Vehicle automation and freeway 'pipeline' capacity in the context of legal standards of care

The study evaluates, in the context of freeway segments, the interaction between automated cars’ kinematic capabilities and the standard legal requirement for the operator of an automobile to not strike items that are in its path (known as the ‘Assured Clear Distance Ahead’ criterion). The objective is to characterize the impacts of ACDA-compliant driving behavior on the system-level indicator of roadway-network capacity. We assess the barriers to automated cars operating non-ACDA-compliant driving strategies, develop a straightforward ACDA-compliant automated-driving model to analytically estimate freeway ‘pipeline’ capacity, compare this behavior to human drivers, and interpret quantitative findings which are based on a range of rationally-specified parameter values and explicitly account for kinematic uncertainty. We demonstrate that automated cars pursuing ACDA-compliant driving strategies would have distinctive “fundamental diagrams” (relationships between speed and flow). Our results suggest that such automated-driving strategies (under a baseline set of assumptions) would sustain higher flow rates at free-flow speeds than human drivers, however at higher traffic volumes the rate of degradation in speed due to congestion would be steeper. ACDA-compliant automated cars also would have a higher level of maximum-achievable throughput, though the impact on maximum throughput at free-flow speed depends on the specific interpretation of ACDA. We also present a novel quantification of the tradeoff between freeway-capacity and various degrees of safety (one failure in 100,000 events, one failure in 1,000,000, etc.) that explicitly accounts for the irreducible uncertainty in emergency braking performance, by drawing on empirical distributions of braking distance testing. Finally, we assess the vulnerability of ACDA-compliant automated cars to lateral ‘cut-ins’ by vehicles making lane changes. The paper concludes with a brief discussion of policy questions and research needs

Oxygen abundance in the Sloan Digital Sky Survey

We present two samples of \hii galaxies from the Sloan Digital Sky Survey (SDSS) spectroscopic observations data release 3. The electron temperatures($T_e$) of 225 galaxies are calculated with the photoionized \hii model and $T_e$ of 3997 galaxies are calculated with an empirical method. The oxygen abundances from the $T_e$ methods of the two samples are determined reliably. The oxygen abundances from a strong line metallicity indicator, such as $R_{23}$, $P$, $N2$, and $O3N2$, are also calculated. We compared oxygen abundances of \hii galaxies obtained with the $T_e$ method, $R_{23}$ method, $P$ method, $N2$ method, and $O3N2$method. The oxygen abundances derived with the $T_e$ method are systematically lower by $\sim$0.2 dex than those derived with the $R_{23}$ method, consistent with previous studies based on \hii region samples. No clear offset for oxygen abundance was found between $T_e$ metallicity and $P$, $N2$ and $O3N2$ metallicity. When we studied the relation between N/O and O/H, we found that in the metallicity regime of \zoh > 7.95, the large scatter of the relation can be explained by the contribution of small mass stars to the production of nitrogen. In the high metallicity regime, \zoh > 8.2, nitrogen is primarily a secondary element produced by stars of all masses.Comment: 7 pages, 3 figures. A&A accepte

Tissue specific induction of p62/sqstm1 by farnesoid X receptor

Background: Farnesoid X Receptor (FXR) is a member of the nuclear receptor superfamily and is a ligand-activated transcription factor essential for maintaining liver and intestinal homeostasis. FXR is protective against carcinogenesis and inflammation in liver and intestine as demonstrated by the development of inflammation and tumors in the liver and intestine of FXR knock-out mice. However, mechanisms for the protective effects of FXR are not completely understood. This study reports a novel role of FXR in regulating expression of Sqstm1, which encodes for p62 protein. p62 plays an important role in maintaining cellular homeostasis through selective autophagy and activating signal transduction pathways, such as NF-κB to support cell survival and caspase-8 to initiate apoptosis. FXR regulation of Sqstm1 may serve as a protective mechanism. Methods and Results: This study showed that FXR bound to the Sqstm1 gene in both mouse livers and ileums as determined by chromatin immunoprecipitation. In addition, FXR activation enhanced transcriptional activation of Sqstm1 in vitro. However, wild-type mice treated with GW4064, a synthetic FXR ligand, showed that FXR activation induced mRNA and protein expression of Sqstm1/p62 in ileum, but not in liver. Interestingly, FXR-transgenic mice showed induced mRNA expression of Sqstm1 in both liver and ileum compared to wild-type mice. Conclusions: Our current study has identified a novel role of FXR in regulating the expression of p62, a key factor in protein degradation and cell signaling. Regulation of p62 by FXR indicates tissue-specific and gene-dosage effects. Furthermore, FXR-mediated induction of p62 may implicate a protective mechanism of FXR. © 2012 Williams et al

Predicting Drug-Target Interaction Networks Based on Functional Groups and Biological Features

Background: Study of drug-target interaction networks is an important topic for drug development. It is both timeconsuming and costly to determine compound-protein interactions or potential drug-target interactions by experiments alone. As a complement, the in silico prediction methods can provide us with very useful information in a timely manner. Methods/Principal Findings: To realize this, drug compounds are encoded with functional groups and proteins encoded by biological features including biochemical and physicochemical properties. The optimal feature selection procedures are adopted by means of the mRMR (Maximum Relevance Minimum Redundancy) method. Instead of classifying the proteins as a whole family, target proteins are divided into four groups: enzymes, ion channels, G-protein- coupled receptors and nuclear receptors. Thus, four independent predictors are established using the Nearest Neighbor algorithm as their operation engine, with each to predict the interactions between drugs and one of the four protein groups. As a result, the overall success rates by the jackknife cross-validation tests achieved with the four predictors are 85.48%, 80.78%, 78.49%, and 85.66%, respectively. Conclusion/Significance: Our results indicate that the network prediction system thus established is quite promising an

Estimation of absorption line indices of early-type galaxies using colours

Context. Absorption line indices are widely used to determine the stellar population parameters such as age and metallicity of galaxies, but it is not easy to obtain the line indices of some distant galaxies that have colours available. Aims. This paper investigates the correlations between absorption line indices and colours. Methods. A few statistical fitting methods are mainly used, via both the observational data of Sloan Digital Sky Survey and a widely used theoretical stellar population model. Results. Some correlations between widely used absorption line indices and ugriz colours are found from both observational data of early-type galaxies and a theoretical simple stellar population model. In particular, good correlations between colours and widely used absorption line indices such as Dn(4000), HgammaA, HgammaF, HdeltaA, Mg1, Mg2, and Mgb, are shown in this paper. Conclusions. Some important absorption line indices of early-type galaxies can be estimated from their colours using correlations between absorption line indices and colours. For example, age-sensitive absorption line indices can be estimated from (u-r) or (g-r) colours and metallicity-sensitive ones from (u - z) or (g - z). This is useful for studying the stellar populations of distant galaxies, especially for statistical investigations.Comment: 9 pages, 21 figures, will be shown in A&

Insights into long noncoding RNAs of naked mole rat (Heterocephalus glaber) and their potential association with cancer resistance

Additional file 4: Table S3. Differential expressed lncRNAs identified in naked mole rat (Heterocephalus glaber) genome