Search Results (2,008)

With the rapid growth of digital computing, communication, and storage devices applied in various real-world scenarios, more and more data have been collected and stored to drive the development of machine learning techniques. It is also noted that the data that emerge in real-world applications tend to become more complex. In this study, we regard a complex data type, i.e., multi-label data, acquired with a time constraint in a dynamic online scenario. Under such conditions, constructing a learning model has to face two challenges: it requires dynamically adapting the variances in label correlations and imbalanced data distributions and it requires more labeling consumptions. To solve these two issues, we propose a novel online multi-label active learning (OMAL) algorithm that considers simultaneously adopting uncertainty (using the average entropy of prediction probabilities) and diversity (using the average cosine distance between feature vectors) as an active query strategy. Specifically, to focus on label correlations, we use a classifier chain (CC) as the multi-label learning model and design a label co-occurrence ranking strategy to arrange label sequence in CC. To adapt the naturally imbalanced distribution of the multi-label data, we select weight extreme learning machine (WELM) as the basic binary-class classifier in CC. The experimental results on ten benchmark multi-label datasets that were transformed into streams show that our proposed method is superior to several popular static multi-label active learning algorithms in terms of both the Macro-F1 and Micro-F1 metrics, indicating its specifical adaptions in the dynamic data stream environment. Full article

Understanding the population dynamics and interspecific interactions in subtropical forests is crucial for uncovering the underlying mechanisms of species coexistence and community stability. Two censuses were conducted between 2018 and 2023 in a 9.6 ha subtropical evergreen broad-leaved forest dynamics plot situated in Mount Wuyi, southeastern China. Utilizing co-occurrence networks and long-term data, we examined the relationship between species interactions and their contributions to community assembly. Our findings reveal that high mortality rates among small-diameter individuals have created ecological niches, facilitating the establishment of 12 new species between 2018 and 2023. A generalized linear mixed-effects model showed positive relationships between sapling abundance and conspecific neighbor density. Co-occurrence networks demonstrated a shift toward higher positive interactions but reduced modularity, indicating a more integrated yet less stable community structure. Despite their low abundance, rare species demonstrated significant roles in network connectivity and stability, underscoring their status as keystone species. Additionally, the significant correlations between topographic factors and species richness highlighted the role of environmental filtering in shaping community composition. Our findings contribute to a deeper understanding of subtropical forest community dynamics, emphasizing the importance of long-term monitoring to unravel the complex interactions between populations and their environmental conditions. This study represents the first long-term observational experiment conducted in a subtropical secondary forest, providing valuable insights into the dynamics of forest community assembly in this region. Full article

This study introduces a novel one-dimensional Fractional Time–Space Stochastic Advection–Diffusion Equation that revolutionizes the modeling of moisture transport within atmospheric boundary layers adjacent to oceanic surfaces. By synthesizing fractional calculus, advective transport mechanisms, and pink noise stochasticity, the proposed model captures the intricate interplay between temporal memory effects, non-local turbulent diffusion, and the correlated-fluctuations characteristic of complex ocean–atmosphere interactions. The framework employs the Caputo fractional derivative to represent temporal persistence and the fractional Laplacian to model non-local turbulent diffusion, and incorporates a stochastic term with a $1/f$ power spectral density to simulate environmental variability. An efficient numerical solution methodology is derived utilizing complementary Fourier and Laplace transforms, which elegantly converts spatial fractional operators into algebraic expressions and yields closed-form solutions via Mittag–Leffler functions. This method’s application to a benchmark coastal domain demonstrates that stronger advection significantly increases the spatial extent of conditions exceeding fog formation thresholds, revealing advection’s critical role in moisture transport dynamics. Numerical simulations demonstrate the model’s capacity to reproduce both anomalous diffusion phenomena and realistic stochastic variability, while convergence analysis confirms the numerical scheme’s robustness against varying noise intensities. This integrated fractional stochastic framework substantially advances atmospheric moisture modeling capabilities, with direct applications to meteorological forecasting, coastal climate assessment, and environmental engineering. Full article

There are several accidents in China’s high-speed railways where passengers fall off the platform every year. In response to the risks of falling off high-speed railway platforms associated with passenger overcrowding, this study explores the platform exit width range in determining how to reduce the risk. In order to quantify the risk, we first define the risk probability to measure the likelihood of passengers falling off the platform. Then, we propose an integrated model that combines the passenger flow assignment with a dynamic calculation of passenger flow. This methodology addresses the passenger flow assignment through modeling passenger choices based on path utilities and determines an interpretable exit width range that ensures safe, non-congested evacuation within the designated timeframe. Empirical analysis reveals that the ranges of exit width and achieving different aims of risk probabilities are negatively correlated. The current exit width of 6 m on high-speed railway platforms is insufficient. Our results recommend expanding this width to between 6.43 and 7.01 m to facilitate more efficient passenger exits under normal operating conditions (risk probability of 10%). This adjustment potentially reduces the required investment in surveillance equipment by 77.7% and halves the monetary costs, thereby encouraging railway managers to implement these recommendations. Due to being restricted by a fixed platform width of 10 m, the limitation of optimizing the exit width aims to allow about 2770 passengers at most to leave the platform within the specified travel time. Full article

Modern sensing technologies used in the field of ground-based telescopes still present several challenges. First of all, these challenges are associated with the development of new-generation instruments for astronomical observations and with the influence of Earth’s atmosphere on radiation in various ranges of the electromagnetic spectrum. The atmosphere is often the main factor determining the technical characteristics of the instruments in both the optical and millimeter ranges. In particular, for millimeter/submillimeter telescopes, water vapor is the main gas that determines atmospheric opacity. The correct assessment of water vapor makes it possible to estimate the optical opacity of the atmosphere and, on this basis, the capabilities of the millimeter/submillimeter telescope and the limitations of its use in the mode of very long baseline interferometry. Many studies seek to effectively characterize water vapor content and dynamics for site-testing purposes regarding ground-based millimeter and submillimeter telescope application. In the present article, we study the water vapor content within a fairly large region, which has been poorly covered in the modern literature. Based on the ERA-5 reanalysis data as a site-testing-oriented tool, we obtained spatial distributions of the precipitable water vapor (PWV) within a large region (${20}^{\circ }\mathrm{N}$–${70}^{\circ }\mathrm{N}$, ${35}^{\circ }\mathrm{E}$–${120}^{\circ }\mathrm{E}$). These distributions of PWV were corrected with respect to the characteristic vertical scale of water vapor $H_{eff}$ and the relative height difference in the grid nodes in the ERA-5. The calculated values of PWV are highly correlated with the Global Navigation Satellite System-derived PWV, with Pearson coefficients greater than 0.9. Using the refined estimations, we determined the median values of atmospheric opacities corresponding to new prospective sites (Khulugaisha Peak and Tashanta) as well as the Special Astrophysical Observatory (the key astronomical observatory in Russia). Together with Ali in China, Khulugaisha Peak and Tashanta are considered by us as potential sites for the placement of a millimeter/submillimeter telescope within the framework of the project of the Eurasian Submillimeter Telescopes. The results obtained in this paper suggest promising atmospheric conditions for astronomic observations, at least in the millimeter range. In particular, we believe that this study will be a basis for the Eurasian Submillimeter Telescopes (ESMT) project, within the framework of which it is assumed to create a number of ground-based millimeter/submillimeter telescopes. Full article

The hot deformation behavior of 4Cr16MoCu martensitic stainless steel alloyed with 1% Cu was investigated through hot compression tests at temperatures ranging from 900 to 1150 °C and strain rates of 0.001 to 1 s⁻¹. The addition of Cu is strategically employed to synergistically enhance precipitation hardening and corrosion resistance, yet its complex interplay with hot deformation mechanisms remains poorly understood, demanding systematic investigation. The results revealed a narrow forging temperature range and significant strain rate sensitivity, with deformation resistance increasing markedly at higher strain rates. An Arrhenius constitutive model incorporating a seventh-degree polynomial for strain compensation was developed to describe the flow stress dependence on deformation temperature and strain rate. The model demonstrated high accuracy, with a correlation coefficient (R²) of 0.9917 and an average absolute relative error (AARE) of 3.8%, providing a reliable theoretical foundation for practical production applications. Furthermore, a hot processing map was constructed based on the dynamic material model (DMM), and the optimal hot working parameters were determined through microstructural analysis: an initial forging temperature of 1125 °C, a final forging temperature of 980 °C, and a strain rate of 0.1 s⁻¹. These conditions resulted in a fine and uniform grain structure, while strain rates above 0.18 s⁻¹ were identified as unfavorable due to the risk of uneven deformation. Full article

The increasing prevalence of multidrug-resistant (MDR) pathogens, particularly ESKAPE bacteria, necessitates alternative antimicrobial strategies. Probiotics, particularly lactic acid bacteria, protect against pathogenic infections. This study aimed to characterize Schleiferilactobacillus harbinensis WU01, isolated from fermented palm sap, and evaluate its probiotic potential and antimicrobial activity. Its probiotic characteristics were assessed based on low-pH and bile tolerance, auto-aggregation, hydrophobicity, and adhesion to Caco-2 cells. Antimicrobial activity against ESKAPE pathogens was evaluated using the agar well diffusion assay. Whole-genome sequencing (WGS) and in silico analysis were performed to identify bacteriocin-related genes, virulence factors, and antibiotic-resistance genes. WU01 exhibited a strong tolerance to gastrointestinal conditions, with high survival rates under acidic and bile-salt environments. S. harbinensis WU01 demonstrated significant auto-aggregation, high hydrophobicity, and strong adhesion to Caco-2 cells. Antimicrobial assays revealed inhibitory activity against MDR ESKAPE pathogens, which correlated with the presence of bacteriocin-related genes, including those homologous to Carnocin_CP52. Molecular dynamics (MDs) simulations confirmed the interaction of Carnocin_CP52 with bacterial membranes, suggesting a mechanism for pathogen disruption. WGS confirmed the absence of virulence and antimicrobial-resistance genes, confirming its safety for probiotic applications. These findings suggest that S. harbinensis WU01 possesses probiotic properties and antimicrobial activity against ESKAPE pathogens. The combined results highlight its potential application in functional foods and therapeutic interventions. Full article

Numerous studies have explored the role of colour in classroom environments and its effects on learning, cognition and motivation. However, research on coloured lighting remains limited, with most studies focusing only on correlated colour temperature (CCT). Addressing this gap, our study examines various chromatic lighting conditions that enhance learning outcomes while allowing for dynamic applications in educational settings. Conducted over three academic years in six primary classrooms, this quasi-experimental study employed a pretest and a control group to assess the effects of three chromatic lighting scenarios (orange, green and purple) on cognitive processes, emotional responses and basic instrumental learning. Descriptive, variance and comparative analyses revealed conclusive evidence of coloured lighting’s impact, though effects varied across different variables. The study highlights the potential of dynamic lighting approaches to support learning and suggests that AI-assisted lighting adjustments could aid teachers. The findings support the broader implementation of coloured lighting in primary classrooms, advocating for cost-effective, sustainable and adaptive solutions beyond conventional lighting. Such advancements are expected to enhance students’ learning, cognition and motivation while providing greater flexibility in educational environments. Full article

Rainfall-induced freshwater influx is a major nutrient source in estuarine and coastal waters, often driving changes in phytoplankton community structure and blooms. In Jinhae Bay of Korea, a critical area for shellfish aquaculture, the interaction between the Nakdong River discharge and the Tsushima Warm Current creates a frontal zone conducive to phytoplankton proliferation. This study investigated the seasonal variation in phytoplankton communities, including harmful and toxin-producing species, in relation to environmental factors from February 2022 to November 2023 in Jinhae Bay. Except for the summer increase in certain dinoflagellates, diatoms, including Chaetoceros spp., Pseudo-nitzschia spp., and Skeletonema spp., dominated the phytoplankton community across seasons. In addition, nutrient influx from the Nakdong River, particularly nitrate + nitrite and silicate (p < 0.001), was a key driver of phytoplankton community structure. Spatially, phytoplankton communities differed between the inner (St. 1 and 4) and outer (St. 2 and 3) areas in the bay, likely due to the influences of seasonal river discharge, the Tsushima Warm Current, and tidal currents. Among harmful algal blooms causative species, dinoflagellate Margalefidnium polykrikoides was correlated with water temperature, exhibiting higher densities in summer. In contrast, Akashiwo sanguinea was mainly observed in winter. In addition, we found that toxin-producing dinoflagellates, such as Alexandrium catenella, Dinophysis acuminata, and Gonyaulax spinifera, were most prevalent in spring and summer, and their appearance was linked to complex interactions among freshwater influx, water temperature, and current dynamics. Our findings underscore the critical role of bay-specific oceanographic conditions, shaped by tidal and current patterns, in conjunction with riverine nutrient inputs, in driving seasonal phytoplankton blooms. This study provides valuable baseline data for understanding harmful/toxic microalgal dynamics in Jinhae Bay and offers key insights for effective coastal ecosystem management and conservation along the Korean Peninsula. Full article

This paper investigates the ability of our selective small molecule TG2 inhibitor 1-155 in reducing fibrosis in a bleomycin-induced pulmonary fibrosis mouse model. Formulated as a fine stable suspension, 1-155 was delivered intranasally (IN) at 3 mg/kg via IN delivery once daily. It significantly inhibited collagen deposition in the lungs in the bleomycin-challenged mice. Compared to its vehicle control treatment, a significant reduction in a key myofibroblast marker α smooth muscle actin and TG2 was also detected in the 1-155-treated animals. Most importantly, 1-155 treatment significantly improved several key lung function parameters, such as cord compliance, vital capacity, and dynamic compliance, which are comparable to that found for the positive control nintedanib at a much higher dosage of 60 mg/kg twice daily via oral delivery. The 1-155-treated mice showed a trend in improvement of average body weight. For the first time, our study demonstrates the effectiveness of a selective small molecule TG2 inhibitor in reducing pulmonary fibrosis in a pre-clinical model. Importantly, we were able to correlate this effect of 1-155 with the improvement of animal lung function showing the potential of the use of TG2 inhibitors as a therapeutic treatment for fibrotic lung conditions like IPF. Full article

The accurate assessment of anomalous head posture (AHP) is crucial for diagnosing, treating, and monitoring postural changes in individuals with ocular impairments. This study evaluated the accuracy of a digital goniometer and an iOS-based application by comparing their measurements to a gold-standard motion capture (MoCap) system. Additionally, it assessed cervical range of motion (ROM) limitations in children with AHP versus healthy controls. Fifteen pediatric patients with ocular-origin AHP and 20 age-matched controls participated. Head rotation and inclination were measured using a goniometer, the iOS app, and MoCap under static and dynamic conditions. Pearson’s correlation coefficient (PCC), root mean square error (RMSE), and Bland–Altman plots assessed inter-system agreement, while MoCap analyzed cervical ROM. The results showed strong agreement between the ophthalmological tools and MoCap for head rotation (PCC = 0.86, RMSE = 3.43°) and inclination (PCC = 0.82, RMSE = 5°), with no significant inter-system differences (p > 0.05). AHP patients exhibited reduced head flexion (p < 0.05), suggesting long-term postural adaptations. Digital goniometers and smartphone applications provide accurate, cost-effective AHP assessment alternatives, particularly in resource-limited settings. Future research should expand cohorts and integrate multidisciplinary approaches to refine assessment and treatment strategies. Full article

Accurate flow measurement is crucial for energy efficiency in industrial applications. This study investigates entropy generation in measuring orifice plates under high-pressure conditions (80 bar, 400 °C) using computational fluid dynamics (CFD) in OpenFOAM. Two turbulence models, k-ω SST and Spalart–Allmaras, are employed to analyze compressible steam flow and identify local entropy sources. Building on recent findings, this research explores the hypothesis that the discharge coefficient reflects entropy generation. The orifice plate’s abrupt flow contraction and expansion contribute to significant energy dissipation, affecting exergy efficiency. By quantifying entropy sources through numerical simulations, this study provides insights into optimizing flow metering techniques and reducing irreversibilities. The results show a strong correlation between entropy generation and the discharge coefficient, offering a new approach to improving measurement accuracy. This research supports the advancement of energy-efficient flow measurement methods, aligning with sustainable engineering practices. Full article

The middle–upper Eocene successions of northwest Fayum, Egypt, provide a crucial archive for reconstructing paleoenvironmental conditions and paleobiogeographical patterns of the southern Tethys realm. Stratigraphically, the investigated section is subdivided into three rock units: the Gehannam Formation (Bartonian-Priabonian), the Birket Qarun Formation, and the Qasr El Sagha Formation (Priabonian). A total of 101 benthic foraminiferal taxa, representing 31 genera, 23 families, 13 superfamilies, and four suborders, were identified. The middle–late Eocene age is primarily determined by the co-occurrence of index spinose planktonic foraminifera (Acarinina spp., Morozovelloides spp., and Globigerinatheka semiinvoluta) and benthic foraminiferal assemblages, further supported by the presence of the nannofossil marker Chiasmolithus oamaruensis. Four local benthic biozones are identified and correlated with coeval zones in nearby areas. Quantitative analyses of benthic foraminiferal individuals, diversity indices, ecological parameters, and the benthic foraminiferal oxygen index (BFOI) reveal distinct environmental shifts. The rock unit occupied by the late middle Eocene assemblages is diversified and dominated by calcareous infaunal taxa (e.g., Bolivina spp., Fursenkoina spp., and Nonionella spp.), indicative of low-oxygen outer neritic conditions associated with elevated organic influx. In contrast, the late Eocene Birket Qarun and Qasr El Sagha showed an increase in epifaunal forms and reduced diversity, suggesting a transition to dysoxic-oxic conditions. Paleobiogeographical analysis indicates a strong affinity with the Tethyan realm, with potential faunal exchange through the Trans-Saharan Seaway. These findings enhance our understanding of Paleogene marine connections between the Tethyan and Indo-Pacific realms, contributing to broader discussions on Eocene paleobiogeography and depositional dynamics in North Africa. Full article

Droughts have been exacerbated by climate change, posing significant risks to ecosystems, hydrology, agriculture, and human society. In this paper, we present the development and evaluation of a high-resolution 1 km SPEI (Standardized Precipitation-Evapotranspiration Index) dataset to enhance drought monitoring at finer spatial scales. The high-resolution SPEI datasets, derived using high-resolution TPDC precipitation and satellite-based MODIS potential evapotranspiration data, were compared with a coarse-resolution 50 km SPEI dataset derived from CRU measurements, as well as vegetation health indices (VHIs) and root zone soil moisture (SM), over two climatically contrasting regions in China: Northeast China (NEC) and Southwest China (SWC). The evaluation highlights the MODIS-based high-resolution SPEI’s ability to capture regional drought dynamics and improved correlation with vegetation and soil moisture dynamics. NEC, with its relatively flat topography and recent experience of significant droughts, and SWC, characterized by complex terrain and high precipitation variability, provided ideal testbeds for examining the performance of the 1 km SPEI. The results demonstrate that the high-resolution dataset offered superior spatial detail in detecting drought conditions, making it valuable for agricultural planning and water resource management in diverse climates. Full article

The purpose of this paper is to obtain a partial clustering model of viscosity including the influence of clusters. This paper also establishes a quantitative correlation between the dynamic viscosity of alloys and temperature of liquidus in isotherms. The research methods are a theoretical substantiation of possibility of the isolated use of the Boltzmann distribution (energy spectrum) for the kinetic energy of the chaotic (thermal) motion and particle collisions as applied to a condensed state of matter. In this paper, the author’s concept of chaotic particles is applied to substantiate the existence of an energy class of particles present in the liquid in the form of clusters. The novelty of the paper is that it obtains a quantitative physical and mathematical model of temperature dependences of the dynamic viscosity based on destruction of clusters as the temperature increases. The mathematical model is compared with viscosity data from the state diagram, starting from the liquidus barrier. This approach was developed first and allows constructing viscosity isotherms based on the thermochemical initial data with extrapolation to the region of ultra-high temperatures. The proposed new model is verified in an example of a Cu-Sn alloy. The high correlation coefficient indicates the correctness of the derived equations and possibility of predicting the distribution of the viscosity of the alloy at high temperatures based on its state diagram. But the main fundamental novelty of the work is the discovery of the relationship between the activation energy of viscous flow and the barrier of randomization, which is present in the partial clustering model. The application of the new partial clustering viscosity model can be utilized across various fields involving fluid dynamics. In our study, the practical implementation of this novel partial clustering viscosity model will ensure the effective execution of metallurgical processes designed using these values at extremely high temperatures, determine optimal operating conditions, and provide more substantiated requirements for metal and alloy production technologies. Full article