The influence of brewing method on bioactive compounds residues in spent coffee grounds of different roasting degree and geographical origin

The content of bioactive compounds in spent coffee grounds (SGC) was studied. SGC were obtained from Coffea arabica beans of different roasting degrees (light and dark) and different geographical origins (Nicaragua, Columbia and Mexico) processed using four brewing methods (mocha, filtered, drip and infusion). The highest caffeine and chlorogenic acid contents were determined in filtered spent coffee extracts. All extracts of light roasted spent coffee grounds showed lower browning index levels in comparison to that from dark roasted spent coffee grounds. Generally, the highest content of total polyphenolic compounds and highest antioxidant capacity were determined in extracts prepared in drip. In conclusion, the results obtained in this study indicate that the spent coffee grounds produced of domestic levels, especially those obtained from filter coffeemaker, could be considered as a good source of natural antioxidants.     

Machine Learning-Based Predictions of Customers’ Decisions in Car Insurance

Predicting customer decisions allows companies to obtain higher profits due to better resource management. The accuracy of those predictions can be currently boosted by the application of machine learning algorithms.

We propose a new method to predict a car driver’s decision about taking a replacement car after a vehicle accident happens. We use feature engineering to create attributes of high significance. The generated attributes are related to time (e.g., school holidays), place of collision (e.g., distance from home), time and conditions (e.g., weather), vehicles (e.g., vehicle value), addresses of both the victim and the perpetrator. Feature engineering involves external sources of data.

Five machine learning methods of classification are considered: decision trees, multi-layer perceptrons, AdaBoost, logistic regression and gradient boosting. Algorithms are tested on real data from a Polish insurance company. Over 80% accuracy of prediction is achieved. Significance of the attributes is calculated using the linear vector quantization method.

Presented work shows the applicability of machine learning in the car insurance market.     

Influence of Nb5+ ions on phase transitions and polar disorder above TC in PbZrO3 studied by Raman spectroscopy

Micro-Raman light scattering experiments on PbZrO₃ (PZO) single crystal doped with Nb⁵⁺ have been investigated. Special attention was paid to the paraelectric (PE) phase in which nominally forbidden first-order Raman spectra were detected at temperatures far above the phase transition T_C. Complex Raman spectra were observed in the vicinity of three structural phase transitions. These results mainly from the coexistence of phases with different symmetries in a wide temperature range below T_C. The Raman measurements have been compared with dielectric and optical observations and proved that polar nanoregions in a centrosymmetric lattice appear well above T_C. It was shown that doping ABO₃ perovskites with heterovalent ions like Nb⁵⁺ unbalances charge neutrality of the lattice and strongly extends the temperature range of polar regions. The investigations performed point out that in the PE matrix the interaction between electrons and lattice vibrations, as recently suggested for pure PZO, plays an important role.     

Iron(II) Sulfate(VI) from Titania Production as a Raw Material for Preparation of Hydrogen Sulfide Sorbents

A hybrid sorbent material for removal of hydrogen sulfide from air was developed. The material is based on activated carbon and iron compounds obtained from waste iron(II) sulfate(VI) heptahydrate. The iron salt is deposited on the carbonaceous support and subjected to oxidation (Fe²⁺ to Fe³⁺) using atmospheric oxygen under alkaline conditions. An effect of H₂O₂ addition to the process on the composition of the resultant material was also examined. X-ray diffraction (XRD) analyses confirmed easy conversion of waste FeSO₄·7H₂O to iron oxides Fe₃O₄ and FeOOH. The activated carbon supporting iron oxides revealed a higher efficiency in H₂S elimination from air compared to the commercial activated carbon, without any modification.     

Mo–Si–B alloys for ultra-high-temperature space and ground applications: liquid-assisted fabrication under various temperature and time conditions

Journal of Materials Science - Boron-doped molybdenum silicides have been already recognized as attractive candidates for space and ground ultra-high-temperature applications far beyond limits of...     

Multiscale approach to the morphology,structure, and segmental dynamics of complex degradable aliphatic polyurethanes

A multiscale approach spanning from the segmental (subnanometer) up to micrometer level was applied for detailed study of the self‐assembly of aliphatic block polyurethane (PU) elastomers. To understand the principles of the self‐organization of hard and soft segments in the complex multi‐component systems, several two‐component model PU samples, that is, the products of 1,6‐diisocyanatohexane (HDI) with three diols differing in the length and constitution were also prepared, characterized, and investigated: (i) polycarbonate‐based macrodiol (MD), (ii) biodegradable oligomeric diol (DL‐L; product of butane‐1,4‐diol and D,L‐lactide), and (iii) butane‐1,4‐diol (BD). The study (particularly ¹³C‐¹H PILGRIM NMR spectra) reveals complex internal organization and interesting (application appealing) behavior of multi‐component PUs. Hard segments (HDI+BD products) feature self‐assembled and significantly folded chain conformations with interdomain spacing 15–22 nm (small‐angle X‐ray scattering analysis). The small domains are hierarchically assembled in various structural formations of µm size (spherulites) depending on PU composition, as detected by transmission electron microscopy and atomic force microscopy. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41590.     

Wetting Behavior and Reactivity of Molten Silicon with h-BN Substrate at Ultrahigh Temperatures up to 1750 °C

For a successful implementation of newly proposed silicon-based latent heat thermal energy storage systems, proper ceramic materials that could withstand a contact heating with molten silicon at temperatures much higher than its melting point need to be developed. In this regard, a non-wetting behavior and low reactivity are the main criteria determining the applicability of ceramic as a potential crucible material for long-term ultrahigh temperature contact with molten silicon. In this work, the wetting of hexagonal boron nitride (h-BN) by molten silicon was examined for the first time at temperatures up to 1750 °C. For this purpose, the sessile drop technique combined with contact heating procedure under static argon was used. The reactivity in Si/h-BN system under proposed conditions was evaluated by SEM/EDS examinations of the solidified couple. It was demonstrated that increase in temperature improves wetting, and consequently, non-wetting-to-wetting transition takes place at around 1650 °C. The contact angle of 90° ± 5° is maintained at temperatures up to 1750 °C. The results of structural characterization supported by a thermodynamic modeling indicate that the wetting behavior of the Si/h-BN couple during heating to and cooling from ultrahigh temperature of 1750 °C is mainly controlled by the substrate dissolution/reprecipitation mechanism.