cssi/SciSciGPT-SciSciNet huggingface dataset:
On the S-Euclidean minimum of an ideal class

We show that the S-Euclidean minimum of an ideal class is a rational number, generalizing a result of Cerri. We also give some corollaries which explain the relationship of our results with Lenstra's notion of a norm-Euclidean ideal class and the conjecture of Barnes and Swinnerton-Dyer on quadratic forms. The proof is self-contained but uses ideas from ergodic theory and topological dynamics, particularly those of Berend.
Academic Performance Estimation with Attention-based Graph Convolutional Networks.

Student's academic performance prediction empowers educational technologies including academic trajectory and degree planning, course recommender systems, early warning and advising systems. Given a student's past data (such as grades in prior courses), the task of student's performance prediction is to predict a student's grades in future courses. Academic programs are structured in a way that prior courses lay the foundation for future courses. The knowledge required by courses is obtained by taking multiple prior courses, which exhibits complex relationships modeled by graph structures. Traditional methods for student's performance prediction usually neglect the underlying relationships between multiple courses; and how students acquire knowledge across them. In addition, traditional methods do not provide interpretation for predictions needed for decision making. In this work, we propose a novel attention-based graph convolutional networks model for student's performance prediction. We conduct extensive experiments on a real-world dataset obtained from a large public university. The experimental results show that our proposed model outperforms state-of-the-art approaches in terms of grade prediction. The proposed model also shows strong accuracy in identifying students who are at-risk of failing or dropping out so that timely intervention and feedback can be provided to the student.
New Bounds on the Tile Complexity of Thin Rectangles at Temperature-1.

In this paper, we study the minimum number of unique tile types required for the self-assembly of thin rectangles in Winfree’s abstract Tile Assembly Model (aTAM), restricted to temperature-1. Using Catalan numbers, planar self-assembly and a restricted version of the Window Movie Lemma, we derive a new lower bound on the tile complexity of thin rectangles at temperature-1 in 2D. Then, we give the first known upper bound on the tile complexity of “just-barely” 3D thin rectangles at temperature-1, where tiles are allowed to be placed at most one step into the third dimension. Our construction, which produces a unique terminal assembly, implements a just-barely 3D, zig-zag counter, whose base depends on the dimensions of the target rectangle, and whose digits are encoded geometrically, vertically-oriented and in binary.
A class of skewed distributions with applications in environmental data

AbstractIn environmental studies, many data are typically skewed and it is desired to have a flexible statistical model for this kind of data. In this article, we study a class of skewed distributi...
A Microelectronic Sensor Device Powered by a Small Implantable Biofuel Cell.

Biocatalytic buckypaper electrodes modified with pyrroloquinoline quinone (PQQ)-dependent glucose dehydrogenase and bilirubin oxidase for glucose oxidation and oxygen reduction, respectively, were prepared for their use in a biofuel cell. A small (millimeter-scale; 2×3×2 mm3 ) enzyme-based biofuel cell was tested in a model glucose-containing aqueous solution, in human serum, and as an implanted device in a living gray garden slug (Deroceras reticulatum), producing electrical power in the range of 2-10 μW (depending on the glucose source). A microelectronic temperature-sensing device equipped with a rechargeable supercapacitor, internal data memory and wireless data downloading capability was specifically designed for activation by the biofuel cell. The power management circuit in the device allowed the optimized use of the power provided by the biofuel cell dependent on the sensor operation activity. The whole system (power-producing biofuel cell and power-consuming sensor) operated autonomously by extracting electrical energy from the available environmental source, as exemplified by extracting power from the glucose-containing hemolymph (blood substituting biofluid) in the slug to power the complete temperature sensor system and read out data wirelessly. Other sensor systems operating autonomously in remote locations based on the concept illustrated here are envisaged for monitoring different environmental conditions or can be specially designed for homeland security applications, particularly in detecting bioterrorism threats.
Innovative Learning Environments : The Role of Energy-Efficient Investments in Russian Preschool Education Facilities (A Case Study of the Khanty-Mansyisk Region)

This paper discusses an example of an early childhood development facility intervention in the Khanty-Mansyisk region of the Russian Federation and its potential to produce efficiency gains in the region and the country overall. The government of the region is introducing changes to the built environment of its early childhood development centers. The proposed new design is based on the concept of the learning environment as a third teacher. The smaller footprint of the new buildings will increase the amount of active space per child, and the new design will include energy efficiency measures. The economic impact of these measures will reduce operating costs throughout the lifecycle of the building and provide strong evidence to education policy makers in the rest of the region and the country as a whole in favor of child-centered, healthy, and energy efficient early childhood development infrastructure.
Optimistic Regret Minimization for Extensive-Form Games via Dilated Distance-Generating Functions

We study the performance of optimistic regret-minimization algorithms for both minimizing regret in, and computing Nash equilibria of, zero-sum extensive-form games. In order to apply these algorithms to extensive-form games, a distance-generating function is needed. We study the use of the dilated entropy and dilated Euclidean distance functions. For the dilated Euclidean distance function we prove the first explicit bounds on the strong-convexity parameter for general treeplexes. Furthermore, we show that the use of dilated distance-generating functions enable us to decompose the mirror descent algorithm, and its optimistic variant, into local mirror descent algorithms at each information set. This decomposition mirrors the structure of the counterfactual regret minimization framework, and enables important techniques in practice, such as distributed updates and pruning of cold parts of the game tree. Our algorithms provably converge at a rate of $T^{-1}$, which is superior to prior counterfactual regret minimization algorithms. We experimentally compare to the popular algorithm CFR+, which has a theoretical convergence rate of $T^{-0.5}$ in theory, but is known to often converge at a rate of $T^{-1}$, or better, in practice. We give an example matrix game where CFR+ experimentally converges at a relatively slow rate of $T^{-0.74}$, whereas our optimistic methods converge faster than $T^{-1}$. We go on to show that our fast rate also holds in the Kuhn poker game, which is an extensive-form game. For games with deeper game trees however, we find that CFR+ is still faster. Finally we show that when the goal is minimizing regret, rather than computing a Nash equilibrium, our optimistic methods can outperform CFR+, even in deep game trees.
Average Case Column Subset Selection for Entrywise $\ell_1$-Norm Loss

We study the column subset selection problem with respect to the entrywise $\ell_1$-norm loss. It is known that in the worst case, to obtain a good rank-$k$ approximation to a matrix, one needs an arbitrarily large $n^{\Omega(1)}$ number of columns to obtain a $(1+\epsilon)$-approximation to an $n \times n$ matrix. Nevertheless, we show that under certain minimal and realistic distributional settings, it is possible to obtain a $(1+\epsilon)$-approximation with a nearly linear running time and poly$(k/\epsilon)+O(k\log n)$ columns. Namely, we show that if the input matrix $A$ has the form $A = B + E$, where $B$ is an arbitrary rank-$k$ matrix, and $E$ is a matrix with i.i.d. entries drawn from any distribution $\mu$ for which the $(1+\gamma)$-th moment exists, for an arbitrarily small constant $\gamma > 0$, then it is possible to obtain a $(1+\epsilon)$-approximate column subset selection to the entrywise $\ell_1$-norm in nearly linear time. Conversely we show that if the first moment does not exist, then it is not possible to obtain a $(1+\epsilon)$-approximate subset selection algorithm even if one chooses any $n^{o(1)}$ columns. This is the first algorithm of any kind for achieving a $(1+\epsilon)$-approximation for entrywise $\ell_1$-norm loss low rank approximation.
The MyMOMA domain of MYO19 encodes for distinct Miro-dependent and Miro-independent mechanisms of interaction with mitochondrial membranes

MYO19 interacts with mitochondria through a C-terminal membrane association domain (MyMOMA). Specific mechanisms for localization of MYO19 to mitochondria are poorly understood. Using promiscuous biotinylation data in combination with existing affinity-capture databases, we have identified a number of putative MYO19-interacting proteins. We chose to explore the interaction between MYO19 and the mitochondrial GTPase Miro2 by expressing mchr-Miro2 in combination with GFP-tagged fragments of the MyMOMA domain and assaying for recruitment of MYO19-GFP to mitochondria. Coexpression of MYO19898-970 -GFP with mchr-Miro2 enhanced MYO19898-970 -GFP localization to mitochondria. Mislocalizing Miro2 to filopodial tips or the cytosolic face of the nuclear envelope did not recruit MYO19898-970 -GFP to either location. To address the kinetics of the Miro2/MYO19 interaction, we used FRAP analysis and permeabilization-activated reduction in fluorescence analysis. MyMOMA constructs containing a putative membrane-insertion motif but lacking the Miro2-interacting region displayed slow exchange kinetics. MYO19898-970 -GFP, which does not include the membrane-insertion motif, displayed rapid exchange kinetics, suggesting that MYO19 interacting with Miro2 has higher mobility than MYO19 inserted into the mitochondrial outer membrane. Mutation of well-conserved, charged residues within MYO19 or within the switch I and II regions of Miro2 abolished the enhancement of MYO19898-970 -GFP localization in cells ectopically expressing mchr-Miro2. Additionally, expressing mutant versions of Miro2 thought to represent particular nucleotide states indicated that the enhancement of MYO19898-970 -GFP localization is dependent on Miro2 nucleotide state. Taken together, these data suggest that membrane-inserted MYO19 is part of a larger complex, and that Miro2 plays a role in integration of actin- and microtubule-based mitochondrial activities.
Algorithmic search in group theory

Abstract A method of random search based on Kolmogorov complexity is proposed and applied to two search problems in group theory. Some experimental evidence as to the efficacy of the method is presented.
On the projective normality and normal presentation on higher dimensional varieties with nef canonical bundle

Abstract In this article we prove new results on projective normality and normal presentation of adjunction bundle associated to an ample and globally generated line bundle on higher dimensional smooth projective varieties with nef canonical bundle. As one of the consequences of the main theorem, we give bounds on very ampleness and projective normality of pluricanonical linear systems on varieties of general type in dimensions three, four and five. These improve known such results.
Modeling the Interplay between Photosynthesis, CO 2 Fixation, and the Quinone Pool in a Purple Non-Sulfur Bacterium

Rhodopseudomonas palustris CGA009 is a purple non-sulfur bacterium that can fix carbon dioxide (CO2) and nitrogen or break down organic compounds for its carbon and nitrogen requirements. Light, inorganic, and organic compounds can all be used for its source of energy. Excess electrons produced during its metabolic processes can be exploited to produce hydrogen gas or biodegradable polyesters. A genome-scale metabolic model of the bacterium was reconstructed to study the interactions between photosynthesis, CO2 fixation, and the redox state of the quinone pool. A comparison of model-predicted flux values with available Metabolic Flux Analysis (MFA) fluxes yielded predicted errors of 5-19% across four different growth substrates. The model predicted the presence of an unidentified sink responsible for the oxidation of excess quinols generated by the TCA cycle. Furthermore, light-dependent energy production was found to be highly dependent on the quinol oxidation rate. Finally, the extent of CO2 fixation was predicted to be dependent on the amount of ATP generated through the electron transport chain, with excess ATP going toward the energy-demanding Calvin-Benson-Bassham (CBB) pathway. Based on this analysis, it is hypothesized that the quinone redox state acts as a feed-forward controller of the CBB pathway, signaling the amount of ATP available.
Metal Bridge in S4 Segment Supports Helix Transition in Shaker Channel.

Abstract Voltage-gated ion channels play important roles in physiological processes, especially in excitable cells, in which they shape the action potential. In S4-based voltage sensors voltage-gated channels, a common feature is shared; the transmembrane segment 4 (S4) contains positively charged residues intercalated by hydrophobic residues. Although several advances have been made in understating how S4 moves through a hydrophobic plug upon voltage changes, the possible helix transition from α- to 310-helix in S4 during the activation process is still unresolved. Here, we have mutated several hydrophobic residues from I360 to F370 in the S4 segment into histidine, in i, i + 3 and i, i + 6 or i, i + 4 and i, i + 7 pairs, to favor 310- or α-helical conformations, respectively. We have taken advantage of the ability of His to coordinate Zn2+ to promote metal ion bridges, and we have found that the histidine introduced at position 366 (L366H) can interact with the introduced histidine at position 370 (stabilizing that portion of the S4 segment in α-helical conformation). In the presence of 20 μM of Zn2+, the activation currents of L366H:F370H channels were slowed down by a factor of 3.5, and the voltage dependence is shifted by 10 mV toward depolarized potentials with no change on the deactivation time constant. Our data supports that by stabilizing a region of the S4 segment in α-helical conformation, a closed (resting or intermediate) state is stabilized rather than destabilizing the open (active) state. Taken together, our data indicates that S4 undergoes α-helical conformation to a short-lived different secondary structure transiently before reaching the active state in the activation process.
Center of mass and the optimal quantizers for some continuous and discrete uniform distributions

AbstractIn this paper, we first consider a flat plate (called a lamina) with uniform density ρ that occupies a region of the plane. We show that the location of the center of mass, also known as th...
Transcriptome analyses of tumor-adjacent somatic tissues reveal genes co-expressed with transposable elements

Despite the long-held assumption that transposons are normally only expressed in the germ-line, recent evidence shows that transcripts of transposable element (TE) sequences are frequently found in the somatic cells. However, the extent of variation in TE transcript levels across different tissues and different individuals are unknown, and the co-expression between TEs and host gene mRNAs have not been examined. Here we report the variation in TE derived transcript levels across tissues and between individuals observed in the non-tumorous tissues collected for The Cancer Genome Atlas. We found core TE co-expression modules consisting mainly of transposons, showing correlated expression across broad classes of TEs. Despite this co-expression within tissues, there are individual TE loci that exhibit tissue-specific expression patterns, when compared across tissues. The core TE modules were negatively correlated with other gene modules that consisted of immune response genes in interferon signaling. KRAB Zinc Finger Proteins (KZFPs) were over-represented gene members of the TE modules, showing positive correlation across multiple tissues. But we did not find overlap between TE-KZFP pairs that are co-expressed and TE-KZFP pairs that are bound in published ChIP-seq studies. We find unexpected variation in TE derived transcripts, within and across non-tumorous tissues. We describe a broad view of the RNA state for non-tumorous tissues exhibiting higher level of TE transcripts. Tissues with higher level of TE transcripts have a broad range of TEs co-expressed, with high expression of a large number of KZFPs, and lower RNA levels of immune genes.
Disulfide Chaperone Knockouts Enable In Vivo Double Spin Labeling of an Outer Membrane Transporter.

Abstract Recent advances in the application of electron paramagnetic resonance spectroscopy have demonstrated that it is possible to obtain structural information on bacterial outer membrane (OM) proteins in intact cells from extracellularly labeled cysteines. However, in the Escherichia coli OM B12 transport protein, BtuB, the double labeling of many cysteine pairs is not possible in a wild-type K12-derived E. coli strain. It has also not yet been possible to selectively label single or paired cysteines that face the periplasmic space. Here, we demonstrate that the inability to produce reactive cysteine residues in pairs is a result of the disulfide bond formation system, which functions to oxidize pairs of free-cysteine residues. Mutant strains that are dsbA or dsbB null facilitate labeling pairs of cysteines. Moreover, we demonstrate that the double labeling of sites on the periplasmic-facing surface of BtuB is possible using a dsbA null strain. BtuB is found to exhibit different structures and structural changes in the cell than it does in isolated OMs or reconstituted systems, and the ability to label and perform electron paramagnetic resonance in cells is expected to be applicable to a range of other bacterial OM proteins.
Identifying mediating variables with graphical models: an application to the study of causal pathways in people living with HIV

We empirically demonstrate that graphical models can be a valuable tool in the identification of mediating variables in causal pathways. We make use of graphical models to elucidate the causal path...
A study on the multi-axial fatigue failure behavior of notched composite laminates

Abstract Composite structures must endure a great variety of multi-axial stress states during their lifespan while guaranteeing their structural integrity and functional performance. Understanding the fatigue behavior of these materials, especially in the presence of notches that are ubiquitous in structural design, lies at the hearth of this study which presents a comprehensive investigation of the fracturing behavior of notched quasi-isotropic [+45/90/−45/0]s and cross-ply [0/90]2s laminates under multi-axial quasi-static and fatigue loading. The investigation of the S-N curves and stiffness degradation, and the analysis of the damage mechanisms via micro-computed tomography clarified the effects of the multi-axiality ratio and the notch configuration. Furthermore, it allowed to conclude that damage progression under fatigue loading can be substantially different compared to the quasi-static case. Future efforts in the formulation of efficient fatigue models will need to account for the transition in damaging behavior in the context of the type of applied load, the evolution of the local multiaxiality ratio, the structure size and geometry, and stacking sequence. By providing important data for model calibration and validation, this study represents a first step towards this important goal.
On the Effect of the Activation Function on the Distribution of Hidden Nodes in a Deep Network.

We analyze the joint probability distribution on the lengths of the vectors of hidden variables in different layers of a fully connected deep network, when the weights and biases are chosen randoml...
Automated Reasoning about XACML 3.0 Delegation Using Answer Set Programming.

XACML is an XML-based declarative access control language standardized by OASIS. Its latest version 3.0 has several new features including the concept of delegation for decentralized administration of access control. Though it is important to avoid unintended consequences of ill-designed policies, delegation makes formal analysis of XACML policies highly complicated. In this paper, we present a logic-based approach to XACML 3.0 policy analysis. We formulate XACML 3.0 in Answer Set Programming (ASP) and use ASP solvers to perform automated reasoning about XACML policies. To the best of our knowledge this is the first work that fully captures the XACML delegation model in a formal executable language.
On Consistency of Graph-based Semi-supervised Learning

Graph-based semi-supervised learning is one of the most popular methods in machine learning. Some of its theoretical properties such as bounds for the generalization error and the convergence of the graph Laplacian regularizer have been studied in computer science and statistics literature. However, a fundamental statistical property – consistency – that is, the prediction by the algorithm can identify the underlying truth with unlimited data. This is not to be confused with the existence of solutions in an equation system, which is a term used in algebra. – has not been proved. In this article, we study the consistency problem under a non-parametric framework. We obtain the following two results: 1) We prove that graph-based semi-supervised learning on the test data is consistent in the case that the estimated scores are enforced to be equal to the observed responses for the labeled data (the hard criterion). The sample size of unlabeled data are allowed to grow at a slower rate than the size of the labeled data in this result. 2) We give a counterexample demonstrating that the estimator can be inconsistent for the case when the estimated scores are not required to be equal to the observed responses (the soft criterion), where a tuning parameter is used to balance the loss function and the graph Laplacian regularizer. These somewhat surprising theoretical findings are supported by numerical studies on both synthetic and real datasets. Moreover, numerical studies show that the hard criterion constantly outperforms the soft criterion even when the sample size of unlabeled data is smaller than the size of labeled data. This suggests that practitioners can safely choose the hard criterion without the burden of selecting the tuning parameter in the soft criterion.
Exact sampling for some multi-dimensional queueing models with renewal input

Using a result of Blanchet and Wallwater (2015) for exactly simulating the maximum of a negative drift random walk queue endowed with independent and identically distributed (i.i.d.) increments, we extend it to a multi-dimensional setting and then we give a new algorithm for simulating exactly the stationary distribution of a first-in–first-out (FIFO) multi-server queue in which the arrival process is a general renewal process and the service times are i.i.d.: the FIFO GI/GI/c queue with . Our method utilizes dominated coupling from the past (DCFP) as well as the random assignment (RA) discipline, and complements the earlier work in which Poisson arrivals were assumed, such as the recent work of Connor and Kendall (2015). We also consider the models in continuous time, and show that with mild further assumptions, the exact simulation of those stationary distributions can also be achieved. We also give, using our FIFO algorithm, a new exact simulation algorithm for the stationary distribution of the infinite server case, the GI/GI/ model. Finally, we even show how to handle fork–join queues, in which each arriving customer brings c jobs, one for each server.
From FE Combiners to Secure MPC and Back

Cryptographic combiners allow one to combine many candidates for a cryptographic primitive, possibly based on different computational assumptions, into another candidate with the guarantee that the resulting candidate is secure as long as at least one of the original candidates is secure. While the original motivation of cryptographic combiners was to reduce trust on existing candidates, in this work, we study a rather surprising implication of combiners to constructing secure multiparty computation protocols. Specifically, we initiate the study of functional encryption combiners and show its connection to secure multiparty computation.
Periodically poled thin-film lithium niobate microring resonators with a second-harmonic generation efficiency of 250,000%/W

Lithium niobate (LN), dubbed by many as the silicon of photonics, has recently risen to the forefront of chip-scale nonlinear optics research since its demonstration as an ultralow-loss integrated photonics platform. Due to its significant quadratic nonlinearity (χ(2)), LN inspires many important applications such as second-harmonic generation (SHG), spontaneous parametric downconversion, and optical parametric oscillation. Here, we demonstrate high-efficiency SHG in dual-resonant, periodically poled z-cut LN microrings, where quasi-phase matching is realized by field-assisted domain engineering. Meanwhile, dual-band operation is accessed by optimizing the coupling conditions in fundamental and second-harmonic bands via a single pulley waveguide. As a result, when pumping a periodically poled LN microring in the low power regime at around 1617 nm, an on-chip SHG efficiency of 250,000%/W is achieved, a state-of-the-art value reported among current integrated photonics platforms. An absolute conversion efficiency of 15% is recorded with a low pump power of 115 μW in the waveguide. Such periodically poled LN microrings also present a versatile platform for other cavity-enhanced quasi-phase-matched χ(2) nonlinear optical processes.
Optimizing Nutrition Assessment to Create Better Outcomes in Lung Transplant Recipients: A Review of Current Practices

Lung transplantation offers patients with end-stage lung disease an opportunity for a better quality of life, but with limited organ availability it is paramount that selected patients have the best opportunity for successful outcomes. Nutrition plays a central role in post-surgical outcomes and, historically, body mass index (BMI) has been used as the de facto method of assessing a lung transplant candidate’s nutritional status. Here, we review the historical origins of BMI in lung transplantation, summarize the current BMI literature, and review studies of alternative/complementary body composition assessment tools, including lean psoas area, creatinine-height index, leptin, and dual x-ray absorptiometry. These body composition measures quantify lean body mass versus fat mass and may provide a more comprehensive analysis of a patient’s nutritional state than BMI alone.
Towards Scalable Gaussian Process Modeling

Numerous engineering problems of interest to the industry are often characterized by expensive black-box objective experiments or computer simulations. Obtaining insight into the problem or performing subsequent optimizations requires hundreds of thousands of evaluations of the objective function which is most often a practically unachievable task. Gaussian Process (GP) surrogate modeling replaces the expensive function with a cheap-to-evaluate data-driven probabilistic model. While the GP does not assume a functional form of the problem, it is defined by a set of parameters, called hyperparameters. The hyperparameters define the characteristics of the objective function, such as smoothness, magnitude, periodicity, etc. Accurately estimating these hyperparameters is a key ingredient in developing a reliable and generalizable surrogate model. Markov chain Monte Carlo (MCMC) is a ubiquitously used Bayesian method to estimate these hyperparameters. At the GE Global Research Center, a customized industry-strength Bayesian hybrid modeling framework utilizing the GP, called GEBHM, has been employed and validated over many years. GEBHM is very effective on problems of small and medium size, typically less than 1000 training points. However, the GP does not scale well in time with a growing dataset and problem dimensionality which can be a major impediment in such problems. In this work, we extend and implement in GEBHM an Adaptive Sequential Monte Carlo (ASMC) methodology for training the GP enabling the modeling of large-scale industry problems. This implementation saves computational time (especially for large-scale problems) while not sacrificing predictability over the current MCMC implementation. We demonstrate the effectiveness and accuracy of GEBHM with ASMC on four mathematical problems and on two challenging industry applications of varying complexity.
Prioritizing Enforcement in Insider Trading

The Comment argues that some federal insider trading rules can be contracted around by corporations, and thus should be seen as "default rules" rather than "mandatory rules." In certain cases, corporations have the power to permit insider trading in their own stock. The Comment argues that the enforcement of insider trading rules should focus most heavily on those insider trading rules that cannot be contracted around.
Integral factorial ratios: irreducible examples with height larger than 1

This paper gives over 50 new examples of two-parameter families of integral factorial ratios of height 2. These examples are also shown to be irreducible, in the sense that they do not arise by put...
Privacy-Preserving Parametric Inference: A Case for Robust Statistics

Differential privacy is a cryptographically motivated approach to privacy that has become a very active field of research over the last decade in theoretical computer science and machine learning. ...
Federal Institutions and the Democratic Transition: Learning from South Africa

FEDERAL INSTITUTIONS AND THE DEMOCRATIC TRANSITION: Lessons from South Africa by Robert P. Inman and Daniel L. Rubinfeld Draft, December 2, 2005 ABSTRACT We present a political economy model of a peaceful transition from autocracy to democracy, motivated by, and calibrated to, South Africa at the time of its own successful transition from white, elite rule under apartheid to today’s multi-racial democracy. The primary barrier faced by South Africa in its transition is symptomatic of a central difficulty to peaceful transitions generally: How can the emerging majority credibly promise not to economically exploit the once ruling elite? South Africa found its answer in a form of governance we call democratic federalism. The central feature of such a constitution is to create an annual policy game – we study fiscal policy – where the new majority and the old elite each credibly control one policy instrument of central importance to the other party. In our version, the majority run central government decides all tax policy while provinces, at least one of which is politically controlled by the old elite, are assigned responsibility for providing important redistributive services. In effect, the federal constitution creates a policy “hostage game” between the new majority and the old elite in which each can check policy abuses by the other. We show that for plausible specifications of the political economy, this annual policy game has a stable, less- than-fully exploitative stationary equilibrium that the elite may prefer to current autocratic rule. Our model “predicts” the current federal fiscal system of South Africa and then shows that under this system – which has proven stable at least over the past 12 years – the old economic elite will prefer democracy to apartheid provided their rate of time preference is less than the internal rate of return ( = .128) from South Africa’s transition from autocracy to democratic federalism. Robert P. Inman is the Richard K. Mellon Professor, Finance and Economics, the Wharton School, University of Pennsylvania, Philadelphia, PA 19104, inman@wharton.upenn.edu Daniel L. Rubinfeld is the Robert L. Bridges Professor of Law and Professor of Economics, University of California, Berkeley, CA 94720, rubinfeld@law.berkeley.edu
Anterior Chamber Blood Cell Differentiation Using Spectroscopic Optical Coherence Tomography

There is great clinical importance in identifying cellular responses in the anterior chamber (AC) which can indicate signs of hyphema (an accumulation of red blood cells (RBCs)) or aberrant intraocular inflammation (an accumulation of white blood cells (WBCs)). These responses are difficult to diagnose and require specialized equipment such as ophthalmic microscopes and specialists trained in examining the eye. In this work, we applied spectroscopic OCT to differentiate between RBCs and subtypes of WBCs, including neutrophils, lymphocytes and monocytes, both in vitro and in ACs of porcine eyes. We located and tracked single cells in OCT volumetric images, and extracted the spectroscopic data of each cell from the detected interferograms using short-time Fourier Transform (STFT). A look-up table of Mie spectra was generated and used to correlate the spectroscopic data of single cells to their characteristic sizes. The accuracy of the method was first validated on 10um polystyrene microspheres. For RBCs and subtypes of WBCs, the extracted size distributions based on the best Mie spectra fit were significantly different between each cell type by using the Wilcoxon rank-sum test. A similar size distribution of neutrophils was also acquired in the measurements of cells introduced into the ACs of porcine eyes, further supporting spectroscopic OCT for potentially differentiating and quantifying blood cell types in the AC in vivo.
Harmonia: near-linear scalability for replicated storage with in-network conflict detection

Distributed storage employs replication to mask failures and improve availability. However, these systems typically exhibit a hard tradeoff between consistency and performance. Ensuring consistency introduces coordination overhead, and as a result the system throughput does not scale with the number of replicas. We present Harmonia, a replicated storage architecture that exploits the capability of new-generation programmable switches to obviate this tradeoff by providing near-linear scalability without sacrificing consistency. To achieve this goal, Harmonia detects read-write conflicts in the network, which enables any replica to serve reads for objects with no pending writes. Harmonia implements this functionality at line rate, thus imposing no performance overhead. We have implemented a prototype of Harmonia on a cluster of commodity servers connected by a Barefoot Tofino switch, and have integrated it with Redis. We demonstrate the generality of our approach by supporting a variety of replication protocols, including primary-backup, chain replication, Viewstamped Replication, and NOPaxos. Experimental results show that Harmonia improves the throughput of these protocols by up to 10 x for a replication factor of 10, providing near-linear scalability up to the limit of our testbed.
End-to-End Trainable Non-Collaborative Dialog System.

End-to-end task-oriented dialog models have achieved promising performance on collaborative tasks where users willingly coordinate with the system to complete a given task. While in non-collaborative settings, for example, negotiation and persuasion, users and systems do not share a common goal. As a result, compared to collaborate tasks, people use social content to build rapport and trust in these non-collaborative settings in order to advance their goals. To handle social content, we introduce a hierarchical intent annotation scheme, which can be generalized to different non-collaborative dialog tasks. Building upon TransferTransfo (Wolf et al. 2019), we propose an end-to-end neural network model to generate diverse coherent responses. Our model utilizes intent and semantic slots as the intermediate sentence representation to guide the generation process. In addition, we design a filter to select appropriate responses based on whether these intermediate representations fit the designed task and conversation constraints. Our non-collaborative dialog model guides users to complete the task while simultaneously keeps them engaged. We test our approach on our newly proposed ANTISCAM dataset and an existing PERSUASIONFORGOOD dataset. Both automatic and human evaluations suggest that our model outperforms multiple baselines in these two non-collaborative tasks.
Opioid Tolerance in Critical Illness.

Opioid Tolerance in Critical Illness This review describes the indications for opioid therapy in patients in the intensive care unit, mechanisms of opioid tolerance, and current and potential mitig...
Inferring Tracker-Advertiser Relationships in the Online Advertising Ecosystem using Header Bidding

Online advertising relies on trackers and data brokers to show targeted ads to users. To improve targeting, different entities in the intricately interwoven online advertising and tracking ecosystems are incentivized to share information with each other through client-side or server-side mechanisms. Inferring data sharing between entities, especially when it happens at the server-side, is an important and challenging research problem. In this paper, we introduce KASHF: a novel method to infer data sharing relationships between advertisers and trackers by studying how an advertiser's bidding behavior changes as we manipulate the presence of trackers. We operationalize this insight by training an interpretable machine learning model that uses the presence of trackers as features to predict the bidding behavior of an advertiser. By analyzing the machine learning model, we are able to infer relationships between advertisers and trackers irrespective of whether data sharing occurs at the client-side or the server-side. We are also able to identify several server-side data sharing relationships that are validated externally but are not detected by client-side cookie syncing.
Natural and pathogenic protein sequence variation affecting prion-like domains within and across human proteomes.

Impaired proteostatic regulation of proteins with prion-like domains (PrLDs) is associated with a variety of human diseases including neurodegenerative disorders, myopathies, and certain forms of cancer. For many of these disorders, current models suggest a prion-like molecular mechanism of disease, whereby proteins aggregate and spread to neighboring cells in an infectious manner. The development of prion prediction algorithms has facilitated the large-scale identification of PrLDs among “reference” proteomes for various organisms. However, the degree to which intraspecies protein sequence diversity influences predicted prion propensity has not been systematically examined. Here, we explore protein sequence variation introduced at genetic, post-transcriptional, and post-translational levels, and its influence on predicted aggregation propensity for human PrLDs. We find that sequence variation is relatively common among PrLDs and in some cases can result in relatively large differences in predicted prion propensity. Sequence variation introduced at the post-transcriptional level (via alternative splicing) also commonly affects predicted aggregation propensity, often by direct inclusion or exclusion of a PrLD. Finally, analysis of a database of sequence variants associated with human disease reveals a number of mutations within PrLDs that are predicted to increase prion propensity. Our analyses expand the list of candidate human PrLDs, quantitatively estimate the effects of sequence variation on the aggregation propensity of PrLDs, and suggest the involvement of prion-like mechanisms in additional human diseases.
6'-Methoxy Raloxifene-analog enhances mouse bone properties with reduced estrogen receptor binding.

Raloxifene (RAL) is an FDA-approved drug used to treat osteoporosis in postmenopausal women. RAL suppresses bone loss primarily through its role as a selective estrogen receptor modulator (SERM). This hormonal estrogen therapy promotes unintended side effects, such as hot flashes and increased thrombosis risk, and prevents the drug from being used in some patient populations at-risk for fracture, including children with bone disorders. It has recently been demonstrated that RAL can have significant positive effects on overall bone mechanical properties by binding to collagen and increasing bone tissue hydration in a cell-independent manner. A Raloxifene-Analog (RAL-A) was synthesized by replacing the 6-hydroxyl substituent with 6-methoxy in effort to reduce the compound's binding affinity for estrogen receptors (ER) while maintaining its collagen-binding ability. It was hypothesized that RAL-A would improve the mechanical integrity of bone in a manner similar to RAL, but with reduced estrogen receptor binding. Molecular assessment showed that while RAL-A did reduce ER binding, downstream ER signaling was not completely abolished. In-vitro, RAL-A performed similarly to RAL and had an identical concentration threshold on osteocyte cell proliferation, differentiation, and function. To assess treatment effect in-vivo, wildtype (WT) and heterozygous (OIM+/-) female mice from the Osteogenesis Imperfecta (OI) murine model were treated with either RAL or RAL-A from 8 weeks to 16 weeks of age. There was an untreated control group for each genotype as well. Bone microarchitecture was assessed using microCT, and mechanical behavior was assessed using 3-point bending. Results indicate that both compounds produced analogous gains in tibial trabecular and cortical microarchitecture. While WT mechanical properties were not drastically altered with either treatment, OIM+/- mechanical properties were significantly enhanced, most notably, in post-yield properties including bone toughness. This proof-of-concept study shows promising results and warrants the exploration of additional analog iterations to further reduce ER binding and improve fracture resistance.
Large‐scale ciliary reversal mediates capture of individual algal prey by Müller's larva

We documented capture of microalgal prey by several species of wild‐caught Muller's larvae of polyclad flatworms. To our knowledge, this is the first direct observation of feeding mechanism in this classical larval type. High‐speed video recordings showed that virtually all captures were mediated by large‐scale transient ciliary reversal over one or more portions of the main ciliary band corresponding to individual lobes or tentacles. Local ciliary beat reversals altered near‐field flow to suck parcels of food‐containing water mouthward. Many capture episodes entailed sufficient coordinated flow disruption that these compact‐bodied larvae tumbled dramatically. Similar behaviors were recorded in at least four distinct species, one of which corresponds to the ascidian‐eating polyclad Pseudoceros canadensis.
When Lift-and-Project Cuts Are Different

In this paper, we present a method to determine if a lift-and-project cut for a mixed-integer linear program is irregular, in which case the cut is not equivalent to any intersection cut from the b...
Singularity of random Bernoulli matrices

For each $n$, let $M_n$ be an $n\times n$ random matrix with independent $\pm 1$ entries. We show that ${\mathbb P}\{\mbox{$M_n$ is singular}\}=(1/2+o_n(1))^n$, which settles an old problem. Some generalizations are considered.
Optimal dynamic futures portfolio in a regime-switching market framework

We study the problem of dynamically trading futures in a regime-switching market. Modeling the underlying asset price as a Markov-modulated diffusion process, we present a utility maximization appr...
Generalized gorensteinness and a homological determinant for preprojective algebras

The study of invariants of group actions on commutative polynomial rings has motivated many developments in commutative algebra and algebraic geometry. It has been of particular interest to underst...
A simple proof of necessity in the McCullough-Quiggin theorem

A short and simple proof of necessity in the McCullough-Quiggin characterization of positive semi-definite kernels with the complete Pick property is presented.
Online Caching With Wireless Fronthauling and Delivery in Fog-Aided Networks

Fog Radio Access Network (F-RAN) exploits cached contents at edge nodes (ENs) and fronthaul connection to the cloud for content delivery. Assuming dedicated fronthaul links between cloud and each EN, previous works focused on analyses of F-RANs using offline or online caching depending whether the content popularity is time-invariant or time-variant. Extension has been done for multicast fronthaul link connecting cloud to only two ENs and time-invariant popularity. In contrast, the scope of this work is on the case where multicast fronthaul link connects arbitrary number of ENs to the cloud and content popularity is time-variant. Normalized Delivery Time (NDT) is used as a performance measure and by investigating proactive online caching, analytical results reveal that the power scaling of fronthaul transmission sets a limit on the performance of F-RAN.
Relaxing The Hamilton Jacobi Bellman Equation To Construct Inner And Outer Bounds On Reachable Sets

We consider the problem of overbounding and underbounding both the backward and forward reachable set for a given polynomial vector field, nonlinear in both state and input, with a given semialgebriac set of initial conditions and with inputs constrained pointwise to lie in a semialgebraic set. Specifically, we represent the forward reachable set using the "value function" which gives the optimal cost to go of an optimal control problems and if smooth satisfies the Hamilton-JacobiBellman PDE. We then show that there exist polynomial upper and lower bounds to this value function and furthermore, these polynomial "sub-value" and "super-value" functions provide provable upper and lower bounds to the forward reachable set. Finally, by minimizing the distance between these "sub-value" and "super-value" functions in the L 1 -norm, we are able to construct inner and outer bounds for the reachable set and show numerically on several examples that for relatively small degree, the Hausdorff distance between these bounds is negligible.
Robust Hierarchical MPC for Handling Long Horizon Demand Forecast Uncertainty with Application to Automotive Thermal Management

This paper presents a robust hierarchical MPC (H-MPC) for dynamic systems with slow states subject to demand forecast uncertainty. The H-MPC has two layers: (i) the scheduling MPC at the upper layer with a relatively long prediction/planning horizon and slow update rate, and (ii) the piloting MPC at the lower layer over a shorter prediction horizon with a faster update rate. The scheduling layer MPC calculates the optimal slow states, which will be tracked by the piloting MPC, while enforcing the system constraints according to a long-range and approximate prediction of the future demand/load, e.g., traction power demand for driving a vehicle. In this paper, to enhance the H-MPC robustness against the long-term demand forecast uncertainty, we propose to use the high-quality preview information enabled by the connectivity technology over the short horizon to modify the planned trajectories via a constraint tightening approach at the scheduling layer. Simulation results are presented for a simplified vehicle model to confirm the effectiveness of the proposed robust H-MPC framework in handling demand forecast uncertainty.