Search Results (2,224)

Gaussian networks are degree-four symmetric interconnection networks defined over residue classes of Gaussian integers. Earlier work showed that, when the generator $\alpha =a+bi$ satisfies $gcd(a,b)=1$, the real and imaginary dimensions directly form two edge-disjoint Hamiltonian cycles. A later construction extended the result to the non-coprime case $gcd(a,b)=d>1$, but its proof relied on long node-sequence tables and separate odd/even cases for d. This paper presents a unified closed-form construction that covers both $d=1$ and $d>1$, and both odd and even d, without separate case tables. In the rectangular representation with d rows and $r=(a^2+b^2)/d$ columns, the construction uses a constant-time local switch rule, meaning constant time per individual switch, for each $q=1,2,\dots ,d-1$ at column $a_q=q-1$. Each switch removes two horizontal edges and inserts two vertical edges. The switched horizontal structure forms the first Hamiltonian cycle, while its edge-complement in the Gaussian network forms the second Hamiltonian cycle. Thus, the full edge set is partitioned into two edge-disjoint Hamiltonian cycles. The construction requires $O\left(d\right)$ switch-generation time and $O\left(N\right)$ time to list the two cycles, where $N=a^2+b^2$. Exhaustive validation for all $1\le a\le b\le 100$, excluding only the degenerate $N=2$ network, and large-scale validation up to $N=3,250,000$ confirm implementation correctness and demonstrate practical scalability. Full article

Copper and its alloys are widely used in electrical, automotive, aerospace, and energy applications because of their excellent thermal and electrical conductivity. However, the low hardness and poor wear resistance of pure Cu limit its use under tribologically demanding sliding conditions. In this study, Cu matrix composites reinforced with 1 wt.% boron carbide (B₄C), boron (B), chromium (Cr), cobalt (Co), alumina (Al₂O₃), and graphite (Gr) were fabricated by powder metallurgy and comparatively evaluated under identical processing and testing conditions. Phase constitution and microstructural characteristics were analyzed by XRD, SEM, and EDS, while mechanical and tribological behavior was assessed by Vickers hardness and dry sliding wear tests. All reinforcements improved the hardness of the Cu matrix compared with unreinforced Cu. The hardness increase followed the order Cu–B₄C (68.91%) > Cu–B (66.43%) > Cu–Gr (63.97%) > Cu–Al₂O₃ (61.79%) > Cu–Cr (42.69%) > Cu–Co (36.04%). Dry sliding wear tests, performed under a 10 N normal load, 0.05 m s⁻¹ sliding speed, and 1000 m sliding distance against a 316L stainless-steel ball, showed that all reinforced composites exhibited lower mass loss and more stable sliding behavior than pure Cu. Among all samples, Cu–B₄C displayed the best wear performance, with a 154.8% improvement in wear resistance relative to pure Cu. SEM analysis of the worn surfaces revealed that reinforcement addition reduced severe plastic deformation, groove formation, and delamination, leading to a more stable wear regime. Graphite- and boron-containing composites benefited from interfacial lubrication and contact stabilization, whereas B₄C and Al₂O₃ improved wear resistance through rigid-particle strengthening and enhanced load-bearing capacity. By comparing ceramic, metalloid, metallic, oxide, and solid-lubricating reinforcements at the same low addition level and under identical processing and testing conditions, this study provides a reinforcement-selection framework for Cu-based composites requiring improved hardness and dry-sliding durability. Full article

This retrospective quantitative data analysis study aimed to investigate sex- and age-related differences in the physiological distribution of [¹⁸F]FDOPA uptake in long axial field-of-view (LAFOV) PET images across a range of organs and tissues. A retrospective quantitative data analysis study of 106 anonymized PET/CT images acquired from vertex to mid-thigh with minimal abnormalities, divided in two gender groups and two age groups was used for this study. The mean and max lean body mass weighted standardized uptake values ($SU{L}_{mean}$, $SU{L}_{max}$), target-to-background ratios ($TBR$), and coefficients of variation ($CoV$) were used to quantify tracer uptake. Sex- and age-related differences in uptake were organ- and metric-specific. Most organs showed comparable uptake between males and females. However, males exhibited higher absolute uptake in metabolically active organs and females showed greater intra-organ heterogeneity. Aging was generally associated with increased tracer uptake and variability, especially in women, with the hip showing higher uptake in younger individuals. Statistically significant differences were most prominent in women and varied by organ and metric. In conclusion, both sex and age significantly influence [¹⁸F]FDOPA PET tracer uptake and variability in an organ- and metric-specific manner. Incorporating sex- and age-adjusted reference values may improve the accuracy and personalization of PET imaging in clinical and research settings. Full article

Hydrogen is a clean and renewable energy carrier, but its reversible storage near ambient conditions remains a major challenge. Here, density functional theory (DFT) combined with ab initio molecular dynamics (AIMD) is employed to assess the newly predicted 2D orthorhombic diboron dinitride (o-B${}_2$N${}_2$) monolayer, in pristine and Li-functionalized forms, as a hydrogen storage medium. On the pristine surface, H${}_2$ physisorbs with binding energies of −0.158 to −0.174 eV. Li atoms anchor strongly at the hexagonal hollow sites ($E_{\mathrm{bind}}$ from −0.979 to −1.321 eV, strongest at the B-rich H1 site), donate 0.65–0.84 $\left|e\right|$ to the substrate, and render the semiconducting monolayer metallic. A positive cluster formation energy ($+0.171$ eV per Li pair) and a 5 ps AIMD simulation at 400 K confirm that the Li adatoms remain dispersed, without clustering. Each Li${}^{+}$ center polarizes and binds up to five H${}_2$ molecules, with average adsorption energies of −0.207 to −0.336 eV/H${}_2$, within the optimal window for room-temperature reversible storage. The 4Li@o-B${}_2$N${}_2$(20H${}_2$) system attains a theoretical gravimetric capacity of 15.12 wt% and a practical capacity of 10.99 wt% under realistic operating conditions (charging at 30 atm/25 ${}^{\circ }$C; release at 3 atm/100 ${}^{\circ }$C). These results establish Li-functionalized o-B${}_2$N${}_2$ as a promising hydrogen storage material that merits experimental exploration. Full article

This paper introduces and investigates a novel two-parameter sequence, termed the biparametric Appell extension (B-App-Ex) and denoted by ${\mathcal{B}}_n(x;\lambda ,\alpha )$. Standard classical Appell sequences often lack sufficient structural parameters, which can limit their operational flexibility in certain advanced spectral schemes. To address this limitation, we construct an enhanced operational framework by integrating a binomial structural kernel ${(1+w)}^{\lambda }$ with a linear exponential scaling $e^{\alpha xw}$ entirely within the Appell class. We provide a rigorous logical deduction of the fundamental properties of this sequence, including its explicit power series representation, a characteristic three-term recurrence relation, and a governing second-order differential equation (DEq.). A significant contribution of this work is the establishment of analytically exact connection and inverse connection formulas between the B-App-Ex basis and various classical orthogonal polynomial (COP) families. Numerical verification via a collocation-based projection framework demonstrates that these algebraic kernels achieve near-machine epsilon precision (≈${10}^{-15}$), remaining stable even for high-order approximations. Furthermore, by isolating the dilation factor $\alpha$, we establish an $O\left(N\right)$ computational complexity that offers a reduction in latency by approximately two orders of magnitude compared to classical matrix-based transformations. The results demonstrate that the proposed biparametric (Bip.) extension offers a versatile and highly optimized analytical template for modeling complex dynamic systems where structural shifting and spatial scaling must be tuned simultaneously. Full article

Microplastics, MPs, plastic particles with dimensions between 0.1 and 5 mm, represent an important environmental pollutant. The removal of microplastics from natural and wastewater is a challenging research topic. In this regard, high-performance technical solutions must be identified, which can be based on existing treatment and purification technologies, to ensure their removal at concentration values in accordance with the legislation in force. In this study, the efficiency of removing some fractions of polyurethane microplastics, with dimensions smaller than 500 µm, from aqueous synthetic solutions with a concentration of 0.2 g L⁻¹, i.e., around 175 NTU, was evaluated. In the first stage of the study, the doses of coagulants and flocculants effective for the removal of microplastics were identified through the Jar Test. The variation in turbidity and their removal efficiencies were evaluated in the presence of classic coagulants, such as aluminum sulfate, Al₂(SO₄)₃·18H₂O, SA; iron sulfate (ferrous sulfate), FeSO₄, IS; polyaluminum chloride, [Al₂(OH)_nCl_6-n], PAC; Aloe Vera, AV, a flocculant; and activated carbon, AC, of the Norit GAC 830 W type. Classic coagulants, such as aluminum sulfate, have a good efficiency in removing microplastics, being able to provide a residual turbidity in the range of 6–10 NTU after a retention time of 50–60 min. In the second stage of the study, the removal efficiency of microplastics was tested using a laboratory pilot plant—called in the study the Smart Decantation-Filtration System, SDFS. The efficiency of the decanter was studied using Response Surface Methodology (RSM) to identify mathematical models that characterize the influence of key process variables: flow rate (A), microplastic size (B) and aluminum sulfate concentration (C) on microplastic removal efficiency. Sedimentation in the specially constructed decanter can raise the optimal value of the removal efficiency of polyurethane microplastics to 98.98%, and filtration can ensure an efficiency that reaches over 99.5%. Through this research, we aimed to identify viable solutions that can be applied to remove microplastics, MPs, from natural and wastewater. A novel element is the fact that we chose to study the removal of polyurethane, which is studied little in the literature. We identified the optimal doses of coagulants and flocculants that help sedimentation of MPs. The efficiency of an installation called Smart Decantation-Filtration System, specially designed to ensure increased efficiency in the removal of microplastics, was determined. The results obtained were encouraging. Full article

Background/Objectives: Resistant pathogenic bacteria and fungi are a growing problem worldwide; therefore, the discovery of new active ingredients is an important challenge for which the functionalization of natural terpenes with biologically active heterocycles can provide a basis. To reach this goal, a series of 1,4-disubstituted-1,2,3-triazole conjugates was designed and synthesized starting from commercially available α-santonin. Methods: The key azido derivative intermediate was prepared according to literature procedures via Michael addition between dehydrosantonin and the TMSN₃/AcOH/Et₃N system at its highly reactive α-methylene-γ-lactone motif. Subsequently, the obtained azide was applied to regioselective Huisgen 1,3-dipolar cycloaddition reaction with a wide range of terminal alkynes bearing N-, S- and O-heterocycles. These include pyridine, pyrimidine, purine, quinoline, indol, or coumarin to afford the sesquiterpene–heterocycle chimaeras. All triazole conjugates were screened for in vitro antiproliferative activity by MTT assay against HeLa, MDA-MB231, SiHa, MCF-7 and A2780 human cancer cell lines compared with fibroblast cells (NIH/3T3) to check their cytotoxicity and antimicrobial effects on two Gram-positive (B. subtilis, S. aureus) pathogenic bacteria, two Gram-negative (E. coli and P. aeruginosa) pathogenic bacteria, and two yeasts (C. krusei and C. albicans). Results: The results indicated that most of the examined compounds expressed weak activity against human cell lines, while some of them showed moderate activity against S. aureus (up to 99% inhibition at 100 µg/mL conc.), C. krusei (up to 51% inhibition at 10 µg/mL conc.) and C. albicans (up to 52% inhibition at 10 µg/mL conc.). Conclusions: Further structural modification of the best, selective antibacterial and antifungal compounds may open the possibility to the development of effective natural sesquiterpene-based selective antimicrobial agents. Full article

Background: Chatbots are becoming increasingly valuable in clinical settings, offering rapid access to medical information, aiding documentation, and improving perioperative patient education. Their adaptability makes them promising tools for personalized perioperative risk stratification (PRS) and anesthesia planning, but their definitive role remains uncertain. We aimed to evaluate chatbot performance in PRS compared to standard clinical judgment and to assess the certainty of the evidence supporting their use. Methods: This systematic review (PROSPERO ID: CRD42025642357) followed PRISMA extended and PRISMA-S guidelines. The population was defined according to the PICO framework: we included adult surgical patients undergoing anesthesia assessment (P), evaluated with LLM-based chatbots for perioperative risk stratification and anesthesia planning (I), compared with traditional clinician assessment (C), and extracted performance metrics (O). Comprehensive searches of PubMed, MEDLINE, Scopus, Embase, Google Scholar, Open Gray, ClinicalTrials.gov, WHO ICTRP, and Cochrane Library Central were conducted through January 2026. Risk of bias and study quality were assessed using PROBAST-AI, RoB-2, and ROBINS-I. Certainty of the evidence was assessed using GRADE system. A random-effects meta-analysis of pooled chatbot accuracy was performed, with subgroup analyses by ASA status and perioperative risk stratification. A sensitivity analysis was performed with a leave-one-out exclusion test. Results: Eleven studies published between 2023 and January 2026 were included (N = 227,059 patients). Five prospective cohorts, two large retrospective cohorts, one randomized non-inferiority trial, and three non-clinical or mixed-methods studies were found. Meta-analysis showed that the pooled accuracy of LLM-based chatbots for AI–clinician concordance in perioperative risk stratification and ASA classification was 0.90 [95% CI: 0.42–0.99; 95% prediction interval 0.03–1.00]. Subgroup analyses indicated that the ASA status prediction subgroup reached a pooled accuracy of 0.91 (95% CI: 0.46 to 0.99), whereas the exploratory perioperative risk stratification subgroup showed an accuracy of 0.73 (95% CI: 0.10 to 0.98). Performance decreased with increasing patient complexity. Evidence is limited by small sample sizes, extreme sample size skew toward a single center, geographic bias, inconsistent outcome definitions and performance metrics, and incomplete reporting of adverse events. Most studies lacked prospective trial registration or robust control for confounding, and publication bias cannot be excluded. Conclusions: LLM-based chatbots show promising performance in routine perioperative risk stratification but remain unreliable in complex cases, with potential safety concerns. Given the overall very low GRADE certainty of evidence, these tools should be used as clinician-supervised decision support aids for routine ASA assessment, and should not be relied upon for autonomous use in complex cases or for general perioperative risk stratification. Other: This research received no external funding. PROSPERO ID: CRD42025642357. Full article

To explore the treatment-efficient photocatalytic system for organic peroxide production wastewater under visible light, the g-C₃N₄ catalyst, synthesized via thermal polycondensation, exhibited distinct optical absorption properties confirmed by UV-vis diffuse reflectance spectroscopy (UV–vis DRS). Operational parameters—specifically pH, catalyst loading, light intensity, and reaction time—were systematically optimized. Under optimal conditions (pH 5, g-C₃N₄ dosage 1.0 g/L, light intensity 1300 W/m², reaction time 4 h), the system removed 72.8% of the COD, significantly enhancing the wastewater biodegradability (B/C ratio increased from 0.118 to 0.193). Analytical techniques, including gas chromatography–mass spectrometry (GC-MS) and UV-vis absorption spectroscopy, verified the effective decomposition of organic contaminants. Furthermore, radical quenching assays identified superoxide radicals (·O₂⁻) and photogenerated electrons (e⁻) as the primary reactive species driving the photocatalytic process, highlighting the potential of g-C₃N₄ for industrial wastewater pretreatment. Full article

We develop a collection of nontrivial examples that illustrate and test recent stability results for linear control systems ($LCS$) on Lie groups. We treat the main structural classes: Abelian (${\mathbb{R}}^n$), nilpotent (Heisenberg), solvable non-nilpotent (rigid motions of the plane $SE\left(2\right)$), compact semisimple ($SO\left(3\right)$), noncompact semisimple ($SL(2,\mathbb{R})$ via Iwasawa decomposition) and mixed/Levi-type groups. The examples are designed to (i) show the sharpness of geometric boundedness criteria, (ii) exhibit typical failure modes (exponential escape, polynomial central drift, noncompact neutrals), and (iii) demonstrate how the canonical quotient and suitable outputs recover $BIBO$ stability. The executive framework ($ICS$ existence/uniqueness, canonical quotient $G/\Gamma$, $BIBO$ characterization, robustness and ISS-type bounds) is briefly recalled; the main part of the paper consists of detailed worked examples implementing the practical checklist for applying these theorems. Full article

Masked diffusion language models (MDLMs) apply full bidirectional attention at every denoising step, which incurs $\mathcal{O}\left(T{n}^2\right)$ cost in the number of steps T and the sequence length n. For an 8B parameter model at n = 8192 with T = 128, the KV cache alone exceeds 40 GB and rules out long document generation on a single GPU. We introduce SW-SpeedDLM, an inference wrapper for pretrained MDLMs that generates sequences of up to 16,384 tokens on one A100 with 40 GB. The framework comprises three components, each targeting a distinct bottleneck. Segmented SlidingWindow Denoising (SSWD) restricts each denoising loop to a window of W tokens and reduces the per-step cost to $\mathcal{O}(W^{2}n/S)$. Cross-Segment KV Compression (CSKV) encodes each completed window into C summary tokens that later windows attend to at $\mathcal{O}\left(C\right)$ cost. Window Level Speculative Acceptance (WLSA) lets a small draft model propose k denoising steps that the target model verifies in a single forward pass, yielding up to 2.4× per window speedup. We prove that WLSA preserves the exact marginal distribution of the target model. On MDLM-860M and LLADA-8B across PG-19, LongBench, and WritingPrompts, SW-SpeedDLM achieves 3.7× higher throughput at n = 8192 than full attention generation at n = 2048 (its maximum feasible length) and lowers peak memory by 2.5× relative to full attention at n = 4096, the longest length full attention can support before exhausting GPU memory, while also increasing PG-19 bits per character by only 0.18. Full article

This study was conducted to explore how varying the concentration of nano-La₂O₃ particles in the plating bath influences the morphology, constitution, and corrosion resistance of Ni-B composite coatings deposited on N80 carbon steel via electroless plating. The novelty of this work lies in the systematic investigation on the co-deposition behavior and grain refinement mechanism of nano-La₂O₃ in electroless Ni-B system, which has been rarely reported in previous studies. The microstructure and chemical composition of the coatings were characterized through a combination of SEM, EDS, XPS and XRD analyses. SEM confirmed that a dense Ni-B/La₂O₃ composite coating was formed, with a uniform thickness of approximately 10 μm, and the nano-La₂O₃ particles were evenly distributed. XPS analysis verified the presence of B, C, O, Ni and La, while XRD analysis revealed a refinement in crystalline size due to the addition of the nanoparticles. The corrosion resistance enhancement mechanism is attributed to the triple synergistic effect: nano-La₂O₃ pins grain boundaries and refines Ni-B grains to the minimum average size of 12.943 nm at the optimal concentration of 8 g·L⁻¹; the refined grain structure promotes the formation of a continuous and dense Ni(OH)₂ passive film; the uniformly dispersed nanoparticles act as physical barriers to block the penetration of corrosive media. Electrochemical measurements demonstrated that this coating exhibited outstanding anti-corrosion performance, as confirmed by a remarkably positive corrosion potential (E_corr = −0.37189 V) and a minimal corrosion current density (I_corr = 3.7524 μA/cm²). The results conclusively show that nano-La₂O₃ reinforcement effectively enhances the corrosion protection performance of electroless Ni-B alloy coatings. Full article

Post-exercise release of cardiac biomarkers reflects physiological adaptations of the myocardium to exercise; however, data on their kinetics after exhaustive exercise under hypoxia remain scarce. We determined the kinetics of cardiac biomarker changes following a single bout of exercise to volitional exhaustion under normoxia and moderate normobaric hypoxia (2000 m and 3000 m a.s.l.) in trained (n = 12; VO_2max 64.2 ± 2.9 mL·kg⁻¹·min⁻¹) and untrained (n = 12; VO_2max 44.1 ± 7.4 mL·kg⁻¹·min⁻¹) men. Participants performed a graded exercise test (GXT) followed by a constant-workload exercise test (CXT) at the lactate threshold under three conditions (FiO₂ = 20.9%, 16.5%, 14.4%). Venous blood was sampled at rest, immediately post-exercise, and at 2, 6, and 24 h of recovery for determination of cardiac troponin T (cTnT) and I (cTnI), myoglobin (Mb), creatine kinase MB isoform (CK-MB), heart-type fatty acid-binding protein (H-FABP), ischemia-modified albumin (IMA), and N-terminal pro-B-type natriuretic peptide (NT-proBNP) by ELISA. Exhaustive exercise induced significant elevations in all biomarkers, peaking at 2–6 h post-exercise and largely returning to resting values by 24 h. Moderate normobaric hypoxia did not augment the cardiac biomarker response; rather, it attenuated the increases in Mb, NT-proBNP, and IMA, likely due to earlier peripheral fatigue and lower absolute mechanical work. The inhibitory effect of hypoxia on cTnI release was observed exclusively in trained men, suggesting an interaction between training-related cardiac adaptations and the hypoxic stimulus. These findings support the safety of high-intensity exercise at simulated altitudes of 2000–3000 m a.s.l. Full article

Biostimulants from Ascophyllum nodosum (L.) are effective as regulators of molecular, physiological and biochemical processes in plants. Two independent experiments were conducted using foliar application in Rosa × hybrida variety White O’Hara of two A. nodosum-based biostimulant formulations (B1: A. nodosum (10% w/v), N, P₂O₅, K, Ca, Mg, oxidizable total organic carbon (3% w/v), minor elements, and free amino acids (3.9% w/v); B2: A. nodosum (11% w/v), oxidizable total organic carbon (6.8% w/v) N (37.2% w/v), and P₂O₅ (50% w/v)). Each experiment was conducted in a Randomized Complete Block Design (RCBD) with a factorial arrangement including four treatments (0; 0.5; 1.0; and 1.5 mL L⁻¹), which were evaluated over two production cycles. Foliar chlorophyll (μmol m⁻²), stomatal conductance (mmol m⁻² s⁻¹), and leaf vapor pressure deficit were measured every two weeks, and productivity was evaluated at the end of the cycle. Statistical differences were detected in chlorophyll content for the application of B1 and B2 over two production cycles with increases of around 16–17% in chlorophyll compared to the control. Significant differences in stomatal conductance were detected during weeks 20 and 22 for all doses. The control treatment consistently exhibited lower means for the leaf vapor pressure deficit compared to B1 and B2. Biostimulants improved photosynthetic activity and carbon assimilation and also delayed leaf senescence. B1 at 1 mL L⁻¹ reduced unproductive stems from 54% to 38% compared to the control. Biostimulant treatments enhanced physiological tolerance to temperature extremes (2.2–32.6 °C). Based on the results, 1.5 mL L⁻¹ of the B1 biostimulant and 1 mL L⁻¹ of the B2 are recommended; these findings offer key insights for optimizing rose cultivation and prove that intensive floriculture can be both productive and sustainable. Full article

Single image dehazing remains a fundamental challenge in computer vision due to the ill-posed nature of the inverse problem and the spatial heterogeneity of real atmospheric haze. Existing convolutional approaches suffer from two structural deficiencies: bounded receptive fields that fail to model large-scale haze gradients, and isotropic kernels insensitive to the directional patterns of atmospheric scattering. This paper proposes ACTA-AOD, a lightweight end-to-end dehazing network that addresses both limitations within a unified framework built upon the AOD-Net K-parameterization. The network integrates two complementary modules: (1) W-EMSAv2, a windowed efficient multi-scale attention module that reduces attention complexity from $\mathcal{O}(N^{2}C)$ to $\mathcal{O}(N{M}^{2}C/4)$ while preserving full-spectrum spatial information through pixel-shuffle reconstruction; and (2) the ACTA Fusion module, which combines structural-reparameterization-based asymmetric convolution with cross-dimensional Triple Attention for direction-sensitive local detail recovery at zero inference-time overhead. On the RESIDE benchmark, ACTA-AOD achieves peak signal-to-noise ratio (PSNR) of 26.02 dB and structural similarity index measure (SSIM) of 0.910 on indoor synthetic data, and 26.13 dB/0.910 on outdoor synthetic data, surpassing the AOD-Net baseline by $+3.41$ dB (indoor) and $+3.58$ dB (outdoor) in PSNR, and exceeding the strongest learning-based baseline (AECRNet, CVPR 2021) by $+1.17$ dB (indoor) and $+1.75$ dB (outdoor). The model processes images at 81 frames per second on a single GPU. Ablation studies and stratified robustness evaluation across five haze density levels confirm the complementary, synergistic contribution of each module. Full article