cssi/SciSciGPT-SciSciNet huggingface dataset:
Towards a systematic computational framework for modeling multi-agent decision-making at micro level for smart vehicles in a smart world

Abstract We propose a multi-agent based computational framework for modeling decision-making and strategic interaction at micro level for smart vehicles in a smart world. The concepts of Markov game and best response dynamics are heavily leveraged. Our aim is to make the framework conceptually sound and computationally practical for a range of realistic applications, including micro path planning for autonomous vehicles. To this end, we first convert the would-be stochastic game problem into a closely related deterministic one by introducing risk premium in the utility function for each individual agent. We show how the sub-game perfect Nash equilibrium of the simplified deterministic game can be solved by an algorithm based on best response dynamics. In order to better model human driving behaviors with bounded rationality, we seek to further simplify the solution concept by replacing the Nash equilibrium condition with a heuristic and adaptive optimization with finite look-ahead anticipation. In addition, the algorithm corresponding to the new solution concept drastically improves the computational efficiency. To demonstrate how our approach can be applied to realistic traffic settings, we conduct a simulation experiment: to derive merging and yielding behaviors on a double-lane highway with an unexpected barrier. Despite assumption differences involved in the two solution concepts, the derived numerical solutions show that the endogenized driving behaviors are very similar. We also briefly comment on how the proposed framework can be further extended in a number of directions in our forthcoming work, such as behavioral calibration using real traffic video data, and computational mechanism design for traffic policy optimization.
Manager perception and proprietary investment disclosure

This paper investigates the role of manager perception in proprietary disclosure decisions. I find robust evidence that firms with overconfident CEOs (managers who are more likely to perceive proprietary costs to be lower) provide significantly more narrative R&D disclosures than firms without overconfident CEOs. In cross-sectional analysis, I find that this result is driven by observations where proprietary costs are more significant and salient. Consistent with R&D disclosures being proprietary, I find that the return on R&D is significantly lower when firms have more R&D disclosure and that this relation is not impacted by the presence of an overconfident CEO except through higher R&D disclosure. Finally, I find no association between having an overconfident CEO and nonproprietary disclosure. Collectively, these results suggest that manager perception of proprietary costs is an important determinant of firms’ voluntary proprietary disclosure.
Z′-explorer: A simple tool to probe Z′ models against LHC data

Abstract New Physics model building requires a vast number of cross-checks against available experimental results. In particular, new neutral, colorless, spin-1 bosons Z ′ , can be found in many models. We introduce in this work a new easy-to-use software Z ′ -explorer which probes Z ′ models to all available decay channels at LHC. This program scrutinizes the parameter space of the model to determine which part is still allowed, which is to be shortly explored, and which channel is the most sensitive in each region of parameter space. The user does not need to implement the model nor run any Monte Carlo simulation , but instead just needs to use the Z ′ mass and its couplings to Standard Model particles. We describe Z ′ -explorer backend and provide instructions to use it from its frontend while applying it to a variety of Z ′ models. In particular, we show Z ′ -explorer application and utility in a sequential Standard Model, a B-L Z ′ and a simplified two-sector or Warped/Composite model. The output of the program condenses the phenomenology of the model features, the experimental techniques, and the search strategies in each channel in an enriching outcome. We find that compelling add-ons to the software would be to include correlation between decay channels, low-energy physics results, and Dark Matter searches. The software is open-source ready to use, and available for modifications, improvements, and updates by the community. Program summary Program Title:: Z ′ -explorer CPC Library link to program files: https://doi.org/10.17632/k7tdp8kwgf.1 Developer's repository link: github.com/ro-sanda/Z--explorer Licensing provisions: GNU General Public License v3 Programming language: C++ and bash Nature of problem: Many New Physics models have a Z' in its spectrum. As any new model, it should be contrasted to experimental results in all its predictions. In particular, if they have a Z', there are many constraints that should be satisfied simultaneously. Also, one may wonder which of all these constraints –if satisfied– would be the optimal channel to look for the Z' in the proposed New Physics model. Solution method: The Z'-explorer software makes a fast and practical answer to both problems: i) Whether a Z' is discarded or not by experimental results, and ii) Which is the most sensitive channel to look for it. Being very easy to implement, the Z'-explorer tool allows to test a New Physics Z' against all the LHC direct observables of Z' searches, and provides the sensitivity to each one of them.
A 30 cm mercury ion thruster module

Low specific impulse hollow cathode mercury thrustor for deep space electric propulsion, using SERT 2 configuration
Convergence of Spectral Triples on Fuzzy Tori to Spectral Triples on Quantum Tori

Fuzzy tori are finite dimensional C*-algebras endowed with an appropriate notion of noncommutative geometry inherited from an ergodic action of a finite closed subgroup of the torus, which are meant as finite dimensional approximations of tori and more generally, quantum tori. A mean to specify the geometry of a noncommutative space is by constructing over it a spectral triple. We prove in this paper that we can construct spectral triples on fuzzy tori which, as the dimension grows to infinity and under other natural conditions, converge to a natural spectral triple on quantum tori, in the sense of the spectral propinquity. This provides a formal assertion that indeed, fuzzy tori approximate quantum tori, not only as quantum metric spaces, but as noncommutative differentiable manifolds—including convergence of the state spaces as metric spaces and of the quantum dynamics generated by the Dirac operators of the spectral triples, in an appropriate sense.
Codes, Cubes, and Graphical Designs

Graphical designs are an extension of spherical designs to functions on graphs. We connect linear codes to graphical designs on cube graphs, and show that the Hamming code in particular is a highly effective graphical design. We show that even in highly structured graphs, graphical designs are distinct from the related concepts of extremal designs, maximum stable sets in distance graphs, and t-designs on association schemes.
Polarimetric signatures of the photon ring of a black hole that is pierced by a cosmic axion string

A black hole image contains a bright ring of photons that have closely circled the black hole on their way from the source to the detector. Here, we study the photon ring of a rotating black hole which is pierced by a global hyper-light axion-type cosmic string. We show that the coupling 𝜙F $$ \overset{\sim }{F} $$ between the axion 𝜙 and the photon can give rise to a unique polarimetric structure of the photon ring. The structure emerges due to an Aharonov-Bohm type effect that leads to a change of the polarization directions of linear polarized photons when they circle the black hole. For several parameter choices, we determine concrete polarization patterns in the ring. Measuring these patterns can provide us with a way of determining the value of the coefficient of the mixed anomaly between electromagnetism and the symmetry that gave rise to the cosmic string. Finally, we briefly review a possible formation mechanism of black holes that are pierced by cosmic strings and discuss under which conditions we can expect such objects to be present as supermassive black holes in the center of galaxies.
Dark matter, cosmic positrons in alpha magnetic spectrometer experiment and particle-cosmology with Yang–Mills gravity

Abstract We discuss a model of dark matter consisting of high energy anti-electron-neutrinos with leptonic force, which is produced by the conserved leptonic charge g l associated with Lee–Yang’s U 1 gauge symmetry. Based on particle-cosmology for early universe, the high energy neutrino (HEN) model of dark matter assumes that the neutron decay processes, n → p + + e − + ν ¯ e , dominate the epoch after the creation, collision and confinement processes of quarks and antiquarks in the beginning. The HEN model implies the following results: There are almost equal numbers of electrons, protons and anti-electron-neutrinos dominated the matter cosmos. There are unobservable and ubiquitous anti-electron-neutrinos ν ¯ e with leptonic charge g l in the universe. Although the total mass of anti-electron-neutrino dark matter is negligible in the universe, its enhanced gravitational and leptonic forces could lead to the observed flat rotation curves due to relativistic ν ¯ e , whose static force involves a factor E ν / m ν ≈ 1 0 6 . We estimate the leptonic charge to be g l ≈ 7 × 1 0 − 21 . The model predicts that the anti-electron-neutrino dark matter can interact with cosmic-ray protons to produce positrons, i.e. ν ¯ e + p + → e + + n , through weak interaction of the unified electroweak theory. The anti-electron-neutrino dark matter sheds light on the Alpha Magnetic Spectrometer (AMS) experiment, which has detected the intriguing excess of cosmic-ray positrons over what is expected. The HEN model of dark matter suggests an experimental test of the new Lee–Yang force between electrons by using modern precision Cavendish experiment.
Selection for or against escape from nonsense mediated decay is a novel signature for the detection of cancer genes.

Abstract Escape from nonsense mediated mRNA decay (NMD-) can produce activated or inactivated gene products, and bias in rates of escape can identify functionally important genes in germline disease. We hypothesized that the same would be true of cancer genes, and tested for NMD- bias within The Cancer Genome Atlas pan-cancer somatic mutation dataset. We identify 29 genes that show significantly elevated or suppressed rates of NMD-. This novel approach to cancer gene discovery reveals genes not previously cataloged as potentially tumorigenic, and identifies many potential driver mutations in known cancer genes for functional characterization.
New Circular Security Counterexamples from Decision Linear and Learning with Errors.

We investigate new constructions of n-circular counterexamples with a focus on the case of n = 2. We have a particular interest in what qualities a cryptosystem must have to be able to separate such circular security from IND-CPA or IND-CCA security. To start, we ask whether there is something special about the asymmetry in bilinear groups that is inherent in the works of [1] and [17] or whether it is actually the bilinearity that matters. As a further question, we explore whether such counterexamples are derivable from other assumptions such as the Learning with Errors (LWE) problem. If it were difficult to find such counterexamples, this might bolster our confidence in using 2-circular encryption as a method of bootstrapping Fully Homomorphic Encryption systems that are based on lattice assumptions. The results of this paper broadly expand the class of assumptions under which we can build 2circular counterexamples. We first show for any constant k ≥ 2 how to build counterexamples from a bilinear group under the decision k-linear assumption. Recall that the decision k-linear assumption becomes progressively weaker as k becomes larger. This means that we can instantiate counterexamples from symmetric bilinear groups and shows that asymmetric groups do not have any inherently special property needed for this problem. We then show how to create 2-circular counterexamples from the Learning with Errors problem. This extends the reach of these systems beyond bilinear groups and obfuscation.
FlashFlow: A Secure Speed Test for Tor

The Tor network uses a measurement system called TorFlow to estimate its relays' forwarding capacity and to balance traffic among them. This system has been shown to be vulnerable to adversarial manipulation, and inaccuracies even in benign circumstances have long been observed. To solve the issues with security and accuracy, we present FlashFlow, a system to measure the capacity of Tor relays. Our analysis shows that FlashFlow limits a malicious relay to obtaining a capacity estimate at most 1.33 times its true capacity. Through realistic Internet experiments, we find that FlashFlow measures relay capacity with $\geq {89\%}$ accuracy 95 % of the time. Through simulation, we find that FlashFlow can measure the entire Tor network in less than 5 hours using 3 measurers with 1 Gbit/s of bandwidth each. Performance simulations using FlashFlow for load balancing shows that, compared to TorFlow, network weight error decreases by 86 %, while the median of 50 KiB, 1 MiB, and 5 MiB transfer times decreases by 15 %, 29 %, and 37 %, respectively. Moreover, FlashFlow yields more consistent client performance: the median rate of transfer timeouts decreases by 100 %, while the standard deviation of 50 KiB, 1 MiB, and 5 MiB transfer times decreases by 55%, 61 %, and 41 %, respectively. We also find that the performance improvements increase relative to TorFlow as the total client-traffic load increases, demonstrating that FlashFlow is better suited to supporting network growth.
Frobenius C∗-algebras and local adjunctions of C∗-correspondences

Generalizing the well-known correspondence between two-sided adjunctions and Frobenius algebras, we establish a one-to-one correspondence between local adjunctions of C∗-correspondences, as defined...
Towards Novel Target Discovery Through Open-Set Domain Adaptation

Open-set domain adaptation (OSDA) considers that the target domain contains samples from novel categories unobserved in external source domain. Unfortunately, existing OSDA methods always ignore the demand for the information of unseen categories and simply recognize them as "unknown" set without further explanation. This motivates us to understand the unknown categories more specifically by exploring the underlying structures and recovering their interpretable semantic attributes. In this paper, we propose a novel framework to accurately identify the seen categories in target domain, and effectively recover the semantic attributes for unseen categories. Specifically, structure preserving partial alignment is developed to recognize the seen categories through domain-invariant feature learning. Attribute propagation over visual graph is designed to smoothly transit attributes from seen to unseen categories via visual-semantic mapping. Moreover, two new cross-main benchmarks are constructed to evaluate the proposed framework in the novel and practical challenge. Experimental results on open-set recognition and semantic recovery demonstrate the superiority of the proposed method over other compared baselines.
Thin position through the lens of trisections of 4-manifolds

Motivated by M. Scharlemann and A. Thompson's definition of thin position of 3-manifolds, we define the width of a handle decomposition a 4-manifold and introduce the notion of thin position of a compact smooth 4-manifold. We determine all manifolds having width equal to $\{1,\dots, 1\}$, and give a relation between the width of $M$ and its double $M\cup_{id_\partial} \overline M$. In particular, we describe how to obtain genus $2g+2$ and $g+2$ trisection diagrams for sphere bundles over orientable and non-orientable surfaces of genus $g$, respectively. By last, we study the problem of describing relative handlebodies as cyclic covers of 4-space branched along knotted surfaces from the width perspective.
Mortar-based Entropy-Stable Discontinuous Galerkin Methods on Non-conforming Quadrilateral and Hexahedral Meshes

High-order entropy-stable discontinuous Galerkin (DG) methods for nonlinear conservation laws reproduce a discrete entropy inequality by combining entropy conservative finite volume fluxes with summation-by-parts (SBP) discretization matrices. In the DG context, on tensor product (quadrilateral and hexahedral) elements, SBP matrices are typically constructed by collocating at Lobatto quadrature points. Recent work has extended the construction of entropy-stable DG schemes to collocation at more accurate Gauss quadrature points (Chan et al. in SIAM J Sci Comput 41(5):A2938–A2966, 2019) . In this work, we extend entropy-stable Gauss collocation schemes to non-conforming meshes. Entropy-stable DG schemes require computing entropy conservative numerical fluxes between volume and surface quadrature nodes. On conforming tensor product meshes where volume and surface nodes are aligned, flux evaluations are required only between “lines” of nodes. However, on non-conforming meshes, volume and surface nodes are no longer aligned, resulting in a larger number of flux evaluations. We reduce this expense by introducing an entropy-stable mortar-based treatment of non-conforming interfaces via a face-local correction term, and provide necessary conditions for high-order accuracy. Numerical experiments for the compressible Euler equations in two and three dimensions confirm the stability and accuracy of this approach.
Soft hydraulics: from Newtonian to complex fluid flows through compliant conduits.

Abstract Microfluidic devices manufactured from soft polymeric materials have emerged as a paradigm for cheap, disposable and easy-to-prototype fluidic platforms for integrating chemical and biological assays and analyses. The interplay between the flow forces and the inherently compliant conduits of such microfluidic devices requires careful consideration. While mechanical compliance was initially a side-effect of the manufacturing process and materials used, compliance has now become a paradigm, enabling new approaches to microrheological measurements, new modalities of micromixing, and improved sieving of micro- and nano-particles, to name a few applications. This topical review provides an introduction to the physics of these systems. Specifically, the goal of this review is to summarize the recent progress towards a mechanistic understanding of the interaction between non-Newtonian (complex) fluid flows and their deformable confining boundaries. In this context, key experimental results and relevant applications are also explored, hand-in-hand with the fundamental principles for their physics-based modeling. The key topics covered include shear-dependent viscosity of non-Newtonian fluids, hydrodynamic pressure gradients during flow, the elastic response (deformation and bulging) of soft conduits due to flow within, the effect of cross-sectional conduit geometry on the resulting fluid–structure interaction, and key dimensionless groups describing the coupled physics. Open problems and future directions in this nascent field of soft hydraulics, at the intersection of non-Newtonian fluid mechanics, soft matter physics, and microfluidics, are noted.
Influence-guided Data Augmentation for Neural Tensor Completion

How can we predict missing values in multi-dimensional data (or tensors) more accurately? The task of tensor completion is crucial in many applications such as personalized recommendation, image and video restoration, and link prediction in social networks. Many tensor factorization and neural network-based tensor completion algorithms have been developed to predict missing entries in partially observed tensors. However, they can produce inaccurate estimations as real-world tensors are very sparse, and these methods tend to overfit on the small amount of data. Here, we overcome these shortcomings by presenting a data augmentation technique for tensors. In this paper, we propose DAIN, a general data augmentation framework that enhances the prediction accuracy of neural tensor completion methods. Specifically, DAIN first trains a neural model and finds tensor cell importances with influence functions. After that, DAIN aggregates the cell importance to calculate the importance of each entity (i.e., an index of a dimension). Finally, DAIN augments the tensor by weighted sampling of entity importances and a value predictor. Extensive experimental results show that DAIN outperforms all data augmentation baselines in terms of enhancing imputation accuracy of neural tensor completion on four diverse real-world tensors. Ablation studies of DAIN substantiate the effectiveness of each component of DAIN. Furthermore, we show that DAIN scales near linearly to large datasets.
Chiral Effective Field Theory’s Impact on Advancing Quantum Monte Carlo Methods

Thirty years ago, Steven Weinberg published his seminal paper on “Nuclear Forces from chiral Lagrangians” [1] which has revolutionized the field of theoretical nuclear physics. Nowadays, interactions derived from chiral effective field theory are routinely used to describe nuclear systems ranging from atomic nuclei to the dense matter explored in the core of neutron stars with theoretical uncertainty estimates. In our contribution to the special issue “Celebrating 30 years of Steven Weinberg’s paper Nuclear Forces from Chiral Lagrangians”, we focus on the impact that chiral effective field theory interactions have played in advancing microscopic studies of atomic nuclei and the nuclear-matter equation of state using quantum Monte Carlo methods.
Conjugate Phase Retrieval in Paley–Wiener Space

We consider the problem of conjugate phase retrieval in Paley–Wiener space $$PW_{\pi }$$ . The goal of conjugate phase retrieval is to recover a signal f from the magnitudes of linear measurements up to unknown phase factor and unknown conjugate, meaning f(t) and $$\overline{f(t)}$$ are not necessarily distinguishable from the available data. We show that conjugate phase retrieval can be accomplished in $$PW_{\pi }$$ by sampling only on the real line by using structured convolutions. We also show that conjugate phase retrieval can be accomplished in $$PW_{\pi }$$ by sampling both f and $$f^{\prime }$$ only on the real line. Moreover, we demonstrate experimentally that the Gerchberg–Saxton method of alternating projections can accomplish the reconstruction from vectors that do conjugate phase retrieval in finite dimensional spaces. Finally, we show that generically, conjugate phase retrieval can be accomplished by sampling at three times the Nyquist rate, whereas phase retrieval requires sampling at four times the Nyquist rate.
Improving Coherence and Consistency in Neural Sequence Models with Dual-System, Neuro-Symbolic Reasoning

Human reasoning can often be understood as an interplay between two systems: the intuitive and associative ("System 1") and the deliberative and logical ("System 2"). Neural sequence models -- which have been increasingly successful at performing complex, structured tasks -- exhibit the advantages and failure modes of System 1: they are fast and learn patterns from data, but are often inconsistent and incoherent. In this work, we seek a lightweight, training-free means of improving existing System 1-like sequence models by adding System 2-inspired logical reasoning. We explore several variations on this theme in which candidate generations from a neural sequence model are examined for logical consistency by a symbolic reasoning module, which can either accept or reject the generations. Our approach uses neural inference to mediate between the neural System 1 and the logical System 2. Results in robust story generation and grounded instruction-following show that this approach can increase the coherence and accuracy of neurally-based generations.
Access to COVID-19 Vaccines in High-, Middle-, and Low-Income Countries Hosting Clinical Trials.

The COVID-19 pandemic has led to the rapid development of multiple vaccines, vaccines that were tested in clinical trials located in several countries around the world. Because prior research has shown that pharmaceuticals do not receive consistent and timely authorization for use in lower-income countries where they are tested, we conducted a cross-sectional study examining the authorization or approval and delivery for COVID-19 vaccines recommended by the World Health Organization (WHO) in the countries where they were tested. While countries of varying incomes have largely authorized the COVID-19 vaccines tested within their populations for use, high-income countries have received proportionately more doses, enabling them to more fully vaccinate their populations. As many lower-income countries continue to experience inequitable shortfalls in COVID-19 vaccine supply amid the ongoing pandemic, efforts must be undertaken to ensure timely access in countries across all income groups, including those hosting clinical trials.
Environment-Assisted Shortcuts to Adiabaticity

Envariance is a symmetry exhibited by correlated quantum systems. Inspired by this “quantum fact of life,” we propose a novel method for shortcuts to adiabaticity, which enables the system to evolve through the adiabatic manifold at all times, solely by controlling the environment. As the main results, we construct the unique form of the driving on the environment that enables such dynamics, for a family of composite states of arbitrary dimension. We compare the cost of this environment-assisted technique with that of counterdiabatic driving, and we illustrate our results for a two-qubit model.
Nearly Minimax Optimal Reinforcement Learning for Discounted MDPs

We study the reinforcement learning problem for discounted Markov Decision Processes (MDPs) under the tabular setting. We propose a model-based algorithm named UCBVI-$\gamma$, which is based on the \emph{optimism in the face of uncertainty principle} and the Bernstein-type bonus. We show that UCBVI-$\gamma$ achieves an $\tilde{O}\big({\sqrt{SAT}}/{(1-\gamma)^{1.5}}\big)$ regret, where $S$ is the number of states, $A$ is the number of actions, $\gamma$ is the discount factor and $T$ is the number of steps. In addition, we construct a class of hard MDPs and show that for any algorithm, the expected regret is at least $\tilde{\Omega}\big({\sqrt{SAT}}/{(1-\gamma)^{1.5}}\big)$. Our upper bound matches the minimax lower bound up to logarithmic factors, which suggests that UCBVI-$\gamma$ is nearly minimax optimal for discounted MDPs.
Attention: How high-frequency trading improves price efficiency following earnings announcements

Abstract Recent research indicates that high-frequency trading (HFT) helps incorporate fundamental information into prices, but how this happens is unclear. We examine reduced attention constraints as an important channel through which HFT enhances price efficiency. Using multiple proxies of attention constraints, we find that price inefficiencies are reduced by 65%–100% when high-frequency traders (HFTs) trade following low attention earnings announcements: initial price responses are larger and post-earnings-announcement drift is reduced. Results are not driven by firm size or announcement time-of-day. Our findings highlight how limited attention, a human bias affecting asset prices, is mitigated when machines trade.
IMMUNOCHEMISTRY OF THE PNEUMOCOCCAL TYPES II, V, AND VI III. Tests with Derivatives of the Specific Polysaccharides of Types II and VI

Abstract Rebers, P. A. (Rutgers, The State University, New Brunswick, N. J.), E. Hurwitz, M. Heidelberger, and S. Estrada-Parra. Immunochemistry of the pneumococcal types II, V, and VI. III. Tests with derivatives of the specific polysaccharides of types II and VI. J. Bacteriol. 83:335–342. 1962.—The type-specific pneumococcal polysaccharides, S II and S VI, were oxidized with periodate, and the capacity of the derivatives for precipitation by antibodies and adsorption by erythrocytes was studied. The derivatives were further modified by reduction, oxidation, and condensation with urea. Oxidation of S VI with periodate reduced its precipitation of homologous antibodies much less than did similar treatment of S II. About one-half of the components are attacked in both cases, but in S II, glucuronic acid end groups, the chief determinants of specificity, are destroyed by periodate, whereas in S VI, the structures responsible for specificity are either less affected or yield derivatives with almost as much affinity for antibody as the original polysaccharide. S II and S VI are not adsorbed by washed rabbit or human erythrocytes, but their periodate-oxidized derivatives are readily taken up, presumably owing to their newly formed reactive aldehyde groups, giving high titers in passive hemagglutination. The method should be applicable to other polysaccharides which do not adsorb readily on red cells.
The Associations between Loss and Posttraumatic Stress and Depressive Symptoms Following Hurricane Ike

Disasters can have wide-ranging effects on individuals and their communities. Loss of specific resources (e.g., household contents, job) following a disaster has not been well studied, despite the implications for preparedness efforts and postdisaster interventions. OBJECTIVE: To provide information about the effects of loss on postdisaster distress, the present study assessed associations between disaster-related variables, including the loss of specific resources, and postdisaster distress. METHOD: Random-digit dialing methodology was used to recruit hurricane-affected adults from Galveston and Chambers, TX, counties one year after Hurricane Ike. Data from 1,249 survivors were analyzed to identify predictors of distress. RESULTS: Variables that were significantly associated with posttraumatic stress disorder symptoms included sustained losses, hurricane exposure, and sociodemographic characteristics; similar results were obtained for depressive symptoms. CONCLUSIONS: Together, these findings suggest risk factors that may be associated with the development of posthurricane distress that can inform preparedness efforts and posthurricane interventions. Language: en
Modulation of stability of the Escherichia coli heat shock regulatory factor sigma.

The heat shock response of Escherichia coli is under the positive control of the sigma 32 protein (the product of the rpoH gene). We found that overproduction of the sigma 32 protein led to concomitant overproduction of the heat shock proteins, suggesting that the intracellular sigma 32 levels limit heat shock gene expression. In support of this idea, the intracellular half-life of the sigma 32 protein synthesized from a multicopy plasmid was found to be extremely short, e.g., less than 1 min at 37 and 42 degrees C. The half-life increased progressively with a decrease in temperature, reaching 15 min at 22 degrees C. Finally, conditions known previously to increase the rate of synthesis of the heat shock proteins, i.e., a mutation in the dnaK gene or expression of phage lambda early proteins, were shown to simultaneously result in a three- to fivefold increase in the half-life of sigma 32. Images
A low-power two-stage harmonic rejection quadrature mixer employing bias-current reuse

A bias-sharing two-stage harmonic rejection mixer that provides quadrature baseband outputs is demonstrated. The devices that bias the RF transconductors in a one-stage harmonic-rejection downconverter are configured to provide a second-stage of harmonic rejection for reducing the impact of gain coefficient errors, without requiring additional bias current. Clock retiming is used to desensitize the design to clock phase errors. The design is implemented in a 130nm CMOS process, and demonstrates a gain of 35.8 dB, an in-band output 1dB compression of −6 dBVp, a DSB NF of 11.5 dB, and an analog power dissipation of 14 mW from a 1.2 V supply. Harmonic rejection in excess of 60 dB is measured without calibration. Operation using a clock frequency in the range from 800 MHz to 2 GHz is verified. Mechanisms relating to bias-sharing that can potentially degrade performance including flicker noise and even-order harmonic response are identified. Circuit techniques for mitigating these issues that exploit orthogonal phasing of RF and baseband signals are described.
Rethinking classic examples of recent speciation in plants

Summary This paper reviews the evidence that three pairs of diploid annual plant species are related as progenitor and recent derivative. The species pairs are Layia glandulosa and Layia discoidea, Clarkia biloba and Clarkia lingulata, and Stephanomeria exigua ssp. coronaria and Stephanomeria malheurensis. The three cases are examples of Verne Grant's model of ‘Quantum Speciation’, in which a derived species is budded off and acquires new traits while the parental species continues more or less as before. The derived species differ from their progenitors in different ways and show different modes of reproductive isolation. However, the number of differences between each derivative and its progenitor appears to be few and relatively simple in genetic terms. Comparison of a recently evolved species with its progenitor can reveal what happens during speciation because overall divergence is minimal and the direction of evolution is clear. Evidence from DNA sequences may be particularly useful to recognize additional examples of progenitor and derivative relationship.
Risk Management, Capital Structure and Capital Budgeting in Financial Institutions

We test how active management of bank credit risk exposure affects capital structure, capital budgeting and profits. We find that banks that rebalance their CI they also lend more to businesses, both as a percentage of total assets and as a percentage of their overall lending, and they enjoy higher profits. The results hold controlling for bank size and holding company affiliation and are robust over time. We conclude that increasingly sophisticated risk management practices in banking are likely to improve the availability of bank credit.
Loop shaping in mixed H 2 and H ∞ optimal control

Mixed H2 and H∞ optimal control law design by shaping of the loop transfer function to meet engineering goals is considered. The development is closely analogous to the linear quadratic Gaussian with loop transfer recovery (LQG/LTR) procedure for H2 optimal control law design, with an additional constraint on the H∞ norm of a certain disturbance transfer function matrix. To facilitate the numerical computation Of the controller, the main results of mixed H2 and H∞ optimization are modified by assuming that the design weights are interdependent and that the disturbance inputs are uncorrelated. The condition that forms the basis for loop transfer recovery, under which the dynamic compensator recovers the properties of the state feedback, static gain controller, is derived. A mixed H2 and H∞ version of the Kalman equality is derived to show the relationship between the achievable loop shape and the design parameters. A design procedure that implements the equations is given, and a numerical example is shown to illustrate the design procedure.
Spectroscopic investigations of band offsets of MgO|AlxGa1-xN epitaxial heterostructures with varying AlN content

Epitaxial (111) MgO films were prepared on (0001) AlxGa1−xN via molecular-beam epitaxy for x = 0 to x = 0.67. Valence band offsets of MgO to AlxGa1−xN were measured using X-ray photoelectron spectroscopy as 1.65 ± 0.07 eV, 1.36 ± 0.05 eV, and 1.05 ± 0.09 eV for x = 0, 0.28, and 0.67, respectively. This yielded conduction band offsets of 2.75 eV, 2.39 eV, and 1.63 eV for x = 0, 0.28, and 0.67, respectively. All band offsets measured between MgO and AlxGa1−xN provide a > 1 eV barrier height to the semiconductor.
The Department of Molecular Medicine at The University of Texas Institute of Biotechnology

The extracellular regions of many cell surface proteins of the immune system contain distinct domains that may be linked in many different ways and are often only loosely tethered to the transmembrane segment. In efforts to identify regions critical for binding, molecular models of these domains are used to select residues for mutagenesis and to map binding sites. Many immune cell surface proteins belong to protein superfamilies and display only limited sequence identity compared to proteins of known three-dimensional (3D) structure, often 30% or less. Therefore, detailed 3D structures are difficult to predict, and structure-based sequence analysis and model assessment are particularly important components of the model building process. In some cases, experimentally determined structures have made it possible to assess the accuracy of predictions, which illustrates the opportunities and shortcomings of the approach. Herein the model-based identification of binding sites in cell surface proteins is described and representative examples are discussed.
Contrasting subcellular localization of the Kv1.2 K+ channel subunit in different neurons of rat brain

In the nervous system, a wide diversity of K+ channels are formed by the oligomeric assembly of subunits encoded by a large number of K+ channel genes. The physiological functions of a specific K+ channel subunit in vivo will be dictated in part by its subcellular location within neurons. We have used a combined in situ hybridization and immunocytochemical approach to determine the subcellular distribution of Kv1.2, a member of the Shaker subfamily of K+ channel genes. In contrast to other characterized K+ channel subunits, Kv1.2 protein shows a complex differential subcellular distribution in neurons of rat brain. In some of these neurons (e.g., hippocampal and cortical pyramidal cells, and Purkinje cells), Kv1.2 is concentrated in dendrites, while in others (e.g., cerebellar basket cells), Kv 1.2 is predominantly, if not exclusively, localized to nerve terminals. Furthermore, Kv1.2 immunoreactivity was also detected in certain axon tracts. We hypothesize that the differential sorting of Kv1.2 could result from association of Kv1.2 with varying heterologous K+ channel subunits in different cell types, with the implication that Kv1.2 may participate in distinct heteromultimeric K+ channels in different subcellular domains. The findings suggest that Kv1.2-containing K+ channels may play diverse functional roles in several neuronal compartments, regulating presynaptic or postsynaptic membrane excitability, depending on the neuronal cell type.
Physical Properties of Water

This chapter discusses the physical properties of water, but by necessity, it contains an explanation of both atmospheric and hydrostatic pressure. The water molecule is dipolar—there are negatively and positively charged sites on opposite sides of the molecule. As a result, water molecules form hydrogen bonds with other water molecules. Hydrogen bonds are stronger than van der Waals attractions that occur among molecules, and impart unique physical properties to water. The dipolar molecule and hydrogen bonding greatly influence the density, vapor pressure, freezing point, boiling point, surface tension, phase changes, specific heat, dielectric constant, viscosity, cohesion, adhesion, and capillarity of water. Water has its maximum density at about 4 °C; this results in ice floating and the potential for thermal stratification of natural water bodies. The physical properties of water are of intrinsic interest, but some of these properties influence water quality as will be seen in other chapters.
Computed tomographic imaging of the normal immature California sea lion head (Zalophus californianus).

Different computed tomography (CT) protocols were tested to optimize imaging of the head of the California sea lion. Transverse mode images were superior to helical mode images. Bone structures were best imaged using 1 mm slice width combined with a high-frequency image reconstruction algorithm and best viewed using a wide window setting. Soft tissue structures were generally difficult to differentiate with the exception of the orbital region, which was best imaged using 2 mm slice width combined with a medium-frequency image reconstruction algorithm and best viewed using a narrow window setting. Anatomic features specific to the California sea lion were identified on CT images and were consistent with previously published data. These included absence of the lacrimal bone, nasolacrimal ducts, and paranasal sinuses. Upon qualitative assessment of the orbit and nasal cavity, there was a triangular-shaped interorbital nasal cavity on transverse images, and extensive, highly convoluted ethmoid turbinates. The permanent dental formula was identical to previous reports. In conclusion, we provide a detailed description of the anatomy of the immature California sea lion head and a definition of two imaging protocols.
Tumid lupus erythematosus: criteria for classification with immunohistochemical analysis.

Objective To define comprehensive criteria for the classification and differential diagnosis of tumid lupus erythematosus (LE). Methods A prospective study of patients fulfilling the classical description of tumid LE was performed. Clinical evaluation, histopathologic and direct immunofluorescence analyses of skin specimens, and serologic evaluation were conducted. The inflammatory cell infiltrate was quantitatively investigated by immunohistochemical analysis of fresh frozen skin specimens using multiple lymphocytic markers. Results Fifteen patients were followed for a mean of 7 years. Smooth, indurated, nonscarring, pink to violaceous papules, plaques, or nodules, devoid of surface changes were distributed on sun exposed sites. The mean lesion duration was 2 years, female:male ratio was 8:7, and racial distribution was 11 white, 2 Hispanic, and 2 African American patients. Histopathologic findings included a superficial and deep, perivascular, and frequently periadnexal infiltrate of lymphocytes, mucin deposition throughout the dermis, and absent to focal dermal-epidermal junctional involvement. Direct immunofluorescence immunoreactants and low titer antinuclear antibodies were variably present. Immunohistochemical findings included a predominance of pan-T cell marker CD3-expressing (78.0% ± 6.3%) T lymphocytes. Most were CD4 expressing (82.7% ± 8.0%) helper T cells; a minority were CD8 expressing (31.3% ± 14.0%) cytotoxic T cells. The CD4:CD8 ratio was 3.1 (±1.3):1. One patient developed systemic LE and one a discoid LE lesion. Conclusion Comprehensive clinical, histopathologic, and immunohistochemical criteria for the classification of tumid LE are proposed that differentiate tumid LE from other cutaneous disorders that may be clinically and histologically indistinguishable. The chronic, benign course indicates that tumid LE be classified as a form of chronic cutaneous LE, although it may be a cutaneous feature of systemic LE.
A scalable algorithm for molecular property estimation in high dimensional scaffold-based libraries

An algorithm is presented for the estimation of molecular properties over a library built around a scaffold, which has N sites for functionalization with Mi moieties at the ith scaffold site, corresponding to a library of \({\prod_{i=1}^N M_i}\) molecules. The algorithm relies on a series of operations involving (i) synthesis and property measurement of a minimal number of T randomly sampled members of the library, (ii) expression of the observed property in terms of a high-dimensional model representation (HDMR) of the moiety → property map, (iii) optimization of the ordered sequence of moieties on each site to regularize the HDMR map and (iv) interpolation using the map to estimate the properties of as yet unsynthesized compounds. The set of operations is performed iteratively aiming to reach convergence of the predictive HDMR map with as few synthesized samples as possible. Through simulation, the number T of required random molecular samples is shown to scale very favorably with \({T < < \prod^N_{i=1} M_i}\) for cases up to N = 20 and Mi = 20. For example, high estimation quality was attained for simulated libraries with T ~ 5,000 sampled compounds for a library of 2012 members and T ~ 12,500 sampled compounds for a library of 2020 members. The algorithm is based on the assumption that a systematic pattern exists in the moiety → property map provided that the moieties are optimally ordered on the scaffold sites within the context of HDMR. The overall procedure is referred to as the substituent reordering HDMR algorithm (SR-HDMR). The technique was also successfully tested with laboratory data for estimating C13-NMR shifts in a tri-substituted benzene library and for lac operon repression binding.
Dehydroascorbate reductase affects non-photochemical quenching and photosynthetic performance.

Ascorbic acid (Asc) is a major antioxidant involved in photoprotection and photosynthetic function in plants. Dehydroascorbate reductase (DHAR) catalyzes the regeneration of Asc from its oxidized state and serves as an important regulator of Asc recycling. In this work, we used a molecular biochemical approach to investigate how the efficiency of Asc recycling affects non-photochemical quenching (NPQ). Suppression of DHAR expression resulted in a lower induction of NPQ that correlated with reductions in chlorophyll and xanthophyll pigments, quantum yield of photosystem II, and CO2 assimilation, whereas the level of reactive oxygen species increased. The quickly reversible component of NPQ decreased and the slowly reversible or irreversible component of NPQ increased following a reduction in DHAR expression. Significant photoinhibition was also observed following exposure to high light. Direct feeding with Asc restored the appropriate induction of NPQ in DHAR-suppressed leaves. In contrast, increasing DHAR expression increased the pool size of xanthophyll and chlorophyll pigments as well as the rate of CO2 assimilation, particularly at high light intensities, whereas the level of reactive oxygen species was reduced. Leaves with increased DHAR expression experienced less photoinhibition than did wild-type plants following exposure to high light. DHAR activity, therefore, can affect the appropriate induction of NPQ and level of photoprotection during exposure to high light.
A Comparison of the Tune Books of Tufts and Walter

Two 1721 Boston tune books, one by Thomas Walter, the other by John Tufts, contain explanatory introductions. Either could be considered the first music education textbook printed in America. The purpose of this study was to compare the musical arrangements of the fifth edition (1726) of Tufts's An Introduction to the Singing of Psalm Tunes (the earliest extant Tufts edition with three-part arrangements) with the tune settings of Walter's The Grounds and Rules of Musicke Explained (1721) and the ninth edition (1698) of The Psalms, Hymns, and Spiritual Songs of the Old and New Testament, commonly known as the “Bay Psalm Book.” These comparisons demonstrated that Tufts's fifth edition and Walter's first edition are musically identical and are therefore more closely related to each other than to other well-known sources. This and other evidence lends incontrovertible support to Irving Lowens's notion that Walter was Tufts's primary musical source for the fifth and later editions. Thus, Walter deserves primac...
Teaching introductory geographic information systems through problem-based learning and public scholarship

Teaching geographic information systems (GIS) requires linking concepts with technical skills, which can be challenging, especially in standard lecture and laboratory-format courses. This paper reports on an introductory undergraduate GIS course that incorporated a community-driven problem-based learning exercise as a major component of the course. Analysis of student performance and course evaluations indicates that the exercise was effective in aiding student learning of GIS, while also teaching research and other professional development skills, and providing insight into an important social issue within their community. Benefits and cautions are discussed from the perspective of students, instructor, university and local community.