cssi/SciSciGPT-SciSciNet huggingface dataset:
Multiplets of Superconformal Symmetry in Diverse Dimensions

We systematically analyze the operator content of unitary superconformal multiplets in d ≥ 3 spacetime dimensions. We present a simple, general, and efficient algorithm that generates all of these multiplets by correctly eliminating possible null states. The algorithm is conjectural, but passes a vast web of consistency checks. We apply it to tabulate a large variety of superconformal multiplets. In particular, we classify and construct all multiplets that contain conserved currents or free fields, which play an important role in superconformal field theories (SCFTs). Some currents that are allowed in conformal field theories cannot be embedded in superconformal multiplets, and hence they are absent in SCFTs. We use the structure of superconformal stress tensor multiplets to show that SCFTs with more than 16 Poincare supercharges cannot arise in d ≥ 4, even when the corresponding superconformal algebras exist. We also show that such theories do arise in d = 3, but are necessarily free.
Discussion of “Making sense of soft information: Interpretation bias and loan quality”

Abstract Campbell, Loumioti, and Wittenberg-Moerman (2018), henceforth CLW, provide evidence on the effect of human cognitive limitations on the processing of soft information in a Credit Union. Their results suggest that cognitive limitations constitute an important barrier to financial markets' ability to extract soft information. In this discussion, I delineate CLW's contribution and implications of their results, highlight key features of the empirical analyses that address interpretational difficulties that might confront some readers, and point out some limitations and unanswered questions that appear important to address in future research to obtain a more complete understanding of soft information production in financial markets.
Ataxin-7 and Non-stop coordinate SCAR protein levels, subcellular localization, and actin cytoskeleton organization

Atxn7, a subunit of SAGA chromatin remodeling complex, is subject to polyglutamine expansion at the amino terminus, causing spinocerebellar ataxia type 7 (SCA7), a progressive retinal and neurodegenerative disease. Within SAGA, the Atxn7 amino terminus anchors Non-stop, a deubiquitinase, to the complex. To understand the scope of Atxn7-dependent regulation of Non-stop, substrates of the deubiquitinase were sought. This revealed Non-stop, dissociated from Atxn7, interacts with Arp2/3 and WAVE regulatory complexes (WRC), which control actin cytoskeleton assembly. There, Non-stop countered polyubiquitination and proteasomal degradation of WRC subunit SCAR. Dependent on conserved WRC interacting receptor sequences (WIRS), Non-stop augmentation increased protein levels, and directed subcellular localization, of SCAR, decreasing cell area and number of protrusions. In vivo, heterozygous mutation of SCAR did not significantly rescue knockdown of Atxn7, but heterozygous mutation of Atxn7 rescued haploinsufficiency of SCAR.
Voluntary Retreat for Decentralized Interference Reduction in Robot Swarms

In densely-packed robot swarms operating in confined regions, spatial interference–which manifests itself as a competition for physical space–forces robots to spend more time navigating around each other rather than performing the primary task. This paper develops a decentralized algorithm that enables individual robots to decide whether to stay in the region and contribute to the overall mission, or vacate the region so as to reduce the negative effects that interference has on the overall efficiency of the swarm. We develop this algorithm in the context of a distributed collection task, where a team of robots collect and deposit objects from one set of locations to another in a given region. Robots do not communicate and use only binary information regarding the presence of other robots around them to make the decision to stay or retreat. We illustrate the efficacy of the algorithm with experiments on a team of real robots.
Spectrum Sharing in Vehicular Networks Based on Multi-Agent Reinforcement Learning

This paper investigates the spectrum sharing problem in vehicular networks based on multi-agent reinforcement learning, where multiple vehicle-to-vehicle (V2V) links reuse the frequency spectrum preoccupied by vehicle-to-infrastructure (V2I) links. Fast channel variations in high mobility vehicular environments preclude the possibility of collecting accurate instantaneous channel state information at the base station for centralized resource management. In response, we model the resource sharing as a multi-agent reinforcement learning problem, which is then solved using a fingerprint-based deep Q-network method that is amenable to a distributed implementation. The V2V links, each acting as an agent, collectively interact with the communication environment, receive distinctive observations yet a common reward, and learn to improve spectrum and power allocation through updating Q-networks using the gained experiences. We demonstrate that with a proper reward design and training mechanism, the multiple V2V agents successfully learn to cooperate in a distributed way to simultaneously improve the sum capacity of V2I links and payload delivery rate of V2V links.
Petrosal morphology and cochlear function in Mesozoic stem therians.

Here we describe the bony anatomy of the inner ear and surrounding structures seen in three plesiomorphic crown mammalian petrosal specimens. Our study sample includes the triconodont Priacodon fruitaensis from the Upper Jurassic of North America, and two isolated stem therian petrosal specimens colloquially known as the Hoovor petrosals, recovered from Aptian-Albian sediments in Mongolia. The second Hoovor petrosal is here described at length for the first time. All three of these petrosals and a comparative sample of extant mammalian taxa have been imaged using micro-CT, allowing for detailed anatomical descriptions of the osteological correlates of functionally significant neurovascular features, especially along the abneural wall of the cochlear canal. The high resolution imaging provided here clarifies several hypotheses regarding the mosaic evolution of features of the cochlear endocast in early mammals. In particular, these images demonstrate that the membranous cochlear duct adhered to the bony cochlear canal abneurally to a secondary bony lamina before the appearance of an opposing primary bony lamina or tractus foraminosus. Additionally, while corroborating the general trend of reduction of venous sinuses and plexuses within the pars cochlearis seen in crownward mammaliaforms generally, the Hoovor petrosals show the localized enlargement of a portion of the intrapetrosal venous plexus. This new vascular feature is here interpreted as the bony accommodation for the vein of cochlear aqueduct, a structure that is solely, or predominantly, responsible for the venous drainage of the cochlear apparatus in extant therians. Given that our fossil stem therian inner ear specimens appear to have very limited high-frequency capabilities, the development of these modern vascular features of the cochlear endocast suggest that neither the initiation or enlargement of the stria vascularis (a unique mammalian organ) was originally associated with the capacity for high-frequency hearing or precise sound-source localization.
Managing Student Behavior in the Middle Grades Using Class-wide Function-Related Intervention Teams

During the transition from the elementary to middle grades, young adolescents may become increasingly vulnerable for emotional and behavioral problems. Class-Wide Function-Related Intervention Team...
John's Position is not good for approximation

A well-known consequence of John’s theorem states that any symmetric convex body K ⊂ ℝn in John’s position can be approximated by a polytope P with a polynomial number of facets in n, so that $$P\; \subset \;K\; \subset \;\sqrt n P$$. This results extends to the non-symmetric case if the homothety ratio grows to n. In this note, we study how well this result holds in the non-symmetric case, if the homothety ratio is reduced below n. We prove the following: For R = o(n) and a sufficiently large n, there exists a convex body K ⊂ ℝn in John’s position for which there is no polytope P with a polynomial in n number of facets, such that K ⊂ P ⊂ RK. Moreover, for $$R = O\left({\sqrt n} \right)$$, there exists a convex body for which a polytope with an exponential number of facets is needed.
Sequential detection with limited memory

Sequential tests outperform fixed sample size tests by requiring fewer samples on average to achieve the same level of error performance. The sequential probability ratio test (SPRT) has been suggested by Wald (1947) for sequential binary hypothesis testing problems. SPRT recursively calculates the likelihood of an observed data stream and requires this likelihood to be stored in memory between samples. In this paper we study the design of sequential detection tests under memory constraints. We derive the optimal sequential test in the case where only a quantized version of the likelihood can be stored in memory. An application of the proposed techniques is large scale sensor networks where price and communication constraints dictate limited complexity devices, which store and transmit concise representations of the state of nature.
Quickest Detection of Dynamic Events in Networks

The problem of quickest detection of dynamic events in networks is studied. At some unknown time, an event occurs, and a number of nodes in the network are affected by the event, in that they undergo a change in the statistics of their observations. It is assumed that the event is dynamic, in that it can propagate along the edges in the network, and affect more and more nodes with time. The event propagation dynamics is assumed to be unknown. The goal is to design a sequential algorithm that can detect a “significant” event, i.e., when the event has affected no fewer than $\eta $ nodes, as quickly as possible, while controlling the false alarm rate. Fully connected networks are studied first, and the results are then extended to arbitrarily connected networks. The designed algorithms are shown to be adaptive to the unknown propagation dynamics, and their first-order asymptotic optimality is demonstrated as the false alarm rate goes to zero. The algorithms can be implemented with linear computational complexity in the network size at each time step, which is critical for online implementation. Numerical simulations are provided to validate the theoretical results.
Innovative activity and gender dynamics

We explore the innovative performance of firms resulting from their Phase II Small Business Innovation Research (SBIR) research-funded projects in terms of the gender dynamics of the firms. Using commercialization as the relevant performance metric, we find that Phase II projects led by a female principal investigator (PI) have greater probability of being commercialized in female-owned firms than in male-owned firms. This result is consistent with the findings from other settings that females tend to perform better when working under a female supervisor.
Person-following by autonomous robots: A categorical overview:

A wide range of human–robot collaborative applications in diverse domains, such as manufacturing, health care, the entertainment industry, and social interactions, require an autonomous robot to fo...
The value of tax progressivity: Evidence from survey experiments

Abstract The aim of this paper is to investigate how people value tax progressivity. More precisely, I study the potential trade-off between any improvement in the final income distribution and the progressivity of the tax schedule. To do this, I designed survey experiments in which respondents were asked to rank or to choose between different taxation-redistribution schemes with different treatments varying in terms of information availability: (1) when only information about final incomes is provided; and (2) when information about average tax rates is also available. Using a within-subject design, the instability of rankings between (1) and (2) indicates whether or not respondents value tax progressivity. I find that information about tax rates significantly affects respondents' judgments about tax schemes. They exhibit a strong preference for tax progressivity, i.e., they accept a fall in the quality of the final income distribution in exchange for progressive taxation. The results of an additional treatment suggest that the mere fact of providing new information cannot account for this finding.
Angularly adaptive P1–double P0 flux-limited diffusion solutions of non-equilibrium grey radiative transfer problems

Abstract The double spherical harmonics angular approximation in the lowest order, i.e. double P 0 ( DP 0 ), is developed for the solution of time-dependent non-equilibrium grey radiative transfer problems in planar geometry. Although the DP 0 diffusion approximation is expected to be less accurate than the P 1 diffusion approximation at and near thermodynamic equilibrium, the DP 0 angular approximation can more accurately capture the complicated angular dependence near a non-equilibrium radiation wave front. In addition, the DP 0 approximation should be more accurate in non-equilibrium optically thin regions where the positive and negative angular domains are largely decoupled. We develop an adaptive angular technique that locally uses either the DP 0 or P 1 flux-limited diffusion approximation depending on the degree to which the radiation and material fields are in thermodynamic equilibrium. Numerical results are presented for two test problems due to Su and Olson and to Ganapol and Pomraning for which semi-analytic transport solutions exist. These numerical results demonstrate that the adaptive P 1 – DP 0 diffusion approximation can yield improvements in accuracy over the standard P 1 diffusion approximation, both without and with flux-limiting, for non-equilibrium grey radiative transfer.
Mapping short-latency cortical responses to electrical stimulation of thalamic motor nuclei by increasing sampling rate - A technical report.

Abstract Direct electrical stimulation (DES) of the cortex is a clinically indispensable brain mapping technique that provides reliable information about the distribution of eloquent cortex and its connectivity to the white matter bundles. Here we present a technical report on mapping the short latency cortical responses to stimulation of the ventral anterior nucleus of human thalamus. Reliable downstream responses were noted in the regions connected to the ventral anterior nucleus i.e. superior and inferior frontal gyri, supplementary motor area and limbic substructures (cingulate gyrus and hippocampus).
Quantifying CDS Sortability of Permutations by Strategic Pile Size

The special purpose sorting operation, context directed swap (CDS), is an example of the block interchange sorting operation studied in prior work on permutation sorting. CDShas been postulated to ...
Automatic Compiler Based FPGA Accelerator for CNN Training

Training of convolutional neural networks (CNNs) on embedded platforms to support on-device learning is earning vital importance in recent days. Designing flexible training hardware is much more challenging than inference hardware, due to design complexity and large computation/memory requirement. In this work, we present an automatic compiler based FPGA accelerator with 16-bit fixed-point precision for complete CNN training, including Forward Pass (FP), Backward Pass (BP) and Weight Update (WU). We implemented an optimized RTL library to perform training-specific tasks and developed an RTL compiler to automatically generate FPGA-synthesizable RTL based on user-defined constraints. We present a new cyclic weight storage/access scheme for on-chip BRAM and off-chip DRAM to efficiently implement non-transpose and transpose operations during FP and BP phases, respectively. Representative CNNs for CIFAR-10 dataset are implemented and trained on Intel Stratix 10 GX FPGA using proposed hardware architecture, demonstrating up to 479 GOPS performance.
Continuous Data Acquisition for Liquid Argon Time Projection Chamber Neutrino Detectors Using FPGA-Based Real-Time Compression Algorithms

Liquid argon time projection chambers (LArTPCs) have been proposed as neutrino detectors that combine both large sizes to maximize the number of neutrino interactions and detailed recording of the interaction. The readout of thousands of channels at MHz sampling rates produce images of the neutrino-nucleus interaction with millimeter-scale resolution, enabling the identification of the resulting particles and offering multiple handles to measure their energies at the expense of large data rates. Continuous acquisition of the LArTPC data is required to enable the use of high-latency triggers for capturing non-accelerator-beam events. We describe the case of the continuous readout of the MicroBooNE LArTPC, that grants the possibility of acquiring the neutrino burst from a supernova using the SNEWS (Supernova Early Warning System) alert as delayed trigger. The continuous data acquisition is accomplished by using real-time compression algorithms (zero suppression and Huffman compression) implemented in an FPGA in the readout electronics.
A mechanical model reveals that non-axisymmetric buckling lowers the energy barrier associated with membrane neck constriction

Membrane neck formation is essential for scission, which, as recent experiments on tubules have demonstrated, can be location dependent. The diversity of biological machinery that can constrict a neck such as dynamin, actin, ESCRTs and BAR proteins, and the range of forces and deflection over which they operate, suggest that the constriction process is functionally mechanical and robust to changes in biological environment. In this study, we used a mechanical model of the lipid bilayer to systematically investigate the influence of location, symmetry constraints, and helical forces on membrane neck constriction. Simulations from our model demonstrated that the energy barriers associated with constriction of a membrane neck are location-dependent. Importantly, if symmetry restrictions are relaxed, then the energy barrier for constriction is dramatically lowered and the membrane buckles at lower values of forcing parameters. Our simulations also show that constriction due to helical proteins further reduces the energy barrier for neck formation when compared to cylindrical proteins. These studies establish that despite different molecular mechanisms of neck formation in cells, the mechanics of constriction naturally leads to a loss of symmetry that can lower the energy barrier to constriction.
A note on the consistency operator

It is a well known empirical observation that natural axiomatic theories are pre-well-ordered by consistency strength. For any natural theory $T$, the next strongest natural theory is $T+\mathsf{Con}_T$. We formulate and prove a statement to the effect that the consistency operator is the weakest natural way to uniformly extend axiomatic theories.
Making plants into cost-effective bioreactors for highly active antimicrobial peptides.

As antibiotic-resistant bacterial pathogens become an ever-increasing concern, antimicrobial peptides (AMPs) have grown increasingly attractive as alternatives. Potentially, plants could be used as cost-effective AMP bioreactors; however, reported heterologous AMP expression is much lower in plants than in E. coli expression systems and often results in plant cytotoxicity, even for AMPs fused to carrier proteins. This suggests that there may be a physical characteristic of the previously described heterologous AMPs which impedes efficient expression in plants. Using a meta-analysis of protein databases, this study has determined that native plant AMPs were significantly less cationic than AMPs native to other taxa. To apply this finding to plant expression, the transient expression of 10 different heterologous AMPs, ranging in charge from +7 to -5, was tested in the tobacco, Nicotiana benthamiana. Elastin-like polypeptide (ELP) was used as the carrier protein for AMP expression. ELP fusion allowed for a simple, cost-effective temperature shift purification. Using this system, all five anionic AMPs expressed well, with two at unusually high levels (375 and 563 μg/gfw). Furthermore, antimicrobial activity against Staphylococcus epidermidis was an order of magnitude greater (average minimum inhibitory concentration MIC of 0.26μM) than that typically seen for AMPs expressed in E. coli systems and was associated with the uncleaved fusion peptide. In summary, this study describes a means of expressing AMP fusions in plants in high yield, purified by a simple temperature-shift protocol, resulting in a fusion peptide with high antimicrobial activity and without the need for a peptide cleavage step.
Efficient Optical Quantification of Heterogeneous Emitter Ensembles

Defect-based quantum emitters in solid state materials offer a promising platform for quantum communication and sensing. Confocal fluorescence microscopy techniques have revealed quantum emitters in a multitude of host materials. The ability to quickly and accurately sample emitter ensembles is an important tool for characterizing these new quantum emitter systems. In some materials, however, optical properties vary widely between emitters, even within the same sample. In these cases, traditional ensemble fluorescence measurements are confounded by heterogeneity, whereas individual defect-by-defect studies are impractical. Here, we develop a method to quantitatively and systematically analyze the properties of heterogeneous emitter ensembles using large-area photoluminescence maps. We apply this method to study the effects of sample treatments on emitters in hexagonal boron nitride, and we find that low-energy (3 keV) electron irradiation creates emitters, whereas high-temperature (850 °C) annealing in an...
Incorporating human and learned domain knowledge into training deep neural networks: A differentiable dose-volume histogram and adversarial inspired framework for generating Pareto optimal dose distributions in radiation therapy

Purpose We propose a novel domain-specific loss, which is a differentiable loss function based on the dose-volume histogram (DVH), and combine it with an adversarial loss for the training of deep neural networks. In this study, we trained a neural network for generating Pareto optimal dose distributions, and evaluate the effects of the domain-specific loss on the model performance. Methods In this study, three loss functions - mean squared error (MSE) loss, DVH loss, and adversarial (ADV) loss - were used to train and compare four instances of the neural network model: (a) MSE, (b) MSE + ADV, (c) MSE + DVH, and (d) MSE + DVH+ADV. The data for 70 prostate patients, including the planning target volume (PTV), and the organs at risk (OAR) were acquired as 96 × 96 × 24 dimension arrays at 5 mm3 voxel size. The dose influence arrays were calculated for 70 prostate patients, using a 7 equidistant coplanar beam setup. Using a scalarized multicriteria optimization for intensity-modulated radiation therapy, 1200 Pareto surface plans per patient were generated by pseudo-randomizing the PTV and OAR tradeoff weights. With 70 patients, the total number of plans generated was 84 000 plans. We divided the data into 54 training, 6 validation, and 10 testing patients. Each model was trained for a total of 100,000 iterations, with a batch size of 2. All models used the Adam optimizer, with a learning rate of 1 × 10-3 . Results Training for 100 000 iterations took 1.5 days (MSE), 3.5 days (MSE+ADV), 2.3 days (MSE+DVH), and 3.8 days (MSE+DVH+ADV). After training, the prediction time of each model is 0.052 s. Quantitatively, the MSE+DVH+ADV model had the lowest prediction error of 0.038 (conformation), 0.026 (homogeneity), 0.298 (R50), 1.65% (D95), 2.14% (D98), and 2.43% (D99). The MSE model had the worst prediction error of 0.134 (conformation), 0.041 (homogeneity), 0.520 (R50), 3.91% (D95), 4.33% (D98), and 4.60% (D99). For both the mean dose PTV error and the max dose PTV, Body, Bladder and rectum error, the MSE+DVH+ADV outperformed all other models. Regardless of model, all predictions have an average mean and max dose error Conclusion The MSE+DVH+ADV model performed the best in these categories, illustrating the importance of both human and learned domain knowledge. Expert human domain-specific knowledge can be the largest driver in the performance improvement, and adversarial learning can be used to further capture nuanced attributes in the data. The real-time prediction capabilities allow for a physician to quickly navigate the tradeoff space for a patient, and produce a dose distribution as a tangible endpoint for the dosimetrist to use for planning. This is expected to considerably reduce the treatment planning time, allowing for clinicians to focus their efforts on the difficult and demanding cases.
Density Deconvolution With Additive Measurement Errors Using Quadratic Programming

Distribution estimation for noisy data via density deconvolution is a notoriously difficult problem, especially for typical noise distributions like Gaussian. We develop a density deconvolution est...
Work-from-anywhere: The productivity effects of geographic flexibility

ABSTRACT An emerging form of remote work allows employees to work-from-anywhere, so that the worker can choose to live in a preferred geographic location. While traditional work-from-home (WFH) programs offer the worker temporal flexibility, work-from-anywhere (WFA) programs offer both temporal and geographic flexibility. WFA should be viewed as a nonpecuniary benefit likely to be preferred by workers who would derive greater utility by moving from their current geographic location to their preferred location. We study the effects of WFA on productivity at the United States Patent and Trademark Office (USPTO) and exploit a natural experiment in which the implementation of WFA was driven by negotiations between managers and the patent examiners’ union, leading to exogeneity in the timing of individual examiners’ transition from a work-from-home to a work-from-anywhere program. This transition resulted in a 4.4 percent increase in output without affecting the incidence of rework. We also report results related to a plausible mechanism: an increase in observable effort as the worker transitions from a WFH to a WFA program. We employ illustrative field interviews, micro- data on locations, and machine learning analysis to shed further light on geographic flexibility, and summarize worker, firm, and economy-wide implications of provisioning WFA. Keywords geographic flexibility, work-from-anywhere, remote work, telecommuting, worker mobility ABOUT THE AUTHOR/S Prithwiraj Choudhury Harvard Business School pchoudhury@hbs.edu Prithwiraj (Raj) Choudhury is the Lumry Family Associate Professor at the Harvard Business School. He was an Assistant Professor at Wharton prior to joining Harvard. His research is focused on studying the Future of Work, especially the changing Geography of Work. In particular, he studies the productivity effects of geographic mobility of workers, causes of geographic immobility and productivity effects of remote work practices such as ‘Work from anywhere’ and ‘All-remote’. Cirrus Foroughi Harvard Business School cforoughi@hbs.edu Barbara Larson Northeastern University b.larson@northeastern.edu New Future of Work 2020, August 3–5, 2020 © 2020 Copyright held by the owner/author(s)
Learning-Based Inversion-Free Model-Data Integration to Advance Ecosystem Model Prediction

Ecosystem model prediction is important for understanding ecosystem responses to climate change and for management support. Model prediction and quantification of predictive uncertainty of ecosystems have long been investigated. The traditional workflow, which calibrates models to match observations and then uses the calibrated models for predictions, relies heavily on inverse modeling to constrain uncertain parameters in complex forward models. This inversion-based prediction approach is infeasible for complex models with heterogeneous parameter uncertainties and incapable of rapid integration of streaming and multiple sources of data because of the difficulty and computational cost in the model inversion, which is typically ill-posed and can require hundreds of thousands of expensive forward simulations to be performed iteratively. We propose to circumvent inverse modeling by precomputing an ensemble of unconstrained forward simulations and then using machine learning (ML) methods to learn the statistical relationship between simulated observation and prediction quantities. Once the ML model has learned the relationship, it can be used to make predictions of future system behavior with uncertainty quantification based on observations. The proposed learningbased inversion-free model prediction (LIMP) framework is computationally efficient which only requires a few thousands of fully parallelizable forward simulations. Additionally, LIMP can continually update predictions based on streaming observations from multiple locations and sources without necessarily requiring extra model simulations. In this study, we apply LIMP to a regional terrestrial ecosystem model with 47 parameters for testing, refining, and evaluating the approach. We demonstrate that LIMP can be used for efficient model prediction, rapid data assimilation, and cost-effective experimental design for improving robust predictive understanding of ecosystems.
Frequent acquirers and management compensation

We find positive contemporaneous, short‐, and long‐run effects of an increase in the acquisition rate on management compensation. A positive bidirectional causality exists between acquisition frequency and management compensation. A higher firm value is likely to associate with higher acquisition frequency. Acquisition rate has a positive impact on the market share. Acquirers with lower market share are more likely to become frequent acquirers. A causal order follows from lower market share to higher acquisition frequency to higher firm value to higher management compensation. The impact of acquisition frequency on management compensation is higher for value‐enhancing acquirers relative to value‐destroying acquirers.
Efficient wavefront sensing for space-based adaptive optics

Future large space telescopes will be equipped with adaptive optics (AO) to overcome wavefront aberrations and achieve high contrast for imaging faint astronomical objects, such as Earth-like exoplanets and debris disks. In contrast to AO that is widely used in ground telescopes, space-based AO systems will use focal plane wavefront sensing to measure the wavefront aberrations. Focal plane wavefront sensing is a class of techniques that reconstructs the light field based on multiple focal plane images distorted by deformable mirror (DM) probing perturbations. We report an efficient focal plane wavefront sensing approach for space-based AO that optimizes the DM probing perturbation and thus also the integration time for each image. Simulation of the AO system equipped with a vortex coronagraph has demonstrated that our approach enables efficient information acquisition and significantly reduces the time needed for achieving high contrast in space.
Intrinsic sensory disinhibition contributes to intrusive re-experiencing in combat veterans

Intrusive re-experiencing of traumatic events is a hallmark symptom of posttraumatic stress disorder, characterized by rich and vivid sensory details as reported in “flashbacks”. While prevailing models of trauma intrusions focus on dysregulated emotional processes, we hypothesize that a deficiency in intrinsic sensory inhibition could drive overactivation of sensory representations of trauma memories, precipitating sensory-rich intrusions. In a sample of combat veterans, we examined resting-state alpha (8–12 Hz) oscillatory activity (in both power and posterior→frontal connectivity), given its role in sensory cortical inhibition, in association with intrusive re-experiencing symptoms. Veterans further participated in an odor task (including both combat and non-combat odors) to assess olfactory trauma memory and emotional response. We observed an association between intrusive re-experiencing symptoms and attenuated resting-state posterior→frontal alpha connectivity, which were both correlated with olfactory trauma memory. Importantly, olfactory trauma memory was identified as a mediator of the relationship between alpha connectivity and intrusive re-experiencing, suggesting that deficits in intrinsic sensory inhibition contributed to intrusive re-experiencing of trauma via heightened trauma memory. Therefore, by permitting unfiltered sensory cues to enter information processing and activate sensory representations of trauma, sensory disinhibition can constitute a sensory mechanism of intrusive re-experiencing in trauma-exposed individuals.
Economic Evaluation of Tailored Web versus Tailored Telephone-Based Interventions to Increase Colorectal Cancer Screening among Women

Screening for colorectal cancer is cost-effective, but many U.S. women are nonadherent, and the cost-effectiveness of web-based tailored screening interventions is unknown. A randomized controlled trial, COBRA (Increasing Colorectal and Breast Cancer Screening), was the source of information for the economic evaluation. COBRA compared screening among a Usual Care group to: (i) tailored Phone Counseling intervention; (ii) tailored Web intervention; and (iii) tailored Web + Phone intervention groups. A sample of 1,196 women aged 50 to 75 who were nonadherent to colorectal cancer screening were recruited from Indiana primary care clinics during 2013 to 2015. Screening status was obtained through medical records at recruitment with verbal confirmation at consent, and at 6-month follow-up via medical record audit and participant self-report. A "best sample" analysis and microcosting from the patient and provider perspectives were applied to estimate the costs and effects of the interventions. Statistical uncertainty was analyzed with nonparametric bootstrapping and net benefit regression analysis. The per participant cost of implementing the Phone Counseling, Web-based, and Web + Phone Counseling interventions was $277, $314, and $336, respectively. The incremental cost per person screened for the Phone Counseling compared with no intervention was $995, while the additional cost of Web and the Web + Phone compared with Phone Counseling did not yield additonal persons screened. Tailored Phone Counseling significantly increased colorectal cancer screening rates compared with Usual Care. Tailored Web interventions did not improve the screening rate compared with the lower cost Phone Counseling intervention.
Fluoxetine effects on behavior and adult hippocampal neurogenesis in female C57BL/6J mice across the estrous cycle

Some mood disorders, such as major depressive disorder, are more prevalent in women than in men. However, historically preclinical studies in rodents have a lower inclusion rate of females than males, possibly due to the fact that behavior can be affected by the estrous cycle. Several studies have demonstrated that chronic antidepressant treatment can decrease anxiety-associated behaviors and increase adult hippocampal neurogenesis in male rodents. Very few studies have looked at the effects of antidepressants on behavior and neurogenesis across the estrous cycle in naturally cycling female rodents. Here, we analyze the effects of chronic treatment with the selective serotonin reuptake inhibitor (SSRI) fluoxetine (Prozac) on behavior and adult hippocampal neurogenesis in naturally cycling C57BL/6J females across all four phases of the estrous cycle. In naturally cycling C57BL/6J females, fluoxetine decreases negative valence behaviors associated with anxiety in the elevated plus maze and novelty-suppressed feeding task, reduces immobility time in forced swim test, and increases adult hippocampal neurogenesis. Interestingly, the effects of fluoxetine on several negative valence behavior and adult hippocampal neurogenesis measures were mainly found within the estrus and diestrus phases of the estrous cycle. Taken together, these data are the first to illustrate the effects of fluoxetine on behavior and adult hippocampal neurogenesis across all four phases of the murine estrous cycle.
Multivariate Alexander quandles, II. The involutory medial quandle of a link

Joyce showed that for a classical knot K, the order of the involutory medial quandle is |detK|. Generalizing Joyce’s result, we show that for a classical link L of μ ≥ 1 components, the order of th...
Measurement and Theoretical Interpretation of Exciton Diffusion as a Function of Intermolecular Separation for Squaraines Targeted for Bulk Heterojunction Solar Cells

The efficiency of bulk heterojunction (BHJ) organic photovoltaic (OPV) devices depends significantly upon absorption of photons and the migration of the photogenerated excited state to the heteroju...
A Framework for Theoretical Inquiry into Law and Aging

With populations aging worldwide, the need for appropriate and just public policy related to old age is critical. Elder law scholars can support the creation of such policy by advancing the theoretical understanding of the relationship between law and aging — understanding that can help policymakers identify and prioritize goals, and evaluate potential interventions. This Article aims to provide a framework for this work by distilling the core theoretical questions at the intersection of law and aging. It also challenges common assumptions that could pose a barrier to developing a more robust theory of law and aging. Specifically, it argues that scholarship in this area will be most fruitful if it recognizes that the study and practice of “elder law” are intertwined but not a single unified field, that “preferential” treatment of older adults can be a form of discrimination, and that old age is not a universal human experience.
Bandits with Adversarial Scaling

We study adversarial scaling, a multi-armed bandit model where rewards have a stochastic and an adversarial component. Our model captures display advertising where the click-through rate can be decomposed to a (fixed across time) arm-quality component and a non-stochastic user-relevance component (fixed across arms). Despite the relative stochasticity of our model, we demonstrate two settings where most bandit algorithms suffer. On the positive side, we show that two algorithms, one from the action elimination and one from the mirror descent family are adaptive enough to be robust to adversarial scaling. Our results shed light on the robustness of adaptive parameter selection in stochastic bandits, which may be of independent interest.
3GPP-Inspired Stochastic Geometry-Based Mobility Model for a Drone Cellular Network

This paper deals with the stochastic geometry- based characterization of the time-varying performance of a drone cellular network in which the initial locations of drone base stations (DBSs) are modeled as a Poisson point process (PPP) and each DBS is assumed to move on a straight line in a random direction. This drone placement and trajectory model closely emulates the one used by the third generation partnership project (3GPP) for drone-related studies. Assuming the nearest neighbor association policy for a typical user equipment (UE) on the ground, we consider two models for the mobility of the serving DBS: (i) UE independent model, and (ii) UE dependent model. Using displacement theorem from stochastic geometry, we characterize the time- varying interference field as seen by the typical UE, using which we derive the time-varying coverage probability and data rate at the typical UE. We also compare our model with more sophisticated mobility models where the DBSs may move in nonlinear trajectories and demonstrate that the coverage probability and rate estimated by our model act as lower bounds to these more general models. To the best of our knowledge, this is the first work to perform a rigorous analysis of the 3GPP-inspired drone mobility model and establish connection between this model and the more general non-linear mobility models.
Bitter taste receptors stimulate phagocytosis in human macrophages through calcium, nitric oxide, and cyclic-GMP signaling

Bitter taste receptors (T2Rs) are GPCRs involved in detection of bitter compounds by type 2 taste cells of the tongue, but are also expressed in other tissues throughout the body, including the airways, gastrointestinal tract, and brain. These T2Rs can be activated by several bacterial products and regulate innate immune responses in several cell types. Expression of T2Rs has been demonstrated in immune cells like neutrophils; however, the molecular details of their signaling are unknown. We examined mechanisms of T2R signaling in primary human monocyte-derived unprimed (M0) macrophages (M $$\Phi$$ s) using live cell imaging techniques. Known bitter compounds and bacterial T2R agonists activated low-level calcium signals through a pertussis toxin (PTX)-sensitive, phospholipase C-dependent, and inositol trisphosphate receptor-dependent calcium release pathway. These calcium signals activated low-level nitric oxide (NO) production via endothelial and neuronal NO synthase (NOS) isoforms. NO production increased cellular cGMP and enhanced acute phagocytosis ~ threefold over 30–60 min via protein kinase G. In parallel with calcium elevation, T2R activation lowered cAMP, also through a PTX-sensitive pathway. The cAMP decrease also contributed to enhanced phagocytosis. Moreover, a co-culture model with airway epithelial cells demonstrated that NO produced by epithelial cells can also acutely enhance M $$\Phi$$ phagocytosis. Together, these data define M $$\Phi$$ T2R signal transduction and support an immune recognition role for T2Rs in M $$\Phi$$ cell physiology.
Many Voices in China’s Legal Profession: Plural Meanings of Weiquan

Figuring prominently in prevailing portraits of activism and political contention in contemporary China are weiquan [rights defense] lawyers. Outside of China, the word weiquan emerged in the early 2000s and had achieved near-hegemonic status by the late 2000s as a descriptive label for a corps of activist lawyers—who numbered between several dozen and several hundred—committed to the cause and mobilizing in pursuit of human rights protections vis-a-vis China’s authoritarian party-state. This article challenges the dominant nomenclature of Chinese activism, in which weiquan in general and weiquan lawyers in particular loom large. A semantic history of the word weiquan, traced through an analysis of four decades of officially sanctioned rights discourse, reveals its politically legitimate origins in the official lexicon of the party-state. Unique survey data collected in 2009 and 2015 demonstrate that Chinese lawyers generally understood the word in terms of the party-state’s official language of rights, disseminated through its ongoing public legal education campaign. Because the officially-sanctioned meaning of weiquan, namely “to protect citizens’ lawful rights and interests,” is consistent with the essential professional responsibility of lawyers, fully half of a sample of almost 1,000 practicing lawyers from across China self-identified as weiquan lawyers. Such a massive population of self-identified weiquan lawyers—approximately 80,000 in 2009 assuming that the sample is at least reasonably representative—makes sense only if local meanings of the term profoundly diverge from its dominant English-language representations. Concluding speculations consider and call for further research on why this word was appropriated and redefined by activist Chinese lawyers in the first place.
The number of 4-colorings of the Hamming cube

Let Qd be the d-dimensional hypercube and N = 2d. We prove that the number of (proper) 4-colorings of Qd is asymptotically 6e2N, as was conjectured by Engbers and Galvin in 2012. The proof uses a combination of information theory (entropy) and isoperimetric ideas originating in work of Sapozhenko in the 1980’s.
A General Framework of Exact Primal-Dual First-Order Algorithms for Distributed Optimization ∗

We study the problem of minimizing a sum of local objective convex functions over a network of processors/agents. This problem naturally calls for distributed optimization algorithms, in which the agents cooperatively solve the problem through local computations and communications with neighbors. While many of the existing distributed algorithms with constant stepsize can only converge to a neighborhood of optimal solution, some recent methods based on augmented Lagrangian and method of multipliers can achieve exact convergence with a fixed stepsize. However, these methods either suffer from slow convergence speed or require minimization at each iteration. In this work, we develop a class of distributed first-order primal-dual methods, which allows for multiple primal steps per iteration. This general framework makes it possible to control the trade-off between the performance and the execution complexity in primal-dual algorithms. We show that for strongly convex and Lipschitz gradient objective functions, this class of algorithms converges linearly to the optimal solution under appropriate constant stepsize choices. Simulation results confirm the superior performance of our algorithm compared to existing methods.
CALCIFIED PLAQUES IN PATIENTS WITH ACUTE CORONARY SYNDROMES

Calcified plaques as an underlying pathology in patients with acute coronary syndromes (ACS) have not been systematically studied. We conducted detailed analysis of calcified culprit plaques in patients with ACS. From 1241 patients with ACS who had undergone pre-intervention optical coherence
A Robust Effect Size Index

Effect size indices are useful tools in study design and reporting because they are unitless measures of association strength that do not depend on sample size. Existing effect size indices are developed for particular parametric models or population parameters. Here, we propose a robust effect size index based on M-estimators. This approach yields an index that is very generalizable because it is unitless across a wide range of models. We demonstrate that the new index is a function of Cohen's d, [Formula: see text], and standardized log odds ratio when each of the parametric models is correctly specified. We show that existing effect size estimators are biased when the parametric models are incorrect (e.g., under unknown heteroskedasticity). We provide simple formulas to compute power and sample size and use simulations to assess the bias and standard error of the effect size estimator in finite samples. Because the new index is invariant across models, it has the potential to make communication and comprehension of effect size uniform across the behavioral sciences.
Assessing the statistical uniqueness of the Younger Dryas: a robust multivariate analysis

Abstract. During the last glacial period (ca. 120–11 kyr BP), dramatic temperature swings, known as Dansgaard–Oeschger (D–O) events, are clearly manifest in high-resolution oxygen isotope records from the Greenland Ice Sheet. Although variability in the Atlantic Meridional Overturning Circulation (AMOC) is often invoked, a unified explanation for what caused these “sawtooth-shaped” climate patterns has yet to be accepted. Of particular interest is the most recent D–O-shaped climate pattern that occurred from ∼ 14 600 to 11 500 years ago – the Bolling–Allerod (BA) warm interstadial and the subsequent Younger Dryas (YD) cold stadial. Unlike earlier D–O stadials, the YD is frequently considered a unique event, potentially resulting from a rerouting and/or flood of glacial meltwater into the North Atlantic or a meteorite impact. Yet, these mechanisms are less frequently considered as the cause of the earlier stadials. Using a robust multivariate outlier detection scheme – a novel approach for traditional paleoclimate research – we show that the pattern of climate change during the BA/YD is not statistically different from the other D–O events in the Greenland record and that it should not necessarily be considered unique when investigating the drivers of abrupt climate change. In so doing, our results present a novel statistical framework for paleoclimatic data analysis.