Search Results (8,390)

Gait is a sensitive marker of mobility decline and fall risk, motivating unobtrusive sensing methods that can extract spatiotemporal parameters outside specialized gait laboratories. This paper presents a physics-based comparison of two millimeter-wave frequency-modulated continuous-wave (FMCW) radar deployment paradigms using a low-cost, system-on-chip (SoC) 60 GHz Infineon BGT60TR13C radar sensor: (i) a fixed (tripod-mounted) corridor observer and (ii) a shoe-mounted body-centric configuration attached to the medial side of the left shoe. Four healthy adult author-participants performed repeated 30 s corridor trials under five gait styles (regular, slow, fast, simulated festination, and simulated freezing-of-gait), including brief pauses during turns; an empty-corridor recording was acquired to characterize static clutter. Step events were detected using peak-picking on foot-related velocity envelopes with adaptive thresholds, and step count, cadence, step time, and step-time variability were derived. Performance of the fixed and shoe-mounted configurations was quantitatively compared to video ground truth using mean absolute percentage error (MAPE) for step count estimation. Across all gait styles, the shoe-mounted FMCW radar consistently reduced step-count error relative to the fixed corridor-mounted configuration, with the largest gains under irregular patterns (e.g., festination: 37.1% fixed vs. 9.6% shoe-mounted). These findings highlight the advantages of body-centric millimeter-wave radar sensing and support low-cost SoC radar as a pathway toward wearable, privacy-preserving gait monitoring in real-world environments. Full article

Advanced high-temperature fluid reactors (ARs), such as sodium fast reactors (SFRs) and molten salt cooled reactors (MSCRs) utilize high-temperature fluids at ambient pressure. To melt the fluid during reactor startup and prevent fluid freezing during cooldown, the thermal–hydraulic systems of such ARs include heater zones consisting of specific heaters with controllers, temperature sensors, and thermal insulation. The failure of heater zones due to insulation material degradation or improper installation, resulting in parasitic heat losses, can lead to fluid freezing. The detection of faults using a heat-transfer model is difficult because of a lack of knowledge of the experimental details. Data-driven machine learning of heater zone temperature time series offers a viable alternative. In this study, we benchmarked the performance of recurrent neural networks (RNNs) in an analysis of heat-up transient temperature time series of heater zones installed on a liquid sodium vessel. The RNN models include long short-term memory (LSTM) and gated recurrent unit (GRU) networks, as well as their bi-directional variants, BiLSTM and BiGRU. Anomalous temperature points were designated using a percentile-based threshold applied to residual fluctuations in the detrended temperature time series. Additionally, the impact of the exponentially weighted moving average (EWMA) method on detection accuracy was examined. The RNN models’ performance was assessed using precision, recall, and F₁ score metrics. Results demonstrated that RNN models effectively detect anomalies in temperature time series with the best models for each heater zone achieving F₁ scores of over 93%. To explain the variations in RNN model performance across different heater zones, we used Kullback–Leibler (KL) divergence to quantify the relative entropy between training and testing data, and the Detrended Fluctuation Analysis (DFA) to assess long-range temporal correlations. For datasets with strong long-range correlations and minimal relative entropy between training and testing data, GRU is the best-performing model. When the data exhibits weaker long-term correlations and a significant relative entropy between training and testing distributions, BiGRU shows the best performance. For the data sets with intermediate values of both KL divergence and DFA, the best performance is obtained with LSTM and BiLSTM, respectively. Full article

Given that freeze–thaw damage of prestressed concrete significantly threatens structural service life and that existing conventional simulation techniques fail to capture prestress time series, this paper proposes a deep learning prediction model based on the Transformer model. The model integrates a multi-head self-attention mechanism and positional encoding to effectively capture long-range dependencies in prestressed time series. It enhances temporal modeling capability through a 128-dimensional high-dimensional feature space (chosen to balance representation capacity and computational efficiency for the dataset scale) and a 4-layer encoder stacking structure. A dataset was constructed using time-series data from three prestressed concrete components subjected to 50 freeze–thaw cycles. The F-a component was used as the training set, while F-b and F-c served as the testing sets. During the training phase, a Noam learning rate scheduler, gradient clipping, and an early stopping strategy were employed. The results indicate that the training strategy enables the loss function to converge quickly without overfitting, demonstrating good generalization performance. The prediction model performs well on the F-a and F-c datasets, with determination coefficients (R²) of 0.8404 and 0.8425, and corresponding Mean Absolute Error (MAE) of 61.71 MPa and 57.41 MPa, respectively. It can accurately track the periodic variation trend of prestress, demonstrating the model’s effectiveness in prestress prediction. This model provides a new technical tool for the health monitoring and performance prediction of prestressed concrete structures in freeze–thaw environments. Full article

With applications in psychology, security, and human–computer interaction, facial expression recognition (FER) has become an essential tool for non-verbal communication. Current research often categorizes expressions into micro- and macro-types, yet existing datasets suffer from inconsistent labelling for classes, limited diversity of the databases, and insufficient scale for the currently available datasets. To address these gaps, this work proposes a novel framework combining the diffusion model with pre-trained CNNs. Leveraging original images from established datasets, CASME II, we generate synthetic facial expressions to augment training data, mitigating bias and inconsistency. The synthetic dataset is evaluated using ResNet 50, VGG16 and Inception V3 architectures. Inception V3 trained on the proposed AI-generated dataset and tested using CASME II, VGG-16 with data augmentation applied is trained on CASME II and tested on the proposed AI-generated dataset, and Inception V3 with 30% freezing layers method is trained on the proposed AI-generated dataset and tested using CASME II. These all successfully achieved state-of-the-art performance. The data augmentation and freezing layers approaches significantly improved the performance of the models. Our proposed approaches achieved state-of-the-art performance and outperformed most of the existing state-of-the-art approaches benchmarked in this study. Full article

In Canada, Indigenous communities have been disproportionately flooded. Specifically, Fort Albany First Nation (FN) located on a flood plain near the mouth of the Albany River in subarctic Ontario, Canada, has been evacuated frequently due to flooding or the threat of flooding―even though dikes were constructed in the late 1990s to safeguard the community. Thus, a fundamental question needs to be asked: Why is Fort Albany FN located on a flood plain in the first place? We answer the question through an Indigenous environmental justice lens using document and archival research in the context of the treaty making process between Fort Albany FN and the British Crown, and the establishment of reserves. In brief, procedural issues were noted, as there was no transparency in reserve choice at the time of signing the treaty, and during the actual surveying of the reserve boundaries with certain types of land being excluded from reserve locations, unbeknownst to the FNs peoples. The Cree were also misled into believing that they would retain access to their whole traditional homeland―and not be confined to reserve land―the Cree believed that they only agreed to share the land. Historically, the Cree harmonized with the seasons and would not be residing in the Albany River floodplain during river freeze-up and during river break-up―adaptive behaviour to avoid flooding. Harmonizing with the environment had allowed the mobile Cree to live successfully with the annual flooding of the Albany River for millennia, until being forced to live permanently on reserve land by the colonial government. Nonetheless, the Cree still sustain their cultural worldview acknowledging the Cree cycle of life. The way forward for Fort Albany First Nation will be either relocation to high ground or trying to tame nature by reinforcing the existing dikes—or some novel combination of both based on two worldviews. Full article

Maintaining ballast performance in seasonal frozen regions is essential for resilient and sustainable railway infrastructure because freeze–thaw-driven fouling can shorten service life and increase maintenance-related material consumption. To investigate the deterioration mechanisms of fouled railway ballast in seasonal frozen regions, freeze–thaw cycle tests and cyclic loading model tests were conducted in sequence using a custom low-temperature geotechnical system. The test results processed by Origin software indicate that unfrozen water migrates toward the freezing front under temperature gradients and forms ice lenses during freezing. During thawing, meltwater is retained above the underlying frozen soil. Repeated freeze–thaw cycles therefore promote progressive water accumulation in the upper soil layers, eventually forming a clay layer with high water content. Under cyclic loading, interlayer thickening exhibited clear moisture thresholds relative to the clay liquid limit (LL = 24%). Below the LL (18–24%), ballast penetration and fines migration were limited and thickness increased slowly. Above the LL, rapid strength loss accelerated penetration and upward transport. At an initial water content of 32%, fines migration surpassed the ballast surface and the ballast became fully fouled, meaning that the fouled interlayer thickness equaled the full 100 mm ballast-layer thickness. Fouling severity increased sharply with moisture: the void contaminant index exceeded the maintenance criterion (VCI > 40%) at 28% water content and evolved into severe mud pumping at higher concentrations. Excess pore water pressure developed stratification with depth, maintaining an upward hydraulic gradient near the interface and yielding a net water loss of 2.24–6.91% in the upper fine-grained layer. These quantified thresholds and mechanistic insights provide actionable trigger points for condition-based maintenance and climate-adaptive design, helping extend track-bed service life and reduce resource-intensive ballast renewal in seasonal frozen regions. Full article

The development of collagen-based composite materials offers new opportunities for designing bioactive porous structures with tunable properties. This study focuses on sponges or scaffolds fabricated from fish skin-derived tropocollagen combined with detonation nanodiamonds (NDs), aiming to explore how incorporation of NDs and application of radiation, as a potential sterilization method, influence structural and functional characteristics of the material. Freeze-dry methods of sponge fabrication resulted in a bilayered structure of open porosity, with microporosity at the top and a microchannel at the lower part of the material. The sponges demonstrated mechanical properties with relatively low elongation of below 10%, while the maximum stress was reduced by ca. 20% due to irradiation. Hydration and absorption experiments, mimicking the resorption of collagen in physiological conditions of expected application as wound dressing material, demonstrated controllable fluid uptake and gradual material dissolution, taking place over several hours, depending essentially on the irradiation treatment and morphological characteristics of the sponge. These findings highlight the versatility of collagen–nanodiamond composites as platforms, in which structural design and processing parameters control performance. Moreover, they provide a strong indication of the expected behavior of collagen–nanoparticle systems, including those incorporating NDs modified to impart specific biological functionality, such as antimicrobial activity. Full article

Accurate time-domain photovoltaic (PV) models are needed to evaluate performance under outdoor variability beyond STC datasheet conditions. This paper presents a traceable modeling workflow based on the standard single-diode formulation, implemented in MATLAB/Simulink (R2023a) as a modular white-box architecture that explicitly resolves photocurrent generation and loss mechanisms (diode recombination, shunt leakage, and series resistance effects) with temperature-consistent propagation through V_T(T) and saturation-current terms. The method couples optical boundary conditions to the electrical model by embedding plane-of-array (POA) excitation via the incidence angle Θ(t) and roof albedo directly into the photocurrent source term, preserving the causal chain from mounting geometry to electrical response. Calibration is separated from prediction by initializing key parameters using the standard Simulink PV block and then freezing them for time-domain evaluation. The workflow is validated on a 395 W rooftop prototype using 1 min resolved POA irradiance (ISO 9060:2018 Class A radiometric chain) and module temperature (IEC 60751 Class A Pt100), synchronized with electrical measurements. Over a multi-week campaign, the model exhibits high fidelity, with a worst-case relative current error of ~1.1% and a consistently low bias and dispersion, quantified by ME, MAE, RMSE, σ_e, and thresholded MAPE. Full article

Mineral resources serve as a critical foundation for China’s energy system, with the Ordos Basin’s Tarangole mining area being a key mineral production base in the central and western regions. To support the restoration, development, and productivity enhancement of the mining area, this research systematically investigates the geological and mechanical properties of the sandstone in the region. Herein the innovation lies in its comprehensive analysis of the influence mechanisms of multiple factors—such as geological groups, particle size, evaluation indicators, sampling depth, temperature, and creep rate—on the mechanical behavior of sandstone. The study, through engineering geological surveys and mechanical testing of frozen sandstone (including uniaxial and triaxial creep tests), led to the following key findings: (1) the sandstone in the area is prone to softening and disintegration, classified as soft to moderately soft rock (UCS range: 5.14–10.26 MPa in natural state), with a basic quality grade of IV–V. (2) The thermal conductivity and specific heat capacity of the rock vary significantly with temperature. The recommended freezing temperature is −5 °C, based on engineering experience and economic considerations. (3) Freezing can effectively enhance the strength of sandstone (e.g., the strength of medium- and coarse-grained sandstone increases by 5 MPa at −20 °C compared to −10 °C), although it still falls within the category of extremely soft rock. (4) The water-ice phase transition induced by low temperatures significantly enhances the overall strength, stiffness, and deformation resistance of saturated sandstone. Accordingly, freezing measures can effectively enhance rock mass strength under low-temperature conditions. It is recommended that mining operations be prioritized during winter or colder seasons to ensure construction safety and efficiency. Full article

Background/Objectives: Dextran sulfate sodium (DSS) is widely used to induce intestinal injury, reducing intestinal barrier integrity and thus contributing to systemic inflammation and oxidative stress, which may affect liver homeostasis and central nervous system function. In this context, the intake of phenolic compounds and anthocyanins from fruits such as jabuticaba has gained attention due to their antioxidant and anti-inflammatory properties. This study evaluated the effects of jabuticaba in the form of freeze-dried whole fruit, freeze-dried peel, and microencapsulated peel extract on DSS-induced damage to the gut–liver–brain axis in an in ovo model. Methods: Fertile eggs were assigned to five groups: water, DSS, DSS plus whole jabuticaba (WJ), DSS plus jabuticaba peel (JP), and DSS plus microencapsulated jabuticaba peel (JM). Duodenal, colon, and liver gene expressions; and histomorphometry, cecal microbiota, and brain gene expressions were evaluated at hatch. Results: DSS administration increased NF-κB expression and reduced MUC-2 in the duodenum, induced colonic inflammation, altered cecal microbiota, and caused hepatic oxidative stress, evidenced by elevated iNOS and enlarged fat globules, while reducing brain BDNF levels. Jabuticaba treatments mitigated intestinal, hepatic, and neural damage by reducing inflammatory markers; enhancing MUC-2, ZO-2, JAM-2, and claudin-1 expression; increasing villus area and goblet cell numbers; normalizing CAT and SOD activities in the liver; decreasing COX-2; increasing dopamine; and restoring BDNF in the brain. Conclusions: This study demonstrates that jabuticaba exerts protective effects along the gut–liver–brain axis, highlighting its potential as a functional food to support intestinal, hepatic, and brain health. Full article

This study aimed to valorize by-products from cabbage processing to produce nutrient-rich powders that are suitable for food incorporation and, as a case study, to evaluate their application in texture-modified jelly intended for senior consumers. Freeze-dried powders from cabbage leaves and cores were analyzed for physicochemical properties, nutritional value, and antioxidant activity. Steaming significantly affected water absorption, solubility, and color: powders from fresh cabbage exhibited higher water solubility and lighter, greener hues, whereas powders from steamed cabbage showed darker, yellow–red tones due to pigment degradation. Nutritional analysis confirmed high dietary fiber contents (>30 g/100 g dry weight) in all powders. Core powders contained more potassium and phosphorus, with minimal mineral losses being observed after steaming. Sugar profiling showed greater fructose, glucose, and total sugar contents in leaf powders, whereas sucrose predominated in core powders. Steaming facilitated maltose formation. Although steaming generally reduced total phenolic content, it increased antioxidant activity in steamed leaf powders. Application trials demonstrated that cabbage powder concentrations strongly influenced jelly composition, including dietary fiber, total phenolic content and mineral levels, while pectin concentration primarily affected texture. Optimized formulations yielded nutritionally enriched jellies with acceptable sensory properties, demonstrating the feasibility of using cabbage processing by-products as a value-added food ingredient. Full article

Currently, one of the major trends in the construction industry is the creation of structures with increased strength and durability. The solution is the use of nanomaterials as modifiers for cementitious composites. The aim of this study is to produce concretes with a variable structure modified with a combination of aluminum oxide (NA) and titanium oxide (NT) nanoparticles with improved properties. A variatropic structure is characterized by differences in properties across the cross-section of the material. Concretes were produced using vibration (V), centrifugation (C), and vibrocentrifugation (VC) technologies. Modification was carried out with NA particles from 0% to 4.0% in increments of 1.0% and NT from 0% to 2.0% in increments of 0.5% of the binder mass. Through experimental study, the impact of combined nanomodification on the compressive strength, water absorption, and frost resistance of concrete created with different technologies was investigated. The most effective modification dosages with NA and NT particles were determined to be 2% and 1%. The determination of concrete properties and the statistical processing of experimental results were carried out in accordance with the requirements of standardized methods. Compared to control samples, the maximum compressive strengths for V, C, and VC concretes were 12.4%, 17.5%, and 20.3% higher, reaching 48.9 MPa, 58.4 MPa, and 62.9 MPa, respectively. The lowest water absorptions for V, C, and VC concretes were 5.21%, 4.24%, and 3.76%, which are 18.5%, 24.4%, and 29.2% lower than those of the control samples. After a series of freeze–thaw cycles—6 for V, 8 for C, and 10 for VC—the losses in compressive strength and mass of the nanomodified composites were less than those of the control samples, indicating an increase in the frost resistance of concrete. The influence of concrete production technology on the effect of nanomodification with NA and NT particles was proven. Nanomodified C and VC concretes have improved physical and mechanical properties compared to V concretes. Nanomodified concretes with a variable structure have a more organized microstructure with a greater number of clusters of calcium silicate hydroxides. The resulting variable-structure concrete has improved properties and can be used to manufacture columns, piles, and transmission line supports. Full article

This study aimed to develop a pH-responsive microencapsulation system using complex coacervation with chitosan (CS) and hydrolyzed karaya gum (HKG) as natural wall materials to encapsulate ginger essential oil (GEO) as a core material. Key parameters influencing coacervate formation and encapsulation efficiency were studied and optimized. The results indicated that the maximum complexation yield (77.3%) was achieved at a pH of 4.6 with a CS:HKG mass ratio of 1:2. Under these optimal conditions, microcapsules were fabricated at various wall-to-core ratios, with the 3:1 ratio demonstrating the highest encapsulation efficiency (65.73%) and process yield (75.7%). Physicochemical characterization revealed that the microcapsules possessed low hygroscopicity and a pH-dependent solubility profile. Scanning electron microscopy (SEM) showed that freeze-dried microcapsules had a more porous, amorphous structure compared to the denser, irregular particles produced by oven-drying. Crucially, in vitro release studies demonstrated a pronounced pH-responsive behavior: GEO release was significantly faster and more extensive in simulated gastric fluid (pH 2.0) than in neutral or simulated intestinal fluid (pH 7.4). These findings highlight the successful fabrication of a stable CS-HKG micro-delivery system that effectively protects GEO and facilitates its controlled, targeted release in acidic environments, indicating strong potential for applications in gastric targeted functional food and pharmaceutical products. Full article

Bacterial nanocellulose (BNC) is gaining interest in multiple industrial applications. BNC dehydration would improve its industrialization while affecting its techno-functional properties (water binding or gelling capacity). This work analyses this aspect in a representative food system where these are fundamental properties: low-fat sausages with pre-emulsified sunflower oil. Native (n-BNC) and freeze-dried (d-BNC) bacterial nanocelluloses were studied at different concentrations. During thermal processing, all batters exhibited the typical viscoelastic transition associated with protein gelation. Formulations containing d-BNC developed a higher final elastic moduli and a broader concentration range of structural reinforcement compared to n-BNC systems. In the cooked sausages, BNC incorporation enhanced hardness, cohesiveness, and water-holding capacity, particularly at intermediate concentrations. Micrographs showed that d-BNC led to a finer and more homogeneous microarchitecture, while n-BNC aggregated in hollows of the meat protein network. Additionally, the Pickering effect of dried BNC produced meat emulsions with smaller oil droplets in agreement with the differences in lightness detected. Results suggest that freeze-dried BNC could be a convenient and effective option for the food industry due to its low weight, longer storage period, and easy handling compared to native BNC. Full article

This study systematically investigated the effects of freeze-drying on chicken, pork, and beef by examining pH, moisture content, rehydration capacity, water distribution, color, and texture profile at 2, 4, 6, 8, and 11 h. The pH values of all meats remained relatively stable within 5.6–6.2 throughout the drying process. Moisture content followed a “rapid dehydration-slower drying-stabilization” pattern, with pork retaining higher moisture during the mid-drying phase, while chicken and beef lost water more rapidly. The rehydration capacity increased with prolonged drying, with chicken showing the highest rehydration efficiency. Color changes were species-dependent. Specifically, chicken initially brightened before slight darkening, beef lost lightness with a temporary increase in redness, and pork gradually yellowed. Texture profiles also varied, with chicken maintaining relative stability throughout the drying process, beef showing temporary mid-drying hardness, and pork experiencing rapid declines in springiness and cohesiveness alongside fluctuating hardness. These findings provide valuable insights for optimizing freeze-drying protocols to preserve quality, functional performance, and sensory characteristics across different meat types. Full article