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Permittivity extraction of sandy soils through uncalibrated and thickness-independent meniscus-free measurements using a hollow coaxial line
Abstract Measurement techniques for accurate moisture level determination of various soil conditions are becoming popular in recent studies. Microwave-driven techniques, as positioned into indirect methods, could be tailored for precise and real-time detection of soil moisture. However, improper implementation of calibration techniques or usage of imperfect calibration standards required for precise measurements by these techniques presents a challenging limitation for their widespread usage. Besides, meniscus formation on top of soil samples with a sufficient moisture level could adversely influence the performance of these techniques. In this study, we present a microwave extraction method for eliminating the requirement of a formal calibration procedure and additionally removing the effect of meniscus on measurements through relative measurements of sandy soil samples while maintaining accurate permittivity extraction with no information of sample thickness. To achieve our goal, a mathematical framework unifying wave-cascading matrix and state-transition matrix presentations is proposed for permittivity determination from three measurement configurations (empty line, the (sandy) soil sample sandwiched between two identical plugs, and a shifted version of this plug-sample-plug configuration) and their inverses implemented by port switching operation. The proposed method is first validated by permittivity measurements of two liquid samples (distilled water and methanol). Then, permittivity measurements of two sandy soil samples (having more than 90% sand content) were conducted using Type-N-to-EIA 1-5/8” coaxial lines (with no universal calibration standard) over 0.05 GHz–3.0 GHz. From these measurements, it is noted that our meniscus-free method determines permittivity with a maximum absolute difference of 3.4% (evaluated from five independent measurements) while another similar method, suffering from meniscus presence, extracts permittivity with a maximum absolute difference of 4.0%. This indicates a clear advantage of our method for measurements of sandy soil samples having meniscus formation. We then utilized to construct a calibration curve, compared with other calibration curves using by other methods, allowing prediction of moisture volume content ( $$\theta _v$$ ) of the tested sandy soil samples from measured permittivity data whose conformity analysis implemented by the three-pole Debye model and the Mironov-Fomin model. It is observed that this calibration curve could be utilized to predict $$\theta _v$$ within $$5\%$$ margin from measured permittivity data.
Trump one year on: How six US researchers plan to protect science amid chaos and cuts
Astrocyte CCN1 stabilizes neural circuits in the adult brain
Nighttime warming enhances photosynthetic activity and induces changes in chloroplast membrane structure and antioxidant profile in Platycerium ferns
Surface markers on supermeres outperform extracellular vesicles in colorectal cancer diagnosis
Abstract Extracellular nanocarriers, such as extracellular vesicles (EVs), lipoproteins, supermeres, and exomeres are diverse lipid-protein-nucleic acid assemblies. Among them, supermeres hold significant diagnostic potential but are challenging to characterize due to limited surface biomarker information and labor-intensive isolation methods. This study introduces an isolation-free Ion Exchange Membrane Sensing method for the detection of supermeres within 30 min using 50 µL of sample, with a sensitivity of 10⁶–10⁷ supermeres/mL. Validation through ultracentrifugation (UC) and surface plasmon resonance (SPR) confirms the detection accuracy and specificity. Supermeres carry key proteins such as HSPA13, ENO2, and DDR1 analogous to tetraspanin in EV. Supermeres outperform small EVs (sEVs) and exomeres across multiple shared and unique surface proteins critical to colorectal cancer diagnosis, highlighting their superior clinical utility and potential as next-generation biomarkers in precision medicine.
Forget formalism: mathematics was built on infighting and emotional turmoil
Iterative multiblock framework for high frequency EEG based neurological disorder detection
Intelligent decision-making systems for early detection of alzheimer’s disease using wearable technologies and deep learning
Modular Harris Hawks optimization with trend-guided differential evolution and Gaussian exploration for global optimization and engineering design
Morphological evaluation and ınheritance of powdery mildew resistance in garden pea (Pisum sativum L.)
‘Greed is the iron cage of our times’ — why nationalism is here to stay
Advancing sports performance evaluation through T spherical fuzzy FUCA MCDM approach to real time basketball analytics
A machine learning-based prediction model for poor prognosis in sepsis using lymphocyte count: a national, multicenter prospective cohort
Abstract Sepsis-induced immunosuppression leads to poor prognosis. Circulating lymphocyte count (LC), as an easily accessible clinical marker, closely reflects the immune status of sepsis. The study aims to perform immune phenotyping of sepsis patients using dynamic LC for early identification of high-risk individuals. A latent class trajectory model (LCTM) was used to analyze the dynamic trajectories of lymphocyte count (LC) based on repeated measurements obtained within at least two measurements of lymphocyte count (LC) within the first 24 h after sepsis diagnosis, followed by two more between day 2 and day 7. Survival differences among subphenotypes were assessed using Kaplan–Meier curves and Cox regression. Feature selection was conducted via the Boruta algorithm, and a high-precision machine learning model was developed to predict the target trajectory. Model interpretability was ensured through SHapley Additive exPlanations (SHAP). The predictive performance of the model for ICU mortality was assessed using the receiver operating characteristic (ROC) curve. The derivation cohort included 2085 sepsis patients from the China Multicenter Sepsis database, and the external validation cohort of 1299 sepsis patients. We identified four trajectory patterns of LC dynamics, among which the persistent lymphopenia (PL) subgroup exhibited the highest disease severity and poorest prognosis. The trajectory model demonstrated consistent patterns in external validation. Six machine learning models were utilized to determine the best model to identify the PL subphenotype, and an online prediction tool was developed for clinical application. Incorporating the PL trajectory subphenotype significantly improved the predictive performance for ICU mortality. Dynamic LC trajectories effectively capture immunological heterogeneity in sepsis, encompassing immunocompromised and immunocompetent hosts. These findings underscore the importance of early identification of patients with persistent lymphopenia to better target populations for future sepsis immunotherapy.
Cretaceous crocodyliform reconciles conflicting evidence on the Mesozoic paleogeography of Europe during the Gondwana-Laurasia split
Abstract Inferred biotic exchanges between Europe and Africa during the Cretaceous have been used to support the hypothesis that the complete separation of Europe from Gondwana postdated the split of the remaining Laurasian landmasses from Gondwana. Under this framework, Europe, conceptualized as part of a proposed ‘Eurogondwana’, is thought to have maintained biogeographic connections with Africa well into the Cretaceous. A key piece of evidence underpinning this hypothesis has been the crocodyliform Doratodon carcharidens from the Late Cretaceous of Europe, previously interpreted as closely related to Gondwanan taxa. However, the material attributed to this species is fragmentary, and its skeletal anatomy—critical for phylogenetic inference—remains poorly understood. Here we describe a new partial skull of Doratodon carcharidens which represents some of the most complete material of ‘Gondwanan’ taxa in the European Cretaceous. Our updated phylogenetic analysis unexpectedly and robustly places D. carcharidens among the Laurasian clade Paralligatoridae and reveals that morphological similarities to Gondwanan ziphosuchians, such as ziphodont dentition, are the result of remarkable ecomorphological convergence rather than shared ancestry. By reinterpreting the systematic position of further taxa representing biogeographic enigma, such as Ogresuchus furatus , our phylogeny implies a major role of the primary breakup of Pangea into Laurasia and Gondwana for crocodyliform divergence. A critical reassessment of the purported evidence for ‘Gondwanan’ fish and tetrapod immigrants in Europe reveals that it is largely based on highly fragmentary and sporadic specimens, as well as weakly supported phylogenetic hypotheses. Given the sparse and uneven Jurassic and Cretaceous fossil record in both Europe and Africa, it remains plausible that taxa previously interpreted as Gondwanan dispersers instead represent vicariant relicts. Our results conflict with recent paleobiogeographic scenarios, highlight the absence of compelling evidence for the Eurogondwana hypothesis and instead support a primary Gondwana-Laurasia split.
Floating science stations: my month on a research vessel looking after buoys
Evolution of plastic zone in surrounding rock of roadway within anisotropic stratum under complex in-situ stress
Towards reliable elastic characterization of glass bead reinforced thermoplastic composites using impulse excitation and conventional testing
Abstract Reliable determination of elastic properties is essential for the structural use of polymer composites in engineering applications. This work aims to evaluate the impulse excitation technique (IET) as a method for determining elastic constants of glass bead‑reinforced polyamide 66 (PA66) and polybutylene terephthalate (PBT), and to compare its performance to tensile testing (TT), dynamic mechanical analysis (DMA), and oscillatory torsion (OT). Commercial PA66 and PBT grades with 0–40 wt% glass beads were injection‑molded and annealed; the addition of glass beads increased Young’s moduli by 60–70% for PA66 and 40–60% for PBT compared to the neat matrices, depending on filler content. IET, supported by finite element analysis, provided dynamic flexural and longitudinal moduli, shear modulus, and Poisson’s ratio which were comparable to those obtained from TT, DMA and OT. In the linear elastic regime IET data differed within the standard deviations of TT, DMA and OT. The moduli determined by flexural excitation using IET and DMA agreed within experimental uncertainty only above an amplitude threshold of approximately 110 μm, while Young’s moduli from TT and IET showed good agreement, though TT exhibited greater variability. Consistent trends were also found for shear modulus and Poisson’s ratio. The higher longitudinal moduli (4 to 8% for PA66 and 2 to 4% for PBT) measured by IET are explained by higher frequencies (3 to 4 orders of magnitude) and cross-sectional microstructural anisotropy and crystallinity differences confirmed by microscopy and calorimetry. The results demonstrate that IET is a much faster, non‑destructive and accurate method for obtaining elastic constants of thermoplastic composites particularly suited for the design and dimensioning of load‑bearing structural components.