Search Results (5,638)

Human serum albumin (HSA) binding critically influences drug distribution and pharmacokinetics. In this study, HSA affinity chromatography was integrated with machine-learning-based quantitative structure–retention relationship (QSRR) modeling to elucidate structural determinants of albumin binding in a library of 115 fluoroquinolone (FQs) derivatives. Experimentally determined logk_HSA values were obtained using biomimetic chromatography, and these were then used as modelling endpoints. Following descriptor reduction via Least Absolute Shrinkage and Selection Operator (LASSO) and systematic benchmarking of 42 regression algorithms, support vector regression (SVR) and nu-support vector regression (ν-SVR) with radial basis function kernels demonstrated superior predictive performance. A parsimonious 12-descriptor ν-SVR model achieved strong calibration and validation metrics (R² = 0.916, Q²_test = 0.823, concordance correlation coefficient (CCC) = 0.899) and satisfied Organisation for Economic Co-operation and Development (OECD) criteria, including applicability domain assessment. Shapley Additive exPlanations (SHAP)-based interpretation revealed that albumin binding is governed by a balance between hydrophobic surface area and distributed electronic properties, whereas excessive localized polarity and quaternary ammonium functionalities reduce affinity. This experimentally anchored and interpretable modeling framework provides mechanistic insight into HSA binding in fluoroquinolones and offers a robust tool for rational pharmacokinetic optimization. Furthermore, in order to make the model easily accessible to users, we have packaged it in the form of an online application. Full article

The semiconductor industry has long relied on Statistical Process Control (SPC) for yield and reliability management. In early technology nodes, classic univariate tools such as Shewhart charts, cumulative sums (CUSUM), exponentially weighted moving averages (EWMA), and the Cp/Cpk exponent could effectively monitor a finite set of key variables. However, sub-5nm and emerging 3 nm technologies have fundamentally changed the statistical environment. Advanced patterning, high-aspect-ratio etching, atomic layer deposition (ALD), chemical-mechanical polishing (CMP), and novel materials have drastically narrowed the process window. At these scales, nanometer-level deviations in critical dimensions (CD), overlay, or surface roughness can significantly impact yield. Simultaneously, modern wafer fabs generate massive amounts of high-frequency sensor data and high-dimensional metrology data. Traditional SPC assumptions—such as independence, normality, low dimensionality, and stationarity—often do not hold. Semiconductor data exhibits: (i) extremely high-dimensionality and strong intervariate correlations; (ii) a hierarchical structure encompassing fab → tooling → chamber → recipe → batch → wafer → field; and (iii) metrological delays and sampling limitations leading to incomplete and asynchronous observations. To address these challenges, this paper reviews advanced statistical methods applicable to wafer fabrication. These methods include multivariate statistical process control (MSPC) approaches such as Hotelling T² statistics, PCA/PLS combining T² and Q statistics, contribution diagnostics, time-series drift and change point detection, and Bayesian hierarchical modeling for uncertainty-aware monitoring in data-limited scenarios. Furthermore, we discuss how to integrate these methods with fault detection and classification (FDC), line-to-line monitoring (R2R), advanced process control (APC), and manufacturing execution systems (MES). This paper focuses on scalable, interpretable, and maintainable implementations that transform statistical analysis from a passive monitoring tool into an active component of data-driven fab control. Full article

This paper presents a low-cost retrofitting pipeline for a legacy industrial robot that uses a single RGB webcam and monocular 2D keypoint tracking to estimate human-arm posture angles ${\mathit{\theta }}^{\left(\mathrm{h}\right)}$ and map them to robot-axis joint targets ${\mathbf{q}}_{\mathrm{cmd}}^{\left(\mathrm{r}\right)}$ for A1–A3 on a KUKA KR5-2 ARC HW, while keeping the wrist orientation (A4–A6) fixed. Rather than targeting full six-DoF manipulation, the main contribution is an experimental characterization of how far monocular 2D posture-to-axis mapping can be used reliably for coarse placement and safeguarded low-speed demonstrations on a legacy robot platform. Vision-side accuracy was evaluated per axis against goniometer-based reference angles ${\mathit{\theta }}_{\mathrm{ref}}^{\left(\mathrm{h}\right)}$, showing low errors for A2–A3 within the tested range and larger errors for A1 due to monocular yaw/depth ambiguity and occlusions. The study also analyzes failure modes during simultaneous multi-joint motion, where performance degrades notably, especially for A2 and A3, and reports practical mitigation directions such as improved viewpoints, multi-view/depth sensing, and stricter dropout handling. Runtime behavior is additionally characterized through a loop timing budget, with an end-to-end latency of 185.44 ms and an effective loop frequency of 5.39 Hz, which is consistent with low-speed online operation within the demonstrated scope. The system was implemented in a fenced industrial cell with restricted access and emergency stop; no collaborative operation is claimed. Full article

Domestication has profoundly shaped the phenotypic differentiation and genetic architecture of Perilla. However, analyses of the morphological difference between its cultivated and weedy forms across its varieties remains incomplete. This study analyzed morphological variation, genetic diversity, population structure, and marker–trait associations of 45 accessions representing the cultivated and weedy forms of two Perilla varieties (P. frutescens var. frutescens and var. crispa) collected from South Korea and Japan. Analyses of ten qualitative and quantitative agronomic traits revealed clear domestication-related differentiation. Cultivated var. frutescens showed larger and heavier seeds, whereas cultivated var. crispa and the weedy accessions were characterized by longer inflorescences and higher floret numbers but smaller seeds. Strong positive correlations were observed among seed-related traits, particularly between seed size and seed weight (r = 0.932), indicating coordinated selection of seed traits. Genetic diversity analysis using 70 SSR markers identified 330 alleles consistent with domestication bottlenecks in cultivated forms while higher diversity was generally retained in the weedy accessions. Population structure, UPGMA clustering, and principal coordinate analyses broadly differentiated the cultivated and weedy accessions, although partial admixture indicated shared ancestry and historical gene flow. Association mapping using Q-based GLM and Q + K MLM models identified 23 significant marker–trait associations involving 16 SSR markers consistently detected across both models. Several markers were associated with multiple traits, implying pleiotropy or tight genetic linkage. Notably, five SSR markers (KNUPF192, KNUPF202, KNUPF207, KNUPF230, and KNUPF238) may represent potential candidate loci for marker-assisted selection to improve seed-related traits in var. frutescens and leaf-related traits in var. crispa. Full article

The increasing penetration of renewable energy has led to the large-scale integration of power electronic devices into the power grid. In weakly connected grids, such devices are connected to the grid via voltage source converters (VSCs) using grid-forming (GFM) control strategies. Ideally, the point of common coupling (PCC) with the grid is treated as a purely inductive circuit. However, in weak grids, the resistance-to-inductance ratio (R/X) cannot be ignored, which leads to the power coupling problem between active power (P) and reactive power (Q). This phenomenon impedes the precise control of P and Q, potentially resulting in steady-state power deviations and even system instability. Traditional power-decoupling methods based on virtual inductance (VI) have inherent limitations and fail to achieve complete decoupling between P and Q. To address this issue, this paper first analyzes the influencing factors of power coupling through an established power coupling model. Comparisons between the output voltage and the degree of power coupling demonstrate that power decoupling can be achieved by compensating the output voltage. Consequently, an improved power-decoupling strategy based on apparent power feedforward (APPFF) is proposed. The proposed APPFF method realizes complete P-Q decoupling, with a steady-state reactive power error of less than 1% of the rated value. Compared with the PI-decoupling method, the reactive power overshoot is reduced by about 24%, and no additional active power overshoot is introduced. Compared with the conventional virtual inductance method that only reduces coupling by up to 35%, APPFF eliminates the power coupling fundamentally while retaining the reactive power–voltage droop characteristics and fast dynamic response. By directly compensating the reference voltage to the ideal value using apparent power as the feedforward variable, the proposed method is essentially different from the existing voltage/angle compensation schemes. The feasibility and effectiveness of the proposed decoupling method are verified under various working conditions, such as different R/X ratios, line resistances and power references, through both Simulink simulations and experimental results. Full article

Background: Left bundle branch block (LBBB) and QRS prolongation are markers of electrical dyssynchrony in heart failure, but they do not fully reflect its mechanical consequences. Myocardial work (MW)-derived indices may provide a more comprehensive assessment of left ventricular (LV) mechanical dyssynchrony. We evaluated associations between LV MW parameters, QRS duration, and LBBB in patients with heart failure with reduced ejection fraction (HFrEF) referred for ICD/CRT implantation. Methods: In this single-centre observational cross-sectional study, 96 consecutive patients referred for ICD or CRT implantation were screened. All patients underwent standardized baseline comprehensive echocardiography followed by advanced MW analysis. Myocardial work index (MWI) dispersion was assessed using two complementary methods. MWI dispersion (SD) was calculated as the standard deviation of segmental MWI values across all LV segments, and MWI dispersion (IQR) was defined as the interquartile range (IQR) of segmental MWI values. We evaluated the associations between QRS duration and MW-derived dyssynchrony parameters (individual and composite), as well as their discriminative performance for LBBB. Seven patients were excluded from further analysis due to inadequate echocardiography image quality. Results: The final study group comprised 89 patients with HFrEF (median age 65.5 years), of whom 67.4% were assigned to CRT. LBBB was present in 41.6%, and the median QRS duration was 142 ms (112–162). All analyzed LV MW indices were significantly associated with QRS duration (all q < 0.01). The strongest correlations were observed for MWI dispersion (IQR) (r = 0.58), peak strain dispersion (PSD) (r = 0.54), lateral–septal work asymmetry (r = 0.53), and MWI dispersion (SD) (r = 0.52) (all q < 0.0001). All MW indices differed significantly between patients with and without LBBB (all q ≤ 0.0001). MWI dispersion (IQR) showed the best single-marker discrimination of LBBB (AUC = 0.852). Composite indices achieved AUC = 0.84 but did not significantly improve discrimination versus MWI dispersion (IQR) alone. Conclusions: Myocardial work-derived indices of left ventricular dyssynchrony are strongly associated with QRS duration and the presence of LBBB in patients with HFrEF. Among them, MWI dispersion (IQR) was shown to be the best-performing MW marker for identifying LBBB. These findings suggest that MW dispersion may serve as a robust echocardiographic marker of mechanical dyssynchrony and warrants further investigation as a potential tool for predicting CRT response. Full article

The hypoxic microenvironment plays a critical role in the progression of canine osteosarcoma (OSA) by promoting different cellular responses, including the release of extracellular vesicles (EVs). Given the clinical aggressiveness of canine OSA, the aim of this study was to evaluate the miRNAome profile in EVs released in vitro by four canine OSA cell lines under hypoxic conditions. In particular, for this study we used two commercial canine osteosarcoma cell lines (D17 and D22) and two primary osteosarcoma cell lines obtained in our laboratory (Penny and Wall). D17, D22, Penny, and Wall cell lines were cultured under normoxic and hypoxic conditions (200 µM CoCl₂) for 24 h. EVs were isolated by size-exclusion chromatography and characterized by nanoparticle tracking analysis and Western blotting. miRNAs extracted from EVs were then sequenced and analyzed using bioinformatics approaches. The most representative miRNAs were identified and validated by qPCR using the miRCURY LNA miRNA PCR assay. miRNome profiling identified 233 miRNAs differentially expressed in EVs across all analyzed cell lines. Among these, 94 miRNAs were detected exclusively under hypoxic conditions. From this subset, 43 miRNAs were selected for further validation by qPCR. The qPCR results showed that miR-222-3p and miR-186-5p were significantly downregulated in the Wall cell line under hypoxia (p ≤ 0.05). TargetScan and pathway enrichment analyses demonstrated that miR-186-5p regulates target genes involved in different cellular processes. In human osteosarcoma, low serum levels of miR-222-3p are associated with poor prognosis, while miR-186-5p is recognized as a key hypoxia-responsive miRNA. Collectively, these results suggest the potential of EV-associated miRNAs as biomarkers in canine OSA and support their relevance in translational and comparative oncology. Full article

The rotational evolution of pulsars is governed by torque mechanisms whose mathematical structure encodes fundamental symmetries of the underlying physics. We demonstrate that the standard spin-down equation $\dot{f}=-sf-r{f}^3-g{f}^5$ derives from a discrete antisymmetry requirement, namely invariance of the torque under reversal of rotation sense, which restricts the frequency dependence to odd integer powers. We show that physically motivated plasma processes systematically break this symmetry, introducing fractional frequency exponents: viscous Ekman pumping at the crust–superfluid boundary layer ($f^{3/2}$), magnetohydrodynamic turbulent dissipation via Kolmogorov and Sweet–Parker cascades ($f^{10/3}$, $f^{11/3}$), non-linear superfluid vortex dynamics ($f^{5/2}$), and saturated r-mode oscillations ($f^{7-2\beta }$). The central result is an exact analytical resolution of the long-standing Crab pulsar braking index puzzle: the observed $n=2.51\pm 0.01$, which has defied explanation for nearly four decades, emerges naturally from the superposition of magnetic dipole radiation ($\dot{f}\propto f^3$) and boundary layer Ekman pumping ($\dot{f}\propto f^{3/2}$), with analytically derived coefficients yielding a dipole-component surface field $B_p=6.2\times {10}^{12}$ G—higher than the standard $\sqrt{P\dot{P}}$ estimate of $3.8\times {10}^{12}$ G, because that formula conflates dipole and non-dipole torques, but lower than applying the Larmor formula to the full spin-down rate ($7.6\times {10}^{12}$ G), since $32.7\%$ of the total torque is non-radiative boundary-layer dissipation. We develop the Riemann–Liouville fractional calculus formalism for these equations, showing that fractional derivatives break time-translation symmetry through intrinsic memory effects, with solutions expressed in terms of Mittag-Leffler and Fox H-functions that interpolate continuously between exponential (fully symmetric) and power-law (scale-free symmetric) relaxation. Lambert–Tsallis $W_q$ functions with non-extensive parameter q encoding broken statistical symmetry enable equation-of-state-independent inference of neutron star compactness and tidal deformability. Our framework establishes a unified symmetry-based classification of pulsar spin-down mechanisms and predicts frequency-dependent braking indices evolving at rate $\mathrm{d}n/\mathrm{d}t\sim 2\times {10}^{-4}$ yr⁻¹, yielding $\mathrm{\Delta }n\approx 0.01$ over 50 years—testable with current pulsar timing programmes. The formalism provides a coherent theoretical foundation connecting plasma microphysics at the neutron star interior to macroscopic observables in electromagnetic and gravitational wave channels. Full article

Walnut septum (WS), a major by-product of walnut processing, represents a promising source of bioactive compounds with potential antioxidant and antimicrobial properties. This study aimed to characterise the phytochemical composition of WS extracts from different habitat origins and evaluate their antimicrobial activity. Total amino acids were profiled by gas chromatography–mass spectrometry, while phenolic compounds were analysed using high-performance liquid chromatography. Both methods were evaluated according to ICH Q2 (R2) guidelines for analytical procedure validation. The results showed a complex composition of amino acids and polyphenols, including ellagic acid and quercitrin. However, it was clear that habitat variations in WS samples had a significant impact on the quantities and composition of phenolic compounds and total amino acids in WS extracts. Antimicrobial activity was assessed against Gram-positive and Gram-negative bacterial strains. Variations in antimicrobial efficacy were associated with differences in phenolic composition and content due to habitat differences in WS sample origins. Collectively, this study highlights the WS as a valuable agro-industrial by-product with potential applications as a natural source of antimicrobial compounds in food and pharmaceutical systems. Full article

Natural bioactive polysaccharides have been investigated for their ability to modulate antiviral immune responses. Polysaccharide peptide (PSP) from Coriolus versicolor previously restricted human immunodeficiency virus type 1 (HIV-1) entry into monocytic cells through a protein kinase R (PKR)-dependent cytoskeletal mechanism. However, its impact on antiviral signaling in adaptive cluster of differentiation 4 (CD4)+ T-cell models remains incompletely defined. Here, we evaluated concentration- and time-dependent effects of PSP (50–1000 µg/mL) in Jurkat T cells over 3 and 6 days. Cell viability was assessed by MTT, trypan blue exclusion, and viable cell density analysis. Immunoblotting and reverse transcription quantitative polymerase chain reaction (RT-qPCR) were performed to examine Toll-like receptor 4 (TLR4), nuclear factor kappa B (NF-κB), signal transducer and activator of transcription 1 and 2 (STAT1/STAT2), PKR, interferon gamma (IFN-γ), and cofilin-1 signaling. PSP did not induce cytotoxicity at any concentration. Instead, PSP promoted dose- and time-dependent upregulation of intracellular TLR4, PKR, phospho-PKR (Thr446), Cofilin-1, phospho-Cofilin-1 (Ser3), phospho-STAT1 (Tyr701), phospho-STAT2 (Tyr690), phospho-NF-κB (Ser536), and IFN-γ, with amplified responses at Day 6. These changes were paralleled by transcriptional induction of antiviral-associated genes. Collectively, PSP induces coordinated interferon (IFN)-associated and cytoskeletal regulatory signaling in Jurkat T cells without cytotoxicity, providing a mechanistic framework for future evaluation of viral permissiveness and antiviral responses in adaptive immune models. Full article

Entropic cosmology with the Rényi entropy of the apparent horizon $S_R=(1/\alpha )ln(1+\alpha S_{BH})$, where $S_{BH}$ is the Bekenstein–Hawking entropy, is studied. By virtue of the thermodynamics–gravity correspondence, a model of dark energy is investigated. The generalized Friedmann equations for the Friedmann–Lemaître–Robertson–Walker spatially flat universe with barotropic matter fluid are obtained. We compute the dark energy density ${\rho }_D$, pressure $p_D$, and the deceleration parameter q of the universe. At some model parameters, the normalized density parameter of the matter ${\mathsf{\Omega }}_{m0}\approx 0.315$ and the deceleration parameter $q_0\approx -0.535$ for the current epoch, which are in the agreement with the Planck data, are found. Making use of the thermodynamics–gravity correspondence, we describe the late-time acceleration of the universe. The entropic cosmology considered here is equivalent to cosmology based on the teleparallel gravity with the definite function $F\left(T\right)$. The Hubble parameters are in approximate agreement (within 5 percents) with the observational Hubble data for redshifts $0.07\le z\le 1.75$ at the entropy parameter $\alpha \approx 0.305G{H}_0^2$. Full article

Siponimod, a selective sphingosine 1-phosphate (S1P) receptor modulator, represents a next-generation therapeutic drug for active secondary progressive multiple sclerosis. This study conducted in-depth forced degradation studies of siponimod in solid state subjected to acidic, alkaline, oxidative, photolytic, and thermal conditions, in compliance with ICH guidelines Q1A (R2) and Q3A (R2). An HPLC method was developed to quantify siponimod and separate its degradation products (DPs). The DPs were characterized using LC-HRMS/MS and LC-MSⁿ techniques. Moreover, the toxicological profiles of siponimod and its DPs were evaluated through the in silico tools ProTox 3.0 and ADMETlab 3.0, with molecular docking and dynamics simulations assessing their binding to the S1P1 receptor. Siponimod was stable to light but degraded under acidic, alkaline, oxidative, and thermal stress, producing five products: DP-1 (acidic), DP-2/3 (oxidative), DP-4 (hydrolytic), and DP-5 (thermal). The toxicity prediction suggested that neither siponimod nor its DPs exhibited carcinogenic or mutagenic potential, and the molecular modeling analysis revealed that DP-2 and DP-3 demonstrated favorable binding affinities, with stable dynamic profiles and thermodynamic properties that closely resembled those of siponimod. As far as we know, this is the first study on the structural elucidation of the DPs of siponimod by LC-HRMS/MS and LC-MSⁿ. Full article

As a representative form of extreme weather, typhoons inflict widespread and systemic damage, posing a severe threat to the livestock industry. The stress they induce, typhoon stress (TS), is an unavoidable and complex environmental challenge that severely disrupts the ovarian function of Wenchang chickens. In this preliminary study, we employed a two-group comparison design (n = 6 per group) integrating behavioral observations, serum biochemical assays, histopathological examinations, and molecular analyses (qPCR, 16S rDNA sequencing, and transcriptome sequencing) to explore the role of the microbiota–gut–brain–ovarian axis (MGBOA) in this process. The findings revealed that TS markedly reduced water intake and locomotor activity, while it elevated serum corticosterone (CORT) and oxidative stress markers. It also induced shifts in gut microbiota composition, including a decrease in Bacteroides and an increase in Escherichia–Shigella. Furthermore, TS compromises duodenal intestinal barrier integrity, as evidenced by downregulation of the tight junction proteins TJP1 and CLDN1, structural damage to intestinal villi, and a reduced villus-to-crypt ratio. In the hypothalamus, VIP mRNA expression was upregulated, while GHSR expression was downregulated; the expression of the tight junction protein CLDN5 was also reduced. In the ovary, reproductive potential was suppressed, manifested by a reduction in follicle number and downregulation of STAR expression. Ovarian transcriptome analysis highlighted enrichments in pathways associated with inflammation (e.g., Toll-like receptor signaling) and lipid metabolism (e.g., PPAR signaling). These results support the hypothesis that TS impairs egg production via the MGBOA, providing preliminary mechanistic insights into how environmental stressors might disrupt animal productivity through MGBOA-mediated pathways. Full article

This paper develops novel similarity and dissimilarity measures for $(p,q,r)$-fractional fuzzy sets to enhance information discrimination and decision-making under complex uncertainty. We first introduce axiomatic dissimilarity measures and establish their fundamental mathematical properties, including boundedness, symmetry, monotonicity, and identity conditions. Based on these, we derive corresponding similarity measures that improve discrimination capability. We further propose a multi-criteria group decision-making framework to facilitate robust, accurate ranking of alternatives by integrating the developed measures into a $(p,q,r)$-fractional fuzzy inferior ratio method. The approach evaluates alternatives using relative inferiority relationships and provides stable, reliable rankings in uncertain environments. Illustrative examples demonstrate the proposed method’s effectiveness and applicability, and sensitivity analysis examines decision robustness. Comparative analysis with existing methods confirms the superiority of the proposed framework, showing that it offers stronger discrimination ability and serves as a flexible, reliable tool for complex multi-criteria group decision problems under $(p,q,r)$-fractional fuzzy environments. Full article