Miracle-dz/UniFAR-FTUs huggingface dataset:
IgG-Dependent Dismutation of Superoxide in Patients with Different Types of Multiple Sclerosis and Healthy Subjects

This work is the first to demonstrate that class G immunoglobulins (IgGs) in patients with multiple sclerosis and healthy individuals have the ability to catalyze the dismutation reaction of the superoxide anion radical. Thus, superoxide dismutase (SOD) activity is an intrinsic property of antibodies, which is confirmed by a number of stringent criteria. SOD activity of IgGs in patients with multiple sclerosis statistically significantly exceeds such activity in healthy individuals by 2-4 times. Moreover, the maximum activity has been registered in patients with relapsing remitting multiple sclerosis. The kinetic characteristics of the SOD reaction of IgGs are several orders of magnitude lower than those for the SOD enzyme but do not differ between patients with multiple sclerosis and healthy individuals. Consequently, abzymes with SOD activity have a lower catalysis rate than that of the enzymes and form a stronger complex with the substrates. Inhibitory analysis showed that this activity is inhibited by classical metal-dependent SOD inhibitors. The activity of IgGs was inhibited by classical metal-dependent inhibitors EDTA and TETA (triethylenetetramine). Also, high catalase activity of IgGs was detected in these patients. We suggest that these abzymes help protect the body from oxidative stress.
Compliance and Performance Analysis of Procurement Processes Using Process Mining

Procurement processes are essential part of the value chain of an organization to provide services and products. A regular analysis and optimization of these processes is beneficial for companies to increase quality, reduce costs, and identify process risks. Process mining techniques provide insights into the common flows of activities, detect deviations and compliance issues, and report process performance. In this paper, we present the analysis and evaluation of procurement processes of a company in the area of coatings and paints from the Netherlands. Applying filtering and discovering techniques, the paper presents six process models for handling different types of purchase orders. In addition, deviations of these flows and compliance violations, their frequencies, and root causes are described. Finally, key performance indicators regarding throughput time are defined and measured.
Temporary Contracts and Workers’ Satisfaction

Fixed-term contracts are often considered a key policy tool for increasing employment. As we show that contract limitation lowers job satisfaction using data from the German SocioEconomic Panel study, we detect a drawback of promoting temporary employment that has not been identified so far. We find that the “honeymoon-hangover” effect of a new job must be taken into account to reveal this result. We examine reasons why employees suffer from temporary contracts and analyse the “Flexicurity” idea of compensating workers with security. Our findings contribute to research on workers’ well-being as well as to the debate on labour market flexibilisation. JEL Classification: J28, J41
Image-based change detection to reduce false alarms in the Vision1200 synthetic aperture sonar

High-resolution synthetic aperture sonar (SAS) images were processed from a NATO change detection (CD) trial in 2014. An automatic CD processing chain was implemented, consisting of normalization, filtering, coarse registration, fine registration and sub-pixel registration. Various algorithms and parametrizations were used at the different steps in order to determine the best processing chain. Detection quality was determined using Receiver Operating Characteristic (ROC) curves for all combinations. The best CD processing chain was able to reduce the false alarm rate by up to 40 times as compared to conventional detection.
Influences of Salinity, Light and Temperature on Seed Germination of Leucaena leucocephala (Lam.) de Wit

The experiment was investigated to study evaluate the seed germination of Leucaena leucocephala (Lam.) de Wit. under salinity, temperature, light and their interaction on the rate and final percentage of germination. The experiment was carried out in plant physiology laboratory at College of Science, King Saud University, Riyadh, Saudi Arabia. The collected seeds of Leucaena was treated with boiling water for 3 minutes then left to germinate in Petri dishes in growth chamber under the investigated treatments. Seven concentrations of sodium chloride solution had EC of (0, 50, 100, 300, 400, 500 and 600 mM) were applied to seeds as irrigation water and exposed to three temperature degree (20, 30 and 40 C). Seeds untreated with NaCl germinated well in a wide range of temperatures and in both full light and complete dark. Seed germination decreased significantly with the increase in both NaCl concentration and temperature. Optimal germination percentage occurred at 30 C. The inhibitory effect of high salinity on final germination percentage was greater at 40 C than at 20 and 30 C. However, germination rate was significantly greater at 40 C than at 20 and 30 C in lower salinity and the reverse was true at higher salinity. Germination in light was significantly greater than in the dark at lower salinity levels and high temperature.
Livestock Brucellosis: Frequency of Mutations Causing Resistance to Fluoroquinolone, Streptomycin and Rifampin

Background: Malta fever caused by the Brucella spp. is an endemic zoonotic infectious disease in Iran. Evaluation of the disease control is essential for socioeconomic and public health-related concerns. Objectives: This study aimed to evaluate the prevalence of Brucella spp. and the frequency of mutations responsible for resistance to rifampin, streptomycin, and fluoroquinolones in sheep from Mianeh, Southwest of West Azarbaijan Province, Iran. Methods: A total number of 1,220 blood samples were collected in Mianeh. Positive samples screened using Rose Bengal Plate Test (RBPT) were subjected to Polymerase Chain Reaction (PCR). Finally, positive samples were investigated for the presence of mutated aminoglycoside adenylyl-transferase-A1 (aadA1) (conventional PCR), DNA gyrase subunit A (gyrA), topoisomerase IV subunit C (parC) (MAMA PCR for both) and RNA polymerase β-subunit (rpoB) (MAS PCR) responsible for antibiotic resistance. Results: There were 41 Brucella abortus Cell Surface Protein 31 Positive (BCSP31+) samples out of 111 RBPT positive samples which 15% (n = 7) of them were obtained from vaccinated sheep. Of the total BCSP31+ samples 9 were carrying mutated aadA1, 3 carrying mutated parC and only one sample carrying mutated rpoB. None of the samples were positive for mutated gyrA. Conclusions: The prevalence of Brucellosis in livestock in the city of Mianeh has been higher than in other areas in Iran, and some antibiotic resistance genes have been identified in livestock specimens. It can be concluded that due to the relatively good efficacy of the vaccines, the need for vaccination in all livestock farms of this city is important.
The USTC-iFlytek System For CHiME-4 Challenge

The submitted system for CHiME-4 this year includes significant improvements over the previous one for CHiME-3, including the front-end design, training data augmentation via different versions of the official training data, acoustic model fusion, and language model fusion. The final average WERs of the real test set are 2.24%, 3.91%, 9.15% for 6-channel, 2channel, and 1-channel, respectively.
The Long-run Impact of Media Sentiment on Stock Returns∗

We examine the impact of fundamental and behavioral factors on stock returns in light of the E cient Market Hypothesis. With two novel sentiment datasets, we nd positive and signi cant correlations between fundamental macroeconomic factors, media sentiment (a combination of sentiment from Reuters and TV news) and stock returns. We show with vector error correction models that media sentiment causes persistent changes in stock returns over months, and that there is a constant and longer-lasting overreaction in stock prices to media sentiment, con rming earlier studies. Reuters sentiment is the more persistent behavioral variable to forecast stock returns than TV sentiment.
Parameterisation of Aquifer Hydraulic Properties : A Contaminant Hydrogeology Perspective

The development of hydrogeology as a distinct discipline in geosciences was initially driven by the exploitation of aquifers for public and industrial water supply. Cost effective development of groundwater resources necessarily involves characterisation of the sustainable yield of an aquifer, which requires the estimation of transmissivity, storativity, permeability and/or hydraulic conductivity. This information is important for conceptual site model (CSM) development (both geologic and hydraulic), design and positioning of abstraction wells, and well pump selection. As water resource hydrogeologists tend to work at the “aquifer” scale, hydraulic properties are often determined at the scale of many 10s to 100s of metres. Parameterisation of aquifer properties at this scale is usually achieved via pumping tests, where water is pumped from a well or borehole while measurements are taken of volumetric discharge, drawdown in the well, and drawdown response in adjacent piezometers. These observations are then interpreted using analytical and semi-analytical solutions (see Kruseman and de Ridder, 2000 for a comprehensive review) that describe the physical hydrogeology of the aquifer. In 1935, Theis derived an analytical solution to the unsteady state flow of water to a well in a confined aquifer, following on from Thiem’s work on steady state flow in 1906. Various refinements subsequently followed (e.g. Cooper and Jacob, 1946; Hantush, 1962; Papadopulos and Cooper, 1967), along with the development of solutions for leaky (Hantush and Jacob, 1955; Neuman and Witherspoon, 1969), unconfined (Neuman, 1974), and fractured (Gringarten and Witherspoon, 1972) aquifers. These methods involve matching pumping test data to type curves to estimate hydraulic conductivity and/or transmissivity. Today, many of these solutions and curve-matching routines are used in commercially-available pumping test interpretation software, making the determination of bulk aquifer hydraulic properties straightforward and rapid.
PHYSICAL WELL-BEING AND MALODOUR EXPOSURE: THE IMPACT OF AN INTENSIVE PIG FARMING OPERATION ON A COMMUNITY IN TRINIDAD

There is a high demand for pork products in Trinidad because of its lower cost compared to other meats and its preferential taste. Erin farm in Trinidad is the largest piggery in the country. Intensive livestock production has been shown to produce a large amount of biological waste which can be harmful to human health. This study investigated the impact of malodors from this piggery on the physical health of persons in the surrounding community. Direct measures of gases were done over a 3 month period and community members were surveyed using a questionnaire to determine their perception of the severity of the malodors and the frequency of selected health-related symptoms. Repeat measures were done in a matched community some 5000m away from the piggery. Data were assessed using paired ttests, chi square and multiple regression analysis. Results showed: significant differences in ammonia and hydrogen sulphide levels between the test and control communities (p<.001 level) and significantly higher incidences of health symptoms (p<.05 level) between the communities (headaches, eye, nose and throat issues, wheezing, sneezing, shortness of breath, difficulty in concentration and general discomfort. Regression results showed that higher adverse malodour ratings significantly impacted health status of residents living close to the piggery (P<.001). Findings suggest intervention by The Environmental Management Agency to mediate in this community to have a solution in which the farm can continue to operate and the residents’ health is not further compromised.
A model of wind and altitude effects on 110-m hurdles

We have adapted a model of 100-m sprint performances to simulate the effects of wind velocity and race altitude on 110-m hurdle performance. For a 2 m.s wind in the direction of motion, performance improves by 0.19 seconds. Each 625 m of altitude improves performance by 0.03 s. These effects are approximately twice the magnitude of those in the 100-m sprint. According to our estimated corrections, the current event World Record holder Colin Jackson should keep his title, albeit due to a difference race run under more extreme conditions (headwind and altitude).
The Impact of Water on Particle Emissions from Heated Cooking Oil

ABSTRACT Four edible oils and five oil-water ratios were heated to investigate the effect of water on the particle emission characteristics of particles emitted from heated cooking oil. PM2.5 and particles ranging from 0.01–10 μm emitted during oil-water heating were monitored via a DustTrak, a condensation particle counter and an aerodynamic particle sizer. The results showed that the PM2.5 levels and the particle number concentrations of the series of corn or peanut oil-water emulsions could be up to 6 and 50 times higher, respectively, than those of the series of soybean or canola oil-water emulsions. All heated oil-water emulsions at an oil-water ratio of 6-1 generated higher total particle concentrations than those of other ratios. The promoting factors (normalized by the corresponding oil volume to total volume) for the concentration of ultrafine particles, PM1 and PM2.5 ranging from 1.20 to 3.32, 1.14 to 2.50 and 0.71 to 2.14, respectively. In addition, the ratio of ultrafine particles (10–100 nm) to total particles and the particle number mode and median diameters changed with the oil-water ratio, but no obvious trend was observed. The regression results showed that the impact of water on particle emissions is not statistically significant.
Image Reconstruction Using Modified Hybrid Transform

In this paper, an algorithm for reconstruction of a completely lost blocks using ModifiedHybrid Transform. The algorithms examined in this paper do not require a DC estimationmethod or interpolation. The reconstruction achieved using matrix manipulation based onModified Hybrid transform. Also adopted in this paper smart matrix (Detection Matrix) to detectthe missing blocks for the purpose of rebuilding it. We further asses the performance of theModified Hybrid Transform in lost block reconstruction application. Also this paper discussesthe effect of using multiwavelet and 3D Radon in lost block reconstruction.
What Went Wrong for Bad Solvers during Thematic Map Analysis? Lessons Learned from an Eye-Tracking Study

Thematic map analysis is a complex and challenging task that might result in map user failure for many reasons. In the study reported here, we wanted to search for differences between successful and unsuccessful map users, focusing—unlike many similar studies—on strategies applied by users who give incorrect answers. In the eye-tracking study, followed by a questionnaire survey, we collected data from 39 participants. The eye-tracking data were analyzed both qualitatively and quantitatively to compare participants’ strategies from various perspectives. Unlike the results of some other studies, it turned out that unsuccessful participants show some similarities that are consistent across most analyzed tasks. The main issues that characterize bad solvers relate to improper use of the thematic legend, the inability to focus on relevant map layout elements, as well as on adequate map content. Moreover, they differed in the general problem-solving approach used as they, for example, tended to choose fast, less cautious, strategies. Based on the collected results, we developed tips that could help prevent unsuccessful participants ending with an incorrect answer and therefore be beneficial in map use education.
The paltry power of priors versus populations

Biological experiments often involve hypothesis testing at the scale of thousands to millions of tests. Alleviating the multiple testing burden has been a goal of many methods designed to boost test power by focusing tests on the alternative hypotheses most likely to be true. Very often, these methods either explicitly or implicitly make use of prior probabilities that bias significance for favored sets thought to be enriched for significant finding. Nevertheless, most genomics experiments, and in particular genome-wide association studies (GWAS), still use traditional univariate tests rather than more sophisticated approaches. Here we use GWAS to demonstrate why unbiased tests remain in favor. We calculate test power assuming perfect knowledge of a prior distribution and then derive the population size increase required to provided the same boost without a prior. We show that population size is exponentially more important than prior, providing a rigorous explanation for the observed avoidance of prior-based methods. Author summary Biological experiments often test thousands to millions of hypotheses. Gene-based tests for human RNA-Seq data, for example, involve approximately 20,000; genome-wide association studies (GWAS) involve about 1 million effective tests. The conventional approach is to perform individual tests and then apply a Bonferroni correction to account for multiple testing. This approach implies a single-test p-value of 2.5 × 10−6 for RNA-Seq experiments, and a p-value of 5 × 10−8 for GWAS, to control the false-positive rate at a conventional value of 0.05. Many methods have been proposed to alleviate the multiple-testing burden by incorporating a prior probability that boosts the significance for a subset of candidate genes or variants. At the extreme limit, only the candidate set is tested, corresponding to a decreased multiple testing burden. Despite decades of methods development, prior-based tests have not been generally used. Here we compare the power increase possible with a prior with the increase possible with a much simpler strategy of increasing a study size. We show that increasing the population size is exponentially more valuable than increasing the strength of prior, even when the true prior is known exactly. These results provide a rigorous explanation for the continued use of simple, robust methods rather than more sophisticated approaches.
Real-Time Guitar Amplifier Emulation with Deep Learning

This article investigates the use of deep neural networks for black-box modelling of audio distortion circuits, such as guitar amplifiers and distortion pedals. Both a feedforward network, based on the WaveNet model, and a recurrent neural network model are compared. To determine a suitable hyperparameter configuration for the WaveNet, models of three popular audio distortion pedals were created: the Ibanez Tube Screamer, the Boss DS-1, and the Electro-Harmonix Big Muff Pi. It is also shown that three minutes of audio data is sufficient for training the neural network models. Real-time implementations of the neural networks were used to measure their computational load. To further validate the results, models of two valve amplifiers, the Blackstar HT-5 Metal and the Mesa Boogie 5:50 Plus, were created, and subjective tests were conducted. The listening test results show that the models of the first amplifier could be identified as different from the reference, but the sound quality of the best models was judged to be excellent. In the case of the second guitar amplifier, many listeners were unable to hear the difference between the reference signal and the signals produced with the two largest neural network models. This study demonstrates that the neural network models can convincingly emulate highly nonlinear audio distortion circuits, whilst running in real-time, with some models requiring only a relatively small amount of processing power to run on a modern desktop computer.
Theoretical Investigation of an Alcohol-Filled Tellurite Photonic Crystal Fiber Temperature Sensor Based on Four-Wave Mixing

For this study, a temperature sensor utilizing a novel tellurite photonic crystal fiber (PCF) is designed. In order to improve the sensor sensitivity, alcohol is filled in the air holes of the tellurite PCF. Based on the degenerate four-wave mixing theory, temperature sensing in the mid-infrared region (MIR) can be achieved by detecting the wavelength shift of signal waves and idler waves during variations in temperature. Simulation results show that at a pump wavelength of 3550 nm, the temperature sensitivity of this proposed sensor can be as high as 0.70 nm/°C. To the best of our knowledge, this is the first study to propose temperature sensing in the MIR by drawing on four-wave mixing (FWM) in a non-silica PCF.
Classifying spatial patterns of brain activity with machine learning methods: application to lie detection

Patterns of brain activity during deception have recently been characterized with fMRI on the multisubject average group level. The clinical value of fMRI in lie detection will be determined by the ability to detect deception in individual subjects, rather than group averages. High-dimensional non-linear pattern classification methods applied to functional magnetic resonance (fMRI) images were used to discriminate between the spatial patterns of brain activity associated with lie and truth. In 22 participants performing a forced-choice deception task, 99% of the true and false responses were discriminated correctly. Predictive accuracy, assessed by cross-validation in participants not included in training, was 88%. The results demonstrate the potential of non-linear machine learning techniques in lie detection and other possible clinical applications of fMRI in individual subjects, and indicate that accurate clinical tests could be based on measurements of brain function with fMRI.
Direct stress field estimation through waveform matching

Conventionally, the routine workflow of stress field estimation from seismic data consists of two steps: focal mechanism inversion and stress inversion. This two-step workflow suffers from the cumulative uncertainties of both the focal mechanism inversion process and the stress inversion process. To mitigate the cumulative errors, a few previous studies have put efforts to directly estimate the stress field using P-wave polarities. In this study, we develop a new approach to directly estimate tectonic stress fields with better accuracy through waveform matching. This new approach combines the two steps into a one-step workflow to mitigate the cumulative uncertainties through the physical relationship between a stress field and the recorded waveforms. This method assumes a homogeneous stress field in space in the local source region and that the fault slip occurs in the direction of the resolved shear stress acting on the fault plane. Under these assumptions, the stress pattern that generates the theoretical waveforms that best fit the waveforms observed is directly retrieved as the true stress field. The merits of the new approach include that this approach can mitigate the cumulative uncertainties suffered from the conventional two-step workflow and does not require determination of the focal mechanisms of each event; thus, this method is applicable to data sets with few stations. Synthetic tests with and without noise are conducted to demonstrate the performance and merits of this method. Then, the new approach is applied to a real data set from central Oklahoma between March 2013 and March 2016. The resulting stress pattern is consistent with that estimated from previous studies examining the same region. These applications show the benefits and validity of the new approach.