Search Results (138)

Background: Adolescence is characterized by rapid physical growth and neuromuscular reorganization, which may influence the development of postural control. Gender-specific differences in pubertal timing suggest that girls may achieve postural stability earlier than boys, but evidence remains inconsistent. This cross-sectional pilot study aimed to examine gender differences in static postural control among adolescents. Material and methods: A total of 59 students (28 females, 31 males; mean age 13.49 ± 0.97 years) from two schools in Bari, Italy, participated. Postural stability was assessed during bipedal and single-leg stance tasks under eyes-open and eyes-closed conditions using an inertial sensor placed at the lumbosacral region. The primary outcomes were sway path length and oscillation ellipse area. Results: Females demonstrated significantly shorter path length in eyes-open bipedal stance (p = 0.027, d = −0.51), as well as reduced ellipse area (p = 0.047, d = −0.44) and path length (p = 0.010, d = −0.62) in eyes-closed bipedal stance. No significant gender differences were observed in single-leg stance. Conclusions: These findings support the hypothesis that adolescent girls exhibit superior postural stability compared to boys, particularly under challenging sensory conditions. Such differences may reflect earlier maturational processes and suggest possible implications for motor development, injury prevention, and sports training. Full article

Background and Objectives: Spinal anesthesia is increasingly preferred in pediatric surgeries due to its rapid onset, high success rate, and low risk of systemic complications. However, the influence of age and body mass index (BMI) on block characteristics in adolescents remains insufficiently studied. Materials and Methods: This retrospective study evaluated 190 pediatric patients (aged 9–18 years; 154 male, 36 female) undergoing elective surgery with spinal anesthesia. Patients were stratified by age (Group 1: 9–14 years; Group 2: 15–18 years) and BMI (Group A: 16.00–19.65 kg/m²; Group B: 19.66–23.31 kg/m²). The primary outcome was sensory block duration. Secondary outcomes included sedation requirements, complications, analgesic requirement times, and Visual Analog Scale (VAS) scores. Results: Group 2 had significantly longer sensory block duration and lower postoperative VAS scores at 3 and 12 h compared to Group 1 (p < 0.001). Lower BMI was associated with greater sedation requirements (p < 0.001) and a higher incidence of intraoperative nausea and vomiting (p = 0.013). Complications were infrequent (hypotension 6.3%, bradycardia 2.1%, PONV 7.1%, postoperative headache 3.1%) and managed conservatively. Conclusions: Age and BMI meaningfully influence spinal anesthesia characteristics in pediatric patients. Older adolescents achieved longer sensory block durations and better postoperative analgesia, whereas younger and lower-BMI patients required more sedation and had higher nausea rates. Individualized spinal anesthesia planning, considering age, BMI, and developmental stage, may optimize clinical outcomes. Prospective studies are warranted to validate these findings. Full article

Background/Objectives: The spinal cord is a critical component of the central nervous system that transmits neural signals between the brain and the body’s peripheral regions through its nerve roots. Despite being partially protected by the vertebral column, the spinal cord remains highly vulnerable to trauma, tumors, infections, and degenerative or inflammatory disorders. These conditions can disrupt neural conduction, resulting in severe functional impairments, such as paralysis, motor deficits, and sensory loss. Therefore, accurate and comprehensive spinal cord segmentation is essential for characterizing its structural features and evaluating neural integrity. Methods: In this study, we propose a fully automated method for segmentation of the cervical spinal cord in sagittal magnetic resonance (MR) images. This method facilitates rapid clinical evaluation and supports early diagnosis. Our approach uses a Swin-Unet architecture, which integrates vision transformer blocks into the U-Net framework. This enables the model to capture both local anatomical details and global contextual information. This design improves the delineation of the thin, curved, low-contrast cervical cord, resulting in more precise and robust segmentation. Results: In experimental studies, the proposed Swin-Unet model (SWU1), which uses transformer blocks in the encoder layer, achieved Dice Similarity Coefficient (DSC) and Hausdorff Distance 95 (HD95) scores of 0.9526 and 1.0707 mm, respectively, for cervical spinal cord segmentation. These results confirm that the model can consistently deliver precise, pixel-level delineations that are structurally accurate, which supports its reliability for clinical assessment. Conclusions: The attention-enhanced Swin-Unet architecture demonstrated high accuracy in segmenting thin and complex anatomical structures, such as the cervical spinal cord. Its ability to generalize with limited data highlights its potential for integration into clinical workflows to support diagnosis, monitoring, and treatment planning. Full article

Aflatoxin (AF) contamination in pistachios remains a critical food safety and trade challenge, given the potent carcinogenicity of AF-B₁ and the nut’s high susceptibility to Aspergillus infection throughout production and storage. Traditional decontamination methods such as roasting, irradiation, ozonation, and acid/alkaline treatments can reduce AF levels but often degrade sensory and nutritional quality, implying the need for more sustainable approaches. In recent years, innovative nonthermal interventions, including pulsed light, cold plasma, nanomaterial-based adsorbents, and bioactive coatings, have demonstrated significant potential to decrease fungal growth and AF accumulation while preserving product quality. Biosensing technologies such as electrochemical immunosensors, aptamer-based systems, and optical or imaging tools are advancing rapid, portable, and sensitive detection capabilities. Combining these experimental strategies with artificial intelligence (AI) and machine learning (ML) models can increasingly be applied to integrate spectral, sensor, and imaging data for predicting fungal development and AF risk in real time. This review brings together progress in nonthermal reduction strategies, biosensing innovations, and data-driven approaches, presenting a comprehensive perspective on emerging tools that could transform pistachio safety management and strengthen compliance with global regulatory standards. Full article

Background/Objectives: Electrical threshold testing (ETT) offers a promising method for assessing somatosensory function. Despite its growing use, fundamental aspects such as the physiological recovery time required between repeated threshold measurements remain poorly understood. This gap is critical when evaluating sensory, motor, or pain thresholds (EST, EMT, EPT) in pre–post designs or rapid intra-session protocols. The aim is to investigate the short-term recovery dynamics of electrical thresholds following electrical threshold testing, and to determine the minimum interval required for values to return to a stable baseline. Methods: In this pilot, repeated-measures study, 10 healthy adults (20 upper limbs) underwent three progressive stimulation trials (sensory, motor, and pain). Electrical thresholds were assessed at fixed recovery intervals (0–120 s), with duplicate measurements at each time point. Stability was defined as the absence of significant differences between repeated measures. Results: EST stabilized rapidly after sensory or motor stimulation, showing no significant differences beyond 0 and 15 s, respectively. Within pain stimulation, EST recovered at 60 s. EMT showed immediate recovery with motor stimulation and required longer recovery with pain stimulation, with stabilization observed at 90 s. EPT exhibited the highest variability, with the smallest time-dependent differences observed immediately after the first assessment. Conclusion: Recovery time after electrical stimulation varies by threshold type and intensity of the stimuli. EST and EMT can be reliably reassessed immediately after sensory and motor stimulation, respectively. However, when stimulation reaches EPT level, EST requires 60 s to recover and EMT needs 90 s. EPT demonstrates higher variability, indicating the need for further investigation. These findings support the implementation of standardized recovery intervals in ETT and underscore the importance of interpreting EPT results with caution during rapid assessments. Full article

Background: Precise upper limb movements are essential for daily tasks and motor function. Feedforward responses enable anticipatory movement planning, while feedback responses utilize sensory information for real-time corrections. Long-latency reflexes (LLRs) represent rapid feedback responses during unexpected perturbations and are integral in maintaining motor control, yet the factors governing LLRs in the upper extremity remain unclear. Methods: Forty healthy participants with ages ranging from 20 to 45 years (mean = 26.75, and SD = 5.6), performed a unilateral visuomotor elbow flexion and extension task with one arm while following a sinusoidal target at varied resistances and speeds. Task performance was quantified and communicated to participants after each bout. Resistance was randomly released during the flexion phase to trigger a perturbation. Electromyography data from the biceps and triceps muscles were analyzed for the long-latency reflex (LLR) and secondarily for the short-latency reflex (SLR), and voluntary response (VR) phases. Results: In response to unexpected upper extremity perturbations, participants relied on two core strategies. Inhibitory LLRs within the biceps were prominent, emphasizing inhibition to maintain movement stability 50–150 ms post-disturbance. Additionally, volitional control through the triceps allowed participants to regain precision starting from over 150 ms. Participants’ responses to perturbations were dependent on speed and resistance but were not modified with learning across repeated attempts. Conclusions: This study reveals that participants demonstrate both long-latency and volitional responses to counteract perturbations during an upper extremity visuomotor task. These findings highlight that a predominant agonist inhibition strategy emerged during the during unpredictable perturbations of the upper extremity. Understanding these responses may inform rehabilitation and pharmaceutical interventions when treating individuals with neurological conditions that influence motor control. Full article

In many real-world control tasks, agents operate under partial observability, where access to complete state information is limited or corrupted by noise. This poses significant challenges for reinforcement learning algorithms, as methods relying on full states or long observation histories can be computationally expensive and less robust. Four-Phase Rapid Motor Adaptation (FRMA) is a reinforcement learning framework designed to address these challenges in high-frequency control tasks under partial observability. FRMA proceeds through four sequential stages: (i) full-state pretraining to establish a strong initial policy, (ii) auxiliary hidden-state prediction for LSTM memory initialization, (iii) aligned latent representation learning to bridge partial observations with full-state dynamics, and (iv) latent-state policy fine-tuning for robust deployment. Notably, FRMA leverages full-state information ($s_t$) only during training to supervise latent representation learning, while at deployment it requires only short sequences of recent observations and actions. This allows agents to infer compact and informative latent states, achieving performance comparable to policies with full-state access. Extensive experiments on continuous control benchmarks show that FRMA attains near-optimal performance even with minimal observation–action histories, reducing reliance on long-term memory and computational resources. Moreover, FRMA demonstrates strong robustness to observation noise, maintaining high control accuracy under substantial sensory corruption. These results indicate that FRMA provides an effective and generalizable solution for partially observable control tasks, enabling efficient and reliable agent operation when full state information is unavailable or noisy. Full article

This study investigates the effects of species, geographical origin, and processing on the proximate composition of frog leg meat, with a focus on developing predictive models for processing status. Data were systematically compiled from 18 published studies, yielding 32 entries across 10 edible frog species and multiple processing methods. Proximate composition parameters (moisture, protein, fat, ash) were compared between processed and unprocessed samples, and classification models were trained using moisture content as the primary predictor. Logistic regression and several machine learning algorithms, including Stochastic Gradient Descent, Support Vector Machine, Random Forest, and Decision Tree, were benchmarked under a Leave-One-Study-Out (LOSO) cross-validation framework. Results demonstrated that moisture content alone was sufficient to accurately distinguish processing status, with a critical threshold of ~73% separating processed from unprocessed frog legs. Logistic regression achieved perfect specificity and precision (100%) with an overall accuracy of 96.8%, while other classifiers also performed strongly (>90% accuracy). These findings confirm moisture as a species- and origin-independent marker of processing, offering a simple, rapid, and cost-effective tool for authenticity verification and quality control in frog meat and potentially other niche protein products. Future work should expand sample coverage, validate thresholds across processing types, and integrate biochemical and sensory quality assessments. Full article

Background/Objectives: Rhodiola rosea L. (Crassulaceae), a perennial adaptogenic herb native to Northern Europe, Asia, and North America, is renowned for its therapeutic properties attributed to phenolic compounds including flavonoids, phenylethanoids, phenylpropanoids, and cinnamyl alcohol glycosides. The plant’s antioxidant and anti-inflammatory activities align with its traditional use in boosting physical and cognitive performance, reducing fatigue, and improving stress resilience. However, conventional dosage forms present compliance challenges, particularly for vulnerable populations with swallowing difficulties. This study aimed to develop and optimize orally disintegrating tablets (ODTs) containing standardized Rhodiola rosea root and rhizome (RR) dry extract to ensure rapid disintegration and acceptable taste, thereby improving patient compliance. Methods: Dried Rhodiola rosea root and rhizome (particle size 2–3 mm) were extracted using 70% m/m ethanol using the fractionated maceration methodology. The resulting dry RR extract was standardized to 3.0% m/m rosavin content by blending batches of the extract and analyzed using validated chromatographic methods. The standardized dry extract was formulated into ODTs via direct compression technology. Various excipients were evaluated to achieve rapid disintegration while masking the characteristic bitter taste of RR extract. Results: The optimized ODT formulation (500 mg, 11 mm ø, 20% standardized RR dry extract) disintegrated within 3 min and effectively masking the characteristic bitterness of the RR extract. The formulation maintained content uniformity and did not exhibit loss of active compounds during processing, meeting European Pharmacopoeia requirements for ODTs. Conclusions: The developed ODTs containing standardized Rhodiola rosea extract offer a patient-friendly alternative for oro-mucosal administration, supporting improved compliance in populations with swallowing difficulties while retaining the extract’s phytochemical integrity and sensory acceptability. Full article

The shelf life of perishable foods is traditionally determined by microbiological, chemical, and sensory analyses, which are well-established and reliable. However, these methods can be time-consuming and resource-intensive, and they may not fully account for unexpected storage deviations, such as temperature fluctuations or equipment failures. Smart films emerge as a promising alternative, enabling rapid, visual, and low-cost food quality monitoring. This study developed smart films based on zein/gelatin/cellulose nanocrystals (Z/G/CNC) functionalized with alizarin (AL, 0–3% w/w), produced by casting (12.5% zein, 12.5% gelatin, and 5% CNC w/w). The films were characterized for morphological, physicochemical, thermal, and spectroscopic properties, chromatic response at pH 3–11, activity against Escherichia coli and Staphylococcus aureus, and applicability in monitoring Merluccid hake fillets. The incorporation of AL reduced water solubility, increased water vapor permeability and contact angle, imparted a more intense orange coloration, and improved thermal resistance. AL also increased thickness and elongation at break while reducing tensile strength and Young’s modulus. All films exhibited excellent UV-blocking capacity (<1% transmittance). Noticeable color changes were observed, with the Z/G/CNC/AL1 film being the most sensitive to pH variations. During Merluccid hake storage, ΔE values exceeded 3 within 72 h, with a color change from orange to purple, correlating with fillet pH (8.14) and total volatile basic nitrogen (TVB-N) (24.73 mg/100 g). These findings demonstrate the potential of the developed films as biodegradable sensors for smart packaging of perishable foods. Full article

With the rapid advancement of industrial intelligence, ensuring occupational safety has become an increasingly critical concern. Among the essential personal protective equipment (PPE), safety helmets play a vital role in preventing head injuries. There is a growing demand for real-time detection of helmet chinstrap wearing status during industrial operations. However, existing detection methods often encounter limitations such as user discomfort or potential privacy invasion. To overcome these challenges, this study proposes a non-intrusive approach for detecting the wearing state of helmet chinstraps, inspired by the mechanosensory hair arrays found on spider legs. The proposed method utilizes multiple MEMS inertial sensors to emulate the sensory functionality of spider leg hairs, thereby enabling efficient acquisition and analysis of helmet wearing states. Unlike conventional vibration-based detection techniques, posture signals reflect spatial structural characteristics; however, their integration from multiple sensors introduces increased signal complexity and background noise. To address this issue, an improved adaptive convolutional neural network (ICNN) integrated with a long short-term memory (LSTM) network is employed to classify the tightness levels of the helmet chinstrap using both single-sensor and multi-sensor data. Experimental validation was conducted based on data collected from 20 participants performing wall-climbing robot operation tasks. The results demonstrate that the proposed method achieves a high recognition accuracy of 96%. This research offers a practical, privacy-preserving, and highly effective solution for helmet-wearing status monitoring in industrial environments. Full article

Despite the continued growth of the gluten-free food market, there is a dearth of sensory and consumer knowledge on commercial products. The existing research is mostly limited to hedonic measurements and ingredient effects instead of analytical methods for a better understanding of product characteristics of gluten-free crackers specifically. In this work, a semi-trained consumer panel used projective mapping to choose objectively different plain/original crackers from a pool of sixteen commercial gluten-free cracker varieties. The cracker samples represented a widespread sensory space originating from different key ingredients such as brown rice, white rice, flaxseed, cassava flour, nut flour blend, millet blend, and tapioca/potato starch blend. Based on projective mapping results, the crackers that mostly represented the sensory space were selected for characterization by a modified flash profiling method. The consumer panel developed 74 descriptors: 30 aromas, 28 flavors, 15 texture terms, and a mouthfeel attribute. The samples were monadically rated for intensity on a 4-point scale (0 = none, 1 = low, 2 = medium, and 3 = high). Rice, toasted, salt, grain, burnt, flaxseed, bitter, earthy, nutty, seeds, and grass were the prevalent aromas and flavors. Others were specific to cracker type. Some of these attributes can be traced back to the ingredients list. Results suggest that ingredients used in small portions are defining the flavor properties over the major grains/flour blends. All samples had some degree of crunchiness, crispness, and pasty mouthfeel; rice crackers were particularly firm, hard, and chewy; brown rice crackers were gritty; crackers with tuber starches/flours were more airy, soft, smooth, and flaky. Overall, the samples shared more aroma and flavor notes than texture attributes. In comparison to trained panel results, consumers generated a greater number of terms and were successful in finding subtle differences primarily in texture but had many overlapped flavors. The developed consumer terminology will facilitate the gluten-free industry to tailor communication that better resonates with consumer experiences, needs, and product values. Full article

Sensory evaluation is essential to understand consumer perception. This study compared three descriptive methods (Check-All-That-Apply (CATA), Flash Profile, and Pivot Profile) to characterize muffins formulated with alternative flours (purple corn and amaranth) in comparison to a wheat-based control. Six formulations (T0–T5) were evaluated: CATA and Pivot Profile were applied with 100 consumers, while Flash Profile was conducted with 15 panelists. Multivariate statistical analyses were used: correspondence analysis for CATA and Pivot, and Generalized Procrustes Analysis for Flash Profile. All three methods showed high discriminative power: CATA explained 94.36% of the variance, identifying three main groups; Flash Profile explained 63.88%, highlighting differences in texture and aroma; and Pivot Profile explained 81.10%, revealing complex interactions among sensory attributes. Sample T1 (100% purple corn) showed a distinctive sensory profile (bitter and dry), while samples T2 to T5 presented intermediate characteristics. The RV coefficient confirmed significant congruence between the methods. CATA effectively identified relevant sensory differences, Pivot Profile generated descriptors in relation to a control sample, and Flash Profile enabled exploratory analysis. The choice of method depends on the study objective, with each approach offering complementary sensory information. Full article

Rapid economic growth and changing consumer patterns have made fresh-cut fruits and vegetables household staples because of their high nutritional value, their role in reducing the risk of illnesses and other health problems, and convenience. However, fresh-cut produce is susceptible to the rapid deterioration of sensory quality, nutrient loss, foodborne pathogens contamination, and spoilage caused by microbial growth, which can lead to consumer health risks. Thus, there is an urgent need to improve preservation methods, to increase the shelf life of fresh-cut produce. This review examines the primary mechanisms underlying quality deterioration in fresh-cut produce and critically evaluates emerging preservation technologies including physical, chemical, and biopreservation for their efficacy in reducing microbial growth while maintaining product quality. This paper also discusses key gaps and proposes future research directions to improve preservation methods, extend shelf life, and ensure the safety of fresh-cut produce. Full article

Cordyceps sinensis (C. sinensis) is widely recognized for its bioactive compounds and associated health benefits. However, due to its delicate nature, conventional chilled storage often results in the rapid degradation of valuable compounds, leading to loss of nutritional value and overall quality. This study integrated and evaluated comprehensive strategies: three gas-conditioning and two light-based preservation methods for maintaining both quality and nutritional integrity during 12-day chilled storage at 4 °C. The results revealed that vacuum packaging significantly inhibited weight loss (3.49%) compared to in the control group (10.77%) and preserved sensory quality (p < 0.05). UV-based interventions notably suppressed polyphenol oxidase and tyrosinase activities by 36.4% and 29.7%, respectively (p < 0.05). Modified atmosphere packaging (MAP) with 80% N₂ and 20% CO₂ (MAP-N₂CO₂) maintained higher levels of cordycepin (1.77 µg/g) and preserved energy charge above 0.7 throughout storage. The results suggest that MAP-based treatments are superior methods for the chilled storage of C. sinensis, with diverse advantages and their corresponding shelf lives associated with different gas compositions. Full article