Miracle-dz/UniFAR-FTUs huggingface dataset:
Relaxation layer in electro-magnetically driven strong shocks

A study on electro-magnetically driven shock in laboratory experiments is reported. The shock waves are driven by a compact pulse device at 40 km/s into a high-Z gas with 1 μg/cm3. The pulse power device with tapered electrodes can generate a quasi steady and one-dimensional shock. Ion-electron and ionization relaxation processes, based on a steady and 1-Dimensional shock condition, are calculated. Comparison of the experimental result to calculation one indicates that the shocks produced by the pulse power device have potential to observe ion-electron and ionization relaxation layer with an appropriate spatial scale.
Techno-mathematical literacies in digital age: Which categories are importance for teachers?

Nowadays, digital technologies development potentially have changed on teaching and learning activities and demands teachers’ competencies and literacy. In this study, narrative review is used to identify the types of Techno-mathematical Literacy (TmL) that the teachers need to acquire in this digital age. There are seven categories of TmL studied, namely: data literacy, ability to use computer software, communication skills, ability to analyze errors, ability to interpret numbers, creativity, and drawing skills. The results show that the seven categories are crucial for teachers to execute their role in this highly demanding era. These results also indicate that techno-mathematical literacy needs to be applied in the field of teacher education to adequately equip the students with the skills required in the workplace. The result also suggested that teachers need to be encouraged to develop their instructional design in the attempt to enhance students’ techno-mathematical literacy.
Modelling and simulation of a double‐star induction machine vector control using copper‐losses minimization and parameters estimation

This paper shows that it is possible to extend the principle of field‐oriented control (FOC) approach to a double‐star induction motor (DSIM). In the first stage, a robust variable structure current controller based on space phasor voltages PWM scheme is established. In this current controller design, only the stator currents and rotor speed sensors are used. In the second stage, the FOC method developed for DSIM is motivated by the minimization of the copper losses. The developed approach uses a loss model controller (LMC) and an adaptive rotor flux observer to compute the adequate rotor flux value minimizing the copper losses. The control variables are the stator currents or the machine input power. Compared to the constant rotor flux approach, it is proved that higher performances are achieved. However, the sensitivity of the FOC to parameter error of the machine still remains a problem. To guarantee the performance of the vector control, the stator and rotor resistances are adapted on‐line, based on the Lyapunov theory. An appropriate choice of the reference model allows building a Lyapunov function by means of which the updating law can be found. The simulation results show the satisfactory behaviour of the proposed identification algorithm. Copyright © 2002 John Wiley & Sons, Ltd.
Important edge identification in complex networks based on local and global features

Identifying important nodes and edges in complex networks has always been a popular research topic in network science and also has important implications for the protection of real-world complex systems. Finding the critical structures in a system allows us to protect the system from attacks or failures with minimal cost. To date, the problem of identifying critical nodes in networks has been widely studied by many scholars, and the theory is becoming increasingly mature. However, there is relatively little research related to edges. In fact, critical edges play an important role in maintaining the basic functions of the network and keeping the integrity of the structure. Sometimes protecting critical edges is less costly and more flexible in operation than just focusing on nodes. Considering the integrity of the network topology and the propagation dynamics on it, this paper proposes a centrality measure based on the number of high-order structural overlaps in the first and second-order neighborhoods of edges. The effectiveness of the metric is verified by the infection–susceptibility (SI) model, the robustness index R, and the number of connected branches θ. A comparison is made with three currently popular edge importance metrics from two synthetic and four real networks. The simulation results show that the method outperforms existing methods in identifying critical edges that have a significant impact on both network connectivity and propagation dynamics. At the same time, the near-linear time complexity can be applied to large-scale networks.
3D reconstruction of typical entities based on multi-perspective images

With the progress of technology, 3D printing technology has gradually developed and matured, and has been widely used in aerospace, game artifacts, medical industry and heritage conservation. As a reverse engineering technology of 3D printing, 3D reconstruction technology can reconstruct a 3D mesh model from several images of typical target entities. Monocular 3D reconstruction has the advantages of easy access and low cost. Therefore, this paper improves a multi-view stereo reconstruction technique based on monocular camera: DC-MVSNet. Firstly, the collected multi-view images are sparse reconstructed by colmap to obtain sparse point clouds and camera poses. Then, it is input into DC-MVSNet network and output to get the depth map corresponding to the reference image. Finally, the 3D point cloud model is obtained by deep fusion. In the feature extraction module and depth map refinement module, a densenet and a coordinate attention mechanism are added respectively to improve the feature extraction ability. The proposed method is compared with previous works. The results show that the reconstruction completeness of the algorithm for weakly textured objects is improved in both objective quantitative indexes and subjective perception. The study can be deployed on win10, linux and embedded systems, working reliably and practically. It is of significant reference value for 3D printing reverse engineering.
Readiness of SMEs for Adopt Big Data: An Empirical Study in Vietnam

: This study aims to characterize the readiness of big data adoption and identify important factors for assessing the readiness of Vietnamese SMEs to adopt big data. Consequently, divide SMEs into specific groups based on readiness aspects in order to establish individual group-related recommendations for adopting big data. Questionnaires were used to collect data from 274 SME managers in the manufacturing and service sectors. The key factors defining the readiness of big data application in SMEs were determined by Exploratory Factor Analysis. K-mean clustering analysis was used to group SMEs. The findings highlighted that SMEs are well prepared to adopt big data in decision-making culture, customer interaction, data security, and business strategy factors but not ready in human resources, technology resources, budget resources, government support, and vendor support factors. Big data adoption readiness was defined into three dimensions, namely, Resources, Governance, and Environment readiness. The findings of this study will be important for managers, providers, and policymakers to better understand the factors that assess readiness to adopt big data in SMEs. Hence, they could build e ff ective strategies to incorporate big data and increase their business value and competitiveness.
Retrospective Evaluation of Hematological and Clinical Factors Associated with 30-Day Mortality in 170 Patients Diagnosed with Intracerebral Hematoma in a Single Center in Turkey

Background This retrospective study from a single center in Turkey aimed to evaluate hematological and clinical factors related with 30-day mortality in patients diagnosed with intracerebral hematoma (ICH) between 2013 and 2021. Material/Methods All 170 consecutive patients (>18 years) admitted to the Intensive Care Unit (ICU) with spontaneous ICH were analyzed. Cranial computed tomography was performed in all patients. Venous blood samples were routinely obtained upon admission. Demographic characteristics, blood test results, imaging data, and survival data were retrieved from the institutional digital database. The primary goal of this study was to investigate the role of presenting demographic and clinical characteristics and blood tests in predicting 30-day mortality in patients with spontaneous ICH. Results Receiver operating characteristic curve analysis showed that the Glasgow coma scale (GCS) score (≤9), hematoma volume (>13.4 cm3), hemoglobin (≤13.1 g/dL), international normalized ratio (>1.25), C-reactive protein (CRP) (>7.5 mg/L), and third-day neutrophil-to-lymphocyte ratio (>17.8) could be used to predict 30-day mortality. Patients with low GCS scores (≤9) had a 14.432-fold higher risk of death than other patients (OR: 14.432, 95% CI: 6.421–32.441, P<0.001). Patients with high CRP levels (>7.5) had a 3.323-fold higher risk of death than other patients (OR: 3.323, 95% CI: 1.491–7.405, P=0.003). Conclusions Tailoring scoring systems to include CRP may be beneficial for predicting spontaneous ICH prognosis. However, further studies assessing CRP and other inflammatory markers are necessary to assess whether inflammatory activity could be associated with worse outcomes in patients with ICH.
Planar-defect characteristics and cross-sections of 〈001〉, 〈111〉, and 〈112〉 InAs nanowires

We report on detailed structural and morphological characterizations of InAs nanowires of 〈001〉, 〈111〉, and 〈112〉 crystallographic directions grown on (001)B InAs wafer substrates using high-resolution transmission electron microscopy. We find that 〈001〉-oriented InAs nanowires are cubic zincblende-type structure and free of planar defects. The 〈111〉- and 〈112〉-oriented InAs nanowires both have densely twinned (111) planar defects that are perpendicular and parallel to the growth direction, respectively. The cross sections of all three types of InAs nanowires are obtained from 3D reconstructions using electron tomography. The characteristics of the planar defects and the 3D wire shape should provide better estimations of microstructure-relevant physical properties, such as conductivity and Young’s modulus of InAs nanowires.
Emerging Wearable Biosensor Technologies for Stress Monitoring and Their Real-World Applications

Wearable devices are being developed faster and applied more widely. Wearables have been used to monitor movement-related physiological indices, including heartbeat, movement, and other exercise metrics, for health purposes. People are also paying more attention to mental health issues, such as stress management. Wearable devices can be used to monitor emotional status and provide preliminary diagnoses and guided training functions. The nervous system responds to stress, which directly affects eye movements and sweat secretion. Therefore, the changes in brain potential, eye potential, and cortisol content in sweat could be used to interpret emotional changes, fatigue levels, and physiological and psychological stress. To better assess users, stress-sensing devices can be integrated with applications to improve cognitive function, attention, sports performance, learning ability, and stress release. These application-related wearables can be used in medical diagnosis and treatment, such as for attention-deficit hyperactivity disorder (ADHD), traumatic stress syndrome, and insomnia, thus facilitating precision medicine. However, many factors contribute to data errors and incorrect assessments, including the various wearable devices, sensor types, data reception methods, data processing accuracy and algorithms, application reliability and validity, and actual user actions. Therefore, in the future, medical platforms for wearable devices and applications should be developed, and product implementations should be evaluated clinically to confirm product accuracy and perform reliable research.
Direct Solution of Elliptic Equations by Block Cyclic Reduction and Factorization

Abstract Poisson's and Helmholtz's equations are perhaps the most frequently occurring and important types of partial differential equations encountered in the atmospheric sciences. This paper presents a very fast, accurate technique for finding the numerical solution known as cyclic reduction and factoralization. This method has not heretofore been brought to the attention of the meteorological community at large. This direct method essentially reduces the solution of a separable two-dimensional elliptic equation on an N×M grid to N log2N tri-diagonal systems of order M which are solved by Gaussian elimination. In its simplest form, as described here, the cyclic reduction procedure can be applied if N is 2n−1, 2n2n=1, depending on boundary conditions. However, extensions of the method have been developed which have removed this restrictive limitation. The method is also easily generalized to higher dimensional problems. The mathematical development of the cyclic reduction method is presented here in comp.
From zero-dimension cavities to free-energy functionals for hard disks and hard spheres

We present a systematic approach to derive fundamental-measure theory free-energy functionals for hard disks and hard spheres, entirely from the exact free energy in the zero-dimensional limit of a narrow cavity which cannot hold more than one molecule. The functionals are within the generic class that includes the previous successful versions, but have the remarkable property to yield the exact functional for quasi-one-dimensional density distributions.
Forecasting Airline Fatalities in the World Using a Univariate Time Series Model

This research fit a univariate time series model to the Airline Fatalities in the world from 1920 through 2013. The Box-Jenkins Autoregressive Integrated Moving Average (ARIMA) Model was estimated and the best fitting ARIMA model was used to obtain the post-sample forecasts for five years. The fitted model for the Fatalities was ARIMA (0,1,1) with BIC of 12.375, Stationary R2 of 0.416, and MLE of 243.390. This model was further validated by Ljung-Box test with no significant Autocorrelation between the residuals at different lag times and subsequently by white noise of residuals from the diagnostic checks performed which clearly portray randomness of the standard error of the residuals, no significant spike in the residual plots of ACF and PACF. The forecasts value indicates that Airline Fatalities will increase insignificantly for the next five years (2014-2018).
Spin injection from Heusler alloys into semiconductors: A materials perspective

The notion of using electron spins as bits for highly efficient computation coupled with non-volatile data storage has driven an intense international research effort over the past decade. Such an approach, known as spin-based electronics or spintronics, is considered to be a promising alternative to charge-based electronics in future integrated circuit technologies. Many proposed spin-based devices, such as the well-known spin-transistor, require injection of spin polarized currents from ferromagnetic layers into semiconductor channels, where the degree of injected spin polarization is crucial to the overall device performance. Several ferromagnetic Heusler alloys are predicted to be half-metallic, meaning 100% spin-polarized at the Fermi level, and hence considered to be excellent candidates for electrical spin injection. Furthermore, they exhibit high Curie temperatures and close lattice matching to III-V semiconductors. Despite their promise, Heusler alloy/semiconductor heterostructures investigated in the past decade have failed to fulfill the expectation of near perfect spin injection and in certain cases have even demonstrated inferior behavior compared to their elemental ferromagnetic counterparts. To address this problem, a slew of theoretical and experimental work has emerged studying Heusler alloy/semiconductor interface properties. Here, we review the dominant prohibitive materials challenges that have been identified, namely atomic disorder in the Heusler alloy and in-diffusion of magnetic impurities into the semiconductor, and their ensuing detrimental effects on spin injection. To mitigate these effects, we propose the incorporation of half-metallic Heusler alloys grown at high temperatures (>200 °C) along with insertion of a MgO tunnel barrier at the ferromagnet/semiconductor interface to minimize magnetic impurity in-diffusion and potentially act as a spin-filter. By considering evidence from a variety of structural, optical, and electrical studies, we hope to paint a realistic picture of the materials environment encountered by spins upon injection from Heusler alloys into semiconductors. Finally, we review several emerging device paradigms that utilize Heusler alloys as sources of spin polarized electrons.
Variance bounds for passively locating an acoustic source with a symmetric line array

The maximum‐likelihood (ML) processor is presented for passively estimating range and bearing to an acoustic source. The source signal is observed for a finite‐time duration at several sensors in the presence of uncorrelated noise. When the speed of sound in an isovelocity medium and the sensor positions are known, the ML estimator for position constrains the source to sensor delays to be focused into a point corresponding to a hypothesized source location. The variances of the range error and bearing error are presented for the optimum processor. It is shown that for bearing and range estimation, different sensor configurations are desirable. However, if the area of uncertainty is to be minimized, then the sensors should be divided into equal groups with one‐third of the sensors in each group.
Dual Activation and Photocatalyst-Induced Selective Detection in Defect Tuned Pd–ZnO Thin Films for Low ppm Detection of CH and CO

The selectivity of CO and CH4 remains a hurdle to researchers working on metal-oxide-based sensors, as the sensing mechanism is analogous for both gases. With this objective, an attempt has been made to realize selective sensing of CH4 (up to 1 ppm) and CO (up to 1 ppm) by introducing a selective photocatalyst layer (Zn5(OH)8Cl2.H2O) on Pd–ZnO. It has been noticed that the incorporation of a photocatalytic layer is found to be highly efficacious in providing the sensor with a strong absorption reaction and propelling the surface conversion kinetics. The role of dual activation and photocatalytic activity in selectivity along with tunability is also explored in this work. The dual activation incorporates the benefits of both temperature and optical excitation on metal-oxide-based sensors, highlighting the innumerable advantages and nullifying the disadvantages of both methods. Tunable and selective sensing with a response time/recovery time of 40 s is explicated. The method for improving the sensing performance of Pd–ZnO–photocatalyst-based nanostructures in terms of repeatability and cross sensitivity with respect to 1 ppm of CO, 1 ppm of CH4, 1 ppm of NH3, 250 ppm of CO, and 40% of O2 is discoursed. It has been observed that the sensor with a sensitivity of 23%/ppm for CH4 and 93%/ppm for CO with a minimum baseline drift of less than 3% is achieved. The long-term stability and repeatability of dual-activated sensors are also verified, and less than 3% change has been noticed. The work can be extended for the selectivity of other metal oxides as well.
DadY (PA5303) is required for fitness of Pseudomonas aeruginosa when growth is dependent on alanine catabolism

Pseudomonas aeruginosa inhabits diverse environmental niches that can have varying nutrient composition. The ubiquity of this organism is facilitated by a metabolic strategy that preferentially utilizes low-energy, non-fermentable organic acids, such as amino acids, rather than the high-energy sugars preferred by many other microbes. The amino acid alanine is among the preferred substrates of P. aeruginosa. The dad locus encodes the constituents of the alanine catabolic pathway of P. aeruginosa. Physiological roles for DadR (AsnC-type transcriptional activator), DadX (alanine racemase), and DadA (D-amino acid dehydrogenase) have been defined in this pathway. An additional protein, PA5303, is encoded in the dad locus in P. aeruginosa. PA5303 is a member of the ubiquitous Rid protein superfamily and is designated DadY based on the data presented herein. Despite its conservation in numerous Pseudomonas species and membership in the Rid superfamily, no physiological function has been assigned to DadY. In the present study, we demonstrate that DadA releases imino-alanine that can be deaminated by DadY in vitro. While DadY was not required for alanine catabolism in monoculture, dadY mutants had a dramatic fitness defect in competition with wild-type P. aeruginosa when alanine served as the sole carbon or nitrogen source. The data presented herein support a model in which DadY facilitates flux through the alanine catabolic pathway by removing the imine intermediate generated by DadA. Functional characterization of DadY contributes to our understanding of the role of the broadly conserved Rid family members.
Constrained optimal control of an electronic throttle

The overall vehicle performance is strongly influenced by the quality of the control of the electronic throttle – a DC motor driven valve that regulates the inflow of air to the vehicle's engine. Designing a controller for the throttle system is a challenging task since one has to cope with two strong non-linearities: the gearbox friction and the so-called “limp-home” non-linearity. In this paper we address these issues by solving a constrained optimal control problem formulated for the discrete-time piecewise affine (PWA) model of the throttle. In an off-line, dynamic programming procedure we obtain the look-up table like solution to the optimal control problem. Such a solution allows the real-time controller implementation that would otherwise be impossible to achieve due to the small sampling time needed for the application at hand. We address the issue of the PWA friction modelling in more detail by considering both static and dynamic friction models. Two different control strategies are studied: constrained finite time optimal control (CFTOC), used in the regulator case, and constrained time-optimal control (CTOC), used in the reference tracking case. We report experimental results with both control strategies. The reference tracking controller significantly outperformed a tuned PID controller with a feedforward compensation of non-linearities in terms of the response speed while preserving the response quality regarding the absence of an overshoot and the static accuracy within the measurement resolution.
Potential in spin-density-functional theory of noncollinear magnetism determined by the many-electron ground state

Since Spin Density Functional Theory was first proposed, but also recently, examples were constructed to show that a spin-potential may share its ground state with other spin-potentials. In fact, for collinear magnetic fields and systems with fixed magnetization, the mapping between potentials and ground states is invertible, provided the magnetization is not saturated and that spin-potentials are determined within a spin-constant. We complete the proof that the mapping is invertible also for non-collinear magnetic fields and systems with more than one electron. We then discuss the non-collinear exchange and correlation energy functional and suggest improvements.