cssi/SciSciGPT-SciSciNet huggingface dataset:
Consistent high-frequency calibration

Abstract Economic models are meant to provide a framework to describe real-world economic activities. In principle, how well a model performs this task can be evaluated by how close the model's simulated activities track the observed ones. A necessary first step in simulating a model is to choose values for the model's parameters in accordance with actual economic data. A fundamental problem in economic modelling, however, is that actual economic data are sampled at time intervals that are typically longer than the decision intervals of actual economic agents. One popular resolution of this problem is to constrain the length of the decision intervals of theoretical economic agents to be equal to the length of the actual data-sampling intervals. This widely adopted approach makes it feasible to directly calibrate theoretical models to the observed data, but it can introduce substantial biases in the models’ empirical performance, as demonstrated by recent research that has allowed the decision intervals to be shorter than the data-sampling intervals. This alternative, high-frequency modelling approach, however, has brought with itself a fundamental issue that direct calibration of the models’ parameters is no longer feasible. In response, researchers have employed an ad hoc rule to transform commonly chosen lower-frequency parameter values (which can be calibrated directly from the available data) to their high-frequency counterparts. We show in this paper that this standard transformation rule has three major drawbacks. First, it produces internal inconsistencies in steady-state equilibrium conditions. Second, it is sometimes at odds with microeconomic evidence. And third, it can result in inaccurate log-linear approximations to the models’ true equilibrium solutions by worsening the fit of both the transition dynamic coefficients and the point of approximation itself. We present here an alternative, coherent transformation rule for calibrating high-frequency models that directly addresses these three shortcomings. We then use our consistent transformation rule to calibrate high-frequency versions of two well-known economic models and show how it improves these models’ empirical performance.
Attitudes Toward Fertility Preservation Among Transgender Youth and Their Parents.

Abstract Purpose While gender-affirming hormones (GAH) may impact the fertility of transgender and gender diverse (TGGD) youth, few pursue fertility preservation (FP). The objective of this study is to understand youth and parent attitudes toward FP decision-making. Methods This study is a cross-sectional survey of youth and parents in a pediatric, hospital-based gender clinic from April to December 2017. Surveys were administered electronically, containing 34 items for youth and 31 items for parents regarding desire for biological children, willingness to delay GAH for FP, and factors influencing FP decisions. Results The mean age of youth (n = 64) was 16.8 years, and 64% assigned female at birth; 46 parents participated. Few youth (20%) and parents (13%) found it important to have biological children or grandchildren, and 3% of youth and 33% of parents would be willing to delay GAH for FP. The most common factor influencing youth FP decision-making was discomfort with a body part they do not identify with (69%), and for the parents, whether it was important to their child (61%). In paired analyses, youth and their parents answered similarly regarding youth desire for biological children and willingness to delay GAH for FP. Conclusions The majority of TGGD youth and parents did not find having biological offspring important and were not willing to delay GAH for FP. Discomfort with reproductive anatomy was a major influencing factor for youth FP decision-making and their child's wishes was a major factor for parents. Future qualitative research is needed to understand TGGD youth and parent attitudes toward FP and to develop shared decision-making tools.
Defecography: Results in 55 patients and impact on clinical management

We reviewed the medical records and defecograms in 55 consecutive patients to determine the impact of results of defecography on clinical management. Main indication for defecography was constipation, present in 40 (73%) of 55 patients. In the remaining 15 patients, indications included obstructed defecation (5), incontinence (5), and miscellaneous symptoms (5). Defecography evaluated pelvic floor motion by assessing changes in the anorectal angle (ARA) and anorectal junction (ARJ) during various maneuvers, extent of evacuation, and structural abnormalities. Patients were grouped based on results of defecography as being normal (26) or abnormal (29). Comparison of measurements of the ARA and ARJ with various maneuvers showed no significant differences between the two groups. Clinical impact was determined by analyzing therapy done following defecography and subsequent patient response. In the normal group, 15 patients were managed medically, seven surgically, and four lost to follow-up. Clinical improvement occurred in 13 (59%) of 22 patients, with similar results between medical (60%) and surgical (57%) therapy. In the abnormal group, 16 had medical management, seven surgical therapy, and six lost to follow-up. Clinical improvement occurred in 13 (57%) of 23 patients but surgical therapy showed more improvement. In conclusion, most standard measurements of the ARA and ARJ were of no value in determining abnormality. Results of defecography did not alter selection of medical or surgical therapy, and had little impact on patient response to therapy.
14 – Sequences and Series

In Chapter 13 we saw how a wide variety of functions could be approximated by polynomials. A polynomial in x is a finite sum of terms of the form akxk. In this chapter we will discuss what we mean by an infinite sum. The infinite sums we describe are called infinite series. We will discuss the theory of infinite series and will show how it can give us a great deal of information about a wide variety of functions.
Trade intensity and business cycle synchronization: Are developing countries any different?

Some key criteria in the optimal currency area literature are that countries should join a currency union if they have closer international trade links and more symmetric business cycles. However, both criteria are endogenous. Frankel and Rose (1998) find that trade intensity increases cycle correlation among industrial countries. We study whether the same result holds true for the case of developing countries, as their different patterns of international trade and specialization may lead to cyclical asymmetries among them and between industrial and developing countries. We gather annual information for 147 countries for 1960-99 (33,676 country pairs) and find: (i) countries with higher bilateral trade exhibit higher business cycle synchronization, with an increase of one standard deviation in bilateral trade intensity raising the output correlation from 0.05 to 0.09 for all country pairs; (ii) countries with more asymmetric structures of production exhibit a smaller business cycle correlation; (iii) the impact of trade integration on business cycles is higher for industrial countries than both developing and industrial-developing country pairs; (iv) a one standard deviation increase in bilateral trade intensity leads to surges in output correlation from 0.25 to 0.39 among industrial countries, from 0.08 to 0.10 for our sample of industrial-developing country pairs, and from 0.03 to 0.06 among developing countries; (v) the impact of trade intensity on cycle correlation is smaller the greater the production structure asymmetries between the countries.
Multi-objective Ranking via Constrained Optimization

In this paper, we introduce an Augmented Lagrangian based method to incorporate the multiple objectives (MO) in a search ranking algorithm. Optimizing MOs is an essential and realistic requirement for building ranking models in production. The proposed method formulates MO in constrained optimization and solves the problem in the popular Boosting framework – a novel contribution of our work. Furthermore, we propose a procedure to set up all optimization parameters in the problem. The experimental results show that the method successfully achieves MO criteria much more efficiently than existing methods.
Who Votes for Medicaid Expansion? Lessons from Maine’s 2017 Referendum

Context In November 2017, Maine became the first state in the nation to vote on a key provision of the Affordable Care Act: the expansion of Medicaid. Methods This study merged official election results from localities across Maine with Census Bureau and American Hospital Association data to identify characteristics of areas that support Medicaid expansion. Findings Places with more bachelor's degree holders more often vote in favor, whereas those with more associate's degree graduates tend to vote against. Conditional on education rates, areas with more uninsured individuals who would qualify for expanded coverage tend to vote in favor, while those with more high-income individuals tend to vote against. Also conditional on education rates, greater hospital employment is associated with support for expansion, but the presence of other health professionals, whose incomes might decrease from expansion, is associated with less support. Conclusions Voting patterns are mostly consistent with economic self-interest, except for the sizable association of bachelor's degree holders with support for Medicaid expansion. Direct democracy can shift Medicaid policy: extrapolating to other states, the model predicts that hypothetical referenda would pass in 5 of the 18 states that had not yet expanded Medicaid at the time of Maine's vote.
Improved Embeddings with Easy Positive Triplet Mining

Deep metric learning seeks to define an embedding where semantically similar images are embedded to nearby locations, and semantically dissimilar images are embedded to distant locations. Substantial work has focused on loss functions and strategies to learn these embeddings by pushing images from the same class as close together in the embedding space as possible. In this paper, we propose an alternative, loosened embedding strategy that requires the embedding function only map each training image to the most similar examples from the same class, an approach we call "Easy Positive" mining. We provide a collection of experiments and visualizations that highlight that this Easy Positive mining leads to embed-dings that are more flexible and generalize better to new unseen data. This simple mining strategy yields recall performance that exceeds state of the art approaches (including those with complicated loss functions and ensemble methods) on image retrieval datasets including CUB, Stanford Online Products, In-Shop Clothes and Hotels-50K. Code is available at: https://github.com/littleredxh/EasyPositiveHardNegative
An Engineered CRISPR-Cas9 Mouse Line for Simultaneous Readout of Lineage Histories and Gene Expression Profiles in Single Cells

Summary Tracing the lineage history of cells is key to answering diverse and fundamental questions in biology. Coupling of cell ancestry information with other molecular readouts represents an important goal in the field. Here, we describe the CRISPR array repair lineage tracing (CARLIN) mouse line and corresponding analysis tools that can be used to simultaneously interrogate the lineage and transcriptomic information of single cells in vivo. This model exploits CRISPR technology to generate up to 44,000 transcribed barcodes in an inducible fashion at any point during development or adulthood, is compatible with sequential barcoding, and is fully genetically defined. We have used CARLIN to identify intrinsic biases in the activity of fetal liver hematopoietic stem cell (HSC) clones and to uncover a previously unappreciated clonal bottleneck in the response of HSCs to injury. CARLIN also allows the unbiased identification of transcriptional signatures associated with HSC activity without cell sorting.
Superiority of Bayes estimators over the MLE in high dimensional multinomial models and its implication for nonparametric Bayes theory

Abstract The performance of Bayes estimators is examined, in comparison with the MLE, in multinomial models with a relatively large number of cells. The prior for the Bayes estimator is taken to be the conjugate Dirichlet, i.e., the multivariate Beta, with exchangeable distributions over the coordinates, including the non-informative uniform distribution. The choice of the multinomial is motivated by its many applications in business and industry, but also by its use in providing a simple nonparametric estimator of an unknown distribution. It is striking that the Bayes procedure outperforms the asymptotically efficient MLE over most of the parameter spaces for even moderately large dimensional parameter spaces and rather large sample sizes.
An Energy-aware Online Learning Framework for Resource Management in Heterogeneous Platforms

Mobile platforms must satisfy the contradictory requirements of fast response time and minimum energy consumption as a function of dynamically changing applications. To address this need, systems-on-chip (SoC) that are at the heart of these devices provide a variety of control knobs, such as the number of active cores and their voltage/frequency levels. Controlling these knobs optimally at runtime is challenging for two reasons. First, the large configuration space prohibits exhaustive solutions. Second, control policies designed offline are at best sub-optimal, since many potential new applications are unknown at design-time. We address these challenges by proposing an online imitation learning approach. Our key idea is to construct an offline policy and adapt it online to new applications to optimize a given metric (e.g., energy). The proposed methodology leverages the supervision enabled by power-performance models learned at runtime. We demonstrate its effectiveness on a commercial mobile platform with 16 diverse benchmarks. Our approach successfully adapts the control policy to an unknown application after executing less than 25% of its instructions.
Braneworld effective field theories — holography, consistency and conformal effects

Braneworld theories are often described as low-energy effective field theories (EFTs) featuring an infinitely thin 3-brane and 4D fields exactly localized on it. We investigate whether an exactly localized braneworld can arise as a limit of a theory of 5D fields. Using a holographic formalism we argue that such limit does not exist in the presence of gravity, therefore implying a discontinuity in the space of EFTs. We then present specific models involving exactly localized fields in which inconsistencies appear, which are solved when fields are taken as quasilocalized. Part of our arguments rely on conjectures from the “swampland” program. Our investigation motivates braneworld EFTs built from 5D fields, i.e. quasilocalized braneworlds. Observable effects from quasilocalization are significant for warped braneworlds such as Randall-Sundrum II (RSII), and are reminiscent of a conformal hidden sector. Focusing on the gauge-gravity sector we show that manifestations of the quasilocalized warped braneworld include i) an anomalous running of SM gauge couplings ii) a conformal contribution to SM gauge boson scattering induced by 5D gravity. Constraining these effects puts an upper bound on the 5D EFT cutoff, implying that the warped braneworld hypothesis could — at least in principle — be tested completely.
Cooperative Resolvability and Secrecy in the Cribbing Multiple-Access Channel

We study channel resolvability for the discrete memoryless multiple-access channel with cribbing, i.e., the characterization of the amount of randomness required at the inputs to approximately produce a chosen i.i.d. output distribution according to Kullback-Leibler divergence. We analyze resolvability rates when one encoder cribs (i) the input of the other encoder; or the output of the other encoder, (ii) non-causally, (iii) causally, or (iv) strictly-causally. For scenarios (i)-(iii), we exactly characterize the channel resolvability region. For (iv), we provide inner and outer bounds for the channel resolvability region; the crux of our achievability result is to handle the strict causality constraint with a block-Markov coding scheme in which dependencies across blocks are suitably hidden. Finally, we leverage the channel resolvability results to derive achievable secrecy rate regions for each of the cribbing scenarios under strong secrecy constraints.
Statistical Engineering for Wind Tunnel Testing of Mars Parachute Designs

Formal experiment design and analysis techniques featuring design of experiments were applied to a Mars parachute wind tunnel test. The experiments were part of an extensive study conducted in 2014...
Algebraic hardness versus randomness in low characteristic

We show that lower bounds for explicit constant-variate polynomials over fields of characteristic p > 0 are sufficient to derandomize polynomial identity testing over fields of characteristic p. In this setting, existing work on hardness-randomness tradeoffs for polynomial identity testing requires either the characteristic to be sufficiently large or the notion of hardness to be stronger than the standard syntactic notion of hardness used in algebraic complexity. Our results make no restriction on the characteristic of the field and use standard notions of hardness.We do this by combining the Kabanets-Impagliazzo generator with a white-box procedure to take pth roots of circuits computing a pth power over fields of characteristic p. When the number of variables appearing in the circuit is bounded by some constant, this procedure turns out to be efficient, which allows us to bypass difficulties related to factoring circuits in characteristic p.We also combine the Kabanets-Impagliazzo generator with recent "bootstrapping" results in polynomial identity testing to show that a sufficiently-hard family of explicit constant-variate polynomials yields a near-complete derandomization of polynomial identity testing. This result holds over fields of both zero and positive characteristic and complements a recent work of Guo, Kumar, Saptharishi, and Solomon, who obtained a slightly stronger statement over fields of characteristic zero.
A Formal Analysis of Multimodal Referring Strategies Under Common Ground.

In this paper, we present an analysis of computationally generated mixed-modality definite referring expressions using combinations of gesture and linguistic descriptions. In doing so, we expose some striking formal semantic properties of the interactions between gesture and language, conditioned on the introduction of content into the common ground between the (computational) speaker and (human) viewer, and demonstrate how these formal features can contribute to training better models to predict viewer judgment of referring expressions, and potentially to the generation of more natural and informative referring expressions.
New Results for the Complexity of Resilience for Binary Conjunctive Queries with Self-Joins

The resilience of a Boolean query on a database is the minimum number of tuples that need to be deleted from the input tables in order to make the query false. A solution to this problem immediately translates into a solution for the more widely known problem of deletion propagation with source-side effects. In this paper, we give several novel results on the hardness of the resilience problem for conjunctive queries with self-joins, and, more specifically, we present a dichotomy result for the class of single-self-join binary queries with exactly two repeated relations occurring in the query. Unlike in the self-join free case, the concept of triad is not enough to fully characterize the complexity of resilience. We identify new structural properties, namely chains, confluences and permutations, which lead to various NP-hardness results. We also give novel involved reductions to network flow to show certain cases are in P. Although restricted, our results provide important insights into the problem of self-joins that we hope can help solve the general case of all conjunctive queries with self-joins in the future.
Mechanisms of γ-Secretase Activation and Substrate Processing.

Amyloid β-peptide, the principal component of characteristic cerebral plaques of Alzheimer's disease (AD), is produced through intramembrane proteolysis of the amyloid precursor protein (APP) by γ-secretase. Despite the importance in the pathogenesis of AD, the mechanisms of intramembrane proteolysis and substrate processing by γ-secretase remain poorly understood. Here, complementary all-atom simulations using a robust Gaussian accelerated molecular dynamics (GaMD) method and biochemical experiments were combined to investigate substrate processing of wildtype and mutant APP by γ-secretase. The GaMD simulations captured spontaneous activation of γ-secretase, with hydrogen bonded catalytic aspartates and water poised for proteolysis of APP at the e cleavage site. Furthermore, GaMD simulations revealed that familial AD mutations I45F and T48P enhanced the initial e cleavage between residues Leu49-Val50, while M51F mutation shifted the e cleavage site to the amide bond between Thr48-Leu49. Detailed analysis of the GaMD simulations allowed us to identify distinct low-energy conformational states of γ-secretase, different secondary structures of the wildtype and mutant APP substrate, and important active-site subpockets for catalytic function of the enzyme. The simulation findings were highly consistent with experimental analyses of APP proteolytic products using mass spectrometry and Western blotting. Taken together, the GaMD simulations and biochemical experiments have enabled us to elucidate the mechanisms of γ-secretase activation and substrate processing, which should facilitate rational computer-aided drug design targeting this functionally important enzyme.
TGFβ signaling is required for tenocyte recruitment and functional neonatal tendon regeneration

Tendon injuries are common with poor healing potential. The paucity of therapies for tendon injuries is due to our limited understanding of the cells and molecular pathways that drive tendon regeneration. Using a mouse model of neonatal tendon regeneration, we identified TGFβ signaling as a major molecular pathway that drives neonatal tendon regeneration. Through targeted gene deletion, small molecule inhibition, and lineage tracing, we elucidated TGFβ-dependent and TGFβ-independent mechanisms underlying tendon regeneration. Importantly, functional recovery depended on canonical TGFβ signaling and loss of function is due to impaired tenogenic cell recruitment from both Scleraxis-lineage and non-Scleraxis-lineage sources. We show that TGFβ signaling is directly required in neonatal tenocytes for recruitment and that TGFβ ligand is positively regulated in tendons. Collectively, these results show a functional role for canonical TGFβ signaling in tendon regeneration and offer new insights toward the divergent cellular activities that distinguish regenerative vs fibrotic healing.
Advancing Computational Reproducibility in the Dataverse Data Repository Platform

Recent reproducibility case studies have raised concerns showing that much of the deposited research has not been reproducible. One of their conclusions was that the way data repositories store research data and code cannot fully facilitate reproducibility due to the absence of a runtime environment needed for the code execution. New specialized reproducibility tools provide cloud-based computational environments for code encapsulation, thus enabling research portability and reproducibility. However, they do not often enable research discoverability, standardized data citation, or long-term archival like data repositories do. This paper addresses the shortcomings of data repositories and reproducibility tools and how they could be overcome to improve the current lack of computational reproducibility in published and archived research outputs.
Communication-Efficient Asynchronous Stochastic Frank-Wolfe over Nuclear-norm Balls.

Large-scale machine learning training suffers from two prior challenges, specifically for nuclear-norm constrained problems with distributed systems: the synchronization slowdown due to the straggling workers, and high communication costs. In this work, we propose an asynchronous Stochastic Frank Wolfe (SFW-asyn) method, which, for the first time, solves the two problems simultaneously, while successfully maintaining the same convergence rate as the vanilla SFW. We implement our algorithm in python (with MPI) to run on Amazon EC2, and demonstrate that SFW-asyn yields speed-ups almost linear to the number of machines compared to the vanilla SFW.
Collateral Misreporting in the Residential Mortgage-Backed Security Market

Securitized mortgage appraisals routinely target pre-specified valuations, 45% of purchase loan appraisals exactly equal purchase prices, and appraisals virtually never fall below purchase prices. ...
Hadron and Nuclear Physics on the Light Front

The QCD light-front (LF) Hamiltonian equation H_{LF}|\Psi> = M^2 |\Psi> derived from quantization at fixed LF time \tau = t+z/c provides a causal, frame-independent, method for computing hadron spectroscopy as well as dynamical observables such as structure functions, transverse momentum distributions, and distribution amplitudes. The LF formalism also leads to novel nuclear phenomena, such as "hidden color", "color transparency", "nuclear-bound quarkonium" and the shadowing and antishadowing of nuclear structure functions. For example, there are five distinct color-singlet Fock state representations of the six color-triplet quarks of the deuteron. The hidden color Fock states become manifest when the deuteron is probed when it has small transverse size, as in measurements of the deuteron form factor at large momentum transfer. The QCD Lagrangian with zero quark mass has no explicit mass scale. However, as shown by de Alfaro, Fubini, and Furlan (dAFF), a mass scale can appear in the equations of motion without affecting the conformal invariance of the Action. When one applies the dAFF procedure to the QCD LF Hamiltonian, it leads to a color confining potential \kappa^4 \zeta^2 for mesons, where \zeta^2 is the LF radial variable conjugate to the qbar-q invariant mass squared. The same result, including spin terms, is obtained using LF holography (AdS/QCD) -- the duality between LF dynamics and AdS_5 -- if one modifies the AdS_5 Action by the dilaton exp{+\kappa^2 z^2} in the fifth dimension z. If this procedure is generalized using superconformal algebra, the resulting LF eigensolutions provide unified Regge spectroscopy of mesons, baryons, and tetraquarks, including remarkable supersymmetric relations between the masses of mesons, baryons and tetraquarks with a universal Regge slope...
New Insights on One-Sided Lipschitz and Quadratically-Inner Bounded Nonlinear Dynamic Systems

Nonlinear dynamic systems can be classified into various classes depending on the modeled nonlinearity. These classes include Lipschitz, bounded Jacobian, one-sided Lipschitz (OSL), and quadratically inner-bounded (QIB). Such classes essentially yield bounding constants characterizing the nonlinearity. This is then used to design observers and controllers through Riccati equations or matrix inequalities. While analytical expressions for bounding constants of Lipschitz and bounded Jacobian nonlinearity are studied in the literature, OSL and QIB classes are not thoroughly analyzed-computationally or analytically. In short, this paper develops analytical expressions of OSL and QIB bounding constants. These expressions are posed as constrained maximization problems, which can be solved via various optimization algorithms. This paper also presents a novel insight particularly on QIB function set: any function that is QIB turns out to be also Lipschitz continuous.
Alexander Calder’s Half-Circle, Quarter-Circle, and Sphere (1932):A Complex History of Repainting Unraveled

The Whitney Museum of American Art, New York, owns one of the largest motorized works made by the renowned American artist Alexander Calder, titled Half-Circle, Quarter-Circle, and Sphere. Created in 1932, and acquired by the Whitney in 1969, this seminal work was featured in an iconic exhibition held in 2017 and entitled Calder: Hypermobility. Prior to that, the object underwent a series of treatments in order to repair its main kinetic elements that had become compromised during its lifetime. While the work’s mechanism retained its creator’s ingenious engineering solutions, the motor, urethane belts, plug, and electrical wires turned out to be neither original, nor authentic to the period. The appearance of the piece had also been altered, as most surfaces displayed multiple layers of overpainting and, thus, did not deliver the proper gloss, hue, and texture. These observations prompted a first, comprehensive scientific study to investigate the stratigraphy of Calder’s painted surfaces on Half-Circle, Quarter-Circle, and Sphere, with the final goal to comprehend and restore its original appearance through careful removal of the overpaint. Non-invasive X-ray fluorescence (XRF) analysis was carried out to gain initial insight into the paints’ composition. After that, extensive microscopic sampling was performed to assess the possible presence of original layers below the repainting throughout the object’s surface. Cross sections were examined with optical microscopy and analyzed with Fourier-transform infrared (FTIR) and Raman spectroscopies, as well as scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM/EDS), in order to identify pigments, colorants, and extenders located in the various paint layers. Scrapings were also investigated with pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) for a detailed characterization of the binding media. Scientific analysis revealed, in selected white and red areas, up to eleven layers of overpaint composed of a wide array of modern materials, including pigments (titanium white in the form of tetragonal rutile and a variety of synthetic organic red pigments) and binders (alkyd or late formulations of enamels based on ortho-phthalic acid/phthalic anhydride, glycerol and pentaerythritol, polyvinyl acetate with various plasticizers, and acrylics). On the other hand, the identification of materials that were available in the early 1930s, such as zinc white, calcite, and gypsum, as well as traditional drying oil binders, supported the hypothesis that a layer of original paint may still be present in certain areas. In addition to shedding new light on the stratigraphy of Calder’s painted surfaces, this study informed the optimization of a treatment plan tailored for the safe removal of the overpaint to uncover the original layer, wherever present.
Efficient machine learning approach for optimizing the timing resolution of a high purity germanium detector

Abstract We describe here an efficient machine-learning based approach for the optimization of parameters used for extracting the arrival time of waveforms, in particular those generated by the detection of 511 keV annihilation γ -rays by a 60 cm3 coaxial high purity germanium detector (HPGe). The method utilizes a type of artificial neural network (ANN) called a self-organizing map (SOM) to cluster the HPGe waveforms based on the shape of their rising edges. The optimal timing parameters for HPGe waveforms belonging to a particular cluster are found by minimizing the time difference between the HPGe signal and a signal produced by a BaF2 scintillation detector. Upon applying these variable timing parameters to the HPGe signals, we achieved a γ – γ coincidence timing resolution of ∼ 4.3 ns at the 511 keV photopeak (defined as 511 ± 50 keV) and a timing resolution of ∼ 6.5 ns for the entire γ -ray spectrum—without rejecting any valid pulses. This timing resolution approaches the best obtained by analog nuclear electronics, without the corresponding complexities of analog optimization procedures. We further demonstrate the universality and efficacy of the machine learning approach by applying the method to the generation of secondary electron time-of-flight spectra following the implantation of energetic positrons on a sample.
Enhanced room temperature infrared LEDs using monolithically integrated plasmonic materials

Remarkable systems have been reported recently using the polylithic integration of semiconductor optoelectronic devices and plasmonic materials exhibiting epsilon-near-zero (ENZ) and negative permittivity. In traditional noble metals, the ENZ and plasmonic response is achieved near the metal plasma frequency, limiting plasmonic optoelectronic device design flexibility. Here, we leverage an all-epitaxial approach to monolithically and seamlessly integrate designer plasmonic materials into a quantum dot light emitting diode, leading to a 5.6× enhancement over an otherwise identical non-plasmonic control sample. The device presented exhibits optical powers comparable, and temperature performance far superior, to commercially available devices.
Connexin-46/50 in a dynamic lipid environment resolved by CryoEM at 1.9 Å

Gap junctions establish direct pathways for cells to transfer metabolic and electrical messages. The local lipid environment is known to affect the structure, stability and intercellular channel activity of gap junctions; however, the molecular basis for these effects remains unknown. Here, we incorporate native connexin-46/50 (Cx46/50) intercellular channels into a dual lipid nanodisc system, mimicking a native cell-to-cell junction. Structural characterization by CryoEM reveals a lipid-induced stabilization to the channel, resulting in a 3D reconstruction at 1.9 A resolution. Together with all-atom molecular dynamics simulations, it is shown that Cx46/50 in turn imparts long-range stabilization to the dynamic local lipid environment that is specific to the extracellular lipid leaflet. In addition, ~400 water molecules are resolved in the CryoEM map, localized throughout the intercellular permeation pathway and contributing to the channel architecture. These results illustrate how the aqueous-lipid environment is integrated with the architectural stability, structure and function of gap junction communication channels. The local lipid environment is known to affect the structure, stability and intercellular channel activity of gap junctions, however, the molecular basis for these effects remains unknown. Here authors report the CryoEM structure of Cx46/50 lipid-embedded channels, by which they reveal a lipid-induced stabilization to the channel.
Modeling an integrated HIV prevention and care continuum to achieve the Ending the HIV Epidemic goals.

Objective We sought to evaluate, which combinations of HIV prevention and care activities would have the greatest impact towards reaching the US Ending the HIV Epidemic (EHE) plan goals of HIV incidence reduction. Design A stochastic network-based HIV transmission model for men who have sex with men (MSM), calibrated to surveillance estimates in the Atlanta area, a focal EHE jurisdiction. Methods Model scenarios varied HIV screening rates under different assumptions of how HIV-negative MSM would be linked to PrEP initiation, and rates of HIV care linkage and retention for those screening positive. Results A ten-fold relative increase in HIV screening rates (to approximately biannual screening for black and Hispanic MSM and quarterly for white MSM) would lead to 43% of infections averted if integrated with PrEP initiation. Improvements focused only on black MSM would achieve nearly the same outcome (37% of infections averted). Improvements to HIV care retention would avert 41% of infections if retention rates were improved ten-fold. If both screening and retention were jointly improved ten-fold, up to 74% of cumulative infections would be averted. Under this scenario, it would take 4 years to meet the 75% EHE goal and 12 years to meet the 90% goal for Atlanta MSM. Conclusion Reaching the EHE 75% incidence reduction goals by their target dates will require immediate and substantial improvements in HIV screening, PrEP, and ART care retention. Meeting these EHE goals in target jurisdictions like Atlanta will be possible only by addressing the HIV service needs of black MSM.
Daily Activity Recognition and Assessment System for Stroke Rehabilitation

Research Objectives To test an initial algorithm for recognizing and classifying daily activities of individuals with stroke in an unstructured home environment using a depth sensor. Design This study was a developmental, iterative design, completed in three phases. Setting In Phase 1, the algorithm was trained in a kitchen. In Phase 2, the trained algorithm was tested on 5 participants data collected from natural home kitchen environments. In Phase 3, the algorithm was trained and tested in natural home kitchen environments (individuals post-stroke). Participants In Phase 1, the system was trained with 11 individuals (age 18-40) without any disabilities. In Phase 2, the trained algorithm was tested on 5 participants with and without disabilities. In Phase 3, the algorithm was trained and tested on 15 adults post-stroke. Interventions In Phase 1, each participant completed 3 sets of prescribed activities. In Phase 2, participants completed meal preparation tasks and all data were recorded by the VicoVR and the Foresite sensor.All data (depth images and skeletal data) from Phase I were used to trained the Convolutional-deconvolutional neural network (CNN). Main Outcome Measures Per-frame accuracies and per-action accuracies were calculated for all algorithm tests. Results For the mock kitchen in Phase 1, the per-frame accuracy was 85.1% and the per-action accuracy was 92.1%. In Phase 2, the per-frame accuracies ranged from 52.0% to 89.7% and the per-action accuracies ranged from 54.3% to 88.5%. Phase 3 is currently ongoing. Our current tests of the algorithm show per-frame accuracies of 51.5% to 67.3% and per-action accuracies from 55.6% to 77.9%. Conclusions The per-action and per-frame accuracies indicate that the algorithm requires further training and testing. This study is the first of its kind to develop an unobtrusive assessment of daily activity. Author(s) Disclosures Dr. Skubic holds equity in Foresite Healthcare, the company that produces the sensor used in Phases 2 and 3 of this study. Dr. Proffitt has nothing to declare. Ms. Ma has nothing to declare.
Direct laser cooling of a symmetric top molecule

Ultracold polyatomic molecules have potentially wide-ranging applications in quantum simulation and computation, particle physics, and quantum chemistry. For atoms and small molecules, direct laser cooling has proven to be a powerful tool for quantum science in the ultracold regime. However, the feasibility of laser-cooling larger, nonlinear polyatomic molecules has remained unknown because of their complex structure. We laser-cooled the symmetric top molecule calcium monomethoxide (CaOCH3), reducing the temperature of ~104 molecules from 22 ± 1 millikelvin to 1.8 ± 0.7 millikelvin in one dimension and state-selectively cooling two nuclear spin isomers. These results demonstrate that the use of proper ro-vibronic transitions enables laser cooling of nonlinear molecules, thereby opening a path to efficient cooling of chiral molecules and, eventually, optical tweezer arrays of complex polyatomic species.
Sorting an array using the topological sort of a corresponding comparison graph

Abstract The quest for efficient sorting is ongoing, and we will explore a graph-based stable sorting strategy, in particular employing comparison graphs. We use the topological sort to map the comparison graph to a linear domain, and we can manipulate our graph such that the resulting topological sort is the sorted array. By taking advantage of the many relations between Hamiltonian paths and topological sorts in comparison graphs, we design a Divide-and-Conquer algorithm that runs in the optimal O ( n log ⁡ n ) time. In the process, we construct a new merge process for graphs with relevant invariant properties for our use. Furthermore, this method is more space-efficient than the famous MergeSort since we modify our fixed graph only.
Stress-Induced Intercalation Instability

Abstract We present a linear stability analysis to demonstrate that a flat coherent phase boundary formed by the (de)intercalation of solutes into a compound is unstable against perturbations with wavelengths larger than a critical wavelength. This critical wavelength is controlled by the competition between the interface energy and the elastic strain energy caused by the misfit between the solute-rich and solute-poor phases. It increases with the distance between the phase boundary and free surface of the compound, and so the instability is most pronounced when the boundary is close to the surface at the early stage of the (de)intercalation process. Numerical calculations show that such instability leads to non-uniform intercalation behavior. We find that uniform intercalation cannot be achieved unless the phase boundary moves at a speed greater than a critical velocity. Estimate of the magnitude of this velocity suggests that the stress-induced intercalation instability is generally operative in intercalation compounds used for battery applications.
A Novel Mapping Strategy Utilizing Mouse Chromosome Substitution Strains Identifies Multiple Epistatic Interactions That Regulate Complex Traits.

The genetic contribution of additive versus non-additive (epistatic) effects in the regulation of complex traits is unclear. While genome-wide association studies typically ignore gene-gene interactions, in part because of the lack of statistical power for detecting them, mouse chromosome substitution strains (CSSs) represent an alternate approach for detecting epistasis given their limited allelic variation. Therefore, we utilized CSSs to identify and map both additive and epistatic loci that regulate a range of hematologic- and metabolism-related traits, as well as hepatic gene expression. Quantitative trait loci (QTLs) were identified using a CSS-based backcross strategy involving the segregation of variants on the A/J-derived substituted chromosomes 4 and 6 on an otherwise C57BL/6J genetic background. In the liver transcriptomes of offspring from this cross, we identified and mapped additive QTLs regulating the hepatic expression of 768 genes, and epistatic QTL pairs for 519 genes. Similarly, we identified additive QTLs for fat pad weight, platelets, and the percentage of granulocytes in blood, as well as epistatic QTL pairs controlling the percentage of lymphocytes in blood and red cell distribution width. The variance attributed to the epistatic QTL pairs was approximately equal to that of the additive QTLs; however, the SNPs in the epistatic QTL pairs that accounted for the largest variances were undetected in our single locus association analyses. These findings highlight the need to account for epistasis in association studies, and more broadly demonstrate the importance of identifying genetic interactions to understand the complete genetic architecture of complex traits.
Trade shocks and youth jobs

This paper examines the impacts of trade on youth employment in the United States. The overarching goal is to link lessons from the decline of manufacturing jobs in the past decades to future prospects for the US economy. We find higher rates of job losses with exposure to import competition for US youth, than for older workers. Our analysis uses buyer–supplier relationships between sectors of the US economy to show that the direct effects of trade on the importing sectors underrepresent the impact of trade on jobs.
Steady states of thin film droplets on chemically heterogeneous substrates

We study steady-state thin films on a chemically heterogeneous substrates of finite size, subject to no-flux boundary conditions. Based on the structure of the bifurcation diagram, we classify the one-dimensional steady-state solutions that exist on such substrates into six different branches and develop asymptotic estimates for the steady-states on each branch. We show using perturbation expansions, that leading order solutions provide good predictions of the steady-state thin films on stepwise-patterned substrates. The analysis in one dimension can be extended to axisymmetric solutions. We also examine the influence of the wettability contrast on linear stability and dynamics. Results are also applied to describe two-dimensional droplets on hydrophilic square patches and striped regions used in microfluidic applications.
Neuronal Subcompartment Classification and Merge Error Correction

Recent advances in 3d electron microscopy are yielding ever larger reconstructions of brain tissue, encompassing thousands of individual neurons interconnected by millions of synapses. Interpreting reconstructions at this scale demands advances in the automated analysis of neuronal morphologies, for example by identifying morphological and functional subcompartments within neurons. We present a method that for the first time uses full 3d input (voxels) to automatically classify reconstructed neuron fragments as axon, dendrite, or somal subcompartments. Based on 3d convolutional neural networks, this method achieves a mean f1-score of 0.972, exceeding the previous state of the art of 0.955. The resulting predictions can support multiple analysis and proofreading applications. In particular, we leverage finely localized subcompartment predictions for automated detection and correction of merge errors in the volume reconstruction, successfully detecting 90.6% of inter-class merge errors with a false positive rate of only 2.7%.
Self-generating lower bounds and continuation for the Boltzmann equation

For the spatially inhomogeneous, non-cutoff Boltzmann equation posed in the whole space $${\mathbb {R}}^3_x$$ , we establish pointwise lower bounds that appear instantaneously even if the initial data contains vacuum regions. Our lower bounds depend only on the initial data and upper bounds for the mass and energy densities of the solution. As an application, we improve the weakest known continuation criterion for large-data solutions, by removing the assumptions of mass bounded below and entropy bounded above.
Stable super-resolution limit and smallest singular value of restricted Fourier matrices

Abstract We consider the inverse problem of recovering the locations and amplitudes of a collection of point sources represented as a discrete measure, given M + 1 of its noisy low-frequency Fourier coefficients. Super-resolution refers to a stable recovery when the distance Δ between the two closest point sources is less than 1 / M . We introduce a clumps model where the point sources are closely spaced within several clumps. Under this assumption, we derive a non-asymptotic lower bound for the minimum singular value of a Vandermonde matrix whose nodes are determined by the point sources. Our estimate is given as a weighted l 2 sum, where each term only depends on the configuration of each individual clump. The main novelty is that our lower bound obtains an exact dependence on the Super-Resolution Factor S R F = ( M Δ ) − 1 . As noise level increases, the sensitivity of the noise-space correlation function in the MUSIC algorithm degrades according to a power law in SRF where the exponent depends on the cardinality of the largest clump. Numerical experiments validate our theoretical bounds for the minimum singular value and the sensitivity of MUSIC. We also provide lower and upper bounds for a min-max error of super-resolution for the grid model, which in turn is closely related to the minimum singular value of Vandermonde matrices.