties is published. The association rules are securely combined to form the combined rule set using the Commutative RSA algorithm. The combined rule sets established are used to classify or mine the data. The results discussed in this paper compare the accuracy of the rules generated using the C4. 5 based KDLPPDM system and the CS. 0 based KDLPPDM system using receiver operating characteristics curves (ROC).