Stable System Research Articles

India in the Global Microelectronics Market

The Indian government attaches high importance to the development of microelectronics industry in order to achieve the goals of Self-reliant India Campaign (Atmanirbhar Bharat Abhiyan) announced in May 2020. The main objectives of special programs and measures are to give an impetus to the domestic manufacturing sector, attract investments, and generate direct and indirect employment. The BJP government’s vision for electronics industry is focused on expanding production facilities to meet local demand and ramp up exports. It is important to note the impact of external/global factors as well. In searching for alternative options to China, large electronic companies are considering the possibility of transferring manufacturing operations to India, noting such country’s advantages like the fastest economic growth, large workforce, rapidly expanding middle class and stable political system. Step by step India keens to become a prominent player in the global microelectronics market. The article analyzes the key stages of the development of electronics industry in India, explores taken by the current central government efforts to promote electronics system design and IT hardware manufacturing in the country.

The Relationship Between Financial Development and Logistics Performance Index: A Panel ARDL Approach in Emerging Markets

The term "emerging markets" refers to countries that are undergoing economic and financial development. As financial development progresses in these nations, the capital available for international trade and the expansion of logistics infrastructure grows as well. This increased capital enables the financing of international trade activities and facilitates the execution of necessary logistics operations efficiently and effectively. Additionally, with enhanced financial development, it becomes easier to secure the capital required to improve logistics infrastructure and make it more functional. In this study, analyses are conducted using the Panel autoregressive distributed lag method in emerging market countries to evaluate the direct and indirect effects of financial development on logistics performance. The results reveal that increased access to financial institutions and markets positively affects logistics performance in both the short and long term. Among financial variables, the depth of financial institutions exhibits the strongest long-term influence, suggesting that a stable financial system is crucial for logistics efficiency. These insights provide valuable guidance for decision-makers aiming to strengthen logistics infrastructure and trade capabilities. By recognizing the role of financial development in supporting logistics performance, policymakers can craft strategies that support sustainable economic growth through improved logistics processes.

Probabilistic Robust Damping Controller Optimization for Mitigating Subsynchronous Control Interaction in DFIG and PMSG‐Based Wind Farms

ABSTRACTAdvanced control and mitigation solutions are required due to the enormous challenges posed by sub‐synchronous control interaction in wind farms. These concerns include system instability, potential damage to turbines, and grid stability issues. This research presents the probabilistic robust damping controller, an adaptive control approach, to address the issues in grid‐connected wind farms. The innovation employs the balanced remora optimization algorithm to optimize controller parameters, ensuring system stability under various conditions. For permanent magnet synchronous generator‐based wind farms with weak grid circumstances, critical elements such as the DC‐link voltage, the d‐q axis current reference, and the actual values in the grid‐side converter are essential for problem mitigation. The controller generates controlled output using these input signals. The MATLAB‐based implementation demonstrates the controller effectiveness in damping issues within a series‐compensated doubly fed induction generator. Comparative analysis with conventional controllers under different grid conditions and disturbances validates its superior performance. Time‐domain simulations, both with and without time delay, further confirm the controller's ability to enhance system stability and dampen the issues. Four schemes are used to evaluate the doubly fed induction generator‐based wind farms: wind speed at 13 m/s with 75% series compensation, 7 m/s with 75% compensation, 9 m/s with 45% compensation, and 9 m/s with 60% compensation. Under short circuit ratio, the wind farms based on permanent magnet synchronous generators are analyzed in three scenarios: normal, strong, and weak cases.

Current Technological Advances in Mucoadhesive Buccal Drug Delivery Systems and Their Therapeutic Applications

Buccal drug delivery has emerged as a promising route of administration, offering distinct advantages over conventional oral delivery systems. The unique physiological characteristics of the buccal mucosa, including rich vascularity and relatively high permeability, make it an attractive site for both local and systemic drug administration. Bioadhesive formulations have revolutionized buccal drug delivery by ensuring prolonged contact with the mucosal surface, thereby enhancing drug absorption and bioavailability. Recent developments in polymer science have introduced novel mucoadhesive materials, including thiolated polymers, lectins, and stimuli-responsive systems, which demonstrate superior adhesion properties and controlled release characteristics. Various formulation approaches, such as films, tablets, patches, and hydrogels, have been developed to optimize drug delivery through the buccal route. These systems incorporate permeation enhancers, enzyme inhibitors, and novel drug carriers to overcome the biological barriers associated with buccal delivery. The application of nanotechnology has further advanced the field, introducing nanostructured formulations that exhibit enhanced mucoadhesion and improved drug permeation. Current research focuses on developing intelligent delivery systems that respond to physiological triggers and maintain therapeutic drug levels. Understanding the critical factors affecting bioadhesion, including polymer characteristics, environmental conditions, and physiological variables, has led to the development of more effective formulations. The integration of modern analytical techniques and quality control measures ensures the development of stable and efficient buccal delivery systems and improves patient compliance and therapeutic outcomes

Interfacial instability in a viscoelastic microfluidic coflow system

Understanding interfacial instability in a coflow system has relevance in the effective manipulation of small objects in microfluidic applications. We experimentally elucidate interfacial instability in stratified coflow systems of Newtonian and viscoelastic fluid streams in microfluidic confinements. By performing a linear stability analysis, we derive equations that describe the complex wave speed and the dispersion relationship between wavenumber and angular frequency, thus categorizing the behaviour of the systems into two main regimes: stable (with a flat interface) and unstable (with either a wavy interface or droplet formation). We characterize the regimes in terms of the capillary numbers of the phases in a comprehensive regime plot. We decipher the dependence of interfacial instability on fluidic parameters by decoupling the physics into viscous and elastic components. Remarkably, our findings reveal that elastic stratification can both stabilize and destabilize the flow, depending on the fluid and flow parameters. We also examine droplet formation, which is important for microfluidic applications. Our findings suggest that adjusting the viscous and elastic properties of the fluids can control the transition between wavy and droplet-forming unstable regimes. Our investigation uncovers the physics behind the instability involved in interfacial flows of Newtonian and viscoelastic fluids in general, and the unexplored behaviour of interfacial waves in stratified liquid systems. The present study can lead to a better understanding of the manipulation of small objects and production of droplets in microfluidic coflow systems.

Thermal Management Approach to Stabilization of Disordered Active Sites for Sabatier Reaction.

The transition metal nanocatalysts containing disordered active sites can potentially achieve efficient Sabatier reactions with high selectivity. However, it remains a challenge to maintain the stability of these active sites in such an exothermic reaction. Here, a thermal management approach is reported to address this challenge. Specifically, an efficient and stable catalytic system is developed by integrating urchin-like Ru nanoparticles with disordered active sites (d-RuNUs) and multi-walled carbon nanotubes (MWCNTs) as heat transfer framework, which achieves a CH4 yield of 3.3mol g-1 h-1 with nearly 100% selectivity in 12h. The characterizations reveal that the thermal-induced crystallization seriously weakens the adsorption of CO2, leading to significant degradation of catalytic performance. The heat transfer simulation confirms that the MWCNTs with high thermal conductivity play a key role in rapidly redistributing the reaction heat, thereby preventing the crystallization of disordered structures. This work elucidates the deactivation mechanism of disordered active sites in exothermic reactions and opens the avenue for local thermal management of non-thermal equilibrium reactions.

A multi-scale and multi-modal convolutional neural network for condition monitoring of transmission line

Abstract Monitoring the fatigue damage of transmission lines is crucial for stable power system operation. However, existing model-driven methods face challenges such as high computational complexity and reliance on expert knowledge, while data-driven methods require large amounts of abnormal state data. To address these issues, a multi-scale and multi-modal convolutional neural network (CNN) is proposed for real-time condition monitoring of transmission lines. Key steps include: firstly, empirical Fourier decomposition is used to decompose the original signals, extracting multi-scale state information at different frequency scales. Then, time-domain, frequency-domain, and time–frequency domain analyses are performed on the decomposed signals to capture multi-modal information. Based on this, a multi-modal fusion network is proposed based on a CNN to extract shallow and deep features, with a fully connected layer used for multi-modal feature fusion. Notably, the algorithm is implemented on a microprocessor for practical application. Experimental results show that the proposed model achieves a diagnostic accuracy of 93.06%, outperforming classical networks. It also surpasses models trained solely on time, frequency, or time–frequency features by 25.18%, 21.8%, and 19.3%, respectively.

Robust, Thermally Stable and Impurity-Tolerant Aluminum-Based Catalyst System for Polylactide Production under Industrial Conditions

Robust, Thermally Stable and Impurity-Tolerant Aluminum-Based Catalyst System for Polylactide Production under Industrial Conditions

Synthetic G-jet-structures in modal homotopy type theory

Abstract This article constructs the moduli stack of torsion-free $G$ -jet-structures in homotopy type theory with one monadic modality. This yields a construction of this moduli stack for any $\infty$ -topos equipped with any stable factorization systems. In the intended applications of this theory, the factorization systems are given by the deRham-Stack construction. Homotopy type theory allows a formulation of this abstract theory with surprisingly low complexity. This is witnessed by the accompanying formalization of large parts of this work.

Non-covalent interactions in conjugated polymer blends: Insights into the stability of PVC/PM6 and CPE/PM6 systems.

This study investigates the role of non-covalent interactions (NCIs) in stabilizing blends of the conjugated polymer PM6 with additives polyvinyl chloride (PVC) and chlorinated polyethylene (CPE). Using the NCI index, reduced density gradient analysis, and energy decomposition analysis (EDA), we quantify the contributions of van der Waals forces, hydrogen bonding, and steric repulsions in these systems. Our results reveal that PVC/PM6 blends exhibit stronger NCI, particularly C-H⋯π and C-Cl⋯π interactions, compared to CPE/PM6 blends. EDA further shows that dispersion forces and electrostatic interactions are the primary stabilizing factors in the PVC blend, with hydrogen bonding also playing a critical role. These findings highlight the importance of chlorine content in enhancing NCI and promoting the stability of polymer blends. The insights from this work provide valuable guidance for designing more stable polymer-additive systems in organic electronics and other material applications.

Asymmetric LKF approach for stability analysis of multi-area load frequency control systems with time-varying delays

ABSTRACT The widespread use of communication networks in power systems to send and receive control signals causes time delays in the feedback loop. Improper handling of these delays might degrade controller performance or cause system instability. This work presents new stability criteria that are less conservative in analysing the influence of delays on the stable operation of PI controller-based multi-area power systems with uncertainties and disturbances. An asymmetric Lyapunov-Krasovskii functional technique is used to reduce conservatism by relaxing the condition that all matrices associated with the LKF formulation need not be symmetric or have positive definiteness. In contrast, the symmetric LKF requires all matrices to be symmetric. Two tight-bound integral inequalities are implemented to compute the quadratic integral terms included in the derivative of asymmetric LKF. The less conservative stability conditions are derived for multi-area LFC systems subjected to delays, parameter uncertainties, and disturbances by utilising asymmetric LKF. The superiority of the proposed stability criterion is determined both theoretically and through simulation. According to the analysis, the proposed stability criterion provides higher delay margins than existing techniques.

Tunable semiconductor lasers for enhancing optical fiber patch cord performance in stable optical communication systems

Tunable semiconductor lasers for enhancing optical fiber patch cord performance in stable optical communication systems

Capacitance-based mass flow rate measurement of two-phase hydrogen in a 0.5 in. tube

Mass flow rate is a critical measurement parameter when designing cryogenic hydrogen fluid systems. It is important in custody transfer applications for calculating financial obligations, fundamental fluid property research/modeling, and fluid system design applications to optimize chill down performance, maintain thermal equilibriums, and provide feedback control for pumps and valves. However, due to the large temperature differential between cryogenic fluids and the environment, there is often multiphase flow during system chilldown and steady state operation. Current available cryogenic flow measurement techniques are not equipped to deal with the complex multiphase flow inherent in cryogenic fluid systems, resulting in significant measurement errors. This mass flow measurement inaccuracy can cause financial loss, system instability, and even component failure, resulting in a strong market demand for a multiphase cryogenic mass flow meter to optimize and control sophisticated and costly cryogenic systems. This paper presents a solution in the form of a novel capacitance-based technique for measuring the multiphase mass flow rate of cryogenic hydrogen in a terrestrial environment. The device was calibrated and tested on a ½” tube multiphase hydrogen flow loop at a cryogenic hydrogen test facility. An error of ± 2 % full scale was achieved across a range of flow conditions, including transient and steady states.

Diacylglycerol kinase ζ is a positive insulin secretion regulator in pancreatic β-cell line MIN6

Some isoforms of diacylglycerol (DAG) kinase (DGK), an enzyme converting DAG into phosphatidic acid, i.e., DGKα, γ and δ, have been reportedly involved in the regulation of pancreatic β-cell function. DGKζ has also been reported to be expressed in rat pancreatic β-cells. However, its function in pancreatic β-cells remains unknown. The present study aimed to elucidate the function of DGKζ in pancreatic β-cells. The expression of DGKζ was detected in the β-cell line MIN6B and mouse pancreatic islets and in the cytoplasmic fraction from MIN6B cells. The knockdown of DGKζ with siRNA significantly decreased glucose-induced insulin secretion in MIN6B cells. The induction of DGKζ expression in MIN6CEon1 cells with a doxycycline-inducible stable expression system significantly increased glucose-induced insulin secretion. In contrast, glucose-induced insulin secretion was not changed when a kinase-dead DGKζ mutant (G356D) was overexpressed in MIN6CEon1 cells, indicating that a mechanism dependent on its kinase activity mediates the facilitatory effect of DGKζ on glucose-induced insulin secretion. Additionally, we revealed that DGKζ overexpression exhibited no effect on cell cycle of MIN6 cells. These results suggest that DGKζ plays a facilitatory role in insulin secretion in pancreatic β-cells.

Comparison of Nondeterministic Stable Linear Systems by ($\gamma,\delta$)-Similarity

Comparison of Nondeterministic Stable Linear Systems by ($\gamma,\delta$)-Similarity

A Kernel-Based Approach to Errors-in-Variables Identification of Stable Multivariable Linear Systems

A Kernel-Based Approach to Errors-in-Variables Identification of Stable Multivariable Linear Systems

Stimulated Pickering emulsion stabilized by binary particles with contrasting wettability and trace surfactant

The investigationof self-assembled particle structures at fluid interfaces has gained considerable interest across various fields. In particular, Pickering emulsions (PEs) stabilized by binary particles co-assembling at these interfaces have attracted even more attention. To explore the self-assembly process of superhydrophobic and superhydrophilic particles at oil–water (O/W) interfaces influenced by a trace amount of surfactant, a series of experiments were conducted. A small quantity (0.01 mmol·L−1) of dodecyltrimethylammonium bromide (DTAB) was introduced, establishing a variable stable emulsion system with high salt tolerance, capable of withstanding up to 6 mol·L−1 NaCl, in synergism with the particles. The DTAB concentration required to stabilize the O/W emulsion with particles was as low as 0.001 mmol·L−1. The stability and type of the resulting emulsion could be adjusted by varying the ratio of hydrophobic to hydrophilic particle (R) or by modifying acid/base conditions. The systems exhibited robust cyclic acid/base regulated demulsification and phase inversion behavior, maintaining stability over at least 10 cycles. Results indicated that the stability and nature of the emulsion were influenced by the curvature of the interface formed by the self-assembled interfacial particle structures, arising from the competitive adsorption of both types of particles and trace surfactant. Further analysis revealed a correlation between interfacial curvature and the surface charges of the particles, which could be modulated through DTAB adsorption. This study elucidated the behavior of hydrophilic and hydrophobic particle self-assembly at interfaces, provided a straightforward strategy for co-preparing switchable emulsions using superhydrophilic and superhydrophobic particles, and expanded the range of amphiphilic particles available for producing PEs. This approach presents significant potential for future research and applications in the field of PEs.

Fabrication and characterization of potato short amylose, zein, and pectin ternary composite particles stabilized pickering emulsions and their application on nuciferine delivery

Nuciferine exhibits properties such as reducing blood sugar and fat, however, it is hindered by its poor water solubility and low bioavailability. Pickering emulsions can efficiently encapsulate, protect and deliver active ingredients. In recent years, the use of biologically derived natural materials as emulsifiers to construct Pickering emulsions has become a research hotspot. This research utilized an enzymatic hydrolysis technique to produce short amylose. Subsequently, a ternary composite of short amylose (DBS), zein, and pectin (PEC) was formulated to stabilize Pickering emulsion, with the incorporation of nuciferine aiming to enhance the performance of lotus leaves in terms of both stability and bioavailability. The study revealed that varying amounts of DBS addition had a significant impact on the micromorphological structure and functional properties of DBS-Zein-PEC ternary composite particles. Specifically, the addition of 0.4 g of DBS led to a notable reduction in particle size to 735.2 nm and Zeta potential to −29.6 mV, creating a three-dimensional network with a closely packed lamellar structure. Optimal process conditions for preparing Pickering emulsion included a 3-minute homogenization time, rotation speed of 15000 rpm, and 5 % ternary composite particle addition. Under these conditions, O/W Pickering emulsion was successfully prepared, achieving a 90.5 % encapsulation rate for nuciferine. The resulting emulsion exhibited a minimum particle size of 4.09 μm, displayed good storage stability, resistance to salt ions and pH variations, viscous fluid characteristics, tolerance to oral and gastric environments, and slow release of nuciferine in the small intestine, thereby enhancing its bioavailability. These findings offer insights into the loading and delivery of nuciferine and serve as a technical guide for developing highly stable emulsion gel systems.

Fast-response and stable weak measurement system for protein-antibody specific detection

The probing technique for the specific binding of proteins and antibodies plays a crucial role in the domains of biotechnology, medicine, and pharmacology. The development of rapid and highly sensitive probing technique for specific interactions remains an enduring focus. This paper presents a quantum weak measurement technique for rapid and highly sensitive detection of protein-antibody specific binding, effectively reducing noise and achieving measurement accuracy approaching the standard quantum limit. The speed of our detection technology is determined by the response time of the dual-channel detection, which can reach nanoseconds. The results show that the detection limit can reach 26 ng/ml, and the detection range is 0∼3.44μg/ml. The quantum weak measurement technique developed in this study offers a heuristic approach for protein-antibody interaction detection with broad application prospects.

Optimization of the seru production system with demand fluctuation: A Mean-CVaR model

The increasingly diverse and non-deterministic customer demands have given rise to the seru production system. This study aims to address the multi-objective seru formation problem under demand fluctuations, with the mean and the CVaR or standard deviation of total completion time minimized. In particular, two multi-objective stochastic optimization models, i.e., Mean-CVaR and Mean-Std, are constructed to determine the number of seru, the allocation scheme of workers and batches. Then, the Local Search Fast Non-dominated Sorting Genetic Algorithm (NSGA-II-LS) is designed to solve the proposed models. Numerical experiments validate the method’s effectiveness by demonstrating that, compared to the Mean-Std model, the Mean-CVaR model enhances the seru system’s capability and stability in coping with stochastic demand fluctuations through an average reduction of 4% in expected value and an average reduction of 36% in standard deviation. The effects of confidence level, the product batch number, and the standard deviation on the results have been analyzed. The results show that the Mean-CVaR method helps achieve a more stable seru system in terms of reducing standard deviation. Moreover, product batch division is beneficial to the CVaR of total processing time but detrimental to the mean processing time.