Miracle-dz/UniFAR-FTUs huggingface dataset:
Apprentissage statistique : application au trafic routier à partir de données structurées et aux données massives

Cette these s'interesse a l'apprentissage pour donnees massives. On considere en premier lieu, des trajectoires definies par des sequences de geolocalisations. Une nouvelle mesure de distance entre trajectoires (Symmetrized Segment-Path Distance) permet d'identifier par classification hierarchique des groupes de trajectoires, modelises ensuite par des melanges gaussiens decrivant les deplacements par zones. Cette modelisation est utilisee de facon generique pour resoudre plusieurs types de problemes lies aux trafic routier : prevision de la destination finale d'une trajectoire, temps d'arrivee a destination, prochaine zone de localisation. Les exemples analyses montrent que le modele propose s'applique a des environnements routiers differents et, qu'une fois appris, il s'applique a des trajectoires aux proprietes spatiales et temporelles differentes. En deuxieme lieu, les environnements technologiques d'apprentissage pour donnees massives sont compares sur des cas d'usage industriels.
A No-Reference Image Sharpness Metric Based on Large-Scale Structure

Most of no-reference image sharpness metrics suffer interference of tiny textures and the contrast around edges. Based on large-scale structure, this paper proposes a novel metric to avoid this problem. Firstly prominent edges are extracted by a weighted least-squares filter. Then, we calculate the statistics proportion of edges with different width and the mean value of the maximum gradients from the 51th to 250th as the features of the image. Finally, the support vector regression is used to get the relationship model between the features and the subjective assessment result. The metric can reduce the influence of textures, contrast and the content of images effectively, accordingly enhancing the assessment accuracy.
Isolation and Characterization of Antimicrobial Metabolites from the Sophora tonkinensis-Associated Fungus Penicillium sp. GDGJ-N37

Chemical investigation of Penicillium sp. GDGJ-N37, a Sophora tonkinensis-associated fungus, yielded two new azaphilone derivatives, N-isoamylsclerotiorinamine (1) and 7-methoxyl-N-isoamylsclerotiorinamine (2), and four known azaphilones (3–6), together with two new chromone derivatives, penithochromones X and Y (7 and 8). Their structures were elucidated based on spectroscopic data, CD spectrum, and semi-synthesis. Sclerotioramine (3) showed significant antibacterial activities against B. subtilis and S. dysentery, and it also showed most potent anti-plant pathogenic fungi activities against P. theae, C. miyabeanus, and E. turcicum.
Formaldehyde and nitrogen dioxide in the atmosphere during summer weather extremes and wildfires in European Russia in 2010 and Western Siberia in 2012

ABSTRACT Based on the data from the Ozone Monitoring Instrument (OMI; Aura) satellite instrument, an analysis of changes in total formaldehyde (CH2O) column and tropospheric nitrogen dioxide (NO2) column, associated with the extreme summer weather regimes and wildfires in European Russia (ER) in 2010 and Western Siberia (WS) in 2012, was carried out. In both territories, over the clusters of intense fires, an approximately two-fold increase in CH2O content and a 20% increase in NO2 content were observed. Unlike NO2, the changes in the CH2O content over ER and WS also reveal positive correlation with the regional surface temperature.
Morphological pre-processing for classification of hyperspectral data from urban areas

Classification of hyperspectral data with high spatial resolution is discussed. A method based on mathematical morphology for pre-processing of the hyperspectral data is investigated. In this approach, opening and closing morphological transforms are used in order to isolate bright (opening) and dark (closing) structures in images, where bright/dark means brighter/darker than the surrounding features in the images. Then, a morphological profile is constructed based on the repeated use of openings and closings with a differently sized structuring element. In order to apply the morphological approach to hyperspectral data, principal components are computed. Then, the principal components are used as base images for the morphological profiles. The use of extended morphological profiles, based on more than one principal component is proposed. In experiments, two data sets are classified. The proposed method performs well in terms of classification accuracies. It gives similar overall accuracies to statistical approaches.
Wiwitan Sebagai Pergelaran Budaya Dalam Tinjauan Ekofeminisme

Penelitian ini melakukan analisis wiwitan di Desa Sumber, Kecamatan Dukun, Kabupaten Magelang, Jawa Tengah sebagai pergelaran budaya. Tradisi Wiwitan secara umum merupakan sebuah bentuk penghormatan kepada Dewi Sri yang merupakan dewi padi. Sejarah turunnya ajaran wiwitan dimulai dari cerita rakyat Dewi Sri yang datang ke Tanah Jawa saat mengalami paceklik. Mereka memohon kepada Tuhan untuk diberikan rezeki dan terbebas dari bencana yang saat itu melanda. Wiwitan merupakan bentuk upacara yang berupa selamatan atau kenduri dan dilaksanakan sebelum melakukan panen. Menarik untuk dilihat mengapa pada masa sekarang ritual ini tetap dilakukan oleh sebagian petani meski dengan cara yang sederhana. Pada ritual tersebut terdapat unsur-unsur pertunjukan. Metode penelitian kualitatif memiliki beberapa keunggulan, yaitu: penyesuaian metode kualitatif lebih mudah apabila berhadapan dengan kenyataan peneliti, menyajikan secara langsung hakikat hubungan antara peneliti dan responden, serta lebih peka dan dapat menyesuaikan diri dengan banyak penajaman pengaruh bersama dan terhadap pola- pola nilai yang dihadapi. Sebagai sebuah kegiatan yang mengandung unsur pertunjukan, maka kajian dari sudut pandang teater sangat memungkinkan. Ada keterkaitan antara teater dan ritual sehingga mengkaji sebuah ritual dengan pendekatan teater ataupun sebaliknya sangat memungkinkan dengan menggunakan pemahaman pergelaran budaya atau cultural performance. Sosok Dewi Sri sebagai dewi padi yang dipuja petani memperlihatkan konsep Kosmologi Jawa terhadap Perempuan. Adanya unsur laki-laki dan perempuan dalam bentuk-bentuk ritual memperlihatkan bahwa kajian ekofeminisme bisa dilakukan pada ritual. Konsep ekofeminisme membahas bagaimana menyetarakan antara perempuan dan bumi serta hubunganya dengan laki-laki dalam budaya patriarki. Kata kunci: wiwitan, pergelaran budaya, ritual, ekofeminisme
Review on Relationship between Drilling Rate and Rock Mechanical Parameters in a Tunnel

The advanced percussive drilling exploration in the rock tunnel is a direct geologic forecast method which is convenient,fast and inexpensive.The geological condition ahead of the workface can be determined by the data obtained from drilling,so the geologic accidents can be avoided to rome degree.By this method the location of strata can be forecasted through three boreholes not in a plane.The prediction ~ strata property is usually a qualita- tive one.In this paper,based on one type of percussive drill and lots of data from drilling,the relationship between drilling rate and some rock mechanical parameters is established.These parameters consist of rock compressive strength,rock density,rock cohesion and angle of internal friction.According to the rock classification standard, drilling data and factual rock class,the relationship between the drilling rate and rock classification index is also es- tablished.Based on these conclusions,the quantitative prediction of strata property can be realized,that is to say, some rock mechanical parameters and rock class can be determined according to the drilling rate.This work will be helpful in changing tunnel design and preventing the accidents.
A Novel Approach to Multi-Channel Speech Enhancement Based on Graph Neural Networks

Multi-channel speech enhancement aims at utilizing spatial relationships between signals captured from a microphone array along with temporal-spectral information efficiently to estimate the clean target. An emerging approach is to design deep learning-based end-to-end architectures. In this work, we provide a new way to process latent multi-channel representations. We introduce a novel end-to-end system called temporal graph convolutional network, which views the embedding space of multi-channel signals as a graph and leverages the power of graph neural networks (GNNs) to analyze spatial correlations as well as temporal-spectral information simultaneously. To be specific, graph convolutional networks (GCNs), a popular GNN variant, are integrated into a complex convolutional encoder-decoder structure to compute a complex ideal ratio mask. The estimated mask is subsequently multiplied with the reference microphone spectrogram to get enhanced speech. We demonstrate the superiority of our approach by comparing it to state-of-the-art methods on ConferencingSpeech 2021 Challenge data. Our results and analyses prove that GCN is a novel yet promising mechanism for speech enhancement systems, providing an interesting alternative for recent deep learning-based approaches and inspiration for future research.
Wild plant species with broader precipitation niches exhibit stronger host selection in rhizosphere microbiome assembly

Abstract Plants actively recruit microbes from the soil, forming species-specific root microbiomes. However, their relationship with plant adaptations to temperature and precipitation remains unclear. Here we examined the host-selected and conserved microbiomes of 13 native plant species in the Xilingol steppe, Inner Mongolia, a semi-arid region in China. By calculating the global precipitation and temperature niches of these plants, considering plant phylogenetic distances, and analyzing functional traits, we found that these factors significantly influenced the rhizosphere microbiome assembly. We further quantified the strength of host selection and observed that plants with wider precipitation niches exhibited greater host selection strength in their rhizosphere microbiome assembly and higher rhizosphere bacterial diversity. In general, the rhizosphere microbiome showed a stronger link to plant precipitation niches than temperature niches. Haliangium exhibited consistent responsiveness to host characteristics. Our findings offer novel insights into host selection effects and the ecological determinants of wild plant rhizosphere microbiome assembly, with implications for steering root microbiomes of wild plants and understanding plant-microbiome evolution.
Impact of ferroptosis-related risk genes on macrophage M1/M2 polarization and prognosis in glioblastoma

Objective To explore the effect impact of ferroptosis on macrophage polarization and patient prognosis in glioblastoma. Methods We screened ferroptosis-related risk from the public datasets of primary and recurrent glioblastoma, combined with reported ferroptosis genes, calculated the risk genes among the ferroptosis-related genes using the LASSO Cox regression model, and investigated the relationship between these ferroptosis-related risk genes in the tumor and the spectrum of infiltrating M1/M2 macrophages. Macrophages were analyzed using the CIBERSORTx deconvolution algorithm. Samples from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA) and a single-cell RNA sequencing dataset (GSE84465) were included. The expression levels of ferroptosis-related risk genes and molecular markers of M1 and M2 macrophages were detected by qPCR and western blot. Results A total of fourteen ferroptosis-related risk genes were obtained and the patients’ risk scores were calculated. Compared with patients in the low-risk group, patients in the high-risk group had worse prognosis. The M1/M2 macrophage ratio and risk score were negatively correlated, indicating that the tumor microenvironment of glioblastoma in the high-risk group contained more M2 than M1 macrophages. In the single-cell RNA sequencing dataset, the risk score of ferroptosis-related genes in tumor cells was positively correlated with the proportion of high M2 macrophages. The expression of eight ferroptosis-related risk genes was increased in glioblastoma cell, which promoted the polarization of M1 macrophages to M2. Conclusion We investigated the fourteen ferroptosis-related risk genes in glioblastoma for the first time, and clarified the impact of ferroptosis-related risk genes on M1/M2 macrophage polarization and patient prognosis.
The effect of diabetes and prediabetes on the prevalence, complications and mortality in nonalcoholic fatty liver disease

Background/Aims Nonalcoholic fatty liver disease (NAFLD) is closely associated with diabetes. The cumulative impact of both diseases synergistically increases risk of adverse events. However, present population analysis is predominantly conducted with reference to non-NAFLD individuals and has not yet examined the impact of prediabetes. Hence, we sought to conduct a retrospective analysis on the impact of diabetic status in NAFLD patients, referencing non-diabetic NAFLD individuals. Methods Data from the National Health and Nutrition Examination Survey 1999–2018 was used. Hepatic steatosis was defined with United States Fatty Liver Index (US-FLI) and FLI at a cut-off of 30 and 60 respectively, in absence of substantial alcohol use. A multivariate generalized linear model was used for risk ratios of binary outcomes while survival analysis was conducted with Cox regression and Fine Gray model for competing risk. Results Of 32,234 patients, 28.92% were identified to have NAFLD. 36.04%, 38.32% and 25.63% were non-diabetic, prediabetic and diabetic respectively. Diabetic NAFLD significantly increased risk of cardiovascular disease (CVD), stroke, chronic kidney disease, all-cause and CVD mortality compared to non-diabetic NAFLD. However, prediabetic NAFLD only significantly increased the risk of CVD and did not result in a higher risk of mortality. Conclusions Given the increased risk of adverse outcomes, this study highlights the importance of regular diabetes screening in NAFLD and adoption of prompt lifestyle modifications to reduce disease progression. Facing high cardiovascular burden, prediabetic and diabetic NAFLD individuals can benefit from early cardiovascular referrals to reduce risk of CVD events and mortality.
Long-term Evaluation of Commercial Air Quality Sensors: An 1 Overview from the QUANT Study 2

In times of growing concern about the impacts of air pollution across the globe, lower-cost sensor 18 technology is giving the first steps in helping to enhance our understanding and ability to manage air quality issues. 19 While the benefits of greater spatial coverage and real-time measurements that these systems offer are evident, 20 challenges still need to be addressed regarding sensor reliability and data quality. Given the limitations imposed by 21 intellectual property, commercial implementations are often "black boxes", which represents an extra challenge as it 22 limits end-users' understanding of the data production process. In this paper we present an overview of the QUANT 23 (Quantification of Utility of Atmospheric Network Technologies) study, a comprehensive 3-year assessment across a 24 range of urban environments in the United Kingdom. QUANT stands out as one of the most comprehensive studies 25 of commercial air quality sensor systems carried out to date, encompassing a wide variety of companies in a single 26 evaluation and including two generations of sensor technologies. Integrated into an extensive data set open to the 27 public, it was designed to provide a long-term evaluation of the precision, accuracy
Manfaat Terapi Kelompok Mindfulness Based Stress Reduction (MBSR) Daring terhadap Kecemasan dan Afek Mahasiswa yang Mengerjakan Skripsi

In order to complete an undergraduate degree, college students in Indonesia are mandated to finish their undergraduate thesis (usually called as „ skripsi ‟ in Indonesian) in their final year of study. Finishing an undergraduate thesis is known to be a challenging process as one‟s ability in problem solving, writing, and conducting research is tested. This study aims to determine the effectiveness of online group Mindfulness Based Stress Reduction (MBSR) in reducing anxiety and negative affect and also increasing positive affect in college students who are currently working on their undergraduate thesis. This study is conducted using a randomized within-between group design with follow-up including an experimental (n = 22) and control group (n = 8). The data is collected in 3 time points (pretest, posttest, and 1 month follow-up) using GAD-7 to measure anxiety and PANAS to measure positive and negative affect. It is found that the experimental group had significantly lower score of anxiety (F(2, 56) = 15.90, p = < . 001) and negative affect (F (2, 56) = 8.76, p = <0.001) at the follow-up. However, there was no significant mean difference in positive affect. In conclusion, online group MBSR is effective in reducing college students‟ anxiety and negative affect during the completion of undergraduate thesis.
Identification of Key Service Features for Evaluating the Quality of Metaverse Services: A Text Mining Approach

Recent advances in the metaverse have revolutionized the way services are experienced, creating a virtual world that seamlessly blends real-life and digital experiences. While research on metaverse services has traditionally focused on technological advancements, recent efforts emphasize the need for a customer-oriented approach to evaluating service quality. However, few studies have explored this customer-oriented approach. To address this gap, this paper identifies and prioritizes nine service features that significantly influence customer satisfaction in metaverse services from a customer-oriented perspective. In particular, this study analyzed 437,527 online customer reviews of Roblox, Bitmoji, and VRchat by employing text mining and machine learning algorithms, such as topic modeling, sentiment analysis, and logistic regression. As a result, the ‘co-experience’ feature emerges as a crucial factor, closely aligned with user objectives when engaging with metaverse services. These findings provide valuable insights for service managers to enhance their offerings effectively, positioning them favorably in the evolving metaverse landscape.
Variational model for infrared and visible light image fusion with saliency preservation

Abstract. Infrared and visible light image fusion is an important issue in the field of infrared technology. A variational model based on saliency preservation is proposed to help fusion process for infrared and visible light image by enhancing the saliency information of source images. The proposed variational model is composed by the weighted fusion term and the gradient fusion term. A weight function constructed by the saliency map of the source images is proposed to form the weighted fusion term. While in the gradient fusion, the target gradient is obtained by the maximum eigen-value and corresponding eigen-vector of the weighted structure tensor that also contains the salient information of the source images. Experimental results indicate that the proposed variational model better emphasizes the target information of the source images and outperforms other state-of-the-art fusion methods in both aspects of subjective visual and objective performance.
Ni–Fe bimetallic catalysts with high dispersion supported by SBA-15 evaluated for the selective oxidation of benzyl alcohol to benzaldehyde

A wetness impregnation method was used to impregnate the substrate with a substantial quantity of oleic acid together with a metal precursor, leading to significantly dispersed Ni–Fe bimetallic catalysts based on mesoporous SBA-15. Using a wide variety of characterization methods, such as XRD, BET, and TEM Analysis, the physiochemical properties of the catalyst were determined. The addition of the metal does not have any effect on the structural characteristics of the SBA-15 catalyst, as validated by transmission electron microscopy (TEM), which shows that the prepared SBA-15 supported catalyst has a hexagonal mesoporous structure. The catalytic capabilities of the Ni–Fe-SBA-15 catalysts were evaluated in the conversion of BzOH using tert-butyl hydroperoxide (TBHP) as an oxidant and acetonitrile as a solvent. The Ni/Fe-SBA-15 (NFS-15) catalytic composition is the best of the developed catalysts, with a maximum conversion of 98% and a selectivity of 99%. In-depth investigations were conducted into the molar ratio of TBHP to BzOH, the dosage of the catalyst, the reaction rate, temperature, and solvent. The recycling investigations indicate that the synthesized Ni/Fe-SBA-15 (NFS-15) catalyst seems to be more durable up to seven successive cycles.
Traffic Data Collection Using Thermal Camera Under Varying Lighting and Temperature Conditions in Multimodal Environments

Vision-based monitoring systems using visible-spectrum (regular) video cameras can complement or substitute conventional sensors and provide rich positional and classification data. Recently, new camera technologies, including thermal video sensors, have become available and may improve the performance of digital video-based sensors. However, the performance of thermal cameras under various lighting and temperature conditions has rarely been evaluated at multimodal facilities including urban intersections, where road user classification is required. The purpose of this research is to integrate existing tracking and classification computer-vision methods for automated data collection and to evaluate the performance of thermal video sensors under varying lighting and temperature conditions. The evaluation is based on the detection, classification, and speed measurements of road users. For this purpose, thermal and regular video data was collected simultaneously under different conditions across multiple sites. Among the main findings, the results show that the regular-video sensor only narrowly outperformed the thermal sensor during daytime conditions. However, the performance of the thermal sensor is significantly better for low visibility and shadows conditions, in particular for pedestrian and cyclist data collection. Interestingly, the thermal video performs acceptably during daytime, with a miss rate around 5 %. This paper also shows the importance of retraining the algorithm on thermal data with an improvement in the global accuracy of 48 %. Moreover, speed measurements by the thermal camera were consistently more accurate than for the regular video at daytime and nighttime. The thermal videos are insensitive to lighting interference and pavement temperature, and solve the issues associated with visible light cameras for traffic data collection, especially for locations with pedestrians and cyclists. In addition, thermal sensors offer other benefits such as privacy, insensitivity to glare, storage space and lower processing requirements.
A re-appraisal of Aralosaurus tuberiferus (Dinosauria, Hadrosauridae) from the Late Cretaceous of Kazakhstan

Aralosaurus tuberiferus ROZHDESTVENSKY, 1968 (Dinosauria: Hadrosauridae) is based on a fragmentary skull from the Beleutinskaya Svita (? Turonian, Late Cretaceous) from the Sakh-Sakh locality of central Kazakhstan. Redescription of the type material reveals that it is a valid taxon, characterised by a hollow nasal crest-like structure located far in front of the orbits and by a well-developed curved crest on the maxilla that borders laterally the caudal part of the premaxillary shelf. Phylogenetic analysis, based on 36 cranial characters, indicates that A. tuberiferus is the most basal lambeosaurine hadrosaurid known to date; it is therefore not a gryposaur-like hadrosaurine as previously described. Lambeosaurines originated from Asia and then migrated to North America before or at the beginning of the late Campanian. They remained well diversified in eastern Asia until the late Maastrichtian.