17315 research outputs found
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The formation of hydroxyl radicals during hydrodynamic cavitation in microfluidic reactors using salicylic acid dosimetry
No full textCavitation is a phase change phenomenon that generates highly energized bubbles due to low local pressures. The collapse of these bubbles releases this energy to the surrounding area in different forms upon the pressure recovery. Free radical production, which is considered as chemical effect of the bubble collapse, plays a major role in many applications, from wastewater treatment to material exfoliation. Although some studies underscore the importance of chemical effects for acoustic cavitation (AC), their investigations in hydrodynamic cavitation (HC) are challenging due to the difficulty in controlling cavitating flows. One of the approaches that could shed light on this challenging aspect is to shrink the reactor scale to micro-scale size (“HC on a chip”). In this regard, we investigated the chemical effects of HC using Salicylic Acid (SA) dosimetry in three different micro-scale designs (long diaphragm, micro-orifice, and micro-venturi configurations) and compared the results to those of a macro-scale HC reactor. High-speed visualization revealed important links between flow patterns and the formation of hydroxyl radicals (•OH), which contributed to the SA products. This study thus focused on comparing the effectiveness of the three micro-scale reactors in terms of •OH formation. According to the results, the “HC on a chip” concept demonstrated significantly higher efficiency in generating SA products compared to the macro-scale HC reactor. For instance, the micro-scale HC reactors achieved an SA concentration of approximately 0.6 μg/mL in just 5 cycles, while the macro-scale HC reactor required 164 cycles to reach a similar concentration (0.45 μg/mL). This substantial reduction in the number of cycles highlights the potential of micro-scale HC reactors for efficient and rapid generation of SA products
Enhancement of mechanical properties of carbon fiber epoxy composites using methylmethacrylate-butadiene-styrene (MBS) core-shell nanoparticles
No full textThis work investigates the use of readily dispersed methylmethacrylate-butadiene-styrene (MBS) core-shell nanoparticles to improve the mechanical properties of carbon fiber epoxy (CF/EP) composites. Through the vacuum-assisted resin transfer molding (VARTM) process, CF/EP composites were manufactured with varying MBS particle loadings from 1 wt. to 7 wt. %. The mechanical properties of the composites were determined via three-point bending, Charpy impact, short-beam shear, and Mode-I fracture toughness tests, adhering to the relevant ASTM standards. The results show that the addition of MBS particles significantly increased Mode-I interlaminar fracture toughness (GIc), with the highest increase observed at 7 wt. % particle loading, demonstrating a nearly 177% improvement over the reference composite. The flexural modulus of composites slightly decreased with 1 wt. % MBS nanoparticles, indicating increased flexibility, while a synergistic effect at 7 wt. % MBS enhanced stiffness and structural reinforcement. The incorporation of MBS nanoparticles in CF/EP composites also enhanced Charpy impact strength and damping properties, with the highest impact strength observed at 7 wt. % MBS. Higher MBS content reduced the storage modulus, while the glass transition temperature remained relatively unchanged
Development of an oxygen-insensitive Nrf2 reporter reveals redox regulation under physiological normoxia
No full textReactive oxygen species, particularly hydrogen peroxide (H2O2), play crucial roles in cellular signaling, with Nrf2 serving as a key transcription factor in maintaining redox homeostasis. However, the precise influence of H2O2 on Nrf2 activity under physiological normoxia remains unclear due to the limitations of oxygen-sensitive imaging methods. To address this, we developed and validated an oxygen-insensitive Nrf2 reporter named pericellular oxygen-insensitive Nrf2 transcriptional performance reporter (POINTER). We employed this reporter in human cerebral microvascular endothelial cells (hCMEC/D3). Using POINTER, we investigated how varying intracellular H2O2 concentrations affect Nrf2 regulation under normoxia (5 kPa O2) compared to hyperoxia (ambient air, 21 kPa O2). We manipulated intracellular H2O2 levels through exogenous application, chemogenetic production using a modified amino acid oxidase, and pharmacological induction with Auranofin. Our findings reveal that Nrf2 transcriptional activity is significantly lower under normoxia than under hyperoxia, supporting previous literature and expectations. Using POINTER, we found that both antioxidant pathway inhibition and sustained H2O2 elevation are essential for modulating Nrf2 activity. These findings provide new insights into the regulation of Nrf2 by H2O
High throughput microparticle production using microfabricated nozzle array
No full textPolymeric microparticles have triggered critical advancements in drug delivery systems, offering significant improvements in therapeutic efficacy by controlling the delivery while minimizing adverse side effects of the pharmaceuticals. However, conventional microparticle fabrication techniques face several limitations, such as particle size variability, early drug degradation, and production inefficiencies. In this study, we developed a microparticle production system (MPS) in which a precision spraying technology was integrated with a microfabricated nozzle array-based piezoelectric transducer. High-throughput microparticle production was achieved using Poly(d,l-lactide-co-glycolide) (PLGA) dissolved in dichloromethane (DCM) and dimethyl carbonate (DMC). The resulting PLGA microparticles exhibited remarkable consistency in size uniformity with an average diameter of 8.9 ± 1.7 μm. Detailed characterization through scanning electron microscopy (SEM) and focused ion beam (FIB) analyses revealed distinct surface and internal structures and demonstrated the effect of solvent volatility on microparticle morphology. Chloramphenicol (CHL) was used as a model drug, and an encapsulation efficiency of 38.7% and a loading efficiency of 16.2% were achieved. The PLGA microparticles showed sustained CHL release and demonstrated effective antibacterial activity against Escherichia coli (E. coli), highlighting their potential for controlled therapeutic applications. This developed MPS system offers a scalable and efficient approach for producing PLGA-based microparticles with controlled drug release profiles, making it valuable in the industrial-scale production of advanced drug delivery technologies
Mixing thermal coherent states for precision and range enhancement in quantum thermometry
No full textThe unavoidable interaction between thermal environments and quantum systems typically leads to the degradation of quantum coherence, which can be fought against by reservoir engineering. We propose the realization of a special mixture of thermal coherent states by coupling a thermal bath with a two-level system (TLS) that is longitudinally coupled to a resonator. We find that the state of the resonator is a special mixture of two oppositely displaced thermal coherent states, whereas the TLS remains thermal. This observation is verified by evaluating the second-order correlation coefficient for the resonator state. Moreover, we reveal the potential benefits of employing the mixture of thermal coherent states of the resonator in quantum thermometry. In this context, the resonator functions as a probe to measure the unknown temperature of a bath mediated by a TLS, strategically bridging the connection between the two. Our results show that the use of an ancillary-assisted probe may enhance the precision and broaden the applicable temperature range
Large deflection analysis of functionally graded reinforced sandwich beams with auxetic core using physics-informed neural network
No full textThis paper aims to investigate the large deflection behavior of a sandwich beam reinforced with functionally graded (FG) graphene platelets (GPL) together with an auxetic core, rested on a nonlinear elastic foundation. The nonlinear governing equations of the problem are derived using Hamilton’s principle based on the Euler-Bernoulli beam theory for large deflections. Five different distributions are considered to describe the dispersion of GPL in the top and bottom faces of the sandwich beam. The Physics-Informed Neural Network (PINN) method is employed to model the nonlinear deflection of the beam under various boundary conditions. This study highlights the effectiveness of PINN in handling the complexities of nonlinear structural analyses. The findings underscore the impact of the core auxeticity, GPL amount and distribution, and elastic foundation coefficient on the nonlinear deflection of the sandwich beam under different loading scenarios. For instance, using Type I configuration can reduce the deflection of the beam by nearly half compared to using Type IV. Furthermore, a nonlinear foundation with a unit coefficient results in a 48% reduction in deflection compared to the scenario without an elastic foundation
Bayesian frequency estimation under local differential privacy with an adaptive randomized response mechanism
No full textFrequency estimation plays a critical role in many applications involving personal and private categorical data. Such data are often collected sequentially over time, making it valuable to estimate their distribution online while preserving privacy. We propose AdOBEst-LDP, a new algorithm for adaptive, online Bayesian estimation of categorical distributions under local differential privacy (LDP). The key idea behind AdOBEst-LDP is to enhance the utility of future privatized categorical data by leveraging inference from previously collected privatized data. To achieve this, AdOBEst-LDP uses a new adaptive LDP mechanism to collect privatized data. This LDP mechanism constrains its output to a subset of categories that "predicts"the next user's data. By adapting the subset selection process to the past privatized data via Bayesian estimation, the algorithm improves the utility of future privatized data. To quantify utility, we explore various well-known information metrics, including (but not limited to) the Fisher information matrix, total variation distance, and information entropy. For Bayesian estimation, we utilize posterior sampling through stochastic gradient Langevin dynamics, a computationally efficient approximate Markov chain Monte Carlo (MCMC) method.We provide a theoretical analysis showing that (i) the posterior distribution of the category probabilities targeted with Bayesian estimation converges to the true probabilities even for approximate posterior sampling, and (ii) AdOBEst-LDP eventually selects the optimal subset for its LDP mechanism with high probability if posterior sampling is performed exactly. We also present numerical results to validate the estimation accuracy of AdOBEst-LDP. Our comparisons show its superior performance against non-adaptive and semi-adaptive competitors across different privacy levels and distributional parameters
Framing the Central Bank Digital Currency (CBDC) revolution
No full textAs global cooperation to develop and launch CBDCs further unfolds, the revolutionary innovation presents an emerging research field. This paper aims to provide a framework of CBDC by stressing its differences from other available digital currencies and cash in terms of advantages and disadvantages. The CBDC outlook, in its current and future, is presented. Additionally, an exploration of the prevalent themes in a cross-sectional analysis of tweets posted between 17 and 25 March 2021 with the #CBDC hashtags are presented to complement the discussion on the emerging landscape for informing the policy – and decision-makers on the opportunities and challenges involved
A fragile relationship: Turkey and the European Union moving beyond membership with external differentiated integration
No full textTurkey’s relations with the European Union depend on extensive legal instruments, drivers of interdependence and voluntary compliance to the EU rules. With an Association Agreement dating back to 1963 and accession negotiations opened in 2005, there is a high degree of asymmetric interdependence between Turkey and the EU. This article examines Turkish-EU relations from the angle of external differentiated integration (EDI). Accordingly, this article assesses the feasibility of the current state of Turkey’s fragile relations with the EU as a functional model of external differentiated integration. Turkish EDI provides an innovative framework for keeping Turkey anchored to the European order, for which neither full membership nor a complete break up seems plausible. To assess shades of non-membership for Turkey, the article relies on an extensive keyword-based assessment of EU-Lex documents, trade statistics and a co-occurrence network analysis for the EU’s 2012 and 2022 Progress Reports on Turkey. The findings shed light on the complexities of the EU’s EDI with non-members
Additive cyclic codes over Fq3
No full textLet Fq be an arbitrary finite field and n ≥ 2 be an integer with gcd(n,q) = 1. We study all Fq-linear additive cyclic codeseses over Fq3 of length n systematically. This much more complicated compared to the same task over Fq2. We obtain a canonical unique representation. We explicitly obtain the dual codes in the canonical form under the Euclidean and trace the Galois inner products. We characterize and construct large classes of complementary dual codes among Fq-linear additive cyclic codes over Fq3 of length n under the trace Euclidean and the trace Galois inner products. We obtain interesting differences depending on the canonical representation and also on the inner products. We also study subfield subcodes and trace (onto Fq) codes