Miracle-dz/UniFAR-FTUs huggingface dataset:
Extension of Murray-Davies tone reproduction model by adding edge effect of halftone dots

We propose expanding the Murray-Davies formula by adding the effect of edges of solid inks in a halftoned image. The expanded formula takes into account the spectral reflectance of paper white, full tone ink and mixed area scaled by the fractional area coverages. Here, mixed area mainly refers to the edge of an inked dot where the density is very low, and lateral exchange of photons can occur. Also, in such area the paper micro components may have higher scattering power than ink, especially, in uncoated paper. Our methodology uses cyan, magenta and yellow separation ramps printed on different papers by impact and non-impact based printing technologies. The samples include both frequency and amplitude modulation halftoning methods of various print resolutions. Based on pixel values, the captured microscale halftoned image is divided into three categories: solid ink, mixed area, and unprinted paper between the dots. The segmented images are then used to measure the fractional area coverage that the model receives as parameters. We have derived the characteristic reflectance spectrum of mixed area by rearranging the expanded formula and replacing the predicted term with the measured value using half of the maximum colorant coverage. Performance has clearly improved over the Murray-Davies model with and without dot gain compensation, more importantly, preserving the linear additivity of reflectance of the classical physics-based model.
On $BP\langle 2\rangle$-cooperations

In this paper we develop techniques to compute the cooperations algebra for the second truncated Brown-Peterson spectrum BP〈2〉. We prove that the cooperations algebra BP〈2〉∗BP〈2〉 decomposes as a direct some of a F2-vector space concentrated in Adams filtration 0 and a F2[v0, v1, v2]-module which is concentrated in even degrees and v2-torsion free. A recursive procedure is also developed to provide an basis of the v2-torsion free part.
Modelling crack propagation in concrete structures with a two scale approach

A simplified computational technique based on a refined global–local method is applied to the failure analysis of concrete structures. The technique distinguishes the scale of the structure, modelled with large size finite elements, from the scale at which material non‐linearity occurs due to progressive cracking and macro‐crack propagation. The finite element solution is split into two parts: a linear elastic analysis on a coarse mesh over the entire structure and a non‐linear analysis over a small part of the structure where a dense finite element grid is employed. In the non‐linear calculation, a non‐local damage model is implemented. These two computations are coupled with the help of an iterative scheme. The size and location of the region where a non‐linear analysis is performed, is adapted to follow the development of the damage zone. Numerical examples of mode I fracture of concrete specimens with straight and curved cracks are presented. Copyright © 2003 John Wiley & Sons, Ltd.
EM Algorithm Based on Fuzzification and its Application

EM algorithm is a common method to solve mixed model parameters in statistical classification of remote sensing image. The EM algorithm based on fuzzification is presented in this paper to use a fuzzy set to represent each training sample. Via the weighted degree of membership, different samples will be of different effect during iteration to decrease the impact of noise on parameter learning and to increase the convergence rate of algorithm. The function and accuracy of classification of image data can be completed preferably.
Electron energy transport inferences from modulated electron cyclotron heating in DIII-D

Electron thermal energy transport in high-temperature plasmas is poorly understood. A useful characterization of the transport as energy flux versus temperature gradient may be obtained for a modest range of fluxes and gradients about an equilibrium by using modulated electron cyclotron heating. The transport is rapid and stiff (high χinc) at the outside, becoming slower and more diffusive toward the center.
Application of Some Drought Stress Indices to Study Response of Durum Wheat Triticum durum to Different Levels of Water Depletion

A pot experiment was conducted to investigate the effect of five levels of soil water depletion from field capacity (30, 40, 50, 60, and 70%) on some growth, yield and yield components of durum wheat (Triticum durum L.) VAR-ACSAD/65, with testing ten stress and drought indices to indicate the suitable index that could be simply used to interpret drought stress conditions. Results indicated significant effect of soil water depletion levels on wheat plant height, tillers per plant, spikes per plant, spike length, and total chlorophyll content, increasing water depletion levels decreased all recorded data. The effect on spike numbers per plant; spike length; number of seeds per spike; 1000 seeds weight (gm); seed yield per plant; straw yield per plant; biological yield per plant and harvest index were negatively dependent on drought stress to the level of no seed yield under the highest water depletion level 70%. Drought indices could classify to three categories; unity to zero, zero to higher value, high values to lower values. The relationship between drought indices were either positive or negatively correlated to plant seed yield. All studied crop drought indices were suitable for studying crop drought cases. The wheat variety acsad/65 was sensitive to drought stress.
Eigenvalue enclosures

This paper is concerned with methods for numerical computation of eigenvalue enclosures. We examine in close detail the equivalence between an extension of the Lehmann-Maehly-Goerisch method developed a few years ago by Zimmermann and Mertins, and a geometrically motivated method developed more recently by Davies and Plum. We extend various previously known results in the theory and establish explicit convergence estimates in both settings. The theoretical results are supported by two benchmark numerical experiments on the isotropic Maxwell eigenvalue problem.
Function Prediction of Peptide Toxins with Sequence-Based Multi-Tasking PU Learning Method

Peptide toxins generally have extreme pharmacological activities and provide a rich source for the discovery of drug leads. However, determining the optimal activity of a new peptide can be a long and expensive process. In this study, peptide toxins were retrieved from Uniprot; three positive-unlabeled (PU) learning schemes, adaptive basis classifier, two-step method, and PU bagging were adopted to develop models for predicting the biological function of new peptide toxins. All three schemes were embedded with 14 machine learning classifiers. The prediction results of the adaptive base classifier and the two-step method were highly consistent. The models with top comprehensive performances were further optimized by feature selection and hyperparameter tuning, and the models were validated by making predictions for 61 three-finger toxins or the external HemoPI dataset. Biological functions that can be identified by these models include cardiotoxicity, vasoactivity, lipid binding, hemolysis, neurotoxicity, postsynaptic neurotoxicity, hypotension, and cytolysis, with relatively weak predictions for hemostasis and presynaptic neurotoxicity. These models are discovery-prediction tools for active peptide toxins and are expected to accelerate the development of peptide toxins as drugs.
Trabecular Bone Score as an Index of Bone Fragility in Patients with Acromegaly: A Systematic Review and Meta-Analysis

Background: Acromegaly is characterized by impaired bone quality and increased fracture risk. However, due to the pathophysiology of acromegalic osteopathy, bone mineral density (BMD) does not represent a reliable predictor for fragility fractures in this setting. Trabecular bone score (TBS) has been recently evaluated as an alternative index of skeletal fragility in acromegalic patients. However, no conclusive data are still available in this regard. Methods: PubMed/Medline, EMBASE, Cochrane Library, Ovid, and CINAHL databases were systematically searched until June 2022 for studies reporting data either about the comparison of TBS values between acromegalic patients and non-acromegalic controls or about the relationship – within acromegalic patients – between TBS values and fracture risk. Effect sizes were pooled through a random-effect model. Results: Eight studies were eligible for inclusion in the meta-analysis, encompassing 336 acromegalic patients and 490 non-acromegalic controls. Overall, TBS was significantly lower in acromegalic patients compared to controls (−0.089, 95% CI: [−0.111, −0.067], p < 0.01), irrespective of acromegaly disease activity and gonadal status. With respect to fracture risk, TBS was significantly lower in acromegalic patients with vertebral fractures than in those without (−0.099, 95% CI: [−0.166, −0.032], p < 0.01). Conclusion: In this meta-analysis, we specifically assessed the role of TBS as an index of bone quality and fracture risk in patients with acromegaly. Our results support the notion that TBS could be of value in the assessment and management of skeletal fragility in acromegalic patients, especially in light of the poor information provided in this setting by BMD.
Flows of Nematic Liquid Crystals

The first liquid crystal was discovered about a century ago by Reinitzer (1888), who observed that the organic crystal cholesteryl benzoate melted at a temperature of 145°C yielding a turbid fluid which, upon the further addition of heat, became clear at a temperature of 179°C. The turbid fluid was found to exhibit optical birefringence, so the intermediate state apparently possessed the mechanical pro­ perties of a liquid and the optical properties of a crystal. Further research on the melts of organic crystals composed of relatively long organic molecules indicated that there was often a succession of liquid crystalline states between the crystal and the isotropic fluids. Mixtures of an isotropic liquid and either amphiphilic molecules as in soaps, or the rodlike molecular configurations of synthetic poly­ peptides, were also found to exhibit birefringence over ranges of concentration and/or temperature. The liquid crystalline states can be broadly classified into two types, smectic and nematic, on the basis of the molecular order that is characteristic of each. In smectic liquid crystals the molecules are arranged in parallel layers, often with their long axis oriented normal to the layers. Usually the molecules of each layer possess the mobility of a fluid within the layer. The orientation of the long axis with respect to the layer and the degree of mobility of the molecules within the layers provide the basis for further subclassifications of the smectics. Nematic liquid crystals are less ordered than smectics. In nematics the centers of mass of the molecules are unordered, as in isotropic fluids ; but the relatively long molecules exhibit an orientational ordering and, locally, seek to remain parallel to one another. In an ideal sample of nematic there is uniform parallel alignment of the molecules, and short-range molecular forces resist any departures from this homogeneous state. Chiral molecules with a liquid crystalline phase exhibit a variation of the nematic ordering. In these materials, called cholesteric liquid crystals, the molecules, locally, lie on parallel planes in which nematic order prevails ; how­ ever, as the normal to the planes is traversed, the direction of the molecules rotates with a pitch that is comparable to optical wavelengths.
A comparison between ICRF theory and experiment

The status of, successively, RF modeling theory, experimental interpretation methods and comparison between theory and experiment is discussed. As far as the recent developments in theory are concerned, it is found that full wave models appear to be consistent with ray-tracing models and to yield comparable results when applied to selected cases where both are applicable. Methods for including consistent gradient terms in the wave equation have now been found; however, a unified understanding of the impact of such corrections is desirable. From the experimental point of view several procedures have been developed based on sawteeth analysis, modulation or simulation, to evaluate the fraction of the power coupled to the plasma bulk and the power deposition profiles. Comparison between experiments and theory on these subjects as well as for coupling indicates that the ICRF physics is well understood. Tail analysis has been done extensively only for PLT; further work is going on for JET and TEXTOR, which clearly reveals their presence and the importance of their role. chi e analysis in the presence of RF has also been done; however, several of the presently available thermal diffusion models seem to be able to fit the experimental data. It is concluded that, in the ICRF field, theory nowadays provides quite reliable tools and that extensive comparisons with experiments should be pursued in order to provide the basis for the understanding of the interplay between heating, velocity diffusion, confinement and edge effects.
A Theory of Transfers: Duality and convolution

We introduce and study the permanence properties of the class of linear transfers between probability measures. This class contains all cost minimizing mass transports, but also martingale mass transports, the Schrodinger bridge associated to a reversible Markov process, and the weak mass transports of Tala- grand, Marton, Gozlan and others. The class also includes various stochastic mass transports to which Monge-Kantorovich theory does not apply. We also introduce the cone of convex transfers, which include any p-power (p > 1) of a linear transfer, but also the logarithmic entropy, the Donsker-Varadhan infor- mation and certain free energy functionals. This first paper is mostly about exhibiting examples that point to the pervasiveness of the concept in the important work on correlating probability distributions. Duality formulae for general transfer inequalities follow in a very natural way. We also study the infinite self-convolution of a linear transfer in order to establish the existence of generalized weak KAM solutions that could be applied to the stochastic counterpart of Fathi-Mather theory.
Radar altimetry for classifying surface conditions of subarctic lakes during freezing and thawing periods

ABSTRACT Ice cover on subarctic lakes is an important indicator of climate change at local- or regional scales. This study proposes a new approach for classifying altimetry data from Jason-2 and SARAL/Altika satellite missions to characterize surface states of subarctic lakes. It focuses on Great Slave Lake (Canada) during freeze-up and thaw periods. For the first time, parameters from altimetry waveforms were used in an unsupervised clustering to establish distinct clusters from waveforms observed from Jason-2 and SARAL/Altika during the freeze-up and the thaw period. Clusters are assigned to the different surface states (open water, pure ice and leads) based on a priori altimetry and radiometric information. The statistics of these clusters were then used to construct two trained models of supervised classification based upon KNN (K-nearest neighbour) and SVM (support vector machine). The SVM-based model yielded the best results (accuracy of 92% with Jason-2, and 98% with SARAL/Altika). It was used to classify all waveforms considered in the study from the nominal orbits of Jason-2 (2008–2016) and SARAL/Altika (2013–2016). Results were superimposed onto Moderate Resolution Imaging Spectroradiometer (MODIS) products for qualitative visual and semi-quantitative assessments.
A Johnson--Lindenstrauss Framework for Randomly Initialized CNNs

How does the geometric representation of a dataset change after the application of each randomly initialized layer of a neural network? The celebrated Johnson--Lindenstrauss lemma answers this question for linear fully-connected neural networks (FNNs), stating that the geometry is essentially preserved. For FNNs with the ReLU activation, the angle between two inputs contracts according to a known mapping. The question for non-linear convolutional neural networks (CNNs) becomes much more intricate. To answer this question, we introduce a geometric framework. For linear CNNs, we show that the Johnson--Lindenstrauss lemma continues to hold, namely, that the angle between two inputs is preserved. For CNNs with ReLU activation, on the other hand, the behavior is richer: The angle between the outputs contracts, where the level of contraction depends on the nature of the inputs. In particular, after one layer, the geometry of natural images is essentially preserved, whereas for Gaussian correlated inputs, CNNs exhibit the same contracting behavior as FNNs with ReLU activation.
A new construction of compact torsion-free $G_2$-manifolds by gluing families of Eguchi–Hanson spaces

We give a new construction of compact Riemannian 7-manifolds with holonomy $G_2$. Let $M$ be a torsion-free $G_2$-manifold (which can have holonomy a proper subgroup of $G_2$) such that $M$ admits an involution $\iota$ preserving the $G_2$-structure. Then $M/{\langle \iota \rangle}$ is a $G_2$-orbifold, with singular set $L$ an associative submanifold of $M$, where the singularities are locally of the form $\mathbb R^3 \times (\mathbb R^4 / \{\pm 1\})$. We resolve this orbifold by gluing in a family of Eguchi-Hanson spaces, parametrized by a nonvanishing closed and coclosed $1$-form $\lambda$ on $L$. Much of the analytic difficulty lies in constructing appropriate closed $G_2$-structures with sufficiently small torsion to be able to apply the general existence theorem of the first author. In particular, the construction involves solving a family of elliptic equations on the noncompact Eguchi-Hanson space, parametrized by the singular set $L$. We also present two generalizations of the main theorem, and we discuss several methods of producing examples from this construction.
The deformation of a liquid film flowing down an inclined plane wall over a small particle arrested on the wall

The shape of the free surface of a liquid film flowing down an inclined plane wall over a particle captured on the wall is studied in the asymptotic limit where the size of the particle is much smaller than the film thickness, and the Reynolds number is vanishingly small. Using the boundary integral method for Stokes flow, the problem is formulated in terms of a system of four linear integral and differential equations for the elevation of the free surface and the three components of the velocity at the free surface, and is solved using a semi‐iterative method. The results demonstrate that the particle causes a marked deformation of the free surface upstream right before the particle, and a surface corrugation resembling a surface wake downstream behind the particle. The detailed features of the deformation and the disturbance flow are affected strongly by the geometry of the particle, surface tension, and the inclination of the wall.
An Improved Block 2DPCA Face Recognition Algorithm with L1-Norm

Most of the existing Block 2DPCA algorithms are based on Frobenius norm, which makes them sensitive to outliers. In this paper, we propose a new improved Block 2DPCA algorithm with L1-norm, which is robust to outliers. The experimental results of FERET face database indicated that the recognition performance of new algorithm is superior to Block 2DPCA, more robust than Block 2DPCA.
Parameter identification in a structured population model

We study parameter identification problems in a structured population model without mutations. Given measurements of the total population size or critical points of the population, we aim to recover its growth rate, death rate or initial distribution. We present uniqueness results under suitable assumptions and present counterexamples when these assumptions are violated. Our results are supplemented by numerical studies, either based on Tikhonov regularization or the use of explicit reconstruction formulas.
Manifolds with higher homotopy which do not support Anosov diffeomorphisms

We show that various classes of closed manifolds with non‐trivial higher homotopy groups do not support (transitive) Anosov diffeomorphisms. In particular, we show that a finite product of spheres at least one of which is even‐dimensional does not support transitive Anosov diffeomorphisms.
Near-Infrared Spectroscopy and Hubble Space Telescope Imaging of a Dusty Starburst Extremely Red Object

We present near-infrared spectroscopy and Hubble Space Telescope (HST) imaging of ERO J164023+4644, an Extremely Red Object (ERO) with (R-K) = 5.9 at z = 1.05 that has been detected by Infrared Space Observatory (ISO) at 15 μm. ERO J164023 resembles a disk galaxy, with an optical/infrared spectral energy distribution that is strongly reddened by dust (LFIR/LB ≲ 200; AV ~ 5). The combination of the narrow width of the emission lines in our spectra (~300 km s-1) and the relatively high [N II]/Hα line ratio indicate that this is a "composite" starburst-Seyfert galaxy. Assuming that star formation dominates the energy output, we constrain the star formation rate to lie in the broad range ~10-700 M☉ yr-1 from a variety of star formation indicators. We compare ERO J164023 with the only other spectroscopically identified dusty EROs: HR10 (z = 1.44) and ISO J1324-2016 (z = 1.50). ERO J164023 and HR10 have similar disklike morphologies in the rest-frame UV, and both exhibit a variation in the apparent dust obscuration depending upon the diagnostic used, which suggests that there is a complex spatial mix of stellar populations and dust in these galaxies. In contrast, the compact morphology and spectral properties of ISO J1324-2016 indicate that it is a dusty quasar. Overall, our results demonstrate that the population of dusty galaxies identified using photometric ERO criteria includes systems ranging from pure starbursts through transition systems, such as ERO J164023, to dusty quasars. We suggest that the classification of EROs into these subclasses, necessary for the detailed modeling of the population, cannot be reliably achieved from optical/near-infrared photometry and instead requires mid/far-infrared or submillimeter photometry and near-infrared spectroscopy. The advent of efficient multiobject spectrographs working in the near-infrared, as well as the imminent launch of SIRTF, therefore promises the opportunity of rapid progress in our understanding of the elusive ERO population.
Fast dual proximal gradient algorithms with rate $O(1/k^{1.5})$ for convex minimization

We consider minimizing the composite function that consists of a strongly convex function and a convex function. The fast dual proximal gradient (FDPG) method decreases the dual function with a rate $O(1/k^2)$, leading to a rate $O(1/k)$ for decreasing the primal function. We propose a generalized FDPG method that guarantees an $O(1/k^{1.5})$ rate for the dual proximal gradient norm decrease. By relating this to the primal function decrease, the proposed approach decreases the primal function with the improved $O(1/k^{1.5})$ rate.