cssi/SciSciGPT-SciSciNet huggingface dataset:
Simple, Fast, Accurate Intent Classification and Slot Labeling for Goal-Oriented Dialogue Systems.

With the advent of conversational assistants, like Amazon Alexa, Google Now, etc., dialogue systems are gaining a lot of traction, especially in industrial setting. These systems typically consist of Spoken Language understanding component which, in turn, consists of two tasks - Intent Classification (IC) and Slot Labeling (SL). Generally, these two tasks are modeled together jointly to achieve best performance. However, this joint modeling adds to model obfuscation. In this work, we first design framework for a modularization of joint IC-SL task to enhance architecture transparency. Then, we explore a number of self-attention, convolutional, and recurrent models, contributing a large-scale analysis of modeling paradigms for IC+SL across two datasets. Finally, using this framework, we propose a class of ‘label-recurrent’ models that otherwise non-recurrent, with a 10-dimensional representation of the label history, and show that our proposed systems are easy to interpret, highly accurate (achieving over 30% error reduction in SL over the state-of-the-art on the Snips dataset), as well as fast, at 2x the inference and 2/3 to 1/2 the training time of comparable recurrent models, thus giving an edge in critical real-world systems.
Spatiotemporal Mode-Locking in Multimode Fiber Lasers

Optical fibers designed to support multiple transverse modes offer opportunities to study wave propagation in a setting that is intermediate between single-mode fiber and free-space propagation. To date, virtually all mode-locked lasers are based on resonators that support a single transverse spatial mode. Recently, the first reports of locking of multiple transverse and longitudinal modes of a fiber laser have been reported [1]. The variety of lasing states, and the potential for complete 3-dimensional control of a lasing field provide new research opportunities. The peak power of spatiotemporally-mode-locked lasers scales faster than the core area, which should lead to unprecedented performance from fiber lasers. The basic concepts of spatiotemporal mode-locking will be explained, and opportunities for future work will be outlined.
EnTAP: Bringing faster and smarter functional annotation to non-model eukaryotic transcriptomes

EnTAP (Eukaryotic Non-Model Transcriptome Annotation Pipeline) was designed to improve the accuracy, speed, and flexibility of functional gene annotation for de novo assembled transcriptomes in non-model eukaryotes. This software package addresses the fragmentation and related assembly issues that result in inflated transcript estimates and poor annotation rates of protein-coding transcripts. Following filters applied through assessment of true expression and frame selection, open-source tools are leveraged to functionally annotate the reduced set of translated proteins. Downstream features include fast similarity search across five repositories, protein domain assignment, orthologous gene family assessment, and Gene Ontology (GO) term assignment. The final annotation integrates across multiple databases and selects an optimal assignment from a combination of weighted metrics describing similarity search score, taxonomic relationship, and informativeness. Researchers have the option to include additional filters to identify and remove contaminants, identify associated pathways, and prepare the transcripts for enrichment analysis. This fully featured pipeline is easy to install, configure, and runs significantly faster than comparable annotation packages. EnTAP is optimized to generate extensive functional information for the gene space of organisms with limited or poorly characterized genomic resources.
Predicted Effects of Severing Enzymes on the Length Distribution and Total Mass of Microtubules

Microtubules are dynamic cytoskeletal polymers whose growth and shrinkage are highly regulated as eukaryotic cells change shape, move, and divide. One family of microtubule regulators includes the ATP-hydrolyzing enzymes spastin, katanin, and fidgetin, which sever microtubule polymers into shorter fragments. Paradoxically, severases can increase microtubule number and mass in cells. Recent work with purified spastin and katanin accounts for this phenotype by showing that, in addition to severing, these enzymes modulate microtubule dynamics by accelerating the conversion of microtubules from their shrinking to their growing states and thereby promoting their regrowth. This leads to the observed exponential increase in microtubule mass. Spastin also influences the steady-state distribution of microtubule lengths, changing it from an exponential, as predicted by models of microtubule dynamic instability, to a peaked distribution. This effect of severing and regrowth by spastin on the microtubule length distribution has not been explained theoretically. To solve this problem, we formulated and solved a master equation for the time evolution of microtubule lengths in the presence of severing and microtubule dynamic instability. We then obtained numerical solutions to the steady-state length distribution and showed that the rate of severing and the speed of microtubule growth are the dominant parameters determining the steady-state length distribution. Furthermore, we found that the amplification rate is predicted to increase with severing, which is, to our knowledge, a new result. Our results establish a theoretical basis for how severing and dynamics together can serve to nucleate new microtubules, constituting a versatile mechanism to regulate microtubule length and mass.
The anthelmintic drug praziquantel activates a schistosome transient receptor potential channel.

The anthelmintic drug praziquantel (PZQ) is used to treat schistosomiasis, a neglected tropical disease that affects over 200 million people worldwide. PZQ causes Ca2+ influx and spastic paralysis of adult worms and rapid vacuolization of the worm surface. However, the mechanism of action of PZQ remains unknown even after 40 years of clinical use. Here, we demonstrate that PZQ activates a schistosome transient receptor potential (TRP) channel, christened Sm.TRPMPZQ, present in parasitic schistosomes and other PZQ-sensitive parasites. Several properties of Sm.TRPMPZQ were consistent with known effects of PZQ on schistosomes, including (i) nanomolar sensitivity to PZQ; (ii) stereoselectivity toward (R)-PZQ; (iii) mediation of sustained Ca2+ signals in response to PZQ; and (iv) a pharmacological profile that mirrors the well-known effects of PZQ on muscle contraction and tegumental disruption. We anticipate that these findings will spur development of novel therapeutic interventions to manage schistosome infections and broader interest in PZQ, which is finally unmasked as a potent flatworm TRP channel activator.
HOOMD-blue: A Python package for high-performance molecular dynamics and hard particle Monte Carlo simulations

Abstract HOOMD-blue is a particle simulation engine designed for nano- and colloidal-scale molecular dynamics and hard particle Monte Carlo simulations. It has been actively developed since March 2007 and available open source since August 2008. HOOMD-blue is a Python package with a high performance C++/CUDA backend that we built from the ground up for GPU acceleration. The Python interface allows users to combine HOOMD-blue with other packages in the Python ecosystem to create simulation and analysis workflows. We employ software engineering practices to develop, test, maintain, and expand the code.
A relational model of data for large shared data banks

Future users of large data banks must be protected from having to know how the data is organized in the machine (the internal representation). A prompting service which supplies such information is not a satisfactory solution. Activities of users at terminals and most application programs should remain unaffected when the internal representation of data is changed and even when some aspects of the external representation are changed. Changes in data representation will often be needed as a result of changes in query, update, and report traffic and natural growth in the types of stored information.Existing noninferential, formatted data systems provide users with tree-structured files or slightly more general network models of the data. In Section 1, inadequacies of these models are discussed. A model based on n-ary relations, a normal form for data base relations, and the concept of a universal data sublanguage are introduced. In Section 2, certain operations on relations (other than logical inference) are discussed and applied to the problems of redundancy and consistency in the user's model.
Conformational dynamics and phase behavior of lipid vesicles in a precisely controlled extensional flow

Lipid vesicles play a key role in fundamental biological processes. Despite recent progress, we lack a complete understanding of the non-equilibrium dynamics of vesicles due to challenges associated with long-time observation of shape fluctuations in strong flows. In this work, we present a flow-phase diagram for vesicle shape and conformational transitions in planar extensional flow using a Stokes trap, which enables control over the center-of-mass position of single or multiple vesicles in precisely defined flows [A. Shenoy, C. V. Rao and C. M. Schroeder, Proc. Natl. Acad. Sci. U. S. A., 2016, 113(15), 3976-3981]. In this way, we directly observe the non-equilibrium conformations of lipid vesicles as a function of reduced volume ν, capillary number Ca, and viscosity contrast λ. Our results show that vesicle dynamics in extensional flow are characterized by the emergence of three distinct shape transitions, including a tubular to symmetric dumbbell transition, a spheroid to asymmetric dumbbell transition, and quasi-spherical to ellipsoid transition. The experimental phase diagram is in good agreement with recent predictions from simulations [V. Narsimhan, A. P. Spann and E. S. Shaqfeh, J. Fluid Mech., 2014, 750, 144]. We further show that the phase boundary of vesicle shape transitions is independent of the viscosity contrast. Taken together, our results demonstrate the utility of the Stokes trap for the precise quantification of vesicle stretching dynamics in precisely defined flows.
A General Framework for Symmetric Property Estimation

In this paper we provide a general framework for estimating symmetric properties of distributions from i.i.d. samples. For a broad class of symmetric properties we identify the {\em easy} region where empirical estimation works and the {\em difficult} region where more complex estimators are required. We show that by approximately computing the profile maximum likelihood (PML) distribution \cite{ADOS16} in this difficult region we obtain a symmetric property estimation framework that is sample complexity optimal for many properties in a broader parameter regime than previous universal estimation approaches based on PML. The resulting algorithms based on these \emph{pseudo PML distributions} are also more practical.
Counting points of slope varieties over finite fields.

The slope variety of a graph is an algebraic set whose points correspond to drawings of that graph. A complement-reducible graph (or cograph) is a graph without an induced four-vertex path. We construct a bijection between the zeroes of the slope variety of the complete graph on $n$ vertices over $\mathbb{F}_2$, and the complement-reducible graphs on $n$ vertices.
Prediction of a wide variety of linear complexions in face centered cubic alloys

Abstract Linear complexions are defect states that have been recently discovered along dislocations in body centered cubic Fe-based alloys. In this work, we use atomistic simulations to extend this concept and explore segregation-driven structural transitions at dislocations in face centered cubic alloys. We identify a variety of stable, nanoscale-size structural and chemical states, which are confined near dislocations and can be classified as linear complexions. Depending on the alloy system and thermodynamic conditions, such new states can preserve, partially modify, or relax the original dislocation cores they were born at. By considering different temperatures and compositions, we construct linear complexion diagrams that are similar to bulk phase diagrams, defining the important conditions for complexion formation while also specifying an expected complexion size and type. Several notable new complexion types were predicted here: (1) nanoparticle arrays comprised of L12 phases in Ni-Fe, Ni-Al, and Al-Zr, (2) replacement of stacking faults with layered complexions comprised of (111) planes from the Cu5Zr intermetallic phase in Cu-Zr, (3) platelet arrays comprised of two-dimensional Guinier-Preston zones in Al-Cu, and finally (4) coexistence of multiple linear complexions containing both Guinier-Preston zones and L12 phases in ternary Al-Cu-Zr. All of these new complexion states are expected to alter material properties and affect the stability of the dislocations themselves, offering a unique opportunity for future materials design.
Randnet: Deep Learning with Compressed Measurements of Images

Principal component analysis, dictionary learning, and auto-encoders are all unsupervised methods for learning representations from a large amount of training data. In all these methods, the higher the dimensions of the input data, the longer it takes to learn. We introduce a class of neural networks, termed RandNet, for learning representations using compressed random measurements of data of interest, such as images. RandNet extends the convolutional recurrent sparse auto-encoder architecture to dense networks and, more importantly, to the case when the input data are compressed random measurements of the original data. Compressing the input data makes it possible to fit a larger number of batches in memory during training. Moreover, in the case of sparse measurements, training is more efficient computationally. We demonstrate that, in unsupervised settings, RandNet performs dictionary learning using compressed data. In supervised settings, we show that RandNet can classify MNIST images with minimal loss in accuracy, despite being trained with random projections of the images that result in a 50% reduction in size. Overall, our results provide a general principled framework for training neural networks using compressed data.
Automated Ransomware Behavior Analysis: Pattern Extraction and Early Detection.

Security operation centers (SOCs) typically use a variety of tools to collect large volumes of host logs for detection and forensic of intrusions. Our experience, supported by recent user studies on SOC operators, indicates that operators spend ample time (e.g., hundreds of man hours) on investigations into logs seeking adversarial actions. Similarly, reconfiguration of tools to adapt detectors for future similar attacks is commonplace upon gaining novel insights (e.g., through internal investigation or shared indicators). This paper presents an automated malware pattern-extraction and early detection tool, testing three machine learning approaches: TF-IDF (term frequency–inverse document frequency), Fisher’s LDA (linear discriminant analysis) and ET (extra trees/extremely randomized trees) that can (1) analyze freshly discovered malware samples in sandboxes and generate dynamic analysis reports (host logs); (2) automatically extract the sequence of events induced by malware given a large volume of ambient (un-attacked) host logs, and the relatively few logs from hosts that are infected with potentially polymorphic malware; (3) rank the most discriminating features (unique patterns) of malware and from the behavior learned detect malicious activity, and (4) allows operators to visualize the discriminating features and their correlations to facilitate malware forensic efforts. To validate the accuracy and efficiency of our tool, we design three experiments and test seven ransomware attacks (i.e., WannaCry, DBGer, Cerber, Defray, GandCrab, Locky, and nRansom). The experimental results show that TF-IDF is the best of the three methods to identify discriminating features, and ET is the most time-efficient and robust approach.
A Game of Nontransitive Dice

Summary. We consider a two-player, simultaneous-move game where each player selects any permissible n-sided die for a fixed integer n. For any n > 3, there is a unique Nash equilibrium in pure stra...
BagNet: Berkeley Analog Generator with Layout Optimizer Boosted with Deep Neural Networks

The discrepancy between post-layout and schematic simulation results continues to widen in analog design due in part to the domination of layout parasitics. This paradigm shift is forcing designers to adopt design methodologies that seamlessly integrate layout effects into the standard design flow. Hence, any simulation-based optimization framework should take into account time-consuming post-layout simulation results. This work presents a learning framework that learns to reduce the number of simulations of evolutionary-based combinatorial optimizers, using a DNN that discriminates against generated samples, before running simulations. Using this approach, the discriminator achieves at least two orders of magnitude improvement on sample efficiency for several large circuit examples including an optical link receiver layout.
A Bayesian framework for estimating human capabilities

Abstract The capabilities approach provides a rich framework for welfare assessment, but its practical relevance is limited by methodological difficulties associated with the measurement of human capabilities. We argue that, unlike existing approaches to capability estimation, Bayesian stochastic frontier analysis (BSFA) is consistent with the key features of the capabilities approach and thus provides a natural framework for estimating capabilities. Using simulated data, we show that BSFA outperforms the leading alternatives (e.g., structural equation models) in comparable settings. We further show that our approach is more flexible than the alternatives: BSFA can provide cardinal representations of entire capability sets and can be used with continuous, discrete, and multivariate outcomes. Finally, we provide an empirical illustration of our estimator by examining the impact of Uganda’s Youth Opportunities Program on the educational capabilities of children in the treated households.
Boolean Function Analogs of Covering Systems

SummaryBob Hough recently disproved a long-standing conjecture of Paul Erdős regarding covering systems. Inspired by his seminal paper, we describe analogs of covering systems to Boolean functions,...
Light-Inducible Recombinases for Bacterial Optogenetics

Optogenetic tools can provide direct and programmable control of gene expression. Light-inducible recombinases, in particular, offer a powerful method for achieving precise spatiotemporal control of DNA modification. However, to-date this technology has been largely limited to eukaryotic systems. Here, we develop optogenetic recombinases for Escherichia coli that activate in response to blue light. Our approach uses a split recombinase coupled with photodimers, where blue light brings the split protein together to form a functional recombinase. We tested both Cre and Flp recombinases, Vivid and Magnet photodimers, and alternative protein split sites in our analysis. The optimal configuration, Opto-Cre-Vvd, exhibits strong blue light-responsive excision and low ambient light sensitivity. For this system we characterize the effect of light intensity and the temporal dynamics of light-induced recombination. These tools expand the microbial optogenetic toolbox, offering the potential for precise control of DNA excision with light-inducible recombinases in bacteria.
Systematic Comparison of High-throughput Single-Cell and Single-Nucleus Transcriptomes during Cardiomyocyte Differentiation

A comprehensive reference map of all cell types in the human body is necessary for improving our understanding of fundamental biological processes and in diagnosing and treating disease. High-throughput single-cell RNA sequencing techniques have emerged as powerful tools to identify and characterize cell types in complex and heterogeneous tissues. However, extracting intact cells from tissues and organs is often technically challenging or impossible, for example in heart or brain tissue. Single-nucleus RNA sequencing provides an alternative way to obtain transcriptome profiles of such tissues. To systematically assess the differences between high-throughput single-cell and single-nuclei RNA-seq approaches, we compared Drop-seq and DroNc-seq, two microfluidic-based 3′ RNA capture technologies that profile total cellular and nuclear RNA, respectively, during a time course experiment of human induced pluripotent stem cells (iPSCs) differentiating into cardiomyocytes. Clustering of time-series transcriptomes from Drop-seq and DroNc-seq revealed six distinct cell types, five of which were found in both techniques. Furthermore, single-cell trajectories reconstructed from both techniques reproduced expected differentiation dynamics. We then applied DroNc-seq to postmortem heart tissue to test its performance on heterogeneous human tissue samples. Our data confirm that DroNc-seq yields similar results to Drop-seq on matched samples and can be successfully used to generate reference maps for the human cell atlas.
Intestine-specific deletion of metal transporter Zip14 (Slc39a14) causes brain manganese overload and locomotor defects of manganism

Impaired manganese (Mn) homeostasis can result in excess Mn accumulation in specific brain regions and neuropathology. Maintaining Mn homeostasis and detoxification is dependent on effective Mn elimination. Specific metal transporters control Mn homeostasis. Human carriers of mutations in the metal transporter ZIP14 and whole body Zip14-knockout (WB-KO) mice display similar phenotypes, including spontaneous systemic and brain Mn overload and motor dysfunction. Initially, it was believed that Mn accumulation due to ZIP14 mutations was caused by impaired hepatobiliary Mn elimination. However, liver-specific Zip14-KO mice did not show systemic Mn accumulation or motor deficits. ZIP14 is highly expressed in the small intestine and is localized to the basolateral surface of enterocytes. Thus, we hypothesized that basolaterally localized ZIP14 in enterocytes provides another route for the elimination of Mn. Using wild-type and intestine-specific Zip14-KO (I-KO) mice, we have shown that ablation of intestinal Zip14 is sufficient to cause systemic and brain Mn accumulation. The lack of intestinal ZIP14-mediated Mn excretion was compensated for by the hepatobiliary system; however, it was not sufficient to maintain Mn homeostasis. When supplemented with extra dietary Mn, I-KO mice displayed some motor dysfunctions and brain Mn accumulation based on both MRI imaging and chemical analysis, thus demonstrating the importance of intestinal ZIP14 as a route of Mn excretion. A defect in intestinal Zip14 expresssion likely could contribute to the Parkinson-like Mn accumulation of manganism.NEW & NOTEWORTHY Mn-induced parkinsonism is recognized as rising in frequency because of both environmental factors and genetic vulnerability; yet currently, there is no cure. We provide evidence in an integrative animal model that basolaterally localized ZIP14 regulates Mn excretion and detoxification and that deletion of intestinal ZIP14 leads to systemic and brain Mn accumulation, providing robust evidence for the indispensable role of intestinal ZIP14 in Mn excretion.
Interaction of Aβ42 with Membranes Triggers the Self-Assembly into Oligomers.

The self-assembly of amyloid β (Aβ) proteins into oligomers is the major pathogenic event leading to Alzheimer’s disease (AD). Typical in vitro experiments require high protein concentrations, whereas the physiological concentration of Aβ is in the picomolar to low nanomolar range. This complicates the translation of results obtained in vitro to understanding the aggregation process in vivo. Here, we demonstrate that Aβ42 self-assembles into aggregates on membrane bilayers at low nanomolar concentrations - a pathway in which the membrane plays the role of a catalyst. Additionally, physiological ionic conditions (150 mM NaCl) significantly enhance on-membrane aggregation, leading to the rapid formation of oligomers. The self-assembly process is reversible, so assembled aggregates can dissociate from the membrane surface into the bulk solution to further participate in the aggregation process. Molecular dynamics simulations demonstrate that the transient membrane-Aβ interaction dramatically changes the protein conformation, facilitating the assembly of dimers. The results indicate peptide–membrane interaction is the critical step towards oligomer formation at physiologically low protein concentrations.
Brain Differences Associated with Self-Injurious Thoughts and Behaviors: A Meta-Analysis of Neuroimaging Studies

This meta-analysis aims to evaluate whether the extant literature justifies any definitive conclusions about whether and how SITBs may be associated with brain differences. A total of 77 papers (N = 4,903) published through January 1, 2019 that compared individuals with and without SITBs were included, resulting in 882 coordinates. A pooled meta-analysis assessing for general risk for SITBs indicated a lack of convergence on structural differences. When all types of control groups were considered, functional differences in the left posterior cingulate cortex (PCC), right amygdala, left hippocampus, and right thalamus were significant using multi-level kernel density analysis (pcorrected < 0.05) but nonsignificant using activation-likelihood estimation. These results suggest that a propensity for internally-oriented, emotional processing coupled with under-active pain processing could potentially underlie SITBs, but additional research is needed to test this possibility. Separate analyses for types of SITBs suggested that the brain differences associated with deliberate self-harm were consistent with the overall findings. Checkered moderator effects were detected. Overall, the meta-analytic evidence was not robust. More studies are needed to reach definitive conclusions about whether SITBs are associated with brain differences.
Sector bias in public programs: US nonprofit hospitals

This study investigates whether the public perceives nonprofit organizations as different from private for-profit and public organizations and whether introducing new performance management systems would provide positive credits to the organization. Using two randomized survey experiments on US hospitals (one with an adult sample and the other with a student sample), we replicate the study of Hvidman & Andersen (2016) in Denmark with an extension of adding a nonprofit organization cue. The results show no sectoral differences among the hospitals and no positive feedback for adopting a new performance management system.
What the hands tell us about mathematical learning: A synthesis of gesture use in mathematics instruction

Abstract Mathematical achievement is an early predictor of students’ academic outcomes, and mathematics achievement continues to be important throughout life. Thus, it is essential to examine instructional methods that enhance mathematical learning. One method that may impact mathematical learning is the use of gestures, yet a comprehensive methodical review of the data has not been conducted. The current study examined the impact that gestures have on student learning when educators use gestures during mathematical instruction and educators’ perception of student mathematical knowledge when students use gestures. A systematic search was conducted to assemble research studies that evaluated the use of gestures in mathematical instruction with students in preschool to 12th grade. Empirical data from 35 research articles indicate that gestures used by students or educators that enhance verbal instruction can increase student mathematical performance and memory. Furthermore, it is practical to teach students and educators to use gestures effectively during mathematical learning.
Spectral analysis of 2D outlier layout

Thompson's partition of a cyclic subnormal operator into normal and completely non-normal components is combined with a non-commutative calculus for hyponormal operators for separating outliers from the cloud, in rather general point distributions in the plane. The main result provides exact transformation formulas from the power moments of the prescribed point distribution into the moments of the uniform mass carried by the cloud. The proposed algorithm solely depends on the Hessenberg matrix associated to the original data. The robustness of the algorithm is reflected by the insensitivity of the output under trace class, or by a theorem of Voiculescu, under certain Hilbert-Schmidt class, additive perturbations of the Hessenberg matrix.
Dynamic Evolution of Euchromatic Satellites on the X Chromosome in Drosophila melanogaster and the simulans Clade.

Satellite DNAs (satDNAs) are among the most dynamically evolving components of eukaryotic genomes and play important roles in genome regulation, genome evolution, and speciation. Despite their abundance and functional impact, we know little about the evolutionary dynamics and molecular mechanisms that shape satDNA distributions in genomes. Here, we use high-quality genome assemblies to study the evolutionary dynamics of two complex satDNAs, Rsp-like and 1.688 g/cm3, in Drosophila melanogaster and its three nearest relatives in the simulans clade. We show that large blocks of these repeats are highly dynamic in the heterochromatin, where their genomic location varies across species. We discovered that small blocks of satDNA that are abundant in X chromosome euchromatin are similarly dynamic, with repeats changing in abundance, location, and composition among species. We detail the proliferation of a rare satellite (Rsp-like) across the X chromosome in D. simulans and D. mauritiana. Rsp-like spread by inserting into existing clusters of the older, more abundant 1.688 satellite, in events likely facilitated by microhomology-mediated repair pathways. We show that Rsp-like is abundant on extrachromosomal circular DNA in D. simulans, which may have contributed to its dynamic evolution. Intralocus satDNA expansions via unequal exchange and the movement of higher order repeats also contribute to the fluidity of the repeat landscape. We find evidence that euchromatic satDNA repeats experience cycles of proliferation and diversification somewhat analogous to bursts of transposable element proliferation. Our study lays a foundation for mechanistic studies of satDNA proliferation and the functional and evolutionary consequences of satDNA movement.
Characterization of OA development between sexes in the rat medial meniscal transection model

Summary Objective Osteoarthritis (OA) is a chronic degenerative disease of the joints characterized by articular cartilage degradation. While clear sex differences exist in human OA development, most pre-clinical research has been conducted solely in male animals, limiting generalizability of findings to both sexes. The objective of this study was to determine if sex impacts the progression and severity of OA in the rat medial meniscal tear (MMT) preclinical model used to surgically induce OA. It was hypothesized that differences would be observed between males and females following MMT surgery. Design An MMT model was employed in male and female Lewis rats to induce OA. Animals were euthanized 3 weeks post-surgery and EPIC-μCT was used to quantitatively evaluate articular cartilage structure and composition, osteophyte volumes and subchondral bone structure. Results Analysis of medial 1/3 articular cartilage, showed increased cartilage thickness and proteoglycan loss in the MMT of both sexes, when compared to sham. Both male and female MMT groups also saw increased subchondral bone mineral density and larger osteophyte volumes. Significant interactions between sex and OA development were seen in normalized cartilage volume (larger in females), and normalized total osteophyte volumes (larger in males). Conclusion This study demonstrates the viability of both sexes in the rat MMT preclinical OA model. Though clear differences exist, this model can be used to model OA development and evaluate sex as a factor in the efficacy of OA therapeutics.
Interpreting Effect Sizes of Education Interventions.

Researchers commonly interpret effect sizes by applying benchmarks proposed by Jacob Cohen over a half century ago. However, effects that are small by Cohen’s standards are large relative to the im...
Compressibility of Natural Rubber at Pressures Below 500 KG/CM2

The specific volumes of unvulcanized natural rubber and of a peroxide-cured vulcanizate of natural rubber were measured at pressures of 1-500 kg/cm2 at temperatures from 0 to 25 °C. Observations on mercury-filled dilatometers were made through a window in the pressure system. No time effects or hysteresis phenomena were observed. The specific volume V in cm3/e over the range studied can be represented by V=V0,25{1+A(t-25)}{1+[α25+k1(t-25)]P+[β25+k2(t-25)]P2} where P is the pressure in kg/cm2, and t the temperature in °C. The constants for the unvulcanized and for the peroxide-cured samples are: V0,25= 1.0951 and 1.1032 cm3/g;104A = 6.54 and 6.36 per degree;106α25= -50.5 and -50.4 (kg/cm2)-1;106k1 = -0.227 and -0.203 per degree;109β25= 10 and 11.5 (kg/cm2)-2;and 109k2=0.048 and 0.073 per degree, respectively. The compressibility of unvulcanized natural rubber at 25° and 1 kg/cm2 is thus 50.5×10-6 (kg/cm2)-1 falling to 40.6×10-6 (kg/cm2) -1 at a pressure of 500 kg/cm2. It is concluded that a low degree of vulcanization produces no significant changes in the constants listed. The values are not far different from those obtained by extrapolating to zero sulfur content the observations of Scott on the rubbersulfur system. Calculations of values of compressibility (and its reciprocal the bulk modulus), "internal pressure", bulk wave velocity, difference between specific heats, and several other physical properties are in reasonable agreement with those obtained by direct observation by other workers. For the prediction of values at pressures above 500 kg/cm2 the use of the Tait equation is recommended.
Novel Chemical Mixtures for Hydrogen Generation by Combustion

*† ‡ Fuel cells are attractive power sources for various terrestrial and aerospace applications, since they provide much higher specific energy than batteries. Their deployment, however, is hindered by the lack of efficient methods for hydrogen storage. Metal borohydrides, such as sodium borohydride, are efficient hydrogen-storing compounds but their use requires either expensive catalysts or mixing with solid oxidizer salts, which can produce harmful byproducts. To solve this problem, we propose sodium borohydride/aluminum/water mixtures for combustion-based generation of hydrogen. In the proposed mixtures, the highly exothermic reaction of aluminum with water assists hydrolysis of sodium borohydride, eliminating the need of catalyst. Upon ignition, such mixtures exhibit selfsustained propagation of combustion wave with simultaneous release of hydrogen stored in sodium borohydride and water. We report mixture ingredients and sodium borohydride/metal mass ratios required for stable generation of hydrogen, with ~7 wt% yield and environmentally benign solid byproducts.
SANTLR: Speech Annotation Toolkit for Low Resource Languages.

While low resource speech recognition has attracted a lot of attention from the speech community, there are a few tools available to facilitate low resource speech collection. In this work, we present SANTLR: Speech Annotation Toolkit for Low Resource Languages. It is a web-based toolkit which allows researchers to easily collect and annotate a corpus of speech in a low resource language. Annotators may use this toolkit for two purposes: transcription or recording. In transcription, annotators would transcribe audio files provided by the researchers; in recording, annotators would record their voice by reading provided texts. We highlight two properties of this toolkit. First, SANTLR has a very user-friendly User Interface (UI). Both researchers and annotators may use this simple web interface to interact. There is no requirement for the annotators to have any expertise in audio or text processing. The toolkit would handle all preprocessing and postprocessing steps. Second, we employ a multi-step ranking mechanism facilitate the annotation process. In particular, the toolkit would give higher priority to utterances which are easier to annotate and are more beneficial to achieving the goal of the annotation, e.g. quickly training an acoustic model.
Scattering Theory for the Quantum Envelope of a Classical System

Classical dynamics, reformulated in terms of its quantum envelope is studied for the stationary states of the interacting system. The dynamical variable of ``elapsed time`` plays a crucial role in this study. It is shown that the perturbation series for the elapsed time can be summed in various simple cases even when standard perturbation series diverge. For the special class of systems where the interactions fall off sufficiently fast at infinity one could define ``in`` and ``out`` states; and consequently the wave matrices and scattering matrices. The scattering phase shifts bear a simple relation to the time delay in scattering.
Further analysis of electronic states in the muffin-tin model of a disordered alloy

Several new results on the evaluation of the spectral function $A(\stackrel{\ensuremath{\rightarrow}}{\mathrm{k}},E)$ and average density of states $\ensuremath{\rho}(E)$ in a realistic model of a substitutional binary alloy are presented. This work is primarily concerned with the conditions under which a given approach can be relied upon to yield a non-negative spectrum. In the average $t$ matrix and coherent-potential approximations, a link is established between the sign of $A(\stackrel{\ensuremath{\rightarrow}}{\mathrm{k}},E)$ and the Argand diagram for the energy-shell matrix elements ${\ensuremath{\tau}}_{L}$ of the effective atomic scattering operators: If ${\ensuremath{\tau}}_{L}$ lies within the unitarity circle, then $A(\stackrel{\ensuremath{\rightarrow}}{\mathrm{k}},E)g0$. The connection between this result and our earlier work on the optical theorem is shown to require a renormalization of certain free-electron singularities. Finally, an independent proof is outlined, based on the Lloyd equations, that the coherent potential density of states is always non-negative.
Explaining Episodes of Growth Accelerations, Decelerations, and Collapses in Western Africa

The growth literature has had problems explaining the "sub-Saharan African growth dummy" in cross-country regressions. Instead of taking the usual approach of focusing on long-run growth and assuming that sub-Saharan countries have homogenous parameters in growth regressions, we concentrate our analysis on episodes of growth turnarounds (identifying growth accelerations, decelerations, and collapses) and use only West African countries in our sample. Using probits for a group of 22 Western African economies for the period 1960–2006, we find that growth accelerations are most clearly associated with external shocks, economic liberalization, political stability, and closeness to the coast; decelerations occurred during short-lived regimes and when corruption indices weakened; and collapses are linked to external shocks, falling domestic credit, and proximity to the coast.
The structure of a cometary Type I tail: Ground‐based and ice observations of P/Giacobini‐Zinner

The in situ magnetic field and plasma measurements from the International Cometary Explorer (ICE) Mission obtained on September 11, 1985 are compared with CCD images of P/Giacobini-Zinner (G-Z) acquired with the 3.6 m Canada-France-Hawaii Telescope (CFHT) on Mauna Kea, Hawaii and a slit spectrogram from Lick Observatory during the same period. The CFHT image at ∼3.5 hr after the ICE encounter showed a short central ion tail with a diameter of ∼3 × 10³ km and a length of ∼2 × 104 km as observed in the H2O+ bandpass centered at 7025 A. There was no distinct evidence of fine structure or ray activity. The Lick spectrogram of the H2O+ emissions taken ∼0.5 hr post-encounter with the slit perpendicular to the sun-comet line showed an ion tail with a diameter of 1.2 × 104 km. The ICE observations revealed a well defined 9.6 × 10³ km diameter magnetotail composed of two magnetic lobes in pressure equilibrium with a high beta central plasma sheet. These differing measures of tail width are found to be mutually consistent if the ion emissions observed at Earth originate in a slab-shaped plasma sheet whose orientation is controlled by the direction of the interplanetary magnetic field. The results of this study also suggest that some thinning and thickening of cometary type I tails, usually attributed to plasma instabilities, may be due to changes in the angle at which the plasma sheet is viewed as IMF direction varies.
Insights on Variance Estimation for Blocked and Matched Pairs Designs

Evaluating blocked randomized experiments from a potential outcomes perspective has two primary branches of work. The first focuses on larger blocks, with multiple treatment and control units in ea...
Plumbagin-induced apoptosis in human prostate cancer cells is associated with modulation of cellular redox status and generation of reactive oxygen species

3830 Plumbagin (5-hydroxy-2-methyl-1, 4-naphthoquinone) occurs naturally in the herb Plumbago zeylanica L., which has been safely used for centuries in Indian Ayurvedic and traditional oriental medicine practices for the treatment of various ailments, including rheumatoid arthritis, acne, and microbial infections. Plumbagin has attracted a great deal of research interest due to its diverse pharmacological effects. The known pharmacological effects of plumbagin or Plumbago zeylanica extract include anti-leishmanial, anti-bacterial, anti-fungal, anti-allergic, hypolipidaemic, anti-atherosclerotic, and anticancer effects. For instance, dietary feeding of 200 ppm plumbagin decreased the incidence and multiplicity of azoxymethane-induced intestinal carcinogenesis in rats. We now demonstrate that plumbagin suppresses growth of cultured human prostate cancer cells (PC-3, LNCaP, and C4-2) irrespective of their androgen responsiveness or p53 status. The viability of each cell line was decreased significantly by treatment with plumbagin at pharmacologically relevant concentrations. Contrary to previous reports, plumbagin-mediated decrease in prostate cancer cell viability was not due to perturbations in cell cycle progression. Instead, plumbagin-mediated decrease in cell viability correlated with apoptosis induction characterized by appearance of sub-diploid apoptotic fraction and release of histone-associated DNA fragments into the cytosol. The plumbagin-induced apoptosis was associated with generation of reactive oxygen species (ROS) and depletion of intracellular glutathione levels. Pretreatment of cells with antioxidants inhibited plumbagin-mediated ROS generation as well as release of histone-associated DNA fragments into the cytosol. Plumbagin treatment also resulted in alteration of expression of genes responsible for ROS metabolism, including superoxide dismutase 2 (Mn-SOD) as revealed by RT2 Superarray analyses. Activity and protein levels of Mn-SOD were reduced by treatment with plumbagin in a dose-dependent manner. In conclusion, the present study reveals that the plumbagin-induced apoptosis in human prostate cancer cells is mediated by modulation of cellular redox status and ROS generation (supported in part by NCI grant CA115498).
Compliance-Time-Temperature Relationships from Indentation Measurements on a Pure-Gum Rubber Vulcanizate

Abstract Previous work on the calculation of shear compliance J (limit of the ratio of strain to stress at zero deformation) from observations of the indentation of a flat natural rubber surface by a rigid sphere has been extended over greater ranges of time, temperature, and state of vulcanization. The extreme ranges of time were 5 sec to 23.5 hr and of temperature −67 to +100° C. The curves of JT against log t−60 (where t−60 is the equivalent time at −60° C and T is in °K) were sigmoid with a region of maximum slope and continuing through a region of minimum slope extending over about 7 decades. In contrast with predictions of the Williams, Landel, and Ferry equation, the empirically determined shift of abscissa necessary to give a single JT curve was found to be a linear function of T−1 with a slope corresponding to an “apparent activation energy” of 36.9 kcal (°K)− (mole)−1 (154.5 k.J (°K)−(mole)−1).
Scalable Bid Landscape Forecasting in Real-Time Bidding

In programmatic advertising, ad slots are usually sold using second-price (SP) auctions in real-time. The highest bidding advertiser wins but pays only the second highest bid (known as the winning price). In SP, for a single item, the dominant strategy of each bidder is to bid the true value from the bidder’s perspective. However, in a practical setting, with budget constraints, bidding the true value is a sub-optimal strategy. Hence, to devise an optimal bidding strategy, it is of utmost importance to learn the winning price distribution accurately. Moreover, a demand-side platform (DSP), which bids on behalf of advertisers, observes the winning price if it wins the auction. For losing auctions, DSPs can only treat its bidding price as the lower bound for the unknown winning price. In literature, typically censored regression is used to model such partially observed data. A common assumption in censored regression is that the winning price is drawn from a fixed variance (homoscedastic) uni-modal distribution (most often Gaussian). However, in reality, these assumptions are often violated. We relax these assumptions and propose a heteroscedastic fully parametric censored regression approach, as well as a mixture density censored network. Our approach not only generalizes censored regression but also provides flexibility to model arbitrarily distributed real-world data. Experimental evaluation on the publicly available dataset for winning price estimation demonstrates the effectiveness of our method. Furthermore, we evaluate our algorithm on one of the largest demand-side platform and significant improvement has been achieved in comparison with the baseline solutions.
Local rigidity of Lyapunov spectrum for toral automorphisms

We study the regularity of the conjugacy between an Anosov automorphism L of a torus and its small perturbation. We assume that L has no more than two eigenvalues of the same modulus and that L4 is irreducible over ℚ. We consider a volume-preserving C1-small perturbation f of L. We show that if Lyapunov exponents of f with respect to the volume are the same as Lyapunov exponents of L, then f is C1+Holder conjugate to L. Further, we establish a similar result for irreducible partially hyperbolic automorphisms with two-dimensional center bundle.
The Edge of Depth: Explicit Constraints Between Segmentation and Depth

In this work we study the mutual benefits of two common computer vision tasks, self-supervised depth estimation and semantic segmentation from images. For example, to help unsupervised monocular depth estimation, constraint from semantic segmentation has been explored implicitly such as sharing and transforming features. In contrast, we propose to explicitly measure the border consistency between segmentation and depth and minimize it in a greedy manner by iteratively supervising the network towards a locally optimal solution. Partially this is motivated by our observation that semantic segmentation even trained with limited ground truth (200 images of KITTI) can offer more accurate border than that of any (monocular or stereo) image-based depth estimation. Through extensive experiments, our proposed approach advance the state of the art on unsupervised monocular depth estimation in the KITTI benchmark.