Search Results (1,070)

The present study evaluated the effects of the prepartum administration of immunotropic preparations on the growth performance, physiological status, and metabolic profile of calves. Sixty pregnant Holstein cows were divided into three groups (n = 20 each): the first experimental group received a single intramuscular injection of sodium nucleinate (5 mL), the second experimental group received a single intramuscular injection of Ribotan (5 mL), and the control group received saline solution. All treatments were administered 3–9 days before calving. The obtained calves were monitored until 60 days of age. Clinical, growth, hematological, and biochemical parameters were assessed at days 1, 10, 30, and 60. Calves from the treated cows showed improved neonatal adaptation, including faster development of standing posture and the suckling reflex. Body weight was significantly higher in experimental groups at 30 and 60 days (p ≤ 0.05), with consistently greater average daily gains. Blood analysis revealed increased total protein, albumin, and γ-globulin levels, indicating enhanced protein metabolism and immune status. In contrast, cortisol concentrations were lower in treated groups, reflecting reduced physiological stress. Multivariate (PCA) and correlation analyses confirmed strong associations between growth performance, metabolic activity, and immune indicators, and demonstrated clear separation between control and treated groups. Ribotan exhibited the most pronounced biological effect, while sodium nucleinate showed moderate but consistent improvements. In conclusion, prepartum immunotropic treatment of cows enhances early-life adaptation, metabolic efficiency, and growth performance of calves and may represent a practical strategy for improving calf rearing outcomes in dairy farming systems. Full article

Under the dual constraints of global food security and ecological protection, conventional agriculture is hampered by low resource efficiency and sluggish environmental response. Crop digital twin technology establishes a dynamic virtual reality system that integrates crops, environment, and water to enable real-time interaction and optimization. Based on the existing literature, this paper reviews the concept, architecture, and core modules of this technology and summarizes its applications in precision irrigation and crop monitoring. There are three major bottlenecks that persist, including limited high-frequency multi-source sensing and spatiotemporal fusion, insufficient parameter calibration and dynamic updating, and weak cross-scale integration from plant to watershed. Water is increasingly recognized as the key constraint and control variable and acting as both the central physiological driver of crop growth and the mass-flow link that connects the soil–plant–atmosphere continuum. The spatiotemporal dynamics of crop water deficit, compensatory root water uptake, evapotranspiration feedback, and the hydraulic behavior of irrigation-district canal systems constitute the core hydrological processes that must be simulated within the digital twin. Synchronizing crop water demand, soil moisture dynamics, atmospheric evapotranspiration, and irrigation scheduling within a unified spatiotemporal framework establishes a complete sensing, diagnosis, prediction and regulation technical chain. This chain offers a core pathway for alleviating agricultural water scarcity, improving irrigation efficiency, and ensuring food security. Full article

Heart rate variability (HRV) is an established biomarker of autonomic nervous system activity, yet its profile in miniature cattle remains poorly understood despite their growing importance in sustainable farming. This study compared HRV parameters between miniature and Holstein cows and assessed the influence of age on these profiles. Eighty clinically healthy female cattle (40 miniature, 40 Holstein), aged 2 to 8 years, were evaluated under field conditions using a Polar H10 heart rate monitor. RR intervals were analyzed using Kubios HRV software to obtain time- and frequency-domain indices. Miniature cows exhibited significantly lower heart rates and higher time-domain measures (RMSSD and SDNN) compared to Holsteins, while frequency-domain analysis revealed significant differences in LF, HF, and LF/HF ratio, suggesting group-associated differences in proportional autonomic balance. Age-stratified analysis revealed that these physiological distinctions were more pronounced in older cows (6–8 years). However, given the observational cross-sectional design of this study, confounding factors—specifically the different farm environments, management systems, and the active lactation status of the Holstein group—preclude attributing these differences solely to breed or body size. Therefore, these results suggest an associative physiological pattern rather than a definitive autonomic adaptation. Despite these limitations, portable HRV monitoring proved feasible under farm conditions, providing valuable preliminary baseline data that can inform future controlled studies on bovine cardiovascular welfare. Full article

Individuals with Duchenne muscular dystrophy (DMD) are prone to nutritional imbalances, and zinc deficiency may contribute to impaired bone health. This study evaluated serum zinc status and the effects of oral supplementation on bone parameters in DMD. In this quasi-experimental before-and-after study, 34 patients were assessed at three time points over eight months. Eligible participants who met the inclusion criteria and agreed to participate received the proposed interventions during routine follow-up at the Neurology outpatient clinic. Anthropometry, dietary intake, bone mineral density (BMD), bone mineral content (BMC), and serum zinc were measured; supplementation (5–15 mg/day) was provided for four months. Baseline zinc deficiency was observed in 36.7% of participants. No significant overall changes were detected. Stratified analyses revealed a modest increase in total body BMD among individuals with adequate baseline BMD (p = 0.02). As this finding emerged from a subgroup analysis, it should be interpreted cautiously, and the potential contribution of physiological growth to the observed change cannot be excluded. In addition, zinc-deficient participants showed a significant rise in serum zinc levels (p = 0.008). These findings suggest that the response to zinc supplementation may vary according to baseline nutritional and skeletal status and underscore the relevance of micronutrient monitoring in individuals with DMD. Trial registration: The trial was also registered in the Brazilian Registry of Clinical Trials under the code RBR-7cfdxm, approved on 14 June 2018. Full article

Wireless Body Area Networks (WBANs) have become an essential component of modern Internet of Medical Things (IoMT) healthcare systems, enabling continuous monitoring of patient physiological signals through wearable sensors. Despite their advantages, WBAN environments remain highly prone to cyber threats, privacy breaches, and single points of failure. To address these risks, this work proposes a Hybrid Multi-Metric Anomaly Detection (HM-MAD) framework deployed on the NodeMCU-32S platform with BLE 5.0 connectivity for secure continuous glucose monitoring (CGM) data transmission. The detection model simultaneously analyses physiological signals, system-level parameters, and network-level communication metrics, enabling the reliable identification of multiple cyberattacks. The proposed system focuses on securing data transmission against relay attacks, where attackers induce communication delay without modifying payloads, potentially leading to false glucose readings, improper insulin dosage delivery, unauthorized control or denial-of-service. The Convolutional Neural Network (CNN) and Bi-Directional Long Short Term Memory (BiLSTM) model classifies attack types including timing manipulation, replay attacks, power glitches, firmware tampering, and sensor spoofing. Experimental evaluation demonstrates that the proposed CNN + BiLSTM framework achieves 94.6% detection accuracy with an average inference latency of 15 ms, representing a 50% latency reduction compared to Transformer-based intrusion detection models (30 ms), while simultaneously reducing computational overhead by 28% in terms of floating-point operations and memory utilization. These results indicate that the HM-MAD framework provides an effective and scalable solution for protecting resource-constrained IoMT healthcare systems against emerging cyber threats. Full article

This paper presents a compact wearable patch antenna operating in the 2.4 GHz ISM band for biomedical Internet of Things (IoT)-based healthcare monitoring applications. The proposed antenna is intended for integration with wearable biomedical sensors in order to support real-time physiological data transmission in remote patient monitoring systems. The antenna was designed on an FR4 substrate to achieve good impedance matching and stable radiation performance. The antenna showed good performance, with a reflection coefficient of −39.56 dB and a gain of 3.01 dB. SAR analysis confirmed compliance with IEEE and ICNIRP safety standards for wearable applications. In addition, the antenna prototype was fabricated and experimentally validated using a vector network analyzer (VNA), showing good agreement between simulated and measured results. Furthermore, the proposed system was implemented by integrating an ESP32 microcontroller with a MAX30100 physiological sensor, where the sensor is responsible for acquiring real-time biomedical data, including heart rate and blood oxygen saturation (SpO₂). The ESP32 processes the acquired data and enables wireless transmission through the proposed antenna to a smartphone and laptop using the Blynk IoT platform, which allows real-time remote monitoring and visualization of physiological parameters. The obtained results confirm the suitability of the proposed antenna for wearable biomedical devices, remote healthcare monitoring, and IoT-enabled healthcare applications. Full article

Introduction: Sharks are key species in marine ecosystems, and their conservation is a priority across European waters. However, several fisheries unintentionally capture sharks as bycatch, raising concerns about their post-capture survival. In the Gulf of Cadiz, demersal trawl fisheries frequently capture the catsharks Galeus atlanticus and G. melastomus. Objective: This study aimed to assess the short-term survival rates of these two species following trawl capture and to identify potential blood biochemical markers predictive of survival. Methodology: Fieldwork was conducted aboard an oceanographic research vessel over two spring seasons. Standarized demersal trawl hauls of 1-h duration were performed. Immediately after capture, individuals were transferred to onboard seawater tanks, where their recovery was monitored for 24 h. Blood samples were collected at two time points: immediately after capture and after the 24-h recovery period. Biochemical parameters associated with secondary stress responses were analyzed. Results: Survival rates were high for both species, reaching 88 ± 8% for G. atlanticus and 90 ± 4% for G. melastomus. Blood analyses indicated a clear physiological recovery in all surviving individuals after 24 h, evidenced by the normalization of stress-related parameters. Notably, interspecific differences were observed in certain biochemical markers after capture, including amino acids and lactate concentrations, suggesting species-specific responses to capture stress. Conclusions: These findings provide valuable insights into the resilience of demersal catsharks to trawl-induced stress and highlight the potential of blood biomarkers as a tool for predicting post-capture survival. The results support the development of evidence-based onboard handling protocols aimed at maximizing the survival of incidentally captured sharks. Such measures can contribute to more sustainable fisheries management and the conservation of vulnerable elasmobranch species in European waters. Full article

Hybrid snakehead (Channa argus × Channa maculata) is a major cultured freshwater fish in China, but standardized health monitoring using serum biochemistry is limited by the lack of species-specific reference intervals. This study established reference intervals for 20 serum biochemical parameters in hybrid snakehead reared under 27 °C for 90 days. The body weights of the sampled fish ranged from 50 g to 160 g and were exempted from diseases by health check. All parameters were measured using an automated analyzer with commercial reagent kits. Most parameters exhibited non-normal, right-skewed distributions, and only total protein (TP) was normally distributed. Smoothed bootstrap resampling and kernel density estimation were applied to extract the main peak distribution and reduce bias from outliers and long tails. Species-specific reference intervals were established based on the main peak data, providing more reliable physiological baselines than conventional percentiles. Correlation analysis revealed coordinated changes among liver function, nutrient metabolism, tissue damage, and digestive enzymes. These results provide a standardized tool for health assessment, subclinical disease diagnosis, and comparative analysis in juvenile hybrid snakehead maintained at an optimal temperature in indoor mesocosm systems. Full article

The southeastern coastal region of China is extensively influenced by the circum-Pacific geothermal activity, particularly during the excavation of deep-buried tunnels, where the confined space leads to the accumulation of heat flow, resulting in high-temperature and high-humidity environments. These conditions are detrimental to both the physical and mental health of workers and the safe operation of equipment. Based on this, the Lijiashan deep-buried high-temperature tunnel along the Wen-Yu High-Speed Railway (Wenling-Yuhuan) was selected as a case study. Field monitoring was conducted to assess the surrounding rock stress, temperature distribution characteristics of the surrounding rock and structure, and the humid and high-temperature environment within the tunnel during construction. A comprehensive evaluation index considering both temperature and humidity was employed to evaluate the tunnel construction environment. The results indicate the following: (1) During tunnel excavation, the maximum surrounding rock pressure occurs at the arched shoulder, and the fractures induced by blasting effectively relieve stress, mitigating the risk of rockburst. (2) The seepage paths of the surrounding rock are redistributed during excavation, converging towards the invert, with the osmotic pressure being approximately 10 times that of the upper structure. (3) The temperature at the tunnel face, secondary lining, and surrounding rock is significantly influenced by the heat released from concrete hydration. The closer the surrounding rock is to the support structure, the higher the temperature, with the secondary lining reaching up to 58.6 °C and the working area up to 35.2 °C. (4) Water spraying can reduce the temperature in the construction area by approximately 0.65% at the Kelvin temperature conditions, but it increases humidity by about 16%. The average humidity levels within the tunnel are 75.3% during the day and 87.5% at night. (5) Evaluation of workers’ physiological parameters reveals that the humid and high-temperature environment during tunnel construction is consistently unfavorable for workers’ health. Full article

Intelligent sensors and Internet of Medical Things (IoMT) platforms are rapidly changing smart healthcare by enabling continuous capture of physiological, behavioral, and clinical events outside conventional hospital settings. Yet the value of connected sensing depends on more than signal acquisition alone. A practical remote-monitoring ecosystem must also convert sensor alerts, clinician-facing summaries, and historical electronic clinical records (ECRs) into ranked evidence that supports care decisions. This study reframes a large-AI clinical retrieval model as the intelligence layer of an edge–cloud IoMT architecture. The proposed framework combines Transformer-Based Sequence (TBS) encoding, BioBERT-driven representation learning, explicit retrieval, and domain-guided re-ranking to connect sensor-originated narratives, patient records, and clinician queries. The empirical evaluation is conducted on Medical Information Mart for Intensive Care III (MIMIC-III) and i2b2, two de-identified clinical text benchmarks that approximate the documentation layer of real-world remote patient monitoring. Compared with strong baselines, including DeepBio, UniT2T, Web4IR, A2A-API, CoLTiD, VLRG, ColBERT, DeepSDH, BiRex, and DL4BTM, the proposed model achieves the best overall performance, reaching F1/Pre/NDCG scores of 0.8399/0.8338/0.5235 on MIMIC-III and 0.8090/0.8100/0.5129 on i2b2. Ablation experiments confirm the importance of exploratory data adaptation, critical feature modeling, critical token learning, cross-disciplinary supervision, and data-driven regularization. Parameter sensitivity analysis shows stable behavior for beta values greater than or equal to 1, with the strongest results at beta = 5. The study concludes that large-AI retrieval can strengthen the clinical interpretation layer required for IoMT-enabled remote monitoring, while future work should validate the approach on live multimodal sensor streams and privacy-preserving deployments. Full article

Cat welfare assessment in Animal-assisted aervices (AAS) is necessary to ensure engagement in AAS does not impair welfare. An initial systematic search conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines revealed a complete lack of studies specifically addressing this topic. Consequently, a second-step search was performed, widened to the existing tools for monitoring cat welfare in general. Three scoping reviews using PRISMA guidelines were performed, focusing on the three principal fields of welfare assessment: health, behaviour, and physiology/endocrinology. Studies published on Scopus in 2011–2026, written in English and assessing feline (Felis catus) welfare were selected. A total of 2728 records were identified, of which 43 met the inclusion criteria (including 7 reviews and 1 scientific report); the methods used to assess cat welfare were summarized and discussed for their potential application in AAS. Although multiple tools are available, most are context- or disease-specific and some are not validated. Approximately half of the studies employed more than one indicator or method, with behavioural parameters being the most frequently used through questionnaires or scores. This work provides a practical framework to support veterinarians, handlers, and researchers in the selection of appropriate tools for cat welfare monitoring in AAS. Full article

Non-invasive fetal electrocardiogram (FECG) extraction from maternal abdominal ECG (AECG) is crucial for prenatal monitoring but remains challenging due to strong interference from maternal ECG (MECG), baseline drift, and noise. We propose an FECG extraction method based on minimal channel attention (MCA) and flow matching (FM), learning a deterministic mapping from AECG to FECG via a probabilistic path. To balance the preservation of physiological signals and separation of interference, we employ bridge variance scheduling for the diffusion process. Target matching loss is introduced to regress the FECG directly, enhancing training stability and waveform fidelity. For feature selection, a minimal channel attention module with global average pooling and a single linear layer is embedded after feature extraction, capturing cross-channel dependencies with minimal parameters. Enhanced residual connections are incorporated to retain underlying features and optimize gradient flow in deep networks. Experiments on two public datasets (ADDB and BDDB) with a leave-one-out cross-validation strategy show that our method achieves average Pearson correlation coefficients (PCCs) of 0.94 ± 0.050 on ADDB and 0.91 ± 0.122 on BDDB, demonstrating robust performance across diverse real-world recording conditions. The method balances high accuracy with efficient feature extraction, offering a reliable solution for non-invasive fetal heart health monitoring. Full article

Pulse oximetry is an essential standard monitor in modern anesthetic practice, enabling continuous noninvasive assessment of arterial oxygen saturation and pulse rate throughout the perioperative period. Since its introduction into clinical medicine, pulse oximetry has significantly improved patient safety by facilitating early detection of hypoxemia and physiologic deterioration. Despite its widespread use, clinicians may underrecognize the technical principles, physiologic assumptions, and limitations that influence measurement accuracy. This review provides a perioperative perspective on pulse oximetry, including the physics of photoplethysmography, sensor technologies, and practical considerations for optimal probe placement and signal acquisition. Sources of inaccuracy such as motion artifact, low perfusion states, dyshemoglobinemias, ambient light interference, skin pigmentation, and venous pulsation are discussed in detail. The review further examines perioperative applications across preoperative evaluation, intraoperative monitoring, and postoperative recovery, while also exploring advanced parameters including perfusion index (PI) and pleth variability index (PVI). Emerging innovations such as multi-wavelength systems and artificial intelligence (AI)-enhanced signal analysis are also highlighted. A comprehensive understanding of pulse oximetry allows anesthesiologists to appropriately interpret monitor data, recognize device limitations, and optimize perioperative patient care. Full article

Street-food grilling is a common occupation in Asia, yet the occupational health risks associated with cooking-generated polycyclic aromatic hydrocarbons (PAHs) exposure, occurring alongside plausible unmeasured co-exposures such as ambient heat and physical workload, remain under-researched. This study investigated the internal dose of PAH exposure and its association with early biological effects and physiological strain among grill restaurant workers. A cross-sectional study was conducted involving grill workers and 20 age/BMI-matched controls. Urinary 1-hydroxypyrene (1-OHP) was utilized as the primary exposure biomarker. The study assessed early biological effects such as oxidative stress (8-OHdG, F₂-isoprostanes), lung epithelial integrity (CC16), and genotoxicity (BPDE-DNA adducts) via ELISA. Physiological parameters, including blood pressure and heart rate, were recorded to evaluate acute cardiovascular strain. Workers had significantly elevated urinary 1-OHP levels compared to controls (Hodges–Lehmann ratio = 3.66, 95% CI: 1.68–7.12, representing a 3.7-fold median increase), with exposure levels increasing proportionally to smoke proximity. Notably, workers demonstrated a significantly higher median resting heart rate (HL ratio = 1.13, 95% CI: 1.05–1.23; +12.9%) and systolic blood pressure (HL ratio = 1.09, 95% CI: 1.00–1.18; +8.9%) compared to their office-based peers. Although strong correlations were observed among biological effect biomarkers (r_s = 0.42–0.63), there were no significant differences between groups for 8-OHdG, CC16, or BPDE-DNA adducts, suggesting that cardiovascular parameters reflect acute short-term responses, while genomic damage markers may require higher cumulative exposure thresholds to become detectable. The study revealed that grill restaurant workers face substantial internal PAH exposure and significant cardiovascular strain, occurring alongside plausible unmeasured co-exposures including ambient heat and physical workload. The prevalence of chronic cough and elevated heart rate is a critical early warning sign for occupational health. Our findings indicate that current general ventilation is inadequate, highlighting an urgent need for localized engineering controls and comprehensive health surveillance, including cardiovascular monitoring in the service sector. Full article

Reliable monitoring of spontaneous affect is essential in biomedical sensing, where involuntary facial signals serve as objective indicators of physiological states. Micro expression recognition (MER) is particularly challenging due to the sub-second, low amplitude nature of these signals. Many existing MER methods rely on apex (peak) frame detection, making them sensitive to temporal localization errors and difficult to deploy in unconstrained settings. To address this, we propose an apex-free framework that analyzes facial dynamics by structuring motion-magnified features along a newly introduced magnification intensity axis. By applying Eulerian motion magnification across multiple discrete levels and collapsing the sequences into single accumulation images, we generate a multi-level representation of subtle facial dynamics without requiring frame-level annotations. A lightweight shared temporal mixer (STM) is employed to analyze the dynamic evolution of motion across the magnification intensity axis. Subsequently, a dual-branch convolutional neural network (CNN), processing low- and high-amplification regimes respectively, integrates a convolutional block attention module (CBAM) to capture subtle facial motion while effectively filtering out irrelevant noise. Our model is highly efficient, requiring only 0.94 M parameters and 262 MFLOPs, which is significantly lower than the computational demands of standard backbones such as ResNet18 or VGG16. To ensure the model generalizes to new individuals, we evaluated it by testing on subjects whose data was entirely excluded from the training process. Under this rigorous setup, the proposed method achieves approximately 80% and 70% accuracy on the CASME II and SMIC datasets respectively, showing performance comparable to, or in some cases, slightly above current state-of-the-art methods. Considering both the competitive accuracy and high computational efficiency, the proposed framework holds significant potential for practical integration into real-time affect monitoring systems, particularly within biomedical applications. Full article