Search Results (38,857)

In this paper, we revisit the recent result of Luo, Xu, and Raina on an Erdélyi-type integral for Saran’s three-variable hypergeometric function $F_K$. We provide a new proof of this integral and derive an attractive new integral related to Appell’s function $F_2$. A further extension on the L-variable $F_K$ function, which appears in physics, is also discussed. Furthermore, we prove various q-Erdélyi-type integrals for the q-analogue of the $F_K$-function. An interesting discrete analogue is also included. We also provide a valuable compilation of the sources for known Erdélyi-type integrals of many different hypergeometric functions. Full article

Owing to its high theoretical sodium-storage capacity of approximately 1000 mAh g⁻¹ and cost-efficient characteristics, Fe₂VO₄ has emerged as a highly attractive anode material for sodium-ion batteries (SIBs). In this work, MXene-incorporated Fe₂VO₄ composites were successfully synthesized. Comprehensive electrochemical characterization demonstrates that MXene incorporation significantly enhances the electronic conductivity and sodium-ion diffusion kinetics of Fe₂VO₄, while effectively mitigating volume expansion during cycling. The synthetic substantially improves its cycling stability and rate capability. When the MXene loading ratio is optimized at 5 wt%, the composite exhibits outstanding cyclic durability, with a remarkable reversible specific capacity of 323.3 mAh g⁻¹ maintained after 200 cycles at a current density of 0.1 A g⁻¹. Furthermore, the composite demonstrates outstanding rate performance, with a specific capacity of 164.5 mAh g⁻¹ achieved at a current density of 2 A g⁻¹. The synergistic integration of Fe₂VO₄ and MXene not only constructs a three-dimensional electrically conductive framework for efficient charge transport but also reinforces strong structural stability against cycling-induced degradation. This work proposes a versatile engineering strategy that can be adapted for other conversion-type electrode materials in the context of advanced energy storage technologies. Full article

Peroxydisulfate (PDS, S₂O₈²⁻) is an important oxidant for a wide range of industrial applications, including organic synthesis, polymer preparation, wastewater treatment and environmental remediation. Currently, PDS is commercially produced by electrolysis of sulfate solution. Photoelectrochemistry (PEC) provides an alternative approach to PDS generation by reducing the energy required to drive this process. Because PEC uses solar light as an abundant, free resource, it is an attractive technique for PDS generation compared to electrolysis. WO₃, owing to its excellent stability in acidic environments, is an excellent metal oxide candidate for producing PDS. Withstanding stronger acidic pH as well as absorption of visible light as a major fraction of solar light renders WO₃ a promising material for PEC-based PDS production when compared with other semiconductors. This mini review examines light-assisted, sustainable production of PDS on WO₃ photoanodes. It mainly involves the oxidation of the anion bisulfate, HSO⁴⁻, in a highly acidic pH. The efficiency of photoelectrochemical generation of PDS is greatly influenced by important factors, including suppressing recombination of photoinduced charge carriers, cocatalyst loading, minimizing competing side reactions, and establishing coupled reactions. In this review, we briefly discussed the key highlights to date in the application of WO₃ as a stable photoanode material for producing PDS. It provides insight into the potential of photocatalysis as an emerging route for the sustainable synthesis of PDS as a valuable chemical oxidant. Besides the significant progress made so far, the PDS production rate remains low, and minimizing the recombination tendency to achieve a higher photocurrent density could further boost PEC-based PDS production. Full article

In this paper, we investigate parameter estimation for a class of linear self-attracting diffusion processes. Specifically, we consider processes with a drift coefficient given by $-\theta \left({\int }_0^t(X_t-X_u)du\right)$. Employing both maximum likelihood estimation and least squares estimation, we show that the resulting estimators coincide. We establish the consistency and asymptotic normality of ${\widehat{\theta }}_N$ for high-frequency data, and assess its numerical performance through simulation studies. Full article

As the demand for polyethylene terephthalate (PET) continues to rise, significant environmental pollution caused by challenges in PET degradation has garnered global attention. Given the crucial role of esterases in depolymerizing PET into reusable monomers, such enzymes capable of degrading plastics have attracted considerable interest. In this study, we used the previously reported ultra-efficient mutant of the PET-degrading enzyme Ideonella sakaiensis PETase, known as FASTase, as a positive control. We investigated the PET-degrading activity of esterase E4, derived from Altererythrobacter indicus. The results demonstrated that E4 exhibits degradative activity toward the PET substrate bis(2-hydroxyethyl) terephthalate, the PET model substrate bis(benzyloxyethyl) terephthalate, and PET nanoparticles. Notably, E4 retains its degradation activity under high-temperature and high-salt conditions and can enhance the enzymatic activity of FASTase when acting synergistically. Given the low structural and sequence similarity between E4 and IsPETase, our research broadens the scope for screening PET-degrading enzymes. Full article

Quercetin, one of the most abundant flavonoids in nature, has attracted the attention of many researchers due to its chemical and biological properties. A series of metal–quercetin complexes (Cu²⁺, Co²⁺, Zn²⁺, Sn²⁺, Al³⁺, Cd²⁺ and Mg²⁺) were synthesized and systematically characterized by Fourier transform infrared spectroscopy (FTIR), UV-visible spectroscopy (UV–Vis) and nuclear magnetic resonance (NMR). These analyses confirmed that the complexes predominantly form through coordination with the 4-carbonyl group and adjacent phenolic hydroxyls. This induces measurable shifts in the ν(C=O), ν(O–H), and π→π* transition bands relative to free quercetin. The antioxidant capacity of the complexes was evaluated using 2,2-Diphenyl-1-Picrylhydrazyl (DPPH^•) radical scavenging method, 2,2′-Azinobis(3-Ethylbenzothiazoline-6-Sulfonic Acid) (ABTS^•)⁺ radical activity, and Ferric Reducing Antioxidant Power (FRAP) assay. Several complexes exhibited higher radical scavenging efficiency than quercetin, with inhibition percentages exceeding 80% in the DPPH^• and ABTS^•+ assays. Others showed reduced activity due to the masking of redox-active hydroxyl groups during metal coordination. FRAP results corroborated these trends, indicating metal-dependent modulation of reducing power. Antimicrobial evaluation revealed that selected complexes were more active than free quercetin, particularly against Staphylococcus aureus and Candida spp., with minimum inhibitory concentrations (MICs) ranging from 75–250 μg mL⁻¹. Overall, metal complexation significantly alters the electronic structure and biological behavior of quercetin, highlighting the potential of metal–flavonoid complexes as multifunctional antioxidants and antimicrobials. Full article

As a new class of green functional liquids, deep eutectic solvents (DESs) have attracted increasing attention as alternatives to conventional solvents, such as mineral acids, organic solvents and ionic liquids (ILs), in nuclear chemistry. Owing to their low cost, easy preparation, structural tunability, and adjustable physicochemical properties, DESs provide unique solvation and coordination environments that enable various applications. This review summarizes recent research advances in the application of DESs for the chemical processes of the nuclear fuel cycle. Particular emphasis is focused on dissolution, extraction and separation, electrochemical deposition and redox processes, radionuclide capture, decontamination and detection. This review highlights the fundamental advantages and current limitations of DES-based systems and outlines future trends. Full article

The application of quantum machine learning (QML) to security-relevant problems has attracted growing attention, yet its practical behavior in realistic workloads remains insufficiently characterized. This paper investigates the feasibility and limitations of variational quantum classifiers (VQCs) for identifying dummy power traces in side-channel analysis (SCA). A controlled benchmarking framework is developed to evaluate training stability, sensitivity to key design parameters, and resource–performance trade-offs under realistic constraints. To move beyond idealized simulation, hardware-relevant factors, including finite measurement budgets and device noise, are incorporated, and inference robustness under degraded operating conditions is assessed. The results show that VQCs can capture meaningful discriminative patterns in structured side-channel data, although robustness and performance depend strongly on encoding strategy, circuit depth, and measurement conditions. These findings provide an empirical assessment of the potential and limitations of QML for side-channel security and offer practical guidance for future research. Full article

Fibrous natural-origin materials are not only attractive as raw materials in various applications but are also often produced as waste products in some manufacturing processes. Despite their comprehensive implementation as thermal or noise isolation materials, their behavior under mechanical load is not yet fully understood, and there are no assignments of existing universal material models for the category of fibrous materials. The conducted experimental research provides a methodology with which to evaluate the structural behavior of fibrous materials under applied compression force and classify these materials according to their mechanical properties based on a certain material model. As a result of this research, we observed that the mechanical properties of the fibrous material during compression mode are determined by the fibrous structure, with insignificant influence from the physical nature of the material itself. This investigation provides an analysis of the application of a hyperelastic incompressible isotropic model to fibrous material of different origins. Hyperelastic material models of the Money–Rivlin, Ogden, Yeoh, and polynomial type were implemented. The fitting quality of the Yeoh third-order model obtained the best fitting results for animal wool and mineral wool. Cotton wool showed the best fitting results with the polynomial fifth-order model. The outcome of this research will help create finite element models for structural analysis, efficiently modelling structural responses to vibration or noise. For most animal and mineral wool samples, the best agreement with the experimental compression curves was obtained using the Yeoh third-order hyperelastic model, with coefficients of determination R² between 0.979 and 0.996, while fifth-order polynomial fits locally reached R² up to 0.9999 for aged cotton wool. Full article

The heavy metal pollution linked to extractive activities has attracted broad public attention. To examine the current state of heavy metal pollution in river sediments around iron tailing zones, this study was carried out to evaluate the distribution features, potential sources, and environmental hazards of heavy metals (HMs, Cr, Cd, Ni, Cu, Zn, Pb, As, and Hg) in the surface sediments of rivers in the Xiangshan area of Ma’anshan City. Results indicated that, except for Cr, the mean heavy metal concentrations exceeded the soil background levels in Anhui’s Huaihe River Basin. Variability in metal concentrations among the sediments was moderate, exhibiting an uneven spatial distribution. Significant positive correlations were detected between various HMs in the sediments, suggesting a common pollution source. Source analysis findings revealed that the HMs primarily originate from agricultural fertilization, mining, and smelting activities. Evaluation results from both the single-factor pollution index and the Nemerow comprehensive index indicated that the upstream section of the Caishi River is severely polluted by HMs. The potential ecological risk index evaluation results demonstrated that 85% of sediment samples from sampling points achieved a high comprehensive potential ecological risk level for HMs, with Cd, Cu, and Hg identified as the key contributors. The human health risk assessment demonstrated that both adults and children are subjected to carcinogenic risks from heavy metal exposure, with children exhibiting a higher risk level. This study offers valuable insights into managing heavy metal contamination in river sediments adjacent to iron tailings regions. Full article

Titanium matrix composites reinforced with carbon nanotubes (CNTs) have attracted significant attention due to their potential to overcome the inherent limitations of titanium alloys in hardness, wear resistance, and strength–toughness balance. With the rapid development of additive manufacturing (AM) technologies, the integration of CNT reinforcements into titanium matrices provides new opportunities for fabricating high-performance lightweight components. This review systematically summarizes recent progress in the preparation and application of CNT-reinforced titanium matrix composites for AM. Key powder preparation strategies, including mechanical mixing, chemical coating, and in situ growth methods, are critically compared in terms of CNT dispersion uniformity, structural integrity preservation, powder flowability, and process compatibility. The influence of CNT incorporation on AM behavior and final material performance is discussed, with particular emphasis on multiscale strengthening mechanisms such as enhanced laser absorption, load transfer effects, grain refinement, and dispersion strengthening induced by TiC formation. Current challenges mainly involve achieving homogeneous CNT distribution, controlling interfacial reactions, and balancing dispersion efficiency with structural damage. Future research directions are proposed, focusing on advanced powder engineering techniques, interface regulation strategies, and deeper understanding of the relationships between processing parameters, microstructure evolution, and mechanical properties. This work provides a comprehensive reference for the design and fabrication of next-generation CNT-reinforced titanium-based materials. Full article

Temozolomide and dacarbazine are untargeted anticancer prodrugs that have been widely employed in the treatment of melanoma and glioblastoma. These agents decompose into a short-lived monomethyl triazene intermediate, culminating in the release of a methyl diazonium cation that serves as the DNA-alkylating species responsible for tumour destruction. However, due to their high chemical lability, these agents have been associated with chemotherapy resistance, mutagenicity, tumour relapse, and significant off-target toxicity. One promising strategy towards the resolution of these limitations involves the design of arylmethyl triazene prodrugs, which enable targeted tumour-specific drug delivery. This review explores the various approaches used to selectively deliver alkyl aryl triazenes as alternatives to current therapies. It highlights early chemical strategies such as N-acylation and etherification of monomethyl triazenes, along with associated kinetic studies. The selective activation of novel triazenes in murine and human melanoma cells through a tyrosinase-responsive promoiety is discussed. Recent progress in nitroaromatic-based prodrugs designed to exploit the hypoxic microenvironment of glioblastoma is also examined. Additionally, we summarise the development of combi-triazenes and their underlying chemistries, which enable the simultaneous release of two active therapeutic agents. Full article

The 2025 approval of the selective NaV1.8 blocker suzetrigine for acute pain marked a pivotal advance in analgesic drug development. Yet the subsequent failure of Vertex’s next-generation NaV1.8 inhibitor VX993 to demonstrate clinical analgesia underscores enduring challenges in translating mechanistic promise into patient benefit. This review examines why promising targets and compounds, spanning NaV and TRP channels, often falter and outlines a path toward more reliable target selection and validation. I first summarize the pain pathway, from nociceptor transduction through spinal processing to cortical perception, emphasizing how inflammation and peripheral sensitization reshape excitability. Historically serendipitous, pain drug discovery now prioritizes molecular precision. Most approved chronic pain therapies act in the CNS and are limited by modest efficacy and adverse effects. Nociceptor-enriched targets (NaV1.7/1.8/1.9; TRP channels) remain attractive, yet redundancy among NaV subtypes and the necessity of blocking targets at the correct anatomical sites complicate translation. Human genetics and multi-omics provide a powerful, unbiased engine for target discovery. Rare high-impact variants offer strong causal hypotheses, while common polygenic contributions illuminate broader susceptibility. Large biobanks increasingly reveal a mismatch between legacy pain targets and genetically supported candidates across neuronal and non-neuronal cells. Human DRG transcriptomics highlight NaV channel redundancy. Human in vitro electrophysiology and PK/PD analyses show suzetrigine achieves ~90–95% NaV1.8 engagement, yet neurons can still fire unless additional channels are blocked. Species differences and drug distribution (including BBB/PNS penetration and P-gp efflux) critically influence efficacy; centrally accessible blockade (e.g., for NaV1.7 or TRPA1) may be necessary to achieve robust analgesia, challenging peripherally restricted strategies. Osteoarthritis illustrates how obesity-driven metabolic inflammation, synovial immune activation, subchondral bone remodeling, and specific nociceptor subtypes converge to drive mechanical pain. Multi-omic integration across diseased human tissues can pinpoint causal processes and cell types, enabling more selective and safer target choices. I propose a practical framework for target validation that integrates: (i) rigorous human genetic support; (ii) cell-type and site-of-action mapping; (iii) human-relevant electrophysiology and PK/PD with verified target engagement; (iv) species-appropriate models; (v) consideration of modality (small molecule, biologic, RNA, targeted protein degradation). Advancing genetically and anatomically aligned targets, tested at the right sites and exposures, offers the best path to genuinely effective, better-tolerated pain therapeutics. Full article

Halide double perovskites with near-infrared (NIR) emission are promising for optoelectronic applications. NIR-II (1000–1700 nm) emission, in particular, is attractive due to its strong tissue penetration, high spatial resolution, and low biological light damage risk. However, materials capable of NIR-II emission often require additional sensitizers and suffer from issues such as narrow emission bandwidth and low photoluminescence efficiency. In this work, we report a Re⁴⁺ doping strategy using Cs₂WCl₆, a vacancy–ordered double perovskite, to achieve efficient NIR-II emission. Spectroscopic and dynamic measurements reveal energy transfer between the Cs₂WCl₆ matrix and the Re⁴⁺ centers, resulting in efficient broadband NIR-II emission centered at 1345 nm (FWHM ≈ 87 nm), along with broad excitation ranging from 250 to 850 nm. The optimal NIR-II emission occurs at 1345 nm with a photoluminescence quantum yield (PLQY) of 29.83% when the Re⁴⁺ doping concentration is 1%. This work demonstrates an efficient, sensitizer-free method for achieving broadband NIR-II emission and provides a new material strategy for high–performance double perovskites NIR light sources. Full article