Development of whey-based beverages

This paper considers beverages consisting of whey, fruit components (orange, pear, peach, and apple), citric acid and sucrose. It also offers their optimal composition. The dry matter of the fruit component, the pH of the beverage and its sucrose content were independent variables. Blends were prepared in accordance with the factorial design. After pasteurization, they were exposed to a sensor analysis so that the following characteristics were estimated: flavour, odour, colour, sediment, appearance and total quality (sum of the previous factors). By applying the regression analysis method, a mathematical model of each characteristic was derived. None of the characteristic functions had an extreme, so the maxima lay at the boundaries of the independent variables (6% of dry matter and 4% or 2% of sucrose ). Only the pH changed within a narrow range. The statistical method has shown that the quality of blends with orange and pear mostly depends on the sucrose content, while the quality of blends with peach and apple depends on the dry matter of the fruit. Interaction of dry matter and sucrose is most significant for the blend with pear, while the balance between sucrose and pH strongly depends on the quality of all the other products. The peach–whey beverage containing 6% of dry matter and 2% of sucrose as well as having pH 3.6 proved to be the best.     

Site Disorder as a Predictor for Compositionally Complex 5RE2Zr2O7 Ceramic Phase Stability

Phase formation and stability of five component compositionally complex rare earth zirconates (5RE₂Zr₂O₇) were investigated by X-ray diffraction and electron microprobe analysis. Zirconates with different rare earth compositions (LaNdSmEuDy, LaNdSmEuYb, LaNdEuErYb, LaNdDyErYb, SmEuDyYHo, LaYHoErYb, and DyYHoErYb) were synthesized at 1700°C and 2000°C by the solid-state method to investigate the effect of A-site site disorder (δ_A) on phase stability. Increased site disorder results from mixed cation occupancy with localized crystallographic strain and bond disorder. Compositions LaNdSmEuDy (δ_A = 4.6) and LaNdSmEuYb (δ_A = 6.0) produced a single pyrochlore phase and compositions SmDyYHoErYb (δ_A = 2.8), LaYHoErYb (δ_A = 6.2), and DyYHoErYb (δ_A = 1.7) produced a single fluorite phase. High δ_A compositions LaNdEuErYb (δ_A = 6.9) and LaNdDyErYb (δ_A = 7.2) produced a pyrochlore and fluorite phase mixture at 1700°C. Single phase was obtained for the latter composition at 2000°C. Of the single phase compositions calcined at 1700°C, LaNdSmEuYb and LaYHoErYb (both with largest δ_A) showed decomposition to mixed fluorite and pyrochlore phases during lower temperature anneals, indicating entropic stabilization. Comparison with prior work shows a temperature dependence of the critical δ_A for phase stability, and compositions near it are expected to be entropy stabilized.     

Electromyogram-Based Lip-Reading via Unobtrusive Dry Electrodes and Machine Learning Methods (Small 17/2023)

Lip-reading provides an effective speech communication interface for people with voice disorders and for intuitive human–machine interactions. Existing systems are generally challenged by bulkiness, obtrusiveness, and poor robustness against environmental interferences. The lack of a truly natural and unobtrusive system for converting lip movements to speech precludes the continuous use and wide-scale deployment of such devices. Here, the design of a hardware–software architecture to capture, analyze, and interpret lip movements associated with either normal or silent speech is presented. The system can recognize different and similar visemes. It is robust in a noisy or dark environment. Self-adhesive, skin-conformable, and semi-transparent dry electrodes are developed to track high-fidelity speech-relevant electromyogram signals without impeding daily activities. The resulting skin-like sensors can form seamless contact with the curvilinear and dynamic surfaces of the skin, which is crucial for a high signal-to-noise ratio and minimal interference. Machine learning algorithms are employed to decode electromyogram signals and convert them to spoken words. Finally, the applications of the developed lip-reading system in augmented reality and medical service are demonstrated, which illustrate the great potential in immersive interaction and healthcare applications.     

Linker Independent Regioselective Protonation Triggered Detoxification of Sulfur Mustards with Smart Porous Organic Photopolymer

The development of efficient metal-free photocatalysts for the generation of reactive oxygen species (ROS) for sulfur mustard (HD) decontamination can play a vital role against the stockpiling of chemical warfare agents (CWAs). Herein, one novel concept is conceived by smartly choosing a specific ionic monomer and a donor tritopic aldehyde, which can trigger linker-independent regioselective protonation/deprotonation in the polymeric backbone. In this context, the newly developed vinylene-linked ionic polymers (TPA/TPD-Ionic) are further explored for visible-light-assisted detoxification of HD simulants. Time-resolved-photoluminescence (TRPL) study reveals the protonation effect in the polymeric backbone by significantly enhancing the life span of photoexcited electrons. In terms of catalytic performance, TPA-Ionic outperformed TPD-Ionic because of its enhanced excitons formation and charge carrier abilities caused by the donor-acceptor (D-A) backbone and protonation effects. Moreover, the formation of singlet oxygen (¹O₂) species is confirmed via in-situ Electron Spin Resonance (ESR) spectroscopy and density functional theory (DFT) analysis, which explained the crucial role of solvents in the reaction medium to regulate the (¹O₂) formation. This study creates a new avenue for developing novel porous photocatalysts and highlights the crucial roles of sacrificial electron donors and solvents in the reaction medium to establish the structure-activity relationship.