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In this paper, we introduce a general concept for the analysis of temporal and multivariate data and the system LFPeers that applies this concept to temporal similarity search and results exploration. The conceptual workflow divides the analysis in two phases: a search phase to find the most similar objects to a query object before a time point t 0 in the temporal data, and an exploration phase to analyze and contextualize this subset of objects after t 0. LFPeers enables users to search for peers through interactive similarity search and filtering, explore interesting behavior of this peer group, and learn from peers through the assessment of diverging behaviors. We present the conceptual workflow to learn from peers and the LFPeers system with novel interfaces for search and exploration in temporal and multivariate data. An earlier workshop publication for LFPeers included a usage scenario targeting epidemiologists and the public who want to learn from the Covid-19 pandemic and distinguish successful and ineffective measures. In this extended paper, we now show how our concept is generalized and applied by domain experts in two case studies, including a novel case on stocks data. Finally, we reflect on the new state of development and on the insights gained by the experts in the case studies on the search and exploration of temporal data to learn from peers. [Display omitted] • Conceptual framework for temporal and multimodal similarity search and exploration. • Visual Analytics system for cause–effect analysis on temporal data. • Interactive user-defined search and exploration of data objects by similarity. [ABSTRACT FROM AUTHOR]

Extant research has highlighted the pros and cons of the use of (a) competition and (b) positive (peer) pressure as two mechanisms for invoking peer effects to bring about long-term behavior change. However, these mechanisms have been studied separately and in different contexts. In this paper, we compare the differential impacts of competition versus positive pressure-induced pro-environmental behavior change in the same target population. This study spans a seven-year horizon between 2013 and 2019 (pre-COVID) during which the workforce of about 2500 employees in the Stephan P. Clark Government Center in Miami, Florida, was split into four groups - one control and three treatment groups. Each treatment group was subjected to (a) a healthy inter-group competition through tracking, benchmarking, and comparing monthly group level electricity saving, and (b) positive pressure through the appointment of champions who encouraged pro-environmental behavior among their group members. Studying these mechanisms concurrently in the same population allows for a nuanced comparison of their differential impacts on pro-environmental behavior change. • In this paper, we compare the differential impacts of competition-induced spillover and supervision-induced peer pressure in affecting pro-environmental behavior change in the same target over a seven-year analysis horizon. • The study spans 2013-2019 during which the workforce of about 2500 employees in a building was split into four groups (one control and three treatment) and was subjected to both peer pressure and healthy competition. • The study spans 2013-2019 during which the workforce of about 2500 employees in a building was split into four groups (one control and three treatment) and was subjected to both peer pressure and healthy competition. • These results have implications for the design of pro-environment campaigns that could leverage peer effects through fostering an environment of intragroup pride and healthy inter-group rivalry sprinkled with intermittent supervisory interventions for making long-term impacts. [ABSTRACT FROM AUTHOR]

This paper examines the predictive value of peer's observations of an individual, applied to computational models of certain states of that individual. In a study of 28 days, 13 participants provided self-assessments about their level of stress, fatigue, and anxiety, while their smartphone passively recorded the sensor's data. Simultaneously, their designated peers provided assessments about the level of stress, fatigue, and anxiety they perceived from the participant using the PeerMA method. We extracted sensor-derived features (sDFs) from the participant's smartphone, and peer-derived features (pDFs) from the peer's assessments. We evaluated the pDFs on a binary classification task using three machine learning algorithms (Decision Tree-DT, Random Forest-RF, and Extreme Gradient Boosting-XGB). As a result, the classification accuracy consistently increased when the algorithms were trained with the sDFs plus the pDFs, compared the tradition of using only the sDFs. More importantly, the classification accuracy was the highest when we trained the algorithms only with the pDFs (73.3% DT, 73.7% RF, and 71.1% XGB), which represents a unique contribution of this paper. The findings are encouraging about the incorporation of peer's observations in machine learning with potential benefits in the fields of personal sensing and pervasive computing, especially for mental health and well-being. [ABSTRACT FROM AUTHOR]

In recent years, green innovation has become an important means of achieving sustainable development, but the impact of peer firms on green innovation is less discussed. To fill this research gap, this paper explores the effect of peer firms on the green innovation activities of the Chinese A-share listed firms in the manufacturing industry from 2011 to 2020 and investigates influencing factors of peer effect. The main findings are as follows. First, there is a peer effect in making green innovation decisions. Second, industry competition has a positive moderating effect on the peer effect of green innovation. Third, digital financial inclusion and government intervention both promote the peer effect of green innovation. The peer effect is more significant with a high degree of digital financial inclusion. But the peer effect has no significant difference between different degrees of government intervention. This paper aims to explore the influencing factors of a firm's green innovation from the perspective of peer effect. The research results can provide a guide for the government to better promote green innovation activities of firms and benign competition in the industry. • A firm's green innovation activities are positively affected by industry peers. • Industry competition has a positive moderating effect on green innovation peer effect. • Digital financial inclusion and government intervention both promote the peer effect. • The peer effect is more significant with a high degree of digital financial inclusion. • The peer effect has no significant difference between different degrees of government intervention. [ABSTRACT FROM AUTHOR]

Abstract: Learning nurtured through experimentation is very important for enabling sustainability transitions. Over the last decade, different strands of research have investigated social learning and its associated processes to better understand learning efforts aimed at socio-technical system change. While some necessary process considerations to enable social learning have been established, actual design and organisation of experiments that aim to create a social learning situation remain largely unexplored. Against this background, this paper presents an empirical, mixed-method study that investigated a governance experiment within the Australian urban water sector. This experiment enabled widespread learning, resulting in socio-technical system change. The research reveals that social learning in particular is more complex in reality than in theory and that not all system stakeholders need to learn the same to achieve system change. Further, this paper develops a framework that outlines enabling starting conditions and features for designing and organising social learning situations. The framework comprises focus projects, multi-organisational peer groups, distributed facilitation, adaptability and flexibility, time and science/research. The key findings provide practical strategies for designing and operationalising policy and governance reform agendas that embrace learning situations. [Copyright &y& Elsevier]

Abstract: This paper estimates the causal effect of taking a course in quantitative reasoning on students’ academic performance and classroom peer-group composition at a liberal arts college. To identify effects, the paper compares the outcomes of otherwise similar students who barely passed a baseline quantitative skills assessment (not taking the course) with students who barely failed (taking the course). The regression-discontinuity estimates show little impact on academic outcomes for student close to the passing cutoff, including grades on subsequent courses with quantitative content, but we are unable to distinguish small from zero effects. Exogenous course assignment does affect the composition of students’ classroom peer groups in subsequent years. The effects can only be generalized to students in the vicinity of the passing threshold (but not students with much worse quantitative skills at the baseline). We discuss implications for research and policy on remediation. [Copyright &y& Elsevier]

This paper estimates how peers’ achievement gains are affected by the presence of potentially disruptive and emotionally sensitive children in the school-cohort. We exploit that some children move between schools and thus generate variation in peer composition in the receiving school-cohort. We identify three groups of potentially disruptive and emotionally sensitive children from detailed Danish register data: children with divorced parents, children with parents convicted of crime, and children with a psychiatric diagnosis. We find that adding potentially disruptive children lowers the academic achievement of peers by about 1.7–2.3% of a standard deviation. [ABSTRACT FROM AUTHOR]

Building energy use benchmarking is the process of measuring the energy performance of buildings relative to their peer group for creating awareness and identifying energy-saving opportunities. In this paper, we present the design and implementation of BEEM , a data-driven energy use benchmarking system for buildings in Singapore. The peer groups for comparison are established using a public energy disclosure data set. We use an ensemble tree algorithm for accurately modeling building energy use and for identifying the most influential factors. Our models reduce the prediction error from 24.39% to 6.04%, on average, when compared to the baseline linear regression models, which were used in the previous energy efficiency labeling program in Singapore, and outperforms ten other recent models. Using the prototype implementation of BEEM, we benchmarked three building types, office (290), hotel (203), and retail (125), and compared their rating. The code repository and the accompanying data set are released as an open-source project for community use. [ABSTRACT FROM AUTHOR]

Abstract: Using longitudinal administrative data from a large elite research university, this paper analyzes the role of peers and grades in determining major persistence in the life and physical sciences. In the physical sciences, analyses using within-course, across-time variation show that ex-ante measures of peer quality in a student''s introductory courses has a lasting impact on the probability of persisting in the major. This peer effect exhibits important non-linearities such that weak students benefit from exposure to stronger peers while strong students are not dragged down by weaker peers. In both the physical and the life sciences, I find evidence that students are “pulled away” by their high grades in non-science courses and “pushed out” by their low grades in their major field. In the physical sciences, females are found to be more responsive to grades than males, consistent with psychological theories of stereotype vulnerability. [Copyright &y& Elsevier]

Abstract: In this paper we consider the stress–displacement–rotation formulation of the plane linear elasticity problem with pure traction boundary conditions and develop a new dual-mixed finite element method for approximating its solution. The main novelty of our approach lies on the weak enforcement of the non-homogeneous Neumann boundary condition through the introduction of the boundary trace of the displacement as a Lagrange multiplier. A suitable combination of PEERS and continuous piecewise linear functions on the boundary are employed to define the dual-mixed finite element scheme. We apply the classical Babuška–Brezzi theory to show the well-posedness of the continuous and discrete formulations. Then, we derive a priori rates of convergence of the method, including an estimate for the global error when the stresses are measured with the L 2-norm. Finally, several numerical results illustrating the good performance of the mixed finite element scheme are reported. [Copyright &y& Elsevier]

The design studio, at the heart of design education everywhere, embodies the underlying presumption that students who work side by side, and often in collaboration, benefit from being exposed to a large number of ideas of peers and instructors. Good ideas, it is believed, are the base for creative design processes. In this study we follow ideas as communicated in the studio during a semester-long exercise. We ask: when and how are ideas influential? Which ideas qualify as good ideas, and how are they developed? How do they lead to a good product? Previous research, which is briefly reviewed here, shows that influential (critical, in our terminology) ideas share a fundamental property: they are richly interlinked with other ideas. In this paper we substantiate this tenet by showing that this is also the case in the design studio. In addition, we look at other properties of design ideas and correlate them with students'' project grades, which are indicative of successful, and creative, design outcomes. [Copyright &y& Elsevier]

Abstract: In this paper we unify the derivation of finite element subspaces guaranteeing unique solvability and stability of the Galerkin schemes for a new class of dual-mixed variational formulations. The approach, which has been applied to several linear and nonlinear boundary value problems, is based on the introduction of additional unknowns given by the flux and the gradient of velocity, and by the stress and strain tensors and rotations, for fluid mechanics and elasticity problems, respectively. In this way, the procedure yields twofold saddle point operator equations as the resulting weak formulations (also named dual–dual ones), which are analyzed by means of a slight generalization of the well known Babuška–Brezzi theory. Then, in order to introduce well posed Galerkin schemes, we extend the arguments used in the continuous case to the discrete one, and show that some usual finite elements need to be suitably enriched, depending on the nature of the problem. This leads to piecewise constant functions, Raviart–Thomas of lowest order, PEERS elements, and the deviators of them, as the appropriate subspaces. [Copyright &y& Elsevier]

This paper examines the effects of Asian peers on non-Asian student achievement in New York City public schools. We use exogenous variation in the share of Asian students across cohorts within schools stemming from a fertility shock among the Asian population in the Chinese year of the Dragon. Results show that a 10-percentage-point increase in the share of Asian students reduces non-Asian math and ELA scores by 0.14 and 0.16 standard deviations. The reduction in achievement is associated with an increase in the share of non-Asian students who fail to demonstrate the skills expected at the grade, especially in math. [ABSTRACT FROM AUTHOR]