627 research outputs found
Protecting Trade Secrets and Confidential Information from Media Disclosure: Removing the Reporter\u27s Shield
This Note will address the problem facing businesses in Ohio when the laws protecting trade secrets and confidential information come into direct conflict with laws protecting the media. Part II of this Note will discuss the concept and various legal definitions attributed to trade secrets and confidential proprietary information. Parts III and IV will discuss trade secrets, confidential information and the related remedies available to companies, with emphasis on the statutes under Ohio\u27s criminal code. This Note will then focus on the protection afforded the media by both an Ohio shield statute which protects confidential sources, and the U.S. Constitution which protects freedom of the press. Finally, this Note will suggest that a company can pursue legal recourse for obtaining the identity of informants directly from the media, through the use of a grand jury subpoena, since newspersons are not entitled to an absolute testimonial privilege
UAW v. Johnson Controls: The Supreme Court Fails to Get the Lead Out, Overlooks Fetal Harm Resulting from Workplace Exposure
UAW v. Johnson Controls, Inc., recently decided by the United States Supreme Court, has resulted in what one commentator described as [t]he strongest and most important sex-discrimination victory in nearly 30 years. As a result of the decision, employers can no longer bar women from hazardous jobs through fetal-protection policies, except under the most extreme and narrow circumstances. This legal victory for women in the workplace, however, has seriously impacted the debate over the protection of fetal health and safety. The Supreme Court, in a seemingly encore presentation of Roe, again overlooked the harm facing the unborn child in Johnson Controls as it rejected the employer\u27s fetal-protection policy as sex discrimination within the workplace. In both Johnson Controls and Roe, the Court provided favorable results for the woman at the expense of the fetus. It may well be that the Court, in its attempt to protect the woman, is practicing its own form of discrimination against the fetus
On the criticality of inferred models
Advanced inference techniques allow one to reconstruct the pattern of
interaction from high dimensional data sets. We focus here on the statistical
properties of inferred models and argue that inference procedures are likely to
yield models which are close to a phase transition. On one side, we show that
the reparameterization invariant metrics in the space of probability
distributions of these models (the Fisher Information) is directly related to
the model's susceptibility. As a result, distinguishable models tend to
accumulate close to critical points, where the susceptibility diverges in
infinite systems. On the other, this region is the one where the estimate of
inferred parameters is most stable. In order to illustrate these points, we
discuss inference of interacting point processes with application to financial
data and show that sensible choices of observation time-scales naturally yield
models which are close to criticality.Comment: 6 pages, 2 figures, version to appear in JSTA
The Effect of Nonstationarity on Models Inferred from Neural Data
Neurons subject to a common non-stationary input may exhibit a correlated
firing behavior. Correlations in the statistics of neural spike trains also
arise as the effect of interaction between neurons. Here we show that these two
situations can be distinguished, with machine learning techniques, provided the
data are rich enough. In order to do this, we study the problem of inferring a
kinetic Ising model, stationary or nonstationary, from the available data. We
apply the inference procedure to two data sets: one from salamander retinal
ganglion cells and the other from a realistic computational cortical network
model. We show that many aspects of the concerted activity of the salamander
retinal neurons can be traced simply to the external input. A model of
non-interacting neurons subject to a non-stationary external field outperforms
a model with stationary input with couplings between neurons, even accounting
for the differences in the number of model parameters. When couplings are added
to the non-stationary model, for the retinal data, little is gained: the
inferred couplings are generally not significant. Likewise, the distribution of
the sizes of sets of neurons that spike simultaneously and the frequency of
spike patterns as function of their rank (Zipf plots) are well-explained by an
independent-neuron model with time-dependent external input, and adding
connections to such a model does not offer significant improvement. For the
cortical model data, robust couplings, well correlated with the real
connections, can be inferred using the non-stationary model. Adding connections
to this model slightly improves the agreement with the data for the probability
of synchronous spikes but hardly affects the Zipf plot.Comment: version in press in J Stat Mec
Intrinsic limitations of inverse inference in the pairwise Ising spin glass
We analyze the limits inherent to the inverse reconstruction of a pairwise
Ising spin glass based on susceptibility propagation. We establish the
conditions under which the susceptibility propagation algorithm is able to
reconstruct the characteristics of the network given first- and second-order
local observables, evaluate eventual errors due to various types of noise in
the originally observed data, and discuss the scaling of the problem with the
number of degrees of freedom
A Very High Speed True Random Number Generator with Entropy Assessment
International audienceThe proposed true random number generator (TRNG) exploits the jitter of events propagating in a self-timed ring (STR) to generate random bit sequences at a very high bit rate. It takes advantage of a special feature of STRs that allows the time elapsed between successive events to be set as short as needed, even in the order of picoseconds. If the time interval between the events is set in concordance with the clock jitter magnitude, a simple entropy extraction scheme can be applied to generate random numbers. The proposed STR-based TRNG (STRNG) follows AIS31 recommendations: by using the proposed stochastic model, designers can compute a lower entropy bound as a function of the STR characteristics (number of stages, oscillation period and jitter magnitude). Using the resulting entropy assessment, they can then set the compression rate in the arithmetic post-processing block to reach the required security level determined by the entropy per output bit. Implementation of the generator in two FPGA families confirmed its feasibility in digital technologies and also confirmed it can provide high quality random bit sequences that pass the statistical tests required by AIS31 at rates as high as 200 Mbit/s
Production of Secondary Organic Aerosol During Aging of Biomass Burning Smoke From Fresh Fuels and Its Relationship to VOC Precursors
After smoke from burning biomass is emitted into the atmosphere, chemical and physical processes change the composition and amount of organic aerosol present in the aged, diluted plume. During the fourth Fire Lab at Missoula Experiment, we performed smog-chamber experiments to investigate formation of secondary organic aerosol (SOA) and multiphase oxidation of primary organic aerosol (POA). We simulated atmospheric aging of diluted smoke from a variety of biomass fuels while measuring particle composition using high-resolution aerosol mass spectrometry. We quantified SOA formation using a tracer ion for low-volatility POA as a reference standard (akin to a naturally occurring internal standard). These smoke aging experiments revealed variable organic aerosol (OA) enhancements, even for smoke from similar fuels and aging mechanisms. This variable OA enhancement correlated well with measured differences in the amounts of emitted volatile organic compounds (VOCs) that could subsequently be oxidized to form SOA. For some aging experiments, we were able to predict the SOA production to within a factor of 2 using a fuel-specific VOC emission inventory that was scaled by burn-specific toluene measurements. For fires of coniferous fuels that were dominated by needle burning, volatile biogenic compounds were the dominant precursor class. For wiregrass fires, furans were the dominant SOA precursors. We used a POA tracer ion to calculate the amount of mass lost due to gas-phase oxidation and subsequent volatilization of semivolatile POA. Less than 5% of the POA mass was lost via multiphase oxidation-driven evaporation during up to 2 hr of equivalent atmospheric oxidation
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