Search Results (244)

As calibration errors have a direct impact on epipolar consistency, rectification accuracy, and metric 3D reconstruction performance, stereo camera calibration is a fundamental requirement for high-accuracy 3D modeling and reliable digital twin data acquisition. Because current calibration workflows (based on pairwise calibration methods) lack systematic data-quality checks mechanisms, there is a clear need for more robust data selection strategies. The novelty of the approach consists in the development of a new outlier-aware stereo calibration algorithm (OutAw) that introduces a unified multi-stage approach that integrates hard geometric selection, candidate subset generation, multi-criterion ranking, bootstrap stability analysis, and triangulation assessment into a comprehensive and systematic calibration framework. Unlike conventional approaches, OutAw (through its mechanism of detecting and rejecting inconsistent pairs) redefines the calibration strategy from arbitrary to criterion-based data selection. Also, the proposed algorithm is compared with BSC (a baseline OpenCV all-pairs calibration algorithm) and InterFil (an intermediate filtered variant) using 49 stereo pairs (at 1280 × 720 resolution) captured using a planar checkerboard. OutAw algorithm achieved (using only nine image pairs) superior results (epipolar error 0.5119 px, stereo RMS 0.7666 px) to the BSC ones (epipolar error 1.3687 px, stereo RMS 1.9385 px), representing statistically significant improvements (60.5%, respectively 62.3%). OutAw geometric consistency was validated by triangulation-based metrics (square-length standard deviation 0.1140 mm and square absolute error 0.1097 mm). Contamination analysis revealed that as the outlier rate increases, the calibration process degrades progressively. Also, the results obtained highlight that geometric quality-driven image selection is critical for achieving a reliable stereo calibration for DT applications. Full article

Herein, p-NbSe₂ thin films were deposited onto n-Si substrates to fabricate an n-Si/p-NbSe₂ (SNS) heterojunction for visible light communication (VLC) applications. Structural analysis revealed that the NbSe₂ films possess a trigonal phase and are composed of slightly elongated and irregularly shaped grains with an average size of 0.131 μm. Electrical characterization showed that the SNS heterojunction exhibits pronounced rectifying behavior, with a bias-dependent asymmetry factor reaching 6.6 × ${10}^3$. The photodetection performance of the device was evaluated under illumination from white, blue, red, tungsten, and infrared LEDs. The device exhibited excellent photodetection characteristics across the visible region, achieving a maximum responsivity of 3.79/3.68 AW⁻¹, external quantum efficiency of 1160/809%, noise equivalent power of 4.43 × 10⁻¹⁴ /4.57 × 10⁻¹⁴ WHz^−1/2, and specific detectivity of 3.91 × 10¹²/3.79 × 10¹² Jones under blue/white light illumination, confirming its practical relevance for VLC systems. In addition, frequency-dependent photocurrent measurements under modulated blue and white LED illumination revealed −3 dB bandwidths of approximately 775 Hz and 716 Hz, respectively, supporting the potential of the n-Si/p-NbSe₂ photodiode for low-frequency VLC-related visible-light detection. Compared with previously reported photodiodes used in VLC and IR technologies, the present device demonstrated superior responsivity and EQE%, together with competitive NEP and detectivity. The enhanced performance is attributed to efficient photocarrier generation and collection across the Si/NbSe2 heterojunction. These results confirm that the fabricated SNS photodiode is a promising candidate for high-sensitivity and efficient visible light communication applications. Full article

Many deterministic multi-objective optimization methods generate Pareto outcomes by repeatedly solving scalarized subproblems for different preference or reference vectors. When the number of objectives is $m\ge 3$, the resulting samples lie on an $(m-1)$-dimensional Pareto surface in objective space. For tasks such as visualization, trade-off exploration, interactive decision making, and sensitivity analysis, a finite cloud of non-dominated points may be insufficient; one often needs a continuous surrogate of the Pareto surface together with a quantitative control of its reconstruction error. This paper studies the corresponding outer-loop reconstruction problem: how should new reference vectors be selected so as to reconstruct the Pareto surface to a prescribed uniform accuracy while using as few scalarized solves as possible? We propose Certified Adaptive Triangulation Sampling (CATS), a curvature-aware adaptive triangulation method for reconstructing a Pareto surface from an oracle $u\mapsto z\left(u\right)$, $u\in {\Delta }_d$, where $d=m-1$. CATS builds a simplicial mesh over the reference simplex and refines the cell with the largest local interpolation quantity $\eta \left(\tau \right)=\frac{1}{2}\left({max}_k{M}_{\tau ,k}\right)\mathrm{diam}{\left(\tau \right)}^2$, where $M_{\tau ,k}$ is an upper bound on the Hessian norm of the kth component of the oracle-induced map over $\tau$. This quantity matches the natural error scale of affine interpolation for $C^2$ maps. The rigorous certified interpretation of CATS applies when the preference-to-Pareto map is single-valued, $C^2$, and equipped with reliable local Hessian-norm upper bounds. If such bounds are replaced by numerical curvature estimates, the same rule can still be used as an adaptive refinement indicator, but the resulting stopping test is not a formal certificate unless those estimates are themselves validated. Under the certified assumptions, we prove that the stopping condition ${max}_{\tau }\eta \left(\tau \right)\le \epsilon$ guarantees ${sup}_{u\in {\Delta }_d}{\parallel z\left(u\right)-\widehat{z}\left(u\right)\parallel }_{\infty }\le \epsilon$, and that the oracle complexity of certified simplicial piecewise-affine reconstruction is $\mathsf{\Theta }\left({\epsilon }^{-d/2}\right)$. On the rigorously certified core tests, CATS uses $2.7\times$–$3.8\times$ fewer oracle calls than uniform reference-direction sampling and $1.2\times$–$1.6\times$ fewer than an AWS-inspired patch-area refinement rule. Additional benchmark studies, evaluated with the same interpolation quantity as a practical stopping indicator, show the same qualitative advantage, especially on anisotropic and localized surface geometries. Full article

Air-dried mutton is a traditional, culturally significant meat product, yet its spontaneous fermentation is inherently constrained by unstable microbial communities, leading to batch-to-batch quality inconsistency and potential food safety hazards. Elucidating whether composite starter cultures can modulate the microbiota and enhance product quality is therefore critical for standardized industrial processing. Herein, we investigated the effects of a defined starter culture (composed of Lactiplantibacillus plantarum and Pediococcus pentosaceus in a 2:1 ratio, with a total inoculum of 10⁸ CFU/g) on the quality and flavor of air-dried mutton, comparing inoculated samples (FJ) with naturally fermented controls (ZR). The fermentation was conducted at 30 °C and 95% relative humidity (RH) for 24 h, followed by air-drying at 4 °C for 21 d, with all assays performed in three biological and three technical replicates. Starter inoculation significantly reduced the pH, water activity (Aw), total volatile basic nitrogen (TVB-N), and thiobarbituric acid reactive substances (TBARS) values while improving sensory acceptability (p < 0.05). Amplicon sequencing analysis revealed a lactic acid bacteria (LAB)-dominated microbiota in FJ samples, with elevated abundances of Pediococcus and Lactobacillus and reduced abundance of Pseudomonas. The inoculated group also exhibited altered eicosapentaenoic acid content and a more diverse volatile flavor profile, with eight key aroma compounds positively correlating with LAB abundance. These findings demonstrate that composite starter inoculation improves physicochemical quality, stabilizes the microbial community, and enhances flavor in air-dried mutton. Further mechanistic validation and scale-up trials are required to confirm industrial applicability. Full article

Blue–green spaces serve as the core carriers of urban ecosystems, and their conservation and optimization have emerged as pivotal issues in territorial spatial planning and ecological governance. Taking Guilin, a national innovation demonstration zone for China’s Sustainable Development Agenda, as the study area, a deep learning-based DBDTAF-Net classification model is constructed using 2020 Sentinel-2 remote sensing imagery and AW3D30 Digital Surface Model (DSM) data. The model achieves a mean Intersection-over-Union (mIoU) of 86.05% on the test set and an IoU of 94.67% for rocky desertification areas. Based on the classification results, 21 derived indicators (including landscape patterns of BGSs) and six meteorological and topographic factors, alongside three core ecosystem service indicators—Aboveground Biomass (AGB), Net Primary Productivity (NPP), and soil conservation—are extracted to characterize their spatial patterns. The XGBoost-SHAP framework is employed to quantify the driving effects and threshold responses of BGS patterns on ecosystem services. The results indicate that (1) BGSs in Guilin display a spatial pattern of “green-dominated, blue-supplemented, generally contiguous yet locally fragmented,” and all three ecosystem services exhibit significant spatial clustering. (2) Landscape pattern factors of green spaces constitute the dominant influencing factors, with contribution rates ranging from 22.3% to 28.6%. Specifically, green space_COHESION demonstrates a stable linear positive effect. A green space ratio below 45% suppresses AGB, whereas exceeding 45% shifts to a positive effect and represents an efficient enhancement interval for NPP while exerting a continuously positive influence on soil conservation. A cultivated land proportion below 30% leads to a strongly increasing inhibitory effect on AGB and soil conservation, whereas its inhibition on NPP weakens beyond 20%. A construction land proportion exceeding 10% significantly suppresses NPP, and the inhibitory effect stabilizes above 20%. Green space patch density below 0.8 shows a pronounced negative effect, which diminishes above 0.8. Blue space factors exert relatively weak effects. (3) The ecosystem service supply capacity varies across functional zones in Guilin, with the ecological barrier zone performing the best, the modern agricultural zone performing moderately, and the six central urban districts of the Shanshui Metropolis Area exhibiting the lowest levels. This study provides a technical framework for high-precision extraction of urban BGSs and quantitative analysis of factors influencing ecosystem services, offers decision support for ecological conservation and restoration in Guilin, and furthermore proposes insights for the coordinated development of rational land resource utilization and ecosystem service enhancement in other karst cities. Full article

Driven by climate change and population growth, coastal flood risk is rising, making high-precision Digital Elevation Models (DEMs) essential for inundation simulation and risk assessment. Although global open-source DEMs are increasingly available, their regional applicability and uncertainty still require quantitative evaluation. Taking Lianyungang, a coastal city in eastern China, as the study area, this study used ICESat-2 ATL08 laser altimetry as the reference to assess the vertical accuracy of eight mainstream open-source DEMs: the ASTER GDEM, FABDEM, AW3D30 DEM, SRTM DEM, MERIT DEM, NASA DEM, Copernicus DEM, and TanDEM-X DEM. The effects of slope, aspect, and land cover on DEM errors were analyzed, and the Height Above Nearest Drainage (HAND) model was used to evaluate how DEM vertical accuracy and spatial resolution affect flood inundation simulation. The results show that the FABDEM has the highest accuracy (RMSE = 1.24 m; NMAD = 0.49 m), followed by the Copernicus DEM GLO-30 (RMSE = 1.56 m; NMAD = 0.65 m), whereas the ASTER GDEM performs worst (RMSE = 5.36 m; NMAD = 3.69 m). The SRTM DEM systematically underestimates ICESat-2 elevations, with mean and median errors of −1.85 m and −1.80 m, mainly due to acquisition time differences and land-use changes in Lianyungang. DEM errors generally increase with slope, are higher on west-facing slopes, and are larger over water bodies than over cropland and impervious surfaces. HAND simulations show that DEM-derived inundation differences are greatest under low-threshold conditions. At the 1 m HAND threshold, the MERIT DEM produces the largest inundation area (4370.28 km²), while the ASTER GDEM produces the smallest area (3330.53 km²); these differences decrease as the threshold increases. Overall, the FABDEM provides the most accurate flood inundation representation in Lianyungang, while the Copernicus DEM GLO-30 is a reliable alternative. Full article

This study developed a chicken nugget analogue formulated with hydrated textured soy protein (HTSP), a meat analogue based on extruded Sacha Inchi cake (MASI), and hydrated gluten (HWG). Instrumental texture analysis, cooking loss and yield, water activity (a_w), pH, and color measurements were used to evaluate the effects of these protein sources. An optimal formulation was established using a D-optimal mixture design combined with a desirability function, aiming to maximize the springiness index (0.69) and minimize the hue angle (83.81 °), with a commercial chicken nugget (SF) used as reference. The optimal blend (HTSP 20.75%, MASI 46.25%, and HWG 33%) achieved a desirability value of 0.71 and was experimentally validated within a 95% confidence interval. Physicochemical characterization of the optimal formulation (OF) showed moisture content of 56.04%, protein content of 12.04%, fat content of 4.46%, and carbohydrate content of 25.54%. The OF exhibited low cooking loss (6.82%), high yield (93.18%), and favorable textural properties, including hardness (6.11 N), cohesiveness (0.20), springiness index (0.33), and chewiness index (0.40 N). Color parameters were L* 68.02, a* 1.33, b* 24.35, and a hue angle of 86.87°. Compared with commercial chicken nuggets, the OF showed similar physical and nutritional characteristics but lower fat content. Sensory evaluation using check-all-that-apply (CATA) and hedonic tests (n = 70 panelists) indicated that the commercial nugget (SF) had the highest flavor and overall acceptability but was primarily associated with greasy and salty attributes. The OF nugget was positively perceived for its crispiness and breading adhesion, although a slight bitterness was reported. In contrast, the commercial vegan nugget (FF) showed the lowest acceptability due to its dry texture and low juiciness. Overall, the results highlight the potential of plant-based protein blends for developing meat analogues; however, further optimization of flavor and aroma is required. In addition, compliance with regulatory requirements for labeling, allergen disclosure, and novel-ingredient disclosure remains essential for market entry. Full article

To extend shelf life and enjoy the aroma and bioactive properties of wild nettle all year long, a drying operation is needed. This research aimed to compare conventional drying with modern drying technology using ultrasound to investigate intensification of the process together with the quality of sensitive leafy herbs. The kinetic, energy, and selected quality attributes typical for dry products of plant origin were analyzed: color, water activity, and polyphenol retention. Drying tests on wild nettle were carried out at two temperatures of 50 and 70 °C, with and without airborne ultrasound (100 and 200 W). The results showed that the application of ultrasound contributed to higher drying rates throughout the moisture content range compared to convective drying at the same air temperature. The higher the ultrasound power, the higher the increase in drying rate and shorter drying time, confirming intensification of moisture diffusion due to ultrasound assistance. The higher temperature and ultrasound level strongly influenced the final appearance and antioxidant properties of dry nettle, leading to color change (dE00 = 8.2) and polyphenol degradation (36%). However, all of the analyzed drying variants reduced the risk of microbial development (a_w = 0.444). In conclusion, ultrasound can be effectively applied to intensify the drying of nettle leaves by providing more favorable drying conditions, including a 53% reduction in drying time and a drying rate more than twice as fast as that of convective drying. Full article

This study evaluated the feasibility of developing 3D-printable chontaduro (Bactris gasipaes) gel inks. Freeze-dried chontaduro pulp and encapsulated Lactiplantibacillus plantarum were used. Two formulations were analysed: a control (ChC) and a probiotic ink (ChLp) containing 10% (w/w) microencapsulated cells in a maltodextrin–whey protein carrier. Both were baked at 140 °C under zero humidity and evaluated for water activity, colour, texture, and sensory properties. Rheological analysis showed shear-thinning behaviour for both inks. Notably, ChLp had higher storage (G′) and loss (G″) modulus, which may indicate structural reinforcement by the carrier. Furthermore, FTIR suggested enhanced protein–polysaccharide interactions and ionic cross-linking. Both inks were found to be extrudable; however, ChLp showed a 4.1% reduction in printed height. Baking reduced water activity (aw < 0.88) and caused Maillard browning, which was more pronounced in ChLp. With respect to microbial viability, Ltp. Plantarum viability (~7.1 log CFU/g) was maintained after extrusion but lost after baking. Sensory evaluation indicated formulation-dependent differences in colour (greater yellowness) and texture (reduced adhesiveness, increased hardness) for ChLp. Overall, these findings showed chontaduro gel as a viable matrix for 3D food printing, with the encapsulated carrier altering physicochemical and sensory descriptors. Full article

In this study, we combined lead-free inorganic perovskite, CsSnI₃, with a transition metal chalcogenide, MoS₂, to develop a hybrid architecture for photodetectors utilizing the SCAPS-1D simulation tool. The performance of the photodetector was investigated across various thicknesses, doping concentrations, light intensities, and temperatures. An in-depth analysis of built-in potential, recombination rate, generation rate, quantum efficiency, I-V characteristics, and other performance parameters showed that the ideal thickness, doping density, bulk defect density, and interface defect density for enhanced photodetector performance are 800 nm, 1 × 10¹⁹ cm⁻³, 1 × 10¹⁴ cm⁻³, and 1 × 10¹⁰ cm⁻³, respectively. The photodetector exhibits optimal performance within the wavelength range of 200–500 nm and under illumination levels of 500–700 mW/m², maintaining a consistent responsivity of 0.59 A/W, a detectivity of 4.28 × 10¹³ Jones, a photocurrent of 34.50 mA/cm², and a low dark current of 10⁻⁶ mA/cm², with good thermal stability over a wide range of temperatures. The findings indicate that the CsSnI₃/MoS₂ heterojunction photodetector exhibits superior performance characterized by enhanced sensitivities throughout a broad operational range within the UV–blue visible spectrum and paves the way for the development of cost-effective, high-performance photodetectors in future optoelectronic applications. Full article

Terahertz radiation exhibits significant potential for communications, imaging, and spectroscopy. However, the development of efficient and low-cost THz detectors remains challenging due to limitations such as insufficient sensitivity, slow response speed, and poor room temperature stability. This work presents an innovative quasi-2D perovskite/Weyl semimetal (Co₃Sn₂S₂) heterojunction THz detector that combines complementary material properties via band engineering. The device achieves a remarkable responsivity of 374.15 A/W, a specific detectivity of 6.27 × 10¹¹ cm·Hz^1/2·W⁻¹, and a noise-equivalent power of 0.29 pW·Hz^−1/2 at 0.1 THz. This performance stems from the strong THz absorption of the perovskite layer combined with the high carrier mobility and topological surface states of the Co₃Sn₂S₂, which collectively enable ultrafast carrier extraction and suppressed interfacial recombination. This heterojunction design offers a novel strategy for high-performance terahertz detection and facilitates its integration into next-generation portable, integrated devices. Full article

Bird migration is an awe-inspiring phenomenon that causes massive global shifts in bird distributions twice a year. To understand the evolution of this phenomenon, it is crucial to know the mortality costs of these journeys. Extreme weather-related events can lead to abnormally high mortality rates among migratory birds, while high mercury concentration may reduce the survival of songbirds in the field, especially for the long-distance migrant insectivores. Yet the specific vulnerability factors remain largely unknown. We collected the opportunistic dead Eastern Red-rumped Swallows (Cecropis daurica) in a mass-mortality event caused by a cold wave in autumn migration in Southern China. Mercury concentration in their tail feathers is 0.57 ± 0.37 µg g⁻¹, lower than the established toxicity threshold for birds. The claws’ hydrogen stable isotopic (δD) values ranged from −116 to −78 ‰, with a mean of (−88.00 ± 8.22) ‰. Stable hydrogen isotopes indicated broad origins for the Eastern Red-rumped Swallows, ranging from ~30° N to ~62° N and ~10° E to ~150° E. Considering subspecies ranges, most of the dead swallows likely came from their almost furthest breeding sites. Our results indicated the primary cause of the mass-mortality event was likely fatigue or starvation resulting from long-distance flight during an extreme cold wave. Mercury exposure may not be the main direct cause of death. Full article

(1) Background: Exploring regional foods can help consumers expand their options for consuming diverse food products in various forms. This could enhance human health in local populations. (2) Methods: The present study evaluated the physicochemical composition of quince powder using standard analytical methods. Color parameters were determined using a PCE-CSM colorimeter equipped with a xenon lamp; the antioxidant activity via DPPH, ABTS, FRAP, and CUPRAC methods; the sorption capacity (at 10 °C, 25 °C, 40 °C and a_w from 0.1 to 0.9) through the static gravimetric method; and monolayer moisture content (MMC) with the BET model. The isotherms were fitted via modified Chung–Pfost, Halsey, Henderson and Oswin models. (3) Results: The approximate physico-chemical composition of laboratory-produced quince powder (dried at 45 °C for 10 h) was: proteins—1.27 g, carbohydrates—75.80 g, fats—0.49 g, fibers—21.50 g, ash—2.31 g, and nutritional value—355.65 kcal. The color analysis indicated limited non-enzymatic browning. Antioxidant activity was confirmed by all four methods. The three-parametric Halsey model is recommended to describe the representative S-shaped isotherms from type II. The MMC for the adsorption process ranged from 14.41% d.b. to 7.09% d.b., and for the desorption process, it ranged from 13.11% d.b. to 7.80% d.b.; (4) Conclusions: This study presents a quince powder as a convenient form for both storage and consumption, emphasizing its value as a rich source of bioactive compounds and its suitability for home production and regular inclusion in a healthy daily diet. Full article

Digital elevation models (DEMs) are foundational for critical tasks such as flood inundation simulation, disaster risk assessment, and ecosystem monitoring in coastal zones, yet their vertical accuracy is significantly compromised by complex terrain and surface characteristics. This study quantitatively decomposes the vertical errors of three 30 m global DEMs (COP30, NASADEM, and AW3D30) across the subtropical coastal region of Southeast China using ICESat-2 ATL08 data as a reference. By integrating an eXtreme Gradient Boosting (XGBoost) model with SHapley Additive exPlanations (SHAP), we successfully decoupled systematic biases from random noise. The results show that NASADEM achieved the lowest RMSE (7.775 m), followed by COP30 and AW3D30. While the Terrain Ruggedness Index (TRI) and categorically encoded Land Cover were identified as the universally dominant error drivers across all datasets, explainable analysis revealed distinct secondary mechanisms: X-band COP30 is notably susceptible to canopy height, exhibiting significant positive bias in forests exceeding 15 m; C-band NASADEM shows a systematic bias related to topographic position, typically overestimating ridges and underestimating valleys; and optical AW3D30 is significantly affected by stereo-matching errors. Furthermore, the analysis quantified a systematic error component of ~40%. These findings provide a data-driven basis for DEM selection and highlight that accuracy improvements should prioritize vegetation removal for radar DEMs and enhanced stereo-matching for optical models. Full article

The accuracy of Digital Elevation Models (DEMs) plays a crucial role in determining their reliability for geoscientific and engineering applications. Next-generation distributed interferometric synthetic aperture radar (SAR) constellations, such as the PIESAT-1 wheel constellation with its “one primary, three secondary” setup, provide a novel method for efficiently acquiring high-precision DEMs. However, a comprehensive and systematic performance evaluation of DEMs derived from such an innovative constellation is lacking, particularly in the context of comparative studies under complex terrain conditions. This study uses PIESAT-1 SAR imagery to generate a 10 m resolution DEM through multi-baseline interferometric processing. The ICESat-2 ATL08 dataset serves as the reference baseline, and mainstream products, including ZY-3, GLO-30, TanDEM-X DEM, and AW3D30, are incorporated for a multidimensional vertical accuracy evaluation, considering land cover, slope, aspect, and topographic profiles. The results indicate that, in three representative mountainous regions, the PIESAT-1 DEM achieves optimal overall accuracy (RMSE = 3.25 m). Furthermore, in regions with significant radar geometric distortions, such as south-facing slopes, vegetation-covered areas, and regions with noticeable anthropogenic topographic changes, the PIESAT-1 DEM demonstrates superior stability and information capture capabilities relative to conventional single- or dual-baseline SAR systems. This study validates the technological potential of the PIESAT-1 wheel constellation in enhancing DEM accuracy and terrain adaptability, and provides insights for the scientific selection of high-resolution topographic data and the design of future spaceborne interferometric missions. Full article