On-line determination of organochlorine pesticides in water by solid-phase microextraction and gas chromatography with electron capture detection

This paper describes the extraction of 20 organochlorine pesticides (OCPs) from water samples using solid-phase microextraction (SPME). Three fused-silica fibers coated or bonded with polydimethylsiloxane (PDMS) of different film thicknesses (20-, 30-, and 100-μm) were evaluated. The extraction time, the effects of stirring and addition of NaCl to the aqueous sample, the linear range and the precision of this technique, and the effect of carryover were examined for 20 analytes and are presented here. A comparison with results using conventional liquid-liquid extraction demonstrate that the SPME technique is well suited as a fast screening technique for OCPs in water samples.     

Effect of molecular architecture on DBS-induced block copolymer gels: A rheological study

Dibenzylidene sorbitol (DBS) is capable of gelling a variety of organic solvents and polymeric materials by forming a rigid, 3-D hydrogen-bonded network. In this work, two poly(siloxane)/poly(propylene oxide) segmented copolymers of equal composition and molecular weight, but different architectures (endblocked vs. pendant), as well as a pure poly(propylene oxide), have been gelled with DBS. We have investigated the dynamic rheological properties of these gels to ascertain the effect of copolymer architecture, PDMS comonomer and DBS concentration on network formation.     

Reductive allylation of poly(chlorotrifluoroethylene)

Treatment of poly(chlorotrifluoroethylene) with allyltin reagents results in the clean replacement of chlorine by the allyl group under free-radical–chain conditions (AIBN, allyltributyltin), affording about a 10% degree of functionalization. An improved method using one-electron reduction of the polymer with cobalt(II) (generated by reduction of chloro(pyridine)bis(dimethylglyoximato)cobalt(III) with Mg) and allyltributyltin gives 50% functionalization. Further modification of the allyl group is realized through hydroboration-oxidation to the alcohol and subsequent Cr(VI) oxidation to the acid. A mechanistic discussion is provided. © John Wiley & Sons, Inc.     

New cationic group 4 metal alkyl complexes

Cationic group 4 metal alkyl complexes containing tetradentate Schiff base ligands, (acen) Zr(R)⁺ and (F6-acen) Zr(R)⁺, are prepared by protonolysis of suitable neutral dialkyl precursors. These complexes display electrophilic behavior and are moderately active ethylene polymerization catalysts in the presence of 1 molar equivalent of AlR₃.     

Defined carrageenan derivatives as angiogenesis inhibitors

Three carrageenans derived from red algae and three partially modified carrageenans were tested for their ability to inhibit the formation of new blood capillaries on the chorionallantois membrane of the hen egg. It could be clearly demonstrated that they were better angiogenesis inhibitors than the standard compound suramin.     

Optimization of STEM-HAADF Electron Tomography Reconstructions by Parameter Selection in Compressed Sensing Total Variation Minimization-Based Algorithms

A novel procedure to optimize the 3D morphological characterization of nanomaterials by means of high angle annular dark field scanning-transmission electron tomography is reported and is successfully applied to the analysis of a metal- and halogen-free ordered mesoporous carbon material. The new method is based on a selection of the two parameters (μ and β) which are key in the reconstruction of tomographic series by means of total variation minimization (TVM). The parameter-selected TVM reconstructions obtained using this approach clearly reveal the porous structure of the carbon-based material as consisting of a network of parallel, straight channels of ≈6 nm diameter ordered in a honeycomb-type arrangement. Such an unusual structure cannot be retrieved from a TVM 3D reconstruction using default reconstruction values. Moreover, segmentation and further quantification of the optimized 3D tomographic reconstruction provide values for different textural parameters, such as pore size distribution and specific pore volume that match very closely with those determined by macroscopic physisorption techniques. The approach developed can be extended to other reconstruction models in which the final result is influenced by parameter choice.     

New Interfaces and Approaches to Machine Learning When Classifying Gestures within Music

Interactive music uses wearable sensors (i.e., gestural interfaces—GIs) and biometric datasets to reinvent traditional human–computer interaction and enhance music composition. In recent years, machine learning (ML) has been important for the artform. This is because ML helps process complex biometric datasets from GIs when predicting musical actions (termed performance gestures). ML allows musicians to create novel interactions with digital media. Wekinator is a popular ML software amongst artists, allowing users to train models through demonstration. It is built on the Waikato Environment for Knowledge Analysis (WEKA) framework, which is used to build supervised predictive models. Previous research has used biometric data from GIs to train specific ML models. However, previous research does not inform optimum ML model choice, within music, or compare model performance. Wekinator offers several ML models. Thus, we used Wekinator and the Myo armband GI and study three performance gestures for piano practice to solve this problem. Using these, we trained all models in Wekinator and investigated their accuracy, how gesture representation affects model accuracy and if optimisation can arise. Results show that neural networks are the strongest continuous classifiers, mapping behaviour differs amongst continuous models, optimisation can occur and gesture representation disparately affects model mapping behaviour; impacting music practice.     

Geometry Optimization of Thermoelectric Modules: Deviation of Optimum Power Output and Conversion Efficiency

Besides the material research in the field of thermoelectrics, the way from a material to a functional thermoelectric (TE) module comes alongside additional challenges. Thus, comprehension and optimization of the properties and the design of a TE module are important tasks. In this work, different geometry optimization strategies to reach maximum power output or maximum conversion efficiency are applied and the resulting performances of various modules and respective materials are analyzed. A Bi₂Te₃-based module, a half-Heusler-based module, and an oxide-based module are characterized via FEM simulations. By this, a deviation of optimum power output and optimum conversion efficiency in dependence of the diversity of thermoelectric materials is found. Additionally, for all modules, the respective fluxes of entropy and charge as well as the corresponding fluxes of thermal and electrical energy within the thermolegs are shown. The full understanding and enhancement of the performance of a TE module may be further improved.