Miracle-dz/UniFAR-FTUs huggingface dataset:
First Report of Low Pathogenic Avian Influenza Subtype H9N2 in African Houbara Bustards (Chlamydotis undulata undulata) and Gamebirds in Morocco: Clinico-Pathological Findings, Molecular Characterization, and Associated Coinfections

We report in this paper the first detection of low pathogenic avian influenza (LPAI) subtype H9N2 in houbara bustards and in gamebirds in Morocco. Starting in 2019, an increase in mortality rates related to respiratory distress was recorded in these species. Necropsy of the specimens revealed fibrinous sinusitis and tracheitis with intra-bronchial fibrin casts, which are consistent with H9N2 infection in chickens; therefore, implication of the virus in these outbreaks was strongly suspected. Consequently, between January 2020 and June 2023, birds with respiratory signs were necropsied for pathological lesions, tissue samples were examined by histopathology, and samples of trachea, lungs, and cecal tonsils were analyzed using quantitative real-time PCR for the detection of H9N2 virus. In addition, the sequencing of isolates was performed and lastly differential diagnosis with other respiratory pathogens was carried out. During the study period, 93 samples were collected from suspected H9N2 outbreaks, of which 30 tested positive for H9N2 virus: 23 Houbara bustards, 4 partridges, 2 quails, and 1 pheasant. Moreover, sequencing of the HA gene of the virus showed 97.33% nucleotide identity with strains reported previously in broilers in Morocco in 2017 and in 2022. Phylogenetic analysis grouped the Moroccan partridge isolates in the same cluster as viruses isolated in Morocco between 2016 and 2022, Algeria (2017), Burkina Faso (2017), Nigeria (2019), and Togo (2020). Additionally, 10 house sparrows from the premises of these birds were examined for the presence of H9N2 virus, revealing a 30% positivity rate. In conclusion, LPAIV H9N2 is circulating in houbara bustards and gamebirds in Morocco, and house sparrows might be a possible source of the infection. To our knowledge, this is the first report of LPAI H9N2 in the African species of houbara bustards worldwide and in gamebirds in Morocco.
Additional distributional data of the genera Brachymeria Westwood and Monodontomerus Westwood (Hymenoptera, Chalcidoidea), with two new records from Greece

Chalcidoidea is a hyperdiverse superfamily of mostly small, parasitoid wasps of which 14 families and at least 422 species have been recorded from Greece. In the present study, additional distributional data from Greece is provided for Brachymeria rugulosa (Forster, 1859) and Brachymeria tibialis (Walker, 1834). Furthermore, Brachymeria podagrica (Fabricius, 1787) and Monodontomerus obscurus Westwood, 1833 are recorded for the first time from Greece. As well, a new host gall species for B. rugulosa is noted and the presence of Brachymeria inermis (Fonscolombe, 1840) is briefly discussed. Finally, a checklist for the genera Brachymeria (Hymenoptera, Chalcididae) and Monodontomerus (Hymenoptera, Torymidae) is compiled.
Acute In Vivo Administration of Compound 21 Stimulates Akt and ERK1/2 Phosphorylation in Mouse Heart and Adipose Tissue

The angiotensin II type 2 (AT2) receptor has a role in promoting insulin sensitivity. However, the mechanisms underlying the AT2 receptor-induced facilitation of insulin are still not completely understood. Therefore, we investigated whether acute in vivo administration of AT2 receptor agonist compound 21 (C21) could activate insulin signaling molecules in insulin-target tissues. We report that, in male C57BL/6 mice, an acute (5 min, 0.25 mg/kg; i.v.) injection of C21 induces the phosphorylation of Akt and ERK1/2 at activating residues (Ser473 and Thr202/Tyr204, respectively) in both epididymal white adipose tissue (WAT) and heart tissue. In WAT, the extent of phosphorylation (p) of Akt and ERK1/2 induced by C21 was approximately 65% of the level detected after a bolus injection of a dose of insulin known to induce maximal activation of the insulin receptor (IR). In the heart, C21 stimulated p-Akt to a lesser extent than in WAT and stimulated p-ERK1/2 to similar levels to those attained by insulin administration. C21 did not modify p-IR levels in either tissue. We conclude that in vivo injection of the AT2 receptor agonist C21 activates Akt and ERK1/2 through a mechanism that does not involve the IR, indicating the participation of these enzymes in AT2R-mediated signaling.
De Novo RNA Sequencing and Transcriptome Analysis of Sclerotium rolfsii Gene Expression during Sclerotium Development

Sclerotium rolfsii is a destructive soil-borne fungal pathogen that causes stem rot in cultivated plants. However, little is known about the genetic basis of sclerotium development. In this study, we conducted de novo sequencing of genes from three different stages of S. rolfsii (mycelia, early sclerotium formation, and late sclerotium formation) using Illumina HiSeqTM 4000. We then determined differentially expressed genes (DEGs) across the three stages and annotated gene functions. STEM and weighted gene-co-expression network analysis were used to cluster DEGs with similar expression patterns. Our analysis yielded an average of 25,957,621 clean reads per sample (22,913,500–28,988,848). We identified 8929, 8453, and 3744 DEGs between sclerotium developmental stages 1 versus 2, 1 versus 3, and 2 versus 3, respectively. Additionally, four significantly altered gene expression profiles involved 220 genes related to sclerotium formation, and two modules were positively correlated with early and late sclerotium formation. These results were supported by the outcomes of qPCR and RNA-sequencing conducted on six genes. This is the first study to provide a gene expression map during sclerotial development in S. rolfsii, which can be used to reduce the re-infection ability of this pathogen and provide new insights into the scientific prevention and control of the disease. This study also provides a useful resource for further research on the genomics of S. rolfsii.
Thresholding approaches for estimating paraspinal muscle fat infiltration using T1‐ and T2‐weighted MRI: Comparative analysis using water–fat MRI

Abstract Background Paraspinal muscle fat infiltration is associated with spinal degeneration and low back pain, however, quantifying muscle fat using clinical magnetic resonance imaging (MRI) techniques continues to be a challenge. Advanced MRI techniques, including chemical‐shift encoding (CSE) based water–fat MRI, enable accurate measurement of muscle fat, but such techniques are not widely available in routine clinical practice. Methods To facilitate assessment of paraspinal muscle fat using clinical imaging, we compared four thresholding approaches for estimating muscle fat fraction (FF) using T1‐ and T2‐weighted images, with measurements from water–fat MRI as the ground truth: Gaussian thresholding, Otsu's method, K‐mean clustering, and quadratic discriminant analysis. Pearson's correlation coefficients (r), mean absolute errors, and mean bias errors were calculated for FF estimates from T1‐ and T2‐weighted MRI with water–fat MRI for the lumbar multifidus (MF), erector spinae (ES), quadratus lumborum (QL), and psoas (PS), and for all muscles combined. Results We found that for all muscles combined, FF measurements from T1‐ and T2‐weighted images were strongly positively correlated with measurements from the water–fat images for all thresholding techniques (r = 0.70–0.86, p < 0.0001) and that variations in inter‐muscle correlation strength were much greater than variations in inter‐method correlation strength. Conclusion We conclude that muscle FF can be quantified using thresholded T1‐ and T2‐weighted MRI images with relatively low bias and absolute error in relation to water–fat MRI, particularly in the MF and ES, and the choice of thresholding technique should depend on the muscle and clinical MRI sequence of interest.
Atoms of the lattices of residuated mappings

Given a lattice L, we denote by Res(L) the lattice of all residuated maps on L. The main objective of the paper is to study the atoms of Res(L) where L is a complete lattice. Note that the description of dual atoms of Res(L) easily follows from earlier results of Shmuely (1974). We first consider lattices L for which all atoms of Res(L) are mappings with 2-element range and give a sufficient condition for this. Extending this result, we characterize these atoms of Res(L) which are weakly regular residuated maps in the sense of Blyth and Janowitz (Residuation Theory, 1972). In the rest of the paper we investigate the atoms of Res(M) where M is the lattice of a finite projective plane, in particular, we describe the atoms of Res(F), where F is the lattice of the Fano plane.
A Hierarchical Scheme of Road Unevenness Perception With LiDAR for Autonomous Driving Comfort

Road unevenness is a significant factor affecting the comprehensive driving performance of vehicles. Monitoring road roughness conditions in advance significantly contributes to ride safety and comfort. However, there are hardly comprehensive implementations for comfort promotion purpose based on LiDAR point clouds. This paper proposes a hierarchical scheme that separately describes road regular and irregular unevenness. Firstly, real-vehicle experiments for collecting point clouds of various uneven roads are conducted with the designed hardware platform. A dense point cloud dataset with road bump or pothole annotations is released. Then, an improved PointNet++ model adapted to irregular unevenness recognition is developed. Comparison experiments with the recent segmentation methods verify the superiority of our model in this task. The mIoU metric on the test set reaches 91.6%, outperforming 3.0% than the original model. Road elevation profiles on tire trajectories are finally constructed. The statistical parameters of regular unevenness and geometric features of the irregular sections are extracted, respectively. The proposed perception scheme for road roughness provides detailed and accurate road condition information. It has great potential in practical applications for road unevenness monitoring and vehicle comfort improvement.
Researching long-run trends in South East England 1931-2011 for the European Union and Greater London Authority

This paper describes the sources, methods and preliminary results of two related projects on historical census data funded by government bodies for policy purposes. Both required data for diverse historical reporting areas to be redistricted to a single set of modern units. All redistricting is done by a simple vector overlap method, but this requires boundary data for both the modern and the historical units; and, as far as possible, that the historical units be more detailed than the modern ones. Even for recent periods, locating boundary maps is often much harder than locating statistics.
A re-evaluation of a Laxfordian terrane boundary in the Lewisian Complex of South Harris, NW Scotland

The recent reinterpretation of the Lewisian Complex as a series of amalgamated terranes represents a significant advance in our understanding of these rocks. However, on the Outer Hebrides, a key observation that a supposed post-1675 Ma terrane boundary is based on is flawed. Specifically, on South Harris a group of c. 1675 Ma granite pegmatites has previously been described as occurring only to the NE of, and terminating abruptly within, a supposed terrane-bounding shear zone (the Langavat Shear Zone), which thus post-dates the pegmatites. New mapping indicates that granite pegmatites occur on both sides of, and throughout the Langavat Shear Zone, and that within most of this shear zone the pegmatites are not strongly deformed, inconsistent with them predating this shear zone. Furthermore, new U–Pb geochronological data suggest that the pegmatites SW of the supposed boundary were also intruded around 1675 Ma, similar to those in the NE, and supporting the field evidence that the pegmatites continue through the Langavat Shear Zone without interruption. Two phases of post-pegmatite deformation are identified, but these relate to relatively minor reactivation of the Langavat Shear Zone, not the initiation of this major shear zone, which predates the pegmatites.
Use of Enabling Levers and Constraining Levers to Radical Innovation: Intervention of Knowledge Sharing and Technological Turbulence

Purpose: This study investigates how the absorptive management control system affects in the development of radical innovation. The purpose of this paper is to analyze the influence of using different types of management control (enabling levers and constraining levers) on radical innovation, which is mediated by knowledge sharing and moderated by technological turbulence. Methods: This study uses a methodology partial least squares structural equation modeling and qualitative comparative analysis have been applied to a sample of 253 Indonesian startups. Results and Conclusion: Enabling levers and constraining levers have an influence in generating the necessary knowledge sharing for a company to transfer information within, which affects the production of radical innovation, meaning innovation that is in line with market development and demand. Technological turbulence, as a moderator, has a relationship between knowledge sharing and radical innovation. Implication of research: The results can be useful for managers of startups in the traction stage, as the research highlights different management controls and possible combinations that can be used to drive radical innovation. Additionally, the research highlights the role of knowledge sharing in promoting radical innovation, especially in the context of technological turbulence.
Federated-Learning Topic Modeling Based Text Classification Regarding Hate Speech During COVID-19 Pandemic

—One of the most challenging tasks in knowledge discovery is extracting the semantics of the content regarding emotional context from the natural language text. The COVID-19 pandemic gave rise to many serious concerns and has led to several controversies including spreading of false news and hate speech. This paper particularly focuses on Islamophobia during the COVID-19. The widespread usage of social media platforms during the pandemic for spreading of false information about Muslims and their common religious practices has further fueled the existing problem of Islamophobia. In this respect, it becomes very important to distinguish between the genuine information and the Islamophobia related false information. Accordingly, the proposed technique in this paper extracts features from the textual content using approaches like Word2Vec and Global Vectors. Next, the text classification is performed using various machine learning and deep learning techniques. The performance comparison of various algorithms has also been reported. After experimental evaluation, it was found that the performance metric like F1-score indicate that Support Vector Machine performs better than other alternatives. Similarly, Convolutional Neural Network also achieved promising results.
A Study on New Identification Method and Application Case for Black-Spots Section of Mountainous Highways

The method for identifying the black-spots section of highways in mountainous terrain is an important research content of the traffic safety.When technical indexes of road can't ensure safety movement of vehicle,the movement of vehicle will incline towards danger,which causes the black-spots section of road.The parameters of operating speed and acceleration of the vehicle movement have bigger effects on the vehicle safety,which reflects the movement state of the vehicle from different degree.By comprehensive analysis on speed consistency factor and the acceleration factors,a new method is put forward,namely synthesized analysis method of vehicle movement parameter,for identifying the black-spots of highways in mountainous terrain.On the basis of expatiation for the basic idea of the method,feasible applied conditions and technique process of the method are given.Case study indicates that the method can efficiently identify the black-spots section of highways with complicated road condition in mountainous terrain.
The application of hyperspectral remote sensing to coast environment investigation

Requirements for monitoring the coastal zone environment are first summarized.Then the application of hyperspectral remote sensing to coast environment investigation is introduced,such as the classification of coast beaches and bottom matter,target recognition,mine detection,oil spill identification and ocean color remote sensing.Finally,what is needed to follow on in application of hyperspectral remote sensing to coast environment is recommended.
Flow network derivation from a high resolution DEM in a low relief, agrarian landscape

Digital flow networks derived from digital elevation models (DEMs) sensitively react to errors due to measurement, data processing and data representation. Since high‐resolution DEMs are increasingly used in geomorphological and hydrological research, automated and semi‐automated procedures to reduce the impact of such errors on flow networks are required. One such technique is stream‐carving, a hydrological conditioning technique to ensure drainage connectivity in DEMs towards the DEM edges. Here we test and modify a state‐of‐the‐art carving algorithm for flow network derivation in a low‐relief, agricultural landscape characterized by a large number of spurious, topographic depressions. Our results show that the investigated algorithm reconstructs a benchmark network insufficiently in terms of carving energy, distance and a topological network measure. The modification to the algorithm that performed best, combines the least‐cost auxiliary topography (LCAT) carving with a constrained breaching algorithm that explicitly takes automatically identified channel locations into account. We applied our methods to a low relief landscape, but the results can be transferred to flow network derivation of DEMs in moderate to mountainous relief in situations where the valley bottom is broad and flat and precise derivations of the flow networks are needed. Copyright © 2013 John Wiley & Sons, Ltd.
Diurnal Wind Characteristics in and around Chisapani Confluence of Karnali River in Mid-Western Nepal

The mountain gap flow characteristics in and around the Chisapani mountain gap of Karnali River basin has been numerically simulated using the Weather Research and Forecasting (WRF) model to understand its spatial and temporal characteristics and its implications. The model was initialized with NCEP initial and boundary conditions to carry continuous integrations 168 long hours to identify the general flow field during early springtime. The river valley accumulates channels and flushes a narrow jet stream of about 10 ms-1 in speed and 500 m in its depth into the vast southern plain via Chisapani mountain gap during night and morning time whereas in the afternoon, the mountain feeds up-valley wind of about 4 ms -1 from the southern plain up into the Karnali River basin. Journal of Institute of Science and Technology, 2015, 20(2): 1-5
Assessing functional impulsivity using functional near-infrared spectroscopy

Introduction In neuromarketing, a recently developing, inter-disciplinary field combining neuroscience and marketing, neurophysiological responses have been applied to understand consumers' behaviors. While many studies have focused on explicit attitudes, few have targeted implicit aspects. To explore the possibility of measuring implicit desire for a product, we focused on functional impulsivity related to obtaining a product as a reward and devised a product-rewarded traffic light task (PRTLT). The PRTLT requires participants to take risks under time pressure in order for them to maximize rewards in the form of commercial products, with the brand of products being an independent variable. Thus, we explored the feasibility of applying a PRTLT in a neuromarketing context to implicitly differentiate between the perceived value of products and supported our data with neurophysiological evidence obtained using fNIRS to concurrently monitor cortical activation. Methods Thirty healthy students were asked to perform the PRTLT. We compared participants' functional impulsivity toward two different chocolate products that had obviously different values. Along with their behavioral responses, participants' cerebral hemodynamic responses during the PRTLT were measured using fNIRS covering the lateral prefrontal cortices and the neighboring regions. We conducted adaptive general linear model (GLM) analysis for hemodynamic responses. First, we identified the regions involved in the PRTLT. Second, we compared activation patterns between expensive and inexpensive conditions. Results Behavioral analysis confirmed that the expensive condition trended toward producing a higher PRTLT score than did the inexpensive condition. fNIRS neuroimaging analysis showed task-derived activation in the bilateral dorsolateral prefrontal cortex (DLPFC) and frontopolar cortex (FPC). Moreover, we found significant differences between expensive and inexpensive conditions in the cortical activations in the FPC and the left-DLPFC. Conclusion These results imply that the two products evoked different functional impulsivity, and the hemodynamic responses reflect that. Thus, we concluded that it is possible to observe differences in demand for products using a PRTLT that evokes functional impulsivity. The current study presents a new possibility in neuromarketing research of observing differences between consumers' covert attitudes toward commercially available products, possibly providing a neural basis related to hidden needs for some products.