Miracle-dz/UniFAR-FTUs huggingface dataset:
Noise gain and operating temperature of quantum well infrared photodetectors

The difference between the noise gain associated with dark current and the photoconductive gain in quantum well infrared photodetectors is discussed in light of recent experiments. The theoretical model is based on a single key parameter: the electron trapping probability. An empirical expression for the trapping probability or, alternatively, the electron escape probability is proposed. Using the dark current, the gain, the trapping probability expressions, and the device operating temperature for achieving background limited infrared performance is discussed.
Mixed‐interpolated elements for thin shells

The subject of this work is the construction of some special finite elements for the numerical solution of Naghdi cylindrical shell problems. The standard numerical approximation of the shell problem is subjected to the shear and membrane locking phenomenon, i.e. the numerical solution degenerates for low thickness. The most common way to avoid locking is the use of modified bilinear forms to describe the shear and membrane energy of the shell. In this paper we build a family of special finite elements that still follow the above strategy by introducing a linear operator that reduces the influence both of the shear and membrane energy terms. The main idea comes from the non-standard mixed interpolated tensorial components (MITC) formulation for Reissner-Mindlin plates. The performance of the new elements is then tested for solving benchmark problems involving very thin shells. The results show both the properties of convergence and robustness.
Phenotypic diversity within yam (Dioscorea spp.) germplasm collection in Uganda

A deeper understanding of the morphology of available germplasm is an indispensable initial step for yam genetic improvement and enhanced production in Uganda. However, there is limited information in Uganda on the diversity of yam. The objective of this study was to characterize the diversity of yam cultivars farmers have utilized for decades in Uganda together with germplasm recently introduced from West Africa using phenotypic traits. A germplasm collection of 291 genotypes was characterized based on 28 phenotypic variables. The phenotypic traits data were subjected to multivariate analysis using principal component analysis (PCA) and cluster analysis. Phenotypic traits assessed were informative and discriminating, with 62% of total variation explained among the �rst six principal components. Our results showed that the important phenotypic traits contributing to most of the variability among the genotypes were leaf characteristics, �owering characteristics, and tuber traits. In general, most genotypes collected within Uganda were identi�ed with amorphous tuber shapes compared to material sourced from West Africa. Dendrogram generated using “ward” hierarchical clustering revealed two major clusters with few of the genotypes sharing similarities. The study has shown that there is ample phenotypic variability within the major yam genotypes in Uganda yam germplasm that can be used for genetic improvement. The results are also useful with regard to the identi�cation and conservation of elite genotypes for future genetic improvement of yam in Uganda. More in-depth molecular and biochemical studies to further understand the diversity are recommended.
Energy-Efficient 360-Degree Video Streaming on Multicore-Based Mobile Devices

360° video streaming becomes increasingly popular on video platforms. However, streaming (downloading and processing) 360° video consumes a large amount of energy on mobile devices, but little work has been done to address this problem, especially considering recent advances in the mobile architecture. Through real measurements, we found that existing systems activate all processor cores during video streaming, which consumes a great deal of energy, but this is unnecessary since most heavy computations in 360° video processing are handled by the hardware accelerators such as hardware decoder, GPU, etc. To save energy, we propose to selectively activate the proper processor cluster and adaptively adjust the CPU frequency based on the video quality. We model the impacts of video resolution and CPU frequency on power consumption, and model the impacts of video features and network effects on Quality of Experience (QoE). With the developed models, we formulate the energy and QoE aware 360° video streaming problem as an optimization problem with the goal of maximizing QoE and minimizing energy. We then propose an efficient algorithm to solve this optimization problem. Evaluation results demonstrate that the proposed algorithm can significantly reduce the energy consumption while maintaining QoE.
Boundary extraction of moving objects from image sequence

In this paper we address a new approach of contour extraction of moving objects using active contours in an image sequence. Both the spatial convolution process and the external boundary tracing algorithm (EBTA) are used to resolve the problem of automatically locating the initial contour for the external boundaries of an object in the image. Ongoing directions where the contour moves are decided by one of three directions instead of eight directions. We could reduce the time complexity of the energy minimizing operation of the contour by considering only three ongoing directions. In order to apply the proposed algorithm to consecutive imagery, a Kalman filter, an optimal parameter estimator, is adopted. The algorithm extracts the contour of an object from only two consecutive images and takes 0.36 seconds of CPU time.
A generalization of Griffiths's theorem on rational integrals

We generalize Griffiths' theorem on the Hodge filtration of the primitive cohomology of a smooth projective hypersurface, using the local Bernstein-Sato polynomials, the V-filtration of Kashiwara and Malgrange along the hypersurface and the Brieskorn module of the global defining equation of the hypersurface.
Two Graphical Techniques Useful in Detecting Correlation Structure in Repeated Measures Data

Abstract Analysis of repeated measures data using a mixed model includes specifying a form for the covariance matrix of the within-subject observations. This reduction in the number of estimated parameters from the unspecified structure may improve the efficiency of inferences made. An implementation of this technique has been incorporated in the MIXED procedure of the SAS® statistical package, and includes a wide range of options for the structure of the covariance matrix. It is demonstrated that draftman's display plots and/or plots in a coordinate system with parallel axes can aid in visualizing the dispersion structure.
Finite difference time domain simulation of soil ionization in grounding systems under lightning surge conditions

This paper proposes a Maxwell’s equations finite difference time domain (FDTD) approach for electromagnetic transients in ground electrodes in order to take into account the non linear effects due to soil ionization. A time variable soil resistivity method is used in order to simulate the soil breakdown, without the formulation of an initial hypothesis about the geometrical shape of the ionized zone around the electrodes. The model has been validated by comparing the computed results with available data found in technical literature referred to concentrated earths. Some application examples referred to complex grounding systems are reported to show the computational capability of the proposed model.
Piston Motion Performance Analysis of a 3DOF Electrothermal MEMS Scanner for Medical Applications

MEMS scanners are useful for medical applications as optical coherence tomography and laser microsurgery. Although widespread design of MEMS scanners have been presented, their behavior is not well known, and thus, their motions are not easily and efficiently controlled. This deficiency induces several difficulties (limited resolution, accuracy, cycle time, etc.), and to tackle this problem, this article presents the modeling of an ISC electrothermally actuated MEMS mirror and the experimental characterization for the piston motion. Modeling and characterization are important to implement the control. A multiphysic model is proposed, and an experimental validation is performed with a good correspondence for a voltage range from 0 V to 3.5 V with a maximum displacement up to 200 µm and with a relative tilting difference of 0.1°. The article also presents a simple and efficient experimental setup to measure a displacement in dynamic and static mode, or a mirror plane tilting in static mode.
Destruction mechanism of ZnO varistors due to high currents

The destruction process of ZnO varistors caused by high currents is described. When high currents were applied to ZnO varistors, two kinds of destruction modes were found: a cracking mode and a puncture mode. The puncture mode is caused by melting of the region where current concentrates. The puncture process was simulated by a computer, solving a set of heat transfer equations. The relationships among the destruction energy, uniformity of the sintered body and nonohmic I‐V characteristics were obtained. The simulated results are consistent with the experimental results and show that the destruction energy depends strongly on the uniformity.
An experimental study of anharmonic micromachined silicon resonators

The use of resonant sensors with high mechanical Q factors is based on a vibrating element acting as a harmonic oscillator. The existence and consequence of non-linearity, for some special resonant structures and above critical values, are not often taken into account. For experiments in which the mechanical deflection gives basically the physical information, a lack of knowledge of possible non-linearity may have dramatic consequences for the exploitation of the results. Different free-standing silicon resonators have been micromachined and an experimental device to test the dynamical properties of these structures has been designed. The resonant structures were electrostatically excited in flexural mode. The results have revealed a spectacular non-linear behaviour of the thin films at ambient temperature. It is well established that this anharmonic behaviour is linked to the mechanical properties of these resonators rather than to the electrostatic excitation. The experiments have revealed three different types of non-linear behaviour. These experimental results are presented and analysed starting from the non-linear differential equation.
Random multiplicative processes: An elementary tutorial

An elementary discussion of the statistical properties of the product of N independent random variables is given. The motivation is to emphasize the essential differences between the asymptotic N→∞ behavior of a random product and the asymptotic behavior of a sum of random variables—a random additive process. For this latter process, it is widely appreciated that the asymptotic behavior of the sum and its distribution is provided by the central limit theorem. However, no such universal principle exists for a random multiplicative process. In this case, the ratio between the average value of the product 〈P〉 and the most probable value Pmp diverges exponentially in N as N→∞. Within a continuum approximation, the classical log‐normal form is often invoked to describe the distribution of the product. It is shown, however, that the log‐normal provides a poor approximation for the asymptotic behavior of the average value and, also, for the higher moments of the product. A procedure for computing the correct lea.
A Particle Swarm Runge-Kutta Optimization Algorithm for Solving the BVP of Ordinary Differential Equation ⋆

We transform the boundary value problem of ordinary differential equation into an unconstrained optimization problem. To find an effective algorithm for that problem, we incorporate the Runge-Kutta (R-K) method into the Particle Swarm Optimization algorithm (PSO) and construct a new PSO based R-K method. We use several famous boundary value problem to testify the efficiency of the proposed algorithm. The computational results show that the proposed new method is quite promising.
Two-Group Comparisons and Univariate Classification

An alternative analysis of the traditional two-group single response variable design is discussed. The proposed analysis involves the classification, or assignment, of experimental units to populations represented by the two groups. Methods of estimating probabilities of correct classification are discussed. Three real data sets are provided to illustrate the utility of a classification analysis in describing both group as well as individual differences. A table of sample sizes required to yield estimates of probabilities of correct classification within a given tolerance of optimum probabilities is presented. Operational definitions of "substantive significance" are proposed.
Directed-bond percolation on hypercubic lattices

The directed d-weight method is used to obtain the expansion of the mean-size series, S(p), for the simple acyclic hypercubic lattices, to order p9. The following expansion is also derived: pc(d)=1/d+1/2d3+1/d4+3/d5+21/2d6+479/12d7+O(d-8).
Multiple Comparisons in Microarray Data Analysis

Multiplicity is a challenging statistical issue in drug discovery, and a particular example is microarray study. The traditional approach of controlling of the family-wise error rate (FWER) is conservative when the number of tests is large. A more appropriate approach is to control the false discovery rate (FDR). Since the development of the Benjamini and Hochberg (BH) FDR procedure in 1995, many modifications have been proposed aimed at relaxing the requirement for independent test statistics or improving the power of the BH FDR procedure. Comparisons of these procedures in the current literature are not comprehensive and the conclusions on performances are inconsistent. The objectives of this article are three-fold: (a) to perform a more comprehensive comparison of extant multiple testing procedures using two real microarray datasets and various simulated data sets; (b) to explore potential reasons for the inconsistencies in published simulation results; and (c) to identify suitable FDR procedures under different scenarios according to covariance structure, percent of true null hypotheses among multiple tests, and sample size.
Verification of Newton approach method to gain better significant results for the transformation problem

Abstract In this article, we emphasize the application of Box-Cox and the Alternative method of transformation to the different type of case. The assumptions of Analisis of Variance (ANOVA) are met after the passing through the both method and the reliability of the results is given by the value of Anderson Darling (AD) statistical test. The MINITAB software is used in order to get the plot of the residual and the significance results of the normality could be compared from the gaining residual results.
Discovery of Single Independent Latent Variable

Latent variable discovery is a central problem in data analysis with a broad range of applications in applied science. In this work, we consider data given as an invertible mixture of two statistically independent components and assume that one of the components is observed while the other is hidden. Our goal is to recover the hidden component. For this purpose, we propose an autoencoder equipped with a discriminator. Unlike the standard nonlinear ICA problem, which was shown to be non-identifiable, in the special case of ICA we consider here, we show that our approach can recover the component of interest up to entropy-preserving transformation. We demonstrate the performance of the proposed approach in several tasks, including image synthesis, voice cloning, and fetal ECG extraction.
Various dark hollow beams propagating in uniaxial crystals orthogonal to the optical axis

The propagation of dark hollow beams with circular, elliptical and rectangular symmetries in uniaxial crystals orthogonal to the optical axis is investigated. Analytical formulae for various dark hollow beams propagating in uniaxial crystals orthogonal to the optical axis are derived, and the propagation properties of various dark hollow beams are studied in detail. We find that the dark hollow beam of circular or non-circular symmetry will spread in the xy plane with the increase in propagation distance, and various hollow beams can keep their initial beam profile almost invariant for a short propagation distance in uniaxial crystals.
Machine learning for patent intelligence

Digitalization is a strong driver in society, business, and science. Patent management, especially the search for and analysis of patents, is also being shaped by digitalization advances. Unlike prior studies – which mainly focus on the purposes and methods used for patent search and analysis –, this review focuses on the underlying digitalization trends that have become mainstream in the landscape of providers’ patent information databases and interrogation tools. By analyzing seven public and 20 commercial providers, a total of 15 different digitalization trends are outlined. Public providers specifically focus on trends for patent search, e.g. machine translation, while commercial providers rather focus on more sophisticated trends for patent analysis, e.g. predictive analytics. All of the 15 identified trends point toward four digitalization domains that were discerned by means of a hybrid coding approach, namely cloud computer technology, data management, data analytics, and artificial intelligence. Conclusively, tensions that are caused by the progress of these trends are discussed, e.g. the seamless transition from search to analysis versus less explainability.
An edge-based scale- and affine-invariant algorithm for remote sensing image registration

For remote sensing image registration, we find that affine transformation is suitable to describe the mapping between images. Based on the scale-invariant feature transform (SIFT), affine-SIFT (ASIFT) is capable of detecting and matching scale- and affine-invariant features. Unlike the blob feature detected in SIFT and ASIFT, a scale-invariant edge-based matching operator is employed in our new method. To find the local features, we first extract edges with a multi-scale edge detector, then the distinctive features (we call these ‘feature from edge’ or FFE) with computed scale are detected, and finally a new matching scheme is introduced for image registration. The algorithm incorporates principal component analysis (PCA) to ease the computational burden, and its affine invariance is embedded by discrete sampling as ASIFT. We present our analysis based on multi-sensor, multi-temporal, and different viewpoint images. The operator shows the potential to become a robust alternative for point-feature-based registration of remote-sensing images as subpixel registration consistency is achieved. We also show that using the proposed edge-based scale- and affine-invariant algorithm (EBSA) results in a significant speedup and fewer false matching pairs compared to the original ASIFT operator.
Case Studies on Ground-Fault Protection of Microgrid Power Systems With Diverse Power Sources

In this paper, we share the experiences of designing, installing, and commissioning grounding and ground fault protection systems for three different low-voltage and medium-voltage power systems. The first project is a low-voltage service entrance with a standby generator. The second is a large peak shaving battery and a photovoltaic (PV) power plant that must seamlessly island and reconnect to the transmission grid without loss of power to customers. The third is a transportable microgrid with a grid forming with droop battery inverter and synchronous condenser with a flywheel. Complicating these designs are the great diversity in 480 V power system designs, the limitations of inverters, and the need to comply with National Electric Code (NEC). NEC compliance and good engineering practices are explained. The logic behind each design is shared, and a checklist is provided to guide others in proper design practices. The solutions shared are shown to be simple, easily maintained, reliable, NEC-compliant, fully monitored, and ready for the rapidly changing power system of the future.
Spatiotemporal evolution of aeolian dust in China: An insight into the synoptic records of 1984–2020 and nationwide practices to combat desertification

Aeolian dust is closely related to land degradation, desertification, and sand and dust storm weather, and is a significant factor influencing the Earth's biogeochemical cycles. Here we present an investigation of the recent synoptic features of atmospheric dust in China and analyze its spatiotemporal change based upon meteorological observation data and satellite products. It shows that aeolian dust frequency in China has decreased gradually from 1984 to 2020. The outbreak frequency of dust storms declined significantly by 97.7%, followed by severe dust storm, dust in suspension, and blowing dust with 88.8%, 75%, and 64.3% reduction, respectively. The main dust sources influencing China are the Mongolian Gobi Desert, the Taklimakan Desert, the Hexi Corridor, the Alxa Plateau Desert, the Qaidam basin Desert, and the northeast‐southwest stretching semiarid farming‐pasture ecotone. Atlantic multidecadal oscillation (AMO) and Pacific decadal oscillation (PDO) may play an important role in teleconnection with aeolian dust event occurrence in China. Their correlation coefficients are −0.6 and 0.37, respectively. For more than 40 years, China has made huge investments in ecological restoration projects, and enacted national policies and laws to mitigate desertification. Significant environmental improvement has consequently ensued in China in the early 21st century, and the aeolian dust events were reduced to a record minimum in 2020. In contrast to the growing nationwide greenness, China is now facing up to an incremental dust risk generated from extraterritorial source regions such as the Mongolian Gobi Desert and Central Asian desiccated salt lakes.
A semi-markov approach to stochastic compartmental models

In the past, various methods using either differential equations or differential-difference equations have been used to analyze stochastic compartmental models. In this paper a semi-Markov process approach is used to provide a framework for analyzing such models. The distribution function of the number of particles in each of the compartments is derived along with the stationary distributions. Various models found in the literature arising from biological and reliability applications are analyzed here using the semi-Markov process technique.
Multiquadric Radial Basis Function Method for Boundary Value and Free Vibration Problems

Radial basis function method is a generalized version of the multiquadric radial basis function method (MQRBF). It is considered an important tool for interpolating multidimensional scattered data. Its ability to handle arbitrarily scattered data, to easily generalize to several space dimensions, and to provide spectral accuracy have made it popular in various applications. In this paper development of the multi quadric radial basis function (MQRBF) has been discussed. Shape parameter plays important role, when MQRBF is applied to solve boundary value problems and it significantly affects the stability and accuracy. Value of the shape parameter decreases as number of data points increases. The effect of shape parameter is explained in details. Approaches for solving boundary value problems using multiquadric radial basis function have been mentioned.