Place Distress and Job Growth: Are Recent Job Growth Trends Significantly More Favorable for Distressed Counties?

This paper examines whether recent job growth trends have become more favorable toward counties with greater baseline economic distress. Job growth trends are “competitive job growth,” which is defined as growth that exceeds what would be expected based on how a county’s industries are growing nationally. Baseline county distress is measured by the county’s “prime-age employment rate,” the employment to population ratio for 25–54-year-olds. The core findings are fourfold. First, for the most distressed counties, job growth trends have become more favorable since 2019, compared to the 2001–2007 and 2007–2019 periods. The timing of this recent improvement is consistent with a possible influence of recent federal policies. Second, for the least distressed counties, job growth trends have become less favorable in post-2019 growth and 2007–2019 growth compared to the 2001–2007 period. The timing suggests these trends are probably due not to recent federal policies but rather to other economic forces such as rising costs in some less distressed counties. Third, similar trends are also evident for industry groups such as manufacturing and high-tech, again industries which recently have been targeted by federal policies. Fourth, these recent trends toward greater job growth in more distressed counties are modest in size, in the sense that they are insufficient to significantly lower employment rate gaps between more distressed counties and the national average

Almost perfect nonlinear power functions with exponents expressed as fractions

Let $F$ be a finite field, let $f$ be a function from $F$ to $F$, and let $a$ be a nonzero element of $F$. The discrete derivative of $f$ in direction $a$ is $\Delta_a f \colon F \to F$ with $(\Delta_a f)(x)=f(x+a)-f(x)$. The differential spectrum of $f$ is the multiset of cardinalities of all the fibers of all the derivatives $\Delta_a f$ as $a$ runs through $F^*$. The function $f$ is almost perfect nonlinear (APN) if the largest cardinality in the differential spectrum is $2$. Almost perfect nonlinear functions are of interest as cryptographic primitives. If $d$ is a positive integer, the power function over $F$ with exponent $d$ is the function $f \colon F \to F$ with $f(x)=x^d$ for every $x \in F$. There is a small number of known infinite families of APN power functions. In this paper, we re-express the exponents for one such family in a more convenient form. This enables us to give the differential spectrum and, even more, to determine the sizes of individual fibers of derivatives.Comment: 30 page

A Comparison of Optimization Techniques for Power Patterns with Low Sidelobes Generated by Linear Arrays with Efficient Excitation Distributions

This is the peer reviewed version of the following article: S. Kyle Smith; Julio C. Brégains; Kathleen L. Melde; Francisco Ares " comparison of optimization techniques for power patterns with low sidelobes generated by linear arrays with efficient excitation distributions", Microwave and Optical Technology Letters, 57 - 60 Volume: 45, Issue: 1, Apr. 2005, which has been published in final form at DOI: 10.1002/mop.20722. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."[Abstract] Equispaced linear arrays that have uniformly excited central elements and monotonically decreasing flanking segments have been shown to yield low-sidelobe patterns with specified constraints on the effective radiated voltage (ERV). An analytical method for generating these distributions using a constrained least-squares (CLS) method, with restrictions on both the peak amplitude of the elements and the ERV, has been discussed in a previous work. Simulated annealing (SA) is a versatile global-optimization technique that can be effectively used for similar purposes, but can also provide additional control over some other design parameters. In this paper, we inspect both methods—indicating some of their advantages and drawbacks—through some numerical results

What Is the Best Reference RNA? And Other Questions Regarding the Design and Analysis of Two-Color Microarray Experiments

The reference design is a practical and popular choice for microarray studies using two-color platforms. In the reference design, the reference RNA uses half of all array resources, leading investigators to ask: What is the best reference RNA? We propose a novel method for evaluating reference RNAs and present the results of an experiment that was specially designed to evaluate three common choices of reference RNA. We found no compelling evidence in favor of any particular reference. In particular, a commercial reference showed no advantage in our data. Our experimental design also enabled a new way to test the effectiveness of pre-processing methods for two-color arrays. Our results favor using an intensity-normalization and foregoing background-subtraction. Finally, we evaluate the sensitivity and specificity of data quality filters, and propose a new filter that can be applied to any experimental design and does not rely on replicate hybridizations

Analysis of methods for assimilating fire perimeters into a coupled fire-atmosphere model

Correctly initializing the fire within coupled fire-atmosphere models is critical for producing accurate forecasts of meteorology near the fire, as well as the fire growth, and plume evolution. Improperly initializing the fire in a coupled fire-atmosphere model can introduce forecast errors that can impact wind circulations surrounding the fire and updrafts along the fire front. A well-constructed fire initialization process must be integrated within coupled fire-atmosphere models to ensure that the atmospheric component of the model does not become numerically unstable due to excessive heat fluxes released during the ignition, and that realistic fire-induced atmospheric circulations are established at the model initialization time. The primary objective of this study is to establish an effective fire initialization method in a coupled fire-atmosphere model, based on the analysis of the impact of the initialization procedure on the model’s ability to resolve fire-atmosphere circulations and fire growth. Here, we test three different fire initialization approaches leveraging the FireFlux II experimental fire, which provides a comprehensive suite of observations of the pyroconvective column, local micrometeorology, and fire characteristics. The two most effective fire initialization methods identified using the FireFlux II case study are then tested on the 380,000-acre Creek Fire, which burned across the central Sierra Nevada mountains during the 2020 Western U.S. wildfire season. For this case study, simulated pyroconvection and fire progression are evaluated using plume top height observations from MISR and airborne fire perimeter data, to assess the effectiveness of different initialization methods in the context of establishing pyroconvection and resolving the fire growth. The analyses of both the experimental fire simulation and the wildfire simulation indicate that the spin-up initialization method based on historical fire progression that masks out inactive fire regions provides the best results in terms of resolving the fire-induced vertical circulation and fire progression

Sampling related individuals within ponds biases estimates of population structure in a pond‐breeding amphibian

Effective conservation and management of pond‐breeding amphibians depends on the accurate estimation of population structure, demographic parameters, and the influence of landscape features on breeding‐site connectivity. Population‐level studies of pond‐breeding amphibians typically sample larval life stages because they are easily captured and can be sampled nondestructively. These studies often identify high levels of relatedness between individuals from the same pond, which can be exacerbated by sampling the larval stage. Yet, the effect of these related individuals on population genetic studies using genomic data is not yet fully understood. Here, we assess the effect of within‐pond relatedness on population and landscape genetic analyses by focusing on the barred tiger salamanders (Ambystoma mavortium) from the Nebraska Sandhills. Utilizing genome‐wide SNPs generated using a double‐digest RADseq approach, we conducted standard population and landscape genetic analyses using datasets with and without siblings. We found that reduced sample sizes influenced parameter estimates more than the inclusion of siblings, but that withinpond relatedness led to the inference of spurious population structure when analyses depended on allele frequencies. Our landscape genetic analyses also supported different models across datasets depending on the spatial resolution analyzed. We recommend that future studies not only test for relatedness among larval samples but also remove siblings before conducting population or landscape genetic analyses. We also recommend alternative sampling strategies to reduce sampling siblings before sequencing takes place. Biases introduced by unknowingly including siblings can have significant implications for population and landscape genetic analyses, and in turn, for species conservation strategies and outcomes

Relationship Between Neck Circumference and Cardiometabolic Parameters in HIV-Infected and non–HIV-Infected Adults

OBJECTIVE: Upper body fat is associated with increased cardiometabolic risk. More recently, neck circumference (NC) and/or neck fat have been associated with hyperlipidemia, impaired glucose homeostasis, and hypertension. The objective of this study was to determine whether this relationship is evident in HIV-infected individuals, who often exhibit changes in relative fat distribution, and to determine whether NC is independently associated with carotid intima-media thickness (cIMT) in HIV and non–HIV-infected patients. RESEARCH DESIGN AND METHODS: Body composition, including anthropometrics, visceral adipose tissue assessment by CT, and metabolic parameters, including lipids, cIMT, and oral glucose tolerance test, were measured in 174 men and women with HIV infection and 154 non–HIV-infected subjects. NC was measured in triplicate inferior to the laryngeal prominence. RESULTS: In univariate analysis, NC was significantly and positively related to blood pressure, hemoglobin A1c, glucose, and insulin and significantly and negatively related to HDL cholesterol in HIV-infected individuals and HIV-negative control subjects. NC was significantly associated with cIMT in univariate regression analysis among HIV-infected (r = 0.21, P = 0.006) and non–HIV-infected (r = 0.31, P = 0.0001) patients. This relationship remained significant among non–HIV-infected patients (R2 = 0.45, P < 0.001) but not HIV-infected patients in multivariate modeling controlling for age, sex, race, smoking hypertension, glucose, and lipids. CONCLUSIONS: Among both HIV and non–HIV-infected patients, increased NC is strongly associated with decreased HDL and impaired glucose homeostasis. Among non–HIV-infected subjects, NC also predicts increased cIMT when controlling for traditional risk factors

Broadly Shared Local Economic Success Since 2000: New Measures and New Lessons for Communities

In recent decades, many local labor markets—especially those in former industrial areas—have experienced lagging employment rates, hourly wages, and annual earnings. Even in places that have thrived, disadvantaged racial and ethnic groups and those with less education have often fared poorly, and long-term growth has bypassed many Americans at the middle and bottom of the income distribution. This report examines the relative economic success over the past two decades (prior to the COVID pandemic) of different local labor markets throughout the United States, both for residents overall and for those of different demographic groups. We construct a new, publicly available database for economic indicators for these labor markets—both commuting zones and core-based statistical areas—for each of 160 demographic cells and three time periods. Our economic indicators account for demographic and cost-of-living differences across areas, facilitating comparisons of economic trends across geographies for different groups of interest. We show that locations that have performed well in terms of employment growth have not always performed well in terms of earnings growth; moreover, areas that have seen broad growth overall for their residents have often seen growth lag for vulnerable groups. To more systematically understand factors associated with economic success for different groups, we examine the relationship with baseline correlates and supplement these descriptive regressions with insights from narrative case studies. Although initial industry mix plays an important role, other factors, including government investment and local leadership, may matter even more