cssi/SciSciGPT-SciSciNet huggingface dataset:
Shattering the neutral surrogate myth in end-of-life decisionmaking: Terri Schiavo and her family.

In the Terri Schiavo case, different family members who want the legal authority to make decisions for Terri Schiavo have sought different treatment options - with results as opposed as life and death. Had the case not come before the courts, Michael Schiavo, Terri's husband, would have had Terri's feeding tube removed long ago; Terri's parents, Mary and Robert Schindler, if either had been named surrogate in Michael's stead, would continue feeding her indefinitely. Recognizing, as the Schiavo case highlights, that who among family members speaks for the patient can determine the course of treatment or non-treatment for a patient, it is necessary to turn renewed attention to the question of why families, whether we define them as spouses or parents, are involved in the end-of-life decisionmaking of their relatives. Are they merely a representative or even fiduciary of the patient or are they stakeholders in their own right? Do we look to family members as surrogates because they ensure a sounder process, a neutral process, for determining patient preferences and interests, or do we look to family members as surrogates because we recognize that families want to be (and perhaps should be?) involved? This paper argues that some deference to family members' own interests can be justified on the grounds of a broad notion of patient self-determination, but some degree of deference might also be justified out of respect for family members' own interests. Our law should not demand strict neutrality of these family members, but should acknowledge that their interests may have value as well. At the same time, there must be limits: the family's preferences and interests should not be allowed to overshadow those of the patient.
The global current systems of the Martian induced magnetosphere

Induced magnetospheres form around conductive non-magnetized planetary objects (such as the ionospheres of Mars, Venus, Titan, Pluto and comets) in the electrodynamic interaction with a magnetized flowing plasma, such as the solar wind. The resulting induced currents couple the ionosphere and the deflected plasma, thus they provide insight into the solar wind’s role in powering the heating, escape and evolution of planetary atmospheres. In contrast to the analogous current systems in intrinsic magnetospheres, which were mapped decades ago at Earth, the current systems of induced magnetospheres are largely unexplored. Here, we use five years of magnetic field measurements from the Mars Atmosphere and Volatile EvolutioN (MAVEN) orbiter to empirically map the current systems of the Martian induced magnetosphere. We find unexpected features, in particular: coupling of the ionosphere and the bow shock, asymmetries between the north–south electric hemispheres and a twist in the near-Mars current system. The current flow pattern in the induced magnetosphere of Mars indicates a system driven by a magnetospheric convective electric field, powered by the solar wind interaction. Without an intrinsic magnetic field, Mars’s magnetosphere is induced by direct interaction between its atmosphere and the solar wind. The mapping of the associated current system, obtained by the MAVEN spacecraft, unveils its convective-driven nature and displays various structural differences compared to Earth.
Distributed and consistent multi-image feature matching via QuickMatch:

In this work, we consider the multi-image object matching problem in distributed networks of robots. Multi-image feature matching is a keystone of many applications, including Simultaneous Localiza...
Rethinking international subsidy rules

Geo‐economic tensions, notably associated with the rise of China, and global collective action problems—climate change and the COVID‐19pandemic—call for international cooperation to revise and develop rules to guide both the use of domestic subsidies and responses by governments to cross‐border competition spillover effects. Current WTO rules dividing all subsidies into prohibited or actionable categories are no longer fit for purpose. Piecemeal efforts in preferential trade agreements and bi‐ or trilateral configurations offer a basis on which to build but are too narrow in scope. Addressing spillover effects of subsidies could start with G20 countries launching a work programme to mobilise an epistemic community concerned with subsidy policies, tasked with building a more solid evidence base on the magnitude, purpose and effects of subsidy policies. The need for such cooperation has become even more pressing by the COVID‐19 pandemic and associated increase in the use of subsidy programmes in major economies.
Structure–property linkage in shocked multi-material flows using a level-set-based Eulerian image-to-computation framework

Morphology and dynamics at the mesoscale play crucial roles in the overall macro- or system-scale flow of heterogeneous materials. In a multi-scale framework, closure models upscale unresolved sub-grid (mesoscale) physics and therefore encapsulate structure–property (S–P) linkages to predict performance at the macroscale. This work establishes a route to S–P linkage, proceeding all the way from imaged microstructures to flow computations in one unified level-set-based framework. Level sets are used to: (1) define embedded geometries via image segmentation; (2) simulate the interaction of sharp immersed boundaries with the flow field; and (3) calculate morphological metrics to quantify structure. Mesoscale dynamics is computed to calculate sub-grid properties, i.e., closure models for momentum and energy equations. The S–P linkage is demonstrated for two types of multi-material flows: interaction of shocks with a cloud of particles and reactive meso-mechanics of pressed energetic materials. We also present an approach to connect local morphological characteristics in a microstructure containing topologically complex features with the shock response of imaged samples of such materials. This paves the way for using geometric machine learning techniques to associate imaged morphologies with their properties.
Temporal learning of bottom-up connections via spatially nonspecific top-down inputs

Abstract In the brain, high-order and low-order areas are connected via bottom-up connections (from low-order to high-order areas) and top-down connections (from high-order to low-order areas). While bottom-up signals are thought to be critical in generating perception, functions of top-down signals have not been clearly delineated. One popular theory is that top-down inputs modify the activity of specific cell assemblies to modulate responses to bottom-up inputs. However, a different line of studies proposes that not all top-down inputs are specifically delivered. As the leading theories cannot account for nonspecific top-down inputs, we seek potential functions of nonspecific top-down signals using network models in our study. Our simulation results suggest that top-down inputs can regulate low-order area responses by providing temporal information even without spatial specificity. Specifically, the temporal information in nonspecific top-down inputs can weaken the undesired bottom-up connections, contributing to bottom-up connections’ learning. Further, we found that cortical rhythms (synchronous oscillatory neural responses) are critical in the proposed learning process of bottom-up connections in our model.
Handling Adaptive Compromise for Practical Encryption Schemes

We provide a new definitional framework capturing the multi-user security of encryption schemes and pseudorandom functions in the face of adversaries that can adaptively compromise users’ keys. We provide a sequence of results establishing the security of practical symmetric encryption schemes under adaptive compromise in the random oracle or ideal cipher model. The bulk of analysis complexity for adaptive compromise security is relegated to the analysis of lower-level primitives such as pseudorandom functions.
Characterization of the rate, predictors, and thrombotic complications of thrombocytosis in iron deficiency anemia.

The association of thrombocytosis with iron deficiency anemia (IDA) is well-recognized, but data describing the rate, predictors, and risk of thrombotic complications associated with IDA-related thrombocytosis are limited. We queried an institutional patient data repository containing comprehensive chart data for over 6 million patients to identify IDA patients with and without thrombocytosis and thrombotic events over a 40-year time period (1979 to 2019). Demographics, hematological parameters, thrombosis history, and other medical history were collected. Fidelity of query data was assessed via detailed manual chart review of 700 patients, including confirmation of ferritin and hematologic parameters in addition to temporal and clinical association of thrombocytosis. Our queries identified 36 327 cases of IDA of which 15 022 had thrombocytosis. Following assessment for data integrity, we observed a thrombocytosis rate of 32.6% in patients with IDA. The rate of thrombosis was calculated to be 7.8% in patients with IDA and 15.8% in patients with IDA and thrombocytosis. Platelet mass index at time of peak thrombocytosis was significantly higher than at baseline and was strongly negatively correlated with hemoglobin at peak thrombocytosis. A multivariable model demonstrated a significant predictive relationship between decreasing hemoglobin and increasing platelet count at peak thrombocytosis. In conclusion, we observed reactive thrombocytosis in one-third of IDA patients, and a 2-fold thrombosis risk in patients with IDA and thrombocytosis compared with patients with IDA alone. Given the global burden of untreated and undertreated IDA, adequate IDA treatment may reduce thrombotic complications and associated morbidity and mortality.
Something seems fishy: mainstream consumer response to drag queen imagery

This study investigates how drag queen imagery in advertising and mainstream consumers’ tolerance towards homosexuality (i.e., drag queens) affect their attitudes towards the advertisement and brand in the context of beauty brand advertising. Based on the social identity theory, this study posits that implicit (vs. explicit) drag queen-themed imagery and consumers holding high tolerance as an in-group of LGBTQ+ cultures (vs. out-group of lower tolerance individuals) would have greater impact on ad attitude and brand attitude independently and together. A web-based experiment reveals that while different imagery types (implicit vs. explicit) in ads do not differentiate attitudes toward ad and brand, consumers’ individual tolerance of the drag queen culture positively affects such responses. Additionally, the ad imagery and consumer tolerance toward drag queens have an interaction effect on brand attitude via ad attitude in the explicit drag queen-themed imagery condition but not in implicit imagery. The results add insight to a growing body of literature on the LGBTQ+ and social identity theory research and benefit marketers with a better understanding of how to manage drag queen-themed advertisements within mainstream media.
Heterogeneity in the information content of 8-K disclosures about private targets: Acquirer size and target significance

Abstract In this paper, we empirically analyze the disclosures required by the Securities Exchange Commission (SEC) for acquisitions of privately held target firms by public acquirers. We find that 8-K disclosures filed by public acquirers within a week after the announcement date of the takeover of a privately held target firm materially affect the pricing and the trading of the acquirers' shares around the event date, but only for large acquiring firms. This impact is economically significant even for targets classified as “insignificant” by the SEC, but again, only for large acquirers. Our results suggest that it may be optimal to further reduce the disclosure costs faced by smaller acquirers in acquisitions of private targets.
Resilience of Dynamic Routing in the Face of Recurrent and Random Sensing Faults

Feedback dynamic routing is a commonly used control strategy in transportation systems. This class of control strategies rely on real-time information about the traffic state in each link. However, such information may not always be observable due to temporary sensing faults. In this article, we consider dynamic routing over two parallel routes, where the sensing on each link is subject to recurrent and random faults. The faults occur and clear according to a finite-state Markov chain. When the sensing is faulty on a link, the traffic state on that link appears to be zero to the controller. Building on the theories of Markov processes and monotone dynamical systems, we derive lower and upper bounds for the resilience score, i.e. the guaranteed throughput of the network, in the face of sensing faults by establishing stability conditions for the network. We use these results to study how a variety of key parameters affect the resilience score of the network. The main conclusions are: (i) Sensing faults can reduce throughput and destabilize a nominally stable network; (ii) A higher failure rate does not necessarily reduce throughput, and there may exist a worst rate that minimizes throughput; (iii) Higher correlation between the failure probabilities of two links leads to greater throughput; (iv) A large difference in capacity between two links can result in a drop in throughput.
Accelerated ADMM based Trajectory Optimization for Legged Locomotion with Coupled Rigid Body Dynamics

Trajectory optimization is becoming increasingly powerful in addressing motion planning problems of under-actuated robotic systems. Numerous prior studies solve such a class of large non-convex optimal control problems in a hierarchical fashion. However, numerical accuracy issues are prone to occur when one uses a full-order model to track reference trajectories generated from a reduced-order model. This study investigates an approach of Alternating Direction Method of Multipliers (ADMM) and proposes a new splitting scheme for legged locomotion problems. Rigid body dynamics constraints and other general constraints such as box and cone constraints are decomposed to multiple sub-problems in a principled manner. The resulting multi-block ADMM framework enables us to leverage the efficiency of an unconstrained optimization method-Differential Dynamical Programming-to iteratively solve the optimizations using centroidal and wholebody models. Furthermore, we propose a Stage-wise Accelerated ADMM with over-relaxation and varying-penalty schemes to improve the overall convergence rate. We evaluate and validate the performance of the proposed ADMM algorithm on a car-parking example and a bipedal locomotion problem over rough terrains.
Dynamically Reconfigurable Microwave Circuits Leveraging Abrupt Phase-Change Material

This article proposes a concept for dynamically reconfigurable distributed microwave circuits by leveraging the abrupt conductivity transition in phase-change materials (PCMs). Metallic inclusions ( $\ll \lambda $ ) are embedded in the PCM film—vanadium dioxide (VO2)—to provide low loss and reconfigurability. To validate this concept, a variety of coplanar waveguide transmission lines are designed and fabricated with metallic inclusions in VO2 films, and the lines’ performance are characterized up to 50 GHz. From measurements, a transmission-line-based model and an equivalent circuit model of the VO2 with inclusions are developed to aid in rapid design. An electromagnetic model was developed, and it indicates that loss can be close to conventional metallic distributed circuits with 100–200-nm-thick VO2 films. A criterion for maximum operating frequency is defined, and it indicates that 10- $\mu \text{m}$ unit-cells with thicker films could operate up to 60.3 GHz. Unit-cell sizes are proposed for various bands with quality factors from 10.2 to 29.3. Using the models, two applications are presented: a tunable dipole from 2.13 to 9.07 GHz and a tunable triple-stub matching network from 5 to 40 GHz with high $|\Gamma |$ . The proposed method appears viable for the realization of arbitrary programmable distributed circuits and antennas in the microwave and low-millimeter-wave bands.
Incorporating Prior Knowledge into Regularized Regression

Motivation Associated with genomic features like gene expression, methylation and genotypes, used in statistical modeling of health outcomes, there is a rich set of meta-features like functional annotations, pathway information and knowledge from previous studies, that can be used post hoc to facilitate the interpretation of a model. However, using this meta-feature information a priori rather than post hoc can yield improved prediction performance as well as enhanced model interpretation. Results We propose a new penalized regression approach that allows a priori integration of external meta-features. The method extends LASSO regression by incorporating individualized penalty parameters for each regression coefficient. The penalty parameters are, in turn, modeled as a log-linear function of the meta-features and are estimated from the data using an approximate empirical Bayes approach. Optimization of the marginal likelihood on which the empirical Bayes estimation is performed using a fast and stable majorization-minimization procedure. Through simulations, we show that the proposed regression with individualized penalties can outperform the standard LASSO in terms of both parameters estimation and prediction performance when the external data is informative. We further demonstrate our approach with applications to gene expression studies of bone density and breast cancer. Availability and implementation The methods have been implemented in the R package xtune freely available for download from https://cran.r-project.org/web/packages/xtune/index.html.
Early COVID-19 Interventions Failed to Replicate 1918 St. Louis vs. Philadelphia Outcomes in the United States

The Coronavirus disease 2019 (COVID-19) pandemic has elicited an abrupt pause in the United States in multiple sectors of commerce and social activity. As the US faces this health crisis, the magnitude and rigor of their initial public health response was unprecedented. As a response, the entire nation shutdown at the state-level for the duration of a ~1-3 months. These public health interventions, however, were not arbitrarily decided, but rather, implemented as a result of evidence-based practices. These practices were a result of lessons learned during the 1918 influenza pandemic and the city-level non-pharmaceutical interventions (NPIs) taken across the US. During the 1918 pandemic, two model cities, St. Louis, MO, and Philadelphia, PA, carried out two different approaches to address the spreading disease, which resulted in two distinctly different outcomes. Our group has evaluated the state-level public health response adopted by states across the US, with a focus on New York, California, Florida, and Texas, and compared the effectiveness of reducing the spread of COVID-19. Our assessments show that while the states mentioned above benefited from the implementations of early preventative measures, they inadequately replicated the desired outcomes observed in St. Louis during the 1918 crisis. Our study indicates that there are other factors, including health disparities that may influence the effectiveness of public health interventions applied. Identifying more specific health determinants may help implement targeted interventions aimed at preventing the spread of COVID-19 and improving health equity.
Programming Multifaceted Pulmonary T Cell Immunity by Combination Adjuvants

Summary Induction of protective mucosal T cell memory remains a formidable challenge to vaccinologists. Using a combination adjuvant strategy that elicits potent CD8 and CD4 T cell responses, we define the tenets of vaccine-induced pulmonary T cell immunity. An acrylic-acid-based adjuvant (ADJ), in combination with Toll-like receptor (TLR) agonists glucopyranosyl lipid adjuvant (GLA) or CpG, promotes mucosal imprinting but engages distinct transcription programs to drive different degrees of terminal differentiation and disparate polarization of TH1/TC1/TH17/TC17 effector/memory T cells. Combination of ADJ with GLA, but not CpG, dampens T cell receptor (TCR) signaling, mitigates terminal differentiation of effectors, and enhances the development of CD4 and CD8 TRM cells that protect against H1N1 and H5N1 influenza viruses. Mechanistically, vaccine-elicited CD4 T cells play a vital role in optimal programming of CD8 TRM and viral control. Taken together, these findings provide further insights into vaccine-induced multifaceted mucosal T cell immunity with implications in the development of vaccines against respiratorypathogens, including influenza virus and SARS-CoV-2.
Should Virus Capsids Assemble Perfectly? Theory and Observation of Defects

Abstract Although published structural models of viral capsids generally exhibit a high degree of regularity or symmetry, structural defects might be expected because of the fluctuating environment in which capsids assemble and the requirement of some capsids for disassembly before genome delivery. Defective structures are observed in computer simulations, and are evident in single-particle cryoelectron microscopy studies. Here, we quantify the conditions under which defects might be expected, using a statistical mechanics model allowing for ideal, defective, and vacant sites. The model displays a threshold in affinity parameters below which there is an appreciable population of defective capsids. Even when defective sites are not allowed, there is generally some population of vacancies. Analysis of single particles in cryoelectron microscopy micrographs yields a confirmatory ≳15% of defective particles. Our findings suggest structural heterogeneity in virus capsids may be under-appreciated, and also points to a nontraditional strategy for assembly inhibition.
(Mis)judging Ordinary Meaning?: Corpus Linguistics, the Frequency Fallacy, and the Extension-Abstraction Distinction in “Ordinary Meaning” Textualism

Rarely is a new yardstick of legal meaning created. But over the past decade, corpus linguistics has begun to be utilized as a new tool to measure ordinary meaning in statutory interpretation and original public meaning in constitutional interpretation. The legal application of corpus linguistics posits that an examination of every use of a term in a wide variety of documents can yield a more complete, impartial understanding of a word than can dictionaries, intuition, or an unsystematic survey of sources. Corpora could supplement, or even supplant, dictionaries and nativespeaker intuition in legal analyses. For originalism in particular, legal corpus linguistics promises to offer what would be a more scientific methodology for a point of view which, until now, has lacked one. However, corpus linguistics, as applied to legal problems, falls prey to a fatal methodological criticism – the frequency fallacy. The criticism states that in a corpus, an unusual meaning can have many corpus entries while a perfectly ordinary meaning can be completely absent from the corpus. That is, frequency is not a good measure of meaning. Since legal corpus linguistics relies on frequency, the corpus cannot inform legal meaning. This article parries this otherwise fatal critique. It argues that while the frequency fallacy is self-evidently true, the fallacy is not inherent to the corpus, but rather is an artifact of misinterpreting the corpus by treating it like a dictionary. This defense consists of a number of steps. The first step distinguishes between two different methods of discerning ordinary meaning: extension and abstraction. As illustrated by Yates v. United States and United States v. Marshall, extension entails extending the statutory term to varying facts, while abstraction keeps the facts constant and abstracts out key qualities to find an appropriate term. Critically, this article argues that abstraction offers a way to avoid the frequency fallacy. Second, to use abstraction properly, one must analyze not only the presence of the legal term in question but also its absence; that is, one must determine the presence or absence of other terms to describe a similar factual scenario to distinguish between artifacts of language and facts about the world. This article concludes by arguing that this method has a beneficial emergent quality. Not only does this answer make legal corpus analysis methodologically sound, but it also paves the way for the first tool to approximate how an ordinary person would read the law, thus potentially furthering the rule of law.
An autonomous rendezvous and docking system using cruise missile technologies

In November 1990 the Autonomous Rendezvous & Docking (AR&D) system was first demonstrated for members of NASA's Strategic Avionics Technology Working Group. This simulation utilized prototype hardware from the Cruise Missile and Advanced Centaur Avionics systems. The object was to show that all the accuracy, reliability and operational requirements established for a space craft to dock with Space Station Freedom could be met by the proposed system. The rapid prototyping capabilities of the Advanced Avionics Systems Development Laboratory were used to evaluate the proposed system in a real time, hardware in the loop simulation of the rendezvous and docking reference mission. The simulation permits manual, supervised automatic and fully autonomous operations to be evaluated. It is also being upgraded to be able to test an Autonomous Approach and Landing (AA&L) system. The AA&L and AR&D systems are very similar. Both use inertial guidance and control systems supplemented by GPS. Both use an Image Processing System (IPS), for target recognition and tracking. The IPS includes a general purpose multiprocessor computer and a selected suite of sensors that will provide the required relative position and orientation data. Graphic displays can also be generated by the computer, providing the astronaut / operator with real-time guidance and navigation data with enhanced video or sensor imagery.
Stochastic PDE limit of the dynamic ASEP

We study a stochastic PDE limit of the height function of the dynamic asymmetric simple exclusion process (dynamic ASEP). Introduced in Borodin (Symmetric elliptic functions, IRF models, and dynamic exclusion processes, 2017), the dynamic ASEP has a jump parameter $$q\in (0,1)$$ and a dynamical parameter $$\alpha >0$$ . It degenerates to the standard ASEP height function when $$\alpha $$ goes to 0 or $$\infty $$ . We consider a very weakly asymmetric regime, i.e. for $$\varepsilon $$ tending to zero we set $$q=e^{-\varepsilon }$$ . We show that under the parabolic scaling the height function of the dynamic ASEP converges to the solution of the space-time Ornstein–Uhlenbeck (OU) process. We also introduce the dynamic ASEP on a ring with generalized rate functions. Under the very weakly asymmetric scaling, we show that the dynamic ASEP (with generalized jump rates) on a ring also converges to the solution of the space-time OU process on [0, 1] with periodic boundary conditions.
Black-Box Non-interactive Non-malleable Commitments

There has been recent exciting progress on building non-interactive non-malleable commitments from judicious assumptions. All proposed approaches proceed in two steps. First, obtain simple “base” commitment schemes for very small tag/identity spaces based on a various sub-exponential hardness assumptions. Next, assuming sub-exponential non-interactive witness indistinguishable proofs (NIWIs), and variants of keyless collision resistant hash functions, construct non-interactive compilers that convert tag-based non-malleable commitments for a small tag space into tag-based non-malleable commitments for a larger tag space.
Axial-DeepLab: Stand-Alone Axial-Attention for Panoptic Segmentation

Convolution exploits locality for efficiency at a cost of missing long range context. Self-attention has been adopted to augment CNNs with non-local interactions. Recent works prove it possible to stack self-attention layers to obtain a fully attentional network by restricting the attention to a local region. In this paper, we attempt to remove this constraint by factorizing 2D self-attention into two 1D self-attentions. This reduces computation complexity and allows performing attention within a larger or even global region. In companion, we also propose a position-sensitive self-attention design. Combining both yields our position-sensitive axial-attention layer, a novel building block that one could stack to form axial-attention models for image classification and dense prediction. We demonstrate the effectiveness of our model on four large-scale datasets. In particular, our model outperforms all existing stand-alone self-attention models on ImageNet. Our Axial-DeepLab improves 2.8% PQ over bottom-up state-of-the-art on COCO test-dev. This previous state-of-the-art is attained by our small variant that is \(3.8\times \) parameter-efficient and \(27\times \) computation-efficient. Axial-DeepLab also achieves state-of-the-art results on Mapillary Vistas and Cityscapes.
A Machine Learning based Framework for KPI Maximization in Emerging Networks using Mobility Parameters

Current LTE network is faced with a plethora of Configuration and Optimization Parameters (COPs), both hard and soft, that are adjusted manually to manage the network and provide better Quality of Experience (QoE). With 5G in view, the number of these COPs are expected to reach 2000 per site, making their manual tuning for finding the optimal combination of these parameters, an impossible fleet. Alongside these thousands of COPs is the anticipated network densification in emerging networks which exacerbates the burden of the network operators in managing and optimizing the network. Hence, we propose a machine learning-based framework combined with a heuristic technique to discover the optimal combination of two pertinent COPs used in mobility, Cell Individual Offset (CIO) and Handover Margin (HOM), that maximizes a specific Key Performance Indicator (KPI) such as mean Signal to Interference and Noise Ratio (SINR) of all the connected users. The first part of the framework leverages the power of machine learning to predict the KPI of interest given several different combinations of CIO and HOM. The resulting predictions are then fed into Genetic Algorithm (GA) which searches for the best combination of the two mentioned parameters that yield the maximum mean SINR for all users. Performance of the framework is also evaluated using several machine learning techniques, with CatBoost algorithm yielding the best prediction performance. Meanwhile, GA is able to reveal the optimal parameter setting combination more efficiently and with three orders of magnitude faster convergence time in comparison to brute force approach.
Jet Collimation by Small-Scale Magnetic Fields

A popular model for jet collimation is associated with the presence of a large-scale and predominantly toroidal magnetic field originating from the central engine (a star, a black hole, or an accretion disk). Besides the problem of how such a large-scale magnetic field is generated, in this model the jet suffers from the fatal long-wave mode kink magnetohydrodynamic instability. In this paper we explore an alternative model: jet collimation by small-scale magnetic fields. These magnetic fields are assumed to be local, chaotic, and tangled, but are dominated by toroidal components. Just as in the case of a large-scale toroidal magnetic field, we show that the "hoop stress" of the tangled toroidal magnetic fields exerts an inward force which confines and collimates the jet. The magnetic "hoop stress" is balanced either by the gas pressure of the jet or by centrifugal force if the jet is spinning. Since the length scale of the magnetic field is small (< the cross-sectional radius of the jet the length of the jet), in this model the jet does not suffer from the long-wave mode kink instability. Many other problems associated with the large-scale magnetic field are also eliminated or alleviated for small-scale magnetic fields. Though it remains an open question how to generate and maintain the required small-scale magnetic fields in a jet, the scenario of jet collimation by small-scale magnetic fields is favored by the current study on disk dynamo which indicates that small-scale magnetic fields are much easier to generate than large-scale magnetic fields.
Low Temperature VECSEL-to-Diamond Heterogeneous Integration with Ag-In Spinodal Nanostructured Layer

Abstract Low temperature heterogeneous integration with diamond is the key technology in pushing upwards the high-power limit of a vertically-external-cavity surface-emitting laser (VECSEL). This work successfully accomplished a functional high-power VECSEL-to-diamond device with a modified Ag-In transient liquid phase (TLP) bonding technology. The post-bonding quality of VECSEL epitaxial membrane was thoroughly examined with scanning electron microscopy (SEM), focus ion beam (FIB) and high resolution high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM). Owing to the low-temperature process, thermal-activated diffusion and thermo-mechanical stress have been suppressed to the minimal level within the epitaxial layers while optimizing the heat-spreading capability of the diamond. Interestingly, with experimental and thermodynamic evidences, a distinct nanostructure from spinodal decomposition has been discovered in the Ag-In bonding layer for the first time, whose structural feature is beneficial to the reliability of a VECSEL-to-diamond device. Conceptually, this work opens a new bonding technology category, i.e., Ag-In spinodal bonding.
Emergent Spatial Structure and Entanglement Localization in Floquet Conformal Field Theory

We study the energy and entanglement dynamics of (1+1)D conformal field theories (CFTs) under a Floquet drive with the sine-square deformed (SSD) Hamiltonian. Previous work has shown that this model supports both a nonheating and a heating phase. Here, we analytically establish several robust and “superuniversal” features of the heating phase which rely on conformal invariance but not on the details of the CFT involved. First, we show the energy density is concentrated in two peaks in real space, a chiral and an antichiral peak, which leads to an exponential growth in the total energy. The peak locations are set by fixed points of the Mobius transformation. Second, all of the quantum entanglement is shared between these two peaks. In each driving period, a number of Bell pairs are generated, with one member pumped to the chiral peak and the other member pumped to the antichiral peak. These Bell pairs are localized, accumulate at these two peaks, and can serve as a source of quantum entanglement. Third, in both the heating and nonheating phases, we find that the total energy is related to the half system entanglement entropy by a simple relation E(t)∝cexp[(6/c)S(t)] with c being the central charge. In addition, we show that the nonheating phase, in which the energy and entanglement oscillate in time, is unstable to small fluctuations of the driving frequency in contrast to the heating phase. Finally, we point out an analogy to the periodically driven harmonic oscillator which allows us to understand global features of the phases and introduce a quasiparticle picture to explain the spatial structure, which can be generalized to setups beyond the SSD construction.
Formation of collapsed tetragonal phase in EuCo2As2 under high pressure

The structural properties of EuCo2As2 have been studied up to 35 GPa, through the use of x-ray diffraction in a diamond anvil cell at a synchrotron source. At ambient conditions, EuCo2As2 (I4/mmm) has a tetragonal lattice structure with a bulk modulus of 48 ± 4 GPa. With the application of pressure, the a axis exhibits negative compressibility with a concurrent sharp decrease in c-axis length. The anomalous compressibility of the a axis continues until 4.7 GPa, at which point the structure undergoes a second-order phase transition to a collapsed tetragonal (CT) state with a bulk modulus of 111 ± 2 GPa. We found a strong correlation between the ambient pressure volume of 122 parents of superconductors and the corresponding tetragonal to collapsed tetragonal phase transition pressures.
Protostar Mass Functions in Young Clusters

In an improved model of protostar mass functions (PMFs), protostars gain mass from isothermal cores in turbulent clumps. Their mass accretion rate is similar to Shu accretion at low mass and to reduced Bondi accretion at high mass. Accretion durations follow a simple expression in which higher-mass protostars accrete for longer times. These times are set by ejections, stellar feedback, and gravitational competition, which terminate accretion and reduce its efficiency. The mass scale is the mass of a critically stable isothermal core. In steady state, the PMF approaches a power law at high mass because of competition between clump accretion and accretion stopping. The power law exponent is the ratio of the timescales of accretion and accretion stopping. The protostar luminosity function (PLF) peaks near 1 L ☉ because of inefficient accretion of core gas. Models fit observed PLFs in four large embedded clusters. These indicate that their underlying PMFs may be top-heavy compared with the initial mass function, depending on the protostar radius model.
Lower bound on the number of non-simple closed geodesics on surfaces

We give a lower bound on the number of non-simple closed geodesics on a hyperbolic surface, given upper bounds on both length and self-intersection number. In particular, we carefully show how to construct closed geodesics on pairs of pants, and give a lower bound on the number of curves in this case. The lower bound for arbitrary surfaces follows from the lower bound on pairs of pants. This lower bound demonstrates that as the self-intersection number $$K = K(L)$$ goes from a constant to a quadratic function of L, the number of closed geodesics transitions from polynomial to exponential in L. We show upper bounds on the number of such geodesics in a subsequent paper.
NEOWISE Reactivation Mission Year Two: Asteroid Diameters and Albedos

The Near-Earth Object Wide-field Infrared Survey Explorer (NEOWISE) reactivation mission has completed its third year of surveying the sky in the thermal infrared for near-Earth asteroids and comets. NEOWISE collects simultaneous observations at 3.4 and 4.6 μm of solar system objects passing through its field of regard. These data allow for the determination of total thermal emission from bodies in the inner solar system, and thus the sizes of these objects. In this paper, we present thermal model fits of asteroid diameters for 170 NEOs and 6110 Main Belt asteroids (MBAs) detected during the third year of the survey, as well as the associated optical geometric albedos. We compare our results with previous thermal model results from NEOWISE for overlapping sample sets, as well as diameters determined through other independent methods, and find that our diameter measurements for NEOs agree to within 26% (1σ) of previously measured values. Diameters for the MBAs are within 17% (1σ). This brings the total number of unique near-Earth objects characterized by the NEOWISE survey to 541, surpassing the number observed during the fully cryogenic mission in 2010.
Sensitivity of inflationary predictions to pre-inflationary phases

How sensitive are the predictions of inflation to pre-inflationary conditions when the number of efolds of inflation is not too large? In an attempt to address this question, we consider a simple model where the inflationary era is preceded by an era dominated by a radiation fluid, which is coupled to the inflaton only gravitationally and which extends back to the Planck era. We show that there is a natural generalized Bunch-Davies vacuum state for perturbations to the coupled inflaton-gravity-fluid system at early times. With this choice of initial state the model predicts interesting deviations from the standard power spectrum of single field slow-roll inflation at large scales. However, the deviations are too small to be observable in near future CMB observations.
Radii and Distances of Cepheids. I. Method and Measurement Errors

We develop a formulation of the Baade-Wesselink method which uses the Fourier coefficients of the observables. We derive an explicit, analytic expression to determine the mean radius from each Fourier order. The simplicity of this method allows us to derive the uncertainty in the mean radius due to measurement errors. Using simulations and a recent data set we demonstrate that the precision of the radius measurement with optical magnitudes is in most cases limited by the accuracy of the measurement of the phase difference between the light and the color index curve. In this case it is advantageous to determine the inverse radius, because it has normal errors.
Transient terahertz photoconductivity measurements of minority-carrier lifetime in tin sulfide thin films: Advanced metrology for an early stage photovoltaic material

Materials research with a focus on enhancing the minority-carrier lifetime of the light-absorbing semiconductor is key to advancing solar energy technology for both early stage and mature material platforms alike. Tin sulfide (SnS) is an absorber material with several clear advantages for manufacturing and deployment, but the record power conversion efficiency remains below 5%. We report measurements of bulk and interface minority-carrier recombination rates in SnSthin films using optical-pump, terahertz-probe transient photoconductivity (TPC) measurements. Post-growth thermal annealing in H2S gas increases the minority-carrier lifetime, and oxidation of the surface reduces the surface recombination velocity. However, the minority-carrier lifetime remains below 100 ps for all tested combinations of growth technique and post-growth processing. Significant improvement in SnSsolar cell performance will hinge on finding and mitigating as-yet-unknown recombination-active defects. We describe in detail our methodology for TPC experiments, and we share our data analysis routines in the form freely available software.
The Lie module and its complexity

The complexity of a module is an important homological invariant that measures the polynomial rate of growth of its minimal projective resolution. For the symmetric group Σn, the Lie module Lie(n) has attracted a great deal of interest in recent years. We prove here that the complexity of Lie(n) in characteristic p is t, where p is the largest power of p dividing n, thus proving a conjecture of Erdmann, Lim and Tan. The proof uses work of Arone and Kankaanrinta which describes the homology H•(Σn, Lie(n)) and earlier work of Hemmer and Nakano on complexity for modules over Σn that involves restriction to Young subgroups.
Large‐scale asymmetry between clockwise and counterclockwise galaxies revisited

The ability of digital sky surveys to collect and store very large amounts of data provides completely new ways to study the local universe. Perhaps one of the most provocative observations reported with such tools is the asymmetry between galaxies with clockwise and counterclockwise spin patterns. Here I use $\sim1.7\cdot10^5$ spiral galaxies from SDSS and sort them by their spin patterns (clockwise or counterclockwise) to identify and profile a possible large-scale pattern of the distribution of galaxy spin patterns as observed from Earth. The analysis shows asymmetry between the number of clockwise and counterclockwise spiral galaxies imaged by SDSS, and a dipole axis. These findings largely agree with previous reports using smaller datasets. The probability of the differences between the number of galaxies to occur by chance is (P<4*10^-9), and the probability of an asymmetry axis to occur by mere chance is (P<1.4*10^-5).
Explicit Formulas for Heat Kernels on Diamond Fractals

This paper provides explicit pointwise formulas for the heat kernel on compact metric measure spaces that belong to a ( $${\mathbb{N}\times\mathbb{N})}$$ -parameter family of fractals, which are regarded as projective limits of metric measure graphs and do not satisfy the volume doubling property. The formulas are applied to obtain uniform continuity estimates of the heat kernel and to derive an expression of the fundamental solution of the free Schrodinger equation. The results also open up the possibility to approach infinite dimensional spaces based on this model.
No Trace Left Behind: STEREO Observation of a Coronal Mass Ejection Without Low Coronal Signatures

The availability of high-quality synoptic observations of the extreme-ultraviolet (EUV) and visible corona during the SOHO mission has advanced our understanding of the low corona manifestations of coronal mass ejections (CMEs). The EUV imager/white light coronagraph connection has been proven so powerful, it is routinely assumed that if no EUV signatures are present when a CME is observed by a coronagraph, then the event must originate behind the visible limb. This assumption carries strong implications for space weather forecasting but has not been put to the test. This paper presents the first detailed analysis of a frontside, large-scale CME that has no obvious counterparts in the low corona as observed in EUV and Hα wavelengths. The event was observed by the SECCHI instruments onboard the STEREO mission. The COR2A coronagraph observed a slow flux-rope-type CME, while an extremely faint partial halo was observed in COR2B. The event evolved very slowly and is typical of the streamer-blowout CME class. EUVI A 171 A images show a concave feature above the east limb, relatively stable for about two days before the eruption, when it rises into the coronagraphic fields and develops into the core of the CME. None of the typical low corona signatures of a CME (flaring, EUV dimming, filament eruption, waves) were observed in the EUVI B images, which we attribute to the unusually large height from which the flux rope lifted off. This interpretation is supported by the CME mass measurements and estimates of the expected EUV dimming intensity. Only thanks to the availability of the two viewpoints we were able to identify the likely source region. The event originated along a neutral line over the quiet-Sun. No active regions were present anywhere on the visible (from STEREO B) face of the disk. Leaving no trace behind on the solar disk, this observation shows unambiguously that a CME eruption does not need to have clear on-disk signatures. Also it sheds light on the question of "mystery" geomagnetic storms, storms without clear solar origin (formerly called problem storms). We discuss the implications for space weather monitoring. Preliminary inspection of STEREO data indicates that events like this are not uncommon, particularly during the ongoing period of deep solar minimum.
A refinement of entanglement entropy and the number of degrees of freedom

We introduce a \renormalized entanglement entropy" which is intrinsically UV nite and is most sensitive to the degrees of freedom at the scale of the size R of the entangled region. We illustrated the power of this construction by showing that the qualitative behavior of the entanglement entropy for a non-Fermi liquid can be obtained by simple dimensional analysis. We argue that the functional dependence of the \renormalized entanglement entropy" on R can be interpreted as describing the renormalization group ow of the entanglement entropy with distance scale. The corresponding quantity for a spherical region in the vacuum, has some particularly interesting properties. For a conformal eld theory, it reduces to the previously proposed central charge in all dimensions,