cssi/SciSciGPT-SciSciNet huggingface dataset:
Optimal Placement of Energy Storage in Distribution Networks

We study the problem of optimal placement and capacity of energy storage devices in a distribution network to minimize total energy loss. A continuous tree with linearized DistFlow model is developed to model the distribution network. We analyze structural properties of the optimal solution when all loads have the same shape. We prove that it is optimal to place storage devices near the leaves of the network away from the substation, and that the scaled storage capacity monotonically increases toward the leaves. Moreover, under optimal storage placement, the locational marginal value of storage is equalized wherever nonzero storage is deployed and increases from the substation toward any leaf node over places where there is zero storage deployment. We illustrate through simulations that these structural properties are robust in that they hold approximately when some of our modeling assumptions are relaxed.
Micromachined Silicon Transducers for Measuring Force, Pressure, and Motion

Integrated-circuit technology has provided the capability of defining very precise patterns on a silicon surface. When these patterns are used with advanced chemical etching techniques, well defined, very small structures can be formed from a silicon wafer, thereby suggesting a low-cost method of batch fabricating highly uniform, highly repeatable physical shapes. The combination of IC photolithography plus controlled etching of silicon has been labelled "micromachining," because of the inherent precision it provides. Certain kinds of silicon are highly piezoresistive, in that the resistivity changes very significantly with applied stress. Piezoresistors formed in such silicon enable us to convert mechanically induced stress into an electrical signal. Including piezoresistors into appropriate micromachined silicon shapes thus yields transducers for measuring such physical quantities as acceleration, pressure, and force, as will be described in this paper.
Hemolytic-Uremic Syndrome in Two Siblings From a Nonendemic Area

The hemolytic-uremic syndrome (HUS) has been recognized as a cause of acute renal failure in infancy and childhood since 1955. 1 The syndrome is characterized by a diarrheal prodrome, microangiopathic hemolytic anemia, thrombocytopenia, and renal failure. Numerous articles from both endemic 2.3 and nonendemic 4.5 regions have reported the broad spectrum of severity of this disease. However, relatively little emphasis has been given to the tendency of this disorder to occur in siblings. This article reports HUS in two brothers from a nonendemic area and demonstrates the variations in severity of this disease. Report of Cases .—Case1.—A 4-year-old boy was admitted to Henrietta Egleston Hospital for Children, Atlanta, after bloody diarrhea, vomiting, and increasing lethargy of five days' duration. Bloodtinged urine had developed the day prior to admission. Physical examination showed a lethargic but easily aroused child. The blood pressure (BP) was 96/62 mm Hg. The conjunctivae were mildly
Treatment of Stage D Prostatic Carcinoma With Megestrol Acetate

Nine previously untreated patients with stage D prostatic carcinoma received megestrol acetate 40 mg orally three times daily. Responses included five partial regressions, two stabilizations, and two progressions. Duration of response ranged from 3 + to 33 + months, with a mean of 11.7 months and a median of 12 months. Three of five patients who had failed prior hormonal therapy remained objectively stable while receiving megestrol acetate. No gastrointestinal toxicity, gynecomastia, fluid retention, or thromboembolic complications were observed during treatment. Weight gain of 5 to 51 pounds occurred in seven of 14 patients.
Acquired Renal Cysts and Multiple Renal Cell and Urothelial Tumors

This paper reports two cases of acquired renal cysts and multiple renal cell tumors in end-stage kidneys with a discussion of the pathogenesis of these lesions. The first patient had been on maintenance dialysis for approximately three years when he was found to have multiple renal cysts and renal cell tumors. He subsequently developed multifocal urothelial carcinomas of the lower urinary tract. The second patient had progressive renal failure due to hypertensive vascular disease when he underwent left nephrectomy because of multiple renal cysts and renal cell carcinoma. He later developed terminal renal failure and was maintained on chronic dialysis. He expired three years later. At autopsy, the right kidney also demonstrated multiple cysts and renal cell tumors.
Leonid meteor ablation, energy exchange, and trail morphology

Abstract This paper describes theoretical model studies of the interaction of Leonid meteoroids with the earth’s atmosphere. Subject to some modest-to-strenuous approximations we compute the rates of ablation and deceleration, energy deposition, and terminal altitudes of the meteors as functions of their initial mass and bulk density, velocity, trajectory entry angle, drag coefficient, heat of ablation, and an ablation energy transfer fraction. We find that the dominant energy deposition in the atmosphere is associated with the stopping of the ablated meteor particles and vapor by the surrounding air. Then having computed the energy deposition rates vs. altitude we compute the hydrodynamic and radiative expansion of the hot wake material in the radial direction, along with the associated air chemistry. From the computed results we can then plot two-dimensional temperature contours – as functions of the instantaneous distance behind the meteor and radial distance from the center of the wake, at various altitudes along the meteor’s path. We also compute the rates of emission of radiation and the radiative efficiency, and discuss comparisons with observations.
Crime, punishment, and causation: The effect of etiological information on the perception of moral agency.

Moral judgments about a situation are profoundly shaped by the perception of individuals in that situation as either moral agents or moral patients (Gray & Wegner, 2009; Gray, Young, & Waytz, 2012). Specifically, the more we see someone as a moral agent, the less we see them as a moral patient, and vice versa. As a result, casting the perpetrator of a transgression as a victim tends to have the effect of making them seem less blameworthy (Gray & Wegner, 2011). Based on this theoretical framework, we predicted that criminal offenders with a mental disorder that predisposes them to antisocial behavior would be judged more negatively when the disorder is described as having a genetic origin than when it is described as environmentally caused, as in the case of childhood abuse or accident. Further, we predicted that some environmental explanations would mitigate attributions of blame more than others, namely, that offenders whose disorder was caused by childhood abuse (intentional harm) would be seen as less blameworthy than offenders whose disorder is caused by an unfortunate accident (unintentional harm). Results from two vignette-based studies designed to test these predictions, conducted with participants recruited from Amazon Mechanical Turk (N = 244 and N = 387, respectively), confirmed the first prediction but not the second. Implications of this research for three areas — the psychology of moral judgment, philosophical debates about moral responsibility and determinism, and the practice of the law — are discussed in the sequel.
Out-of-Register Aβ42 Assemblies as Models for Neurotoxic Oligomers and Fibrils.

We propose a variant of the recently found S-shaped Aβ1−42-motif that is characterized by out-of-register C-terminal β-strands. We show that chains with this structure can not only form fibrils that are compatible with the NMR signals, but also barrel-shaped oligomers that resemble the ones formed by the much smaller cylindrin peptides. Running at physiological temperatures long all-atom molecular dynamics simulations with an explicit solvent, we study the stability of these constructs and show that they are plausible models for neurotoxic oligomers. Analyzing the transitions between different assemblies we suggest a mechanism for amyloid formation in Alzheimer’s disease.
Droughts, Conflict, and the African Slave Trade

Historians have frequently suggested that droughts helped facilitate the African slave trade. By introducing a previously unused dataset on 19th century rainfall levels in Africa, I provide the first empirical answer to this hypothesis. I show that negative rainfall shocks and long-run shifts in the mean level of rainfall increased the number of slaves exported from a given region and may have had a persistent impact on the level of development today. Using geocoded data on 19th century African conflicts, I show that these drought conditions also increased the likelihood of conflict, but only in the slave exporting regions of Africa. I also explore the role of household desperation, the internal African slave market, and disease outbreaks in explaining the negative relationship between droughts and slave exports. I find limited evidence for for these alternative mechanisms, with household desperation having the most empirical support. These results contribute to our understanding of the process of selection into the African slave trade.
The Big Occulting Steerable Satellite (BOSS)

Natural (such as lunar) occultations have long been used to study sources on small angular scales, while coronographs have been used to study high-contrast sources. We describe here the properties of the Big Occulting Steerable Satellite (BOSS), a large steerable occulting satellite to combine both of these techniques. BOSS will have several advantages over standard occulting bodies. BOSS would block all but about 4 × 10-5 of the light at 1 μm in the region of interest around the star for planet detections (with even better blocking possible using new film surface etching techniques). Because the occultation occurs outside the telescope, scattering inside the telescope does not degrade this performance. BOSS could be combined with a space telescope at the Earth-Sun L2 point to yield very long integration times, in excess of 3000 s. If placed in Earth orbit, integration times of 160-1600 s can be achieved from most major telescope sites for objects in over 90% of the sky. Applications for BOSS include direct imaging of planets around nearby stars. Planets separated by as little as 0.1''-0.25'' from the star they orbit could be seen down to a relative intensity as little as 1 × 10-9 around a magnitude 8 (or brighter) star. Other applications include ultra-high-resolution imaging of compound sources, such as microlensed stars and quasars, down to a resolution as little as 0.1 mas.
On total Springer representations for classical types

We give explicit formulas on total Springer representations for classical types. We also describe the characters of restrictions of such representations to a maximal parabolic subgroup isomorphic to a symmetric group. As a result, we give closed formulas for the Euler characteristic of Springer fibers.
The (Uneven) Spatial Distribution of the Bakken Oil Boom

Resulting from a booming shale-energy sector, from 2007 to 2014, income per capita in North Dakota increased 40%. Does this reflect the experience of a few oil-rich counties, or were the gains more evenly distributed across the region? We find the shale boom generated significant economic gains for counties above and near the Bakken Shale Formation, but not for those farther away. We also document significant state-border effects, which are not easily explained. Conditional on distance to the Bakken region, the shale boom generated limited outward migration from South Dakota, and as a result, the economic gains that accrued there were muted.
Can Deep Reinforcement Learning solve Erdos-Selfridge-Spencer Games?

Deep reinforcement learning has achieved many recent successes, but our understanding of its strengths and limitations is hampered by the lack of rich environments in which we can fully characterize optimal behavior, and correspondingly diagnose individual actions against such a characterization. Here we consider a family of combinatorial games, arising from work of Erdos, Selfridge, and Spencer, and we propose their use as environments for evaluating and comparing different approaches to reinforcement learning. These games have a number of appealing features: they are challenging for current learning approaches, but they form (i) a low-dimensional, simply parametrized environment where (ii) there is a linear closed form solution for optimal behavior from any state, and (iii) the difficulty of the game can be tuned by changing environment parameters in an interpretable way. We use these Erdos-Selfridge-Spencer games not only to compare different algorithms, but test for generalization, make comparisons to supervised learning, analyse multiagent play, and even develop a self play algorithm. Code can be found at: this https URL
Drugging DNA repair to target T-ALL cells.

Despite recent progress in treatment, prognostication for T-cell acute lymphoblastic leukemia (T-ALL) patients, including those with early T-cell precursor ALL (ETP-ALL), is rather poor [1]. Theref...
Individual Differences in Locomotor Function Predict the Capacity to Reduce Asymmetry and Modify the Energetic Cost of Walking Poststroke.

Changes in the control of the lower extremities poststroke lead to persistent biomechanical asymmetries during walking. These asymmetries are associated with an increase in energetic cost, leading ...
Comparative analysis of hybrid DC breaker and assembly HVDC breaker

Voltage Source Converters (VSC) are becoming more common in modern High Voltage DC (HVDC) transmission systems. One of the major challenges in a multi-terminal VSC-HVDC is protection against DC side faults. Two major designs, namely, the hybrid DC breaker and the assembly HVDC breaker, are compared for operational behavior, speed of operation and current carrying capability. The Dual Modular Redundancy (DMR) technique is utilized for decision making of a fault scenario. This uses a dual voting system when one result contradicts the other. This helps in the design of a fail-safe mechanism for the operation of both types of breakers. Current threshold combined with directional change is considered for the breaker operation. A three-terminal bipolar VSC HVDC system is designed in PSCAD/EMTDC and simulation results are utilized to draw a comparison of the two different designs of DC breakers.
Targeting novel mechanisms of pain in sickle cell disease

Patients with sickle cell disease (SCD) suffer from intense pain that can start during infancy and increase in severity throughout life, leading to hospitalization and poor quality of life. A unique feature of SCD is vaso-occlusive crises (VOCs) characterized by episodic, recurrent, and unpredictable episodes of acute pain. Microvascular obstruction during a VOC leads to impaired oxygen supply to the periphery and ischemia reperfusion injury, inflammation, oxidative stress, and endothelial dysfunction, all of which may perpetuate a noxious microenvironment leading to pain. In addition to episodic acute pain, patients with SCD also report chronic pain. Current treatment of moderate to severe pain in SCD is mostly reliant upon opioids; however, long-term use of opioids is associated with multiple side effects. This review presents up-to-date developments in our understanding of the pathobiology of pain in SCD. To help focus future research efforts, major gaps in knowledge are identified regarding how sickle pathobiology evokes pain, pathways specific to chronic and acute sickle pain, perception-based targets of “top-down” mechanisms originating from the brain and neuromodulation, and how pain affects the sickle microenvironment and pathophysiology. This review also describes mechanism-based targets that may help develop novel therapeutic and/or preventive strategies to ameliorate pain in SCD.
Swing voting in the 2016 presidential election in counties where midlife mortality has been rising in white non-Hispanic Americans

Abstract Understanding the effects of widespread disruption of the social fabric on public health outcomes can provide insight into the forces that drive major political realignment. Our objective was to estimate the association between increases in mortality in middle-aged non-Hispanic white adults from 1999 to 2005 to 2009–2015, health inequalities in life expectancy by income, and the surge in support for the Republican Party in pivotal US counties in the 2016 presidential election. We conducted a longitudinal ecological study in 2764 US counties from 1999 to 2016. Increases in mortality were measured using age-specific (45–54 years of age) all-cause mortality from 1999 to 2005 to 2009–2015 at the county level. Support for the Republican Party was measured as the party's vote share in the presidential election in 2016 adjusted for results in 2008 and 2012. We found a significant up-turn in mortality from 1999 to 2005 to 2009–2015 in counties where the Democratic Party won twice (2008 and 2012) but where the Republican Party won in 2016 (+10.7/100,000), as compared to those in which the Democratic Party won in 2016 (−15.7/100,000). An increase in mortality of 15.2/100,000 was associated with a significant (p
Common Business Components and Services toward More Agile and Flexible Industry Solutions and Assets

Summary form only given. In many decades, many organizations, especially large consulting companies, have been designing, implementing and managing business solutions for every industry around the globe. But due to numerous limitations in process, tooling and skills, most of those solutions were made very specific to individual industry and client needs at its early design stage. Therefore, reuse and more importantly, managing the ever changing business requirements, become almost impossible. Service-orientation and architecture, model-driven business development provides us a new and powerful approach to facilitate asset based industry solution design and development. To further accelerate this, this tutorial discusses about an innovative approach that take advantage of many proven best software engineering practices, from object/component based technology, meta-data driven architecture types (archetypes) that are used to model the common structural and in some cases non-structural business entities such as customer, product, payment, etc. In order to address the consequences introduced by abstracting those common elements out of the specific industry model and be able to enable easy and meta-data based transformation, we properly decompose business components/services into a multi-layered business architecture. Therefore, process/components/services can be decomposed accordingly to facilitate the decomposition and abstraction, while maintaining certain level of necessary traceability across various artifacts. In the realization phase, existing assets/operational systems will be mapped and transformed to the required business components and services to best leverage those existing valuable industry/client investments. To support such a SOA based, model and business driven development process, existing tooling, especially the necessary transformation and integration capability, needs to be significantly enhanced. This tutorial will also present some recommendation based on some recent design and implementation, and they could be used to guide future tooling alignment and integration effort across software modeling, implementation and solution products. In addition, we will present how to leverage existing internal or external assets or product offerings and the open industry reference models and standards (such as ACCORD, ebXML, ARTS/IxRetail). This work is based on authors' collective experience in leading the large end-to-end client engagements across many industries, while promoting various industry leading software engineering best practices.
Distributed Distance-Bounded Network Design Through Distributed Convex Programming

Solving linear programs is often a challenging task in distributed settings. While there are good algorithms for solving packing and covering linear programs in a distributed manner (Kuhn et al. 2006), this is essentially the only class of linear programs for which such an algorithm is known. In this work we provide a distributed algorithm for solving a different class of convex programs which we call â€œdistance-bounded network design convex programsâ€. These can be thought of as relaxations of network design problems in which the connectivity requirement includes a distance constraint (most notably, graph spanners). Our algorithm runs in O((D/e) log n) rounds in the LOCAL model and with high probability finds a (1+e)-approximation to the optimal LP solution for any 0 < e ≤ 1, where D is the largest distance constraint. While solving linear programs in a distributed setting is interesting in its own right, this class of convex programs is particularly important because solving them is often a crucial step when designing approximation algorithms. Hence we almost immediately obtain new and improved distributed approximation algorithms for a variety of network design problems, including Basic 3- and 4-Spanner, Directed k-Spanner, Lowest Degree k-Spanner, and Shallow-Light Steiner Network Design with a spanning demand graph. Our algorithms do not require any â€œheavyâ€ computation and essentially match the best-known centralized approximation algorithms, while previous approaches which do not use heavy computation give approximations which are worse than the best-known centralized bounds.
Properties of epitaxial ZnO thin films for GaN and related applications

In this paper, we present a detailed study of high quality (110) ZnO films, epitaxially grown on R-plane sapphire substrates by metal-organic chemical vapor deposition (MOCVD). The epitaxial relationships are (11 $$\bar 2$$ 0 ) ZnO//( 01 $$\bar 1$$ 2 ) Al2O3 and [0001] ZnO//[0 $$\bar 1$$ 11] Al2O3 as confirmed by X-ray diffraction (θ-2θ, and ϕ-scan) and high-resolution cross-sectional transmission electron microscopy (HR-TEM). Low temperature photoluminescence (PL) indicates the ZnO thin films are almost strain free. Optical absorption and reflection measurements with linearly polarized light indicate a strong optical anisotropy. The polarization rotation towards the C-axis associated with the optical anisotropy is utilized to demonstrate an optically addressed ultra-fast, ultraviolet light modulator.
Convergence of Wnt, growth factor, and heterotrimeric G protein signals on the guanine nucleotide exchange factor Daple

Cellular proliferation, differentiation, and morphogenesis are shaped by multiple signaling cascades, and their dysregulation plays an integral role in cancer progression. Three cascades that contribute to oncogenic potential are those mediated by Wnt proteins and the receptor Frizzled (FZD), growth factor receptor tyrosine kinases (RTKs), and heterotrimeric G proteins and associated GPCRs. Daple is a guanine nucleotide exchange factor (GEF) for the G protein G αi . Daple also binds to FZD and the Wnt/FZD mediator Dishevelled (Dvl), and it enhances β-catenin–independent Wnt signaling in response to Wnt5a-FZD7 signaling. We identified Daple as a substrate of multiple RTKs and non-RTKs and, hence, as a point of convergence for the three cascades. We found that phosphorylation near the Dvl-binding motif in Daple by both RTKs and non-RTKs caused Daple/Dvl complex dissociation and augmented the ability of Daple to bind to and activate G αi , which potentiated β-catenin–independent Wnt signals and stimulated epithelial-mesenchymal transition (EMT) similarly to Wnt5a/FZD7 signaling. Although Daple acts as a tumor suppressor in the healthy colon, the concurrent increased abundance of Daple and epidermal growth factor receptor (EGFR) in colorectal tumors was associated with poor patient prognosis. Thus, the Daple-dependent activation of G αi and the Daple-dependent enhancement of β-catenin–independent Wnt signals are not only stimulated by Wnt5a/FZD7 to suppress tumorigenesis but also hijacked by growth factor–activated RTKs to enhance tumor progression. These findings identify a cross-talk paradigm among growth factor RTKs, heterotrimeric G proteins, and the Wnt/FZD pathway in cancer.
Race and Economic Opportunity in the United States: an Intergenerational Perspective

We study the sources of racial disparities in income using anonymized longitudinal data covering nearly the entire U.S. population from 1989 to 2015. We document three results. First, black Americans and American Indians have much lower rates of upward mobility and higher rates of downward mobility than whites, leading to persistent disparities across generations. Conditional on parent income, the black-white income gap is driven by differences in wages and employment rates between black and white men; there are no such differences between black and white women. Hispanic Americans have rates of intergenerational mobility more similar to whites than blacks, leading the Hispanic-white income gap to shrink across generations. Second, differences in parental marital status, education, and wealth explain little of the black-white income gap conditional on parent income. Third, the black-white gap persists even among boys who grow up in the same neighborhood. Controlling for parental income, black boys have lower incomes in adulthood than white boys in 99% of Census tracts. The few areas with small black-white gaps tend to be low-poverty neighborhoods with low levels of racial bias among whites and high rates of father presence among blacks. Black males who move to such neighborhoods earlier in childhood have significantly better outcomes. However, less than 5% of black children grow up in such areas. Our findings suggest that reducing the black-white income gap will require efforts whose impacts cross neighborhood and class lines and increase upward mobility specifically for black men.
Dynamic representation of 3D auditory space in the midbrain of the free-flying echolocating bat.

Humans and other animals can navigate their natural environments seamlessly, even if there are obstacles in their path. However, it is not well understood how an animal’s brain processes information from the senses to map where it is in relation to these objects, both in terms of distance and direction. Bats can help answer these questions because they use a biological navigation system: echolocation. Bat produce high-pitched squeaks and then listen to the echoes that return when the sound bounces off of nearby objects. A bat can then use this information to estimate both which direction an object is, and how far away it is. Bats can also change their echolocation signals to focus on different objects, and researchers can record and analyze these signals to directly measure what the bat is paying attention to. Kothari, Wohlgemuth and Moss have now investigated how the brain cells of bats process the animals’ movements while flying in three-dimensional space. A wireless probe was inserted into the midbrain region of each bat to detect whenever there was an electrical impulse in the nearby brain cells. The bats were then allowed to fly freely in a large room that contained obstacles, while each bat’s echolocation signals and brain activity were recorded. The experiments revealed a group of brain cells that codes for the position of an object in three-dimensional space. Kothari, Wohlgemuth and Moss noted that these brain cells register the distance to objects more precisely when the bat changed its echolocation behavior to focus on those objects. Moreover, the activity in the bat’s brain also shifted when the bat noticed a closer object. These findings are not only relevant to echolocating bats, but rather reflect the general role that shifts in attention may play when many species map the locations of objects around them. Further similar studies with other species would contribute to a more complete understanding of animals’ nervous systems work under natural conditions. In the future, these findings, and the studies that build upon them, could be applied to other fields of research like medicine or engineering. For example, smart wireless devices, designed to record and transmit physiological measurements based on movement, could efficiently monitor human health, and robots equipped with adaptive sonar could navigate effectively in complex environments.
A general mixture equation of state for double bonding carboxylic acids with ≥2 association sites.

In this paper, we obtain the first general multi-component solution to Wertheim’s thermodynamic perturbation theory for the case that molecules can participate in cyclic double bonds. In contrast to previous authors, we do not restrict double bonding molecules to a 2-site association scheme. Each molecule in a multi-component mixture can have an arbitrary number of donor and acceptor association sites. The one restriction on the theory is that molecules can have at most one pair of double bonding sites. We also incorporate the effect of hydrogen bond cooperativity in cyclic double bonds. We then apply this new association theory to 2-site and 3-site models for carboxylic acids within the polar perturbed chain statistical associating fluid theory equation of state. We demonstrate the accuracy of the approach by comparison to both pure and multi-component phase equilibria data. It is demonstrated that the 3-site association model gives substantially a different hydrogen bonding structure than a 2-site appro...
TGF-β Sustains Tumor Progression through Biochemical and Mechanical Signal Transduction.

Transforming growth factor β (TGF-β) signaling transduces immunosuppressive biochemical and mechanical signals in the tumor microenvironment. In addition to canonical SMAD transcription factor signaling, TGF-β can promote tumor growth and survival by inhibiting proinflammatory signaling and extracellular matrix (ECM) remodeling. In this article, we review how TGF-β activated kinase 1 (TAK1) activation lies at the intersection of proinflammatory signaling by immune receptors and anti-inflammatory signaling by TGF-β receptors. Additionally, we discuss the role of TGF-β in the mechanobiology of cancer. Understanding how TGF-β dampens proinflammatory responses and induces pro-survival mechanical signals throughout cancer development is critical for designing therapeutics that inhibit tumor progression while bolstering the immune response.
Stakeholder perceptions of the United States energy transition: Local-level dynamics and community responses to national politics and policy

Abstract The literature on energy transitions tends to focus on forces operating within entire sectors or across multiple sectors, and usually at the national or international-level. This focus can disguise the fact that transitions often have uneven geographic effects, and specifically adverse consequences for some frontline communities. In this article, we examine how U.S. communities have fared during the current transition toward lower carbon sources of energy. We analyze data compiled from interviews and surveys with stakeholders working in three locations: Detroit, Michigan; St. Louis, Missouri; and Appalachian coal country. We find that a majority of stakeholders perceive evidence of the energy transition in their communities and are concerned about their community’s ability to adapt. Our results, however, suggest heterogeneity among perceptions across the study sites. Stakeholders in Appalachia are most concerned about local job loss and employment availability, with more severe implications for younger and older generations, while those in Detroit and St. Louis express more concerns about the rising cost of energy and the implications for low-income residents. We also find that these stakeholder perceptions do not substantially change after recent political shifts at the federal level but sub-national activism and collaboration has increased.
Speeding up Context-based Sentence Representation Learning with Non-autoregressive Convolutional Decoding

We propose an asymmetric encoder-decoder structure, which keeps an RNN as the encoder and has a CNN as the decoder, and the model only explores the subsequent context information as the supervision. The asymmetry in both model architecture and training pair reduces a large amount of the training time. The contribution of our work is summarized as 1. We design experiments to show that an autoregressive decoder or an RNN decoder is not necessary for the encoder-decoder type of models in terms of learning sentence representations, and based on our results, we present 2 findings. 2. The two interesting findings lead to our final model design, which has an RNN encoder and a CNN decoder, and it learns to encode the current sentence and decode the subsequent contiguous words all at once. 3. With a suite of techniques, our model performs good on downstream tasks and can be trained efficiently on a large unlabelled corpus.
A Four-Vertex Theorem for Frieze Patterns?

Given two Coxeter's frieze patterns with the same width and consisting of positive numbers, choose a row and consider the periodic sequence of the differences of the respective entries of the two friezes. We ask for which rows this sequence must change sign at least four times over the period. We prove that this is the case for the first and for the second non-trivial rows, and that this is true, for all rows, for an infinitesimal version of the question. The article also contains expository material on the four vertex theorem and on Coxeter's frieze patterns.
Legislative Capacity and Credit Risk

Legislatures differ in their institutional capacity to draft and enact policy. While strong legislatures can increase the congruence of policy outcomes to the electorate's preferences, they can also inject uncertainty into markets with their ability to alter the political economic landscape. We argue that this uncertainty will manifest in a state's ability to borrow and hypothesize a negative relationship between legislative capacity and credit-worthiness. Using ratings of general obligation bonds issued by the American states over nearly two decades and data on the institutional capacity of state legislative assemblies, we find support for the claim that having a legislature that is better equipped to affect policy change increases credit risk evaluations. The results we present broaden our understanding of the importance of legislative institutions, the determinants of credit risk, and the economic implications of democratic responsiveness.
A novel method for epileptic seizure detection using coupled hidden markov models

We propose a novel Coupled Hidden Markov Model to detect epileptic seizures in multichannel electroencephalography (EEG) data. Our model defines a network of seizure propagation paths to capture both the temporal and spatial evolution of epileptic activity. To address the intractability introduced by the coupled interactions, we derive a variational inference procedure to efficiently infer the seizure evolution from spectral patterns in the EEG data. We validate our model on EEG aquired under clinical conditions in the Epilepsy Monitoring Unit of the Johns Hopkins Hospital. Using 5-fold cross validation, we demonstrate that our model outperforms three baseline approaches which rely on a classical detection framework. Our model also demonstrates the potential to localize seizure onset zones in focal epilepsy.
Effective Machine Learning Based Format Selection and Performance Modeling for SpMV on GPUs

Sparse Matrix-Vector multiplication (SpMV) is a key kernel for many applications in computational science and data analytics. Several efforts have addressed the optimization of SpMV on GPUs, and a number of compact sparse-matrix representations have been considered for it. It has been observed that the sparsity pattern of non-zero elements in a sparse matrix has a significant impact on achieving SpMV performance. Further, no single sparse-matrix format is consistently the best across the range of sparse matrices encountered in practice. In this paper, we perform a comprehensive study that explores the use of Machine Learning to answer two questions: 1) Given an unseen sparse matrix, can we effectively predict the best format for SpMV on GPUs? 2) Can SpMV execution time for that matrix be predicted, for different matrix formats? By identifying a small set of sparse matrix features to use in training the ML models, we demonstrate that efficient prediction of the best format with ? 88% accuracy can be achieved when selecting between six well known sparse-matrix formats on two GPU architectures (NVIDIA Pascal and Kepler), and ? 10% relative mean error (RME) with execution time prediction.
Modeling of reaction-diffusion transport into a core-shell geometry

Abstract Fickian diffusion into a core-shell geometry is modeled. The interior core mimics pancreatic Langerhan islets and the exterior shell acts as inert protection. The consumption of oxygen diffusing into the cells is approximated using Michaelis-Menten kinetics. The problem is transformed to dimensionless units and solved numerically. Two regimes are identified, one that is diffusion limited and the other consumption limited. A regression is fit that describes the concentration at the center of the cells as a function of the relevant physical parameters. It is determined that, in a cell culture environment, the cells will remain viable as long as the islet has a radius of around 142 µm or less and the encapsulating shell has a radius of less than approximately 283 µm. When the islet is on the order of 100 µm it is possible for the cells to remain viable in environments with as little as 4.6 × 10 − 2 mol/m − 3 O2. These results indicate such an encapsulation scheme may be used to prepare artificial pancreas to treat diabetes.
Hardware Translation Coherence for Virtualized Systems

To improve system performance, operating systems (OSes) often undertake activities that require modification of virtual-to-physical address translations. For example, the OS may migrate data between physical pages to manage heterogeneous memory devices. We refer to such activities as page remappings. Unfortunately, page remappings are expensive. We show that a big part of this cost arises from address translation coherence, particularly on systems employing virtualization. In response, we propose hardware translation invalidation and coherence or HATRIC, a readily implementable hardware mechanism to piggyback translation coherence atop existing cache coherence protocols. We perform detailed studies using KVM-based virtualization, showing that HATRIC achieves up to 30% performance and 10% energy benefits, for per-CPU area overheads of 0.2%. We also quantify HATRIC's benefits on systems running Xen and find up to 33% performance improvements.
An experimental investigation of preference misrepresentation in the residency match.

The development and deployment of matching procedures that incentivize truthful preference reporting is considered one of the major successes of market design research. In this study, we test the degree to which these procedures succeed in eliminating preference misrepresentation. We administered an online experiment to 1,714 medical students immediately after their participation in the medical residency match—a leading field application of strategy-proof market design. When placed in an analogous, incentivized matching task, we find that 23% of participants misrepresent their preferences. We explore the factors that predict preference misrepresentation, including cognitive ability, strategic positioning, overconfidence, expectations, advice, and trust. We discuss the implications of this behavior for the design of allocation mechanisms and the social welfare in markets that use them.
Classification and construction of higher-order symmetry-protected topological phases of interacting bosons

Motivated by the recent discovery of higher-order topological insulators, we study their counterparts in strongly interacting bosons: ``higher-order symmetry-protected topological (HOSPT) phases.'' While the usual (first-order) SPT phases in $d$ spatial dimensions support anomalous $(d\ensuremath{-}1)$-dimensional surface states, HOSPT phases in $d$ dimensions are characterized by topological boundary states of dimension $(d\ensuremath{-}2)$ or smaller, protected by certain global symmetries and robust against disorders. Based on a dimensional reduction analysis, we show that HOSPT phases can be built from lower-dimensional SPT phases in a way that preserves the associated crystalline symmetries. When the total symmetry is a direct product of global and crystalline symmetry groups, we are able to classify the HOSPT phases using the K\"unneth formula of group cohomology. Based on a decorated domain-wall picture of the K\"unneth formula, we show how to systematically construct the HOSPT phases, and demonstrate our construction with many examples in two and three dimensions.
Do Neighborhoods Affect Credit Market Decisions of Low-Income Borrowers? Evidence from the Moving to Opportunity Experiment

This paper provides new evidence on the long-term impacts of neighborhood environment on low-income credit decisions by analyzing financial outcomes and borrowing decisions of participants of the Moving to Opportunity (MTO) experiment. The MTO experiment was a unique, large-scale experiment that offered families vouchers to move to better neighborhoods via randomized lottery. Families received one of two types of housing vouchers: the first (Experimental) required families to move to very low poverty neighborhoods, and the second (Section 8) allowed families unrestricted choice of neighborhood. We find that participants who moved to lower poverty neighborhoods as young children experienced better access to and greater use of credit into adulthood, with the largest effects experienced by those who moved to the lowest poverty neighborhoods. While we do not find adult and older children experience the same benefits to credit outcomes, we do find they experience improvements in delinquency and debt behaviors, particularly among those who received unrestricted Section 8 vouchers. We also find evidence that children whose families received unrestricted Section 8 vouchers have significantly lower payday loan usage.
The entitlement effect in the ultimatum game – does it even exist?

Abstract Since the seminal paper of Hoffman et al. (1994), an entitlement effect is believed to exist in the Ultimatum Game, in the sense that proposers who have earned their role (as opposed to having it randomly allocated) offer a smaller share of the pie to their matched responder. The entitlement effect is at the core of experimental Public Choice – not just because it concerns the topics of bargaining and negotiations, but also because it relates to the question about under which circumstances actors behave more rational. We conduct three experiments, two in the laboratory and one online, with more than 1,250 participants. Our original motivation was to study gender differences, but ultimately we could not replicate the entitlement effect in the Ultimatum Game in any of our three experiments. Potential reasons for why the replication attempts fail are discussed.
A novel preoperative model to predict 90-day surgical mortality in patients considered for renal cell carcinoma surgery

Abstract Introduction Surgical benefits for renal cell carcinoma must be weighed against competing causes of mortality, especially in the elderly patient population. We used a large cancer registry to evaluate the impact of patient and cancer-specific factors on 90-day mortality (90DM). A nomogram to predict the odds of short-term mortality was created. Materials and Methods The National Cancer Database was queried to identify all patients with clinically localized, nonmetastatic disease treated with partial or radical nephrectomy. Using a random sample of 60%, multiple logistic regression with 90DM outcomes were performed to identify preoperative variables associated with mortality. Variables included age, sex, race, co-morbidity score, tumor size, and presence of a thrombus. A nomogram was created and tested on the remaining 40% of patients to predict 90DM. Results 183,407 patients met inclusion criteria. Overall 90DM for the cohort was 1.9%. All preoperative variables significantly influenced the risk of 90DM. Patient age was by far the strongest predictor. Nomogram scores ranged from 0 to 12. Compared to patients with 0 to 1 points, those with 2 to 3 (odds ratio [OR] 2.89, 2.42–3.46; P P 6 (OR 12.86, 10.83–15.27; P 80 years of age alone placed patients into the highest risk of surgical mortality. Conclusions Management of localized kidney cancer must consider competing causes of mortality, especially in elderly patients with multiple co-morbidities. We present a preoperative tool to calculate risk of surgical short-term mortality to aid surgeon–patient counseling.
Techniques for Regulating Military Force

This book chapter identifies and analyzes some of the techniques that states use to regulate their war powers, and then reflects on the value of comparative research in this area. Three basic techniques are: (1) to establish substantive standards on when the government may or may not use force, (2) to divide among different branches of government the authority to deploy the country’s armed forces, and (3) to subject such decisions to oversight or review. There is considerable variation, both across countries and over time within particular countries, in how and with what effect each technique is used. Given this variation, comparative war powers research is likely to be of limited relevance to national officials who make use of force decisions or to analysts who seek to explain them. Instead, the principal benefit of such research might be to bring into stark relief a country’s own national ethos — to shed light on how it defines itself and conceives of its relationship with the rest of the world.
Local Explanation Methods for Deep Neural Networks Lack Sensitivity to Parameter Values

Explaining the output of a complicated machine learning model like a deep neural network (DNN) is a central challenge in machine learning. Several proposed local explanation methods address this issue by identifying what dimensions of a single input are most responsible for a DNN's output. The goal of this work is to assess the sensitivity of local explanations to DNN parameter values. Somewhat surprisingly, we find that DNNs with randomly-initialized weights produce explanations that are both visually and quantitatively similar to those produced by DNNs with learned weights. Our conjecture is that this phenomenon occurs because these explanations are dominated by the lower level features of a DNN, and that a DNN's architecture provides a strong prior which significantly affects the representations learned at these lower layers. NOTE: This work is now subsumed by our recent manuscript, Sanity Checks for Saliency Maps (to appear NIPS 2018), where we expand on findings and address concerns raised in Sundararajan et. al. (2018).
Moreau-type characterizations of polar cones

Abstract A theorem of Moreau (1962) states that given a closed convex cone C and its (negative) polar cone C ∘ in a real Hilbert space H, vectors y ∈ C and z ∈ C ∘ are metric projections of a vector u ∈ H on C and C ∘ , respectively, if and only if they satisfy the following conditions: y and z are orthogonal and u = y + z . We show that these conditions provide characteristic properties of polar cones C and C ∘ in the family of pairs of convex subsets of H or R n . A related result on separation of C and a convex subcone of C ∘ is proved.