28 research outputs found
HOW STATISTICAL SAMPLING CAN SOLVE THE CONUNDRUM OF COMPENSATION DISCLOSURES UNDER DODD-FRANK
Financial Crises and Legislation
Scholars frequently assert that financial legislation in the United States is primarily crisis driven. This “crisis-legislation hypothesis” is often cited as an explanation for various supposed shortcomings of US financial legislation, including that it is poorly conceived and inadequate to the problems it aims to address. Other scholars embrace the hypothesis, but from the perspective that crises are the needed impetus to prompt constructive reforms. Despite the prevalence of this hypothesis, however, its threshold assumption—that Congress passes major financial legislation only when financial crises arise—has never been analyzed empirically. This article provides that analysis. We first devise a new system for assessing legislative importance based on the notion of citation indexing, the principle at the heart of algorithms employed by modern search engines such as Google. Using a suite of legislative importance metrics, we show that the crisis-legislation hypothesis strongly fits for securities laws but far less so for banking laws. We conclude, therefore, that reformers would be ill-advised to push for government interventions in the banking system only following crises and that those seeking to understand dysfunction in US bank regulation will need to pursue fuller explanations
Genome, Functional Gene Annotation, and Nuclear Transformation of the Heterokont Oleaginous Alga \u3ci\u3eNannochloropsis oceanica\u3c/i\u3e CCMP1779
Unicellular marine algae have promise for providing sustainable and scalable biofuel feedstocks, although no single species has emerged as a preferred organism. Moreover, adequate molecular and genetic resources prerequisite for the rational engineering of marine algal feedstocks are lacking for most candidate species. Heterokonts of the genus Nannochloropsis naturally have high cellular oil content and are already in use for industrial production of high-value lipid products. First success in applying reverse genetics by targeted gene replacement makes Nannochloropsis oceanica an attractive model to investigate the cell and molecular biology and biochemistry of this fascinating organism group. Here we present the assembly of the 28.7 Mb genome of N. oceanica CCMP1779. RNA sequencing data from nitrogen-replete and nitrogendepleted growth conditions support a total of 11,973 genes, of which in addition to automatic annotation some were manually inspected to predict the biochemical repertoire for this organism. Among others, more than 100 genes putatively related to lipid metabolism, 114 predicted transcription factors, and 109 transcriptional regulators were annotated. Comparison of the N. oceanica CCMP1779 gene repertoire with the recently published N. gaditana genome identified 2,649 genes likely specific to N. oceanica CCMP1779. Many of these N. oceanica–specific genes have putative orthologs in other species or are supported by transcriptional evidence. However, because similarity-based annotations are limited, functions of most of these species-specific genes remain unknown. Aside from the genome sequence and its analysis, protocols for the transformation of N. oceanica CCMP1779 are provided. The availability of genomic and transcriptomic data for Nannochloropsis oceanica CCMP1779, along with efficient transformation protocols, provides a blueprint for future detailed gene functional analysis and genetic engineering of Nannochloropsis species by a growing academic community focused on this genus
HEMT large-signal integral transform model including trapping and impact ionization
A new large-signal FET model is proposed which simultaneously covers trapping, impact ionization, breakdown and thermal effects in an effective analytical channel current formulation. Drain current and charge functions are described using an integral transform of conductances and capacitances. An InAlAs/InGaAs mHEMT extraction example demonstrates a good simultaneous prediction of DC, small-signal and large signal performance of the device in spite of different low frequency dispersion effects which may be related to trapping and impact ionization effects in the device