Pollution Induced Community Tolerance(PICT) of Microorganisms in Soil Incubated with Different Levels of PB

Soil microbial activity is adversely affected by pollutants such as heavy metals, antibiotics and pesticides. Organic amendments including sewage sludge, municipal compost and vermicompost are recently used to improve soil structure and fertility. But, these materials contain heavy metals including Pb, Cd, Zn, Ni and Cu that are toxic to soil microorganisms and may lead to occurrence of more tolerant microbes. Among these, Pb is the most abundant and has more negative effect on soil microbial ecology. In this study, Pb levels of 0, 100, 200, 300, 400 and 500 mg Pb [as Pb(NO3)2] per kg soil were added to the pots containing 2 kg of a loamy soil and incubated for 6 months at 25°C with soil moisture of - 0.3 MPa. Dehydrogenase activity of soil as a measure of microbial activity was determined on 15, 30, 90 and 180 days after incubation. Triphenyl tetrazolium chloride (TTC) was used as an electron acceptor in this assay. PICTs (€IC50 values) were calculated for each Pb level and incubation time. Soil microbial activity was decreased by increasing Pb level during 30 days of incubation but the induced tolerance appeared on day 90 and thereafter. During 90 to 180 days of incubation, the PICT was gradually developed by increasing Pb level up to 200 mg kg-1, but the rate of enhancement was steeper at higher concentrations.

DAMQ-Based Approach for Efficiently Using the Buffer Spaces of a NoC Router

In this paper we present high performance dynamically allocated multi-queue (DAMQ) buffer schemes for fault tolerance systems on chip applications that require an interconnection network. Two virtual channels shared the same buffer space. Fault tolerant mechanisms for interconnection networks are becoming a critical design issue for large massively parallel computers. It is also important to high performance SoCs as the system complexity keeps increasing rapidly. On the message switching layer, we make improvement to boost system performance when there are faults involved in the components communication. The proposed scheme is when a node or a physical channel is deemed as faulty, the previous hop node will terminate the buffer occupancy of messages destined to the failed link. The buffer usage decisions are made at switching layer without interactions with higher abstract layer, thus buffer space will be released to messages destined to other healthy nodes quickly. Therefore, the buffer space will be efficiently used in case fault occurs at some nodes.

Creating or Destroying Objects Plan in the Graphplan Framework

At present, intelligent planning in the Graphplan framework is a focus of artificial intelligence. While the Creating or Destroying Objects Planning (CDOP) is one unsolved problem of this field, one of the difficulties, too. In this paper, we study this planning problem and bring forward the idea of transforming objects to propositions, based on which we offer an algorithm, Creating or Destroying Objects in the Graphplan framework (CDOGP). Compared to Graphplan, the new algorithm can solve not only the entire problems that Graphplan do, but also a part of CDOP. It is for the first time that we introduce the idea of object-proposition, and we emphasize the discussion on the representations of creating or destroying objects operator and an algorithm in the Graphplan framework. In addition, we analyze the complexity of this algorithm.

A Case Study of Collective Action in Fishermen's Wives Group (KUNITA), Malaysia

Collective action can be an effective means for local development as well as important strategy to enhance livelihoods especially among rural people. This article explores the level of collective action among members of Fishermen-s Wives Group (KUNITA) in Malaysia. KUNITA was established by the Malaysian Fishery Development Authority (LKIM) with an objective to increase the socio-economic status of fishermen-s families. The members who are mostly the wives and daughters of fishermen are strongly encouraged by LKIM to venture into entrepreneurship activities. The objective of this research was to see the level of collective action among members in KUNITA groups in the state of Selangor. The finding shows that high level of collective action among KUNITA members is strongly based on volunteerism. However, the level of cooperation among members in the group is relatively low. The findings present significant challenges for the group in maintaining the sustainability of KUNITA organization.

Study on the Effect of Sulphur, Glucose, Nitrogen and Plant Residues on the Immobilization of Sulphate-S in Soil

In order to evaluate the relationship between the sulphur (S), glucose (G), nitrogen (N) and plant residues (st), sulphur immobilization and microbial transformation were monitored in five soil samples from 0-30 cm of Bastam farmers fields of Shahrood area following 11 treatments with different levels of Sulphur (S), glucose (G), N and plant residues (wheat straw) in a randomized block design with three replications and incubated over 20, 45 and 60 days, the immobilization of SO4 -2-S presented as a percentage of that added, was inversely related to its addition rate. Additions of glucose and plant residues increased with the C-to-S ratio of the added amendments, irrespective of their origins (glucose and plant residues). In the presence of C sources (glucose or plant residues). N significantly increased the immobilization of SO4 -2-S, whilst the effect of N was insignificant in the absence of a C amendment. In first few days the amounts of added SO4 -2-S immobilized were linearly correlated with the amounts of added S recovered in the soil microbial biomass. With further incubation the proportions of immobilized SO4 -2-S remaining as biomass-S decreased. Decrease in biomass-S was thought to be due to the conversion of biomass-S into soil organic-S. Glucose addition increased the immobilization (microbial utilization and incorporation into the soil organic matter) of native soil SO4 -2-S. However, N addition enhance the mineralization of soil organic-S, increasing the concentration of SO4 - 2-S in soil.

The Determinants of Corporate Cash Holdings in Nigeria: Evidence from General Method of Moments (GMM)

The study examines the determinants of corporate cash holding of non-financial quoted firms in Nigeria using a sample of fifty four non-financial quoted firms listed on the Nigeria Stock Exchange for the period 1995-2009. Data were sourced from the Annual reports of the sampled firms and analyzed using Generalized Method of Moments(GMM). The study finds evidence supportive of a target adjustment model and that firms can not instantaneously adjust towards the target cash level owing to the fact that adjustment cost being costly,. Also, the result shows significant negative relationship between cash holdings and firm size, net working capital, return on asset and bank relationship and positive relationship with growth opportunities, leverage, inventories, account receivables and financial distress. Furthermore, there is no significant relationship between cash holdings and cash flow. In Nigerian setting, most of the variables that are relevant for explaining cash holdings in the Developed countries are found by this study to be relevant also in Nigeria.

HDS: Alumina- Boria Supported Catalysts

Hydrodesulfurization (HDS) of dibenzothiophene (DBT) in a high pressure batch reactor was done at 320 °C on CoMoS/Al2O3-B2O3 (4, 10, and 16 wt. % of Boria) using nhexadecane as solvent, dimethyldisulfide (DMDS) in tetradecane as sulfur agent, and stirring at 1000 rpm. The effects of boria were investigated by using X-ray diffraction (XRD), Temperature programmed desorption (TPD) of ammonia, and Brunauer-Emmet- Teller (BET) experiments. The results showed that the catalyst prepared with low boria content (4 wt. %) had HDS activity (in pseudo first order kinetic constant basis) value ~1.45 times higher to that of CoMoS/Al2O3 catalyst.

The Grey Relational Analysis of the Influence Factors of Profit in Cartoon-s Character Merchandising Rights

This paper constructs a four factors theoretical model of Chinese small and medium enterprises based on the “cartoon characters- reputation - enterprise marketing and management capabilities – protection of the cartoon image - institutional environment" by literature research, case studies and investigation. The empirical study show that the greatest impact on current merchandising rights income is the institutional environment friendliness, followed by marketing and management capabilities, input of character image protection and Cartoon characters- reputation through the real-time grey relational analysis, and the greatest impact on post-merchandising rights profit is Cartoon characters reputation, followed by the institutional environment friendliness, then marketing and management ability and input of character image protection through the time-delay grey relational analysis.

mCRM-s New Opportunities of Customer Satisfaction

This paper aims at a new challenge of customer satisfaction on mobile customer relationship management. In this paper presents a conceptualization of mCRM on its unique characteristics of customer satisfaction. Also, this paper develops an empirical framework in conception of customer satisfaction in mCRM. A single-case study is applied as the methodology. In order to gain an overall view of the empirical case, this paper accesses to invisible and important information of company in this investigation. Interview is the key data source form the main informants of the company through which the issues are identified and the proposed framework is built. It supports the development of customer satisfaction in mCRM; links this theoretical framework into practice; and provides the direction for future research. Therefore, this paper is very useful for the industries as it helps them to understand how customer satisfaction changes the mCRM structure and increase the business competitive advantage. Finally, this paper provides a contribution in practice by linking a theoretical framework in conception of customer satisfaction in mCRM for companies to a practical real case.

GeNS: a Biological Data Integration Platform

The scientific achievements coming from molecular biology depend greatly on the capability of computational applications to analyze the laboratorial results. A comprehensive analysis of an experiment requires typically the simultaneous study of the obtained dataset with data that is available in several distinct public databases. Nevertheless, developing a centralized access to these distributed databases rises up a set of challenges such as: what is the best integration strategy, how to solve nomenclature clashes, how to solve database overlapping data and how to deal with huge datasets. In this paper we present GeNS, a system that uses a simple and yet innovative approach to address several biological data integration issues. Compared with existing systems, the main advantages of GeNS are related to its maintenance simplicity and to its coverage and scalability, in terms of number of supported databases and data types. To support our claims we present the current use of GeNS in two concrete applications. GeNS currently contains more than 140 million of biological relations and it can be publicly downloaded or remotely access through SOAP web services.

Heuristic Continuous-time Associative Memories

In this paper, a novel associative memory model will be proposed and applied to memory retrievals based on the conventional continuous time model. The conventional model presents memory capacity is very low and retrieval process easily converges to an equilibrium state which is very different from the stored patterns. Genetic Algorithms is well-known with the capability of global optimal search escaping local optimum on progress to reach a global optimum. Based on the well-known idea of Genetic Algorithms, this work proposes a heuristic rule to make a mutation when the state of the network is trapped in a spurious memory. The proposal heuristic associative memory show the stored capacity does not depend on the number of stored patterns and the retrieval ability is up to ~ 1.

A Reproduction of Boundary Conditions in Three-Dimensional Continuous Casting Problem

The paper discusses a 3D numerical solution of the inverse boundary problem for a continuous casting process of alloy. The main goal of the analysis presented within the paper was to estimate heat fluxes along the external surface of the ingot. The verified information on these fluxes was crucial for a good design of a mould, effective cooling system and generally the whole caster. In the study an enthalpy-porosity technique implemented in Fluent package was used for modeling the solidification process. In this method, the phase change interface was determined on the basis of the liquid fraction approach. In inverse procedure the sensitivity analysis was applied for retrieving boundary conditions. A comparison of the measured and retrieved values showed a high accuracy of the computations. Additionally, the influence of the accuracy of measurements on the estimated heat fluxes was also investigated.

Kinetics of Palm Oil Cracking in Batch Reactor

The kinetics of palm oil catalytic cracking over aluminum containing mesoporous silica Al-MCM-41 (5% Al) was investigated in a batch autoclave reactor at the temperatures range of 573 – 673 K. The catalyst was prepared by using sol-gel technique and has been characterized by nitrogen adsorption and x-ray diffraction methods. Surface area of 1276 m2/g with average pore diameter of 2.54 nm and pore volume of 0.811 cm3/g was obtained. The experimental catalytic cracking runs were conducted using 50 g of oil and 1 g of catalyst. The reaction pressure was recorded at different time intervals and the data were analyzed using Levenberg- Marquardt (LM) algorithm using polymath software. The results show that the reaction order was found to be -1.5 and activation energy of 3200 J/gmol.

Development and in vitro Characterization of Self-nanoemulsifying Drug Delivery Systems of Valsartan

The present study is aim to prepare and evaluate the selfnanoemulsifying drug delivery (SNEDDS) system of a poorly water soluble drug valsartan in order to achieve a better dissolution rate which would further help in enhancing oral bioavailability. The present research work describes a SNEDDS of valsartan using labrafil M 1944 CS, Tween 80 and Transcutol HP. The pseudoternary phase diagrams with presence and absence of drug were plotted to check for the emulsification range and also to evaluate the effect of valsartan on the emulsification behavior of the phases. The mixtures consisting of oil (labrafil M 1944 CS) with surfactant (tween 80), co-surfactant (Transcutol HP) were found to be optimum formulations. Prepared formulations were evaluated for its particle size distribution, nanoemulsifying properties, robustness to dilution, self emulsication time, turbidity measurement, drug content and invitro dissolution. The optimized formulations are further evaluated for heating cooling cycle, centrifugation studies, freeze thaw cycling, particle size distribution and zeta potential were carried out to confirm the stability of the formed SNEDDS formulations. The prepared formulation revealed t a significant improvement in terms of the drug solubility as compared with marketed tablet and pure drug.

Correction of Infrared Data for Electrical Components on a Board

In this paper, the data correction algorithm is suggested when the environmental air temperature varies. To correct the infrared data in this paper, the initial temperature or the initial infrared image data is used so that a target source system may not be necessary. The temperature data obtained from infrared detector show nonlinear property depending on the surface temperature. In order to handle this nonlinear property, Taylor series approach is adopted. It is shown that the proposed algorithm can reduce the influence of environmental temperature on the components in the board. The main advantage of this algorithm is to use only the initial temperature of the components on the board rather than using other reference device such as black body sources in order to get reference temperatures.

Kinetics of Polyethylene Terephthalate (PET)and Polystyrene (PS) Dynamic Pyrolysis

Thermo-chemical treatment (TCT) such as pyrolysis is getting recognized as a valid route for (i) materials and valuable products and petrochemicals recovery; (ii) waste recycling; and (iii) elemental characterization. Pyrolysis is also receiving renewed attention for its operational, economical and environmental advantages. In this study, samples of polyethylene terephthalate (PET) and polystyrene (PS) were pyrolysed in a microthermobalance reactor (using a thermogravimetric-TGA setup). Both polymers were prepared and conditioned prior to experimentation. The main objective was to determine the kinetic parameters of the depolymerization reactions that occur within the thermal degradation process. Overall kinetic rate constants (ko) and activation energies (Eo) were determined using the general kinetics theory (GKT) method previously used by a number of authors. Fitted correlations were found and validated using the GKT, errors were within ± 5%. This study represents a fundamental step to pave the way towards the development of scaling relationship for the investigation of larger scale reactors relevant to industry.

Combining Molecular Statics with Heat Transfer Finite Difference Method for Analysis of Nanoscale Orthogonal Cutting of Single-Crystal Silicon Temperature Field

This paper uses quasi-steady molecular statics model and diamond tool to carry out simulation temperature rise of nanoscale orthogonal cutting single-crystal silicon. It further qualitatively analyzes temperature field of silicon workpiece without considering heat transfer and considering heat transfer. This paper supposes that the temperature rise of workpiece is mainly caused by two heat sources: plastic deformation heat and friction heat. Then, this paper develops a theoretical model about production of the plastic deformation heat and friction heat during nanoscale orthogonal cutting. After the increased temperature produced by these two heat sources are added up, the acquired total temperature rise at each atom of the workpiece is substituted in heat transfer finite difference equation to carry out heat transfer and calculates the temperature field in each step and makes related analysis.

Elaboration and Optimization of Pellets Used for Precise Glass Grinding

In this work, grinding or microcutting tools in the form of pellets were manufactured using a bounded alumina abrasive grains. The bound used is a vitreous material containing quartz feldspars, kaolinite and a quantity of hematite. The pellets were used in glass grinding process to replace the free abrasive grains lapping process. The study of the elaborated pellets were done to define their effectiveness in the grinding process and to optimize the influence of the pellets elaboration parameters. The obtained results show the existence of an optimal combination of the pellets elaboration parameters for each glass grinding phase (coarse to fine grinding). The final roughness (rms) reached by the elaborated pellets on a BK7 glass surface was about 0.392 μm.

Educational Robotics Constructivism and Modeling of Robots using Reverse Engineering

The project describes the modeling of various architectures mechatronics specifically morphologies of robots in an educational environment. Each structure developed by students of pre-school, primary and secondary was created using the concept of reverse engineering in a constructivist environment, to later be integrated in educational software that promotes the teaching of educational Robotics in a virtual and economic environment.

Unsupervised Texture Classification and Segmentation

An unsupervised classification algorithm is derived by modeling observed data as a mixture of several mutually exclusive classes that are each described by linear combinations of independent non-Gaussian densities. The algorithm estimates the data density in each class by using parametric nonlinear functions that fit to the non-Gaussian structure of the data. This improves classification accuracy compared with standard Gaussian mixture models. When applied to textures, the algorithm can learn basis functions for images that capture the statistically significant structure intrinsic in the images. We apply this technique to the problem of unsupervised texture classification and segmentation.