Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Transfer Learning-Based Broken Rotor Fault Diagnosis For Induction Motors

Modern industrial drives use induction motors (IM) due to their starting and running torque requirements and four-quadrant operation. The voltages and currents of each of the three phases as well as the acceleration and velocity signals may be used to identify failures in the rotor bars of the motor. In the past, traditional signal processing-based feature extraction approaches and machine learning algorithms have been used for the diagnosis of the number of broken rotor bars for a failed IM. In this paper, a new scheme is investigated for the determination of the number of broken rotor bars. Specifically, the deep learning approaches are examined for the mentioned purposes. To this end, transfer learning approaches on the convolutional neural network (CNN) are presented. For denoising, initially, a bandpass filter is employed, and then the signals are converted to time-frequency images by using the continuous wavelet transform (CWT). The obtained images are used for the fine-tuning of the pre-trained ResNet18 model and the deep feature extraction and classification with the support vector machine (SVM) classifier. The classification accuracy is used for performance evaluation metrics. Moreover, the experiments show that the highest accuracy score of 100% is obtained with the deep features that are extracted from the mechanical vibration signal and current signal. On the other hand, a performance comparison with the published approaches is also carried out. Finally, the comparisons show that the proposed method produces better accuracy scores than the compared methods.
The Network Bass Model with Behavioral Compartments

A Bass diffusion model is defined on an arbitrary network, with the additional introduction of behavioral compartments, such that nodes can have different probabilities of receiving the information/innovation from the source and transmitting it to other nodes. The dynamics are described by a large system of non-linear ordinary differential equations, whose numerical solutions can be analyzed in dependence on diffusion parameters, network parameters, and relations between the compartments. For example, in a simple case with two compartments (Enthusiasts and Sceptics about the innovation), we consider cases in which the “publicity” and imitation terms act differently on the compartments, and individuals from one compartment do not imitate those of the other, thus increasing the polarization of the system and creating sectors of the population where adoption becomes very slow. For some categories of scale-free networks, we also investigate the dependence on the features of the networks of the diffusion peak time and of the time at which adoptions reach 90% of the population.
Detection of Influenza D-Specific Antibodies in Bulk Tank Milk from Swedish Dairy Farms

Influenza D virus (IDV) has been detected in bovine respiratory disease (BRD) outbreaks, and experimental studies demonstrated this virus’s capacity to cause lesions in the respiratory tract. In addition, IDV-specific antibodies were detected in human sera, which indicated that this virus plays a potential zoonotic role. The present study aimed to extend our knowledge about the epidemiologic situation of IDV in Swedish dairy farms, using bulk tank milk (BTM) samples for the detection of IDV antibodies. A total of 461 and 338 BTM samples collected during 2019 and 2020, respectively, were analyzed with an in-house indirect ELISA. In total, 147 (32%) and 135 (40%) samples were IDV-antibody-positive in 2019 and 2020, respectively. Overall, 2/125 (2%), 11/157 (7%) and 269/517 (52%) of the samples were IDV-antibody-positive in the northern, middle and southern regions of Sweden. The highest proportion of positive samples was repeatedly detected in the south, in the county of Halland, which is one of the counties with the highest cattle density in the country. In order to understand the epidemiology of IDV, further research in different cattle populations and in humans is required.
On the 1‐Loop Renormalization of the Electroweak Standard Model and its Application to Leptonic Processes

A renormalization scheme for the electroweak standard model is presented in which the electric charge and the masses of the gauge bosons, Higgs particle and fermions are used as physical parameters. The photon is treated such that quantum electrodynamics is contained as a simple substructure. Field renormalization respecting the gauge symmetry gives finite propagators and vertex functions. The Ward identities between the Green functions of the unphysical sector allow a renormalization that maintains the simple pole structure of the propagators in the t'Hooft-Feynman gauge. We give a complete list of self energies and all renormalization constants also in the unphysical Higgs and ghost sector. Explicit results are given for the renormalized self energies, vertex functions and boxes that enter the evaluation of 1-loop radiative corrections to fermionic processes. We calculate the 1-loop radiative corrections to purely leptonic reactions like μ decay, vμμe scattering and μ pair production in e+e−annihilation. A test of the standard model is performed by comparing these low energy data with the results of the PP collider experiments for the W and Z boson masses.
A versatile Markovian point process

We introduce a versatile class of point processes on the real line, which are closely related to finite-state Markov processes. Many relevant probability distributions, moment and correlation formulas are given in forms which are computationally tractable. Several point processes, such as renewal processes of phase type, Markov-modulated Poisson processes and certain semi-Markov point processes appear as particular cases. The treatment of a substantial number of existing probability models can be generalized in a systematic manner to arrival processes of the type discussed in this paper. Several qualitative features of point processes, such as certain types of fluctuations, grouping, interruptions and the inhibition of arrivals by bunch inputs can be modelled in a way which remains computationally tractable.
Nanometer molecular lithography

We demonstrate a three‐step parallel process for the fabrication of a 1‐nm‐thick metal (Ta/W) film with 15‐nm‐diam holes periodically arranged on a triangular lattice of parameter 22 nm. In this process, a two‐dimensional crystalline protein monolayer is deposited on a smooth substrate, metal coated by evaporation, and then ion milled. Under ion milling this protein‐metal heterostructure exhibits differential metal removal and rearrangement which varies on a protein molecular length scale. The spatial ordering of the resulting holes has the same nanometer periodicity as the protein lattice.We demonstrate a three‐step parallel process for the fabrication of a 1‐nm‐thick metal (Ta/W) film with 15‐nm‐diam holes periodically arranged on a triangular lattice of parameter 22 nm. In this process, a two‐dimensional crystalline protein monolayer is deposited on a smooth substrate, metal coated by evaporation, and then ion milled. Under ion milling this protein‐metal heterostructure exhibits differential metal removal and rearrangement which varies on a protein molecular length scale. The spatial ordering of the resulting holes has the same nanometer periodicity as the protein lattice.
A Universal Test Scheme for Power Conversion Embedded Control System with Full-Coverage on Inner Variables

Embedded system becomes one of widely-employed system schemes applied in broad areas, such as power conversion, industrial control, test and measurement, and so on. A universal test scheme with full-coverage on inner variables is present, which will improve the testability of power conversion embedded control system. Feathers of this embedded control system are introduced, and the function structure of the general test scheme is described. Some key problems of the test scheme, such as data type, variable property table, multi-type pointer array, and multi-type data packing and unpacking are discussed. Finally, the effect of the universal test scheme is testified by the implementation of a typical power conversion demonstration.
Comparison of electro-optical switching between polymer-stabilised cubic and amorphous blue phases

We prepared polymer-stabilised cubic and amorphous blue phase liquid crystals consisting of the same materials at different UV-curing temperatures using photopolymerisation. Then we investigated the effects of polymer stabilisation on their physical properties. The UV-curing temperature does not affect phase stabilisation of the polymer-stabilised amorphous BPIII (PS-BPIII). Temperatures of the PS-BPIII were found to be extended to more than 50 K. However, a critical temperature exists in the polymer stabilisation process for the PS-cubic BP. Although no substantial difference in response speed was found between the polymer-stabilised cubic and amorphous structures, larger hysteresis and higher residual birefringence were observed in the PS-cubic BP than in the PS-BPIII. Amorphous BPIII with an amorphous network of disclination lines has no critical temperature for the polymer stabilisation and realises a high-performance display.
Multi-USV Dynamic Navigation and Target Capture: A Guided Multi-Agent Reinforcement Learning Approach

Autonomous unmanned systems have become an attractive vehicle for a myriad of military and civilian applications. This can be partly attributed to their ability to bring payloads for utility, sensing, and other uses for various applications autonomously. However, a key challenge in realizing autonomous unmanned systems is the ability to perform complex group missions, which require coordination and collaboration among multiple platforms. This paper presents a cooperative navigating task approach that enables multiple unmanned surface vehicles (multi-USV) to autonomously capture a maneuvering target while avoiding both static and dynamic obstacles. The approach adopts a hybrid multi-agent deep reinforcement learning framework that leverages heuristic mechanisms to guide the group mission learning of the vehicles. Specifically, the proposed framework consists of two stages. In the first stage, navigation subgoal sets are generated based on expert knowledge, and a goal selection heuristic model based on the immune network model is used to select navigation targets during training. Next, the selected goals’ executions are learned using actor-critic proximal policy optimization. The simulation results with multi-USV target capture show that the proposed approach is capable of abstracting and guiding the unmanned vehicle group coordination learning and achieving a generally optimized mission execution.
2 - Diagramme de Voronoï appliqué à la segmentation d'images et à la détection d'évènements en imageris multi-sources (1)

In this paper, we propose a Voronoi representation of the image support in order to obtain segmentation . We manipulate a Voronoi diagram in a split and merge environnent in order to match the polygons with homogeneous region of the image . This tool is also used to obtain a solution of the problem of multisource image analysis .
Early Milk Total and Differential Cell Counts as a Diagnostic Tool to Improve Antimicrobial Therapy Protocols

Simple Summary The prevention and control of mastitis, from a One Health perspective, should balance the risk of intramammary infections, impairing cow health and welfare, and the need of a reduction of antimicrobial usage (e.g., applying selective dry-cow therapy), thus decreasing antimicrobial resistance. This study showed that the application of an early diagnosis (5–16 days after calving) based on PLCC (neutrophils + lymphocyte count/mL) has good accuracy, a sustainable cost, and could potentially reduce the frequency of antimicrobial treatment compared with conventional diagnostic protocols based on SCC at the first milk test after calving. Abstract Mastitis is a major cause of antimicrobial treatments either during lactation or at drying off. From a One Health perspective, there should be a balance between the risk of IMI that may impair cow health and welfare and the reduction of antimicrobial usage to decrease antimicrobial resistance, as may happen when applying selective dry-cow therapy. This reduction may be achieved by an early and accurate diagnosis followed by prudent and rationale therapeutical protocols. This study aims to assess the accuracy of PLCC (neutrophils + lymphocyte count/mL) in identifying cows at risk of having IMI due to major pathogens (S.aureus, Str.agalactiae, Str.uberis, and Str.dysgalactiae), and to simulate the impact of this early diagnosis on the potential number of treatments using a decision-tree model. The results of this study showed that PLCC had an overall accuracy of 77.6%. The results of the decision-tree model based on data from the 12 participating herds, with an overall prevalence of major pathogens of 1.5%, showed a potential decrease in the number of treatments of about 30% (from 3.4% to 2.5%) when PLCC in early lactation (days 5–16) was used to identify cows at risk for major pathogens compared with using SCC at the first milk test (days 17–43). The study confirmed that it is possible to improve animal health and reduce the risk of antimicrobial use through early IMI detection based on PLCC and applying a rationale and prudent antimicrobial protocol.
The Michelson Stellar Interferometer: A Phase Sensitive Variation of the Optical Instrument

A short summary is given of a variation of the Michelson stellar interferometer. This is an adaptation of part of the principle of the radio-frequency phase-sensitive interferometer developed by the author in 1958 and it enables the phase component associated with the structure of the source to be determined. The technique may also be used to determine the correct relative amplitude of the visibility function of the star at two spacings even when phase and amplitude errors are present.
Joint Direct Estimation of Emitter Location and Antenna Beam Direction Based on Baseband Reconstruction

This article addresses the problem of locating a stationary noncooperative emitter using multiple moving receivers. A signal baseband reconstruction-based algorithm is proposed to locate the emitter directly from the received signals, without assuming static delay and Doppler shift in any observing interval. Besides the information of time difference of arrival (TDOA) and frequency difference of arrival (FDOA), the received signal strength (RSS) information is further utilized when the source emits signals in free space with an omni antenna. In a more complex scenario where the emitter adopts a directional antenna, an iterative algorithm is proposed to jointly estimate the emitter location and its antenna beam direction, where a traditional direct position determination (DPD) method is used to initiate the iteration. The Cramér–Rao lower bounds (CRLBs) of the emitter position and the beam direction are derived. Three numerical cases are included to investigate the performance of the proposed algorithms. The signal baseband reconstruction-based DPD algorithm shows improved applicability when the assumption of static time delay and Doppler shift is inappropriate and performs similarly to the classical DPD methods when the assumption holds. In the case of free-space propagation, it shows that the localization accuracy can be improved when RSS is further utilized. When the transmitting beam is directional, however, simply ignoring the directivity characteristics would lead to nonnegligible localization biases. By jointly estimating the emitter location and antenna beam direction, the RSS information can be effectively utilized to improve the localization accuracy, and a much more accurate estimation of beam direction can be obtained simultaneously.
Edge enhancement of medical ultrasonic images based on similarity

To improve edge detection level of medical ultrasonic images,a weighted contrast enhancement method of medical ultrasound images based on similarity estimation is proposed.Firstly the similarity of the processing window around a pixel and matching template is calculated.According to the relationship between the similarity and each parts of ultrasound image,the matched images are enhanced by local enhancement approach when it satisfied with correlation condition.The weighted average method for multiple images is used to obtain the final enhancement results.Experimental results with this method shows better contrast resolution,better edge feature detection than the original,and also preserved the structure without losing useful clinical information.In this respect,this method remedies the shortage of traditional enhancement algorithms.
A Metro WDM Star Network with a Hybrid MAC Protocol Based on an Arrayed Waveguide Grating

In this paper, we introduce a reliable, scalable, and cost-effective switchless wavelength division multiplexing (WDM) network based on a quality-of-service supporting reservation-based medium access control (MAC) protocol. The protocol not only provides both packet and circuit switching but also supports multicasting. The network efficiency is significantly increased by spatially reusing wavelengths and exploiting multiple free spectral ranges (FSRs) of arrayed waveguide grating (AWG) employed in the architecture. We have demonstrated the feasibility of this architecture by simulating in $Optsim^{TM}$ .
The Description of the Navy Operational Global Atmospheric Prediction System's Spectral Forecast Model

Abstract We present a description of the development of the spectral forecast components of the Navy Operational Global Atmospheric Prediction System (NOGAPS). The original system, called 3.0, was introduced in January 1988. New versions were introduced in March 1989 (3.1) and August 1989 (3.2). A brief description of each version of the forecast model is given. Each physical parameterization is also described. We discuss the large changes in 3.1 and the motivation behind the changes. Statistical results from forecast comparison tests are discussed. Figures showing the total monthly forecast performance in the Northern Hemisphere and the Southern Hemisphere are also given. A brief discussion is presented of computational details, running times, and memory requirements of the forecast model.
An Improved ORB Feature Extraction Algorithm Based on Enhanced Image and Truncated Adaptive Threshold

The ORB (Oriented fast and rotated brief, ORB) algorithm is limited by its inability to extract feature points or extract only a small number of feature points when a fixed threshold is used in complex lighting conditions. To address this issue, this paper proposes a method that combines image enhancement with truncated adaptive threshold to improve the ORB feature extraction algorithm. Firstly, the original image is converted to grayscale. Secondly, the image is enhanced by applying Gaussian filtering for noise reduction, truncated adaptive gamma brightness adjustment, and unsharp masking operation. Then, the enhanced image is segmented into subregions of a specified size, and an improved truncated OTUS method is employed to calculate the adaptive threshold for each subregion. Finally, ORB feature points are extracted by utilizing the adaptive threshold. Experimental results show that the improved ORB algorithm can significantly increase the number of feature points in complex lighting conditions, with good accuracy, real-time performance, and robustness.
Identification of key pathways, genes and immune cell infiltration in hypoxia of high-altitude acclimatization via meta-analysis and integrated bioinformatics analysis

Background: For individuals acutely exposed to high-altitude regions, environmental hypobaric hypoxia induces several physiological or pathological responses, especially immune dysfunction. Therefore, hypoxia is a potentially life-threatening factor, which has closely related to high-altitude acclimatization. However, its specific molecular mechanism is still unclear. Methods: The four expression profiles about hypoxia and high altitude were downloaded from the Gene Expression Omnibus database in this study. Meta-analysis of GEO datasets was performed by NetworkAnalyst online tool. Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene ontology (GO) enrichment analysis, and visualization were performed using R (version 4.1.3) software, respectively. The CIBERSORT analysis was conducted on GSE46480 to examine immune cell infiltration. In addition, we experimentally verified the bioinformatics analysis with qRT-PCR. Results: The meta-analysis identified 358 differentially expressed genes (DEGs), with 209 upregulated and 149 downregulated. DEGs were mostly enriched in biological processes and pathways associated with hypoxia acclimatization at high altitudes, according to both GO and KEGG enrichment analyses. ERH, VBP1, BINP3L, TOMM5, PSMA4, and POLR2K were identified by taking intersections of the DEGs between meta-analysis and GSE46480 and verified by qRT-PCR experiments, which were inextricably linked to hypoxia. Immune infiltration analysis showed significant differences in immune cells between samples at sea level and high altitudes. Conclusion: Identifying the DEGs and pathways will improve our understanding of immune function during high-altitude hypoxia at a molecular level. Targeting hypoxia-sensitive pathways in immune cells is interesting in treating high-altitude sickness. This study provides support for further research on high-altitude acclimatization.
Effect of Different Silane Coupling Agents In-Situ Modified Sepiolite on the Structure and Properties of Natural Rubber Composites Prepared by Latex Compounding Method

With the increasing demand for eco-friendly, non-petroleum-based natural rubber (NR) products, sepiolite, a naturally abundant, one-dimensional clay mineral, has been identified as a suitable material for reinforcing NR through the latex compounding method. To create superior NR/sepiolite composites, three silane coupling agents with different functional groups were used to modify sepiolite in situ via grafting or adsorption during the disaggregation and activation of natural sepiolite, which were subsequently mixed with natural rubber latex (NRL) to prepare the composites. The results showed that the modified sepiolite improved the dispersion and interfacial bonding strength with the rubber matrix. VTES-modified sepiolite containing C=C groups slightly improved the performance but retarded the vulcanization of the NR composites, and MPTES and TESPT-modified sepiolites containing -SH and −S4− groups, respectively, effectively accelerated vulcanization, inducing the composites to form a denser crosslink network structure, and exhibiting excellent dynamic and static properties, such as the modulus at a 300% increase from 8.82 MPa to 16.87 MPa, a tear strength increase from 49.6 N·mm−1 to 60.3 N·mm−1, as well as an improved rolling resistance and abrasive resistance of the composites. These findings demonstrate that modified sepiolite can be used to produce high-quality NR/sepiolite composites with enhanced properties.