Browse Articles
Discover research articles across all indexed journals
Nuclear condensates formed by truncated mutant NEK1s impede ribosomal RNA biogenesis and drive motor dysfunction
A new ultra-high gain CI-based DC/DC converter with low voltage and current stresses
Abstract By integrating a three-winding coupled inductor (TWCI) with voltage multiplier cells, this study proposes a quadratic DC–DC converter that achieves ultra-high voltage gain while maintaining continuous input current and a common ground. The proposed coupled-inductor topology is specifically engineered to minimize both voltage and current stresses across all circuit components, thereby enhancing overall performance and enabling potential cost reductions. Enhanced design flexibility is a key feature of the proposed configuration, particularly because the secondary winding of the TWCI operates in a semi-trans-inverse manner, allowing high voltage gains to be realized even with a very low turns ratio. Regenerative passive clamp circuits are incorporated to recover the leakage energy of the TWCI and to limit voltage stresses on the active switches, which are driven with simultaneous switching patterns. The converter’s vertical structure further alleviates semiconductor voltage stress, while intrinsic current sharing between the TWCI and the input inductor substantially reduces power dissipation in the main power components. Additionally, turn-off switching losses of both active switches are minimized via a quasi-resonant cell. The paper presents a comprehensive steady-state analysis, detailed power loss evaluation, a comparative study with existing topologies, and key design guidelines. All theoretical contributions are conclusively validated through experimental results obtained from a 200 W hardware prototype, converting a 25 V input to a 400 V output.
In situ topotactic transition to porous crystals boosts methane photooxidation
Abstract The rapid recombination of photogenerated electron-hole pairs represents a fundamental bottleneck in photocatalysis. Constructing porous single crystals is expected to resolve this issue by simultaneous optimization of light absorption, charge transport and mass diffusion. Here, we present a topotactic lattice contraction strategy for synthesizing porous single-crystalline zinc blende ZnO monoliths with exceptional crystallinity, phase purity and high porosity. In situ transmission electron microscopy reveals the atomic-scale formation process: preferential S/O migration along {222} channels enable epitaxial nucleation, while interfacial strain induces vacancy coalescence into interconnected nanopores. The low defect density in ZnO effectively suppresses photogenerated carrier recombination, exhibiting improved charge transport and prolonged carrier lifetime. Incorporating atomically dispersed Ru sites (0.6 wt%) further enhances charge separation efficiency, achieving 82% selectivity for methyl hydroperoxide in methane photooxidation while maintaining >85% activity over 40 hours. This work establishes a route to porous single crystals, advancing material design for prospective application in photocatalysis.
Environmental tobacco smoke and sleep fragmentation in children with suspected sleep apnea
Tip functionalization of anisotropic plasmonic nanoparticles with conductive polymer patches via site-selective micelle intercalation
Integrated precipitation and solidification strategies for fast-dissolving amorphous valsartan nanocomposites
Abstract Poor aqueous solubility and nanoparticle instability remain key challenges in the development of solid oral formulations for BCS class II drugs. In this study, valsartan nanoparticles were prepared by reverse liquid antisolvent precipitation and stabilized using drying- and carrier-mediated strategies. Crystalline valsartan Form E was first prepared and characterized, and solvent screening was performed to select an appropriate precipitation medium. In the presence of Pluronic F-127, stable nanosuspensions with an average particle size of approximately 30 nm and a narrow size distribution (PDI ≈ 0.196) were obtained. Spray drying and freeze drying with AEROSIL ® 200 produced solid amorphous formulations, as confirmed by PXRD and DSC. Both dried nanosystems released more than 80% of valsartan within 10 min, whereas spray-dried micronized valsartan required approximately 60 min to reach a comparable dissolution level. Montmorillonite K10 functionalized with protamine sulfate was further used for nanoparticle recovery and stabilization. The optimized VMP nanocomposite containing 40% valsartan and 3 mg protamine sulfate per gram of carrier showed enhanced initial dissolution. Overall, controlled antisolvent precipitation combined with carrier surface engineering provides an effective strategy for improving the dissolution performance of poorly water-soluble drug nanoparticles.
Atmospheric CO₂-to-acetaldehyde artificial photosynthesis in metallo hydrogen-bonded organic frameworks
Abstract Artificial photosynthesis of acetaldehyde from atmospheric CO 2 is highly promising, yet remains severely limited by low CO 2 concentration in air and sluggish proton transfer kinetics. Herein, we report metallo hydrogen-bonded organic frameworks (MHOFs) of HNNU-X (X = O, S, Se) which enable acetaldehyde synthesis directly from air, water, and natural sunlight. Among them, HNNU-Se exhibits a competitive acetaldehyde production rate of 557.1 μmol g⁻¹ h⁻¹ with high electron-based selectivity of 95% under outdoor conditions, without need of sacrificial agents. Mechanistic studies reveal that HNNU-X creates a proton-rich microenvironment in which [Zn(tpy)] 2+ cations function as CO 2 capture and activation sites for direct air capture, while [XCN] – anions serve as proton shuttles, facilitating rapid transfer of in-situ generated H⁺ from solar-driven water oxidation to adsorbed CO 2 . This work enables the synergistic coupling of CO 2 reduction and H 2 O oxidation, thereby achieving efficient artificial photosynthesis of acetaldehyde.
Tunable optical and UV-blocking properties of eco-friendly CMC/ZnO nanocomposite films
Abstract As environmental sustainability standards become more stringent, there is a growing need for biodegradable and renewable UV-protective films. Thus, this study looked at how zinc oxide nanoparticles (ZnO-NPs) affect the optical properties of carboxymethyl cellulose sodium (CMC) using a standard method called solution-casting. Fourier-transform infrared (FTIR) spectroscopy revealed that the carboxyl groups of CMC were ionized, forming hydrogen bonds with ZnO-NPs. X-ray diffraction (XRD) analysis confirmed the formation of CMC/ZnO nanocomposites through the characteristic diffraction peaks of ZnO-NPs, while the crystallite size of the nanocomposites decreased with increasing ZnO-NP concentration. The optical analysis found that as the amount of ZnO increased, the HOMO/LUMO band gap decreased from 5.21 eV to 5.10, 4.67, 4.43, and 3.98 eV, which was linked to the smaller crystallite size. Moreover, the refractive index of CMC increased from 1.78 to 1.84, 2.23, 2.51, and 2.60 due to the addition of 2, 4, 6, and 8 wt.% of ZnO-NPs, indicating modified optical properties suitable for various applications. The CMC/ZnO nanocomposite films showed strong UV-blocking performance, with the film containing 8 wt% ZnO-NPs blocking 94% of UVC (200–280 nm), 93.5% of UVB (280–320), and 93% of UVA (320–400 nm) radiation. Thus, based on the known biodegradable nature of the CMC matrix, CMC/ZnO nanocomposites can be considered as promising candidates for biodegradable UV-protective materials. The long-term stability of the optical properties was evaluated by re-measuring the absorbance and transmittance of pure CMC films and those doped with 8 wt% ZnO-NPs after more than 6 months of storage under normal conditions. Despite minor variations in film thickness, the optical measurements remained highly consistent, demonstrating that both pure and doped CMC films retain their optical performance over extended periods. A preliminary test using green chillies was conducted to evaluate the moisture-retention performance of the prepared films under UVA light, providing an initial indication of their ability to reduce water loss and maintain firmness during storage.
The impact of digital intelligence on urban ecological efficiency and its spatial spillover effects: evidence from China
Synthesis of Ce-MOF/Ag composites with improved electrocatalytic activity and stability for sustainable water splitting
Abstract The increasing global demand for clean and sustainable energy has intensified the need for efficient hydrogen production via water splitting, yet the development of cost-effective and high-performance electrocatalysts remains a major challenge. In this context, the present study focuses on the design of an advanced MOF-based composite to enhance catalytic efficiency and stability. This study was focused on preparing an MOF-based composite to enhance its efficiency in water splitting applications. The MOF framework was enhanced with additional active ingredients to boost its overall performance, stability, and catalytic activity. Developing such advanced composites is crucial for addressing the challenges of energy conversion and hydrogen generation via water splitting, which is considered a clean and sustainable route for future energy systems. A metal–organic framework (MOF) containing cerium and MOF-Ag composites have been synthesized using the green methodology. The generated materials were examined using several analytical methods, including contact angle, powder X-ray diffraction (PXRD), FTIR, Brunauer-Emmett-Teller (BET), transmission electron microscope (TEM) and scanning electron microscopy (SEM). The average particle size of the synthesized MOF-Ag composites ranges from 36.7 to 41.3 nm, which is confirmed by the SEM data in combination with the Gaussian mixture model. The BET and contact angle data confirm the mesoporous and hydrophilic characteristics of the MOF-Ag composites. The activity of the modified Ce-MOF and MOF-Ag composites electrode was utilized for water-splitting purposes. The current flowing through the electrodes lasts for five hours. The electrodes (MOF, MOF-Ag1, MOF-Ag2, and MOF-Ag3) attained the current density of 10 mA cm − 2 at potentials of ‒1.16, ‒0.88, ‒0.9, and ‒0.94 V (vs. RHE) for HER and at potentials of 2.5, 2.07, 2.12, and 2.18 V (vs. RHE) for OER, respectively. Additionally, each of the changed surfaces (MOF, MOF-Ag1, MOF-Ag2, and MOF-Ag3) had its Tafel slopes calculated¸ yielding values of 150, 76, 86, and 91 mV dec − 1 for HER and 178, 90, 128, and 138 mV dec − 1 for OER.
CCC-MMTN: towards robust classification of confusable modulations in few-shot scenarios
Multi-objective optimization of sustainable incremental sheet metal forming of recycled e-waste copper using a novel hybrid RSM-Fuzzy AHP -Fuzzy GRA
Fuzzy K-means–based outlier detection in plastic-degradation-related protein sequences using PSI-BLAST, Jaccard similarity, and OMA features
Hybrid variational quantum-classical data assimilation for numerical weather prediction using Lorenz system benchmarks
Abstract The major computational bottleneck of operational Numerical Weather Prediction (NWP) is data assimilation, in which a high-dimensional, prohibitively expensive variational cost function must be minimised repeatedly, with computational costs scaling alongside model resolution. This work presents a systematic empirical evaluation of an Adaptive Hybrid Variational Quantum-Classical (VQE)-based framework for Four-Dimensional Variational Data Assimilation (4DVAR), benchmarked against Classical BFGS optimisation and three deep learning baselines: a standard Long Short-Term Memory network (LSTM), a task-aligned Data Assimilation LSTM (DA-LSTM), and a Neural Ordinary Differential Equation (Neural ODE) across two canonical chaotic atmospheric models of increasing complexity: the three-variable Lorenz-1963 (L63) and the forty-variable Lorenz-1996 (L96) systems. All experiments were conducted using PennyLane quantum simulation across 50 independent runs per method, with rigorous statistical validation including paired t-tests, Wilcoxon signed-rank tests, bootstrap 95% confidence intervals, and formal effect size estimation. Results are reported with full timing decomposition separating quantum circuit execution (T 1 ), classical optimiser time (T 2 ), and infrastructure overhead (T 3 ). The central finding is that the Adaptive Hybrid Quantum-Classical model with a Hardware-Efficient Ansatz (Hybrid QC-HEA) achieves a mean 4DVAR cost of 2.10 on L63 and 21.0 on L96 representing only 11.7% and 14.8% above the Classical 4DVAR baseline respectively—differences that are not statistically significant at p < 0.05. Crucially, Hybrid QC-HEA outperforms all three deep learning baselines by substantial margins on L96, achieving 5.5x lower cost than DA-LSTM, 5.2x lower than LSTM, and 8.3x lower than Neural ODE. The Hybrid QC-HEA also exhibits the tightest cost distribution across 50 runs on L96, demonstrating superior operational reliability compared to all competing methods. Conversely, all-quantum VQE-based methods with no refinement by classical methods scale to cost 32 and 75x more than classical on L96, and thus gradient-free quantum optimisation without the classical BFGS refinement step is ultimately impractical to high-precision data assimilation and the classical BFGS refinement step is in any case a fundamental element of the architecture. Computational scaling analysis reveals that Classical 4DVAR wall-clock time grows 126-fold from L63 to L96, consistent with theoretical predictions of exponentially increasing complexity in chaotic optimisation landscapes, while the hybrid framework maintains near-classical accuracy at both scales. These results constitute an empirical proof-of-concept for hybrid quantum-classical data assimilation on realistic atmospheric models, establishing a reproducible benchmarking framework for future investigation on near-term quantum processors based NISQ devices.