Search Results (4,903)

This study presents the application of Mycelial_Net, a biologically inspired deep learning architecture, to the analysis and classification of mineral images in thin section under optical microscopy. The model, inspired by the adaptive connectivity of fungal mycelium networks, was trained on a test mineral image database to extract structural features and to classify various minerals. The performance of Mycelial_Net was evaluated in terms of accuracy, robustness, and adaptability, and compared against conventional convolutional neural networks. The results demonstrate that Mycelial_Net, properly integrated with Residual Networks (ResNets), offers superior analysis capabilities, interpretability, and resilience to noise and artifacts in petrographic images. This approach holds promise for advancing automated mineral identification and geological analysis through adaptive AI systems. Full article

Background/Objectives: The optimal healing process following root canal treatment involves biological apical sealing through new cementum formation. Bone morphogenetic protein 7 (BMP-7) has recently gained attention as a potential regulator of cementoblast differentiation and periodontal regeneration. However, its effects on periodontal ligament fibroblasts (PDLFs) and the underlying mechanisms remain incompletely understood. This study aimed to investigate whether BMP-7 induces cementoblast-like differentiation of PDLFs both in vivo and in vitro via the BMP-SMAD signaling pathway. Methods: In a rat pulpectomy model, root canals were treated with or without BMP-7 and examined histologically and immunohistochemically for F-spondin (Spon1) expression. In vitro, human PDLFs were stimulated with BMP-7, and analyses of mineralization, cementoblast marker expression, alkaline phosphatase activity, and SMAD-1/5/9 phosphorylation were conducted. Results: Immunohistochemical analysis revealed that Spon1-positive regions increased around the apical area following BMP-7 treatment, suggesting the induction of cementoblast-like differentiation. In vitro, BMP-7 enhanced the expression of cementoblast-associated genes and mineral deposition while activating SMAD-1/5/9 signaling. Phosphorylation was suppressed by the BMP receptor inhibitor LDN-193189, indicating canonical BMP-SMAD pathway involvement. Conclusions: Although the specific concentration range of maximal activity remains to be determined, the findings collectively suggest that BMP-7 can promote cementoblast-like differentiation of PDLFs and may contribute to apical healing through cementum-related mechanisms. These results provide mechanistic and biological insights that support the potential of BMP-7 as a modulator for biologically favorable periapical tissue regeneration following root canal therapy. Full article

This study investigates the adsorption behavior of natural sepiolite for the removal of cadmium (Cd²⁺), copper (Cu²⁺), and nickel (Ni²⁺) ions from aqueous solutions under batch conditions. The sepiolite was extensively characterized prior to adsorption experiments. Mineralogical analysis confirmed the presence of crystalline sepiolite, while DTG-TGA revealed thermal stability with distinct weight loss linked to surface and structural water. BET analysis indicated a high surface area of 194 m²/g and a mesoporous structure favorable for adsorption. Batch experiments evaluated the effects of contact time, pH, adsorbent dosage, and initial metal concentration. Adsorption was highly pH-dependent, with maximum removal near-neutral pH values. Higher adsorbent dosages reduced in a lower adsorption capacity per unit mass, primarily because the fixed amount of solute was distributed over a larger number of available sites, leading to unsaturation of the adsorbent surface and possible particle agglomeration. Isotherm modeling revealed that the Langmuir model provided the best fit, indicating monolayer adsorption with maximum adsorption capacities of 15.95 mg/g for Cd(II), 37.31 mg/g for Cu(II), and 17.83 mg/g for Ni(II). Langmuir constants indicated favorable interactions. Kinetics showed rapid adsorption within the first hour, reaching equilibrium at 240 min through surface adsorption and intraparticle diffusion. Cu(II) exhibited the fastest uptake, while Ni(II) adsorbed more slowly, suggesting differences in diffusion rates among the metal ions. Desorption using 0.1 N HCl achieved over 80% efficiency for all metals, confirming sepiolite reusability. Overall, raw sepiolite is an effective, low-cost adsorbent for removing potentially toxic elements from water. Full article

Laser-induced breakdown spectroscopy (LIBS) is a promising elemental analysis technique that has rapidly evolved in numerous fields, including biomedical research and medical sciences, over the last two decades. In combination with other methods, it has the potential to examine complex biological structures and their species distributions. The present work first develops the basic understanding of LIBS and then reviews its evolution in oncological diagnosis and calcified tissue analysis from medical perspectives over the last 11 years. LIBS can potentially improve early cancer detection and monitor treatment outcomes, ultimately enhancing patient care and diagnosis. It has effectively differentiated between malignant and normal tissues and also classifies cancer stages and types based on disease severity. Its applications for categorising and identifying calcified tissues are attractive for inspecting minerals, while soft tissue is more challenging, given the potential for significant matrix effects. This review article deals with the following aspects of LIBS and its application: (i) the fundamentals of this analytical measurement method, (ii) the matrix effect and its influence on the LIBS analyses of various biological tissues, (iii) the role of signal enhancement methodologies and artificial intelligence models to advance the method for analyses of biological sample materials, and (iv) applications of LIBS in cancer and calcified tissues investigations. This article also addresses challenges and opportunities encountered in these applications and discusses prospects, providing a comprehensive overview of the current state and potential advancement in LIBS technology. Full article

Coagulation–flocculation, historically reliant on simple inorganic salts, has evolved into a technically sophisticated process that is central to the removal of turbidity, suspended solids, organic matter, and an expanding array of micropollutants from complex wastewaters. This review synthesizes six decades of research, charting the transition from classical aluminum and iron salts to high-performance polymeric, biosourced, and hybrid coagulants, and examines their comparative efficiency across multiple performance indicators—turbidity removal (>95%), COD/BOD reduction (up to 90%), and heavy metal abatement (>90%). Emphasis is placed on recent innovations, including magnetic composites, bio–mineral hybrids, and functionalized nanostructures, which integrate multiple mechanisms—charge neutralization, sweep flocculation, polymer bridging, and targeted adsorption—within a single formulation. Beyond performance, the review highlights persistent scientific gaps: incomplete understanding of molecular-scale interactions between coagulants and emerging contaminants such as microplastics, per- and polyfluoroalkyl substances (PFAS), and engineered nanoparticles; limited real-time analysis of flocculation kinetics and floc structural evolution; and the absence of predictive, mechanistically grounded models linking influent chemistry, coagulant properties, and operational parameters. Addressing these knowledge gaps is essential for transitioning from empirical dosing strategies to fully optimized, data-driven control. The integration of advanced coagulation into modular treatment trains, coupled with IoT-enabled sensors, zeta potential monitoring, and AI-based control algorithms, offers the potential to create “Coagulation 4.0” systems—adaptive, efficient, and embedded within circular economy frameworks. In this paradigm, treatment objectives extend beyond regulatory compliance to include resource recovery from coagulation sludge (nutrients, rare metals, construction materials) and substantial reductions in chemical and energy footprints. By uniting advances in material science, process engineering, and real-time control, coagulation–flocculation can retain its central role in water treatment while redefining its contribution to sustainability. In the systems envisioned here, every floc becomes both a vehicle for contaminant removal and a functional carrier in the broader water–energy–resource nexus. Full article

Soil organic carbon (SOC) is a critical component of soil health, influencing soil structure, soil water retention capacity, and nutrient cycling while playing a key role in the global carbon cycle. Accurate SOC estimation over croplands is essential for sustainable land management and climate change mitigation. This study explores a novel approach to SOC estimation using multi-frequency synthetic aperture radar (SAR) data, specifically Sentinel-1 and ALOS-2/PALSAR-2 imagery, combined with advanced machine learning techniques for cropland SOC estimation. Diverse agricultural practices, with major crop types such as rice (Oryza sativa), finger millet (Eleusine coracana), Niger (Guizotia abyssinica), maize (Zea mays), and vegetable cultivation, characterize the study region. By integrating C-band (Sentinel-1) and L-band (ALOS-2/PALSAR-2) SAR data with key polarimetric features such as the C2 matrix, entropy, and degree of polarization, this study enhances SOC estimation. These parameters help distinguish variations in soil moisture, texture, and mineral composition, reducing their confounding effects on SOC estimation. An ensemble model incorporating Random Forest (RF) and neural networks (NNs) was developed to capture the complex relationships between SAR data and SOC. The NN component effectively models complex non-linear relationships, while the RF model helps prevent overfitting. The proposed model achieved a correlation coefficient (r) of 0.64 and a root mean square error (RMSE) of 0.18, demonstrating its predictive capability. In summary, our results offer an efficient approach for enhanced SOC mapping in diverse agricultural landscapes, with ongoing work targeting challenges in data availability to facilitate large-scale SOC mapping. Full article

Osteoporosis is a progressive bone disorder characterized by decreased bone mineral density and structural deterioration, leading to increased fracture risk. Conventional treatments, although effective, are limited by adverse effects and low long-term adherence. In recent years, polyphenols, plant-derived bioactive compounds, have emerged as promising candidates for bone health promotion due to their antioxidant, anti-inflammatory, and osteo-regulatory properties. This review synthesizes the current preclinical and clinical evidence on the potential of polyphenols, including quercetin, resveratrol, curcumin, isoflavones, and epigallocatechin gallate, to modulate bone metabolism and prevent or mitigate osteoporosis. Mechanistically, polyphenols enhance osteoblastogenesis, inhibit osteoclast differentiation, regulate the RANKL/OPG axis, and activate key osteogenic pathways such as Wnt/β-catenin and MAPKs. Additionally, their estrogen-like activity and ability to modulate gut microbiota offer further therapeutic potential. Preclinical models consistently demonstrate improvements in bone mass, architecture, and turnover markers, while clinical trials, although limited, support their role in preserving bone density, particularly in postmenopausal women. Despite promising outcomes, variability in bioavailability, dosage, and study design limits current translational application. Further large-scale clinical studies and standardized formulations are needed. Polyphenols represent a compelling adjunct or alternative approach in the integrated management of osteoporosis. Full article

Comprehensive Meta-Analysis (CMA) software, using data from 64 global studies (288 dietary assessments, 194,356 broilers) evaluated the effects of substituting inorganic trace minerals (ITM) with proteinate trace minerals (PTM) in broiler diets at various inclusion levels. Replacing ITM with PTM at equivalent (100%) or reduced (11–80%) levels improved performance metrics, showing reduced total feed intake (FI) (−6 g/bird), lower average daily feed intake (ADFI) (−0.43 g/bird), higher average daily gain (ADG) (+0.36g), greater body weight gain (BWG) (+4.29 g/bird), higher final body weight (BW) (+7.50 g/bird), improved feed conversion ratio (FCR) (−1.26%), and lower mortality (−10.95%), all significant (p < 0.05). Median mineral inclusion reductions of 40% Cu, 59.82% Fe, 41.41% Mn, and 34.67% Zn had no adverse effects, instead enhancing outcomes. Across 17 studies (25,144 broilers, 85 dietary assessments), mineral excretion decreased significantly with PTM versus ITM by 16% Cu, 14% Fe, 21% Mn, and 15% Zn (p < 0.001). When PTM replaced ITM at 50–80% inclusion, further benefits were observed, including lower total FI (−7 g/bird), lower ADFI (−1.07 g/bird), higher ADG (+1.67), higher BWG (+2.65 g/bird), lower FCR (−4.50%) and lower mortality (−11.09%) with mineral inclusion reductions of 17% Cu, 42.16% Fe, 42.89% Mn, and 50% Zn. Meta-regression identified significant influences (p < 0.05) from study variables such as strain, study duration, and region. Life cycle assessment modelling demonstrated PTM inclusion lowered gross carbon emissions by 3.5% and lower emission intensities per unit live weight of both feed use and overall lifecycle by 4.5% and 4.1%, respectively on diets of high and low soybean meal inclusion. Overall, replacing ITM with PTM in broiler diets can promote production performance of broilers and lower mineral excretion levels while contributing to a lower CFP. Full article

The Global Cement and Concrete Association (GCCA) estimated that by 2050, 36% industry-wide sustainable value will be created, which includes sequestering CO₂ into the cement and concrete industry to produce commercially feasible high-value products. Direct utilization of CO₂ in the cement and concrete industry, which utilizes natural and sustainable materials, is gaining momentum. Naturally occurring mixtures of hydro magnesite and huntite are important industrial minerals which, upon endothermic decomposition over a specific temperature range, will release water and CO₂. This unique chemistry has led to such mixtures being successfully utilized as fire retardants, replacing aluminum hydroxide or Alumina Tri-Hydrate (ATH). Despite the developed marketplace for magnesium-based fire-retardant products, there is little mention of CO₂ mineral carbonation methods, which attempt to recover and convert magnesium from natural seawater or industrial waste into oxides or carbonates as part of the carbon sequestration initiative. The hypothesis to be proven in this work states that if the process of seawater mineral carbonation is prematurely quenched, Mg²⁺ ionic species in seawater adsorbed on the calcite lattice formation will be trapped and therefore recovered in various oxidized forms, such as magnesium oxides, magnesium hydro magnesite, and magnesium carbonate precipitates. A novel method to recover magnesium Mg²⁺ ions from seawater was successfully explored and documented; as such, from an initial concentration of 1250 ppm Mg²⁺ in raw seawater, the average concentration of spent Mg²⁺ ions after the reaction was as low as 20 ppm. A very efficient near-total recovery of Mg²⁺ from the seawater into the solid precipitates was recorded. Subsequently, the process for continuous seawater mineral carbonation for the production of magnesium/brucite/huntite products was successfully proven and optimized to operate with a 30 s reaction time, a dynamic feedstock concentration, [CaO] at 1 gpl in seawater and a room temperature reaction temperature (30 °C), where the average yield of the fire-retardant magnesium-based compounds was 26% of the synthesized precipitates. Approximately 5000 g of the hydro magnesite materials was molded into a fire-retardant brick or concrete wall, which was subjected to an accredited fire performance and durability testing procedure BS476-22:1987. There were encouraging results from the fire resistance testing, where the fire-retardant material passed BS476-22:1987, with performance criteria such as physical integrity failure, the maximum allowable face temperature, and a minimum duration before failure, which was up to 104 min, evaluated. Full article

Hydrogen-fuelled internal combustion engines (H₂ICEs) generate water vapour that can condense in the sump and form water-in-oil emulsions, altering lubricant performance. This study measures the viscosity–temperature behaviour, copper corrosivity, and boundary tribology of three commercial oils—synthetic (5W-40), semi-synthetic (10W-40), and mineral (15W-40)—emulsified with 5–40 wt% water and tested in both freshly emulsified and aged (3 months; clarified oil layer) states. In fresh emulsions, viscosity rose with water fraction. At 25 ^∘C and 40 wt%, the increase was 44.4% (5W-40), 78.7% (10W-40), and 81.2% (15W-40) versus the neat oils. Ageing drove viscosities toward the baseline, with the strongest effect observed for 15W-40, indicating destabilisation. The Vogel–Fulcher–Tammann (VFT) model was fitted to all datasets (RMSE < 5%). A VFT-based screening map uses two ratios at the friction test temperature: $R_{\eta }=\eta /{\eta }_{\mathrm{neat}}$ (relative film-forming tendency) and $R_s=S/S_{\mathrm{neat}}$ with $S=B/{(T-T_0)}^2$ (thermal-thinning sensitivity). A Preferred regime, $R_{\eta }\ge 1.25$ and $R_s\le 0.95$, is correlated with lower friction, smaller wear scars, and copper rating 1a, with most aged conditions migrated out of this regime. Under boundary conditions, 5–10 wt% water generally reduced friction, whereas higher fractions and ageing increased friction and wear. Synthetic oil (5W-40) showed the most robust response. Full article

A large-scale sandstone-type uranium deposit, recently discovered within the petroleum field of the Jingchuan area on the southwestern margin of the Ordos Basin, exemplifies a classic case of uranium exploration success achieved through the analysis of petroleum geological data including borehole logs. By synthesizing borehole radioactive logs and seismic surveys, we delineated target sandstone geometry, connectivity, and ore-controlling structures (e.g., paleochannels, redox interfaces). This study establishes a novel methodology for sandstone-type uranium exploration in petroliferous basins, unifying geophysical and geochemical datasets to define drill-validated targets. We integrated detailed core logging, petrography, and assay data to delineate the deposit’s geology. This included the host strata composition, ore-body morphology, mineralogy, and alteration assemblages. Our analysis identified the critical controls on mineralization: sandbody architecture, structural framework, and redox zonation. Based on these constraints, we constructed a genetic metallogenic model. Furthermore, we elucidated the mechanistic role of hydrocarbons in uranium mineralization and demonstrated the strategic potential of repurposing legacy oilfield data for synergistic uranium targeting. The Jingchuan uranium deposit provides both an exploration blueprint and theoretical foundations for uranium targeting in analogous sedimentary basins. Full article

Saline aquaculture tailwater challenges conventional constructed wetlands (CWs) with their limited phosphorus (P) removal capacity. To address this, iron-carbon constructed wetlands (IC-CWs) were developed and operated under four salinity gradients (0, 10, 20, and 30) for 155 days to investigate the effects of salinity on P removal and associated microbial mechanisms. The results showed that salinity critically influenced long-term P removal, with the system at salinity 20 (S20) achieving the highest total phosphorus (TP) removal efficiency (78.80 ± 6.01%). Enhanced P removal was primarily attributed to the upregulation of phosphate transport genes (pstS, 14.25-fold increase) and elevated activity of key enzymes (AKP and ACP) in phosphorus-accumulating organisms (PAOs). However, high salinity (30) suppressed microbial metabolic functions. Metagenomic analysis revealed that salinity stress reshaped microbial community structure, with Bacteroidota abundance increasing 10-fold in S20 compared to S0 (control). This phylum harbored the phnE gene, significantly promoting organic phosphorus mineralization. Additionally, iron release increased with rising salinity, and the relative abundance of the phnE gene in Bacteroidota was highest in the S20 group, indicating a close association between iron release and PAOs as well as organic P mineralization genes. The quadratic polynomial model revealed that iron release under high salinity followed nonlinear kinetics, with passivation layer rupture promoting iron-phosphorus precipitate desorption in later stages. These findings provide a theoretical basis for optimizing salinity parameters to enhance chemical-biological P removal synergy, offering a promising strategy for saline aquaculture wastewater treatment. Full article

In this work, three hydraulic fluids—a paraffinic mineral hydraulic oil (H46) and two biodegradable oils (HETG46—hydraulic oil based on natural esters and HF-E46—hydraulic oil based on synthetic esters derived from fatty acids extracted from vegetable oils)—were studied in both fresh and thermally degraded states. The study of these oils was performed both from a rheological and spectroscopic point of view using Fourier transform infrared spectroscopy (FTIR). The thermal degradation process consisted of repeated heating and cooling cycles at four different temperatures for 15 min performed eight times. The rheological characterization was initially performed for the fresh oils, and the results obtained were compared with those of the thermally degraded samples. For the rheological characterization, two rheological models (the Newtonian model and the power law model) were used, following which the rheological parameters were determined. At the same time, this work highlights how thermal degradation influences the rheological behavior and chemical structure of hydraulic fluids. The results obtained showed that the Newtonian model best describes the rheological behavior of the analyzed fluids. From a chemical point of view, FTIR analysis did not reveal significant changes between fresh fluids and those subjected to thermal degradation. Full article

Effect-based toxicity assessments are crucial for evaluating the risks of disinfection byproducts (DBPs), particularly unknown species, generated during drinking water chlorination. However, the accuracy of this approach is highly dependent on unbiased sample extraction. Conventional methods often employ single, low-pH extraction, which may fail to recover pH-sensitive amphoteric DBPs derived from amphoteric precursors (e.g., nitrogenous compounds). This study investigated how extraction pH affects the measured biotoxicity of DBPs formed from three model precursors: biopterin (Bip), cytosine (Cyt), and tryptophan (Trp). Under excess chlorine conditions, all three precursors degraded rapidly. The formation of aliphatic DBPs followed the order Trp > Cyt > Bip, and the maximum toxicity of the non-volatile extracts, assessed via a Vibrio fischeri bioassay, followed the reverse order: Bip > Trp > Cyt. This toxicity profile was significantly influenced by extraction pH, with maximum toxicity observed for Bip at around pH 4.0, under weakly acidic conditions for Trp, and under neutral to alkaline conditions for Cyt. For all precursors, the total organic carbon concentration remained constant throughout chlorination, indicating negligible mineralization and the predominant formation of non-aliphatic, likely heteroaromatic, products. These findings demonstrate that conventional extractions at a single low pH can lead to the incomplete recovery of toxic DBPs from amphoteric precursors. Therefore, pH-optimized extraction protocols are necessary for a more accurate risk assessment of chlorinated drinking water. Full article

This study presents a statistical modelling and optimization of an argon-activated electrohydraulic plasma discharge (EHPD) process for the degradation and mineralization of p-nitrophenol (p-NP) in water. The EHPD reactor design incorporated dual dielectric plates to initiate plasma discharge through a central orifice. A fractional factorial design (FFD) was first employed to screen four operating variables, including argon flow rate, pH, applied power, and persulfate dosage, on the p-NP degradation efficiency and energy yield, revealing argon flow rate and applied power as two identified, significant process factors. These were then further optimized using a central composite design (CCD) and response surface methodology (RSM), with the optimal operating condition found to be 2.73 L/min and 128.6 W for argon flow rate and applied power, respectively. Under the optimal operating conditions, 10 min treatment of 50 mg/L p-NP achieved a degradation efficiency of 94.2% and 75.8% total organic carbon (TOC) removal, along with a first-order reaction rate constant of 0.296 min⁻¹ and an energy efficiency of 0.22 g/kWh. The reaction mechanism for p-NP degradation by EHPD was proposed and confirmed with optical emission spectroscopy and radical scavengers. The optimized EHPD process proved both effective and energy-efficient in treating p-nitrophenol, highlighting its potential as a scalable and sustainable plasma-based technology for eliminating persistent organic pollutants and promoting greener water treatment practices. Full article