Joint Simon effect in movement trajectories

In joint action literature it is often assumed that acting together is driven by pervasive and automatic process of co-representation, that is, representing the co-actor’s part of the task in addition to one’s own. Much of this research employs joint stimulus-response compatibility tasks varying the stimuli employed or the physical and social relations between participants. In this study we test the robustness of co-representation effects by focusing instead on variation in response modality. Specifically, we implement a mouse-tracking version of a Joint Simon Task in which participants respond by producing continuous movements with a computer mouse rather than pushing discrete buttons. We have three key findings. First, in a replication of an earlier study we show that in a classical individual Simon Task movement trajectories show greater curvature on incongruent trials, paralleling longer response times. Second, this effect largely disappears in a Go-NoGo Simon Task, in which participants respond to only one of the cues and refrain from responding to the other. Third, contrary to previous studies that use button pressing responses, we observe no overall effect in the joint variants of the task. However, we also detect a notable diversity in movement strategies adopted by the participants, with some participants showing the effect on the individual level. Our study casts doubt on the pervasiveness of co-representation, highlights the usefulness of mouse-tracking methodology and emphasizes the need for looking at individual variation in task performance.

Geoprocessing and Landscape Ecology for Assessment Fragmentation and Connectivity of the Habitats of the Microregion of Ceres, Goiás (Brazil)

This study aimed to map and evaluate the evolution of habitat fragmentation between 2009 and 2018, using the Microregion of Ceres (Goiás) as a sample reference, using principles of Landscape Ecology. The methodology comprised the mapping of the fragments in the two years analyzed, using the OLI/Landsat 8 sensor, using scenes 222/70 and 222/71. The SPRING 5.2 software was used, where the supervised classification was performed, applying the semi-automatic process. The computational algorithm applied to classify the scenes was Maxver, which classifies pixel by pixel and groups the information of each one into homogeneous regions. After extracting the fragments of native vegetation, the methodology proposed by Juvanhol et al. (2011), in which the fragments were grouped into classes: Very Small (MP) ≤5 hectares; Small (P) ≥5.01 and ≤10 hectares; Medium (M) ≥10.01 and ≤100 hectares and Large (G) ≥100.01 hectares. For the analysis based on metrics in Landscape Ecology, the ArcGis 9.2 Patch Analyst extension was used. The results showed the expansion of vegetation cover areas in the study area, concentrated on tops of hills, APP and legal reserves. However, they pointed out intense fragmentation of native vegetation, which hinders the performance of fragments as habitats. It is considered that, from the contemporary problem of degradation of natural environments to the detriment of economic development, studies like this are necessary in order to identify existing environmental problems and propose strategies to minimize and mitigate ecological imbalances.

Decision making in control systems based on data analysis

Technological processes are always accompanied by deviations from the set mode, which is due to the influence of many external and internal factors. The environmental parameters, the components of input raw materials, and the condition of technological equipment are constantly changing, which requires solving the problem of finding the optimal control parameters and, in some cases, the parameters of the process itself. Most industries are focused on obtaining the final product with a given level of quality. Changes in parameters of the technological process may deteriorate the quality of production and cause defects or even emergency situations. To prevent this, forecasting methods are used. The task of constructing predictive models based on experimental data is relevant for a wide range of technological processes. Today, predictive models are widely used in management, diagnosis and identification. The vast majority of these models are based on artificial intelligence technologies or methods of mathematical statistics. The most widespread forecasting models find application in areas such as banking, insurance, business economics, medicine, diagnostics of technical components and equipment, and forecasting the parameters of technological processes. Despite the well-developed algorithm for model development and application, the main problem that remains is to acquire data, select an appropriate model structure, and integrate the model into existing control systems. The paper will predict the parameters of the technological process of methanol production under reduced pressure. The production of methanol under reduced pressure is a multi-stage process, and the emergence of problems at some stage will adversely affect further work and the end result. Note that there are all problems related to the performance of technological processes in the production of methanol, which are described above. Therefore, another task is to forecast emergencies, taking into account the indicators of all stages in the process. The development of models for forecasting emergencies and controlling thermal regimes and their further integration into the existing automatic process control system is proposed to be performed according to the principles of industrial revolution – Industry 4.0. Important components of Industry 4.0 are the Internet of Things, data analysis, and digital duplicates. Each of these components solves a partial problem and, collectively, they provide full automation of production, forecasting of real-time process indicators, and calculation of optimal control. The process of methanol production under reduced pressure can be fully automated in accordance with the components of Industry 4.0. First, there is instrumentation that allows the values of technological process to be obtained over time. Second, given a moderate size of these data, one can obtain models of control objects, perform their software implementation, and use them to calculate optimal control or predict the state of the process. The paper proposes a variant of constructing a virtual model based on experimental data and its further use with actual values ​​of process parameters. A regression model was chosen to develop a model for predicting the temperature regime. Regression analysis allows checking the statistical significance of the parameters, assessing the adequacy and accuracy of the model, and establishing the nature and closeness of the relationship between the studied phenomena. It is also important to predict the occurrence of emergency (adverse) situations at the workplace. For this purpose, it is necessary to determine a list of these situations according to the technological regulations and develop a model for forecasting emergencies. There are various forms of presenting a model for forecasting emergencies. A decision tree is one of them. It will be developed for the production of methanol. The resulting tree is a graphical structure of the verbal (semantic) model relying on the expert's reasoning in solving problems related to emergencies. This is a network structure, whose nodes indicate potential deviations of the control object from the normal mode of operation. The resulting tree is used to solve forecasting and diagnosing problems. For practical use, the decision tree is implemented in software as an "if - then" set of rules. The software is used as an element of a higher-level system in relation to the existing automatic process control system.

Simulated visual hallucinations in virtual reality enhance cognitive flexibility

Historically, psychedelic drugs are known to modulate cognitive flexibility, a central aspect of cognition permitting adaptation to changing environmental demands. Despite proof suggesting phenomenological similarities between artificially-induced and actual psychedelic altered perception, experimental evidence is still lacking about whether the former is also able to modulate cognitive flexibility. To address this, we measure participants' cognitive flexibility through behavioral tasks after the exposure to virtual reality panoramic videos and their hallucinatory-like counterparts generated by the DeepDream algorithm. Results show that the estimated semantic network has a flexible structure when preceded by altered videos. Crucially, following the simulated psychedelic exposure, individuals also show an attenuated contribution of the automatic process and chaotic dynamics underlying the decision process. This suggests that simulated altered perceptual phenomenology enhances cognitive flexibility, presumably due to a reorganization in the cognitive dynamics that facilitates the exploration of uncommon decision strategies and inhibits automated choices.

A Systematic Survey on Multi-document Text Summarization

Automatic text summarization is a technique of generating short and accurate summary of a longer text document. Text summarization can be classified based on the number of input documents (single document and multi-document summarization) and based on the characteristics of the summary generated (extractive and abstractive summarization). Multi-document summarization is an automatic process of creating relevant, informative and concise summary from a cluster of related documents. This paper does a detailed survey on the existing literature on the various approaches for text summarization. Few of the most popular approaches such as graph based, cluster based and deep learning-based summarization techniques are discussed here along with the evaluation metrics, which can provide an insight to the future researchers.

Analysis of Satisfaction in the Use of Technological Simulation Tools in the Learning of the Automatic Process Control Course

The objective of this article is to describe the satisfaction of the students in the use of technological simulation tools in the learning of the automatic process control course, generated by distance education. The Academic Satisfaction Scale (ESA) was used as a measurement instrument. As the research was carried out, the re-sults revealed that of the indicators that present the highest degree of satisfaction, 56.8% of the student’s state that they strongly agree with what was learned through the use of technological simulation tools in the subject of the course of control of automatic processes and 54.5% indicate that the technological tools used in the contents of the subject excite them. Likewise, by means of the R squared, it can be indicated that the satisfaction of the students with the developed subject, in which technological simulation tools were used (I6), influences 0.637, that is, 63.7%, on the general satisfaction of academic experience in the virtual environment (I7); This is translated with the following equation: I7 = 0.309 + 0.637 * I6.

The Automated Map. Public innovation for the generation of the National Topographic Map of Spain

Several reasons have prompted the National Geographic Institute of Spain (IGN-Spain) to implement an automatic process to generate the National Topographic Map 1:25,000 (MTN) instead trough the traditional manual way, pointing out the growing lack of human resources, in addition to the search for a quick response to the increasing demand of updated geoinformation by the society.This new automated process provides an annual production of all the map sheets composing the MTN25 (4.019 files), what is an unprecedented time record, so that the users can quickly both download them from the Download Centre Website and visualize the maps through the visualization web services WMS and WMTS. This methodology is also applied to the creation of sheets for printed publication, whose final output requires a simplified manual editing process.

“Les Hypothèses Trop Hasardées”

This essay argues that the difficulties Émile Zola faced in closing the Rougon-Macquart novel cycle reveal a political imaginary whose notion of a clean line of progress depends on a technical supplement it disavows. At critical points Zola’s method exposes the disavowal of this technical supplement that functions as the prosthetic by which man overcomes a hereditary deficiency, his original psychosis in Zola’s account, and is also the means by which he allegorizes history as progress. But this supplement must also disappear from view, or operate as a vanishing mediator. Because, for Zola, the immediate political problem of engendering the right kind of political subjects for the Third Empire must be integrated into a larger evolutionary history, the rational overcoming of the original psychosis takes the form of a necessary and indeed automatic process. What is at stake here is not the inhumanism of generalizing the “Anthropos,” which has come under recent scrutiny, but the inhumanism integral to any humanism that imagines itself as teleologically or historically oriented—the inhumanism in humanism that subtends any imaginary of evolution or progress, because such a humanism must have recourse to technical prosthesis.