Search Results (69)

The accurate identification of wood patterns is critical for optimizing the use of sustainable wood building materials, promoting resource efficiency, and reducing waste in construction. This study presents a deep learning-based approach for enhanced wood material recognition, combining EfficientNet architecture with advanced data augmentation techniques to achieve robust classification. The augmentation strategy incorporates geometric transformations (flips, shifts, and rotations) and photometric adjustments (brightness and contrast) to improve dataset diversity while preserving discriminative wood grain features. Validation was performed using a controlled augmentation pipeline to ensure realistic performance assessment. Experimental results demonstrate the model’s effectiveness, achieving 88.9% accuracy (eight out of nine correct predictions), with further improvements from targeted image preprocessing. The approach provides valuable support for preliminary sustainable building material classification, and can be deployed through user-friendly interfaces without requiring specialized AI expertise. The system retains critical wood pattern characteristics while enhancing adaptability to real-world variability, supporting reliable material classification in sustainable construction. This study highlights the potential of integrating optimized neural networks with tailored preprocessing to advance AI-driven sustainability in building material recognition, contributing to circular economy practices and resource-efficient construction. Full article

OT 355 (4FGL J1734.3 + 3858) is a relatively rarely studied but highly variable, moderate-redshift (z = 0.975) flat-spectrum radio quasar (blazar). With this work, we aim to study its optical variability on different timescales, which can help us to better understand the physical processes in relativistic jets operating in blazar-type active galactic nuclei. OT 355 was observed in four colors (BVRI) during 41 nights between 2017 and 2023 using three 1 and 2 m class telescopes. The object was also monitored on intra-night timescales, for about 100 h in total. In addition, secondary standard stars in the field of OT 355 were calibrated in order to facilitate future photometric studies. We detected significant intra-night and night-to-night variations of up to 0.5 mag. Variability characteristics, color changes, and a possible “rms-flux” relation were studied and discussed. Using simple arguments, we show that a negative “rms-flux” relation should be expected if many independent processes/regions drive the short-term variability via Doppler factor changes, which is not observed in this and other cases. This finding raises arguments for the idea that more complex multiplicative processes are responsible for blazar variability. Studying blazar variability, especially on the shortest possible timescales, can help to estimate the strength and geometry of their magnetic fields, the linear sizes of the emitting regions, and other aspects, which may be of importance for constraining and modeling blazars’ emitting mechanisms. Full article

Micromixing is a crucial process in microfluidic systems. In biochemical and chemical analysis, the sample is usually tested with reagents. These solutions must be well mixed for the reaction to be possible, generally using micromixers manufactured with sophisticated and expensive technology. The present work shows the design and evaluation of micromixers fabricated with LTCC (low-temperature co-fired ceramics) and FDM (fused deposition modeling) technologies for the development of functional and complex geometries. Two-dimensional planar serpentine and 3D chaotic convection serpentine micromixers were manufactured and implemented in an automated microanalytical system using photometric methods. To evaluate the performance of the micromixers, flow, mixing and absorbance measurements were carried out. Green tape and PP materials were used and showed good resistance to the acidic chemical solutions. The devices presented achieved mixing times in seconds, a reduced dispersion due to their aspect ratio, high sensitivity, and precision in photometric measurement. The optical sensing cells stored sample volumes in a range of 10 to 600 µL, which allowed the reduction of reagent consumption and waste generation. These are ideal characteristics for in situ measurement, portable, and low-cost applications focused on green chemistry and biochemistry. Full article

This paper presents the results of the photometric and spectral monitoring of the galaxy NGC 3516, which is an active galactic nucleus (AGN) of type Sy $1.5$ with a changing look. Observations were carried out at the Fesenkov Astrophysical Institute (FAI, Almaty, Kazakhstan) and the Shamakhy Astrophysical Observatory (ShAO, Shamakhy, Azerbaijan). Spectral monitoring of this galaxy in the wavelength range 4000–7000 Å began in 2020, while photometric observations have been conducted since 2014. During the observation period, estimates of the galaxy’s brightness in the B, V and $Rc$ filters were obtained, as well as measurements of the emission line and continuum fluxes. The light curve shows increased brightness of NGC 3516 in 2016 and 2019. The increase of emission line fluxes of H$\beta$ and H$\alpha$ and continuum began in 2019 and continued until spring 2020, when these characteristics reached their maximal values. A powerful X-ray flare took place on 1 April 2020. A new phase of brightening began in 2021 and has continued until 2025. After reaching their maxima in 2020, the emission fluxes of H$\beta$ and H$\alpha$ decreased by a factor of 1.5–2 and remained at a low level until 2022–2023, when they began to increase again. Medium-resolution spectra obtained on 20 April 2020, with the 1-meter “West” telescope (TSHAO) were used to study the broad components of the H$\beta$ and H$\alpha$ emission line profiles. Model calculations showed that the broad profile of the H$\alpha$ line consists of a central unshifted component and two (blue and red) components shifted symmetrically relative to the central component by a velocity of $v=980\pm 20$ km ${\mathrm{s}}^{-1}$. The H$\beta$ emission line was relatively weak, so the radial velocity of its components was determined with a large uncertainty: $900\pm 600$ km ${\mathrm{s}}^{-1}$. Full article

Decoding the aroma composition plays a key role in designing and producing foods that consumers prefer. Due to the complex matrix and diverse aroma compounds of foods, isolation and quantitative analytical methods were systematically reviewed. Selecting suitable and complementary aroma extraction methods based on their characteristics can provide more complete aroma composition information. Multiple mass spectrometry detectors (MS, MS/MS, TOF-MS, IMS) and specialized detectors, including flame ionization detector (FID), electron capture detector (ECD), nitrogen–phosphorus detector (NPD), and flame photometric detector (FPD), are the most important qualitative technologies in aroma identification and quantification. Furthermore, the real-time monitoring of aroma release and perception is an important developing trend in the aroma perception of future food. A combination of artificial intelligence for chromatographic analysis and characteristic databases could significantly improve the qualitative analysis efficiency and accuracy of aroma analysis. External standard method and stable isotope dilution analysis were the most popular quantification methods among the four quantification methods. The combination with flavoromics enables the decoding of aroma profile contributions and the identification of characteristic marker aroma compounds. Aroma analysis has a wide range of applications in the fields of raw materials selection, food processing monitoring, and products quality control. Full article

We present the results of photometric and spectroscopic observations of a poorly studied B-type supergiant with infrared excess, the hot post-AGB star IRAS 21546+4721. Based on our photometric observations in the $UBV{R}_C{I}_C$ bands, we detected rapid, night-to-night, non-periodic brightness variations in the star with peak-to-peak amplitudes up to $0{.}^{m}3$ in the V band, as well as color–color and color–brightness correlations. Based on its variability characteristics, IRAS 21546+4721 appears similar to other hot post-AGB stars. Possible causes of the photometric variability are discussed. Additionally, we acquired low-resolution spectra in a wavelength range from 3500 to 7500 Å. The spectrum contains absorption lines typical of an early B-type star, along with a set of emission lines of H I, He I, [O I], [O II], [N II], [S II], and C II originating from an ionized circumstellar envelope. An analysis of the emission spectrum allowed us to estimate the parameters of the gas envelope ($N_e$∼ 10⁴ cm⁻³, $T_e$∼ 10,000 K) and the star’s temperature (∼26,500 K). The radial velocity measured from the emission lines was $V_r=-141\pm 7$ km s⁻¹. Full article

In recent years, the rapid advancement and pervasive deployment of unmanned aerial vehicle (UAV) technology have catalyzed transformative applications across the military, civilian, and scientific domains. While aerial imaging has emerged as a pivotal tool in modern remote sensing systems, persistent challenges remain in achieving robust small-target detection under complex all-weather conditions. This paper presents an innovative multimodal fusion framework incorporating photometric perception and cross-attention mechanisms to address the critical limitations of current single-modality detection systems, particularly their susceptibility to reduced accuracy and elevated false-negative rates in adverse environmental conditions. Our architecture introduces three novel components: (1) a bidirectional hierarchical feature extraction network that enables the synergistic processing of heterogeneous sensor data; (2) a cross-modality attention mechanism that dynamically establishes inter-modal feature correlations through learnable attention weights; (3) an adaptive photometric weighting fusion module that implements spectral characteristic-aware feature recalibration. The proposed system achieves multimodal complementarity through two-phase integration: first by establishing cross-modal feature correspondences through attention-guided feature alignment, then performing weighted fusion based on photometric reliability assessment. Comprehensive experiments demonstrate that our framework achieves an improvement of at least 3.6% in mAP compared to the other models on the challenging LLVIP dataset, and with particular improvements in detection reliability on the KAIST dataset. This research advances the state of the art in aerial target detection by providing a principled approach for multimodal sensor fusion, with significant implications for surveillance, disaster response, and precision agriculture applications. Full article

Be stars are rapidly rotating B-type stars surrounded by circumstellar disks formed from self-ejected material. Understanding the mechanisms driving mass ejection and disk formation, known as the Be phenomenon, requires a detailed investigation of their variability and underlying physical processes. In this study, we analyze the photometric, spectroscopic, and seismic characteristics of three Be stars—HD 212044, 28 Cyg, and HD 174237—using high-cadence data from the TESS mission and spectral data from the BeSS database. Photometric variability was analyzed through iterative prewhitening and wavelet techniques, revealing distinct frequency groups associated with non-radial pulsations (NRPs). Spectral data provided equivalent width measurements of the H$\alpha$ line, which correlated with photometric changes, reflecting dynamic interactions between the stars and their disks. Seismic analysis identified core rotation rates and buoyancy travel times for HD 212044 and 28 Cyg, offering insights into internal stellar processes and angular momentum distribution. HD 212044 exhibits a strong negative correlation between photometric brightness and H$\alpha$ equivalent width, whereas this correlation is weaker in the case of 28 Cyg. The findings for these two stars highlight the interplay between NRPs, rapid rotation, and circumstellar disk dynamics. In contrast, the case of HD 174237 presents an example of how a binary system with mass transfer and a B-type component is revealed when observed simultaneously with space-based photometry and ground-based spectroscopy, demonstrating the importance of distinguishing classical Be stars from interacting binaries. Full article

Background/Objectives: This work introduces accuracy- and precision-ROC curves in addition to SS– and PV–ROC curves and shows a novel means of profiling biomarker characteristics for validation of optimal cutoffs in clinical diagnostics and decision making. Methods: This investigation included 91 patients with a confirmed bladder cancer diagnosis and 1152 patients without evidence of cancer. The study performed a quantitative investigation of used-up test cassettes from the visual UBC^® Rapid qualitative point-of-care assay, which had already been applied in routine diagnostics. Using a photometric reader, quantitative data could also be obtained from the test line of the used cassettes. The ROC curves were constructed using different thresholds or cutoff levels to determine the TP/TN and FP/FN values for each threshold at concentrations of 5, 10, 30, 50, 90, 110, 250 and 300 µg/L. The resulting TP/TN and FP/FN values were used to calculate the sensitivity/specificity, accuracy, precision and predictive values in order to plot the ROC curves with integrated cutoff value distributions and their index cutoff diagrams. Results: A common, optimal cutoff value for all the diagnostic parameters was derived with the aid of an ROC index cutoff diagram. It includes higher specificity and an acceptable number of NPVs. As a result, use of a sensitivity–specificity ROC curve and the Youden index only permits the selection of a maximal threshold value or cutoff point for the biomarker of interest but disregards the clinical status of the patient, whereas the precision, accuracy and predictive values give information related to the disease. Conclusions: This work’s novelty compared to the existing methodology includes the first international publication of accuracy- and precision-ROC curves. It enables the investigation of the relationship among the sensitivity, specificity, precision, accuracy and predictive values at varied cutoff levels within a bioassay, presenting these in a single graph consisting of selected receiver operating characteristic (ROC) curves for each parameter, including cutoff distribution curves. This is a transparent method to identify appropriate cutoffs for multiple diagnostic parameters. According to the results, the single-sided use of a sensitivity–specificity ROC curve including the maximal Youden index value as an optimal cutoff or single-point determinations for predictive values cannot provide diagnostic information of the same quality as that given by a multi-parameter diagnostic profile and a multi-parameter cutoff-index-diagram-derived optimal value as presented within this work. The proposed multi-parameter cutoff-index diagram includes novel index cutoff AOX. It is a new different method that allows a quantitative comparison of the results from multi-parameter ROC curves, which cannot be performed with the AUC. However, the methods are different and do not exclude each other. Full article

The asymptotic giant branch (AGB) phase, experienced by low- and intermediate-mass stars (LIMSs), plays a crucial role in galaxies due to its significant dust production. Planetary nebulae (PNe) offer a novel perspective, providing valuable insights into the dust production mechanisms and the evolutionary history of LIMSs. We selected a sample of nine PNe from the Large Magellanic Cloud (LMC), likely originating from single stars. By modeling their spectral energy distributions (SEDs) with photoionization techniques, we successfully reproduced the observed photometric data, spectra, and chemical abundances. This approach enabled us to constrain key characteristics of the central stars (CSs), dust, and gaseous nebulae, which were then compared with predictions from stellar evolution models. By integrating observational data across ultraviolet (UV) to infrared (IR) wavelengths, we achieved a comprehensive understanding of the structure of the PNe in our sample. The results of the SED analysis are consistent with evolutionary models and previous studies that focus on individual components of the PN, such as dust or the gaseous nebula. Our analysis enabled us to determine the metallicity, the progenitor mass of the CSs, and the amount of dust and gas surrounding the CSs, linking these properties to the previous AGB phase. The PN phase provides critical insights into the physical processes active during earlier evolutionary stages. Additionally, we found that higher progenitor masses are associated with greater amounts of dust in the surrounding nebulae but lower amounts of gaseous material compared to sources with lower progenitor masses. Full article

It was shown earlier that the use of fast protein and metabolites liquid chromatography (FPMLC) and low-cost deep UV–LED-based optical chromatographic sensors with PD-10 desalting columns as a separation element can facilitate the monitoring of patients on chronic peritoneal dialysis (PD). Previously, we established that the first peak in the FPMLC chromatograms of effluent dialysate is mainly responsible for proteins and could be used for the assessment of peritoneal protein loss in patients on PD, while the origin and clinical significance of the other two peaks still remain unclear. Optical absorption and fluorescence spectroscopy in the UV and visible regions of 240…720 nm were used for the analysis of PD effluent chromatographic fractions collected from a drainpipe of the sensor with photometric detection at 280 nm; chromatograms of twenty dialysate samples were processed. The absorption and fluorescence spectra of the first fraction demonstrated peaks at 270 nm and 330 nm, respectively, which is typical for proteins. The absorption spectra of the third fraction revealed the characteristic maxima of creatinine and uric acid, while the fluorescence spectra showed the characteristic peak of indoxyl sulfate 375 nm at 270 nm excitation. The second fraction had a single, extremely wide absorption band, strong fluorescence was observed at 440–450 nm while excited at 370 nm. Such spectral characteristics are typical for advanced glycation end products (AGE). Thus, it was demonstrated that deep UV–LED-based affordable chromatographic sensors could provide significantly more information about the composition of PD effluent dialysate than just the total protein concentration, including the contents of clinically significant metabolites, e.g., indoxyl sulfate and AGE. Moreover, the introduction of optical fluorescence detection could significantly improve the capabilities of such devices. Full article

Luminance is the fundamental photometric quantity representing the technical meaning of brightness. It is usually measured from a distance using a matrix sensor, which is the basis of the professional instrument. However, specific technical requirements must be fulfilled to achieve accurate results. This paper considers whether modern high-resolution smartphone cameras are suitable for luminance measurements. Three cameras from high-end smartphones were evaluated on a dedicated laboratory stand. The sensors’ output characteristics showed relatively good linearity of the individual R, G, and B channels. Unfortunately, the spectral sensitivities were unfavorable, as the minimum error achieved was about 17%. This device is classified outside the generally accepted quality scale for photometric instruments. The presented investigation confirmed that none of the high-resolution smartphone cameras tested was suitable for use as a universal luminance camera. However, one of the test devices can be developmental if restrictively calibrated and used only in a specialistic laboratory stand. Using a smartphone (or only its camera) for luminance measurements requires proper advanced calibration. It is possible, but it limits us to only dedicated applications. The pilot study presented in this paper will help create a suitable test stand for spectacle vision systems, e.g., virtual reality equipment. Full article

Due to the existence of low-textured areas in indoor scenes, some self-supervised depth estimation methods have specifically designed sparse photometric consistency losses and geometry-based losses. However, some of the loss terms cannot supervise all the pixels, which limits the performance of these methods. Some approaches introduce an additional optical flow network to provide dense correspondences supervision, but overload the loss function. In this paper, we propose to perform depth self-propagation based on feature self-similarities, where high-accuracy depths are propagated from supervised pixels to unsupervised ones. The enhanced self-supervised indoor monocular depth estimation network is called SPDepth. Since depth self-similarities are significant in a local range, a local window self-attention module is embedded at the end of the network to propagate depths in a window. The depth of a pixel is weighted using the feature correlation scores with other pixels in the same window. The effectiveness of self-propagation mechanism is demonstrated in the experiments on the NYU Depth V2 dataset. The root-mean-squared error of SPDepth is 0.585 and the δ₁ accuracy is 77.6%. Zero-shot generalization studies are also conducted on the 7-Scenes dataset and provide a more comprehensive analysis about the application characteristics of SPDepth. Full article

A lightscape, as a special visual landscape, has unique temporal and spatial characteristics that traditional photometric measurements and descriptions struggle to capture accurately. Despite their significance, there is a lack of in-depth understanding of the on-site perception of lightscapes’ temporal and spatial characteristics, including in outdoor university campus spaces. This study aims to explore the temporal and spatial characteristics of outdoor lightscapes on university campuses and their potential perceptual influencing factors, providing sustainable design, planning, and management suggestions for campus lightscapes. This study was conducted in the Wushan Campus of the South China University of Technology. It employs a “lightwalk” method for on-site perception evaluation, combining qualitative and quantitative approaches to investigate the temporal and spatial characteristics of lightscapes in outdoor university campus spaces and the effect of temporal and spatial factors on lightscape perception. The main findings are as follows: (1) Meteorological, architectural, and biophilic lightscape dominate the outdoor campus lightscapes. (2) The temporal and spatial characteristics of the lightscapes are affected by changes in natural light, the transition of light sources from day to night, human activity patterns, and the functional characteristics of the site. (3) The correlation between meteorological and traffic lightscape types and lightscape perception is diminished during the evening periods. This method should be a good way to optimize water and architectural lightscape at night to alleviate discomfort. (4) In green-shaded spaces, the association between meteorological, architectural, and traffic lightscape types and the evaluations of emotional, luminous, and eventful aspects is significantly enhanced, suggesting an increase in such spaces to improve lightscape experience quality. This study advocates that the construction of buildings and environments should be “human-oriented”, paying attention to the scientific foundation that humans perceive the habitat environment through the “five senses”. Research on lightscapes’ temporal and spatial characteristics, exploration of the temporal and spatial modes of lightscape perception, and avoiding energy waste and light pollution are conducive to the design and construction of university campuses in line with the principles of sustainable development. The lightscape optimization strategies derived from this study can not only provide practical guidance for the design and management of campus but also may offer valuable recommendations for planning sustainable campus development. Full article

China’s Chang’E-5 (CE-5) mission has successfully landed in the Northern Oceanus Procellarum of the Moon. Lunar mineralogical spectrometer (LMS), as one of the important payloads onboard CE-5 Lander–Ascender Combination, aims to study the physical and compositional properties of the landing area. This paper applies the Legendre phase function to correct the photometric effects on the LMS in situ spectra and reveal the photometric characteristic of the CE-5 landing area. LMS obtained the reflectance spectra in various geometric configurations by performing full-view scanning of the CE-5 landing area. By fitting these LMS spectral data, the parameters $b=-0.29$ and $c=0.44$ of the Legendre phase function were obtained. This indicates the strong forward scattering characteristic of the CE-5 landing area, which is similar to that of the Chang’E-4 (CE-4) landing area, and the side scattering is weaker than that of CE-4. In addition, we derived the FeO content of the landing area using the photometric-corrected LMS spectral data. Our results demonstrate that the estimated FeO content of the landing area is close to the laboratory measured data of the returned samples. The LMS in situ reflectance data will contribute to a better understanding of the physical and mineralogical properties of the CE-5 landing area. Full article