cssi/SciSciGPT-SciSciNet huggingface dataset:
Cryo-EM Structure of Full-length HIV-1 Env Bound With the Fab of Antibody PG16.

Abstract The HIV-1 envelope protein (Env) is the target of neutralizing antibodies and the template for vaccine immunogen design. The dynamic conformational equilibrium of trimeric Env influences its antigenicity and potential immunogenicity. Antibodies that bind at the trimer apex stabilize a "closed" conformation characteristic of the most difficult to neutralize isolates. A goal of vaccine development is therefore to mimic the closed conformation in a designed immunogen. A disulfide-stabilized, trimeric Env ectodomain -- the "SOSIP" construct -- has many of the relevant properties; it is also particularly suitable for structure determination. Some single-molecule studies have, however, suggested that the SOSIP trimer is not a good representation of Env on the surface of a virion or an infected cell. We isolated Env (fully cleaved to gp120 and gp41) from the surface of expressing cells using tagged, apex-binding Fab PG16 and determined the structure of the PG16-Env complex by cryo-EM to an overall resolution of 4.6 A. Placing the only purification tag on the Fab ensured that the isolated Env was continuously stabilized in its closed, native conformation. The Env structure in this complex corresponds closely to the SOSIP structures determined by both x-ray crystallography and cryo-EM. Although the membrane-interacting elements are not resolved in our reconstruction, we can make inferences about the connection between ectodomain and membrane-proximal external region (MPER) by reference to the published cryo-tomography structure of an Env "spike" and the NMR structure of the MPER-transmembrane segment. We discuss these results in view of the conflicting interpretations in the literature.
A small family business: synergistic and additive effects of the queen and the brood on worker reproduction in a primitively eusocial bee.

ABSTRACT The mechanisms that maintain reproductive division of labor in social insects are still incompletely understood. Most studies focus on the relationship between adults, overlooking another important stakeholder – the juveniles. Recent studies show that not only the queen but also the brood regulate worker reproduction. However, how the two coordinate to maintain reproductive monopoly remained unexplored. Here, we disentangled the roles of the brood and the queen in primitively eusocial bees (Bombus impatiens) by examining their separated and combined effects on worker behavioral, physiological and brain gene expression. We found that young larvae produce a releaser effect on workers, decreasing oviposition and aggression, while the queen produces both releaser and primer effects, modifying worker behavior and reproductive physiology. The expression of reproduction- and aggression-related genes was altered in the presence of both queen and brood but was stronger or the same in the presence of the queen. We identified two types of interactions between the queen and the brood in regulating worker reproduction: (1) synergistic interactions regulating worker physiology, where the combined effect of the queen and the brood on worker physiology was greater than their separate effects; (2) additive interactions, where the combined effect of the queen and the brood on worker behavior was similar to the sum of their separate effects. Our results suggest that the queen and the brood interact synergistically and additively to regulate worker behavior and reproduction, and this interaction exists at multiple regulatory levels.
Examining the institutional drivers of Public-Private Partnership (PPP) market performance: a fuzzy set Qualitative Comparative Analysis (fsQCA)

This study explores whether different constellations of institutional factors create unique causal ‘paths’ to mature PPP market performance. Using fuzzy set Qualitative Comparative Analysis (fsQCA)...
Reconstruction under outliers for fourier-sparse functions

We consider the problem of learning an unknown f with a sparse Fourier spectrum in the presence of outlier noise. In particular, the algorithm has access to a noisy oracle for (an unknown) f such that (i) the Fourier spectrum of f is k-sparse; (ii) at any query point x, the oracle returns y such that with probability 1 − ρ, |y − f(x)| ≤ ϵ. However, with probability ρ, the error y − f(x) can be arbitrarily large. We study Fourier sparse functions over both the discrete cube {0, 1}n and the torus [0, 1) and for both these domains, we design efficient algorithms which can tolerate any ρ While our main results pertain to the case where the location of the outliers, i.e., x such that |y − f(x)| > ϵ is randomly distributed, we also study the case where the outliers are adversarially located. In particular, we show that over the torus, assuming that the Fourier transform satisfies a certain granularity condition, there is a sample efficient algorithm to tolerate ρ = Ω(1) fraction of outliers and further, that this is not possible without such a granularity condition. Finally, while not the principal thrust, our techniques also allow us non-trivially improve on learning low-degree functions f on the hypercube in the presence of adversarial outlier noise. Our techniques combine a diverse array of tools from compressive sensing, sparse Fourier transform, chaining arguments and complex analysis.
RT-PCR based tyrosine kinase display profiling of canine melanoma: IGF-1 receptor as a potential therapeutic target

1115 Introduction: Metastatic melanoma can be a devastating disease, and the optimal nonsurgical treatment remains unknown. Canine mucosal melanoma (CMM) resembles human melanoma in terms of metastatic behavior, refractoriness to standard therapy, and tumor antigen expression but it is not known how closely CMM resembles human melanoma with regard to molecular pathogenesis. There is a wealth of information available regarding tyrosine kinase (TK) expression in human cancer, however no attempt has been made to systematically define the repertoire of TKs expressed in CMM. This study employed a molecular technique called RT-PCR display to simultaneously evaluate the expression of up to 30 different TKs in a CMM cell line. Materials and Methods: mRNA was extracted and reverse-transcribed from the 17CM98 CMM cell line, then subjected to PCR using degenerate primers coding for highly conserved regions flanking the kinase domains of many receptor and nonreceptor TKs. The resulting 210-bp product was ligated into pCR-Topo2.1 and used to transform E. coli. Multiple bacterial colonies were isolated, the cDNA inserts sequenced and then compared with published sequence data using BLASTn. Results and Conclusions: Sequencing 46 clones yielded canine homologs of IGF-1R (50%), JAK1 (17%), PDGFR-a (11%), FGFR1 (9%), Axl (7%), c-Abl (4%), and PTK2 (2%). Interestingly, IGF-1R, JAK1 and Axl were detected using a similar technique in human melanoma, supporting the cross-species validity of this assay. Given the relative abundance of IGF-1R clones, we sought to determine the biologic effect of rhIGF-1 in 17CM98 cells. IGF-1 stimulated IGF-1R phosphorylation, cell proliferation and VEGF production in 17CM98, and protected the cells from serum starvation-induced apoptosis. Addition of the IGF-1R kinase inhibitor ADW742 (Novartis) abrogated all IGF-1 induced changes. Expression of IGF-1R mRNA was detected in 5 of 5 additional CMM cell lines evaluated, suggesting that IGF-1R expression may be common in CMM cells and providing a novel target for future therapy. In conclusion, this study demonstrates the applicability of the tyrosine kinase RT-PCR display technique to canine cells, suggests that a similar spectrum of TKs are expressed by human and canine melanoma, and demonstrates the efficacy of ADW742 in IGF-1R expressing canine tumor cells.
Enabling Cyberattack-Resilient Load Forecasting through Adversarial Machine Learning

Developing cyberattack-resilient load forecasting is critical for electric utilities in the face of increasingly broad cyberattack surfaces. It is, however, a challenging task due to the adversary's unknown behaviors. This paper bridges the gap by developing an adversarial machine learning (AML) approach for cyberattack-resilient load forecasting. The novelties of this paper include: 1) its analysis of cyber security issues for traditional artificial neural network (ANN) based load forecasting; 2) the ensemble adversarial training it establishes to tackle different attack scenarios; and 3) the selection of parameters for AML it evaluates to achieve desired performance. Test results validate the effectiveness and excellent performance of the presented method.
Holographic codes on Bruhat–Tits buildings and Drinfeld symmetric spaces

This paper is based on the author's talk at the Arbeitstagung 2017. It discusses some general approaches to the construction of classical and quantum holographic codes on Bruhat-Tits trees and buildings and on Drinfeld symmetric spaces, in the context of the p-adic AdS/CFT correspondence.
On the perturbation of the Moore–Penrose inverse of a matrix

Abstract The Moore–Penrose inverse of a matrix has been extensively investigated and widely applied in many fields over the past decades. One reason for the interest is that the Moore–Penrose inverse can succinctly express some important geometric constructions in finite-dimensional spaces, such as the orthogonal projection onto a subspace and the linear least squares problem. In this paper, we establish new perturbation bounds for the Moore–Penrose inverse under the Frobenius norm, some of which are sharper than the existing ones.
Genetic screens in isogenic mammalian cell lines without single cell cloning

Isogenic pairs of cell lines, which differ by a single genetic modification, are powerful tools for understanding gene function. Generating such pairs of mammalian cells, however, is labor-intensive, time-consuming, and, in some cell types, essentially impossible. Here, we present an approach to create isogenic pairs of cells that avoids single cell cloning, and screen these pairs with genome-wide CRISPR-Cas9 libraries to generate genetic interaction maps. We query the anti-apoptotic genes BCL2L1 and MCL1, and the DNA damage repair gene PARP1, identifying both expected and uncharacterized buffering and synthetic lethal interactions. Additionally, we compare acute CRISPR-based knockout, single cell clones, and small-molecule inhibition. We observe that, while the approaches provide largely overlapping information, differences emerge, highlighting an important consideration when employing genetic screens to identify and characterize potential drug targets. We anticipate that this methodology will be broadly useful to comprehensively study gene function across many contexts. Isogenic pairs of cell lines are powerful tools but time-consuming to generate. Here the authors conduct genome-wide genetic interactions screens of ‘anchor’ genes with SaCas9 and SpCas9.
Inflammation and matrix metalloproteinase 9 (Mmp-9) regulate photoreceptor regeneration in adult zebrafish.

Brain injury activates complex inflammatory signals in dying neurons, surviving neurons, and glia. Here, we establish that inflammation regulates the regeneration of photoreceptors in the zebrafish retina and determine the cellular expression and function of the inflammatory protease, matrix metalloproteinase 9 (Mmp-9), during this regenerative neurogenesis. Following photoreceptor ablation, anti-inflammatory treatment suppresses the number of injury-induced progenitors and regenerated photoreceptors. Upon photoreceptor injury, mmp-9 is induced in Muller glia and Muller glia-derived photoreceptor progenitors. Deleting mmp-9 results in over production of injury-induced progenitors and regenerated photoreceptors, but over time the absence of Mmp-9 compromises the survival of the regenerated cones. At all time-points studied, the levels of tnf-α are significantly elevated in mutant retinas. Anti-inflammatory treatment in mutants rescues the defects in cone survival. These data provide a link between injury-induced inflammation in the vertebrate CNS, Mmp-9 function during neuronal regeneration and the requirement of Mmp-9 for the survival of regenerated cones.
Classification of Neurodevelopmental Age in Normal Infants Using 3D-CNN based on Brain MRI

Human brain development is rapid during infancy and early childhood. Many disease processes impair this development. Therefore, brain developmental age estimation (BDAE) is essential for all diseases affecting cognitive development. Brain magnetic resonance imaging (MRI) of infants shows brain growth and morphologic patterns during childhood. Therefore, we can estimate the developmental age from brain images. However, MRI analysis is time consuming because each scan contains millions of data points (voxels). We investigated the three-dimensional convolutional neural network (3D CNN), a deep learning algorithm, to rapidly classify neurodevelopmental age with high accuracy based on MRIs. MRIs from normal newborns were obtained from the National Institute of Mental Health (NIMH) Data Archive. Age categories of pediatric MRIs were 3 wks ± 1 wk, 1 yr ± 2 wks, and 3 yrs ± 4 wks. We trained a BDAE method using T1, T2, and proton density (PD) images from MRI scans of 112 individuals using 3D CNN. Compared with the known age, our method has a sensitivity of 99% and specificity of 98.3%. Moreover, our 3D CNN model has better performance in neurodevelopmental age estimation than does 2D CNN.
Inertial Sensor-Based Centripetal Acceleration as a Correlate for Lateral Margin of Stability During Walking and Turning

There is growing interest in using inertial sensors to continuously monitor gait during free-living mobility. Inertial sensors can provide many gait measures, but they struggle to capture the spatial stability of the center-of-mass due to limitations estimating sensor-to-sensor distance. While the margin of stability (MoS) is an established outcome describing the instantaneous mechanical stability of gait relating to fall-risk, methods to estimate the MoS from inertial sensors have been lacking. Here, we developed and tested a framework, based on centripetal acceleration, to determine a correlate for the lateral MoS using inertial sensors during walking with or without turning. Using three synchronized sensors located bilaterally on the feet and lumbar spine, the average centripetal acceleration over the subsequent step can be used as a correlate for lateral MoS. Relying only on a single sensor on the lumbar spine yielded similar results if the stance foot can be determined from other means. Additionally, the centripetal acceleration correlate of lateral MoS demonstrates clear differences between walking and turning, inside and outside turning limbs, and speed. While limitations and assumptions need to be considered when implemented in practice, this method presents a novel correlate for the lateral MoS during walking and turning using inertial sensors, although further validation is required for other activities and populations.
Differential lipid dynamics in stocked and wild juvenile lake trout

Abstract After 45 years of stocking, lake trout in Lake Champlain have started to exhibit strong natural recruitment, suggesting a recent change in limiting factors such as prey availability or overwinter survival. The abundance of juvenile wild lake trout varies among regions of Lake Champlain which suggests the prey base, or foraging success, may vary geographically within the lake. One metric that can indicate differences in resources across regions is lake trout lipid content, which reflects the availability of food and serves as an important energy reserve for overwinter survival. We quantified total lipid content of stocked and wild age-0 to age-3 lake trout among lake regions and seasons. No spatial differences in lipid content were apparent, but wild fish had higher overall mean ± SE percent total lipid content (17.0 ± 0.7% of dry mass) than stocked fish (15.2 ± 0.7%). Lipids in fish stocked in November were high (35.1 ± 0.7% of dry mass) but dropped by spring (14.9 ± 1.3%) and continued to decline through autumn. Wild fish showed seasonal changes with winter depletion in lipids followed by summer increase, and a plateau in autumn. The lipid depletion in stocked fish poses two competing hypotheses: 1) the high lipid concentration is necessary for stocked age-0 fish to transition to foraging in the wild, or 2) the high lipid concentration is difficult to maintain on a wild diet and reduces survival in the first post-stocking year.
Quantifying posterior effect size distribution of susceptibility loci by common summary statistics

Testing millions of single nucleotide polymorphisms (SNPs) in genetic association studies has become a standard routine for disease gene discovery. In light of recent re-evaluation of statistical practice, it has been suggested that p-values are unfit as summaries of statistical evidence. Despite this criticism, p-values contain information that can be utilized to address the concerns about their flaws. We present a new method for utilizing evidence summarized by p-values for estimating odds ratio (OR) based on its approximate posterior distribution. In our method, only p-values, sample size, and standard deviation for ln(OR) are needed as summaries of data, accompanied by a suitable prior distribution for ln(OR) that can assume any shape. The parameter of interest, ln(OR), is the only parameter with a specified prior distribution, hence our model is a mix of classical and Bayesian approaches. We show that our method retains the main advantages of the Bayesian approach: it yields direct probability statements about hypotheses for OR and is resistant to biases caused by selection of top-scoring SNPs. Our method enjoys greater flexibility than similarly inspired methods in the assumed distribution for the summary statistic and in the form of the prior for the parameter of interest. We illustrate our method by presenting interval estimates of effect size for reported genetic associations with lung cancer. Although we focus on OR, the method is not limited to this particular measure of effect size and can be used broadly for assessing reliability of findings in studies testing multiple predictors.
Decentralized Dynamic State Estimation with Bimodal Gaussian Mixture Measurement Noise

This paper proposes a decentralized dynamic state estimation (DSE) algorithm with bimodal Gaussian mixture measurement noise. The decentralized DSE is formulated using the Ensemble Kalman Filter (EnKF) and then compared with the unscented Kalman filter (UKF). The performance of the proposed framework is verified using the WSCC 9-bus system simulated in the Real Time Digital Simulator (RTDS). The phasor measurement unit (PMU) measurements are streamed in real-time from the RTDS runtime environment to MATLAB for real-time visualization and estimation. To consider the data corruption scenario in the streaming process, a bi-modal distribution containing two normal distributions with different weights and variances are added to the measurements as the noise component. The performances of both UKF and EnKF are then compared for by calculating the mean-squared-errors (MSEs) between the actual and estimated states.
A Spectral De-mixing Model for Triplex In Vivo Imaging of Optical Coherence Tomography Contrast Agents

The ability to detect multiple contrast agents simultaneously would greatly enhance Optical Coherence Tomography (OCT) images, providing nuanced biological context to physiological structures. However, previous OCT contrast agent work has been limited to scenarios where only a single contrast agent could be robustly detected within each voxel. We present a novel spectroscopic technique for de-mixing the spectral signal from multiple OCT contrast agents within a single voxel. We validate our technique in vitro and also demonstrate in vivo imaging of three spectrally distinct gold nanobipyramids, trafficking within the lymphatic system of a live mouse. This approach opens the door to a much broader range of pre-clinical and clinical OCT applications where multiplexed labeling is desirable.
The incidence of venous thromboembolism in children following colorectal resection for inflammatory bowel disease: A multi-center study.

Abstract Background/Purpose Children with inflammatory bowel disease (IBD) have increased risk for venous thromboembolism (VTE). We sought to determine incidence and risk factors for postoperative VTE in a multicenter cohort of pediatric patients undergoing colorectal resection for IBD. Methods Retrospective review of children ≤ 18 years who underwent colorectal resection for IBD from 2010 to 2016 was performed at four children's hospitals. Primary outcome was VTE that occurred between surgery and last follow-up. Factors associated with VTE were determined using univariable and multivariable analyses. Results Two hundred seventy-six patients were included with median age 15 years [13,17]. Forty-two children (15%) received perioperative VTE chemoprophylaxis, and 88 (32%) received mechanical prophylaxis. DVT occurred in 12 patients (4.3%) at a median of 14 days postoperatively [8,147]. Most were portomesenteric (n = 9, 75%) with the remaining catheter-associated DVTs in extremities (n = 3, 25%). There was no association with chemoprophylaxis (p > 0.99). On Cox regression, emergent procedure [HR 18.8, 95%CI: 3.18–111], perioperative plasma transfusion [HR 25.1, 95%CI: 2.4–259], and postoperative infectious complication [HR 10.5, 95%CI: 2.63–41.8] remained predictive of DVT. Conclusion Less than 5% of pediatric IBD patients developed postoperative VTE. Chemoprophylaxis was not protective but rarely used. Patients with risk factors identified in this study should be monitored or given prophylaxis for VTE. Level of Evidence Treatment Study, Level III.
Singularity of Some Random Continued Fractions

We prove singularity of some distributions of random continued fractions that correspond to iterated function systems with overlap and a parabolic point. These arose while studying the conductance of Galton-Watson trees.
Identifying profiles of struggling adult readers: relative strengths and weaknesses in lower-level and higher-level competencies

A major challenge in research with struggling adult readers is their heterogeneity in reading-related competencies and demographic characteristics. The purpose of this investigation was to identify unique profiles of skill sets among struggling adult readers and explore informative demographic differences between profiles. Using latent class analysis with a sample of 542 struggling adult readers, we uncovered four empirically distinct classes of readers based on their performance on ten assessments of lower-level and higher-level competencies. On all measured competencies, globally impaired readers (n = 123) demonstrated the largest deficits and globally better readers (n = 86) outperformed all other classes. Two intermediate profiles, weak decoders (n = 144) and weak language comprehenders (n = 189), exhibited complementary patterns of strengths and weaknesses on lower-level and higher-level competencies. One-way ANOVA and chi-square tests of difference indicated that the classes differed significantly in terms of reading comprehension performance, age, and language background but not high school completion. Implications for instruction and future research are discussed.
Local Nash Equilibria are Isolated, Strict Local Nash Equilibria in ‘Almost All’ Zero-Sum Continuous Games

We prove that differential Nash equilibria are generic amongst local Nash equilibria in continuous zerosum games. That is, there exists an open-dense subset of zero-sum games for which local Nash equilibria are nondegenerate differential Nash equilibria. The result extends previous results to the zero-sum setting, where we obtain even stronger results; in particular, we show that local Nash equilibria are generically hyperbolic critical points. We further show that differential Nash equilibria of zero-sum games are structurally stable. The purpose for presenting these extensions is the recent renewed interest in zero-sum games within machine learning and optimization. Adversarial learning and generative adversarial network approaches are touted to be more robust than the alternative. Zero-sum games are at the heart of such approaches. Many works proceed under the assumption of hyperbolicity of critical points. Our results justify this assumption by showing ‘almost all’ zero-sum games admit local Nash equilibria that are hyperbolic.
Comparative genomics and full-length Tprk profiling of Treponema pallidum subsp. pallidum reinfection

Developing a vaccine against Treponema pallidum subspecies pallidum, the causative agent of syphilis, remains a public health priority. Syphilis vaccine design efforts have been complicated by lack of an in vitro T. pallidum culture system, prolific antigenic variation in outer membrane protein TprK, and lack of functional annotation for nearly half of the genes. Understanding the genetic basis of T. pallidum reinfection can provide insights into variation among strains that escape cross-protective immunity. Here, we present comparative genomic sequencing and deep, full-length tprK profiling of two T. pallidum isolates from blood from the same patient that were collected six years apart. Notably, this patient was diagnosed with syphilis four times, with two of these episodes meeting the definition of neurosyphilis, during this interval. Outside of the highly variable tprK gene, we identified 14 coding changes in 13 genes. Nine of these genes putatively localized to the periplasmic or outer membrane spaces, consistent with a potential role in serological immunoevasion. Using a newly developed full-length tprK deep sequencing protocol, we profiled the diversity of this gene that far outpaces the rest of the genome. Intriguingly, we found that the reinfecting isolate demonstrated less diversity across each tprK variable region compared to the isolate from the first infection. Notably, the two isolates did not share any full-length TprK sequences. Our results are consistent with an immunodominant-evasion model in which the diversity of TprK explains the ability of T. pallidum to successfully reinfect individuals, even when they have been infected with the organism multiple times.
Correlating nuclear morphology and external force with combined atomic force microscopy and light sheet imaging separates roles of chromatin and lamin A/C in nuclear mechanics

Chromatin and lamin A/C separately resist strain in nuclear volume and surface area, respectively, during compression as studied with combined atomic force microscopy and light sheet imaging. Chrom...
Testing for COVID-19: Willful ignorance or selfless behavior?

Widespread testing is key to controlling the spread of COVID-19. But should we worry about self-selection bias in the testing? The recent literature on willful ignorance says we should – people often avoid health information. In the context of COVID-19, such willful ignorance can bias testing data. Furthermore, willful ignorance often arises when selfish wants conflict with social benefits, which might be particularly likely for potential ‘super-spreaders’ – people with many social interactions – given people who test positive are urged to self-isolate for two weeks. We design a survey in which participants (n = 897) choose whether to take a costless COVID-19 test. We find that 70% would take a test. Surprisingly, the people most likely to widely spread COVID-19 – the extraverts, others who meet more people in their daily lives and younger people – are the most willing to take a test. People's ability to financially or emotionally sustain self-isolation does not matter to their decision. We conclude that people are selfless in their decision to test for COVID-19. Our results are encouraging – they imply that COVOD-19 testing may succeed in targeting those who generate the largest social benefits from self-isolation if infected, which strengthens the case for widespread testing.
Inhibitory tagging in an interrupted visual search

Inhibition of return facilitates visual search, biasing attention away from previously examined locations. Prior research has shown that, as a result of inhibitory tags associated with rejected distractor items, observers are slower to detect small probes presented at these tagged locations than they are to detect probes presented at locations that were unoccupied during visual search, but only when the search stimuli remain visible during the probe-detection task. Using an interrupted visual search task, in which search displays alternated with blank displays, we found that inhibitory tagging occurred in the absence of the search array when probes were presented during these blank displays. Furthermore, by manipulating participants’ attentional set, we showed that these inhibitory tags were associated only with items that the participants actively searched. Finally, by probing before the search was completed, we also showed that, early in search, processing at distractor locations was actually facilitated, and only as the search progressed did evidence for inhibitory tagging arise at those locations. These results suggest that the context of a visual search determines the presence or absence of inhibitory tagging, as well as demonstrating for the first time the temporal dynamics of location prioritization while search is ongoing.
Entanglement of Two Atoms Using Rydberg Blockade

Abstract Over the past few years we have built an apparatus to demonstrate the entanglement of neutral Rb atoms at optically resolvable distances using the strong interactions between Rydberg atoms. Here we review the basic physics involved in this process: loading of single atoms into individual traps, state initialization, state readout, single-atom rotations, blockade-mediated manipulation of Rydberg atoms, and demonstration of entanglement.
Child Care Subsidy Receipt, Employment, and Child Care Choices of Single Mothers

Abstract This paper examines the impact of actual subsidy receipt of single mothers on their joint employment and child care mode decisions in the post-welfare reform environment. Results indicate that single mothers are highly responsive to child care subsidies by increasing their employment while moving away from parental and relative care toward center care in the process.
WHAT GOES AROUND COMES AROUND: THE IMPACT OF PERSONAL CONFLICT STYLE ON WORK CONFLICT AND STRESS

Conflict styles are typically seen as a response to particular situations. By contrast, we argue that individual conflict styles may shape an employee's social environment, affecting the level of ongoing conflict and thus his or her experience of stress. Using data from a hospital‐affiliated clinical department, we find that those who use a more integrative style experience lower levels of task conflict, reducing relationship conflict, which reduces stress. Those who use a more dominating or avoiding style experience higher levels of task conflict, increasing relationship conflict and stress. We conclude that an employee's work environment is, in part, of his or her own making.
Nonlinear time series classification using bispectrum‐based deep convolutional neural networks

Time series classification using novel techniques has experienced a recent resurgence and growing interest from statisticians, subject-domain scientists, and decision makers in business and industry. This is primarily due to the ever increasing amount of big and complex data produced as a result of technological advances. A motivating example is that of Google trends data, which exhibit highly nonlinear behavior. Although a rich literature exists for addressing this problem, existing approaches mostly rely on first and second order properties of the time series, since they typically assume linearity of the underlying process. Often, these are inadequate for effective classification of nonlinear time series data such as Google Trends data. Given these methodological deficiencies and the abundance of nonlinear time series that persist among real-world phenomena, we introduce an approach that merges higher order spectral analysis (HOSA) with deep convolutional neural networks (CNNs) for classifying time series. The effectiveness of our approach is illustrated using simulated data and two motivating industry examples that involve Google trends data and electronic device energy consumption data.
Did Inequality in Farm Sizes Lead to Suppression of Banking and Credit in the Late Nineteenth Century

This article creates a new database that covers all U.S. banks in the census years between 1870 and 1900 to test the interaction between inequality and financial development when the banking system was starting over from scratch. A fixed-effects panel regression shows that the number of banks per thousand people in the South has a strong positive relationship with the size of farm operations. This suggests that large southern farm operators welcomed new banks after the Civil War. When the analysis is extended into the 1900s, the relationship becomes more negative, as bankers may have tried to block entrants.
Chapter 11 – Relativity I

The requirement of relativity that the speed of light should be the same in all frames of reference moving at a constant velocity with respect to each other leads to the Lorentz transformations, which relate the space coordinates and the time of events in different frames of reference. The Lorentz transformations enable one to derive formulas describing Lorentz contraction and time dilation relating the length and time separation of events with respect to different reference frames. An invariant space-time interval can be defined by the equation (interval)2=(c×time separation)2−(space separation)2.(interval)2=(c×time separation)2−(space separation)2. For two events occurring at the same spatial location, the invariant interval is equal to c times the time separation of the events. The time interval in a reference frame in which events happen at the same point is called the proper time interval. The Lorentz transformations can be cast into a form where ct appears on the same footing as the space coordinates. This leads to the definition the position-time vector xμ with components, x0 = ct, x1, x2, and x3, and to the general definition of a four-vector tμ as a set of four quantities that transform as the components of xμ. Using the concept of a four-vector, one can construct Lorentz invariants, which are independent of the state of motion of the observer.
Dynamic MRI using deep manifold self-learning

We propose a deep self-learning algorithm to learn the manifold structure of free-breathing and ungated cardiac data and to recover the cardiac CINE MRI from highly under-sampled measurements. Our method learns the manifold structure in the dynamic data from navigators using autoencoder network. The trained autoencoder is then used as a prior in the image reconstruction framework. We have tested the proposed method on free-breathing and ungated cardiac CINE data, which is acquired using a navigated golden-angle gradient-echo radial sequence. Results show the ability of our method to better capture the manifold structure, thus providing us reduced spatial and temporal blurring as compared to the SToRM reconstruction.
Learning nonlinear loop invariants with gated continuous logic networks

Verifying real-world programs often requires inferring loop invariants with nonlinear constraints. This is especially true in programs that perform many numerical operations, such as control systems for avionics or industrial plants. Recently, data-driven methods for loop invariant inference have shown promise, especially on linear loop invariants. However, applying data-driven inference to nonlinear loop invariants is challenging due to the large numbers of and large magnitudes of high-order terms, the potential for overfitting on a small number of samples, and the large space of possible nonlinear inequality bounds. In this paper, we introduce a new neural architecture for general SMT learning, the Gated Continuous Logic Network (G-CLN), and apply it to nonlinear loop invariant learning. G-CLNs extend the Continuous Logic Network (CLN) architecture with gating units and dropout, which allow the model to robustly learn general invariants over large numbers of terms. To address overfitting that arises from finite program sampling, we introduce fractional sampling—a sound relaxation of loop semantics to continuous functions that facilitates unbounded sampling on the real domain. We additionally design a new CLN activation function, the Piecewise Biased Quadratic Unit (PBQU), for naturally learning tight inequality bounds. We incorporate these methods into a nonlinear loop invariant inference system that can learn general nonlinear loop invariants. We evaluate our system on a benchmark of nonlinear loop invariants and show it solves 26 out of 27 problems, 3 more than prior work, with an average runtime of 53.3 seconds. We further demonstrate the generic learning ability of G-CLNs by solving all 124 problems in the linear Code2Inv benchmark. We also perform a quantitative stability evaluation and show G-CLNs have a convergence rate of 97.5% on quadratic problems, a 39.2% improvement over CLN models.
SQuINTing at VQA Models: Introspecting VQA Models With Sub-Questions

Existing VQA datasets contain questions with varying levels of complexity. While the majority of questions in these datasets require perception for recognizing existence, properties, and spatial relationships of entities, a significant portion of questions pose challenges that correspond to reasoning tasks – tasks that can only be answered through a synthesis of perception and knowledge about the world, logic and / or reasoning. Analyzing performance across this distinction allows us to notice when existing VQA models have consistency issues – they answer the reasoning questions correctly but fail on associated low-level perception questions. For example, in Figure 1, models answer the complex reasoning question “Is the banana ripe enough to eat?” correctly, but fail on the associated perception question “Are the bananas mostly green or yellow?” indicating that the model likely answered the reasoning question correctly but for the wrong reason. We quantify the extent to which this phenomenon occurs by creating a new Reasoning split of the VQA dataset and collecting VQAintrospect, a new dataset1 which currently consists of 200K new perception questions which serve as sub questions corresponding to the set of perceptual tasks needed to effectively answer the complex reasoning questions in the Reasoning split. Our evaluation shows that state-of-the-art VQA models have comparable performance in answering perception and reasoning questions, but suffer from consistency problems. To address this shortcoming, we propose an approach called Sub-Question Importance-aware Network Tuning (SQuINT), which encourages the model to attend to the same parts of the image when answering the reasoning question and the perception sub question. We show that SQuINT improves model consistency by ∼7%, also marginally improving performance on the Reasoning questions in VQA, while also displaying better attention maps.
Probabilistic Assumptions Matter: Improved Models for Distantly-Supervised Document-Level Question Answering

We address the problem of extractive question answering using document-level distant super-vision, pairing questions and relevant documents with answer strings. We compare previously used probability space and distant supervision assumptions (assumptions on the correspondence between the weak answer string labels and possible answer mention spans). We show that these assumptions interact, and that different configurations provide complementary benefits. We demonstrate that a multi-objective model can efficiently combine the advantages of multiple assumptions and outperform the best individual formulation. Our approach outperforms previous state-of-the-art models by 4.3 points in F1 on TriviaQA-Wiki and 1.7 points in Rouge-L on NarrativeQA summaries.
Limited Role for Antibiotics in COVID-19: Scarce Evidence of Bacterial Coinfection

Background: There is currently a paucity of data describing bacterial coinfections, related antibiotic prescribing patterns, and the potential role of antimicrobial stewardship in the care of patients infected with SARS-CoV-2. Methods: This prospective, observational study was conducted from March 10, 2020 to April 21, 2020 in admitted patients with confirmed COVID-19. Patients were included if ≥ 18 years old and admitted to the hospital for further treatment. Data was collected via chart review from the enterprise electronic health record database. Data collected include factors driving antibiotic choice, indication, and duration of therapy as well as microbiological data. Findings: Antibiotics were initiated on admission in 87/147 (59%) patients. Of these, 85/87 (98%) prescriptions were empiric. The most common indication for empiric antibiotics was concern for community-acquired pneumonia (76/85, 89%) with the most prescribed antibiotics being ceftriaxone and azithromycin. The median duration of antibiotic therapy was two days (interquartile range 1-5). No patients had a community-acquired bacterial respiratory coinfection, but 10/147 (7%) of patients were found to have concurrent bacterial infections from a non-respiratory source, and one patient was diagnosed with active pulmonary tuberculosis at the time of admission for COVID-19. Interpretation: Bacterial coinfection in patients with COVID-19 was infrequent. Antibiotics are likely unnecessary in patients with mild symptoms. There is little role for broad-spectrum antibiotics to empirically treat multidrug resistant organisms in patients with COVID-19, regardless of disease severity. Antimicrobial stewardship remains important in patients infected with SARS-CoV-2.
The Dynamics of the Corona Borealis Supercluster

The dynamics of the Corona Borealis (Cor Bor) supercluster was studied on a sample of 1555 galaxies in the vicinity of the six Abell clusters (A2061, A2065, A2067, A2079, A2089, and A2092) which comprise the supercluster. For all galaxies in this sample, photographic R photometry and accurate positional data are available. New R photometry and/or new redshifts were obtained for 97 galaxies, bringing the number of galaxies in this system for which the redshifts are available to 182. The central cluster R band luminosity, X-ray luminosity, and surface density were correlated with the cluster velocity dispersion and virial mass. The amount of matter in the supercluster, estimated to be about 8.2 x 10 to the 15th solar masses, is considered to be sufficient to bind the six Cor Bor clusters, which are contained within a volume of about 13 Mpc in radius. Dynamical time scales are comparable with the Hubble time, making it unlikely that the system is virialized.
The distraction effect of non-audit services on audit quality

Abstract Regulators have expressed concerns that an emphasis on non-audit services (NAS) could distract from the audit function, even for clients with minimal NAS purchases. Motivated by this concern, we examine whether a greater emphasis on providing NAS to audit clients generally (i.e., not to a specific client) can distract from the audit function, thus reducing audit quality. We find evidence of an NAS distraction effect, where a greater emphasis on NAS at the audit office-level results in more client financial statement restatements, even after controlling for client-specific NAS. Further, the association exists among clients that purchase minimal NAS, suggesting that this association relates to distraction effects in addition to independence issues examined in prior research. This study should be of interest to audit firms, audit committees, and regulators because it provides new evidence regarding issues related to a business model that includes both audit and non-audit services.
Introducing grapheme-phoneme correspondences (GPCs): exploring rate and complexity in phonics instruction for kindergarteners with limited literacy skills

Two experiments explored rates for introducing grapheme-phoneme correspondences (GPCs) and the types of correspondences taught for optimal alphabet and early literacy skills learning. In both studies, children entered with minimal alphabet knowledge and were randomly assigned within classrooms to one of two treatments delivered individually over 5 weeks. In Study 1, children grades K-1 were assigned to instruction in a set of either 10 (Slow rate, n = 33) or 15 (Fast rate, n = 32) single- and two-letter GPCs. Study 1 findings indicated that children who learned five added GPCs did not reduce learning of the common set of 10 learned GPCs for any measure (including letter names, sounds, letter sound writing, word reading, and spelling), and learning favored Fast items over Slow for letter sounds, letter sound writing, and word reading (median d = 0.30). In Study 2, kindergarteners were assigned to instruction in either single letters only (Single, n = 30) or mixed-size GPCs (Mixed, n = 31). Instruction included application of GPCs to decoding and spelling. Results showed that kindergarteners in the Mixed condition made significantly greater gains learning the four two-letter GPCs across measures (median d = 0.86), and no significant differences between groups on measures of the 11 one-letter GPCs common to both conditions. Findings add precision to understanding how rate and order of introducing GPCs influence children’s initial alphabet learning. Further study of empirically validated methods of alphabet instruction may benefit in particular those children most at risk for acquiring this foundational knowledge.
Identifying States of Collateral Sensitivity during the Evolution of Therapeutic Resistance in Ewing's Sarcoma

Advances in the treatment of Ewing's sarcoma (EWS) are desperately needed, particularly in the case of metastatic disease. A deeper understanding of collateral sensitivity, where the evolution of therapeutic resistance to one drug aligns with sensitivity to another drug, may improve our ability to effectively target this disease. For the first time in a solid tumor, we produced a temporal collateral sensitivity map that demonstrates the evolution of collateral sensitivity and resistance in EWS. We found that the evolution of collateral resistance was predictable with some drugs but had significant variation in response to other drugs. Using this map of temporal collateral sensitivity in EWS, we can see that the path toward collateral sensitivity is not always repeatable, nor is there always a clear trajectory toward resistance or sensitivity. Identifying transcriptomic changes that accompany these states of transient collateral sensitivity could improve treatment planning for patients with EWS.
Multiplicative series, modular forms, and Mandelbrot polynomials

We say a power series $\sum_{n=0}^\infty a_n q^n$ is multiplicative if the function $n\mapsto a_n/a_1$ ($n\ge 1$) is so. In this paper, we consider multiplicative power series $f$ such that $f^2$ is also multiplicative. We find various solutions for which $f$ is a rational function or a theta series and prove that the complete set of solutions is the locus of a (probably reducible) affine variety over C. The precise determination of this variety is a finite computational problem but seems to be outside the reach of current computer algebra systems. The proof of the theorem depends on a bound on the logarithmic capacity of the Mandelbrot set.
Flashes from normal stars

The characteristics of flashes from 24 normal stars are presented and discussed. Rate estimates are made for the flashes and possible mechanisms for them are considered. The consequences for the earth of solar flashes of varying intensities are examined.