The use of exp(iS[x]) in the sum over histories

The use of $\sum \exp(iS[x])$ as the generic form for a sum over histories in configuration space is discussed critically and placed in its proper context. The standard derivation of the sum over paths by discretizing the paths is reviewed, and it is shown that the form $\sum \exp(iS[x])$ is justified only for Schrodinger-type systems which are at most second order in the momenta. Extending this derivation to the relativistic free particle, the causal Green's function is expressed as a sum over timelike paths, and the Feynman Green's function is expressed both as a sum over paths which only go one way in time and as a sum over paths which move forward and backward in time. The weighting of the paths is shown not to be $\exp(iS[x])$ in any of these cases. The role of the inner product and the operator ordering of the wave equation in defining the sum over histories is discussed.Comment: 22 pages, Latex, Imperial-TP-92-93-4

The 2024 Europe report of the Lancet Countdown on health and climate change: unprecedented warming demands unprecedented action

Record-breaking temperatures were recorded across the globe in 2023. Without climate action, adverse climate-related health impacts are expected to worsen worldwide, affecting billions of people. Temperatures in Europe are warming at twice the rate of the global average, threatening the health of populations across the continent and leading to unnecessary loss of life. The Lancet Countdown in Europe was established in 2021, to assess the health profile of climate change aiming to stimulate European social and political will to implement rapid health-responsive climate mitigation and adaptation actions. In 2022, the collaboration published its indicator report, tracking progress on health and climate change via 33 indicators and across five domains. This new report tracks 42 indicators highlighting the negative impacts of climate change on human health, the delayed climate action of European countries, and the missed opportunities to protect or improve health with health-responsive climate action. The methods behind indicators presented in the 2022 report have been improved, and nine new indicators have been added, covering leishmaniasis, ticks, food security, health-care emissions, production and consumption-based emissions, clean energy investment, and scientific, political, and media engagement with climate and health. Considering that negative climate-related health impacts and the responsibility for climate change are not equal at the regional and global levels, this report also endeavours to reflect on aspects of inequality and justice by highlighting at-risk groups within Europe and Europe's responsibility for the climate crisis

Reliability Estimation In Interaction Analysis

Interaction analysts use a variety of nominal, ordinal, and interval level tests to assess coding reliability. This paper evaluates approaches to measuring reliability in interaction analysis by: (1) presenting criteria for a sound reliability estimate, (2) evaluating currently used tests against these criteria, and (3) discussing application of appropriate tests to interaction data. © 1984, Taylor & Francis Group, LLC. All rights reserved

Winds of Change: A Century of Agroclimate Research

Climate has been of primary concern from the beginning of agricultural research. Early in the 20th century, climatology and agronomy evolved separately, focusing primarily on production agriculture and crop adaptation. Concepts developed include thermal units and water use efficiency. The integrated discipline of agroclimatology developed in the mid-20th century. As theoretical understanding evolved, numerous papers related to agroclimatology were named Citation Classics. Spectral properties of plants and soils were identified that underpin today’s remote sensing technologies. Commercialization of instrumentation enhanced our ability to efficiently collect data using standardized methods. Private and public-sector partnerships advanced research capacity. Later in the 20th century, research focus shifted toward integrating knowledge into crop growth and agronomic models. Remote sensing provided capacity to gain theoretical and practical understanding of regional scale processes. In the early 21st century, recognition of earth as a system along with inter-related human systems is driving research and political agendas. There is a pressing need to change our data-rich to an information-rich environment. The emerging cyberinformatics field along with natural resource and agricultural system models allow us to apply climate information to assessments and decision support related to water supply, production, environmental management, and other issues. Solutions to today’s problems require interdisciplinary and multi-sectoral teams. While needs have never been greater, fewer universities maintain critical mass required to off er advance degrees in agroclimatology. It will be increasingly important that agrclimatology attract top students and provide training and practical experience in conducting integrated systems research, communications, and team skills

Empirical evaluation of computational emotional contagion models

Abstract. In social psychology, emotional contagion describes the widely observed phenomenon of one person’s emotions being influenced by surrounding people’s emotions. While the overall effect is agreed upon, the underlying mechanism of the spread of emotions has seen little quantification and application to computational agents despite extensive evidence of its impacts in everyday life. In this paper, we examine computational models of emotional contagion by implementing two models ([2] and [8]) that draw from two separate lines of contagion research: thermodynamics-based and epidemiological-based. We first perform sensitivity tests on each model in an evacuation simulation, ESCAPES, showing both models to be reasonably robust to parameter variations with certain exceptions. We then compare their ability to reproduce a real crowd panic scene in simulation, showing that the thermodynamics-style model ([2]) produces superior results due to the ill-suited contagion mechanism at the core of epidemiological models. We also identify that a graduated effect of fear and proximity-based contagion effects are key to producing the superior results. We then reproduce the methodology on a second video, showing that the same results hold, implying generality of the conclusions reached in the first scene.

A New Look at Emotional Intelligence: A Dual-Process Framework

In this article, the author provides a framework to guide¦research in emotional intelligence. Studies conducted up¦to the present bear on a conception of emotional intelligence¦as pertaining to the domain of consciousness and¦investigate the construct with a correlational approach.¦As an alternative, the author explores processes underlying¦emotional intelligence, introducing the distinction¦between conscious and automatic processing as a potential¦source of variability in emotionally intelligent¦behavior. Empirical literature is reviewed to support the¦central hypothesis that individual differences in emotional¦intelligence may be best understood by considering¦the way individuals automatically process emotional¦stimuli. Providing directions for research, the author¦encourages the integration of experimental investigation¦of processes underlying emotional intelligence with¦correlational analysis of individual differences and¦fosters the exploration of the automaticity component¦of emotional intelligence

A New Look at Emotional Intelligence: A Dual-Process Framework

In this article, the author provides a framework to guide¦research in emotional intelligence. Studies conducted up¦to the present bear on a conception of emotional intelligence¦as pertaining to the domain of consciousness and¦investigate the construct with a correlational approach.¦As an alternative, the author explores processes underlying¦emotional intelligence, introducing the distinction¦between conscious and automatic processing as a potential¦source of variability in emotionally intelligent¦behavior. Empirical literature is reviewed to support the¦central hypothesis that individual differences in emotional¦intelligence may be best understood by considering¦the way individuals automatically process emotional¦stimuli. Providing directions for research, the author¦encourages the integration of experimental investigation¦of processes underlying emotional intelligence with¦correlational analysis of individual differences and¦fosters the exploration of the automaticity component¦of emotional intelligence