Miracle-dz/UniFAR-FTUs huggingface dataset:
Dijkstra-like ordered upwind methods for solving static Hamilton-Jacobi equations

The solution of a static Hamilton-Jacobi Partial Differential Equation (HJ PDE) can be used to determine the change of shape in a surface for etching/deposition/lithography applications, to provide the first-arrival time of a wavefront emanating from a source for seismic applications, or to compute the minimal-time trajectory of a robot trying to reach a goal. HJ PDEs are nonlinear so theory and methods for solving linear PDEs do not directly apply. An efficient way to approximate the solution is to emulate the causal property of this class of HJ PDE: the solution at a particular point only depends on values backwards along the characteristic that passes through that point and solution values always increase along characteristics. In our discretization of the HJ PDE we enforce an analogous causal property, that the solution value at a grid node may only depend on the values of nodes in its numerical stencil which are smaller. This causal property is related but not the same thing as an upwinding property of schemes for time dependent problems. The solution to such a discretized system of equations can be efficiently computed using a Dijkstra-like method in a single pass through the grid nodes in order of nondecreasing value. We develop two Dijkstra-like methods for solving two subclasses of static HJ PDEs. The first method is an extension of the Fast Marching Method for isotropic Eikonal equations and it can be used to solve a class of axis-aligned anisotropic HJ PDEs on an orthogonal grid. The second method solves general convex static HJ PDEs on simplicial grids by computing stencils for a causal discretization in an initial pass through the grid nodes, and then solving the discretization in a second Dijkstra-like pass through the nodes.
Markov chain Monte Carlo, Sufficient Statistics, and Particle Filters

This article considers how to implement Markov chain Monte Carlo (MCMC) moves within a particle filter. Previous, similar, attempts have required the complete history (“trajectory”) of each particle to be stored. Here, it is shown how certain MCMC moves can be introduced within a particle filter when only summaries of each particles' trajectory are stored. These summaries are based on sufficient statistics. Using this idea, the storage requirement of the particle filter can be substantially reduced, and MCMC moves can be implemented more efficiently. We illustrate how this idea can be used for both the bearingsonly tracking problem and a model of stochastic volatility. We give a detailed comparison of the performance of different particle filters for the bearings-only tracking problem. MCMC, combined with a sensible initialization of the filter and stratified resampling, produces substantial gains in the efficiency of the particle filter.
Determination of piezoelectric fields in strained GaInN quantum wells using the quantum-confined Stark effect

We have identified piezoelectric fields in strained GaInN/GaN quantum well p-i-n structures using the quantum-confined Stark effect. The photoluminescence peak of the quantum wells showed a blueshift with increasing applied reverse voltages. This blueshift is due to the cancellation of the piezoelectric field by the reverse bias field. We determined that the piezoelectric field points from the growth surface to the substrate and its magnitude is 1.2 MV/cm for Ga0.84In0. 16N/GaN quantum wells on sapphire substrate. In addition, from the direction of the field, the growth orientation of our nitride epilayers can be determined to be (0001), corresponding to the Ga face.
A wide baseline matching method based on scale invariant feature descriptor

Image matching is a fundamental aspect of many problems in computer vision. We describe a novel wide baseline matching method based on scale invariant feature descriptor. First, corners in image pairs are detected based on an improved Curvature Scale-Space (CSS) technique. These corners are relatively invariant to affine transformations, and are represented by using Scale Invariant Feature Transform (SIFT) descriptor to provide robust matching. The nearest neighbor distance is then applied to remove mismatched corners. Finally, the robust estimation algorithm, RANSAC, is adopt to estimate the fundamental matrix from the correspondence, and at the same time identify inlying matches. Experiments demonstrate the feasibility of this method.
Existence of blow-up solutions for a degenerate parabolic-elliptic Keller–Segel system with logistic source

This paper deals with existence of finite-time blow-up solutions to a degenerate parabolic–elliptic Keller–Segel system with logistic source. Recently, finite-time blow-up was established for a degenerate Jäger–Luckhaus system with logistic source. However, blow-up solutions of the aforementioned system have not been obtained. The purpose of this paper is to construct blow-up solutions of a degenerate Keller–Segel system with logistic source.
On methods of sieves and penalization

We develop a general theory which provides a unified treatment for the asymptotic normality and efficiency of the maximum likelihood estimates (MLE's) in parametric, semiparametric and nonparametric models. We find that the asymptotic behavior of substitution estimates for estimating smooth functionals are essentially governed by two indices: the degree of smoothness of the functional and the local size of the underlying parameter space. We show that when the local size of the parameter space is not very large, the substitution standard (nonsieve), substitution sieve and substitution penalized MLE's are asymptotically efficient in the Fisher sense, under certain stochastic equicontinuity conditions of the loglikelihood. Moreover, when the convergence rate of the estimate is slow, the degree of smoothness of the functional needs to compensate for the slowness of the rate in order to achieve efficiency. When the size of the parameter space is very large, the standard and penalized maximum likelihood procedures may be inefficient, whereas the method of sieves may be able to overcome this difficulty. This phenomenon is particularly manifested when the functional of interest is very smooth, especially in the semiparametric case.
Measurement of optical fibers by interferometric methods

An overview of some important results is presented in measurement of optical fibers by interferometric methods in two domains. Both time-domain and spectral-domain measurements are analyzed theoretically including the effect of the first-order and second-order intermodal dispersion. In the time-domain measurements, a tandem configuration of a Michelson interferometer and a few-mode optical fiber is used and the spatial interference fringes are resolved to measure the intermodal group optical path difference. In the spectral-domain measurements, the intermodal interference at the output of an optical fiber alone shows up as a periodic modulation of the source spectrum when a high-resolution spectrometer is used. Utilizing a white-light spectral interferometric method employing a low-resolution spectrometer and a tandem configuration of a Michelson interferometer and an optical fiber under test, the equalization wavelengths are resolved and the intermodal dispersion in the optical fiber can be measured over a wide spectral range. We have used the method for measuring either intermodal dispersion in circular-core, elliptical-core and bow-tie fibers or dispersion of birefringence in elliptical-core fibers.
Non-polar InGaN quantum dot emission with crystal-axis oriented linear polarization

Polarization sensitive photoluminescence is performed on single non-polar InGaN quantum dots. The studied InGaN quantum dots are found to have linearly polarized emission with a common polarization direction defined by the [0001] crystal axis. Around half of ∼40 studied dots have a polarization degree of 1. For those lines with a polarization degree less than 1, we can resolve fine structure splittings between −800 μeV and +800 μeV, with no clear correlation between fine structure splitting and emission energy.
H2 FORMATION IN DIFFUSE CLOUDS: A NEW KINETIC MONTE CARLO STUDY

We used the continuous-time random-walk Monte Carlo technique to study anew the formation of H2 on the surfaces of interstellar dust grains in diffuse interstellar clouds. For our study, we considered three different grain materials, olivine (a polycrystalline silicate), amorphous silicate, and amorphous carbon, as well as a grain temperature that depends on granular size. For some runs, we included temperature fluctuations. Four different granular surfaces were used, one “flat” with one type of binding site due to physisorption, one “rough” with five different types of physisorption binding sites due to lateral forces, and two with sites for chemisorption, one in which chemisorption sites are entered through precursor physisorption sites, and one in which chemisorption is direct but occurs with a barrier for the adsorption of the first hydrogen atom. We found that on flat and rough olivine surfaces, molecular hydrogen is formed at low efficiencies, with smaller grains contributing very little despite their large numbers due to high temperatures. For flat amorphous carbon and amorphous silicate surfaces, the efficiency increases, reaching unity for the largest grains. For models with barrierless chemisorption, the efficiency of formation of H2 is near unity at all grain sizes considered, while for direct chemisorption via a barrier, we found efficiencies of 0.13–0.6 depending upon the barrier, but independent of grain size. Treating the flat olivine and amorphous silicate surfaces with temperature fluctuations increases the efficiency of H2 formation.
GroundFlow: Liquid-based Haptics for Simulating Fluid on the Ground in Virtual Reality

Utilizing haptic devices to enhance the immersive experience is a direct approach in virtual reality (VR) applications. Various studies develop haptic feedback using force, wind, and thermal mechanisms. However, most haptic devices simulate feedback in dry environments such as the living room, prairie, or city. Water-related environments are thus less explored, for example, rivers, beaches, and swimming pools. In this paper we present GroundFlow, a liquid-based haptic floor system for simulating fluid on the ground in VR. We discuss design considerations and propose a system architecture and interaction design. We conduct two user studies to assist in the design of a multiple-flow feedback mechanism, develop three applications to explore the potential uses of the mechanism, and consider the limitations and challenges thereof to inform VR developers and haptic practitioners.
Least Squares Approximation of Completely Monotonic Functions by Sums of Exponentials

We consider the approximation of a given completely monotonic function $F(t)$ by an exponential sum $Y(t) = a_1 \exp ( - \lambda t) + \cdots + a_n \exp ( - \lambda _n t)$ using the $L_2 $-norm associated with a suitable measure $d\mu (t)$. A best approximation exists and is characterized by a generalized version of the Aigrain–Williams equations. Examples are given to show that a given F may have several best approximations. We apply Rice’s dual algorithm for nonlinear $L_2 $-approximation to this problem and show that it reduces the norm of the error at each step. The algorithm calls for the repeated solution of an associated nonlinear Hermite interpolation problem which involves simple rational functions when $d\mu (t) = dt,0 < t < \infty $. The rate of convergence can be accelerated from first to second order by an inexpensive extrapolation. We discuss the numerical implementation of the algorithm and present numerical results for $F(t) = {1} /{(1 + t)},d\mu (t) = dt,0 < t < \infty $.
On Expressing the Probabilities of Categorical Responses as Linear Functions of Covariates

Logistic regression is usually used to model probabilities of categorical responses as functions of covariates. However, the link connecting the probabilities to the covariates is non-linear. We show in this paper that when the cross-classification of all the covariates and the dependent variable have no empty cells, then the probabilities of responses can be expressed as linear functions of the covariates. We demonstrate this for both the dichotmous and polytomous dependent variables.
A Generalized Logistic Item Response Model Parameterizing Test Score Inappropriateness

The person response curve has been suggested as a possible model for test score inappropriateness (Lums den, 1977, 1978; Weiss, 1973). The two-parameter person response curve proposed by Lumsden includes a person slope parameter but abandons the notion of differential item relatedness to the underlying trait. As an alternative, a generalized logistic model is consid ered that includes all item parameters of the three- parameter logistic model (Birnbaum, 1968). In addi tion to the usual person location parameter, the model has extra person parameters representing two possible characterizations of test score inappropriateness: a slope parameter indicating the degree to which a per son responds differently to items of varying difficulty, and an asymptote parameter measuring a person's pro clivity to engage in effective guessing or to omit items in the presence of partial information. To assess the model's feasibility, statistical comparisons were made between parameter estimates from data simulated ac cording to the model and the original simulation parameters. The results seem encouraging, but addi tional empirical study is needed before firm conclu sions can be drawn.
Whole‐genome re‐sequencing provides key genomic insights in farmed Arctic charr (Salvelinus alpinus) populations of anadromous and landlocked origin from Scandinavia

Arctic charr (Salvelinus alpinus) is a niche‐market high‐value species for Nordic aquaculture. Similar to other salmonids, both anadromous and landlocked populations are encountered. Whole‐genome re‐sequencing (22X coverage) was performed on two farmed populations of anadromous (Sigerfjord; n = 24) and landlocked (Arctic Superior; n = 24) origin from Norway and Sweden respectively. More than 5 million SNPs were used to study their genetic diversity and to scan for selection signatures. The two populations were clearly distinguished through principal component analysis, with the mean fixation index being ~0.12. Furthermore, the levels of genomic inbreeding estimated from runs of homozygosity were 6.23% and 8.66% for the Norwegian and the Swedish population respectively. Biological processes that could be linked to selection pressure associated primarily with the anadromous background and/or secondarily with domestication were suggested. Overall, our study provided insights regarding the genetic composition of two main strains of farmed Arctic charr from Scandinavia. At the same time, ample genomic resources were produced in the magnitude of millions of SNPs that could assist the transition of Nordic Arctic charr farming in the genomics era.
Red Meat Intake, Indole-3-Acetate, and Dorea longicatena Together Affect Insulin Resistance after Gastric Bypass

Roux-en-Y Gastric bypass (RYGB) promotes improvement in type 2 diabetes (T2D) shortly after surgery, with metabolic mechanisms yet to be elucidated. This study aimed to investigate the relationship between food intake, tryptophan metabolism, and gut microbiota on the glycemic control of obese T2D women after RYGB surgery. Twenty T2D women who underwent RYGB were evaluated before and three months after surgery. Food intake data were obtained by a seven-day food record and a food frequency questionnaire. Tryptophan metabolites were determined by untargeted metabolomic analysis, and the gut microbiota was determined by 16S rRNA sequencing. The glycemic outcomes were fasting blood glucose, HbA1C, HOMA-IR, and HOMA-beta. Linear regression models were applied to assess the associations between the changes in food intake, tryptophan metabolism, and gut microbiota on glycemic control after RYGB. All variables changed after RYGB (p < 0.05), except for tryptophan intake. Jointly, the variation in red meat intake, plasma indole-3-acetate, and Dorea longicatena was associated with postoperative HOMA-IR {R2 0.80, R2 adj 0.74; p < 0.01}. Red meat intake decreased three months after bariatric surgery while indole-3-acetate and Dorea longicatena increased in the same period. These combined variables were associated with better insulin resistance in T2D women after RYGB.
Genome-Wide Analysis of microRNA Expression Profile in Roots and Leaves of Three Wheat Cultivars under Water and Drought Conditions

Wheat is one of the most important food sources on Earth. MicroRNAs (miRNAs) play important roles in wheat productivity. To identify wheat miRNAs as well as their expression profiles under drought condition, we constructed and sequenced small RNA (sRNA) libraries from the leaves and roots of three wheat cultivars (Kukri, RAC875 and Excalibur) under water and drought conditions. A total of 636 known miRNAs and 294 novel miRNAs were identified, of which 34 miRNAs were tissue- or cultivar-specific. Among these, 314 were significantly regulated under drought conditions. miRNAs that were drought-regulated in all cultivars displayed notably higher expression than those that responded in a cultivar-specific manner. Cultivar-specific drought response miRNAs were mainly detected in roots and showed significantly different drought regulations between cultivars. By using wheat degradome library, 6619 target genes were identified. Many target genes were strongly enriched for protein domains, such as MEKHLA, that play roles in drought response. Targeting analysis showed that drought-downregulated miRNAs targeted more genes than drought-upregulated miRNAs. Furthermore, such genes had more important functions. Additionally, the genes targeted by drought-downregulated miRNAs had multiple interactions with each other, while the genes targeted by drought-upregulated miRNAs had no interactions. Our data provide valuable information on wheat miRNA expression profiles and potential functions in different tissues, cultivars and drought conditions.
Living with Epilepsy in Adolescence in Italy: Psychological and Behavioral Impact

Background: People with epilepsy have a higher prevalence of behavioral and neuropsychiatric comorbidities compared to the general population and those with other chronic medical conditions, although the underlying clinical features remain unclear. The goal of the current study was to characterize behavioral profiles of adolescents with epilepsy, assess the presence of psychopathological disorders, and investigate the reciprocal interactions among epilepsy, psychological functioning, and their main clinical variables. Methods: Sixty-three adolescents with epilepsy were consecutively recruited at the Epilepsy Center, Childhood and Adolescence Neuropsychiatry Unit of Santi Paolo e Carlo hospital in Milan (five of them were excluded) and assessed with a specific questionnaire for psychopathology in adolescence, such as the Questionnaire for the Assessment of Psychopathology in Adolescence (Q-PAD). Q-PAD results were then correlated with the main clinical data. Results: 55.2% (32/58) of patients presented at least one emotional disturbance. Body dissatisfaction, anxiety, interpersonal conflicts, family problems, uncertainty about the future, and self-esteem/well-being disorders were frequently reported. Gender and poor control of seizures are associated with specific emotional features (p < 0.05). Conclusions: These findings highlight the importance of screening for emotional distress, recognition of the impairments, and provision of adequate treatment and follow-up. A pathological score on the Q-PAD should always require the clinician to investigate the presence of behavioral disorders and comorbidities in adolescents with epilepsy.
A real-time and convex model for the estimation of muscle force from surface electromyographic signals in the upper and lower limbs

Surface electromyography (sEMG) is a signal consisting of different motor unit action potential trains and records from the surface of the muscles. One of the applications of sEMG is the estimation of muscle force. We proposed a new real-time convex and interpretable model for solving the sEMG—force estimation. We validated it on the upper limb during isometric voluntary flexions-extensions at 30%, 50%, and 70% Maximum Voluntary Contraction in five subjects, and lower limbs during standing tasks in thirty-three volunteers, without a history of neuromuscular disorders. Moreover, the performance of the proposed method was statistically compared with that of the state-of-the-art (13 methods, including linear-in-the-parameter models, Artificial Neural Networks and Supported Vector Machines, and non-linear models). The envelope of the sEMG signals was estimated, and the representative envelope of each muscle was used in our analysis. The convex form of an exponential EMG-force model was derived, and each muscle’s coefficient was estimated using the Least Square method. The goodness-of-fit indices, the residual signal analysis (bias and Bland-Altman plot), and the running time analysis were provided. For the entire model, 30% of the data was used for estimation, while the remaining 20% and 50% were used for validation and testing, respectively. The average R-square (%) of the proposed method was 96.77 ± 1.67 [94.38, 98.06] for the test sets of the upper limb and 91.08 ± 6.84 [62.22, 96.62] for the lower-limb dataset (MEAN ± SD [min, max]). The proposed method was not significantly different from the recorded force signal (p-value = 0.610); that was not the case for the other tested models. The proposed method significantly outperformed the other methods (adj. p-value < 0.05). The average running time of each 250 ms signal of the training and testing of the proposed method was 25.7 ± 4.0 [22.3, 40.8] and 11.0 ± 2.9 [4.7, 17.8] in microseconds for the entire dataset. The proposed convex model is thus a promising method for estimating the force from the joints of the upper and lower limbs, with applications in load sharing, robotics, rehabilitation, and prosthesis control for the upper and lower limbs.
A Frequency Reconfigurable Folded Antenna for Cognitive Radio Communication

In this work, a spectrum-sensing monopole antenna was used to operate in different frequency bands for cognitive radio applications. The proposed antenna consists of a folded monopole antenna with a partial ground plane, and it can be used for various wireless technologies operated at various frequencies from 1.5 to 3.5 GHz. The suggested antenna was printed on a RO4003 substrate with 3.38 permittivity and an overall size of 60 × 60 × 0.813 mm3. To achieve reconfigurability of the antenna, PIN diodes (HPND-4005) were inserted at different lengths along the antenna to obtain the desired performance. The antenna was fabricated and experimentally tested to validate the simulation outcomes, and distinct consistency between the simulation and measurement outcomes was obtained. Computer simulation tool (CST) software was used to design and simulate the suggested antenna and then the model was fabricated to validate the simulation outcomes.