6,145 research outputs found

    The weak jobs recovery: whatever happened to "the great American jobs machine"?

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    Authors Freeman and Rodgers find that the current recovery, which started in 2001, has been the worst in recent history in terms of job creation. They determine that the slow employment growth of the recovery is not attributable to the poor performance of a particular sector, nor is it concentrated in certain geographic areas. ; The authors conclude that the weak jobs recovery represents a major shift in the link between the labor market and the economy over the business cycle. They also find that the slow job growth has disproportionate effects on groups especially sensitive to business cycle swings, such as African-Americans, new labor-market entrants, out-of-school youth and less educated workers.Labor market ; Business cycles ; Economic conditions

    Area Economic Conditions and the Labor Market Outcomes of Young Men in the 1990s Expansion

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    The current expansion has shattered the length of the previous longest peace-time boom and brought unemployment rates below four percent in 44 percent of metropolitan areas. We estimate the expansion's impact on the labor market outcomes of less-educated men. We find that young men, especially young African American men in tight labor markets experienced a boost in employment and earnings. Adult men had no gains, and their earnings barely changed even in areas with unemployment rates below 4 percent. Youths have higher earnings and employment in low crime states and poorer labor market outcomes in states where incarcerations are high.

    Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks

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    We study the problem of synthesizing a number of likely future frames from a single input image. In contrast to traditional methods, which have tackled this problem in a deterministic or non-parametric way, we propose a novel approach that models future frames in a probabilistic manner. Our probabilistic model makes it possible for us to sample and synthesize many possible future frames from a single input image. Future frame synthesis is challenging, as it involves low- and high-level image and motion understanding. We propose a novel network structure, namely a Cross Convolutional Network to aid in synthesizing future frames; this network structure encodes image and motion information as feature maps and convolutional kernels, respectively. In experiments, our model performs well on synthetic data, such as 2D shapes and animated game sprites, as well as on real-wold videos. We also show that our model can be applied to tasks such as visual analogy-making, and present an analysis of the learned network representations.Comment: The first two authors contributed equally to this wor

    Physical Primitive Decomposition

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    Objects are made of parts, each with distinct geometry, physics, functionality, and affordances. Developing such a distributed, physical, interpretable representation of objects will facilitate intelligent agents to better explore and interact with the world. In this paper, we study physical primitive decomposition---understanding an object through its components, each with physical and geometric attributes. As annotated data for object parts and physics are rare, we propose a novel formulation that learns physical primitives by explaining both an object's appearance and its behaviors in physical events. Our model performs well on block towers and tools in both synthetic and real scenarios; we also demonstrate that visual and physical observations often provide complementary signals. We further present ablation and behavioral studies to better understand our model and contrast it with human performance.Comment: ECCV 2018. Project page: http://ppd.csail.mit.edu

    Visual Dynamics: Stochastic Future Generation via Layered Cross Convolutional Networks

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    We study the problem of synthesizing a number of likely future frames from a single input image. In contrast to traditional methods that have tackled this problem in a deterministic or non-parametric way, we propose to model future frames in a probabilistic manner. Our probabilistic model makes it possible for us to sample and synthesize many possible future frames from a single input image. To synthesize realistic movement of objects, we propose a novel network structure, namely a Cross Convolutional Network; this network encodes image and motion information as feature maps and convolutional kernels, respectively. In experiments, our model performs well on synthetic data, such as 2D shapes and animated game sprites, and on real-world video frames. We present analyses of the learned network representations, showing it is implicitly learning a compact encoding of object appearance and motion. We also demonstrate a few of its applications, including visual analogy-making and video extrapolation.Comment: Journal preprint of arXiv:1607.02586 (IEEE TPAMI, 2019). The first two authors contributed equally to this work. Project page: http://visualdynamics.csail.mit.ed

    Examining the impacts of convective environments on storms using observations and numerical models

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    2022 Summer.Includes bibliographical references.Convective clouds are significant contributors to both weather and climate. While the basic environments supporting convective clouds are broadly known, there is currently no unifying theory on how joint variations in different environmental properties impact convective cloud properties. The overaching goal of this research is to assess the response of convective clouds to changes in the dynamic, thermodynamic and aerosol properties of the local environment. To achieve our goal, two tools for examining convective cloud properties and their environments are first described, developed and enhanced. This is followed by an examination of the response of convective clouds to changes in the dynamic, thermodynamic and aerosol properties using these enhanced tools. In the first study comprising this dissertation, we assess the performance of small temperature, pressure, and humidity sensors onboard drones used to sample convective environments and convective cloud outflows by comparing them to measurements made from a tethersonde platform suspended at the same height. Using 82 total drone flights, including nine at night, the following determinations about sensor accuracy are made. First, when examining temperature, the nighttime flight temperature errors are found to have a smaller range than the daytime temperature errors, indicating that much of the daytime error arises from exposure to solar radiation. The pressure errors demonstrate a strong dependence on horizontal wind speed with all of the error distributions being multimodal in high wind conditions. Finally, dewpoint temperature errors are found to be larger than temperature errors. We conclude that measurements in field campaigns are more accurate when sensors are placed away from the drone's main body and associated propeller wash and are sufficiently aspirated and shielded from incoming solar radiation. The Tracking and Object-Based Analysis of Clouds (tobac) tracking package is a commonly used tracking package in atmospheric science that allows for tracking of atmospheric phenomena on any variable and on any grid. We have enhanced the tobac tracking package to enable it to be used on more atmospheric phenomena, with a wider variety of atmospheric data and across more diverse platforms than before. New scientific improvements (three spatial dimensions and an internal spectral filtering tool) and procedural improvements (enhanced computational efficiency, internal re-gridding of data, and treatments for periodic boundary conditions) comprising this new version of tobac (v1.5) are described in the second study of this dissertation. These improvements have made tobac one of the most robust, powerful, and flexible identification and tracking tools in our field and expanded its potential use in other fields. In the third study of this dissertation, we examine the relationship between the thermodynamic and dynamic environmental properties and deep convective clouds forming in the tropical atmosphere. To elucidate this relationship, we employ a high-resolution, long-duration, large-area numerical model simulation alongside tobac to build a database of convective clouds and their environments. With this database, we examine differences in the initial environment associated with individual storm strength, organization, and morphology. We find that storm strength, defined here as maximum midlevel updraft velocity, is controlled primarily by Convective Available Potential Energy (CAPE) and Precipitable Water (PW); high CAPE (>2500 J kg-1) and high PW (approximately 63 mm) are both required for midlevel CCC updraft velocities to reach at least 10 m s-1. Of the CCCs with the most vigorous updrafts, 80.9% are in the upper tercile of precipitation rates, with the strongest precipitation rates requiring even higher PW. Furthermore, vertical wind shear is the primary differentiator between organized and isolated convective storms. Within the set of organized storms, we also find that linearly-oriented CCC systems have significantly weaker vertical wind shear than nonlinear CCCs in low- (0-1 km, 0-3 km) and mid-levels (0-5 km, 2-7 km). Overall, these results provide new insights into the joint environmental conditions determining the CCC properties in the tropical atmosphere. Finally, in the fourth study of this dissertation, we build upon the third study by examining the relationship between the aerosol environment and convective precipitation using the same simulations and tracking approaches as in the third study. As the environmental aerosol concentrations are increased, the total domain-wide precipitation decreases (-3.4%). Despite the overall decrease in precipitation, the number of tracked terminal congestus clouds increases (+8%), while the number of tracked cumulonimbus clouds is decreased (-1.26%). This increase in the number of congestus clouds is accompanied by an overall weakening in their rainfall as aerosol concentration increases, with a decrease in overall rain rates and an increase in the number of clouds that do not precipitate (+10.7%). As aerosol particles increase, overall cloud droplet size gets smaller, suppressing the initial generation of rain and leading to clouds evaporating due to entrainment before they are able to precipitate

    Assessing changes in the agricultural productivity of upland systems in the light of peatland restoration

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    Human activity has had a profound negative impact on the structure and function of the earth’s ecosystems. However, with a growing awareness of the value of the services provided by intact ecosystems, restoration of degraded land is increasingly used as a means of reviving ecosystem function. Upland landscapes offer an excellent example of an environment heavily modified by human land use. Agriculture has been the key driver of ecosystem change, but as upland habitats such as peatlands can provide a number of highly valuable services, future change may focus on restoration in order to regain key ecosystem processes. However, as pastoral farming continues to dominate upland areas, ecosystem restoration has the potential to conflict with existing land use. This thesis attempts to assess differences in the agricultural productivity of the different habitat types present in upland pastures. Past and present land use have shaped the distribution of different upland habitat types, and future changes associated with ecosystem restoration are likely to lead to further change in vegetation communities. Three key contributors to agricultural productivity are examined. Firstly, variation in the nutritional quality of different upland habitats is assessed, in order to understand their value for grazing animals. Secondly, levels of livestock use in different habitats are compared in order to identify areas of particular importance for grazing. Finally, parasite populations are measured in different habitats in order provide an indication of which habitats pose the greatest potential risk of infection.It is shown that these factors appear to differ between habitats, meaning that agricultural productivity may show spatial variation in upland pastures. However, it appears that peatland restoration might have a negligible impact on farming in upland pastures due to apparent minor differences in the agricultural productivity of the habitats most likely to be affected

    William Webb Freeman Papers, 1912-1954

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    Finding aid for the William Webb Freeman Papers, 1912-1954

    Avon Alkaline Igneous Province, Missouri: Characterization of subcontinental mantle source and evolution via chemical analysis of olivine

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    This article presents the crystallization age of, and composition of olivine phenocrysts within an alnoite of, the Avon Alkaline Igneous Province (AAIP) of Ste. Genevieve County, Missouri. The AAIP is an ultramafic igneous province consisting of approx. 80 known intrusives of diverse lithology and texture. 40Ar/39 Ar geochronology indicates an emplacement age of 386 +/- 1 Ma, which establishes the AAIP as the only known Devonian-age ultramafic igneous body in the Midwestern U.S. Study of the AAIP provides a unique opportunity to characterize the Devonian-age subcontinental mantle and the processes that generated the suite of ultramafic rocks present in the province. The compositions of 52 olivine crystals are characterized using electron microprobe analysis. Olivine major element compositions are homogeneous, Mg-rich (Fo86.9-Fo89.9), and exhibit variation in trace element (e.g., Ni, Cr, Co, Ti, P) abundances consistent with fractional crystallization. These results indicate that AAIP olivines are phenocrysts rather than mantle xenocrysts. Olivine geothermometry indicates derivation at temperatures of approx. 1500-1750⁰C at pressures of 1.6 to 5.4 GPa. Olivine trace element discrimination diagrams indicate AAIP magmas were derived from mantle sources with a compositional alkalic affinity, similar to other continental alkaline rocks and kimberlite. A mantle origin via partial melting of peridotite mantle is suggested due to the high Mg content, results of geothermometric modeling, and high Ca and Ti abundance within olivine phenocrysts. Disequilibrium textures observed in alnöite olivine are consistent with resorption of magmatic olivine as a result of decompression and fractional crystallization --Abstract, page iv
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