Search Results (145)

This study investigated the effects of lemon verbena extract (LVE) on sleep regulation using both a pentobarbital-induced sleep model and an EEG-based sleep assessment model in mice. To elucidate its potential mechanisms, mice were randomly assigned to five groups: control, positive control (diazepam, 2 mg/kg b.w.), and three LVE-treated groups receiving 40, 80, or 160 mg/kg b.w. via oral administration. In the pentobarbital-induced sleep model, mice underwent a two-week oral administration of LVE, followed by intraperitoneal pentobarbital injections. The results demonstrated that LVE significantly shortened sleep latency and prolonged sleep duration compared to the control group. Notably, adenosine A1 receptor expression, both at the mRNA and protein levels, was markedly upregulated in the brains of LVE-treated mice. Furthermore, LVE’s administration led to a significant increase in the mRNA expression of gamma-aminobutyric acid type A (GABA_A) receptor subunits (α2 and β2) in brain tissue. In the electroencephalography (EEG)/electromyogram (EMG)-based sleep model, mice underwent surgical implantation of EEG and EMG electrodes, followed by one week of LVE administration. Quantitative EEG analysis revealed that LVE treatment reduced wakefulness while significantly enhancing REM and NREM sleep’s duration, indicating its potential sleep-promoting effects. These findings suggest that LVE may serve as a promising natural sleep aid, improving both the quality and duration of sleep through the modulation of adenosine and GABAergic signaling pathways. Full article

This paper presents an optimized 868 MHz low-noise amplifier (LNA) based on a bipolar junction transistor (BJT), specifically designed for wake-up receivers operating in the sub-GHz band. The proposed LNA achieves low noise, high gain, and good impedance matching while consuming only $3.2$ mA from a $3.3$ V supply, resulting in a total power consumption of $10.56$ mW. Designing efficient sub-GHz LNAs for low-power applications involves a careful balance between multiple performance metrics. Higher gain typically requires increased biasing current, which can raise power consumption, while achieving a low noise figure often conflicts with input-matching constraints. The presented design addresses these trade-offs by leveraging the BFP740 BJT and employing a stub-based microstrip matching network to simultaneously optimize the gain, noise figure, and input–output matching. Simulation results, using both external lumped elements and microstrip techniques, show a forward gain ($S_{21}$) of $15.2$ dB at 868 MHz, with an input reflection coefficient ($S_{11}$) of $-6.9$ dB and an output reflection coefficient ($S_{22}$) of $-6.3$ dB. The amplifier achieves a minimum noise figure of approximately $1.77$ dB, which is notably low for this frequency band. These results demonstrate that the proposed LNA offers a compact, energy-efficient, and cost-effective solution, ideally suited for always-on, low-power wireless applications such as Internet of Things (IoT) devices and wireless sensor networks. Full article

Background: Nursing leadership is associated with a host of benefits for patient outcomes and health services. Pressures relating to the COVID-19 pandemic saw many relatively inexperienced nurses thrust into leadership roles, often with little notice. In response to this situation, The Tasmanian Health Service—Hospitals South created the Leadership Excellence in Practice Program (L-EPP) as a way of developing the leadership skills of its nurses and midwives. This study aimed to describe the development of the L-EPP and to evaluate it from the perspective of its participants and their peers. Methods: A longitudinal mixed-methods study was conducted using data from the first two offerings of the L-EPP. The L-EPP employs a blended learning model comprised of e-learning, work-integrated learning and face-to-face workshops. Surveys targeting the participants’ leadership abilities were completed at numerous time points by participants themselves, their peers, and their managers. Results: A total of 57 participants completed the program. Workshop surveys indicated that these sessions were generally well-received by participants. Significant improvements were observed in several domains of leadership, from the perspective of the participants themselves and their peers and managers. Conclusions: The program was well-received by its participants, and would serve as a useful template for other organisations seeking to build the leadership capacity of their nurses and midwives. This may be particularly useful to organisations seeking to upskill their existing staff and prevent further attrition of nurses and midwives in the wake of the pandemic. Full article

Background/Objectives: Primary insomnia is characterized by persistent sleeplessness that is not caused by medical, psychological, or environmental factors. It is defined by difficulty initiating or maintaining sleep for at least one month, leading to significant distress or impairment in daily functioning. This randomized, crossover, double-blind, placebo-controlled clinical trial aimed to assess the efficacy and tolerability of a Scutellaria lateriflora L. extract-based food supplement in subjects with mild to moderate primary insomnia. Methods: A total of 66 participants, aged 18–70 years, were randomly allocated into two groups (1:1 allocation ratio) and received either the food supplement (400 mg/day) or a placebo for 56 days, separated by a 28-day washout period. The clinical effectiveness of the food supplement was assessed using the Pittsburgh Sleep Quality Index (PSQI) as the primary outcome measure. Secondary outcomes included sleep-wake cycle parameters (sleep onset latency, sleep efficiency, and total sleep time) and a Visual Analog Scale (VAS). Results: A significant improvement in sleep-wake balance following supplementation with S. lateriflora, as reflected by enhanced scores in both primary and secondary outcomes, was observed. Furthermore, none of the participants reported adverse effects from the food supplement. Conclusions: Overall, these findings suggest that a S. lateriflora extract-based food supplement is a safe and effective strategy for restoring the sleep-wake cycle and improving quality of life in individuals with primary insomnia. Full article

Objective: We aim to determine the association between insomnia symptoms and mental health in females and males and compare mental health care utilization and perceived barriers between females and males with insomnia symptoms. Methods: This is a cross-sectional study using the National Health Interview Survey. Insomnia symptoms included self-reported “trouble falling asleep”, ‘trouble staying asleep”, and “waking up feeling not well rested”. Mental health included self-reported anxiety and depression. Multivariable logistic regression was used to assess the association between insomnia symptoms and mental health in females and males. Results: A total of 26,691 adults were included. The mean age was 48.2 years; 51.4% were females, and 48.6% were males. Insomnia symptoms were associated with anxiety and depression for both females and males. These associations were stronger in younger adults (<50 years) than older adults (≥50 years). Females with insomnia symptoms were more likely to receive mental health care (OR = 1.7; 95% CI = 1.53, 1.87) but also to delay mental health care because of its cost (OR = 1.96; 95% CI: 1.67, 2.30) or needed mental health care but did not get it because of the cost (OR = 2.14; 95% CI: 1.82, 2.50) than their males counterpart. Conclusions: Insomnia symptoms were associated with mental health in females and males, being stronger in younger adults than older adults, with gender differences in mental health care utilization and financial barriers to mental health care. Holistic approaches involving prevention and better access to mental health care are warranted. Full article

Objectives: The present scoping review aims to map the existing evidence on psychological and behavioral interventions targeting patients with narcolepsy type 1 and type 2. Methods: A literature search was performed using the databases Scopus, PubMed, and PsycINFO. Studies were included if they (1) employed randomized controlled trials, non-randomized trials, or quasi-experimental studies; (2) were published in English; (3) were published in peer-reviewed journals; (4) examined the impact of psychological interventions on psychopathological (primary outcomes) and narcolepsy-related symptoms (secondary outcomes); and (5) involved patients with a diagnosis of narcolepsy using recognized diagnostic criteria regardless of whether they were receiving pharmacological treatment or were untreated. No restrictions were imposed on the publication date to comprehensively map the available evidence. Data were extracted to address the review aims and presented as a narrative synthesis. Results: The database search yielded six studies. Treatment options for individuals with narcolepsy encompass psychological and behavioral interventions, such as telehealth interventions, meditation/relaxation therapy, and scheduled napping. The primary outcomes were daytime sleepiness, wakefulness maintenance, sleep attacks, the severity of symptoms of narcolepsy, sleep paralysis episodes, depression, and psychological functioning. The secondary outcomes were sleep-problem-related quality of life, sleep inertia, and sleep quality. The psychological and behavioral interventions exhibited variability in terms of the intervention type, personnel involved, number of sessions, and duration. Most of the contributions also lack details regarding the training of professionals and the specifics of the interventions. Additionally, the evidence quality was deemed low based on the Crowe Critical Appraisal Tool. Conclusions: Although the importance of nonpharmacological approaches is well recognized, there is limited evidence to support the efficacy of psychological and behavioral interventions in narcolepsy. This is further complicated by the wide range of psychological and behavioral interventions available. Full article

In many applications, recognizing the depth of sleep (e.g., light, deep, REM sleep) while the subject is sleeping enables innovative features. For instance, in SAE Level 4 autonomous driving, a driver may need to takeover the vehicle control in case the autopilot is exiting its operational design domain. Depending on the depth of the sleep, the subject may need time to takeover effectively; hence, it is particularly relevant to know in which sleep stage the subject is (e.g., light sleep, deep sleep, and REM sleep), and possibly initiate actions to prevent the subject to remain in those sleep stages that lead to longer takeover time. Sleep stage classification can be achieved through an on-the-fly algorithm, which generates output in response to each input portion without knowledge of future inputs, unlike an off-Line algorithm that provides output just after receiving the entire input sequence. Various studies have analyzed algorithms or devices that identify sleep stages during the night; however, these typically require electroencephalography (EEG), which is obtrusive, or specialized devices. This study describes the development of an on-the-fly sleep-scoring algorithm using Heart Rate (HR), RR intervals, which is the distance between two consecutive heartbeats, and accelerometer data from a smartwatch, widespread, non-invasive, and affordable but accurate device. The subjects involved in our study wore a commercial off-the-shelf wearable device during a full night’s sleep, and were also monitored using a reference medical device to establish the ground truth by means of a full polysomnography (PSG) analysis. The on-the-fly sleep scoring algorithm based on smartwatch data was tested against PSG-based scoring, achieving 88.46% accuracy, 91.42% precision, and 93.52% sensitivity in sleep–wake identification. Deep sleep was correctly identified 69.38% of times, light sleep in 50.62%, REM sleep 62.02% and wakefulness 73.48% of times. Full article

Underwater wireless sensor networks (UWSNs) widely used for maritime object detection or for monitoring of oceanic parameters that plays vital role prediction of tsunami to life-cycle of marine species by deploying sensor nodes at random locations. However, the dynamic and unpredictable underwater environment poses significant challenges in communication, including interference, collisions, and energy inefficiency. In changing underwater environment to make routing possible among nodes or/and base station (BS) an adaptive receiver-initiated deep adaptive with power control and collision avoidance MAC (DAWPC-MAC) protocol is proposed to address the challenges of interference, collisions, and energy inefficiency. The proposed framework is based on Deep Q-Learning (DQN) to optimize network performance by enhancing collision avoidance in a varying sensor locations, conserving energy in changing path loss with respect to time and depth and reducing number of relaying nodes to make communication reliable and ensuring synchronization. The dynamic and unpredictable underwater environment, shaped by variations in environmental parameters such as temperature (T) with respect to latitude, longitude, and depth, is carefully considered in the design of the proposed MAC protocol. Sensor nodes are enabled to adaptively schedule wake-up times and efficiently control transmission power to communicate with other sensor nodes and/or courier node plays vital role in routing for data collection and forwarding. DAWPC-MAC ensures energy-efficient and reliable time-sensitive data transmission, improving the packet delivery rati (PDR) by 14%, throughput by over 70%, and utility by more than 60% compared to existing methods like TDTSPC-MAC, DC-MAC, and ALOHA MAC. These enhancements significantly contribute to network longevity and operational efficiency in time-critical underwater applications. Full article

This paper presents the concept, design, and performance analysis of an active radio wake-up and radio identification subsystem as part of an advanced localization device intended to operate within a large-scale freight wagon localization system. The system provides an efficient and cost-effective way to localize freight carriages, which, in the majority of cases, are currently not tracked. The localization device is battery-powered and uses an ultra-low-power radio interface for detecting wake-on-radio signals from nearby operator devices. The same interface is also used for communication within an ad-hoc wireless mesh network, which allows the localization devices to select the best device to send out localization information from the whole cluster through a cellular connection in order to minimize overall battery energy usage. The article presents the overall system architecture construction of the radio interface, including the wake-up subsystem, as well as the results of performance measurements. Full article

Smart Cities leverage large networks of wirelessly connected nodes embedded with sensors and/or actuators. Cellular IoT, such as NB-IoT and 5G RedCap, is often preferred for these applications thanks to its long range, extensive coverage, and good quality of service. In these networks, wireless communication dominates power consumption, motivating research on energy-efficient yet resilient and robust wireless systems. Many IoT use cases require low latency but cannot afford high-power radios continuously operating to accomplish this. In these cases, wake-up receivers (WURs) are a promising solution: while the high-power main radio (MR) is turned off/idle, a lightweight WUR is continuously monitoring the RF channel; when it detects a wake-up sequence, the WUR will turn on the MR for subsequent communications. This article provides an overview of WUR hardware design considerations and challenges for 4G and 5G cellular IoT, summarizes the recent 3GPP activities to standardize NB-IoT and 5G wake-up signals, and presents a state-of-the-art WUR chip. Full article

Obstructive sleep apnea syndrome (OSAS) is a frequently underdiagnosed sleep disorder marked by recurrent episodes of apnea and/or hypopnea during sleep, primarily resulting from the partial or complete collapse of the upper airway. OSAS significantly affects patients’ health and quality of life. Additionally, it is a recognized risk factor for inducing microsleep episodes during daily activities, particularly in occupations such as professional driving, where sustained attention is critical. The aim of our study was to identify an effective screening test for use in outpatient settings, capable of distinguishing patients with a severe form of OSAS. Patients who test positive with this screening tool would subsequently be prioritized for polysomnographic evaluation in a sleep laboratory. A total of 64 patients who underwent polysomnography (PSG) or polygraphy (PG) examination at our clinic were subsequently examined by USG of the tongue with measurements of tongue base thickness (TBT) and the distance between lingual arteries (DLA) during wakefulness and in a relaxed tongue position. The measurements of TBT and DLA were subsequently correlated with the apnea–hypopnea index (AHI) obtained from PSG or PG. In our cohort of patients diagnosed with severe OSAS, a TBT threshold of ≥65 mm served as an effective cutoff value. A TBT value of ≥65 mm reached an AUC value of 78.1%, sensitivity of 74.4%, specificity of 61.9%, positive predictive value of 80%, negative predictive value of 54.2% and overall accuracy of 70.3%. A DLA value of ≥30 mm in our sample of patients with severe OSAS showed an AUC of 76.5%, sensitivity of 69.8%, specificity of 71.1%, positive predictive value of 83.3%, negative predictive value of 53.6%, and overall accuracy of 70.3%. Tongue USG markers, particularly TBT and DLA measurements during wakefulness and in a relaxed tongue position, show potential as effective screening tools for identifying severe OSAS in European populations. These markers demonstrate improved accuracy over traditional screening questionnaires by reducing the likelihood of false-negative results. Patients with a positive screening should preferably be referred for polysomnography. In this way, patients with a serious illness could receive adequate therapy sooner. Full article

This paper presents a passive Envelope Detector (ED) to be used for reception of OOK-modulated signals, such as in Wake-Up Receivers employed within Wireless Sensor Networks, widely used in the IoT. The main goal is implementing a temperature compensation mechanism in order to keep the passive ED input resistance roughly constant over temperature, making it a constant load for the preceding matching network and ultimately keeping the overall receiving chain sensitivity constant over temperature. The proposed ED was designed using STMicroelectronics 90 nm CMOS technology to receive 1 kbps OOK-modulated packets with a 433 MHz carrier frequency and a 0.6 V supply. The use of a block featuring a Proportional-to-Absolute Temperature (PTAT) current yields a 5 dB reduction in sensitivity temperature variation across the −40 °C to 120 °C range. Moreover, two different implementations were compared, one targeting minimal mismatch and the other one targeting minimal area. The minimal area version appears to be better in terms of estimated overall chain sensitivity at all temperatures despite a higher sensitivity spread. Full article

Background: Exogenous melatonin, a nutraceutical for maintaining a healthy sleep–wake cycle and managing sleep disorders, requires large, repeated doses due to its low bioavailability and short half-life. This necessitates the development of a sustained-release formulation with a longer half-life and sustained plasma concentration. Therefore, exogenous novel 5 mg sustained-release melatonin capsules (Melatonin-SR, test product) were formulated. Methods: This open-label cross-over study compared the pharmacokinetics (maximum concentration [C_max], time to reach C_max [T_max], area under the curve [AUC], and elimination half-life [t_1/2]) and the safety of Melatonin-SR with 5 mg immediate-release melatonin capsules (Melatonin-IR, reference product) after single-dose oral administration in healthy fasting adults. Results: Sixteen participants (aged 18–45 years) were randomized (1:1) to receive either Melatonin-SR or Melatonin-IR in two periods with a 7-day washout period. Melatonin-SR reported a lower C_max (11,446.87 pg/mL) compared to Melatonin-IR (22,786.30 pg/mL). The mean T_max of Melatonin-SR and Melatonin-IR was 1.26 h and 0.87 h, respectively. The mean t_1/2 of Melatonin-SR (5.10 h) was prolonged by five-fold compared to Melatonin-IR (1.01 h). One adverse event (vomiting) was reported following the administration of the Melatonin-IR. Conclusions: Melatonin-SR resulted in higher and sustained plasma melatonin concentrations for an extended period and was well-tolerated. Hence, Melatonin-SR may be a promising nutraceutical for maintaining healthy sleep. Full article

(1) Background and Objectives: Catheter-related bladder discomfort (CRBD), a common and distressing consequence of indwelling urinary catheters, can significantly impact postoperative recovery. This study aimed to determine the effectiveness of bladder irrigation with a 0.05% lidocaine normal saline solution for the prevention of CRBD following transurethral surgery. (2) Materials and Methods: In this randomized, double-blind, placebo-controlled trial, patients were assigned to either a control group receiving normal saline or a treatment group receiving 0.05% lidocaine (2% lidocaine 25 mL in 1000 mL saline) for bladder irrigation. Both groups were administered fentanyl (1 μg/kg) for analgesia at the end of the procedure. The primary endpoint was the assessment of the incidence and severity of CRBD upon awakening within the first 6 h postoperatively, using a four-grade scale based on the patients’ reports of discomfort. (3) Results: Out of 79 patients completing the study, the incidence of moderate to severe CRBD was significantly lower in the lidocaine group (5.1%, 2/39) compared to the control group (25%, 10/40) at 10 min after waking from anesthesia (p = 0.014). Furthermore, the lidocaine group experienced significantly less CRBD at 1 and 2 h postoperative (2.6% and 0%, respectively) compared to the control group (20% and 10%, respectively) (p = 0.015, p = 0.043), with no significant differences at 6 h (p = 0.317). (4) Conclusions: The results suggest that bladder irrigation with 0.05% lidocaine reduces the occurrence of moderate to severe CRBD by nearly 80% in the initial 2 h postoperative period after transurethral surgery. Full article

Modeling the atmospheric boundary layer (ABL) in the area of a wind farm using computational fluid dynamics (CFD) methods allows us to study the characteristics of air movement, the shading effect, the influence of relief, etc., and can be actively used in studies of local territories where powerful wind farms are planned to be located. The operating modes of a wind farm largely depend on meteorological phenomena, the intensity and duration of which cause suboptimal operating modes of wind farms, which require the use of modern tools for forecasting and classifying precipitation. The methods and approaches used to predict meteorological phenomena are well known. However, for designed and operated wind farms, the influence of meteorological phenomena on the operating modes, such as freezing rain and hail, remains an urgent problem. This study presents a multi-layered neural network for the classification of precipitation zones, designed to identify adverse meteorological phenomena for wind farms according to weather stations. The neural network receives ten inputs and has direct signal propagation between six hidden layers. During the training of the neural network, an overall accuracy of 81.78%, macro-average memorization of 81.07%, and macro-average memorization of 75.05% were achieved. The neural network is part of an analytical module for making decisions on the application of control actions (control of the boundary layer of the atmosphere by injection of silver iodide, ionization, etc.) and the formation of the initial conditions for CFD modeling. Using the example of the Ulyanovsk wind farm, a study on the movement of air masses in the area of the wind farm was conducted using the initial conditions of the neural network. Digital models of wind turbines and terrain were created in the Simcenter STAR-CCM+ software package, version 2022.1; an approach based on a LES model using an actuating drive disk model (ADM) was implemented for modeling, allowing calculation with an error not exceeding 5%. According to the results of the modeling of the current layout of the wind turbines of the Ulyanovsk wind farm, a significant overlap of the turbulent wake of the wind turbines and an increase in the speed deficit in the area of the wind farm were noted, which significantly reduced its efficiency. A shortage of speed in the near and far tracks was determined for special cases of group placement of wind turbines. Full article