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Synthetic Aperture Radar (SAR) is a potent instrument for estimating soil moisture across vast farmland areas. However, when soil salinity rises, existing SAR retrieval models for soil moisture become less accurate. Soluble salts in soil water alter the inherent correlation between the SAR backscattering coefficients and soil water, thus compromising the performance of retrieval models. The need to get surface roughness parameters from the field also limits the widespread application of the model. To address these issues, we developed a retrieval model for salty soil moisture assessment under small-scale roughness surfaces. First, we found a method to distinguish between slightly rough and rough surfaces using scattering entropy obtained from full-polarization decomposition. Then, we harnessed the co-polarization ratio to mitigate the effect of surface roughness in slightly rough conditions. Later, we developed a soil moisture retrieval model based on the co-polarization ratio, considering incidence angle, residual roughness, and soluble salt content. The validation of the model was verified using field surveying data, yielding an RMSE of 0.026 cm3 ·cm− 3 for the estimated soil moisture. This accuracy is comparable to or surpasses the level achieved by SAR for non-salinized soil moisture retrieval. Our findings showed that Scattering entropy is an effective parameter for distinguishing scattering mechanisms on farmland surfaces effectively. Specifically, when the scattering entropy of farmland is less than 0.5, the co-polarization ratio can mitigate some surface roughness effects. Additionally, when the soil-soluble salt content is incorporated, our model can accurately estimate the soil moisture of salty soil. [ABSTRACT FROM AUTHOR]

Monocyclic 5‐membered heterocycles including imidazoles, thiazoles, oxazoles, and their related compounds have gained significant attention in medicinal chemistry because of their potent anticancerous activity. These small heterocyclic molecules possess versatile properties, including biological activity, absorption, distribution, metabolism, excretion, and chemical diversity that give them immense potential as anticancer agents. It is also a fact that inherent characteristic of azoles to combine with many biological molecules through hydrogen bond, stacking, and hydrophobic interaction makes them effective against almost all cancer types. In the present paper the author discusses the way which is connected with chemical structure of monocyclic azoles and their anticancer activity namely the ability of these compounds to intercalate with DNA, to inhibit some enzymes and to interfere cellular signaling pathways. Interestingly, several azole derivatives have been seen to be effective in preclinical efficacy studies as well as in clinical trials and are considered to be potent in overcoming the problem of resistance and side effects of the common anticancer agents. As the synthetic chemistry progresses, the structural system of the azoles has diversified and development in the pharmacology has become more specific. This has helped in enhancing the formation of new molecules in the azole class with improved selectivity and efficacy. Furthermore, the comprehensive review explains how computational chemistry and structure‐activity relationship (SAR) approaches are applied to the design of future‐generation azole compounds. In light of these facts, this article is designed to give a broad overview of the current state of monocyclic azole‐based anticancer agents in an attempt to further assert its therapeutic promise and spur further attempts at infusing the said agents into the cancer therapeutics fray. The discoveries made in this study may allow the development the radical different therapeutic approaches, which could lead to improved and targeted treatment of cancer. [ABSTRACT FROM AUTHOR]

Intertidal habitats have been significantly impacted by accelerated climate change in Arctic regions over the past few decades, particularly in Svalbard. New substrates are exposed as glacier retreat, making them accessible to benthic vegetation. Remote sensing techniques, including Sentinel-1 synthetic aperture radar (SAR) imagery and drones, provide the opportunity to acquire and study submerged habitats when they are exposed to the atmosphere during low tide. St. Jonsfjorden, Eidembukta, and Trygghamna were the three bays in Svalbard where this research was conducted. We used SAR imagery to determine relatively narrow intertidal zones, acknowledging that the spatial resolution of Sentinel-1 SAR imagery is limited to 10 m. Although this limitation posed a challenge when attempting to classify these narrow intertidal zones due to the coarse resolution of the data, we categorized the intertidal zones into three habitat types: vegetated rock, rock, and mixed sediment. The accuracy of this classification was consistently reliable, with a range of 64–78%. The classification results indicated that 25% of the total intertidal zone is composed of substrates that are suitable for macroalgae growth. It is remarkable that 80% of this substrate is vegetated. Additionally, this investigation demonstrated that vegetation is significantly absent in areas adjacent to glaciers. The magnitude of the glacier appears to influence the extent of this vegetation-free zone. [ABSTRACT FROM AUTHOR]

Backscatter and derived parameters from Synthetic Aperture Radar (SAR) may vary across the swath as the incident angle increases from the near to the far range, especially in the ScanSAR mode. Previous studies characterize this angular variation in the form of linear regression for commonly used ice types, namely first-year (FYI) and multi-year (MYI). The present study took advantage of the appearance of three grounded multi-year ice floes, viewed at different radar incidence angles, in a series of 22 RADARSAT-2 fully-polarimetric images, acquired over the Resolute Passage in the Canadian Arctic, during the period from 21 October to 28 December 2017. The ice properties remained invariant during the observation period; hence, variation of radar parameters of MYI can be attributed to change of incidence angle only. Quantification of angular variation of the selected SAR parameters was performed. They include conventional orthogonal backscatter coefficients, derived parameters from the incoherent decomposition of Cloude-Pottier, Yamaguchi, and Touzi, as well as a set of parameters from the compact polarimetry mode. Results specify the parameters that reveal variation with incidence angle and present the linear regressions equations. The explanation for the behaviour of each parameter, in terms of showing or not showing an angular trend, is offered. Results will be useful when using the polarimetric parameters in the sea ice classification scheme. [ABSTRACT FROM AUTHOR]

Deep learning algorithms have found extensive utility in Automatic Target Recognition (ATR) using Synthetic Aperture Radar (SAR). Despite this, conventional deep learning-based ATR models often lack in their performance when subjected to Extended Operating Conditions (EOCs). Significant variations in depression, noise interference, limited training data, and partial occlusion are primary factors in EOCs. In this paper, we proposed a deep neural network-based technique to recognize SAR targets for Standard Operating Conditions (SOC) and Extended Operating Conditions (EOC). The proposed approach comprises an encoder and decoder network. The encoder network integrates multiple dilated convolutions to address noise-induced recognition challenges for extracting multi-scale features. Furthermore, a feature refinement module is integrated within the multi-scale channels to enhance the extraction of discriminative and resilient features. Feature refinement selectively emphasizes informative features while suppressing irrelevant ones. Additionally, a salient attention block and a spatial feature learning module are introduced for feature selection. Selected features are then utilized in the top-level network layer of the encoder network to preserve spatial relationships among diverse features. This spatial feature learning module aids in recognition performance, particularly when training data is scarce. The decoder network consists of stacked transposed convolution layers, facilitating the encoder network's acquisition of discriminative image features. Experimental evaluations were conducted on the Moving and Stationary Target Acquisition and Recognition (MSTAR) dataset to validate the efficacy of the proposed methodology. [ABSTRACT FROM AUTHOR]

Assessing maize yield is critical, as it is directly influenced by the crop's growth conditions. Therefore, real-time monitoring of maize growth is necessary. Regular monitoring of maize growth indicators is essential for optimizing irrigation management and evaluating agricultural yield. However, quantifying the physical aspects of regional crop development using time-series data is a challenging task. This research was conducted at the Dengkou Experimental Station in the Hetao irrigation area, Northwest China, to develop a monitoring tool for regional maize growth parameters. The tool aimed to establish a correlation between satellite-based physical data and actual crop growth on the ground. This study utilized dual-polarization Sentinel-1A GRD SAR data, accessible via the Google Earth Engine (GEE) cloud platform. Three polarization descriptors were introduced: θc (pseudo-scattering type parameter), Hc (pseudo-scattering entropy parameter), and mc (co-polar purity parameter). Using an unsupervised clustering framework, the maize-growing area was classified into several scattering mechanism groups, and the growth characteristics of the maize crop were analyzed. The results showed that throughout the maize development cycle, the parameters θc, Hc, and mc varied within the ranges of 26.82° to 42.13°, 0.48 to 0.89, and 0.32 to 0.85, respectively. During the leaf development stage, approximately 80% of the maize sampling points were concentrated in the low-to-moderate entropy scattering zone. As the plants reached the big trumpet stage, the entire cluster shifted to the high-entropy vegetation scattering zone. Finally, at maturity, over 60% of the sampling points were located in the high-entropy distribution scattering zone. This study presents an advanced analytical tool for crop management and yield estimation by utilizing precise and high-resolution spatial and temporal data on crop growth dynamics. The tool enhances the accuracy of crop growth management across different spatial and temporal conditions. [ABSTRACT FROM AUTHOR]

This paper introduces a systematic approach to the design of Direct Current-to-Digital Converter (DIDC) specifically engineered to overcome the limitations of traditional current measurement methodologies in System-on-Chip (SoC) designs. The proposed DIDC addresses critical challenges such as high power consumption, large area requirements, and the need for intermediate analog signals. By incorporating a current mirror in a cascode topology and managing the current across multiple binary-sized branches with the Successive Approximation Register (SAR) logic, the design achieves precise current measurement. A simple comparator, coupled with an isolation circuit, ensures accurate and reliable sensing. Fabricated using the TSMC 180 nm process, the DIDC achieves 8-bit precision without the need for nonlinearity calibration, showcasing remarkable energy efficiency with an energy per conversion of 1.52 pJ, power consumption of 117 µW, and a compact area of 0.016 mm². This innovative approach not only reduces power consumption and area, but also provides a scalable and efficient solution for next-generation semiconductor technologies. The ability to conduct online measurements during both standard operations and in-field conditions significantly enhances the performance and reliability of SoCs, making this DIDC a promising advancement in the field. [ABSTRACT FROM AUTHOR]

In recent years, drone-based Synthetic Aperture Radar (SAR) systems have emerged as flexible and cost-efficient solutions for detecting changes in the Earth's surface, retrieving topographic data, or detecting ground displacement processes in localized areas, among other applications. These systems offer a unique combination of short and versatile revisit times and flexible acquisition geometries that are not achievable with space-borne, airborne, or ground-based SAR sensors. However, due to platform limitations and flight stability issues, they also present significant challenges regarding instrument design and data processing, particularly when generating interferometric repeat-pass datasets. This paper demonstrates the feasibility of repeat-pass interferometry using a Ku-band drone-based SAR system. The system integrates a dual-channel Ku-band Frequency Modulated Continuous Wave (FMCW) radar with cross-track single-pass interferometric capabilities, mounted on a drone platform. The proposed repeat-pass interferometric processing chain leverages an accurate Digital Elevation Model (DEM), generated from the single-pass interferograms, to precisely coregister the entire stack of acquisitions, thereby producing repeat-pass interferograms free from residual motion errors. The results underscore the potential of this system and the processing chain proposed for generating multi-temporal repeat-pass stacks suitable for repeat-pass applications. [ABSTRACT FROM AUTHOR]

A multiband microstrip antenna integrated with an electromagnetic bandgap (EBG) structure operating at WLAN and WiMAX frequencies is proposed for wearable applications. The antenna consists of a circular patch surrounded by the ground plane, separated by a ring slot. The size of the integrated antenna has been significantly reduced to 0.28 $\lambda $ λ ×0.28 $\lambda $ λ and thickness of 0.024 $\lambda $ λ. A single-layered planar groundless EBG structure has been designed to suppress the wideband of frequencies from 2.2 to 5.4 GHz. An equivalent circuit model is presented to explain the zero-degree reflection phase of the EBG. Integration of the antenna with the EBG structure and a simple resonator bestows operating bands at 2.45 and 5.2, 5.5 and 5.8 GHz with significantly low back radiation. The gain and directivity of the antenna have been increased to 5.41 dB and 6.2 dB, respectively. The Specific Absorption Rate (SAR) of the antenna has been reduced to 0.0859W/kg, which is significantly lower than the admissible SAR value recommended by the Federal Communications Commission (FCC). The antenna is fabricated on an FR4 substrate, and its measured radiation characteristics are well matched to the simulated one. [ABSTRACT FROM AUTHOR]

In China, high‐speed trains have become a major means of transportation for the masses. When the passengers wearing pacemakers travel on high‐speed trains, electromagnetic environment in the carriage where the GSM‐R voice and data antennae are located should be concerned. In this work, a real‐size carriage monopole antennae simulating voice and data antennae as high‐frequency radiation sources and wearing pacemaker passenger' models were established to study the electromagnetic exposure of the passenger at different conditions. The results showed that when the passenger faced the voice antenna, he suffered much greater electromagnetic radiation than when his back in turned from it. The electric field strength, average SAR, and temperature rise of the heart when facing the antenna were 27.3 V/m, 0.0102 W/kg, and 0.0016°C, respectively. Meanwhile, the temperature rise of the pacemaker was 0.001°C. We also obtained the values of electromagnetic dose for the whole body. All data were below the limits of the ICNIRP guidelines. These results indicate that the electromagnetic fields generated by the GSM‐R voice and data antennae do not harm the health of passengers wearing pacemaker. [ABSTRACT FROM AUTHOR]

Forest degradation is a major issue in ecosystem monitoring, and to take reformative measures, it is important to detect, map, and quantify the losses of forests. Synthetic Aperture Radar (SAR) time-series data have the potential to detect forest loss. However, its sensitivity is influenced by the ecoregion, forest type, and site conditions. In this work, we assessed the accuracy of open-source C-band time-series data from Sentinel-1 SAR for detecting deforestation across forests in Africa, South Asia, and Southeast Asia. The statistical Cumulative Sums of Change (CuSUM) algorithm was applied to determine the point of change in the time-series data. The algorithm's robustness was assessed for different forest site conditions, SAR polarizations, resolutions, and under varying moisture conditions. We observed that the change detection algorithm was affected by the site- and forest-management activities, and also by the precipitation. The forest type and eco-region affected the detection performance, which varied for the co- and cross-pol backscattering components. The cross-pol channel showed better deforested region delineation with less spurious detection. The results for Kalimantan showed a better accuracy at a 100 m spatial resolution, with a 25.1% increase in the average Kappa coefficient for the VH polarization channel in comparison with a 25 m spatial resolution. To avoid false detection due to the high impact of soil moisture in the case of Haldwani, a seasonal analysis was carried out based on dry and wet seasons. For the seasonal analysis, the cross-pol channel showed good accuracy, with an average Kappa coefficient of 0.85 at the 25 m spatial resolution. This work was carried out in support of the upcoming NISAR mission. The datasets were repackaged to the NISAR-like HDF5 format and processing was carried out with methods similar to NISAR ATBDs. [ABSTRACT FROM AUTHOR]

The radar-backscattering coefficient (σ0) depends on surface characteristics and instrumental parameters (wavelength, polarization, and incidence angle). For Sentinel-1 (S1), with incidence angles ranging from 25° to 45°, σ0 for similar targets typically differs by a few dB depending on their localization in the S1 swath. Overcoming this angular dependence is crucial for the operational applications of radar data. In theory, σ0 follows a cosine function with an exponent "N" that represents the degree of dependence between σ0 and the incidence angle. In order to reduce the effect of the incidence angle on σ0, dynamic N normalizations based on vegetation descriptors, NDVI and SAR Ratio (VV/VH), were applied and then compared to the results obtained with temporally fixed N normalizations. N was estimated at each S1 date during the period of the study for three main summer crops: corn, soybean, and sunflower. Analysis shows that the angular dependence of the S1 σ0 is similar for all three crops. N varies from 3.0 for low NDVI values to 2.0 for high NDVI values (stage of maximal vegetation development) in the VV polarization and from 2.5 to 1.5 for the VH polarization. Furthermore, N fluctuates strongly during the periods before plant emergence and after harvesting, due to variations in the soil roughness. Finally, the results demonstrated that the dynamic normalization of σ0 significantly reduces its angular dependence compared to fixed N (N = 1 and N = 2), with SAR ratio-based normalization performing similarly to NDVI-based normalization. [ABSTRACT FROM AUTHOR]

The field of maritime surveillance is one of great strategical importance from the point of view of both civil and military applications. The growing availability of spaceborne imagery makes it a great tool for ship detection, especially when paired with information from the automatic identification system (AIS). However, small vessels can be challenging targets for spaceborne sensors without relatively high resolution. Moreover, when faced with non-cooperative targets, hull detection alone is insufficient for obtaining critical information like target speed and heading. The wakes generated by the movement of ships can be used to solve both of these issues. Several interesting solutions have been developed over the years, based on both traditional and learning-based methodologies. This review aims to provide the first thorough overview of ship wake detection solutions, highlighting the key ideas behind traditional applications, then covering more innovative applications based on deep learning (DL), to serve as a solid starting point for present and future researchers interested in the field. [ABSTRACT FROM AUTHOR]

The three‐dimensional structure of the Tropical Cyclone's baroclinic wake is synthesized as an averaged baroclinic‐dominant response of the upper ocean. The resulting persisting sea surface depression can easily be monitored using the present‐day altimeter constellation. Following a semi‐empirical framework, these baroclinic wake signatures are linked to the inner core TC dynamic and the ocean stratification. To collect these fine‐scale parameters, spaceborne SAR instruments and Argo fleet are used, to precisely capture the maximum wind region and the irregularities of the ocean vertical structure. This combination of high‐resolution information is found paramount to fully capture the modulation of sea surface height anomalies, and its mean trend, especially for major hurricanes. Baroclinic signatures mostly range around 10–20 cm and peak at 40 cm. Deeper anomalies correspond to barotropic response, removed from the present analysis. Plain Language Summary: In the wakes of Tropical Cyclones (TCs), sea surface depressions of about 10 cm appear. These TC signatures are persistent enough to be easily monitored by the current fleet of altimeter instruments. A measured sea surface height anomaly integrates and reduces the air/sea interactions during the TC passage into a single observable metric. It mostly encodes the cyclonic wind forcing and the interior ocean state. A broad constellation of remote sensing and in‐situ instruments has been gathered to compile 200 cyclonic episodes, collecting a wide range of TC sizes, intensities, and translation speeds together with oceanic conditions. A synthetic relationship is found to robustly predict most observed sea surface height anomalies. Moreover, when high‐resolution information is available to estimate the ocean interior state and the TC radius of maximum winds. Such a diagnostic thus explains the dominant baroclinic ocean response to a TC passage, and, inversely, can be used to infer ocean stratification or forcing parameters in the absence of high‐resolution observations. Key Points: Residual sea surface height anomalies from the cold wakes of Tropical Cyclones are analyzed using a multi‐modal approach at global scaleA scaling law provides a robust interpretation of the baroclinic response to given ocean stratification and forcing conditionsHigh resolution measurements are found critical to correctly anticipate the SSHA amplitudes with localized pre‐storm ocean stratification [ABSTRACT FROM AUTHOR]

Many SAR images have been utilized for geologic disasters investigations with the continuous launch of new Synthetic Aperture Radar (SAR) satellites such as ALOS-2/PALSAR-2. However, to proactively respond to transient slope failures caused by heavy rainfall, rapid extraction of areas of surface change accompanying slope failures is required. This study proposes two methods for quantitatively extracting slope failure areas using L-band SAR observations with slope units (SUs) as the evaluation units. The first method is based on the threshold method, which automates the selection of thresholds for various disaster-affected conditions, such as land use and topography. The second method is a machine-learning-based density ratio estimation method, which uses multi-temporal periodic observation data and pre- and post-disaster data to detect outliers through feature selection optimization. In the observation direction with the shortest satellite observation period, the F1 score (The F1 score is the harmonic mean of the precision and recall) of the threshold method for accuracy evaluation is 61.91%, and the F1 score of the density ratio method is 65.87%. Both methods can reduce the problem of low extraction accuracy caused by the effect of speckle noise. When slope failure occurs, both methods can extract the area of surface change within hours of a disaster. The method proposed in this study displays good applicability in supporting emergency rescue and the prevention of secondary disasters. [ABSTRACT FROM AUTHOR]

In this article, a regional ocean surface waves dataset from Sentinel‐1 A and B Synthetic Aperture Radar (SAR) satellites has been described. The ocean wave data have been extracted from the Sentinel‐1 level‐2 OCN (ocean) product as provided by the European Space Agency and downloadable for this region from the Copernicus Australasia regional data hub. The source OCN data have been produced by evolving versions of Sentinel‐1 Instrument Processing Facility (IPF). The structure of the source OCN NetCDF files changes over time and presents a challenge in performing long duration, time series analyses, including the examination of potential inconsistencies in OCN wave data, due to employment of different IPF versions over the duration of the satellite missions. Here, the input OCN wave data have been homogenized to a single, easily usable standard format after applying a quality assurance and control procedure that removes various inconsistencies in variables, coordinates, dimensions and land flag, and through the addition of new auxiliary variables. The new format has the desirable properties of being compact in size, consistent in structure, and scalable in temporal and spatial coverage. It is also convenient to use and offers opportunities to perform fast, multi‐year regional processing and analysis for calibration and validation studies and scientific applications. No re‐processing of Sentinel‐1 level‐1 data has been carried out in this work. [ABSTRACT FROM AUTHOR]

This research studies the characteristics of snow-covered area (SCA) from two vastly different sensors: optical (Moderate-Resolution Imaging Spectroradiometer, or MODIS, equipped on board the Terra satellite) and radar (Synthetic Aperture Radar (SAR) on-board Sentinel-1 satellites). The focus are the five mountain ranges of the Iberian Peninsula (Cantabrian System, Central System, Iberian Range, Pyrenees, and Sierra Nevada). The MODIS product was selected to identify SCA dynamics in these ranges using the Probability of Snow Cover Presence Index (PSCPI). In addition, we evaluate the potential advantage of the use of SAR remote sensing to complete optical SCA under cloudy conditions. For this purpose, we utilize the Copernicus High-Resolution Snow and Ice SAR Wet Snow (HRS&I SWS) product. The Pyrenees and the Sierra Nevada showed longer-lasting SCA duration and a higher PSCPI throughout the average year. Moreover, we demonstrate that the latitude gradient has a significant influence on the snowline elevation in the Iberian mountains (R2 ≥ 0.84). In the Iberian mountains, a general negative SCA trend is observed due to the recent climate change impacts, with a particularly pronounced decline in the winter months (December and January). Finally, in the Pyrenees, we found that wet snow detection has high potential for the spatial gap-filling of MODIS SCA in spring, contributing above 27% to the total SCA. Notably, the additional SCA provided in winter is also significant. Based on the results obtained in the Pyrenees, we can conclude that implementing techniques that combine SAR and optical satellite sensors for SCA detection may provide valuable additional SCA data for the other Iberian mountains, in which the radar product is not available. [ABSTRACT FROM AUTHOR]

Interactions between ocean surface currents, winds and waves at the atmosphere-ocean interface are key controls of lateral and vertical exchanges of water, heat, carbon, gases and nutrients in the global Earth System. The SeaSTAR satellite mission concept proposes to better quantify and understand these important dynamic processes by measuring two-dimensional fields of total surface current and wind vectors with unparalleled spatial and temporal resolution (1 × 1 km2 or finer, 1 day) and unmatched precision over one continuous wide swath (100 km or more). This paper presents a comprehensive numerical analysis of the expected performance of the Earth Explorer 11 (EE11) SeaSTAR mission candidate in the case of idealised and realistic 2D ocean currents and wind fields. A Bayesian framework derived from satellite scatterometry is adapted and applied to SeaSTAR's bespoke inversion scheme that simultaneously retrieves total surface current vectors (TSCV) and ocean surface vector winds (OSVW). The results confirm the excellent performance of the EE11 SeaSTAR concept, with Root Mean Square Errors (RMSE) for TSCV and OSVW at 1 × 1 km2 resolution consistently better than 0.1 m/s and 0.4 m/s, respectively. The analyses highlight some performance degradation in some relative wind directions, particularly marked at near range and low wind speeds. Retrieval uncertainties are also reported for several variations around the SeaSTAR baseline three-azimuth configuration, indicating that RMSEs improve only marginally (by ∼0.01 m/s for TSCV) when including broadside Radial Surface Velocity or broadside dual-polarisation data in the inversion. In contrast, our results underscore (a) the critical need to include broadside Normalised Radar Cross Section data in the inversion; (b) the rapid performance degradation when broadside incidence angles become steeper than 20° from nadir; and (c) the benefits of maintaining ground squint angle separation between fore and aft lines-of-sight close to 90°. The numerical results are consistent with experimental performance estimates from airborne data and confirm that the EE11 SeaSTAR concept satisfies the requirements of the mission objectives. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to synthesize azine analogues of 1,2-diphenylethan-1-one while assessing their ability to scavenge free radicals with DPPH. In order to explore these compounds' potential as novel antioxidant agents with possible applications in the pharmaceutical, neutraceutical, and other industries, we synthesized them. Methods: The initial steps involved reacting 1,2-diphenylethan-1-one and additional amount of hydrated hydrazine in an ethanol solvent to produce the needed hydrazone, which paved the way for a two-step reaction that produced azine derivatives. Ultimately, a number of substituted aldehydes that are aromatic were heated by reflux condition, catalyzed by acetic acid with the obtained hydrazone to produce the azine derivatives in high yields. Results: These synthetic derivatives were screened for their anti-oxidant activity, compound (IIe) (IC50 = 24.13 ± 0.27 µM), (IIf) (IC50 = 29.11 ± 0.41 µM), and (IIg) (IC50 = 31.12 ± 0.44 µM) attributed the most excellent activity, however compound (IIc) and (IId) were found as significant DPPH free radical scavenging agents with IC50 values 46.21 ± 0.12 and 49.23 ± 0.54 µM, respectively while compound (IIa) and (IIb) displayed less anti-oxidant effect with IC50 values 55.11 ± 0.24 and 66.21 ± 0.12 µM. Conclusions: The study shows that the azine derivatives under investigation have promising potential as synthetic antioxidants due to their significant DPPH radical scavenging action. Furthermore, compounds containing electron-donating groups exhibit antioxidant activity comparable to that of ascorbic acid, an antioxidant that occurs naturally. These findings highlight the antioxidant qualities of the synthetic azine derivatives and suggest potential applications as medical treatments for oxidative stress-related illnesses. [ABSTRACT FROM AUTHOR]

Oleanolic acid, a naturally occurring triterpenoid compound, has garnered significant attention in the scientific community due to its diverse pharmacological properties. Continuing our previous work on the synthesis of oleanolic acid dimers (OADs), a simple, economical, and safe acetylation reaction was performed. The newly obtained derivatives (AcOADs, 3a–3n) were purified using two methods. The structures of all acetylated dimers (3a–3n) were determined based on spectral methods (IR, NMR). For all AcOADs (3a–3n), the relationship between the structure and the expected directions of pharmacological activity was determined using a computational method (QSAR computational analysis). All dimers were also tested for their cytotoxic activity on the SKBR-3, SKOV-3, PC-3, and U-87 cancer cell lines. HDF cell line was applied to evaluate the Selectivity Index of the tested compounds. All cytotoxic tests were performed with the application of the MTT assay. Finally, all dimers of oleanolic acid were subjected to DPPH and CUPRAC tests to evaluate their antioxidant activity. The obtained results indicate a very high level of cytotoxic activity (IC50 for most AcOADs below 5.00 µM) and a fairly high level of antioxidant activity (Trolox equivalent in some cases above 0.04 mg/mL). [ABSTRACT FROM AUTHOR]

Water extraction from synthetic aperture radar (SAR) images has an important application value in wetland monitoring, flood monitoring, etc. However, it still faces the problems of low generalization, weak extraction ability of detailed information, and weak suppression of background noises. Therefore, a new framework, Multi-scale Attention Detailed Feature fusion Network (MADF-Net), is proposed in this paper. It comprises an encoder and a decoder. In the encoder, ResNet101 is used as a solid backbone network to capture four feature levels at different depths, and then the proposed Deep Pyramid Pool (DAPP) module is used to perform multi-scale pooling operations, which ensure that key water features can be captured even in complex backgrounds. In the decoder, a Channel Spatial Attention Module (CSAM) is proposed, which focuses on feature areas that are critical for the identification of water edges by fusing attention weights in channel and spatial dimensions. Finally, the high-level semantic information is effectively fused with the low-level edge features to achieve the final water detection results. In the experiment, Sentinel-1 SAR images of three scenes with different characteristics and scales of water body are used. The PA and IoU of water extraction by MADF-Net can reach 92.77% and 89.03%, respectively, which obviously outperform several other networks. MADF-Net carries out water extraction with high precision from SAR images with different backgrounds, which could also be used for the segmentation and classification of other tasks from SAR images. [ABSTRACT FROM AUTHOR]

In recent years, several strategies have been developed for the treatment of transthyretin-related amyloidosis, whose complex clinical manifestations involve cardiomyopathy and polyneuropathy. In view of this, transthyretin stabilizers represent a major cornerstone in treatment thanks to the introduction of tafamidis into therapy and the entry of acoramidis into clinical trials. However, the clinical treatment of transthyretin-related amyloidosis still presents several challenges, urging the development of new and improved therapeutics. Bearing this in mind, in this paper, the most promising among the recently published transthyretin stabilizers were reviewed. Their activity was described to provide some insights into their clinical potential, and crystallographic data were provided to explain their modes of action. Finally, structure–activity relationship studies were performed to give some guidance to future researchers aiming to synthesize new transthyretin stabilizers. Interestingly, some new details emerged with respect to the previously known general rules that guided the design of new compounds. [ABSTRACT FROM AUTHOR]

Disturbances in the ionosphere can severely affect synthetic aperture radar (SAR) acquisition and also the accuracy of differential SAR interferometry (D-InSAR) techniques. Focusing on the mid-latitudes, we report for the first time the effect of small-scale ionospheric irregularities on the interferograms generated by the C-band Sentinel-1 satellite. The interferograms obtained during the geomagnetic storm on 4 November 2021 showed finger-like stripes of phase artefacts, while the interferograms obtained on non-storm days did not show such anomalies. Such phase artefacts introduce an error greater than ± 3π in the interferogram. By further checking the gridded total electron content (TEC) from the ground-based global navigation satellite system (GNSS) network, as well as the in-situ electron density measured by ESA's Swarm satellite, the finger-like stripes in the interferograms are found to be correlated with ionospheric bulge structures generated during the geomagnetic storm. Since both the interferogram stripes and the ionospheric bulges exhibit a comparable east-west extension, it is believed that the interferograms can also be used to reflect the small-scale structures of ionospheric bulge fringes. For example, in this case, the latitudinal width of each finger-like stripe reaches about 8 km. Our result implies that the C-band interferogram has the potential to probe the two-dimensional ionospheric structures with unprecedented resolution, which cannot be achievable by the gridded GNSS-TEC. [ABSTRACT FROM AUTHOR]

Contemporary synthetic aperture radar (SAR) image processing techniques face various challenges, particularly in ship detection, background noise reduction, and information preservation. To address these issues, this paper introduces a novel model we called SAR-ShipSwin, which combines the swin transformer and feature pyramid network as the backbone network structure, specifically designed for ship detection in SAR images. The backbone network optimizes computational efficiency and handles occlusion and overlap issues in SAR images successfully by introducing the improved window multi-head self-attention module. To further enhance recognition accuracy, we design the background modeling network, which efficiently identifies and eliminates complex background features. Additionally, we introduce the spatial intensity geometric pooling technique, a novel pooling strategy that preserves geometric and structural information of the original region of interest, significantly reducing information loss and distortion. Considering the diverse ship shapes in SAR images, we specially design the dynamic ship shape adaptive convolution module, which dynamically adjusts the shape of convolution kernels to better match the targets. The proposed model is validated on the SSDD and HRSID datasets, achieving state-of-the-art performance. [ABSTRACT FROM AUTHOR]

This paper presents a background calibration method assisted with noise-shaping, for a 10-b bridged SAR ADC. It proposes calibrating the mismatches from the MSB capacitors using the LSBs. First-order noise-shaping has been employed to facilitate the calibration as well as the analog-to-digital conversion. Since noise-shaping is able to shape both the comparator input and quantization noise, it is expected to improve the calibration effects as well as the SNR, for the SAR ADC. Measurement results show, upon the proposed calibration, the SAR's INL and SNR are improved by 3 LSB and 9 dB, respectively, compared to when the noise shaping is off. Fabricated using a 55 nm CMOS MOMCAP technology and tested with a −2.5 dB sinewave input, the bridged SAR ADC achieves an SNR of 62.2 dB and an INL better than 1 LSB, when consuming a power of 7 2 μ W , at a supply voltage of 1.2 V and sampling frequency of 50 kHz. The ADC's active area is 3 0 0 × 3 8 0 μ m 2 . [ABSTRACT FROM AUTHOR]

Investigating pedestrian safety disparities across sociodemographic groups is essential for enhancing traffic safety. This study examines the impact of sociodemographic and built environment characteristics on pedestrian crashes. It introduces a comprehensive macro spatial analysis framework that includes a global regression model, spatial autoregressive models, and a local spatial regression model. Three measures of pedestrian injury are analyzed. The findings reveal that a higher percentage of the high-income population significantly correlates with lower rates of pedestrian injuries across all three measures. Conversely, a higher percentage of the low-income population shows a significant positive correlation with the proportion of crashes involving the Black population, and with the proportion of severe pedestrian crashes involving the Black population. Pedestrian-oriented network density is negatively associated with fatal or severely injurious crashes involving the Black population. These results emphasize the need to account for spatial variations and equity when addressing pedestrian safety disparities. • A comprehensive spatial modeling framework using OLS, SAR, and MGWR explores spatial autocorrelation and non-stationarity in pedestrian crashes. • The research analyzes disparities in pedestrian safety and evaluates pedestrian crash rates and Black population involvement in total and severe crashes. • Higher-income areas have lower pedestrian injury rates, while low-income areas see more severe crashes involving the Black population. [ABSTRACT FROM AUTHOR]

SAR and ISR are key acquired resistances in plants that play major role in imparting resistance to plants against various pathogens namely bacteria, virus, nematodes etc. The increasing awareness towards chemicals has led scientists to work on new mechanism of resistances. Both SAR and ISR are of future perspective for disease management. SAR require salicylic acid as transport molecule along with other complexes that include reactive oxygen species, lipid molecules whereas ISR require Jasmonic acid as signal molecule. SAR is more long lasting and broad spectrum as compared to ISR. Non-pathogenic bacteria and insectivores induce ISR. In future, disease management will be more focused on ISR and SAR. [ABSTRACT FROM AUTHOR]

Lipophilicity is an essential parameter of a compound that determines the solubility and pharmacokinetic properties that determine the transport of the drug to the molecular target. Dimers of dipyridothiazines are diazaphenothiazine derivatives exhibiting diverse anticancer potential in vitro, which is related to their affinity for histone deacetylase. In this study, the lipophilicity of 16 isomeric dipyridothiazine dimers was investigated theoretically and experimentally by reversed-phase thin-layer chromatography (RP-TLC) in an acetone–TRIS buffer (pH = 7.4). The relative lipophilicity parameter RM0 and specific hydrophobic surface area b were significantly intercorrelated, showing congeneric classes of dimers. The parameter RM0 was transformed into parameter logPTLC by use of the calibration curve. Molecular descriptors, ADMET parameters and probable molecular targets were determined in silico for analysis of the pharmacokinetic profile of the tested compounds showing anticancer activity. The analyzed compounds were tested in the context of Lipinski's rule of five, Ghose's rule and Veber's rule, confirming their bioavailability. [ABSTRACT FROM AUTHOR]

Staphylococcus aureus possesses sar family genes, including sarA, S, R, T, U, V, X, Y, Z, and rot, which are transcription factors involved in biofilm formation and quorum sensing. In contrast, Staphylococcus epidermidis has sarA, R, V, X, Y, Z, and rot genes; specifically, SarA, Z, and X are involved in biofilm formation. The expression of the sar family members in S. epidermidis isolated from clinical and non-clinical environments is unknown. This study aimed to establish if clinical and non-clinical isolates of S. epidermidis express the sar family members. We genotyped isolates from clinical ocular infections (n = 52), or non-clinical healthy conjunctiva (n = 40), and healthy skin (n = 50), using multilocus sequence typing (MLST) and the staphylococcal chromosomal cassette mec (SCCmec). We selected strains with different genotypes and representatives of each source of isolation, and the presence of the sar family genes was detected using PCR and RT-qPCR to determine their expression. The sar family genes were present in all selected strains, with no observed differences. The relative expression of the sar family showed that all selected strains expressed each gene weakly, with no significant differences observed between them or between different sources of isolation. In conclusion, the presence and relative expression of the sar family genes are very similar among strains, with no differences based on their origin of isolation and genotype. [ABSTRACT FROM AUTHOR]

Traditional near-field synthetic aperture radar (SAR) imaging algorithms reveal target features by exploiting signal amplitude and phase information. However, electromagnetic wave propagation is constrained by short distance. Therefore, the spherical wave approximation needs to be considered. In addition, it is also limited by equipment ambient noise, azimuth-distance coupling, wave scattering, and transmission power. Both the amplitude and phase of the signal suffer from the interference of multiple clutter, so they cannot be effectively utilized. To address these issues, this paper introduces a covering penetration detection system based on an improved Range Migration Algorithm (IMRMA) imaging method. Firstly, the proposed method minimizes interferences from the front end of the system using an optimized window to balance denoising and information preservation. Next, interval non-uniform interpolation, instead of Stolt interpolation decoupling, is employed to reduce the computational overhead significantly. To minimize the effects due to wave scattering and propagation loss, distance information is enhanced using amplitude and phase compensation. This reduces scattering effects and enhances image quality. An experimental system is constructed based on a vector network analyzer (VNA) to image the target. The proposed method takes about half the time of traditional RMA. The PSNR in the chunky bowl experiment is higher than 14 dB, which is higher than all the compared methods in the paper. The test results show that the designed system and the reported method can effectively achieve high-resolution images by strengthening the target intensity and suppressing the environmental artifacts. [ABSTRACT FROM AUTHOR]

The Hindu Kush Himalaya (HKH) is one of the most flood-prone regions in the world, yet heavy cloud cover and limited in situ observations have hampered efforts to monitor the impact of heavy rainfall, flooding, and inundation during severe weather events. This paper introduces HydroSAR, a Sentinel-1 SAR-based hazard monitoring service which was co-developed with in-region partners to provide year-round, low-latency weather hazard information across the HKH. This paper describes the end user-focused concept and overall design of the HydroSAR service. It introduces the main processing algorithms behind HydroSAR's broad product portfolio, which includes qualitative visual layers as well as quantitative products measuring the surface water extent and water depth. We summarize the cloud-based implementation of the developed service, which provides the capability to scale automatically with the event size. A performance assessment of our quantitative algorithms is described, demonstrating the capabilities to map the flood extent and water depth with an accuracy of >90% and <1 m, respectively. An application of the HydroSAR service to the 2023 South Asia monsoon seasons showed that monsoon floods peaked near 6 August 2023 and covered 11.6% of Bangladesh in water. At the peak of the flood season, nearly 13.5% of Bangladesh's agriculture areas were affected. [ABSTRACT FROM AUTHOR]

The determination of swelling/shrinking phenomena, from natural and anthropogenic activity, is examined in this study through the synergy of various remote sensing methodologies. For the period of 2016–2022, a time-series InSAR analysis of Sentinel-1 satellite images, with a Coherent Change Detection procedure, was conducted to calculate the Normalized Coherence Difference. These were combined with Sentinel-2 multispectral data by exploiting the Normalized Difference Vegetation Index to create multi-temporal image composites. In addition, ALOS-Palsar DEM derivatives highlighted the geomorphological characteristics, which, in conjunction with the satellite imagery outcomes and other auxiliary spatial datasets, were embedded within a Multi-Criteria Decision Analysis (MCDA) model. The synergy of the remote sensing and GIS techniques' applicability within the MCDA model highlighted the zones undergoing seasonal swelling/shrinking processes in Pyrgos–Parekklisia and Moni regions in Cyprus. The accuracy assessment of the produced final MCDA outcome provided an overall accuracy of 72.4%, with the Kappa statistic being 0.66, indicating substantial agreement of the MCDA outcome with the results from a Persistent Scatterer Interferometry analysis and ground-truth observations. Thus, this study offers decision-makers a powerful procedure to monitor longer- and shorter-term swelling/shrinking phenomena. [ABSTRACT FROM AUTHOR]

This paper analyzes the advantages and the drawbacks of using the Synthetic Aperture Radar (SAR) azimuth multichannel technique known as Multi-Aperture Processing Scheme (MAPS), in a set of relevant application cases that are far from the canonical ones. In the scientific literature on this topic, equally distributed azimuth channels with the quasi-monostatic deployment are assumed. With this research, we aim at extending the models from the current literature to (i) a generic bistatic acquisition geometry, (ii) a set of cases where the number of receiving tiles is not the same for each channel, or (iii) the tiles are shared between adjacent channels thus creating an overlapping configuration. The paper introduces the mathematical models for the listed non-conventional MAPS cases. Dealing with the bistatic MAPS, we first solve the problem by interpreting multichannel acquisition as a bank of Linear Time Invariant (LTI) filters. Then, a more physical approach, based on discrimination of the direction of arrivals (DoAs) is pursued. The effectiveness of the two methods and the advantages of the second approach on the first are proved by using a simplified 1D end-to-end simulation. Even limiting to the monostatic configuration, the azimuth antenna tiles have always been supposed equally partitioned among the RX channels. Overcoming this limit has two advantages: (i) more MAPS possible solutions in case few azimuth tiles are available, as in the ROSE-L mission; (ii) the number of channels can be designed independently of the number of tiles, also allowing asymmetric solutions, useful for a phase array antenna with an odd number of tiles such as in the SAOCOM-1 mission. Conversely, sharing one or more receiving tiles in different receiving channels makes the input noise partially correlated. The drawback is an increase in the noise level. A trade-off is determined for the different solutions obtained using simulations with real mission parameters. The theoretical performance and the end-to-end simulations are compared. [ABSTRACT FROM AUTHOR]

This article proposes a small multiple-input multiple-output (MIMO) wearable antenna system with four coplanar waveguide-fed antennas operating in the new radio band 79 (4.4–5 GHz) applications. The suggested MIMO antenna system consists of four identical hexagonal-shaped monopole radiators, and each is printed on polymide substrate with the size of 1.33 λ0 × 1.03 λ0, where λ0 is the wavelength at centre frequency 4.5 GHz. By placing four antenna elements in orthogonal arrangements, independent radiation pattern is achieved, thereby increasing isolation better than 17 dB. Specifically, no dedicated mechanism has been introduced to obtain the substantial isolation. All the antenna elements in the MIMO arrangement have broadband operation resonating between 4.4 and 5 GHz covering n79 (new radio band) 5G applications. The proposed antenna has a peak gain around 3.8–4 dBi over the operating frequency with radiation efficiency ranging from 88% to 90%. Since flexible substrate is used in the design, conformability of the antenna has been verified by performing bending analysis. The MIMO antenna provides better measured results, which are consistent with the simulated results; therefore, the antenna explored in this research could be the better candidate for 5G conformal and wearable applications. [ABSTRACT FROM AUTHOR]

According to the 2018 report of the United Nations Office for Disaster Risk Reduction (UNISDR), the total number of recorded flood events between 1998 and 2017 was 3,148. This means there is an average of 13 monthly floods on our Earth. Satellite monitoring using Sentinel-1 synthetic aperture radar (SAR) can be effectively used to map floods. It provides a short revisit time, a high spatial resolution of 5 m, and a swath of up to 400 km. In this study, we compare two promising flood mapping algorithms to map floods which are common phenomena in the An Giang area, and to monitor the mapping difficulty of flood peaks. The two mapping algorithms are Global Flood Mapper (GFM), an open-source Google Earth Engine (GEE) application; and the other algorithm implemented the Otsu threshold method and change detection approach. They were visually compared using Sentinel-2 optical data and a land-use land cover (LULC) map of An Giang, Vietnam. The results show that the GFM overcomes the misclassification of flooded and non-flooded areas. A good statistical agreement showed that the performance of flood maps derived from the modified GFM algorithm on Sentinel-1 VH-VV-VH RGB composite and Sentinel-2 images have better accuracy than the Otsu Sentinel-1 technique by $\sim20\% $ ∼ 20 %. [ABSTRACT FROM AUTHOR]

Diabetes mellitus (DM) is an endocrinological disorder in which blood sugar levels get elevated and if unmanaged, it leads to several critical complications. Existing therapies or drugs are not able to attain absolute control of DM. Moreover, associated side/adverse effects associated with pharmacotherapy further worsen the Quality of life of patients. Present review is focused on therapeutical potential of flavonoids in management of diabetes and diabetic complications. Plenteous literature has established significant potential of flavonoids in the treatment of diabetes and diabetic complications. A number of flavonoids are found to be effective in treatment of not only diabetes but progression of diabetic complication was also found to be attenuated with the use of flavonoids. Moreover, SAR studies of some flavonoids also indicated the that efficacy of flavonoids is increased with a change in functional group of flavonoids in the treatment of diabetes and diabetic complications. A number of clinical trials are into action to investigate the therapeutic potential of flavonoids as first-line drugs or as adjuvants for treatment of diabetes and diabetic complications.. Owing to their diverse mechanism of action, efficacy and safety, flavonoids may be conscripted as potential candidate for treatment of diabetic complications. [ABSTRACT FROM AUTHOR]

Kidney cancer is a significant health concern worldwide, with early detection crucial for successful treatment outcomes. Recently, there has been an increasing focus on investigating affordable and non-intrusive methods for detecting cancer at its early stages. This proposed approach delves into the utilization of antenna arrays to identify kidney cancer. Specifically, antenna array with circular polarization has been crafted to identify tumors in the human kidney. This array design has been implemented using CST software, operating at 2.4 GHz. The antenna array having a dimension of 150 mm x 150 mm. The array consists of four-square patches each having a length of 30 mm and the spacing between the patches is preferred to be 20 mm for ensuring the mutual coupling. FR4 substrate is used with the relative permittivity 4.3 and 1.6 mm thickness. The axial ratio of the circularly polarized antenna is 0.9 dB at 2.4 GHz. The reflection coefficient S 11 = –30dB. The renal phantom in humans has been built with the kidney, adrenal gland, ureter, skin, fat, and muscle components to allow for precise simulation. Following that, four stages of cancer tumors were built employing all of the necessary qualities. For every stage of the cancer tumor, the reflection coefficient growth and resonance frequency shift are calculated. For the initial stages, the resonance frequency shift is very low. Consequently, the primary determinant of detection is the rise in S 11 . For 3rd and 4th stages of the tumor, there is a significant change in resonance frequency and increase S 11 , which facilitates identification. The calculated specific absorption rate (SAR) is a smaller amount than the safety thresholds, indicating that using this method is safe. Overall, this research points to a novel, easy-to-use method for kidney cancer screening. This method has the following benefits: it is non-invasive, safe, quick, affordable, and comfortable, and it emits no ionizing radiation during the measurement process. Furthermore, a range of output parameters such as gain, directivity, and polar radiation have been accurately computed. [ABSTRACT FROM AUTHOR]

The current study focuses on the devastating floods along the Kosi River in Bihar in July 2020, which were recorded by Sentinel-1A satellite images. Three flood-affected districts in Saharsa, Supaul, and Madhepura have been selected for this study. Pre- and post-flood images from the Sentinel-1A satellite were utilized to generate the flood-inundated map, and pre-flood Landsat-8 datasets were used to generate the land use and land cover maps. Finally, damage assessment was done by superimposing land use and land cover on a flood-inundated map. The results showed that Madhepura was the most affected district with 57.6% of its barren land experiencing inundation. Furthermore, a comparison of cloud cover percentages during the flood was undertaken using the Sentinel-1A, Sentinel-2B, and Landsat-8 datasets. The findings indicate Sentinel-1A has less than 1% cloud cover, making it suitable for flood monitoring. Due to urbanization and industrialization, land use/cover (LULC) varies rapidly, and the effect on the flood plain must be determined. TerrSet's Land Change Modeler uses cellular automata–Markov modeling to project LULC maps for 2030 and their implications for subsequent flooding. The findings indicate that Saharsa will see an increase in the built-up area of 2.7%, Supaul with a gain of 13.4%, and Madhepura will see a growth of 10.3%. The growth of built-up regions in the near future will encourage greater impermeable layers and more discharge. Therefore, land use planners, environmentalists, and lawmakers should consider these LULC changes in water resource planning. [ABSTRACT FROM AUTHOR]

The 2022 Paktika earthquake (moment magnitude: 6.2) occurred on June 22, 2022, near the border between the Khost and Paktika Provinces of Afghanistan, causing heavy damage and casualties in Paktika Province. This study evaluated the crustal deformation and associated strong motions induced by the Paktika earthquake. Crustal deformations were determined using the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique and three-dimensional finite element method (3DFEM) and the results were compared. The permanent ground displacements obtained from the DInSAR and 3D-FEM analyses were similar in terms of amplitude and areal distribution. Strong motions were estimated using the 3D-FEM with and without considering regional topography. The estimations of maximum ground acceleration, velocity, and permanent ground deformations were compared among each other as well as with those inferred from failures of some simple structures in the Spera and Gayan districts. The inferred maximum ground acceleration and velocity from the failed adobe structures were more than 300 Gal and 50 cm/s, respectively, nearly consistent with the estimates obtained using empirical methods. The empirical method yielded a maximum ground acceleration of 347 Gal, whereas the maximum ground velocity was approximately 50 cm/s. In light of these findings, some surface expressions of crustal deformations and strong ground motions, such as failures of soil and rock slopes and rockfalls, have been presented. The rock slope failures in the epicentral area were consistent with those observed during various earthquakes in Afghanistan and worldwide. [ABSTRACT FROM AUTHOR]

Medicinal chemistry highly values the benzimidazole scaffold as a pharmacophore owing to its versatile range of biological functions. In the present study, 17 derivatives of 2‐aryl‐N1‐arylacetamido benzimidazoles 3(a–q) were synthesized by nucleophilic substitution reactions between different 2‐chloro‐N‐(aryl)‐acetamides 2(a–q) and 2‐(4‐chlorophenyl)‐1H‐benzo[d]imidazole (1) in N, N‐dimethylformamide, and evaluated for in vitro anti‐HIV and antifungal activities. Of these derivatives, compounds 3 a, 3 b, 3 i, and 3 n showed moderate inhibitory efficacy against HIV‐1 RT, whereas the remaining compounds showed negligible activity compared to the standard drug efavirenz. In contrast, most of the test compounds demonstrated significant efficacy against fungal strains such as Candida albicans and Aspergillus niger. Compounds 3 a, 3 f, 3 m, and 3 n were the most effective antifungal agents. We applied computational approaches to rationalize the potency of the newly synthesized inhibitors. [ABSTRACT FROM AUTHOR]

Inhibitors of the interaction between Neuropilin-1 (NRP-1) and Vascular Endothelial Growth Factor-A165 (VEGF-A165) hold significant promise as therapeutic and diagnostic agents directed against cancers overexpressing NRP-1. In our efforts in this field, a few series of strong and fairly stable peptide-like inhibitors of the general formula Lys(Har)1-Xaa2-Xaa3-Arg4 have been previously discovered. In the current work, we focused on Lys(Har)-Dap/Dab-Pro-Arg sequence. The aim was to examine whether replacing C-terminal Arg with its homologs and mimetics would yield more stable yet still potent inhibitors. Upon considering the results of modelling and other factors, ten novel analogues with Xaa4 = homoarginine (Har), 2-amino-4-guanidino-butyric acid (Agb), 2-amino-3-guanidino-propionic acid (Agp), citrulline (Cit), 4-aminomethyl-phenylalanine [Phe(4-CH2-NH2)] were designed, synthesized and evaluated. Two of the proposed modifications resulted in inhibitors with activity slightly lower [e.g. IC50 = 14.3 μM for Lys(Har)-Dab-Pro-Har and IC50 = 19.8 μM for Lys(Har)-Dab-Pro-Phe(4-CH2-NH2)] than the parent compounds [e.g. IC50 = 4.7 μM for Lys(Har)-Dab-Pro-Arg]. What was a surprise to us, the proteolytic stability depended more on position two of the sequence than on position four. The Dab2-analogues exhibited half-life times beyond 60 h. Our results build up the knowledge on the structural requirements that effective VEGF-A165/NRP-1 inhibitors should fulfil. [ABSTRACT FROM AUTHOR]

In response to the pressing global challenge of antibiotic resistance, time efficient design and synthesis of novel antibiotics are of immense need. Polycyclic polyprenylated acylphloroglucinols (PPAP) were previously reported to effectively combat a range of gram‐positive bacteria. Although the exact mode of action is still not clear, we conceptualized a late‐stage divergent synthesis approach to expand our natural product‐based PPAP library by 30 additional entities to perform SAR studies against methicillin‐resistant Staphylococcus aureus (MRSA). Although at this point only data from cellular assays are available and understanding of molecular drug‐target interactions are lacking, the experimental data were used to generate 3D‐QSAR models via an artificial intelligence training and to identify a common pharmacophore model. The experimentally validated QSAR model enabled the estimation of anti‐MRSA activities of a virtual compound library consisting of more than 100,000 in‐silico generated B PPAPs, out of which the 20 most promising candidates were synthesized. These novel PPAPs revealed significantly improved cellular activities against MRSA with growth inhibition down to concentrations less than 1 μm. [ABSTRACT FROM AUTHOR]

This paper explores the potential of an Integrated Sensing and Communication (ISAC) system to enhance search-and-rescue operations. While prior research has explored ISAC capabilities in Unmanned Aerial Vehicles (UAVs), our study focuses on addressing the specific challenges posed by modern communication standards (e.g., power, frequency, and bandwidth limitations) in the context of search-and-rescue missions. The paper details effective methods for processing echoed signals generated by downlink transmissions and evaluates key performance indicators, including Noise Equivalent Sigma Zero (NESZ) and channel capacity. Additionally, we utilize synchronization uplink signals transmitted by User Equipment (UE) to improve target detection and classification of possible victims by fusing SAR imagery with triangulation results from uplink signals. An experimental campaign validates the proposed setup by integrating SAR images of the environment with active localization results, both produced by a UAV equipped with a Software Defined Radio (SDR) payload. Our results demonstrate the system's capability to detect and localize buried targets in avalanche scenarios, with localization errors ranging from centimeters to 10 m depending on environmental conditions. This successful integration highlights the practical applicability of our approach in challenging search-and-rescue missions. [ABSTRACT FROM AUTHOR]

Abundant datasets are critical to train models based on deep learning technologies for ship detection applications. Compared with optical images, ship detection based on synthetic aperture radar (SAR) (especially the high-Earth-orbit spaceborne SAR launched recently) lacks enough training samples. A novel cross-domain attention GAN (CDA-GAN) model is proposed for optical-to-SAR translation, which can generate high-quality SAR amplitude training samples of a target by optical image conversion. This high quality includes high geometry structure similarity of the target compared with the corresponding optical image and low background noise around the target. In the proposed model, the cross-domain attention mechanism and cross-domain multi-scale feature fusion are designed to improve the quality of samples for detection based on the generative adversarial network (GAN). Specifically, a cross-domain attention mechanism is designed to simultaneously emphasize discriminative features from optical images and SAR images at the same time. Moreover, a designed cross-domain multi-scale feature fusion module further emphasizes the geometric information and semantic information of the target in a feature graph from the perspective of global features. Finally, a reference loss is introduced in CDA-GAN to completely retain the extra features generated by the cross-domain attention mechanism and cross-domain multi-scale feature fusion module. Experimental results demonstrate that the training samples generated by the proposed CDA-GAN can obtain higher ship detection accuracy using real SAR data than the other state-of-the-art methods. The proposed method is generally available for different orbit SARs and can be extended to the high-Earth-orbit spaceborne SAR case. [ABSTRACT FROM AUTHOR]

DDR1 and DDR2 are nonintegrin collagen receptors in the receptor tyrosine kinase family. Both DDRs bind to various collagen types and perform crucial functions in embryo development. DDRs are different from other receptor tyrosine kinases due to their interaction with extracellular matrix components and unusual activation kinetics. DDR regulates cell migration, survival, proliferation, differentiation, and extracellular matrix remodeling. Dysregulated DDR function is linked to the advancement of several human illnesses, including fibrosis, arthritis, neurodegenerative diseases, and cancer. DDRs play a vital role in disease progression and development. Therefore, the use of DDR inhibitors represents a promising therapeutic strategy, particularly for disorders with limited therapy alternatives. In recent years, DDRs have been regarded as attractive targets for drug development, as evidenced by a significant rise in research in this field. The current review illustrates about recent advancement of small molecules, their designing strategies and structure‐activity relationship. The DDR inhibitors can contain various core structures such as pyrimidine, phthalazine, pyrazole, pyrazine, imidazo[1,2‐a]sspyrazine, quinazoline, and thieno[3,2‐b]pyridin‐7‐yl derivatives. Furthermore, based on the constructive analysis of the published derivatives, we found that the majority of the powerful compounds have a similar scaffold (amide linker, hydrophobic tail, hinge binder with or without spacer). Among the different literature, the most potent compounds 4 (imidazo[1,2‐a]pyrazine), 5 (pyridine), 19 (pyridine), and 24 (quinazoline) displayed potent activity against DDR1 with IC50 values ranging from 2.26 – 4.67 nM, while DDR2 IC50 values ranging from 3.2 – 7.29 nM. This approach will help medicinal chemists to refine and develop novel small molecules targeting DDR1 and DDR2. [ABSTRACT FROM AUTHOR]

A series of new 7‐{3‐[3‐(Benzylidene‐amino)‐[1,2,4]triazole‐1‐yl]‐propoxy}‐4‐methyl‐chromen‐2‐one molecular hybrids 7(a–k) were synthesized using molecular hybridization approach. The synthesized new benzylidene‐triazole tethered coumarin molecular hybrids were characterized by spectroscopic studies and elemental analysis. The coumarin molecular hybrids have been explored for their antifungal efficacy in terms of tubulin inhibitors using molecular modelling studies against tubulin alphabeta hetero dimer protein. The results clearly demonstrated strong binding affinity of coumarin molecular hybrids with indole substituted and 2,4‐dihydroxy substituted as antagonists with respective binding scores of −10.5 and −10.7 kcal/mol towards tubulin alphabeta hetero dimer protein which was higher in comparison to standards griseofulvin (−8.2 kcal/mol) and fluconazole (−8.1 kcal/mol). In addition, broth dilution method was used to conduct in‐vitro antifungal studies against three fungal strains namely Candida albicans, Aspergillus niger and Aspergillus fumigatus. The results obtained clearly illustrate the antifungal activity of indole and 2,4‐dihydroxy substituted compounds which are consistent with docking simulations. Out of all the synthesized molecular hybrids, indole and 2,4‐dihydroxy substituted compounds depict outstanding antifungal activity with Minimum Inhibitory Concentration (MIC) value of 31.25 μg/ml and 62.5 μg/ml towards C.albicans and with MIC value of 31.25 for both these molecules towards A.niger in each case which is quite higher than griseofulvin and fluconazole respectively. Present work clearly demonstrates the potential efficacy of synthesized indole and 2,4‐dihydroxy substituted coumarin molecular hybrids to be considered as lead compounds for the development of new agents against resistant strains for the treatment of fungal infection. [ABSTRACT FROM AUTHOR]

The Eastern Mediterranean region, a vital conduit for global maritime trade, faces significant environmental challenges due to marine pollution, particularly from oil spills. This is the first study covering the long period of comprehensive monitoring of oil pollution using the full mission of Sentinel-1 Synthetic Aperture Radar (SAR) data in the Mediterranean Sea, so this research aims to detect and analyze comprehensively the occurrence of oil spills in the Eastern Mediterranean over a decade (2014–2023). This study focuses on identifying geographical distribution patterns, proximity to shorelines, frequency across maritime zones, and potential sources of these spills, especially around major ports and maritime routes. This study utilizes SAR data from the Sentinel-1 satellite. The methodology included automated detection algorithms within the Sentinel application platform (SNAP) and integration with GIS mapping to study oil spill patterns and characteristics. Over 1000 Sentinel-1 scenes were investigated in the northern Mediterranean waters off the coast of Egypt, to detect and analyze 355 oil spill events with a total impacted area of more than 6000 km2. The analysis of temporal spill distribution reveals significant fluctuations from year to year. Within the entire timeline of the study, 2017 had the largest spatial areas covering one thousand square kilometers. In contrast, the single largest spill recorded during the study period occurred in 2020, covering 198.73 square kilometers. The results identified a non-uniform distribution of oil spills and primarily exhibiting elongated patterns aligned with the navigation routes. The distinct increase of oil spill incidents was within the Exclusive Economic Zone (EEZ), obviously drifted to the coastline and around major ports. The study emphasizes the critical role of remote sensing technologies in addressing environmental challenges caused by the maritime transport sector, advocating for enhanced monitoring and regulatory enforcement to protect marine ecosystems and support sustainable naval activities. The findings highlight the urgent need for targeted continuous monitoring and rapid response strategies in high-traffic maritime areas, particularly around the EEZ and major ports. [ABSTRACT FROM AUTHOR]

There is an urgent need to develop non-destructive testing (NDT) methods for infrastructure facilities and residences, etc., where human lives are at stake, to prevent collapse due to aging or natural disasters such as earthquakes before they occur. In such inspections, it is desirable to develop a remote, non-contact, non-destructive inspection method that can inspect cracks as small as 0.1 mm on the surface of a structure and damage inside and on the surface of the structure that cannot be seen by the human eye with high sensitivity, while ensuring the safety of the engineers inspecting the structure. Based on this perspective, we developed a radar module (absolute gain of the transmitting antenna: 13.5 dB; absolute gain of the receiving antenna: 14.5 dB) with very high directivity and minimal loss in the signal transmission path between the radar chip and the array antenna, using our previously developed technology. A single-input, multiple-output (SIMO) synthetic aperture radar (SAR) imaging system was developed using this module. As a result of various performance evaluations using this system, we were able to demonstrate that this system has a performance that fully satisfies the abovementioned indices. First, the SNR in millimeter-wave (MM-wave) imaging was improved by 5.4 dB compared to the previously constructed imaging system using the IWR1443BOOST EVM, even though the measured distance was 2.66 times longer. As a specific example of the results of measurements on infrastructure facilities, the system successfully observed cracks as small as 0.1 mm in concrete materials hidden under glass fiber-reinforced tape and black acrylic paint. In this case, measurements were also made from a distance of about 3 m to meet the remote observation requirements, but the radar module with its high-directivity and high-gain antenna proved to be more sensitive in detecting crack structures than measurements made from a distance of 780 mm. In order to estimate the penetration length of MM waves into concrete, an experiment was conducted to measure the penetration of MM waves through a thin concrete slab with a thickness of 3.7 mm. As a result, Λexp = 6.0 mm was obtained as the attenuation distance of MM waves in the concrete slab used. In addition, transmission measurement experiments using a composite material consisting of ceramic tiles and fireproof board, which is a component of a house, and experiments using composite plywood, which is used as a general housing construction material in Japan, succeeded in making perspective observations of defects in the internal structure, etc., which are invisible to the human eye. [ABSTRACT FROM AUTHOR]

Infections with Flaviviridae viruses, such as hepatitis C (HCV), dengue (DENV), and yellow fever (YFV) viruses, are major public health problems worldwide. In the case of HCV, treatment is associated with drug resistance and high costs, while there is no clinically approved therapy for DENV and YFV. Consequently, there is still a need for new chemotherapies with alternative modes of action. We have previously identified novel 2-hydroxypyrazino[1,2-a]indole-1,3(2H,4H)-diones as metal-chelating inhibitors targeting HCV RNA replication. Here, by utilizing a structure-based approach, we rationally designed a second series of compounds by introducing various substituents at the indole core structure and at the imidic nitrogen, to improve specificity against the RNA-dependent RNA polymerase (RdRp). The resulting derivatives were evaluated for their potency against HCV genotype 1b, DENV2, and YFV-17D using stable replicon cell lines. The most favorable substitution was nitro at position 6 of the indole ring (compound 36), conferring EC50 1.6 μM against HCV 1b and 2.57 μΜ against HCV 1a, with a high selectivity index. Compound 52, carrying the acetohydroxamic acid functionality (-CH2CONHOH) on the imidic nitrogen, and compound 78, the methyl-substituted molecule at the position 4 indolediketopiperazine counterpart, were the most effective against DENV and YFV, respectively. Interestingly, compound 36 had a high genetic barrier to resistance and only one resistance mutation was detected, T181I in NS5B, suggesting that the compound target HCV RdRp is in accordance with our predicted model. [ABSTRACT FROM AUTHOR]

Multichannel Synthetic Aperture Radar (MC-SAR) systems, such as Azimuth Multi-Phase Centre (AMPC) SAR, provide an effective solution for achieving high-resolution wide-swath (HRWS) imaging by reducing the pulse repetition frequency (PRF) to increase the swath width. However, in an Electronic Countermeasures (ECM) environment, the image quality of multichannel SAR systems can be significantly degraded by electromagnetic interference. Previous research into interference and counter-interference techniques has predominantly focused on single-channel SAR systems, with relatively few studies addressing the specific challenges faced by MC-SAR systems. This paper uses the classical spatial filtering technique of adaptive digital beamforming (DBF). Considering the Doppler ambiguity present in the echoes, two schemes—Interference Reconstruction And Cancellation (IRC) and Channel Grouping Nulling (CGN)—are designed to effectively eliminate suppressive interference. The IRC method eliminates the effects of interference without losing spatial degrees of freedom, ensuring effective suppression of Doppler ambiguity in subsequent processing. This method shows significant advantages under conditions of strong Doppler ambiguity and low jammer-to-signal ratio. Conversely, the CGN method mitigates the effect of interference on multichannel imaging at the expense of degrees of freedom redundant to Doppler ambiguity suppression. It shows remarkable interference suppression performance under weak-Doppler-ambiguity conditions, allowing for better image recovery. Simulations performed on point and distributed targets have validated that the proposed methods can effectively remove interfering signals and achieve high-resolution wide-swath (HRWS) SAR images. [ABSTRACT FROM AUTHOR]