Search Results (1,885)

This study details the validation of a novel microbead beating extraction (MBE) technique for the analysis of polycyclic aromatic compounds (PACs) in sediments. The method’s performance was evaluated against international analytical validation criteria, including trueness, precision, measurement uncertainty and robustness. Limits of detection and quantitation were consistently low (≤6.5 and 21 ng g⁻¹, respectively), trueness for the majority of analytes fell within accepted performance criteria, and repeatability values for most analytes were generally <10%. Analytical data confirm the method’s reliability, with more than 80% of certified analytes in two certified reference materials (CRMs) meeting the satisfactory z-score (∣z∣ ≤ 2.0). Furthermore, the method’s inter-laboratory repeatability, as measured by HorRat values, fell within the range recommended by the Association for Official Analytical Chemist for most analytes, and combined measurement uncertainties showed no statistical difference from the certified uncertainties of the CRMs. Incorporating an in situ cleanup step enabled the MBE method to substantially reduce extraction times (<15 min) and reduces solvent consumption by ~60% compared with conventional pressurize fluid extraction while maintaining good quality data objectives. By meeting or exceeding well-established metrics for good laboratory performance, the MBE method demonstrates reliability, efficiency, and a greener approach for the routine analysis of PACs in sediments. Full article

Community-oriented policing (COP) has long been hailed as an approach to enhancing community trust in police, addressing community problems proactively rather than reactively, and fostering police-community engagement. However, some law enforcement agencies experience difficulty in translating the broad philosophy of COP into a practical and actionable strategy. Agencies cannot expect to fulfill COP objectives without a structured plan and accountability for achieving this goal. Therefore, drawing on existing themes for operationalizing proactive community engagement, this paper brings current research and best practices together to present a set of evidence-based strategies for COP foot and bike patrols. We highlight relevant considerations and tips that may be underscored in the minutiae of implementation within the COP foot and bike patrol process, yet remain critical to success. By operationalizing COP foot and bike patrols at several stages, the authors aim to assist agencies in striving for more than just symbolic or temporary approaches to COP. Full article

The accelerating adoption of electric vehicles (EVs) is intensifying pressure on urban power grids, particularly during evening peak hours. Existing smart-charging frameworks remain constrained by centralized control, static pricing, and limited integration of predictive intelligence. This study presents SMARGE, a hybrid AI–Blockchain smart charging platform that combines load forecasting, dynamic pricing, and cryptocurrency-based incentives to enhance decentralized EV energy management in Gaziantep Province. An ensemble of forecasting models (SARIMA, LightGBM, N-BEATS, and TFT) predicts 2026 hourly electricity demand, while an adaptive inverse-sigmoid pricing mechanism generates real-time incentives and disincentives for EV charging behavior. A fuzzy logic-based behavioral model simulates both unmanaged and managed charging across three scenarios. Results show that managed charging reduces peak load by 22.43%, shifts 67.45% of energy demand to off-peak periods, and achieves 94.86% charging fulfillment under constrained grid conditions. The blockchain layer—implemented through a custom ERC-20 token (SMARGE) on the Ethereum Sepolia testnet—enables secure, transparent, and low-cost microtransactions with an average confirmation time of 0.63 s. These findings demonstrate that tightly coupling AI forecasting with tokenized blockchain incentives can improve grid stability, lower operational costs, and enhance user autonomy in a scalable and decentralized manner. While promising, the study is limited by assumptions of synthetic user behavior and ideal communication conditions; future work will validate the platform in real-world pilot deployments and across different urban regions. Full article

Postural orthostatic tachycardia syndrome (POTS), characterized by a rise in heart rate of at least 30 beats per minute from supine to standing position without accompanying orthostatic hypotension, is one of the most common autonomic disorders with disabling cardiovascular and neurologic manifestations. Hormonal influence has been long recognized by the disorder predominantly affecting women of reproductive age, with frequent onset around menarche, exacerbation of symptoms before or during menses, and pregnancy being one of POTS triggers. Hormone replacement therapy (HRT) and menopause in women with POTS have not been studied, but issues surrounding HRT are highly relevant as women with POTS transition from reproductive age to menopause. Given a rising prevalence of POTS due to post-COVID onset and the US Food and Drug Administration recently removing the black box warning on estrogen-containing HRT formulations, informed decisions and risk assessments regarding HRT use in women with POTS are warranted. In this narrative review, existing studies on hormones and POTS and its common comorbidities are reviewed, and key points in decision-making on the use of HRT in women with POTS are discussed. In summary, for women with significant menopausal symptoms and/or exacerbation of POTS during the peri- or postmenopausal period, using some forms of HRT for treatment of menopausal symptoms may be considered, accounting for comorbidities, cardiovascular risk and other factors. Vaginal estrogen appears to be safe for most women while transdermal estrogen and micronized progesterone can be utilized for significant menopausal symptoms, although outcomes of their long-term use are unknown. Full article

Music is more than just entertainment. It is a complex auditory stimulus that engages various cognitive processing systems. Accordingly, natural music-listening patterns may reveal insights into individual differences in general cognitive ability (GCA). In this study (N = 185), we used real-world smartphone-based music-listening records collected over five months to explore this question. We quantified participants’ listening habits (e.g., listening durations) and music preferences based on audio characteristics (e.g., tempo, mode) and lyrical characteristics (e.g., positive emotion words, affiliation words) of the songs they had listened to. These strictly behavioral features were used to predict GCA scores using linear LASSO regression and nonlinear random forest models. Out-of-sample cross-validation indicated modest predictive performance, with only the random forest model detecting small but reliable associations between music-listening behavior and GCA. Interpretable machine learning analyses showed that lyrics-based preferences were the most informative feature group, followed by listening habits, whereas audio characteristics contributed little predictive value. We discuss how these findings offer initial evidence that cognitive ability may be reflected, albeit subtly, in micro-patterns of everyday, non-achievement-related behavior, and outline conceptual and methodological challenges for future work using digital behavioral data to complement traditional cognitive assessment. Full article

Background/Objectives: Domestic violence against women is a widespread global health issue profoundly affecting victims, their families, and society. This study aimed to assess the prevalence, patterns, risk factors, and health sequelae of domestic violence among females during reproductive age in Sharkia governorate, Egypt. Methods: A cross-sectional descriptive study was conducted from April to December 2024. A total of 379 females of reproductive age (15–49 years) were recruited using simple random sampling from secondary schools and Maternal and Child Health centers affiliated with the Ministry of Health. Data were collected using a structured interview questionnaire covering sociodemographic characteristics, violence exposure (physical, psychological, economic, and sexual), risk factors, causes, severity, perpetrators, and consequences. Results: The overall prevalence of domestic violence was 88%. Psychological violence was the most common form (78%), followed by physical violence (63%), and economic violence (43%). Insults were the predominant form of verbal abuse, while slapping and beating were the most common manifestations of physical violence. Husbands were identified as the primary perpetrators across all violence types. Major risk factors included cigarette use by the abuser (47%), alcohol and drug use (14%), and psychological problems (11%). The most frequently reported consequences were anxiety, fear, and depression (82%), followed by insomnia (55%) and seeking separation (49%). Conclusions: Domestic violence against women of reproductive age is highly prevalent in the study setting, with significant physical and psychological consequences. Comprehensive interventions, including awareness campaigns, legal enforcement, women empowerment programs, and healthcare provider training, are urgently needed to address this critical public health issue. Full article

Morphine is widely used as an analgesic in vertebrates, yet its cardiorespiratory safety and effective therapeutic range remain poorly explored in fish. This study investigated the dose-dependent effects of morphine on cardiac and respiratory parameters of juvenile tambaqui (Colossoma macropomum). Juveniles (25.95 ± 4.08 g) were randomly assigned to control, sham (0.9% saline) or morphine groups (24, 28, 32, 36 and 40 mg kg⁻¹, i.p.). Electrocardiogram (ECG) recordings were used to assess heart rate (HR), PQ, RR and QT intervals, and QRS amplitude, while opercular beat rate (OBR) and opercular beat intensity (OBI) were measured to evaluate respiratory responses. Morphine induced a significant dose-dependent bradycardia and QT prolongation, without affecting QRS amplitude or conduction integrity. Respiratory frequency and intensity also decreased with increasing doses, with responses plateauing above 32 mg kg⁻¹. The EC₅₀ for HR reduction was 27.18 mg kg⁻¹, aligning with a safe therapeutic range of 24–32 mg kg⁻¹. By establishing this dose–response dynamic, the study provides the first characterization of a physiologically safe therapeutic window of morphine in tambaqui and highlights its safety profile for cardiorespiratory parameters. Moreover, the present results demonstrate that the opioid system of juvenile tambaqui is functionally developed, providing a physiological basis for future studies on nociception and analgesic efficacy, with relevance to welfare-oriented practices in aquaculture. Full article

Motion artifacts corrupt wearable ECG signals and generate false alarms of arrhythmias, limiting the clinical adoption of continuous cardiac monitoring. We present a dual-stream deep learning framework for motion-robust binary arrhythmia classification through multi-modal sensor fusion and multi-SNR training. ResNet-18 processes ECG spectrograms, while CNN-BiLSTM encodes accelerometer motion patterns; attention-gated fusion with gate diversity regularization adaptively weights modalities based on signal reliability. Training in MIT-BIH data augmented at three noise levels (24, 12, 6 dB) enables noise-invariant learning with successful generalization to unseen conditions. The framework achieves 99.5% accuracy under clean signals, gracefully degrading to 88.2% at extreme noise (−6 dB SNR)—a 46% improvement over training with single-SNR. The high gate diversity ($\sigma >0.37$) confirms adaptive context-dependent fusion. With a 0.09% false positive rate and real-time processing (238 beats/second), the system provides practical continuous arrhythmia screening, establishing the foundation for hierarchical monitoring systems where binary screening activates detailed multi-class diagnosis. Full article

Impaired glucose metabolism, a known precursor to type 2 diabetes, is associated with dysregulation of the autonomic nervous system. To assess such autonomic states, consumer wearable devices provide continuous, non-invasive physiological monitoring and may capture autonomic signatures related to metabolic status. This exploratory study examined whether dynamic features of heart rate (HR) and heart rate variability (HRV) during sleep—derived from a consumer wrist-worn device (Fitbit)—are associated with glucose metabolism status in free-living adults. We analyzed 189 nights from 18 participants (7 participants in the higher-glycemic-risk group, estimated glycated hemoglobin (HbA1c) ≥ 5.5%; 11 participants in the lower-glycemic-risk group, estimated HbA1c < 5.5%). From 28 candidate HR/HRV variables, Elastic Net regression ($\alpha =0.5$) was applied to identify features associated with nocturnal mean glucose. Fourteen features retained non-zero coefficients; notably, dynamic features capturing overnight trends and variability patterns showed stronger associations than conventional static mean values. The nocturnal trends of within-window standard deviation and variance of $ln\left(\mathrm{RMSSD}\right)$ (root mean square of successive differences between consecutive RR intervals, estimated here from PPG-derived inter-beat intervals; RMSSD) emerged as prominent candidates, alongside HR variability indices. Independent between-group comparisons further confirmed that two dynamic HRV features differed significantly between the lower- and higher-glycemic-risk groups (both $\mathit{p}<0.05$; Cohen’s $\left|d\right|>1.1$). Specifically, the lower-glycemic-risk group exhibited decreasing overnight trends in HRV variability, consistent with progressive autonomic stabilization during sleep. In contrast, the higher-glycemic-risk group showed increasing variability trends, suggestive of persistent autonomic instability. These directional patterns are consistent with prior evidence linking autonomic dysfunction to impaired glucose metabolism. We characterize these findings as hypothesis-generating. The identified dynamic HR/HRV features represent physiologically plausible candidate correlates of glycemic status and warrant confirmatory investigation in larger, independent cohorts with laboratory-measured HbA1c. More broadly, this work highlights the potential of widely available, consumer-grade wearable devices to move beyond activity tracking and support continuous, real-world assessment of cardiometabolic health, thereby expanding their utility in everyday health monitoring and preventive medicine. Full article

Non-contact measurement plays a crucial role in monitoring the heart rate of preterm and low birth weight infants in the neonatal intensive care unit (NICU). Addressing the challenges of weak heartbeat signals easily overwhelmed by noise in non-contact heart rate detection for these neonates, this paper proposes a millimeter-wave radar-based heart rate detection method using adaptive subband variable step-size least mean square (LMS) filtering. The innovative approach divides the chest echo signal into multiple subbands, employing an error-based variable step-size update strategy in each subband. By utilizing the abdominal signal as a reference, the heartbeat information is enhanced through adaptive filtering, and the results from various subbands are fused. The heart rate estimation is achieved by combining the fused results with time-frequency analysis using wavelet transform. Experimental results on data collected from multiple preterm infants in the NICU demonstrate that the proposed algorithm can reduce the root mean square error (RMSE) of preterm infant heart rate estimation to below 5 Beats Per Minute (BPM), providing a novel solution for the application of millimeter-wave radar in NICU heart rate monitoring. Full article

This research investigates the impact of augmented and virtual reality (AR/VR) and AI-enabled chatbots, both individually and collectively, on consumer engagement of e-commerce platforms. Moreover, this research examines the mediating effects of perceived utility, ease of use, and enjoyment and the moderating effects of product type and technology readiness, respectively. By applying the theories of Technology Acceptance Model (TAM) and Stimulus–Organism–Response (S-O-R), this research proposed this theoretical framework and adopted a mixed-method research method. This research collected its empirical findings from 486 respondents who had utilized chatbots and AR/VR technology on three of China’s most popular e-commerce platforms, including Taobao, JD.com, and Pinduoduo. Structural equation modeling was utilized for hypothesis testing, and semi-structured interviews on 30 participants were used for validation of empirical findings. Results reveal that both AI chatbot features (β = 0.35, p < 0.001) and AR/VR technologies (β = 0.42, p < 0.001) significantly enhance consumer engagement, with AR/VR demonstrating stronger effects. Perceived enjoyment emerged as the strongest mediator (AI: β = 0.14; AR/VR: β = 0.18), surpassing traditional utilitarian factors. Technology readiness significantly moderated these relationships, with high-readiness consumers showing substantially stronger responses (AI: β = 0.45; AR/VR: β = 0.52). Experience goods amplified technology effects compared to search goods. Multi-group analysis revealed platform-specific variations, while robustness checks identified diminishing returns for AI chatbots but not AR/VR technologies. This research contributes to digital marketing and information systems literature by providing empirical evidence of differential technology impacts on engagement, highlighting the dominance of hedonic over utilitarian pathways in consumer technology adoption. The findings offer practical guidance for e-commerce platforms in optimizing technology investments and designing engagement strategies. Full article

Background/Objectives: One of the topics of electrocardiographic risk factor studies is investigations of beat-to-beat QT interval variability. The seminal study that reported QT variability as a prognostic risk factor introduced the so-called QT variability index (QTVi). QTVi quantification relies not only on the variance of QT intervals but also on correction factors, including RR interval variance, heart rate, and overall QT interval duration. This study investigated the influence of all the measured factors on QTVi values. Methods: Long-term electrocardiograms (ECGs) were obtained from 251 healthy subjects (mean age 33.6 ± 9.1 years, 108 females) during repeated postural tests that involved supine, sitting, and standing positions maintained for 10 or 15 min. During each position, a 5-min ECG segment with a stable heart rate and without any ectopic disturbances was found. In these segments, standard deviations of normal-to-normal RR (NN) interval durations (SDNN) and of beat-to-beat QT interval durations (SDQT) were measured together with the means of NN and QT intervals. QTVi was subsequently calculated. For each subject, results obtained during each postural position were averaged. Results: In multivariable regression models, evaluated separately in female and male sex-subgroups of the population, QTVi values were significantly dependent on SDQT, SDNN, and mean NN intervals (all p < 0.001) but practically independent of mean QT interval durations. Conclusions: QTVi is significantly influenced by factors that are unrelated to the beat-to-beat changes in QT interval durations. This needs to be considered when interpreting QTVi values. In future studies, multivariable statistical models are needed to ensure that QTVi findings are independent of associated heart rate variability indices. Full article

Ventricular–arterial coupling (VAC) describes the dynamic interaction between left ventricular (LV) systolic elastance and the time-varying elastance/impedance of the arterial tree, a relationship that governs the instantaneous generation of aortic flow and ultimately cardiac output. VAC, typically expressed as the ratio of effective arterial elastance (Ea) to LV end-systolic elastance (Ees), has provided valuable mechanistic and prognostic insights, but is limited by its lumped, largely steady-state nature and by the need for pressure–volume modeling or complex surrogate formulas. Contemporary time-domain and wave-intensity approaches have underscored that the shape of proximal aortic pressure–flow waveforms encodes rich beat-by-beat information about ventricular–arterial interaction and energy transfer. Doppler echocardiography of the ascending aorta provides a readily available, high-temporal resolution measure of proximal aortic flow that is already used to quantify stroke volume, cardiac output and valvular lesions. We propose that proximal aortic flow, as recorded by Doppler echocardiography, may serve as a clinically practical proxy for beat-by-beat VAC, reflecting the instantaneous matching of ventricular and aortic elastances, which regulates the ejected flow towards peripheral tissues according to metabolic needs. Full article

Background: Benign paroxysmal positional vertigo (BPPV) is the most common peripheral vestibular disorder and most frequently involves the posterior semicircular canal (PSC). Atypical apogeotropic variants of PSC-BPPV may present with pure down-beating positional nystagmus, mimicking contralateral anterior semicircular canal involvement and resulting in diagnostic and therapeutic uncertainty. Objective: To assess the effectiveness of the Bascule/Pendular maneuver in managing patients with pure down-beating positional nystagmus and suspected apogeotropic PSC-BPPV. Methods: A total of 178 patients presenting with pure down-beating positional nystagmus without a torsional component were evaluated using a standardized diagnostic protocol under video-Frenzel goggle monitoring. All patients underwent the Bascule/Pendular maneuver, a modification of the classical Semont maneuver designed to mobilize otoconial debris along the vertical canal planes (Left Anterior–Right Posterior and Right Anterior–Left Posterior), regardless of precise lateralization. Conversion of nystagmus from the apogeotropic to the geotropic variant was considered the primary outcome. Results: The maneuver was well tolerated, with no procedural interruptions or complications. Immediate conversion to the geotropic variant was achieved in 86 patients (48.3%) after a single maneuver. In the remaining patients, successful conversion was obtained after additional maneuvers, most commonly following a second application on the contralateral plane. Once geotropization was achieved, all patients were successfully treated using a standard posterior canal repositioning maneuver. Conclusions: The Bascule/Pendular maneuver is a practical and effective approach for patients presenting with pure down-beating positional nystagmus and suspected apogeotropic PSC-BPPV. By facilitating conversion to the geotropic form, it allows prompt treatment with conventional repositioning maneuvers and may represent a useful first-line strategy in atypical BPPV presentations. Full article

Background/Objectives: Patients with WPW syndrome have a risk of sudden cardiac death that can be assessed using an electrophysiological study. In symptomatic patients, the preferred route is intracardiac, whereas in asymptomatic children, transesophageal. Our study aimed to evaluate the risk using a transesophageal study, considering a threshold age of 12 years for sedation. Methods: We investigated 41 asymptomatic WPW children with a mean age of 12.5 ± 4.4 years (range 1 to 18 years old), with 48.8% being male. We determined three values: (1) the accessory pathway effective refractory period (APERP), (2) the minimal cycle length demonstrating 1:1 conduction through the accessory pathway, and (3) the shortest RR interval between two consecutive pre-excited beats during atrial fibrillation. Results: Children under 12 years had a mean age of 7.5 ± 2.5 years, while those over 12 years had a mean age of 15.5 ± 1.9 years. Sedation was administered exclusively to children under 12 years of age. Orthodromic reentrant tachycardia was induced in four children, and atrial fibrillation was induced in 14 children. Comparing the group under 12 with the group over 12, the mean APERP was 296 ± 38 ms vs. 286 ± 45 ms (p = 0.48), the average 1:1 conduction over the accessory pathway was 287.3 ± 41 ms vs. 282 ± 46 ms (p = 0.71), and the average shortest pre-excited RR interval during atrial fibrillation was 280 ms vs. 262 ms years (p = 0.75). Conclusions: Asymptomatic children under 12 years of age showed a lower incidence of inducible atrial fibrillation. They had accessory pathways with reduced risk, except one, and no children under 12 years underwent catheter ablation. Full article