Introduction: Harvested blueberries can be processed into wine to extend their shelf life and increase their commercial value. In order to produce fruit wine, external sugar is often added prior to fermentation to increase the final alcohol content to a target of 8–12% (v/v) to meet consumer expectations.Method: we explore the effect of 8–14% (w/w) sucrose on the physicochemical properties of blueberry wine throughout the main fermentation process. We monitor changes of alcohol content, sugar, color, phenol, acidity, anthocyanin, and odor.Results and discussion: We notice that sucrose affects the fermentation process and physicochemical composition of the final blueberry wine by fermentation rate, fermentation color and protection of functional substances protection. Additional sucrose extends the total time of fermentation, and increases wine acidity. The color of the wine is also affected, with added sugar darkening and yellowing the final product. Interestingly, the sucrose has a protective effect on anthocyanin levels, although total anthocyanin levels are still substantially reduced following fermentation. Finally, the additional sugar increases accumulation of volatile odor components, particularly alcohols and esters, as measured by an electronic nose. We conclude that an addition of 12% sucrose produces wine with superior physicochemical properties of alcohol, anthocyanin loss and odor relative to other conditions tested and recommend this approach to commercial manufacturers.

• Low-salt pickling increased the content of SFA, PUFA and MUFA in salted eggs. • Low-salt process can achieve the same effect as traditional processes and is healthy alternative. • Phospholipids may be responsible for the unique quality of salted egg yolk.

Microsphere-assisted microscopy serves as an effective super-resolution technique in biological observations and nanostructure detections, and optical trapping is widely used for the manipulation of small particles like microspheres. In this study, we focus on the selection of microsphere types for the combination of the optical trapping and the super-resolution microsphere-assisted microscopy, by considering the optical trapping performances and the super-resolution imaging ability of index-different microspheres in water simultaneously. Finally, the polystyrene (PS) sphere and the melamine formaldehyde (MF) sphere have been selected from four typical index-different microspheres normally used in microsphere-assisted microscopy. In experiments, the optically trapped PS/MF microsphere in water has been used to achieve super-resolution imaging of a 139 nm line-width silicon nanostructure grating under white light illumination. The image quality and the magnification factor are affected by the refractive index contrast between the microspheres and the immersion medium, and the difference of image quality is partly explained by the photonic nanojet. This work guides us in selecting proper microspheres, and also provides a label-free super-resolution imaging technique in many research fields.

Source and mask optimization (SMO) technology is increasingly relied upon for resolution enhancement of photolithography as critical dimension (CD) shrinks. In advanced CD technology nodes, little process variation can impose a huge impact on the fidelity of lithography. However, traditional source and mask optimization (SMO) methods only evaluate the imaging quality in the focal plane, neglecting the process window (PW) that reflects the robustness of the lithography process. PW includes depth of focus (DOF) and exposure latitude (EL), which are computationally intensive and unfriendly to gradient-based SMO algorithms. In this study, we propose what we believe to be a novel process window enhancement SMO method based on the Nondominated Sorting Genetic Algorithm II (NSGA-II), which is a multi-objective optimization algorithm that can provide multiple solutions. By employing the variational lithography model (VLIM), a fast focus-variation aerial image model, our method, NSGA-SMO, can directly optimize the PW performance and improve the robustness of SMO results while maintaining the in-focus image quality. Referring to the simulations of two typical patterns, NSGA-SMO showcases an improvement of more than 20% in terms of DOF and EL compared to conventional multi-objective SMO, and even four times superior to single-objective SMO for complicated patterns.

Source optimisation (SO) is an approved approach to improve the imaging quality in inverse lithography techniques. It is critical to apply an optimisation approach with high convergence efficiency and minimum errors in pixel-based SO. To improve the convergence efficiency of the pixel-based SO, a route of particle swarm optimiser (PSO) combined with the adaptive nonlinear control strategy (ANCS) is proposed in this study. As a global optimisation algorithm, ANCS-PSO has the attributes of breaking away from the local optimum by adjusting the particle learning factor adaptively. In addition, the nonlinear control approach can broaden the search range and speed up the convergence of the iteration operation. The proposed approach also is compared with the linear decreasing inertia weight strategy and the simulated annealing strategy. The performance verification simulation displays the validity of PSO-ANCS and its potentials in SO with high convergence efficiency and optimisation capacity, by comparing the linear decreasing inertia weight strategy and the simulated annealing strategy.