Search Results (13,318)

Phycobiliproteins (PBPs) are a family of pigment-proteins renowned for their exceptional light-harvesting, fluorescent, and antioxidant properties. Among cyanobacteria, Spirulina stands out as one of the richest natural sources of PBPs, particularly phycocyanin (PC) and allophycocyanin (APC), yet the large-scale production of analytical-grade PBPs remains hampered by an inherently complex downstream process that relies on multiple purification steps, compromising both yield and scalability. This work presents a streamlined strategy to obtain analytical-grade PC, combining ultrasound-assisted extraction (UAE) with an aqueous ionic liquid (IL) solution and a single hydrophobic interaction chromatography (HIC) step, integrated within a biorefinery framework. The proposed approach yielded analytical-grade PC with a recovery of up to 50.44% and enhanced APC purity up to 10.57-fold. Furthermore, the IL was successfully reused in both extraction and purification steps without compromising yield or purity. The environmental performance of the proposed process was assessed through a cradle-to-gate life cycle assessment (LCA), with system boundaries encompassing the following biorefinery stages: cultivation, harvesting and drying, PC extraction and purification, post-processing, and spent biomass valorization via anaerobic digestion. The LCA identified the main environmental hotspots and guided the proposal of targeted process improvements—particularly HIC salt substitution and increased IL recovery—which reduced environmental impacts by 65.9–89.8% across most categories. The proposed strategy was further benchmarked against two model scenarios for analytical-grade PC production, one conventional and one innovative, revealing its relative advantages and limitations. Overall, this work demonstrates a viable pathway for producing high-purity PC that balances process efficiency with environmental sustainability, supporting the development of greener microalgae-based bioprocesses. Full article

Background: Exercise adaptation is increasingly recognized as an immunometabolic process driven by coordinated interactions among inflammatory signaling, mitochondrial regulation, metabolic homeostasis, and recovery-associated physiology. Within this framework, NLRP3 inflammasome activation and PPARD-mediated metabolic signaling have emerged as biologically relevant pathways potentially involved in exercise-induced physiological adaptation. However, the contribution of regulatory genetic variations linking these pathways remains poorly characterized. Objective: To synthesize current evidence regarding the integration of NLRP3- and PPARD-related pathways in exercise immunometabolism and adaptive physiological responses to exercise, with particular emphasis on the regulatory variants NLRP3 rs10754558 and PPARD rs2267668 as potential contributors to interindividual variability in exercise adaptation. Methods: A structured narrative review complemented by exploratory systems-level in silico analyses was conducted using the PubMed, Scopus, and Web of Science databases until March 2026. Evidence related to exercise physiology, inflammatory regulation, metabolic adaptation, and exercise-associated phenotypes involving the NLRP3 and PPARD pathways was evaluated. Complementary analyses included functional annotation, protein–protein interaction network analysis, and pathway enrichment using STRING, Reactome, KEGG, Gene Ontology, and other publicly available genomic databases. Particular attention was given to the functional and regulatory context of rs10754558 and rs2267668 within the interconnected inflammatory and metabolic pathways relevant to exercise adaptation. Results: The reviewed evidence identified recurrent interactions among the inflammatory and metabolic pathways involved in exercise adaptation and recovery. NLRP3 rs10754558 and PPARD rs2267668 were identified as candidate regulatory variants potentially positioned at the interface between inflammatory responsiveness and metabolic flexibility, providing a biologically plausible framework for understanding the interindividual variability in exercise adaptation. Exploratory system-level analyses identified recurrent associations among inflammatory signaling, mitochondrial function, energy-sensing pathways, and metabolic regulation. These findings primarily reflect the functional annotations and system-level pathway associations identified through exploratory analyses. Conclusions: Current evidence supports a systems-level physiological framework in which inflammatory and metabolic pathways interact dynamically during exercise adaptation and recovery. NLRP3- and PPARD-related pathways, including the candidate regulatory variants rs10754558 and rs2267668, may contribute to interindividual variability in exercise-associated physiological responses and represent promising targets for future hypothesis-driven investigations in exercise immunometabolism, exercise genomics and precision exercise medicine. Full article

Studying Bingham flows in permeable media under a periodic magnetic field enhances the understanding of yield-stress fluids for applications like oil recovery and filtration. This study combines non-Newtonian behavior with porous-medium resistance and magnetic variations, facilitating the analysis of complex flow phenomena, including oscillatory yielding and improved flow control in porous structures. The viscous potential theory is employed to streamline the mathematical processes. The utilization of linear governing partial differential equations of motion, along with appropriate nonlinear boundary conditions, yields additional simplifications. The investigation yields a nonlinear Mathieu oscillator that governs the interfacial displacement. A non-perturbative method is used to convert this nonlinear ordinary differential equation into a linear equation. A non-dimensional formulation minimizes the fundamental variables required to characterize the system by establishing a collection of dimensionless physical characteristics. The study analyzes a nonlinear Mathieu oscillator with complex coefficients to explore system dynamics related to elevation. By simplifying the variable coefficients, it enhances the examination of stability and resonance behavior. Despite inherent complexities, the work effectively clarifies fundamental concepts, contributing to a more coherent understanding of the subject. The Hartman number, magnetic field, and magnetic permeability ratio exert a destabilizing effect. Conversely, the Bingham parameter, Weber number, and periodic frequency exert a stabilizing influence. Full article

Efficient recovery of long-chain dicarboxylic acids (LCDAs) from aqueous fermentation broths is a key challenge for the industrial development of bio-based LCDA production. This study evaluates liquid–liquid extraction (LLE) as a downstream recovery strategy, comparing physical extraction (PE) and reactive extraction (RE) for DCA 12, DCA 16, and DCA 18. The novelty of this work lies in demonstrating that LCDA extraction is governed by mechanisms fundamentally different from those of short- and medium-chain dicarboxylic acids. Whereas shorter chain dicarboxylic acids are mainly controlled by dissociation degree, LCDA recovery is strongly influenced by carbon-chain apolarity, low aqueous solubility, and compound losses through agglomeration, precipitation, and/or micellization. PEs enabled the selective recovery of the more hydrophobic DCA 16 and DCA 18 over DCA 12, confirming the dominant role of chain length in LCDA separation. In contrast, RE with Aliquat^®336 maximized total LCDA recovery, achieving extraction efficiencies above 85%, but with reduced selectivity. Validation in autoclaved fermentation broth from UCO feedstock confirmed the potential of Aliquat^®336 in octanol for high LCDA recovery, while revealing lower extraction efficiencies than in model mixtures due to broth matrix complexity. Overall, this study establishes LLE as a promising platform for LCDA recovery and highlights that future downstream process design must balance total recovery, chain-length selectivity, and broth-specific matrix effects. Full article

In rocky mountainous regions characterized by shallow, barren soils and water scarcity, non-rainfall water, such as condensation, plays a crucial ecological role in mitigating seasonal drought in forest trees. To enhance the water-use capacity of vegetation, this study utilized a previously developed eco-friendly PVA–CS/SA–Ca²⁺ hydrogel. The primary objective was to elucidate the synergistic mechanisms by which the hydrogel optimizes condensed water utilization and drives the ecophysiological recovery of Pinus tabuliformis and Platycladus orientalis, two keystone afforestation species in northern China. Utilizing a controlled environmental chamber to simulate the condensation and humidification process, the experiment established three treatments: a control group (CK), a pot-sealed group (PS, to isolate soil water absorption), and a hydrogel-amended group (Hydrogel-Root Wrapping, HRW). To comprehensively evaluate the water utilization mechanisms, the amount of condensed water captured by the system was quantified, and hydrogen isotope tracing techniques were employed to precisely track water transport pathways and contribution rates. Concurrently, key physiological parameters were systematically determined, including leaf water potential, stomatal conductance, leaf water content, net photosynthetic rate, and transpiration rate. The results demonstrated the following: (1) the hydrogel significantly enhanced the condensation water capture capacity of the system. The net mass gains of the Pinus tabuliformis and Platycladus orientalis systems under the HRW treatment reached 26.3 g and 32.9 g, respectively, which represented 1.17 and 1.30 times those of the CK treatment, and 1.52 and 1.54 times those of the PS treatment. (2) Isotope tracing confirmed that both tree species possess significant Foliar Water Uptake (FWU) capacity. Following condensation, the δ²H values in the leaves of Platycladus orientalis and Pinus tabuliformis surged to 113.5‰ and 85.3‰, respectively, with stem δ²H values increasing by 31‰ and 22‰ compared to their initial baseline. (3) The introduction of the hydrogel in the HRW treatment provided 11.2% and 10.9% of the stem water supply for Platycladus orientalis and Pinus tabuliformis, respectively, thereby reducing their dependence on soil water by 8.3% and 13.1%. In contrast, there was no significant difference in the fractional contribution of condensation water to stem water between the PS and CK treatments. (4) Regarding physiological responses, the application of the hydrogel material effectively improved the physiological status of the plants. The leaf water potentials of Pinus tabuliformis and Platycladus orientalis increased to −0.15 MPa and −1.32 MPa, respectively. Concurrently, stomatal conductance (3.25 and 3.64 mm·s⁻¹) and leaf water content (58.4% and 67.4%) were significantly higher than those in the other treatments. In summary, the hydrogel can significantly enhance the capture, conversion, and utilization efficiency of condensation water by vegetation, effectively optimizing the water supply dynamics of the system. This provides key theoretical and technical support for ecological afforestation in difficult sites within rocky mountainous areas. Full article

Direction-of-arrival (DOA) estimation of cyclostationary signals is an important problem in array signal processing, especially in sensor-limited and underdetermined scenarios. Sparse arrays and cyclostationary statistics can improve virtual degrees of freedom and target selectivity, but incomplete difference coarray information caused by missing lags may degrade virtual covariance reconstruction and reduce the reliability of DOA estimation in closely spaced, coherent, and interference-contaminated environments. To address this issue, this paper proposes a cyclostationary DOA estimation method based on an augmented extended coprime array (AECA), SVT-based hole recovery, and weighted atomic norm minimization (ANM). The proposed method first constructs the cyclic correlation matrix at the target cyclic frequency and maps it into the AECA-based virtual coarray domain. Redundant lag observations are then aggregated, and an iterative hole recovery procedure is applied to obtain an initial structured virtual covariance matrix. On this basis, a weighted ANM-based covariance refinement model is introduced, where directly observed lags and SVT-recovered hole entries are assigned different confidence levels. The final DOA estimates are obtained using MUSIC on the refined virtual covariance matrix. Simulation results under the considered underdetermined, closely spaced, coherent-source, and interference-contaminated scenarios show that the proposed method achieves lower RMSE and clearer spectral responses than the selected baseline methods. Additional ablation, parameter sensitivity, cyclic frequency mismatch, non-Gaussian noise, and runtime analyses further clarify the contribution, robustness range, and computational cost of the proposed framework. Full article

This study investigated the kinetics of chalcopyrite dissolution in an alkaline monosodium glutamate (MSG) solution using H₂O₂ and KMnO₄. The aims were to optimize process conditions for maximum copper dissolution and to study the kinetic mechanism of dissolution under varying conditions, such as particle size, oxidant type and concentration, temperature, and the presence of gangue minerals. Results showed that KMnO₄ exhibited better oxidative efficiency and stability than H₂O₂, yielding copper recoveries above 90% in most conditions while keeping the dissolution of some gangue metals, such as calcium, magnesium, and iron, lower, thereby reducing MSG consumption. Temperature and particle size were the most important factors in the effects on leaching kinetics; smaller particles allow higher initial reaction rates, while larger particles allow prolonged dissolution. The shrinking core model (SCM) was thus used to perform kinetic analysis and determine that diffusion controls the leaching process through the product layer. The calculated activation energies of 18.2 kJ/mol of MSG-H₂O₂ and 17.3 kJ/mol of MSG-KMnO₄ confirm the diffusional mechanism. Full article

Plastic forming of the workpiece is a key quality indicator during deforming broaching. This study aims at technological control over workpiece forming by establishing a relationship with technological factors, including broaching modes: interference, tool geometry, and workpiece wall thickness. The research methods used included numerical simulation of the deformation process and the stress–strain state of a plastic steel workpiece. The constructed simulation models allowed tracking stress and strain evolution on the inner and outer surfaces, revealing their differences. The approach’s originality lies in establishing the key influence of critical contact pressure in the deformation zone on strain state changes. Its appearance is influenced by interference, tool geometry, and workpiece wall thickness. Circumferential strain depends solely on interference and workpiece wall thickness, remaining independent of the angle, α. A relationship is provided to determine the interference ensuring the outer dimension. The calculation method for determining the processed hole diameter was improved, considering the real deformation zone scheme, simulation results, and elastic recovery. The relationship between the processed hole diameter, broaching modes, and workpiece wall thickness has been established. It is necessary to set the angle that ensures the absence of axial strain. A technological control scheme for forming is developed, and an application example is provided. Full article

In this paper, a multi-objective optimisation method based on the Non-dominated sorting genetic algorithm II (NSGA-II) is proposed, which proves to be effective in solving the computer-aided molecular design (CAMD) problem in the design of solvents for cooling crystallisation. A multi-objective optimisation model has been developed for the CAMD problem of solvents in the crystallisation process with the toxicity, solubility parameters, and potential recovery of the solvents as objective functions and the feasibility of the molecular structure as constraints. The properties involved are to be calculated by the group contribution method, and the solubility parameters of the solute in the solvent are calculated based on the Universal Quasichemical Functional-group Activity Coefficients (UNIFAC) model. Based on this method, cooling crystallisation solvents for 2-mercaptobenzothiazole (MBT) and sebacic acid were designed. The results indicate that the proposed multi-objective CAMD framework exhibits a certain degree of generality. Even when the optimisation parameters and methods differ from those of other existing frameworks, it does not overlook the optimal solutions under specific design conditions. Furthermore, clustering of the Pareto front for MBT revealed that, since multi-objective optimisation does not aim to obtain a single optimal solution, it can identify multiple candidate solvents that balance potential yield and toxicity. This approach avoids the issue of single-objective optimisation, which tends to overemphasise potential yield at the expense of toxicity. Full article

The wet recovery of spent lithium iron phosphate (LFP) batteries is severely hindered by the low efficiency of copper removal. Here, a new process has been developed using a copper-removing chelating resin with pyridine nitrogen, carboxyl, and hydroxyl groups for the selective separation of copper ions. This copper chelating resin achieved a copper removal efficiency of 96.99% and reduced the residual copper content to below 10 milligrams per liter, significantly outperforming the traditional iron powder method. The adsorption process is highly sensitive to pH, with the highest efficiency at pH 1.75. A concentration of 2.0 moles per liter of H₂SO₄ can achieve a desorption rate of approximately 95%. The adsorption process follows the Langmuir isothermal equation and the pseudo-second-order kinetic model, corresponding to single-layer chelated chemical adsorption. Mechanism studies have confirmed that the synergistic coordination effect of the multifunctional groups helps in the efficient capture of copper ions. This copper chelating resin exhibits excellent stability, reversibility, and reusability, providing a promising method for efficient copper removal and recovery in the wet metallurgical recycling of LFP. Full article

Background: Sleep deprivation is one of the major public health and performance risk factors, with documented effects on vigilance, executive function, emotional regulation, and safety-critical behaviour. This review examines how event-related potentials (ERPs)—which provide millisecond-level resolution of cognitive processing stages—can clarify which neural processes are most affected by sleep loss, from early sensory encoding to later evaluative and control-related stages. Materials and Methods: This study was conducted as a systematic review of human studies on sleep deprivation and ERPs. Eligible studies included human participants, focused primarily on acute/total sleep deprivation, and reported ERP outcomes (e.g., amplitude, latency, topography, or related event-locked EEG measures). Searches were performed in major biomedical/psychology databases using sleep deprivation and ERP terms, with additional forward/backward citation searching. Data was extracted in a structured format (participant characteristics, deprivation protocol, ERP methods, behavioural outcomes, ERP findings, and recovery/countermeasure effects). Due to substantial heterogeneity in paradigms, protocols, and ERP methods, findings were synthesised narratively rather than meta-analysed. Risk of bias was assessed with RoB 2 and ROBINS-I. Results: The search identified 854 records, of which 82 studies were included following deduplication, screening, full-text review, and citation chasing. Samples were typically small, highly selected, and dominated by healthy young adults, with frequent attrition related to prolonged wakefulness and EEG data-quality constraints. Across studies, sleep deprivation produced stage-specific and task-dependent ERP effects rather than a single uniform pattern. The most consistent findings involved mid-to-late components. These components typically showed prolonged latency and reduced amplitude. In some cases, amplitude increases were observed and interpreted as compensatory recruitment. Early sensory/pre-attentive components (e.g., P1/N1/MMN/P50) were often relatively preserved, but showed selective vulnerability, including latency slowing, reduced filtering/gating, or decreased phase locking. A recurring observation was a behaviour–ERP dissociation, where ERP abnormalities were detectable even when behavioural impairment was modest, indicating covert neural inefficiency or compensation. Recovery sleep, naps, and countermeasures (e.g., modafinil, caffeine) produced partial, component-specific recovery, with amplitude and latency often recovering at different rates. Conclusions: The evidence indicates that sleep deprivation primarily disrupts higher-order, late-stage, and temporally coordinated neural processing, while earlier sensory processing is often preserved but becomes slower and less stable. Among ERP markers, the P300/P3 family is the most robust and informative signature of sleep loss effects and recovery. ERPs are therefore a sensitive tool for detecting neural dysfunction and compensation under sleep deprivation, including changes that may precede overt behavioural decline. Future research must improve the generalisability and reproducibility of ERP findings by employing larger, more diverse samples, alongside more standardised methodological, recording, and reporting practices. Full article

Common beans contain insoluble-bound phenolic compounds with potential bioactive properties; however, their recovery generally depends on harsh hydrolytic conditions and organic solvents. This study evaluated alternative extraction strategies for the recovery of insoluble-bound phenolic compounds from raw and cooked common bean flours of two Andean varieties (Peumo and Magnum), using Viscozyme L^®, ultrasound, and pretreatment with ultrasound followed by Viscozyme L^®. The resulting extracts were characterized in terms of phenolic profile by UPLC-ESI-MS/MS, total phenolic content (TPC), and antioxidant activity. Enzymatic treatment improved the recovery of insoluble-bound phenolic compounds and antioxidant activity compared with the control, while ultrasound alone showed limited effectiveness under the evaluated conditions. The combination of ultrasound pretreatment and Viscozyme L^® generally improved recovery of some phenolic compounds and antioxidant-related endpoints relative to control conditions. Cooking generally reduced TPC and antioxidant activity, although the effect on individual phenolic compounds depended on the extraction treatment. Overall, enzyme-assisted extraction, especially when combined with ultrasonic pretreatment, represents a promising strategy for improving the recovery of insoluble phenolic compounds from common bean flour. Further optimization is still needed to improve the sustainability of the process and its industrial applicability. Full article

The paper presents AI Sentinel, a closed-loop socio-technical approach to monitoring, analyzing, and responding to negative hotel reviews through a combination of big data analytics, natural language processing, and machine learning predictive modeling. A total of 85,178 reviews were analyzed for 80 European hotel properties, with 5665 (mean = 6.54) classified as negative and 79,513 (mean = 9.22) classified as positive. Latent Dirichlet Allocation (LDA) was used to discover topics; Gradient Boosting was used to classify high-risk reviews (AUC = 0.919); and a rule-based engine was employed for routing recovery/delivery of service. This analysis identified ten major complaint areas in guest reviews, with Cleanliness, staff behavior, and room quality accounting for 47.0% of negative comments about hotels and forming the Critical tier of intervention. There are three key theoretical contributions made by this study: (1) establishing operationalization of joint socio-technical optimization in AI-augmented service management; (2) introducing algorithmic service sensing as a time-compression mechanism for recovery workflow; and (3) demonstrating that the integration of unsupervised topic modeling with supervised risk classifications can provide a compounded analytical approach. Managerial consequences include risk prioritization at the portfolio level, the design of specific services to target certain traveler segments, nationality-based recovery threshold levels, and an appropriate governance structure that meets the requirements of the General Data Protection Regulation and the new European Union Artificial Intelligence Act. Full article

This study investigates the effect of waste cement dust (CD) and rock wool (RW) inorganic fiber on the tribological performance of brake friction composite materials. Five formulations were fabricated by varying CD from 65 to 45 wt.% and RW from 5 to 25 wt.% and evaluated for tribological properties on a Chase friction testing machine in accordance with IS 2742 test procedures. The results show that composites containing higher CD and lower RW exhibited higher coefficients of friction, lower friction variability, and improved fade resistance. In contrast, composites containing higher RW and lower CD showed improved recovery characteristics and substantially enhanced wear resistance. The performance coefficient of friction decreased from about 0.521 to 0.442 as the formulation shifted from CD-rich to RW-rich compositions, while the variability coefficient increased from about 0.364 to 0.516. The highest wear was recorded for the composite containing 65 wt.% CD and 5 wt.% RW inorganic fiber, whereas the lowest friction fluctuations were obtained for the composite containing 55 wt.% CD and 15 wt.% RW inorganic fiber. Finally, a simple ranking process-based decision-making technique was employed to evaluate the overall performance of all the composites, suggesting 55 wt.% CD as the optimal content. These findings confirm the potential of waste CD as a viable functional constituent in brake friction composites when combined with RW inorganic fiber in an optimized manner. Full article

Northern Colombian Creole-Antillean avocado constitutes a promising agroindustrial resource because of its lipid-rich composition and regional availability. Despite this potential, the industrial exploitation of this biomass remains limited, particularly regarding the technical assessment of large-scale oil production systems. In this study, an avocado oil production process was evaluated through computer-aided simulation combined with the Water–Energy–Product (WEP) methodology to assess operational behavior, resource utilization, and process efficiency from an integrated technical perspective. The evaluated system achieved an overall production yield of 9.43%, mainly affected by the elevated raw material requirements associated with oil generation. Nevertheless, the extraction stage exhibited favorable technical performance, reaching an oil recovery efficiency of 81.42%. Concerning water management, the process required 26.85 m³/t of freshwater and generated wastewater equivalent to 96.05% of the total water consumed, revealing important limitations related to water integration and recirculation within the process configuration. From an energy perspective, the system presented a specific energy intensity of 19,929 MJ/t, with natural gas representing the predominant energy source throughout the operation. Overall, the obtained results demonstrate that the proposed process is technically viable for avocado oil production while also identifying critical opportunities for improving resource utilization, decreasing water demand, and enhancing the operational sustainability of the system. Full article