cssi/SciSciGPT-SciSciNet huggingface dataset:
A simple proof of a new set disjointness with applications to data streams

The multiplayer promise set disjointness is one of the most widely used problems from communication complexity in applications. In this problem there are k players with subsets S1, ..., Sk, each drawn from {1, 2,..., n}, and we are promised that either the sets are (1) pairwise disjoint, or (2) there is a unique element j occurring in all the sets, which are otherwise pairwise disjoint. The total communication of solving this problem with constant probability in the blackboard model is Ω(n/k). We observe for most applications, it instead suffices to look at what we call the "mostly" set disjointness problem, which changes case (2) to say there is a unique element j occurring in at least half of the sets, and the sets are otherwise disjoint. This change gives us a much simpler proof of an Ω(n/k) randomized total communication lower bound, avoiding Hellinger distance and Poincare inequalities. Our proof also gives strong lower bounds for high probability protocols, which are much larger than what is possible for the set disjointness problem. Using this we show several new results for data streams: 1. for l2-Heavy Hitters, any O(1)-pass streaming algorithm in the insertion-only model for detecting if an e-l2-heavy hitter exists requires [EQUATION] bits of memory, which is optimal up to a log n factor. For deterministic algorithms and constant e, this gives an Ω(n1/2) lower bound, improving the prior Ω(log n) lower bound. We also obtain lower bounds for Zipfian distributions. 2. for lp-Estimation, p > 2, we show an O(1)-pass Ω(n1−2/p log(1/δ)) bit lower bound for outputting an O(1)- approximation with probability 1 − δ, in the insertion-only model. This is optimal, and the best previous lower bound was Ω(n1−2/p + log(1/δ)). 3. for low rank approximation of a sparse matrix in RdXn, if we see the rows of a matrix one at a time in the row-order model, each row having O(1) non-zero entries, any deterministic algorithm requires [EQUATION] memory to output an O(1)-approximate rank-1 approximation. Finally, we consider strict and general turnstile streaming models, and show separations between sketching lower bounds and non-sketching upper bounds for the heavy hitters problem.
Unsupervised Progressive Learning and the STAM Architecture

We first pose the Unsupervised Progressive Learning (UPL) problem: an online representation learning problem in which the learner observes a non-stationary and unlabeled data stream, and identifies a growing number of features that persist over time even though the data is not stored or replayed. To solve the UPL problem we propose the Self-Taught Associative Memory (STAM) architecture. Layered hierarchies of STAM modules learn based on a combination of online clustering, novelty detection, forgetting outliers, and storing only prototypical features rather than specific examples. We evaluate STAM representations using classification and clustering tasks. While there are no existing learning scenarios which are directly comparable to UPL, we compare the STAM architecture with two recent continual learning works; Memory Aware Synapses (MAS), and Gradient Episodic Memories (GEM), which have been modified to be suitable for the UPL setting.
Non-autophagy role of Atg5 and NBR1 in unconventional secretion of IL-12 prevents gut dysbiosis and inflammation.

Intestinal myeloid cells play a critical role in balancing intestinal homeostasis and inflammation. Here, we report that expression of the autophagy related 5 (Atg5) protein in myeloid cells prevents dysbiosis and excessive intestinal inflammation by limiting IL-12 production. Mice with a selective genetic deletion of Atg5 in myeloid cells (Atg5ΔMye) showed signs of dysbiosis prior to colitis and exhibited severe intestinal inflammation upon colitis induction that was characterized by increased IFNγ production. The exacerbated colitis was linked to excess IL-12 secretion from Atg5-deficient myeloid cells and gut dysbiosis. Restoration of the intestinal microbiota or genetic deletion of IL-12 in Atg5ΔMye mice attenuated the intestinal inflammation in Atg5ΔMye mice. Additionally, Atg5 functions to limit IL-12 secretion through modulation of late endosome (LE) acidity. Lastly, the autophagy cargo receptor NBR1, which accumulates in Atg5-deficient cells, played a role by delivering IL-12 to LE. In summary, Atg5 expression in intestinal myeloid cells acts as an anti-inflammatory brake to regulate IL-12 thus preventing dysbiosis and uncontrolled IFNγ-driven intestinal inflammation.
Provable Super-Convergence With a Large Cyclical Learning Rate

Conventional wisdom dictates that learning rate should be in the stable regime so that gradient-based algorithms don’t blow up. This letter introduces a simple scenario where an unstably large learning rate scheme leads to a super fast convergence, with the convergence rate depending only logarithmically on the condition number of the problem. Our scheme uses a Cyclical Learning Rate where we periodically take one large unstable step and several small stable steps to compensate for the instability. These findings also help explain the empirical observations of [Smith and Topin, 2019] where they show that CLR with a large maximum learning rate can dramatically accelerate learning and lead to so-called “super-convergence”. We prove that our scheme excels in the problems where Hessian exhibits a bimodal spectrum and the eigenvalues can be grouped into two clusters (small and large). The unstably large step is the key to enabling fast convergence over the small eigen-spectrum.
Quantum Generative Models for Small Molecule Drug Discovery

Existing drug discovery pipelines take 5–10 years and cost billions of dollars. Computational approaches aim to sample from regions of the whole molecular and solid-state compounds called chemical space, which could be on the order of $10^{60}$ . Deep generative models can model the underlying probability distribution of both the physical structures and property of drugs and relate them nonlinearly. By exploiting patterns in massive datasets, these models can distill salient features that characterize the molecules. Generative adversarial networks (GANs) discover drug candidates by generating molecular structures that obey chemical and physical properties and show affinity toward binding with the receptor for a target disease. However, classical GANs cannot explore certain regions of the chemical space and suffer from training instabilities. The practical utility of such models is limited due to the vast size of the search space, characterized by millions of parameters. A full quantum GAN may require more than 90 qubits even to generate small molecules with up to nine heavy atoms. The proposed quantum GAN with a hybrid generator (QGAN-HG) model is composed of a hybrid quantum generator that supports various number of qubits and quantum circuit layers, and a classical discriminator. The QGAN-HG with less than 20% of the original parameters can learn molecular distributions as efficiently as its classical counterpart. Another extended version of the proposed QGAN-HG, which utilizes multiple quantum subcircuits, considerably accelerates our standard QGAN-HG training process and avoids the potential gradient vanishing issue of deep neural networks.
Umpolung Strategy for Arene C−H Etherification Leading to Functionalized Chromanes Enabled by I(III) N-Ligated Hypervalent Iodine Reagents

The direct formation of aryl C–O bonds via the intramolecular dehydrogenative coupling of a C–H bond and a pendant alcohol represents a powerful synthetic transformation. Herein, we report a method for intramolecular arene C–H etherification via an umpoled alcohol cyclization mediated by an I(III) N-HVI reagent. This approach provides access to functionalized chromane scaffolds from primary, secondary and tertiary alcohols via a cascade cyclization-iodonium salt formation, the latter providing a versatile functional handle for downstream derivatization. Computational studies support initial formation of an umpoled O-intermediate via I(III) ligand exchange, followed by competitive direct and spirocyclization/1,2-shift pathways.
On the limitations of single-step drift and minorization in Markov chain convergence analysis

Over the last three decades, there has been a considerable effort within the applied probability community to develop techniques for bounding the convergence rates of general state space Markov chains. Most of these results assume the existence of drift and minorization (d&m) conditions. It has often been observed that convergence rate bounds based on single-step d&m tend to be overly conservative, especially in high-dimensional situations. This article builds a framework for studying this phenomenon. It is shown that any convergence rate bound based on a set of d&m conditions cannot do better than a certain unknown optimal bound. Strategies are designed to put bounds on the optimal bound itself, and this allows one to quantify the extent to which a d&m-based convergence rate bound can be sharp. The new theory is applied to several examples, including a Gaussian autoregressive process (whose true convergence rate is known), and a Metropolis adjusted Langevin algorithm. The results strongly suggest that convergence rate bounds based on single-step d&m conditions are quite inadequate in high-dimensional settings.
Impossible configurations for geodesics on negatively-curved surfaces

Hass and Scott’s example of a 4-valent graph on the 3-punctured sphere that cannot be realized by geodesics in any metric of negative curvature is generalized to impossible configurations filling surfaces of genus n with k punctures for any n and k.
The Changing Lightcurve of the Double-mode RR Lyrae Variable Star V338 Boo

We present an analysis of the lightcurve extracted from Transiting Exoplanet Survey Satellite Full Frame Images of the double-mode RR Lyrae V338 Boo. We find that the fundamental mode pulsation is changing in amplitude across the 54 days of observations. The first overtone mode pulsation also changes, but on a much smaller scale. Harmonics and combinations of the primary pulsation modes also exhibit unusual behavior. Possible connections with other changes in RR Lyrae pulsations are discussed, but a full understanding of the cause of the changes seen in V338 Boo should shed light on some of the most difficult and unanswered questions in stellar pulsation theory, and astrophysics more generally.
From Culture to Clothing: Discovering the World Events Behind a Century of Fashion Images

Fashion is intertwined with external cultural factors, but identifying these links remains a manual process limited to only the most salient phenomena. We propose a data-driven approach to identify specific cultural factors affecting the clothes people wear. Using large-scale datasets of news articles and vintage photos spanning a century, we introduce a multi-modal statistical model to detect influence relationships between happenings in the world and people's choice of clothing. Furthermore, we apply our model to improve the concrete vision tasks of visual style forecasting and photo timestamping on two datasets. Our work is a first step towards a computational, scalable, and easily refreshable approach to link culture to clothing.
Most powerful test sequences with early stopping options

We extended the application of uniformly most powerful tests to sequential tests with different stage-specific sample sizes and critical regions. In the one parameter exponential family, likelihood ratio sequential tests are shown to be uniformly most powerful for any predetermined $$\alpha $$ -spending function and stage-specific sample sizes. To obtain this result, the probability measure of a group sequential design is constructed with support for all possible outcome events, as is useful for designing an experiment prior to having data. This construction identifies impossible events that are not part of the support. The overall probability distribution is dissected into components determined by the stopping stage. These components are the sub-densities of interim test statistics first described by Armitage et al. (J R Stat Soc: Ser A 132:235–244, 1969) that are commonly used to create stopping boundaries given an $$\alpha $$ -spending function and a set of interim analysis times. Likelihood expressions conditional on reaching a stage are given to connect pieces of the probability anatomy together. The reduction of support caused by the adoption of an early stopping rule induces sequential truncation (not nesting) in the probability distributions of possible events. Multiple testing induces mixtures on the adapted support. Even asymptotic distributions of inferential statistics that are typically normal, are not. Rather they are derived from mixtures of truncated multivariate normal distributions.
Sufficient conditions for feasibility of optimal control problems using Control Barrier Functions

Abstract It has been shown that satisfying state and control constraints while optimizing quadratic costs subject to desired (sets of) state convergence for affine control systems can be reduced to a sequence of quadratic programs (QPs) by using Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs). One of the main challenges in this approach is ensuring the feasibility of these QPs, especially under tight control bounds and safety constraints of high relative degree. The main contribution of this paper is to provide sufficient conditions for guaranteed feasibility. The sufficient conditions are captured by a single constraint that is enforced by a CBF, which is added to the QPs such that their feasibility is always guaranteed. The additional constraint is designed to be always compatible with the existing constraints, therefore, it cannot make a feasible set of constraints infeasible — it can only increase the overall feasibility. We illustrate the effectiveness of the proposed approach on an adaptive cruise control problem.
Contingencies from Observations: Tractable Contingency Planning with Learned Behavior Models

Humans have a remarkable ability to accurately reason about future events, including the behaviors and states of mind of other agents. Consider driving a car through a busy intersection: it is necessary to reason about the physics of the vehicle, the intentions of other drivers, and their beliefs about your own intentions. For example, if you signal a turn, another driver might yield to you; or if you enter the passing lane, another driver might decelerate to give you room to merge in front. Competent drivers must plan how they can safely react to a variety of potential future behaviors of other agents before they make their next move. This requires contingency planning: explicitly planning a set of conditional actions that depend on the stochastic outcome of future events. In this work, we develop a general-purpose contingency planner that is learned end-to-end using high-dimensional scene observations and low-dimensional behavioral observations. We use a conditional autoregressive flow model for contingency planning. We show how this model can tractably learn contingencies from behavioral observations. We developed a closed-loop control benchmark of realistic multi-agent scenarios in a driving simulator (CARLA), on which we compare our method to various noncontingent methods that reason about multi-agent future behavior, and find that our contingency planning method achieves qualitatively and quantitatively superior performance.
Magnetic loading of magnetars’ flares

Magnetars, the likely sources of Fast Radio Bursts (FRBs), produce both steady highly relativistic magnetized winds, and occasional ejection events. We demonstrate that the requirement of conservation of the magnetic flux dominates the overall dynamics of magnetic explosions. This is missed in conventional hydrodynamic models of the ejections as expanding shell with parametrically added magnetic field, as well as one-dimensional models of magnetic disturbances. Most of the initial free energy of an explosion is actually spent on stretching its own internal magnetic field, while doing minimal $pdV$ work against the surrounding. Magnetic explosions from magnetars come into force balance with the pre-flares wind close to the light cylinder. They are then advected quietly with the wind, or propagate as electromagnetic disturbances. No powerful shock waves are generated in the wind.
A Murine Model with JAK2V617F Expression in Both Hematopoietic Cells and Vascular Endothelial Cells Recapitulates the Key Features of Human Myeloproliferative Neoplasm

The myeloproliferative neoplasms (MPNs) are characterized by an expansion of the neoplastic hematopoietic stem/progenitor cells (HSPC) and an increased risk of cardiovascular complications. The acquired kinase mutation JAK2V617F is present in hematopoietic cells in a majority of patients with MPNs. Vascular endothelial cells (ECs) carrying the JAK2V617F mutation can also be detected in patients with MPNs. In this study, we show that a murine model with both JAK2V617F-bearing hematopoietic cells and JAK2V617F-bearing vascular ECs recapitulated all the key features of the human MPN disease, which include disease transformation from essential thrombocythemia to myelofibrosis, extramedullary splenic hematopoiesis, and spontaneous cardiovascular complications. During aging and MPN disease progression, there was a loss of both HSPC number and HSPC function in the marrow while the neoplastic hematopoiesis was relatively maintained in the spleen, mimicking the advanced phases of human MPN disease. Different vascular niche of the marrow and spleen could contribute to the different JAK2V617F mutant stem cell functions we have observed in this JAK2V617F-positive murine model. Compared to other MPN murine models reported so far, our studies demonstrate that endothelial dysfunction plays an important role in both the hematologic and cardiovascular abnormalities of MPN. Key PointsO_LIA murine model in which JAK2V617F is expressed in both hematopoietic cells and ECs recapitulated the key features of the human MPN disease C_LIO_LIDifferent vascular niche of the marrow and spleen could contribute to different JAK2V617F HSC functions during MPN disease progression C_LI
Mycobacterium tuberculosis canonical virulence factors interfere with a late component of the TLR2 response

For many intracellular pathogens, the phagosome is the site of events and interactions that shape infection outcome. Phagosomal membrane damage, in particular, is proposed to benefit invading pathogens. To define the innate immune consequences of this damage, we profiled macrophage transcriptional responses to wild-type Mycobacterium tuberculosis (Mtb) and mutants that fail to damage the phagosomal membrane. We identified a set of genes with enhanced expression in response to the mutants. These genes represented a late component of the TLR2-dependent transcriptional response to Mtb, distinct from an earlier component that included Tnf. Expression of the later component was inherent to TLR2 activation, dependent upon endosomal uptake, and enhanced by phagosome acidification. Canonical Mtb virulence factors that contribute to phagosomal membrane damage blunted phagosome acidification and undermined the endosome-specific response. Profiling cell survival and bacterial growth in macrophages demonstrated that the attenuation of these mutants is partially dependent upon TLR2. Further, TLR2 contributed to the attenuated phenotype of one of these mutants in a murine model of infection. These results demonstrate two distinct components of the TLR2 response and identify a component dependent upon endosomal uptake as a point where pathogenic bacteria interfere with the generation of effective inflammation. This interference promotes tuberculosis (TB) pathogenesis in both macrophage and murine infection models.
DeepStrike: Remotely-Guided Fault Injection Attacks on DNN Accelerator in Cloud-FPGA

As Field-programmable gate arrays (FPGAs) are widely adopted in clouds to accelerate Deep Neural Networks (DNN), such virtualization environments have posed many new security issues. This work investigates the integrity of DNN FPGA accelerators in clouds. It proposes DeepStrike, a remotely-guided attack based on power glitching fault injections targeting DNN execution. We characterize the vulnerabilities of different DNN layers against fault injections on FPGAs and leverage time-to-digital converter (TDC) sensors to precisely control the timing of fault injections. Experimental results show that our proposed attack can successfully disrupt the FPGA DSP kernel and misclassify the target victim DNN application.
Genome-wide association mapping of transcriptome variation in Mimulus guttatus indicates differing patterns of selection on cis- versus trans-acting mutations.

We measured the floral bud transcriptome of 151 fully sequenced lines of Mimulus guttatus from one natural population. Thousands of single nucleotide polymorphisms (SNPs) are implicated as transcription regulators, but there is a striking difference in the Allele Frequency Spectrum (AFS) of cis-acting and trans-acting mutations. Cis-SNPs have intermediate frequencies (consistent with balancing selection) while trans-SNPs exhibit a rare-alleles model (consistent with purifying selection). This pattern only becomes clear when transcript variation is normalized on a gene-to-gene basis. If a global normalization is applied, as is typically in RNAseq experiments, asymmetric transcript distributions combined with "rarity disequilibrium" produce a super-abundance of false positives for trans-acting SNPs. To explore the cause of purifying selection on trans-acting mutations, we identified gene expression modules as sets of co-expressed genes. The extent to which trans-acting mutations influence modules is a strong predictor of allele frequency. Mutations altering expression of genes with high "connectedness" (those that are highly predictive of the representative module expression value) have the lowest allele frequency. The expression modules can also predict whole-plant traits such as flower size. We find that a substantial portion of the genetic (co)variance among traits can be described as an emergent property of genetic effects on expression modules.
Improved optical standing-wave beam splitters for dilute Bose–Einstein condensates

Bose–Einstein condensate (BEC)-based atom interferometry exploits low temperatures and long coherence lengths to facilitate high-precision measurements. Progress in atom interferometry promises improvements in navigational devices like gyroscopes and accelerometers, as well as applications in fundamental physics such as accurate determination of physical constants. Previous work demonstrates that beam splitters and mirrors for coherent manipulation of dilute BEC momentum in atom interferometers can be implemented with sequences of non-resonant standing-wave light pulses. While previous work focuses on the optimization of the optical pulses’ amplitude and duration to produce high-order momentum states with high fidelity, we explore how varying the shape of the optical pulses affects optimal beam-splitter performance, as well as the effect of pulse shape on the sensitivity of optimized parameters in achieving high fidelity in high-momentum states. In simulations of two-pulse beam splitters utilizing optimized square, triangle, and sinc-squared pulse shapes applied to dilute BECs, we, in some cases, reduce parameter sensitivity by an order of magnitude while maintaining fidelity.
ASDF: A new data format for astronomy

Abstract We present the case for developing a successor format for the immensely successful FITS format. We first review existing alternative formats and discuss why we do not believe they provide an adequate solution. The proposed format is called the Advanced Scientific Data Format (ASDF) and is based on an existing text format, YAML, that we believe removes most of the current problems with the FITS format. An overview of the capabilities of the new format is given along with specific examples. This format has the advantage that it does not limit the size of attribute names (akin to FITS keyword names) nor place restrictions on the size or type of values attributes have. Hierarchical relationships are explicit in the syntax and require no special conventions. Finally, it is capable of storing binary data within the file in its binary form. At its basic level, the format proposed has much greater applicability than for just astronomical data.
Taxonomy of USA east coast fishing communities in terms of social vulnerability and resilience

Abstract Increased concern with the impacts that changing coastal environments can have on coastal fishing communities led to a recent effort by NOAA Fisheries social scientists to develop a set of indicators of social vulnerability and resilience for the U.S. Southeast and Northeast coastal communities. A goal of the NOAA Fisheries social vulnerability and resilience indicator program is to support time and cost effective use of readily available data in furtherance of both social impact assessments of proposed changes to fishery management regulations and climate change adaptation planning. The use of the indicators to predict the response to change in coastal communities would be enhanced if community level analyses could be grouped effectively. This study examines the usefulness of combining 1130 communities into 35 relevant subgroups by comparing results of a numerical taxonomy with data collected by interview methods, a process herein referred to as “ground-truthing.” The validation of the taxonomic method by the method of ground-truthing indicates that the clusters are adequate to be used to select communities for in-depth research.
Advanced Ceramics, Electronic Ceramics

Electronic ceramics is a generic term describing a class of inorganic, nonmetallic materials utilized in the electronics industry. The term electronic ceramics generally pertains to polycrystalline inorganic solids comprised of randomly oriented crystallites (grains) intimately bonded together. This random orientation of small, micrometer-size crystals results in an isotropic ceramic possessing equivalent properties in all directions. Electronic ceramics are often combined with metals and polymers to meet the requirements of a broad spectrum of high technology applications, computers, telecommunications, sensors, and actuators. Electronic ceramics encompass a wide range of materials and crystal structure families used as insulators, capacitors, piezoelectrics, magnetics, semiconductor sensors, conductors, and the recently discovered high temperature superconductors. The development of multifunctional three-dimensional ceramic arrays called monolithic ceramics (MMC), continues the miniaturization process to provide a new generation of robust, inexpensive products. Rapid advances in integrated circuit technology have led to improved processing and manufacturing of multilayer ceramics (MLC), which consist of alternating layers of dielectric and metal electrodes, especially for capacitors and microelectronic packages. Presently, multilayer capacitors and packaging make up more than half the electronic ceramics market. Advances in the field of electronic ceramics are being made in new materials, novel powder synthesis methods, and in ceramic integration. The continuing miniaturization of electronic packaging should see the replacement of components and processes using such thin-film technologies developed for semiconductors as sputtering, chemical vapor deposition, and sol–gel. Keywords: Ceramics; Structure-property relationships; Electroceramics, Powder; Electronic ceramics; Thick film
Blacked Out: Government Secrecy in the Information Age, by Alasdair Roberts

The world has achieved unprecedented levels of government openness in the last three decades. When the United States passed the Freedom of Information Act in 1966, it was—in Alasdair Roberts's word...
Identifying beneficial teammates using multi-dimensional trust

Multi-agent teams must be capable of selecting the most beneficial teammates for different situations. Multi-dimensional trustworthiness assessments have been shown significantly beneficial to agents when selecting appropriate teammates to achieve a given goal. Reliability, quality, availability, timeliness and compatibility define the behavioral constraints of the multidimensional trust (MDT) model. Given the MDT model in this research, an agent learns to identify the most beneficial teammates by prioritizing each dimension differently. An agent's attitudes towards rewards, risks and urgency are used to drive an agent's prioritization of dimensions in a MDT model. Each agent is equipped with a Temporal-Difference (TD) learning mechanism with tile coding to identify its optimal set of attitudes and change its attitudes when the environment changes. Experimental results show that changing attitudes to give preferences for respective dimensions in the MDT offers a superior means to finding the best teammates for goal achievement.
Comparison of different methodologies for the computation of ground conductivity in Brazil

This paper describes the calculation of the average ground conductivity from electric field measurements on MF frequency band carried out in Rio Grande do Norte state, Brazil. This effort aims to provide accurate information on the ground conductivity, which is a key parameter related to digital broadcast system planning at frequencies below 30 MHz. Two prediction models are analyzed. One of them is fully described by Norton and Van der Pol formulations and the other one has more input parameters, intended for urban use. Measurements were performed at 1090 kHz.
Optimum cumulant-based blind beamforming for coherent signals and interferences

We propose an optimum cumulant-based blind beamforming method for signal recovery in coherent signal environments. Our approach is applicable to any array configuration having arbitrary and unknown response. There is no need to estimate the directions of arrival. A comparable result does not exist using second-order statistics.
Graduate Student Use of Campus Green Spaces and the Impact on Their Perceptions of Quality of Life

Students’ perception of their overall academic experience and the campus environment is related to academic accomplishment, and research has found that the designed environment of the university can influence the degree of stress students may feel. Past research found that undergraduate student use of campus green spaces and perceptions of quality of life were related to each other. The main objective of this study was to investigate the relationship between graduate student use of campus green spaces and their perceptions of quality of life at a university in Texas. A total of 347 of 3279 ( 10%) of the graduate student body received e-mails with information regarding the incentive for participation and instructions on accessing an on-line survey. The survey included questions that related to student use of campus green spaces, overall quality of life statements, an instrument to measure the quality of life of university students, and demographic questions. A total of 79 (22.8% response rate) graduate student questionnaires were collected and analyzed to compare perceptions of quality of life of university students and the level of individual usage of campus green spaces. Descriptive statistics determined that, unlike undergraduates who were primarily ‘‘high users’’ of campus green spaces, graduate students were about equally split between being ‘‘low,’’ ‘‘medium,’’ and ‘‘high users’’ of campus green spaces. However, graduate students still ranked their quality of life highly. Finally, this study found that, unlike undergraduates, graduate students did not have a statistically significant relationship between greenuser scores and perception of quality of life scores. It may be that graduate students have less time to spend in outdoor spaces, yet still meet their quality of life needs through other means such as academic achievements.
Lesions of the central nucleus of the amygdala, but not the paraventricular nucleus of the hypothalamus, block the excitatory effects of corticotropin-releasing factor on the acoustic startle reflex

Intracerebroventricular (icv) infusion of corticotropin-releasing factor (CRF) was previously found to produce a long-lasting, dose- dependent (0.1–1.0 microgram) increase in the amplitude of the acoustic startle reflex. The present study sought to determine where in the CNS CRF acts to increase startle. Intracisternal infusion of CRF (0.1–1.0 microgram) increased startle with a time course and magnitude similar to that produced by icv CRF, unlike intrathecal infusion, which produced a small, more rapid enhancement of startle. While lesions of the paraventricular nucleus of the hypothalamus had no effect on icv CRF-enhanced startle, bilateral lesions of the central nucleus of the amygdala significantly attenuated the excitatory effect of icv CRF but had no effect on intrathecal CRF-enhanced startle. Even though lesions of the amygdala blocked icv CRF-enhanced startle, local infusion of CRF into the amygdala did not significantly elevate startle. The present data indicate that the amygdala is part of the neural circuitry required for icv CRF to elevate startle, but does not appear to be the primary receptor area where CRF acts. The involvement of the amygdala in icv CRF-enhanced startle is consistent with the hypothesis that both the amygdala and CRF are critically involved in fear and stress.
Design of the national compact stellarator experiment (NCSX)

Abstract The National Compact Stellarator Experiment (NCSX) [ http://www.pppl.gov/ncsx/Meetings/CDR/CDRFinal/EngineeringOverview_R2.pdf ] is being designed as a proof of principal test of a quasi-axisymmetric compact stellarator. This concept combines the high beta and good confinement features of an advanced tokamak with the low current, disruption-free characteristics of a stellarator. NCSX has a three-field-period plasma configuration with an average major radius of 1.4 m, an average minor radius of 0.33 m and a toroidal magnetic field on axis of up to 2 T. The stellarator core is a complex assembly of four coil systems that surround the highly shaped plasma and vacuum vessel. Heating is provided by up to four, 1.5 MW neutral beam injectors and provision is made to add 6 MW of ICRH. The experiment will be built at the Princeton Plasma Physics Laboratory, with first plasma expected in 2007.
Slack allocation algorithm for parallel machines

Energy consumption is a critical issue in parallel and distributed embedded systems. We present a novel algorithm for energy efficient scheduling of Directed Acyclic Graph (DAG) based applications on Dynamic Voltage Scaling (DVS) enabled systems. Experimental results show that our algorithm provides near optimal solutions for energy minimization with considerably smaller computational time and memory requirements compared to an existing algorithm that provides near optimal solutions.
On the persistent sodium current in squid giant axons.

R. F. Rakowski, D. C. Gadsby, and P. DeWeer have reported a persistent, tetrodotoxin-sensitive sodium ion current (I NaP) in squid giant axons having a low threshold (-90 mV) and a maximal inward a...
Critical phenomena and finite-size scaling in communication networks?

This paper presents a statistical mechanics-based approach to investigate critical phenomena and size scaling in communication networks. The qualitative nature of phase transitions in the underlying network systems is characterized; and its static and dynamic critical behaviors are identified. Effects of network size, different routing strategies have been analyzed. In all these analyses, phase transition is considered using a single intensive parameter of the communication network system, namely the external packet load. These problems have been investigated by extensive simulation on the model of a wired communication network.
Ferromagnetic Resonance of Single-Domain Particles

The ferromagnetic-resonance spectra of powders containing single-domain particles have been studied experimentally and theoretically. The theory is based on the Stoner-Wohlfarth model. The line shapes were calculated with the aid of a high-speed digital computer. Measurements were made on $\ensuremath{\gamma}$-${\mathrm{Fe}}_{2}$${\mathrm{O}}_{3}$ powders, both with and without an applied steady magnetic field. For zero applied steady field, the theoretical line shapes agree well with the experimental ones provided the particle shape distribution, the crystalline anisotropy, and the particle interactions are taken into account. With an applied field, the theoretical curves with only the shape distribution considered do not agree with the theoretical ones. It is found that the anisotropy constant ${K}_{1}$ and the relaxation time $\ensuremath{\tau}$ of $\ensuremath{\gamma}$-${\mathrm{Fe}}_{2}$${\mathrm{O}}_{3}$ are approximately -2.5\ifmmode\times\else\texttimes\fi{}${10}^{5}$ ergs/${\mathrm{cm}}^{3}$ and 2.0\ifmmode\times\else\texttimes\fi{}${10}^{\ensuremath{-}10}$ sec, respectively.
Sparsely substituted chlorins as core constructs in chlorophyll analogue chemistry. Part 2: Derivatization

Stable chlorins bearing few or no substituents have been subjected to a variety of reactions including demetalation, magnesium insertion, oxochlorin formation, and bromination followed by Suzuki coupling. The kinetics of deuteration also have been determined for two oxochlorins and a series of chlorins bearing 0, 1, 2, or 3 meso-aryl substituents.
An axle-driven alternator-rectifier system for caboose power supply

The application of 2-way telephone communication to moving railroad trains has created a need for a dependable power supply for railway cabooses. A study of the system requirements indicated an axle-driven alternator-rectifier equipment to be better suited to this application than the conventional d-c generator. A 3?5-kw alternator system has been developed, paying particular attention to the requirements of this service and to the fact that the equipment must operate over long periods without attention.
THE OPTIMAL CONVERGENCE OF REGIONAL INCOMES

For many policy considerations it is assumed that the convergence of regional mean income will improve national equity by reducing overall inequality. The literature on decomposability of social welfare functions implies that this assumption is unwarranted. This paper develops a notion of optimal regional convergence. In general, the point of optimal convergence depends on the shapes of the regional income distributions, the inequality index used, and the rule for distributing interregional transfers. These concepts are illustrated with data on the regional income distributions of the Southern and Northern United States.
Polyelectrolyte Complexes with pH-Tunable Solubility

Polyelectrolyte complexes (PECs) with pH-tunable solubility were formed from a random copolymer of diallyldimethylammonium (DADMA) and acrylic acid (AA) having a net positive charge as polycation and poly(styrenesulfonate) as polyanion. Quasi-soluble PEC nanoparticles could be produced from solutions of exceptionally high polymer concentration by manipulating pH and ionic strength. The aggregation of the PEC nanoparticles, reversible using either changes in salt concentration or pH, exhibited well-defined hysteresis. Dynamic and static light scattering as well as transmission electron microscopy showed well-defined particles produced in the quasi-soluble limit. Viscosity and titration experiments supported a core−shell model for the dispersed nanoparticles and revealed preferential ion pairing of DADMA with sulfonic acid groups over AA units.
Biobased Chitosan/Polybenzoxazine Cross-Linked Films: Preparation in Aqueous Media and Synergistic Improvements in Thermal and Mechanical Properties

A novel class of polymer blends has been prepared from main-chain-type benzoxazine polymer (MCBP) and chitosan (CTS), a modified biomacromolecule. A water-soluble, main-chain-type benzoxazine polymer, MCBP(BA-tepa), was synthesized from the reaction of bisphenol A (BA), tetraethylenepentamine (TEPA) and formalin. The structure of the MCBP(BA-tepa) was confirmed by proton nuclear magnetic resonance spectroscopy (1H NMR) and Fourier transform infrared spectroscopy (FT-IR). The polymer blends were prepared by mixing MCBP(BA-tepa) and CTS in aqueous acetic acid solution (1%). The CTS/MCBP(BA-tepa) films are cross-linked by thermal treatment via the ring-opening polymerization of benzoxazine structures in the main chain to produce an AB-cross-linked network. Differential scanning calorimetry (DSC) and FT-IR were used to study the effects of CTS on the polymerization behavior of benzoxazine. Hydrogen bonding between polybenzoxazine and CTS structures was also observed. The mechanical and thermal properties of c...
Functional bias in molecular evolution rate of Arabidopsis thaliana

Characteristics derived from mutation and other mechanisms that are advantageous for survival are often preserved during evolution by natural selection. Some genes are conserved in many organisms because they are responsible for fundamental biological function, others are conserved for their unique functional characteristics. Therefore one would expect the rate of molecular evolution for individual genes to be dependent on their biological function. Whether this expectation holds for genes duplicated by whole genome duplication is not known. We empirically demonstrate here, using duplicated genes generated from the Arabidopsis thaliana α-duplication event, that the rate of molecular evolution of genes duplicated in this event depend on biological function. Using functional clustering based on gene ontology annotation of gene pairs, we show that some duplicated genes, such as defense response genes, are under weaker purifying selection or under stronger diversifying selection than other duplicated genes, such as protein translation genes, as measured by the ratio of nonsynonymous to synonymous divergence (dN/dS). These results provide empirical evidence indicating that molecular evolution rate for genes duplicated in whole genome duplication, as measured by dN/dS, may depend on biological function, which we characterize using gene ontology annotation. Furthermore, the general approach used here provides a framework for comparative analysis of molecular evolution rate for genes based on their biological function.
Cooling of optical fiber in aiding and opposing forced gas flow

Abstract Convective flows in annular passages with the inner core moving at constant speed were investigated for conditions applied to the cooling of optical fiber during the draw process. Temperature dependent gas properties were fully accounted for in the complete set of conservation equations. The geometrical configuration of the model was formulated to reflect experimental conditions previously used for cooling of the fiber in forced flow. The numerical solution of the conservation equations was validated using experimental measurements. The numerical results were used to predict the variation of fiber temperature at the cooling section exit with respect to relevant draw parameters for aiding and opposing flows. A mean temperature for the gas properties was found, that can be used to predict within 10% the exit fiber temperature using constant property modeling. The results presented allow estimation of the fiber temperature for a wide range of operating conditions and cooling section geometries.
Diagnostic and measurement issues in the assessment of pediatric bipolar disorder: implications for understanding mood disorder across the life cycle

The goal of this paper is to review assessment research of bipolar disorder in children and adolescents. The review addresses numerous themes: the benefits and costs of involving clinical judgment in the diagnostic process, particularly with regard to diagnosis and mood severity ratings; the validity of parent, teacher, and youth self-report of manic symptoms; how much cross-situational consistency is typically shown in mood and behavior; the extent to which a parent's mental health status influences their report of child behavior; how different measures compare in terms of detecting bipolar disorder, the challenges in comparing the performance of measures across research groups, and the leading candidates for research or clinical use; evidence-based strategies for interpreting measures as diagnostic aids; how test performance changes when a test is used in a new setting and what implications this has for research samples as well as clinical practice; the role of family history of mood disorder within an assessment framework; and the implications of assessment research for the understanding of phenomenology of bipolar disorder from a developmental framework.
Synthesis of the C1′–C11′ portion of pamamycin-607 via a stereoselective oxymercuration of a gamma—silyloxyallene and a stereospecific magnesium—methanol reduction

The C1′–C11′ portion of the antibiotic pamamycin-607, a novel homologue and C2-epimer of nonactic acid, was synthesized in six steps from 4,5-hexadien-1-ol via a novel cis-selective oxymercuration/transpalladation/methoxycarboxylation of a γ-silyloxyallene and a syn-selective reduction of a 2-(2-tetrahydrofuranyl)acrylate using magnesium in methanol. Spectroscopic properties of a derivative of the synthetic C1′–C11′ portion match those of material derived from the natural product.
Nanoporous Materials Derived from Polymeric Bicontinuous Microemulsions

We demonstrate a universal approach to the synthesis of nanoporous materials with pore structures that are highly precise replications of bicontinuous microemulsions. The materials can be formed at...
Derivation of a matrix describing a rugate dielectric thin film

In optical coating calculations, a 2 × 2 matrix formalism is generally used to describe the effect of each layer on the electromagnetic field. In current applications, the layers are considered homogeneous, and, therefore, the matrix used is restricted to this particular case. In this paper, a 2 × 2 matrix describing an inhomogeneous dielectric thin film is derived from Maxwell’s equations. The inhomogeneity is assumed to vary along the direction perpendicular to the film plane. No restriction is made on the amplitude of its variation. The matrix is illustrated in the case of a rugate filter designed according to Sossi’s Fourier transform technique. An improved approximation for the Fourier transform technique is then introduced.
X-Ray Diffraction Study of Fossil Elemis

X-ray diffraction identification of α-amyrin in guayaquillite, Highgate copalite and glessite places these fossil resins among the elemis In the Burseraceae family of angiosperm trees. Correlation of their geographical occurrences lends support to the belief that the so-called Amber Forests flourished during Eocene as well as Oligocene times.