cssi/SciSciGPT-SciSciNet huggingface dataset:
DRDr II: Detecting the Severity Level of Diabetic Retinopathy Using Mask RCNN and Transfer Learning

DRDr II is a hybrid of machine learning and deep learning worlds. It builds on the successes of its antecedent, namely, DRDr, that was trained to detect, locate, and create segmentation masks for two types of lesions (exudates and microaneurysms) that can be found in the eyes of the Diabetic Retinopathy (DR) patients; and uses the entire model as a solid feature extractor in the core of its pipeline to detect the severity level of the DR cases. We employ a big dataset with over 35 thousand fundus images collected from around the globe and after 2 phases of preprocessing alongside feature extraction, we succeed in predicting the correct severity levels with over 92% accuracy.
Recurrent Neural Networks for Hierarchically Mapping Human-Robot Poses

To perform many critical manipulation tasks successfully, human-robot mimicking systems should not only accurately copy the position of a human hand, but its orientation as well. Deep learning methods trained from pairs of corresponding human and robot poses offer one promising approach for constructing a human-robot mapping to accomplish this. However, ignoring the spatial and temporal structure of this mapping makes learning it less effective. We propose two different hierarchical architectures that leverage the structural and temporal human-robot mapping. We partially separate the robotic manipulator's end-effector position and orientation while considering the mutual coupling effects between them. This divides the main problem-making the robot match the human's hand position and mimic its orientation accurately along an unknown trajectory-into several sub-problems. We address these using different recurrent neural networks (RNNs) with Long-Short Term Memory (LSTM) that we combine and train hierarchically based on the coupling over the aspects of the robot that each controls. We evaluate our proposed architectures using a virtual reality system to track human table tennis motions and compare with single artificial neural network (ANN) and RNN models. We compare the benefits of using deep learning neural networks with and without our architectures and find smaller errors in position and orientation, along with increased flexibility in wrist movement are obtained by our proposed architectures.
Packing and Covering Immersions in 4-Edge-Connected Graphs

Abstract A graph G contains another graph H as an immersion if H can be obtained from a subgraph of G by splitting off edges and removing isolated vertices. In this paper, we prove an edge-variant of the Erdős-Posa property with respect to the immersion containment in 4-edge-connected graphs. More precisely, we prove that for every graph H, there exists a function f such that for every 4-edge-connected graph G, either G contains k pairwise edge-disjoint subgraphs each containing H as an immersion, or there exists a set of at most f ( k ) edges of G intersecting all such subgraphs. This theorem is best possible in the sense that the 4-edge-connectivity cannot be replaced by the 3-edge-connectivity.
Full Gradient Solution to Adaptive Hybrid Control

This paper focuses on the adaptation mechanisms in adaptive hybrid controllers. Most adaptive hybrid controllers update two filters individually according to the filtered reference least mean squares (FxLMS) algorithm. Because this algorithm was derived for feedforward control, it does not take into account the presence of a feedback loop in the gradient calculation. This paper provides a derivation of the proper weight vector gradient for hybrid (or feedback) controllers that takes into account the presence of feedback. In this formulation, a single weight vector is updated rather than two individually. An internal model structure is assumed for the feedback part of the controller. The full gradient is equivalent to that used in the standard FxLMS algorithm with the addition of a recursive term that is a function of the modeling error. Some simulations are provided to highlight the advantages of using the full gradient in the weight vector update rather than the approximation.
ViP-DeepLab: Learning Visual Perception with Depth-aware Video Panoptic Segmentation

In this paper, we present ViP-DeepLab, a unified model attempting to tackle the long-standing and challenging inverse projection problem in vision, which we model as restoring the point clouds from perspective image sequences while providing each point with instance-level semantic interpretations. Solving this problem requires the vision models to predict the spatial location, semantic class, and temporally consistent instance label for each 3D point. ViP-DeepLab approaches it by jointly performing monocular depth estimation and video panoptic segmentation. We name this joint task as Depth-aware Video Panoptic Segmentation, and propose a new evaluation metric along with two derived datasets for it, which will be made available to the public. On the individual sub-tasks, ViP-DeepLab also achieves state-of-the-art results, outperforming previous methods by 5.1% VPQ on Cityscapes-VPS, ranking 1st on the KITTI monocular depth estimation benchmark, and 1st on KITTI MOTS pedestrian. The datasets and the evaluation codes are made publicly available1.
Expression of Human ACE2 N-terminal Domain, Part of the Receptor for SARS-CoV-2, in Fusion With Maltose-Binding Protein, E. coli Ribonuclease I and Human RNase A

The SARS-CoV-2 viral genome contains a positive-strand single-stranded RNA of ∼30 kb. Human ACE2 protein is the receptor for SARS-CoV-2 virus attachment and infection. We propose to use ribonucleases (RNases) as antiviral agents to destroy the viral genome in vitro. In the virions, the RNA is protected by viral capsid proteins, membrane proteins, and nucleocapsid proteins. To utilize RNases as antiviral strategy, we set out to construct RNase fusion with human ACE2 receptor N-terminal domain (ACE2NTD). We expressed six proteins in E. coli cells: (1) MBP-ACE2NTD, (2) ACE2NTD-GFP, (3) RNase I (6×His), (4) RNase III (6×His), (5) RNase I-ACE2NTD (6×His), and (6) human RNase A-ACE2NTD (6×His). We evaluated fusion expression in different E. coli strains, partially purified MBP-ACE2NTD protein from the soluble fraction of bacterial cell lysate, and refolded MBP-ACE2NTD protein from inclusion body. The engineered RNase I-ACE2NTD (6×His) and hRNase A-ACE2NTD (6×His) fusions are active in cleaving SARS-CoV-2 RNA fragment in vitro. The recombinant RNase I (6×His) and RNase III (6×His) are active in cleaving RNA and dsRNA in test tube. This study provides a proof-of-concept for construction of fusion protein between human receptor and nuclease that may be used to degrade viral nucleic acids.
EMBED: A Low Dimensional Reconstruction of Gut Microbiome Dynamics Based on Ecological Normal Modes

The gut microbiome is well-established to be a significant driver of host health and disease. Longitudinal studies involving high-throughput sequencing technologies have begun to unravel the complex dynamics of these ecosystems, and quantitative frameworks are now being developed to better understand their organizing principles. Dimensionality reduction can offer unique insights into gut bacterial dynamics by leveraging collective abundance fluctuations of multiple bacteria driven by similar underlying ecological factors. However, methods providing lower-dimensional representations of gut microbial dynamics both at the community and individual taxa level are currently missing. To that end, we develop EMBED: Essential Microbiome Dynamics. Similar to normal modes in structural biology, EMBED infers ecological normal modes (ECNs), which represent the unique set of orthogonal dynamical trajectories capturing the collective behavior of a community. We show that a small number of ECNs accurately describe gut microbiome dynamics across data sets that encompass dietary changes and antibiotic-related perturbations. Importantly, we find that ECNs often reflect specific ecological behaviors, providing natural templates along which the dynamics of individual bacteria may be partitioned. Collectively, our results highlight the utility of dimensionality reduction approaches to understanding the dynamics of the gut microbiome and provide a framework to study the dynamics of other high-dimensional systems as well.
Hospital admissions from care homes in England during the COVID-19 pandemic: a retrospective, cross-sectional analysis using linked administrative data

Background Care home residents have complex healthcare needs but may have faced barriers to accessing hospital treatment during the first wave of the COVID-19 pandemic. Objectives To examine trends in the number of hospital admissions for care home residents during the first months of the COVID-19 outbreak. Methods Retrospective analysis of a national linked dataset on hospital admissions for residential and nursing home residents in England (257,843 residents, 45% in nursing homes) between 20 January 2020 and 28 June 2020, compared to admissions during the corresponding period in 2019 (252,432 residents, 45% in nursing homes). Elective and emergency admission rates, normalised to the time spent in care homes across all residents, were derived across the first three months of the pandemic between 1 March and 31 May 2020 and primary admission reasons for this period were compared across years. Results Hospital admission rates rapidly declined during early March 2020 and remained substantially lower than in 2019 until the end of June. Between March and May, 2,960 admissions from residential homes (16.2%) and 3,295 admissions from nursing homes (23.7%) were for suspected or confirmed COVID-19. Rates of other emergency admissions decreased by 36% for residential and by 38% for nursing home residents (13,191 fewer admissions in total). Emergency admissions for acute coronary syndromes fell by 43% and 29% (105 fewer admission) and emergency admissions for stroke fell by 17% and 25% (128 fewer admissions) for residential and nursing home residents, respectively. Elective admission rates declined by 64% for residential and by 61% for nursing home residents (3,762 fewer admissions). Conclusions This is the first study showing that care home residents' hospital use declined during the first wave of COVID-19, potentially resulting in substantial unmet health need that will need to be addressed alongside ongoing pressures from COVID-19.
Tidal breakup of the nucleus of Comet Shoemaker-Levy 9

The breakup of Comet Shoemaker-Levy 9 is discussed both in the context of splitting as a cometary phenomenon, comparing this object with other split comets, and as an event with its own idiosyncrasies. The physical appearance of the comet is described, features diagnostic of the nature of tidal splitting are identified, and the implications for modelling the event are spelled out. Among the emphasized issues is the problem of secondary fragmentation, which documents the comet's continuing disintegration during 1992-94 and implies that in July 1992 the parent object split tidally near Jupiter into 10-12, not 21, major fragments. Also addressed are the controversies involving models of a strengthless agglomerate versus a discrete cohesive mass and estimates for the sizes of the progenitor and its fragments.
Stochastic modeling of scientific impact

Recent research has found that select scientists have a disproportional share of highly cited papers. Researchers reasoned that this could not have happened if success in science was random and introduced a hidden parameter Q , or talent, to explain this finding. So, the talented high-Q scientists have many high-impact papers. Here I show that an upgrade of an old random citation copying model could also explain this finding. In the new model the probability of citation copying is not the same for all papers but is proportional to the logarithm of the total number of citations to all papers of its author. Numerical simulations of the model give results similar to the empirical findings of the Q -factor article.
Characteristics and Challenges of Cuban Freemasons in the twentieth century. A demographic approach

We present a statistical and historical analysis of the development of the Grand Lodge of Cuba during 1945–2010, based on our demographic study of this institution. Research identifies and evaluates important factors that have contributed to membership growth and decline, in the second half of the 20th Century. Important characteristics of this institution are identified and discussed, as they relate to the development of the evolving Cuban civil society.
Examining the examiners: Students' privacy and security perceptions of online proctoring services

In response to the Covid-19 pandemic, educational institutions quickly transitioned to remote learning. The problem of how to perform student assessment in an online environment has become increasingly relevant, leading many institutions and educators to turn to online proctoring services to administer remote exams. These services employ various student monitoring methods to curb cheating, including restricted (“lockdown”) browser modes, video/screen monitoring, local network traffic analysis, and eye tracking. In this paper, we explore the security and privacy perceptions of the student test-takers being proctored. We analyze user reviews of proctoring services' browser extensions and subsequently perform an online survey (n = 102). Our findings indicate that participants are concerned about both the amount and the personal nature of the information shared with the exam proctoring companies. However, many participants also recognize a trade-off between pandemic safety concerns and the arguably invasive means by which proctoring services ensure exam integrity. Our findings also suggest that institutional power dynamics and students' trust in their institutions may dissuade students' opposition to remote proctoring. © is held by the author/owner. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee. USENIX Symposium on Usable Privacy and Security (SOUPS) 2021.
Plasma Fluctuations in a Kaufman Thruster

Measurements of the RMS magnitude, spectra, and cross correlations for the fluctuations in the beam, discharge, and neutralizer keeper currents are presented for a 30 cm diameter dished grid ion thruster for a range of magnetic baffle currents. The ratio of RMS to mean ion beam current varied from 0.04 to 0.23. The spectra of the amplitudes of the beam and discharge current fluctuations were taken up to 9 MHz and show that the predominant amplitudes occur at frequencies of 10 kHz or below. The falloff with increasing frequency is rapid. Frequencies above 100 kHz the spectral levels are 45 kb or more below the maximum peak amplitudes. The cross correlations revealed the ion beam fluctuations to have large radial and axial scales.
Measuring systematic risk from managerial organization capital

Organization capital (OC) constitutes a firm’s unique, hard-to-mimic, hard-to-transfer culture, internal knowledge and language, policies and procedures, growth opportunities and information technology, brand name and any other aspects that are not directly related to the production process. In order to disentangle value enhancement from agency costs inherent in the OC, we calibrate systematic risk premiums from the loss of managerial OC rents by decomposing OC into: (1) portable economic rents in the form of disclosed executive compensation and (2) a strategic component comprised of undisclosed, non-portable OC rents mixed with agency costs. Shareholders in firms with high strategic component (not the portable component) earn an annual systematic risk premium of 4.6%. Disclosures revealing the breakdown between OC and agency costs in the strategic component (earnings surprises, managerial obfuscation and stock mispricing) as well as corporate governance eliminate this risk premium by revealing the OC rents in strategic component and increasing OC portability.
Scattering and inverse scattering for the AKNS system: A rational function approach

We consider the use of rational basis functions to compute the scattering and inverse scattering transforms associated with the AKNS system. The proposed numerical forward scattering transform computes the solution of the AKNS system that is valid on the entire real axis and thereby computes a reflection coefficient at a point by solving a single linear system. The proposed numerical inverse scattering transform makes use of a novel improvement in the rational function approach to the oscillatory Cauchy operator, enabling the efficient solution of certain Riemann--Hilbert problems without contour deformations. The latter development enables access to high-precision computations and this is demonstrated on the inverse scattering transform for the one-dimensional Schrodinger operator with a $\mathrm{sech}^2$ potential.
Genealogical structure changes as range expansions transition from pushed to pulled

Range expansions accelerate evolution through multiple mechanisms, including gene surfing and genetic drift. The inference and control of these evolutionary processes ultimately rely on the information contained in genealogical trees. Currently, there are two opposing views on how range expansions shape genealogies. In invasion biology, expansions are typically approximated by a series of population bottlenecks producing genealogies with only pairwise mergers between lineages-a process known as the Kingman coalescent. Conversely, traveling wave models predict a coalescent with multiple mergers, known as the Bolthausen-Sznitman coalescent. Here, we unify these two approaches and show that expansions can generate an entire spectrum of coalescent topologies. Specifically, we show that tree topology is controlled by growth dynamics at the front and exhibits large differences between pulled and pushed expansions. These differences are explained by the fluctuations in the total number of descendants left by the early founders. High growth cooperativity leads to a narrow distribution of reproductive values and the Kingman coalescent. Conversely, low growth cooperativity results in a broad distribution, whose exponent controls the merger sizes in the genealogies. These broad distribution and non-Kingman tree topologies emerge due to the fluctuations in the front shape and position and do not occur in quasi-deterministic simulations. Overall, our results show that range expansions provide a robust mechanism for generating different types of multiple mergers, which could be similar to those observed in populations with strong selection or high fecundity. Thus, caution should be exercised in making inferences about the origin of non-Kingman genealogies.
A formula for boundary correlations of the critical Ising model

Given a finite rhombus tiling of a polygonal region in the plane, the associated critical Z-invariant Ising model is invariant under star-triangle transformations. We give a simple matrix formula describing spin correlations between boundary vertices in terms of the shape of the region. When the region is a regular polygon, our formula becomes an explicit trigonometric sum.
New Constructions of Group-Invariant Butson Hadamard Matrices

Let G be a finite group and let h be a positive integer. A BH(G, h) matrix is a G-invariant ∣G∣ × ∣G∣ matrix H whose entries are complex hth roots of unity such that H H* = ∣G∣I∣G∣, where H* denotes the complex conjugate transpose of H, and I∣G∣ denotes the identity matrix of order ∣G∣. In this paper, we give three new constructions of BH(G, h) matrices. The first construction is the first known family of BH(G, h) matrices in which G does not need to be abelian. The second and the third constructions are two families of BH(G, h) matrices in which G is a finite local ring.
On Controlling for Misstatement Risk

Ex ante misstatement risk confounds nearly all settings relying on restatements as a measure of audit quality, but researchers continue to debate how to effectively control for this construct. In this study, we consider a recent approach that involves controlling for prior period restatements (“Lagged Restatements”). Using a controlled simulation as well as a basic archival analysis, we show that a lagged restatement control can significantly bias coefficient estimates. We demonstrate this bias using audit fees as a variable of interest but also show the same issue persists for other constructs that respond to the identification of a restatement (i.e., internal control material weaknesses and auditor changes). We conclude by discussing alternative approaches for controlling for ex ante misstatement risk and providing guidance for future research. Taken together, this study provides an important methodological contribution to the broad literature using restatements as a measure of audit quality.
Genetic ancestry predicts male–female affiliation in a natural baboon hybrid zone

Opposite-sex social relationships are important predictors of fitness in many animals, including several group-living mammals. Consequently, understanding sources of variance in the tendency to form opposite-sex relationships is important for understanding social evolution. Genetic contributions are of particular interest due to their importance in long-term evolutionary change, but little is known about genetic effects on male–female relationships in social mammals, especially outside of the mating context. Here, we investigate the effects of genetic ancestry on male–female affiliative behaviour in a hybrid zone between the yellow baboon, Papio cynocephalus, and the anubis baboon, Papio anubis, in a population in which male–female social bonds are known predictors of life span. We place our analysis within the context of other social and demographic predictors of affiliative behaviour in baboons. Genetic ancestry was the most consistent predictor of opposite-sex affiliative behaviour we observed, with the exception of strong effects of dominance rank. Our results show that increased anubis genetic ancestry is associated with a subtle, but significantly higher, probability of opposite-sex affiliative behaviour, in both males and females. Additionally, pairs of anubis-like males and anubis-like females were the most likely to socially affiliate, resulting in moderate assortativity in grooming and proximity behaviour as a function of genetic ancestry. Our findings indicate that opposite-sex affiliative behaviour partially diverged during baboon evolution to differentiate yellow and anubis baboons, despite overall similarities in their social structures and mating systems. Furthermore, they suggest that affiliative behaviour may simultaneously promote and constrain baboon admixture, through additive and assortative effects of ancestry, respectively.
Intertwining operator associated to symmetric groups and summability on the unit sphere

Abstract An integral representation of the intertwining operator for the Dunkl operators associated with symmetric groups is derived for the class of functions of a single component. The expression provides a closed form formula for the reproducing kernels of h -harmonics associated with symmetric groups when one of the components is a coordinate vector. The latter allows us to establish a sharp result for the Cesaro summability of h -harmonic series on the unit sphere.
OpinionRank: Extracting Ground Truth Labels from Unreliable Expert Opinions with Graph-Based Spectral Ranking

As larger and more comprehensive datasets become standard in contemporary machine learning, it becomes increasingly more difficult to obtain reliable, trustworthy label information with which to train sophisticated models. To address this problem, crowdsourcing has emerged as a popular, inexpensive, and efficient data mining solution for performing distributed label collection. However, crowdsourced annotations are inherently untrustworthy, as the labels are provided by anonymous volunteers who may have varying, unreliable expertise. Worse yet, some participants on commonly used platforms such as Amazon Mechanical Turk may be adversarial, and provide intentionally incorrect label information without the end user's knowledge. We discuss three conventional models of the label generation process, describing their parameterizations and the model-based approaches used to solve them. We then propose OpinionRank, a model-free, interpretable, graph-based spectral algorithm for integrating crowdsourced annotations into reliable labels for performing supervised or semi-supervised learning. Our experiments show that OpinionRank performs favorably when compared against more highly parameterized algorithms. We also show that OpinionRank is scalable to very large datasets and numbers of label sources, and requires considerably fewer computational resources than previous approaches.
Ergodic imitation: Learning from what to do and what not to do

With growing access to versatile robotics, it is beneficial for end users to be able to teach robots tasks without needing to code a control policy. One possibility is to teach the robot through successful task executions. However, near-optimal demonstrations of a task can be difficult to provide and even successful demonstrations can fail to capture task aspects key to robust skill replication. Here, we propose a learning from demonstration (LfD) approach that enables learning of robust task definitions without the need for near-optimal demonstrations. We present a novel algorithmic framework for learning tasks based on the ergodic metric—a measure of information content in motion. Moreover, we make use of negative demonstrations—demonstrations of what not to do—and show that they can help compensate for imperfect demonstrations, reduce the number of demonstrations needed, and highlight crucial task elements improving robot performance. In a proof-of-concept example of cart-pole inversion, we show that negative demonstrations alone can be sufficient to successfully learn and recreate a skill. Through a human subject study with 24 participants, we show that consistently more information about a task can be captured from combined positive and negative (posneg) demonstrations than from the same amount of just positive demonstrations. Finally, we demonstrate our learning approach on simulated tasks of target reaching and table cleaning with a 7-DoF Franka arm. Our results point towards a future with robust, data-efficient LfD for novice users.
Adaptation and genomic erosion in fragmented Pseudomonas aeruginosa populations in the sinuses of people with cystic fibrosis.

Summary Pseudomonas aeruginosa notoriously adapts to the airways of people with cystic fibrosis (CF), yet how infection-site biogeography and associated evolutionary processes vary as lifelong infections progress remains unclear. Here we test the hypothesis that early adaptations promoting aggregation influence evolutionary-genetic trajectories by examining longitudinal P. aeruginosa from the sinuses of six adults with CF. Highly host-adapted lineages harbored mutator genotypes displaying signatures of early genome degradation associated with recent host restriction. Using an advanced imaging technique (MiPACT-HCR [microbial identification after passive clarity technique]), we find population structure tracks with genome degradation, with the most host-adapted, genome-degraded P. aeruginosa (the mutators) residing in small, sparse aggregates. We propose that following initial adaptive evolution in larger populations under strong selection for aggregation, P. aeruginosa persists in small, fragmented populations that experience stronger effects of genetic drift. These conditions enrich for mutators and promote degenerative genome evolution. Our findings underscore the importance of infection-site biogeography to pathogen evolution.
Identification of high confidence human poly(A) RNA isoform scaffolds using nanopore sequencing.

Nanopore sequencing devices read individual RNA strands directly. This facilitates identification of exon linkages and nucleotide modifications; however, using conventional methods the 5' and 3' ends of poly(A) RNA cannot be identified unambiguously. This is due in part to the architecture of the nanopore/enzyme-motor complex, and in part to RNA degradation in vivo and in vitro that can obscure transcription start and end sites. In this study, we aimed to identify individual full-length human RNA isoform scaffolds among ~4 million nanopore poly(A)-selected RNA reads. First, to identify RNA strands bearing 5' m7G caps, we exchanged the biological cap for a modified cap attached to a 45-nucleotide oligomer. This oligomer adaptation method improved 5' end sequencing and ensured correct identification of the 5' m7G capped ends. Second, among these 5'-capped nanopore reads, we screened for ionic current signatures consistent with a 3' polyadenylation site. Combining these two steps, we identified 294,107 individual high-confidence full-length RNA scaffolds, most of which (257,721) aligned to protein-coding genes. Of these, 4,876 scaffolds indicated unannotated isoforms that were often internal to longer, previously identified RNA isoforms. Orthogonal data confirmed the validity of these high-confidence RNA scaffolds.
A higher burden of multiple sclerosis genetic risk confers an earlier onset.

Background:Age at onset of multiple sclerosis (MS) is an objective, influential predictor of the evolution of MS independent of disease duration.Objectives:Determine the influence of MS genetic pre...
Geometrically Matched Multi-source Microscopic Image Synthesis Using Bidirectional Adversarial Networks.

Microscopic images from multiple modalities can produce plentiful experimental information. In practice, biological or physical constraints under a given observation period may prevent researchers from acquiring enough microscopic scanning. Recent studies demonstrate that image synthesis is one of the popular approaches to release such constraints. Nonetheless, most existing synthesis approaches only translate images from the source domain to the target domain without solid geometric associations. To embrace this challenge, we propose an innovative model architecture, BANIS, to synthesize diversified microscopic images from multi-source domains with distinct geometric features. The experimental outcomes indicate that BANIS successfully synthesizes favorable image pairs on C. elegans microscopy embryonic images. To the best of our knowledge, BANIS is the first application to synthesize microscopic images that associate distinct spatial geometric features from multi-source domains.
Revisiting decompression sickness risk and mobility in the context of the SmartSuit, a hybrid planetary spacesuit

Gas pressurized spacesuits are cumbersome, cause injuries, and are metabolically expensive. Decreasing the gas pressure of the spacesuit is an effective method for improving mobility, but reduction in the total spacesuit pressure also results in a higher risk for decompression sickness (DCS). The risk of DCS is currently mitigated by breathing pure oxygen before the extravehicular activity (EVA) for up to 4 h to remove inert gases from body tissues, but this has a negative operational impact due to the time needed to perform the prebreathe. In this paper, we review and quantify these important trade-offs between spacesuit pressure, mobility, prebreathe time (or risk of DCS), and space habitat/station atmospheric conditions in the context of future planetary EVAs. In addition, we explore these trade-offs in the context of the SmartSuit architecture, a hybrid spacesuit with a soft-robotic layer that, not only increases mobility with assistive actuators in the lower body, but it also applies some level of mechanical counterpressure (MCP). The additional MCP in hybrid spacesuits can be used to supplement the gas pressure (i.e., increasing the total spacesuit pressure), therefore reducing the risk of DCS (or reduce prebreathe time). Alternatively, the MCP can be used to reduce the gas pressure (i.e., maintaining the same total spacesuit pressure), therefore increasing mobility. Finally, we propose a variable pressure concept of operations for the SmartSuit spacesuit. Our framework quantifies critical spacesuit and habitat trade-offs for future planetary exploration and contributes to the assessment of human health and performance during future planetary EVAs.
Hardware-Efficient Microwave-Activated Tunable Coupling between Superconducting Qubits.

Author(s): Mitchell, Bradley K; Naik, Ravi K; Morvan, Alexis; Hashim, Akel; Kreikebaum, John Mark; Marinelli, Brian; Lavrijsen, Wim; Nowrouzi, Kasra; Santiago, David I; Siddiqi, Irfan | Abstract: Generating high-fidelity, tunable entanglement between qubits is crucial for realizing gate-based quantum computation. In superconducting circuits, tunable interactions are often implemented using flux-tunable qubits or coupling elements, adding control complexity and noise sources. Here, we realize a tunable $ZZ$ interaction between two transmon qubits with fixed frequencies and fixed coupling, induced by driving both transmons off-resonantly. We show tunable coupling over one order of magnitude larger than the static coupling, and change the sign of the interaction, enabling cancellation of the idle coupling. Further, this interaction is amenable to large quantum processors: the drive frequency can be flexibly chosen to avoid spurious transitions, and because both transmons are driven, it is resilient to microwave crosstalk. We apply this interaction to implement a controlled phase (CZ) gate with a gate fidelity of $99.43(1)\%$ as measured by cycle benchmarking, and we find the fidelity is limited by incoherent errors.
Increasing Liquid State Machine Performance with Edge-of-Chaos Dynamics Organized by Astrocyte-modulated Plasticity

The liquid state machine (LSM) combines low training complexity and biological plausibility, which has made it an attractive machine learning framework for edge and neuromorphic computing paradigms. Originally proposed as a model of brain computation, the LSM tunes its internal weights without backpropagation of gradients, which results in lower performance compared to multi-layer neural networks. Recent findings in neuroscience suggest that astrocytes, a long-neglected non-neuronal brain cell, modulate synaptic plasticity and brain dynamics, tuning brain networks to the vicinity of the computationally optimal critical phase transition between order and chaos. Inspired by this disruptive understanding of how brain networks self-tune, we propose the neuron-astrocyte liquid state machine (NALSM) that addresses under-performance through self-organized near-critical dynamics. Similar to its biological counterpart, the astrocyte model integrates neuronal activity and provides global feedback to spike-timing-dependent plasticity (STDP), which self-organizes NALSM dynamics around a critical branching factor that is associated with the edge-of-chaos. We demonstrate that NALSM achieves state-of-the-art accuracy versus comparable LSM methods, without the need for data-specific hand-tuning. With a top accuracy of 97.61% on MNIST, 97.51% on N-MNIST, and 85.84% on Fashion-MNIST, NALSM achieved comparable performance to current fully-connected multi-layer spiking neural networks trained via backpropagation. Our findings suggest that the further development of brain-inspired machine learning methods has the potential to reach the performance of deep learning, with the added benefits of supporting robust and energy-efficient neuromorphic computing on the edge.
Integrated Optical Addressing of a Trapped Ytterbium Ion

A surface ion trap with integrated waveguides produces no additional heating and modest frequency shifts due to photoinduced charging when uv light is delivered to an ion, thus providing the stability needed for compact quantum timekeeping devices.
Neural optimal feedback control with local learning rules

A major problem in motor control is understanding how the brain plans and executes proper movements in the face of delayed and noisy stimuli. A prominent framework for addressing such control problems is Optimal Feedback Control (OFC). OFC generates control actions that optimize behaviorally relevant criteria by integrating noisy sensory stimuli and the predictions of an internal model using the Kalman filter or its extensions. However, a satisfactory neural model of Kalman filtering and control is lacking because existing proposals have the following limitations: not considering the delay of sensory feedback, training in alternating phases, and requiring knowledge of the noise covariance matrices, as well as that of systems dynamics. Moreover, the majority of these studies considered Kalman filtering in isolation, and not jointly with control. To address these shortcomings, we introduce a novel online algorithm which combines adaptive Kalman filtering with a model free control approach (i.e., policy gradient algorithm). We implement this algorithm in a biologically plausible neural network with local synaptic plasticity rules. This network performs system identification and Kalman filtering, without the need for multiple phases with distinct update rules or the knowledge of the noise covariances. It can perform state estimation with delayed sensory feedback, with the help of an internal model. It learns the control policy without requiring any knowledge of the dynamics, thus avoiding the need for weight transport. In this way, our implementation of OFC solves the credit assignment problem needed to produce the appropriate sensory-motor control in the presence of stimulus delay.
Hedging on the Hill: Does Political Hedging Reduce Firm Risk?

We examine whether firms’ political hedging activities are effective at mitigating political risk. Focusing on the risk induced by partisan politics, we measure political hedging as the degree to w...
All-optical fluorescence blinking control in quantum dots with ultrafast mid-infrared pulses.

Photoluminescence intermittency is a ubiquitous phenomenon, reducing the temporal emission intensity stability of single colloidal quantum dots (QDs) and the emission quantum yield of their ensembles. Despite efforts to achieve blinking reduction by chemical engineering of the QD architecture and its environment, blinking still poses barriers to the application of QDs, particularly in single-particle tracking in biology or in single-photon sources. Here, we demonstrate a deterministic all-optical suppression of QD blinking using a compound technique of visible and mid-infrared excitation. We show that moderate-field ultrafast mid-infrared pulses (5.5 μm, 150 fs) can switch the emission from a charged, low quantum yield grey trion state to the bright exciton state in CdSe/CdS core–shell QDs, resulting in a significant reduction of the QD intensity flicker. Quantum-tunnelling simulations suggest that the mid-infrared fields remove the excess charge from trions with reduced emission quantum yield to restore higher brightness exciton emission. Our approach can be integrated with existing single-particle tracking or super-resolution microscopy techniques without any modification to the sample and translates to other emitters presenting charging-induced photoluminescence intermittencies, such as single-photon emissive defects in diamond and two-dimensional materials. Photoluminescence blinking is a ubiquitous phenomenon that detrimentally reduces emission stability and quantum yield. Now, an all-optical method, which employs ultrafast mid-infrared pulses, can effectively suppress the blinking of single CdSe/CdS core–shell quantum dots.
Output feedback stabilization

The 1D wave model presentation of a 2D system is treated. The stabilization problem for the wave model using output feedback is considered. Necessary and/or sufficient conditions for the stabilization problem are derived. Numerical examples are given to illustrate the several techniques. >
Scoring systems for measuring progression of visual field loss in clinical trials of glaucoma treatment.

Abstract Objectives To compare the statistical properties of two visual field scoring systems used by clinical trials of glaucoma treatments with a view to their performance as longitudinal measures of visual field progression. Design Cohort study comparing the scoring systems used by the Advanced Glaucoma Intervention Study (AGIS) and the Collaborative Initial Glaucoma Treatment Study (CIGTS) using pairs of visual fields (C-30-2 of the Humphrey Analyzer) spaced 1 year apart. Participants Sixty-seven eyes of 56 subjects with glaucomatous visual field loss from a natural history study of glaucoma were examined. Methods Because both scoring systems are scaled so that they range from 0 to 20, the AGIS and CIGTS scores were compared by scatterplot, Pearson correlation, and the mean difference between scores. The difference between pairs of scores 1 year apart was used to compare the temporal variability of each scoring system. The proportion of subjects whose visual field "deteriorated" in 1 year by the amount specified for unconfirmed progression in each clinical trial was calculated. Main outcome measures Mean difference in scores 1 year apart and the variance of these differences were measured. Results The median scores for the first of the two fields was 5.2 (interquartile range [IQR] = 9.8) for CIGTS and 5.0 (IQR = 7.0) for AGIS. The CIGTS scores were slightly larger than AGIS scores by an average of 0.5 ( P = 0.06). The mean CIGTS score of the baseline fields was 0.06 (standard deviation=3.8) higher than the mean of the second fields and 0.12 (standard deviation=2.8) higher for AGIS. Fifteen percent of eyes had CIGTS scores that deteriorated by three or more (the cutoff for unconfirmed progression) over 1 year, while 7.5% of eyes had AGIS scores that deteriorated by four or more (the AGIS cutoff for unconfirmed progression) over the same period. Twenty-one percent improved by CIGTS criteria, while 12% improved by AGIS criteria. Conclusions CIGTS scores are systematically slightly higher than AGIS scores. The CIGTS scoring system has higher temporal variability than the AGIS system. The CIGTS criterion for unconfirmed progression over a 1-year period is likely to lead to higher estimated rates of progression than the AGIS criteria. This is mostly because of the difference in the definition of progression between the two study criteria.
A Chlorophyll Fluorescence Analysis of the Allocation of Radiant Energy Absorbed in Photosystem 2 Antennae of Cotton Leaves During Exposure to Chilling

When dark-acclimated cotton (Gossypium hirsutum L. cv. Coker 312) leaves, pre-treated with lincomycin to inhibit chloroplast protein repair processes, were exposed to 10 °C and a PPFD of 500 μmol m-2 s-1, the proportion of excitation energy entering photochemistry (P) increased, but only to 5 % of the total energy absorbed at steady state levels of P, which were reached at 40 min of irradiation. Thermal dissipation (D) of absorbed energy increased throughout the 360 min irradiation period and accounted for the greatest portion of absorbed energy at 10 °C. When D was partitioned into constitutive (DCON), regulated (DREG), and photoinhibitory (DPI) components, it was primarily composed of DREG, the readily reversible portion of D. However, the induction of D was slow at 10 °C. Sixty minutes were required for D to reach 70 % of the energy absorbed. Considerable absorption of energy in excess of that utilized in photochemistry or dissipated thermally (designated as E) occurred, especially during induction of P and D. Over the irradiation period, the time-dependent averaged E exhibited an inverse, linear relationship with the ratio of variable (Fv) to maximum (Fm) fluorescence (PS2 efficiency) and a linear relationship with DPI. We propose that time-dependent averaged E may be useful for estimating the potential for damage to PS2 under stressful environmental conditions.
The social meanings of social networks: integrating SNA and ethnography of social networking

In this talk, I examine the manifest, emic meanings of social networking in the context of social network analysis and it uses this to discuss how the confluence of social science and computational sociology can contribute to a richer understanding of how emerging social technologies shape and are shaped by people's everyday practices.
Mental Health and Social Development

Our task during this week is to consider mental health, social development and cultural values. All of these terms relate to the same issue. Persons who are content, happy, efficient, effective and contributing are probably mentally healthy. Such qualities can be reached only within the boundaries of permissable behavior sanctioned by one’s culture. The person who is satisfying to himself or herself is likely to be satisfying to others in the culture. Also, the culture is likely to assess that individual as being one who is promoting the general good of the community. In this sense, such a person attends to the social development of his or her own culture, while at the same time providing an example of that culture’s mentally healthy person. Such a person practices positive mental health.
Recent trends in cost-related medication nonadherence among stroke survivors in the United States.

Objective Recent economic and health policy changes may have affected the ability of chronically ill patients to afford their medications. We assessed changes in cost-related nonadherence (CRN) to medication before and after the implementation of Medicare Part D in 2006.
The association between alcohol use and cardiovascular disease among people living with HIV: a systematic review.

AbstractBackground: People living with HIV-infection (PLWH) have higher prevalence and earlier onset of cardiovascular disease (CVD), compared to uninfected populations. It is unclear how alcohol consumption is related to CVD among PLWH. Objectives: To summarize the current literature and strength of evidence regarding alcohol consumption as a risk factor for CVD among PLWH, to generate summary estimates for the effect of alcohol consumption on CVD outcomes, and to make recommendations for clinical practice and future research based on the findings and limitations of existing studies. Methods: A systematic review was conducted using Pubmed/Medline to identify relevant peer-reviewed articles published between 1 January 1999 and 1 January 2014. After critical review of the literature, 13 studies were identified. Risk ratios were extracted or calculated and sample size weighted summary estimates were calculated. Results: The prevalence of a CVD diagnosis or event ranged from 5.7–24.0%. The weighted pooled cr...
Female Pardosa milvina wolf spiders increase silk advertisements when in the presence of silk from courting males

Abstract Female wolf spider silk is known to elicit searching and courtship behavior among adult males, however variation in the types of silk females deposit, the context in which it occurs, and the role of male silk in courtship displays and female responses has rarely been examined. We measured male Pardosa milvina (Hentz 1844) silk deposition while performing courtship displays. We then examined whether female silk deposition changes when encountering silk produced from a courting rather than a non-courting male and compared these conditions to female silk deposition in the absence of male silk. We measured the quantity of three different types of silk (draglines, cord silk, and attachment disks) deposited by females across substrates previously occupied by a courting male, a non-courting male, or no male. Females significantly increased attachment disk deposition in the presence of silk from a courting rather than a non-courting male. Females also showed elevated dragline deposition in the presence o...