Miracle-dz/UniFAR-FTUs huggingface dataset:
Lightweight multiscale framework for segmentation of high-resolution remote sensing imagery

Abstract. Deep convolutional neural network semantic segmentation has played a significant role in remote sensing applications due to its capability of end-to-end training and automatic high-level features extraction. Highly accurate predictions have been recorded from different network architectures that are designed using the convolutional layers. However, the accuracy is mainly achieved at a very high cost of computation, which renders the network infeasible for real-time application on resource-constrained devices. Therefore, there is a need to establish a trade-off between accuracy and model efficiency. Our paper proposes a lightweight, highly accurate, memory-efficient segmentation network capable of deployment on resource-constrained devices. Our proposed network of 1.09 million trainable parameters attains an appreciable accuracy of 89.41% and 88.78% on the Vaihingen and Potsdam respective dataset of the ISPRS 2D Semantic Labeling Challenge. The result from the speed and the memory efficiency experiment shows that our proposed network is suitable for real-time remote sensing applications.
Land cover classification based on the PSPNet and superpixel segmentation methods with high spatial resolution multispectral remote sensing imagery

Abstract. Classifying land cover using high-resolution remote-sensing images is challenging. The emergence of deep learning provides improved possibilities, but owing to the limitations of network structures, traditional convolutional neural network methods lose essential information about boundaries and small ground objects. We propose a superpixel-optimized convolutional neural network (SOCNN) framework to overcome this weakness. The SOCNN includes three modules: a semantic segmentation module, a superpixel optimization module, and a fusion module. The performance of the first module was evaluated using several common networks. PSPNet outperformed other networks, obtaining a pixel accuracy of 83.25%, a Kappa coefficient of 0.7862, and a mean intersection over union of 64.19%. Weighted loss was introduced to alleviate the effect of category imbalance, and the class pixel accuracy of category 11 improved by 19.77% with a weight of 20. The subpixel model was evaluated, and the pixel accuracy reached 83.43% with the superpixel-FCN method. Our superpixel optimized module improved the pixel accuracy of the object boundary by 1.37% when the fusion factor was 0.65. These results show that the SOCNN method is effective for recovering boundary information.
MDCNN: multispectral pansharpening based on a multiscale dilated convolutional neural network

Abstract. Convolutional neural networks (CNNs) have achieved remarkable results in multispectral (MS) and panchromatic (PAN) image fusion (pansharpening) because of their strong image feature extraction ability. However, previous CNN-based pansharpening methods mostly use an ordinary convolution, which has a small receptive field in the convolution layer, has insufficient contextual information, and can only extract shallow features, which is not conducive to learning the complex nonlinear mapping relationship between the input image and the fused image. Therefore, this study proposes a pansharpening algorithm based on a multiscale densely convolutional neural network (MDCNN). First, a two-stream network is used for feature extraction, with two convolution layers to extract spectral information from MS images. The multiscale convolutional feature extraction module is designed to extract the spatial detail features of the PAN images. Second, the proposed multiscale densely connected modules and residual modules are used as the backbone of the fusion network. Finally, the deep features generated are reconstructed, and spectral mapping is used to retain spectral information to obtain a high-resolution fusion image. Experimental results using three satellite image datasets show that the proposed algorithm generates high-quality fusion images, and it outperforms most advanced pansharpening methods in subjective visual and objective evaluation indexes.
Panchromatic and multispectral image fusion using the spatial frequency and the à trous wavelet transform

Abstract. We propose a panchromatic (Pan) and multispectral (MS) image fusion method in order to synthesize an MS image with enhanced spatial resolution and preserved spectral information of the original MS image. The proposed method is based on the spatial frequency and the à trous wavelet transform (SFATWT). The à trous wavelet transform (ATWT) is used to decompose Pan and MS images into low and high frequencies. The spatial frequency is exploited in the image fusion rules to improve the details or the high-frequency information which will be injected into the MS image. The ATWT reconstruction makes it possible to produce MS image with high spatial resolution. To validate the proposed method, two image sets are used. The first one is acquired by the SPOT (Satellite Pour l’Observation de la Terre) satellite with a resolution ratio of 2. The second one is the Algerian satellite AlSat 2A images with a resolution ratio of 4. The fused results are evaluated by means of qualitative and quantitative comparisons. The assessment of fused products has shown that the proposed method is promising.
Efficient multitask learning analyses on grain silo measurement

Abstract. Determining the amount of grain stored in silos is very important for accurate commercial inventory planning. A convolutional neural network (CNN) is developed for the first time to determine the amount of the grain using step-frequency continuous wave radar (SFCWR) signals. The radar reflection signal of different grain quantity for different grain surface patterns is gathered by means of a constructed experimental setup. 5681 measurements are performed in the scaled model silo containing different weights (0 to 20 kg) grain stacked as different surface patterns. The dataset is then created using the spectrograms of SFCWR signals. While 1420 data randomly selected from the dataset are used for testing, the remaining 4261 data are used for training. The results are then compared with the pretrained CNNs, demonstrating the superiority of the proposed method. The accuracy of the methods is given with metric parameters for both classification and regression. The proposed multitask CNN model obtained higher performance with 0.2865 MAE, 0.5053 MAPE, 0.8047 MSE, and 0.8971 RMSE for regression task and 99.23% accuracy, 99.09% sensitivity, 99.52% specitivity, 99.42% precision, 99.25% F1-score, and 98.83% MCC for classification. These metric performances are better than the previous study with 3.29 MAPE in the literature. The results obtained reveal that, with proper modeling and successful training, CNNs can be effectively used for the quantity measurement applications of the grain stacks.
Quantitative Estimation of Total Phenolicsand Flavonoids in Soymida febrifuga leaves

Soymida febrifuga is belonging to family meliaceae. The bark, fruit and leaves contains important constituents like Quercetin-3-O-L-rhamnoside, 3-O-rutinoside, lupeol, sitosterol, methyl angolensate, deoxyandirobin. The plant has found to be ethnobotanically important. The bark is acrid; refrigerant, anthelmintic, aphrodisiac, laxative; good for sore throat; removes “vata “ cures “tridosha” fevers, cough; removes blood impurities; good for ulcers, leprosy, dysentery (Ayurveda). The bark is the bowels and useful in fevers in fevers (Yunani). The bark is astringent, tonic and antiperiodic [1,2]. In intermittent fevers and general debility, in the advanced stages of dysentery, in diarrhea, and in other cases requiring the use of astringents, it has been used with success. The decoction forms a good substitute for oak-bark, and is well adapted for gargles, vaginal infections and enemas. Present study revealed the estimations of total phenolics and flavonoids were carried out according to standard procedure. Estimation of Total Phenolic Folin Ciocalteu Method and Aluminium chloride colorimetric method was used for flavonoids determination. Determination of total phenolics and flavonoids were carried out results methanol extract contains 21.7%, water 48.2% and total aqueous 32.23% w/w of and methanol contains 24.27%, water 42.86% and total aqueous 26.38% respectively.
Feeling excited and fluent: how consumers respond to the visual appeals of products in an online shopping environment

ABSTRACT Visual appeal is a critical determinant in eliciting positive consumer responses. In an online shopping environment, in which consumers’ interaction with products is limited to the visual, the pictorial representation of products becomes of paramount importance. While product visual appeal is a widely applied concept, relatively little is known about the underlying mechanisms of how consumers process the visual appearance of a product in an online setting and form attitudes toward a newly encountered brand. The purpose of this study is to examine both how varying levels of product visuals online affect aesthetic appreciation and brand attitudes as well as to what extent arousal and processing fluency can link appreciation and attitudes. The levels of online product visual appeals were manipulated in a 2 (good vs. plain package design) × 2 (high vs. low image quality) factorial design (N = 407). The contrast analysis revealed that better product visuals increased the arousal and fluency that consumers experienced. The structural equation modeling showed that consumers’ arousal and fluency mediated the relationship between product visuals and consumers’ aesthetic and attitudinal responses. The regression analysis also indicated that arousal and processing fluency independently affected visual aesthetic appreciation.
Designing sampling protocols for plant-pollinator interactions - timing, meteorology, flowering variations and failed captures matter

ABSTRACT Plant-pollinator interactions are key components of ecosystem functioning and are therefore increasingly studied. Of all the approaches used to estimate these interactions, the capture of pollinators along transects is a widely used and recognized method. However, specific choices of sampling design can strongly influence observations of insect visits and bias ecological interpretations. Yet, there is no agreement on the best transect design. Sampling intensity (number and length of transects) is an important element of these choices, but not the only one. Here we investigate the influence of three other facets of protocol choices that commonly arise when designing pollination transects: (i) the influence of sampling conditions that may interact with ecological variables of interest or bias observations, (ii) the measurement of floral availability frequency, and (iii) the management of insects observed but not captured. We quantified the importance of these three protocol choices using a large dataset of 720 plant-pollinator transects in protected wet meadows in France. Our results demonstrate the need to (i) cover a wide range of temporal and meteorological conditions for each site, and (ii) repeat the assessment of plot attractiveness for pollinators (a major covariate, usually simply derived from one-off vegetation surveys). In addition, we show that (iii) for analyses of visitation density among insect groups, failed insect captures should not be discarded but incorporated into the analyses. Overall, this research identifies three key choices in transect design and highlights their influence in our understanding of plant-pollinator interactions.
Is Ophrys pollination more opportunistic than previously thought? Insights from different field methods of pollinator observation

ABSTRACT Global changes induce a general decline in the abundance and diversity of European orchids and their pollinators. Such a decline is especially likely to affect species engaged in specialized interactions, thereby causing their replacement by generalists. In this study, we focused on sexually deceptive orchids from the genus Ophrys, which are often described as extreme specialists. We describe several observations of Ophrys pollinators in the Mediterranean region in order to: i) compare four different field methods to monitor Ophrys pollinators, and ii) provide more information on these pollinators to re-evaluate the specialization of Ophrys-pollinator interactions and discuss the ecological context in which these interactions take place. We discovered several new pollinator species for various Ophrys taxa, including unexpected ones. We also showed that the prolonged observation of mass-flowering and neighbouring Ophrys plants optimizes the chances of observing Ophrys pollinators without disturbing natural pollination. We argue that Ophrys pollination may be more opportunistic than classically described in the literature, likely involving one main pollinator and one or several secondary pollinators across the range of each Ophrys species. This study provides new methodological and conceptual insights into Ophrys pollination.
Review on spatial domain image steganography techniques

Abstract Steganography techniques leads main role in embedding process of secret information into cover information in order to provide good security. These techniques are very essential, when sending the confidential information from one place to another place in the field of defense and medical. Hence, it is a challenging and important task to hide the secret information in to cover information. This review provides classification of steganography techniques, existing and proposed techniques with advantages and disadvantages. As per observations of existing methods, much amount of information hides using spatial domain techniques than transform domain techniques. This review mainly focuses on the spatial domain image steganography techniques.
Probing syllable structure through acoustic measurements: case studies on American English and Jazani Arabic

Previous research has found that different syllabic (particularly simplex vs. complex onset) organisations have different temporal stability signatures in articulations – this observation is based entirely on articulatory measurements. In this article, we present the results of three production experiments which show that similar correlations between onset organisation and temporal stability metrics are observable in an analysis of acoustic measurements in American English and Jazani Arabic. The results that we present show stability across speakers and test items for both language groups, and highlight the possibility of using acoustic techniques to help to investigate the organisation of onsets in other languages.
Much ado about nothing: assessing the impact of the 4.2 kya event on human subsistence patterns in northern Mesopotamia using stable isotope analysis

Abstract The effects of the 4.2 kya climatic event on northern Mesopotamia have been the subject of significant scholarly debate, with the notion of a megadrought that forced local populations to migrate attracting particular attention. Here, the authors analyse stable carbon (δ13C) and nitrogen (δ15N) isotopes in human tooth and bone samples to assess trends in subsistence practice at three sites in Syria before, during and after the presumed megadrought event. Despite the proximity of the sites, isotopic differences between them are more significant than diachronic change. Combined with other archaeological evidence, these results indicate a continuity in subsistence patterns, with no indication of disruption associated with the 4.2 kya event.
The earliest water buffalo in the Caucasus: shifting animals and people in the medieval Islamic world

Abstract The expansion of the Umayyad and Abbasid Caliphates (seventh to ninth centuries AD) brought diverse regions from the Indus Valley to the Eurasian Steppe under hegemonic control. An overlooked aspect of this political process is the subsequent translocation of species across ecological zones. This article explores species introduction in the early Islamic world, presenting the first archaeological evidence for domestic water buffalo in the Caucasus—identified using zooarchaeological and ZooMS methods on material from the historical site of Bardhaʿa in Azerbaijan. We contextualise these finds with historical accounts to demonstrate the exploitation of medieval marginal zones and the effects of centralised social reorganisation upon species dispersal.
A method for space archaeology research: the International Space Station Archaeological Project

Abstract How does a ‘space culture’ emerge and evolve, and how can archaeologists study such a phenomenon? The International Space Station Archaeological Project seeks to analyse the social and cultural context of an assemblage relating to the human presence in space. Drawing on concepts from contemporary archaeology, the project pursues a unique perspective beyond sociological or ethnographical approaches. Semiotic analysis of material culture and proxemic analysis of embodied space can be achieved using NASA's archives of documentation, images, video and audio media. Here, the authors set out a method for the study of this evidence. Understanding how individuals and groups use material culture in space stations, from discrete objects to contextual relationships, promises to reveal intersections of identity, nationality and community.
Repositioning of Fungal-based Peptides as Modulators of Angiotensin-converting Enzyme-related Carboxypeptidase, SARS-coronavirus HR2 Domain, and Coronavirus Disease 2019 Main Protease

Abstract Background and Objectives Angiotensin-converting enzyme-related carboxypeptidase, SARS-Coronavirus HR2 Domain, and COVID-19 main protease are essential for the cellular entry and replication of coronavirus in the host. This study investigated the putative inhibitory action of peptides form medicinal mushrooms, namely Pseudoplectania nigrella, Russula paludosa, and Clitocybe sinopica, towards selected proteins through computational studies. Materials and Methods The respective physicochemical properties of selected peptides were predicted using ProtParam tool, while the binding modes and binding free energy of selected peptides toward proteins were computed through HawkDock server. The structural flexibility and stability of docked protein–peptide complexes were assessed through iMODS server. Results The peptides showed an optimum binding afinity with the molecular targets; plectasin from P. nigrella showed the highest binding free energy compared to peptides from R. paludosa and C. sinopica. Besides, molecular dynamic simulations showed all fungal-based peptides could influence the flexibility and stability of selected proteins. Conclusion The study revealed fungal-based peptides could be explored as functional modulators of essential proteins that are involved in the cellular entry of coronavirus.
Computer Methods and Programs in Biomedicine

Background: As blood testing is radiation-free, low-cost and simple to operate, some researchers use machine learning to detect COVID-19 from blood test data. However, few studies take into consideration the imbalanced data distribution, which can impair the performance of a classiﬁer. Method: A novel combined dynamic ensemble selection (DES) method is proposed for imbalanced data to detect COVID-19 from complete blood count. This method combines data preprocessing and improved DES. Firstly, we use the hybrid synthetic minority over-sampling technique and edited nearest neighbor (SMOTE-ENN) to balance data and remove noise. Secondly, in order to improve the performance of DES, a novel hybrid multiple clustering and bagging classiﬁer generation (HMCBCG) method is proposed to reinforce the diversity and local regional competence of candidate classiﬁers. Results: The experimental results based on three popular DES methods show that the performance of HMCBCG is better than only use bagging. HMCBCG + KNE obtains the best performance for COVID-19 screening with 99.81% accuracy, 99.86% F1, 99.78% G-mean and 99.81% AUC. Conclusion: Compared to other advanced methods, our combined DES model can improve accuracy, G-mean, F1 and AUC of COVID-19 screening
A new sugar for an old phage: A c-di-GMP dependent polysaccharide pathway sensitizes E. coli for bacteriophage infection

Bacteriophages are ubiquitous parasites of bacteria and major drivers of bacterial ecology and evolution. Despite an ever-growing interest in their biotechnological and therapeutic applications, detailed knowledge of the molecular mechanisms underlying phage-host interactions remains scarce. Here, we show that bacteriophage N4 exploits a novel surface glycan, NGR, as a receptor to infect its host Escherichia coli. We demonstrate that this process is regulated by the second messenger c-di-GMP and that N4 infection is specifically stimulated by the diguanylate cyclase DgcJ while the phosphodiesterase PdeL effectively protects E. coli from N4-mediated killing. PdeL-mediated protection requires its catalytic activity to reduce c-di-GMP and includes a secondary role as a transcriptional repressor. We demonstrate that PdeL binds to and represses the promoter of the wec operon, which encodes components of the ECA exopolysaccharide pathway. However, only the acetylglucosamine epimerase WecB but none of the other ECA components is required for N4 infection. Based on this, we postulate that NGR is an N-acetylmannosamine-based carbohydrate polymer that is produced and exported to the cell surface of E. coli in a c-di-GMP dependent manner where it serves as a receptor for N4. This novel carbohydrate pathway is conserved in E. coli and other bacterial pathogens, serves as the primary receptor for a range of N4-like bacteriophages, and is induced at elevated temperature and by specific amino acid-based nutrients. These studies provide an entry point into understanding how bacteria use specific regulatory mechanisms to balance costs and benefits of highly conserved surface structures. Importance Because bacterial surface glycans are in direct contact with the environment they can provide essential protective functions during infections or against competing bacteria. But such structures are also ‘Achilles heels’ as they can serve as primary receptors for bacteriophages. Bacteria thus need to carefully control the exposure of conserved surface glycans to balance costs and benefits. Here, we identify a novel exopolysaccharide that is widely conserved in E. coli and is used by N4 and related bacteriophages as primary receptor. We demonstrate that the synthesis of NGR (N4 glycan receptor) is tightly controlled by the second messenger c-di-GMP in a highly specific manner and by a single diguanylate cyclase. These studies provide an example of how bacteria can alleviate the strong selective pressure imposed on them by bacteriophages entering through conserved surface structures by carefully regulating their synthesis and secretion.