Search Results (6,634)

Room-temperature sodium–sulfur (RT Na-S) batteries hold great potential in the field of large-scale energy storage due to their high theoretical energy density and low cost of raw materials. However, the inherent low conductivity, notorious shuttling, and sluggish kinetics of cathode materials cause the loss of active substances and capacity delay, hindering the practical application of RT Na-S batteries. Owing to their low cost, variable oxidation states, and unsaturated d orbitals, transition metal (TM)-based catalysts have been extensively studied in circumventing the above shortcomings. Herein, the review first elaborates on the reaction mechanisms and current challenges of RT Na-S batteries. Subsequently, the role and function mechanism of TM-based catalysts (including single/dual atoms, nanoparticles, compounds, and heterostructures) in RT Na-S batteries are described. Specifically, based on the theories of electronic transfer and atomic orbital hybridization, the interaction mechanism between TM-based catalysts and polysulfides, as well as the catalytic performance, are systematically discussed and summarized. Finally, a discussion on the challenges and future research perspectives associated with TM-based catalysts for RT Na-S batteries is provided. Full article

We present a full-spectrum machine learning framework for refractive index sensing using simulated absorption spectra from meta-grating structures composed of titanium or silicon nanorods under TE and TM polarizations. Linear regression was applied to 80 principal components extracted from each spectrum, and model performance was assessed using five-fold cross-validation, simulating real-world biosensing scenarios where unknown patient samples are predicted based on standard calibration data. Titanium-based structures, dominated by broadband intensity changes, yielded the lowest mean squared errors and the highest accuracy improvements—up to an 8128-fold reduction compared to the best single-feature model. In contrast, silicon-based structures, governed by narrow resonances, showed more modest gains due to spectral nonlinearity that limits the effectiveness of global linear models. We also show that even the best single-wavelength predictor is identified through data-driven analysis, not visual selection, highlighting the value of automated feature preselection. These findings demonstrate that spectral shape plays a key role in modeling performance and that full-spectrum linear approaches are especially effective for intensity-modulated index sensors. Full article

Water surface temperature (WST) is an important environmental variable, and its monitoring is essential for understanding and mitigating the impacts of climate change and human activities. For this, satellite remote sensing is particularly useful in providing WST data, especially in cases when in situ monitoring is limited or absent, as is often the case in small inland water bodies. In this study, the approach of retrieving the historical WST data from Landsat-5 Thematic Mapper (TM) was tested by analysing different cases across various water bodies in Lithuania, including two small inland lakes, an artificial reservoir, the Curonian Lagoon, and the coastal waters of the southeastern Baltic Sea. Our results demonstrate that WST can be accurately estimated from single-band Landsat-5 TM images, achieving an R² of around 0.9 in comparison with both in situ (with RMSE of 1.35–1.73 °C) and with MODIS satellite (RMSE of 1.11–1.23 °C) water temperature data, thus enabling analysis of water temperature variations in small-sized lakes and other water bodies, and contributing to the reliable monitoring of WST trends. Full article

Transcranial Direct Current Stimulation (tDCS) and Transcranial Magnetic Stimulation (TMS) are neuromodulatory techniques with therapeutic potential for similar disorders; however, their molecular effects require further elucidation, and whether both strategies work in similar biological pathways is unknown. Thus, determining whether these effects are unique or shared across techniques is essential for optimizing their therapeutic applications. We investigated the long-term effects of tDCS by generating a novel transcriptomic dataset and comparing it to immediate tDCS effects and long-term TMS effects using publicly available data. Transcriptomics data were generated using nanopore sequencing on parietal cortices below the stimulation electrode of C57BL/6 mice that underwent repetitive anodal tDCS (200 µA) for 20 min over 5 consecutive days. Bioinformatics analyses were conducted on this dataset in conjunction with publicly available datasets on immediate tDCS and long-term TMS effects. Repetitive tDCS induces long-term alterations in protein translation, mitochondrial function, and cellular respiration, while TMS primarily affects calcium-mediated signaling, suggesting distinct neuromodulatory and molecular mechanisms. These findings demonstrate that tDCS and TMS elicit lasting but distinct molecular changes, highlighting technique-specific neuromodulatory effects relevant to their therapeutic applications. Full article

This study examines how educational attainment and creative-class identity influence public library use among Black homeowners in Ward 8, Washington, D.C., a historically disinvested, yet resilient, Black community. Using an adapted theoretical framework (Chatman’s Small World Theory, Florida’s creative class theory, and Crenshaw’s intersectionality), the research investigates how symbolic capital informs institutional engagement in a racially homogeneous but economically stratified setting. A survey of 56 Black homeowners examined the relationships among education, income, creative-class identity, and library use. Logistic regression analysis revealed that higher educational attainment was a significant predictor of identification with the Black Creative Class^TM. However, neither income nor creative-class identity significantly predicted public library use. These findings challenge the assumption that middle-class status or creative-class affiliation ensures participation in educational or cultural institutions. Instead, they suggest that deeper dynamics, such as cultural relevance, perceived alignment, and trust, may shape engagement with public libraries. The study advances knowledge in library and information science (LIS) and urban studies by demonstrating how spatial context and class distinctions within Black communities shape library engagement. The results underscore the need for culturally responsive library strategies that recognize class-based variation within racial groups, moving beyond monolithic models of community outreach. Full article

Ciclopirox (CPX), a topical antifungal agent of the N-hydroxypyridone class, has gained renewed interest for its potential anticancer, antiviral, antibacterial, and neuroprotective effects. However, due to lack of reliable validated bioanalytical methods, current insights into its pharmacokinetics profile beyond topical use remain limited. To support therapeutic repurposing, we developed and validated a rapid, sensitive LC-MS/MS method for systemic pharmacokinetic evaluation in mice. The method employs methyl derivatization of CPX’s N-hydroxy group, producing methylated CPX (Me-CPX) for improved chromatographic performance which was subsequently retained on the Atlantis^TM T3 C18 reverse phase column. Concentration of CPX is determined indirectly based on the measured response of Me-CPX. The method achieved excellent recovery, a 4-min rapid runtime, sensitivity with LLOQ of 3.906 nM (0.81 ng/mL), and a linear range up to 1000 nM (r ≥ 0.9998). All validation parameters including intra- and inter-day accuracy, precision, matrix effects, stability and dilution integrity met the criteria defined by regulatory International Council for Harmonisation (ICH) M10 bioanalytical method validation guidelines. Application of the method to in vitro plasma protein binding studies revealed high protein binding (>99%) of CPX in both human and mice plasma. Preliminary PK analysis following intravenous and oral administration in CD-1 mice demonstrated moderate systemic exposure after oral dosing, with an estimated absolute bioavailability of 52.5%. These findings establish the method’s suitability and robustness for preclinical and future clinical development of CPX as a repurposed therapeutic agent. Full article

In developing countries, indoor air pollution in rural areas is often attributed to the use of solid biomass fuels for cooking. Such fuels generate particulate matter (PM), carbon monoxide (CO), carbon dioxide (CO₂), polyaromatic hydrocarbons (PAHs), and volatile organic compounds (VOCs). PM created from biomass combustion is a pollutant particularly damaging to health. This rigorous study employed a personal sampling device and multi-stage cascade impactor to collect airborne PM (including PM_2.5) and deposited ash from 20 real-world kitchen microenvironments. A robust analysis of the PM was undertaken using a range of morphological, physical, and chemical techniques, the results of which were then compared to a controlled burn experiment. Results revealed that airborne PM was predominantly carbon (~85%), with the OC/EC ratio varying between 1.17 and 11.5. Particles were primarily spherical nanoparticles (50–100 nm) capable of deep penetration into the human respiratory tract (HRT). This is the first systematic characterisation of biomass cooking emissions in authentic rural kitchen settings, linking particle morphology, chemistry and toxicology at health-relevant scales. Toxic heavy metals like Cr, Pb, Cd, Zn, and Hg were detected in PM, while ash was dominated by crustal elements such as Ca, Mg and P. VOCs comprised benzene derivatives, esters, ethers, ketones, tetramethysilanes (TMS), and nitrogen-, phosphorus- and sulphur-containing compounds. This research showcases a unique collection technique that gathered particles indicative of their potential for penetration and deposition in the HRT. Impact stems from the close link between the physico-chemical properties of particle emissions and their environmental and epidemiological effects. By providing a critical evidence base for exposure modelling, risk assessment and clean cooking interventions, this study delivers internationally significant insights. Our methodological innovation, capturing respirable nanoparticles under real-world conditions, offers a transferable framework for indoor air quality research across low- and middle-income countries. The findings therefore advance both fundamental understanding of combustion-derived nanoparticle behaviour and practical knowledge to inform public health, environmental policy, and the UN Sustainable Development Goals. Full article

Hollow coaxial double-shell submicron fibers were fabricated by combining electrospinning and atomic layer deposition (ALD). Polyvinyl alcohol (PVA) fibers were electrospun to serve as templates for the subsequent atomic layer deposition (ALD) of ZnO doped with transition metals (TM: Ni, Co, and Fe). An inner shell of amorphous Al₂O₃ was first deposited at low-temperature ALD to protect the polymer template. The PVA core was then removed through high-temperature annealing in air. Finally, a top shell of TM-doped ZnO was deposited at an elevated temperature within the ALD window for ZnO. The morphology, microstructure, elemental composition, and crystallinity of these submicron hollow double-shell fibers were thoroughly investigated using scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), and X-ray photoelectron spectroscopy (XPS). Full article

Background: Electronic monitoring adherence devices (EAMDs) are increasingly being utilized in various healthcare settings to track medication adherence. Objective: To determine the accuracy of the Sensal Health MyAide™ Smart Doc in capturing dose removal from the vial, specifically the time of dose removal and the number of pills removed for each actuation of the device. Methods: This validation study compares the device’s recording of dose withdrawals from a prescription vial by simulated patients against reference documentation reported using MS Forms by the participants. Three participants completed a 4-day study consisting of two non-consecutive 1 h sessions per day encompassing six actuations from the prescription vial to be captured by the Sensal Health MyAide™ Smart Dock after their informed consent was obtained. Statistical analysis included percent agreement and Cohen’s kappa assessing agreement between user-reported data and electronic measurement data recorded by the MyAide™ Smart Dock. Outcome measures included confirmation of the specific user, time of dose removal (±1 min), and the number of pills withdrawn. Results: Three subjects were recruited to provide data for a total of 144 actuations. The study found perfect 100% agreement across the number of pills withdrawn and specific users withdrawing the pills and 99% agreement for the time of administration. The Cohen’s kappa values for the outcome measures were 1.00 (95%CI [1.00, 1.00]) for the number of pills dispensed and specific user and 0.993 (95%CI [0.990, 0.996]) for the time of administration. Conclusions: This study found that the Sensal Health MyAide™ Smart Dock can accurately record the time of administration, the number of pills dispensed, and the identity of the user dispensing the pills. Full article

RMB₆-TMB₂ (RM = rare earth elements, TM = transition metal elements) composites retain superior field emission properties of RMB₆ while addressing its inherent mechanical limitations by constructing a eutectic structure with TMB₂. Herein, an in situ route for synthesizing RMB₆-TMB₂ composite nanopowders with homogeneous phase distribution using reduction reactions was proposed. The LaB₆-ZrB₂ composite nanopowders were synthesized in situ for the first time using sodium borohydride (NaBH₄) as both a reducing agent and boron source, with lanthanum oxide (La₂O₃) and zirconium dioxide (ZrO₂) serving as metal sources. The effects of the synthesis temperature on phase compositions and microstructure of the composites were systematically investigated. The LaB₆-ZrB₂ system with a eutectic weight ratio exhibited an accelerated reaction rate, achieving a complete reaction at 1000 °C, 300 °C lower than that of single-phase ZrB₂ synthesis. The composite phases were uniformly distributed even at nanoscale. The composite powder displayed an average particle size of ~170 nm when synthesized at 1300 °C. With the benefit of the in situ synthesis method, LaB₆-TiB₂, CeB₆-ZrB₂, and CeB₆-TiB₂ composite powders were successfully synthesized. This process effectively addresses phase separation and contamination issues typically associated with traditional mixing methods, providing a scalable precursor for high-performance RMB₆-TMB₂ composites. Full article

Traffic-induced noise pollution is a significant environmental issue, driving the development of advanced noise-reducing pavement materials. Semi-dense graded asphalt mixtures (SDAMs) present a promising compromise, offering enhanced acoustic properties compared to conventional dense-graded asphalt mixtures while maintaining superior durability to porous asphalt mixtures. However, the mechanism underlying the relationship between the energy dissipation characteristics and noise reduction effects of such mixtures remains unclear, which limits further optimization of their noise reduction performance. This study designed and prepared semi-dense graded noise-reducing asphalt mixtures SMA-6 TM, SMA-10 TM, and SMA-13 TM (SMA TM represents noise-reducing SMA mixture) based on traditional dense-graded asphalt mixtures SMA-6, SMA-10, and SMA-13, and conducted tests for water stability, high-temperature performance (60 °C), and low-temperature performance (−10 °C). Subsequently, energy loss parameters such as loss factor and damping ratio were calculated through dynamic modulus tests to characterize their energy dissipation properties. The mechanism linking the energy dissipation characteristics of semi-dense graded asphalt mixtures to noise reduction was investigated. Finally, the noise reduction effect was further verified through a tire free fall test and a close-proximity (CPX) method. The indoor test results indicate that the semi-dense mixtures exhibited a trade-off in performance: their dynamic stability was 11.1–11.3% lower and low-temperature performance decreased by 4.2% (SMA-13 TM) to 14.1% (SMA-6 TM), with moisture stability remaining comparable. Conversely, they demonstrated superior damping, with consistently higher loss factors and damping ratios. All mixtures reached peak damping at 20 °C, and the loss factor showed a strong positive correlation (R² > 0.91) with energy dissipation. Field results from a test section showed that the optimized SMA-10 TM mixture yielded a significant tire–road noise reduction of 3–5 dB(A) relative to the SMA-13, while concurrently meeting key performance criteria for anti-water ability and durability. This study establishes a link between the energy dissipation in SDAM and their noise reduction efficacy. The findings provide a theoretical framework for optimizing mixture designs and support the wider application of SDAM as a practical noise mitigation solution. Full article

An environmentally friendly biodegradable and flexible polymer with exceptional mechanical, thermal and electromagnetic interference shielding is urgently needed to reduce environmental pollutants and electromagnetic waves to preserve human health. The paper presents our study where we developed biodegradable electrospun nanocomposite by employing polybutylene succinate (PBS) with multiwalled carbon nanotubes (MWCNTs). The crystallization temperature Tc and melting temperature Tm of electrospun PBS/MWCNT composites with 3 wt% of MWCNTs was increased noticeably by 4 °C and 5 °C. The tensile strength increased by about 2.61 ± 0.15MPA and the elastic modulus increased by about 0.72 ± 0.02 GPa with the addition of 3% MWCNT in polybutylene succinate. The increase in MWCNT content from 0.5 to 3 wt% led to an enhanced storage modulus and electrical properties 5 to 8 times higher in comparison to PBS. Moreover, the MWCNT was tested in different concentrations in PBS for electromagnetic interference shielding (EMI) and the most applicable results were obtained when the MWCNT was 3% which is capable of providing 25.5 db EMI shielding efficiency. The percolation threshold capability of PBS/MWCNT electrospun nanocomposites was 0.94 wt% and has significant entanglement of the MWCNTs and MWCNT network in the PBS matrix for conductive pathways. The study offers a viable process for creating an electrospun PBS/MWCNT composite that is lightweight, biodegradable and has exceptional electromagnetic shielding capabilities. Full article

Objective: The aim of this study is to develop and evaluate the antibacterial and anti-biofilm efficacy of ciprofloxacin-coated tympanostomy tubes (TTs) using a sustained-release varnish (SRV-CIPRO) and introduce a novel tympanic membrane model for preclinical evaluation. Study Design: This was an in vitro experimental study. Setting: This study was conducted in a biofilm research laboratory in an academic medical center. Methods: Sterile fluoroplastic TTs were coated with SRV-CIPRO or placebo varnish. A novel tympanic membrane (TM) model was developed using a layered agar–plastic system. Antibacterial activity, biofilm inhibition, and bacterial viability were assessed through agar diffusion, MTT, ATP quantification, HR-SEM, and SD-CLSM. Results: SRV-CIPRO-coated TTs exhibited sustained antibacterial activity for up to 10 days. Compared to the placebo, SRV-CIPRO significantly inhibited biofilm formation, reduced metabolic activity, and decreased bacterial viability (p < 0.05). Imaging confirmed fewer bacterial colonies on SRV-CIPRO TTs. The TM model allowed realistic testing of tube insertion and infection simulation. Conclusion: SRV-CIPRO-coated TTs offer sustained antibiotic delivery, potentially reducing postoperative otorrhea and biofilm-related complications. The TM model provides a platform for preclinical evaluation of middle ear devices. Full article

Lithium-ion batteries (LIBs) have garnered extensive application across various domains. However, frequent safety incidents associated with these LIBs have emerged as a significant impediment to their further advancement. Consequently, there is an urgent necessity to develop a novel fire extinguishing agent that possesses both rapid fire suppression and efficient cooling capabilities, thereby effectively mitigating the occurrence and propagation of fires in LIBs. This study pioneers the development of an adaptive thermosensitive microcapsule (TM) fire extinguishing agent synthesized via in situ polymerization. The TM encapsulates a ternary composite core—perfluorohexanone (C₆F₁₂O), heptafluorocyclopentane (C₅H₃F₇), and 2-bromo-3,3,3-trifluoropropene (2-BTP)—within a melamine–urea–formaldehyde (MUF) resin shell. The TM was prepared via in situ polymerization, combined with FE-SEM, FTIR, TG–DSC, and laser particle size analysis to verify that the TM had a uniform particle size and complete coating structure. The results demonstrate that the TM can effectively suppress the thermal runaway (TR) of LIBs through the synergistic effects of physical cooling, chemical suppression, and gas isolation. Specifically, the peak TR temperature of a single-cell LIB is reduced by 14.0 °C, and the heating rate is decreased by 0.17 °C/s. Additionally, TM successfully blocked the propagation of TR thereby preventing its spread in the dual-LIB module test. Limitations of single-component agents are overcome by this innovative system by leveraging the ternary core’s complementary functionalities, enabling autonomous TR suppression without external systems. Furthermore, the TM design integrates precise thermal responsiveness, environmental friendliness, and cost-effectiveness, offering a transformative safety solution for next-generation LIBs. Full article

Neurodegenerative disorders such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and multiple sclerosis (MS) are marked by progressive network dysfunction that challenges conventional, protocol-based neurorehabilitation. In parallel, neuromodulation, encompassing deep brain stimulation (DBS), transcranial magnetic stimulation (TMS), transcranial direct current stimulation (tDCS), vagus nerve stimulation (VNS), and artificial intelligence (AI), has matured rapidly, offering complementary levers to tailor therapy in real time. This narrative review synthesizes current evidence at the intersection of AI and neuromodulation in neurorehabilitation, focusing on how data-driven models can personalize stimulation and improve functional outcomes. We conducted a targeted literature synthesis of peer-reviewed studies identified via PubMed, Embase, Scopus, and reference chaining, prioritizing recent clinical and translational reports on adaptive/closed-loop systems, predictive modeling, and biomarker-guided protocols. Across indications, convergent findings show that AI can optimize device programming, enable state-dependent stimulation, and support clinician decision-making through multimodal biomarkers derived from neural, kinematic, and behavioral signals. Key barriers include data quality and interoperability, model interpretability and safety, and ethical and regulatory oversight. Here we argue that AI-enhanced neuromodulation reframes neurorehabilitation from static dosing to adaptive, patient-specific care. Advancing this paradigm will require rigorous external validation, standardized reporting of control policies and artifacts, clinician-in-the-loop governance, and privacy-preserving analytics. Full article