Utilisation comparée du verveux et du sonar pour l'étude des migrations latérales des poissons dans le delta central du Niger

Dans le Delta Central du Niger, les migrations locales des poissons ont été contrôlées au niveau d'un chenal de jonction entre le fleuve et une mare de la plaine inondée. Une détection des poissons par sonar (échosondage horizontal) a été mise en oeuvre seule et conjointement à un échantillonnage des migrations à l'aide d'un verveux, sur plusieurs cycles de 24 heures en phase de crue et de décrue. La variation de densité et/ou d'activité des poissons enregistrée par le sonar (écho-traces) montre un profil nycthéméral comprenant un pic à l'aube et un autre au crépuscule. La densité nocturne d'écho-traces, relativement stable entre ces deux pics, tend à augmenter en fin de nuit lorsque le verveux barre le chenal, ralentissant ainsi le flux migratoire qui s'accumule devant l'engin. Les pics de l'aube et du crépuscule correspondraient à une augmentation d'activité locale à laquelle s'ajoute une activité migratoire effective révélée par les captures du verveux. Cette interprétation explique que la corrélation positive entre densité d'écho-traces et captures du verveux comprenne certaines "aberrations" résultant entre autres de l'activité non migratrice. L'utilisation conjuguée du sonar et d'un engin de pêche permet une meilleure interprétation des résultats obtenus avec chaque technique en attirant l'attention sur les biais qui peuvent résulter des facteurs éthologiques. (Résumé d'auteur

A Back Propagation Neural Network Model with the Synthetic Minority Over-Sampling Technique for Construction Company Bankruptcy Prediction

Improving model accuracy is one of the most frequently addressed issues in bankruptcy prediction. Several previous studies employed artificial neural networks (ANNs) to improve the accuracy at which construction company bankruptcy can be predicted. However, most of these studies use the sample-matching technique and all of the available company quarters or company years in the dataset, resulting in sample selection biases and between-class imbalances. This study integrates a back propagation neural network (BPNN) with the synthetic minority over-sampling technique (SMOTE) and the use of all of the available company-year samples during the sample period to improve the accuracy at which bankruptcy in construction companies can be predicted. In addition to eliminating sample selection biases during the sample matching and between-class imbalance, these methods also achieve the high accuracy rates. Furthermore, the approach used in this study shows optimal over-sampling times, neurons of the hidden layer, and learning rate, all of which are major parameters in the BPNN and SMOTE-BPNN models. The traditional BPNN model is provided as a benchmark for evaluating the predictive abilities of the SMOTE-BPNN model. The empirical results of this paper show that the SMOTE-BPNN model outperforms the traditional BPNN

INDIA-CHINA STRATEGIC COMPETITION IN THE INDIAN OCEAN

The XXI is considered by major countries in the Asia-Pacific region as ‘the century of sea and ocean’ and is accompanied by fierce competition among the nations to gain interest in the sea regions. On the basis that previously only considered the competition for military objectives, geostrategic bases and traffic channels through the straits, nowadays, countries worldwide have stepped up the competition for economic interests and marine resources. The development of military power and the competitive activities for resources at sea show clear the tendency to use the sea to contain the continent. In that context, the Indian Ocean, as the world’s third largest ocean, has an important geographic location and rich and diverse natural resources; the arterial sea route is gradually becoming the center of new world geopolitics and an important area in the strategic competition between two ‘Asian giants’ - India and China. The competition between these countries in the Indian Ocean is growing and profoundly impacts the region’s stability and security. This article focuses on the position and important role of the Indian Ocean in the policies of India and China, the fierce competition between the two countries in nearly two decades of the XXI century.    &nbsp

A database for propagation models

A database of various propagation phenomena models that can be used by telecommunications systems engineers to obtain parameter values for systems design is presented. This is an easy-to-use tool and is currently available for either a PC using Excel software under Windows environment or a Macintosh using Excel software for Macintosh. All the steps necessary to use the software are easy and many times self explanatory

First-principles study on the structural and electronic properties of single-layer MoSi2N4

Motivated by the successful exfoliation of a novel two-dimensional MoSi2N4 materials, in this work, we investigate the structural and electronic properties of a novel single-layer MoSi2N4 and the effect of strain engineering by using the first-principles calculations based on the density functional theory. The single-layer MoSi2N4 has a hexagonal structure with a space group of P6m1, which is dynamically stable. The material exhibits a semiconducting characteristic with an indirect band gap of 1.80/2.36 eV calculated by using the PBE/HSE functional. The conduction band minimum at the K point of the material originates from the Mo atom, while its valence band maximum at the G point is contributed by the hybridization between the Mo and N atoms. The electronic properties of the single-layer MoSi2N4 can be modulated with strain engineering, giving rise to a transition from a semiconductor to a metal and tending to a change in the band gap. Our results demonstrate that the single-layer MoSi2N4 is a promising candidate for electronic and optoelectronic applications

SEROTYPES, TOXINS AND ANTIBIOTIC RESISTANCE OF Escherichia coli (E.COLI) STRAINS ISOLATED FROM DIARRHEIC RABBITS IN PHU VANG, THUA THIEN HUE

This study was conducted to determine the prevalence of E. coli in rabbits, their biochemical and serological characteristics, common virulence genes, and antibiotic resistance. The diarrhea rabbit feces were collected from households and rabbit farms in Phu Vang - Thua Thien Hue with a total of 250 samples for testing. The results showed that rabbits age from 31 to 45 days old had the highest incidence of diarrhea disease caused by E.coli (92.0%) and the lowest infection rate was observed in rabbits over 60 days old with an infection rate of 30%. Further, the isolated E.coli strains tested biochemical characteristics showed 100% motile, positive for indole and methyl red, fermenting glucose and lactose. Simultaneously these strains were detected belong to 7 serotypes O103, O157, O158, O169, O44, O125, O153 and susceptible to cefuroxime (95.45%), akamicin (86.37%), streptomycin (81.82%), amoxicillin (81.82%), tetracycline (68.18%), colistin (68.18%), ampicillin (63.63%), gentamycin (59.10%) and levofloxacin (50.0%), whilst resistant to doxycycline (100%), sulfamethoxazole-bactrim (95.46%), and neomycin (86.37%). By using PCR assay for detection of virulence genes of the isolated E. coli strains, there were 7 strains carried virulence genes, of which 4/7 E. coli strains carried eaeA and tsh genes (57.14%), 2/7 strains carried stx2 gene (28.57%); 1/7 E. coli strains carried stx1 gene (14.28%) and the F4, F5 and F6 genes were not found in all serotypes in this study

Benchmarking Jetson Edge Devices with an End-to-end Video-based Anomaly Detection System

Innovative enhancement in embedded system platforms, specifically hardware accelerations, significantly influence the application of deep learning in real-world scenarios. These innovations translate human labor efforts into automated intelligent systems employed in various areas such as autonomous driving, robotics, Internet-of-Things (IoT), and numerous other impactful applications. NVIDIA's Jetson platform is one of the pioneers in offering optimal performance regarding energy efficiency and throughput in the execution of deep learning algorithms. Previously, most benchmarking analysis was based on 2D images with a single deep learning model for each comparison result. In this paper, we implement an end-to-end video-based crime-scene anomaly detection system inputting from surveillance videos and the system is deployed and completely operates on multiple Jetson edge devices (Nano, AGX Xavier, Orin Nano). The comparison analysis includes the integration of Torch-TensorRT as a software developer kit from NVIDIA for the model performance optimisation. The system is built based on the PySlowfast open-source project from Facebook as the coding template. The end-to-end system process comprises the videos from camera, data preprocessing pipeline, feature extractor and the anomaly detection. We provide the experience of an AI-based system deployment on various Jetson Edge devices with Docker technology. Regarding anomaly detectors, a weakly supervised video-based deep learning model called Robust Temporal Feature Magnitude Learning (RTFM) is applied in the system. The approach system reaches 47.56 frames per second (FPS) inference speed on a Jetson edge device with only 3.11 GB RAM usage total. We also discover the promising Jetson device that the AI system achieves 15% better performance than the previous version of Jetson devices while consuming 50% less energy power.Comment: 18 pages, 7 figures, 5 table

India-China strategic competition in the Indian Ocean

The XXI is considered by major countries in the Asia-Pacific region as ‘the century of sea and ocean' and is accompanied by fierce competition among the nations to gain interest in the sea regions. On the basis that previously only considered the competition for military objectives, geostrategic bases and traffic channels through the straits, nowadays, countries worldwide have stepped up the competition for economic interests and marine resources. The development of military power and the competitive activities for resources at sea show clear the tendency to use the sea to contain the continent. In that context, the Indian Ocean, as the world's third largest ocean, has an important geographic location and rich and diverse natural resources; the arterial sea route is gradually becoming the center of new world geopolitics and an important area in the strategic competition between two 'Asian giants' - India and China. The competition between these countries in the Indian Ocean is growing and profoundly impacts the region's stability and security. This article focuses on the position and important role of the Indian Ocean in the policies of India and China, the fierce competition between the two countries in nearly two decades of the XXI century

Qsun: an open-source platform towards practical quantum machine learning applications

Currently, quantum hardware is restrained by noises and qubit numbers. Thus, a quantum virtual machine that simulates operations of a quantum computer on classical computers is a vital tool for developing and testing quantum algorithms before deploying them on real quantum computers. Various variational quantum algorithms have been proposed and tested on quantum virtual machines to surpass the limitations of quantum hardware. Our goal is to exploit further the variational quantum algorithms towards practical applications of quantum machine learning using state-of-the-art quantum computers. This paper first introduces our quantum virtual machine named Qsun, whose operation is underlined by quantum state wave-functions. The platform provides native tools supporting variational quantum algorithms. Especially using the parameter-shift rule, we implement quantum differentiable programming essential for gradient-based optimization. We then report two tests representative of quantum machine learning: quantum linear regression and quantum neural network.Comment: 18 pages, 7 figure

Synthesis and Investigation of the Physical Properties of Lead-Free BCZT Ceramics

This work presents the structure, microstructure, and physical properties of low sintering temperature lead-free ceramics 0.52(Ba0.7Ca0.3)TiO3-0.48Ba(Zr0.2Ti0.8)O3 doped with nano-sized ZnO particles (noted as BCZT/x, x is the content of ZnO nanoparticles in wt.%, x = 0.00, 0.05, 0.10, 0.15, 0.20, and 0.25). The obtained results of Raman scattering and dielectric measurements have confirmed that Zn2+ has occupied B-site, to cause a deformation in the ABO3-type lattice of the BCZT/x specimens. The 0.15 wt.% ZnO-modified ceramic sintered at 1350°C exhibited excellent piezoelectric parameters: d33 = 420 pC/N, d31 = −174 pC/N, kp = 0.483, kt = 0.423, and k33 = 0.571. The obtained results indicate that the high-quality lead-free BCZT ceramic could be successfully synthesized at a low sintering temperature of 1350°C with an addition of appropriated amount of ZnO nanoparticles. This work also reports the influence of the sintering temperature on structure, microstructure, and piezoelectric properties of BCZT/0.15 compound. By rising sintering temperature, the piezoelectric behaviors were improved and rose up to the best parameters at a sintering temperature of 1450°C (d33 = 576 pC/N and kp = 0.55). The corresponding properties of undoped BCZT ceramics were investigated as a comparison. It also presented that the sintering behavior and piezo-parameters of doped BCZT samples are better than the undoped BCZT samples at each sintering temperature