Search Results (1,197)

This paper presents a hybrid computational architecture for efficient and robust digital transmission inspired by helical genetic structures. The proposed system integrates advanced modulation schemes, such as multi-pulse-position modulation (MPPM), high-order quadrature amplitude modulation (QAM), and chirp spread spectrum (CSS), along with Reed–Solomon error correction and quantum-assisted search, to optimize performance in noisy and non-line-of-sight (NLOS) optical environments, including VLC channels modeled with log-normal fading. Through mathematical modeling and simulation, we demonstrate that the number of helical transmissions required for genome-scale data can be drastically reduced—up to 95% when using parallel strands and high-order modulation. The trade-off between redundancy, spectral efficiency, and error resilience is quantified across several configurations. Furthermore, we compare classical genetic algorithms and Grover’s quantum search algorithm, highlighting the potential of quantum computing in accelerating decision-making and data encoding. These results contribute to the field of operations research and supply chain communication by offering a scalable, energy-efficient framework for data transmission in distributed systems, such as logistics networks, smart sensing platforms, and industrial monitoring systems. The proposed architecture aligns with the goals of advanced computational modeling and optimization in engineering and operations management. Full article

The entropy function, as a measure of information and uncertainty, has been widely applied in various scientific disciplines. One notable extension of entropy is exponential entropy, which finds applications in fields such as optimization, image segmentation, and fuzzy set theory. In this paper, we explore the continuous case of generalized exponential entropy and analyze its behavior under symmetric and asymmetric probability distributions. Particular emphasis is placed on illustrating the role of symmetry through analytical results and graphical representations, including comparisons of entropy curves for symmetric and skewed distributions. Moreover, we investigate the relationship between the proposed entropy model and other information-theoretic measures such as entropy and extropy. Several non-parametric estimation techniques are studied, and their performance is evaluated using Monte Carlo simulations, highlighting asymptotic properties and the emergence of normality, an aspect closely related to distributional symmetry. Furthermore, the consistency and biases of the estimation methods, which rely on kernel estimation with ${\rho }_{corr}$-mixing dependent data, are presented. Additionally, numerical calculations based on simulation and medical real data are applied. Finally, a test of uniformity using different test statistics is given. Full article

The vegetation cover in the Red River Basin (RRB) has undergone considerable changes over the past 20 years. Identifying vegetation cover and its transboundary differences is crucial for assessing the ecological health of the region. This study utilized normalized difference vegetation index (NDVI) data (2000–2023) to analyze the spatiotemporal dynamics of fractional vegetation cover (FVC) and its transboundary differences within the RRB. The results revealed the following: (1) From 2000 to 2023, overall FVC in the basin increased, with a mean value of 0.64, indicating favorable vegetation conditions. (2) In terms of spatial distribution, the RRB in China (RRBC) generally exhibited higher FVC in the west and lower FVC in the east, whereas the RRB in Vietnam and Laos (RRBVL) exhibited higher FVC in the east and lower FVC in the west. Regarding spatiotemporal changes, in RRBC, the changes were primarily characterized by both non-significant improvement (56.01%) and extremely significant improvement (21.45%). Conversely, RRBVL exhibited both areas of extremely significant improvement (25.4%) and areas of extremely significant degradation (18%). (3) Anthropogenic activities exerted a stronger influence than precipitation on both spatiotemporal changes and transboundary differences in FVC. In conclusion, an overall increase in FVC is observed throughout the RRB, with notable transboundary variations. Full article

This study investigated the optimization of optical film configurations to mitigate angular color deviation—a persistent challenge in quantum dot (QD) backlight displays. A white backlight was implemented by placing a yellow CdSe-based QD film on a blue edge-lit backlight, followed by various combinations of prism and diffusion films. Optical characteristics, including luminance, spectral distribution, and chromaticity coordinates, were systematically measured over a viewing-angle range of −70° to 70° for different film arrangements. Applying one or two prism films significantly enhanced normal luminance and improved color conversion efficiency by forming vertical optical cavities; however, this also introduced the side-lobe phenomenon, leading to color non-uniformity. Placing a diffusion film between the QD and prism films did not resolve these issues, whereas positioning it as the topmost layer above the prism films effectively eliminated color dispersion and produced a uniform luminance distribution. These results provide practical design guidelines for optimizing optical film stacks in QD-enhanced backlight units to achieve superior color uniformity in LCD displays. Full article

Background: The normal pattern of nipple enhancement on magnetic resonance imaging (MRI) is defined based on healthy individuals, as it correlates with the structural anatomy of the nipple–areola complex (NAC). Understanding the normal range of nipple morphology and enhancement on MRI allows radiologists to better identify abnormalities. Some authors have previously detailed the morphology and characteristics of nipple–areola complex enhancement, both in normal and pathologically infiltrating conditions. Our aim is to present a case series involving a population of women with breast cancer infiltrating the NAC, retrospectively evaluated at our institution. Furthermore, based on previously published literature and our own experience, we intend to propose potential standardized language to describe tumor-infiltrating NAC enhancement on MRI and compare it with CT and PET findings. Methods: Our study included 110 breast cancer patients with NAC infiltration, who were referred to our hospital from August 2023 to July 2024. All patients were candidates for neoadjuvant chemotherapy and therefore underwent MRI and CT; 33 of them also underwent PET/CT. We distinguished the MRI enhancement pattern based on morphology and intensity. There were three types of morphology: SLE (superficial linear enhancement) at the skin level, NEZ (non-enhancing area immediately below the SLE), and INE (nipple enhancement below the NEZ but above the nipple base). In INE, the pattern could be linear or patchy. Depending on the intensity, the enhancement could be minimal, mild, moderate, or marked. The enhancement on CT depended on the distribution of pathological tissue in the infiltrated NAC and could be present or absent; it could involve the nipple base, the nipple body, or both. For quantitative analysis, we used the maximum standardized uptake value (SUV) measured in early-stage PET/CT images, obtained by delineating a three-dimensional volume of interest (VOI) on the NAC. Results: In our population, the most represented enhancement pattern was INE (110), while slightly less than half of the patients showed invasion of the NEZ (49). Approximately one quarter of the patients presented linear ductal INE (36), while the majority presented patchy INE (74). On CT and PET/CT, NAC enhancement was detectable in almost all patients (102), mainly involving the base and the body together. Correlation analysis in the following pairs of variables showed a high association, with a Kendall’s tau value greater than 0.7 (p < 0.001): (1) involvement of the NEZ on ce-MR and pattern of nipple involvement on ce-CT (CT score); (2) morphological pattern of INE on ce-MR (INE score) and intensity of INE enhancement on MR; and (3) pattern of nipple involvement on ce-CT (CT score) and intensity of INE enhancement on MR. The calculated mean SUV of pathological NACs on PET/CT for early-stage images was 3.59, while the mean SUV of contralateral normal NACs was 2.12. The calculated mean NAC-SUV ratio was 1.7. Conclusions: Although pathological involvement of the NAC cannot always be assessed in the final surgical specimen due to the effects of neoadjuvant chemotherapy, so the “gold standard” of histological reference is missing, MRI and CT with morphology and enhancement descriptors, and additionally PET/CT with SUV measurement can, in our opinion, provide valuable information on the infiltrated nipple. Standardized language for describing breast tumors infiltrating the NAC is desirable to ensure consistent interpretation across different radiologists. Full article

Accurate postharvest quality evaluation of soybeans is essential for preserving product value and meeting industry standards. Traditional inspection methods are often inconsistent, labor-intensive, and unsuitable for high-throughput operations. This study presents a non-destructive soybean classification approach using a simplified reflectance-mode hyperspectral imaging system equipped with a single light source, eliminating the complexity and maintenance demands of dual-light configurations used in prior studies. A spectral–spatial data fusion strategy was developed to classify harvested soybeans into four categories: normal, split, diseased, and foreign materials such as stems and pods. The dataset consisted of 1140 soybean samples distributed across these four categories, with spectral reflectance features and spatial texture attributes extracted from each sample. These features were combined to form a unified feature representation for use in classification. Among multiple machine learning classifiers evaluated, Linear Discriminant Analysis (LDA) achieved the highest performance, with approximately 99% accuracy, 99.05% precision, 99.03% recall and 99.03% F1-score. When evaluated independently, spectral features alone resulted in 98.93% accuracy, while spatial features achieved 78.81%, highlighting the benefit of the fusion strategy. Overall, this study demonstrates that a single-illumination HSI system, combined with spectral–spatial fusion and machine learning, offers a practical and potentially scalable approach for non-destructive soybean quality evaluation, with applicability in automated industrial processing environments. Full article

The often used analytical representation of the Maxwell–Boltzmann classical speed distribution function (F) for elastic, indivisible particles assumes an infinite limit for the speed. Consequently, volume and the number of particles (n) extend to infinity: Both infinities contradict assumptions underlying this non-relativistic formulation. Finite average kinetic energy and temperature (T) result from normalization of F removing n: However, total energy (i.e., heat of the collection) remains infinite because n is infinite. This problem persists in recent adaptations. To better address real (finite) systems, wherein T depends on heat, we generalize this one-parameter distribution (F, cast in energy) by proposing a two-parameter gamma distribution function (F*) in energy which reduces to F at large n. Its expectation value of kT (k = Boltzmann’s constant) replicates F, whereas the shape factor depends on n and affects the averages, as expected for finite systems. We validate F* via a first-principle, molecular dynamics numerical model of energy and momentum conserving collisions for 26, 182, and 728 particles in three-dimensional physical space. Dimensionless calculations provide generally applicable results; a total of 10⁷ collisions suffice to represent an equilibrated collection. Our numerical results show that individual momentum conserving collisions in three-dimensions provide symmetrical speed distributions in all Cartesian directions. Thus, momentum and energy conserving collisions are the physical cause for equipartitioning of energy: Validity of this theorem for other systems depends on their specific motions. Our numerical results set upper limits on kinetic energy of individual particles; restrict the n particles to some finite volume; and lead to a formula in terms of n for conserving total energy when utilizing F* for convenience. Implications of our findings on matter under extreme conditions are briefly discussed. Full article

Mid–long-term streamflow prediction (MLSP) plays a critical role in water resource planning amid growing hydroclimatic and anthropogenic uncertainties. Although AI-based models have demonstrated strong performance in MLSP, their capacity to quantify predictive uncertainty remains limited. To address this challenge, a DeepAR-based probabilistic modeling framework is developed, enabling direct estimation of streamflow distribution parameters and flexible selection of output distributions. The framework is applied to two case studies with distinct hydrological characteristics, where combinations of recurrent model structures (GRU and LSTM) and output distributions (Normal, Student’s t, and Gamma) are systematically evaluated. The results indicate that the choice of output distribution is the most critical factor for predictive performance. The Gamma distribution consistently outperformed those using Normal and Student’s t distributions, due to its ability to better capture the skewed, non-negative nature of streamflow data. Notably, the magnitude of performance gain from using the Gamma distribution is itself region-dependent, proving more significant in the basin with higher streamflow skewness. For instance, in the more skewed Upper Wudongde Reservoir area, the model using LSTM structure and Gamma distribution reduces RMSE by over 27% compared to its Normal-distribution counterpart (from 1407.77 m³/s to 1016.54 m³/s). Furthermore, the Gamma-based models yield superior probabilistic forecasts, achieving not only lower CRPS values but also a more effective balance between high reliability (PICP) and forecast sharpness (MPIW). In contrast, the relative performance between GRU and LSTM architectures was found to be less significant and inconsistent across the different basins. These findings highlight that the DeepAR-based framework delivers consistent enhancement in forecasting accuracy by prioritizing the selection of a physically plausible output distribution, thereby providing stronger and more reliable support for practical applications. Full article

This study analyzes the volatility of Bitcoin using stochastic volatility models fitted to one-minute transaction data for the BTC/USDT pair between 1 April 2023, and 31 March 2024. Bernstein polynomial terms were introduced to accommodate intraday and intraweek seasonality, and flexible return distributions were used to capture distributional characteristics. Seven return distributions—normal, Student-t, skew-t, Laplace, asymmetric Laplace (AL), variance gamma, and skew variance gamma—were considered. We further incorporated explanatory variables derived from the trading volume and price changes to assess the effects of order flow. Our results reveal structural market changes, including a clear regime shift around October 2023, when the asymmetric Laplace distribution became the dominant model. Regression coefficients suggest a weakening of the volume–volatility relationship after September and the presence of non-persistent leverage effects. These findings highlight the need for flexible, distribution-aware modeling in 24/7 digital asset markets, with implications for market monitoring, volatility forecasting, and crypto risk management. Full article

Pituitary pars intermedia dysfunction (PPID) is a common, slowly progressive, neurodegenerative disorder of the older horse. Oxidative damage to the hypothalamic periventricular neurons results in loss of dopaminergic inhibition of the pars intermedia region of the pituitary gland. Consequently, there is increased production of the pro-opiomelanocortin (POMC)-derived hormones normally produced by this region, as well as initial melanocyte hypertrophy and hyperplasia, followed by adenomatous change. Clinical signs that are highly suggestive of the disease are generalised and regional hypertrichosis and delayed/abnormal coat shedding. Numerous clinical signs provide a moderate clinical suspicion, including hyperhidrosis, abnormal fat distribution/regional adiposity, epaxial muscle atrophy/loss of topline, laminitis, weight loss, recurrent infections, behavioural changes/lethargy, polyuria and polydipsia, a pot-bellied appearance, bulging supraorbital fat pads, reduced wound healing, lordosis and infertility. In all animals, a diagnosis of PPID is made based on the signalment, clinical signs and results of further diagnostic tests, with age being a crucial factor to consider. Currently recommended further diagnostic tests are measurement of basal adrenocorticotrophic hormone (ACTH) concentrations (all year) and evaluation of the ACTH response to thyrotrophin-releasing hormone (TRH) using seasonally adjusted references intervals (non-autumn). Animals should also be tested for insulin dysregulation, as laminitis risk in PPID is associated with hyperinsulinaemia. PPID can be managed but not cured; it is a lifelong condition. The individual clinical signs can be managed, e.g., clipping the excessive haircoat and providing unrestricted access to water for individuals with polydipsia. Alternatively, pharmacological management can be employed, and the dopamine-2 receptor agonist pergolide is licensed/approved for the treatment of equine PPID. This should be prescribed in combination with dietary recommendations based on the body condition score and insulin sensitivity status of the individual animal. Full article

Seedling cultivation of rice (Oryza sativa L.) is a critical initial step in rice production. This study investigated the effects of sowing methods and strigolactone (GR24) on rice seedlings under salt stress. Results showed that drill-sown seedlings exhibited superior quality under normal conditions compared to broadcast-sown seedlings. Salt stress significantly increased the contents of Cl⁻, Na⁺, reactive oxygen species (ROS), and malondialdehyde (MDA), disrupted chloroplast structure and hormonal balance, and reduced gas exchange parameters and chlorophyll fluorescence parameters. Notably, drill-sowing conferred stronger salt tolerance than broadcast-sowing. Exogenous application of GR24 enhanced activities of antioxidant enzymes—including superoxide dismutase (SOD), ascorbate peroxidase (APX), peroxidase (POD), and catalase (CAT)—and elevated non-enzymatic antioxidant contents such as ascorbic acid (ASA), glutathione (GSH), total phenolics, and flavonoids, alongside related enzyme activities. Concurrently, GR24 reduced Na⁺ and Cl⁻ accumulation, lowered the Na⁺/K⁺ ratio, and increased the contents of K⁺, Ca²⁺, Mg²⁺, and hormones. Consequently, GR24 decreased MDA and ROS levels, protected membrane integrity, reduced electrolyte leakage, repaired chloroplast structure, and improved gas exchange and chlorophyll fluorescence parameters. Due to their superior spatial distribution and photosynthetic efficiency, drill-sown seedlings synergized with GR24 to enhance antioxidant capacity under salt stress, enabling more effective scavenging of peroxidative radicals, stabilization of the photosynthetic system, and mitigation of salt-induced growth inhibition. Ultimately, this combination demonstrated greater stress alleviation than broadcast-sown seedlings. Full article

Burrowing mammals function as ecosystem engineers by creating spatial heterogeneity in the soil structure and vegetation composition, thereby providing microhabitats for a wide range of organisms. These keystone species play a crucial role in maintaining local ecosystem functions and delivering ecosystem services. However, in Mongolia, where overgrazing has accelerated due to the expansion of a market-based economy, scientific knowledge remains limited regarding the impacts of human activities on such species. In this study, we focused on the Siberian marmot (Marmota sibirica), an ecosystem engineer inhabiting typical Mongolian steppe ecosystems. We assessed the relationship between the spatial distribution of marmot burrows and vegetation conditions both inside and outside Hustai National Park. Burrow locations were recorded in the field, and the Normalized Difference Vegetation Index (NDVI) was calculated, using Planet Lab, Dove-2 satellite imagery (3 m spatial resolution). Through a combination of remote sensing analyses and vegetation surveys, we examined how the presence or absence of anthropogenic disturbance (i.e., livestock grazing) affects the ecological functions of marmots. Our results showed that the distance between active burrows was significantly shorter inside the park (t = −2.68, p = 0.0087), indicating a higher population density. Furthermore, a statistical approach, using beta regression, revealed a significant interaction between the burrow type (active, non-active, off-colony area) and region (inside vs. outside the park) on the NDVI (e.g., outside × non-active: z = −5.229, p < 0.001). Notably, in areas with high grazing pressure outside the park, the variance in the NDVI varied significantly as a function of burrow presence or absence (e.g., July 2023, active vs. off-colony area: F = 133.46, p < 0.001). Combined with vegetation structure data from field surveys, our findings suggest that marmot burrowing activity may contribute to the enhancement of vegetation quality and spatial heterogeneity. These results indicate that the Siberian marmot remains an important component in supporting the diversity and stability of steppe ecosystems, even under intensive grazing pressure. The conservation of this species may thus provide a promising strategy for utilizing native ecosystem engineers in sustainable land-use management. Full article

Objectives: This study aimed to assess the precision of dose delivery to the target in adaptive carbon ion radiotherapy (CIRT) for locally advanced non-small cell lung cancer (LA-NSCLC) in cumulative dosimetry. Methods: Forty-six patients who received CIRT were included (64 Gy[relative biological effectiveness, RBE] in 16 fractions) with treatment plan computed tomography (CT) and weekly CT scans. Offline adaptive radiotherapy (ART) was administered if the dose distribution significantly worsened. Daily doses were calculated from weekly CTs and integrated into plan CT scans using deformable image registration. The dosimetry parameters were compared between the as-scheduled plan and adaptive replan in patients receiving ART. Survival outcomes and toxicity were compared between the ART and non-ART groups. Results: ART was implemented for 27 patients in whom adaptive replans significantly increased the median V_98% of the clinical tumor volume from 96.5% to 98.1% and D_98% from 60.5 to 62.7 Gy(RBE) compared with the as-scheduled plans (p < 0.001). The conformity and uniformity of the dose distribution improved (p < 0.001), with no significant differences in the doses to normal tissues (lungs, heart, esophagus, and spinal cord) from the as-scheduled plans (p > 0.05). The ART and non-ART groups demonstrated comparable local control, progression-free survival, and overall survival (p > 0.05). No grade 3 or higher radiation-related toxicities were observed. Conclusions: ART enhanced target dose coverage while maintaining acceptable normal tissue exposure, supporting weekly CT monitoring integration during CIRT for the timely intervention for anatomical variations, ensuring precise dose delivery in LA-NSCLC. Full article

Urban greening distribution critically impacts residents’ quality of life and environmental sustainability. While the Green View Index (GVI), derived from street view imagery, is widely adopted for urban green space assessment, its limitation lies in the inability to capture non-street-area vegetation. Remote sensing imagery, conversely, provides full-coverage urban vegetation data. This study focuses on Beijing’s Third Ring Road area, employing DeepLabv3+ to calculate a street-view-based GVI as a predictor. Correlations between the GVI and Sentinel-2 spectral bands, along with two vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and Fractional Vegetation Cover (FVC), were analyzed under varying buffer radius. Regression and classification models were subsequently developed for GVI prediction. The optimal classifier was then applied to estimate green perception levels in non-street zones. The results demonstrated that (1) at a 25 m buffer radius, the near-infrared band, NDVI, and FVC exhibited the highest correlations with the GVI, reaching 0.553, 0.75, and 0.752, respectively. (2) Among the five machine learning regression models evaluated, the random forest algorithm demonstrated superior performance in GVI estimation, achieving a coefficient of determination (R²) of 0.787, with a root mean square error (RMSE) of 0.063 and a mean absolute error (MAE) of 0.045. (3) When evaluating categorical perception levels of urban greenery, the Extremely Randomized Trees classifier (Extra Trees) demonstrated superior performance in green vision perception level estimation, achieving an accuracy (ACC) score of 0.652. (4) The green perception level in non-road areas within Beijing’s Third Ring Road is 56.8%, which is considered relatively poor. Moreover, the green perception level within the Second Ring Road is even lower than that in the area between the Second and Third Ring roads. This study is expected to provide valuable insights and references for the adjustment and optimization of green perception distribution in Beijing, thereby supporting more informed urban planning and the development of sustainable, human-centered green spaces across the city. Full article

Galectin-9 (Gal-9, LGALS9) is a member of the family of carbohydrate-binding lectins known as galectins. Galectins bind a diverse repertoire of galactose-bearing glycoprotein receptors expressed across multiple cell types. These interactions elicit a broad spectrum of pleiotropic effects important in both normal physiology and disease pathogenesis. Gal-9 contains two separate carbohydrate recognition domains with overlapping yet also divergent binding affinities for distinct glycostructures. This tandem repeat motif enables fine-tuning of its various biological functions. Additional control of Gal-9 activity is provided via multiple gene variants, protein isoforms, tissue distribution, and cell type-associated glycoprotein binding profiles. Within the tumor microenvironment, Gal-9 interacts with immune, non-immune, and cancer cells to influence malignant progression. Its binding of the premier immune checkpoint glycoreceptors, T-cell immunoglobulin and mucin-domain-containing-3 (TIM-3) and programmed cell death protein 1 (PD-1), places Gal-9 apart as a burgeoning target for immunotherapy. In this review, we delve into important aspects of Gal-9 immunobiology in tumorigenesis, including glycobiological and lineage-dependent functions. We further examine Gal-9 as a promising new glyco-immune checkpoint target for cancer therapy. Full article