Bipartite coherent-state quantum key distribution with strong reference pulse

We propose an optical scheme for quantum key distribution in which bits are encoded in relative phases of four bipartite weak coherent states ${|\alpha, \alpha\rangle, |-\alpha, -\alpha\rangle, |-\alpha, \alpha\rangle}$ and ${|\alpha, -\alpha \rangle}$ , with respect to a strong reference pulse. We discuss security of the scheme against eavesdropping strategies like, photon number splitting, photon beam splitting and intercept-resend attacks. It is found that present scheme is more sensitive against these eavesdropping strategies than the two-dimensional non-orthogonal state based protocol and BB84 protocol. Our scheme is very simple, requires only passive optical elements like beam splitters, phase shifters and photon detectors, hence is at the reach of presently available technology.     

Inclusion dynamics hybrid automata

Hybrid systems are dynamical systems with the ability to describe mixed discrete-continuous evolution of a wide range of systems. Consequently, at first glance, hybrid systems appear powerful but recalcitrant, neither yielding to analysis and reasoning through a purely continuous-time modeling as with systems of differential equations, nor open to inferential processes commonly used for discrete state-transition systems such as finite state automata. A convenient and popular model, called hybrid automata, was introduced to model them and has spurred much interest on its tractability as a tool for inference and model checking in a general setting. Intuitively, a hybrid automaton is simply a “finite-state” automaton with each state augmented by continuous variables, which evolve according to a set of well-defined continuous laws, each specified separately for each state. This article investigates both the notion of hybrid automaton and the model checking problem over such a structure. In particular, it relates first-order theories and analysis results on multivalued maps and reduces the bounded reachability problem for hybrid automata whose continuous laws are expressed by inclusions (x′f(x,t)) to a decidability problem for first-order formulæ over the reals. Furthermore, the paper introduces a class of hybrid automata for which the reachability problem can be decided and shows that the problem of deciding whether a hybrid automaton belongs to this class can be again decided using first-order formulæ over the reals. Despite the fact that the bisimulation quotient for this class of hybrid automata can be infinite, we show that our techniques permit effective model checking for a nontrivial fragment of CTL.     

Highly Efficient Quasi 2D Blue Perovskite Electroluminescence Leveraging a Dual Ligand Composition

Perovskite light-emitting diodes (PeLEDs) are advancing because of their superior external quantum efficiencies (EQEs) and color purity. Still, additional work is needed for blue PeLEDs to achieve the same benchmarks as the other visible colors. This study demonstrates an extremely efficient blue PeLED with a 488 nm peak emission, a maximum luminance of 8600 cd m⁻², and a maximum EQE of 12.2% by incorporating the double-sided ethane-1,2-diammonium bromide (EDBr₂) ligand salt along with the long-chain ligand methylphenylammonium chloride (MeCl). The EDBr₂ successfully improves the interaction between 2D perovskite layers by reducing the weak van der Waals interaction and creating a Dion–Jacobson (DJ) structure. Whereas the pristine sample (without EDBr₂) is inhibited by small stacking number (n) 2D phases with nonradiative recombination regions that diminish the PeLED performance, adding EDBr₂ successfully enables better energy transfer from small n phases to larger n phases. As evidenced by photoluminescence (PL), scanning electron microscopy (SEM), and atomic force microscopy (AFM) characterization, EDBr₂ improves the morphology by reduction of pinholes and passivation of defects, subsequently improving the efficiencies and operational lifetimes of quasi-2D blue PeLEDs.     

Event-triggered control for discrete-time multi-agent average consensus

We consider the average consensus problem for the multi-agent system in the discrete-time domain. Three triggering based control protocols are developed, which dictate the broadcast and control update instants of individual agents to alleviate communication and computational burden. Lyapunov-based design methods prescribe when agents should communicate and update their control so that the network converges to the average of agents' initial states. We start with a static version of the distributed event-triggering law and then generalize it so that it involves an internal auxiliary variable to regulate the threshold dynamically for each agent. The third protocol uses a self-triggering algorithm to avoid continuous listening wherein each agent estimates its next triggering time and broadcasts it to its neighbors at the current triggering time. Numerical simulations are shown to validate the efficacy of the proposed algorithms.     

An extended hesitant fuzzy set using SWARA-MULTIMOORA approach to adapt online education for the control of the pandemic spread of COVID-19 in higher education institutions

The world has been challenged since late 2019 by COVID-19. Higher education institutions have faced various challenges in adapting online education to control the pandemic spread of COVID-19. The present study aims to conduct a survey study through the interview and scrutinizing the literature to find the key challenges. Subsequently, an integrated MCDM framework, including Stepwise Weight Assessment Ratio Analysis (SWARA) and Multiple Objective Optimization based on Ratio Analysis plus Full Multiplicative Form (MULTIMOORA), is developed. The SWARA procedure is applied to the analysis and assesses the challenges to adapt the online education during the COVID-19 outbreak, and the MULTIMOORA approach is utilized to rank the higher education institutions on hesitant fuzzy sets. Further, an illustrative case study is considered to express the proposed idea's feasibility and efficacy in real-world decision-making. Finally, the obtained result is compared with other existing approaches, confirming the proposed framework's strength and steadiness. The identified challenges were systemic, pedagogical, and psychological challenges, while the analysis results found that the pedagogical challenges, including the lack of experience and student engagement, were the main essential challenges to adapting online education in higher education institutions during the COVID-19 outbreak.

     

Nanomembrane‐Based,Thermal‐Transport Biosensor for Living Cells

Knowledge of materials' thermal‐transport properties, conductivity and diffusivity, is crucial for several applications within areas of biology, material science and engineering. Specifically, a microsized, flexible, biologically integrated thermal transport sensor is beneficial to a plethora of applications, ranging across plants physiological ecology and thermal imaging and treatment of cancerous cells, to thermal dissipation in flexible semiconductors and thermoelectrics. Living cells pose extra challenges, due to their small volumes and irregular curvilinear shapes. Here a novel approach of simultaneously measuring thermal conductivity and diffusivity of different materials and its applicability to single cells is demonstrated. This technique is based on increasing phonon‐boundary‐scattering rate in nanomembranes, having extremely low flexural rigidities, to induce a considerable spectral dependence of the bandgap‐emission over excitation‐laser intensity. It is demonstrated that once in contact with organic or inorganic materials, the nanomembranes' emission spectrally shift based on the material's thermal diffusivity and conductivity. This NM‐based technique is further applied to differentiate between different types and subtypes of cancer cells, based on their thermal‐transport properties. It is anticipated that this novel technique to enable an efficient single‐cell thermal targeting, allow better modeling of cellular thermal distribution and enable novel diagnostic techniques based on variations of single‐cell thermal‐transport properties.     

Development,optimization, and characterization of a novel tea tree oil nanogel using response surface methodology

Purpose: To develop and optimize nanoemulsion (NE)-based emulgel (EG) formulation as a potential vehicle for topical delivery of tea tree oil (TTO).

Methodology: Central composite design was adopted for optimizing the processing conditions for NE preparation by high energy emulsification method viz. surfactant concentration, co-surfactant concentration, and stirring speed. The optimized NE was developed into emulgel (EG) using pH sensitive polymer Carbopol 940 and triethanolamine as alkalizer. The prepared EG was evaluated for its pH, viscosity, and texture parameters, ex vivo permeation at 37?°C and stability. Antimicrobial evaluation of EG in comparison to conventional gel and pure TTO was also carried out against selected microbial strains.

Results and discussion: Optimized NE had particle size and zeta potential of 16.23?±?0.411?nm and 36.11?±?1.234?mV, respectively. TEM analysis revealed the spherical shape of droplets. The pH of EG (5.57?±?0.05?) was found to be in accordance with the range of human skin pH. EG also illustrated efficient permeation (79.58?μL/cm²) and flux value (J_SS) of 7.96?μL cm²/h through skin in 10?h. Viscosity and texture parameters, firmness (9.3?±?0.08?g), spreadability (2.26?±?0.06?mJ), extrudability (61.6?±?0.05?mJ), and adhesiveness (8.66?±?0.08?g) depict its suitability for topical application. Antimicrobial evaluation of EG with same amount of TTO as conventional gel revealed broader zones of growth inhibitions against all the selected microbial strains. Moreover, EG was also found to be nonirritant (PII 0.0833). These parameters were consistent over 90 d.

Conclusion: TTO EG turned out to be a promising vehicle for the topical delivery of TTO with enhanced therapeutic efficacy.     

Experimental investigations into electric discharge grinding and ultrasonic vibration-assisted electric discharge grinding of Inconel 601

The paper presents experimental investigations into electric discharge grinding (EDG) and ultrasonic vibration-assisted electric discharge grinding (UVAEDG) of Inconel 601. The process parameters selected for both processes were duty cycle, discharge current, pulse on time, grinding wheel speed, work speed, and speed ratio to study their influence on responses like surface roughness (R_a) and material removal rate (MRR). It was found that duty cycle, wheel speed, work speed, discharge current, speed ratio, and pulse duration significantly influenced MRR and R_a. It was inferred that MRR increased with increase in duty cycle, wheel speed, current, work speed, and pulse duration in both EDG and UVAEDG processes. It was also inferred that R_a increased with rise in duty factor, pulse on time, and discharge current in EDG and UVAEDG processes.     

Nanocrystalline Nd–Fe–B Anisotropic Magnets by Flash Spark Plasma Sintering

Flash spark plasma sintering (flash SPS) is an attractive method to obtain Nd–Fe–B magnets with anisotropic magnetic properties when starting from melt-spun powders. Compared to the benchmark processing route via hot pressing with subsequent die upsetting, flash SPS promises electroplasticity as an additional deformation mechanism and reduced tool wear, while maximizing magnetic properties by tailoring the microstructure—fully dense and high texture. A detailed parameter study is conducted to understand the influence of Flash SPS parameters on the densification and magnetic properties of commercial MQU-F powder. It is revealed that the presintering conditions and preheating temperature before applying the power pulse play a major role for tailoring grain size and texture in the case of hot deformation via Flash SPS. Detailed microstructure and magnetic domain evaluation disclose the texture enhancement with increasing flash SPS temperature at the expense of coercivity. The best compromise between remanence and coercivity (1.37 T and 1195 kA m⁻¹, respectively) is achieved through a combination of presintering at 500 °C for 120 s and preheating temperature of 600 °C, resulting in a magnet with energy product (BH)_max of 350 kJm⁻³. These findings show the potential of flash SPS to obtain fully dense anisotropic nanocrystalline magnets with high magnetic performance.