cssi/SciSciGPT-SciSciNet huggingface dataset:
Iterated sumsets and setpartitions

Let $$G\cong {\mathbb {Z}}/m_1{\mathbb {Z}}\times \cdots \times {\mathbb {Z}}/m_r{\mathbb {Z}}$$ be a finite abelian group with $$m_1\mid \cdots \mid m_r=\exp (G)$$ . The n-term subsums version of Kneser’s Theorem, obtained either via the DeVos–Goddyn–Mohar Theorem or the Partition Theorem, has become a powerful tool used to prove numerous zero-sum and subsequence sum questions. It provides a structural description of sequences having a small number of n-term subsequence sums, ensuring this is only possible if most terms of the sequence are contained in a small number of H-cosets. For large $$n\ge \frac{1}{p}|G|-1$$ or $$n\ge \frac{1}{p}|G|+p-3$$ , where p is the smallest prime divisor of |G|, the structural description is particularly strong. In particular, most terms of the sequence become contained in a single H-coset, with additional properties holding regarding the representation of elements of G as subsequence sums. This strengthened form of the subsum version of Kneser’s Theorem was later shown to hold under the weaker hypothesis $$n\ge {\mathsf {d}}^*(G)$$ , where $$\mathsf d^*(G)=\sum _{i=1}^{r}(m_i-1)$$ . In this paper, we reduce the restriction on n even further to an optimal, best-possible value, showing we need only assume $$n\ge \exp (G)+1$$ to obtain the same conclusions, with the bound further improved for several classes of near-cyclic groups.
Abstract 1016: The androgen receptor splice variant AR-V7 associates with the glucocorticoid receptor following androgen blockade

Expression of the constitutively active androgen receptor splice variant AR-V7 is associated with resistance to anti-androgen therapies and worse clinical outcomes in prostate cancer. Dimerization is a requirement for AR-V7 transcriptional activity, but whether that occurs through homodimerization or heterodimerization remains poorly understood. Because NR3C-family nuclear hormone receptors rely on a highly conserved D-box motif within the DNA-binding domain to mediate dimerization, we hypothesized that AR-V7 can heterodimerize with other NR3C-family nuclear hormone receptors, with a particular interest in the glucocorticoid receptor (GR). Like AR-V7, GR is upregulated in prostate cancer following androgen blockade, regulates canonical AR target genes, and is associated with resistance to anti-androgen therapies. Using NanoBRET technology in HEK293 cells, we found that AR-V7 interacts with liganded NR3C-family nuclear hormone receptors, including the full-length androgen receptor, the progesterone receptor, the mineralocorticoid receptor, and, most notably, GR. Using co-immunoprecipitation and proximity ligation assays, we demonstrate that AR-V7 associates with GR following androgen blockade in both the VCaP cell line and the CWR-22RV1 cell line, two models of prostate cancer that express endogenous AR-V7 and GR. Preliminary ChIP-Seq experiments in these cell lines suggest AR-V7 and GR chromatin occupancy at the same genomic sites in a ligand-dependent manner. Taken altogether, this data suggests AR-V7 can utilize GR as an alternative binding partner to initiate heterodimerization and transcriptional activation. Citation Format: Eric Bueter, David Hosfield, Erin McAuley, Phillip Selman, Geoffrey Greene, Suzanne D. Conzen, Russell Z. Szmulewitz. The androgen receptor splice variant AR-V7 associates with the glucocorticoid receptor following androgen blockade [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1016.
Perennial warm-season grasses for producing biofuel and enhancing soil properties: An alternative to corn residue removal

Removal of corn (Zea mays L.) residues at high rates for biofuel and other off-farm uses may negatively impact soil and the environment in the long term. Biomass removal from perennial warm-season grasses (WSGs) grown in marginally productive lands could be an alternative to corn residue removal as biofuel feedstocks while controlling water and wind erosion, sequestering carbon (C), cycling water and nutrients, and enhancing other soil ecosystem services. We compared wind and water erosion potential, soil compaction, soil hydraulic properties, soil organic C (SOC), and soil fertility between biomass removal from WSGs and corn residue removal from rainfed no-till continuous corn on a marginally productive site on a silty clay loam in eastern Nebraska after 2 and 3 years of management. The field-scale treatments were as follows: (i) switchgrass (Panicum virgatum L.), (ii) big bluestem (Andropogon gerardii Vitman), and (iii) low-diversity grass mixture [big bluestem, indiangrass (Sorghastrum nutans (L.) Nash), and sideoats grama (Bouteloua curtipendula (Michx.) Torr.)], and (iv) 50% corn residue removal with three replications. Across years, corn residue removal increased wind-erodible fraction from 41% to 86% and reduced wet aggregate stability from 1.70 to 1.15 mm compared with WSGs in the upper 7.5 cm soil depth. Corn residue removal also reduced water retention by 15% between -33 and -300 kPa potentials and plant-available water by 25% in the upper 7.5 cm soil depth. However, corn residue removal did not affect final water infiltration, SOC concentration, soil fertility, and other properties. Overall, corn residue removal increases erosion potential and reduces water retention shortly after removal, suggesting that biomass removal from perennial WSGs is a desirable alternative to corn residue removal for biofuel production and maintenance of soil ecosystem services.
Cyclin B3 is dispensable for mouse spermatogenesis

Cyclins, as regulatory partners of cyclin-dependent kinases (CDKs), control the switch-like cell cycle transitions that orchestrate orderly duplication and segregation of genomes. Compared to mitosis, relatively little is known about how cyclin-CDK complexes control meiosis, the specialized cell division that generates gametes for sexual production. Mouse cyclin B3 was previously shown to have expression restricted to the beginning of meiosis, making it a candidate to regulate meiotic events. Indeed, female mice lacking cyclin B3 are sterile because oocytes arrest at the metaphase-to-anaphase transition of meiosis I. However, whether cyclin B3 functions during spermatogenesis was untested. Here, we found that males lacking cyclin B3 are fertile and show no detectable defects in spermatogenesis based on histological analysis of seminiferous tubules. Cytological analysis further showed no detectable defects in homologous chromosome synapsis or meiotic progression, and suggested that recombination is initiated and completed efficiently. Moreover, absence of cyclin B3 did not exacerbate previously described meiotic defects in mutants deficient for cyclin E2, suggesting a lack of redundancy between these cyclins. Thus, unlike in females, cyclin B3 is not essential for meiosis in males despite its prominent meiosis-specific expression.
Simulated Basic Safety Message: Concept & Application

In this paper, we introduce a concept called Simulated - BSM that leverages the combination of rich vehicular sensor feed (speed, object proximity, SLAM maps etc.), and emerging guaranteed low-latency communication protocols (DSRC, 5G) to enhance efficiency & safety of transport facilities. The main idea is that an ego-vehicle with local sensor feed capability creates a basic safety message for any identified rogue vehicles in its field of view, and broadcasts it to infrastructure for implementing efficient and safe control actions. System architecture details are discussed. The efficacy of S-BSM framework was successfully demonstrated in the context of enhancing safe & efficient operations at rural high-speed signalized intersection.
Adaptive Influence Maximization with Myopic Feedback

We study the adaptive influence maximization problem with myopic feedback under the independent cascade model: one sequentially selects k nodes as seeds one by one from a social network, and each selected seed returns the immediate neighbors it activates as the feedback available for by later selections, and the goal is to maximize the expected number of total activated nodes, referred as the influence spread. We show that the adaptivity gap, the ratio between the optimal adaptive influence spread and the optimal non-adaptive influence spread, is at most 4 and at least e/(e-1), and the approximation ratios with respect to the optimal adaptive influence spread of both the non-adaptive greedy and adaptive greedy algorithms are at least \frac{1}{4}(1 - \frac{1}{e}) and at most \frac{e^2 + 1}{(e + 1)^2} < 1 - \frac{1}{e}. Moreover, the approximation ratio of the non-adaptive greedy algorithm is no worse than that of the adaptive greedy algorithm, when considering all graphs. Our result confirms a long-standing open conjecture of Golovin and Krause (2011) on the constant approximation ratio of adaptive greedy with myopic feedback, and it also suggests that adaptive greedy may not bring much benefit under myopic feedback.
Extracellular matrix micropatterning technology for whole cell cryogenic electron microscopy studies.

Author(s): Engel, Leeya; Gaietta, Guido; Dow, Liam; Swift, Mark; Pardon, Gaspard; Volkmann, Niels; Weis, William; Hanein, Dorit; Pruitt, Beth | Abstract: ABSTRACT Cryogenic electron tomography is the highest resolution tool available for structural analysis of macromolecular organization inside cells. Micropatterning of extracellular matrix (ECM) proteins is an established in vitro cell culture technique used to control cell shape. Recent traction force microscopy studies have shown correlation between cell morphology and the regulation of force transmission. However, it remains unknown how cells sustain increased strain energy states and localized stresses at the supramolecular level. Here, we report a technology to enable direct observation of mesoscale organization in epithelial cells under morphological modulation, using a maskless protein photopatterning method to confine cells to ECM micropatterns on electron microscopy substrates. These micropatterned cell culture substrates can be used in mechanobiology research to correlate changes in nanometer-scale organization at cell-cell and cell-ECM contacts to strain energy states and traction stress distribution in the cell.
Imaging characteristics and clinical outcomes of biphenotypic sinonasal sarcoma

Objectives Biphenotypic sinonasal sarcoma (BSS) is a new, rare tumor characterized by concomitant neural and myogenic differentiation. The aim of this study is to describe the imaging characteristics and clinical outcomes of this neoplasm. Methods A retrospective review of BSS patients surgically treated within a tertiary academic health care system was performed. Imaging characteristics and clinical outcomes were reviewed. Results Five patients underwent surgical resection of BSS tumors. Negative surgical margins were achieved in four (80%) patients. There were no deaths but two (40%) patients developed local recurrences during the postoperative follow-up period (median follow-up 31.4 months). Review of imaging characteristics revealed a median tumor size of 3.8 cm in greatest dimension. All tumors were unilateral and centered within the nasoethmoidal region. In all cases, the tumors extended to the nasal septum, lamina papyracea, and anterior skull base with variable degrees of erosion through these structures. On CT, involved bony structures demonstrated mixed lytic and sclerotic pattern, with definitive hyperostotic bone identified in four (80%) cases. On MRI, tumors were isointense-to-mixed iso/hypointense on both T1- and T2-weighted sequences with one tumor demonstrating mixed T2 hyperintensity. All cases demonstrated gadolinium contrast enhancement. Conclusions BSS is a locally aggressive tumor with a low risk of regional or distant metastases but has a significant rate of recurrence even with adequate resection. Despite its rarity, BSS should be considered in the differential diagnosis when imaging demonstrates a unilateral nasoethmoidal mass that is predominantly isointense to cerebral gray matter on T2-weighted MRI and is hyperostotic on CT. Level of evidence 4.
Scaling Ordered Stream Processing on Shared-Memory Multicores

Many modern applications require realtime processing of large volumes of high speed data. Such data processing can be specified in the form of a dataflow graph that exposes multiple opportunities for parallelizing its execution, in the form of data, pipeline and task parallelism. This paper focuses on the problem of effectively parallelizing ordered streaming computations by exploiting low overhead, shared memory parallelism on a multicore machine. We propose an adaptive runtime that dynamically maps the exposed parallelism in a streaming computation to that of the machine using scheduling heuristics. Further, we address some key problems in effectively realizing ordered data parallelism. We propose a new approach for parallelizing partitioned stateful operators that can handle load imbalance across partitions effectively and mostly avoid delays due to ordering constraints. We also present a low latency, non-blocking concurrent data structure to order outputs produced by concurrent workers on an operator. Finally, we perform an in-depth empirical evaluation illustrating the trade-offs and effectiveness of our concurrent data-structures and scheduling heuristics using micro-benchmarks and on the TPCx-BB benchmark.
Short and Intermediate Term Outcomes of the Convergent Procedure: Initial Experience in a Tertiary Referral Center.

Purpose The Convergent procedure is a hybrid, multidisciplinary treatment for symptomatic atrial fibrillation (AF) consisting of minimally invasive surgical epicardial ablation and percutaneous/catheter endocardial ablation. We investigated outcomes following introduction of the Convergent procedure at our institution. Methods Retrospective study examining single-center outcomes. Demographic, procedural, and post-procedural variables were collected with follow-up data obtained at 3, 6, and 12 months. Results In all, 36 patients with paroxysmal (11%) or persistent/long-standing persistent (89%) AF underwent the Convergent procedure. 36% also underwent concomitant left atrial appendage (LAA) exclusion by thoracoscopic placement of an epicardial clip. Mean age 60.6 ± 8.0 years with mean arrhythmia burden of 3.9 ± 2.7 years. All patients had failed prior attempts at medical management, 81% had failed prior cardioversion, and 17% had failed prior catheter ablation. Convergent was performed successfully in all patients with no peri-procedural deaths or major complications. At 3 and 12 months, 77.8% and 77.3% of patients, respectively, were free from symptomatic arrhythmia. 65.8% were off anti-arrhythmic medication at 12 months. Conclusions The Convergent procedure is safe and has good short- and intermediate-term clinical success rates. This unique hybrid approach combines strengths of surgical and catheter ablation and should be part of any comprehensive AF treatment program.
Using a design approach to create collaborative governance

In complex, shared-power settings, policymakers, administrators and other kinds of decision makers increasingly must engage in collaborative inter-organisational efforts to effectively address challenging public issues. These collaborations must be governed effectively if they are to achieve their public purposes. A design approach to the governance of collaborations can help, especially if it explicitly focuses on the design and use of formal and informal settings for dialogue and deliberation (forums), decision making (arenas) and resolution of residual disputes (courts). The success of a design approach will depend on many things, but especially on leaders and leadership and careful attention to the design and use of forums, arenas and courts and the effective use of power. The argument is illustrated by examining the emergence and governance of a collaboration designed to cope with the fragmented policy field of minority business support.
Taking a machine’s perspective: Humans can decipher adversarial images

How similar is the human mind to the sophisticated machine-learning systems that mirror its performance? Models of object categorization based on convolutional neural networks (CNNs) have achieved human-level benchmarks in assigning known labels to novel images. These advances promise to support transformative technologies such as autonomous vehicles and machine diagnosis; beyond this, they also serve as candidate models for the visual system itself -- not only in their output but perhaps even in their underlying mechanisms and principles. However, unlike human vision, CNNs can be "fooled" by adversarial examples -- carefully crafted images that appear as nonsense patterns to humans but are recognized as familiar objects by machines, or that appear as one object to humans and a different object to machines. This seemingly extreme divergence between human and machine classification challenges the promise of these new advances, both as applied image-recognition systems and also as models of the human mind. Surprisingly, however, little work has empirically investigated human classification of such adversarial stimuli: Does human and machine performance fundamentally diverge? Or could humans decipher such images and predict the machine's preferred labels? Here, we show that human and machine classification of adversarial stimuli are robustly related: In eight experiments on five prominent and diverse adversarial imagesets, human subjects reliably identified the machine's chosen label over relevant foils. This pattern persisted for images with strong antecedent identities, and even for images described as "totally unrecognizable to human eyes". We suggest that human intuition may be a more reliable guide to machine (mis)classification than has typically been imagined, and we explore the consequences of this result for minds and machines alike.
Smart material actuated angel wings for live theatrical effect.

The University of Minnesota Mechanical Engineering Department, in collaboration with the Theater Arts & Dance Department, designed and built smart material actuated angel wings for the theater production of Jose Rivera's play Marisol. The design challenge coordinated aesthetic, structural, mechanical, and electrical requirements for a successful theatrical effect. The aesthetic design drew influence from Baroque Catholic art and 90's grunge fashion for dramatic effect. The wing structure was inspired by the skeletal structure of swan wings, which resulted in the design of a Nickel-Titanium (NiTi) shape memory alloy (SMA) actuated mechanical linkage that mimicked the shape and motion of swan wings. A hidden electrical circuit with a simple pushbutton switch provided the actor with control over the wing movement. The unique design constraints that came with designing a mechanism for theatrical use, along with the close collaboration between the two departments, led to a successful wearable mechanism with dramatic stage effect.
Integrating machine learning and multiscale modeling—perspectives, challenges, and opportunities in the biological, biomedical, and behavioral sciences

Fueled by breakthrough technology developments, the biological, biomedical, and behavioral sciences are now collecting more data than ever before. There is a critical need for time- and cost-efficient strategies to analyze and interpret these data to advance human health. The recent rise of machine learning as a powerful technique to integrate multimodality, multifidelity data, and reveal correlations between intertwined phenomena presents a special opportunity in this regard. However, machine learning alone ignores the fundamental laws of physics and can result in ill-posed problems or non-physical solutions. Multiscale modeling is a successful strategy to integrate multiscale, multiphysics data and uncover mechanisms that explain the emergence of function. However, multiscale modeling alone often fails to efficiently combine large datasets from different sources and different levels of resolution. Here we demonstrate that machine learning and multiscale modeling can naturally complement each other to create robust predictive models that integrate the underlying physics to manage ill-posed problems and explore massive design spaces. We review the current literature, highlight applications and opportunities, address open questions, and discuss potential challenges and limitations in four overarching topical areas: ordinary differential equations, partial differential equations, data-driven approaches, and theory-driven approaches. Towards these goals, we leverage expertise in applied mathematics, computer science, computational biology, biophysics, biomechanics, engineering mechanics, experimentation, and medicine. Our multidisciplinary perspective suggests that integrating machine learning and multiscale modeling can provide new insights into disease mechanisms, help identify new targets and treatment strategies, and inform decision making for the benefit of human health.
Identification of immunoreactive linear epitopes of Borrelia miyamotoi

Borrelia miyamotoi is an emerging tick-borne spirochete transmitted by ixodid ticks. Current serologic assays for B. miyamotoi are impacted by genetic similarities to other Borrelia and limited understanding of optimal antigenic targets. In this study, we employed the TBD-Serochip, a peptide array platform, to identify new linear targets for serologic detection of B. miyamotoi. We examined a wide range of suspected B. miyamotoi antigens and identified 352 IgM and 91 IgG reactive peptides, with the majority mapping to variable membrane proteins. These included peptides within conserved fragments of variable membrane proteins that may have greater potential for differential diagnosis. We also identified reactive regions on FlaB, and demonstrate crossreactivity of B. burgdorferi s.l. C6 with a B. miyamotoi C6-like peptide. The panel of linear peptides identified in this study can be used to enhance serodiagnosis of B. miyamotoi.
The Dynamic Chromatin Architecture of the Regenerating Liver.

Background & Aims The adult liver is the main detoxification organ and routinely is exposed to environmental insults but retains the ability to restore its mass and function upon tissue damage. However, extensive injury can lead to liver failure, and chronic injury causes fibrosis, cirrhosis, and hepatocellular carcinoma. Currently, the transcriptional regulation of organ repair in the adult liver is incompletely understood. Methods We isolated nuclei from quiescent as well as repopulating hepatocytes in a mouse model of hereditary tyrosinemia, which recapitulates the injury and repopulation seen in toxic liver injury in human beings. We then performed the assay for transposase accessible chromatin with high-throughput sequencing specifically in repopulating hepatocytes to identify differentially accessible chromatin regions and nucleosome positioning. In addition, we used motif analysis to predict differential transcription factor occupancy and validated the in silico results with chromatin immunoprecipitation followed by sequencing for hepatocyte nuclear factor 4α (HNF4α) and CCCTC-binding factor (CTCF). Results Chromatin accessibility in repopulating hepatocytes was increased in the regulatory regions of genes promoting proliferation and decreased in the regulatory regions of genes involved in metabolism. The epigenetic changes at promoters and liver enhancers correspond with the regulation of gene expression, with enhancers of many liver function genes showing a less accessible state during the regenerative process. Moreover, increased CTCF occupancy at promoters and decreased HNF4α binding at enhancers implicate these factors as key drivers of the transcriptomic changes in replicating hepatocytes that enable liver repopulation. Conclusions Our analysis of hepatocyte-specific epigenomic changes during liver repopulation identified CTCF and HNF4α as key regulators of hepatocyte proliferation and regulation of metabolic programs. Thus, liver repopulation in the setting of toxic injury makes use of both general transcription factors (CTCF) for promoter activation, and reduced binding by a hepatocyte-enriched factor (HNF4α) to temporarily limit enhancer activity. All sequencing data in this study were deposited to the Gene Expression Omnibus database and can be downloaded with accession number GSE109466 .
Spatially patterned microribbon-based hydrogels induce zonally-organized cartilage regeneration by stem cells in 3D.

Abstract Regenerating cartilage with biomimetic zonal organization, which is critical for tissue function, remains a great challenge. The objective of this study was to evaluate the potential of spatially-patterned, multi-compositional, macroporous, extracellular matrix-based microribbon (µRB) µRB scaffolds to regenerate cartilage with biochemical, mechanical, and morphological zonal organization by mesenchymal stem cells (MSCs) compared to conventional multi-layer nanoporous hydrogels. MSCs were seeded in either trilayer microribbon (µRB) or hydrogel (HG) scaffolds that were composed of layered biomaterial compositions that had been chosen for their ability to differentiate MSCs into chondrocytes with zonal properties. To mimic the aligned collagen morphology in the superficial layer of native cartilage, an additional experimental group added MSC-laden aligned µRBs to the surface of the superficial layer of a µRB trilayer. Tuning µRB alignment and compositions in different zones led to zonal-specific responses of MSCs to create neocartilage with zonal biochemical, morphological, and mechanical properties, while trilayer HGs led to minimal cartilaginous deposition overall. Trilayer µRBs created neocartilage exhibiting significant increases in compressive modulus (up to 456 kPa) and > 4-fold increase in sGAG production from superficial to deep zones. Aligned gelatin µRBs in the superficial zone further enhanced biomimetic mimicry of the produced neocartilage by leading to robust collagen deposition and superficial zone protein production. Statement of significance Regenerating cartilage with zonal organization using mesenchymal stem cells (MSCs) remains a great challenge. We developed a spatially-patterned, gradient, macroporous, trilayer microribbon (µRB) scaffold that we used to engineer MSC-based neocartilage with zonal trends that match native cartilage in many aspects, including collagen, sGAG, superficial zone protein, and compressive moduli. This is in direct contrast to conventional trilayer nanoporous hydrogels which led to minimal cartilage deposition and weak mechanical properties. It took only 21 days for MSC-seeded trilayer µRB scaffolds to reach cartilage-mimicking compressive moduli without requiring high cell seeding density, which has never been reported before. While this paper focuses on cartilage zonal organization, gradient µRB scaffolds can be used to repair other tissue interfaces such as osteochondral defects.
Localized energy for wave equations with degenerate trapping

Localized energy estimates have become a fundamental tool when studying wave equations in the presence of asymptotically at background geometry. Trapped rays necessitate a loss when compared to the estimate on Minkowski space. A loss of regularity is a common way to incorporate such. When trapping is sufficiently weak, a logarithmic loss of regularity suffices. Here, by studying a warped product manifold introduced by Christianson and Wunsch, we encounter the first explicit example of a situation where an estimate with an algebraic loss of regularity exists and this loss is sharp. Due to the global-in-time nature of the estimate for the wave equation, the situation is more complicated than for the Schrodinger equation. An initial estimate with sub-optimal loss is first obtained, where extra care is required due to the low frequency contributions. An improved estimate is then established using energy functionals that are inspired by WKB analysis. Finally, it is shown that the loss cannot be improved by any power by saturating the estimate with a quasimode.
Symmetries of CMB Temperature Correlation at Large Angular Separations

A new analysis is presented of the angular correlation function C(Θ) of cosmic microwave background temperature at large angular separation, based on published maps derived from Wilkinson Microwave Anisotropy Probe and Planck satellite data, using different models of astrophysical foregrounds. It is found that using a common analysis, the results from the two satellites are very similar. In particular, it is found that previously published differences between measured values of C(Θ) near Θ = 90° arise mainly from different choices of masks in regions of largest Galactic emissions, and that demonstrated measurement biases are reduced by eliminating masks altogether. Maps from both satellites are shown to agree with C(90°) = 0 to within estimated statistical and systematic errors, consistent with an exact symmetry predicted in a new holographic quantum model of inflation.
Distinct Waking States for Strong Evoked Responses in Primary Visual Cortex and Optimal Visual Detection Performance.

Variability in cortical neuronal responses to sensory stimuli and in perceptual decision making performance is substantial. Moment-to-moment fluctuations in waking state or arousal can account for much of this variability. Yet, this variability is rarely characterized across the full spectrum of waking states, leaving the characteristics of the optimal state for sensory processing unresolved. Using pupillometry in concert with extracellular multi-unit and intracellular whole-cell recordings, we found that the magnitude and reliability of visually evoked responses in primary visual cortex (V1) of awake, passively behaving male mice increase as a function of arousal and are largest during sustained locomotion periods. During these high-arousal, sustained locomotion periods, cortical neuronal membrane potential was at its most depolarized and least variable. Contrastingly, behavioral performance of mice on two distinct visual detection tasks was generally best at a range of intermediate arousal levels, but worst during high arousal with locomotion. These results suggest that large, reliable responses to visual stimuli in V1 occur at a distinct arousal level from that associated with optimal visual detection performance. Our results clarify the relation between neuronal responsiveness and the continuum of waking states, and suggest new complexities in the relation between primary sensory cortical activity and behavior. SIGNIFICANCE STATEMENT Cortical sensory processing strongly depends on arousal. In the mouse visual system, locomotion (associated with high arousal) has previously been shown to enhance the sensory responses of neurons in primary visual cortex (V1). Yet, arousal fluctuates on a moment-to-moment basis, even during quiescent periods. The characteristics of V1 sensory processing across the continuum of arousal are unclear. Furthermore, the arousal level corresponding to optimal visual detection performance is unknown. We show that the magnitude and reliability of sensory-evoked V1 responses are monotonic increasing functions of arousal, and largest during locomotion. Visual detection behavior, however, is suboptimal during high arousal with locomotion, and usually best during intermediate arousal. Our study provides a more complete picture of the dependence of V1 sensory processing on arousal.
Impact of Approximate DFT Density Delocalization Error on Potential Energy Surfaces in Transition Metal Chemistry.

For approximate density functional theory (DFT) to be useful in catalytic applications of transition metal complexes, modeling strategies must simultaneously address electronic, geometric, and ener...
On the Effectiveness of the Pooling Methods for Biomedical Relation Extraction with Deep Learning

Deep learning models have achieved state-of-the-art performances on many relation extraction datasets. A common element in these deep learning models involves the pooling mechanisms where a sequence of hidden vectors is aggregated to generate a single representation vector, serving as the features to perform prediction for RE. Unfortunately, the models in the literature tend to employ different strategies to perform pooling for RE, leading to the challenge to determine the best pooling mechanism for this problem, especially in the biomedical domain. In order to answer this question, in this work, we conduct a comprehensive study to evaluate the effectiveness of different pooling mechanisms for the deep learning models in biomedical RE. The experimental results suggest that dependency-based pooling is the best pooling strategy for RE in the biomedical domain, yielding the state-of-the-art performance on two benchmark datasets for this problem.
Photopatterned Membranes and Chemical Gradients Enable Scalable Phenotypic Organization of Primary Human Colon Epithelial Models

Biochemical gradients across the intestinal epithelium play a major role in governing intestinal stem cell compartmentalization, differentiation dynamics, and organ-level self-renewal. However, scalable platforms that recapitulate the architecture and gradients present in vivo are absent. We present a platform in which individually addressable arrays of chemical gradients along the intestinal crypt long axis can be generated, enabling scalable culture of primary in vitro colonic epithelial replicas. The platform utilizes standardized well plate spacing, maintains access to basal and luminal compartments, and relies on a photopatterned porous membrane to act as diffusion windows while supporting the in vitro crypts. Simultaneous fabrication of 3875 crypts over a single membrane was developed. Growth factor gradients were modeled and then experimentally optimized to promote long-term health and self-renewal of the crypts which were assayed in situ by confocal fluorescence microscopy. The cultured in vitro crypt arrays successfully recapitulated the architecture and luminal-to-basal phenotypic polarity observed in vivo. Furthermore, known signaling regulators (e.g., butyrate and DAPT) produced measurable and predictable effects on the organized cell compartments, each decreasing crypt proliferation in the basal regions to negligible values. This platform is readily adaptable to the screening of tissue from individual patients to assay the impact of food and bacterial metabolites and/or drugs on colonic crypt dynamics. Importantly, the cassette is compatible with a wide range of sensing/detection modalities, and the developed fabrication methods should find applications for other cell and tissue types.
Schizophrenia polygenic risk score and 20-year course of illness in psychotic disorders.

Understanding whether and how the schizophrenia polygenic risk score (SZ PRS) predicts course of illness could improve diagnosis and prognostication in psychotic disorders. We tested whether the SZ PRS predicts symptoms, cognition, illness severity, and diagnostic changes over the 20 years following first admission. The Suffolk County Mental Health Project is an inception cohort study of first-admission patients with psychosis. Patients were assessed six times over 20 years, and 249 provided DNA. Geographically- and demographically-matched never psychotic adults were recruited at year 20, and 205 provided DNA. Symptoms were rated using the Schedule for the Assessment of Positive Symptoms and Schedule for the Assessment of Negative Symptoms. Cognition was evaluated with a comprehensive neuropsychological battery. Illness severity and diagnosis were determined by consensus of study psychiatrists. SZ PRS was significantly higher in first-admission than never psychotic groups. Within the psychosis cohort, the SZ PRS predicted more severe negative symptoms (β = 0.21), greater illness severity (β = 0.28), and worse cognition (β = −0.35), across the follow-up. The SZ PRS was the strongest predictor of diagnostic shifts from affective to non-affective psychosis over the 20 years (AUC = 0.62). The SZ PRS predicts persistent differences in cognition and negative symptoms. The SZ PRS also predicts who among those who appear to have a mood disorder with psychosis at first admission will ultimately be diagnosed with a schizophrenia spectrum disorder. These findings show potential for the SZ PRS to become a tool for diagnosis and treatment planning.
Hybrid Dispersion Dirac Semimetal and Hybrid Weyl Phases in Luttinger Semimetals: A Dynamical Approach

It is shown that hybrid Dirac and Weyl semimetals can be realized in a 3D Luttinger semimetal with quadratic band touching (QBT). This is illustrated using a periodic kicking scheme. In particular, the focus is on a momentum‐dependent driving (nonuniform driving) and the realization of various hybrid Dirac and Weyl semimetals is demonstrated. A unique hybrid dispersion Dirac semimetal with two nodes is identified, where one of the nodes is linear while the other is dispersed quadratically. Next, it is shown that by tilting QBT via periodic driving and in the presence of an external magnetic field, one can realize various single/double hybrid Weyl semimetals depending on the strength of external field. Finally, it is noted that in principle, phases that are found in this work can also be realized by employing the appropriate electronic interactions.
New analytical tools for HDG in elasticity, with applications to elastodynamics

We present some new analytical tools for the error analysis of hybridizable discontinuous Galerkin (HDG) method for linear elasticity. These tools allow us to analyze more variants of HDG method using the projection-based approach, which renders the error analysis simple and concise. The key result is a tailored projection for the Lehrenfeld-Schoberl type HDG (HDG+ for simplicity) methods. By using the projection we recover the error estimates of HDG+ for steady-state and time-harmonic elasticity in a simpler analysis. We also present a semi-discrete (in space) HDG+ method for transient elastic waves and prove it is uniformly-in-time optimal convergent by using the projection-based error analysis. Numerical experiments supporting our analysis are presented at the end.
Verified Uncertainty Calibration

Applications such as weather forecasting and personalized medicine demand models that output calibrated probability estimates---those representative of the true likelihood of a prediction. Most models are not calibrated out of the box but are recalibrated by post-processing model outputs. We find in this work that popular recalibration methods like Platt scaling and temperature scaling are (i) less calibrated than reported, and (ii) current techniques cannot estimate how miscalibrated they are. An alternative method, histogram binning, has measurable calibration error but is sample inefficient---it requires $O(B/\epsilon^2)$ samples, compared to $O(1/\epsilon^2)$ for scaling methods, where $B$ is the number of distinct probabilities the model can output. To get the best of both worlds, we introduce the scaling-binning calibrator, which first fits a parametric function that acts like a baseline for variance reduction and then bins the function values to actually ensure calibration. This requires only $O(1/\epsilon^2 + B)$ samples. We then show that methods used to estimate calibration error are suboptimal---we prove that an alternative estimator introduced in the meteorological community requires fewer samples ($O(\sqrt{B})$ instead of $O(B)$). We validate our approach with multiclass calibration experiments on CIFAR-10 and ImageNet, where we obtain a 35\% lower calibration error than histogram binning and, unlike scaling methods, guarantees on true calibration.
Population-level Eccentricity Distributions of Imaged Exoplanets and Brown Dwarf Companions: Dynamical Evidence for Distinct Formation Channels

The orbital eccentricities of directly imaged exoplanets and brown dwarf companions provide clues about their formation and dynamical histories. We combine new high-contrast imaging observations of substellar companions obtained primarily with Keck/NIRC2 together with astrometry from the literature to test for differences in the population-level eccentricity distributions of 27 long-period giant planets and brown dwarf companions between 5 and 100 au using hierarchical Bayesian modeling. Orbit fits are performed in a uniform manner for companions with short orbital arcs; this typically results in broad constraints for individual eccentricity distributions, but together as an ensemble, these systems provide valuable insight into their collective underlying orbital patterns. The shape of the eccentricity distribution function for our full sample of substellar companions is approximately flat from e = 0–1. When subdivided by companion mass and mass ratio, the underlying distributions for giant planets and brown dwarfs show significant differences. Low mass ratio companions preferentially have low eccentricities, similar to the orbital properties of warm Jupiters found with radial velocities and transits. We interpret this as evidence for in situ formation on largely undisturbed orbits within massive extended disks. Brown dwarf companions exhibit a broad peak at e ≈ 0.6–0.9 with evidence for a dependence on orbital period. This closely resembles the orbital properties and period-eccentricity trends of wide (1–200 au) stellar binaries, suggesting that brown dwarfs in this separation range predominantly form in a similar fashion. We also report evidence that the "eccentricity dichotomy" observed at small separations extends to planets on wide orbits: the mean eccentricity for the multi-planet system HR 8799 is lower than for systems with single planets. In the future, larger samples and continued astrometric orbit monitoring will help establish whether these eccentricity distributions correlate with other parameters such as stellar host mass, multiplicity, and age.
Local Non-Bayesian Social Learning with Stubborn Agents *

With the rise of social networks like Twitter and Facebook, people increasingly receive news through non-traditional sources. One recent study shows that two-thirds of American adults have gotten news through social media [1]. Such news sources are fundamentally different than traditional ones like print media and television, in the sense that social media users read and discuss news on the same platform. As a consequence, users turning to these platforms for news receive information not only from major publications but from others users as well; in the words of [2], a user “with no track record or reputation can in some cases reach as many readers as Fox News, CNN, or the New York Times.” This phenomenon famously reared its head during the 2016 United States presidential election, when fake news stories were shared tens of millions of times [2].
Harnessing the Power of Infinitely Wide Deep Nets on Small-data Tasks

Recent research shows that the following two models are equivalent: (a) infinitely wide neural networks (NNs) trained under l2 loss by gradient descent with infinitesimally small learning rate (b) kernel regression with respect to so-called Neural Tangent Kernels (NTKs) (Jacot et al., 2018). An efficient algorithm to compute the NTK, as well as its convolutional counterparts, appears in Arora et al. (2019a), which allowed studying performance of infinitely wide nets on datasets like CIFAR-10. However, super-quadratic running time of kernel methods makes them best suited for small-data tasks. We report results suggesting neural tangent kernels perform strongly on low-data tasks. 1. On a standard testbed of classification/regression tasks from the UCI database, NTK SVM beats the previous gold standard, Random Forests (RF), and also the corresponding finite nets. 2. On CIFAR-10 with 10 – 640 training samples, Convolutional NTK consistently beats ResNet-34 by 1% - 3%. 3. On VOC07 testbed for few-shot image classification tasks on ImageNet with transfer learning (Goyal et al., 2019), replacing the linear SVM currently used with a Convolutional NTK SVM consistently improves performance. 4. Comparing the performance of NTK with the finite-width net it was derived from, NTK behavior starts at lower net widths than suggested by theoretical analysis(Arora et al., 2019a). NTK’s efficacy may trace to lower variance of output.
Psychological Processes and Symptom Outcomes in Mindfulness-Based Stress Reduction for Cancer Survivors: A Pilot Study.

Growing evidence supports the efficacy of mindfulness-based interventions for symptoms in cancer survivors. Identifying theory-based psychological processes underlying their effects on symptoms would inform research to enhance their efficacy and cost-effectiveness. We conducted secondary analyses examining the effect of mindfulness-based stress reduction (MBSR) for cancer-related fatigue on mindfulness facets, self-compassion, and psychological inflexibility. We also examined whether changes in these processes were associated with the symptom outcomes of fatigue interference, sleep disturbance, and emotional distress. Thirty-five persistently fatigued cancer survivors (94% female, 77% breast cancer survivors) were randomized to either MBSR for cancer-related fatigue or a waitlist control (WC) condition. Self-report measures were administered at pre-intervention, post-intervention, and 1-month follow-up. Then the WC group received MBSR and completed a post-intervention follow-up. Linear mixed modeling analyses of the first three time points showed steady increases over time for certain mindfulness facets (observing, acting with awareness, and nonjudging) and self-compassion in favor of the MBSR group. When analyzing pre- and post-intervention data across study conditions, none of the psychological processes predicted change in fatigue interference. However, increased nonjudging was associated with decreased sleep disturbance (β = −.39, p = 0.003), and increased acting with awareness was associated with decreased emotional distress (β = − 0.36, p = 0.003). Self-compassion did not predict change in symptom outcomes. Results point to specific psychological processes that may be targeted to maximize the efficacy of future MBSR interventions for cancer survivors.
Zeros of Normalized Sections of Non Convergent Power Series

A well known result due to Carlson (C R Acad Sci Paris 178:1677–1680, 1924) affirms that a power series with finite and positive radius of convergence R has no Ostrowski gaps if and only if the sequence of zeros of its nth sections is asymptotically equidistributed to $$\partial \mathbb {D}_R$$. Here we extend this characterization to those power series with null radius of convergence, modulo some necessary normalizations of the sequence of the sections of f.
A truthful cardinal mechanism for one-sided matching

We revisit the well-studied problem of designing mechanisms for one-sided matching markets, where a set of n agents needs to be matched to a set of n heterogeneous items. Each agent i has a value vi,j for each item j, and these values are private information that the agents may misreport if doing so leads to a preferred outcome. Ensuring that the agents have no incentive to misreport requires a careful design of the matching mechanism, and mechanisms proposed in the literature mitigate this issue by eliciting only the ordinal preferences of the agents, i.e., their ranking of the items from most to least preferred. However, the efficiency guarantees of these mechanisms are based only on weak measures that are oblivious to the underlying values. In this paper we achieve stronger performance guarantees by introducing a mechanism that truthfully elicits the full cardinal preferences of the agents, i.e., all of the vi,j values. We evaluate the performance of this mechanism using the much more demanding Nash bargaining solution as a benchmark, and we prove that our mechanism significantly outperforms all ordinal mechanisms (even non-truthful ones). To prove our approximation bounds, we also study the population monotonicity of the Nash bargaining solution in the context of matching markets, providing both upper and lower bounds which are of independent interest.