Sleep Cycle Research Articles

Assessment of Sleep Stages in Unconscious Patients with Acute Severe Traumatic Brain Injury

Abstract Background The existence of a sleep cycle in deeply unconscious patients with severe traumatic brain injury (TBI) remains unknown. Evaluating the sleep patterns of these patients may provide insights into their consciousness and help predict functional recovery. Aims and Objectives This prospective observational study aimed to assess the usefulness of monitoring the sleep cycle in the prognostication of unconscious TBI patients. Materials and Methods A purposive sampling technique was employed to include 39 patients with severe TBI (Glasgow Coma Scale [GCS] ≤ 8). The average GCS score at admission was (5.76 ± 1.65). Sleep was monitored using an actigraphy smartwatch for 4 consecutive days, (3.15 ± 2.49) days postbrain injury. Sleep cycle monitoring tool and unconscious patient outcome monitoring tool were employed. An outcome assessment was done based on the GCS score. Results Severe TBI patients exhibit intact sleep cycle (i.e., deep sleep, light sleep, and rapid eye movement sleep) despite being deeply unconscious, even in the acute stage. Total sleep duration was found to be significantly higher at a mean of 19.97 hours as compared to the mean of 8 hours as per the smartwatch reference value for normal individuals. Patients with improved sleep cycles had a higher likelihood of GCS improvement (p < 0.05). Conclusion This study is the first of its kind to demonstrate that the sleep cycle is a reliable prognostic factor for the recovery of consciousness in the acute phase of severe TBI among unconscious patients, with improvement in the sleep cycle mirroring neurological improvement.

Сontribution of circadian rhythms to the development of neurological disorders after prolonged anesthesia

Despite the improvement of pre-, intra- and postoperative care methods, the problem of the development of postoperative neurological complications following prolonged anesthesia remains. A mechanism of occurrence of these complications may be circadian rhythm disorders. This article presents a review of the literature data on the prevalence, pathophysiological mechanisms, and risk factors of postoperative autonomic and circadian disorders. Notably, circadian rhythm disorders in surgical patients are observed at several levels: disruption of the sleep and wakefulness cycle, decreased melatonin secretion, instability of cortisol levels and body temperature, and changes in the vegetative balance towards sympathetic regulation. These disorders contribute to the development of postoperative pain and cognitive and anxiety-depressive disorders, hinder effective rehabilitation, and may be associated with postoperative mortality.

Recent advances in sleep cycle regulation and hormonal imbalance: a comprehensive review

A vital physiological function, sleep is necessary for general health and wellbeing. It is essential for several body processes, including as metabolism, immunological response, emotional control, and cognitive function. A complicated mechanism involving intricate connections between brain circuits, neurotransmitters, and hormone cues governs the sleep-wake cycle. Scientific research has recently made significant progress in understanding the mechanisms behind the control of the sleep cycle and how it relates to hormone imbalance. The goal of this thorough review is to examine the most recent research in this area, with a particular emphasis on the interaction between hormone variations and sleep regulation.

Quantitative Electroencephalography in Term Neonates During the Early Postnatal Period Across Various Sleep States.

Neonatal sleep is pivotal for their growth and development, yet manual interpretation of raw images is time-consuming and labor-intensive. Quantitative Electroencephalography (QEEG) presents significant advantages in terms of objectivity and convenience for investigating neonatal sleep patterns. However, research on the sleep patterns of healthy neonates remains scarce. This study aims to identify QEEG markers that distinguish between different neonatal sleep cycles and analyze QEEG alterations across various sleep stages in relation to postmenstrual age. From September 2023 to February 2024, full-term neonates admitted to the neonatology department at the Obstetrics and Gynecology Hospital of Fudan University were enrolled in this study. Electroencephalographic (EEG) recordings were obtained from neonates aged 37-42 weeks, within 1-7 days post-birth. The ROC curve was employed to evaluate QEEG features related to amplitude, range EEG (rEEG), spectral density, and connectivity across different sleep stages. Furthermore, regression analyses were performed to investigate the association between these QEEG characteristics and postmenstrual age. The alpha frequency band's spectral_diff_F3 emerged as the most potent discriminator between active sleep (AS) and quiet sleep (QS). In distinguishing AS from wakefulness (W), the theta frequency's spectral_diff_C4 was the most effective, whereas the delta frequency's spectral_diff_P4 excelled in differentiating QS from W. During AS and QS phases, there was a notable increase in entropy within the delta frequency band across all monitored brain regions and in the spectral relative power within the theta frequency band, correlating with postmenstrual age (PMA). Spectral difference showcases the highest discriminative capability across awake and various sleep states. The observed patterns of neonatal QEEG alterations in relation to PMA are consistent with the maturation of neonatal sleep, offering insights into the prediction and evaluation of brain development outcomes.

Altered circadian rhythm, sleep, and rhodopsin 7–dependent shade preference during diapause in Drosophila melanogaster

To survive adverse environments, many animals enter a dormant state such as hibernation, dauer, or diapause. Various Drosophila species undergo adult reproductive diapause in response to cool temperatures and/or short day-length. While flies are less active during diapause, it is unclear how adverse environmental conditions affect circadian rhythms and sleep. Here we show that in diapause-inducing cool temperatures, Drosophila melanogaster exhibit altered circadian activity profiles, including severely reduced morning activity and an advanced evening activity peak. Consequently, the flies have a single activity peak at a time similar to when nondiapausing flies take a siesta. Temperatures ≤15 °C, rather than photoperiod, primarily drive this behavior. At cool temperatures, flies rapidly enter a deep-sleep state that lacks the sleep cycles of flies at higher temperatures and require high levels of stimulation for arousal. Furthermore, we show that at 25 °C, flies prefer to siesta in the shade, a preference that is virtually eliminated at 10 °C. Resting in the shade is driven by an aversion to blue light that is sensed by Rhodopsin 7 outside of the eyes. Flies at 10 °C show neuronal markers of elevated sleep pressure, including increased expression of Bruchpilot and elevated Ca2+ in the R5 ellipsoid body neurons. Therefore, sleep pressure might overcome blue light aversion. Thus, at the same temperatures that cause reproductive arrest, preserve germline stem cells, and extend lifespan, D. melanogaster are prone to deep sleep and exhibit dramatically altered, yet rhythmic, daily activity patterns.

Intermittent hypoxia induces Th17/Treg imbalance in a murine model of obstructive sleep apnea.

Obstructive sleep apnea (OSA) is characterized by cyclic normoxic and hypoxic conditions (intermittent hypoxia, IH) induced by the repeated closure of the upper-airway respiratory tract. As a pathomechanism of OSA, IH results in various comorbidities via chronic inflammation and related pathways. However, the role of other inflammatory cells, such as lymphocytes, has not been well-explored. This study aimed to examine the effects of IH on the distribution and balance of T cell subsets and other related cytokines, and mechanisms in the immune system. We modified OSA mouse model (male C57BL/6N male) using our customized chamber that controls specific sleep and oxygenic cycles. To induce hypoxia, the IH group was repeatedly exposed to 5% O2 and 21% O2 lasting for 120 s each for 7 h daily for 4 weeks. Mice were then subjected to a recovery period of 4 weeks, in which IH stimulation was ceased. T cells and related cytokines were analyzed using flow cytometry and immunohistochemistry. Compared with the control group, the IH group had significantly lower levels of CD4+CD25+Foxp3+ regulatory T cells but higher levels of Th 17, IL-4, HIF-1, and inflammatory cytokines. After the recovery period, these altered changes in the immune cells were recovered, and we found no significant difference in their levels between the control and recovery groups. This study revealed that the Th17/Treg ratio is increased by intermittent hypoxia, and this imbalance can explain immune-related diseases, including recently reported allergies, autoimmune, and even cancer diseases, arising from OSA.

Enabling sustainable green communication in three-tier 5G ultra dense HetNet with sleep cycle modulated energy harvesting

Enabling sustainable green communication in three-tier 5G ultra dense HetNet with sleep cycle modulated energy harvesting

NREM Slow-Wave Activity in Adolescents Is Differentially Associated With ADHD Levels and Normalized by Pharmacological Treatment.

A compelling hypothesis about attention-deficit/hyperactivity disorder (ADHD) etiopathogenesis is that the ADHD phenotype reflects a delay in cortical maturation. Slow-wave activity (SWA) of non-rapid eye movement (NREM) sleep electroencephalogram (EEG) is an electrophysiological index of sleep intensity reflecting cortical maturation. Available data on ADHD and SWA are conflicting, and developmental differences, or the effect of pharmacological treatment, are relatively unknown. We examined, in samples (Mage = 16.4, SD = 1.2), of ever-medicated adolescents at risk for ADHD (n = 18; 72% boys), medication-naïve adolescents at risk for ADHD (n = 15, 67% boys), and adolescents not at risk for ADHD (n = 31, 61% boys) matched for chronological age and controlling for non-ADHD pharmacotherapy, whetherADHD pharmacotherapy modulates the association between NREM SWA and ADHD risk in home sleep. Findings indicated medication-naïve adolescents at risk for ADHD exhibited greater first sleep cycle and entire night NREM SWA than both ever-medicated adolescents at risk for ADHD and adolescents not at risk for ADHD and no difference between ever-medicated, at-risk adolescents, and not at-risk adolescents. Results support atypical cortical maturation in medication-naïve adolescents at risk for ADHD that appears to be normalized by ADHD pharmacotherapy in ever-medicated adolescents at risk for ADHD. Greater NREM SWA may reflect a compensatory mechanism in middle-later adolescents at risk for ADHD that normalizes an earlier occurring developmental delay.

Insulin Management for Gestational and Type 2 Diabetes in Pregnancy.

Insulin is preferred as the first-line agent for glucose management of gestational diabetes mellitus and type 2 diabetes in pregnancy when nutritional and lifestyle modifications are unable to achieve pregnancy-specific glucose targets. Individual heterogeneity in defects of insulin secretion or sensitivity in liver and muscle, unique genetic influences on pregnancy glycemic regulation, and variable cultural and lifestyle behaviors that affect meal, activity, sleep, and occupational schedules necessitate a personalized approach to insulin regimens. Newer insulin preparations have been developed to mimic the physiologic release of endogenous insulin, maintaining appropriate basal levels to cover hepatic gluconeogenesis and simulate the rapid, meal-related, bolus rise of insulin. Such physiologic basal-bolus dosing of insulin can be administered safely, achieving tighter glycemic control while reducing episodes of hypoglycemia. Insulin initiation and titration require understanding the pharmacodynamics of different insulin preparations in addition to a patient's glycemic profiles, effect of variable nutritional intake and mealtimes, physical activity, stress, timing of sleep cycles, and cultural habits. Educating and empowering patients to learn how their glucose responds to insulin, portion and content of meals, and physical activity can increase personal engagement in therapy, flexibility in eating patterns, and improved glycemic control. This Clinical Expert Series article is focused on optimizing insulin management (initiation, dosing, and titration) of gestational and type 2 diabetes in pregnancy.

Dexmedetomidine as a Short-Use Analgesia for the Immature Nervous System.

Pain management in neonates continues to be a challenge. Diverse therapies are available that cause loss of pain sensitivity. However, because of side effects, the search for better options remains open. Dexmedetomidine is a promising drug; it has shown high efficacy with a good safety profile in sedation and analgesia in the immature nervous system. Though dexmedetomidine is already in use for pain control in neonates (including premature neonates) and infants as an adjunct to other anesthetics, the question remains whether it affects the neuronal activity patterning that is critical for development of the immature nervous system. In this study, using the neonatal rat as a model, the pharmacodynamic effects of dexmedetomidine on the nervous and cardiorespiratory systems were studied. Our results showed that dexmedetomidine has pronounced analgesic effects in the neonatal rat pups, and also weakly modified both the immature network patterns of cortical and hippocampal activity and the physiology of sleep cycles. Though the respiration and heart rates were slightly reduced after dexmedetomidine administration, it might be considered as the preferential independent short-term therapy for pain management in the immature and developing brain.

Exploring the Role of Circadian Rhythms in Sleep and Recovery: A Review Article.

Sleep is essential for every living organism. Humans spend about one-third of their lives sleeping. Sleep has been studied extensively, and the role of sleep in psychological, mental, and physical well-being is established to be the best. The rhythm of the brain between wakefulness and sleep is called the circadian rhythm, which ismainly controlled by melatonin and the pineal gland. The imbalance of this rhythm can lead to devastating effects on health. Vigorous workouts close to bedtime can interfere with falling asleep. Meal timing and composition can significantly affect sleep quality. It is advised to avoid large meals, caffeine, and alcohol before bedtime. Heavy meals close to bedtime can lead to poor sleep and hormone disruption. By following these guidelines enumerated in the article, individuals can improve sleep quality and overall health. Sleep cycles, especially rapid eye movement sleep, have a profound influence on mental and physical health. Adhering to recommended sleep practices enhances bodily restoration, fortifies the immune system, and upholds metabolic equilibrium. Sleep hygiene aligned with circadian rhythms is crucial for disease prevention and well-being. Healthcare professionals should prioritize sleep optimization strategies for patient care and public health.

The Effects of Obstructive Sleep Apnea on the Cardiovascular System: A Comprehensive Review.

Obstructive sleep apnea (OSA) is an increasingly relevant cause of cardiovascular morbidity worldwide. Although the association between OSA and the cardiovascular system is well-known, the extent of its effects is still a topic of interest, including pathophysiologic mechanisms, cardiovascular sequelae, and OSA therapies and their effects. Commonly described mechanisms of cardiovascular etiologies revolve around sympathetic activation, inflammation, and intermittent hypoxia resulting from OSA. Ultimately, these effects lead to manifestations in the cardiovascular system, such as arrhythmias, hypertension, and heart failure, among others. The resulting sequelae of OSA may also have differential effects based on gender and age; several studies suggest female gender to have more susceptibility to cardiovascular mortality, as well as an increase in age. Furthermore, several therapies for OSA, both established and emerging, show a reduction in cardiovascular morbidity and may even reduce cardiovascular burden. Namely, the establishment of CPAP has led to improvement in hypertension and cardiac function in patients with heart failure and even reduced the progression of early stages of atherosclerosis. Effective management of OSA decreases abnormal neural sympathetic activity, which results in better rhythm control and blood pressure control, both in waking and sleep cycles. With newer therapies for OSA, its effects on the cardiovascular system may be significantly reduced or even reversed after long-term management. The vast extent of OSA on the cardiovascular system, as well as current and future therapeutic strategies, will be described in detail in this review.

Оценка эффективности нового лекарственного препарата Курс Успокоин таблетки для коррекции возрастных когнитивных нарушений у кошек

The treatment by Kurs Uspokoin tablets in a minimum initial daily dose of 7 mg/kg for the first three days, with a further increase to 14 mg/kg, showed a positive effect in correcting the behavior of older cats with progressive simptoms of cognitive disfunction. During the treatment were registered a statistically and clinically significant decrease in idiopathic vocalization, restoration of sleep cycles and wakefulness, elimination of house-soiling behavior, disorientation, increased activity, and improvement of social behavior. During the treatment by Kurs Uspokoin tablets and after its discontinuation no adverse reactions were registered.

Hypoxia and oxidative stress impair autophagy and cell death mechanisms in trophoblast cells and reduce placental effciency in rodents

Introduction: Hypoxia and oxidative stress can activate autophagy, a lysosomal degradation pathway that maintains cellular homeostasis. Impairments in autophagy mechanisms have been observed in placentas from obstetric complications associated with placental hypoxia and oxidative stress, such as preeclampsia and intrauterine growth restriction. The objective of this study was to investigate the effects of hypoxia and oxidative stress on placental cell autophagy. We hypothesized that exposure to oxidative stress and hypoxia would alter the balance between cytotoxic and cytoprotective mechanisms in human trophoblast cells and rat placentas and would adversely affect placental effciency. Methods: We used an in vitro model incorporating human trophoblast cells (BeWo cells) exposed to an oxidative stressor, antimycin A (10, 100, 320 μM) or vehicle for 4 hours. Trophoblast cell death and autophagy mechanisms were assessed via flow cytometry and western blotting. Additionally, we used a rodent model of gestational sleep apnea, a pregnancy complication associated with placental hypoxia. Long Evans timed-pregnant dams were exposed to chronic intermittent hypoxia (CIH; n=6-8) or normoxia (NX; n=8-9) during their sleep cycle from gestational day (GD) 15 to 20 (term=21-23 days). Results: In trophoblast cells (n=5-9 independent experiments), antimycin A increased necrosis and LC3 A/B II/I ratio (autophagy marker) at 100 μM compared to vehicle (p≤0.015). At antimycin A 320 μM, necrosis remained elevated, while BAX (pro-apoptotic marker) and p62 (autophagosomal flux marker) were reduced compared to vehicle (p<0.0001), and LC3 A/B II/I ratio returned to vehicle levels (p>0.05 vs. vehicle). Placental weights from CIH exposed dams were greater (NX: 0.51±0.02 g vs. CIH: 0.60±0.03 g, p=0.015) and fetal to placental weight ratios (marker of placental effciency) were reduced compared to control pregnancies (NX: 5.25±0.13 vs. CIH: 4.43±0.14, p=0.0006) on GD20. Gestational CIH did not affect (p>0.05) fetal weights (NX: 2.76±0.06 g vs. CIH: 2.61±0.06 g), crown to rump length (NX: 3.32±0.03 cm vs. CIH: 3.18±0.12 cm), abdominal girth (NX: 3.22±0.06 cm vs. CIH: 3.32±0.12 cm), or litter size (NX: 11.9±0.90 vs. CIH: 10.5±0.82). Conclusion: Oxidative stress alters the balance between cytotoxic and cytoprotective mechanisms in trophoblast cells, promoting cell necrosis. Although assessment of autophagy machinery and cell death in placentas from hypoxic pregnancies is ongoing, our results indicate that gestational CIH adversely affects placental effciency. NIH R01 HL146562, AHA 22PRE-900431, T32 AG020494, AHA 22POST-903250. This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Validation of Downloadable Mobile Snore Applications by Polysomnography (PSG).

Obstructive sleep apnea (OSA) is a common breathing disorder during sleep that is associated with symptoms such as snoring, excessive daytime sleepiness, and breathing interruptions. Polysomnography (PSG) is the most reliable diagnostic test for OSA; however, its high cost and lengthy testing duration make it difficult to access for many patients. With the availability of free snore applications for home-monitoring, this study aimed to validate the top three ranked snore applications, namely SnoreLab (SL), Anti Snore Solution (ASS), and Sleep Cycle Alarm (SCA), using PSG. Sixty participants underwent an overnight PSG while simultaneously using three identical smartphones with the tested apps to gather sleep and snoring data. The study discovered that all three applications were significantly correlated with the total recording time and snore counts of PSG, with ASS showing good agreement with snore counts. Furthermore, the Snore Score, Time Snoring of SL, and Sleep Quality of SCA had a significant correlation with the natural logarithm of apnea hypopnea index (lnAHI) of PSG. The Snore Score of SL and the Sleep Quality of SCA were shown to be useful for evaluating snore severity and for pre-diagnosing or predicting OSA above moderate levels. These findings suggest that some parameters of free snore applications can be employed to monitor OSA progress, and future research could involve adjusted algorithms and larger-scale studies to further authenticate these downloadable snore and sleep applications.

Individualised prediction of resilience and vulnerability to sleep loss using EEG features.

It is well established that individuals differ in their response to sleep loss. However, existing methods to predict an individual's sleep-loss phenotype are not scalable or involve effort-dependent neurobehavioural tests. To overcome these limitations, we sought to predict an individual's level of resilience or vulnerability to sleep loss using electroencephalographic (EEG) features obtained from routine night sleep. To this end, we retrospectively analysed five studies in which 96 healthy young adults (41 women) completed a laboratory baseline-sleep phase followed by a sleep-loss challenge. After classifying subjects into sleep-loss phenotypic groups, we extracted two EEG features from the first sleep cycle (median duration: 1.6 h), slow-wave activity (SWA) power and SWA rise rate, from four channels during the baseline nights. Using these data, we developed two sets of logistic regression classifiers (resilient versus not-resilient and vulnerable versus not-vulnerable) to predict the probability of sleep-loss resilience or vulnerability, respectively, and evaluated model performance using test datasets not used in model development. Consistently, the most predictive features came from the left cerebral hemisphere. For the resilient versus not-resilient classifiers, we obtained an average testing performance of 0.68 for the area under the receiver operating characteristic curve, 0.72 for accuracy, 0.50 for sensitivity, 0.84 for specificity, 0.61 for positive predictive value, and 3.59 for likelihood ratio. We obtained similar performance for the vulnerable versus not-vulnerable classifiers. These results indicate that logistic regression classifiers based on SWA power and SWA rise rate from routine night sleep can largely predict an individual's sleep-loss phenotype.

Comprehensive analysis of dynamic topology sensor linkage for the internet of things

In today’s developing IoT world, wireless sensor interactions are critical. To ensure full system IP compatibility, industry efforts are focused on standardizing the WSN protocol suite and enabling the second generation of IoT devices to be produced. As a result of their robust communications and conformance to less verbose WSN features such as sleep cycles required to keep end nodes’ total energy consumption low, the WSN protocols are strong contenders for use as a highly useable implementation layer for the IoT. Existing smart systems make use of system assets for critical IoT functions. Compared to a wired configuration, wireless sensors are easier to install and provide more device flexibility. As sensor technology advances, WSNs will become a critical component of the IoT and an essential tool for achieving the IoT paradigm’s goal. It’s also crucial to think about whether or not a WSN’s sensors should be fully linked into the IoT’s. For WSNs, a multi-objective optimization technique for selecting the most energy-efficient CH is described. The CHs for each lattice were first selected using a candidate CH selection method. Energy waste and data redundancy were also decreased by using multi-hop networking. An inventive new method has also been devised to ensure perfect implementation. The Evolutionary Algorithm (EA) model and optimization techniques used in this work provided an energy-efficient Machine Learning (ML) strategy for selecting WSN CH. First, the CH of each lattice was calculated using a candidate CH selection method. According to the results of the simulation, the suggested model’s performance is superior to traditional approaches in terms of network lifespan, energy efficiency, and reduced consumption.

Sleep Disorder and its Treatment: From Nature to Laboratory

Sleep is the natural cellular repair mechanism to improve and restore central neural mechanism, memory, hormonal imbalance, and finally, cell rejuvenation. Sleep disorder is characterized by insomnia, circadian rhythm disorder (CRD), sleep apnea, narcolepsy, parasomnia, and restless leg syndrome (RLS) or periodic limb movement disorder (PLMD). Both oversleeping and less sleeping are associated with sleep disorders (SD). Anxiety, schizophrenia, weight loss/gain, hypothyroidism, and oxidative stress are the most common outcomes of SD. There is also a genetic explanation behind circadian rhythmicity, circadian disorder, narcolepsy-cataplexy syndrome, fatal familial insomnia, and somnambulism. Excessive work pressure, stress, and consumption of caffeine and alcohol collectively push a person toward sleep deprivation. Anxiety, schizophrenia, weight loss/gain, hypothyroidism, and oxidative stress are the most common outcomes of SD. Adenosine, melatonin, dopamine, serotonin, gamma amino butyric acid (GABA), orexin, and histamine regulate SDs by various pathways. Among natural sources, Centella asiatica, Bacopa monnieri, Acorus calamus, Withania somnifera, Nardostachys jatamansi, Poria cocos is, Valeriana officinalis, Matricaria chamomilla, Lavandula angustifolia, Nelumbo nucifera, Melissa officinalis, Convolvulus pluricaulis, Camellia sinensis, Ziziphus jujube, Datura stramonium, Zhizhipus jujube, Passiflora incarnata, and Moringa oleifera showed remarkable effects on different forms of SDs through GABAA, serotonin, and melatonin receptors. Pramipexole, ropinirole, rotigotine, clonazepam, lorazepam, estazolam, zolpidem, lemborexant, daridorexant, and suvorexant showed its activity in the treatment of SDs as a dopamine agonist, inhibitor of GABAA receptor, dual orexin receptor antagonist, respectively. This article focused on the types of SDs, the effects of SDs on mental health, receptors involved in the sleep cycle, and the impact of natural molecules and synthetic molecules in the management of SDs.

Ayurvedic Insights on Improving Poor Sleep Quality

Sleep – this natural urge is so essential phenomenon of life that engages our one third of life-span, still indulging in being slept is mystery to everyone. At one side adequate sleep quality imparts fair concentration, emotional, cognitive motivational harmony inside body’s mind, soul and consciousness. Contrary to which inadequate sleep or poor sleep quality leads to tiredness, lack of focus, exhaustion, a low pain tolerance, anxiety, irritational thoughts, hallucinations, loss of appetite, constipation and many more. Sleep has a positive impact over digestion, metabolism, nourishment and health. It is irresistible, irreplaceable and unique boon for us, which is pillar of our life. The natural cycle of sleep and awakening is depending on Awastha of Sharir Dosha, Kaal Dosha, and few more factors as depicted in Ayurveda texts. So, the quality of sleep depends on these factors. If there is Kshaya of Kapha, or Vriddhi of Vata and Pitta, then the quality of sleep disturbs. In the realm of holistic well-being, Ayurveda, the ancient Indian system of medicine, offers profound insights into optimizing sleep quality. Through personalized approaches, Ayurvedic remedies like herbal formulations, lifestyle modifications, and relaxation techniques aim to rebalance Doshas and promote restful sleep. Integrating practices such as meditation, gentle yoga, and consistent sleep routines can pacify Vata and Pitta Dosha, calm the mind, and induce relaxation, fostering deeper and more rejuvenating sleep. Ayurveda's holistic perspective provides a natural and sustainable pathway to address poor sleep quality and promote overall well-being. The present paper is here to discuss in detail about Sukh Nidra.

Recognition of Energy Harvesting Techniques for Enhanced Operation in WSN Using IoT with Deep Learning

The recognition of energy harvesting techniques for enhanced operation in Wireless Sensor Networks (WSN) using IoT and deep learning entails a novel approach to improving the energy efficiency and operational durability of sensor nodes deployed in various environments. Energy harvesting refers to the process of collecting energy from diverse sources such as solar power, thermal energy, wind energy, and mechanical vibrations, and converting it into electrical energy to power electronic devices, including sensor nodes in a WSN. The integration of the Internet of Things with WSNs allows for interconnectivity, enabling enhanced communication, data exchange, and remote management capabilities. This integration facilitates the deployment of more intelligent and adaptive sensor networks, capable of making decisions based on collected information. Deep learning, a subset of machine learning, plays a vital role in enhancing the operation of WSNs by providing advanced data analysis and predictive modeling capabilities. Through the utilization of deep learning algorithms, the proposed system can forecast energy consumption patterns, identify optimal periods for energy harvesting, and optimize the energy efficiency of sensor nodes. This includes adjusting operational parameters such as data communication rates or sleep cycles based on the predicted availability of harvested energy. Deep learning also aids in identifying and prioritizing the most viable energy sources in the deployment environment of the WSN. By employing appropriate energy harvesting techniques based on environmental conditions, such as solar energy harvesting in summer or mechanical vibration harvesting in industrial settings, the proposed method ensures more efficient operation and sustainability of sensor networks across various applications.