Search Results (10,391)

Euterpe precatoria Mart. is an increasingly important palm for subsistence and income generation in central and western Amazonia with growing demand for its fruit pulp, which is an alternative source of açaí juice for domestic and international markets. This study synthesizes current knowledge on its systematics, ecology, fruit production in natural populations, fruit quality, uses, population management, and related areas, identifying critical research gaps. A systematic literature survey was conducted across databases including Web of Science, Scopus, Scielo, CAPES, and Embrapa. Of 1568 studies referencing Euterpe, 273 focused on E. precatoria, with 90 addressing priority themes. Genetic diversity studies suggest the E. precatoria may represent a complex of species. Its population abundance varies across habitats: the highest variability occurs in terra firme, followed by baixios and várzeas. Várzeas exhibit greater productivity potential, with more bunches per plant and higher fruit weight than baixios; no production data exist for terra firme. Additionally, E. precatoria has higher anthocyanin content than E. oleracea, the primary commercial açaí species. Management of natural populations and cultivation practices are essential for sustainable production; however, studies in these fields are still limited. The information is crucial to inform strategies aiming to promote the sustainable production of the species. Full article

The increasing demand for critical raw materials such as copper and cobalt highlights the need for efficient beneficiation of low-grade ores. This study investigates a copper–cobalt sulfide ore (0.99% Cu, 0.028% Co) using froth flotation to produce high-grade concentrates. Various types of surfactants are applied in different ways, each serving an essential function such as acting as collectors, frothers, froth stabilizers, depressants, activators, pH modifiers, and more. A series of flotation tests employing different collectors (SIPX, PBX, AERO, DF 507B) and process conditions was conducted to optimize recovery and selectivity. Methyl isobutyl carbinol (MIBC) was consistently used as the foaming agent, and 700 g/L was used as the slurry density at 25 °C. Dosages of 30 and 100 g/t¹ were used in all tests. Notably, adjusting the pH to ~4 using HCl significantly improved cobalt concentrate separation. The optimized flotation conditions yielded concentrates with over 15% Cu and metal recoveries exceeding 80%. Mineralogical characterization confirmed the selective enrichment of target metals in the concentrate. The results demonstrate the potential of this beneficiation approach to contribute to the European Union’s supply of critical raw materials. Full article

Concrete is an essential material in the construction industry due to its strength and versatility. However, its quality can be compromised by environmental factors during its fresh and early-age states. To address this vulnerability, various sensors have been implemented to monitor critical parameters. While high-precision sensors (e.g., piezoelectric and fiber optic) offer accurate measurements, their cost and fragility limit their widespread use in construction environments. In response, this study proposes a cost-effective, Arduino-based wireless monitoring system to track temperature and humidity in fresh and early-age concrete elements. The system was validated through laboratory tests on cylindrical specimens and industrial applications on self-compacting concrete New Jersey barriers. The sensors recorded temperature variations between 15 °C and 35 °C and relative humidity from 100% down to 45%, depending on environmental exposure. In situ monitoring confirmed the system’s ability to detect thermal gradients and evaporation dynamics during curing. Additionally, the presence of embedded sensors caused a tensile strength reduction of up to 37.5% in small specimens, highlighting the importance of sensor placement. The proposed solution demonstrates potential for improving quality control and curing management in precast concrete production with low-cost devices. Full article

This study investigated the effects of color shade and curing time on the degree of conversion (DC) and microhardness of colored compomers. A total of 162 samples (81 for DC, 81 for microhardness) were prepared, with nine samples per color group (gold, blackberry, green, pink, orange, lemon, blue, silver) and for the control. Samples were subdivided into three polymerization subgroups (3 s/3200 mW/cm², 10 s/1000 mW/cm², 20 s/1000 mW/cm²). The DC was analyzed via fourier transform infrared spectroscopy (FTIR) and microhardness was measured using Vickers testing. Statistical analysis included two-way ANOVA and Spearman correlation (α = 0.05). The colored compomers demonstrated a significantly lower DC compared to the control group (p ≤ 0.001). Among the tested colors, green exhibited the lowest DC (33.3%), while orange showed the highest (51.0%). A significant difference in DC was observed across curing times (p = 0.005), with the 3 s and 20 s groups exhibiting significantly higher conversion rates than the 10 s group. Microhardness values exhibited significant variation depending on the color (p < 0.001). Gold compomers demonstrated the lowest microhardness, whereas silver compomers showed comparable performance with the control group (p = 0.154). A moderate correlation between DC and microhardness was observed overall (ρ = 0.42, p = 0.003). However, the observed relationships were color-dependent: orange displayed a strong positive correlation (ρ = 0.78), whereas pink revealed no meaningful association (ρ = −0.15). Color and curing time critically influence compomer performance. High-intensity short curing is viable for lighter colors, while darker colors require extended curing. Customized protocols are essential to optimize clinical outcomes in pediatric dentistry. Full article

Sensor selection in IoT-based smart healthcare systems is a complex fuzzy decision-making problem due to the presence of numerous uncertain and interdependent evaluation criteria. Traditional fuzzy multi-criteria decision-making (MCDM) approaches often assume independence among criteria and rely on aggregation operators that impose sharp transitions between preference levels. These assumptions can lead to decision outcomes with insufficient differentiation, limited discriminatory capacity, and potential issues in consistency and sensitivity. To overcome these limitations, this study proposes a novel fuzzy decision-making framework by integrating Quasi-D-Overlap functions into the fuzzy MARCOS (Measurement of Alternatives and Ranking According to Compromise Solution) method. Quasi-D-Overlap functions represent a generalized extension of classical overlap operators, capable of capturing partial overlaps and interdependencies among criteria while preserving essential mathematical properties such as associativity and boundedness. This integration enables a more intuitive, flexible, and semantically rich modeling of real-world fuzzy decision problems. In the context of real-time health monitoring, a case study is conducted using a hybrid edge–cloud architecture, involving sensor tasks such as heartrate monitoring and glucose level estimation. The results demonstrate that the proposed method provides greater stability, enhanced discrimination, and improved responsiveness to weight variations compared to traditional fuzzy MCDM techniques. Furthermore, it effectively supports decision-makers in identifying optimal sensor alternatives by balancing critical factors such as accuracy, energy consumption, latency, and error tolerance. Overall, the study fills a significant methodological gap in fuzzy MCDM literature and introduces a robust fuzzy aggregation strategy that facilitates interpretable, consistent, and reliable decision making in dynamic and uncertain healthcare environments. Full article

Background: Mediastinal staging plays a critical role in guiding treatment decisions for non-small cell lung cancer (NSCLC). While mediastinoscopy has been the gold standard for assessing mediastinal lymph node involvement, endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) has emerged as a minimally invasive alternative with comparable diagnostic accuracy. This systematic review evaluates the diagnostic performance, safety, cost-effectiveness, and feasibility of EBUS-TBNA versus mediastinoscopy for mediastinal staging. Methods: A systematic literature review was conducted in accordance with PRISMA guidelines, including searches in Medline, Scopus, EMBASE, and Cochrane databases for studies published from 2010 onwards. A total of 1542 studies were identified, and after removing duplicates and applying eligibility criteria, 100 studies were included for detailed analysis. The extracted data focused on sensitivity, specificity, complications, economic impact, and patient outcomes. Results: EBUS-TBNA demonstrated high sensitivity (85–94%) and specificity (~100%), making it an effective first-line modality for NSCLC staging. Mediastinoscopy remained highly specific (~100%) but exhibited slightly lower sensitivity (86–90%). EBUS-TBNA had a lower complication rate (~2%) and was more cost-effective, while mediastinoscopy provided larger biopsy samples, essential for molecular and histological analyses. The need for general anaesthesia, longer hospital stays, and increased procedural costs make mediastinoscopy less favourable as an initial approach. Combining both techniques in select cases enhanced overall staging accuracy, reducing false negatives and improving diagnostic confidence. Conclusions: EBUS-TBNA has become the preferred first-line mediastinal staging method due to its minimally invasive approach, high diagnostic accuracy, and lower cost. However, mediastinoscopy remains crucial in cases requiring posterior mediastinal node assessment or larger tissue samples. The integration of both techniques in a stepwise diagnostic strategy offers the highest accuracy while minimizing risks and costs. Given the lower hospitalization rates and economic benefits associated with EBUS-TBNA, its widespread adoption may contribute to more efficient resource utilization in healthcare systems. Full article

Background: Trichosporon spp. are opportunistic fungi, capable of causing infection, especially in critically ill individuals who often use broad-spectrum antibiotics, invasive devices, and have comorbidities. Objectives The aim of this study was to analyze individuals’ clinical characteristics, evaluate tolerance to biocides, as well as biofilm formation and efflux pump activity in isolates of Trichosporon asahii. Methods: Clinical isolates of T. asahii collected between 2020 and 2023 from both hospitalized and non-hospitalized individuals, of both sexes, regardless of age, were tested for tolerance to sodium hypochlorite, hydrogen peroxide, benzalkonium chloride, and ethyl alcohol. Efflux pump activity was also assessed using ethidium bromide, and biofilm formation was measured with the Safranin test. Clinical parameters such as outcomes, source, and length of hospitalization were analyzed through electronic medical records. Results: A total of 37 clinical isolates of T. asahii were identified. Thirty-three (83.8%) isolates were from hospitalized individuals, with 81.82% collected in ICUs, an average hospital stay of 35 days, and a mortality rate of 51.6%. The tested strains displayed the largest mean inhibition zone for 2% sodium hypochlorite, indicating lower tolerance. A high level of efflux pump expression was detected among clinical isolates. Biofilm formation was detected in 25/67.5% of the isolates. Conclusions: These findings highlight the clinical relevance of T. asahii, particularly in critically ill individuals, and underscore the pathogen’s ability to tolerate biocides, express efflux pumps, and form biofilms, all of which may contribute to its persistence and pathogenicity in hospital environments. Enhanced surveillance and effective microbial control measures are essential to mitigate the risks associated with T. asahii infections. Full article

Integrating BIM curriculum into traditional construction management (CM) programs is essential to meet the increasing industry demand for BIM-ready graduates. However, academia struggles with BIM curriculum integration due to unfamiliar emerging BIM technologies, and the increased workload associated with curriculum transformation. Disciplines including nursing, health science, and medical overcame the same challenges using the ability-desire-knowledge-ability-reinforcement (ADKAR) change management model, while CM programs have not explored this model for BIM curriculum development. Thus, this research introduces the ADKAR change management lens to BIM curriculum development by proposing a practically modified and replicable ADKAR model for CM programs. Focus group interviews with 14 academics from the UK, USA, Korea, and Australia, revealed establishing a sense of urgency by appointing a BIM champion is the most critical step before the BIM curriculum development. Instant advice demystifying uncertain BIM concepts is recognised the most effective motivation among academia. Well-balanced BIM concept integrations is ‘sine qua non’ since excessively saturating BIM aspects across the program can dilute students’ essential domain knowledge. Students’ evaluation over the BIM curriculum were collected through a six-year longitudinal focus group interviews, revealing that progressive BIM learnings scaffolded from foundational concepts to advanced applications throughout their coursework is the most valuable. Full article

Background: Attachments are essential components in clear aligner therapy, enhancing retention and improving the predictability of tooth movements. Mechanical and wear properties of the composite resins used for attachment reproduction are critical to maintaining their integrity and shape over time. This study aimed to evaluate and compare the mechanical properties, thermal behavior, and wear performance of the hybrid composite Aligner Connect (AC) and the flowable resin (Connect Flow, CF). Methods: Twenty samples (ten AC and ten CF) were reproduced. All specimens underwent differential scanning calorimetry (DSC), combustion analysis, flat instrumented indentation, compression stress relaxation tests, and tribological analysis. A 3D wear profile reconstruction was performed to assess wear surfaces. Results: DSC and combustion analyses revealed distinct thermal transitions, with CF showing significantly lower Tg values (103.8 °C/81.4 °C) than AC (110.8 °C/89.6 °C) and lower residual mass after combustion (23% vs. 61%), reflecting reduced filler content and greater polymer mobility. AC exhibited superior mechanical properties, with higher maximum load (585.9 ± 22.36 N) and elastic modulus (231.5 ± 9.1 MPa) than CF (290.2 ± 5.52 N; 156 ± 10.5 MPa). Stress relaxation decrease was less pronounced in AC (18 ± 4%) than in CF (20 ± 4%). AC also showed a significantly higher friction coefficient (0.62 ± 0.060) than CF (0.55 ± 0.095), along with greater wear volume (0.012 ± 0.0055 mm³ vs. 0.0070 ± 0.0083 mm³) and maximum depth (36.88 ± 3.642 µm vs. 17.91 ± 3.387 µm). Surface roughness before wear was higher for AC (Ra, 0.577 ± 0.035 µm; Rt, 4.369 ± 0.521 µm) than for CF (Ra, 0.337 ± 0.070 µm; Rt, 2.862 ± 0.549 µm). After wear tests, roughness values converged (Ra, 0.247 ± 0.036 µm for AC; Ra, 0.236 ± 0.019 µm for CF) indicating smoothened and similar surfaces for both composites. Conclusions: The hybrid nanocomposite demonstrated greater properties in terms of stiffness, load-bearing capacity, and structural integrity when compared with flowable resin. Its use may ensure more durable attachment integrity and improved aligner–tooth interface performance over time. Full article

Background/Objectives: Orbital reconstruction remains one of the most demanding procedures in maxillofacial surgery. It requires not only precise anatomical knowledge but also poses multiple intraoperative challenges. Limited surgical visibility—especially in transconjunctival or transcaruncular approaches—demands exceptional precision from the surgeon. At the same time, the complex anatomical structure of the orbit, its rich vascularization and innervation, and the risk of severe postoperative complications—such as diplopia, sensory deficits, impaired ocular mobility, or in the most serious cases, post-traumatic blindness due to nerve injury or orbital compartment syndrome—necessitate the highest level of surgical accuracy. In this context, patient-specific implants (PSIs), commonly fabricated from zirconium oxide or ultra-high-density polyethylene, have become invaluable. Within CAD-based reconstructive planning, especially for orbital implants, critical factors include the implant’s anatomical fit, passive stabilization on intact bony structures, and non-interference with orbital soft tissues. Above all, precise replication of the orbital dimensions is essential for optimal clinical outcomes. This study compares the morphological accuracy of orbital structures based on anthropometric measurements from 3D models generated from fan-beam computed tomography (FBCT) and cone-beam computed tomography (CBCT). Methods: A cohort group of 500 Caucasian patients aged 8 to 88 years was analyzed. 3D models of the orbits were generated from FBCT and CBCT scans. Anthropometric measurements were taken to evaluate the morphological accuracy of the orbital structures. The assessed parameters included orbital depth, orbital width, the distance from the infraorbital rim to the infraorbital foramen, the distance between the piriform aperture and the infraorbital foramen, and the distance from the zygomatico-orbital foramen to the infraorbital rim. Results: Statistically significant differences were observed between virtual models derived from FBCT and those based on CBCT in several key parameters. Discrepancies were particularly evident in measurements of orbital depth, orbital width, the distance from the infraorbital rim to the infraorbital foramen, the distance between the piriform aperture and the infraorbital foramen, and the distance from the zygomatico-orbital foramen to the infraorbital rim. Conclusions: The statistically significant discrepancies in selected orbital dimensions—particularly in regions of so-called thin bone—demonstrate that FBCT remains the gold standard in the planning and design of CAD/CAM patient-specific orbital implants. Despite its advantages, including greater accessibility and lower radiation dose, CBCT shows limited reliability in the context of orbital and infraorbital reconstruction planning. Full article

Reactive oxygen species (ROS) are often seen solely as harmful byproducts of oxidative metabolism, yet evidence reveals their paradoxical roles in both promoting and inhibiting cancer progression. Despite advances, precise context-dependent mechanisms by which ROS modulate oncogenic signaling, therapeutic response, and tumor microenvironment dynamics remain unclear. Specifically, the spatial and temporal aspects of ROS regulation (i.e., the distinct effects of mitochondrial versus cytosolic ROS on the PI3K/Akt and NF-κB pathways, and the differential cellular outcomes driven by acute versus chronic ROS exposure) have been underexplored. Additionally, the specific contributions of ROS-generating enzymes, like NOX isoforms and xanthine oxidase, to tumor microenvironment remodeling and immune modulation remain poorly understood. This review synthesizes current findings with a focus on these critical gaps, offering novel mechanistic insights into the dualistic nature of ROS in cancer biology. By systematically integrating data on ROS source-specific functions and redox-sensitive signaling pathways, the complex interplay between ROS concentration, localization, and persistence is elucidated, revealing how these factors dictate the paradoxical support of tumor progression or induction of cancer cell death. Particular attention is given to antioxidant mechanisms, including NRF2-mediated responses, that may undermine the efficacy of ROS-targeted therapies. Recent breakthroughs in redox biosensors (i.e., redox-sensitive fluorescent proteins, HyPer variants, and peroxiredoxin–FRET constructs) enable precise, real-time ROS imaging across subcellular compartments. Translational advances, including redox-modulating drugs and synthetic lethality strategies targeting glutathione or NADPH dependencies, further highlight actionable vulnerabilities. This refined understanding advances the field by highlighting context-specific vulnerabilities in tumor redox biology and guiding more precise therapeutic strategies. Continued research on redox-regulated signaling and its interplay with inflammation and therapy resistance is essential to unravel ROS dynamics in tumors and develop targeted, context-specific interventions harnessing their dual roles. Full article

Building change detection and building damage assessment are two essential tasks in post-disaster analysis. Building change detection focuses on identifying changed building areas between bi-temporal images, while building damage assessment involves segmenting all buildings and classifying their damage severity. These tasks play a critical role in disaster response and urban development monitoring. Although supervised learning has significantly advanced building change detection and damage assessment, its reliance on large labeled datasets remains a major limitation. In contrast, self-supervised learning enables the extraction of meaningful data representations without explicit training labels. To address this challenge, we propose a self-supervised learning approach that unifies denoising autoencoders and contrastive learning, enabling effective data representation for building change detection and damage assessment. The proposed architecture integrates a dual denoising autoencoder with a Vision Transformer backbone and contrastive learning strategy, complemented by a Feature Pyramid Network-ResNet dual decoder and an Edge Guidance Module. This design enhances multi-scale feature extraction and enables edge-aware segmentation for accurate predictions. Extensive experiments were conducted on five public datasets, including xBD, LEVIR, LEVIR+, SYSU, and WHU, to evaluate the performance and generalization capabilities of the model. The results demonstrate that the proposed Denoising AutoEncoder-enhanced Dual-Fusion Network (DAEDFN) approach achieves competitive performance compared with fully supervised methods. On the xBD dataset, the largest dataset for building damage assessment, our proposed method achieves an F1 score of 0.892 for building segmentation, outperforming state-of-the-art methods. For building damage severity classification, the model achieves an F1 score of 0.632. On the building change detection datasets, the proposed method achieves F1 scores of 0.837 (LEVIR), 0.817 (LEVIR+), 0.768 (SYSU), and 0.876 (WHU), demonstrating model generalization across diverse scenarios. Despite these promising results, challenges remain in complex urban environments, small-scale changes, and fine-grained boundary detection. These findings highlight the potential of self-supervised learning in building change detection and damage assessment tasks. Full article

With the advancement of low-carbon and sustainable development initiatives, electric scooters, recognized as essential transportation tools and leisure products, have gained significant popularity, particularly among young people. However, the current electric scooter market is plagued by severe product similarity. Once the initial novelty fades for users, the usage frequency declines, resulting in considerable resource wastage. This research collected user needs via surveys and employed the KJ method (affinity diagram) to synthesize fragmented insights into cohesive thematic clusters. Subsequently, a hierarchical needs model for electric scooters was constructed using analytical hierarchy process (AHP) principles, enabling systematic prioritization of user requirements through multi-criteria evaluation. By establishing a house of quality (HoQ), user needs were transformed into technical characteristics of electric scooter products, and the corresponding weights were calculated. After analyzing the positive and negative correlation degrees of the technical characteristic indicators, it was found that there are technical contradictions between functional zoning and compact size, lightweight design and material structure, and smart interaction and usability. Then, based on the theory of inventive problem solving (TRIZ), the contradictions were classified, and corresponding problem-solving principles were identified to achieve a multi-functional innovative design for electric scooters. This research, leveraging a systematic industrial design analysis framework, identified critical pain points among electric scooter users, established hierarchical user needs through priority ranking, and improved product lifecycle sustainability. It offers novel methodologies and perspectives for advancing theoretical research and design practices in the electric scooter domain. Full article

Weed management remains a critical challenge in the U.S. container ornamental production industry, where weeds not only compete with crops for limited resources but also harbor pests and pathogens, thereby diminishing plant quality and marketability. The paper explores the economic impact of weed infestations, herbicide resistance development, and the limited availability of selective herbicides for ornamental crops in the United States. This review synthesizes current chemical weed control tactics, focusing not only on both preemergence and postemergence herbicides commonly used in ornamental nurseries, but also organic alternatives and integrated weed management (IWM) approaches as complementary strategies by evaluating their effectiveness, crop safety, and usage. There is a critical need for research in the areas of alternative chemical options such as insecticides, miticides (e.g., Zerotol and Tetra Curb Max), and organic products for liverwort control in greenhouses. Although essential oils and plant-based extracts show some potential, their effectiveness and practical use remain largely unexplored. Full article

This study aims to understand the meaning nursing professionals attribute to their lived experiences of providing humanized care within a public hospital setting. Grounded in Jean Watson’s theory of human caring, the research adopts a qualitative, descriptive phenomenological design to capture the perceptions and emotions of nurses regarding humanized care. Data were collected through semi-structured interviews with nine experienced nurses, selected through purposive sampling. The interviews, conducted virtually between July and December 2024, were analyzed using Colaizzi’s method and supported by Atlas.ti software. Four main thematic categories emerged: institutional health policies, professional image and identity, strengths and challenges in care, and essential competencies for humanized care. The findings highlight the critical role of empathy, cultural sensitivity, ethical commitment, and emotional presence in delivering compassionate care. Participants emphasized that, beyond clinical procedures, humanized care requires relational and contextual sensitivity, often hindered by institutional limitations and excessive administrative burdens. The study concludes that nursing professionals are key agents in promoting ethical, empathetic, and culturally respectful practices that humanize health services. These insights offer valuable contributions for designing policies and training strategies aimed at strengthening humanized care as a cornerstone of quality healthcare systems. Full article