Closed-form solutions for a disk, a filter, and a window for an x-ray beamline at the Advanced Photon Source

Several temperature closed-form solutions are developed and presented in this paper. The heating on a one-dimensional thin disk and a two-dimensional thin plate are analyzed. Parametric studies are also included to determine the optimized temperature for the designs

Strangeness Enhancement in p+Ap+A and S+AS+A Interactions at SPS Energies

The systematics of strangeness enhancement is calculated using the HIJING and VENUS models and compared to recent data on $\,pp\,$, $\,pA\,$ and $\,AA\,$ collisions at CERN/SPS energies ($200A\,\, GeV\,$). The HIJING model is used to perform a {\em linear} extrapolation from $pp$ to $AA$. VENUS is used to estimate the effects of final state cascading and possible non-conventional production mechanisms. This comparison shows that the large enhancement of strangeness observed in $S+Au$ collisions, interpreted previously as possible evidence for quark-gluon plasma formation, has its origins in non-equilibrium dynamics of few nucleon systems. % Strangeness enhancement %is therefore traced back to the change in the production dynamics %from $pp$ to minimum bias $pS$ and central $SS$ collisions. A factor of two enhancement of $\Lambda^{0}$ at mid-rapidity is indicated by recent $pS$ data, where on the average {\em one} projectile nucleon interacts with only {\em two} target nucleons. There appears to be another factor of two enhancement in the light ion reaction $SS$ relative to $pS$, when on the average only two projectile nucleons interact with two target ones.Comment: 29 pages, 8 figures in uuencoded postscript fil

HDAC8 and STAT3 Repress BMF Gene Activity in Colon Cancer Cells

Histone deacetylase (HDAC) inhibitors are undergoing clinical trials as anticancer agents, but some exhibit resistance mechanisms linked to anti-apoptotic Bcl-2 functions, such as BH3-only protein silencing. HDAC inhibitors that reactivate BH3-only family members might offer an improved therapeutic approach. We show here that a novel seleno-α-keto acid triggers global histone acetylation in human colon cancer cells and activates apoptosis in a p21-independent manner. Profiling of multiple survival factors identified a critical role for the BH3-only member Bcl-2-modifying factor (Bmf). On the corresponding BMF gene promoter, loss of HDAC8 was associated with signal transducer and activator of transcription 3 (STAT3)/specificity protein 3 (Sp3) transcription factor exchange and recruitment of p300. Treatment with a p300 inhibitor or transient overexpression of exogenous HDAC8 interfered with BMF induction, whereas RNAi-mediated silencing of STAT3 activated the target gene. This is the first report to identify a direct target gene of HDAC8 repression, namely, BMF. Interestingly, the repressive role of HDAC8 could be uncoupled from HDAC1 to trigger Bmf-mediated apoptosis. These findings have implications for the development of HDAC8-selective inhibitors as therapeutic agents, beyond the reported involvement of HDAC8 in childhood malignancy

Generative models of the human connectome

The human connectome represents a network map of the brain's wiring diagram and the pattern into which its connections are organized is thought to play an important role in cognitive function. The generative rules that shape the topology of the human connectome remain incompletely understood. Earlier work in model organisms has suggested that wiring rules based on geometric relationships (distance) can account for many but likely not all topological features. Here we systematically explore a family of generative models of the human connectome that yield synthetic networks designed according to different wiring rules combining geometric and a broad range of topological factors. We find that a combination of geometric constraints with a homophilic attachment mechanism can create synthetic networks that closely match many topological characteristics of individual human connectomes, including features that were not included in the optimization of the generative model itself. We use these models to investigate a lifespan dataset and show that, with age, the model parameters undergo progressive changes, suggesting a rebalancing of the generative factors underlying the connectome across the lifespan.Comment: 38 pages, 5 figures + 19 supplemental figures, 1 tabl

Interplay between residual protease activity in commercial lactases and the subsequent digestibility of β-casein in a model system

One of the conventional ways to produce lactose-hydrolyzed (LH) milk is via the addition of commercial lactases into heat-treated milk in which lactose is hydrolyzed throughout storage. This post-hydrolysis method can induce proteolysis in milk proteins due to protease impurities remaining in commercial lactase preparations. In this work, the interplay between lactose hydrolysis, proteolysis, and glycation was studied in a model system of purified β-casein (β-CN), lactose, and lactases using peptidomic methods. With a lactase presence, the proteolysis of β-CN was found to be increased during storage. The protease side-activities mainly acted on the hydrophobic C-terminus of β-CN at Ala, Pro, Ile, Phe, Leu, Lys, Gln, and Tyr positions, resulting in the formation of peptides, some of which were N-terminal glycated or potentially bitter. The proteolysis in β-CN incubated with a lactase was shown to act as a kind of “pre-digestion”, thus increasing the subsequent in vitro digestibility of β-CN and drastically changing the peptide profiles of the in vitro digests. This model study provides a better understanding of how the residual proteases in commercial lactase preparations affect the quality and nutritional aspects of β-CN itself and could be related to its behavior in LH milk

Quantum Vulnerability Analysis to Guide Robust Quantum Computing System Design

While quantum computers provide exciting opportunities for information processing, they currently suffer from noise during computation that is not fully understood. Incomplete noise models have led to discrepancies between quantum program success rate (SR) estimates and actual machine outcomes. For example, the estimated probability of success (ESP) is the state-of-the-art metric used to gauge quantum program performance. The ESP suffers poor prediction since it fails to account for the unique combination of circuit structure, quantum state, and quantum computer properties specific to each program execution. Thus, an urgent need exists for a systematic approach that can elucidate various noise impacts and accurately and robustly predict quantum computer success rates, emphasizing application and device scaling. In this article, we propose quantum vulnerability analysis (QVA) to systematically quantify the error impact on quantum applications and address the gap between current success rate (SR) estimators and real quantum computer results. The QVA determines the cumulative quantum vulnerability (CQV) of the target quantum computation, which quantifies the quantum error impact based on the entire algorithm applied to the target quantum machine. By evaluating the CQV with well-known benchmarks on three 27-qubit quantum computers, the CQV success estimation outperforms the estimated probability of success state-of-the-art prediction technique by achieving on average six times less relative prediction error, with best cases at 30 times, for benchmarks with a real SR rate above 0.1%. Direct application of QVA has been provided that helps researchers choose a promising compiling strategy at compile time

Calculating Dilepton Rates from Monte Carlo Simulations of Parton Production

To calculate dilepton rates in a Monte Carlo simulation of ultrarelativistic heavy ion collisions, one usually scales the number of similar QCD processes by a ratio of the corresponding differential probabilities. We derive the formula for such a ratio especially for dilepton bremsstrahlung processes. We also discuss the non-triviality of including higher order corrections to direct Drell-Yan process. The resultant mass spectra from our Monte Carlo simulation are consistent with the semi-analytical calculation using dilepton fragmentation functions.Comment: 14 pages in RevTex, 3 figures in uuencoded files, LBL-3466