Search Results (4,471)

Rotating machinery is a key component in modern industry, and its operating condition directly affects equipment safety and production reliability. However, discrepancies among different machines cause source–target distribution shifts, while fault annotation for target machines is costly, limiting the performance of deep learning-based diagnosis under cross-machine scenarios with limited labels. To address these issues, this paper proposes a multi-scale time–frequency semantic consistency model based on self-supervised transferable representation learning, termed MTFSC. First, augmented waveform views and multi-scale frequency-domain views are constructed from unlabeled source-domain vibration signals for self-supervised pre-training without source labels. Then, a time-domain impulse-aware feature extractor and a time–frequency decoupled spectral feature extractor are designed to enhance local impulsive responses and emphasize fault-sensitive time–frequency patterns. Furthermore, a semantic-aware soft contrastive loss is developed to mine potential semantic neighbors from multi-scale frequency-domain structural similarity, reducing false-negative effects in conventional hard-label contrastive learning. Finally, the pre-trained time-domain extractor is transferred to the target machine and fine-tuned with limited labeled samples. Experimental results show that MTFSC outperforms comparison methods under different labeled sample ratios and achieves an average accuracy of 97.5% across four cross-machine diagnostic tasks. Full article

A new approach to 5,5-fused heterocyclic derivatives of cyclopentadienylmanganese tricarbonyl and pentamethylruthenocene is presented. 1,2-Dicarbophenoxycyclopentadienyl complexes of manganese and ruthenium were hydrolyzed to 1,2-dicarboxylic acids. Oxalyl chloride converted the acids to chlorocarbonyls, which reacted with bis(trimethylsilyl)sulfide to give the cyclopentadienyl-fused thioanhydrides. Alternatively, dehydration of the diacids with trifluoroacetic anhydride closed the diacids to cyclopentadienyl-fused anhydrides. Treatment of the anhydrides with p-toluidine followed by oxalyl chloride led to cyclopentadienyl-fused carboxylic imides. This approach enables direct comparison of electron-deficient Mn(CO)₃ and electron-rich Ru(Cp*) coordination environments on the 5,5-fused heterocycles. Spectroscopic data reveal systematic downfield NMR shifts and higher infrared carbonyl stretching frequencies for the manganese complexes, consistent with lower electron density in the Mn(CO)₃ compared to Ru(Cp*). Crystallographic analyses confirm that heterocycle fusion occurs without significant perturbation of the metal–cyclopentadienyl geometry. Comparative analysis across the series demonstrates that metal-dependent effects are primarily electronic rather than structural, with the Mn(CO)₃ and Ru(Cp*) fragments modulating electron distribution within the fused ligand framework. Full article

Floodplain wetlands are globally important ecosystems, yet altered hydrological regimes increasingly disrupt the balance between woody and non-woody vegetation. In Australia’s regulated Murray–Darling Basin, it remains unclear whether woody plant encroachment represents a persistent shift toward terrestrialisation or a dynamic process that can be periodically reversed by flooding. This study quantified long-term patterns of woody-vegetation encroachment and retreat across 32,000 ha of mapped wetlands in the mid-Murrumbidgee River floodplain from 1988 to 2023, and assessed how hydrological variability and floodplain connectivity mediate these dynamics. Using open, analysis-ready Earth observation data from Digital Earth Australia (DEA) within the Open Data Cube (ODC) framework, we combined DEA Land Cover for transition mapping, Water Observations for hydrological masking, Landsat surface reflectance for Enhanced Vegetation Index (EVI)-based spectral plausibility testing, and the Wetlands Insight Tool for qualitative temporal context. Woody-vegetation dynamics were strongly non-linear and closely linked to alternating drought and flood phases. During the Millennium Drought (2001–2009), mapped woody-cover decline exceeded 50% of wetland area in some sub-regions, whereas the post-drought recovery interval (2008–2013) produced encroachment exceeding 40% in the most affected areas. Across the full 35-year record, mean encroachment rates ranged from 85 to 250 ha yr⁻¹ among sub-regions, summing to approximately 865 ha yr⁻¹ of woody expansion across the floodplain, while retreat rates were lower overall (approximately 634 ha yr⁻¹), resulting in a net expansion of woody cover. Local hydrological connectivity strongly mediated these responses: infrequently inundated wetlands showed persistent terrestrialisation, whereas more frequently inundated, better-connected wetlands experienced periodic flood-driven retreat. Landsat-derived EVI broadly supported the mapped transitions, indicating general consistency with canopy greening and canopy decline, supporting the ecological plausibility of the detected changes. This open DEA–ODC workflow provides a transparent, transferable framework for operational wetland monitoring and demonstrates that maintaining natural flood frequency, duration, and connectivity is essential for sustaining the resilience of regulated floodplain systems. Full article

Diffusion models have achieved remarkable success in image generation, but their iterative denoising process requires repeated evaluations of large neural networks, resulting in high inference latency. Recent training-free acceleration methods, such as DeepCache, exploit temporal redundancy in U-Net features by caching and reusing high-level representations across adjacent denoising steps. However, existing caching strategies usually adopt a static skip-branch selection throughout the sampling trajectory, ignoring the stage-dependent frequency evolution of diffusion sampling. In this paper, we propose an interval-guided adaptive branch routing strategy to improve training-free feature reuse. Motivated by the observation that low-frequency global structures change rapidly in early denoising stages while high-frequency details dominate later refinement, our method dynamically adjusts the skip branch according to the timestep. It preserves deeper computation in early stages for semantic reconstruction and progressively shifts to shallower branches in later stages to reduce redundant computation while maintaining fine-grained details. The proposed method requires no retraining and can be directly applied to pretrained U-Net-based diffusion models. Experiments show that FreqCache achieves up to 1.93× speedup on CIFAR-10, 1.50× speedup on LSUN-Bedroom and LSUN-Churches, and 10.60× speedup on ImageNet 256 × 256 compared with the baseline, while maintaining an Fréchet Inception Distance (FID) score comparable to or slightly better than DeepCache at the same cache interval. Full article

This paper advances pump energy optimization by shifting the analytical focus from nominal efficiency to energy-optimal operating areas derived directly from in-field measurements. A structured experimental methodology is presented for reconstructing pump performance under real hydraulic and electrical conditions using existing systems and variable frequency drives. High-resolution datasets obtained from in-field testing are densified and normalized to map the operational area of pumps across flow, head, and rotational speed. The Best Electricity Use Point (BEUP) is identified as an energy-optimal area rather than a single operating point, accounting for system-level losses. Application to a municipal water supply pumping station on Kos Island (Greece) demonstrates that real operating behavior deviates substantially from manufacturer specifications and that BEUP-oriented control enables systematic reductions in energy consumption while improving hydraulic stability and mechanical stress conditions. The proposed framework supports a transition from static efficiency concepts to adaptive, measurement-driven pump operation. Full article

The integration of collaborative robots into industrial environments requires rigorous safety validation under the Power and Force Limiting (PFL) regime. This review article systematically maps the technological and normative development of certified Pressure and Force Measurement Devices (PFMDs) and experimental biofidelic instruments for Physical Human–Robot Interaction (pHRI) between the years 2011 and 2026. A quantitative screening of 68 studies revealed a publication peak in impact metrology in 2021. This peak occurred with a five-year latency after the release of the ISO/TS 15066 technical specification. Although global interest in collaborative robotics steadily grows, the publication trend indicates a gradual shift in scientific focus from reactive testing toward proactive prevention. A methodological deconstruction of four Research Questions (RQs) identifies persistent limitations in safety evaluation. The findings demonstrate that the internal structure of conventional sensors induces nonlinear shock filtering and parasitic oscillations (RQ1). Furthermore, the rigid fixation of test stands generates unrealistic pressure spikes. This physical limitation forces a transition to flexible and pendulum-based configurations (RQ2). Commercial flat films physically fail due to sensor saturation and introduced stiffness. Such failures accelerate the development of conformable electronic skins (e-skins) and multimodal test manikins (RQ3). To ensure interlaboratory reproducibility within the current ISO 10218-2:2025 standard, the text defines imperative metrological parameters. These parameters strictly include frequency response, calibration protocols, and volumetric mapping of inertial masses (RQ4). Furthermore, the analysed publications were systematically stratified into distinct technological categories, strictly reflecting their primary engineering domains, ranging from empirical metrological evaluation and sensor hardware design to advanced numerical modeling. Finally, the vision for future research anticipates a definitive shift toward proactive anti-collision technologies, encompassing Artificial Intelligence (AI), machine vision, and Augmented Reality/Virtual Reality/Mixed reality (AR/VR/MR). Future methodologies must also consider demographic anisotropies and the cognitive fatigue of the human operator. Full article

Dual antiplatelet therapy (DAPT) with aspirin and a P2Y12 inhibitor remains the cornerstone of antithrombotic management after myocardial revascularization. However, the traditional “one-size-fits-all” approach to DAPT duration and intensity fails to account for marked interindividual variability in drug response—driven by genetic polymorphisms, notably CYP2C19 variants like CYP2C19*2, which reach a frequency of up to 75% in specific groups like the Melanesian population—comorbidities such as diabetes and chronic kidney disease, and dynamic clinical factors including age and concomitant medications. We examine the current landscape of precision medicine tools for individualizing DAPT, including platelet function testing, point-of-care genotyping, validated clinical risk scores, and emerging artificial intelligence (AI)–based predictive models. Evidence from landmark trials is synthesized to evaluate escalation, de-escalation, and duration-tailoring strategies within the ischemic–bleeding trade-off framework. Special populations requiring individualized approaches are reviewed, including patients with atrial fibrillation, the elderly, and those requiring urgent noncardiac surgery with perioperative bridging. Future directions, including multi-omics integration, novel antiplatelet agents, and AI-driven clinical decision support systems, are also explored. As a narrative review, conclusions should be interpreted as reflective of current evidence synthesis rather than systematic-review-grade evidence, given the absence of formal risk-of-bias scoring or meta-analytic pooling. Personalized DAPT guided by complementary genetic and phenotypic testing, integrated with dynamic risk stratification, offers a paradigm shift from empiric therapy toward precision-guided antithrombotic management with the potential to simultaneously reduce ischemic and bleeding complications. Full article

Introduction: The tub gurnard (Trigla lyra) is a demersal species of commercial interest whose long-term distributional dynamics remain poorly understood. Understanding spatial and temporal changes is essential for fisheries management and for assessing biogeographic shifts. Objective: To characterise the spatio-temporal distribution and persistence of T. lyra across Galician and Cantabrian Sea waters over a 33-year period (1993–2025) and to identify environmental and fishing drivers associated with observed changes. Methodology: We analysed data from the DEMERSALES bottom trawl survey series (1993–2025), for which the sampling design remained consistent throughout. Species distribution was modelled using a delta–GAM framework (presence–absence and positive values), complemented by a presence-only GAM fitted to Vessel Monitoring System (VMS) data; because these data were only available for 2009–2023, this model was restricted to that period for biological coherence. Environmental predictors included bathymetry, slope, sediment composition (organic matter, mud, fine and coarse sand), bottom temperature, and salinity. Spatial structure was assessed using aggregation curves, occupied area, centre of gravity, a Space Selectivity Index, and an Index of Persistence. Results: The occupied area increased from 45 to 963 km² (+2040%), accompanied by a sustained decline in the Space Selectivity Index and a westward shift of the distributional centroid (~20 km), indicating progressive range broadening. The frequency of occurrence rose from 4.5% in 1993 to 87.7% in 2025, reflecting a marked increase in spatial occupancy and encounter probability. Abundance increased sharply after 2015 (+47%), consistent with strong positive year effects in the GAM. Higher occurrence and densities were associated with muddy substrates, intermediate to high organic content, and depths of 100–300 m, matching the stable aggregation cores found along the shelf break. A reduction in trawling effort (−38% in mean intensity, −17% in swept area over 14 years) likely facilitated these trends. Conclusions: T. lyra expanded its distribution and shifted westward between 1993 and 2025, with persistent aggregation cores on the shelf break. No significant effect of temperature was found, suggesting that climate warming is not the primary driver; the expansion appears most plausibly to have been favoured by the decline in fishing pressure. Full article

This paper targets the air-to-ground (A2G) data backhaul scenario of UAVs and proposes a communication system based on coherent optical zero-padding orthogonal frequency division multiplexing (CO-ZP-OFDM), which unifies atmospheric turbulence scintillation, pointing errors, and Doppler frequency shift into a composite channel model. The system employs the Gamma-Gamma (GG) distribution to describe turbulence-induced intensity fluctuations, a Gaussian beam truncation model to characterize pointing errors, and a dual-pilot method to estimate and compensate the Doppler frequency offset. Furthermore, on a polarization-time-frequency (PTF) three-dimensional orthogonal grid pilot structure, we derive theoretical mean square error (MSE) expressions for the zero-forcing (ZF) and minimum mean square error (MMSE) estimators, and analyze their MSE characteristics under the proposed pilot model. Simulation results show that, under moderate turbulence, the shrinkage factor of the MMSE estimator yields only about $0.4$ dB MSE reduction over ZF at $\mathrm{SNR}=10$ dB, whereas the full receiver pipeline that combines coherence-bandwidth pilot averaging with the MMSE and maximum ratio combining (MRC) equalizer reduces the empirical MSE by approximately 15 dB. The bit error rate (BER) performance tests indicate that, under turbulence-free conditions with ideal channel estimation, the system can reduce the BER below ${10}^{-4}$ at an SNR of approximately 12 dB. Under strong turbulence conditions with MMSE channel estimation, the SNR cost required to achieve a BER of ${10}^{-3}$ is approximately 18 dB, which corresponds to a 3 to 5 dB BER gain over the ZF baseline at the same SNR. Further simulation analysis shows that the average pointing loss is highly sensitive to the angular jitter at the 1 km link distance: an angular jitter of 1 mrad incurs about 18 dB of loss, and a sub-mrad pointing stability (i.e., ${\sigma }_{\mathrm{jit}}<0.062$ mrad) is required to keep the average pointing loss below 1 dB. Full article

Underwater communication is essential for marine research, yet saline environments pose significant challenges as electromagnetic waves suffer from severe attenuation and optical systems face scattering. Consequently, acoustic transmission remains the most practical method for medium- to long-range communication. This study investigates the impact of salinity, transmission frequency, and propagation distance on signal integrity, specifically focusing on the feasibility of using a square-wave carrier with On-Off Keying (OOK) modulation as a simpler, low-cost alternative to traditional sinusoidal frequency-shift keying (FSK). Experiments were conducted in a custom glass tank and analyzed via MATLAB. The results reveal that increased salinity and higher frequencies led to greater signal distortion and attenuation, which complicates reliable binary recovery. However, despite these environmental hurdles, the study demonstrates that square-wave OOK allows for successful binary data recovery over short distances. The findings suggest that simplified modulation schemes could potentially be used for short-range underwater communication in controlled environments, particularly where minimizing system complexity is of concern. Ultimately, the work provides valuable insights into how environmental factors influence acoustic signal integrity, offering a preliminary basis for future development of accessible and efficient underwater communication platforms targeted to shallow water communication. Full article

This paper presents an open-source miniaturised readout device designed for the wireless interrogation of passive LC sensors and wireless power transmission. The system is based on a Sparkfun RedBoard Artemis microcontroller with a custom-printed circuit board as an extension, providing a compact, low-cost alternative to expensive laboratory-grade equipment. The reader coil is excited by a signal that can be tuned digitally in both frequency and amplitude. The resonance frequency of a wirelessly coupled LC tank is detected by monitoring the voltage minimum of a rectified signal envelope, which corresponds to the impedance change of the reader inductance at resonance. Experimental validation demonstrates that the device accurately tracks resonance frequency shifts resulting from variations of the LC tank’s capacitance, performing comparably to laboratory-grade impedance analysers. Testing the influence of axial separation between the two coils up to 25 $\mathrm{m}$$\mathrm{m}$ showed stable and identifiable voltage dips. The programmable excitation signal peak-to-peak voltage ranges from $0.81$ V to $5.35$ V. The device enables fully stand-alone operation with a display and navigation switch, making it suitable for untethered LC wireless sensing and actuation applications. Full article

Wireless power transfer (WPT) is increasingly used in smart manufacturing, unmanned platforms, and contactless power-supply applications. However, weak coupling, load-dependent impedance drift, and spatial misalignment can shift the resonant condition, leading to unstable output voltage and reduced transfer efficiency. This paper proposes a constant-voltage WPT method that combines a non-uniform winding coupler, parasitic coils, and dynamic capacitor compensation. A composite magnetic coupler with dense outer windings, loose inner windings, and parasitic coils is first developed, and a region-based electromagnetic model is established to characterise self-inductance, mutual inductance, and coupling coefficients. An improved LCC-S compensation network with a dynamic capacitor compensation matrix is then derived to keep the system close to resonant operation at the nominal 85 kHz operating point under load variation and coil-displacement-induced coupling changes. A zero-voltage-switching-angle tracking method with mutual-inductance correction is further introduced to compensate for phase deviation and maintain soft-switching operation through limited switching-frequency adjustment. Experimental validation demonstrates that the system maintains a stable constant-voltage output across a load range of 20–50 Ω and under 5 cm lateral and longitudinal offsets. The measured efficiency remains above 89% and reaches 93.7% under the optimal coupling and load-matching condition. Full article

Reliable fault diagnosis of rotating machinery is critical for averting serious failures in modern industrial systems. While data-driven deep learning has advanced condition monitoring, its success is fundamentally predicated on the availability of independent and identically distributed (I.I.D.) datasets. In realistic operational environments, machinery frequently experiences massive domain shifts induced by varying rotational speeds. Concurrently, acquiring high-fidelity fault instances is limited compared to abundant healthy baseline data, often resulting in a long-tailed distribution. Under such data-starved conditions, conventional few-shot domain adaptation (FSDA) methodologies often may be affected by distributional erasure; global alignment objectives are mainly driven by the healthy majority, causing sparse fault signatures to be erroneously absorbed as noise and leading to severe diagnostic performance degradation. To address this setting, this study develops a physics-guided dual-stream fusion framework for extreme few-shot cross-domain fault diagnosis. The method does not treat the Laplace wavelet, STFT, CNNs, or AdaBN as newly introduced techniques. Instead, it integrates these components into a unified diagnostic pipeline designed for long-tailed target support sets under large speed shifts. A learnable Laplace wavelet convolution is used in the temporal branch to emphasize transient impact responses, while STFT spectrograms provide a complementary time-frequency representation for the two-dimensional branch. The two feature streams are then fused for target fault classification. For domain adaptation, a Strict AdaBN strategy is applied using only the target support set, rather than the target test data or a large unlabeled target pool. Under the evaluated 50 healthy + 12 fault support condition, the healthy samples provide target-domain operating-background statistics for BN recalibration, while the limited fault samples are used for supervised classifier adjustment. Experiments on the HUSTbearing and Torino DIRG datasets show that the proposed integrated framework achieves stable performance under the evaluated few-shot cross-speed settings. These results suggest that combining physics-guided Laplace convolution, time-frequency representations, and support-set-restricted BN recalibration can be useful for bearing fault diagnosis when target fault samples are limited. Full article

Ultrasonic thickness resonance can be effectively used to detect and quantify the level of corrosion in steel nuclear storage containers as well as other corrosion-prone thin-walled structures, such as pipes and storage tanks. Electro-Magnetic Acoustic Transducers (EMATs) have several advantages over more traditional piezoelectric-based transducers; namely, they can be used in a non-contact fashion on robotic platforms, allowing for measurements regardless of surface conditions or temperature. The major challenge of EMAT application is the power required to counteract the low actuation efficiency, which is achieved with a high-power ultrasonic pulse generator and a transformer circuit. Resonance techniques, in which most of the energy is concentrated near structural resonance frequencies, are preferable to improve efficiency of electro-magnetic acoustic measurements. This methodology was applied to 316L stainless steel thin plates subjected to uniform corrosion as well as pitting corrosion imitating different damage scenarios in a nuclear waste container. The resonant peak frequency shift was found to be proportional to the severity of corrosion for minimally corroded samples. However, the complete disappearance of the resonance peak was observed in the samples with severe corrosion damage. The EMAT liftoff distance was studied to quantify its effect on the amplitude, spread, and frequency of resonant peaks. Recommendations for use of EMATs for assessing corrosion damage are presented. The study demonstrates the success of frequency-based detection of corrosion damage in 316L stainless steel used in fabrication of nuclear waste storage containers. Full article

This study established a refined, distributed SWAT modeling framework that integrates elevation-band and snowmelt modules to reconstruct the alpine hydrological and sediment cycles of the Koshi River Basin (KRB) over the period 1990–2024, with climate scenarios constructed using the delta change approach. The KRB, a major transboundary watershed traversing China, Nepal, and India, was selected owing to its critical hydro-climatic role under the destabilizing “Asian Water Tower”; it generates substantial sediment yield, hosts the densest concentration of hydropower potential within the Ganges system, and spans an extreme vertical gradient from Mount Everest to the southern alluvial plains. Results reveal accelerated warming at a rate of 0.21 °C per decade and an overall warming–wetting trend, punctuated by an abrupt interdecadal shift around 2015. Precipitation dominated interannual streamflow variability, with enhanced rainfall triggering basin-wide sediment surges that overwhelmed the natural buffering capacity of the land surface. Conversely, rising temperatures intensified actual evapotranspiration, markedly depleting soil water and reducing total water yield and monsoon runoff, although sustained snow and glacier melt effectively elevated the dry-season low-flow baseline. The integrated climate forcing reshaped the disparity between hydrological extremes, imposing severe seasonal eco-hydrological stress that manifested as a pre-monsoon deficit in terrestrial green water and acute summer sediment outbursts for aquatic habitats. Furthermore, the flood regime exhibited an altered distribution, with mid-to-high frequency floods enhanced while low-frequency extreme flood peaks declined. The hydro-sedimentological regime consequently exhibits pronounced nonlinear responses to climate change, providing a critical, threshold-based scientific foundation for adaptive transboundary water resource management. Full article