Search Results (8,104)

Accurate walking trajectory estimation is critical for monitoring activity levels in healthcare and occupational safety applications. Ultra-Wideband (UWB) technology has emerged as a key solution for indoor human activity and trajectory tracking. However, its performance is fundamentally limited by Non-Line-of-Sight (NLOS) errors and kinematic drift during turns. To address these challenges, this study introduces a novel integrated IMU-UWB framework for walking trajectory estimation in NLOS scenarios involving turning gait. The algorithm integrates an error-state Kalman filter (ESKF) and a phase-aware turning correction module. Experiments were carried out to evaluate the effectiveness of this framework. The results show that the presented framework demonstrates significant improvements in walking trajectory estimation, with a smaller mean absolute error (7.0 cm) and a higher correlation coefficient, compared to the traditional methods. By effectively mitigating both NLOS-induced ranging errors and turn-related drift, this system enables reliable indoor tracking for healthcare monitoring, industrial safety, and consumer navigation applications. Full article

The rapid growth of Internet-connected devices integrating into our everyday lives has no end in sight. As more devices and sensor networks are manufactured, security tends to be a low priority. However, the security of these devices is critical, and many current research topics are looking at the composition of simpler techniques to increase overall security in these low-power commercial devices. Transmission security (TRANSEC) methods are one option for physical-layer security and are a critical area of research with the increasing reliance on the Internet of Things (IoT); most such devices use standard low-power Time-division multiple access (TDMA) or frequency-division multiple access (FDMA) protocols susceptible to reverse engineering. This paper provides a hardware validation of previously proposed techniques for the intentional injection of noise into the phase mapping process of a spread spectrum signal used within a receiver-assigned code division multiple access (RA-CDMA) framework, which decreases an eavesdropper’s ability to directly observe the true phase and reverse engineer the associated PRNG output or key and thus the spreading sequence, even at high SNRs. This technique trades a conscious reduction in signal correlation processing for enhanced obfuscation, with a slight hardware resource utilization increase of less than 2% of Adaptive Logic Modules (ALMs), solidifying this work as a low-power technique. This paper presents the candidate method, quantifies the expected performance impact, and incorporates a hardware-based validation on field-programmable gate array (FPGA) platforms using arbitrary-phase phase-shift keying (PSK)-based spread spectrum signals. Full article

All olive (Olea europaea L.) plant tissues have a high phenolic content. However, the effects of the cultivar and sampling period on the tissue phenolic content remain almost unknown; in addition, the interactions between nutrient uptake and leaf phenol concentrations have not been clarified. This study sampled olive leaves to explore how the cultivar, sampling period, and their interaction affect leaf phenol and nutrient concentrations. Leaves were collected from six cultivars during three seasonal periods: harvest (October; SP1), dormancy (January; SP2), and pruning (March; SP3). Five were Istrian cultivars (‘Bova’, ‘Buža muška’, ‘Buža puntoža’, ‘Istarska bjelica’, ‘Rošinjola’), and one was the Italian cultivar ‘Leccino’. Phenolic profiles in olive leaves were correlated with potassium (K), phosphorus (P), and copper (Cu) concentrations. However, significant correlations between these nutrients and oleuropein, verbascoside, and total phenolic content (TPC) were determined only for ‘Rošinjola’. Oleuropein was the most abundant phenolic compound, while among genotypes, ‘Buža muška’ showed the highest oleuropein levels across all sampling periods, indicating its potential source of oleuropein in olive leaves. Seasonal variations in olive leaf phenolic compounds appear to be strongly influenced by phenological phase, nutrient dynamics, and weather conditions, as confirmed by multivariate analysis across sampling periods and cultivars. The findings emphasise the importance of selecting both an appropriate cultivar and sampling period to maximise the accumulation of olive leaf phenolic compounds. Nevertheless, long-term experimentation on cultivars with a high leaf phenolic potential, like ‘Buža muška’ and ‘Rošinjola’, is necessary in order to develop appropriate farming strategies for maximising phenolic compounds with human or plant health benefits. Full article

As critical components in continental shale systems, the composition and evolution of clay minerals are fundamental to their diagenetic processes and petrophysical properties. The Chang-7 shales in the Ordos Basin exhibit abundant clay mineral content, offering a valuable case study for clay mineral research under moderate diagenetic conditions. This study employed XRD analysis to determine the whole-rock mineralogy, clay mineral composition, and the evolution characteristics of illite-smectite mixed-layer minerals (I/S). Comprehensive clay mineral datasets compiled from 13 newly analyzed wells and existing literature revealed distinct lateral distribution patterns. Total Organic Carbon (TOC) analysis and vitrinite reflectance (R_o) measurements provided systematic quantification of organic matter abundance and thermal maturation parameters in the studied samples. The results reveal that the Chang-7 shale exhibits a characteristic clay mineral assemblage, with I/S (average 44.2%) predominating over illite (34.7%), followed by chlorite (15.6%) and limited kaolinite (5.4%). Frequent volcanic activities provided substantial precursor materials for smectite formation, which actively participated in subsequent illitization processes, while chlorite and kaolinite distributions were predominantly controlled by provenance inputs and sedimentary facies, respectively. Inconsistencies exist between diagenetic stages inferred from I/S mixed-layer ratios and R_o values, particularly in low-maturity samples exhibiting accelerated illitization. The observed negative correlation between TOC content and mixed-layer ratios in Well YY1 and YSC Section samples demonstrates the catalytic role of organic matter in facilitating smectite-to-illite transformation. These results systematically clarify the coupled effects of sedimentary-diagenetic processes, offering new insights into the mutual interactions between inorganic and organic phases during illitization under natural geological conditions. The findings advance the understanding of Chang-7 shale oil and gas systems and offer practical guidance for future exploration. Full article

To address the challenges of dynamic coupling interference and time-frequency feature degradation in current approaches to Ultra-High-Frequency Radio-Frequency Identification (UHF RFID) behavior recognition, this study proposes a novel behavior recognition method integrating multi-feature analysis with a dual-path residual network. The proposed method mitigates interference by using phase difference methods to eliminate signal errors and cross-correlation, as well as adaptive equalization algorithms to decouple interfering signals. To identify the target tags participating in behavioral interactions, we construct a three-dimensional feature space and apply an improved weighted isolated forest algorithm to detect active tags during interactions. Subsequently, Doppler shift analysis extracts behavioral features, and multiscale wavelet-packet decomposition generates time-frequency representations. The dual-path residual network then fuses global and local features from these time-frequency representations for behavioral classification, thereby identifying interaction behaviors such as ‘taking away’, ‘putting back’, and ‘hesitation’ (characterized by picking up, then putting back). Experimental results demonstrate that the proposed scheme achieves behavioral recognition accuracy of 94% in complex scenarios, significantly enhancing the overall robustness of interaction behavior recognition. Full article

Background: This cross-sectional study was conducted among adult Omani patients with a confirmed laboratory diagnosis of COVID-19 to determine the prevalence of dizziness, tinnitus and headache in the pre-, during and post-COVID-19 recovery phases. Methodology: The characteristics and severity of symptoms of dizziness, tinnitus and headache in the above three phases were determined by telephone interviews. The severity of symptoms was recorded using the visual analog score. Results: The total number of patients selected was n = 102 (M/F 50/50%; overall mean age = 33.52 ± 3.6 years). The pre-COVID-19 prevalence of dizziness was 16%, tinnitus 13% and headache 53%. During COVID, the prevalence of dizziness increased to 41%; for tinnitus, it remained the same; and for headache, it increased to 73%. Compared to the lower age group category (30–32 years); the pre-COVID-19 prevalence of dizziness was significantly higher in the 33–40 years age group. The severity of symptoms showed a significant correlation in different phases, pre- and post-COVID-19, for dizziness (r = 0.556), tinnitus (r = 0.714) and headache (r = 0.696), and tinnitus during and post-COVID-19 (r = 0.570). Conclusion: The prevalence of dizziness, tinnitus and headaches was high in COVID-19 patients. All symptoms pre-COVID-19 and during COVID-19 persisted post-COVID-19. Full article

This study examines patterns of artificial intelligence (AI) adoption in Ecuadorian micro and small enterprises (MSEs), with an emphasis on functional diversity across value chain activities. Based on a cross-sectional dataset of 781 enterprises and an entropy-based model, it assesses internal variability in AI use and explores its relationship with strategic perception and dynamic capabilities. The findings reveal predominant partial adoption, alongside high functional entropy in sectors such as mining and services, suggesting an ongoing phase of technological experimentation. However, a significant gap emerges between perceived strategic use and actual functional configurations—especially among microenterprises—indicating a misalignment between intent and organizational capacity. Barriers to adoption include limited technical skills, high costs, infrastructure constraints, and cultural resistance, yet over 70% of non-adopters express future adoption intentions. Regional analysis identifies both the Andean Highlands and Coastal regions as “innovative,” although with distinct profiles of digital maturity. While microenterprises focus on accessible tools (e.g., chatbots), small enterprises engage in data analytics and automation. Correlation analyses reveal no significant relationship between functional diversity and strategic value or capability development, underscoring the importance of qualitative organizational factors. While primarily descriptive, the entropy-based approach provides a robust diagnostic baseline that can be complemented by multivariate or qualitative methods to uncover causal mechanisms and strengthen policy implications. The proposed framework offers a replicable and adaptable tool for characterizing AI integration and informing differentiated support policies, with relevance for Ecuador and other emerging economies facing fragmented digital transformation. Full article

Identifying reliable geochemical signals that reflect crustal stress evolution remains a major challenge in earthquake monitoring. Spring fluids, due to their deep circulation and rapid response, provide an important window into fault-zone processes. This study presents three years (May 2022–March 2025) of hourly hydrogen gas (H₂) concentration monitoring in spring gases from the Muji Basin on the northern Pamir Plateau, integrated with meteorological and seismic data. H₂ concentrations exhibited a stable diurnal pattern, positively correlated with water and air temperatures and negatively correlated with atmospheric pressure. Short-term anomalies during seismically quiet periods may reflect a combination of temperature-dependent solubility effects and transient degassing caused by localized gas accumulation and sudden release under heterogeneous fault and aquifer conditions. During seismically active phases, sustained increases in H₂ concentrations were also recorded; however, such anomalies did not consistently precede earthquakes, instead reflecting broader phases of tectonic instability and episodic fault-zone degassing. These findings highlight the potential of long-term H₂ monitoring to improve our understanding of the coupling between crustal stress, fluid transport, and degassing processes in tectonically active regions. Full article

Chlorogenic acid (CGA)-rich extracts from Eucommia ulmoides Oliver (CAE) are known for their gut health and antioxidant benefits in livestock. This study examines the effects of CAE supplementation during the peri-implantation period on sow reproductive performance and the gut microbiota. Sixty Dongliao black sows were randomized to receive either no supplementation (control) or CAE at 600 or 2000 mg/kg daily from gestation day −5 through day 15. High-dose CAE intake significantly increased total antioxidant capacity (T-AOC), superoxide dismutase (SOD), catalase (CAT), immunoglobulin A (IgA), and immunoglobulin M (IgM) levels in sow serum but decreased malondialdehyde (MDA) levels. Fecal short-chain fatty acids (SCFAs) also increase significantly. These changes correlate with improved reproductive performance, including a larger litter size, higher numbers of live-born piglets, a greater individual birth weight of live-born piglets, a higher total litter birth weight of live-born piglets, and a lower mortality rate. 16S rRNA sequencing of the fecal microbiota revealed that CAE markedly altered microbial diversity and composition, reducing the abundance of potentially harmful bacteria but increasing the abundance of beneficial bacteria. In conclusion, supplementation with CAE during the peri-implantation phase can reduce oxidative stress, alter the gut microbiota composition, and improve sow reproductive performance, thus potentially increasing breeding farm profitability. Full article

The gut microbiome has emerged as a critical determinant of immune-checkpoint inhibitor (ICI) efficacy. A narrative review of 95 clinical studies (2015–2025) shows that patients with greater gut microbial diversity and relative enrichment of commensals such as Akkermansia, Ruminococcus, and other short-chain fatty acid producers experience longer progression-free and overall survival, particularly in melanoma and non-small-cell lung cancer. Broad-spectrum antibiotics given within 30 days of ICI initiation and over-the-counter mixed probiotics consistently correlate with poorer outcomes. Early phase I/II trials of responder-derived fecal microbiota transplantation in ICI-refractory melanoma achieved objective response rates of 20–40%, while pilot high-fiber or plant-forward dietary interventions improved immunologic surrogates such as CD8⁺ tumor infiltration. Machine-learning classifiers that integrate 16S or metagenomic profiles predict ICI response with an area under the ROC curve of 0.83–0.92. Methodological heterogeneity across sampling, sequencing, and clinical endpoints remains a barrier, underscoring the need for standardization and larger, well-powered trials. Full article

The school and university periods represent a critical phase in individuals’ cognitive, emotional, and behavioural development. Numerous lifestyle factors can influence executive functions and high-level cognitive processes crucial for learning and behavioural adaptation. Sleep and physical activity are two variables that influence executive functions and that could be modified through behavioural interventions. Numerous scientific studies suggest that adequate sleep quality and duration are linked to improved cognitive performance. Similarly, regular physical exercise correlates with neurocognitive benefits. However, these two aspects of lifestyle are often compromised in students, resulting in attention difficulties, reduced working memory, and difficulty in inhibitory control, all aspects of non-optimal executive functioning. Even though the scientific literature separately explores “sleep and executive functions” and “physical activity and executive functions”, few studies have integrated the two factors to assess their combined effect on executive functioning, particularly within the student population. The present narrative review aims to outline an integrated theoretical framework of existing scientific literature and to identify any knowledge gaps that may guide future research. It could provide relevant insights for designing preventive or promotional interventions to enhance students’ cognitive performance and mental well-being. Full article

Traumatic brain injury (TBI), a leading cause of mortality and disability, recognizes a primary, immediate injury due to external forces, and a secondary phase that includes inflammation that can lead to complications such as the post-traumatic confusional state (PTCS), potentially impacting long-term neurological recovery. An earlier identification of these complications, including PTCS, upon admission to intensive rehabilitation units (IRU) could possibly allow the design of personalized rehabilitation protocols in the immediate post-acute phase of moderate-to-severe TBI. The present study aims to identify potential biomarkers to distinguish between TBI patients with and without PTCS. We analyzed cellular and molecular mechanisms involved in neuroinflammation (IL-6, IL-1β, IL-10 cytokines), neuroendocrine function (norepinephrine, NE, epinephrine, E, dopamine), and neurogenesis (glial cell line-derived neurotrophic factor, GDNF, insuline-like growth factor 1, IGF-1, nerve growth factor, NGF, brain-derived growth factor, BDNF) using enzyme-linked immunosorbent assay (ELISA), comparing results between 29 TBI patients (17 with PTCS and 12 non-confused) and 34 healthy controls (HC), and correlating results with an actigraphy-derived sleep efficiency parameter. In TBI patients compared to HC, serum concentration of (1) pro-inflammatory IL-1β cytokine was significantly increased while that of anti-inflammatory IL-10 cytokine was significantly decreased; (2) NE, E and DA were significantly increased; (3) GDNF, NGF and IGF-1 were significantly increased while that of BDNF was significantly decreased. Importantly, IL-10 serum concentration was significantly lower in PTCS than in non-confused patients, correlating positively with an improved actigraphy-derived sleep efficiency parameter. An anti-inflammatory environment may be associated with better prognosis after TBI. Full article

This study aims to analyze the relationships between concerns and sentiments of stakeholders and the drought stage in a semi-arid region of Ceará from Language Technologies based on Artificial Intelligence. The dataset comprises 36 meeting minutes of water management bodies (2007–2024), of which 17 correspond to dry periods and 19 to normal periods (reservoir volume > 50%). Natural Language Processing (NLP) techniques were applied to generate word clouds, and sentiment analysis was performed using a Large Language Model (Llama 3.2, 3B). Sentiment scores were compared with reservoir volume data. Results show that both perceptions and themes differed between drought and normal phases, with higher water availability coinciding with more positive sentiments. A moderate positive correlation was found between sentiment and reservoir volume (r = 0.53, p = 0.00095, 95% CI [0.24, 0.73]). Statistical tests confirmed differences between periods (Welch’s t-test, p = 0.0018; Mann-Whitney, p = 0.0039). Box-plot analyses indicated that over 75% of sentiments were positive in normal phases, while about 65% were negative in drought phases. These findings highlight the sensitivity of human perceptions to hydrological conditions and point to the potential of LLMs as innovative instruments for integrating qualitative data into complex socio-environmental analyses. Full article

For arid and semi-arid regions like Xinjiang, analyzing the spatiotemporal patterns of September precipitation and their atmospheric circulation teleconnections is crucial for ecosystem preservation. This research examined how the August Asian–Pacific Oscillation (APO) influenced the September precipitation patterns in northern Xinjiang. The results show that the thermal anomalies resulting from the August APO exhibited persistence into September, triggering atmospheric circulation anomalies that ultimately affected the precipitation patterns in northern Xinjiang, with a notable negative correlation. The positive (negative) August APO phase corresponded to reduced (increased) mid-tropospheric geopotential heights over Asia and the Arabian Sea, significantly enhancing anomalous cyclonic (anticyclonic) circulation patterns in these regions. These circulation patterns induced anomalous northerlies (southerlies) over northern Xinjiang and the region from eastern Iran to the Persian Gulf, thereby reducing (increasing) the moisture transport from the Arabian Sea. Furthermore, the anomalous divergence (convergence) of cold/warm air masses and subsidence (ascent) motions exacerbated (enhanced) these effects, ultimately suppressing (enhancing) the September precipitation in northern Xinjiang. Full article

Background: Endometriosis is a chronic, estrogen-dependent inflammatory and immunological disease, with chronic pain being its predominant clinical manifestation. This condition significantly impairs quality of life and is frequently associated with depressive and anxiety symptoms, further exacerbating social and occupational dysfunction in affected women. The aim of this study was to assess the relationship between chronic pain in patients with endometriosis and the severity of depressive symptoms. Methods: A retrospective analysis was conducted on the medical records of 60 women of reproductive age treated at the Tomaszewski Medical Center in Białystok between 2023 and 2024. Pain intensity was evaluated using the Visual Analogue Scale (VAS) and the McGill Pain Questionnaire, while depressive symptoms were assessed with the Beck Depression Inventory (BDI). Results: Statistical analyses included the Student t-test, Wilcoxon signed-rank test, chi-square test, and Shapiro–Wilk test, with significance set at p < 0.05. Pain intensity was significantly higher during menstruation (M = 7.23) compared to non-menstrual phases of the cycle (M = 4.55; p < 0.001). Accompanying symptoms included sleep disturbances, reduced activity, and gastrointestinal complaints. Depressive symptoms were also more severe during menstruation (M = 30.12) than during the rest of the cycle (M = 22.15; p < 0.001). A significant association between pain severity and depressive symptoms was observed during menstruation (χ²(4) = 12.89; p = 0.012), but not outside this phase. Conclusions: (1) Pain in endometriosis is chronic and cyclic in nature. (2) Depressive symptoms are common but may be masked by nonspecific somatic complaints. (3) Pain intensity strongly correlates with the severity of depressive disorders, particularly during menstruation. (4) The coexistence of depression significantly impairs patient functioning. (5) Effective management of endometriosis should integrate gynecological treatment with psychological support and psychiatric care when necessary. Full article