Search Results (7,149)

Understanding the intricate relationship between sensory perception and physicochemical properties of cacao-based products is crucial for advancing quality control and driving product innovation. However, effectively integrating these heterogeneous data sources poses a significant challenge, particularly when sensory evaluations are derived from low-quality, subjective, and often inconsistent annotations provided by multiple experts. We propose a comprehensive framework that leverages a correlated chained Gaussian processes model for learning from crowds, termed MAR-CCGP, specifically designed for a customized Casa Luker database that integrates sensory and physicochemical data on cacao-based products. By formulating sensory evaluations as regression tasks, our approach enables the estimation of continuous perceptual scores from physicochemical inputs, while concurrently inferring the latent, input-dependent reliability of each annotator. To address the inherent noise, subjectivity, and non-stationarity in expert-generated sensory data, we introduce a three-stage methodology: (i) construction of an integrated database that unifies physicochemical parameters with corresponding sensory descriptors; (ii) application of a MAR-CCGP model to infer the underlying ground truth from noisy, crowd-sourced, and non-stationary sensory annotations; and (iii) development of a novel localized expert trustworthiness approach, also based on MAR-CCGP, which dynamically adjusts for variations in annotator consistency across the input space. Our approach provides a robust, interpretable, and scalable solution for learning from heterogeneous and noisy sensory data, establishing a principled foundation for advancing data-driven sensory analysis and product optimization in the food science domain. We validate the effectiveness of our method through a series of experiments on both semi-synthetic data and a novel real-world dataset developed in collaboration with Casa Luker, which integrates sensory evaluations with detailed physicochemical profiles of cacao-based products. Compared to state-of-the-art learning-from-crowds baselines, our framework consistently achieves superior predictive performance and more precise annotator reliability estimation, demonstrating its efficacy in multi-annotator regression settings. Of note, our unique combination of a novel database, robust noisy-data regression, and input-dependent trust scoring sets MAR-CCGP apart from existing approaches. Full article

The use of single-layer aerated concrete walls in residential construction has a tradition of over 60 years. Its main advantage is thermal insulation. It is the most advantageous among construction materials used for the construction of external walls. The possibility of modifying the dimensions of the blocks leads to meeting subsequent restrictive values of the heat transfer coefficient U. The high dimensional accuracy of the blocks allows the use of dry vertical joints and thin joints with a thickness of 1–3 mm, the thermal influence of which is omitted. However, the thermal uniformity of such a wall is strictly dependent on the quality of workmanship. The main objective of the analysis is to assess the impact of moisture on the U_wall of walls as a function of vertical joint spacing and horizontal joint thickness. It should be said that the effect of humidity and manufacturing accuracy on the thermal properties of aerated concrete walls has not been sufficiently studied. Further study of these patterns is necessary. Particular attention should be paid to the thin-bed mortar, which depends on the manufacturing accuracy. The separation of AAC masonry elements that occurs during bricklaying significantly affects the thermal insulation of walls. This issue has not yet been analysed. The scientific objective of this article is to develop a procedure for determining the thermal properties of a small, irregular air space created as a result of the separation of masonry elements and the impact of this separation on the thermal insulation of the wall. Based on the analysis of the thermal conductivity of voids and masonry elements, it was determined that this impact is visible at low AAC densities. A detailed analysis taking into account both these joints and horizontal joints, as well as different moisture levels, made it possible to determine the permissible separation of AAC blocks, at which the high thermal insulation requirements applicable in most European countries are met. The analysis showed that it is possible to meet the thermal protection requirements for 42 cm wide blocks intended for single-layer walls with a maximum vertical contact width of 3 mm and a joint thickness of up to 2 mm. AAC moisture content plays a major role in thermal insulation. Insulation requirements can be met for AAC in an air-dry state, as specified by ISO 10456. Full article

Soil reflects ecosystem processes and is influenced by gradual biospheric changes, which can affect its biotic components. In fairy rings, soil morphology, physicochemical properties, and biota are interconnected within a shared environmental space. In La Bertolina grasslands, while fungal and bacterial genomics have been investigated, the micromorphological soil effects of these rings have not. This study micromorphologically analyzed thin sections of three fairy rings at four zones: the ring center, the zone of peak growth in 2013 (R13), the predicted growth zone for 2019 (R19), and outside the ring. From each zone, two thin soil sections were prepared, totaling 24 samples. Fungal structures were exhaustively described according to morphological criteria following reference by multiple authors. The soil was a calcareous, loamy Regosol, and showed moderately developed crumb or laminar microstructures. Nine types of fungal structures were identified, consistent with genomic findings in the zone. Although fungal abundance did not vary across zones, mesofauna droppings were more frequent in R13 and R19, which was related to higher nutrient or water availability due to the fungal activity. Regarding the groundmass of the topsoil, neither the composition nor the microstructure of the surface horizons varied according to the moment of appearance of the ring at the sampled points. Full article

Vehicular communication is crucial for the future of intelligent transportation systems. However, providing continuous high-data-rate connectivity for vehicles in hard-to-reach areas, such as highways, rural regions, and disaster zones, is challenging, as deploying ground base stations (BSs) is either infeasible or too costly. In this paper, multiple unmanned aerial vehicles (UAVs) using millimeter-wave (mmWave) bands are proposed to deliver high-data-rate and secure communication links to vehicles. This is due to UAVs’ ability to fly, hover, and maneuver, and to mmWave properties of high data rate and security, enabled by beamforming capabilities. In this scenario, the vehicle should autonomously select the optimal UAV to maximize its achievable data rate and ensure long coverage periods so as to reduce the frequency of UAV handovers, while considering the UAVs’ battery lives. However, predicting UAVs’ coverage periods and optimizing mmWave beam directions are challenging, since no prior information is available about UAVs’ positions, speeds, or altitudes. To overcome this, out-of-band communication using orthogonal time-frequency space (OTFS) modulation is employed to enable the vehicle to estimate UAVs’ speeds and positions by assessing channel state information (CSI) in the Delay-Doppler (DD) domain. This information is used to predict maximum coverage periods and optimize mmWave beamforming, allowing for the best UAV selection. Compared to other benchmarks, the proposed scheme shows significant performance in various scenarios. Full article

Bacterial cell morphology might result from natural selection to gain a competitive advantage under environmentally stressful conditions such as nutrient limitation. In nutrient-limited conditions, a higher surface-to-volume ratio is crucial for cell survival because it allows for a more efficient exchange of nutrients and waste products. A bacterial strain YC6860^T isolated from the rhizosphere of rice (Oryza sativa L.) showed pleomorphic behavior with smooth cell morphology and wrinkled surface rods depending upon nutritional conditions. Based on scanning and transmission electron microscopy studies, we hypothesized that the surface-to-volume ratio of cells would increase with decreasing nutrient concentrations and tested this quantitatively. The transition from smooth to wrinkled cell surface morphology could be one of the adaptation strategies by which YC6860^T maximizes its ability to access available nutrients. To characterize the properties of the wrinkled strain, we performed taxonomic and phylogenetic analyses. 16S rRNA gene sequencing results showed that the strain represented a novel, deep-rooting lineage within the order Rhizobiales with the highest similarity of 94.2% to Pseudorhodoplanes sinuspersici RIPI 110^T. Whole-genome sequencing was also performed to characterize its genetic features. The low phylogenetic and genetic similarity is probably related to the wrinkled morphology of the strain. Therefore, we propose that the strain YC6860^T might belong to a new genus and species, named Rugositalea oryzae. In addition, taxonomic analysis showed that YC6860^T is Gram-negative, aerobic, and rod-shaped with regular surface wrinkles under nutrient-limiting conditions, resembling a delicate twist of fusilli, with groove depths of 48.8 ± 3.7 nm and spacing of 122.5 ± 16.9 nm. This unique cell structure with regular rugosity could be the first finding that has not been reported in the existing bacterial morphology. Full article

A pyrochlore-type crystal structure photocatalytic nanomaterial, Ho₂FeSbO₇, was successfully synthesized using a hydrothermal method. Additionally, a fluorite-structured Bi_0.5Yb_0.5O_1.5 was prepared via rare earth Yb doping. Finally, a novel Ho₂FeSbO₇/Bi_0.5Yb_0.5O_1.5 heterojunction photocatalyst (HBHP) was fabricated using a solvothermal method. The crystal structure, surface morphology, and physicochemical properties of the samples were characterized using XRD, a micro-Raman spectrometer, FT-IR, XPS, ultraviolet photoelectron spectroscopy (UPS), TEM, and SEM. The results showed that Ho₂FeSbO₇ possessed a pyrochlore-type cubic crystal structure (space group Fd-3m, No. 227), while Bi_0.5Yb_0.5O_1.5 featured a fluorite-type cubic structure (space group Fm-3m, No. 225). The results of the degradation experiment indicated that when HBHP, Ho₂FeSbO₇, or Bi_0.5Yb_0.5O_1.5 was employed as a photocatalytic nanomaterial, following 140 min of visible light irradiation, the removal efficiency of ciprofloxacin (CIP) reached 99.82%, 86.15%, or 73.86%, respectively. This finding strongly evidenced the remarkable superiority of HBHP in terms of photocatalytic performance. Compared to the individual catalyst Ho₂FeSbO₇, Bi_0.5Yb_0.5O_1.5, or N-doped TiO₂, the removal efficiency of CIP by HBHP was 1.16 times, 1.36 times, or 2.52 times higher than that by Ho₂FeSbO₇, Bi_0.5Yb_0.5O_1.5, or N-doped TiO₂, respectively. The radical trapping experiments indicated that in the CIP degradation process, the hydroxyl radical owned the strongest oxidation ability, followed by the superoxide anion and the photoinduced hole. These studies are of great significance for the degradation of antibiotics and environmental protection. Full article

Soft robots demonstrate significant advantages in applications within complex environments due to their unique material properties and structural designs. However, they also face challenges in fault diagnosis, such as nonlinearity, time variability, and the difficulty of precise modeling. To address these issues, this paper proposes a fault diagnosis method based on multimodal spatiotemporal features and ensemble learning. First, a sliding-window Kalman filter is utilized to eliminate noise interference from multi-source signals, constructing separate temporal and spatial representation spaces. Subsequently, an adaptive weight strategy for feature fusion is applied to train a heterogeneous decision tree model, followed by a dynamic weighted voting mechanism based on confidence levels to obtain diagnostic results. This method optimizes the feature extraction and fusion process in stages, combined with a dynamic ensemble strategy. Experimental results indicate a significant improvement in diagnostic accuracy and model robustness, achieving precise identification of faults in soft robots. Full article

The Unit Inverse Maxwell–Boltzmann (UIMB) distribution is introduced as a novel single-parameter model for data constrained within the unit interval ($0,1$), derived through an exponential transformation of the Inverse Maxwell–Boltzmann distribution. Designed to address the limitations of traditional unit-interval distributions, the UIMB model exhibits flexible density shapes and hazard rate behaviors, including right-skewed, left-skewed, unimodal, and bathtub-shaped patterns, making it suitable for applications in reliability engineering, environmental science, and health studies. This study derives the statistical properties of the UIMB distribution, including moments, quantiles, survival, and hazard functions, as well as stochastic ordering, entropy measures, and the moment-generating function, and evaluates its performance through simulation studies and real-data applications. Various estimation methods, including maximum likelihood, Anderson–Darling, maximum product spacing, least-squares, and Cramér–von Mises, are assessed, with maximum likelihood demonstrating superior accuracy. Simulation studies confirm the model’s robustness under normal and outlier-contaminated scenarios, with MLE showing resilience across varying skewness levels. Applications to manufacturing and environmental datasets reveal the UIMB distribution’s exceptional fit compared to competing models, as evidenced by lower information criteria and goodness-of-fit statistics. The UIMB distribution’s computational efficiency and adaptability position it as a robust tool for modeling complex unit-interval data, with potential for further extensions in diverse domains. Full article

Coal rupture in coal mining is prone to cause rockburst dynamic hazards. To investigate the effect of joint structure characteristics on the mechanical behavior and the fracture mechanism of coal sample. In this study, uniaxial compression numerical simulation experiments were carried out on coal sample with joint spacings (JSs) of 3 mm and 6 mm and joint angles (JAs) of 0°, 30°, 60°, 90°, respectively, by using the discrete element method (DEM) method. The combined effect of JS and JA on the mechanical properties of coal and its damage mechanism is investigated. The results show that: (1) By increasing JA, the uniaxial compressive strength (UCS) of the specimen first decreased and increased, and the UCS was minimized at θ = 60°. The cracks in the coal sample were transformed from “X”-shaped distribution to “V”-shaped distribution and were dominated by shear cracks. (2) The enlargement of JS contributed to increasing the UCS of the coal sample. At the same time, the crack length remarkably expanded, and the crack distribution broadened. (3) A smaller JA favors the development of tensile cracks and the aggregation of tensile chains towards the end of the specimen. The cracking inclination of the coal sample showed an inverse “N”-type movement with the increase in JA. (4) As the increase in JS benefits the forming of tensile cracks, the extension of cracking inclination of coal sample diminishes. The spread range and accumulation level of tensile chain grows. Full article

To address the issues of numerous influencing factors on material quality, difficulty in determining the optimal mix proportion, and the need to clarify the formation mechanism when foam concrete is used as an internal mold for prefabricated components, this study conducted orthogonal tests to investigate the influence laws of fly ash content, foam content, foaming agent dilution ratio, and water–binder ratio on the dry density and compressive strength of foam concrete, and determined the optimal mix proportion via analysis of variance (ANOVA). Additionally, scanning electron microscopy (SEM) tests were performed to analyze the effects of these four factors on the microscopic pore morphology of foam concrete from a microscopic perspective, thereby revealing its formation mechanism, and engineering applications were carried out. The results show that the primary-to-secondary order of factors affecting the dry density and compressive strength of foam concrete is as follows: foam content (B) > water–binder ratio (D) > foaming agent dilution ratio (C) > fly ash content (A). The optimal mix proportion is 5% fly ash content, 18% foam content, a 30-fold foaming agent dilution ratio, and a water–binder ratio of 0.55. Under this mix proportion, the pore size of foam concrete ranges from 200 μm to 500 μm with uniform distribution, and the pore spacing is between 20 μm and 30 μm, with almost no connected pores. When the foam concrete slurry sets and hardens, hydration products such as calcium silicate hydrate (C-S-H) gel, calcium hydroxide, ettringite (AFt), and monosulfate aluminate (AFm) are generated around the bubbles. The mechanical properties of foam concrete are afforded by the combined action of these hydration products and the pore structure. Full article

The tight sandstone gas reservoirs of the Xujiahe Formation are critical targets for tight gas exploration and development in the Sichuan Basin. While Class I reservoirs have been successfully developed using staged volume fracturing technology, efforts are being increasingly directed toward Class II and III matrix-type blocks. These reservoirs are characterized by a low permeability, high geo-stress differentials, strong heterogeneity, and limited fracture development. These properties result in several challenges, including ambiguous gas production sources, low reservoir utilization rates, significant variability in horizontal well performance, and rapid early-stage production decline—all of which hinder the effective development of matrix-type reservoirs. This study examines two representative fractured wells, Xin 8-5H and Xinsheng 204-1H, located in Class II and III blocks of the Xujiahe Formation gas reservoir. To identify gas production sources, we establish full-fracturing-section productivity models. Furthermore, accounting for variations in geological characteristics, we develop distinct productivity models for three key zones, the matrix area, fracture area, and fault area, to evaluate the productivity controls. The findings reveal that well Xin 8-5H primarily produces gas from the matrix and fault zones, whereas well Xinsheng 204-1H derives most of its production from the matrix and natural fractures. In matrix-dominated zones, generating complex fracture networks enhances productivity. An optimal cluster spacing of approximately 14 m ensures broad pressure sweep coverage while maintaining effective inter-cluster fracture connectivity. Additionally, natural fractures in the Xu-2 matrix reservoirs play a vital role in fluid communication. To maximize reservoir contact, well trajectories should be designed such that natural fractures are oriented either parallel or perpendicular to the wellbore, thereby improving lateral and vertical development. Near fault zones, adjusting cluster spacing to 14–25 m—while keeping the distance between faults and fracturing stages below 50 m—effectively connects faults and substantially increases production. This study introduces a systematic methodology for identifying gas sources in matrix reservoirs and optimizes key productivity-influencing parameters. The results provide both theoretical insights and practical strategies for the efficient development of Xu-2 matrix reservoirs. Full article

In many practical applications, data collected over time often exhibit autocorrelation, which, if unaccounted for, can lead to biased or misleading statistical inferences. To address this issue, we propose a varying-coefficient additive model for density-valued responses, incorporating a functional auto-regressive (FAR) error process to capture serial dependence. Our estimation procedure consists of three main steps, utilizing spline-based methods after mapping density functions into a linear space via the log-quantile density transformation. First, we obtain initial estimates of the bivariate varying-coefficient functions using a B-spline series approximation. Second, we estimate the error process from the residuals using spline smoothing techniques. Finally, we refine the estimates of the additive components by adjusting for the estimated error process. We establish theoretical properties of the proposed method, including convergence rates and asymptotic behavior. The effectiveness of our approach is further demonstrated through simulation studies and applications to real-world data. Full article

Urban green spaces (UGSs) are a vital component of urban landscapes nowadays, with an impact on energy distribution in cities and local climate regulation. This study aims to quantify the thermal and optical behavior of various materials in a small-scale Mediterranean UGS and provide insights into the use of green and artificial materials in urban parks. The analysis also includes the changes in the UGS’s optical and thermal properties following its restoration in 2024. The thermal comfort in the UGS is assessed for the 2020–2024 period, along with the reflectivity and surface temperatures of the different materials pre- (in 2022) and post-restoration (in 2024), using in situ measurements. The results show notable seasonal and interannual variability in the thermal comfort of the site. The impact of vegetation on the UGS was critical. The vegetation-covered surfaces exhibited surface temperatures close to ambient air temperature, highlighting their effective thermal regulation. During summer mornings, the average temperatures of the vegetation-covered surfaces were around 30.5 °C, lower compared to artificial or non-green materials, like asphalt, concrete, gravel, and dry bare soil, which were above 42 °C. The vegetation albedo was relatively lower (around 0.19), while artificial covers showed a greater reflectance (up to 0.35), thus boosting the heat retention. These results highlight the essential importance of green infrastructure incorporation to boost the thermal dynamics of urban open spaces and mitigate climate change effects. Full article

The continuous annealing process is widely used in the production of advanced high-strength steels. However, to tightly regulate the mechanical properties of the steel, precise control of processing parameters is needed. Although some techniques are available to monitor the mechanical properties of the steel on entry and exit to the furnace, monitoring the evolving microstructure of the steel through installation of sensors in the annealing line is extremely challenging due to the high temperature, high speed of the steel strip and limited space in the furnace. This study presents the development and validation of a multifrequency electromagnetic sensor system for real-time monitoring of microstructural transformations in steel during thermal cycling, intended for deployment in a continuous annealing line. Experiments were conducted on austenitic stainless steel to study the signal response to an increase in resistivity without a change in magnetic permeability. Pure nickel was tested to investigate the response to a change in magnetic permeability and the ferromagnetic-to-paramagnetic transition at its Curie temperature. A ferritic stainless steel was also tested to assess the performance of the system for high-temperature ferromagnetic materials and a higher-temperature ferromagnetic-to-paramagnetic transition. The tests indicate a strong response to material resistivity and permeability changes, with complementary information from different frequencies. Test results are supplemented by a finite element modelling study into the effect of a change in frequency and permeability on sensor response, with a discussion on the implications of experimental and modelling results for future applications. The results show that the developed system has the potential to characterise thermally induced changes in steels, establishing proof of concept for non-destructive, high-temperature electromagnetic sensing in steel processing and setting the foundation for further industrial deployment in phase and recrystallisation monitoring. Full article

Introduction: Guided bone regeneration (GBR) is a key approach for managing alveolar ridge defects. Although titanium meshes are widely used for non-resorbable space maintenance, their limitations have prompted interest in alternative materials. Polyetheretherketone (PEEK), a high-performance thermoplastic, has emerged as a potential barrier due to its mechanical strength, radiolucency, and compatibility with digital workflows. Objective: To map the current evidence on the use of PEEK barriers in GBR, focusing on biological performance, mechanical properties, and clinical outcomes in animal and human studies. Methods: A scoping review was conducted following PRISMA-ScR guidelines. Eligible studies included in vivo animal models or clinical trials involving PEEK barriers for alveolar bone regeneration. Data on study design, defect type, barrier characteristics, surgical protocol, outcomes, and complications were extracted. Results: Five studies met the inclusion criteria: two animal models and three clinical trials. All reported successful space maintenance and bone gain with PEEK barriers, with outcomes comparable to titanium meshes. Customization through CAD/CAM or 3D printing was common. Complications such as soft tissue dehiscence and exposure occurred but generally did not affect regeneration. Evidence was limited by small sample sizes, short follow-up, and single-center designs. Conclusions: PEEK barriers show promise as customizable alternatives to traditional GBR membranes. However, current evidence is limited and geographically concentrated. Future multicenter studies with long-term follow-up and standardized outcome measures are needed to validate the clinical potential of PEEK in bone regeneration. Full article