Search Results (1,699)

The availability of detritus is a key factor influencing aquatic biota and can significantly affect decomposition processes. In this study, we investigated how varying quantities of surrounding detritus impact leaf litter decay rates. It was tested in flowing and still-water microcosms to highlight context-dependent effects of surrounding detritus on leaf litter decomposition. To isolate the effect of detritus amount, experiments were conducted in laboratory microcosms simulating lotic and lentic ecosystems, each containing leaf fragments for decomposition assessments. Four detritus quantities were tested, with invertebrates either allowed or restricted from moving among detritus patches. Leaf decomposition rates were influenced by the amount of surrounding detritus, with slower decay observed at higher detritus conditions, regardless of invertebrate mobility. Detritivore distribution responded to both detritus quantity and oxygen availability, showing a preference for high detritus conditions. Additionally, detritus quantity affected microbial activity with a quadratic response, as indicated by leaf respiration rates. Overall, our findings indicate that the amount of surrounding detritus modulates leaf litter decomposition independently of invertebrate density, by influencing oxygen dynamics and, consequently, the activity of biological decomposers. Full article

Mud pulse telemetry (MPT) systems are a promising approach to transmitting downhole data to the ground. During transmission, the amplitudes of pressure waves decay exponentially with distance, and the channel is often frequency-selective due to reflection and multipath effect. To address these issues, this work proposes a fractional Fourier transform (FrFT)-based channel estimation and equalization method. Leveraging the energy aggregation of linear frequency-modulated signals in the fractional Fourier domain, the time delay and attenuation parameters of the multipath channel can be estimated accurately. Furthermore, a fractional Fourier domain equalizer is proposed to pre-filter the frequency-selective fading channel using fractionally spaced decision feedback equalization. The effectiveness of the proposed method is evaluated through a simulation analysis and field experiments. The simulation results demonstrate that this method can significantly reduce multipath effects, effectively control the impact of noise, and facilitate subsequent demodulation. The field experiment results indicate that the demodulation of real data achieves advanced data rate communication (over 12 bit/s) and a low bit error rate (below 0.5%), which meets engineering requirements in a 3000 m drilling system. Full article

Effective postharvest cooling of olive fruit is increasingly critical under rising harvest temperatures driven by climate change. This study models passive cooling dynamics using a trait-based, mixed-effects statistical framework. Ten olive groups—representing seven cultivars and different ripening or size stages—were subjected to controlled cooling conditions. Surface temperature was recorded using infrared thermal imaging, and morphological and compositional traits were quantified. Temperature decay was modeled using Newton’s Law of Cooling, extended with a quadratic time term to capture nonlinear trajse thectories. A linear mixed-effects model was fitted to log-transformed, normalized temperature data, incorporating trait-by-time interactions and hierarchical random effects. The results confirmed that fruit weight, specific surface area (SSA), and specific heat capacity (SHC) are key drivers of cooling rate variability, consistent with theoretical expectations, but quantified here using a trait-based statistical model applied to olive fruit. The quadratic model consistently outperformed standard exponential models, revealing dynamic effects of traits on temperature decline. Residual variation at the group level pointed to additional unmeasured structural influences. This study demonstrates that olive fruit cooling behavior can be effectively predicted using interpretable, trait-dependent models. The findings offer a quantitative basis for optimizing postharvest cooling protocols and are particularly relevant for maintaining quality under high-temperature harvest conditions. Full article

To overcome the limitations of single-objective optimization in permanent magnet synchronous motor (PMSM) performance enhancement, this study proposes an adaptive moving least squares (AMLS) for a 12-pole/36-slot built-in PMSM. Through comprehensive exploration of the design space, a systematic approach is established for holistic motor performance improvement. The Gaussian weight function is modified to improve the model’s fitting accuracy, and the decay rate of the control weight is optimized. The optimal adaptive meta-model for the built-in PMSM is selected based on the coefficient of determination. Subsequently, sensitivity analysis is conducted to identify the parameters that most significantly influence key performance indicators, including torque ripple, stator core loss, electromagnetic force amplitude, and average output torque. These parameters are then chosen as the optimal design variables. A multi-objective optimization framework, built upon the optimal adaptive meta-model, is developed to address the multi-objective optimization problem. The results demonstrate increased output torque, along with reductions in stator core loss, torque ripple, and radial electromagnetic force, thereby significantly improving the overall performance of the motor. Full article

Concave surface is a common geometry in both industrial buildings and natural environments; the flame spread behaviors on this special surface are worth studying, while few studies have been completed yet. In this study, kraft paper, which is a typical charring material, was chosen to investigate the behaviors of concurrent flame spread on concave surfaces. The results showed that there were three stages of the flame spread process on a concave surface: the flame gathering stage, the flame acceleration stage and the flame burnout stage. A peak mass loss rate was found at the end of the flame acceleration stage and then decayed rapidly due to the lack of sample that can maintain the flame spread. An experiential equation to predict the maximum mass loss rate was established. The flame spread showed an obvious acceleration with the increase in curvature, a new dimensionless number was proposed to find out whether the flame spread was accelerated or not. For the accelerated flame spread, the critical value is 0.85. Segmented expressions between dimensionless flame height and dimensionless heat release rate were developed, with good correlation for smaller curvatures. This study’s results will fill the blank of flame propagation on concave surfaces, improve the understanding of fires in special cases, and provide assistance in related fire risk evaluations. Full article

Sweet cherry (Prunus avium L.) is becoming increasingly popular in China, but its postharvest quality deteriorates significantly during harvest storage and transport. Here, we investigated the efficiency of different modified atmosphere packaging (MAP) treatments on the quality and physiology of ‘Meizao’ sweet cherry during 60 days of cold storage (0 ± 0.5 °C). Fruits were sealed in four types of MAP low-density polyethylene (LDPE) liners (PE20, PE30, PE40, and PE50), with unsealed 20 μm LDPE packaging bags used as the control. Our findings demonstrated that PE30 packaging established an optimal gas composition (7.0~7.7% O₂ and 3.6~3.9% CO₂) that effectively preserved ‘Meizao’ sweet cherry quality. It maintained the fruit color, firmness, soluble solid content (SSC), titratable acidity (TA), and vitamin C (Vc) content while simultaneously delaying deteriorative processes such as weight loss, pedicel browning, and fruit decay. These results indicate that PE30 was the most suitable treatment for preserving the quality of ‘Meizao’ sweet cherries during cold storage. Furthermore, physiological research showed that significant inhibition of respiration rate was achieved by PE30, accompanied by maintained activities of antioxidant enzymes (CAT, POD, and SOD), which consequently led to reduced accumulations of ethanol and malondialdehyde (MDA) during cold storage. To date, no systematic studies have investigated the physiological and biochemical responses of ‘Meizao’ to different thickness-dependent LDPE-MAP conditions. These observations highlight the power of the optimized PE30 packaging as an effective method for extending the fruit storage life, delaying postharvest senescence, and maintaining fruit quality of ‘Meizao’ sweet cherry. Full article

Persea americana (avocado) is a healthy fruit, rich in unsaturated fatty acids, various minerals, and vitamins. As avocado cultivation continues to expand globally, its development is increasingly constrained by concomitant diseases, among which fruit rot and anthracnose have emerged as significant threats to fruit quality. Menglian in Yunnan Province is the largest avocado production area in China. In November 2024, fruit rot was observed on avocado fruits in Yunnan, China, characterized by reddish-brown discoloration, premature ripening, softening, and pericarp decay, with a field infection rate of 22%. Concurrently, anthracnose was detected in avocado fruits, presenting as small dark brown spots that developed into irregular rust-colored lesions, followed by dry rot depressions, ultimately leading to soft rot, peeling, or hardened dry rot, with a field infection rate of 15%. Infected fruit samples were collected, and fungal strains were isolated, purified, and inoculated via spore suspension, followed by re-isolation. The strains were conclusively identified as Diaporthe phaseolorum (SWFU20, SWFU21) and Colletotrichum fructicola (SWFU12, SWFU13) through an integrated approach combining DNA extraction, polymerase chain reaction (PCR), sequencing, phylogenetic reconstruction, and morphological characterization. This is the first report of D. phaseolorum causing fruit rot and C. fructicola causing anthracnose on avocado in China. In future research, we will test methods for the control of D. phaseolorum and C. fructicola. The identification of these pathogens provides a foundation for future disease management research, supporting the sustainable development of the avocado industry. Full article

The chiral nonlinear Schrödinger equation (CNLSE) serves as a simplified model for characterizing edge states in the fractional quantum Hall effect. In this paper, we leverage the generalization and parameter inversion capabilities of physics-informed neural networks (PINNs) to investigate both forward and inverse problems of 1D and 2D CNLSEs. Specifically, a hybrid optimization strategy incorporating exponential learning rate decay is proposed to reconstruct data-driven solutions, including bright soliton for the 1D case and bright, dark soliton as well as periodic solutions for the 2D case. Moreover, we conduct a comprehensive discussion on varying parameter configurations derived from the equations and their corresponding solutions to evaluate the adaptability of the PINNs framework. The effects of residual points, network architectures, and weight settings are additionally examined. For the inverse problems, the coefficients of 1D and 2D CNLSEs are successfully identified using soliton solution data, and several factors that can impact the robustness of the proposed model, such as noise interference, time range, and observation moment are explored as well. Numerical experiments highlight the remarkable efficacy of PINNs in solution reconstruction and coefficient identification while revealing that observational noise exerts a more pronounced influence on accuracy compared to boundary perturbations. Our research offers new insights into simulating dynamics and discovering parameters of nonlinear chiral systems with deep learning. Full article

We provide an approach to detect a nitrogen-vacancy (NV) center, which might be a defect in a diamond nanomembrane, using a dual-coupling optomechanical system. The NV center modifies the energy-level structure of a dual-coupling optomechanical system through dressed states arising from its interaction with the mechanical membrane. Thus, we study the photon blockade in the cavity of a dual-coupling optomechanical system in which an NV center is embedded in a single-crystal diamond nanomembrane. The NV center significantly influences the statistical properties of the cavity field. We systematically investigate how three key NV center parameters affect photon blockade: (i) its coupling strength to the mechanical membrane, (ii) transition frequency, and (iii) decay rate. We find that the NV center can shift, give rise to a new dip, and even suppress the original dip in a bare quadratic optomechanical system. In addition, we can amplify the effect of the NV center on photon statistics by adding a gravitational potential when the NV center has little effect on photon blockade. Therefore, our study provides a method to detect diamond nanomembrane defects in a dual-coupling optomechanical system. Full article

This paper proposes a Distributed Adaptive Regularization Algorithm (DARN) for solving composite non-convex and non-smooth optimization problems in multi-agent systems. The algorithm employs a three-phase iterative framework to achieve efficient collaborative optimization: (1) a local regularized optimization step, which utilizes proximal mappings to enforce strong convexity of weakly convex objectives and ensure subproblem well-posedness; (2) a consensus update based on doubly stochastic matrices, guaranteeing asymptotic convergence of agent states to a global consensus point; and (3) an innovative adaptive regularization mechanism that dynamically adjusts regularization strength using local function value variations to balance stability and convergence speed. Theoretical analysis demonstrates that the algorithm maintains strict monotonic descent under non-convex and non-smooth conditions by constructing a mixed time-scale Lyapunov function, achieving a sublinear convergence rate. Notably, we prove that the projection-based update rule for regularization parameters preserves lower-bound constraints, while spectral decay properties of consensus errors and perturbations from local updates are globally governed by the Lyapunov function. Numerical experiments validate the algorithm’s superiority in sparse principal component analysis and robust matrix completion tasks, showing a 6.6% improvement in convergence speed and a 51.7% reduction in consensus error compared to fixed-regularization methods. This work provides theoretical guarantees and an efficient framework for distributed non-convex optimization in heterogeneous networks. Full article

Series of pyrene-labeled diols (Py₂-DOs) and polyols (Py-POs) were synthesized by coupling a number (n_PyBA) of 1-pyrenebutyric acids to diols and polyols to yield series of end-labeled linear (n_PyBA = 2) and branched (n_PyBA > 2) oligomers, respectively. Pyrene excimer formation (PEF) between an excited and a ground-state pyrene was studied for the Py₂-DO and Py-PO samples by analyzing their fluorescence spectra and decays in tetrahydrofuran, dioxane, N,N-dimethylformamide, and dimethyl sulfoxide. Global model-free analysis (MFA) of the pyrene monomer and excimer fluorescence decays yielded the average rate constant (<k>) for PEF. After the calculation of the local pyrene concentration ([Py]_loc) for the Py₂-DO and Py-PO samples, the <k>-vs.-[Py]_loc plots were linear in each solvent, with larger and smaller slopes for the Py₂-DO and Py-PO samples, respectively, resulting in a clear kink in the middle of the plot. The difference in slope was attributed to a bias for PEF between pyrenes close to one another on the densely branched Py-PO constructs resulting in lower apparent [Py]_loc and <k> values. This study illustrated the ability of PEF to probe how steric hindrance along a main chain affects the dynamic encounters between substituents in multifunctional oligomers such as diols and polyols. Full article

Object detection technology enables the automatic identification of photovoltaic (PV) panel locations and conditions, significantly enhancing operational efficiency for maintenance teams while reducing the time and cost associated with manual inspections. Challenges arise due to the low resolution of remote sensing images combined with small-sized targets—PV panels intertwined with complex urban or natural backgrounds. To address this, a parallel architecture model based on YOLOv5 was designed, substituting traditional residual connections with parallel convolution structures to enhance feature extraction capabilities and information transmission efficiency. Drawing inspiration from the bottleneck design concept, a primary feature extraction module framework was constructed to optimize the model’s deep learning capacity. The improved model achieved a 4.3% increase in mAP, a 0.07 rise in F1 score, a 6.55% enhancement in recall rate, and a 6.2% improvement in precision. Additionally, the study validated the model’s performance and examined the impact of different loss functions on it, explored learning rate adjustment strategies under various scenarios, and analyzed how individual factors affect learning rate decay during its initial stages. This research notably optimizes detection accuracy and efficiency, holding promise for application in large-scale intelligent PV power station maintenance systems and providing reliable technical support for clean energy infrastructure management. Full article

With the development and application of electric vehicles powered by lithium-ion batteries (LIBs) at high altitude, the lack of research on the aging laws and mechanisms of LIBs under a low-pressure aviation environment has become an important obstacle to their safe application. Herein, the influences and mechanisms of high-altitude and low-pressure environment (50 kPa) on the cycling performance of commercial pouch LIBs were systematically studied. The results showed that low air pressure caused a sharp decrease in battery capacity to 46.6% after 200 cycles, with a significant increase in charge transfer impedance by 70%, and the contribution rate of active lithium loss reached 74%. Low air pressure led to irreversible deformation of the battery, resulting in the expansion of the gap between the electrodes, poor electrolyte infiltration, and reduction of the effective lithium insertion area, which in turn induced multiple synergistic accelerated decay mechanisms, including obstructed lithium-ion transmission, reduced interfacial reaction efficiency, increased active lithium consumption, changes in heat generation structure, and a significant increase in heat generation. After applying external force, the deformation of the electrode was effectively suppressed, and the cycle capacity retention rate increased to 87.6%, which significantly alleviated the performance degradation of LIBs in low pressure environment. This work provides a key theoretical basis and engineering solutions for the design of power batteries in high-altitude areas. Full article

The architecture of contemporary museums often emphasizes visual aesthetics, such as large volumes, open-plan layouts, and highly reflective finishes, resulting in acoustic challenges, such as excessive reverberation, poor speech intelligibility, elevated background noise, and reduced privacy. This study quantified the impact of surface—specific absorption treatments on acoustic metrics across eight gallery spaces. Room impulse responses calibrated virtual models, which simulated nine absorption scenarios (low, medium, and high on ceilings, floors, and walls) and evaluated reverberation time (T₂₀), speech transmission index (STI), clarity (C₅₀), distraction distance (r_D), Spatial Decay Rate of Speech (D_2,S), and Speech Level at 4 m (L_p,A,S,4m). The results indicate that going from concrete to a wooden floor yields the most rapid T₂₀ reductions (up to −1.75 s), ceiling treatments deliver the greatest STI and C₅₀ gains (e.g., STI increases of +0.16), and high-absorption walls maximize privacy metrics (D_2,S and L_p,A,S,4m). A linear regression model further predicted the STI from T₂₀, total absorption (Sabins), and room volume, with an 84.9% conditional R², enabling ±0.03 accuracy without specialized testing. These findings provide empirically derived, surface-specific “first-move” guidelines for architects and acousticians, underscoring the necessity of integrating acoustics early in museum design to balance auditory and visual objectives and enhance the visitor experience. Full article

The present study investigated the efficacy of edible coatings formulated with gellan gum and lemon peel extract (LPE) in preserving the postharvest quality of cherry tomatoes (Solanum lycopersicum var. cerasiforme). Selected fruits exhibiting uniform ripeness and free from defects were sanitized and coated with solutions containing different HAG/LAG (high- and low-acyl gellan gum) ratios, incorporating 4.0% (w/v) LPE. Physicochemical and physiological parameters, including soluble solids content, weight loss, pH, titratable acidity, oxygen consumption, carbon dioxide and ethylene production, skin redness (a*/b* ratio), and decay incidence, were systematically assessed under storage conditions of 25 °C and 70% relative humidity. HAG-coated fruits showed the lowest weight loss (1.08%), higher soluble solids (7.11 °Brix), and greater firmness (3.11 N/mm²) compared to uncoated controls. Moreover, they exhibited reduced oxygen consumption (0.06 mg·kg⁻¹·h⁻¹), ethylene production (3.10 mg·kg⁻¹·h⁻¹), and decay rate (2%). Redness was better preserved, and decay rates were substantially (p < 0.05) reduced throughout the storage period. These findings highlight the potential of HAG-based edible coatings enriched with LPE as an innovative postharvest technology to extend shelf life, maintain quality attributes, and reduce postharvest losses in cherry tomatoes. Full article