RESUMEN
Online experiments have been transforming the field of behavioral research, enabling researchers to increase sample sizes, access diverse populations, lower the costs of data collection, and promote reproducibility. The field of developmental psychology increasingly exploits such online testing approaches. Since infants cannot give explicit behavioral responses, one key outcome measure is infants' gaze behavior. In the absence of automated eyetrackers in participants' homes, automatic gaze classification from webcam data would make it possible to avoid painstaking manual coding. However, the lack of a controlled experimental environment may lead to various noise factors impeding automatic face detection or gaze classification. We created an adult webcam dataset that systematically reproduced noise factors from infant webcam studies which might affect automated gaze coding accuracy. We varied participants' left-right offset, distance to the camera, facial rotation, and the direction of the lighting source. Running two state-of-the-art classification algorithms (iCatcher+ and OWLET) revealed that facial detection performance was particularly affected by the lighting source, while gaze coding accuracy was consistently affected by the distance to the camera and lighting source. Morphing participants' faces to be unidentifiable did not generally affect the results, suggesting facial anonymization could be used when making online video data publicly available, for purposes of further study and transparency. Our findings will guide improving study design for infant and adult participants during online experiments. Moreover, training algorithms using our dataset will allow researchers to improve robustness and allow developmental psychologists to leverage online testing more efficiently.
RESUMEN
Various transition metal catalysts have been utilized for ethylene polymerization. Silver catalysts have attracted less attention as the catalysts, but are potential for production of high molecular weight polyethylene. Herein, we report that silver complexes with various N-heterocyclic carbene (NHC) ligands in combination with modified methylaluminoxane (MMAO) afford polyethylene with high molecular weight (melting point over 140°C). SEM observation showed that the produced polyethylene has ultra-high molecular weight. NMR investigation of the reaction between the silver complexes with organoaluminums indicate that the NHC ligands transfer from the silver complex to aluminum to produce NHC aluminum complexes. Ph3C[B(C6F5)4] abstract methyl group from the NHC aluminum complex to afford cationic aluminum complex. The NHC aluminum complex promoted ethylene polymerization in the presence of Ph3C[B(C6F5)4] and organoaluminums. NHC ligand also promoted ethylene polymerization in combination with MMAO to produce polyethylene with high melting point (140.7°C). Thus, the aluminum complexes are considered to be the actual active species in silver-catalyzed ethylene polymerization.
RESUMEN
Organically modified niobate nanosheets are promising building blocks for the design of advanced hybrid materials. Nanosheets with controlled thickness and surface composition are important for precise structural design of the nanosheet-based materials. In this work, single-layered and double-layered niobate nanosheets functionalized by phenylphosphonate moieties were selectively prepared by interlayer grafting of A-type and B-type intercalation derivatives of potassium hexaniobate (K4Nb6O17·3H2O) with phenylphosphonic acid (PPA), followed by exfoliation by ultrasonication in acetonitrile. The interlayer grafting of PPA was monitored using X-ray diffraction (XRD), Fourier transform infrared (FTIR), and solid-state NMR spectroscopy, and the thicknesses of the exfoliated nanosheets were measured by atomic force microscopy (AFM). Transparent hybrid films were obtained by incorporating the single- and double-layered nanosheets into an epoxy matrix.
