Set Of Actions Research Articles

NeuroEditor: a tool to edit and visualize neuronal morphologies.

The digital extraction of detailed neuronal morphologies from microscopy data is an essential step in the study of neurons. Ever since Cajal's work, the acquisition and analysis of neuron anatomy has yielded invaluable insight into the nervous system, which has led to our present understanding of many structural and functional aspects of the brain and the nervous system, well beyond the anatomical perspective. Obtaining detailed anatomical data, though, is not a simple task. Despite recent progress, acquiring neuron details still involves using labor-intensive, error prone methods that facilitate the introduction of inaccuracies and mistakes. In consequence, getting reliable morphological tracings usually needs the completion of post-processing steps that require user intervention to ensure the extracted data accuracy. Within this framework, this paper presents NeuroEditor, a new software tool for visualization, editing and correction of previously reconstructed neuronal tracings. This tool has been developed specifically for alleviating the burden associated with the acquisition of detailed morphologies. NeuroEditor offers a set of algorithms that can automatically detect the presence of potential errors in tracings. The tool facilitates users to explore an error with a simple mouse click so that it can be corrected manually or, where applicable, automatically. In some cases, this tool can also propose a set of actions to automatically correct a particular type of error. Additionally, this tool allows users to visualize and compare the original and modified tracings, also providing a 3D mesh that approximates the neuronal membrane. The approximation of this mesh is computed and recomputed on-the-fly, reflecting any instantaneous changes during the tracing process. Moreover, NeuroEditor can be easily extended by users, who can program their own algorithms in Python and run them within the tool. Last, this paper includes an example showing how users can easily define a customized workflow by applying a sequence of editing operations. The edited morphology can then be stored, together with the corresponding 3D mesh that approximates the neuronal membrane.

Being Bhil: The politics of becoming indigenous in India and Pakistan

ABSTRACT This article, based on ethnographic fieldwork and archival data, examines the limits of indigeneity and the role of the nation state in unintentionally fostering or discouraging identity formations of certain kinds. It focuses on Bhils, the largest ‘tribal’ group in South Asia with a population of around 17 million, to ask why they are seen as ‘indigenous’ in India though not in Pakistan. It shows how the colonial category of ‘tribes’ for the Bhils has been sustained and strengthened in postcolonial India due to institutional and bureaucratic practices, vernacular publications, upper-caste and transnational activism while a different set of actions by the state of Pakistan have resulted in absence of such ‘regimes of discipline.’ This divergent scenario is contrasted with a field view of the rural countryside by describing the complexity of self-identity and claims-making of the Bhils around the Narmada Valley, India and Tharparkar, Sindh province, Pakistan. The identity claims of the Bhils in both the countries, ranging from Kshatriya (upper-caste warriors) to Dalits (formerly ‘untouchable’ castes) show striking similarities, though also differ at times and is mostly at odds with the global indigeneity discourse and the administrative categories.

Fixed point sets and orbit spaces of wedge of three spheres

Let X be a finite CW-complex having mod p cohomology isomorphic to a wedge of three spheres Sn∨Sm∨Sl,1≤n≤m≤l. The aim of this paper is to determine the fixed point sets of actions of the cyclic group of prime order on X. We also classify the orbit spaces of free actions of G=Zp,p a prime or G=Sd,d=1 or 3, on X and derive the Borsuk-Ulam type results.

Минимизация трудоемкости выполнения комплекса вспомогательных действий для операций механической обработки

Abstract. The technological process of manufacturing mechanical engineering products using metal-cutting machines is a structurally complex process. This process can be described by the combination of two types of actions: the working stroke, which results in a change in the structure and properties of the workpiece, and an auxiliary transition, the task of which is to prepare the technological system for the execution of the working process. The execution 
 of auxiliary transitions does not entail a change in the structure and properties of the product, but leads to an increase in the complexity of its manufacture, therefore, increasing the efficiency of technological processes of mechanical processing largely depends on optimizing the complexity of performing a complex of auxiliary transitions. The purpose of the work is to develop a model for optimizing the parameters of a complex of auxiliary transitions for machining operations. The structure of the control object “Technological system” is described, within which two subcategories of control objects are defined: the control object “Technological equipment” and the control object “Wearable equipment”. Hypergraphs of changes in their intermediate states are presented for these subcategories of control objects. According to the presented models, the subcategory of the control object “Technological equipment” has 4 levels of control, the subcategory of the control object “Wearable tooling” has 3 levels of control. Lists of single and vector optimization criteria have been formed for the intermediate states of control objects. A description of a set of actions for the transition of control objects from the (i – 1) state to thei-estate is presented. A list of control parameters has been defined for each subcategory of the control object. The use of the presented model contributes to increasing the efficiency of the technological process by optimizing the values of the parameters of the complex of auxiliary actions at the stage of technological preparation of production.

Bulk Power Systems Emergency Control Based on Machine Learning Algorithms and Phasor Measurement Units Data: A State-of-the-Art Review

Modern electrical power systems are characterized by a high rate of transient processes, the use of digital monitoring and control systems, and the accumulation of a large amount of technological information. The active integration of renewable energy sources contributes to reducing the inertia of power systems and changing the nature of transient processes. As a result, the effectiveness of emergency control systems decreases. Traditional emergency control systems operate based on the numerical analysis of power system dynamic models. This allows for finding the optimal set of preventive commands (solutions) in the form of disconnections of generating units, consumers, transmission lines, and other primary grid equipment. Thus, the steady-state or transient stability of a power system is provided. After the active integration of renewable sources into power systems, traditional emergency control algorithms became ineffective due to the time delay in finding the optimal set of control actions. Currently, machine learning algorithms are being developed that provide high performance and adaptability. This paper contains a meta-analysis of modern emergency control algorithms for power systems based on machine learning and synchronized phasor measurement data. It describes algorithms for determining disturbances in the power system, selecting control actions to maintain transient and steady-state stability, stability in voltage level, and limiting frequency. This study examines 53 studies piled on the development of a methodology for analyzing the stability of power systems based on ML algorithms. The analysis of the research is carried out in terms of accuracy, computational latency, and data used in training and testing. The most frequently used textual mathematical models of power systems are determined, and the most suitable ML algorithms for use in the operational control circuit of power systems in real time are determined. This paper also provides an analysis of the advantages and disadvantages of existing algorithms, as well as identifies areas for further research.

Uncaptured Value in the Business Model: Analysing its Modes in Social Enterprises in the Sustainable Fashion Industry

Social enterprises (SEs) combine economic and social goals and are essential pillars to contribute to a better world. SEs often manage limited resources; wasting some could mean minimizing their social contributions. This study, supported by the theoretical lens of the business model (BM), analyses the modes of uncaptured value in SEs. This qualitative study examines micro and small SEs from the sustainable fashion industry based on ethnographic views and semi-structured interviews. This study contributes to the literature and the managerial field by examining the modes of uncaptured value and their consequences while organizing them in two groups according to the set of decisions and actions of the SEs; presenting a framework that represents stages of the development of SEs according to their relationship with modes of uncaptured value; and, providing a set of valuable knowledge to support the qualification of SEs in better structuring their BMs and practices. Understanding the modes of uncaptured value in the BMs of SEs leverages the value that could be delivered but is not, especially in a context of resource scarcity and social demands.

Personalized motor imagery prediction model based on individual difference of ERP

Objective. Motor imagery-based brain–computer interaction (MI-BCI) is a novel method of achieving human and external environment interaction that can assist individuals with motor disorders to rehabilitate. However, individual differences limit the utility of the MI-BCI. In this study, a personalized MI prediction model based on the individual difference of event-related potential (ERP) is proposed to solve the MI individual difference. Approach. A novel paradigm named action observation-based multi-delayed matching posture task evokes ERP during a delayed matching posture task phase by retrieving picture stimuli and videos, and generates MI electroencephalogram through action observation and autonomous imagery in an action observation-based motor imagery phase. Based on the correlation between the ERP and MI, a logistic regression-based personalized MI prediction model is built to predict each individual’s suitable MI action. 32 subjects conducted the MI task with or without the help of the prediction model to select the MI action. Then classification accuracy of the MI task is used to evaluate the proposed model and three traditional MI methods. Main results. The personalized MI prediction model successfully predicts suitable action among 3 sets of daily actions. Under suitable MI action, the individual’s ERP amplitude and event-related desynchronization (ERD) intensity are the largest, which helps to improve the accuracy by 14.25%. Significance. The personalized MI prediction model that uses the temporal ERP features to predict the classification accuracy of MI is feasible for improving the individual’s MI-BCI performance, providing a new personalized solution for the individual difference and practical BCI application.

Contribution of proactive management of healthcare risks to the reduction of adverse events in a maternity hospital

BackgroundThe risks of the childbirth assistance process are still very high, both for mothers and babies. According to the WHO, birth-related asphyxia accounts for 23% of all 3.3 million annual...

Reinforcement learning-based multi-objective differential evolution algorithm for feature selection

Feature Selection (FS) can be used to determine the optimal subset of features from a raw dataset by reducing dimensionality and improving accuracy. In this study, a reinforcement learning-based multi-objective differential evolution algorithm (RLMODE) for FS is proposed, which is modeled as a multi-objective optimization problem. First, a reinforcement learning-based offspring generation strategy is designed. The offspring generation strategy is based on the Q-learning framework, which considers each individual in the population as an agent. The dominance relationship between an agent and its predecessor is used to encode the state. A well-chosen action set containing three typical differential evolution mutation operators is available for each agent. The reward is used to update the exclusive Q-table. Moreover, a novel Pareto front (PF) relearning strategy is devised to allow adequate communication between individuals on the PF. The PF relearning strategy reevaluates the potential value of all individuals on the PF as a whole. This promotes the propagation of excellent solutions and improves PF diversity. The proposed RLMODE initially demonstrates its strength in benchmarks. The excellent results for 17 datasets demonstrate RLMODE’s merits in terms of dimensionality reduction and accuracy improvement. Therefore, the proposed RLMODE method is a promising FS technique.

A Reinforcement Learning Approach to Guide Web Crawler to Explore Web Applications for Improving Code Coverage

Web crawlers are widely used to automatically explore and test web applications. However, navigating the pages of a web application can be difficult due to dynamic page generation. In particular, the inputs for the web form fields can affect the resulting pages and subsequent navigation. Therefore, choosing the inputs and the order of clicks on a web page is essential for an effective web crawler to achieve high code coverage. This paper proposes a set of actions to quickly fill in web form fields and uses reinforcement learning algorithms to train a convolutional neural network (CNN). The trained agent, named iRobot, can autonomously select actions to guide the web crawler to maximize code coverage. We experimentally compared different reinforcement learning algorithms, neural networks, and actions. The results show that our CNN network with the proposed actions performs better than other neural networks in terms of branch coverage using the Deep Q-learning (DQN) or proximal policy optimization (PPO) algorithm. Furthermore, compared to previous studies, iRobot can increase branch coverage by about 1.7% while reducing training time to 12.54%.

Incomplete preferences or incomplete information? On Rationalizability in games with private values

I propose a notion of Rationalizability, called Incomplete Preference Rationalizability, for games with incomplete preferences. Under an appropriate topological condition, the incomplete preference rationalizable set is non-empty and compact. I argue that incomplete orderings can be used to model incomplete information in strategic settings. Drawing on this connection, I show that in games with private values the sets of incomplete preference rationalizable actions, of belief-free rationalizable actions (Battigalli et al., 2011; Bergemann and Morris, 2017), and of interim correlated rationalizable actions (Dekel et al., 2007) of the universal type space coincide.

Mobilising transformative community-based climate change adaptation

Under-resourced and marginalised communities often have limited government support, and therefore, must decide by themselves if and how they adapt to the uncertainties of climate change. Community-based climate change adaptation (CbA) forms a plausible approach here. In practice, however, CbA projects often fail to address the underlying causes of vulnerability like power relations and sociocultural structures that influence adaptation measures adopted and outcomes. In response, this perspective paper explores the concept of transformative community-based climate change adaption (TCbA), a reflexive approach that focuses on empowering communities by reframing the decision-making context. It discusses pathways of mobilising this shift to transformative CbA in three steps: (1) specifying the characteristics of a TCbA; (2) exploring the leverage points to mobilise it, and (3) recommending a set of actions and processes that facilitate co-decided interventions at the identified leverage points. These leverage points include "the structure of information flow", "rules of the system" and “power to change system structure or self-organise". The paper concludes by emphasising that the shift to transformative CbA begins when facilitators and members of the community undertaking a CbA project are reflexive about how the societal context of decision processes, like power relations, influence community adaptation decision-making, planning and implementation.

Improving students' interest in IPS lessons by Inquiring Minds Want to Know learning model

This study aims to determine the increase in student interest in social studies subjects through the Inquiring Minds Want to Know model. This research includes planning, implementation, observation, and reflection. The research took place in 2 cycles with a sample of 34 students of class IX G SMP Negeri 34 Batam. Data collection techniques using observation, interviews, documentation and questionnaires. The validity of the research data using data triangulation with quantitative analysis. The results of this study indicate that learning using the Inquiring Minds Want To Know method is able to increase student learning interest, this is supported by an increase in fun and competition during learning, this can be seen from the results of the pre-action questionnaire of 62.3% increasing to 68.03% in cycle I, and in cycle II it increased to 73.3% and was supported by observations from cycle I of 56.5% to cycle II of 73.8%, an increase of 17.3%. From the results of observations and questionnaires, it was obtained that the average student interest in the first cycle was 62.4% and 73.6% in the second cycle. This means that students' interest in learning has exceeded the success criteria of the action set, namely 70%.

ПОДАТКОВА ЗВІТНІСТЬ: СУТНІСТЬ ТА ПОРЯДОК СКЛАДАННЯ

The article analyzes the approaches of leading national scholars to the definition of the concept of "tax reporting". The author characterizes the necessity of tax reporting, since it characterizes the status of an enterprise's obligations related to the accrual and payment of taxes and other mandatory payments. Tax reporting is submitted to the tax authorities.
 The purpose of the article is to deepen theoretical research on the essence of the concept of "tax reporting", to disclose the methodology of its preparation with a view to improving its quality, reliability and objectivity.
 Summarizing the approaches of scholars to the essence of tax reporting, it is worth noting three approaches. According to the first one, tax reporting is considered as a set of documents containing information on the calculation of tax liabilities; according to the second one, it is considered as a set of actions of the taxpayer on preparation and submission of reports; according to the third one, it is considered as a set of consolidated interrelated indicators characterizing the activities of the enterprise for a certain period.
 Having studied the essence of the concept of "tax reporting", we propose to supplement Article 14 of the Tax Code of Ukraine with the following definition: tax reporting is reporting containing information on the tax liabilities of an enterprise by type of tax and fees.
 The Ministry of Finance of Ukraine regulates tax reporting by establishing forms of tax returns, calculations and reports by type of tax and fee.
 The tax reporting procedure can be divided into 4 stages: Stage 1 - selection of the required form of tax reporting in accordance with the type of tax/fee; Stage 2 - preparation of a tax return for the tax/fee, i.e., entering data directly; Stage 3 - verification of the document for correctness of preparation, compliance of the entered data with the accounting data, correctness of determination of the tax base, taxable object, tax rate; Stage 4 - signing of tax reports.
 Based on the study of tax reporting on national taxes and fees, it should be noted that not all forms contain information on the procedure for their preparation. For the preparation of individual forms by type of tax and fees, notes are used after the main part of the tax reporting. Therefore, we believe that the central executive body that ensures the formation and implementation of the state financial policy should develop recommendations on the preparation of tax reporting forms for those taxes and fees that do not have them, as this will contribute to better coverage of information on tax liabilities and significantly reduce the number of pages of tax reports.

ShakingBot: dynamic manipulation for bagging

AbstractBag manipulation through robots is complex and challenging due to the deformability of the bag. Based on the dynamic manipulation strategy, we propose a new framework, ShakingBot, for the bagging tasks. ShakingBot utilizes a perception module to identify the key region of the plastic bag from arbitrary initial configurations. According to the segmentation, ShakingBot iteratively executes a novel set of actions, including Bag Adjustment, Dual-arm Shaking, and One-arm Holding, to open the bag. The dynamic action, Dual-arm Shaking, can effectively open the bag without the need to take into account the crumpled configuration. Then, the robot inserts the items and lifts the bag for transport. We perform our method on a dual-arm robot and achieve a success rate of 21/33 for inserting at least one item across various initial bag configurations. In this work, we demonstrate the performance of dynamic shaking action compared to the quasi-static manipulation in the bagging task. We also show that our method generalizes to variations despite the bag’s size, pattern, and color. Supplementary material is available at https://github.com/zhangxiaozhier/ShakingBot.

Trends in monitoring of Australia’s threatened birds (1990–2020): much improved but still inadequate

ABSTRACT Monitoring is vital to conservation, enabling conservation scientists to detect population declines, identify threats and measure the effectiveness of interventions. However, not all threatened taxa are monitored, monitoring quality is variable, and the various components of monitoring are likely to differ in their rates of improvement over time. We assessed the presence of monitoring and monitoring quality, using a range of metrics, for all Australia’s threatened bird taxa from 1990 to 2020 (four assessments spanning 30 years). We used our assessments to understand decadal trends in the number of taxa monitored; monitoring quality; and the groups that conduct monitoring. The monitoring of Australia’s threatened birds has increased substantially since 1990, from 19% of taxa to 75% in 2020. Monitoring quality has also improved, with 24.1% of taxa assessed overall as ‘Good’ or ‘Very Good’ in 2020 (up from 4.8% in 1990). However, by 2020, most monitoring programmes still scored poorly for Data availability/reporting, Management linkage, Demographic data and Training/succession planning. In 2020, private individuals and governments accounted for 59% of monitoring contributions, with the greatest number of taxa monitored by private individuals (79 of 166 taxa assessed). Despite improvements in monitoring since 1990, only a minority of taxa had high-quality monitoring in the most recent assessment period. Monitoring is a powerful tool in conservation, justifying investment in improving how it is conducted. We draw on our results and examples of high-quality monitoring programmes to develop a set of priority actions to improve monitoring of Australia’s threatened birds.

A Timestamp-Based Inertial Best-Response Dynamics for Distributed Nash Equilibrium Seeking in Weakly Acyclic Games.

In this article, we consider the problem of distributed game-theoretic learning in games with finite action sets. A timestamp-based inertial best-response dynamics is proposed for Nash equilibrium seeking by players over a communication network. We prove that if all players adhere to the dynamics, then the states of players will almost surely reach consensus and the joint action profile of players will be absorbed into a Nash equilibrium of the game. This convergence result is proven under the condition of weakly acyclic games and strongly connected networks. Furthermore, to encounter more general circumstances, such as games with graphical action sets, state-based games, and switching communication networks, several variants of the proposed dynamics and its convergent results are also developed. To demonstrate the validity and applicability, we apply the proposed timestamp-based learning dynamics to design distributed algorithms for solving some typical finite games, including the coordination games and congestion games.

AULA DE PORTUGUÊS COMO ENCONTRO ENTRE A OUTRA PALAVRA E A PALAVRA OUTRA: UM ESTUDO SOBRE RELAÇÕES ECOLÓGICAS

ABSTRACT This article has as its theme the event Portuguese class taken as an encounter (Ponzio, 2010a), as it pertains to the education of the students as readers and producers of text-utterances. The objective was to draw possible implications in the event Portuguese class from: a) the organizational setting of the administrative actions in the scope of the educational institution; b) the setting of the literacy events and practices in the scope of the study field groups; and c) literacy practices of the students that participated. The theoretical basis includes the Vigotskian ideology, the Bakhtin Circle and the studies in literacy. From the data gathered, I infer that there are two school cultures in the field of study, in ecological relations, which are, namely, culture of (un)ease in School 1 and culture of (re)affirmation in School 2. Thus, I support the thesis that the event Portuguese class as encounter implies ecological relations in the scope of the two school cultures coexistent in these same relationships: the (un)ease and the (re)affirmation, reiterated/feedbacked, respectively, in/by the three dimensions of the tripartite architectonics of each culture, both referenced by the other in the encounters — or lack of such encounters — of the subjects immersed in the larger ecology under study.

Educational coworking as a means of developing sustainable mobility of students

Sustainable mobility of students includes a set of actions aimed at bringing to a clean ecological lifestyle. This study is devoted to the development of sustainable mobility of students by means of coworking, the influence of this space on the training of future personnel who are able to master new technologies, apply them to solve practical problems, formulate and solve hypotheses, defend their point of view, work in a team, take responsibility not only for themselves, but also for team members. All this is possible only if there are innovative laboratories that stimulate the joint cognitive activity of students by developing the innovative potential of an educational organization by means of coworking, which motivates collaborations. Despite the increasing attention to the role of sustainable mobility used in the transport sector, at the moment there are few publications devoted to its organization and their functioning in the context of an educational organization. There is no comprehensive understanding of its importance as a mobile space for the development and maintenance of innovations in educational institutions with the possibility of developing the younger generation. That is why the innovation laboratory at the Lyceum is a tool for the formation of motivation to learn natural sciences, which allows them to jointly solve tasks within the framework of project activities, developing sustainable mobility for them. The coworking model of work in the lyceum environment not only contributes to the development of sustainable mobility, but also develops key skills in all participants of the educational process, such as self-organization, time management, presentation and communication skills.

The need and prerequisites for conducting an unaccountable form of VAT calculation

The article discusses the prerequisites for the creation of a new concept of VAT calculation based on the transfer of the function of calculating VAT to tax authorities through invoices, with the simultaneous cancellation of tax reporting on this tax. This concept implies that sellers issue invoices in electronic form through an electronic document management operator, who will transfer them to the tax authorities for their calculation of tax and billing to the taxpayer for payment. This approach will eliminate the need for businesses to comply with frequently changing tax laws and reduce the risks of tax evasion. The topic of the article is relevant because the current concept of the procedure for calculating and declaring taxes was introduced in the last century and is aimed at self-calculation of taxes by the taxpayer with subsequent preparation and filing of tax returns. However, modern conditions raise the issue of effective tax calculation in a new way and allows shifting these functions to fiscal authorities. The purpose of the study is to determine the readiness of the current situation for the introduction of a new concept of VAT calculation, the subject is the current VAT calculation mechanism. This work has practical significance, which consists in the potential introduction of a new concept of tax calculation. Before considering the issue outlined in this article, it is necessary to understand the conceptual apparatus, however, the study of tax terms does not relate to the topic of this work, which is why it will not be given. Therefore, for the purposes of this article, the calculation and procedure for calculating taxes means a set of actions of a taxpayer (or a tax authority in the case of transfer of such a function to it) to determine the amount of tax due to the budget.