Search Results (615)

The dynamic phosphorylation of the human RNA Pol II CTD establishes a code applicable to all eukaryotic transcription processes. However, the ability of these specific post-translational modifications to convey molecular signals through structural changes remains unclear. We previously explained that each gene can be modeled as a combination of n circuits connected in parallel. RNA Pol II accesses these circuits and, through a series of pulses, matches the resonance frequency of the DNA qubits, enabling it to extract genetic information and quantum teleport it. Negatively charged phosphates react under RNA Pol II catalysis, which increases the electron density on the deoxyribose acceptor carbon (2’C in the DNA sugar backbone). The phosphorylation effect on the stability of a carbon radical connects tyrosine to the nitrogenous base, while the subsequent pulses link the protein to molecular water through hydrogen bonds. The selective activation of inert C(sp³)–H bonds begins by reading the quantum information stored in the nitrogenous bases. The coupling of hydrogen proton transfer with electron transfer in water generates a supercurrent, which is explained by the correlation of pairs of the same type of fermions exchanging a boson. All these changes lead to the formation of a molecular protein–DNA–water transcriptional condensate. Full article

Enhancing the resilience of renewable energy systems in ultra-weak grids is crucial for promoting sustainable energy adoption and ensuring a reliable power supply during disturbances. Ultra-weak grids characterized by a very low Short-Circuit Ratio, less than 2, and high grid impedance significantly impair voltage and frequency stability, imposing challenging conditions for Inverter-Based Resources. To address these challenges, this paper considers a 110 KVA, three-phase, two-level Voltage Source Converter, interfacing a 700 V DC link to a 415 V AC ultra-weak grid. X/R = 1 is controlled using Sinusoidal Pulse Width Modulation, where the Grid-Connected Converter operates in Grid-Forming Mode to maintain voltage and frequency stability under a steady state. During symmetrical and asymmetrical faults, the converter transitions to Grid-Following mode with current control to safely limit fault currents and protect the system integrity. After fault clearance, the system seamlessly reverts to Grid-Forming Mode to resume voltage regulation. This paper proposes an improved control strategy that integrates voltage feedforward reactive power support and virtual capacitor-based virtual inertia using Active Disturbance Rejection Control, a robust, model-independent controller, which rapidly rejects disturbances by regulating d and q-axes currents. To test the practicality of the proposed system, real-time implementation is carried out using the OPAL-RT OP4610 platform, and the results are experimentally validated. The results demonstrate improved fault current limitation and enhanced DC link voltage stability compared to a conventional PI controller, validating the system’s robust Fault Ride-Through performance under ultra-weak grid conditions. Full article

Quantum memory is essential for the prolonged storage and retrieval of quantum information. Nevertheless, no current studies have focused on the creation of effective quantum memory for continuous variables while accounting for the decoherence rate. This work presents an effective continuous-variable quantum key distribution method with parameter optimization utilizing the Elitist Elk Herd Random Immigrants Optimizer (2E-HRIO) technique. At the outset of transmission, the quantum device undergoes initialization and authentication via Compressed Hash-based Message Authentication Code with Encoded Post-Quantum Hash (CHMAC-EPQH). The settings are subsequently optimized from the authenticated device via 2E-HRIO, which mitigates the effects of decoherence by adaptively tuning system parameters. Subsequently, quantum bits are produced from the verified device, and pilot insertion is executed within the quantum bits. The pilot-inserted signal is thereafter subjected to pulse shaping using a Gaussian filter. The pulse-shaped signal undergoes modulation. Authenticated post-modulation, the prediction of link failure is conducted through an authenticated channel using Radial Density-Based Spatial Clustering of Applications with Noise. Subsequently, transmission occurs via a non-failure connection. The receiver performs channel equalization on the received signal with Recursive Regularized Least Mean Squares. Subsequently, a dataset for side-channel attack authentication is gathered and preprocessed, followed by feature extraction and classification using Adaptive Depthwise Separable Convolutional Neural Networks (ADS-CNNs), which enhances security against side-channel attacks. The quantum state is evaluated based on the signal received, and raw data are collected. Thereafter, a connection is established between the transmitter and receiver. Both the transmitter and receiver perform the scanning process. Thereafter, the calculation and correction of the error rate are performed based on the sifting results. Ultimately, privacy amplification and key authentication are performed using the repaired key via B-CHMAC-EPQH. The proposed system demonstrated improved resistance to decoherence and side-channel attacks, while achieving a reconciliation efficiency above 90% and increased key generation rate. Full article

In recent years, passive acoustic monitoring (PAM) technology has significantly contributed to advancements in aquaculture techniques, system iterations, and increased production yields within intelligent feeding systems for Penaeus vannamei. However, current PAM-based intelligent feeding systems do not incorporate environmental factors into the decision process, limiting the improvement of monitoring accuracy in complex environments such as ponds. To establish a connection between environmental factors and the feeding acoustics of P. vannamei, this study utilized PAM technology combined with video analysis to investigate the effects of three key environmental factors—temperature, ammonia nitrogen, and nitrite nitrogen—on the feeding behavioral characteristics of shrimp, with a specific focus on acoustic signals “clicks”. The results demonstrated a significant correlation between the number of clicks and feed consumption in shrimp across different treatments, establishing this stable relationship as a reliable indicator for assessing shrimp feeding status. When water temperature increased from 20 °C to 32 °C, shrimp feed consumption showed an elevation from 0.46 g to 0.95 g per 30 min, with the average number of clicks increasing from 388 to 2947.58 and sound pressure levels rising accordingly. Conversely, ammonia nitrogen at 12 mg/L reduced feed consumption by 0.15 g and decreased click counts by 911.75 pulses compared to controls, while nitrite nitrogen at 40 mg/L similarly suppressed feed consumption by 0.15 g and the average number of clicks by 304.75. A rise in water temperature stimulated shrimp behaviors such as feeding, swimming, and foraging, while elevated concentrations of ammonia nitrogen and nitrite nitrogen significantly inhibited shrimp activity. Redundancy analysis revealed that temperature was the most prominent factor among the three environmental factors influencing shrimp feeding. This study is the first to quantify the specific effects of common environmental factors on the acoustic feeding signals and feeding behavior of P. vannamei using PAM technology. It confirms the feasibility of using PAM technology to assess shrimp feeding conditions under diverse environmental conditions and the necessity of integrating environmental monitoring modules into future feeding systems. This study provides behavioral evidence for the development of precise feeding technologies and the upgrade of intelligent feeding systems for P. vannamei. Full article

To address the challenges of extracting rolling bearing degradation information and the insufficient performance of conventional convolutional networks, this paper proposes a rolling bearing degradation state identification method based on the improved monopulse feature extraction and a one-dimensional dilated residual convolutional neural network (1D-DRCNN). First, the fault pulse envelope waveform features are extracted through phase scanning and synchronous averaging, and a two-stage grid search strategy is employed to achieve FCC calibration. Subsequently, a 1D-DRCNN model is constructed to identify rolling bearing degradation states under different working conditions. The experimental study collects the vibration signals of nine degradation states, including the different sizes of inner and outer ring local faults as well as normal conditions, to comparatively analyze the proposed method’s rapid calibration capability and feature extraction quality. Furthermore, t-SNE visualization is utilized to analyze the network response to bearing degradation features. Finally, the degradation state identification performance across different network architectures is compared in pattern recognition experiments. The results show that the proposed improved feature extraction method significantly reduces the iterative calibration computational burden while effectively extracting local fault degradation information and overcoming complex working condition influence. The established 1D-DRCNN model integrates the advantages of dilated convolution and residual connections and can deeply mine sensitive features and accurately identify different bearing degradation states. The overall recognition accuracy can reach 97.33%. Full article

For power electronic interfaces, Direct Power Control (DPC) has emerged as a leading control technique, especially in applications such as synchronous motors, induction motors, and other electric drives; renewable energy sources (such as photovoltaic inverters and wind turbines); and converters that are grid-connected, such as Virtual Synchronous Generator (VSG) and Static Compensator (STATCOM) configurations. DPC accomplishes several significant goals by avoiding the inner current control loops and doing away with coordinating transformations. The application of STATCOM based on three- and five-level diode-clamped inverters is covered in this work. The study checks the abilities of DPC during power control adjustments during diverse grid operation scenarios while detailing how multilevel inverters affect system stability and power reliability. Proportional Integral (PI) controllers are used to control active and reactive power levels as part of the control approach. This study shows that combining DPC with Sinusoidal Pulse Width Modulation (SPWM) increases the system’s overall electromagnetic performance and control accuracy. The performance of STATCOM systems in power distribution and transient response under realistic operating conditions is assessed using simulation tools applied to three-level and five-level inverter topologies. In addition to providing improved voltage quality and accurate reactive power control, the five-level inverter structure surpasses other topologies by maintaining a total harmonic distortion (THD) below 5%, according to the main findings. The three-level inverter operates efficiently under typical grid conditions because of its straightforward design, which uses less processing power and computational complexity. Full article

Pulse and Glide (PnG), as a fuel-saving technique, has primarily been applied to manual transmission vehicles. So, its effectiveness when integrated with a novel vehicle type like connected and automated vehicles (CAVs) remains largely unexplored. On the other hand, CAVs have evidently received less attention regarding energy conservation, and their prominent perception capabilities clearly exhibit individual variations. In light of this, this study investigates the impacts of PnG combined with CAVs on energy conservation and safety within the emerging mixed traffic flow composed of CAVs with varying sensing accuracies. The results indicate the following: (i) compared to the traditional driving modes, the PnG can achieve a maximum fuel-saving rate of 39.53% at Fuel Consumption with Idle (FCI), reducing conflicts by approximately 30% on average; (ii) CAVs, equipped with sensors boasting a greater detection range, markedly enhance safety during vehicle operation and contribute to a more uniform distribution of individual fuel consumption; (iii) PnG modes with moderate acceleration, such as 1–2 m/s², can achieve excellent fuel consumption while ensuring safety and may even slightly enhance the operational efficiency of the intersection. The findings could provide a theoretical reference for the transition of transportation systems toward sustainability. Full article

This paper presents an adaptive Maximum Power Point Tracking (MPPT) strategy for grid-connected photovoltaic (PV) systems that uses an Adaptive Neuro-Fuzzy Inference System (ANFIS) optimized by Particle Swarm Optimization (PSO) to enhance energy extraction efficiency under diverse environmental conditions. The proposed ANFIS-PSO-based MPPT controller performs dynamic adjustment Pulse Width Modulation (PWM) switching to minimize Total Harmonic Distortion (THD); this will ensure rapid convergence to the maximum power point (MPP). Unlike conventional Perturb and Observe (P&O) and Incremental Conductance (INC) methods, which struggle with tracking delays and local maxima in partial shading scenarios, the proposed approach efficiently identifies the Global Maximum Power Point (GMPP), improving energy harvesting capabilities. Simulation results in MATLAB/Simulink R2023a demonstrate that under stable irradiance conditions (1000 W/m², 25 °C), the controller was able to achieve an MPPT efficiency of 99.2%, with THD reduced to 2.1%, ensuring grid compliance with IEEE 519 standards. In dynamic irradiance conditions, where sunlight varies linearly between 200 W/m² and 1000 W/m², the controller maintains an MPPT efficiency of 98.7%, with a response time of less than 200 ms, outperforming traditional MPPT algorithms. In the partial shading case, the proposed method effectively avoids local power maxima and successfully tracks the Global Maximum Power Point (GMPP), resulting in a power output of 138 W. In contrast, conventional techniques such as P&O and INC typically fail to escape local maxima under similar conditions, leading to significantly lower power output, often falling well below the true GMPP. This performance disparity underscores the superior tracking capability of the proposed ANFIS-PSO approach in complex irradiance scenarios, where traditional algorithms exhibit substantial energy loss due to their limited global search behavior. The novelty of this work lies in the integration of ANFIS with PSO optimization, enabling an intelligent self-adaptive MPPT strategy that enhances both tracking speed and accuracy while maintaining low computational complexity. This hybrid approach ensures real-time adaptation to environmental fluctuations, making it an optimal solution for grid-connected PV systems requiring high power quality and stability. The proposed controller significantly improves energy harvesting efficiency, minimizes grid disturbances, and enhances overall system robustness, demonstrating its potential for next-generation smart PV systems. Full article

This paper presents the possibilities of using the reaction sintering method for the production of tool steel used in medicine. The applied method enables the sintering of powders in one technological process. The SPS (spark plasma sintering) process is a technology in which electric pulses generate heat and pressure, which allows for the quick and effective connection of powder particles into a homogeneous material with high density and good mechanical properties. As a result, a product of small dimensions and a precisely defined chemical composition, established at the stage of preparing the powder mixture, is obtained. The advantages of the applied production process are the sintering time and small amounts of post-production waste compared to conventional methods of producing a finished product from steel. The method of producing a semi-finished product is particularly useful in the case of small-scale and small-sized production. The subject of the research was the analysis of the conditions for obtaining X30Cr13 martensitic steel used for the production of surgical instruments. This paper analyzes the effect of sintering temperature and time on sinterability and on selected physical and mechanical properties of the obtained materials. The sintering parameters of the starting mixture have been optimized to obtain the highest possible sinter properties, such as density and hardness. Based on the analysis of the results, it was found that the powder preparation method for the SPS process and the grain size significantly affect the microstructure and mechanical properties of the final product. The optimal sintering parameters for X30Cr13 steel are a temperature of 950 °C and a sintering time of 12 min. Furthermore, the use of the SPS method allows for a reduction in the manufacturing costs of martensitic steel semi-finished products. Full article

Onboard Vehicle-to-Everything (V2X) communication technology is being widely implemented in domains such as intelligent driving, vehicle–road cooperation, and smart transportation. Nevertheless, time synchronization in V2X systems suffers from instability due to the random loss of Global Navigation Satellite System (GNSS) Pulse-Per-Second (PPS) signals. To address this challenge, a model-driven local clock correction approach is proposed. Leveraging probability theory and mathematical statistics, models for the randomly lost GNSS PPS signals are developed. High-order polynomials are used to model local clocks. An optimized Kalman-filter-based time compensation algorithm is then devised to compensate for time errors during PPS signal loss. A software-based task-scheduling solution for precision-time synchronization is developed. An experimental testbed was then built to measure both terminal clocks and PPS signals. The proposed algorithm was integrated into the V2X terminals. Results show that the full-value PPS signals follow an exponential distribution. The onboard clock correction algorithm operates stably across three V2X terminals and accurately predicts clock variations. Furthermore, the virtual clocks achieve an average absolute error of 1.1 μs and a standard deviation of 16 μs, meeting the time synchronization requirements for V2X communication in intelligent connected vehicles. Full article

The rapid growth of inverter-based resources (IBRs) has created a need for new islanding detection methodologies to determine whether an IBR has been disconnected from the transmission grid in some manner (islanded) or remains connected to the transmission grid (grid-connected). Active islanding detection methods inject a signal into the power system to achieve detection. Existing schemes frequently limit consideration to a single node system with one IBR. Schemes tested on multiple IBRs often see interference, with the signals from one IBR disturbing the others, or require intricate communication. Further, several methods destabilize an islanded grid to detect it, preventing a prospective microgrid from remaining in operation while islanded. This work develops an active islanding detection scheme using Pulse Compression Probing (PCP) that is microgrid-compatible and can be used with multiple IBRs without requirement for communication. This active islanding detection scheme can be implemented on existing inverter switching sequences and has a detection time of 167–223 ms, well within the detection time specified by existing standards. The method is verified via electromagnetic transient (EMT) simulation on a modified version of a 34-bus test system. Full article

Background/Objectives: Hypertension is strongly linked to changes in vascular function and lipid metabolism. This study aimed to examine the relationship between lipid profiles, various metabolic biomarkers, and pulse wave analysis in patients with hypertension. Methods: A group of 66 hypertensive patients, aged 64 ± 10 years, participated in pulse wave analysis utilizing an oscillometric device. Multiple lipid serum biomarkers were assessed, such as total cholesterol (TC), triglycerides (TG), and non-HDL cholesterol (non-HDL). Lipid balance index (LBI) was determined by considering TG, LDL, HDL levels, and lipid-lowering medications. Results: Notable correlations were observed for SBP, DBP, and early vascular aging (EVA) with lipid biomarkers. In addition to serum lipids, metabolic syndrome, insulin resistance, and non-alcoholic fatty liver disease (NAFLD) were significantly linked to pulse wave analysis variables. Multiple regression analysis showed that only TC continued to have a significant association with DBP. Conclusions: Total cholesterol, triglycerides, non-HDL cholesterol, and lipid balance index provide information about systolic and diastolic blood pressure, as well as early vascular aging in hypertensive patients. LBI offers valuable vascular insights in hypertensive individuals with cardiovascular risk factors, early vascular aging, insulin resistance, and NAFLD. The connection between metabolic biomarkers and pulse wave measurements in individuals with hypertension offers a comprehensive method for the early identification of vascular injury and could enhance the prediction of major cardiovascular events. Full article

Transcranial pulse stimulation (TPS) is a non-invasive neuromodulation method that uses, high-intensity acoustic shockwaves to deliver focused mechanical stimulation to neural tissue with minimal thermal effects. The mechanism of action includes but is not limited to promotion of blood flow and angiogenesis through mechanotransduction. Clinical data to date are limited and preliminary. In Alzheimer’s disease (AD), TPS has demonstrated cognitive and mood improvements in pilot studies and secondary endpoint analysis in first randomized trials. The enhancement of gamma-band oscillations and network connectivity has been reported. Clinical observations in Parkinson’s disease (PD) suggest TPS as a hypothesis-generating approach to address non-motor symptoms—such as depression, cognitive decline, and the freezing of gait—through theoretical modulation of basal ganglia–cortical circuits. TPS is CE-marked in Europe for AD and shows a favorable safety profile; however, ethical considerations arise from the limited evidence base, potential impairment of patient autonomy and judgment in dementia, and the risk of withholding established treatments. TPS should only be offered under structured scientific protocols or within patient registries to ensure rigorous oversight. Ensuring that consent processes account for cognitive capacity, and that TPS is applied as adjunct rather than replacement therapy, is paramount. Future research must include large-scale randomized controlled trials (RCTs), standardize stimulation protocols, deepen mechanistic insight, and embed robust ethical frameworks. Full article

Background: The impact of exogenous explicit knowledge on early motor learning is highly variable and may be influenced by excitability within the procedural sensorimotor network. Recent transcranial magnetic stimulation (TMS) studies suggest that variability in interneuron recruitment by anterior–posterior (AP) currents is linked to differences in functional connectivity between premotor and motor regions. Objectives: This study used controllable pulse parameter TMS (cTMS) to assess how AP-sensitive interneuron excitability interacts with explicit knowledge to influence motor learning. Methods: Seventy-two participants were grouped as AP-positive (n = 36) and AP-negative groups (n = 36) based on whether an AP threshold could be obtained before reaching maximal stimulator output. A narrow (30 µs) stimulus was employed to target the longest latency corticospinal inputs selectively. Participants then practiced a continuous visuomotor tracking task and completed a delayed retention test. Half of each group received explicit knowledge of a repeated sequence embedded between random sequences. Random sequence tracking performance assessed general sensorimotor efficiency; repeated sequence performance assessed sequence-specific learning. Results: Both AP₃₀-positive participants, with and without explicit knowledge, and the AP₃₀-negative without explicit knowledge demonstrated similar improvements in sensorimotor efficiency driven by offline consolidation. However, AP₃₀-negative participants given explicit instruction exhibited significantly reduced improvement in sensorimotor efficiency, primarily due to impaired offline consolidation. Conclusions: These findings suggest that individuals with low excitability in long-latency AP-sensitive inputs may be more vulnerable to interference from explicit instruction. The current results highlight the importance of accounting for individual differences in interneuron excitability when developing instructional strategies for motor learning. Full article

Background: Diode lasers are valuable in oral surgery due to their excellent hemostasis, minimum post-operative pain, and minimally invasive procedures. A dual-wavelength diode laser in dentistry combines two distinct wavelengths, typically 450 nm and 808 nm, to provide a versatile approach to soft tissue procedures. This ex vivo study investigated the quantity of thermal effects of a dual-wavelength diode laser on porcine lingual mucosa to determine the optimal laser parameters for oral soft tissue biopsies and to improve the reliability of histological evaluation. The presence of thermal damage in the prelesional margins may compromise the diagnostic accuracy, particularly in cases of suspected malignancy. Methods: Thirty-six porcine lingual mucosa samples were excised using a diode laser (Wiser 3, Doctor Smile) in continuous wave (CW) and pulsed wave (PW) modes at average powers of 2, 3, and 4 W. The samples, preserved in 5% buffered formalin, underwent histological evaluation to measure epithelial and connective tissue damage. Results: The study demonstrated variable thermal effects depending on the laser mode and power settings. Minimal epithelial damage (0.62 mm) was observed at 2 W CW, while maximum damage (3.12 mm) occurred at 4 W pulsed wave (PW). Connective tissue exhibited slightly greater damage than epithelial tissue, with minimal damage (0.53 mm) at 4 W CW and maximum damage (3.19 mm) at 4 W pulsed wave (PW). Statistical analyses were performed using t-tests and ANOVA and revealed significant differences in tissue damage between certain groups, highlighting the impact of laser parameters on thermal effects. Conclusions: The dual-wavelength diode laser seems to have good surgical properties and is suitable for managing complex clinical cases. Although the low power average showed minimal thermal damage, for the importance of the diagnosis of suspected lesions of malignancy, a 2 mm prelesional margin should be maintained. Full article