Search Results (26)

Mirror segmentation remains challenging because mirror regions often share appearance with the reflected scene, while sensor depth around mirrors is frequently missing, noisy, or geometrically inconsistent. Although recent RGB-based methods have achieved strong results by exploiting contextual and symmetry-aware cues, their ability to use geometric information reliably is still limited. In this paper, we propose a reliable RGB-D mirror segmentation framework built upon SATNet. Specifically, we extend the symmetry-aware baseline with a dedicated depth branch that injects hierarchical sensor-depth features into the multi-scale decoder, and we introduce a Reliability-Guided Residual Correction Module (RGRCM) for final prediction refinement. Instead of treating predicted depth as an independent modality branch, RGRCM internally constructs dual-depth evidence from sensor depth and monocular depth estimated by a pretrained Depth Anything v2 model, encoding raw depth observations, cross-depth discrepancies, validity cues, and local depth instability. The resulting evidence is used to guide uncertainty-aware residual correction only in regions where depth-driven refinement is likely to be beneficial. Experiments on the RGBD-Mirror benchmark show that the proposed method achieves 83.57 IoU, 0.899 $F_{\beta }$, 0.026 MAE, and 6.26 BER, outperforming existing RGB and RGB-D mirror segmentation methods. Full article

This study employs effective field theory to investigate the magnetic properties of the Carbon-60 fullerene cage (C₆₀). The analysis shows that the magnetic behavior of the C60 molecule mirrors that of its sixty constituent carbon atoms, a phenomenon attributed to the molecule’s unique cage geometry and defined herein as the “identic magnetic effect” (IME). Furthermore, thermodynamic quantities, including magnetic susceptibility, specific heat, and internal energy, exhibit dual peaks at the coercive field points when the temperature is below the critical threshold (T < Tc). As the temperature exceeds this threshold (T > Tc), these peaks coalesce into a single maximum. These findings show good quantitative agreement with experimental phase transition characteristics, reflecting the magnetic behavior induced by the C₆₀ cage geometry. IME behavior can open the door to modeling and produce a new class of IME sensors (IMESs). Full article

Driven by the national policy of total water resources control and efficiency improvement, the behavior of water resource utilization reduction by firms is widespread, which may have an impact on the value of firms. This study integrates dynamic capability theory and signaling theory to construct a dual-path analytical framework, systematically investigating the impact of water utilization reduction on firm value and its intrinsic mechanisms. Based on data from Chinese A-share listed companies spanning 2012–2023, fixed-effect models, mediation-effect tests, and heterogeneity analysis are employed for empirical verification. The results reveal that water utilization reduction exerts a significant dual-path promoting effect on firm value: it enhances financial performance (ROA) primarily through technological innovation, reflecting the process of resource orchestration and dynamic capability construction; concurrently, it boosts market performance (Tobin’s Q) mainly by improving ESG performance as a signaling channel, mirroring the capital market’s positive pricing of green signals. Further heterogeneity analysis indicates that these effects are more pronounced during the policy deepening stage, in non-water-intensive industries, and in humid/sub-humid regions. This study contributes theoretical support and empirical evidence for firms’ green transformation and the formulation of differentiated water resource policies by the government, highlighting the synergistic development of high-quality economic growth and ecological civilization construction. Full article

Background/objectives: Metabolomics has emerged as a powerful systems-biology tool for deciphering dynamic metabolic alterations occurring during infectious diseases and following vaccination. While genomics and proteomics provide extensive molecular and regulatory information, metabolomics uniquely reflects the biochemical phenotype associated with infection, immune activation, and immunometabolic reprogramming. The objective of this review is to provide an integrated analysis of metabolomics applications across both neglected tropical diseases (NTDs) and non-NTD pathogens, highlighting its dual role in biomarker discovery and vaccine response evaluation. Methods: A comprehensive literature-based synthesis was conducted to examine metabolomic studies in infectious diseases and vaccinology. Metabolic perturbations associated with specific pathogens, as well as vaccine-induced metabolic changes and correlates of immune responses, were systematically analyzed and compared across NTD and non-NTD contexts. Results: Distinct pathogen- and vaccine-associated metabolic signatures were identified, reflecting alterations in glycolysis, amino acid metabolism, lipid remodeling, and immunoregulatory pathways. Comparative analysis revealed both shared and disease-specific metabolic biomarkers across NTDs and non-NTD infections. Importantly, vaccine-related metabolic correlates were shown to mirror immune activation states and, in some cases, predict immunogenicity and response durability. Conclusions: This review bridges metabolomics research in infectious disease pathogenesis and vaccine immunology across the NTD and non-NTD spectrum. By integrating these domains, it introduces the concept of “metabolic immuno-signatures” as predictive and translational tools for evaluating vaccine efficacy and immune response outcomes. Full article

This paper presents Rain-Cloud Condensation Optimizer (RCCO), a nature-inspired metaheuristic that maps cloud microphysics to population-based search. Candidate solutions (“droplets”) evolve under a dual-attractor dynamic toward both a global leader and a rank-weighted cloud core, with time-decaying coefficients that progressively shift emphasis from exploration to exploitation. Diversity is preserved via domain-aware coalescence and opposition-based mirroring sampled within the coordinate-wise band defined by two parents. Rare heavy-tailed “turbulence gusts” (Cauchy perturbations) enable long jumps, while a wrap-and-reflect scheme enforces feasibility near the bounds. A sine-map initializer improves early coverage with negligible overhead. RCCO exposes a small hyperparameter set, and its per-iteration time and memory scale linearly with population size and problem dimension. RCOO has been compared with 21 state-of-the-art optimizers, over the CEC 2022 benchmark suite, where it achieves competitive to superior accuracy and stability, and achieves the top results over eight functions, including in high-dimensional regimes. We further demonstrate constrained, real-world effectiveness on five structural engineering problems—cantilever stepped beam, pressure vessel, planetary gear train, ten-bar planar truss, and three-bar truss. These results suggest that a hydrology-inspired search framework, coupled with simple state-dependent schedules, yields a robust, low-tuning optimizer for black-box, nonconvex problems. Full article

Access to clean cooking remains a major challenge in rural and off-grid areas where traditional fuels are costly, harmful, or scarce. Solar cooking offers a sustainable solution, but many existing systems suffer from fixed positioning and low efficiency. This study presents a low-cost, dual-axis solar tracking parabolic dish cooker designed for such regions, featuring adjustable pot holder height and portability for ease of use. The system uses an Arduino UNO, LDR sensors, and a DC gear motor to automate sun tracking, ensuring optimal alignment throughout the day. A 0.61 m parabolic dish with ≥97% reflective silver-coated mirrors concentrates sunlight to temperatures exceeding 300 °C. Performance tests in April, June, and November showed boiling times as low as 3.37 min in high-irradiance conditions (7.66 kWh/m²/day) and 6.63 min under lower-irradiance conditions (3.86 kWh/m²/day). Compared to fixed or single-axis systems, this design achieved higher thermal efficiency and reliability, even under partially cloudy skies. Built with locally available materials, the system offers an affordable, clean, and effective cooking solution that supports energy access, health, and sustainability in underserved communities. Full article

All-dielectric metasurfaces offer a low-loss alternative to plasmonic metasurfaces. We proposed the configuration for high-reflectivity all-dielectric metasurfaces based on single-crystal diamond (SCD) resonators on fused silica substrate and conducted simulations to optimize and analyze such a configuration via the FDTD solver. We utilized GMR as the design principle to select the configuration and the substrate material, and analyzed the scattering properties of a single SCD resonator by multipole decomposition. Then, we demonstrated that both the cylindrical resonators in square lattice and frustum-shaped resonators in hexagonal lattice can achieve near-unity reflectivity (>99.99%) and ultra-low absorption (<0.001%) at 795 nm, the typical alkali-metal laser wavelength. Additionally, we demonstrated that such a design is quite tolerant of fabrication errors and further supports its potential for realistic applications. To expand the functionality of such devices across multiple wavelengths, dual-band high-reflectivity metasurfaces at 744 nm and 828 nm were also designed. Our work is quite useful for designing diamond-based highly reflective mirrors, paving the way for low-loss all-dielectric reflective metasurfaces in high-power laser applications. Full article

In this paper, a data processing approach was developed to accurately extract the ring-down time and amplitude of the saturated cavity ring-down (CRD) signal; both were utilized to determine simultaneously the high reflectance and residual transmittance of highly reflective (HR) mirrors with a dual-channel CRD configuration. The influence of saturation was eliminated by deleting the beginning saturated data points of the saturated CRD signal and fitting the remaining non-saturated CRD signal to a single-exponential function. By comparing the reflectance/transmittance measurement results of HR samples obtained via data processing of saturated CRD signals and via single-exponentially fitting non-saturated CRD signals with utilization of neutral density filter(s) to eliminate saturation, it was found that the reflectances obtained with both methods were in excellent agreement, while the residual transmittance obtained with the saturated CRD signal was more accurate than that obtained with the neutral-density-filter-attenuated non-saturated CRD signal. The proposed data processing method eliminated the need to use the neutral density filters, therefore avoiding the adding of the optical density error to the uncertainty of residual transmittance measurement and improving the measurement accuracy. The proposed data processing method also extended the dynamic range of the dual-channel CRD scheme for simultaneous measurement of reflectance, transmittance and optical loss. Full article

This study presents a novel simultaneous double-exposure contact mirror-based method for fabricating holographic multi-notch filters with dual operational central wavelengths. The proposed method leverages coupled wave theory, the geometric relationships of K-vectors, and a reflection-type recording setup, incorporating additional reflecting mirrors to guide the recording beams. To validate the approach, a holographic notch filter was fabricated using photopolymer recording materials, resulting in operational wavelengths of 531.13 nm and 633.01 nm. The measured diffraction efficiencies at these wavelengths were η_s = 52.35% and η_p = 52.45% for 531.13 nm, and η_s = 67.30% and η_p = 67.40% for 633.01 nm. The component’s performance was analyzed using s- and p-polarized spectral transmission intensities at various reconstruction angles, revealing polarization-independent characteristics under normal incidence and polarization-dependent behavior under oblique incidence. The study also explored the relationships between recording parameters, such as incident angle, wavelength, emulsion expansion, and dispersion. The findings demonstrate that the first operational central wavelength is primarily influenced by the recording wavelength, while the second is primarily determined by the incident angle, covering a range from visible light to near-infrared. This method offers significant potential for cost-effective, mass-produced filters in optoelectronic applications. Full article

A carbon dioxide (CO₂) gas sensor based on non-dispersive infrared (NDIR) technology has been developed and is suitable for use in portable devices for high-precision CO₂ detection. The NDIR gas sensor comprises a MEMS infrared emitter, a MEMS thermopile detector with an integrated optical filter, and a compact gas cell with high optical coupling efficiency. A dual-ellipsoid mirror optical system was designed, and based on optical simulation analysis, the structure of the dual-ellipsoid reflective gas chamber was designed and optimized, achieving a coupling efficiency of up to 54%. Optical and thermal simulations were conducted to design the sensor structure, considering thermal management and light analysis. By optimizing the gas cell structure and conditioning circuit, we effectively reduced the sensor’s baseline noise, enhancing the overall reliability and stability of the system. The sensor’s dimensions were 20 mm × 10 mm × 4 mm (L × W × H), only 15% of the size of traditional NDIR gas sensors with equivalent detection resolution. The developed sensor offers high sensitivity and low noise, with a sensitivity of 15 μV/ppm, a detection limit of 90 ppm, and a resolution of 30 ppm. The total power consumption of the whole sensor system is 6.5 mW, with a maximum power consumption of only 90 mW. Full article

In this study, we employ a dual-objective optimization model, utilizing the Implicit Modified Coverage Location Problem (MCLP-Implicit) approach, to determine an appropriate fire station allocation. Our objectives encompass maximizing coverage in areas with a heightened projected demand, based on socioeconomic predictors of building fires, and concurrently minimizing the distance of uncovered demand zones to the closest fire station. The challenges of this model reflect the criticality of strategic placement, aiming for not just swift response times but also the complete coverage of a region with priority given to subregions with a pronounced potential for incidents. The applicability of the proposed approach is demonstrated through a case study in south-east Queensland. Our findings indicate that there is a tangible justification for adopting this model. The broader coverage and wider spread of locations it produces can greatly aid in the dynamic deployment of personnel during surges caused by seasonal fluctuations or unforeseen calamities. By weaving in socioeconomic aspects into demand predictions, our model has also maintained appropriate coverage to socioeconomically disadvantaged communities in the region. Nevertheless, it is paramount to underline the recommendation that further research should account for road connectivity—a pivotal factor when pinpointing these locations in the real world. This research paves the way for enriched insights in long-term urban planning and fire response protocol crafting, especially in regions mirroring similar socioeconomic profiles or risks of natural disasters, not to mention its commercial implications to the relevant industry servicing the fire and rescue authorities. Full article

Augmented reality heads-up displays (AR-HUDs) have a much richer display than traditional heads-up displays. An ideal AR-HUD requires two or more focal planes to display basic and interactive driving information to the car driver separately. We present an off-axis reflective optical structure for dual-focal-plane displays using a single projection-type picture generation unit (PGU) and two freeform mirrors. The dual-focal-plane AR-HUD system designed in this paper can simultaneously generate high-quality far-field image (13° × 4°, 10 m) and near-field images (13° × 1.4°, 3.5 m) in a 130 mm × 60 mm eyebox. A fully automated analysis program is written to analyze the modulation transfer function (MTF) and distortion values of the optical system over the entire eyebox range. The analysis results show that the maximum distortion values of the far-field image and near-field image in the eyebox range are 3.15% and 3.58%, respectively. The MTF was greater than 0.3 at 7.2 lp/mm for both near-field images and far-field images. We also designed a projection lens for the projection-type PGU used in this system. The projection lens uses three plane mirrors to fold the image plane of the projection system into different positions to serve as the image source for the AR-HUD. This research provides a new solution for realizing the dual-focal-plane AR-HUD, which not only satisfies the need for simultaneous display of near-field basic information and far-field interactive information, but also has a larger display screen. Full article

This paper presents a novel sensor for the detection and characterization of regions of air turbulence. As part of the ground truth process, it consists of a combined Schlieren imager and a Radar Acoustic Sounding System (RASS) to produce dual-modality “images” of air movement within the measurement volume. The ultrasound-modulated Schlieren imager consists of a strobed point light source, parabolic mirror, light block, and camera, which are controlled by two laptops. It provides a fine-scale projection of the acoustic pulse-modulated air turbulence through the measurement volume. The narrow beam 40 kHz/17 GHz RASS produces spectra based on Bragg-enhanced Doppler radar reflections from the acoustic pulse as it travels. Tests using artificially generated air vortices showed some disruption of the Schlieren image and of the RASS spectrogram. This should allow the higher-resolution Schlieren images to identify the turbulence mechanisms that are disrupting the RASS spectra. The objective of this combined sensor is to have the Schlieren component inform the interpretation of RASS spectra to allow the latter to be used as a stand-alone sensor on a UAV. Full article

Augustine of Hippo’s early works distinguish between the earthly human person, driven by worldly desires, and the reborn person, oriented towards heaven. Later, in his monumental De ciuitate Dei (On the City of God), Augustine expands on this distinction, proposing the existence of two cities: the earthly city, characterized by the love of self; and the city of God, characterized by the love of God. This tension between the two loves shapes human understanding of and place in the world. This article explores how the said tension reflects a duality in human nature, tracing the development of the relationship between Augustine’s doctrine of the two cities and his reflections on the dual human nature from his early works to De ciuitate Dei. The article studies whether the duality of human nature mirrors the dichotomy between the ciuitas Dei (city of God) and the ciuitas terrena (earthly city), examining how the conflict between good and evil within individuals and society serves as a model for the conflict between the two cities in Augustine’s doctrine, with a focus on how these concepts are expounded in his earlier writings and articulated in his De ciuitate Dei. It examines how the interaction between these loves manifests in human actions and desires, and shapes our understanding of the good and desirable. Ultimately, this article seeks to address the question of whether the tension between the love of God and the love of self, both in society and in human nature, is capable of harmonious resolution in Augustine’s mindset. Full article

To improve the detection sensitivity of a porous silicon optical biosensor in the real-time detection of biomolecules, a non-spectral porous silicon optical biosensor technology, based on dual-signal light detection, is proposed. Double-light detection is a combination of refractive index change detection and fluorescence change detection. It uses quantum dots to label probe molecules to detect target molecules. In the double-signal-light detection method, the first detection-signal light is the detection light that is reflected from the surface of the porous silicon Bragg mirror. The wavelength of the detection light is the same as the wavelength of the photonic band gap edge of the porous silicon Bragg mirror. CdSe/ZnS quantum dots are used to label the probe DNA and hybridize it with the target DNA molecules in the pores of porous silicon to improve its effective refractive index and enhance the detection-reflection light. The second detection-signal light is fluorescence, which is generated by the quantum dots in the reactant that are excited by light of a certain wavelength. The Bragg mirror structure further enhances the fluorescence signal. A digital microscope is used to simultaneously receive the digital image of two kinds of signal light superimposed on the surface of porous silicon, and the corresponding algorithm is used to calculate the change in the average grey value before and after the hybridization reaction to calculate the concentration of the DNA molecules. The detection limit of the DNA molecules was 0.42 pM. This method can not only detect target DNA by hybridization, but also detect antigen by immune reaction or parallel biochip detection for a porous silicon biosensor. Full article