Miracle-dz/UniFAR-FTUs huggingface dataset:
Explainable Deep Learning for Medical Imaging Models Through Class Specific Semantic Dictionaries

Explainability is important in the design and deployment of neural networks. It allows engineers to design better models and can give end-users an improved understanding of the outputs. However, many explainability methods are unsuited to the domain of medical imaging. Saliency mapping methods only describe what regions of an input image contributed to the output, but don't explain the important visual features within those regions. Feature visualization methods have not yet been useful in the domain of medical imaging due to the visual complexity of images generally resulting in un-interpretable features. In this work, we propose a novel explainability technique called “Class Specific Semantic Dictionaries”. This extends saliency mapping and feature visualisation methods to enable the analysis of neural network decision-making in the context of medical image diagnosis. By utilising gradient information from the fully connected layers, our approach is able to give insight into the channels deemed important by the network for the diagnosis of each particular disease. The important channels for a class are contextualised by showing the highly activating examples from the training data, providing an understanding of the learned features through example. The explainability techniques are combined into a single User Interface (UI) to streamline the evaluation of neural networks. To demonstrate how our new method overcomes the explainability challenges of medical imaging models we analyse COVID-Net, an open source convolutional neural network for diagnosing COVID-19 from chest x-rays. We present evidence that, despite achieving 96.3% accuracy on the test data, COVID-Net uses confounding variables not indicative of underlying disease to discriminate between COVID-Positive and COVID-Negative patients and may not generalise well on new data.
Digitization technologies in transport logistics: A systematic literature review protocol

The trend toward a greater proportion of digitization technologies in use can also be seen in the area of transport logistics. Currently, however, digitization technologies in transport logistics are predominantly represented by telematics systems that record vehicle-related data and transmit them via corresponding communication technologies. At the level of the loaded goods, for example, there is a comparatively smaller proportion of digitization technologies in use, which results in a lower degree of process transparency. The industry is characterized by a very heterogeneous technology landscape and application-specific processes. As a result, there is no deep and comprehensive understanding of already deployed and additionally suitable digitization technologies in transportation logistics. In order to generally outline a specific research field thematically, systematic literature reviews (SLR) are used, as their purpose is to compile and highlight the scientific findings to date. This article presents a research protocol that describes the methodological procedure for conducting an appropriate systematic literature review in order to accommodate the necessary scientific rigor. The research protocol precedes the systematic literature review in order to describe the state of research regarding deployed and additionally suitable digitization technologies within transportation logistics.
Daytime traveling ionospheric disturbances observed at L ≈ 4.5 in western Quebec with rapid‐run ionosondes

Daytime traveling ionospheric disturbances (TIDs) are studied with a close-spaced triangulation network of rapid-run ionosondes. Observations in November and March (1985–1986) found disturbances traveling only southward, with a clockwise progression during the day from southeastward to southwestward. Further observations in May and August (1987) found travel in all directions with no apparent order or progression. These observations are contrary to earlier results in May (1982), using a wider-spaced network in northern New England together with a chain of single stations extending northward, in which source locations appeared to be bracketed between the northern stations with waves traveling northward as well as southward from those sources. These results suggest possible seasonal control but, at present, still leave as a quandary the question of what and where the sources are. With new digital equipment it is planned to obtain longer time series of observations and the vertical component of the propagation vector. With the latter and the horizontal component the vertical inclination of the phase fronts can be obtained and they in turn can be tracked backward to source regions at any given height.
Detection of Depression from IoMT Time Series Data using UMAP features

Depression is the most serious and prevalent public health problem that has led to an increase in suicidal risks, suicidal ideations, and much more impact on family relations. A diagnosis of mental health problems lacks a direct quantitative test. Conventionally experts evaluate the symptoms and signs through patient interviews or questionnaires. Data generated by wearable IoMT devices (e.g. wrist actigraph) provides an efficient objective way to diagnose depression and related mental health problems in the early stages. In this paper, we propose UMAP (Uniform Manifold Approximation and Projection) based feature extraction and neural network classifier for depression detection (both Unipolar and bipolar disorders) from IoMT (Internet of Medical Things) data (Depresjon Dataset). The classification of depression from 24-hour motor activity data shows a sensitivity of 96.257% and a specificity of 98.50%.
A Hybrid Vision Transformer Approach for Mathematical Expression Recognition

Mathematical expression recognition is one of the important processes in scientific documents analysis. Despite the importance of this task, solving mathematical expression recognition is still very challenging. One of the reasons for the difficulty of math recognition compared to normal text recognition is that math formula usually has 2-D spatial structure relationship [1] instead of 1-D ones from normal text data. The spatial structure relationship of math formula is presented by many math symbols such as superscript, subscript, fraction symbol, etc. The traditional approach usually solves this problem in two stages. First, the character segmentation stage is used to segment each character in math formula and then classify it based on the given vocabulary. Second, the structural analysis stage is used to identify the spatial relationships between all characters of the math formula.
Electromagnetic scattering from an infinite circular metallic cylinder coated by an elliptic dielectric one

The scattering from an infinite, circular, perfectly conducting cylinder coated by an elliptic dielectric cylinder is considered. The electromagnetic field is expressed in terms of both circular and elliptical cylindrical wave functions, which are connected with one another by well-known expansion formulas. In the special case of small h=ka/2 (a is the interfocal distance of the elliptic dielectric and k its wavenumber), exact, closed-form expressions of the form S(h)=S(0)(1+gh/sup 2/+O(h/sup 4/)) are obtained for the scattered field and the various scattering cross sections. Both polarizations are considered for normal incidence. Graphical results for various values of the parameters are given. >
Pressure-induced phase transformation of In2Se3

In2Se3 has potential as a phase-change material for memory applications. Understanding its phase diagram is important to achieve controlled switching between phases. Using x-ray diffraction and a diamond-anvil cell, the pressure-dependent structural properties of In2Se3 powder were studied at room temperature. α-In2Se3 transforms into the β phase at 0.7 GPa, an order of magnitude lower than phase-transition critical pressures in typical semiconductors. The β phase persists upon decompression to ambient pressure. Raman spectroscopy experiments confirm this result. The bulk moduli are reported and the c/a ratio for the β phase is shown to have a highly nonlinear dependence on pressure.
Position measurement with a resolution and noise‐limited instrument

A common problem in experimental data analysis is to locate the position of a signal to an accuracy which is substantially less than the actual signal width. By applying maximum likelihood estimation to this problem, this paper derives theoretical limits on the ability to locate signal position. The limiting error in position measurement is shown to be a simple function of the instrument resolution, the density of sample points, and the signal‐to‐noise ratio of the data. An interesting conclusion is that position information on a much finer scale than the minimum instrument sampling interval is contained in data of modest signal‐to‐noise ratio. The common procedure of excluding the portion of the data lying below an amplitude threshold to guard against background fluctuations is incorporated in the maximum likelihood analysis. It is shown that selection of the optimum amplitude threshold level depends on the type of noise present in the data, and can be an important factor in position accuracy. The analyt.
Spectroscopic and polarimetric observations of NGC 1333 and the surrounding dark cloud complex

Spectroscopy and polarimetry of several very red stars, noted on Near Infrared Photographic Sky Survey photographs in the region of NGC 1333, have yielded a ''map'' suggesting the extent of polarization arising from a two-cloud structure in the region. Spectral types and color indices of the stars allow us to infer that grain radii in the clouds exceed typical interstellar medium values and, further, that they increase with optical depth into the cloud. Our observations indicate that the cloud structure is far more extensive than previously realized.
Moisture Origin and Meridional Transport in Atmospheric Rivers and Their Association with Multiple Cyclones

AbstractDuring December 2006 many cyclones traveled across the North Atlantic, causing temperature and precipitation in Norway to be well above average. Large excursions of high vertically integrated water vapor, often referred to as atmospheric rivers, reached from the subtropics to high latitudes, inducing precipitation over western Scandinavia. The sources and transport of atmospheric water vapor in the North Atlantic storm track during that month are examined by means of a mesoscale model fitted with water vapor tracers. Decomposition of the modeled total water vapor field into numerical water vapor tracers tagged by evaporation latitude shows that when an atmospheric river was present, a higher fraction of water vapor from remote, southerly source regions caused more intense precipitation. The tracer transport analysis revealed that the atmospheric rivers were composed of a sequence of meridional excursions of water vapor, in close correspondence with the upper-level flow configuration. In cyclone co.
Raman Scattering by Bulk Phonons in Microcrystalline Silver and Copper via Electronic Surface Excitations

In Raman scattering from cryocondensed metal films one observes the bulk acoustic phonons. This is not caused by the laser field which penetrates the metal, but via the scattering of optically excited intrasurface band electron hole pairs by the phonons. Phonons with wave vector $\mathbf{Q}$ contribute to the Raman signal according to the scattering probability $S(\mathbf{q})$ of the image states by surface roughness, where $\mathbf{q}$ is the projection of $\mathbf{Q}$ onto the low index facets having occupied electronic surface states, in the present case mainly of (111) orientation.
Empirical mode decomposition and long-range correlation analysis of sunspot time series

Sunspots, which are the best known and most variable features of the solar surface, affect our planet in many ways. The number of sunspots during a period of time is highly variable and arouses strong research interest. When multifractal detrended fluctuation analysis (MF-DFA) is employed to study the fractal properties and long-range correlation of the sunspot series, some spurious crossover points might appear because of the periodic and quasi-periodic trends in the series. However many cycles of solar activities can be reflected by the sunspot time series. The 11-year cycle is perhaps the most famous cycle of the sunspot activity. These cycles pose problems for the investigation of the scaling behavior of sunspot time series. Using different methods to handle the 11-year cycle generally creates totally different results. Using MF-DFA, Movahed and co-workers employed Fourier truncation to deal with the 11-year cycle and found that the series is long-range anti-correlated with a Hurst exponent, H, of about 0.12. However, Hu and co-workers proposed an adaptive detrending method for the MF-DFA and discovered long-range correlation characterized by H≈0.74. In an attempt to get to the bottom of the problem in the present paper, empirical mode decomposition (EMD), a data-driven adaptive method, is applied to first extract the components with different dominant frequencies. MF-DFA is then employed to study the long-range correlation of the sunspot time series under the influence of these components. On removing the effects of these periods, the natural long-range correlation of the sunspot time series can be revealed. With the removal of the 11-year cycle, a crossover point located at around 60 months is discovered to be a reasonable point separating two different time scale ranges, H≈0.72 and H≈1.49. And on removing all cycles longer than 11 years, we have H≈0.69 and H≈0.28. The three cycle-removing methods—Fourier truncation, adaptive detrending and the proposed EMD-based method—are further compared, and possible reasons for the different results are given. Two numerical experiments are designed for quantitatively evaluating the performances of these three methods in removing periodic trends with inexact/exact cycles and in detecting the possible crossover points.
Climate as a Result of the Earth Heat Reflection

Climate as a Result of the Earth Heat Reflection The authors show that the mean global temperature - and, therefore, climate - is determined mainly by the reflected portion of the total heat received from the Sun. The heat reflected directly by infra-red radiation is insufficient for maintenance of the temperature necessary for the Earth life, since it is limited by absorption windows created by green-house gases (mainly water molecules). The deficient heat is transported by a strong vertical convective air stream - a component of the total air circulation. This heat - limited only by Newton's law - is delivered to the upper troposphere layers not containing water molecules, from where it is dissipated, practically unlimitedly, at the infra-red radiation wavelengths corresponding to cooled media. The convection, in compliance with Newton's law, creates a negative feedback, which stabilizes the processes of temperature changes on the Earth reducing them by half. Klimats Kā Zemes Siltuma Nodošanas Faktors Darbā parādīts, ka Zemes vidējo temperatūru un, tātad, klimatu, nosaka galvenokārt Saules saņemtā siltuma atstarošanas apjoms. Siltums, kas tiek atstarots tieši ar radiāciju caur troposfēru ir nepietiekošs Zemes dzīvei nepieciešamās temperatūras uzturēšanai, jo to ierobežo siltumnīcas gāzu radīti (galvenokārt ūdens molekulu) absorbcijas logi. Nepietiekošais siltums tiek atdots ar vispārējās gaisa cirkulācijas sastāvdałas - stiprām vertikālām konvekcijas gaisa plūsmām. Tās siltumu, ierobežotu tikai ar Ņūtona likumu, nogādā uz ūdens molekulu nesaturošiem augšējiem troposfēras slāņiem, no kurienes tas ar atdzisušai videi atbilstošiem infrasarkanā starojuma viłņu garumiem tiek praktiski neierobežoti izkliedēts. Konvekcija, kas pateicoties Ņūtona likumam rada negatīvu atgriezenisko saiti, stabilizē Zemes temperatūras izmaiņas procesu, divkārši samazinot tās izmainās apmērus.
Vacuum arc cathode spot grouping and motion in magnetic fields

Two of the important vacuum arc phenomena observed when the arc runs in a transverse magnetic field are cathode spot grouping and the cathode spot retrograde motion, i.e., in the anti-Amperian direction. This paper summarizes the main experimental observations and proposes a physical model for spot grouping and spot retrograde motion. The proposed spot motion model take in account the previous theoretical model of the cathode thermal regime and the plasma flow near the cathode surface that is based on two conditions: i) the heat loss in the cathode bulk is relatively small to the heat influx, and ii) the plasma flow in the Knudsen layer is impeded. In the present model, the current per group spot is calculated by assuming that the plasma kinetic pressure is comparable to the self-magnetic pressure in the acceleration region of cathode plasma jet. The model includes equations for the current per spot group, spot velocity dependence on the magnetic field and on the arc current in vacuum, as well as in gas filled arc gap. The calculated currents per spot group and spot velocity increase linearly with the magnetic field and arc current, and this dependencies well agree with previous observations. The cathode spot retrograde motion in short electrode gaps and at atmospheric pressure arcs, and the reversal motion in strong magnetic fields (>1 T) observed by Robson and Engel are discussed. The details of the retrograde motion observed in the last decades including the spot velocity dependence on the electrode gap, roughness, temperature, and material could be understood in the frame of the proposed model.
Relative entropy of grayscale images degraded by bit-plane quantization and random noise

This paper presents an experimental study of the relative entropy of grayscale images degraded by bit-quantization and additive random noise. Bit-plane quantization is produced by removing any number of selected bit-planes from a given grayscale image, whereas noise is modeled additively using impulse, uniform, Gaussian, Poisson, and Cauchy probability density functions. A comparison of the behavior of relative entropy with other image measures such as the normalized mean square error, the signal-to-noise ratio, and the correlation coefficient is also given for different levels of bit-plane quantization and parameter values of the aforementioned noise probability density functions. An illustrative example is provided together with characteristic graphs that demonstrate quantitatively the overall discrimination capability performed by the relative entropy measure.
An entropy estimator with least square error [biological signals]

Presents a new entropy estimator which minimizes mean squared error between its estimate and true entropy. It uses a new entropy function approximated by a polynomial when an information source outputs two kinds of source symbols independently. In conventional entropy estimation, entropy has been estimated by replacing true occurrence probabilities of each source symbol in the entropy function with their estimates. In this case, the entropy estimator is not optimum in the meaning of least square error. This article demonstrates that the proposed entropy estimator achieves excellent mean squared error compared to a conventional entropy estimator.
Chemical definition of the mesospheric polar vortex

We present a simple chemical definition to demark the edge of the mesospheric polar vortices. Because this vortex definition does not rely on the wind field, it is useful in the mesosphere where wind observations are sparse and reanalysis winds are unreliable. The chemical definition is also insensitive to double jets that complicate vortex identification in the mesosphere. The algorithm is based on horizontal gradients of carbon monoxide (CO) and mirrors the widely used vortex edge definition in the stratosphere based on potential vorticity (PV) gradients. Here the approach is used to identify the Arctic vortex in the mesosphere during a 10 year (2004–2014) record of Microwave Limb Sounder data. Vortex size and shape comparisons are made where the CO and PV methods overlap in the upper stratosphere. A case study is presented during the NH 2008–2009 winter that demonstrates the fidelity of the CO gradient method on individual days and emphasizes the impact of double jets on methods to identify the polar vortex. We recommend transitioning from a PV or stream function‐based vortex definition in the stratosphere to using a CO gradient definition above 0.1 hPa (~60 km). The CO gradient method identifies a coherent region of high CO at 80 km that is confined to mid‐to‐high latitudes 99.8% of the time during Arctic winter. Taking advantage of the CO gradient method to identify the polar vortex adds ~20 km of reliable vortex information (from 60 to 80 km) in a region of the atmosphere where reanalyses are most suspect.
Non-Gaussian initial conditions in cosmological N-body simulations. II, Cold Dark Matter models

Results are reported on N-body simulations of the large-scale structure of the Universe starting from non-Gaussian initial conditions in a cold dark matter cosmogony. Three multiplicative models are condidered where the peculiar gravitational potential is obtained by performing a non-linear transformation on a Gaussian random field: while keeping the standard form for the initial power spectrum, this procedure provides highly non-random phases. The resulting distributions in space and velocity are analysed by different statistical tests and compared with the evolution of a standard Gaussian model with the same initial amplitude.
Temporal study of long-pulse relativistic magnetron operation

A streak camera was used to make observations of apparent plasma motion in the interaction space of an A6 relativistic magnetron with an explosive emission cathode. The anode plasma luminosity velocity was measured to be 0.8 cm/ mu s, comparable with the gap closure velocity, which was indirectly measured to be 1.0-1.6 cm/ mu s, depending upon the magnetic field. The gap closure velocity appeared to be independent of the microwave oscillation. Long-pulse operation (hundreds of nanoseconds) as a function of the magnetron-modulator interaction is also presented. At 250 kV the A6 emitted microwave pulses out of a single resonator for up to 250 ns in duration, with peak power up to 90 MW and a characteristic single-spike pulse length of 150 ns. >
Highly Accurate 3-D Position Measurement and Non-Linear Coordinate Transformation

An important preprocess in computer vision is to measure the position of an object and to eradicate lens distortion which hampers the recognition of an object from its image. At first, the slit-ray projection method is investigated and some ideas for increasing measurement accuracy are proposed. A regression to normal distribution is achieved by the least squares method for the pixel positions and their intensities. Because of this, the slit-ray center position can be determined with a high accuracy of 0.05 pixel. A method for correcting the distortion of the slit-ray intensity caused by non-uniform reflection is described. It involves compensating the intensity on the basis of a uniform reference light. Optimum measurement conditions for the slit-ray width and the regression range are obtained by examining the relation between intensity fluctuations and measurement error. In order to increase 3-D measurement accuracy, methods for calibrating various parameters are described. Next, by combining three ideas, i.e., the reference of the shift quantities, the en bloc processing of pixel groups and the separation of the transformation into two directions, non-linear coordinate transformation time is reduced. This is effective for the speedy correction of image distortion.