Miracle-dz/UniFAR-FTUs huggingface dataset:
Global Convergence Rate of Deep Equilibrium Models with General Activations

In a recent paper, Ling et al. investigated the over-parametrized Deep Equilibrium Model (DEQ) with ReLU activation. They proved that the gradient descent converges to a globally optimal solution for the quadratic loss function at a linear convergence rate. This paper shows that this fact still holds for DEQs with any generally bounded activation with bounded first and second derivatives. Since the new activation function is generally non-homogeneous, bounding the least eigenvalue of the Gram matrix of the equilibrium point is particularly challenging. To accomplish this task, we must create a novel population Gram matrix and develop a new form of dual activation with Hermite polynomial expansion.
E-CRF: Embedded Conditional Random Field for Boundary-caused Class Weights Confusion in Semantic Segmentation

Modern semantic segmentation methods devote much effect to adjusting image feature representations to improve the segmentation performance in various ways, such as architecture design, attention mechnism, etc. However, almost all those methods neglect the particularity of class weights (in the classification layer) in segmentation models. In this paper, we notice that the class weights of categories that tend to share many adjacent boundary pixels lack discrimination, thereby limiting the performance. We call this issue Boundary-caused Class Weights Confusion (BCWC). We try to focus on this problem and propose a novel method named Embedded Conditional Random Field (E-CRF) to alleviate it. E-CRF innovatively fuses the CRF into the CNN network as an organic whole for more effective end-to-end optimization. The reasons are two folds. It utilizes CRF to guide the message passing between pixels in high-level features to purify the feature representation of boundary pixels, with the help of inner pixels belonging to the same object. More importantly, it enables optimizing class weights from both scale and direction during backpropagation. We make detailed theoretical analysis to prove it. Besides, superpixel is integrated into E-CRF and served as an auxiliary to exploit the local object prior for more reliable message passing. Finally, our proposed method yields impressive results on ADE20K, Cityscapes, and Pascal Context datasets.
Benchmarking Bayesian neural networks and evaluation metrics for regression tasks

Due to the growing adoption of deep neural networks in many fields of science and engineering, modeling and estimating their uncertainties has become of primary importance. Despite the growing literature about uncertainty quantification in deep learning, the quality of the uncertainty estimates remains an open question. In this work, we assess for the first time the performance of several approximation methods for Bayesian neural networks on regression tasks by evaluating the quality of the confidence regions with several coverage metrics. The selected algorithms are also compared in terms of predictivity, kernelized Stein discrepancy and maximum mean discrepancy with respect to a reference posterior in both weight and function space. Our findings show that (i) some algorithms have excellent predictive performance but tend to largely over or underestimate uncertainties (ii) it is possible to achieve good accuracy and a given target coverage with finely tuned hyperparameters and (iii) the promising kernel Stein discrepancy cannot be exclusively relied on to assess the posterior approximation. As a by-product of this benchmark, we also compute and visualize the similarity of all algorithms and corresponding hyperparameters: interestingly we identify a few clusters of algorithms with similar behavior in weight space, giving new insights on how they explore the posterior distribution.
Asymptotically optimal synthesis of reversible circuits

For a long time, reversible circuits have attracted much attention from the academic community. They have plenty of applications in various areas, such as digital signal processing, cryptography, quantum computing, etc. Although the lower bound $\Omega(2^n n/\log n)$ for synthesis of an $n$-wire reversible circuit has been proposed for about 20 years, none of the existing synthesis methods achieves this bound. Previous algorithms, based on BDD(Binary decision diagram) or cycle, yield circuits with $O(2^n n)$ elementary gates in the worst case. In this paper, we prove for the first time that the lower bound is asymptotically optimal, by proposing a procedure to implement an arbitrary $n$-wire reversible circuit with no more than $O(2^n n/\log n)$ elementary gates.
Aflatoxin contaminated chili pepper detection by hyperspectral imaging and machine learning

Mycotoxins are toxic secondary metabolites produced by fungi. They have been demonstrated to cause various health problems in humans, including immunosuppression and cancer. A class of mycotoxins, aflatoxins, has been studied extensively because they have caused many deaths particularly in developing countries. Chili pepper is also prone to aflatoxin contamination during harvesting, production and storage periods. Chemical methods to detect aflatoxins are quite accurate but expensive and destructive in nature. Hyperspectral and multispectral imaging are becoming increasingly important for rapid and nondestructive testing for the presence of such contaminants. We propose a compact machine vision system based on hyperspectral imaging and machine learning for detection of aflatoxin contaminated chili peppers. We used the difference images of consecutive spectral bands along with individual band energies to classify chili peppers into aflatoxin contaminated and uncontaminated classes. Both UV and halogen illumination sources were used in the experiments. The significant bands that provide better discrimination were selected based on their neural network connection weights. Higher classification rates were achieved with fewer numbers of spectral bands. This selection scheme was compared with an information-theoretic approach and it demonstrated robust performance with higher classification accuracy.
Discontinuous Galerkin formulation for eddy‐current problems

Purpose – The purpose of this paper is to describe a method for solving eddy current problems. Discontinuous basis functions are applied to conducting regions in eddy‐current problems. This results in a block‐diagonal mass matrix allowing explicit time stepping without having to solve large algebraic systems.Design/methodology/approach – The effect of the basis functions in the conducting region is limited to the respective finite element. This yields to a block‐diagonal mass matrix, whereas each block in this matrix belongs to one finite element. In the nonconducting region, traditional finite elements are used which leads to well‐conditioned system matrices. For the two regions, different time steps are used.Findings – To avoid instability, a term which penalizes the tangential jump of the magnetic vector potential A has to be added. A value for weighting this term is suggested and tested on a simple two dimensional example.Originality/value – The proposed method leads to a potentially fast method for s.
Magnetoencephalography-theory, instrumentation, and applications to noninvasive studies of the working human brain

Magnetoencephalography (MEG) is a noninvasive technique for investigating neuronal activity in the living human brain. The time resolution of the method is better than 1 ms and the spatial discrimination is, under favorable circumstances, 2-3 mm for sources in the cerebral cortex. In MEG studies, the weak 10 fT-1 pT magnetic fields produced by electric currents flowing in neurons are measured with multichannel SQUID (superconducting quantum interference device) gradiometers. The sites in the cerebral cortex that are activated by a stimulus can be found from the detected magnetic-field distribution, provided that appropriate assumptions about the source render the solution of the inverse problem unique. Many interesting properties of the working human brain can be studied, including spontaneous activity and signal processing following external stimuli. For clinical purposes, determination of the locations of epileptic foci is of interest. The authors begin with a general introduction and a short discussion of the neural basis of MEG. The mathematical theory of the method is then explained in detail, followed by a thorough description of MEG instrumentation, data analysis, and practical construction of multi-SQUID devices. Finally, several MEG experiments performed in the authors' laboratory are described, covering studies of evoked responses and of spontaneous activity in both healthy and diseased brains. Many MEG studies by other groups are discussed briefly as well.
ANALYTICAL EXPRESSIONS FOR THE MAGNETIC FIELD OF PRACTICAL COILS

We present a set of new simple closed‐form analytical formulas for the calculation of the magnetic field produced at any point of space by any solid polyhedral conductor with a uniform current density j. The formulas have been obtained by analytical integration of Ampere's law under the only assumptions that the conductor is bounded by flat surfaces and that j = constant in the conductor. This includes bars, bricks, tetrahedrons, wedges, prisms, trapezoids, pyramids, and polyhedrons in general. The formulas contain no singularities, and can be used for the numerical calculation of the field at any point, including points inside the conductor, or on its surface, edges or corners. The formulas can easily be extended for conductors of infinite length. Extensive numerical tests of the formulas have been performed.
Detection of the (3, 0) Phillips band of interstellar C2 toward zeta Ophiuchi

Observations of C2 in the (3,O) band around 7720 A toward Zeta Ophiuchi are presented and used to provide additional support for the suggestion of a low temperature in the center of the principal cloud toward that star. Twelve absorption features belonging to the P, Q, and R branches and originating from levels up to J-double prime = 10 can be identified. Measured equivalent widths and the column densities obtained from them by assuming a linear relationship are presented. The column densities in the various rotational levels generally agree well with those found from observations of C2 in the (2,0) Phillips band around 8750 A. The observed C2 rotational distribution implies a low kinetic temperature of roughly 30 K and a relatively low but uncertain density of roughly 200/cm in the center of the cloud.
A particle-gridless hybrid method for incompressible flows

A particle–gridless hybrid method for the analysis of incompressible flows is presented. The numerical scheme consists of Lagrangian and Eulerian phases as in an arbitrary Lagrangian–Eulerian (ALE) method, where a new-time physical property at an arbitrary position is determined by introducing an artificial velocity. For the Lagrangian calculation, the moving-particle semi-implicit (MPS) method is used. Diffusion and pressure gradient terms of the Navier–Stokes equation are calculated using the particle interaction models of the MPS method. As an incompressible condition, divergence of velocity is used while the particle number density is kept constant in the MPS method. For the Eulerian calculation, an accurate and stable convection scheme is developed. This convection scheme is based on a flow directional local grid so that it can be applied to multi-dimensional convection problems easily. A two-dimensional pure convection problem is calculated and a more accurate and stable solution is obtained compared with other schemes. The particle–gridless hybrid method is applied to the analysis of sloshing problems. The amplitude and period of sloshing are predicted accurately by the present method. The range of the occurrence of self-induced sloshing predicted by the present method shows good agreement with the experimental data. Calculations have succeeded even for the higher injection velocity range, where the grid method fails to simulate. Copyright © 1999 John Wiley & Sons, Ltd.
Neotropical sisterhood: new species of Gyrodactylus von Nordmann, 1832 (Platyhelminthes: Monogenea) infecting Rhamdia guatemalensis and Rhamdia laticauda (Siluriformes: Heptapteridae) in Mexico

Abstract We describe two new species of monogenean parasites of the genus Gyrodactylus von Nordmann, 1832 infecting Neotropical catfishes (Siluriformes) in southern Mexico: Gyrodactylus chulini n. sp. from ‘chulín’, Rhamdia laticauda collected in Oaxaca; and Gyrodactylus juili n. sp. from ‘juil’, Rhamdia guatemalensis from Veracruz. Morphologically, both new taxa are similar to Gyrodactylus spp. infecting catfishes (Siluriformes) in South America. Sequences of the internal transcribed spacers (ITS1-5.8S–ITS2 rDNA), the D2+D3 domains of the large ribosomal subunit (28S rDNA) and the cytochrome oxidase II (COII) gene were obtained from multiple parasite specimens and analysed using Bayesian inference. Phylogenetic hypotheses using ITS rDNA and COII genes, recovered two new Gyrodactylus species from Rhamdia spp. : G. chulini n. sp. ; and Gyrodactylus juili n. sp. , which are sister species to Gyrodactylus lilianae, a parasite of Rhamdia quelen in Brazil, and show strong affinity to other gyrodactytlids infecting Neotropical catfishes. This suggests that these new taxa, the first gyrodactylids described from Rhamdia spp. in Mexico, co-migrated to Tropical Middle America with their Neotropical catfish hosts, after the emergence of the Isthmus of Panama.
Fabrication of Sub-Micron Period Surface Structures in LiNbO3

Sub-micron period reversed domain patterns are fabricated in congruent LiNbO 3 by using electric field overpoling. Slight wet etching of the domain engineered samples in HF solution generates surface relief structures faithfully reproducing the resist pattern geometries generated by holographic lithography. Moiré holographic lithography is also used to fabricate more complicated resist templates to be transferred onto the LiNbO 3 substrates as surface structures. A wide variety of structures is presented and discussed. The preliminary results show the possibility to use the fabricated structures for the realization of photonic crystal devices such as Bragg gratings, micro-ring resonators, etc. for telecom applications.
An isotope dilution-liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS)-based candidate reference measurement procedure (RMP) for the quantification of lamotrigine in human serum and plasma

Abstract Objectives We developed an isotope dilution (ID)-liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based candidate reference measurement procedure (RMP) for lamotrigine in human serum and plasma, using quantitative nuclear magnetic resonance-characterized reference standards to ensure traceability to the International System of Units. Methods A sample preparation protocol based on protein precipitation combined with LC-MS/MS analysis using a C18 column for chromatographic separation was established for the quantification of lamotrigine in human serum and plasma. Assay validation was performed according to current guidelines. Spiked serum and plasma samples were used to assess selectivity and specificity; a post-column infusion experiment and comparison of standard line slopes were performed to ascertain possible matrix effects. Precision and accuracy were determined in a 5 days validation experiment. Measurement uncertainty was determined per the Guide to the Expression of Uncertainty in Measurement. Results The method allowed the quantification of lamotrigine in serum and plasma in a range of 0.600–24.0 μg/mL without any observable matrix effects. The relative mean bias (n=6) ranged from 1.7 to 3.7%; intermediate precision, including variances in between-day, -calibration, and -injection, was ≤2.4%, independent of the level and matrix. Total measurement uncertainty for a single measurement was ≤2.6%; expanded uncertainty was ≤5.2% (coverage factor k=2). Conclusions This candidate RMP based on ID-LC-MS/MS provides a traceable and reliable platform for the standardization of routine assays and the evaluation of clinical samples.
A system of additive functional equations in complex Banach algebras

Abstract In this article, we solve the system of additive functional equations: 2 f ( x + y ) − g ( x ) = g ( y ) , g ( x + y ) − 2 f ( y − x ) = 4 f ( x ) \left\{\phantom{\rule[-1.25em]{}{0ex}}\begin{array}{l}2f\left(x+y)-g\left(x)=g(y),\\ g\left(x+y)-2f(y-x)=4f\left(x)\end{array}\right. and prove the Hyers-Ulam stability of the system of additive functional equations in complex Banach spaces. Furthermore, we prove the Hyers-Ulam stability of f f -hom-ders in Banach algebras.
Azimuth Calculation and Telecommunication between VR Headset and Smartphones for Nearby Interaction

This paper aims to break the boundary between VR and IoT devices by creating interactions between 2D screens and the 3D virtual environment. Since headsets are expensive and not accessible to everyone, we aim to create a lower boundary for people to take part in the VR world using their smartphones. Existing research mostly focuses on creating new haptic devices for VR, we instead leverage existing IoT devices that people already own, such as smartphones, to make VR technologies more accessible to multiple IoT users. There are two parts in our project: azimuth detection and communication between the VR environment and IoT devices.
Hedgehog: Detecting Drink Spiking on Wearables

People increasingly carry wearables and the capabilities of these devices have reached a point where it is increasingly possible to harness the devices to support everyday interactions. We contribute a new use of wearables by demonstrating how they can be used to safeguard against drink spiking, the deliberate act of adding substances to another person's drink. We design Hedgehog, a pervasive sensing approach that re-purposes the optical sensors in off-the-shelf wearables to identify spiked drinks by analysing differences in light reflectivity resulting from small particles inside the drink. We present a wearable prototype inspired by a smart ring design and conduct rigorous experiments that show the Hedgehog reaches up to 89.71% accuracy in detecting drinks that are tampered with. Our work demonstrates how pervasive sensing enables innovative applications and how smart wearables can be re-purposed to support personal safety.
The Effects of Using Poly-Universe on Computational Thinking in Biology and Physical Education

Today’s teaching and didactical methods are trying more and more to integrate digital technologies and computational thinking (CT) into other subjects. One way of combining and integrating these important skills and CT into all subjects, school levels, and school types is to include the game Poly-Universe (PolyUni). According to the results of the Poly-Universe in School Education (PUSE) study 2018, the game can be expected to have a positive effect on visual perceptual progress, including isolation and the development of shape-background skills. So far, however, comparatively few attempts have been made to explore the educational possibilities of PolyUni for different school levels and subjects, besides mathematics. This research explores how PolyUni can be used to promote CT and to evaluate whether the learning objectives in the subjects of physical education and biology have been achieved. Furthermore, it examines how PolyUni combines the requirements of the different curricula in secondary school, based on self-designed tasks. Additionally, further aspects PolyUni can promote besides the curriculum in secondary school are discussed. To explore the above-mentioned aspects, a mixed-methods study methodology was used. The participant observation method was employed for qualitative data collection, and a self-designed assessment grid and additional picture analysis were used for the quantitative data. The game was utilized in two workshops for biology and physical education at an Austrian secondary school, and fifty-six students were observed and analyzed. Based on the present data, it can be assumed that PolyUni helps to achieve the requirements of the curricula and pre-defined teaching and learning objectives in a playful way. Furthermore, the game not only promotes CT in secondary school but also encourages enjoyment and collaboration between peers in biology and physical education lessons.
Learning Channels to Support Interaction and Collaboration in CourseMapper

Massive Open Online Courses (MOOCs) have proved to be revolutionary in the development and widespread of educational technology over the past few years. It has been identified that these systems, despite all the benefits, lack interaction and collaboration around learning materials. This paper explores how to leverage learning channels to support interaction and collaboration in MOOC environments. We present the design, implementation, and evaluation details of learning channels in CourseMapper, a MOOC platform which supports collaboration and interaction around learning materials using collaborative Pdf and video annotations. More specifically, we report on the application and results of a human-centered design (HCD) approach used to systematically design learning channels. Three design iterations with five new users in each iteration (N=15) were conducted from an initial user interview to the final design. After the development, user experience with the system was evaluated with end users (N=10) based on the Technology Acceptance Model (TAM). The evaluation results show that the introduction of learning channels provides a valuable mechanism to support effective interaction and collaboration in a MOOC environment.
Atmospheric radiation and atmospheric humidity

This paper presents a report of some aspects of the effect of the dominant greenhouse gas in the earth's atmosphere, water vapour, on the radiative balance of the planet. Results from two satellite experiments which provide data on the concentration of water vapour in the upper and middle troposphere are presented. the first is the HALogen Occultation Experiment, HALOE, on the National Aeronautics and Space Administration Upper Atmosphere Research Satellite, for which retrievals of humidity have been made down to levels of about 150 hPa. These data reveal a number of interesting features in terms of the space and time variability of water vapour in the lower stratospherehpper troposphere. Comparison of HALOE measurements with the water vapour fields calculated in one general circulation climate model reveal substantial differences, which could significantly affect calculations of radiative balance. A second source of global data is the Television Infra‐red Observation Satellite's Operational Vertical Sounder, TOVS, which uses infrared vertical soundings. Considerable variability of upper tropospheric humidity is revealed by TOVS measurements, and an interesting relationship between brightness temperature and relative humidity, identified by other workers, is discussed. Sensitivity studies are presented of the effect on the outgoing‐radiation spectrum of varying the amount of water vapour throughout the troposphere. It is shown that uncertainties of only a few percent in knowledge of the humidity distribution in the atmosphere could produce changes to the outgoing spectrum of similar magnitude to that caused by doubling carbon dioxide in the atmosphere. Errors in the water vapour amounts generated in model simulations of the climate could, therefore, be significant in climate change calculations.