Effect of microstructural features on the corrosion behavior of severely deformed Al–Mg–Si alloy

The aim of this study was to determine the influence of severe plastic deformation processing and the changes in microstructure resulting therefrom on the corrosion resistance of an Al–Mg–Si alloy. The alloy was processed using incremental equal channel angular pressing, which caused a reduction in grain size from 15 to 0.9 µm. The grain refinement was accompanied by an increase in the number of grain boundaries and dislocations, and by changes in grain orientation. However, there was no change in the size and number of intermetallic particles, which presumably resulted in a constant number of galvanic couplings. Electrochemical experiments revealed only slight differences between the samples before and after processing. Higher potential transients/oscillations upon immersion and increased corrosion currents in the vicinity of corrosion potential point to slightly higher reactivity of the most refined material. This indicates that intermetallic particles are the most crucial microstructural elements in terms of corrosion resistance. Their impact exceeds that of grain boundaries, in particular, at the stage of corrosion initiation. The development of corrosion attack is controlled more by the microstructure of the matrix as the grain refinement resulted in a less pronounced corrosion attack in comparison with the coarse-grained sample.     

Charge Transportation and Chirality in Liquid Crystalline Helical Network Phases of Achiral BTBT-Derived Polycatenar Molecules

First examples of multichain (polycatenar) compounds, based on the π-conjugated [1]benzothieno[3,2-b]benzothiophene unit are designed, synthesized, and their soft self-assembly and charge carrier mobility are investigated. These compounds, terminated by the new fan-shaped 2-brominated 3,4,5-trialkoxybenzoate moiety, form bicontinuous cubic liquid crystalline (LC) phases with helical network structure over extremely wide temperature ranges (>200 K), including ambient temperature. Compounds with short chains show an achiral cubic phase with the double network, which upon increasing the chain length, is at first replaced by a tetragonal 3D phase and then by a mirror symmetry is broken triple network cubic phase. In the networks, the capability of bypassing defects provides enhanced charge carrier mobility compared to imperfectly aligned columnar phases, and the charge transportation is non-dispersive, as only rarely observed for LC materials. At the transition to a semicrystalline helical network phase, the conductivity is further enhanced by almost one order of magnitude. In addition, a mirror symmetry broken isotropic liquid phase is formed beside the 3D phases, which upon chain elongation is removed and replaced by a hexagonal columnar LC phase.     

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.     

ZnO Nanoplatelets with Controlled Thickness: Atomic Insight into Facet-Specific Bimodal Ligand Binding Using DNP NMR

Colloidal nanoplatelets (NPLs) and nanosheets with controlled thickness have recently emerged as an exciting new class of quantum-sized nanomaterials with substantially distinct optical properties compared to 0D quantum dots. Zn-based NPLs are an attractive heavy-metal-free alternative to the so far most widespread cadmium chalcogenide colloidal 2D semiconductor nanostructures, but their synthesis remains challenging to achieve. The authors describe herein, to the best of their knowledge, the first synthesis of highly stable ZnO NPLs with the atomically precise thickness, which for the smallest NPLs is 3.2 nm (corresponding to 12 ZnO layers). Furthermore, by means of dynamic nuclear polarization-enhanced solid-state ¹⁵N NMR, the original role of the benzamidine ligands in stabilizing the surface of these nanomaterials is revealed, which can bind to both the polar and non-polar ZnO facets, acting either as X- or L-type ligands, respectively. This bimodal stabilization allows obtaining hexagonal NPLs for which the surface energy of the facets is modulated by the presence of the ligands. Thus, in-depth study of the interactions at the organic–inorganic interfaces provides a deeper understanding of the ligand–surface interface and should facilitate the future chemistry of stable-by-design nano-objects.     

Energy Efficiency Trade-Off Between Duty-Cycling and Wake-Up Radio Techniques in IoT Networks

Wireless Personal Communications - For robust monitoring, control and proper energy management of renewable energy sources (RES), wireless sensing networks (WSNs) are proved to be a vital solution....     

Effectiveness of strategic environmental assessment in Poland

The paper presents the results of an evaluation of the effectiveness of SEA obtained as a result of a survey with the participation of stakeholders. In Poland, several hundred SEAs are conducted annually at the local and regional levels and several at the national level. Although the survey demonstrated that SEA is evaluated as effective or quite effective, the respondents pointed to several irregularities in the non-procedural dimension of effectiveness. The main ones in terms of substantive effectiveness are that SEA is rarely used to help develop plans/programmes and procedures are highly politicised. Moreover, low effectiveness in terms of variant assessment and cumulative impacts and nearly non-existent monitoring of the actual effects of implementing plans/programmes influence substantive effectiveness significantly. The respondents pointed to the problem resulting from the fact that plan-makers are unwilling to take into account the SEA recommended changes. They also emphasised that there are certain attempts to put pressure on SEA consultants to make the conclusions less stringent. Respondents indicate that in Poland the costs associated with conducting SEA often outweigh the profits. The research shows that the society is properly informed about SEA, but public involvement is still low.     

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.     

Poly(L-lysine)-poly(ethylene glycol) layers with different structure and their influence on silica suspension stability

The effects of the structure of di- and triblock copolymers of poly(L-lysine) – LYS with poly(ethylene glycol) – PEG as well as the length of nonionic fragment in the LYS-PEG macromolecule on the copolymer chains conformation in the adsorption layer formed on the colloidal silica (SiO2) surface were examined. Spectrophotometry and turbidimetry were applied for the determination of copolymer adsorbed amounts and stability coefficients of silica aqueous suspensions. The electrokinetic parameters such as solid surface charge density and zeta potential were also estimated. The adsorption of LYS-PEG was proved to be the highest at pH 10 whereas the lowest adsorption on the solid surface was found for the triblock copolymer with long fragments of LYS at the same pH value.     

Linear correlation between pH value of stimulated beef and electrical current intensity

The aim of the present study was to determine mathematical relationships between pH changes in beef 24 h post-slaughter and changes in the intensity of electrical current flowing through bull and heifer carcasses during high-voltage electrical stimulation. The electrical stimulation was applied 40 min postmortem for 120 s. The pH values of m. longissimus thoracis et lumborum were analyzed in the function of electrical current intensity changes and its change during electrical stimulation. Mathematical linear correlations of the y = ax ± b type were demonstrated between pH values at 2, 6, and 24 h postmortem and the initial (I_i) and ultimate (I_u) electrical current intensity values, the difference between them and the initial pH values determined before electrical stimulation. High multiple correlation coefficients (R² = 0.416, α ≤ 0.001) between I_u and pH values 24 h post-slaughter enabled concluding that there is a possibility to predict a pH value of stimulated carcass with high accuracy, and thus also beef quality, based merely on the ultimate electrical current intensity values.     

Biological Water Treatment by a Hybrid Fluidized-Bed Bioreactor: Theoretical Study

A hybrid fluidized-bed bioreactor for water purification was proposed and analyzed. It is a novel type of bioreactor characterized by hitherto unknown stationary and dynamic features. Steady-state characteristics of this hybrid bioreactor with external liquid circulation are presented. A quantitative analysis of steady-state properties of the bioreactor was performed with the aid of an original mathematical model developed for a double-substrate aerobic microbiological process. A steady-state analysis of aerobic processes characterized by different oxygen demand was performed. The effect of essential parameters was evaluated, including carbonaceous substrate concentration in the feed stream to the apparatus, aeration intensity, total residence time of a liquid in the bioreactor, and height of the bed of fine carrier particles.