Unique Spatial Distribution Research Articles

Strong seasonality and unsuspected diversity of haptophytes explored by metabarcoding analysis in the Chinese seas

The haptophytes, are essential components of the marine pico- and nano-plankton but little is known about their diversity and abundance due to the small size. In this study, the taxonomic composition, geographical distribution, and seasonal variation of the haptophytes in the Bohai Sea, the Yellow Sea, and the East China Sea were investigated using DNA metabarcoding in April and October of 2021. A total of 623 and 3756 haptophyte amplicon sequence variants (ASVs) were obtained in spring and autumn, respectively. All currently described or detected haptophyte orders were retrieved, including several deep-branching novel environmental lineages with relative high abundance. The predominant groups were Chrysochromulina, Clade HAP 2-3-4-5, Phaeocystis, and Prymnesium in spring, and Chrysochromulina, Phaeocystis, and Emiliania/Gephyrocapsa Compelx in autumn. The richness and diversity showed seasonal variation, with higher alpha diversity occurred in autumn than that of spring. Different haptophyte taxa exhibited unique spatial distribution patterns and water temperature was significantly correlated with the observed community dissimilarities and was the most influential driving factor in both seasons. Our results highlight the high hidden diversity and seasonal variations of haptophytes in the Chinese seas.

Study on the spatial distribution characteristics of traditional villages and their response to the water network system in the lower yangtze river basin

Traditional villages hold significant historical and cultural value as the precious heritage of China’s agricultural civilization. Currently, against the backdrop of increasing urbanization and rapid expansion of urban construction land, the spatial patterns of traditional villages across various regions in China are being encroached upon and damaged, with protection pressures growing daily. As one of the important cradles of Chinese civilization, the Lower Yangtze River Basin (LYRB) has traditional villages closely linked with its water systems, forming a unique human-land relationship and spatial distribution pattern. However, influenced by the rapid urbanization process, the spatial patterns of traditional villages in this region also face a crisis, and the contradiction between protection and development is becoming increasingly prominent. How to balance this contradiction and ensure the reasonable protection and sustainable development of traditional villages has become an urgent issue to address. Therefore, this study focuses on the LYRB. Using ArcGIS tools and combined with mathematical analysis methods, the spatial distribution characteristics and essential influencing factors of traditional villages in this area were screened and analyzed. The objective was to examine the spatial structural relationship between traditional villages, four water system types, and nine sub-basin units, intending to reveal the unique interdependence between the water system and traditional villages in this area. This would provide scientific support for the formulation of scientific conservation strategies. The research results show that: (1) Traditional villages in The LYRB form two core clusters spatially and exhibit substantial spatial accumulation; (2) Water system characteristics are the main factors affecting the distribution of traditional villages; (3) In the LYRB, the spatial distribution of the nine sub-basins is closely related to the spatial distribution of traditional villages, resulting in typical regional spatial differentiation of traditional villages in this area. This study is based on a watershed perspective, and the results highlight the importance of the water system network in the development of traditional villages, revealing a unique spatial dependency relationship between traditional villages and the water network in the LYRB. In order to ensure the comprehensive protection of the traditional village system in this region, it is essential to adhere to the fundamental principles that govern its spatial configuration. A tripartite collaborative protection system based on the watershed should be formulated from the perspective of the overall distribution relationship between the water network and the traditional villages. This system would serve to protect the overall landscape, the water network pattern, and the traditional villages. Establishing an overall pattern view of integrating the water system network and the traditional villages is essential.

Community Group Purchasing of Next-Day Delivery: Bridging the Last Mile Delivery for Urban Residents during COVID-19

The rapid development of new retail and the impact of COVID-19 have catalyzed the blowout growth of community group purchasing. The emergence of community group purchasing collection and delivery points (CGPCDPs) has become a new way to solve the “last mile” problem of new retail delivery. Based on the point of interest (POI) data of CGPCDPs of Nansha District, Guangzhou City, this study advances our understanding by identifying unique operational models, service targets, and spatial distribution patterns of CGPCDPs, which differ significantly from traditional pick-up points (PPs). The conclusions are as follows: (1) Most CGPCDPs depend on wholesale and retail shops, and their main service targets are urban and rural communities, followed by industrial areas. (2) The distribution of CGPCDPs has apparent spatial differentiation. At the macro scale, it shows the characteristics of “central agglomeration and peripheral dispersion”. It is distributed along the “northwest-southeast” direction and presents a “dual-core multi-center” pattern. At the meso–micro scale, different built environments in developed areas of cities, villages in the city (ChengZhongCun), and rural areas show distinct distribution patterns. (3) The main influencing factors of their spatial distribution are population density, construction land, house price, supporting place, residence density, urban community, and road proximity.

Energy management enhancement of a smart home supplied by renewable energy system

Solar energy is a reliable and eco-friendly solution for power outages in Karbala, Iraq. This study presents a smart grid technology model for energy management in electrical systems, optimizing power schemes and economic benefits through a unique spatial distribution approach in Iraq, with the primary objective of ensuring consistent base loads for smart homes while achieving other economic goals. The algorithm’s effectiveness was tested in three different scenarios. The energy was supplied by the national grid and battery bank-powered base loads. Meteorological data, including temperature and solar radiation, was gathered from a station in Karbala city for testing and evaluation. The study found that energy consumption decreased by 85% in April, with solar energy accounting for 37% of the total consumption. Smart homes saved 48% of energy, reducing reliance on the grid to 15%, as well as the reduction of energy consumption reached up to 47% and 60% in January and July, respectively, with solar energy estimated at 14% and 26% in those months.

A lightweight spatially-aware classification model for breast cancer pathology images

Breast cancer is a prevalent malignant tumour with high global incidence. Its diagnosis relies primarily on the analysis of pathological breast images. Owing to the complex organisation of the tumour microenvironment, neural network models are essential as efficient classification tools in the field of pathological image analysis. This study introduced spatially-aware attention swift parallel convolution network (SPA-SPCNet), a lightweight and low-latency model for classifying breast pathologies. A novel module for multi-scale feature extraction was constructed using a depthwise separable convolution method. It focuses on the multi-scale features of pathological images to alleviate recognition problems caused by similar local features in breast cancer tissues. The module concatenates the convolutions of different kernels from three branches. Second, a lightweight dynamic spatially-aware attention module was introduced to integrate the visual graph convolutional architecture in a branch. This allowed the model to capture the spatial structure and relationships in image, enabling better handling of the unique spatial distribution relationship between breast cancer tissue structures. The other branch utilises a self-attention mechanism in the transformer. The module can dynamically adjust the attention of the model to different regions in the image, allowing it to focus on the key features of the complex spatial distribution of breast cancer tissue. This feature fusion method enabled the model to capture both global semantics and local details. Compared with existing lightweight models, the proposed model has advantages in terms of tissue structure classification accuracy, parameter quantity, floating-point operations, and real-time inference speed, providing a powerful tool for computer-aided breast pathological image classification.

Revealing hidden diversity and community dynamics of land snails through DNA barcoding: implications for conservation and ecological studies

IntroductionLand snails play a crucial role in maintaining ecosystem sustainability within their habitats. Therefore, understanding the characteristics of their communities is vital for ecological studies and the development of effective conservation strategies. In this study, land snail communities inhabiting the Hyrcanian forest were identified and the variations in their community composition along elevational gradients were investigated.MethodsSnail samples were collected from three distinct elevations in three different forest locations within the Hyrcanian area of Iran. This study utilized DNA barcoding to identify land snail species. By employing statistical analyses such as ANOVA and PERMANOVA, significant differences in the features of snail communities across different elevations were examined. Concurrently, soil samples were collected from each site to assess soil physicochemical parameters about snail presence.ResultThrough this comprehensive analysis, a total of 10 OTUs, were further classified into seven families, and nine genera were identified. Five of these genera had never been reported in the study region before. We observed a decline in OTU richness with increasing elevation; however, the maximum abundance of snails was found at higher elevations. CCA demonstrated that Ca, Mg, and moisture saturation predominantly shape snail community composition.DiscussionThe unique climatic conditions and spatial distribution of precipitation from lowlands to highlands, as well as from west to east, make the Hyrcanian forests an ideal case study area for understanding the dynamics of land snail communities. In summary, this study provides new insights into the land snail communities thriving in the Hyrcanian forests. The findings from our research can contribute to the development of effective conservation management strategies for forest ecosystems. By understanding the factors influencing the distribution and composition of land snail communities, we can make informed decisions to protect and preserve land snails and the balance they maintain within their habitats.

Rotation-invariant rapid TRISO-fueled pebble identification based on feature matching and point cloud registration

The Pebble-bed reactor (PBR) utilizing TRISO-fueled pebbles is a promising Gen-IV reactor design due to its inherent safety and thermal efficiency. Identification of pebbles exiting the core may provide IAEA with additional information enhancing PBR safeguards help validate software predicting pebble flow behavior and burnup, and optimize fuel usage strategies should granular fuel management be needed. We propose a rapid, accurate pebble identification method applicable to commercial PBRs. Our approach relies on the unique spatial distribution of TRISO particles associated with each pebble, which can be extracted through X-ray CT. We developed an algorithm to identify a single pebble from 100,000 pebbles and achieved 100% identification accuracy in 90,000 trials, with arbitrary rotations and high noise levels. Remarkably, the outermost TRISO particle positions within a 0.6-mm shell suffice for unique identification. With an average identification time of under 50s per pebble, our method is compatible with PBR operational demands.

Earthquake supercycles and fault interaction over the past 32 ka in the Lake Ebinur area, Xinjiang, China

Earthquake prediction and disaster assessment in tectonically active regions require a continuous and complete regional seismic archive, which is commonly difficult to obtain, especially for prehistoric records. Here, high-resolution analysis of the sedimentary sequence from Lake Ebinur in Xinjiang revealed a detailed history of environment evolution since 32 ka ago. Both the Cl content and ultrafine proportion revealed the changing climate: the climate was relatively dry with low lake-water volumes from 32 to 12 ka, while the climate became warmer and wetter since 12 ka. In addition, eight earthquakes were identified by comprehensive analysis of grain size and geochemical element proxies, showing more than two seismic supercycles, with gaps of ∼10.4 ka; these gaps are much larger than those inferred previously (∼4–7 ka). Notably, these seismic events exhibited a pattern of mutual transmittance between the BoA and Jinghenan faults. Such fault interaction can occur in the Lake Ebinur area because it is dominated by weak lithosphere in which strain is easily accumulated and released; the interaction can also be attributed to the unique spatial distribution and immature nature of both faults. Combined with trenching investigations, our high-resolution analysis of lacustrine sediments can reveal a complete history of tectonic activity, which can efficiently serve regional earthquake prediction and disaster assessment.

Anatomical location, sex, and age modulate adipocyte progenitor populations in perivascular adipose tissues.

Perivascular adipose tissue (PVAT) regulates vascular function due to its capacity to synthesize vasoactive products and its mechanical properties. PVATs most abundant cells are adipocytes, and their populations are maintained by the maturation of adipocyte progenitor cells (APC), which may play a pivotal role in the pathogenesis of cardiovascular diseases. However, the distribution of APC within PVAT depots, their potential variation in spatial location, and the influence of sex and age on their abundance remain unknown. We hypothesize that APC abundance in PVAT is affected by location, age, sex and that APC subtypes have specific spatial distributions. PVAT from thoracic and abdominal aorta, and mesenteric arteries, and AT from interscapular, gonadal, and subcutaneous depots from 13-week and 30-week-old females and males Pdgfrα-CreERT2 x LSL-tdTomato mice (n = 28) were analyzed. Abdominal aorta PVAT had fewer progenitors than mesenteric PVAT and gonadal AT. Aging reduced the abundance of APC in the thoracic aorta but increased their numbers in mesenteric PVAT. Females had more APC than males in mesenteric PVAT and gonadal AT depots. APC exhibited unique spatial distribution in the aorta and mesenteric PVAT where they localized neighboring vasa vasorum and arteries. APC subtypes (APC1, APC2, APC3, diff APC) were identified in all PVAT depots. Thoracic aorta PVAT APC3 were located in the adventitia while diff APC were in the parenchyma. This study identified variability in APC populations based on depot, age, and sex. The distinctive spatial distribution and the presence of diverse APC subtypes suggest that they may contribute differently to cardiovascular diseases-induced PVAT remodeling.

GES: A New Building Damage Data Augmentation and Detection Method Based on Extremely Imbalanced Data and Unique Spatial Distribution of Satellite Images

GES: A New Building Damage Data Augmentation and Detection Method Based on Extremely Imbalanced Data and Unique Spatial Distribution of Satellite Images

Viologen Guest-Mediated Luminescence Emission Tuning and Photochromic Behavior by a Series of Viologen@Zn-MOF Materials.

The encapsulation of various guest molecules into the pores of metal-organic frameworks (MOFs) to form hybrid materials has attracted significant attention due to their unique spatial distribution and certain preferential geometry of the guests inside the MOFs. This arrangement often results in the guests exhibiting unique physical and chemical properties due to their intramolecular interactions with the host. In this article, five viologen derivatives were introduced as guests in a Zn-MOF with different benzene ring lengths, resulting in the formation of host-guest three-dimensional (3D) MOFs. The five compounds exhibited guest-dependent emission wavelength, color, and excellent photochromic behavior upon ultraviolet (UV) light radiation due to the distinct electronic transfer and π···π stacking interactions between the viologen guests and the host framework. This study provides a host-guest strategy for designing color-tunable luminescent and highly sensitive photochromic materials.

Elucidating Interfacial Dynamics of Ti-Al Systems Using Molecular Dynamics Simulation and Markov State Modeling.

Due to their remarkable mechanical and chemical properties, Ti-Al-based materials are attracting considerable interest in numerous fields of engineering, such as automotive, aerospace, and defense. With their low density, high strength, and resistance to corrosion and oxidation, these intermetallic alloys and metal-compound composites have found diverse applications. However, additive manufacturing and heat treatment of Ti-Al alloys frequently lead to brittleness and severe formation of defects. The present study delves into the interfacial dynamics of these Ti-Al systems, particularly focusing on the behavior of Ti and Al atoms in the presence of TiAl3 grain boundaries under experimental heat treatment conditions. Using a combination of molecular dynamics and Markov state modeling, we scrutinize the kinetic processes involved in the formation of TiAl3. The molecular dynamics simulation indicates that at the early stage of heat treatment, the predominating process is the diffusion of Al atoms toward the Ti surface through the TiAl3 grain boundaries. Markov state modeling identifies three distinct dynamic states of Al atoms within the Ti/Al mixture that forms during the process, each exhibiting a unique spatial distribution. Using transition time scales as a qualitative measure of the rapidness of the dynamics, it is observed that the Al dynamics is significantly less rapid near the Ti surface compared to the Al surface. Put together, the results offer a comprehensive understanding of the interfacial dynamics and reveal a three-stage diffusion mechanism. The process initiates with the premelting of Al, proceeds with the prevalent diffusion of Al atoms toward the Ti surface, and eventually ceases as the Ti concentration within the mixture progressively increases. The insights gained from this study could contribute significantly to the control and optimization of manufacturing processes for these high-performing Ti-Al-based materials.

Interesting effects of harmonically scattered waves from 1D functionally graded nonlinear inclusions

The interaction of monochromatic elastic waves with nonlinear inclusions shows the presence of harmonically scattered waves. Challenges in obtaining theoretical solutions and limitations of conducting experiments to understand harmonic scattering of the nonlinear waves from functionally graded materials motivate us to conduct numerical experiments. Harmonic scattering of the elastic waves from highly local functionally graded nonlinear inclusions is exploited in this study to propose a novel building block of new nonlinear metamaterials that can effectively control harmonic responses. The simple, commonly observed, unique spatial distribution of the nonlinear parameters is proposed so that the area under the distribution remains the same for a constant-sized inclusion. Despite different spatial distributions, these functionally graded distributions show the same harmonic responses of both forward and backscattered waves during the interaction of monochromatic waves and one-way two-wave mixing. The amplitudes of all possible combinations of harmonics remain the same as long as the area under the spatially distributed nonlinear parameters curve, irrespective of the distribution curves. Reducing the area under the curve of the functionally graded nonlinear inclusion simply by reducing the maximum value of the functionally distributed nonlinear parameters, a decrease in the amplitudes of the harmonics is demonstrated.

Selective oxidation of p-phenylenediamine for blood glucose detection enabled by Se-vacancy-rich TiSe2-x@Au nanozyme

Nanozymes with enzyme-like characteristics have drawn wide interest but the catalytic activity and substrate selectivity of nanozymes still need improvement. Herein, Se-vacancy-rich TiSe2-x@Au nanocomposites are designed and demonstrated as nanozymes. The TiSe2-x@Au nanocomposites show excellent peroxidase-like activity and the chromogenic substrate p-phenylenediamine (PPD) can be selectively oxidized to compounds that exhibit an absorption peak at 413 nm that differs from that of self-oxidation or generally oxidized species, suggesting high catalytic activity and strong substrate selectivity. Theoretical calculations reveal that the PPD adsorption geometry at Se vacancies with an adsorption energy of −3.00 eV shows a unique spatial configuration and charge distribution, thereby inhibiting the free reaction and promoting both the activity and selectivity in PPD oxidation. The TiSe2-x@Au colorimetric system exhibits a wide linear range of 0.015 mM–0.6 mM and a low detection limit of 0.0037 mM in the detection of glucose. The blood glucose detection performance for human serum samples is comparable to that of a commercial glucose meter in the hospital (relative standard deviation < 6%). Our findings demonstrate a new strategy for rapid and accurate detection of blood glucose and our results provide insights into the future design of nanozymes.

Modelling the effect of 3D temperature and chemistry on the cross-correlation signal of transiting ultra-hot Jupiters: a study of five chemical species on WASP-76b

ABSTRACT Ultra-hot Jupiters are perfect targets for transmission spectroscopy. However, their atmospheres feature strong spatial variations in temperature, chemistry, dynamics, cloud coverage, and scale height. This makes transit observations at high spectral resolution challenging to interpret. In this work, we model the cross-correlation signal of five chemical species – Fe, CO, H2O, OH, and TiO – on WASP-76b, a benchmark ultra-hot Jupiter. We compute phase-dependent high-resolution transmission spectra of three-dimensional (3D) SPARC/MITgcm models. The spectra are obtained with gCMCRT, a 3D Monte-Carlo radiative-transfer code. We find that, on top of atmospheric dynamics, the phase-dependent Doppler shift of the absorption lines in the planetary rest frame is shaped by the combined effect of planetary rotation and the unique 3D spatial distribution of chemical species. For species probing the dayside (e.g. refractories or molecules like CO and OH), the two effects act in tandem, leading to increasing blueshifts with orbital phase. For species that are depleted on the dayside (e.g. H2O and TiO), the two effects act in an opposite manner, and could lead to increasing redshifts during the transit. This behaviour yields species-dependent offsets from a planet’s expected Kp value that can be much larger than planetary wind speeds. The offsets are usually negative for refractory species. We provide an analytical formula to estimate the size of a planet’s Kp offsets, which can serve as a prior for atmospheric retrievals. We conclude that observing the phase-resolved absorption signal of multiple species is key to constraining the 3D thermochemical structure and dynamics of ultra-hot Jupiters.

Analysis of Soil Pysical and Chemical Properties in Liangucheng National Reserve in Minqin, China

This study aimed to explore the basic characteristics of soil and improve the natural environment in arid desert areas. The study was conducted in the Liangucheng National Reserve in Minqin, Gansu, and SPSS, EXCEL and GIS software was used to analyze and process data. The semivariogram model and Kriging interpolation method were used to analyze the basic characteristics, mutual relationships, and spatial distribution patterns of the primary physical and chemical properties of the soil in the reserve, including the soil moisture content, conductivity, pH, organic matter, nitrogen, phosphorus, and potassium. The results show that the soil conditions in the reserve are poor, with low water content and nutrient content. The soil characteristics were correlated and were not substantially affected by soil pH and electrical conductivity. Additionally, the measured soil elements had a unique spatial distribution pattern and similarities in their spatial distribution patterns. The spatial correlation between total soil phosphorus and pH was strongest, and the northern part of the reserve, especially near Qingtu Lake, had the best soil conditions, and the central area had the worst soil conditions.

A new technical pathway for extracting high accuracy surface deformation information in coal mining areas using UAV LiDAR data: An example from the Yushen mining area in western China

Western China is the world’s major coal-producing area, accounting for 1/3 of global coal production. Large-scale underground coal mining has led to serious ground deformation that has unique spatial and temporal characteristics. However, there are obvious engineering limitations to using GNSS, InSAR, and other common measurement techniques for monitoring mining subsidence. In recent years, researchers have attempted to use UAV LiDAR to monitor subsidence in mining areas. Point clouds are obtained through periodic ground scanning. Surface subsidence information is extracted through the filtering, modeling, and superposition processes. Conventional point cloud processing usually produces subsidence models that are too noisy and only provide information on surface subsidence. This means that it is unable to capture the horizontal ground displacement accompanying subsidence in mining areas, which hinders the practical application of this technology. A local flat point extraction (LFPE) algorithm based on geomorphic features is proposed. The algorithm extracts flat surface point clouds from the scan data and calculates the precise subsidence value of the ground by superposition to facilitate deformation monitoring. The obtained subsidence volume is spatially interpolated based on the unique spatial distribution characteristics of the mining subsidence basin to generate the initial surface subsidence model. By denoising this model, we can obtain a fine surface subsidence model that avoids significant noise caused by non-ground point clouds participating in modeling and superposition in common processing methods. On this basis, we successfully extracted the horizontal displacement information accompanying subsidence by employing sub-pixel correlation using the surface feature images before and after subsidence. The proposed technical pathway was validated by applying it to a coal mining subsidence area in the Yushen mining area in western China. Results demonstrate that, compared to conventional treatments, the proposed subsidence modeling method using laser scanning point clouds improves monitoring accuracy by over 50% while also obtaining the necessary horizontal displacement information for engineering requirements. These findings confirm the efficiency and accuracy of the proposed method for acquiring 3D surface deformation in mining areas.

Different Characteristics and Drivers of the Extraordinary Pakistan Rainfall in July and August 2022

The unprecedented and long-lasting abnormal monsoon rainfall attacked Pakistan in the summer of 2022, causing severe flooding. This study investigated the sub-seasonal characteristics and mechanisms of this distinctively extreme precipitation event. The historical rainfall in July and August and extreme precipitation mainly occurred in northern Pakistan. Both the monthly rainfall in July and August 2022 and the extreme precipitation during the summer were far exceeding the historical record and involved unique spatial distribution. The rainfall in July 2022 is nationwide and mainly located in northern Pakistan, while the rainfall in August and extreme precipitation occurred in southern Pakistan. Different physical processes are responsible for the precipitation in July and August 2022. In July, the South Asian high (SAH) and Iranian high extended eastward. Meanwhile, the anticyclonic circulation anomalies occurred in northwestern Pakistan and the easterly winds enhanced in the south side of the Tibetan Plateau (TP), which strengthened water vapor transporting from the Bay of Bengal and cooperated with the cyclonic system over the Arabian Sea to enhance the precipitation over Pakistan. In August, the SAH further extended eastward and the Western Pacific Subtropical High extended westward to the TP. Meanwhile, the European blocking (EB) developed, and a deep trough appeared over northwestern Pakistan. This weakened the easterly flow along southern TP but enhanced the southerly flow accompanying the cyclone over the Bay of Bengal and the Arabian Sea, and thus guided the water vapor transporting to southern Pakistan and enhanced the precipitation. The extreme precipitation in July was mainly attributed to the unusually strong Indian monsoon, while the extreme precipitation in August was the result of a combination of the Indian monsoon and EB. The study provided important information about extreme precipitation in Pakistan, which will help policymakers take measures to deal with the effects of flooding.

Effect of transmission characteristics of femtosecond laser focusing on micro-/nanostructure morphology of titanium alloy

Various types of micro-/nanostructures can be fabricated by femtosecond laser irradiation on metal surfaces. It has received extensive attention and research because of its potential application value. In this paper, the effect of laser focusing position on the micro-/nanostructure formation on the surface of a titanium alloy (TC4) was systematically researched. The experimental results show that, in the process of femtosecond laser focusing, a spatial distribution of laser energy with a narrower beam center and a ring around the beam is formed in front of the geometric focus and the distribution of laser energy changes along the laser transmission direction. This property can affect the morphology of the micro-/nanostructure on the surface of irradiated materials. It is believed that the new spatial distribution of laser fluence caused by focusing is due to the nonlinear process of plasma defocus and laser self-focusing caused by multi-photon or tunnel ionization in front of the target by focusing the femtosecond laser. The discovery of the nonlinear characteristics of the focused femtosecond laser and the application of the unique energy spatial distribution to the surface morphology of the fabricated surface put forward a new idea for the direct fabrication of micro-/nanostructures via femtosecond laser, which has certain significance for the development of micro-/nanofabrication technology of femtosecond lasers.

3D single shot lensless incoherent optical imaging using coded phase aperture system with point response of scattered airy beams

Interferenceless coded aperture correlation holography (I-COACH) techniques have revolutionized the field of incoherent imaging, offering multidimensional imaging capabilities with a high temporal resolution in a simple optical configuration and at a low cost. The I-COACH method uses phase modulators (PMs) between the object and the image sensor, which encode the 3D location information of a point into a unique spatial intensity distribution. The system usually requires a one-time calibration procedure in which the point spread functions (PSFs) at different depths and/or wavelengths are recorded. When an object is recorded under identical conditions as the PSF, the multidimensional image of the object is reconstructed by processing the object intensity with the PSFs. In the previous versions of I-COACH, the PM mapped every object point to a scattered intensity distribution or random dot array pattern. The scattered intensity distribution results in a low SNR compared to a direct imaging system due to optical power dilution. Due to the limited focal depth, the dot pattern reduces the imaging resolution beyond the depth of focus if further multiplexing of phase masks is not performed. In this study, I-COACH has been realized using a PM that maps every object point into a sparse random array of Airy beams. Airy beams during propagation exhibit a relatively high focal depth with sharp intensity maxima that shift laterally following a curved path in 3D space. Therefore, sparse, randomly distributed diverse Airy beams exhibit random shifts with respect to one another during propagation, generating unique intensity distributions at different distances while retaining optical power concentrations in small areas on the detector. The phase-only mask displayed on the modulator was designed by random phase multiplexing of Airy beam generators. The simulation and experimental results obtained for the proposed method are significantly better in SNR than in the previous versions of I-COACH.