cssi/SciSciGPT-SciSciNet huggingface dataset:
Robust Evaluation Matrix: Towards a More Principled Offline Exploration of Instructional Policies

The gold standard for identifying more effective pedagogical approaches is to perform an experiment. Unfortunately, frequently a hypothesized alternate way of teaching does not yield an improved effect. Given the expense and logistics of each experiment, and the enormous space of potential ways to improve teaching, it would be highly preferable if it were possible to estimate in advance of running a study whether an alternative teaching strategy would improve learning. This is true even in learning at scale situations, since even if it is logistically easier to recruit a large number of subjects, it remains a high stakes environment because the experiment is impacting many real students. For certain classes of alternate teaching approaches, such as new ways to sequence existing material, it is possible to build student models that can be used as simulators to estimate the performance of learners under new proposed teaching methods. However, existing methods for doing so can overestimate the performance of new teaching methods. We instead propose the Robust Evaluation Matrix (REM) method which explicitly considers model mismatch between the student model used to derive the teaching strategy and that used as a simulator to evaluate the teaching strategy effectiveness. We then present two case studies from a fractions intelligent tutoring system and from a concept learning task from prior work that show how REM could be used both to detect when a new instructional policy may not be effective on actual students and to detect when it may be effective in improving student learning.
Improving Student Outcomes in Higher Education: The Science of Targeted Intervention

Many theoretically based interventions have been developed over the past two decades to improve educational outcomes in higher education. Based in social-psychological and motivation theories, well-crafted interventions have proven remarkably effective because they target specific educational problems and the processes that underlie them. In this review, we evaluate the current state of the literature on targeted interventions in higher education with an eye to emerging theoretical and conceptual questions about intervention science. We review three types of interventions, which focus on the value students perceive in academic tasks, their framing of academic challenges, and their personal values, respectively. We consider interventions that (a) target academic outcomes (e.g., grades, major or career plans, course taking, retention) in higher education, as well as the pipeline to college, and (b) have been evaluated in at least two studies. Finally, we discuss implications for intervention science moving forward.
Surface oxidation and thermoelectric properties of indium-doped tin telluride nanowires

The recent discovery of excellent thermoelectric properties and topological surface states in SnTe-based compounds has attracted extensive attention in various research areas. Indium doped SnTe is of particular interest because, depending on the doping level, it can either generate resonant states in the bulk valence band leading to enhanced thermoelectric properties, or induce superconductivity that coexists with topological states. Here we report on the vapor deposition of In-doped SnTe nanowires and the study of their surface oxidation and thermoelectric properties. The nanowire growth is assisted by Au catalysts, and their morphologies vary as a function of substrate position and temperature. Transmission electron microscopy characterization reveals the formation of an amorphous surface in single crystalline nanowires. X-ray photoelectron spectroscopy studies suggest that the nanowire surface is composed of In2O3, SnO2, Te and TeO2 which can be readily removed by argon ion sputtering. Exposure of the cleaned nanowires to atmosphere leads to rapid oxidation of the surface within only one minute. Characterization of electrical conductivity σ, thermopower S, and thermal conductivity κ was performed on the same In-doped nanowire which shows suppressed σ and κ but enhanced S yielding an improved thermoelectric figure of merit ZT compared to the undoped SnTe.
Potential Mechanisms and Functions of Intermittent Neural Synchronization.

Neural synchronization is believed to play an important role in different brain functions. Synchrony in cortical and subcortical circuits is frequently variable in time and not perfect. Few long intervals of desynchronized dynamics may be functionally different from many short desynchronized intervals although the average synchrony may be the same. Recent analysis of imperfect synchrony in different neural systems reported one common feature: neural oscillations may go out of synchrony frequently, but primarily for a short time interval. This study explores potential mechanisms and functional advantages of this short desynchronizations dynamics using computational neuroscience techniques. We show that short desynchronizations are exhibited in coupled neurons if their delayed rectifier potassium current has relatively large values of the voltage-dependent activation time-constant. The delayed activation of potassium current is associated with generation of quickly-rising action potential. This “spikiness” is a very general property of neurons. This may explain why very different neural systems exhibit short desynchronization dynamics. We also show how the distribution of desynchronization durations may be independent of the synchronization strength. Finally, we show that short desynchronization dynamics requires weaker synaptic input to reach a pre-set synchrony level. Thus, this dynamics allows for efficient regulation of synchrony and may promote efficient formation of synchronous assemblies.
Cardiovascular effects of the addition of nilotinib to standard therapy for acute myeloid leukemia.

Nilotinib is a second-generation tyrosine kinase inhibitor (TKI), which inhibits the activity of KIT, BCR-ABL, PDGF-A, PDGF-B and FLT-3 [1]. KIT is involved in regulating proliferation and apoptosi...
Robust High-Dimensional Volatility Matrix Estimation for High-Frequency Factor Model

High-frequency financial data allow us to estimate large volatility matrices with relatively short time horizon. Many novel statistical methods have been introduced to address large volatility matr...
Integrated Flight/Propulsion Control: Requirements and Issues

Abstract The integration of flight and propulsion control is an emerging technology that has the potential to offer significant improvements in the mission capabilities of future aircraft systems. Both increased efficiency as well as extended flight and maneuver envelopes have already been demonstrated. There are two main areas of research required to realize fully the benefits of integrating flight and propulsion control. The first is the development of hardware that allows the use of engine air to produce forces and moments about the vehicle axes suitable for high bandwidth attitude control. Thrust vectoring schemes, lift augmentation schemes and direct force/moment control schemes are potential concepts. The second research area is the development of a design approach that will yield integrated control laws. There are several factors which complicate the development of an integrated control design approach. One is that the types of control appropriate for the flight and propulsion systems are fundamentally different and hence global control design approaches may not be practical. Another is that there are a variety of issues such as design accountability that make it desirable to partition the problem. Specifically, control design tasks that relate to airframe safety should be assigned to the airframe manufacturer and those that relate to propulsion to the engine manufacturer. Presented below is an argument that a decentralized-hierarchical design approach is a practical method for designing integrated flight/propulsion control systems. Both the flight control problem and propulsion control problem are reviewed to highlight their differences (emphasis is placed on the propulsion control). Finally, a brief summary is presented of a design approach which is under development and appears to offer a promising solution (the development of this approach was begun under the Air Force DMICS program [1]).
Monitoring Behavioral Evolution for On-Line Fault Detection

Abstract The evolution graph monitor is defined and illustrated for on-line monitoring of computer-controlled processes with both discrete and continuous dynamics. Using a behavioral model specification of the process dynamics, the evolution graph monitor builds and maintain an efficient representation of the set of admissible system trajectories which are consistent with the on-line observations as they are received. In contrast to simulation-based methods, the evolution graph approach handles delayed, uncertain, and infrequent observations for systems with widely varying operating characteristics. A behavioral model specification and evolution graph monitor have been developed to perform on-line fault detection for an electric arc furnace in a continuous-caster steel mill. This application is used throughout the paper to illustrate the details of the approach.
Enterococcal Bacteremia in Two Large Community Teaching Hospitals

Abstract This report reviews 55 episodes of enterococcal bacteremia at two large community teaching hospitals. Fifty-eight percent of the patients were older than 60 years, and 84 percent of the patients had some underlying illness. The most common sources of bacteremia were the urinary tract (24 percent), cutaneous wound infection (11 percent), and intra-abdominal infection (11 percent). Five patients had entero-coccal endocarditis. Antimicrobial therapy in the week preceding enterococcal bacteremia (42 percent) and polymicrobial bacteremia (38 percent) were common. Despite the institution of appropriate antimicrobial therapy in 75 percent of the patients (41 of 55 patients), the overall mortality rate was 44 percent. Male sex and the presence of a rapidly or ultimately fatal underlying illness were the only factors that showed a statistical tendency toward adversely influencing the mortality risk in enterococcal bacteremia.
The Problem With Being Special Democratic Values and Special Assessments

In the face of voter-imposed tax limitations, local governments have adopted ever-more complex financial mechanisms to balance their budgets. Increasingly, municipalities in California have made use of special assessments to finance local infrastructure improvements and other vital government services. These assessments bill property owners for public goods and services in proportion to the “special benefits” that they receive. Because benefit assessments are constitutionally distinct from taxes, the growth in assessment financing has come partly as a direct response to increased constraints on the ability of local governments to raise general taxes. Our contention is that this growth should prove cause for concern due to the unusual combination of social choice pathologies to which special assessments fall vulnerable. Field interviews with public officials and the consultants they call on to help create these assessments suggest that special assessments can indeed pose special democratic problems.
Association of Retroperitoneal Fibrosis and Interstitial Nephritis

• A patient with renal failure and light-chain proteinuria showed roentgenographic evidence of retroperitoneal fibrosis on further examination. Diffuse hyperglobulinemia, low levels of C3 and C4, and elevated C1q binding were noted. Biopsy specimens of the kidney and retroperitoneal tissue disclosed a dense pleomorphic cellular infiltrate with a preponderance of plasma cells. Renal function improved slowly after ureterolysis and institution of prednisone therapy. The case emphasizes the immunologic features of the early phase of idiopathic retroperitoneal fibrosis. ( Arch Intern Med 1981;141:1361-1363)
Marangoni effects on a thin liquid film coating a sphere with axial or radial thermal gradients

We study the time evolution of a thin liquid film coating the outer surface of a sphere in the presence of gravity, surface tension, and thermal gradients. We derive the fourth-order nonlinear partial differential equation that models the thin film dynamics, including Marangoni terms arising from the dependence of surface tension σ on temperature T. We consider two different imposed temperature distributions with axial or radial thermal gradients. We analyze the stability of a uniform coating under small perturbations and carry out numerical simulations in COMSOL for a range of parameter values. In the case of an axial temperature gradient, we find steady states either with uniform film thickness or with the fluid accumulating at the bottom or near the top of the sphere, depending on the total volume of liquid in the film, dictating whether gravity or Marangoni effects dominate. This suggests a potential method for the indirect measurement of dσ/dT by monitoring the thickness profile of the thin film. In the case of a radial temperature gradient, a stability analysis reveals the most unstable non-axisymmetric modes on an initially uniform coating film.
Physics reach of BTeV

Abstract BTeV is a collider program at the Fermilab Tevatron dedicated to the study of CP violation, mixing, and rare decays in beauty and charm hadrons. The detectors is a forward spectrometer sited at the C-Zero interaction region.
Effects of Contact Network Models on Stochastic Epidemic Simulations

The importance of modeling the spread of epidemics through a population has led to the development of mathematical models for infectious disease propagation. A number of empirical studies have collected and analyzed data on contacts between individuals using a variety of sensors. Typically one uses such data to fit a probabilistic model of network contacts over which a disease may propagate. In this paper, we investigate the effects of different contact network models with varying levels of complexity on the outcomes of simulated epidemics using a stochastic Susceptible-Infectious-Recovered (SIR) model. We evaluate these network models on six datasets of contacts between people in a variety of settings. Our results demonstrate that the choice of network model can have a significant effect on how closely the outcomes of an epidemic simulation on a simulated network match the outcomes on the actual network constructed from the sensor data. In particular, preserving degrees of nodes appears to be much more important than preserving cluster structure for accurate epidemic simulations.
Brain explorer for connectomic analysis

Visualization plays a vital role in the analysis of multimodal neuroimaging data. A major challenge in neuroimaging visualization is how to integrate structural, functional, and connectivity data to form a comprehensive visual context for data exploration, quality control, and hypothesis discovery. We develop a new integrated visualization solution for brain imaging data by combining scientific and information visualization techniques within the context of the same anatomical structure. In this paper, new surface texture techniques are developed to map non-spatial attributes onto both 3D brain surfaces and a planar volume map which is generated by the proposed volume rendering technique, spherical volume rendering. Two types of non-spatial information are represented: (1) time series data from resting-state functional MRI measuring brain activation; (2) network properties derived from structural connectivity data for different groups of subjects, which may help guide the detection of differentiation features. Through visual exploration, this integrated solution can help identify brain regions with highly correlated functional activations as well as their activation patterns. Visual detection of differentiation features can also potentially discover image-based phenotypic biomarkers for brain diseases.
Insulin resistance in cavefish as an adaptation to a nutrient-limited environment

Periodic food shortages are a major challenge faced by organisms in natural habitats. Cave-dwelling animals must withstand long periods of nutrient deprivation, as-in the absence of photosynthesis-caves depend on external energy sources such as seasonal floods. Here we show that cave-adapted populations of the Mexican tetra, Astyanax mexicanus, have dysregulated blood glucose homeostasis and are insulin-resistant compared to river-adapted populations. We found that multiple cave populations carry a mutation in the insulin receptor that leads to decreased insulin binding in vitro and contributes to hyperglycaemia. Hybrid fish from surface-cave crosses carrying this mutation weigh more than non-carriers, and zebrafish genetically engineered to carry the mutation have increased body weight and insulin resistance. Higher body weight may be advantageous in caves as a strategy to cope with an infrequent food supply. In humans, the identical mutation in the insulin receptor leads to a severe form of insulin resistance and reduced lifespan. However, cavefish have a similar lifespan to surface fish and do not accumulate the advanced glycation end-products in the blood that are typically associated with the progression of diabetes-associated pathologies. Our findings suggest that diminished insulin signalling is beneficial in a nutrient-limited environment and that cavefish may have acquired compensatory mechanisms that enable them to circumvent the typical negative effects associated with failure to regulate blood glucose levels.
Automated Crowdturfing Attacks and Defenses in Online Review Systems

Malicious crowdsourcing forums are gaining traction as sources of spreading misinformation online, but are limited by the costs of hiring and managing human workers. In this paper, we identify a new class of attacks that leverage deep learning language models (Recurrent Neural Networks or RNNs) to automate the generation of fake online reviews for products and services. Not only are these attacks cheap and therefore more scalable, but they can control rate of content output to eliminate the signature burstiness that makes crowdsourced campaigns easy to detect. Using Yelp reviews as an example platform, we show how a two phased review generation and customization attack can produce reviews that are indistinguishable by state-of-the-art statistical detectors. We conduct a survey-based user study to show these reviews not only evade human detection, but also score high on "usefulness" metrics by users. Finally, we develop novel automated defenses against these attacks, by leveraging the lossy transformation introduced by the RNN training and generation cycle. We consider countermeasures against our mechanisms, show that they produce unattractive cost-benefit tradeoffs for attackers, and that they can be further curtailed by simple constraints imposed by online service providers.
Financial globalization : a glass half empty ?

Since the 1970s, the world has embarked on a new financial globalization era. Cross-country capital flows have significantly increased in developed and developing countries. However, the characteristics of financial globalization differ from what was originally expected. Various examples illustrate this point. Although the literature predicted large gains from financial globalization (such as additional funding, broad diversification, and deeper financial systems), the positive effects have been more limited. In developed and developing countries, financial globalization has manifested in increasing gross capital flows (inflows and outflows) rather than larger net flows. Capital markets are segmented and only a few large firms access international markets. International institutional investors do not seem to have played a stabilizing role, helping to exacerbate and transmit crises across countries. Although financial globalization has brought several beneficial changes, its net effects and spillovers to the overall economies participating in it have yet to be understood.
Co-exposure to methylmercury and inorganic arsenic in baby rice cereals and rice-containing teething biscuits.

Abstract Background Rice is an important dietary source for methylmercury (MeHg), a potent neurotoxin, and inorganic arsenic (As), a human carcinogen. Rice baby cereals are a dietary source of inorganic As; however, less is known concerning MeHg concentrations in rice baby cereals and rice teething biscuits. Methods MeHg concentrations were measured in 36 rice baby cereals, eight rice teething biscuits, and four baby cereals manufactured with oats/wheat (n = 48 total). Arsenic (As) species, including inorganic As, were determined in rice baby cereals and rice teething biscuits (n = 44/48), while total As was determined in all products (n = 48). Results Rice baby cereals and rice teething biscuits were on average 61 and 92 times higher in MeHg, respectively, and 9.4 and 4.7 times higher in total As, respectively, compared to wheat/oat baby cereals. For a 15-g serving of rice baby cereal, average MeHg intake was 0.0092 μg day−1 (range: 0.0013–0.034 μg day−1), while average inorganic As intake was 1.3 μg day−1 (range: 0.37–2.3 μg day−1). Inorganic As concentrations in two brands of rice baby cereal (n = 12/36 boxes of rice cereal) exceeded 100 ng/g, the proposed action level from the U.S. Food and Drug Administration. Log10 MeHg and inorganic As concentrations in rice baby cereals were strongly, positively correlated (Pearson's rho = 0.60, p Conclusions Rice-containing baby cereals and teething biscuits were a dietary source of both MeHg and inorganic As. Studies concerning the cumulative impacts of MeHg and inorganic As on offspring development are warranted.
Comparison of Gaussian process modeling software

Abstract Gaussian process fitting, or kriging, is often used to create a model from a set of data. Many available software packages do this, but we show that very different results can be obtained from different packages even when using the same data and model. We describe the parameterization, features, and optimization used by eight different fitting packages that run on four different platforms. We then compare these eight packages using various data functions and data sets, revealing that there are stark differences between the packages. In addition to comparing the prediction accuracy, the predictive variance – which is important for evaluating precision of predictions and is often used in stopping criteria – is also evaluated.
Sentiment Manipulation in Online Platforms: An Analysis of Movie Tweets

Online platforms are prone to abuse and manipulations from strategic parties. For example, social media and review websites suffer from sentiment manipulations, manifested in the form of opinion spam and fake reviews. The consequence of such manipulations is the deterioration of information quality as well as loss in consumer welfare. We study one of movie studios’ operation activities, sentiment manipulation, in the context of movie tweets. Using the movie release and movie studios’ earning announcement dates as sources of exogenous shocks, we find that both the average Twitter sentiment and the proportion of highly positive tweets exhibit a significant drop on the movie's release day or movie studios’ earnings announcement day. In addition, independent productions and low budget movies tend to experience a larger drop than major studio productions and high budget movies. To examine the effect of competition on firm manipulation, we construct a movie competition measure based on both the time and theme dimensions through topic modeling, and we find that a higher level of competition leads to a larger drop in Twitter sentiment. Overall, these observations suggest that firms might be actively managing online sentiment in a strategic manner. Our study sheds light on the reliability of sentiment analysis and contributes to our understanding of potential strategic manipulation in the operation of movie studios. This article is protected by copyright. All rights reserved.
Comorbidity, Physical Function, and Quality of Life in Older Adults with Acute Myeloid Leukemia

The purpose of this study is to describe the pathology, impact of comorbidities, functional limitations, symptoms, and quality of life (QOL) related to treatment of acute myeloid leukemia (AML) in older adults. AML is a rare aggressive hematologic disease that occurs most often in older adults. The prognosis for older patients with AML is markedly worse due to genetic mutations and patient characteristics such as comorbidities and functional limitations. Patient characteristics may influence treatment decisions, as well as impact symptoms, functional ability, health-related outcomes, and QOL. As the population continues to age, the number of people diagnosed with AML is expected to increase. Better management of comorbidities is imperative to improving QOL and other treatment-related outcomes. Prospective, longitudinal, and multi-site studies are warranted to further understand the interaction between these characteristics on symptoms, outcomes, and QOL.
Cis-regulatory evolution integrated the Bric-à-brac transcription factors into a novel fruit fly gene regulatory network.

Gene expression evolution through gene regulatory network (GRN) changes has gained appreciation as a driver of morphological evolution. However, understanding how GRNs evolve is hampered by finding relevant cis-regulatory element (CRE) mutations, and interpreting the protein-DNA interactions they alter. We investigated evolutionary changes in the duplicated Bric-a-brac (Bab) transcription factors and a key Bab target gene in a GRN underlying the novel dimorphic pigmentation of D. melanogaster and its relatives. It has remained uncertain how Bab was integrated within the pigmentation GRN. Here, we show that the ancestral transcription factor activity of Bab gained a role in sculpting sex-specific pigmentation through the evolution of binding sites in a CRE of the pigment-promoting yellow gene. This work demonstrates how a new trait can evolve by incorporating existing transcription factors into a GRN through CRE evolution, an evolutionary path likely to predominate newly evolved functions of transcription factors.
A Framework for Understanding and Achieving Sustainability of Complex Systems

This article introduces a systems framework for understanding the sustainability of complex adaptive and evolvable systems such as the human social system, viewed as a subsystem of the whole Earth system. The argument is advanced that subsystems of semi-closed supra-systems must fulfil a ‘purpose’ in the context of the larger supra-system in order to achieve sustained continuance. The success of the system in interacting with its environment over an extended time frame depends on that system's ability to regulate its activities, both internal and external so as to remain ‘fit’. The roles of adaptivity and evolvability and the mechanisms of a hierarchical cybernetic governance subsystem in maintaining these are discussed as the means for achieving sustainability in all types of complex systems. An operational definition of sustainability is put forth along with a set of necessary conditions that must be obtained in order for complex systems to achieve it. Copyright © 2017 John Wiley & Sons, Ltd.
Optimizing Internet Transit Routing for Content Delivery Networks

Content delivery networks (CDNs) maintain multiple transit routes from content distribution servers to eyeball ISP networks which provide Internet connectivity to end users. Due to the dynamics of varying performance and pricing on transit routes, CDNs need to implement a transit route selection strategy to optimize performance and cost tradeoffs. In this paper, we formalize the transit routing problem using a multi-attribute objective function to simultaneously optimize end-to-end performance and cost. Our approach allows CDNs to navigate the cost and performance tradeoff in transit routing through a single control knob. We evaluate our approach using real-world measurements from CDN servers located at 19 geographically distributed Internet exchange points. Using our approach, CDNs can reduce transit costs on average by 57% without sacrificing performance.
The use of ambient humidity conditions to improve influenza forecast

Laboratory and epidemiological evidence indicate that ambient humidity modulates the survival and transmission of influenza. Here we explore whether the inclusion of humidity forcing in mathematical models describing influenza transmission improves the accuracy of forecasts generated with those models. We generate retrospective forecasts for 95 cities over 10 seasons in the United States and assess both forecast accuracy and error. Overall, we find that humidity forcing improves forecast performance (at 1-4 lead weeks, 3.8% more peak week and 4.4% more peak intensity forecasts are accurate than with no forcing) and that forecasts generated using daily climatological humidity forcing generally outperform forecasts that utilize daily observed humidity forcing (4.4% and 2.6% respectively). These findings hold for predictions of outbreak peak intensity, peak timing, and incidence over 2- and 4-week horizons. The results indicate that use of climatological humidity forcing is warranted for current operational influenza forecast.
Software for web-based tic suppression training

Exposure and response prevention (ERP) is a first-line behavior therapy for obsessive-compulsive disorder and Tourette syndrome (TS). However, ERP for tic disorders requires intentional tic suppression, which for some patients is difficult even for brief periods. Additionally, practical access to behavior therapy is difficult for many patients, especially those in rural areas. The authors present a simple, working web platform (TicTrainer) that implements a strategy called reward-enhanced exposure and response prevention (RE–ERP). This strategy sacrifices most expert therapist components of ERP, focusing only on increasing the duration of time for which the user can suppress tics through automated differential reinforcement of tic-free periods (DRO). RE–ERP requires an external tic monitor, such as a parent, during training sessions. The user sees increasing digital rewards for longer and longer periods of successful tic suppression, similar to a video game score. TicTrainer is designed with security in mind, storing no personally identifiable health information, and has features to facilitate research, including optional masked comparison of tics during DRO vs. noncontingent reward conditions. A working instance of TicTrainer is available from https://tictrainer.com/
Sweat Equity in U.S. Private Business

In this paper, we first provide evidence that existing measures of business incomes and valuations based on widely-used surveys such as the Survey of Consumer Finances are mismeasured. We then develop a theory disciplined by U.S. national accounts and business census data to measure net incomes and private business sweat equity—which is the value of time to build customer bases, client lists, and other intangible assets. We estimate an aggregate sweat equity value of 0.65 times GDP, with little cross-sectional dispersion in valuations when compared to business net incomes and large cross-sectional dispersion in rates of return. Our estimate of sweat equity is close to the estimate of marketable fixed assets used in production by private businesses, implying a high ratio of intangible to total assets. We use the model to evaluate the impact of greater tax compliance of private businesses and lower tax rates on the net income of both privately held and publicly traded businesses. We find larger sectoral and aggregate effects from the tax policy experiments relative to studies that abstract from private business and, in particular, the accumulation of sweat capital. Finally, we show that our results are robust to including non-pecuniary benefits of business ownership.
Comparing growth in linguistic comprehension and reading comprehension in school-aged children with autism versus typically developing children.

Author(s): Grimm, Ryan P; Solari, Emily J; McIntyre, Nancy S; Zajic, Matthew; Mundy, Peter C | Abstract: Many children with autism spectrum disorders (ASD) struggle with reading comprehension. Linguistic comprehension is an important predictor of reading comprehension, especially as children progress through elementary school and later grades. Yet, there is a dearth of research examining longitudinal relations between linguistic comprehensions in school-age children with ASD compared to typically-developing peers (TD). This study compared the developmental trajectories of linguistic and reading comprehension in samples of children with ASD and age-matched TD peers. Both groups were administered measures of linguistic and reading comprehension multiple times over a 30-month period. Latent growth curve modeling demonstrated children with ASD performed at significantly lower levels on both measures at the first timepoint and these deficits persisted across time. Children with ASD exhibited growth in both skills comparable to their TD peers, but this was not sufficient to enable them to eventually achieve at a level similar to the TD group. Due to the wide age range of the sample, age was controlled and displayed significant effects. Findings suggest linguistic comprehension skills are related to reading comprehension in children with ASD, similar to TD peers. Further, intervention in linguistic comprehension skills for children with ASD should begin early and there may be a finite window in which these skills are malleable, in terms of improving reading comprehension skills. Autism Res 2018, 11: 624-635. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY:There is relatively little research concerning reading comprehension development in children with ASD and how they compare to TD peers. This study found children with ASD began at lower achievement levels of linguistic comprehension and reading comprehension than TD peers, but the skills developed at a similar rate. Intervening early and raising initial levels of linguistic and reading comprehension may enable children with ASD to perform similarly to TD peers over time.
Distinct descending motor cortex pathways and their roles in movement

Activity in the motor cortex predicts movements, seconds before they are initiated. This preparatory activity has been observed across cortical layers, including in descending pyramidal tract neurons in layer 5. A key question is how preparatory activity is maintained without causing movement, and is ultimately converted to a motor command to trigger appropriate movements. Here, using single-cell transcriptional profiling and axonal reconstructions, we identify two types of pyramidal tract neuron. Both types project to several targets in the basal ganglia and brainstem. One type projects to thalamic regions that connect back to motor cortex; populations of these neurons produced early preparatory activity that persisted until the movement was initiated. The second type projects to motor centres in the medulla and mainly produced late preparatory activity and motor commands. These results indicate that two types of motor cortex output neurons have specialized roles in motor control.
Assembling and Disassembling Planar Structures With Divisible and Atomic Components

This paper considers an assembly problem. Let there be two interlocking parts, only one of which may be cut into pieces. How many pieces should we cut the divisible part into to separate the parts using a sequence of rigid-body motions? In this initial exploration, we primarily consider 2-D polygonal parts. This paper presents an algorithm that computes a lower bound on the number of pieces that the divisible part must be cut into. This paper also presents a complete algorithm that constructs a set of cuts and a motion plan for disassembly, yielding an upper bound on the required number of pieces. Applications of the future extension of this paper to 3-D may include robot self-assembly, interlocking 3-D model design, search-and-rescue, packaging, and robotic surgery. Note to Practitioners —This paper presents an opposite problem of immobilization or caging. Given two interlocking parts, only one of which may be cut into pieces. How can we unimmobilize or uncage one from another? We explore this problem in two aspects: the lower bound and the upper bound on the number of pieces that the divisible part must be cut into. This paper is an early theoretical exploration of this problem. We verified our methods in a virtual 2-D environment instead of building physical structures. Extension of this paper to 3-D could have many applications, including robot self-assembly, 3-D fabrication model design, search-and-rescue, packaging, and robotic surgery.
FAM35A associates with REV7 and modulates DNA damage responses of normal and BRCA1‐defective cells

To exploit vulnerabilities of tumors, it is urgent to identify associated defects in genome maintenance. One unsolved problem is the mechanism of regulation of DNA double-strand break repair by REV7 in complex with 53BP1 and RIF1, and its influence on repair pathway choice between homologous recombination and non-homologous end-joining. We searched for REV7-associated factors in human cells and found FAM35A, a previously unstudied protein with an unstructured N-terminal region and a C-terminal region harboring three OB-fold domains similar to single-stranded DNA-binding protein RPA, as novel interactor of REV7/RIF1/53BP1. FAM35A re-localized in damaged cell nuclei, and its knockdown caused sensitivity to DNA-damaging agents. In a BRCA1-mutant cell line, however, depletion of FAM35A increased resistance to camptothecin, suggesting that FAM35A participates in processing of DNA ends to allow more efficient DNA repair. We found FAM35A absent in one widely used BRCA1-mutant cancer cell line (HCC1937) with anomalous resistance to PARP inhibitors. A survey of FAM35A alterations revealed that the gene is altered at the highest frequency in prostate cancers (up to 13%) and significantly less expressed in metastatic cases, revealing promise for FAM35A as a therapeutically relevant cancer marker.
Violation of Field Line Conservation and Associated Spatial Scales in Particle‐in‐Cell Simulations and MMS Data

For the first time, space flight technology exists to detect, in situ, violation of magnetic field line conservation. The violation of magnetic line conservation on scales smaller than the system size is a necessary and sufficient condition for finite magnetic field reconnection. We demonstrate that violation of line conservation produces a detectable, structured signature both in particle-in-cell simulations of reconnection and in data from the Magnetospheric Multi-Scale mission. In particle-in-cell simulations of asymmetric reconnection, the quantity-which we call M-that identifies this violation achieves significant values in electron skin depth-scale layers that extend away from the separator, with higher values emerging on the low-density, high-magnetic-field side of the current sheet. At the separator, M owes largely to perpendicular gradients in the parallel electric field, while it attains its highest values away from the separator in dispersed, layered structures associated with gradients in the perpendicular nonideal electric field and electron transport. Sub-ion scale bipolar forms of the quantity also appear further from the separator. In two MMS burst data intervals detecting the electron diffusion region, we find that M exceeds measurement uncertainties both at the separator and near the separatrices. One interval has highly sheared reconnecting fields and the other a stronger guide field. For one event, we determine the location and scale of M and the inner electron diffusion region relative to electron outflows and the magnetic separatrices. The measure can therefore serve as a potent diagnostic for magnetic reconnection in space measurements.
Environmental and Evolutionary Drivers of the Modular Gene Regulatory Network Underlying Phenotypic Plasticity for Stress Resistance in the Nematode Caenorhabditis remanei

Organisms can cope with stressful environments via a combination of phenotypic plasticity at the individual level and adaptation at the population level. Changes in gene expression can play an important role in both. Significant advances in our understanding of gene regulatory plasticity and evolution have come from comparative studies in the field and laboratory. Experimental evolution provides another powerful path by which to learn about how differential regulation of genes and pathways contributes to both acclimation and adaptation. Here we present results from one such study using the nematode Caenorhabditis remanei. We selected one set of lines to withstand heat stress and another oxidative stress. We then compared transcriptional responses to acute heat stress of both and an unselected control to the ancestral population using a weighted gene coexpression network analysis, finding that the transcriptional response is primarily dominated by a plastic response that is shared in the ancestor and all evolved populations. In addition, we identified several modules that respond to artificial selection by (1) changing the baseline level of expression, (2) altering the magnitude of the plastic response, or (3) a combination of the two. Our findings therefore reveal that while patterns of transcriptional response can be perturbed with short bouts of intense selection, the overall ancestral structure of transcriptional plasticity is largely maintained over time.
Phylogenetically novel uncultured microbial cells dominate Earth microbiomes

To describe a microbe's physiology, including its metabolism, environmental roles, and growth characteristics, it must be grown in a laboratory culture. Unfortunately, many phylogenetically novel groups have never been cultured, so their physiologies have only been inferred from genomics and environmental characteristics. Although the diversity, or number of different taxonomic groups, of uncultured clades has been studied well, their global abundances, or numbers of cells in any given environment, have not been assessed. We quantified the degree of similarity of 16S rRNA gene sequences from diverse environments in publicly available metagenome and metatranscriptome databases, which we show have far less of the culture bias present in primer-amplified 16S rRNA gene surveys, to those of their nearest cultured relatives. Whether normalized to scaffold read depths or not, the highest abundances of metagenomic 16S rRNA gene sequences belong to phylogenetically novel uncultured groups in seawater, freshwater, terrestrial subsurface, soil, hypersaline environments, marine sediment, hot springs, hydrothermal vents, nonhuman hosts, snow, and bioreactors (22% to 87% uncultured genera to classes and 0% to 64% uncultured phyla). The exceptions were human and human-associated environments, which were dominated by cultured genera (45% to 97%). We estimate that uncultured genera and phyla could comprise 7.3 × 1029 (81%) and 2.2 × 1029 (25%) of microbial cells, respectively. Uncultured phyla were overrepresented in metatranscriptomes relative to metagenomes (46% to 84% of sequences in a given environment), suggesting that they are viable. Therefore, uncultured microbes, often from deeply phylogenetically divergent groups, dominate nonhuman environments on Earth, and their undiscovered physiologies may matter for Earth systems. IMPORTANCE In the past few decades, it has become apparent that most of the microbial diversity on Earth has never been characterized in laboratory cultures. We show that these unknown microbes, sometimes called "microbial dark matter," are numerically dominant in all major environments on Earth, with the exception of the human body, where most of the microbes have been cultured. We also estimate that about one-quarter of the population of microbial cells on Earth belong to phyla with no cultured relatives, suggesting that these never-before-studied organisms may be important for ecosystem functions. Author Video: An author video summary of this article is available.
PieAPP: Perceptual Image-Error Assessment Through Pairwise Preference

The ability to estimate the perceptual error between images is an important problem in computer vision with many applications. Although it has been studied extensively, however, no method currently exists that can robustly predict visual differences like humans. Some previous approaches used hand-coded models, but they fail to model the complexity of the human visual system. Others used machine learning to train models on human-labeled datasets, but creating large, high-quality datasets is difficult because people are unable to assign consistent error labels to distorted images. In this paper, we present a new learning-based method that is the first to predict perceptual image error like human observers. Since it is much easier for people to compare two given images and identify the one more similar to a reference than to assign quality scores to each, we propose a new, large-scale dataset labeled with the probability that humans will prefer one image over another. We then train a deep-learning model using a novel, pairwise-learning framework to predict the preference of one distorted image over the other. Our key observation is that our trained network can then be used separately with only one distorted image and a reference to predict its perceptual error, without ever being trained on explicit human perceptual-error labels. The perceptual error estimated by our new metric, PieAPP, is well-correlated with human opinion. Furthermore, it significantly outperforms existing algorithms, beating the state-of-the-art by almost 3A— on our test set in terms of binary error rate, while also generalizing to new kinds of distortions, unlike previous learning-based methods.
Hematopoietic-restricted Ptpn11E76K reveals indolent MPN progression in mice.

Juvenile Myelomonocytic Leukemia (JMML) is a pediatric myeloproliferative neoplasm (MPN) that has a poor prognosis. Somatic mutations in Ptpn11 are the most frequent cause of JMML and they commonly occur in utero. Animal models of mutant Ptpn11 have probed the signaling pathways that contribute to JMML. However, existing models may inappropriately exacerbate MPN features by relying on non-hematopoietic-restricted Cre-loxP strains or transplantations into irradiated recipients. In this study we generate hematopoietic-restricted models of Ptpn11E76K-mediated disease using Csf1r-MCM and Flt3Cre. We show that these animals have indolent MPN progression despite robust GM-CSF hypersensitivity and Ras-Erk hyperactivation. Rather, the dominant pathology is pronounced thrombocytopenia with expanded extramedullary hematopoiesis. Furthermore, we demonstrate that the timing of tamoxifen administration in Csf1r-MCM mice can specifically induce recombinase activity in either fetal or adult hematopoietic progenitors. We take advantage of this technique to show more rapid monocytosis following Ptpn11E76K expression in fetal progenitors compared with adult progenitors. Finally, we demonstrate that Ptpn11E76K results in the progressive reduction of T cells, most notably of CD4+ and naive T cells. This corresponds to an increased frequency of T cell progenitors in the thymus and may help explain the occasional emergence of T-cell leukemias in JMML patients. Overall, our study is the first to describe the consequences of hematopoietic-restricted Ptpn11E76K expression in the absence of irradiation. Our techniques can be readily adapted by other researchers studying somatically-acquired blood disorders.