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Significance: In laser therapy and diagnosis of skin diseases, the irradiated light distribution, which is determined by the absorption coefficient μa and reduced scattering coefficient μs′ of the epidermis, dermis, and subcutaneous fat, affects the treatment outcome and diagnosis accuracy. Although values for μa and μs′ have been reported, detailed analysis for Asian skin tissues is still lacking. Aim: We present μa and μs′ measurements of Asian skin tissues in the 400- to 1100-nm wavelength range for evaluating optical penetration depth and energy deposition. Approach: The measurements with Asian human skin samples are performed employing a double integrating sphere spectrometric system and an inverse Monte Carlo technique. Using the measured parameters, the optical penetration depth and energy deposition are quantitatively analyzed. Results: The μa of the epidermis layer varies among different ethnic groups, while the μa of the other layers and the μs′ of all of the layers exhibit almost no differences. The analysis reveals that the optical penetration depth and the energy deposition affect the photodynamic therapy treatment depth and the heat production in skin tissue, respectively. Conclusions: The experimentally measured values of μa and μs′ for Asian skin tissues are presented, and the light behavior in Asian skin tissues is analyzed using a layered tissue model.

Significance: The polymer, polydimethylsiloxane (PDMS), has been increasingly used to make tissue simulating phantoms due to its excellent processability, durability, flexibility, and limited tunability of optical, mechanical, and thermal properties. We report on a robust technique to fabricate PDMS-based tissue-mimicking phantoms where the broad range of scattering and absorption properties are independently adjustable in the visible- to near-infrared wavelength range from 500 to 850 nm. We also report on an analysis method to concisely quantify the phantoms’ broadband characteristics with four parameters. Aim: We report on techniques to manufacture and characterize solid tissue-mimicking phantoms of PDMS polymers. Tunability of the absorption (μa  (  λ  )  ) and reduced scattering coefficient spectra (μs′(λ)) in the wavelength range of 500 to 850 nm is demonstrated by adjusting the concentrations of light absorbing carbon black powder (CBP) and light scattering titanium dioxide powder (TDP) added into the PDMS base material. Approach: The μa  (  λ  )   and μs′(λ) of the phantoms were obtained through measurements with a broadband integrating sphere system and by applying an inverse adding doubling algorithm. Analyses of μa  (  λ  )   and μs′(λ) of the phantoms, by fitting them to linear and power law functions, respectively, demonstrate that independent control of μa  (  λ  )   and μs′(λ) is possible by systematically varying the concentrations of CBP and TDP. Results: Our technique quantifies the phantoms with four simple fitting parameters enabling a concise tabulation of their broadband optical properties as well as comparisons to the optical properties of biological tissues. We demonstrate that, to a limited extent, the scattering properties of our phantoms mimic those of human tissues of various types. A possible way to overcome this limitation is demonstrated with phantoms that incorporate polystyrene microbead scatterers. Conclusions: Our manufacturing and analysis techniques may further promote the application of PDMS-based tissue-mimicking phantoms and may enable robust quality control and quality checks of the phantoms.

The scattering and backscattering enhancement factors (f(RH) and fb(RH)) describe how aerosol particle light scattering and backscattering, respectively, change with relative humidity (RH). They are important parameters in estimating direct aerosol radiative forcing (DARF). In this study we use the dataset presented in Burgos et al. (2019) that compiles f(RH) and fb(RH) measurements at three wavelengths (i.e., 450, 550 and 700 nm) performed with tandem nephelometer systems at multiple sites around the world. We present an overview of f(RH) and fb(RH) based on both long-term and campaign observations from 23 sites representing a range of aerosol types. The scattering enhancement shows a strong variability from site to site, with no clear pattern with respect to the total scattering coefficient. In general, higher f(RH) is observed at Arctic and marine sites, while lower values are found at urban and desert sites, although a consistent pattern as a function of site type is not observed. The backscattering enhancement fb(RH) is consistently lower than f(RH) at all sites, with the difference between f(RH) and fb(RH) increasing for aerosol with higher f(RH). This is consistent with Mie theory, which predicts higher enhancement of the light scattering in the forward than in the backward direction as the particle takes up water. Our results show that the scattering enhancement is higher for PM1 than PM10 at most sites, which is also supported by theory due to the change in scattering efficiency with the size parameter that relates particle size and the wavelength of incident light. At marine-influenced sites this difference is enhanced when coarse particles (likely sea salt) predominate. For most sites, f(RH) is observed to increase with increasing wavelength, except at sites with a known dust influence where the spectral dependence of f(RH) is found to be low or even exhibit the opposite pattern. The impact of RH on aerosol properties used to calculate radiative forcing (e.g., single-scattering albedo, ω0, and backscattered fraction, b) is evaluated. The single-scattering albedo generally increases with RH, while b decreases. The net effect of aerosol hygroscopicity on radiative forcing efficiency (RFE) is an increase in the absolute forcing effect (negative sign) by a factor of up to 4 at RH = 90 % compared to dry conditions (RH < 40 %). Because of the scarcity of scattering enhancement measurements, an attempt was made to use other more commonly available aerosol parameters (i.e., ω0 and scattering Ångström exponent, αsp) to parameterize f(RH). The majority of sites (75 %) showed a consistent trend with ω0 (higher f(RH = 85 %) for higher ω0), while no clear pattern was observed between f(RH = 85 %) and αsp. This suggests that aerosol ω0 is more promising than αsp as a surrogate for the scattering enhancement factor, although neither parameter is ideal. Nonetheless, the qualitative relationship observed between ω0 and f(RH) could serve as a constraint on global model simulations.

The prediction and modeling of sound propagation rely heavily on accurate representations of surface scattering. Traditional scattering coefficients, often based on random-incidence assumptions, fail to capture the directional dependence of sound reflections from rough surfaces. This paper introduces a methodology for determining and representing bidirectional surface scattering coefficients, moving beyond the limitations of existing Lambertian-based approaches. We propose a framework that leverages numerical simulations and physical measurements to compute bidirectional scattering coefficients from reflected sound pressure distributions with finite-size samples. The methodology is validated using a well-documented sinusoidal test surface, comparing our results with analytical solutions for infinite-size samples and former random-incidence scattering coefficient measurements. Additionally, we propose a data storage format compatible with the Spatially Oriented Format for Acoustics (SOFA) to facilitate the integration of bidirectional scattering coefficients into sound propagation models. This work provides a foundation for improved acoustic simulations in applications ranging from room acoustics to urban noise control.

Continuous wave near infrared spectroscopy (CW-NIRS) is widely exploited in clinics to estimate skeletal muscles and brain cortex oxygenation. Spatially resolved spectroscopy (SRS) is generally implemented in commercial devices. However, SRS suffers from two main limitations: the assumption on the spectral dependence of the reduced scattering coefficient [ ] and the modeling of tissue as homogeneous. We studied the accuracy and robustness of SRS NIRS. We investigated the errors in retrieving hemodynamic parameters, in particular tissue oxygen saturation ( ), when was varied from expected values, and when layered tissue was considered. We simulated hemodynamic variations mimicking real-life scenarios for skeletal muscles. Simulations were performed by exploiting the analytical solutions of the photon diffusion equation in different geometries: (1) semi-infinite homogeneous medium and constant ; (2) semi-infinite homogeneous medium and linear changes in ; (3) two-layered media with a superficial thickness , 7.5, 10 mm and constant . All simulated data were obtained at source-detector distances , 40, 45 mm, and analyzed with the SRS approach to derive hemodynamic parameters (concentration of oxygenated and deoxygenated hemoglobin, total hemoglobin concentration, and tissue oxygen saturation, ) and their relative error. Variations in affect the estimated (up to ), especially if changes are different at the two wavelengths. However, the main limitation of the SRS method is the presence of a superficial layer: errors strongly larger than 20% were retrieved for the estimated when the superficial thickness exceeds 5 mm. These results highlight the need for more sophisticated strategies (e.g., the use of multiple short and long distances) to reduce the influence of superficial tissues in retrieving hemodynamic parameters and warn the SRS users to be aware of the intrinsic limitation of this approach, particularly when exploited in the clinical environment.

Most conventional dehazing methods obtain quality results by solving atmospheric scattering model (ASM) using acquired variables (i.e., global atmospheric light and transmission map). Prior-based strategies have made significant achievements in this task. Nonetheless, they usually obtain unrealistic dehazed images since strong assumptions can barely suit all circumstances. In this paper, we propose a novel image dehazing method with adaptive scattering coefficients to realize visual-friendly and quality-orientated restoration. Specifically, a regional rank-based technique is applied to find the most likely atmospheric light candidate. And then, different from previous image dehazing methods that rely on haze-relevant priors to estimate a transmission map, we develop an image quality-aware approach, together with a dynamic scattering coefficient. In this phase, an optimization function constrained by the image quality-aware indicators is designed to compute the scattering coefficient or transmission. The Fibonacci algorithm is further employed to solve this optimization problem. The proposed method produces high-quality results and exhibits favorable quantitative and qualitative performance compared to related methods.

The reduced scattering coefficient (μs′), measured using time-resolved near-infrared spectroscopy (TR-NIRS) has been linked to brain water diffusion assessed by diffusion tensor imaging, suggesting its potential as a bedside marker of cerebral microstructure. However, the physiological determinants of μs′ and its early postnatal changes remain unclear. This study examined clinical associations with cerebral μs′ in healthy term newborn infants during the first 2 postnatal days. Eighteen newborn infants underwent TR-NIRS at 6 and 36 h postnatally. Associations between μs′ and 14 clinical variables were analysed using generalised estimating equations. Median μs′ was 7.395 cm−1 (IQR: 6.140–8.159) at 6 h and 7.112 cm−1 (IQR: 6.473–7.410) at 36 h, with no significant difference (p = 0.327). Male sex was associated with higher μs′ (regression coefficient = 0.895, p = 0.007), whereas caesarean delivery (regression coefficient = −0.969, p = 0.012) was associated with lower μs′. A significant interaction between caesarean delivery and postnatal age indicated that the negative effect diminished between 6 and 36 h after birth (difference = 0.057, p = 0.016). These findings suggest delivery mode transiently influences brain scattering, whereas the effect of sex remains stable, supporting further investigation of TR-NIRS as an acute-phase cerebral marker.

Measurements of inherent optical properties (IOPs) and characteristics of concentration and composition of suspended particles were made on original and size-fractionated surface water samples from Arctic fjords and coastal waters of western Spitsbergen in the Svalbard archipelago, in the summer months of 2021 and 2022. Optical measurements included the spectral scattering coefficient of particles, and spectral absorption coefficients of particles as well as depigmented (non-algal) particles and phytoplankton. Assemblages of suspended particles were characterised by measuring the mass concentrations of suspended particulate matter (SPM), particulate organic matter (POM), particulate inorganic matter (PIM), and phytoplankton pigments including chlorophyll a (Chla). All measurements were performed on original (unfiltered) seawater and on size-fractionated samples obtained by filtration using a combination of nylon meshes and membrane filters. This allowed us to determine the contribution of the fractions of very small (VS), small (S) and combined medium and large particles (ML) to the total SPM and Chla, as well as to the total scattering and absorption coefficients. The obtained results: (i) indirectly indicate a clear variability in particle size distributions occurring in the studied marine environment (e.g., the contribution of ML size fraction to SPM (the ratio SPMML/SPM) varied between 0.10 and 0.52); (ii) indicate noticeable differences in composition between size fractions (e.g., the POM/SPM ratio was on average 0.21 for the S fraction, and 0.34 and 0.32 for the VS and ML fractions, respectively); (iii) in most cases indicate that the fraction S had the largest contribution to all analysed spectral optical coefficients, followed by the VS and ML fractions (the average contributions of the S fraction to scattering coefficient of particles and absorption coefficient of particles or depigmented (non-algal) particles were above 0.6 in the entire analysed spectral ranges); (iv) allowed for the identification of statistical relationships between selected characteristics describing changes in particle size and variability of particle IOPs (e.g., we observed statistical relations between SPMML/SPM and the spectral slope of scattering coefficient by particles, as well as SPM-specific coefficients of scattering by particles).

A secondary reconstruction technique based on multi-section reconstruction is proposed to simultaneously reconstruct the space-dependent absorption coefficient, scattering coefficient, and thermal conductivity fields without any priori information in the participating medium. In the forward model, the finite volume method (FVM) is used to solve the coupled radiative–conductive problem. The radiative and temperature signals on one side of the medium boundary induced by laser irradiation heating are served as input measurements for the inverse analysis. In the inverse model, the sequential quadratic programming (SQP) algorithm is employed to solve the optimization problems. By this technique, more measurement signals can be obtained, which is necessary for exactly reconstructing the space-dependent optical and thermophysical parameters fields. All the retrieval results show that the proposed secondary reconstruction technique based on multi-section reconstruction can be adopted to reconstruct the complex space-dependent absorption coefficient, scattering coefficient, and thermal conductivity fields accurately and efficiently. This proposed technique will play an important role in practical application, such as non-destructive testing of materials, biology imaging in clinical medicine and optimization and design of composites.

Complex-terrain clutter presents serious nonuniformity, which has a significant impact on radar target detection, communication, and navigation. The accurate acquisition of the clutter characteristics by measurement or calculation for large and complex terrains has always posed a challenge due to the high costs of the measurement, as well as the intricate and diverse environmental factors. To address this challenge, we proposed a research methodology that leverages the similarity of multidimensional terrain features to infer the clutter characteristics of unmeasured regions, particularly those that are difficult or impossible to measure directly. In order to realize this study object, we constructed a dataset consisting of multidimensional environmental and clutter data to quantitatively characterize the complex environmental information in a vast territory. Within the dataset, we selected two regions with similar terrain characteristics: one region served as the source data for mining and analyzing features, while the other was designated as the target data region for method validation. Through the application of prior-knowledge-based classification and multifactor weight analysis on the dataset, two novel estimation techniques were devised. The first method, designated as PCKRF, blended prior-knowledge classification, weighted K-means clustering, and the random forest (RF) algorithm; and the second method, labeled PCKMW, integrated prior-knowledge classification, weighted K-means clustering, and the minimum weighted distance (MW) approach. In estimating and validating the clutter data from the source region to the target region, the performances of both the PCKRF and PCKMW methods were notably superior to those of the RF, MW, and K-means minimum weighting (KMW). Specifically, the root-mean-squared error (RMSE) was enhanced from a range of 7 dB–10 dB to a range of 4 dB–6 dB, while the determination coefficient (R2) was increased from a range of −1.15–0.09 to a range of 0.25–0.66. The above demonstration illustrates that the current achievements in the clutter estimation methods offer a viable option for accurately recognizing clutter characteristics in complex-terrain environments where comprehensive data collection may be difficult or impossible, with lower human and economic costs.