Search Results (8,363)

Cyanobacteria are a prolific source of bioactive metabolites with expanding applications in sustainable agriculture and biotechnology. This work explores, for the first time in thermotolerant Colombian isolates, the impact of light spectrum, photoperiod, and irradiance on the co-production of exopolysaccharides (EPS) and indole-3-acetic acid (IAA). Six strains from hot-spring environments were screened under varying blue:red (B:R) LED ratios and full-spectrum illumination. Hapalosiphon sp. UFPS_002 outperformed all others, reaching ~290 mg L⁻¹ EPS and 28 µg mL⁻¹ IAA in the initial screen. Response-surface methodology was then used to optimize light intensity and photoperiod. EPS peaked at 281.4 mg L⁻¹ under a B:R ratio of 1:5 LED, 85 µmol m⁻² s⁻¹, and a 14.5 h light cycle, whereas IAA was maximized at 34.4 µg mL⁻¹ under cool-white LEDs at a similar irradiance. The quadratic models exhibited excellent predictive power (R² > 0.98) and a non-significant lack of fit, confirming the light regime as the dominant driver of metabolite yield. These results demonstrate that precise photonic tuning can selectively steer carbon flux toward either EPS or IAA, providing an energy-efficient strategy to upscale thermotolerant cyanobacteria for climate-resilient biofertilizers, bioplastics precursors, and other high-value bioproducts. Full article

Optical Coherence Tomography (OCT) has evolved from a breakthrough ophthalmologic imaging tool into a cornerstone technology in interventional cardiology. After its initial applications in retinal imaging in the early 1990s, OCT was subsequently envisioned for cardiovascular use. In 1995, its ability to visualize atherosclerotic plaques was demonstrated in an in vitro study, and the following year marked the acquisition of the first in vivo OCT image of a human coronary artery. A major milestone followed in 2000, with the first intracoronary imaging in a living patient using time-domain OCT. However, the real inflection point came in 2006 with the advent of frequency-domain OCT, which dramatically improved acquisition speed and image quality, enabling safe and routine imaging in the catheterization lab. With the advent of high-resolution, second-generation frequency-domain systems, OCT has become clinically practical and widely adopted in catheterization laboratories. OCT progressively entered interventional cardiology, first proving its safety and feasibility, then demonstrating superiority over angiography alone in guiding percutaneous coronary interventions and improving outcomes. Today, it plays a central role not only in clinical practice but also in cardiovascular research, enabling precise assessment of plaque biology and response to therapy. With the advent of artificial intelligence and hybrid imaging systems, OCT is now evolving into a true precision-medicine tool—one that not only guides today’s therapies but also opens new frontiers for discovery, with vast potential still waiting to be explored. Tracing its historical evolution from ophthalmology to cardiology, this narrative review highlights the key technological milestones, clinical insights, and future perspectives that position OCT as an indispensable modality in contemporary interventional cardiology. As a guiding thread, the myth of Prometheus is used to symbolize the evolution of OCT—from its illuminating beginnings in ophthalmology to its transformative role in cardiology—as a metaphor for how light, innovation, and knowledge can reveal what was once hidden and redefine clinical practice. Full article

Sources of renewable energy have attracted considerable attention. Their expanded use will have a substantial impact on both the cost of energy production and climate change. Solar energy is one efficient and safe option; however, solar energy harvesting sites, irrespective of the location, can impact the ecosystem. This experimental study explores the energy available inside and outside of novel miniature energy harvesting cages by measuring light intensity and power generated. Varying light intensity outside the cage has been utilized to study the remaining energy inside the cage of a flexible design, where the heights of the harvesting panels are parameters. Cages are built from custom photovoltaic panels arranged in a staircase manner to provide access to growing plants. The balance between power generation and biological development is investigated. Two different structures are presented to explore the variation of illumination intensity inside the cages. The experimental results show a substantial reduction in energy inside the cages. The experimental results showed up to 24% reduction in illumination inside the cages in winter. The reduction is even larger in summer, up to 57%. The results from the models provide a framework to study the possible impact on a biological system residing inside the cages, paving the way for practical farming with sustainable energy harvesting. Full article

Systems thinking (ST) is a foundational cognitive skillset to advance sustainability education but has not been well examined for learners prior to higher education. This case study research in rural middle schools in the Midwestern U.S. examines systems thinking outcomes of a place-based energy literacy unit focused on energy-efficient building design. The unit employs the science of energy-efficient, green buildings to illuminate the ways in which energy flows between natural and built environments. The unit emphasized electrical, light, and thermal energy systems and the ways these systems interact to create functional and energy-efficient buildings. This study focuses on three case study classrooms where students across schools (n = 89 students) created systems models as part of pre- and post-unit tests (n = 162 models). The unit tests consisted of student drawings, annotations, and writings, culminating into student-developed systems models. Growth from pre- to post-test was observed in both the identification of system elements and the linkages between elements. System elements included in the models were common classroom features, such as windows, lights, and temperature control, suggesting that rooting the unit in place-based teaching may support ST skills. Full article

This study presents the development of Cu-doped NiMo/TiO₂ photoelectrocatalysts for simultaneous green hydrogen production and pharmaceutical pollutant removal under simulated solar irradiation. The catalysts were synthesized via wet impregnation (15 wt.% total metal loading with 0.6 wt.% Cu) and thermally treated at 400 °C and 900 °C to investigate structural transformations and catalytic performance. Comprehensive characterization (XRD, BET, SEM, XPS) revealed phase transitions, enhanced crystallinity, and redistribution of redox states upon Cu incorporation, particularly the formation of NiTiO₃ and an increase in oxygen vacancies. Crystallite sizes for anatase, rutile, and brookite ranged from 21 to 47 nm at NiMoCu400, while NiMoCu900 exhibited only the rutile phase with 55 nm crystallites. BET analysis showed a surface area of 44.4 m²·g⁻¹ for NiMoCu400, and electrochemical measurements confirmed its higher electrochemically active surface area (ECSA, 2.4 cm²), indicating enhanced surface accessibility. In contrast, NiMoCu900 exhibited a much lower BET surface area (1.4 m²·g⁻¹) and ECSA (1.4 cm²), consistent with its inferior photoelectrocatalytic performance. Compared to previously reported binary NiMo/TiO₂ systems, the ternary NiMoCu/TiO₂ catalysts demonstrated significantly improved hydrogen production activity and more efficient photoelectrochemical degradation of paracetamol. Specifically, NiMoCu400 showed an anodic peak current of 0.24 mA·cm⁻² for paracetamol oxidation, representing a 60% increase over NiMo400 and a cathodic current of –0.46 mA·cm⁻² at –0.1 V vs. RHE under illumination, nearly six times higher than the undoped counterpart (–0.08 mA·cm⁻²). Mott–Schottky analysis further revealed that NiMoCu400 retained n-type behavior, while NiMoCu900 exhibited an unusual inversion to p-type, likely due to Cu migration and rutile-phase-induced realignment of donor states. Despite its higher photosensitivity, NiMoCu900 showed negligible photocurrent, confirming that structural preservation and surface redox activity are critical for photoelectrochemical performance. This work provides mechanistic insight into Cu-mediated photoelectrocatalysis and identifies NiMoCu/TiO₂ as a promising bifunctional platform for integrated solar-driven water treatment and sustainable hydrogen production. Full article

Multimodal object detection leverages the complementary characteristics of visible (RGB) and infrared (IR) imagery, making it well-suited for challenging scenarios such as low illumination, occlusion, and complex backgrounds. However, most existing fusion-based methods rely on static or heuristic strategies, limiting their adaptability to dynamic environments. To address this limitation, we propose CLSANet, a cognitive learning-based self-adaptive network that enhances detection performance by dynamically selecting and integrating modality-specific features. CLSANet consists of three key modules: (1) a Dominant Modality Identification Module that selects the most informative modality based on global scene analysis; (2) a Modality Enhancement Module that disentangles and strengthens shared and modality-specific representations; and (3) a Self-Adaptive Fusion Module that adjusts fusion weights spatially according to local scene complexity. Compared to existing methods, CLSANet achieves state-of-the-art detection performance with significantly fewer parameters and lower computational cost. Ablation studies further demonstrate the individual effectiveness of each module under different environmental conditions, particularly in low-light and occluded scenes. CLSANet offers a compact, interpretable, and practical solution for multimodal object detection in resource-constrained settings. Full article

Our purpose is to evaluate the binocular contrast sensitivity function (CSF) in a presbyopic population and compare the results obtained with four different simultaneous-vision center-near multifocal contact lens (MCL) designs for distance vision under two illumination conditions. Additionally, chromatic CSF (red-green and blue-yellow) was evaluated. A randomized crossover pilot study was conducted. Four daily disposable lens designs, based on simultaneous-vision and center-near correction, were compared. The achromatic contrast sensitivity function (CSF) was measured binocularly using the CSV1000e test under two lighting conditions: room light on and off. Chromatic CSF was measured using the OptoPad-CSF test. Comparison of achromatic results with room lighting showed a statistically significant difference only for 3 cpd (p = 0.03) between the baseline visit (with spectacles) and all MCLs. Comparison of achromatic results without room lighting showed no statistically significant differences between the baseline and all MCLs for any spatial frequency (p > 0.05 in all cases). Comparison of CSF-T results showed a statistically significant difference only for 4 cpd (p = 0.002). Comparison of CSF-D results showed no statistically significant difference for all frequencies (p > 0.05 in all cases). The MCL designs analyzed provided satisfactory achromatic contrast sensitivity results for distance vision, similar to those obtained with spectacles, with no remarkable differences between designs. Chromatic contrast sensitivity for the red-green and blue-yellow mechanisms revealed some differences from the baseline that should be further investigated in future studies. Full article

Indoor horticulture requires a substantial quantity of electricity to meet crops extended photoperiodic requirements for optimal photosynthetic rate. Simultaneously, global electricity costs have grown dramatically in recent years, endangering the sustainability and profitability of indoor vertical farms and/or modern greenhouses that use artificial lighting systems to accelerate crop development and growth. This study investigates the growth rate and physiological development of cherry tomato plants cultivated in a pilot indoor vertical farm at the Agricultural University of Athens’ Laboratory of Farm Structures (AUA) under continuous and disruptive lighting. The leaf physiological traits from multiple photoperiodic stress treatments were analyzed and utilized to estimate the plant’s tolerance rate under varied illumination conditions. Four different photoperiodic treatments were examined and compared, firstly plants grew under 14 h of continuous light (C-14L10D/control), secondly plants grew under a normalized photoperiod of 14 h with intermittent light intervals of 10 min of light followed by 50 min of dark (NI-14L10D/stress), the third treatment where plants grew under 14 h of a load-shifted energy demand response intermittent lighting schedule (LSI-14L10D/stress) and finally plants grew under 13 h photoperiod following of a load-shifted energy demand response intermittent lighting schedule (LSI-13L11D/stress). Plants were subjected also under two different light spectra for all the treatments, specifically WHITE and Blue/Red/Far-red light composition. The aim was to develop flexible, energy-efficient lighting protocols that maintain crop productivity while reducing electricity consumption in indoor settings. Results indicated that short periods of disruptive light did not negatively impact physiological responses, and plants exhibited tolerance to abiotic stress induced by intermittent lighting. Post-harvest data indicated that intermittent lighting regimes maintained or enhanced growth compared to continuous lighting, with spectral composition further influencing productivity. Plants under LSI-14L10D and B/R/FR spectra produced up to 93 g fresh fruit per plant and 30.4 g dry mass, while consuming up to 16 kWh less energy than continuous lighting—highlighting the potential of flexible lighting strategies for improved energy-use efficiency. Full article

Super-resolution microscopy (SRM) has revolutionized our understanding of subcellular structures, including cell organelles and viruses. For human immunodeficiency virus (HIV), SRM has significantly advanced knowledge of viral structural biology and assembly dynamics. This review analyzes how SRM techniques (particularly PALM, STORM, STED, and SIM) have been applied over the past decade to study HIV structural components and assembly. By categorizing and comparing studies based on SRM methods, HIV components, and labeling strategies, we assess the strengths and limitations of each approach. Our analysis shows that PALM is most commonly used for live-cell imaging of HIV Gag, while STED is primarily used to study the viral envelope (Env). STORM and SIM have been applied to visualize various components, including Env, capsid, and matrix. Antibody labeling is prevalent in PALM and STORM studies, targeting Env and capsid, whereas fluorescent protein labeling is mainly associated with PALM and focused on Gag. A recent emphasis on Gag and Env points to deeper investigation into HIV assembly and viral membrane dynamics. Insights from SRM studies of HIV not only enhance virological understanding but also inform future research in therapeutic strategies and delivery systems, including extracellular vesicles. Full article

Liquid crystal elastomers (LCEs) have shown great potential in the field of soft robotics due to their unique actuation capabilities. Despite the growing number of experimental studies in the soft robotics field, theoretical research remains limited. In this paper, a dynamic model of a bionic arm using an LCE fiber as artificial muscle is established, which exhibits periodic oscillation controlled by periodic illumination. Based on the assumption of linear damping and angular momentum theorem, the dynamics equation of the model oscillation is derived. Then, based on the assumption of linear elasticity model, the periodic spring force of the fiber is given. Subsequently, the evolution equations for the cis number fraction within the fiber are developed, and consequently, the analytical solution for the light-excited strain is derived. Following that, the dynamics equation is numerically solved, and the mechanism of the controllable oscillation is elucidated. Numerical calculations show that the stable oscillation period of the bionic arm depends on the illumination period. When the illumination period aligns with the natural period of the bionic arm, the resonance is formed and the amplitude is the largest. Additionally, the effects of various parameters on forced oscillation are analyzed. The results of numerical studies on the bionic arm can provide theoretical support for the design of micro-machines, bionic devices, soft robots, biomedical devices, and energy harvesters. Full article

Computer vision is of wide interest to perform the phenotyping of horticultural crops such as apple trees at high throughput. In orchards specially constructed for variety testing or breeding programs, computer vision tools should be able to extract phenotypical information form each tree separately. We focus on segmenting individual apple trees as the main task in this context. Segmenting individual apple trees in dense orchard rows is challenging because of the complexity of outdoor illumination and intertwined branches. Traditional methods rely on supervised learning, which requires a large amount of annotated data. In this study, we explore an alternative approach using prompt engineering with the Segment Anything Model and its variants in a zero-shot setting. Specifically, we first detect the trunk and then position a prompt (five points in a diamond shape) located above the detected trunk to feed to the Segment Anything Model. We evaluate our method on the apple REFPOP, a new large-scale European apple tree dataset and on another publicly available dataset. On these datasets, our trunk detector, which utilizes a trained YOLOv11 model, achieves a good detection rate of $97\%$ based on the prompt located above the detected trunk, achieving a Dice score of 70% without training on the REFPOP dataset and 84% without training on the publicly available dataset.We demonstrate that our method equals or even outperforms purely supervised segmentation approaches or non-prompted foundation models. These results underscore the potential of foundational models guided by well-designed prompts as scalable and annotation-efficient solutions for plant segmentation in complex agricultural environments. Full article

Metasurfaces have drawn extensive research attention for their unique optical properties and vast application potential. Among the various resonant modes induced in metasurfaces, BIC and electric anapole modes stand out as particularly interesting due to their distinctive physical characteristics. In this work, we designed and investigated novel dimeric dumbbell-shaped metasurfaces incorporating two independently tunable asymmetric parameters. This structural innovation enables the simultaneous excitation of both electric anapole and QBIC modes under normally incident MIR illumination. More importantly, by adjusting these two asymmetric parameters, one can independently tune the resonance peaks of the two modes, thereby overcoming the performance limits of conventional single-peak modulation. This metasurface design demonstrates outstanding performance for dielectric environment-sensing applications. We conducted a comprehensive investigation of the sensing sensitivity for dumbbell-shaped metasurfaces of various geometries. Our simulation results show that the circular-shaped configuration achieved high sensitivity, reaching 20,930 GHz/RIU. This work offers a novel design paradigm for multi-mode control and functionalization of metasurface structures. Full article

Multi-modal object detection that fuses RGB (Red-Green-Blue) and infrared (IR) data has emerged as an effective approach for addressing challenging visual conditions such as low illumination, occlusion, and adverse weather. However, most existing multi-modal detectors prioritize accuracy while neglecting computational efficiency, making them unsuitable for deployment on resource-constrained edge devices. To address this limitation, we propose PONet, a lightweight and efficient multi-modal vehicle detection network tailored for real-time edge inference. PONet incorporates Polarized Self-Attention to improve feature adaptability and representation with minimal computational overhead. In addition, a novel fusion module is introduced to effectively integrate RGB and IR modalities while preserving efficiency. Experimental results on the VEDAI dataset demonstrate that PONet achieves a competitive detection accuracy of 82.2% mAP@0.5 while sustaining a throughput of 34 FPS on the OrangePi AIpro 20T device. With only 3.76 M parameters and 10.2 GFLOPs (Giga Floating Point Operations), PONet offers a practical solution for edge-oriented remote sensing applications requiring a balance between detection precision and computational cost. Full article

Aging is a multifactorial process that affects various physiological functions, including masticatory performance, which is crucial for oral health and nutritional well-being. Impaired masticatory function, often due to factors such as tooth loss, reduced salivation, or muscle atrophy, can lead to significant nutritional challenges and compromise the overall health of elderly individuals. Recent research has illuminated the interconnectedness of masticatory function, oral microbiota, and gut health, suggesting that altered chewing ability may disrupt oral microbial communities, which in turn affect gastrointestinal health and systemic inflammation. This commentary review provides a comprehensive analysis of the role of masticatory function in aging, exploring its impact on the oral microbiota, gut health, and broader nutritional status. We discuss the potential consequences of impaired mastication, including malnutrition, dysbiosis, and gastrointestinal disorders, and explore possible strategies for improving masticatory function and maintaining a healthy gut microbiome through interventions like dietary modifications, oral care, and rehabilitation. We aim to underscore the importance of integrating masticatory function management into the broader context of aging-related healthcare, promoting holistic, multidisciplinary approaches to support nutritional needs and quality of life in older adults. Full article

The transition to sustainable energy systems demands efficient recycling methods for critical raw materials like lithium. In this study, we present a new class of pH- and light-switchable flotation collectors based on isomeric derivatives of the natural product Punicine, termed inverse Punicines. These amphoteric molecules were synthesized via a straightforward four-step route and structurally tuned for hydrophobization by alkylation. Their performance as collectors was evaluated in microflotation experiments of lithium aluminate (LiAlO₂) and silicate matrix minerals such as melilite and calcium silicate. Characterization techniques including ultraviolet-visible (UV-Vis), nuclear magnetic resonance (NMR) and electron spin resonance (ESR) spectroscopy as well as contact angle, zeta potential (ζ potential) and microflotation experiments revealed strong pH- and structure-dependent interactions with mineral surfaces. Notably, N-alkylated inverse Punicine derivatives showed high flotation yields for LiAlO₂ at pH of 11, with a derivative possessing a dodecyl group attached to the nitrogen as collector achieving up to 86% recovery (collector conc. 0.06 mmol/L). Preliminary separation tests showed Li upgrading from 5.27% to 6.95%. Radical formation and light-response behavior were confirmed by ESR and flotation tests under different illumination conditions. These results demonstrate the potential of inverse Punicines as tunable, sustainable flotation reagents for advanced lithium recycling from complex slag systems. Full article