Miracle-dz/UniFAR-FTUs huggingface dataset:
A real-time image-processing-system-on-chip for security feature detection and classification

Nonlinear spatial transforms and fuzzy pattern classification with unimodal potential functions are already established in signal processing. They have proved to be excellent tools in feature extraction and classification. We propose an inspection method for pattern recognition and classification of two dimensional translation variant security elements such as stripes, kinegrams and others, which are widely used as applications in bank note printing. The system is based on discrete non linear translation invariant circular transforms and fuzzy pattern classification. Nonlinear discrete circular transforms are adaptable transforms, which can be optimized for different application tasks, such as translation variant object analysis and position location. They are mainly used as generators for feature vectors. Even though, the feature vector is theoretically translation invariant, the object movement creates a translation tolerant feature vector, because in real systems and applications many problems can occur, such as signal and optical distortions. Therefore, the features should be further analysed by a fuzzy pattern classifier. Implementation of the transforms and fuzzy pattern classifier in radix-2-structures is possible, allowing fast calculations with a computational complexity of O(N) up to O(Nld(N)). Furthermore, the algorithms can be implemented in one Field Programmable Gate Array (FPGA), which operates with 40 MHz clock rate.
Physical Properties of the Solar Magnetic Photosphere under the MISMA Hypothesis. II. Network and Internetwork Fields at the Disk Center

This paper is the second in a series that models photospheric magnetic structures in terms of atmospheres having optically thin fluctuations of magnetic field and thermodynamic state (the MISMA hypothesis). We apply an inversion procedure to the polarization of Fe I λ6301. 5 and Fe I λ6302. 5 observed in network and internetwork regions with the Advanced Stokes Polarimeter. Some 5200 independent spectra, comprising mildly asymmetric to very abnormal Stokes profiles, were reproduced by a single type of model atmosphere. It has three components, two that are magnetized and one that is not. A large fraction among the field strengths we measure are in the kG regime, but simulations suggest that the polarization of the observed Fe I lines weakens below detectable levels for fields substantially smaller than the observed ones. Synthesis of Stokes profiles of the IR Fe I λ15648. 5 line in MISMAs reveals the opposite behavior, i.e., an increase of polarization for sub-kG fields. The highly transparent MISMAs inferred from observations are significantly brighter in the continuum than an unmagnetized atmosphere. The mass of the magnetic structures tends to be at rest, although a minor fraction undergoes strong downflows. Downflows are also present in the nonmagnetic environment. A significant number of fitted Stokes profiles require opposite magnetic polarities within the same resolution element. The occurrence of mixed polarities increases with weakening degree of polarization, such that 25% of the weakest signals require mixed polarity. The weak polarization signals account for most of the total (unsigned) magnetic flux of the observed region. By extrapolation, this indicates that a significant fraction of photospheric magnetic flux remains undetected. The MISMA framework provides a unified and physically consistent scenario for interpretation of quiet Sun magnetism. Moreover, it is the only one available at present that is able to fit the abnormal Stokes profiles as revealed by the new generation of sensitive Stokes polarimeters.
Impact of land cover changes on Long‐Term Regional‐Scale groundwater recharge simulation in cold and humid climates

In cold and humid climates, warming temperatures will result in longer growing seasons, leading to land cover changes that could have long‐term impacts on groundwater recharge (GWR), in addition to the direct impacts of climate change. The objective of this study was therefore to investigate whether land cover (LC) changes need to be considered when simulating long‐term regional‐scale potential GWR in cold and humid climates by (1) quantifying how LC changes impact simulated GWR and (2) quantifying the combined impacts of LC and climate changes on the future GWR changes. Using the region of southern Quebec (Canada) as a case study and a water budget model, this work proposes an innovative coupling of land cover change scenarios and specific future climate conditions to simulate spatially distributed transient GWR over the 1951–2100 period. The results showed that including LC changes in long‐term GWR simulations produced statistically significant increases in GWR compared to using a constant LC through time (average of +13 mm). Massive afforestation taking place on agricultural lands simulated for one of the scenario chains (RCP4.5) increased GWR by reducing runoff during the snow‐dominated period (average − 17 mm). The results also showed that GWR was more sensitive to climate change for scenarios that included intense land cover changes. Additionally, the spatial distribution of the LC changes influenced their simulated impacts on GWR. Considering that the methodology was computationally feasible and entirely transferrable to the new CMIP6 ensemble, LC changes should be considered systematically in long‐term groundwater resources simulations.
Determining the Bending Rigidity of Free-Standing Planar Phospholipid Bilayers

We describe a method to determine membrane bending rigidity from capacitance measurements on large area, free-standing, planar, biomembranes. The bending rigidity of lipid membranes is an important biological mechanical property that is commonly optically measured in vesicles, but difficult to quantify in a planar, unsupported system. To accomplish this, we simultaneously image and apply an electric potential to free-standing, millimeter area, planar lipid bilayers composed of DOPC and DOPG phospholipids to measure the membrane Young’s (elasticity) modulus. The bilayer is then modeled as two adjacent thin elastic films to calculate bending rigidity from the electromechanical response of the membrane to the applied field. Using DOPC, we show that bending rigidities determined by this approach are in good agreement with the existing work using neutron spin echo on vesicles, atomic force spectroscopy on supported lipid bilayers, and micropipette aspiration of giant unilamellar vesicles. We study the effect of asymmetric calcium concentration on symmetric DOPC and DOPG membranes and quantify the resulting changes in bending rigidity. This platform offers the ability to create planar bilayers of controlled lipid composition and aqueous ionic environment, with the ability to asymmetrically alter both. We aim to leverage this high degree of compositional and environmental control, along with the capacity to measure physical properties, in the study of various biological processes in the future.
Market reaction to the Russian Ukrainian war: a global analysis of the banking industry

Purpose The purpose of this paper is to study the market reactions of the banking industry to the Russian–Ukraine war. Design/methodology/approach This paper uses an event study methodology, regression analyses and interaction effects to study the effect of the war on banks stock prices and analyze factors that explain the cumulative abnormal return. Findings First, this study finds a significant decline of almost 1.5% in return on the war date. Similar patterns were observed for all continents, but Europe had the most severe drop of about 4%. Second, after excluding the contemporaneous influence of the whole market using the market model, global bank equities returns fell by about 1% on the war date, indicating that bank stocks were more severely impacted by the war than the average stock market. Net-of-market return approach further reveals that bank stock prices decreased 1.4% more on the event day compared to the prewar market average. Third, the impacts of the war and sanctions were persistent when the war continued. Banks stocks were most hit in Europe, Asia and North America. Originality/value This paper pioneers the study of the effect of the Russia–Ukraine war on the banking industry. This paper also analyzes the reaction pattern of bank stocks before, during and after the war to explain the behavior and expectations of investors toward the war.
Airline brand image, passenger perceived value and loyalty towards full-service and low-cost carriers

Purpose This study aims to examine the mediating and moderating processes that link airline brand image to passenger loyalty through perceived value. Design/methodology/approach The research participants were Taiwanese passengers with experience travelling abroad by air. Structural equation modelling and multigroup analysis were used to investigate the effect of airline brand image and perceived value on the loyalty of passengers using full-service and low-cost carriers. Findings For both airline types, airline brand image had a significant and positive effect on passenger perceived value. Perceived value had a significant and positive effect on passenger loyalty, perceived value was a crucial mediator and airline type was not a key moderator in the model. Originality/value In this study, focusing on the perspective of Taiwanese passengers, a conceptual model of the factors that lead to passenger loyalty, with a focus on brand image, was developed. This paper contributes to the literature and application field by examining the mediating effect of perceived value and the moderating role of airline type in the aviation industry; on the basis of the results, potential recovery strategies for airlines in the post-COVID-19 era are provided.
Radio Jupiter after Voyager: An overview of the planetary radio astronomy observations

Jupiter's low frequency radio emission morphology as observed by the Planetary Radio Astronomy (PRA) instrument onboard the Voyager spacecraft is reviewed. The PRA measurement capabilities and limitations are summarized following over two years of experience with the instrument. As a direct consequence of the PRA spacecraft observations, unprecedented in terms of their sensitivity and frequency coverage, at least three previous unrecognized emission components were discovered: broadband and narrow band kilometric emission and the lesser arc decametric emission. Their properties are reviewed. In addition, the fundamental structure of the decameter and hectometer wavelength emission, which is believed to be almost exclusively in the form of complex but repeating arc structures in the frequency time domain, is described. Dramatic changes in the emission morphology of some components as a function of Sun-Jupiter-spacecraft angle (local time) are described. Finally, the PRA in suit measurements of the Io plasma torus hot to cold electron density and temperature ratios are summarized.
Lattice thermal resistivity of III–V compound alloys

Lattice thermal resistivities of III–V compound alloys have been analyzed with a theoretical prediction based on a simplified model of the alloy‐disorder scattering. The theoretical prediction shows a quite good agreement with the experimental data on various III–V ternary compounds. This model has also been applied to obtain the thermal resistivity of In1−x Gax Asy P1−y lattice‐matched to InP for the composition range of 0≤y≤1.0. The result indicates that the thermal resistivity increases markedly with alloying and exhibits a maximum value of about 24 W−1 deg cm at an alloying composition of y≂0.75.
On deceiving malware classification with section injection

We investigate how to modify executable files to deceive malware classification systems. This work’s main contribution is a methodology to inject bytes across a malware file randomly and use it both as an attack to decrease classification accuracy but also as a defensive method, augmenting the data available for training. It respects the operating system file format to make sure the malware will still execute after our injection and will not change its behavior. We reproduced five state-of-the-art malware classification approaches to evaluate our injection scheme: one based on Global Image Descriptor (GIST) + K-Nearest-Neighbors (KNN), three Convolutional Neural Network (CNN) variations and one Gated CNN. We performed our experiments on a public dataset with 9339 malware samples from 25 different families. Our results show that a mere increase of 7% in the malware size causes an accuracy drop between 25% and 40% for malware family classification. They show that an automatic malware classification system may not be as trustworthy as initially reported in the literature. We also evaluate using modified malware alongside the original ones to increase networks robustness against the mentioned attacks. The results show that a combination of reordering malware sections and injecting random data can improve the overall performance of the classification. All the code is publicly available.
Strengths and Limitations of a Single-Comparison, Alternate-Response (SCAR) Procedure for Establishing Uni- and Multi-Nodal Stimulus Equivalence Classes

Factors determining the yield of establishing stimulus equivalence (SE) classes by means of a single-comparison, alternate-response (SCAR) procedure were explored in a series of experiments. Training involved Pavlovian study phases alternating with response phases until a criterion of performance was attained: there was no trial-by-trial feedback. Factors studied included the explicitness of instructions, types of stimuli used, number of classes to be established, number of nodes, types of tests, exemplar training, and response to an opportunity to relearn. Instructions did not need to be so explicit with 12 or fewer classes as they had been in an earlier study with 48 classes; stimulus type was not critical; but the procedure gave low yields with 3-nodal compared with 1-nodal classes, even with only 3 such classes. Added exemplar training helped to increase yield, but this was still poorer than in an otherwise similar study in which a matching-to-sample (MTS) procedure was substituted for the alternate response requirement. A key distinction may lie in the ambiguity of the alternate response requirement in contrast with the implicit rule in MTS that one of the stimuli present in the comparison array must be correct.
Codetections of Other Respiratory Viruses Among Children Hospitalized With COVID-19.

OBJECTIVES To assess the clinical impact of respiratory virus codetections among children hospitalized with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. METHODS During March 2020 to February 2022, the US coronavirus disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET) identified 4372 children hospitalized with SARS-CoV-2 infection admitted primarily for fever, respiratory illness, or presumed COVID-19. We compared demographics, clinical features, and outcomes between those with and without codetections who had any non-SARS-CoV-2 virus testing. Among a subgroup of 1670 children with complete additional viral testing, we described the association between presence of codetections and severe respiratory illness using age-stratified multivariable logistic regression models. RESULTS Among 4372 children hospitalized, 62% had non-SARS-CoV-2 respiratory virus testing, of which 21% had a codetection. Children with codetections were more likely to be <5 years old (yo), receive increased oxygen support, or be admitted to the ICU (P < .001). Among children <5 yo, having any viral codetection (<2 yo: adjusted odds ratio [aOR] 2.1 [95% confidence interval [CI] 1.5-3.0]; 2-4 yo: aOR 1.9 [95% CI 1.2-3.1]) or rhinovirus/enterovirus codetection (<2 yo: aOR 2.4 [95% CI 1.6-3.7]; 2-4: aOR 2.4 [95% CI 1.2-4.6]) was significantly associated with severe illness. Among children <2 yo, respiratory syncytial virus (RSV) codetections were also significantly associated with severe illness (aOR 1.9 [95% CI 1.3-2.9]). No significant associations were seen among children ≥5 yo. CONCLUSIONS Respiratory virus codetections, including RSV and rhinovirus/enterovirus, may increase illness severity among children <5 yo hospitalized with SARS-CoV-2 infection.
Applied multiple regression/correlation analysis for the behavioral sciences

Contents: Preface. Introduction. Bivariate Correlation and Regression. Multiple Regression/Correlation With Two or More Independent Variables. Data Visualization, Exploration, and Assumption Checking: Diagnosing and Solving Regression Problems I. Data-Analytic Strategies Using Multiple Regression/Correlation. Quantitative Scales, Curvilinear Relationships, and Transformations. Interactions Among Continuous Variables. Categorical or Nominal Independent Variables. Interactions With Categorical Variables. Outliers and Multicollinearity: Diagnosing and Solving Regression Problems II. Missing Data. Multiple Regression/Correlation and Causal Models. Alternative Regression Models: Logistic, Poisson Regression, and the Generalized Linear Model. Random Coefficient Regression and Multilevel Models. Longitudinal Regression Methods. Multiple Dependent Variables: Set Correlation. Appendices: The Mathematical Basis for Multiple Regression/Correlation and Identification of the Inverse Matrix Elements. Determination of the Inverse Matrix and Applications Thereof.
Effect of Heat Conduction of SnS-Cu x S Solar Control Coated Semitransparent Wall on Turbulent Natural Convection in a Square Cavity

Interaction effects of semitransparent glazing with SnS-Cu x S solar control coating on the turbulent natural convection in a square cavity containing air is analyzed numerically. The size of the cavity covers a range from 0.70 to 6.98 m (Ra = 109–1012). One vertical wall of the cavity is isothermal, and the opposite one is the semitransparent glazing. Top and bottom walls are adiabatic. The 2-D mass, momentum, and energy equations using the turbulent k– ϵ model are solved by the finite-volume technique. The model is verified, reducing the problem to a differentially heated square cavity and indicating very good agreement. The isotherms, turbulent viscosity distributions, temperatures of the interior and exterior surfaces of the glazing with solar control coating (SCCG) and without solar control coating (WSCCG) for the 6.98-m cavity are presented. The average semitransparent wall temperatures were 64°C for SCCG and 40°C for WSCCG. The Nusselt numbers for SCCG and WSCCG versus the length of the cavity show that the difference is a range of 17% to 22%. Correlations for the average Nusselt numbers for steady state are presented for 0.70 m ≤ W ≤ 6.98 m and Pr = 0.71. The solar heat gain coefficient SHGC indicates that for the glazing with SnS-Cu x S solar control coating, the energy gain toward the interior decreases by 48.8%.
Mach 6 Wake Flow Simulations Using a Large-Eddy Simulation/Reynolds-Averaged Navier–Stokes Model

A hybrid large-eddy simulation/Reynolds-averaged Navier–Stokes turbulence model is used to simulate the Mach 6 flow around a scaled model similar to NASA’s Orion multipurpose crew vehicle. The results for surface pressure and heat transfer are compared with experimental data from previous base flow experiments conducted at the Calspan—University at Buffalo Research Center. Using the highest Reynolds number test case (11×106 based on capsule diameter), different numerical aspects of the hybrid approach are addressed, such as use of a low-dissipation scheme, a modification to the eddy-viscosity blending function, time-averaging results, filtering computational results, and sensitivity to grid resolution. In addition, results are compared with Reynolds-Averaged Navier–Stokes using Menter’s two-equation baseline model and to detached-eddy simulation predictions. By introducing a new modification to the blending from Reynolds-averaged Navier–Stokes to large-eddy simulation within boundary layers, very good agr.
Neutron-capture cross-sections of 244Cm and 246Cm measured with an array of large germanium detectors in the ANNRI at J-PARC/MLF

The neutron neutron-capture cross cross-sections of 244Cm and 246Cm were measured by the time-of-flight method in the energy range of 1–300 300 eV with an array of large germanium detectors in the Accurate Neutron-Nucleus Reaction measurement InstrumentANNRI at Material and Life Science Experimental Facility (MLF) of the Japan Proton Accelerator Research ComplexJ-PARC/MLF. The 244Cm resonances at around 7.7 and 16.8 8 eV and the 246Cm resonances at around 4.3 and 15.3 3 eV were observed in the capture reactions for the first time. The uncertainties of the obtained cross cross-sections are 5.8% at the top of the first resonance of 244Cm and 6.6% at that of 246Cm. The rResonance analyses were performed for low-energy ones using the code SAMMY. The prompt γ-ray spectra of 244Cm and 246Cm were also obtained. Eight and five new prompt γ-ray emissions were observed in the 244Cm(n, γ) and 246Cm(n, γ) reactions, respectively.
Relationship between Reaction Times and Post-COVID-19 Symptoms Assessed by a Web-Based Visual Detection Task

Long-COVID is a clinical condition in which patients affected by SARS-CoV-2 usually report a wide range of physical and cognitive symptoms from 3 to 6 months after the infection recovery. The aim of the current study was to assess the link between self-reported long-COVID symptoms and reaction times (RTs) in a self-administered Visual Detection Task (VDT) in order to identify the predictor symptoms of the slowing in reaction times to determine attention impairment. In total, 362 participants (age (mean ± S.D.: 38.56 ± 13.14); sex (female–male: 73.76–26.24%)) responded to a web-based self-report questionnaire consisting of four sections: demographics, disease-related characteristics, and medical history questions. The final section consisted of a 23 item 5-point Likert-scale questionnaire related to long-term COVID-19 symptoms. After completing the questionnaire, subjects performed a VDT on a tablet screen to assess reaction times (RTs). An exploratory factorial analysis (EFA) was performed on the 23 long-COVID symptom questions, identifying 4 factors (cognition, behavior, physical condition, presence of anosmia and/or ageusia). The most important predictors of RTs were cognition and physical factors. By dissecting the cognitive and physical factors, learning, visual impairment, and headache were the top predictors of subjects’ performance in the VDT. Long-COVID subjects showed higher RTs in the VDT after a considerable time post-disease, suggesting the presence of an attention deficit disorder. Attention impairment due to COVID-19 can be due to the presence of headaches, visual impairments, and the presence of cognitive problems related to the difficulty in learning new activities. The link between the slowing of reaction times and physical and cognitive symptoms post-COVID-19 suggests that attention deficit disorder is caused by a complex interaction between physical and cognitive symptoms. In addition, the study provides evidence that RTs in a VDT represent a reliable measure to detect the presence of long-COVID neurological sequelae.
Periodic intensity variation in [SIII] 9531A emission from the Jupiter plasma torus

The intensity variation of [SIII] 9531 A line emission from the hot plasma torus of Jupiter was measured from Kitt Peak National Observatory during April 1982 using a scanning Fabry-Perot spectrometer with a field of view 2 RJ in diameter centered at 6 RJ on the centrifugal equator. During the observational period, which covered 43 rotations of Jupiter, the intensities showed a periodic variation consistent with a zone of enhanced emission approximately 90° in longitude rotating with a period of 10.2 hours, or 2.8% longer than Jupiter' rotational period.