Miracle-dz/UniFAR-FTUs huggingface dataset:
Intelligent Monitoring Method of Crude Fuel Images Based On Deep Learning

The conditions of crude fuel can reflect the reaction degree in a blast furnace, and the real-time monitoring and analysis of the crude fuel can improve production performance and stabilize the conditions of the furnace. The results of crude fuel conditions obtained by traditional manual sampling detection are low in accuracy, and have danger and hysteresis. In order to reduce the workload of personnel and improve detection accuracy and timeliness, this paper proposes an intelligent monitoring method of crude fuel images based on deep learning. According to the method, attention mechanisms are added on the basis of a Mask R-CNN algorithm, so that the detection accuracy is improved, and besides, the problem of overfitting is solved. In order to ensure the detection accuracy under high-speed motion blurred images, a DeblurGAN-v2 algorithm is used to deblur the images; and when a dataset is built, data enhancement is used to increase the number and types of samples, so that the algorithm can adapt to the actual production environment of a factory. Through a crude fuel detection experiment, the effectiveness of the algorithm in the aspect of improving the detection accuracy of clear and blurred images is verified.
Blow-up of solutions of a class of strongly non-linear dissipative wave equations of Sobolev type with sources

We consider the abstract Cauchy problem for a first-order ordinary differential equation with non-linear operator coefficients. The results are applied to some strongly non-linear dissipative wave equations of Sobolev type. We obtain sufficient conditions for the problem to be globally soluble, as well as sufficient conditions for the solutions to blow up in finite time. These conditions are close to being necessary. Under certain supplementary assumptions on the non-linear operators, we prove that the problem is soluble in any finite cylinder. Under certain conditions on the norm of the initial functions, we prove that the solution of the problem blows up in finite time. We give examples of equations of Sobolev type satisfying these conditions.
The implementation checklist: A pragmatic instrument for accelerating research‐to‐implementation cycles

Learning health systems require rapid‐cycle research and nimble implementation processes to maximize innovation across disparate specialties and operations. Existing detailed research‐to‐implementation frameworks require extensive time commitments and can be overwhelming for physician‐researchers with clinical and operational responsibilities, inhibiting their widespread adoption. The creation of a short, pragmatic checklist to inform implementation processes may substantially improve uptake and implementation efficiency across a variety of health systems.
8–13 µm spectrophotometry of galaxies – IV. Six more Seyferts and 3C 345

On presente les spectres 8-13 μm de six noyaux de Seyfert (NGC 4151, NGC 4051, MCG 8-11-11, NGC 2992, MCG 5-23-16 et NGC 7674) et du quasar 3C345. L'emission IR presente deux composantes: une composante non thermique associee directement avec la source nucleaire en loi de puissance et une composante thermique due aux grains de poussiere de dimensions >0,01 μm
Non-destructive testing of debonding defects in thermal barrier coating system using laser infrared thermography

Thermal barrier coating (TBC) system is indispensable for the heavy duty gas turbines or the aero-engine blades working at high temperature. Since the interface crack is one of the crucial issues affecting the integrity of the TBC, it is necessary to inspect the debonding defects in TBC by using a non-destructive testing (NDT) technique. Laser infrared thermography (LIRT) is a high efficiency NDT tool for thin-wall structures such like the TBC, and the LIRT using a homogeneous laser beam is especially suitable for detection of the debonding defects. In this paper, the feasibility of the homogeneous LIRT is verified for NDT of the debonding detection at first through finite element numerical simulation. Second, an experimental system using the diffractive optical element and a plano-concave lens is setup to conduct LIRT measurement with a wide homogeneous square laser spot. By using TBC specimen with debonding defects fabricated using the salt dissolving method, the pulsed LIRT and lock-In LIRT are conducted to detect the artificial debonding defects in TBC test-pieces. It is proved that the pulsed LIRT is of higher efficiency and the measured thermal image can be improved through denoising processing by using algorithm such as TSR, PCA etc. It is also found that the TSR image processing method costs less and can give results of higher contrast. The experimental results show that the debonding defects of diameter larger than 3 mm can be efficiently and accurately detected with the LIRT technique.
Helminth Community Structure of Tits Cyanistes caeruleus and Parus major (Paridae) during Their Autumn Migration on the Southern Baltic Coast

Simple Summary Parasites of birds can be an indicator of environmental quality, but this issue is very poorly understood. Migratory birds can transfer parasites between ecosystems, thus increasing the size of their populations. The biodiversity of bird parasites and the predominance of specific parasite species can be influenced, as in the case of non-parasitic animals, by global changes in the environment, including climate change and anthropogenic transformation of ecosystems. The aim of the present research was to describe and compare helminth communities of Eurasian blue tit Cyanistes caeruleus and the Great tit Parus major, at the component community and infracommunity level, on the southern coast of the Baltic Sea during autumn migration to their wintering grounds. The main findings of the research were the presence of several parasite species that had not previously been recorded in these tits in Poland, the dominance of the digenetic fluke, and the high prevalence of the filarial nematodes. Abstract The research problem undertaken in this study is to determine the scale of infection of Eurasian blue tit Cyanistes caeruleus and Great tit Parus major and the biological diversity of their internal parasites, helminths. The aim of the study is to gain new knowledge about the structure of the helminth communities of the Eurasian blue tit and Great tit on the southern coast of the Baltic Sea during autumn migration to their wintering grounds. Helminths of tits were collected in 2008–2012 on the southern coast of the Baltic Sea in Poland. PAST v. 2.11 software was used for the calculations. Barcoding DNA was used to identify trematodes initially classified based on morphological characters to the genera Leucochloridium and Urogonimus. Cestodes Anonchotaenia globata were recorded for the first time in Poland. The Eurasian blue tit is a new host in Poland for three species of helminths: cestode Monosertum parinum and filarial nematodes, Cardiofilaria pavlovskyi, and Diplotriaena henryi. The Great tit is a new host in Poland for trematode Urogonimus macrostomus, cestode A. globata and M. parinum, and filarial nematode Diplotriaena obtusa. The nematode C. pavlovskyi was the species most frequently recorded in both host species. A high degree of similarity was found between the component communities and infracommunities of helminths in Eurasian blue tit and Great tit. The new information provided in this study has increased our knowledge of the transmission of helminths in Central Europe.
A curve representation of human activity

One of the main challenges of high level analysis of human behavior is the high dimension of the feature space. To overcome the curse of dimensionality, we propose in this paper, a space curve representation of the high dimensional behavior features. The features of interest here, are restricted to sequences of shapes of the human body such as those extracted from a video sequence. This evolution is a one dimensional sub-manifold in shape space. The central idea of the proposed representation takes root in the Whitney embedding theorem which guarantees an embedding of a one dimensional manifold in as a space curve. The resulting of such dimension reduction, is a simplification of comparing two behaviors to that of comparing two curves in R3. This comparison is additionally theoretically and numerically easier to implement for statistical analysis. By exploiting sampling theory, we are moreover able to achieve a computationally efficient embedding that is invertible. Specifically, we first construct a global coordinates expression for the one dimension manifold and sampled along a generating curve.As experiment result, we provide substantiating modeling examples and illustrations of behavior classification.
Multi-Stage Progressive Audio Bandwidth Extension

Audio bandwidth extension can enhance subjective sound quality by increasing bandwidth of audio signal. This paper presents a novel multi-stage progressive method for time domain causal bandwidth extension. Each stage of the progressive model contains a light weight scale-up module to generate high frequency signal and a supervised attention module to guide features propagating between stages. Time-frequency two-step training method with weighted loss for progressive output is adopted to supervise bandwidth extension performance improves along stages. Test results show that multi-stage model can improve both objective results and perceptual quality progressively. The multi-stage progressive model makes bandwidth extension performance adjustable according to energy consumption, computing capacity and user preferences.
A GNSS Instrumentation Covert Directional Spoofing Algorithm for UAV Equipped With Tightly-Coupled GNSS/IMU

Measurement and navigation users cannot operate without the positioning, navigation, and timing (PNT) service provided by the global navigation satellite system (GNSS) instrumentation, but users are also faced with unpredictable and complex interference and even spoofing. In order to effectively control and even counter the unmanned aerial vehicle (UAV) that may pose security threats, using the GNSS spoofing technology to counter UAV is an effective and important technical means. Compared with the existing spoofing algorithms, this article fully considers the navigation system configuration and flight control principle, as well as antispoofing module of UAV equipped, the UAV dynamic model under GNSS spoofing environment is established, and the response law of UAV state to spoofing is analyzed. In order to realize the covert directional spoofing on UAV equipped with tightly-coupled GNSS and inertial measurement unit (IMU), a GNSS covert spoofing algorithm is proposed. The algorithm includes a fixed-point four-step spoofing strategy and pays attention to avoiding the least-squares residual receiver autonomous integrity monitoring (LSR-RAIM) of UAV, so as to ensure the concealment of the deception process. Through the construction of experimental platform and experimental analysis, the effectiveness and concealment of the algorithm are verified. The experiment shows that the spoofing yaw angle error of GNSS covert directional spoofing is −0.03°. In addition, the spoofer has effectively avoided the LSR-RAIM of UAV system in the whole process, and the evasion rate has reached 100% to achieve covert spoofing. For the actual spoofing scenario application, the spoofing yaw angle error can meet the actual needs. Future work will focus on the research and design of more complex covert spoofing algorithms to meet the spoofing needs of UAV equipped with more complex navigation systems and antispoofing techniques.
A UAV-Aided Vehicular Integrated Platooning Network for Heterogeneous Resource Management

Platooning unmanned ground vehicles (UGVs) are envisioned as a green and effective paradigm to enhance transportation performance. However, limited computing, communication, and energy resources hinder the development of platooning UGVs. To overcome these issues, we introduce heterogeneous computing (HC) resource and unmanned aerial vehicle (UAV). Specifically, we build a novel UAV-aided integrated platooning (VIP) vehicle network for energy consumption minimization based resource management. First, joint optimization problem is considered with HC allocation, power control, and platoon control. Second, a two-phase federated learning (FL) based solution is proposed to solve the nonconvex problem. The solution consists of one phase called dynamic parameter server selection and the other phase called federated resource management. Third, the effectiveness and superiority of the propose approach is validated by the numerical simulations with several benchmarks.
Capillary Pumped-Loop Thermal Performance Improvement with Electrohydrodynamic Technique

The capillary pumped loop (CPL) is a state-of-the-art technology for cooling spacecraft and telecommunication devices. It is a two-phase heat-transport device in which the driving force is provided by the capillary action of the wick material In the evaporator. Compared to the widely used heat pipes, it provides a higher heat-transport capacity, more flexibility of installation, and greater heat-transport distance because of wickless transport lines and the absence of liquid and vapor counterflowing. The major disadvantages of the CPL are long and complicated startup procedures and the possibility of deprime at high heat input and large load variations. This paper investigates the liquid-vapor separation and thermal management with the electrohydrodynamic (EHD) technique for an EHD-assisted CPL using R-134a as the working fluid. An experimental investigation, along with a mechanism analysis, was employed to evaluate the potential of the EHD technique for thermal performance improvement of CPL systems. Experimental results showed that enhancements, up to three times, could be obtained in heat-transfer coefficients by applying an electric field at different heat load levels. The depriming conditions of a capillary pump can also be prevented with the EHD technique.
Flow Response of Active Flow Control Actuators

Numerical and experimental analysis of a synthetic jet actuator in quiescent air is reported. The study focuses on the actuator itself and on the vorticity field as well as on structures that are generated by the actuator. Large eddies simulation was used for numerical analysis and phase-locked, two-dimensional microscopic-particle image velocimetry technique was used in the experiment. In the numerical simulation, the equations were integrated using a nondissipative scheme that enforces discrete conservation of kinetic energy. The internal cavity flow of the actuator was part of the simulation. The actuator under consideration is of a unique design, fabricated to accommodate practical issues associated with helicopter rotor application. However, it has the same operating principles as a conventional synthetic jet actuator. Harmonics of the forcing frequency were traced in the velocity field. Insight into the evolution of the vortical structures, jet flapping, and onset of turbulence in the jet was retrie.
Hydrolysis, Biodegradation and Ion Sorption in Binary Biocomposites of Chitosan with Polyesters: Polylactide and Poly(3-Hydroxybutyrate)

The film binary composites polylactide (PLA)–chitosan and poly(3-hydroxybutyrate) (PHB)–chitosan have been fabricated and their functional characteristics, such as hydrolysis resistance, biodegradation in soil, and ion sorption behavior have been explored. It was established that hydrolysis temperature and acidity of solutions are differently affected by the weight loss of these two systems. Thus, in the HCl aqueous solutions, the stability of the PHB-chitosan composites is higher than the stability of the PLA-chitosan one, while the opposite situation was observed for biodegradation in soil. The sorption capacity of both composites to Fe3+ ions was investigated and it was shown that, for PHB-chitosan composites, the sorption is higher than for PLA-chitosan. It was established that kinetics of sorption obeys the pseudo-first-order equation and limiting values of sorption correspond to Henry’s Law formalism. By scanning electron microscopy (SEM), the comparative investigation of initial films and films containing sorbed ions was made and the change of films surface after Fe3+ sorption is demonstrated. The findings presented could open a new horizon in the implementation of novel functional biodegradable composites.
Enabling the Electrochemical Performance of Maricite-NaMnPO4 and Maricite-NaFePO4 Cathode Materials in Sodium-Ion Batteries

NaMnPO4 and NaFePO4, polyanion cathode materials, exist in two different phases maricite/natrophilite and maricite/olivine, respectively. Both natrophilite NaMnPO4 and olivine NaFePO4 are electrochemically active and possess a one-dimensional tunnel for sodium-ion migration; however, these two phases are thermodynamically unstable. Therefore, they can be synthesized through an electrochemical route. On the contrary, maricite (m)-NaMnPO4 and maricite (m)-NaFePO4 are thermodynamically stable forms but have a huge activation energy of their diffusion pathways for sodium extraction and insertion in the crystal structure, which hinders electrochemical reactions. Therefore, the electrochemical behaviour of commercial m-NaMnPO4 and m-NaFePO4 has been studied to find a way for enabling them electrochemically. Ball milling and thermal/mechanical carbon coating are employed to reduce the particle size to enhance the electrochemical performance and shorten the diffusion pathway. Moreover, ball milling leads to defects and partial phase transformation. The electrochemical performance of milled-coated NaMnPO4 and NaFePO4 has been thoroughly investigated and compared. The phase transition of NaFePO4 is revealed by a differential scanning calorimeter. As a result, the achievable capacities of both cathode materials are significantly enhanced up to ∼50 mAh.g−1 via the particle size reduction as well as by carbon coating. However, the side reactions and agglomeration problems in such materials need to be minimized and must be considered to enable them for applications.
Design and Research of Digital Twin System for Hybrid Robot

Based on the digital twin technology, this paper studies the mechanism modeling and monitoring method of a five degrees of freedom hybrid robot, establishes the forward and inverse kinematics models of the robot by using the intermediate parameter method, analyzes the end error by introducing the idea of kinematic equivalent chain, and proposes to extract the flutter characteristics based on the variational mode decomposition. Application modules are designed to monitor the working state of the robot.
Preparation of Titanium-doped Indium Oxide Films by Ultrasonic Spray Pyrolysis Method

Titanium-doped indium oxide (ITiO) films were deposited on soda-lime glass by ultrasonic spray pyrolysis. The optimum conditions of deposition parameters, such as dopant concentration for lowest resistivity were investigated. Phase formation and microstructure of the films were examined by XRD and SEM. AFM was used to obtain the surface topology of the prepared films. The optical transmission and resistivity of films were determined by UV-Vis-NIR spectrophotometer and Van der Pauw method respectively. The resistivity of films depended on the titanium content. The feasibility study of using the ITiO as one of the TCO for solar cell was discussed.
Homogenization of high power diode laser beams for pumping and direct applications

High power diode lasers have become an established source for numerous direct applications like metal hardening and polymer welding due to their high efficiency, small size, low cost and high reliability. These laser sources are also used for efficient pumping of solid state lasers as Nd:YAG lasers. To increase the output power of diode lasers up to several kilowatts, the emitters are scaled laterally by forming a diode laser bar and vertically by forming a diode laser stack. For most applications like hardening and illumination, though, the undefined far field distribution of most commercially available high power diode laser stacks states a major drawback of these devices. As single emitters and bars can fail during their lifetime, the near field distribution does not remain constant. To overcome these problems, the intensity distribution can be homogenized by a waveguide or by microoptic devices. The waveguide segments the far field distribution by several total internal reflections, and these segments are overlaid at the waveguide's exit surface. By the microoptic device, the near field is divided into beamlets which are overlaid by a field lens. Both approaches are presented, and realized systems are described.
Formation of Metal-Oxide Nanocomposites with Highly Dispersed Co Particles from a Co-Zr Powder Blend by Mechanical Alloying and Hydrogen Treatment

The use of metal powders produced by mechanical treatment in various fields, such as catalysis or gas absorption, is often limited by the low specific surface area of the resulting particles. One of the possible solutions for increasing the particle fineness is hydrogen treatment; however, its effect on the structure of mechanically treated powders remains unexplored. In this work, for the first time, a metal-oxide nanocomposite powder was produced by mechanical alloying (MA) in a high-energy planetary ball mill from commercial powders of Zr and Co in the atomic ratio Co:Zr = 53:47 in an inert atmosphere, followed by high-pressure hydrogenation at room temperature. The initial powders and products of alloying and hydrogenation were studied by XRD, 59Co Internal Field NMR, SEM, and HRTEM microscopy with EDX mapping, as well as Raman spectroscopy. MA resulted in significant amorphization of the powders, as well as extensive oxidation of zirconium by water according to the so-called “Fukushima effect”. Moreover, an increase in hcp Co sites was observed. 59Co IF NMR spectra revealed the formation of magnetically single-domain cobalt particles after hydrogenation. The crystallite sizes remained unchanged, which was not observed earlier. The pulverization of Co and an increase in hcp Co sites made this nanocomposite suitable for the synthesis of promising Fischer–Tropsch catalysts.
Deteksi Kebocoran Pipa Air Menggunakan Machine Learning dengan Jaringan Nirkabel IEEE 802.15.4

Pipa adalah cara paling ekonomis dan paling aman dalam mendistribusikan hasil produk seperti air, petrokimia, gas, dan cairan lainnya. Terlepas dari manfaat tersebut, ternyata pipa memiliki ancaman yaitu potensi kebocoran. Artikel ini membahas pendeteksian kebocoran pipa air menggunakan parameter debit aliran. Pengujian dilakukan pada dua format dataset, menggunakan raw dataset dan process dataset menggunakan metode volume balance. Pada proses pembelajaran ada beberapa hal yang perlu disoroti seperti pemilihan tipe dataset, pre-processing dengan menormalisasi dataset, dan menerapkan metode fungsi kernel untuk meningkatkan kinerja akurasi prediksi ukuran dan lokasi kebocoran pipa. Dataset dilatih menggunakan algortima SVM untuk mengklasifikasikan ukuran dan lokasi kebocoran pipa. Hasil klasfikasi ukuran kebocoran dengan fungsi kernel polynomial pada raw dataset mencapai akurasi sebesar 98,25%, recall 99,1%, presisi 99,8%, dan F-measure 99,5%. Sedangkan fungsi kernel Radial Basis Function pada process dataset mencapai akurasi tertinggi sebesar 89,7%, recall 94,4%, presisi 95,4%, dan F-measure 94,6%. Dalam hal mengidentifkasikan lokasi kebocoran, fungsi kernel polynomial pada raw dataset meningkatkan akurasi sebesar 88,96%, recall 94,7%, presisi 91,5%, dan F-measure 92,8%. Sedangkan fungsi kernel polynomial pada process dataset mencapai akurasi sebesar 74,42%, recall 74,1%, presisi 72,8%, dan F-measure 71,3%.