Reviewerly/exHarmony huggingface dataset:
Multi-Cue Gate-Shift Networks for Mouse Behavior Recognition

Automatic identification of mouse behavior plays an important role in the study of disease or treatment, especially regarding the short-term action of mice. Existing three-dimensional (3D) convolutional neural networks (CNNs) and two-dimensional (2D) CNNs have different limitations when addressing the task of mouse behavior recognition. For instance, 3D CNNs require a large calculation cost, while 2D CNNs cannot capture motion information. To solve these problems, a low-computational and efficient multi-cue gate-shift network (MGSN) was developed. First, to capture motion information, a multi-cue feature switching module (MFSM) was designed to utilize RGB and motion information. Second, an adaptive feature fusion module (AFFM) was designed to adaptively fuse the features. Third, we used a 2D network to reduce the amount of computation. Finally, we performed an extensive evaluation of the proposed module to study its effectiveness in mouse behavior recognition, achieving state-of-the-art accuracy results using the Jiang database, and comparable results using the Jhuang database. An absolute improvement of +5.41% over the benchmark gate-shift module was achieved using the Jiang database.
Dynamic parameters in Sequential Decision Making

Sequential Decision Making (SDM) problems optimize over the sequence of actions (or, decisions) taken to minimize the underlying cumulative cost. These sequence of actions are referred to as the policy of the SDM. Often these problems comprise of additional (fixed and manipulable) parameters; and the objective is to determine the optimal policy as well as the manipulable parameters that minimizes the SDM cost. In this paper we address the class of SDM problems that are characterized by dynamic parameters; where the dynamics is pre-specified for a subset of parameters and manipulable for others. The objective is to determine the manipulable parameter dynamics as well as the time-varying policy such that the associated SDM cost gets minimized at each time instant. To this end, we develop a control-theoretic framework to design the manipulable parameter dynamics such that it tracks the optimal values of the parameters, and simultaneously determines the time-varying optimal policy. Our methodology builds upon a Maximum Entropy Principle (MEP) based framework that addresses SDMs. More precisely, the above framework results into a smooth approximation of the SDM cost which we utilize as a control Lyapunov function. We show that under the resulting control law the parameters asymptotically track the local optimal, the proposed control law is Lipschitz continuous and bounded, and the policy of the SDM is optimal for a given set of parameter values. The simulations demonstrate the efficacy of our proposed methodology.
Blockchain and Pharmaceuticals: A Bibliometric and Systematic Literature Review of Scientific Publications Between 2000 and 2021

Recent years have seen quite a significant interest from blockchain projects in the pharmaceutical industry. Moreover, blockchain has generated an increasing amount of interest from professionals worldwide in pharmaceuticals. Blockchain technology has been strongly cited as a critical element in pharmaceutical supply chain management, clinical data management, and product traceability advancements and a critical element in strategic planning. Through co-occurrence and co-citation analysis, this research aims to provide a systematic review based on bibliometrics and a systematic literature review (SLR). To begin with, 473 academic documents were collected from the Microsoft Academic, Crossref, Europe PMC, Wikidata, and PubMed databases. To examine interconnection patterns, co-occurrence and co-citation analyses were conducted along with network visualization. The results of the analysis have presented relevant keywords, the number of papers published by year, productive authors, and the publication years of important journals. The data has been processed, and the results have been visualized using the VOSviewer software. Accordingly, this study provides insight into the state of the art in blockchain and pharmaceutical research and highlights research gaps.
Dynamic chaotic Gold-Panning Optimizer and its typical engineering applications

Swarm intelligence algorithms are one of the key technologies in solving optimization problems for practical engineering applications, such as mechanical structure design, image analysis, process flow design, etc. Higher accuracy and efficiency mean better comprehensive performance in the practical engineering system based on optimization methods. Gold-Panning Algorithm is one of the swarm intelligence algorithms proposed in 2021, for solving image segmentation problems. However, the self decision-making mechanism based on multi-agent information interaction introduced in it weakens its convergence ability, resulting in its ability to exploit potential solutions being limited. Hence, chaotic maps were introduced to improve the optimization capacity and efficiency, which can provide a more reliable and effective ability to explore and exploit potential optimal solutions in different iteration stages. Moreover, a dynamic selection strategy is utilized to choose the better step-size iteration scheme between the Gaussian distribution and Levy flight. It can further strengthen the exploitation capability of the Gold-Panning Algorithm, reducing the possibility of premature convergence. Based on CEC’2020 benchmark functions, Dynamic Chaotic Gold-Panning Optimizer is compared with the other meta-heuristic algorithms to evaluate its performance and the results shows strong competitiveness in both robustness and accuracy for solving optimization problems. Then, based on the proposed optimizer, its binary variant is applied in feature selection. Besides, combined with the bilateral filtering and threshold segmentation model, the image blind denoising and image segmentation optimization schemes are proposed respectively. Simulation results indicate it presents an excellent comprehensive performance in solving the corresponding engineering task.
Clustering airborne gamma-ray spectrometry data in Nova Friburgo, State of Rio de Janeiro, southeastern Brazil

The goal of this study was to test different image clustering techniques, using airborne gamma-ray spectrometry data to optimize the interpretation of areas with similar properties in large scale. The methodology applied was based on the comparison of two techniques of data-driven classification (K-means and Gaussian Mixture Models) and a technique of knowledge-driven classification (Simplified RGB) to discriminate domains from the primary variables potassium (K), uranium (eU), and thorium (eTh) obtained from airborne gamma-ray spectrometry surveys. The performance of these three methods was evaluated through pre-processing techniques and post-processing including the best number of clusters/classes, visual interpretation, internal validation, and boxplot analysis. The clustering performance was considered satisfactory through the visual interpretation and comparison with the geological map and the DEM, for all three methods. For a quantitative analysis, the simplest model of unsupervised clustering Gaussian Mixture Models prevailed.
Genome-wide association study of cryopreserved semen quality traits in Holstein-Friesian bulls

Here-and-there models and equilibrium models were investigated as a semantical framework for answer-set programming by Pearce, Valverde, Cabalar, Lifschitz, Ferraris and others. The semantics of equilibrium logic is given in an indirect way: the notion of an equilibrium model is defined in terms of quantification over here-and-there models. We here give a direct semantics of equilibrium logic, stated for a modal language embedding the language of equilibrium logic.
Manifold reconstructed semi-supervised domain adaptation for histopathology images classification

Deep learning has been applied in computer-aided whole slide images diagnosis widely. However, most deep networks require lots of labeled samples, which is time-consuming and laborious. Meanwhile, most existing methods only extract the deep abstract features only, ignoring the low-level features, which contain the cell structure information. To solve the problems mentioned above, a manifold reconstructed semi-supervised domain adaptation model is proposed for whole slide images’ classification. First, a transferred network BreNet is proposed for extracting features from multiple layers of source and target domains. Multi-level features are fused and aligned to characterize the cell structure of the target domain. A novel manifold reconstructed domain adaptation method is proposed to obtain the low-dimensional embedding of the fused features and minimize the cross-domain discrepancy simultaneously. The patch-level prediction probabilities are aggregated for final image-level classification. The experimental results evaluated on three breast cancer datasets indicate the potential of the proposed method for histopathology classification in clinical setting.
Dynamic Utility-Improving Time Series Data Perturbation Framework

Enforcing privacy on data collected from sensors located on modern devices and industrial equipment is a challenging research topic. Data protection is not the only aspect to be considered, as data utility is equally important. In this context, this paper proposes a times series data privacy framework capable of dynamically increasing utility when requested. The approach involves implementing a sub-module within the existing perturbation module to compute new perturbation parameters. Experimental results conducted on a driver data set collected via the OBD-II port on KIA Motors vehicles demonstrate that the method can incrementally increase utility and involves a small number of computations. Additionally, the new perturbation parameters for increasing utility are computed at the device level without the need to transfer unprotected data to a third-party system.
Identifying the Constructive Features of Historical Violins Using Computer Tomography

The aim of the paper was to identify the constructive and geometric characteristics of both historical and current violins. Thus, the main method of identifying the geometrical characteristics was based on computer tomography (CT) imaging analysis, as a non-invasive and non-destructive method, considering that all the analyzed structures were in good working order. Based on the CT images, the dimensions in the 3 main sections of the violins were determined, comparing them with each other. The results highlighted the fact that the constructive shape of the old violins varied from one school of luthiers to another, the degree of bowing of the front and back plates being dependent on the processing techniques used. Moreover, the imaging method provided details regarding the constructive elements of old violins, information that is difficult to access with the naked eye. All these results are correlated with the dynamic and acoustic properties of violins, helping to understand the connection between the constructive form of the resonator body and their acoustic response.
Influence of Immersive Virtual Reality on Cognitive and Affective Learning Goals

With the increasing prevalence of immersive virtual reality (VR) systems in educational contexts, it is important to understand how the use of VR impacts cognitive, affective, and psychomotor learning processes and learning outcomes. Proponents argue that VR can improve the quality of learning by stimulating individual learning processes to generate interest and motivate them to learn. Others claim that immersive media such as VR disrupts learning by increasing distraction, which leads to a decrease in cognitive performance and a reduction in acquired knowledge. To collect evidence on how VR influences learning, we performed a quantitative study. One group received information (about environment protection) before and after being immersed in two different VR applications, which incorporate content-related informational context. The second group was presented the same information but without the VR experience. We found that cognitive learning was better for the participants without the complementary VR experience, as they remembered information better. However, affective learning was better for the participants with the complementary VR experience. One week after the presentation of the content, participants with the complementary VR experiences had an increased awareness of threats to nature as well as the commitment to act environmentally conscious. Our findings, thus, support voices stating that VR can support learning, as well as those arguing against it. Whether the use of VR is supportive depends on the learning goals.
Improving a Gamified Language Learning Chatbot Through AI and UX Boosting

In this paper, we show how the chatbot-based collaborative English learning app Escapeling can be enhanced through state-of-the-art artificial intelligence (AI) techniques and user experience improvements. In this app, intermediate learners can practice different skills in the available tasks, which are integrated in a gamified escape room scenario. To enhance the learning experience, we implement AI-powered grammar-learning support in a free writing task and we improve adaptive feedback for other tasks. Furthermore, we address affective aspects of learning and improve the user experience by integrating different types of situation-dependent visualizations and an improved contextualization in the storyflow into our app. Finally, students can now also practice listening comprehension within the app. Preliminary results gathered in three qualitative evaluation sessions indicate a noteworthy boost of the didactic value, user satisfaction, and enjoyment of Escapeling due to reported updates.
A Study on the Sustainability of the Online/Hybrid Education System Within the Faculty of Civil Engineering (Technical University of Cluj-Napoca)

The COVID-19 pandemic has forced both economic operators and educational institutions, including universities, to adapt quickly to a new way of working: teleworking. Universities used telework, by conducting exclusive online teaching activities in a first stage, then in hybrid system. We conducted a pilot study in order to investigate the perception of both teachers and students on the online/hybrid system and whether the system could be sustainable and efficient in terms of learning, educational materials and other material resources in the future for technical universities, once online education will be legally regulated.Our study revealed that certain types of teaching activities, such as some courses, seminars or laboratories are suitable for this type of teaching, whereas others (mainly engineering disciplines) require face-to-face activities. Hence, the respondents (teachers and students) stated that the hybrid system was be the most suitable. One in two teaches were in favor of carrying out certain online courses, since the system has certain advantages that are worth maintaining in the future The percentage of Bachelor of science and Master of science students who chose an online or hybrid system only for courses and seminars/laboratory courses that are suitable for this kind of teaching totaled 42.3%, while the percentage of those who chose an online system without any other nuances was 40.4%.
A Pedagogical Conversational Agent for Tutoring in the Development of Educational Research Projects

Some countries struggle to respond in a personalized way to a growing student base, owing to the student-teacher ratio being 13:1 on average. Practice and theoretical review indicate that there is an analysis lack in e-learning of the Pedagogical Conversational Agent (PCA) for tutoring in the development of educational research projects. Therefore, the objective was to determine the algorithm of the PCA dialogic system for tutoring the Integrating Knowledge Project at the National University of Education. The population was students of the Basic Education Career, distance learning, academic period semester I—2021 (N = 1,124), and the sample, with a 95% confidence level and an estimated sampling error of 5%, was 287 participants. They were selected by cluster sampling technique. Paradigm was pragmatism, and method was a light mixed method of convergent design (questionnaire variant) of descriptive scope, cross-sectional and empirical. The research used descriptive statistics and content analysis. The main results were the algorithm’s meta-inferences, which should have a teacher/tutor’s role, offer emotional support, identify errors in the dialogue topics of the domain, and so forth. This research is significant because it determines the generalities and particularity of the PCA dialogue system from and for the students. Moreover, it initiates the linkage of the PCA dialogue system and the tutoring of educational research projects.
Digital Skills of the Ecuadorian Population in the Framework of a Hybrid Society

This work has been prepared with the aim of analyzing the evolution and conditions of digital skills in Ecuador in recent years, as well as contextualizing it in relation to the global and regional scope, using official data from the Economic Commission for Latin America and the Caribbean and the Ecuadorian Institute of Statistics and Censuses, in addition to other institutions. The results show that the conditions for the development of digital skills both at the regional and national levels have improved, but there is still a long way to go for developed nations. Likewise, there is a preference for the use of ICT for entertainment purposes instead of productivity, which reflects a lack of optimization in the use of technologies to generate economic well-being, which is why there is a lack of skills for the development of new technologies.
State of Art of Blockchain Technology in the Educational Sector

The objective of this chapter is to present a systematic literature review of the state of blockchain in the educational sector in terms of solution strategies, issues, challenges, and trends. A systematic literature review was conducted using four bibliographic databases, IEEExplore, Sciencedirect, Springerlink, and the ACM digital library. These databases were searched, and the results filtered using an inclusion and exclusion criteria. This led to 54 studies being included for detailed analysis. In this chapter, researchers give the details of these articles and also give a summary of the main areas that blockchain has been used in the educational sector, for instance, for storing and sharing student credentials and certificates. This chapter also discusses the prototypes proposed in the studied articles and in particular the fact that their actual use in a real educational environment is missing from the literature. This review also highlights the fact that there is a lack of consensus in terms of common working practices with blockchains in the educational sector among stakeholders.
Mineral associations in the geochemical halos of Milin Kamak ore deposit, Bulgaria

The focus of this study is the mineralogical interpretation of the determined geochemical associations in the Milin Kamak deposit. Based on the results of the factor analysis, an attempt was made for interpretation of the factor axes by mineralogical studies and EPMA analysis. Three factor associations are related to the hydrothermal ore-forming processes. The main factor axes related to Au is quartz-polymetallic stage and is represented by pyrite, marcasite, arsenopyrite, pyrrhotite, sphalerite, galena and chalcopyrite.
Digital competences in distance education for high school education systems. Study case: institutions incorporated to the UAEMex

The purpose of this paper is to identify the perception of digital competencies that teachers should have at the Upper Secondary Level (NMS) based on the recommendations of UNESCO (2019). The case study is for the Schools Incorporated to the Autonomous University of the State of Mexico. The phenomenon has an origin during and post pandemic. The research is based on a review of recent studies no more than ten years old. The methodological design is qualitative, with a case study method based on the population of teachers of the schools incorporated to the UAEMex. An instrument called e-Open (Rámirez and Tenorio, 2021) was adapted and used for a sample of 500 high school teachers during the 2020-2021 school year. Data collection was carried out through questionnaires that were applied through the google forms platform, establishing the procedures for data collection and analysis according to the e-Open instrument for the Measurement of Competencies Recommendations for Open Education in the UNESCO Framework (2019). The analysis of the information is described and narrated from the data obtained through the questionnaire. The data is displayed in bar graphs. The results of the surveys show the percentages with respect to the five recommendations of the instrument with the 31 items, UNESCO (2019). The evidence supports that 70% of teachers have ICT capacity development. The institution raised 70% the development of support policies. But 50% considered that access to ICT was effective, inclusive and equitable. In addition, 55% considered that the creation of sustainability models is required, and finally 80% considered that international promotion models for teachers should be strengthened. In sum, this study supports the importance of dispersing digital competencies in secondary education systems.
Directing treatments to employ the place in the theatrical performance

The most important topics that constitute the aesthetic and substantive aspect of the theatrical performance represented by the spatial environment of the presentation and the proposed virtual place that contains the technical and artistic elements of the presentation and highlights the strength of influence on it. In light of the above, the researchers divided the topic into four chapters.&#x0D; The first chapter contained (the methodological framework), which included the research problem with regard to the directing treatments between the directors in establishing or creating theatrical venue, the importance of the research and the aim of the research, and the limits of the research to conclude the chapter by defining the terms.&#x0D; The second chapter (the theoretical framework) was divided into two sections that dealt with in the first topic: (the concept of theatrical place), while the second topic came under the title (directive experiences of employing the place in the world theater), and previous studies and the results of the theoretical framework. The third chapter contains&#x0D; (Research procedures) include the research sample, which is a play (Passport), the research community, the reason for selecting the sample and analyzing the sample.&#x0D; While the fourth and final chapter came with (results and conclusions), and included the recommendations suggested by the researchers, as well as the proposals, and contained a list of sources