Search Results (5,642)

The increasing demand for lithium-ion batteries (LIBs) raises concerns about the security of critical raw material supply and the management of hazardous waste. Efficient recycling can alleviate these issues by transforming spent batteries into high-value secondary materials for the circular economy. Industrial recycling has traditionally focused on the recovery of nickel (Ni) and cobalt (Co), whereas lithium (Li) recovery has often been sidelined due to technical complexities and fluctuating economic incentives. To meet the European Union (EU) Batteries Regulation target of 80% lithium recovery by the end of 2031, technically effective and economically viable lithium recovery strategies are required. This study investigates the use of food-grade sucrose as an organic reductant for the targeted recovery of lithium from NMC622 and NCA battery materials. The process combines sucrose-assisted reductive roasting with selective water leaching. The effects of roasting temperature, holding time, sucrose dosage, and heating rate were systematically evaluated and optimised. Under the best conditions of 600 °C, 15 min, 15 wt% sucrose, and a heating rate of 20 °C/min, lithium leaching efficiencies of 93.2% and 87.6% were achieved for separated NMC622 cathode material and NMC622-derived black mass, respectively. The method was also applicable to NCA-based black mass, reaching 83.7% lithium recovery under the same conditions. Mechanistic analysis revealed that lithium release was strongly controlled by the extent of transition metal reduction. Cobalt was fully reduced to its metallic state under all tested conditions. However, maximum lithium recovery required nickel to be reduced to metallic Ni and manganese-containing phases to be converted to MnO. The sucrose-assisted roasting process was rapid and holding times longer than 15 min decreased lithium recovery. This decrease was caused by the formation of poorly soluble lithium-containing phases, such as LiF and Li₃PO₄. F composition analysis showed the black mass (1.06 wt%) and anode fractions (2.26 wt%) to contain significantly more F than the cathode fraction (0.46 wt%), hence leading to the 5% Li leaching efficiency difference between cathode and black mass fractions under most conditions tested. Overall, these results demonstrate that sucrose-assisted reductive roasting, followed by selective water leaching, provides a rapid and effective route for high-efficiency lithium recovery from NMC- and NCA-based battery materials. Full article

Accurate measurement of serum uric acid (UA) is critical for disease assessment and therapeutic monitoring; however, numerous factors can compromise the accuracy of UA detection. This study describes a novel circulating immunoglobulin M (IgM)-involved protein complex that interferes with the uricase method and reduces serum UA measurement accuracy. A total of 24 serum samples were collected from 18 patients, and complete clinical information and laboratory data were obtained. Samples were divided into three groups according to their UA reaction curves. Optical density values were extracted to analyze differential insoluble properties, serum viscosity was measured, coimmunoprecipitation was performed for IgM complex detection, and three additional clinical methodologies were used for UA measurement and comparison. All samples exhibiting unique reaction curves showed simultaneous elevations in IgM and complement component 4 (C4) levels. Circulating IgM formed a protein complex with C4d without significantly increasing serum viscosity. The insolubility of the IgM–C4d complex was attributable to the particular alkaline component of the uricase reagent. Inaccurate UA measurements could only be corrected by mass spectrometry. This study represents the first report of the circulating IgM–C4d protein complex. Given that serum UA serves as a crucial therapeutic indicator for specific patient populations, mass spectrometry is the preferred analytical method for accurate UA quantification in these individuals. Full article

Background/Objectives: Mass spectrometry-based newborn screening for small-molecule biomarkers typically employs a rapid first-tier screen that omits chromatographic separations before mass spectrometric analysis, followed, only for a subset of samples and disorders, by a longer, more specific second-tier assay that includes liquid chromatographic separation prior to mass spectrometry. The second-tier screen is used when the primary biomarker lacks sufficient specificity and may result in higher false-positive rates. The throughput and specificity of first-tier newborn screening assays have been relatively stagnant over the past two decades despite significant improvements in mass spectrometry instrumentation. With the continuous expansion of disorders added to the Recommended Uniform Screening Panel in the United States, newborn screening laboratories have a need for higher-throughput assays and improved specificity. Methods: We developed and evaluated two first-tier tandem mass spectrometry approaches using a modern dual-needle, dual-loop LC-MS/MS platform: (1) a 30-s flow injection analysis tandem mass spectrometry (FIA-MS/MS) assay and (2) a rapid first-tier liquid chromatography tandem mass spectrometry (LC-MS/MS) assay using a hydrophilic interaction chromatography (HILIC) guard column (1TH). Analytical performance was assessed using dried blood spot quality control and linearity materials, including evaluations of recovery, precision, linearity, and matrix effects. Results: The 30-s FIA-MS/MS assay quadrupled the throughput of current 2-min FIA-MS/MS assays used routinely in newborn screening laboratories. The throughput improvement was achievable due to increased scan speeds of the mass spectrometer as well as the dual needle/loop design of the autosampler. In addition, these instrumentation improvements made it possible to employ liquid chromatographic separations prior to MS/MS analysis without sacrificing the approximately 2-min sample-to-sample throughput of conventional FIA-MS/MS workflows. The 1TH LC-MS/MS method separated critical isobaric and isomeric biomarkers, reduced matrix effects, improved specificity and quantification accuracy, and demonstrated acceptable recovery, precision, and linearity for newborn screening applications. Conclusions: Recent advances in LC-MS/MS instrumentation can be leveraged to either substantially increase first-tier newborn screening throughput or improve analytical specificity while maintaining current workflow timelines. First-tier LC-MS/MS using a HILIC guard column provides improved specificity that can reduce the need for second-tier testing, thereby improving overall throughput and turnaround time of the newborn screening workflow. These approaches provide flexible solutions for newborn screening laboratories seeking to accommodate expanding screening panels without compromising analytical quality or efficiency. Full article

Background: Menopause represents a critical physiological transition associated with hormonal changes that influence both metabolic health and quality of life (QoL). Metabolic dysfunction-associated steatotic liver disease (MASLD), a common metabolic condition, is closely linked to menopause; however, its independent contribution to QoL impairment remains unclear. This study aimed to investigate the interplay between menopausal status, metabolic dysfunction, MASLD, and QoL in midlife women. Methods: A cross-sectional observational study was conducted including 80 women aged 45–55 years, comprising both premenopausal and menopausal participants. Clinical, anthropometric, biochemical, and imaging data were collected. MASLD was diagnosed using magnetic resonance imaging in the presence of metabolic dysfunction. Metabolic assessment included glucose, insulin, liver enzymes, C-reactive protein, and indices of insulin resistance (HOMA-IR) and sensitivity (QUICKI). QoL was evaluated using the Utian Quality of Life (UQOL) scale. Associations were examined using univariate and multivariable linear regression models. Results: MASLD prevalence was significantly higher in menopausal women compared with non-menopausal women (61.9% vs. 15.8%, p < 0.001). Metabolic parameters, particularly insulin resistance and body mass index, were strongly associated with MASLD. The mean total UQOL score indicated moderate QoL. In multivariable analysis, menopausal status was the only independent predictor of reduced total QoL (b = −4.93, p = 0.01) and occupational health domain (b = −4.60, p = 0.001). MASLD and metabolic parameters were not independently associated with overall QoL. Correlation analyses revealed modest associations between metabolic markers and specific QoL domains, particularly occupational and physical health. Conclusions: Menopause is the primary determinant of reduced QoL in midlife women, particularly affecting functional domains, while MASLD does not independently impact QoL despite its strong association with metabolic dysfunction. These findings suggest that menopausal status may play a more prominent role in quality-of-life outcomes than MASLD in women undergoing the menopausal transition. However, the cross-sectional design does not allow conclusions regarding causal or mechanistic relationships. Full article

Leftover spaces, often associated with neglected urban corners, bear physical and conceptual similarities to ignored parts of designed wholes. This study proposes an analytical approach to develop resilient intervention strategies by analyzing the production of leftover spaces through users’ emotional experiences. An experimental pilot study was conducted along Söğütlüçeşme Street in Kadıköy, Istanbul, where all corner points were typologically classified based on morphological characteristics. To measure the impact of these configurations on spatial emotional characters, a survey was implemented using Plutchik’s wheel of emotions. Following a quantitative analysis of emotion frequencies and intensities, findings were visualized via radar charts and spatialized using QGIS 3.40 to generate an emotional map. The resulting emotional maps were further used to identify spatial vulnerabilities and resilience priorities across the study area. By making the gaps between point-based emotional clusters continuous through the IDW interpolation method, the emotional topography of the study area was modeled, thereby presenting an analytical framework that identifies emotional thresholds, spatial vulnerabilities, and resilience priorities. Results indicate that as the physical boundaries of corner voids expand, influenced by angling and massing decisions, public diversity increases, creating a positive emotional atmosphere. Conversely, compressed voids demonstrate a higher potential for producing leftover spaces. This study reveals that mapping user emotions as a data layer is critical for constructing more inclusive and resilient urban environments. Full article

The environmentally sustainable decontamination of chemical warfare agents (CWAs) remains a critical challenge. This study reports the solar-driven photocatalytic degradation of live CWAs—GD, HD, HN1, and HN2—using titanium dioxide (TiO₂) under natural sunlight. Experiments were conducted in an OPCW-designated laboratory to ensure authenticity and practical relevance. TiO₂ exhibited substantial photocatalytic activity, achieving 60% degradation of GD, 63% of HD, 76% of HN1, and 93% of HN2 after 6 h. High-resolution mass spectrometry (HR-MS) analysis suggested plausible degradation pathways for nitrogen mustards consistent with the higher apparent reactivity of HN2; detailed identification of intermediates and reactive oxygen species remains a subject for future investigation. These findings provide mechanistic insights into the photocatalytic behavior of nitrogen-based agents and address a notable gap in studies that have largely focused on sulfur mustards and nerve agents. Beyond military applications, this solar-assisted photocatalytic approach provides mechanistic information relevant to the green remediation of highly toxic organic contaminants and broader chemical hazard mitigation. This work contributes foundational knowledge toward eco-friendly decontamination technologies capable of mitigating diverse CWA threats. Full article

This study aimed to explore the correlations of nuclear factor erythroid 2-related factor-2 (NRF2) gene polymorphisms, prepregnancy body mass index (BMI) and the interaction between them with the risk of preeclampsia (PE). A case–control study was conducted in which pregnant women with PE (n = 198) and normotensive pregnant women (n = 396) were recruited as the case group and control group, respectively, from two tertiary hospitals in Hunan Province. Data collection was achieved through face-to-face interviews utilizing a standardized questionnaire, along with perinatal health care records. Blood samples were also collected, and genotyping of nine single-nucleotide polymorphisms (SNPs) in the NRF2 gene was subsequently performed using the MassArray platform. Both univariate and multivariate logistic regression analyses were employed to assess the associations of NRF2 gene polymorphisms with prepregnancy BMI and their interactions with the risk of PE. Multivariate logistic regression analyses revealed a significant association between prepregnancy BMI and PE susceptibility. Specifically, prepregnancy overweight/obesity (BMI ≥ 24.0 kg/m²) was associated with an elevated risk of PE (adjusted OR = 4.59, 95% CI: 2.82–7.45), whereas underweight status (BMI < 18.5 kg/m²) was correlated with a reduced PE risk (adjusted OR = 0.38, 95% CI: 0.18–0.78). The NRF2 polymorphism rs13005431 exhibited a protective effect against PE under the additive genetic model (adjusted OR = 0.59, 95% CI: 0.37–0.93). Furthermore, logistic regression analyses revealed a significant effect of the multiplicative interaction between prepregnancy overweight/obesity and polymorphisms rs35652124 (adjusted OR = 0.24, 95% CI: 0.06–0.89) and rs2627765 (adjusted OR = 3.62, 95% CI: 1.07–12.23) on susceptibility to PE. These findings collectively underscore the critical and independent roles of prepregnancy BMI, NRF2 polymorphisms, and their interactions in modulating PE susceptibility, suggesting that the combined effects of metabolic profiles and genetic determinants may act synergistically to shape PE risk. Full article

The issue of water resources in a semi-arid country such as Morocco has been present for many years and is becoming increasingly critical. The droughts experienced over recent decades have demonstrated the country’s extreme vulnerability to any water deficit. In this context, the Berrechid plain represents a relevant case study illustrating both the practical and theoretical challenges of groundwater governance. The aquifer is heavily exploited to satisfy agricultural, industrial, and domestic needs. This study develops a hybrid “grey-box” modeling approach for predicting groundwater depth (GWD) fluctuations under climate change (CC). Unlike conventional black-box machine learning models, our framework combines a deterministic physical engine with a stochastic machine learning corrector. The physical component simulates aquifer mass balance using the Hargreaves method for evapotranspiration, linear drainage, climate memory via exponential decay, and an anthropogenic trend parameter (xi). The machine learning component—XGBoost with quantile regression—is trained exclusively on physical model residuals and predicts the 5th, 50th, and 95th percentiles, providing explicit 90% confidence intervals. Hydrological states (dry, normal, wet) are identified via K-means clustering for context-aware correction. The model is calibrated using historical data (1972–2019) and validated using blocked time-series cross-validation. Climate projections under the RCP 4.5 and RCP 8.5 scenarios were used to forecast GWD up to 2100. At piezometer 3933/20, the best performance was achieved, with an RMSE of 0.347 m and a KGE of 0.742 during the validation period. The proposed approach is suitable for seasonal GWD forecasting and offers practical value for water managers and decision-makers in the Berrechid region. Full article

Background: Accurate assessment of neonatal sleep is critical for monitoring brain development and identifying potential neurological disorders, yet manual scoring of multi-channel EEG recordings is labor-intensive and prone to variability. Methods: To address this, we propose a lightweight temporal–spatial feature fusion network for automatic neonatal sleep staging. The model employs a dual-branch architecture to separately capture temporal dependencies and spatial correlations in EEG signals, which are then integrated through feature concatenation and a compact classifier to obtain comprehensive feature representations while maintaining low computational complexity. Results: The framework was evaluated on a clinical neonatal dataset (CHFD) for tasks including sleep–wake classification, quiet sleep detection, and three-stage sleep staging, achieving superior performance compared with several state-of-the-art methods. Additional evaluation on the MASS-S3 adult dataset demonstrate that the model retains competitive accuracy and F1-score, indicating strong generalization across populations. Conclusions: These results suggest that jointly modeling temporal and spatial features enables robust and efficient automatic sleep staging. The proposed approach offers a practical solution for clinical applications and edge deployment, providing reliable, multi-dimensional assessment of neonatal brain activity and laying the groundwork for future studies integrating larger datasets or multimodal physiological signals. Full article

Al-Cu-Fe quasicrystalline coatings were deposited on AISI 321 stainless steel substrates by high-velocity oxy-fuel (HVOF) spraying at oxygen pressures of 3.0, 3.5, and 4.0 bar. The influence of oxygen pressure on the phase composition, microstructure, porosity, corrosion behavior, thermal stability, and microhardness of the coatings was investigated using X-ray diffraction (XRD), scanning electron microscopy coupled with energy-dispersive spectroscopy (SEM/EDS), ImageJ porosity analysis, electrochemical corrosion testing in 3.5 wt.% NaCl solution, simultaneous thermal analysis (TGA/DSC), and microhardness measurements. XRD analysis revealed the formation of quasicrystalline-related intermetallic phases together with Al, Fe₃Al₁₃, FeAl, Fe₃O₄, CuFe₂O₄, Cu₂O, and CuO phases. The coating deposited at 3.5 bar exhibited the lowest porosity (5.37%), the most homogeneous microstructure, and the largest residual coating thickness after corrosion testing. SEM and EDS analyses indicated that corrosion preferentially initiated at pores, splat boundaries, and phase interfaces, while the coating produced at 3.5 bar demonstrated the most stable surface condition after exposure to a 3.5 wt.% NaCl solution. Thermal analysis showed that all coatings remained stable up to 900 °C. Sample (a) exhibited the lowest mass loss and the highest thermal stability, whereas sample (b) demonstrated the most favorable combination of structural integrity, phase ordering, coating density, corrosion-related performance, and thermal stability. Microhardness values of the coatings ranged from 754 to 778 HV, significantly exceeding that of the AISI 321 substrate. The results demonstrate that oxygen pressure is a critical parameter controlling the microstructure and functional properties of HVOF-sprayed Al-Cu-Fe coatings, with 3.5 bar providing the most balanced set of properties. Full article

Mie lidar has been profoundly applied in the profiling of aerosol optical coefficients in atmosphere. However, few studies further explore quantitative strategies for the retrieval of aerosol mass profiles from lidar observation. To address the growing need for spatial and temporal aerosol mass data, a synergic retrieval algorithm for simultaneously profiling the aerosol extinction coefficient and mass composition from spaceborne dual-channel lidar data is proposed. By constructing the relationship between mixed aerosol mass profiles and extinction coefficients at different wavelengths by a forward model, additional constraints are induced to improve the accuracy of lidar ratio, which is a critical parameter for the retrieval of aerosol extinction coefficients by solving the lidar equation. Meanwhile, aerosol composition profiles can also be deduced based on the a priori estimation of aerosol compositions and intrinsic optical features of the aerosols. This method is first applied in simulated data with wavelengths at 532 nm and 1064 nm. The simulations are based on the reanalysis data of aerosol mass concentration profiles in Inner Mongolia, China. Compared with the classic Fernald method using empirically estimated lidar ratio, the proposed method improves the accuracy of column-integrated aerosol extinction coefficients (also known as aerosol optical depth, AOD) by 19.58% at 532 nm and 3.57% at 1064 nm. The accuracy for column dust and sulfate aerosols is enhanced by 12.46% and 17.58%, respectively. Further validation with CALIOP observations suggests that the proposed method produces improved extinction results and reliable aerosol composition information. Full article

In 2022, the World Health Organization (WHO) published the Fungal Priority Pathogens List (FPPL), yet its application has remained largely focused on human medicine, with limited consideration of animal hosts and veterinary diagnostics. This retrospective study aimed to characterise the occurrence of WHO critical- and high-priority yeasts in veterinary clinical submissions in Portugal within an explicit One Health framework. All yeast-positive submissions received by a Portuguese veterinary diagnostic laboratory between 2019 and 2026 were reviewed. Isolates were identified phenotypically, by an automated identification system and by MALDI-TOF mass spectrometry. Data on host species, sample type and year of submission were analysed using standard descriptive and inferential statistics. Among 2033 mycological submissions, 219 were yeast-positive. Out of these, 82 isolates (37.4%) corresponded to WHO critical- or high-priority taxa, most frequently Candida albicans, followed by Nakaseomyces glabratus, Cryptococcus neoformans var. neoformans, the Candida parapsilosis complex and Candida tropicalis. The remaining 137 isolates (62.6%) corresponded to non-WHO taxa, among which the most frequent were Papiliotrema laurentii and Debaryomyces hansenii (n = 21 each; 15.3%), followed by the Stephanoascus ciferrii complex (n = 15; 11.0%), Meyerozyma guilliermondii and Candida sake (n = 12 each; 8.8%), and Wickerhamomyces anomalus (n = 9; 6.6%). WHO-prioritised taxa were recovered predominantly from ornamental birds, as well as from dogs, cats and marine mammals. These findings demonstrate that FPPL-listed yeasts are regularly detected among yeast-positive veterinary diagnostic submissions and highlight ornamental birds as prominent hosts within this dataset. Full article

To address the critical challenge of 0–100 Hz low-frequency vibration control for marine hydraulic pipelines, this paper proposes a dedicated fiber-reinforced magnetorheological elastomer (MRE) isolator and a genetic algorithm-optimized fuzzy control strategy utilizing the magnetically tunable properties of MREs. An upper-lower split-type isolator is designed to suppress axial and radial vibrations through the shear and Compression Modes of MRE, respectively, and a two-degree-of-freedom (2-DOF) dynamic model is established to analyze the effects of mass ratio and natural frequency ratio on the system’s amplitude magnification factor. A Mamdani-type fuzzy controller, with acceleration error and its rate of change as inputs and control voltage as output, is optimized via a genetic algorithm. Simulation and experimental results show that 31–56.5% amplitude attenuation is achieved under 25–35 Hz single-frequency excitation; 12 dB isolation in the 5–23 Hz band at the input end and a maximum 15 dB isolation in multiple bands for the suspended pipeline section are obtained without external forced excitation; and efficient 0–100 Hz full-band isolation is realized at an applied current of 1.5 A. This work verifies the effectiveness of the proposed scheme for low-frequency vibration control of marine hydraulic pipelines. Full article

Background: Confident chemical annotation in nontarget small-molecule mass spectrometry critically depends on the availability of high-quality tandem mass spectral (MS²) reference libraries. While community efforts have driven significant expansion of open-access repositories, technical challenges in assembling standardized, metadata-rich records continue to limit broader participation, underscoring the need for improved computational tools to assist contributors. Methods: To promote the creation and sharing of standardized reference MS² spectral records, we have developed Librarian, a free, open-access web application designed for rapid and scalable assembly of high-resolution MS² libraries. Librarian integrates automated retrieval and harmonization of chemical identifiers and metadata from PubChem, compound mixture design for high-resolution mass spectrometry (HRMS) acquisition, and assembly of curated MS² spectra into repository-ready records compatible with public spectral databases. Results: Through a simple in-browser interface, Librarian offers a flexible end-to-end workflow compatible with popular open-source pre-processing tools to lower technical barriers and facilitate broader community participation in library development. As a demonstration, we used Librarian to create and deposit a spectral library comprising over 1500 new MS² records into MassBank, which was further applied in retrospective analysis of environmental datasets. Conclusions: Librarian streamlines the creation of standardized, metadata-rich and repository-ready MS² reference records. Addressing a key bottleneck in community spectral library development and sharing, Librarian supports the continued growth of open-access resources for metabolomics, exposomics, and environmental mass spectrometry. The Librarian web application is publicly accessible via the SciLifeLab Serve platform. Full article

Large-reclined seating has emerged as a favored configuration in the luxury transport sector. While the static advantages are evident, the effect of this posture on dynamic comfort is not clear. This study investigated the objective biodynamics and subjective discomfort of the human body sitting in a large-reclined posture (58° from the vertical) under single axis vertical and lateral vibration excitations. The transmissibility of the human–seat system and apparent mass of the human body were measured respectively. The results revealed a critical transition between static and dynamic comfort: while the 58° posture offers superior static relaxation, dynamic discomfort dominates the overall perception when the excitation intensity exceeds a threshold of 0.249 m/s² r.m.s. Objective measurements indicated that dynamic comfort degradation in large-reclined postures is primarily driven by altered inherent biodynamic characteristics. These findings highlight that future luxury vehicle seating must incorporate targeted dynamic isolation to compensate for posture-induced comfort degradation and ensure premium ride quality. Full article