cssi/SciSciGPT-SciSciNet huggingface dataset:
An Imprint of the Galactic Magnetic Field in the Diffuse Unpolarized Dust Emission

It is well known that aligned, aspherical dust grains emit polarized radiation and that the degree of polarization depends on the angle ψ between the interstellar magnetic field and the line of sight. However, anisotropy of the dust absorption cross sections also modulates the total intensity of the radiation as the viewing geometry changes. We report a detection of this effect in the high Galactic latitude Planck data, finding that the 353 GHz dust intensity per N_(HI) is smaller when the Galactic magnetic field is mostly in the plane of the sky and larger when the field is mostly along the line of sight. These variations are of opposite sign and roughly equal magnitude as the changes in polarized intensity per N_(HI) with ψ, as predicted. In principle, the variation in intensity can be used in conjunction with the dust polarization angle to constrain the full 3D orientation of the Galactic magnetic field.
4d $ \mathcal{N} $ =2 theories with disconnected gauge groups

In this paper we present a beautifully consistent web of evidence for the existence of interacting 4d rank-1 $$ \mathcal{N} $$ = 2 SCFTs obtained from gauging discrete subgroups of global symmetries of other existing 4d rank-1 $$ \mathcal{N} $$ = 2 SCFTs. The global symmetries that can be gauged involve a non-trivial combination of discrete subgroups of the U(1) R , low-energy EM duality group $$ \mathrm{S}\mathrm{L}\left(2,\kern0.5em \mathbb{Z}\right) $$ , and the outer automorphism group of the flavor symmetry algebra, Out(F ). The theories that we construct are remarkable in many ways: (i) two of them have exceptional F 4 and G 2 flavor groups; (ii) they substantially complete the picture of the landscape of rank-1 $$ \mathcal{N} $$ = 2 SCFTs as they realize all but one of the remaining consistent rank-1 Seiberg-Witten geometries that we previously constructed but were not associated to known SCFTs; and (iii) some of them have enlarged $$ \mathcal{N} $$ = 3 SUSY, and have not been previously constructed. They are also examples of SCFTs which violate the ShapereTachikawa relation between the conformal central charges and the scaling dimension of the Coulomb branch vev. We propose a modification of the formulas computing these central charges from the topologically twisted Coulomb branch partition function which correctly compute them for discretely gauged theories.
Semigroups, Rings, and Markov Chains

We analyze random walks on a class of semigroups called “left-regular bands.” These walks include the hyperplane chamber walks of Bidigare, Hanlon, and Rockmore. Using methods of ring theory, we show that the transition matrices are diagonalizable and we calculate the eigenvalues and multiplicities. The methods lead to explicit formulas for the projections onto the eigenspaces. As examples of these semigroup walks, we construct a random walk on the maximal chains of any distributive lattice, as well as two random walks associated with any matroid. The examples include a q-analogue of the Tsetlin library. The multiplicities of the eigenvalues in the matroid walks are “generalized derangement numbers,” which may be of independent interest.
Impact of Audiovisual-Assisted Therapeutic Ambience in Radiation Therapy (AVATAR) on Anesthesia Use, Payer Charges, and Treatment Time in Pediatric Patients.

Abstract Purpose Pediatric radiation therapy (RT) requires optimal immobilization that often necessitates daily anesthesia. To decrease anesthesia use, we implemented a novel audiovisual-assisted therapeutic ambience in RT (AVATAR) system that projects video onto a radiolucent screen within the child's line of vision to provide attentional diversion. We investigated its reduction on anesthesia use, payer charges, and treatment time, in addition to its impact on radiation delivery. Methods and Materials A 6-year retrospective analysis was performed among children undergoing RT (n = 224) 3 years before and 3 years after the introduction of AVATAR. The frequency of anesthesia use before and after AVATAR implementation, in addition to RT treatment times, were compared. The number of spared anesthesia treatments allowed for a charge to payer analysis. To document the lack of surface dose perturbation by AVATAR, a phantom craniospinal treatment course was delivered both with and without AVATAR. Additionally, an ion chamber course was delivered to document changes to the dose at depth. Results More children were able to avoid anesthesia use entirely in the post-AVATAR cohort compared with the pre-AVATAR cohort (73.2% vs 63.4%; P = .03), and fewer required anesthesia for each treatment (18.8% vs 33%; P = .03). AVATAR introduction reduced anesthesia use for all ages studied. Treatment time per session was reduced by 38% using AVATAR compared with anesthesia. There were 326 fewer anesthesia sessions delivered over 3 years after AVATAR was introduced, with an estimated savings of >$500,000. Optically stimulated luminescent dosimeters revealed a small increase in dose of 0.8% to 9.5% with AVATAR, whereas the use of a thermomolded face mask increased skin dose by as much as 58%. Conclusions AVATAR introduction decreased anesthesia use in children undergoing RT. More children avoided anesthesia entirely, and fewer needed anesthesia for every treatment, resulting in a reduction in treatment time and savings of nearly $550,000 in approximately 3 years, with minimal perturbation of RT dose delivery.
Property inference for deep neural networks

We present techniques for automatically inferring formal properties of feed-forward neural networks. We observe that a significant part (if not all) of the logic of feed forward networks is captured in the activation status (on or off) of its neurons. We propose to extract patterns based on neuron decisions as preconditions that imply certain desirable output property e.g., the prediction being a certain class. We present techniques to extract input properties, encoding convex predicates on the input space that imply given output properties and layer properties, representing network properties captured in the hidden layers that imply the desired output behavior. We apply our techniques on networks for the MNIST and ACASXU applications. Our experiments highlight the use of the inferred properties in a variety of tasks, such as explaining predictions, providing robustness guarantees, simplifying proofs, and network distillation.
The Age-Period-Cohort-Interaction Model for Describing and Investigating Inter-cohort Deviations and Intra-cohort Life-course Dynamics

Social scientists have frequently sought to understand the distinct effects of age, period, and cohort, but disaggregation of the three dimensions is difficult because cohort = period − age. We arg...
Polling-Systems-Based Autonomous Vehicle Coordination in Traffic Intersections With No Traffic Signals

As autonomous vehicle technology advances rapidly, the design and operation of networks composed of fully autonomous vehicles have attracted immense interest. It is widely anticipated that fully autonomous vehicle networks will drastically improve performance. In this paper, we consider a widely studied problem, in which autonomous vehicles arriving at an intersection adjust their speeds to traverse the intersection as rapidly as possible, while avoiding collisions. We propose a coordination control algorithm, assuming stochastic models for the arrival times of the vehicles. The proposed algorithm extends the widely studied polling systems analysis to the case involving customers subject to second-order differential constraints. We provide provable guarantees on 1) safety, no collisions occur surely, and 2) performance, rigorous bounds on the expected delay. We also provide a stability analysis for the resulting queueing system. We demonstrate the algorithm in an extensive simulation study, providing one to two orders of magnitude improvement in delays over the traditional traffic light.
Noncompact complete Riemannian manifolds with singular continuous spectrum embedded into the essential spectrum of the Laplacian, I. The hyperbolic case

We construct Riemannian manifolds with singular continuous spectrum embedded in the absolutely continuous spectrum of the Laplacian. Our manifolds are asymptotically hyperbolic with sharp curvature bounds.
Molecular and cellular determinants of motor asymmetry in zebrafish

Asymmetries in motor behavior, such as human hand preference, are observed throughout bilateria. However, neural substrates and developmental signaling pathways that impose underlying functional lateralization on a broadly symmetric nervous system are unknown. Here we report that in the absence of over-riding visual information, zebrafish larvae show intrinsic lateralized motor behavior that is mediated by a cluster of 60 posterior tuberculum (PT) neurons in the forebrain. PT neurons impose motor bias via a projection through the habenular commissure. Acquisition of left/right identity is disrupted by heterozygous mutations in mosaic eyes and mindbomb, genes that regulate Notch signaling. These results define the neuronal substrate for motor asymmetry in a vertebrate and support the idea that haploinsufficiency for genes in a core developmental pathway destabilizes left/right identity.
Human Capital as Engine of Growth: The Role of Knowledge Transfers in Promoting Balanced Growth within and across Countries

Unlike physical capital, human capital has both embodied and disembodied dimensions. It can be perceived not only as skill and acquired knowledge but also as knowledge spillover effects between ove...
pH-Dependent Grafting of Cancer Cells with Antigenic Epitopes Promotes Selective Antibody-Mediated Cytotoxicity

A growing class of immunotherapeutics work by redirecting components of the immune system to recognize markers on the surface of cancer cells. However, such modalities will remain confined to a relatively small subgroup of patients because of the lack of universal targetable tumor biomarkers among all patients. Here, we designed a unique class of agents that exploit the inherent acidity of solid tumors to selectively graft cancer cells with immuno-engager epitopes. Our targeting approach is based on pHLIP, a unique peptide that selectively targets tumors in vivo by anchoring to cancer cell surfaces in a pH-dependent manner. We established that pHLIP-antigen conjugates trigger the recruitment of antibodies to the surface of cancer cells and induce cytotoxicity by peripheral blood mononuclear and engineered NK cells. These results indicate that these agents have the potential to be applicable to treating a wide range of solid tumors and to circumvent problems associated with narrow windows of selectivity.
Inverse Designed Metalenses with Extended Depth of Focus

We design, fabricate and characterize a cylindrical metasurface lens operating at ∼ 625nm with a depth of focus exceeding that of an ordinary lens using adjoint optimization-based inverse electromagnetic design.
Two weight inequalities for positive operators: doubling cubes

For the maximal operator M on Rd, and 1<p,ρ<∞, there is a finite constant D=Dp,ρ so that this holds. For all weights w,σ on Rd, the operator M(σ⋅) is bounded from Lp(σ)→Lp(w) if and only if the pair of weights (w,σ) satisfy the two weight Ap condition, and this testing inequality holds: ∫QM(σ1Q)pdw≲σ(Q), for all cubes Q for which there is a cube P⊃Q satisfying σ(P)≤Dσ(Q), and l(P)≥ρl(Q). This was recently proved by Kangwei Li and Eric Sawyer. We give a short proof, which is easily seen to hold for several closely related operators.
Dual-Path RNN: Efficient Long Sequence Modeling for Time-Domain Single-Channel Speech Separation

Recent studies in deep learning-based speech separation have proven the superiority of time-domain approaches to conventional time-frequency-based methods. Unlike the time-frequency domain approaches, the time-domain separation systems often receive input sequences consisting of a huge number of time steps, which introduces challenges for modeling extremely long sequences. Conventional recurrent neural networks (RNNs) are not effective for modeling such long sequences due to optimization difficulties, while one-dimensional convolutional neural networks (1-D CNNs) cannot perform utterance-level sequence modeling when its receptive field is smaller than the sequence length. In this paper, we propose dual-path recurrent neural network (DPRNN), a simple yet effective method for organizing RNN layers in a deep structure to model extremely long sequences. DPRNN splits the long sequential input into smaller chunks and applies intra- and inter-chunk operations iteratively, where the input length can be made proportional to the square root of the original sequence length in each operation. Experiments show that by replacing 1-D CNN with DPRNN and apply sample-level modeling in the time-domain audio separation network (TasNet), a new state-of-the-art performance on WSJ0-2mix is achieved with a 20 times smaller model than the previous best system.
Intrinsic diophantine approximation in Carnot groups and in the Siegel model of the Heisenberg group

We study an intrinsic notion of Diophantine approximation on a rational Carnot group G. If G has Hausdorff dimension Q, we show that its Diophantine exponent is equal to $$(Q+1)/Q$$, generalizing the case $$G=\mathbb {R}^n$$. We furthermore obtain a precise asymptotic on the count of rational approximations. We then focus on the case of the Heisenberg group $$\mathbf {H}^n$$, distinguishing between two notions of Diophantine approximation by rational points in $$\mathbf {H}^n$$: Carnot Diophantine approximation and Siegel Diophantine approximation. We provide a direct proof that the Siegel Diophantine exponent of $$\mathbf {H}^1$$ is equal to 1, confirming the general result of Hersonsky-Paulin, and then provide a link between Siegel Diophantine approximation, Heisenberg continued fractions, and geodesics in the Picard modular surface. We conclude by showing that Carnot and Siegel approximation are qualitatively different: Siegel-badly approximable points are Schmidt winning in any complete Ahlfors regular subset of $$\mathbf {H}^n$$, while the set of Carnot-badly approximable points does not have this property.
Impact of online course discussion on education leadership students’ reflections

Educators learn through reflection on how power shapes their own practices, expressing their concerns about the constraints they face, and brainstorming solutions to address them. Educators create and adjust their philosophies and practices by reflecting on how abstract theories manifest themselves in life. The online discussion format affords students the opportunity to improve their reflective practices through the use of structured questions, supervised scaffolding, shared experience, and opportunities to connect theory to practice. In essence, online discussions offer educators a dynamic and energetic atmosphere in which they can interact with each other. The purpose of the study was to examine the impact of online discussions on students’ critical skills as they reflect on issues dealing with students’ diversity. The results demonstrated that the use of structured online discussions contributed to the elevation of graduate students’ reflective practices as they contemplated the social and cultural issues that impact students’ learning and their educational practices.
History of Factor Analysis: A Psychological Perspective†

The history of unrestricted (exploratory) factor analysis is briefly reviewed from the perspective of its contribution to psychological theory, particularly models of mental abilities. Attention is focused on the contributions of Spearman and Thurstone. Various means of judging the quality of a factor solution are described. The logic of factor analysis as a means of identifying meaningful psychological constructs from a matrix of correlations is introduced from the algebraic and geometric perspectives. Keywords: exploratory; factor analysis; history; psychometric perspective; unrestricted
Ionization probability of sputtered atoms

The ionization probability of atoms sputtered from metal surfaces is discussed with the use of an approach of Blandin, Nourtier, and Hone. A general expression is obtained for this probability for the case in which the energy position of the sputtered-atom valence level has a linear dependence on distance and the atom velocity is constant. A limiting form of this expression was given by Brako and Newns; this limiting form is very useful in analyzing the higher-velocity part of the data obtained by Yu for O/sup -/ sputtered from transition-metal surfaces. Analysis of the lower-velocity part of the data proceeds by the combination of the more general formulation of the theory with a very simple trajectory determined on the basis of a Morse-potential interaction between the sputtered adatom and the substrate atom which strikes it. A good account of Yu's experimental data is obtained with the use of parameter values determined solely from measurements and calculations of the ground-state properties of oxygen adsorbed on metal surfaces.
Phonon anharmonicity in silicon from 100 to 1500 K

Inelastic neutron scattering was performed on silicon powder to measure the phonon density of states (DOS) from 100 to 1500 K. The mean fractional energy shifts with temperature of the modes were $\ensuremath{\langle}\ensuremath{\Delta}{\ensuremath{\varepsilon}}_{i}/{\ensuremath{\varepsilon}}_{i}\ensuremath{\Delta}T\ensuremath{\rangle}=\ensuremath{-}0.07$, giving a mean isobaric Gr\"uneisen parameter of $+6.95\ifmmode\pm\else\textpm\fi{}0.67$, which is significantly different from the isothermal parameter of +0.98. These large effects are beyond the predictions from quasiharmonic models using density functional theory or experimental data, demonstrating large effects from phonon anharmonicity. At 1500 K the anharmonicity contributes $0.15{k}_{\mathrm{B}}$/atom to the vibrational entropy, compared to $0.03{k}_{\mathrm{B}}$/atom from quasiharmonicity. Excellent agreement was found between the entropy from phonon DOS measurements and the reference NIST-JANAF thermodynamic entropy from calorimetric measurements.
CROSSMODAL AND MULTISENSORY INTERACTIONS BETWEEN VISION AND TOUCH.

Over the past two decades, there has been growing appreciation of the multisensory nature of perception and its neural basis. Consequently, the concept has arisen that the brain is “metamodal”, with a task-based rather than strictly modality-based organization (Pascual-Leone & Hamilton, 2001; Lacey et al., 2009a; James et al., 2011). Here we focus on interactions between vision and touch in humans, including crossmodal interactions where tactile inputs evoke activity in neocortical regions traditionally considered visual, and multisensory integrative interactions. It is now established that cortical areas in both the ventral and dorsal pathways, previously identified as specialized for various aspects of visual processing, are also routinely recruited during the corresponding aspects of touch (for reviews see Amedi et al., 2005; Sathian & Lacey, 2007; Lacey & Sathian, 2011, 2014). When these regions are in classical visual cortex so that they would traditionally be regarded as unisensory, their engagement is referred to as crossmodal, whereas other regions lie in classically multisensory sectors of the association neocortex. Much of the relevant work concerns haptic perception (active sensing using the hand) of shape; this work is therefore considered in detail. We consider how vision and touch might be integrated in various situations and address the role of mental imagery in visual cortical activity during haptic perception. Finally, we present a model of haptic object recognition and its relationship with mental imagery (Lacey et al., 2014).
Discounting Pension Liabilities: Funding versus Value

We argue that the appropriate discount rate for pension liabilities depends on the objective. In particular, if the objective is to measure pension under- or overfunding, a default-free discount rate should always be used, even if the liabilities are themselves not default-free. If, instead, the objective is to determine the market value of pension benefits, then it is appropriate that discount rates incorporate default risk. We also discuss the choice of a default-free discount rate. Finally, we show how cost-of-living adjustments that are common in public pensions can be accounted for and valued in this framework.
Alignment at Work: Using Language to Distinguish the Internalization and Self-Regulation Components of Cultural Fit in Organizations

Author(s): Doyle, Gabriel; Srivastava, Sameer B.; Goldberg, Amir; Frank, Michael C. | Abstract: Cultural fit is widely believed to affect the success of individuals and the groups to which they belong. Yet it remains an elusive, poorly measured construct. Recent research draws on computational linguistics to measure cultural fit but overlooks asymmetries in cultural adaptation. By contrast, we develop a directed, dynamic measure of cultural fit based on linguistic alignment, which estimates the influence of one person’s word use on another’s and distinguishes between two enculturation mechanisms: internalization and selfregulation. We use this measure to trace employees’ enculturation trajectories over a large, multi-year corpus of corporate emails and find that patterns of alignment in the first six months of employment are predictive of individuals downstream outcomes, especially involuntary exit. Further predictive analyses suggest referential alignment plays an overlooked role in linguistic alignment.
STRUCTURAL WEB SEARCH ENGINE

We present a new approach in web search engines. The web creates new challenges for information retrieval. The vast improvement in information access is not the only advantage resulting from the keyword search. Additionally, much potential exists for analyzing interests and relationships within the structure of the web. The creation of a hyperlink by the author of a web page explicitly represents a relationship between the source and destination pages which demonstrates the hyperlink structure between web pages. Our web search engine searches not only for the keywords in the web pages, but also for the hyperlink structure between them. Comparing the results of structural web search versus keyword-based search indicates an improved ability to access desired information. We also discuss steps toward mining the queries input to the structural web search engine.
PRECURSORS TO INTERSTELLAR SHOCKS OF SOLAR ORIGIN

On or about 2012 August 25, the Voyager 1 spacecraft crossed the heliopause into the nearby interstellar plasma. In the nearly three years that the spacecraft has been in interstellar space, three notable particle and field disturbances have been observed, each apparently associated with a shock wave propagating outward from the Sun. Here, we present a detailed analysis of the third and most impressive of these disturbances, with brief comparisons to the two previous events, both of which have been previously reported. The shock responsible for the third event was first detected on 2014 February 17 by the onset of narrowband radio emissions from the approaching shock, followed on 2014 May 13 by the abrupt appearance of intense electron plasma oscillations generated by electrons streaming outward ahead of the shock. Finally, the shock arrived on 2014 August 25, as indicated by a jump in the magnetic field strength and the plasma density. Various disturbances in the intensity and anisotropy of galactic cosmic rays were also observed ahead of the shock, some of which are believed to be caused by the reflection and acceleration of cosmic rays by the magnetic field jump at the shock, and/or by interactions with upstream plasma waves. Comparisons to the two previous weaker events show somewhat similar precursor effects, although differing in certain details. Many of these effects are very similar to those observed in the region called the "foreshock" that occurs upstream of planetary bow shocks, only on a vastly larger spatial scale.
A hybrid model of optimal reinsurance: a discussion of ‘Optimal reinsurance designs based on risk measures: a review’ by Jun Cai and Yichun Chi

I wholeheartedly congratulate Professors Cai and Chi (referred to as CC hereafter) for their extensive review paper that surveys the optimal reinsurance designs based on risk measures. This paper s...
Cloud Removal in Satellite Images Using Spatiotemporal Generative Networks

Satellite images hold great promise for continuous environmental monitoring and earth observation. Occlusions cast by clouds, however, can severely limit coverage, making ground information extraction more difficult. Existing pipelines typically perform cloud removal with simple temporal composites and hand-crafted filters. In contrast, we cast the problem of cloud removal as a conditional image synthesis challenge, and we propose a trainable spatiotemporal generator network (STGAN) to remove clouds. We train our model on a new large-scale spatiotemporal dataset that we construct, containing 97640 image pairs covering all continents. We demonstrate experimentally that the proposed STGAN model outperforms standard models and can generate realistic cloud-free images with high PSNR and SSIM values across a variety of atmospheric conditions, leading to improved performance in downstream tasks such as land cover classification.
TiM-DNN: Ternary In-Memory Accelerator for Deep Neural Networks

The use of lower precision has emerged as a popular technique to optimize the compute and storage requirements of complex deep neural networks (DNNs). In the quest for lower precision, recent studies have shown that ternary DNNs (which represent weights and activations by signed ternary values) represent a promising sweet spot, achieving accuracy close to full-precision networks on complex tasks. We propose TiM-DNN, a programmable in-memory accelerator that is specifically designed to execute ternary DNNs. TiM-DNN supports various ternary representations including unweighted {−1, 0, 1}, symmetric weighted $\{-a,0,a\}$ , and asymmetric weighted $\{-a,0,b\}$ ternary systems. The building blocks of TiM-DNN are TiM tiles—specialized memory arrays that perform massively parallel signed ternary vector–matrix multiplications with a single access. TiM tiles are in turn composed of ternary processing cells (TPCs), bit-cells that function as both ternary storage units and signed ternary multiplication units. We evaluate an implementation of TiM-DNN in 32-nm technology using an architectural simulator calibrated with SPICE simulations and RTL synthesis. We evaluate TiM-DNN across a suite of state-of-the-art DNN benchmarks including both deep convolutional and recurrent neural networks. A 32-tile instance of TiM-DNN achieves a peak performance of 114 TOPs/s, consumes 0.9-W power, and occupies 1.96 mm2 chip area, representing a $300\times $ and $388\times $ improvement in TOPS/W and TOPS/mm2, respectively, compared to an NVIDIA Tesla V100 GPU. In comparison to specialized DNN accelerators, TiM-DNN achieves $55\times $ - $240\times $ and $160\times $ - $291\times $ improvement in TOPS/W and TOPS/mm2, respectively. Finally, when compared to a well-optimized near-memory accelerator for ternary DNNs, TiM-DNN demonstrates $3.9\times $ - $4.7\times $ improvement in system-level energy and $3.2\times $ - $4.2\times $ speedup, underscoring the potential of in-memory computing for ternary DNNs.
Evaluating the Portability of an NLP System for Processing Echocardiograms: A Retrospective, Multi-site Observational Study

While natural language processing (NLP) of unstructured clinical narratives holds the potential for patient care and clinical research, portability of NLP approaches across multiple sites remains a major challenge. This study investigated the portability of an NLP system developed initially at the Department of Veterans Affairs (VA) to extract 27 key cardiac concepts from free-text or semi-structured echocardiograms from three academic edical centers: Weill Cornell Medicine, Mayo Clinic and Northwestern Medicine. While the NLP system showed high precision and recall easurements for four target concepts (aortic valve regurgitation, left atrium size at end systole, mitral valve regurgitation, tricuspid valve regurgitation) across all sites, we found moderate or poor results for the remaining concepts and the NLP system performance varied between individual sites.
The Logic of Violence in Drug War

Drug traffickers sometimes share profits peacefully. Other times they fight. We propose a model to investigate this variation, focusing on the role of the state. Seizing illegal goods can paradoxically increase traffickers’ profits, and higher profits fuel violence. Killing kingpins makes crime bosses short-sighted, also fueling conflict. Only by targeting the most violent traffickers can the state reduce violence without increasing supply. These results help explain empirical patterns of violence in drug war, which is less studied than are interstate or civil war but often as deadly.
On the longest spanning tree with neighborhoods

We study a maximization problem for geometric network design. Given a set of n compact neighborhoods in ℝd, select a point in each neighborhood, so that the longest spanning tree on these points (a...
A Tale of Two Perplexities: Sensitivity of Neural Language Models to Lexical Retrieval Deficits in Dementia of the Alzheimer’s Type

In recent years there has been a burgeoning interest in the use of computational methods to distinguish between elicited speech samples produced by patients with dementia, and those from healthy controls. The difference between perplexity estimates from two neural language models (LMs) - one trained on transcripts of speech produced by healthy participants and one trained on those with dementia - as a single feature for diagnostic classification of unseen transcripts has been shown to produce state-of-the-art performance. However, little is known about why this approach is effective, and on account of the lack of case/control matching in the most widely-used evaluation set of transcripts (DementiaBank), it is unclear if these approaches are truly diagnostic, or are sensitive to other variables. In this paper, we interrogate neural LMs trained on participants with and without dementia by using synthetic narratives previously developed to simulate progressive semantic dementia by manipulating lexical frequency. We find that perplexity of neural LMs is strongly and differentially associated with lexical frequency, and that using a mixture model resulting from interpolating control and dementia LMs improves upon the current state-of-the-art for models trained on transcript text exclusively.
Physical conditions in photodissociation regions: Application to galactic nuclei

Infrared and sub-millimeter observations are used in a simple procedure to determine average physical properties of the neutral interstellar medium in Galactic photodissociation regions as well as in ensembles of clouds which exist in the nuclei of luminous infrared galaxies. The relevant observations include the Infrared Astronomy Satellite (IRAS) infrared continuum measurements, infrared spectroscopy of the fine-structure lines of SiII 35 microns, OI 63 microns, and CII 158 microns, and the 2.6 mm CO (J=1-0) rotational transition. The diagnostic capabilities of the OI 145 microns line is also addressed. Researchers attribute these emission lines as well as the continuum to the atomic/molecular photodissociation region on the surfaces of molecular clouds which are illuminated by strong ultraviolet fields. They use the theoretical photodissociation region models of Tielens and Hollenbach (1985, Ap. J., 291, 722) to construct simple diagrams which utilize line ratios and line to continuum ratios to determine the average gas density n, the average incident far-ultraviolet flux G sub o, and the temperature of the atomic gas T.
The Outer Limits of Contention Resolution on Matroids and Connections to the Secretary Problem

Contention resolution schemes have proven to be a useful and unifying abstraction for a variety of constrained optimization problems, in both offline and online arrival models. Much of prior work restricts attention to product distributions for the input set of elements, and studies contention resolution for increasingly general packing constraints, both offline and online. In this paper, we instead focus on generalizing the input distribution, restricting attention to matroid constraints in both the offline and online random arrival models. In particular, we study contention resolution when the input set is arbitrarily distributed, and may exhibit positive and/or negative correlations between elements. We characterize the distributions for which offline contention resolution is possible, and establish some of their basic closure properties. Our characterization can be interpreted as a distributional generalization of the matroid covering theorem. For the online random arrival model, we show that contention resolution is intimately tied to the secretary problem via two results. First, we show that a competitive algorithm for the matroid secretary problem implies that online contention resolution is essentially as powerful as offline contention resolution for matroids, so long as the algorithm is given the input distribution. Second, we reduce the matroid secretary problem to the design of an online contention resolution scheme of a particular form.
A universal time scale for vortex ring formation

The formation of vortex rings generated through impulsively started jets is studied experimentally. Utilizing a piston/cylinder arrangement in a water tank, the velocity and vorticity fields of vortex rings are obtained using digital particle image velocimetry (DPIV) for a wide range of piston stroke to diameter (L/D) ratios. The results indicate that the flow field generated by large L/D consists of a leading vortex ring followed by a trailing jet. The vorticity field of the leading vortex ring formed is disconnected from that of the trailing jet. On the other hand, flow fields generated by small stroke ratios show only a single vortex ring. The transition between these two distinct states is observed to occur at a stroke ratio of approximately 4, which, in this paper, is referred to as the ‘formation number’. In all cases, the maximum circulation that a vortex ring can attain during its formation is reached at this non-dimensional time or formation number. The universality of this number was tested by generating vortex rings with different jet exit diameters and boundaries, as well as with various non-impulsive piston velocities. It is shown that the ‘formation number’ lies in the range of 3.6–4.5 for a broad range of flow conditions. An explanation is provided for the existence of the formation number based on the Kelvin–Benjamin variational principle for steady axis-touching vortex rings. It is shown that based on the measured impulse, circulation and energy of the observed vortex rings, the Kelvin–Benjamin principle correctly predicts the range of observed formation numbers.
Does the Market Correctly Value Investment Options

This paper shows that the stock market misprices firms’ investment options. We build a real options model of optimal investment under uncertainty to estimate the value of firms’ investment options. We show that firms with valuable investment options have a higher likelihood of being mispriced. Importantly, this mispricing is not one-sided, as such firms are equally likely to be undervalued or overvalued. Our paper adds to the debate on whether public equity markets are myopic and systematically undervalue innovative firms. We show that this is not necessarily the case.
What are the minimum requirements to establish proficiency in lung ultrasound training for quantifying B‐lines?

Aims The goal of this study was to determine the number of scans needed for novice learners to attain proficiency in B-line quantification compared with expert interpretation. Methods and results This was a prospective, multicentre observational study of novice learners, physicians and non-physicians from three academic institutions. Learners received a 2 h lung ultrasound (LUS) training session on B-line assessment, including lecture, video review to practice counting and hands-on patient scanning. Learners quantified B-lines using an eight-zone scanning protocol in patients with suspected acute heart failure. Ultrasound (US) machine settings were standardized to a depth of 18 cm and clip length of 6 s, and tissue harmonics and multibeam former were deactivated. For quantification, the intercostal space with the greatest number of B-lines within each zone was used for scoring. Each zone was given a score of 0-20 based on the maximum number of B-lines counted during one respiratory cycle. The B-line score was determined by multiplying the percentage of the intercostal space filled with B-lines by 20. We compared learner B-line counts with a blinded expert reviewer (five US fellowship-trained faculty with > 5 years of clinical experience) for each lung zone scanned; proficiency was defined as an intraclass correlation of > 0.7. Learning curves for each learner were constructed using cumulative sum method for statistical analysis. The Wilcoxon rank-sum test was used to compare the number of scans required to reach proficiency between different learner types. Twenty-nine learners (21 research associates, 5 residents and 3 non-US-trained emergency medicine faculty) scanned 2629 lung zones with acute pulmonary oedema. After a mean of 10.8 (standard deviation 14.0) LUS zones scanned, learners reached the predefined proficiency standard. The number of scanned zones required to reach proficiency was not significantly different between physicians and non-physicians (P = 0.26), learners with no prior US experience vs. > 25 prior patient scans (P = 0.64) and no prior vs. some prior LUS experience (P = 0.59). The overall intraclass correlation for agreement between learners and experts was 0.74 and 0.80 between experts. Conclusions Our results show that after a short, structured training, novice learners are able to achieve proficiency for quantifying B-lines on LUS after scanning 11 zones. These findings support the use of LUS for B-line quantification by non-physicians in clinical and research applications.
Taking a hint: How to leverage loss predictors in contextual bandits?

We initiate the study of learning in contextual bandits with the help of loss predictors. The main question we address is whether one can improve over the minimax regret $\mathcal{O}(\sqrt{T})$ for learning over $T$ rounds, when the total error of the predicted losses relative to the realized losses, denoted as $\mathcal{E} \leq T$, is relatively small. We provide a complete answer to this question, with upper and lower bounds for various settings: adversarial and stochastic environments, known and unknown $\mathcal{E}$, and single and multiple predictors. We show several surprising results, such as 1) the optimal regret is $\mathcal{O}(\min\{\sqrt{T}, \sqrt{\mathcal{E}}T^\frac{1}{4}\})$ when $\mathcal{E}$ is known, in contrast to the standard and better bound $\mathcal{O}(\sqrt{\mathcal{E}})$ for non-contextual problems (such as multi-armed bandits); 2) the same bound cannot be achieved if $\mathcal{E}$ is unknown, but as a remedy, $\mathcal{O}(\sqrt{\mathcal{E}}T^\frac{1}{3})$ is achievable; 3) with $M$ predictors, a linear dependence on $M$ is necessary, even though logarithmic dependence is possible for non-contextual problems.\n\nWe also develop several novel algorithmic techniques to achieve matching upper bounds, including 1) a key \emph{action remapping} technique for optimal regret with known $\mathcal{E}$, 2) computationally efficient implementation of Catoni's robust mean estimator via an ERM oracle in the stochastic setting with optimal regret, 3) an underestimator for $\mathcal{E}$ via estimating the histogram with bins of exponentially increasing size for the stochastic setting with unknown $\mathcal{E}$, and 4) a self-referential scheme for learning with multiple predictors, all of which might be of independent interest.
Rigorous Guarantees for Tyler's M-estimator via quantum expansion

Estimating the shape of an elliptical distribution is a fundamental problem in statistics. One estimator for the shape matrix, Tyler's M-estimator, has been shown to have many appealing asymptotic properties. It performs well in numerical experiments and can be quickly computed in practice by a simple iterative procedure. Despite the many years the estimator has been studied in the statistics community, there was neither a non-asymptotic bound on the rate of the estimator nor a proof that the iterative procedure converges in polynomially many steps. Here we observe a surprising connection between Tyler's M-estimator and operator scaling, which has been intensively studied in recent years in part because of its connections to the Brascamp-Lieb inequality in analysis. We use this connection, together with novel results on quantum expanders, to show that Tyler's M-estimator has the optimal rate up to factors logarithmic in the dimension, and that in the generative model the iterative procedure has a linear convergence rate even without regularization.
Trigeminal schwannoma presenting with malocclusion: A case report and review of the literature.

Background Trigeminal schwannomas are rare tumors of the trigeminal nerve. Depending on the location, from which they arise along the trigeminal nerve, these tumors can present with a variety of symptoms that include, but are not limited to, changes in facial sensation, weakness of the masticatory muscles, and facial pain. Case description We present a case of a 16-year-old boy with an atypical presentation of a large trigeminal schwannoma: painless malocclusion and unilateral masticatory weakness. This case is the first documented instance; to the best of our knowledge, in which a trigeminal schwannoma has led to underbite malocclusion; it is the 19th documented case of unilateral trigeminal motor neuropathy of any etiology. We discuss this case as a unique presentation of this pathology, and the relevant anatomy implicated in clinical examination aid in further understanding trigeminal nerve pathology. Conclusion We believe our patient's underbite malocclusion occurred secondary to his trigeminal schwannoma, resulting in associated atrophy and weakness of the muscles innervated by the mandibular branch of the trigeminal nerve. Furthermore, understanding the trigeminal nerve anatomy is crucial in localizing lesions of the trigeminal nerve.
Combining Laue diffraction with Bragg coherent diffraction imaging at 34-ID-C.

Measurement modalities in Bragg coherent diffraction imaging (BCDI) rely on finding a signal from a single nanoscale crystal object which satisfies the Bragg condition among a large number of arbitrarily oriented nanocrystals. However, even when the signal from a single Bragg reflection with (hkl) Miller indices is found, the crystallographic axes on the retrieved three-dimensional (3D) image of the crystal remain unknown, and thus localizing in reciprocal space other Bragg reflections becomes time-consuming or requires good knowledge of the orientation of the crystal. Here, the commissioning of a movable double-bounce Si (111) monochromator at the 34-ID-C endstation of the Advanced Photon Source is reported, which aims at delivering multi-reflection BCDI as a standard tool in a single beamline instrument. The new instrument enables, through rapid switching from monochromatic to broadband (pink) beam, the use of Laue diffraction to determine crystal orientation. With a proper orientation matrix determined for the lattice, one can measure coherent diffraction patterns near multiple Bragg peaks, thus providing sufficient information to image the full strain tensor in 3D. The design, concept of operation, the developed procedures for indexing Laue patterns, and automated measuring of Bragg coherent diffraction data from multiple reflections of the same nanocrystal are discussed.
Multi-fidelity machine-learning with uncertainty quantification and Bayesian optimization for materials design: Application to ternary random alloys.

We present a scale-bridging approach based on a multi-fidelity (MF) machine-learning (ML) framework leveraging Gaussian processes (GP) to fuse atomistic computational model predictions across multiple levels of fidelity. Through the posterior variance of the MFGP, our framework naturally enables uncertainty quantification, providing estimates of confidence in the predictions. We used density functional theory as high-fidelity prediction, while a ML interatomic potential is used as low-fidelity prediction. Practical materials’ design efficiency is demonstrated by reproducing the ternary composition dependence of a quantity of interest (bulk modulus) across the full aluminum–niobium–titanium ternary random alloy composition space. The MFGP is then coupled to a Bayesian optimization procedure, and the computational efficiency of this approach is demonstrated by performing an on-the-fly search for the global optimum of bulk modulus in the ternary composition space. The framework presented in this manuscript is the first application of MFGP to atomistic materials simulations fusing predictions between density functional theory and classical interatomic potential calculations.
Indeterminate Prenatal Ultrasounds and Maternal Anxiety: A Prospective Cohort Study.

Prenatal ultrasounds often yield indeterminate (incomplete or minor abnormality) findings with limited clinical utility. We evaluate impact of indeterminate findings on maternal anxiety. A single-U.S.-center prospective cohort study administered the Perinatal Anxiety Screening Scale (PASS; control mean = 13.4; > 20 denotes clinically significant anxiety) before and after prenatal ultrasounds in February-May 2017. Ultrasound reports were coded as: normal; indeterminate; or major abnormality. Primary outcome was anxiety after indeterminate vs. normal ultrasounds. Secondary outcomes included anxiety change from pre-to-post-ultrasound and relative to women’s characteristics. Linear regression adjusted for confounders. Of 286 ultrasounds, 51.0% were normal, 40.5% indeterminate (22.0% incomplete; 18.5% minor abnormality), and 8.0% major abnormalities. Indeterminate findings were unrelated to age, race, parity, infertility, or psychiatric history, but associated with gestational age (26.6%/45.0%/52.5% for first/second/third trimesters; p < 0.001), and obesity (48.8 vs. 37.0%; p = 0.031). Pretest anxiety was highest in second/third trimesters (p = 0.029), and in subjects aged age ≤ 24 or younger(p < 0.001), with a history of anxiety (p < 0.001),) or with prior pregnancy loss (p = 0.011). Mean anxiety score decreased pre-to-posttest across all groups. Indeterminate findings were associated with higher PASS scores than normal findings: pretest 20.1 vs. 16.4 (p = 0.026) and posttest 16.9 vs. 12.2 (p = 0.009; adjusted-p = 0.01). Versus normal ultrasounds, incomplete findings were associated with higher post-ultrasound anxiety (p = 0.007; adjusted-p = 0.01) and smaller decreases from pre-to-posttest (adjusted-p = 0.03), whereas minor abnormalities had higher pretest anxiety (p = 0.029) with larger pre-to-posttest decreases (adjusted-p =0.010). Indeterminate ultrasounds, especially incomplete findings, are associated with significantly higher anxiety than normal findings, suggesting need for evidence-based counseling, management and strategies for decreasing number of indeterminate results.