Damage identification in concrete using impact non-linear reverberation spectroscopy

High amplitude non-linear acoustic methods have shown potential for the identification of micro damage in brittle materials such as concrete. Commonly, these methods evaluate a non-linearity parameter from the relative change in frequency and attenuation with strain amplitude. Here, a novel attenuation model is introduced to describe the free reverberation from a standard impact resonance frequency test, together with an algorithm for estimating the unknown model coefficients. The non-linear variation can hereby by analyzed over a wider dynamic range as compared to conventional methods. The experimental measurement is simple and fully compatible with the standardized free-free linear impact frequency test.     

A new reverse reduce-error ensemble pruning algorithm

Although greedy algorithms possess high efficiency, they often receive suboptimal solutions of the ensemble pruning problem, since their exploration areas are limited in large extent. And another marked defect of almost all the currently existing ensemble pruning algorithms, including greedy ones, consists in: they simply abandon all of the classifiers which fail in the competition of ensemble selection, causing a considerable waste of useful resources and information. Inspired by these observations, an interesting greedy Reverse Reduce-Error (RRE) pruning algorithm incorporated with the operation of subtraction is proposed in this work. The RRE algorithm makes the best of the defeated candidate networks in a way that, the Worst Single Model (WSM) is chosen, and then, its votes are subtracted from the votes made by those selected components within the pruned ensemble. The reason is because, for most cases, the WSM might make mistakes in its estimation for the test samples. And, different from the classical RE, the near-optimal solution is produced based on the pruned error of all the available sequential subensembles. Besides, the backfitting step of RE algorithm is replaced with the selection step of a WSM in RRE. Moreover, the problem of ties might be solved more naturally with RRE. Finally, soft voting approach is employed in the testing to RRE algorithm. The performances of RE and RRE algorithms, and two baseline methods, i.e., the method which selects the Best Single Model (BSM) in the initial ensemble, and the method which retains all member networks of the initial ensemble (ALL), are evaluated on seven benchmark classification tasks under different initial ensemble setups. The results of the empirical investigation show the superiority of RRE over the other three ensemble pruning algorithms.     

A modified particle swarm optimization with multiple subpopulations for multimodal function optimization problems

In this paper, a modified particle swarm optimization (PSO) algorithm is developed for solving multimodal function optimization problems. The difference between the proposed method and the general PSO is to split up the original single population into several subpopulations according to the order of particles. The best particle within each subpopulation is recorded and then applied into the velocity updating formula to replace the original global best particle in the whole population. To update all particles in each subpopulation, the modified velocity formula is utilized. Based on the idea of multiple subpopulations, for the multimodal function optimization the several optima including the global and local solutions may probably be found by these best particles separately. To show the efficiency of the proposed method, two kinds of function optimizations are provided, including a single modal function optimization and a complex multimodal function optimization. Simulation results will demonstrate the convergence behavior of particles by the number of iterations, and the global and local system solutions are solved by these best particles of subpopulations.     

New nanocomposite based on poly(lactic-co-glycolic acid) copolymer and magnetite. Synthesis and characterization

The study presents the preparation of the new magnetic nanocomposite based on PLGA and magnetite. The PLGA used to obtain the magnetic nanocomposites was synthesized by the copolymerization of lactic acid with glycolic acid, in the presence of tin octanoate [Sn(Oct)₂] as catalyst, by polycondensation procedure. Magnetite was obtained by co-precipitation from aqueous salt solutions FeCl₂/FeCl₃. The particles size of magnetite was 420 nm, and the saturation magnetization 62.78 emu/g, while the PLGA/magnetite nanocomposite size was 864 nm and the saturation magnetization 39.44 emu/g. The magnetic nanocomposites were characterized by FT-IR, DLS technique, SEM, VSM and simultaneous thermal analyses (TG–FTIR–MS). The polymer matrix PLGA acts as a shell and carrier for the active component, while magnetite is the component which makes targeting possible by external magnetic field manipulation. Based on the gases resulted by thermal degradation of PLGA copolymer, using the simultaneous analysis TG–FTIR–MS, a possible degradation mechanism was proposed.     

THE effect of Srandom DOPANT fluctuation on threshold voltage and drain current variation in junctionless nanotransistors

We investigate the effect of dopant random fluctuation on threshold voltage and drain current variation in a two-gate nanoscale transistor. We used a quantum-corrected technology computer aided design simulation to run the simulation (10000 randomizations). With this simulation, we could study the effects of varying the dimensions (length and width), and thicknesses of oxide and dopant factors of a transistor on the threshold voltage and drain current in subthreshold region (off) and overthreshold (on). It was found that in the subthreshold region the variability of the drain current and threshold voltage is relatively fixed while in the overthreshold region the variability of the threshold voltage and drain current decreases remarkably, despite the slight reduction of gate voltage diffusion (compared with that of the subthreshold). These results have been interpreted by using previously reported models for threshold current variability, load displacement, and simple analytical calculations. Scaling analysis shows that the variability of the characteristics of this semiconductor increases as the effects of the short channel increases. Therefore, with a slight increase of length and a reduction of width, oxide thickness, and dopant factor, we could correct the effect of the short channel.     

Characteristics and formation mechanism of porosities in CFRP during laser joining of CFRP and steel

An experimental investigation on the mechanism of porosity formation during the laser joining of carbon fiber reinforced polymer (CFRP) and steel is presented. The porosity morphology and distribution were characterized by optical and scanning electron microscopy, and the thermal pyrolysis behaviors were investigated by thermal analysis and designed back-side cooling experiments. The results show that there are two types of porosities in CFRP. Porosity I only appears when the heat input is more than 77.8 J/mm. It has a smooth inner wall and distributes near the bonding interface between CFRP and steel at the central area of melted zone, which is caused by gaseous products such as CO₂, NH₃, H₂O, and hydrocarbons produced by the pyrolysis of CFRP. Porosity II can be seen under all joining conditions. It has a rough inner wall and distributes far away from the bonding interface, concentrating at the final solidification locations. Porosity II is caused by the shrinkage of melted CFRP during solidification stage.     

Reactive Oxygen and Nitrogen Species in Defense/Stress Responses Activated by Chitosan in Sycamore Cultured Cells

Chitosan (CHT) is a non-toxic and inexpensive compound obtained by deacetylation of chitin, the main component of the exoskeleton of arthropods as well as of the cell walls of many fungi. In agriculture CHT is used to control numerous diseases on various horticultural commodities but, although different mechanisms have been proposed, the exact mode of action of CHT is still unknown. In sycamore (Acer pseudoplatanus L.) cultured cells, CHT induces a set of defense/stress responses that includes production of H₂O₂ and nitric oxide (NO). We investigated the possible signaling role of these reactive molecules in some CHT-induced responses by means of inhibitors of production and/or scavengers. The results show that both reactive nitrogen and oxygen species are not only a mere symptom of stress conditions but are involved in the responses induced by CHT in sycamore cells. In particular, NO appears to be involved in a cell death form induced by CHT that shows apoptotic features like DNA fragmentation, increase in caspase-3-like activity and release of cytochrome c from the mitochondrion. On the contrary, reactive oxygen species (ROS) appear involved in a cell death form induced by CHT that does not show these apoptotic features but presents increase in lipid peroxidation.     

Rapid detection of viable Bacillus cereus emetic and enterotoxic strains in food by coupling propidium monoazide and multiplex PCR (PMA-mPCR)

Bacillus cereus can cause emetic and diarrheal food poisoning. It is widespread in nature and therefore, considered a major foodborne pathogen. To develop a sensitive and reliable assay for detecting enterotoxin genes (nheA, entFM, hblD, cytK) and emetic toxin (ces), specific primers each targeting one individual gene were designed. Propidium monoazide (PMA) was coupled with the developed multiplex PCR (mPCR) for the detection of viable B. cereus. The inclusivity and exclusivity of the PMA-mPCR was confirmed using a panel of 44 strains including 17 emetic and 9 enterotoxic B. cereus reference strains and 18 non-target strains. The limit of detection (LOD) without PMA treatment in pure DNA was 2 pg/reaction tube. The LOD of mPCR assay in pure heat-killed dead bacteria was 4.0 × 10² CFU/mL. Also, the LOD on the viable bacteria with or without PMA treatment was similar (3.8 × 10² CFU/mL) showing that the PMA treatment did not significantly decrease sensitivity. Finally, the newly developed PMA-mPCR successfully detected 4.8 × 10³ and 3.6 × 10³ CFU/g of viable B. cereus F4810/72 (emetic) and B. cereus ATCC 12480 (enterotoxic) reference strains, respectively, in food samples. Hence, this study combines PMA and mPCR to detect viable B. cereus with a wide range of toxin detection (5 toxins). Thus, the novel PMA-mPCR assay developed in this study is a rapid and efficient diagnostic tool for the monitoring of viable B. cereus in food samples and potentially other samples via appropriate DNA extraction.     

Hydrocarbon-based electrode ionomer for proton exchange membrane fuel cells

The electrode ionomer is a key factor that significantly affects the catalyst layer morphology and fuel cell performance. Herein, sulfonated poly(arylene ether sulfone)-based electrode ionomers with polymers of various molecular weights and alcohol/water mixtures were prepared, and those comprising the alcohol/water mixture showed a higher performance than the ones prepared using higher boiling solvents, such as dimethylacetamide; this is owing to the formation of the uniformly dispersed ionomer catalyst layer. The relation between ionomer molecular weight for the same polymer structure and the sulfonation degree was investigated. Because the chain length of polymer varies with molecular weight and chain entanglement degree, its molecular weight affects the electrode morphology. As the ionomer covered the catalyst, the agglomerates formed were of different morphologies according to their molecular weight, which could be deduced indirectly through dynamic light scattering and scanning electron microscopy. Additionally, the fuel cell performance was confirmed in the current-voltage curve.