cssi/SciSciGPT-SciSciNet huggingface dataset:
Effects of Bush Tax Cut and Obama Tax Increase on corporate payout policy and stock returns

This article analyzes the effects of the American Taxpayer Relief Act of 2012 (Obama Tax Increase) and the Jobs and Growth Tax Relief Reconciliation Act of 2003 (Bush Tax Cut) on corporate payout decision and stock returns. Logit and fixed-effect panel data analyses are conducted on all firms listed in NYSE, Amex and NASDAQ in the announcement windows of two, three and four quarters before and after the tax reforms. The results show that the implementation of these tax reforms more persistently affects dividend payments than stock repurchases. It also has a boosting effect on stock returns in the Bush Tax Cut that is 75 % greater than their reducing effect in the Obama Tax Increase, in absolute terms, controlling for dividend payment and stocks repurchase. These effects are robust to different market capitalization sizes. Less solvent firms persistently spend larger dollar amounts in stock repurchases, especially in the announcement of the Bush Tax Cut (+1.11 % per solvency ratio percentage in the [−2Q, +2Q] window). Insolvency is more often significant and with positive impacts on stock returns in the Obama Tax Increase, suggesting that some investors decide to migrate to leveraged-high-growth firms once they realize that some dividend-paying firms could change their dividend policies.
Species sorting along a subsidy gradient alters bacterial community stability

The movement of resources between terrestrial and aquatic habitats has strong effects on ecological processes in recipient ecosystems. Allochthonous inputs modify the quality and quantity of the available resource pool in ways that may alter the composition and stability of recipient communities. Inputs of terrestrial dissolved organic carbon (tDOC) into aquatic ecosystems represent a large influx of resources that has the potential to affect local communities, especially microorganisms. To evaluate the effects of terrestrial inputs on aquatic bacterial community composition and stability, we manipulated the supply rate of tDOC to a set of experimental ponds. Along the tDOC supply gradient, we measured changes in diversity and taxon-specific changes in relative abundance and activity. We then determined community stability by perturbing each pond using a pulse of inorganic nutrients and measuring changes in composition and activity (i.e., responsiveness) along the gradient. Terrestrial DOC supply significantly altered the composition of the active bacterial community. The composition of the active bacterial community changed via decreases in richness and evenness as well as taxon-specific changes in relative abundance and activity indicating species sorting along the gradient. Likewise, the responsiveness of the active bacterial community decreased along the gradient, which led to a more stable active community. We did not, however, observe these changes in diversity and stability in the total community (i.e., active and inactive organisms), which suggests that tDOC supply modifies bacterial community stability through functional not structural changes. Together, these results show that altered aquatic terrestrial linkages can have profound effects on the activity and stability of the base of the food web and thus can alter ecosystem functioning.
Confidence-Weighted Bipartite Ranking

Bipartite ranking is a fundamental machine learning and data mining problem. It commonly concerns the maximization of the AUC metric. Recently, a number of studies have proposed online bipartite ranking algorithms to learn from massive streams of class-imbalanced data. These methods suggest both linear and kernel-based bipartite ranking algorithms based on first and second-order online learning. Unlike kernelized ranker, linear ranker is more scalable learning algorithm. The existing linear online bipartite ranking algorithms lack either handling non-separable data or constructing adaptive large margin. These limitations yield unreliable bipartite ranking performance. In this work, we propose a linear online confidence-weighted bipartite ranking algorithm (CBR) that adopts soft confidence-weighted learning. The proposed algorithm leverages the same properties of soft confidence-weighted learning in a framework for bipartite ranking. We also develop a diagonal variation of the proposed confidence-weighted bipartite ranking algorithm to deal with high-dimensional data by maintaining only the diagonal elements of the covariance matrix. We empirically evaluate the effectiveness of the proposed algorithms on several benchmark and high-dimensional datasets. The experimental results validate the reliability of the proposed algorithms. The results also show that our algorithms outperform or are at least comparable to the competing online AUC maximization methods.
A unified framework for harmonic analysis of functions on directed graphs and changing data

We present a general framework for studying harmonic analysis of functions in the settings of various emerging problems in the theory of diffusion geometry. The starting point of the now classical diffusion geometry approach is the construction of a kernel whose discretization leads to an undirected graph structure on an unstructured data set. We study the question of constructing such kernels for directed graph structures, and argue that our construction is essentially the only way to do so using discretizations of kernels. We then use our previous theory to develop harmonic analysis based on the singular value decomposition of the resulting non-self-adjoint operators associated with the directed graph. Next, we consider the question of how functions defined on one space evolve to another space in the paradigm of changing data sets recently introduced by Coifman and Hirn. While the approach of Coifman and Hirn requires that the points on one space should be in a known one-to-one correspondence with the points on the other, our approach allows the identification of only a subset of landmark points. We introduce a new definition of distance between points on two spaces, construct localized kernels based on the two spaces and certain interaction parameters, and study the evolution of smoothness of a function on one space to its lifting to the other space via the landmarks. We develop novel mathematical tools that enable us to study these seemingly different problems in a unified manner.
The Role of Implicit Theories in Evaluations of “Plus-Size” Advertising

In this research, we examine plus-size female consumers' reactions to the use of plus-size female models in advertising. We demonstrate that not only objective body size but also implicit beliefs about the malleability of one's size affect attitudes toward a product advertised by a plus-size model. Further, we find that this interactive effect is mediated by perceived similarity to the model, and appears only when the plus-size model is used to advertise a body-relevant product. These findings contribute to the burgeoning study of larger-sized female models in advertising and suggest that “plus-size” is not a one-size-fits-all label.
Theory perspective: SCES 2016

New discoveries and developments in almost every area of correlated electron physics were presented at SCES 2016. Here, I provide a personal perspective on some of these developments, highlighting some new ideas in computational physics, discussing the ‘hidden order’ challenges of cuprate and heavy electron superconductors, the mysterious bulk excitations of the topological Kondo insulator and new progress in research on quantum spin ice, iron-based superconductors and quantum criticality.
Accelerator considerations of large circular colliders

As we consider the tremendous physics reaches of the big future circular electron–positron and proton–proton colliders, it might be advisable to keep a close track of what accelerator challenges they face. Good progresses are being made, and yet it is reported here that substantial investments in funding, manpower, as well as a long sustained time to the R&D efforts will be required in preparation to realize these dream colliders.
A design for an electro-optic implementation of a wideband nulling system

A design for an optical implementation of a wideband multibeam nulling antenna system is presented. The basic optical design, which consists of various electro-optical devices connected by optical fibers, can be used in either an IF-to-optical or an RF-to-optical implementation. All the required optical components are either within or slightly beyond current capabilities. In addition, the electro-optical devices have no inherent limitation that will prevent their being upgraded in several years to allow operation at frequencies well into the EHF range. >
Factors influencing temporal patterns in crime in a large American city: A predictive analytics perspective.

Background Improving the accuracy and precision of predictive analytics for temporal trends in crime necessitates a good understanding of the how exogenous variables, such as weather and holidays, impact crime. Methods We examine 5.7 million reported incidents of crime that occurred in the City of Chicago between 2001 to 2014. Using linear regression methods, we examine the temporal relationship of the crime incidents to weather, holidays, school vacations, day-of-week, and paydays. We correct the data for dominant sources of auto-correlation, and we then employ bootstrap methods for model selection. Importantly for the aspect of predictive analytics, we validate the predictive capabilities of our model on an independent data set; model validation has been almost universally overlooked in the literature on this subject. Results We find significant dependence of crime on time of year, holidays, and weekdays. We find that dependence of aggressive crime on temperature depends on the hour of the day, and whether it takes place outside or inside. In addition, unusually hot/cold days are associated with unusual fluctuations upwards/downwards in crimes of aggression, respectively, regardless of the time of year. Conclusions Including holidays, festivals, and school holiday periods in crime predictive analytics software can improve the accuracy and precision of temporal predictions. We also find that including forecasts for temperature may significantly improve short term crime forecasts for the temporal trends in many types of crime, particularly aggressive crime.
Time Series Analysis

The time-domain approach to the modeling and forecasting of time series is outlined. Weakly stationary processes are introduced, and an introduction to autoregressive moving average processes and their properties is given. Estimation, model selection, and prediction with these models are considered, and extensions to multivariate time series, state-space models, and nonlinear models are indicated. Keywords: trend; seasonality; autocovariance function; ARMA process; prediction; multivariate series
TOO MUCH FOR TOO LITTLE: COST ANALYSIS OF CURRENT TOTAL HIP ARTHROPLASTY FOLLOW-UP PRACTICES

Total hip arthroplasty (THA) is a common and extremely beneficial procedure that is being performed more often as the population ages. Current THA follow-up guidelines require large amounts of resources and may not justify their cost with increased patient outcomes. Most problems that would require THA revision will cause symptoms. Late-presenting asymptomatic THAs that are found to require revision are complicated and expensive to address and often lead to poor patient outcomes. Follow-up visits for THA patients are essentially a screening tool to identify asymptomatic THAs that require revision. The rate of asymptomatic THA revision and the subsequent cost of screening for them is not well reported in the literature. Given the relative shortage of orthopaedic resources, efficient use of clinic time should be a priority and inefficient practices should be identified and changed. We calculated the rate of asymptomatic hip revisions over the first twenty years of THA ownership. We further calculated the cost of a single visit to the orthopaedic clinic for follow up of a THA. Finally, we calculated the cost savings of decreasing the follow-up schedule to a total of three visits. The cost savings of foregoing the screening to identify one asymptomatic THA requiring revision is CAD $1.2 million. Asymptomatic THAs requiring revision are rare and, as such, require a large amount of follow up to diagnose. As a screening tool, regular orthopaedic follow up of THA is an inefficient use of resources. Current follow-up guidelines are cost-prohibitive and should be made much less frequent in order to save resources.
Strained GaN quantum-well FETs on single crystal bulk AlN substrates

We report the first realization of molecular beam epitaxy (MBE) grown strained GaN quantum well field-effect transistors on single-crystal bulk AlN substrates. The fabricated double heterostructure FETs exhibit a two-dimensional electron gas (2DEG) density in the excess of 2 × 1013/cm2. The ohmic contacts to the 2DEG channel were formed by the n+ GaN MBE regrowth process, with a contact resistance of 0.13 Ω · mm. The Raman spectroscopy using the quantum well as an optical marker reveals the strain in the quantum well and strain relaxation in the regrown GaN contacts. A 65-nm-long rectangular-gate device showed a record high DC drain current drive of 2.0 A/mm and peak extrinsic transconductance of 250 mS/mm. Small-signal RF performance of the device achieved the current gain cutoff frequency fT∼120 GHz. The DC and RF performances demonstrate that bulk AlN substrates offer an attractive alternative platform for strained quantum well nitride transistors for the future high-voltage and high-power microwave ap...
Regional Bowen ratio controls on afternoon moist convection: A large eddy simulation study

This study examines the effect of the regional Bowen ratio β, the ratio of the domain-averaged surface sensible heat flux (SHF) to latent heat flux (LHF), on afternoon moist convection. With a temporally evolving but spatially uniform surface available energy over a mesoscale domain under a weak capping inversion, we run large eddy simulation of the afternoon convective boundary layer (CBL). We first prescribe a small β of 0.56 (a wet surface) and then the reversed large β of 1.80 (a dry surface) by switching the SHF and LHF fields. The perturbation fields of the fluxes are prescribed with the Fourier spectra of κ− 3 (κ is horizontal wave number; strong mesoscale heterogeneity) and κ0 (homogeneity). The large β cases have strong vertical buoyancy fluxes and produce more vigorous updrafts. In the heterogeneous, large β surface case, with the removal of convective inhibition over a mesoscale subdomain of large SHF, deep convection develops. In the heterogeneous, small β surface case, convective clouds develop but do not progress into precipitating convection. In the homogeneous surface cases, randomly distributed shallow clouds develop with significantly more and thicker clouds in the large β case. (Co)spectral analyses confirm the more vigorous turbulent thermals in the large β cases and reveal that the moisture advection by the surface heterogeneity-induced mesoscale flows makes the correlation between mesoscale temperature and moisture perturbations change from negative to positive, which facilitates the mesoscale pool of high relative humidity air just above the CBL top, a necessary condition for deep convection.
A bioeconomic model for weed management in corn and soybean

Abstract A bioeconomic model of weed management in corn and soybean called WEEDSIM is introduced. WEEDSIM innovates beyond existing decision support models by incorporating weed population dynamics into the decision rule, while at the same time accomodating multiple weed species and control treatments. The associated WFARM model provides a whole-farm shell, making it possible either to modify WEEDSIM recommendations in a context where field time is limiting, or to evaluate the performance of WEEDSIM recommendations over various states of nature. WEEDSIM and WFARM are modularly programmed and rely on external data files, making then easily modified and expanded.
The interaction of fission fragments with electron-beam charged polyfluoroethylene propylene

The interaction of fission fragments with electron-beam-charged polyfluoroethylene propylene (FEP) produces a detectable signal characteristic of the event. Both an electrical signal and luminescence were observed. Fission of /sup 235/U by thermal neutrons produces fission fragments with energies of 60 to 100 MeV that deposit their energy in 14 to 20 mu m of FEP. Aluminized FEP with a thickness of 25.4 mu m was charged to 10/sup -7/ C/cm/sup 2/ and exposed to fission fragments. They produced electrical pulses from charges of approximately 10/sup -16/ C that were induced on the electrodes. Uncoated electrets emitted a flash of light when struck by a fission fragment. Both phenomena were transient in that aging or annealing of the electret eliminated the signal. The size and transient nature of the electrical signal be explained by a charge-intersection model for the interaction of the ions. >
Learning to invert: Signal recovery via Deep Convolutional Networks

The promise of compressive sensing (CS) has been offset by two significant challenges. First, real-world data is not exactly sparse in a fixed basis. Second, current high-performance recovery algorithms are slow to converge, which limits CS to either non-real-time applications or scenarios where massive back-end computing is available. In this paper, we attack both of these challenges head-on by developing a new signal recovery framework we call DeepInverse that learns the inverse transformation from measurement vectors to signals using a deep convolutional network. When trained on a set of representative images, the network learns both a representation for the signals (addressing challenge one) and an inverse map approximating a greedy or convex recovery algorithm (addressing challenge two). Our experiments indicate that the DeepInverse network closely approximates the solution produced by state-of-the-art CS recovery algorithms yet is hundreds of times faster in run time. The tradeoff for the ultrafast run time is a computationally intensive, off-line training procedure typical to deep networks. However, the training needs to be completed only once, which makes the approach attractive for a host of sparse recovery problems.
Pruning The ELM Survey: Characterizing Candidate Low-mass White Dwarfs through Photometric Variability

We assess the photometric variability of nine stars with spectroscopic Teff and log(g) values from the ELM Survey that locate them near the empirical extremely low-mass (ELM) white dwarf instability strip. We discover three new pulsating stars: SDSS J135512.34+195645.4, SDSS J173521.69+213440.6 and SDSS J213907.42+222708.9. However, these are among the few ELM Survey objects that do not show radial velocity variations to confirm the binary nature expected of helium-core white dwarfs. The dominant 4.31-hr pulsation in SDSS J135512.34+195645.4 far exceeds the theoretical cutoff for surface reflection in a white dwarf, and this target is likely a high-amplitude delta Scuti pulsator with an overestimated surface gravity. We estimate the probability to be less than 0.0008 that the lack of measured radial velocity variations in four of eight other pulsating candidate ELM white dwarfs could be due to low orbital inclination. Two other targets exhibit variability as photometric binaries. Partial coverage of the 19.342-hr orbit of WD J030818.19+514011.5 reveals deep eclipses that imply a primary radius > 0.4 solar radii--too large to be consistent with an ELM white dwarf. The only object for which our time series photometry adds support to the ELM white dwarf classification is SDSS J105435.78-212155.9, with consistent signatures of Doppler beaming and ellipsoidal variations. We interpret that the ELM Survey contains multiple false positives from another stellar population at Teff < 9000 K, possibly related to the sdA stars recently reported from SDSS spectra.
Mode Volume, Energy Transfer, and Spaser Threshold in Plasmonic Systems with Gain

We present a unified approach to describe spasing in plasmonic systems modeled by quantum emitters interacting with resonant plasmon mode. We show that spaser threshold implies detailed energy transfer balance between the gain and plasmon mode and derive explicit spaser condition valid for arbitrary plasmonic systems. By defining carefully the plasmon mode volume relative to the gain region, we show that the spaser condition represents, in fact, the standard laser threshold condition extended to plasmonic systems with dispersive dielectric function. For extended gain region, the saturated mode volume depends solely on the system parameters that determine the lower bound of threshold population inversion.
Double/Debiased/Neyman Machine Learning of Treatment Effects

Chernozhukov et al. (2016) provide a generic double/de-biased machine learning (ML) approach for obtaining valid inferential statements about focal parameters, using Neyman-orthogonal scores and cross-fitting, in settings where nuisance parameters are estimated using ML methods. In this note, we illustrate the application of this method in the context of estimating average treatment effects and average treatment effects on the treated using observational data.
Right atrial strain is predictive of clinical outcomes and invasive hemodynamic data in group 1 pulmonary arterial hypertension

Transthoracic echocardiography (TTE) is a practical and widely used tool for risk stratification in pulmonary arterial hypertension (PAH). We hypothesized that right atrial (RA) reservoir function, represented by peak RA systolic strain, correlates with invasive hemodynamic measurements and clinical outcomes in PAH. Patients with group 1 PAH who had TTE within 6 months of index PAH clinic visit and right heart catheterization were included in this retrospective study. Peak RA strain in the 2D apical 4-chamber view was measured with speckle-tracking software. The primary endpoint was a composite of prostacyclin initiation, lung transplantation, and death. RA strain was also measured in healthy control subjects. Among the 37 patients studied, 25 (68%) met the primary endpoint. RA strain was significantly lower among patients who met the primary endpoint than among those who did not (mean 20% vs. 33%, P = 0.002). Strain was lower in PAH patients than in controls (mean 24% vs. 35%, P = 0.0001). RA strain correlated negatively with hemodynamic data including RA pressure (R = −0.31), mean pulmonary arterial pressure (R = −0.33), and pulmonary vascular resistance (R = −0.39), and positively with cardiac index (R = 0.44). In receiver operating characteristic analysis to distinguish between patients meeting the primary endpoint and event-free survivors, RA strain was not significantly different from RA volume, right ventricular (RV) fractional area change, RV basal diameter, or right ventricular systolic pressure (area under the curve 0.82, 0.81, 0.83, 0.86, and 0.97, respectively). Our results demonstrate that RA strain is predictive of clinical outcomes in PAH. Further research is needed to determine if RA strain is independently associated with outcomes in this population.
Engaging Human Rights in the Response to the Evolving Zika Virus Epidemic

In late 2015, an increase in the number of infants born with microcephaly in poor communities in northeast Brazil prompted investigation of antenatal Zika infection as the cause. Zika now circulates in 69 countries, and has affected pregnancies of women in 29 countries.Public health officials, policymakers, and international organizations are considering interventions to address health consequences of the Zika epidemic. To date, public health responses have focused on mosquito vector eradication, sexual and reproductive health services, knowledge and technology including diagnostic test and vaccine development, and health system preparedness.We summarize responses to date and apply human rights and related principles including nondiscrimination, participation, the legal and policy context, and accountability to identify shortcomings and to offer suggestions for more equitable, effective, and sustainable Zika responses.
Workplace Support and Diversity in the Market for Public School Teachers

Mentoring, and to a greater extent support from high-level administrators, has been shown to decrease worker turnover in general, but little is known about its differential impact on minority worke...
An arithmetic property of the set of angles between closed geodesics on hyperbolic surfaces of finite type

For a hyperbolic surface S of finite type we consider the set A(S) of angles between closed geodesics on S. Our main result is that there are only finitely many rational multiples of $$\pi $$ in A(S).
On the volume of the polytope of doubly stochastic matrices

We study the calculation of the volume of the polytope Bn of n × n doubly stochastic matrices (real nonnegative matrices with row and column sums equal to one). We describe two methods. The first involves a decompos ition of the polytope into simplices. The second involves the enumeration of “magic squares”, that is, n × n nonnegative integer matrices whose rows and columns all sum to the same integer. We have used the first method to confirm the previously known values through n = 7. This method can also be used to compute the volumes of faces of Bn For example, we have observed that the volume of a particular face of Bn appears to be a product of Catalan numbers. We have used the second method to find the volume for n = 8, which we believe was not previously known.
Financing of Firms, Labor Reallocation and the Distributional Role of Monetary Policy

We analyze monetary policy in a heterogenous firms environment where cash con- strained firms finance operations through external financing and cash unconstrained firms operate by using internal funds. We show that firms respond differently to shocks: expansionary monetary policy sharply increases the relative employment of the cash constrained firms while positive productivity shocks induce a rise in the relative employment of the cash unconstrained firms. Our analysis points to a clear role of monetary policy in reallocating resources across sectors that differ in their financing capabilities. Furthermore, the predictions of our model match the empirical evidence implying that financially constrained firms react sharply to monetary policy shocks but are less cyclical than unconstrained firms following productivity shocks.
Perceiving and reasoning about liquids using fully convolutional networks

Liquids are an important part of many common manipulation tasks in human environments. If we wish to have robots that can accomplish these types of tasks, they must be able to interact with liquids...
INTRA-OPERATIVE SCIATIC NERVE ASSESSMENT IN COMPLEX TOTAL HIP ARTHROPLASTY USING A HANDHELD NERVE STIMULATOR: A CASE SERIES

Intro Sciatic nerve injury (SNI) is a rare and potentially devastating complication after total hip arthroplasty (THA). Neural monitoring has been found in several studies to be useful in preventing SNI, but can be difficult to practically implement during surgery. In this study, we examine the results of using a handheld nerve stimulator for intraoperative sciatic nerve monitoring during complex THA requiring limb lengthening and/or significant manipulation of the sciatic nerve. Methods We retrospectively reviewed a consecutive series of 11 cases (9 patients, 11 hips) with either severe developmental dysplasia of the hip (Crowe 3–4) or other underlying conditions requiring complex hip reconstruction involving significant leg lengthening and/or nerve manipulation. Sciatic nerve function was monitored intra-operatively with a handheld nerve stimulator by obtaining pre- and post-reduction conduction thresholds during component trialling. The results of nerve stimulation were then used to influence intraoperative decision- making (downsizing components, shortening osteotomy). Results No permanent postoperative sciatic nerve complication occurred, with an average increase of 28.5mm in limb length, ranging from 6 to 51mm. In 2 out of 11 cases, a change in nerve response was identified after trial reduction, which resulted in an alternate surgical plan (femoral shortening osteotomy and downsizing femoral head). In the remainder cases, the stimulator demonstrated a response consistent with the baseline assessment, assuring that the appropriate lengthening was achieved without SNI. One patient had a transient motor and sensory peroneal nerve palsy, which resolved within two weeks. Conclusions The intraoperative use of a handheld nerve stimulator facilitates surgical decision-making and can potentially prevent SNI. The real-time assessment of nerve function allows immediate corrective action to be taken before nerve injury occurs.
Virtual Betti numbers and virtual symplecticity of 4-dimensional mapping tori

In this note, we compute the virtual first Betti numbers of 4-manifolds fibering over $$S^1$$ with prime fiber. As an application, we show that if such a manifold is symplectic with nonpositive Kodaira dimension, then the fiber itself is a sphere or torus bundle over $$S^1$$ . In a different direction, we prove that if the 3-dimensional fiber of such a 4-manifold is virtually fibered then the 4-manifold is virtually symplectic unless its virtual first Betti number is 1.
Generic Representation Theory of the Unipotent Upper Triangular Groups

It is generally believed (and for the most part it is probably true) that Lie theory, in contrast to the characteristic zero case, is insufficient to tackle the representation theory of algebraic groups over prime characteristic fields. However, in this article we show that, for a large and important class of unipotent algebraic groups (namely the unipotent upper triangular groups Un), and under a certain hypothesis relating the characteristic p to both n and the dimension d of a representation (specifically, p ≥ max(n, 2d)), Lie theory is completely sufficient to determine the representation theories of these groups. To finish, we mention some important analogies (both functorial and cohomological) between the characteristic zero theories of these groups and their “generic” representation theory in characteristic p.
Maximizing Stochastic Monotone Submodular Functions

We study the problem of maximizing a stochastic monotone submodular function with respect to a matroid constraint. Because of the presence of diminishing marginal values in real-world problems, our model can capture the effect of stochasticity in a wide range of applications. We show that the adaptivity gap—the ratio between the values of optimal adaptive and optimal nonadaptive policies—is bounded and is equal to e/(e − 1). We propose a polynomial-time nonadaptive policy that achieves this bound. We also present an adaptive myopic policy that obtains at least half of the optimal value. Furthermore, when the matroid is uniform, the myopic policy achieves the optimal approximation ratio of 1 − 1/e. This paper was accepted by Dimitris Bertsimas and Yinyu Ye, optimization.
A distortion based approach for protecting inferences

Eavesdropping attacks in inference systems aim to learn not the raw data, but the system inferences to predict and manipulate system actions. We argue that conventional information security measures can be ambiguous on the adversary's estimation abilities, and adopt instead a distortion based framework that enables to operate over a metric space. We show that requiring perfect distortion-based security is more frugal than requiring perfect information-theoretic secrecy even for block length one codes, offering in some cases unbounded gains. Within this framework, we design algorithms that enable to efficiently use shared randomness, and show that each bit of shared random key is exponentially useful in security.
Charm and bottom heavy baryon mass spectrum from lattice QCD with 2+1 flavors

We present results for the mass spectrum of charm and bottom heavy baryons, using MILC coarse lattice configurations with 2+1 flavors. Clover heavy quark propagators with the Fermilab interpretation and improved staggered light quark propagators are used to construct two point functions with local operators for different flavor and spin states.
The Phenology of Sand Crabs, Lepidopa benedicti (Decapoda: Albuneidae)

ABSTRACT Faulkes, Z., 2017. The phenology of sand crabs, Lepidopa benedicti (Decapoda: Albuneidae). Albuneid sand crabs are widespread on sandy beaches around the world, but because they conceal themselves by digging in sand and are often found at low densities, little is known about their basic biology. Lepidopa species were collected from the beaches of South Padre Island, Texas, on the western coast of Gulf of Mexico, a location that had previously been suggested to act as a population sink. The site contained Lepidopa benedicti and L. websteri, although the latter was extremely rare (collected three times in 5 years). There was significant variation in abundance across the year, with higher densities in summer and lower in winter. Ovigerous females, carrying up to almost 2000 eggs, were found from late spring through summer, with most of the young of the year appearing in autumn. The sex ratio was biased toward females. The average size of L. benedicti in South Texas was smaller than individuals in Fl...
"How Germany's Anti-Keynesianism Has Brought Europe to Its Knees"

This paper investigates the (lack of any lasting) impact of John Maynard Keynes’s General Theory on economic policy-making in Germany. The analysis highlights the interplay between economic history...
Status of Superstring and M-Theory

The first lecture gives a colloquium-level overview of string theory and M-theory. The second lecture surveys various attempts to construct a viable model of particle physics. A recently proposed approach, based on F-theory, is emphasized.
Linear stability analysis of symmetric periodic simultaneous binary collision orbits in the planar pairwise symmetric four-body problem

Abstract We apply the symmetry reduction method of Roberts to numerically analyze the linear stability of a one-parameter family of symmetric periodic orbits with regularizable simultaneous binary collisions in the planar pairwise symmetric four-body problem with a mass m ∈ ( 0 , 1 ] as the parameter. This reduces the linear stability analysis to the computation of two eigenvalues of a 3 × 3 matrix for each m ∈ ( 0 , 1 ] obtained from numerical integration of the linearized regularized equations along only the first one-eighth of each regularized periodic orbit. The results are that the family of symmetric periodic orbits with regularizable simultaneous binary collisions changes its linear stability type several times as m varies over ( 0 , 1 ] , with linear instability for m close or equal to 0.01 , and linear stability for m close or equal to 1 .
EMT, CSCs, and drug resistance: the mechanistic link and clinical implications

The success of anticancer therapy is usually limited by the development of drug resistance. Such acquired resistance is driven, in part, by intratumoural heterogeneity - that is, the phenotypic diversity of cancer cells co-inhabiting a single tumour mass. The introduction of the cancer stem cell (CSC) concept, which posits the presence of minor subpopulations of CSCs that are uniquely capable of seeding new tumours, has provided a framework for understanding one dimension of intratumoural heterogeneity. This concept, taken together with the identification of the epithelial-to-mesenchymal transition (EMT) programme as a critical regulator of the CSC phenotype, offers an opportunity to investigate the nature of intratumoural heterogeneity and a possible mechanistic basis for anticancer drug resistance. In fact, accumulating evidence indicates that conventional therapies often fail to eradicate carcinoma cells that have entered the CSC state via activation of the EMT programme, thereby permitting CSC-mediated clinical relapse. In this Review, we summarize our current understanding of the link between the EMT programme and the CSC state, and also discuss how this knowledge can contribute to improvements in clinical practice.
Quantum-corrected Geometry of Horizon Vicinity

We study the deformation of the horizon-vicinity geometry caused by quantum gravitational effects. Departure from the semi-classical picture is noted, and the fact that the matter part of the action comes at a higher order in Newton's constant than does the Einstein-Hilbert term is crucial for the departure. The analysis leads to a Firewall-type energy measured by an infalling observer for which quantum generation of the cosmological constant is critical. The analysis seems to suggest that the Firewall should be a part of such deformation and that the information be stored both in the horizon-vicinity and asymptotic boundary region. We also examine the behavior near the cosmological horizon.
HIP JOINT PRESERVATION: AVOIDING OR DEFERRING ARTHROPLASTY

Over the past fifteen years hip preservation surgery has rapidly evolved. Improved understanding of the pathomechanics and associated intra-articular degeneration of both hip instability and femoroacetabular impingement have led to improved surgical indications, refined surgical techniques and more effective joint preservation surgical procedures. The periacetabular osteotomy (PAO) was initially introduced by Ganz and colleagues and has become the preferred treatment in North America for pre-arthritic, symptomatic acetabular dysplasia. Both hip arthroscopy and safe surgical dislocation of the hip have been popularised for the treatment of symptomatic femoroacetabular impingement disorders. Hip arthroscopy is effective for focal and\or accessible impingement lesions while the surgical dislocation approach is reserved for nonfocal disease patterns as seen in complex FAI, and residual Perthes and SCFE deformities. Femoroacetabular impingement from major acetabular retroversion can be managed with the PAO if there is coexistent posterosuperior acetabular insufficiency. Short- to mid-term results of these procedures are generally good to excellent for most patients and the complication rates associated with these procedures are very acceptable. Long-term outcomes are best known for the PAO. Several recent studies have documented survivorship rates of 65–90% at 10–20-year follow-up. Certain factors are associated with long-term success including minimal pre-operative radiographic OA, early symptoms, accurate acetabular correction, and younger age. These data strongly suggest that the PAO can defer THA to an older age for most patients while completely avoiding arthroplasty may only be possible in select patients with excellent congruency, no secondary OA and an ideal surgical correction.
Racial Bias in Bail Decisions

This article develops a new test for identifying racial bias in the context of bail decisions—a high-stakes setting with large disparities between white and black defendants. We motivate our analysis using Becker’s model of racial bias, which predicts that rates of pretrial misconduct will be identical for marginal white and marginal black defendants if bail judges are racially unbiased. In contrast, marginal white defendants will have higher rates of misconduct than marginal black defendants if bail judges are racially biased, whether that bias is driven by racial animus, inaccurate racial stereotypes, or any other form of bias. To test the model, we use the release tendencies of quasi-randomly assigned bail judges to identify the relevant race-specific misconduct rates. Estimates from Miami and Philadelphia show that bail judges are racially biased against black defendants, with substantially more racial bias among both inexperienced and part-time judges. We find suggestive evidence that this racial bias is driven by bail judges relying on inaccurate stereotypes that exaggerate the relative danger of releasing black defendants.
Progressive mitochondrial protein lysine acetylation and heart failure in a model of Friedreich's ataxia cardiomyopathy.

Introduction The childhood heart disease of Friedreich’s Ataxia (FRDA) is characterized by hypertrophy and failure. It is caused by loss of frataxin (FXN), a mitochondrial protein involved in energy homeostasis. FRDA model hearts have increased mitochondrial protein acetylation and impaired sirtuin 3 (SIRT3) deacetylase activity. Protein acetylation is an important regulator of cardiac metabolism and loss of SIRT3 increases susceptibility of the heart to stress-induced cardiac hypertrophy and ischemic injury. The underlying pathophysiology of heart failure in FRDA is unclear. The purpose of this study was to examine in detail the physiologic and acetylation changes of the heart that occur over time in a model of FRDA heart failure. We predicted that increased mitochondrial protein acetylation would be associated with a decrease in heart function in a model of FRDA. Methods A conditional mouse model of FRDA cardiomyopathy with ablation of FXN (FXN KO) in the heart was compared to healthy controls at postnatal days 30, 45 and 65. We evaluated hearts using echocardiography, cardiac catheterization, histology, protein acetylation and expression. Results Acetylation was temporally progressive and paralleled evolution of heart failure in the FXN KO model. Increased acetylation preceded detectable abnormalities in cardiac function and progressed rapidly with age in the FXN KO mouse. Acetylation was also associated with cardiac fibrosis, mitochondrial damage, impaired fat metabolism, and diastolic and systolic dysfunction leading to heart failure. There was a strong inverse correlation between level of protein acetylation and heart function. Conclusion These results demonstrate a close relationship between mitochondrial protein acetylation, physiologic dysfunction and metabolic disruption in FRDA hypertrophic cardiomyopathy and suggest that abnormal acetylation contributes to the pathophysiology of heart disease in FRDA. Mitochondrial protein acetylation may represent a therapeutic target for early intervention.
Approximate Program Smoothing Using Mean-Variance Statistics, with Application to Procedural Shader Bandlimiting

This paper introduces a general method to approximate the convolution of an arbitrary program with a Gaussian kernel. This process has the effect of smoothing out a program. Our compiler framework models intermediate values in the program as random variables, by using mean and variance statistics. Our approach breaks the input program into parts and relates the statistics of the different parts, under the smoothing process. We give several approximations that can be used for the different parts of the program. These include the approximation of Dorn et al., a novel adaptive Gaussian approximation, Monte Carlo sampling, and compactly supported kernels. Our adaptive Gaussian approximation is accurate up to the second order in the standard deviation of the smoothing kernel, and mathematically smooth. We show how to construct a compiler that applies chosen approximations to given parts of the input program. Because each expression can have multiple approximation choices, we use a genetic search to automatically select the best approximations. We apply this framework to the problem of automatically bandlimiting procedural shader programs. We evaluate our method on a variety of complex shaders, including shaders with parallax mapping, animation, and spatially varying statistics. The resulting smoothed shader programs outperform previous approaches both numerically, and aesthetically, due to the smoothing properties of our approximations.
Diagnosing Noisy Process Data using Neural Networks

Abstract An account of the application of neural networks for detecting and diagnosing faults during process transients in the presence of random measurement noise is presented The approach employs a feedforward neural network with backpropagation as the learning algorithm. Two representation techniques for capturing dynamic process trend data in the form of a timeseries as well as in the form of a moving average have been developed and used for training the network. Networks with various number of hidden units have been tested and compared with respect to their performance in recall and generalization. The time required for training increases substantially when the level of noise in the training data increases. Trained networks have excellent recall performance even in the presence of noise, in both steady state and dynamic processes. The networks are successful in diagnosing untrained, noisy single fault patterns in a large majority of the steady state and dynamic cases tested.
Single-Dose Captopril Scintigraphy in the Diagnosis of Renovascular Hypertension

Renal scintigraphy with [99mTc]diethylenetriaminepentaacetic acid (DTPA) and/or sodium-iodine-131-o-iodohippurate (HIP) was performed before and after an oral dose of captopril (50 mg) in 18 patients with renovascular hypertension (RVH) due to renal artery stenosis (RAS) and 18 controls. In every patient with RVH, captopril induced, enhanced or sustained abnormal findings on HIP scintigraphy depending on the degree of RAS. With DTPA scintigraphy, renal function decreased after captopril in ten kidneys with RVH-related RAS and adequate baseline renal function, but this phenomenon was not evident in 11 kidneys with RVH and poor renal function. Captopril did not influence HIP or DTPA studies of kidneys with patent renal arteries (patients after successful renal angioplasty, patients with essential hypertension, contralateral kidneys of patients with unilateral RVH) or ipsilateral kidneys with mild and subcritical (less than 60%) RAS in patients without hypertension and/or normal renal vein renin activity. When HIP and DTPA scintigraphy were compared in the same patients, HIP demonstrated greater sensitivity and specificity than DTPA, particularly in patients with poor renal function. HIP scintigraphy before and after a single dose of captopril may provide a rapid sensitive and minimally invasive test for screening patients with hypertension.
Diatom centromeres suggest a mechanism for nuclear DNA acquisition

Centromeres are essential for cell division and growth in all eukaryotes, and knowledge of their sequence and structure guides the development of artificial chromosomes for functional cellular biology studies. Centromeric proteins are conserved among eukaryotes; however, centromeric DNA sequences are highly variable. We combined forward and reverse genetic approaches with chromatin immunoprecipitation to identify centromeres of the model diatom Phaeodactylum tricornutum We observed 25 unique centromere sequences typically occurring once per chromosome, a finding that helps to resolve nuclear genome organization and indicates monocentric regional centromeres. Diatom centromere sequences contain low-GC content regions but lack repeats or other conserved sequence features. Native and foreign sequences with similar GC content to P. tricornutum centromeres can maintain episomes and recruit the diatom centromeric histone protein CENH3, suggesting nonnative sequences can also function as diatom centromeres. Thus, simple sequence requirements may enable DNA from foreign sources to persist in the nucleus as extrachromosomal episomes, revealing a potential mechanism for organellar and foreign DNA acquisition.
Nuclei Segmentation of Fluorescence Microscopy Images Using Three Dimensional Convolutional Neural Networks

Fluorescence microscopy enables one to visualize subcellular structures of living tissue or cells in three dimensions. This is especially true for two-photon microscopy using near-infrared light which can image deeper into tissue. To characterize and analyze biological structures, nuclei segmentation is a prerequisite step. Due to the complexity and size of the image data sets, manual segmentation is prohibitive. This paper describes a fully 3D nuclei segmentation method using three dimensional convolutional neural networks. To train the network, synthetic volumes with corresponding labeled volumes are automatically generated. Our results from multiple data sets demonstrate that our method can successfully segment nuclei in 3D.