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Introduction: According to current knowledge, at birth, the pineal gland and melatonin receptors are already present and the suprachiasmatic nucleus is largely functional, and noradrenaline, the key pineal transmitter, can be detected in the early foetal period. It is still unclear why the pineal gland is not able to start its own pulsatile synthesis and secretion of melatonin in the first months of life, and as a result, infants during this time are dependent on an external supply of melatonin. Method: The causes and consequences of this physiological melatonin deficiency in human infancy are examined in a systematic review of the literature, in which 40 of 115 initially selected publications were evaluated in detail. The references of these studies were checked for relevant studies on this topic. References from previous reviews by the author were taken into account. Results: The development and differentiation of the pineal gland, the pinealocytes, as the site of melatonin synthesis, and the development and synaptic coupling of the associated predominantly noradrenergic neural pathways and vessels and the associated Lhx4 homebox only occurs during the first year of life. Discussion: The resulting physiological melatonin deficiency is associated with sleep disorders, infant colic, and increased crying in babies. Intervention studies indicate that this deficiency should be compensated for through breastfeeding, the administration of nonpooled donor milk, or through industrially produced chrononutrition made from nonpooled cow’s milk with melatonin-poor day milk and melatonin-rich night milk. Full article

Deprivation of sleep (DS) and its effects on circadian rhythm gene expression are not well understood despite their influence on various physiological and psychological processes. This study aimed to elucidate the changes in the expression of circadian rhythm genes following a night of sleep and DS. Their correlation with sleep architecture and physical activity was also examined. The study included 81 participants who underwent polysomnography (PSG) and DS with actigraphy. Blood samples were collected after PSG and DS. Expression levels of brain and muscle ARNT-like 1 (BMAL1), circadian locomotor output cycles kaput (CLOCK), neuronal PAS domain protein 2 (NPAS2), period 1 (PER1), cryptochrome 1 (CRY1) and nuclear receptor subfamily 1 group D member 1 (NR1D1) were analyzed using qRT-PCR. DS decreased the expression of CLOCK and BMAL1 while increasing PER1. PER1 expression correlated positively with total sleep time and non-rapid-eye-movement (NREM) sleep duration and negatively with sleep latency, alpha, beta and delta waves in the O1A2 lead. Physical activity during DS showed positive correlations with CLOCK, BMAL1, and CRY1. The findings highlight the role of PER1 in modulating sleep patterns, suggesting potential targets for managing sleep-related disorders. Further research is essential to deepen the understanding of these relationships and their implications. Full article

Currently, the number of vehicles in circulation continues to increase steadily, leading to a parallel increase in vehicular accidents. Among the many causes of these accidents, human factors such as driver drowsiness play a fundamental role. In this context, one solution to address the challenge of drowsiness detection is to anticipate drowsiness by alerting drivers in a timely and effective manner. Thus, this paper presents a Convolutional Neural Network (CNN)-based approach for drowsiness detection by analyzing the eye region and Mouth Aspect Ratio (MAR) for yawning detection. As part of this approach, endpoint delineation is optimized for extraction of the region of interest (ROI) around the eyes. An NVIDIA Jetson Nano-based device and near-infrared (NIR) camera are used for real-time applications. A Driver Drowsiness Artificial Intelligence (DD-AI) architecture is proposed for the eye state detection procedure. In a performance analysis, the results of the proposed approach were compared with architectures based on InceptionV3, VGG16, and ResNet50V2. Night-Time Yawning–Microsleep–Eyeblink–Driver Distraction (NITYMED) was used for training, validation, and testing of the architectures. The proposed DD-AI network achieved an accuracy of 99.88% with the NITYMED test data, proving superior to the other networks. In the hardware implementation, tests were conducted in a real environment, resulting in 96.55% and 14 fps on average for the DD-AI network, thereby confirming its superior performance. Full article

Elevated temperatures in urban centers have become a common problem in cities around the world. However, the climate problems in suburban areas are equally severe; there is an urgent need to find zero-carbon ways to mitigate this problem. Recent studies have revealed the thermal performance of vegetation, buildings, and water surfaces. They functioned differently regarding the climate at different periods of the day. Accordingly, this study synthesizes remote sensing technology and meteorology station observation data to deeply explore the differences in the role of each climate-influencing factor in the suburban areas of Chengdu. The land surface temperature (LST) and air temperature (T_a) were used as thermal environmental indicators, while the normalized difference vegetation index (NDVI), normalized difference water index (NDWI), normalized difference built-up index (NDBI), and altitude were used as environmental factors. The results showed that the relevant influences of the environmental factors on the climate in the sample areas were significantly affected by the time of the day. The NDVI (R² = 0.5884), NDBI (R² = 0.3012), and altitude (R² = 0.5638) all showed strong correlations with T_a during the night (20:00–7:00), which gradually weakened after sunrise, yet the NDWI showed a poorer cooling effect during the night, which gradually strengthened after sunrise, reaching a maximum at 15:00 (R² = 0.5012). One reason for this phenomenon was the daily weather changes. These findings facilitate the advancement of the understanding of the climate in suburban areas and provide clear directions for further thermal services targeted towards people in different urban areas. Full article

This study investigates the possibility of utilising a drone equipped with a thermal camera to monitor the spatial distribution of red deer (Cervus elaphus) and to determine their behavioural patterns, as well as preferences for vegetation types in a moor in Denmark. The spatial distribution of red deer was mapped according to time of day and vegetation types. Reed deer were separated manually from fallow deer (Dama dama) due to varying footage quality. Automated object detection from thermal camera footage was used to identification of two behaviours, “Eating” and “Lying”, enabling insights into the behavioural patterns of red deer in different vegetation types. The results showed a migration of red deer from the moors to agricultural fields during the night. The higher proportion of time spent eating in agricultural grass fields compared to two natural vegetation types, “Grey dune” and “Decalcified fixed dune”, indicates that fields are important foraging habitats for red deer. The red deer populations were observed significantly later on grass fields compared to the natural vegetation types. This may be due to human disturbance or lack of randomisation of the flight time with the drone. Further studies are suggested across different seasons as well as the time of day for a better understanding of the annual and diurnal foraging patterns of red deer. Full article

Night lighting is essential for urban life, and the occurrence of faults can significantly affect the presentation of lighting effects. Many reasons can cause lighting faults, including the damage of lamps and circuits, and the typical manifestation of the faults is that the lights do not light up. The current troubleshooting mainly relies on artificial visual inspection, making detecting faults difficult and time-consuming. Therefore, it is necessary to introduce technical means to detect lighting faults. However, current research on lighting fault detection mainly focuses on using non-visual methods such as sensor data analysis, which has the disadvantages of having a high cost and difficulty adapting to large-scale fault detection. Therefore, this study mainly focuses on solving the problem of the automatic detection of night lighting faults using machine vision methods, especially object detection methods. Based on the YOLOv5 model, two data fusion models have been developed based on the characteristics of lighting fault detection inverse problems: YOLOv5 Channel Concatenation and YOLOv5 Image Fusion. Based on the dataset obtained from the developed automatic image collection and annotation system, the training and evaluation of these three models, including the original YOLOv5, YOLOv5 Channel Concatenation, and YOLOv5 Image Fusion, have been completed. Research has found that applying complete lighting images is essential for the problem of lighting fault detection. The developed Image Fusion model can effectively fuse information and accurately detect the occurrence and area of faults, with a mAP value of 0.984. This study is expected to play an essential role in the intelligent development of urban night lighting. Full article

Remotely sensed nighttime light data have become vital for electrification mapping in data-scarce regions. However, uncertainty persists regarding the veracity of these electrification maps. This study investigates how characteristics of electrified areas influence their detectability using nighttime lights. Utilizing a dataset comprising the locations, installation date, and electricity purchase history of thousands of electric meters and transformers from utilities in Rwanda and Kenya, we present a systematic error assessment of electrification maps produced with nighttime lights. Descriptive analysis is employed to offer empirical evidence that the likelihood of successfully identifying an electrified nighttime light pixel increases as characteristics including the time since electrification, the number of meters within a pixel, and the total annual electricity purchase of meters in a pixel increase. The performance of models trained on various temporal aggregations of nighttime light data (annual, quarterly, monthly, and daily) was compared, and it was determined that aggregation at the monthly level yielded the best results. Additionally, we investigate the transferability of electrification models across locations. Our findings reveal that models trained on data from Rwanda demonstrate strong transferability to Kenya, and vice versa, as indicated by balanced accuracies differing by less than 5% when additional data from the test location are included in the training set. Also, models developed with data from the centralized grid in East Africa were found to be useful for detecting areas electrified with off-grid systems in West Africa. This research provides valuable insight into the characterization of sources of nighttime lights and their utility for mapping electrification. Full article

An equatorial plasma bubble (EPB) is characterized by ionospheric irregularities which disturb radio waves by causing phase and amplitude scintillations or even signal loss. It is becoming increasingly important in space weather to assure the reliability of radio systems in both space and on the ground. This paper presents a newly established GNSS ionospheric observation network (GION) around the north equatorial ionization anomaly (EIA) crest in south China, which has a longitudinal coverage of ∼30° from 94°E to 124°E. The measurement with signals from geostationary earth orbit (GEO) satellites of the BeiDou navigation satellite system (BDS) is capable of separating the temporal and spatial variations of the ionosphere. A temporal fluctuation of TEC (TFT) parameter is proposed to characterize EPBs. The longitude of the EPBs’ generation can be located with TFT variations in the time–longitude dimension. It is found that the post-sunset EPBs have a high degree of longitudinal variability. They generally show a quasiperiodic feature, indicating their association with atmospheric gravity wave activities. Wave-like structures with different scale sizes can co-exist in the same night. Full article

Natural gas (NG) is commonly used in kitchens, powering stoves, ovens, and other appliances. While it is known for its efficiency and convenience, NG contributes to the release of nitrogen dioxide (NO₂) and can have significant implications for human health. In this study, the importance of the use of NG in kitchens on human exposure to NO₂ was analyzed. An extensive literature review in the field was conducted, and the NO₂ levels were assessed in kitchens with NG cookers in Aveiro and electric cookers in Porto, both in Portugal. Higher levels of NO₂ were found in kitchens in Aveiro, where NO₂ levels outdoors are lower than in Porto. This pollutant can spread to other rooms, especially when ventilation is lacking, which is particularly concerning during colder seasons and at night. As around 70% of the time is spent at home, this can have a significant impact on human exposure to NO₂. Therefore, although Aveiro has low levels of NO₂ outdoors, its population may be exposed to much higher levels of this pollutant than the Porto population, a city with air quality issues, but predominantly using electric cookers. This finding emphasizes the need for the stricter regulation of NG use indoors to protect human health and also suggests a shift in human health protection policies from mere monitoring/control of outdoor air quality to a comprehensive assessment of human exposure, including exposure to indoor air quality. Full article

Chemical desiccation is widely used in agriculture to anticipate harvest and mitigate the effects of adverse environmental conditions. It is applied to both grains and seeds. Although this practice is widely used, there are still significant gaps in understanding the effects of different herbicide application times on seed quality and plant physiological responses. The objective of this study was to evaluate the effects of different herbicide application times on cowpea, focusing on seed quality, physiological responses, and biochemical composition, including chlorophylls, carotenoids, sugars, and proline, under nocturnal desiccation. In the first experiment, eight herbicides and two mixtures were applied at night: diquat, flumioxazin, diquat + flumioxazin, glufosinate ammonium, saflufenacil, carfentrazone, diquat + carfentrazone, atrazine, and glyphosate. All of the tested herbicides caused a reduction in normal seedling formation, with the diquat + carfentrazone combination resulting in 100% abnormal seedlings. A significant decrease in chlorophyll levels (chlorophyll a: 63.5%, chlorophyll b: 50.2%) was observed using diquat, which indicates damage to photosynthetic processes, while the carotenoid content increased. Total soluble sugars and proline were also negatively impacted, reflecting physiological stress and metabolic changes in seedlings. In the second experiment, three application times were tested with diquat, diquat + flumioxazin, and diquat + carfentrazone. Nocturnal application showed the most significant reduction in chlorophyll levels and increased carotenoid levels. Application at noon and late afternoon also significantly changed the soluble sugar and proline levels. These results indicate that the herbicide application time directly influences the seeds’ physiological quality. Full article

The examination of land-use change simulations across a range of scenarios represents a pivotal research avenue for the advancement of sustainable development analysis. Nevertheless, the extant research merely categorises all building land in a land-use classification into a single category, which is unable to provide a detailed analysis of the dynamic internal spatial form of the city. This paper analyses 17 LCZ land-use types in Guiyang City in 2013 and 2022, and reclassifies them into 7 RLCZ land-use types based on the height of urban building sites. It also proposes three possible scenarios of BAU, WLC, and SPC in 2040 and simulates their land-use changes using the PLUS model. The results demonstrate that (1) the size of low-rise buildings in Guiyang has declined significantly over the past decade; (2) built-up land within cities is significantly affected by drivers such as night-time lighting, topography, elevation, and roads; (3) the SPC scenario emphasises a development pattern of land intensification and a focus on high density in urban built space. It also protects the stability of the ecosystem. The scenario can provide informative suggestions for spatial pattern changes in rapidly developing cities such as Guiyang. Full article

Durum wheat (DW) is one of the major crops grown in the Mediterranean area, a climate-vulnerable region where the increase in day/night (d/n) temperature is severely threatening DW yield stability. In order to improve DW heat tolerance, the introgression of chromosomal segments derived from the wild gene pool is a promising strategy. Here, four DW-Thinopyrum spp. near-isogenic recombinant lines (NIRLs) were assessed for their physiological response and productive performance after intense heat stress (IH, 37/27 °C d/n) had been applied for 3 days at anthesis. The NIRLs included two primary types (R5, R112), carriers (+) of a differently sized Th. ponticum 7el1L segment on the DW 7AL arm, and two corresponding secondary types (R69-9/R5, R69-9/R112), possessing a Th. elongatum 7EL segment distally inserted into the 7el1L ones. Their response to the IH stress was compared to that of corresponding non-carrier sib lines (−) and the heat-tolerant cv. Margherita. Overall, the R112+, R69-9/R5+ and R69-9/R112+ NIRLs exhibited a tolerant behaviour towards the applied stress, standing out for the maintenance of leaf relative water content but also for the accumulation of proline and soluble sugars in the flag leaf and the preservation of photosynthetic efficiency. As a result, all the above three NIRLs (R112+ > R69-9/R5+ > R69-9/R112+) displayed good yield stability under the IH, also in comparison with cv. Margherita. R112+ particularly relied on the strength of spike fertility/grain number traits, while R69-9/R5+ benefited from efficient compensation by the grain weight increase. This work largely confirmed and further substantiated the value of exploiting the wild germplasm of Thinopyrum species as a useful source for the improvement of DW tolerance to even extreme abiotic stress conditions, such as the severe heat treatment throughout day- and night-time applied here. Full article

Strategically enriching the environment of zoo felids to encourage innate behaviors is essential to good welfare. To investigate how engagement differs among sensory-based enrichment, six items representing tactile (firehose log, Jolly Eggs), visual (mirror, movie), and olfactory (cinnamon, cologne) sensory categories were offered to three adult cheetah siblings. Each item was offered four times: twice during daytime hours and twice overnight (≥5 h/occasion). Static video monitoring was used to investigate engagement frequency and duration for each item and to observe grooming behaviors. Cheetahs engaged with visual enrichment more frequently (p < 0.05) and for greater (p < 0.05) periods than other items. Allogrooming occurred most frequently (p < 0.05) when the movie was provisioned at night. Tactile enrichment was only modestly engaged, with fewer but longer engagements (p < 0.05) at nighttime than at daytime. Autogrooming frequency did not vary among enrichment items but was greater (p < 0.05) at night than day. These findings showed that zoo cheetah responses to sensory enrichment items differed based on type and time of day. Visual stimuli were favored, whereas olfactory stimuli were generally ignored. This illustrates the benefit of diverse sensory-specific enrichment strategies. Such dynamic strategies can help overcome the challenge of individual preferences to encourage engagement reflective of the animal’s natural behaviors. Full article

Objectives: Eating disorders (EDs) have emerged as a growing public health concern. However, the role of sleep in this context remains underexplored. The aim of this cross-sectional study was to determine the associations between sleep parameters and chronotype with ED risk in a sample of university students in Spain. Methods: ED risk was assessed via the Sick, Control, One stone, Fat, Food Questionnaire, and sleep quality was assessed via the Pittsburgh Sleep Quality Index. Other sleep parameters and chronotypes were self-reported. Sociodemographic, body composition, lifestyle, and depressive symptom data were collected. Logistic and linear regression models adjusted for the main confounders were used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs) of the study associations. Results: A total of 403 students (70.2% female) aged 18 to 30 years participated in the study. Those reporting poor sleep quality (OR = 1.85, 95% CI 1.08–3.17, p = 0.025) and ≤6 h of night-time sleep duration (OR = 4.14, 95% CI 2.00–8.57, p < 0.01) were more likely to be at risk of EDs in the adjusted analyses. The association between night-time sleep duration and the risk of ED did not remain significant when we adjusted for sleep quality. In addition, an evening chronotype was associated with an increased risk of EDs (OR = 1.68, 95% CI 1.07–2.66, p = 0.039) only before adjustment for confounders. Conclusions: Among university students, poorer sleep quality was cross-sectionally associated with EDs. Future prospective studies are needed to examine whether promoting sleep quality may serve as an effective strategy for preventing the risk of EDs. Full article

This paper presents an advanced automatic number plate recognition (ANPR) system designed specifically for Qatar’s diverse license plate landscape and challenging environmental conditions. Leveraging the YOLOv8 deep learning model, particularly the YOLOv8s variant, we achieve state-of-the-art accuracy in both license plate detection and number recognition. Our innovative approach includes a comprehensive dataset enhancement technique that simulates adverse conditions, significantly improving the model’s robustness in real-world scenarios. We integrate edge computing using a Raspberry Pi with server-side processing, demonstrating an efficient solution for real-time ANPR applications. The system maintains greater than 93% overall performance across various environmental conditions, including night-time and rainy scenarios. We also explore the impact of various pre-processing techniques, including edge detection, k-mean thresholding, DBSCAN, and Gaussian mixture models, on the ANPR system’s performance. Our findings indicate that modern deep learning models like YOLOv8 are sufficiently robust to handle raw input images and do not significantly benefit from additional pre-processing. With its high accuracy and real-time processing capability, the proposed system represents a significant advancement in ANPR technology and is particularly suited for Qatar’s unique traffic management needs and smart city initiatives. Full article