Search Results (7,581)

The CdSe/CdZnS colloidal quantum wells, with their exceptionally high carrier mobility and ultrafast response characteristics, emerge as highly promising candidate material for high-performance active terahertz modulators—indispensable core components critical for next-generation communication technologies. A high-performance, cost-effective terahertz modulator was fabricated through spin-coating CdSe(4ML)/CdZnS nanosheets onto a silicon substrate. This all-optical device demonstrates broadband modulation capabilities (0.25–1.4 THz), achieving a remarkable modulation depth of 87.6% at a low power density of 2 W/cm^2. Demonstrating pump-power-efficient terahertz modulation characteristics, this core–shell composite shows immediate applicability in terahertz communication systems and non-destructive testing equipment. Full article

Nuclear power plant (NPP) shear walls are typically ultra-thick and heavily reinforced, posing significant challenges for conventional cast-in-place (CIP) construction. To overcome these issues, this study proposes a precast concrete shear wall (PCSW) system with bolted connections. Owing to orthogonal wall layouts dictated by functional requirements, these structures are subjected to significant out-of-plane seismic demands, making their performance under such loading a critical design concern. Therefore, this paper investigates the out-of-plane seismic performance of scaled (1:2) models of PCSWs (300 mm thick) under an axial pressure ratio of 0.2 and without axial pressure through low-cycle repeated load tests, and compares them with corresponding CIP shear walls. All specimens exhibited flexural failure, while damage in PCSWs was relatively minor and concentrated within the grouting layer. Compared with CIP specimens, the precast specimens showed more pinching and smaller residual deformation, with cumulative energy dissipation reaching 70–80% of CIP specimens. The flexural load-bearing capacity of the precast specimens was close to that of the CIP specimens, with differences within 5%. The ductility of the precast specimens under axial pressure ratios of 0 and 0.2 was 4.54 and 2.68, respectively, differing from the CIP specimens by 16% and −10%. The stiffness degradation trends of both systems were essentially consistent. Overall, the results demonstrate that the out-of-plane seismic performance of PCSWs with bolted connections is broadly equivalent to that of CIP counterparts, confirming their feasibility for application in NPPs. Full article

The peculiarity of the functioning of modern electric power systems, caused by the presence of renewable energy sources, flexible control devices based on power electronics, and the reduction of the reserve of the transmission capacity of the electric network, increases the relevance of identifying and damping low-frequency oscillations (LFOs) of the electrical mode. This paper presents a comparative analysis of methods for estimating the parameters of low-frequency oscillations. Their applicability limits are shown as well as their peculiarity associated with low adaptability, and time costs in assessing the parameters of the electrical mode with low-frequency oscillations are revealed. A method for the accelerated evaluation of low-frequency oscillation parameters is proposed, the delay of which is ¼ of the oscillation cycle. The method was tested on both synthetic and physical signals. In the first case, the source of data was a four-machine mathematical model of a power system. In the second case, signals of transient processes occurring in a real power system were used as physical data. The accuracy of the proposed method was obtained by calculating the difference between the original and reconstructed signals. As a result, calculated error values were obtained, describing the accuracy and efficiency of the proposed method. The proposed algorithm for estimating LFO parameters displayed an error value not exceeding 0.8% for both synthetic and physical data. Full article

6G low-power and lossy network (6G LLN) is a kind of distributed network designed for IoT and edge computing scenarios of the sixth-generation mobile communication technology. Its routing technologies should fully consider characteristics of green and low carbon, constrained nodes, lossy links, etc. This paper proposes an improved routing protocol for low-power and lossy networks (I-RPL) to better suit the characteristics of 6G LLN and meet its application requirements. I-RPL has designed new context-aware routing metrics, which include the residual energy indicator, buffer utilization ratio, ETX, delay, and hop count to meet multi-dimensional network QoS requirements. The candidate parent and its preferred parent’s residual energy indicator and buffer utilization ratio are calculated recursively to reduce the effect of upstream parents. ETX and delay calculating methods are improved to ensure a better performance. Moreover, I-RPL has optimized the network construction process to improve energy and protocol efficiency. I-RPL has designed scientific multiple routing metrics evaluation theories (Lagrangian multiplier theories), proposed new rank computing and optimal route selecting mechanisms to simplify protocol, and optimized broadcast suppression and network reliability. Finally, theoretical analysis and experiment results show that the average end-to-end delay of I-RPL is 13% lower than that of RPL; the average alive node number increased 11% and so on. So, I-RPL can be applied well to the 6G LLN and is superior to RPL and its improvements. Full article

Electroencephalography (EEG) electrodes require low impedance, high biocompatibility, and long-term performance. Conventional Ag/AgCl wet electrodes achieve low impedance but suffer from dehydration and skin irritation, whereas dry electrodes often induce discomfort or exhibit high impedance. To address these limitations, this study engineered a hydrogel-based electrode by incorporating PEDOT:PSS and the nonionic surfactant Triton X-100 into an acrylic acid hydrogel matrix. The flexible acrylic acid backbone, conductive PEDOT:PSS domains, and the nanofibrillar network promoted by Triton X-100 simultaneously enhanced mechanical compliance and electrical stability. In addition, the structural rearrangement of PEDOT:PSS was verified through morphological analyses. The fabricated electrode exhibited a modulus comparable to human soft tissue, demonstrated strong interfacial adhesion in shear tests, and significantly reduced skin–electrode contact impedance. Furthermore, EEG measurements showed that the hydrogel electrode achieved alpha- and beta-band signal power comparable to commercial Ag/AgCl electrodes. These findings establish the PEDOT:PSS–Triton X-100 hydrogel electrode as a promising candidate to replace conventional wet and dry electrodes for reliable EEG applications. Full article

Partial discharge (PD) source localization is an essential technology to identify the location of defects in power cables. This paper presents a complete cable PD localization system. To improve localization accuracy and reduce computational cost, the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise—Multiscale Permutation Entropy–Improved Wavelet Threshold (CEEMDAN-MPE-IWT) method is first employed to effectively suppress noise in PD signals. Subsequently, Cross-Correlation (CC) coefficients are calculated between the double-ended signals to eliminate low-quality signals with poor correlation. Furthermore, the retained signals are subjected to time-window cropping to minimize redundant data and enhance computational efficiency. Based on the processed signals, multiple time delay estimates are derived using the Generalized Cross-Correlation (GCC) algorithm, and the K-means clustering algorithm is subsequently applied to determine the final localization result. Finally, a cable PD experimental platform is established to validate the proposed method. Experimental results demonstrate that the proposed approach achieves a relative localization error of less than 3%, indicating high localization accuracy and strong potential for engineering applications. Full article

To address low energy utilization efficiency and severe exergy destruction from direct discharge of high-temperature turbine exhaust, this study proposes a supercritical CO₂ Brayton cogeneration system with a series-connected hot water heat exchanger for stepwise waste heat recovery. Based on finite-time thermodynamics, a physical model that provides a more realistic framework by incorporating finite temperature difference heat transfer, irreversible compression, and expansion losses is established. Aiming to maximize exergy output rate under the constraint of fixed total thermal conductance, the decision variables, including working fluid mass flow rate, pressure ratio, and thermal conductance distribution ratio, are optimized. Optimization yields a 16.06% increase in exergy output rate compared with the baseline design. The optimal parameter combination is a mass flow rate of 79 kg/s and a pressure ratio of 5.64, with thermal conductance allocation increased for the regenerator and cooler, while decreased for the heater. The obtained results could provide theoretical guidance for enhancing energy efficiency and sustainability in S-CO₂ cogeneration systems, with potential applications in industrial waste heat recovery and power generation. Full article

Energy security remains a central challenge in the context of global sustainability, as geopolitical dynamics, technological advancements, and environmental imperatives converge to reshape energy systems worldwide. This comprehensive review explores the intricate relationship between geopolitics and energy policy, with a particular focus on Türkiye’s evolving energy landscape. It examines how diversification of energy sources, investments in renewable technologies, resilient infrastructure development, and international collaborations collectively contribute to securing national and global energy futures. The study highlights the geopolitical significance of strategic energy corridors, resource competition, and the emergent role of renewable energy in redefining power structures. Drawing on comparative case studies, including Germany’s Energiewende, Norway’s resource management, Japan’s post-Fukushima challenges, and the United States’ shale revolution, the review distills lessons applicable to Türkiye and other emerging economies navigating energy transitions. Future trends discussed include the rising importance of energy storage, smart grids, digitalization, cybersecurity, and equitable energy access. Policy recommendations emphasize integrated approaches that balance economic growth, environmental stewardship, and national security, advocating for proactive diversification, innovation, and multilateral cooperation. The article concludes that achieving a resilient, low-carbon, and geopolitically stable energy system requires coordinated global efforts anchored in adaptive governance and inclusive stakeholder engagement. This work provides a valuable framework for policymakers, researchers, and practitioners committed to advancing sustainable and secure energy pathways in Türkiye and beyond. Full article

Children with intoeing gait are at increased risk of tripping and consequent injury, reduced mobility, and psychological issues. Quantification of tripping is needed outside the gait lab during daily life for improved clinical assessment and treatment evaluation and to enrich the database for artificial intelligence (AI) learning. This paper presents the development of a low-cost, wearable tripping monitor to log a child’s Tripping Hazard Events (THEs) and steps taken during two weeks of everyday activity. A combination of sensors results in a high probability of THE detection, even during rapid gait, while guarding against false positives and minimizing power and therefore monitor size. A THE is logged when the feet come closer than a predefined threshold during the intoeing foot swing phase. Foot proximity is determined by a Radio Frequency Identification (RFID) reader in “sniffer” mode on the intoeing foot and a target of passive Near-Field Communication (NFC) tags on the contralateral foot. A Force Sensitive Resistor (FSR) in the intoeing shoe sets a time window for sniffing during gait and enables step counting. Data are stored in 15 min epochs. Laboratory testing and an IRB-approved human participant study validated system performance and identified the need for improved mechanical robustness, prompting a redesign of the monitor. A custom Python (version 3.10.13)-based Graphical User Interface (GUI) lets clinicians initiate recording sessions and view time records of THEs and steps. The monitor’s flexible design supports broader applications to real-world activity detection. Full article

Adaptive Equivalent Consumption Minimization Strategies (A-ECMSs) are one of the best methodologies to optimize fuel consumption of plug-in hybrid vehicles (PHEVs) coupled with low computational requirements. In this paper, a review of A-ECMSs is proposed. Starting from an economic-environmental contextualization, hybrid vehicles are presented and classified, together with their modeling methodologies and the physical-mathematical representation of their components. Next, the control theory for hybrid vehicles is introduced and classified, deriving the A-ECMS approach. Several works accounting for different A-ECMS implementations, based on technology integration, time horizon, adaptivity mechanism, and technique, are addressed. The literature analysis shows a broad coverage of possibilities: the simple proportional-integral (PI) rule for equivalence factor adaptivity is often used, imposing a given battery state-of-charge (SoC); it is possible to optimally plan the battery SoC trajectory through offline optimization with optimal algorithms or by predicting ahead conditions with model predictive control (MPC) or neural networks (NNs); the integration with emerging technologies such as Vehicle-To-Everything (V2X) can be helpful, accounting also for car-following data and GPS information. Moreover, speed prediction is another common technique to optimally plan the battery SoC trajectory. Depending on available on-board computational power and data, it is possible to choose the best A-ECMS according to its application. Full article

Second-life electric vehicle batteries (SLBs) represent a promising asset for enhancing grid flexibility and advancing circular economy objectives in the power sector. This paper proposes a conceptual trigger-based PDCA (Plan–Do–Check–Act) framework for the sustainable grid integration of SLBs, enabling adaptive operational control across diverse application scenarios. The framework combines lifecycle KPI monitoring, degradation and performance tracking, and economic feasibility assessment with trigger-driven dispatch logic. Technical, financial, and environmental indicators are systematically integrated into the four PDCA phases, providing a structured basis for adaptive management. To illustrate applicability, indicative KPI calculations are presented for three representative scenarios (HV Backup, RES Smoothing, and Frequency Regulation). These examples demonstrate how the framework supports scenario-based planning, performance evaluation, and decision-making under uncertainty. Compared with existing state-of-the-art approaches, which typically analyse technical or economic aspects in isolation, the proposed framework introduces a modular, multi-model architecture that aligns operational triggers with long-term sustainability goals. By embedding reuse-oriented strategies into an adaptive PDCA cycle, the study offers a clear and practical methodology for maximising SLB value while minimising degradation and environmental impacts. The framework provides a valuable reference framework for structured SLB deployment, supporting more resilient, cost-effective, and low-carbon energy systems. Full article

The precise analysis of protein interactions in their native cellular context and the sensitive quantification of protein abundance in biological fluids are both fundamental to understanding health and disease. Traditional methods for cellular imaging and biochemical quantification often face limitations in specificity, sensitivity, or the preservation of spatial information. The proximity ligation assay (PLA) is a versatile technological platform developed to overcome these challenges by converting protein recognition events into amplifiable DNA signals, thereby achieving exceptional sensitivity. This foundational principle has given rise to two major formats: in situ PLA (isPLA) and solution-phase PLA. In basic research, isPLA provides high-resolution visualization of protein–protein interactions (PPIs), post-translational modifications (PTMs), and subcellular architecture directly within fixed cells and tissues. In translational and clinical applications, solution-phase PLA enables the highly sensitive quantification of low-abundance biomarkers in liquid samples, which is critical for diagnostics and prognostics in fields such as oncology, neuroscience, and infectious diseases. This review discusses the foundational principles, development, and diverse applications of PLA platforms. We also highlight significant technological advancements, including the development of high-throughput formats, integration with advanced readouts, and the use of alternative affinity reagents. These innovations continue to transform PLA from a targeted validation method into a powerful and multifaceted platform for both fundamental systems biology and clinical diagnostics. Full article

The global economy frequently experiences cycles of rapid growth followed by abrupt crashes, challenging economists and analysts in forecasting and risk management. Crashes like the dot-com bubble crash and the 2008 global financial crisis caused huge disruptions to the world economy. These crashes have been found to display somewhat similar characteristics, like rapid price inflation and speculation, followed by collapse. In search of these underlying patterns, the Log-Periodic Power-Law (LPPL) model has emerged as a promising framework, capable of capturing self-reinforcing dynamics and log-periodic oscillations. However, while log-periodic structures have been tested in developed and stable markets, they lack validation in volatile and developing markets. This study investigates the applicability of the LPPL framework for modeling financial crashes in the Brazilian stock market, which serves as a representative case of a volatile market, particularly through the Bovespa Index (IBOVESPA). In this study, daily data spanning 1993 to 2025 is analyzed to model pre-crash oscillations and speculative bubbles for five major market crashes. In addition to the traditional LPPL model, autoregressive residual analysis is incorporated to account for market noise and improve predictive accuracy. The results demonstrate that the enhanced LPPL model effectively captures pre-crash oscillations and critical transitions, with low error metrics. Eigenstructure analysis of the Hessian matrices highlights stiff and sloppy parameters, emphasizing the pivotal role of critical time and frequency parameters. Overall, these findings validate LPPL-based nonlinear modeling as an effective approach for anticipating speculative bubbles and crash dynamics in complex financial systems. Full article

Background/Objectives: Liquid biopsy using cfDNA has emerged as a promising, minimally invasive alternative to traditional tissue biopsy for detecting cancer-associated mutations. However, the extremely low proportion of mutant DNA in cfDNA poses a major challenge for accurate detection, especially when using conventional sequencing methods. To address this limitation, we sought to develop a highly sensitive diagnostic strategy to selectively enrich rare mutant sequences and improve the detection of clinically important mutations in patients with NSCLC. Methods: We established a CRISPR/Cas12a-based diagnostic system designed to selectively cleave WT DNA, thereby increasing the relative abundance of mutant DNA in cfDNA samples. Following Cas12a-mediated WT cleavage, the remaining DNA was subjected to PCR amplification for mutation identification. The system was applied to plasma cfDNA from blood samples of 48 NSCLC patients to evaluate its ability to detect two major EGFR mutations: L858R and exon 19 deletion. Results: The CRISPR/Cas12a-based diagnostic system effectively identified low-frequency EGFR mutations in cfDNA. Specifically, all 7 L858R-positive samples and 6 out of 11 samples harboring exon 19 deletions—previously validated through tissue biopsy—were successfully detected. This demonstrated a high degree of concordance between our liquid biopsy approach and conventional diagnostic methods. Conclusions: Our findings highlight the potential of the CRISPR/Cas12a-based mutation enrichment system as a powerful tool for detecting rare oncogenic mutations in liquid biopsy samples. This technique enhances diagnostic sensitivity and could be broadly applicable for the non-invasive detection of various genetic alterations in cancer and other diseases. Full article

Virtual Machine Introspection (VMI) is a powerful technology used to detect and analyze malicious software inside Virtual Machines (VMs) from the outside. Asynchronous access to the VM’s memory can be insufficient for efficient monitoring of what is happening inside of a VM. Active VMI introduces breakpoints to intercept VM execution at relevant points. Especially for frequently visited breakpoints, and even more so for production systems, it is crucial to keep performance overhead as low as possible. In this paper, we present an empirical study that compares the performance of four VMI breakpoint-implementation variants—EPT switching (SLAT view switching) with and without fast single-stepping acceleration, instruction repair, and instruction emulation—from two VMI applications (DRAKVUF, SmartVMI) with the XEN hypervisor on 20 Intel Core i processors ranging from the fourth to the thirteenth generation. Instruction emulation was the fastest method across all 20 tested platforms. Modern processors such as the Intel Core i7 12700H and Intel Core i9 13900HX achieved median breakpoint-processing times as low as 15 µs for the emulation mechanism. The slowest method was instruction repair, followed by EPT switching and EPT switching with FSS. The order was the same for all measurements, indicating that this is a strong and generalizable result. Full article