Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic Detection of Sorbite Content in High Carbon Steel Wire Rod

This paper presents a method for the automatic detection of sorbite content in high-carbon steel wire rods. A semantic segmentation model of sorbite based on DeepLabv3+ is established. The sorbite structure is segmented, and the prediction results are analyzed and counted based on the metallographic images of high-carbon steel wire rods marked manually. For the problem of sample imbalance, the loss function of Dice loss + focal loss is used, and the perturbation processing of training data is added. The results show that this method can realize the automatic statistics of sorbite content. The average pixel prediction accuracy is as high as 94.28%, and the average absolute error is only 4.17%. The composite application of the loss function and the enhancement of the data perturbation significantly improve the prediction accuracy and robust performance of the model. In this method, the detection of sorbite content in a single image only takes 10 s, which is 99% faster than that of 10 min using the manual cut-off method. On the premise of ensuring detection accuracy, the detection efficiency is significantly improved and the labor intensity is reduced.
Exploring Computer Science student engagement factors within the learning analytics context to increase their academic achievement

The study aims to improve student retention rate and maintain student engagement level by exploring the student motivation factors within a learning analytics context. This research is an exploratory case study within the Computer Science Department at the University of Huddersfield, UK. The research focuses to develop a model to explore undergraduate CS student motivation factors through Self-Determination Theory and train the identified factors using learning analytics records. The identified factors will contribute to enhance the student academic achievement and their engagement with the course. In addition, the factors can be used to assist the future designer of learning analytics (LA) tools to adapt the human center design approach. Therefore, the new LA tools can incorporate cognitive and noncognitive factors that can enhance student retention rate and engagement toward computer science department. The study adapts a mixed-method approach using survey, interview and learning analytics records. More than 10,000 thousand virtual learning environment records were analyzed from the year 2018 to 2021. The analysis findings revealed that there are 8 significant factors that can have an impact on CS student engagement and therefore affecting their final grade.
Streamwise dispersion and mixing in quasi-two-dimensional steady turbulent jets

Abstract We investigate experimentally and theoretically the streamwise transport and dispersion properties of steady quasi-two-dimensional plane turbulent jets discharged vertically from a slot of width $d$ into a fluid confined between two relatively close rigid boundaries with gap $W\ensuremath{\sim} O(d)$ . We model the evolution in time and space of the concentration of passive tracers released in these jets using a one-dimensional time-dependent effective advection–diffusion equation. We make a mixing length hypothesis to model the streamwise turbulent eddy diffusivity such that it scales like $b(z){ \overline{w} }_{m} (z)$ , where $z$ is the streamwise coordinate, $b$ is the jet width, ${ \overline{w} }_{m} $ is the maximum time-averaged vertical velocity. Under these assumptions, the effective advection–diffusion equation for $\phi (z, t)$ , the horizontal integral of the ensemble-averaged concentration, is of the form ${\partial }_{t} \phi + {K}_{a} {\text{} {M}_{0} \text{} }^{1/ 2} {\partial }_{z} \left(\phi / {z}^{1/ 2} \right)= {K}_{d} {\text{} {M}_{0} \text{} }^{1/ 2} {\partial }_{z} \left({z}^{1/ 2} {\partial }_{z} \phi \right)$ , where $t$ is time, ${K}_{a} $ (the advection parameter) and ${K}_{d} $ (the dispersion parameter) are empirical dimensionless parameters which quantify the importance of advection and dispersion, respectively, and ${M}_{0} $ is the source momentum flux. We find analytical solutions to this equation for $\phi $ in the cases of a constant-flux release and an instantaneous finite-volume release. We also give an integral formulation for the more general case of a time-dependent release, which we solve analytically when tracers are released at a constant flux over a finite period of time. From our experimental results, whose concentration distributions agree with the model, we find that ${K}_{a} = 1. 65\pm 0. 10$ and ${K}_{d} = 0. 09\pm 0. 02$ , for both finite-volume releases and constant-flux releases using either dye or virtual passive tracers. The experiments also show that streamwise dispersion increases in time as ${t}^{2/ 3} $ . As a result, in the case of finite-volume releases more than 50 % of the total volume of tracers is transported ahead of the purely advective front (i.e. the front location of the tracer distribution if all dispersion mechanisms are ignored and considering a ‘top-hat’ mean velocity profile in the jet); and in the case of constant-flux releases, at each instant in time, approximately 10 % of the total volume of tracers is transported ahead of the advective front.
The dead pig's photo album: Affective visual rituals in collective identity formation

Recent research on visually mediated activism has focused on visual practices as forms of political expression. Conversely, this article will demonstrate that visuality is not only used for protest mobilisation, but that it also plays a significant role in solidifying movement-internal collective identity through a set of distinct visual rituals that produce a shared understanding through affect. Based on an ethnography of everyday visual practices and social experiences of visuality (online and offline) in the Save Movement's ‘Pig Save’ protest events, we identify three forms of affective visual rituals: (1) witnessing; (2) mourning; and (3) semiotic rituals. We argue that these visual rituals are not only expressions of shared values, but construct collective political identity through backstage visual emotion work (affect).
Ecological Driving Framework of Hybrid Electric Vehicle Based on Heterogeneous Multi-Agent Deep Reinforcement Learning

Hybrid electric vehicles (HEVs) have great potential to be discovered in terms of energy saving and emission reduction, and ecological driving provides theoretical guidance for giving full play to their advantages in real traffic scenarios. In order to implement an ecological driving strategy with the lowest cost throughout the life cycle in a car-following scenario, the safety and comfort, fuel economy, and battery health need to be considered, which is a complex nonlinear and multiobjective coupled optimization task. Therefore, a novel multi-agent deep deterministic policy gradient (MADDPG) based framework with two heterogeneous agents to optimize adaptive cruise control (ACC) and energy management strategy (EMS), respectively, is proposed, thereby decoupling optimization objectives of different domains. Because of the asynchronous of multi-agents, different learning rate schedules are analyzed to coordinate the learning process to optimize training results; an improvement on the prioritized experience replay (PER) technique is proposed, which improves the optimization performance of the original MADDPG method by more than 10%. Simulations under mixed driving cycles show that, on the premise of ensuring car-following performance, the overall driving cost, including fuel consumption and battery health degradation of the MADDPG-based method, can reach 93.88% of that of DP, and the proposed algorithm has good adaptability to different driving conditions.
A Junction Temperature Monitoring Method for IGBT Modules Based on Turn-Off Voltage With Convolutional Neural Networks

Junction temperature monitoring (JTM) is essential for reliability evaluation and health management for insulated-gate bipolar transistor (IGBT) modules, and thus is extensively focused on in power electronics converters. However, many JTM methods for IGBT modules are criticized for providing inaccurate junction temperature information with strong load current dependence. To address this, a JTM method based on the turn-off voltage (TOV) and convolutional neural networks (CNN) is proposed in this article. In this method, the TOV is used as the junction temperature indicator, and the characterization behavior of the TOV during turn-off transient process is thoroughly analyzed. Then, the parameter dependence of the TOV is investigated. Considering the proposed JTM method may be subject to the issue of load current dependence and show an undesirable performance, the CNN is adopted to maintain the accuracy of junction temperature prediction due to its excellent global and local feature recognition capability. With this regards, the proposed JTM method enables to provide accurate junction temperature information under different conditions. Finally, the double-pulse tests and experimental tests are carried out to validate the effectiveness of the proposed JTM method.
Ionospheric signatures of solar flares.

VLF waves propagate in the Earth-ionosphere waveguide (EIW). The EIW is bounded below by the surface of the Earth and above by the ionospheric D-region (50–90 km altitude). The conditions for wave propagation in the EIW are studied and derived specifically for VLF propagation. The D-region is maintained by shortwave solar radiation that ionises the neutral atmosphere. The Wait parameters, H ′ (reflection height) and β (sharpness), describe the lower boundary of the D-region. Any enhancement in solar X-rays modifies these parameters, leading to a change in the propagation conditions for VLF signals. The effect of the terminator is presented where, it is found to narrow the depression of the monthly averaged diurnal amplitude profile from summer to winter. A series of solar flares were identified of which two case studies are presented. H ′ and β are calculated from the VLF signals by the Long Wave Propagation Code (LWPC). It is found that H ′ decreased and β increased at the time of flare. Once H ′ and β are obtained, the electron density profile can be constructed which is of crucial importance for VLF waves propagating in the EIW. The gradient of the electron density profile is found to increase as β increases. It’s found that all the modal interference minima are moved towards the transmitter at the time of the flare. For flares of great magnitude, extrapolation is required to classify the flare in a magnitude class using VLF data. The change in the phase of the VLF signal is found to be linearly proportional to the change in the X-ray flux.
Face Monitor: An Arbitrary Approach for Facial Engagement Monitoring in Virtual Classrooms

Following the spread of COVID-19, a sharp rise was found in virtual classrooms worldwide, where ensuring the continuous engagement of participants is a big challenge. Continuous engagement relies on continuous authentication, where technologies like biometrics are helpful to determine the engagement level of the participants. In our work, we developed an application called Face Monitor, which uses facial soft bio-metrics to authenticate the participants arbitrarily, and later to determine the engagement level using this arbitrary authentication information. Our developed application Face Monitor is a critical component of our proposed multi-faceted engagement monitoring platform known as ENGAGE. In our work, several existing online teaching and learning platforms are also compared for existing engagement monitoring support and we defined our own criterion for relative engagement. This paper presents a complete architecture of our developed application called Face Monitor, its functioning, and an output demo. In our opinion, Face Monitor is a genuinely useful application for the higher education sector throughout the world. Face Monitor can be useful to determine the relative level of engagement for different participants during a series of teaching sessions and to calculate overall grades for a module or training session.
Pursuer Coordination Against a Fast Evader via Coverage Control

Scalable pursuer coordination for reach-avoid games against a fast evader are developed leveraging coverage control over manifolds. The maintenance of a manifold, termed defense surface, prevents the evader and its target from occupying the same half-space and shown sufficient as a cooperative capture strategy. Nonlinear control synthesis continually reconfigures the pursuers to enable a defense surface via coverage. Simulation results empirically validate that the proposed condition serves as a surrogate objective for pursuer team coordination.
Occurrence and ecological risk assessment of pharmaceutically active compounds in neotropical small basins, Brazil

Abstract: Aim The aim of our study was to evaluate the contamination levels of selected pharmaceutically active compounds (PAC) and their potential ecological threat to forested streams. Methods Samples of stream water were collected in the second largest city in Mato Grosso do Sul State in center-west of Brazil. Physicochemical parameters and concentrations of PAC were quantified in samples collected in six field campaigns. Ecological risk assessment (ERA) based on risk quotient (RQ) was performed based on the maximum measured concentration of PAC in water. Results Six pharmaceutical compounds were successfully quantified in the forested streams, namely caffeine, naproxen, diclofenac, estriol, estradiol and ethinylestradiol. From the point of view of ecological risk, ethinylestradiol (22,57), estradiol (1,46), diclofenac (16.99) and caffeine (5.30) can be considered as priorities PAC, as they present moderate to high risks to aquatic organisms and may also cause damage to the food chain. Conclusions This study provides valuable information to emphasize the importance of continuous monitoring of forested streams in the west central region of the country, as well as efforts to control the input of these micropollutants into watercourses.
Spherically symmetric states of Hookium in a cavity

When a two-electron atom or ion is enclosed in an impenetrable spherical cavity, level crossings and avoided crossings are observed as the cavity radius changes. The locations of those crossings depend on the cavity radius and the nuclear charge of the system. The question arises as to whether this crossing behavior is unique to the one-electron Coulomb potential or whether it can be observed in other confined single-particle electron potentials. In this work we examined some low-lying singlet and triplet states of two-electron systems with isotropic harmonic single-particle 3D potentials. The spherically symmetric S states are analyzed using variational energies calculated with Hylleraas-type function. The energy dependence of low-lying states is considered as a function of the cavity radius and the harmonic force constant. For positive force constants, there exist cavity radii where the 21S and 13S states are degenerate. Analogous points do not exist for the two-electron quantum dot where the one-electron potential corresponds to an infinite rectangular box. The structure of the energy spectrum for negative force constants is also studied. The similarities and differences of the two-electron S states for the Coulomb and harmonic potentials are considered.
New Form of the Hamiltonian Equations for the Nonlinear Water-Wave Problem, Based on a New Representation of the DTN Operator, and Some Applications

We present a new Hamiltonian formulation for the non-linear evolution of surface gravity waves over a variable impermeable bottom. The derivation is based on Luke’s variational principle and the use of an exact (convergent up to the boundaries) infinite-series representation of the unknown wave potential, in terms of a system of prescribed vertical functions (explicitly dependent on the local depth and the local free-surface elevation) and unknown horizontal modal amplitudes. The key idea of this approach is the introduction of two unconventional modes ensuring a rapid convergence of the modal series. The fully nonlinear water-wave problem is reformulated as two evolution equations, essentially equivalent with the Zakharov-Craig-Sulem formulation. The Dirichlet-to-Neumann operator (DtN) over arbitrary bathymetry is determined by means of a few first modes, the two unconventional ones being most important. While this formulation is exact, its numerical implementation, even for general domains, is not much more involved than that of the various simplified models (Boussinesq, Green-Nagdhi) widely used in engineering applications. The efficiency of this formulation is demonstrated by the excellent agreement of the numerical and experimental results for the case of the classical Beji-Battjes experiment. A more complicated bathymetry is also studied.Copyright © 2015 by ASME
Asynchronous Engagement through Online Discussion Forums: Experiences from English Language Students in a Philippine State University

The creation of a well-developed ecological environment for English language teachers in digital platforms is a relevant and humane practice amidst the pandemic. During these times of crisis, Higher Education Institutions (HEIs) in the Philippines need to adopt new learning modalities. However, some students find it difficult to attend in synchronous mode of classes, as an alternative way, teachers need to employ asynchronous activities such as conducting online discussion forums (ODFs) where students can freely interact and share their insights on a topic within the given timeframe. Studies conducted on ODFs in the English language classrooms remain scant, especially in the Philippines, which examined the same or related focus. Thus, through qualitative approach, semi-structured interviews were conducted to 21 freshmen English language students in a Philippine state university. Further, the data was analyzed using conventional content analysis method (Hsieh and Shannon, 2005). The findings indicated the students’ insights on the use of ODFs such as it its risk for cheating during the asynchronous forums, its accessibility through Facebook as a platform for asynchronous engagement, encourage the exchange of ideas for new learning opportunities, and helps review the previous lessons discussed. There were notable challenges encountered by the students, however, specific strategies they have employed were disclosed. Also, when ODFs will be managed well by classroom teachers, students will become more engaged in asynchronous discussions. © 2023 JELS and the Authors - Published by JELS.
Automatic detection method of conveyor belt deviation based on DeepLabv3+

Conveyor is one of the main equipment for coal production and transportation. Due to impact fatigue, uneven surface stress of conveyor belt and other external factors, deviation will occur, leading to material overflow and damage to transportation equipment. Therefore, it is of great significance to detect the deviation status of the conveyor belt quickly and timely to ensure the safe and efficient operation of the transportation system. This paper presents an automatic detection method of belt deviation based on DeeplabV3+, which can detect the deviation of any position of belt conveyor. We have established a new belt edge dataset under real working conditions. In order to improve the deviation detection accuracy, we expand and erode the image after feature extraction, extract the centerline, and finally detect the deviation distance through the deviation detection module. Experiments show that this method can well balance the detection accuracy and detection speed. The processing speed of a single image is 0.32 s, and the conveyor belt edge detection error is less than 6mm, this method has good real-time performance and high precision, and can be applied to the production scene of underground coal mine.
AC Copper Loss Reduction in Planar Inductors With Magnetic Building Blocks-Based Gapless Parallel Symmetrical Magnetoresistance Structure

Fringing and proximity effects are the main reasons for serious ac copper loss in high-frequency planar inductors. In this article, a novel air-gapless core structure based on magnetic building blocks (MBBs) with magnetoresistance parallel and symmetrically distributed relative to the windings is proposed, in which two magnetic building blocks parallel to the printed circuit board (PCB) windings are made of metal soft magnetic material with low relative permeability and three magnetic building blocks perpendicular to windings are made of ferrite with high relative permeability. Equivalent magnetic circuit models and theoretical analysis for the proposed core structure reveal that even if the interleaved winding structure fails in the inductor, a better distribution of magnetomotive force can be obtained by optimizing the distribution of magnetoresistance. Compared with the conventional inductors using stand airgaps, both the fringing and proximity effects can be weakened by the designed parallel symmetrical magnetoresistance core structure, which has been verified in 3-D finite-element analysis (FEA)-based simulations. The FEA calculated results show that the proposed optimized core structure can achieve a 46% reduction in ac resistance, and this advantage will extend with increasing frequency over a certain frequency range. On a boost converter operating in critical conduction mode, experimental verification including converter efficiency test and inductor loss test was carried out. The maximum efficiency improvement was 1.4%, and the reduction of inductor loss was also verified.
Antibiotics Resistance and Adhesive Properties of Clinical Staphylococcus aureus Isolated from Wound Infections

Staphylococcus aureus (S. aureus) is a ubiquitous pathogen responsible for several severe infections. This study aimed to investigate the adhesive properties and antibiotic resistance among clinical S. aureus isolated from Hail Hospital Province, Kingdom of Saudi Arabia (KSA), using molecular approaches. This study was conducted according to the ethical committee at Hail’s guidelines on twenty-four S. aureus isolates. A polymerase chain reaction (PCR) was performed to identify genes encoding the β-lactamase resistance (blaZ), methicillin resistance (mecA), fluoroquinolone resistance (norA), nitric oxide reductase (norB), fibronectin (fnbA and fnbB), clumping factor (clfA) and intracellular adhesion factors (icaA and icaD). This qualitative study tested adhesion based on exopolysaccharide production on Congo red agar (CRA) medium and biofilm formation on polystyrene by S. aureus strains. Among 24 isolates, the cna and blaz were the most prevalent (70.8%), followed by norB (54.1%), clfA (50.0%), norA (41.6%), mecA and fnbB (37.5%) and fnbA (33.3%). The presence of icaA/icaD genes was demonstrated in almost all tested strains in comparison to the reference strain, S. aureus ATCC 43300. The phenotypic study of adhesion showed that all tested strains had moderate biofilm-forming capacity on polystyrene and represented different morphotypes on a CRA medium. Five strains among the twenty-four harbored the four genes of resistance to antibiotics (mecA, norA, norB and blaz). Considering the genes of adhesion (cna, clfA, fnbA and fnbB), these genes were present in 25% of the tested isolates. Regarding the adhesive properties, the clinical isolates of S. aureus formed biofilm on polystyrene, and only one strain (S17) produced exopolysaccharides on Congo red agar. All these results contribute to an understanding that the pathogenesis of clinical S. aureus isolates is due to their antibiotic resistance and adhesion to medical material.