cssi/SciSciGPT-SciSciNet huggingface dataset:
Vibrio cholerae Motility in Aquatic and Mucus-Mimicking Environments.

Cholera disease is caused by Vibrio cholerae infecting the lining of the small intestine and results in severe diarrhea. V. cholerae’s swimming motility is known to play a crucial role in pathogenicity and may aid the bacteria in crossing the intestinal mucus barrier to reach sites of infection, but the exact mechanisms are unknown. The cell can be either pushed or pulled by its single polar flagellum, but there is no consensus on the resulting repertoire of motility behaviors. We use high-throughput three-dimensional (3D) bacterial tracking to observe V. cholerae swimming in buffer, in viscous solutions of the synthetic polymer PVP, and in mucin solutions that may mimic the host environment. We perform a statistical characterization of its motility behavior on the basis of large 3D trajectory data sets. We find that V. cholerae performs asymmetric run-reverse-flick motility, consisting of a sequence of a forward run, reversal, and a shorter backward run, followed by a turn by approximately 90°, called a flick, preceding the next forward run. Unlike many run-reverse-flick swimmers, V. cholerae’s backward runs are much shorter than its forward runs, resulting in an increased effective diffusivity. We also find that the swimming speed is not constant but subject to frequent decreases. The turning frequency in mucin matches that observed in buffer. Run-reverse-flick motility and speed fluctuations are present in all environments studied, suggesting that these behaviors also occur in natural aquatic habitats as well as the host environment. IMPORTANCE Cholera disease produces vomiting and severe diarrhea and causes approximately 100,000 deaths per year worldwide. The disease is caused by the bacterium Vibrio cholerae colonizing the lining of the small intestine. V. cholerae’s ability to swim is known to increase its infectivity, but the underlying mechanisms are not known. One possibility is that swimming aids in crossing the protective mucus barrier that covers the lining of the small intestine. Our work characterizing how V. cholerae swims in environments that mimic properties of the host environment may advance the understanding of how motility contributes to infection.
Supervised tensor decomposition with features on multiple modes

Higher-order tensors have received increased attention across science and engineering. While most tensor decomposition methods are developed for a single tensor observation, scientific studies ofte...
Configurations of noncollinear points in the projective plane

We consider the space Fn of configurations of n points in ℙ2 satisfying the condition that no three of the points lie on a line. For n=4,5,6, we compute H∗(Fn;ℚ) as an 𝔖n–representation. The cases n=5,6 are computed via the Grothendieck–Lefschetz trace formula in etale cohomology and certain “twisted” point counts for analogous spaces over 𝔽q.
Killing Globally, Punishing Locally?: The Still-Unmapped Ecology of Atrocity

This article reviews Mark A. Drumbl's Atrocity, Punishment and International Law (Cambridge 2007), which is critical of the international criminal law (ICL) paradigm and proposes alternatives to more realistically account for the collective and social aspects of mass violence. Drumbl’s core intuition — that the ICL paradigm fails, and by its nature will fail, to address much of the complexity of great evil, while also driving out local variation responsive to the interests and needs of affected communities — is surely right, and his conclusion — that it is time to move beyond the protectively encomiastic Pollyannism of the early ICL project and begin to ask searching questions about costs, benefits, failings, and improvement — is right as well. So the intuitions and the conclusions are right; the framework in between — and the implications beyond — are places of complexity, contestation, and, inevitably, speculation.This review develops around a theme which, though a minor note in Drumbl's book, is one that might productively be brought to the fore, because it complements the argument: the idea of an ecology of atrocity and punishment. The rationales for diverse responses to atrocity lie in claims about local, particular instantiations of highly general universal norms in ways that are sensitive to context, culture, history, politics, and values. The language of environmentalism and biodiversity or of human and cultural geography might ground and describe the rationales of complexity, diversity, and underlying commonality that Drumbl locates in cosmopolitan pluralism: genetically related, but speciated, specialized, inter-related but suited to the niches in which they dwell. And so although the tropes and frameworks of these disciplines are not the structure Drumbl has chosen, he has — as with his principal themes — indicated a direction in which things might evolve: an ecological perspective with the still-unfinished project of mapping that implies.
Interpretable Sparse Proximate Factors for Large Dimensions

This article proposes sparse and easy-to-interpret proximate factors to approximate statistical latent factors. Latent factors in a large-dimensional factor model can be estimated by principal comp...
Small cardinals and small Efimov spaces

Abstract We introduce and analyze a new cardinal characteristic of the continuum, the splitting number of the reals, denoted s ( R ) . This number is connected to Efimov's problem, which asks whether every infinite compact Hausdorff space must contain either a non-trivial convergent sequence, or else a copy of β N .
The Possible Weakening of Financial Accounting from Tax Reforms

There are past and proposed tax law changes that contain provisions that affect financial reporting. These include calls for book-tax conformity, proposals to increase the links between financial accounting and taxable incomes, and actions by Congress that make direct alterations to U.S. GAAP. I submit that these tax law changes potentially threaten financial reporting quality. I discuss my concerns about why such provisions have not attracted attention from accountants to the extent they should and make a case for more awareness and more research going forward.
LayoutReader: Pre-training of Text and Layout for Reading Order Detection

Reading order detection is the cornerstone to understanding visually-rich documents (e.g., receipts and forms). Unfortunately, no existing work took advantage of advanced deep learning models because it is too laborious to annotate a large enough dataset. We observe that the reading order of WORD documents is embedded in their XML metadata; meanwhile, it is easy to convert WORD documents to PDFs or images. Therefore, in an automated manner, we construct ReadingBank, a benchmark dataset that contains reading order, text, and layout information for 500,000 document images covering a wide spectrum of document types. This first-ever large-scale dataset unleashes the power of deep neural networks for reading order detection. Specifically, our proposed LayoutReader captures the text and layout information for reading order prediction using the seq2seq model. It performs almost perfectly in reading order detection and significantly improves both open-source and commercial OCR engines in ordering text lines in their results in our experiments. The dataset and models are publicly available at https://aka.ms/layoutreader.
Systematic evaluation of chromosome conformation capture assays.

Chromosome conformation capture (3C) assays are used to map chromatin interactions genome-wide. Chromatin interaction maps provide insights into the spatial organization of chromosomes and the mechanisms by which they fold. Hi-C and Micro-C are widely used 3C protocols that differ in key experimental parameters including cross-linking chemistry and chromatin fragmentation strategy. To understand how the choice of experimental protocol determines the ability to detect and quantify aspects of chromosome folding we have performed a systematic evaluation of 3C experimental parameters. We identified optimal protocol variants for either loop or compartment detection, optimizing fragment size and cross-linking chemistry. We used this knowledge to develop a greatly improved Hi-C protocol (Hi-C 3.0) that can detect both loops and compartments relatively effectively. In addition to providing benchmarked protocols, this work produced ultra-deep chromatin interaction maps using Micro-C, conventional Hi-C and Hi-C 3.0 for key cell lines used by the 4D Nucleome project. This analysis systematically evaluates cross-linking chemistry and chromatin fragmentation strategies commonly used in 3C assays and introduces an improved Hi-C protocol for detecting loops and compartments.
On the large charge sector in the critical O(N) model at large N

We study operators in the rank-j totally symmetric representation of O(N) in the critical O(N) model in arbitrary dimension d, in the limit of large N and large charge j with j/N ≡ $$ \hat{j} $$ fixed. The scaling dimensions of the operators in this limit may be obtained by a semiclassical saddle point calculation. Using the standard Hubbard-Stratonovich description of the critical O(N) model at large N, we solve the relevant saddle point equation and determine the scaling dimensions as a function of d and $$ \hat{j} $$ , finding agreement with all existing results in various limits. In 4 < d < 6, we observe that the scaling dimension of the large charge operators becomes complex above a critical value of the ratio j/N, signaling an instability of the theory in that range of d. Finally, we also derive results for the correlation functions involving two “heavy” and one or two “light” operators. In particular, we determine the form of the “heavy-heavy-light” OPE coefficients as a function of the charges and d.
Reducing interaural tonotopic mismatch preserves binaural unmasking in cochlear implant simulations of single-sided deafness.

Binaural unmasking, a key feature of normal binaural hearing, can refer to the improved intelligibility of masked speech by adding masking that facilitates perceived separation of target and masker. A question relevant for cochlear implant users with single-sided deafness (SSD-CI) is whether binaural unmasking can still be achieved if the additional masking is spectrally degraded and shifted. CIs restore some aspects of binaural hearing to these listeners, although binaural unmasking remains limited. Notably, these listeners may experience a mismatch between the frequency information perceived through the CI and that perceived by their normal hearing ear. Employing acoustic simulations of SSD-CI with normal hearing listeners, the present study confirms a previous simulation study that binaural unmasking is severely limited when interaural frequency mismatch between the input frequency range and simulated place of stimulation exceeds 1–2 mm. The present study also shows that binaural unmasking is largely retained when the input frequency range is adjusted to match simulated place of stimulation, even at the expense of removing low-frequency information. This result bears implications for the mechanisms driving the type of binaural unmasking of the present study and for mapping the frequency range of the CI speech processor in SSD-CI users.
Monochromatic combinatorial lines of length three

We show that there is a constant $c$ such that any colouring of the cube $[3]^n$ in $c \log \log n$ colours contains a monochromatic combinatorial line.
Exploiting BERT for Multimodal Target Sentiment Classification through Input Space Translation

Multimodal target/aspect sentiment classification combines multimodal sentiment analysis and aspect/target sentiment classification. The goal of the task is to combine vision and language to understand the sentiment towards a target entity in a sentence. Twitter is an ideal setting for the task because it is inherently multimodal, highly emotional, and affects real world events. However, multimodal tweets are short and accompanied by complex, possibly irrelevant images. We introduce a two-stream model that translates images in input space using an object-aware transformer followed by a single-pass non-autoregressive text generation approach. We then leverage the translation to construct an auxiliary sentence that provides multimodal information to a language model. Our approach increases the amount of text available to the language model and distills the object-level information in complex images. We achieve state-of-the-art performance on two multimodal Twitter datasets without modifying the internals of the language model to accept multimodal data, demonstrating the effectiveness of our translation. In addition, we explain a failure mode of a popular approach for aspect sentiment analysis when applied to tweets. Our code is available at https://github.com/codezakh/exploiting-BERT-thru-translation.
Geometric structures related to the braided Thompson groups

In previous work, joint with Bux, Fluch, Marschler and Witzel, we proved that the braided Thompson groups are of type $${{\,\mathrm{F}\,}}_\infty $$ . The proof utilized certain contractible cube complexes, which in this paper we prove are $${{\,\mathrm{CAT}\,}}(0)$$ . We then use this fact to compute the geometric invariants $$\Sigma ^m(F_{{\text {br}}})$$ of the pure braided Thompson group $$F_{{\text {br}}}$$ . Only the first invariant $$\Sigma ^1(F_{{\text {br}}})$$ was previously known. A consequence of our computation is that as soon as a subgroup of $$F_{{\text {br}}}$$ containing the commutator subgroup $$[F_{{\text {br}}},F_{{\text {br}}}]$$ is finitely presented, it is automatically of type $${{\,\mathrm{F}\,}}_\infty $$ .
Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency

Twitter uses machine learning to crop images, where crops are centered around the part predicted to be the most salient. In fall 2020, Twitter users raised concerns that the automated image cropping system on Twitter favored light-skinned over dark-skinned individuals, as well as concerns that the system favored cropping woman's bodies instead of their heads. In order to address these concerns, we conduct an extensive analysis using formalized group fairness metrics. We find systematic disparities in cropping and identify contributing factors, including the fact that the cropping based on the single most salient point can amplify the disparities because of an effect we term argmax bias. However, we demonstrate that formalized fairness metrics and quantitative analysis on their own are insufficient for capturing the risk of representational harm in automatic cropping. We suggest the removal of saliency-based cropping in favor of a solution that better preserves user agency. For developing a new solution that sufficiently address concerns related to representational harm, our critique motivates a combination of quantitative and qualitative methods that include human-centered design.
Genetically Encoded CRISPR Components Yield Efficient Gene Editing in the Invasive Pest Drosophila suzukii.

Originally from Asia, Drosophila suzukii Matsumura is a global pest of economically important soft-skinned fruits. Also commonly known as spotted wing drosophila, it is largely controlled through r...
Identifying the Roles of Accounting Accruals in Corporate Financial Reporting

Research in corporate financial reporting identifies two important roles of accounting accruals. First, accruals smooth fluctuations in operating cash flows. Second, accruals allow recognition of l...
HaPPY-Mine: Designing a Mining Reward Function.

In cryptocurrencies, the block reward is meant to serve as the incentive mechanism for miners to commit resources to create blocks and in effect secure the system. Existing systems primarily divide the reward in proportion to expended resources and follow one of two static models for total block reward: (i) a fixed reward for each block (e.g., Ethereum), or (ii) one where the block reward halves every set number of blocks (e.g., the Bitcoin model of halving roughly every 4 years) but otherwise remains fixed between halvings. In recent work, a game-theoretic analysis of the static model under asymmetric miner costs showed that an equilibrium always exists and is unique [4]. Their analysis also reveals how asymmetric costs can lead to large-scale centralization in blockchain mining, a phenomenon that has been observed in Bitcoin and Ethereum and highlighted by other studies including [11, 16].
New Experimental Methods to Study Proppant Embedment in Shales

Productivity in fractured wells typically declines when severe proppant embedment shrinks the fracture aperture and creates conductivity clogging fines. However, the mechanisms linking embedment to decline are poorly characterized. In the absence of this understanding, very few models take proppant embedment into account when predicting production decline. We developed new experimental techniques to characterize proppant embedment mechanisms and properties and combined these results with analytical analysis to quantify stress-dependent elastic and plastic deformation, as well as time-dependent creep deformation. We developed two novel experimental setups to tease apart the elastic, plastic, and creep deformation curves. A constant displacement vs. measured load embedment test generated the elastic and plastic data, and the constant load vs. measured displacement embedment test generated creep data. Results show that plastic and creep deformation dominated proppant embedment in shale, while the elastic deformation component is insignificant.
Extreme Scale Survey Simulation with Python Workflows

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will soon carry out an unprecedented wide, fast, and deep survey of the sky in multiple optical bands. The data from LSST will open up a new discovery space in astronomy and cosmology, simultaneously providing clues toward addressing burning issues of the day, such as the origin of dark energy and and the nature of dark matter, while at the same time yielding data that will, in turn, pose fresh new questions. To prepare for the imminent arrival of this remarkable data set, it is crucial that the associated scientific communities be able to develop the software needed to analyze it. Computational power now available allows us to generate synthetic data sets that can be used as a realistic training ground for such an effort. This effort raises its own challenges—the need to generate very large simulations of the night sky, scaling up simulation campaigns to large numbers of compute nodes across multiple computing centers with different architectures, and optimizing the complex workload around memory requirements and widely varying wall clock times. We describe here a large-scale workflow that melds together Python code to steer the workflow, Parsl to manage the large-scale distributed execution of workflow components, and containers to carry out the image simulation campaign across multiple sites. Taking advantage of these tools, we developed an extreme-scale computational framework and used it to simulate five years of observations for 300 square degrees of sky area. We describe our experiences and lessons learned in developing this workflow capability, and highlight how the scalability and portability of our approach enabled us to efficiently execute it on up to 4000 compute nodes on two supercomputers.
#StayHome or #Marathon?: Social Media Enhanced Pandemic Surveillance on Spatial-temporal Dynamic Graphs

COVID-19 has caused lasting damage to almost every domain in public health, society, and economy. To monitor the pandemic trend, existing studies rely on the aggregation of traditional statistical models and epidemic spread theory. In other words, historical statistics of COVID-19, as well as the population mobility data, become the essential knowledge for monitoring the pandemic trend. However, these solutions can barely provide precise prediction and satisfactory explanations on the long-term disease surveillance while the ubiquitous social media resources can be the key enabler for solving this problem. For example, serious discussions may occur on social media before and after some breaking events take place. To take advantage of the social media data, we propose a novel framework, Social Media enhAnced pandemic suRveillance Technique (SMART), which is composed of two modules: (i) information extraction module to construct heterogeneous knowledge graphs based on the extracted events and relationships among them; (ii) time series prediction module to provide both short-term and long-term forecasts of the confirmed cases and fatality at the state-level in the United States and to discover risk factors for COVID-19 interventions. Extensive experiments show that our method largely outperforms the state-of-the-art baselines by 7.3% and 7.4% in confirmed case/fatality prediction, respectively.
The effects of vacant lot greening and the impact of land use and business presence on crime

We examine the effect of the Philadelphia LandCare vacant lot greening initiative on crime and the extent to which surrounding land uses and business types moderate this intervention. We rely on a ...
High-girth near-Ramanujan graphs with localized eigenvectors

We show that for every prime d and α ∈ (0, 1/6), there is an infinite sequence of (d + 1)-regular graphs G = (V, E) with high girth Ω(α logd(∣V∣), second adjacency matrix eigenvalue bounded by $$(3/\sqrt 2)\sqrt d $$ , and many eigenvectors fully localized on small sets of size O(mα). This strengthens the results of [GS18], who constructed high girth (but not expanding) graphs with similar properties, and may be viewed as a discrete analogue of the “scarring” phenomenon observed in the study of quantum ergodicity on manifolds. Key ingredients in the proof are a technique of Kahale [Kah92] for bounding the growth rate of eigenfunctions of graphs, discovered in the context of vertex expansion and a method of Erdős and Sachs for constructing high girth regular graphs.
A Photographic Insight Into the Motion of Liquid-Vapor Interface During Rapid Evaporation of a Liquid Droplet on a Heated Surface

Photographic observations of the boiling phenomena have played an important role in gaining insight into the boiling mechanism. This paper presents a brief historical review of the available literature on the photographic studies in pool and flow boiling. This is followed by the results of the photographic studies conducted in the author’s laboratory on liquid droplets impinging on a heated surface. Liquid-vapor interface and contact line movements are observed through a high speed camera at high resolution. The effect of surface roughness an surface temperature on dynamic advancing and receding contact angles has been studied. Also, the effect of rapid evaporation on advancing and receding contact angles, liquid-vapor interface motion, and dryout front propagation have been investigated.
What Helps Transformers Recognize Conversational Structure? Importance of Context, Punctuation, and Labels in Dialog Act Recognition

Dialog acts can be interpreted as the atomic units of a conversation, more fine-grained than utterances, characterized by a specific communicative function. The ability to structure a conversational transcript as a sequence of dialog acts -- dialog act recognition, including the segmentation -- is critical for understanding dialog. We apply two pre-trained transformer models, XLNet and Longformer, to this task in English and achieve strong results on Switchboard Dialog Act and Meeting Recorder Dialog Act corpora with dialog act segmentation error rates (DSER) of 8.4% and 14.2%. To understand the key factors affecting dialog act recognition, we perform a comparative analysis of models trained under different conditions. We find that the inclusion of a broader conversational context helps disambiguate many dialog act classes, especially those infrequent in the training data. The presence of punctuation in the transcripts has a massive effect on the models' performance, and a detailed analysis reveals specific segmentation patterns observed in its absence. Finally, we find that the label set specificity does not affect dialog act segmentation performance. These findings have significant practical implications for spoken language understanding applications that depend heavily on a good-quality segmentation being available.
Modeling the effect of the vaccination campaign on the Covid-19 pandemic.

Population-wide vaccination is critical for containing the SARS-CoV-2 (Covid-19) pandemic when combined with restrictive and prevention measures. In this study we introduce SAIVR, a mathematical model able to forecast the Covid-19 epidemic evolution during the vaccination campaign. SAIVR extends the widely used Susceptible-Infectious-Removed (SIR) model by considering the Asymptomatic (A) and Vaccinated (V) compartments. The model contains several parameters and initial conditions that are estimated by employing a semi-supervised machine learning procedure. After training an unsupervised neural network to solve the SAIVR differential equations, a supervised framework then estimates the optimal conditions and parameters that best fit recent infectious curves of 27 countries. Instructed by these results, we performed an extensive study on the temporal evolution of the pandemic under varying values of roll-out daily rates, vaccine efficacy, and a broad range of societal vaccine hesitancy/denial levels. The concept of herd immunity is questioned by studying future scenarios which involve different vaccination efforts and more infectious Covid-19 variants.
Online Continual Learning for Visual Food Classification

Food image classification is challenging for real-world applications since existing methods require static datasets for training and are not capable of learning from sequentially available new food images. Online continual learning aims to learn new classes from data stream by using each new data only once without forgetting the previously learned knowledge. However, none of the existing works target food image analysis, which is more difficult to learn incrementally due to its high intra-class variation with the unbalanced and unpredictable characteristics of future food class distribution. In this paper, we address these issues by introducing (1) a novel clustering based exemplar selection algorithm to store the most representative data belonging to each learned food for knowledge replay, and (2) an effective online learning regime using balanced training batch along with the knowledge distillation on augmented exemplars to maintain the model performance on all learned classes. Our method is evaluated on a challenging large scale food image database, Food-1K, by varying the number of newly added food classes. Our results show significant improvements compared with existing state-of-the-art online continual learning methods, showing great potential to achieve lifelong learning for food image classification in real world.
Validation of Hemostasis Assays, Analyzers, and Reagents

A key responsibility of the laboratory director is to assure that information and services provided by the laboratory meet the needs of its users and conform to established regulations and standards even before clinical specimens are tested and results are generated for patient care. The process of providing this assurance is commonly referred to as validation.
Critical Incident Technique in the Basket

Abstract Different IS research methods focus on or measure different aspects of IS phenomena, and studies based on various me thodologies thus contribute to the accumulation of strong evidence to support IS theories. We conducted a systematic and reproducible review of ten years of Critical Incident Technique (“CIT”) papers published in the IS Scholars Basket of eight journals. CIT is used extensively in industrial and organizational psychology, marketing and other business disciplines. In IS Basket journals 13 papers fully or partially applied CIT as a research method. We classified these studies per three key elements - incident elicitation, selection, and analysis—and seven criteria employed in other disciplines’ CIT studies. We found that few studies used “full” CIT and we conclude that CIT is underutilized as a research method in IS. Our paper contributes by offering CIT guidelines for authors and reviewers and suggestions for using CIT to build stronger theory in several IS sub-disciplines.
Procalcitonin for prediction of chorioamnionitis in preterm premature rupture of membranes.

Objective: To assess serum procalcitonin (PCT), a marker of monocyte activity, in predicting chorioamnionitis in preterm premature rupture of membranes (PPROM).Methods: Prospective cohort study in ...
Development of Central Neurotransmitter Systems

Inter-neuronal communication is mediated primarily by chemical neurotransmitters, which are released from the nerve terminal, diffuse across the synaptic cleft and interact with specific receptors on adjacent neurons. The development of the biochemical machinery for neurotransmission is closely linked to the functional maturation of the brain's neuronal circuitry. Components essential for neurotransmission (e.g., synthetic enzymes, endogenous neurotransmitters, re-uptake processes and receptors) serve as specific biochemical markers for neuronal systems. The appearance of and developmental increases in these markers during fetal and postnatal life occur with the cessation of neuronal replication and initiation of neuropil elaboration. Discrete groups of neurotransmitter-specific neurons develop according to different timetables, resulting in a shifting pattern of their relative influence in the maturing brain. Human and animal studies demonstrate an early innervation of the neocortex by catecholaminergic axons while neurons using gamma-aminobutyric acid (GABA) mature somewhat later; and the ontogeny of the acetylcholine neurons lags behind both of these. Within each neuronal group the individual biochemical components for neurotransmission also follow differing time courses of maturation. Animal studies, in which cortical neurons were ablated by administering a toxin to the fetus, illustrate the interplay between intrinsic programmes and environmental influences in the assembly of neuronal circuits. The brain's preparation for independent life is characterized by a continual reorganization of neurotransmitter pathways.
Advances in Solution Culture Methods for Plant Mineral Nutrition Research

Publisher Summary This chapter reviews some of the advances in solution culture methodology for plant mineral nutrition research. It focuses primarily on methodological advancements for the specific study of mineral nutrition, but recognizes that the methods may be useful for other types of physiological research as well. The methods are described for overcoming one of the most fundamental limitations of traditional solution culture, the absence of chemical “buffering” of nutrient concentrations. In soils, the soil solution is depleted of nutrients by plant uptake, but continuously replenished via chemical and biological reactions of the solid phase. The uses of flowing solution cultures are discussed in detail. The chapter provides an overview of methods wherein nutrients are continuously or intermittently added in proportion to plant growth. For convenience, abbreviations and chemical names for the chelating agents and pH buffers discussed throughout this paper are summarized.
Behavioral SDF and the Sentiment Premium

This chapter illustrates how sentiment is manifest within asset prices through the stochastic discount factor (SDF). The main result is a decomposition theorem for the log-SDF. The theorem states that the log-SDF is the sum of a fundamental component and sentiment. If sentiment is small relative to the fundamental component, then investor errors exert a minor effect on asset prices. If sentiment is large relative to the fundamental component, then investor errors exert a major effect on asset prices. It presents two central decomposition results. The first result is that the log-SDF can be expressed as the sum of a fundamental component and sentiment. The second result is that the expected excess return (or risk premium) on any security can be expressed as the sum of a fundamental premium corresponding to efficient prices and a sentiment premium to reflect sentiment-based risk. When prices are efficient, sentiment is zero and the sentiment premium is zero. In this case the SDF is only equal to a fundamental premium, and the risk premium only reflects fundamental risk. In the long term, an investor's survival is determined by a survival index that combines his or her time discount factor and the entropy of his or her beliefs. However, investors who violate Bayes rule and do not learn quickly enough will typically vanish in the long run.
Digital Control Using Digital Signal Processing

1. Introduction to Digital Control Using Digital Signal Processing. Background. Digital Control versus Analog Control. Classical Control versus Modern Control. Design Process Overview. Role of DSPs in Control System Designs. CAE Tools. Summary. 2. Mathematical Methods of Discrete Systems. Introduction. Difference Equations. Unit Pulse Response and Discrete Convolution. The z-Transform. Discrete System Transfer Function. Frequency Response. Relationship Between the s and z Domains. Summary. Problems. 3. Analysis of Discrete Systems. Introduction. Sampled-Data Systems. State-Variable Methods. Nonlinear Discrete Systems. Stability Analysis. Sensitivity Analysis. Summary. Problems. 4. Design of Digital Control Systems. Introduction. Control System Design Parameters. Conventional Design Tools. Compensation. Summary. Problems. 5. DSPs in Control Systems. Introduction. Fundamentals of Digital Signal Processing. Single-Chip DSPs. Applications of DSPs in Control Systems. Summary. Problem. 6. Modern Design Techniques and Their Applications. Introduction. Controllability and Pole-Placement. Observability and State Estimation. Linear Quadratic Optimal Design. Fuzzy Logic Control. Summary. Problems. Appendix A. The MATRIXx and MATLAB Design and Analysis Software. MATRIXx. MATLAB. Appendix B. DSPACE. DSP-CITpro/eco Products from dSPACE. Appendix C. Tables of Transforms. Table of z-Transforms. Table of Laplace Transforms. Appendix D. Partial-Fraction Expansion Method. Appendix E. Matrix Analysis. Appendix F. Motion Controller Boards. PMAC-STD 32. STD/DSP Series. Appendix G. Sample DSP Programs. Assembly Code for the Torque Loop of Example 5.1. DSP16 Code for the Adaptive Servo Controller of Example 5.3. Appendix H. Computer Architecture. Index.
MUTATION TO NEOSTIGMINE RESISTANCE IN A CHOLINESTERASE-CONTAINING PSEUDOMONAS

Abstract Searle, Barbara W. (Stanford University School of Medicine, Palo Alto, Calif.) and Avram Goldstein. Mutation to neostigmine resistance in a cholinesterase-containing Pseudomonas. J. Bacteriol. 83:789–796. 1962.—In a strain of Pseudomonas fluorescens containing an inducible cholinesterase, the activity of that enzyme is rate-limiting for growth when acetyl-choline is the sole source of carbon or nitrogen. Under these circumstances, neostigmine, a cholinesterase inhibitor, becomes a growth inhibitor. A neostigmine-resistant mutant was isolated, and the properties of its cholinesterase were compared with those of the wild-type enzyme. There were no differences in penetration of cells by inhibitor, rate of enzyme-inhibitor combination, affinity of inhibitor or substrate for the cholinesterase, or protective effect of substrate upon the enzyme. However, the mutant consistently formed cholinesterase at about twice the wild-type rate. Mutation, in this case, appears to result in a specific change in the differential rate of enzyme biosynthesis. The relationship of this change to neostigmine resistance is discussed, and it is suggested that the effect observed here may be prototypic of a general type of mechanism responsible for acquired drug resistance.
Population genetic variation, geographic structure, and multiple origins of autopolyploidy in Galax urceolata

Premise of the study Whereas population genetic studies have examined allopolyploids, comparable studies of naturally occurring autopolyploids remain rare. To address fundamental questions regarding autopolyploidy, we undertook a detailed population genetic study of one of the classic examples of autopolyploidy, Galax urceolata (Diapensiaceae), which comprises diploid, triploid, and autotetraploid cytotypes. Galax is endemic to the Appalachian Mountains, the adjacent piedmont, sandhills, and coastal plain and represents perhaps the most widely known example of autopolyploidy in nature. Methods Flow cytometry was used to diagnose ploidal level of ∼1000 individuals across 71 populations. We used 10 microsatellite markers to examine genetic variation across the geographic range of Galax and assessed multiple origins though comparisons of diploid, triploid, and tetraploid accessions using multiple analytical approaches. Key results Tetraploids had higher levels of heterozygosity than diploids did. Genetic variation in diploid and tetraploid Galax is geographically structured among the ecoregions of the southeastern United States. Autotetraploidy in Galax urceolata has occurred independently at least 46 times, with triploidy having occurred a minimum of 31 times. Conclusions Genetic differentiation among ecoregions suggests historical patterns of local adaptation. The numerous independent origins of tetraploid Galax reported here are among the highest frequencies of independent polyploidizations ever reported for any polyploid (auto- or allopolyploid).
Undergraduate electromagnetics: a new paradigm

The traditional use of differential and integral vector calculus as the basis for undergraduate electromagnetic courses is reconsidered. A compelling case is made for improved student understanding by basing introductory electromagnetics on two mutually supporting principles-spatial discretization and numeric formulation. Dividing space into discrete cells facilitates casting the laws of electromagnetics in terms of lumped element circuit theory. The vector nature of fields evolves naturally from the behavior of these discrete circuit elements. Numeric formulations for discretized space similar to those used by electromagnetic professionals take the form of remarkably simple models and algorithms. Powerful computer engines and graphics operate on these formulations to solve "real world" applications and bring the physical concepts to life. This "work in progress" is presented to stimulate audience comments and discussion.
23Na chemical-shift imaging

The maintenance of a sodium gradient across the plasma membrane is of crucial importance to living systems. Short-term changes in the sodium gradient are essential to nerve impulse transmission and cell excitability, while long-term changes in the gradient occur as the cells’ high-energy phosphate metabolites become depleted and/ or cell death occurs. The study of sodium and sodium gradients in biological systems is thus critical for an understanding of their physiology. Over the past few years advances in 23Na NMR spectroscopy have made it an increasingly useful tool for the study of sodium in biological tissue. In particular, the development of paramagnetic shift reagents for cations has provided the means to distinguish intracellular and extracellular sodium pools and to track the breakdown of the sodium gradient as a function of ischemia or cell death (1-8). The success of spectroscopic studies using cationic shift reagents to differentiate intraand extracellular sodium pools and track changes in the sodium gradient on a global basis in vivo has led us to develop a chemical-shift-imaging technique for sodium so that spectroscopic information may be obtained on a regional basis. Although common for ‘H imaging studies, CSI experiments for 23Na have not been performed previously due to the difficulties created by the extremely short relaxation times and low concentrations of sodium in vivo. A recent preliminary report describes microimaging experiments using the shift reagent dysprosium tripolyphosphate (9). Using frequency-selective RF pulses to excite the well-resolved resonances of shifted and unshifted sodium, two images of the different sodium pools were sequentially produced. This technique depends upon the complete resolution of the sodium resonances, rarely obtainable with shift reagents other than the toxic tripolyphosphate, and requires separate experiments for each sodium species. We have developed CSI techniques for sodium to be used in conjunction with nontoxic paramagnetic shift reagents such as DyTTHA3-. These experiments allow the simultaneous generation of separate images of the intracellular and extracellular sodium pools, and therefore the direct monitoring of the distribution of sodium on a regional basis. The technique does not require complete resolution of the shifted and unshifted sodium species
Protein Folding and Recognition in the Cell -- an in Silico Approach

I will review the approach of coarse-grained molecular simulations for the investigation of protein folding and protein-protein interactions in a cellular environment, particularly the one for the research from my group. We used a low-resolution model for the representation of proteins and macromolecules that mimic a jam-packed space inside a cell. We made these low-resolution models act like “a real thing” by keeping the physics in its dynamics and the principle of chemical interactions between macromolecules in the simulations. With this approach, we were able to characterize the mechanism of protein folding and protein-protein interactions that involve structurally large rearrangement in the presence of dominant forces inside a cell, such as the volume exclusion from the macromolecular crowding effect and the ionic strength. Based on simple ideas for modeling a large system, I will report several new discoveries and testable predictions from our computational studies.
Enterohepatic cycling of 3H-estrone in the bull: Identification of estrone-3-glucuronide

Abstract Following surgical preparation of a bull with indwelling catheters in the gallbladder and duodenum, the animal was injected with radio-estrone. Bile was collected. Subsequently, this bile containing radioactive metabolites, all of which appeared to be conjugated with glucuronic acid, was infused into the duodenum. In another similar experiment, pure radio-esterone was added to otherwise non-radioactive bile and infused into the duodenum. Urine and newly formed bile was collected during and following the two infusions. In each case the bile collected post-absorption was radioactive, and it contained only conjugated metabolites. These were distributed into three peaks of radioactivity which appeared at about 30, 180 and 330min after infusion. Analysis of the bile collected post-absorption revealed that there were two major metabolites, estrone and 17α-estradiol. Biliary metabolites were purified and separated by column and paper chromatography. Using color reactions, chromatography, enzymatic hydrolysis, formation of derivatives, crystallization to constant S.A. and U.V. and I.R. spectra, estrone conjugates was identified as estrone-3-glucuronide. 17α-estradiol was in the form of a mono-glucuronide and a diglucuronide similar to biliary metabolites of 17β-estradiol. The ratio of radioactivity excreted in bile to that excreted in urine was 2:5 after the infusion of the conjugated metabolites of estrone and 1.2:1 after the infusion of pure estrone. It is clear that in this animal enterohepatic cycling of estrogens took place, but the physiological role and the biochemical components to the process remain to be elucidated.
Experiential constraints on the development of tolerance to amphetamine hypophagia following sensitization of stereotypy: instrumental contingencies regulate the expression of sensitization

In previous research, sensitization of stereotypy induced by injections of 2.5 mg/kg amphetamine did not interfere with subsequent tolerance development to the hypophagic effect of 2 mg/kg. This study examined the effect of a higher sensitizing dose. Rats given intermittent injections of 5 mg/kg amphetamine and then challenged with various doses of amphetamine showed focused head scanning at 2 mg/kg and oral stereotypy at 4 mg/kg. In contrast, saline controls showed diffuse sniffing and head scanning at 2 and 4 mg/kg. Subgroups from each condition were then given daily injections of either amphetamine (2 mg/kg) or saline and access to milk for 30 min. Dose-response tests revealed that both drugged groups learned to suppress stereotypy in order to feed at 2 mg/kg, but only the non-sensitized group could do so at 4 mg/kg. These results demonstrate that (1) rats learn to suppress only those stereotyped movements that they experience in the context of feeding and (2) instrumental contingencies can influence the expression of behavioral sensitization.
Sequential extrusion-microwave pretreatment of switchgrass and big bluestem.

Abstract Developing an effective and economical biomass pretreatment method is a significant roadblock to meeting the ever growing demand for transportation fuels. Earlier studies with different feedstocks revealed that in the absence of chemicals, neither extrusion nor microwave could be standalone pretreatments. However, there is potential that the advantages of these individual methods can be harnessed in a sequential pretreatment process. Accordingly, switchgrass and big bluestem were extruded and then subject to microwave pretreatment, under optimal conditions that had been separately determined in prior studies. Pretreated biomass was then subject to enzymatic hydrolysis to understand the effectiveness of the sequential pretreatment on sugar recovery and generation of fermentation inhibitors. Statistical analysis confirmed that moisture content, microwave power level, and exposure time (and their interactions) had significant influence on sugar recovery. Sequential pretreatment of switchgrass (25% moisture, 450 W and 2.5 min) resulted in a maximum glucose, xylose, and total sugar recovery of 52.6%, 75.5%, and 59.2%, respectively. This was higher by 1.27 and 2.71, 1.21 and 4.60, and 1.25 and 2.87 times compared to extrusion alone and the unpretreated control, respectively. The same sequential pretreatment conditions achieved maximum glucose, xylose, and total sugar recovery of 83.2%, 92.1%, and 68.1%, respectively, for big bluestem. This was 1.14 and 4.1, 1.18 and 2.7, and 1.20 and 3.0 times higher than extrusion alone and the unpretreated control, respectively. This sequential pretreatment process did not aggravate acetic acid formation over levels observed with the individual pretreatments. Furthermore, furfural, HMF, and formic acid were not detected in any of the treatments. Although the sequential pretreatment process enhanced sugar recovery without increasing the levels of potential fermentation inhibitors, the increased energy input for the microwave treatment may not be economical.