To reduce risk incidents in large bridge construction, it is necessary to study the interaction mechanisms and dynamic changes among various risk factors during the construction of large bridges. First, the evolution mechanism of construction risks for large bridges is analyzed, and a risk factor structure system is established. Then, based on system dynamics theory, a causal loop diagram and flow–stock diagram are constructed, and system dynamics equations for each variable in the flow diagram are established to build a system dynamics model. Finally, taking a large bridge construction project as an example, the variable equations are assigned actual values, and the construction risk level is simulated and analyzed. The results show that, ➀ continuous investment in safety funds can effectively reduce the overall risk level of the system, ➁ changes in the management risk subsystem have a significant impact on the overall risk level of large bridge construction, and ➂ increasing the safety investment ratio in both the personnel risk subsystem and the management risk subsystem can effectively reduce the total risk level of the system. Full article

The improved wear and corrosion resistance of gray cast iron (GCI) with enhanced mechanical properties is a proven stepping stone towards the longevity of its versatile industrial applications. In this article, we have tailored the microstructural properties of GCI by alloying it with titanium (Ti) and tungsten (W) additives, which resulted in improved mechanical, wear, and corrosion resistance. The results also show the nucleation of the B-, D-, and E-type graphite flakes with the A-type graphite flake in the alloyed GCI microstructure. Additionally, the alloyed microstructure demonstrated that the ratio of the pearlite volume percentage to the ferrite volume percentage was improved from 67/33 to 87/13, whereas a reduction in the maximum graphite length and average grain size from 356 ± 31 µm to 297 ± 16 µm and 378 ± 18 µm to 349 ± 19 µm was detected. Consequently, it improved the mechanical properties and wear and corrosion resistance of alloyed GCI. A significant improvement in Brinell hardness, yield strength, and tensile strength of the modified microstructure from 213 ± 7 BHN to 272 ± 8 BHN, 260 ± 3 MPa to 310 ± 2 MPa, and 346 ± 12 MPa to 375 ± 7 MPa was achieved, respectively. The substantial reduction in the wear rate of alloyed GCI from 8.49 × 10⁻³ mm³/N.m to 1.59 × 10⁻³ mm³/N.m resulted in the upgradation of the surface roughness quality from 297.625 nm to 192.553 nm. Due to the increase in the corrosion potential from −0.5832 V to −0.4813 V, the impedance of the alloyed GCI was increased from 1545 Ohm·cm² to 2290 Ohm·cm². On the basis of the achieved experimental results, it is suggested that the reliability of alloyed GCI based on experimentally validated microstructural compositions can be ensured during the operation of plants and components in a severe wear and corrosive environment. It can be predicted that the proposed alloyed GCI components are capable of preventing the premature failure of high-tech components susceptible to a wear and corrosion environment. Full article

Patients with fibromyalgia syndrome tend to report deficits in cognitive functions; however, there is no clear consensus on which cognitive domains are impaired. The aim of this study was to compare the differences in cognitive performance between a group of patients with fibromyalgia syndrome and a group of pain-free subjects controlling for the covariables anxiety, depression, and sleep quality. In total, 130 patients with fibromyalgia syndrome and 111 pain-free subjects with an average age of 54.96 years completed the evaluation protocol consisting of sociodemographic data, psychological data, and neurocognitive tests. All data were collected from May 2022 to May 2023. Multivariate analyses of covariance (MANCOVAs) were conducted to assess intergroup differences in all neurocognitive tests. MANCOVA analyses showed that the group of patients with fibromyalgia showed a worse cognitive performance than the group of pain-free subjects after controlling for anxiety, depression, and sleep quality. This study found that fibromyalgia patients exhibited worse cognitive performance and executive function than pain-free subjects. Thus, cognitive performance seems to not be related with anxiety, depression, or sleep quality in our sample of women with FMS. Full article

Every numerical general relativistic investigation starts from the solution of the initial value equations at a given time. Astrophysically relevant initial values for different systems lead to distinct sets of equations that obey specific assumptions tied to the particular problem. Therefore, a robust and efficient solver for a variety of strongly gravitating sources is needed. In this work, we present the OpenMP version of the Compact Object CALculator (COCAL) on shared memory processors. We performed extensive profiling of the core COCAL modules in order to identify bottlenecks in efficiency, which we addressed. Using modest resources, the new parallel code achieves speedups of approximately one order of magnitude relative to the original serial COCAL code, which is crucial for parameter studies of computationally expensive systems such as magnetized neutron stars, as well as its further development towards more realistic scenarios. As a novel example of our new code, we compute a binary quark system where each companion has a dimensionless spin of $0.43$ aligned with the orbital angular momentum. Full article

Our study employs multi-level agent-based modeling and computational techniques to explore education as a complex system. With an underlying focus that education should be underpinned by a scientific understanding of student learning, we created computational models that simulated learning dynamics in classrooms, integrating both quantitative and qualitative insights. Through these models, we conducted experiments aligned with real classroom data to address key questions, such as “How can we effectively support the academic progress of underperforming students, who are disproportionately from low socio-economic status (SES) backgrounds, to close their multi-year achievement gap in mathematics?” Our study analyzes various instructional approaches for mathematical learning, and our findings highlight the potential effectiveness of Productive Failure as an instructional approach. Considerations of the broader applicability of computational methods in advancing educational research are also provided. Full article

In the field of civil aviation, the nose landing gear is a critical component that is prone to damage during taxiing. With the advent of new technologies such as towing taxi-out and hub motors, the nose landing gear faces increasingly complex operational environments, thereby imposing higher performance demands. Ensuring the structural safety of the nose landing gear is fundamental for the successful application of these technologies. However, current research on aircraft nose landing gear under these new conditions is somewhat lacking, particularly in terms of reliable analysis models for real-world scenarios. This study focuses on a typical Class C aircraft, specifically the B-727 model, for which a finite element model of the nose landing gear is developed. Modal testing of the aircraft’s nose landing gear is conducted using the impact hammer method, and the results are compared with those from the simulations. The experimental data indicate that the error range for the first seven natural frequencies is between 0.23% and 9.27%, confirming the high accuracy of the developed landing gear model. Furthermore, with towing taxi-out as the primary scenario, a dynamic model of the aircraft towing system is established, and an analysis on the structural strength and topological optimization of the nose landing gear under various conditions, including high speeds and heavy loads, is performed. The results show that the developed model can effectively support the analysis and prediction of the mechanical behavior of the nose landing gear. Under high-speed, heavy-load conditions, the nose landing gear experiences significantly increased loads, with the maximum deformation primarily occurring at the lower section of the shock strut’s outer cylinder. However, no damage occurred. Additionally, under these conditions, an optimized structural design for the landing gear was identified, which, while ensuring structural strength, achieves a 22.32% reduction in the mass of the outer cylinder, also ensuring safety in towing taxi-out conditions. Full article

In a number of tomographic applications, data cannot be fully acquired, resulting in severely underdetermined image reconstruction. Conventional methods in such cases lead to reconstructions with significant artifacts. To overcome these artifacts, regularization methods are applied that incorporate additional information. An important example is TV reconstruction, which is known to be efficient in compensating for missing data and reducing reconstruction artifacts. On the other hand, tomographic data are also contaminated by noise, which poses an additional challenge. The use of a single regularizer must therefore account for both the missing data and the noise. A particular regularizer may not be ideal for both tasks. For example, the TV regularizer is a poor choice for noise reduction over multiple scales, in which case ${\ell }^1$ curvelet regularization methods are well suited. To address this issue, in this paper, we present a novel variational regularization framework that combines the advantages of different regularizers. The basic idea of our framework is to perform reconstruction in two stages. The first stage is mainly aimed at accurate reconstruction in the presence of noise, and the second stage is aimed at artifact reduction. Both reconstruction stages are connected by a data proximity condition. The proposed method is implemented and tested for limited-view CT using a combined curvelet–TV approach. We define and implement a curvelet transform adapted to the limited-view problem and illustrate the advantages of our approach in numerical experiments. Full article

Acute myeloid leukemia is the second most frequent type of leukemia in adults. Due to a high risk of development of chemoresistance to first-line chemotherapy, the survival rate of patients in a 5-year period is below 30%. One of the reasons is that the AML population is heterogeneous, with cell populations partly composed of very primitive CD34+CD38- hematopoietic stem/progenitor cells, which are often resistant to chemotherapy. First-line treatment with cytarabine and idarubicin fails to inhibit the proliferation of CD34+CD38- cells. In this study, we investigated Metformin’s effect with or without first-line conventional chemotherapy, or with other drugs like venetoclax and S63845, on primitive and undifferentiated CD34+ AML cells in order to explore the potential of Metformin or S63845 to serve as adjuvant therapy for AML. We found that first-line conventional chemotherapy treatment inhibited the growth of cells and arrested the cells in the S phase of the cell cycle; however, metformin affected the accumulation of cells in the G2/M phase. We observed that CD34+ KG1a cells respond better to lower doses of cytarabine or idarubicin in combination with metformin. Also, we determined that treatment with cytarabine, venetoclax, and S63845 downregulated the strong tendency of CD34+ KG1a cells to form cell aggregates in culture due to the downregulation of leukemic stem cell markers like CD34 and CD44, as well as adhesion markers. Also, we found that idarubicin slightly upregulated myeloid differentiation markers, CD11b and CD14. Treatment with cytarabine, idarubicin, venetoclax, metformin, and S63845 upregulated some cell surface markers like HLA-DR expression, and metformin upregulated CD9, CD31, and CD105 cell surface marker expression. In conclusion, we believe that metformin has the potential to be used as an adjuvant in the treatment of resistant-to-first-line-chemotherapy AML cells. Also, we believe that the results of our study will stimulate further research and the potential use of changes in the expression of cell surface markers in the development of new therapeutic strategies. Full article

Abdominal imaging of autosomal dominant polycystic kidney disease (ADPKD) has historically focused on detecting complications such as cyst rupture, cyst infection, obstructing renal calculi, and pyelonephritis; discriminating complex cysts from renal cell carcinoma; and identifying sources of abdominal pain. Many imaging features of ADPKD are incompletely evaluated or not deemed to be clinically significant, and because of this, treatment options are limited. However, total kidney volume (TKV) measurement has become important for assessing the risk of disease progression (i.e., Mayo Imaging Classification) and predicting tolvaptan treatment’s efficacy. Deep learning for segmenting the kidneys has improved these measurements’ speed, accuracy, and reproducibility. Deep learning models can also segment other organs and tissues, extracting additional biomarkers to characterize the extent to which extrarenal manifestations complicate ADPKD. In this concept paper, we demonstrate how deep learning may be applied to measure the TKV and how it can be extended to measure additional features of this disease. Full article

The prevalence of obesity and morbid obesity in Taiwan has risen sharply in recent decades, as in other parts of the world, necessitating urgent action to prevent and curb its detrimental effects. Asian populations are susceptible to the repercussions of obesity at a lower body weight. A higher BMI is associated with more frequent outpatient visits, in-hospital admissions, higher medical costs, and a lower quality of life. However, effective weight management approaches are unlikely to be maintained in the long term without assimilation into daily lifestyle practices. This qualitative study, based on semi-structured interviews with 14 doctors, dieticians, and nurses who work to control the weight of people with obesity, explored and identified multilevel barriers in the context of daily life to improve the efficacy and execution of weight management strategies. They considered diets, physical activity, and sleep as key weight management activities. The cultural and psychosocial aspects of daily life were observed to have an impact upon weight management, particularly family conflicts due to cultural dynamics and socially and culturally reinforced food practices. To improve population weight, less-recognised aspects need to be addressed alongside the inclusion of mental health specialists in weight management protocols and policy interventions to minimise obesogenic practices and create environments conducive to weight management. Full article

This study presents the effects of piston bowl size on the characteristics of a four-stroke single-cylinder diesel engine, which is considered in relation to changes in factors such as fuel injection pressure and turbocharger pressure. The study was carried out by 3D modeling using AVL Fire with an omega combustion chamber size and dimensions determined by the ratio between the diameter and depth of the piston bowl, which varies from 3.4 to 10.0. Additionally, the turbocharger pressure varies from 0.15 to 0.45 MPa at an engine speed of 1400 rpm and fuel injection pressure up to 300 MPa. The results show that the engine reaches the best values of indicated power, fuel efficiency, and a substantial decrease in emissions of nitrogen oxides at a turbocharger pressure from 0.25 to 0.35 MPa and with a ratio of the diameter to the depth from 7.8 to 10. However, the injection angle changes slightly, and the penetration depth and the tip velocity decrease with increasing boost pressure. While the piston bowl parameters only impact significantly on the tip velocity, the penetration and the spray angle are almost unchanged. In addition, the variation in the diameter of the combustion chamber has an influence on the fluctuation of the spray tip velocity and penetration. Full article

A comparative metabolomic study of three varieties of alfalfa (Medicago varia Mart.) was performed via extraction with supercritical carbon dioxide modified with ethanol (EtOH) and the detection of bioactive compounds via tandem mass spectrometry. Several experimental conditions were investigated in the pressure range of 50–250 bar, with ethanol used as a co-solvent in an amount of 1% of the total volume in the liquid phase at a temperature in the range of 31–70 °C. The most effective extraction conditions were as follows: a pressure of 250 Bar and a temperature of 60 °C for M. varia. M. varia contains various phenolic compounds and sulfated polyphenols with valuable biological activity. Tandem mass spectrometry (HPLC-ESI–ion trap) was applied to detect the target analytes. A total of 103 bioactive compounds (59 polyphenols and 44 compounds belonging to other chemical groups) were tentatively identified in extracts from aerial parts of alfalfa. For the first time, twenty-one chemical constituents from the polyphenol group (flavones: Formononetin, Chrysoeriol, Cirsimaritin, Cirsiliol, Cirsilineol, tricin-O-hexoside, Apigenin C-glucose C-deoxyhexoside, Apigenin 7-O-diglucuronide, 2′-Hydroxygenistein 4′,7-O-diglucoside, etc.) and six from other chemical groups (saponins: Soyasaponin II, Soyasaponin gamma g, Soyasaponin I, Soyasaponin Bd, Soyaysaponin beta g, etc.) were identified in the aerial parts of M. varia. Full article

This study proposes a three-dimensional upper bound solution for estimating the soil thrust of tracked vehicles on saturated clay slopes. The present study considered block, triangular wedge, and trapezoidal wedge failure modes to formulate an upper bound solution for each. The analytical solution for soil thrust was determined as the minimum upper bound solution among those for each failure mode. This analytical solution was validated through numerical simulations that modeled track-ground interactions. Parametric studies, based on the upper bound solution, assessed the impact of track system shape, vehicle weight, undrained shear strength, and ground slope on soil thrust. The analytical solutions and parametric studies provide a rapid method for assessing vehicle operability on clay slopes and offer references for designing tracked vehicles suitable for site conditions. Full article

In this study, a Ti₃C₂ MXene@g-C₃N₄ composite powder (TM-CN) was prepared by the ultrasonic self-assembly method and then loaded onto a carbon nanofiber membrane by the self-assembly properties of MXene for the treatment of organic pollutants in wastewater. The characterization of the TM-CN and the C-TM-CN was conducted via X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), and Fourier transform infrared spectrometer (FTIR) to ascertain the successful modification. The organic dye degradation experiments demonstrated that introducing an appropriate amount of Ti₃C₂ MXene resulted in the complete degradation of RhB within 60 min, three times the photocatalytic efficiency of a pure g-C₃N₄. The C-TM-CN exhibited the stable and outstanding photocatalytic degradation of the RhB solution over a wide range of pH values, indicating the characteristics of the photodegradation of organic pollutants in a wide range of aqueous environments. Furthermore, the results of the cyclic degradation experiments demonstrated that the C-TM-CN composite film maintained a degradation efficiency of over 85% after five cycles, thereby confirming a notable improvement in its cyclic stability. Consequently, the C-TM-CN composite film exhibits excellent photocatalytic performance and is readily recyclable, making it an auspicious eco-friendly material in water environment remediation. Full article

Graphs in the field of science and technology make considerable use of theoretical concepts. When dealing with numerous links and circumstances in which there are varying degrees of ambiguity or robustness in the connections between aspects, rather than purely binary interactions, cubic fuzzy graphs ($\mathcal{C}\mathcal{F}\mathcal{G}s)$ are more adaptable and compatible than fuzzy graphs. To better represent the complexity of interactions or linkages in the real world, an emerging $\mathcal{C}\mathcal{F}\mathcal{G}$ can be very helpful in achieving better problem-solving abilities that specialize in domains like network analysis, the social sciences, information retrieval, and decision support systems. This idea can be used for a variety of uncertainty-related issues and assist decision-makers in selecting the best course of action through the use of a $\mathcal{C}\mathcal{F}\mathcal{G}$. Enhancing the maximized network of three cubic fuzzy graphs’ decision-making efficiency was the ultimate objective of this study. We introduced the maximal product of three cubic fuzzy graphs to investigate how interval-valued fuzzy membership, fuzzy membership, and the miscellany of relations are all simultaneously supported through the aspect of degree and total degree of a vertex. Furthermore, the domination on the maximal product of three $\mathcal{C}\mathcal{F}\mathcal{G}s$ was illustrated to analyze the minimum domination number of the weighted $\mathcal{C}\mathcal{F}\mathcal{G}$, and the proposed approach is illustrated with applications. Full article

Ecuador stands as a nation inheriting a profound ancestral legacy in the utilization of medicinal plants, reflective of the rich biodiversity embraced by various ethnic groups. Despite this heritage, many of these therapeutic resources remain insufficiently explored concerning their toxicity and potential pharmacological effects. This study focused on a comprehensive evaluation of cytotoxicity and the potential subcellular targets within various extracts and nine isolated metabolites from carefully selected medicinal plants. Assessing their impact on the breast cancer cell line (MCF7), we subsequently examined the most active fractions for effects on the cell cycle, microtubule network, centrosome duplication, γH2AX foci, and E-cadherin. The investigated crude extracts and isolated compounds from Ecuadorian medicinal plants demonstrated cytotoxic effects, influencing diverse cellular pathways. These findings lend credence to the traditional uses of Ecuadorian medicinal plants, which have served diverse therapeutic purposes. Moreover, they beckon the exploration of the specific chemicals, whether in isolation or combination, responsible for these observed activities. Full article

This study is part of a project on initial assessment of first language (L1) literacy in adult newcomers prior to the commencement of L2 studies in Swedish. Here, we explore the assessment summaries of newcomers’ L1 literacy, performed by L2-teachers, with assistance from an interpreter. According to the syllabus, instruction in Swedish for Immigrants (SFI) should be adapted to the individual´s needs and goals; however, SFI often fails to do so. L1 literacy—i.e., using texts in different domains (school, work, society, and everyday life)—serves as a foundation for L2 learning and teachers’ access to and utilization of students L1 literacy can significantly enhance instruction. From a sociocultural approach to literacy and based on Luke and Freebody’s ‘Four Resource Model’, a qualitative document analyses of L1 literacy assessment summaries (N=50) demonstrated literacy practices form different domains of student life, beyond school literacy. Literacy practices from all four learner roles, i.e., Code-Breaker, Text Participant, Text User and Text Analyst were identified in the assessments to various degrees dependent on the students’ background, which is illustrated by a close analysis of 5 summaries. This information is both important for teachers’ planning of second language teaching and in the long term for the development of second language teacher education. Full article

Due to being sessile, plants develop a broad range of defense pathways when they face abiotic or biotic stress factors. Although plants are subjected to more than one type of stress at a time in nature, the combined effects of either multiple stresses of one kind (abiotic or biotic) or more kinds (abiotic and biotic) have now been realized in agricultural lands due to increases in global warming and environmental pollution, along with population increases. Soil-borne pathogens, or pathogens infecting aerial parts, can have devastating effects on plants when combined with other stressors. Obtaining yields or crops from sensitive or moderately resistant plants could be impossible, and it could be very difficult from resistant plants. The mechanisms of combined stress in many plants have previously been studied and elucidated. Recent studies proposed new defense pathways and mechanisms through signaling cascades. In light of these mechanisms, it is now time to develop appropriate strategies for crop protection under multiple stress conditions. This may involve using disease-resistant or stress-tolerant plant varieties, implementing proper irrigation and drainage practices, and improving soil quality. However, generation of both stress-tolerant and disease-resistant crop plants is of crucial importance. The establishment of a database and understanding of the defense mechanisms under combined stress conditions would be meaningful for the development of resistant and tolerant plants. It is clear that leaf pathogens show great tolerance to salinity stress and result in pathogenicity in crop plants. We noticed that regulation of the stomata through biochemical applications and some effort with the upregulation of the minor gene expressions indirectly involved with the defense mechanisms could be a great way to increase the defense metabolites without interfering with quality parameters. In this review, we selected wheat as a model plant and Zymoseptoria tritici as a model leaf pathogen to evaluate the defense mechanisms under saline conditions through physiological, biochemical, and molecular pathways and suggested various ways to generate tolerant and resistant cereal plants. Full article

Offshore wind power has attracted significant attention due to its high potential, capability for large-scale farms, and high capacity factor. However, it faces high investment costs and issues with subsea power transmission. Conventional high-voltage AC (HVAC) methods are limited by charging current, while high-voltage DC (HVDC) methods suffer from the high cost of power conversion stations. The low-frequency AC (LFAC) method mitigates the charging current through low-frequency operation and can reduce power conversion station costs. This paper aims to identify the economically optimal frequency by comparing the investment costs of LFAC systems at various frequencies. The components of LFAC, including transformers, offshore platforms, and cables, exhibit frequency-dependent characteristics. Lower frequencies result in an increased size and volume of transformers, leading to higher investment costs for offshore platforms. In contrast, cable charging currents and losses are proportional to frequency, causing the total cost to reach a minimum at a specific frequency. To determine the optimal frequency, simulations of investment costs for varying capacities and distances were conducted. Full article

Plant growth and development are driven by intricate processes, with the cell membrane serving as a crucial interface between cells and their external environment. Maintaining balance and signal transduction across the cell membrane is essential for cellular stability and a host of life processes. Ion channels play a critical role in regulating intracellular ion concentrations and potentials. Among these, K⁺ channels on plant cell membranes are of paramount importance. The research of Shaker K⁺ channels has become a paradigm in the study of plant ion channels. This study offers a comprehensive overview of advancements in Shaker K⁺ channels, including insights into protein structure, function, regulatory mechanisms, and research techniques. Investigating Shaker K⁺ channels has enhanced our understanding of the regulatory mechanisms governing ion absorption and transport in plant cells. This knowledge offers invaluable guidance for enhancing crop yields and improving resistance to environmental stressors. Moreover, an extensive review of research methodologies in Shaker K⁺ channel studies provides essential reference solutions for researchers, promoting further advancements in ion channel research. Full article

A theoretical model, based on the classical Pennes’ bioheat theory, incorporating various boundary conditions, was established and compared to analyze the influence of the latent heat of vaporization via simulation. The aim was to elucidate the extent of its influence. The thermal damage rate, governed by the vaporization heat of biological tissue, is introduced as a key factor. Functional relationships between temperature and incident laser power, spatial position, and time are derived from the classical Pennes’ bioheat equation. According to the theoretical model, numerical simulations and experimental validations are conducted using Comsol Multiphysics 6.0, considering the tissue latent heat of vaporization. The model incorporating the latent heat of vaporization proved more suitable for analyzing the interactions between laser and biological tissue, evident from the degree of fit between simulated and experimental data. The minimum deviations between theoretical and experimental observations were determined to be 2.43% and 5.11% in temperature and thermal damage, respectively. Furthermore, this model can be extended to facilitate the theoretical analysis of the impact of vaporization heat from different primary tissue components on laser-tissue interaction. Full article