Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel, Fast, Reliable, and Data-Driven Method for Simultaneous Single-Trial Mining and Amplitude—Latency Estimation Based on Proximity Graphs and Network Analysis

Both amplitude and latency of single-trial EEG/MEG recordings provide valuable information regarding functionality of the human brain. In this article, we provided a data-driven graph and network-based framework for mining information from multi-trial event-related brain recordings. In the first part, we provide the general outline of the proposed methodological approach. In the second part, we provide a more detailed illustration, and present the obtained results on every step of the algorithmic procedure. To justify the proposed framework instead of presenting the analytic data mining and graph-based steps, we address the problem of response variability, a prerequisite to reliable estimates for both the amplitude and latency on specific N/P components linked to the nature of the stimuli. The major question addressed in this study is the selection of representative single-trials with the aim of uncovering a less noisey averaged waveform elicited from the stimuli. This graph and network-based algorithmic procedure increases the signal-to-noise (SNR) of the brain response, a key pre-processing step to reveal significant and reliable amplitude and latency at a specific time after the onset of the stimulus and with the right polarity (N or P). We demonstrated the whole approach using electroencephalography (EEG) auditory mismatch negativity (MMN) recordings from 42 young healthy controls. The method is novel, fast and data-driven succeeding first to reveal the true waveform elicited by MMN on different conditions (frequency, intensity, duration, etc.). The proposed graph-oriented algorithmic pipeline increased the SNR of the characteristic waveforms and the reliability of amplitude and latency within the adopted cohort. We also demonstrated how different EEG reference schemes (REST vs. average) can influence amplitude-latency estimation. Simulation results revealed robust amplitude-latency estimations under different SNR and amplitude-latency variations with the proposed algorithm.
An Analysis of the “Great Gale of October 1881” using the Twentieth Century Reanalysis

This paper examines the historically recorded storm of 14 October 1881, the “Great Gale of October 1881”, over Great Britain. We analyse the storm in the “Twentieth Century Reanalysis” Version 2c (20CRv2c) and in historical weather charts printed in the Quarterly Journal of the Royal Meteorological Society. The focus is on the temporal evolution of sealevel pressure over the Atlantic from 9 to 14 October. We find a generally good agreement between the hand-analysed charts and the ensemble mean of 20CRv2c. The development and track of several individual depressions during this six-day period is well reproduced in 20CRv2c. However, regionally some differences are found between the two data sources.
Just in Time Support to Aide Cardio-Pulmonary Resuscitation

Cardiovascular disease is the leading cause of death in the United States with over 696,000 cases recorded by the Center for Disease Control (CDC) in 2002 (National Center for Health Statistics, 2002). In particular, Sudden Cardiac Arrest (SCA) claims 300,000 to 400,000 American lives annually (AHA, 2005, Huikuri, Castellanos & Myerburd, 2001, Zipes & Wellens, 1998). Ventricular fibrillation is believed to be the insidious perpetrator associated with the majority of these heart maladies (AHA, 2005, Cummins & Hazinski, 2000). Unfortunately, most victims that experience SCA have only a small chance of survival (Stiell, Nichol, Wells, De Maio, Nesbitt, Blackburn, & Spaite, 2003; Zipes & Wellens, 1998). Increasing the probability of survival of SCA victims requires skilled and knowledgeable responders. Usually the task falls to EMTs, firefighters, police officers, or other highly trained responders. Unfortunately, these experts are not always available on site which means that critical time is lost by moving responders to the victim. An alternative approach to provide rapid access to responders is to develop and provide supportive technology that guides a novice through the procedure of resuscitating the victim by presenting information and feedback at the time when it is needed. However, such approach needs methodologically and conceptually to be rooted in cognitive psychology and human factors since these fields can direct work that aims at the robust improvement of human performance of novices. The successful application of this approach has the potential to improve usability of medical devices for non-experts, beyond the design of defibrillators. Below we will outline the elements that need to be included in the development of a system that allows an untrained responder to deal with a SCA by providing elementary cardiopulmonary resuscitation (CPR). This approach is based on the idea of Just-in-Time Support (JITS). First, we will outline the tradition into which such JITS falls conceptually. Then, we will describe the differences between current architectures of Intelligent Tutorial Systems (ITS) and the constraints under which a true JITS has to operate. In the following section we provide a conceptual framework that allows analysis of human performance in the context of complex procedural tasks. Next, we will describe a JITS developed for the purpose of evaluating the feasibility and effectiveness of this approach, and report the results of an experimental study that evaluated a JITS. Finally, we will discuss the findings in the context of future developments of defibrillators and other systems that require guidance of novice users when using these advanced medical technologies in emergency situations.
Mixed-Initiative Active Learning for Generating Linguistic Insights in Question Classification

We propose a mixed-initiative active learning system to tackle the challenge of building descriptive models for under-studied linguistic phenomena. Our particular use case is the linguistic analysis of question types, in particular in understanding what characterizes information-seeking vs. non-information-seeking questions (i.e., whether the speaker wants to elicit an answer from the hearer or not) and how automated methods can assist with the linguistic analysis. Our approach is motivated by the need for an effective and efficient human-in-the-loop process in natural language processing that relies on example-based learning and provides immediate feedback to the user. In addition to the concrete implementation of a question classification system, we describe general paradigms of explainable mixed-initiative learning, allowing for the user to access the patterns identified automatically by the system, rather than being confronted by a machine learning black box. Our user study demonstrates the capability of our system in providing deep linguistic insight into this particular analysis problem. The results of our evaluation are competitive with the current state-of-the-art.
Running head : PERSONALITY AND INTERGENERATIONAL INCOME 1 Personality as a Form of Economic Advantage ? The Role of Conscientiousness in the Intergenerational Transmission of Income

Concerns about rising economic inequality and reduced economic mobility have increased significantly in the United States in recent decades. To combat these issues, understanding the mechanisms behind the intergenerational transmission of income is essential. One possible mechanism that has been understudied is conscientiousness. Previous research has found that conscientiousness is a significant predictor of earnings in adulthood, and that conscientiousness can be passed from parents to child through genetic and environmental factors. Therefore, we wanted to examine the direct and indirect effects that parent conscientiousness had on their children’s income. Using data from the Midlife in the United States study and the United States Consumer Report, we analyzed these indirect and direct intergenerational effects, using structural equation modelling and path analysis. We did not find any direct or total effects of parent conscientiousness on child income, but did find evidence for an indirect effect of parent conscientiousness on child income, through the transmission of conscientiousness between parents and children. While our study has several major limitations, primarily due to the lack of precise personality and income data from parents, our results indicate that the intergenerational transmission of conscientiousness could still be one mechanism for the transmission of income, in addition to expanding on the existing literature on the direct effects of conscientiousness on income. PERSONALITY AND INTERGENERATIONAL INCOME 4
Fault Tolerance for Lifeline-Based Global Load Balancing

Fault tolerance has become an important issue in parallel computing. It is often addressed at system level, but application-level approaches receive increasing attention. We consider a parallel programming pattern, the task pool, and provide a fault-tolerant implementation in a library. Specifically, our work refers to lifeline-based global load balancing, which is an advanced task pool variant that is implemented in the GLB framework of the parallel programming language X10. The variant considers side effect-free tasks whose results are combined into a final result by reduction. Our algorithm is able to recover from multiple fail-stop failures. If recovery is not possible, it halts with an error message. In the algorithm, each worker regularly saves its local task pool contents in the main memory of a backup partner. Backups are updated for steals. After failures, the backup partner takes over saved copies and collects others. In case of multiple failures, invocations of the restore protocol are nested. We have implemented the algorithm by extending the source code of the GLB library. In performance measurements on up to 256 places, we observed an overhead between 0.5% and 30%. The particular value depends on the application’s steal rate and task pool size. Sources of performance overhead have been further analyzed with a logging component.1
An investigation into some security issues in the DDS messaging protocol

The convergence of Operational Technology and Information Technology is driving integration of the Internet of Things and Industrial Control Systems to form the Industrial Internet of Things. Due to the influence of Information Technology, security has become a high priority particularly when implementations expand into critical infrastructure. At present there appears to be minimal research addressing security considerations for industrial systems which implement application layer IoT messaging protocols such as Data Distribution Services (DDS). Simulated IoT devices in a virtual environment using the DDSI-RTPS protocol were used to demonstrate that enumeration of devices is possible by a non-authenticated client in both active and passive mode. Further, modified sequence numbers were found to be a potential denial of service attack, and malicious heartbeat messages were fashioned to be effective at denying receipt of legitimate messages.
Impact of Network Centrality Positions on Innovation Performance of the Firm: Evidence from China Automobile Industry

Innovation has attracted attention of researches in last 20 years, while networks and clusters are relatively new research subjects. In our paper we made an attempt to find the relationship between network centrality indexes and innovation performance. Each index represents different features of being in the network. To find the network indexes we have constructed adjacency matrixes based on alliance data. For our research we have chosen China’s automobile industry network as an example, for the reason that Chinese automobile industry showed tremendous growth in recent decade and is fit to research scope which we are conducting. We have collected the data on innovation performance for 59 firms in China’s automobile industry. We used UCINET software program to get the data regarding network properties. After we ran the negative binomial regression model on Gretl software program and constructed 5 models, with total of 7 variables. We have analyzed the relationship between innovation performance and three network centrality measures. According to our new findings firms in the network with more total number of connections and firms with more connections with well-connected firms have better innovation performance. We found that there is no effect on innovation performance when firms have capability to pass information fast.
2018-6 Dynamics of Deterrence: A Macroeconomic Perspective on Punitive Justice Policy

We argue that transitional dynamics play a critical role in the evaluation of punitive incarceration reform on crime, inequality and the macroeconomy. Individuals’ past choices related to crime and employment under old policies have persistent consequences that limit their future responses to policy changes. Novel cohort evidence is provided in support of this mechanism. A quantitative model of this theory calibrated using restricted administrative data predicts nuanced, non-monotone dynamics of crime and incarceration similar to the U.S. experience following a single permanent increase in punitive incarceration in the 1980s. Increased inequality and declining employment accompany these changes and are borne unequally across generations.
Pilot study of acceptance and commitment therapy for irritable bowel syndrome: A preliminary analysis of treatment outcomes and processes of change

Background The aim of this study was to investigate the efficacy and proposed processes of change of acceptance and commitment therapy (ACT) in improving the outcomes of irritable bowel syndrome (IBS). Methods A total of 56 consecutive patients recruited from a specialist clinic were included in the study and completed an ACT treatment protocol (one-day group workshop plus self-help manual). Assessments of process (acceptance of IBS) and outcome variables (symptom severity, avoidance behaviours, quality of life, and gastrointestinal anxiety) were carried at four time points (assessment, pre-treatment, post-treatment, and follow-up). Results A significant increase in the acceptance of IBS and improvement in all outcome variables was observed from pre- to post-treatment and follow-up (effect sizes medium to large). Improvements in all outcomes were associated with increases in acceptance of IBS. Changes in acceptance of IBS from pre- to post-treatment were a significant predictor of improvements in outcomes from pre-treatment to follow-up. Conclusions Results support the efficacy of a brief ACT protocol in improving IBS outcomes and maintaining therapy effects at six-month follow-up. Preliminary support for the treatment process proposed was also found.
THE EFFICIENCY OF ACTIVITY-AIDED TEACHING USING AN E-LEARNING PROGRAM IN AGROCHEMISTRY AS A BACHELOR DEGREE SUBJECT

The activity-aided teaching using e-learning program was assessed in students’ training in Agrochemistry subject in the first year of bachelor degree study at the Faculty of Agrobiology, Food and Natural Resources of Czech University of Life Sciences Prague. The e-learning program integrated with active methods had greater efficiency in the students’ education than in classical, formal teaching. The study was achieved on two groups of students; control group (with classical teaching) and tested group (with activated teaching). Students were distributed into groups randomly and the input knowledge in chemistry followed the Gaussian distribution. Basic students’ knowledge on general chemistry was very low on the average and did not correspond with the curricular programs for secondary schools established in the Czech Republic. Activated methods of Agrochemistry teaching consisted mainly from motivation, regularly repetition connected with homework and from usage of e-learning program for self-study. The teaching effectiveness was proved by students’ score from three particular tests and by effective progression and by relative progression. The score from particular tests was related to the score from the entrance test. There were two coefficients of the students’ progression defined properly, and are applicable for a numerical or percentage value. Students from the tested group achieved statistically significantly (α = 0.05) higher scores (186 points) than students in the control group (136 points) in all three particular tests. Evaluation according to effective progression and relative progression proved the higher progress in the tested group compare to the control group. The evaluation of teaching efficiency can be proved by effective as well relative progression. The effective progression was 55 % in tested group and 26 % in control group. Higher significance of tested students’ progression was shown on relative progression; 64 % in tested students and 19 % in control students. The e-learning teaching integrated with active methods can be recommended for higher education.
Bi-Objective Optimization Model for Harvesting of Sugarcane with Fixed and Variable Costs of Harvesting

In this research, the purpose was to find the optimal quantity and optimal time for harvesting of sugarcane in order to maximize the revenue and minimize the gathering cost. The government determines the sugarcane price which is based on weight and sweetness. The cost of production was separated into two parts: a fixed cost and a variable cost. The ε-constraints method was applied to solve a bi-objective mathematical model in which maximizing the revenue was the main objective. The optimal harvesting policies for sugarcane in four regions of Thailand were calculated from the model for crop years 2012/13, 2013/14 and 2014/15. The optimal revenues calculated for the sugarcane harvesting were compared with the actual revenue received by the sugarcane farmers in the four regions for the three crop years.
Aurora — Object-Oriented Framework for Simulation and Analysis of Flow Networks

Aurora object-oriented framework is a set of generic Java classes and interfaces that can be used as base objects in applications that model flow networks, such as road networks, networks of irrigation canals, or oil and gas pipelines. Any network consists of directed links, nodes and monitors. A substance (traffic, water, oil or gas, etc.) flows through the links that connect the nodes. Nodes can be simple, used to connect one or more input with one or more output links, and complex, which are networks themselves. Simple nodes host local controllers that control flows coming into a node from the input links. Complex nodes make the Aurora network structure hierarchical. Monitors are special objects whose purpose is to monitor the state of specified links and nodes and feed the observed data to complex controllers, whose purpose is the coordinated control of multiple nodes, or generate events. Events change network configuration or inputs. They can be generated by user and triggered at user-specified times, or by monitors and triggered based on the data observed by those monitors. Aurora Road Network Modeler (RNM) is a set of tools for operational planning and management of travel corridors (road networks comprised of freeways and surrounding urban arterials), which is based on Aurora object-oriented framework. It consists of three graphical applications with intuitive user interface: Simulator runs macroscopic traffic simulations based on the CTM model, allowing the user to create simulation scenarios by means of events that change specific configuration parameters of the road network at specific times; Configurator is used to build road network configurations from scratch or edit the existing ones; and GIS Importer extracts road information from the GIS . shp and . dbf files and saves it in the XML format of Aurora configuration file. Aurora RNM is open source and can be freely downloaded from the internet.
AUDITORY SCENE CLASSIFICATION BASED ON THE SPECTRO-TEMPORAL STRUCTURE ANALYSIS

In this report, we present a modular system for acoustic scenes classification. Our proposed system contains four modules to compute the representations describing spectro-temporal properties of audio data. The frequency components are extracted from cochleagram and low-level audio feature contours. An onset map is used to determine the properties of temporal structure, and binaural cues are additional components in the final feature space. Computed features are formed into vector and fed to random forests classifier for the purpose of classification. The results were submitted to the 2017 IEEE AASP DCASE challenge.
Automating the recoding , analysis , and interpretation pipeline using naturalistic visual scenes April

Machine learning often focuses on how best to infer structure from data. Also important is the ability to convey that structure to human users. We investigate a system for automating quantification, analysis, and presentation of data to human users. We focus on the domain of natural scenes, an area in which human performance has been well explored, and can thus be used to inform choices of computational tools. Informed by perceptual science, we characterize a corpus of images in terms of the statistics of their orientation distributions. In two experiments, we compare mixture and topic models for analysis, and teaching-optimized versus average images for conveying model structure to people. Using a categorization task, in Experiment 1, we find that, when subclusters are overlapping and categorization difficult, examples selected to teach the category structure lead to improved categorization performance relative to examples closest to the mean. Experiment 2 further shows that mixture models outperformed topic models and teaching examples outperformed maximum likelihood. By leveraging cognitively natural machine learning methods to facilitate automatic analysis and summary of naturalistic data, this work has implications for conveying both typicality and variability of experiences in complex data.
Effect of Pulse Width Modulation on the Performance of Hybrid Cascaded Five Level Inverter

For industrial applications medium power and medium voltage ac drives are more attractive. In order to reduce high dv/dt and to minimize the ripple in torque Multi Level Inverter (MLI)s are proposed. For the realization of Multi Level Inverters, different topologies have been emerging. Among these topologies, hybrid topologies are proven to be better than the conventional topologies. This paper compares the performance of a hybrid cascaded five level inverter with and without using the pulse width modulation technique. The frequency spectrum of the output voltage and currents are compared. For the simulation MATLAB software Simulink is used.
Rural leisure opportunities for people with disabilities: needs and challenges in Quebec

ABSTRACT The issue of leisure for people with disabilities is central as the practice of these activities helps counteract certain problems of sedentariness, social isolation or stigmatization. This problematic is even more complicated in rural areas, where limited means, as well as geographical location and scope slow down certain avenues of leisure development for these challenged populations. The objective of this study was to seek to understand the realities experienced by partners of the Quebec Association for Leisure of People with Disabilities. Through focus groups and semi-directed interviews conducted with 70 local actors, this study highlights the fact that these challenged populations can enjoy a fair amount of leisure time, although it is increasingly difficult to maintain due, in particular, to precarious financial and human situations. The analyses also suggest that future challenges regarding this issue will be linked to partnerships, planning and programming considerations.