Atmospheric Factors Research Articles

Photochemical Production of Singlet Oxygen in Adirondack Long-Term Monitoring Lakes of Varying Browning Status.

Widespread browning of surface waters in boreal and temperate regions of the Northern Hemisphere has been documented through long-term monitoring of color or dissolved organic matter (DOM) over recent decades. While the ecological implications of browning have received considerable attention, its impacts on the photochemical production of reactive intermediates from DOM remain understudied despite their importance for biogeochemical processes and contaminant fate in sunlit surface waters. To address this gap, we investigated singlet oxygen (1O2) production in 37 lakes within the Adirondack Long-Term Monitoring (ALTM) program. Wavelet coherence tests confirmed the synchrony between dissolved organic carbon (DOC) and color as well as the time-scale-dependent influence of regional atmospheric and hydroclimatic factors on DOC dynamics in these lakes. Hydrogeological conditions of lake watersheds (e.g., hydrologic connectivity and surficial geology) and seasonal variations in DOM quality jointly shaped the spatiotemporal patterns of the apparent quantum yields of 1O2. Within the euphotic zone, depth-averaged steady-state concentrations of 1O2 were higher in lakes experiencing more intense browning, as operationally defined through trend analyses of long-term water chemistry data; however, the relevance of 1O2-mediated reactions depends on the time scales of photochemical transformation relative to lake flushing. Overall, our study provides an initial assessment of 1O2 production in relation to lake browning and highlights the need for long-term photochemical measurements for an improved assessment.

Stability of the Luminescent Properties of Nanosilicon Coated With Nitrogen Heterocyclic Carbene

ABSTRACTThe color cathodoluminescence of nanosilicon stabilized with organic ligands of different donor–acceptor nature was studied for the first time. The dependence of cathodoluminescence intensity and spectral composition on the dose of 18‐keV electron irradiation was obtained. For most of the samples studied, an increase in the intensity of cathodoluminescence lines associated with nanosilicon was observed at low radiation doses, while a significant decrease in intensities at high radiation doses was present. The nanosilicon (nc‐Si) sample, which was stabilized by nitrogen heterocyclic carbene (electron–donor nature), showed the best stability against atmospheric factors and resistance to electron irradiation.

Atmospheric Arc Discharge as a Fabrication Tool for Synthesizing Iron Nanoparticles Embedded into Carbon Nanosheets

Simple and reliable method was engaged to obtain densely-packed and easy-to-manipulate arrays of iron nanoparticles protected from the potential action of atmospheric factors, which are in demand for catalytic applications. For the purpose, atmospheric arc discharge was initiated in a discharge gap of 10 mm between stainless steel electrodes. The gap was filled with a mixture of micrometre-sized powders of graphite and iron. After passing a direct arc current of 140 A for 2 min, a significant change in the morphology and chemical composition of the initial materials was observed. After a positive polarity was supplied to a smaller electrode, carbon nanosheets with an average width of 200 mm and thickness of about 20 nm that host Fe nanoparticles with diameters mostly ranging from 10 to 40 nm were found. Moreover, the initial oxygen content of 18% wt. was reduced to just 4% wt., as measured in the synthesized nanocomposites.

Advanced modelling of the night sky background light for imaging atmospheric Cherenkov telescopes

Aims. A significant source of noise for imaging atmospheric Cherenkov telescopes (IACTs), which are designed to measure air showers caused by astrophysical gamma rays, is optical light emitted from the night sky. This night sky background (NSB) influences IACT operating times and their sensitivity. Thus, for scheduling observations and instrument simulation, an accurate estimate of the NSB is important. Methods. A physics-driven approach to simulating wavelength-dependent, per-photomultiplier-pixel NSB was developed. It included contributions from scattered moonlight, starlight, diffuse galactic light, zodiacal light, and airglow emission. It also accounted for the absorption and scattering of optical light in the atmosphere and telescope-specific factors such as mirror reflectivity, photon detection efficiency, and focal length. The simulated results were corrected for pointing inaccuracies and individual pixel sensitivities and were compared to data from the high energy stereoscopic system (H.E.S.S.) IACT array. The software package developed for this analysis will be made publicly available. Results. Validation against H.E.S.S. data shows small deviations from the prediction, which are attributable to airglow and atmospheric variability. Per-pixel predictions provide a good match to the data, with a relative 90% error range of [‒21%, 19%]. Compared to the existing standard modelling approach of assuming a constant background, which yields a relative 90% error range of [−64%, 48%], this represents a significant improvement.

Ensemble Learning-Based Soft Computing Approach for Future Precipitation Analysis

This study integrated the strengths of ensemble learning and soft computing to develop a future regional rainfall model for evaluating the complex characteristics of island precipitation. Soft computing uses the well-developed adaptive neuro-fuzzy inference system, which has been successfully applied in atmospheric hydrology and combines the features of neural networks and fuzzy logic. This combination enables artificial intelligence (AI) to effectively represent reasoning derived from complex data and expert experience. Due to the multiple atmospheric and hydrological factors that influence rainfall, the nonlinear interrelations among them are highly intricate. Nonlinear principal component analysis can extract nonlinear features from the data, reduce dimensionality, and minimize the adverse effects of data noise and excessive input factors on soft computing, which may otherwise result in poor model performance. Ultimately, ensemble learning enhances prediction accuracy and reduces uncertainty. This study used Tamsui and Kaohsiung in Taiwan as case study locations. Historical monthly rainfall data (January 1950 to December 2005) from Tamsui Station and Kaohsiung Station of the Central Weather Administration, along with historical and varied emission scenario data (RCP 4.5 and RCP 8.5) from three AR5 GCM models (ACCESS 1.0, CSIRO-MK3.6.0, MRI-CGCM3), were used to evaluate future regional rainfall trends and uncertainties through the method proposed in this study. The research findings indicate the following: (1) Ensemble learning results demonstrate that all examined general circulation models effectively simulate historical rainfall trends. (2) The average rainfall trends under the RCP 4.5 emission scenario are generally consistent with historical rainfall trends. (3) The exceedance probabilities of future rainfall during the mid-term (2061–2080) and long-term (2081–2100) suggest that Kaohsiung may experience precipitation events with higher rainfall than historical data during dry seasons (October to April of next year), while Tamsui Station may exhibit greater variability in terms of exceedance probabilities. (4) Under both the RCP 4.5 and RCP 8.5 emission scenarios, the percentage changes in future rainfall variability at Kaohsiung Station during dry seasons are higher than those during wet seasons (May to September), indicating an increased risk of extreme precipitation events during dry seasons.

Fast decomposition of typical endocrine disturbing compounds in microdroplets under sunlight irradiation in the presence of ozone.

Fast decomposition of typical endocrine disturbing compounds in microdroplets under sunlight irradiation in the presence of ozone.

Using thermal portraits to identify targets in conditions of high atmospheric noise

The article examines the problem of object identification based on thermal images in highly noisy atmospheric conditions, which is critical for various fields, including military applications, security, search and rescue operations, and industry. The primary focus is on analyzing modern methods for compensating for the effects of atmospheric factors such as fog, rain, dust, and temperature fluctuations, which significantly degrade the quality of thermal images. The study reviews key approaches to noise compensation, including image filtering techniques, mathematical heat transfer models, multispectral sensors, machine learning-based algorithms, and hybrid systems. Special emphasis is placed on In-Scene Atmospheric Correction and Kalman Filter Augmentation algorithms, which enable effective adaptation to changing conditions and ensure high accuracy in analysis. The main advantages and drawbacks of each method are discussed, with particular attention to their practical implementation.

Influence of Weather and Climate on the Spatial Distribution of Forest Fires in Indonesia: A Bibliometric Study

Abstract Forest and land fires in Indonesia represent a major environmental challenge, frequently associated with climatic and atmospheric events such as the El Niño Southern Oscillation (ENSO). This study utilizes a bibliometric methodology to examine 1,312 Scopus-indexed publications from 2000 to 2024, concentrating on the spatial and thematic distribution of research concerning fire incidents in Indonesia. The study employs bibliometric analysis based on a set of keywords, including regions and a number of weather and climate drivers, and also Latent Dirichlet Allocation (LDA) modeling. The analysis identifies ENSO as the primary atmospheric influence, especially in Kalimantan and Sumatra, where its interaction with IOD intensifies fire hazards. Through the LDA modeling, five principal study issues were discerned: data-driven fire monitoring, peatland fires, community-based fire management, air pollution and haze, and ecosystem consequences. Although Sumatra and Kalimantan receive predominant academic focus, areas such as Papua, Sulawesi, and Nusa Tenggara are less investigated, particularly due to lower occurence of forest and land fires. Based on this result, recommendations involve incorporating meteorological data into fire mitigation techniques and intensifying attention on localized atmospheric factors are importamt to enhance adaptive management of forest and land fires in Indonesia.

Variability and trends of atmospheric deposition, climate conditions, and radial tree growth in Romanian eLTER Sites

Atmospheric deposition plays a crucial role on forest ecosystems status, as it transports a range of micro- and macronutrients, along with pollutants, from the atmosphere to forest environment. As it’s well known, variations in climatic factors significantly influence tree growth. The amount of precipitation, which dissolves deposited elements and alters soil element concentrations, plays a determinate role in shaping tree growth. As a result, atmospheric inputs can be a substantial contributor to the annual nutrient supply required for tree growth. However, excessive nutrient and pollutant deposition can have negative effects on trees, soil quality, and water resources. Additionally, the combined impact of air pollution and climate change can suppress nutrient availability, soil moisture and finally, tree growth and forest productivity. This study evaluates the effects of atmospheric deposition and climatic factors, such as temperature and precipitation, on tree growth in four eLTER sites across Romania. It also examines the temporal variations of these parameters within these locations. The main objective is to analyse long-term monitoring data, i.e., radial growth of trees as an indicator of forest productivity in response to pollutants and atmospheric deposition. To achieve this, a quantitative assessment of atmospheric deposition flux has been carried out over the last decade by periodically collecting throughfall water in permanent research plots, followed by the determination of mineral ion concentrations. Radial tree growth was measured using band dendrometers. Principal Component Analysis was used to determine the relationships between tree growth, climate factors, and atmospheric deposition. The results indicate that, despite a decreasing trend in atmospheric deposition, they may still have a negative impact on tree growth. Furthermore, correlation matrix analysis of the studied parameters revealed that nitrate had the most significant influence on tree growth, followed by temperature, precipitation, and soil pH. Overall, preliminary results provide an overview of the temporal variability of atmospheric deposition across forest ecosystems in Romania.

Corrosion-wear performance evaluation of 8Cr4Mo4V-bearing steel with pit-corroded defects considering fractal dimensions

Abstract In the field of tribology research, most of the problem-oriented methods for evaluating corrosion-wear interaction behavior are complex and time-consuming. The present work aims to establish the correlation between corroded surface characteristic parameters and corrosion-wear coupling damage of 8Cr4Mo4V-bearing steels, and an object-oriented strategy for corrosion-wear properties estimation is proposed. The alternating corrosion-wear behavior of 8Cr4Mo4V-bearing steel is investigated by integrating salt spray tests with tribological experiments in three types of corrosive conditions, considering the effects of industrial atmosphere and haze particles. The evolution of corroded surface morphologies is determined by image analysis combined with fractal theory, among which the fractal dimension of corrosion pits (FDCP) is calculated using a box-counting algorithm on binarized images after edge detection. The influence of corroded surfaces and atmospheric corrosion factors on friction and wear is studied. Results show that corrosion defects exhibit significant fractal features, the FDCP is depended on damage degree of corroded surfaces. Owing to the corrosion-crush effect, the wear resistance of 8Cr4Mo4V-bearing steels is decreased significantly. The FDCP exhibits a robust positive correlation with the corrosion ratio, whereas it demonstrates a weak correlation with tribological performance indicators. A damage coefficient of corrosion defect (DCCD) is proposed to evaluate the corrosion-wear performance of 8Cr4Mo4V-bearing steels, which take into account the coupling effect in corrosion defects and surface morphologies. These research findings significantly contribute to assessing and controlling the corrosion-wear properties of 8Cr4Mo4V-bearing steels in marine atmospheric environments.

POLYURETHANE PROTECTIVE MATERIALS: VISCOELASTIC AND TRIBOLOGICAL PROPERTIES

In order to spread the practice of using polyurethanes previously developed by us as polyurethane anticorrosive coatings (PAC), in addition to their resistance to the action of various destructors. It is also important to resist deformational dynamic loads, which can lead to the destruction of adhesive bonds between the polymer and the surface to be protected, as well as mechanical loads, in particular abrasion. Studies of the PAC based on the blend of network polyurethane/aromatic linear polyurethane NPU/LPU 70/30 and aliphatic linear/aromatic network polyurethane APU/NPU 80/20, reproduced for the verification of the main properties showed that the PAC based on NPU/LPU70/30, APU/NPU 80/20 are characterized by high adhesion - their adhesive strength is less than a point, and have high cohesion indicators: 40.3/40.0 kg/cm2 respectively. The introduction of inorganic pigments increases these values to 40.3 and 43.7 kg/cm2, respectively. The thermal stability of both types of PM is estimated at 260 C, the addition of 5% inorganic pigment increases this figure to 270 C, also for both polymers. PACs are resistant to the action of abiotic destructors: distilled and sea water, ethyl acetate, diesel fuel, aviation gasoline, 20% solutions of H2SO4 and KOH, and are also resistant to the flow of complex atmospheric factor NPU/LPU70/30, APU/NPU80/20 retain strength by 82% / 95%, respectively. The introduction of inorganic pigment, 5%, increases the resistance to 115% / 99%. PACs are resistant to dynamic deformation loads, which is confirmed by the presence of damping properties of coatings at temperatures close to the temperatures of use of coatings - tan δ more than 0.1. The use of inorganic pigments increases this indicator - to 0.175. The produced polyurethanes are resistant to abrasion. At the application of a load during the test, which significantly exceeds the practice of using polymeric protective coatings, this value is 0.001 g/cm2 - 0.006 g/cm2. By analogy with building codes, the polymers obtained can be used under certain conditions (load) as protective polymer coatings with anti-slip properties - since their coefficient of friction μ > 0.5. In general, they can be used as matrices for obtaining various protective coatings using functional modifiers and fillers.

Temporal Analysis of Radio Refractivity Variation over Kaduna: Implications for Radio Wave Communication Systems

Study’s Excerpt:• Refractivity in Nigeria’s savannah is stable yearly (±13 N) but swings monthly (112 N) with wet/dry seasons.• Humidity, not temperature, drives refractivity peaks (391 N) in October rains, setting a new regional record.• ERA5 data is valid for West African refractivity, bridging ground data gaps for climate-based models.• Guides adaptive systems (antenna/power tuning) to boost telecom planning in Nigeria’s savannah zones.• Kaduna’s refractivity aligns with rainforest, not savannah, challenging assumptions on regional propagation.Full Abstract: Surface radio refractivity is a crucial parameter in studying radio wave communication as it quantifies the bending of electromagnetic waves by atmospheric factors. This study examines the temporal variations of this parameter in tropical savannah region of Kaduna, Nigeria, for a long time. Accurate measurements of temperature, atmospheric pressure, and relative humidity extracted from high-resolution meteorological data from the ECMWF ERA5 reanalysis dataset were used to perform this research. The radio refractivity is computed using ITU-recommended models integrating these variables to express radio refractivity in N-units, which is a global standard for values comparison. The analysis revealed that yearly mean refractivity remained notably stable, fluctuating between 340.0565 and 353.4296 N-units, a modest range of 13.3731 N-units across four decades. This stability points out how easily atmospheric conditions can be predicted in long-term communication planning in Kaduna. On the other hand monthly radio refractivity show high variability ranging from 279.0400 N-units in March 1990 to 391.5037 N-units in October 1997—a difference of 112.4637 N-units. This variability originated from the wet and dry seasons of the location of the study. Higher radio refractivity values during the rainy season indicate a sharp increase in water vapour pressure and humidity, while lower refractivity values mark the dry season. These results indicate the necessity of utilising local climate conditions when studying electromagnetic wave propagation and fill a critical gap in long-term refractivity research, especially in tropical savannah areas.

Contributing factors to aggressive incidents in correctional and forensic psychiatric care: a rapid evidence assessment

Purpose Aggression within secure settings poses considerable concern. This study aims to offer more recent considerations of factors, such as cultural and environmental, that contribute to the prediction of aggressive security incidents, focusing on a rapid evidence assessment (REA) of available literature since 2018. Design/methodology/approach Preferred Reporting Items for Systematic Reviews and Meta-Analyses (Moher et al., 2009) guidelines were used for this REA, taking guidance from a previous study (Ireland et al., 2019) for the development of search terms. Findings Twenty-three final studies were included in the REA. All studies were conducted in either a prison (n = 8), a psychiatric inpatient facility with involuntary or compulsory treatment (n = 7) or forensic secure services (n = 7), with one study looking at both a general inpatient psychiatric hospital and forensic services. The thematic analysis noted four main themes that were predictive of aggressive security incidents, these were inadequate living facilities and poor physical environment, institutional security levels predicting aggression, restricted movement and the lack of meaningful activities and ward atmosphere and staff factors impacting staff–client relationships and consequent aggression. Practical implications This REA adds value to understanding the current interplay between the living facilities, wider forensic environment and staff interaction in a forensic client’s aggressive behaviours. Originality/value This REA offers an updated reflection and understanding on the presentation of aggression in secure forensic environments.

Reconstruction of paleoclimatic changes in the Sebkha environment: A case study of Sebkha El-Guettiate (Southeast Tunisia)

This study investigates climatic variations and natural cyclostratigraphy in Sebkha El-Guettiate (Southeastern Tunisia) through a multidisciplinary approach. Using a 150 cm sediment core, the research combines geological and sedimentological analyses with statistical methods such as Principal Component Analysis (PCA), clustering, and spectral analysis, alongside analyses (pH and electrical conductivity) to reconstruct the paleoenvironmental history of the sebkha. Variability in particle-size fractions serves as the primary proxy for deriving cyclostratigraphic information. The results reveal dual climatic cycles with periodicities of approximately 2000, 1600, 1300, 1000, 800, 595, 324, and 166 years, with major cycles linked to solar activity (2000 and 1000 years), Atlantic Ocean internal forcing (1600 years), and oceanic thermohaline circulation (1300 and 800 years). Other periodicities likely reflect additional oceanographic and atmospheric factors. These findings provide valuable insights into past environmental conditions and climate-sedimentation interplay in arid regions, offering a reference point for future paleoenvironmental research in similar settings.

Projecting Daily Maximum Temperature Using an Enhanced Hybrid Downscaling Approach in Fujian Province, China

The rise in global temperatures and increased extreme weather events, such as heatwaves, underscore the need for accurate regional projections of daily maximum temperature (Tmax) to inform effective adaptation strategies. This study develops the CNN-BMA-QDM model, which integrates convolutional neural networks (CNNs), Bayesian model averaging (BMA), and quantile delta mapping (QDM) to downscale and project Tmax under future climate scenarios. The CNN-BMA-QDM model stands out for its ability to capture nonlinear relationships between Tmax and atmospheric circulation factors, reduce model uncertainty, and correct bias, thus improving simulation accuracy. The CNN-BMA-QDM model is applied to Fujian Province, China, using three CMIP6 GCMs and four shared socioeconomic pathways (SSPs) to project Tmax from 2015 to 2100. The results show that CNN-BMA-QDM outperforms CNN-BMA, CNNs, and other downscaling methods (e.g., RF, BPNN, SVM, LS-SVM, and SDSM), particularly in simulating extreme value at the 99% and 95% percentiles. Projections of Tmax indicate consistent warming trends across all SSP scenarios, with spatially averaged warming rates of 0.0077 °C/year for SSP126, 0.0269 °C/year for SSP245, 0.0412 °C/year for SSP370, and 0.0526 °C/year for SSP585. Coastal areas experience the most significant warming, with an increase of 4.62–5.73 °C under SSP585 by 2071–2100, while inland regions show a smaller rise of 3.64–3.67 °C. Monthly projections indicate that December sees the largest increase (5.30 °C under SSP585 by 2071–2100), while July experiences the smallest (2.40 °C). On a seasonal scale, winter experiences the highest warming, reaching 4.88 °C under SSP585, whereas summer shows a more modest rise of 3.10 °C. Notably, the greatest discrepancy in Tmax rise between the south and north occurs during the summer. These findings emphasize the importance of developing tailored adaptation strategies based on spatial and seasonal variations. The results provide valuable insights for policymakers and contribute to the advancement of regional climate projection research.

Comparative Analysis of Spline and Exponential Spline Filters for Gaussian Noise Reduction in Satellite Images: Introducing a Novel Nonlinear Filtering Approach

Satellite imagery often suffers from noise due to various atmospheric and sensor-related factors, which can significantly degrade image quality and hinder subsequent analysis. This article presents a comprehensive study on denoising satellite images utilizing spline interpolation and exponential spline techniques. We propose a novel nonlinear filter designed to enhance the denoising process, and we compare its performance against traditional spline-based methods. The evaluation metrics employed include the Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM), which are critical for assessing image quality. Our experimental results demonstrate that the proposed nonlinear filter consistently outperforms both spline interpolation and exponential spline methods, achieving superior PSNR and SSIM values. This study highlights the proposed filter's effectiveness in preserving image details while reducing noise and contributes to the ongoing advancements in remote sensing image processing techniques. The findings underscore the potential of nonlinear filtering approaches in enhancing the quality of satellite imagery for various applications.

Spatio-temporal patterns of evapotranspiration in the temperate Eastern German lowlands and its response to climate and land use change

Evapotranspiration (ET) is a key factor in the water and energy cycle, playing a critical role, especially in agricultural regions. The eastern German lowlands, with their continental climate, are one of the driest regions in Germany, yet agriculture is the dominant land use. This study investigates the spatio-temporal variability of ET and its response to climate and land use/land cover change (LUCC) using MODIS remote sensing products and in-situ measurements over the period 2000-2020. The results show a slight increase in the mean annual ET, with local increases of up to 7.2% in the southern and southeastern parts of Brandenburg. LUCC revealed a 22.2% decrease in grassland to cropland conversion, leading to a decline in ET of 21%, while conversion from grassland to cropland increased by 14.8%, resulting in a 10% increase in ET. The strongest relationship with ET was found for vapor pressure deficit (VPD), temperature (Temp), and relative humidity (RH), which contributed 25.2%, 30.9%, and 23.2%, respectively, to its total variability. In addition to atmospheric factors soil moisture (SM) also contributed 17.7% to ET, but only in grassland. LUCC played a minor role as 22% of the study area was under conversion. Consequently, climate change, represented by the temporal change of the climatic factors, was identified as the dominant driver of ET in the study area, accounting for 97% of its variability. Accordingly, these findings underscore the importance of Temp, RH, and SM in agricultural and water resource management.

Crowding and Atmospheric Experience in Theme Parks: A Comparison Study of Disneyland and Chimelong Park

ABSTRACT Albeit an attempt has been made to focus on the impact of crowding on tourist behavior and experience, few studies associate it with atmospheric factors. This article aims to assess the extent to which human crowding and spatial crowing have influenced the emotion, satisfaction, and behavioral intentions of tourists in Shanghai Disneyland and Zhuhai Chimelong Ocean Kingdom, whose themes and designed atmospheres differ from each other. The Mehrabian Russell model is the primary rationale. During the field trips, 295 and 410 valid samples were collected in the two cases. The results manifest that the two parks show no significant differences in spatial crowding and negative emotions. However, significant differences exist in human crowding, positive emotions, satisfaction, and behavioral intentions. The impact of human crowding at Chimelong is both positive and negative, whereas at Disneyland, both forms of crowding have exclusively negative effects. The scope and intensity of crowding’s effects depend on visitors’ expectations of the atmospheres and interactive experiences at the theme parks. This study enhances the understanding of crowding effects in relation to theme park atmospheres.

Optimal Choice of Laser Beam Diameter in Atmospheric Communication Networks of Distributed and Mobile Type

Relevance. The rapid development of the Internet of Things technology has led to an exponential increase in the number of different intelligent hardware connected to the Internet, which, in turn, has contributed to the emergence of a large amount of data to be transmitted over communication systems. Electromagnetic communication networks have insufficient potential to solve this problem, and optical information transmission systems via atmospheric channels are one of the real options for solving this problem. However, optical atmospheric communication systems are subject to the influence of atmospheric factors, i.e. due to absorption, scattering, and diffraction, the laser beam is weakened in power and broadens. In well-known works on the divergence of the beam, the question of the dependence of the maximum divergence of the beam on such indicators as the power of the laser source, the geometric length of the channel, and the wavelength of optical radiation is investigated. At the same time, in these works, one channel of the laser communication network is considered, and the question of choosing the diameter of the laser beam in all channels of the laser multichannel atmospheric network is not discussed. Purpose. The problem of optimal choice of the diameter of a laser beam in a multichannel atmospheric optical communication system of a distributed type is formulated, taking into account the divergence of the beam. The essence of the proposed solution, unlike well-known works that solve the optimization problem taking into account the influence of beam divergence, the solution to this goal covers both stationary and mobile versions of the network channels of the entire multichannel system. The task was solved by forming a single target functional and further optimizing it in order to identify the optimal relationship between the radius of the beam at the input of the channel receiver and the radius of the beam at the output of the radiator when applied to the atmospheric channel under consideration, taking into account the possibility of its broadening. It is shown that such an expansion of the diameter of the laser beam, according to the optimal law identified, makes it possible to achieve a maximum of the average intensity of the laser beam transmitted through the atmospheric channel to all receivers of the system. The conducted model studies of the proposed method for accounting for beam diameter broadening confirmed the possibility of obtaining an optimal ratio between the main indicators of a multichannel laser atmospheric network. Scientific novelty. A mathematical model for optimizing the choice of beam diameter in a multichannel laser atmospheric network has been developed. Theoretical and practical significance. Optimization of the proposed model made it possible to obtain an optimal ratio between the main indicators of a multi-channel laser atmospheric network of a distributed type, which can be used in the construction of such systems.

Pollen-induced asthma: a specific pheno-endotype of disease?

Asthma is a heterogeneous syndrome with a significant social and economic impact. While the knowledge of pheno-endotypes has advanced in severe asthma, little attention has been paid to the phenotypes of mild-moderate asthma. Along this line, a systematic review of the current literature on pollen-induced asthma was carried out, targeting the question whether it can be considered a specific phenotype of disease, with a focus on the role of pollen and its interplay with asthma. This article reports the first part of the review, which covered background information on the multiple atmospheric and environmental factors affecting pollen concentration, the molecular bases of pollen-induced allergenicity and the pathogenic effector circuits that sustain and amplify inflammatory signals in response to allergens in sensitized subjects.