Search Results (74,729)

Maintaining well integrity is essential in the oil and gas industry to prevent environmental hazards, operational risks, and economic losses. Cement bond log (CBL) tools are essential in evaluating cement bonding and ensuring wellbore stability. This study presents a patent landscape review of CBL technologies, based on 3473 patent documents from the Lens.org database. After eliminating duplicates and irrelevant entries, 167 granted patents were selected for in-depth analysis. These were categorized by technology type (wave, electrical, radiation, neutron, and other tools) and by material focus (formation, casing, cement, and borehole fluid). The findings reveal a dominant focus on formation evaluation (59.9%) and a growing reliance on wave-based (22.2%) and other advanced tools (25.1%), indicating a shift toward high-precision diagnostics. Geographically, 75% of granted patents were filed through the U.S. Patent and Trademark Office, and 97.6% were held by companies, underscoring the dominance of corporate innovation and the minimal presence of academia and individuals. The review also identifies notable patents that reflect significant technical innovations and discusses their role in advancing diagnostic capabilities. These insights emphasize the need for broader collaboration and targeted research to advance well integrity technologies in line with industry goals for operational performance and safety. Full article

Proper joint function has a significant impact on people’s quality of life. Joints are the point of connection between two or more bones and consist of at least three elements: joint surfaces, the joint capsule, and the joint cavity. Joint diseases are a serious social problem. Risk factors for the development of these diseases include overweight and obesity, gender, and intestinal microbiome disorders. Another factor that is considered to influence joint diseases is trace elements. Under normal conditions, elements such as iron (Fe), copper (Cu), cobalt (Co), iodine (I), manganese (Mn), zinc (Zn), silver (Ag), cadmium (Cd), mercury (Hg), lead (Pb), nickel (Ni) selenium (Se), boron (B), and silicon (Si) are part of enzymes involved in reactions that determine the proper functioning of cells, regulate redox metabolism, and determine the maturation of cells that build joint components. However, when the normal concentration of the above-mentioned elements is disturbed and toxic elements are present, dangerous joint diseases can develop. In this article, we focus on the role of trace elements in joint function. We describe the molecular mechanisms that explain their interaction with chondrocytes, osteocytes, osteoblasts, osteoclasts, and synoviocytes, as well as their proliferation, apoptosis, and extracellular matrix synthesis. We also focus on the role of these trace elements in the pathogenesis of joint diseases: rheumatoid arthritis (RA), osteoarthritis (OA), psoriatic arthritis (PsA), ankylosing spondylitis (AS), and systemic lupus erythematosus (SLE). We describe the roles of increased or decreased concentrations of individual elements in the pathogenesis and development of joint diseases and their impact on inflammation and disease progression, referring to molecular mechanisms. We also discuss their potential application in the treatment of joint diseases. Full article

This essay provides a fine-grained analysis of selected passages of Giulio Aleni (艾儒略 1582–1649)’s translation of Catholic liturgy into classical Chinese in late imperial China. It focuses on the hitherto underexplored relationships between Aleni’s resort to medieval Aristotelianism and Thomism, as well as his translation-based introduction of Catholic Eucharistic theology into China. The case studies here revolve around Aleni’s Chinese translation of Aristotelian-Thomistic hylomorphism, with a focus on his interpretation of “anima” (i.e., the soul, which corresponds largely to linghun 靈魂 in Chinese), which is a multifaceted Western concept that pertains simultaneously to Aristotelian-Thomistic philosophy and Eucharistic theology. It is argued that in his overarching project of introducing Western learnings (i.e., 西學) to sixteenth- and seventeenth-century China, Aleni’s attention is centered primarily on the body-soul and form-matter relationship. This is, as understood here, motivated to a great extent by his scholarly awareness that properly informing Chinese Catholics of the Aristotelian-Thomistic underpinning of Western metaphysics enacts an indispensable role in introducing Catholic liturgy into China, notably the mystery of the Eucharist and Transubstantiation that would not have been effectively introduced to China without having the Western philosophical underpinnings already made available to Chinese intellectuals. Aleni’s use of medieval European cultural legacy thus requires more in-depth analysis vis-à-vis his translational poetics in China. Accordingly, the intellectual and liturgical knowledge in Aleni’s Chinese œuvres shall be investigated associatively, and the medievalism embodied by Aleni offers a valid entry point and productive critical prism. Full article

Hydrogels, characterized by their high water content, tunable mechanical properties, and excellent biocompatibility, have emerged as a promising material platform for the preservation of cultural heritage. Their unique physicochemical features enable non-invasive and adaptable solutions for environmental regulation, structural stabilization, and antifungal protection. This review provides a comprehensive overview of recent progress in hydrogel-based strategies specifically developed for the conservation of cultural relics, with a particular focus on antifungal performance—an essential factor in preventing biodeterioration. Current hydrogel systems, composed of natural or synthetic polymer networks integrated with antifungal agents, demonstrate the ability to suppress fungal growth, regulate humidity, alleviate mechanical stress, and ensure minimal damage to artifacts during application. This review also highlights future research directions, such as the application prospects of novel materials, including stimuli-responsive hydrogels and self-dissolving hydrogels. As an early exploration of the use of hydrogels in antifungal protection and broader cultural heritage conservation, this work is expected to promote the wider application of this emerging technology, contributing to the effective preservation and long-term transmission of cultural heritage worldwide. Full article

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the etiologic agent that causes the coronavirus disease (COVID-19) identified in Wuhan, in 2019. Men are more prone to developing severe manifestations than women, suggesting a possible crucial role of sex hormones. 17,β-Estradiol (E2) and 1,25 α dihydroxyvitamin D₃ (calcitriol) act upon gene pathways as immunomodulators in several infectious respiratory diseases. In this study, we aimed to evaluate the influence of E2 and calcitriol on the VSV-based pseudovirus SARS-CoV-2 and SARS-CoV-2 infection in vitro. We infected Vero E6 cells with the recombinant VSV-based pseudovirus SARS-CoV-2 and the SARS-CoV-2 viruses according to the pre-treatment and pre–post-treatment models. The Angiotensin-Converting Enzyme 2 (ACE2) and Vitamin D Receptor (VDR) gene expression did not change under different treatments. The VSV-based pseudovirus SARS-CoV-2 infection showed a significant decrease in the focus-forming unit count in the presence of E2 and calcitriol (either alone or in combination) in the pre-treatment model, while in the pre–post-treatment model, the infection was inhibited only in the presence of E2. Th SARS-CoV-2 infection highlighted a decrease in viral titres in the presence of E2 and calcitriol only in the pre–post-treatment model. 17,β-Estradiol and calcitriol can exert an inhibitory effect on SARS-CoV-2 infections, demonstrating their protective role against viral infections. Full article

The construction industry has been troubled by a shortage of skilled labor and safety accidents in recent years. Therefore, more and more robots are introduced to undertake dangerous and repetitive jobs, so that human workers can concentrate on higher-value and creative problem-solving tasks. Nevertheless, although human–robot collaboration (HRC) shows great potential, most existing evaluation methods still focus on the single performance of either the human or robot, and systematic indicators for a whole HRC team remain insufficient. To fill this research gap, the present study constructs a comprehensive evaluation framework for HRC team performance in construction projects. Firstly, a detailed literature review is carried out, and three theories are integrated to build 33 indicators preliminarily. Afterwards, an expert questionnaire survey (N = 15) is adopted to revise and verify the model empirically. The survey yielded a Cronbach’s alpha of 0.916, indicating excellent internal consistency. The indicators rated highest in importance were task completion time (µ = 4.53) and dynamic separation distance (µ = 4.47) on a 5-point scale. Eight indicators were excluded due to mean importance ratings falling below the 3.0 threshold. The framework is formed with five main dimensions and 25 concrete indicators. Finally, an AHP-TOPSIS method is used to evaluate the HRC team performance. The AHP analysis reveals that Safety (weight = 0.2708) is prioritized over Productivity (weight = 0.2327) by experts, establishing a safety-first principle for successful HRC deployment. The framework is demonstrated through a case study of a human–robot plastering team, whose team performance scored as fair. This shows that the framework can help practitioners find out the advantages and disadvantages of HRC team performance and provide targeted improvement strategies. Furthermore, the framework offers construction managers a scientific basis for deciding robot deployment and team assignment, thus promoting safer, more efficient, and more creative HRC in construction projects. Full article

The transition to green energy in the transport sector is becoming a priority in the context of global climate challenges and the European Green Deal. This paper investigates the development of alternative fuelling stations, particularly electric vehicle (EV) charging infrastructure and hydrogen stations, across EU countries with a focus on Poland. It combines a policy and technology overview with a quantitative scientific analysis, offering a multidimensional perspective on green infrastructure deployment. A Pearson correlation analysis reveals significant links between charging station density and both GDP per capita and the share of renewable energy. The study introduces an original Infrastructure Accessibility Index (IAI) to compare infrastructure availability across EU member states and models Poland’s EV charging station demand up to 2030 under multiple growth scenarios. Furthermore, the article provides a comprehensive overview of biofuels, including first-, second-, and third-generation technologies, and highlights recent advances in hydrogen and renewable electricity integration. Emphasis is placed on life cycle considerations, energy source sustainability, and economic implications. The findings support policy development toward zero-emission mobility and the decarbonisation of transport systems, offering recommendations for infrastructure expansion and energy diversification strategies. Full article

In this work, Laser Powder Bed Fusion (LPBF), an additive manufacturing (AM) process, was optimised to produce pure magnesium components. The focus of the presented work is on the prediction of the relative product density using the machine learning model XGBoost to improve the production process and thus the usability of the material for practical use. Experimental tests with different parameters, laser power, scanning speed and layer thickness, and fixed parameters, track overlapping and hatching distance, were analysed and resulted in relative material densities between 89.29% and 99.975%. The XGBoost model showed high predictive power, achieving an R² test result of 0.835, a mean absolute error (MAE) of 0.728 and a root mean square error (RMSE) of 0.982. Feature importance analysis showed that the interaction of laser power and scanning speed had the largest influence on the predictions at 35.9%, followed by laser power × layer thickness at 29.0%. The individual contributions were laser power (11.8%), scanning speed (10.7%), scanning speed × layer thickness (9.0%) and layer thickness (3.6%). These results provide a data-based method for LPBF parameter settings that improve manufacturing efficiency and component performance in the aerospace, automotive and biomedical industries and identify optimal parameter regions for a high density, serving as a pre-optimisation stage. Full article

The sugarcane industry plays a crucial economic role worldwide, with sucrose and ethanol as its main products. However, its processing generates large volumes of by-products—such as bagasse, molasses, vinasse, and straw—that contain valuable components for biotechnological valorization. This review integrates approximately 100 original research articles published in JCR-indexed journals between 2015 and 2025, of which over 50% focus specifically on sugarcane-derived agroindustrial residues. The biotechnological approaches discussed include submerged fermentation, solid-state fermentation, enzymatic biocatalysis, and anaerobic digestion, highlighting their potential for the production of biofuels, enzymes, and high-value bioproducts. In addition to identifying current advances, this review addresses key technical challenges such as (i) the need for efficient pretreatment to release fermentable sugars from lignocellulosic biomass; (ii) the compositional variability of by-products like vinasse and molasses; (iii) the generation of metabolic inhibitors—such as furfural and hydroxymethylfurfural—during thermochemical processes; and (iv) the high costs related to inputs like hydrolytic enzymes. Special attention is given to detoxification strategies for inhibitory compounds and to the integration of multifunctional processes to improve overall system efficiency. The final section outlines emerging trends (2024–2025) such as the use of CRISPR-engineered microbial consortia, advanced pretreatments, and immobilization systems to enhance the productivity and sustainability of bioprocesses. In conclusion, the valorization of sugarcane by-products through biotechnology not only contributes to waste reduction but also supports circular economy principles and the development of sustainable production models. Full article

Introduction/Objective: Post-bariatric surgery patients require long-term, coordinated care to address complex nutritional, physiological, and behavioral challenges. Personalized smart nutrition, combining individualized dietary strategies with targeted monitoring, has emerged as a valuable direction for optimizing recovery and long-term outcomes. This article examines how traditional medical protocols can be enhanced by digital solutions in a multidisciplinary framework. Methods: The study analyzes current clinical practices, including personalized meal planning, physical rehabilitation, biochemical marker monitoring, and psychological counseling, as applied in post-bariatric care. These established approaches are then analyzed in relation to the NutriMonitCare system, a digital health system developed and tested in a laboratory environment. Used here as an illustrative example, the NutriMonitCare system demonstrates the potential of digital tools to support clinicians through real-time monitoring of dietary intake, activity levels, and physiological parameters. Results: Findings emphasize that medical protocols remain the cornerstone of post-surgical management, while digital tools may provide added value by enhancing data availability, supporting individualized decision making, and reinforcing patient adherence. Systems like the NutriMonitCare system could be integrated into interdisciplinary care models to refine nutrition-focused interventions and improve communication across care teams. However, their clinical utility remains theoretical at this stage and requires further validation. Conclusions: In conclusion, the integration of digital health tools with conventional post-operative care has the potential to advance personalized smart nutrition. Future research should focus on clinical evaluation, real-world testing, and ethical implementation of such technologies into established medical workflows to ensure both efficacy and patient safety. Full article

Demand Side Management (DSM) plays a crucial role in modern energy systems, enabling more efficient use of energy resources and contributing to the sustainability of the power grid. This study examines DSM strategies within a multi-environment context encompassing residential, commercial, and industrial sectors, with a focus on diverse appliance types that exhibit distinct operational characteristics and user preferences. Initially, a single-objective optimization approach using Genetic Algorithms (GAs) is employed to minimize the total energy cost under a real Time-of-Use (ToU) pricing scheme. This heuristic method allows for the effective scheduling of appliance operations while factoring in their unique characteristics such as power consumption, usage duration, and user-defined operational flexibility. This study extends the optimization problem to a multi-objective framework that incorporates the minimization of CO₂ emissions under a real annual energy mix while also accounting for user discomfort. The Non-dominated Sorting Genetic Algorithm II (NSGA-II) is utilized for this purpose, providing a Pareto-optimal set of solutions that balances these competing objectives. The inclusion of multiple objectives ensures a comprehensive assessment of DSM strategies, aiming to reduce environmental impact and enhance user satisfaction. Additionally, this study monitors the Peak-to-Average Ratio (PAR) to evaluate the impact of DSM strategies on load balancing and grid stability. It also analyzes the impact of considering different periods of the year with the associated ToU hourly schedule and CO₂ emissions hourly profile. A key innovation of this research is the integration of detailed, category-specific metrics that enable the disaggregation of costs, emissions, and user discomfort across residential, commercial, and industrial appliances. This granularity enables stakeholders to implement tailored strategies that align with specific operational goals and regulatory compliance. Also, the emphasis on a user discomfort indicator allows us to explore the flexibility available in such DSM mechanisms. The results demonstrate the effectiveness of the proposed multi-objective optimization approach in achieving significant cost savings that may reach 20% for industrial applications, while the order of magnitude of the trade-offs involved in terms of emissions reduction, improvement in discomfort, and PAR reduction is quantified for different frameworks. The outcomes not only underscore the efficacy of applying advanced optimization frameworks to real-world problems but also point to pathways for future research in smart energy management. This comprehensive analysis highlights the potential of advanced DSM techniques to enhance the sustainability and resilience of energy systems while also offering valuable policy implications. Full article

The hull of a linear code C is the intersection of C with its dual code. The goal is to study the dimensions of the hulls of optimal binary and ternary linear codes for a given length and dimension. The focus is on the lengths at which self-orthogonal (respectively, LCD) optimal codes exist at fixed dimension. Full article

The evidence for photobiomodulation in reducing postoperative pain after endodontic instrumentation is classified as low or very low certainty, indicating a need for further research. Longitudinal pain assessments over 24 h are crucial, and studies should explore these pain periods. Background/Objectives: This double-blind, randomized controlled clinical trial evaluated the effect of PBM on pain following single-visit endodontic treatment of maxillary molars at 4, 8, 12, and 24 h. Primary outcomes included pain at 24 h; secondary outcomes included pain at 4, 8, and 12 h, pain during palpation/percussion, OHIP-14 analysis, and frequencies of pain. Methods: Approved by the Research Ethics Committee (5.598.290) and registered in Clinical Trials (NCT06253767), the study recruited adults (21–70 years) requiring endodontic treatment in maxillary molars. Fifty-eight molars were randomly assigned to two groups: the PBM Group (n = 29), receiving conventional endodontic treatment with PBM (100 mW, 333 mW/cm², 9 J distributed at 3 points near root apices), and the control group (n = 29), receiving conventional treatment with PBM simulation. Pain was assessed using the Visual Analog Scale. Results: Statistical analyses used chi-square and Mann–Whitney tests, with explained variance (η²). Ten participants were excluded, leaving 48 patients for analysis. No significant differences were observed in postoperative pain at 24, 4, 8, or 12 h, or in palpation/percussion or OHIP-14 scores. Pain frequencies ranged from 12.5% to 25%. Conclusions: PBM does not influence post-treatment pain in maxillary molars under these conditions. These results emphasize the importance of relying on well-designed clinical trials to guide treatment decisions, and future research should focus on personalized dosimetry adapted to the anatomical characteristics of the treated dental region to enhance the accuracy and efficacy of therapeutic protocols. Full article

Change point models are widely used in medical and epidemiological studies to capture the threshold effects of continuous covariates on health outcomes. These threshold effects represent critical points at which the relationship between biomarkers or risk factors and disease risk shifts, often reflecting underlying biological mechanisms or clinically relevant intervention points. While most existing methods focus on right-censored data, interval censoring is common in large-scale clinical trials and follow-up studies, where the exact event times are not observed but are known to fall within time intervals. In this paper, we propose a semiparametric transformation model with an unknown change point for interval-censored data. The model allows flexible transformation functions, including the proportional hazards and proportional odds models, and it accommodates both main effects and their interactions with the threshold variable. Model parameters are estimated via the EM algorithm, with the change point identified through a profile likelihood approach using grid search. We establish the asymptotic properties of the proposed estimators and evaluate their finite-sample performance through extensive simulations, showing good accuracy and coverage properties. The method is further illustrated through an application to the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial data. Full article

The plant-based oil industry contributes significantly to food waste/by-products in the form of underutilized biomass, including oil pomace, cake/meal, seeds, peels, wastewater, etc. These waste/by-products contain a significant quantity of nutritious and bioactive compounds (phenolics, lignans, flavonoids, dietary fiber, proteins, and essential minerals) with proven health-promoting effects. The utilization of them as natural, cost-effective, and food-grade functional ingredients in novel food formulations holds considerable potential. This review highlights the potential of waste/by-products generated during plant-based oil processing as a promising source of bioactive compounds and covers systematic research, including recent studies focusing on innovative extraction and processing techniques. It also sheds light on their promising potential for valorization as food ingredients, with a focus on specific examples of food fortification. Furthermore, the potential for value creation in the food industry is emphasized, taking into account associated challenges and limitations, as well as future perspectives. Overall, the current information suggests that the valorization of plant-based oil industry waste and by-products for use in the food industry could substantially reduce malnutrition and poverty, generate favorable health outcomes, mitigate environmental concerns, and enhance economic profit in a sustainable way by developing health-promoting, environmentally sustainable food systems. Full article