Reviewerly/exHarmony huggingface dataset:
Revamping the GFZ Energy Magnitude computation procedure to establish a new service

&amp;lt;p&amp;gt;Location and magnitude are the primary information released by any seismological observatory to characterize an earthquake. Nowadays, the size of large enough earthquakes are routinely measured in terms of released seismic moment (moment magnitude, Mw). Whereas events with Mw above about 5.5 populate seismological archives connected to global monitoring networks, the moment magnitude of smaller events require the analysis of regional and local dense networks, or the establishment of empirical relationships to convert other magnitude scales into Mw (e.g., local magnitude to moment magnitude conversions). Since Mw is constructed over a physical parameter, it does not saturate. Moreover, being the seismic moment connected to tectonic features such as fault area and the average slip, Mw became the reference magnitude for seismic hazard studies. Although Mw accomplishes perfectly the task of characterizing the earthquake size, it does not provide the most complete view about the earthquake strength since Mw is insensitive to changes in the rupture dynamics. An assessment of the amount of the seismic energy released by an event (energy magnitude Me) is allowing to complement Mw with a measure of the earthquake size more suitable to evaluate the earthquake shaking potential.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;Aiming at introducing soon a new real-time service providing Me for major earthquakes we are presenting in this study the results of benchmark tests against the procedure proposed by Di Giacomo et al., in 2008 [1] as well as the analysis performed on a larger data set including all major events available in the GEOFON catalogue with a published moment magnitude since 2011. The initial procedure has been translated to a python code within the Stream2segment package [2] and leveraging on EIDA and IRIS data services, more than 2000 station for ~5000 events since 2011 have been downloaded and processed. The large data set used and the real-time application pose new challenges, among them the teleseismic distance, the strongly unbalanced network and the real-time data flow making the data set used dynamic. We present and discuss here the effects of these complications and how we are tackling them towards the implementation of new service at GFZ computing Me in real-time.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;amp;#160;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;em&amp;gt;[1] Di Giacomo, D., Grosser, H., Parolai, S., Bormann, P., and Wang, R. (2008), Rapid determination of Me for strong to great shallow earthquakes, Geophys. Res. Lett., 35, L10308, doi:10.1029/2008GL033505.&amp;lt;/em&amp;gt;&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;&amp;lt;em&amp;gt;[2] Riccardo Zaccarelli, Dino Bindi, Angelo Strollo, Javier Quinteros, Fabrice Cotton; Stream2segment: An Open&amp;amp;#8208;Source Tool for Downloading, Processing, and Visualizing Massive Event&amp;amp;#8208;Based Seismic Waveform Datasets. Seismological Research Letters ; 90 (5): 2028&amp;amp;#8211;2038. doi: https://doi.org/10.1785/0220180314&amp;lt;/em&amp;gt;&amp;lt;/p&amp;gt;
Automation of Tutor’s Activities in Higher Education Institutions

The aim of the research is to automate tutoring activities in higher education institutions. The developed module of the program “Tutor’s Diary” will automate the implementation of educational and methodological activities of the tutor in higher educational institutions with students in the framework of educational programs.
READING LITERACY IN THE FOREIGN LANGUAGE. THE KEY POSITION OF THE INPUT TEXT AND ITS SELECTION

The article focuses on the problem of the reading literacy in a foreign language, analysing the specific case of Italian, within the context of Slovak schooling ambience at high schools. The paper identifies some of the major problem students have in reading written texts. These are based either on inherent cognitive lacks, poor general culture or on various failing reading strategies. The extensive reading and the elevated textual competence are some of the goals nowadays language didactics aims to achieve. This implicates the improvement of the lexical approach, then critical thinking strategies, which would allow the readers to evaluate better the information contained in the input text as well as its textual structure. The language intended as a cultural construct needs to be studied in its intercultural aspect, stressed by selection of authentic input texts of various textual genres. These should be centered by the topic in correspondence with the learners´ motivation. Some practice advise is given in the conclusion of the paper.
Does Financial Development Affect the Economic Growth Gains from Trade Openness?

This article examines the relationship between trade openness, financial development and economic growth on a panel of four North African countries (Tunisia, Morocco, Algeria and Egypt), over a 5-year period from 1998 to 2017. Using dynamic panel data model estimated by means of the Generalized Method of Moments (GMM), we found that trade openness is positively related to economic growth. We also found that trade openness appears to be working as a complement to financial development and, moreover, that the effect of trade openness is more pronounced in the presence of the financial development variable. The findings suggest that trade openness and financial development are important elements in determining economic growth in these countries. Therefore, the policy-makers should continue to patronize the development of their financial sector and to allow more trade openness in order to achieve a high and sustainable economic growth.
Fake Video Detection Using Facial Color

The field of image forgery is widely studied, and with the recent introduction of deep networks based image synthesis, detection of fake image sequences has increased the challenge. Specifically, detecting spoofing attacks is of grave importance. In this study we exploit the minute changes in facial color of human faces in videos to determine real from fake videos. Even when idle, human skin color changes with sub-dermal blood flow, these changes are enhanced under stress and emotion. We show that extracting facial color along a video sequence can serve as a feature for training deep neural networks to successfully determine fake vs real face sequences.
MULTICLOUD DEPLOYMENT TO SUPPORT REMOTE LEARNING

In the context of the ongoing pandemic, the need for remote collaboration between teachers and groups of students has become an important educational aspect. A possible solution is to move the entire activity to the Cloud, thus offering other advantages besides the much-needed interaction, such as disaster recovery and resource management. As cost savings are now more important than ever, one also needs to make the right choice between the Cloud providers where to deploy the educational environments. A platform focussed on multicloud deployment and collaboration can facilitate one to benefit from the advantages mentioned above, providing usage simplicity for teams of students and researchers that need to continue their activity during the lockdown period. The result of our research is a multicloud deployment platform that helps users with their choices on the deployment of infrastructure and tools, even without possessing advanced technical knowledge. Thus, one can create multiple environments for test, development and production whenever he/she needs it. The paper discusses the educational advantages that a platform with such features can provide and the help it can represent for teachers, students, and researchers in the current world situation.From a technical perspective, the means of deployment include technologies such as Docker, Kubernetes, Helm, and Terraform. The Cloud infrastructure is automatically deployed using Terraform scripts and the Kubernetes resources are deployed with Helm Charts. Helm Charts and Terraform are the source for automatic deployment and will be triggered when a user deploys the infrastructure from the web application. These methods are frequently used to create/delete/recreate environments and to move resources very fast on Cloud subscriptions; they are also supported by the most important Cloud providers.The solution presented in this paper has the purpose to develop means for increasing the collaboration among the academic personnel such as teachers, researchers and students who face a tough period in which they have to learn, research and perform evaluations using online tools. As a result, the platform can ensure a strong work connection fulfills the objective of providing on-Cloud capabilities that may exceed a local laboratory environment. The paper describes an example that applies these ideas to the modelling field, by presenting the multicloud deployment of a generic modeling environment, alongside its model interpreters, used for Model Driven Engineering classes and the related research.
An Ensemble Framework of Multi-ratio Undersampling-based Imbalanced Classification

Class imbalance is commonly observed in real-world data, and it is problematic in that it degrades classification performance due to biased supervision. Undersampling is an effective resampling approach to the class imbalance. The conventional undersampling-based approaches involve a single fixed sampling ratio. However, different sampling ratios have different preferences toward classes. In this paper, an undersampling-based ensemble framework, MUEnsemble, is proposed. This framework involves weak classifiers of different sampling ratios, and it allows for a flexible design for weighting weak classifiers in different sampling ratios. To demonstrate the principle of the design, in this paper, a uniform weighting function and a Gaussian weighting function are presented. An extensive experimental evaluation shows that MUEnsemble outperforms undersampling-based and oversampling-based state-of-the-art methods in terms of recall, gmean, F-measure, and ROC-AUC metrics. Also, the evaluation showcases that the Gaussian weighting function is superior to the uniform weighting function. This indicates that the Gaussian weighting function can capture the different preferences of sampling ratios toward classes. An investigation into the effects of the parameters of the Gaussian weighting function shows that the parameters of this function can be chosen in terms of recall, which is preferred in many real-world applications.
Inversion-Free Leontief Inverse: Statistical Regularities in Input-Output Analysis From Partial Information

We present a baseline stochastic framework for assessing inter-sectorial relationships in a generic economy. We show that - irrespective of the specific features of the technology matrix for a given country or a particular year - the Leontief multipliers (and any upstreamness/downstreamness indicator computed from the Leontief inverse matrix) follow a universal pattern, which we characterize analytically. We formulate a universal benchmark to assess the structural inter-dependence of sectors in a generic economy. Several empirical results on World Input-Output Database (WIOD, 2013 Release) are presented that corroborate our findings.
Document Towers: A MATLAB software implementing a three-dimensional architectural paradigm for the visual exploration of digital documents and libraries

This article introduces the generic Document Towers paradigm, visualization, and software for visualizing the structure of paginated documents, based on the metaphor of documents-as-architecture. The Document Towers visualizations resemble three-dimensional building models and represent the physical boundaries of logical (e.g., titles, images), semantic (e.g., topics, named entities), graphical (e.g., typefaces, colors), and other types of information with spatial extent as a stack of rooms and floors. The software takes as input user-supplied JSON-formatted coordinates and labels of document entities, or extracts them itself from ALTO and InDesign IDML files. The Document Towers paradigm and visualization enable information systems to support information behaviors other than goal-oriented searches. Visualization encourages exploration by generating panoramic overviews and fostering serendipitous insights, while the use of metaphors assists with comprehension of the representations through the application of a familiar cognitive model. Document Towers visualizations also provide access to types of information other than textual content, specifically by means of their physical structure, which corresponds to the material, logical, semantic, and contextual aspects of documents. Visualization renders documents transparent, making the invisible visible and facilitating analysis at a glance and without the need for physical manipulation. Keyword searches and other language-based interactions with documents must be clearly expressed and will return only answers to questions asked; by contrast, visual observation is well suited to fuzzy goals and uncovering unexpected aspects of the data.
Feasibility of Wearable Display Glasses for Medical Students in the Endoscopy Room

Several attempts have been made to incorporate smart glasses in the medical field. We applied wearable display glasses to show the position of an observer during endoscopy and compared students' responses between the conventional and new methods.We surveyed 28 medical students regarding the use of wearable display devices. The students used wearable display glasses to observe an endoscopic procedure and answered the prepared questionnaire. Their collected responses were analyzed for statistical correlations between each variable.The survey of medical students revealed disadvantages including dizziness (dissatisfied and very dissatisfied: 21.5%) and eye fatigue (25% dissatisfied) and advantages including concentration (satisfied and very satisfied: 57.2%) and securing patient rights (71.4%). The students showed more positive than negative reviews regarding the new devices (32.1% vs. 21.5%).We investigated the advantages and disadvantages of viewing the endoscope image with new wearable display glasses compared to the conventional method using the survey to record user experience. The results revealed relatively positive responses from the medical students in the survey. If the new device compensates for some shortcomings, its use in the endoscopy room will be feasible.
EA-Based ASV Trajectory Planner for Pollution Detection in Lentic Waters

This paper presents a new planner based on Evolutionary Algorithms (EAs) to optimize the trajectory of an Autonomous Surface Vehicle (ASV), equipped with a probe, that has to determine the location of a pollutant in lentic water bodies (e.g. reservoirs, dams). To achieve it, our planner 1) exploits the information provided by a simulator that determines the pollutant distribution based on the water currents and 2) is supported by an EA that optimizes the mission duration, the ASV trajectory length and the measurements taken by its probe in highly polluted areas. The current version of the planner also ensures that the trajectories are feasible from the ASV and water body perspective, and solves this constrained multi-objective problem as a mono-objective one that linearly combines the constraint and objective functions. The preliminary results over different scenarios show that the planner can already determine overall good solutions, but that needs to be modified (e.g. using a multi-objective intended EA) to improve them further.
Policy Analysis of Educational Services for the One Belt One Road Initiative under the covid-19 Epidemic

Abstract Education undertakes the era mission of serving China’s external development strategy, and provides comprehensive personnel support, constructive intellectual support, shared humanistic exchanges, and harmonios understanding of value for the interconnections among countries along the One Belt One Road ( obor ). Since 2014, China’s policies on “education + ‘One Belt One Road’” have been continuously refined and expanded, and a policy system of education’s services for the obor initiative has been initially formed, which providing high-quality and top-level designs for promoting the construction of obor initiative. Educational services for the obor initiative are facing new challenges and opportunities under the global covid -19 epidemic. For example, the international misunderstandings and stigmatizations bring opportunities for introspecting the construction of China’s international discourse system; the traditional cooperation modes of offline education is blocked, which brings opportunities for exploring new forms of educational services; the contents and modes of education are becoming increasingly diversified, putting forward higher requirements for the comprehensive qualities of each educational subject. In the future period of normalization of epidemic prevention and control, it is urgent to improve the quality of educational services by maintaining strategical focuses, such as deepening the educational opening up and cooperation, optimizing the personnel training concepts and teaching modes, and improving the guarantee mechanism.
NoSQL Comparative Performance Study

This article aims to introduce the concept of NoSQL, describe the database systems Cassandra and MongoDB, but above all, perform a comparative study (practical) of both systems, on the same dataset. The YCSB benchmark tool is to test different types of operations - reading, writing, and reading and writing - by performing these tests on various workloads, through progressive increases of clients to perform the operations, in order to compare the two solutions in terms of performance. Preliminary results show that Cassandra generally performs better in all types of operations, but it depends more on the capacity in terms of resources of the machine. On the other hand, MongoDB is able to achieve better results in a scenario where hardware resources are lower, with performance levels slightly higher than Cassandra.
Boosting Generalization in Bio-signal Classification by Learning the Phase-Amplitude Coupling

Various hand-crafted feature representations of bio-signals rely primarily on the amplitude or power of the signal in specific frequency bands. The phase component is often discarded as it is more sample specific, and thus more sensitive to noise, than the amplitude. However, in general, the phase component also carries information relevant to the underlying biological processes. In fact, in this paper we show the benefits of learning the coupling of both phase and amplitude components of a bio-signal. We do so by introducing a novel self-supervised learning task, which we call phase-swap, that detects if bio-signals have been obtained by merging the amplitude and phase from different sources. We show in our evaluation that neural networks trained on this task generalize better across subjects and recording sessions than their fully supervised counterpart.
Directional phase-unwrapping algorithm and phase shift technique on hydrogel

Refractive index microstructures, which can be written by multiphoton absorption with femtosecond lasers, have many applications. Here we present a directional phase-unwrapping algorithm with phase-shifting technique and apply it to the metrology of hydrogel microstructures. A staircase phase-unwrapping algorithm is demonstrated. This fast quality-guided path phase-unwrapping applies well to situations that are geometrically well defined and is quite tolerant of phase noise. To achieve precise very small phase shifts, we also present a slant angle technique on a DC servo stage along with phase shift measurement, allowing us to achieve 6.5 nm step sizes.
EXAMINING THE FACTORS AFFECTING THE USE OF ONLINE ASSESSMENT TOOLS IN DISTANCE EDUCATION

Covid-19 has changed educational practices dramatically. Many institutions started to present distance education to students from different grade levels. Universities, also, integrated distance education into their programs to provide the continuity of the education. Online assessment tools used for assessing the performance of students in distance education gained a big importance. Hence, the aim of this study was to understand the factors affecting the use of online assessment tools from the perspective of university students and instructors. The participants of the study were 25 students taking three different online courses in digital game design department in spring semester of 2019-2020 academic year. Additionally, three instructors who implemented online assessment tools in their distant courses were included in the study. Semi-structured interviews were used to get data from students and instructors. Content analysis was implemented to analyze the data. According to the results, 3 themes, namely, easy use, consistency between online content and assessment and technical issues were the main factors for university students. For the theme of easy use, most of the students indicated that online assessment tools, such as quizzes and exams should be easy to perform. They also stated the need of clear instructions appeared on the assessment tools. For the consistency between online content and assessment, the university students emphasized that the selected online assessment tool should match with its content. Additionally, a variety of online assessment tools, such as matching, ordering, filling the blanks, short answer etc. should be implemented for handling the whole content. For the last theme of technical issues, a majority of students mentioned about the need for eliminating errors. According to them, there should be no session errors, timer errors, login errors and submission errors especially for synchronous online assessments. Based on the results of semi-structured interviews with instructors, 2 themes, namely capability of online assessment and understanding students’ needs were appeared. For the theme of capability of online assessment, instructors need to be capable of using all online assessment related tasks, such as creating assignment, ordering questions, including timer…etc. For the theme of understanding students’ needs, the instructors indicated the importance of providing a variety of online assessment tools. According to them, a variety of online assessment tools is critical for students because of assessing the content deeply especially in university level. The results of this study can be helpful for instructors, academicians and several experts studying the online assessment. As a future study, comparative long-term research of analyzing the online assessment tools and procedures would be a good contribution to the field.