Search Results (4,656)

The decoupled operation of electricity and water systems under variable demand conditions and tightly coupled operational constraints tends to increase total operating costs and reduce overall resource-use efficiency. In response, this study develops an integrated optimization framework for the short-term management of water–energy nexus systems composed of thermal generating units, co-production units, and a desalination plant. The proposed formulation is designed to simultaneously satisfy electricity and water demands while minimizing the total operating cost over a 24 h scheduling horizon. Methodologically, the problem is formulated as a mixed-integer nonlinear programming (MINLP) model implemented and solved in GAMS. The model explicitly incorporates electricity and water balance equations, generation-capacity limits, desalination bounds, thermal ramp-rate constraints, technical coupling relationships between electric power and water production in co-production units, and non-separable quadratic cost functions that preserve the techno-economic structure of joint production. The results confirm the technical and economic consistency of the integrated dispatch. In particular, the optimized solution satisfies an electricity demand of 45,491 MWh and a water demand of 7930 m³ with complete hourly balance consistency over the full scheduling horizon. Thermal units supply 59.4% of total electricity production, whereas co-production units contribute the remaining 40.6%. From the hydraulic perspective, the desalination plant provides 61.7% of total water demand, while co-production units supply 38.3%. The resulting total operating cost is USD 179,618.92. Relative to a decoupled benchmark, the integrated formulation reduces the total operating cost by USD 25,325.92, equivalent to 12.36%. These findings demonstrate that the proposed MINLP framework provides a robust and operationally relevant tool for the short-term planning of strongly coupled water–energy systems. Full article

The microstructure, phase composition, and high-temperature oxidation behavior of Al_0.5CoCr_0.5NiPt_0.1 and AlCoCr_0.5NiPt_0.1 multi-principal element alloys (MPEAs) at 1100 °C in air were investigated. Depending on the content of aluminum, the microstructure of as-cast samples contains FCC and BCC solid solutions. Similarly, the ratio of two solid solutions varies depending on the aluminum content in the alloy. When the content of aluminum is x = 0.5, the microstructure is dominated by the FCC solid solution, while a BCC solid solution is dominated when the concentration of aluminum is increased to x = 1.0. Moreover, in both MPEAs, platinum exists as a part of solid solutions rather than a separate phase. High-temperature oxidation was carried out in a Plavka.Pro PM-1 SmartKiln muffle furnace under isothermal conditions at 1100 °C for 100 h exposure in air, and weighing was performed every 10 h. The maximum specific weight gain for the Al_0.5CoCr_0.5NiPt_0.1 alloy was 0.965 mg/cm², and 0.675 mg/cm² for the AlCoCr_0.5NiPt_0.1 alloy. Based on the high-temperature oxidation experiment results, it was established that AlCoCr_0.5NiPt_0.1 MPEA exhibits greater resistance towards high-temperature dry air corrosion with the formation of an exclusive Al₂O₃ scale on the surface with 3–5 μm thickness; the parabolic oxidation rate constant for this alloy is k_p = 20.2 × 10^–13 (g²/cm⁴s). Introduction of platinum into the composition of the Fe-free AlCoCr_0.5Ni alloy reduces the value of the parabolic oxidation rate constant by half. Full article

This study evaluates the technical feasibility of deploying containerized oxy-combustion power modules with integrated CO₂ capture in remote Ecuadorian Amazon oil fields. Associated petroleum gas is conditioned with a 35 wt.% diethanolamine (DEA) sweetening stage specifically implemented to remove H₂S and reduce acid-gas loading prior to combustion, improving fuel quality and protecting downstream equipment while increasing methane mole fraction for combustion. System efficiency is governed by stoichiometric oxygen demand, with methane requiring 2 mol O₂/mol fuel and hexane requiring 11 mol O₂/mol fuel; favoring methane-rich streams reduces ASU energy demand, enhances combustion performance, and lowers separation costs. The combined oxy-combustion cycle attains a thermal efficiency of 33.10% and an exergetic efficiency of 39.98%. Major energy penalties arise from the cryogenic air separation unit and the CCS train, yet operational tuning of CO₂ recirculation and steam flow could raise thermal efficiency by up to 2%. The ASU produces oxygen at 96.67% purity with an energy consumption of 0.385 kWh/kg O₂, while the CCS achieves 99.99% CO₂ capture at 0.41 kWh/kg CO₂. Sourcing gas from three production blocks provides flexibility to accommodate supply variability. The modular 272 MW unit demonstrates viability for off-grid power supply, routine flaring reduction, and scalable acid-gas valorization in frontier oilfields. Full article

This paper investigates co-continuous structures in immiscible polymer blends through three-dimensional (3D) computational calculations based on a multiphase phase-field equation for fluid flow. The mathematical model describes phase separation with the Cahn–Hilliard (CH) equation and fluid motion with the incompressible Navier–Stokes (NS) equations. Both polymers are treated as Newtonian viscous fluids, and the model includes surface tension, viscosity, and volume fraction effects. A semi-implicit finite difference method (FDM) solves the CH equation, and a projection method maintains the incompressibility of the flow field. Multigrid techniques solve the nonlinear systems efficiently. In addition, a connectivity-based detection algorithm determines whether a phase forms a connected structure that reaches all boundaries of the numerical domain. The numerical results show that the morphology changes from a droplet–matrix structure to a co-continuous structure as the volume fraction increases. The interfacial area per unit volume reaches a local maximum near the transition between these two regimes. Full article

TiO₂ is normally a preferred photocatalyst; however, its photocatalytic performance is constrained by its low surface area, wide band gap, and high electron–hole pair recombination rates. The objective of this study was to optimize the photocatalytic efficiency of TiO₂ by impregnating it onto activated carbon derived from Senegalia mellifera biomass. The quantitative study involved synthesizing TiO₂ using the precipitation technique and preparing AC through both chemical and physical activation methods. The prepared AC samples were impregnated with TiO₂ NPs using the wet impregnation method. The physicochemical properties of the samples were examined using several characterization techniques, namely, FTIR, EDS, Raman, UV reflectance, STA, SEM, and BET. The photocatalytic efficiency of AC/TiO₂ composites was evaluated through methyl orange degradation. The results showed significant improvement in photocatalytic performance when TiO₂ was supported on AC. The modified photocatalyst exhibited enhanced surface area, thus increased active sites for photocatalysis, improving electron–hole separation and reducing recombination. The 50%CO₂/AC-0.5TiO₂ composite demonstrated superior photocatalytic activity under both UV and visible light irradiation. It showed 52.1% MO removal under visible light and 76.1% MO removal under UV light. The study concludes that biomass-derived AC/TiO₂ composites present a promising, cost-effective and sustainable approach of enhancing photocatalytic activities. Full article

Nuclear transport is a vital system that mediates movement of essential biomolecules between the nucleus and cytoplasm. It is tightly regulated by the Importin (IMP) superfamily to maintain separation of cellular compartments. Cellular stress in various forms, particularly oxidative, can suspend nuclear transport and lead to cell death. Prolonged oxidative stress manifests in myriad conditions, including cancer, viral infection and metabolic disease. An IMP protein, Importin-13 (IMP13), retains function under stress, while all other IMP family members tested to date do not. Phylogenetic and structural analysis revealed Transportin-3 (TNPO3) as the closest homologue of IMP13, suggesting it may also retain its function under stress. Subcellular localisation studies indicated that TNPO3 maintained its typical subcellular localisation, even in the presence of stress, unlike most IMP family members. Also, fluorescence recovery after photobleaching (FRAP) demonstrated that TNPO3 shuttling is unaffected under stress. Co-immunoprecipitation studies examining cargo binding revealed the capacity of TNPO3 to bind its cargo in the presence of stress. This demonstrated for the first time that TNPO3 retains functionality under stress conditions, in contrast to other IMPs, but similar to IMP13. Furthermore, both IMP13 and TNPO3 appear to protect against the potentially critical mislocalisation of Ran, a key molecule involved in the maintenance of the nuclear transport system. Full article

Classifying power quality disturbances (PQDs) under strong noise conditions remains challenging for existing deep learning models. These models typically separate denoising from feature extraction, often rely on attention mechanisms that operate along only a single dimension, and tend to achieve high accuracy at the cost of high complexity, which limits their performance under low signal-to-noise ratio conditions and hinders practical deployment. To address these limitations, this paper proposes AD-PDAF-Net, which organically integrates three key mechanisms through a co-design strategy. Unlike conventional methods that depend on preprocessing, an adaptive soft thresholding denoising layer is embedded into a lightweight residual network to progressively suppress noise during feature extraction, thereby unifying denoising with feature learning. A parallel dual attention module independently refines features along the channel and temporal dimensions, then adaptively fuses them using learnable weights to capture both frequency domain and temporal characteristics of disturbances. The lightweight network entry replaces aggressive downsampling with small convolutions to preserve transient details, and a bidirectional long short-term memory network (BiLSTM) efficiently captures temporal dependencies. Evaluated on a dataset of 25 disturbance categories defined in IEEE Std 1159-2019, the model achieves a classification accuracy of 97.26% and a Kappa coefficient of 97.02% under 20 dB white Gaussian noise, along with an accuracy of 98.78% under mixed noise conditions. The model has only 0.36 million parameters and a computational cost of just 1.50 GFLOPS. Through this co-design, AD-PDAF-Net achieves both high noise robustness and high classification accuracy with minimal computational overhead, offering an effective solution for time series signal recognition in resource constrained environments. Full article

This study presents a combined process of sulfide precipitation followed by hydrogen peroxide leaching for rhenium recovery from copper smelting waste acid under ambient temperature and pressure. The process first removed copper through selective sulfide precipitation, then achieved co-precipitation of rhenium and arsenic to obtain a rhenium-rich precipitate. Subsequently, exploration of rhenium-containing precipitate leaching using H₂O₂ solution was conducted under isothermal conditions at 20 °C. The effects of H₂O₂ concentration, liquid-to-solid ratio, acidity, and leaching time rhenium extraction efficiency were examined systematically. The optimal leaching conditions were determined as: H₂O₂ concentration of 150 g/L, liquid-to-solid ratio of 5:1 mL/g, stirring speed of 350 r/min, and leaching time of 30 min. Under these conditions, the leaching conversions of rhenium and arsenic reached 96.0% and 93.8%, respectively. Through characterization of precipitate and leaching residue using ICP, SEM-EDS, XRD, and XPS analyses, the process and related reactions were elucidated. Results demonstrated that low-valence rhenium oxides and sulfides serve as the main reactive species during H₂O₂ leaching, whereas organic sulfur, high-valence oxides, and copper sulfide remained stable and resistant to leaching. Selective precipitation of copper effectively eliminated insoluble metal sulfides from rhenium-containing precipitates, thereby enabling efficient separation of rhenium under mild conditions. Full article

This review summarizes innovative co-formulation strategies for non-marketed dry powder inhalers (DPIs), enabling the simultaneous pulmonary delivery of multiple active pharmaceutical ingredients (APIs). Key approaches include co-amorphous systems (COAMS) and co-crystals, which combine two APIs into a single particle, improving aerodynamic properties, solubility, dissolution, and patient compliance while reducing manufacturing complexity. Core–shell microparticles, produced via spray drying, allow spatial separation and controlled release of APIs, minimizing drug–drug interactions and enabling tailored pharmacokinetics. Co-spray drying of dual APIs can yield particles with superior aerosolization and stability, though examples remain limited. Nanoparticle-based systems offer enhanced lung deposition and cellular uptake but face challenges in device compatibility, scalability, and regulatory approval. Each technology presents unique advantages and limitations regarding manufacturability, dose flexibility, and clinical translation. This review also highlights advances in in vitro toxicity testing, including air–liquid interface cultures, organoids, lung-on-chip models, and precision-cut lung slices, which are increasingly important as alternatives to animal studies. The importance of using an aerosol exposure system for the testing is highlighted. Ultimately, the choice of co-formulation platform should balance scientific innovation with practical considerations of manufacturing and regulatory requirements to maximize therapeutic benefit and commercial viability for future DPI combination products. Full article

Polyetherimide (Ultem-1000) hollow-fiber membranes were developed for biogas purification with emphasis on the relationship between spinning conditions, membrane morphology, gas transport properties, and module performance. Hollow fibers were prepared from dope solutions based on dimethylformamide (DMF) and N-methyl-2-pyrrolidone (NMP) at different conditions, followed by post-treatment with 1 and 3 wt.% silicone solution in n-heptane to reduce nonselective defects and improve selectivity toward the intrinsic behavior of dense PEI films. SEM analysis revealed that DMF-based fibers formed a more open, macrovoid-rich structure, whereas NMP-based fibers exhibited a more homogeneous sponge-like morphology with a better-defined selective layer. DMF-based fibers experienced faster demixing, which promoted macrovoid formation, increased pore connectivity of the substructure, lowered mass transfer resistance, and at the same time increased the probability of nonselective pathways and defect-related loss of selectivity. This structural evolution was reflected in gas transport properties: untreated DMF fibers showed high mixed-gas permeance but limited selectivity, while NMP fibers demonstrated lower permeance and selectivity values closer to those of the dense film. Silicone post-treatment significantly improved separation performance, with 3 wt.% coating being markedly more effective than 1 wt.% coating. The best compromise between permeance and selectivity was achieved for the DMF-based fibers treated with 3 wt.% silicone, which exhibited CO₂ and H₂S permeances of 39.4 and 47.12 GPU, respectively, together with selectivity values of 22.4, 26.8 and 20.2 for CO₂/CH₄, H₂S/CH₄ and CO₂/N₂. A membrane module containing 500 fibers was studied during the quasi-real biogas upgrading. With increasing stage-cut, the CH₄ concentration in the retentate increased from ~74 to 96 mol.%, while CO₂ decreased from ~21 to 2 mol.%. The results demonstrate that structure control combined with silicone post-treatment is an effective strategy for producing PEI hollow fibers suitable for simultaneous methane enrichment and removal of acid impurities from biogas. Full article

Air pollution is one of the fundamental environmental problems that directly threaten public health, ecosystems, and sustainable urban life in regions with high industrialization and urbanization density. This study aims to investigate whether the air pollution dynamics in Gaziantep and Kilis, two neighboring cities in Turkey, exhibit distinctive city-specific characteristics in their time series. In this context, Dynamic Time Warping (DTW) distance matrix and hierarchical clustering approaches were applied to compare the temporal behavior of pollutants from daily time series of PM10, SO₂, CO, and O₃ measurements across provinces between 2021 and 2025. Random Forest (RF), XGBoost, and Support Vector Machines (SVM) models were then developed to examine the separability of cities based solely on pollutant concentrations. The results revealed that the RF and XGBoost models successfully classified the two cities with over 93% accuracy. Additionally, SHAP analysis was used to interpret the contribution of each pollutant within the classification models, indicating that PM10 and SO₂ have relatively higher importance in distinguishing between the two cities. It should be noted that SHAP provides model-based interpretability rather than a direct representation of physical or atmospheric mechanisms. The findings suggest that pollutant time series may exhibit statistically distinguishable structures even between neighboring cities. Full article

Lactococcosis caused by Lactococcus garvieae is an emerging threat to warmwater aquaculture, yet evidence integrating field outbreaks with robust molecular confirmation and controlled virulence testing remains limited for Thailand’s cage-cultured tilapia. From May to October 2025, acute mortality events were investigated in cage-cultured Nile tilapia (Oreochromis niloticus) in a reservoir in Ubon Ratchathani Province, Thailand. Suspected outbreaks were defined by abrupt daily mortality exceeding 5% accompanied by septicemia-like clinical signs. Water quality during sampling covered the following ranges: temperature 28.6–31.9 °C, pH 6.5–7.0, salinity 0.02–0.03 ppt, electrical conductivity 0.036–0.046 mS/cm, TDS 22.20–26.50 mg/L, total alkalinity 17.0–34.0 mg/L as CaCO₃, total hardness 12.0–60.0 mg/L as CaCO₃, dissolved oxygen 6.5–7.0 mg/L, and NH₃ were below the limit of detection. Full-length 16S rRNA tissue profiling revealed strong tissue partitioning: blood microbiomes were consistently dominated by Lactococcus and L. garvieae at the species level, whereas gills showed higher richness and mixed communities with multiple opportunistic taxa. Culture isolation was more reliable from blood than gills, yielding 16 Gram-positive, catalase-negative isolates (AAHM-LG2501–AAHM-LG2516) that clustered within the L. garvieae clade in near full-length 16S rRNA phylogenetic analysis and were separated from closely related Lactococcus lineages. A representative blood isolate (AAHM-LG2501) showed dose-dependent virulence in controlled challenges, with an LD₅₀ of ~1.05 × 10⁵ CFU/fish by intraperitoneal injection and an LC₅₀ of ~1.20 × 10⁶ CFU/mL by immersion. Histopathology supported systemic dissemination, with injection producing more consistent multi-organ lesions than immersion, particularly in head kidney, liver, and spleen, while gills exhibited route-associated epithelial and vascular alterations. Together, these findings confirm L. garvieae as a major etiological agent of septicemic outbreaks in cage-cultured tilapia in Thailand and support a practical surveillance framework prioritizing blood sampling, molecular confirmation, and risk-based monitoring to guide biosecurity and vaccine-oriented prevention. Full article

Personalized medicine aims to tailor therapy based on patient-specific molecular and biological characteristics, while nanomedicine focuses on engineering delivery systems to overcome pharmacokinetic and biological barriers. Despite major advances, both fields are limited when applied separately. This review discusses integrating patient stratification with rational nanocarrier design, a combination termed personalized nanomedicine, as a framework to maximize therapeutic index. With emphasis on clinically validated and late-stage examples, we analyze how molecular stratification informs therapeutic design, with particular focus on translational constraints and engineering trade-offs. Results: Personalized medicine enables precise target identification and patient stratification but does not address delivery barriers that limit therapeutic distribution and safety. Conversely, nanomedicine overcomes delivery challenges but exhibits patient- and disease-dependent variability. Merging these approaches allows nanocarrier design to be tailored to disease biology and patient-specific barriers to effective treatment. Recent clinically successful examples demonstrate that co-optimizing biological targeting and delivery engineering can improve translational robustness. Conclusions: Personalized nanomedicine represents a convergence of molecular stratification and engineered delivery systems, a fusion that facilitates context-dependent therapeutic design rather than one-size-fits-all formulations. While significant translational and regulatory challenges remain, treating delivery design as an integral component of personalization offers a viable path toward broader clinical implementation. Continuing to integrate patient profiling with nanoengineering principles will be essential for translating personalized nanomedicine from promising case studies into standard clinical practice. Full article

To in situ and efficiently degrade irreversible membrane contaminants under mild conditions, SiC ceramic membranes (CMs) were imparted a catalytic ozonation functionality. A spinel-type CoFe₂O₄ catalyst was fabricated via a citrate-assisted sol–gel method and subsequently impregnated into the macropores of SiC ceramic membranes through a urea-assisted one-step combustion technique. The as-prepared catalytic membranes (CoFe₂O₄-CM) were systematically characterized by SEM, EDS, XRD and XPS techniques, and the catalytic ozonation performance was evaluated in an integrated catalytic ozonation–membrane separation system (CoFe₂O₄-CM/O₃). A flux recovery rate (FRR) of 93.33% was achieved at an ozone concentration of 70.27 mg·L⁻¹ within 30 min, indicating that a catalytic self-cleaning membrane was successfully developed. The possible catalytic reaction mechanism was elucidated by identifying reactive oxygen species generated using free radical quenching tests and electron paramagnetic resonance (EPR) analysis. This study offers a promising and environmentally friendly strategy for ceramic membrane cleaning in various membrane separation fields. Full article

Single image dehazing remains challenging because haze simultaneously distorts global illumination, scene structure, and fine textures, making rigid low–high frequency decoupling prone to error propagation and detail inconsistency. To address this issue, we propose CoFiWaveMamba, a coarse-to-fine wavelet-guided Mamba network for single image dehazing. The proposed method first employs wavelet decomposition to separate low- and high-frequency components. For low-frequency restoration, a 2D selective-scan Mamba-based module is introduced to capture long-range dependencies, combined with lightweight high-frequency-guided spatial modulation and Shuffle-guided Sequence Attention, we design a progressive coarse-to-fine refinement strategy that combines Fourier-domain global spectral consistency with wavelet-domain directional detail representation, enabling more targeted recovery of edges and textures. Experiments on synthetic and real dehazing benchmarks, including Haze4K, RESIDE-6K, HSTS-SYNTHETIC, I-Haze, NH-Haze, Dense-Haze, and O-HAZE, as well as ablation studies, verify the effectiveness of the proposed design. Overall, CoFiWaveMamba provides a more coordinated solution for global haze removal and local detail reconstruction, helping suppress residual haze, ringing artifacts, oversharpening, and texture inconsistency while restoring clearer and more natural images. Full article