Hosing of a Long Relativistic Particle Bunch in Plasma.

Experimental results show that hosing of a long particle bunch in plasma can be induced by wakefields driven by a short, misaligned preceding bunch. Hosing develops in the plane of misalignment, self-modulation in the perpendicular plane, at frequencies close to the plasma electron frequency, and are reproducible. Development of hosing depends on misalignment direction, its growth on misalignment extent and on proton bunch charge. Results have the main characteristics of a theoretical model, are relevant to other plasma-based accelerators and represent the first characterization of hosing.

The unequal effects of the health-economy trade-off during the COVID-19 pandemic.

Despite the global impact of the coronavirus disease 2019 pandemic, the question of whether mandated interventions have similar economic and public health effects as spontaneous behavioural change remains unresolved. Addressing this question, and understanding differential effects across socioeconomic groups, requires building quantitative and fine-grained mechanistic models. Here we introduce a data-driven, granular, agent-based model that simulates epidemic and economic outcomes across industries, occupations and income levels. We validate the model by reproducing key outcomes of the first wave of coronavirus disease 2019 in the New York metropolitan area. The key mechanism coupling the epidemic and economic modules is the reduction in consumption due to fear of infection. In counterfactual experiments, we show that a similar trade-off between epidemic and economic outcomes exists both when individuals change their behaviour due to fear of infection and when non-pharmaceutical interventions are imposed. Low-income workers, who perform in-person occupations in customer-facing industries, face the strongest trade-off.

Building an alliance to map global supply networks.

New firm-level data can inform policy-making.

Forecasting the propagation of pandemic shocks with a dynamic input-output model.

We introduce a dynamic disequilibrium input-output model that was used to forecast the economics of the COVID-19 pandemic. This model was designed to understand the upstream and downstream propagation of the industry-specific demand and supply shocks caused by COVID-19, which were exceptional in their severity, suddenness and heterogeneity across industries. The model, which was inspired in part by previous work on the response to natural disasters, includes the introduction of a new functional form for production functions, which allowed us to create bespoke production functions for each industry based on a survey of industry analysts. We also introduced new elements for modeling inventories, consumption and labor. The resulting model made accurate real-time forecasts for the decline of sectoral and aggregate economic activity in the United Kingdom in the second quarter of 2020. We examine some of the theoretical implications of our model and find that the choice of production functions and inventory levels plays a key role in the propagation of pandemic shocks. Our work demonstrates that an out of equilibrium model calibrated against national accounting data can serve as a useful real time policy evaluation and forecasting tool.

Controlled Growth of the Self-Modulation of a Relativistic Proton Bunch in Plasma.

A long, narrow, relativistic charged particle bunch propagating in plasma is subject to the self-modulation (SM) instability. We show that SM of a proton bunch can be seeded by the wakefields driven by a preceding electron bunch. SM timing reproducibility and control are at the level of a small fraction of the modulation period. With this seeding method, we independently control the amplitude of the seed wakefields with the charge of the electron bunch and the growth rate of SM with the charge of the proton bunch. Seeding leads to larger growth of the wakefields than in the instability case.

Valuing the Future and Discounting in Random Environments: A Review.

We address the process of discounting in random environments, which allows valuation of the future in economic terms. We review several approaches to the problem regarding different well-established stochastic market dynamics in the continuous-time context and include the Feynman-Kac approach. We also review the relation between bond-pricing theory and discounting and introduce both the market price of risk and the risk neutral measure from an intuitive point of view devoid of excessive formalism. We provide the discount for each economic model and discuss their key results. We finally present a summary of our previous empirical studies for several countries on the long-run discount problem.

A simulation of the insurance industry: the problem of risk model homogeneity.

We develop an agent-based simulation of the catastrophe insurance and reinsurance industry and use it to study the problem of risk model homogeneity. The model simulates the balance sheets of insurance firms, who collect premiums from clients in return for insuring them against intermittent, heavy-tailed risks. Firms manage their capital and pay dividends to their investors and use either reinsurance contracts or cat bonds to hedge their tail risk. The model generates plausible time series of profits and losses and recovers stylized facts, such as the insurance cycle and the emergence of asymmetric firm size distributions. We use the model to investigate the problem of risk model homogeneity. Under the European regulatory framework Solvency II, insurance companies are required to use only certified risk models. This has led to a situation in which only a few firms provide risk models, creating a systemic fragility to the errors in these models. We demonstrate that using too few models increases the risk of nonpayment and default while lowering profits for the industry as a whole. The presence of the reinsurance industry ameliorates the problem but does not remove it. Our results suggest that it would be valuable for regulators to incentivize model diversity. The framework we develop here provides a first step toward a simulation model of the insurance industry, which could be used to test policies and strategies for capital management.

Healthy and Respectful Workplaces: The Experiences of Dental Hygienists in Canada.

INTRODUCTION: Like any health care practitioner, dental hygienists can experience mistreatment in the workplace. They can be subjected to harassment, bullying, abuse, and violence. These negative experiences can have adverse consequences on psychological and physical well-being and can lead to job dissatisfaction, depression, and burnout. The aim of this study was to describe dental hygienists' experiences related to healthy and respectful workplaces. METHODS: This was an online self-administered survey sent to all members of the Canadian Dental Hygienists Association. Respondents were asked to report the occurrence, frequency, and impact of different types of mistreatment as experienced over their career. RESULTS: In total, 3,780 dental hygienists responded to the survey (response rate = 22%). More than 70% of respondents experienced some form of mistreatment over their career from dentists, office managers, coworkers, and/or patients. Of those who experienced mistreatment, 67% reported losing the respect they felt for the offending person, 55% reported experiencing symptoms of depression, and 30% quit their job. CONCLUSIONS: Mistreatment toward dental hygienists can be prevalent in Canadian dental care settings, resulting in negative consequences to dental hygienists' well-being. KNOWLEDGE TRANSFER STATEMENT: The findings of this article suggest that measures are needed to support healthy and respectful workplaces in Canadian dental care settings. This includes but is not limited to 1) training and education for all members of the dental care team concerning mistreatment, 2) enacting policies in dental care settings to discourage these types of behaviors, and 3) providing help and support to individuals who experience these incidents.

How production networks amplify economic growth.

Technological improvement is the most important cause of long-term economic growth. In standard growth models, technology is treated in the aggregate, but an economy can also be viewed as a network in which producers buy goods, convert them to new goods, and sell the production to households or other producers. We develop predictions for how this network amplifies the effects of technological improvements as they propagate along chains of production, showing that longer production chains for an industry bias it toward faster price reduction and that longer production chains for a country bias it toward faster growth. These predictions are in good agreement with data from the World Input Output Database and improve with the passage of time. The results show that production chains play a major role in shaping the long-term evolution of prices, output growth, and structural change.

Emergent inequality and business cycles in a simple behavioral macroeconomic model.

Standard macroeconomic models assume that households are rational in the sense that they are perfect utility maximizers and explain economic dynamics in terms of shocks that drive the economy away from the steady state. Here we build on a standard macroeconomic model in which a single rational representative household makes a savings decision of how much to consume or invest. In our model, households are myopic boundedly rational heterogeneous agents embedded in a social network. From time to time each household updates its savings rate by copying the savings rate of its neighbor with the highest consumption. If the updating time is short, the economy is stuck in a poverty trap, but for longer updating times economic output approaches its optimal value, and we observe a critical transition to an economy with irregular endogenous oscillations in economic output, resembling a business cycle. In this regime households divide into two groups: poor households with low savings rates and rich households with high savings rates. Thus, inequality and economic dynamics both occur spontaneously as a consequence of imperfect household decision-making. Adding a few "rational" agents with a fixed savings rate equal to the long-term optimum allows us to match business cycle timescales. Our work here supports an alternative program of research that substitutes utility maximization for behaviorally grounded decision-making.

How market ecology explains market malfunction.

Standard approaches to the theory of financial markets are based on equilibrium and efficiency. Here we develop an alternative based on concepts and methods developed by biologists, in which the wealth invested in a financial strategy is like the abundance of a species. We study a toy model of a market consisting of value investors, trend followers, and noise traders. We show that the average returns of strategies are strongly density dependent; that is, they depend on the wealth invested in each strategy at any given time. In the absence of noise, the market would slowly evolve toward an efficient equilibrium, but the statistical uncertainty in profitability (which is calibrated to match real markets) makes this noisy and uncertain. Even in the long term, the market spends extended periods of time away from perfect efficiency. We show how core concepts from ecology, such as the community matrix and food webs, give insight into market behavior. For example, at the efficient equilibrium, all three strategies have a mutualistic relationship, meaning that an increase in the wealth of one increases the returns of the others. The wealth dynamics of the market ecosystem explain how market inefficiencies spontaneously occur and gives insight into the origins of excess price volatility and deviations of prices from fundamental values.

Transition between Instability and Seeded Self-Modulation of a Relativistic Particle Bunch in Plasma.

We use a relativistic ionization front to provide various initial transverse wakefield amplitudes for the self-modulation of a long proton bunch in plasma. We show experimentally that, with sufficient initial amplitude [≥(4.1±0.4) MV/m], the phase of the modulation along the bunch is reproducible from event to event, with 3%-7% (of 2π) rms variations all along the bunch. The phase is not reproducible for lower initial amplitudes. We observe the transition between these two regimes. Phase reproducibility is essential for deterministic external injection of particles to be accelerated.

Occupational mobility and automation: a data-driven network model.

The potential impact of automation on the labour market is a topic that has generated significant interest and concern amongst scholars, policymakers and the broader public. A number of studies have estimated occupation-specific risk profiles by examining how suitable associated skills and tasks are for automation. However, little work has sought to take a more holistic view on the process of labour reallocation and how employment prospects are impacted as displaced workers transition into new jobs. In this article, we develop a data-driven model to analyse how workers move through an empirically derived occupational mobility network in response to automation scenarios. At a macro level, our model reproduces the Beveridge curve, a key stylized fact in the labour market. At a micro level, our model provides occupation-specific estimates of changes in short and long-term unemployment corresponding to specific automation shocks. We find that the network structure plays an important role in determining unemployment levels, with occupations in particular areas of the network having few job transition opportunities. In an automation scenario where low wage occupations are more likely to be automated than high wage occupations, the network effects are also more likely to increase the long-term unemployment of low-wage occupations.

Oral Health and Cardiovascular Disease: Mapping Clinical Heterogeneity and Methodological Gaps.

BACKGROUND: Numerous studies have examined the associations between poor oral health and the incidence of cardiovascular disease (CVD) over the past 25 y. This long history of research has resulted in a broad and heterogenous epidemiological field whose implications are difficult to understand and whose methodological gaps are hard to track. OBJECTIVES: This systematic mapping review aims to systematically map clinical heterogeneity and methodological gaps in assessing the relationship between poor oral health and CVD outcomes. METHODS: Medline, Embase, and Cochrane Library were searched to identify longitudinal studies that examined the relationship between any oral health indicator and CVD outcomes. Each database was searched from its inception date and June 27, 2018. Extracted data assess the clinical heterogeneity (participants' characteristics, exposure and outcome measures, length of follow-up) and methodological gaps (availability of randomized controlled trials, utilization of time-varying exposures, propensity methods, mediation analysis, and competing risks analysis). RESULTS: Eighty-five studies met the inclusion criteria. Clinical heterogeneity is evident in participants' characteristics (age, clinical status, and occupation) and in the definitions of oral health indicators and CVD outcomes. More important, a significant proportion of studies reported unclear definitions for CVD outcomes. The search strategy did not reveal any randomized controlled trials. Time-varying exposures, propensity methods, mediation analysis, and competing risks analysis are used infrequently in the identified studies. CONCLUSION: There is a need for a universally accepted conceptual framework on the association between oral health and CVD to derive more consistent definitions for oral health and CVD outcomes that are aligned with the investigated research questions. There is also a need to use emerging research methods to maximize the impact of research in this area. KNOWLEDGE TRANSFER STATEMENT: Clinical heterogeneity is evident in the definitions of oral health indicators and cardiovascular disease outcomes. Propensity methods, mediation analysis, and competing risks analysis are used infrequently in the identified studies. The identified clinical heterogeneity and methodological gaps interfere with summarizing existing evidence and understanding their practical implications. Advancing the current understanding of the associations between oral health and cardiovascular disease goes hand in hand with minimizing clinical heterogeneity and closing the identified methodological gaps.

Conservation of the name Aeromonas eucrenophila over the name Aeromonas punctata for the organism based on type stain NCMB 74T and universally defined as 'Aeromonas DNA hybridization group 6'.

In a companion paper, we requested the Judicial Commission to correct the type strain of Aeromonas punctata from ATCC 15468T to NCMB 74T (=ATCC 23309T). Correction of this error on the 1980 Approved Lists by an Opinion of the Judicial Commission will remove the status of the name Aeromonas caviae as a junior objective synonym of A. punctata. This is important because the scientific community continues to use the name A. caviae almost exclusively instead of A. punctata. However, the corrective action of this Opinion will cause a new problem. A. punctata and A. eucrenophila will then become objective synonyms because both species will have the same type strain NCMB 74T, and A. punctata would have priority because it was published first (1890 vs. 1987). Thus, A. punctata rather than A. eucrenophila would become the correct name for DNA hybridization group 6. A. punctata has had a very confusing history since it was first described as Bacillus punctatus by Zimmermann in 1890. It was without a type strain for over 50 years, and unfortunately, has had an incorrect type strain for some 40 years. The name A. punctata as a bacterial species has been used incorrectly in the literature very frequently, either based on the wrong type strain or with the wrong definition or circumscription. The name A. punctata is not accepted or used by most specialists who study and publish scientific papers and reviews on Aeromonas. Under the heading 'Rejection of Names' Rule 56a of the Bacterial Code states reasons why the Judicial Commission can reject a name, the first is: '(1) An ambiguous name (nomen ambiguum), i.e., a name which has been used with different meanings and thus has become a source of error'. Rule 56a gives the Judicial Commission authority to place names on the list of rejected names. Our analysis of its history leads us to state unequivocally that A. punctata currently is, and has been throughout the vast majority of its history, an ambiguous name. After considering all the possible alternatives and their consequences we request the Judicial Commission to go against the rules of priority; to invoke case (1) of Rule 56a, and issue an Opinion conserving A. eucrenophila over A. punctata; and to place the name A. punctata on the list of rejected names. We argue that these actions will give instant stability to a complex and confusing situation by making A. eucrenophila rather than A. punctata the correct name for 'Aeromonas DNA hybridization group 6', an association that is almost universally accepted by the scientific community as reflected in the literature.

Proton Bunch Self-Modulation in Plasma with Density Gradient.

We study experimentally the effect of linear plasma density gradients on the self-modulation of a 400 GeV proton bunch. Results show that a positive or negative gradient increases or decreases the number of microbunches and the relative charge per microbunch observed after 10 m of plasma. The measured modulation frequency also increases or decreases. With the largest positive gradient we observe two frequencies in the modulation power spectrum. Results are consistent with changes in wakefields' phase velocity due to plasma density gradients adding to the slow wakefields' phase velocity during self-modulation growth predicted by linear theory.

Proton-driven plasma wakefield acceleration in AWAKE.

In this article, we briefly summarize the experiments performed during the first run of the Advanced Wakefield Experiment, AWAKE, at CERN (European Organization for Nuclear Research). The final goal of AWAKE Run 1 (2013-2018) was to demonstrate that 10-20 MeV electrons can be accelerated to GeV energies in a plasma wakefield driven by a highly relativistic self-modulated proton bunch. We describe the experiment, outline the measurement concept and present first results. Last, we outline our plans for the future. This article is part of the Theo Murphy meeting issue 'Directions in particle beam-driven plasma wakefield acceleration'.