Miracle-dz/UniFAR-FTUs huggingface dataset:
Density estimation using non-parametric and semi-parametric mixtures

This article presents a general framework for univariate non-parametric density estimation, based on mixture models. Similar to kernel-based estimation, the proposed approach uses bandwidth to control the density smoothness, but each density estimate for a fixed bandwidth is determined by non-parametric likelihood maximization, with bandwidth selection carried out as model selection. This leads to simple models, yet with higher accuracy, especially in terms of the Kullback–Leibler or the Hellinger risk. The particular problem of estimating a symmetric density function is investigated. Both simulation study and real-world data examples suggest that the mixture-based estimators outperform their kernel-based counterparts.
Four-phase Buck Converter Design and Thermal Modeling Using FEA Simulation

Equipment with high efficiency, high power density, reduced size and low cost are in demand in the automotive industry. This work presents a method to design and model a high power-density four-phase DC-DC Buck converter for an automotive application and using the components operating temperature as a design criteria. A parameter sweep is done to select the operating point of the DC-DC converter combined with an iterative method to select part numbers, where preference is given to components that are AEC-Qxxx qualified. The converter is modeled and power losses are computed in SPICE considering the parasitic elements present in the PCB and the dynamic characteristics and non-idealities of the electronic components; thermal modeling is performed using Ansys Icepak. The results indicate that the design meets all electrical and thermal requirements for an automotive application. An efficiency of 95.97% is obtained in a four-phase DC-DC Buck converter that supplies a total of 800 W to 4 loads, in a space of 43.77 cm3, that is, an estimated power density of 18.28 W/cm3.
Evaluation of Convolutional Neural Network for Automatic Caries Detection in Digital Radiograph Panoramic on Small Dataset

Dental caries or tooth decay is damage to the hard tissues of the teeth that can occur in the enamel, dentin, and cementum areas. Panoramic radiography is a screening tool for tactile or visual examination of the oral cavity which is useful for further diagnosis and treatment. The process of segmentation of panoramic radiographs is a difficult process because there is no homogeneity between panoramic images with one another. Noise levels, vertebral column images, and low contrast are the main challenges in image processing. This study evaluates CNN to detect caries automatically on panoramic radiographs on a small dataset. The dataset consisted of manually cropped maxillary and mandibular premolars and molars. An augmentation strategy consisting of horizontal flip, vertical flip, and affine transformation is used to produce a wider variety of images. This study compares the architecture of non-pretrained and pretrained models consisting of 3-layer CNN, 3-layer CNN with batch normalization, ResNet18, and ResNeXt50 32×4d. Evaluation was carried out on 400 training data and 76 testing data. Combination of augmentation strategies and pre-trained ResNet18 and ResNeXt50 32×4d achieves high accuracy compared to other models.
Bad Data Detection and Handling in ICT Platforms for Energy Systems

In this paper, we present a modular tool for bad data detection, handling and recovery in ICT platforms. The proposed tool can be easily applied to platforms with different structures to perform online and offline analysis aimed at monitoring the data quality, recovering bad data, and investigating the proper operation of the platform’s components. Firstly, the considered framework is introduced, then each module is described underlying its characteristics. Moreover, we present and discuss the results obtained by means of the recovery tool on a real test case.
Fundamental Multi-factor Deep-learning Strategy For Cryptocurrency Trading

This paper investigates how to use deep learning methods to combine with traditional multi-factor models and construct a quantitative trading model based on an AutoEncoder algorithm (AE) to classify cryptocurrencies since 2009, so as to screen out ones with investment value and then construct an effective investment portfolio. The AE algorithm is capable of handling high-dimensional data and mining interfactor non-linearities. Our empirical results on cryptocurrencies show that the model outperforms single-type factors and benchmark in terms of Cumulative Returns and the Sharpe Ratio.
Learning Cybersecurity in IoT-based Applications through a Capture the Flag Competition

The Internet of Things (IoT) is one of the main foundations of Industry 4.0, providing widespread connectivity of systems and devices, which promotes significant benefits, such as improved performance, responsiveness, and reconfigurability. However, it also brings some security problems, which make these devices and systems vulnerable to cyberattacks, consequently demanding efficient learning and training initiatives to address the challenges regarding the qualification of undergraduate students and active professionals to design more secure systems, as well as to be more aware of cyberthreats during the management and use of them. With this in mind, this paper describes a Capture the Flag competition based on IoT cybersecurity. The participants’ feedback and performance evaluation show that this type of hands-on competition strongly contributes to learning the importance of cybersecurity in IoT-based applications.
Recent Developments of Solid-State Electrolytes for All-Solid-State Lithium Metal Batteries

With the rapid popularization and development of lithium-ion batteries (LIBs), a series of challenges concerning the safety issues and the limited capacity of LIBs has drawn increasing attention. To address these challenges, all-solid-state batteries (ASSBs) with the solid-state electrolytes (SSEs), which have demonstrated high energy density and high safety, are expected to grow as next-generation power source for electric vehicles to replace conventional LIBs. This paper reviews the progress of SSE techniques, including inorganic, polymer and composite solid electrolyte systems. The advantages and limitations of these SSEs were further discussed with the summarization and comments about the preparation and modification techniques, as well as their applications and enhancements in ASSB. By giving a systematic introduction to the existing popular solid electrolyte strategies, the perspectives about the challenges and developments for the practical applications of SSEs are also proposed. The technology of SSEs reveals high promising future and great potential to reshape the power sources of electric vehicles.
Sustaining Education by Actualizing Affordances of Social Media Platforms During the Pandemic

This paper draws on the affordances theory and investigates the ways in which pre-service teachers are sustaining social media uptake in learning by taking advantage of the opportunities afforded by the new delivery methods during the pandemic. This research is part of a descriptive mixed methods study. A questionnaire and in-depth, qualitative interviews were used to explore pre-service teachers’ perceptions of the affordances of social media platforms for learning and the actualization of those affordances. The survey and interview data were analyzed through the theoretical lens of affordance theory. The results suggest that the pre-service teachers actualized the affordances of social media by their knowledgeable use in a dynamic learning environment. The key findings are that the teachers perceived the social media applications to be flexible, useful and practical (functional affordances), bridges formal and informal learning and supported self-regulated learning (cognitive affordances), allowed pre-service teachers to assume new identities and discover learning as independent learners who had control over their learning (identity creation affordances), and fostered interaction and collaborative feedback (social affordances). Lack of guidance or lack of teacher presence was the main constraint. This research produces new knowledge and analysis and makes new theoretical contributions on the specific affordances of social media technologies. This study adds to and extends existing literature by contributing to an understanding of the actualization of the affordances of social media platforms.
The moments of the number of exits from a simply connected region

We generalise the work of Cramér and Leadbetter, Ylvisaker and Ito on the level crossings of a stationary Gaussian process to multivariate processes. Necessary and sufficient conditions for the existence of the expected number of crossings E(C) of the boundary of a region of ℝ p by a stationary vector stochastic process are obtained, along with an explicit formula for E(C) in the Gaussian case. A rigorous proof of Belyaev's integral formula for the factorial moments of the number of exits from a region of ℝ p is given for a class of processes which includes Gaussian processes having a finite second order spectral moment matrix. Applications to χ2 processes are briefly considered.
Correlative factor of death in patients with infected pancreatic necrosis after surgical intervention

Background: Acute pancreatitis (AP) was a potentially fatal disease with a variation in severity. Infected pancreatic necrosis was a common complication in AP which needed surgical intervention. The present study was to study the correlative factors of death in patients with infected pancreatic necrosis after surgical intervention. Methods: From January 2016 to October 2019, a total of 186 patients with infected pancreatic necrosis after surgical intervention in the First Medical Center, Chinese PLA General Hospital were retrospectively enrolled in this study. Of the 186 patients, 22 who died in the hospital were defined as a mortality group and the others as a survival group. The clinical characteristic of the 2 groups was compared and the relative risk of mortality in patients with infected pancreatic necrosis after the surgical intervention was studied. Results: Acute fluid collection, acute kidney injury, acute lung injury, acute liver injury, multiple organ dysfunction syndromes, abdominal bleeding, abdominal Acinetobacter baumannii infection, pulmonary infection, pulmonary A baumannii infection, positive blood culture, A baumannii of blood culture, severe acute pancreatitis according to Atlanta 2012, the use of continuous renal replacement therapy, mechanical ventilation and minimally invasive retroperitoneal pancreatic necrosectomy was associated with death in hospital. Older age, longer acute kidney injury lasting time, longer acute lung injury lasting time, longer acute liver injury lasting time, and longer multiple organ dysfunction syndromes lasting time in predicting mortality in patients with infected pancreatic necrosis after surgical intervention were (0.635 [95% confidence interval (CI): 0.512–0.758], P = . 040), (0.877 [95% CI: 0.788–0.965], P = .000], (0.932 [95% CI: 0.897–0.968], P = .000), (0.822 [95% CI: 0.708–0.935], P = .000), and (0.943 [95% CI: 0.887–0.998], P = .000). Due to the small number of death cases, the results of the multivariate analyses were not available. Conclusion: In this single-center retrospective study of 186 cases of infected pancreas necrosis, the correlative factors of death are identified. The results warranted further strategies are needed especially focusing on elder patients to prevent blood infection and to protect the functions of vital organs.
Research of SIFT matching algorithm in binocular vision

According to that the SIFT algorithm contains contour property in the process of computation of scale-space, this paper proposes an improved SIFT algorithm named Contour directed-SIFT to offset the flaws of real-time in SIFT algorithm. In order to improve the accuracy of SIFT algorithm, the paper improve the Contour directed-SIFT algorithm using the epipolar constraint. Taking the two aspects above, a new matching algorithm based on SIFT algorithm in binocular vision is proposed. This algorithm can assure the real-time and accuracy in matching images, which can be applied in matching of massive features of tridimensional vision.
DIVISION OF THE HUMANITIES AND SOCIAL SCIENCES

: Social welfare funcitons for privafe goods economies with classical preferences are considered. It is shown that every social welfare function satisfying a weak nonimposition condition and the independence of irrelevant alternatives axiom is of one of the following forms. It is either null or the class of decisive coalitions is an ultrafilter or the class of anti-decisive coalitions is an ultrafilter.
Elastic Moduli of Diamond as a Function of Pressure and Temperature

Values of wave velocities and elastic moduli at 25°C were measured for hydrostatic pressures to 20 000 psi (excess over 1 atm). Variations of velocities and moduli at 1 atm were obtained over a temperature range of +50°C to −195.8°C. Adiabatic stiffness moduli (units of 1012 dyn/cm2), their pressure derivatives, and their temperature coefficients (units of 10−5/C), are shown below for 1 atm and 25°C. ModulusValuePressure derivativesTemperature coefficientc1110.79±0.055. 98±0.7−1.37±0.2c12 1.24±0.053. 06±0.7−5.70±1.5c44 5.78±0.022. 98±0.3−1.25±0.1
Global invertibility of Sobolev functions and the interpenetration of matter

Synopsis A global inverse function theorem is established for mappings u: Ω → ℝn, Ω ⊂ ℝn bounded and open, belonging to the Sobolev space W1.p(Ω), p > n. The theorem is applied to the pure displacement boundary value problem of nonlinear elastostatics, the conclusion being that there is no interpenetration of matter for the energy-minimizing displacement field.
OPTICAL PROPERTIES OF INDIUM ANTIMONIDE InSb

An understanding of the optical properties of Indium Antimonide (InSb) is important because of the increasing application of InSb in many optical and electronics devices. Optical properties of Indium Antimonide (InSb) have been investigated by means of the Kramers and Kronig method in photon energy range 1.0 – 6.01eV. The properties investigated includes: refractive index which has a maximum value of 4.91 at photon energy 1.82eV; the extinction coefficient which has a maximum value of 3.72 at photon energy 4.05eV; the dielectric constant, the real part of the complex dielectric constant, which has a maximum value of 22.3 at photon energy 1.77eV; the imaginary part of the complex dielectric constant having a maximum value of 21.3 at photon energy 3.85eV; the transmittance which has a maximum value of 0.20 at photon energy 3.61eV; the absorption coefficient which has a maximum value of 1.53 x 10 m at photon energy 4.09eV; the reflectance which has a maximum value of 0.64 at 4.17eV; the reflection coefficient which has a maximum value of 0.80 at photon energy 4.17eV; the real part of optical conductivity which has a maximum value of 9.99 x 10 at 3.89eV; and the imaginary part of the optical conductivity has a maximum value of 4.49 x 10 at 4.13eV. The values obtained for optical properties of InSb are essentially important for emerging InSb applications such as fabrication of antenna-coupled infrared detectors, photo-electric, magnet-electric conversion devices and optoelectronic devices.
Buoyancy of Convective Vertical Motions in the Inner Core of Intense Hurricanes. Part II: Case Studies

Abstract This is the second of two papers on the buoyancy of convective vertical motions in the inner core of intense hurricanes. This paper uses extensive airborne radar, dropwindsonde, and flight-level observations in Hurricanes Guillermo (1997) and Georges (1998) to illustrate typical azimuthal distribution of buoyant convection and demonstrate that the low-level eye can be an important source region for buoyant eyewall convection. In both hurricanes, eyewall vertical velocity and radar reflectivity are asymmetric and exhibit persistent relationships with the direction of the environmental vertical wind shear. Mesoscale vertical motions exhibit a wavenumber-1 structure with maximum ascent downshear and weak descent upshear. The mesoscale reflectivity maxima are located left-of-shear. Buoyant eyewall updraft cores and transient convective-scale reflectivity cells are predominantly downshear and left-of-shear. Most eyewall downdraft cores that transport significant mass downward are located upshear. Nega.
Retrieval of Tropical Cirrus Thermal Optical Depth, Crystal Size, and Shape Using a Dual-View Instrument at 3.7 and 10.8 μm

Abstract In this paper the authors derive thermal optical depth at 3.7 and 10.8 μm for tropical cirrus utilizing Along Track Scanning Radiometer data under nighttime conditions. By analytically solving the equation of radiative transfer, inclusive of scattering, a pair of nonlinear equations can be solved for the optical depth. Stable and unique solutions for the optical depth are found by combining nadir and forward (55°) views. The accuracy of the analytic solution is compared with solutions from a numerical radiative transfer model assuming an isothermal cirrus cloud. Numerical solutions for two nonisothermal cirrus clouds are also compared with the analytic solution for an equivalent mean cloud temperature. The numerical model uses appropriate hexagonal column scattering phase functions at 3.7 and 10.8 μm. The largest analytic model error is shown to occur at nadir, and it is shown that this error is not overly sensitive to crystal size and is independent of cloud-top temperature. A correction to the .
Quantifying the dynamic evolution of individual arched magnetic flux tubes

Highly dynamic arched ‘loops’ of plasma were created in the laboratory with a magnetized plasma gun. The magnetic structure of the loops was found to be consistent with that of an expanding flux tube subject to a kink instability. High-speed flows were found to transport plasma along the loop axis, from both footpoints toward the apex of the arched loop. Two complementary MHD models were used to explain the expansion and axial flows, both of which scale in proportion to a ‘toroidal Alfven speed’.
Flow Boiling in Horizontal Tubes: Part 3—Development of a New Heat Transfer Model Based on Flow Pattern

A new heat transfer model for intube flow boiling in horizontal plain tubes is proposed that incorporates the effects of local two-phase flow patterns, flow stratification and partial dryout in annular flow. Significantly, the local peak in the heat transfer coefficient versus vapor quality can now be determined from the prediction of the location of onset of partial dryout in annular flow. The new method accurately predicts a large, new database of flow boiling data, and is perticularly better than existing mehods at high vapor qualities (x > 85%) and for stratified types of flows.
Strain engineering of band offsets in Si/Ge core-shell nanowires

We present first-principles studies on how to engineer band lineups of nanosized radial heterojunctions, Si/Ge core-shell nanowires. Our calculation reveals that band offsets of these one-dimensional nanostructures can be tailored by applying the axial strain. In particular, the valence band offset can be efficiently tuned in a wide range and even be diminished with applied strain. Two mechanisms contributing to this strain engineering of band offsets are discussed. Our proposed approach to control band offsets in nanosized heterojunctions may be of practical interest for nanoelectronics and photovoltaic applications.
Logit-based stochastic user equilibrium problem for entry-exit toll schemes

This paper proposes a logit-based stochastic user equilibrium (SUE) problem for networks with entry-exit toll schemes that result in nonadditive path costs. First, it develops a strictly convex minimization model in terms of path flows for the problem. Second, by decomposing the original problem into two kinds of subproblems that possess the additive path costs, this study designs a novel two-stage stochastic loading algorithm exempted from path enumeration or generation. Hence, the method of successive average embedded with the proposed stochastic loading algorithm can identify the logit-based SUE link and entry-exit flows. Finally, two numerical examples are used to demonstrate the proposed model and algorithm.
Charge trapping in alumina and its impact on the operation of metal-alumina-nitride-oxide-silicon memories: Experiments and simulations

We investigate the electron/hole trapping phenomena in alumina blocking oxide and their impact on the program/erase operations and retention of TaN/Al2O3/Si3N4/SiO2/Si (TANOS) memory devices. For this purpose, we perform simulations using a physical model that reproduces the charge injection/trapping in TANOS devices, which is extended in order to account for the charge trapping phenomena in the blocking layer. We derive the electrical characteristics of both electron and hole traps in Al2O3 by reproducing the measured program, erase, and retention transients. Our results show that the amount of electron charge trapped in the alumina during a program operation strongly depends on the stack composition and program voltages and can account for up to 25% of the total threshold voltage shift, whereas hole trapping during erase is negligible. Finally, we investigate the degradation of retention caused by the electron trapping in the alumina blocking layer, which is shown to result in an accelerated charge loss.
Biexcitons in semiconductor quantum wires

We report on spectrally resolved four-wave mixing experiments on ${\mathrm{In}}_{x}{\mathrm{Ga}}_{1\ensuremath{-}x}\mathrm{A}\mathrm{s}/\mathrm{G}\mathrm{a}\mathrm{A}\mathrm{s}$ quantum wires for a wide range of lateral sizes. Due to the polarization dependence of the four-wave mixing signal, beats in the decay of the signal and an additional emission line in the four-wave mixing spectrum can be clearly attributed to biexcitons. We find that the biexciton binding energy depends on both the vertical and lateral dimensions of the wires. For quantum wires with a large vertical confinement we observe an enhancement of the binding energy of about 40% as compared to a two-dimensional reference sample whereas the biexciton binding energy is found to be wire width independent in wires with shallow vertical confinement.
Four dimensional N = 2 theories from six dimensions

By formulating the six dimensional (0 ; 2) superconformal field the- ory X [ j ] on a Riemann surface decorated with certain codimension two de- fects, a multitude of four dimensional N = 2 supersymmetric field theories can be constructed. In this dissertation, various aspects of this construc- tion are investigated in detail for j = A;D;E . This includes, in partic- ular, an exposition of the various partial descriptions of the codimension two defects that become available under dimensional reductions and the relationships between them. Also investigated is a particular observable of this class of four dimensional theories, namely the partition function on the four sphere and its relationship to correlation functions in a class of two di- mensional non-rational conformal field theories called Toda theories. It is pointed out that the scale factor that captures the Euler anomaly of the four dimensional theory has an interpretation in the two dimensional language, thereby adding one of the basic observables of the 4d theory to the 4d/2d dictionary