Do Small States Get More Federal Monies? Myth and Reality about the US Senate Malapportionment

We analyze the relationship between senate malapportionment and the allocation of the US federal budget to the states during the period 1978-2002. A substantial literature originating from the in�uential paper by Atlas et al. (1995), using a within estimation methodology �nds that small and overrepresented states get signi�cantly larger shares of federal funds. Revisiting the econometric speci�cation used by the current empiri- cal research, we show that the number of senators percapita is inappropriate to capture malapportionement in regressions using broad federal programs, and that the results ob- tained with this indicator are extremely non-robust to reasonable speci�cation changes. In particular, senators percapita have a signi�cant impact on federal spending only in re- gressions containing state �xed e¤ects. Furthermore, the coefficients estimated using the within methodology are statistically di¤erent across states and, therefore, cannot be used to assess spending differentials between states. The magnitude and signi�cance of those coe¢ cients suggest a within state-speci�c inverse relationship between broad spending categories and population which is not systematically related to the size of the states and seems more compatible with incrementalist theories of budget allocation.federal budget; malapportionment; small state advantage; overrepresentation

Do Small States Get More Federal Monies?Myth and Reality About the US SenateMalapportionment

We analyze the relationship between senate malapportionment and the allocation ofthe US federal budget to the states during the period 1978-2002. A substantialliterature originating from the influential paper by ?) finds that small andoverrepresented states get significantly larger shares of federal funds. We show thatthese studies suffer from fundamental identification problems and grosslyoverestimate the impact of malapportionment. Most of the estimated impact is not ascale but a change effect. Rather than evidence of "small state advantage", we findthat states with fast growing population are penalized in the allocation of the federalbudget independently of whether they are large or small.federal budget, malapportionment, small state advantage,overrepresentation

The power of the purse: what do the data say on US federal budget allocation to the states?"

This paper provides new evidence on the relevance of alternative theories of federal budget allocation to US States. Using a panel of 48 states over 20 years, we estimate the size and relative importance of different institutional and political factors in determining such allocation. We find that although socio-economic characteristics are very important explanatory variables of spending allocation, some states receive disproportionate amounts of money for reasons essentially linked to politics and the budget allocation process. In particular we find that the overrepresentation of small states determined by the Senate and Presidential election systems has an important impact on federal budget allocation. States whose governor has the same political affiliation of the President receive more federal funds in the form of procurement and defense spending. On the other hand, the political alignment between governor and majority in the House and/or Senate does not affect the allocation of federal funds. We do not find any evidence that marginal states receive more funding; on the opposite we find that safe states tend to be rewarded. Finally, the appropriation committee membership affects the distribution of broad spending categories like total expenditure per capita and direct payments to individuals, while senior members have a disproportionate impact on grant allocationfederal budget, pork-barrel, congress, committees, president

Why do small states receive more federal money? Us senate representation and the allocation of federal budget

In this paper we provide new evidence on the importance of the so-called small state advantage for the allocation of the US federal budget. We also provide a new interpretation of the available empirical evidence. Analyzing outlays for the period 1978-2002, we show that not only does the population size of a state matter, but so too does its dynamics. Once population scale and change effects are separated, the impact of population size is substantially reduced, and population change turns out to be an important explanatory variable of current spending patterns. The impact of scale and change effects varies substantially across spending programs. Small states enjoy an advantage in defense spending, whereas fast growing ones are penalized in grants allocations. Our results imply that the interests of the states are not easily aligned around their population size alone. The distortion associated with population dynamics is concentrated on federal grants where formulas play a substantial role in limitin budgetary adjustments. Hence, a large part of the inverse relationship between spending and population appears to be driven by mechanisms of budgetary inertia which are compatible with incrementalist theories of budget allocation

Unveiling Web Fingerprinting in the Wild Via Code Mining and Machine Learning

Abstract Fueled by advertising companies' need of accurately tracking users and their online habits, web fingerprinting practice has grown in recent years, with severe implications for users' privacy. In this paper, we design, engineer and evaluate a methodology which combines the analysis of JavaScript code and machine learning for the automatic detection of web fingerprinters. We apply our methodology on a dataset of more than 400, 000 JavaScript files accessed by about 1, 000 volunteers during a one-month long experiment to observe adoption of fingerprinting in a real scenario. We compare approaches based on both static and dynamic code analysis to automatically detect fingerprinters and show they provide different angles complementing each other. This demonstrates that studies based on either static or dynamic code analysis provide partial view on actual fingerprinting usage in the web. To the best of our knowledge we are the first to perform this comparison with respect to fingerprinting. Our approach achieves 94% accuracy in small decision time. With this we spot more than 840 fingerprinting services, of which 695 are unknown to popular tracker blockers. These include new actual trackers as well as services which use fingerprinting for purposes other than tracking, such as anti-fraud and bot recognition

TVFS: Topology Voltage Frequency Scaling for Reliable Embedded ConvNets

This brief introduces Topology Voltage Frequency Scaling (TVFS), a performance management technique for embedded Convolutional Neural Networks (ConvNets) deployed on low-power CPUs. Using TVFS, pre-trained ConvNets can be efficiently processed over a continuous stream of data, enabling reliable and predictable multi-inference tasks under latency constraints. Experimental results, collected from an image classification task built with MobileNet-v1 and ported into an ARM Cortex-A15 core, reveal TVFS holds fast and continuous inference (from few runs, up to 2000), ensuring a limited accuracy loss (from 0.9% to 3.1%), and better thermal profiles (average temperature 16.4 °C below the on-chip critical threshold)

Diffusion tensor imaging mapping of brain white matter pathology in mitochondrial optic neuropathies

BACKGROUND AND PURPOSE: Brain white matter is frequently affected in mitochondrial diseases; optic atrophy gene 1-autosomal dominant optic atrophy and Leber hereditary optic neuropathy are the most frequent mitochondrial monosymptomatic optic neuropathies. In this observational study, brain white matter microstructure was characterized by DTI in patients with optic atrophy gene 1-autosomal dominant optic atrophy and Leber hereditary optic neuropathy, in relation to clinical and genetic features. MATERIALS AND METHODS: Nineteen patients with optic atrophy gene 1-autosomal dominant optic atrophy and 17 with Leber hereditary optic neuropathy older than 18 years of age, all genetically diagnosed, and 19 healthy volunteers underwent DTI by using a 1.5T MR imaging scanner and neurologic and ophthalmologic assessments. Brain white matter DTI metrics were calculated for all participants, and, in patients, their correlations with genetics and clinical findings were calculated. RESULTS: Compared with controls, patients with optic atrophy gene 1-autosomal dominant optic atrophy had an increased mean diffusivity in 29.2% of voxels analyzed within major white matter tracts distributed throughout the brain, while fractional anisotropy was reduced in 30.3% of voxels. For patients with Leber hereditary optic neuropathy, the proportion of altered voxels was only 0.5% and 5.5%, respectively, of which half was found within the optic radiation and 3.5%, in the smaller acoustic radiation. In almost all regions, fractional anisotropy diminished with age in patients with optic atrophy gene 1-autosomal dominant optic atrophy and correlated with average retinal nerve fiber layer thickness in several areas. Mean diffusivity increased in those with a missense mutation. Patients with Leber hereditary optic neuropathy taking idebenone had slightly milder changes. CONCLUSIONS: Patients with Leber hereditary optic neuropathy had preferential involvement of the optic and acoustic radiations, consistent with trans-synaptic degeneration, whereas patients with optic atrophy gene 1-autosomal dominant optic atrophy presented with widespread involvement suggestive of a multisystemic, possibly a congenital/developmental, disorder. White matter changes in Leber hereditary optic neuropathy and optic atrophy gene 1-autosomal dominant optic atrophy may be exploitable as biomarkers. ABBREVIATIONS: DOA autosomal dominant optic atrophy; FA fractional anisotropy; LHON Leber hereditary optic neuropathy; MD mean diffusivity; OPA1 optic atrophy gene 1 ;O R optic radiation; RNFL retinal nerve fiber layer; TBSS tract-based spatial statistic

Secondary post-geniculate involvement in Leber's hereditary optic neuropathy.

Leber's hereditary optic neuropathy (LHON) is characterized by retinal ganglion cell (RGC) degeneration with the preferential involvement of those forming the papillomacular bundle. The optic nerve is considered the main pathological target for LHON. Our aim was to investigate the possible involvement of the post-geniculate visual pathway in LHON patients. We used diffusion-weighted imaging for in vivo evaluation. Mean diffusivity maps from 22 LHON visually impaired, 11 unaffected LHON mutation carriers and 22 healthy subjects were generated and compared at level of optic radiation (OR). Prefrontal and cerebellar white matter were also analyzed as internal controls. Furthermore, we studied the optic nerve and the lateral geniculate nucleus (LGN) in post-mortem specimens obtained from a severe case of LHON compared to an age-matched control. Mean diffusivity values of affected patients were higher than unaffected mutation carriers (P<0.05) and healthy subjects (P<0.01) in OR and not in the other brain regions. Increased OR diffusivity was associated with both disease duration (B\u200a=\u200a0.002; P<0.05) and lack of recovery of visual acuity (B\u200a=\u200a0.060; P<0.01). Post-mortem investigation detected atrophy (41.9\% decrease of neuron soma size in the magnocellular layers and 44.7\% decrease in the parvocellular layers) and, to a lesser extent, degeneration (28.5\% decrease of neuron density in the magnocellular layers and 28.7\% decrease in the parvocellular layers) in the LHON LGN associated with extremely severe axonal loss (99\%) in the optic nerve. The post-geniculate involvement in LHON patients is a downstream post-synaptic secondary phenomenon, reflecting de-afferentation rather than a primary neurodegeneration due to mitochondrial dysfunction of LGN neurons