Search Results (14)

This study explores the anticancer, antioxidant, and phytochemical activities of Laurus nobilis L. ethanolic leaf extract. The extract demonstrated selective cytotoxicity against four human cancer cell lines, showing strong cytotoxic effect against ovarian (ES2), head and neck (SAS), and colorectal (HT-29) cancer cells, with IC₅₀ values ranging from 3.8 ± 0.3 to 4.4 ± 0.6 µg/mL. Notably, it exhibited only moderate inhibition of the MDA-MB-231 breast cancer cell line (IC₅₀ = 18.5 ± 0.8 µg/mL), possibly reflecting intrinsic differences in cell line sensitivity. Importantly, the extract showed low toxicity toward normal human fibroblasts (HDF), with an IC₅₀ value exceeding 100 µg/mL, indicating a favorable selectivity profile. The flow cytometry analysis showed that the extract caused cell death and stopped the cell cycle in both SAS and ES2 cancer cell lines. In SAS cells, extract treatment significantly increased apoptotic cells (21.1% ± 0.3%) compared to the control (6.3% ± 0.4%), along with G2 phase accumulation, indicating G2 arrest. Similarly, in ES2 cells, apoptosis increased (16.2% ± 1.3% vs. control 8.1% ± 1.0%), and a significant cell accumulation in the S phase was observed, suggesting disruption of cell cycle progression. Antioxidant screenings showed impressive dose-dependent DPPH radical scavenging activity (25–2000 µg/mL), although less potent than ascorbic acid (2.6 µg/mL). UPLC-QTOF/MS phytochemical analysis revealed various phenolic constituents, such as flavonoids and phenolic acids, and an inferred association with the recorded bioactivities. This preliminary work indicates that L. nobilis extracts may act as natural anticancer and antioxidant agents; however, it was limited to in vitro testing with non-standardized samples, underscoring the need for further research to validate and extend these findings for future applications. Full article

We report the RAD@home citizen science discovery of two rare spiral-host radio galaxies (NGC 3898 and WISEA J221656.57-132042434.1 or RAD-“Thumbs up” galaxy), both exhibiting asymmetric radio lobes extending over 30 to 220 kiloparsec scales. We present a multi-wavelength image analysis of these two sources using radio, optical, and ultraviolet data. Both host galaxies are young, star-forming systems with asymmetric or distorted stellar disks. These disks show similarities to those in galaxies undergoing ram pressure stripping, and the radio morphologies resemble those of asymmetric or bent FR-II and wide-angle-tailed radio galaxies. We suggest that non-uniform gas density in the environment surrounding the ram pressure-stripped disks may contribute to the observed asymmetry in the size, shape, and brightness of bipolar radio lobes. Such environmental effects, when properly accounted for, could help explain many of the non-standard radio morphologies observed in Seyfert galaxies and in recently identified populations of galaxies with galaxy-scale radio jets, which are now being revealed through deep and sensitive radio surveys with uGMRT, MeerKAT, LOFAR, and, in the future, SKAO. These findings also underscore the potential of citizen science to complement professional research and data-driven approaches involving machine learning and artificial intelligence in the analysis of complex radio sources. Full article

In this paper, we revisit the extension of the classical non-standard cosmological model in which dissipative processes are considered through a bulk viscous term in the new field $\varphi$, which interacts with the radiation component during the early universe. Specifically, we consider an interaction term of the form ${\Gamma }_{\varphi }{\rho }_{\varphi }$, where ${\Gamma }_{\varphi }$ represents the decay rate of the field and ${\rho }_{\varphi }$ denotes its energy density and a bulk viscosity described by $\xi ={\xi }_0{\rho }_{\varphi }^{1/2}$, within the framework of Eckart’s theory. This extended non-standard cosmology is employed to explore the parameter space for the production of Feebly Interacting Massive Particles (FIMPs) as Dark Matter candidates, assuming a constant thermal averaged Dark Matter production cross-section ($⟨\sigma v⟩$), as well as a preliminary analysis of the non-constant case. In particular, for certain combinations of the model and Dark Matter parameters, namely ($T_{\mathrm{end}}$,$\kappa$) and $(m_{\chi },⟨\sigma v⟩)$, where $T_{\mathrm{end}}$ corresponds to the temperature at which $\varphi$ decays, $\kappa$ is the ratio between the initial energy density of $\varphi$ and radiation, and $m_{\chi }$ is the Dark Matter mass, we identify extensive new parameter regions where Dark Matter can be successfully established while reproducing the currently observed relic density, in contrast to the predictions of $\Lambda$CDM and classical non-standard cosmological scenarios. Full article

With the rapid expansion of highway networks, the demand for timely and reliable road information has steadily increased. However, some guide signs on newly built or extended highways in China have not been updated or adjusted in time, resulting in incomplete information and non-standard setups. These issues not only affect drivers’ navigation experience but may also negatively impact road safety and traffic efficiency. Therefore, it is crucial to establish a scientifically sound evaluation system and a comprehensive assessment model for highway guide signs. This study selected a representative highway (G2 Expressway in China) as the research subject and combined questionnaire surveys with field investigations to identify common issues such as vague information and irregular placement of guide signs. Through an in-depth analysis of travel demand, the core requirements of drivers were summarized as safety, efficiency, and comfort. Based on these insights, the study proposes four key design principles for guide signs: standardization, readability, continuity, and consistency. A set of quantifiable evaluation indicators was developed through a comprehensive analysis of key factors affecting signage performance, and factor analysis was applied to verify the independence and rationality of the indicators. On this basis, an evaluation model was constructed using the technique for order preference by similarity to ideal solution (TOPSIS) to scientifically quantify the effectiveness of guide signs. The model was applied in a field study on the Hebei section of the G2 Expressway in China (with comprehensive traffic sign coverage, high traffic volume, and more traffic sign issues), with results demonstrating the feasibility and practicality of the proposed evaluation system and model. This research offers a systematic solution to enhance the service quality of highway guide signs and provides essential references for future highway planning and management practices. It aims to comprehensively improve drivers’ travel experiences and promote the development of sustainable and intelligent transportation networks, offering valuable insights for building integrated urban systems. Full article

The left periphery of non-standard Dutch similative clauses hosts a variety of different elements (such as gelijk “like”, zo “so”, als “as”, and hoe “how”) that can sometimes co-occur following a strict hierarchy that seems to hold in other (non-standard) Germanic varieties as well. The present contribution aims to show that the fixed ordering of these elements as well as their function in the structure can be accounted for if similative clauses are taken to be prepositional relative clauses with a complex complementizer domain involving at least three CP-projections. Specifically, I show that these elements lexicalize different parts of the relative construction, including the head complex raising to the edge of the similative in line with a head-raising analysis. To support this idea, I will mostly provide data from Dutch and Dutch dialects, although the analysis can (and should) be extended to other Germanic varieties. Full article

This paper develops novel results in the harmonic analysis of Bessel operators, extending their theory to higher-dimensional and non-Euclidean spaces. We present a refined framework for Hardy spaces associated with Bessel operators, emphasizing atomic decompositions, dual spaces, and connections to Sobolev and Besov spaces. The spectral theory of families of boundary-interpolating operators is also expanded, offering precise eigenvalue estimates and functional calculus applications. Furthermore, we explore Bessel operators under non-standard measures, such as fractal and weighted geometries, uncovering new analytical phenomena. Key implications include advanced insights into singular integrals, heat kernel behavior, and the boundedness of Riesz transforms, with potential applications in fractal geometry, constrained wave propagation, and mathematical physics. Full article

Nonstandard finite-difference (NSFD) methods, pioneered by R. E. Mickens, offer accurate and efficient solutions to various differential equation models in science and engineering. NSFD methods avoid numerical instabilities for large time steps, while numerically preserving important properties of exact solutions. However, most NSFD methods are only first-order accurate. This paper introduces two new classes of explicit second-order modified NSFD methods for solving n-dimensional autonomous dynamical systems. These explicit methods extend previous work by incorporating novel denominator functions to ensure both elementary stability and second-order accuracy. This paper also provides a detailed mathematical analysis and validates the methods through numerical simulations on various biological systems. Full article

Empirical evidence indicates that asset returns adhere to an extended normal distribution characterized by excessive kurtosis and non-zero skewness. Consequently, option prices derived from this distribution diverge from those predicted by the Black–Scholes model. Despite the significance of option price sensitivities for risk management in investment portfolios, the existing literature lacks a thorough exploration of these sensitivities within the context of the extended normal distribution. This article addresses this research gap by deriving the Greeks for options based on the extended normal distribution. The Greeks under consideration include Vega, Delta, Theta, Gamma, Rho, Vanna, Charm, and Vera, all of which are crucial for informed financial decision-making. Furthermore, this study provides a detailed analysis of how these option price sensitivities vary with different levels of kurtosis, offering valuable insights for various market applications. This contribution not only enhances the theoretical understanding of option pricing under non-standard distributions but also presents practical implications for portfolio risk management. Full article

The petroleum and natural gas industries exhibit a high dependency on lifting equipment for oil and gas. Any malfunction in these devices can lead to severe economic losses. Therefore, continuous and timely monitoring of the status of pumping equipment is of paramount importance to proactively prevent potential issues. In an effort to enhance this monitoring process, this study delves into multi-source data images at the well site and extends traditional information analysis methods. It introduces an improved YOLOv7 method based on switchable atrous convolution. While the YOLOv7 algorithm achieves a balance between speed and accuracy, its robustness in non-standard environments is suboptimal. To address this limitation, we propose the utilization of a switchable atrous convolution method for enhancement, thereby augmenting the adaptability of the model. Images of pumping units from diverse scenarios are actively collected and utilized to construct training, validation, and test sets. Different models, including YOLOv7SAC, YOLOv7, and YOLOv5-n, undergo testing, and their detection performances are systematically compared in complex environments. Experimental findings demonstrate that YOLOv7SAC consistently attains optimal detection results across various scenes. In conclusion, the study suggests that the combination of the YOLOv7 model with switchable atrous convolution proves effective for detecting pumping unit equipment in complex scenarios. This provides robust theoretical support for the detection and identification of pumping equipment issues under challenging conditions. Full article

Legacy machinery poses a specific challenge when integrated into modern manufacturing lines. While modern machinery provides swift methods of integration and inbuilt predictive maintenance (PdM), older machines, while physically fully functional, are less attractive to reuse, a specific reason being their lack of ready-to-implement PdM hardware and models. More sustainable manufacturing operations can be achieved if the useable lifespan of functional older machinery can be extended through retrofittable PdM and modern industrial communication systems. While PdM models can be developed for a class (make/model) of machine with retrofitted sensing, it is often found that legacy machines will deviate greatly from their original form, through nonstandard maintenance and component replacement actions during their lengthy lifespan. This would mean that each legacy machine would require a custom PdM model, a cost often leading to the removal or nonusage of legacy machines. This paper proposes a framework designed for the generation of an efficient PdM algorithm which would allow for the reuse of legacy machines retrofitted with low-cost sensing in modern manufacturing for increased sustainability. Given a limited number of data samples collected from a machine to be maintained, we aim to predict a failure or/and maintenance time by making use of the difference between the characteristics of the variation of the healthy and unhealthy data collected from the machine. We measure the healthiness of the machine by using a Siamese network trained with a public dataset and fine-tuned with data samples obtained from machines with similar characteristics. Although we use different training and testing datasets coming from completely different sources, we obtain reasonable results thanks to the proposed technique. The results of simulations and the statistical analysis enable us to devise a transfer learning technique and a Siamese network employed for failure detection in the machine. The proposed system will allow for the continued use of older machines in modern facilities, enabling more sustainable manufacturing models. Full article

A mathematical model of the vaporization process in the coil is developed, taking into account the experimental data. To investigate and visualize the evaporation procedure in the coil, a mathematical pattern of the vapor-liquid mixture motion is compiled and reproduced. In the methodology of the study of the movement of the steam-water mixture, correction coefficients are proposed for calculating the velocities of the coolant in non-standard coaxial coils. The parameters were calculated using data sensitivity analysis and data validation was performed by repeated tests; uncertainty was detected when using the instruments, as well as the total extended uncertainty, the upper and lower limit of uncertainty for each measured parameter. In addition, as part of the steam generator set, solar collectors operate in the summer mode. Using the example of the studied steam generator operating in the conditions of an oil and gas field in the subarctic climate, it is shown that it is possible to use air-type solar collectors for the ventilation system of the production room, as well as water-heating solar collectors for technical systems of hot water supply and chemical water treatment. Full article

In this paper, the analysis is centered on Noether-type first integrals in Lagrange-Hamilton dynamics based on autonomous second-order Lagrangians. More precisely, by using the classical Noether’s theorem and a non-standard Legendrian duality, the single-time and multi-time versions of Noether’s result are investigated for autonomous second-order Lagrangians. A correspondence is established between the invariances under flows and the first integrals for autonomous second-order Lagrangians. In this way, our results extend, unify and improve several existing theorems in the current literature. Full article

For the first time we introduce non-standard neutrosophic topology on the extended non-standard analysis space, called non-standard real monad space, which is closed under neutrosophic non-standard infimum and supremum. Many classical topological concepts are extended to the non-standard neutrosophic topology, several theorems and properties about them are proven, and many examples are presented. Full article

We extend for the second time the nonstandard analysis by adding the left monad closed to the right, and right monad closed to the left, while besides the pierced binad (we introduced in 1998) we add now the unpierced binad—all these in order to close the newly extended nonstandard space under nonstandard addition, nonstandard subtraction, nonstandard multiplication, nonstandard division, and nonstandard power operations. Then, we extend the Nonstandard Neutrosophic Logic, Nonstandard Neutrosophic Set, and Nonstandard Probability on this Extended Nonstandard Analysis space, and we prove that it is a nonstandard neutrosophic lattice of first type (endowed with a nonstandard neutrosophic partial order) as well as a nonstandard neutrosophic lattice of second type (as algebraic structure, endowed with two binary neutrosophic laws: inf_N and sup_N). Many theorems, new terms introduced, better notations for monads and binads, and examples of nonstandard neutrosophic operations are given. Full article