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This study explores whether participation in the US Federal Emergency Management Agency’s Com- munity Rating System (CRS), a voluntary community flood risk management program, is a function of policy diffusion or an act of free-riding. Policy diffusion would suggest that, all else being equal, once a community has joined the CRS, neighboring communities will be more likely to follow their lead and participate in the CRS. Free-riding would imply that neighboring communities might choose not to participate in the CRS because they perceive that their community benefits from surrounding communities’ participation. Results indicate that a community’s decision to participate in the CRS is not influenced by the characteristics of or the behavior of their neighbors. The results of this study do, however, show that population density, aggregate housing values, rentership rate, and flat topography are significant predictors of CRS participation. 

This study systematically reviews the diverse body of research on community flood risk management in the USA to identify knowledge gaps and develop innovative and practical lessons to aid flood management decision-makers in their efforts to reduce flood losses. The authors discovered and reviewed 60 studies that met the selection criteria (e.g., study is written in English, is empirical, focuses on flood risk management at the community level in the USA, etc.). Upon reviewing the major findings from each study, the authors identified seven practical lessons that, if implemented, could not only help flood management decision-makers better understand communities’ flood risks, but could also reduce the impacts of flood disasters and improve communities’ resilience to future flood disasters. These seven lessons include: (1) recognizing that acquiring open space and conserving wetlands are some of the most effective approaches to reducing flood losses; (2) recognizing that, depending on a community’s flood risks, different development patterns are more effective at reducing flood losses; (3) considering the costs and benefits of participating in FEMA’s Community Rating System program; (4) engaging community members in the flood planning and recovery processes; (5) considering socially vulnerable populations in flood risk management programs; (6) relying on a variety of floodplain management tools to delineate flood risk; and (7) ensuring that flood mitigation plans are fully implemented and continually revised. 

Floods remain the most destructive natural hazard worldwide. Understanding and improving flood management at the community scale (i.e., levels larger than the individual or household, but smaller than regions, states, or nations) is important in order to reduce communities’ vulnerability to floods. The growing literature examining flood management at the community scale has not emphasized analysis of the impacts of a flood-risk management policy on migration and development. We contribute new evidence on the impact of the Community Ratings System (CRS), a community scale federal program, on migration and development in the United States. The CRS program was created in 1990 to enable communities to voluntarily reduce flood risks, and in return, receive discounted flood insurance premiums. Using panel data (1970–2010), the study estimates fixed-effects regressions with robust standard errors clustered by group. The results indicate that the CRS discourages new construction and the construction of mobile homes or trailers in participating communities. Also, the CRS discourages population growth, but encourages people to stay in CRS participating communities. The study will benefit both academics and practitioners by helping to illuminate the impact of the CRS on migration and development, and improve our understanding of community-scale flood risk management. 

This study analyzes which communities adopted flood risk management practices during the past 25 years. In particular, we focus on community-scale flood management efforts undertaken voluntarily in towns and counties across the United States. In 1990, the US Federal Emergency Management Agency created the Community Rating System (CRS) to provide incentives to local governments to improve flood resilience. About 1,300 counties and cities voluntarily participate in the CRS, but most eligible communities do not participate. Here, we explore the factors shaping community CRS participation, such as flood risk, socio-economic characteristics, and economic resources, and we assess the competing phenomena of policy diffusion versus free riding. Previous models of community-scale flood mitigation activities have all considered each community’s decision as independent of one another. Yet one community’s flood management activities might directly or indirectly influence its neighbors’ mitigation efforts. Spillover effects or “contagion” may arise if neighboring communities learn from or seek to emulate or outcompete early adopting neighbors. Conversely, stricter regulation in one community may allow its neighbors to capitalize on looser regulation either by attracting more development or enjoying reduced “downstream” flood risks. This paper presents a conceptual model that allows for multiple forces affecting diffusion, such as copycatting and learning from neighboring communities, free-riding on neighbors’ efforts, and competing with neighbors to provide valuable amenities. We empirically test for these alternative diffusion pathways after controlling for the spatially correlated extant flood risks, building patterns, and demographics. The analysis integrates several large datasets to predict community flood risk management for all cities and counties in the US since 1990. Controls for local flood risk combined with a spatial lag regression model allow separate identification of alternative diffusion pathways. The results indicate strong evidence of copycatting and also suggest possible free-riding. 

A study of the anomalous couplings of the Higgs boson to vector bosons, including$${\textit{CP}}$$$\mathrm{CP}$-violation effects, has been conducted using its production and decay in the WW channel. This analysis is performed on proton–proton collision data collected with the CMS detector at the CERN LHC during 2016–2018 at a center-of-mass energy of 13 TeV, and corresponds to an integrated luminosity of 138$$\,\text {fb}^{-1}$$${\text{fb}}^{-1}$. The different-flavor dilepton$$({\textrm{e}} {{\upmu }})$$$\left(\text{e}\mu \right)$final state is analyzed, with dedicated categories targeting gluon fusion, electroweak vector boson fusion, and associated production with a W or Z boson. Kinematic information from associated jets is combined using matrix element techniques to increase the sensitivity to anomalous effects at the production vertex. A simultaneous measurement of four Higgs boson couplings to electroweak vector bosons is performed in the framework of a standard model effective field theory. All measurements are consistent with the expectations for the standard model Higgs boson and constraints are set on the fractional contribution of the anomalous couplings to the Higgs boson production cross section.

 

A measurement is presented of a ratio observable that provides a measure of the azimuthal correlations among jets with large transverse momentum$$p_{\textrm{T}}$$$p_{\text{T}}$. This observable is measured in multijet events over the range of$$p_{\textrm{T}} = 360$$$p_{\text{T}}=360$–$$3170\,\text {Ge}\hspace{-.08em}\text {V} $$$3170\text{Ge}\text{V}$based on data collected by the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13$$\,\text {Te}\hspace{-.08em}\text {V}$$$\text{Te}\text{V}$, corresponding to an integrated luminosity of 134$$\,\text {fb}^{-1}$$${\text{fb}}^{-1}$. The results are compared with predictions from Monte Carlo parton-shower event generator simulations, as well as with fixed-order perturbative quantum chromodynamics (pQCD) predictions at next-to-leading-order (NLO) accuracy obtained with different parton distribution functions (PDFs) and corrected for nonperturbative and electroweak effects. Data and theory agree within uncertainties. From the comparison of the measured observable with the pQCD prediction obtained with the NNPDF3.1 NLO PDFs, the strong coupling at the Z boson mass scale is$$\alpha _\textrm{S} (m_{{\textrm{Z}}}) =0.1177 \pm 0.0013\, \text {(exp)} _{-0.0073}^{+0.0116} \,\text {(theo)} = 0.1177_{-0.0074}^{+0.0117}$$${\alpha }_{\text{S}}\left(m_{\text{Z}}\right)=0.1177\pm 0.0013{\text{(exp)}}_{-0.0073}^{+0.0116}\text{(theo)}=0.{1177}_{-0.0074}^{+0.0117}$, where the total uncertainty is dominated by the scale dependence of the fixed-order predictions. A test of the running of$$\alpha _\textrm{S}$$${\alpha }_{\text{S}}$in the$$\,\text {Te}\hspace{-.08em}\text {V}$$$\text{Te}\text{V}$region shows no deviation from the expected NLO pQCD behaviour.

 

Energy correlators that describe energy-weighted distances between two or three particles in a hadronic jet are measured using an event sample of$\sqrt{s}=13\mathrm{TeV}$proton-proton collisions collected by the CMS experiment and corresponding to an integrated luminosity of$36.3{\mathrm{fb}}^{-1}$. The measured distributions are consistent with the trends in the simulation that reveal two key features of the strong interaction: confinement and asymptotic freedom. By comparing the ratio of the measured three- and two-particle energy correlator distributions with theoretical calculations that resum collinear emissions at approximate next-to-next-to-leading-logarithmic accuracy matched to a next-to-leading-order calculation, the strong coupling is determined at the$Z$boson mass:${\alpha }_S(m_Z)=0.1229_{-0.0050}^{+0.0040}$, the most precise${\alpha }_S(m_Z)$value obtained using jet substructure observables.