Search Results (831)

Background/Objectives: Accented speech reflects systematic deviation from target-language phonetic norms. This study demonstrates that perceived accent strength covaries with selective, gradient differences in phonological feature realization. We examine whether perceived accents in Hindi- and Tamil-accented English reflect uniform segmental deviation or cue-specific patterns of phonological feature realization. Methods: English speech produced by native speakers of Hindi and Tamil was evaluated using native listener accentedness ratings. Phonetic variation was analyzed using posterior probabilities of phonological features derived from a machine learning model, Phonet. The analyses focused on liquids (laterals and rhotics (e.g., /l/, /ɭ/, and /ɻ/) and labial segments in the fricative–glide space (e.g., /v/, /w/, and /ʋ/), with attention to word position and feature-level generalization. Results: Accentedness ratings differed systematically for Hindi- and Tamil-accented English and covaried with a subset of phonological feature dimensions, yielding contrast- and context-specific patterns of perceptually relevant variation. Not all features that varied in production contributed to perceived accent strength. Conclusions: These findings support a cue-specific, perception-grounded account of accentedness and establish phonological feature posteriors derived from Phonet as interpretable phonological categories through which gradient L2 production differences are evaluated by listeners. Full article

Kolmogorov–Arnold Networks employ learnable univariate activation functions on edges rather than fixed node nonlinearities. Standard B-spline implementations require $O\left(3KW\right)$ parameters per layer (K basis functions, W connections). We introduce shared Gaussian radial basis functions with learnable centers ${\mu }_k^{\left(l\right)}$ and widths ${\sigma }_k^{\left(l\right)}$ maintained globally per layer, reducing parameter complexity to $O(KW+2LK)$ for L layers—a threefold reduction, while preserving Sobolev convergence rates $O\left(h^{s-\Omega }\right)$. Width clamping at ${\sigma }_{min}={10}^{-6}$ and tripartite regularization ensure numerical stability. On MNIST with architecture $[784,128,10]$ and $K=5$, RBF-KAN achieves $87.8\%$ test accuracy versus $89.1\%$ for B-spline KAN with $1.4\times$ speedup and 33% memory reduction, though generalization gap increases from $1.1\%$ to $2.7\%$ due to global Gaussian support. Physics-informed neural networks demonstrate substantial improvements on partial differential equations: elliptic problems exhibit a $45\times$ reduction in PDE residual and maximum pointwise error, decreasing from $1.32$ to $0.18$; parabolic problems achieve a $2.1\times$ accuracy gain; hyperbolic wave equations show a $19.3\times$ improvement in maximum error and a $6.25\times$ reduction in $L^2$ norm. Superior hyperbolic performance derives from infinite differentiability of Gaussian bases, enabling accurate high-order derivatives without polynomial dissipation. Ablation studies confirm that coefficient regularization reduces mean error by 40%, while center diversity prevents basis collapse. Optimal basis count $K\in [3,5]$ balances expressiveness and overfitting. The architecture establishes Gaussian RBFs as efficient alternatives to B-splines for learnable activation networks with advantages in scientific computing. Full article

Accurate normalization of RT-qPCR data requires selecting stable internal control genes, particularly in models characterized by dynamic metabolic transitions, such as 3T3-L1 adipocytes. The current study compares the expression stability of nine widely used housekeeping genes (HKGs) (peptidylprolyl isomerase A (Ppia), glyceraldehyde-3-phosphate dehydrogenase (Gapdh), beta-2 microglobulin (B2M), ribosomal protein, large, P0 (36b4), hydroxymethylbilane synthase (Hmbs), hypoxanthine guanine phosphoribosyl transferase (Hprt), tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta polypeptide (Ywhaz), 18S ribosomal RNA (18S), and β-actin (Actb)) across key stages of differentiation (days 0, 9, and 18) and under treatments with palmitic acid and docosahexaenoic acid. Stability was assessed using four classical algorithms—geNorm, NormFinder, BestKeeper, and RefFinder—supplemented by the ΔCt method, conventional statistical testing, correlation, and regression analysis relative to two target genes, fatty acid-binding protein 4 (Fabp4) and sterol regulatory element binding transcription factor 1 (Srebf1). The obtained data indicate that no single HKG remains universally stable across these experimental conditions, and the expression of traditionally used reference genes (Gapdh, Actb, Hprt, 18S) is highly influenced by both the stage of adipogenesis and exposure to lipid-modulating factors. In contrast, Ppia, 36b4, and B2M—despite some of them being underestimated in use as references—consistently display the lowest variability across most analytical tools, forming a reliable and functionally diverse normalization panel. It should be noted that our initial stability assessment revealed apparent discrepancies among mathematical evaluation methods, emphasizing the need for a holistic, multiple-level approach strategy. The applied combination of algorithmic and statistical methods provides a more rigorous and objective framework for assessing the stability of reference genes, which is highly recommended in such a complex adipocyte-based model. Full article

Filters and congruences are fundamental concepts in residuated lattices for characterizing their structure. In this paper, using a complete lattice L as the truth-value set and based on a triangular norm T and its induced operator ${\nu }_T$, we investigate new operational properties of $TL$-fuzzy filters and $TL$-fuzzy congruences. We first define the ${\otimes }_T$ and ${\nu }_T$-operations on L-fuzzy sets and study their effects on $TL$-fuzzy filters. Next, we examine the congruence-preserving properties and operational rules of $TL$-fuzzy congruences under ${*}_T$ and ${\diamond }_{{\nu }_T}$-compositions. Finally, leveraging the correspondence between $TL$-fuzzy filters and $TL$-fuzzy congruences, we explore the interplay and internal relationships among their respective operations. Full article

This paper analyses the role of landscape as a fundamental dimension of post-earthquake recovery in the inland areas of Central Italy, arguing that reconstruction must be understood not only as the repair of damaged buildings but as a broader territorial process affecting identity, spatial organization, and long-term settlement trajectories. In this sense, post-earthquake recovery is also interpreted as a strategic opportunity to reinforce coast–inland relationships, acknowledging the structural interdependence between inland Apennine areas and coastal urban systems. Drawing on insights from applied research conducted in the L’Aquila 2009 crater and on the conceptual framework developed within the PRIN TRIALS project, the paper discusses how seismic events accelerate pre-existing territorial dynamics and produce enduring transformations, particularly in the proximity landscapes surrounding historic centres. Rather than presenting empirical findings, the contribution offers a theoretical and operational framework aimed at integrating landscape considerations into reconstruction processes. It outlines key concepts such as landscape quality, transformative resilience, and permanent temporariness; reviews critical normative aspects linked to emergency procedures; and proposes a set of landscape-oriented guidelines and criteria for the contextual integration of reconstruction projects. These include landscape quality objectives, multiscalar readings of identity values, and operational tools such as visual-impact assessment, Project Reference Context analysis, and principles for managing transformations in peri-urban and historic environments. Overall, the paper argues that adopting a landscape-based perspective can strengthen territorial cohesion, support the sustainable redevelopment of historic centres and their surroundings, and embed post-earthquake reconstruction within broader coast–inland territorial strategies aimed at long-term resilience and balanced regional development in Apennine communities. Full article

Obesity is associated with multiple comorbidities and therefore requires a multidisciplinary approach. Particular attention is given to the role of visceral adiposity and its impact on quality of life. Childhood obesity, in particular, is a major global public health challenge with physical, psychological, and social consequences extending into adulthood. Within the framework of personalized medicine, assessing physical fitness and health-related quality of life (HRQoL) offers valuable insight for defining individualized therapeutic goals. Objective: To evaluate the relationship between physical fitness and HRQoL in children with simple obesity and to highlight the potential value of personalized approaches in pediatric obesity management. Methods: This study included 123 patients aged 8–16 years with simple obesity who were hospitalized at the Children’s Memorial Health Institute in Warsaw. Obesity was diagnosed according to CDC growth charts (OLAF study). Physical fitness was assessed using the EUROFIT test battery (8 trials), and HRQoL was measured with the Kidscreen-52 questionnaire (10 domains). Results: The overall EUROFIT test performance in the study group was significantly lower compared with population norms (p < 0.001). Similarly, HRQoL scores reported by both children and their parents were significantly below reference values (p < 0.001). Conclusions: Reduced physical fitness is strongly associated with impaired quality of life in children with obesity. Personalized interventions aimed at improving motor performance may represent an effective strategy in the prevention and treatment of pediatric obesity. Full article

Background/Objectives: Heel pressure ulcers are a relevant complication in critically ill patients and may negatively affect recovery after ICU discharge. This study investigated health-related quality of life (HRQoL) and mobility levels one year after ICU discharge in survivors who developed heel pressure ulcers. Methods: A prospective observational study was conducted in the ICU of an academic tertiary-level hospital in Milan (Italy) from 1 January 2023 to 31 December 2024. Adult survivors were enrolled, and HRQoL was assessed using the EQ-5D-5L questionnaire. Functional status at ICU discharge was evaluated using the Manchester Mobility Score and Barthel Index. This study adhered to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Results: Among 3144 ICU admissions, 52 survivors were enrolled. At ICU discharge, functional status was markedly impaired: only 15 patients (28.9%) were able to stand upright according to the Manchester Mobility Score, and none achieved even moderate levels of independence. At one year, 47 patients (90.4%) completed the follow-up, and 15 of them (31.9%) continued to report moderate-to-severe mobility limitations. The mean EQ-5D index value was 0.75 (SD 0.27), representing a significant reduction compared with Italian population norms (p < 0.001). Conclusions: ICU survivors who developed heel pressure ulcers exhibit reduced HRQoL at one year after discharge. These findings emphasize the need for structured post-ICU rehabilitation and targeted follow-up. Full article

Quantitative real-time PCR (qPCR) remains a cornerstone method for analyzing gene expression due to its high sensitivity, specificity, and reproducibility. However, for reliable results in relative quantification studies, the choice of an appropriate reference gene is critical to ensure accurate normalization. The expression of commonly used reference genes can vary depending on developmental stage and experimental conditions, making their validation essential. To date, no validated reference genes have been reported for Agrostemma githago L. (corn cockle, Caryophyllaceae). To facilitate research on genes involved in natural product biosynthesis and specialized metabolism regulation, we aimed to identify the most stable reference genes across various plant organs and cultivation conditions of this species. Drawing on previous literature, we have selected seven housekeeping genes widely used for evaluation: actin, β-tubulin, elongation factor 1α, glyceraldehyde-3-phosphate dehydrogenase, histone H3, translation elongation factor 1, and eukaryotic translation initiation factor 5A1 (for which two primer sets were tested). The nucleotide sequences of these potential reference genes were identified from the A. githago transcriptome. Using qRT-PCR, transcript levels of seven potential reference genes were estimated in 40 different A. githago samples, including 25 in vitro samples under various treatment conditions and 15 soil-grown samples representing A. githago organs in different developmental stages. Expression stability of candidate reference genes was assessed using the RefFinder platform, which combines four commonly applied statistical algorithms: geNorm, NormFinder, BestKeeper, and the comparative Δ-Ct method. The results revealed that the selection of optimal reference genes varied based on the particular organ, developmental stage and condition being examined. TIF5A1-2 (one of the two primer pairs tested) and GAPHD consistently exhibited the most stable expression under various conditions in vitro. EF1α and H3 exhibited superior performance across different organs of soil-grown plants. Moreover, our integrated analysis enabled the identification of the two most stable, universal reference genes suitable for normalization in A. githago under all tested conditions—H3 and TIF5A1-2. Our work provides a robust foundation for future transcriptomic and functional studies of the specialized metabolism of A. githago and other related species. Full article

Pronunciation assessment is central to computer-assisted pronunciation training (CAPT) and speaking tests, yet most systems still adopt a native norm, treating deviations from canonical L1 pronunciations as errors. In contrast, rating rubrics and psycholinguistic evidence emphasize intelligibility for a target listener population and show that listeners rapidly adapt their phonetic categories to new accents. We argue that automatic assessment should likewise be referenced to the target learner group. We build a Transformer-based mispronunciation detection (MD) model that computationally mimics listener adaptation: it is first pre-trained on multi-speaker Librispeech, then fine-tuned on the non-native L2-ARCTIC corpus that represents a specific learner population. Fine-tuning, using either synthetic or human MD labels, constrains updates to the phonetic space (i.e., the representation space used to encode phone-level distinctions, the learned phone/phonetic embedding space, and its alignment with acoustic representations), which means that only the phonetic module is updated while the rest of the model stays fixed. Relative to the pre-trained model, L2 adaptation substantially improves MD recall and F1, increasing ROC–AUC from 0.72 to 0.85. The results support a target-population norm and inform the design of perception-aligned, fairer automatic pronunciation assessment systems. Full article

Automated detection of impact craters is essential for planetary surface studies, yet it remains a challenging task due to variable morphology, degraded rims, complex geological settings, and inconsistent illumination conditions. This study presents a novel crater detection methodology designed for large-scale analysis of Lunar Reconnaissance Orbiter Wide-Angle Camera (WAC) imagery. The framework integrates several key components: automatic region-of-interest (ROI) selection to constrain the search space, Canny edge detection to enhance crater rims while suppressing background noise, and a modified Hough transform that efficiently localizes elliptical features by restricting votes to edge points validated through local fitting. Candidate ellipses are then refined through a two-stage adjustment, beginning with L1-norm fitting to suppress the influence of outliers and fragmented edges, followed by least-squares optimization to improve geometric accuracy and stability. The methodology was tested on four representative Wide-Angle Camera (WAC) sites selected to cover a range of crater sizes (between ~1 km and 50 km), shapes, and geological contexts. The results showed detection rates between 82% and 91% of manually identified craters, with an overall mean of 87%. Covariance analysis confirmed significant reductions in parameter uncertainties after refinement, with standard deviations for center coordinates, shape parameters, and orientation consistently decreasing from the L1 to the L2 stage. These findings highlight the effectiveness and computational efficiency of the proposed approach, providing a reliable tool for automated crater detection, lunar morphology studies, and future applications to other planetary datasets. Full article

Microtubules are cylindrical protein polymers that organize the cytoskeleton and play essential roles in intracellular transport, cell division, and possibly cognition. Their highly ordered, quasi-crystalline lattice of tubulin dimers, notably tryptophan residues, endows them with a rich topological and arithmetic structure, making them natural candidates for supporting coherent excitations at optical and terahertz frequencies. The Penrose–Hameroff Orch OR theory proposes that such coherences could couple to gravitationally induced state reduction, forming the quantum substrate of conscious events. Although controversial, recent analyses of dipolar coupling, stochastic resonance, and structured noise in biological media suggest that microtubular assemblies may indeed host transient quantum correlations that persist over biologically relevant timescales. In this work, we build upon two complementary approaches: the parametric resonance model of Nishiyama et al. and our arithmetic–geometric framework, both recently developed in Quantum Reports. We unify these perspectives by describing microtubules as rectangular lattices governed by the imaginary quadratic field $\mathbb{Q}\left(i\right)$, within which nonlinear dipolar oscillations undergo stochastic parametric amplification. Quantization of the resonant modes follows Gaussian norms $N=p^2+q^2$, linking the optical and geometric properties of microtubules to the arithmetic structure of $\mathbb{Q}\left(i\right)$. We further connect these discrete resonances to the derivative of the elliptic L-function, $L\prime (E,1)$, which acts as an arithmetic free energy and defines the scaling between modular invariants and measurable biological ratios. In the appended adelic extension, this framework is shown to merge naturally with the Bost–Connes and Connes–Marcolli systems, where the norm character on the ideles couples to the Hecke character of an elliptic curve to form a unified adelic partition function. The resulting arithmetic–elliptic resonance model provides a coherent bridge between number theory, topological quantum phases, and biological structure, suggesting that consciousness, as envisioned in the Orch OR theory, may emerge from resonant processes organized by deep arithmetic symmetries of space, time, and matter. Full article

In this work, we propose a nonlinear fractional partial differential equation model incorporating a Caputo fractional derivative in time, a second-order spatial derivative, and a nonlinear Fredholm integral term. This model accounts for memory effects, anomalous diffusion, and nonlocal interactions, offering a more realistic description of complex transport phenomena compared to classical integer-order models. To solve the model numerically, we develop a fully discrete scheme that combines Lagrange interpolation-based approximation for the Caputo fractional derivative in time with central difference discretization for the spatial derivative. This approach ensures accuracy and flexibility in handling both the fractional derivative and the nonlinear integral term. A comprehensive convergence and stability analysis is conducted, establishing second-order accuracy in space and nearly second-order accuracy in time. Rigorous error estimates confirm the reliability and robustness of the proposed scheme for practical computations. Finally, a numerical example with a known exact solution is solved to validate the method. Errors are computed in both the $L_2$ and maximum norms, and the temporal and spatial convergence orders are verified. The results, summarized in tables, demonstrate the effectiveness of the fully discrete scheme and underscore the practical utility of the proposed fractional model in complex physical and engineering systems. Full article

Background/Objectives: The selection and validation of species-specific housekeeping genes (HKGs) have become increasingly common in functional genomics, with application of quantitative Polymerase Chain Reaction (qPCR) or cDNA-based qPCR (RT-qPCR). Despite the Macrobrachium amazonicum having RNA-seq studies available, there are still no data on the most stable and consistent HKGs for use in relative gene expression analyses. Therefore, the present study aimed to identify and validate seven HKGs in M. amazonicum: Eukaryotic Translation Initiation Factor (EIF), 18S ribosomal RNA (18S), Ribosomal Protein L18 (RPL18), β-actin, α-tubulin (α-tub), Elongation Factor 1-α (EF-1α), and Glyceraldehyde-3-phosphate Dehydrogenase (GAPDH). Methods: The HKGs were identified in the M. amazonicum transcriptome, characterized for identity confirmation, and compared against public databases. Subsequently, RT-qPCR assays were prepared using muscle, hepatopancreas, gills, testis, androgenic gland, and ovary to assess the stability of the HKG markers, employing the comparative ∆Ct, BestKeeper, NormFinder, and GeNorm methods. Results: All candidate HKGs identified showed high similarity with other decapods. Reactions performed with these markers demonstrated high specificity, PCR efficiency, and elevated coefficients of determination. The comprehensive ranking, indicated that no single HKG was stable across all tissues, with HKGs showing the best stability being tissue-specific. The most stable HKGs were RPL18 and 18S. GAPDH, historically used as an HKG, showed the poorest performance in stability ranking for most tissues tested, whereas β-actin was most suitable only for ovarian. Conclusions: These data reinforce the need for species-specific HKG validation and provide an appropriate panel of reference markers for gene expression studies in the M. amazonicum. Full article

This work focuses on solving the singularly perturbed generalized Hodgkin-Huxley (HH) problem. The HH equation is numerically solved by a collocation approach using third-degree splines. The forward difference technique is utilized for time discretization, while $\theta$-weighted schemes are employed for space discretization. Solving non-linear models using discretization and quasi-linearization results in a set of linear algebraic equations, which are solved using matrices. Furthermore, Von Neumann’s (VN) stability and Spectral Radius (S.R) reveal that the suggested technique is unconditionally stable. To assess the performance and accuracy of this method, absolute error (AE), $L_2$, and $L_{\infty }$ norms are offered. The results align with the literature. Simulation results show that the proposed strategy produces accurate results. Full article

Fig (Ficus carica L.), a deciduous fruit tree that belongs to the Moraceae family, is cultivated worldwide as an important fruit crop for raw and processed foods. Quantitative real-time PCR (RT-qPCR) is a widely used method in F. carica to elucidate expression of genes related to various physiological responses. However, no studies have identified appropriate reference genes for RT-qPCR normalization in F. carica. In this study, 12 genes were selected from the F. carica genome as candidate reference genes for normalizing target gene expression. All candidate genes exhibited high amplification efficiency and specificity in the absence of primer dimers or extra PCR amplicons. The expression levels of the candidate genes were measured in three different plant tissues (fruit, leaf, and stem) under fungal pathogen infection using RT-qPCR. Their expression stabilities were evaluated using four computational algorithms: geNorm, Normfinder, delta-Ct, and BestKeeper. The RefFinder program was also used to calculate the geometric mean of the stability rankings obtained from these algorithms. The comprehensive ranking revealed that FcYLS8, FcPP2A, and FcAP2M were the most stable reference genes under biotic stress in the fruits, leaves, and stems, respectively. In contrast, traditional reference genes such as FcACT2, FcEF-1α, FcGAPDH, FcUBC21, and FcUBQ5 exhibited relatively low expression stability in all tested tissues. This study identified and validated stable reference genes for RT-qPCR normalization in F. carica, thus providing a valuable resource for accurate gene expression studies under biotic stress and highlighting the importance of validating reference genes to ensure reliable and reproducible RT-qPCR analysis. Full article