cssi/SciSciGPT-SciSciNet huggingface dataset:
Applying the Revised ABA Model Rules in the Age of the Internet: The Problem of Metadata

Symposiums are a tradition that date to the dawn of Western Civilization. The ancient Greeks often gathered for a convivial meeting where they leisurely dined and drank while engaged in intellectual conversation about a particular topic. The word “symposium” derives from the Greek word meaning to come together and drink. 1 Plato called one of his dialogues, the Symposium. 2 The Jewish Seder evolved into a symposium reflecting on the Exodus from Egypt. 3 It is an honor to participate in this Symposium on Legal Ethics. The topic of this Symposium focuses on the Ethical Infrastructure and Culture of Law Firms. The culture of every law firm must emphasize competence. Indeed, the first rule of legal ethics, the prime directive, if you will, is competence. To emphasize that point, the Model Rules of Professional Conduct (“Model Rules” or “Rules”) 4 designates its first rule, Rule 1.1, “Competence.” 5 Competence requires the lawyer to “keep abreast of changes in the law and its practice,” and means that lawyers must learn about “the benefits and risks associated with relevant technology.” 6 That technology increases exponentially the risks of
Shady Grove, the Rules Enabling Act, and the Application of State Summary Judgment Standards in Federal Diversity Cases

Although most states have adopted procedural rules for civil actions that are based upon the Federal Rules of Civil Procedure, not all state courts have chosen to follow the Supreme Court’s interpretation of Rule 56 in Celotex Corp. v. Catrett. Notwithstanding similarities between the language of Rule 56 and corresponding state summary judgment rules, several states have interpreted their own rules more restrictively than the Celotex plurality construed the federal rule. As a result, it is more difficult in those states for a moving party to obtain summary judgment in state court than it is in federal court. This article summarizes the relevant history of the Erie/Hanna doctrine, including its origins in both the Rules of Decision Act and the Rules Enabling Act, and analyzes Shady Grove Orthopedic Associates v. Allstate Insurance Co., the latest landmark in the Supreme Court’s Erie jurisprudence. It highlights how certain state courts have distinguished their summary judgment rules from the interpretation of the federal rule set forth in Celotex. Finally, it argues that, based upon the controlling precedent from Justice Stevens’ concurring opinion in Shady Grove, a federal court sitting in diversity should apply the state standard for adjudicating a motion for summary judgment if it differs from the Celotex standard. Specifically, the results of several lower court decisions applying Shady Grove suggest that the case has revived the possibility that a Federal Rule of Civil Procedure that otherwise controls the issue in dispute might be invalidated under the Rules Enabling Act as abridging, enlarging, or modifying a substantive right. A lasting (and perhaps unintended) legacy of the fractured Shady Grove case, therefore, may be that it have opened the door to the increased application of state rules – and, potentially, state summary judgment standards – by federal courts sitting in diversity.
Self-referential thinking and equilibrium as states of mind in games: fMRI evidence ✩

Sixteen subjects' brain activity were scanned using previous termfMRInext term as they made choices, expressed beliefs, and expressed iterated 2nd-order beliefs (what they think others believe they will do) in eight games. Cingulate cortex and prefrontal areas (active in “theory of mind” and social reasoning) are differentially activated in making choices versus expressing beliefs. Forming self-referential 2nd-order beliefs about what others think you will do seems to be a mixture of processes used to make choices and form beliefs. In equilibrium, there is little difference in neural activity across choice and belief tasks; there is a purely neural definition of equilibrium as a “state of mind.” “Strategic IQ,” actual earnings from choices and accurate beliefs, is negatively correlated with activity in the insula, suggesting poor strategic thinkers are too self-focused, and is positively correlated with ventral striatal activity (suggesting that high IQ subjects are spending more mental energy predicting rewards).
Business–Government Relations and Industrial Change: The Politics of Upgrading in Morocco and Tunisia

Summary Processes of upgrading and the promotion of industrial “clusters,” which encompass multiple policies, institutions, and actors, necessarily vary from place to place. Based on the evidence from Morocco and Tunisia, this article contends that different patterns of business–government relations facilitate different elements of industrial upgrading and cluster promotion. State-dominated political economies may be more amenable to implementing macroeconomic and infrastructure-related measures, which are critical in the initial stages of upgrading. Political economies with more organized business communities may be better equipped to pursue the kinds of inter-firm linkages traditionally associated with later phases of upgrading, when the focus is on boosting innovation.
Trade 2.0

Where the last century saw the dismantling of barriers to trade in goods, the new century will see the dismantling of barriers to trade in services. Once theorized as nontradable, services now join goods in a global marketplace powered by advances in communications technology. Today, an engineer, accountant, or lawyer can supply her services across the globe without boarding a plane. Less well understood is that cyber-trade encompasses not just the services outsourced to Bangalore, but also the online services supplied by Silicon Valley to the world. Apple, eBay, and Yahoo too are exporters of information services, seeking to become middlemen to the world. Google now earns half of its income overseas. Almost sub rosa, the Internet has become a global trading platform rivaling any history has yet produced. But law developed over millennia for the paradigm of goods is unprepared for trade, version 2.0. The pressure on law is clear: Antigua challenges U.S. rules barring online gambling; Brazil demands that Google identify hate speakers; an Alien Torts Statute suit charges Yahoo with abetting Chinese torture; and the United States challenges Chinese media restrictions on movie, music, and financial information services. Once we recognize the connections between these disputes, we can begin to form a general theory of cyber-trade. Ricardo’s theory of comparative advantage applies to all trade, whether in goods or in information. Economic theory thus counsels, and international treaties compel, the dismantling of barriers to cyber-trade. Yet, because of its remote nature, it is easy to assert consumer protection to bar online competition. I articulate a principle of technological neutrality to smoke out barriers hiding under this veneer. To flourish, cyber-trade will also require digital analogues to the physical infrastructure for services, from handshakes to courts. The footloose nature of cyber-trade poses a more fundamental challenge - to law itself. Via the net, service providers can flout local law from afar. This race to the bottom arises from the exploitation of overly liberal regimes, lacking consumer and other protections. A second potential race to the bottom arises from overly repressive regimes, which require service providers to serve as auxiliaries of the authoritarian state. I offer principles to protect local control of global Internet trade without jeopardizing either human rights or the World-Wide nature of the Web.
Learning Hyperbolic Representations of Topological Features

Learning task-specific representations of persistence diagrams is an important problem in topological data analysis and machine learning. However, current state of the art methods are restricted in terms of their expressivity as they are focused on Euclidean representations. Persistence diagrams often contain features of infinite persistence (i.e., essential features) and Euclidean spaces shrink their importance relative to non-essential features because they cannot assign infinite distance to finite points. To deal with this issue, we propose a method to learn representations of persistence diagrams on hyperbolic spaces, more specifically on the Poincare ball. By representing features of infinite persistence infinitesimally close to the boundary of the ball, their distance to non-essential features approaches infinity, thereby their relative importance is preserved. This is achieved without utilizing extremely high values for the learnable parameters, thus the representation can be fed into downstream optimization methods and trained efficiently in an end-to-end fashion. We present experimental results on graph and image classification tasks and show that the performance of our method is on par with or exceeds the performance of other state of the art methods.
Business Strategy, Human Capital, and Managerial Incentives

We posit that the value of a manager’s human capital depends on the firm’s business strategy. The resulting interaction between business strategy and managerial incentives aects the organization of business activities, both the internal organization of the firm and the determination of firm boundaries. We illustrate the impact of this interaction on firm boundaries in a dynamic agency model. There may be disadvantages in merging two firms even when such a merger allows the internalization of externalities between the two firms. Merging, by making unprofitable certain decisions, increases the cost of inducing managerial eort. This incentive cost is a natural consequence of the manager’s business-strategy-specific human capital.
The Importance of Recognizing Trauma Throughout Capital Mitigation Investigations and Presentations

Psychological trauma lies at the heart of death penalty cases. This is most immediately and obviously true because of the unspeakable grief and irrevocably altered lives that follow the loss of a loved one to homicide. But it is also an almost universal feature of the lives of capitally charged and convicted defendants. Assessing the role of trauma is (or should be) an essential component of any competent mitigation investigation and any competent assessment of mental health issues in a capital case. Sadly, many clients on death row across the country—clients with trauma histories of extraordinary severity and chronicity—had little or no information about these histories presented at trial. Others had some limited information provided, but that information was incomplete, poorly developed and presented, and lacked a coherent explanation or expert guidance as to its significance and the unique psychological factors that rendered them so disabled. Still others
Reflections on US—Zeroing: A Study in Judicial Overreaching by the WTO Appellate Body

One of the underappreciated developments in international trade law is the degree to which the WTO Appellate Body is failing to abide by negotiated procedural norms in reviewing Member State action. This essay highlights systemic problems with Appellate Body decision-making as reflected in the controversial case of US-Zeroing. The problems reflected in USZeroing go to central issues of judicial restraint, including concerns regarding the standard of review, appellate fact-finding, and justiciable notions of ripeness. This essay concludes that the Appellate Body in US-Zeroing circumvented the particularized standard of review required under the WTO Agreement, took upon itself the unacceptable task of appellate fact-finding, and inappropriately expanded the authority to hear facial challenges of discretionary agency action. In short, the US-Zeroing decision belies the felicitous notion that WTO dispute resolution embraces an approach of judicial restraint. The WTO Agreements require the Appellate Body to defer to reasonable Member State interpretations of WTO treaty obligations in a manner analogous to Chevron deference. As US-Zeroing underscores, the Appellate Body in fact has eschewed anything approaching Chevron deference. The essay suggests that the Appellate Body is overreaching in not adhering to its obligations to defer. The essay also highlights the problem of Appellate Body fact-finding in US-Zeroing. The essay argues that the case is troubling because the WTO agreements require WTO panels to defer to the objective and unbiased factual findings of Member State authorities, and doubly troubling because the Appellate Body's assessment of the facts under the DSU requires deference to the factual findings of the WTO panels. As such, the WTO agreements require double deference to factual findings below. But the Appellate Body in US-Zeroing displayed no such deference. Finally, the essay focuses on the movement away from the mandatory/discretionary doctrine. That doctrine was the essential limitation on facial challenges to Member State action that did not rise to the level of mandatory obligations. As a consequence of the Appellate Body's interpretation in US-Zeroing, facial challenges once reserved for provisions of binding legislation are now available for virtually any general and prospective agency action. Quite literally, the Appellate Body's decision in US-Zeroing suggests that review of discretionary agency action will be more robust and searching when undertaken by an exacting international body in Geneva than by a deferential federal court in New York.
Beyond Coercion: Justice Kennedy's Aversion to Animus

In evaluating the constitutionality of religious displays, Justice Kennedy adheres to the coercion test. A creche on the courthouse steps is acceptable because it does not coerce anyone to support or participate in a religious exercise. He rejects the endorsement test, which asks whether the display makes reasonable nonadherents feel like outsiders, finding it to be "flawed in its fundamentals and unworkable in practice." Yet in the free exercise context, Kennedy has focused on whether a community shows hostility to minority faiths, and his opinions in Romer and Lawrence stress that legislatures acted unconstitutionally in showing animus to gays. Suppose a passive religious display conveyed a message of animus. Imagine, for example, a plaque on the courthouse wall that quoted Leviticus: "Thou shalt not lie with mankind, as with womankind: it is abomination." I believe Kennedy would strike down the display on the ground that it makes a reasonable gay observer feel like a pariah in the community, an approach similar to the endorsement test.
DICEY WAS NOT DICEYAN

There is an apparent paradox between Dicey's treatment of parliamentary sovereignty as the central premise of the British constitution and his advocacy of the referendum, a tool of popular sovereignty. Bogdanor wrote: [i]t is paradoxical that Dicey should have been the first to advocate the referendum in Britain, for he was the author of the classic work Introduction to the Study of the Law of the Constitution (1885). Foremost among the principles there identified as central to the British Constitution was the sovereignty of Parliament—a principle generally held to preclude the referendum. Cosgrove, who wrote an authoritative biography on Dicey, explained that Dicey turned to the referendum in his search for a device that would prevent Home Rule. Dicey's commitment to defeat Home Rule, he wrote, distorted his judgment.
Targeting primary and metastatic uveal melanoma with a G protein inhibitor.

Uveal melanoma (UM) is the most common intraocular tumor in adults. Nearly half of UM patients develop metastatic disease and often succumb within months because effective therapy is lacking. A novel therapeutic approach has been suggested by the discovery that UM cell lines driven by mutant constitutively active Gq or G11 can be targeted by FR900359 (FR) or YM-254890, which are bioavailable, selective inhibitors of the Gq/11/14 subfamily of heterotrimeric G proteins. Here, we have addressed the therapeutic potential of FR for UM. We found that FR inhibited all oncogenic Gq/11 mutants reported in UM. FR arrested growth of all Gq/11-driven UM cell lines tested, but induced apoptosis only in a few. Similarly, FR inhibited growth of, but did not efficiently kill, UM tumor cells from biopsies of primary or metastatic tumors. FR evoked melanocytic redifferentiation of UM tumor cells with low (class 1), but not high (class 2), metastatic potential. FR administered systemically below its LD50 strongly inhibited growth of PDX-derived class 1 and class 2 UM tumors in mouse xenograft models and reduced blood pressure transiently. FR did not regress xenografted UM tumors or significantly affect heart rate, liver function, hematopoiesis, or behavior. These results indicated the existence of a therapeutic window in which FR can be explored for treating UM and potentially other diseases caused by constitutively active Gq/11.
Explosion analysis from images: Trinity and Beirut

Images of an explosion can be used to study some of its physical properties. After reviewing the key aspects of the method originally developed to study the first nuclear detonation and analyzing the Trinity blast data, the method is applied to the Beirut explosion of August 2020 by using images from videos posted online. The applicability of the method is discussed and the process of selection, extraction, and analysis of the data is presented. The estimate for the energy yield of the Beirut explosion is found to be $2.3^{+1.1}_{-1.1}$ TJ or $0.6^{+0.3}_{-0.3}$ kt of TNT equivalent. The result is consistent with others recently appeared in the literature using different methods. Notice that this article includes content that some readers may find distressing.
Language and reality at the end of life.

Journal of Law, Medicine & Ethics, 28 (2000): 267–278. © 2000 by the American Society of Law, Medicine & Ethics. o find adequate answers to a changing reality heavily influenced by advances in technology, medical professionals have developed and adopted an array of terms that have brought new concepts into the profession. “Dignity,” “vegetative state,” “futility,” “double effect,” and “brain death” have become indispensable words in the medical setting. In the following discussion, the attention is on terminology. If we believe in phenomenology, the assumption is that we should closely reflect on the words we use in all spheres of life, especially in those that concern life and death. This article calls for a sincere discussion about these terms and concepts. The thesis put forward is that the language in the medical setting serves primarily the physicians, at times at the expense of the patients’ best interests. This language and the concepts it describes have generated an unhealthy atmosphere for patients, which might lead to undesirable actions at the end of patients’ lives.
Saccharomyces cerevisiae Ecm2 Modulates the Catalytic Steps of pre-mRNA Splicing

Genetic, biochemical, and structural studies have elucidated the molecular basis for spliceosome catalysis. Splicing is RNA catalyzed and the essential snRNA and protein factors are well-conserved. However, little is known about how non-essential components of the spliceosome contribute to the reaction and modulate the activities of the fundamental core machinery. Ecm2 is a non-essential yeast splicing factor that is a member of the Prp19-related complex of proteins. Cryo-electron microscopy (cryo-EM) structures have revealed that Ecm2 binds the U6 snRNA and is entangled with Cwc2, a factor previously found to promote a catalytically active conformation of the spliceosome. These structures also indicate that Ecm2 and the U2 snRNA likely form a transient interaction during 5' splice site (SS) cleavage. We have characterized genetic interactions between ECM2 and alleles of splicing factors that alter the catalytic steps in splicing. In addition, we have studied how loss of ECM2 impacts splicing of pre-mRNAs containing non-consensus or competing SS. Our results show that ECM2 functions during the catalytic stages of splicing. Our data are consistent with Ecm2 facilitating the formation and stabilization of the 1st-step catalytic site, promoting 2nd-step catalysis, and permiting alternate 5' SS usage. We propose that Cwc2 and Ecm2 can each fine-tune the spliceosome active site in unique ways. Their interaction network may act as a conduit through which splicing of certain pre-mRNAs, such as those containing weak or alternate splice sites, can be regulated.
The characteristics of multi-source mobility datasets and how they reveal the luxury nature of social distancing in the U.S. during the COVID-19 pandemic

This study reveals the human mobility from various sources and the luxury nature of social distancing in the U.S during the COVID-19 pandemic by highlighting the disparities in mobility dynamics fr...
NSan: a floating-point numerical sanitizer

Sanitizers are a relatively recent trend in software engineering. They aim at automatically finding bugs in programs, and they are now commonly available to programmers as part of compiler toolchains. For example, the LLVM project includes out-of-the-box sanitizers to detect thread safety (tsan), memory (asan,msan,lsan), or undefined behaviour (ubsan) bugs. In this article, we present nsan, a new sanitizer for locating and debugging floating-point numerical issues, implemented inside the LLVM sanitizer framework. nsan puts emphasis on practicality. It aims at providing precise, and actionable feedback, in a timely manner. nsan uses compile-time instrumentation to augment each floating-point computation in the program with a higher-precision shadow which is checked for consistency during program execution. This makes nsan between 1 and 4 orders of magnitude faster than existing approaches, which allows running it routinely as part of unit tests, or detecting issues in large production applications.
Ad Hoc Procedure

“Ad hoc procedure” seems like an oxymoron. A traditional model of the civil justice system depicts courts deciding cases using impartial procedures that are defined in advance of specific disputes. This model reflects a process-based account of the rule of law in which the process through which laws are made helps to ensure that lawmakers act in the public interest. Judgments produced using procedures promulgated in advance of specific disputes are legitimate because they are the product of fair rules of play designed in a manner that is the opposite of ad hoc. Actual litigation frequently reveals the inadequacy of procedures created according to this traditional model. To fix the procedural problems that arise in such cases, litigants, judges, lawyers, and legislatures can design procedure on the fly, changing the “rules of the road” as the case proceeds. Ad hoc procedure-making allows the civil justice system to function when ordinary procedure fails, but it challenges the rule-of-law values reflected in the traditional model of procedural design. Instead of being created by lawmakers who operate behind a veil of ignorance, ad hoc procedure is made by actors seeking specific outcomes in pending cases. The circumstances in which ad hoc procedure is created raise concerns about lawmakers’ motivations, the transaction costs of one-off procedural interventions, the wisdom and fairness of those interventions, and the separation of powers. This Article introduces the phenomenon of ad hoc procedure and considers its place in a world where much procedure continues to be made through the traditional model. Focusing on ad hoc procedural statutes, the Article contends that such statutes’ legitimacy—or lack thereof—depends on different factors than ordinary civil procedure. Unable to claim legitimacy from the circumstances in which it is crafted, ad hoc procedural legislation must instead derive legitimacy from the necessity to address a procedural problem and the effort to produce substantively just outcomes.
Magnetic reconnection and thermal equilibration

When a magnetic field is forced to evolve on a time scale τev, as by footpoint motions driving the solar corona or non-axisymmetric instabilities in tokamaks, the magnetic field lines undergo large-scale changes in topology on a time scale approximately an order of magnitude longer than τev. But the physics that allows such changes operates on a time scale eight or more orders of magnitude slower. An analogous phenomenon occurs in air. Temperature equilibration occurs on a time scale approximately an order of magnitude longer than it takes air to cross a room, τev, although the physical mechanism that allows temperature equilibration is approximately four orders of magnitude slower than τev. The use of Lagrangian coordinates allows the fundamental equations to be solved and both phenomena explained. The theories of thermal equilibration and magnetic reconnection are developed in parallel to help readers obtain an understanding of the importance and implications of analyses using Lagrangian coordinates.
Knowledge- and Data-driven Services for Energy Systems using Graph Neural Networks

The transition away from carbon-based energy sources poses several challenges for the operation of electricity distribution systems. Increasing shares of distributed energy resources (e.g. renewable energy generators, electric vehicles) and internet-connected sensing and control devices (e.g. smart heating and cooling) require new tools to support accurate, data-driven decision making. Modelling the effect of such growing complexity in the electrical grid is possible in principle using state-of-the-art power-power flow models. In practice, the detailed information needed for these physical simulations may be unknown or prohibitively expensive to obtain. Hence, data-driven approaches to power systems modelling, including feed-forward neural networks and auto-encoders, have been studied to leverage the increasing availability of sensor data, but have seen limited practical adoption due to lack of transparency and inefficiencies on large-scale problems. Our work addresses this gap by proposing a data- and knowledge-driven probabilistic graphical model for energy systems based on the framework of graph neural networks (GNNs). The model can explicitly factor in domain knowledge, in the form of grid topology or physics constraints, thus resulting in sparser architectures and much smaller parameters dimensionality when compared with traditional machine-learning models with similar accuracy. Results obtained from a real-world smart-grid demonstration project show how the GNN was used to inform grid congestion predictions and market bidding services for a distribution system operator participating in an energy flexibility market.
Amplitude-Aware Lossy Compression for Quantum Circuit Simulation

Classical simulation of quantum circuits is crucial for evaluating and validating the design of new quantum algorithms. However, the number of quantum state amplitudes increases exponentially with the number of qubits, leading to the exponential growth of the memory requirement for the simulations. In this paper, we present a new data reduction technique to reduce the memory requirement of quantum circuit simulations. We apply our amplitude-aware lossy compression technique to the quantum state amplitude vector to trade the computation time and fidelity for memory space. The experimental results show that our simulator only needs 1/16 of the original memory requirement to simulate Quantum Fourier Transform circuits with 99.95% fidelity. The reduction amount of memory requirement suggests that we could increase 4 qubits in the quantum circuit simulation comparing to the simulation without our technique. Additionally, for some specific circuits, like Grover's search, we could increase the simulation size by 18 qubits.
Optimization problems related to zigzag pocket machining

A fundamental problem of manufacturing is to produce mechanical parts from billets by clearing areas within specified boundaries from the material. Based on a graph-theoretical formulation, the algorithmic handling of one particular machining problem—``zigzag pocket machining''—is investigated. We present a linear-time algorithm that ensures that every region of the pocket is machined exactly once, while attempting to minimize the number of tool retractions required. This problem is shown to be ${\cal N\cal P}$ -hard for pockets with holes. Our algorithm is provably good in the sense that the machining path generated for a pocket with h holes requires at most 5 . . . OPT + 6 . . . h retractions, where OPT is the (unknown) minimum number of retractions required by any algorithm. The algorithm has been implemented, and practical tests for pockets without holes suggest that one can expect an approximation factor of about 1.5 for practical examples, rather than the factor 5 as proved by our analysis.
PFirewall: Semantics-Aware Customizable Data Flow Control for Smart Home Privacy Protection.

Internet of Things (IoT) platforms enable users to deploy home automation applications. Meanwhile, privacy issues arise as large amounts of sensitive device data flow out to IoT platforms. Most of the data flowing out to a platform actually do not trigger automation actions, while homeowners currently have no control once devices are bound to the platform. We present PFirewall, a customizable data-flow control system to enhance the privacy of IoT platform users. PFirewall automatically generates data-minimization policies, which only disclose minimum amount of data to fulfill automation. In addition, PFirewall provides interfaces for homeowners to customize individual privacy preferences by defining user-specified policies. To enforce these policies, PFirewall transparently intervenes and mediates the communication between IoT devices and the platform, without modifying the platform, IoT devices, or hub. Evaluation results on four real-world testbeds show that PFirewall reduces IoT data sent to the platform by 97% without impairing home automation, and effectively mitigates user-activity inference/tracking attacks and other privacy risks.
Pentosan polysulfate maculopathy versus age-related macular degeneration: Comparative assessment with multimodal imaging.

OBJECTIVE To evaluate whether pentosan polysulfate maculopathy manifests distinctive imaging features that can be differentiated from those found in age-related macular degeneration (AMD). METHODS Local databases were queried to identify patients with a diagnosis of interstitial cystitis who were seen at the Emory Eye Center between May 2014 and January 2019 and who had fundus imaging available for review. Ninety patients met the eligibility criteria. Masked graders categorized patients based on imaging characteristics as follows: category 1: pentosan polysulfate maculopathy; category 2: AMD or drusen; category 3: neither; and category 4: unsure. Pentosan polysulfate exposure characteristics were compared among groups. RESULTS Of the 90 subjects evaluated, 79 (88%) were female and the median age was 61.5 years (range, 30-89). Seventeen patients were placed in category 1; 25 in category 2; 47 in category 3, and; 1 in category 4. Among categories 1 to 4, respectively, 17 (100%), 15 (60%), 28 (60%), and 0 patients had exposure to pentosan polysulfate (p = 0.007). Mean cumulative exposure to pentosan polysulfate across the four categories was 2.1, 0.36, 0.34, and 0 kg, respectively (p < 0.00001). Eyes with pentosan polysulfate maculopathy did not have typical drusen in the macula. CONCLUSION Although pentosan polysulfate maculopathy resembles some aspects of AMD, the 2 conditions can be differentiated with the use of multimodal fundus imaging.
Bosonic Fields in Causal Set Theory

In this paper we will define a Lagrangian for scalar and gauge fields on causal sets, based on the selection of an Alexandrov set in which the variations of appropriate expressions in terms of either the scalar field or the gauge field holonomies around suitable loops take on the least value. For these fields, we will find that the values of the variations of these expressions define Lagrangians in covariant form.
Generative modeling of convolutional neural networks

Abstract: The convolutional neural networks (CNNs) have proven to be a powerful tool for discriminative learning. Recently researchers have also started to show interest in the generative aspects of CNNs in order to gain a deeper understanding of what they have learned and how to further improve them. This paper investigates generative modeling of CNNs. The main contributions include: (1) We construct a generative model for the CNN in the form of exponential tilting of a reference distribution. (2) We propose a generative gradient for pre-training CNNs by a non-parametric importance sampling scheme, which is fundamentally different from the commonly used discriminative gradient, and yet has the same computational architecture and cost as the latter. (3) We propose a generative visualization method for the CNNs by sampling from an explicit parametric image distribution. The proposed visualization method can directly draw synthetic samples for any given node in a trained CNN by the Hamiltonian Monte Carlo (HMC) algorithm, without resorting to any extra hold-out images. Experiments on the challenging ImageNet benchmark show that the proposed generative gradient pre-training consistently helps improve the performances of CNNs, and the proposed generative visualization method generates meaningful and varied samples of synthetic images from a large-scale deep CNN.
Autodidactic Neurosurgeon: Collaborative Deep Inference for Mobile Edge Intelligence via Online Learning

Recent breakthroughs in deep learning (DL) have led to the emergence of many intelligent mobile applications and services, but in the meanwhile also pose unprecedented computing challenges on resource-constrained mobile devices. This paper builds a collaborative deep inference system between a resource-constrained mobile device and a powerful edge server, aiming at joining the power of both on-device processing and computation offloading. The basic idea of this system is to partition a deep neural network (DNN) into a front-end part running on the mobile device and a back-end part running on the edge server, with the key challenge being how to locate the optimal partition point to minimize the end-to-end inference delay. Unlike existing efforts on DNN partitioning that rely heavily on a dedicated offline profiling stage to search for the optimal partition point, our system has a built-in online learning module, called Autodidactic Neurosurgeon (ANS), to automatically learn the optimal partition point on-the-fly. Therefore, ANS is able to closely follow the changes of the system environment by generating new knowledge for adaptive decision making. The core of ANS is a novel contextual bandit learning algorithm, called μLinUCB, which not only has provable theoretical learning performance guarantee but also is ultra-lightweight for easy real-world implementation. We implement our system on a video stream object detection testbed to validate the design of ANS and evaluate its performance. The experiments show that ANS significantly outperforms state-of-the-art benchmarks in terms of tracking system changes and reducing the end-to-end inference delay.
Self-Supervised Hyperboloid Representations from Logical Queries over Knowledge Graphs

Knowledge Graphs (KGs) are ubiquitous structures for information storage in several real-world applications such as web search, e-commerce, social networks, and biology. Querying KGs remains a foundational and challenging problem due to their size and complexity. Promising approaches to tackle this problem include embedding the KG units (e.g., entities and relations) in a Euclidean space such that the query embedding contains the information relevant to its results. These approaches, however, fail to capture the hierarchical nature and semantic information of the entities present in the graph. Additionally, most of these approaches only utilize multi-hop queries (that can be modeled by simple translation operations) to learn embeddings and ignore more complex operations such as intersection, and union of simpler queries. To tackle such complex operations, in this paper, we formulate KG representation learning as a self-supervised logical query reasoning problem that utilizes translation, intersection and union queries over KGs. We propose Hyperboloid Embeddings (HypE), a novel self-supervised dynamic reasoning framework, that utilizes positive first-order existential queries on a KG to learn representations of its entities and relations as hyperboloids in a Poincare ball. HypE models the positive first-order queries as geometrical translation, intersection, and union. For the problem of KG reasoning in real-world datasets, the proposed HypE model significantly outperforms the state-of-the art results. We also apply HypE to an anomaly detection task on a popular e-commerce website product taxonomy as well as hierarchically organized web articles and demonstrate significant performance improvements compared to existing baseline methods. Finally, we also visualize the learned HypE embeddings in a Poincare ball to clearly interpret and comprehend the representation space.
School Choice Programs: The Impacts on Housing Values

We review both the theoretical and empirical literature relating to the impact of school choice programs, particularly voucher programs, on residential property values. Beginning with the seminal w...
YAP1 Regulates the Self-organized Fate Patterning of hESCs-Derived Gastruloids

ABSTRACT During gastrulation, the coordinated activity of BMP, WNT and NODAL signaling pathways guide the differentiation of the pluripotent epiblast into the three germinal layers. Recent studies underline the role of the Hippo-effector YAP1 regulating WNT and NODAL signaling pathways and repressing mesoendodermal differentiation in human embryonic stem cells (hESCs). However, the contribution of YAP1 to the cell-fate patterning decisions that transform the epiblast in a three-germ layer gastrula remains unknown. We address this question by analyzing micropatterned 2D-gastruloids derived from hESCs, in the presence and absence of YAP1. Our findings show that YAP1 is necessary for gastrulation. YAP1 KO-gastruloids display reduced ectoderm layer and enlarged mesoderm and endoderm layers, compared to WT. Furthermore, YAP1 regulates the self-organized patterning of the hESCs, as the discrete position of the three germ layers is altered in the YAP1 KO-gastruloids. Our epigenome (single-nuclei ATACseq) and transcriptome (RNA-seq) analysis revealed that YAP1 directly represses the chromatin accessibility and transcription of key genes in the NODAL pathway, including the NODAL and FOXH1 genes. In WT gastruloids, a gradient of NODAL: SMAD2.3 signaling from the periphery to the center of the colony regulates the exit of pluripotency toward endoderm, mesoderm and ectoderm, respectively. Hence, in the absence of YAP1, a hyperactive NODAL signaling retains SMAD2.3 in the nuclei impeding the self-organized differentiation of hESCs. Accordingly, the partial inhibition of NODAL signaling is sufficient to rescue the differentiation and pattern -defective phenotypes of the YAP1 KO gastruloids. Our work revealed that YAP1 is a master regulator of NODAL signaling, essential to instruct germ layer fate patterning in human gastruloids.
Multi-Task Self-Supervised Pre-Training for Music Classification

Deep learning is very data hungry, and supervised learning especially requires massive labeled data to work well. Machine listening research often suffers from limited labeled data problem, as human annotations are costly to acquire, and annotations for audio are time consuming and less intuitive. Besides, models learned from labeled dataset often embed biases specific to that particular dataset. Therefore, unsupervised learning techniques become popular approaches in solving machine listening problems. Particularly, a self-supervised learning technique utilizing reconstructions of multiple hand-crafted audio features has shown promising results when it is applied to speech domain such as emotion recognition and automatic speech recognition (ASR). In this paper, we apply self-supervised and multi-task learning methods for pre-training music encoders, and explore various design choices including encoder architectures, weighting mechanisms to combine losses from multiple tasks, and worker selections of pretext tasks. We investigate how these design choices interact with various downstream music classification tasks. We find that using various music specific workers altogether with weighting mechanisms to balance the losses during pre-training helps improve and generalize to the downstream tasks.
Decentralized Adaptive Control for Collaborative Manipulation of Rigid Bodies

In this work, we consider a group of robots working together to manipulate a rigid object to track a desired trajectory in $\text{SE}(3)$ . The robots do not know the mass or friction properties of the object, or where they are attached to the object. They can, however, access a common state measurement, either from one robot broadcasting its measurements to the team, or by all robots communicating and averaging their state measurements to estimate the state of their centroid. To solve this problem, we propose a decentralized adaptive control scheme wherein each agent maintains and adapts its own estimate of the object parameters in order to track a reference trajectory. We present an analysis of the controller’s behavior, and show that all closed-loop signals remain bounded, and that the system trajectory will almost always (except for initial conditions on a set of measure zero) converge to the desired trajectory. We study the proposed controller’s performance using numerical simulations of a manipulation task in 3-D, as well as hardware experiments which demonstrate our algorithm on a planar manipulation task. These studies, taken together, demonstrate the effectiveness of the proposed controller even in the presence of numerous unmodeled effects, such as discretization errors and complex frictional interactions.
City Guarding with Limited Field of View.

Drones and other small unmanned aerial vehicles are starting to get permission to fly within city limits. While video cameras are easily available in most cities, their purpose is to guard the streets at ground level. Guarding the aerial space of a city with video cameras is a problem that so far has been largely ignored. In this paper, we present bounds on the number of cameras needed to guard the city's aerial space (roofs, walls, and ground) using cameras with 180-degree range of vision (the region in front of the guard), which is common for most commercial cameras. We assume all buildings are vertical and have a rectangular base. Each camera is placed at a top corner of a building. We considered the following two versions: (i) buildings have an axis-aligned ground base and, (ii) buildings have an arbitrary orientation. We give necessary and sufficient results for (i), necessary results for (ii), and conjecture sufficiency results for (ii). Specifically, for (i) we prove a sufficiency bound of 2k + k/4 +4 on the number of vertex guards, while for (ii) we show that 3k + 1 vertex guards are sometimes necessary, where k is the total number of buildings in the city.
Thermal control of laser powder bed fusion using deep reinforcement learning

Abstract Powder-based additive manufacturing techniques provide tools to construct intricate structures that are difficult to manufacture using conventional methods. In Laser Powder Bed Fusion, components are iteratively built by selectively melting specific areas of the powder bed to form the two-dimensional cross section of the specific part. However, the high occurrence of defects impact the adoption of this method for precision applications. Therefore, a control policy for dynamically altering process parameters to avoid phenomena that lead to defect occurrences is necessary. A Deep Reinforcement Learning (DRL) framework that derives a versatile control strategy for minimizing the likelihood of these defects is presented. The generated control policy alters either the velocity or power of the laser during the melting process to ensure the consistency of the melt pool and reduce overheating in the generated product. The control policy is trained and validated on efficient simulations of the continuum temperature distribution of the powder bed layer under various laser trajectories.
Protecting Privacy and Transforming COVID-19 Case Surveillance Datasets for Public Use.

ObjectivesFederal open-data initiatives that promote increased sharing of federally collected data are important for transparency, data quality, trust, and relationships with the public and state, ...
Design and Evaluation of a Simple Data Interface for Efficient Data Transfer across Diverse Storage

Modern science and engineering computing environments often feature storage systems of different types, from parallel file systems in high-performance computing centers to object stores operated by cloud providers. To enable easy, reliable, secure, and performant data exchange among these different systems, we propose Connector, a plug-able data access architecture for diverse, distributed storage. By abstracting low-level storage system details, this abstraction permits a managed data transfer service (Globus, in our case) to interact with a large and easily extended set of storage systems. Equally important, it supports third-party transfers: that is, direct data transfers from source to destination that are initiated by a third-party client but do not engage that third party in the data path. The abstraction also enables management of transfers for performance optimization, error handling, and end-to-end integrity. We present the Connector design, describe implementations for different storage services, evaluate tradeoffs inherent in managed vs. direct transfers, motivate recommended deployment options, and propose a model-based method that allows for easy characterization of performance in different contexts without exhaustive benchmarking.
Using submodularity within column generation to solve the flight-to-gate assignment problem

Abstract In this paper, we provide a column generation-based approach for solving the airport flight-to-gate assignment problem, where the goal is to minimize the on-ground portion of arrival delays by optimally assigning each scheduled flight to a compatible gate. Specifically, we use a set covering formulation for the master problem and decompose the pricing problem such that each gate is the basis for an independent pricing problem to be solved for assignment patterns with negative reduced costs. We use a combination of an approximation algorithm based on the submodularity of the underlying set and dynamic programming algorithms to solve the independent pricing problems. To the best of our knowledge, this is the first use of submodularity property to efficiently solve pricing problems and improve the performance of column generation algorithm. We show that the dynamic programming algorithm is pseudo-polynomial when there are integer inputs. We also design and employ a rolling horizon method and block decomposition algorithm to solve large-sized instances. Finally, we perform extensive computational experiments to validate the performance of our approach.