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Water-in-water (w/w) emulsions, comprising aqueous droplets within another continuous aqueous phase, rely on a low interfacial tension for stability. Thus far, it has been challenging to control their size and stability without the use of stabilizers. In this study, we introduce a microfluidic technique that addresses these challenges, producing stable w/w emulsions with precisely controlled size and uniformity. Results shows that using an acoustically actuated microfluidic mixer, PEG, Dextran, and alginate solutions (84.66 mPa.s viscosity difference) were homogenized rapidly, forming uniformly distributed w/w emulsions stabilized in alginate gels.The emulsion size, uniformity, and shear sensitivity can be tuned by modifying the alginate concentration. Biocompatibility was evaluated by monitoring the viability of kidney cells in the presence of emulsions and gels. In conclusion, this study not only showed emulsion formation with a high mixing efficiency exceeding 90 % for all viscosities, actuated at an optimized frequency of 1.064 MHz, but also demonstrated that an aqueous, solvent, and emulsifier-free composition exhibited remarkable biocompatibility, holding promise for precise drug delivery, cosmetics, and food applications.

Abstract The applications of terahertz metamaterials are being actively explored in recent times for applications in high-speed communication devices, miniature photonic circuits, and bio-chemical devices because of their wide advantages. The toroidal resonance, a new type of metasurface resonance, has been examined with great interest to utilize its properties in terahertz metasurface applications. This study reports a proof of concept design of a toroidal metasurface that experimentally demonstrates binary computing operations in the terahertz frequency regime. The analog computing of binary operations is achieved by the passive tuning of distance between the split ring resonators comprising the meta-molecule. The amplitude modulation is utilized as a method of determining the Boolean logic outputs of the system. The proposed metasurface could be further optimized for high amplitude modulations and active logic gate operations using tunable materials including graphene and ITO. The proposed metasurface consists of three split-ring resonators, and the near-field coupling between the adjacent resonators dictates the Boolean operations. A multipole analysis of the scattered powers of terahertz radiation determines the toroidal excitation in the metasurface. The proposed metasurfaces experimentally define AND Boolean logic operation at 0.89 terahertz, and OR Boolean logic operation at 0.97 terahertz. Numerical simulations support the experimentally obtained results. Additionally, we numerically report the excitation of NAND operation at 0.87 THz. Such toroidal analog computing metasurfaces could find applications in digitized terahertz circuits and integrated photonic devices.

The research presents a novel approach to inventory modelling, emphasizing stochastic demand and dynamic pricing strategies for a seasonal sales framework. The methodology divides the sales season into intervals, each associated with distinct pricing strategies influenced by stochastic factors. The study employ exponential smoothing for demand forecasting, optimizing inventory replenishment and dynamic pricing strategies through developed algorithms. Notably, the study determine the optimal smoothing parameter for demand forecasting, balancing responsiveness to recent demand patterns with long-term stability. Proposed research achieves a comprehensive framework empowering businesses to enhance competitiveness and profitability by addressing challenges of stochastic demand and dynamic pricing. Dynamic pricing strategies outperformed classical strategies, allowing businesses to respond promptly to demand fluctuations and optimize profit margins during sales seasons. Incorporating stochastic demand models enabled organizations to implement safety stock and buffer inventory levels effectively, mitigating risks associated with uncertain demand patterns. Real-time data analysis was crucial for adjusting price dynamics and making effective management decisions, leading to improved financial performance. The iterative nature of dynamic pricing strategies emphasized the importance of continuous refinement to adapt to evolving market dynamics. This approach enables data-driven decisions, adaptation to market fluctuations, and improved inventory management despite unpredictable demand. Ultimately, this study provides valuable insights and methodologies applicable across industries for efficient and profitable inventory management.