cssi/SciSciGPT-SciSciNet huggingface dataset:
Institutional Property-Type Herding in Real Estate Investment Trusts

This study examines whether institutional investors exhibit herding behavior by property type in real estate investment trusts (REITs). Our analysis of changes in institutional portfolio holdings indicates strong evidence of this behavior. We analyze the autocorrelation in aggregate institutional demand, and find that most of it is driven by institutional investors following the trades of others. This herding occurs at the property-type level, and not at the individual firm level. Although momentum trading explains a small amount of this herding, institutional property-type demand is more strongly associated with lagged demand than lagged returns. The results suggest that correlated information signals drive herding in REITs. In addition, we examine the extent to which herding in REIT property types affects price performance in the private real estate market. We find that information transmission resulting from institutional herding in REITs occurs faster in public real estate markets than in private markets.
Regiocontrol in catalytic reductive couplings through alterations of silane rate dependence.

Combinations of ligand, reducing agent, and reaction conditions have been identified that allow alteration in the rate- and regioselectivity-determining step of nickel-catalyzed aldehyde–alkyne reductive couplings. Whereas previously developed protocols involve metallacycle-forming oxidative cyclization as the rate-determining step, this study illustrates that the combination of large ligands, large silanes, and elevated reaction temperature alters the rate- and regiochemistry-determining step for one of the two possible product regioisomers. These modifications render metallacycle formation reversible for the minor isomer pathway, and σ-bond metathesis of the metallacycle Ni–O bond with the silane reductant becomes rate limiting. The ability to tune regiocontrol via this alteration in reversibility of a key step allows highly regioselective outcomes that were not possible using previously developed methods.
Li intercalation into 1D TiS2(en) chains.

The intercalation of metal cations in 2D layered materials allows for the discovery of unique electronic, magnetic and correlated properties. We demonstrate that reversible Li intercalation is also achievable in the hybrid organic/inorganic dimensionally reduced 1D van der Waals solid TiS2(ethylenediamine). Upon intercalation, electrons are injected into the lattice as Ti4+ is reduced to Ti3+ leading to an order of magnitude decrease in electrical resistivity. This reversible intercalation process opens up new opportunities to fine-tune the physical properties in this emerging family of dimensionally reduced materials.
Rational Design of a Second Generation Catalyst for Preparation of Allylsilanes Using the Silyl-Heck Reaction

Using rational ligand design, we have developed of a second-generation ligand, bis(3,5-di-tert-butylphenyl)(tert-butyl)phosphine, for the preparation of allylsilanes using the palladium-catalyzed silyl-Heck reaction. This new ligand provides nearly complete suppression of starting material alkene isomerization that was observed with our first-generation catalyst, providing vastly improved yields of allylsilanes from simple alkene starting materials. The studies quantifying the electronic and steric properties of the new ligand are described. Finally, we report an X-ray crystal structure of a palladium complex resulting from the oxidative addition of Me3SiI using an analogous ligand that provides significant insight into the nature of the catalytic system.
Program evaluation and causal inference with high-dimensional data

In this paper, we provide efficient estimators and honest confidence bands for a variety of treatment effects including local average (LATE) and local quantile treatment effects (LQTE) in data-rich environments. We can handle very many control variables, endogenous receipt of treatment, heterogeneous treatment effects, and function-valued outcomes. Our framework covers the special case of exogenous receipt of treatment, either conditional on controls or unconditionally as in randomized control trials. In the latter case, our approach produces efficient estimators and honest bands for (functional) average treatment effects (ATE) and quantile treatment effects (QTE). To make informative inference possible, we assume that key reduced-form predictive relationships are approximately sparse. This assumption allows the use of regularization and selection methods to estimate those relations, and we provide methods for post-regularization and post-selection inference that are uniformly valid (honest) across a wide range of models. We show that a key ingredient enabling honest inference is the use of orthogonal or doubly robust moment conditions in estimating certain reduced-form functional parameters. We illustrate the use of the proposed methods with an application to estimating the effect of 401(k) eligibility and participation on accumulated assets. The results on program evaluation are obtained as a consequence of more general results on honest inference in a general moment-condition framework, which arises from structural equation models in econometrics. Here, too, the crucial ingredient is the use of orthogonal moment conditions, which can be constructed from the initial moment conditions. We provide results on honest inference for (function-valued) parameters within this general framework where any high-quality, machine learning methods (e.g., boosted trees, deep neural networks, random forest, and their aggregated and hybrid versions) can be used to learn the nonparametric/high-dimensional components of the model. These include a number of supporting auxiliary results that are of major independent interest: namely, we (1) prove uniform validity of a multiplier bootstrap, (2) offer a uniformly valid functional delta method, and (3) provide results for sparsity-based estimation of regression functions for function-valued outcomes.
An Outcome Evaluation of the Indianapolis Community Court

Seeking to alleviate traditional criminal justice system processing for low-level non-violent crimes, community courts have emerged as a viable alternative. These courts use innovative community-based efforts to address the needs of defendants charged with quality-of-life crimes and attempt to improve the surrounding community. Using a retrospective quasi-experimental design, this research examines recidivism outcomes for a sample of 574 defendants who were referred to the Indianapolis Community Court. Repeated-measures ANOVA models were used to assess 1- and 3-year follow-up intervals. Survival models were used to determine whether significant differences between groups exist on the timing of recidivism events. The analysis revealed no statistically significant differences between those individuals who were processed through community court and those processed through traditional courts. The implications of these findings for future research and community court policy and practice are discussed.
Economic Valuation Models for Insurers

Abstract Recently much attention has been given to the approaches insurers undertake in valuing their liabilities and assets. For example, in 1994 the American Academy of Actuaries created a Fair Valuation of Liabilities Task Force to address the issue [see Doll et al. (1998), Reitano (1997), Babbel (1997, 1998b), Babbel and Merrill (1996), and Merrill (1997)]. In 1997, the Academy established a Valuation Law Task Force and a Valuation Tools Working Group to investigate the various valuation approaches extant and to recommend the models best suited to the task. Much of the literature on valuation has focused on the strengths and shortcomings of the various models. Some of the work has addressed larger questions, but in our view it is useful and necessary to provide a taxonomy of approaches and evaluate them in a systematic way in accordance with how well they achieve their aims. In this paper we focus primarily on the economic valuation of insurance liabilities, although we do address some valuation issue...
Viscoelastic Properties of Rubberlike Composite Propellants and Filled Elastomers

Abstract The mechanical properties of rubberlike composite propellants and similar filled elastomers are determined largely by the volume fraction of filler, the visco-elastic properties of the binder, and the interactions between the binder and filler particles. The ratio of the quasi-equilibrium modulus of the composite to that for the unfilled elastomer increases with the volume fraction of the filler, apparently according to an equation of the form proposed by Eilers and Van Dyck. However, the same ratio for the dynamic storage modulus decreases as the frequency is increased or the temperature is decreased. The time-dependent tensile properties can be characterized by stress-strain curves measured at different strain rates and temperatures. Both the small deformation and ultimate properties can be represented by master curves, which are functions only of the experimental time scale, along with a temperature function which is a near-universal function of the glass temperature. Propellants under constan...
Photochemical control of biological processes

Photochemical regulation of biological processes offers a high level of control to study intracellular mechanisms with unprecedented spatial and temporal resolution. This report summarizes the advances made in recent years, focusing predominantly on the in vivo regulation of gene function using irradiation with UV light. The majority of the described applications entail the utilization of photocaging groups installed either on a small molecule modulator of biomolecular function or directly on a biological macromolecule itself.
Private Webmail 2.0: Simple and Easy-to-Use Secure Email

Private Webmail 2.0 (Pwm 2.0) improves upon the current state of the art by increasing the usability and practical security of secure email for ordinary users. More users are able to send and receive encrypted emails without mistakenly revealing sensitive information. In this paper we describe four user interface traits that positively affect the usability and security of Pwm 2.0. In a user study involving 51 participants we validate that these interface modifications result in high usability, few mistakes, and a strong understanding of the protection provided to secure email messages. We also show that the use of manual encryption has no effect on usability or security.
Thermoelectric Properties of Ba1.9Ca2.4Mg9.7Si7: A New Silicide Zintl Phase with the Zr2Fe12P7 Structure Type

Ba1.9Ca2.4Mg9.7Si7 was grown as large crystals from the reaction of silicon with barium and calcium in Mg/Al flux. This compound is a charge-balanced Zintl phase with the Zr2Fe12P7 structure type in hexagonal space group P6 (a = 11.196(2) A, c = 4.4595(9) A); barium occupies the Zr sites, the lighter alkaline earths (Mg, Ca) mix on the Fe sites, and silicon occupies the phosphorus sites. An isostructural germanide (Ba1.2Sr0.9Mg11.9Ge7, a = 11.064(1) A, c = 4.3709(6) A)) was similarly synthesized from reactions of germanium with barium and strontium in Mg/Al flux. Density of states calculations indicate these phases are semimetals, in agreement with their charge-balanced nature. Measurements of electrical resistivity, thermal conductivity, and Seebeck coefficient were carried out from 300–1000 K to investigate the thermoelectric properties of Ba1.9Ca2.4Mg9.7Si7. This compound is an n-type semimetal with low thermal conductivity (2 W/(m·K)), moderate Seebeck coefficient (−200 μV/K at 900 K), and a thermoel...
More problems for Newtonian cosmology

Abstract I point out a radical indeterminism in potential-based formulations of Newtonian gravity once we drop the condition that the potential vanishes at infinity (as is necessary, and indeed celebrated, in cosmological applications). This indeterminism, which is well known in theoretical cosmology but has received little attention in foundational discussions, can be removed only by specifying boundary conditions at all instants of time, which undermines the theory's claim to be fully cosmological, i.e., to apply to the Universe as a whole. A recent alternative formulation of Newtonian gravity due to Saunders (Philosophy of Science 80 (2013) pp. 22-48) provides a conceptually satisfactory cosmology but fails to reproduce the Newtonian limit of general relativity in homogenous but anisotropic universes. I conclude that Newtonian gravity lacks a fully satisfactory cosmological formulation.
Coupling carbon dioxide reduction with water oxidation in nanoscale photocatalytic assemblies

The reduction of carbon dioxide by water with sunlight in an artificial system offers an opportunity for utilizing non-arable land for generating renewable transportation fuels to replace fossil resources. Because of the very large scale required for the impact on fuel consumption, the scalability of artificial photosystems is of key importance. Closing the photosynthetic cycle of carbon dioxide reduction and water oxidation on the nanoscale addresses major barriers for scalability as well as high efficiency, such as resistance losses inherent to ion transport over macroscale distances, loss of charge and other efficiency degrading processes, or excessive need for the balance of system components, to mention a few. For the conversion of carbon dioxide to six-electron or even more highly reduced liquid fuel products, introduction of a proton conducting, gas impermeable separation membrane is critical. This article reviews recent progress in the development of light absorber–catalyst assemblies for the reduction and oxidation half reactions with focus on well defined polynuclear structures, and on novel approaches for optimizing electron transfer among the molecular or nanoparticulate components. Studies by time-resolved optical and infrared spectroscopy for the understanding of charge transfer processes between the chromophore and the catalyst, and of the mechanism of water oxidation at metal oxide nanocatalysts through direct observation of surface reaction intermediates are discussed. All-inorganic polynuclear units for reducing carbon dioxide by water at the nanoscale are introduced, and progress towards core–shell nanotube assemblies for completing the photosynthetic cycle under membrane separation is described.
Economic Development, Flow of Funds and the Equilibrium Interaction of Financial Frictions

We use a variety of different datasets from Thailand to study not only the extremes of micro and macro variables but also within-country flow of funds and labor migration. We develop a general equilibrium model that encompasses regional variation in the type of financial friction and calibrate it to measured variation in regional aggregates. The model predicts substantial capital and labor flows from rural to urban areas even though these differ only in the underlying financial regime. Predictions for micro variables not used directly provide a model validation. Finally, we estimate the impact of a policy of counterfactual, regional isolationism.
Economic Policy and Cotton in Uzbekistan

Uzbekistan is the seventh largest global cotton producer and third largest cotton supplier for world markets. Uzbekistan’s Government policies largely shield cotton producers from world market price signals, and cotton area has changed little over the past decade despite strong international price fluctuations. Government pricing and exchange rate policies tax cotton producers and more than offset the value of input subsidies for cotton growers. The degree of taxation declined for several years after 2000, but increased again in the late 2000s. In the 2009, cotton output dropped as Uzbekistan responded to reduced water availability and increased global food prices with higher taxes on cotton growers. With continued taxation of cotton production, Uzbekistan likely will continue to lose ground to more dynamic cotton exporters like India and Brazil. As a result, USDA’s longrun baseline projections for Central Asia show that the region’s share of world cotton production will continue to fall over the next decade.
Debt Relief: the Development and Poverty Impact

No development issue has quite captured the public imagination in the same way as debt relief. The juxtaposition of the billions of dollars owed and the grinding poverty of the countries concerned deliver an easy campaigning slogan and a seemingly straightforward policy recommendation: cancel the debt. But at the same time debt is also a complex issue, evident in measuring the stream of principal and interest payments over time (the net present value — NPV — of debt with, in turn, its assumptions about discount rates), the arcane language of ‘decision points’ and ’completion points’, the vexed question of what we mean by ‘debt sustainability (and the assorted ratios of debt-to-exports, debt-to-GDP, and debt-to-revenue), not to mention the interconnections with Poverty Reduction Strategy Papers (PRSPs) and the Millennium Development Goals (MDGs). Successive debt relief initiatives from the 1980s onwards with, since the mid-1990s, the heavily indebted poor countries (HIPC) initiative (later ’enhanced’) and now the Multilateral Debt Relief Initiative (MDRI) have steadily become more generous — but just how generous remains a matter of dispute. And not all indebted poor countries are HIPCs, and not all poor countries have large debts. The issue of horizontal equity across countries as well as the problem of moral hazard therefore arise.
Evaluating Methods for Identifying Cancer in Free-Text Pathology Reports Using Various Machine Learning and Data Preprocessing Approaches

Automated detection methods can address delays and incompleteness in cancer case reporting. Existing automated efforts are largely dependent on complex dictionaries and coded data. Using a gold standard of manually reviewed pathology reports, we evaluated the performance of alternative input formats and decision models on a convenience sample of free-text pathology reports. Results showed that the input format significantly impacted performance, and specific algorithms yielded better results for presicion, recall and accuracy. We conclude that our approach is sufficiently accurate for practical purposes and represents a generalized process.
Universal Polarization

A method to polarize channels universally is introduced. The method is based on combining channels of unequal capacities in each polarization step, as opposed to the standard method of combining identical channels. The locations of the good and bad channels that emerge upon polarization are only a function of the polar transform chosen, and are otherwise independent of the channel being polarized. This yields a simple method to design universal polar codes for discrete memoryless channels. It is also shown that the less noisy ordering of channels is preserved under polarization, and thus, a good polar code for a given channel will perform well over a less noisy one.
Resolving key manufacturing challenges in Flip Chip QFN package

FC (Flip Chip) QFN package integrates a flip chip interconnect in a QFN (Quad Flat No-leads) body and combines the electrical efficiency of the flip chip interconnect and thermal efficiency of the QFN package. Other advantages include shorter assembly cycle time vs wirebonded QFN and small chip-to-pkg ratio closest to WCSP in terms of package footprint. The versatility of the flip chip QFN package opens new markets with applications on power management and DC-to-DC converters. Although advantageous as a package, the interconnect and package combination introduces several challenges due to its unique design features. This paper enumerates the manufacturing challenges of flip chip QFN associated with its unique package construction features and their possible solutions to the challenges by selecting the correct materials, defining design rules and performing process optimizations.
Human gene therapy.

Although gene therapy as a treatment for disease holds great promise, progress in developing effective clinical protocols has been slow. The problem lies in the development of safe and efficient gene-delivery systems. This review will evaluate the problems and the potential solutions in this new field of medicine.
Naphthodithiophene-based donor materials for solution processed organic solar cells

Abstract As an emerging donor building block, naphthodithiophene (NDT) is causing more concerns in the field of organic semiconductors. With the rigid and coplanar molecule structure, NDT will exhibit more application space relying on its own advantage for facilitating the charge carrier transport. In this review article, we have summarized the development progress on the NDT-based donor materials for solution processed organic solar cells. Discussions and comments on those representative NDT type materials about structure and property are also presented.
Deep learning for reward design to improve Monte Carlo tree search in ATARI games

Monte Carlo Tree Search (MCTS) methods have proven powerful in planning for sequential decision-making problems such as Go and video games, but their performance can be poor when the planning depth and sampling trajectories are limited or when the rewards are sparse. We present an adaptation of PGRD (policy-gradient for reward-design) for learning a reward-bonus function to improve UCT (a MCTS algorithm). Unlike previous applications of PGRD in which the space of reward-bonus functions was limited to linear functions of hand-coded state-action-features, we use PGRD with a multi-layer convolutional neural network to automatically learn features from raw perception as well as to adapt the non-linear reward-bonus function parameters. We also adopt a variance-reducing gradient method to improve PGRD's performance. The new method improves UCT's performance on multiple ATARI games compared to UCT without the reward bonus. Combining PGRD and Deep Learning in this way should make adapting rewards for MCTS algorithms far more widely and practically applicable than before.
Cobalt(III)-Catalyzed C-H Bond Amidation with Isocyanates.

The first examples of cobalt(III)-catalyzed C–H bond addition to isocyanates are described, providing a convergent strategy for arene and heteroarene amidation. Using a robust air- and moisture-stable catalyst, this transformation demonstrates a broad isocyanate scope and good functional-group compatibility and has been performed on gram scale.
GENDER PERFORMANCE GAPS: QUASI‐EXPERIMENTAL EVIDENCE ON THE ROLE OF GENDER DIFFERENCES IN SLEEP CYCLES

Sleep studies suggest that girls go to sleep earlier, are more active in the morning, and cope with sleep deprivation better than boys. We provide the first causal evidence on how gender differences in sleep cycles can help explain the gender performance gap. We exploit over 240,000 assignment-level grades from a quasi-experiment where students' schedules alternated between morning and afternoon start times each month. Relative to girls, we find that boys' achievement benefits from a later start time. For classes taught at the beginning of the school day, our estimates explain up to 16% of the gender performance gap. (JEL H52, I20, I21)
Phenotypic lentivirus screens to identify functional single domain antibodies.

Manipulation of proteins is key in assessing their in vivo function. Although genetic ablation is straightforward, reversible and specific perturbation of protein function remains a challenge. Single domain antibody fragments, such as camelid-derived VHHs, can serve as inhibitors or activators of intracellular protein function, but functional testing of identified VHHs is laborious. To address this challenge, we have developed a lentiviral screening approach to identify VHHs that elicit a phenotype when expressed intracellularly. We identified 19 antiviral VHHs that protect human A549 cells from lethal infection with influenza A virus (IAV) or vesicular stomatitis virus (VSV), respectively. Both negative-sense RNA viruses are vulnerable to VHHs uniquely specific for their respective nucleoproteins. Antiviral VHHs prevented nuclear import of viral ribonucleoproteins or mRNA transcription, respectively, and may provide clues for novel antiviral reagents. In principle, the screening approach described here should be applicable to identify inhibitors of any pathogen or biological pathway. A lentiviral screening platform for camelid-derived antibody fragments (VHHs) identifies 19 antiviral VHHs that protect human cells from influenza A virus or vesicular stomatitis virus by preventing vRNP nuclear import or mRNA transcription.
A ROTATING PLATFORM TKA: AN EVOLUTION IN DESIGN

Why are total knees being revised? Aseptic loosening, poly wear, and instability account for up to 59% of revision TKA procedures. Younger and more active patients are placing greater demands on total knee arthroplasty (TKA) implants and international registries have documented a much higher rate of TKA failure in this population. Implant designs utilised in the active patient population should focus on optimisation of long term wear properties and minimising interface stress. Instability after TKA, often related to technical concerns at the time of the index procedure, accounts for by far the greatest subset of failures, excluding infection, in the early revision TKA patients ( This surgical demonstration will highlight gap balancing techniques and a new rotating platform TKA system as an option for the active patient population.
Computational investigation of plasma-wall interaction issues in magnetized target fusion

In the concept known as magnetized target fusion (MTF) in the United States and magnitnoye obzhatiye (MAGO) in Russia, a preheated and magnetized target plasma is hydrodynamically compressed to fusion conditions. Because the magnetic field suppresses losses by electron thermal conduction in the fuel during the target implosion heating process, the implosion velocity may be much smaller than in traditional inertial fusion. Hence "liner-on-plasma" magnetically driven using relatively inexpensive electrical pulsed power, may be practical. The relatively dense, hot target plasma, with starting conditions O(10/sup 18/ cm/sup -3/, 100 eV, 100 kG), may spend 10 or more microseconds in contact with a metal wall during formation and compression. Influx of a significant amount of high-Z wall material during this time could lead to excessive cooling by dilution and radiation that would prevent the desired near-adiabatic compression heating of the plasma to fusion conditions. Magnetohydrodynamic (MHD) calculations including detailed effects of radiation, heat conduction, and resistive field diffusion are being done, using several different computer codes, to investigate such plasma-wall interaction issues in ongoing MTF target plasma experiments and in proposed liner-on-plasma MTF experiments.
An Analytical Model-Based Auto-tuning Framework for Locality-Aware Loop Scheduling

HPC developers aim to deliver the very best performance. To do so they constantly think about memory bandwidth, memory hierarchy, locality, floating point performance, power/energy constraints and so on. On the other hand, application scientists aim to write performance portable code while exploiting the rich feature set of the hardware. By providing adequate hints to the compilers in the form of directives appropriate executable code is generated. There are tremendous benefits from using directive-based programming. However, applications are also becoming more and more complex and we need sophisticated tools such as auto-tuning to better explore the optimization space. In applications, loops typically form a major and time-consuming portion of the code. Scheduling these loops involves mapping from the loop iteration space to the underlying platform - for example GPU threads. The user tries different scheduling techniques until the best one is identified. However, this process can be quite tedious and time consuming especially when it is a relatively large application, as the user needs to record the performance of every schedule’s run. This paper aims to offer a better solution by proposing an auto-tuning framework that adopts an analytical model guiding the compiler and the runtime to choose an appropriate schedule for the loops, automatically and determining the launch configuration for each of the loop schedules. Our experiments show that the predicted loop schedule by our framework achieves the speedup of 1.29x on an average against the default loop schedule chosen by the compiler.
Stratigraphy of the north polar layered deposits of Mars from high-resolution topography

NASA Earth and Space Science Fellowship [NNX13AO55H]; NASA's Mars Reconnaissance Orbiter project (HiRISE)
Recognition of multiple objects using geometric hashing techniques

This paper discusses the development of a robust robot vision system for implementation in a flexible assembly cell. The vision system is capable of recognizing the identity and returning the three-dimensional position and orientation of each object in a physical scene. The scenes of interest may consist of one or more (possibly occluded) industrial objects. A typical unstructured factory lighting environment is assumed. The resulting vision system is model-based and learns an object either through CAD data or by physically viewing the object via a black and white CCD intensity image. The geometric representation of the object is generated off-line and stored in a hash table. During recognition, the hash table is accessed to identify the object and return a transformation matrix encoding its three-dimensional pose. The hash table makes use of the straight- and parallel-line invariance properties of the affine approximation to the perspective transform, and allows for the bulk of the computational load to be shifted off-line. A feature point classification approach has been implemented which results in significant reductions in both hash table size and online recognition times. The latest version of the authors' software recognizes relatively flat industrial objects in any three-dimensional configuration and from any viewing angle. Experimental results for multiple real-world objects (such as screwdrivers and pliers) in occluded scenes have resulted in recognition times of less than one second per object. In addition, this geometric hashing technique may be easily extended to the recognition of general three-dimensional objects. >
Understanding citizen reactions and ebola-related information propagation on social media

In severe outbreaks such as Ebola, bird flu and SARS, people share news, and their thoughts and responses regarding the outbreaks on social media. Understanding how people perceive the severe outbreaks, what their responses are, and what factors affect these responses become important. In this paper, we conduct a comprehensive study of understanding and mining the spread of Ebola-related information on social media. In particular, we (i) conduct a large-scale data-driven analysis of geotagged social media messages to understand citizen reactions regarding Ebola; (ii) build information propagation models which measure locality of information; and (iii) analyze spatial, temporal and social properties of Ebola-related information. Our work provides new insights into Ebola outbreak by understanding citizen reactions and topic-based information propagation, as well as providing a foundation for analysis and response of future public health crises.
The Discretization Problem for continuous frames.

Abstract We characterize when a coherent state or continuous frame for a Hilbert space may be sampled to obtain a frame, which solves the discretization problem for continuous frames. In particular, we prove that every bounded continuous frame for a Hilbert space may be sampled to obtain a frame. We give multiple applications to different classes of frames such as scalable frames and Gabor frames.
Tethered capsule endomicroscopy: from bench to bedside at a primary care practice

Due to the relatively high cost and inconvenience of upper endoscopic biopsy and the rising incidence of esophageal adenocarcinoma, there is currently a need for an improved method for screening for Barrett’s esophagus. Ideally, such a test would be applied in the primary care setting and patients referred to endoscopy if the result is suspicious for Barrett’s. Tethered capsule endomicroscopy (TCE) is a recently developed technology that rapidly acquires microscopic images of the entire esophagus in unsedated subjects. Here, we present our first experience with clinical translation and feasibility of TCE in a primary care practice. The acceptance of the TCE device by the primary care clinical staff and patients shows the potential of this device to be useful as a screening tool for a broader population.
Raman study of the vibrational modes in ZnGeN2 (0001)

A Raman spectroscopy study was carried out on ZnGeN2 hexagonal single crystal (0001)-oriented platelets obtained by reaction of gaseous ammonia with a Zn-Ge-Sn liquid alloy at 758 °C. The sample geometry allowed measurement of the A2 and A1 Raman modes. First-principles calculations of the spectra were carried out using an improved pseudopotential. Measurements with crossed polarizers yielded spectra that agreed well with first-principles calculations of the A2 modes. Measurements with parallel polarizers should in principle provide the A1L modes. However, for most of the Raman modes, the LO-TO splitting was calculated to be smaller than could be resolved experimentally, and for the few modes which were predicted to have larger LO-TO splittings, the LO mode was not observed. This absence is tentatively explained in terms of overdamped LO-plasmon coupling.
Boundary Estimates for a Degenerate Parabolic Equation with Partial Dirichlet Boundary Conditions

We study the boundary regularity properties and derive pointwise a priori supremum estimates of weak solutions and their derivatives in terms of suitable weighted $$L^2$$-norms for a class of degenerate parabolic equations that satisfy homogeneous Dirichlet boundary conditions on certain portions of the boundary. Such equations arise in population genetics in the study of models for the evolution of gene frequencies. Among the applications of our results is the description of the structure of the transition probabilities and of the hitting distributions of the underlying gene frequencies process.
Situation Recognition from Multimodal Data

Situation recognition is the problem of deriving actionable insights from heterogeneous, real-time, big multimedia data to benefit human lives and resources in different applications. This tutorial will discuss the recent developments towards converting multitudes of data streams including weather patterns, stock prices, social media, traffic information, and disease incidents into actionable insights.
An aerosol activation metamodel of v1.2.0 of the pyrcel cloud parcel model: development and offline assessment for use in an aerosol–climate model

Abstract. We describe an emulator of a detailed cloud parcel model which has been trained to assess droplet nucleation from a complex, multimodal aerosol size distribution simulated by a global aerosol–climate model. The emulator is constructed using a sensitivity analysis approach (polynomial chaos expansion) which reproduces the behavior of the targeted parcel model across the full range of aerosol properties and meteorology simulated by the parent climate model. An iterative technique using aerosol fields sampled from a global model is used to identify the critical aerosol size distribution parameters necessary for accurately predicting activation. Across the large parameter space used to train them, the emulators estimate cloud droplet number concentration (CDNC) with a mean relative error of 9.2 % for aerosol populations without giant cloud condensation nuclei (CCN) and 6.9 % when including them. Versus a parcel model driven by those same aerosol fields, the best-performing emulator has a mean relative error of 4.6 %, which is comparable with two commonly used activation schemes also evaluated here (which have mean relative errors of 2.9 and 6.7 %, respectively). We identify the potential for regional biases in modeled CDNC, particularly in oceanic regimes, where our best-performing emulator tends to overpredict by 7 %, whereas the reference activation schemes range in mean relative error from −3 to 7 %. The emulators which include the effects of giant CCN are more accurate in continental regimes (mean relative error of 0.3 %) but strongly overestimate CDNC in oceanic regimes by up to 22 %, particularly in the Southern Ocean. The biases in CDNC resulting from the subjective choice of activation scheme could potentially influence the magnitude of the indirect effect diagnosed from the model incorporating it.
MEDIAL PIVOT TKA, ENHANCING SAGITTAL STABILITY

Total joint arthroplasty is an extremely high quality medical intervention with measured benefit to individual patients and society as a whole. However, nearly 20% of patients following total knee arthroplasty (TKA) may report some level of dissatisfaction following surgery. Weight-bearing-in-flexion activities such as squatting and ascending/descending stairs are those activities with which patients most frequently report dissatisfaction. It is assumed that optimal functioning following TKA requires proper femoral and tibial implant positioning in all planes (sagittal, coronal, and axial), proper femoral-tibial balance in the coronal and sagittal plane and durable fixation irrespective of implant design and the manner in which the surgery is executed. Posterior stabilised (PS) and cruciate retaining (CR) TKA designs are the most predominant implants utilised yet their kinematics are infrequently close to normal. In addition, there is little clinical evidence that one design is superior to another. Alternative designs such as bi-cruciate and medially stabilised designs are much less frequently used and much less frequently studied. However, in both cases, isolated centers with relatively small volumes of patients studied have reported outcomes superior to PS and CR designs depending on the metric assessed. With respect to kinematics, bi-cruciate and medially stabilised designs have displayed certain patterns of behavior that more closely mimic the native knee both in-vitro and in-vivo. Normal knee kinematics, as described by Freeman and Pinskerova, includes lateral sided femoral rollback with progressive knee flexion (alternatively thought of as internal tibial rotation with flexion) and sagittal plane stability achieved through the medial compartment. In theory, both optimal sagittal plane stability and internal tibial rotation with progressive flexion (consistent with normal dynamic changes in tibial tubercle – trochlear groove distance) following TKA should optimise weight-bearing-in-flexion kinematics and load transfer. Patient-related satisfaction with such activities might thus reasonably improve and may help explain the separate findings of Pritchett and Hossain regarding outcomes following medially stabilised TKA. Medially stabilised TKA affords sagittal plane stability in mid-flexion and internal tibial rotation with flexion without the complexity and unique failure modes seen following bi-cruciate TKA. The work flow of performing medially stabilised TKA is similar to PS and CR surgical techniques and the surgeon need not climb a steep learning curve. In addition, similar to PS TKA, medial stabilised TKA is applicable to any primary state in which coronal plane balance can be achieved. Further investigation in well-designed trials is necessary to fully develop an understanding of how different contemporary TKA designs might impact patient reported outcome. Larger registry populations of medially stabilised TKA over time are also necessary to best assess survivorship compared to other contemporary designs.
Faculty Mentoring Practices in Academic Emergency Medicine.

Background Mentoring is considered a fundamental component of career success and satisfaction in academic medicine. However, there is no national standard for faculty mentoring in academic emergency medicine and a paucity of literature on the subject. Objectives To conduct a descriptive study of faculty mentoring programs and practices in academic departments of emergency medicine. Methods An electronic survey instrument was sent to 135 department chairs of emergency medicine (EM) in the United States. The survey queried faculty demographics, mentoring practices, structure, training, expectations, and outcome measures. Chi-square and Wilcoxon Rank Sum tests were used to compare metrics of mentoring effectiveness (i.e., number of publications and NIH funding) across mentoring variables of interest. Results Thirty-nine of 135 departments completed the survey, with a heterogeneous mix of faculty classifications. While only 43.6% of departments had formal mentoring programs, many augmented faculty mentoring with project or skills based mentoring (66.7%), peer mentoring (53.8%), and mentoring committees (18%). Although the majority of departments expected faculty to participate in mentoring relationships, only half offered some form of mentoring training. The mean number of faculty publications per department per year was 52.8, and eleven departments fell within the top 35 NIH funded EM departments. There was an association between higher levels of perceived mentoring success and both higher NIH funding (p=0.022) and higher departmental publications rates (p=0.022). In addition, higher NIH funding was associated with mentoring relationships that were assigned (80%), self-identified (20%), or mixed (22%), (p=0.026). Conclusions Our findings help to characterize the variability of faculty mentoring in EM, identify opportunities for improvement, and underscore the need to learn from other successful mentoring programs. This study can serve as a basis to share mentoring practices and stimulate conversation around strategies to improve faculty mentoring in EM. This article is protected by copyright. All rights reserved.
American jihadi terrorism: A comparison of homicides and unsuccessful plots

ABSTRACTWhile the number of American jihadi terrorist attacks remains relatively rare, terrorist plots thwarted by law enforcement have increased since September 11, 2001. Although these law enforcement blocks of would-be terrorists are considered counterterrorism triumphs by the FBI, human rights and civil liberty watch groups have conversely suggested that those who plan for attacks alongside government informants and undercover agents may be unique and essentially dissimilar from terrorists. Underlying this debate is the empirical question of how planned yet unsuccessful attacks and their plotters compare to successful terrorist homicides and their perpetrators. The current study addresses this question by comparatively examining jihadi terrorist homicides and unsuccessful plots occurring in part or wholly on U.S. soil between 1990 and 2014. Data for this study come from the U.S. Extremist Crime Database (ECDB), an open-source database with information on terrorism and extremist crimes. Based on these ...
Parallel heuristics for scalable community detection

Novel parallel heuristics for community detection in large-scale graphs.Multi-threaded implementations using OpenMP.Thorough experimental evaluation of parallel heuristics on a platform with 32 cores. Community detection has become a fundamental operation in numerous graph-theoretic applications. It is used to reveal natural divisions that exist within real world networks without imposing prior size or cardinality constraints on the set of communities. Despite its potential for application, there is only limited support for community detection on large-scale parallel computers, largely owing to the irregular and inherently sequential nature of the underlying heuristics. In this paper, we present parallelization heuristics for fast community detection using the Louvain method as the serial template. The Louvain method is a multi-phase, iterative heuristic for modularity optimization. Originally developed by Blondel et al. (2008), the method has become increasingly popular owing to its ability to detect high modularity community partitions in a fast and memory-efficient manner. However, the method is also inherently sequential, thereby limiting its scalability. Here, we observe certain key properties of this method that present challenges for its parallelization, and consequently propose heuristics that are designed to break the sequential barrier. For evaluation purposes, we implemented our heuristics using OpenMP multithreading, and tested them over real world graphs derived from multiple application domains (e.g., internet, citation, biological). Compared to the serial Louvain implementation, our parallel implementation is able to produce community outputs with a higher modularity for most of the inputs tested, in comparable number or fewer iterations, while providing absolute speedups of up to 16 ? using 32 threads.
Frequency channel delay modulation for interference-robust low data rate communication

We propose a technique for low-data rate (∼ 100 kb/s) millimeter-wave radio communications for applications involving large numbers of users in severe interference environments. The essential principle is to divide large bandwidths into channels having bandwidths which are individually orders of magnitude greater than the message bit rate, apply a direct sequence spread spectrum carrier to each channel, and represent information as time offsets between channels. Among other benefits, this approach is intrinsically robust to multipath fading and delay spread, is intrinsically robust to interference, and is well-suited for low-size/weight/power/cost implementation. In this paper we describe the technique, analyze performance, and describe a simple hardware implementation.
Policy search for multi-robot coordination under uncertainty

We introduce a principled method for multi-robot coordination based on a general model termed a MacDec-POMDP of multi-robot cooperative planning in the presence of stochasticity, uncertain sensing, and communication limitations. A new MacDec-POMDP planning algorithm is presented that searches over policies represented as finite-state controllers, rather than the previous policy tree representation. Finite-state controllers can be much more concise than trees, are much easier to interpret, and can operate over an infinite horizon. The resulting policy search algorithm requires a substantially simpler simulator that models only the outcomes of executing a given set of motor controllers, not the details of the executions themselves and can solve significantly larger problems than existing MacDec-POMDP planners. We demonstrate significant performance improvements over previous methods and show that our method can be used for actual multi-robot systems through experiments on a cooperative multi-robot bartending domain.
Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is the most common and severe form of muscular dystrophy and is caused by mutations in the dystrophin gene. Dystrophin, together with several other protein components, is part of a complex known as the dystrophin–glycoprotein complex (DGC). The DGC plays an essential role in maintaining the structural integrity of the muscle cell membrane by providing a link between the extracellular matrix and the cytoskeleton. The absence of functional dystrophin and the consequent loss of the DGC ultimately lead to chronic muscle damage resulting in progressive muscle weakness seen in DMD patients. There are currently no long-term effective treatments available, and DMD patients usually die from respiratory or cardiac muscle failure in their 20s. Animal models of the disease, including the mdx mouse and cxmd canine model, have been developed to aid in the understanding of the disease mechanism and to test the effectiveness of potential treatments. Clinical trials of several promising experimental strategies, including gene therapy, exon-skipping therapy, and cell-based therapy, are currently under way.