The study is handling the application of geopolymer , as one of the eco-friendly green binder materials. The experimental study provided composites of geopolymer , as an alternative restoration mortar to traditional mortars and employed them according to the needs of restoration operations (blocks, mortars, adhesives, etc.). The study presents a composite of an inorganic geopolymer. Examinations and tests were also carried out on stone, mortar, the components of the proposed geopolymer mixtures and the prepared samples.

The components of the geopolymer mixtures were selected from two geopolymer sources, metakaolin or kaolin as a natural source, fly ash as a secondary industrial product, limestone powder, natural hydraulic lime (NHL-5), sand, distilled water and sodium hydroxide (NaOH) was used as an activating agent.

Mixtures were prepared in varying proportions with three molarities (6,4,2 mol) and composites were also applied to experimental models of stone samples and clay mortars to choose the best geopolymer composites for their application in the restoration of mural paintings at Saqqara necropolis in Egypt.

The results for the selected geopolymer mixtures showed densities ranging from 2.0 to 2.17 g/cm³, porosity ranging from 6.98% to 18.99%, and compressive strength ranging from 31.91 to 53.81 MPa, which is approximately 2.3 times more than the compressive strength of wall painting support

Water pollution caused by heavy metals such as zinc (Zn(II)), copper (Cu(II)), and cadmium (Cd(II)) poses significant environmental and health risks due to their persistence and toxicity. This study investigates the synthesis and characterization of novel conductive polymer (polypyrrole and polyaniline) montmorillonite nanocomposites (PPy@Mont and PAni@Mont) as efficient adsorbents for heavy metal removal from aqueous solutions. The composites were prepared via intercalation of the polymers into sodium-exchanged montmorillonite using in situ polymerization, yielding materials with enhanced adsorption properties. Comprehensive characterization was performed using XRD, FTIR, TGA, SEM, and EDX spectroscopic and microscopic techniques to confirm successful polymer incorporation and evaluate structural and thermal stability. Batch adsorption experiments assessed the effects of pH, contact time, adsorbent dosage, initial metal concentration, and temperature on the adsorption performance. Both composites exhibited optimal adsorption at pH 7.5 and equilibrium at 110 minutes. PPy@Mont demonstrated higher adsorption capacities for Zn(II) and Cu(II), while PAni@Mont showed superior performance for Cd(II). Adsorption isotherms and kinetic studies revealed that the process aligns with Langmuir and pseudo-second-order models, indicating chemisorption as the dominant mechanism. These findings highlight the potential of PPy@Mont and PAni@Mont as cost-effective, efficient, and reusable adsorbents for heavy metal remediation.

Introduction: Salvia is the largest genus within the Lamiaceae family, comprising over 1,000 species of considerable importance to the pharmaceutical, food, and cosmetic industries. Salvia nemorosa L. (S. nemorosa) is a less explored representative of this genus, associated with antioxidant, analgesic, antimicrobial, antifungal, antidiabetic, and acetylcholinesterase inhibitory activities. This study aimed to evaluate the phytochemical profiles of essential oils (EOs) obtained from four wild populations of S. nemorosa L. collected across different regions of Bulgaria. Methods: The phytochemical profiles of the four samples were analyzed using gas chromatography-mass spectrometry (GC–MS). In addition, histochemical analysis of lipid accumulation was carried out with Sudan III staining, and sections were examined under a light microscope equipped with a digital camera and image processing software. Results: GC–MS analyses revealed the presence of sesquiterpene hydrocarbons, monoterpene hydrocarbons, oxygenated sesquiterpenes, and oxygenated monoterpenes. The predominant compounds were germacrene D (17.64–41.34%), β-caryophyllene (9.50–22.38%), and caryophyllene oxide (4.66–7.35%), with other notable constituents including sabinene (6.88–21.89%), bicyclogermacrene (7.67%), and phytol (5.21%). Based on the high content of these compounds, the EOs may exhibit considerable antioxidant, antimicrobial, and anti-inflammatory activities. Histochemical analysis confirmed the presence of lipid structures, as indicated by orange-stained droplets. These findings provide valuable insights into the phytochemistry of S. nemorosa L., highlighting its promise for future pharmacological and industrial applications.

Manila City experiences recurrent flooding driven by its low-lying topography, high population density, and rapid urbanization. Traditional hydrodynamic models, while accurate, are computationally expensive and unsuitable for rapid scenario evaluation. This study proposes a structured, scenario-based flood susceptibility mapping framework using supervised machine learning trained on synthetic hydrodynamic simulations to address these limitations. Synthetic rainfall hyetographs each representing rainfall intensities at 5-minute intervals over a 2-hour duration were used to simulate flood events through two-dimensional unsteady flow modeling in HEC-RAS. The resulting maximum flood extent maps serve as ground truth data for model training. Input features consist of digital elevation model (DEM), soil type, land use, and the rainfall hyetograph vector, all preprocessed into spatially aligned raster datasets. Machine learning classifiers including Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) were trained to identify flooded areas at the pixel level and feature vectors were constructed by combining spatial characteristics with rainfall inputs. The trained models accept new input conditions comprising DEM, soil type, land use, and a defined rainfall hyetograph and produce a corresponding maximum flood susceptibility map. This capability enables flood susceptibility predictions for a wide range of hypothetical rainfall events without the need to rerun simulations wherein resulting maps can inform land-use planning, infrastructure design, evacuation planning, and disaster risk management in flood-prone urban environments such as Manila City.

Introduction:
In the context of a circular economy, the integration of renewable materials into structural components is a key pursuit in mechanical engineering. Honeycomb sandwich structures are widely used in energy absorption and impact mitigation due to their high strength-to-weight ratio. This study explores the use of wood-fiber-reinforced poly (lactic acid) (PLA/WF) in 3D-printed sandwich panels inspired by the end-trabecular structure of beetle elytra.

Methods:
Two structural configurations—a traditional honeycomb plate (HP) and a beetle elytron-inspired plate (EBEP)—were fabricated using fused filament fabrication with both pure PLA and PLA/WF materials. Out-of-plane compression tests were conducted alongside finite element analysis (FEA) to evaluate mechanical performance. Additionally, microstructural characterization using SEM and a cost analysis of the materials were performed.

Results:
PLA/WF-based structures exhibited a 10–17% increase in specific compressive strength and a 26–44% improvement in energy absorption compared to PLA counterparts. The EBEP design demonstrated over 90% higher structural efficiency than HP. FEA results closely matched experimental data, confirming model validity. SEM revealed multiple reinforcement mechanisms in PLA/WF, including improved stress transfer, interfacial bonding, and energy dissipation through micro-voids and crystalline domains.

Conclusion:
The synergistic effect of biomimetic geometry and natural fiber reinforcement significantly improves the compressive performance and sustainability of 3D-printed sandwich panels. The PLA/WF-based EBEP offers a lightweight, cost-effective, and eco-friendly solution for mechanical components requiring energy absorption, such as crashworthy modules or protective layers in mechanical systems.

Introduction: Liposomal metered dose inhalers possess ample superiorities in pulmonary disease therapy. Nevertheless, liposomes are vulnerable to aggregate in the propellant medium, giving the bottleneck low stability for the clinical translation. Current stabilization strategies based on the physical barrier become invalid in the propellant medium, and there is anurgent need to seek a valid approach to overcome the bottleneck issue. To achieve this goal, we have proposed a new strategy: a micro-coagulated ion-doping protein corona “repulsive barrier”.

Methods: In this research, a liposomal inhalation aerosol was prepared based on the encapsulation system of liposome-Ca²⁺-Cl^--bovine serum albumin. Its size, charge, and morphology were characterized, followed by in vitro release and encapsulation capacity analysis by dialysis. Finally, fluorescent labelling was assessed for aerosol particle distribution and deposition to evaluate its aerodynamic properties.

Results: The findings indicated that the coronated nanoparticles were more homogeneous than other control formulations. Concurrently, the zeta potential was approximately -19 mV, suggesting the surface charge properties were unaffected. The formulation achieved 90% cumulative in vitro release without burst release. The three prepared systems exhibited comparable drug encapsulation efficiencies, reaching 80%. In addition, strong fluorescence signals were detected by fluorescence imaging, which confirmed the excellent encapsulation effect.

Conclusions: The consistent and reproducible results of particle size, zeta potential, morphology, drug release profile, and encapsulation efficiency collectively demonstrated the successful fabrication of the micro-coagulated ion-doping protein corona “repulsive barrier” system. Furthermore, the aerodynamic property assessment showed that the particle size distribution was reasonable and the aerodynamic properties were satisfactory after nebulization.

Titanium dioxide nanoparticles (TiO₂ NPs) were produced as a consequence of the synthesis procedure by making use of an aqueous extract of navel orange (Citrus sinensis L.) and the co-precipitation approach. The structural and morphological characteristics of the nanocomposites were validated by the use of X-ray diffraction (XRD) as well as scanning electron microscopy (SEM). The findings from both methods revealed that the nanoparticles were effectively generated. These nanoparticles displayed the structure of anatase and ranged in size from fifty to one hundred fifty nanometers for each particle. In order to test the photocatalytic activity of the TiO₂NPs under natural sun irradiation utilizing a batch approach, the ability of the bio-synthesized TiO₂NPs to destroy Malachite green, which is a deadly organic dye, was used. The results of this study showed that the TiO₂ nanoparticles exhibited outstanding photocatalytic activity of green malachite after being exposed to natural solar irradiation for a period of forty-five minutes. Additionally, they were successful in achieving a deterioration rate of 78% or higher. When the findings of this study are taken into consideration, it seems that titanium dioxide nanoparticles are a material that has the potential to be effective for the photodegradation of textiles. This material might be used in applications that are connected to environmental remediation.

As the world confronts intensifying climate change, reducing anthropogenic carbon dioxide (CO2) emissions from industrial sources has become an urgent global priority. With global CO2 emissions surpassing 36 Gt annually, post-combustion carbon capture remains a critical strategy in climate mitigation, particularly for fossil-fuel-based industries. This study presents the dynamic modeling and advanced control of a monoethanolamine (MEA)-based CO2 absorption–regeneration system. A comprehensive process model was developed in MATLAB/Simulink, incorporating mass and energy balances, vapor–liquid equilibrium, and absorber–stripper interactions. The model was validated against established benchmark datasets to ensure reliability. To enhance control performance under variable flue gas conditions, three strategies were evaluated: conventional proportional–integral-derivative (PID) control, fuzzy logic control (FLC), and model predictive control (MPC). The control objective was to maintain a CO2 capture efficiency above 90% while minimizing energy consumption. Simulation results demonstrate that MPC achieved a 12.4% reduction in reboiler energy duty (from 3.90 to 3.42 GJ/ton CO₂) and improved dynamic response time by 37% compared to PID control. FLC exhibited strong robustness under ±10% inlet CO2 fluctuations, albeit with slower recovery dynamics. These findings highlight the potential of intelligent control strategies to significantly improve the energy efficiency and operational flexibility of solvent-based carbon capture systems. The proposed framework supports the integration of advanced control in industrial CO2 capture facilities to enable cost-effective and resilient industrial decarbonization.

This study showed sustainable solutions for the growing demand for biodegradable composites in the construction industry through the acquisition and recycling of wood residues and lignocellulosic materials. The researchers focused on producing an alternative palm oil-based polyurethane adhesive, designated as Modified Reused Palm Oil-Polyurethane adhesive (MRPO-PU), for binding sugarcane bagasse particle boards. This approach leverages agricultural waste, contributing to a circular economy. The MRPO-PU adhesive was created by cleaning used palm oil through filtration and heating, followed by epoxidation and hydroxylation reactions. Characterization using Fourier Transform Infrared Spectroscopy (FTIR) confirmed the bio-polyol's readiness for the next stage, where it was mixed with Polymeric Diphenylmethane Diisocyanate (pMDI) to form the polyurethane adhesive. Particleboards with varying adhesive ratios (15 to 85 wt%) were produced and subjected to physical and mechanical testing. Physical testing involved immersing the boards in water for 24 hours, measuring thickness swelling (TS) and water absorption (WA). Mechanical properties were determined using a Universal Testing Machine (UTM) in the Civil Engineering Laboratory at Adamson University. The results demonstrated a positive correlation between adhesive content and the mechanical properties of the particleboards, indicating that increased adhesive content enhances their mechanical strength and dimensional stability. This research provides valuable insights for developing sustainable, high-performance particleboards using repurposed waste materials.

CAR T-cell therapy has been a massive win against some of the toughest blood cancers. But there is a real sticking point. Every single treatment is a one-off, handcrafted from a patient's own cells. That process takes too long, costs far too much, and frankly, depends on the patient having T-cells strong enough for the job after they have already been through punishing therapies.

So, our goal has been to move from making these one-by-one to having them ready on the shelf. The intention with allogeneic therapy is to use cells from healthy donors to build a stockpile of a standardized, reliable treatment. This makes a powerful therapy available to patients in days, not weeks, at a fraction of the cost. Of course, the big question is safety—how do you stop the donor cells from attacking the patient? That is where the elegant part comes in. Using CRISPR gene-editing, we make one tiny, precise tweak: we just snip out the T-cell receptor. By removing that one piece, the new cells no longer see the patient's body as foreign, solving the graft-versus-host disease problem and making a universal therapy a reality.

This paper involves allogeneic CRISPR-engineered CAR T-cells that provide standardized, affordable, and ready-to-use cancer immunotherapy, overcoming delays, costs, and graft-versus-host limitations.