Search Results (723)

Background: DNA methylation is a key epigenetic mechanism whose dynamics are closely linked to ageing. Modern epigenetic clocks predict biological age based on the average methylation level. The concept of “epigenetic rejuvenation” posits that at early stages of development, the biological age of the embryo may decrease, reaching a minimum (“ground zero”) at the gastrulation stage. However, standard averaging methods may not account for important rearrangements in the internal structure of methylation. Objective: To apply the apparatus of information theory and topological data science to the analysis of scNMT-seq data and to test whether DNA methylation entropy decreases from stage E4.5 to E6.5, which would correspond to an approach towards the biological zero state. Methods: Publicly available scNMT-seq data (GSE121690) were analyzed. Five entropy measures were calculated for each cell (Shannon, Renyi, Tsallis, LZ-complexity, local gradient entropy (entropy of variations in the smoothed histogram of the methylation distribution), and persistent entropy (PE)—a topological complexity measure). For the five-dimensional entropy feature space, a Rips complex was constructed, and persistence diagrams H_0 and H_1 were computed. Results: All five entropy measures decreased significantly, with LZ complexity showing the largest relative reduction (−28.4%) and the strongest independent signal (partial r = −0.181). Among all the complexity measures studied, LZ complexity exhibited the largest relative reduction, underscoring its heightened sensitivity to the progressive ordering of the epigenetic landscape. Notably, the ternary encoding of LZ complexity showed strong correlation with Shannon entropy (r = 0.71), indicating that algorithmic complexity, when accounting for partial methylation states, aligns closely with statistical entropy while retaining sensitivity to spatial order. The consistency of results across binary and ternary encodings confirms the robustness of LZ complexity as a structural biomarker. Persistent entropy confirmed the general dynamics (decrease from 15.91 to 14.89, p = 0.01). Topological analysis of the multidimensional space revealed a qualitative reorganization: at stage E6.5, stable cyclic structures (H₁) emerge, while at E4.5 the space is dominated by a single large-scale cycle. Null model validation confirmed that the observed H₁-cycles are genuine topological features rather than random fluctuations. Comprehensive topological characterization showed that normalized persistent entropy increases from 0.846 to 0.882 (p < 0.001), while maximum persistence decreases from 0.446 to 0.218 (p < 0.001), reflecting a transition from a homogeneous state to structured diversification—multiple, evenly distributed cycles corresponding to distinct cell lineages. Consistent with this, regional disorder (RE/RD) at the single-cell level decreases from E4.5 to E6.5 (RE: −25.5%, RD: −27.4%, p < 10⁻¹³), while global entropy also decreases, together painting a picture of epigenetic rejuvenation as ordered consolidation at the whole-genome scale. An SVM model trained on 15 entropy and structural features achieved stage classification with an accuracy of 93.4% and AUC of 0.981, confirming the diagnostic potential of the approach. Conclusions: The decrease in DNA methylation entropy from E4.5 to E6.5 corresponds to an approach to “ground zero”—the point of minimum biological age in embryogenesis—and supports the hypothesis of a link between decreasing entropy and epigenetic rejuvenation. The addition of topological analysis reveals the hidden organization of epigenetic diversity, showing that ordering does not lead to homogenization but is accompanied by the formation of distinguishable cell lineages. Full article

This study evaluates groundwater quality in the Bismil Plain (Diyarbakır, Southeast Türkiye) using a total of 208 samples collected from 26 wells during eight seasonal sampling periods conducted between 2022 and 2024. In each sample, pH, electrical conductivity (EC), and the major ions Ca²⁺, Mg²⁺, Na⁺, K⁺, Cl⁻, SO₄²⁻, HCO₃⁻ and NO₃⁻ were analyzed, and a WHO-based Water Quality Index (WQI) was calculated for every observation. The study combines classical hydrochemical interpretation methods, including descriptive statistics, hierarchical correlation analysis, variance inflation factor, and Piper and Gibbs diagrams, with an explainable machine learning framework integrating SHAP-based feature selection into Random Forest, XGBoost, support vector regression, and stacking ensemble models. In addition, spatial residuals were evaluated using Moran’s I and ordinary kriging, anomalies were identified using Isolation Forest and Local Outlier Factor algorithms, and predictive uncertainty was quantified through bootstrap resampling. WQI values ranged from 79.37 to 125.48 (mean: 99.67), with all samples classified only within the “Good” (49.5%) and “Poor” (50.5%) quality categories, indicating that the aquifer is close to a critical water-quality threshold. Spatially, the highest (poorest-quality) WQI values form a coherent zone in the south-western and central parts of the plain, whereas the central-eastern wells return the lowest values; the same pattern is reproduced by all four models. XGBoost and the stacking ensemble models showed comparable predictive performance (R² = 0.911 and 0.910; RMSE = 3.29 and 3.27, respectively), while SHAP analysis identified EC as the dominant controlling factor, followed by NO₃⁻, SO₄²⁻, Ca²⁺, Mg²⁺ and Cl⁻ (mean |SHAP| = 6.86, 1.57, 1.10, 1.09, 0.85 and 0.72 WQI units, respectively). Moran’s I computed on the residual fields was −0.067 (p = 0.275) for XGBoost and −0.068 (p = 0.273) for the stacking ensemble, so ordinary kriging of these residuals produced an essentially null correction, whereas the SVR residuals remained spatially autocorrelated (I = 0.242; p = 0.001) and were meaningfully corrected by the geostatistical step. The originality of the study lies in integrating explainable machine learning, geostatistical residual analysis, anomaly detection, and bootstrap-based uncertainty assessment within a unified framework for a multi-season groundwater dataset, while also evaluating the effectiveness of spatial correction using a Moran’s I-based approach. Full article

For a semiprime $N=sp$, the normalized CRT–Bézout map assigns each unit modulo N a unique pair $(m,n)$ in the rectangle $\{1,\dots ,p-1\}\times \{1,\dots ,s-1\}$. The coordinates $mn$, $\Delta =ms+np$, and $\delta =ms-np$ satisfy ${\Delta }^2-{\delta }^2=4Nmn$ and give the geometric diagrams studied here. We describe the bounded affine slices $Am+Bn=\lambda$, including their point counts, complement symmetry, vertices, and spacings. We also write modular squaring in these coordinates: the two components evolve independently, while the nonempty fibers are orbits of a four-element Klein group. The complement symmetry of the slices is compatible with these dynamics. Finally, we determine the two admissible points with $\left|\delta \right|=1$ and prove an exact count for the points in a central strip $\left|\delta \right|<T$. These results describe the geometry attached to a known factorization; they do not give a new factorization algorithm. Full article

Cervical cancer (CC) affects women worldwide, and more than 95% of cases are caused by persistent infection with high-risk human papillomavirus (HR-HPV), such as type 16, which promotes the progression of precancerous lesions to cancer. This study aimed to identify differentially expressed proteins (DEPs) in biopsies from patients with HPV16+ low-grade squamous intraepithelial lesions (LSILs) and from patients with HPV16+ squamous cell carcinoma (SCC) compared with those from HPV-negative normal cervical tissue (NCT HPV−) controls. The samples were analyzed by high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS) using a data-independent acquisition (DIA) approach. Data processing and differential protein expression analysis were performed with the DIA-NN software (Data-Independent Acquisition Neural Networks), followed by bioinformatics analyses, including Venn diagrams, pathway enrichment, functional interactome, The Cancer Genome Atlas (TCGA)-SCC data integration, and Western blot detection. In total, 1607 DEPs associated with cell adhesion and extracellular matrix proteins were identified in LSILs, whereas 1516 DEPs associated with catalytic and transport activities were identified in SCC; the proteins overexpressed in LSILs (332) were enriched in processes such as metabolism, immune response activation, and stress and cell death responses. In contrast, proteins overexpressed in SCC (205) were associated with the cell cycle, DNA damage, drug metabolism, proteasome degradation, methylation, and immune response. Interaction analyses highlighted proteins related to early proteins 1,5,6 and 7 (E1, E5, E6, and E7). In terms of the two DEPs, S100 calcium binding protein A10 (S100A10/p11) and thymidine phosphorylase (TYMP) were detected in patients with LSIL, HSIL, and SCC at the protein level, consistent with their higher transcript levels in public datasets. Given the small, exploratory cohort, these findings are hypothesis-generating, and validation in a larger, balanced, independent cohort is required. In conclusion, this study identified DEPs associated with the progression of premalignant lesions to SCC that may represent candidate biomarkers and therapeutic targets warranting further investigation. Full article

A hyper compressor is one of the most critical pieces of equipment for synthesizing low-density polyethylene (LDPE) with a discharge pressure up to 350 MPa. Such a high discharge pressure creates significant challenges for safety and reliability. In this study, a 3D transient computational fluid dynamics (CFD) model of a hyper-compressor’s interstage pipeline was adopted to examine the characteristics of pressure pulsation inside the interstage pipeline. First, flow channels of multiple poppets in the combined valve were simplified into a single channel while keeping the flow area identical. A single-degree-of-freedom equation was employed to calculate the dynamic motion of the simplified valve. Then, the acceleration, velocity, and lift of the valve were acquired by accumulating pressure-induced forces. Finally, the entire model was solved, and the p–θ diagram inside the working chambers and the pressure pulsation inside the interstage pipeline were acquired. It was found that the isotropic indexes of compression and expansion processes were 29.1 and 3.17 for the first stage of the hyper-compressor, and 36.85 and 3.65 for the second stage, respectively. The indices were significantly higher than those of the common compressor due to the higher compressibility of ethylene at hyper-pressures. The maximal pressure pulsations around the first stage and the second stage were 17.5% and 16.22%, respectively. Strain gauges were adopted to measure the on-site pressure pulsation. The results showed that the proposed CFD model was able to predict the coupling of thermodynamic processes in the working chamber and pressure pulsation in the pipeline. The comparison between the predicted and measured frequency vs. amplitude diagrams showed that the discrepancies at lower harmonics were smaller than those at higher harmonics. The maximum discrepancy of the dominant harmonic amplitudes between the CFD prediction and the strain gauge measurement was within approximately ±13%. Full article

Runoff recharge increases during the wet season in arid inland river basins; however, solute inputs along river courses, evaporite salt dissolution, and leaching from saline sediments may still substantially modify the chemical composition of surface waters. To identify the sources of major ions, hydrochemical controlling processes, and salt-enriched river reaches during the wet season in the Cele River Basin, 107 surface water samples were collected from the mainstream of the Cele River and five major tributaries in August 2025. Field and laboratory analyses were conducted for pH, total dissolved solids (TDS), electrical conductivity (EC), dissolved oxygen (DO), and major ions, including Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl⁻, SO₄²⁻, and HCO₃⁻. Piper diagrams, Gibbs diagrams, ionic ratios, Spearman correlation analysis, and principal component analysis (PCA) were used to characterize the major-ion composition, hydrochemical facies, and controlling factors. The results show that the surface waters were generally weakly alkaline, with pH values ranging from 7.42 to 8.46. TDS and EC exhibited pronounced spatial heterogeneity, with higher salinity levels in the Buzang River, the Cele River mainstream, and the Uluk Say River, and relatively lower mineralization in the Bostan River and Nur River. SO₄²⁻ and Cl⁻ dominated the anionic composition, together accounting for 80.3% of total anions, whereas Ca²⁺ + Mg²⁺ and Na⁺ + K⁺ jointly controlled the cationic composition, accounting for 57.3% and 42.7% of total cations, respectively. The Piper diagram indicated that the Cl·SO₄–Na·Ca type was the dominant hydrochemical facies, accounting for 67.3%, suggesting a pronounced sulfate–chloride salt-enrichment signature during the wet season. Evidence from Gibbs diagrams, ionic end-member ratios, and PCA further indicates that the hydrochemical composition is primarily constrained by rock weathering and jointly influenced by sulfate and chloride salt dissolution, evaporation–concentration processes, and leaching from saline sediments. These processes reflect the coexistence of runoff dilution and salt reloading during the wet season. The Buzang River, Cele River mainstream, and Uluk Say River should be prioritized for continuous water-quality monitoring and salinity-risk early warning, while TDS, EC, Na⁺, Cl⁻, and SO₄²⁻ can serve as core indicators for diagnosing wet-season water–salt processes and tracking water-quality baselines. This study identifies the key salt-enriched reaches, major ion sources, and hydrochemical control mechanisms of surface waters in the Cele River Basin during the wet season, providing a scientific basis for water-quality protection, oasis agricultural water regulation, and sustainable water–salt management in arid inland river basins. Full article

Nickel-based alloys are promising structural materials for molten salt systems; however, secondary-phase formation during long-term high-temperature exposure may introduce local corrosion susceptibility because secondary phases have compositions and redox stabilities distinct from the matrix. Here, we combine CALculation of PHAse Diagrams (CALPHAD)-based phase prediction with redox thermodynamic analysis to assess phase-specific corrosion susceptibility in Inconel 625 (IN625) and SA508 low-alloy steel under molten chloride conditions. Equilibrium phase constitutions at 1000 K were predicted using Thermo-Calc, and redox equilibrium potentials were calculated for representative-phase dissolution reactions of major metallic elements in each phase. The dominant α and γ phases in SA508 exhibited similar Fe-ionization potentials of −1.728 and −1.768 V vs. Cl2/Cl⁻, respectively. In IN625, the γ matrix exhibited a Cr-ionization potential of −1.964 V vs. Cl2/Cl⁻, whereas the P phase showed the most negative potential of −2.132 V vs. Cl2/Cl⁻, 0.168 V more negative than the matrix, identifying the P phase as the primary local thermodynamic weak point. These results show that phase-specific metal-ionization susceptibility cannot be inferred solely from nominal alloy composition or matrix behavior. The proposed framework provides a thermodynamic screening approach for identifying susceptible secondary phases in multicomponent alloys under molten-salt conditions. Full article

The CaO-Al₂O₃-Fe₂O₃ system is widely encountered in cement production, iron ore sintering, metallurgical slags, and refractory materials. A thermodynamic assessment of the CaO-Fe₂O₃ and CaO-Al₂O₃-Fe₂O₃ systems was carried out in this study based on the CALculation of PHAse Diagrams (CALPHAD) method. The liquid was modeled using the ionic two-sublattice model, expressed as (Ca⁺², Al⁺³, Fe⁺²) _P (O⁻², AlO_1.5, FeO_1.5, Va, O) _Q. The Compound Energy Formalism (CEF) was adopted to describe compounds and solid solutions. A self-consistent thermodynamic assessment of the CaO-Fe₂O₃ and CaO-Al₂O₃-Fe₂O₃ systems was achieved, enabling accurate reproduction of phase equilibrium and thermodynamic data. The obtained thermodynamic description provides a useful foundation for the design, optimization, and processing of refractory materials. Full article

Groundwater is a principal irrigation water source worldwide; however, its quality is increasingly diminished by rapid urbanization, improper agricultural practices, and accelerating industrial activities. Groundwater management is especially important in areas where soil salinization and erosion are more probable, such as arid and semi-arid zones. In view of this, the Armavir region of the Republic of Armenia was selected as the study area, being an intensively cultivated agricultural zone. The objective of this study was to assess and map the quality of groundwater for irrigation using advanced methods, taking into account both climatic conditions and anthropogenic influences. A total of 72 groundwater samples were collected during the irrigation season from 41 unconfined and 31 confined aquifer wells. Key hydrochemical parameters (pH, EC, TDS, Cl⁻, HCO₃⁻, CO₃²⁻, Na⁺, K⁺, Ca²⁺ and Mg²⁺), irrigation indices (SAR, Na%, MH, RSC and PI), and graphical methods (Gibbs, USSL and Wilcox diagrams) were applied to assess groundwater quality. An integrated assessment was performed using the Irrigation Water Quality Index (IWQI), and spatial distribution was evaluated through geostatistical analysis and GIS mapping. Although certain individual hydrochemical parameters indicated limitations for irrigation in localized areas, particularly within the unconfined aquifer, the integrated IWQI assessment revealed that groundwater predominantly falls within the good to excellent categories across the study area, with more favorable conditions observed in the confined aquifer. These findings constitute an essential prerequisite for counteracting soil salinization and promoting sustainable agricultural development. Full article

To enhance the thermal performance of a Stirling air conditioner, this study applies Schmidt-based dimensionless analysis to systematically investigate the influence of key structural parameters on its cooling and heating characteristics. A dimensionless thermodynamic framework is established under the ideal isothermal assumptions of the Schmidt model to investigate the effects of temperature ratio, swept volume ratio, dead volume ratio, and phase angle on a Stirling system. The results indicate that increasing the temperature ratio enhances the thermodynamic driving potential; however, excessive temperature ratios introduce stronger irreversibilities, resulting in saturation or even degradation of effective cooling performance. The dimensionless cooling capacity increases significantly with phase angle, rising from 0.25 at α = 50° to 0.65 at α = 120°, while heating capacity peaks at α ≈ 71.6° with ε_e = 0.18. The p–v diagram analysis reveals optimal work output at α ≈ 75°, where the cycle area reaches 20.8, representing a 44.4% increase from the value at 15°. Performance saturation occurs at τ > 3 and κ > 6 for cooling and beyond κ > 4 for heating. Within the assumptions of the ideal Schmidt model, the results suggest that medium-to-high temperature ratios (τ ≈ 3–4) combined with moderate swept volume ratios (κ ≈ 6–8) provide the optimal balance between thermodynamic performance and structural compactness; these parameter combinations should be regarded as theoretical design references for ideal operating conditions rather than directly applicable engineering optimization guidelines. Full article

Rare earth elements (REEs), including yttrium, scandium and lanthanides, are essential for advanced technologies, particularly in electronics, defense and renewable energy systems. The main primary REE sources include bastnaesite, monazite and ion-adsorption clays, while secondary sources comprise permanent magnets, phosphors, LEDs and other technological waste. The growing demand, together with China’s dominant position in the global REE market and export restrictions, has increased concerns regarding the security of the REE supply in the European Union. This study evaluates selected primary REE resources and their processing possibilities using hydrometallurgical methods, with an emphasis on the thermodynamic aspects of REE leaching. The research focuses on the construction and analysis of Eh–pH diagrams generated using HSC Chemistry software to predict the stability of dissolved and solid species under different leaching conditions. These diagrams help identify suitable conditions for selective REE extraction and improve the understanding of the mechanisms governing hydrometallurgical processing. The results provide insight into the stability regions of REE species and indicate favorable conditions for selective leaching and recovery. Full article

This study presents the design and modeling of a first-of-its-kind experimental prototype integrating a high-temperature air-based Concentrated Solar Power (CSP) receiver with a diabatic Compressed Air Energy Storage (CAES) system. The prototype architecture and operating modes are defined, and a detailed thermal model of an Open Volumetric Air Receiver (OVAR) is developed and optimized, with emphasis on passive mass flow regulation under non-uniform solar flux. At nominal conditions (800 °C), the receiver achieves a predicted thermal efficiency of 81.6%. Transient simulations assess off-design dynamic behavior under realistic conditions, showing sensitivity to solar fluctuations and need for heliostat aiming strategies to reduce thermal non-uniformities and ensure stable outlet temperatures. For the CAES subsystem, a techno-economic analysis identifies high-pressure (300 bar) commercial gas cylinders as the most cost-effective aboveground storage solution, while discharge simulations yield a required storage volume of 4.8 m³. Finally, the complete piping and instrumentation diagram (P&ID) of the integrated system is presented, defining the experimental configuration. Overall, this work establishes the design basis for the future experimental demonstration of hybrid CAES-CSP operation for dispatchable renewable power generation and supports subsequent control development and scale-up analyses. Full article

Industrial digitalization increasingly requires automated tools capable of extracting structured knowledge from complex engineering documentation, such as Piping and Instrumentation Diagrams (P&IDs). This work proposes an integrated framework that combines object detection and Large Language Models (LLMs) for automated Knowledge Graph (KG) generation. The approach enables the transformation of unstructured P&ID schematics into machine-interpretable representations, supporting data-driven analysis and decision-making. A modular pipeline is developed, including image pre-processing, symbol detection via a YOLO-based model, and identification of semantic relations between schematic elements using LLMs. The proposal also includes the definition of a reference ontology, which is exploited for the construction of the KG, and a diagram dataset designed to test the performance of the object detection model. The KG generation procedure achieves strong results in terms of image reconstruction across a wide set of industrial schematics, while also preserving the semantic integrity and completeness of the original diagrams. The proposed method represents a significant step toward the digitalization of industrial knowledge, bridging traditional engineering documentation and semantic-based technologies. Full article

Building Information Modelling (BIM) has digitized construction, yet automated cost estimation still suffers from fragmented data and deterministic forecasts that ignore uncertainty. To address this gap, this study introduces a novel framework integrating agentic artificial intelligence (AI) with large language models (LLMs) to enable probabilistic cost estimation from disparate BIM data. The system employs four specialized collaborative agents operating via a shared memory module centered on an LLM with natural language understanding, code generation, and chain-of-thought reasoning. A prototype using GPT-4 Turbo, AutoGen, and Monte Carlo simulation was tested on three real-world structures. Compared to three baselines, the framework reduced processing time (4.2 vs. 18.5–68.0 min), manual interventions (0.8 vs. 9–14), and improved entity resolution accuracy (86.5% vs. 46–62%) with well-calibrated probabilistic forecasts, achieving 86.0% empirical coverage for nominal 90% prediction intervals (Prediction Interval Coverage Probability [PICP] = 86.0%, Prediction Interval Width [PIW] = 0.28; p < 0.01). Qualitative analysis confirmed effective semantic conflict resolution and actionable risk visualization via tornado diagrams. The framework tackles long-standing BIM estimation challenges by delivering probabilistic, transparent outputs. Future work includes digital twin integration, open-source LLM deployment, and during-construction forecasting. Full article

Shallow groundwater systems of rural municipalities are highly vulnerable to long-term contamination from former on-site sanitation systems, while the hydrochemical response of the aquifer after sewerage network development may be delayed by several factors. In the present study, a total of 147 shallow groundwater samples collected during the summer sampling campaigns of 2018, 2019, 2023, and 2024 were analyzed for general water-quality parameters including pH, EC, NH₄⁺, NO₂⁻, NO₃⁻, PO₄⁻, Cl⁻, SO₄²⁻, microelements, and potentially toxic elements, including As, Pb, Cd, Ni, Cu, Zn, Fe, and Mn. The dataset was evaluated using descriptive statistics, Piper, Wilcox, and Gibbs diagrams, hierarchical cluster analysis, principal component analysis, and GIS-based spatial interpolation. The results indicate that, more than ten years after sewerage network development (2014), shallow groundwater in the study area still shows considerable contamination, primarily characterized by elevated mean concentrations of ammonium (0.836 mg/L), nitrate (177.43 mg/L), and chloride (313.26 mg/L), accompanied by high electrical conductivity (3115 µS/cm) and sodium enrichment (378.12 mg/L). Spatial and boxplot analyses of SAR further indicated increasing sodium-related heterogeneity after 2018, with higher local SAR values in 2023–2024. Hydrochemical diagrams revealed a shift towards Ca-Cl type to Na–Cl types, while multivariate analyses confirmed that salinity enrichment, nitrate contamination, water–rock interaction and redox-sensitive trace element mobilization act as overlapping but partly separable controls. The nitrate–chloride source plot indicated mixed contamination origins, dominated by residual sewage influence and manure-related inputs, with diffuse agricultural nitrogen leaching. Arsenic was used as a supporting indicator of mixing with wastewater; however, As was no longer detectable in most of the investigated wells, suggesting a marked reduction in the former wastewater leakage. These results support the slow attenuation of contamination in the shallow groundwater system affected by former wastewater infiltration and highlight the need for continuous monitoring. Full article