Search Results (91)

Environmental monitoring systems often operate continuously, measuring various parameters, including carbon dioxide levels (CO₂), relative humidity (RH), temperature (T), and other factors that affect environmental conditions. Such systems are often referred to as smart systems because they can autonomously monitor and respond to environmental conditions and can be integrated both indoors and outdoors to detect, for example, structural anomalies. However, these systems typically have high energy consumption, data overload, and large equipment sizes, which makes them difficult to install in constrained spaces. Therefore, three challenges remain unresolved: efficient energy use, accurate data measurement, and compact installation. To address these limitations, this study proposes a two-to-one threshold sampling approach, where the CO₂ measurement is activated when the specified T and $RH$ change thresholds are exceeded. This event-driven method avoids redundant data collection, minimizes power consumption, and is suitable for resource-constrained embedded systems. The proposed approach was implemented on a low-power, small-form and self-made multivariate sensor based on the PIC16LF19156 microcontroller. In contrast, a commercial monitoring system and sensor modules based on the Arduino Uno were used for comparison. As a result, by activating only key points in the T and $RH$ signals, the number of CO₂ measurements was significantly reduced without loss of essential signal characteristics. Signal reconstruction from the reduced points demonstrated high accuracy, with a mean absolute error (MAE) of 0.0089 and root mean squared error (RMSE) of 0.0117. Despite reducing the number of CO₂ measurements by approximately 41.9%, the essential characteristics of the signal were saved, highlighting the efficiency of the proposed approach. Despite its effectiveness in controlled conditions (in buildings, indoors), environmental factors such as the presence of people, ventilation systems, and room layout can significantly alter the dynamics of CO₂ concentrations, which may limit the implementation of this approach. Future studies will focus on the study of adaptive threshold mechanisms and context-dependent models that can adjust to changing conditions. This approach will expand the scope of application of the proposed two-to-one sampling technique in various practical situations. Full article

Modular integrated construction (MiC) is a cutting-edge approach to construction that significantly improves efficiency and reduces project timelines by prefabricating entire building modules off-site. Despite the operational benefits of MiC, the carbon footprint of its extensive supply chain remains understudied. This study develops a hybrid approach that combines multi-agent simulation (MAS) with deep learning to provide scenario-based estimations of CO₂ emissions, costs, and schedule performance for MiC supply chain. First, we build an MAS model of the MiC supply chain in AnyLogic, representing suppliers, the prefabrication plant, road transport fleets, and the destination site as autonomous agents. Each agent incorporates activity data and emission factors specific to the process. This enables us to translate each movement, including prefabricated components of construction deliveries, module transfers, and module assembly, into kilograms of CO₂ equivalent. We generate 23,000 scenarios for vehicle allocations using the multi-agent model and estimate three key performance indicators (KPIs): cumulative carbon footprint, logistics cost, and project completion time. Then, we train artificial neural network and statistical regression machine learning algorithms to captures the non-linear interactions between fleet allocation decisions and project outcomes. Once trained, the models are used to determine optimal fleet allocation strategies that minimize the carbon footprint, the completion time, and the total cost. The approach can be readily adapted to different MiC configurations and can be extended to include supply chain, production, and assembly disruptions. Full article

Cognitive dysfunction represents one of the most persistent and disabling features of Long COVID, yet its molecular underpinnings remain incompletely understood. This narrative review synthesizes current evidence on the pathophysiological mechanisms linking SARS-CoV-2 infection to long-term neurocognitive sequelae. Key processes include persistent neuroinflammation, blood–brain barrier (BBB) disruption, endothelial dysfunction, immune dysregulation, and neuroendocrine imbalance. Microglial activation and cytokine release (e.g., IL-6, TNF-α) promote synaptic dysfunction and neuronal injury, while activation of inflammasomes such as NLRP3 amplifies CNS inflammation. Vascular abnormalities, including microthrombosis and BBB leakage, facilitate the infiltration of peripheral immune cells and neurotoxic mediators. Hypothalamic–pituitary–adrenal axis dysfunction and reduced vagal tone further exacerbate systemic inflammation and autonomic imbalance. Biomarkers such as GFAP, NFL, IL-6, and S100B have been associated with both neuroinflammation and cognitive symptoms. Notably, transcriptomic signatures in Long COVID overlap with those observed in Alzheimer’s disease, highlighting shared pathways involving tau dysregulation, oxidative stress, and glial reactivity. Understanding these mechanisms is critical for identifying at-risk individuals and developing targeted therapeutic strategies. This review underscores the need for longitudinal research and integrative biomarker analysis to elucidate the molecular trajectory of cognitive impairment in Long COVID. Full article

Purpose: Post-COVID-19 syndrome (PCS) is characterized by low cardio-respiratory fitness (CRF). Recent research focuses on the role of autonomic nervous system dysfunction (AD) as a potential contributor to the diminished exercise performance. The aim is to determine the prevalence of AD—chronotropic insufficiency (CI) and abnormal heart rate recovery (HRR) in long-term PCS subjects and to analyse their association with exercise capacity. Patients and Methods: A total of 192 subjects with a history of SARS-CoV-2 infection were included. Chronic Fatigue Syndrome Questionnaire (CFSQ) was applied, and two symptomatic and asymptomatic emerged. Forty-seven had post-COVID complaints, persisting up to thirty months post-acute episode. CI and HRR were determined during the cardio-pulmonary exercise test (CPET). Results: Symptomatic subjects were divided into mild (20) and moderate-severe (27), depending on the CFSQ score; forty-eight PCS subjects without complaints served as a control group. Subjects with moderate-severe PCS showed lower peak VO2 (24.13 ± 6.1 mL/min/kg vs. 26.73 ± 5.9 mL/min/kg, vs. 27.01 ± 6.3 mL/min/kg), as compared to the mild/asymptomatic subjects. Diminished physical activity was established in 10 (37%) of the moderate-severe, 7 (35%) of the mildly symptomatic and 14 (29%) of the asymptomatic groups. The occurrence of AD in the mild/moderate-severe and control groups were, respectively, CI 35% vs. 81.5% vs. 12.5%. Abnormal HRR was, respectively, 20% vs. 33% vs. 8%. None of the subjects had depleted breathing reserve, dynamic hyperinflation, exercise bronchospasm or desaturation. Neither CI nor abnormal HRR correlated to peak O2. Conclusions: AD is present among long-term PCS subjects and may limit the cardio-respiratory response to exercise but is not independently associated with it. Assuming the multiorgan ANS innervation, it is highly probable that AD has diverse pathological pathways in the various PCS phenotypes and contributes differently by cerebral, cardiovascular, respiratory, peripheral or mixed pathways to the diminished neuro-cognitive and physical performance. Full article

The high-input production mode of rice monoculture (RM) has caused severe soil degradation and biodiversity loss, necessitating a transition toward more sustainable practices. The traditional rice-fish co-culture (RF) may provide valuable insights for this situation. However, it remains elusive how long-term RF system influences soil microbial community structure, enzyme activities, and carbon (C) sequestration. Here, a study was conducted at two representative RF areas in Lianshan Zhuang and Yao Autonomous County. At Shatian (P1), three treatments included rice monoculture (RM1) and 2-year and 5-year RF (RF2, RF5). At Gaoliao (P2), the experimental treatments included rice monoculture (RM2) and 15 and 30 years of RF (RF15, RF30). We collected the surface layer (0–20 cm) soils. Then, we analyzed the chemical properties, phospholipid fatty acids (PLFA), and enzyme activities to investigate the effects of their variation on soil C sequestration. The results showed that RF treatments significantly increased soil organic C (SOC) content. Specifically, RF2 and RF5 treatments promoted the SOC content by 4.82% and 13.60% compared with RM1 treatment at P1, respectively; RF15 and RF30 treatments increased the SOC content by 23.41% and 31.93% compared with RM2 treatment at P2, respectively. Additionally, RF5 treatment significantly increased the biomass of the soil microbial community in comparison with RM1 treatment, as did RF15 treatment and RF30 treatment compared with RM2 treatment, including the contents of total PLFA and the PLFA of gram-positive bacteria (G+), gram-negative bacteria (G−), actinomycetes, fungi, and bacteria. Activities of β-glucosidase, cellobiohydrolase, β-1,4-N-acetylglucosaminidase, and urease significantly increased in RF5 and RF30 treatments. The piecewise SEM results indicated that the changes of total PLFA content and the PLFA content ratio of fungi to bacteria were related to contents of dissolved organic C (DOC) and total N (TN) under different RF durations, which are key indicators affecting SOC content. Overall, SOC storage increases with the RF durations, and soil microbial community structure may drive soil C sequestration under long-term RF, which provides a scientific significance and practical value in promoting the sustainability of agricultural ecosystems, enhancing the potential of soil as a carbon sink, and addressing global climate change. Full article

On 23 January 2024, a M_S7.1 earthquake struck Wushi County, Xinjiang Uygur Autonomous Region, marking the largest seismic event in the Southern Tianshan (STS) region in the past century. This study investigates the relationship between hydrothermal fluid circulation and seismic activity by analyzing the chemical composition and origin of fluids in natural hot springs along the Maidan Fracture (MDF). Results reveal two distinct hydrochemical water types (Ca-HCO₃ and Ca-Mg-Cl). The δD and δ¹⁸O values indicating spring water are influenced by atmospheric precipitation input and altitude. Circulation depths (621–3492 m) and thermal reservoir temperatures (18–90 °C) were estimated. Notably, the high ³He/⁴He ratios (3.71 Ra) and mantle-derived ³He content reached 46.48%, confirming that complex gas–water–rock interactions occur at fracture intersections. Continuous monitoring at site S13 (144 km from the epicenter of the Wushi M_S7.1 earthquake) captured pre-and post-seismic hydrogeochemical fingerprints linked to the Wushi MS7.1 earthquake. Stress accumulation along the MDF induced permeability changes, perturbing hydrogeochemical equilibrium. At 42 days pre-Wushi M_S7.1 earthquake, δ¹³C DIC exceeded +2σ thresholds (−2.12‰), signaling deep fracture expansion and CO₂ release. By 38 days pre-Wushi M_S7.1 earthquake, Na⁺, SO₄²⁻, and δ¹⁸O surpassed 2σ levels, reflecting hydraulic connection between deep-seated and shallow fracture networks. Ion concentrations and isotope values showed dynamic shifts during the earthquake, which revealed episodic stress transfer along fault asperities. Post-Wushi M_S7.1 earthquake, fracture closure reduced deep fluid input, causing δ¹³C DIC to drop to −4.89‰, with ion concentrations returning to baseline within 34 days. Trace elements such as Be and Sr exhibited anomalies 12 days before the Wushi M_S7.1 earthquake, while elements like Li, B, and Rb showed anomalies 24 days after the Wushi M_S7.1 earthquake. Hydrochemical monitoring of hot springs captures such critical stress-induced signals, offering vital insights for earthquake forecasting in tectonically active regions. Full article

It is believed that the deployment of autonomous vehicles in Europe has the potential to achieve safer, more sustainable and more equitable mobility. This study provides new insight into the hopes and expectations of citizens across five European countries for autonomous transport systems via a qualitative co-creation activity. A diverse and inclusive sample of 147 citizens was invited to generate their own ideas about how self-driving transport could be usefully deployed. Participants were asked to describe, in detail, what the vehicle would be like, what kind of mobility service it would provide, and who the target users would be. Structured qualitative analysis of the answers identified 337 distinct scenarios for autonomous vehicles across seven archetypes. In this paper, we describe a number of features of autonomous services that citizens expect and analyze the differences between demographic groups. We found that citizens across all five countries share a vision of autonomous mobility as electric- or hydrogen-powered, with a much greater use of shared mobility than is currently the case. This understanding of the expectations of a diverse group of citizens offers valuable insights for industry and policymaker actors to implement regarding future technology and transport investment and policy and service development. Full article

The air we breathe contains contaminants such as particulate matter (PM), carbon dioxide (${\mathrm{CO}}_2$), nitrogen dioxide (${\mathrm{NO}}_2$), and nitric oxide (NO), which, when inhaled, bring about several changes in the autonomous responses of our body. Our previous work showed that we can use the human body as a sensor by making use of autonomous responses (or biometrics), such as changes in electrical activity in the brain, measured via electroencephalogram (EEG) and physiological changes, including skin temperature, galvanic skin response (GSR), and blood oxygen saturation (${\mathrm{SpO}}_2$). These biometrics can be used to estimate pollutants, in particularly ${\mathrm{PM}}_1$ and ${\mathrm{CO}}_2$, with high degree of accuracy using machine learning. Our previous work made use of the Welch method (WM) to obtain a power spectral density (PSD) from the time series of EEG data. In this study, we introduce a novel approach for obtaining a PSD from the EEG time series, developed by Astrapi, called the Astrapi Spectrum Analyzer (ASA). The physiological responses of a participant cycling outdoors were measured using a biometric suite, and ambient ${\mathrm{CO}}_2$, ${\mathrm{NO}}_2$, and NO were measured simultaneously. We combined physiological responses with the PSD from the EEG time series using both the WM and the ASA to estimate the inhaled concentrations of ${\mathrm{CO}}_2$, ${\mathrm{NO}}_2$, and NO. This work shows that the PSD obtained from the ASA, when combined with other physiological responses, provides much better results (RMSE = 9.28 ppm in an independent test set) in estimating inhaled ${\mathrm{CO}}_2$ compared to making use of the same physiological responses and the PSD obtained by the WM (RMSE = 17.55 ppm in an independent test set). Small improvements were also seen in the estimation of ${\mathrm{NO}}_2$ and NO when using physiological responses and the PSD from the ASA, which can be further confirmed with a large number of dataset. Full article

Alzheimer’s disease (AD) pathogenesis involves progressive synaptic degeneration, a process potentially driven by maladaptive microglial pruning activity. While synaptic loss is a hallmark of AD, the molecular signals triggering pathological microglia-mediated synaptic engulfment remain elusive. Clec7a—a key marker of disease-associated microglia (DAM)—is known to activate spleen tyrosine kinase (SYK) signaling, enhancing Aβ phagocytosis and neuroprotective functions in 5×FAD models. However, its role in regulating synapse–microglia interactions under tauopathic conditions remains undefined. Our analysis revealed a progressive activation of the Clec7a–SYK signaling axis in the hippocampus of PS19 tauopathy mice, correlating with disease progression. Spatial mapping demonstrated a significant co-localization of Clec7a with hippocampal microglia, suggesting cell-autonomous signaling. The pharmacological inhibition of Clec7a achieved multimodal therapeutic effects by attenuating microglial hyperreactivity, suppressing neuroinflammatory cytokine release, and restoring physiological synaptic turnover. Mechanistically, we identified MD2 as a synaptic “eat-me” signal on tauopathy-related synapses, recruiting Clec7a+ microglia to drive aberrant synaptic elimination in PS19 mice. Strikingly, Clec7a blockade rescued hippocampal-dependent memory deficits in behavioral tests. These findings position Clec7a as a context-dependent therapeutic target, with inhibition strategies showing particular promise for tauopathy-related synaptic degeneration. Full article

Background: Periodic limb movements in sleep (PLMS) are characterised by repetitive, involuntary limb movements that occur during sleep and are often associated with autonomic nervous system dysregulation. While it is known that PLMS influence cardiovascular parameters, the exact role of heart rate variability (HRV) and the balance between sympathetic and parasympathetic activity remains unclear. Previous studies have suggested that longer PLMS events may trigger more pronounced autonomic responses, but the relationship between the duration of PLMS and autonomic dynamics has yet to be fully explored. This study aims to investigate the influence of PLMS duration on autonomic co-activation and its potential cardiovascular implications. Methods: A retrospective analysis was conducted on polysomnographic, demographic, and medical data from five patients, encompassing a total of 1348 PLMS events. We measured heart rate (HR), high-frequency HRV (HF-HRV), systolic blood pressure (SBP), and diastolic blood pressure (DBP) for 10 heartbeats before and 10 heartbeats after each PLMS series. A time–frequency approach was used, employing 10 RR interval segments to analyse HF-HRV dynamics. Statistical analysis was performed using IBM SPSS Statistics (v. 28.0.0.0), and the Kruskal–Wallis test was used to assess statistically significant deviations from baseline. Results: HF-HRV increased during PLMS, indicating enhanced parasympathetic activation. No significant changes in mean DBP or SBP were observed with leg movements of <2.1 s. However, with movements of >2.1 s, significant increases in DBP and SBP were noted, suggesting sympathetic activation. Longer PLMS events were associated with greater parasympathetic activity, while the absence of HR changes indicates concurrent sympathetic activation, supporting autonomic co-activation. Conclusions: Our study indicates that PLMS events lasting >2.1 s are linked to increased parasympathetic activity, likely accompanied by sympathetic activation. This simultaneous activation of both branches of the autonomic nervous system, referred to as autonomic co-activation, could lead to autonomic dysregulation and an increased risk of cardiovascular instability, including potentially life-threatening events. Full article

Long COVID, also known as post-acute sequelae of SARS-CoV-2 infection (PASC), is increasingly recognized as a condition affecting not only adults but also children and adolescents. While children often experience milder acute COVID-19 symptoms compared to adults, some develop persistent physical, psychological, and neurological symptoms lasting for weeks or months after initial infection. The most commonly reported symptoms include debilitating fatigue, respiratory issues, headaches, muscle pain, gastrointestinal disturbances, and cognitive difficulties, which significantly impact daily activities, schooling, and social interactions. Additionally, many children with long COVID experience psychological symptoms, such as anxiety, depression, mood swings, and irritability, likely exacerbated by prolonged illness and lifestyle disruptions. Risk factors for long COVID in children include pre-existing health conditions such as asthma, obesity, and neurological disorders, with adolescents and females seemingly more affected. Hypothesized mechanisms underlying long COVID include chronic immune dysregulation, persistent viral particles stimulating inflammation, autonomic nervous system dysfunction, and mitochondrial impairment, which may collectively contribute to the variety of observed symptoms. Long-term outcomes remain uncertain; however, long COVID can lead to school absenteeism, social withdrawal, and psychological distress, potentially affecting cognitive development. Severe cases may develop chronic conditions such as postural orthostatic tachycardia syndrome (POTS) and reduced exercise tolerance. This review synthesizes the existing literature on long COVID in children, examining its prevalence, symptomatology, risk factors, and potential mechanisms, with an emphasis on the need for further clinical studies. While existing research largely relies on surveys and self-reported data, clinical assessments are essential to accurately characterize long COVID in pediatric populations and to guide effective management strategies. Full article

Singapore’s national myopia prevention efforts have largely focused on school vision screening and public education on outdoor activities in the past two decades. Given the emergence of evidence-based myopia interventions, this policy review and analysis investigates the potential benefits and drawbacks of optometrist prescribing privileges as it has been proposed to reduce the barriers to access effective interventions, such as combined therapy (e.g., orthokeratology treatment and low-dose atropine therapy). In this policy analysis, two policy options were identified to be feasible based on evidence from a systematic literature search and they were analysed along with status quo using the Centers for Disease Control and Prevention (CDC) Policy Analysis Framework. This includes independent prescribing and supplementary prescribing, where the former entails autonomous clinical decision making, and the latter entails co-management with ophthalmological supervision. The policy review and analysis found independent prescribing the most favourable and concluded that this should be implemented in view of its benefits for the community. Public health impact is expected to be substantial due to increased patient access, reduced treatment costs, early interventions, improved treatment compliance, and reduced wait times and inconvenience. It is feasible because treatment processes can be streamlined, and it can be implemented based on existing collaborative prescribing frameworks. Economical and budgetary impact is also substantial given the direct savings generated, which can consequently help to reduce the disease burden. Full article

This study investigates the potential of bioaugmentation with Bacillus species to enhance wastewater treatment and develop a bacterial–CaCO₃ system for self-healing cement applications. Utilizing microbiologically induced calcium carbonate precipitation (MICP), this study evaluates the dual functionality of Bacillus licheniformis and B. muralis strains. For wastewater treatment, the bioaugmentation process achieved significant pollutant reductions, including a 99.52% decrease in biochemical oxygen demand (BOD₅), a 92.13% reduction in chemical oxygen demand (COD), and a substantial removal of heavy metals and nutrients. This process also produced high concentrations of CaCO₃ precipitate enriched with viable bacterial cells, demonstrating an eco-friendly approach to improving water quality. For self-healing cement applications, bioaugmented CaCO₃ crystals were coated with nutrient and sodium silicate layers to form a bacterial–CaCO₃ coupled system. This system demonstrated a 92% recovery in compressive strength after 180 days, highlighting its ability to autonomously repair microcracks in cement-based materials. The layered encapsulation strategy ensured bacterial viability and a controlled activation mechanism, offering a scalable and sustainable solution for infrastructure resilience. This dual-function approach addresses critical environmental and construction challenges by linking efficient wastewater treatment with innovative self-healing material development, contributing to global sustainability and circular economy goals. Full article

As creative tourism consolidates both as an autonomous research area and a valid sustainable form of tourism based on learning, active participation, co-creation, creative self-expression, and local community engagement, its economic models have evolved from simple creative activities to complex territorial and technological-based networks, boosting the entrepreneurship of creative communities in tourism. Seen as a means of territorial development strategy through tourism, creative networks can stem from private partnerships, the public sector, the local community, or third sector organisations. Focusing on a case study approach, this research adopts a multidimensional framework with the goal of analysing the benefits of creative tourism towards a creative tourism network. Using a quantitative approach through Likert scale statements of five items, this research aimed to study the creative supply and demand linked to a creative tourism network. Based on the principles and benefits of creative tourism and the goals of the creative network, the following dimensions were analysed: job creation; production and commerce of creative products; safeguarding of tangible and intangible heritage; development of social capital between network agents; creative and innovative images of the region; the active role of the local community in the network; and the consumption profile of the creative tourist through the network. The main conclusions of the study point to the network boosting local job creation and preserving local traditions but struggling to expand sales and increase tourist stays. While it enhances the region’s image, there is a need for stronger collaboration and community engagement. Full article

Four-wheel independent drive and four-wheel independent steering (4WID-4WIS) vehicles provide increased redundancy in fault-tolerant control (FTC) schemes, enhancing heterogeneous fault-tolerant capabilities. This paper addresses the challenge of maintaining vehicle safety and maneuverability in the presence of actuator faults in autonomous vehicles, focusing on 4WID-4WIS systems. A novel unified hierarchical active FTC strategy is proposed to handle various actuator failures. The strategy includes an upper-layer motion controller that determines resultant force requirements based on trajectory tracking errors and a middle-layer allocation system that redistributes tire forces to fault-free actuators using fault information. This study, for the first time, considers multi-fault scenarios involving longitudinal and lateral coupling, calculating FTC boundaries for each fault type. Additionally, a fault tolerance index is introduced for 256 fault scenarios, using singular value decomposition to linearly represent the vehicle attainable force domain. Based on this, an adaptive velocity planning strategy is developed to balance safety and maneuverability under fault conditions. Matlab 2021a/Simulink and Carsim 2019 co-simulation results validate the proposed strategies, demonstrating significant improvements in fault-tolerant performance, particularly in complex and emergency scenarios. Full article