cssi/SciSciGPT-SciSciNet huggingface dataset:
Physical reservoir computing with origami and its application to robotic crawling.

A new paradigm called physical reservoir computing has recently emerged, where the nonlinear dynamics of high-dimensional and fixed physical systems are harnessed as a computational resource to achieve complex tasks. Via extensive simulations based on a dynamic truss-frame model, this study shows that an origami structure can perform as a dynamic reservoir with sufficient computing power to emulate high-order nonlinear systems, generate stable limit cycles, and modulate outputs according to dynamic inputs. This study also uncovers the linkages between the origami reservoir’s physical designs and its computing power, offering a guideline to optimize the computing performance. Comprehensive parametric studies show that selecting optimal feedback crease distribution and fine-tuning the underlying origami folding designs are the most effective approach to improve computing performance. Furthermore, this study shows how origami’s physical reservoir computing power can apply to soft robotic control problems by a case study of earthworm-like peristaltic crawling without traditional controllers. These results can pave the way for origami-based robots with embodied mechanical intelligence.
Streaming k-PCA: Efficient guarantees for Oja's algorithm, beyond rank-one updates

We analyze Oja's algorithm for streaming $k$-PCA, and prove that it achieves performance nearly matching that of an optimal offline algorithm. Given access to a sequence of i.i.d. $d \times d$ symmetric matrices, we show that Oja's algorithm can obtain an accurate approximation to the subspace of the top $k$ eigenvectors of their expectation using a number of samples that scales polylogarithmically with $d$. Previously, such a result was only known in the case where the updates have rank one. Our analysis is based on recently developed matrix concentration tools, which allow us to prove strong bounds on the tails of the random matrices which arise in the course of the algorithm's execution.
WikiTableT: A Large-Scale Data-to-Text Dataset for Generating Wikipedia Article Sections

Datasets for data-to-text generation typically focus either on multi-domain, single-sentence generation or on single-domain, long-form generation. In this work, we cast generating Wikipedia sections as a data-to-text generation task and create a large-scale dataset, WikiTableT, that pairs Wikipedia sections with their corresponding tabular data and various metadata. WikiTableT contains millions of instances, covering a broad range of topics, as well as a variety of flavors of generation tasks with different levels of flexibility. We benchmark several training and decoding strategies on WikiTableT. Our qualitative analysis shows that the best approaches can generate fluent and high quality texts but they struggle with coherence and factuality, showing the potential for our dataset to inspire future work on long-form generation.
Learning to Generate Task-Specific Adapters from Task Description

Pre-trained text-to-text transformers such as BART have achieved impressive performance across a range of NLP tasks. Recent study further shows that they can learn to generalize to novel tasks, by including task descriptions as part of the source sequence and training the model with (source, target) examples. At test time, these fine-tuned models can make inferences on new tasks using the new task descriptions as part of the input. However, this approach has potential limitations, as the model learns to solve individual (source, target) examples (i.e., at the instance level), instead of learning to solve tasks by taking all examples within a task as a whole (i.e., at the task level). To this end, we introduce Hypter, a framework that improves text-to-text transformer’s generalization ability to unseen tasks by training a hypernetwork to generate task-specific, light-weight adapters from task descriptions. Experiments on ZEST dataset and a synthetic SQuAD dataset demonstrate that Hypter improves upon fine-tuning baselines. Notably, when using BART-Large as the main network, Hypter brings 11.3% comparative improvement on ZEST dataset.
Deep Feature Space Trojan Attack of Neural Networks by Controlled Detoxification.

Trojan (backdoor) attack is a form of adversarial attack on deep neural networks where the attacker provides victims with a model trained/retrained on malicious data. The backdoor can be activated when a normal input is stamped with a certain pattern called trigger, causing misclassification. Many existing trojan attacks have their triggers being input space patches/objects (e.g., a polygon with solid color) or simple input transformations such as Instagram filters. These simple triggers are susceptible to recent backdoor detection algorithms. We propose a novel deep feature space trojan attack with five characteristics: effectiveness, stealthiness, controllability, robustness and reliance on deep features. We conduct extensive experiments on 9 image classifiers on various datasets including ImageNet to demonstrate these properties and show that our attack can evade state-of-the-art defense.
SYMMETRIES, HORIZONS AND BLACK HOLE ENTROPY

Black holes behave as thermodynamic systems, and a central task of any quantum theory of gravity is to explain these thermal properties. A statistical mechanical description of black hole entropy once seemed remote, but today we suffer an embarrassment of riches: despite counting very different states, many inequivalent approaches to quantum gravity obtain identical results. Such “universality” may reflect an underlying two-dimensional conformal symmetry near the horizon, which can be powerful enough to control the thermal characteristics independent of other details of the theory. This picture suggests an elegant description of the relevant degrees of freedom as Goldstone-boson-like excitations arising from symmetry breaking by the conformal anomaly.
Bridgman growth of germanium crystals in a rotating magnetic field

Abstract A series of (1 0 0)-oriented gallium-doped germanium crystals has been grown by the vertical Bridgman method and under the influence of a rotating magnetic field (RMF). Time-dependent flow instabilities occur when the critical magnetic Taylor number ( T m c ) is exceeded, and this can be observed by noting the appearance of striations in the grown crystals. T m c decreases as the aspect ratio of the melt increases, and approaches the theoretical limit expected for an infinite cylinder. Intentional interface demarcations are introduced by pulsing the RMF on and off. The RMF has a marked effect on the interface shape, changing it from concave to nearly flat as the RMF strength is increased.
Fusion 360 gallery: a dataset and environment for programmatic CAD construction from human design sequences

Parametric computer-aided design (CAD) is a standard paradigm used to design manufactured objects, where a 3D shape is represented as a program supported by the CAD software. Despite the pervasiveness of parametric CAD and a growing interest from the research community, currently there does not exist a dataset of realistic CAD models in a concise programmatic form. In this paper we present the Fusion 360 Gallery, consisting of a simple language with just the sketch and extrude modeling operations, and a dataset of 8,625 human design sequences expressed in this language. We also present an interactive environment called the Fusion 360 Gym, which exposes the sequential construction of a CAD program as a Markov decision process, making it amendable to machine learning approaches. As a use case for our dataset and environment, we define the CAD reconstruction task of recovering a CAD program from a target geometry. We report results of applying state-of-the-art methods of program synthesis with neurally guided search on this task.
Assessing the relationship between health and household portfolio allocation

This paper surveys the literature on the relationship between health and household portfolio allocation and provides updated empirical analysis based on recent data. Prior research finds robust evidence for cross-sectional correlations between measures of health status and portfolio decisions, but establishing the causal pathways and underlying mechanisms has proven more difficult and complex. Analysis from the most recently available 2016 and 2018 waves of the Health and Retirement Study yields results that are consistent with existing literature. Households with worse self-reported health have a lower probability of holding various types of financial assets and invest a higher share of their portfolios in safe assets, relative to other asset categories. However, there is only weak evidence that new health shocks to a household change portfolio holdings. The paper concludes with a discussion of the implications of this research and directions for future work.
QCD beyond diagrams

Quantum chromodynamics (QCD), the theory of the strong interactions, involves quarks interacting with non-Abelian gluon fields. This theory has many features that are difficult to impossible to see...
Gerstenhaber bracket on Hopf algebra and Hochschild cohomologies

Abstract We calculate the Gerstenhaber bracket on Hopf algebra and Hochschild cohomologies of the Taft algebra T p for any integer p > 2 which is a nonquasi-triangular Hopf algebra. We show that the bracket is indeed zero on Hopf algebra cohomology of T p , as in all known quasi-triangular Hopf algebras. This example is the first known bracket computation for a nonquasi-triangular algebra. Also, we find a general formula for the bracket on Hopf algebra cohomology of any Hopf algebra with bijective antipode on the bar resolution that is reminiscent of Gerstenhaber's original formula for Hochschild cohomology.
Learning a neural diff for speech models

As more speech processing applications execute locally on edge devices, a set of resource constraints must be considered. In this work we address one of these constraints, namely over-the-network data budgets for transferring models from server to device. We present neural update approaches for release of subsequent speech model generations abiding by a data budget. We detail two architecture-agnostic methods which learn compact representations for transmission to devices. We experimentally validate our techniques with results on two tasks (automatic speech recognition and spoken language understanding) on open source data sets by demonstrating when applied in succession, our budgeted updates outperform comparable model compression baselines by significant margins.
How Long to Estimate Sparse MIMO Channels

Large MIMO transceivers are integral components of next-generation wireless networks. However, for such systems to be practical, their channel estimation process needs to be fast and reliable. Although several solutions for fast estimation of sparse channels do exist, there is still a gap in understanding the fundamental limits governing this problem. Specifically, we need to better understand the lower bound on the number of measurements under which accurate channel estimates can be obtained. This work bridges that knowledge gap by deriving a tight asymptotic lower bound on the number of measurements. This not only helps develop a better understanding for the sparse MIMO channel estimation problem, but it also provides a benchmark for evaluating current and future solutions.
Mechanistic determination of tear film thinning via fitting simplified models to tear breakup

Purpose: Little quantitative or mechanistic information about tear film breakup can be determined directly via current imaging techniques. In this paper, we present simplified mathematical models based on two proposed mechanisms of tear film breakup: evaporation of water from the tear film and tangential fluid flow within the tear film. We use our models to determine whether one or a combination of the two mechanisms causes tear film breakup in a variety of instances. In this study, we estimate related breakup parameters that cannot currently be measured in breakup during subject trials, such as tear film osmolarity and thinning rates. The present study validates our procedure against previous work.Methods: Five ordinary differential equation models for tear film thinning were designed that model evaporation, osmosis, and various types of tangential flow. Eight tear film breakup instances occurring within a time interval of 1–8 s postblink of five healthy subjects thatwere identified in fluorescence images in previous work were fit with these five models. The fitting procedure used a nonlinear least squares optimization that minimized the dierence of the computed theoretical fluorescent intensity from the models and the experimental fluorescent intensity from the images. The optimization was conducted over the evaporation rate and up to three tangential flow rate parameters. The smallest norm of the difference was determined to correspond to the model that best explained the tear film dynamics.Results: All of the breakup instances were best fit by models with time-dependent tangential flow. Our optimal parameter values and thinning rate as well as tangential fluid flow profiles compare well with previous partial differential equation model results in most instances.Conclusion: Our fitting results suggest that a combination of tangential fluid flow and evaporation cause most of the breakup instances. Comparison with results from previous work suggests that the simplified models can capture the essential tear film dynamics in most cases, thereby validating this procedure for wider usage.
Graviton chirality and topological order in the half-filled Landau level

The fractional quantum Hall state at the Landau level filling factor $5/2$ is extremely interesting because it is likely the first non-Abelian state, but its precise nature remains unclear after decades of study. We demonstrate this can be resolved by studying the chirality of its graviton excitations, using circularly polarized Raman scattering. We discuss the advantage of this bulk probe over the existing edge probes.
Sufficient condition for root reconstruction by parsimony on binary trees with general weights

We consider the problem of inferring an ancestral state from observations at the leaves of a tree, assuming the state evolves along the tree according to a two-state symmetric Markov process. We establish a general branching rate condition under which maximum parsimony, a common reconstruction method requiring only the knowledge of the tree topology (but not of the substitution rates or other parameters), succeeds better than random guessing uniformly in the depth of the tree. We thereby generalize previous results of [13, 37]. Our results apply to both deterministic and i.i.d. edge weights.
Robust Place Recognition using an Imaging Lidar

We propose a methodology for robust, real-time place recognition using an imaging lidar, which yields image-quality high-resolution 3D point clouds. Utilizing the intensity readings of an imaging lidar, we project the point cloud and obtain an intensity image. ORB feature descriptors are extracted from the image and encoded into a bag-of-words vector. The vector, used to identify the point cloud, is inserted into a database that is maintained by DBoW for fast place recognition queries. The returned candidate is further validated by matching visual feature descriptors. To reject matching outliers, we apply PnP, which minimizes the reprojection error of visual features’ positions in Euclidean space with their correspondences in 2D image space, using RANSAC. Combining the advantages from both camera and lidar-based place recognition approaches, our method is truly rotation-invariant, and can tackle reverse revisiting and upside down revisiting. The proposed method is evaluated on datasets gathered from a variety of platforms over different scales and environments. Our implementation and datasets are available at https://git.io/image-lidar.
Mitigating Racial Biases in Toxic Language Detection with an Equity-Based Ensemble Framework

Recent research has demonstrated how racial biases against users who write African American English exists in popular toxic language datasets. While previous work has focused on a single fairness criteria, we propose to use additional descriptive fairness metrics to better understand the source of these biases. We demonstrate that different benchmark classifiers, as well as two in-process bias-remediation techniques, propagate racial biases even in a larger corpus. We then propose a novel ensemble-framework that uses a specialized classifier that is fine-tuned to the African American English dialect. We show that our proposed framework substantially reduces the racial biases that the model learns from these datasets. We demonstrate how the ensemble framework improves fairness metrics across all sample datasets with minimal impact on the classification performance, and provide empirical evidence for its ability to unlearn the annotation biases towards authors who use African American English. ** Please note that this work may contain examples of offensive words and phrases.
Uniqueness of weakly reversible and deficiency zero realizations of dynamical systems.

Abstract A reaction network together with a choice of rate constants uniquely gives rise to a system of differential equations, according to the law of mass-action kinetics. On the other hand, different networks can generate the same dynamical system under mass-action kinetics. Therefore, the problem of identifying “the” underlying network of a dynamical system is not well-posed, in general. Here we show that the problem of identifying an underlying weakly reversible deficiency zero network is well-posed, in the sense that the solution is unique whenever it exists. This can be very useful in applications because from the perspective of both dynamics and network structure, a weakly reversible deficiency zero (WR0) realization is the simplest possible one. Moreover, while mass-action systems can exhibit practically any dynamical behavior, including multistability, oscillations, and chaos, WR0 systems are remarkably stable for any choice of rate constants: they have a unique positive steady state within each invariant polyhedron, and cannot give rise to oscillations or chaotic dynamics. We also prove that both of our hypotheses (i.e., weak reversibility and deficiency zero) are necessary for uniqueness.
A statistical learning assessment of Huber regression

Abstract As one of the triumphs and milestones of robust statistics, Huber regression plays an important role in robust inference and estimation. It has also been finding a great variety of applications in machine learning. In a parametric setup, it has been extensively studied. However, in the statistical learning context where a function is typically learned in a nonparametric way, there is still a lack of theoretical understanding of how Huber regression estimators learn the conditional mean function and why it works in the absence of light-tailed noise assumptions. To address these fundamental questions, this paper conducts an assessment of Huber regression from a statistical learning viewpoint. First, we show that the usual risk consistency property of Huber regression estimators, which is usually pursued in machine learning, cannot guarantee their learnability in mean regression. Second, we argue that Huber regression should be implemented in an adaptive way to perform mean regression, implying that one needs to tune the scale parameter in accordance with the sample size and the moment condition of the noise. Third, with an adaptive choice of the scale parameter, we demonstrate that Huber regression estimators can be asymptotic mean regression calibrated under ( 1 + e ) -moment conditions ( e > 0 ) on the conditional distribution. Last but not least, under the same moment conditions, we establish almost sure convergence rates for Huber regression estimators. Note that the ( 1 + e ) -moment conditions accommodate the special case where the response variable possesses infinite variance and so the established convergence rates justify the robustness feature of Huber regression estimators. In the above senses, the present study provides a systematic statistical learning assessment of Huber regression estimators and justifies their merits in terms of robustness from a theoretical viewpoint.
The bitter end: T2R bitter receptor agonists elevate nuclear calcium and induce apoptosis in non-ciliated airway epithelial cells

Bitter taste receptors (T2Rs) localize to airway motile cilia and initiate innate immune responses in retaliation to bacterial quorum sensing molecules. Activation of cilia T2Rs leads to calcium-driven NO production that increases cilia beating and directly kills bacteria. Several diseases, including chronic rhinosinusitis, COPD, and cystic fibrosis, are characterized by loss of motile cilia and/or squamous metaplasia. To understand T2R function within the altered landscape of airway disease, we studied T2Rs in non-ciliated airway cell lines and primary cells. Several T2Rs localize to the nucleus in de-differentiated cells that typically localize to cilia in differentiated cells. As cilia and nuclear import utilize shared proteins, some T2Rs may target to the nucleus in the absence of motile cilia. T2R agonists selectively elevated nuclear and mitochondrial calcium through a G-protein-coupled receptor phospholipase C mechanism. Additionally, T2R agonists decreased nuclear cAMP, increased nitric oxide, and increased cGMP, consistent with T2R signaling. Furthermore, exposure to T2R agonists led to nuclear calcium-induced mitochondrial depolarization and caspase activation. T2R agonists induced apoptosis in primary bronchial and nasal cells differentiated at air-liquid interface but then induced to a squamous phenotype by apical submersion. Air-exposed well-differentiated cells did not die. This may be a last-resort defense against bacterial infection. However, it may also increase susceptibility of de-differentiated or remodeled epithelia to damage by bacterial metabolites. Moreover, the T2R-activated apoptosis pathway occurs in airway cancer cells. T2Rs may thus contribute to microbiome-tumor cell crosstalk in airway cancers. Targeting T2Rs may be useful for activating cancer cell apoptosis while sparing surrounding tissue.
Identifying Morality Frames in Political Tweets using Relational Learning

Extracting moral sentiment from text is a vital component in understanding public opinion, social movements, and policy decisions. The Moral Foundation Theory identifies five moral foundations, each associated with a positive and negative polarity. However, moral sentiment is often motivated by its targets, which can correspond to individuals or collective entities. In this paper, we introduce morality frames, a representation framework for organizing moral attitudes directed at different entities, and come up with a novel and high-quality annotated dataset of tweets written by US politicians. Then, we propose a relational learning model to predict moral attitudes towards entities and moral foundations jointly. We do qualitative and quantitative evaluations, showing that moral sentiment towards entities differs highly across political ideologies.
A Review of Adversarial Attack and Defense for Classification Methods

Despite the efficiency and scalability of machine learning systems, recent studies have demonstrated that many classification methods, especially deep neural networks (DNNs), are vulnerable to adversarial examples; i.e., examples that are carefully crafted to fool a well-trained classification model while being indistinguishable from natural data to human. This makes it potentially unsafe to apply DNNs or related methods in security-critical areas. Since this issue was first identified by Biggio et al. (2013) and Szegedy et al.(2014), much work has been done in this field, including the development of attack methods to generate adversarial examples and the construction of defense techniques to guard against such examples. This paper aims to introduce this topic and its latest developments to the statistical community, primarily focusing on the generation and guarding of adversarial examples. Computing codes (in python and R) used in the numerical experiments are publicly available for readers to explore the surveyed methods. It is the hope of the authors that this paper will encourage more statisticians to work on this important and exciting field of generating and defending against adversarial examples.
The AGN Fraction in Dwarf Galaxies from eROSITA: First Results and Future Prospects

Determining the fraction of nearby dwarf galaxies hosting massive black holes (BHs) can inform our understanding of the origin of "seed" black holes at high redshift. Here we search for signatures of accreting massive BHs in a sample of dwarf galaxies ($M_\star \le 3 \times 10^9~M_\odot$, $z \leq 0.15$) selected from the NASA-Sloan Atlas (NSA) using X-ray observations from the eROSITA Final Equatorial Depth Survey (eFEDS). On average, our search is sensitive to active galactic nuclei (AGNs) in dwarf galaxies that are accreting at $\gtrsim 1\%$ of their Eddington luminosity. Of the ${\sim}28,000$ X-ray sources in eFEDS and the $495$ dwarf galaxies in the NSA within the eFEDS footprint, we find six galaxies hosting possible active massive BHs. If the X-ray sources are indeed associated with the dwarf galaxies, the X-ray emission is above that expected from star formation, with X-ray source luminosities of $L_{0.5-8~\textrm{keV}} \sim 10^{39\textrm{-}40}$ erg s$^{-1}$. Additionally, after accounting for chance alignments of background AGNs with dwarf galaxies, we estimate there are between 0-9 real associations between dwarf galaxies and X-ray sources in the eFEDS field at the $95\%$ confidence level. From this we find an upper limit on the eFEDS-detected dwarf galaxy AGN fraction of $\le 1.8\%$, which is broadly consistent with similar studies at other wavelengths. We extrapolate these findings from the eFEDS sky coverage to the planned eROSITA All-Sky Survey and estimate that upon completion, the all-sky survey could yield as many as ${\sim}1350$ AGN candidates in dwarf galaxies at low redshift.
Success of Surgical Left Atrial Appendage Closure: Assessment by Transesophageal Echocardiography

Of the 137 patients, 52 (38%) underwent excision and 85 (62%) underwent exclusion (73 suture and 12 stapler). Only 55 of 137 (40%) of closures were successful. Successful LAA closure occurred more often with excision (73%) than suture exclusion (23%) and stapler exclusion (0%) (p 0.001). We found LAA thrombus to be present in 28 of 68 patients (41%) with unsuccessful LAA exclusion versus none with excision. At time of TEE, 6 patients with successful LAA closure (11%) and 12 with unsuccessful closure (15%) had evidence of stroke/transient ischemic attack (p 0.61).
The Expressive Free Trade Agreement

In the international investment context, this paper focuses on the expressive power of the FTAs or BITs; expression of them may impact the players in the games. First, the paper examines the boost of the BITs and FTAs. The main focus is to test the application of game theory to the FTAs or BITs; the one is sequential game and the other is simultaneous (two-by-two) game, which the FTA would have the same setting. The question is how the states would play in the game table of the FTAs. In games, this paper tries to find Nash equilibrium in pure strategies. It assumes "perfect information" to simplify the games. Calculating the probability in mixed strategy and in the imperfect information is out of the scope of the paper. Second, the paper tests the "expressive law," which includes "focal point." It delves into the creation and function of the focal points and what their implications to the FTAs are. The paper assumes that the FTA may be an expressive power for the players when they form the future agreements. I take the example of newly signed: the Korea-US FTA, putting put into the Hawk-Dove (HD) game, which would lead to two potential equilibriums. The prevalence of one of them depends on which one is more salient. Also, traders' game and naked traders' game applies the logics in the prisoner's dilemma to international trade context. Last, the paper shows the expressive impact of the FTAs after they are signed.
Perspective: Behavioural addictions matter.

More research, and dedicated funding, is needed to understand and successfully treat compulsive habits, says Marc Potenza.
Tumour necrosis factor-α-induced loss of intestinal barrier function requires TNFR1 and TNFR2 signalling in a mouse model of total parenteral nutrition

Tumour necrosis factor-α (TNF-α) has been reported to play a central role in intestinal barrier dysfunction in many diseases; however, the precise role of the TNF-α receptors (TNFRs) has not been well defined using in vivo models. Our previous data showed that enteral nutrient deprivation or total parenteral nutrition (TPN) led to a loss of intestinal epithelial barrier function (EBF), with an associated upregulation of TNF-α and TNFR1. In this study, we hypothesized that TNF-α plays an important role in TPN-associated EBF dysfunction. Using a mouse TPN model, we explored the relative roles of TNFR1 vs. TNFR2 in mediating this barrier loss. C57/BL6 mice underwent intravenous cannulation and were given enteral nutrition or TPN for 7 days. Tumour necrosis factor-α receptor knockout (KO) mice, including TNFR1KO, TNFR2KO or TNFR1R2 double KO (DKO), were used. Outcomes included small intestine transepithelial resistance (TER) and tracer permeability, junctional protein zonula occludens-1, occludin, claudins and E-cadherin expression. In order to address the dependence of EBF on TNF-α further, exogenous TNF-α and pharmacological blockade of TNF-α (Etanercept) were also performed. Total parenteral nutrition led to a loss of EBF, and this was almost completely prevented in TNFR1R2DKO mice and partly prevented in TNFR1KO mice but not in TNFR2KO mice. The TPN-associated downregulation of junctional protein expression and junctional assembly was almost completely prevented in the TNFR1R2DKO group. Blockade of TNF-α also prevented dysfunction of the EBF and junctional protein losses in mice undergoing TPN. Administration of TPN upregulated the downstream nuclear factor-B and myosin light-chain kinase (MLCK) signalling, and these changes were almost completely prevented in TNFR1R2DKO mice, as well as with TNF-α blockade, but not in TNFR1KO or TNFR2KO TPN groups. Tumour necrosis factor-α is a critical factor for TPN-associated epithelial barrier dysfunction, and both TNFR1 and TNFR2 are involved in EBF loss. Nuclear factor-B and MLCK signalling appear to be important downstream mediators involved in this TNF-α signalling process.
Self-Injurious Behavior in Intellectual Disabilities, edited by Johannes Rojahn, Stephen R. Schroeder, and Theodore A. Hoch

Self-injurious behavior (SIB) among individuals with intellectual and related developmental disabilities (IDD) is a clinically daunting and scientifically challenging behavior problem with profound...
Regulation of Oleoresinosis in Grand Fir (Abies grandis) (Coordinate Induction of Monoterpene and Diterpene Cyclases and Two Cytochrome P450-Dependent Diterpenoid Hydroxylases by Stem Wounding)

Oleoresin (pitch) is a defensive secretion composed of monoterpene olefins (turpentine) and diterpene resin acids (rosin) that is produced in grand fir (Abies grandis Lindl.) stems in response to wounding. Monoterpene and diterpene biosynthesis are coordinately induced in wounded stems as determined by monitoring the activity of monoterpene and diterpene cyclases, as well as two cytochrome P450-dependent diterpenoid hydroxylases involved in the formation of ([mdash])-abietic acid, the principal resin acid of this species. The activity of these enzymes reaches maximum levels that are 5- to 100-fold higher than those of nowwounded control stems 10 d after wounding and this is followed by a synchronous decline. The increase in biosynthetic activity is consequently followed by the accumulation of a viscous mass of resin acids, with the loss of the volatile monoterpenes, at the site of injury. The observed coordinate induction of monoterpene olefin and abietic acid bio-synthesis and the results of oleoresin analysis are consistent with the role of the volatile monoterpenes as a solvent for the mobilization and deposition of resin acids at the wound site to seal the injury with a rosin barrier after the evaporation of the turpentine. The last step of resin acid biosynthesis is catalyzed by an operationally soluble aldehyde dehydrogenase that is not inducible by wounding but seemingly is expressed constitutively at a high level. In vivo [14C]acetate feeding and resin analysis indicate that this enzyme is not efficiently coupled to the earlier steps of the pathway.
Sensemaking and Entrepreneurship

Sensemaking is an elusive concept. Yet, it holds great promise as a lens through which entrepreneurs' behavior can be better understood. In this article, key aspects of sensemaking including identity, enactment, and plausibility are used to develop important insight. Keywords: entrepreneurs; sensemaking; identity; enactment; plausibility
Impediments to the effective use of ballistics imaging information in criminal investigations: lessons from the use of IBIS in a developing nation

We use a case study approach to explore the facilitators and impediments to effectively using forensics ballistics imaging technology to improve police investigations in a developing country. The study site, Trinidad and Tobago, a nation located in the Caribbean basin, was experiencing a homicide epidemic during the time of this study. The homicide epidemic involved the repeated use of a limited number of firearms, conditions that are ideal for ballistics imaging technology. This nation also possessed a professionalized forensic crime lab and advanced ballistic imaging technology. The analysis reveals that the effective use of ballistics imaging was impeded by inefficient processes and backlogs at the national crime lab, time delays in identifying ballistics hits, and an inefficient system of transmitting hit reports to police investigators. In sum, organizational arrangements in the forensic crime lab and police in the focal country blunted the effectiveness of a proven forensic technology.
Comments on the inverse scattering transform and related nonlinear evolution equations

Page 1 In t roduc t ion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2 Methodology of t he Inverse Sca t te r ing Trans fo rm . . . . . . . . . . . . . . . . . . . . . . 6 3 Scat te r ing Opera to r s . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 4 The Kor t eweg-de Vries equa t ion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 5 Analy t ic problems associa ted wi th t h e n X n s ca t t e r ing p rob lems . . . . . . . . . . . . . . 13 6 Analy t ic problems associated wi th discrete sca t t e r ing problems . . . . . . . . . . . . . . . 16 7 Analy t ic problem for ILW and B O . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 8 Analy t ic problems for mul t id imens iona l sy s t ems . . . . . . . . . . . . . . . . . . . . . . . 21 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
An update on adenomyosis uteri

Abstract Adenomyosis is a gynecological condition commonly encountered in clinical practice. It is defined as the presence of endometrium within the myometrium. The prevalence of this condition in asymptomatic women is unclear, and a large proportion of these women may have associated pathology such as leiomyomas, endometriosis, endometrial polyps, and hyperplasia. Most of the time, diagnosis is made on histological examination of specimen following hysterectomy or adenomyomectomy. We will look at the role of various imaging modalities, such as pelvic ultrasound and magnetic resonance imaging, and their value in improving the accuracy of preoperative diagnosis. Various medical and surgical therapies will also be discussed. Careful counseling on the available treatment options form an important component of clinical care. Hysterectomy is the definitive treatment for women who no longer desire fertility.
Phylogenetics of Chondrichthyes and the problem of rooting phylogenies with distant outgroups

Erroneous estimates of ingroup relationships can be caused by attributes in the outgroup chosen to root the tree. Phylogenetic analyses of DNA sequences frequently yield incorrect estimates of ingroup relationships when the outgroup used to ‘‘root’’ the tree is highly divergent from the ingroup. This is especially the case when the outgroup has a different base composition than the ingroup. Unfortunately, in many instances, alternative less divergent outgroups are not available. In such cases, investigators must either target genes with attributes that minimize the problem (slowly evolving genes with stationary base compositions – which are often not ideal for estimating relationships among the more closely related ingroup taxa) or use inference models that are explicitly tailored to deal with an attenuated historical signal with a superimposed non-stationary base composition. In this paper we explore the problem both empirically and through simulation. For the empirical component we looked at the phylogenetic relationships among elasmobranch fishes (sharks and rays), a group whose closest living outgroup, the holocephalan Ghost fishes, are separated from the elasmobranchs by more than 100 million years of evolution. We compiled a data set for analysis comprising 10 single-copy nuclear protein-coding genes (12096 bp) for representatives of the major lineages within elasmobranchs and holocephalans. For the simulation, we used an evolutionary model on a fixed tree topology to generate DNA sequence data sets which varied both in their distance to the outgroup, and in their base compositional difference between ingroup and outgroup. Results from both the empirical data set and the simulation, support the idea that deviation from base compositional stationarity, in conjunction with distance from the root can act in concert to compromise accuracy of estimated relationships within the ingroup. We tested several approaches to mitigate such problems. We found, that excluding genes with overall faster rates and heterogeneous base compositions, while the least sophisticated of the methods evaluated, seemed to be the most effective.
The short-range mechanism of surface enhanced raman scattering

Abstract In addition to the electromagnetic influences which increase the local field at the surface of suitably rough free-electron-like metals, molecule and site specific electronic resonances are also frequently operative. This leads to enhanced scattering beyond that caused by the electromagnetic mechanism alone. The electronic resonances involve charge-transfer excitation between members of an active complex MwAgxCly(H2O)z which involves the probe molecule M and, in the electrochemical environment, the constituents of the solution. These complexes allow the resonance to be communicated to Raman transitions in all members of the complex. The stability of the complexes are sensitive to changes in the environment, such as the applied voltage and to the presence of foreign metal ions, through induced changes in y, the number of halide or pseudo-halide ions in the complex. Through analysis of the vibrational signature of the probe molecule under various environmental influences we are able to observe subtle changes in the character of the bonding between that molecule and the rest of the complex. These changes can also be interpreted as indirect results of changes in the value of y.
The Spatial Distribution of Extended Red Emission in the Planetary Nebula NGC 7027

Les observations spectroscopiques CCD du continuum optique de la nebuleuse planetaire NGC 7027 sont presentees. La distribution spatiale de la bande d'emission rouge etendue (ERE) attribuee a la photoluminescence des carbones amorphes hydrogenes est analysee. L'intensite moyenne integree de la bande ERE est determine.
Posttranscriptional mechanisms are responsible for accumulation of truncated c-myc RNAs in murine plasma cell tumors.

Abstract c-myc messenger RNAs are known to be extremely unstable (t 12 = 10 min) in normal and tumor cells, suggesting that degradation could play an important role in regulating their steady state level in the cytoplasm. We have investigated the stabilities of c- myc mRNAs in three murine plasmacytomas, where the c- myc gene either remains intact (ABPC20) or exists in a truncated form (MPC-11 and J558L) subsequent to 6;15 or 12;15 chromosome translocations respectively, and in an A-MuLV-induced pre-B lymphoma line (18–81.5) that lacks chromosome translocations and contains both c- myc genes in their normal context. The truncated myc genes in J558L and MPC-11 lack the promoters of the normal gene but are transcribed from cryptic promoters within the first c- myc intron. We found that posttranscriptional processes are largely responsible for the higher steady state accumulations of truncated c- myc transcripts, while broken and intact c- myc genes are transcribed at comparable rates.
Role of tryptophan repeats and flanking amino acids in Myb-DNA interactions.

Abstract The c-myb protooncogene codes for a sequence-specific DNA-binding protein that appears to act as a transcriptional regulator and is highly conserved through evolution. The DNA-binding domain of Myb has been shown to contain three imperfectly conserved repeats of 52 amino acids that constitute the amino-terminal end. Within each repeat, there are three tryptophans that are separated by 18 or 19 amino acids and are flanked by basic amino acids. To determine the role of tryptophans and the flanking basic amino acids in the DNA-binding activity of Myb proteins, we have selectively mutagenized individual tryptophans as well as some of the amino acid residues that flank these tryptophans. Replacement of these tryptophans with glycine, proline, or arginine abolished the DNA-binding activity whereas replacement with other aromatic amino acids or leucine or alanine did not appreciably affect this activity. On the other hand the replacement of two amino acids, asparagine and lysine, that flank the last tryptophan with acidic amino acids completely abolished their DNA-binding activity. These results are consistent with a model we present in which the tryptophans form a hydrophobic scaffold that plays a crucial role in maintaining the helix-turn-helix structure of the DNA binding domain. Basic and polar amino acids adjacent to these tryptophans seem to participate directly in DNA binding.
Inertial sensor based motion trajectory visualization and quantitative quality assessment of hemiparetic gait

The analysis of the biomechanics surrounding human gait has been used by many disciplines, and is especially useful in fields such as neurology, where many diseases are diagnosed clinically through careful observations of a person's movement. In patients afflicted by neurological diseases, hemiparetic gait is common and this abnormal gait causes the state of the art in motion reconstruction to fail. This paper presents two novel contributions to the area. The first is a novel gait trajectory reconstruction and visualization method with a zero velocity detection method targeting hemiparetic gait patterns, enabling reconstruction and visualization of hemiparetic gait in true 3D space. The second is a set of novel quality metrics developed in conjunction with the UCLA Department of Neurology, for evaluating patients suffering from neurological diseases.
Mediation in verbal concept learning

Summary In a study of mediation in verbal concept learning, words that are members of known classes, and words that could not readily be classed with other task words, were each used both as relevant and as irrelevant stimuli. These four conditions were studied in three experiments that varied in the number of relevant and irrelevant words presented. The results were the same, on the whole, in all three experiments, both in terms of trials to learn, and with an error measure assumed to be sensitive to mediation. Among relevant words, class words were more rapidly learned, and showed more evidence of mediation, than nonclass words. Among irrelevant words, there was no difference, as a main effect, between class vs. nonclass words. There was a significant interaction such that when class words were relevant, performance was usually better with nonclass irrelevant words, but when nonclass words were relevant, performance was better with irrelevant class words. It was suggested that there was evidence for mediation of response when class words were positively reinforced, and perhaps for mediation of nonresponse when class words were negatively reinforced.
Assessment of Operative Competency in Otolaryngology Residency: Survey of US Program Directors†

Objectives/Hypothesis: 1) Assess current status of operative competency assessment and feedback among US Otolaryngology residency programs. 2) Evaluate correlations between assessment or feedback tools and remediation. Study Design: Survey of Program Directors. Methods: The survey was sent to 100 Program Directors inquiring about program size, mode of feedback, assessment tools, surgical portfolios, remediation, and number of residents requiring remediation in past 5 years. Associations between assessment questions and remediation (yes or no) were statistically assessed with the χ2 goodness-of-fit test. For more complicated analyses, multiple logistic regression models were created to assess predictors of the binary outcome of radiation. Results: Among 72 respondents, subjective evaluations are used by 95.8% (69 of 72). Formative feedback after cases is used by 38.9% (28 of 72). Summative feedback at end of the rotation is done by 57.0% (41 of 72). Objective Structured Assessments of Technical Skills is used by 15.3% (11 of 72) of programs, most are large on the basis of number of residents or faculty or both. Operative portfolios are kept by 48.6% (35 of 72) of programs. The percentage of programs with mechanisms for remediation is 41.7% (30 of 72). Similarly, of the programs who responded to the remediation question, the percentage with at least one resident requiring remediation is 37.5%. Programs who report at least one resident remediation are statistically more likely to have a remediation mechanism in place (75% vs. 27.5%; P <.001). There is also a statistically significant association with formative feedback and having resident remediation (58.3% vs. 30%; P = .025). Conclusions: Standardized surgical curricula and assessment tools are needed. Programs with more intensive evaluation or remediation mechanisms are statistically more likely to report residents requiring remediation. This may reflect their ability to better identify the struggling resident. Alternatively, having a resident requiring remediation may be the catalyst that initiates the need for more intensive evaluation tools and remediation mechanisms. The Accreditation Council for Graduate Medical Education's and society will demand that we produce competent surgeons. Therefore, all Otolaryngology training programs should be developing and implementing formal surgical assessment tools, methods to identify residents requiring remediation, and remediation mechanisms.
Electronic model of synaptic transmission

This paper covers the design and testing of a circuit to emulate synaptic transmission in electronic circuits. It briefly explains the mathematical models of synaptic behavior, and then delves into the structure and performance of the electronic model.