cssi/SciSciGPT-SciSciNet huggingface dataset:
Routing for Traffic Networks With Mixed Autonomy

In this article, we propose a macroscopic model for studying routing on networks shared between human-driven and autonomous vehicles that captures the effects of autonomous vehicles forming platoons. We use this to study inefficiency due to selfish routing and bound the price of anarchy (PoA), the maximum ratio between total delay experienced by selfish users and the minimum possible total delay. To do so, we establish two road capacity models, each corresponding to an assumption regarding the platooning capabilities of autonomous vehicles. Using these, we develop a class of road delay functions, parameterized by the road capacity, that are polynomial with respect to vehicle flow. We then bound the PoA and the bicriteria, another measure of the inefficiency due to selfish routing, for general networks with multiple source-destination pairs. We find these bounds depend on: the degree of the polynomial in the road delay function; and the degree of asymmetry, the difference in how human-driven and autonomous traffic affect road delay. We demonstrate that these bounds recover the classical bounds when no asymmetry exists. We show the bounds are tight in certain cases and that the PoA bound is order optimal with respect to the degree of asymmetry.
Checking Phylogenetic Decisiveness in Theory and in Practice

Suppose we have a set X consisting of n taxa and we are given information from k loci from which to construct a phylogeny for X. Each locus offers information for only a fraction of the taxa. The question is whether this data suffices to construct a reliable phylogeny. The decisiveness problem expresses this question combinatorially. Although a precise characterization of decisiveness is known, the complexity of the problem is open. Here we relate decisiveness to a hypergraph coloring problem. We use this idea to (1) obtain lower bounds on the amount of coverage needed to achieve decisiveness, (2) devise an exact algorithm for decisiveness, (3) develop problem reduction rules, and use them to obtain efficient algorithms for inputs with few loci, and (4) devise an integer linear programming formulation of the decisiveness problem, which allows us to analyze data sets that arise in practice.
Deep Learning-Based Feature Extraction in Iris Recognition: Use Existing Models, Fine-tune or Train From Scratch?

Modern deep learning techniques can be employed to generate effective feature extractors for the task of iris recognition. The question arises: should we train such structures from scratch on a relatively large iris image dataset, or it is better to fine-tune the existing models to adapt them to a new domain? In this work we explore five different sets of weights for the popular ResNet-50 architecture to find out whether iris-specific feature extractors perform better than models trained for non-iris tasks. Features are extracted from each convolutional layer and the classification accuracy achieved by a Support Vector Machine is measured on a dataset that is disjoint from the samples used in training of the ResNet-50 model. We show that the optimal training strategy is to fine-tune an off-the-shelf set of weights to the iris recognition domain. This approach results in greater accuracy than both off-the-shelf weights and a model trained from scratch. The winning, fine-tuned approach also shows an increase in performance when compared to previous work, in which only off-the-shelf (not fine-tuned) models were used in iris feature extraction. We make the best-performing ResNet-50 model, fine-tuned with more than 360,000 iris images, publicly available along with this paper.
Ischemic stroke in COVID-19: An urgent need for early identification and management.

Objective In the setting of the Coronavirus Disease 2019 (COVID-19) global pandemic caused by SARS-CoV-2, a potential association of this disease with stroke has been suggested. We aimed to describe the characteristics of patients who were admitted with COVID-19 and had an acute ischemic stroke (AIS). Methods This is a case series of PCR-confirmed COVID-19 patients with ischemic stroke admitted to an academic health system in metropolitan Atlanta, Georgia (USA) between March 24th, 2020 and July 17th, 2020. Demographic, clinical, and radiographic characteristics were described. Results Of 396 ischemic stroke patients admitted during this study period, 13 (2.5%) were also diagnosed with COVID-19. The mean age of patients was 61.6 ± 10.8 years, 10 (76.9%) male, 8 (61.5%) were Black Americans, mean time from last normal was 4.97 ± 5.1 days, and only one received acute reperfusion therapy. All 13 patients had at least one stroke-associated co-morbidity. The predominant pattern of ischemic stroke was embolic with 4 explained by atrial fibrillation. COVID-19 patients had a significantly higher rate of cryptogenic stroke than non-COVID-19 patients during the study period (69% vs 17%, p = 0.0001). Conclusions In our case series, ischemic stroke affected COVID-19 patients with traditional stroke risk factors at an age typically seen in non-COVID populations, and mainly affecting males and Black Americans. We observed a predominantly embolic pattern of stroke with a higher than expected rate of cryptogenic strokes, a prolonged median time to presentation and symptom recognition limiting the use of acute reperfusion treatments. These results highlight the need for increased community awareness, early identification, and management of AIS in COVID-19 patients.
Dynamically Reconfigurable Discrete Distributed Stiffness for Inflated Beam Robots

Inflated continuum robots are promising for a variety of navigation tasks, but controlling their motion with a small number of actuators is challenging. These inflated beam robots tend to buckle under compressive loads, producing extremely tight local curvature at difficult-to-control buckle point locations. In this paper, we present an inflated beam robot that uses distributed stiffness changing sections enabled by positive pressure layer jamming to control or prevent buckling. Passive valves are actuated by an electromagnet carried by an electromechanical device that travels inside the main inflated beam robot body. The valves themselves require no external connections or wiring, allowing the distributed stiffness control to be scaled to long beam lengths. Multiple layer jamming elements are stiffened simultaneously to achieve global stiffening, allowing the robot to support greater cantilevered loads and longer unsupported lengths. Local stiffening, achieved by leaving certain layer jamming elements unstiffened, allows the robot to produce "virtual joints" that dynamically change the robot kinematics. Implementing these stiffening strategies is compatible with growth through tip eversion and tendonsteering, and enables a number of new capabilities for inflated beam robots and tip-everting robots.
Latitude and Celiac Disease Prevalence: A Meta-Analysis and Meta-Regression.

Background & Aims The latitudinal gradient effect is described for several autoimmune diseases including celiac disease in the United States. However, the association between latitude and global celiac disease prevalence is unknown. We aimed to explore the association between latitude and serology-based celiac disease prevalence through meta-analysis. Methods We searched MEDLINE, Embase, Cochrane, and Scopus databases from their beginning through June 29, 2018, to identify screening studies that targeted a general population sample, used serology-based screening tests, and provided a clear location from which we could assign a latitude. Studies were excluded if sampling was based on symptoms, risk factors, or referral. Study selection and data extraction were performed by independent reviewers. The association measures between latitude and prevalence of serology-based celiac disease were evaluated with random-effects meta-analyses and meta-regression. Results Of the identified 4667 unique citations, 128 studies were included, with 155 prevalence estimates representing 40 countries. Celiac disease was more prevalent at the higher latitudes of 51° to 60° (relative risk [RR], 1.62; 95% CI, 1.09–2.38) and 61° to 70° (RR, 2.30; 95% CI, 1.36–3.89) compared with the 41° to 50° reference level. No statistically significant difference was observed at lower latitudes. When latitude was treated as continuous, we found a statistically significant association between CD prevalence and latitude overall in the world (RR, 1.03, 95% CI, 1.01–1.05) and a subregional analysis of Europe (RR, 1.05; 95% CI, 1.02–1.07) and North America (RR, 1.1; 95% CI, 1.0–1.2). Conclusions In this comprehensive review of screening studies, we found that a higher latitude was associated with greater serology-based celiac disease prevalence.
Are Borders Inside or Outside

When a boat disappears over the horizon, does a distant observer detect the last moment in which the boat is visible, or the first moment in which the boat is not visible? This apparently ludicrous way of reasoning, heritage of long-lasting medieval debates on decision limit problems, paves the way to sophisticated contemporary debates concerning the methodological core of mathematics, physics and biology. These ancient, logically-framed conundrums throw us into the realm of bounded objects with fuzzy edges, where our mind fails to provide responses to plain questions such as: given a closed curve with a boundary (say, a cellular membrane) how do you recognize what is internal and what is external? We show how the choice of an alternative instead of another is not arbitrary, rather points towards entirely different ontological, philosophical and physical commitments. This paves the way to novel interpretations and operational approaches to challenging issues such as black hole singularities, continuous time in quantum dynamics, chaotic nonlinear paths, logarithmic plots, demarcation of living beings. In the sceptical reign where judgements seem to be suspended forever, the contemporary scientist stands for a sort of God equipped with infinite power who is utterly free to dictate the rules of the experimental settings.
Semi-supervised Learning for Fetal Brain MRI Quality Assessment with ROI Consistency

Fetal brain MRI is useful for diagnosing brain abnormalities but is challenged by fetal motion. The current protocol for T2-weighted fetal brain MRI is not robust to motion so image volumes are degraded by inter- and intra- slice motion artifacts. Besides, manual annotation for fetal MR image quality assessment are usually time-consuming. Therefore, in this work, a semi-supervised deep learning method that detects slices with artifacts during the brain volume scan is proposed. Our method is based on the mean teacher model, where we not only enforce consistency between student and teacher models on the whole image, but also adopt an ROI consistency loss to guide the network to focus on the brain region. The proposed method is evaluated on a fetal brain MR dataset with 11,223 labeled images and more than 200,000 unlabeled images. Results show that compared with supervised learning, the proposed method can improve model accuracy by about 6% and outperform other state-of-the-art semi-supervised learning methods. The proposed method is also implemented and evaluated on an MR scanner, which demonstrates the feasibility of online image quality assessment and image reacquisition during fetal MR scans.
Continuum Schroedinger Operators for Sharply Terminated Graphene-Like Structures

We study the single electron model of a semi-infinite graphene sheet interfaced with the vacuum and terminated along a zigzag edge. The model is a Schroedinger operator acting on $$L^2(\mathbb {R}^2)$$ : $$H^\lambda _{\mathrm{edge}}=-\Delta +\lambda ^2 V_\sharp $$ , with a potential $$V_\sharp $$ given by a sum of translates an atomic potential well, $$V_0$$ , of depth $$\lambda ^2$$ , centered on a subset of the vertices of a discrete honeycomb structure with a zigzag edge. We give a complete analysis of the low-lying energy spectrum of $$H^\lambda _{\mathrm{edge}}$$ in the strong binding regime ( $$\lambda $$ large). In particular, we prove scaled resolvent convergence of $$H^\lambda _{\mathrm{edge}}$$ acting on $$L^2(\mathbb {R}^2)$$ , to the (appropriately conjugated) resolvent of a limiting discrete tight-binding Hamiltonian acting in $$l^2(\mathbb {N}_0;\mathbb {C}^2)$$ . We also prove the existence of edge states: solutions of the eigenvalue problem for $$H^\lambda _{\mathrm{edge}}$$ which are localized transverse to the edge and pseudo-periodic plane-wave like parallel to the edge. These edge states arise from a “flat-band” of eigenstates of the tight-binding model.
Universal screening for Lynch syndrome in uterine cancer patients: A quality improvement initiative

Abstract Objective To determine the feasibility and effectiveness of a quality improvement initiative (QI) to adopt universal screening for Lynch syndrome in uterine cancer patients at an institution that previously employed age-based screening. Methods Prior to the initiative, tumors of patients with uterine cancer diagnosed at age ≤ 60 years were screened for mismatch repair deficiency (MMR) and microsatellite instability (MSI). The QI process change model adopted universal testing of all uterine cancer specimens and implemented provider training, standardized documentation, and enhanced use of the electronic medical record (EMR). We compared screening rates, results of screening, follow up of abnormal results, and final diagnoses from the pre- and post-implementation periods. Results Pre- and post-implementation screening rates for women age ≤ 60 years at the time of diagnosis were 45/78 (57.7%) and 64/68 (94.5%), respectively. The screening rate for all patients with uterine cancer increased from 73/190 (38.4%) to 172/182 (94.5%). The rate of abnormal screening results increased from 15/190 (7.9%) to 44/182 (24.0%) cases. Genetics referral rates among screen positives increased from 3/15 (20.0%) to 16/44 (36.4%). Germline diagnoses increased from 2/190 (1.1%) with two Lynch syndrome diagnoses to 4/182 (2.2%) including three Lynch syndrome diagnoses and one BRCA1 germline diagnosis. The number of patients errantly not screened decreased from at least 32 patients to 3 patients after the intervention. Conclusions Adherence to screening guidelines significantly improved after interventions involving provider education, optimal use of the EMR, and simplification of screening indications. These interventions are feasible at other institutions and translatable to other screening indications.
Ten-Day Decitabine with Venetoclax Versus Intensive Chemotherapy in Relapsed or Refractory Acute Myeloid Leukemia: A Propensity Score Matched Analysis

Context: Relapsed/refractory (R/R) acute myeloid leukemia (AML) has poor outcomes. While lower-intensity venetoclax-containing regimens are standard for older/unfit patients with newly diagnosed AML, it is unknown how such regimens compare to intensive chemotherapy (IC) for R/R AML. Objective: To compare outcomes of R/R AML treated with 10-day decitabine and venetoclax (DEC10-VEN; NCT03404193) vs IC-based regimens Design: This was a retrospective study. Propensity scores derived from baseline characteristics were used to match patients treated with DEC10-VEN and IC to minimize bias. Patients and Setting: Sixty-five patients in the DEC10-VEN cohort were matched to 130 IC recipients treated at the University of Texas MD Anderson Cancer Center. The median ages for the DEC10-VEN and IC groups were 64 and 58 years, respectively, and baseline characteristics were balanced between the two cohorts. Interventions: DEC10-VEN comprised of decitabine for 10-days and venetoclax 400 mg daily (DiNardo et al. Lancet Haematol. 2020.) IC-based regimens included idarubicin with cytarabine (IA), with or without cladribine (CLIA), clofarabine (CIA), or fludarabine (FIA or FLAG-IDA), with or without additional agents. Main Outcome Measures: Response rates per ELN 2017 criteria, rate of negative MRD by flow cytometry, early mortality, safety, event-free survival (EFS), and overall survival (OS). Results: DEC10-VEN conferred significantly higher responses compared to IC, including higher overall response rate (60% vs 36%, odds ratio [OR]: 3.28, p Conclusions: DEC10-VEN represents an appropriate salvage therapy and may offer better responses and survival compared to IC in adults with R/R AML. Funding: NCI CCSG CA016672, R01CA235622.
On the Detection of Disinformation Campaign Activity with Network Analysis

seek to influence and polarize political topics through massive coordinated efforts. In the process, these efforts leave behind artifacts, which researchers have leveraged to analyze the tactics employed by disinformation campaigns after they are taken down. Coordination network analysis has proven helpful for learning about how disinformation campaigns operate; however, the usefulness of these forensic tools as a detection mechanism is still an open question. In this paper, we explore the use of coordination network analysis to generate features for distinguishing the activity of a disinformation campaign from legitimate Twitter activity. Doing so would provide more evidence to human analysts as they consider takedowns. We create a time series of daily coordination networks for both Twitter disinformation campaigns and legitimate Twitter communities, and train a binary classifier based on statistical features extracted from these networks. Our results show that the classifier can predict future coordinated activity of known disinformation campaigns with high accuracy (F1 =0.98). On the more challenging task of out-of-distribution activity classification, the performance drops yet is still promising (F1= 0.71), mainly due to an increase in the false positive rate. By doing this analysis, we show that while coordination patterns could be useful for providing evidence of disinformation activity, further investigation is needed to improve upon this method before deployment at scale.
Effects of Correlated Noise on the Performance of Persistence Based Dynamic State Detection Methods

The ability to characterize the state of dynamic systems has been a pertinent task in the time series analysis community. Traditional measures such as Lyapunov exponents are often times difficult to recover from noisy data, especially if the dimensionality of the system is not known. More recent binary and network based testing methods have delivered promising results for unknown deterministic systems, however noise injected into a periodic signal leads to false positives. Recently, we showed the advantage of using persistent homology as a tool for achieving dynamic state detection for systems with no known model and showed its robustness to white Gaussian noise. In this work, we explore the robustness of the persistence based methods to the influence of colored noise and show that colored noise processes of the form $1/f^{\alpha}$ lead to false positive diagnostic at lower signal to noise ratios for $\alpha<0$.
Capitalism with Chinese characteristics

Presents a story of two Chinas â€“ an entrepreneurial rural China and a state-controlled urban China. In the 1980s, rural China gained the upper hand. In the 1990s, urban China triumphed. In the 1990s, the Chinese state reversed many of its rural experiments, with long-lasting damage to the economy and society. A weak financial sector, income disparity, rising illiteracy, productivity slowdowns, and reduced personal income growth are the product of the capitalism with Chinese characteristics of the 1990s and beyond. While GDP grew quickly in both decades, the welfare implications of growth differed substantially. The book uses the emerging Indian miracle to debunk the widespread notion that democracy is automatically anti-growth. As the country marked its 30th anniversary of reforms in 2008, China faces some of its toughest economic challenges and substantial vulnerabilities that require fundamental institutional reforms.
Timing Solution and Single-pulse Properties for Eight Rotating Radio Transients

Rotating radio transients (RRATs), loosely defined as objects that are discovered through only their single pulses, are sporadic pulsars that have a wide range of emission properties. For many of them, we must measure their periods and determine timing solutions relying on the timing of their individual pulses, while some of the less sporadic RRATs can be timed by using folding techniques as we do for other pulsars. Here, based on Parkes and Green Bank Telescope (GBT) observations, we introduce our results on eight RRATs including their timing-derived rotation parameters, positions, and dispersion measures (DMs), along with a comparison of the spin-down properties of RRATs and normal pulsars. Using data for 24 RRATs, we find that their period derivatives are generally larger than those of normal pulsars, independent of any intrinsic correlation with period, indicating that RRATs' highly sporadic emission may be associated with intrinsically larger magnetic fields. We carry out Lomb–Scargle tests to search for periodicities in RRATs' pulse detection times with long timescales. Periodicities are detected for all targets, with significant candidates of roughly 3.4 hr for PSR J1623−0841 and 0.7 hr for PSR J1839−0141. We also analyze their single-pulse amplitude distributions, finding that log-normal distributions provide the best fits, as is the case for most pulsars. However, several RRATs exhibit power-law tails, as seen for pulsars emitting giant pulses. This, along with consideration of the selection effects against the detection of weak pulses, imply that RRAT pulses generally represent the tail of a normal intensity distribution.
Polymer crowding and shape distributions in polymer-nanoparticle mixtures

Macromolecular crowding can influence polymer shapes, which is important for understanding the thermodynamic stability of polymer solutions and the structure and function of biopolymers (proteins, RNA, DNA) under confinement. We explore the influence of nanoparticle crowding on polymer shapes via Monte Carlo simulations and free-volume theory of a coarse-grained model of polymer-nanoparticle mixtures. Exploiting the geometry of random walks, we model polymer coils as effective penetrable ellipsoids, whose shapes fluctuate according to the probability distributions of the eigenvalues of the gyration tensor. Accounting for the entropic cost of a nanoparticle penetrating a larger polymer coil, we compute the crowding-induced shift in the shape distributions, radius of gyration, and asphericity of ideal polymers in a theta solvent. With increased nanoparticle crowding, we find that polymers become more compact (smaller, more spherical), in agreement with predictions of free-volume theory. Our approach can be easily extended to nonideal polymers in good solvents and used to model conformations of biopolymers in crowded environments.
PHOTOIONIZATION MODELS FOR THE SEMI-FORBIDDEN C iii] 1909 EMISSION IN STAR-FORMING GALAXIES

The increasing neutrality of the intergalactic medium at z>6 suppresses Ly-alpha emission, and spectroscopic confirmation of galaxy redshifts requires detecting alternative UV lines. The strong [C III] 1907 + C III] 1909 doublet frequently observed in low-metallicity, actively star-forming galaxies is a promising emission feature. We present CLOUDY photoionization model predictions for C III] equivalent widths (EWs) and line ratios as a function of starburst age, metallicity, and ionization parameter. Our models include a range of C/O abundances, dust content, and gas density. We also examine the effects of varying the nebular geometry and optical depth. Only the stellar models that incorporate binary interaction effects reproduce the highest observed C III] EWs. The spectral energy distributions from the binary stellar population models also generate observable C III] over a longer timescale relative to single-star models. We show that diagnostics using C III] and nebular He II 1640 can separate star-forming regions from shock-ionized gas. We also find that density-bounded systems should exhibit weaker C III] EWs at a given ionization parameter, and C III] EWs could therefore select candidate Lyman continuum-leaking systems. In almost all models, C III] is the next strongest line at 6.
Black holes coupled to a massive dilaton

Abstract We investigate charged black holes coupled to a massive dilaton. It is shown that black holes which are large compared to the Compton wavelength of the dilaton resemble the Reissner-Nordstrom solution, while those which are smaller than this scale resemble the massless dilaton solutions. Black holes of order of the Compton wavelength of the dilaton can have wormholes outside the event horizon in the string metric. Unlike all previous black hole solutions, nearly extremal and extremal black black holes (of any size) repel each other. We argue that extremal black holes are quantum mechanically unstable to decay into several widely separated black holes. We present analytic arguments and extensive numerical results to support these conclusions.
LARGE BIAS FOR INTEGERS WITH PRIME FACTORS IN ARITHMETIC PROGRESSIONS

We prove asymptotic formulas for the number of integers at most that can be written as the product of distinct primes with each prime factor in an arithmetic progression , . For any , our result is uniform for . Moreover, we show that there are large biases toward certain arithmetic progressions , and such biases have connections with Mertens’ theorem and the least prime in arithmetic progressions.
Sorting same-size red blood cells in deep deterministic lateral displacement devices

Microfluidic sorting of deformable particles finds many applications, for example, medical devices for cells. Deterministic lateral displacement (DLD) is one of them. Particle sorting via DLD relies only on hydrodynamic forces. For rigid spherical particles, this separation is to a great extent understood and can be attributed to size differences: large particles displace in the lateral direction with respect to the flow while small particles travel in the flow direction with negligible lateral displacement. However, the separation of non-spherical deformable particles such as red blood cells (RBCs) is more complicated than that of rigid particles. For example, is it possible to separate deformable particles that have the same size but different mechanical properties? We study deformability-based sorting of same-size RBCs via DLD using an in-house integral equation solver for vesicle flows in two dimensions. Our goal is to quantitatively characterize the physical mechanisms that enable the cell separation. To this end, we systematically investigate the effects of the interior fluid viscosity and membrane elasticity of a cell on its behaviour. In particular, we consider deep devices in which a cell can show rich dynamics such as taking a particular angular orientation depending on its mechanical properties. We have found out that cells moving with a sufficiently high positive inclination angle with respect to the flow direction displace laterally while those with smaller angles travel with the flow streamlines. Thereby, deformability-based cell sorting is possible. The underlying mechanism here is cell migration due to the cell’s positive inclination and the shear gradient. The higher the inclination is, the farther the cell can travel laterally. We also assess the efficiency of the technique for dense suspensions. It turns out that most of the cells in dense suspensions do not displace in the lateral direction no matter what their deformability is. As a result, separating cells using a DLD device becomes harder.
Hierarchical Probabilistic Inference of Cosmic Shear

Point estimators for the shearing of galaxy images induced by gravitational lensing involve a complex inverse problem in the presence of noise, pixelization, and model uncertainties. We present a probabilistic forward modeling approach to gravitational lensing inference that has the potential to mitigate the biased inferences in most common point estimators and is practical for upcoming lensing surveys. The first part of our statistical framework requires specification of a likelihood function for the pixel data in an imaging survey given parameterized models for the galaxies in the images. We derive the lensing shear posterior by marginalizing over all intrinsic galaxy properties that contribute to the pixel data (i.e., not limited to galaxy ellipticities) and learn the distributions for the intrinsic galaxy properties via hierarchical inference with a suitably flexible conditional probabilitiy distribution specification. We use importance sampling to separate the modeling of small imaging areas from the global shear inference, thereby rendering our algorithm computationally tractable for large surveys. With simple numerical examples we demonstrate the improvements in accuracy from our importance sampling approach, as well as the significance of the conditional distribution specification for the intrinsic galaxy properties when the data are generated from an unknown number of distinct galaxy populations with different morphological characteristics.
Genus-minimal crystallizations of PL 4-manifolds

For \(d\ge 2\), the regular genus of a closed connected PL d-manifold M is the least genus (resp., half of genus) of an orientable (resp., a non-orientable) surface into which a crystallization of M imbeds regularly. The regular genus of every orientable surface equals its genus, and the regular genus of every 3-manifold equals its Heegaard genus. For every closed connected PL 4-manifold M, it is known that its regular genus \({{\mathcal {G}}}(M)\) is at least \(2 \chi (M) + 5m -4\), where m is the rank of the fundamental group of M. In this article, we introduce the concept of “weak semi-simple crystallization” for every closed connected PL 4-manifold M, and prove that \({{\mathcal {G}}}(M)= 2 \chi (M) + 5m -4\) if and only if M admits a weak semi-simple crystallization. We then show that the PL invariant regular genus is additive under the connected sum within the class of all PL 4-manifolds admitting a weak semi-simple crystallization. Also, we note that this property is related to the 4-dimensional Smooth Poincare Conjecture.
Quantum deconstruction of 5D SQCD

We deconstruct the fifth dimension of 5D SCQD with general numbers of colors and flavors and general 5D Chern-Simons level; the latter is adjusted by adding extra quarks to the 4D quiver. We use deconstruction as a non-stringy UV completion of the quantum 5D theory; to prove its usefulness, we compute quantum corrections to the SQCD5's prepotential. We also explore the moduli/parameter space of the deconstructed SQCD5 and show that for |kcs| < nc−½nf it continues to negative values of 1/g25d. In many cases there are flop transitions connecting SQCD5 to exotic 5D theories such as E0, and we present several examples of such transitions. We compare deconstruction to brane-web engineering of the same SQCD5 and show that the phase diagram is the same in both cases; indeed, the two UV completions are in the same universality class, although they are not dual to each other. Hence, the phase structure of an SQCD5 (and presumably any other 5D gauge theory) is inherently five-dimensional and does not depends on a UV completion.
Marangoni elasticity of flowing soap films

The Marangoni elasticity of a soap film is found by measuring the speed of an oblique shock on a flowing film.
New curvature conditions for the Bochner Technique

We show that manifolds with $$ \lceil \frac{n}{2} \rceil $$ -positive curvature operators are rational homology spheres. This follows from a more general vanishing and estimation theorem for the pth Betti number of closed n-dimensional Riemannian manifolds with a lower bound on the average of the lowest $$n-p$$ eigenvalues of the curvature operator. This generalizes results due to D. Meyer, Gallot–Meyer, and Gallot.
Robust and Flexible Estimation of Stochastic Mediation Effects: A Proposed Method and Example in a Randomized Trial Setting.

Background Causal mediation analysis can improve understanding of the mechanism s underlying epidemiologic associations. However, the utility of natural direct and indirect effect estimation has been limited by the assumption of no confounder of the mediator-outcome relationship that is affected by prior exposure (which we call an intermediate confounder)--an assumption frequently violated in practice. Methods We build on recent work that identified alternative estimands that do not require this assumption and propose a flexible and double robust targeted minimum loss-based estimator for stochastic direct and indirect effects. The proposed method intervenes stochastically on the mediator using a distribution which conditions on baseline covariates and marginalizes over the intermediate confounder. Results We demonstrate the estimator's finite sample and robustness properties in a simple simulation study. We apply the method to an example from the Moving to Opportunity experiment. In this application, randomization to receive a housing voucher is the treatment/instrument that influenced moving with the voucher out of public housing, which is the intermediate confounder. We estimate the stochastic direct effect of randomization to the voucher group on adolescent marijuana use not mediated by change in school district and the stochastic indirect effect mediated by change in school district. We find no evidence of mediation. Conclusions Our estimator is easy to implement in standard statistical software, and we provide annotated R code to further lower implementation barriers.
Optimizing Ground-based Observations of O2 in Earth Analogs

Brinson Foundation; Smithsonian Institution; National Science Foundation [DGE1745303]; Ford Foundation through a Ford Foundation Predoctoral Fellowship
An update on the LHC monojet excess

In previous work, we identified an anomalous number of events in the LHC jets+MET searches characterized by low jet multiplicity and low-to-moderate transverse energy variables. Here, we update this analysis with results from a new ATLAS search in the monojet channel which also shows a consistent excess. As before, we find that this “monojet excess” is well-described by the resonant production of a heavy colored state decaying to a quark and a massive invisible particle. In the combined ATLAS and CMS data, we now find a local (global) preference of 3.3σ (2.5σ) for the new physics model over the Standard Model-only hypothesis. As the signal regions containing the excess are systematics-limited, we consider additional cuts to enhance the signal-to-background ratio. We show that binning finer in HT and requiring the jets to be more central can increase S/B by a factor of ∼1.5.
Picard groups of punctured spectra of dimension three local hypersurfaces are torsion-free

Let (R,m) be a local ring and U_R=Spec(R) -{m} be the punctured spectrum of R. Gabber conjectured that if R is a complete intersection of dimension 3, then the abelian group Pic(U_R) is torsion-free. In this note we prove Gabber's statement for the hypersurface case. We also point out certain connections between Gabber's Conjecture, Van den Bergh's notion of non-commutative crepant resolutions and some well-studied questions in homological algebra over local rings.
Lithium Production in Companions of Accreting X-Ray Binaries by Neutron Spallation of C, N, O Elements

We examine the processes that could lead to the observed enhancement of Li and possibly other light elements (Be, B) in the companions of a number of X-ray novae. We conclude that one of the most promising mechanisms is the spallation of CNO elements on the surface of the companion induced by the neutron flux produced in the hot accretion flow onto the compact object. Direct production of the observed Li and its deposition onto the dwarf companion seem less likely, mainly because of the possibility of its destruction in the production region itself and difficulties in its deposition associated with the configuration of the companion's magnetic field. We discuss other potential observables of the above scenario.
Template matching route classification

This paper details a route classification method for American football using a template matching scheme that is quick and does not require manual labeling. Pre-defined routes from a standard receiver route tree are aligned closely with game routes in order to determine the closest match. Based on a test game with manually labeled routes, the method achieves moderate success with an overall accuracy of 72% of the 232 routes labeled correctly.
The entropy for general extremal black holes

We use the Kerr/CFT correspondence to calculate the entropy for all known extremal stationary and axisymmetric black holes. This is done with the help of two ansatzs that are general enough to cover all such known solutions. Considering only the contribution from the Einstein-Hilbert action to the central charge(s), we find that the entropy obtained by using Cardy’s formula exactly matches with the Bekenstein-Hawking entropy.
CONSTRAINED SIMULATION OF THE BULLET CLUSTER

In this work, we report on a detailed simulation of the Bullet Cluster (1E0657-56) merger, including magnetohydrodynamics, plasma cooling, and adaptive mesh refinement. We constrain the simulation with data from gravitational lensing reconstructions and the 0.5-2 keV Chandra X-ray flux map, then compare the resulting model to higher energy X-ray fluxes, the extracted plasma temperature map, Sunyaev-Zel'dovich effect measurements, and cluster halo radio emission. We constrain the initial conditions by minimizing the chi-squared figure of merit between the full two-dimensional (2D) observational data sets and the simulation, rather than comparing only a few features such as the location of subcluster centroids, as in previous studies. A simple initial configuration of two triaxial clusters with Navarro-Frenk-White dark matter profiles and physically reasonable plasma profiles gives a good fit to the current observational morphology and X-ray emissions of the merging clusters. There is no need for unconventional physics or extreme infall velocities. The study gives insight into the astrophysical processes at play during a galaxy cluster merger, and constrains the strength and coherence length of the magnetic fields. The techniques developed here to create realistic, stable, triaxial clusters, and to utilize the totality of the 2D image data, will be applicable to future simulation studies of other merging clusters. This approach of constrained simulation, when applied to well-measured systems, should be a powerful complement to present tools for understanding X-ray clusters and their magnetic fields, and the processes governing their formation.
The field of definition of affine invariant submanifolds of the moduli space of abelian differentials

The field of definition of an affine invariant submanifold M is the smallest subfield of R such that M can be defined in local period coordinates by linear equations with coefficients in this field. We show that the field of definition is equal to the intersection of the holonomy fields of translation surfaces in M, and is a real number field of degree at most the genus. We show that the projection of the tangent bundle of M to absolute cohomology H 1 is simple, and give a direct sum decomposition of H 1 analogous to that given by Moller in the case of Teichmuller curves. Applications include explicit full measure sets of translation surfaces whose orbit closures are as large as possible, and evidence for finiteness of algebraically primitive Teichmuller curves. The proofs use recent results of Avila, Eskin, Mirzakhani, Mohammadi and Moller. 32G15, 37D40
Periodic Event-Triggered Synchronization of Linear Multi-Agent Systems With Communication Delays

Multi-agent systems' cooperation to achieve global goals is usually limited by sensing, actuation, and communication issues. At the local level, continuous measurement and actuation is only approximated by the use of digital mechanisms that measure and process information in order to compute and update new control input values at discrete time instants. Interaction with other agents takes place, in general, through a digital communication channel with limited bandwidth where transmission of continuous-time signals is not possible. This technical note considers the problem of consensus (or synchronization of state trajectories) of multi-agent systems that are described by general linear dynamics and are connected using undirected graphs. The proposed event-triggered consensus protocol not only avoids the need for continuous communication between agents but also provides a decentralized method for transmission of information in the presence of time-varying communication delays, where each agent decides its own broadcasting time instants based only on local information. This method gives more flexibility for scheduling information broadcasting compared to periodic and sampled-data implementations.
Magnetic Fields Threading Black Holes: Restrictions from General Relativity and Implications for Astrophysical Black Holes

The idea that black hole spin is instrumental in the generation of powerful jets in active galactic nuclei and X-ray binaries is arguably the most contentious claim in black hole astrophysics. Because jets are thought to originate in the context of electromagnetism, and the modeling of Maxwell fields in curved spacetime around black holes is challenging, various approximations are made in numerical simulations that fall under the guise of ‘ideal magnetohydrodynamics’. But the simplifications of this framework may struggle to capture relevant details of real astrophysical environments near black holes. In this work, we highlight tension between analytic and numerical results, specifically between the analytically derived conserved Noether currents for rotating black hole spacetimes and the results of general relativistic numerical simulations (GRMHD). While we cannot definitively attribute the issue to any specific approximation used in the numerical schemes, there seem to be natural candidates, which we explore. GRMHD notwithstanding, if electromagnetic fields around rotating black holes are brought to the hole by accretion, we show from first principles that prograde accreting disks likely experience weaker large-scale black hole-threading fields, implying weaker jets than in retrograde configurations.
Towards Tight Bounds for the Streaming Set Cover Problem

We consider the classic Set Cover problem in the data stream model. For n elements and m sets (m ≥ n) we give a O(1/δ)-pass algorithm with a strongly sub-linear ~O(mnδ) space and logarithmic approximation factor. This yields a significant improvement over the earlier algorithm of Demaine et al. [10] that uses exponentially larger number of passes. We complement this result by showing that the tradeoff between the number of passes and space exhibited by our algorithm is tight, at least when the approximation factor is equal to 1. Specifically, we show that any algorithm that computes set cover exactly using ({1 over 2δ}-1) passes must use ~Ω(mnδ) space in the regime of m=O(n). Furthermore, we consider the problem in the geometric setting where the elements are points in R2 and sets are either discs, axis-parallel rectangles, or fat triangles in the plane, and show that our algorithm (with a slight modification) uses the optimal ~O(n) space to find a logarithmic approximation in O(1/δ) passes.Finally, we show that any randomized one-pass algorithm that distinguishes between covers of size 2 and 3 must use a linear (i.e., Ω(mn)) amount of space. This is the first result showing that a randomized, approximate algorithm cannot achieve a space bound that is sublinear in the input size.This indicates that using multiple passes might be necessary in order to achieve sub-linear space bounds for this problem while guaranteeing small approximation factors.
The Small-Mass Limit and White-Noise Limit of an Infinite Dimensional Generalized Langevin Equation

We study asymptotic properties of the Generalized Langevin Equation (GLE) in the presence of a wide class of external potential wells with a power-law decay memory kernel. When the memory can be expressed as a sum of exponentials, a class of Markovian systems in infinite-dimensional spaces is used to represent the GLE. The solutions are shown to converge in probability in the small-mass limit and the white-noise limit to appropriate systems under minimal assumptions, of which no global Lipschitz condition is required on the potentials. With further assumptions about space regularity and potentials, we obtain $$L^1$$ convergence in the white-noise limit.
26Al IN THE EARLY SOLAR SYSTEM: NOT SO UNUSUAL AFTER ALL

Recently acquired evidence shows that extrasolar asteroids exhibit over a factor of 100 variation in the iron to aluminum abundance ratio. This large range likely is a consequence of igneous differentiation that resulted from heating produced by radioactive decay of 26Al with an abundance comparable to that in the solar system's protoplanetary disk at birth. If so, the conventional view that our solar system began with an unusually high amount of 26Al should be discarded.
Baryons and chiral symmetry

The relevance of chiral symmetry in baryons is highlighted in three examples in the nucleon spectroscopy and structure. The first one is the importance of chiral dynamics in understanding the Roper resonance. The second one is the role of chiral symmetry in the lattice calculation of πNσ term and strangeness. The third one is the role of chiral U(1) anomaly in the anomalous Ward identity in evaluating the quark spin and the quark orbital angular momentum. Finally, the chiral effective theory for baryons is discussed.
The Abundances of Light Neutron-capture Elements in Planetary Nebulae. III. The Impact of New Atomic Data on Nebular Selenium and Krypton Abundance Determinations

The detection of neutron(n)-capture elements in several planetary nebulae (PNe) has provided a new means of investigating s-process nucleosynthesis in low-mass stars. However, a lack of atomic data has inhibited accurate trans-iron element abundance determinations in astrophysical nebulae. Recently, photoionization (PI) and recombination data were determined for Se and Kr, the two most widely detected n-capture elements in nebular spectra. We have incorporated these new data into the photoionization code Cloudy. To test the atomic data, numerical models were computed for 15 PNe that exhibit emission lines from multiple Kr ions. We found systematic discrepancies between the predicted and observed emission lines that are most likely caused by inaccurate PI and recombination data. These discrepancies were removed by adjusting the Kr+?Kr3+ PI cross sections within their cited uncertainties and the dielectronic recombination rate coefficients by slightly larger amounts. From grids of models spanning the physical conditions encountered in PNe, we derive new, broadly applicable ionization correction factor (ICF) formulae for calculating Se and Kr elemental abundances. The ICFs were applied to our previous survey of near-infrared [Kr iii] and [Se iv] emission lines in 120 PNe. The revised Se and Kr abundances are 0.1?0.3 dex lower than former estimates, with average values of [Se/(O, Ar)] = 0.12 ? 0.27 and [Kr/(O, Ar)] = 0.82 ? 0.29, but correlations previously found between their abundances and other nebular and stellar properties are unaffected. We also find a tendency for high-velocity PNe that can be associated with the Galactic thick disk to exhibit larger s-process enrichments than low-velocity PNe belonging to the thin-disk population.