Search Results (1,077)

Autism Spectrum Disorder (ASD) is frequently accompanied by gastrointestinal disturbances, dietary selectivity, and altered stress responses, with growing evidence pointing to gut–brain axis involvement. While intestinal microbiota has been extensively studied, the role of the oral microbiota remains underexplored. This study investigates the associations between oral microbiota composition and behavioral, gastrointestinal, dietary, and neuroendocrine parameters in children with ASD. A total of 45 children aged 2–18 years comprised the study group. Data collection included oral swabs for 16S rRNA gene sequencing, salivary cortisol sampling, dietary records, and standardized behavioral assessments using the Vineland Adaptive Behavior Scale. A total of 363 microbial species across 11 phyla were identified. Significant correlations were observed between specific bacterial taxa and functional gastrointestinal disorders (FGIDs), dietary patterns, salivary cortisol rhythms, and functioning. Children with FGIDs, food selectivity, or macronutrient imbalances exhibited enriched pro-inflammatory taxa (e.g., Selenomonas, Megasphaera), whereas those with typical cortisol secretion or higher adaptive functioning showed greater microbial diversity and abundance of health-associated genera (e.g., Bifidobacterium dentium). These findings suggest that oral microbiota profiles may reflect systemic physiological and neurobehavioral traits in children with ASD. Further longitudinal studies are needed to clarify causal relationships and support the development of microbiota-targeted interventions. Full article

Drought disturbances are becoming more frequent with global warming. Accurately assessing the regulatory effect of drought on vegetation phenology is key to understanding terrestrial ecosystem response mechanisms in the context of climate change. Previous studies on cumulative and lagged effects of drought on vegetation growth have mostly focused on a single vegetation type or the overall vegetation NDVI, overlooking the possible influence of different adaptation strategies of different vegetation types and differences in drought effects on different phenological nodes. This study investigates the cumulative and lagged effects of drought on vegetation phenology across a region of East Asia from 2001 to 2020 using NDVI data and the Standardized Precipitation Evapotranspiration Index (SPEI). We analyzed the start of growing season (SOS) and end of growing season (EOS) responses to drought across four vegetation types: deciduous needleleaf forests (DNFs), deciduous broadleaf forests (DBFs), shrublands, and grasslands. Results reveal contrasting phenological responses: drought delayed SOS in grasslands through a “drought escape” strategy but advanced SOS in forests and shrublands. All vegetation types showed earlier EOS under drought stress. Cumulative drought effects were strongest on DNFs, SOS, and shrubland SOS, while lagged effects dominated DBFs and grassland SOS. Drought impacts varied with moisture conditions: they were stronger in dry regions for SOS but more pronounced in humid areas for EOS. By confirming that drought effects vary by vegetation type and phenology node, these findings enhance our understanding of vegetation adaptation strategies and ecosystem responses to climate stress. Full article

Ensuring the safe operation of Unmanned Aerial Vehicles (UAVs) is crucial for both mission-critical and safety-critical tasks. In scenarios where UAVs must track airborne targets, they need to follow the target’s path while maintaining a safe distance, even in the presence of unmodeled dynamics and environmental disturbances. This paper presents a novel collision avoidance strategy for dynamic quadrotor UAVs during target-tracking missions. We propose a safety controller that combines a learning-based Control Barrier Function (CBF) with standard sliding mode feedback. Our approach employs a neural network that learns the true CBF constraint, accounting for wind disturbances, while the sliding mode controller addresses unmodeled dynamics. This unified control law ensures safe leader-following behavior and precise trajectory tracking. By leveraging a learned CBF, the controller offers improved adaptability to complex and unpredictable environments, enhancing both the safety and robustness of the system. The effectiveness of our proposed method is demonstrated through the AirSim platform using the PX4 flight controller. Full article

In addressing the challenges of low path tracking accuracy and poor robustness during tractor autonomous operation, this paper proposes a path tracking control method for tractors that integrates prescribed performance with sliding mode control (SMC). A key feature of this control method is its inherent immunity to system parameter perturbations and external disturbances, while ensuring path tracking errors are constrained within a predefined range. First, the tractor is simplified into a two-wheeled vehicle model, and a path tracking error model is established based on the reference operation trajectory. By defining a prescribed performance function, the constrained tracking control problem is transformed into an unconstrained stability control problem, guaranteeing the boundedness of tracking errors. Then, by incorporating SMC theory, a prescribed performance sliding mode path tracking controller is designed to achieve robust path tracking and error constraint for the tractor. Finally, both simulation and field experiments are conducted to validate the method. The results demonstrate that compared with the traditional SMC method, the proposed method effectively mitigates the impact of complex farmland conditions, reducing path tracking errors while enforcing strict error constraints. Field experiment data shows the proposed method achieves an average absolute error of 0.02435 m and a standard deviation of 0.02795 m, confirming its effectiveness and superiority. This research lays a foundation for the intelligent development of agricultural machinery. Full article

This paper proposes a novel control strategy for a dual-stage grid-connected solar photovoltaic (PV) system designed to ensure reliable and efficient operation under unstable grid conditions. The strategy incorporates a Phase-Locked Loop (PLL)-based positive sequence estimator for accurate detection of grid voltage disturbances, including sags, swells, and fluctuations in solar irradiance. A dynamic DC-link voltage regulation mechanism is employed to minimize converter power losses and enhance the performance of the Voltage Source Converter (VSC) under weak grid scenarios. The control scheme maintains continuous maximum power point tracking (MPPT) and unity power factor (UPF) operation, thereby improving overall grid power quality. The proposed method is validated through comprehensive simulations and real-time hardware implementation using the OPAL-RT OP4510 platform. The results demonstrate compliance with IEEE Standard 519, confirming the effectiveness and robustness of the proposed strategy. Full article

Background: Insomnia and excessive sleepiness are significant health problems with a complex etiology, increasingly affecting young people, especially students. This study aimed to assess the prevalence of sleep disturbances and patterns of psychoactive drug use among female Polish students. We also explored the potential impact of the COVID-19 pandemic on sleep behaviors. We hypothesized that sleep disorders are common in this group, that medical students are more likely to experience insomnia and excessive sleepiness, and that the pandemic has exacerbated both sleep disturbances and substance use. Methods: This cross-sectional study utilized a custom survey designed using standardized questionnaires—the Athens Insomnia Scale and Epworth Sleepiness Scale—that was distributed online using the Computer-Assisted Web Interviewing method. A total of 11,988 responses were collected from 31 January 2016 to 1 January 2021. Inclusion criteria were being female, having a college student status, and giving informed consent. Results: Among the 11,988 participants, alcohol use declined after the pandemic began (p = 0.001), while sedative use increased (p < 0.001). Insomnia (AIS) was associated with study year, university profile, and field of study (p < 0.001), with the highest rates in first-year and non-medical students. It was more common among users of sedatives, psychostimulants, and multiple substances. No significant change in insomnia was found before and after the pandemic. Excessive sleepiness (ESS) peaked in first-year and medical students. It decreased during the pandemic (p < 0.001) and was linked to the use of alcohol, psychostimulants, cannabinoids, and multiple substances. Conclusions: These findings highlight that female students are particularly vulnerable to sleep disorders. The influence of the COVID-19 pandemic on sleep disturbances remains inconclusive. Given the varied results in the existing literature, further research is needed. Full article

Ensuring a sustainable and healthy human environment in university dormitories is essential for students’ learning, living, and overall health and well-being. To address this need, we carried out a series of systematic field measurements of the noise levels at 30 dormitories in three representative major urban universities in a major provincial capital city in China and designed and implemented a comprehensive questionnaire and surveyed 1005 students about their perceptions of their acoustic environment. We proposed and applied a sustainability–health-oriented, multidimensional assessment framework to assess the acoustic environment of the dormitories and student responses to natural sound, technological sounds, and human-made sounds. Using the Structural Equation Modeling (SEM) approach combined with the field measurements and student surveys, we identified three categories and six factors on student health and well-being for assessing the acoustic environment of university dormitories. The field data indicated that noise levels at most of the measurement points exceeded the recommended or regulatory thresholds. Higher noise impacts were observed in early mornings and evenings, primarily due to traffic noise and indoor activities. Natural sounds (e.g., wind, birdsong, water flow) were highly valued by students for their positive effect on the students’ pleasantness and satisfaction. Conversely, human and technological sounds (traffic noise, construction noise, and indoor noise from student activities) were deemed highly disturbing. Gender differences were evident in the assessment of the acoustic environment, with male students generally reporting higher levels of the pleasantness and preference for natural sounds compared to female students. Educational backgrounds showed no significant influence on sound perceptions. The findings highlight the need for providing actionable guidelines for dormitory ecological design, such as integrating vertical greening in dormitory design, water features, and biodiversity planting to introduce natural soundscapes, in parallel with developing campus activity standards and lifestyle during noise-sensitive periods. The multidimensional assessment framework will drive a sustainable human–ecology–sound symbiosis in university dormitories, and the category and factor scales to be employed and actions to improve the level of student health and well-being, thus, providing a reference for both research and practice for sustainable cities and communities. Full article

This paper proposes a GNSS-compatible method for characterizing the motion of UAV-based navigation enhancement platforms, designed to provide reliable navigation and positioning services in emergency scenarios where GNSS signals are unavailable or severely degraded. The method maps UAV trajectories into standard GNSS navigation messages by establishing a correspondence between ephemeris parameters and platform positions through coordinate transformation and Taylor series expansion. To address modeling inaccuracies, the approach incorporates truncation error analysis and motion-assumption compensation via parameter optimization. This design enables UAV-mounted pseudolite systems to broadcast GNSS-compatible signals without modifying existing receivers, significantly enhancing rapid deployment capabilities in complex or degraded environments. Simulation results confirm precise positional representation in static scenarios and robust error control under dynamic motion through higher-order modeling and optimized broadcast strategies. UAV flight tests demonstrated a theoretical maximum error of 0.4262 m and an actual maximum error of 3.1878 m under real-world disturbances, which is within operational limits. Additional experiments confirmed successful message parsing with standard GNSS receivers. The proposed method offers a lightweight, interoperable solution for integrating UAV platforms into GNSS-enhanced positioning systems, supporting timely and accurate navigation services in emergency and disaster relief operations. Full article

The most frequently used laboratory animals for studies on adipose tissue properties and obesity are rodents. However, there are significant differences in the types of visceral fat depots between rodents and humans, including fat depots in the heart area. The large human fat depot of greatest interest in cardiac research is the epicardial adipose tissue (EAT). Its properties are widely investigated, because the EAT lies directly on the heart’s surface and can easily affect myocardial physiology. The major fat depot in rodents‘ chest—pericardial fat—is located on the ventral surface of the parietal lamina of the pericardium and is often incorrectly referred to as the EAT. Further confusion arises from reports claiming that rodents are entirely devoid of the EAT. We decided to verify adipose tissues in the heart area of 16 male Sprague Dawley rats under physiological conditions and in obesity. The animals in the NFD group (n = 8) were fed with a standard diet while these in the HFD group (n = 8) were fed with a high-fat diet (31% fat) starting from 4 weeks after birth. When the animals reached 12 weeks, the presence of fat deposits was verified. Additionally, their blood was collected to characterize carbohydrate and lipid metabolism changes, adipokine profile alterations, and their systemic inflammation status. The obesogenic diet caused significant disturbances in their carbohydrate and lipid metabolism, as well as hyperleptinemia. A high-fat diet primarily promoted the accumulation of pericardial fat, which was absent in the NFD rats and observed in 6 out of the 8 HFD animals. In both groups, adipocytes were also found directly on the hearts’ surfaces (EAT), albeit in very small numbers and limited to the atrioventricular groove on the dorsal side of the hearts. These adipocytes were dispersed among the vessels, making quantitative assessment and separation difficult, however, macroscopic evaluation revealed no noticeable differences in its extent. In conclusion, although rats are not entirely devoid of the EAT, their suitability for studying the properties of the EAT appears to be considerably limited. Full article

Background/Objectives: Schizophrenia has been associated with increased inflammatory and metabolic disturbances. Perceived family support potentially affects inflammatory and metabolic biomarkers. The aim of this study was to determine the interrelations between family support, C-reactive protein (CRP) and Body Mass Index (BMI) in a sample of outpatients with schizophrenia. Importantly, this study sought to elucidate the effect of perceived family support on inflammatory processes among patients with schizophrenia. Methods: In this cross-sectional correlation study, 206 outpatients with schizophrenia in clinical remission completed a standardized self-report questionnaire that assessed family support (Family Support Scale—FSS). Sociodemographic, clinical and laboratory data were also recorded. Results: Among the participants, 49.5% had detectable CRP values (≥0.11 mg/dL), whereas 14.6% had positive CRP levels (>0.6 mg/dL). There was a significant difference in CRP levels among the different BMI groups (normal weight/overweight vs. obese). For obese patients, the crude odds ratios (ORs) for detectable and positive CRP values were 1.980 (95% confidence interval (CI) [1.056, 3.713]) and 27.818 (95% CI [6.300, 122.838]), respectively. Significant positive correlations were observed among CRP, BMI and illness duration, while scores on the FSS were negatively associated with these variables. The results of binary logistic regression analysis indicated that both BMI and family support were significant factors in determining the likelihood of having positive CRP levels, with each unit increase in the BMI associated with a 17% (95% CI [0.025, 0.337]) increase in the odds, and with each unit increase in family support leading to an 8.6% (95% CI [0.018, 0.15]) decrease. A moderation analysis revealed that the association between family support and the probability of having positive CRP levels depends on the BMI value, but only for obese patients did the protective effect of family support significantly decrease the magnitude of the risk of having positive CRP (b = −0.1972, SE = 0.053, OR = 0.821, p = 0.000, 95% CI [−0.3010, −0.0934]). Conclusions: The effect of perceived family support on inflammatory responses becomes evident in cases where beyond metabolic complications, inflammatory processes have already been established. Increased perceived family support seems to protect against inflammation and, notably, the association between low perceived family support and increased inflammation is even stronger. Establishing the role of family involvement during the treatment of patients with schizophrenia through inflammatory processes is a novelty of this study, emphasizing the need to incorporate family therapy into psychiatric treatment plans. However, primary interventions are considered necessary for patients with schizophrenia in order to maintain their BMI within normal limits and avoid the subsequent nosological sequelae. Full article

The human voice is an invaluable tool for communication, carrying information about a speaker’s emotional state and cognitive health. Recent research highlights the potential of acoustic biomarkers to detect early signs of mental health and neurodegenerative conditions. Despite their promise, vocal biomarkers remain underutilized in clinical settings, with limited standardized protocols for assessment. This Perspective article argues for the integration of acoustic biomarkers into digital health solutions to improve the detection and monitoring of cognitive impairment and emotional disturbances. Advances in speech analysis and machine learning have demonstrated the feasibility of using voice features such as pitch, jitter, shimmer, and speech rate to assess these conditions. Moreover, we propose that singing, particularly simple melodic structures, could be an effective and accessible means of gathering vocal biomarkers, offering additional insights into cognitive and emotional states. Given its potential to engage multiple neural networks, singing could function as an assessment tool and an intervention strategy for individuals with cognitive decline. We highlight the necessity of further research to establish robust, reproducible methodologies for analyzing vocal biomarkers and standardizing voice-based diagnostic approaches. By integrating vocal analysis into routine health assessments, clinicians and researchers could significantly advance early detection and personalized interventions for cognitive and emotional disorders. Full article

Parkinson’s Disease (PD) is a progressive neurodegenerative disorder marked by motor and non-motor symptoms, including cognitive decline, mood disturbances, and sensory deficits. While dopaminergic treatments remain the gold standard, they present long-term side effects and limited impact on non-motor symptoms. Transcranial Pulse Stimulation (TPS) has emerged as a promising adjunct therapy in neurological and psychiatric conditions, but its effects in PD remain underexplored. This open-label, single-arm trial protocol involves 14 PD participants and outlines a personalized 12-session treatment approach combined with a homogeneously distributed TPS intervention among patients with PD. The approach addresses the subject’s most prominent symptoms, as identified through validated clinical assessments, encompassing domains related to both motor and non-motor symptoms. Over 2.5 months, besides the intervention sessions, the 14 participants will undergo an MRI brain scan, a baseline assessment, a post-treatment assessment, and a 1-month follow-up assessment. The study aims to determine whether personalized TPS is a feasible and safe intervention and whether it improves PD symptoms across multiple functional domains. This study represents the first structured attempt to evaluate a multimodal, personalized TPS intervention in patients with PD. It addresses gaps in current treatment approaches and may support the development of future strategies for integrated, symptom-targeted neuromodulation. Full article

Background. Major Depressive Disorder (MDD) is a highly prevalent and disabling condition frequently accompanied by cognitive deficits, impaired psychosocial functioning, and biological rhythm disturbances. Despite extensive literature on individual associations between depression and circadian disruptions, the mediating role of biological rhythms in the functional outcomes of MDD remains underexplored. Objectives. This study aimed to explore the associations between depression severity, biological rhythms, sleep quality, and psychosocial functioning, and to assess whether biological rhythm disturbances mediate the impact of depression on functioning. Methods. Sixty-one inpatients diagnosed with moderate-to-severe MDD were assessed using standardized instruments: BDI-II for depressive symptoms, BRIAN for biological rhythms, PSQI for sleep quality, and FAST for global functioning. Group comparisons, non-parametric correlations, and a mediation analysis were conducted to test direct and indirect effects. Results. Participants showed severe depressive symptoms, impaired functioning, disrupted biological rhythms, and poor sleep. Women reported more depressive episodes, reduced autonomy, and worse sleep than men. Depression severity was associated with circadian and sleep disturbances, which in turn related to functional impairment. Mediation analysis suggested that biological rhythms partially mediate the impact of depression on functioning. Conclusions. Findings from this preliminary analysis suggest that biological rhythm disturbances may play a mediating role in the relationship between depressive symptoms and daily psychosocial functioning. While not conclusive, these results highlight the potential relevance of chronobiological factors in understanding functional outcomes in MDD. Further research using longitudinal and controlled designs is needed to clarify these associations and their clinical implications. Full article

Forests provide habitat for diverse species and play a key role in mitigating climate change. Remote sensing enables efficient monitoring of many forest attributes across vast areas, thus supporting effective and efficient management strategies. This study aimed to identify an effective combination of remote sensing sensors for estimating biophysical variables in Mediterranean and temperate forests that can be easily translated into an operational context. Aboveground biomass (AGB), canopy height (CH), and forest canopy cover (FCC) were estimated using a combination of optical (Sentinel-2, Landsat) and radar sensors (Sentinel-1 and TerraSAR-X/TanDEM-X), along with records of past forest disturbances and topography-related variables. As a reference, lidar-derived AGB, CH, and FCC were used. Model performance was assessed not only with standard approaches such as out-of-bag sampling but also with completely independent lidar-derived reference datasets, thus enabling evaluation of the model’s temporal inference capacity. In Mediterranean forests, models based on optical imagery outperformed the radar-enhanced models when estimating FCC and CH, with elevation and spectral indices being key predictors of forest structure. In contrast, in denser temperate forests, radar data (especially X-band relative heights) were crucial for estimating CH and AGB. Incorporating past disturbance data further improved model accuracy in these denser ecosystems. Overall, this study underscores the value of integrating multi-source remote sensing data while highlighting the limitations of temporal extrapolation. The presented methodology can be adapted to enhance forest variable estimation across many forest ecosystems. Full article

Background and Objectives: Idiopathic normal-pressure hydrocephalus (NPH) is a treatable, but diagnostically challenging condition in the elderly marked by gait disturbance, cognitive decline, and urinary incontinence. Ventriculoperitoneal (VP) shunting is effective, but the prognostic significance of symptom duration before surgery remains unclear. This systematic review evaluates symptom duration in NPH patients with postoperative outcomes. Methods: A systematic search of PubMed, Scopus, and Embase was conducted per PRISMA guidelines. Studies were included if they assessed clinical or radiological outcomes of VP shunting in adult NPH patients, reported symptom duration, and had a follow-up of at least one month. Clinical outcomes (MMSE, TUG, NPH score) were qualitatively analyzed due to study heterogeneity. Results: Twenty-four studies comprising 1169 patients were included (mean age: 72.45 years; mean symptom duration: 33.04 months). Most studies reported clinical improvement after VP shunting. However, few directly evaluated the effect of symptom duration, yielding inconsistent findings: some suggested better outcomes with shorter symptom duration, while others found no clear correlation. Larger studies often lacked conclusive data, and no randomized controlled trials were identified. Conclusions: VP shunting remains an effective intervention for NPH; however, evidence supporting the predictive value of preoperative symptom length is inconclusive. This review highlights the need for standardized diagnostic protocols and larger prospective studies to clarify this association and optimize surgical timing. Full article