cssi/SciSciGPT-SciSciNet huggingface dataset:
Forensic Interviewers' Difficulty With Invitations: Faux Invitations and Negative Recasting

An ongoing challenge for forensic interviewers is to maximize their use of invitations, such as requests that the child "tell me more about" details mentioned by the child. Examining 434 interviews with 4- to 12-year-old children questioned about abuse, this study analyzed (1) faux invitations, in which interviewers prefaced questions with "tell me" but then asked a noninvitation, (2) negative recasts, in which interviewers started to ask an invitation but then recast the question as a wh- or option-posing question, and (3) other aspects of questions that may relate to productivity independent of their status as invitations. About one fourth of "tell me" questions were faux invitations, and over 80% of recasts were negative. The frequency of both faux invitations and negative recasts increased during the substantive phase of the interviews, and these were related to decreased productivity, increased nonresponsiveness, and increased uncertainty. In contrast, use of exhaustive terms (e.g., "tell me everything") and nonstatic questions (e.g., about actions) was related to increased productivity. The results suggest that training should teach interviewers when and how strategic use of invitations and other question types can elicit specific types of forensically relevant information.
ON THE GEOMETRY OF CERTAIN ISOSPECTRAL SETS IN THE FULL KOSTANT-TODA LATTICE

This paper uses momentum mappings on generalized flag manifolds and their momentum polytopes to study the geometry of the level sets of the 1-chop integrals of the full Kostant-Toda lattice in certain isospectral submanifolds of the phase space. Expressions for these integrals are derived
On neuronal capacity

We define the capacity of a learning machine to be the logarithm of the number (or volume) of the functions it can implement. We review known results, and derive new results, estimating the capacity of several neuronal models: linear and polynomial threshold gates, linear and polynomial threshold gates with constrained weights (binary weights, positive weights), and ReLU neurons. We also derive capacity estimates and bounds for fully recurrent networks and layered feedforward networks.
Numerically Destabilizing Minimal Discs

When calculating the index of a minimal surface, the set of smooth functions on a domain with compact support is the standard setting to describe admissible variations. We show that the set of admi...
Bioinformatics pipeline using JUDI: Just Do It!

Summary Large-scale data analysis in bioinformatics requires pipelined execution of multiple software. Generally each stage in a pipeline takes considerable computing resources and several workflow management systems (WMS), e.g. Snakemake, Nextflow, Common Workflow Language, Galaxy, etc. have been developed to ensure optimum execution of the stages across two invocations of the pipeline. However, when the pipeline needs to be executed with different settings of parameters, e.g. thresholds, underlying algorithms, etc. these WMS require significant scripting to ensure an optimal execution. We developed JUDI on top of DoIt, a Python based WMS, to systematically handle parameter settings based on the principles of database management systems. Using a novel modular approach that encapsulates a parameter database in each task and file associated with a pipeline stage, JUDI simplifies plug-and-play of the pipeline stages. For a typical pipeline with n parameters, JUDI reduces the number of lines of scripting required by a factor of O(n). With properly designed parameter databases, JUDI not only enables reproducing research under published values of parameters but also facilitates exploring newer results under novel parameter settings. Availability and implementation https://github.com/ncbi/JUDI. Supplementary information Supplementary data are available at Bioinformatics online.
Valuing innovative endoscopic techniques: prophylactic clip closure after endoscopic resection of large colon polyps.

Background and Aims Clip closure of the mucosal defect after resecting large (≥20 mm) nonpedunculated colorectal polyps reduces postprocedure bleeding and is cost saving for payers. Clip costs are not reimbursed by payers, posing a major barrier to adoption of this technique in the community. We aimed to determine appropriate clip costs to support broader use of this procedure in practice. Methods We performed budget impact analysis using our recent decision analytic model, comparing prophylactic clip closure with no clip closure on national cost and outcomes data, to determine the maximum feasible clip price while maintaining cost savings in practice. Sensitivity analyses were performed on important clinical factors. Results In the original model, the baseline postprocedure bleeding risk was 6.8%, increasing cost of care by $614.11 averaged among all patients undergoing large polyp resection without clip closure. Prophylactic clip closure of only large right-sided polyps reduced postprocedure bleeding risk by 70.7% but resulted in cost saving only if the price of clips was $100 or less. Comparatively, prophylactic clip closure of large left-sided polyps had no clinical benefit and was not cost saving. Clip closure strategies focused only on extra-large polyps (≥40 mm), or patients taking antithrombotics regardless of polyp characteristics, were only minimally cost saving. Cost savings and maximum tolerated clip prices depended on medical comorbidity, which directly influences the costs of care to manage postprocedure bleeding. Conclusions Prophylactic clip closure after endoscopic resection of large colon polyps, particularly those in the right colon segment, is cost saving but requires clip costs less than $100. Translating these findings into practice requires gastroenterology practices to obtain reimbursement from payers for improved clinical outcomes and to align commercial clip prices with this clinical indication.
How Big are Fiscal Multipliers in Latin America

This paper uses the strategy and data of Blanchard and Perotti (BP) to identify fiscal shocks and estimate fiscal multipliers for the United States. With these results, it computes the cumulative multiplier of Ramey and Zubairy (2018), now common in the literature. It finds that, contrary to the peak and through multipliers reported by BP, the cumulative tax multiplier is much larger than the cumulative spending one. Hence, the conclusions depend on the definition of multiplier. This methodology is also used to estimate the effects of fiscal shocks on economic activity in eight Latin American countries. The results suggest that the fiscal multipliers vary significantly across countries, and in some cases multipliers are larger than previously estimated.
DEDUCE: Diverse scEne Detection methods in Unseen Challenging Environments

In recent years, there has been a rapid increase in the number of service robots deployed for aiding people in their daily activities. Unfortunately, most of these robots require human input for training in order to do tasks in indoor environments. Successful domestic navigation often requires access to semantic information about the environment, which can be learned without human guidance. In this paper, we propose a set of DEDUCE1 -Diverse scEne Detection methods in Unseen Challenging Environments algorithms which incorporate deep fusion models derived from scene recognition systems and object detectors. The five methods described here have been evaluated on several popular recent image datasets, as well as real-world videos acquired through multiple mobile platforms. The final results show an improvement over the existing state-of-the-art visual place recognition systems.1Supplementary material including code and the videos of the different experiments are available at https://sites.google.com/eng.ucsd.edu/deduce.
An Evaluation of Alternative Multiple Testing Methods for Finance Applications

In almost every area of empirical finance, researchers confront multiple tests. One high-profile example is the identification of outperforming investment managers, many of whom beat their benchmarks purely by luck. Multiple testing methods are designed to control for luck. Factor selection is another glaring case in which multiple tests are performed, but numerous other applications do not receive as much attention. One important example is a simple regression model testing five variables. In this case, because five variables are tried, a t-statistic of 2.0 is not enough to establish significance. Our paper provides a guide to various multiple testing methods and details a number of applications. We provide simulation evidence on the relative performance of different methods across a variety of testing environments. The goal of our paper is to provide a menu that researchers can choose from to improve inference in financial economics.
Wide-vergence, multi-spectral adaptive optics scanning laser ophthalmoscope with diffraction-limited illumination and collection.

Visualizing and assessing the function of microscopic retinal structures in the human eye is a challenging task that has been greatly facilitated by ophthalmic adaptive optics (AO). Yet, as AO imaging systems advance in functionality by employing multiple spectral channels and larger vergence ranges, achieving optimal resolution and signal-to-noise ratios (SNR) becomes difficult and is often compromised. While current-generation AO retinal imaging systems have demonstrated excellent, near diffraction-limited imaging performance over wide vergence and spectral ranges, a full theoretical and experimental analysis of an AOSLO that includes both the light delivery and collection optics has not been done, and neither has the effects of extending wavefront correction from one wavelength to imaging performance in different spectral channels. Here, we report a methodology and system design for simultaneously achieving diffraction-limited performance in both the illumination and collection paths for a wide-vergence, multi-spectral AO scanning laser ophthalmoscope (SLO) over a 1.2 diopter vergence range while correcting the wavefront in a separate wavelength. To validate the design, an AOSLO was constructed to have three imaging channels spanning different wavelength ranges (543 ± 11 nm, 680 ± 11 nm, and 840 ± 6 nm, respectively) and one near-infrared wavefront sensing channel (940 ± 5 nm). The AOSLO optics and their alignment were determined via simulations in optical and optomechanical design software and then experimentally verified by measuring the AOSLO’s illumination and collection point spread functions (PSF) for each channel using a phase retrieval technique. The collection efficiency was then measured for each channel as a function of confocal pinhole size when imaging a model eye achieving near-theoretical performance. Imaging results from healthy human adult volunteers demonstrate the system’s ability to resolve the foveal cone mosaic in all three imaging channels despite a wide spectral separation between the wavefront sensing and imaging channels.
Effect of basal precipitates on extension twinning and pyramidal slip: A micro-mechanical and electron microscopy study of a Mg–Al binary alloy

Abstract Understanding the effects of basal precipitates on plasticity is of scientific interest and practical importance in the development of high-strength magnesium alloys. In this study, compression experiments are carried out on solution-treated and aged Mg–9wt.% Al binary alloy single-crystal micropillars cut from large-grained polycrystalline samples. The samples are compressed in two different orientations ( and ) to examine the effects of basal-precipitates on extension twinning and pyramidal slip, respectively. In the solution-treated, precipitate-free, samples, the propagation and thickening of single twins dominates, while in the aged micropillars with Mg17Al12 basal-precipitates, multiple twins are observed suggesting a substantial increase in the stress required to propagate and thicken twins compared to nucleating twins. In addition, these basal precipitates are observed to be more effective than c-axis rod precipitates in Mg-Zn alloy in impeding twin growth for the studied volume fractions. In samples, the plate-like, Mg17Al12 precipitates are found to provide enormous strengthening under compression, compared to solution-treated samples, by hindering the motion of pyramidal dislocations. Further still, our comparative analysis suggests that pyramidal-slip/precipitate interactions, whether via bowing between or cutting precipitates, differ from one Mg alloy to another depending on the geometry and alignment of their precipitates. Our findings offer insights into how manipulating precipitation in the design and processing of Mg alloys can lead to superior mechanical properties.
AKT but not MYC promotes reactive oxygen species-mediated cell death in oxidative culture

Oncogenes can create metabolic vulnerabilities in cancer cells. We tested how AKT and MYC affect the ability of cells to shift between respiration and glycolysis. Using immortalized mammary epithelial cells, we discovered that constitutively active AKT but not MYC induced cell death in galactose culture, where cells rely on oxidative phosphorylation for energy generation. However, the negative effects of AKT were temporary, and AKT-expressing cells recommenced growth after ∼15 days in galactose. To identify the mechanisms regulating AKT-mediated cell death, we used metabolomics and found that AKT cells dying in galactose upregulated glutathione metabolism. Proteomic profiling revealed that AKT cells dying in galactose also upregulated nonsense-mediated mRNA decay, a marker of sensitivity to oxidative stress. We therefore measured levels of reactive oxygen species (ROS) and discovered that galactose induced ROS exclusively in cells expressing AKT. Furthermore, ROS were required for galactose-induced death of AKT-expressing cells. We then confirmed that galactose induced ROS-mediated cell death in breast cancer cells with upregulated AKT signaling. These results demonstrate that AKT but not MYC restricts the flexibility of cancer cells to use oxidative phosphorylation.
Deletion of M-Opsin Prevents M Cone Degeneration in a Mouse Model of Leber Congenital Amaurosis.

Mutations in retinoid isomerase (RPE65) or lecithin-retinol acyltransferase (LRAT) disrupt 11-cis-retinal synthesis and cause Leber congenital amaurosis (LCA). Despite the success of recent RPE65 gene therapy, follow-up studies show that patients continue to experience photoreceptor degeneration and lose vision benefit over time. In Lrat−/− mouse model, mislocalized medium (M)-wavelength opsin was degraded, whereas mislocalized short (S)-wavelength opsin accumulated before the onset of cone degeneration. The mechanism for the foveal M/long-wavelength cone photoreceptor degeneration in LCA is unknown. By crossing Lrat−/− mice with a proteasome reporter mouse strain, this study showed that M-opsin–enriched dorsal cones in Lrat−/− mice exhibit proteasome stress because of the degradation of large amounts of M-opsin. Deletion of M-opsin relieves the proteasome stress and completely prevents M cone degeneration in Lrat−/−Opn1sw−/− mice (a pure M cone LCA model, Opn1sw encoding S-opsin) for at least 12 months. These results suggest that M-opsin degradation–associated proteasome stress plays a major role in M cone degeneration in Lrat−/− model. This finding may represent a general mechanism for M cone degeneration in multiple forms of cone degeneration because of M-opsin mislocalization and degradation. These results have important implications for the current gene therapy strategy for LCA that emphasizes the need for combinatorial therapies to both improve vision and slow photoreceptor degeneration.
Energy-based graph convolutional networks for scoring protein docking models

Structural information about protein-protein interactions, often missing at the interactome scale, is important for mechanistic understanding of cells and rational discovery of therapeutics. Protein docking provides a computational alternative for such information. However, ranking near-native docked models high among a large number of candidates, often known as the scoring problem, remains a critical challenge. Moreover, estimating model quality, also known as the quality assessment problem, is rarely addressed in protein docking. In this study, the two challenging problems in protein docking are regarded as relative and absolute scoring, respectively, and addressed in one physics-inspired deep learning framework. We represent protein and complex structures as intra- and inter-molecular residue contact graphs with atom-resolution node and edge features. And we propose a novel graph convolutional kernel that aggregates interacting nodes' features through edges so that generalized interaction energies can be learned directly from 3D data. The resulting energy-based graph convolutional networks (EGCN) with multihead attention are trained to predict intra- and inter-molecular energies, binding affinities, and quality measures (interface RMSD) for encounter complexes. Compared to a state-of-the-art scoring function for model ranking, EGCN significantly improves ranking for a critical assessment of predicted interactions (CAPRI) test set involving homology docking; and is comparable or slightly better for Score_set, a CAPRI benchmark set generated by diverse community-wide docking protocols not known to training data. For Score_set quality assessment, EGCN shows about 27% improvement to our previous efforts. Directly learning from 3D structure data in graph representation, EGCN represents the first successful development of graph convolutional networks for protein docking.
Tree invariants and Milnor linking numbers with indeterminacy

This paper concerns the tree invariants of string links, introduced by Kravchenko and Polyak, which are closely related to the classical Milnor linking numbers also known as μ-invariants. We prove...
Biquandle module invariants of oriented surface-links

We define invariants of oriented surface-links by enhancing the biquandle counting invariant using \textit{biquandle modules}, algebraic structures defined in terms of biquandle actions on commutative rings analogous to Alexander biquandles. We show that bead colorings of marked graph diagrams are preserved by Yoshikawa moves and hence define enhancements of the biquandle counting invariant for surface links. We provide examples illustrating the computation of the invariant and demonstrate that these invariants are not determined by the first and second Alexander elementary ideals and characteristic polynomials.
Autophosphorylation of the CK1 kinase domain regulates enzyme activity and function

Abstract CK1 enzymes are conserved, acidophilic serine/threonine kinases with a variety of critical cellular functions; misregulation of CK1 contributes to cancer, neurodegenerative diseases, and sleep phase disorders. Despite this, little is known about how CK1 activity is controlled. Here, we describe a new mechanism of CK1 autoregulation that is conserved in CK1 enzymes from yeast to human – the autophosphorylation of a threonine in the mobile L-EF loop proximal to the active site. Phosphorylation at this site inhibits kinase activity, in contrast to well-characterized T-loop autophosphorylation in other kinase families. Consequently, yeast and human enzymes with phosphoablating mutations at this site are hyperactive. In S. pombe, hyperactive CK1 causes defects in cell growth and morphology at a high level but protection from heat shock at a low level, highlighting the necessity of regulated CK1 function. We propose that phosphorylation on the L-EF loop prevents substrate docking with the kinase domain by shielding the positively charged binding pocket and/or sterically hindering the active site. Due to the strong sequence conservation of this autophosphorylation site and the functional importance of the L-EF loop, which is unique to the CK1 family of kinases, this mechanism is likely to regulate the majority of CK1 enzymes in vivo. Significance Statement Kinases in the CK1 family are important signaling enzymes, and they function in multiple pathways within the same cell. Misregulation of CK1 activity contributes to human disease, including cancer, neurodegenerative disease, and sleep phase disorders, yet the mechanisms that control CK1 activity are not well understood. We have identified a conserved autophosphorylation site in the CK1 kinase domain that inhibits substrate phosphorylation. We hypothesize that by using kinase domain autophosphorylation in combination with other regulatory mechanisms, CK1 enzymes can coordinate the phosphorylation of their substrates in different pathways.
Integrated likelihood for phylogenomics under a no-common-mechanism model.

Multi-locus species phylogeny inference is based on models of sequence evolution on gene trees as well as models of gene tree evolution within the branches of species phylogenies. Almost all statistical methods for this inference task assume a common mechanism across all loci as captured by a single value of each branch length of the species phylogeny. In this paper, we pursue a “no common mechanism" (NCM) model, where every gene tree evolves according to its own parameters of the species phylogeny. Based on this model, we derive an analytically integrated likelihood of both species trees and networks given the gene trees of multiple loci under an NCM model. We demonstrate the performance of inference under this integrated likelihood on both simulated and biological data. The model presented here will afford opportunities for exploring connections among various criteria for estimating species phylogenies from multiple, independent loci. Furthermore, further development of this model could potentially result in more efficient methods for searching the space of species phylogenies by focusing solely on the topology of the phylogeny.
Gifts and goals: Behavioral nudges to improve child food choice at school

Abstract The rising childhood obesity rate calls for interventions aimed at improving food choice. We conducted a field experiment with over 1,400 children to measure the impact of interventions based on two behavioral theories: reciprocity and theories of self-control. We found that unconditional gifts (triggering reciprocity) increased choice of the healthier milk by 15 percentage points. Giving the option to set a goal (an internal commitment device) increased choice of the healthier milk by 10 percentage points. Our results have implications for policy and practice, as low-cost school-based interventions may have an impact on what kids choose to eat and (by extension) on obesity.
IN-PROCESS OPTICAL GAUGING FOR NUMERICAL MACHINE TOOL CONTROL

Closing a control loop on a transducer coupled to a slide positioning screw or on a tool slide itself places all machine errors such as backlash, tool deflection, tool wear, lead error, etc. external to the control loop. These errors are accommodated by an optical measuring/control system which directly monitors the workpiece in-process and uses the actual workpiece dimensional data to close the tool-position control loop. The system uses the image of the diffuse reflection of incident laser light from the workpiece focused on a position sensitive photodetector as a tracking signal for mechanical distance measurement to the workpiece surface from a fixed reference. Measurement resolution of ± .0004′ (± 10 microns) is achieved. Design data relating laser power, source-target distance, measured surface roughness and grain, optical base line length to measurement precision, resolution, frequence response and measurement range are discussed.
When did Ownership Separate from Control? Corporate Governance in the Early Nineteenth Century

�This article analyzes the ownership structures and governance institutions of New York’s corporations in the 1820s, using a new dataset collected from the records of the state’s 1823 capital tax, and from the corporate charters. In contrast to Berle and Means’s account of the development of the corporation, the results indicate that many firms were dominated by large shareholders, who were represented on the firms’ boards, and held sweeping power to utilize the firms’ resources for their own benefit. To address this problem, many firms configured their voting rights in a way that curtailed the power of large investors. “. . . we complain of directors considering themselves the company, when they are merely the agents.” 1
Cooperative Database Systems

Research in cooperative answering stems from three areas: natural language interface and dialogue systems, database systems, and logic programming and deductive database systems. The emphasis of this article is on cooperative databases. It covers such topics as presuppositions, misconceptions, intensional query answering, user modeling, query relaxation, and associative query answering. Keywords: cooperative database system (CoBase); intensional query answering; query relaxation; associative query answering; cooperative operations; type abstraction hierarchy (TAH)
Propagating instabilities in structures

Publisher Summary This chapter analyzes propagating instabilities in structures. In practice, propagating instabilities are initiated from local imperfections that locally weaken the structure and cause local change in geometry (collapse). Very much like a set of dominoes, once the geometric integrity of such structures is compromised, the instability has the potential of spreading over the whole structure. The problem of finite inflation of an elastic tube is discussed in Section II of this chapter and demonstrates the complexity of a localization-type instability, which in this case takes the form of a bulge and the subsequent propagation or spreading of the bulge. The problem, once understood, can be solved quite adequately with relative ease using finite-deformation membrane theory. Thus, it provides a model problem for introducing some of the features of this type of behavior. Section III summarizes much of the progress achieved in this problem to date. Section IV addresses localized collapse and the propagation of collapse in shells lining stiffer cylinders. Section V revisits the classical problem of buckling of arches and demonstrates how a long panel with an arch cross section, loaded by pressure, develops a localized buckle that then can propagate at a relatively low pressure and collapse the whole panel.
Censored Quantile Instrumental Variable Estimates of the Price Elasticity of Expenditure on Medical Care

Efforts to control medical care costs depend critically on how individuals respond to prices. I estimate the price elasticity of expenditure on medical care using a censored quantile instrumental variable (CQIV) estimator. CQIV allows estimates to vary across the conditional expenditure distribution, relaxes traditional censored model assumptions, and addresses endogeneity with an instrumental variable. My instrumental variable strategy uses a family member's injury to induce variation in an individual's own price. Across the conditional deciles of the expenditure distribution, I find elasticities that vary from -0.76 to -1.49, which are an order of magnitude larger than previous estimates.
Bootstrapping Structural VARs: Avoiding a Potential Bias in Confidence Intervals for Impulse Response Functions

Constructing bootstrap confidence intervals for impulse response functions (IRFs) from structural vector autoregression (SVAR) models has become standard practice in empirical macroeconomic research. The accuracy of such confidence intervals can deteriorate severely, however, if the bootstrap IRFs are biased. We document an apparently common source of bias in the estimation of the VAR error covariance matrix which can be easily reduced by a scale adjustment. This bias is generally unrecognized because it only affects the bootstrap estimates of the error variance, not the original OLS estimates. Nevertheless, as we illustrate here, analytically, with sampling experiments, and in an example from the literature, the bootstrap error variance bias can have significant distorting effects on bootstrap IRF confidence intervals. We also show that scale-adjusted bootstrap confidence intervals can be expected to exhibit improved coverage accuracy.
Chapter 16 – Salamanders

Salamanders are tailed amphibians with distinct heads and occur largely in the Northern Hemisphere (Holoarctic). Most have four well-developed limbs. About 619 species are known, distributed among 10 families. Most salamanders live in moist habitats, frequently adjacent to or in streams, lakes, or swamps. One group of plethodontids (lungless salamanders), the bolitoglossines, has undergone a major radiation in the tropics of Mexico and Central America, with a few species occurring in the Amazon rainforest. Nearly 45% of known species belong to this subfamily. Conservation status of salamanders is summarized. An up-to-date phylogeny details approximate time periods during which divergences occurred during the evolutionary history of salamanders and shows evolutionary relationships among the families as we now know them. Taxonomic accounts provide information on generic content, distribution, characteristics, and biology of each family.
The Mismatch between Public Nuisance Law and Global Warming

This article makes three principal points regarding the recent efforts to use public nuisance litigation to address the problem of climate change. First, the courts should not invoke the political question doctrine to dismiss such cases but instead focus on lack of private party standing and the impossibility of proving causation as grounds for dismissal. Second, the courts and commentators would better understand the disadvantages of common law litigation as a means of addressing climate change if they conceptualized climate change as not a traditional pollution problem with a polluter and victim of pollution but rather as a large-scale commons resource management problem. Finally, state legislative action to address climate change is likely to be more effective and less overreaching than regulation via public nuisance litigation, and may be needed to prompt responsible action by the federal political branches. The courts can facilitate responsible state legislative action by following approaches to fede...
Lack of association between angiotensin-converting enzyme inhibitors and angiotensin receptor blockers and pain improvement in patients with oral cancer

Background There is a growing body of literature implicating angiotensin II in the modulation of tumour-associated inflammation and pain. However, the impact of angiotensin-converting enzyme inhibitors (ACEis) and angiotensin II receptor blockers (ARBs) on pain and inflammation has not yet been studied in oral cancers. The objective is to investigate the role of ACEi and ARB pharmacotherapy on preoperative pain and inflammatory biomarkers, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and monocyte-to-lymphocyte ratio (MLR), in patients with oral cancer. Methods We performed a retrospective study on patients who underwent oral cancer surgery. The Wilcoxon rank-sum test or Kruskal-Wallis analysis was used to evaluate differences in demographic, tumour-related and preoperative characteristics and amongst patients using ARBs, ACEis and no treatment. Multivariable analysis was fitted to estimate the effects of important covariates on severe preoperative pain. Results A total of 162 patients with oral malignancies were included in the study. After adjusting for significant covariates, patients with perineural invasion were found to have higher levels of pain (p = 0.0278). Similarly, patients taking ARBs were found to have lower levels of perineural invasion (p = 0.035). The analysis did not demonstrate a significant difference in pain levels when comparing ARBs or ACEis to the no treatment group (p = 0.250). Furthermore, the use of ARB or ACEi did not significantly alter preoperative NLR (p = 0.701) or MLR (p = 0.869). Conclusions When compared to no treatment, ARBs and ACEis are not associated with significant analgesic effect or decreased inflammatory scores (NLR, PLR and MLR).
When to Use Convolutional Neural Networks for Inverse Problems

Reconstruction tasks in computer vision aim fundamentally to recover an undetermined signal from a set of noisy measurements. Examples include super-resolution, image denoising, and non-rigid structure from motion, all of which have seen recent advancements through deep learning. However, earlier work made extensive use of sparse signal reconstruction frameworks (e.g. convolutional sparse coding). While this work was ultimately surpassed by deep learning, it rested on a much more developed theoretical framework. Recent work by Papyan et. al. provides a bridge between the two approaches by showing how a convolutional neural network (CNN) can be viewed as an approximate solution to a convolutional sparse coding (CSC) problem. In this work we argue that for some types of inverse problems the CNN approximation breaks down leading to poor performance. We argue that for these types of problems the CSC approach should be used instead and validate this argument with empirical evidence. Specifically we identify JPEG artifact reduction and non-rigid trajectory reconstruction as challenging inverse problems for CNNs and demonstrate state of the art performance on them using a CSC method. Furthermore, we offer some practical improvements to this model and its application, and also show how insights from the CSC model can be used to make CNNs effective in tasks where their naive application fails.
Coercivity estimates for integro-differential operators

We provide a general condition on the kernel of an integro-differential operator so that its associated quadratic form satisfies a coercivity estimate with respect to the $$H^s$$ -seminorm.
Scattering for a particle interacting with a Bose gas

We study the long-time behavior of solutions to an ODE- Schrodinger type system that models the interaction of a particle with a Bose gas. We show that the particle has sonic or subsonic ballistic ...
A Machine-Learning-Based Importance Sampling Method to Compute Rare Event Probabilities

We develop a novel computational method for evaluating the extreme excursion probabilities arising from random initialization of nonlinear dynamical systems. The method uses excursion probability theory to formulate a sequence of Bayesian inverse problems that, when solved, yields the biasing distribution. Solving multiple Bayesian inverse problems can be expensive; more so in higher dimensions. To alleviate the computational cost, we build machine-learning-based surrogates to solve the Bayesian inverse problems that give rise to the biasing distribution. This biasing distribution can then be used in an importance sampling procedure to estimate the extreme excursion probabilities.
Logarithmic Kodaira dimension and zeros of holomorphic log-one-forms

In this paper, we prove that the zero-locus of any global holomorphic log-one-form on a projective log-smooth pair (X; D) of log-general type must be non-empty.
Effects of Internet Cognitive-Behavioral Therapy on Depressive Symptoms and Surrogates of Cardiovascular Risk in Human Immunodeficiency Virus: A Pilot, Randomized, Controlled Trial

Background Depression is associated with an increased risk of cardiovascular disease in human immunodeficiency virus (HIV). We hypothesized that reducing depressive symptoms would improve HIV-related cardiovascular risk. Methods We conducted a single-center, randomized (1:1), controlled, parallel-group, assessor-blinded, pilot trial comparing Beating the Blues US (BtB)-an evidence-based, 8-session, internet cognitive-behavioral therapy for depression-with usual care (UC) in HIV-positive participants receiving virologically suppressive antiretroviral therapy and with Patient Health Questionnaire (PHQ)-9 scores ≥10. The primary endpoint was change in brachial artery flow-mediated dilation (FMD) at 12 weeks. Secondary endpoints were FMD change at 24 weeks and inflammation, coagulation, and metabolic biomarker changes at 12 and 24 weeks. Results Fifty-four participants were randomized (27 in each arm). Mean reductions in PHQ-9 scores were significantly greater with BtB versus UC at 12 weeks (-5.60 vs -1.52; P = .007) and 24 weeks (-6.00 vs -1.38; P = .008); reductions in the Hopkins Symptom Checklist Depression Scale-20 scores were also significantly greater with BtB versus UC at 24 weeks (-0.72 vs -0.35; P = .029). Changes in FMD between arms were not significantly different at 12 or 24 weeks. Significantly larger reductions in soluble (s)CD14 and sCD163 with BtB versus UC were found at 12 and 24 weeks, respectively. Conclusions Compared with UC, internet cognitive-behavioral therapy using BtB resulted in greater improvements in depressive symptoms and monocyte activation markers but did not improve FMD in this pilot trial. These data support performing larger studies to determine the potential salutatory effects of behavioral therapies for depression on HIV-related inflammation.
Nucleation and Growth of CrSi2 on Si(111)

Chromium disilicide layers have been grown on Si(111) in a commercial molecular beam epitaxy machine. Islands are found to nucleate with more than one epitaxial orientation, and three different orientations have been identified: CrSi2(0001)//Si(111) with CrSi2 [1010]//Si[110]. CrSi2(0001)//Si(111) with CrSi2[ll20]//Si[1l0], and CrSi2(1100)//Si(111) with CrSi2[000l]//Si[112]. Very thin (2 nm) layers have been studied under a variety of growth conditions to determine factors controlling the orientation of nuclei. The degree and direction of substrate misorientation, the growth technique, and the use of a CoSi2 buffer layer are all factors affecting the morphology of CrSi2 islands.
Limited Regional Aerosol and Cloud Microphysical Changes Despite Unprecedented Decline in Nitrogen Oxide Pollution During the February 2020 COVID-19 Shutdown in China

Abstract Following the emergence of a novel coronavirus in Wuhan, China instituted shutdown measures starting in late January and continuing into February 2020 to arrest the spread of the disease This resulted in a sharp economic contraction unparalleled in recent Chinese history Satellite retrievals show that nitrogen dioxide pollution declined by an unprecedented amount (~50% regionally) from its expected unperturbed value, but regional-scale column aerosol loadings and cloud microphysical properties were not detectably affected The disparate impact is tied to differential economic impacts of the shutdown, in which transportation, a disproportionate source of nitrogen oxide emissions, underwent drastic declines (~90% reductions in passenger traffic), whereas industry and power generation, responsible for >90% of particulate emissions, were relatively less affected (~20% reductions in electricity and thermal power generation) A combination of anomalously warm and humid meteorological conditions and complex chemical interactions further decreased nitrogen dioxide concentrations but likely enhanced secondary aerosol formation
Beating humans in a penny-matching game by leveraging cognitive hierarchy theory and Bayesian learning.

It is a long-standing goal of artificial intelligence (AI) to be superior to human beings in decision making. Games are suitable for testing AI capabilities of making good decisions in non-numerical tasks. In this paper, we develop a new AI algorithm to play the penny-matching game considered in Shannon's "mind-reading machine" (1953) against human players. In particular, we exploit cognitive hierarchy theory and Bayesian learning techniques to continually evolve a model for predicting human player decisions, and let the AI player make decisions according to the model predictions to pursue the best chance of winning. Experimental results show that our AI algorithm beats 27 out of 30 volunteer human players.
Policy Note: A Universal Equity–Efficiency Model for Pricing Water

Drawing on theoretical, practical, and normative rationales, the analysis presented here calls for revisiting the prevailing water service paradigm, and the values and frames it reflects. As is inc...
Potassium starvation induces autophagy in yeast.

Autophagy is a conserved process that recycles cellular contents to promote survival. Although nitrogen limitation is the canonical inducer of autophagy, recent studies have revealed several other nutrients important to this process. In this study, we used a quantitative, high-throughput assay to identify potassium starvation as a new and potent inducer of autophagy in the yeast Saccharomyces cerevisiae. We found that potassium-dependent autophagy requires the core pathway kinases Atg1, Atg5, and Vps34, and other components of the phosphatidylinositol 3-kinase complex. Transmission EM revealed abundant autophagosome formation in response to both stimuli. RNA-Seq indicated distinct transcriptional responses: nitrogen affects transport of ions such as copper, whereas potassium targets the organization of other cellular components. Thus, nitrogen and potassium share the ability to influence molecular supply and demand but do so in different ways. Both inputs promote catabolism through bulk autophagy, but result in distinct mechanisms of cellular remodeling and synthesis.
Reduced Density Matrix Cumulants: The Combinatorics of Size-Consistency and Generalized Normal Ordering.

Reduced density matrix cumulants play key roles in the theory of both reduced density matrices and multiconfigurational normal ordering. We present a new, simpler generating function for reduced de...
Perturbation of in vivo Neural Activity Following α-Synuclein Seeding in the Olfactory Bulb

Background Parkinson's disease (PD) neuropathology is characterized by intraneuronal protein aggregates composed of misfolded α-Synuclein (α-Syn), as well as degeneration of substantia nigra dopamine neurons. Deficits in olfactory perception and aggregation of α-Syn in the olfactory bulb (OB) are observed during early stages of PD, and have been associated with the PD prodrome, before onset of the classic motor deficits. α-Syn fibrils injected into the OB of mice cause progressive propagation of α-Syn pathology throughout the olfactory system and are coupled to olfactory perceptual deficits. Objective We hypothesized that accumulation of pathogenic α-Syn in the OB impairs neural activity in the olfactory system. Methods To address this, we monitored spontaneous and odor-evoked local field potential dynamics in awake wild type mice simultaneously in the OB and piriform cortex (PCX) one, two, and three months following injection of pathogenic preformed α-Syn fibrils in the OB. Results We detected α-Syn pathology in both the OB and PCX. We also observed that α-Syn fibril injections influenced odor-evoked activity in the OB. In particular, α-Syn fibril-injected mice displayed aberrantly high odor-evoked power in the beta spectral range. A similar change in activity was not detected in the PCX, despite high levels of α-Syn pathology. Conclusion Together, this work provides evidence that synucleinopathy impacts in vivo neural activity in the olfactory system at the network-level.
Preclinical characterization of mobocertinib highlights the putative therapeutic window of this novel EGFR inhibitor to EGFR exon 20 insertion mutations.

Abstract Introduction EGFR exon 20 insertion mutations account for 10% of all EGFR mutations and are mostly insensitive to approved EGFR tyrosine kinase inhibitors (EGFR TKIs). Novel EGFR TKIs have been developed or repurposed for these mutants. A limited number of preclinical studies have detailed these EGFR TKIs. We sought to use commercially available mobocertinib (TAK-788) to characterize the preclinical therapeutic window of this EGFR TKI against EGFR mutations and to probe possible on-target mechanisms of resistance (EGFR-C797S). Methods We used models of EGFR mutations to probe representative first, second, third generation, and in-development EGFR exon 20-active (poziotinib, mobocertinib) TKIs. We also introduced EGFR-C797S to these models to identify mechanisms of resistance. Results Cells driven by the most common EGFR exon 20 insertion mutations (A767_V769dupASV, D770_N771insSVD, H773_V774insH, and others) were inhibited by in-development EGFR TKIs at doses below those affecting EGFR-wildtype; albeit more common EGFR mutations (exon 19 deletions and L858R) were inhibited more readily by mobocertinib and poziotinib. Mobocertinib was able to inhibit the phosphorylation of EGFR in multiple preclinical models. The presence of EGFR-C797S led to greater than 200-fold resistance in proliferation assays probing mobocertinib and osimertinib. A review of clinical studies of mobocertinib disclosed responses that could be lasting. Conclusions This is one of the initial reports to characterize the novel EGFR TKI mobocertinib and highlights its broad activity against EGFR mutants plus the therapeutic window to EGFR exon 20 insertion mutations; and EGFR-C797S as a possible mechanism of resistance. Further clinical development of mobocertinib merits continuation.
BioLitMine: Advanced Mining of Biomedical and Biological Literature About Human Genes and Genes from Major Model Organisms.

The accumulation of biological and biomedical literature outpaces the ability of most researchers and clinicians to stay abreast of their own immediate fields, let alone a broader range of topics. Although available search tools support identification of relevant literature, finding relevant and key publications is not always straightforward. For example, important publications might be missed in searches with an official gene name due to gene synonyms. Moreover, ambiguity of gene names can result in retrieval of a large number of irrelevant publications. To address these issues and help researchers and physicians quickly identify relevant publications, we developed BioLitMine, an advanced literature mining tool that takes advantage of the medical subject heading (MeSH) index and gene-to-publication annotations already available for PubMed literature. Using BioLitMine, a user can identify what MeSH terms are represented in the set of publications associated with a given gene of the interest, or start with a term and identify relevant publications. Users can also use the tool to find co-cited genes and a build a literature co-citation network. In addition, BioLitMine can help users build a gene list relevant to a MeSH terms, such as a list of genes relevant to "stem cells" or "breast neoplasms." Users can also start with a gene or pathway of interest and identify authors associated with that gene or pathway, a feature that makes it easier to identify experts who might serve as collaborators or reviewers. Altogether, BioLitMine extends the value of PubMed-indexed literature and its existing expert curation by providing a robust and gene-centric approach to retrieval of relevant information.
A Survey of Robotics and Emotion: Classifications and Models of Emotional Interaction

As emotion plays a growing role in robotic research it is crucial to develop methods to analyze and compare among the wide range of approaches. To this end we present a survey of 1427 IEEE and ACM publications that include robotics and emotion. This includes broad categorizations of trends in emotion input analysis, robot emotional expression, studies of emotional interaction and models for internal processing. We then focus on 232 papers that present internal processing of emotion, such as using a human's emotion for better interaction or turning environmental stimuli into an emotional drive for robotic path planning. We conducted constant comparison analysis of the 232 papers and arrived at three broad categorization metrics - emotional intelligence, emotional model and implementation - each including two or three subcategories. The subcategories address the algorithm used, emotional mapping, history, the emotional model, emotional categories, the role of emotion, the purpose of emotion and the platform. Our results show a diverse field of study, largely divided by the role of emotion in the system, either for improved interaction, or improved robotic performance. We also present multiple future opportunities for research and describe intrinsic challenges common in all publications.