Search Results (3,165)

Digital twins represent a transformative innovation for battery energy storage systems (BESS), offering real-time virtual replicas of physical batteries that enable accurate monitoring, predictive analytics, and advanced control strategies. These capabilities promise to significantly enhance system efficiency, reliability, and lifespan. Yet, despite the clear technical potential, large-scale deployment of digital twin-enabled battery systems faces critical governance barriers. This study identifies three major challenges: fragmented standards and lack of interoperability, weak or misaligned market incentives, and insufficient cybersecurity safeguards for interconnected systems. The central contribution of this research is the development of a comprehensive governance framework that aligns these three pillars—standards, market and regulatory incentives, and cybersecurity—into an integrated model. Findings indicate that harmonized standards reduce integration costs and build trust across vendors and operators, while supportive regulatory and market mechanisms can explicitly reward the benefits of digital twins, including improved reliability, extended battery life, and enhanced participation in energy markets. For example, simulation-based evidence suggests that digital twin-guided thermal and operational strategies can extend usable battery capacity by up to five percent, providing both technical and economic benefits. At the same time, embedding robust cybersecurity practices ensures that the adoption of digital twins does not introduce vulnerabilities that could threaten grid stability. Beyond identifying governance gaps, this study proposes an actionable implementation roadmap categorized into short-, medium-, and long-term strategies rather than fixed calendar dates, ensuring adaptability across different jurisdictions. Short-term actions include establishing terminology standards and piloting incentive programs. Medium-term measures involve mandating interoperability protocols and embedding digital twin requirements in market rules, and long-term strategies focus on achieving global harmonization and universal plug-and-play interoperability. International examples from Europe, North America, and Asia–Pacific illustrate how coordinated governance can accelerate adoption while safeguarding energy infrastructure. By combining technical analysis with policy and governance insights, this study advances both the scholarly and practical understanding of digital twin deployment in BESSs. The findings provide policymakers, regulators, industry leaders, and system operators with a clear framework to close governance gaps, maximize the value of digital twins, and enable more secure, reliable, and sustainable integration of energy storage into future power systems. Full article

As the realization of fully autonomous driving becomes increasingly plausible, its rapid development raises serious privacy concerns. At present, while personal information of passengers and pedestrians is routinely collected, its purpose and usage history are rarely disclosed, and pedestrians in particular are effectively deprived of any meaningful control over their privacy. Furthermore, no institutional framework exists to prevent the misuse or abuse of such data by authorized insiders. This study proposes the application of a novel privacy protection framework—Verifiable Record of AI Output (VRAIO)—to autonomous driving systems. VRAIO encloses the entire AI system behind an output firewall, and an independent entity, referred to as the Recorder, conducts purpose-compliance screening for all outputs. The reasoning behind each decision is recorded in an immutable and publicly auditable format. In addition, institutional deterrence is enhanced through penalties for violations and reward systems for whistleblowers. Focusing exclusively on outputs rather than input anonymization or interpretability of internal AI processes, VRAIO aims to reconcile privacy protection with technical efficiency. This study further introduces two complementary mechanisms to meet the real-time operational demands of autonomous driving: (1) pre-approval for designated outputs and (2) unrestricted approval of internal system communication. This framework presents a new institutional model that may serve as a foundation for ensuring democratic acceptance of fully autonomous driving systems. Full article

The synergistic effect of using D2EHPA and TOPO together to enhance the extraction of samarium(III) from aqueous media via emulsion liquid membrane (ELM) technology was explored. D2EHPA in binary mixtures with TBP and in ternary mixtures with TOPO and TBP was also tested. Among the tested extractants, a binary mixture of 0.1% (w/w) D2EHPA and 0.025% (w/w) TOPO achieved 100% samarium(III) extraction at a low loading. This mixture outperformed D2EHPA-TBP and other systems because D2EHPA strongly binds to Sm(III) ions, while TOPO increases the solubility and transport efficiency of metal complexes. Additionally, process factors that optimize performance and minimize emulsion breakage were examined. Key insights for successfully implementing the process include the following: 5 min emulsification with 0.75% Span 80 in kerosene at pH 6.7 (natural), 250 rpm stirring, a 1:1 internal/membrane phase volume ratio, a 20:200 treatment ratio, and a 0.2 N HNO₃ stripping agent. These insights produced stable, fine droplets, enabling complete recovery and rapid carrier regeneration without emulsion breakdown. Extraction kinetics accelerate with temperature up to 35 °C but declined above this limit due to emulsion rupture. The activation energy was calculated to be 33.13 kJ/mol using pseudo-first-order rate constants. This suggests that the process is diffusion-controlled rather than chemically controlled. Performance decreases with Sm(III) feed concentrations greater than 200 mg/L and in high-salt matrices (Na₂SO₄ > NaCl > KNO₃). Integrating these parameters yields a scalable, low-loading ELM framework capable of achieving complete Sm(III) separation with minimal breakage. Full article

This study focuses on the power systems of inland waterway vessels in Chinese Yangtze River, systematically outlining the low-carbon technology pathways for different power system types. A comparative analysis is conducted on the technical feasibility, emission reduction potential, and economic viability of LNG, methanol, ammonia, pure electric and hybrid power systems, revealing the bottlenecks hindering the large-scale application of each system. Key findings indicate that: (1) LNG and methanol fuels offer significant short-term emission reductions in internal combustion engine power systems, yet face constraints from methane slip and insufficient green methanol production capacity, respectively; (2) ammonia enables zero-carbon operations but requires breakthroughs in combustion stability and synergistic control of NO_X; (3) electric vessels show high decarbonization potential, but battery energy density limits their range, while PEMFC lifespan constraints and SOFC thermal management deficiencies impede commercialization; (4) hybrid/range-extended power systems, with superior energy efficiency and lower retrofitting costs, serve as transitional solutions for existing vessels, though challenged by inadequate energy management strategies and multi-equipment communication protocol interoperability. A phased transition pathway is proposed: LNG/methanol engines and hybrid systems dominate during 2025–2030; ammonia-powered systems and solid-state batteries scale during 2030–2035; post-2035 operations achieve zero-carbon shipping via green hydrogen/ammonia. Full article

This study investigates the effect of a nonlinear saturation controller (NSC) on the van der Pol–Mathieu–Duffing oscillator (VMDO). The oscillator is a single degree of freedom (DOF) system. It is driven by an external force. It is described by a nonlinear differential equation (DE). The multiple-scale perturbation method (MSPT) is applied. It gives second-order analytical solutions. The first indirect Lyapunov method is used. It provides the frequency–response equation. It also shows the stability conditions. Internal resonance is included. The analysis considers steady-state responses. It studies simultaneous primary resonance with a 1:2 internal resonance (${\Lambda }_1\cong {\varpi }_1$ and ${\varpi }_1\cong 2{\varpi }_2$). Time–response simulations are presented. They show controlled and uncontrolled systems. Numerical solutions (NSs) are obtained with the fourth-order Runge–Kutta method (RK-4). They are compared with the approximate analytical solution (AS). The agreement is strong. It confirms the perturbation method. It shows that the method captures the main system dynamics. Full article

In the Eastern Cape Province of South Africa, rural women agripreneurs encounter ongoing structural challenges in accessing formal finance, securing land rights, and gaining leadership roles, despite their vital contribution to agriculture and food security. This research combines a thematic review of secondary sources from 2018 to 2024 with an embedded case study based on primary qualitative data with women involved in the Citrus Growers Association–Grower Development Company (CGA–GDC) public–private partnership. This dual approach connects local, real-world entrepreneurial experiences with global financial inclusion initiatives, especially the G20 Women’s Empowerment Principles and the G20 Development Agenda. The findings highlight a consistent gap between policy and practice: while frameworks at both national and international levels advocate for women’s financial inclusion, actual implementation in rural agribusiness often neglects gender differences. Women’s engagement is limited by insecure land rights, restricted access to formal credit, male-controlled cooperative management, and insufficient gender-specific data monitoring. Drawing comparative insights from Kenya, India, and West Africa, the study proposes seven interconnected policy suggestions, such as establishing gender-disaggregated data systems, expanding women-led cooperatives, reforming land tenure laws, including entrepreneurial financial literacy in capacity-building programmes, and utilising gender-sensitive digital finance solutions. By connecting grassroots empirical evidence with global policy discussions, this study aims to contribute to academic debates and practical efforts to develop gender-responsive financial ecosystems, thereby boosting women’s economic independence, entrepreneurial activity, and rural progress in South Africa and similar contexts in the Global South. Full article

The ability to identify and control the sex of embryos holds significant commercial implications for livestock production. Due to the high costs and instability of detection methods, it is necessary to establish a time-saving, effective, simple, and reliable method to identify the sex of mammalian embryos. This study designs primer probes based on the SRY gene sequence in the sex-determining region of the Y chromosome of sheep and combines qPCR to amplify both the SRY gene and the internal reference gene GAPDH as a control. By adjusting and optimizing the detection system with ultra-trace of genomic DNA (gDNA) from sheep blood and embryos, we sexed sheep embryos cultured in vitro. The results show that male embryos exhibit specific amplification bands for both the GAPDH and SRY genes, while female embryos only have amplification bands for the GAPDH gene. The sensitivity of the sheep embryo sex identification system established in this study can be as low as 5.64 pg of DNA, with an accuracy rate of 100% for embryo sex identification. Full article

The growing need for efficient battery reuse and recycling requires rapid, reliable methods to assess the state of health (SoH) of lithium-ion cells. Conventional SoH estimation based on full charge–discharge cycling is slow, energy-intensive, and unsuitable for dismantled cells with unknown histories. This work presents an automated diagnostic approach using Electrochemical Impedance Spectroscopy (EIS) combined with Electrical Equivalent Circuit (EEC) modeling for fast, non-invasive SoH estimation. A correlation between fitted EIS parameters and cell degradation stages was established through controlled aging tests on NMC-based lithium-ion cells. The methodology was implemented in custom software (BaterurgIA) integrated into a robotic testing bench, enabling automatic EIS acquisition, data fitting, and SoH determination. The system achieves SoH estimation with 5–10% accuracy for cells in intermediate and advanced degradation stages, while additional parameters improve sensitivity during early aging. Compared to conventional cycling methods, the proposed approach reduces diagnostic time from hours to minutes, minimizes energy consumption, and offers predictive insights into internal degradation mechanisms. This enables fast and reliable cell grading for reuse, reconditioning, or recycling, supporting the development of scalable solutions for battery second-life applications and circular economy initiatives. Full article

This paper presents a low-cost variable buoyancy system (VBS) that can be integrated into Hybrid Aerial Underwater Vehicles (HAUVs). HAUVs are widely used in scientific research and must be lightweight and highly maneuverable to ensure sufficient endurance and operational reliability in underwater/air environments. To meet these key requirements, this study designs a low-cost and sustainable VBS that can adjust the attitude and depth of the HAUV during underwater operations. By redesigning the pipeline structure, the number of airbags, and their placement, internal gas self-circulation was achieved, thereby reducing costs. The PID controller based on depth and attitude information was further developed to ensure that the VBS operated more stably under complex underwater conditions. Field experiments on the application of the designed VBS on an HAUV based on a PID controller showed that the HAUV with the VBS could maintain the desired robot attitude and vertical speed and perform stable vertical movements. Full article

Background/Objectives: This study examines individual perceptions of national healthcare system efficiency before and after the COVID-19 pandemic across 18 countries grouped into three clusters (the Anglo-world, Europe, East Asia). This paper aims to identify the demographic, socioeconomic, health-related, and macroeconomic healthcare drivers of public assessments, and explain changes in attitudes between 2011–2013 and 2021–2023. Methods: Using individual-level data from the International Social Survey Programme (ISSP) for 2011–2013 and 2021–2023, logistic regression models of perceived healthcare inefficiency are estimated. In addition, the Oaxaca–Blinder decomposition model is adopted in order to decompose the assessment gap between the two periods. Models include a range of individual demographic and socioeconomic characteristics and national healthcare controls (healthcare expenditure, potential years of life lost). Results: Health-related factors, especially self-assessed health and trust in doctors, consistently emerge as predictors of more favourable evaluations across regions and periods. Higher national healthcare expenditure is associated with more positive public views and is the single largest contributor to the improved assessments in 2021–2023. Demographic and socioeconomic variables show smaller regionally and temporally heterogeneous effects. Decomposition indicates that both changes in observed characteristics (notably, expenditure and trust) and unobserved behavioural, cultural, or institutional shifts account for the gap in public healthcare assessments between the two time periods. Conclusions: Public assessments of healthcare systems are primarily shaped by individual health status, trust in providers, and national spending rather than differential demographic and socioeconomic traits. Therefore, policymakers should couple targeted investments in the healthcare sector in order to address adequately public healthcare needs, and strengthen doctor–patient relationships in order to sustain public support. Future research should focus on disentangling the cultural and behavioural pathways influencing healthcare attitudes. Full article

This study introduces a novel energy-based inverse method for estimating residual stresses in structures composed of one-dimensional elements undergoing elastic–plastic deformation. The problem is reformulated as a global optimization task governed by the principle of minimum total potential energy. Rather than solving equilibrium equations directly, the internal stress distribution is inferred by minimizing the structure’s total potential energy using a real-coded genetic algorithm. This approach avoids gradient-based solvers, matrix assembly, and incremental loading, making it suitable for nonlinear and history-dependent systems. Plastic deformation is encoded through element-wise stress-free lengths, and a dynamic fitness exponent strategy adaptively controls selection pressure during the evolutionary process. The method is validated on single- and multi-bar truss structures under axial tensile loading, using a bilinear elastoplastic material model. The results are benchmarked against nonlinear finite element simulations and analytical calculations, demonstrating excellent predictive capability with stress errors typically below 1%. In multi-material systems, the technique accurately reconstructs tensile and compressive residual stresses arising from elastic–plastic mismatch using only post-load geometry. These results demonstrate the method’s robustness and accuracy, offering a fully non-incremental, variational alternative to traditional inverse approaches. Its flexibility and computational efficiency make it a promising tool for residual stress estimation in complex structural applications involving plasticity and material heterogeneity. Full article

Aerodynamic ablation of external control surfaces and structural complexity in hypersonic reentry vehicles (HRVs) pose significant challenges for maneuverability and system reliability. To address these issues, this study develops a novel bank-to-turn (BTT) control strategy integrating a single internal moving mass with differential ailerons, eliminating reliance on ablation-prone elevators/rudders while enhancing internal space utilization. A coupled 7-DOF dynamics model explicitly quantifies inertial-rolling interactions induced by the moving mass, revealing critical stability boundaries for roll maneuvers. To ensure robustness against aerodynamic uncertainties, aileron failures, and high-frequency mass-induced disturbances, a dynamic inversion controller is augmented with an L1 adaptive layer decoupling estimation from control for improved disturbance rejection. Monte Carlo simulations demonstrate: (1) a 20.6% reduction in roll-tracking error (L₂-norm) under combined uncertainties compared to dynamic inversion control, and (2) a 72% suppression of oscillations under aerodynamic variations. Comparative analyses confirm superior transient performance and robustness in worst-case scenarios. This work offers a practical solution for high-maneuverability hypersonic vehicles, with potential applications in reentry vehicle design and multi-actuator system optimization. Full article

Femtosecond lasers have evolved continuously over the past three decades, enabling the transition of research from fundamental studies in atomic and molecular physics to the realm of practical applications. In femtosecond laser amplifiers, to ensure strict synchronization between the seed laser pulse and the pump laser, enabling their precise overlap during the amplification process and avoiding a decline in pulse amplification efficiency and the generation of undesired phase noise, this study designed a synchronous timing signal generation system based on the combination of FPGA and analog delay. This system was investigated from three aspects: delay pulse width adjustment within a certain range, precise delay resolution, and external trigger jitter compensation. By using a FPGA digital counter to achieve coarse-delay control over a wide range and combining it with the method of passive precise fine delay, the system can generate synchronous delay signals with a large delay range, high precision, and multiple channels. Regarding the problem of asynchronous phase between the external trigger and the internal clock, a jitter compensation circuit was proposed, consisting of an active gated integrator and an output comparator, which compensates for the uncertainty of trigger timing through analog delay. The verification of this study shows that the system operates stably under an external trigger with a repetition frequency of 80 MHz. The output delay range is from 10 ns to 100 $\mu$s, the coarse-delay resolution is 10 ns, the fine-delay adjustment step is 1.25 ns, and the pulse jitter is reduced from a maximum of 10 ns to the hundred-picosecond level. This meets the requirements of femtosecond laser amplifiers for synchronous trigger signals and offers essential technical support and fundamental assurance for the high-power and high-efficiency amplification of Ti:sapphire ultrashort laser pulses. Full article

Motor impairments significantly affect individuals’ ability to perform activities of daily living, reducing autonomy and quality of life. In response to this, robot-assisted rehabilitation has emerged as an effective and practical solution, enabling controlled limb movements and supporting functional recovery. This study presents the development of an upper-limb exoskeleton designed to assist rehabilitation by integrating neurophysiological signal processing and real-time control strategies. The system incorporates a proportional–derivative (PD) controller to execute cyclic flexion and extension movements based on a sinusoidal reference signal, providing repeatability and precision in motion. The exoskeleton integrates a brain–computer interface (BCI) that utilizes electroencephalographic signals for therapy selection and engagement enabling user-driven interaction. The EEG data extraction was possible by using the UltraCortex Mark IV headset, with electrodes positioned according to the international 10–20 system, targeting alpha-band activity in channels O1, O2, P3, P4, Fp1, and Fp2. These channels correspond to occipital (O1, O2), parietal (P3, P4), and frontal pole (Fp1, Fp2) regions, associated with visual processing, sensorimotor integration, and attention-related activity, respectively. This approach enables a more adaptive and personalized rehabilitation experience by allowing the user to influence therapy mode selection through real-time feedback. Experimental evaluation across five subjects showed an overall mean accuracy of 86.25% in alpha wave detection for EEG-based therapy selection. The PD control strategy achieved smooth trajectory tracking with a mean angular error of approximately 1.70°, confirming both the reliability of intention detection and the mechanical precision of the exoskeleton. Also, our core contributions in this research are compared with similar studies inspired by the rehabilitation needs of stroke patients. In this research, the proposed system demonstrates the potential of integrating robotic systems, control theory, and EEG data processing to improve rehabilitation outcomes for individuals with upper-limb motor deficits, particularly post-stroke patients. By focusing the exoskeleton on a single degree of freedom and employing low-cost manufacturing through 3D printing, the system remains affordable across a wide range of economic contexts. This design choice enables deployment in diverse clinical settings, both public and private. Full article

In Central Asian countries (CACs) Yes. we agree to remove Highlights part atmosphere pollution is increasing due to population growth, economic growth, agricultural development, energy consumption and climate change. The countries of the region developed climate change adaptation strategies—Nationally Determined Contributions (NDCs) under the UN Framework Convention on Climate Change (UNFCCC). At the same time, regional integration, which should be a necessary condition for achieving the Sustainable Development Goals (SDGs) in the solving of general environmental problems, is not involved. This article shows the importance of a comprehensive analysis of greenhouse gas (GHG) and non-greenhouse emissions into the atmosphere for the entire Central Asian region as a single ecosystem. The energy intensity of national economies structure was chosen as the main factor determining the level of pollution. The analysis shows that over the past 30 years, the main part of the commodity exports (73.6–81.4%) of Kazakhstan and Turkmenistan has been fossil natural resources. There is a strong economic dependence on coal and other types of fuel, which leads to atmospheric emissions. The analysis shows that limited financial resources, lack of effective systemic monitoring and control of air quality that meets modern international requirements and standards, leads to absence of tangible changes in practice yet. Over 30 years in CACs, the share of CO₂ emissions associated with fuel combustion has not decreased and amounts to 78%. The key mechanisms for reducing atmospheric emissions are significantly increase investments in the transformation of the economies in the context of regional development, interstate cooperation, the introduction of environmental norms, standards harmonized with world ones, green technologies based on alternative energy, sustainable transport and logistics infrastructure. Full article