Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of machine symmetry on reduction of cogging torque in permanent-magnet brushless motors

We study two methods to reduce cogging torque, both based on the analysis of the rotational symmetry in a brushless permanent-magnet motor. The first one seeks to lower the symmetry in the flux of a conventional motor with asymmetrical magnet distribution. The second one uses auxiliary slots to increase the frequency of the cogging. Analytical calculations have been made to predict the harmonic spectra of the models. Numerical calculations by the finite-element method were carried out. The results support the analytical conclusions. The frequency of the torque pulsation was increased, as predicted. We obtain a peak-to-peak cogging torque reduction of about 85% for each of the two methods. Dynamical calculations show no changes in the mean torque produced. The asymmetrical motor could introduce some ripple due to the EMF shifting.
On Modeling and Estimation of Response Probabilities When Missing Data are Not Missing at Random October 2010

Most methods that deal with the estimation of response probabilities assume either explicitly or implicitly that the missing data are ‘missing at random’ (MAR). However, in many practical situations this assumption is not valid, since the probability of responding often depends on the outcome value or on latent variables related to the outcome. The case where the missing data are not MAR (NMAR) can be treated by postulating a parametric model for the distribution of the outcomes under full response and a model for the response probabilities. The two models define a parametric model for the joint distribution of the outcome and the response indicator, and therefore the parameters of this model can be estimated by maximization of the likelihood corresponding to this distribution. Modeling the distribution of the outcomes under full response, however, can be problematic since no data are available from this distribution. Sverchkov (2008) proposed two approaches that permit estimating the parameters of the model for the response probabilities without modelling the distribution of the outcomes under full response. The approaches utilize relationships between the population, the sample and the sample-complement distribution derived in Pfeffermann and Sverchkov (1999) and Sverchkov and Pfeffermann (2004). The present paper extends one of these approaches.
Structural Characteristics of Convective Systems over South America Related to Cold-Frontal Incursions

Abstract International Satellite Cloud Climatology Project (ISCCP DX) and microwave sensor data collected by the Tropical Rainfall Measuring Mission (TRMM) are used to identify and describe structural characteristics of convective systems (CSs) over continental South America (SA) related to cold-frontal incursions in a 3-yr period. An austral wet-season climatology for CS events of the three most important types of front–tropical convection interaction is built by applying latitude–time diagrams and a cloud-tracking method to DX data. Type 1 is characterized by the penetration of a cold front over subtropical SA that interacts with convection and moves with it into lower tropical latitudes. Type 2 refers to Amazon convection and its enhancement in a quasi-stationary northwest–southeast-oriented band extending from the Amazon to subtropical SA along with the passage of a cold front in the subtropics and characterizes the synoptic formation of the South Atlantic convergence zone. A quasi-stationary cold fro.
A Crank-Nicolson Method of Autocatalytic Reaction-Diffusion Systems

In this paper we used two numerical methods to investigate propagating heat solutions of PDEs. The explicit and Crank-Nicolson methods and the results show that Crank-Nicolson method is more accurate than the explicit method. As an illustration, we used the above method to an autocatalytic reaction diffusion equations involving two diffusing chemicals in one dimension.
Classification of the nonlinear dynamics in an initially curved bistable micro/nano-electro-mechanical system resonator

The nonlinear dynamics of a bistable micro/nano-electro-mechanical system resonator composed of an arch-shaped microbeam is investigated. The initially curved microbeam is actuated through a combined DC and AC electrostatic parallel plate field. A single degree of freedom model obtained using the Galerkin's decomposition method with distributed electrostatic force is implemented in order to investigate the resonator dynamics near its primary resonance. According to the shape of the potential energy function which depends on the system parameters, the nonlinear dynamics of the system are classified into certain categories. The appearance of various nonlinear phenomena including dynamic snap-through, dynamic pull-in, chaotic or large amplitude vibrations, hysteresis and softening-type behaviours are discussed within the introduced categories. A typical case scrutinised on detail, showing consequent snap-through instabilities which are responsible for transitions between the present stable configurations of the arch-shaped microbeam. Details of the resulting hysteresis loop governing these transitions are discussed. Moreover, discussion is provided about the formation of the hysteresis loops which can affect the filtering functionality of the proposed bistable MEMS resonator.
Satellite Measurement of Stratospheric Winds and Ozone Using Doppler Michelson Interferometry. Part I: Instrument Model and Measurement Simulation

Abstract This paper presents an instrument model and observation simulations for the measurement of stratospheric winds and ozone concentration using a satellite instrument employing imaging and the Doppler Michelson interferometery technique. The measurement technique and instrument concept are described. The instrument model and simulations are based on initial design characteristics of the Canadian Stratospheric Wind Interferometer for Transport Studies (SWIFT) satellite instrument. SWIFT employs an imaging array and a field-widened Michelson interferometer. It will measure stratospheric winds and ozone densities using the wind-induced phase shifts of interferograms from atmospheric limb radiance spectra in the vicinity of the vibration–rotation ozone line at 1133.4335 cm−1. The measurement simulation and analysis tools have been developed to assess the SWIFT instrument performance and to evaluate the impact of instrument and measurement characteristics on expected wind and ozone errors. Sample results.
Hydrodynamic diffusion of sedimenting point particles in a vertical shear flow

Abstract The hydrodynamic diffusion of sedimenting point particles in a vertically sheared periodic system is investigated numerically and theoretically. In both the velocity-gradient direction and the vorticity direction, the rate of hydrodynamic diffusion is reduced as the shear rate is increased. In the velocity-gradient direction, two-particle interactions cause no net displacement, and three-particle interactions are necessary for diffusive behaviour. In contrast to an unsheared system, the resulting diffusion coefficient is only weakly dependent upon the size of the system and ${\widehat{D}}_{xx} \sim 4. 2\times 1{0}^{- 4} \hspace{0.167em} {n}^{2} {(f/ \mu )}^{4} {\dot {\gamma } }^{- 3} \ln (0. 42\widehat{L}{(\mu \dot {\gamma } / f)}^{1/ 2} )$ , where $n$ is the particle number density, $f$ the force per particle, $\mu $ the fluid viscosity, $\dot {\gamma } $ the imposed shear rate, and $\widehat{L}$ the system size. In the vorticity direction, although individual two-particle interactions cause no net displacement, a superposition of interactions is sufficient to cause diffusion-like linear growth of the ensemble-averaged square particle displacements. The associated diffusion coefficient is given by ${\widehat{D}}_{yy} \sim 9. 47\times 1{0}^{- 4} \hspace{0.167em} n{(f/ \mu )}^{2} \widehat{L}\hspace{0.167em} {\dot {\gamma } }^{- 1} $ . At sufficiently long times, the effect of multi-particle interactions cannot be neglected and there is a transition to another regime in which the diffusion coefficient is similar in form, but slightly reduced from this value. The dependence of ${\widehat{D}}_{xx} $ and ${\widehat{D}}_{yy} $ on the number density and dimensionless shear rate is explained using theoretical scaling arguments and analyses.
The Benefits and Costs of Transparent Supervision of Public Banks: Evidence from Disclosure of SEC Comment Letters

Using the SEC’s 2004 decision to begin publicly disclosing its comment letters, we study the consequences of increased regulatory transparency on the banking industry. Exploiting the fact that the SEC only issues comment letters to public banks, we adopt a difference-in-differences design, and begin by demonstrating that, compared to private banks, public banks improve the timeliness of their loan provisions. However, the effects of enhanced regulatory transparency on banks’ lending activities are mixed. On the one hand, increased transparency slows loan growth and exacerbates procyclical lending for public banks. On the other hand, transparency encourages public banks to shift credit towards safer borrowers. Further analyses shed light on the mechanisms underlying these shifts. Public banks receiving CLs in the public-disclosure period experience an increase in funding costs and intensified regulatory scrutiny from other bank regulators. Taken together, the results highlight the duality of regulatory transparency for the banking industry.
A 20-Gene Signature Predicting Survival in Patients with Clear Cell Renal Cell Carcinoma Based on Basement Membrane

Objectives The most common subtype of renal cell carcinoma, clear cell renal cell carcinoma (ccRCC), has a high heterogeneity and aggressive nature. The basement membrane (BM) is known to play a vital role in tumor metastasis. BM-related genes remain untested in ccRCC, however, in terms of their prognostic significance. Methods BM-related genes were gleaned from the most recent cutting-edge research. The RNA-seq and clinical data of the ccRCC were obtained from TCGA and GEO databases, respectively. The multigene signature was constructed using the univariate Cox regression and the LASSO regression algorithm. Then, clinical features and prognostic signatures were combined to form a nomogram to predict individual survival probabilities. Using functional enrichment analysis and immune-correlation analysis, we investigated potential enrichment pathways and immunological characteristics associated with BM-related-gene signature. Results In this study, we built a model of 20 BM-related genes and classified them as high-risk or low-risk, with each having its anticipated risk profile. Patients in the high-risk group showed significantly reduced OS compared with patients in the low-risk group in the TCGA cohort, as was confirmed by the testing dataset. Functional analysis showed that the BM-based model was linked to cell-substrate adhesion and tumor-related signaling pathways. Comparative analysis of immune cell infiltration degrees and immune checkpoints reveals a central role for BM-related genes in controlling the interplay between the immune interaction and the tumor microenvironment of ccRCC. Conclusions We combined clinical characteristics known to predict the prognosis of ccRCC patients to create a gene signature associated with BM. Our findings may also be useful for forecasting how well immunotherapies would work against ccRCC. Targeting BM may be a therapeutic alternative for ccRCC, but the underlying mechanism still needs further exploration.
Intrinsic competition between 2 pupal parasitoids of Drosophila suzukii (Diptera: Drosophilidae)

The parasitoids Pachycrepoideus vindemmiae Rondani (Hymenoptera: Pteromalidae) and Trichopria anastrephae Costa Lima (Hymenoptera: Diapriidae) have great potential in controlling Drosophila suzukii (Matsumura); however, both, compete for the same resources. In this study, we evaluated whether the different stages of development of the primary parasitoid reduce the negative effect of intrinsic competition. For this, we first defined the duration of each immature stage of both parasitoid species and then offered D. suzukii pupae containing the first parasitoid (P. vindemmiae or T. anastrephae) at different stages of development to the second parasitoid (P. vindemmiae or T. anastrephae). We also checked the second parasitoid's preference (P. vindemmiae or T. anastrephae) for the primary parasitoid at different stages of development (P. vindemmiae or T. anastrephae) or D. suzukii pupae nonparasitized. Our evaluations showed that T. anastrephae preferred to parasitize pupae that were not previously parasitized and that had not parasitized puparia of D. suzukii when P. vindemmiae was in later stage to the 1st instar. However, P. vindemmiae preferred to parasitize pupae previously parasitized by T. anastrephae. In an environment of intrinsic competition, the first parasitoid to parasitize has an advantage, except when the pupal stage of T. anastrephae is parasitized by P. vindemmiae. The variation in the parasitoids' oviposition time mitigates the competition effect; however, for use in biological control programs, the hyperparasitoids P. vindemmiae, does not prove to be advantageous, as they can affect the establishment of primary parasitoids such as T. anastrephae, and can act as competitors for resources.
ImageDroid: Using Deep Learning to Efficiently Detect Android Malware and Automatically Mark Malicious Features

The popularity of the Android platform has led to an explosion in malware. The current research on Android malware mainly focuses on malware detection or malware family classification. These studies need to extract a large number of features, which consumes a lot of manpower and material resources. Moreover, some malware use obfuscation to evade decompiler tools extracting features. To address these problems, we propose ImageDroid, a method based on the image format of Android applications that can not only detect and classify malware without prior knowledge but also detect the obfuscated malware. Furthermore, we utilize the Grad-CAM interpretable mechanism of the deep learning model to automatically label the image that play a key role in determining maliciousness in a visual way. We evaluate ImageDroid over 10,000 Android applications. Experimental results show that the accuracy of malicious detection and multifamily classification achieve 97.2% and 95.1%, respectively, and the detection accuracy of obfuscated malware achieves 94.6%.
Extrema-based Anisotropic Diffusion for Multi-scale Edge-preserving Image Decomposition ⋆

We present a new algorithm for decomposing an image based on the modified anisotropic diffusion equation. Inspired by edge-preserving-smoothing technique and the relationship between bilateral filtering and the nonlinear diffusion equation, we use the local extrema and gradient of the input image to extract information detailly. Basing on the key assumption that the spatial detail are characterized by the density of local extrema and the norm of gradient, we develop a method for decomposing images into base layer which records the salient edge of the image, and detail layer which records the fine scale texture. The experimental results demonstrate the effective of the proposed filter in application of the high-dynamic-range images display when compared with existing edge-preserving filter algorithms.
Bridging Performance and Adaptive Landscapes to Understand Long-Term Functional Evolution

Understanding functional adaptation demands an integrative framework that captures the complex interactions between form, function, ecology, and evolutionary processes. In this review, we discuss how to integrate the following two distinct approaches to better understand functional evolution: (1) the adaptive landscape approach (ALA), aimed at finding adaptive peaks for different ecologies, and (2) the performance landscape approach (PLA), aimed at finding performance peaks for different ecologies. We focus on the Ornstein-Uhlenbeck process as the evolutionary model for the ALA and on biomechanical modeling to estimate performance for the PLA. Whereas both the ALA and the PLA have each given insight into functional adaptation, separately they cannot address how much performance contributes to fitness or whether evolutionary constraints have played a role in form-function evolution. We show that merging these approaches leads to a deeper understanding of these issues. By comparing the locations of performance and adaptive peaks, we can infer how much performance contributes to fitness in species’ current environments. By testing for the relevance of history on phenotypic variation, we can infer the influence of past selection and constraints on functional adaptation. We apply this merged framework in a case study of turtle shell evolution and explain how to interpret different possible outcomes. Even though such outcomes can be quite complex, they represent the multifaceted relations among function, fitness, and constraints.
Application of RADAR technology to aerial LIDAR systems for enhancement of shallow underwater target detection

Since microwaves do not penetrate water, RADAR, the principal tool for remote sensing of the earth and atmosphere, cannot be used directly for the detection of underwater objects. Currently, aerial light detecting and ranging (LIDAR) systems are therefore preferred for the detection and ranging of objects submerged in the sea. LIDAR provides for large area coverage at high speed, but it lacks coherent detection capability, a shortcoming that severely limits system sensitivity and underwater target contrast. In response to this problem, this paper details the merging of RADAR and LIDAR technologies in the constitution of a hybrid LIDAR-RADAR detection scheme. This new sensor configuration has reduced incoherent backscatter clutter by 17 dB in laboratory experiments and related computer simulations. >
Optimizing the WSR-88D Mesocyclone/Tornadic Vortex Signature Algorithm Using WATADS—A Case Study*

Abstract A tornado outbreak occurred in east-central Minnesota around 0000 UTC 22 July 1995, within 80 km of the KMPX WSR-88D, at the Minneapolis–Chanhassen Weather Service Forecast Office (WSFO). The WSR-88D Mesocyclone/Tornadic Vortex Signature algorithm (MTA) identified only two Tornadic Vortex Signatures (TVSs) out of 14 confirmed tornadoes. A detailed examination of Doppler velocity products revealed operator-defined TVSs, intense gate-to-gate azimuthal shear, in 10 of the 14 storms. This outbreak presented an opportunity to optimize MTA performance because the algorithm performed poorly and the KMPX radar sampled many weak tornadoes at close range. Numerous combinations of two adaptable parameters, threshold pattern vector (TPV) and threshold TVS shear (TTS), were systematically tested using the WSR-88D Algorithm Testing and Display System (WATADS) and archive level II data. MTA’s performance improved significantly when default values were optimized. The number of tornadoes detected increased from t.
Existence of global weak solution for boundary value problems for compressible fluid models with nonlocal capillary tensor

This work is devoted to proving the global existence of a weak solution for a general isothermal model of capillary fluids, which can be used as a phase transition model. Using results of Lions in [20] on the compressible Navier-Stokes system we show the global stability of weak solutions for an initial-boundary-value problem with isentropic pressure and generaliued pressure. To illustrate the analysis a number of numerical experiments on rising bubbles in a closed container are displayed.
Quantum computingwithout entang lement

It is generally believed that entanglement is essential for quantum computing. We present here a few simple examples in which quantum computing without entanglement is better than anythingclassically achievable, in terms of the reliability of the outcome after a 0xed number of oracle calls. Usinga separable (that is, unentang led) state, we show that the Deutsch–Jozsa problem and the Simon problem can be solved more reliably by a quantum computer than by the best possible classical algorithm, even probabilistic. We conclude that: (a) entanglement is not essential for quantum computing; and (b) some advantage of quantum algorithms over classical algorithms persists even when the quantum state contains an arbitrarily small amount of information—that is, even when the state is arbitrarily close to beingtotally mixed. c 2004 Elsevier B.V. All rights reserved.
Mass-Flux Characteristics of Tropical Cumulus Clouds from Wind Profiler Observations at Darwin, Australia

AbstractCumulus parameterizations in weather and climate models frequently apply mass-flux schemes in their description of tropical convection. Mass flux constitutes the product of the fractional area covered by convection in a model grid box and the vertical velocity in cumulus clouds. However, vertical velocities are difficult to observe on GCM scales, making the evaluation of mass-flux schemes difficult. Here, the authors combine high-temporal-resolution observations of in-cloud vertical velocities derived from a pair of wind profilers over two wet seasons at Darwin with physical properties of precipitating clouds [cloud-top heights (CTH), convective–stratiform classification] derived from the Darwin C-band polarimetric radar to provide estimates of cumulus mass flux and its constituents. The length of this dataset allows for investigations of the contributions from different cumulus cloud types—namely, congestus, deep, and overshooting convection—to the overall mass flux and of the influence of large-.
Live Load Multiple Presence Factors for Design and Evaluation of Short-to-Medium Span Highway Bridges

The critical live loads in bridge design or evaluation could be caused by either a single vehicle event or simultaneous occurrence of two or more vehicles, which is usually called a “multiple presence event. ” The multiple presence factors (MPFs) are then defined to assess the live load effects from single and multiple presence events. The MPFs from the American Association of State Highway and Transportation Officials Load and Resistance Factor Design (AASHTO LRFD) were derived three decades ago, by assuming the probability of multiple presence events based on field observation. In addition, the correlation among truck loads in multiple presence events needs further evaluation based on actual data, as previous studies have assumed either fully correlated or independence across the lanes. There is an imperative need to re-evaluate the MPFs based on the available weight-in-motion data. This paper derives the MPFs for bridge live loads based on both traffic simulation and probabilistic modeling, utilizing existing weigh-in-motion data. It is found that the MPFs are affected by two major factors: truck loads and probability of multiple presence events. Truck loads can be further defined as the mean and standard deviation of loads on each lane, and the covariance of the load effects across the lanes. The probability of multiple presence events is related to average daily truck traffic, and the distribution of the traffic. The dispersion of truck volume and covariance of load effects across the lanes shows significant impact on the MPFs. Statistics of MPFs are obtained and recommendations to AASHTO LRFD are provided for 2-lane and 3-lane MPFs.