Sense Of Norm Research Articles

Iterative learning approach for consensus tracking of partial difference multi-agent systems with control delay under switching topology

In this paper, the consensus tracking problem for the linear and nonlinear partial difference multi-agent systems with switching communication topology and control delay is investigated. Based on relative local measurements of neighboring followers, while considering spatio-temporal discretization and initial state deviation, a discrete distributed consensus protocol with initial value learning is designed for each agent via D-type iterative learning approach. Through rigorous mathematical theoretical analysis, the necessary and sufficient conditions are obtained. Under the switching of the communication topology, these conditions ensure that the consensus tracking control of the MASs can be solved. After applying the designed protocol, in the sense of the L2 norm and along the positive direction of the iteration axis, the consensus tracking error between any two agents can converge to zero. Finally, some simulation examples are used to demonstrate the validity of the protocol and theoretical results.

Strategically Unequal: How Class, Culture, and Institutional Context Shape Academic Strategies

When facing common setbacks like a missed due date or low assignment grade, some students take action to change the outcome while others do not. This study compares academic strategies by social class and across institutional context through interviews with working- and upper-middle-class students at a public regional and flagship university. Academic strategies are based on parentally-transmitted skills and knowledge as well as class-cultural norms of selfhood and the meaning of being a student. At the flagship, class-privileged students negotiated grades and deadlines using strategies rooted in a sense of entitlement and norms of individualism and self-exceptionalism, whereas working-class students’ norms of interdependence and compliance inhibited negotiation, reproducing existing inequalities. Institutional context mediated this effect: at the regional, both groups requested flexibility but did not (successfully) contest grades, minimizing class-privileged students’ advantage. Organizational habitus explains why academic strategies differed and were more or less likely to reproduce inequality at each university.

Maternal self-conception and mental wellbeing during the first wave of the COVID-19 pandemic. A qualitative interview study through the lens of "intensive mothering" and "ideal worker" ideology.

Mothers tended to be responsible for most of the (additional) caregiving and domestic tasks during the COVID-19 pandemic while simultaneously having to pursue their work duties. Increased role conflicts, parenting stress, and exhaustion predict adverse mental health. We aimed to examine how women referred to and made sense of dominant gender norms in their arrangements of pandemic daily life and how these beliefs impacted their maternal self-conception. Qualitative interviews with 17 women were analyzed through the lens of “intensive mothering” ideology and “ideal workers” norms, emphasizing notions of maternal guilt rising from a perceived mismatch between the ideal and actual maternal self-conception. We found that mothers' notions of guilt and their decreases in health link to dominant discourses on motherhood and intersect with “ideal worker” norms. As such, these norms amplify the burden of gendered health inequalities.

Relationship between Visitors’ Sense of Place, Recreation Behavior, and Acceptability of Resource Allocation Strategies at a Reservoir Facing a Water Crisis

Municipal drawdowns at public reservoirs can negatively impact recreational uses on site. Therefore, sustaining recreation requires understanding how users relate themselves with the reservoir and the resource therein, and how they will respond to circumstances and policies impacting the resource. Researchers use placedbased theory, particularly sense of place (SOP), to assess the user community’s perspective on the natural resource or recreation site of interest. This study utilized visitor survey data (n=282) from Canton Reservoir in Oklahoma to assess visitors’ sense of place (SOP), and to evaluate the relationship of SOP with their acceptability of alternative water allocation strategies and future intention of visiting the reservoir under depleted water conditions. Visitors had a high level of SOP with the reservoir and supported protective water allocation strategies that either favor the retention of water on-site or ensure a fair distribution between recreation and municipal use. Results suggest a positive relationship between visitors' SOP and their intended trips to the reservoir even under depleted water conditions. The findings highlight the psychological, functional, and emotional benefits associated with the recreational use of the Canton Reservoir, which will in turn help managers make more informed and balanced decisions about water conservation and allocation. Insights from this study will also contribute in literature on the sense of place and protective norms and offers several implications for the management of public reservoirs.

Singular Values of Dual Quaternion Matrices and Their Low-Rank Approximations

The dual quaternion matrix is an important and powerful tool for the study of multi-agent formation control. However, many basic properties of dual quaternion matrices are still not studied, due to the difficulty incurred by the non-commutativity of multiplication and existence of zero divisors of dual quaternion numbers. In this paper, we study some basic properties of dual quaternion matrices, including the polar decomposition theorem, the minimax principle and Weyl’s type monotonicity inequality for singular values, spectral norm and the Pythagoras theorem. Based upon these, we further present the best low-rank approximations for dual quaternion matrices, and discuss the relationship between the approximation degree characterizations of the best low-rank approximations in the sense of Frobenius norm and spectral norm, in addition to proving a fundamental property of the best low-rank approximation of dual quaternion matrices in a given subspace. These results are of importance to the applications in rigid body motion and data reduction.

Associations between the neighbourhood social environment and preschool children’s physical activity and screen time

BackgroundThe neighbourhood social environment (NSE) has been associated with physical activity and screen time behaviours in adults and youth however less is known about this relationship in preschool-aged children (2–5 years). This study seeks to explore associations between the NSE and the physical activity and screen time behaviours of preschool-aged children.MethodCross-sectional data was collected in 2019. Parents (n = 214) of preschool-aged children (m = 3.8 ± 0.8 years), from 187 different Australian postcodes representing all states and territories were invited to complete an online survey where they answered questions about their NSE (perceived social cohesion, social interaction, sense of community, social norms and neighbourhood crime) and proxy-reported their child’s usual physical activity and screen time (minutes/day). Two hierarchical linear regressions were run separately to assess relationships between NSE predictor variables and physical activity and screen time. Three logistic regressions were run to determine associations between NSE constructs and the likelihood of meeting: 1) physical activity (≥ 180 min/day including ≥ 60 min of moderate-to-vigorous-intensity), 2) screen time (≤ 60 min/day) and 3) both physical activity and screen time guidelines. Child age, gender, childcare attendance, and neighbourhood level socioeconomic status (SES) were controlled for in all analyses.ResultsSocial interaction was associated with increased daily physical activity (b = 17.76, 95%CI = 0.81, 34.71), decreased daily screen time (b = -12.77, 95%CI = -23.23, -2.23) and improved the likelihood of meeting physical activity (OR = 1.81, 95%CI = 1.20, 2.75) and combined physical activity and screen time guidelines (OR = 1.51, 95%CI = 1.03, 2.21). Higher neighbourhood crime was associated with a lower likelihood of meeting screen time guidelines (OR = 0.47, 95%CI = 0.47, 0.99). Social cohesion, sense of community and social norms were not statistically significant predictors of daily physical activity, screen time or meeting guidelines.ConclusionSocial interaction showed the most consistent associations with physical activity and screen time. Future research should consider potential mediators of this relationship, including parental facilitation of children’s outdoor time. Improving understanding of the relationship between the NSE and physical activity and screen time in young children can help to guide community-based initiatives striving to optimise behavioural, health and social outcomes.

A novel high-performance quadrature rule for BEM formulations

This paper describes a general approach to compute the boundary integral equations that appear when the boundary element method is applied for solving common engineering problems. The proposed procedure consists of a new quadrature rule to accurately evaluate singular and weakly singular integrals in the sense of the Cauchy Principal Value by an exclusively numerical procedure. This procedure is based on a system of equations that results from the finite part of known integrals, that include the shape functions used to approximate the field variables. The solution of this undetermined system of equations in the minimum norm sense provides the weights of the quadrature rule. A MATLAB script to compute the quadrature rule is included as supplementary material of this work. This approach is implemented in a boundary element method formulation based on the Bézier–Bernstein space as an approximation basis to represent both geometry and field variables for verification purposes. Specifically, heat transfer, elastostatic and elastodynamic problems are considered.

Iterative learning based consensus control for distributed parameter type multi‐agent differential inclusion systems

AbstractThis article considers the learning consensus problem of distributed parameter type multi‐agent differential inclusion systems including parabolic type and hyperbolic type. By imposing a Lipschitz condition on a set‐valued mapping and utilizing distributed ‐type iterative learning consensus control protocols, an iterative learning process is established. Further, sufficient conditions for the convergence of the consensus error between any two agents in the sense of the certain norm are obtained with the help of Steiner‐type selectors. Finally, numerical simulations verify the validity of the proposed method.

Beyond the “lowest common denominator”? Mutually binding commitments in European security and defence cooperation: the case of the Nordic states

ABSTRACT Literature on European security and defence cooperation usually asserts that differences in national security interests and security cultures prevent agreement beyond the “lowest common denominator”. I propose that it is possible for states to agree on mutually binding commitments also in this policy field. Using Nordic security and defence cooperation as a case study, I examine what characterises their mutual commitments and how we might account for them. The article adds to the literature on European security and defence cooperation by suggesting that binding commitments in security and defence would not have come about in the Nordic context without a sense of “Nordic togetherness”. This conclusion is important because it demonstrates that a shared sense of identity and norms is significant for understanding how security and defence cooperation between states is possible.

Adaptive Bundle Methods for Nonlinear Robust Optimization

Currently, there are few theoretical or practical approaches available for general nonlinear robust optimization. Moreover, the approaches that do exist impose restrictive assumptions on the problem structure. We present an adaptive bundle method for nonlinear and nonconvex robust optimization problems with a suitable notion of inexactness in function values and subgradients. As the worst-case evaluation requires a global solution to the adversarial problem, it is a main challenge in a general nonconvex nonlinear setting. Moreover, computing elements of an ε-perturbation of the Clarke subdifferential in the [Formula: see text]-norm sense is in general prohibitive for this class of problems. In this article, instead of developing an entirely new bundle concept, we demonstrate how existing approaches, such as Noll’s bundle method for nonconvex minimization with inexact information [Noll D (2013) Bundle method for non-convex minimization with inexact subgradients and function values. Computational and Analytical Mathematics, Springer Proceedings Mathematics, vol. 50 (Springer, New York), 555–592.] can be modified to be able to cope with this situation. Extending the nonconvex bundle concept to the case of robust optimization in this way, we prove convergence under two assumptions: first, that the objective function is lower C1 and, second, that approximately optimal solutions to the adversarial maximization problem are available. The proposed method is, hence, applicable to a rather general setting of nonlinear robust optimization problems. In particular, we do not rely on a specific structure of the adversary’s constraints. The considered class of robust optimization problems covers the case that the worst-case adversary only needs to be evaluated up to a certain precision. One possibility to evaluate the worst case with the desired degree of precision is the use of techniques from mixed-integer linear programming. We investigate the procedure on some analytic examples. As applications, we study the gas transport problem under uncertainties in demand and in physical parameters that affect pressure losses in the pipes. Computational results for examples in large realistic gas network instances demonstrate the applicability as well as the efficiency of the method. Summary of Contribution: Nonlinear robust optimization is a relevant field of research as real-world optimization problems usually suffer from not precisely known parameters, for example, physical parameters that cannot be measured exactly. Currently, there are few theoretical or practical approaches available for general nonlinear robust optimization. Moreover, the methods that do exist impose restrictive assumptions on the problem structure. Writing nonlinear robust optimization tasks in minimax form, in principle, bundle methods can be used to solve the resulting nonsmooth problem. However, there are a number of difficulties to overcome. First, the inner adversarial problem needs to be solved to global optimality, which is a major challenge in a general nonconvex nonlinear setting. In order to cope with this, an adaptive solution approach, which allows for inexactness, is required. A second challenge is then that the computation of elements from an ε-neighborhood of the Clarke subdifferential is, in general, prohibitive. We show how an existing bundle concept by D. Noll for nonconvex problems with inexactness in function values and subgradients can be adapted to this situation. The resulting method only requires availability of approximate worst-case evaluations, and in particular, it does not rely on a specific structure of the adversarial constraints. To evaluate the worst case with the desired degree of precision, one possibility is the use of techniques from mixed-integer linear programming. In the course of the paper, we discuss convergence properties of the resulting method and demonstrate its efficiency by means of robust gas transport problems.

Study on the Psychology of Drivers Dealing with Illegal Parking Behavior

This research intends to examine and analyze how drivers' psychology and awareness variables leading an erroneous parking behavior affect illegal parking by employing the theory of planned behavior. The theory of planned behavior is explained by the relationships among ‘Attitude toward the behavior’, ‘Subjective norms’, and ‘Perceived behavioral control’ affecting ‘Intention’ and ‘Behavior’. Using the results of drivers' parking awareness survey conducted in Changwon City in 2017, variables related to each of the attitude toward the behavior, subjective norm, and perceived behavioral control for illegal parking were extracted, and the effects they would have on behavioral intentions were analyzed. Analysis of the structural equation model revealed that Attitude toward the behavior' had a positive effect on the willingness to avoid illegal parking as ‘Intention’. On the other hand, ‘Perceived behavioral control’ had a negative effect. It was also found that the latter had bigger-minus-effect on the willingness to avoid illegal parking behavior than the former. In other words, although there is a sense of norm that illegal parking is wrong behavior, which can cause harm to people including drivers and pedestrians, etc., it means that the willingness to violate the norm is up to 2.6 times higher than to follow the norm depending on driver's situation. The results of this study will be a helpful tool for policymakers to understand the driver's parking behavior and hence to develop a rational parking management policy.

The construction of higher-order numerical approximation formula for Riesz derivative and its application to nonlinear fractional differential equations (I)

The main goal of this paper is to construct high-order numerical differential formulas approximating the Riesz derivative and apply them to the numerical solution of the nonlinear space fractional Ginzburg–Landau equations. Firstly, we introduce a novel second-order fractional central difference operator for the approximation of the Riesz derivative with order α∈(1,2]. Moreover, based on the difference operator and the compact technique, a novel fourth-order fractional compact difference operator is also derived. Secondly, using the fourth-order difference operator in space and the Crank–Nicolson method in time, a high-order difference scheme is proposed for the nonlinear space fractional Ginzburg–Landau equations. Thirdly, besides the standard energy method, some new techniques and important lemmas are developed to prove the unique solvability, stability and convergence in the sense of different norms. It is proved that the difference scheme is unconditionally stable and convergent with order Oτ2+h4 for α∈(1,1.5), where τ and h are the temporal step size and spatial step size, respectively. Finally, some numerical examples are given to show the efficiency and accuracy of the numerical differential formulas and finite difference scheme.

Leveraging Neuroscience to Fight Stigma Around Mental Health.

Labels serve as identifiers and convenient descriptors of inanimate and animate objects. In humans, given labels can easily become part of an individual’s self-perceived identity. Negative labels ascribed to a person can result in internalized stigma, a state that will shape the subject’s biography. This can ultimately impact the person’s mental and physical health since perceived and/or anticipated stigma discourages the use of social and health services. Per definition, stigma involves labeling of persons with physical, mental, or social characteristics that do not match the observer’s arbitrarily conditioned and calibrated sense of norms (public stigma); such labeling may eventually become embedded in rules, regulations, and laws (structural stigma). Internalized stigma projects onto a person’s emotions and actions. Public (enacted) stigma results from stereotyping (collectively agreed-upon notions about a group of persons that are used to categorize these people) and devaluation, which subsequently leads to social distancing, discrimination, and blatant abuse of human rights. Much of what we know about stigma results from research in the psychosocial sciences and, more recently, from social neuroscience. The stigma around mental health has generated much attention in the field of psychiatry where, to date, most research has focussed on epidemiology and anti-stigma interventions. This essay intends to stimulate thought, debate, and research within the behavioral neuroscience community and, therefore, to inform evidence-based design and implementation of neuroscience-based approaches by other professionals working towards the elimination of the stigma attached to mental illness. The article starts by considering the concept of stigma and the psychological processes that give rise to the phenomenon; it also considers how projected and perceived stigma are multiplied. Finally, after a brief review of the few existing neuroscientific explorations of stigma, gaps in our knowledge of the neurobiological basis of stigma are identified and discussed.

Pedagogical ethics and pedagogical tact

The article considers pedagogical ethics as a set of norms and rules of behavior of a teacher, which ensures the moral nature of pedagogical activity and as a science that studies the origin and nature, structure, functions and features of the manifestation of morality, and pedagogical tact as a sense of norm or observance by the teacher of the rules of behavior and etiquette, expressing its moral character and as a means of organizing interaction between the teacher and pupils.

RFN: A Random-Feature Based Newton Method for Empirical Risk Minimization in Reproducing Kernel Hilbert Spaces

In supervised learning using kernel methods, we often encounter a large-scale finite-sum minimization over a reproducing kernel Hilbert space (RKHS). Large-scale finite-sum problems can be solved using efficient variants of Newton method, where the Hessian is approximated via sub-samples of data. In RKHS, however, the dependence of the penalty function to kernel makes standard sub-sampling approaches inapplicable, since the gram matrix is not readily available in a low-rank form. In this paper, we observe that for this class of problems, one can naturally use kernel approximation to speed up the Newton method. Focusing on randomized features for kernel approximation, we provide a novel second-order algorithm that enjoys local superlinear convergence and global linear convergence (with high probability). We derive the theoretical lower bound for the number of random features required for the approximated Hessian to be close to the true Hessian in the norm sense. Our numerical experiments on real-world data verify the efficiency of our method compared to several benchmarks.

The Best Approximation of an Objective State With a Given Set of Quantum States

AbstractApproximating a quantum state by the convex mixing of some given states has strong experimental significance and provides alternative understandings of quantum resource theory. It is essentially a complex optimal problem which, up to now, has only partially solved for qubit states. Here, the most general case is focused on that the approximation of a d‐dimensional objective quantum state by the given state set consisting of any number of (mixed‐) states. The problem is thoroughly solved with a closed solution of the minimal distance in the sense of l2 norm between the objective state and the set. In particular, the minimal number of states in the given set is presented to achieve the optimal distance. The validity of this closed solution is further verified numerically by several randomly generated quantum states.

Probabilistic-constrained distributed fusion filtering for a class of time-varying systems over sensor networks: a torus-event-triggering mechanism

This paper investigates the problem of distributed fusion over sensor networks with probabilistic constraints and stochastic perturbations. In order to save the bandwidth resources, a new event-triggering mechanism (ETM), called torus-event-triggering mechanism (TETM), is utilised for data transmission. Compared with the traditional ETMs, the TETM has two thresholds, which will not only discard the sampling data smaller than the lower threshold but also hold back the packet larger than the upper threshold. The main purpose of this paper is to design a time-varying distributed fusion filter such that: (1) the probability of the filtering error falling in a given ellipsoid domain is greater than a specified value and (2) the ellipsoidal set is minimised in the sense of matrix norm at each time point. To achieve the above-mentioned purpose, sufficient conditions are given to obtain the global fusion with the help of the recursive linear matrix inequality technique. The desired local filter parameters are then computed by solving an optimisation problem with some inequality constraints. Finally, a numerical simulation is given to illustrate the effectiveness and applicability of the proposed distributed fusion strategy.

‘My dream is that I share the bed with only one man’: Perceptions and practices of premarital sex among Catholic women in Belgium

Drawing on qualitative research with Catholic women who are active in the Church in Belgium, this article sets out to analyse how these women negotiate and manage premarital sexuality. I map their practices, experiences, and strategies, and explore how they make sense of religious and secular norms regarding premarital sexuality. By using two notions as theoretical frameworks, namely religious agency and growth ethics, I argue that combining both can lead to a fertile approach to yielding new insights into the field of religion and sexuality. In so doing, I demonstrate that although not all my interlocutors refrain from sexual relations before marriage, they develop personal sexual ethics, which are distinctly informed by Catholic understandings.

일본의 학교폭력 현황과 대책

Objectives The purpose of this study was to analyze the present state and policy of school violence in Japan and to identify its characteristics.
 Methods To this end, the analysis was focused on the current situation and basic measures announced by the Japanese Ministry of Education, Culture, Sports, Science and Technology in 2020.
 Results As a result, the following four characteristics were obtained : First, the number of school violence was the highest in elementary school. In Japan, school violence was more prevalent in elementary school than in secondary school, and 1-3 grades were more common in elementary school than in grades 4-6. Second, for the prevention of school violence, there was a tendency in Japan to place importance on human relationships within schools (or classes) and to emphasize the sense of group norms. Third, Japan is emphasizing early detection of school violence and early response. Fourth, serious school violence was dealt with separately from general school violence. In the case of Japan, suicide, serious physical or physical injury, or loss of money or valuables, or students not attending school for a long period of time, were considered a serious situation, and special measures were taken.
 Conclusions School violence in Japan has shown a tendency to increase little by little over the past five years, and the Ministry of Education, Culture, Sports, Science and Technology (MEXT) in Japan responds specifically to the prevention of school violence, focusing on four main areas: prevention, early detection, early response, and response to serious situations.

Error bounds for the spectral approximation of the potential of a homogeneous almost spherical body

Several kinds of approximation of the gravitational potential of a homogeneous body by truncated spherical harmonics series are in use in physical geodesy. However, only one of them is capable of a representation converging to the true potential in the whole layer between the Brillouin sphere and the Bjerhammar sphere of the body. We aim at providing various majorizations, namely upper bounds, of the error with the double purpose of proving explicitly the convergence in the sense of different norms and of giving computable bounds, that might be used in numerical studies. The first aim is reached for all the norms. For the second, however, it turns out that among the bounds, when applied to the example of the terrain correction of the Earth, only those referring to the mean absolute error and the mean squared error at the level of Brillouin sphere of minimum radius give significant and useful results. In order to make the computation an easy exercise, a simple approximate formula has been developed requiring only the use of the distribution function of the heights of the surface of the body with respect to the Bjerhammar sphere.