Search Results (5,786)

Among the many nanomaterials studied for biomedical uses, silica and gold nanoparticles have gained significant attention because of their unique physical and chemical properties and their compatibility with living tissues. Mesoporous silica nanoparticles (MSNs) have great stability and a large surface area, while gold nanoparticles (AuNPs) display remarkable optical features. Both types of nanoparticles have been widely researched for their individual roles in drug delivery, imaging, biosensing, and therapy. When combined with gadolinium (Gd), a common contrast agent, these nanostructures provide improved imaging due to gadolinium’s strong paramagnetic properties. This study focuses on incorporating gold nanoparticles and gadolinium into a silica matrix to develop a theranostic system. Various analytical techniques were used to characterize the nanocomposites, including infrared spectroscopy (FTIR), ultraviolet-visible spectroscopy (UV-Vis), thermogravimetric analysis (TGA), nitrogen adsorption, scanning electron microscopy (SEM), dynamic light scattering (DLS), X-ray fluorescence (XRF), X-ray diffraction (XRD), vibrating sample magnetometry (VSM), and neutron activation analysis (NAA). Techniques like XRF mapping, XANES, nitrogen adsorption, SEM, and VSM were crucial in confirming the presence of gadolinium and gold within the silica network. VSM and EPR analyses confirmed the attenuation of the saturation magnetization for all nanocomposites. This validates their potential for biomedical applications in diagnostics. Moreover, activating gold nanoparticles in a nuclear reactor generated a promising radioisotope for cancer treatment. These results indicate the potential of using a theranostic nanoplatform that employs mesoporous silica as a carrier, gold nanoparticles for radioisotopes, and gadolinium for imaging purposes. Full article

The global textile industry has a significant environmental impact, driven by fast fashion and rising consumption, which leads to large amounts of waste. In Chile, this problem is especially visible, with thousands of tons of discarded clothing accumulating in open areas and landfills. This study explores how to design a practical textile revalorization system grounded in local reality. We used a qualitative mixed-methods approach, combining semi-structured interviews with six experts in textile circularity and an online survey completed by 328 people. Thematic analysis revealed low public awareness of textile recycling, limited consumer participation, and major structural barriers, including scarce infrastructure and unclear regulations. Experts emphasized the importance of coordinated action among government, industry, and grassroots recyclers, while survey respondents highlighted the need for education and easier recycling options. Based on these insights, we propose an integrated framework that combines education campaigns, better recycling systems, and formal recognition of informal recyclers’ work. While centered on Chile, the study offers ideas that could support textile circularity efforts in other countries facing similar challenges. By merging expert knowledge with everyday public perspectives, the approach helps design more realistic and socially grounded solutions for textile waste management. As with many exploratory frameworks, external validation remains a necessary step for future research to strengthen its robustness and applicability. Full article

This study investigates the influence of post-deposition thermal annealing temperature on the crystal structure, chemical composition, and electrical performance of solution-processed indium oxide (In₂O₃) thin films. Based on thermogravimetric analysis (TGA) of the precursor solution, annealing temperatures of 350, 450, and 550 °C were adopted. The resulting In₂O₃ films were characterized using ultraviolet–visible (UV–Vis) spectroscopy, atomic force microscopy (AFM), Raman spectroscopy, and Hall-effect measurements to evaluate their optical, morphological, crystalline polymorphism, and electrical properties. The results revealed that the film annealed at 450 °C exhibited a field-effect mobility of 4.28 cm²/V·s and an on/off current ratio of 2.15 × 10⁷. The measured hysteresis voltages were 3.11, 1.80, and 0.92 V for annealing temperatures of 350, 450, and 550 °C, respectively. Altogether, these findings indicate that an annealing temperature of 450 °C provides an optimal balance between the electrical performance and device stability for In₂O₃-based thin-film transistors (TFTs), making this condition favourable for high-performance oxide electronics. Full article

Background: Age-related macular degeneration is a major cause of vision loss, and improved visualization of macular neovascularization (MNV) on OCT angiography (OCTA) could enhance clinical assessment. This study aimed to establish a simple and accessible image enhancement method. Methods: We retrospectively analyzed 24 eyes from 22 patients with MNV at the Doheny UCLA Eye Centers. Grayscale-inverted OCTA images were generated using the basic “Invert” function in ImageJ 1.51 23. Each original and inverted image pair was assessed for seven MNV-related features: structure and area within 3 × 3 mm, 6 × 6 mm and 12 × 12 mm scans, and presence of polypoidal lesions. Twenty-one ophthalmologists graded visibility using a standardized five-point scale. Paired comparisons were performed using the Wilcoxon signed-rank test. Results: Grayscale inversion significantly improved the visualization of MNV structure in 6 × 6 mm scans (mean difference: +0.67 ± 1.02; p = 0.008), 12 × 12 mm scans (+0.62 ± 1.07; p = 0.013), and detection of polypoidal lesions (+0.43 ± 0.98; p = 0.030). No significant differences were found for 3 × 3 mm structure (p = 0.793) or area-related features (all p > 0.3). Conclusions: Grayscale inversion may enhance MNV visibility and polypoidal lesion detection on OCTA. As this study relied solely on subjective assessments, future work should incorporate quantitative image analysis. Full article

As a vital driver of supply chain management, data has evolved into both a foundational resource and a critical production factor for optimizing supply chains and mitigating risk. This study adopts a four-dimensional framework (i.e., visibility, coordination, flexibility, and redundancy) to investigate how data asset information disclosure (DAID) shapes supply chain risk (SCR). Relative to the existing literature, this paper contributes by examining the determinants of supply chain risk from the perspective of data asset information disclosure and by conducting empirical analyses using double debiased machine learning and causal mediation analysis. The results show that DAID significantly lowers SCR, with results robust to multiple sensitivity checks. Economically, a one-standard-deviation increase in DAID leads to an average decline in SCR of 0.63%. Causal mediation analysis, aligned with the theoretical dimensions, reveals that DAID mitigates SCR through four channels: enhancing information transparency, improving visibility, strengthening agile responsiveness, and increasing supply chain concentration. Heterogeneity tests reveal stronger effects among firms facing fewer financing constraints, operating in more marketized environments, and designated as chain master firms. Further evidence suggests that reduced SCR promotes a greater capacity for coordinated innovation within the supply chain. Full article

The functionalization of textiles with nanomaterials through green synthesis offers a promising pathway for sustainable material innovation. This study explores the in situ green synthesis of silver nanoparticles (AgNPs) onto cotton fabrics using Solanum tuberosum (potato) peel extract as a natural reducing and stabilizing agent. The synthesis conditions were optimized by varying silver nitrate concentration, extract volume, temperature, pH, and reaction time, after which the optimized protocol was applied for fabric treatment. The presence and distribution of AgNPs were confirmed through UV-Visible spectroscopy, Fourier-transform infrared spectroscopy, scanning electron microscopy and dynamic light scattering. The treated fabrics demonstrated strong and durable antibacterial performance, with inhibition zones of 23 ± 0.02 against Escherichia coli and 16 ± 0.01 against Staphylococcus aureus. Notably, antibacterial activity was retained even after 20 washing cycles, demonstrating the durability of the treatment. Mechanical testing revealed a 32.25% increase in tensile strength and a corresponding 10.47% reduction in elongation at break compared to untreated fabrics, suggesting improved durability with moderate stiffness. Air permeability decreased by 8.8%, correlating with the rougher surface morphology observed in Scanning Electron Microscopy images. Thermal analysis showed a decrease in thermal stability relative to untreated cotton, highlighting the influence of AgNPs on degradation behavior. Overall, this work demonstrates that potato peel waste, an abundant and underutilized biomass, can be used as a sustainable source for the green synthesis of AgNP-functionalized textiles. The approach provides a cost-effective and environmentally friendly strategy for developing multifunctional fabrics, while supporting circular economy goals in textile engineering. Full article

This paper presents a CMOS-based hybrid system capable of noninvasively quantifying the total hemoglobin (tHb), the oxygen saturation (SpO₂), and the heart rate (HR) by utilizing five-wavelength (670, 770, 810, 850, and 950 nm) photoplethysmography. Conventional pulse oximeters are limited to the measurements of SpO₂ and heart rate, therefore hindering the real-time estimation of tHb that is clinically essential for monitoring anemia, chronic diseases, and postoperative recovery. Therefore, the proposed hybrid system enables us to distinguish between the concentrations of oxygenated (HbO₂) and deoxygenated hemoglobin (Hb) by using the absorption characteristics of five wavelengths from the visible to near-infrared range. This CMOS hybrid mixed-signal architecture includes a light emitting diode (LED) driver as a transmitter and an optoelectronic receiver with on-chip avalanche photodiodes, followed by a field-programmable gate array (FPGA) for a real-time signal processing pipeline. The proposed hybrid system, validated through post-layout simulations and algorithmic verification, achieves high precision with ±0.3 g/dL accuracy for tHb and ±1.5% for SpO₂, while the heart rate is extracted via 1024-point Fast Fourier Transform (FFT) with an error below ±0.2%. These results demonstrate the potential of a CMOS-based hybrid system as a feasible solution to achieve real-time, low-power, and high-accuracy analysis of bio-signals for clinical and home-use applications. Full article

Reliable navigation for mobile robots in dynamic, human-populated environments remains a significant challenge, as moving objects often cause localization drift and map corruption. While Simultaneous Localization and Mapping (SLAM) techniques excel in static settings, issues like keyframe redundancy and optimization inefficiencies further hinder their practical deployment on robotic platforms. To address these challenges, we propose DKB-SLAM, a real-time RGB-D visual SLAM system specifically designed to enhance robotic autonomy in complex dynamic scenes. DKB-SLAM integrates optical flow with Gaussian-based depth distribution analysis within YOLO detection frames to efficiently filter dynamic points, crucial for maintaining accurate pose estimates for the robot. An adaptive keyframe selection strategy balances map density and information integrity using a sliding window, considering the robot’s motion dynamics through parallax, visibility, and matching quality. Furthermore, a heterogeneously weighted local bundle adjustment (BA) method leverages map point geometry, assigning higher weights to stable edge points to refine the robot’s trajectory. Evaluations on the TUM RGB-D benchmark and, crucially, on a mobile robot platform in real-world dynamic scenarios, demonstrate that DKB-SLAM outperforms state-of-the-art methods, providing a robust and efficient solution for high-precision robot localization and mapping in dynamic environments. Full article

This paper introduces CodeDive, a web-based programming environment with real-time behavioral tracking designed to enhance student progress assessment and provide timely support for learners, while also addressing the academic integrity challenges posed by Large Language Models (LLMs). Visibility into the student’s learning process has become essential for effective pedagogical analysis and personalized feedback, especially in the era where LLMs can generate complete solutions, making it difficult to truly assess student learning and ensure academic integrity based solely on the final outcome. CodeDive provides this process-level transparency by capturing fine-grained events, such as code edits, executions, and pauses, enabling instructors to gain actionable insights for timely student support, analyze learning trajectories, and effectively uphold academic integrity. It operates on a scalable Kubernetes-based cloud architecture, ensuring security and user isolation via containerization and SSO authentication. As a browser-accessible platform, it requires no local installation, simplifying deployment. The system produces a rich data stream of all interaction events for pedagogical analysis. In a Spring 2025 deployment in an Operating Systems course with approximately 100 students, CodeDive captured nearly 25,000 code snapshots and over 4000 execution events with a low overhead. The collected data powered an interactive dashboard visualizing each learner’s coding timeline, offering actionable insights for timely student support and a deeper understanding of their problem-solving strategies. By shifting evaluation from the final artifact to the developmental process, CodeDive offers a practical solution for comprehensively assessing student progress and verifying authentic learning in the LLM era. The successful deployment confirms that CodeDive is a stable and valuable tool for maintaining pedagogical transparency and integrity in modern classrooms. Full article

This study examines the global mobility of researchers in the smart city domain from 2000 to 2020, using inter-country and intercity affiliation data from the Web of Science. Employing network analysis and spatial econometric models, the paper maps the structural reconfiguration of scientific labor circulation. The results show that the international mobility network is dense yet asymmetric, dominated by a small set of high-frequency corridors such as China–United States, which intensified markedly over the two decades. While early networks were fragmented and polycentric, the later period reveals a multipolar configuration with significant growth in South–South and intra-European exchanges. At the city level, Beijing, Shanghai, Wuhan, and Nanjing emerged as central nodes, reflecting the consolidation of East Asian hubs within the global knowledge system. Mesoscale community detection highlights the coexistence of territorially embedded ecosystems and transregional corridors sustained by thematic and reputational affinities. Growth decomposition indicates that high-income countries benefit from both talent retention and international inflows, while upper-middle-income countries rely heavily on inbound mobility. Spatial regression and quantile models confirm that economic growth and baseline scientific visibility remain robust drivers of urban smart city performance. In contrast, mobility effects are context-dependent and heterogeneous across city positions. Together, these findings demonstrate that researcher mobility is not only a vector of knowledge exchange but also a mechanism that reinforces spatial hierarchies and reshapes the geography of global smart city innovation. Full article

Zinc oxide (ZnO), a wide-bandgap semiconductor, has garnered significant interest for photocatalytic applications due to its excellent chemical stability, non-toxicity, and strong oxidative capability. In this study, density functional theory (DFT) calculations were employed to explore the impact of ruthenium (Ru) doping on the structural, electronic, and magnetic properties of wurtzite ZnO. The introduction of Ru leads to bandgap narrowing and the emergence of impurity states, thereby enhancing visible light absorption. Charge density analysis reveals enhanced electron delocalization, while the projected density of states (PDOS) indicates strong hybridization between the Ru 4d orbitals and the ZnO electronic states. The density of states at the Fermi level, N(EF), exhibits a notable dependence on doping concentration and magnetic configuration. For non-magnetic states, N(EF) reaches 11 states/eV and 9.5 states/eV at 12.5% and 25% Ru concentrations, respectively. In ferromagnetic configurations, these values decrease to 0.65 states/eV and 1.955 states/eV, while antiferromagnetic states yield 4.945 states/eV and 0.65 states/eV. These variations highlight Ru’s crucial role in regulating electronic density, thereby affecting electrical conductivity, magnetic properties, and photocatalytic efficiency. The results offer theoretical guidance for designing high-performance Ru-doped ZnO photocatalysts. Full article

Social isolation is a critical but understudied concern for people living with HIV (PLHIV), particularly in rural U.S. communities where social visibility is high and access to supportive services is limited. Disclosure of HIV status is often framed as a health-promoting behavior that facilitates engagement with care and access to social support, yet it can also increase vulnerability to exclusion and isolation, especially where confidentiality is difficult to maintain. Using data from a pilot survey of rural PLHIV in the United States ($n=17$), this study examines when disclosure may function adaptively and when it may coincide with a heightened social burden. A Social Isolation Index was constructed from 15 indicators of exclusion across family, community, and institutional domains. Disclosure was measured both by the number of people informed and whether sexual partners were told. Typological methods and Qualitative Comparative Analysis (QCA) were applied to explore how disclosure patterns relate to race, sexual identity, and reported isolation. The results indicate that disclosure is not uniformly protective: several participants who disclosed widely also reported high levels of isolation, with heterosexual and Black participants often reporting a higher cumulative burden. These findings challenge one-size-fits-all assumptions about disclosure in public health messaging and underscore the need for tailored strategies that recognize both disclosure and nondisclosure as potentially adaptive responses in rural and marginalized communities. Full article

Polylactic acid (PLA) is an eco-friendly polymer known for its biodegradability and biocompatibility, yet its properties are sensitive to recycling and sterilization. These processes may cause chain scission and structural irregularities, leading to reduced strength, brittleness, or unpredictable deformation. In this study, PLA and recycled PLA (Re-PLA) specimens were produced by FDM 3D printing with different infill rates (25%, 50%, 75%), layer thicknesses (0.15, 0.20, 0.25 mm), and printing orientations (0°, 45°, 90°). Steam sterilization at 121 °C and 1 bar for 15 min simulated biomedical conditions. Mechanical, surface, degradation, and biocompatibility properties were examined using three-point bending, roughness measurements, SEM, and cell viability tests. Results showed that infill rate was the main parameter affecting flexural strength and surface quality, while orientation increased roughness. Sterilization and recycling made deformation less predictable, particularly in St-Re-PLA. SEM revealed stronger bonding at higher infill, but more brittle fractures in PLA and Re-PLA, while sterilized specimens showed ductile features. No visible degradation occurred at any infill level. Regression analysis confirmed that second-order polynomial models effectively predicted flexural strength, with layer thickness being most influential. These findings provide critical insights into optimizing PLA and Re-PLA processing for biomedical applications, particularly in the production of sterilizable and recyclable implantable devices. Full article

Advanced rider assistance systems (ARAS) play a crucial role in enhancing motorcycle safety through features such as collision avoidance, blind-spot detection, and adaptive cruise control, which rely heavily on sensors like radar, cameras, and LiDAR. However, their performance is often compromised under adverse weather conditions, leading to sensor interference, reduced visibility, and inconsistent reliability. This study evaluates the effectiveness and limitations of ARAS technologies in rain, fog, and snow, focusing on how sensor performance, algorithms, techniques, and dataset suitability influence system reliability. A thematic analysis was conducted, selecting studies focused on ARAS in adverse weather conditions based on specific selection criteria. The analysis shows that while ARAS offers substantial safety benefits, its accuracy declines in challenging environments. Existing datasets, algorithms, and techniques were reviewed to identify the most effective options for ARAS applications. However, more comprehensive weather-resilient datasets and adaptive multi-sensor fusion approaches are still needed. Advancing in these areas will be critical to improving the robustness of ARAS and ensuring safer riding experiences across diverse environmental conditions. Full article

This article offers a new perspective on Miriam’s red jewel in Nathaniel Hawthorne’s The Marble Faun (1860), interpreting it as a symbol of Jewish femininity, diasporic memory, and aesthetic resistance. Although the jewel has received little critical attention, this study suggests that it plays a central role in shaping Miriam’s identity and in articulating broader cultural anxieties around gender, ethnicity, and visibility. Through intertextual readings of Shakespeare’s Jessica and Walter Scott’s Rebecca and Rowena, the essay situates Miriam within a literary tradition of Jewish women whose identities are mediated through symbolic adornments. In addition to literary analysis, the article draws on visual art history—particularly Carol Ockman’s interpretation of Jean-Auguste-Dominique Ingres’s 1848 portrait of Baronne de Rothschild—to explore how 19th-century visual culture contributed to the eroticization and exoticization of Jewish women. By placing Hawthorne’s portrayal of Miriam in dialogue with such visual representations, the essay highlights how the red jewel functions as a site of encoded cultural meaning. The analysis is further informed by feminist art theory (Griselda Pollock) and postcolonial critique (Edward Said), offering an interdisciplinary approach to questions of identity, marginalization, and symbolic resistance. While not claiming to offer a definitive reading, this article aims to open new interpretive possibilities by foregrounding the jewel’s narrative and symbolic significance. In doing so, it contributes to ongoing conversations in Hawthorne studies, Jewish cultural history, and the intersections of literature and visual art. Full article