Search Results (610)

While real face features are known to influence social evaluations, the social perception of illusory faces remains largely unexplored despite neural similarities to real faces. This study aimed to fill this gap by manipulating the width-to-height ratio, chin shape, and eye–mouth distance of illusory faces and assessing their effects on perceived gender, cuteness, trustworthiness, dominance, attractiveness, and emotion. Key findings include the following: (1) high width-to-height ratios significantly boosted attractiveness for female participants but not for male participants; (2) round chins consistently enhanced perceptions of masculinity, cuteness, attractiveness, and trustworthiness; (3) eye–mouth distance was found to affect emotional perception. This research offers crucial experimental insights into the determinants of social evaluations for illusory faces. Full article

This study explored the effects of adding a newly developed type of polydextrose on the appearance, sensory score, and textural parameters of steamed bread and the microstructure of dough, as well as the pasting, thermal, and thermal mechanical properties of high-gluten wheat flours. The results revealed that, compared with a control sample, 3–10% of polydextrose addition significantly increased the hardness, adhesiveness, gumminess, and chewiness of steamed bread, but other textural parameters like springiness, cohesiveness, and resilience remained basically the same. Further, in contrast to the control sample, 3–10% polydextrose addition significantly reduced the specific volume and width/height ratio of steamed bread but increased the brightness index, yellowish color, and color difference; improved the internal structure; and maintained the other sensory parameters and total score. Polydextrose addition decreased the peak, trough, final, breakdown, and setback viscosity of the pasting of wheat flour suspension solutions but increased the pasting temperature. Polydextrose additions significantly reduced the enthalpy of gelatinization and the aging rate of flour paste but increased the peak temperature of gelatinization. A Mixolab revealed that, with increases in the amount of added polydextrose, the dough’s development time and heating rate increased, but the proteins weakened, and the peak torque of gelatinization, starch breakdown, and starch setback torque all decreased. Polydextrose additions increased the crystalline regions of starch, the interaction between proteins and starch, and the β-sheet percentage of wheat dough without yeast and of steamed bread. The amorphous regions of starch were increased in dough through adding polydextrose, but they were decreased in steamed bread. Further, 3–10%of polydextrose addition decreased the random coils, α-helixes, and β-turns in dough, but the 3–7% polydextrose addition maintained or increased these conformations in steamed bread, while 10% polydextrose decreased them. In unfermented dough, as a hydrogel, the 5–7% polydextrose addition resulted in the formation of a continuous three-dimensional network structure with certain adhesiveness and elasticity, with increases in the porosity and gas-holding capacity of the product. Moreover, the 10% polydextrose addition further increased the viscosity, freshness, and looseness of the dough, with smaller and more numerous holes and indistinct boundaries between starch granules. These results indicate that the 3–10% polydextrose addition increases the chewiness and freshness of steamed bread by improving the gluten network structure. This study will promote the addition of polydextrose in steamed bread to improve shelf-life and dietary fiber contents. Full article

Phalaenopsis is a widely cultivated ornamental plant of considerable economic value worldwide. However, traditional growing medium, sphagnum moss, is limited and non-renewable. It also decomposes slowly and is prone to environmental issues. Therefore, there is an urgent need to identify more environmentally friendly and efficient alternatives. Biochar, a sustainable material with excellent physical and chemical properties, has been recognized as an effective promoter of plant growth. In this study, we investigated the influence of biochar derived from three raw materials (corn straw, bamboo, and walnut) mixed1 with coconut shell at ratios of 1:2, 1:10, and 4:1, on the growth of Phalaenopsis ‘Big Chili’. Over a 150-day controlled experiment, we evaluated multiple growth parameters, including plant height, crown width, total root length, total projected area, total surface area, and root volume. Compared to the traditional growing medium, the optimal biochar-coconut shell mixture (maize straw biochar: coconut shell = 1:2) increased plant height and crown width by 7.55% and 6.68%, respectively. Root metrics improved substantially, with total root length increasing by 10.96%, total projected area by 22.82%, total surface area by 22.14%, and root volume by 38.49%. Root biomass in the optimal treatment group increased by 42.47%, while aboveground and belowground dry weights increased by 6.16% and 77.11%, respectively. These improvements were closely associated with favorable substrate characteristics, including low bulk density, high total and water-holding porosity, moderate aeration, and adequate nutrient availability. These findings demonstrate that substrate characteristics critically influence plant performance and that biochar–coconut shell mixtures, particularly at a 1:2 ratio, represent a viable and sustainable alternative to sphagnum moss for commercial cultivation of Phalaenopsis. Full article

To address the issues of insufficient feature extraction, single-fall judgment method, and poor real-time performance of traditional fall detection algorithms in occluded scenes, a top-down fall detection algorithm based on improved YOLOv8 combined with BAM-HRNet is proposed. First, the Shufflenetv2 network is used to make the backbone of YOLOv8 light weight, and a mixed attention mechanism network is connected stage-wise at the neck to enable the network to better obtain human body position information. Second, the HRNet network integrated with the channel attention mechanism can effectively extract the position information of key points. Then, by analyzing the position information of skeletal key points, the decline speed of the center of mass, the angular velocity between the trunk and the ground, and the human body height-to-width ratio are jointly used as the discriminant basis for identifying fall behaviors. In addition, when a suspected fall is detected, the system automatically activates a voice inquiry mechanism to improve the accuracy of fall judgment. The results show that the accuracy of the object detection module on the COCO and Pascal VOC datasets is 64.1% and 61.7%, respectively. The accuracy of the key point detection module on the COCO and OCHuman datasets reaches 73.49% and 70.11%, respectively. On the fall detection datasets, the accuracy of the proposed algorithm exceeds 95% and the frame rate reaches 18.1 fps. Compared with traditional algorithms, it demonstrates superior ability to distinguish between normal and fall behaviors. Full article

To ensure the green, safe, and efficient extraction of mineral resources and promote sustainability, the stability of mined-out areas has become a critical factor affecting safe production and ecological restoration in underground metal mines. The instability of underground goafs poses a significant threat to mine safety, especially when irregular excavation patterns interact with high ground stress, exacerbating instability risks. Most existing studies lack a systematic and multidisciplinary integrated framework for comprehensive evaluation and management. This paper proposes a trinity research system of “assessment–optimization–governance”, integrating theoretical analysis, three-dimensional fluid–solid coupling numerical simulation, and a filling sequence optimization method based on genetic algorithms. An analysis of data measured from 243 pillars and 49 goafs indicates that approximately 20–30% of the pillars have a factor of safety (FoS) below 1.0, signaling immediate instability risks; additionally, 58% do not meet the threshold for long-term stability (FoS ≥ 1.5). Statistical and spatial analyses highlight that pillar width-to-height ratio (W/H) and cross-sectional area significantly influence stability; when W/H exceeds 1.5, FoS typically surpasses 2.0. Numerical simulations reveal pore water pressures of 1.4–1.8 MPa in deeper goafs, substantially reducing effective stress and accelerating plastic zone expansion. Stability classification categorizes the 49 goafs into 7 “poor”, 37 “moderate”, and 5 “good” zones. A genetic algorithm-optimized filling sequence prioritizes high-risk area remediation, reducing maximum principal stress by 60.96% and pore pressure by 28.6%. Cemented waste rock filling applied in high-risk areas, complemented by general waste rock filling in moderate-risk areas, significantly enhances overall stability. This integrated method provides a scientific foundation for stability assessment and dynamic remediation planning under complex hydrogeological conditions, offering a risk-informed and scenario-specific application of existing tools that improves engineering applicability. Full article

H-section steel members, as a commonly used load-bearing receiving member in building structures, may be subjected to the impact of accidental loads during their service life, and therefore, the impact loads need to be considered when carrying out the design. In this paper, based on experimental testing, the particle swarm optimization algorithm (PSO) is used to optimize the hyperparameters of the multilayer perceptron (MLP), and a combined prediction model PSO-MLP for H-section steel members subjected to lateral impact loads is proposed to predict the damage of the H-section steel members after impact. The results show that the prediction model based on PSO-MLP can predict the damage of the H-beam columns more accurately, and compared to the random forest model (RF) and the support vector machine (SVM), the PSO-MLP model has better prediction accuracy and robustness. In addition, the effects of different features on the impact performance of the members were analyzed, in which the weakest impact location is 0.57 L away from the fixed end and the effects of axial compression ratio, flange, and web thickness were similar to the results of previous studies; the impact angle showed a strong nonlinear relationship with the critical impact velocity, which the weakest impact angle is around 50° from the strong axle; and the height and width of the cross-section showed a linear enhancement of the impact performance. Full article

Fracture energy plays a pivotal role in ensuring the safe design of concrete structures. Currently, experimental testing remains the predominant methodology for exploring fracture energy in concrete. Nevertheless, this approach is hindered by protracted sample production cycles and test loading conditions that contribute to elevated expenses. Moreover, owing to the complex nonlinear behavior exhibited by concrete during the fracturing process, existing empirical formulas exhibit restricted precision when forecasting fracture energy. Therefore, in order to swiftly and accurately predict the fracture energy of concrete and investigate the impact of various factors on it, this study employs a deep learning algorithm to establish the correlation between parameters and fracture energy. Additionally, an interpretable deep learning prediction model for fracture energy is proposed, which is then compared with existing empirical formulas. Finally, the SHapley Additive exPlanations (SHAP) interpretability method is utilized to interpret and analyze the prediction results. The SHAP method can identify and visualize the contribution direction (positive/negative) and magnitude of the input features and reveal the relative importance of parameters at both local and global levels simultaneously. This analysis effectively explains the decision-making mechanism of the “black box” model and significantly improves the problem of insufficient interpretability that is common in traditional machine learning methods. The findings demonstrate that over 87% of the prediction results from the deep learning model in this study exhibit a relative error of less than 10% on the test set. The model effectively captures the intricate nonlinear relationship among characteristic parameters, exhibiting superior accuracy and generalization capabilities compared to empirical formulas. The SHAP values of the input parameters are visualized to assess their influence on fracture energy: initially, fracture energy increases and then decreases with increasing compressive strength, age, and coarse aggregate proportion; fracture energy increases with increasing maximum particle size of aggregate until it reaches 20 mm, after which it stabilizes; a high water–binder ratio reduces fracture energy; within the range of 400 mm, fracture energy increases with height, exhibiting a noticeable size effect; fracture energy increases with specimen width, but the size effect diminishes beyond 150 mm width; fracture energy decreases as span–height ratio increases; seam height ratio exhibits an initial increase followed by a decrease in fracture energy, with larger ratios showing a more pronounced size effect; an increase in ligament height enhances fracture energy while maintaining a significant size effect. Full article

As a by-product of phosphate fertilizer production, phosphogypsum (PG) poses pressing environmental challenges that demand urgent resolution. To address the research gap in dynamic impact behavior of PG-modified concrete (PGC), this study developed truss-reinforced PGC slabs (PG volumetric fractions: 0% and 2%) and evaluated their impact resistance through drop-weight tests from a 3.75 m height. A systematic parametric investigation was conducted to quantify the effects of slab thickness (100–120 mm), steel plate reinforcement at the tension zone, PG content, and impact cycles. Experimental results revealed that increasing slab thickness to 120 mm reduced mid-span displacement by 13%, while incorporating steel plate reinforcement provided an additional 5.3% reduction. Notably, PG addition effectively suppressed crack propagation, transitioning failure modes from radial fracture patterns to localized mid-span damage. Finite element modeling ABAQUS (2022) validated experimental observations, demonstrating strong agreement. While optimized PG dosage (2%) exhibited limited influence on impact resistance, it enhanced PG utilization efficiency by 18%. Combined with increased slab thickness (displacement reduction: 13%), this study establishes a design framework balancing environmental sustainability and structural reliability for impact-resistant PGC applications. Within the framework of truss-reinforced concrete slabs with constant PG dosage, this study established a numerical model for geometric parameter modulation of impactors. Through systematic adjustment of the drop hammer’s contact width (a) and vertical geometric height (h), a dimensionless control parameter—aspect ratio c = h/a (0.2 ≤ c ≤ 1.8)—was proposed. Nonlinear dynamic analysis revealed that the peak impact load demonstrates an inverse proportional functional decay relationship with increasing c, yielding an empirical predictive model. These parametrized regularities provide theoretical foundations for contact interface optimization in impact-resistant structural design. Full article

During the intense heatwaves of late summer 2024, Washington, D.C.’s urban landscape revealed the powerful influence of urban morphology on microclimates and air quality. This study investigates the impact of building height-to-width (H/W) ratios on the urban heat island (UHI) effect, using a combination of field measurements and Computational Fluid Dynamics (CFD) simulations to understand the dynamics. Street-level data collected from late August to November 2024 across three sites in Washington, D.C., indicate that high H/W ratios (1.5–2.0) increased temperatures by approximately 2–3 °C and reduced wind speeds to around 0.8 m/s. These conditions led to elevated pollutant concentrations, with ozone (O₃) ranging from 1.8 to 7.3 ppb, nitrogen dioxide (NO₂) from 0.3 to 0.5 ppm, and carbon monoxide (CO) remaining relatively constant at approximately 2.1 ppm. PM_2.5 concentrations fluctuated between 2.8 and 0.4 $\mathsf{\mu }$g/m³. Meanwhile, lower H/W ratios (less than 1.5) demonstrated better air circulation and lower pollution levels. The CFD simulations are in agreement with the experimental data, yielding an RMSE of 0.75 for temperature, demonstrating its utility for forecasting UHI effects under varying urban layouts. These results demonstrate the potential of Computational Fluid Dynamics in not only modeling but also predicting UHI dynamics. Full article

Bacterial leaf streak (BLS) is one of the internationally significant quarantine diseases in rice. Effectively utilizing BLS resistance genes from wild rice (Oryza rufipogon Griff.) to breed new varieties offers a fundamental solution for BLS control. This study focused on the fine mapping of the BLS resistance gene bls2 and the development of closely linked molecular markers for breeding BLS-resistant lines. Using a Guangxi common wild rice accession DY19 (carrying bls2) as the donor parent and the highly BLS-susceptible indica rice variety 9311 as the recipient parent, BLS-resistant rice lines were developed through multiple generations of backcrossing and selfing, incorporating molecular marker-assisted selection (MAS), single nucleotide polymorphism(SNP) chip genotyping, pathogen inoculation assays, and agronomic trait evaluation. The results showed that bls2 was delimited to a 113 kb interval between the molecular markers ID2 and ID5 on chromosome 2, with both markers exhibiting over 98% accuracy in detecting bls2. Four stable new lines carrying the bls2 segment were obtained in the BC₅F₄ generation. These four lines showed highly significant differences in BLS resistance compared with 9311, demonstrating moderate resistance or higher with average lesion lengths ranging from 0.69 to 1.26 cm. Importantly, no significant differences were observed between these resistant lines and 9311 in key agronomic traits, including plant height, number of effective panicles, panicle length, seed setting rate, grain length, grain width, length-to-width ratio, and 1000-grain weight. Collectively, two molecular markers closely linked to bls2 were developed, which can be effectively applied in MAS, and four new lines with significantly enhanced resistance to BLS and excellent agronomic traits were obtained. These findings provide technical support and core germplasm resources for BLS resistance breeding. Full article

The functionality of unmanned aerial vehicles (UAVs) in agricultural applications was improved by optimizing the parameters of the vector bracket in a vertical takeoff and landing UAV to maximize thrust and lift-to-drag ratio. First, the results of computational fluid dynamics simulations were compared with wind tunnel data to ensure an accurate model of the considered UAV, indicating a thrust coefficient error of less than 3% and a UAV lift-to-drag ratio error of less than 8%. Next, this model was applied to simulate the propeller thrust and UAV lift-to-drag ratio for 25 sample points selected using a central composite experimental design by varying the four structural parameters of the vector bracket. A kriging algorithm was subsequently applied to construct response surface models based on the results. Finally, a Multi-Objective Genetic Algorithm was employed to determine the optimal parameter values maximizing the two coefficients. The optimal structural parameters for the UAV vector bracket were determined to comprise a vector bracket height of 51 mm, fixed bracket length of 168 mm, fixed bracket width of 69 mm, and ball socket outer diameter of 31 mm. These values provided a 19% larger propeller thrust coefficient than those of the original UAV. Full article

While building the steel–concrete composite girder bridge by means of the incremental launching method, the steel box is directly in the sunlight, and the temperature impact should not be neglected. However, the existing specifications fail to offer the temperature gradient pattern applicable to the steel box featuring a significant height–width ratio and straight web. This paper, relying on the Fenshui River Bridge situated in the southwest region of China, carried out a temperature test. By analyzing the experimental data, the rules of temperature changes at the measuring points in various positions of the steel box were studied, and the temperature disparities of the steel box across different seasons were contrasted. Through the analysis of the test data, the rule governing temperature distribution across the height dimension of the cross-section and its change with time were studied, and a model designed to represent the temperature gradient within the steel box was put forward. By utilizing the numerical model, the effect of the temperature gradient on the force acting on the structure in the process of incremental launching was analyzed. The findings indicate that the temperature of the top plate of the steel box is the highest from 14:00 to 16:00. There is a lag phenomenon in the temperature rise in the bottom plate. The greatest temperature disparity between the upper and lower plates of the steel box is not always present in the season when the temperature is comparatively high. The curve of temperature gradient change exhibits nonlinear features, and the variation in temperature is considerable within the scope of 1 m. In this article, a double-broken line temperature gradient model is put forward, with the corresponding temperature gradient of 17.8 °C. The temperature gradient obviously affects the structural stress, changing the stress distribution, and it notably impacts the deformation. The deformation generated on the guide beam due to the temperature gradient makes up 39% of the total deformation. The temperature gradient is not a fixed value. When the steel box girder is under the jacking process, especially while the structure remains in its maximum cantilever condition and is about to cross the pier, the time should be avoided when the temperature gradient is at its highest. Full article

Steel-reinforced concrete (SRC) deep beams have been widely used in engineering applications such as high-rise buildings and long-span bridges, with their structural behavior and mechanical properties attracting significant research attention. To investigate the shear cracking behavior of SRC deep beams, seven specimens with a scale of 0.4 times were designed for static loading tests, and the influence of the shear-span-to-depth ratio λ, the width ratio of the steel flange, and the height ratio of the steel web on the width and spacing of the diagonal crack was considered. The cracking behavior of the diagonal cracks in the shear span area were recorded by the digital image correlation (DIC) technique. The results show the following: (1) the use of the DIC technology revealed the entire process of crack occurrence, development, and evolution and obtained the distribution characteristics of crack development; (2) the steel flange width has a slight effect on the spacing and width of the diagonal cracks. The diagonal crack width increased with the improvement of the height of the steel web, but the influence of the steel web on the spacing of diagonal cracks was not significant. When the height ratio increased from 0.3 to 0.45 and 0.6, the maximum oblique crack width increased by 13% and 14.5%. Based on the above experimental results and relevant analysis conclusions, an improved method was proposed to calculate the diagonal crack width of composite deep beams by further considering the influence of the crack angle. Finally, the experimental results verified its high accuracy in a qualitative analysis. The calculation method proposed in this article can be used to predict and estimate the width of diagonal cracks in SRC deep beams. Full article

During the natural growth of trees, a large number of branches are formed, with a negative impact on timber quality. Therefore, pruning is an essential measure in forest cultivation. In this work, the effect of pruning on poplar timber quality was evaluated. This study used an artificial forest of Populus deltoides “Nanlin 3804”, established in 2014, as the research object. Pruning was carried out in March 2018 and March 2020 with a pruning intensity of one-third, and a control group was also set up. In December 2023, the growth of 11-year-old poplars under different treatments was investigated and analyzed, and sample trees were cut down for a wood property analysis. The results showed that pruning did not have a significant effect on the growth of the diameter at breast height, the tree height, or the volume. However, pruning could significantly facilitate the forming of higher-quality timber with smaller knots. Compared to unpruned wood, the ring width decreased 1–2 years after pruning, while it turned out to be greater than that of the control 3 years after pruning. Moreover, pruning can reduce the degree of trunk tapering. The fiber aspect ratio two years after pruning was greater than that of the control. The distribution frequency of fiber lengths of between 1500 μm and 1900 μm and that of fiber widths of between 32 μm and 38 μm were higher than that of the control. However, pruning had little effect on their density and oven-dried shrinkage. In addition, compared to the control, the bending strength and the modulus of elasticity increased by approximately 11%–14%, the impact toughness decreased by approximately 5%, and the compressive strength increased by approximately 6%. Pruning proved to be a successful method to improve the timber quality. Full article

Lilium holds significant horticultural and ecological importance. Understanding the morpho-anatomical diversity of the stems can provide insights into taxonomy and breeding strategies. This study comprehensively examined the stem morpho-anatomy of 71 Lilium taxa to elucidate taxonomic and structural differences. For the first time, four distinct jigsaw-puzzle-shaped shapes of epidermal cells (Ep) in monocot stems, novel I-shaped and Co-xylem (O-, X-, W-, Q-shaped) vascular bundles (Vb) in Lilium stems, and quantitative characteristics (Vb density, xylem/phloem area ratio, etc.) were systematically discovered and analyzed. Asiatic (A) and Longiflorum × A (LA) hybrids displayed epidermal appendages, while Oritenal × Trumpet (OT) hybrids featured thicker sclerenchymatous rings (Sr). Collateral Vb in hybrids visually displayed bicollateral with degraded bundle sheaths (Bs), contrasting with intact circular Bs in wild species. Ward.D clustering categorized Lilium taxa into group A (Oritenal and OT hybrids) and B (A, LA, Trumpet, Longiflorum × Oriental hybrids and wild species), with Mantel’s test identified height, Ep shape, Ep length/width ratio, cortex/Sr thickness ratio and Bs integrity as key discriminators. Bending stems exhibited a higher Vb area. These findings establish a comprehensive pheno-anatomical framework for Lilium, which can guide future breeding programs and ecological studies. Full article