We present a new approach to retrieve Aerosol Optical Depth (AOD) from Moderate Resolution Imaging Spectroradiometer (MODIS) over the turbid coastal water. This approach supplements the operational Dark Target (DT) aerosol retrieval algorithm that currently don’t conduct any AOD retrieval in the regions with large water-leaving radiances in the visible spectrum. Over the global coastal water regions in all cloud-free conditions, this unavailability of AOD retrievals due to the inherent limitation in existing DT algorithm is ~20%. Here, we refine the MODIS DT algorithm by considering that water-leaving radiance at 2.1 μm is negligible regardless of water turbidity. This refinement, with the assumption that the aerosol single scattering properties over coastal turbid water are similar to that over the adjacent open-ocean pixels, yields ~18% more of MODIS-AERONET collocated pairs for six AEROENT stations in the coastal water regions. Furthermore, comparison with these AERONET observations show that the new AOD retrievals are in either equivalent or better accuracy than those retrieved by the MODIS operational algorithm (over coastal land and non-turbid coastal water). Combining the new retrievals with the existing MODIS operational retrievals not only yield an overall improvement of AOD over those coastal water regions, but also successfully extend the spatial and temporal coverage of MODIS AOD retrievals over the coastal regions where 60% of human population resides, and thereby, aerosol impacts on regional air quality and climate are expected to be significant.

We develop a machine learning (ML) approach for improving the accuracy of the horizontal dis-tribution of the aerosol optical depth (AOD) simulated by the CHIMERE chemistry-transport model over Northern Africa using Moderate-Resolution Imaging Spectroradiometer (MODIS) AOD satellite observations. These observations are used during the training phase of the ML method for deriving a regional bias correction of AODs simulated by CHIMERE. The results are daily maps of regional bias corrected AODs with full horizontal coverage over Northern Africa. We test four types of ML models: multiple linear regression (MLR), random forests (RF), gradi-ent boosting (XGB), and multiple layer perceptron networks (NN). We perform comparisons with satellite and independent ground-based observations of AOD that are not used in the training phase. They suggest that all models have overall comparable performances with a slight advantage of the RF model which expresses less spatial artifacts. While the method slightly underestimates the very high AODs, it significantly reduces biases and absolute errors, and clearly enhances linear correlations with respect to independent observations. This im-provement for deriving the AOD is particularly relevant for high dust pollution regions like the Sahara Desert, which dramatically lack ground-based measurements for validations of chemis-try-transport modeling which currently remains challenging and imprecise.

The air quality monitoring network in Alaska is currently limited to ground-based observations in urban areas and national parks leaving a large proportion of the state unmonitored. The use of MODIS aerosol optical depth (AOD) to estimate ground-level particulate pollution concentrations has been successfully demonstrated around the world, and could potentially be used in Alaska. In this work, MODIS AOD measurements at 550 nm were validated against AOD derived from AERONET ground-based sunphotometers in Barrow and Bonanza Creek to determine if MODIS AOD from the Terra and Aqua satellites could be used to estimate ground-level particulate pollution concentrations. The MODIS AOD was obtained from MODIS collection 6 using the dark target Land and Ocean algorithms from 2000 to 2014. MODIS data could only be obtained between the months of April and October; therefore, it could only be validated for those months. Individual and combined Terra and Aqua MODIS data were considered. The results showed that MODIS collection 6 products at 10 km resolution for Terra and Aqua combined are not valid over land but are valid over the ocean. On the other hand, the individual Terra and Aqua MODIS collection 6 AOD products at 10 km resolution are valid over land individually but not when combined. Results also suggest the MODIS collection 6 AOD products at 3 km resolution are valid over land and ocean and perform better over land than the 10-km product. These findings indicate that MODIS collection 6 AOD products can be used quantitatively in air quality applications in Alaska during the summer months.

Gaze tracking of high-speed moving targets is a novel application mode for low Earth orbit microsatellites. In this mode, small satellites are equipped with high-resolution narrow-field-of-view video cameras for stable gaze-tracking imaging of high-speed moving targets. This paper proposes a high-precision attitude adaptive integral sliding mode control method with a feedforward compensation disturbance observer to enhance the capability of a microsatellite attitude control system for gaze tracking of high-speed moving targets. Specifically, first, we present the attitude control system model for microsatellites and the calculation method for the desired attitude of target tracking based on image feedback. Then, an adaptive integral sliding mode attitude control algorithm with a feedforward compensation disturbance observer, which meets the requirements of high-precision tracking control, is designed. The developed algorithm utilizes the disturbance observer to observe the friction torque of the flywheel and compensates for it through feedforward control. It also employs the adaptive integral sliding mode control algorithm to reduce the impact of uncertain disturbances, decrease the steady-state error of the system, and enhance the attitude control precision. Simulation experiments demonstrated that the designed disturbance observer can successfully observe the frictional disturbance torque of the flywheel. The attitude Euler angle control precision for high-speed moving target tracking reached 0.009°, and the angular velocity control precision reached 0.005°/s, validating the effectiveness of the proposed approach.

The Advanced Meteorological Image (AMI) onboard GEOKOMPSAT 2A (GK-2A) enables the retrieval of dust aerosol optical depth (DAOD) from geostationary satellites using infrared (IR) channels. IR observations allow the retrieval of DAOD and the dust layer altitude (24 hour) over surface properties, particularly over deserts. In this study, dust events in northeast Asia from 2020 to 2021 were investigated using five GK-2A thermal IR bands (8.7, 10.5, 11.4, 12.3, and 13.3 μm). For the dust cloud, the observed brightness temperature differences (BTDs) of 10.5 and 12.3 μm were found to be always negative, while the BTD of 8.7 and 10.5 μm varies relying on the dust intensity. Making the best use of optical properties, a physical approach for DAOD lookup tables (LUTs) was developed using IR channels to retrieve the DAOD. This study simulated the characteristics of thermal radiation transfer using the forward model and dust aerosols can explain by BTD (10.5, 12.3 μm), which is an intrinsic characteristic of dust aerosol. The DAOD and property of dust can be gained from the brightness temperature (BT) of 10.5 μm and the BTD of 10.5, 12.3 μm. Additionally, the cumulative distribution function (CDF) was employed to strengthen the continuity of 24-hour DAOD, which was applied to the algorithm by calculating the conversion value coefficient for the DAOD error correction of the IR with daytime visible aerosol optical depth (VAOD) as the true value. The results show that DAOD product can be successfully used during both daytime and nighttime to continuously monitor the flow of yellow dust from the GK-2A satellite in northeast Asia. In particular, the validation result of IR DAOD was similar to that of the active satellite product (CALIPSO/CALIOP), which showed a tendency similar to that for IR DAOD at night.

Dynamic optical structural color is always desired in various display applications and usually involves active materials. Full-color generation, especially bi-directional full-color generation in both reflective and transmissive modes, without any active materials included has been rarely investigated. Herein, we demonstrate a scheme of bi-directional full-color generation based on a plasmonic metasurface modulated by rotation of the polarization angle of the incident light without varying the geometry and the optical properties of the materials and the environment where the metasurface resides. The metasurface unit cell consists of plasmonic modules aligning in three directions and is patterned in a square array. The metasurface structural color device generates full colors in both reflection and transmission. Based on the proposed polarization-dependent structural color, information encoding of three multiplexed animal images and quick-responsive (QR) codes is demonstrated to verify the efficient information encoding and decoding of the proposed scheme. The animals can be seen under different polarization incidence and the QR codes can be successfully decoded by the polarization rotation in transmission. The proposed bi-directional full-color generation metasurface has great potential in applications such as kaleidoscope generation, anti-counterfeiting, dynamic color display, and optical information encoding.

In order to investigate the size distributions and seasonal variations of carbonaceous aerosols (OC and EC), the carbonaceous species were collected and then analyzed by using a 9-stage Anderson-type aerosol sampler and DRI Model 2001A Thermal/Optical Carbon Analyzer on the typical industrial city Nanjing in Yangtze River Delta, China in the summer, autumn and winter of 2013 and spring of 2014. OC, EC, SOC and POC exhibited obvious seasonal variations, with the highest level in winter (39.1±14.0, 5.7±2.1, 23.6±11.7 and 14.1±5.7 μg•m^-3) and the lowest level in summer (20.6±6.7, 3.3±2.0, 12.2±3.8 and 8.4±4.1 μg•m^-3), and were mainly centralized in PM_1.1 in four seasons. The concentrations of OC in PM_1.1 varied in the order of winter > autumn > spring > summer, while EC ranked in the order of autumn > winter > summer > spring. In the PM_1.1-2.1 and PM_2.1-10, the concentrations of OC and EC decreased in the sequence of winter > spring > autumn > summer. The size spectra of OC, EC and SOC had bimodal distributions in four seasons, except for EC with four peaks in summer. The size spectra of POC varied greatly with seasons, exhibiting bimodal distribution in winter, trimodal distribution in spring and summer, and four peaks in autumn. The OC/EC ratios were 7.0, 6.3, 7.6 and 6.9 in spring, summer, autumn and winter, respectively, which demonstrated the abundance of secondary organic aerosols in Nanjing. The sources of carbonaceous aerosol varied significantly with seasons, and were dominated by vehicle exhaust, coal and biomass burning in PM_2.1, and dominant by dust, coal and biomass burning in PM_2.1-10.

Axial resolution is one of the most important characteristics of a microscope. In all microscopes, a high axial resolution is desired in order to discriminate information efficiently along the longitudinal direction. However, when studying thick samples that do not contain laterally overlapping information, a low axial resolution is desirable as information from multiple planes can be recorded simultaneously from a single camera shot instead of plane-by-plane mechanical refocusing. In this study, we increased the focal depth of an infrared microscope non-invasively by introducing a binary axicon fabricated on barium fluoride substrate close to the sample. Preliminary results of imaging thick and sparse silk fibers showed an improved focal depth with a slight decrease in lateral resolution and increase in background noise.

Pipeline conflicts arising from data dependencies are a common issue encountered in the hardware implementation of layered QC-LDPC decoders. This paper proposes an efficient layered decoding architecture to reduce pipeline conflicts without introducing stall cycles, by reordering the processing order offline and using the patch method based on variable-to-check message. The experimental results on the LDPC code of the IEEE802.16 standard in the OFDM-PON system demonstrate that the proposed architecture has a sensitivity improvement of 0.125 dBm and 0.375 dBm, respectively, compared with our previous work and the method described in the other work.

Optimal use of Hierarchical Bayesian Model (HBM) assembled aerosol optical depth (AOD)-PM2.5 fused surfaces in epidemiologic studies requires homogeneous temporal and spatial fused surfaces. No analytical method is available to evaluate spatial heterogeneity. The temporal case-crossover design was modified to assess the spatial association between four experimental AOD-PM2.5 fused surfaces and four respiratory-cardiovascular hospital events in 12 km2 grids. The maximum number of adjacent lag grids with significant odds ratios (ORs) identified homogeneous spatial areas (HOSAs). The largest HOSA included 5 grids (lag grids 04; 720 km2) and the smallest HOSA contained 2 grids (lag grids 01; 288 km2). Emergency department asthma and inpatient asthma, myocardial infarction, and heart failure ORs were significantly higher in rural grids without air monitors than in urban grids with air monitors at lag grids 0, 1, and 01. Rural grids had higher AOD-PM2.5 concentration levels, population density, and poverty percent than urban grids. Warm season ORs were significantly higher than cold season ORs for all health outcomes at lag grids 0, 1, 01, and 04. The possibility of elevated fine and ultrafine PM and other demographic and environmental risk factors synergistically contributing to elevated respiratory-cardiovascular chronic diseases in persons residing in rural areas was discussed

The main goal of the Soil Moisture and Ocean Salinity (SMOS) mission over land surfaces is the production of global maps of soil moisture (SM) and vegetation optical depth (τ) based on multi-angular brightness temperature (TB) measurements at L-band. The operational SMOS Level 2 and Level 3 soil moisture algorithms account for different surface effects, such as vegetation opacity and soil roughness at 4 km resolution, in order to produce global retrievals of SM and τ. In this study, we present an alternative SMOS product which was developed by INRA (Institut National de la Recherche Agronomique) and CESBIO (Centre d’Etudes Spatiales de la BIOsphère). This SMOS-INRA-CESBIO (SMOS-IC) product provides daily SM and τ at the global scale and differs from the operational SMOS Level 3 (SMOSL3) product in the treatment of retrievals over heterogeneous pixels. Specifically, SMOS-IC is much simpler and does not account for corrections associated to the antenna pattern and the complex SMOS viewing angle geometry. It considers pixels as homogeneous to avoid uncertainties and errors linked to inconsistent auxiliary data sets which are used to characterize the pixel heterogeneity in the SMOS L3 algorithm. SMOS-IC also differs from the current SMOSL3 product (Version 300, V300) in the values of the effective vegetation scattering albedo (ω) and soil roughness parameters. An inter-comparison is presented in this study based on the use of ECMWF (European Center for Medium range Weather Forecasting) SM outputs and NDVI (Normalized Difference Vegetation Index) from MODIS (Moderate-Resolution Imaging Spectroradiometer). A 6 year (2010-2015) inter-comparison of the SMOS products SMOS-IC and SMOSL3 SM (V300) with ECMWF SM yielded higher correlations and lower ubRMSD (unbiased root mean square difference) for SMOS-IC over most of the pixels. In terms of τ, SMOS-IC τ was found to be better correlated to MODIS NDVI in most regions of the globe, with the exception of the Amazonian basin and of the northern mid-latitudes.

During the smelting process of AOD furnace, the unbalanced reaction of material will lead to the occurrence of splashing. It will not only damage the smelting equipment, but also seriously injure the personnel. In this study, first, the information of liquid level, audio information, and vibration information are detected by multiple sensors respectively. Then, the fused information is used to forecast the splashing. Finally, the multitasking fuzzy controller is used to suppress splashing. The results show that the method of forecasting and suppressing splashing can accurately forecast and achieve rapid suppression. Thus, the efficiency of smelting can be improved.

The Combined Inversion of Surface and AeRosols (CISAR) algorithm for the joint retrieval of surface and aerosol single scattering properties has been further developed in order to extend the retrieval to clouds and overcome the need for an external cloud mask. Pixels located in the transition zone between pure cloud and pure aerosol are often discarded by both aerosol and cloud algorithms, despite being essential for studying aerosol-cloud interactions, which still represent the largest source of uncertainty in climate predictions. The proposed approach aims at filling this gap and deepening the understanding of aerosol properties in cloudy environments. The new CISAR version is applied to Sentinel-3A/SLSTR observations and evaluated against different satellite products and ground measurements. The spatial coverage is greatly improved with respect to algorithms processing only pixels flagged as clear sky by the SLSTR cloud mask. The continuous retrieval of aerosol properties without any safety zone around clouds opens new possibilities for studying aerosol properties in cloudy environments.

The variation of aerosols, especially dust aerosol, in time and space plays an important role in climate forcing studies. Aerosols can effectively reduce land surface longwave emission and re-emit energy at a colder temperature, making estimation of downwelling surface longwave radiation (DSLR) with satellite data difficult. Using the latest atmospheric radiative transfer code (MODTRAN 5.0), we simulate the outgoing longwave radiation (OLR) and DSLR under different land surface and atmospheric profile conditions. The results show that dust aerosol has an obvious “warming” effect to longwave radiation compared with other aerosols, that aerosol longwave radiative forcing (ALRF) increased with increasing aerosol optical depth (AOD), and that the atmospheric water vapor content (WVC) is critical to the understanding of ALRF. A method is proposed to improve the accuracy of DSLR estimation from satellite data for the skies under heavy dust aerosols. The AOD and atmospheric WVC under cloud-free conditions with a relatively simple satellite-based radiation model that yields the high accurate DSLR under heavy dust aerosol are used explicitly as model input to reduce the effects of dust aerosol on the estimation of DSLR. Validations of the proposed model with satellites data and field measurements show that it estimates the DSLR accurately under heavy dust aerosol skies. The root mean square errors (RMSEs) are 20.4 W/M² and 24.2 W/M² for Terra and Aqua satellites, respectively, at the Yingke site, and the biases are 2.7 W/M² and 9.6 W/M², respectively. For the Arvaikheer site, the RMSEs are 23.2 W/M² and 19.8 W/M² for Terra and Aqua, respectively, and the biases are 7.8 W/M² and 10.5 W/M², respectively. The proposed method is especially applicable to acquire relatively high accurate DSLR under heavy dust aerosol using MODIS data with available WVC and AOD data.

In this paper, we introduce a specialized, fully automated experimental arrangement designed for assessing the effectiveness of augmented and virtual reality technologies in healthcare setting and explore its design principles focusing on depth sensor characterization. The main goal of this project is to establish a robust benchtop platform for the quantitative evaluation of extended reality technologies in a controlled environment, emphasizing the practical assessment of augmented reality head-mounted devices. We outline a design concept and considerations for an experimental configuration aimed at creating a realistic testing environment. This apparatus comprises an observation platform mounted on a three-degree-of-freedom motorized system and a test phantom stage. Focusing on real-case scenarios, we utilized a range of sensors, including readily available range-sensing cameras and commercial augmented reality headsets, such as the Intel RealSense L515 LiDAR camera, mounted on the motion control system. The setup enabled automated data collection and facilitates controlled assessments and validation of various facets of augmented reality technologies, including object, hand, and head tracking, as well as static and dynamic image registration. This paper describes the system architecture, the process of automated data collection, and presents several evaluation studies conducted with this setup, providing insights into the quality and temporal noise associated with static or moving objects or observers in augmented reality applications.

Infrared thermography has already been proven to be a significant method in non-destructive evaluation since it gives information with immediacy, rapidity and low cost. However, the thorniest issue for wider application of IRT is the quantification. In this work, we proposed a specific depth quantifying technique by employing the Gated Recurrent Units (GRU) in composite material samples via pulsed thermography (PT). Carbon Fiber Reinforced Polymer(CFRP) embedded with flat bottom holes were designed via Finite Element Method (FEM) modeling in order to precisely control the depth and geometrics of the defects. The GRU model automatically quantified the depth of defects presented in the CFRP material. The proposed method evaluated the accuracy and performance of synthetic CFRP data from FEM for defect depth predictions.

Depth-sensing technology has led to broad applications of inexpensive depth cameras that can capture human motion and scenes in 3D space. Background subtraction algorithms can be improved by fusing color and depth cues, thereby allowing many issues encountered in classical color segmentation to be solved. In this paper, we propose a new fusion method that combines depth and color information for foreground segmentation based on an advanced color-based algorithm. First, a background model and a depth model are developed. Then, based on these models, we propose a new updating strategy that can eliminate ghosting and black shadows almost completely. Extensive experiments have been performed to compare the proposed algorithm with other, conventional RGB-D algorithms. The experimental results suggest that our method extracts foregrounds with higher effectiveness and efficiency.

An innovative mobile Lidar device, developed to monitor volcanic plumes during explosive eruptions at Mt. Etna (Italy) and analyze the optical properties of volcanic particles was upgraded in October 2023 with the aim to improve volcanic plume retrievals. The new configuration of the lidar allows to obtain new data of both the optical and the microphysical properties of the atmospheric aerosol. In fact, after its upgrade, the lidar has the possibility to measure 3β, 2α and 2δ in a configuration defined as “state of the art lidar” where properties such as the particle size distribution and refractive index can be derived. During the lidar implementation we were able to to test the system performance through specific calibration measurements. In this work, the first measurement results are shown and compared with results obtained by other instruments aimed at proving the ability of the upgraded system to more precisely characterize the aerosol optical and microphysical properties.

The advancement in science and technology has led to luffa sponge (LS) being widely used as a natural material in industrial application as its polyporous structure and light texture. In order to enhance the utility of LS fibers as the reinforcement of lightweight composite materials, this study investigate its water absorption, mechanical properties, anatomical characteristic and thermal performance. Hence, moisture regain, tensile properties of LS fiber bundles were measured in accordance with standards and the structural characteristics were investigated via microscopic observation. Scanning electron microscopy (SEM) was used to observe the surface morphology and fracture surface of fiber bundles. Test results shows that the special structure where the phloem tissues degenerate to cavities had a significant influence on the mechanical properties of LS fiber bundles. Additionally, the transverse sectional area occupied by fibers in a fiber bundle (SF), wall thickness and ratio of wall to lumen of fiber cell, and crystallinity of cellulose had an impact on the mechanical properties of LS fiber bundles. Furthermore, the fiber bundles density of LS varies range of 385.46-468.70 kg/m³, much less than that of jute (1360.40 kg/m³) and Arenga engleri (950.20 kg/m³) while LS fiber bundles has superior specific modulus.

Quantum correlations, especially time correlations, are crucial in ghost imaging in order to significantly reduce the background noise on the one hand while increasing the imaging resolution. Moreover, the time correlations serve as a critical reference, distinguishing between signal and noise, which in turn enable clear visualization of biological samples. Quantum imaging also addresses the challenge involved in imaging delicate biological structures with minimal photon exposure and sample damage. Here we explore the recent progress in quantum correlation-based imaging, notably its impact on secure imaging and remote sensing protocols as well as on biological imaging. We also exploit the quantum characteristics of heralded single-photon sources (HSPS) combined with decoy-state methods for secure imaging. This method uses Quantum Key Distribution (QKD) principles to reduce measurement uncertainties and protect data integrity. It is highly effective in low-photon-number regimes for producing high-quality, noise-reduced images. The versatility of decoy-state methods with WCSs (WCS) is also discussed, highlighting their suitability for scenarios requiring higher photon numbers. We emphasize the dual advantages of these techniques: improving image quality through noise reduction and enhancing data security with quantum encryption, suggesting significant potential for quantum imaging in various applications, from delicate biological imaging to secure quantum communication.

Aerosols play an important role in Earth’s climate system, thus long time ground based measurements of aerosol optical properties are useful in understanding this role. 10 years of quality-assured measurements between 2010 and 2020 are used to investigate the aerosol climatology in the Cluj-Napoca area, in North-Western Romania. In this study, we analyze the Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA) and Ångström exponent obtained by CIMEL sun photometer, part of the Aerosol Robotic Network (AERONET) to extract the seasonality of aerosols in the region and investigate the aerosol climatology of the area. Higher aerosol loads are found during July and August. Ångström exponent has the lowest values in April and May and the highest in August. The classification of aerosols using AERONET data is performed to separate dust, biomass burning, polluted urban, marine and continental dominant aerosol mixtures. In addition, the study presents the validation efforts of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) dataset against AERONET AOD over 10 years period.

The influence of growth temperature on the crystalline quality and optical properties of AlGaN at 325 nm, grown using plasma-assisted molecular beam epitaxy (MBE), was investigated. The growth temperature exhibited a significant impact on the growth mode and surface morphology. Specifically, at a growth temperature of 750 degrees Celsius, when appropriate Al and Ga flow rates were employed, the AlGaN layer exhibited exceptional surface morphology and favorable optical properties. The optical properties of the AlGaN material were explored, revealing the presence of two distinct non-radiative recombination centers characterized by different activation energies. The minority carrier lifetimes were measured as 560 ps at 10 K and 64 ps at room temperature. The underlying mechanism was analyzed from the perspective of carrier dynamics, shedding light on the observed phenomena.

A comprehensive theory is developed for the chiral optical response of two configurations of the N-oscillator Born-Kuhn model (NOBK): the helically stacked and the corner stacked models. In the helical NOBK model, there is always a chiral response regardless of the value of N, whereas in the corner NOBK, only configurations with even N demonstrate a chiral response. Generally, the magnitudes of optical rotatory dispersion (ORD) and circular dichroism (CD) increase with N when the parameters of each oscillator are fixed. In cases of weak coupling, the spectral shapes of ORD and CD remain invariant, while strong coupling significantly alters the spectral shapes. For large damping, the spectral amplitude becomes smaller, and the spectral features become broader. In the presence of small damping, strong coupling introduces degeneracy in the coupled oscillator system, leading to multiple spectral features in both ORD and CD across the entire spectral region. This simple model not only can help in the design of tunable chiral metamaterials but also enhance our understanding of chiro-optical responses in structures with different configurations.

Chemical processing of organic material in aqueous atmospheric aerosols and cloudwater is known to form secondary organic aerosols (SOA), although the extent to which each of these processes contributes to total aerosol mass is unclear. In this study, we use GAMMA 5.0, a photochemical box model with coupled gas and aqueous-phase chemistry, to consider the impact of aqueous organic reactions in both aqueous aerosols and clouds on isoprene epoxydiol (IEPOX) SOA over a range of pH for both aqueous phases, including cycling between cloud and aerosol within a single simulation. Low-pH aqueous aerosol, in the absence of organic coatings or other morphology which may limit uptake of IEPOX, is found to be an efficient source of IEPOX SOA, consistent with previous work. Cloudwater at pH 4 or lower is also found to be a potentially significant source of IEPOX SOA. This phenomenon is primarily attributed to the relatively high uptake of IEPOX to clouds as a result of higher water content in clouds as compared to aerosol. For more acidic cloudwater, the aqueous organic material is comprised primarily of IEPOX SOA and lower-volatility organic acids. For both cloudwater and aqueous aerosol, pH is the most significant factor considered in this study in determining the mass of aqueous phase organic acids and IEPOX SOA. Other factors, such as the time of day or sequence of aerosol-to-cloud or cloud-to-aerosol transitions, contribute to less than 15% difference in the final aqSOA fractional composition. The potential significance of cloud processing as a contributor to IEPOX SOA production could account for discrepancies between predicted IEPOX SOA mass from atmospheric models and measured ambient IEPOX SOA mass, or observations of IEPOX SOA in locations where mass transfer limitations are expected in aerosol particles.

Theoretical studies on the generation of nondiffracting and nondispersive light pulses and their experimental implementation are one of the renowned problems within electromagnetics. Current technologies enable creation of short-duration pulses of a few cycles with high power and fluency. An application of these techniques to the field of nondiffracting and nondispersive pulses requires a proper mathematical description of highly focused vector pulses. In this work, we study vector optical bullets in a dielectric medium with different polarization structures: linear, azimuthal, and radial. We report the differences caused by the vector model compared to the scalar model. We analyze effects caused by superluminal, subluminal, or even negative group velocity on properties of vector optical bullets inside a dielectric material.

Statistical denoising techniques have been well studied, however many challenges still remain. This 9 article focuses on determining the least necessary number of significant samples in a statistical pop-10 ulation sampling, while minimizing the impact on the statistical detection of the fiber Bragg grating 11 (FBG) power spectra. This is achieved by using Bayesian decision making, small population statis-12 tics while excluding false detection. First, we investigate the impact of two-sided sliding window 13 technique applied near the cell under the test. The window size varies from 8 to 60 samples. The 14 considered maximum size of population sampling is connected with the number of wavelength 15 samples within the bandwidth of the symmetrical FBG power spectra peaks. Regarding the sym-16 metry of FBG power spectra peaks and the possible reduction of computational demands, we inves-17 tigate the impact of a one-sided sliding window. This enables to achieve less processing latency for 18 real time applications thus brings benefits to FBG-based fiber optical sensing. Both, two- and one-19 sided small population sampling techniques are then experimentally verified. Detection results are 20 analyzed in depth via calculating detection thresholds by using the small size window sliding along-21 side the waveband. From results achieved, it was found that the normality three-sigma rule does 22 not need to be followed while using the small population sampling. Experimental demonstrations 23 and analyses showed that the proposed concept of denoising and statistical threshold detection 24 based on the sliding window does not depend on the prior knowledge of probability distribution 25 functions of the FBG power spectra peaks level and background noise. We have also found that the 26 thresholds’ adaptability mainly depends on the statistical numerical characteristics of the above ad-27 ditive mixture of the FBG power spectra peaks signals and background noise.

The chiral optical Tamm state (COTS) is a special localized state at the interface of a handedness-preserving mirror and a structurally chiral medium such as a cholesteric liquid crystal or a chiral sculptured thin film. The spectral behavior of COTS, observed as reflection resonances, is described by the temporal coupled-mode theory. Mode coupling is different for two circular light polarizations because COTS has a helix structure replicating that of the cholesteric. The mode coupling for co-handed circularly polarized light exponentially attenuates with the cholesteric layer thickness since the COTS frequency falls into the stop band. Cross-handed circularly polarized light freely goes through the cholesteric layer and can excite COTS when reflected from the handedness-preserving mirror. The coupling in this case is proportional to anisotropy of the cholesteric and theoretically it is only anisotropy of magnetic permittivity that can ultimately cancel this coupling. These two couplings being equal results in a polarization crossover (the Kopp--Genack effect) for which a linear polarization is optimal to excite COTS. The corresponding cholesteric thickness and scattering matrix for COTS are generally described by simple expressions.

In Brazil, Brazilian borreliosis (BB), characterized molecularly, exhibits symptoms akin to Lyme disease (LD) but presents unique epidemiological, clinical, and morphological features. This study explores the incidence, diagnostic challenges, and awareness initiatives regarding this disease in Brazil. Employing a narrative review methodology, data were sourced from Pubmed, Ebsco, Google Scholar, and Web of Science without temporal constraints. Results reveal diagnostic complexities in Brazil due to the low sensitivity of conventional tests and the use of North American B. burgdorferi antigens. Despite challenges, epidemiological studies indicate an upswing in cases in humans and animals. Therefore, there is an urgent need to define new biomarkers, molecular strategies, or new antigenic targets to advance the development of vaccines and diagnostics. Early and accurate pathogen identification is crucial for active surveillance to comprehend and manage this zoonosis.

Neural radiance fields (NeRF) leverage a neural representation to encode scenes, obtaining photo-realistic rendering of novel views. However, NeRF has notable limitations. A significant drawback is that it does not capture surface geometry and only renders the object surface colors. Furthermore, the training of NeRF is exceedingly time-consuming. We propose Depth-NeRF as a solution to these issues. Specifically, our approach employs a fast depth completion algorithm to denoise and complete the depth maps generated by RGB-D cameras. These improved depth maps guide the sampling points of NeRF to be distributed closer to the scene's surface, benefiting from dense depth information. Furthermore, we have optimized the network structure of NeRF and integrated depth information to constrain the optimization process, ensuring that the termination distribution of the ray is consistent with the scene’s geometry. Compared to NeRF, our method accelerates the training speed by 18% and significantly reduces the RMSE between the rendered scene depth and the ground truth depth, which indicates that our method can better capture the geometric information of the scene. With these improvements, we can train the NeRF model more efficiently and achieve more accurate rendering results.

With the progression of AI, embedding advanced AI technologies into small robotics and mobile devices has become essential, driving research towards lightweighting AI models. Our study enhances the EPINET depth estimation model for light field images, aiming for compactness and faster inference while preserving accuracy. We conducted two-step experiments aimed at enhancing inference efficiency: Initially, by adjusting input streams and convolution layers, we simplified the CNN model, achieving faster inference times at the cost of reduced accuracy. To address this reduction in accuracy, we then applied knowledge distillation, allowing the simplified model to learn from the original model’s more complex patterns. In our quantitative experiments using two error metrics, MSE (Mean Squared Error) and BadPix, we identified optimal knowledge positions and evaluated the required complexity for the student model. As a result, our method improved MSE by 21% and BadPix by 14% compared to training without it. Furthermore, the student model achieved an inference speed 13% faster than the teacher model and surpassed its accuracy by 10% in MSE. Additionally, we demonstrated that repeatedly applying our approach could further enhance both model compactness and accuracy.

Wavelength selective switches (WSSs) are essential elements for wavelength division multiplexing (WDM) optical networks, as they offer cost-effective, high port-count and flexible spectral channel switching. This work proposes a new hybrid WSS architecture that leverages the beam shaping and steering features of uniform silicon nitride (SiN) based end-fire optical phased arrays (OPAs). By introducing beamforming to a WSS system, the spectral channels on the liquid crystal on silicon (LCoS) panel can be tailored and arranged properly, depending on the optical configuration, using the beam control capabilities of OPAs. Combining 3D-FDTD and ray tracing simulations, the study shows that by reducing the input beam dimensions with proper sizing of the OPAs, the WSS design with the null-steering OPAs layout and 4×No switch size features increased spectral resolution. This extensive beamforming study on the steering-enabled layout reveals the acquirement of an even higher input channel number, achieving up to the 8×No WSS scheme with flexible channel routing on the LCoS panel. Such implementation of beamsteerers can unlock an extra degree of freedom for the switching capabilities of hybrid WSS devices. The results show great promise for the introduction of OPAs in WSS systems and provide valuable insight for the design of future wireless communication links and WDM systems.

We propose a method for creating parallel Bessel-like vortical optical needles with an arbitrary axial intensity distribution via superposition of different cone-angle Bessel vortices. We analyze the interplay between the separation of individual optical vortical needles and their respective lengths and introduce a super-Gaussian function as their axial profile. We also analyze the physical limitations to observe well-separated optic needles, as they are influenced by mutual interference of the individual beams. To verify our theoretical and numerical results, we generate controllable spatial arrays of individual Bessel beams with various numbers and spatial separations by altering the spectrum of the incoming laser beam via the spatial light modulator. We demonstrate experimentally how to implement such beams using a diffractive mask. The presented method facilitates the creation of diverse spatial intensity distributions in three dimensions, potentially finding applications in specific microfabrication tasks or other contexts. These beams may have benefits in laser material processing applications such as nanochannel machining, glass via production, modification of glass refractive indices, and glass dicing.

A Cu₂ZnSnS₄ (CZTS) film with a thickness of approximately 1.5 μm was fabricated on a Mo-coated glass substrate by annealing a CZTS precursor fabricated from nanoparticle ink. The chemical states of the elements in the CZTS thin film in the depth direction were studied to identify the presence of secondary phases, which are detrimental to the performance of solar cells containing CZTS. X-ray diffraction was unable to detect any secondary phases in CZTS because of their small relative amount. Instead, X-ray photoelectron spectroscopy (XPS), which is highly sensitive to chemical state, was conducted at different depths in the CZTS film to further check the presence of secondary phases. XPS analysis revealed peaks shift consistent with the presence of secondary phases. For the CZTS film annealed in a S atmosphere at 575 °C for 3 h, the film surface consisted of a secondary-phase layer composed of CuS, ZnS, and SnSx (x=1 or 2) originating from the decomposition of CZTS. At depths below 80 nm, the film was pure CZTS. Formation of MoS2 at the CZTS–Mo interface was confirmed by XPS analysis of Mo and S.

Using coherent optical detection and digital signal processing, laser phase noise and equalization enhanced phase noise can be effectively mitigated using the feed-forward and feed-back carrier phase recovery approaches. In this paper, theoretical analyses of feed-back and feed-forward carrier phase recovery methods have been carried out in the long-haul high-speed n-level phase shift keying (n-PSK) optical fiber communication systems, involving a one-tap normalized least-mean-square (LMS) algorithm, a block-wise average algorithm, and a Viterbi-Viterbi algorithm. The analytical expressions for evaluating the estimated carrier phase and for predicting the bit-error-rate (BER) performance (such as the BER floors) have been presented and discussed in the n-PSK coherent optical transmission systems by considering both the laser phase noise and the equalization enhanced phase noise. The results indicate that the Viterbi-Viterbi carrier phase recovery algorithm outperforms the one-tap normalized LMS and the block-wise average algorithms for small phase noise variance (or effective phase noise variance), while the one-tap normalized LMS algorithm shows a better performance than the other two algorithms for large phase noise variance (or effective phase noise variance). In addition, the one-tap normalized LMS algorithm is more sensitive to the level of modulation formats.

The Eastern Mediterranean is a highly populated area with air quality problems as well where climate change already is noticed by higher temperatures and changing precipitation pattern. The anthropogenic aerosol affects health and changing concentra-tions and properties of the atmospheric aerosol affect radiation balance and clouds. Continuous long-term observations are essential in assessing the influence of anthro-pogenic aerosols on climate and health. We present 6 years of observations from Navarino Environmental Observatory (NEO), a new station located at the south west tip of Pelo-ponnese, Greece. The two sites at NEO, were evaluated to show the influence of the local meteorology but also to assess the general background aerosol possible. It was found that the background aerosol was originated from aged European aerosols and was strongly influenced by biomass burning, fossil fuel combustion, and industry. When subsiding into the boundary layer, local sources contributed in the air masses moving south. Mesoscale meteorology determined the diurnal variation of aerosol properties such as mass and number by means of typical sea breeze circulation, giving rise to pronounced morning and evening peaks in pollutant levels. While synoptic scale meteorology, mainly large-scale air mass transport and precipitation, strongly influenced the season-ality of the aerosol properties.

In this work, two plasmonic structures with two different periodic nanostructures (nanodisk and nanostrip arrays) separated from the gold layer by an ultrathin dielectric Al2O3 layer are proposed, and their optical properties are simulated as 3-dimensional models using COMSOL Multiphysics software tool. The optical responses, such as the amplification of the electric field and the scattering, absorption and extinction cross sections of the two structures, are investigated and compared. The results show that both structures show strong field enhancement in their gap layer, and the structure with the periodic array of metal nanodisks shows stronger field enhancement and larger absorption, extinction, and scattering cross sections in its dipole resonance wavelength, which is defined as a bright plasmonic mode. In addition, some weaker resonant modes are observed for both structures and the reason for their generation is dis-cussed. The analysis of different possible modes in such structures is crucial for their application in various fields.

Optical backbone networks constitute the fundamental infrastructure employed today by network operators to deliver services to users. As network capacity is a key factor influencing optical network performance, it is important to understand how topological and physical properties impact its behavior and to have the capability to estimate its value. In this context, we propose here a method to evaluate the network capacity that relies on the optical reach to account for physical layer aspects, in conjunction with constrained routing techniques for traffic routing. As this type of routing can lead to traffic blocking, particularly due to the limitation on the number of wavelengths per fiber, we also propose a fiber assignment algorithm designed to deal with this problem. We apply this method to a set of randomly generated networks using a modified Waxman model, and for a network with 60 nodes, in a scenario without blocking, we obtain capacities of about 2.5 Pbit/s for a symbol rate of 64 Gbaud and about 5 Pbit/s for a symbol rate of 128 Gbaud. Remarkably, this duplication in the total network capacity is achieved by an increase in the total fiber length of only about 51%.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

A simple design of an ultrathin six-band polarization-insensitive terahertz perfect metamaterial absorber (PMMA) composed of a metal cross-cave-patch resonator (CCPR) placed over a ground plane was proposed and investigated numerically. The numerical simulation results demonstrate that the average absorption peaks are up to 95% at six resonance frequencies with high quality-factors (>65). In addition, the absorption properties can be kept stability for both normal incident transverse magnetic (TM) and transverse electric (TE) waves. The physical mechanism behind the observed high level absorption is illustrated by the electric and power loss density distributions. The different absorption mainly originates from the higher order multipolar and multipolar plasmon resonance of the structure, which are sharp different to the most previous studies of the PMMAs. Furthermore, the resonance absorption of the PMMA can be tunable by varying the geometric parameters of the unit cell.

The accuracy of cosmic ray observation by the Large High Altitude Air Shower Observatory Wide Field-of-view Cherenkov/fluorescence Telescope Array (LHAASO-WFCTA) is influenced by variations in aerosols in the atmosphere. The solar photometer (CE318-T) is extensively utilized within the Aerosol Robotic Network as a highly precise and reliable instrument for aerosol measurements. With this CE318-T 23, 254 sets of valid data samples in 394 days from October 2020 to October 2022 at the LHAASO site were obtained. Data analysis revealed that the baseline Aerosol Optical Depth (AOD) and A˚ngstro¨m Exponent (AE) at 440-870 nm (AE440−870nm) of the aerosols were calculated to be 0.03 and 1.07, respectively, suggesting that the LHAASO site is among the most pristine regions on Earth. The seasonality of the mean AOD are the order of spring > summer > autumn = winter. The monthly average maximum of AOD440nm occurred in April (0.11 ± 0.05) and the minimum was in December (0.03 ± 0.01). The monthly average of AE440−870nm exhibited slight variations. The seasonal characterization of aerosol types indicated that clean continental background aerosol predominated in autumn and winter, which is the optimal period for the absolute calibration of the WFCTA. Additionally, the diurnal daytime variations of AOD and AE across the four seasons are presented. Our analysis also indicates that the potential origins of aerosol over the LHAASO in four seasons were different and the atmospheric aerosols with higher AOD probably originate mainly from Northern Myanmar and Northeast India region. These results provide a baseline for comparison to the future on-site measurement of extinction coefficient profile and aerosol phase function by LHAASO-WFCTA, also enrich the valuable materials on aerosol observation in the Hengduan Mountains and Tibetan Plateau.

A new class of nano-cube core-shell heterostructures containing Ag coating on the top of WO₃ was fabricated. Physical vapor deposition was used to produce WO₃ based nano-heterostructures. All kind of wet toxic chemical process was avoided to make the process simple and contaminant free. Sputtering of WO₃ and a subsequent thermal annealing process was done to create nano-cubes of WO₃. After that, sputtering of Ag was performed to form the Ag-WO₃ core-shell nano-heterostructures (CSNH). The CSNHs were characterized using field emission scanning electron microscopy (FESEM), energy dispersive spectroscopy (EDS), X-ray diffraction analysis (XRD) and UV-vis spectroscopy. The morphologies, elemental analysis, interfaces, crystallinity, phases, and chemical compositions were analyzed. The bottom-up growth of WO₃ nanocubes was studied using different time periods at 900°C. Ag coating was also studied before and after annealing. Finally, an optical property (band gap) was also analyzed using Tauc plot derive from absorption spectra. The tailoring the band gap of WO₃ from ~2.9eV to ~ 2.45 eV was observed while Ag-WO₃ CSNH formed.

The spectra and global distributions of the X-ray emissions generated by the solar wind charge-exchange (SWCX) process in the terrestrial magnetosheath are investigated based on a global hybrid model and a global geocoronal hydrogen model. The solar wind O6+ ions which are the primary charge state for oxygen ions in solar wind are considered. The line emissivity of the charge-exchange born O5+ ions are calculated by Spectral Analysis System for Astrophysical and Lab oratory (SASAL). It is found that the emission lines from the O5+ ranges from 105.607 to 118.291 eV with the strong line at 107.047 eV. We then simulated the magnetosheath X-ray emission intensity distributions with a virtual camera at two positions of north pole and dusk at six stages during the passing of a perpendicular interplanetary shock combined with a tangential discontinuity structure through the Earth’s magnetosphere. During this process, the X-ray emission intensity increases with time, and the maximum value is 27.11 keV cm-2 s-1 sr-1 on the dayside, which is 4.5 times that before the solar wind structure reaches the Earth. A clear shock structure can be seen in the magnetosheath and moves earthward. The maximum emission intensity seen at dusk is always higher than that seen at north pole.

Face detection is an important problem in computer vision because it enables a wide range of applications, such as facial recognition and analysis of human behavior. The problem is challenging because of the large variations in facial appearance across different individuals and different lighting and pose conditions. One way to detect faces is to utilize a highly advanced face detection method, such as RetinaFace, which uses deep learning techniques to achieve high accuracy in various datasets. However, even the best face detectors can produce false positives, which can lead to incorrect or unreliable results. In this paper, we propose a method for reducing false positives in face detection by using information from a depth map. A depth map is a two-dimensional representation of the distance of objects in an image from the camera. By using the depth information, the proposed method is able to better differentiate between true faces and false positives. The authors evaluate their method on a combined dataset of 549 images, containing a total of 614 upright frontal faces. The results show that the proposed method is able to significantly reduce the number of false positives without sacrificing the overall detection rate. This indicates that the use of depth information can be a useful tool for improving face detection performance.

Optical artificial neural networks (ONNs) — analog computing hardware tailored for machine learning [1,2] — have significant potential for ultra-high computing speed and energy efficiency [3]. We propose a new approach to architectures for ONNs based on integrated Kerr micro-comb sources [4] that is programmable, highly scalable and capable of reaching ultra-high speeds. We experimentally demonstrate the building block of the ONN — a single neuron perceptron — by mapping synapses onto 49 wavelengths of a micro-comb to achieve a high single-unit throughput of 11.9 Giga-FLOPS at 8 bits per FLOP, corresponding to 95.2 Gbps. We test the perceptron on simple standard benchmark datasets — handwritten-digit recognition and cancer-cell detection — achieving over 90% and 85% accuracy, respectively. This performance is a direct result of the record small wavelength spacing (49GHz) for a coherent integrated microcomb source, which results in an unprecedented number of wavelengths for neuromorphic optics. Finally, we propose an approach to scaling the perceptron to a deep learning network using the same single micro-comb device and standard off-the-shelf telecommunications technology, for high-throughput operation involving full matrix multiplication for applications such as real-time massive data processing for unmanned vehicle and aircraft tracking.

Spectral calibration consists of the calibration of wavelengths and the measurement of the instrument's spectral response function (SRF). Unlike conventional slits, the absorbed aerosol sensors (AAS) are used as a slit homogenizer, in which the spectral response function (SRF) is not a conventional Gaussian curve. To be more precise, the SRF is the convolution of the slit function of the spectrometer, the line spread function of the optical system, and the detector response function. The SRF of the slit homogenizer is a flat-topped multi-Gaussian function. Considering the convenience of fitting, a super-Gaussian function, which looks like a similar distribution to the flat-topped multi-Gaussian function, is used to fit the measured data in a spectral calibration. According to the results, the SRF’s shapes, due to the Earth port, resemble a Gaussian curve with a flatted top could be concluded, which contains an FWHM of 1.78–1.82 nm for the AAS. The results show that the correlation coefficients are about 0.99, which proves that the fitting function could better characterize the SRF of the instrument.

The climate change impacts on some regions of the planet faster and stronger. These areas are known as the hot spots for climate change and Cyprus (Nicosia) in the Mediterranean is one of these spots. This paper aims to analyze the significant changes of atmospheric aerosol characteristics in 2019 and during the extreme event of 25 April 2019. We study the aerosol optical thickness (AOT), Ångström exponent, single scattering albedo, refractive index (imaginary and real parts), size, and vertical distribution of aerosol particles during the event of a high atmospheric aerosol contamination over Nicosia in details. For this purpose, we used the ground-based lidar, observations of the sun-photometer AERONET Nicosia station, satellite products from the Moderate Resolution Imaging Spectroradiometer (MODIS), and back trajectories of air movements calculated using the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT). On 23–25 April, according to lidar and sun-photometer observations, strong aerosol pollution over Nicosia was detected. On April 25, 2019, the AOT value exceeds 1.0 at λ = 440 nm. Analysis of the optical and microphysical characteristics supported that the pollution consists of mainly Saharan dust and partly urban aerosols. This assumption was confirmed by HYSPLIT backward trajectories and MODIS images where air masses containing dust particles came from North Africa and from the Eastern part of Europe.

As climate changes, our daily life has been much influenced by abnormal meteorological phenomena such as heavy rainfall, heat wave, heavy snowfall, and fine dust. Atmospheric air quality is worsening day by day and indoor air quality is also affected by interconnected daily activities throughout the inside and outside of buildings and houses. Nowadays, pollutants from various sources are emitted, transformed by sunlight, vapor, and ozone and transported into the city from country to country. Due to these reasons, there have been high demands to monitor the transportation of particulate matters and improve air quality. Monitoring of pollutants and identification of type and its concentration enables us to track and control its generation and consequently find out the solution. However, monitoring of pollutants, especially, particulate matter generation and its transportation is still not fully operated in atmospheric air due to its open nature and meteorological factors. Even though indoor air is relatively easy to monitor and control than outdoor in the aspect of specific volume and contaminant source, but it still needs to consider the meteorological parameters because indoor air is not fully separated from the outdoor air flow and contaminants transportation. In this study, optical approach using spectral sensor was attempted to reveal the feasibility of wavelength and chromaticity values of reflected light from specific particles. From the analysis of reflected light of various particulate matters according to different liquid additives, parameter studies were performed to investigate which experimental conditions can contribute to the enhanced selective sensing of particulate matters. Five different particulate matters such as household dust, soil, talc powder, gypsum powder and yellow pine tree pollen were utilized and observed to elucidate the relationship between property of particulate matter and detected light spectrum. Applicable approaches to assist current particle matter sensors and improve the selective sensing were suggested.

Convolutional Neural Networks (CNNs) are largely hand-crafted, which leads to inefficiency in the constructed network. Various other algorithms have been proposed to address this issue, but the inefficiencies resulting from human intervention have not been addressed. Our proposed EvolveNet algorithm is a task-agnostic evolutionary search algorithm that can find optimal depth and width scales automatically in an efficient way. The optimal configurations are not found using grid search, instead evolved from an existing network. This eliminates inefficiencies that emanate from hand-crafting, thus reducing the drop in accuracy. The proposed algorithm is a framework to search through a large search space of subnetworks until a suitable configuration is found. Extensive experiments on the ImageNet dataset demonstrate the superiority of the proposed method by outperforming the state-of-the-art methods.

This research work was aimed at investigating and determining the depth resolution of a 500Mhz GPR Antenna. The survey was conducted in an open space at the Physics Department, College of science-KNUST. The MALA GPR equipment with 500MHz shielded Antenna in the common offset-mode was used to investigate the depth at which materials were buried. Concrete block, tree roots, plastic bottle with water, glass bottle and Electric wire were each buried in cavities with five different burial depths. The real depth of each material was measured both along and across the cavity and compared to their corresponding GPR measured depth. The comparison of the Real depth and the GPR depth showed almost identical depth measurements with a root mean square deviation of 0.028m. The implication of this is that the 500 Mhz GPR antenna can accurately locate and detect the position of buried materials in the subsurface at a depth within the range (0.20-0.66) m.

Depth maps produced by LiDAR based approaches are sparse. Even high-end LiDAR sensors produce highly sparse depth maps, which are also noisy around the object boundaries. Depth completion is the task of generating a dense depth map from a sparse depth map. While the traditional approaches focus on directly completing this sparsity from the sparse depth maps, modern techniques use RGB images as a guidance tool to resolve this problem. Whilst many others rely on affinity matrices for depth completion. Based on these approaches, we have sub-divided the literature into two major categories; traditional approaches and backbone-based approaches. The latter is further sub-divided into two-branch, and spatial propagation approaches. The two-branch approaches still have a sub-category named guided-kernel approaches. In this paper, for the first time ever we present a comprehensive survey of depth completion methods. We present a novel taxonomy of depth completion approaches, review and detail different state-of-the art techniques within each category for depth completion of LiDAR data, and provide quantitative results for the approaches on KITTI and NYUv2 depth completion benchmark datasets.

Three-dimensional (3D) imaging has attracted more and more interests because of its widespread applications, especially in information and life science. These techniques can be broadly divided into two types: ray-based and wavefront-based 3D imaging. Issues such as imaging quality and system complexity of these techniques limit the applications significantly, and therefore many investigations have focused on 3D imaging from depth measurements. This paper presents an overview of 3D imaging from depth measurements, and provides a summary of the connection between these the ray-based and wavefront-based 3D imaging techniques.

The RHAPS project was launched in 2019 with the major objective to identify specific properties of the fine atmospheric aerosol from combustion sources that are responsible for toxicological effects and can be used as new metrics for health-related outdoor pollution studies. In this paper, we present the overall methodology of RHAPS, and introduce the phenomenology and the first data observed. A comprehensive physico-chemical aerosol characterization has been achieved by means of high-time resolution measurements (e.g. number size distributions, refractory chemical components, elemental composition,) and low-time resolution analyses (e.g. oxidative potential, toxicological assays, chemical composition,…). Preliminary results show a high complexity in the relations observed, the link between air quality and toxicological endpoints being not obvious. We explore data from different points of view: source apportionment of PM1 and the role of source emissions on aerosol toxicity, the oxidative potential as a predictive variable for PM1 toxicity with focus on the secondary organic aerosol possessing redox-active capacity, exposure-response relationships for PM1, and air quality models to forecast PM1 toxicity. We provide a synthesis of results with the outlook to companion papers where data are analyzed in more detail.

Respiratory viral infections, including influenza, respiratory syncytial virus (RSV), and, more recently, the coronavirus disease 2019 (COVID-19) pandemic, continue to pose significant global health threats. Conventional treatments for these infections often face challenges such as limited efficacy, the emergence of drug-resistant strains, and the requirement for frequent administration. In recent years, nanobodies have emerged as a promising class of therapeutic agents due to their unique properties, including small size, high stability, and specific binding capabilities. This mini-review article focuses on the application of nanobodies as spray and aerosol particles for the treatment of respiratory viral infections. Furthermore, we highlight the remarkable efficacy of nanobodies in preclinical and clinical studies against respiratory viruses, including their ability to neutralize viral particles, inhibit viral replication, and modulate the host immune response. We discuss the potential advantages of using nanobodies as inhalable formulations, including their improved delivery to the respiratory tract, enhanced stability in aerosol form, and reduced systemic side effects. Additionally, we explore the various strategies employed to engineer nanobodies for optimal aerosol delivery, such as conjugation to carrier particles or formulation as dry powders. We also examine the potential challenges and limitations associated with the development of nanobody-based aerosol therapies, including production scalability, cost-effectiveness, and regulatory considerations.

During the COVID-19 pandemic face masks grew in importance as their use by the general population was recommended by health officials in order to minimize the risk of infection and prevent further spread of the virus. To ensure health protection of medical personal and other system relevant staff, it is of considerable interest to quickly test if a certain lot of filtering facepiece masks meets the requirements or if the permeability changes under different conditions. As certified penetrometers are rather expensive and were difficult to obtain during the COVID-19 pandemic, we describe two quite simple and cheap methods to quickly test the filter permeability based on an electronic cigarette. The first method uses a precision scale, the second method uses a light scattering detector to measure the filter penetration. To make sure these two methods yield reliable results, both were tested with freshly cut filter samples covering the range of approx. 7% to 60% permeability and compared to the results of a certified penetrometer. The comparison of the two methods with the certified penetrometer showed a good correlation and therefore allow a quick and rather reliable estimation of the permeability. Several examples about the use of faulty masks and the resulting health risks show that simple, fast, cheap and broadly available methods for filter characterization might be useful in these days.

Production and transport of reactive species through plasma-liquid interactions plays a significant role in multiple applications in biomedicine, environment, and agriculture. We experimentally investigated the transport mechanisms of hydrogen peroxide H2O2 and ozone O3, as the typical plasma species, into water. We measured the solvation of gaseous H2O2 and O3 in airflow into water bulk vs. electrosprayed microdroplets while changing the gas and water flow rates, applied voltage that determines the gas-liquid interface area, and treatment time. The solvation rate of H2O2 and O3 increased with the treatment time and the gas-liquid interface area. The total surface area of the electrosprayed microdroplets was larger than that of the bulk, but their lifetime was much shorter. We estimated that only microdroplets with diameters below ~ 40 µm could achieve the saturation by O3 during their lifetime, while the saturation by H2O2 was impossible due to its depletion from air. Besides the short-lived flying microdroplets, the longer-lived bottom microdroplets substantially contributed to H2O2 and O3 solvation in water electrospray. This study contributes to a better understanding of the gaseous H2O2 and O3 transport into water as a function of different parameters and will lead to design optimization of the plasma-liquid interaction systems.

A short review of the important studies was conducted to evaluate the potential of aerosol transmission of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The minimum size of droplets potentially carrying the SARS-CoV-2 was newly estimated and discussed in this review.

Nowadays a recognized need for accurate observations of atmospheric aerosols (AEs) and reactive gases (RGs) exists in the framework of regional, national and global near-surface networks based on permanent or mobile measurement stations. In this context, a paramount and not-trivial issue is related to the correct execution of continuous sampling of ambient air and its subsequent distribution to measurement analyzers hosted inside the stations. Sampling artifacts must be minimized for obtaining reliable pictures of ambient air composition. To respond to this need, a suite of novel “smart” and relatively low-cost systems for the continuous sampling of ambient air was developed in the framework of the Project I-AMICA (2012 – 2015, www.i-amica.eu). These systems were designed to execute AE and RG measurements according with WMO/GAW and ACTRIS recommendations and standard operation procedures. A particular attention was dedicated to the stabilization and control of the sampling flow rates and temperatures. The analysis of one full year of operations at the WMO/GAW regional station of Capo Granitola (GAW ID: CGR, Italy), allowed to conclude that these systems are effective in meeting the technical requirements for correct execution of AE and RG measurements

A new approach to the measurement with elastic lidar of depolarization produced by atmospheric aerosols is presented. The system uses two different telescopes: one for depolarization measurements and another for total-power measurements. The system architecture and principle of operation are described. The first experimental results are also presented, corresponding to a collection of atmospheric conditions over the city of Barcelona.

The Absorbing Aerosol Sensor (AAS) is carried on the Gao Fen 5B (GF-5B) satellite, which allows for measuring the solar backscatter radiation by the atmosphere in UV-VIS wavelength. AAS is an imaging spectrometer using CCD for capturing both continuous spectrum and the cross-track orientation with a 114° wide swath. The broad field-of-view provides daily global envelopment with a 4 km spatial resolution at the nadir. This paper mainly analyzed the initial working status of the instrument in orbit, including wavelength calibration, radiation calibration, detector performance, and product availability. Preliminary observations indicate that the AAS can monitor the absorbing aerosol like dust, biomass burning, volcano ash, and some pollution aerosol and can identify the aerosol events in China and other regions with high spatial resolution.

Extraordinary high aerosol contamination observed in the atmosphere over Kyiv city, Ukraine, during the March – April 2020 period. The source of contamination was the large grass and forest fires in the northern part of Ukraine and the Kyiv region. The level of PM2.5 load investigated using newly established AirVisual sensors mini-network in five areas of the city. The aerosol data from the Kyiv AERONET sun-photometer site analyzed for that period. Aerosol optical depth, Angstrom exponent, and the aerosol particles properties (particles size distribution, single-scattering albedo, and complex refractive index) were analyzed using AERONET sun-photometer observations. The smoke particles observed at Kyiv site during the fires in general correspond to aerosol with optical properties of biomass burning particles. The variability of the optical properties and chemical composition indicates that the aerosol particles in the smoke plumes over Kyiv were produced by different burning material and phases of vegetation fires at different time. The case of enormous PM2.5 aerosol contamination in Kyiv city reveals the need to accept strong measures for forest fire control and prevention in Kyiv region, especially in the north-west region where radioactive contamination from Chornobyl disaster is still significant.

Effects of the convection flow, atmospheric diffusivity and humidity on evolution and travel distances of exhaled aerosol clouds by an infected person are considered. The aim of this work is to evaluate the importance of aerosol transmission routes and the effectiveness of the 2-metre separation distance policy. A potential impact of use of face masks on the infection transmission rate, and an opportunity to reduce infection in hospitals, care homes and other public spaces by appropriate monitoring and filtering of air are also considered. The results obtained demonstrate that aerosol particles generated by coughing and sneezing can travel over 30 m. Modelling of the evolution of aerosol clouds generated by coughing and sneezing enables us to evaluate the deposition dose of aerosol particles in healthy individuals. For example, a person in a public place (e.g. supermarket or car park) can accumulate in the respiratory system up to 200 virus copies in 2 min time by breathing in virus laden aerosols. Wearing face mask considerably reduces the deposited load down to 2 virus copies per 2 min. The modelling also suggests that it should be possible to measure virus causing COVID-19 (SARS-CoV-2) within aerosol particles in hospitals and public places, e.g. care homes and supermarkets.

3D object reconstruction from depth image streams using Kinect-style depth cameras has been extensively studied. In this paper, we propose an approach for accurate camera tracking and volumetric dense surface reconstruction assuming a known cuboid reference object is present in the scene. Our contribu¬tion is three-fold. (a) We maintain drift-free camera pose tracking by incorporating the 3D geometric constraints of the cuboid reference object into the image registration process. (b) We reformulate the problem of depth stream fusion as a binary classification problem, enabling high-fidelity surface reconstruction, especially in the con¬cave zones of objects. (c) We further present a surface denoising strategy to mitigate the topological inconsistency (e.g., holes and dangling triangles), which facilitates the generation of a noise-free triangle mesh. We extend our public dataset CU3D with several new image sequences, test our algorithm on these sequences and quantitatively compare them with other state-of-the-art algorithms. Both our dataset and our algorithm are available as open-source content at https://github.com/zhangxaochen/CuFusion for oth-er researchers to reproduce and verify our results.

Low-cost RGB-D cameras are increasingly used in several research fields including human-machine interaction, safety, robotics, biomedical engineering and even Reverse Engineering applications. Among the plethora of commercial devices, the Intel RealSense cameras proved to be among the best suitable devices, providing a good compromise between cost, ease of use, compactness and precision. Released on the market in January 2018, the new Intel model RealSense D415 has a wide acquisition range (i.e. ~160-10000 mm) and a narrow field of view to capture objects in rapid motion. Given the unexplored potential of this new device, especially when used as a 3D scanner, the present work aims to characterize and to provide metrological considerations on the RealSense D415. In particular, tests are carried out to assess the device performances in the near range (i.e. 100-1000 mm). Characterization is performed by integrating the guidelines of the existing standard (i.e. the German VDI/VDE 2634 part 2 normative) with a number of literature-based strategies. Performance analysis is finally compared against latest close-range sensors, thus providing a useful guidance for researchers and practitioners aiming to use RGB-D cameras in Reverse Engineering applications.

Subsoil tillage loosens compacted soil for better plant growth, but promotes water loss, which is a concern in areas commonly irrigated. Therefore, our objective was to determine the physiological responses of high yield spring corn (Zea mays L.) to Subsoil tillage depth when grown in the western plain irrigation area of Inner Mongolia that leads to the best water use efficiency. The experiment during 2014 and 2015 used Zhengdan958 and Xianyu335 with three differing subsoil tillage depths (30, 40, or 50 cm) as trial factor and shallow rotary as a control. Subsoil tillage increased shoot dry matter accumulation, leading to a greater shoot/root ratio. Subsoil tillage helped retain greater leaf area index in each growth stage, increase the leaf area duration, net assimilation rate, and relative growth rate, with greater effects as tillage was deeper, effectively delaying the aging of the blade. Grain yields were increased by 0.7%–8.9% on average in subsoil tillage treatments compared to conventional soil treatment shallow rotary, Water use efficiency were increased by 1.93%–18.49% on average in subsoil tillage treatment compared to shallow rotary, resulting in net income increases by 2.24% to 6.97% compared to shallow rotary. Among the three different subsoil tillage depth treatment, the grain yield, water use efficiency, and net income is the best under the treatment of subsoil tillage depth of 50 cm.

Deep learning, specifically the supervised approach, has proved to be a breakthrough in depth prediction. However, the generalization ability of deep networks is still limited, and they cannot maintain a satisfactory performance on some inputs. Addressing a similar problem in the segmentation field, a scheme (f-BRS) has been proposed to refine predictions in the inference time. f-BRS adapts an intermediate activation function to each input by using user clicks as sparse labels. Given the similarity between user clicks and sparse depth maps, this paper aims at extending the application of f-BRS to depth prediction. Our experiments show that f-BRS, fused with a depth estimation baseline, is trapped in local optima, and fails to improve the network predictions. To resolve that, we propose a double-stage adaptive refinement scheme (DARS). In the first stage, a Delaunay-based correction module significantly improves the depth generated by a baseline network. In the second stage, a particle swarm optimizer (PSO) delineates the estimation through fine-tuning f-BRS parameters—that is, scales and biases. DARS is evaluated on an outdoor benchmark, KITTI, and an indoor benchmark, NYUv2 while for both the network is pre-trained on KITTI. The proposed scheme outperformed rival methods on both datasets.

Subseasonal-to-seasonal (S2S) weather forecasting has improved in recent years, thanks partly to better representation of physical variables in models. For instance, realistic initializations of snow and soil moisture in models yield enhanced predictability on S2S time scales. Snow depth and soil moisture also mediate month-to-month persistence of near-surface air temperature. Here the role of snow depth as predictor of temperature one month ahead in the Northern Hemisphere is probed via two causal pathways. Through the first pathway, snow depth anomalies in month 1 cause snow depth anomalies in month 2, which then cause temperature anomalies in month 2. This pathway represents the snow–albedo feedback, as well as cooling due to insulation, emissivity and heat loss. It is active from fall to summer, and its effect peaks in March/April in the midlatitudes and in May/June at high latitudes. A complementary second pathway, where snow depth anomalies in month 1 cause soil moisture anomalies in month 2, which then cause temperature anomalies in month 2 through soil moisture–temperature feedbacks, is only active in spring and summer. Its effect peaks later in the warm season than the effect of the first pathway. Geographically, snow depth mediates north of, and soil moisture south of, the areas with the highest temperature predictability from snow depth. These results indicate that the two pathways describe complementary physical mechanisms. The first pathway embodies month-to-month persistence of snow depth, and the second pathway represents melting of snow from one month to the next.

Estimating the infection risks in indoor environments comprises the assessment of the behavior of virus-laden aerosols, i.e. spreading, mixing, removal by air purifiers etc. A promising experimental approach is based on using non-hazardous surrogate aerosols of similar size, e.g. salt particles, to mimic the virus aerosol behavior. This manuscript addresses the issue how a successful transfer of such experiments can be accomplished. Corresponding experiments in two very different environments, a large community hall and a seminar room, with optional use of air purifiers in various constellations were conducted. While high particle concentrations are advantageous in terms of avoiding influence of background aerosol concentrations, it is shown that appropriate consideration of aggregation and settling are vital to theoretically describe the experimentally determined course of particle concentrations. A corresponding model equation for a well-mixed situation is derived and the required parameters are thoroughly determined in separate experiments independently. It is demonstrated that clean air delivery rates (CADR) of air purifiers determined with this approach may differ substantially from common approaches not explicitly taking into account aggregation.

The emergence of new SARSCoV-2 variants can affect vaccine efficacy, laboratory diagnosis and therapies already available, triggering interest in the search for antiviral agents for SARSCoV-2 infections. Ribavirin (RBV) is a broad-spectrum antiviral with demonstrated in vitro activity against multiple viruses, including SARSCoV-2. Methods. This retrospective study evaluated the dynamic and viral clearance of SARSCoV-2 in hospitalized adult participants (PTs) with COVID-19 pneumonia who received RBV aerosol within a compassionate use study. Was also assessed the impact of RBV on the clinical outcome and the mutational profile of SARSCoV-2. Results. The median RNA values measured in nine PTs included in the study de-creased from baseline to discharge (at BL, threshold cycle (Ct)=22.4, IQR 19.84-5.07; at discharge, Ct=27.92, IQR 26.43-36.11). Seven/9 PTs experienced a clinical improvement, while two PTs deceased during hos-pitalization. In PTs with a favorable outcome the virus clearance rate at discharge was 28.6%. The cumulative clearance rate was 71.4% within day 14th from discharge. A mutational pattern after RBV was detected in 3/5 PTs in whom was available whole genome sequencing. Conclusions. RBV may limit SARSCOV-2 replication resulting in a favorable clinical outcome. Ribavirin may also contribute to the mutational spectrum of SARSCoV-2.

In this study, a monoethanolamine aerosol growth model was developed to investigate the aerosol growth factor. Interactions among the internal conditions in an absorber were considered in this aerosol model. Additionally, an experiment was conducted to measure aerosol particle size, for collecting in-house validation data. Sucrose was used as the aerosol nuclei instead of sulfuric acid to prevent the corrosion of equipment used in the experiment. Experimental results showed that the outlet aerosol sizes increased to the same size regardless of the sucrose concentrations. The aerosol growth model was validated using the in-house experimental data. The aerosol growth model efficiently predicted the aerosol size. For investigating aerosol growth effects, particle number concentration was determined to be the primary factor affecting aerosol growth and amine emissions. When the particle number concentration increased, the aerosol size decreased, whereas the MEA emission increased.

Electronic designers nowadays are facing two challenging demands for various applications: miniaturization and increased functionality. To satisfy these seemingly opposed requirements, reducing the number of mounted components—and thus solder joints—in PCB designs becomes an attractive approach by directly printing passive components such as embedded resistors into the circuit. This approach can also potentially increase the reliability, such as “mean time between failures” (MTBF), while reducing the circuit board size. With its unique capabilities for non-contact precision material deposition, the Aerosol Jet® direct-write technology has been enabling additive manufacturing of fine-feature electronics conformally onto flexible substrates of complicated shapes. The CAD/CAM controlled relative motions between substrate and print head allows convenient adjustment of the pattern and pile height of deposited material at a given ink volumetric deposition rate. To date in the printed electronics industry, additively printing embedded polymer-thick-film (PTF) resistors has mostly been done with screen printing using carbon-based paste inks. Here we demonstrate results of Aerosol Jet® printed PTF resistors of resistance values ranging from ~50 W to > 1 kW, adjustable (among several variable parameters) by the number of stacked layers (or print passes with each pass depositing a fixed amount of ink) between contact pads of around 1 mm apart with footprint line typically < 0.3 mm. In principle, any ink material that can be atomized into fine droplets of 1 to 5 microns can be printed with the Aerosol Jet® system. However, the print quality such as line edge cleanliness can significantly influenced by ink rheology which involves solvent volatility, solids loading, and so on. Our atomizable carbon ink was made by simply diluting a screen printing paste with a compatible solvent of reasonable volatility, which can be cured at temperatures below 200 ^oC. We show that Aerosol Jet® printed overlapping lines can be stacked to large pile height (to reduce the resistance value) without significant increase of line width, which enables fabricating embedded resistors with adjustable resistance values in a limited footprint space.

Several long-term monitoring of aerosol datasets from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra/Aqua, Multi-angle Imaging SpectroRadiometer (MISR), Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) are used to derive the dust aerosol optical depth (DOD) in Central Asia based on the Angstrom exponent parameter and/or the particle shape. All sensors agree very well on the interannual variability of DOD. The seasonal analysis of DOD and dust occurrences identified the largest dust loading and the most frequent dust occurrence in the spring and summer, respectively. No significant trend is found during the research period in terms of both DOD and the dust occurrence. Further analysis of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) aerosol products on a case-by-case basis in most dust months of 2007 suggested that the vertical structure is varying in terms of the extension and the dust loading from one event to another, although dust particles of most episodes have similar physical characteristics (the particle shape and size). Our analysis on the vertical structure of dust plumes, the layer-integrated color ratio and depolarization ratio indicates a varied climate effect (e.g., the direct radiative impact) by mineral dust, dependent on the event being observed in Central Asia.

Since the financial crisis in 2008, the U.S. economy has weakened, and the world economy has slowly developed. As the world's leading country, the United States has used many methods to restore the economy. But it does work efficiently. However, there are many issues in developed countries such as domestic social, economic, immigration in the United States/United Kingdom; those are not optimistic. Developed countries have entered a dilemma. The neoliberalism financial system has been unable to move forward. Populists have pointed out that those problems have been causing by globalization. Under the leadership of the Brexit Referendum, President Trump has caused a wave of anti-globalization. Under a series of systems such as the China-US trade war and the US-Mexico border wall repairs, the anti-globalization trend is getting stronger. This article mainly analyzes the in-depth reasons and mechanism research of globalization and anti-globalization alternately—the data obtained from an international method performance study. The results show that anti-globalization is temporary, along with globalization. There are three main factors affecting globalization: the situation of the dominant country, natural disasters, and wars. After so much literature review, I believe that the United States' globalization is gradually weakening, and globalization may return to regionalization under the United States' opposition.

In this study we have investigated the effect of the addition of Nb2O5 (up to 5 mol%) on the structure and luminescent properties of ZnO-B2O3 glass doped with 0.5 mol % Eu2O3 by using of infrared (IR), Raman and photoluminescence (PL) spectroscopy. Physical properties as molar volume, oxygen packing density and glass transition temperature were determined using the results of differential thermal analyisis (DTA) and Archimedes principle for density. IR and Raman spectra revealed that niobium ions incorporate into the base zinc borate glass as NbO4 trtraherda and NbO6 octahedra. A strong red emission from the 5D0 level of Eu3+ ions was registered under near UV (392 nm) excitation using the sharp 7F0 - 5L6 transition of Eu3+. The integrated fluorescence intensity ratio R (5D0 → 7F2/5D0 → 7F1) was calculated to estimate the degree of asymmetry around the active ion, suggesting a location of Eu3+ in non-centrosymmetric sites. The higher Еu3+ luminescence emission observed in zinc borate glasses containing 1÷5 mol% Nb2O5 compared to the Nb2O5-free zinc borate glass evidences that Nb2O5 is suitable component for modification of host glass structure and improving the emission intensity.

Micro-combs [1-4] - optical frequency combs generated by integrated micro-cavity resonators – offer the full potential of their bulk counterparts [5,6], but in an integrated footprint. The discovery of temporal soliton states (DKS – dissipative Kerr solitons) [4,7-11] as a means of mode-locking micro-combs has enabled breakthroughs in many fields including spectroscopy [12,13], microwave photonics [14], frequency synthesis [15], optical ranging [16,17], quantum sources [18,19], metrology [20,21] and more. One of their most promising applications has been optical fibre communications where they have enabled massively parallel ultrahigh capacity multiplexed data transmission [22,23]. Here, by using a new and powerful class of micro-comb called “soliton crystals” [11], we achieve unprecedented data transmission over standard optical fibre using a single integrated chip source. We demonstrate a line rate of 44.2 Terabits per second (Tb/s) using the telecommunications C-band at 1550nm with a spectral efficiency – a critically important performance metric - of 10.4 bits/s/Hz. Soliton crystals exhibit robust and stable generation and operation as well as a high intrinsic efficiency that, together with a low soliton micro-comb spacing of 48.9 GHz enable the use of a very high coherent data modulation format of 64 QAM (quadrature amplitude modulated). We demonstrate error free transmission over 75 km of standard optical fibre in the laboratory as well as in a field trial over an installed metropolitan optical fibre network. These experiments were greatly aided by the ability of the soliton crystals to operate without stabilization or feedback control. This work demonstrates the capability of optical soliton crystal micro-combs to perform in demanding and practical optical communications networks.

Antibiotic-loaded bone cement (ALBC) plays a pivotal role in infection prevention and treatment related to musculoskeletal surgery. The release efficacy of antibiotics from ALBC is closely tied to its surface area, yet little is known about the effective release depth. To investigate the relationship between surface area, volume, and antibiotic elution, spheric ALBC specimens with consistent outer diameters but different internal metal sphere diameters were prepared. Two vancomycin doses were utilized in ALBC specimens with an outer diameter of 35 mm: high (4 g) and low (1 g). Each dosage group included five specimens containing embedded metal spheres with diameters of 15, 25, 29, 32, or 33 mm. The resulting shell-like ALBC specimens had thicknesses of 10 mm, 5 mm, 3 mm, 1.5 mm, or 1 mm, respectively. The specimens were immersed in sterile phosphate buffer solution, and antibiotic elution was measured at designated sampling times (1, 3, 6, 10, 24, 48, 72, and 168 hours). Methylene blue was employed to visualize penetration depth. Vancomycin elution did not display statistically significant differences between high- and low-dose groups. In both groups, specimens with 1 mm thickness exhibited a higher vancomycin release efficiency (high-dose group: 18560±5474 μg, 6.7%; low-dose group: 2017±419 μg, 2.6%), decreasing sharply in thicker ALBC specimens. Methylene blue penetration depth showed no apparent difference between high-dose and low-dose groups. ALBC thickness does not significantly impact antibiotic elution, while surface area and antibiotic dose exert notable effects. These in vitro findings offer potential applications in clinical treatments for musculoskeletal infections.

Biofilm serves as the residence for bacteria, wherein bacteria attach to surfaces and produce extracellular polymeric substances, including proteins, polysaccharides, and extracellular DNA. In recent years, biofilm reactors have gained increasing significance, playing a crucial role, for instance, in immobilizing heavy metals from waterways. This paper employs a bibliographic study to analyze the most important keywords and organizations in the field of biofilm reactors, identifying recent significant papers. Additionally, the paper discusses the opportunities for the future development of biofilm reactors. Through this study, a better understanding of key factors in biofilm reactor research is achieved, providing valuable guidance for future studies and applications in this field.

Ground penetrating radar (georadar, GPR), widely used in geology, archeology and road construction, is an efficient tool for searching and studying subsurface objects and structures. When planning GPR missions, it is necessary to predict the resolution of the device and the achievable probing depth. The article discusses the methods and results of assessing these characteristics of the Loza-V and Loza-N radars obtained in the course of archaeological and geographical expedition works.

Alkali-containing submicron particles were measured continuously during three months, including late winter and spring seasons in Gothenburg, Sweden. The overall aims were to characterize the ambient concentrations of combustion-related aerosol particles and to address the importance of local emissions and long-range transport for the atmospheric concentrations in the urban background environment. K and Na concentrations in the PM1 size range were measured by an alkali aerosol mass spectrometer (Alkali-AMS) and a cluster analysis was conducted. Local meteorological conditions and some other data sets were obtained, and back trajectory analyses and chemical transport model (CTM) simulations were included for the evaluation. The Alkali-AMS cluster analysis indicated three major clusters: 1) biomass burning origin, 2) mixture of other combustion sources, and 3) marine origin. Low temperatures and low wind speed conditions correlated with high concentrations of K-containing particles, mainly due to regional emissions from residential biomass combustion; transport of air masses from continental Europe also contribute to cluster 1. The CTM results indicate that open biomass burning in the eastern parts of Europe may have contributed substantially to high PM2.5 concentrations (and to cluster 1) during an episode in late March. According to the CTM results the mixed cluster (2) is likely to include particles emitted from different source types and no single geographical source region seems to dominate for this cluster. The back trajectory analysis and meteorological conditions indicated that the marine origin cluster was correlated with westerly winds and high wind speed; this cluster had high concentrations of Na-containing particles, as expected for sea salt particles.

Copernicus is Europe's space-based Earth monitoring asset, which consists of a complex set of systems that collect data from different sources: remote sensing satellites (RS) and in-situ sensors such as ground stations, airborne and marine sensors. This study was originally prepared for the needs of the Czech agricultural community, where we provided an in-depth analysis of articles related to Earth observation in precision agriculture. At a later stage, we extended this study by comparing the recommendations of the European EO4Agri project and scientific articles published in MDPI. We had two important objectives, one was to validate the results of the EO4Agri project and the other was to look for gaps in current research and community needs. To recognize the importance of using Sentinel 1 data, we also added a specific analysis of methods for data fusion of Sentinel 1 and Sentinel 2 data.

Infrared thermography has already been proven to be a significant method in non-destructive evaluation since it gives information with immediacy, rapidity, and low cost. However, the thorniest issue for the wider application of IRT is quantification. In this work, we proposed a specific depth quantifying technique by employing the Gated Recurrent Units (GRU) in composite material samples via pulsed thermography (PT). Finite Element Method (FEM) modeling provides the economic examination of the response pulsed thermography. In this work, Carbon Fiber Reinforced Polymer (CFRP) specimens embedded with flat bottom holes are stimulated by a FEM modeling (COMSOL) with precisely controlled depth and geometrics of the defects. The GRU model automatically quantified the depth of defects presented in the stimulated CFRP material. The proposed method evaluated the accuracy and performance of synthetic CFRP data from FEM for defect depth predictions.

Default aerosol extinction coefficient profiles are commonly used instead of measured profiles in radiative transfer modelling, increasing the uncertainties in the simulations. The present study aims to determine the magnitude of these uncertainties and contribute towards the understanding of the complex interactions between aerosols and solar radiation. Default, artificial and measured profiles of the aerosol extinction coefficient are used to simulate the profiles of different radiometric quantities in the atmosphere for different surface, atmospheric, and aerosol properties and for four spectral bands: ultraviolet-B, ultraviolet-A, visible, and near infrared. Case studies are performed over different areas in Europe and North Africa. Analysis of the results shows that under cloudless-skies, changing the altitude of an artificial aerosol layer has minor impact on the levels of shortwave radiation at the top and the bottom of the atmosphere, even for high aerosol loads. Differences up to 30% were however detected for individual spectral bands. Using measured instead of default profiles for the simulations leads to more significant differences in the atmosphere, which become very large during dust episodes (10 – 60% for actinic flux at altitudes between 1 and 2 km, and up to 15 K/day for heating rates depending on site and solar elevation).

Human exposure to infectious aerosols results a transmission of diseases, such as influenza, tuberculosis, and COVID-19. Most dental procedures generate a significant number of aerosolized particles, increasing transmission risk in dental settings. Since the generation of aerosols in dentistry is unavoidable, many clinics started using intervention strategies such as area-filtration units and extraoral evacuation equipment, especially under the relatively recent constraints of the pandemics. However, the effectiveness of these devices in dental operatories has not been studied. Therefore, the dental personnel's ability to position and operate such instruments efficiently is also limited. To address these challenges, we utilized a real-time sensor network for assessment of aerosol dynamics during dental restoration and cleaning producers with and without intervention. The strategies tested during the procedures were (i) local area high-efficiency particle air (HEPA) filters and (ii) extra-oral suction device (EOSD). The study was conducted at the University of Washington School of Dentistry using a network of thirteen fixed sensors positioned within the operatory and one wearable sensor worn by the dental operator. The sensor network provides time and space-resolved particulate matter (PM) data. Three-dimensional (3D) visualization informs aerosol persistence in the operatory. It was found that area filters did not improve the overall aerosol concentration in dental offices significantly. An average of 16% decrease in PM concentration was observed when EOSD equipment was used during the procedures. The combination of real-time sensors and 3D visualization can provide dental personnel and facility mangers with actionable feedback to effectively assess aerosol transmission in medical settings and develop evidence-based intervention strategies.

Growing concerns about the greenhouse effect, global warming, and adverse climate changes primarily stemming from carbon dioxide (CO2) emissions in traditional Portland cement (OPC) used in civil engineering construction, have prompted a shift toward eco-friendly alternatives like geopolymer cement (GPC). Over the last few decades, significant advancements have been made in developing environmentally sustainable pavement construction materials such as GPC to mitigate global CO2 emissions. The success of geopolymer cement (GPC) as an eco-friendly alternative to OPC has garnered attention for its potential to lower carbon emissions and enhance durability. This is attributed to the sustainable production method of GPC, where industrial cementitious waste materials (such as fly ash (FA), metakaolin (MK), mine tailings (MT), slag, etc.) are combined with an eco-friendly alkaline activator and water through the geopolymerization process. Numerous studies on geopolymer concrete indicate that, like OPC, GPC exhibits comparable mechanical properties, including strength, fire resistance, chemical resistance, and durability. This review explores the properties and applications of GPC as a sustainable material in pavement construction, exploring key studies and advancements in geopolymer technology, particularly its suitability for pavement applications. The assessment covers the mechanical properties, long-term performance, and environmental impact of geopolymer-based pavements, providing a comprehensive overview to inform policymakers, engineers, and researchers about the viability of geopolymer-based materials as a sustainable solution for modern pavement construction.

This research presents a comprehensive bibliometric and sentiment analysis of nanocomposite literature from 1990 to 2024. Employing cutting-edge computational methods, the study delves deep into the progression of microstructural characterization, electrical properties, and mechanical behaviors of nanocomposites. The analysis utilizes advanced Boolean search strategies from the Scopus database, ensuring a thorough extraction of thematic content. The results explore various themes and insights, shedding light on trends evident in the Scopus database, particularly the prominence of research on nanocomposite microstructure, electrical attributes, and mechanical performance. The paper also offers textual analytics and bibliometric data, showcasing critical collaborative efforts and influential studies. Significant discoveries encompass the evolution of research language, shifts in thematic focus, and global contributions, providing a comprehensive perspective on the current landscape of nanocomposite research and its dynamic evolution. Moving forward, the "State-of-the-Art and Gaps Extracted from Results and Discussions" section of the paper delves into the most recent advancements in nanocomposite research. It delves into various types of nanocomposites, with a particular emphasis on their microstructural characteristics, electrical properties, mechanical dynamics, and the application of nanocomposite films. This section identifies key research themes, traces historical progress, and highlights emerging trends while underscoring the significance of collaboration and the influence of pivotal studies that have shaped the field. Lastly, in the "Literature Review Guided by Artificial Intelligence" section, the paper introduces a revised approach for researching nanocomposites through AI-guided techniques. This approach prioritizes articles published in 2023 based on citation frequency. Here, the focus is on exploring the relationship between nanocomposites and their electrical properties, emphasizing their fundamental interactions and impact on electrical characteristics. Various nanocomposite systems are covered, highlighting their composition, structure, and functionality. Findings from recent studies are integrated to provide a comprehensive overview of the current state of knowledge in this area. Notably, the sentiment analysis, anchored by an average sentiment score of 0.638771, underscores a positive trajectory in academic discourse, emphasizing the growing recognition of the potential of nanocomposites. The bibliometric exploration maps the intellectual domain, emphasizing pivotal research themes and the influence of crosslinking time on nanocomposite attributes. While this study is thorough, it acknowledges its limitations and advocates for broader database inclusion in future research endeavors. This work elucidates the prevailing trends in nanocomposite research, emphasizing the indispensable role of computational tools in comprehending this vast wealth of information.

(1) Background: The intermediate-depth seismicity in the Vrancea region (Romania) is characterized by localized and persistent earthquake activity that culminates about two or three times in a century with the occurrence of a large event (M 6.5). Here we have revisited some important seismicity characteristics, using earthquake catalog data spanning two different time periods: 2005 – 2013 and 1960 – 2000. (2) Methods: we have determined the b-value of the frequency-magnitude distribution of earthquakes, using a maximum likelihood procedure, and estimated the parameter to quantify anomalous seismicity rate decreases and increases. (3) Results: by using data from the first period, we have confirmed the existence of a decreased b-value in the deepest part of the seismogenic zone; by using data from the second period, we have statistically confirmed the seismic quiescence that preceded the occurrence of the 1977 M7.4 Vrancea earthquake. (4) Conclusions: the decreased b-value has been interpreted either in terms of an increased lithostatic stress with depth or as an indicator of the depth range where the next major Vrancea earthquake may occur. The time variation of the seismicity parameter may reveal anomalous seismic quiescence and increased earthquake rates that may precede the occurrence of large earthquakes.

The scientific community has shown considerable interest in Industry 4.0 due to its capacity to revolutionise the manufacturing sector through digitalisation and data-driven decision-making. However, the actual implementation of Industry 4.0 within complex industrial settings presents obstacles that are typically beyond the scope of mainstream research articles. In this paper, a comprehensive case-study detailing our collaborative partnership with a leading medical device manufacturer is presented. The study traces their evolution from a state of limited digitalisation to the development of a digital intelligence platform that leverages data and machine learning models to enhance operations across a wide range of critical machines and assets. The main business objective was to enhance the energy efficiency of the manufacturing process, thereby improving its sustainability measures while also saving costs. The project encompasses energy modelling and analytics, Fault Detection and Diagnostics (FDD), renewable energy integration and advanced visualisation tools. Together, these components enable informed decision making in the context of energy efficiency.

The fluid flow field at the upper airways is highly complex due to the complex structure of the airway. The inhaled particle flow, the air streamline and the interaction of the continuum and discrete phase could significantly affect the transport behaviour of the inhaled particles. A range of analytical, mathematical and computational fluid dynamics (CFD) models analyzed the airflow and particle transport in different idealized and asymmetric airway models. A precise understanding of the continuum and discrete phase interaction in realistic human airways is missing, and this study aims to develop a CFD-DEM model for particle transport in realistic airways. This study uses the CFD model for the continuum phase and the discrete element method (DEM) for the discrete phase. A soft sphere approach is used for the interaction of the discrete phase. Proper validation is performed for particle transport efficiency. The CFD-DEM model analyzed the particle transport in an idealized and realistic airway model, and different methods are used to analyze the transport behaviour. During the particle-particle interaction, a stagnation point and a high-pressure zone are observed at the airway model's carinal angle. The numerical results report higher deposition efficiency (DE) for particle-particle interaction than without interaction. The flow field becomes highly complex with the spring constant values, and higher DE is found for high spring constant values. The spring dashpot friction-dshf method shows higher deposition at the upper part of the airways than other interaction methods. The findings of this study and more case-specific analysis would improve the knowledge of aerosol transport in airways and the health risk assessment of the patient.

Identifying dust aerosols from passive satellite images is of great interest for many applications. In this study, we developed 5 different machine-learning (ML) and deep-learning (DL) based algorithms, including Logistic Regression, K Nearest Neighbor, Random Forest (RF), Feed Forward Neural Network (FFNN), and Convolutional Neural Network (CNN), to identify dust aerosols in the daytime satellite images from the Visible Infrared Imaging Radiometer Suite (VIIRS) under cloud-free conditions on a global scale. In order to train the ML and DL algorithms, we collocated the state-of-the-art dust detection product from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) with the VIIRS observations along the CALIOP track. The 16 VIIRS M-band observations with the center wavelength ranging from deep blue to thermal infrared, together with solar-viewing geometries and pixel time and locations, are used as the predictor variables. Four different sets of training input data are constructed based on different combinations of VIIRS pixel and predictor variables. The validation and comparison results based on the collocated CALIOP data indicates that the FFNN method based on all available predictor variables is the best performing one among all methods. It has an averaged dust detection accuracy of about 81 %, 89 % and 85 % over land, ocean and whole globe, respectively, compared with collocated CALIOP. When applied to off-track VIIRS pixels, the FFNN method retrieves geographical distributions of dust that are in good agreement with on-track results as well as CALIOP statistics. For further evaluation, we compared our results based on the ML and DL algorithms to NOAA’s Aerosol Detection Product (ADP) , which is a product that classifies dust, smoke and ash using physical-based methods. The comparison reveals both similarity and differences. Overall, this study demonstrates the great potential of ML and DL methods for dust detection and proves that these methods can be trained on the CALIOP track and then applied to the whole granule of VIIRS granule.

Studies on the detection of layers with elevated black carbon aerosol (BC) concentrations and the formation conditions of these layers help understand the vertical distribution of BC concentrations, which will provide a basis for the assessment of climate effects and early BC pollution warnings. By using the Weather Research and Forecasting with Chemistry (WRF-Chem) numerical model, we performed a numerical simulation analysis on the authenticity of strong elevated BC concentration layers that were detected by an aircraft in the mixing layer over Harbin, China, which is a high-emission area, on a clear sunny afternoon in the early heating period of 2016. We then discuss possible problems and solutions when non-vertical paths are used to detect the vertical distribution of BC concentrations. Finally, we discuss the favorable conditions for the formation of elevated BC concentration layers by weak vertical flow. The results show that the horizontal variability of BC concentration in the mixing layer in the observation area in Harbin was sufficiently large during the measurement. This produced a false elevated layer, as detected by the aircraft during one round of spiral flight in the mixing layer. The root mean square of the horizontal distribution of BC concentration did not change with height in the mixing layer during the daytime, but it decreased with the thickness of the mixing layer and was higher in the mixing layer than in the free atmosphere. Therefore, the thinner the mixing layer, in which the vertical distribution of the BC concentration is detected in an inclined path, the stronger interference of the horizontal variability on the detected results. When a spiral flight detection path is used, the aircraft should fly at least two rounds in the mixing layer. In the daytime, due to strong turbulence in the mixing layer, weak vertical uplift is not favorable for the occurrence of elevated BC concentration layers in the mixing layer. In the nighttime, if weak vertical uplift is well matched with the BC concentration or its vertical gradient, elevated BC concentration layers can be formed in the atmosphere. Compared with upper layers far from the ground, nighttime elevated layers are easier to form in lower layers near the ground because high BC concentrations or large vertical gradients are more likely to occur in the lower layers. Both cases facilitate the occurrence of large vertical upward transport rates of BC.

The choice of parameters for laser beams used in the treatment of musculoskeletal diseases is of great importance. First, to reach high penetration depths into biological tissue and, secondly, to achieve the required effects on a molecular level. The penetration depth depends on the wavelength since there are multiple light-absorbing and scattering molecules in tissue with different absorption spectra. The present study is the first comparing the penetration depth of 1064 nm laser light with light of a smaller wavelength (905 nm) using high-fidelity laser measurement technology. Penetration depths in two types of tissue (porcine skin and bovine muscle) were investigated. The transmittance of 1064 nm light through both tissue types was consistently higher than of 905 nm light. The largest differences (up to 5.9%) were seen in the upper 10 mm of tissue, while the difference vanished with increasing tissue thickness. The higher penetration was most likely due to a combination of lower absorption in hemoglobin and less scattering at larger wavelengths, and not due to absorption in melanin. Overall, differences in penetration depth were comparably small and high peak power and short pulse lengths of laser light seem to be more important to efficiently treat deep musculoskeletal diseases.

Atmospheric turbulence characteristics are essential in determining the quality of astronomical images and implementing adaptive optics systems. In this study, the vertical distributions of optical turbulence at the Peak Terskol observatory (43.27472 ° N 42.50083 ° E, 3127 m a.s.l.) using the Era-5 re-analysis and scintillation measurements are investigated. For the closest reanalysis grid node to the observatory, vertical profiles of the structural constant of the air refractive index turbulent fluctuations Cn2 were obtained. The calculated Cn2(z) vertical profiles are compared with the vertical distribution of turbulence intensity obtained from tomographic measurements with Shack-Hartmann sensor. The atmospheric coherence length at the location of Terskol Peak was estimated. Using combination of atmospheric models and scheme paramaterization of turbulence, Cn2(z) profiles at Mt. Kurapdag were obtained. The values of atmospheric coherence length at the Peak Terskol are compared with estimated values of this length at the ten astronomical sites including Ali, Lenghu and Daocheng.

The optical response of bulk germanium sulfide (GeS) is investigated systematically using different polarization-resolved experimental techniques, such as photoluminescence (PL), reflectance contrast (RC), and Raman scattering (RS). It is shown that while the low-temperature (T=5 K) optical band-gap absorption is governed by a single resonance related to the neutral exciton, the corresponding emission is dominated by the disorder/impurity- and/or phonon-assisted recombination processes. Both the RC and PL spectra are found to be linearly polarized along the armchair direction. The low and room (T=300 K) temperature RS spectra consist of six Raman peaks identified with the help of Density Fuctional Theory (DFT) calculations: Ag1, Ag2, Ag3, Ag4, B1g1, and B1g2, which polarization properties are studied under four different excitation energies. We found that the polarization orientations of the Ag2 and Ag4 modes under specific excitation energy can be useful tools to determine the GeS crystallographic directions: armchair and zigzag.

Due to the major impact of climate change on the world's environment, political and economic systems, climate change mitigation has become a pressing priority for the international community and requires rapid action from the whole society. With the continuous advancement of artificial intelligence research, the integration of AI and other technologies makes it more and more used in the whole society. It has become a promising and innovative avenue in the field of climate change mitigation. This paper comprehensively considers the key role of AI technology in the field of climate change mitigation, such as climate modeling, the optimization of renewable energy systems, the development of intelligent solutions for sustainable practices and CSS technology, and affirms its future prospects. It also describes the challenges of AI in the field of climate change mitigation. As researchers, policymakers, and industries collaborate to refine AI methodologies and integrate them into practical applications, a concerted effort is required to establish ethical guidelines, transparency standards, and inclusive governance frameworks.

As the structure of horizontal gas wells is more complicated than that of vertical wells, the form of the liquid-carrying in different sections does not well agree. This makes it problematic to apply the widely used liquid-carrying theory of vertical gas wells in horizontal gas wells. Since the theory focused on the critical gas flow rate, it cannot quantify how much liquid it can remove. Simultaneously, it ignores the fact that the liquid-carrying ability of gas flow is limited and the producing liquid has a certain amount of flowing energy. In this study, the gas-liquid flow law of horizontal gas wells and wellhead drainage stability in different tubing depths were firstly studied. Then, the stability of gas drainage for different tubing depths was analyzed and confirmed. Given the disadvantages of the typical theory of critical gas flow, the mathematical model of different tubing depths for gas drainage is established for horizontal gas wells. The innovative model could take the energy of gas flow and liquid flow into account, and quantify the liquid volume which was removed. By verifying the model with the experiments, the result showed that the relative error of the model is generally less than 10%. It shows the research could provide a scientific basis for the analysis and liquid-carrying capacity for horizontal gas wells.

The change of tire groove depth will have a huge impact on tire performance, and the use of excessively worn tires is not conducive to the driving safety of automobiles. Tire groove depth detection has become one of the annual inspection items of automobiles, but the research on its related detection technology is still relatively backward. Based on the principle of monocular vision ranging (MVR), image processing technology and cloud platform technology, this paper develops a tire groove depth detection system, which realizes non-destructive detection of tire groove depth. In addition, the system uses the cloud platform to store the test results, and builds a multi-level data management system, allowing car owners to keep track of the tire wear status and historical changes, which is of great significance to ensuring driving safety.

The aim of this research work is to get a method for Galfenol electrodeposition thought which we can control the desired percentage of Ga versus Fe that has the maximum magnetostriction constant. Galfenol is electrodeposited on an optical fiber with an imbedded Fiber Bragg Grating (FBG) in its core. The final objective, that goes further of the scope of this research, is to get an optical magnetostrictive sensor. The device will sense magnetic field or current based on the combination of this magnetostrictive Galfenol, that will stress the optical fiber with the application of magnetic field or current and will change the reflected wavelength of the FBG as a consequence of the variation of the Bragg wavelength. We have developed a method of electrodeposition that allows controlling the density of current in the electrodeposition process in order to get the desired percentage of Ga and Fe in the alloy Ga X Fe 1-x. We have manufactured a set of samples with different parameters (as density of current and pH) and we have characterized these samples morphological, structural and magnetically. With this research we want to give to the scientific community the groundwork to design magnetostrictive optical sensors based on and FBG coated by giant magnetostrictive material. In this paper we have developed a method of covering the optical fiber controlling the composition of (Ga X Fe 1-X) in order to be able to get the maximum magnetostriction constant.

A 3D graphene foam made of interconnected multilayer graphene flakes was produced on optical fibres (OF) by laser-induced transformation of a polyimide (PI) film coated on the OF cladding. This material, known as la-ser-induced graphene (LIG), was explored in the electrochemical detection and quantification of dopamine (DA) at physiologically relevant concentrations in the presence of the most relevant interfering molecules in biological fluids, ascorbic acid (AA) and uric acid (UA). The measured limit of detection is 100 nM, the linear range is 0.1 to 5 μM and a maximum sensitivity of 5.0 µA µM−1 cm−2 was obtained for LIG decorated with Pt nanoparticles (NPs). Moreover, immunity to AA and UA interference and to fouling was attained by decorating the LIG elec-trode with Pt NPs and coating with Nafion. These figures of merit underlines the potential of these sensors for the quantification of physiologically relevant concentrations of DA in biological fluids, paving the way for the development of hybrid electrochemical/optical sensing actuating platforms in a lab-on-fibre configuration, with relevant applications in biomedical engineering. The advantages of this hybrid arrangement include the possi-bility of in-situ counterproofing, extended measuring ranges, photoelectrochemical detection and the probing of inaccessible places. This elegant approach can also provide a simple and cost-effective way to fabricate biomed-ical devices with extended functionality, such as medical optical probes with added electrochemical capabilities, optogenetics combined with local electrochemical detection, among others.

Optimal conditions for maximum efficacy of photoinitiated polymerization are theoretically presented. Analytic formulas are shown for the crosslink time, crosslink depth and efficacy function. The roles of photoinitiator (PI) concentration, diffusion depth and light intensity on the polymerization spatial and temporal profiles, for both uniform and non-uniform cases, are presented. For optimal efficacy, a strategy via controlled PI concentration is proposed, where re-supply of PI in high light intensity may achieve a combined-efficacy similar to low light intensity, but has a much faster procedure. A new criterion of efficacy based on the polymerization (crosslink) [strength] and [depth] is introduced. Experimental data are analyzed for the role of PI concentration and light intensity on the gelation time and efficacy.

We discuss a remote sensing system that is used to simultaneously detect range-resolved differential absorption LIDAR (light detection and ranging; DIAL) signals and integrated path DIAL signals (IP-DIAL) from aerosol targets for ranges up to 22 km. The DIAL/IP-DIAL frequency converter consists of an OPO pumped at 1064 nm to produce light at 1.6 μm and operates at 100 Hz pulse repetition frequency. The probe light is free space coupled to a movable platform that contains one transmitter and two receiver telescopes. Hybrid photon counting/current systems increase the dynamic range for detection by two orders of magnitude. Range resolved and column integrated dry-air CO2 and CH4 mixing ratios are obtained from line shape fits of CO2 and CH4 centered at 1602.2 nm and 1645.5 nm, respectively and measured at 10 different frequencies over ≈ 1.5 cm-1 bandwidth. The signal-to-noise ratios (SNR) of the IP-DIAL returns from cloud aerosols approach 1000:1 and the uncertainties in the mixing ratios weighted according to the integrated counts over the cloud segments range from 0.1 % to 1 %. The range averaged DIAL mixing ratios are in good agreement with the IP-DIAL mixing ratios at the 1 % to 2 % level for both CO2 and CH4. These results can serve as a validation method for future active and passive satellite observational systems.

Microbe laden air particles, known as bio-aerosols, are routinely generated, in clinical dentistry due to the operative instrumentation within a milieu rich in salivary organisms. As the major mode of transmission of SARS-CoV-2 appears to be airborne aerosols and droplets, there has been an intense focus on such aerosol generating procedures (AGP). As there has been no systematic reviews on the efficacy of bio-aerosol reducing measure in dentistry, the objective of this systematic review was to evaluate the literature on three major AGPs, rubber dam application, pre-procedural oral rinse, and high-volume evacuation (HVE) aimed at reducing dental bio-aerosols. Method: PubMed via Ovid MEDLINE, EBSCO host, Cochrane Library, and Web of Science databases between January 01, 1985, and April 30, 2020, were searched.Results: A total of 156 records in the English language literature were identified, of which 17 clinical studies with 724 patients were included in the final analyses. The eligible reviewed articles revealed the inadequacy of the afore mentioned three principal AGPs used in contemporary dental practice to minimise bio-aerosols. HVE appears to be the most efficacious method, although no single approach provides total elimination of bio-aerosols. Conclusion:This, the first systematic review on methods of controlling bio-aerosols in dental operatory settings, indicates that employing combination strategies of rubber dam, with a pre-procedural antimicrobial oral rinse, and HVE can significantly minimize bio-aerosols. As the quality of the currently available data on dental bio-aerosols are rather poor, further, controlled, multi-centre studies are essential to address this critical issue.