cssi/SciSciGPT-SciSciNet huggingface dataset:
Multiclass Diffuse Interface Models for Semi-supervised Learning on Graphs

We present a graph-based variational algorithm for multiclass classification of high-dimensional data, motivated by total variation techniques. The energy functional is based on a diffuse interface model with a periodic potential. We augment the model by introducing an alternative measure of smoothness that preserves symmetry among the class labels. Through this modification of the standard Laplacian, we construct an efficient multiclass method that allows for sharp transitions between classes. The experimental results demonstrate that our approach is competitive with the state of the art among other graph-based algorithms.
Consensus-Based Distributed Discrete Optimal Transport for Decentralized Resource Matching

Optimal transport has been extensively used in resource matching to promote the efficiency of resource usages by matching sources to targets. However, it requires a significant amount of computations and storage spaces for large-scale problems. In this paper, we take a consensus-based approach to decentralize discrete optimal transport problems and develop fully distributed algorithms with alternating direction method of multipliers. We show that our algorithms guarantee certain levels of efficiency and privacy besides the distributed nature. We further derive primal and dual algorithms by exploring the primal and dual problems of discrete optimal transport with linear utility functions and prove the equivalence between them. We verify the convergence, online adaptability, and the equivalence between the primal algorithm and the dual algorithm with numerical experiments. Our algorithms reflect the bargaining between sources and targets on the amounts and prices of transferred resources and reveal an averaging principle which can be used to regulate resource markets and improve resource efficiency.
Applying sentinel event reviews to policing

A sentinel event review (SER) is a system-based, multistakeholder review of an organizational error. The goal of an SER is to prevent similar errors from recurring in the future rather than identifying and punishing the responsible parties. In this article, we provide a detailed description of one of the first SERs conducted in an American police department—the review of the Lex Street Massacre investigation and prosecution, which resulted in the wrongful incarceration of four innocent men for 18 months. The results of the review suggest that SERs may help identify new systemic reforms for participating police departments and other criminal justice agencies.
Admission plasma uromodulin and the risk of acute kidney injury in hospitalized patients with cirrhosis: a pilot study

In this study, we found that admission plasma uromodulin levels are significantly lower in patients who developed subsequent acute kidney injury (AKI) during their hospital stay compared with patie...
Human umbilical cord blood monocytes, but not adult blood monocytes, rescue brain cells from hypoxic-ischemic injury: Mechanistic and therapeutic implications

Cord blood (CB) mononuclear cells (MNC) are being tested in clinical trials to treat hypoxic-ischemic (HI) brain injuries. Although early results are encouraging, mechanisms underlying potential clinical benefits are not well understood. To explore these mechanisms further, we exposed mouse brain organotypic slice cultures to oxygen and glucose deprivation (OGD) and then treated the brain slices with cells from CB or adult peripheral blood (PB). We found that CB-MNCs protect neurons from OGD-induced death and reduced both microglial and astrocyte activation. PB-MNC failed to affect either outcome. The protective activities were largely mediated by factors secreted by CB-MNC, as direct cell-to-cell contact between the injured brain slices and CB cells was not essential. To determine if a specific subpopulation of CB-MNC are responsible for these protective activities, we depleted CB-MNC of various cell types and found that only removal of CB CD14+ monocytes abolished neuroprotection. We also used positively selected subpopulations of CB-MNC and PB-MNC in this assay and demonstrated that purified CB-CD14+ cells, but not CB-PB CD14+ cells, efficiently protected neuronal cells from death and reduced glial activation following OGD. Gene expression microarray analysis demonstrated that compared to PB-CD14+ monocytes, CB-CD14+ monocytes over-expressed several secreted proteins with potential to protect neurons. Differential expression of five candidate effector molecules, chitinase 3-like protein-1, inhibin-A, interleukin-10, matrix metalloproteinase-9 and thrombospondin-1, were confirmed by western blotting, and immunofluorescence. These findings suggest that CD14+ monocytes are a critical cell-type when treating HI with CB-MNC.
Facetto: Combining Unsupervised and Supervised Learning for Hierarchical Phenotype Analysis in Multi-Channel Image Data

Facetto is a scalable visual analytics application that is used to discover single-cell phenotypes in high-dimensional multi-channel microscopy images of human tumors and tissues. Such images represent the cutting edge of digital histology and promise to revolutionize how diseases such as cancer are studied, diagnosed, and treated. Highly multiplexed tissue images are complex, comprising 109 or more pixels, 60-plus channels, and millions of individual cells. This makes manual analysis challenging and error-prone. Existing automated approaches are also inadequate, in large part, because they are unable to effectively exploit the deep knowledge of human tissue biology available to anatomic pathologists. To overcome these challenges, Facetto enables a semi-automated analysis of cell types and states. It integrates unsupervised and supervised learning into the image and feature exploration process and offers tools for analytical provenance. Experts can cluster the data to discover new types of cancer and immune cells and use clustering results to train a convolutional neural network that classifies new cells accordingly. Likewise, the output of classifiers can be clustered to discover aggregate patterns and phenotype subsets. We also introduce a new hierarchical approach to keep track of analysis steps and data subsets created by users; this assists in the identification of cell types. Users can build phenotype trees and interact with the resulting hierarchical structures of both high-dimensional feature and image spaces. We report on use-cases in which domain scientists explore various large-scale fluorescence imaging datasets. We demonstrate how Facetto assists users in steering the clustering and classification process, inspecting analysis results, and gaining new scientific insights into cancer biology.
Spontaneous Self-Assembly of Amyloid β (1–40) Into Dimers

The self-assembly and fibrillation of amyloid β (Aβ) proteins is the neuropathological hallmark of Alzheimer's disease. However, the molecular mechanism of how disordered monomers assemble into aggregates remains largely unknown. In this work, we characterize the assembly of Aβ (1–40) monomers into dimers using long-time molecular dynamics simulations. Upon interaction, the monomers undergo conformational transitions, accompanied by change of the structure, leading to the formation of a stable dimer. The dimers are stabilized by interactions in the N-terminal region (residues 5–12), in the central hydrophobic region (residues 16–23), and in the C-terminal region (residues 30–40); with inter-peptide interactions focused around the N- and C-termini. The dimers do not contain long β-strands that are usually found in fibrils.
Stoichiometry, phase, and texture evolution in PLD-Grown hexagonal barium ferrite films as a function of laser process parameters

Abstract Barium hexaferrite (BaFe12O19 or BaM) films were grown on c-plane sapphire (0001) substrates by pulsed laser deposition (PLD) to evaluate the effects of laser fluence on their composition, structure, and magnetic properties. A Continuum Surelite pulsed 266 nm Nd:YAG laser was employed, and the laser fluence was varied systemically between 1 and 5.7 [J/cm2]. As the laser fluence changed the stoichiometric transfer between the BaM targets and deposited thin films were affected. The Fe to Ba ratio in the films increased with laser fluence. The films deposited at laser fluences below 4 J/cm2 showed undesirable 3-dimensional island growth. Moreover, an insufficient laser energy resulted in deposition of secondary phases corresponding to Barium monoferrite (BaFe2O4) and Magnetite (Fe3O4). Alternatively, laser fluences above 5 J/cm2 promoted resputtering of the growing film at the substrate and degraded film quality, structure, and magnetic properties. BaM films deposited at 4.8 J/cm2 - the optimal laser fluence - showed excellent c-axis orientation perpendicular to the film plane with an anisotropy field of 16 kOe and saturation magnetization of 4.39 kG. These results clearly demonstrate a strong influence of laser parameters on PLD-grown hexaferrite films and provide a path for high-yield production using pulsed laser depositions systems.
Productivity and Misallocation in General Equilibrium

We provide a general non-parametric formula for aggregating microeconomic shocks in general equilibrium economies with distortions such as taxes, markups, frictions to resource reallocation, and nominal rigidities. We show that the macroeconomic impact of a shock can be boiled down into two components: its “pure” technology effect; and its effect on allocative efficiency arising from the associated reallocation of resources, which can be measured via changes in factor income shares. We also derive a formula showing how these two components are determined by structural microeconomic parameters such as elasticities of substitution, returns to scale, factor mobility, and network linkages. Overall, our results generalize those of Solow (1957) and Hulten (1978) to economies with distortions. To demonstrate their empirical relevance, we pursue different applications, focusing on markup distortions. For example, we operationalize our non-parametric results and show that improvements in allocative efficiency account for about 50% of measured TFP growth over the period 1997-2015. We also implement our structural results and conclude that eliminating markups would raise TFP by about 40%, increasing the economywide cost of monopoly distortions by two orders of magnitude compared to the famous 0.1% estimates of Harberger (1954).
Cortical Surface Parcellation Using Spherical Convolutional Neural Networks

We present cortical surface parcellation using spherical deep convolutional neural networks. Traditional multi-atlas cortical surface parcellation requires inter-subject surface registration using geometric features with slow processing speed on a single subject (2–3 h). Moreover, even optimal surface registration does not necessarily produce optimal cortical parcellation as parcel boundaries are not fully matched to the geometric features. In this context, a choice of training features is important for accurate cortical parcellation. To utilize the networks efficiently, we propose cortical parcellation-specific input data from an irregular and complicated structure of cortical surfaces. To this end, we align ground-truth cortical parcel boundaries and use their resulting deformation fields to generate new pairs of deformed geometric features and parcellation maps. To extend the capability of the networks, we then smoothly morph cortical geometric features and parcellation maps using the intermediate deformation fields. We validate our method on 427 adult brains for 49 labels. The experimental results show that our method outperforms traditional multi-atlas and naive spherical U-Net approaches, while achieving full cortical parcellation in less than a minute.
Developing a sensor-based mobile application for in-home frailty assessment: a qualitative study

Frailty syndrome disproportionately affects older people, including 15% of non-nursing home population, and is known to be a strong predictor of poor health outcomes. There is a growing interest in incorporating frailty assessment into research and clinical practice, which may provide an opportunity to improve in home frailty assessment and improve doctor patient communication. We conducted focus groups discussions to solicit input from older adult care recipients (non-frail, pre-frail, and frail), their informal caregivers, and medical providers about their preferences to tailor a mobile app to measure frailty in the home using sensor based technologies. Focus groups were recorded, transcribed, and analyzed thematically. We identified three major themes: 1) perspectives of frailty; 2) perceptions of home based sensors; and 3) data management concerns. These relate to the participants’ insight, attitudes and concerns about having sensor-based technology to measure frailty in the home. Our qualitative findings indicate that knowing frailty status is important and useful and would allow older adults to remain independent longer. Participants also noted concerns with data management and the hope that this technology would not replace in-person visits with their healthcare provider. This study found that study participants of each frailty status expressed high interest and acceptance of sensor-based technologies. Based on the qualitative findings of this study, sensor-based technologies show promise for frailty assessment of older adults with care needs. The main concerns identified related to the volume of data collected and strategies for responsible and secure transfer, reporting, and distillation of data into useful and timely care information. Sensor-based technologies should be piloted for feasibility and utility. This will inform the larger goal of helping older adults to maintain independence while tracking potential health declines, especially among the most vulnerable, for early detection and intervention. Keywords: Frailty, wearable, health services.
Heart Failure and Diabetes Mellitus: Defining the Problem and Exploring the Interrelationship

Abstract Type 2 diabetes mellitus and congestive heart failure are highly prevalent diseases with significant morbidity and mortality. These 2 diseases often occur concurrently because of shared risk factors such as coronary artery disease, and also because type 2 diabetes mellitus has direct cardiotoxic effects. Type 2 diabetes mellitus likely has a causative role in the development and prognosis of patients with heart failure. Optimal prevention and treatment of type 2 diabetes mellitus and heart failure likely involves identifying and treating their shared pathophysiologic features. Novel drug therapies, such as sodium-glucose co-transporter 2 inhibitors, offer an exciting potential to better understand the relationship between type 2 diabetes mellitus and heart failure, and may prove to have beneficial effects on cardiovascular outcomes in patients affected by these diseases.
The Origins of Plurilateralism in International Trade Law

This draft article is forthcoming in the Journal of World Investment & Trade. The article examines the historical experience with and understanding of plurilateral trade agreements throughout the General Agreement on Tariffs and Trade (GATT) and World Trade Organization (WTO) to better contextualise assessments of the continued viability of the single undertaking and the recent resurgence of plurilateralism in international trade law. Plurilateral agreements have been playing a significant role in international trade relations for the past fifty years. As such, the current wave of plurilateral agreements does not represent a seachange in approach to trade liberalisation, but rather a continuation of a process that originated many decades ago. Further, while the WTO agreements are multilateral in thatthey apply to all members, they can also l be seen as plurilateral in that not all WTO members have identical responsibilities under such agreements. The article concludes that plurilateralism and multilateralism have much in common, and hence may be mutually supportive rather than binary choices.
CRISPR-Cas12a/Cpf1-assisted precise, efficient and multiplexed genome-editing in Yarrowia lipolytica

CRISPR-Cas9 has been widely adopted as the basic toolkit for precise genome-editing and engineering in various organisms. Alternative to Cas9, Cas12 or Cpf1 uses a simple crRNA as a guide and expands the protospacer adjacent motif (PAM) sequence to TTTN. This unique PAM sequence of Cpf1 may significantly increase the on-target editing efficiency due to lower chance of Cpf1 misreading the PAMs on a high GC genome. To demonstrate the utility of CRISPR-Cpf1, we have optimized the CRISPR-Cpf1 system and achieved high-editing efficiency for two counter-selectable markers in the industrially-relevant oleaginous yeast Yarrowia lipolytica: arginine permease (93% for CAN1) and orotidine 5'-phosphate decarboxylase (~96% for URA3). Both mutations were validated by indel mutation sequencing. For the first time, we further expanded this toolkit to edit three sulfur house-keeping genetic markers (40%-75% for MET2, MET6 and MET25), which confers yeast distinct colony color changes due to the formation of PbS (lead sulfide) precipitates. Different from Cas9, we demonstrated that the crRNA transcribed from a standard type II RNA promoter was sufficient to guide Cpf1 endonuclease activity. Furthermore, modification of the crRNA with 3' polyUs facilitates the faster maturation and folding of crRNA and improve the genome editing efficiency. We also achieved multiplexed genome editing, and the editing efficiency reached 75%-83% for duplex genomic targets (CAN1-URA3 and CAN1-MET25) and 41.7% for triplex genomic targets (CAN1-URA3-MET25). Taken together, this work expands the genome-editing toolbox for oleaginous yeast species and may accelerate our ability to engineer oleaginous yeast for both biotechnological and biomedical applications.
Distributive laws in residuated binars

In residuated binars there are six non-obvious distributivity identities of $$\cdot ,/,\backslash $$ over $$\wedge , \vee $$. We show that in residuated binars with distributive lattice reducts there are some dependencies among these identities; specifically, there are six pairs of identities that imply another one of these identities, and we provide counterexamples to show that no other dependencies exist among these.
Stress-Plus-X (SPX) graph layout

Stress, edge crossings, and crossing angles play an important role in the quality and readability of graph drawings. Most standard graph drawing algorithms optimize one of these criteria which may lead to layouts that are deficient in other criteria. We introduce an optimization framework, Stress-Plus-X (SPX), that simultaneously optimizes stress together with several other criteria: edge crossings, minimum crossing angle, and upwardness (for directed acyclic graphs). SPX achieves results that are close to the state-of-the-art algorithms that optimize these metrics individually. SPX is flexible and extensible and can optimize a subset or all of these criteria simultaneously. Our experimental analysis shows that our joint optimization approach is successful in drawing graphs with good performance across readability criteria.
Minimum Earnings Regulation and the Stability of Marketplaces

We build a model to study the implications of utilization-based minimum earning regulations of the kind recently enacted by New York City for its ride-hailing providers. We identify the precise conditions under which a utilization-based minimum earnings rule causes marketplace instability, where stability is defined as the ability of platforms to keep wages bounded while maintaining the current flexible (free-entry) work model. We also calibrate our model using publicly available data, showing the limited power of the law to increase earnings within an open marketplace. We argue that affected ride-hailing companies might respond to the law by reducing driver flexibility.
Algorithms for efficiently collapsing reads with Unique Molecular Identifiers.

Background Unique Molecular Identifiers (UMI) are used in many experiments to find and remove PCR duplicates. There are many tools for solving the problem of deduplicating reads based on their finding reads with the same alignment coordinates and UMIs. However, many tools either cannot handle substitution errors, or require expensive pairwise UMI comparisons that do not efficiently scale to larger datasets. Results We reformulate the problem of deduplicating UMIs in a manner that enables optimizations to be made, and more efficient data structures to be used. We implement our data structures and optimizations in a tool called UMICollapse, which is able to deduplicate over one million unique UMIs of length 9 at a single alignment position in around 26 s, using only a single thread and much less than 10 GB of memory. Conclusions We present a new formulation of the UMI deduplication problem, and show that it can be solved faster, with more sophisticated data structures.
Solving \((k-1)\)-Stable Instances of k-terminal cut with Isolating Cuts

The k-terminal cut problem, also known as the Multiway Cut problem, is defined on an edge-weighted graph with k distinct vertices called “terminals.” The goal is to remove a minimum weight collection of edges from the graph such that there is no path between any pair of terminals. The problem is NP-hard.
Existential copyright and professional photography

Intellectual property law has intended benefits, but it also carries certain costs — deliberately so. Skeptics have asked: Why should intellectual property law exist at all? To get traction on that overly broad but still important inquiry, we decided to ask a new, preliminary question: What do creators in a particular industry actually use intellectual property for? In this first-of-its-kind study, we conducted thirty-two in-depth qualitative interviews of photographers about how copyright law functions within their creative and business practices. By learning the actual functions of copyright law on the ground, we can evaluate and contextualize existing theories of intellectual property. More importantly, our data call for an expansion of the set of possible justifications for intellectual property. Contrary to accepted wisdom, we find that copyright provides photographers with economic leverage in up-front negotiations with clients but not much benefit in anticopying protection afterwards. Beyond that, copyright also serves as part of photographers’ multifaceted sense of professionalism to protect the integrity of their art and business. Identifying these unrecognized and surprising functions of copyright in creators’ accounts is separate from evaluating their desirability. But we argue that the real-world functions of copyright are better candidates for justification and better subjects for policy discussion than chalkboard theories. In this way, our study of photographers moves the longstanding debate over intellectual property law’s purpose to a new and more informed place.
Pediatrics in Review: Questions for the 41st Year

1. Joseph A. Zenel, MD*,† 1. * Editor-in-Chief , Pediatrics in Review 2. †Sanford Children's Hospital, The Sanford School of Medicine, University of South Dakota, Sioux Falls, SD PIR is now in its 41st year. After last year’s publication of commentaries, blogs, and a supplement devoted to celebrating the past 40 years of the journal, what should PIR ’s next step be? Twenty years ago, the Accreditation Council for Graduate Medical Education described 6 core competencies in which practicing physicians should be skilled. One of those competencies is practice-based learning and improvement. At the end of PIR ’s inaugural year, forward-thinking founding editor Dr Robert Haggerty, intent on improving the journal, reflected on readers’ remarks. (1) Readers gave generally positive comments, and most readers appreciated the mix of review articles and abstracts of current studies. However, some just wanted new material, others solely the basics of standard general practice, and a few simply controversial topics. …
MeteorNet: Deep Learning on Dynamic 3D Point Cloud Sequences

Understanding dynamic 3D environment is crucial for robotic agents and many other applications. We propose a novel neural network architecture called MeteorNet for learning representations for dynamic 3D point cloud sequences. Different from previous work that adopts a grid-based representation and applies 3D or 4D convolutions, our network directly processes point clouds. We propose two ways to construct spatiotemporal neighborhoods for each point in the point cloud sequence. Information from these neighborhoods is aggregated to learn features per point. We benchmark our network on a variety of 3D recognition tasks including action recognition, semantic segmentation and scene flow estimation. MeteorNet shows stronger performance than previous grid-based methods while achieving state-of-the-art performance on Synthia. MeteorNet also outperforms previous baseline methods that are able to process at most two consecutive point clouds. To the best of our knowledge, this is the first work on deep learning for dynamic raw point cloud sequences.
Thiopeptide Defense by an Ant’s Bacterial Symbiont

Fungus-growing ants and their microbial symbionts have emerged as a model system for understanding antibiotic deployment in an ecological context. Here we establish that bacterial symbionts of the ant Trachymyrmex septentrionalis antagonize their most likely competitors, other strains of ant-associated bacteria, using the thiopeptide antibiotic GE37468. Genomic analysis suggests that these symbionts acquired the GE37468 gene cluster from soil bacteria. This antibiotic, with known activity against human pathogens, was previously identified in a biochemical screen but had no known ecological role. GE37468's host-associated defense role in this insect niche intriguingly parallels the function of similar thiopeptides in the human microbiome.
Profiling APOL1 Nephropathy Risk Variants in Genome-Edited Kidney Organoids with Single-Cell Transcriptomics.

Background DNA variants in APOL1 associate with kidney disease, but the pathophysiologic mechanisms remain incompletely understood. Model organisms lack the APOL1 gene, limiting the degree to which disease states can be recapitulated. Here we present single-cell RNA sequencing (scRNA-seq) of genome-edited human kidney organoids as a platform for profiling effects of APOL1 risk variants in diverse nephron cell types. Methods We performed footprint-free CRISPR-Cas9 genome editing of human induced pluripotent stem cells (iPSCs) to knock in APOL1 high-risk G1 variants at the native genomic locus. iPSCs were differentiated into kidney organoids, treated with vehicle, IFN-γ, or the combination of IFN-γ and tunicamycin, and analyzed with scRNA-seq to profile cell-specific changes in differential gene expression patterns, compared with isogenic G0 controls. Results Both G0 and G1 iPSCs differentiated into kidney organoids containing nephron-like structures with glomerular epithelial cells, proximal tubules, distal tubules, and endothelial cells. Organoids expressed detectable APOL1 only after exposure to IFN-γ. scRNA-seq revealed cell type–specific differences in G1 organoid response to APOL1 induction. Additional stress of tunicamycin exposure led to increased glomerular epithelial cell dedifferentiation in G1 organoids. Conclusions Single-cell transcriptomic profiling of human genome-edited kidney organoids expressing APOL1 risk variants provides a novel platform for studying the pathophysiology of APOL1-mediated kidney disease.
Sensor Placement Strategies for Some Classes of Nonlinear Dynamic Systems via Lyapunov Theory

In this paper, the problem of placing sensors for some classes of nonlinear dynamic systems (NDS) is investigated. In conjunction with mixed-integer programming, classical Lyapunov-based arguments are used to find the minimal sensor configuration such that the NDS internal states can be observed while still optimizing some estimation metrics. The paper’s approach is based on two phases. The first phase assumes that the encompassed nonlinearities belong to one of the following function set classifications: bounded Jacobian, Lipschitz continuous, one-sided Lipschitz, or quadratically inner-bounded. To parameterize these classifications, two approaches based on stochastic point-based and interval-based optimization methods are explored. Given the parameterization, the second phase formulates the sensor placement problem for various NDS classes through mixed-integer convex programming. The theoretical optimality of the sensor placement alongside a state estimator design are then given. Numerical tests on traffic network models showcase that the proposed approach yields sensor placements that are consistent with conventional wisdom in traffic theory.
Soft Prototyping Camera Designs for Car Detection Based on a Convolutional Neural Network

Imaging systems are increasingly used as input to convolutional neural networks (CNN) for object detection; we would like to design cameras that are optimized for this purpose. It is impractical to build different cameras and then acquire and label the necessary data for every potential camera design; creating software simulations of the camera in context (soft prototyping) is the only realistic approach. We implemented soft-prototyping tools that can quantitatively simulate image radiance and camera designs to create realistic images that are input to a convolutional neural network for car detection. We used these methods to quantify the effect that critical hardware components (pixel size), sensor control (exposure algorithms) and image processing (gamma and demosaicing algorithms) have upon average precision of car detection. We quantify (a) the relationship between pixel size and the ability to detect cars at different distances, (b) the penalty for choosing a poor exposure duration, and (c) the ability of the CNN to perform car detection for a variety of post-acquisition processing algorithms. These results show that the optimal choices for car detection are not constrained by the same metrics used for image quality in consumer photography. It is better to evaluate camera designs for CNN applications using soft prototyping with task-specific metrics rather than consumer photography metrics.
State Agency Discretion and Entrepreneurship in Regulated Markets

Barriers to entry in regulated markets are frequently conceptualized as static features that must be removed or overcome if new entrants are to successfully enter a market. But government instituti...
Lensing corrections on galaxy-lensing cross correlations and galaxy-galaxy auto correlations

We study the impact of lensing corrections on modeling cross correlations between CMB lensing and galaxies, cosmic shear and galaxies, and galaxies in different redshift bins. Estimating the importance of these corrections becomes necessary in the light of anticipated high-accuracy measurements of these observables. While higher order lensing corrections (sometimes also referred to as post Born corrections) have been shown to be negligibly small for lensing auto correlations, they have not been studied for cross correlations. We evaluate the contributing four-point functions without making use of the Limber approximation and compute line-of-sight integrals with the numerically stable and fast FFTlog formalism. We find that the relative size of lensing corrections depends on the respective redshift distributions of the lensing sources and galaxies, but that they are generally small for high signal-to-noise correlations. We point out that a full assessment and judgement of the importance of these corrections requires the inclusion of lensing Jacobian terms on the galaxy side. We identify these additional correction terms, but do not evaluate them due to their large number. We argue that they could be potentially important and suggest that their size should be measured in the future with ray-traced simulations. We make our code publicly available under https://github.com/VMBoehm/lensing-corrections [1].
Managing Expectations: Instruments vs. Targets

Should policymakers offer forward guidance in terms of a path for an instrument such as interest rates or a target for an outcome such as unemployment? We study how the optimal approach depends on a departure from rational expectations. People have a limited understanding of the behavior of others and of the general equilibrium (GE) effects of policy. The bite of such bounded rationality on implementability and welfare is minimized by target-based guidance if and only if GE feedbacks are strong enough. This offers a rationale for why central banks should shine the spotlight on unemployment when faced with a prolonged liquidity trap, a steep Keynesian cross, or a large financial accelerator.
Robot assisted laparoscopic partial nephrectomy: A viable and safe option in children

Purpose: The safety, benefits and usefulness of laparoscopic partial nephrectomy have been demonstrated in the pediatric population. We describe our technique, and determine the safety and feasibility of robot assisted laparoscopic partial nephrectomy based on our initial experience.Materials and Methods: We retrospectively reviewed robot assisted laparoscopic partial nephrectomy performed at our institution between 2002 and 2005. The technique was conducted via a transperitoneal approach with the da Vinci® Surgical System using standard laparoscopic procedural steps. Clinical indicators of outcomes included estimated blood loss, complications, in hospital narcotic use and length of stay.Results: Robot assisted laparoscopic partial nephrectomy was completed successfully in 9 cases. Mean patient age was 7.2 years and mean followup was 6 months. Mean operative time was 275 minutes and mean estimated blood loss was 49 ml. Operative times improved significantly with experience. Overall patients had a mean hos...
Materials That Make Robots Smart

We posit that embodied artificial intelligence is not only a computational, but also a materials problem. While the importance of material and structural properties in the control loop are well understood, materials can take an active role during control by tight integration of sensors, actuators, computation and communication. We envision such materials to abstract functionality, therefore making the construction of intelligent robots more straightforward and robust. For example, robots could be made of bones that measure load, muscles that move, skin that provides the robot with information about the kind and location of tactile sensations ranging from pressure, to texture and damage, eyes that extract high-level information, and brain material that provides computation in a scalable manner. Such materials will not resemble any existing engineered materials, but rather the heterogeneous components out of which their natural counterparts are made. We describe the state-of-the-art in so-called “robotic materials,” their opportunities for revolutionizing applications ranging from manipulation to autonomous driving, and open challenges the robotics community needs to address in collaboration with allies, such as wireless sensor network researchers and polymer scientists.
Business Cycle Fluctuations and the Life Cycle: How Important is On-The-Job Skill Accumulation?

Abstract We study the effects of on-the-job skill accumulation on average hours worked by age and the volatility of hours over the life cycle in a calibrated general equilibrium model. Two forms of skill accumulation are considered: learning by doing and on-the-job training. In our economy with learning by doing, individuals supply more labor early in the life cycle and less as they approach retirement than they do in an economy without this feature. The impact of this feature on the volatility of hours over the life cycle depends on the value of the intertemporal elasticity of labor supply. When individuals accumulate skills by on-the-job training, there are only weak effects on both the steady-state labor supply and its volatility over the life cycle.
Chapter 5 – Photochemistry of Photosynthesis

Publisher Summary Photosynthesis is composed of many individual steps that work together with high overall efficiency. The process can be divided three stages: the photochemical steps, electron transfer to which is coupled ATP formation, and the biochemical reactions involving the incorporation of CO2 into carbohydrates. This chapter concerns primarily the first stage; however the second stage is also dealt with. The photochemical reactions, which are often referred to as the primary events of photosynthesis, lead to electron transfer along a sequence of molecules, resulting in the formation of NADPH and ATP. Photosynthesis is an extremely efficient energy conversion process considering all of the steps that are involved, each with its inherent energy loss. Nearly all of the enzymes involved in the synthetic reactions of photosynthesis are also found in nonphotosynthetic tissue. Therefore, the unique feature of photosynthesis is the conversion of radiant energy into chemical energy. This chapter emphasizes the light absorption and the excitation transfer aspects of photosynthesis, including the times of the various steps and the historical events involved in elucidating the properties of the two photosystems. It considers the structures and the absorption characteristics of the photosynthetic pigments and the means by which radiant energy is trapped, transferred, and eventually used. Thus, the emphasis is on the photo part of photosynthesis.
Probability of Pilot Interference in Pulsed Radar-Cellular Coexistence: Fundamental Insights on Demodulation and Limited CSI Feedback

This letter considers an underlay pulsed radar-cellular spectrum sharing scenario, where the cellular system uses pilot-aided demodulation, statistical channel state information (S-CSI) estimation and limited feedback schemes. Under a realistic system model, upper and lower bounds are derived on the probability that at least a specified number of pilot signals are interfered by a radar pulse train in a finite CSI estimation window . Exact probabilities are also derived for important special cases which reveal operational regimes where the lower bound is achieved. Using these results, this letter (a) provides insights on pilot interference-minimizing schemes for accurate coherent symbol demodulation, and (b) demonstrates that pilot-aided methods fail to accurately estimate S-CSI of the pulsed radar interference channel for a wide range of radar repetition intervals.
Low regularity solutions for gravity water waves II: The 2D case

The gravity water waves equations describe the evolution of the surface of an incompressible, irrotational fluid in the presence of gravity. The classical regularity threshold for the well-posedness of this system requires initial velocity field in $$H^s$$, with $$s > \frac{1}{2}+ 1$$, and can be obtained by proving standard energy estimates. This threshold was improved by additionally proving Strichartz estimates with loss. In this article, we establish the well-posedness result for $$s > \frac{1}{2}+ 1 - \frac{1}{8}$$, corresponding to proving lossless Strichartz estimates. This provides the sharp regularity threshold with respect to the approach of combining Strichartz estimates with energy estimates.
Assessment of Brain Glucose Metabolism Following Cardiac Arrest by [18F]FDG Positron Emission Tomography

Cardiac arrest (CA) patients who survived by cardiopulmonary resuscitation (CPR) can present different levels of neurological deficits ranging from minor cognitive impairments to persistent vegetative state and brain death. The pathophysiology of the resulting brain injury is poorly understood, and whether changes in post-CA brain metabolism contribute to the injury are unknown. Here we utilized [18F]fluorodeoxyglucose (FDG)-Positron emission tomography (PET) to study in vivo cerebral glucose metabolism 72 h following CA in a murine CA model. Anesthetized and ventilated adult C57BL/6 mice underwent 12-min KCl-induced CA followed by CPR. Seventy-two hours following CA, surviving mice were intraperitoneally injected with [18F]FDG (~ 186 µCi/200 µL) and imaged on Molecubes preclinical micro-PET/computed tomography (CT) imaging systems after a 30-min awake uptake period. Brain [18F]FDG uptake was determined by the VivoQuant software on fused PET/CT images with the 3D brain atlas. Upon completion of Positron emission tomography (PET) imaging, remaining [18F]FDG radioactivity in the brain, heart, and liver was determined using a gamma counter. Global increases in brain [18F]FDG uptake in post-CA mice were observed compared to shams and controls. The median standardized uptake value of [18F]FDG for CA animals was 1.79 versus sham 1.25 (p < 0.05) and control animals 0.78 (p < 0.01). This increased uptake was consistent throughout the 60-min imaging period and across all brain regions reaching statistical significance in the midbrain, pons, and medulla. Biodistribution analyses of various key organs yielded similar observations that the median [18F]FDG uptake for brain was 7.04%ID/g tissue for CA mice versus 5.537%ID/g tissue for sham animals, p < 0.05). This study has successfully applied [18F]FDG-PET/CT to measure changes in brain metabolism in a murine model of asystolic CA. Our results demonstrate increased [18F]FDG uptake in the brain 72 h following CA, suggesting increased metabolic demand in the case of severe neurological injury. Further study is warranted to determine the etiology of these changes.
Spectral models of AM Her stars

Most of the optical light from AM Her systems is cyclotron radiation. Simple models for the spectrum and polarization are successful for some systems, but in others the spectrum rolls over more gently at high frequencies and is polarized over a wider range of frequencies than the models predict. This paper considers the emission from both the sides and top of the accretion column and the effects of oscillations in the shock height. These features lead to a slower roll over at high frequencies than is found in the simple models, but it is still not as flat as in some of the AM Her systems.
Consistent Bayesian sparsity selection for high-dimensional Gaussian DAG models with multiplicative and beta-mixture priors

Abstract Estimation of the covariance matrix for high-dimensional multivariate datasets is a challenging and important problem in modern statistics. In this paper, we focus on high-dimensional Gaussian DAG models where sparsity is induced on the Cholesky factor L of the inverse covariance matrix. In recent work, (Cao et al., 2019), we established high-dimensional sparsity selection consistency for a hierarchical Bayesian DAG model, where an Erdos–Renyi prior is placed on the sparsity pattern in the Cholesky factor L , and a DAG-Wishart prior is placed on the resulting non-zero Cholesky entries. In this paper we significantly improve and extend this work, by (a) considering more diverse and effective priors on the sparsity pattern in L , namely the beta-mixture prior and the multiplicative prior, and (b) establishing sparsity selection consistency under significantly relaxed conditions on p , and the sparsity pattern of the true model. We demonstrate the validity of our theoretical results via numerical simulations, and also use further simulations to demonstrate that our sparsity selection approach is competitive with existing state-of-the-art methods including both frequentist and Bayesian approaches in various settings.
UW-SVC: Scalable Video Coding Transmission for In-Network Underwater Imagery Analysis

Underwater imagery has enabled numerous civilian applications in various domains, ranging from academia to industry, and from industrial surveillance and maintenance to environmental protection and behavior of marine creatures studies. The accumulation of litter and plastic debris at the seafloor and the bottom of rivers are extremely harmful for the aquatic life. We propose a solution for monitoring this problem using a team of Autonomous Underwater Vehicles (AUVs) to exchange the recorded video in order to reconstruct the map of regions of interest. However, underwater video transmission is a challenge in the harsh environment in which radio-frequency waves are absorbed for distances above a few tens of meters, optical waves require narrow laser beams and suffer from scattering and ocean wave motion, and acoustic waves-while long range-provide a very low bandwidth and unreliable channel for communication. In our solution, the scalable coded video of each vehicle is shared in-network with a selected group of receiving vehicles through the underwater acoustic channel. Presented evaluations, including both simulations and experiments, confirm the efficiency and flexibility of the proposed solution using acoustic software-defined modems.
Preventing Financial Crises: An International Perspective

In recent years, the possibility of an international financial crisis has increased because of greater liquidity of international financial markets, an increase in corporate indebtedness, and the decline of the banking industry. Using an asymmetric information analysis, this paper outlines what signals a central bank might look for to determine if a financial crisis is occurring and then describes how central banks might operate and cooperate to prevent financial crises. Copyright 1994 by Blackwell Publishers Ltd and The Victoria University of Manchester
Revisiting Pattern Avoidance and Quasisymmetric Functions

Let $${{\mathfrak {S}}}_n$$ be the nth symmetric group. Given a set of permutations $$\Pi $$, we denote by $${{\mathfrak {S}}}_n(\Pi )$$ the set of permutations in $${{\mathfrak {S}}}_n$$ which avoid $$\Pi $$ in the sense of pattern avoidance. Consider the generating function $$Q_n(\Pi )=\sum _\sigma F_{{{\,\mathrm{Des}\,}}\sigma }$$ where the sum is over all $$\sigma \in {{\mathfrak {S}}}_n(\Pi )$$ and $$F_{{{\,\mathrm{Des}\,}}\sigma }$$ is the fundamental quasisymmetric function corresponding to the descent set of $$\sigma $$. Hamaker, Pawlowski, and Sagan introduced $$Q_n(\Pi )$$ and studied its properties, in particular, finding criteria for when this quasisymmetric function is symmetric or even Schur nonnegative for all $$n\ge 0$$. The purpose of this paper is to continue their investigation by answering some of their questions, proving one of their conjectures, as well as considering other natural questions about $$Q_n(\Pi )$$. In particular, we look at $$\Pi $$ of small cardinality, superstandard hooks, partial shuffles, Knuth classes, and a stability property.
Absorptive loss and band non-parabolicity as a physical origin of large nonlinearity in epsilon-near-zero materials

For decades, nonlinear optics has been used to control the frequency and propagation of light in unique ways enabling a wide range of applications such as ultrafast lasing, sub-wavelength imaging, and novel sensing methods. Through this, a key thread of research in the field has always been the development of new and improved nonlinear materials to empower these applications. Recently, epsilon-near-zero (ENZ) materials have emerged as a potential platform to enhanced nonlinear interactions, bolstered in large part due to the extreme refractive index tuning (Δn∼ 0.1 - 1) of sub-micron thick films that has been demonstrated in literature. Despite this experimental success, the theory has lagged and is needed to guide future experimental efforts. Here, we construct a theoretical framework for the intensity-dependent refractive index of the most popular ENZ materials, heavily doped semiconductors. We demonstrate that the nonlinearity when excited below bandgap, is due to the modification of the effective mass of the electron sea which produces a shift in the plasma frequency. We discuss trends and trade-offs in the optimization of excitation conditions and material choice (such material loss, band structure, and index dispersion), and provide a figure of merit through which the performance of future materials may be evaluated. By illuminating the framework of the nonlinearity, we hope to propel future applications in this growing field.