Small Source Research Articles

On reconstruction of small sources from Cauchy data at a fixed frequency

This short paper is concerned with the numerical reconstruction of small sources from boundary Cauchy data for a single frequency. We study a sampling method to determine the location of small sources in a very fast and robust way. Furthermore, the method can also compute the intensity of point sources provided that the sources are well separated. A simple justification of the method is done using the Green representation formula and an asymptotic expansion of the radiated field for small volume sources. The implementation of the method is non-iterative, computationally cheap, fast, and very simple. Numerical examples are presented to illustrate the performance of the method.

In vivo variable and multi-day response from an insulin-releasing photoactivated depot

Previously we have demonstrated that light can be used to control the release of insulin in diabetic animals, followed by a reduction in blood glucose. This is accomplished using a photoactivated depot (PAD) of insulin injected into the skin, and irradiated by a small external LED light source. In this work for the first time we demonstrate dose–response, showing that we can vary insulin release and commensurate blood glucose reduction by varying the amount of light administered. In addition to demonstrating dose–response, we have shown multi-day depot response, with insulin being released on two different days from the same depot. The material used in these studies was CD-insulin, a form of insulin that has a highly non-polar cyclododecyl group attached, markedly reducing the solubility of the modified material, and allowing it to form a depot upon injection. Upon photolysis, the cyclododecyl group is removed, releasing fully native, soluble insulin. Variable response and multi-day response as demonstrated strongly support the potential utility of the PAD approach for the variable and extended release of therapeutic peptides.

A high-resolution inventory of ammonia emissions from agricultural fertilizer application and crop residue in Taiwan

The presence of ammonia (NH3) in the atmosphere has an impact on atmospheric nitrogen (N) deposition, air quality, and environmental systems. NH3 emissions in Taiwan are mainly driven by N fertilizer application and livestock operations, and their estimates are associated with considerable inaccuracies and uncertainties. In this study, a high-resolution (1 × 1 km) NH3 emissions inventory for agricultural fertilizers and crop residues in Taiwan was developed for 2016. The NH3 emissions were estimated based on detailed local activity data, such as seasonally varying planted areas and fertilizer application rates, and emissions from 88 different crops were resolved to better capture the seasonality and spatial heterogeneity. Emissions factors (EFs) are governed by ambient temperature, soil acidity and other factors. We further estimated NH3 emissions from two agricultural management scenarios, conventional farming (CF) and appropriate fertilization for crops (AF), to quantify the potential reduction in NH3 emissions due to government policy. The NH3 emissions from agricultural fertilizers and crop residues in Taiwan were approximately 25010 (20298.3) tons in 2016 for the CF (AF) scenario. Synthetic N fertilizer contributed 66.9% to the total emissions, followed by organic N fertilizer (32.1%), with crop residue (1.0%) being a relatively small source in the CF scenario. The NH3 emissions hotspots were located in the central to southern part of western Taiwan, where intense agricultural activities are conducted. The peak NH3 emissions occurred in spring and summer and were mainly associated with the cultivation of the first and second seasons of rice. We validated our estimated NH3 emissions with a satellite NH3 column, finding that the spatial-temporal variations in NH3 emissions from fertilizer application were in good coherency with the NH3 column concentration.

Design and characterisation of multi-mode interference reflector lasers for integrated photonics

InAs quantum dot ridge waveguide lasers comprising single-port multi-mode-interference-reflectors (MMIR) and single-cleaved reflectors are designed, fabricated, and characterised, to demonstrate capability for optoelectronic-integrated-circuits. Simulations of an MMIR show high values of fundamental mode reflectivity ( and good selectivity against higher order modes. Deep-etched MMIR lasers fabricated with 0.5 mm long cavities have a threshold current of 24 mA, compared to 75 mA for standard Fabry–Perot cleaved–cleaved FP-RWG lasers of the same length, both at 25 °C, and 56 mA compared to 102 mA at 55 °C. MMIR lasers exhibit stable ground state operation up to 50 °C and show promise as small footprint sources for integrated photonics.

Dense ultraweak fiber Bragg grating temperature detection method based on minimal gating unit demodulation

To solve the problems encountered by fiber Bragg grating temperature sensing technology, such as slow response speed and low detection accuracy in small heat source monitoring, a dense ultraweak fiber Bragg grating (UWFBG) temperature detection method based on minimal gating unit (MGU) demodulation is proposed and experimentally demonstrated. This method utilizes a dense UWFBG array with a spatial distance of 10 cm for linear temperature sensing, which is approximate in size to the heat source. Field programmable gate array/advanced RISC machine-embedded circuitry implements data transfer, analog-to-digital conversion, and 1 GSPS high-speed sampling. The MGU network is trained using a mixture of real and simulated data for the demodulation of the central wavelength. Parameters, such as batch size and hidden units, are explored to optimize the demodulation speed and accuracy of the overlapping spectra. Results show that the UWFBG detection temperature method based on the MGU network can demodulate 1000 sets of wavelength data in 2.7 s and obtains a root mean square error of less than 0.923 pm, thereby achieving a fast response to heat sources of 10 cm size and a detection temperature accuracy better than 0.34 °C.

Hierarchical Interaction between Food Diversity and Competition in Brackish Fish Species in South Korea

Information about the food sources for fish is important not only for predation and food competition, but also for the direct impact on organism interactions, relationships, and biodiversity within aquatic ecosystems. We analyzed the food sources of 21 fish species in 9 families of 6 orders based on the literature data from brackish ecosystems in South Korea to improve the understanding of the estuarine ecosystem. The food sources of the 21 fish species contained 173 families, 86 orders, 39 classes, and 22 phyla. The 21 fish species were classified into 4 groups using hierarchical analysis based on their food sources: Group 1 fishes mainly consumed Amphipoda; Group 2 fishes were zooplanktivores; Group 3 were omnivorous; and Group 4 consumed small food sources, such as Nematoda, Corophiidae, and Harpacticidae. The feeding competition index was relatively high within each group, but the competition index for Group 3, the omnivorous fishes, was low. Network analysis and hub scores represented the importance of food sources consumed by each fish species by showing the connections between the fish and their prey. Polychaeta, Actinopterygii, and Decapoda were the most commonly consumed food sources. Food source diversity was high for zooplanktivores (group 2). Additionally, the food contents of each fish species were classified into freshwater and marine sources for identifying the habitats of the food sources. Trophic level measuring values using the data were similar to the reported literature data. This study can be utilized for understanding estuarine ecosystems and identifying food relationships.

Late Pleistocene to Holocene Palaeohydrological History of the Thermal-Spring-Fed Lake Pețea (NW Romania) Revealed by Radiocarbon Dating and Complex Sedimentological Investigations

Understanding sedimentation processes in response to past hydrogeological and climatic changes and capturing millennial-scale variations is a key focus of lacustrine paleoenvironmental research. This study presents the first high-resolution chronology and sedimentary data for the small thermal-spring-fed Lake Pețea, NW Romania, and unravels the evolutionary history of the lake harboring a unique endemic fauna. Its small size and single source of water make it particularly sensitive to hydrological changes. In the recent past, over-exploitation of the thermal water has led to the complete drying up of the lake and the extinction of its fauna. Nevertheless, past spatio-temporal variation of environmental factors, in particular the fluctuation of lake levels and water temperature, must have had a significant impact on the survival and evolution of the endemic mollusk fauna. This fact makes this study particularly important. Based on our results, a three-stage sedimentary evolution occurred, mainly controlled by major climate-driven hydrological changes also seen in regional records, i.e., 17.5–14.5 ka shallow eutrophic lake, 14.5–5.5 ka oligotrophic carbonate-rich lake, and 5.5–0.5 ka shallow eutrophic lake. A major lowstand at 11.7–10.2 ka due to drier climate was followed by progressively rising water levels up to 5 ka followed by a drop. The main control on lake level fluctuations and sedimentary phases was the varying input of thermal water due to recurring increased/decreased recharge of the underground shallow karst water system. The driving factor of thermal water discharge was different during the Late Glacial than the Holocene. It was the warming of the climate at 14.5 ka cal BP and melting of regional ice sheets in addition to increased precipitation that created an oligotrophic lake by recharging the underground thermal water system. Conversely, during the Holocene, increasing/decreasing moisture availability driven by major climate forcings was in control of thermal water recharge, erosion, and fluctuating lake levels.

Sedimentary provenance in continental rifts: U–Pb detrital zircon, Nd and Sr isotopes and lithogeochemistry of the Eocene alluvial sandstones of the Resende Basin, SE–Brazil

Multiproxy analysis of detrital minerals is a powerful tool for unravelling the source-to-sink evolution of syn-rift sedimentary basins that represent important depositional settings during major rift events. The Cenozoic Resende half-graben in SE Brazil is a classic example of a syn-rift basin developed under oblique extension, which preserves evidence of tectonic episodes and palaeoclimatic conditions during the opening of the Atlantic. Sediment in the basin was sourced from the surrounding basement rocks, which to the faulted margin consists of older Proterozoic orthogranulites and orthogneisses, whilst to the flexural margin is characterised by Neoproterozoic passive margin paragneisses. Cretaceous intra-plate alkaline stocks crop out at the western edge and in the central-south basement of the basin and represent a distinct provenance fingerprint. This study uses new detrital zircons U–Pb ages combined with previously published elemental and Nd and Sr isotopic data to characterise the sedimentary provenance of Eocene alluvial deposits and to understand how sediment sourcing has changed throughout the evolution of the basin. U–Pb detrital zircon analyses from samples collected across the Resende Basin are presented herein. Samples yield a spread of detrital age spectra from the Archaean to the Cretaceous. Precambrian zircons range from ca. 3228 Ma to ca. 542 Ma. Cretaceous zircons yield ages between ca. 138 Ma and ca. 67 Ma. The sediment source location is interpreted by comparing the yielded detrital zircon spectra with the age spectra of zircons from the basement rocks. The dominance of detrital zircons yielding ages of ca. 1500 Ma and ca. 1000 Ma is interpreted to be sourced from the Neoproterozoic basement rocks to the flexural border of the half-graben. Cretaceous zircons from samples with whole rock εNd40Ma > −10 are found in both the western and eastern portions of the half-graben but not in the central portions. It is interpreted that an along-axis fluvial system was responsible for a small increase in the compositional maturity of the Resende sandstones from west to east, resulting in the progressive dilution of Cretaceous alkaline igneous detritus along the basin axis. Preserved metamorphic rims in zircon grains indicate low transport abrasion, suggesting that Cretaceous zircons in the eastern depocentre could be associated with other small proximal sources. U–Pb zircon analyses and Nd and Sr isotopes provide reliable insights regarding sediment provenance and transport processes, whilst element geochemistry supplies evidence for hydraulic sorting effects. Consequently, the data represents a more robust estimation of the provenance patterns of the Resende Basin, showing chemical and geochronological differences that support the division of the basin into three depocentres (western, central, and eastern) connected by a longitudinal fluvial system sourced mostly by sediments coming from the south-western flexural border. This study highlights the usefulness of using multiple provenance proxies to unravel the complex development of rift basins, assessing multiple source terrains and the variable degrees of mixing in sedimentary basins.

Lunar active seismic profiler for investigating shallow substrates of the Moon and other extraterrestrial environments

To investigate the structures and properties of shallow material in extraterrestrial environments, we have developed a lunar active seismic profiler (LASP), which integrates active seismic sources and receivers in a short (~1 m) array that can be deployed on a rover. The small active source generates a chirp waveform that sweeps over a wide frequency range (20–250 Hz). The receivers are coupled to the ground by their own weight, but nevertheless deliver acceptable performance. We improve the signal-to-noise ratio of the seismic signal by stacking waveforms, enabling a minimal source to support the exploration of geological substrates. By processing shot gather of the LASP data, we calculated a dispersion curve of surface waves and obtained an accurate S-wave velocity profile from surface to 1 m depth. The results suggest that regions with even small amounts of subsurface ice (~0.5 wt%) can be identified in LASP results by their anomalously high S-wave velocity. Field experiments demonstrate that the LASP can support estimates of 3D S-wave velocity distributions and the identification of a buried geological boundary. The LASP also detected different degrees of compaction at the experimental site. If two rovers carry these profilers, or if a single rover combines one with a separately deployed receiver or active seismic source, seismic refraction and seismic reflection analyses can be conducted simultaneously in addition to surface wave analyses. These seismic surveys for longer-offset data achieve the exploration of deeper substrates in extraterrestrial settings such as the Moon, Mars, and other solid bodies.

Green and facile synthesis of carbon encapsulated Fe3N nanospheres grown on N-doped porous carbon nanosheet as an excellent anode material

The development of iron nitride anode materials is greatly impeded by their traditional synthetic methods. In this work, carbon encapsulated Fe3N nanospheres grown on N-doped porous carbon nanosheet is successfully prepared by a green, facile and controllable approach. Only a small nitrogen source is needed in the synthetic process by in-situ nitrogenization. The Fe3N nanospheres are coated by carbon and uniformly adhered to N-doped porous carbon nanosheet, which prominently mitigates the variation of volume and elevates the electrochemical reaction kinetics. The feature is conducive to realizing a long life and brilliant rate performance. As an anode for lithium-ion batteries, a high discharge capacity of 484 mA h g−1 is delivered after 600 cycles at 2 A g−1. Extensive impact is brought by this study for the preparation and application of metal nitride materials.

Underwater Small Target Detection Based on YOLOX Combined with MobileViT and Double Coordinate Attention

The underwater imaging environment is complex, and the application of conventional target detection algorithms to the underwater environment has yet to provide satisfactory results. Therefore, underwater optical image target detection remains one of the most challenging tasks involved with neighborhood-based techniques in the field of computer vision. Small underwater targets, dispersion, and sources of distortion (such as sediment and particles) often render neighborhood-based techniques insufficient, as existing target detection algorithms primarily focus on improving detection accuracy and enhancing algorithm complexity and computing power. However, excessive extraction of deep-level features leads to the loss of small targets and decrease in detection accuracy. Moreover, most underwater optical image target detection is performed by underwater unmanned platforms, which have a high demand of algorithm lightweight requirements due to the limited computing power of the underwater unmanned platform with the mobile vision processing platform. In order to meet the lightweight requirements of the underwater unmanned platform without affecting the detection accuracy of the target, we propose an underwater target detection model based on mobile vision transformer (MobileViT) and YOLOX, and we design a new coordinate attention (CA) mechanism named a double CA (DCA) mechanism. This model utilizes MobileViT as the algorithm backbone network, improving the global feature extraction ability of the algorithm and reducing the amount of algorithm parameters. The double CA (DCA) mechanism can improve the extraction of shallow features as well as the detection accuracy, even for difficult targets, using a minimum of parameters. Research validated in the Underwater Robot Professional Contest 2020 (URPC2020) dataset revealed that this method has an average accuracy rate of 72.00%. In addition, YOLOX’s ability to compress the model parameters by 49.6% efficiently achieves a balance between underwater optical image detection accuracy and parameter quantity. Compared with the existing algorithm, the proposed algorithm can carry on the underwater unmanned platform better.

Assessment of the Measures Implemented in Bulgarian Legislation to Reduce the Content of Nitrates in Groundwater Used for Public Water Supply

Summary The article analyzes the application of the current documents related to reducing nitrate pollution of groundwater bodies used for public water supply in the Pleven administrative region. The requirements of the European legislation are fully implemented in the Bulgarian legislation, but the legislative measures have not led to quick and permanent results, i.e., small drinking water sources contaminated with nitrates still exist. Special attention should be paid to the diffusive sources of pollution (mineral fertilization of soils) since they are of the most significant importance in groundwater contamination with nitrates. For settlements with permanently elevated nitrate content (over 50 mg/L), it is necessary to consider the application of an individual approach in dealing with this long-standing problem: changing the water source, mixing the water from two neighboring water sources or implementing specific purification methods (biological denitrification, ion exchange resins, etc.). We analyzed the data from the monitoring of drinking water carried out by the Regional Health Inspectorate – Pleven and found that in the Pleven region, there are 17 towns or villages (out of a total of 123) for which some of the listed measures should be foreseen. The district’s relative share of the exposed population is 3.2%, comparable to the country’s exposed population for 2004-2007.

Takeoff of a 2.1 g Fully Untethered Tailless Flapping-Wing Micro Aerial Vehicle With Integrated Battery

Insect-scale micro-aerial vehicles (MAV) are becoming increasingly important for sensing and mapping spatially constrained environments. However, achieving untethered flight powered by a small and lightweight on-board energy source remains a challenge. In this study, we successfully demonstrated the untethered takeoff of a flapping-wing MAV powered by a commercially available LiPo battery for a short duration without stability control. By incorporating a high-efficiency direct-drive piezoelectric actuator, and an optimized control circuit for high-impedance-width modulation and charge recovery, this electronics configuration realizes over 5 min of practical operation with a thrust of 1.5 times its own weight, while offering wireless communication capability and sensors for attitude estimation. Our MAV has a total mass of 2.1 g, which is an eight-fold reduction compared to the lightest battery-powered tailless flapping-wing MAV currently available, making this the first report of a battery-powered tailless flapping-wing MAV with insect-scale weight.

Crowdfunding as a Financing Alternative for Entrepreneurial Ventures

Abstract Entrepreneurs often use various sources of financing to finalise an entrepreneurial idea. Crowdfunding on specialised internet platforms is an alternative method for collecting funds from several small sources for business investments and projects. The biggest difference between crowdfunding and other forms of financing is that crowdfunding uses smaller amounts of money from many investors interested in a business idea. Crowdfunding has been globally known for over a decade, and in Croatia, the interest has been growing for several years. The paper aims to demonstrate the importance and potential of crowdfunding, which, as a collective micro-investment of citizens, can serve as an alternative funding source for entrepreneurial ventures. The paper presents the research results conducted in Croatia based on the data collected through survey research. The paper investigates the knowledge and familiarity with the term and motives for investing through crowdfunding platforms.

MFUnetr: A transformer-based multi-task learning network for multi-organ segmentation from partially labeled datasets

As multi-organ segmentation of CT images is crucial for clinical applications, most state-of-the-art models rely on a fully annotated dataset with strong supervision to achieve high accuracy for particular organs. However, these models have weak generalization when applied to various CT images due to the small scale and single source of the training data. To utilize existing partially labeled datasets to obtain segmentation containing more organs and with higher accuracy and robustness, we create a multi-task learning network called MFUnetr. By directly feeding a union of datasets, MFUnetr trains an encoder-decoder network on two tasks in parallel. The main task is to produce full organ segmentation using a specific training strategy. The auxiliary task is to segment labeled organs of each dataset using label priors. Additionally, we offer a new weighted combined loss function to optimize the model. Compared to the base model UNETR trained on the fully annotated dataset BTCV, our network model, utilizing a combination of three partially labeled datasets, achieved mean Dice on overlapping organs: spleen + 0.35 %, esophagus + 15.28 %, and aorta + 8.31 %. Importantly, without fine-tuning, the mean Dice calculated on 13 organs of BTCV remained + 1.91 % when all 15 organs were segmented. The experimental results show that our proposed method can effectively use existing large partially annotated datasets to alleviate the problem of data scarcity in multi-organ segmentation.

Using a deep neural network to detect methane point sources and quantify emissions from PRISMA hyperspectral satellite images

Abstract. Anthropogenic emissions of methane (CH4) have made a considerable contribution towards the Earth's changing radiative budget since pre-industrial times. This is because large amounts of methane are emitted from human activities, and the global warming potential of methane is high. The majority of anthropogenic fossil methane emissions to the atmosphere originate from a large number of small (point) sources. Thus, detection and accurate, rapid quantification of such emissions are vital to enable the reduction of emissions to help mitigate future climate change. There exist a number of instruments on satellites that measure radiation at methane-absorbing wavelengths, which have sufficiently high spatial resolution that can be used for detecting plumes of highly spatially localised methane “point sources” (areas on the order of m2 to km2). Searching for methane plumes in methane-sensitive satellite images using classical methods, such as thresholding and clustering, can be useful but is time-consuming and often involves empirical decisions. Here, we develop a deep neural network to identify and quantify methane point source emissions from hyperspectral imagery from the PRecursore IperSpettrale della Missione Applicativa (PRISMA) satellite with 30 m spatial resolution. The moderately high spectral and spatial resolution, as well as considerable global coverage and free access to data, makes PRISMA a good candidate for methane plume detection. The neural network was trained with simulated synthetic methane plumes generated with the large eddy simulation extension of the Weather Research and Forecasting model (WRF-LES), which we embedded into PRISMA images. The deep neural network was successful at locating plumes with a F1 score, precision, and recall of 0.95, 0.96, and 0.92, respectively, and was able to quantify emission rates with a mean error of 24 %. The neural network was furthermore able to locate several plumes in real-world images. We have thus demonstrated that our method can be effective in locating and quantifying methane point source emissions in near-real time from 30 m resolution satellite data, which can aid us in mitigating future climate change.

Two New Methods Based on Implicit Expressions and Corresponding Predictor-Correctors for Gravity Anomaly Downward Continuation and Their Comparison

Downward continuation is a key technique for processing and interpreting gravity anomalies, as it has a major role in reducing values to horizontal planes and identifying small and shallow sources. However, it can be unstable and inaccurate, particularly when continuation depth increases. While the Milne and Adams–Bashforth methods based on numerical solutions of the mean-value theorem have partly addressed these problems, more accurate and realistic methods need to be presented to enhance results. To address these challenges, we present two new methods, Milne–Simpson and Adams–Bashforth–Moulton, based on implicit expressions and their predictor-correctors. We test the validity of the presented methods by applying them to synthetic models and real data, and we obtain stability, accuracy, and large depth (eight times depth intervals) downward continuation. To facilitate wider applications, we use calculated vertical derivatives (of the first order) by the integrated second vertical derivatives (ISVD) method to replace theoretical ones from forward calculations and real ones from observations, obtaining reasonable downward continuations. To further understand the effect of introduced calculation factors, we also compare previous and presented methods under different conditions, such as with purely theoretical gravity anomalies and their vertical derivatives at different heights from forward calculations, calculated gravity anomalies and their vertical derivatives at non-measurement heights above the observation by upward continuation, calculated vertical derivatives of gravity anomalies by the ISVD method at the measurement height, and noise. While the previous Adams–Bashforth method sometimes outperforms the newly presented methods, new methods of the Milne–Simpson predictor-corrector and Adams–Bashforth–Moulton predictor-corrector generally present better downward continuation results compared to previous methods.

Understanding day–night differences in dust aerosols over the dust belt of North Africa, the Middle East, and Asia

Abstract. Utilizing the well-calibrated, high-spectral-resolution equal-quality performance of daytime and nighttime (09:30 and 21:30 local solar Equator-crossing time (local solar ECT)) products of the Infrared Atmospheric Sounder Interferometer (IASI) from the Laboratoire de Météorologie Dynamique (LMD), this study investigates the day–night differences in dust aerosols over the global dust belt of North Africa, the Middle East, and Asia. Both daytime dust optical depth (DOD) and nighttime DOD at 10 µm show high consistency with solar and lunar observations of coarse-mode aerosol optical depth (CAOD) from AErosol RObotic NETwork (AERONET) sites across the dust belt, with correlation coefficients of 0.8–0.9 for most sites. Both IASI DOD and dust layer height show a significant (95 % confidence level) day–night difference over the major dust sources within the dust belt. Daytime DOD over the central to northern Sahara, the central to eastern Arabian Peninsula, and the Taklamakan Desert is significantly higher than that of nighttime but lower than nighttime over the southern Sahel to the Guinea Coast and the western to central Indian subcontinent in the annual mean. The magnitude of the day–night differences in DOD is larger and more evident in boreal winter and spring than in other seasons. The positive day–night differences in DOD (i.e., higher daytime values than nighttime) over the central Sahara, the Middle East, and Asia are likely associated with greater dust emissions driven by higher dust uplift potential (DUP) and stronger wind speeds during daytime. Dust layer heights demonstrate negative day–night differences over dust source regions in the central Sahara, central Arabian Peninsula, and Taklamakan Desert and positive height differences in the southern Sahel to the Guinea Coast, southern parts of the Arabian Peninsula, and large parts of the Indian subcontinent. The higher dust layer height over the Guinea Coast and the Indian subcontinent during the daytime is associated with a deeper planetary boundary layer height and greater convective instability during daytime than nighttime, which promotes vertical transport and mixing of dust aerosols. The corresponding lower daytime DOD over the Sahel and the Indian subcontinent indicates a possible dilution of dust aerosols when they are transported to higher altitudes by convection where they are more susceptible to horizontal transport. Ground-based observations of dust show surface PM10 concentration and CAOD exhibit a spatially varying diurnal cycle across the dust belt. CAOD and PM10 concentrations generally peak in late morning and from late afternoon to midnight in the Sahel and in early afternoon and around early morning in the Middle East, the timings of which are largely consistent with the day–night differences in IASI DOD. It is also found that DOD from reanalysis products (e.g., Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) and ECMWF Atmospheric Composition Reanalysis 4 (EAC4)) failed to capture the day–night differences in IASI DOD in large parts of the dust belt except in small dust source hotspots over North Africa.

Simultaneous off-the-grid regularization and reconstruction for 3D seismic data by a new combined sampling operator

Seismic samples are generally designed to be placed on perfect Cartesian coordinates, that is, on-the-grid. However, sampling geometry is disturbed by obstacles in field applications. Large obstacles result in missing samples. For small obstacles, geophones or sources are placed at an available off-the-grid location nearest to the designed grid. To achieve simultaneous off-the-grid regularization and missing data reconstruction for 3D seismic data, we develop a new mathematical model based on a new combined sampling operator, a 3D curvelet transform, and a fast projection onto convex sets (FPOCS) algorithm. The sampling operator is combined with a binary mask for on-the-grid samples reconstruction and a barycentric Lagrangian (BL) operator for off-the-grid samples regularization. A 2D BL operator is obtained using the tensor product of two 1D BL operators. The inversion problem is efficiently solved based on FPOCS. This method is tested on synthetic and field data sets. The reconstruction results outperform the methods based on the binary mask in terms of signal-to-noise ratio and visual effect.

Spectral age distribution for radio-loud active galaxies in the XMM-LSS field

ABSTRACT Jets of energetic particles, as seen in FR type-I and FR type-II sources, ejected from the centre of radio-loud AGN affect the sources surrounding the intracluster medium/intergalactic medium. Placing constraints on the age of such sources is important in order to measure the jet powers and determine the effects on feedback. To evaluate the age of these sources using spectral age models, we require high-resolution multiwavelength data. The new sensitive and high-resolution MIGHTEE survey of the XMM-LSS field, along with data from the Low Frequency Array (LOFAR) and the Giant Metrewave Radio Telescope (GMRT) provide data taken at different frequencies with similar resolution, which enables us to determine the spectral age distribution for radio-loud AGN in the survey field. In this study, we present a sample of 28 radio galaxies with their best-fitting spectral age distribution analysed using the Jaffe–Perola (JP) model on a pixel-by-pixel basis. Fits are generally good, and objects in our sample show maximum ages within the range of 2.8 to 115 Myr with a median of 8.71 Myr. High-resolution maps over a range of frequencies are required to observe detailed age distributions for small sources, and high-sensitivity maps will be needed in order to observe fainter extended emission. We do not observe any correlation between the total physical size of the sources and their age, and we speculate that both dynamical models and the approach to spectral age analysis may need some modification to account for our observations.