cssi/SciSciGPT-SciSciNet huggingface dataset:
On the Capacity of One-Sided Two User Gaussian Fading Broadcast Channels

In this paper, we investigate upper and lower bounds on the capacity of two-user fading broadcast channels where one of the users has a constant (non-fading) channel. We use the Costa entropy power inequality (EPI) along with an optimization framework to derive upper bounds on the sum-capacity and superposition coding to obtain lower bounds on the sum-rate for this channel. For this fading broadcast channel where one channel is constant, we find that the upper and lower bounds meet under special cases, and in general, we show that the achievable sum-rate comes within a constant of the outer bound.
Efficiency-enhancing signalling in the Samaritan's dilemma*

Suppose an altruistic person, A, is willing to transfer resources to a second person, B, if B comes upon hard times. If B anticipates that A will act in this manner, B will save too little from both agents’ point of view. This is the Samaritan's dilemma. This paper shows that the undersaving result is mitigated if we relax the standard assumption of complete information, because if A is uncertain about how big B's need for support is, B will have an incentive to signal that he is in great need by saving more than he otherwise would have done.
Disproportionality and Disparities among Sexual Minority Youth in Custody

Research indicates that sexual minority youth are disproportionately criminalized in the U.S. and subjected to abusive treatment while in correctional facilities. However, the scope and extent of disparities based on sexual orientation remains largely overlooked in the juvenile justice literature. This study, based on a nationally representative federal agency survey conducted in 2012 (N = 8785; 9.9% girls), reveals that 39.4% of girls and 3.2% of boys in juvenile correctional facilities identified as lesbian, gay, or bisexual. These youth, particularly gay and bisexual boys, report higher rates of sexual victimization compared to their heterosexual peers. Sexual minority youth, defined as both lesbian, gay, and bisexual identified youth as well as youth who identified as straight and reported some same-sex attraction, were also 2–3 times more likely than heterosexual youth to report prior episodes of detention lasting a year or more. Implications for future research and public policy are discussed.
Comparing American soccer dialogues: social media commentary Surrounding the 2014 US men’s and 2015 US women’s World Cup teams

Mega sporting events such as the World Cup have been found to stimulate categorization of in-groups and out-groups among fans. While self-categorization correlates with gender, the sport of soccer ...
Pilot error in automated systems shown by altitude deviation reports

Over 8,000 altitude deviations are reported to NASA's Aviation Safety Reporting System each year. This is almost one an hour. The narratives of pilot incidents relate how errors made in the automation-assisted altitude change task are caused by the difficulty pilots are having interacting with automatic systems. This paper discusses the impact of increased automation in glass-cockpit airliners on the altitude deviations reported by pilots. By observing the way information is processed by the cockpit system, the author suggests that the philosophies of design and training need to change in order to facilitate, not debilitate, the aircrew. >
Drug Proscriptions as Proxy Crimes

Our drug policy has been widely deemed a failure because the criminalization of drug use has not succeeded in reducing prevalence rates. I contend that the most promising basis to defend the justifiability of drug offenses is to construe them as proxy crimes: offenses designed to prevent the commission of other, more serious crimes. I make a case that many law enforcement officials use drug proscriptions for this purpose in the real world. When construed as proxy crimes, drug prohibitions are less vulnerable to some of the familiar objections brought against their legitimacy. Nonetheless, the justification for punishing those who violate drug proscriptions remains unpersuasive.
Innovative enterprise and shareholder value

This article invokes the theory of innovative enterprise to analyse the relation between value creation and value extraction in the evolution of the US economy. Beginning with a managerial, as dist...
Detecting Strong Ties Using Network Motifs

Detecting strong ties among users in social and information networks is a fundamental operation that can improve performance on a multitude of personalization and ranking tasks. There are a variety of ways a tie can be deemed ``strong'', and in this work we use a data-driven (or supervised) approach by assuming that we are provided a sample set of edges labeled as strong ties in the network. Such labeled edges are often readily obtained from the social network as users often participate in multiple overlapping networks via features such as following and messaging. These networks may vary greatly in size, density and the information they carry --- for instance, a heavily-used dense network (such as the network of followers) commonly overlaps with a secondary sparser network composed of strong ties (such as a network of email or phone contacts). This setting leads to a natural strong tie detection task: given a small set of labeled strong tie edges, how well can one detect unlabeled strong ties in the remainder of the network? This task becomes particularly daunting for the Twitter network due to scant availability of pairwise relationship attribute data, and sparsity of strong tie networks such as phone contacts. Given these challenges, a natural approach is to instead use structural network features for the task, produced by combining the strong and ``weak'' edges. In this work, we demonstrate via experiments on Twitter data that using only such structural network features is sufficient for detecting strong ties with high precision. These structural network features are obtained from the presence and frequency of small network motifs on combined strong and weak ties. We observe that using motifs larger than triads alleviate sparsity problems that arise for smaller motifs, both due to increased combinatorial possibilities as well as benefiting strongly from searching beyond the ego network. Empirically, we observe that not all motifs are equally useful, and need to be carefully constructed from the combined edges in order to be effective for strong tie detection. Finally, we reinforce our experimental findings with providing theoretical justification that suggests why incorporating these larger sized motifs as features could lead to increased performance in planted graph models.
Classifying Several Classes of Leibniz Algebras

We extend results related to maximal subalgebras and ideals from Lie to Leibniz algebras. In particular, we classify minimal non-elementary Leibniz algebras and Leibniz algebras with a unique maximal ideal. In both cases, there are types of these algebras with no Lie algebra analogue. We also give a classification of E-Leibniz algebras which is very similiar to its Lie algebra counterpart. Note that a classification of elementary Leibniz algebras has been shown in Batten Ray et al. (2011).
An investigation into the psychological well-being of the biological children of surrogates

Study Objective: The psychological well-being of surrogates’ own children has not been examined in the US. This study seeks to examine whether having a mother who has served as either a traditional...
Kinetic and spectral descriptions of autoionization phenomena associated with atomic processes in plasmas

Abstract This investigation has been devoted to the theoretical description and computer modeling of atomic processes giving rise to radiative emission in energetic electron and ion beam interactions and in laboratory plasmas. We are also interested in the effects of directed electron and ion collisions and of anisotropic electric and magnetic fields. In the kinetic-theory description, we treat excitation, de-excitation, ionization, and recombination in electron and ion encounters with partially ionized atomic systems, including the indirect contributions from processes involving autoionizing resonances. These fundamental collisional and electromagnetic interactions also provide particle and photon transport mechanisms. From the spectral perspective, the analysis of atomic radiative emission can reveal detailed information on the physical properties in the plasma environment, such as non-equilibrium electron and charge-state distributions as well as electric and magnetic field distributions. In this investigation, a reduced-density-matrix formulation is developed for the microscopic description of atomic electromagnetic interactions in the presence of environmental (collisional and radiative) relaxation and decoherence processes. Our central objective is a fundamental microscopic description of atomic electromagnetic processes, in which both bound-state and autoionization-resonance phenomena can be treated in a unified and self-consistent manner. The time-domain (equation-of-motion) and frequency-domain (resolvent-operator) formulations of the reduced-density-matrix approach are developed in a unified and self-consistent manner. This is necessary for our ultimate goal of a systematic and self-consistent treatment of non-equilibrium (possibly coherent) atomic-state kinetics and high-resolution (possibly overlapping) spectral-line shapes. We thereby propose the introduction of a generalized collisional-radiative atomic-state kinetics model based on a reduced-density-matrix formulation. It will become apparent that the full atomic data needs for the precise modeling of extreme non-equilibrium plasma environments extend beyond the conventional radiative-transition-probability and collisional-cross-section data sets.
Effects of dexamethasone treatment and respiratory vaccination on rectal temperature, complete blood count, and functional capacities of neutrophils in beef steers,

The objective of this research was to examine the effects of dexamethasone (DEX) treatment on various aspects of immunity following administration of a multivalent respiratory vaccine, using a model intended to mimic acute versus chronic stress. Angus × Hereford steers ( = 32; 209 ± 8 kg) were stratified by BW and randomly assigned to 1 of 3 treatments: 1) acute stress (ACU), in which 0.5 mg/kg BW DEX was intravenously administered at 1000 h only on d 0; 2) chronic stress (CHR), in which 0.5 mg/kg BW DEX was intravenously administered at 1000 h on d -3 to 0; or 3) control (CON), in which no DEX was administered. Steers were fitted with indwelling jugular catheters and rectal temperature (RT) recording devices on d -4 relative to vaccination and placed in individual stanchions in an environmentally controlled facility. Blood samples were collected and serum was isolated at -74, -50, and -26 h; at 0.5-h intervals from -4 to 6 h; and at 12, 24, 36, 48, and 72 h relative to multivalent respiratory vaccination at 1200 h on d 0. Additional blood samples were used to analyze complete blood cell count (CBC) and functional capacities of neutrophils. There was a treatment × time interaction ( < 0.01) for RT such that DEX treatment in CHR and ACU steers decreased RT on d -3 and 0, respectively. A treatment × time interaction ( < 0.01) was observed for total white blood cells (WBC), neutrophils, lymphocytes, and monocytes. Specifically, DEX increased WBC and neutrophils in CHR and ACU steers ( < 0.001) yet decreased lymphocytes in CHR steers ( = 0.02) compared with CON steers. Neutrophil concentration increased rapidly, within 2 h of the DEX infusion, in ACU steers. Monocytes transiently increased ( < 0.001) in response to DEX treatment in CHR and ACU steers. In contrast, eosinophils were greater ( < 0.01) in CON steers than in ACU and CHR steers. A treatment × time interaction ( = 0.004) was observed for interferon-γ, with CON cattle exhibiting greater concentrations than the ACU and CHR cattle at 5 h after vaccination, through d 3. Treatment also influenced ( ≤ 0.001) the expression of L-selectin on the surface of neutrophils. The percentage of neutrophils engaging in phagocytosis and the oxidative burst were suppressed ( ≤ 0.001) among only the CHR steers, whereas the intensity of the oxidative burst was suppressed ( ≤ 0.001) for both ACU and CHR steers. These data suggest that our model induced acute and chronic immunosuppression and defined the acute response to a multivalent vaccine in CON steers.
Over-incarceration and disenfranchisement

This article presents a model wherein law enforcers propose sentences to maximize their likelihood of reelection, and shows that elections typically generate over-incarceration, i.e., longer than optimal sentences. It then studies the effects of disenfranchisement laws, which prohibit convicted felons from voting. The removal of ex-convicts from the pool of eligible voters reduces the pressure politicians may otherwise face to protect the interests of this group, and thereby causes the political process to push the sentences for criminal offenses upwards. Therefore, disenfranchisement further widens the gap between the optimal sentence and the equilibrium sentence, and thereby exacerbates the problem of over-incarceration. Moreover, this result is valid even when voter turnout is negatively correlated with people’s criminal tendencies, i.e., when criminals vote less frequently than non-criminals.
Utility of Genetic Testing for Confirmation of Abnormal Newborn Screening in Disorders of Long-Chain Fatty Acids: A Missed Case of Carnitine Palmitoyltransferase 1A (CPT1A) Deficiency

An 18-month-old male was evaluated after presenting with disproportionately elevated liver transaminases in the setting of acute gastroenteritis. He had marked hepatomegaly on physical exam that was later confirmed with an abdominal ultrasound. Given this clinical picture, suspicion for a fatty acid oxidation disorder was raised. Further investigation revealed that his initial newborn screen was positive for carnitine palmitoyltransferase 1A (CPT1A) deficiency—a rare autosomal recessive disorder of long-chain fatty acid oxidation. Confirmatory biochemical testing in the newborn period showed carnitine levels to be unexpectedly low with a normal acylcarnitine profile. Thus, it was considered to be a false-positive newborn screen and metabolic follow-up was not recommended. Repeat biochemical testing during this hospitalization revealed a normal acylcarnitine profile. The only abnormalities noted were a low proportion of acylcarnitine species from plasma, an elevated free-to-total carnitine ratio, and mild hypoketotic medium chain dicarboxylic aciduria on urine organic acids. Gene sequencing of CPT1A revealed a novel homozygous splice site variant that confirmed his diagnosis. CPT1A deficiency has a population founder effect in the Inuit and other Arctic groups, but has not been previously reported in persons of Ashkenazi Jewish ancestry.
Port Rail Connectivity and Agricultural Production : Evidence from a Large Sample of Farmers in Ethiopia

Agriculture remains an important economic sector in Africa, employing a large share of the labor force and earning foreign exchange. Among others, transport connectivity has long been a crucial constraint in Africa. In theory, railways have a particularly important role to play in shipping freight and passengers at low cost. However, most African railways were in virtual bankruptcy by the 1990s. Using a large sample of data comprised of more than 190,000 households over eight years in Ethiopia, the paper estimates the impacts of rail transport on agricultural production. Methodologically, the paper takes advantage of the historical event that a major rail line connecting the country to the regional hub, the Port of Djibouti, was abandoned in the 2000s. With spatially highly disaggregated fixed effects and instrumental variables incorporated, an agricultural production function is estimated. The elasticity with respect to port connectivity is estimated at 0.276. The use of fertilizer is also found to increase with transport cost reduction, supporting the fact that a large amount of fertilizer is imported to Ethiopia.
Discrete Frequency Disturbance Rejection in Multivariable Digital Controllers

Abstract The rejection of sinusoidal plant disturbances is a primary objective of closed loop control systems, particularly on spacecraft. In addition, all modem spacecraft use digital, or sampled data, controllers. This paper describes methods for analyzing the frequency response of sampled data controllers to plant disturbances at discrete frequencies. It then describes the proper method for performing direct digital LQR/LQG design with plant augmentation to exactly reject these disturbances. It is shown that the traditional method of mapping to the discrete domain the augmented continuous system does not result in a digital controller that cancels the disturbances. In fact, the disturbance model must be mapped to digital separately with augmentation taking place in the discrete time problem. An example is presented to verify the technique.
Flow Cytometry in Urologic Oncology

Abstract Flow cytometers have proved to be useful research tools in cellular biology. By using these devices, rapid and objective measurements of a variety of cellular parameters can be made on a cell-by-cell basis. The application of flow cytometers to the study of urologic neoplasms is at present very preliminary. The available literature on the flow cytometric study of urologic tumors is presented and discussed.
Real single ion solvation free energies with quantum mechanical simulation

Single ion solvation free energies are one of the most important properties of electrolyte solutions and yet there is ongoing debate about what these values are. Only the values for neutral ion pairs are known. Here, we use DFT interaction potentials with molecular dynamics simulation (DFT-MD) combined with a modified version of the quasi-chemical theory (QCT) to calculate these energies for the lithium and fluoride ions. A method to correct for the error in the DFT functional is developed and very good agreement with the experimental value for the lithium fluoride pair is obtained. Moreover, this method partitions the energies into physically intuitive terms such as surface potential, cavity and charging energies which are amenable to descriptions with reduced models. Our research suggests that lithium's solvation free energy is dominated by the free energetics of a charged hard sphere, whereas fluoride exhibits significant quantum mechanical behavior that cannot be simply described with a reduced model.
Radiologic Contrast-Induced Nephropathy

Contrast nephropathy is the third most common cause of hospital-acquired renal insufficiency. While its exact pathogenesis is unclear, patients with existing renal disease are now known to be at increased risk for developing this complication. Identification of these patients by determination of serum creatinine levels may enable avoidance of contrast exposure or initiation of suitable therapy to minimize this complication if exposure to contrast is unavoidable.
Clinical Utility of Magnetic Resonance Imaging in Pediatrics

• A review of over 100 articles and our own experience of scanning nearly 500 children with magnetic resonance (MR) imaging indicate that MR is well tolerated by children. Magnetic resonance is already proving to be the imaging modality of choice for the central nervous system. It should soon prove its utility for the study of most tumors, vascular problems, and infections of the musculoskeletal system. In other regions of the body, MR can identify abnormality well, but many of these abnormalities can be identified well with other modalities, and the precise role of MR is yet to be defined. We anticipate that the number of indications for the use of MR will grow rapidly. ( AJDC 1986;140:947-956)
Linear Matrix Inequalities for Physically Consistent Inertial Parameter Identification: A Statistical Perspective on the Mass Distribution

With the increased application of model-based whole-body control in legged robots, there has been a resurgence of research interest into methods for accurate system identification. An important class of methods focuses on the inertial parameters of rigid-body systems. These parameters consist of the mass, first mass moment (related to center of mass location), and rotational inertia matrix of each link. The main contribution of this letter is to formulate physical-consistency constraints on these parameters as Linear Matrix Inequalities (LMIs). The use of these constraints in identification can accelerate convergence and increase robustness to noisy data. It is critically observed that the proposed LMIs are expressed in terms of the covariance of the mass distribution, rather than its rotational moments of inertia. With this perspective, connections to the classical problem of moments in mathematics are shown to yield new bounding-volume constraints on the mass distribution of each link. While previous work ensured physical plausibility or used convex optimization in identification, the LMIs here uniquely enable both advantages. Constraints are applied to identification of a leg for the MIT Cheetah 3 robot. Detailed properties of transmission components are identified alongside link inertias, with parameter optimization carried out to global optimality through semidefinite programming.
The generic drug user fee amendments: an economic perspective

Since the vast majority of prescription drugs consumed by Americans are off patent ('generic'), their regulation and supply is of wide interest. We describe events leading up to the US Congress's 2012 passage of the Generic Drug User Fee Amendments (GDUFA I) as part of the Food and Drug Administration Safety and Innovation Act (FDASIA). Under GDUFA I, generic manufacturers agreed to pay approximately $300 million in fees each year of the five-year program. In exchange, the US Food and Drug Administration (FDA) committed to performance goals. We describe GDUFA I's FDA commitments, provisions, goals, and annual fee structure and compare it to that entailed in the authorization and implementation of GDUFA II on October 1, 2017. We explain how user fees required under GDUFA I erected barriers to entry and created scale and scope economies for incumbent manufacturers. Congress changed user fees under GDUFA II in part to lessen these incentives. In order to initiate and sustain user fees under GDUFA legislation, FDA requires the submission of self-reported data on generic manufacturers including domestic and foreign facilities. These data are public and our examination of them provides an unprecedented window into the recent organization of generic drug manufacturers supplying the US market. Our results suggest that generic drug manufacturing is increasingly concentrated and foreign. We discuss the implications of this observed market structure for GDUFA II's implementation among other outcomes.
Heavy-Quark Hybrid Mass Splittings: Hyperfine and “Ultrafine”

It is argued that the heavy-quark limit of QCD requires a certain combination of hyperfine mass splittings in heavy-quark hybrid-meson multiplets to be unusually small. This observation will assist in the exploration of the heavy-quark hybrid spectrum at facilities such as PANDA. Alternatively, a large measured value for this mass splitting indicates that at least one member of the multiplet must contain significant light-quark degrees of freedom.
Fisher information analysis of digital pulse timing

In positron emission tomography (PET), it is possible to obtain useful time-of-flight (TOF) information if the gamma-ray detectors have less than 750 ps timing resolution. Including TOF information to the reconstruction algorithm increases the signal-to-noise ratio (SNR). We obtain timing information by analyzing digital sampled waveforms, where the sampling frequency and number of points acquired affect timing estimation. An efficient data acquisition system acquires the minimum number of samples that contains the most timing information for a desired resolution. We describe a maximum-likelihood (ML) estimation algorithm to assign a time stamp to digital pulses. The method is based on a contracting-grid search algorithm that can be implemented in a field-programmable gate array (FPGA). The Fisher information (FI) matrix that corresponds to the likelihood in the ML estimator quantifies the amount of timing information that can be extracted from the waveforms. Fisher information analyses on different segments of the waveform allow us to determine the amount of data that we need to acquire in order to obtain a desired timing resolution. We present how we simulate waveforms for ML estimation and FI analysis, the ML estimation algorithm and the timing resolution obtained from experimental data using a LaBr 3 crystal and two photomultiplier tubes (PMTs). The results show that for lengthening segments of the pulse, timing resolution approaches a limit. This information will be used to build an efficient DAQ with reduced complexity and cost that nonetheless preserves full timing performance.
Charge-Coupled Device (CCD) Trackers For High-Accuracy Guidance Applications

Recent advances in large area charge coupled device (CCD) imaging detectors and high speed microprocessors have prompted the development of a new class of electro-optical tracking instruments at the Jet Propulsion Laboratory (JPL). These instruments are designed for standardized NASA-wide usage and are characterized by their extremely high pointing accuracy and stability and performance capabilities which are largely software defined and thus easily adapted to a variety of mission requirements. This paper presents an examination of the methods by which CCD detectors are being incorporated in star tracker instruments and the performance capabilities that can be expected from currently available devices. The multi-function sensor concept, in which a single sensor can function in a variety of guidance applications, is described. Software algorithms designed to provide efficient extraction of guidance information from both point and extended images are also presented. CCD star tracker implementations currently underway at JPL are described, and performance data obtained during laboratory testing is presented and discussed.
FOUR-PART FRACTURE IN AN ACTIVE 70-YEAR-OLD: REVERSE IS OVERKILL – AFFIRMS

Management of 4-part fractures of the proximal humerus continues to challenge orthopaedic surgeons, shoulder surgeons, and trauma surgeons. Truly displaced 4-part fractures typically require surgery if the patient is medically able to undergo a surgical procedure. However, outcomes following surgery are not always as predictable as we would like. Results following hemiarthroplasty have led to more predictable pain relief than predictable functional recovery relying exclusively on the fate of tuberosity healing. Tuberosity healing failure leads to nearly universal catastrophic results with pain, dysfunction, and pseudoparalysis. Furthermore, conversion of failed hemiarthroplasty to reverse total shoulder arthroplasty leads to the highest incidence of complications and poorest outcomes of all groups of patients undergoing reverse total shoulder replacement. This is countered by the knowledge that if tuberosity healing occurs the outcome can be reliable with regard to pain relief and functional restoration. Reverse total shoulder arthroplasty, on the other hand, has emerged as a preferred surgical option for many surgeons due to the issues following hemiarthroplasty. The increased prevalence of RTSA for the management of 4-part fractures has come without overwhelming evidence that outcomes are superior especially in light of the increased cost, life-time weight bearing restrictions, and uncertain long-term durability. Long-term follow-up of patients treated with RTSA for 4-part fracture has shown concerning degradation of function and outcomes and remains a valid concern about the long-term durability. We must remain diligent therefore in continuing to better understand which fractures should be treated non-operatively and those that may be amenable to anatomic hemiarthroplasty and finally those which may be better served by using a reverse total shoulder replacement.
DGM: A deep learning algorithm for solving partial differential equations

Abstract High-dimensional PDEs have been a longstanding computational challenge. We propose to solve high-dimensional PDEs by approximating the solution with a deep neural network which is trained to satisfy the differential operator, initial condition, and boundary conditions. Our algorithm is meshfree, which is key since meshes become infeasible in higher dimensions. Instead of forming a mesh, the neural network is trained on batches of randomly sampled time and space points. The algorithm is tested on a class of high-dimensional free boundary PDEs, which we are able to accurately solve in up to 200 dimensions. The algorithm is also tested on a high-dimensional Hamilton–Jacobi–Bellman PDE and Burgers' equation. The deep learning algorithm approximates the general solution to the Burgers' equation for a continuum of different boundary conditions and physical conditions (which can be viewed as a high-dimensional space). We call the algorithm a “Deep Galerkin Method (DGM)” since it is similar in spirit to Galerkin methods, with the solution approximated by a neural network instead of a linear combination of basis functions. In addition, we prove a theorem regarding the approximation power of neural networks for a class of quasilinear parabolic PDEs.
VIX derivatives valuation and estimation based on closed-form series expansions

We propose a new methodology to evaluate VIX derivatives. The approach is based on a closed-form Hermite series expansion, and can be applied to general stochastic volatility models. We exemplify t...
Using web application construction frameworks to protect against code injection attacks

In recent years, the security landscape has changed, with Web applications vulnerabilities becoming more prominent that vulnerabilities stemming from the lack of type safety, such as buffer overruns. Many reports point to code injection attacks such as cross-site scripting and RSS injection as being the most common attacks against Web applications to date. With Web 2.0 existing security problems are further exacerbated by the advent of Ajax technology that allows one to create and compose HTML content from different sources within the browser at runtime, as exemplified by customizable mashup pages like My Yahoo! or Live.com This paper proposes a simple to support, yet a powerful scheme for eliminating a wide range of script injection vulnerabilities in applications built on top of popular Ajax development frameworks such as the Dojo Toolkit, prototype.js, and AJAX.NET. Unlike other client-side runtime enforcement proposals, the approach we are advocating requires only minor browser modifications. This is because our proposal can be viewed as a natural finer-grained extension of the same-origin policy for JavaScript already supported by the majority of mainstream browsers, in which we treat individual user interface widgets as belonging to separate domains Fortunately, in many cases no changes to the development process need to take place: for applications that are built on top of frameworks described above, a slight framework modification will result in appropriate changes in the generated HTML, completely obviating the need for manual code annotation. In this paper we demonstrate how these changes can prevent cross-site scripting and RSS injection attacks using the Dojo Toolkit, a popular Ajax library, as an example.
Evolving software trace links between requirements and source code

Traceability provides support for diverse software engineering activities including safety analysis, compliance verification, test-case selection, and impact prediction. However, in practice, there is a tendency for trace links to degrade over time as the system continually evolves. This is especially true for links between source-code and upstream artifacts such as requirements --- because developers frequently refactor and change code without updating the links. In this paper we present TLE (Trace Link Evolver), a solution for automating the evolution of bidirectional trace links between source code classes or methods and requirements. TLE depends on a set of heuristics coupled with refactoring detection tools and informational retrieval algorithms to detect predefined change scenarios that occur across contiguous versions of a software system. We first evaluate TLE at the class level in a controlled experiment to evolve trace links for revisions of two Java applications. Second, we comparatively evaluate several variants of TLE across six releases of our in-house Dronology project. We study the results of integrating human analyst feed back in the evolution cycle of this emerging project. Additionally, in this system, we compare the efficacy of class-level versus method-level evolution of trace links. Finally, we evaluate TLE in a larger scale across 27 releases of the Cassandra Database System and show that the evolved trace links are significantly more accurate than those generated using only information retrieval techniques.
Training distributed deep recurrent neural networks with mixed precision on GPU clusters

In this paper, we evaluate training of deep recurrent neural networks with half-precision floats. We implement a distributed, data-parallel, synchronous training algorithm by integrating TensorFlow and CUDA-aware MPI to enable execution across multiple GPU nodes and making use of high-speed interconnects. We introduce a learning rate schedule facilitating neural network convergence at up to O(100) workers.Strong scaling tests performed on clusters of NVIDIA Pascal P100 GPUs show linear runtime and logarithmic communication time scaling for both single and mixed precision training modes. Performance is evaluated on a scientific dataset taken from the Joint European Torus (JET) tokamak, containing multi-modal time series of sensory measurements leading up to deleterious events called plasma disruptions, and the benchmark Large Movie Review Dataset [11]. Half-precision significantly reduces memory and network bandwidth, allowing training of state-of-the-art models with over 70 million trainable parameters while achieving a comparable test set performance as single precision.
Land Prices Heading Skyward? An Analysis of Farmland Values across Tanzania

Land markets are developing rapidly in Africa, though there remains a dearth of analysis regarding the direction and correlates of land prices and their implications for public policy in the region. This paper examines trends in land values and the factors influencing these trends in Tanzania. Real land prices rose significantly between 2009 and 2013 by 5.67% per year. A hedonic analysis of land values suggests that improved incentives for farming, urbanization and rising population density, and improved tenure security are possible drivers of rising land prices. We conclude by considering the potential policy implications arising from this work.
The light-cone fock representation in QCD

The light-cone Fock-state representation of QCD encodes the properties of a hadrons in terms of frame-independent wavefunctions, providing a systematic framework for evaluating structure functions, exclusive hadronic matrix elements, including time-like heavy hadron decay amplitudes, form factors, and deeply virtual Compton scattering. A new type of jet production reaction, “self-resolving diffractive interactions” can provide direct information on the light-cone wavefunctions of hadrons in terms of their quark and gluon degrees of freedom as well as the composition of nuclei in terms of their nucleon and mesonic degrees of freedom. The relation of the intrinsic sea to the light-cone wavefunctions is discussed. The decomposition of light-cone spin is illustrated for the quantum fluctuations of an electron.
Rotor-Current-Based Fault Diagnosis for DFIG Wind Turbine Drivetrain Gearboxes Using Frequency Analysis and a Deep Classifier

Fault diagnosis of drivetrain gearboxes is a prominent challenge in wind turbine condition monitoring. Many machine learning algorithms have been applied to gearbox fault diagnosis. However, many of the current machine learning algorithms did not provide satisfactory fault diagnosis results due to their shallow architectures. Recently, a class of machine learning models with deep architectures called deep learning has received more attention, because it can learn high-level features of inputs. This paper proposes a new fault diagnosis method for the drivetrain gearboxes of the wind turbines equipped with doubly-fed induction generators (DFIGs) using DFIG rotor current signal analysis. In the proposed method, the instantaneous fundamental frequency of the rotor current signal is first estimated to obtain the instantaneous shaft rotating frequency. Then, the Hilbert transform is used to demodulate the rotor current signal to obtain its envelope, and the resultant envelope signal contains fault characteristic frequencies that are in proportion to the varying DFIG shaft rotating frequency. Next, an angular resampling algorithm is designed to resample the nonstationary envelope signal to be stationary based on the estimated instantaneous shaft rotating frequency. After that, the power spectral density analysis is performed on the resampled envelope signal for the gearbox fault detection. Finally, a classifier with a deep architecture that consists of a stacked autoencoder and a support vector machine is proposed for gearbox fault classification using extracted fault features. Experimental results obtained from a DFIG wind turbine drivetrain test rig are provided to verify the effectiveness of the proposed method.
Differential Compound Prioritization via Bidirectional Selectivity Push with Power

Effective in silico compound prioritization is a critical step to identify promising drug candidates in the early stages of drug discovery. Current computational methods for compound prioritization usually focus on ranking the compounds based on one property, typically activity, with respect to a single target. However, compound selectivity is also a key property which should be deliberated simultaneously so as to minimize the likelihood of undesired side effects of future drugs. In this paper, we present a novel machine-learning based differential compound prioritization method dCPPP. This dCPPP method learns compound prioritization models that rank active compounds well, and meanwhile, preferably rank selective compounds higher via a bidirectional selectivity push strategy. The bidirectional push is enhanced by push powers that are determined by ranking difference of selective compounds over multiple bioassays. Our experiments demonstrate that the new method dCPPP achieves significant improvement on prioritizing selective compounds over baseline models.
Aligning dynamic networks with DynaWAVE.

Motivation Network alignment (NA) aims to find similar (conserved) regions between networks, such as cellular networks of different species. Until recently, existing methods were limited to aligning static networks. However, real-world systems, including cellular functioning, are dynamic. Hence, in our previous work, we introduced the first ever dynamic NA method, DynaMAGNA++, which improved upon the traditional static NA. However, DynaMAGNA++ does not necessarily scale well to larger networks in terms of alignment quality or runtime. Results To address this, we introduce a new dynamic NA approach, DynaWAVE. We show that DynaWAVE complements DynaMAGNA++: while DynaMAGNA++ is more accurate yet slower than DynaWAVE for smaller networks, DynaWAVE is both more accurate and faster than DynaMAGNA++ for larger networks. We provide a friendly user interface and source code for DynaWAVE. Availability and implementation https://www.nd.edu/∼cone/DynaWAVE/. Contact tmilenko@nd.edu. Supplementary information Supplementary data are available at Bioinformatics online.
TCIApathfinder: an R client for The Cancer Imaging Archive REST API

The Cancer Imaging Archive (TCIA) hosts publicly available de-identified medical images of cancer from over 25 body sites and over 30,000 patients. Over 400 published studies have utilized freely available TCIA images. Images and metadata are available for download through a web interface or a REST API. Here we present TCIApathfinder, an R client for the TCIA REST API. TCIApathfinder wraps API access in user-friendly R functions that can be called interactively within an R session or easily incorporated into scripts. Functions are provided to explore the contents of the large database and to download image files. TCIApathfinder provides easy access to TCIA resources in the highly popular R programming environment. TCIApathfinder is freely available under the MIT license as a package on CRAN (https://cran.r-project.org/web/packages/TCIApathfinder/index.html) and at https://github.com/pamelarussell/TCIApathfinder.
RE-EXAMINING THE CONCEPT OF INFLAMMATORY CELL-INDUCED CORROSION

Recently, a special type of surface pitting found on metal implants was proposed to arise from “inflammatory cell-induced” corrosion (ICI, Figure 1) (1, 2). The actual mechanism of this was unknown, but similar features were suggested to be artefacts of electrocautery damage from revision surgery (3). Under lab conditions and without the influence of any cells, we aimed to reproduce the same surface pits and structures with electrocautery. Methods A polished cobalt-chromium disk (40 mm diameter, 8 mm thick) was marked into 8 sections for various testing conditions (Figure 2a). A stainless steel Bovie tip with a unipolar electrocautery machine (SYSTEM 5000, ConMed, USA) was used at typical surgical coagulation conditions: (70 volt, 120 watts, 562 KHz frequency). We mimicked three types of surgical techniques with the electrocautery: “Dotting” was repeated, on and off, direct surface contact; “Dragging” was constant, direct surface contact; “Hovering” was pausing several millimeters above the surface. We also examined the interplay of these practices on diamond-tip-induced scratches and either dry or wet (normal saline) conditions. High magnification images (Keyence VHX-2000E) were taken after the disk was cleaned with laboratory soap, light mechanical scrubbing, and formalin soak. Results Coagulation mode generated electrical sparks when dotting/dragging and electrical arcs when hovering. These left seared marks that persisted even after cleaning (Figure 2b). At higher magnification, the surface features were comparable in size and shape to those attributed to ICI (1, 2). Areas wet with saline (Figure 3a) showed an abundance of ringed pits with raised edges that closely resembled those observed in Figure 1. Furthermore we obtained images similar to the phenomenon of “cellular tracks” (Figure 3b) (1). Premade scratches did not influence the pit arrangement but scratches made by the Bovie tip produced the characteristic scratch-associated ICI features as observed on implant retrievals in the past (Figure 3c) (4). Discussion In the absence of cells, pitting equivalent to proposed ICI features was successfully replicated using an electrocautery in coagulation mode. Previously (4), we found a high incidence but small surface area of these features on the majority of retrievals, predominantly located in a focal area of the superior aspect of the femoral ball next to the junction of the stem. There were fewer on the inferior aspect which is consistent with electocautery damage when dissecting the hip capsule. The effect of this damage on retained parts is unknown, but electrocautery damage around areas of implant fractures has been reported (3). Conclusion The striking similarities of the recreated pit structures imaged here suggest that the noted features of “inflammatory cell induced corrosion” were artefacts of the electrocautery during revision surgery. Future implant retrieval analysis should acknowledge these structures are not related to any particular mode of failure but should check for them around implant fracture sites.
Amplified North Atlantic warming in the late Pliocene by changes in Arctic gateways

Under previous reconstructions of late Pliocene boundary conditions, climate models have failed to reproduce the warm sea surface temperatures reconstructed in the North Atlantic. Using a reconstruction of mid-Piacenzian paleogeography that has the Bering Strait and Canadian Arctic Archipelago Straits closed, however, improves the simulation of the proxy-indicated warm sea surface temperatures in the North Atlantic in the Community Climate System Model. We find that the closure of these small Arctic gateways strengthens the Atlantic Meridional Overturning Circulation, by inhibiting freshwater transport from the Pacific to the Arctic Ocean and from the Arctic Ocean to the Labrador Sea, leading to warmer sea surface temperatures in the North Atlantic. This indicates that the state of the Arctic gateways may influence the sensitivity of the North Atlantic climate in complex ways, and better understanding of the state of these Arctic gateways for past time periods are needed.
Information scrambling in chaotic systems with dissipation

Chaotic dynamics in closed local quantum systems scrambles quantum information, which is manifested quantitatively in the decay of the out-of-time-ordered correlators (OTOC) of local operators. How is information scrambling affected when the system is coupled to the environment and suffers from dissipation? In this paper, we address this question by defining a dissipative version of OTOC and numerically study its behavior in a prototypical chaotic quantum chain in the presence of dissipation. We find that dissipation leads to not only the overall decay of the scrambled information due to leaking but also structural changes so that the `information light cone' can only reach a finite distance even when the effect of overall decay is removed. Based on this observation we conjecture a modified version of the Lieb-Robinson bound in dissipative systems.
Measuring the Equilibrium Impacts of Credit: Evidence from the Indian Microfinance Crisis

In October 2010, the state government of Andhra Pradesh, India, issued an emergency ordinance, bringing microfinance activities in the state to a complete halt and causing a nationwide shock to the liquidity of lenders, especially those with loans in the affected state. We use this massive dislocation in the microfinance market to identify the causal impacts of a reduction in credit supply on consumption, earnings, and employment in general equilibrium in rural labor markets. Using a proprietary district-level data set from 25 separate, for-profit microlenders matched with household data from the National Sample Survey, we find that district-level reductions in credit supply are associated with significant decreases in casual daily wages, household wage earnings, and consumption. We find a substantial consumption multiplier from credit that is likely driven by two channels—aggregate demand and business investment. We calibrate a simple two-period, two-sector model of the rural economy that incorporates both channels and show that the magnitude of our wage results is consistent with the model’s predictions.