Theoretical kinetic study of the reaction between dimethyl disulfide and OH radicals

The potential energy profile of the reaction between dimethyl disulfide and OH^? radicals is explored by utilizing ab initio and hybrid meta density functional theory methods. Having the energies and structural data of the stationary points, statistical rate theories, such as transition state theory and variable reaction coordinate-transition state theory, are employed to compute the overall rate constants, and discuss the mechanism and product channels. On the basis of the calculations, the overall rate coefficient is predicted to be 2.49?×?10^?10?cm³?molecule^?1?s^?1 at 298?K. It is found that in the most favorable pathway, the reaction proceeds via formation of the relatively unstable intermediate CH₃S^?(OH)SCH₃ decomposing rapidly to yield CH₃S^?+CH₃SOH.     

Beta-lactamase-producing mutants of Streptococcus cremoris

Penicillin-resistant mutants were isolated for six strains of Streptococcus cremoris used in commercial Cheddar cheese manufacture after treatment with N-methyl-N-nitro-N-nitrosoguanidine. The resistant mutants had an elevated minimal growth inhibitory concentration, 2.5 micrograms (4.13 units)/ml, for penicillin G and other beta-lactam antibiotics as compared with the penicillin-susceptible parent strains, which were each sensitive to .05 micrograms (.08 units)/ml. Penicillin resistance was due to the production of beta-lactamase. Plasmid DNA was not demonstrated in partially purified lysates of four mutants. Mutants had normal cellular morphology but altered phage sensitivity patterns. All except one strain were able to support complete phage adsorption. Resistance was retained after 20 passages in absence of penicillin.     

Temporal and Spatial Assessment of Supply and Demand of the Water-yield Ecosystem Service for Water Scarcity Management in Arid to Semi-arid Ecosystems

Water scarcity is one of the problems affecting people’s livelihoods in arid and semi-arid areas, requiring a sustainable balance between water demands and water resources. This study was carried out to assess temporal and spatial distribution of water supply and demand in order to help managers to overcome water scarcity in Jiroft basin, southeastern Iran. Spatial supply and demand of water were mapped and standardized rainfall index (SPI) was used to assess drought for a 20 years period (1994–2014). Supply and demand of water were matched in 23% of the basin area, mostly concentrated in the cold zones. Water supply was reduced up to 80% during dry years, declining water supply-demand matching to 5% of the basin area. Shrub-grass rangelands and deciduous woodlands were the most valuable land covers for conservation with $ 1,100 and $ 936 per hectare water prices respectively. Water value dropped more than 72% in mismanaged ecosystems (p?<?0.01). Our finding showed that water supply-demand ratio can be used as a proxy of ecosystem health and water-yield, which can provide a good information for water resources managers to reduce the threats of water scarcity in arid and semi-arid regions.

     

Design,Facile Synthesis and Characterization of Porphyrin-Zirconium-Ferrite@SiO2 Core-Shell and Catalytic Application in Cyclohexane Oxidation

Silicon - In this study, a new magnetic ZrFe2O4@SiO2-TCPP nanocatalyst with high efficiency was used for the oxidation of cyclohexane to cyclohexanone (Ke) and cyclohexanol (Al). The mesoporous...     

Fuzzy logic controller and cascade inverter for direct torque control of IM

In this paper, a five-level cascaded H-bridge multilevel inverters topology is applied on induction motor control known as direct torque control (DTC) strategy. More inverter states can be generated by a five-level inverter which improves voltage selection capability. This paper also introduces two different control methods to select the appropriate output voltage vector for reducing the torque and flux error to zero. The first is based on the conventional DTC scheme using a pair of hysteresis comparators and look up table to select the output voltage vector for controlling the torque and flux. The second is based on a new fuzzy logic controller using Sugeno as the inference method to select the output voltage vector by replacing the hysteresis comparators and lookup table in the conventional DTC, to which the results show more reduction in torque ripple and feasibility of smooth stator current. By using Matlab/Simulink, it is verified that using five-level inverter in DTC drive can reduce the torque ripple in comparison with conventional DTC, and further torque ripple reduction is obtained by applying fuzzy logic controller. The simulation results have also verified that using a fuzzy controller instead of a hysteresis controller has resulted in reduction in the flux ripples significantly as well as reduces the total harmonic distortion of the stator current to below 4 %.     

THE EFFECT OF PRECIPITATION PARAMETERS ON PREPARATION OF LITHIUM FLUORIDE (LIF) NANO-POWDER

Lithium fluoride powder (LiF) is a white powder with a density of 2.64 gr/cm³ and a melting point of 848°C. This powder has several applications such as flux, glaze, soldering, and aluminum melting process, but one of the most important uses of this powder is its application in dosimetry. The commercial powders currently used for this purpose have average sizes of 5 to 10 micrometers; the objective of this research is to produce LiF powder with nano-metric particle size. In this study, the reaction of LiOH + HF → LiF + H₂O has been selected from among several reactions that were able to produce LiF powder, and some precipitation parameters such as temperature, time, agitation type, and supersaturation degree have been controlled. The morphology, phase analysis, and particle size distribution of the resulting powders were analyzed by SEM, XRD, and LPSA. Finally, lithium fluoride nano-powder was synthesized at a temperature of 25°C, pH about 2-3, reaction time less than 1 s, and agitation by ultrasonic bath.     

NN-based Prediction Interval for Nonlinear Processes Controller

Neural networks (NNs) are extensively used in modelling, optimization, and control of nonlinear plants. NN-based inverse type point prediction models are commonly used for nonlinear process control. However, prediction errors (root mean square error (RMSE), mean absolute percentage error (MAPE) etc.) significantly increase in the presence of disturbances and uncertainties. In contrast to point forecast, prediction interval (PI)-based forecast bears extra information such as the prediction accuracy. The PI provides tighter upper and lower bounds with considering uncertainties due to the model mismatch and time dependent or time independent noises for a given confidence level. The use of PIs in the NN controller (NNC) as additional inputs can improve the controller performance. In the present work, the PIs are utilized in control applications, in particular PIs are integrated in the NN internal model-based control framework. A PI-based model that developed using lower upper bound estimation method (LUBE) is used as an online estimator of PIs for the proposed PI-based controller (PIC). PIs along with other inputs for a traditional NN are used to train the PIC to predict the control signal. The proposed controller is tested for two case studies. These include, a chemical reactor, which is a continuous stirred tank reactor (case 1) and a numerical nonlinear plant model (case 2). Simulation results reveal that the tracking performance of the proposed controller is superior to the traditional NNC in terms of setpoint tracking and disturbance rejections. More precisely, 36% and 15% improvements can be achieved using the proposed PIC over the NNC in terms of IAE for case 1 and case 2, respectively for setpoint tracking with step changes.

     

Transforming Vulnerability Indexing for Saltwater Intrusion into Risk Indexing through a Fuzzy Catastrophe Scheme

Mapping vulnerability to Saltwater Intrusion (SWI) in coastal aquifers is studied in this paper using the GALDIT framework but with a novelty of transforming the concept of vulnerability indexing to risk indexing. GALDIT is the acronym of 6 data layers, which are put consensually together to invoke a sense of vulnerability to the intrusion of saltwater against aquifers with freshwater. It is a scoring system of prescribed rates to account for local variations; and prescribed weights to account for relative importance of each data layer but these suffer from subjectivity. Another novelty of the paper is to use fuzzy logic to learn rate values and catastrophe theory to learn weight values and these together are implemented as a scheme and hence Fuzzy-Catastrophe Scheme (FCS). The GALDIT data layers are divided into two groups of Passive Vulnerability Indices (PVI) and Active Vulnerability Indices (AVI), where their sum is Total Vulnerability Index (TVI) and equivalent to GALDIT. Two additional data layers (Pumping and Water table decline) are also introduced to serve as Risk Actuation Index (RAI). The product of TVI and RAI yields Risk Indices. The paper applies these new concepts to a study area, subject to groundwater decline and a possible saltwater intrusion problem. The results provide a proof-of-concept for PVI, AVI, RAI and RI by studying their correlation with groundwater quality samples using the fraction of saltwater (f_sea), Groundwater Quality Indices (GQI) and Piper diagram. Significant correlations between the appropriate values are found and these provide a new insight for the study area.

     

Analytics of learning tactics and strategies in an online learnersourcing environment

Background

The use of crowdsourcing in a pedagogically supported form to partner with learners in developing novel content is emerging as a viable approach for engaging students in higher-order learning at scale. However, how students behave in this form of crowdsourcing, referred to as learnersourcing, is still insufficiently explored.

Objectives

To contribute to filling this gap, this study explores how students engage with learnersourcing tasks across a range of course and assessment designs.

Methods

We conducted an exploratory study on trace data of 1279 students across three courses, originating from the use of a learnersourcing environment under different assessment designs. We employed a new methodology from the learning analytics (LA) field that aims to represent students' behaviour through two theoretically-derived latent constructs: learning tactics and the learning strategies built upon them.

Results

The study's results demonstrate students use different tactics and strategies, highlight the association of learnersourcing contexts with the identified learning tactics and strategies, indicate a significant association between the strategies and performance and contribute to the employed method's generalisability by applying it to a new context.

Implications

This study provides an example of how learning analytics methods can be employed towards the development of effective learnersourcing systems and, more broadly, technological educational solutions that support learner-centred and data-driven learning at scale. Findings should inform best practices for integrating learnersourcing activities into course design and shed light on the relevance of tactics and strategies to support teachers in making informed pedagogical decisions.     

Design of laminated composite structures for optimum fiber direction and layer thickness,using optimality criteria

In this study, two optimality criteria are presented for optimum design of composite laminates using finite element method. Thickness of the layers and fiber orientation angles in each finite element are considered as the design variables. It will be shown that the optimum design of composite laminates with varying fiber orientations and layers thicknesses may be found by using these optimality criteria in an efficient way, without performing the sensitivity analysis.