cssi/SciSciGPT-SciSciNet huggingface dataset:
Abstract IA12: Targeting DNA repair in cancer therapy

Human cancer cells have genomic instability resulting from germline or acquired defects in DNA repair. One DNA repair pathway—the Fanconi Anemia/BRCA pathway (D9Andrea, A., N Engl J Med 362:1909, 2010)—is defective in many human cancers, including breast, ovarian, and pancreatic neoplasms. Disruption of the FA/BRCA Pathway results in the characteristic chromosome instability and radiation/crosslinker hypersensitivity of these tumors. In general, loss of one DNA repair pathway often leads to hyperdependence on another pathway for tumor cell survival. This hyperdependence offers a unique opportunity for the development of anticancer therapeutics. For instance, FA/BRCA pathway deficient tumors are hyperdependent on Base Excision Repair (BER) and, accordingly, these tumors are hypersensitive to single agent treatment with PARP1 inhibitors, which block BER, or with ATM inhibitors. Our research program is focused on profiling the FA/BRCA pathway and the other five major DNA repair pathways in tumor cells (Kennedy and D9Andrea, JCO 24: 3799, 2006). Each DNA repair pathway has a characteristic biomarker and repairs a specific type of DNA lesion. By profiling these pathways in primary tumor samples with activation-specific antibodies to DNA repair proteins, we have been able (1) to predict the sensitivity of tumors to conventional chemotherapy and radiation (2) to subset tumors for their sensitivity to novel classes of DNA repair inhibitors, (i.e., PARP1, Chk1, ATM, and proteasome inhibitors) and (3) to screen for new small molecule inhibitors of other DNA repair pathways. This combination of novel DNA repair inhibitors, conventional DNA damaging agents, and DNA repair biomarkers offers new opportunities for developing more effective anticancer therapy. In my presentation, I will also discuss novel approaches to sensitizing Triple Negative Breast Cancers (TNBCs) and Ovarian Tumors (OCs) to PARP1 inhibitors. We have previously shown that exposure of these tumors to either a CDK inhibitor or a proteasome inhibitor can block homologous recombination (HR) repair and thereby sensitize the tumor cells to PARP1 inhibitor. The CDK inhibitor/PARP1 inhibitor combination has been examined in orthotopic primary TNBC and OC xenograft models. Finally, we have identified an additional PARP1-dependent DNA repair mechanism in TNBCs and OCs. This pathway is driven by a novel alternative end-joining polymerase, POLθ. These tumors are hypersensitive to inhibitors of this new pathway, suggesting a new target for DNA repair therapies. Citation Format: Alan D. D9Andrea. Targeting DNA repair in cancer therapy. [abstract]. In: Proceedings of the AACR Precision Medicine Series: Targeting the Vulnerabilities of Cancer; May 16-19, 2016; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(1_Suppl):Abstract nr IA12.
Complexity of short Presburger arithmetic

We study complexity of short sentences in Presburger arithmetic (Short-PA). Here by “short” we mean sentences with a bounded number of variables, quantifers, inequalities and Boolean operations; the input consists only of the integers involved in the inequalities. We prove that assuming Kannan’s partition can be found in polynomial time, the satisfability of Short-PA sentences can be decided in polynomial time. Furthermore, under the same assumption, we show that the numbers of satisfying assignments of short Presburger sentences can also be computed in polynomial time.
Cooperative Accumulation of Dynein-Dynactin at Microtubule Minus-Ends Drives Microtubule Network Reorganization

Cytoplasmic dynein-1 is a minus-end-directed motor protein that transports cargo over long distances and organizes the intracellular microtubule (MT) network. How dynein motor activity is harnessed for these diverse functions remains unknown. Here, we have uncovered a mechanism for how processive dynein-dynactin complexes drive MT-MT sliding, reorganization, and focusing, activities required for mitotic spindle assembly. We find that motors cooperatively accumulate, in limited numbers, at MT minus-ends. Minus-end accumulations drive MT-MT sliding, independent of MT orientation, resulting in the clustering of MT minus-ends. At a mesoscale level, activated dynein-dynactin drives the formation and coalescence of MT asters. Macroscopically, dynein-dynactin activity leads to bulk contraction of millimeter-scale MT networks, suggesting that minus-end accumulations of motors produce network-scale contractile stresses. Our data provide a model for how localized dynein activity is harnessed by cells to produce contractile stresses within the cytoskeleton, for example, during mitotic spindle assembly.
High-speed imaging of Raleigh-Taylor instabilities in laser-driven plates

We have previously reported our observations of the dynamic behavior of laser driven plates. Recent improvements and modification of the imaging techniques have identified and provided measurements of Raleigh-Taylor (R-T) instabilities that occur in these events. The microscope system in the LLNL Micro Detonics Facility, was converted to an epi- illuminated polarization configuration. A double pulse nanosecond illuminator and a second independently focusable frame camera were also added to the system. A laser driven plate, that is a dense solid driven by a laser heated, lower density plasma, is inherently R-T unstable. The characteristics and growth of the instability determine whether or not the plate remains intact. In earlier reports we correlated the surface patterning of thin plates with the fiber-optical transmission modes. In subsequent experiments we noted that the plasma burn through patterning in thin plates and the surface patterning of thicker plates did not correspond to the thin plate early time patterning. These observations led to the suspicion of R-T instability. A series of experiments correlating plate thickness and pattern spatial frequency has verified the instability. The plates are aluminum, deposited on the ends of optical fibers. They are launched by a YAG laser pulse traveling down the fiber. Plate velocities are several kilometers per second and characteristic dimensions of the instabilities are a few to tens of microns. Several techniques were used to examine the plates, the most successful being specularly reflecting polarization microscopy looking directly at the plate as it flies toward the camera. These images gave data on the spatial frequencies of the instabilities but could not give the amplitudes. To measure the amplitude of the instability a semi-transparent witness plate was placed a known distance from the plate. As above, the plate was observed using the polarization microscope but using the streak camera as the detector. Both the launch of the plate and its impact into the witness plate are observed on the streak record. Knowing the plate velocity function from earlier velocimetry measurements and observing the variations in the arrival time across the plate, the amplitude of the instability can be calculated.
An Asymptotically Optimal Heuristic for General Non-Stationary Finite-Horizon Restless Multi-Armed Multi-Action Bandits

We propose an asymptotically optimal heuristic, which we term randomized assignment control (RAC) for a restless multi-armed bandit problem with discrete-time and finite states. It is constructed using a linear programming relaxation of the original stochastic control formulation. In contrast to most of the existing literature, we consider a finite-horizon problem with multiple actions and time-dependent (i.e. nonstationary) upper bound on the number of bandits that can be activated at each time period; indeed, our analysis can also be applied in the setting with nonstationary transition matrix and nonstationary cost function. The asymptotic setting is obtained by letting the number of bandits and other related parameters grow to infinity. Our main contribution is that the asymptotic optimality of RAC in this general setting does not require indexability properties or the usual stability conditions of the underlying Markov chain (e.g. unichain) or fluid approximation (e.g. global stable attractor). Moreover, our multi-action setting is not restricted to the usual dominant action concept. Finally, we show that RAC is also asymptotically optimal for a dynamic population, where bandits can randomly arrive and depart the system.
Immunoblastic Lymphadenopathy: Failure of, rather than Lack of Immunoregulation

The lymphoid proliferation characteristic of immunoblastic lymphadenopathy is polyclonal and of B cell lineage. This proliferation of B cells could result from an inherent B cell defect, prolonged and pronounced antigenic stimulation, or inadequate immunoregulation. We recently evaluated a patient with this disorder and found excessive T cell mediated in vitro suppression of both the autologous and allogeneic blastogenic response to mitogen. This enhanced in vitro suppression suggests that the clinically observed lymphoid proliferation in this patient occurred because of autonomous or excessively stimulated B cells and not because of a lack of functional suppressor cells.
Turbidimetric Measurement of Total Urinary Proteins: A Revised Method

A turbidimetric method for the determination of total urinary proteins is proposed that uses a specimen blank for each urine. The precipitant, trichloroacetic acid (TCA), is introduced into the blank and the sample in the same amount. The blank is the supernatant of the TCA-treated urine for each specimen. Turbidity is measured by reading the 420-nm absorbance 35 minutes after the TCA addition when the turbidity curves for most urine samples plateau. This improved method was compared with an established procedure that uses water to prepare the blanks and that measures turbidity 5 minutes after the TCA addition. Of the 69 urine specimens that were analyzed by the two methods, the revised procedure yielded higher values (greater than or equal to 150%) for 5 samples, while 21 samples had lower values (less than or equal to 50%). In the latter group, four cases would have been classified erroneously as having significant proteinuria by the established method.
Bacteremias due to Citrobacter Diversus and Citrobacter Freundii: Incidence, Risk Factors, and Clinical Outcome

• From 1974 to 1982, 38 patients developedCitrobacterbacteremia at two adult community-teaching hospitals in the Detroit Medical Center (incidence, 1.2 cases per 10,000 discharges).Citrobacteraccounted for 0.7% of all bacteremias during the study period. Of 31 cases reviewed,Citrobacterbacteremia frequently developed in elderly patients (65%) and was hospital acquired (77%). Initial sites of infection included the urinary tract (39%), gastrointestinal tract (27%), wound (10%), and unknown (13%). More bacteremias caused byCitrobacter diversustended to arise from the urinary tract, while patients withCitrobacter freundiibacteremia had significantly more gallbladder disease. Patients withCitrobacterbacteremia were more likely than patients withEscherichia colibacteremia to have had additional pathogens in the bloodstream, to develop bacteremia in the hospital, and to have undergone invasive procedures contributing to infection. Significant differences were not observed in demographic, host, or other epidemiologic or clinical factors examined. Of patients withCitrobacterbacteremia, 48% died. (Arch Intern Med1985;145:1808-1810)
Evaluation of the MS-2 and Lumac Systems for the Rapid Screening of Urine Specimens

The authors have evaluated the MS-2 (Abbott) and Lumac (3M) systems for the rapid screening of urine specimens for bacteriuria. These systems, which can detect significant levels of microorganisms in urine in five hours (MS-2) or 30 minutes (Lumac), were compared with a standard overnight plate culture method. Three hundred fifty-eight voided urine specimens were examined. The two systems compared equally at greater than 10(5) colony-forming units (CFU)/mL in terms of false-positive results (11%), false-negative results (2%), sensitivity (98%), specificity (approximately equal to 86%), and positive predictive value (98%), although the Lumac was found to have a lower negative predictive value (by 10%) than the MS-2. The only organism not recognized by the MS-2 at greater than 10(5) CFU/mL was a Lactobacillus; whereas the only specimens missed by the Lumac at greater than 10(5) CFU/mL were two pure cultures of Escherichia coli. At counts of greater than 10(4) to 10(5) CFU/mL, both systems missed numerous (15 of 21 isolates for the MS-2; 12 of 9 isolates for the Lumac) gram-positive cocci. The Lumac system was the most costly, being 3.6 times as expensive as the standard plate method. Although both systems greatly reduce the time required to process urine specimens, the large number of false-positive results, false-negative results at greater than 10(4) to 10(5) CFU/mL, as well as cost suggest that a careful evaluation of a laboratory's specific needs for urine cultures be made to determine whether or not such rapid urine screening systems are appropriate.
The Theory of Planned Behavior and E-cig Use: Impulsive Personality, E-cig Attitudes, and E-cig Use

The current paper applied the Theory of Planned Behavior (TPB; Ajzen & Fishbein, 1988) to understand how impulsive personality traits and attitudes concerning e-cig use relate to the likelihood of electronic cigarette (e-cig) use. Seven hundred and fourteen participants (Mean age = 34.04, SD = 10.89, 48.6% female) completed cross-sectional measures of e-cig use attitudes (CEAC) and the Short UPPS-P Impulsive Behavior Scale. A structural path analysis suggested that urgency and deficits in conscientiousness were significantly related to e-cig attitudes (CFI = 0.99, TLI = 0.99, RMSEA = 0.02; urgency: β = 0.32, p = .001; deficits in conscientiousness: β = -0.48, p < .001). E-cig attitude scores were significantly higher for e-cig users than non-users, β = 0.85, p < .001. There was no significant direct path from impulsive personality traits to e-cig use. Findings provide initial support for a model in which impulsive traits are related to e-cig use through positive e-cig attitudes.
Renal Allograft Rejection: US Evaluation

Real-time ultrasonography (US) was performed on the allografts of 100 consecutive renal transplant recipients at the time of allograft biopsy. Evaluation of the sonograms included the grading of parameters previously demonstrated to be indicative of allograft rejection. The appearance of the renal sinus fat, allograft size, corticomedullary ratio, sharpness of the corticomedullary junction, medullary conspicuity, presence of focal parenchymal abnormalities, and thickening of the pelvic or infundibular wall were individually evaluated. The authors correlated the US and the histopathologic findings. While the accuracy of a positive prediction of rejection was relatively high (83%-90%), this result is influenced by the relatively high prevalence of rejection in the biopsy group (83%). Accuracy of a negative prediction was uniformly low (17%-30%). Mild rejection was difficult to differentiate ultrasonographically from no rejection, although severe rejection could usually be differentiated from mild or no rejection, particularly in patients with the interstitial type of rejection.
Biphasic growth dynamics control cell division in Caulobacter crescentus

Cell size is specific to each species and impacts cell function. Various phenomenological models for cell size regulation have been proposed, but recent work in bacteria has suggested an 'adder' model, in which a cell increments its size by a constant amount between each division. However, the coupling between cell size, shape and constriction remains poorly understood. Here, we investigate size control and the cell cycle dependence of bacterial growth using multigenerational cell growth and shape data for single Caulobacter crescentus cells. Our analysis reveals a biphasic mode of growth: a relative timer phase before constriction where cell growth is correlated to its initial size, followed by a pure adder phase during constriction. Cell wall labelling measurements reinforce this biphasic model, in which a crossover from uniform lateral growth to localized septal growth is observed. We present a mathematical model that quantitatively explains this biphasic 'mixer' model for cell size control.
Magnetorotational instability in a rotating liquid metal annulus

Although the magnetorotational instability (MRI) has been widely accepted as a powerful accretion mechanism in magnetized accretion discs, it has not been realized in the laboratory. The possibility of studying MRI in a rotating liquid metal annulus (Couette flow) is explored by local and global stability analysis. Stability diagrams are drawn in dimensionless parameters, and also in terms of the angular velocities at the inner and outer cylinders. It is shown that MRI can be triggered in a moderately rapidly rotating table-top apparatus, using easy-to-handle metals such as gallium. Practical issues of this proposed experiment are discussed.
GAIN SHARING IN BUNDLED PAYMENT TOTAL JOINT ARTHROPLASTY: IS IT THE WAY FORWARD?

As healthcare spending continues to outpace economic growth, legislators and healthcare economists have explored many processes aimed at improving efficiency and reducing waste within a bundled care environment. Gainsharing or the general concept that organizations and their employees can work together to continually improve outcomes at reduced expenditures in exchange for a portion of the savings has been shown to be effective within the healthcare system. Although gainsharing principles may be applicable to healthcare organizations and their physician partners, specific parameters should be followed when implementing these arrangements. This talk will discuss gainsharing strategies aimed at properly aligning healthcare organizations and physicians, which, if followed, will ensure the successful implementation of gainsharing initiatives.
Fundamental Limits on Ex -Post Enforcement and Implications for Spectrum Rights

The combination of emerging new communication technologies, economic growth, and limited amounts of available spectrum necessitate dynamic tiered sharing. This paper builds on the “spectrum jails” paradigm—a model for light-handed ex-post enforcement. We consider the situation of sharing spectrum between a single primary (higher-tier) user and a single secondary (lower-tier) user. Analyzing this as a two-player game that could be played Stackelberg or simultaneous, we examine what kinds of primary and secondary rights can be credibly enforced. We show that the primary can trust that it will be protected from too much harmful interference and we show how the regulator can set the ex-post enforcement parameters to do this no matter which secondary user becomes capable of using the band. It is impossible to give a universal guarantee to all secondary users that the primary will never make false reports (“cry wolf”) against them. However, it is possible to show that “compatible” secondary users will trust that the primary user will not make false reports against them when the spectrum opportunity is sufficiently attractive for secondary users.
Estimating Pedestrian Exposure for Small Urban and Rural Areas

Pedestrian exposure refers to a pedestrian’s contact with vehicular traffic that can create opportunities for collisions. A myriad of metrics exists to estimate pedestrian exposure, but no consensus has been reached on what metrics should be adopted. Hence this study attempted to synthesize previous studies and recommend methods for estimating pedestrian exposure, with a focus on rural and small urban areas. Five general types of exposure metrics emerged: from area-based measures (e.g., zonal walk miles traveled), through more granular metrics at the point or segment level, to advanced metrics that utilize the behavioral attributes of walk trips (e.g., space–time prism and discrete choice). In addition, the study used a finite mixture model to estimate a household-level pedestrian exposure measure for rural and small urban settings with the use of the National Household Travel Survey 2009 data. The model accounted for household characteristics (e.g., income and vehicle ownership), regional factors, and bl...
The role of noise in alliance formation and collusion in conflicts

Many real-world conflicts are to some extent determined randomly by noise. The way in which noise is modeled in contest success functions (CSFs) has has important implications both for the possibility of forming cooperative relationships as well as for the features of such relationships. In a one-shot conflict, we find that when noise is modeled as an exponential parameter in the CSF, there is a range of values for which an alliance between two parties can be beneficial, whereas that is not the case for an additive noise parameter. In an infinitely repeated conflict setting with additive noise, sustaining collusion via Nash reversion strategies is easier the more noise there is and more difficult the larger the contest's prize value, while an increase in the contest's number of players can make sustaining collusion either more or less difficult, all in marked contrast to the case of an exponential noise parameter. Which noise specification is appropriate is therefore an important consideration for modeling any conflict situation.
The Biology of Bone Metastasis

Bone metastasis, or the development of secondary tumors within the bone of cancer patients, is a debilitating and incurable disease. Despite its morbidity, the biology of bone metastasis represents one of the most complex and intriguing of all oncogenic processes. This complexity derives from the intricately organized bone microenvironment in which the various stages of hematopoiesis, osteogenesis, and osteolysis are jointly regulated but spatially restricted. Disseminated tumor cells (DTCs) from various common malignancies such as breast, prostate, lung, and kidney cancers or myeloma are uniquely primed to subvert these endogenous bone stromal elements to grow into pathological osteolytic or osteoblastic lesions. This colonization process can be separated into three key steps: seeding, dormancy, and outgrowth. Targeting the processes of dormancy and initial outgrowth offers the most therapeutic promise. Here, we discuss the concepts of the bone metastasis niche, from controlling tumor-cell survival to growth into clinically detectable disease.
Use of Single-Primer DNA Amplifications for the Identification of Red Maple (Acer rubrum L.) Cultivars

Abstract Positive cultivar identification is often difficult or impossible based solely on morphological traits. A technique ensuring reliable, repeatable, and unique cultivar identification is needed. The use of molecular markers offers such a technique, allowing assessment of fine levels of variation directly at the DNA level. In this study, RAPD (Random Amplified Polymorphic DNA) markers were investigated for their utility to identify red maple cultivars. Three out of nineteen primers tested resulted in unique banding patterns for all the maples tested, including 9 red maple clones, 5 silver maple seedlings, and 4 purported interspecific cultivars. The red maple cultivars ‘Red Sunset’ and ‘October Glory’, which are almost indistinguishable morphologically as young trees, were clearly distinguished using RAPD markers. RAPD markers provide a consistently reliable technique for red maple cultivar identification.
Spatially resolved capture of hydrogen sulfide from the water column and sedimentary pore waters for abundance and stable isotopic analysis

Sulfur cycling is ubiquitous in sedimentary environments, where it plays a major role in mediating carbon remineralization and impacts both local and global redox budgets. Microbial sulfur cycling is dominated by metabolic activity that either produces (e.g., sulfate reduction, disproportionation) or consumes (sulfide oxidation) hydrogen sulfide (H_2S). As such, improved constraints on the production, distribution, and consumption of H_2S in the natural environment will increase our understanding of microbial sulfur cycling. These different microbial sulfur metabolisms are additionally associated with particular stable isotopic fractionations. Coupling measurements of the isotopic composition of the sulfide with its distribution can provide additional information about environmental conditions and microbial ecology. Here we investigate the kinetics of sulfide capture on photographic films as a way to document the spatial distribution of sulfide in complex natural environments as well as for in situ capture of H_2S for subsequent stable isotopic analysis. Laboratory experiments and timed field deployments demonstrate the ability to infer ambient sulfide abundances from the yield of sulfide on the films. This captured sulfide preserves the isotopic composition of the ambient sulfide, offset to slightly lower δ^(34)S values by ~ 1.2 ± 0.5‰ associated with the diffusion of sulfide into the film and subsequent reaction with silver to form Ag_2S precipitates. The resulting data enable the exploration of cm-scale lateral heterogeneity that complement most geochemical profiles using traditional techniques in natural environments. Because these films can easily be deployed over a large spatial area, they are also ideal for real-time assessment of the spatial and temporal dynamics of a site during initial reconnaissance and for integration over long timescales to capture ephemeral processes.
Independence at the Top of the Triangle: Best Resolution of the Judicial Trilemma?

World Trade Organization (WTO) members have, once again, been unable to agree on the appointment of new members to the Appellate Body (AB) in a timely fashion, as one member's term expired on June 30, 2017, another member resigned in August 2017, and a third member's term will expire in December 2017, with no consensus on a process to fill those posts. The 2017 standoff follows on the heels of a fractious debate during the summer of 2016 over the United States’ decision to block the reappointment of AB member Sueng Wha Chang of Korea to a second term. Given that the AB has just seven members, the inability to quickly appoint new members to replace those whose terms have expired only adds to the difficulty of rendering decisions within the tight time frames called for in the WTO rules.
Asymptotic normality of quadratic forms with random vectors of increasing dimension

Abstract This paper provides sufficient conditions for the asymptotic normality of quadratic forms of averages of random vectors of increasing dimension and improves on conditions found in the literature. Such results are needed in applications of Owen’s empirical likelihood when the number of constraints is allowed to grow with the sample size. Indeed, the results of this paper are already used in Peng and Schick (2013) for this purpose. We also demonstrate how our results can be used to obtain the asymptotic distribution of the empirical likelihood with an increasing number of constraints under contiguous alternatives. In addition, we discuss potential applications of our result. The first example focuses on a chi-square test with an increasing number of cells. The second example treats testing for the equality of the marginal distributions of a bivariate random vector. The third example generalizes a result of Schott (2005) by showing that a standardized version of his test for diagonality of the dispersion matrix of a normal random vector is asymptotically standard normal even if the dimension increases faster than the sample size. Schott’s result requires the dimension and the sample size to be of the same order.
MONTE: the next generation of mission design and navigation software

The Mission analysis, Operations and Navigation Toolkit Environment (MONTE) (Sunseri et al. in NASA Tech Briefs 36(9), 2012) is an astrodynamic toolkit produced by the Mission Design and Navigation Software Group at the Jet Propulsion Laboratory. It provides a single integrated environment for all phases of deep space and Earth orbiting missions. Capabilities include: trajectory optimization and analysis, operational orbit determination, flight path control, and 2D/3D visualization. MONTE is presented to the user as an importable Python language module. This allows a simple but powerful user interface via CLUI or script. In addition, the Python interface allows MONTE to be used seamlessly with other canonical scientific programming tools such as SciPy, NumPy, and Matplotlib. MONTE is the prime operational orbit determination software for all JPL navigated missions.
Reliable Decision Support using Counterfactual Models

Answering "What if?" questions is important in many domains. For example, would a patient's disease progression slow down if I were to give them a dose of drug A? Ideally, we answer our question using an experiment, but this is not always possible (e.g., it may be unethical). As an alternative, we can use non-experimental data to learn models that make counterfactual predictions of what we would observe had we run an experiment. In this paper, we propose the counterfactual GP, a counterfactual model of continuous-time trajectories (time series) under sequences of actions taken in continuous-time. We develop our model within the potential outcomes framework of Neyman and Rubin. The counterfactual GP is trained using a joint maximum likelihood objective that adjusts for dependencies between observed actions and outcomes in the training data. We report two sets of experimental results using the counterfactual GP. The first shows that it can be used to learn the natural progression (i.e. untreated progression) of biomarker trajectories from observational data. In the second, we show how the CGP can be used for medical decision support by learning counterfactual models of renal health under different types of dialysis.
Extreme Overvalued Beliefs: How Violent Extremist Beliefs Become “Normalized”

Extreme overvalued beliefs (EOB) are rigidly held, non-deusional beliefs that are the motive behind most acts of terrorism and mass shootings. EOBs are differentiated from delusions and obsessions. The concept of an overvalued idea was first described by Wernicke and later applied to terrorism by McHugh. Our group of forensic psychiatrists (Rahman, Resnick, Harry) refined the definition as an aid in the differential diagnosis seen in acts of violence. The form and content of EOBs is discussed as well as group effects, conformity, and obedience to authority. Religious cults such as The People’s Temple, Heaven’s Gate, Aum Shinrikyo, and Islamic State (ISIS) and conspiracy beliefs such as assassinations, moon-hoax, and vaccine-induced autism beliefs are discussed using this construct. Finally, some concluding thoughts on countering violent extremism, including its online presence is discussed utilizing information learned from online eating disorders and consumer experience.
ARC: Adversarial Robust Cuts for Semi-Supervised and Multi-Label Classification.

Many structured prediction tasks arising in computer vision and natural language processing tractably reduce to making minimum cost cuts in graphs with edge weights learned using maximum margin methods. Unfortunately, the hinge loss used to construct these methods often provides a particularly loose bound on the loss function of interest (e.g., the Hamming loss). We develop Adversarial Robust Cuts (ARC), an approach that poses the learning task as a minimax game between predictor and "label approximator" based on minimum cost graph cuts. Unlike maximum margin methods, this game-theoretic perspective always provides meaningful bounds on the Hamming loss. We conduct multi-label and semi-supervised binary prediction experiments that demonstrate the benefits of our approach.
Adaptive Caching Networks With Optimality Guarantees

We study the optimal placement of content over a network of caches, a problem naturally arising in several networking applications. Given a demand of content request rates and paths followed, we wish to determine the content placement that maximizes the expected caching gain, i.e., the reduction of routing costs due to intermediate caching. The offline version of this problem is NP-hard and, in general, the demand and topology may be a priori unknown. Hence, a distributed, adaptive approximation algorithm for placing contents into caches is desired. We show that path replication, a simple algorithm frequently encountered in literature, can be arbitrarily suboptimal when combined with traditional eviction policies. We propose a distributed, adaptive algorithm that performs stochastic gradient ascent on a concave relaxation of the expected caching gain, and constructs a probabilistic content placement within a $1-1/e$ factor from the optimal, in expectation. Motivated by our analysis, we also propose a novel greedy eviction policy to be used with path replication, and show through numerical evaluations that both algorithms significantly outperform path replication with traditional eviction policies over a broad array of network topologies.
Inference of population structure from ancient DNA

Methods for inferring population structure from genetic information traditionally assume samples are contemporary. Yet, the increasing availability of ancient DNA sequences begs revision of this paradigm. We present Dystruct (Dynamic Structure), a framework and toolbox for inference of shared ancestry from data that include ancient DNA. By explicitly modeling population history and genetic drift as a time-series, Dystruct more accurately and realistically discovers shared ancestry from ancient and contemporary samples. Formally, we use a normal approximation of drift, which allows a novel, efficient algorithm for optimizing model parameters using stochastic variational inference. We show that Dystruct outperforms the state of the art when individuals are sampled over time, as is common in ancient DNA datasets. We further demonstrate the utility of our method on a dataset of 92 ancient samples alongside 1941 modern ones genotyped at 222755 loci. Our model tends to present modern samples as the mixtures of ancestral populations they really are, rather than the artifactual converse of presenting ancestral samples as mixtures of contemporary groups.
Maximizing Broadcast Throughput Under Ultra-Low-Power Constraints

Wireless object-tracking applications are gaining popularity and will soon utilize emerging ultra-low-power device-to-device communication. However, severe energy constraints require much more careful accounting of energy usage than what prior art provides. In particular, the available energy, the differing power consumption levels for listening, receiving, and transmitting, as well as the limited control bandwidth must all be considered. Therefore, we formulate the problem of maximizing the throughput among a set of heterogeneous broadcasting nodes with differing power consumption levels, each subject to a strict ultra-low-power budget. We obtain the oracle throughput (i.e., maximum throughput achieved by an oracle) and use Lagrangian methods to design EconCast —a simple asynchronous distributed protocol in which nodes transition between sleep, listen, and transmit states, and dynamically change the transition rates. EconCast can operate in groupput or anyput mode to respectively maximize two alternative throughput measures. We show that EconCast approaches the oracle throughput. The performance is also evaluated numerically and via extensive simulations and it is shown that EconCast outperforms prior art by $6\times $ – $17\times $ under realistic assumptions. Moreover, we evaluate EconCast ’s latency performance and consider design tradeoffs when operating in groupput and anyput modes. Finally, we implement EconCast using the TI eZ430-RF2500-SEH energy harvesting nodes and experimentally show that in realistic environments it obtains 57%–77% of the achievable throughput.
Tumors in von Hippel–Lindau syndrome: From head to toe—comprehensive state-of-the-art review

The authors provide an updated review of the molecular cytogenetics and clinical features of von Hippel–Lindau syndrome and discuss the multimodality imaging features of the numerous benign and malignant tumors that can occur in this genetic condition.
Fighting to be Different in the Academy

My entry into the academy was different than many of my colleagues who enter as tenure track faculty, or with dreams of the tenure-track. Like a growing number of faculty, I came to the university as an adjunct. I was not quite aware of what the particular differences between tenure track and non-tenure track even were before I began teaching. Being naive taught me a lot about reality in the academic world. It also exposed the tensions and politics of being an academic and an activist.
Thermal conductivity of Bi/Sb superlattice

The temperature-dependent cross-plane thermal conductivity of a 1-μm thick 50A Bi / 50A Sb superlattice on a (111) CdTe substrate was measured, using a differential 3-ω method. This method uses the temperature difference between the superlattice sample and a reference sample to calculate its cross-plane thermal conductivity. However, the substrate thermal conductivity is comparable to or smaller than the superlattice thermal conductivity near room temperature. This results in a very small or negative temperature difference, making the existing data reduction method inapplicable. Based on an improved model, the temperature-dependent thermal conductivity of the Bi/Sb superlattice is obtained and is about half of the literature value of Bi0.5Sb0.5 bulk alloy.
The Pricing and Performance of Cryptocurrency

This paper examines the performance of cryptocurrencies issued in initial coin offerings (ICOs) over a three-year period after the initial exchange listing. Average (median) ICO underpricing amount...
The Changing (Dis-)utility of Work

We study how changes in the distribution of occupations have affected the aggregate non-pecuniary costs and benefits of working. The physical toll of work is less now than in 1950, with workers shifting away from occupations in which people report experiencing tiredness and pain. The emotional consequences of the changing occupation distribution vary substantially across demographic groups. Work has become happier and more meaningful for women, but more stressful and less meaningful for men. These changes appear to be concentrated at lower education levels.
Analysis of Gap Acceptance Behavior for Unprotected Right and Left Turning Maneuvers at Signalized Intersections using Data Mining Methods: A Driving Simulation Approach:

Gap acceptance predictability has become a vital area of interest for traffic safety and operations due to its complexity and significance in understanding a population’s driving behavior. Recent s...
Gender Privacy: An Ensemble of Semi Adversarial Networks for Confounding Arbitrary Gender Classifiers

Recent research has proposed the use of Semi Adversarial Networks (SAN) for imparting privacy to face images. SANs are convolutional autoencoders that perturb face images such that the perturbed images cannot be reliably used by an attribute classifier (e.g., a gender classifier) but can still be used by a face matcher for matching purposes. However, the generalizability of SANs across multiple arbitrary gender classifiers has not been demonstrated in the literature. In this work, we tackle the generalization issue by designing an ensemble SAN model that generates a diverse set of perturbed outputs for a given input face image. This is accomplished by enforcing diversity among the individual models in the ensemble through the use of different data augmentation techniques. The goal is to ensure that at least one of the perturbed output faces will confound an arbitrary, previously unseen gender classifier. Extensive experiments using different unseen gender classifiers and face matchers are performed to demonstrate the efficacy of the proposed paradigm in imparting gender privacy to face images.
Discussion of “Managing reputation: Evidence from biographies of corporate directors✰

Abstract Gow et al. (2018) (henceforth GWY) examine how directors’ reputation concerns influence the proxy statement disclosure of their business experience. They find that reputation concerns combine with lax disclosure requirements to cause directors’ employment at troubled firms to be omitted from proxy filings. Further, the evidence suggests that these misrepresentations succeed in misleading both the labor and capital markets. In this discussion, I review the literature to highlight the importance of GWY's contribution. I also discuss the study's implications, identify some of its limitations as well as highlight several unanswered questions that provide opportunities for future research.
Does the public sector respond to private competition? An analysis of privatization and prison performance

The competition thesis states that the introduction of competition from private-sector service providers will spur performance improvements in previously monopolistic public-sector service provider...
Synchrophasor Data Correction Under GPS Spoofing Attack: A State Estimation Based Approach

GPS spoofing attack (GSA) has been shown to be one of the most imminent threats to almost all cyber-physical systems incorporated with the civilian GPS signal. Specifically, for our current agenda of the modernization of the power grid, this may greatly jeopardize the benefits provided by the pervasively installed phasor measurement units (PMU). In this paper, we consider the case where synchrophasor data from PMUs are compromised due to the presence of a single GSA, and show that it can be corrected by signal processing techniques. In particular, we introduce a statistical model for synchrophasor- based power system state estimation (SE), and then derive the spoofing-matched algorithms for synchrophasor data correction against GPS spoofing attack. Different testing scenarios in IEEE 14-, 30-, 57-, 118-bus systems are simulated to show the proposed algorithms' performance on GSA detection and state estimation. Numerical results demonstrate that our proposed algorithms can consistently locate and correct the spoofed synchrophasor data with good accuracy as long as the system observability is satisfied. The accuracy of state estimation is significantly improved compared with the traditional weighted least square method and approaches the performance under the Genie-aided method.
Turnout in Transitional Elections: Who votes in Iraq?

Electoral turnout in Iraq is a puzzling phenomenon. Despite the country’s lack of a democratic past, undeveloped party system, volatile political alliances, inexperienced voters, ethnic politics, s...
Learning Gender-Neutral Word Embeddings

Word embedding models have become a fundamental component in a wide range of Natural Language Processing (NLP) applications. However, embeddings trained on human-generated corpora have been demonstrated to inherit strong gender stereotypes that reflect social constructs. To address this concern, in this paper, we propose a novel training procedure for learning gender-neutral word embeddings. Our approach aims to preserve gender information in certain dimensions of word vectors while compelling other dimensions to be free of gender influence. Based on the proposed method, we generate a Gender-Neutral variant of GloVe (GN-GloVe). Quantitative and qualitative experiments demonstrate that GN-GloVe successfully isolates gender information without sacrificing the functionality of the embedding model.
Globalization Effects on the Reports of Non-Endemic Parasitosis in Italy

Protozoa and helminths are responsible for several intestinal parasite infections (IPIs). Generally, helminth infections are very unsafe but scarcely reported in high-income countries, while protozoa and helminth co-infections are usually reported in children living in inadequate hygienic-sanitary conditions and in rural areas. However, the impact of growing globalization, intense travelling, international adoptions and high levels of immigrants and refugees has significantly incremented the incidence of orofecal parasitosis in non-endemic areas. Although most IPs clear without treatment when population, even children, emigrate from endemic to different geographical areas, some IPIs such as strongyloidiasis may persist for decades as subclinical infections or as low-grade disease with nonspecific clinical manifestations, unless to reappear under impairment conditions. Herein we report an unusual case of Giardia lamblia and Trichuris spp. chronic asymptomatic co-infection in a healthy adopted Romanian child, living in a Central Italy rural area, and a hidden case of Strongyloides stercoralis in an adopted Burundian child, resident in South Italy, long misdiagnosed as a recurrent undefined dermatitis. Our report suggests the need to review primary care practitioner guidelines and children’s hospital procedures for appropriate IPIs screening and follow-up, hence providing new screening and prevention strategies, in agreement with international guidelines.
Semi-Supervised Sequence Modeling with Cross-View Training

Unsupervised representation learning algorithms such as word2vec and ELMo improve the accuracy of many supervised NLP models, mainly because they can take advantage of large amounts of unlabeled text. However, the supervised models only learn from task-specific labeled data during the main training phase. We therefore propose Cross-View Training (CVT), a semi-supervised learning algorithm that improves the representations of a Bi-LSTM sentence encoder using a mix of labeled and unlabeled data. On labeled examples, standard supervised learning is used. On unlabeled examples, CVT teaches auxiliary prediction modules that see restricted views of the input (e.g., only part of a sentence) to match the predictions of the full model seeing the whole input. Since the auxiliary modules and the full model share intermediate representations, this in turn improves the full model. Moreover, we show that CVT is particularly effective when combined with multi-task learning. We evaluate CVT on five sequence tagging tasks, machine translation, and dependency parsing, achieving state-of-the-art results.
Understanding How Language-Specific and Domain-General Resources Support Comprehension

A large body of work has demonstrated that reader resources influence inference processes and comprehension, but few models of comprehension have accounted for such resources. The Direct and Mediat...
Machine Learning and Sampling Scheme: An Empirical Study of Money Laundering Detection

This paper studies the interplay of machine learning and sampling scheme in an empirical analysis of money laundering detection algorithms. Using actual transaction data provided by a U.S. financial institution, we study five major machine learning algorithms including Bayes logistic regression, decision tree, random forest, support vector machine, and artificial neural network. As the incidence of money laundering events is rare, we apply and compare two sampling techniques that increase the relative presence of the events. Our analysis reveals potential advantages of machine learning algorithms in modeling money laundering events. This paper provides insights into the use of machine learning and sampling schemes in money laundering detection specifically, and classification of rare events in general.
Cross-Domain 3D Equivariant Image Embeddings

Spherical convolutional networks have been introduced recently as tools to learn powerful feature representations of 3D shapes. Spherical CNNs are equivariant to 3D rotations making them ideally suited to applications where 3D data may be observed in arbitrary orientations. In this paper we learn 2D image embeddings with a similar equivariant structure: embedding the image of a 3D object should commute with rotations of the object. We introduce a cross-domain embedding from 2D images into a spherical CNN latent space. This embedding encodes images with 3D shape properties and is equivariant to 3D rotations of the observed object. The model is supervised only by target embeddings obtained from a spherical CNN pretrained for 3D shape classification. We show that learning a rich embedding for images with appropriate geometric structure is sufficient for tackling varied applications, such as relative pose estimation and novel view synthesis, without requiring additional task-specific supervision.