Search Results (1,512)

Melatonin, a multifunctional hormone with antioxidant, anti-inflammatory, and chronobiotic effects, is essential for a healthy pregnancy and fetal development. In the context of the Developmental Origins of Health and Disease (DOHaD), excessive oxidative stress acts as a key driver of maladaptive fetal programming, increasing lifelong susceptibility to cardiovascular, kidney, and metabolic (CKM) disorders. Importantly, most evidence derives from rodent models, and the protective effects of maternal melatonin supplementation appear partial and model-dependent rather than universal. Experimental studies indicate that maternal melatonin supplementation can prevent programmed hypertension, renal dysfunction, and metabolic derangements by restoring redox homeostasis, influencing epigenetic and nutrient-sensing pathways, and modulating the gut microbiome. Early clinical investigations in pregnancies complicated by preeclampsia or intrauterine growth restriction suggest that melatonin is well tolerated, improves placental function, and benefits neonatal outcomes. However, optimal dosing and long-term safety for offspring remain to be established. This review synthesizes mechanistic and translational evidence, framing melatonin as an integrative biological mediator with potential to guide preventive strategies and mitigate the intergenerational risk of CKM syndrome. Full article

Dual-emission photoluminescence (PL) nanoprobes provide improved analytical performance to develop a reliable and sensitive sensing platform for quantifying chloramphenicol in pharmaceutical samples, thereby ensuring therapeutic efficacy and patient safety. In this work, a dual-emission PL sensing platform combining carbon dots (CDs) and AgInS₂ quantum dots (QDs) capped with mercaptopropionic acid (MPA) was developed for the quantitative determination of chloramphenicol, resorting to chemometric methods for data analysis. CDs, CdTe QDs, and AgInS₂ QDs were synthesized and individually evaluated considering their photostability, PL response and kinetics of their interaction with the antibiotic. After this, two dual-emission probes, CDs/MPA-CdTe and CDs/MPA-AgInS₂, were prepared and assessed based on the complementarity of their individual emission features. The obtained kinetic PL dataset was processed using unfolded partial least squares (U-PLS) in order to explore the multidimensional information of the dual-emission systems and to evaluate the performance of both sensing platforms. CDs/MPA-AgInS₂ probe was demonstrated to be the most efficient sensing platform due to its better compromise between sensitivity and photostability, as well as its cadmium-free composition, allowing the implementation of a more environmentally friendly analytical methodology. The optimization of the U-PLS models involved the assessment of the kinetic acquisition time and different spectral regions. The results showed that reliable, sensitive and efficient quantification could be achieved within the first 5 min of interaction and using the full emission spectrum of the sensing probe. Additionally, different interaction mechanisms were observed for each nanomaterial in the combined probe, being static for the CDs/chloramphenicol interaction and dynamic for MPA-AgInS₂/chloramphenicol interaction, which supports the synergetic behavior of the combined probe. The proposed methodology was effectively applied to commercial pharmaceutical formulations, yielding accurate results with good figures of merit. Therefore, this approach can be used as a relevant alternative to existing methodologies for a rapid, robust, and environmentally friendly method for chloramphenicol quantification. Full article

Advanced sensing technologies increasingly support monitoring and decision-making processes in modern agriculture. This study investigates the feasibility of developing a harvest timing monitoring workflow based on a portable hyperspectral imaging (HSI) system in the visible–near-infrared (VIS-NIR: 400–1000 nm) range, coupled with machine learning. A hierarchical Partial Least Squares–Discriminant Analysis (Hi-PLS-DA) model was developed and tested to discriminate harvestable from non-harvestable plants of Brassica rapa subsp. sylvestris through the identification of open flowers within otherwise closed flower buds in the raceme. The classification included four target plant classes, i.e., green inflorescences, green leaves, yellow flowers, and yellow leaves, along with two non-target classes, background and not-classified (NC), which were included to support the classification process. The predicted hyperspectral images demonstrated a clear distinction between closed and open flowers, supported by satisfactory classification performance (sensitivity, specificity, precision, and F1-score: 0.78–1.00). This workflow proved effective in handling intrinsic outdoor hyperspectral variability, mitigating illumination and canopy texture, and offers useful methodological insights for the possible future integration of HSI-based approaches into automated field applications, paving the way for rapid, real-time harvest decision support. Full article

Enteric diseases are a significant challenge for the poultry industry, causing substantial economic losses and affecting productivity. Turkey astrovirus (TAstV) types 1 and 2 and avian nephritis virus (ANV) are recognized as viral pathogens contributing with enteric diseases in turkeys, particularly in young poults. These viruses, part of the Astroviridae family, are small, round, non-enveloped, positive-sense RNA viruses with high prevalence in turkey flocks. Despite their importance, they had not been identified in Ecuador until now. This study presents the first detection and molecular characterization of TAstV-1, TAstV-2, and ANV in Ecuadorian turkeys using RT-qPCR assays based on SYBR Green, developed and optimized for high sensitivity and specificity. Two hundred intestinal samples were collected from turkeys with enteric disorders, along with fifty cloacal swabs from apparently healthy turkeys in Pichincha Province. The RT-qPCR assays developed demonstrated a limit of detection of one copy of viral genetic material and high repeatability, with inter and intra-assay coefficients of variation below 1%. Based on these tests, TAstV was detected in 93% of turkey samples with gastroenteritis, and none of the samples of the healthy group tested positive, with ANV being the most prevalent, followed by TAstV-2 and TAstV-1. Phylogenetic analysis of the partial ORF1b gene confirmed the genetic relationships between Ecuadorian strains and those from other countries, highlighting possible routes of introduction and evolution of the virus. Co-infections with TAstV-2 and ANV were common, while single infections were predominantly caused by ANV. These findings underscore the critical need for surveillance and biosecurity measures to control the spread of these viruses within Ecuador’s poultry industry. This study provides valuable insights on astrovirus presence in Ecuadorian turkey flocks and establishes robust diagnostic tools for monitoring and managing turkey astrovirus infections. Full article

Global warming profoundly affects hydrological processes and regional aridity. However, the shifts in the arid–humid transition zone and its relationship to divergent surface and subsurface hydrological responses remain not fully understood. This study investigates the spatiotemporal aridity changes in China using hydroclimate datasets (1950–2022) and examines associated hydrological responses via remote sensing (RS) since the early 2000s. The results reveal that: (1) a pronounced ~32-year oscillatory pattern governs both the expansion and contraction of drylands and non-drylands, with China currently in a wetting phase; (2) a distinct climatic transitional zone is identified, and a distinct boundary emerges separating drylands and non-drylands, here referred to as China’s Arid–Humid Divide, reflecting the climatic equilibrium shaped by multiple monsoon systems and local topography; and (3) the nationwide expansion of surface water bodies, following the increase of groundwater storage in partial areas, was detected via recent RS data. These findings provide new insights into the mechanisms driving long-term aridity transitions and support climate adaptation and sustainable land management in China. Full article

This study reports a sustainable and experimentally simple electrochemical platform for monitoring trace Pb²⁺ using pumpkin peel-derived carbon black (CB) as a modifier on a Nafion-coated glassy carbon electrode (CB/Nafion-GCE). Agricultural waste pumpkin peels were converted into CB, offering a low-cost and environmentally friendly sensing material. CB produced at 650 °C was systematically characterized by SEM, TEM, EDX, XRD, FT-IR, and BET, revealing a mesoporous structure, high surface area, and partial graphitization that enlarged the electroactive area and reduced charge transfer resistance relative to the bare GCE. Under optimized square wave anodic stripping voltammetry (SWASV) conditions, the glassy carbon electrode modified with CB produced at 650 °C (CB650-GCE) exhibited a well-defined linear response towards Pb²⁺ with a limit of detection of approximately 0.19 µM and a limit of quantification of about 0.58 µM, together with good selectivity against common coexisting metal ions. The sensor also achieved satisfactory recoveries in tap and seawater samples, demonstrating its potential as a practical, green analytical tool for routine lead surveillance in environmental waters. Full article

Characterizing both the CO₂ distribution and wind dynamics in the Martian mesosphere and lower thermosphere is vital for planetary atmospheric science and mission planning. In this work, we propose a novel dual-channel passive limb-viewing imaging system designed to simultaneously observe partial CO₂ column density and line-of-sight (LOS) wind speed from ultraviolet and visible airglow emissions under dayside and terminator illumination conditions. A dichroic beam splitter separates the ultraviolet and visible channels, ensuring high optical throughput and independent optimization of both subsystems. The ultraviolet channel targets O(¹S) 297.2 nm emission, a well-established Martian limb emission driven by CO₂ photodissociation under solar Lyman-α flux. By applying narrow-band imaging and brightness inversion, this channel provides quantitative constraints on CO₂ column density with a stable and well-defined response function. In the visible channel, we introduce a lens array-based compact static Michelson interferometer optimized for the O(¹S) 557.7 nm green line emission, which has been observed in the Martian dayside limb, providing Doppler wind measurements in the 60–180 km altitude range. Radiative transfer simulations using Mars Climate Database indicate retrieval precisions of ±6~8% for CO₂ column density and better than ±5 m/s for wind speed within the primary emission layer (approximately 60–160 km) under representative dayside limb conditions. This dual-parameter remote sensing concept simultaneously constrains the composition and dynamics of the Martian mesosphere and lower thermosphere region, addressing a long-standing observational gap. The compact and modular design of the system makes it well suited for future Mars orbiter payloads under nominal dayside and terminator observation geometries, providing critical data for validating global circulation models and supporting future entry, descent, and landing system design. Full article

Introduction: Acute ischemic stroke demands interventions that restore perfusion and protect neurons within a narrow therapeutic window. We propose a unified theranostic platform that couples adaptive imaging, topology-aware decision-making, and immediate neuroprotective and micro-dosimetric intervention. Methods: The platform integrates three components. First, a topology-preserving MR–PET engine employs adaptive Poisson-disc sampling, partial Fourier constraints, and structured Hankel low-rank priors in a closed loop. Persistent-homology metrics quantify vascular graph uncertainty and guide subsequent k-space and PET projections, reducing acquisition time while preserving collateral topology. Second, immediate post-reperfusion delivery of glycolic acid attenuates glutamate-driven calcium influx and stabilizes mitochondrial function. Third, trace doses of sol–gel-derived, neutron-activated ⁹⁰Y₂O₃ microspheres provide sharply confined beta irradiation for micro-scale metabolic modulation. Results: In a porcine stroke model replicating the human recanalization workflow, the imaging engine maintained vascular Betti-number invariants within three percent of fully sampled reference scans while reducing acquisition time by nearly half. Glycolic acid reduced glutamate-induced intracellular calcium rise by approximately sixty percent in vitro and decreased infarct volume by thirty-eight percent in vivo. Micro-dosimetry confirmed a mean perivascular beta dose of twenty-eight grays, and histology demonstrated a forty-two percent increase in NeuN-positive neuronal survival compared with standard recanalization. Conclusions: These results demonstrate that intelligent compressed-sensing MR–PET, targeted micro-radioembolization, and glycolic acid neuroprotection can act synergistically to bridge diagnostic imaging and immediate intervention. By coupling imaging, decision-making, and therapy in a closed-loop manner and elevating topological fidelity from a reconstruction byproduct to a control variable, the proposed platform reframes MR–PET from passive diagnostics into an active, decision-driven theranostic system and establishes a foundation for future human trials. Full article

Early detection of fire-related risks in lithium-ion batteries (LIBs) remains a critical challenge, as conventional protection mechanisms typically activate only after irreversible degradation or macroscopic failure occurs. In this study, an innovative sensor-based diagnostic framework is proposed for proactive fire prediction in LIBs by simultaneously monitoring low-frequency and high-frequency electrical signatures generated during battery charge–discharge processes. An electromagnetic (EM) antenna sensor and a high-frequency current transformer (HFCT) sensor were employed to capture complementary voltage- and current-based transient signals associated with internal degradation phenomena. Cell-level experiments were conducted under various C-rates and temperature conditions, including high-stress environments, while module-level validation was performed on a 4-series, 1-parallel (4S1P) configuration at a 2C-rate under ambient temperature. Time–frequency characteristics of the measured signals were systematically evaluated using MATLAB-based continuous wavelet transform (CWT) and discrete wavelet transform (DWT) techniques. The results reveal that degradation-induced transient events exhibit non-stationary, impulsive voltage and current signatures with distinct frequency-band localization, which intensify with increasing C-rate, elevated temperature, and aging progression. At the module level, although signal amplitudes were partially attenuated due to current redistribution, characteristic wavelet energy patterns and time–frequency concentrations remained clearly distinguishable, demonstrating the scalability of the proposed approach. The combined EM antenna–HFCT sensing strategy, together with multi-resolution wavelet analysis, enables effective phenomenological differentiation between normal operational noise and incipient internal fault signatures well before conventional thermal or capacity-based indicators become evident. These findings demonstrate feasibility of the proposed method for early-stage fault diagnosis and highlight its potential applicability to advanced battery management systems for proactive fire prevention in large-scale energy storage and electric vehicle applications. Unlike conventional voltage-, temperature-, or gas-based diagnostics, the proposed approach enables the detection of incipient degradation phenomena at the microsecond scale by exploiting complementary low- and high-frequency electrical signatures. This study provides experimental evidence that wavelet-based EM and HFCT sensing can identify MISC-related precursors significantly earlier than conventional battery management indicators. Full article

Assessing ecosystem health in rapidly urbanizing watersheds requires policy-relevant and empirically grounded indicator systems. Focusing on the Luxi River Basin in Chengdu’s Tianfu New Area, this study develops an ecosystem health evaluation and restoration zoning scheme based on the Pressure–State–Response framework (PSR). Utilizing remote sensing land use maps for 2004, 2014, and 2024 with overall accuracy and Kappa above 85% and 0.80, respectively, a 13-indicator PSR health index with entropy-based weighting was constructed at the township and subdistrict scales. Aiming to support objective indicator selection and interpretation, multiscale landscape dynamics were further quantified using FRAGSTATS and moving window analysis, including mean patch area, patch density, landscape shape index, largest patch index, Shannon diversity index, Shannon evenness index, contagion index, and splitting index, and sensitive landscape descriptors and major driving factors were identified. Results show a shift in landscape patterns, from relatively aggregated configurations toward highly complex and fragmented ones. Largest patch dominance, measured by the largest patch index, declined from 66.71 to 22.79, while connectivity, measured by the contagion index, decreased from 59.74 to 45.10. Subdivision, measured by the splitting index, increased from 2.24 to 12.88, and compositional heterogeneity, measured by the Shannon diversity index, increased from 0.86 to 1.26. The PSR assessment indicates that demographic pressure intensified over time, whereas improvements in water resource supply, technological progress, and industrial upgrading partially alleviated overall pressure in some subregions. Ecosystem state exhibited strong spatial heterogeneity, with sustained high health in the eastern Longquan Mountain area and substantial improvement around Xinglong Lake, while northern urbanized and southern agricultural subregions lagged behind. Environmental governance responses strengthened, with the response index increasing from 0.2297 to 0.9885. Overall ecosystem health demonstrated a modest but stable improvement from 2004 to 2024, with 65.48% of the area revealing slight improvement, 1.14% experiencing substantial improvement, 29.62% remaining stable, and 3.76% experiencing slight degradation. Finally, restoration priority zones were delineated, and targeted strategies were introduced to inform basin-scale ecological management in the Luxi River Basin. Full article

Soil salinization represents a critical constraint to sustainable agriculture in arid and semi-arid regions, where salinity threatens soil productivity, water quality, and ecosystem resilience. Soil salinity pattern prediction is complicated by tightly coupled landscape hydro-climatic processes, wherein the central Sabkha acts as a persistent salt sink, episodic inundation and intense evaporation concentrate dissolved salts, and a shallow saline groundwater table interacts with the semi-arid climate to drive surface salinization. Conventional mapping is laborious and lacks the precision needed to capture the spatio-temporal dynamics of soil salinity across landscapes. This study developed an integrated framework uniting multi-temporal Landsat imagery (2000–2025), hypsometric data, climatic indicators, and in situ soil electrical conductivity (ECe) measurements to model soil salinity dynamics using machine learning (ML), over the Sehb El Masjoune (SEM) semi-arid region, Morocco. A total of 233 soil samples were collected in the investigated area in 2022, 2023, 2024, and 2025 to assess the spatial variability to calibrate and validate modeling findings. To this end, three predictive algorithms, i.e., Gradient-Boosted Trees (GBT), Support Vector Regression (SVR), and Random Forest (RF) were assessed. Our findings showed that SVR achieved the highest predictive capability (R² = 0.76; RMSE = 32.91 dS/m), whereas SVR-based salinity maps revealed a distinct spatial organization of salinization processes, characterized by extremely saline soils (≥64 dS/m) concentrated in the central study area (i.e., SEM center) and a progressive decline toward adjacent agricultural lands (0–8 dS/m). Our results demonstrated that from 2000 to 2025, moderately to highly saline areas (≥16 dS/m) expanded by nearly 10%, driven by recurrent droughts and inefficient drainage. Hydroclimatic analysis confirmed that dry years (SPI: Standardized Precipitation Index ≤ −0.5) promoted net salinity build-up through the expansion and persistence of moderate-to-high salinity classes (≥16 dS/m), whereas wet years (SPI ≥ +0.5) favored temporary leaching and partial recovery, mainly within the low-to-moderate range. This integrative remote sensing–ML approach provides a robust and scalable framework for operational soil salinity monitoring, offering valuable insights for sustainable land-use planning in similar Sabkha’s data-scarce agroecosystems. Full article

Internet of Things (IoT) applications often require only minimal necessary information—such as threshold judgments, binning, or prefixes—yet they must control privacy leakage arising from multi-round and cross-entity access without exposing raw values. Existing solutions, however, frequently rely on ciphertext structures and server-side states, making it difficult to define a leakage upper bound for restricted answers in the sense of Differential Privacy (DP), or they lack unified information budgeting and k-use control. To address these challenges, this paper proposes a verifiable differential privacy partial disclosure scheme for IoT. We employ DP accounting to uniformly constrain the leakage of three types of operators: threshold, binning, and prefix. Furthermore, we design stateless k-use tokens based on Verifiable Random Functions (VRFs) and chained receipts to generate publicly verifiable compliance evidence for each response. We implemented an end-edge-cloud prototype system and evaluated its performance on two use cases: smart meter threshold alarms and industrial sensor out-of-bound detection. Experimental results demonstrate that compared with a baseline relying on server-state counting for k-use control, our stateless k-use mechanism improves throughput by approximately 25–37% under concurrency scales of 1, 8, and 16, and reduces p95 latency by an average of 15%. Meanwhile, in multi-party splicing attack experiments, the re-identification accuracy remains stable in the 0.50–0.52 range, approximating random guessing. These results validate that the proposed scheme possesses low-energy engineering feasibility and audit-friendliness while effectively suppressing splicing risks. Full article

Staphylococcus epidermidis is more often known as a human skin commensal, serving as a primary protective bacterium on the skin’s surface. However, more recent literature highlights the role of S. epidermidis as a nosocomial pathogen and a multidrug-resistant organism that poses a global threat. The evolution of S. epidermidis can be owed to its accumulation of resistance mechanisms, including adhesion, biofilm formation, genomic islands, phage elements, integrated plasmids, and quorum sensing. It is suspected that through gene transfer, S. epidermidis is partially responsible for the feared multidrug-resistant Staphylococcus aureus through the mecA gene and many other genomic island transfers. Overall, prolonged nosocomial exposure and misuse of antibiotics have driven dramatic genomic remodeling in S. epidermidis, characterized by many methods of genetic recombination, SCCmec and insertion sequence acquisition, and accumulation of multiple resistance genes. Our review reviews the role of S. epidermidis as both a commensal and a pathogenic bacterium, summarizes the genes responsible for its multidrug resistance, and describes methods of combatting its invasion. Full article

Rural transportation corridors remain weakly instrumented for continuous low-altitude airspace monitoring. At the same time, Vehicle-to-Everything (V2X) roadside units (RSUs) are increasingly deployed for transportation safety services. This work investigates whether existing RSUs can be extended with passive, cooperative RF sensing to detect small UAVs without modifying standards-compliant ITS communications in the protected 5.9 GHz band. A calibrated simulation study evaluates corridor-scale operation under realistic propagation conditions, including terrain masking and narrowband interference. All results reported in this paper are derived from simulation and do not include field measurements or hardware prototyping. False alarm performance under diverse ISM emitters is not quantified. The results show that cooperative processing across neighboring RSUs improves epoch-level verified detection coverage compared with single-RSU sensing. Bearing variability is reduced for weak or partially masked signals. These gains result from feature-level validation across spatially separated receivers rather than deterministic signal combining. RF calibration constrains detections to physically plausible kilometer-scale ranges. The resulting angular accuracy is sufficient for early warning and track initiation, but not for precise localization. Overall, the findings indicate that existing V2X infrastructure can support supplementary early warning capability for corridor-scale airspace monitoring while preserving primary V2X safety functions. Full article

Civil construction is considered one of the industries with the most significant environmental impact. In this sense, the main goal of this study was to investigate three different mortar sets incorporating industrial lamination waste, assessing their chemical, physical, and microstructural properties, as well as their mechanical performance to develop sustainable mortars. Cylindrical and prismatic specimens were produced using various incorporation methods: reference mortar, mortars with mill scale addition, partial replacement of cement with mill scale residue, and partial replacement of sand with residue, at proportions of 10%, 20%, 30%, 40%, and 50%. In addition, X-ray fluorescence (XRF), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and scanning electron microscopy with energy-dispersive spectroscopy (SEM/EDS) analyses were performed. Physical and mechanical tests included those for bulk density, consistency index, water absorption by capillarity, axial compressive strength, and flexural tensile strength. XRF analyses showed an increase in iron oxide content and a decrease in calcium oxide with the addition of mill scale. XRD analyses confirmed the presence of compounds such as alite and portlandite, which are common in cementitious mortars. FTIR spectra confirmed the presence of functional groups through absorption bands associated with Si–O stretching. SEM images showed slight morphological changes in the composites as the amount of industrial lamination waste increased. The addition of industrial lamination waste affected the spread index and density of the mixtures, while water absorption by capillarity decreased in some formulations with mill scale. Concerning mechanical performance, the strength of the mortars varied with increasing amounts of industrial lamination waste. Full article