Search Results (6,777)

In ultrasonic Lamb wave non-destructive testing of aluminum plates, Lamb wave signals are susceptible to industrial interference, which may obscure useful information. To address this issue, this paper developed a signal denoising method combining Improved Crown Porcupine Optimization (ICPO) and Variational Mode Decomposition (VMD) with an improved wavelet threshold. The ICPO algorithm optimizes VMD parameters using fuzzy entropy as the fitness function. The decomposed modes are categorized into signal-dominant, mixed, and noise-dominant modes by the correlation coefficient method. The mixed modes are denoised using wavelet thresholding, and the final signal is reconstructed from the signal-dominant modes and the denoised mixed modes. Compared with VMD, direct wavelet thresholding, and ICPO-VMD combined with soft or hard thresholding, the proposed method outperforms the compared methods in both quantitative metrics and waveform preservation. These results confirm the effectiveness of the proposed method for aluminum plate Lamb wave denoising under the tested conditions. Full article

Multiphase swirling flows in confined spaces induce highly destructive, nonlinear fluid–structure interaction (FSI) vibrations. Understanding the underlying physical mechanisms is critical for ensuring the safety of industrial operations. This study proposes a mesoscopic multiscale framework coupling the Multi-Relaxation Time Lattice Boltzmann Method with Large Eddy Simulation (MRT-LBM-LES) and the Flügge thin-walled cylindrical shell equations to analyze two-way FSI responses. Variational Mode Decomposition (VMD) and the Hilbert–Huang Transform (HHT) are employed to decouple non-stationary broadband excitation signals. The macroscopic topological evolution of the swirling air core—from initial depression to critical breakthrough—is accurately captured. Dynamic mapping reveals a strict time-domain phase-locking mechanism between macroscopic flow instability and microscopic high-frequency structural excitation caused by cavitation bubble collapse. Furthermore, a dimensionless cross-scale energy cascade index is defined to quantify energy transfer. Results indicate that while higher discharge flow rates delay the critical breakthrough, they trigger a delayed, high-amplitude step mutation in the energy cascade, amplifying the global cumulative excitation energy by nearly 75%. Notably, the dominant high-frequency excitation consistently converges within a narrow band of 760 Hz to 790 Hz, independent of flow rate variations. These findings provide a theoretical foundation for unsteady excitation source localization and targeted vibration reduction in complex industrial pipeline networks. Full article

Background and Objectives: Intra-cyclic variation in swimming velocity is one of the variables most commonly used to assess swimming performance, providing simple, straightforward information for coaches and swimmers. Therefore, the main aim of this study was to assess the consistency and association between the two most commonly used methods for calculating the intra-cyclic variation in velocity in swimming (coefficient of variation—dv1; and range: the difference between the maximum and minimum instantaneous velocities—dv2). Methods: Twenty-one young butterfly swimmers (11 males and 10 females) with an average age of 17.3 ± 2.8 years were recruited for analysis. The measurements were done in the butterfly stroke at maximal velocities. The consistency and association criteria included the intraclass correlation coefficient (ICC) and simple linear regression between the two methods. Results: The ICC between dvs was excellent for the overall sample (ICC = 0.972, p < 0.001), males (ICC = 0.978, p < 0.001), and females (ICC = 0.955, p < 0.001). The linear regression between methods was very high (overall: R² = 0.93, p < 0.001; males: R² = 0.91, p < 0.001; females: R² = 0.86, p < 0.001). Conclusions: Overall, coaches and researchers should be aware that although both methods yielded highly concordant results, they are based on different mathematical formulations and quantify distinct characteristics of the velocity signal. Therefore, their consistency and association should not be interpreted as mathematical equivalence or universal interchangeability. Full article

Plumage anomalies in owls range from common color polymorphisms to rare, extreme aberrations such as leucism, albinism, and melanism, yet systematic syntheses across taxa are scarce. In this review, we collate recent genomic, ecological, and environmental research (2017–2025) on owl plumage anomalies and combine it with new field observations from Israel to examine how depigmentation and hyperpigmentation arise and what their ecological consequences may be. We highlight the exceptional rarity of familial leucism by presenting a brood of Eurasian Eagle Owls (Bubo bubo) from Mount Gilboa containing two Ino and one normally colored fledgling—the first family-level record in this species and only the second wild case of extreme depigmentation in Eurasian Eagle Owls following a leucistic fledgling reported in Spain. We complement this with another sporadic color anomaly in a Little Owl (Athene noctua) from the Galilee and one from Shoham, Central Israel, both exhibiting unusually dark plumage with reduced pale spotting. Together, these records illustrate that owls may show pronounced reductions or alterations in melanin-based plumage coloration. However, the underlying mechanisms—including possible melanin-synthesis defects, altered melanin deposition, and external staining—cannot always be determined from photographs or opportunistic observations alone. By integrating these examples with broader evidence on climate, habitat, diet, and urbanization as drivers of plumage variation, we argue that rare pigment anomalies, although individually exceptional, provide disproportionate insight into camouflage, signaling, fitness, and potential bioindicator roles in owl populations facing rapid environmental change. Full article

Background: Cell migration is a biological process influenced by biochemical signals and mechanical stimuli from the microenvironment. In this context, the accurate characterization of the mechanical microenvironment generated within microfluidic platforms represents an essential step for the design and interpretation of cell migration studies. Understanding how hydrodynamic forces influence the mechanical microenvironment experienced by cells remains a challenge, especially in confined and biomimetic systems. Methods: In this study, a three-dimensional microfluidic device was developed in silico to characterize the effects of flow variation on mechanofluidic parameters and to provide a quantitative basis for designing future cell-migration experiments. Computational fluid dynamics simulations were performed to characterize the velocity, pressure, and wall shear stress (WSS) distributions under different inlet flow rates (0.5, 1, and 5 µL/min) and three distinct inlet/outlet configurations within the same three-dimensional geometry. Rigid hemispherical probe structures were incorporated into the model to quantify the local shear stress acting on cell-sized surfaces. Results: The results demonstrated a direct and linear relationship between the applied flow rate and the WSS, modulated by the channel geometry and the inlet and outlet configuration. Regions near micropores and lateral channels showed high WSS values, while central regions experienced less mechanical stimulation, depending on flow conditions. Comparison with WSS values and ranges associated with cellular responses reported in the literature indicated that certain operational configurations generated mechanical conditions comparable to those previously investigated in cell-based studies, including cell migration applications. Conclusions: Overall, the study highlights the importance of controlling flow conditions in microfluidic platforms and provides a quantitative basis for the development and optimization of three-dimensional microfluidic devices intended for designing future cell-migration experiments. The systematic comparison of three inlet/outlet configurations across three flow rates within the same three-dimensional geometry provides a comparative framework for identifying configuration-dependent changes in the local mechanofluidic environment, supporting the selection of operational conditions for future mechanobiological and cell-migration studies. Full article

Walnuts are commercially important tree nuts whose moisture content (MC) influences quality, shelf life, and post-harvest processing. This study evaluated the potential of low-cost acoustic sensing combined with machine learning for non-destructive MC prediction. Sixty in-shell walnuts were subjected to controlled drying at 40 °C for 26 h, with acoustic recordings and physical measurements collected every two hours. Acoustic signals were processed using Wavelet Soft Threshold Denoising (WSTD), Short-Time Fourier Transform (STFT), and Variational Mode Decomposition (VMD), and features were extracted from the resulting signals. Predictive models included generalized linear models (GLM), random forests (RF), gradient boosting machines (GBM), and Partial Least Squares (PLS) approaches. Following grouped walnut-level validation, the highest MC prediction performance was achieved by the model combining dimensional and acoustic descriptors (RF: R² = 0.836; GBM: R² = 0.826), while the model combining drying time and acoustic descriptors achieved moderate predictive performance (RF: R² = 0.762; GBM: R² = 0.760). Overall, the results provide proof-of-concept evidence that acoustic descriptors may complement physical measurements for non-destructive walnut moisture-content prediction. However, substantially larger independent datasets collected across multiple cultivars, production batches, acquisition conditions, and external validation studies will be required before practical industrial implementation can be considered. Full article

Classical readability formulas are widely used to evaluate academic abstracts, yet the evidence on what they register is mixed, and disciplinary differences are often invoked to explain that inconsistency. This study examines within-field variation, treating forestry-related research as a set of knowledge domains and scoring 4191 English-language Web of Science abstracts from 2008 to 2019 with four classical indices. The abstracts were consistently demanding on all four indices. The most difficult domain was forest economics, policy, governance and social dimensions, with ecology and conservation being intermediate and inventory and management not being distinguishable from tree biology and silviculture. The contrasts persisted within journals, though the distributions overlapped substantially, and most variation remained within domains. With domain and covariates being controlled, no index showed a statistically distinguishable association with normalized citation impact, and the interaction tests did not establish domain heterogeneity. Domain was modestly associated with citation impact, but readability did not account for it. The indices, therefore, register systematic differences in linguistic form across knowledge domains while giving no dependable signal of scholarly uptake. For authors and editors, such scores work best as prompts for closer reading with a domain and an audience in view, not as field-wide standards or proxies for expected citation. Full article

Developmental disorders often arise from complex interactions between genetic variation and environmental factors, yet the molecular mechanisms underlying gene-gene (G × G) and gene-environment (G × E) interactions remain poorly understood. Mouse embryonic eyelid closure provides a genetically tractable in vivo model for investigating these mechanisms. Eyelid closure requires coordinated epithelial migration and cytoskeletal remodeling orchestrated by interconnected signaling pathways. Among these pathways, MAP3K1 functions as a critical signaling hub that integrates inputs from S1PR-RHOA-ROCK and other upstream regulators to activate JNK and promote eyelid closure. Genetic studies show that multiple components within the GPCR-RHOA-ROCK-MAP3K1-JNK network cooperate to maintain developmental robustness. Reducing the activity of pathway components dose-dependently impairs eyelid closure and produces the characteristic eye-open-at-birth (EOB) phenotype. Environmental factors also converge on this network. Although exposure to dioxin does not impair eyelid closure in wild-type embryos, it induces EOB in embryos harboring otherwise phenotypically silent mutations in the MAP3K1 network, such as Map3k1^+/−, Jnk1^−/− and S1pr2^−/−. These findings identify the MAP3K1 pathway as a point of convergence of genetic and environmental signals and establish embryonic eyelid closure as a powerful model for elucidating molecular mechanisms underlying developmental robustness, susceptibility and resilience. Full article

Parkinson’s disease (PD) is associated with alterations in gait symmetry and plantar loading that can be examined using vertical ground reaction force (VGRF) recordings. This study presents a confidence-stratified, physiology-anchored multiple-instance learning framework with concept-bottleneck-inspired pathways (implementation identifier: DRO-PAS-MIL-CBM; hereafter, PAS-MIL) for retrospective session-level PD-versus-control classification. Each gait session is represented as a bag of temporal windows. Eight predefined bilateral signal descriptors are combined with eight learned latent temporal dimensions, aggregated through attention-based pooling, and processed by concept-guided, prototype, anchor-only, and static-feature expert pathways. The evaluation used five-fold person-grouped cross-validation on 306 sessions from 165 participants in the PhysioNet Gait in Parkinson’s Disease database.Inner person-grouped out-of-fold ExtraTrees probabilities were used to construct the confidence strata and distillation targets. PAS-MIL achieved a pooled session-level area under the receiver operating characteristic curve of 0.771, average precision of 0.890, and a mean fold AUC of $0.826\pm 0.041$. Relevance analysis identified C05 (asymmetry variability) and C08 (bilateral change mismatch) as the highest-weighted predefined physiological anchor descriptors. Protocol-stratified sensitivity analysis showed variation across the three source sub-studies, with AUCs ranging from 0.740 to 0.790. Probability calibration remained suboptimal after temperature scaling (mean per-fold ECE, $0.291\pm 0.042$). The results demonstrate the feasibility of integrating physiology-informed descriptors, temporal representation learning, and session-level aggregation. The study is a retrospective proof of concept and does not establish external robustness or clinical deployment readiness. Full article

Addressing the current issues of the uncertain primary frequency bands and the difficulty in directly measuring the spectral characteristics of neural electromagnetic signals transmitted within nerve fibers, this study investigates the spectral and time-domain properties of the neural electromagnetic signals through finite element simulations, using the influence of the node of Ranvier on nerve conduction velocity as a breakthrough point, and develops a coaxial transmission line impedance transformation model. The research results demonstrate that the primary signals capable of effective transmission within nerve fibers may reside in the terahertz (THz) band. They also show that the node of Ranvier essentially functions by regulating its geometric length to achieve impedance matching between the node and the myelin sheath, thereby reaching the optimal efficiency for signal coupling. The above finding not only explains the mechanism underlying the non-monotonic variation in neural conduction velocity with the length of the node of Ranvier, but also provides the latest perspective for understanding the relationship and differences between transmembrane action potentials that accompany the generation of neural signals and information transmission carriers—electromagnetic signals. It may also provide a theoretical supplement to the understanding of signal frequency–timing issues in neural encoding. Full article

Genome-wide association studies (GWASs) have mapped many regions affecting cattle production, health and fertility, yet the lead variant is usually a marker for a linkage-disequilibrium block rather than the molecular lesion. This state-of-the-field review examines how those loci are interpreted at different levels. The literature shows both progress and persistent limits. Colocalization may identify a likely effector transcript without establishing mediation, whereas structural variants missing from SNP-based analyses can account for expression, splicing, or complex-trait signals. Earlier reviews have audited proposed causative variants across cattle and pigs, surveyed causal variants across livestock species, or concentrated on structural variation. Here, these lines of evidence are brought together around a narrower question: Why do cattle complex-trait loci remain resolved at such different biological depths? Coding, regulatory, splicing, and structural examples show where inference is persuasive and where alternatives remain. The evidence is organized as a conceptual landscape, not a validated hierarchy or prescriptive pipeline. The available mechanistic evidence is nevertheless concentrated in commercial taurine, particularly dairy populations, which limits the direct transferability of locus-level conclusions to indicine, African taurine, composite and locally adapted cattle. Priorities include clearer causal terminology, multi-signal and multi-breed analyses, better representation of structural variation, tissue- and cell-state-matched molecular data, native bovine experimental systems and transparent reporting of unresolved explanations. Full article

Background: Steel club training is a form of strength and conditioning exercise that involves swinging weighted clubs through circular and pendular movements, thereby imposing substantial rotational and multiplanar demands on the trunk. However, the core muscle activation patterns elicited by these exercises remain poorly characterized. Purpose: This study aimed to characterize global, muscle-specific, and side-to-side core muscle activation across a battery of steel club exercises and compare it with that of conventional plank variations. Methods: A within-subject experimental design was used in a single-session laboratory setting. Fourteen trained males (n = 14) performed ten steel club exercise conditions (comprising seven distinct movement patterns, with unilateral variations performed bilaterally) using 8 and 16 kg clubs and four isometric plank variations; data from n = 13 were available for the Shield Cast 16 kg condition and the omnibus ANOVA due to one excluded signal. Surface electromyography was bilaterally recorded from the rectus abdominis, external oblique, internal oblique, and multifidus muscles and normalized to maximal voluntary contraction (% MVC). Repeated-measures ANOVA was used to assess global and muscle-specific differences across exercise conditions, and paired-samples t-tests were used to evaluate side-to-side differences. Results: Global core activation significantly differed across exercises (p < 0.001, ηp² = 0.798) and was generally greater during steel club exercises than during conventional planks. The Lateral Pendulum to Shoulder Cast (54.77 ± 9.32% MVC), Gamma Cast (47.79 ± 8.96% MVC), and Shield Cast (43.96 ± 11.25% MVC), all performed with 16 kg, elicited greater global activation than each of the four plank variations (all adjusted p < 0.05). The internal oblique showed the greatest activation across most steel club exercises, reaching 69.40 ± 12.18% MVC during the Lateral Pendulum to Shoulder Cast. Several unilateral exercises also elicited significant side-to-side differences, particularly Mills and Reverse Mills (all p < 0.05). Conclusions: Among experienced steel club practitioners, these exercises elicited exercise-specific, dynamic, and multiplanar core activation patterns, with several exercises—particularly those performed with 16 kg—producing greater global activation than conventional plank variations. These findings support steel club training as a complementary modality for dynamic core training, although the independent contributions of movement pattern and external load, as well as long-term adaptations, remain to be established. Full article

We propose a data-driven procedure, based on convolutional variational autoencoders, to identify the presence of signal pulses in long time series. The dataset consists of synthetic waveforms, each composed of non-Gaussian noise and a log-normal-shaped signal of variable intensity, with a length of 10,000 samples. The model heavily compresses the input waveforms, allowing a direct study of such a reduced representation. After training for 150 epochs on 7500 waveforms, a region in the latent space where the network encodes time-series presenting only background noise emerges, allowing, in turn, to tag as candidates for containing a signal those falling outside. When applied to a test dataset of freshly generated waveforms, 100% of events with signal amplitudes well above the baseline noise are correctly labelled, and this fraction only decreases for amplitudes comparable with accidental noise pulses. This approach was designed to fully exploit the measurements in dual-phase Liquid Argon Time Projection Chambers, as the one of the Recoil Directionality experiment, built in the context of the Darkside project. Full article

Bioactive peptides are an important source of therapeutic molecules and molecular scaffolds involved in defense, signaling, and immune regulation. Despite the extraordinary diversity of Coleoptera, the structural landscape of beetle-derived bioactive peptides remains largely unexplored, limiting our understanding of their evolutionary diversity and biotechnological potential. Here, we performed a large-scale structural survey of predicted toxin-like peptide scaffolds across publicly available Coleoptera transcriptomes by integrating transcriptome mining, peptide maturation prediction, physicochemical characterization, AlphaFold 3 structural modeling, structural similarity analyses, and interpretable machine learning. We identified 291 candidate peptides, of which 155 contained canonical signal peptides and 273 produced mature peptides within the expected size range of known bioactive peptides. Structural analyses revealed that, despite extensive sequence diversity, many candidates were organized into a comparatively restricted repertoire of compact cysteine-rich architectures, indicating that structural similarity is retained across peptides exhibiting substantial primary-sequence variation. Comparative structural analyses further identified recurrent protein architectures shared across multiple beetle lineages, while machine learning prioritization integrated structural and biochemical descriptors to identify high-confidence candidates for future functional characterization. These analyses establish the first structural atlas of predicted toxin-like peptides across Coleoptera and demonstrate that structure-guided transcriptome mining provides a powerful framework for uncovering recurrent bioactive peptide scaffolds that would remain largely undetected using sequence-based approaches alone. Beyond expanding our understanding of peptide evolution in beetles, this resource is a foundation for future structural, functional, and biotechnological exploration of bioactive peptides in underexplored animal groups. Full article

Raw Chinese lacquer, tapped from the sap of Toxicodendron vernicifluum, is a natural water-in-oil microemulsion containing urushiol, polysaccharides, proteins, and laccase. Because this reactive system continues to oxidize and polymerize after harvesting, handling conditions directly determine water content, viscosity, and later film-forming performance. This review analyzes potential in situ stabilization routes that couple purification, low-temperature vacuum dehydration, and quality conditioning at, or near, the collection site. Emphasis is placed on how laccase retention, oxygen exposure, and urushiol polymerization are controlled together to limit transport losses and premature crusting. Portable filtration devices, reported centrifugal filtration systems, and proposed vacuum dehydration strategies are compared in terms of throughput, field compatibility, and process control. Physical and bio-based conditioning strategies, including shear adjustment, oxygen management, and natural film-forming aids, are further considered for on-site regulation. Surface-enhanced Raman spectroscopy (SERS) and portable spectroscopic devices are examined as feedback tools for parameter adjustment under field temperatures, humidity, and storage variation; however, these signals are treated as decision-support indicators that still require lacquer-specific calibration after tapping. The central task is to define a field-compatible process window for water removal, laccase retention, viscosity control, drying behavior, and storage stability before downstream coating preparation. The remaining challenges involve miniaturized equipment, standardized evaluation, evidence-level classification, and dynamic control of coupled variables. Full article