Search Results (329)

Long-term ecological data are rare but are highly desirable for assessing responses to ongoing environmental change. To assess temporal trends in abundance over time and establish a baseline for future comparison, we monitored a plethodontid salamander community for ten years. From 2014 to 2023, we sampled forest plots at Wooster Memorial Park (OH, USA) using a regular and standardized monitoring scheme. Of nine salamander species detected, four were common enough to permit statistical analysis. Three species (Eurycea bislineata, Plethodon cinereus and P. electromorphus) had no statistically significant abundance trends over time. The slimy salamander (P. glutinosus), however, showed a statistically significant decline in abundance. We also report on ecological differences between P. cinereus and P. electromorphus, which occur in sympatry at this site. Specifically, we document significant microhabitat differences between these species, which are suggestive of competition avoidance. Additional data are presented on color morph frequency, body size, sexual dimorphism, frequency of hybridization, mate choices, and phenology of surface activity. As global environmental change accelerates, such baseline information is essential to track organismal responses. We also provide a brief review of other long-term field studies in plethodontid salamanders. Full article

To address the problems of high unharvested rates and header loss rates in existing plot-breeding wheat harvesters, this study presents the design of a comb-type header for plot wheat harvesters. Based on the loss suppression mechanism during wheat harvesting, the key components of the comb-type header were designed. To address the issue in which some wheat ears escape combing during the harvesting process, a multi-stage comb-tooth structure was developed. For the problem of seed retention on the bottom plate of the screw conveyor, the telescopic tooth at the feeding port of the screw conveyor was replaced with a scraper, and a rubber plate was added. To determine the optimal combing time, wheat plant posture changes under the action of the nose (hereinafter referred to as the nose) were analyzed through theoretical analysis, simulation, and bench testing. It was determined that the optimal combing moment occurs when the plants begin to rebound to the maximum reverse bending. On this basis, a numerical simulation model of the header combing system was constructed using the discrete element method, with the header loss rate as the evaluation index to explore the influence of the nose height, the machine forward speed, and the combing drum rotation speed on the header performance. A regression model of header loss was constructed using the Box–Behnken response surface method, and the optimal working parameters were determined as follows: a nose height of 554 mm, a machine forward speed of 0.65 m/s, a combing drum rotation speed of 667 r/min, and the predicted loss rate of 8.59%. To verify the operational performance of the comb-type header, a field test of the wheat-harvesting prototype was conducted. The results showed that, under the optimal working parameters, the header loss rate was 7.24%, no wheat ears escaped combing, and no seed retention occurred in the header, which meets the requirements for plot wheat-breeding harvesting. This study provides a theoretical basis for the design and development of small-sized combing harvesters. Full article

Current saw- and pin-type lint-cleaning systems used by the ginning industry have challenges retaining lint quality. The objective of the research was to test a novel pneumatic fractionator for the lint cleaning of an Upland cotton variety that was both saw- and roller-ginned. The process variables tested were initial lint moisture content in the range of 5.5–15% w.b., line pressure in the range of 276–552 kPa, and residence time in the range of 15–45 s. Experiments were conducted based on a central composite design. Models based on response surface methodology (RSM) were developed for final lint moisture, total trash extracted during lint cleaning, and High-Volume Instrument (HVI) fiber quality. The RSM models adequately described the pneumatic fractionation process, as indicated by the coefficient of determination, predicted vs. observed plots, and residual values. The results indicated that the interactions among initial lint moisture content, residence time, and line pressure significantly affected lint quality. At the optimized pneumatic fractionator process conditions, the predicted lint quality attributes were better for both roller- and saw-ginned lint compared to lint cleaned with saw- and pin-type lint cleaners. The upper half mean length increased by 1 mm, the uniformity index was higher by 0.5–1 percentage points, the strength was 1–2 g/tex higher, and the short fiber content was reduced by more than one percentage point. Color grades were better for pneumatic fractionated lint compared to saw- and pin-type lint cleaning methods. Lint value was approximately 4 cents/kg higher for both saw- and roller-ginned pneumatic fractionated lint, compared to lint cleaned using saw- and pin-type lint cleaners. The novel pneumatic fractionator, when compared to industry-standard saw- and pin-type lint cleaners, effectively cleaned lint while retaining fiber quality and removing most of the motes and trash. Full article

Plasmonic nanostructures support localized surface plasmon resonances (LSPRs) which exhibit intense light–matter interactions, producing unique optical features such as high near-field enhancements and sharp spectral signatures. Among these, plasmon hybridization (PH) and Fano resonance (FR) are two key phenomena that enable tunable spectral responses, yet their classification is often ambiguous when based only on geometry or extinction spectra. In this study, we systematically investigate four representative nanostructures: a simple nanogap dimer (i-type structure), a dolmen structure, a heptamer nanodisk cluster, and a nanoshell particle. We utilize discrete dipole approximation (DDA) to analyze these structures. By separating scattering and absorption spectra and introducing quantitative spectral metrics together with near-field electric-field vector mapping, we provide a unified procedure to interpret resonance origins beyond intensity-only near-field plots. The results show that PH-like behavior can emerge in a dolmen structure commonly regarded as a Fano resonator, while FR-like characteristics can appear in the i-type structure under specific conditions, underscoring the importance of scattering/absorption decomposition and vector-field symmetry. We further evaluate refractive-index sensitivities and discuss implications for plasmonic sensing design. Full article

Background: Recovery following incomplete spinal cord injury (iSCI) remains challenging, with conventional rehabilitation often emphasizing compensation over functional restoration. As most new spinal cord injury cases preserve some motor or sensory pathways, there is increasing interest in therapies that harness neuroplasticity. Robotic exoskeletons provide a promising means to deliver task-specific, repetitive gait training that may promote adaptive neural reorganization. This feasibility study investigates the feasibility, safety, and short-term effects of exoskeleton-assisted walking in individuals with degenerative iSCI. Methods: Two cooperative male patients (patients A and B) with degenerative iSCI (AIS C, neurological level L1) participated in a four-week intervention consisting of one hour of neuromotor physiotherapy followed by one hour of exoskeleton-assisted gait training, three times per week. Functional performance was assessed using the 10-Meter Walk Test, while gait quality was examined through spatiotemporal gait analysis. Vendor-generated surface electromyography (sEMG) plots were available only for qualitative description. Results: Patient A demonstrated a clinically meaningful increase in walking speed (+0.15 m/s). Spatiotemporal parameters showed mixed and non-uniform changes, including longer cycle, stance, and swing times, which reflect a slower stepping pattern rather than improved efficiency or coordination. Patient B showed a stable walking speed (+0.03 m/s) and persistent gait asymmetries. Qualitative sEMG plots are presented descriptively but cannot support interpretations of muscle recruitment patterns or neuromuscular changes. Conclusions: In this exploratory study, exoskeleton-assisted gait training was feasible and well tolerated when combined with conventional physiotherapy. However, observed changes were heterogeneous and do not allow causal or mechanistic interpretation related to neuromuscular control, muscle recruitment, or device-specific effects. These findings highlight substantial inter-individual variability and underscore the need for larger controlled studies to identify predictors of response and optimize rehabilitation protocols. Full article

This study investigates the thermal transport behavior of a time-dependent viscoelastic nanofluid moving over a widening cylindrical surface. A steady magnetic influence is introduced along the transverse direction due to photonic heating, thermal sources, or absorbers, and modified Fourier conduction. A mixture of $CoF{e}_2{O}_4$ and $F{e}_3{O}_4$ nanoparticles are uniformly distributed in ethylene glycol to form a hybrid nanofluid. Using a suitable similarity transformation, the governing equations were reformulated into a set of nonlinear ordinary differential equations. The collocation method (CM) is employed as a discretization approach, combined with feedforward neural networks (FNNs) to enhance computational accuracy. Unsteady patterns in both fluid motion and heat distribution were identified, with the localized Nusselt coefficient influenced by relevant scaling parameters. Results are illustrated through plots and structured data formats for various nanoparticle geometries, including spherical, brick, and platelet forms. The analysis revealed that spherical nanoparticles enhance heat transfer by up to 18–22% compared with brick and platelet forms under strong unsteadiness and relaxation effects. As temporal fluctuation indicators intensify, the thermal distribution increases; however, increasing the relaxation coefficient in the heat response leads to diminished energy levels. Full article

Citrus orchards are especially vulnerable owing to low inter-row vegetation cover, and frequent tillage. Here, we combine controlled field experiments with proximal remote sensing–derived geomorphometric variables and machine learning (ML) to identify key factors of erosion in a Mediterranean climate citrus plantation located close to Seville and the National Park of Doñana (Southern Spain) on Gleyic Regosols (clayic, arenic). We conducted rainfall simulations with 30 s sampling, measured infiltration (mini-disc infiltrometer), saturated hydraulic conductivity (Kfs; Guelph permeameter), compaction (penetrologger), and soil respiration (gas analyzer) at multiple points, and derived high resolution morphometric indices from proximal sensing (UAV-LiDAR). Linear models and Random Forests were trained to explain three responses: soil loss, sediment concentration (SC), and runoff. Results show that soil loss is most strongly associated with maximum compaction and Kfs (multiple regression: R² = 0.68; adjusted R² = 0.52; p = 0.063), while SC increases with surface compaction and exhibits weak relationships with topographic metrics. Runoff decreases with average infiltration, which is related to compaction (β = −4.83 ± 2.38; R² = 0.34; p = 0.077). Diagnostic checks indicate centered residuals with mild heteroscedasticity and a few high leverage observations. Random Forests captured part of the variance for soil loss (≈29%) but performed poorly for runoff, consistent with limited sample size and modest nonlinear signal. Morphometric analysis revealed gentle relief but pronounced convergent–divergent patterns that modulate hydrological connectivity. There were strong differences in the experiments conducted close to the trees and in the tractor trails. We conclude that compaction and near surface hydraulic properties are the most influential and measurable controls of erosion at plot scale and the UAV-LiDAR could not give us extra-insights. We highlight that integrating standardized field protocols with proximal morphometrics and ML can be the best method to prioritize a small set of explanatory variables, helping to reduce experimental effort while maintaining explanatory power. Full article

Marine risers, critical structures connecting underwater production systems and surface floating platforms, stand freely in water and endure extremely complex marine environmental loads. To meet the multi-parameter observation demand for their overall state, a fiber-optic sensing-based marine riser buoy observation system was developed. Unlike traditional point-type and offline monitoring systems, it integrates marine buoys with sensing submarine cables to achieve long-term real-time online monitoring of risers’ overall state via fiber-optic sensing technology. Comprising two main modules (buoy monitoring module and fiber-optic sensing module), the buoy’s stability was verified through theoretical derivation, simulation, and stability curve plotting. Frequency domain analysis of buoy loads and motion responses, along with calculation of motion response amplitude operators (RAOs) at various incident angles, showed the system avoids wave periods in the South China Sea (no resonance), ensuring structural safety for offshore operations. A 7-day marine test of the prototype was conducted in Yazhou Bay, Hainan Province, to monitor real-time temperature and strain data of the riser in the test sea area. The sensing submarine cable accurately responded to temperature changes at different depths with high stability and precision; using the Frenet-based 3D curve reconstruction algorithm, pipeline shape was inverted from the monitored strain data, enabling real-time pipeline monitoring. During the test, the buoy and fiber-optic sensing module operated stably. This marine test confirms the buoy observation system’s reasonable design parameters and feasible scheme, applicable to temperature and deformation monitoring of marine risers. Full article

This study investigates the prediction of immediate settlement (Uz) in soft clay improved with Deep Soil Mixing (DSM) columns under heavy aircraft loading. Two key design parameters were considered: column spacing (2.25 m to 3.75 m) and column length (6 m to 20 m), with both rectangular and triangular arrangements analyzed. The datasets obtained from numerical simulations were modeled using Response Surface Methodology (RSM) and Artificial Neural Networks (ANN), with model calibration and validation performed through k-fold cross-validation. The statistical analysis revealed that both approaches achieved excellent predictive capability, with R² values exceeding 0.999. For the rectangular arrangement, RSM yielded slightly lower errors (RMSE = 0.0636 cm, MAE = 0.0553 cm) compared to ANN (RMSE = 0.0828 cm, MAE = 0.0682 cm), suggesting that a second-order polynomial approximation can effectively describe the settlement response in this configuration. Conversely, for the triangular arrangement, ANN clearly outperformed RSM, reducing RMSE from 0.0725 cm to 0.0265 cm and MAE from 0.0615 cm to 0.0111 cm, thereby capturing the nonlinear stress redistribution associated with isotropic column layouts more effectively. Observed–predicted plots confirmed the high predictive accuracy of both methods, with ANN showing superior generalization in triangular grids. Overall, the findings highlight that RSM remains a robust and computationally efficient tool for rectangular layouts with relatively linear responses. In contrast, ANN provides enhanced accuracy for triangular configurations where nonlinear interactions dominate, making it particularly suitable for DSM design optimization in airport pavement foundations. Full article

Medicinal plants play an essential role in the food, pharmaceutical, and cosmetic industries due to their ability to prevent and treat diseases. In this study, a three-factor, three-level Box–Behnken experimental design (BBD) with response surface methodology (RSM) was used to maximize the conditions of ultrasound-assisted extraction (UAE) of bioactive compounds from matico and chacruna leaves in terms of total extraction yield (TEY), total phenolic content (TPC) and antioxidant activity (AA) using ABTS and DPPH assays. The effect of methanol concentration (X1: 25%, 50%, and 75%), time (X2: 3, 6, and 9 min), and power (X3: 90, 270, and 450 W) was evaluated as independent variables. The experimental results were fitted to second-order polynomial models, and multiple regression analysis and analysis of variance were used to determine the suitability of the models, using which 3D response surface plots were generated. Considering the multivariable optimization, the best extraction conditions were 73.68% v/v methanol, 9 min, 269.32 W for matico, and 64.84% v/v methanol, 3 min, 344.44 W for chacruna. Under these conditions, the maximum value of 18.33 and 20.83% for TEY, 7.16 and 40.86 mg GAE/g dm for TPC, 56.88 and 526.38 µmol TE/g dm for DPPH were predicted for matico and chacruna, respectively. Practical Applications: This research focused on the modeling by response surface methodology (RSM) of Ultrasound-Assisted Extraction of bioactive compounds from matico and chacruna, Peruvian plants used in traditional medicine. The methodologies used allow the maximization of bioactive extraction, which presented a high recovery of phenolics with high antioxidant activity. These results highlight the use of Amazon plants in traditional medicine and their possible use in other industries such as cosmetic or food safety. Full article

This article investigates the impact of Arrhenius energy and the radius of a nanoparticle subject to an irregular heat source on tangent-hyperbolic nanofluid flow over a stretching sheet with nonlinear radiation. The convective boundary effect, higher-order slip, and micropolarity are all included for a water-based $Cu$ nanofluid. The present study investigates the significance of a nanoparticle’s radius under inclined MHD conditions. The thermally convective flow of the nanofluid is optimized for the heat-transfer rate using the response surface technique. The modeled governing equations are converted into a system of first-order ODEs using the proper similarity transformations, and the BVP5C algorithm—a finite-difference-based solver—is then used to solve these ODEs numerically. Microrotation, thermal boundary-layer thickness, and the skin-friction coefficient all decrease as the nanoparticle radius increases. The thermal layer thickens as the Biot number increases. As the higher-order slip parameter coefficient increases, the results indicate that the skin friction and local Nusselt number fall. Using tables, figures, contour plots, and surface plots, the effects of several influencing factors on the rates of heat and mass transfer, as well as on the skin-friction factor, are demonstrated. The study uses “Response Surface Methodology” (RSM) in conjunction with “Analysis of Variance” (ANOVA) to optimize the most important factors, which are probably the magnetic parameter and the nanoparticle radius that control the flow and heat-transfer properties. Additionally, with a Nusselt number $R^2$ value of $99.96$, indicating an excellent fit, the suggested model exhibits amazing precision. The reliability and efficiency of the estimated model are assessed using the residual versus fitted plot. Full article

Anaerobic co-digestion of agro-industrial and municipal biowastes can enhance methane production, but the optimal mixture depends on nonlinear interactions among substrates. This study evaluated swine wastewater (SW), cheese whey (CW), and the organic fraction of municipal solid waste (OFMSW) under mesophilic batch conditions to quantify composition–response relationships and identify a robust operating window. A restricted simplex-centroid mixture design was tested; linear, quadratic, and special cubic models were fitted and evaluated using ANOVA, diagnostic plots, and optimization with desirability mapping. Cumulative methane yield (CMY) ranged between 251 and 295 NmL CH₄ g VS⁻¹ in the mixtures, outperforming SW as single component. All mixtures maintained neutral pH and moderate alkalinity ratios. The special cubic model provided the best performance (high R² and R²pred) and revealed significant ternary interaction. The optimization indicated a composition near 63% SW, 10% CW, and 27% OFMSW with a predicted CMY of 300 NmL CH₄ g VS⁻¹; a high-performance band (desirability 0.90–1.00; corresponding to CMY ≥ 294.8) defined a robust window of ~60–66% SW, 6–20% CW, and 20–31% OFMSW. Overall, balanced ternary co-digestion showed synergistic effects beyond additive expectations, and the response surface model based on mixture design proved effective in capturing interactions and providing flexible guidance for practical implementation. Full article

The present paper aims to develop a systematic, prescriptive, and exclusively statistical problem-solving methodology that integrates scientific experimental design methods with the Six Sigma philosophy. This methodology was used for the study and continuous improvement of a direct dyeing process for textile materials. In the first stages of the methodology, the process was systematically analyzed; color difference was identified, using rank correlation as the main quality requirement of the customer; and the influence of the electrolyte concentration in the dye bath on this quality characteristic was tested, using analysis of variance. In the subsequent stages, a full factorial experiment was carried out to obtain a mathematical model describing the action of the main selected influence factors on the color difference; response surfaces and constant level curves were plotted to find the optimal settings of these influence factors. It was concluded that cotton fabric provides a more uniform chromatic reproduction, i.e., a lower color difference, compared to linen, and the electrolyte concentration of 20 g/L yielded the most stable chromatic performance for both fiber types. Full article

The flow of a two-dimensional incompressible hybrid nanofluid over a stretching cylinder containing microorganisms with parallel effect of inclined magnetohydrodynamic was examined in the current study in relation to chemical reactions, heat source effect, nonlinear heat radiation, and multiple convective boundaries. The main objective of this research is the optimization of heat transfer with inclined MHD and variation in different physical parameters. The governing partial differential equations are transformed into a set of ordinary differential equations by applying the appropriate similarity transformations. The Runge–Kutta method is recognized for using shooting as a technique. Surface plots, graphs, and tables have been used to illustrate how various parameters affect the local Nusselt number, mass transfer, and heat transmission. It is demonstrated that when the chemical reaction parameter rises, the concentration and motile concentration profiles drop. The least responsive is the rate of heat transfer to changes in the inclined magnetic field and most associated with changes in the Biot number and radiation parameter shown in contour plot. The streamline graph illustrates the way fluid flow is affected simultaneously by the magnetic parameter M and an angled magnetic field. Local Nusselt number and local skin friction are improved by the curvature parameter and mixed convection parameter. The contours highlight the intricate interactions between restricted magnetic field, significant radiation, and substantial convective condition factors by displaying the best heat transfer. The three-dimensional surface, scattered graph, pie chart, and residual plotting demonstrate the statistical analysis of the heat transfer. The results support their use in sophisticated energy, healthcare, and industrial systems and enhance our theoretical knowledge of hybrid nanofluid dynamics. Full article

To accurately assess the seismic risk of bridges, this study systematically conducted probabilistic seismic hazard–fragility–risk assessments using a reinforced concrete continuous girder bridge as a case study. First, the CPSHA method from China’s fifth-generation seismic zoning framework was employed to calculate the Peak Ground Acceleration (PGA) with 2%, 10%, and 63% exceedance probabilities over 50 years as 171.16 gal, 98.10 gal, and 28.61 gal, respectively, classifying the site as being with 0.10 g zone (basic intensity VII). Second, by innovatively integrating the Response Surface Method with Monte Carlo simulation, the study efficiently quantified the coupled effects of structural parameter and ground motion uncertainties, a finite element model was established based on OpenSees, and the seismic fragility curves were plotted. Finally, the risk probability of seismic damage was calculated based on the seismic hazard curve method. The results demonstrate that the study area encompasses 46 potential seismic sources according to China’s fifth-generation zoning. The seismic fragility curves clearly show that side piers and their bearings are generally more susceptible to damage than middle piers and their bearings. Over 50 years, the pier risk probabilities for the intact, slight, moderate, severe damage, and collapse are 68.90%, 6.22%, 15.75%, 7.86%, and 1.27%, while the corresponding probabilities of bearing are 3.54%, 44.11%, 25.64%, 7.74%, and 18.97%, indicating significantly higher bearing risks at the moderate damage and collapse levels. The method proposed in this study is applicable to various types of bridges and has high promotion and application value. Full article