Use of a kaolinitic clay as a pozzolanic material for cements: Formulation of blended cement

Local kaolinitic clay (from the region of Tabarka, Tunisia) was tested as a pozzolanic material. Thermal treatments were performed as a means of activation of the minerals. The phase identification, before and after heat treatment, was studied by X-ray diffraction and differential thermal analysis/thermogravimetric analysis (DTA/TGA).

In order to check the effect of three variables (the calcination temperature, the specific surface of the calcined clay and the percentage of incorporation of the heat treated clay in the formula of the blended cement) on the compressive strength of blended cement mortar bars at 7, 28 and 91 days, a Box–Behnken design was set up. It was concluded that the mechanical properties of the blended cements were mainly governed by the percentage of incorporation and the fineness of the calcined clay. It was also demonstrated that increasing the fineness of the calcined clay allowed for increases in the level of cement substitution. Finally, a blended cement composition has been formulated, with optimal results at calcining temperature 700 °C, 30% of calcined clay ground at a Blaine fineness of 7700 cm²/g.     

Antibacterial effects of natural tenderizing enzymes on different strains of Escherichia coli O157:H7 and Listeria monocytogenes on beef

This study determined the efficacy of actinidin and papain on reducing Listeria monocytogenes and three mixed strains of Escherichia coli O157:H7 populations on beef. The average reduction of E. coli O157:H7 was greater than that of L. monocytogenes and higher concentrations of either protease yielded greater reduction in bacterial populations. For instance, actinidin at 700 mg/ml significantly (p ≤ 0.05) reduced the population of L. monocytogenes by 1.49 log cfu/ml meat rinse after 3 h at 25 & 35 °C, and by 1.45 log cfu/ml rinse after 24 h at 5 °C, while the same actinidin concentration significantly reduced the populations of three mixed strains of E. coli O157:H7 by 1.81 log cfu/ml rinse after 3 h at 25 & 35 °C, and 1.94 log cfu/ml rinse after 24 h at 5 °C. These findings suggest that, in addition to improving the sensory attributes of beef, proteolytic enzymes can enhance meat safety when stored at suitable temperatures.     

A model for the analysis of neighbor finding in pointer-based quadtrees

A natural byproduct of the tree-like nature of the quadtree is that many basic image processing operations can be implemented as tree traversals which differ in the nature of the computation that is performed at each node. Some of these computations involve the inspection of a node's adjacent neighbors (termed neighbor finding). A new model is developed for images represented by quadtrees, and it is used to analyze various neighbor-finding techniques. The model's predicted costs for neighbor finding correlate very closely with empirical results and it is superior to the model that was used previously.     

Thermal-tempering analysis of bulk metallic glass plates using an instant-freezing model

The viscoelastic nature of bulk metallic glasses (BMGs), their low thermal conductivity, and the fast cooling used in their processing subject them to thermal tempering. This process leads to a residual stress state in which compression on the surface is balanced by tension in the interior. For the first time, we have calculated such stresses in metallic glasses by adapting an analytical instant-freezing model previously developed for silicate glasses. This model has been demonstrated to be reasonably accurate in predicting the final residual stresses, although, due to its very nature, it neglects transient effects. For an infinite plate geometry and employing processing parameters often used for metallic glasses, we predict that significant residual stresses can be generated in these materials during thermal tempering. Preliminary measurements conducted using the layer-removal method yield compressive residual stress values close to model predictions.     

Achieving MILP feasibility quickly using general disjunctions

Branch and bound algorithms for Mixed-Integer Linear Programming (MILP) almost universally branch on a single variable to create disjunctions. General linear expressions involving multiple variables are another option for branching disjunctions, but are not used for two main reasons: (i) descendent LPs tend to solve more slowly because of the added constraints, so the overall solution time is increased, and (ii) it is difficult to quickly find an effective general disjunction. We study the use of general disjunctions to reach the first MILP-feasible solution quickly, showing for the first time that general disjunctions can provide speed improvements for hard MILP models. The speed-up is due to new and efficient ways to (i) trigger the inclusion of a general disjunction only when it is likely to be beneficial, and (ii) construct effective general disjunctions very quickly. Our empirical results show performance improvements versus a state of the art commercial MILP solver.     

Transfer characteristic of a Goto pair in small-size Josephson junctions

The response of a Goto pair, based on small-size Josephson junctions, to voltage jumps has been studied within the framework of a resistive model. An analytical formula for the time of establishment of the transfer characteristic is obtained and the corresponding estimates are calculated.     

A Resource Allocation Approach for the Generation of Service-Dependent Demand Matrices for Communications Networks

Estimating point-to-point demands from partially available information, such as total demand volumes originating and terminating at nodes and traffic volumes routed on links, has significant applications in various areas, such as communications network planning and transportation planning. Existing methods include matrix and link scaling methods, statistical methods, more complex mathematical programming models, and forecasting using demographic data. We present a new mathematical programming model based on equitable resource allocation. The model considers multiple services, e.g., data, video, and voice, and generates a point-to-point demand matrix for each service. Originating and terminating demands for each service and link loads, aggregated over all services, are viewed as resources. Each point-to-point demand is associated with a performance function that measures its weighted, normalized deviation from a target defined by a service-dependent community of interest matrix. The model formulation has a lexicographic minimax objective function and multiple knapsack resource constraints. The model has an intuitively appealing interpretation and a specialized algorithm can generate demand matrices for large network problems very fast.     

A robust learning based evolutionary approach for thermal-economic optimization of compact heat exchangers

This paper presents a robust, efficient and parameter-setting-free evolutionary approach for the optimal design of compact heat exchangers. A learning automata based particle swarm optimization (LAPSO) is developed for optimization task. Seven design parameters, including discreet and continuous ones, are considered as optimization variables. To make the constraint handling straightforward, a self-adaptive penalty function method is employed. The efficiency and the accuracy of the proposed method are demonstrated through two illustrative examples that include three objectives, namely minimum total annual cost, minimum weight and minimum number of entropy generation units. Numerical results indicate that the presented approach generates the optimum configuration with higher accuracy and a higher success rate when compared with genetic algorithms (GAs) and particle swarm optimization (PSO).