cssi/SciSciGPT-SciSciNet huggingface dataset:
On elliptic factors in real endoscopic transfer I

This paper is concerned with the structure of packets of representations and some refinements that are helpful in endoscopic transfer for real groups. It includes results on the structure and transfer of packets of limits of discrete series representations. It also reinterprets the Adams–Johnson transfer of certain nontempered representations via spectral analogues of the Langlands–Shelstad factors, thereby providing structure and transfer compatible with the associated transfer of orbital integrals. The results come from two simple tools introduced here. The first concerns a family of splittings of the algebraic group G under consideration; such a splitting is based on a fundamental maximal torus of G rather than a maximally split maximal torus. The second concerns a family of Levi groups attached to the dual data of a Langlands or an Arthur parameter for the group G. The introduced splittings provide explicit realizations of these Levi groups. The tools also apply to maps on stable conjugacy classes associated with the transfer of orbital integrals. In particular, they allow for a simpler version of the definitions of Kottwitz–Shelstad for twisted endoscopic transfer in certain critical cases. The paper prepares for spectral factors in twisted endoscopic transfer that are compatible in a certain sense with the standard factors discussed here. This compatibility is needed for Arthur’s global theory. The twisted factors themselves will be defined in a separate paper.
Information processing by endoplasmic reticulum stress sensors

The unfolded protein response (UPR) is a collection of cellular feedback mechanisms that seek to maintain protein folding homeostasis in the endoplasmic reticulum (ER). When the ER is 'stressed', through either high protein folding demand or undersupply of chaperones and foldases, stress sensing proteins in the ER membrane initiate the UPR. Recently, experiments have indicated that these signalling molecules detect stress by being both sequestered by free chaperones and activated by free unfolded proteins. However, it remains unclear what advantage this bidirectional sensor control offers stressed cells. Here, we show that combining positive regulation of sensor activity by unfolded proteins with negative regulation by chaperones allows the sensor to make a more informative measurement of ER stress. The increase in the information capacity of the combined sensing mechanism stems from stretching of the active range of the sensor, at the cost of increased uncertainty due to the integration of multiple signals. These results provide a possible rationale for the evolution of the observed stress-sensing mechanism.
Is it just to pursue honest income

Is it just to pursue honest income? Certainly it’s commutatively just. But is it a becoming use of one’s own? Is it distributively just? Presumptively, yes. The burden of proof should be on the one who denies that someone’s pursuit of honest income is distributively just. Drawing closely on Adam Smith, I argue for that presumption. I treat focal points and price signals: If you think prices are imperfect signals for universal benevolence, just think how imperfect the other signals are! Virtues are swallowed up by self-interest as rivers are lost in the sea, said La Rochefoucauld. We come to the commercial humanism Smith constructed, including his invisible parable of the poor man’s son, producing the Great Enrichment. Cameos are made by Humphrey Bogart and caveats to our maxim that it is presumptively just to pursue honest income.
Mesoscale Liquid Model of Chromatin Recapitulates Nuclear Order of Eukaryotes.

Abstract The nuclear envelope segregates the genome of Eukaryota from the cytoplasm. Within the nucleus, chromatin is further compartmentalized into architectures that change throughout the lifetime of the cell. Epigenetic patterns along the chromatin polymer strongly correlate with chromatin compartmentalization and, accordingly, also change during the cell life cycle and at differentiation. Recently, it has been suggested that subnuclear chromatin compartmentalization might result from a process of liquid-liquid phase separation orchestrated by the epigenetic marking and operated by proteins that bind to chromatin. Here, we translate these observations into a diffuse interface model of chromatin, which we named the mesoscale liquid model of nucleus. Using this streamlined continuum model of the genome, we study the large-scale rearrangements of chromatin that happen at different stages of the growth and senescence of the cell and during nuclear inversion events. In particular, we investigate the role of droplet diffusion, fluctuations, and heterochromatin-lamina interactions during nuclear remodeling. Our results indicate that the physical process of liquid-liquid phase separation, together with surface effects, is sufficient to recapitulate much of the large-scale morphology and dynamics of chromatin along the life cycle of cells.
Privacy governing knowledge in public Facebook groups for political activism

Social media is increasingly used to share information about political issues and coordinate political activism. This paper examines privacy as governance in online knowledge sharing and organizing...
Circulation in High Reynolds Number Isotropic Turbulence is a Bifractal

Velocity circulation around closed loops in turbulent fluids can be described with just two exponents, setting the stage for a simpler statistical theory of turbulence.
Reconciling differences between large-eddy simulations and Doppler-lidar observations of continental shallow cumulus cloud-base vertical velocity

Author(s): Endo, S; Zhang, D; Vogelmann, AM; Kollias, P; Lamer, K; Oue, M; Xiao, H; Gustafson, WI; Romps, DM | Abstract: We investigate a significant model-observation difference found between cloud-base vertical velocity for continental shallow cumulus simulated using large-eddy simulations (LES) and observed by Doppler lidar measurements over the U.S. Southern Great Plains Atmospheric Radiation Measurement Facility. The LES cloud-base vertical velocity is dominated by updrafts that are consistent with a general picture for convective clouds but is inconsistent with Doppler lidar observations that also show the presence of considerable downdrafts. The underestimation of simulated downdrafts is found to be a robust feature, being insensitive to various numerical, physical, or dynamical choices. We find that simulations can more closely reproduce observations only after improving the model physics to use size-resolved microphysics and horizontal longwave radiation, both of which modify the cloud buoyancy and velocity structure near cloud side edges. The results suggest that treatments that capture these structures are needed for the proper simulation and subsequent parameterization development of shallow cumulus vertical transport.
The mean square of the product of a Dirichlet L-function and a Dirichlet polynomial

We establish an analogue of a conjecture of Balasubramanian, Conrey, and Heath-Brown for the family of all Dirichlet characters with conductor up to Q. This forms another application of our work in developing an asymptotic large sieve.
Economic Decisions Through Circuit Inhibition

Summary Economic choices between goods are thought to rely on the orbitofrontal cortex (OFC), but the decision mechanisms remain poorly understood. To shed light on this fundamental issue, we recorded from the OFC of monkeys choosing between two juices offered sequentially. An analysis of firing rates across time windows revealed the presence of different groups of neurons similar to those previously identified under simultaneous offers. This observation suggested that economic decisions in the two modalities are formed in the same neural circuit. We then examined several hypotheses on the decision mechanisms. OFC neurons encoded good identities and values in a juice-based representation (labeled lines). Contrary to previous assessments, our data argued against the idea that decisions rely on mutual inhibition at the level of offer values. In fact, we showed that previous arguments for mutual inhibition were confounded by differences in value ranges. Instead, decisions seemed to involve mechanisms of circuit inhibition, whereby each offer value indirectly inhibited neurons encoding the opposite choice outcome. Our results reconcile a variety of previous findings and provide a general account for the neuronal underpinnings of economic choices.
Low-power (mW) nonlinearities of polarization maintaining fibers

For space missions, there is a need for fiber lasers of minimum power consumption involving stabilized frequency combs. We exploit the extreme sensitivity of the polarization state of circularly polarized light sent through polarization-maintaining (PM) fibers to power and temperature variations. Low-power nonlinear transmission is demonstrated by terminating a PM fiber by an appropriately oriented polarizer. The strong correlation between the power sensitivity of the polarization state and the temperature dependence of the birefringence of the PM fiber can be exploited for optical length stabilization in fiber lasers and interferometers.
Liquid Metallic Hydrogen: A Building Block for the Liquid Sun

Liquid metallic hydrogen provides a compelling material for constructing a condensed matter model of the Sun and the photosphere. Like diamond, metallic hydrogen might have the potential to be a metastable substance requiring high pressures for formation. Once created, it would remain stable even at lower pressures. The metallic form of hydrogen was initially conceived in 1935 by Eugene Wigner and Hillard B. Huntington who indirectly anticipated its elevated critical temperature for liquefaction (Wigner E. and Huntington H.B. On the possibility of a metallic modification of hydrogen. J. Chem. Phys., 1935, v.3, 764–770). At that time, solid metallic hydrogen was hypothesized to exist as a body centered cubic, although a more energetically accessible layered graphite-like lattice was also envisioned. Relative to solar emission, this structural resemblance between graphite and layered metallic hydrogen should not be easily dismissed. In the laboratory, metallic hydrogen remains an elusive material. However, given the extensive observational evidence for a condensed Sun composed primarily of hydrogen, it is appropriate to consider metallic hydrogen as a solar building block. It is anticipated that solar liquid metallic hydrogen should possess at least some layered order. Since layered liquid metallic hydrogen would be essentially incompressible, its invocation as a solar constituent brings into question much of current stellar physics. The central proof of a liquid state remains the thermal spectrum of the Sun itself. Its proper understanding brings together all the great forces which shaped modern physics. Although other proofs exist for a liquid photosphere, our focus remains solidly on the generation of this light.
Systematic Measurement Error in Election Violence Data: Causes and Consequences

What are the causes and consequences of systematic measurement error in violence measures drawn from media-based conflict event data? More specifically, how valid are such event data for geocoding and capturing election violence? This study examines sub-national variation in election violence and uses original data from domestic election monitor surveys as a comparison to widely used sources of event data. The authors show that conventional data under-report events throughout the election cycle, particularly in sparsely populated areas and outside anticipated violence hotspots. Moreover, systematic measurement error of media-based event data for measuring election violence can generate significant relationships where none exist, and can result in different effect magnitudes. The article suggests areas for future research and indicates ways in which existing work on election violence may have been affected by systematic measurement error.
Non-adaptive Quantitative Group Testing Using Irregular Sparse Graph Codes

This paper considers the problem of Quantitative Group Testing (QGT) where there are some defective items among a large population of N items. We consider the scenario in which each item is defective with probability $K/N$, independently from the other items. In the QGT problem, the goal is to identify all or a sufficiently large fraction of the defective items by testing groups of items, with the minimum possible number of tests. In particular, the outcome of each test is a non-negative integer which indicates the number of defective items in the tested group. In this work, we propose a non-adaptive QGT scheme for the underlying randomized model for defective items, which utilizes sparse graph codes over irregular bipartite graphs with optimized degree profiles on the left nodes of the graph as well as binary t-error-correcting BCH codes. We show that in the sub-linear regime, i.e., when the ratio $K/N$ vanishes as N grows unbounded, the proposed scheme with $m=c(t, d) K\left(t \log \left(\frac{\ell N}{c(t, d) K}+1\right)+1\right)$ tests can identify all the defective items with probability approaching 1, where d and $\ell$ are the maximum and average left degree, respectively, and $c(t,\ d)$ depends only on t and d (and does not depend on K and N). For any $t \leq 4$, the testing and recovery algorithms of the proposed scheme have the computational complexity of $O\left(N\log\frac{N}{K}\right)$ and $O\left(K\log\frac{N}{K}\right)$, respectively. The proposed scheme outperforms two recently proposed non-adaptive QGT schemes for the sub-linear regime, including our scheme based on regular bipartite graphs and the scheme of Gebhard et al., in terms of the number of tests required to identify all defective items with high probability.
Ramanujan's influence on string theory, black holes and moonshine.

Ramanujan influenced many areas of mathematics, but his work on q-series, on the growth of coefficients of modular forms and on mock modular forms stands out for its depth and breadth of applicatio...
Generic Bounds On The Maximum Deviations In Sequential Prediction: An Information-Theoretic Analysis

In this paper, we derive generic bounds on the maximum deviations in prediction errors for sequential prediction via an information-theoretic approach. The fundamental bounds are shown to depend only on the conditional entropy of the data point to be predicted given the previous data points. In the asymptotic case, the bounds are achieved if and only if the prediction error is white and uniformly distributed.
Covariate Assisted Principal regression for covariance matrix outcomes

In this study, we consider the problem of regressing covariance matrices on associated covariates. Our goal is to use covariates to explain variation in covariance matrices across units. As such, we introduce Covariate Assisted Principal (CAP) regression, an optimization-based method for identifying components associated with the covariates using a generalized linear model approach. We develop computationally efficient algorithms to jointly search for common linear projections of the covariance matrices, as well as the regression coefficients. Under the assumption that all the covariance matrices share identical eigencomponents, we establish the asymptotic properties. In simulation studies, our CAP method shows higher accuracy and robustness in coefficient estimation over competing methods. In an example resting-state functional magnetic resonance imaging study of healthy adults, CAP identifies human brain network changes associated with subject demographics.
Irradiation Microstructure of Austenitic Steels and Cast Steels Irradiated in the BOR-60 Reactor at 320°C

Reactor internal components are subjected to neutron irradiation in light water reactors, and with the aging of nuclear power plants around the world, irradiation-induced material degradations are of concern for reactor internals. Irradiation-induced defects resulting from displacement damage are critical for understanding degradation in structural materials. In the present work, microstructural changes due to irradiation in austenitic stainless steels and cast steels were characterized using transmission electron microscopy. The specimens were irradiated in the BOR-60 reactor, a fast breeder reactor, up to ~40 dpa at ~320°C. The dose rate was approximately 9.4x10-7 dpa/s. Void swelling and irradiation defects were analyzed for these specimens. A high density of faulted loops dominated the irradiated-altered microstructures. Along with previous TEM results, a dose dependence of the defect structure was established at ~320°C.
The Influence of Perspective Taking Encouraged by the Audit Committee on Auditor and Client Judgments during Accounting Disputes

We examine the influence of an audit committee (AC) that encourages auditors (partners and managers) and clients (CFOs and controllers) to consider an accounting dispute from the other party's pers...
International linkages, technology transfer, and the skilled labor wage share: Evidence from plant-level data in Indonesia

Abstract This paper examines whether technology transfer through international linkages (such as the importing of intermediate inputs and foreign direct investments) influences skilled labor wage shares in Indonesian plants. Using a variety of specifications, estimators, and robustness checks (including Correlated Random Effects Probit, quantile fixed effects regression, and a moment-based instrumental variable (IV) approach), we find that the import of intermediate inputs and foreign direct investment likely facilitate the transfer of technologies from advanced nations, which then results in skill-biased technological change and increased relative skilled labor wage share. These results indicate that, contrary to standard trade theory predictions, international linkages can lead to increased demand for skilled labor and a potential widening of the skilled-unskilled labor wage gap in Indonesia. Our findings support the theoretical explanation provided by Acemoglu (2003). Since firms in developing countries like Indonesia mainly rely on technologies from advanced nations, trade is likely to increase (rather than decrease) the skilled wage premium.
A random walk version of Robbins' problem : small horizon

In Robbins' problem of minimizing the expected rank, a finite sequence of $n$ independent, identically distributed random variables are observed sequentially and the objective is to stop at such a time that the expected rank of the selected variable (among the sequence of all $n$ variables) is as small as possible. In this paper we consider an analogous problem in which the observed random variables are the steps of a symmetric random walk. Assuming continuously distributed step sizes, we describe the optimal stopping rules for the cases $n=2$ and $n=3$ in two versions of the problem: a "full information" version in which the actual steps of the random walk are disclosed to the decision maker; and a "partial information" version in which only the relative ranks of the positions taken by the random walk are observed. When $n=3$, the optimal rule and expected rank depend on the distribution of the step sizes. We give sharp bounds for the optimal expected rank in the partial information version, and fairly sharp bounds in the full information version.
Products of ideals in Leavitt path algebras

Ideals in Leavitt path algebras share many properties with those of integral domains. Since studying factorizations of ideals in integral domains into special types of ideals (e.g., prime, prime-po...
V2: fast detection of configuration drift in Python

Code snippets are prevalent, but are hard to reuse because they often lack an accompanying environment configuration. Most are not actively maintained, allowing for drift between the most recent possible configuration and the code snippet as the snippet becomes out-of-date over time. Recent work has identified the problem of validating and detecting out-of-date code snippets as the most important consideration for code reuse. However, determining if a snippet is correct, but simply out-of-date, is a non-trivial task. In the best case, breaking changes are well documented, allowing developers to manually determine when a code snippet contains an out-of-date API usage. In the worst case, determining if and when a breaking change was made requires an exhaustive search through previous dependency versions. We present V2, a strategy for determining if a code snippet is out-of-date by detecting discrete instances of configuration drift, where the snippet uses an API which has since undergone a breaking change. Each instance of configuration drift is classified by a failure encountered during validation and a configuration patch, consisting of dependency version changes, which fixes the underlying fault. V2 uses feedback-directed search to explore the possible configuration space for a code snippet, reducing the number of potential environment configurations that need to be validated. When run on a corpus of public Python snippets from prior research, V2 identifies 248 instances of configuration drift.
On the Habitable Lifetime of Terrestrial Worlds with High Radionuclide Abundances

The presence of a liquid solvent is widely regarded as an essential prerequisite for habitability. We investigate the conditions under which worlds outside the habitable zones of stars are capable of supporting liquid solvents on their surface over geologically significant timescales via combined radiogenic and primordial heat. Our analysis suggests that super-Earths with radionuclide abundances that are $\gtrsim 10^3$ times higher than Earth can host long-lived water oceans. In contrast, the requirements for long-lived ethane oceans, which have been explored in the context of alternative biochemistries, are less restrictive: relative radionuclide abundances of $\gtrsim 10^2$ could be sufficient. We find that this class of worlds might be detectable ($10\sigma$ detection over $\sim 10$ days integration time at $12.8$ $\mu$m) in principle by the James Webb Space Telescope at distances of $\sim 10$ pc if their ages are $\lesssim 1$ Gyr.
Semi-supervised learning approaches to class assignment in ambiguous microstructures

Abstract Uncovering links between processing conditions, microstructure, and properties is a central tenet of materials analysis. It is well known that microstructure determines properties, but expressing these structural features in a universal quantitative fashion has proved to be extremely difficult. Recent efforts have focused on training supervised learning algorithms to place microstructure images into predefined classes, but this approach assumes a level of a priori knowledge that may not always be available. In this paper, we expand this idea to the semi-supervised context in which class labels are known with confidence for only a fraction of the microstructures that represent the material system. It is shown that classifiers which perform well on both the high-confidence labeled data and the unlabeled, ambiguous data can be constructed by relying on the labeling consensus of a collection of semi-supervised learning methods. We also demonstrate the use of novel error estimation approaches for unlabeled data to establish robust confidence bounds on the classification performance over the entire microstructure space.
Matching Is as Easy as the Decision Problem, in the NC Model

Is matching in NC, i.e., is there a deterministic fast parallel algorithm for it? This has been an outstanding open question in TCS for over three decades, ever since the discovery of randomized NC matching algorithms [Karp et al., 1985; Mulmuley et al., 1987]. Over the last five years, the theoretical computer science community has launched a relentless attack on this question, leading to the discovery of several powerful ideas. We give what appears to be the culmination of this line of work: An NC algorithm for finding a minimum-weight perfect matching in a general graph with polynomially bounded edge weights, provided it is given an oracle for the decision problem. Consequently, for settling the main open problem, it suffices to obtain an NC algorithm for the decision problem. We believe this new fact has qualitatively changed the nature of this open problem. All known efficient matching algorithms for general graphs follow one of two approaches: given by [Edmonds, 1965] and [Lovasz, 1979]. Our oracle-based algorithm follows a new approach and uses many of ideas discovered in the last five years. The difficulty of obtaining an NC perfect matching algorithm led researchers to study matching vis-a-vis clever relaxations of the class NC. In this vein, recently [Goldwasser and Grossman, 2015] gave a pseudo-deterministic RNC algorithm for finding a perfect matching in a bipartite graph, i.e., an RNC algorithm with the additional requirement that on the same graph, it should return the same (i.e., unique) perfect matching for almost all choices of random bits. A corollary of our reduction is an analogous algorithm for general graphs.
Global Imbalances and Policy Wars at the Zero Lower Bound

This paper explores the consequences of extremely low real interest rates in a world with integrated but heterogenous capital markets and nominal rigidities. We establish four main results: (i) Liquidity traps spread to the rest of the world through the current account, which we illustrate with a new Metzler diagram in quantities; (ii) Beggar-thy-neighbor currency and trade wars provide stimulus to the undertaking country at the expense of other countries; (iii) (Safe) public debt issuances and increases in government spending anywhere are expansionary everywhere; (iv) At the ZLB, net issuers of safe assets experience a disproportionate share of the global stagnation.
Multi-Dimensional Spatially-Coupled Code Design: Enhancing the Cycle Properties

A circulant-permutation-based spatially-coupled (SC) code is constructed by partitioning the circulant permutation matrices (CPMs) in the parity-check matrix of a block code into several components and piecing copies of these components in a diagonal structure. By connecting several SC codes, multi-dimensional SC (MD-SC) codes are constructed. In this paper, we present a systematic framework for constructing MD-SC codes with notably better cycle properties than their one-dimensional counterparts. In our framework, the multi-dimensional coupling is performed via an informed relocation of problematic CPMs. This work is general in the terms of the number of constituent SC codes that are connected together, the number of neighboring SC codes that each constituent SC code is connected to, and the length of the cycles whose populations we aim to reduce. Finally, we present a decoding algorithm that utilizes the structures of the MD-SC code to achieve lower decoding latency. Compared to the conventional SC codes, our MD-SC codes have a notably lower population of small cycles, and a dramatic BER improvement. The results of this work can be particularly beneficial in data storage systems, e.g., 2D magnetic recording and 3D Flash systems, as high-performance MD-SC codes are robust against various channel impairments and non-uniformity.
Alpha-synuclein-induced mitochondrial dysfunction is mediated via a sirtuin 3-dependent pathway

Misfolding and aggregation of the presynaptic protein alpha-synuclein (αsyn) is a hallmark of Parkinson’s disease (PD) and related synucleinopathies. Although predominantly localized in the cytosol, a body of evidence has shown that αsyn localizes to mitochondria and contributes to the disruption of key mitochondrial processes. Mitochondrial dysfunction is central to the progression of PD and mutations in mitochondrial-associated proteins are found in familial cases of PD. The sirtuins are highly conserved nicotinamide adenine dinucleotide (NAD+)-dependent enzymes that play a broad role in cellular metabolism and aging. Interestingly, mitochondrial sirtuin 3 (SIRT3) plays a major role in maintaining mitochondrial function and preventing oxidative stress, and is downregulated in aging and age-associated diseases such as neurodegenerative disorders. Herein, we hypothesize that αsyn is associated with decreased SIRT3 levels contributing to impaired mitochondrial dynamics and biogenesis in PD. The level of mitochondrial SIRT3 was assessed in cells expressing oligomeric αsyn within the cytosolic and mitochondrial-enriched fractions. Mitochondrial integrity, respiration, and health were examined using several markers of mitochondrial dynamics and stress response and by measuring the rate of oxygen consumption (OCR). Our findings were validated in a rodent model of PD as well as in human post-mortem Lewy body disease (LBD) brain tissue. Here, we demonstrate that αsyn associates with mitochondria and induces a decrease in mitochondrial SIRT3 levels and mitochondrial biogenesis. We show that SIRT3 downregulation is accompanied by decreased phosphorylation of AMPK and cAMP-response element binding protein (CREB), as well as increased phosphorylation of dynamin-related protein 1 (DRP1), indicative of impaired mitochondrial dynamics. OCR was significantly decreased suggesting a mitochondria respiratory deficit. Interestingly treatment with AMPK agonist 5-aminoimidazole-4-carboxamide-1-β-d-ribofuranoside (AICAR) restores SIRT3 expression, improves mitochondrial function, and decreases αsyn oligomer formation in a SIRT3-dependent manner. Together, our findings suggest that pharmacologically increasing SIRT3 levels can counteract αsyn-induced mitochondrial dysfunction by reducing αsyn oligomers and normalizing mitochondrial bioenergetics. These data support a protective role for SIRT3 in PD-associated pathways and contribute significant mechanistic insight into the interplay of SIRT3 and αsyn.
The Proximity of Communities to the Expanse of Big Data

While individuals living near or on archaeological sites have frequently been hired around the world to dig on archaeological excavations, they have very rarely participated in the recording or doc...
Integrating AI into radiology workflow: levels of research, production, and feedback maturity.

We present a roadmap for integrating artificial intelligence (AI)-based image analysis algorithms into existing radiology workflows such that (1) radiologists can significantly benefit from enhanced automation in various imaging tasks due to AI, and (2) radiologists’ feedback is utilized to further improve the AI application. This is achieved by establishing three maturity levels where (1) research enables the visualization of AI-based results/annotations by radiologists without generating new patient records; (2) production allows the AI-based system to generate results stored in an institution’s picture-archiving and communication system; and (3) feedback equips radiologists with tools for editing the AI inference results for periodic retraining of the deployed AI systems, thereby allowing continuous organic improvement of AI-based radiology-workflow solutions. A case study (i.e., detection of brain metastases with T1-weighted contrast-enhanced three-dimensional MRI) illustrates the deployment details of a particular AI-based application according to the aforementioned maturity levels. It is shown that the given AI application significantly improves with feedback coming from radiologists; the number of incorrectly detected brain metastases (false positives) decreases from 14.2 to 9.12 per patient with the number of subsequently annotated datasets increasing from 93 to 217 as a result of radiologist adjudication.
Lite Transformer with Long-Short Range Attention

Transformer has become ubiquitous in natural language processing (e.g., machine translation, question answering); however, it requires enormous amount of computations to achieve high performance, which makes it not suitable for mobile applications since mobile phones are tightly constrained by the hardware resources and battery. In this paper, we investigate the mobile setting (under 500M Mult-Adds) for NLP tasks to facilitate the deployment on the edge devices. We present Long-Short Range Attention (LSRA), where one group of heads specializes in the local context modeling (by convolution) while another group captures the long-distance relationship (by attention). Based on this primitive, we design Lite Transformer that is tailored for the mobile NLP application. Our Lite Transformer demonstrates consistent improvement over the transformer on three well-established language tasks: machine translation, abstractive summarization, and language modeling. It outperforms the transformer on WMT’14 English-French by 1.2 BLEU under 500M Mult-Adds and 1.7 BLEU under 100M Mult-Adds, and reduces the computation of transformer base model by 2.5x. Further, with general techniques, our Lite Transformer achieves 18.2x model size compression. For language modeling, our Lite Transformer also achieves 3.8 lower perplexity than the transformer around 500M Mult-Adds. Without the costly architecture search that requires more than 250 GPU years, our Lite Transformer outperforms the AutoML-based Evolved Transformer by 0.5 higher BLEU under the mobile setting.
GRAPH IMMERSIONS, INVERSE MONOIDS AND DECK TRANSFORMATIONS

If is a covering map between connected graphs, and is the subgroup of used to construct the cover, then it is well known that the group of deck transformations of the cover is isomorphic to , where is the normalizer of in . We show that an entirely analogous result holds for immersions between connected graphs, where the subgroup is replaced by the closed inverse submonoid of the inverse monoid used to construct the immersion. We observe a relationship between group actions on graphs and deck transformations of graph immersions. We also show that a graph immersion may be extended to a cover in such a way that all deck transformations of are restrictions of deck transformations of .
Development of a High-Rate Front-End ASIC for X-Ray Spectroscopy and Diffraction Applications

We developed a new front-end application-specific integrated circuit (ASIC) to upgrade the Maia X-ray microprobe. The ASIC instruments 32 configurable channels that perform either positive or negative charge amplification, pulse shaping, peak amplitude, and time extraction along with buffered analog storage. At a gain of 3.6 V/fC, 1- $\mu \text{s}$ peaking time, and a temperature of 248 K, an electronic resolution of 13 and 10 $e^{-}$ rms was measured with and without a silicon drift detector (SDD) sensor, respectively. A spectral resolution of 170-eV full-width at half-maximum (FWHM) at 5.9 keV was obtained with an 55Fe source. The channel linearity was better than ± 1 % with rate capabilities up to 40 kcps. The ASIC was fabricated in a commercial 250-nm process with a footprint of 6.3 mm $\times $ 3.9 mm and dissipates 167 mW of static power.
Universal surgery problems with trivial Lagrangian

We study the effect of Nielsen moves and their geometric counterparts, handle slides, on good boundary links. A collection of links, universal for 4-dimensional surgery, is shown to admit Seifert surfaces with trivial Lagrangian. They are good boundary links, with Seifert matrices of a more general form than in known constructions of slice links. We show that a certain more restrictive condition on Seifert matrices is sufficient for proving the links are slice. We also give a correction of a Kirby calculus identity in \cite{FK2}, useful for constructing surgery kernels associated to link-slice problems.
Robust Multi-Channel Speech Recognition Using Frequency Aligned Network

Conventional speech enhancement technique such as beamforming has known benefits for far-field speech recognition. Our own work in frequency-domain multi-channel acoustic modeling has shown additional improvements by training a spatial filtering layer jointly within an acoustic model. In this paper, we further develop this idea and use frequency aligned network for robust multi-channel automatic speech recognition (ASR). Unlike an affine layer in the frequency domain, the proposed frequency aligned component prevents one frequency bin influencing other frequency bins. We show that this modification not only reduces the number of parameters in the model but also significantly and improves the ASR performance. We investigate effects of frequency aligned network through ASR experiments on the real-world far-field data where users are interacting with an ASR system in uncontrolled acoustic environments. We show that our multi-channel acoustic model with a frequency aligned network shows up to 18% relative reduction in word error rate.
Inference With Deep Generative Priors in High Dimensions

Deep generative priors offer powerful models for complex-structured data, such as images, audio, and text. Using these priors in inverse problems typically requires estimating the input and/or hidden signals in a multi-layer deep neural network from observation of its output. While these approaches have been successful in practice, rigorous performance analysis is complicated by the non-convex nature of the underlying optimization problems. This paper presents a novel algorithm, Multi-Layer Vector Approximate Message Passing (ML-VAMP), for inference in multi-layer stochastic neural networks. ML-VAMP can be configured to compute maximum a priori (MAP) or approximate minimum mean-squared error (MMSE) estimates for these networks. We show that the performance of ML-VAMP can be exactly predicted in a certain high-dimensional random limit. Furthermore, under certain conditions, ML-VAMP yields estimates that achieve the minimum (i.e., Bayes-optimal) MSE as predicted by the replica method. In this way, ML-VAMP provides a computationally efficient method for multi-layer inference with an exact performance characterization and testable conditions for optimality in the large-system limit.
Noncommutative Gravity and the Standard-Model Extension

Noncommutative geometry has become popular mathematics for describing speculative physics beyond the Standard Model. Noncommutative QED has long been known to fit within the framework of the Standard-Model Extension (SME). We argue in this work that noncommutative gravity also fits within the SME framework.
Trends in Symbiont-Induced Host Cellular Differentiation.

Bacteria participate in a wide diversity of symbiotic associations with eukaryotic hosts that require precise interactions for bacterial recognition and persistence. Most commonly, host-associated bacteria interfere with host gene expression to modulate the immune response to the infection. However, many of these bacteria also interfere with host cellular differentiation pathways to create a hospitable niche, resulting in the formation of novel cell types, tissues, and organs. In both of these situations, bacterial symbionts must interact with eukaryotic regulatory pathways. Here, we detail what is known about how bacterial symbionts, from pathogens to mutualists, control host cellular differentiation across the central dogma, from epigenetic chromatin modifications, to transcription and mRNA processing, to translation and protein modifications. We identify four main trends from this survey. First, mechanisms for controlling host gene expression appear to evolve from symbionts co-opting cross-talk between host signaling pathways. Second, symbiont regulatory capacity is constrained by the processes that drive reductive genome evolution in host-associated bacteria. Third, the regulatory mechanisms symbionts exhibit correlate with the cost/benefit nature of the association. And, fourth, symbiont mechanisms for interacting with host genetic regulatory elements are not bound by native bacterial capabilities. Using this knowledge, we explore how the ubiquitous intracellular Wolbachia symbiont of arthropods and nematodes may modulate host cellular differentiation to manipulate host reproduction. Our survey of the literature on how infection alters gene expression in Wolbachia and its hosts revealed that, despite their intermediate-sized genomes, different strains appear capable of a wide diversity of regulatory manipulations. Given this and Wolbachia’s diversity of phenotypes and eukaryotic-like proteins, we expect that many symbiont-induced host differentiation mechanisms will be discovered in this system.
An Unbiased Drug Screen for Seizure Suppressors in Duplication 15q Syndrome Reveals 5-HT1A and Dopamine Pathway Activation as Potential Therapies

Abstract Background Duplication 15q (Dup15q) syndrome is a rare neurogenetic disorder characterized by autism and pharmacoresistant epilepsy. Most individuals with isodicentric duplications have been on multiple medications to control seizures. We recently developed a model of Dup15q in Drosophila by elevating levels of fly Dube3a in glial cells using repo-GAL4, not neurons. In contrast to other Dup15q models, these flies develop seizures that worsen with age. Methods We screened repo>Dube3a flies for approved compounds that can suppress seizures. Flies 3 to 5 days old were exposed to compounds in the fly food during development. Flies were tested using a bang sensitivity assay for seizure recovery time. At least 40 animals were tested per experiment, with separate testing for male and female flies. Studies of K+ content in glial cells of the fly brain were also performed using a fluorescent K+ indicator. Results We identified 17 of 1280 compounds in the Prestwick Chemical Library that could suppress seizures. Eight compounds were validated in secondary screening. Four of these compounds regulated either serotonergic or dopaminergic signaling, and subsequent experiments confirmed that seizure suppression occurred primarily through stimulation of serotonin receptor 5-HT1A. Additional studies of K+ levels showed that Dube3a regulation of the Na+/K+ exchanger ATPα (adenosine triphosphatase α) in glia may be modulated by serotonin/dopamine signaling, causing seizure suppression. Conclusions Based on these pharmacological and genetic studies, we present an argument for the use of 5-HT1A agonists in the treatment of Dup15q epilepsy.
Husserlian phenomenology in Korean nursing research: analysis, problems, and suggestions.

Purpose This paper is a critical review of the descriptive phenomenological methodology in Korean nursing research. We propose constructive suggestions for the improvement of descriptive phenomenological methodology in light of Husserl's phenomenological approaches. Methods Using the keywords of 'phenomenology,' 'experience,' and 'nursing,' we identify and analyze 64 Korean empirical phenomenological studies (selected from 282 studies) published in 14 Korean nursing journals from 2005 to 2018. The PubMed and the Korea Citation Index were used to identify the studies. Results Our analysis shows that all the reviewed articles used Giorgi's or Colaizzi's scientific phenomenological methodology, without critical attention to Husserl's philosophical phenomenological principles. Conclusions The use of scientific phenomenology in nursing research, which originated in North America, has become a global phenomenon, and Korean phenomenological nursing research has faithfully followed this scholarly trend. This paper argues that greater integration of Husserlian phenomenological principles into scientific phenomenological methodology in nursing research, such as participant-centered bracketing and eidetic reduction, is needed to ensure that scientific phenomenology lives up to its promise as a research methodology.
A road paved with good intentions?: FERC’s illegal war on state electricity subsidies

Abstract Most initial reviews of FERC’s order have offered scathing criticism of its negative policy consequences. Our critique adds two perspectives not represented thus far in the reaction to FERC’s order. First, we explain how the FERC majority got to the point where it felt compelled to take action against state subsidies and why that judgment, although understandable in some respects, is misguided. FERC’s action follows logically from a flawed policy adopted by a Democratic-majority Commission in 2011. Second, we explain why FERC’s order fails to create a mechanism for a just and reasonable price and violates both the Administrative Procedure Act and Federal Power Act. It is therefore likely to be set aside by a court during the judicial review process.
Measures of Association

Measures of association are numerical estimates of the magnitude of the statistical dependence between two variables, especially if these variables are categorical. A multitude of such measures have been proposed; we review some of the most commonly used ones, dividing them into two types. The first is suitable for nominal scale data, and includes measures of predictive association. The second type is suitable for ordinal data, and includes measures of concordance-discordance. Keywords: nominal data; ordinal data; categorical data; correlation; concordance-discordance; tau
Democratization and civil war

This article examines the impact of civil war on democratization, particularly focusing on whether civil war provides an opportunity for institutional reform. We investigate the impact of war termination in general, along with prolonged violence, rebel victory and international intervention on democratization. Using an unbalanced panel data set of 96 countries covering a 34-year period, our analysis suggests that civil war lowers democratization in the succeeding period. Our findings also suggest that United Nations intervention increases democratization, as do wars ending in stalemates. However, wars ending in rebel victories seem to reduce democratization. These findings appear robust to conditioning, different instrument sets, modelling techniques and the measurement of democracy.
Neighborhoods and Academic Achievement: Results from the Moving to Opportunity Experiment

Families originally living in public housing were assigned housing vouchers by lottery, encouraging moves to neighborhoods with lower poverty rates. Although we had hypothesized that reading and math test scores would be higher among children in families offered vouchers (with larger effects among younger children), the results show no significant effects on test scores for any age group among over 5000 children ages 6 to 20 in 2002 who were assessed four to seven years after randomization. Program impacts on school environments were considerably smaller than impacts on neighborhoods, suggesting that achievement-related benefits from improved neighborhood environments are small.
Tropical hyperelliptic curves in the plane

Abstractly, tropical hyperelliptic curves are metric graphs that admit a two-to-one harmonic morphism to a tree. They also appear as embedded tropical curves in the plane arising from triangulations of polygons with all interior lattice points collinear. We prove that hyperelliptic graphs can only arise from such polygons. Along the way, we will prove certain graphs do not embed tropically in the plane due to entirely combinatorial obstructions, regardless of whether their metric is actually hyperelliptic.