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The deployment of large-scale antenna arrays (ELAAs) in sixth-generation (6G) networks extends wireless communications into the near-field regime, facilitating integrated sensing and communications while introducing security requirements. To ensure secure near-field transmission and sensing accuracy, this paper proposes a framework that jointly minimizes the Cramér-Rao Bound (CRB), guarantees quality-of-service (QoS) for ordinary users, and ensures the covertness of a primary user through an explicit vulnerable-region constraint. The nonconvex problem is addressed through an iterative approach integrating semidefinite relaxation (SDR), alternating optimization (AO), and successive convex approximation (SCA). Numerical results demonstrate sensing performance, QoS satisfaction, and accurate vulnerable-region control.

Background Sleep problems in children have been increasingly recognized as a major public health issue. Previous research has extensively studied and presented many risk factors and potential mechanisms for children’s sleep problems. In this paper, we aimed to identify and summarize the consequences and implications of child sleep problems. Data sources A comprehensive search for relevant English language full-text, peer-reviewed publications was performed focusing on pediatric sleep studies from prenatal to childhood and adolescence in a variety of indexes in PubMed, SCOPUS, and Psych Info published in the past two decades. Both relevant data-based articles and systematic reviews are included. Results Many adverse consequences are associated with child sleep deficiency and other sleep problems, including physical outcomes (e.g., obesity), neurocognitive outcomes (e.g., memory and attention, intelligence, academic performance), and emotional and behavioral outcomes (e.g., internalizing/externalizing behaviors, behavioral disorders). Current prevention and intervention approaches to address childhood sleep problems include nutrition, exercise, cognitive–behavioral therapy for insomnia, aromatherapy, acupressure, and mindfulness. These interventions may be particularly important in the context of coronavirus disease 2019. Specific research and policy strategies can target the risk factors of child sleep as well as the efficacy and accessibility of treatments. Conclusions Given the increasing prevalence of child sleep problems, which have been shown to affect children’s physical and neurobehavioral wellbeing, understanding the multi-aspect consequences and intervention programs for childhood sleep is important to inform future research direction as well as a public health practice for sleep screening and intervention, thus improving sleep-related child development and health.

Existing covert communication schemes based on On–Off Keying (OOK) have not considered asymmetric noise environments, which limits their applicability in complex communication scenarios such as terahertz and underwater acoustic covert communications. To address this issue, this paper proposes a phase-based OOK coding scheme. In particular, the transmitter Alice can adjust the initial phase of the transmitted symbol to align the signal with the stronger noise components in asymmetric noise communication scenarios, thereby exploiting the masking effect of noise to achieve covert transmission. To quantify performance, the KL divergence and mutual information of the OOK coding scheme are adopted as measures of covertness and transmission performance, respectively. An optimization problem involving the input signal distribution an, signal amplitude β, and initial phase angle θ is formulated and solved to obtain the maximum covert transmission rate. Numerical results demonstrate that in asymmetric noise systems, the initial phase angle and the Gaussian noise components on the real and imaginary axes of the complex plane influence both covertness performance and transmission rate. Adjusting the initial phase towards the direction with lower noise components can maximally suppress noise interference, thereby improving the covertness performance.

Dimming control is an indispensable functionality for visible-light communication (VLC) that enables both illumination and data transmission. However, how to achieve both high-resolution dimming control and spectral-efficient communication is still an open problem. Therefore, a novel high-resolution dimmable augmented spectral-efficiency discrete multi-tone (HD-ASE-DMT) architecture is proposed in this paper. To address the limitation of low dimming resolution in a conventional pulse-width modulation (PWM) scheme, a hybrid PWM mechanism was first designed by combining the inter-symbol and intra-symbol PWM signals, which provided flexible and high-resolution two-tier dimming control. Furthermore, a reconstructed process was conceived to achieve the seamless integration of the hybrid PWM and the spectral-efficient ASE-DMT architecture. As a result, the proposed HD-ASE-DMT architecture maintains full compatibility with legacy ASE-DMT receivers, thus reducing the implementation complexity compared to the existing dimmable modulation schemes. Simulation results demonstrated that a two-orders-of-magnitude improvement in the dimming resolution was achieved by the HD-ASE-DMT architecture. Moreover, the spectral efficiency of the HD-ASE-DMT architecture was improved by 29.3% compared to the conventional scheme.

Background Sleep problem is a highly prevalent health issue among pediatric populations across the world. In this review, we aimed to identify risk factors contributing to sleep deficiency and poor sleep hygiene in children. Potential biological, psychosocial, and environmental mechanisms as well as research gaps in the literature are also discussed. Data sources A comprehensive search for relevant English language full-text, peer-reviewed publications was performed focusing on pediatric sleep studies from prenatal to childhood and adolescence in a variety of indexes in PubMed, SCOPUS, and Psych Info. Both relevant data based and systematic reviews are included. Results This paper summarizes many risk factors for childhood sleep problems, including biological (e.g., genetics, gender, age and puberty, prenatal factors, postnatal factors); nutritional (e.g., macronutrients, micronutrients, omega-3 fatty acids, obesity); environmental (e.g., heavy metals, noise, light, air pollution); interpersonal (e.g., family, exposure to violence, screen media use, physical injury); and community/socioeconomic variables (e.g., racial/ethnicity and cultural factors, neighborhood conditions and socioeconomic status, school factors, public health disasters/emergencies), to better understand the development of sleep problems in children. Conclusions Poor childhood sleep is a multifactorial issue affected by a wide range of prenatal and early-life biological, environmental, and psychosocial risk factors and contributors. A better understanding of these risk factors and their mechanisms is an important first step to develop future research and prevention programs focusing on pediatric sleep problems.

Midday napping, a culturally perceived health behavior, is common among adolescents in China. This study aimed to examine the factors associated with habitual midday napping behavior and explore sex differences in these factors. The sample comprised 1549 (62.5% males; mean age 16.29 ± 1.01 years) adolescents from a vocational high school that provided midday napping opportunities. Midday napping and nighttime sleep were measured using self-reported questions, and binary logistic regression was used to examine the associated factors of habitual midday napping. About 78% participants reported midday napping at least three times a week, and were classified as habitual nappers. They were less likely to be female [adjusted OR (aOR) = 0.59 (0.45, 0.78)], to be overweight/obese [aOR = 0.72 (0.53, 0.98)], and to have poor sleep quality [aOR = 0.58 (0.43, 0.77)], and they were more likely to have mothers with middle school or higher education [aOR = 1.35 (1.02, 1.78)]. Separate analyses showed that male habitual nappers were less likely to be overweight/obese [aOR = 0.63 (0.43, 0.92)], perform more physical activity [aOR = 0.59 (0.40, 0.89)], and report poor sleep quality [aOR = 0.55 (0.37, 0.81)], but were more likely to have mothers with higher education [aOR = 1.73 (1.19, 2.51)] than male non-habitual nappers. Female habitual nappers were less likely to report poor sleep quality [aOR = 0.56 (0.36, 0.88)], but more likely to have morning chronotype [aOR = 2.28 (1.21, 4.31)]. Habitual midday napping was associated with multifaceted factors, which provides important information to understand the habitual midday napping behavior of Chinese adolescents.

Sleep stage classification is a necessary step for diagnosing sleep disorders. Generally, experts use traditional methods based on every 30 seconds (s) of the biological signals, such as electrooculograms (EOGs), electrocardiograms (ECGs), electromyograms (EMGs), and electroencephalograms (EEGs), to classify sleep stages. Recently, various state-of-the-art approaches based on a deep learning model have been demonstrated to have efficient and accurate outcomes in sleep stage classification. In this paper, a novel deep convolutional neural network (CNN) combined with a long short-time memory (LSTM) model is proposed for sleep scoring tasks. A key frequency domain feature named Mel-frequency Cepstral Coefficient (MFCC) is extracted from EEG and EMG signals. The proposed method can learn features from frequency domains on different bio-signal channels. It firstly extracts the MFCC features from multi-channel signals, and then inputs them to several convolutional layers and an LSTM layer. Secondly, the learned representations are fed to a fully connected layer and a softmax classifier for sleep stage classification. The experiments are conducted on two widely used sleep datasets, Sleep Heart Health Study (SHHS) and Vincent’s University Hospital/University College Dublin Sleep Apnoea (UCDDB) to test the effectiveness of the method. The results of this study indicate that the model can perform well in the classification of sleep stages using the features of the 2-dimensional (2D) MFCC feature. The advantage of using the feature is that it can be used to input a two-dimensional data stream, which can be used to retain information about each sleep stage. Using 2D data streams can reduce the time it takes to retrieve the data from the one-dimensional stream. Another advantage of this method is that it eliminates the need for deep layers, which can help improve the performance of the model. For instance, by reducing the number of layers, our seven layers of the model structure takes around 400 s to train and test 100 subjects in the SHHS1 dataset. Its best accuracy and Cohen’s kappa are 82.35% and 0.75 for the SHHS dataset, and 73.07% and 0.63 for the UCDDB dataset, respectively.

In wireless sensor networks (WSNs), unmanned aerial vehicles (UAVs) are considered an effective data collection tool. In this paper, we investigate the energy-efficient data collection problem in a UAV-enabled secure WSN without knowing the instantaneous channel state information of the eavesdropper (Eve). Specifically, the UAV collected the information from all the wireless sensors at the scheduled time and forward it to the fusion center while Eve tries to eavesdrop on this confidential information from the UAV. To surmount this intractable and convoluted mixed-integer non-convex problem, we propose an efficient iterative optimization algorithm using the block coordinate descent (BCD) method to minimize the maximum energy consumption of the ground sensor nodes (GSNs) under the constraints of secrecy outage probability (SOP), connection outage probability (COP), minimum secure data, information causality, and UAV trajectory. Numerical results demonstrate the superiority of the algorithm we proposed in energy consumption and secrecy rate compared with other schemes.

Poor sleep and daytime sleepiness in children and adolescents have short- and long-term consequences on various aspects of health. Midday napping may be a useful strategy to reduce such negative impacts. The effect of habitual napping on a wide spectrum of cognitive, behavioral, psychological, and metabolic outcomes has not been systematically investigated. This study characterized midday napping habits in 3819 elementary school children from the China Jintan Cohort Study. In 2011, weekly nap frequency and average duration were collected once from students at grades 4-6. Prior to their completion of elementary school at grade 6 (in 2011-2013 respective to each grade), the following outcomes were collected once: behavioral and academic achievement evaluated by teachers, and self-reported positive psychology measures including grit, self-control, and happiness. IQ tests were conducted on a subgroup. Metabolic indices, including body mass index and fasting glucose concentration, were measured through physical exams. For the whole sample, we assessed associations between napping and each outcome, adjusted for sex, grade, school location, parental education, and time in bed at night. We also conducted stratified analyses on grade 6 (cross-sectional), grade 4 (2-year gap), and grade 5 (1-year gap) data. Overall, napping was significantly associated with higher happiness, grit, and self-control, reduced internalizing behavior problem, higher verbal IQs, and better academic achievement, although specific patterns varied across frequency and duration for different outcomes. More limited significant associations were found for decreased externalizing behavior problems, compared to non-nappers, while no significant associations were found for performance IQ and metabolic outcomes. Results indicate benefits of regular napping across a wide range of adolescent outcomes, including better cognition, better psychological wellness, and reduced emotional/behavioral problems. The current study underscores the need for further large-scale intervention studies to establish causal effects.

Little evidence is available regarding the relationship between zinc and sleep in school children. The present study aimed to examine the cross-sectional and longitudinal associations between blood zinc concentrations and sleep quality throughout childhood. A total of 1295 children from the Jintan Child Cohort in China were included in this study. Venous blood sample of zinc and subjective sleep data were collected when the children were at preschool age (3–5 years old) and early adolescence (11–15 years old). Odds ratios (ORs) reflect the odds of the sleep quality/subdomain being at a greater impairment level associated with 1 unit increase in log zinc concentration. Cross-sectional analyses showed negative correlation of blood zinc concentrations with insufficient sleep duration (OR = 0.432, p = 0.002), sleep disturbances (OR = 0.454, p = 0.009) and poor sleep quality (OR = 0.559, p = 0.049) in adolescence, but no association at preschool age (p > 0.05). Longitudinal analyses indicated that blood zinc concentrations at preschool age predict poor sleep efficiency (OR = 0.186, p = 0.000) and poor sleep quality (OR = 0.358, p = 0.020) in adolescence. Our findings suggest that sufficient zinc concentration is associated with good sleep quality, dependent on the developmental stage in childhood. Future interventional research is warranted to examine the short and long-term effect of zinc status on sleep heath.