Search Results (5,470)

Developing an ultrasensitive electrochemiluminescence (ECL) detection platform remains challenging due to the limited enrichment efficiency of ECL emitters and co-reactants at the electrode interface, as well as the insufficient catalytic enhancement of co-reactant conversion. Moreover, simultaneous in situ analyte enrichment and efficient anti-interference capability are often difficult to achieve in a single sensing interface. Herein, a new ECL platform was developed based on nanocatalyst-supported nanochannel-confined surfactant micelle (SM) system, which integrates an enhanced luminol-dissolved oxygen (DO) ECL response for the ultrasensitive detection of antibiotic rifampicin (RIF). A nanocomposite comprising nitrogen-doped graphene quantum dots and a molybdenum disulfide nanosheet (NGQDs@MoS₂) was modified on an indium tin oxide (ITO) electrode. This nanocomposite layer catalyzed the oxygen reduction reaction (ORR), boosting the co-reactant efficiency of DO. Vertically ordered mesoporous silica film filled with surfactant micelles (SM@VMSF) was subsequently grown in situ on the NGQDs@MoS₂ surface. The hydrophobic micelles enable the simultaneous enrichment of luminol, DO, and RIF. Integrating the triple-enrichment effect of surfactant micelles with the high electrocatalytic effect of NGQDs@MoS₂ nanocomposite results in significant ECL enhancement of the luminol–DO. SM@VMSF also provides an excellent molecular sieving effect, endowing the sensor with high anti-interference capability and stability. RIF quenches the ECL signal by consuming superoxide anion radicals, enabling sensitive detection. Detection of RIF was established with a high sensitivity (2927 a.u. per nM) wide linear range (10 pM to 10 μM) and a low limit of detection (LOD, 2.5 pM). The fabricated sensor exhibits good selectivity and high fabrication reproducibility (relative standard deviation, RSD, of 1.9%). Additionally, the determination of RIF in eye drops and seawater samples was realized. This work offers new insights for the design of high-performance ECL sensing interfaces and sensitive detection of RIF. Full article

Background: Hepatitis C viral infection (HCV) has historically been a leading indication for liver transplantation (LTx), primarily due to its progression to cirrhosis and hepatocellular carcinoma (HCC). However, the advent of direct-acting antiviral agents (DAAs) over a decade ago has revolutionized HCV treatment, achieving sustained virologic response (SVR) in over 90% of patients and potentially altering LTx indications. Aim: To investigate the impact of DAAs on HCV-related indications, with or without HCC, and model future trends in LTx indications. Methods: We retrospectively reviewed 1504 liver transplants performed between 2000 and 2024 at a single center. Patients were categorized into three cohorts: HCV-only, HCC-only, and HCC with HCV co-infection (HCC/HCV). Relative transplant volumes by-year, post-operative outcomes, and HCC recurrence rates were analyzed across pre- and post-DAA eras. ARIMA modeling was employed to project trends in transplant indications through the year 2030. Results: The proportion of transplants for HCV alone declined by 82.3% from 2015 to 2020, while HCC/HCV transplants decreased by 68.8%. Conversely, the total number of transplants for HCC alone increased during this period, with a modest proportional decrease of 8.3% from 2015 to 2020. ARIMA modeling suggests that by 2030, LTxs for HCV alone may be nearly eliminated. The projected proportion of transplants conducted for HCC alone remains the highest of all three study indications at 4.3%. Conclusions: DAAs have reduced LTx due to HCV. By 2030, LTx for HCV-related cirrhosis, particularly without HCC, may be obviated. This underscores the need to reevaluate allocation for emerging oncologic indications. Full article

The CO₂ storage–regeneration (CO₂-SR) process represents a promising strategy for integrating CO₂ capture and catalytic conversion within a single cyclic operation using multifunctional catalysts. In this concept, CO₂ is first stored on basic sites and subsequently converted through methane activation, enabling the coupling of CO₂ capture and reforming reactions in a single reactor. In this work, a series of unsupported Ni–Ba catalysts were investigated as model multifunctional materials for the CO₂-SR process. Catalysts with different Ni/Ba ratios were prepared to analyze how the distribution of storage and catalytic sites influences the cyclic CO₂ capture–conversion behavior. In addition, Rh was introduced as a promoter either during synthesis by co-precipitation or ex situ by impregnation, allowing to evaluate the influence of Rh location and surface enrichment on the catalytic properties. Rh incorporation in the NiBa catalyst (Ni/Ba = 10/1 and Ni/Rh = 100/1) increased the specific surface area (BET area 64 m²·g⁻¹ vs. 55 m²·g⁻¹ for NiBa) and reduced the NiO crystallite size from 250.4 Å to 231.5 Å, indicating improved dispersion of the metallic phase. XPS analysis revealed the coexistence of Rh⁰ and Rh³⁺ species, suggesting that Rh acts as a redox mediator that facilitates hydrogen activation and promotes hydrogen spillover to neighboring Ni sites. Raman and CO₂-TPD results show that Ba-derived domains stabilize carbonate species responsible for CO₂ storage, while Rh enhances catalyst reducibility and modifies the kinetics of carbonate decomposition during the regeneration stage. Transient CO₂–CH₄ pulse experiments demonstrate that the CO₂-SR process proceeds through a dynamic surface cycle involving reversible carbonate formation on Ba-derived basic sites coupled with methane activation on Ni-containing interfacial sites. The results indicate that catalyst performance is governed by a hierarchical surface architecture composed of Ni–O–Ba interfacial domains, reversible Ba–O–Ba carbonate storage sites, and more stable Ba-rich domains. The distribution of these domains, controlled by the Ni/Ba ratio and the dispersion of the metallic phase, determines the reversibility of carbonate formation and the efficiency of the cyclic CO₂ storage–regeneration process. Full article

The rapid development of smart energy infrastructures and renewable energy systems requires advanced sensing solutions that provide high accuracy, expandability, and stability under real operating conditions. However, conventional gas monitoring systems are predominantly based on resistive or voltage-output sensors, which require complex analog front-end circuits and analog-to-digital conversion, leading to increased system complexity, cost, and susceptibility to electromagnetic interference. This paper tackles this limitation by proposing a frequency-domain sensing approach for multichannel monitoring of biogas plant parameters. The objective of this study is to develop and experimentally validate an extendable sensing architecture based on autogenerator microelectronic gas transducers with direct gas concentration–frequency conversion and FPGA-based digital acquisition. The proposed method is grounded in a physical–mathematical model of the space-charge capacitance of gas-sensitive semiconductor structures derived from Poisson’s equation, facilitating analytical formulation of conversion and sensitivity functions. A multichannel FPGA-based measurement system is implemented to process frequency signals without analog conditioning or ADC stages. Experimental validation was performed for CH₄ (0–85%), CO₂ (0–60%), H₂, NH₃, and H₂S (1–20,000 ppm). The results demonstrate measurement uncertainty within 0.25–0.5%, with sensitivity reaching 350–748 Hz/ppm for H₂, 455–750 Hz/ppm for NH₃, and 253–375 Hz/ppm for H₂S, while methane and carbon dioxide sensitivities reach up to 112 kHz/% and 98.7 kHz/%, respectively. Spectral analysis in the LTE-1800 band confirms improved noise immunity (up to 4.5×) and extended transmission capabilities. A 12-channel FPGA-based monitoring system (RDM-BP-1) with a 1 s sampling interval, IP67 protection, and wireless connectivity is developed and validated. The proposed architecture eliminates analog signal conditioning, reduces hardware complexity, and provides an easily expandable and reliable sensing solution for smart buildings, renewable energy systems, and cloud-integrated energy infrastructures. Full article

The widespread integration of wind energy conversion systems has fundamentally reshaped modern power grid architecture. However, the limited dynamic response of wind turbine (WT) converters during grid faults—particularly their inability to provide sufficient reactive current and maintain voltage stability under severe dips—necessitates a redefinition of the conventional low-voltage ride-through (LVRT) curve. This study addresses this challenge by proposing a Mutation-Adaptive Mean Variance Mapping Optimization (A-MVMO) algorithm for the control of grid-side converters (GSCs) in wind farms (WFs). To systematically assess post-fault voltage recovery, a Time-Segmented Analysis for Voltage Recovery (T-SAVR) approach is developed with a multi-objective function. The performance of the proposed A-MVMO is benchmarked against standard MVMO and conventional particle swarm optimization (PSO) under both moderate (0.7 pu) and severe (0.15 pu) voltage dips using the IEEE 39-bus system implemented in DIgSILENT/PowerFactory. The results demonstrate that A-MVMO achieves fast, oscillation-free voltage recovery with negligible overshoot (<1%) and lower current injection than PSO and MVMO, while satisfying all engineering constraints. Moreover, the co-optimization of Park-level and turbine-level controllers ensures seamless coordination, as evidenced by the close tracking between the farm-wide reactive power reference and the aggregated turbine response. The T-SAVR method proves essential for focusing optimization on controllable recovery dynamics, yielding a superior LVRT curve. Full article

Currently, the main method for producing the vitamin C precursor 2-keto-l-gulonic acid (2-KLG) is a two-step fermentation process, in which secondary sterilization and fermentation processes result in higher costs and energy consumption. Consequently, the development of a one-step fermentation process is seen as a more desirable approach for 2-KLG production. In this study, we used Gluconobacter oxydans WTF0512 and Ketogulonicigenium vulgare WTF0114 as co-cultured strains for the production of 2-KLG from d-sorbitol via one-step fermentation. The fermentation behaviors of G. oxydans WTF0512 and K. vulgare WTF0114 were initially investigated. Subsequently, the fermentation process and medium were optimized, and the titer of 2-KLG reached 132.99 ± 0.52 g/L, with a molar conversion rate of 92.42%, which, to the best of our knowledge, is the highest production via one-step fermentation reported to date. These findings will provide a basis for developing a more economical large-scale one-step fermentation process for the production of 2-KLG. Full article

Background: Hematological patients have a high risk of developing severe COVID-19 (37%). Most mRNA vaccine trials in hematological patients showed a low immunogenicity after two doses, while long-term data are scarce. Methods: In this monocentric retrospective observational study, we evaluated humoral and T cell-mediated immune responses in 230 hematological patients after three doses of the Pfizer-BioNTech mRNA COVID-19 vaccine. Patients were stratified by age, disease type/state, prior COVID-19 infection, and treatment status and regimens (anti-CD20 monoclonal antibodies, BTK and BCL-2 inhibitors, and treatment line). Antibody titer to SARS-CoV-2 was assessed by electrochemiluminescence immunoassay and T cell response by QuantiFERON interferon-γ release assay (IGRA). Data were analyzed using univariate (Fisher’s exact test) and Firth’s bias-reduced penalized-likelihood logistic regression. Results: A robust humoral response was observed with 91.55% of patients developing anti-spike antibodies (GMT 988.83 U/mL). Anti-CD20-bendamustine treatment was associated with a significantly lower antibody positivity compared to untreated subjects. Prior COVID-19 infection significantly boosted both antibody positivity (95.9% vs. 85.2%) and GMT (847.02 U/mL vs. 258.79 U/mL). Conversely, T cell response was suboptimal (36.1% positive), particularly in anti-CD20-bendamustine-treated and multi-treated patients (27.1%), but highest in those treated with BTK inhibitors (50%). Multivariable logistic regression analysis linked multiple treatments to lower T cell response. Following vaccination, 29.1% of patients contracted SARS-CoV-2, but only 0.89% developed severe COVID-19. Conclusions: Three doses of mRNA vaccine elicit a strong humoral but a low T cell response, as detected by IGRA, in hematological patients. These findings underscore the importance of completing vaccination before initiating immunosuppressive therapies. Full article

Achieving Great Britain’s 2050 net-zero target requires strategic integration of hydrogen into the national energy system. This study evaluates the system-wide impacts of hydrogen blending (0–100%) using a bi-level optimisation framework that combines long-term cooperative investment planning with short-term operational Optimal Power and Gas Flow (OPGF) simulation. The strategic layer models infrastructure investment decisions under a cooperative game-theoretic structure, where system value is allocated among electricity, hydrogen production, and storage technologies using the Shapley-value payoff mechanism. Contrary to traditional centralised cost-minimisation models, our findings demonstrate that a cooperative planning structure identifies superior transition pathways. Comparative results reveal that at 100% hydrogen penetration, the cooperative framework reduces total system CO${}_2$ emissions by 31%, lowers operational costs by 26%, and decreases total electricity supply requirements by 8% relative to centralised planning. Furthermore, the cooperative approach significantly enhances economic resilience, yielding a more robust Net Present Value (NPV) across all blending levels compared to centralised planning, while ensuring project profitability at lower blending thresholds (20%) where traditional models remain loss-making. Simulation results indicate that hydrogen blending up to 20% maintains operational stability with manageable increases in operational cost. Full hydrogen conversion (100%) increases peak electricity supply requirements by approximately 30% relative to low-blending scenarios due to electrolysis-driven load expansion and conversion losses. The findings demonstrate that hydrogen blending represents a viable transitional pathway when supported by integrated infrastructure development and cooperative stakeholder coordination, enabling a more efficient and economically sustainable phased progression towards Great Britain’s 2050 net-zero target. Full article

Producing single-cell protein (SCP) from syngas-derived ethanol and acetate offers a sustainable solution to global protein shortages, yet microbial utilization mechanisms for these mixtures remain underexplored. This study establishes a systematic bioconversion strategy using Cyberlindnera jadinii TU389. To mitigate acetaldehyde accumulation during ethanol metabolism, we engineered the strain TU546 to overexpress acylating acetaldehyde dehydrogenase (ADA6). TU546 achieved a maximum biomass of 46.7 g/L and a protein yield of 21.69 g/L, representing enhancements of 28.16% and 23.02% over the wild-type, respectively. Transcriptomic analysis revealed extensive metabolic reprogramming. In the C2 assimilation pathway, upregulated aldehyde dehydrogenase and acetyl-CoA Synthetase 1 accelerated acetate conversion to acetyl-CoA, while downregulated pyruvate decarboxylase and alcohol dehydrogenase minimized carbon flux loss. The upregulation of tricarboxylic acid cycle enzymes, the glyoxylate shunt, and acyl-coA oxidase improved carbon skeleton retention. Moreover, the upregulation of transaminases and N-acetylglutamate synthase, synergized with intensified cell proliferation signaling, redirected amino acid metabolism toward a synthesis-enhanced and degradation-controlled paradigm. This synergistic regulatory network drives the high-efficiency bioconversion of ethanol and acetate into SCP, establishing a molecular mechanistic foundation for the valorization of syngas-derived C2 substrates in biological macromolecule production. Full article

Biomass pyrolysis has emerged as a flexible platform for converting low-value residues into higher-value energy carriers (bio-oil, biochar and gas) and carbon-rich materials, with realistic potential for negative emissions when biochar is deployed in long-lived sinks. Over the last decade, three developments have driven the field forward: first, a finer mechanistic understanding of devolatilization and secondary reactions; second, major improvements in analytical techniques for characterising feedstocks and products; and third, more rigorous techno-economic and life-cycle assessments that place pyrolysis in a broader energy-system context. Recent experimental work on forestry and agro-industrial residues has clarified how biomass composition, ash chemistry and operating conditions jointly govern product yields, energy content and stability. Parallel advances in GC×GC–MS, high-resolution mass spectrometry, NMR and thermogravimetric methods have shifted the discussion from bulk “bio-oil” and “char” to families of molecules and well-defined structural domains, which can be deliberately targeted by reactor and catalyst design. Data-driven models, ranging from support vector machines applied to TGA curves to ANFIS and random forests for yield prediction, are now accurate enough to support process screening and multi-objective optimisation. At the system level, commercial fast pyrolysis biorefineries report overall useful energy efficiencies on the order of 80–86%, while slow pyrolysis configurations centred on biochar can be economically viable when carbon storage and co-products are appropriately valued. Thermodynamic analyses confirm that indirect gasification via fast-pyrolysis oil sacrifices some energy and exergy efficiency relative to direct solid-biomass gasification but may offer logistical and integration advantages. This review synthesises recent work on (i) feedstock and process characterisation; (ii) state-of-the-art analytical methods for bio-oil, biochar and gas; (iii) modelling and machine-learning tools; and (iv) energy-system deployment of pyrolysis products. Throughout, the emphasis is on how characterisation and modelling inform concrete design choices and on the trade-offs that arise when pyrolysis is considered as part of a wider decarbonisation portfolio. By integrating laboratory-scale characterisation with system-level modelling, this review aligns biomass pyrolysis with several United Nations Sustainable Development Goals (SDGs). The optimisation of thermochemical conversion pathways for forestry and agro-industrial residues directly supports SDG 7 (Affordable and Clean Energy) by enhancing the efficiency of bio-oil and syngas production. Furthermore, the deployment of biochar as a stable carbon sink for negative emissions and soil amendment addresses SDG 13 (Climate Action) and SDG 15 (Life on Land). By converting low-value waste streams into high-value energy carriers and chemicals within a circular bioeconomy framework, the research further contributes to SDG 12 (Responsible Consumption and Production) and SDG 9 (Industry, Innovation and Infrastructure). Full article

Copper anodic slime is often smelted with lead to improve silver and gold recovery, generating a fine lead-rich fly ash that contains notable amounts of selenium and tellurium. Due to its high lead content and sub-micron particle size, this residue poses significant environmental and occupational health risks. This study evaluates sodium carbonate (Na₂CO₃) leaching as an environmentally benign pre-treatment aimed at partially removing selenium and tellurium while stabilizing lead through carbonate formation. The goal is detoxification rather than maximum metal recovery, enabling safer disposal or subsequent recycling. A central composite design (CCD) in Design-Expert software (Version 12) was used to assess the effects of Na₂CO₃ concentration, temperature, solid-to-liquid ratio, and time on selenium and tellurium dissolution. Selenium recovery reached up to 53.9%, while tellurium recovery peaked at approximately 33.9%. Scanning electron microscopy showed the dust to consist mainly of semi-spherical and elongated particles, with lead carbonate forming preferentially on particle surfaces during leaching. Energy-dispersive spectroscopy confirmed conversion of lead sulfate phases to lead carbonate, which increasingly restricted selenium and tellurium dissolution. Kinetic evaluation suggested selenium leaching follows mixed control involving both surface reaction and diffusion through product layers, whereas tellurium dissolution lacked consistent kinetic behavior. Thermodynamic calculations supported the stabilization of lead as cerussite (PbCO₃), indicating improved environmental safety. The overall dissolution trends were successfully represented using an apparent Shrinking Core Model (SCM) based on measurements collected at 20 °C, 60 °C, and 100 °C. Full article

Background/Objectives: The coronavirus disease 2019 (COVID-19) pandemic profoundly disrupted global respiratory virus circulation, with sharp declines during 2020–2021, followed by a resurgence after the relaxation of public health measures. In South America, post-pandemic respiratory virus dynamics remain insufficiently characterized, particularly in ecologically diverse regions. Arequipa, a high-altitude city in southern Peru, has unique environmental conditions, including marked seasonal temperature variability, that may influence viral transmission. Methods: We performed a cross-sectional analysis of 21,784 nasopharyngeal swabs collected from symptomatic patients at four major hospitals between June 2021 and September 2023. All samples were tested for SARS-CoV-2 by RT-qPCR. Because routine screening for other respiratory viruses was implemented only in SARS-CoV-2-negative cases during the study period, a subset of SARS-CoV-2-negative samples was subsequently analyzed for influenza A virus (IAV), influenza B virus (IBV), and respiratory syncytial virus (RSV) using VIASURE assays. Viral circulation patterns were evaluated by year, month, and epidemiological week. Meteorological data were obtained from the SENAMHI–La Pampilla station. Logistic regression models were used to assess epidemiological and climatic predictors of viral detection. Results: SARS-CoV-2 positivity declined from 20.0% in 2021 to 8.8% in 2023. Conversely, detection of other respiratory viruses among SARS-CoV-2-negative samples increased from 0.8% in 2021 to 29.0% in 2023 (p < 0.01). Temporal increases in detection were observed during 2022–2023, particularly for IAV and RSV. In exploratory analyses, calendar year and relative humidity were associated with IAV and RSV detection, while age and temperature variables were associated with IBV. Conclusions: Climatic and demographic variables were associated with changes in viral detection for IAV, IBV, and RSV during the post-pandemic transition period in Arequipa. These findings describe patterns of viral detection within SARS-CoV-2-negative symptomatic patients and should be interpreted as surveillance-based observations rather than population-level estimates. Strengthened integrated epidemiological and genomic surveillance will be essential for vaccine planning and outbreak preparedness in the post-pandemic era. Full article

To address the poor adaptability and rigid initiation modes of the loitering munition fuze in complex environments and the inadequacy of single fuzzy control against strong interference, this paper proposes a dual-loop adaptive reconfiguration control method. The architecture integrates the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm with fuzzy logic. The inner loop uses TD3 to dynamically optimize fuzzy scaling factors based on real-time interference and state deviations. Concurrently, the outer loop utilizes a Fuze Readiness Index (FRI) and a finite state machine to manage real-time multi-modal mission switching (e.g., proximity, delay, and airburst) and reverse safety-state conversions. Co-simulations under non-stationary composite interference show that the proposed method reduces the burst height RMSE by 82.4% and 61.6% compared with the fixed-threshold and standard fuzzy baselines under the considered non-stationary composite interference setting, respectively. The false alarm rate (FAR) is reduced to 0.15%, and the reconfiguration response time under sudden interference is shortened to 12 ms. Even under extreme conditions, such as 400 ms sensor signal loss, the relative error remains within 5%. These simulation results demonstrate the potential of the proposed architecture to improve precision, responsiveness, and robustness under dynamic interference conditions and show good robustness to intermittent observation loss within the simulated operating envelope. Full article

To address the issues of high wastewater treatment costs and the lack of recycling associated with conventional precipitants such as oxalic acid and ammonium bicarbonate in rare earth precipitation processes, this study proposes a novel gradient alkali conversion–carbonation method based on a green process coupling “rare earth chloride alkali conversion-carbonation with sodium chloride electrolysis.” The primary scientific objective is to elucidate the crystallization mechanism and to achieve controlled preparation of high-quality lanthanum carbonate. By gradient-controlling the addition sequence and rate of alkali liquor and CO₂, lanthanum carbonate tetrahydrate was successfully synthesized. Characterization by XRD, SEM, ICP, and laser particle size analysis indicates that the product prepared by the gradient alkali conversion–carbonation method exhibits a single phase with high crystallinity, as evidenced by sharp and clear XRD diffraction peaks. Furthermore, the median particle size of the product obtained via this method is relatively large, reaching approximately 10 μm, while the particle size distribution Span value remains around 1.0. Mechanistic studies suggest that this method effectively regulates the crystallization process by precisely controlling the introduction and slow dissolution of the La(OH)₃ precursor, thereby reducing the supersaturation of the system during carbonation and facilitating the dissolution–reprecipitation of La³⁺. This work provides a theoretical basis for the preparation of high-quality rare earth carbonates and a process reference for the green recycling route. Full article