Miracle-dz/UniFAR-FTUs huggingface dataset:
Regularized methods for hyperspectral image classification

In this paper, we analyze regularized non-linear methods in the context of hyperspectral image classification. For this purpose, we compare regularized radial basis function neural networks (Reg-RBFNN), standard support vector machines (SVM), and kernel Fisher discriminant (KFD) analysis both theoretically and experimentally. We focus on the accuracy of methods when working in noisy environments, high input dimension, and limited number of training samples. In addition, some other important issues are discussed, such as the sparsity of the solutions, the computational burden, and the capability of the methods to provide probabilistic outputs. Although in general all methods yielded satisfactory results, SVM revealed more effective than KFD and Reg-RBFNN in standard situations regarding accuracy, robustness, sparsity, and computational cost.
Computer Augmentation of Experimental Designs to Maximize |X'X

The main purpose of this paper is to demonstrate the usefulness of a simplex search procedure for the problem of augmenting a given experimental design to “optimize” it with respect to some criterion. In particular, the paper demonstrates the ability of the simplex search procedure to add m points simultaneously to an initial design in order to maximize |X′X| In the process, the paper presents a method for improving the Nelder-Mead simplex search procedure.
Modified Potato Starch as a Potential Retardant for Prolonged Release of Lidocaine Hydrochloride from Methylcellulose Hydrophilic Gel

The problem of drug delivery often concentrates on the prolongation of drug activity. Application of natural polymers which are biodegradable and inexpensive is in the interest of many researchers. The aim of this study was the application of newly synthesized starch derivatives as potential functional excipients proposed for hydrophilic gel with lidocaine hydrochloride (LH) to prolong drug release from the hydrogel matrix. In our study, we investigated the effect of starch modified with citric acid on the release kinetics of LH using UV-VIS and Fourier-transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), as well as viscosity and pH measurements. We demonstrated the effectiveness of citric-acid-modified starch in prolonging the release of LH from methylcellulose gel.
SYMBOLIC CONVEX ANALYSIS

Convex optimization is a branch of mathematics dealing with non-linear optimization problems with additional geometric structure. This area has been the focus of considerable research due to the fact that convex optimization problems are scalable and can be efficiently solved by interior-point methods. Over the last ten years or so, convex optimization has found applications in many new areas including control theory, signal processing, communications and networks, circuit design, data analysis and finance. As with any new problem, of key concern is visualization of the problem space in order to develop intuition. In this thesis we develop tools for the visualization of convex functions. An important operation in convex optimization is that of Fenchel conjugation. Earlier research has developed algorithms for the symbolic Fenchel conjugation in one dimension, or many separable dimensions. In this thesis these algorithms are extended to work in the non-separable many dimensional case.
A parallel algorithm for incremental orthogonalization based on the compact WY representation

We present a parallel algorithm for incremental orthogonalization, where the vectors to be orthogonalized are given one by one at each step. It is based on the compact WY representation and always produces vectors that are orthogonal to working accuracy. Moreover, it has large granularity and can be parallelized eﬃciently. When applied to the GMRES method, this algorithm reduces to a known algorithm by Walker. However, our formulation makes it possible to apply the algorithm to a wider class of incremental orthogonalization problems, as well as to analyze its accuracy theoretically. Numerical experiments demonstrate accuracy and scalability of the algorithm
Surface figure measurement of flat mirrors based on the subaperture stitching interferometry

Large flat mirrors can be characterized using a standard interferometer coupled with stitching the subaperture measurement data. Such systems can measure the global full map of the optical surface by minimizing the inconsistency of data in the adjacent regions. We present a stitching technique that makes use of a commercial phase-shifting Twyman- Green interferometer in combination with an iterative optimized stitching algorithm. The proposed method has been applied to determine the surface errors of planar mirrors with an accuracy of a few nanometers. Moreover, the effect of reference wavefront error is explored. The feasibility and the performance of the proposed system are also demonstrated, along with a detailed error analysis and experimental results.
Predicting and Analyzing X-Rays to Measure Propellant Crack Propagation Speed

Real-time radioscopy (RTR) of solid rocket motors has revealed information about the propellant burning and cracking. This theoretical study evaluated the viability of real-time radioscopy for measuring propellant crack propagation speed. The scope included the quantitative interpretation of crack tip velocity from simulated radiographic images of a burning, center-perforated motor. The simplified motor simulation portrayed a bore crack that moved radially at a speed that was 10 times the propellant burning rate. Comparing the image interpretation with the simulation input quantified the accuracy of the crack velocity measurement under favorable, first-order assumptions. The simulation included the effects of system configuration, finite spatial resolution (from video pixels), and (8-bit) intensity digitization. The image digitization and interpretation introduced a ±20% measurement uncertainty in the crack tip speed for the nominal condition. A ±10% uncertainty resulted from doubling the camera gain. Using curvefitting techniques, the result was a constant 2% bias in the crack tip velocity measurement. This best case analysis shows that RTR has the potential for making acceptable measurements under the conditions studied.
Interactions of bioactive trace metals in shipboard Southern Ocean incubation experiments

In the Southern Ocean, it is well‐known that iron (Fe) limits phytoplankton growth. Yet, other trace metals can also affect phytoplankton physiology. This study investigated feedbacks between phytoplankton growth and dissolved Fe, manganese (Mn), cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), and cadmium (Cd) concentrations in Southern Ocean shipboard incubations. Three experiments were conducted in September–October 2016 near the West Antarctic Peninsula: Incubations 1 and 3 offshore in the Antarctic Circumpolar Current, and Incubation 2 inshore in Bransfield Strait. Additions of Fe and/or vitamin B12 to inshore and offshore waters were employed and allowed assessment of metal (M) uptake relative to soluble reactive phosphorus (P) across a wide range of initial conditions. Offshore, treatments of >1 nmol L−1 added Fe were Fe‐replete, whereas inshore waters were already Fe‐replete. Results suggest Mn was a secondary limiting nutrient inshore and offshore. No Fe‐vitamin B12 colimitation was observed. Overall, M:P uptake in the incubations was closely related to initial dissolved M:P for Fe, Mn, Co, Ni, and Cd, and for Cu inshore. Final concentrations of Fe and Zn were similar across light treatments of the experiments despite very different phytoplankton responses, and we observed evidence for Co/Cd/Zn substitution and for recycling of biogenic metals as inventories plateaued. In dark bottles, the absence of Mn oxidation may have allowed more efficient recycling of Fe and other trace metals. Our results provide insight into factors governing trace metal uptake, with implications for phytoplankton community composition locally and preformed micronutrient bioavailability in Southern Ocean water masses.
Multistate degradation and supervised estimation methods for a condition-monitored device

Multistate reliability has received significant attention over the past decades, particularly its application to mechanical devices that degrade over time. This degradation can be represented by a multistate continuous-time stochastic process. This article considers a device with discrete multistate degradation, which is monitored by a condition monitoring indicator through an observation process. A general stochastic process called the nonhomogeneous continuous-time hidden semi-Markov process is employed to model the degradation and observation processes associated with this type of device. Then, supervised parametric and nonparametric estimation methods are developed to estimate the maximum likelihood estimators of the main characteristics of the model. Finally, the correctness and empirical consistency of the estimators are evaluated using a simulation-based numerical experiment.
Relational template-matching algorithm for FLIR automatic target recognition

Under the Army Night Vision & Electronic Sensors Directorate and the Army Research Laboratory (S3I) sponsored ATR Relational Template Matching (ARTM) program, we have developed a novel model-based forward-looking infrared (FLIR) automatic target recognition (ATR) algorithm with superior performance over other model-based and template matching algorithms. The ARTM algorithm represents a significant advance over other approaches because its performance is relatively insensitive to the extreme variations of target signatures in FLIR imagery. The algorithm has been extensively evaluated in Army-sponsored competitive tests on low-depression ground target scenarios. The ARTM algorithm correctly recognizes target signatures at less than one-half the signal-to-noise level required by other approaches. Also the algorithm performs consistently over signature variations with up to 30 percent shape error.
Sustainability competences in primary school education – a systematic literature review

Abstract Education for sustainable development is needed at all school levels. The aim of this systematic literature review is to increase knowledge on sustainability competences in the context of primary school education for sustainable development. The sustainability competences considered in this study are systems thinking competence, futures thinking competence, values thinking competence, collaboration competence and action-oriented competence. The systematic search was based on PRISMA guidelines, and it was conducted using following databases: ERIC, Scopus, Web of Science and the LUC Finna international e-materials database. The search yielded 14 of 93 articles. The research findings show that systems thinking competence and collaboration competence were the most common of the sustainability competences studied, followed by action-oriented competence and values thinking competence, leaving futures thinking competence less investigated. Furthermore, the findings show that the learning of sustainability competences is based on children’s dialogue and collaboration with other pupils and teachers using their imagination to achieve common environmental goals in their daily lives.
Three‐dimensional Fréchet differential kernels for seismicdelay times

Summary Seismic traveltimes are the most widely exploited data in seismology. Their Frechet or sensitivity kernels are important tools in tomographic inversions based on the Born or single-scattering approximation. The current study is motivated by a paradox posed by two seemingly irreconcilable observations in the numerical calculations for the sensitivity kernels of the traveltime perturbations. Calculations of kernels for 2-D media by the normal-mode approach indicate that traveltimes are most sensitive to the structure on and around the geometrical ray paths corresponding to the seismic arrivals, whereas calculations for 3-D media by geometrical ray theory predict exactly zero sensitivities on the ray paths. In the current work, we employ these two completely different wave-propagation approaches, the more efficient geometrical ray theory and the more accurate normal-mode theory, to investigate the 3-D sensitivities of the delay times to shear-wave speed variations. Expressions for the delay-time Frechet kernels are presented for both methods, and extensive numerical experiments are conducted for various types of seismic phases as well as for different reference earth models. The results show that the contradictory observations are but two examples of a wide range of behaviours in the delay-time sensitivity. For most of the seismic phases in realistic reference models with multiple discontinuities, wave-speed gradients and low-velocity zones, the wavefields are highly complicated and ray theory, which describes the response by the contributions of a few geometrical rays between the source and receiver, produces qualitatively different delay-time kernels from those obtained by the normal-mode theory, which includes essentially all contributions.
Dependence in the 2001 one‐number census project

Summary. The one‐number census approach was developed by the Office for National Statistics to adjust the counts from the 2001 census of England and Wales for underenumeration. The method is underpinned by an assumption of independence between the count of the population that was given by the 2001 census and the count that was given by the Census Coverage Survey. Some dependence was, however, detected, and the paper describes the strategy that was used to measure dependence and to adjust the 2001 census population estimates.
Test of Homogeneity for Some Population Models Based on Counting Processes

This work deals with hypothesis testing for some population models based on counting processes. An asymptotic hypothesis testing to find out certain homogeneity conditions about the parameters of these models is carried out. Some local alternatives are considered and these results are applied to prove homogeneity of the resistance level of susceptible individuals in a population which is subdivided into sub populations and is being attacked by an infectious disease.
Evolution of laser-fired aluminum-silicon contact geometry in photovoltaic devices

The evolution of temperature and velocity fields during laser processing of solar cells to produce an ohmic contact between an aluminum thin film and a silicon wafer is studied using a transient numerical heat transfer and liquid metal flow model. Since small changes in pulse duration, power, and power density can result in significant damage to the substrate and, in extreme cases, expulsion of droplets from the molten zone, the selection of optimal laser processing parameters is critical. The model considers the unusually large heat of fusion of the Al-Si alloy formed during processing and the large composition-dependent two phase region. The calculated size and shape of the fusion zone were in good agreement with the corresponding experimental data, indicating the validity of the model and providing a basis for using the model to develop a better understanding of the laser-assisted fabrication of contacts for solar cell devices. The transient changes in the composition of the Al-Si molten region are fou.
Pulsed-laser deposited Pb(Zr0.52,Ti0.48)O3-on-silicon resonators with high-stopband rejection using feed-through cancellation

A length extensional mode lead zirconate titanate (PZT)-on-Si resonator is presented using 50 Ω termination with high-stopband rejection exploiting feed-through cancellation. A 250-nm-thick (100)-dominant oriented PZT thin-film deposited on top of 3 μm Si using pulsed laser deposition has been used. The resonator is presented with the length of 40 μm (half-wavelength), which corresponds to a resonance frequency of about 83 MHz. The effect of feed-through cancellation has been studied to obtain high-stopband rejection using bottom electrode patterning in the presence of a specific grounding resistance. Using this technique, the stopband rejection can be improved by more than 20 dB.
REDUCTION PROBLEMS IN EXPERIMENTAL INVESTIGATIONS

Let be the result of measuring a signal that is not directly observable, where , and are Hilbert spaces, and is a random element of giving an error in the measurement of . Let be the class of Hilbert-Schmidt operators acting from to , and let be a vector-valued function on giving the quality of the instruments in in such a way that if the quality of is higher than that of . If , forms a solution of the minimum problem then is interpreted as the output signal, distorted by the noise , of an instrument which to within coincides with an instrument of guaranteed quality . The properties of the measurement reduction are studied, and questions of optimal design of measurements are considered.Figures: 2. Bibliography: 8 titles.
Causal Mediation Analysis for Multivariate Longitudinal Data and Survival Outcomes

Abstract This study proposes a joint modeling approach to conduct causal mediation analysis that accommodates multivariate longitudinal data, dynamic latent mediator, and survival outcome. First, we introduce a confirmatory factor analysis model to characterize a time-varying latent mediator through multivariate longitudinal observable variables. Then, we establish a growth curve model to describe the linear trajectory of the dynamic latent mediator and simultaneously explore the relationship between the exposure and the mediating process. Finally, we link the mediating process to the survival outcome through a proportional hazards model. In addition, we use the mediation formula approach to assess the natural direct and indirect effects and prove the identifiability of the causal effects under sequential ignorability assumptions. A Bayesian approach incorporating the Markov chain Monte Carlo algorithm is developed to estimate the causal effects efficiently. Simulation studies are conducted to evaluate the empirical performance of the proposed method. An application to the Alzheimer’s Disease Neuroimaging Initiative study further confirms the utility of the proposed method.
Predicting Convective Downdrafts From Updrafts and Environmental Conditions in a Global Storm Resolving Simulation

One important component of precipitating convection is the formation of convective downdrafts. They can terminate the initial updraft, affect the mean properties of the boundary layer, and cause strong winds at the surface. While the basic forcing mechanisms for downdrafts are well understood, it is difficult to formulate general relationships between updrafts, environmental conditions, and downdrafts. To better understand what controls different downdraft properties, we analyze downdrafts over tropical oceans in a global storm resolving simulation. Using a global model allows us to examine a large number of downdrafts under naturally varying environmental conditions. We analyze the various factors affecting downdrafts using three alternative methods. First, hierarchical clustering is used to examine the correlation between different downdraft, updraft, and environmental variables. Then, either random forests or multiple linear regression are used to estimate the relationships between downdraft properties and the updraft and environmental predictors. We find that these approaches yield similar results. Around 75% of the variability in downdraft mass flux and 37% of the variability in downdraft velocity are predictable. Analyzing the relative importance of our various predictors, we find that downdrafts are coupled to updrafts via the precipitation generation argument. In particular, updraft properties determine rain amount and rate, which then largely control the downdraft mass flux and, albeit to a lesser extent, the downdraft velocity. Among the environmental variables considered, only lapse rate is a valuable predictor: a more unstable environment favors a higher downdraft mass flux and a higher downdraft velocity.
Comparison of embryonic development, from HH21 to HH40, between ostrich (Struthio camelus) and chicken (Gallus gallus)

The chicken has been a representative model organism to study embryonic development in birds, however important differences exist among this class of species. As a representative of one of oldest existing clades of birds, the African ostrich (Struthio camelus), has the largest body among birds, and has two toes. Our purpose is to establish the corresponding stages in ostrich embryo development that match the well‐established HH system of the chicken to facilitate comparative studies between the ostrich and other birds to better understand differences in development.
Luminescence in SrTiO3 and LiNbO3 Crystals Under High Density Pulsed Electron Excitation

The time-resolved luminescence as well as stationary excited luminescence in SrTiO3 (undoped, Nb and Pb doped) and LiNbO3 (congruent and stoichiometric) single crystals was studied. The charge-transfer vibronic exciton in the regular oxy-anion site is suggested to be responsible for luminescence bands at 2.8 eV and 2.75 eV for SrTiO3 and LiNbO3 crystals respectively. It is suggested that luminescence band observed in SrTiO3 at ∼2.2-2.3 eV above 80 K possibly is due to some defect common for all SrTiO3 crystals studied.
Quaternionic methods in integral transforms of geophysical interest

SUMMARY It is well known that the Cauchy integral formula may be used in the study of integral transforms, leading to an elegant formulation in 2-D. We show that the quaternionic analysis of Fueter, and in particular the quaternionic analogue of the Cauchy formula, may be applied to derive integral transforms of vector functions in 3-D in an elegant manner. In particular we show that this result contains as special cases results of interest in the study of integral transforms in geophysics.
Analytical surface-potential-based drain current model for amorphous InGaZnO thin film transistors

A fully analytical surface-potential-based drain current model for amorphous InGaZnO (α-IGZO) thin film transistors (TFTs) has been developed based on a Gaussian distribution of subgap states, with the central energy fixed at the conduction band edge, which is approximated by two exponential distributions. This model includes both drift and diffusion components to describe the drain current in all regions of operation. Using an empirical mobility relationship that depends on both horizontal and vertical electric field, it is demonstrated that the model describes accurately the experimental transfer and output characteristics, making the model suitable for the design of circuits using α-IGZO TFTs.
Distributed output estimation error observer‐based adaptive fault‐tolerant consensus tracking control of multi‐agent systems

The purpose of this study is to discuss the fully distributed design of output estimation error observer and fault‐tolerant consensus tracking control for a class of multi‐agent systems with Lipschitz nonlinear dynamics and actuator faults. Firstly, based on the relative output measurements of neighboring agents, the distributed output estimation error observer is developed to adaptively estimate the state and fault information of each agent, and further overcome the difficulties of online updating the adaptive estimations of unknown hyper‐parameters. Secondly, to achieve the state consensus tracking goal and compensate for the negative effects of actuator faults, the distributed fault‐tolerant consensus tracking control scheme is proposed on the basis of the state estimation and adaptive fault estimation information, and has excellent robustness and consensus tracking control performance. Moreover, sufficient criteria can ensure that consensus tracking error of each agent converges to a small set near the origin. Finally, numerical simulations are provided to show the effectiveness of the proposed fully distributed algorithm.