Search Results (52,111)

Kerr nonlinear effect extremely impacts both the spectral and the temporal evolutions of ultrashort pulses, although it is challenging to tailor over a broadened spectral region. In this work, we propose an on-chip Si₃N₄-organic hybrid waveguide with sophisticated non-monotonic nonlinear coefficient γ(ω). A chirp-free pulse can be broadened or compressed at different peak powers in the normal dispersion range. The impact of the second-order Kerr nonlinearity with respect to frequency can overbalance that of dispersion. This new method deepens the understanding of the high-order nonlinear effects and help exploit innovative nonlinearity-engineered on-chip platforms for pulse shaping in the immediate future. Full article

Adaptive forest and fire management in parks and protected areas is becoming increasingly complex as climate change alters the frequency and intensity of disturbances (wildfires, pest and disease outbreaks, etc.), while park visitation and the number of people living adjacent to publicly managed lands continues to increase. Evidence-based, climate-adaptive forest and fire management practices are critical for the responsible stewardship of public resources and require the continued availability of long-term ecological monitoring data. The US National Park Service has been collecting long-term fire monitoring plot data since 1998, and has continued to add monitoring plots, but these data are housed in databases with limited access and minimal analytic capabilities. To improve the availability and decision support capabilities of this monitoring dataset, we created the Trends in Forest Fuels Dashboard (TFFD), which provides an implementation framework from data collection to web visualization. This easy-to-use and updatable tool incorporates data from multiple years, plot types, and locations. We demonstrate our approach at Rocky Mountain National Park using the ArcGIS Online (AGOL) software platform, which hosts TFFD and allows for efficient data visualizations and analyses customized for the end user. Adopting interactive, web-hosted tools such as TFFD allows the National Park Service to more readily leverage insights from long-term forest monitoring data to support decision making and resource allocation in the context of environmental change. Our approach translates to other data-to-decision workflows where customized visualizations are often the final steps in a pipeline designed to increase the utility and value of collected data and allow easier integration into reporting and decision making. This work provides a template for similar efforts by offering a roadmap for addressing data availability, cleaning, storage, and interactivity that may be adapted or scaled to meet a variety of organizational and management use cases. Full article

Manhole shafts in urban drainage systems are prone to accumulating trapped air pockets during intense rainfall, which can lead to sudden bounce of hinged covers and pose significant near-field risks. However, threshold criteria at the prototype scale remain unavailable. To obtain quantitative evidence of cover bounce under full-scale conditions and to clarify the effects of counterweight, dual-shaft coupling, and pressure–displacement phase lag, a series of experiments have been conducted on a prototype platform consisting of two shafts with hinged covers. Tests have been repeated under various counterweight conditions ranging from 0 to 30 kg. Pressure data from multiple transducers and high-speed video recordings have been synchronously acquired, filtered, and temporally aligned. Based on these, the critical overpressure at initial lift-off was identified, and oscillation characteristics and coupling effects have been analyzed. The critical overpressure was found to increase monotonically with added counterweight. When the counterweight was large, the system transitioned into a decaying response, with negligible subsequent bounce. The single-peak “rise–fall” pattern observed in single-shaft conditions no longer appeared when both covers lifted simultaneously. Notably, the critical overpressure did not coincide with the pressure peak, and a significant phase lag was observed between the pressure maximum and the moment of maximum displacement. These findings provide actionable support for the identification, modeling, and rapid mitigation of manhole cover bounce risks in urban drainage systems. Full article

Silver nanoparticles (AgNPs) are extensively utilized in cosmetics and healthcare products, creating an urgent need for sensitive quantification methods. We report the first application of a metal–organic framework for electrochemical AgNPs sensing in cosmetic samples. A glassy carbon electrode was modified with polyethyleneimine-encapsulated MOF-235 (PEI-MOF-235/GCE); the PEI layer enriches AgNPs through Ag–N coordination, whereas the high-surface-area MOF catalyzes their oxidative dissolution. Under optimized conditions (catalyst loading 1.4 µg mm⁻³, pH 4.3 PBS), differential-pulse voltammetry provided a linear range of 10–100 ng L⁻¹ and a detection limit of 3.93 ng L⁻¹ (S/N = 3). The sensor exhibited excellent stability (RSD ≤ 4.7%) and good anti-interference capability toward common aquatic ions. Compared with a standard HPLC method, recoveries in spiked cosmetic samples were 97.9–102.6%. This MOF-based strategy offers a sensitive, selective, and field-deployable platform for routine monitoring of trace AgNPs. Full article

Above-ground biomass in agroforestry refers to the total mass of living vegetation, primarily trees and shrubs, integrated into agricultural landscapes. It plays a key role in climate change mitigation by capturing and storing carbon. Accurate estimation of above-ground biomass in agroforestry systems requires effective drone deployment and sensor management. This study presents a detailed methodology for biomass estimation using Unmanned Aircraft Systems, based on an experimental campaign conducted in the Campania region of Italy. Multispectral drone platforms were used to generate calibrated reflectance maps and derive vegetation indices for biomass estimation in agroforestry landscapes. Integrating field-measured tree attributes with remote sensing indices improved the accuracy and efficiency of biomass prediction. Following the assessment of mission parameters, flights were conducted using a commercial drone to demonstrate consistency of results across multiple altitudes. Terrain-follow mode and high image overlap were employed to evaluate ground sampling distance sensitivity, radiometric performance, and overall data quality. The outcome is a defined process that enables agronomists to effectively estimate above-ground biomass in agroforestry landscapes using drone platforms, following the procedure outlined in this paper. Predictive performance was evaluated using standard model metrics, including R², RMSE, and MAE, which are essential for replicability and comparison in future studies. Full article

Background/Objectives: Breast cancer remains the most prevalent malignancy among women worldwide, with letrozole (LZ) serving as a critical aromatase inhibitor for hormone receptor–positive cases. However, long-term oral administration of LZ is often associated with systemic adverse effects and poor patient compliance. To overcome these limitations, new non-aqueous nanoemulgels (NEMGs) were developed for transdermal delivery of LZ. Methods: The NEMGs were formulated using glyceryl monooleate (GMO), Sepineo P600^®, Transcutol, propylene glycol, and penetration enhancers propylene glycol laurate (PGL), propylene glycol monocaprylate (PGMC), and Captex^®. Physicochemical characterization, solubility, stability, and in vitro permeation studies were conducted using Strat-M^® membranes, while in vivo pharmacokinetics were evaluated in rat models. Results: The optimized GMO/PGMC-based NEMG demonstrated significantly enhanced drug flux, higher permeability coefficients, and shorter lag times compared with other NEMGs and suspension emulgels. In vivo, transdermal application of the GMO/PGMC-based NEMG over an area of 2.55 cm² produced dual plasma absorption peaks, with 57% of the LZ dose absorbed relative to oral administration over 12 days. Shelf-life and accelerated stability assessments confirmed excellent physicochemical stability with negligible crystallization. Conclusions: The developed LZ NEMG formulations offer a stable, effective, and patient-friendly transdermal drug delivery platform for breast cancer therapy. This system demonstrates potential to improve patient compliance and reduce systemic toxicity compared to conventional oral administration. Full article

The mental health of young adults is a widespread and growing concern in many communities, impacting social sustainability. At the same time, there is growing evidence of the value that nature can provide towards improving health and wellbeing. However, there is little research on the scale of the monetized value of relevant wellbeing benefits from nature exposure. Nature prescribing draws on the growing base of evidence about nature and its health and wellbeing connections, with medical practitioners and/or allied health workers providing a prescription to selected patients to participate in a program that offers interventions intended to improve participant health and/or wellbeing, using a nature setting. This paper is the first to undertake a cost–benefit analysis of nature prescribing, involving a program aimed to improve the wellbeing of young adults with mild to moderate mental illness in regional/rural Victoria, Australia. The evaluation demonstrates that a curated, group-based nature exposure program can yield significant improvement in levels of life satisfaction and mental health in this cohort. Paired sample comparisons and multiple regression analyses suggest that the program produced an increase in mean participant life satisfaction scores of ~0.7 units, measured using Personal Wellbeing Index scores. A project benefit–cost ratio of over four resulted from this. Mental health, as measured by Kessler scale scores, also showed solid improvement, and loneliness was reduced. The unique contributions of nature and of the group-based delivery mode to the measured benefits were not identifiable but the combined effect was evident, improving participants’ likelihood of social inclusion, a major social sustainability goal. Furthermore, the solid program benefit–cost ratios indicate an economically sustainable program, which uses an environmental platform (nature) for its delivery. This links all three triple bottom line sustainability outcomes to this program. Topping up group-based nature exposure, after completion of the six-session, two-hours-per-session program, was important for many participants to sustain benefit levels. Participants emphasized the importance of the program being delivered by trained professionals. Achieving involvement of a suitably sized project comparison or control group through the 8-month program evaluation period to follow-up proved challenging, which somewhat weakens the power of the evaluation findings. Full article

Robotaxi services represent a major step in the commercialization of autonomous driving, offering efficiency, consistency, and safety benefits. However, despite technological advances, their large-scale adoption is far from guaranteed. Most urban users already rely on mature ride-hailing platforms such as Didi and Uber, making the real behavioral question not whether to adopt Robotaxi, but whether to migrate from existing services. Prior studies based on TAM, UTAUT, or trust models have primarily examined users’ initial adoption decisions, overlooking the substitution behavior that better captures how people shift between competing mobility services in real contexts. This study addresses this gap by applying the Push–Pull–Mooring (PPM) framework to examine users’ migration from ride-hailing to Robotaxi services, based on survey data collected from 1206 respondents across four Chinese cities (Beijing, Shanghai, Guangzhou, and Wuhan). The model was tested using structural equation modeling and multi-group analysis (SEM–MGA). Push factors reflect negative experiences with ride-hailing, including social anxiety and insecurity caused by drivers’ behaviors; pull factors emphasize Robotaxi’ autonomy and service reliability; while mooring factors capture habitual ride-hailing use and perceived Robotaxi risk. Findings indicate that push and pull factors significantly promote migration intentions, whereas mooring factors hinder them. Among all factors, perceived risk exerted the strongest negative effect (β = −0.36), underscoring its critical role as a barrier to Robotaxi migration. Gender differences are also evident, with women more sensitive to risks and men more influenced by reliability. By situating adoption within a migration context, this study enriches high-risk innovation theory and offers practical guidance for designing gender-sensitive and user-specific promotion strategies. Full article

Woody plants, comprising forest and fruit tree species, provide essential ecological and economic benefits to society. Their genetic improvement is challenging due to long generation intervals and high heterozygosity. Genetic transformation, which combines targeted DNA delivery with plant regeneration from transformed cells, offers a powerful alternative to accelerating their domestication and improvement. Agrobacterium tumefaciens, Rhizobium rhizogenes, and particle bombardment have been widely used for DNA delivery into a wide variety of explants, including leaves, stems, hypocotyls, roots, and embryos, with regeneration occurring via direct organogenesis, callus-mediated organogenesis, somatic embryogenesis, or hairy root formation. Despite successes, conventional approaches are hampered by low efficiency, genotype dependency, and a reliance on challenging tissue culture. This review provides a critical analysis of the current landscape in woody plant transformation, moving beyond a simple summary of techniques to evaluate the co-evolution of established platforms with disruptive technologies. Key advances among these include the use of developmental regulators to engineer regeneration, the rise in in planta systems to bypass tissue culture, and the imperative for DNA-free genome editing to meet regulatory and public expectations. By examining species-specific breakthroughs in key genera, including Populus, Malus, Citrus, and Pinus, this review highlights a paradigm shift from empirical optimization towards rational, predictable engineering of woody plants for a sustainable future. Full article

This paper introduces a new class of generalized metric structures, called interpolative b-metric spaces, which unify and extend both b-metric spaces and interpolative metric spaces in a non-trivial way. By incorporating a nonlinear correction term alongside a multiplicative scaling parameter into the triangle inequality, this framework enables broader contractive conditions and refined control of convergence behavior. We develop the foundational theory of interpolative b-metric spaces and establish a generalized Ćirić-type fixed point theorem, along with Banach, Kannan, and Bianchini-type results as corollaries. To highlight the originality and applicability of our approach, we apply the main theorem to a nonlinear Volterra-type integral equation, demonstrating that interpolative b-metrics effectively accommodate nonlinear solution structures beyond the scope of traditional metric models. This work offers a unified platform for fixed point analysis and opens new directions in nonlinear and functional analysis. Full article

Entangled photons are essential for photonic quantum technologies. Their generation typically relies on spontaneous parametric down-conversion, but conventional nonlinear crystals are bulky and hard to integrate on chips. Rhombohedral-stacked MoS${}_2$ combines a high refractive index, large second-order nonlinearity, and flexibility for heterogeneous integration, making it a promising platform for integrated quantum photonics. However, the typical thin-film form of 3R-MoS${}_2$ restricts the effective nonlinear interaction length, limiting entanglement generation efficiency in practical devices. To overcome this, phase-matching strategies in integrated waveguides are required but have so far remained undeveloped. Here, we introduce a waveguide-integrated 3R-MoS${}_2$ platform with periodic grooves to achieve quasi-phase matching, enhancing down-conversion efficiency. Leveraging ${\chi }^{\left(2\right)}$ tensor symmetries and orthogonal waveguide modes, the design efficiently generates entangled photons, providing a compact, scalable route toward 2D-material-based integrated quantum photonic circuits. Full article

Therapeutic peptides have gained significant attention due to their high specificity, potency, and safety profiles in treating various diseases. However, their clinical application via the oral route remains challenging. Peptides are inherently unstable in the gastrointestinal environment, where they are rapidly degraded by proteolytic enzymes and acidic pH, leading to poor bioavailability. Additionally, their large molecular size and hydrophilicity restrict passive diffusion across the epithelial barriers of the gastrointestinal tract. These limitations have traditionally necessitated parenteral administration, which reduces patient compliance and convenience. The oral cavity, comprising the buccal and sublingual mucosa, offers a promising alternative for peptide delivery. Its rich vascularization allows for rapid systemic absorption while bypassing hepatic first-pass metabolism. Furthermore, the mucosal surface provides a relatively permeable and accessible site for drug administration. However, the oral cavities also present significant barriers: the mucosal epithelium limits permeability, the presence of saliva causes rapid clearance, and enzymes in saliva contribute to peptide degradation. Therefore, innovative strategies are essential to enhance peptide stability, retention, and permeation in this environment. Nanoparticle-based delivery systems, including lipid-based carriers such as liposomes and niosomes, as well as polymeric nanoparticles like chitosan and PLGA, offer promising solutions. These nanocarriers protect peptides from enzymatic degradation, enhance mucoadhesion to prolong residence time, and facilitate controlled release. Their size and surface properties can be engineered to improve mucosal penetration, including through receptor-mediated endocytosis or by transiently opening tight junctions. Among these, niosomes have shown high encapsulation efficiency and sustained release potential, making them particularly suitable for oral peptide delivery. Despite advances, challenges remain in translating these technologies clinically, including ensuring biocompatibility, scalable manufacturing, and patient acceptance. Nevertheless, the oral cavity’s accessibility, combined with nanotechnological innovations, offers a compelling platform for personalized, non-invasive peptide therapies that could significantly improve treatment outcomes and patient quality of life. Full article

Satellite remote sensing has become an increasingly important approach for detecting and quantifying methane emissions across spatial and temporal scales. While most reviews in the literature have addressed aspects of methane monitoring, they often focus primarily on satellite platforms or provide discussions on retrieval methodologies. This review offers an integrated assessment of recent developments in satellite-based methane detection, combining technical evaluations of satellite instruments with detailed analysis of retrieval techniques and sector-specific applications. The paper distinguishes between area flux mappers and point-source imagers and reviews both established and recent satellite missions, including GHGSat, MethaneSAT, and PRISMA. Retrieval methods are critically compared, covering full-physics models, CO₂ proxy approaches, optimal estimation, and emerging data-driven techniques such as machine learning. The review further examines methane emission characteristics in key sectors, i.e., oil and gas, coal mining, agriculture, and waste management, and discusses how satellite data are applied in emission estimation and mitigation contexts. The paper concludes by identifying technical and operational challenges and outlining research directions to enhance the accuracy, accessibility, and policy relevance of satellite-based methane monitoring. Full article

Dexterous bimanual manipulation remains a challenging task in reinforcement learning (RL) due to the vast state–action space and the complex interdependence between the hands. Conventional end-to-end learning struggles to handle this complexity, and multi-agent RL often faces limitations in stably acquiring cooperative movements. To address these issues, this study proposes a hierarchical progressive policy learning framework for dexterous bimanual manipulation. In the proposed method, one hand’s policy is first trained to stably grasp the object, and, while maintaining this grasp, the other hand’s manipulation policy is progressively learned. This hierarchical decomposition reduces the search space for each policy and enhances both the connectivity and the stability of learning by training the subsequent policy on the stable states generated by the preceding policy. Simulation results show that the proposed framework outperforms conventional end-to-end and multi-agent RL approaches. The proposed method was demonstrated via sim-to-real transfer on a physical dual-arm platform and empirically validated on a bimanual cube manipulation task. Full article

Within the context of Industry 4.0, the integration of heterogeneous industrial devices into unified control and supervision systems remains a fundamental challenge due to diversified communication protocols and interfaces. Conventional industrial gateways relying on customized driver development encounter issues such as high protocol extension costs, lengthy development cycles, and limited compatibility, restricting the agility and scalability of modern industrial embedded control systems. This paper proposes a novel paradigm for industrial interoperability gateways based on a software-defined architecture and graphical modeling. Through layered decoupling of software functions, protocol parsing and data conversion functionalities are encapsulated into draggable graphical components, enabling flexible adaptation and efficient debugging of heterogeneous protocols. The gateway middleware GMGbox architecture was designed and validated through an experimental platform. Results demonstrate that the gateway can accurately and concurrently parse multiple heterogeneous protocols via graphical configuration, stably acquire over 3000 data points, support online visual debugging and flexible deployment of protocol logic, and seamlessly integrate final data with upper-layer systems through standard protocols. Case studies of a level control system and a wastewater treatment plant Supervisory Control and Data Acquisition (SCADA) further validate the effectiveness and practical utility of this paradigm in real-world industrial scenarios. The proposed solution provides a novel architectural paradigm for building reconfigurable and maintainable systems in the field of industrial automation. Full article