Optical limiting using Laguerre-Gaussian beams

We demonstrate optical limiting using the self-lensing effect of a higher-order Laguerre-Gaussian beam in a thin dye-doped polymer sample, which we find is consistent with our model using Gaussian decomposition. The peak phase shift in the sample required for limiting is smaller than for a fundamental Gaussian beam with the added flexibility that the nonlinear medium can be placed either in front of or behind the beam focus.Comment: 3 pages, 4 figure

Effects of temperature and dissolved CO2 on the scaling of water in the presence of copper and zinc

In this study, through the method of rapid controlled precipitation (RCP), the influence of temperature and dissolved CO2 on the scaling capacity of mineral water in the presence of copper and zinc ions was studied in laboratory experiments. The results indicated that with a rise in temperature or concentration of dissolved CO2, the scaling time of Salvetat water greatly decreased and the rate of precipitation considerably increased; therefore, the minimum dosage of copper or zinc ion for achieving total inhibition of scaling needed to be increased, which would provide better guidance for practical use of metal ions in inhibiting the scaling of drinking water

From powder to cloth: Facile fabrication of dense MOF-76(Tb) coating onto natural silk fiber for feasible detection of copper ions

The deposition of powdered MOFs material onto other substrates is essential to avoid inconvenience during its practical applications. In this work, domestic silk fiber was utilized as the skeleton, for successful coating of dense luminescent MOF-76(Tb). Its surface functionality which consist of abundance of intrinsic carboxylic groups, smooth surface structure, and 80% of tensile strength were maintained after being immersed in different thermal solvents (water, ethanol, DMF @ 80 °C) for 24 h, revealing good solvent and thermal resistance. By using hydrothermal, microwave assisted, and layer-by-layer methods, different crystal morphologies (pillar-like, sedimentary-rock-like, and needle-like morphology) and varying degrees of surface coverage rate were obtained, as a result of different levels of anchoring promotion and crystal controlling effect. The MOFs coating can be confirmed by its XRD pattern and fluorescent property. More importantly, the quenching effect of the composite in a condition of Cu2+ was first reported with high selectivity, sensitivity (i.e. a linear detection concentration range of 10−3–10−5 M with a low detection limit up to 0.5 mg/L, KSV of 1192 M−1 at 293 K), and rapid response time (5 min), making the composite a good candidate for colorimetric and fluorescent detection of aquatic Cu2+. The quenching mechanism is proposed to associate with the interaction between Cu2+ and benzene-tricarboxylate (BTC) ligand, which resulted in the decrease of energy transfer efficiency. The selectivity over other common cations depends on the unsaturated electron configuration and the smaller ionic radius of Cu2+

Editor\u27s Notes, Chiba Medical Journal 90-1

Multiple sequence alignment of deduced amino acid sequences of 25 wheat annexin genes with rice annexin OsAnn2 (Os05g31760) obtained by ClustalW. (PDF 212 kb

Heteroaggregation of nanoparticles with biocolloids and geocolloids

The application of nanoparticles has raised concern over the safety of these materials to human health and the ecosystem. After release into an aquatic environment, nanoparticles are likely to experience heteroaggregation with biocolloids, geocolloids, natural organic matter (NOM) and other types of nanoparticles. Heteroaggregation is of vital importance for determining the fate and transport of nanoparticles in aqueous phase and sediments. In this article, we review the typical cases of heteroaggregation between nanoparticles and biocolloids and/or geocolloids, mechanisms, modeling, and important indicators used to determine heteroaggregation in aqueous phase. The major mechanisms of heteroaggregation include electric force, bridging, hydrogen bonding, and chemical bonding. The modeling of heteroaggregation typically considers DLVO, X-DLVO, and fractal dimension. The major indicators for studying heteroaggregation of nanoparticles include surface charge measurements, size measurements, observation of morphology of particles and aggregates, and heteroaggregation rate determination. In the end, we summarize the research challenges and perspective for the heteroaggregation of nanoparticles, such as the determination of αhetero values and heteroaggregation rates; more accurate analytical methods instead of DLS for heteroaggregation measurements; sensitive analytical techniques to measure low concentrations of nanoparticles in heteroaggregation systems; appropriate characterization of NOM at the molecular level to understand the structures and fractionation of NOM; effects of different types, concentrations, and fractions of NOM on the heteroaggregation of nanoparticles; the quantitative adsorption and desorption of NOM onto the surface of nanoparticles and heteroaggregates; and a better understanding of the fundamental mechanisms and modeling of heteroaggregation in natural water which is a complex system containing NOM, nanoparticles, biocolloids and geocolloids

Multidimensional signals and analytic flexibility: Estimating degrees of freedom in human speech analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis which can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling, but also from decisions regarding the quantification of the measured behavior. In the present study, we gave the same speech production data set to 46 teams of researchers and asked them to answer the same research question, resulting insubstantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further find little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system and calibrate their (un)certainty in their conclusions

An Intelligent Method for Lead User Identification in Customer Collaborative Product Innovation

For customer collaborative product innovation (CCPI), lead users are powerful enablers of product innovation. Identifying lead users is vital to successfully carrying out CCPI. In this paper, in order to overcome the shortcomings of traditional evaluation methods, a novel intelligent method is proposed to identify lead users efficiently based on the cost-sensitive learning and support vector machine theory. To this end, the characteristics of lead users in CCPI are first analyzed and concluded in-depth. On its basis, considering the sample misidentification cost and identification accuracy rate, an improved cost-sensitive learning support vector machine (ICS-SVM) method for lead user identification in CCPI is further proposed. A real case is provided to illustrate the effectiveness and advantages of the ICS-SVM method on lead user identification in CCPI. The case results show that the ICS-SVM method can effectively identify lead users in CCPI. This work contributes to user innovation literature by proposing a new way of identifying highly valuable lead users and offers a decision support for the efficient user management in CCPI