Search Results (2,044)

Between approximately 725 and 518 Ma, a suite of specialized felsic plutons and granitic stocks were emplaced across the Arabian Shield, many of which are now recognized as highly mineralized prospects enriched in rare earth elements (REEs), rare metals, and radioactive elements bearing mineralizations. The current investigation focused on the radiological and geochemical characterization of naturally occurring radionuclides, specifically ²³⁸U, ²²⁶Ra, ²³²Th, and ⁴⁰K, within three strategically selected granitic prospects, namely, J. Tawlah albite granite (TW), J. Hamra (HM), and J. Abu Al Dod alkali feldspar syenite and granites (AD). Concerning the radioactivity levels of the investigated granitic stocks, specifically the activity concentrations of ²³⁸U, ²²⁶Ra, ²³²Th, and ⁴⁰K, the measured average values demonstrate significant variability across the TW, HM, and AD stocks. The average ²³⁸U concentrations are 195 (SD = 38.7), 88.66 (SD = 25.6), and 214.3 (SD = 140.8) Bq/kg for TW, HM, and AD granitic stocks, respectively. Corresponding ²²⁶Ra levels are recorded at 172.4 (SD = 34.6), 75.62 (SD = 25.9), and 198.4 (SD = 139.5) Bq/kg. For ²³²Th, the concentrations are markedly elevated in TW at 5453.8 (SD = 2182.9) Bq/kg, compared to 77.16 (SD = 27.02) and 160.2 (SD = 103.8) Bq/kg in HM and AD granitic stocks, respectively. Meanwhile, ⁴⁰K levels are reported at 1670 (SD = 535.9), 2846.2 (SD = 249.9), and 3225 (SD = 222.3) Bq/kg for TW, HM, and AD granitic plutons, respectively. Notably, these values exceed the global average background levels, indicating an anomalous enrichment of the studied granitic occurrences. The mean radiological hazard indices for each granitic unit generally exceed global benchmarks, except for AEDE_out in the HM and AD stocks, which remain below international limits. The geochemical disparities observed are indicative of post-magmatic alteration processes, as substantiated by the interpretation of remote sensing datasets. In light of the significant radiological burden presented by these granitic stocks, it is essential to implement a rigorous precautionary framework for any future mining. These materials must be categorically excluded from uses that entail direct human exposure, especially in residential construction or infrastructure projects. Full article

Mid-infrared passive spectroscopic imaging is a novel non-invasive and remote sensing method based on Planck’s law. It enables the acquisition of component-specific information from the human body by measuring naturally emitted thermal radiation in the mid-infrared region. Unlike active methods that require an external light source, our passive approach harnesses the body’s own emission, thereby enabling safe, long-term monitoring. In this study, we successfully demonstrated the simultaneous, non-invasive measurements of blood glucose and lactate levels of the human body using this method. The measurements, conducted over approximately 80 min, provided emittance data derived from mid-infrared passive spectroscopy that showed a temporal correlation with values obtained using conventional blood collection sensors. Furthermore, to evaluate localized metabolic changes, we performed k-means clustering analysis of the spectral data obtained from the upper arm. This enabled visualization of time-dependent lactate responses with spatial resolution. These results demonstrate the feasibility of multi-component monitoring without physical contact or biological sampling. The proposed technique holds promise for translation to medical diagnostics, continuous health monitoring, and sports medicine, in addition to facilitating the development of next-generation healthcare technologies. Full article

Groundwater level monitoring is crucial for assessing hydrological responses to climate change and human activities, which pose significant threats to the sustainability of semi-arid aquifers and the cultural heritage they sustain. This study presents an integrated remote sensing and transformer-based deep learning framework that combines diverse geospatial datasets to predict spatiotemporal variations across the plain near the Persepolis and Naqsh-e Rustam archaeological complexes—UNESCO World Heritage Sites situated at the plain’s edge. We assemble 432 synthetic aperture radar (SAR) scenes (2015–2022) and derive vertical ground motion rates greater than −180 mm yr⁻¹, which are co-localized with multisource geoinformation, including hydrometeorological indices, biophysical parameters, and terrain attributes, to train transformer models with traditional deep learning methods. A sparse probabilistic transformer (ConvTransformer) trained on 95 gridded variables achieves an out-of-sample R² = 0.83 and RMSE = 6.15 m, outperforming bidirectional deep learning models by >40%. Scenario analysis indicates that, in the absence of intervention, subsidence may exceed 200 mm per year within a decade, threatening irreplaceable Achaemenid stone reliefs. Our results indicate that attention-based networks, when coupled to synergistic geodetic constraints, enable early-warning quantification of groundwater stress over heritage sites and provide a scalable template for sustainable aquifer governance worldwide. Full article

Aloin, a kind of active phenolic component, is sourced from Aloe vera. Recently, the determination of aloin has received enormous attention, owing to its positive performance (including anti-tumor, antibacterial, detoxification, liver protection, anti-stomach damage, and skin protection activities) and painful side effects (increased carcinogenicity caused by excessive use of aloin) impacting human health. This investigation was inspired by the good fluorescence properties of carbon dots (CDs); CD-based sensors have aroused a great deal of interest due to their excellent sensitivity and selectivity. Thus, it is of great significance to develop novel CD-based sensors for aloin determination. Herein, N,F-CDs were designed and synthesized through a convenient hydrothermal strategy; the synthesized N,F-CDs possessed good fluorescence performance and a small particle size (near 4.3 nm), which demonstrated the successful preparation of N,F-CDs. The resulting N,F-CDs possessed a large Stokes shift and could emit a highly stable green fluorescence. The fluorescence of the N,F-CDs could be effectively quenched by aloin through the inner filter effect. Furthermore, the synthesis procedure was easy to operate. Finally, the N,F-CD-coated test strips were fabricated and combined with a miniaturized fluorimeter for the fluorescence detection of aloin via the inner filter effect for the first time. The N,F-CD-coated test strips were fabricated and used for the fluorescence sensing of aloin, and the results were compared with a typical ultraviolet (UV) method. The N,F-CD-coated test strips exhibited high recovery (96.9~106.1%) and sensitivity (31.8 nM, n = 3), good selectivity, low sample consumption (1 μL), high speed (5 min), good stability, and anti-interference properties. The results indicate that N,F-CD-coated test strips are applicable for the quantitative determination of aloin in bovine serum, orange juice, and urine samples. Full article

Nowadays, society is becoming increasingly committed to traveling by plane for work, tourism, and leisure in general. However, either due to internal, specific factors or to external determinants, like terrorism and climate changes, a growing number of travelers have experienced the so-called fear of flying, a persistent, irrational fear of flight-related situations for which a clear, efficacious therapy does not yet exist. Based on the usual interaction with the surrounding environment, conducted by means of the five human senses, and particularly on the neurophysiological pathway followed by the chemical senses, in this study, we revise the findings in the related literature on the topic, proposing an alternative way to alleviate the anxiety related to the fear of flight. This is based on chemosensory stimulation being applied directly during a flight and is possibly concerned with the consumption of meals, an usual activity performed onboard. After an introductory section aimed at understanding the problem, we present some studies related to chemosensory perception during the flight, highlighting the specificities of the scenarios, followed by a description of findings related to the meals proposed by flight companies in this context, and finally wrapping up the possible alternative approaches that could be conducted by such providers to alleviate the fear of flying condition through chemosensory stimulation vehiculated by meals, and enhance the quality of flight experience related to food consumption onboard. Full article

Ammonia, as a toxic and corrosive gas, is widely present in industrial emissions, agricultural activities, and disease biomarkers. Detecting ammonia is of vital importance to environmental safety and human health. Sensors based on MXene have become an effective means for detecting ammonia gas due to their unique hierarchical structure, adjustable surface chemical properties, and excellent electrical conductivity. This study reviews the latest progress in the use of MXene and its composites for the low-temperature detection of ammonia gas. The strategies for designing MXene composites, including heterojunction engineering, surface functionalization, and active sites, are introduced, and their roles in improving sensing performance are clarified. These methods have significantly improved the ability to detect ammonia, offering high selectivity, rapid responses, and ultra-low detection limits within the low-temperature range. Successful applications in fields such as industrial safety, food quality monitoring, medical diagnosis, and agricultural management have demonstrated the multi-functionality of this technology in complex scenarios. The challenges related to the material’s oxidation resistance, humidity interference, and cross-sensitivity are also discussed. This study aims to briefly describe the reasonable design based on MXene sensors, aiming to achieve real-time and energy-saving environmental and health monitoring networks in the future. Full article

Urban electricity power consumption (EPC) prediction plays a crucial role in urban management and sustainable development. Nighttime light (NTL) remote sensing imagery has demonstrated significant potential in estimating urban EPC due to its strong correlation with human activities and energy use. However, most existing models focus on annual-scale estimations, limiting their ability to capture month-scale EPC. To address this limitation, a novel monthly EPC prediction model that incorporates monthly average temperature, and the interaction between NTL data and temperature was proposed in this study. The proposed method was applied to cities within the Yangtze River Delta (YRD) urban agglomeration, and was validated using datasets constructed from NPP/VIIRS and SDGSAT-1 satellite imageries, respectively. For the NPP/VIIRS dataset, the proposed method achieved a Mean Absolute Relative Error (MARE) of 7.96% during the training phase (2017–2022) and of 10.38% during the prediction phase (2023), outperforming the comparative methods. Monthly EPC spatial distribution maps from VPP/VIIRS data were generated, which not only reflect the spatial patterns of EPC but also clearly illustrate the temporal evolution of EPC at the spatial level. Annual EPC estimates also showed superior accuracy compared to three comparative methods, achieving a MARE of 7.13%. For the SDGSAT-1 dataset, leave-one-out cross-validation confirmed the robustness of the model, and high-resolution (40 m) monthly EPC maps were generated, enabling the identification of power consumption zones and their spatial characteristics. The proposed method provides a timely and accurate means for capturing monthly EPC dynamics, effectively supporting the dynamic monitoring of urban EPC at the monthly scale in the YRD urban agglomeration. Full article

Port green spaces are essential protective barriers, enhancing safety and environmental resilience in high-activity port regions. Given the intensity of human activities in these areas, understanding the factors influencing the carbon sequestration capacity and ecological benefits of port green spaces is crucial for developing sustainable green ports. This study integrated field investigations and remote sensing data to estimate carbon density and carbon sequestration capacity in the Dongjiakou Port area, examining their relationship with port green space planning. The results indicated that carbon density in green spaces showed a significant negative correlation with the number of lanes in adjacent roads, where an increase in lane numbers corresponded to lower carbon density. Additionally, carbon density decreased significantly with increasing distance from the shipping center. In contrast, a significant positive correlation was observed between carbon density and distance from large water bodies, indicating that green spaces closer to large water bodies exhibited smaller carbon density. Infrastructure development in Dongjiakou substantially negatively impacted vegetation carbon sequestration capacity, with effects not reversible in the short term. However, green space enhancement efforts provided additional ecological benefits, leading to a 50.9 ha increase in green space area. When assessing carbon density in urbanizing areas, geographical influences should be prioritized. Furthermore, the long-term environmental impacts of urban expansion must be considered at the early planning stages, ensuring the implementation of proactive protective measures to mitigate potential ecological disruptions. Full article

In recent years, heavy metal pollution in farmland soil has become a crisis due to human activities or natural impacts, with particular emphasis on cases from China, where this issue is prominent, greatly affecting crop production and food safety. In the context of a low heavy metal (HM) content in farmland soil, which is difficult to monitor in real time, effective and rapid monitoring of soil plays a decisive role in subsequent targeted protection measures. To this end, this paper provides a narrative review of the application of spectral sensing technology on the basis of the quantitative inversion of heavy metal content in farmland soil using different platforms (ground, airborne, and spaceborne). The sensing process evaluates the mechanism by which soil produces different weak spectral features from the perspective of the heterogeneity of farmland soil. Different methods used for the quantitative inversion of heavy metals (by studying the correlation between soil heavy metals and organic matter, clay minerals, metal oxides, crop vegetation index, etc.) and their feasibility were clarified. At the same time, relevant research on key technologies used in various processes—such as follow-up pretreatment, spectral feature extraction, and the establishment of inversion models for spectral data of different farmland soil types—was summarized, with a primary focus on cases in China. Finally, the challenges, applications, and research directions related to heavy metal spectral inversion in farmland soil were discussed. Full article

Background Veno-venous extracorporeal membrane oxygenation (VV-ECMO) supports critically ill patients with respiratory failure. However, ECMO may induce systemic inflammation, hemolysis, and hemodilution, potentially resulting in endothelial activation and damage. Therefore, this study explored the longitudinal changes in circulating markers of inflammation, hemolysis, and endothelial activation and damage in patients with COVID-19 on VV-ECMO. Methods Plasma was obtained before, within 48 h as well as on day 4, week 1, and week 2 of ECMO support and after decannulation. Circulating markers were measured using Luminex, ELISA, and spectrophotometry. Human pulmonary endothelial cells were exposed to patient plasma, and in vitro endothelial permeability was assessed using electric cell-substrate impedance sensing. Results From April 2020 to January 2022, plasma was collected from 14 patients (71.4% male; age 54 (45–61) years). IL-6 levels decreased (1.238 vs. 0.614 ng/mL, p = 0.039) while ICAM-1 increased (667 vs. 884 ng/mL, p = 0.003) over time when compared to pre-ECMO. Angiopoietin-1 decreased after ECMO initiation (7.57 vs. 3.58 ng/mL, p = 0.030), whereas angiopoietin-2 increased (5.20 vs. 10.19 ng/mL, p = 0.017), particularly in non-survivors of ECMO. Cell-free hemoglobin decreased directly after VV-ECMO initiation but remained stable thereafter (55.29 vs. 9.19 mg/dL, p = 0.017). Moreover, the plasma obtained at several time points during the ECMO run induced in vitro pulmonary endothelial hyperpermeability. Conclusions This exploratory study shows that patients on VV-ECMO support due to COVID-ARDS exhibit progressive endothelial activation and damage but not inflammation and hemolysis. Larger prospective studies are necessary to elucidate pathophysiological pathways leading to endothelial activation and damage, thereby reducing organ failure in these critically ill patients. Full article

The development of wearable robotic exoskeletons has seen rapid progress in recent years, driven by the growing need for technologies that support motor rehabilitation, assist individuals with physical impairments, and enhance human capabilities in both clinical and everyday contexts. Within this field, elbow exoskeletons have emerged as a key focus due to the joint’s essential role in upper limb functionality and its frequent impairment following neurological injuries such as stroke. With increasing research activity, there is a strong interest in evaluating these systems not only from a technical perspective but also in terms of user comfort, adaptability, and clinical relevance. This review investigates recent advancements in elbow exoskeleton technology, evaluating their effectiveness and identifying key design challenges and limitations. Devices are categorized based on three main criteria: mechanical structure (rigid, soft, or hybrid), actuation method, and sensing technologies. Additionally, the review classifies systems by their supported range of motion, flexion–extension, supination–pronation, or both. Through a systematic analysis of these features, the paper highlights current design trends, common trade-offs, and research gaps, aiming to guide the development of more practical, effective, and accessible elbow exoskeletons. Full article

In the context of the relentless pursuit of precision, intelligence, and personalization within the realm of medical technology, the real-time monitoring of human physiological signals has assumed heightened significance. Implantable wireless sensor devices have exhibited extraordinary capabilities in tracking internal physiological parameters, including intraocular pressure, blood glucose levels, electrocardiographic activity, and arterial blood pressure. These devices are characterized by elevated temporal continuity and exceptional measurement accuracy. This paper undertakes an in-depth investigation into the key technologies underlying biodegradable implantable sensing devices. Initially, it expounds on diverse sensing mechanisms employed in implantable devices. Additionally, it presents common data transmission and power supply strategies for wireless sensing systems. Finally, it introduces biodegradable materials suitable for human implantation and their respective application domains and enumerates several implantable devices that are either under development or have already been commercialized. Through an in-depth and comprehensive discourse on the current state of development and extant challenges in this domain, the development trajectory of biodegradable devices is put forward. Moreover, this paper also serves as a valuable reference for the design and selection of implantable medical devices. Full article

Human activity recognition (HAR) using Wi-Fi-based sensing has emerged as a powerful, non-intrusive solution for monitoring human behavior in smart environments. Unlike wearable sensor systems that require user compliance, Wi-Fi channel state information (CSI) enables device-free recognition by capturing variations in signal propagation caused by human motion. This makes Wi-Fi sensing highly attractive for ambient healthcare, security, and elderly care applications. However, real-world deployment faces two major challenges: (1) significant cross-subject signal variability due to physical and behavioral differences among individuals, and (2) limited labeled data, which restricts model generalization. To address these sensor-related challenges, we propose TCN-MAML, a novel framework that integrates temporal convolutional networks (TCN) with model-agnostic meta-learning (MAML) for efficient cross-subject adaptation in data-scarce conditions. We evaluate our approach on a public Wi-Fi CSI dataset using a strict cross-subject protocol, where training and testing subjects do not overlap. The proposed TCN-MAML achieves 99.6% accuracy, demonstrating superior generalization and efficiency over baseline methods. Experimental results confirm the framework’s suitability for low-power, real-time HAR systems embedded in IoT sensor networks. Full article

Globally, ecosystems are affected by climate change, human activities, and natural disasters, which impact ecosystem quality and stability. Vegetation plays a crucial role in ecosystem material cycle and energy transformation, making it important to monitor its resilience under disturbance stress. The Critical Slowing Down (CSD) indicates that as ecosystems near collapse, the autocorrelation of lag temporal increases and resilience decreases. We used the lag Temporal Autocorrelation (TAC) of long-term remote sensing Leaf Area Index (LAI) to monitor vegetation resilience in the Three Gorges Reservoir Area (TGRA). The Disturbance Event Model (DEM) was used to validate the CSD. The results showed the following: (1) The eastern TGRA exhibited high and increasing vegetation resilience, while most areas showed a decline. (2) Among the various vegetation types, forests demonstrated higher resilience than other vegetation types. (3) Precipitation, temperature, and soil moisture significantly influenced vegetation resilience dynamics within the TGRA. (4) For model accuracy, the CSD’s results were consistent with the DEM, confirming its applicability in the TGRA. Overall, the CSD when applied to long-term remote sensing data, provided valuable quantitative indicators for vegetation resilience. Furthermore, more CSD-based indicators are needed to analyze vegetation resilience dynamics and better understand the biological processes determining vegetation degradation and restoration. Full article

Isolated wetlands, as a unique type of wetland, play a key ecological role in hydrological regulation, carbon storage, and biodiversity conservation. Although many studies have been conducted on the monitoring and ecological function assessment of isolated wetlands, a comprehensive and critical review is still lacking. Through a systematic analysis of the literature from the past two decades, we found despite the large number of existing studies on isolated wetlands, direct comparison between them is often difficult due to differences in definitions. Second, human activities and climate change are the primary factors affecting wetland hydrology and leading to wetland isolation in the short term. Third, remote sensing and landscape models serve as basic tools for monitoring and analyzing isolated wetlands, but the low temporal and spatial accuracy of relevant data, along with the short research time spans, limit in-depth studies. Finally, isolated wetlands have multiple ecological functions that exhibit spatial heterogeneity and change over time. In summary, isolated wetlands have indispensable ecological functions that are currently underestimated. It is necessary to scientifically define the concept of isolated wetlands, improve the capability and accuracy of long-term dynamic monitoring, and conduct multi-functional coupling research in the future. Additionally, when formulating future wetland protection and management strategies, attention should be paid to isolated wetlands, and the temporal and spatial differences in their ecological benefits should be considered. Full article