Search Results (632)

While Western theology typically locates omniscience in a personal Creator-God, Indian philosophy presents a notable spectrum. This article traces the dialectical arc of omniscience (sarvajñāna) across major Indian philosophical traditions, arguing that what appears as an epistemological question—“who knows everything?”—is ultimately an ontological puzzle about the nature of consciousness itself. Moving from the Vedic oscillation between cosmic personhood (Puruṣa Sūkta) and primordial uncertainty (Nāsadīya Sūkta), through the Upaniṣadic internalization of omniscience as Self-knowledge (ātmajñatā), the article examines how Nyāya-Yoga affirms divine omniscience as a logical and soteriological necessity, how Mīmāṃsā displaces it onto an impersonal authorless text, and how Jainism and Buddhism reappropriate it as a perfected human achievement. The final section demonstrates that both Sāṃkhya’s isolation (kaivalya) and Advaita Vedānta’s non-dual realization ultimately transcend encyclopedic omniscience, revealing that authentic liberation requires not the possession of maximal information but a transformation from representational object-knowledge to non-objectifying awareness. Together, these trajectories constitute Indian philosophy’s most enduring contribution to the global philosophy of religion: the recognition that the “All” cannot be an object of knowledge, because it is the very condition for any knowledge whatever. Full article

Ambient backscatter systems enable passive sensing and information transfer by utilizing the reflection and modulation of incident radio-frequency (RF) signals. However, in real-world scenarios involving non-cooperative targets such as off-the-shelf printed circuit boards (PCBs), the backscattered signal is extremely weak and often obscured by strong direct-path self-interference (SI) at the receiver. This issue becomes even more severe when unintentional PCB structures act as radiating elements. In this work, we explore ambient backscatter leakage from a compromised PCB using a realistic measurement setup that includes separated transmit and receive antennas and a direct-conversion Universal Software Radio Peripheral (USRP)-based receiver. We demonstrate that residual carrier frequency offset (CFO), caused by oscillator mismatch and hardware imperfections, can spread the dominant SI in the baseband and completely mask the weak backscattered signal. To solve this problem, a software-based post-processing framework is applied. This method leverages the complex baseband representation enabled by the homodyne receiver to jointly manage the carrier and SI components without relying on intermediate-frequency processing or prior knowledge of the target signal parameters. Experimental results show that this approach significantly improves the detectability of weak backscattered baseband information that would otherwise be concealed within the raw I/Q data. This study emphasizes the importance of CFO-aware digital processing in ambient backscatter systems and offers new insights into unintended electromagnetic leakage mechanisms from commercial PCB platforms. Full article

Efficient energy harvesting from open-channel flows offers a sustainable solution for powering distributed sensing systems in water infrastructure. This study investigates a piezoelectric wake-excited membrane vortex-induced vibration (VIV) energy harvester through a combined numerical and mechanical approach. The device features an upstream cylindrical bluff body that generates a periodic vortex street, exciting a downstream flexible membrane equipped with surface-mounted piezoelectric patches. A one-way coupled CFD–FEM framework implemented in ANSYS was employed to assess the effects of membrane length, material stiffness, and flow conditions on hydrodynamic loading, structural deformation, and deformation power. Results show that membrane length mainly affects oscillation amplitude and force levels, whereas material stiffness has a stronger influence on membrane deformation and RMS mechanical power. Among the investigated materials, low-stiffness polyethylene yields the highest deformation power, while none of the analysed configurations reaches a full lock-in condition within the explored parameter range. Complementary mechanical analysis revealed that the stiffness of commercial piezoelectric patches significantly reduces local strain, thereby constraining the practically harvestable energy in the present baseline configuration. Spectral power density analysis identified the dominant shedding frequency and its harmonics, confirming that the flow response is governed by a coherent periodic excitation. These findings highlight key design trade-offs in wake-excited membrane harvesters and provide useful guidance for the future optimisation of self-powered hydraulic monitoring systems. Full article

Beyond supporting ultra-high-capacity data transmission, metropolitan and access networks are expected to enable real-time infrastructure monitoring, driving the emergence of integrated sensing and communication (ISAC). Distributed acoustic sensing (DAS) has proven to be well-suited to urban sensing application requirements, yet its seamless integration into ISAC remains challenging—conventional high-peak-power sensing pulses in DAS induce nonlinear crosstalk in communication channels. DAS inherently suffers from interference fading due to single-frequency laser sources, which limits sensitivity. Here, we propose an ISAC architecture based on an electro-optic (EO) comb and a 7-core fiber, achieving nonlinearity-suppressed self-homodyne transmission and fading-suppressed DAS. Unmodulated comb lines and sensing pulses are polarization-multiplexed into orthogonal polarization states within the central core to minimize nonlinear crosstalk while delivering local oscillators (LOs) for wavelength division multiplexing (WDM) coherent transmission within six outer cores—achieving 10.56 Tbit/s capacity. In addition to supporting WDM transmission, the EO comb’s wavelength diversity is also exploited to enhance DAS performance. Specifically, a dual-pulse probe loaded onto four comb lines yields a 6 dB signal-to-noise ratio gain and a 64% reduction in fading occurrences, achieving a sensitivity of 1.72 $p\epsilon /\sqrt{\mathrm{Hz}}$ with 8 m spatial resolution. Moreover, our system supports simultaneous multi-wavelength backscatter detection in sensing and simplified digital signal processing in self-homodyne communication, reducing receiver complexity and cost. Our work presents a scalable, energy-efficient ISAC framework that unifies high-capacity communication with high-sensitivity sensing, providing a blueprint for future intelligent optical networks. Full article

This paper introduces a reinforced learning-based supervisory control architecture that oversees multiple Recursive Least Squares (RLS) based self-tuning pump controllers and determines when each loop is permitted to adapt its gains. The supervisor learns adaptation policies that minimize interaction between loops while preserving responsiveness to changing hydraulic conditions. A two-loop pump station simulation is used to evaluate performance under product changes and transient flow disturbances. The results show that the supervisory layer reduces the number of simultaneous adaptation events by over 70%, leading to a 32% lower pressure-tracking error and 45% fewer gain-induced oscillations compared to conventional independent adaptive control. The reinforcement learning policy converges within 15 training episodes, resulting in stable adaptation scheduling and seamless transitions. The key novelty of this work lies in introducing decentralized reinforcement-learning-based coordination for adaptive pump control, enabling supervisory decision-making that actively prevents interference between controllers during transients. This approach provides a scalable and lightweight solution for coordinating multi-loop pump stations, enhancing robustness and operational performance in real-world pipeline systems. Full article

The challenges of ensuring the security of electricity supply (SoES) in large aluminium smelters—particularly those that are self-supplied—provide a compelling rationale for further investigation, as research on this class of industrial systems is limited. Firstly, this paper presents an expert technical perspective on the distinct characteristics and operational challenges associated with aluminium potline loads and their supply systems in self-supplied aluminium smelters. This study then examines the supply infrastructure at Emirates Global Aluminium’s plant in Dubai, which has an installed power generation capacity of 3000 MW, supplying a 2000 MW load on a continuous basis through a network of three 132 kV substations. This high-voltage network is modelled and simulated using the CYME network analysis software module. We consider the following key approaches to ensure stable system voltage for desirable SoES: steady-state voltage control, outage planning and reactive power reserve management, active power flow management and load participation. We then study the influence each of these has on the system voltage and, hence, on the overall SoES of the smelter, using time-domain voltage and frequency curves at key network nodes and active power flow through important network interconnectors. The simulation results clearly demonstrate a significant improvement in the base case event by positively damping the oscillations in these responses, highlighting the significance of maintaining a healthy system voltage within a limit of ±2% of the nominal voltage to ensure SoES of the smelter. Full article

Inertial methods are widely used to accelerate the convergence of iterative algorithms for solving fixed-point problems. However, standard inertial terms often introduce undesirable oscillations, particularly in high-dimensional settings. In this paper, we propose a novel parallel double inertial algorithm with adaptive damping control (D-DIMPMHA) for finding a common fixed point of a finite family of nonexpansive mappings in real Hilbert spaces. By integrating a double inertial step with a self-adaptive damping parameter, the proposed method effectively balances momentum and stability, thereby mitigating numerical oscillations without requiring vanishing inertial conditions. We establish the weak convergence theorem of the generated sequence under suitable control conditions. Furthermore, the practical efficiency of the algorithm is demonstrated through numerical experiments on large-scale convex feasibility problems and image restoration problems. Comparative results indicate that the proposed algorithm achieves superior convergence speed and higher restoration quality compared to existing single inertial methods and FISTA. Full article

Slow-oscillation neurofeedback (NF), encompassing slow cortical potential (SCP), infra-low-frequency (ILF), and infra-slow-fluctuation (ISF) protocols, has gained increasing interest as a non-pharmacological intervention in pediatric mental health and neurodevelopmental care. This narrative review synthesizes peer-reviewed literature on the clinical efficacy of slow-oscillation NF in children and adolescents across various conditions, including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), epilepsy, tic disorders, and eating-related concerns. SCP NF is the most extensively studied protocol and shows preliminary efficacy in reducing ADHD symptoms, particularly among individuals capable of learning self-regulation. For ASD and other conditions, early evidence from primarily small-scale or uncontrolled studies suggests possible benefits in emotional regulation, impulsivity, and behavioral symptoms, though findings remain mixed and often non-specific. Methodological heterogeneity, including variation in control conditions, training protocols, and outcome measures, limits the comparability of results. ILF and ISF protocols, while promising, are still emerging and require further validation. Overall, slow-oscillation NF appears to offer potential as a personalized therapeutic option for pediatric populations, but robust, well-controlled trials are needed to clarify its clinical utility and optimize its integration into multimodal care. Full article

In precision aquaculture, feeding automation becomes particularly challenging when the dispenser operates on a non-fixed platform, as its dynamic behavior introduces perturbations that hinder accurate balance measurement and complicate dispenser control. To address this problem, this work proposes the integration of a weight estimator with robust control strategies. Two control approaches are evaluated: (i) a fuzzy proportional controller, where the fuzzy sets are generated using the fuzzy C-means clustering algorithm, and (ii) a self-tuning regulator (STR) based on based on an Autoregressive with Exogenous Input (ARX) model of the dispenser. In addition, the weight estimator employs a model of additive components dependent on the kinematics of the oscillating platform, with its hyperparameters experimentally optimized through cost function minimization. The proposal was experimentally validated using a compact prototype of an automatic dispenser mounted on an oscillating platform with pelletized feed, demonstrating robust performance and good dispensing accuracy, especially when employing the fuzzy-based control. Full article

Low-frequency acoustic fields—common in ventilation ducts, building façades, and industrial infrastructure—remain an underutilized source for ambient energy harvesting, particularly in humid environments where conventional contact-based or mechanically resonant harvesters may degrade over time. This study introduces a theoretical framework for converting acoustic pressure oscillations into electrical power through acoustic–electrokinetic coupling and proposes the Acoustic Baroionic Harvester (ABH) as a solid-state concept combining a Helmholtz resonator with a charged nanoporous membrane. The model is derived from coupled electrokinetic and fluid-mechanical governing relations, leading to closed-form expressions for the open-circuit voltage, internal electrokinetic resistance, and maximum deliverable power as functions of membrane surface charge, electrolyte properties, pore geometry, and resonance-induced pressure amplification. Numerical simulations are performed to validate the analytical scaling laws and to determine operating regimes that maximize power transfer to an external load. Under representative low-frequency acoustic excitation, the ABH predicts open-circuit voltages on the order of tens of millivolts and maximum power densities in the sub-microwatt-per-square-centimeter range. A compact CAD conceptual design tuned to approximately 120 Hz with a moderate resonance quality factor supports the feasibility of practical integration. The proposed approach enables micro-power generation from persistent low-frequency acoustic sources and provides a physically grounded pathway for self-powered sensing applications in built and industrial environments. Full article

Accurately describing driver response mechanisms is fundamental to microscopic traffic modeling. Traditional car-following models typically assume a fixed reaction time, implying a temporal symmetry where drivers exhibit identical response characteristics during acceleration and deceleration. To address this limitation, this paper proposes a Delay Adaptive Car-following Model that incorporates an asymmetric dynamic delay function to capture the symmetry breaking in driving behavior. Calibrated using empirical trajectory data from the Next Generation Simulation program, the proposed model demonstrates superior accuracy over the conventional Full Velocity Difference Model by effectively reproducing the realistic phenomenon of sluggish acceleration and agile deceleration. Linear stability analysis and numerical simulations reveal that, unlike fixed symmetric delays which often induce instability, the asymmetric dynamic delay acts as a self-adaptive damper. This mechanism suppresses the amplification of disturbances and prevents the formation of stop-and-go waves. The results confirm that incorporating temporal symmetry breaking into delay mechanisms significantly enhances the robustness of traffic flow against oscillations. Full article

This paper presents an experimental investigation of unsteady phenomena in shock wave/boundary-layer interaction on natural laminar flow airfoils at transonic speeds. Two airfoils of different relative thickness were studied over a Mach number range of M = 0.62–0.72 using high-speed schlieren visualization, unsteady pressure transducers, and Particle Image Velocimetry (PIV). Two distinct self-sustained periodical oscillation modes were identified. The first mode is a low-frequency oscillation analogous to classical turbulent buffet. The second modes are higher-frequency phenomena linked to oscillations of the laminar separation bubble. A key finding is a novel periodical oscillation regime, which accompanies the first/second mode, and represents laminar-turbulent transition point detaches from the normal shock wave, generating a new shock wave. The results show that the domiN/At mode and its characteristics depend strongly on the airfoil geometry, Mach number, and angle of attack, indicating a more complex transonic buffet behaviour in the presence of extensive laminar flow. Full article

Pumped-storage power stations (PSPSs) are vital for grid stability, yet pump-turbines (PTs) operating in the S-shaped region often induce severe hydraulic instability. To reveal the mechanism of these self-excited oscillations, this study establishes a nonlinear mathematical model based on rigid water column theory and a cubic polynomial approximation of the PT’s nonlinear characteristics. Both analytical derivations and numerical simulations were conducted. Analytical results indicate that, in the absence of surge tanks, self-excited oscillations occur when the PT’s negative hydraulic impedance modulus exceeds the pipeline impedance. With a single surge tank, the system behaves analogously to the Van der Pol oscillator, exhibiting oscillations that converge to a stable limit cycle governed by system parameters. Numerical simulations for a dual-surge-tank system further reveal that, due to initial negative damping, the PT transitions to alternative stable equilibria. Crucially, the transition direction is governed by the polarity of the initial disturbance: negative perturbations lead to the regular turbine region, while positive ones lead to the reverse pump region. Additionally, pipe friction causes the steady-state discharge to deviate slightly from the theoretical static value, with deviations remaining below 2.96%. This work provides a theoretical basis for stability prediction in PSPSs. Full article

This paper presents a closed-loop price–dispatch framework for park-scale virtual power plants (VPPs) with coupled electric–thermal processes under high penetrations of photovoltaics (PVs) and electric vehicles (EVs). The outer layer clears time-varying prices for operator electricity, operator heat, and user feed-in using an improved particle swarm optimizer with adaptive coefficients and velocity clamping. Given these prices, the inner layer executes a lightweight linear source decomposition with feasibility projection that enforces transformer limits, combined heat-and-power (CHP) and boiler constraints, ramping, energy balances, and EV state-of-charge requirements. PV uncertainty is represented by a small set of scenarios and a conditional value-at-risk (CVaR) term augments the welfare objective to control tail risk. On a typical winter day case, the coordinated setting aligns EV charging with solar hours, reduces evening grid imports, and improves a social welfare proxy while maintaining interpretable price signals. Measured outcomes include 99.17% PV utilization (95.14% self-consumption and 4.03% routed to EV charging) and a reduction in EV charging cost from CNY 304.18 to CNY 249.87 (−17.9%) compared with an all-from-operator benchmark; all transformer, CHP/boiler, and EV constraints are satisfied. The price loop converges within several dozen iterations without oscillation. Sensitivity studies show that increasing risk weight lowers CVaR with modest welfare trade-offs, while wider price bounds and higher EV availability raise welfare until physical limits bind. The results demonstrate an effective, interpretable, and reproducible pathway to integrate market signals with engineering constraints in park VPP operations. Full article

In the process of in situ stress fracturing drilling in coal mines, obtaining downhole vibration data not only improves drilling efficiency but also plays a key role in ensuring operational safety. Nevertheless, the energy supply techniques used in current vibration detectors reduce operational performance and escalate excavation expenses. This research proposes a self-powered vibration sensor based on the triboelectric nanogenerator, designed for the operational environment of coal mine in situ stress fracturing drilling. It can simultaneously detect axial and lateral vibration frequencies, and the inclusion of redundant sensing units provides the sensor with high reliability. Experimental outcomes demonstrate that the device functions across a frequency span of 0 to 11 Hz, maintaining error margins for frequency and amplitude under 4%. Furthermore, it functions reliably in environments where temperatures are under 150 °C and humidity is under 90%, proving its strong resilience to environmental factors. In addition, the device possesses self-generating potential, achieving a maximum voltage of 68 V alongside an output current of 51 nA. When connected to a 6 × 10⁷ Ω load, the maximum output power can reach 3.8 × 10⁻⁷ W. Unlike traditional subsurface oscillation detectors, the proposed unit combines self-generation capabilities with highly reliable measurement characteristics, making it more suitable for practical drilling needs. Full article