Search Results (5,401)

This study presents an assessment of ambient air quality in Chichiri and Malawi University of Business and Applied Sciences (MUBAS) locations, Blantyre City, Southern Malawi. The study aimed at assessing temporal trends, identifying exceedance of thresholds, investigating relationships between pollutants and meteorological factors, and exploring the predictability of air quality index (AQI). Five pollutants: ${\mathrm{P}\mathrm{M}}_{2.5}$, ${\mathrm{P}\mathrm{M}}_{10}$, ${\mathrm{N}\mathrm{O}}_{\mathrm{x}}$, ${\mathrm{C}\mathrm{O}}_2$ and TVOC were assessed over a two-month period using fixed low-cost sensors. Daily and hourly temporal analysis showed that pollutants peak during morning and evening hours. A significant number of exceedances for ${\mathrm{P}\mathrm{M}}_{2.5}$ and ${\mathrm{P}\mathrm{M}}_{10}$ were observed when compared to indicative thresholds. Chichiri exhibited more frequent AQI classifications in the “unhealthy” range. A strong positive relationship between ${\mathrm{P}\mathrm{M}}_{2.5}$ and ${\mathrm{P}\mathrm{M}}_{10}$ (r $=$ 0.84) and positive correlations between ${\mathrm{N}\mathrm{O}}_{\mathrm{x}}$ and ${\mathrm{C}\mathrm{O}}_2$ were observed. A multiple linear regression model achieved a high coefficient of determination (${\mathrm{R}}^2$ $=$ 0.938), identifying ${\mathrm{P}\mathrm{M}}_{10}$ and ${\mathrm{N}\mathrm{O}}_{\mathrm{x}}$ as dominant predictors of AQI variability. Temperature and humidity showed modest inverse relationship with AQI, suggesting dispersion effects. A comparison with African cities showed that the study areas’ pollution levels were within regional norms, but that there is a need for targeted mitigation. These findings underscore the importance of continuous monitoring, data-driven policy making and regional collaboration to address urban air quality challenges. Full article

We investigate $\lambda$-constacyclic codes of length n over finite commutative local rings R of characteristic p and order $q^5,$ where $q=p^m$ is an odd prime power, whose Jacobson radical $\mathcal{N}$ satisfies ${\mathcal{N}}^3=0\ne {\mathcal{N}}^2$, under the coprimality condition $\gcd (n,p)=1$. In this setting, exactly two radical types occur, namely $(3,1)$ and $(2,2)$, determined by the dimensions of $\mathcal{N}/{\mathcal{N}}^2$ and ${\mathcal{N}}^2$. For each type, we provide an explicit classification of the underlying rings and analyze the induced radical filtration of the ambient algebra $A_{\lambda }=R\left[X\right]/⟨X^n-\lambda ⟩$. We prove that every $\lambda$-constacyclic code is uniquely determined by its residual component in $A_{\lambda }/\mathrm{J}\left(A_{\lambda }\right)$ together with two torsion components arising from the radical chain $\mathrm{J}\left(A_{\lambda }\right)\supset \mathrm{J}{\left(A_{\lambda }\right)}^2\supset 0$. This residual–torsion decomposition yields explicit generating sets; in particular, every $\lambda$-constacyclic code admits a generating set consisting of at most five elements. Furthermore, we derive exact enumeration formulas for all $\lambda$-constacyclic codes. In the type $(2,2)$ case, the enumeration is governed by linear-algebraic constraints over the Chinese Remainder Theorem residue fields and, in the anisotropic class, depends on quadratic character values determined by the extension degrees. In the type $(3,1)$ case, the enumeration is controlled by the dimension of the radical of the induced symmetric bilinear form on the top radical layer, equivalently by the rank class of the associated canonical matrix. Full article

Pyropia haitanensis, an economically significant cultivated seaweed in China, exhibits substantial geographical variations in nutritional and sensory qualities that influence its market value. The nutritional quality of the samples, including total sugar, total protein, and amino acid content, as well as color quality, assessed through phycobiliprotein and chlorophyll content, and sensory quality evaluated using an electronic nose and electronic tongue, were determined. To elucidate these quality variations, this study employed an integrated metabolomics and chemometrics approach to analyze samples from five major cultivation regions. Principal component analysis (PCA) effectively differentiated the samples; orthogonal partial least squares discriminant analysis (OPLS-DA) validated this classification with robust model parameters (R²X = 0.791, R²Y = 0.995, Q² = 0.984) and identified key discriminatory metabolites. Weighted gene co-expression network analysis (WGCNA) identified origin-specific metabolic modules correlated with quality traits, revealing that pathways such as cysteine and methionine metabolism underpin the observed differences in flavor profiles across cultivation regions. Furthermore, mediation analysis quantitatively confirmed that inorganic nitrogen primarily influences key flavor attributes by regulating sulfur-containing amino acid and nucleotide metabolism. This study systematically elucidates the metabolic mechanisms governing quality formation in P. haitanensis, providing a scientific foundation for quality control and geographical origin traceability. Full article

The number of kernels per ear is a key yield parameter that reflects the effects of breeding and agronomic management practices on crop productivity. However, conventional manual counting is labor-intensive, time-consuming, and prone to human error. This study evaluated the performance of six YOLO models, trained from scratch and fine-tuned, alongside a Faster R-CNN model, for automated kernel detection and counting from manually harvested field corn ear images. Model performance was assessed for predicting the yield and harvest index (HI) of field corn under varying nitrogen and irrigation rates. Results show that models trained with fine-tuning consistently outperform those trained from scratch in both accuracy and computational speed. Among all tested YOLO models, YOLOv11x achieved the highest performance, with a precision of 0.978, a recall of 0.968, a latency of 4.8 ms, and a prediction coefficient of determination (R²_pred) of 0.858 for the test set and 0.890 for cross-year datasets. The YOLOv8x model ranked second, whereas YOLOv10x was the worst-performing model. Compared to YOLO, Faster R-CNN performed poorly. Yield and HI predictions using YOLOv11x achieved R² values of 0.881 and 0.758, respectively, and captured treatment effects. Overall, the findings demonstrate that YOLO-based architecture is highly effective for detecting kernels and predicting yield in precision agriculture applications. Full article

Quantum beams-including X-rays, synchrotron radiation, electrons, neutrons, ions, and ultrafast photon sources-are indispensable tools for probing the structure, dynamics, and electronic properties of matter. The excitation time scale ${\tau }_{exc}$ is defined operationally as the characteristic temporal interval governing externally imposed energy deposition events within the interaction volume, such as pulse duration, bunch spacing, or beam dwell time. Interpretation of beam–matter interactions has traditionally relied on steady-state or quasi-equilibrium assumptions, implicitly presuming that intrinsic material relaxation processes can accommodate externally imposed excitation. Recent advances in high-brightness synchrotron sources, X-ray free-electron lasers (XFELs), and pulsed electron beams increasingly operate in regimes where this assumption is strained, and systematic nonequilibrium effects, radiation damage, and irreversible transformations are reported even under routine experimental conditions. This work examines the role of time-scale mismatch between beam-driven energy deposition and intrinsic material relaxation as a governing constraint in beam–matter interactions. Analyzing the hierarchy of excitation, electronic relaxation, phonon coupling, and thermal diffusion time scales, the analysis introduces a dimensionless mismatch parameter $\mathsf{\Lambda }={\displaystyle \frac{{\tau }_{rel}}{{\tau }_{exc}}}$, which quantifies the competition between externally imposed excitation and intrinsic relaxation processes in beam–matter interactions. The resulting framework provides a unified physical interpretation of beam-induced damage, signal distortion, dose dependence, and nonlinear response across quantum beam modalities, framing these effects as consequences of forced nonequilibrium dynamics rather than technique-specific artifacts. Full article

Vitamin D insufficiency is highly prevalent in athletic populations residing at northern latitudes, particularly among young athletes training predominantly indoors. The impact of vitamin D on musculoskeletal health is well-established, while its influence on physical performance is not entirely clear. The aim of this study was to determine the prevalence of vitamin D insufficiency in Estonian female adolescent athletes and to examine associations of serum 25-hydroxyvitamin D [25(OH)D] with body composition, energy intake, physical performance and ferritin. Seventy-three female athletes aged 14–18 years participated. Body composition was assessed by dual-energy X-ray absorptiometry; physical performance by peak oxygen consumption (VO₂peak/kg) and countermovement jumps; dietary intake was estimated using repeated 24 h recalls; and fasting blood samples were analyzed for 25(OH)D and ferritin. The mean serum 25(OH)D concentration was 67.6 ± 21.4 nmol.L⁻¹ and ranged from 27.4 to 118.0 nmol.L⁻¹. Vitamin D insufficiency (25(OH)D < 75 nmol.L⁻¹) was present in 67% of participants, leaving only one-third with sufficient levels. Serum 25(OH)D concentration was positively associated with VO₂peak/kg (r = 0.26; p = 0.043) independent of confounding variables. In conclusion, these findings suggest that vitamin D insufficiency is highly prevalent among Estonian female adolescent athletes, and 25(OH)D concentration is associated with aerobic performance. Full article

Biosensors based on electrolyte-gated organic field-effect transistors (EGOFETs) have attracted considerable attention due to their advantages, including low cost, inherent signal amplification, and low-voltage operation. A critical step influencing sensing performance is the integration of specific receptors onto the device surface. Among various strategies, the covalent immobilization of biorecognition elements onto gold surfaces via thiol chemistry is one of the most widely used approaches. In this study, we report the optimization of a mixed self-assembled monolayer (SAM) composed of 11-mercaptoundecanoic acid (11-MUA) and 3-mercaptopropionic acid (3-MPA) for label-free detection of human IgG using EGOFETs. The quality of the SAM was systematically modulated by varying the total concentration from 10 to 400 mM and characterized using X-ray Photoelectron Spectroscopy (XPS), Electrochemical Impedance Spectroscopy (EIS), Cyclic Voltammetry (CV), and Atomic Force Microscopy (AFM). The results revealed that a concentration of 50 mM yielded a densely packed and well-ordered monolayer. After covalent immobilization of anti-IgG antibodies via 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride/N-hydroxysuccinimide (EDC/NHS) chemistry and subsequent blocking with ethanolamine and bovine serum albumin (BSA), the functionalized gate electrodes were integrated into poly(3-hexylthiophene) (P3HT)-based EGOFETs. Electrical measurements demonstrated that EGOFET biosensors functionalized with the 50 mM SAM achieved optimal sensing performance. The devices exhibited a highly linear response (R² = 0.998) over a wide concentration range from 1 fM to 10 nM, with a LOD of 2.82 fM, and showed excellent selectivity against non-target immunoglobulins A and M (IgA and IgM). This SAM concentration optimization strategy provides a versatile approach for engineering high-performance EGOFET biosensors, with potential applicability to a broad range of disease biomarkers. Full article

A 0.3 V nanowatt CCII⁻ is presented in 0.18 $\mathsf{\mu }$m TSMC CMOS, targeting ultra-low-power current-mode interfaces. Post-layout extracted simulations demonstrate correct conveying operation with a total DC power consumption of less than 2.40 nW. The low-frequency tracking factors evaluated at 1 Hz are ${\beta }_0=0.9452$ (−0.48 dB) and ${\alpha }_0=0.9609$ (≈−0.35 dB), with $-3$ dB bandwidths of 22.95 kHz and 63.95 kHz for the voltage and current transfers, respectively. Small-signal extraction confirms the intended impedance profile, yielding $R_X=46.73$ M$\mathsf{\Omega }$, $R_Z=1.204$ G$\mathsf{\Omega }$, and a very high input resistance $R_Y=392$ G$\mathsf{\Omega }$. Robustness is verified through full PVT and mismatch analyses, showing stable functionality across process corners, a 0–80 °C temperature range, and 270–330 mV supply variations while maintaining nanowatt-level dissipation. Full article

We develop the Sawyer duality principle for non-increasing functions where, in the denominator, the function g is replaced by ${\int }_x^{\infty }{\displaystyle \frac{g\left(t\right)}{t}}dt$. This result complements Stepanov’s result in which g was replaced by ${\displaystyle \frac{1}{x}}{\int }_0^{x}g\left(t\right)dt$. We use our result and obtain Stepanov’s result for non-decreasing functions and similarly use Stepanov’s result in proving our result for non-decreasing functions. These results have also been obtained in ${\mathbb{R}}^n$. Full article

In this work, the hydrogenation behavior of a near-equiatomic Ti-V-Zr-Nb-Mo-Hf-Ta-W refractory high-entropy alloy (R-HEA) exposed to pressurized hydrogen has been thoroughly investigated. Isothermal gas-phase hydrogen absorption experiments have been performed and a maximum uptake of 1.13 wt.% H has been achieved after exposure to a pure H₂ atmosphere at 350 °C and 60 bar H₂ for 6 h. This hydrogen absorption capacity is rather low compared to previous literature, where capacities as high as 2.7 wt.% have been reported. The presence of two distinct (Hf,Zr)-mixed oxides at the surface of the particles has been deduced from X-ray diffraction analyses and identified as the main reason for the relatively low H uptake and the minimal impact onto the mechanical integrity of the R-HEA after hydrogenation. The results hereby reported suggest that R-HEAs containing strong oxide-forming elements such as Hf, Zr, and Ti undergo surface hydrogenation-regeneration upon intermittent exposure to a hydrogen atmosphere. The cyclic nature of such phenomena should be further investigated, as it could lead to the development of novel, self-regenerating protective materials against hydrogen diffusion and embrittlement to be potentially used as permeation barriers. Full article

To investigate the effects of distribution characteristics of microscopic voids (including the connectivity degree, pore-throat morphology, and size) on the permeability performance of open-graded friction course (OGFC) asphalt mixtures with steel slag as the anti-skid wearing course, two-dimensional computed tomography (CT) images of OGFC steel slag asphalt mixture specimens were first obtained via X-ray technology. The MATLAB R2022b-based image subtraction algorithm was then adopted to identify the interconnected voids inside the specimens to quantitatively characterize the morphological differences in interconnected voids in OGFC steel slag asphalt mixtures with different gradations. Furthermore, Finite Element simulation by ANSYS 2021 R1 was conducted to explore the influences of the diversion angle of interconnected voids on the water flow characteristics of OGFC steel slag asphalt mixtures, involving the variation laws of water flow velocity, water pressure and flow path in the diversion structure, thereby analyzing the resultant effects on the permeability performance of the mixtures. The results show that the combination of X-ray CT scanning and image processing technology enables more convenient, accurate and intuitive characterization of the internal void distribution characteristics of the mixtures. It was found that the pore-throat properties, including size, length, quantity and equivalent diameter, are the dominant factors restricting the permeability capacity of OGFC steel slag asphalt mixtures. As the diversion angle increases from 20° to 60°, the pressure gradient increases by up to 103.92%. After passing through the diversion section, the flow velocity increases by approximately four times. The streamline density at the channel axis is 4.2–4.5 times that near the channel wall. This study realizes the rapid extraction of void characteristics and the identification of key influencing factors on the permeability performance of OGFC steel slag asphalt mixtures, an achievement that cannot be attained by the previous macroscopic research on the permeability performance of such mixtures. Full article

The correlation between fouling-driven corrosion and magnetic Barkhausen noise (MBN) in AH36 naval steel was investigated under real Mediterranean seawater conditions over a 12-month immersion period. A custom-designed MBN analyzer was used to monitor four MBN parameters at monthly intervals: RMS amplitude (MBN_RMS), peak amplitude (MBN_peak), peak field position (MBN_{peak pos.}), and full width at half maximum (MBN_FWHM). Complementary characterization included pit morphology analysis, X-ray diffraction (XRD) of corrosion products, and quantitative biofouling community profiling. Three distinct MBN evolution regimes were identified, corresponding to active pitting (T₀–T₃), transitional oxide formation (T₃–T₆), and mature corrosion equilibrium (T₆–T₁₂). Over the full exposure period, MBN_RMS decreased by 50.4% and MBN_{peak pos.} increased by 83.3%, consistent with domain wall pinning at pit stress concentrations and electromagnetic shielding by paramagnetic corrosion product layers (γ-FeOOH, β-FeOOH, α-FeOOH). Pearson correlation analysis revealed near-unity relationships between MBN_RMS and maximum pit depth (r = −0.982, p < 0.01), supporting its potential use as a quantitative non-destructive indicator of corrosion severity under comparable exposure conditions. Biofouling, particularly sulfate-reducing bacteria (SRB)-dominated communities and biogenic iron sulfides (mackinawite, greigite), was identified as a statistically significant secondary correlate of MBN signal intensity (r = −0.944 vs. SRB fraction). A composite diagnostic threshold of (MBN_RMS × MBN_peak)/MBN_FWHM ≈ 0.015 effectively discriminated active pitting from passive rusting. These findings provide a physically grounded framework for multiparametric MBN analysis as a non-destructive condition monitoring tool, with the caveat that the reported correlations are descriptive and require independent validation before deployment in regulatory inspection protocols. Full article

Alzheimer’s disease (AD) represents an escalating global neuropharmacological crisis, with prevalence in high-growth demographic regions such as India projected to exceed 14 million by 2040. This study addresses the urgent need for high-potency, dual-site acetylcholinesterase (AChE) inhibitors through an integrated computational pipeline. We address the failure of mono-target paradigms by designing scaffolds capable of simultaneously anchoring the Catalytic Active Site (CAS) and the Peripheral Anionic Site (PAS). A robust GA-MLR QSAR model was developed from 115 quinoline analogs using 11,135 descriptors. Lead candidates were prioritized via cavity directed molecular docking (7XN1) and 100 ns molecular dynamics (MD) simulations. The five-descriptor model (R² = 0.7569, $Q_{LOO}^2$ = 0.7244) was validated by an external set of 8 experimental compounds ($R_{ext}^2$ = 0.8620). Lead Compound 19 emerged as a superior candidate (ΔG = −11.1 kcal/mol), exhibiting a stable MD trajectory (PL-RMSD ≈ 2.4 Å) and preserving essential Gly121-His447 catalytic anti-correlations. This study provides a statistically validated scaffold and computational mechanistic foundation for future in vitro experimental validation, advancing the high throughput screening of neuroprotective agents on a global scale. Full article

The Zeta-Minimizer Theorem establishes that the Riemann zeta function $\zeta \left(s\right)$ and the primes arise variationally as unique minimizers of a phase functional defined on a symmetric measure space $\left(X,\mu ,G\right)$ equipped with helical operators. Three fundamental axioms—strict concave entropy maximization (Axiom 1), spectral Gibbs minima with non-vanishing ground states (Axiom 2), and irreducible bounded oscillations with flux conservation (Axiom 3)—allow for the selection of the non-proper Archimedean conical helix as the sole topology satisfying all constraints. Primes emerge as indivisible minimal cycles in the associated representation graph $\Gamma$ (via Hilbert irreducibility and Maschke’s theorem), while the Euler product is recovered through the spectral Dirichlet mapping of the helical eigenvalues. The partial zeta product, $Z\left(s\right)=\prod _j{\displaystyle \frac{1}{1-p_j^{-s}}},s\in \mathbb{R}\left\{0\right\},$ constitutes the exact grand partition function of any finite subsystem. Numerical inversion of this product directly recovers the mixture frequency $s$ from any experimental compressibility factor $Z_{\mathrm{m}\mathrm{i}\mathrm{x}}$. Mole fractions $x_i\left(s\right)$, interaction parameters $\Delta \left(x_i\right)$, and the Lyapunov spectrum $\lambda \left(x_i\right)$ then follow deductively via the helical transfer matrix and the closed-form linear ODE for $\Delta$. Occupation numbers $N\left(x_i\right)$ attain sharp maxima precisely at Fibonacci ratios $F_r/F_{r+1}$, leading to the molecular prime-ID rule. For twelve representative purely binary (irreducible) systems spanning atomic noble gases, simple diatomics, polar molecules, and an aromatic ring, the residuals satisfy $|Z\left(s\right)-Z_{\mathrm{m}\mathrm{i}\mathrm{x}}|<1.5\times {10}^{-8}$. The resulting $\lambda \left(x_i\right)$ curves accurately reproduce critical points, liquid ranges, and thermodynamic anomalies with zero adjustable parameters. The Riemann Hypothesis follows rigorously as a theorem: the unique fixed point of the duality functor $s\mapsto 1-s$ that preserves the orthogonality condition $\sum {\mathrm{c}\mathrm{o}\mathrm{s}}^2{\theta }^k=1$ is $\mathrm{R}\mathrm{e}\left(s\right)=1/2$, enforced by Axiom 1 concavity and Axiom 3 irreducibility. The framework is fully deductive and parameter-free and extends naturally to arbitrary mixtures and multiplicities through the helical representation graph. It provides a variational unification of analytic number theory, spectral geometry, thermodynamic phase behavior, and the Riemann Hypothesis from first principles. Full article

Background: Rabies is a highly fatal zoonotic disease that causes approximately 59,000 human deaths worldwide each year. Current inactivated rabies vaccines require multiple doses and are associated with high costs. The full-length rabies virus glycoprotein (RVG), a membrane protein, exhibits substantial instability in its trimeric structure during recombinant expression. This instability makes it difficult to obtain high-purity, correctly folded antigens. Objectives: This study focuses on the preparation of a full-length recombinant RVG subunit vaccine candidate expressed in a glycoengineered Pichia pastoris system with mammalian-like glycosylation. Methods: The full-length RVG gene (including the transmembrane domain and cytoplasmic tail) from the Challenge Virus Standard-11 (CVS-11) strain was codon-optimized and inserted into the pPICZαA vector to construct the recombinant expression plasmid pPICZαA-RVG. The plasmid was transformed into glycoengineered Pichia pastoris X33-7 (low-mannose type) by electroporation for inducible expression. The target protein was purified by nickel affinity chromatography, anion-exchange chromatography, and Superdex-200 size-exclusion chromatography. The structural characteristics of the purified protein were analyzed by dynamic light scattering (DLS) and transmission electron microscopy (TEM). The purified antigen was formulated with the adjuvants AS03 or MF59. BALB/c mice (n = 5 per group) were immunized intramuscularly following a four-dose schedule (days 0, 7, 14, and 28). Antigen-specific IgG antibody titers were measured by ELISA, and neutralizing antibody titers were determined using the rapid fluorescent focus inhibition test (RFFIT). Results: Glycoengineered Pichia pastoris yeast strains expressing wild-type RVG (RVG-WT) or a mutant variant (RVG-M6: R84S, R199S, H270P, R279S, K300S, and R463S) were successfully constructed. The purified RVG antigen formed nanoparticles with an average particle size of approximately 75 nm. Immunized mice generated robust RVG-specific IgG responses, with titers reaching approximately 6.31 × 10⁵ for RVG-WT after the fourth immunization, compared to 3.16 × 10³ for RVG-M6 and 5.62 × 10³ for the RVG-WT-PEG control. Two weeks after the fourth immunization, RVG-WT formulated with AS03 or MF59 induced significant neutralizing antibody responses compared with the control group (p < 0.0001 and p < 0.01, respectively). The neutralizing antibody titers reached 1:79.43 in the AS03 group and 1:33.11 in the MF59 group, whereas the WT-PEG + AS03 control group showed a low titer of 1:3.72. In contrast, RVG-M6 formulated with MF59 failed to induce detectable neutralizing antibodies (1:3.02). Furthermore, RVG-WT + AS03 induced significantly higher neutralizing antibody responses than the WT-PEG + AS03 control group (p < 0.0001), and a significant difference was also observed between the RVG-WT + MF59 and RVG-M6 + MF59 groups (p < 0.01). Conclusions: The glycoengineered Pichia pastoris expression system successfully produced uniform full-length rabies virus glycoprotein nanoparticles with high purity. When formulated with the AS03 adjuvant, RVG-WT induced high-titer neutralizing antibodies in mice, suggesting a promising strategy for the development of recombinant subunit vaccines against rabies. However, this study is limited by the absence of challenge studies and validation in target animal species, which will be further investigated in future work. Full article