cssi/SciSciGPT-SciSciNet huggingface dataset:
Hunting for Discriminatory Proxies in Linear Regression Models

A machine learning model may exhibit discrimination when used to make decisions involving people. One potential cause for such outcomes is that the model uses a statistical proxy for a protected demographic attribute. In this paper we formulate a definition of proxy use for the setting of linear regression and present algorithms for detecting proxies. Our definition follows recent work on proxies in classification models, and characterizes a model's constituent behavior that: 1) correlates closely with a protected random variable, and 2) is causally influential in the overall behavior of the model. We show that proxies in linear regression models can be efficiently identified by solving a second-order cone program, and further extend this result to account for situations where the use of a certain input variable is justified as a ``business necessity''. Finally, we present empirical results on two law enforcement datasets that exhibit varying degrees of racial disparity in prediction outcomes, demonstrating that proxies shed useful light on the causes of discriminatory behavior in models.
How connected are the U.S. regional natural gas markets in the post-deregulation era? Evidence from time-varying connectedness analysis

Abstract The level of market integration is a critical indicator of resource allocation efficiency. In this paper, we evaluate the dynamic spatial integration in the U.S. natural gas market since deregulation and the relative importance of each location in the overall price discovery process. Using data from seven natural gas spot markets in the U.S, as well as one Canadian spot market located on the border between U.S. and Canada, we find that the U.S. regional natural gas market is on average well-integrated in both the short- and long-runs. The connectedness price index we constructed ranges between 55% and 85% during the sample period (1994–2016). Though the connectedness of the market has generally improved, a marked decline has occurred over the past few years, coincident with the shale gas boom. This decline may be attributed to pipeline capacity constraints in an increasingly oversupplied market and the relatively small number of market participants voluntarily reporting transaction activities to price indexes. We find that the role of each regional market in the overall price discovery process has undergone several shifts during our sample period, depending on the specific market conditions at both the national and regional level. Of the eight locations, Henry Hub and Oneok appear to be the two most active markets, both transmitting and receiving a substantial amount of information throughout most of the sample period.
Nonparametric Bayesian Lomax delegate racing for survival analysis with competing risks

We propose Lomax delegate racing (LDR) to explicitly model the mechanism of survival under competing risks and to interpret how the covariates accelerate or decelerate the time to event. LDR explains non-monotonic covariate effects by racing a potentially infinite number of sub-risks, and consequently relaxes the ubiquitous proportional-hazards assumption which may be too restrictive. Moreover, LDR is naturally able to model not only censoring, but also missing event times or event types. For inference, we develop a Gibbs sampler under data augmentation for moderately sized data, along with a stochastic gradient descent maximum a posteriori inference algorithm for big data applications. Illustrative experiments are provided on both synthetic and real datasets, and comparison with various benchmark algorithms for survival analysis with competing risks demonstrates distinguished performance of LDR.
Learning Attractor Dynamics for Generative Memory

A central challenge faced by memory systems is the robust retrieval of a stored pattern in the presence of interference due to other stored patterns and noise. A theoretically well-founded solution to robust retrieval is given by attractor dynamics, which iteratively cleans up patterns during recall. However, incorporating attractor dynamics into modern deep learning systems poses difficulties: attractor basins are characterised by vanishing gradients, which are known to make training neural networks difficult. In this work, we exploit recent advances in variational inference and avoid the vanishing gradient problem by training a generative distributed memory with a variational lower-bound-based Lyapunov function. The model is minimalistic with surprisingly few parameters. Experiments shows it converges to correct patterns upon iterative retrieval and achieves competitive performance as both a memory model and a generative model.
Central Bank Policies and Inflation A Case Study of Four Less Developed Economies, 1949-57*

Publisher Summary This chapter presents a case study of four less developed economies (LDCs) to analyze central bank policies and inflation. Most of the LDCs have been subject during the postwar period to inflationary pressures of various degrees of intensity. As a rule, these pressures emanate from attempts by one or more sectors of the economy to secure a larger share of the total product. The primary motivations for such attempts are the desire of either the public sector or the private sector, or both, to undertake additional investments and to put the burden of the required additional saving on the other sector. The chapter reviews the experience of four countries Indonesia, Mexico, Nicaragua, and Paraguay that were subject to chronic inflation during 1949–1957It discusses the potential scope for a more effective monetary policy and the reasons for failure to implement such a policy.
On the CCA2 Security of McEliece in the Standard Model

In this paper we study public-key encryption schemes based on error-correcting codes that are IND-CCA2 secure in the standard model. In particular, we analyze a protocol due to Dowsley, Muller-Quade and Nascimento, based on a work of Rosen and Segev. The original formulation of the protocol contained some ambiguities and incongruences, which we point out and correct; moreover, the protocol deviates substantially from the work it is based on. We then present a construction which resembles more closely the original Rosen-Segev framework, and show how this can be instantiated with the McEliece scheme.
Mechanism design for social good

Across various domains---such as health, education, and housing---improving societal welfare involves allocating resources, setting policies, targeting interventions, and regulating activities. These solutions have an immense impact on the day-to-day lives of individuals, whether in the form of access to quality healthcare, labor market outcomes, or how votes are accounted for in a democratic society. Problems that can have an outsized impact on individuals whose opportunities have historically been limited often pose conceptual and technical challenges, requiring insights from many disciplines. Conversely, the lack of inter-disciplinary approach can leave these urgent needs unaddressed and can even exacerbate underlying socioeconomic inequalities.
Gaussian Reciprocal Sequences from the Viewpoint of Conditionally Markov Sequences

The conditionally Markov (CM) sequence contains several classes, including the reciprocal sequence. Reciprocal sequences have been widely used in many areas of engineering, including image processing, acausal systems, intelligent systems, and intent inference. In this paper, the reciprocal sequence is studied from the CM sequence point of view, which is different from the viewpoint of the literature and leads to more insight into the reciprocal sequence. Based on this viewpoint, new results, properties, and easily applicable tools are obtained for the reciprocal sequence. The nonsingular Gaussian (NG) reciprocal sequence is modeled and characterized from the CM viewpoint. It is shown that a NG sequence is reciprocal if and only if it is both CML and CMF (two special classes of CM sequences). New dynamic models are presented for the NG reciprocal sequence. These models (unlike the existing one, which is driven by colored noise) are driven by white noise and are easily applicable. As a special reciprocal sequence, the Markov sequence is also discussed. Finally, it can be seen how all CM sequences, including Markov and reciprocal, are unified.
Inference on finite-population treatment effects under limited overlap

This paper studies inference on finite population average and local average treatment effects under limited overlap, meaning some strata have a small proportion of treated or untreated units. We model limited overlap in an asymptotic framework sending the propensity score to zero (or one) with the sample size. We derive the asymptotic distribution of analog estimators of the treatment effects under two common randomization schemes: conditionally independent and stratified block randomization. Under either scheme, the limit distribution is the same and conventional standard error formulas remain asymptotically valid, but the rate of convergence is slower the faster the propensity score degenerates. The practical import of these results is twofold. When overlap is limited, standard methods can perform poorly in smaller samples, as asymptotic approximations are inadequate due to the slower rate of convergence. However, in larger samples, standard methods can work quite well even when the propensity score is small.
Statistical Learning of Discrete States in Time Series

Time series obtained from time-dependent experiments contain rich information on kinetics and dynamics of the system under investigation. This work describes an unsupervised learning framework, along with the derivation of the necessary analytical expressions, for the analysis of Gaussian-distributed time series that exhibit discrete states. After the time series has been partitioned into segments in a model-free manner using the previously developed change-point (CP) method, this protocol starts with an agglomerative hierarchical clustering algorithm to classify the detected segments into possible states. The initial state clustering is further refined using an expectation-maximization (EM) procedure, and the number of states is determined by a Bayesian information criterion (BIC). Also introduced here is an achievement scalarization function, usually seen in artificial intelligence literature, for quantitatively assessing the performance of state determination. The statistical learning framework, which is comprised of three stages, detection of signal change, clustering, and number-of-state determination, was thoroughly characterized using simulated trajectories with random intensity segments that have no underlying kinetics, and its performance was critically evaluated. The application to experimental data is also demonstrated. The results suggested that this general framework, the implementation of which is based on firm theoretical foundations and does not require the imposition of any kinetics model, is powerful in determining the number of states, the parameters contained in each state, as well as the associated statistical significance.
Employee Voluntary and Involuntary Turnover and Organizational Performance: Revisiting the Hypothesis from Classical Public Administration

This article examines the effects of voluntary, involuntary, and absolute turnover rates on organizational performance. Adopting human capital and cost-benefit theories, this article posits that vo...
Preference matching, income, and population distribution in urban and adjacent rural regions

We analyze the impact of preference matching and income on the distribution of the population in an aggregate economy consisting of an urban and an adjacent rural region. It costs more (less) to live in the urban (rural) region. Individuals choose freely to live either in the urban or in the rural region. They differ in their incomes. These incomes are uniformly distributed on the unit interval. Our analysis leads to four results. First, when the cost differential parameter satisfies a condition, both regions are occupied in the equilibrium. Second, when this parametric condition holds, in any equilibrium in which the mean income of individuals varies across the two regions, every resident of the rural region has a lower income than every resident of the urban region. Third, there exists an income threshold and all individuals with higher (lower) incomes choose to live in the urban (rural) region. Finally, in the equilibrium with income sorting, it is possible to make everyone better off by slightly modifying their residential choices.
Unsupervised identification of disease states from high‐dimensional physiological and histopathological profiles

The liver and kidney in mammals play central roles in protecting the organism from xenobiotics and are at high risk of xenobiotic-induced injury. Xenobiotic-induced tissue injury has been extensively studied from both classical histopathological and biochemical perspectives. Here, we introduce a machine-learning approach to analyze toxicological response. Unsupervised characterization of physiological and histological changes in a large toxicogenomic dataset revealed nine discrete toxin-induced disease states, some of which correspond to known pathology, but others were novel. Analysis of dynamics revealed transitions between disease states at constant toxin exposure, mostly toward decreased pathology, implying induction of tolerance. Tolerance correlated with induction of known xenobiotic defense genes and decrease of novel ferroptosis sensitivity biomarkers, suggesting ferroptosis as a druggable driver of tissue pathophysiology. Lastly, mechanism of body weight decrease, a known primary marker for xenobiotic toxicity, was investigated. Combined analysis of food consumption, body weight, and molecular biomarkers indicated that organ injury promotes cachexia by whole-body signaling through Gdf15 and Igf1, suggesting strategies for therapeutic intervention that may be broadly relevant to human disease.
On Automorphisms of Enveloping Algebras

Given an algebraic Lie algebra $\mathfrak{g}$ over $\mathbb{C}$, we canonically associate to it a Lie algebra $\mathfrak{g}_{\infty}$ defined over $\mathbb{C}_{\infty}$-the reduction of $\mathbb{C}$ mod infinitely large prime, and show that for a class of Lie algebras $\mathfrak{g}_{\infty}$ is an invariant of the derived category of $\mathfrak{g}$-modules. We give two applications of this construction. First, we show that the bounded derived category of $\mathfrak{g}$-modules determines algebra $\mathfrak{g}$ for a class of Lie algebras. Second, given a semi-simple Lie algebra $\mathfrak{g}$ over $\mathbb{C}$, we construct a canonical homomorphism from the group of automorphisms of the enveloping algebra $\mathfrak{U}\mathfrak{g}$ to the group of Lie algebra automorphisms of $\mathfrak{g}$, such that its kernel does not contain a nontrivial semi-simple automorphism. As a corollary we obtain that any finite subgroup of automorphisms of $\mathfrak{U}\mathfrak{g}$ isomorphic to a subgroup of Lie algebra automorphisms of $\mathfrak{g}.$
Approximate Logic Synthesis: A Reinforcement Learning-Based Technology Mapping Approach

Approximate Logic Synthesis (ALS) is the process of synthesizing and mapping a given Boolean network to a library of logic cells so that the magnitude/rate of error between outputs of the approximate and initial (exact) Boolean netlists is bounded from above by a predetermined total error threshold. In this paper, we present Q-ALS, a novel framework for ALS with focus on the technology mapping phase. Q-ALS incorporates reinforcement learning and utilizes Boolean difference calculus to estimate the maximum error rate that each node of the given network can tolerate such that the total error rate at non of the outputs of the mapped netlist exceeds a predetermined maximum error rate, and the worst case delay and the total area are minimized. Maximum Hamming Distance (MHD) between exact and approximate truth tables of cuts of each node is used as the error metric. In Q-ALS, a Q-Learning agent is trained with a sufficient number of iterations aiming to select the fittest values of MHD for each node, and in a cut-based technology mapping approach, the best supergates (in terms of delay and area, bounded further by the fittest MHD) are selected towards implementing each node. Experimental results show that having set the required accuracy of 95% at the primary outputs, Q-ALS reduces the total cost in terms of area and delay by up to 70 % and 36%, respectively, and also reduces the run-time by 2.21 x on average, when compared to the best state-of-the-art academic ALS tools.
QuickStop: A Markov Optimal Stopping Approach for Quickest Misinformation Detection

This paper combines data-driven and model-driven methods for real-time misinformation detection. Our algorithm, named QuickStop, is an optimal stopping algorithm based on a probabilistic information spreading model obtained from labeled data. The algorithm consists of an offline machine learning algorithm for learning the probabilistic information spreading model and an online optimal stopping algorithm to detect misinformation. The online detection algorithm has both low computational and memory complexities. Our numerical evaluations with a real-world dataset show that QuickStop outperforms existing misinformation detection algorithms in terms of both accuracy and detection time (number of observations needed for detection). Our evaluations with synthetic data further show that QuickStop is robust to (offline) learning errors.
Power Control and Frequency Band Selection Policies for Underlay MIMO Cognitive Radio

We study power control and frequency band selection policies for multi-band underlay MIMO cognitive radio with the objective of maximizing the rate of a secondary user (SU) link while limiting the interference leakage toward primary users (PUs) below a threshold. The goal of the SU in each policy is to select one frequency band in each time slot and determine the transmit power. To limit the interference toward PU in time-varying channels, we propose fixed and dynamic transmit power control schemes which depend on PU traffic and the temporal correlation of channels between the SU and the PU. We study the performance of frequency band selection policies that use fixed or dynamic power control. We show that dynamic frequency band selection policies, e.g., policies based on multi-armed bandit framework, wherein SU selects a different frequency band in each slot, result in higher interference toward PU as compared to the fixed band policy wherein SU stays on one band. We also provide an expression for the gap between the rate achieved by SU under a clairvoyant policy and the fixed band policy. It is observed that this gap reduces with increased temporal correlation and with increased number of SU antennas.
On Evaluating CNN Representations for Low Resource Medical Image Classification

Convolutional Neural Networks (CNNs) have revolutionized performances in several machine learning tasks such as image classification, object tracking, and keyword spotting. However, given that they contain a large number of parameters, their direct applicability into low resource tasks is not straightforward. In this work, we experiment with an application of CNN models to gastrointestinal landmark classification with only a few thousands of training samples through transfer learning. As in a standard transfer learning approach, we train CNNs on a large external corpus, followed by representation extraction for the medical images. Finally, a classifier is trained on these CNN representations. However, given that several variants of CNNs exist, the choice of CNN is not obvious. To address this, we develop a novel metric that can be used to predict test performances, given CNN representations on the training set. Not only we demonstrate the superiority of the CNN based transfer learning approach against an assembly of knowledge driven features, but the proposed metric also carries an 87% correlation with the test set performances as obtained using various CNN representations.
Barriers to Educator Implementation of a Classroom-Based Intervention for Preschoolers With Autism Spectrum Disorder

There is considerable need for adoptable evidence-based interventions for implementation in public classrooms serving children with autism spectrum disorders (ASD) during the preschool years, an important period in neurodevelopment. Barriers to implementation, including gaps in teacher education, contribute to the research-to-practice gap and may compromise child outcomes. This qualitative study collected feedback from educators and administrators during their participation in the iterative development phase of a larger project to translate and preliminarily trial an evidence-based intervention in public preschool classrooms. Barriers were identified in areas of educator preparedness, engagement, and cohesion, complexity of instructing students with ASD, limited time/resources, and administrator support. Educators and administrators differed in their perspectives. Innovative strategies are presented for enhancing transportability, along with discussion of implications for teacher education practices and related policy.
Liouville Theory, AdS$_2$ String, and Three-Point Functions

This is a write-up of the lectures given in Young Researchers Integrability School 2017.a#13; The main goal is to explain the connection between the ODE/IM correspondence and thea#13; classical integrability of strings in AdS. As a warm up, we first discuss the classical three-pointa#13; function of the Liouville theory. Our starting point is the well-known fact that the classicala#13; solutions to the Liouville equation can be constructed by solving a certain Schrodinger-likea#13; differential equation. We then convert it into a set of functional equations using the ideaa#13; akin to the ODE/IM correspondence. The classical three-point functions can be computeda#13; directly from these functional equations and the result matches with the classical limit ofa#13; the celebrated DOZZ formula. We then proceed to discuss the semi-classical three-pointa#13; function of strings in AdS2 and show that one can apply a similar idea by making use of thea#13; classical integrability of the string sigma model on AdS2.
Fast compression of OFDM channel state information with constant frequency sinusoidal approximation

We propose CSIApx, a very fast and lightweight method to compress the channel state information (CSI) of Wi-Fi networks. CSIApx approximates the CSI vector as the linear combination of a small number of base sinusoids on constant frequencies and uses the complex coefficients of the base sinusoids as the compressed CSI. While it is well-known that the CSI vector can be represented as the linear combination of sinusoids, fixing the frequencies of the sinusoids is the key novelty of CSIApx, which is guided by our mathematical finding that almost any sinusoid can be approximated by a set of base sinusoids on constant frequencies. CSIApx enjoys very low computation complexity, because key steps in the compression can be pre-computed due to the constant frequencies of the base sinusoids. We extensively test CSIApx with both experimental and synthesized Wi-Fi channel data, and the results confirm that CSIApx can achieve very good compression ratio with little loss of accuracy.
Onset of Telomere Dysfunction and Fusions in Human Ovarian Carcinoma

Telomere dysfunction has been strongly implicated in the initiation of genomic instability and is suspected to be an early event in the carcinogenesis of human solid tumors. Recent findings have established the presence of telomere fusions in human breast and prostate malignancies; however, the onset of this genomic instability mechanism during progression of other solid cancers is not well understood. Herein, we explored telomere dynamics in patient-derived epithelial ovarian cancers (OC), a malignancy characterized by multiple distinct subtypes, extensive molecular heterogeneity, and widespread genomic instability. We discovered a high frequency of telomere fusions in ovarian tumor tissues; however, limited telomere fusions were detected in normal adjacent tissues or benign ovarian samples. In addition, we found relatively high levels of both telomerase activity and hTERT expression, along with anaphase bridges in tumor tissues, which were notably absent in adjacent normal ovarian tissues and benign lesions. These results suggest that telomere dysfunction may occur early in ovarian carcinogenesis and, importantly, that it may play a critical role in the initiation and progression of the disease. Recognizing telomere dysfunction as a pervasive feature of this heterogeneous malignancy may facilitate the future development of novel diagnostic tools and improved methods of disease monitoring and treatment.
The Lancet commission on global health law: the transformative power of law to advance the right to health

A new report by The Lancet-O’Neill-Georgetown University Commission on Global Health and the Law shows how law can fulfill the global pledge of the human right to health, while “leaving no one behind.” I call this “global health with justice.” We need both health and justice. By global health, I mean ever increasing indicators of good health and increased longevity in all countries around the world. By justice I mean that the global “good” of health must be fairly distributed both within and among countries. The Lancet Commission report offers a comprehensive roadmap towards realizing the law’s power to make us healthier and safer, describing how principles – like fairness, participation, and wielding evidence – can shape policies throughout government. It also vividly illustrates how good governance and the rule of law can advance both health and justice. We tend to think of science and medicine as the major drivers of good health. And, of course, these disciplines are vital to develop, implement, and improve healthcare, including pharmaceuticals, vaccines, and medical supplies. Yet, professional medical and nursing services make only a relatively small contribution to population health. More important are population-based interventions that modify core risks to health, such as diet, smoking, alcohol, and physical activity. These interventions are not the product of medicine or healthcare systems. Rather they are driven by law. In other words, what is the wonder drug that could save millions of lives? It is the law, enacted on the floors of national legislatures.
Gender differences in volunteer’s dilemma: Evidence from teamwork among graduate students

Abstract Undertaking logistical tasks in a teamwork setting exhibits a volunteer’s dilemma: it takes only one volunteer to take a costly action to generate a benefit to the entire team. Using naturally-occurring data in a top graduate professional school, I show that female students volunteer significantly more than male students in booking rooms for team meetings. I also find that the gender difference in undertaking this logistical task is statistically and quantitatively significant only when students have limited interaction prior to teamwork. This suggests that when students’ preferences are not completely known to each other, gender stereotyping—beliefs that most female students will undertake such tasks or some male students will not—may disfavor female students who end up bearing a cost higher than males. Even though booking a room involves a relatively small time cost, such costs can add up, and also contribute to gender stereotyping in allocation of tasks in other team settings.
An efficient synthesis of enantiomerically enriched aryllactic esters

Abstract An efficient synthesis of enantiomerically enriched aryllactic esters or acids has been established. Darzen's condensation of arylaldehydes with ethyl chloroacetate followed by catalytic hydrogenation gave racemic aryllactic esters. Enzyme catalyzed (lipase PS-30, Amano) hydrolysis or acetylation provided enantiomerically enriched products. EE's of 65–99% were obtained without optimization of resolution conditions. This route is compatible with a variety of heterocycles and multigram quantities of enantiomerically enriched materials have been prepared. These chiral synthons are useful for the preparation of renin inhibitors as well as other therapeutic agents.
Relating VFCs on thin compactifications

Many moduli spaces that occur in geometric analysis admit “Fredholm-stratified thin compactifications”, and hence admit a relative fundamental class (RFC), as defined previously by the authors. We extend these results, emphasizing the naturality of the RFC, eliminating the need for a stratification, and proving three compatibility results: the invariants defined by the RFC agree with those defined by pseudo-cycles, the RFC is compatible with cutdown moduli spaces, and the RFC agrees with the virtual fundamental class (VFC) constructed by Pardon via implicit atlases in all cases where both are defined.
Selective alkane oxidation: hot and cold approaches to a hot problem

Abstract A large number of attempts at the selective oxidation of alkanes may be classified into three basic types: high-temperature heterogeneous catalysis, biological/biomimetic catalysis, and organometallic activation. In this essay I discuss mechanistic similarities and differences between the three approaches, and their implications for the best opportunities for achieving desired selective transformations.
CircularLogo: A lightweight web application to visualize intra-motif dependencies.

The sequence logo has been widely used to represent DNA or RNA motifs for more than three decades. Despite its intelligibility and intuitiveness, the traditional sequence logo is unable to display the intra-motif dependencies and therefore is insufficient to fully characterize nucleotide motifs. Many methods have been developed to quantify the intra-motif dependencies, but fewer tools are available for visualization. We developed CircularLogo, a web-based interactive application, which is able to not only visualize the position-specific nucleotide consensus and diversity but also display the intra-motif dependencies. Applying CircularLogo to HNF6 binding sites and tRNA sequences demonstrated its ability to show intra-motif dependencies and intuitively reveal biomolecular structure. CircularLogo is implemented in JavaScript and Python based on the Django web framework. The program’s source code and user’s manual are freely available at http://circularlogo.sourceforge.net . CircularLogo web server can be accessed from http://bioinformaticstools.mayo.edu/circularlogo/index.html . CircularLogo is an innovative web application that is specifically designed to visualize and interactively explore intra-motif dependencies.
Characterization of a Replicating Mammalian Orthoreovirus with Tetracysteine-Tagged μNS for Live-Cell Visualization of Viral Factories.

Within infected host cells, mammalian orthoreovirus (MRV) forms viral factories (VFs), which are sites of viral transcription, translation, assembly, and replication. The MRV nonstructural protein μNS comprises the structural matrix of VFs and is involved in recruiting other viral proteins to VF structures. Previous attempts have been made to visualize VF dynamics in live cells, but due to current limitations in recovery of replicating reoviruses carrying large fluorescent protein tags, researchers have been unable to directly assess VF dynamics from virus-produced μNS. We set out to develop a method to overcome this obstacle by utilizing the 6-amino-acid (CCPGCC) tetracysteine (TC) tag and FlAsH-EDT2 reagent. The TC tag was introduced into eight sites throughout μNS, and the capacity of the TC-μNS fusion proteins to form virus factory-like (VFL) structures and colocalize with virus proteins was characterized. Insertion of the TC tag interfered with recombinant virus rescue in six of the eight mutants, likely as a result of loss of VF formation or important virus protein interactions. However, two recombinant (r)TC-μNS viruses were rescued and VF formation, colocalization with associating virus proteins, and characterization of virus replication were subsequently examined. Furthermore, the rTC-μNS viruses were utilized to infect cells and examine VF dynamics using live-cell microscopy. These experiments demonstrate active VF movement with fusion events as well as transient interactions between individual VFs and demonstrate the importance of microtubule stability for VF fusion during MRV infection. This work provides important groundwork for future in-depth studies of VF dynamics and host cell interactions. IMPORTANCE MRV has historically been used as a model to study the double-stranded RNA (dsRNA) Reoviridae family, the members of which infect and cause disease in humans, animals, and plants. During infection, MRV forms VFs that play a critical role in virus infection but remain to be fully characterized. To study VFs, researchers have focused on visualizing the nonstructural protein μNS, which forms the VF matrix. This work provides the first evidence of recovery of replicating reoviruses in which VFs can be labeled in live cells via introduction of a TC tag into the μNS open reading frame. Characterization of each recombinant reovirus sheds light on μNS interactions with viral proteins. Moreover, utilizing the TC-labeling FlAsH-EDT2 biarsenical reagent to visualize VFs, evidence is provided of dynamic VF movement and interactions at least partially dependent on intact microtubules.
Do secondary and tertiary ammonium cations act as structure-directing agents in the formation of layered uranyl selenites?

Two new layered uranyl selenites, [C4H12N2]0.5[UO2(HSeO3)(SeO3)] (1) and [C6H14N2]0.5[UO2(HSeO3)(SeO3)]·0.5H2O·0.5CH3CO2H (2), have been isolated from mild hydrothermal reactions. The preparation o...
Unusual Reagent Control of Diastereoselectivity in the 1,2-Addition of Hard Carbon Nucleophiles to C6-Heteroatom Substituted Cyclohexenones

A surprising and synthetically useful counterion-dependent reversal of diastereoselectivity was found in 1,2-additions of hard carbon nucleophiles to C6-heterosubstituted cyclohexenones. In general, Grignard reagents added syn to the C6-substituent and Li reagents added anti, although some exceptions were found. Selectivities could be increased in some cases by appropriate choice of solvent and/or cosolvent.
Toward reversible control of cucurbit[n]uril complexes.

ConspectusThe cucurbit[n]uril (CBn) host family consists of a group of rigid macrocyclic hosts with barrel-like shapes and limited solubility in aqueous media. These hosts are capable of reaching high binding affinities with positively charged hydrophobic guests. In optimum cases, equilibrium association constant (K) values as high as 1017 M–1 have been reported, exceeding the binding affinity of the avidin–biotin host–guest pair. The synthetic CBn receptors have shattered the notion that highly stable noncovalent complexes can form only when one of the partners is a molecule of biological origin.The work described in this Account is concerned with the development of methods geared toward the reversible modulation of the binding affinity of CBn inclusion complexes under mild conditions. A good fraction of the research work has dealt with redox active guests, such as 4,4′-bipyridinium (viologen), ferrocene, and cobaltocenium derivatives. Our experimental results show that the thermodynamics and kinetics of...
Vinylogous Mannich reactions. Catalytic, asymmetric additions of triisopropylsilyloxyfurans to aldimines

Abstract The vinylogous Mannich reaction of triisopropylsilyloxyfurans with aldimines in the presence of catalytic amounts of the Ti(O i Pr ) 4 (S)- BINOL complex gave substituted aminoalkyl butenolides in good yield and enantioselectivities (up to 54% ee).
Combinatorial Drug Discovery in Nanoliter Droplets

Combinatorial drug treatment strategies perturb biological networks synergistically to achieve therapeutic effects and represent major opportunities to develop advanced treatments across a variety of human disease areas. However, the discovery of new combinatorial treatments is challenged by the sheer scale of combinatorial chemical space. Here, we report a high-throughput system for nanoliter-scale phenotypic screening that formulates a chemical library in nanoliter droplet emulsions and automates the construction of chemical combinations en masse using parallel droplet processing. We applied this system to predict synergy between more than 4,000 investigational and approved drugs and a panel of 10 antibiotics against Escherichia coli, a model gram-negative pathogen. We found a range of drugs not previously indicated for infectious disease that synergize with antibiotics. Our validated hits include drugs that synergize with the antibiotics vancomycin, erythromycin, and novobiocin, which are used against gram-positive bacteria but are not effective by themselves to resolve gram-negative infections.
A Decrease in Serine Levels during Growth Transition Triggers Biofilm Formation in Bacillus subtilis

ABSTRACT Biofilm development in Bacillus subtilis is regulated at multiple levels. While a number of known signals that trigger biofilm formation do so through the activation of one or more sensory histidine kinases, it was discovered that biofilm activation is also coordinated by sensing intracellular metabolic signals, including serine starvation. Serine starvation causes ribosomes to pause on specific serine codons, leading to a decrease in the translation rate of sinR, which encodes a master repressor for biofilm matrix genes and ultimately triggers biofilm induction. How serine levels change in different growth stages, how B. subtilis regulates intracellular serine levels, and how serine starvation triggers ribosomes to pause on selective serine codons remain unknown. Here, we show that serine levels decrease as cells enter stationary phase and that unlike most other amino acid biosynthesis genes, expression of serine biosynthesis genes decreases upon the transition into stationary phase. The deletion of the gene for a serine deaminase responsible for converting serine to pyruvate led to a delay in biofilm formation, further supporting the idea that serine levels are a critical intracellular signal for biofilm activation. Finally, we show that levels of all five serine tRNA isoacceptors are decreased in stationary phase compared with exponential phase. However, the three isoacceptors recognizing UCN serine codons are reduced to a much greater extent than the two that recognize AGC and AGU serine codons. Our findings provide evidence for a link between serine homeostasis and biofilm development in B. subtilis. IMPORTANCE In Bacillus subtilis, biofilm formation is triggered in response to environmental and cellular signals. It was proposed that serine limitation acts as a proxy for nutrient status and triggers biofilm formation at the onset of biofilm entry through a novel signaling mechanism caused by global ribosome pausing on selective serine codons. In this study, we reveal that serine levels decrease at the biofilm entry due to catabolite control and a serine shunt mechanism. We also show that levels of five serine tRNA isoacceptors are differentially decreased in stationary phase compared with exponential phase; three isoacceptors recognizing UCN serine codons are reduced much more than the two recognizing AGC and AGU codons. This finding indicates a possible mechanism for selective ribosome pausing.
A Study of Stress in Microwave Plasma Chemical Vapor Deposited Diamond Films Using X‐Ray Diffraction

Residual stress in polycrystalline diamond films has been studied. Uniform polycrystalline diamond films were deposited on 3.0 in. diameter silicon substrates in a microwave plasma chemical vapor deposition (MPCVD) system. The effects of CH4/H2 ratio, pressure, and power variation on film stress were investigated. The macro-stress, or uniform stress, in the films was measured using the X-ray diffraction (XRD) d-sin2ψ technique. In general, 〈220〉-oriented films exhibited tensile stress and 〈111〉-oriented films were in compression. The micro-stress, or non-uniform stress, calculated from diffraction peak broadening, was observed to be tensile for all samples. Films of relatively small grain size and 〈220〉 orientation showed both the highest micro-stress and the highest macro-stress. Film morphology was analyzed using scanning electron microscopy (SEM) and atomic force microscopy (AFM), while the film texture was studied using XRD. Significant non-diamond carbon was incorporated in 〈220〉-oriented diamond as estimated from the intensity of the broad 1580 cm−1 peak in the Raman spectra. Much less non-diamond carbon was detected in 〈111〉-oriented diamond films. Good correlation between film morphology and measured stress was observed.
Charge transfer and charge transport on the double helix

We present a short review of various experiments that measure charge transfer and charge transport in DNA. Some general comments are made on the possible connection between various 'chemistry-style' charge transfer experiments that probe fluorescence quenching and remote oxidative damage and 'phys-style' measurements that measure transport properties as defined typically in the solid-state. We then describe measurements performed by our group on the millimeter wave response of DNA. By measuring over a wide range of humidity conditions and comparing the response of single strand DNA and double strand DNA, we show that the appreciable AC conductivity of DNA is not due to photon assisted hopping between localized states, but instead due to dissipation from dipole motion in the surrounding water helix.
The Effect of SNAP on the Composition of Purchased Foods: Evidence and Implications

We use detailed data from a large retail panel to study the effect of participation in the Supplemental Nutrition Assistance Program (SNAP) on the composition and nutrient content of foods purchased for at-home consumption. We find that the effect of SNAP participation is small relative to the cross-sectional variation in most of the outcomes we consider. Estimates from a model relating the composition of a household’s food purchases to the household’s current level of food spending imply that closing the gap in food spending between high- and low-SES households would not close the gap in summary measures of food healthfulness.
Sulfite formation versus chlorination of benzyl alcohols with thionyl chloride

Abstract Recently, we have reported the photolytic decay of a library of para -substituted dibenzylic sulfites in a Srinivasan–Griffin–Rayonet photochemical reactor. In an attempt to synthesize the complete library for that study we discovered that bis( p -methoxybenzyl) sulfite and bis( p -phenoxybenzyl) sulfite could not be formed and only their corresponding benzyl chlorides were synthesized. Thus, sulfite formation versus chlorination of a range of para -substituted benzyl alcohols with thionyl chloride was investigated. Sulfite formation was observed to be parabolically related to Swain and Lupton’s Field F -values while chloride formation was found to be linearly related to Swain and Lupton’s Field R -values.
A Reliable Multikilogram-Scale Synthesis of 2-Acetamido-5-Vinylpyridine Using Catalytic BINAP in a Modified Heck Reaction

An optimized Heck ethylenation of 2-acetamido-5-bromopyridine using a unique catalytic combination of phosphine ligands, tri-o-tolylphosphine and BINAP (S-(−)- or racemic) as an additive/promoter i...
KrakenUniq: confident and fast metagenomics classification using unique k -mer counts

False-positive identifications are a significant problem in metagenomics classification. We present KrakenUniq, a novel metagenomics classifier that combines the fast k-mer-based classification of Kraken with an efficient algorithm for assessing the coverage of unique k-mers found in each species in a dataset. On various test datasets, KrakenUniq gives better recall and precision than other methods and effectively classifies and distinguishes pathogens with low abundance from false positives in infectious disease samples. By using the probabilistic cardinality estimator HyperLogLog, KrakenUniq runs as fast as Kraken and requires little additional memory. KrakenUniq is freely available at https://github.com/fbreitwieser/krakenuniq .
A Wideband Sliding Correlator-Based Channel Sounder with Synchronization in 65 nm CMOS

A programmable ultra-wideband sliding correlator-based channel sounder with high temporal and spatial resolution is designed in standard 65 nm CMOS. The baseband chip can be configured either as a baseband transmitter to generate a pseudo-random spread spectrum signal with flexible sequence lengths, or as a baseband receiver with sliding correlator having an absolute timing reference to obtain power delay profiles of the multipath components of the wireless channel. The sequence achieved a chip rate of one Giga-bit-per-second, resulting in a multipath delay resolution of 1 ns. The baseband chip occupies an area of 0.66 mm × 1 mm with a power dissipation of 6 mA at 1.1 V in 65 nm CMOS. The sliding correlator-based channel sounder in this work is a critical block for future low-cost, miniaturized channel sounding systems used in accurate and efficient channel propagation measurements at millimeter-wave frequencies.
Fabrication of SOFC Electrodes by Impregnation Methods

A novel procedure has been developed for fabricating composite electrodes for SOFC by impregnating a porous matrix of the electrolyte material with electronically conductive and catalytic materials. Because this method allows the electrolyte matrix to be calcined at high temperatures prior to adding the other components, thereby avoiding deleterious solid-state reactions, the method allows unprecedented compositional flexibility for both anodes and cathodes. This paper briefly reviews the present state of development for preparing SOFC through impregnation.
Bromine Halides: The Neutral Molecules BrClFn (n = 1− 5) and Their Anions Structures, Energetics, and Electron Affinities

Density functional methods were used for predictions of the structures and energetics of molecules and anions in the series BrClFn (n = 1−5). Very little is known from experiment about these potentially important interhalogen molecules. Energy minima were found for all neutral molecules with the exception of BrClF5. However, the dissociation limits for ClF elimination from the BrClF3 (BHLYP and B3LYP only) and BrClF4 (all methods) molecules lie below the energy of the respective ground states. All the BrClFn anions are bound with respect to the corresponding neutrals; energy minima were found for anions up to BrClF5-. Structures of isomers with the chlorine atom in the central position were also optimized. However, these local minima lie substantially above the bromine-centered structures, and the energy gap between isomers grows with n. For the neutral molecules two paths of dissociation were found to possess the lowest energies, i.e., chlorine atom and ClF elimination. The latter channel becomes predomi...
Intramolecular Inverse Electron Demand Diels–Alder Reactions of Tryptamine with Tethered Heteroaromatic Azadienes

Abstract 1,2,4,5-Tetrazines and 1,2,4-triazines tethered to tryptamine via the ethylamine side chain undergo intramolecular inverse electron demand cycloadditions to produce adducts with the [ABazaCE]-ring skeleton of the Aspidosperma alkaloids.
Enantioselective synthesis of cyclic secondary amines through Mo-catalyzed asymmetric ring-closing metathesis (ARCM).

Carbocyclic amines are synthesized efficiently in up to 93% ee by asymmetric ring-closing metathesis (ARCM) with 2−5 mol % chiral Mo complexes. An example is provided where the catalyst is prepared in situ (catalyst isolation not needed) to afford secondary amines that cannot be prepared by alternative methods.
A convenient approach for solution-phase synthesis of water-soluble galactoside libraries

Abstract A convenient approach for the solution-phase synthesis of water-soluble galactoside libraries through tributylphosphine promoted reaction of azido compounds with carboxylic acids is described.