Search Results (2,969)

The aim of this study is to evaluate the effects of different types of sourdough (I to IV), developed with a specific starter culture (including Lactiplantibacillus plantarum, Levilactobacillus brevis, and Candida famata), on bread fermentation performance and shelf-life. Real-time tracking of multiple parameters (pH, dough rising, ethanol release, and total titratable acidity) was monitored by a smart fermentation oven. The impact of the different treatments on the lactic acid, acetic acid, and ethanol content of the breads were quantified by high performance liquid chromatography analysis. In addition, the bio-preservation capacity of the breads contaminated with fungi was analyzed. The results show that liquid sourdough (D3: Type 2) and backslopped sourdough (D4: Type 3) increased significantly (p < 0.05) in dough rise, dough acidification (lower pH, higher titratable acidity), production of organic acids (lactic and acetic), and presented the optimal fermentation quotient. These findings were substantiated by chemometric analysis, which successfully clustered the starters based on performance and revealed a strong positive correlation between acetic acid production and dough-rise, highlighting the superior heterofermentative profile of D3 and D4. These types of sourdough also stood out for their antifungal capacity, preventing the visible growth of Aspergillus niger and Penicillium commune for up to 10 days after inoculation. Full article

Background: Exocrine pancreatic insufficiency (EPI or PEI) may be prevalent in as many as 3 of 10 people with diabetes due to exocrine pancreatic function being reduced as early as the time of diagnosis. EPI can be treated with pancreatic enzyme replacement therapy (PERT), but the symptom burden of EPI remains high and improved screening and diagnosis methods are needed. Methods: An online survey (n = 324) evaluated the gastrointestinal symptom experiences of people with (n = 155) and without (n = 169) EPI using a novel symptom tool, the Exocrine Pancreatic Insufficiency Symptom Score (EPI/PEI-SS). A large sub-group (n = 120) of people with diabetes with EPI (Type 1, n = 14, Type 2, n = 20) or without EPI (Type 1, n = 78; Type 2; n = 6) was characterized and compared to those without diabetes (n = 204) in a sub-analysis of the larger EPI/PEI-SS study. Results: The symptom burden of EPI is similar, irrespective of diabetes. Like those without diabetes, people with type 1 diabetes with EPI had a statistically significant (p < 0.001) higher mean score (range 0–225) on the EPI/PEI-SS (100.86, SD: 48.92) than people with T1D without EPI (31.59, SD: 28.25), distinct from other GI conditions (p < 0.001). Similar patterns occurred in those with T2D. Conclusions: High EPI/PEI-SS scores seem to distinguish between likely EPI and other GI conditions among people with diabetes, and the EPI/PEI-SS should be further studied as a possible screening method for EPI at a population level. It should also be evaluated as a tool to aid individuals with diabetes in tracking changes to EPI symptoms over time based on PERT titration. Full article

UAV platforms equipped with RTK positioning and LiDAR sensors are increasingly used for landslide monitoring, offering frequent, high-resolution surveys with broad spatial coverage. In this study, we applied high-frequency UAV-based monitoring to the active Baldiola earthflow (Northern Apennines, Italy), integrating 10 UAV–LiDAR and photogrammetric surveys, acquired at average intervals of 14 days over a four-month period. UAV-derived orthophotos and DEMs supported displacement analysis through homologous point tracking (HPT), with robotic total station measurements serving as ground-truth data for validation. DEMs were also used for multi-temporal DEM of Difference (DoD) analysis to assess elevation changes and identify depletion and accumulation patterns. Displacement trends derived from HPT showed strong agreement with RTS data in both horizontal (R² = 0.98) and vertical (R² = 0.94) components, with cumulative displacements ranging from 2 m to over 40 m between April and August 2024. DoD analysis further supported the interpretation of slope processes, revealing sector-specific reactivations and material redistribution. UAV-based monitoring provided accurate displacement measurements, operational flexibility, and spatially complete datasets, supporting its use as a reliable and scalable tool for landslide analysis. The results support its potential as a stand-alone solution for both monitoring and emergency response applications. Full article

The escalating environmental noise pollution along urban rail transit corridors, exacerbated by rapid urbanization, necessitates innovative and efficient noise control measures. A comprehensive investigation was conducted that utilized field measurements of train passing-by noise to establish a statistical energy analysis model for evaluating the acoustic performance of both vertical (VB) and fully enclosed (FB) barrier configurations. The study incorporated Maa’s theory of micro-perforated plate (MPP) parameter optimization and developed a neural network surrogate model focused on insertion loss maximization for barrier geometric design. Key findings revealed significant barrier-induced near-track noise amplification, with peak effects observed at the point located 1 m from the barrier and 2 m above the rail. Frequency-dependent analysis demonstrated a characteristic rise-and-fall reflection pattern, showing maximum amplifications of 1.47 dB for VB and 4.13 dB for FB within the 400–2000 Hz range. The implementation of optimized MPPs was found to effectively eliminate the near-field noise amplification effects, achieving sound pressure level reductions of 4–8 dB at acoustically sensitive locations. Furthermore, the high-precision surrogate model (R² = 0.9094, MSE = 0.8711) facilitated optimal geometric design solutions. The synergistic combination of MPP absorption characteristics and geometric optimization resulted in substantially enhanced barrier performance, offering practical solutions for urban rail noise mitigation strategies. Full article

The wave spectrum, as a key statistical feature describing wave energy distribution, is crucial for understanding wave propagation mechanisms and supporting ocean engineering applications. This study, based on ERA5 reanalysis spectrum data, proposes a model combining CNN and xLSTM for rapid gridded wave spectrum prediction over the Bohai and Yellow Seas domain. It uses 2D gridded spectrum data rather than a spectrum at specific points as input and analyzes the impact of various input factors at different time lags on wave development. The results show that incorporating water depth and mean sea level pressure significantly reduces errors. The model performs well across seasons with the seasonal spatial average root mean square error (SARMSE) of spectral energy remaining below 0.040 m²·s and RMSEs for significant wave height (SWH) and mean wave period (MWP) of 0.138 m and 1.331 s, respectively. At individual points, the spectral density bias is near zero, correlation coefficients range from 0.95 to 0.98, and the peak frequency RMSE is between 0.03 and 0.04 Hz. During a typical cold wave event, the model accurately reproduces the energy evolution and peak frequency shift. Buoy observations confirm that the model effectively tracks significant wave height trends under varying conditions. Moreover, applying a frequency-weighted loss function enhances the model’s ability to capture high-frequency spectral components, further improving prediction accuracy. Overall, the proposed method shows strong performance in spectrum prediction and provides a valuable approach for regional wave spectrum modeling. Full article

This paper presents the design, simulation, and experimental validation of a dual-Circularly Polarized (CP) array antenna to be used as single element for a bistatic radar system, aimed at detecting and tracking objects in Low Earth Orbit (LEO). The antenna operates at 412 MHz in reception mode and consists of an array of 19 slotted-patch radiating elements with a cavity-based metallic superstrate, designed to support dual circular polarization. These elements are arranged in a hexagonal configuration, enabling the array structure to achieve a maximum realized gain of 17 dBi and a Side Lobe Level (SLL) below −17 dB while maintaining high polarization purity. Two identical analog feeding networks enable the precise control of phase and amplitude, allowing the independent reception of Right-Hand and Left-Hand Circularly Polarized (RHCP and LHCP) signals. Full-wave simulations and experimental measurements confirm the high performance and robustness of the system, demonstrating its suitability for integration into large-scale Space Situational Awareness (SSA) sensor networks. Full article

Articulated Tugs and Barges (ATBs) are increasingly recognised for their effectiveness in transporting chemicals, petroleum, bulk goods, and containers, primarily due to their exceptional flexibility and fuel efficiency. Recent projections indicate that the ATB market is on track for significant growth, which is expected to lead to an increase in the annual growth rate from 2025 to 2032. This study aims to analyse the current advancements in ATB technology and provide insights into the ATB fleet and the systems that connect tugboats and barges. Furthermore, it highlights the advantages of this transportation system, especially regarding its role in enhancing energy efficiency within the maritime transport sector. Currently, there is limited information available in the public domain about ATBs compared to other commercial vessels. The analysis reveals that much of the required information for modern ATB design is not accessible outside specialised design companies. The study also focuses on conceptual design aspects, which include the main dimensions, articulated connections, propulsion systems, and machinery, concluding with an evaluation of economic viability. Special emphasis is placed on defining the main dimensions, which is a critical part of the complex design process. In this context, the ratios of length to beam (L/B), beam to draft (B/D), beam to depth (B/T), draft to depth (T/D), and power to the number of tugs cubed (Pw/N³) are established as design control parameters in the conceptual design phase. This aspect underscores the novelty of the present study. Additionally, the economic viability is analysed in terms of both CAPEX (capital expenditures) and OPEX (operational expenditures). While CAPEX does not significantly differ between the methods used in different types of commercial ships, OPEX should account for the unique characteristics of ATB vessels. Full article

This paper investigates the problem of tracking targets with unknown but fixed 3D star-convex shapes using point cloud measurements. While existing methods typically model shape parameters as random variables evolving according to predefined prior models, this evolution process is often unknown in practice. We propose a particular approach within the Expectation Conditional Maximization (ECM) framework that circumvents this limitation by treating shape-defining quantities as parameters estimated directly via optimization. The objective is the joint estimation of target kinematics, extent, and orientation in 3D space. Specifically, the 3D shape is modeled using a radial function estimated via double Fourier series (DFS) expansion, and orientation is represented using the compact, singularity-free axis-angle method. The ECM algorithm facilitates this joint estimation: an Unscented Kalman Smoother infers kinematics in the E-step, while the M-step estimates DFS shape parameters and rotation angles by minimizing regularized cost functions, promoting robustness and smoothness. The effectiveness of the proposed algorithm is substantiated through two experimental evaluations. Full article

This paper presents a hybrid indoor localization framework combining time difference of arrival (TDoA) measurements with a swarm intelligence optimization technique. To address the nonlinear optimization challenges in three-dimensional (3D) indoor localization via TDoA measurements, we systematically evaluate the artificial bee colony (ABC) algorithm and chimpanzee optimization algorithm (ChOA). Through comprehensive Monte Carlo simulations in a cubic 3D environment with eight beacons, our comparative analysis reveals that the ChOA achieves superior localization accuracy while maintaining computational efficiency. Building upon the ChOA framework, we introduce a multi-beacon fusion strategy incorporating a local outlier factor-based linear weighting mechanism to enhance robustness against measurement noise and improve localization accuracy. This approach integrates spatial density estimation with geometrically consistent weighting of distributed beacons, effectively filtering measurement outliers through adaptive sensor fusion. The experimental results show that the proposed algorithm exhibits excellent convergence performance under the condition of a low population size. Its anti-interference capability against Gaussian white noise is significantly improved compared with the baseline algorithms, and its anti-interference performance against multipath noise is consistent with that of the baseline algorithms. However, in terms of dealing with UWB device failures, the performance of the algorithm is slightly inferior. Meanwhile, the algorithm has relatively good time-lag performance and target-tracking performance. The study provides theoretical insights and practical guidelines for deploying reliable localization systems in complex indoor environments. Full article

Although PLA is an attractive biodegradable polymer, its degradation under natural conditions is often slow. This study investigates whether incorporating pounamu (New Zealand jade) particles into PLA can enhance its biodegradation rate under composting conditions at room temperature. PLA composites containing 0 to 15 wt% pounamu were fabricated using both compression molding and 3D printing. A simple, reproducible protocol based on residual mass measurement was developed to monitor the biodegradation process over a 12-month period. The results showed that increasing pounamu content consistently accelerated mass loss of the composite in the compost, indicating enhanced biodegradation. The 3D-printed samples degraded more rapidly than compression-molded ones. This was attributed to the layered structure, internal microcavities, and lower crystallinity of the 3D-printed samples, which provided greater surface area and accessibility for microbial activity. These findings highlight the dual role of pounamu as both a crystallization promoter and a facilitator of biodegradation and underscore the importance of the processing method when designing biodegradable polymer composites for real-world applications. Full article

Fresh water is vital for human activities; however, an increase in the contamination of water bodies has been observed, so it is necessary to monitor the degree of contamination and take measures to preserve it. In Altamira, Tamaulipas, the Guayalejo-Tamesí River basin has three estuaries and seven lagoons, including Laguna El Conejo, of which the National Water Commission only monitors one. The objective of this research is to determine water quality on the basis of the parameters COD, BOD₅, T, pH, and sediment characteristics. The open reflux method was used according to NMX-AA-030-SCFI-2012 for COD, BOD Track II, HACH equipment for BOD₅, and the granulometric characterization recommended by the Unified Soil Classification System ASTM D-2487-17. The water was found to be uniformly contaminated throughout its length in the range of 117.3–200 mg/L COD, and BOD₅ ranged from 15.8–112.75 mg/L throughout the study period, with sediments dominated by poorly graded soil and fine clay. Comprehensive management is needed because the BOD₅/COD ratio varies between 0.11and 0.56, indicating that it contains recalcitrant organic matter, which is difficult to biodegrade. Full article

Modern electronic devices such as smartphones, wearable devices, and robots typically integrate three-dimensional sensors to track the device’s movement in the 3D space. However, sensor measurements in three-dimensional vectors are highly sensitive to device orientation since a slight change in the device’s tilt or heading can change the vector values. To avoid complications, applications using these sensors often use only the magnitude of the vector, as in geomagnetic-based indoor positioning, or assume fixed device holding postures such as holding a smartphone in portrait mode only. However, using only the magnitude of the vector loses the directional information, while ad hoc posture assumptions work under controlled laboratory conditions but often fail in real-world scenarios. To resolve these problems, we propose a universal vector calibration algorithm that enables consistent three-dimensional vector measurements for the same physical activity, regardless of device orientation. The algorithm works in two stages. First, it transforms vector values in local coordinates to those in global coordinates by calibrating device tilting using pitch and roll angles computed from the initial vector values. Second, it additionally transforms vector values from the global coordinate to a reference coordinate when the target coordinate is different from the global coordinate by correcting yaw rotation to align with application-specific reference coordinate systems. We evaluated our algorithm on geomagnetic field-based indoor positioning and bidirectional step detection. For indoor positioning, our vector calibration achieved an 83.6% reduction in mismatches between sampled magnetic vectors and magnetic field map vectors and reduced the LSTM-based positioning error from 31.14 m to 0.66 m. For bidirectional step detection, the proposed algorithm with vector calibration improved step detection accuracy from 67.63% to 99.25% and forward/backward classification from 65.54% to 100% across various device orientations. Full article

Optical sensor technologies are reshaping obesity detection by enabling non-invasive, dynamic analysis of biomechanical and morphological biomarkers. This review synthesizes recent advances in three key areas: optical gait analysis, vision-based pose estimation, and depth-sensing voxel modeling. Gait analysis leverages optical sensor arrays and video systems to identify obesity-specific deviations, such as reduced stride length and asymmetric movement patterns. Pose estimation algorithms—including markerless frameworks like OpenPose and MediaPipe—track kinematic patterns indicative of postural imbalance and altered locomotor control. Human voxel modeling reconstructs 3D body composition metrics, such as waist–hip ratio, through infrared-depth sensing, offering precise, contactless anthropometry. Despite their potential, challenges persist in sensor robustness under uncontrolled environments, algorithmic biases in diverse populations, and scalability for widespread deployment in existing health workflows. Emerging solutions such as federated learning and edge computing aim to address these limitations by enabling multimodal data harmonization and portable, real-time analytics. Future priorities involve standardizing validation protocols to ensure reproducibility, optimizing cost-efficacy for scalable deployment, and integrating optical systems with wearable technologies for holistic health monitoring. By shifting obesity diagnostics from static metrics to dynamic, multidimensional profiling, optical sensing paves the way for scalable public health interventions and personalized care strategies. Full article

Objectives: This study aimed to evaluate the ability of three-dimensional (3D) speckle tracking echocardiography (STE) to detect acute coronary occlusions in patients with non-ST-segment elevation acute coronary syndrome (NSTE-ACS) and its potential diagnostic advantage over two-dimensional (2D) STE. Methods: Fifty-six patients with NSTE-ACS (mean age 64 ± 11 years; 80% male) underwent 2D and 3D transthoracic echocardiography prior to coronary angiography. Global longitudinal strain (GLS), global circumferential strain (GCS), and 3D ejection fraction (EF) were analyzed. Acute coronary occlusion was defined as TIMI flow 0–1 in the presumed culprit artery. Results: Acute coronary occlusion was present in 16 patients (29%). Patients with occlusion had significantly more impaired strain compared to those without: 3D GLS (−12.5 ± 2.7% vs. −15.5 ± 2.1%, p < 0.001), 2D GLS (−12.6 ± 2.8% vs. −15.6 ± 2.0%, p < 0.001), 3D GCS (−24.8 ± 4.4% vs. −27.8 ± 4.3%, p = 0.02), and 2D GCS (−18.1 ± 5.5% vs. −22.9 ± 4.7%, p = 0.002). In contrast, 3D EF did not differ significantly between groups (52.5 ± 4.7% vs. 54.7 ± 5.7%, p = 0.16). Receiver operating characteristic analysis showed that 3D and 2D GLS had the highest diagnostic performance (AUCs 0.81 and 0.78), while 3D EF had the lowest (AUC 0.61). Feasibility was lower for 3D STE (86%) than for 2D longitudinal strain (95%, p = 0.03). Conclusions: Both 3D and 2D GLS showed higher diagnostic accuracy than 3D EF in identifying acute coronary occlusion in NSTE-ACS patients. While 3D STE enables simultaneous assessment of multiple parameters, it did not offer incremental diagnostic value over 2D STE and had lower feasibility. Full article

Muscle–joint flexibility is defined as the ability of a muscle to stretch in a controlled manner, allowing a wide range of movement at the joints. While numerous methodologies exist for improving flexibility, few studies have investigated the role of athletes’ perceptual processes and awareness related to their own body and movement control during such training. In this pilot study, we explored how two different training protocols—static and dynamic stretching (control group, CON) and multi-joint resistance training (experimental group, EXP)—influence both flexibility and psychophysical awareness, understood as a multidimensional construct involving perceived flexibility improvements, self-assessed control over exercise execution, and cognitive-emotional responses such as engagement, motivation, and satisfaction during physical effort. The study involved 24 male amateur track-and-field athletes (mean age 23 ± 2.5 years), randomized into two equal groups. Over 12 weeks, both groups trained three times per week. Flexibility was assessed using the Sit and Reach Test at three time points (pre-, mid-, and post-intervention). A 2 × 3 mixed ANOVA revealed a significant group × time interaction (F = 20.17, p < 0.001), with the EXP group showing greater improvements than the CON group. In the EXP group, Sit and Reach scores increased from pre = 28.55 cm (SD = 4.91) to mid = 29.39 cm (SD = 4.67) and post = 29.48 cm (SD = 4.91), with a significant difference between pre and post (p = 0.01; d = 0.35). The CON group showed minimal changes, with scores of pre = 28.66 cm (SD = 4.92), mid = 28.76 cm (SD = 5.03), and post = 28.84 cm (SD = 5.10), and no significant difference between pre and post (p = 0.20; d = 0.04). Psychophysical awareness was assessed using a custom questionnaire structured on a 5-point Likert scale, with items addressing perception of flexibility, motor control, and exercise-related bodily sensations. The questionnaire showed excellent internal consistency (Cronbach’s α = 0.92). Within the EXP group, psychophysical awareness increased significantly (from 3.50 to 4.17; p = 0.01; d = 0.38), while no significant change occurred in the CON group (p = 0.16). Post-hoc power analysis confirmed small to moderate effect sizes within the EXP group, although between-group differences lacked sufficient statistical power. These results suggest that resistance training may improve flexibility and concurrently enhance athletes’ psychophysical self-awareness more effectively than traditional stretching. Such findings offer practical implications for coaches seeking to optimize flexibility training by integrating alternative methods that promote both physical and perceptual adaptations. Full article