Search Results (30,476)

The Babylonian numeral system, developed more than four thousand years ago, is one of the earliest known positional number systems, employing a sexagesimal (base-60) structure and a limited set of wedge-shaped symbols. Despite their visual simplicity, Babylonian numerals exhibit substantial structural and positional complexity, particularly when multiple symbols are combined to represent larger numerical values. This complexity presents significant challenges for modern computational recognition, especially in handwritten and degraded archaeological contexts. Most existing research has focused on the recognition of isolated Babylonian numeral symbols, which does not adequately reflect real inscriptions where numerals typically appear as composite sequences. To address this limitation, this paper proposes a hybrid deep learning framework capable of identifying, interpreting, and computing the decimal values of multi-symbol handwritten Babylonian numerals. Building on prior work in single-symbol recognition, we construct a synthetic yet realistic dataset of composite numeral images by combining handwritten glyphs into sequences of two to four symbols while incorporating natural variations in spacing, alignment, and handwriting style. The proposed framework integrates a Convolutional Neural Network (CNN) for visual feature extraction with optional structural feature fusion, followed by a Support Vector Machine (SVM) classifier for reliable multi-class discrimination. A rule-based positional decoder is then applied to convert recognized symbol sequences into their corresponding decimal values using Babylonian base-60 logic. By combining visual recognition with positional numerical reasoning, the proposed system enables end-to-end interpretation of handwritten Babylonian numeral sequences. To the best of our knowledge, this work represents one of the first approaches to jointly classify, decode, and compute numerical values from multi-symbol handwritten Babylonian numerals, contributing to digital epigraphy, archaeological text analysis, and cultural heritage preservation. Full article

This study quantitatively evaluates the impact of Wire Arc Additive Manufacturing (WAAM) process parameters on the environmental performance of components produced in Invar 36 alloy. An experimental campaign involving 49 parameter sets was carried out by varying wire feed speed, welding voltage, and welding speed. For each condition, electrical signals, shielding gas consumption, and wire usage were measured and converted into parameter-resolved Life Cycle Inventory (LCI) data. A cradle-to-gate Life Cycle Assessment (LCA) was implemented in SimaPro 9.6 using the European CML-IA baseline v3.10 midpoint method, adopting 1 kg of as-built deposited Invar 36 as the functional unit. Results show that feedstock production represents the dominant hotspot (8.68 kg CO${}_2$-eq/kg), while the WAAM stage contributes between 1.13 and 4.12 kg CO${}_2$-eq/kg, leading to a total impact ranging from 9.81 to 12.80 kg CO${}_2$-eq/kg. As a result, this study demonstrates that process parameter selection strongly influences environmental performance. Indeed, Specific Energy Consumption (SEC) ranges from 0.44 to 1.95 kWh/kg, while argon consumption varies between 0.26 and 1.51 kg/kg of deposited material. By analysing the results and excluding unstable or manufacturing-infeasible deposition regimes, the optimal trade-off between process stability and environmental impact is achieved at approximately WFS = 7 m/min, V = 20 V, and WS = 6.5 mm/s. Beyond quantifying the environmental hotspots of Invar 36 WAAM, this study provides a dedicated, parameter-resolved cradle-to-gate LCA based on experimentally measured foreground data collected across 49 process parameter combinations. By combining environmental assessment with feasibility screening of the investigated deposition regimes, the work identifies not only environmentally favourable conditions, but also parameter regions that are technologically viable for WAAM processing of Invar 36. The resulting dataset provides a benchmark foundation for future sustainability-oriented process optimisation and decision support in WAAM. Full article

Bidirectional AC/DC converters in hybrid microgrids are prone to DC-bus voltage instability caused by source-side, grid-side, and load-side disturbances. Conventional linear active disturbance rejection control (LADRC) suffers from a trade-off between transient overshoot suppression and disturbance rejection capability, which limits its practical application. To address this issue, an improved LADRC strategy for bidirectional AC/DC converters is proposed in this paper. First, a linear tracking differentiator (LTD) is introduced to smooth the DC-bus voltage reference and suppress overshoot caused by abrupt command changes. Second, a proportional-derivative (PD) term is embedded into the linear extended state observer (LESO) to introduce phase lead compensation, thereby improving the observer phase characteristics without excessively increasing the observation bandwidth or amplifying high-frequency noise. Frequency domain analysis, MATLAB/Simulink simulations, and full-hardware prototype experiments are carried out to validate the proposed method. The simulation study covers grid voltage sag, photovoltaic-side source fluctuation, and DC-side load disturbance conditions. To further strengthen the experimental verification, hardware tests are conducted under grid voltage dip, PV-side voltage reduction, and DC-side load-switching conditions. The results consistently show that the proposed strategy can effectively reduce DC-bus voltage fluctuation and improve transient recovery performance compared with conventional LADRC. Therefore, the improved LADRC provides a practical and robust control solution for stabilizing bidirectional converters in AC/DC hybrid microgrids. Full article

Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest malignancies, characterized by early metastasis, dense desmoplastic stroma and a profoundly immunosuppressive, lymphocyte-depleted tumor microenvironment that severely limits the efficacy of current systemic and immunotherapeutic approaches. Oncolytic viruses (OVs), which selectively replicate in and lyse malignant cells while activating antitumor immunity, have emerged as attractive candidates to convert this “cold” tumor into a more inflamed and therapeutically responsive disease. In this review, we summarize clinical evidence on the main OV platforms evaluated in PDAC, including adenovirus, herpes simplex virus, vaccinia virus, parvovirus and reovirus, with a focus on clinical trials. Across these classes of viruses, intratumoral administration has consistently proven feasible and generally well tolerated, with frequent evidence of viral replication, microenvironmental remodeling and immune activation, but only modest and often transient antitumor responses in small, early-phase cohorts. We then discuss key biological and translational challenges that currently limit OV impact in PDAC, such as systemic delivery in the context of pre-existing antiviral immunity and rapid clearance, penetration through the fibrotic stroma, and rational selection of encoded transgenes to reshape myeloid cell-driven, pro-tumoral inflammation and enhance T-cell recruitment. Finally, we outline future directions for the field, including carrier-cell–based systemic delivery, stroma-targeting or cytokine-armed constructs, and combinatorial strategies with chemotherapy and immune checkpoint blockade, arguing that design refinement, innovative combinations and mechanism-driven trial designs will be essential to unlock the full therapeutic potential of oncolytic virotherapy in PDAC. Full article

Background/Objectives: Stereotactic body radiation therapy (SBRT) provides improved pain response and local control for spinal metastases. However, management of local failure after initial SBRT is challenging. We report institutional outcomes, dosimetry, and toxicity for reSBRT following SBRT. Methods: We retrospectively reviewed 61 lesions (55 patients) treated with reSBRT after prior SBRT. Both SBRT courses delivered a median dose of 27 Gy. Patients underwent clinical and radiological evaluation every three months. Toxicity was graded using CTCAE v5.0. Dosimetric parameters for the spinal cord (SC), cauda equina (CE), planning organ-at-risk volumes (PRV), and thecal sac were converted to equivalent dose in 2 Gy fractions (EQD₂) using the linear–quadratic model (α/β = 2). Results: Median follow-up was 10.3 months. Forty lesions (65%) were cervicothoracic and 21 (35%) were lumbosacral. One- and two-year overall survival (OS) were 45% and 29%, respectively, and one- and two-year local control (LC) were 89% and 88%, respectively. Gastrointestinal primary tumors were associated with inferior LC (HR 2.41, 95% CI 1.11–5.23, p = 0.026). Fifteen patients (27%) reported myelitis/neuropathic symptoms during follow-up; four (7%) developed new post-radiation myelitis or neuropathy (RMN) without radiologic progression. Five patients (9%) developed vertebral compression fractures (VCF). Cumulative EQD₂ was not significantly associated with RMN (p = 0.344); all affected patients had thecal sac EQD₂ > 95.5 Gy and relevant nerve roots EQD₂ > 108 Gy. Conclusions: ReSBRT provided a favorable LC with acceptable toxicity. High cumulative dose to the thecal sac and nerve roots may contribute to neurologic toxicity as peripheral nerve injury. Full article

To explicitly illustrate the relationship between heliostat field optimization and power generation, a coupled model was established in Simulink. By optimizing the geometric layout of the heliostat field, the solar heat collection efficiency can be significantly improved, thereby increasing the thermal input to the system. The optimized heliostat field design can convert solar energy into thermal energy more efficiently and transfer it to the steam generator through the molten salt loop, thereby driving power generation in the Rankine cycle. In this process, the Rankine cycle is responsible for converting the thermal energy supplied by the molten salt loop into mechanical work and ultimately into electrical power output. At the same time, real meteorological data from a commercial heliostat field were introduced, and annual power generation simulations demonstrated that the integrated modeling of the heliostat field, thermal storage, and power block based on actual meteorological boundary conditions and system parameters can effectively reflect the power generation performance of a commercial tower solar thermal power plant. Meanwhile, research on heliostat field optimization should further evolve from identifying general patterns toward parameter design and overall system performance improvement. For molten-salt tower solar thermal power plants, key design variables such as receiver tower height, receiver dimensions, heliostat dimensions, and heliostat field spacing parameters affect not only the annual average optical efficiency of the heliostat field and the thermal power output of the receiver, but also the annual power generation of the entire plant. By integrating SOLARPILOT 1.5.2 and SAM 2025.4.16, the design variables were systematically analyzed to investigate their effects on the annual average optical efficiency of the heliostat field, the number of heliostats, the receiver output power, and the annual power generation, and the reasonable value ranges of the heliostat field parameters were determined accordingly. The established Rankine cycle power block model was then coupled with the parameter optimization results to carry out a secondary optimization of the initial heliostat field. Through the above study, the aim is to realize a shift from single-objective geometric optimization of the heliostat field to comprehensive optimization oriented toward annual plant power generation performance and scenario adaptability, thereby providing a basis for scheme design and parameter selection of molten-salt tower solar thermal power plants. For external validation, the annual generation predicted for the Delingha 50 MW commercial plant was 142.15 GWh, corresponding to a relative deviation of 2.64% from the published design value of 146 GWh. This indicates that the coupled framework can reasonably capture the integrated response of the heliostat field, thermal storage system, and power block at the plant level. The model is therefore suitable for generation-oriented parameter screening and preliminary design of tower molten-salt CSP plants, while detailed component-level transient design still requires higher-fidelity engineering models. Full article

Short-horizon equity forecasting remains challenging because daily prices are noisy, heavy-tailed, and subject to structural breaks and regime shifts. We develop a fully automated, reproducible, and leakage-controlled multi-model pipeline for daily forecasting with horizon-specific configuration selection. The task is formulated as predicting cumulative H-day log-returns from OHLCV-derived information and converting them to implied price forecasts. All model families share a homologated design: causal feature construction, a strictly chronological split with an explicit purging rule to prevent label-window overlap for multi-day targets, training-only robustification (winsorization and adaptive clipping), and a unified metric suite computed consistently in return and price spaces. The framework benchmarks transparent baselines (zero- and mean-return), gradient-boosted trees (XGBoost), and deep temporal models (LSTM and CNN/TCN). Lookback length $L\in \{60,180,500\}$ is selected via an internal walk-forward procedure on the pre-evaluation block, and final performance is reported on an external hold-out segment (last 15% of instances). Experiments on daily data for MT, DELL, and the S&P 500 index (through 3 February 2026) show that all families achieve similarly strong price-level fit at $H=1$, largely driven by persistence in the price process, while separation across families becomes more visible at $H=5$. However, predictive performance in return space remains weak, with $R^2$ close to zero or negative, and Diebold–Mariano tests do not provide consistent evidence of statistical superiority over naive benchmarks. Under an operational rule that minimizes hold-out RMSE on the price scale, selected models are asset- and horizon-dependent, supporting horizon-wise selection rather than a single global architecture. Overall, the primary contribution lies in the proposed leakage-controlled evaluation and benchmarking framework rather than in demonstrating consistent predictive gains in financial time series forecasting. Full article

Triboelectric nanogenerators (TENGs) have emerged as versatile self-powered platforms for wearable and implantable biomedical sensing, offering an alternative to battery-dependent electronic devices. By converting biomechanical energy from physiological motion into electrical signals, TENGs enable simultaneous energy harvesting and active sensing within flexible, lightweight, and biocompatible architectures. This review summarizes recent advances from 2020 to 2025 in triboelectric nanogenerator (TENG)-based cardiovascular monitoring. The discussion focuses on material systems, device configurations, sensing mechanisms, and applications including pulse detection and cuffless blood pressure estimation. Representative studies are compared to highlight emerging trends in wearable and self-powered sensing technologies. However, differences in experimental conditions, anatomical sites, calibration methods, and signal-processing approaches limit direct comparison of reported performance. In addition, challenges such as subject-specific calibration, motion artifacts, and limited clinical validation remain. Overall, this review highlights current progress and outlines key challenges for future development and translation of TENG-based cardiovascular monitoring systems. Full article

Massive pelagic Sargassum influxes along Caribbean coasts have created an urgent need for valorization routes for this biomass. Here, sodium alginate was extracted from Sargassum fluitans collected at Chuburná Beach, Yucatán, Mexico, using a multistep extraction involving 0.2% formaldehyde pretreatment at 4 °C and brief heating at 65–70 °C, and subsequently used to prepare calcium-crosslinked alginate nanoparticles by ionotropic gelation. To our knowledge, this is the first direct synthesis of alginate nanoparticles from non-commercial alginate extracted from pelagic S. fluitans. An extraction yield of 18.7 ± 0.05% (mean ± SD, n = 3) was obtained, and UV–Vis, FTIR, and NMR analyses confirmed the characteristic structural features of alginate. ¹H NMR revealed an M-rich composition (F_M = 0.61, F_G = 0.39; M/G = 1.54) with short guluronate blocks (N_G>1 = 2.42), whereas ¹³C NMR corroborated the presence of both β-D-mannuronic and α-L-guluronic acid residues. SEM images showed predominantly spherical-to-subspherical nanoparticles with representative dry diameters of 233–269 nm, whereas DLS measurements at 0, 24, and 72 h revealed a dominant volume-based nanoscale population with main peaks at 12.75–15.31 nm and PDI values of 0.229–0.291, indicating reasonable short-term colloidal stability at room temperature. These results demonstrate that pelagic S. fluitans can serve as a viable feedstock for the production of structurally preserved alginate and calcium-crosslinked alginate nanoparticles. The study supports converting recurrent Sargassum biomass into higher-value polysaccharide-based materials and provides a basis for future application-specific evaluation of these nanomaterials. Full article

Intramuscular fat (IMF) marbling is a key determinant of beef quality, yet predicting how breed-specific gene expression translates into tissue-scale fat patterning remains a major challenge. Using a small public transcriptomic dataset (n = 3 per breed), this study presents a proof-of-concept omics-to-tissue modeling framework that converts RNA-seq data into biophysically interpretable parameters governing intramuscular adipogenesis. Using transcriptomic profiles from GSE161967 (Japanese Black Wagyu versus Chinese Red Steppes), we derived composite indices capturing the adipogenic commitment (φ) and lipid droplet capacity (ψ) from curated gene modules. These indices were mapped via calibrated linear functions to a Cellular Potts Model (CPM), parameterizing the fibro-adipogenic progenitor (FAP) differentiation probability, lipogenesis rate, adipocyte cohesion, and progenitor abundance. The gene-derived parameters placed Wagyu in a high-adipogenic regime ($p_{F\to A}^{\mathrm{base}}$ = 0.65; $k_{lipogenesis}$ = 0.12), while Chinese Red Steppes resided in a low-adipogenic regime (0.25; 0.04). The CPM simulations revealed a sharp, predictive threshold at $p_{F\to A}^{\mathrm{base}}$ ≈ 0.55, below which IMF remained negligible and above which stable adipocyte clusters and 8–9% IMF emerged. Without post hoc tuning, the gene-derived parameters correctly predicted robust marbling in Wagyu and a lean phenotype in Chinese Red Steppes. A sensitivity analysis identified the adipogenic commitment as the primary control parameter, with lipogenesis acting as an amplifier. Together, these results demonstrate that transcriptomic measurements can quantitatively predict emergent marbling phenotypes through a small set of interpretable biophysical parameters, establishing a generalizable framework for forecasting complex tissue traits from omics data. Full article

Docosahexaenoic acid (DHA) is an essential ω-3 polyunsaturated fatty acid (PUFA) with high nutritional and pharmaceutical value. The marine protist Aurantiochytrium is a promising industrial DHA producer; however, its DHA biosynthesis via the PUFA synthase pathway co-produces ω-6 docosapentaenoic acid (DPA), limiting DHA purity. Here, we introduced an ω-3 desaturase from Phytophthora infestans (Pin-O3D) into Aurantiochytrium sp. SD116. Functional validation in an Escherichia coli system co-expressing the native PUFA synthase confirmed that Pin-O3D converts DPA to DHA, shifting the DHA/DPA ratio from 1:1 to 2:1. Pin-O3D was then integrated into the fatty acid synthase (FAS) locus, simultaneously attenuating FAS activity and enabling heterologous gene expression. The engineered strain ΔFAS-Pin-O3D exhibited significantly (p < 0.0001 in t-test) increased DHA content (55.2% of total fatty acids) and DHA/DPA ratio (5.91) in shake flasks, with no negative impact on biomass or lipid accumulation. Fed-batch fermentation confirmed the scalability of this strategy, achieving a >20% increase in DHA/DPA ratio. This study demonstrates that combining heterologous ω-3 desaturase expression with FAS attenuation is an effective approach for optimizing PUFA profiles in Aurantiochytrium. Full article

Background and Clinical Significance: Angiotensin-converting enzyme inhibitors (ACE-Is) are commonly used for treatment of hypertension and are well known among primary care specialists. ACE-I-induced angioedema is a rare, yet possible side effect. It should not be taken lightly, as it can be life-threatening. It is characterized by erythematous or skin-coloured, self-limiting, localized, non-pitting swelling of the submucosal and/or subcutaneous layers of tissue. Usually, it develops in the first year of using the medication, although it can also start several years after using it. Herein, we describe a late-onset ACE-I-induced angioedema, which developed 7 years after using the ACE-I. This case report depicts the challenges of diagnosing ACE-I-induced angioedema, especially if it is late-onset. It highlights the importance of actively asking patients questions about possible side effects of medication even several years after using it and the patients themselves not having any complaints. Case Presentation: We present a 61-year-old Caucasian male with recurring swelling of the lips, tongue and an uncomfortable feeling in the throat, which started 7 years after using an ACE-I: perindopril. There was no airway obstruction or urticaria in any of the episodes. Hereditary angioedema was ruled out by blood analysis. Based on the clinical presentation, images and blood analysis, it was diagnosed as late-onset ACE-I-induced angioedema. After discontinuing the ACE-I, there were two more episodes of angioedema reported, which were a lot milder in symptoms and lasted a shorter time period. Since then, there have been no other episodes of angioedema. Conclusions: It is important to keep in mind angioedema as a possible side effect for patients on ACE-Is. Patients should be regularly and actively questioned about side effects, even if the medication has been started several years ago and no complaints are brought up by the patient. Full article

Background: Monitoring skeletal muscle mass (SMM) during radiotherapy (RT) is important, as SMM loss is associated with poorer clinical outcomes. Cone-beam CT (CBCT), acquired before each RT fraction, offers the potential to track the lumbar skeletal muscle index (LSMI) over time. However, CBCT has lower image quality than conventional CT. This study assessed the agreement between CT and CBCT and evaluated the reliability of LSMI measurements in patients with head and neck squamous cell carcinoma. Methods: Patients who underwent both CT and CBCT on the same day during RT were included. The cross-sectional muscle area at C3 was measured, converted to L3, and used to calculate the LSMI. Two researchers analyzed all scans, with one repeating the measurements. Agreement and reliability were quantified using intraclass correlation coefficients (ICCs) and visualized with Bland–Altman plots. Results: LSMI measurements showed excellent agreement between CBCT and CT (ICC: 0.97–0.99; 95% CI: 0.95–0.99). The intrarater (ICC: 0.99; 95% CI 0.98–0.99) and interrater reliability (ICC: 0.97; 95% CI: 0.66–0.99) were high. Bland–Altman plots, however, revealed wide limits of agreement. Conclusion: CBCT provides reliable LSMI measurements and agrees well with CT, but the observed variability suggests cautious interpretation. When both modalities are available, CT remains the preferred standard for SMM assessment. Full article

Methanol is the simplest C1 oxygenated compound possessing the highest hydrogen-to-carbon ratio and can therefore be used as an effective hydrogen carrier. Furthermore, it can be easily transported by land and sea because it is liquid at room temperature and atmospheric pressure. Methanol can be converted into hydrogen via methanol steam reforming (MSR), aqueous-phase reforming of methanol (APRM), or aqueous methanol dehydrogenation (AMDH). In this review, various catalysts for MSR, APRM, and AMDH are summarized. Highly active and stable catalysts that can operate under low steam-to-methanol ratios are needed to increase the economics of the MSR process. Compared with the MSR process, the APRM process is rather simple because the water–gas shift reaction can occur simultaneously; however, more constraints exist in the selection of active metals and supports to ensure high activity and stability under APRM conditions. The inherently low reaction rate compared to MSR and the structural vulnerability of the catalyst under severe hydrothermal conditions are obstacles that the APRM catalysts must overcome. The low intrinsic catalytic activity and the high cost of homogeneous catalysts represent fundamental limitations inherent to AMDH catalysts. Based on a literature survey of MSR, APRM, and AMDH catalysts, some future research directions are also discussed. Full article

Overcoming the inherent permeability–selectivity trade−off is essential to broaden the practical application of polyamide (PA) reverse osmosis (RO) membranes in brackish water desalination. In this study, we developed a facile and cost-effective alkaline (NaOH) post-treatment method to fabricate high−performance loose-structured RO membranes. The NaOH post−treatment hydrolyzed part of the amide bonds within the membrane, converting them to negatively charged carboxyl groups. This process led to a slight increase in pore size and the formation of a looser structure. Molecular weight cut−off (MWCO) measurements confirmed that the pore size slightly increased from 0.19 nm to 0.21 nm, while X−ray photoelectron spectroscopy (XPS) and zeta potential measurements confirmed the conversion of amide bonds to carboxyl groups, which further enhanced the surface electronegativity. The synergistic effects of pore size enlargement and surface charge modification were elucidated as the key mechanisms for performance enhancement. The TPA membrane exhibited a 2−fold increase in water permeance (from 1.05 to 3.21 L m⁻² h⁻¹ bar⁻¹), while the enhanced surface negative charge contributed to maintaining a high NaCl rejection of 98.5%. Additionally, the membrane also exhibited excellent pH stability as well as long-term stability over 100 h of continuous operation. This easily scalable post−treatment strategy offers a low−cost route to fabricate loose-structured membranes, with significant potential to enhance efficiency and reduce costs in brackish water desalination. Full article