Search Results (11,435)

Recently, due to the expansion of telecommunication and power networks, as well as other structures, the demand for designing efficient and durable tall supporting columns has increased. Efficient steel columns are well known, including prestressed stayed beam–column systems. However, because of their relatively high cost, designers often turn to reinforced concrete structures, which are not only relatively cheaper but also sufficiently strong and resistant to aggressive external influences. Nevertheless, the large self-weight of reinforced concrete structures and considerable material consumption encourage the search for new efficient solutions. One such solution is the use of spun reinforced concrete structures. Compared to conventional reinforced concrete structures, these solutions not only reduce material consumption but also increase durability. This study examines an innovative prestressed stayed beam–column structure consisting of a spun reinforced concrete core and supporting prestressed steel tension ties. The behavior of such a composite structure is analyzed, and calculations of internal forces and displacements are presented. The rational parameters of the composing elements of this new prestressed stayed beam–column structure are discussed, and their influence on the stress–strain state of the structure is evaluated. Expressions are provided for calculating the rational bending moments of the spun reinforced concrete core. The obtained solutions make it possible to select rational cross-sections of the core and ties, as well as the required prestressing of the tension ties, without iterative calculations. Full article

Avoiding highway infrastructure construction cost overruns and reducing associated claims and disputes continues to be a challenge in many countries. Research is needed in identifying notable project planning and management deficiencies that are likely to cause cost overruns. The literature suggests numerous potential causes of cost overrun but the clustering of cause variables and relative importance of clusters has not been researched. The research reported here addresses this knowledge gap using predictive models developed with data contributed by several agencies in participating countries and suggests mitigation measures. Following a review of methods and data sources, a methodological framework is advanced that encompasses statistical methods well suited for providing a scientific basis for identifying important clusters of cost overrun variables. Fifty-three completed questionnaires contributed by knowledge experts and experienced managers from Canada, the United States, the Middle East, and Australia met the sample requirements of statistical methods. Starting from 53 variables, the principal component-supported factor analysis method identified clusters of cost overrun variables and their relative importance was inferred with developed logistic regression models. Deeper insights into the causes of cost overruns obtained from this research suggest mitigation measures (e.g., improved qualification and experience of personnel, enhanced planning and design practices, risk analysis of inputs to cost estimation process) that are within reach of managers. The results can enhance infrastructure planning and management practice including a reduction in claims and disputes. Full article

Background: Tuberculosis (TB) outcomes remain suboptimal in high-burden, resource-constrained settings. Clinical and socio-economic factors contribute to loss to follow-up, failure, and mortality, yet their relative importance remains underexplored. Methods: We analyzed a retrospective cohort of patients treated for pulmonary TB in the Eastern Cape, South Africa. Treatment outcomes were dichotomized as success (cured or treatment completed) versus unsuccessful (loss to follow-up, failure, or death), excluding transfers and patients still on treatment. Predictors included age, gender, income, occupation, comorbidities, HIV status, previous treatment history, patient category, and drug resistance status. Regularized logistic regression was used to estimate odds ratios, while the best decision tree model was applied to identify hierarchical risk profiles. Results: Logistic regression demonstrated high accuracy (86%) and identified drug susceptibility, age, income stability, and comorbidity burden as the strongest predictors of treatment success. The decision tree achieved lower accuracy (65%) but improved detection of unsuccessful outcomes, highlighting a clear hierarchy of risk: (1) drug resistance status, (2) age, (3) income source, and (4) comorbidities. Patients with drug-resistant TB, older age, no income or reliance on grants, and coexisting conditions were at the highest risk of poor outcomes. Conclusions: Drug resistance, age, income, and comorbidity burden shape a hierarchical risk profile for TB treatment outcomes in rural South Africa. Logistic regression offered robust overall classification, while the decision tree provided transparent stratification of at-risk groups. These findings underscore the need for integrated clinical and socio-economic support strategies to improve outcomes in high-burden settings. Full article

Titanium-based alloys are widely used in dental implantology; however, the mechanical limitations of commercially pure titanium (cpTi) and unresolved concerns regarding stress shielding remain. This study evaluated the structure–property–function relationship of a novel β-type titanium–niobium–zirconium (Ti–Nb–Zr; TNZ) alloy for dental implant applications. Laboratory testing assessed the elemental composition, tensile properties, and fatigue resistance of the cpTi, compared with modified Grade 4 cpTi (MG4T). In parallel, a randomized, single-blind, controlled clinical trial was conducted over 12 months to compare the clinical performance of TNZ and MG4T implants under functional loading. A total of 80 participants (mean age: 54.2 years; 43 females, 37 males) were enrolled, with 77 completing the 12-month follow-up (TNZ: n = 38; MG4T: n = 39). Clinical outcomes included implant success and survival, peri-implant soft tissue parameters, marginal bone levels, fractal dimension (FD) analysis of trabecular bone, and adverse events. TNZ implants demonstrated superior fatigue resistance without an increase in the elastic modulus relative to MG4T. Clinically, both groups achieved 100% implant success and survival, with no implant-related adverse events. FD analysis revealed time-dependent bone remodeling without evidence of pathological adaptation. These findings support the functional viability of TNZ as a mechanically robust, biocompatible implant material. Further long-term, multicenter trials are warranted to confirm sustained clinical benefits and broader applicability. Full article

Modern agriculture requires optimizing available resources to maximize production while minimizing environmental impact without increasing economic costs. Hydroponic agriculture replaces soil with inert media that provide physical support for plants but do not supply nutrients. In this type of agricultural production, fertilization with nutrient solutions is essential, as they supply the 15 elements necessary for proper plant development. These solutions consist of mixtures of different amounts of fertilizers dissolved in water. In this context, a method based on a simulated annealing algorithm is proposed, a metaheuristic that optimizes fertilizer quantities in grams to achieve target concentrations in parts per million for six macronutrients and nine micronutrients. The algorithm addresses a multi-objective optimization problem, balancing two competing goals: first, maximizing the accuracy of the fertilizer balance to achieve the required nutritional levels, and second, minimizing the total cost of the fertilizer mixture. The algorithm’s fitness function weights the total cost of the fertilizers used and the total relative error between the concentrations obtained and those desired, allowing the relative importance of cost and accuracy in the nutrient solution to be adjusted. The results of three experiments with varying nutrient levels are presented for a 1000-L water tank. The first experiment consisted of three macronutrients and two micronutrients. The second configuration added three macronutrients and two micronutrients, for a total of ten nutrients. Finally, five micronutrients were added to complete the 15 essential nutrients for plants. It is important to note that there are several methods for calculating micronutrients that contribute to precision agriculture, increasing the complexity of finding a solution that meets established nutritional requirements. The nutrient concentrations in parts per million required for tomato cultivation during the vegetative development stage. To balance nutrient accuracy and solution cost, we applied weighting factors of $0.65,0.75,0.85,0.90,0.95,$ and $1.0$ for accuracy. The corresponding weights for cost were calculated as the complement of these values (totaling 1). By favoring nutrient accuracy with a weighting of 1, accuracies of 0.00500, 0.02618, and 0.03077 parts per million were achieved in each experiment, respectively. Meanwhile, the lowest cost is $2.06$, $2.72$, and $2.70$ USD for the aforementioned experiments. Full article

The rapid expansion of probiotics and other microbiome-modulating interventions has been accompanied by a growing number of human clinical trials. However, despite frequent reports of statistically significant microbiome changes, relatively few studies generate evidence that convincingly supports health claims or translates into reproducible, clinically meaningful outcomes. This gap is often attributed to the inherent complexity and inter-individual variability of the gut microbiome; however, recurring shortcomings in trial design and interpretation likely play an equally important role. In this Commentary, we examine common failure modes that weaken the clinical validation of microbiome-mediated interventions. These include overreliance on descriptive microbiome metrics (e.g., alpha diversity and taxonomic shifts) as surrogate endpoints, misalignment between prespecified endpoints and the claims ultimately advanced, and excessive dependence on symptom-only outcomes in settings characterized by substantial placebo responsiveness. We further highlight how inadequate control of key confounders—particularly diet, antibiotic exposure, and concomitant medications—combined with endpoint overload and underpowered study designs, can obscure true biological signal and increase the risk of irreproducible findings. We argue that stronger evidence emerges when the microbiome is treated as a mechanistic mediator rather than a clinical endpoint. Trials are most interpretable when intended claims are prospectively defined, linked to explicit biological mechanisms, and evaluated using a hierarchy of endpoints that prioritizes host-relevant outcomes and objective biomarkers, with microbiome measures integrated to support mechanistic plausibility. Adoption of staged development pathways disciplined statistical planning, and transparent management of confounding variables can further improve reproducibility and clinical relevance. Full article

The increasing integration of artificial intelligence (AI) in education highlights the need for teacher preparation programs to support pre-service teachers in developing pedagogically grounded and ethically responsible AI competencies. This study designed and preliminarily examined an Experiential Design Learning model within a Digital Learning Ecosystem (EDL–DLE) to support the development of AI competencies and instructional innovation in pre-service science teacher education. A four-phase research and development framework was employed, including conceptual synthesis, model design and expert validation, implementation, and evaluation. Participants were 19 second-year pre-service science teachers from a university in Bangkok. Research instruments included a 40-item AI competency assessment and an instructional innovation evaluation rubric. Paired-sample t-test results indicated statistically significant pre–post difference across all AI competency dimensions, with large effect sizes (Cohen’s d = 0.82–1.59), reflecting notable within-group changes observed within the EDL–DLE learning context. The instructional innovation lesson plans were evaluated as generally strong across multiple dimensions, particularly in learner-centered pedagogy, creativity, and collaboration, while relatively lower performance was observed in appropriate AI technology selection and ethical use. Overall, the findings provide preliminary evidence supporting the feasibility of the EDL–DLE model as an exploratory instructional approach for fostering foundational AI-related pedagogical competencies in pre-service science teacher education. Full article

Complex transcriptional and epigenetic regulation, including variation in promoter-level cis-regulatory architecture, influences infertility. In this study, we performed a purely in silico analysis of the −1000 to −1 bp promoter regions (relative to the annotated TSS) of 13 human fertility-related genes using an integrated motif-discovery and annotation workflow (NNPP, MEME/STREME, Tomtom, FIMO/CentriMo, GOMo, and MethPrimer). Motif discovery identified multiple statistically supported de novo promoter motifs, and motif scanning mapped their occurrences across the analyzed promoters. Similarity searches against curated PWM databases did not yield significant matches under stringent criteria, consistent with divergent or under-represented motif patterns. Functional association analysis and CpG island profiling further highlighted promoter segments that merit prioritization for follow-up testing. As the analysis is purely in silico and restricted to a fixed promoter window, the identified motifs should be interpreted as candidate regulatory elements pending experimental validation. Full article

Background: Periodontal disease is a chronic inflammatory condition characterized by progressive destruction of the supporting tissues of the teeth. MicroRNAs (miRNAs) have emerged as key post-transcriptional regulators of immune and inflammatory responses; however, their coordinated expression patterns in periodontal disease remain incompletely understood. Objective: This study aimed to evaluate the expression of miR-141-3p, miR-146a-5p, and miR-148b-3p in periodontal disease and to explore their potential co-regulation in relation to periodontal inflammation. Methods: Gingival samples were collected from individuals with periodontal disease and periodontally healthy controls. miRNA expression levels were quantified by real-time quantitative PCR using TaqMan assays and normalized to miR-191-5p. Relative expression was calculated using the ΔΔCt method. Statistical analyses included group comparisons and correlation analyses to assess relationships among miRNA expression levels. Results: miR-146a-5p expression was significantly reduced in periodontal disease compared with healthy controls (p < 0.05), while miR-141-3p showed a consistent downward trend without reaching statistical significance. No significant differences were observed for miR-148b-3p expression between groups. Notably, strong positive correlations were identified among the three miRNAs, indicating coordinated expression patterns independent of disease stage or grade. Conclusions: The findings demonstrate altered expression of miR-146a-5p and coordinated regulation of miR-141-3p, miR-146a-5p, and miR-148b-3p in periodontal disease. These results support the concept that miRNAs act within regulatory networks rather than as isolated markers and contribute to a more nuanced understanding of miRNA-mediated regulation in periodontal inflammation. Full article

Background: Subjective well-being (SWB) is an important outcome in healthcare. Identifying correlates of SWB among economically vulnerable populations can inform healthcare delivery and policy decisions. Objective: This study examines whether social capital is more strongly associated with evaluative SWB than mental health among financially insecure households in the U.S. South. Methods: Data were drawn from the SR-Stat Baseline Survey 2024. Multiple regression analysis was used to examine the relative associations of interpersonal trust, institutional trust, and mental health with evaluative SWB, while controlling for socioeconomic-demographic characteristics. Results: Interpersonal trust, institutional trust, and mental health were each significantly associated with evaluative SWB. Institutional trust exhibited the largest standardized association, followed closely by mental health and interpersonal trust, with differences in magnitude remaining modest across variables. Several control variables, particularly age, income, and health insurance coverage, were also independently associated with SWB. Healthcare systems and policymakers may benefit from incorporating trust-building practices, such as transparent communication and equitable service delivery, alongside mental health screening and support, to address multiple dimensions of well-being in economically vulnerable populations. Conclusions: Evaluative SWB among financially insecure households is associated with mental health and trust-based social capital at both interpersonal and institutional levels. These findings highlight the importance of addressing individual functioning and broader institutional contexts when designing interventions aimed at improving well-being. Full article

Background/Objectives: The 2020 Infectious Diseases Society of America (IDSA) guidelines recommend a single 200 mg dose of doxycycline within 72 h of tick removal after a high-risk bite for Lyme disease prophylaxis. However, limited data are available on prescribing practices related to this recommendation in highly endemic Lyme disease areas. Methods: We conducted a retrospective chart review on adult patients (aged ≥ 18 years) who received a single dose of oral doxycycline for Lyme disease prevention for the period 2022–2024 within a rural Wisconsin health system. Patient and provider prescribing characteristics were evaluated. Manual data abstraction was performed on a random sample of 155 prescribing events to assess adherence to IDSA guidelines. Results: A total of 2404 prophylaxis prescriptions were identified; 44% were prescribed to older adults between 65 and 79 years of age, 54% were prescribed to males, and 66% were prescribed to patients living in rural areas. Prescriptions peaked in spring and summer months, consistent with the known seasonal trends in tick activity. Prescribing was distributed relatively evenly across provider types, with the majority (77%) of cases occurring in outpatient and urgent care settings. Upon manual abstraction, doxycycline was indicated in 12% with the remainder either classified as possibly indicated or not indicated due to suboptimal documentation and nonadherence. Conclusions: Our study identified high rates of incomplete documentation and uncertainty in guideline concordance in a Lyme-endemic health system, highlighting the opportunities to support evidence-based prescribing and to improve documentation practices. Full article

To address the limitations of existing two-dimensional asperity shoulder-to-shoulder contact models and to investigate the normal and tangential contact mechanisms of rough surfaces, this study proposes a three-dimensional elastic contact model based on shoulder-to-shoulder paraboloidal asperities within the framework of Hertzian contact theory. The proposed model extends the conventional two-dimensional elastic shoulder-to-shoulder asperity contact model developed by Sepehri by explicitly incorporating the effects of principal surface curvatures, thereby enabling the accurate representation of three-dimensional contact conditions. Analytical relationships among contact load, elastic interference, contact area, and contact pressure are derived. The predictive performance of the proposed model is evaluated through systematic comparisons with Sepehri’s model and finite element analysis (FEA) results. The results demonstrate that the proposed model exhibits significantly improved agreement with the FEA predictions. The maximum relative errors for contact area, maximum contact pressure, and contact interference are 5.74%, 5.96%, and 2.77%, respectively. Furthermore, parametric studies examine the effects of relative offset r and pressing amount Δd on contact displacement, contact area, and maximum contact pressure. Furthermore, parametric studies are conducted to examine the effects of the relative offset r the pressing amount Δd on contact displacement, contact area, and maximum contact pressure. The results indicate that the contact area increases with both r and Δd, whereas the maximum contact pressure and contact displacement exhibit similar trends, increasing with Δd but decreasing with increasing r. These findings validate the accuracy and applicability of the proposed model under varying contact conditions, providing a reliable theoretical foundation for refining asperity contact models and supporting practical engineering contact analyses. Full article

The continued growth of electric vehicle (EV) deployment has placed increasing emphasis on the development of charging infrastructure that is efficient, reliable, and compliant with safety requirements over a wide range of power levels. In EV charging systems, DC–DC converters work as a key interface for voltage adaptation, power regulation, and battery protection, making the choice of converter topology a crucial design consideration. This study provides a comparative and application-focused review of commonly employed isolated and non-isolated DC–DC converter topologies used in EV charging architectures. The comparison is carried out by examining voltage gain behavior, efficiency tendencies, switching and thermal stress, soft-switching capability, component utilization, control complexity, cost-related aspects, and practical deployment constraints. Fundamental operating principles and representative time-domain simulations are used to highlight relative performance trends of PWM-based and resonant isolated converters under typical charging conditions. Rather than introducing new converter structures or control methods, the objective of this work is to offer practical, design-oriented insights that support informed topology selection. Based on the comparative analysis, non-isolated converters are found to be well suited for low- to medium-power onboard charging applications, whereas isolated resonant converters are more appropriate for high-power and fast-charging systems when safety, scalability, efficiency trends, and system-level implementation factors are considered together. Full article

Background/Objectives: Ovarian cancer remains a highly lethal malignancy, largely due to the development of therapeutic resistance, particularly in advanced disease. Combination strategies targeting complementary molecular pathways may enhance antitumor efficacy and help overcome resistance. The present study aimed to systematically evaluate the anticancer effects of the PARP1 inhibitor PJ34 and the natural polyphenol curcumin, administered alone and in combination, in platinum-sensitive and relatively platinum-resistant ovarian cancer models, with an emphasis on quantitative synergy assessment and functionally supported, hypothesis-generating mechanistic insight. Materials and Methods: Cell viability was evaluated using the MTT assay, and IC₅₀ values were derived from dose–response curves. Drug interactions were quantitatively analyzed using the Chou–Talalay method, including combination index (CI) and dose reduction index (DRI) calculations. Intracellular reactive oxygen species (ROS) levels were measured using DCFH-DA-based assays. Cell migration was assessed using scratch-wound assays. Apoptosis was evaluated using Annexin V/PI flow cytometry, caspase-3 activity assays, and quantitative real-time PCR (RT-qPCR) analysis of apoptosis-related genes (Bax, Bcl-2, Caspase-3, Caspase-9, and p53). To further validate the findings under physiologically relevant conditions, three-dimensional (3D) tumor spheroid models were employed, and ROS involvement was functionally interrogated using N-acetyl-L-cysteine (NAC) rescue experiments to assess ROS-associated contributions rather than direct causality. Results: PJ34 and curcumin each reduced cell viability in a dose-dependent manner, whereas their combination produced a synergistic antiproliferative effect with reduced IC₅₀ values. Synergism was particularly pronounced in relatively platinum-resistant SKOV-3 cells. Combination treatment significantly enhanced regulated apoptotic cell death, as demonstrated by increased apoptotic fractions, elevated caspase-3 activity, and an increased Bax/Bcl-2 ratio, with minimal necrosis. While PJ34 moderately increased intracellular ROS levels and curcumin reduced oxidative stress, the combination was associated with the normalization of ROS levels to near-control values. In 3D tumor spheroid models, combined treatment induced marked spheroid shrinkage, loss of structural integrity, and reduced viability, indicating a preservation of synergistic cytotoxic effects beyond two-dimensional (2D) conditions. NAC pretreatment partially attenuated, but did not fully rescue, the cytotoxic effects of the combination, indicating a ROS-associated, but not exclusively ROS-dependent, mechanism of action. In addition, the combination markedly inhibited cell migration in both ovarian cancer cell lines. Conclusions: This preclinical provides evidence that combined PARP1 inhibition and curcumin treatment can exert synergistic antitumor effects in ovarian cancer models, including relatively platinum-resistant disease, through the coordinated suppression of proliferation, induction of regulated apoptosis, and inhibition of migration. The integration of quantitative synergy analysis, 3D spheroid validation, and ROS-rescue experiments provides functionally supported, hypothesis-generating mechanistic insight and supports further evaluation of PARP inhibitor–curcumin combinations as a mechanistic proof-of-concept in advanced preclinical models. Full article

Plants living in wetland environments (hydrophytes) have developed metabolic adaptations to cope with hypoxia. However, the specific metabolic signatures underlying this adaptation in naturally occurring hydrophytes, compared to their mesophytic relatives, remain insufficiently explored. GC-MS was used to carry out a comparative metabolic profiling of leaves from two pairs of closely related species (the hydrophytes Iris pseudacorus and Comarum palustre versus the mesophytes I. sibirica and Argentina anserina). In total, approximately 260 compounds were detected, of which roughly 100 were annotated. Using Principal Component Analysis, we revealed that the primary source of metabolic variation was phylogenetic (genus/tribe affiliation), while a secondary gradient correlated with ecological adaptation to submergence. A common adaptive metabolic signature of hydrophytes was identified, including the accumulation of dicarboxylic acids from Krebs cycle (succinate, fumarate) and glycolytic metabolites (pyruvate), suggesting a restructuring of energy metabolism under oxygen deficiency. Furthermore, hydrophytes, particularly I. pseudacorus, accumulated higher levels of soluble sugars (sucrose, fructose, glucose) and amino acids, thereby supporting energy supply and alternative NAD(P)H reoxidation pathways. Species-specific differences in the accumulation of antioxidants (e.g., flavonoids, ascorbate) were also observed, indicating diverse strategies for managing oxidative stress. Our findings contribute to identifying a “metabolic fingerprint” associated with waterlogging tolerance. Full article