cssi/SciSciGPT-SciSciNet huggingface dataset:
OPTIMUM DESIGN OF ROTOR BLADES FOR VIBRATION REDUCTION IN FORWARD FLIGHT.

Modern structural optimization techniques are applied to vibration reduction of helicopter rotor blades in forward flight. The objective function minimized consists of the oscillatory vertical hub shears or the hub rolling moments at one particular advance ratio. The behavior constraints are the frequency placements of the blade and the requirement that aeroelastic stability margins, in hover, remain unaffected by the optimization process. The aeroelastic stability and response analysis is based on a fully coupled flap-lag-torsional analysis of the blade. Numerical results are presented for some typical soft-in-plane hingeless rotor configurations indicating a 15-40 percent reduction in vibration levels, as well as a blade which is 20 percent lighter than the initial design. These results imply that structural optimization techniques can yield substantial practical benefits in the design process of rotor systems.
On Undecided LP, Clustering and Active Learning

We study colored coverage and clustering problems. Here, we are given a colored point set, where the points are covered by k (unknown) clusters, which are monochromatic (i.e., all the points covered by the same cluster have the same color). The access to the colors of the points (or even the points themselves) is provided indirectly via various oracle queries (such as nearest neighbor, or separation queries). We show that one can correctly deduce the color of all the points (i.e., compute a monochromatic clustering of the points) using a polylogarithmic number of queries, if the number of clusters is a constant. We investigate several variants of this problem, including Undecided Linear Programming and covering of points by k monochromatic balls.
Embeddedness and cohesion: regimes of urban public goods distribution

Why do some urban governing regimes realize a more equal distribution of public goods than others? Local government interventions in Sao Paulo, Brazil, have produced surprisingly effective redistribution of residential public goods — housing and sanitation — between 1989 and 2016. I use original interviews and archival research for a comparative-historical analysis of variation across time in Sao Paulo’s governance of housing and sanitation. I argue that sequential configurations of a) “embeddedness” of the local state in civil society and b) the “cohesion” of the institutional sphere of the local state, explain why and when urban governing regimes generate the coordinating capacity to distribute public goods on a programmatic basis. I further illustrate how these configurations can explain variation in urban governing regimes across the world.
The South African–United States sovereign bond spread and its association with macroeconomic fundamentals

The yield spread of South African to United States 10 year government bonds over the last 5 years has increased substantially to levels approaching those last seen during the mid-1980s. This yield spread increase is replicated in spreads relative to long-term German bonds, as well as for the spread of state owned enterprises (ESKOM) to United States and German bonds. This paper examines the association between the spread and macroeconomic fundamentals over the 1960-2019 sample period, under the GARCH and GARCH-M class of estimators. We find that higher South African economic growth, lower inflation, public and private debt, as well as Rand-Dollar appreciation are all associated with a statistically significantly lower South African - United States yield spread. The strongest impact is associated with the public debt-to-GDP ratio. Mean spread levels do not appear to be influenced by yield volatility. Finally, while there is no evidence of sign bias in the impact of shocks on yield volatility (negative shock impacts are no diÂ¤erent than positive), there is evidence of size bias for both positive and negative shocks: larger shocks have a larger impact on volatility than small, regardless of their sign. Collectively, and even ignoring the impact of private sector leveraging, South Africaâ€™s performance in these macroeconomic fundamentals is associated with an increase in the SA-US yield spread of 363 basis points (since 2012). This constitutes a substantial proportion of the current 741 basis point spread.
A Vertex Model for LLT Polynomials

We describe a novel Yang-Baxter integrable vertex model. From this vertex model we construct a certain class of partition functions that we show are equal to the LLT polynomials of Lascoux, Leclerc, and Thibon. Using the vertex model formalism, we give alternate proofs of many properties of these polynomials, including symmetry and a Cauchy identity.
Irreparable Misidentifications and Reliability: Reassessing the Threshold for Admissibility of Eyewitness Identification

To be admitted at trial, an eyewitness identification resulting from a police-conducted procedure must be "reliable" notwithstanding any suggestivity in the identification process, a point emphatically reaffirmed by the Court in Perry v. New Hampshire. While great attention has been focused on what factors are to be weighed in determining reliability, little discussion has been had regarding the level of reliability, i.e., how sure a reviewing judge must be that the identification claim of "that’s the man" is indeed accurate. While the Court in the past has identified this as an "evidentiary" claim, to be evaluated on whether the identification has possible validity, it has simultaneously linked that determination to two criteria – that what must be avoided are "irreparable" mistaken identifications and that the evidence must be such that a jury can intelligently weigh it. Because DNA exonerations and ample research have shown that factfinders – both jurors and judges – often are incapable of discerning when an identification is erroneous, this Article proposes a sliding scale Due Process test for quantifying reliability. Even where a reviewing court must apply the traditional reliability criteria, the sliding scale test requires a suppression court judge to assess – in light of the jurisdiction’s safeguards such as expert testimony and science-based jury instructions – whether a jury will have enough information to intelligently weigh the identification testimony and avoid an irreparable mistaken identification. The fewer tools available to the jury, the more stringent the reliability determination must be to ensure the Due Process mandate.
Autocatalytic-protection for an unknown locus CRISPR-Cas countermeasure for undesired mutagenic chain reactions

The mutagenic chain reaction (MCR) is a genetic tool to use a CRISPR-Cas construct to introduce a homing endonuclease, allowing gene drive to influence whole populations in a minimal number of generations (Esvelt et al., 2014; Gantz and Bier, 2015; Gantz and Bier, 2016). The question arises: if an active genetic terror event is released into a population, could we prevent the total spread of the undesired allele (Gantz, et al., 2015; Webber et al., 2015)? Thus far, effective protection methods require knowledge of the terror locus (Grunwald et al., 2019). Here we introduce a novel approach, an autocatalytic-Protection for an Unknown Locus (a-PUL), whose aim is to spread through a population and arrest and decrease an active terror event's spread without any prior knowledge of the terror-modified locus, thus allowing later natural selection and ERACR drives to restore the normal locus (Hammond et al., 2017). a-PUL, using a mutagenic chain reaction, includes (i) a segment encoding a non-Cas9 endonuclease capable of homology-directed repair suggested as Type II endonuclease Cpf1 (Cas12a), (ii) a ubiquitously-expressed gene encoding a gRNA (gRNA1) with a U4AU4 3'-overhang specific to Cpf1 and with crRNA specific to some desired genomic sequence of non-coding DNA, (iii) a ubiquitously-expressed gene encoding two gRNAs (gRNA2/gRNA3) both with tracrRNA specific to Cas9 and crRNA specific to two distinct sites of the Cas9 locus, and (iv) homology arms flanking the Cpf1/gRNA1/gRNA2/gRNA3 cassette that are identical to the region surrounding the target cut directed by gRNA1 (Khan, 2016; Zetsche et al., 2015). We demonstrate the proof-of-concept and efficacy of our protection construct through a Graphical Markov model and computer simulation.
Accelerating Optimization and Reinforcement Learning with Quasi Stochastic Approximation

The paper sets out to obtain precise convergence rates for quasi-stochastic approximation (QSA), with applications to optimization and reinforcement learning. The main contributions are obtained for general nonlinear algorithms, under the assumption that there is a well defined linearization near the optimal parameter $\theta^{\ast}$ , with Hurwitz linearization matrix $A^{\ast}$ . Subject to stability of the algorithm (general conditions are surveyed in the paper): (i)If the algorithm gain is chosen as $a_{t}=g/(1+t)^{\rho}$ with $g > 0$ and $\rho\in(0,1)$ , then a “finite-t” approximation is obtained \begin{equation*} a_{t}^{-1}\{\Theta_{t}-\theta^{\ast}\}=\bar{Y}+\Xi_{t}^{\mathrm{I}}+o(1) \end{equation*} where $\Theta_{t}$ is the parameter estimate, $\bar{Y}\in \mathbb{R}^{d}$ is a vector identified in the paper, and $\{\Xi_{t}^{\mathrm{I}}\}$ is bounded with zero mean. (ii)The approximation continues to hold with $a_{t}=g/(1+t)$ under the stronger assumption that $I+gA^{\ast}$ is Hurwitz. (iii)The Ruppert-Polyak averaging technique is extended to this setting, in which the estimates $\{\Theta_{t}\}$ are obtained using the gain in (i), and $\Theta_{t}^{\mathbf{RP}}$ is defined to be the running average. The convergence rate is $1/t$ if and only if $\bar{Y}=0$ . (iv)The theory is illustrated with applications to gradient-free optimization, and policy gradient algorithms for reinforcement learning.
CytoSet: predicting clinical outcomes via set-modeling of cytometry data

Single-cell flow and mass cytometry technologies are being increasingly applied in clinical settings, as they enable the simultaneous measurement of multiple proteins across millions of cells within a multi-patient cohort. In this work, we introduce CytoSet, a deep learning model that can directly predict a patient's clinical outcome from a collection of cells obtained through a blood or tissue sample. Unlike previous work, CytoSet explicitly models the cells profiled in each patient sample as a set, allowing for the use of recently developed permutation invariant architectures. We show that CytoSet achieves state-of-the-art classification performance across a variety of flow and mass cytometry benchmark datasets. The strong classification performance is further complemented by demonstrated robustness to the number of sub-sampled cells per patient and the depth of model, enabling CytoSet to scale adequately to hundreds of patient samples. The strong performance achieved by the set-based architectures used in CytoSet suggests that clinical cytometry data can be appropriately interpreted and studied as sets. The code is publicly available at https://github.com/CompCy-lab/cytoset.
Phonon- and defect-limited electron and hole mobility of diamond and cubic boron nitride: A critical comparison

Diamond and cBN are two of the most promising ultra-wide bandgap semiconductors for applications in high-power high-frequency electronic devices. Despite extensive studies on carrier transport in these materials, there are large discrepancies in their reported carrier mobilities. In this work, we investigate the phonon- and dopant-limited electron and hole mobilities of cBN and diamond with atomistic first-principles calculations in order to understand their fundamental upper bounds to carrier transport. Our results show that although the phonon-limited electron mobilities are comparable between cBN and diamond, the hole mobility is significantly lower in cBN due to its heavier hole effective mass. Moreover, although lattice scattering dominates the mobility at low doping, neutral impurity scattering becomes the dominant scattering mechanism at higher dopant concentrations due to the high dopant ionization energies. Our analysis provides critical insights and reveals the intrinsic upper limits to the carrier mobilities of diamond and cBN as a function of doping and temperature for applications in high-power electronic devices.
Wearables-Only Analysis of Muscle and Joint Mechanics: An EMG-Driven Approach

Complex sensor arrays prohibit practical deployment of existing wearables-based algorithms for free-living analysis of muscle and joint mechanics. Machine learning techniques have been proposed as a potential solution, however, they are less interpretable and generalizable when compared to physics-based techniques. Herein, we propose a hybrid method utilizing inertial sensor- and electromyography (EMG)-driven simulation of muscle contraction to characterize knee joint and muscle mechanics during walking gait. Machine learning is used only to map a subset of measured muscle excitations to a full set thereby reducing the number of required sensors. We demonstrate the utility of the approach for estimating net knee flexion moment (KFM) as well as individual muscle moment and work during the stance phase of gait across nine unimpaired subjects. Across all subjects, KFM was estimated with 0.91 %BWH RMSE and strong correlations (r = 0.87) compared to ground truth inverse dynamics analysis. Estimates of individual muscle moments were strongly correlated (r = 0.81-0.99) with a reference EMG-driven technique using optical motion capture and a full set of electrodes as were estimates of muscle work (r = 0.88-0.99). Implementation of the proposed technique in the current work included instrumenting only three muscles with surface electrodes (lateral and medial gastrocnemius and vastus medialis) and both the thigh and shank segments with inertial sensors. These sensor locations permit instrumentation of a knee brace/sleeve facilitating a practically deployable mechanism for monitoring muscle and joint mechanics with performance comparable to the current state-of-the-art.
Differential Privacy Meets Federated Learning under Communication Constraints

The performance of federated learning systems is bottlenecked by communication costs and training variance. The communication overhead problem is usually addressed by three communication-reduction techniques, namely, model compression, partial device participation, and periodic aggregation, at the cost of increased training variance. Different from traditional distributed learning systems, federated learning suffers from data heterogeneity (since the devices sample their data from possibly different distributions), which induces additional variance among devices during training. Various variance-reduced training algorithms have been introduced to combat the effects of data heterogeneity, while they usually cost additional communication resources to deliver necessary control information. Additionally, data privacy remains a critical issue in FL, and thus there have been attempts at bringing Differential Privacy to this framework as a mediator between utility and privacy requirements. This paper investigates the trade-offs between communication costs and training variance under a resource-constrained federated system theoretically and experimentally, and studies how communication reduction techniques interplay in a differentially private setting. The results provide important insights into designing practical privacy-aware federated learning systems.
On earnings and cash flows as predictors of future cash flows

Abstract Do accruals-based earnings provide better information about future operating cash flows than do operating cash flows themselves, as predicted by the Financial Accounting Standards Board's conceptual framework (FASB, 1978)? While this is a foundational issue in accounting, because it addresses the information added by accrual accounting methods, testing it remains unsettled. We show that when comparing the predictive ability of operating cash flows with that of an equivalent earnings measure calculated on an accrual basis, earnings outperform operating cash flows. The result becomes more pronounced when allowance is made for cross-sectional differences in the relation between firms' earnings and future cash flows. In fact, even “bottom line” earnings then have similar explanatory power as operating cash flows.
Stochastic Graphon Games: I. The Static Case

We consider static finite-player network games and their continuum analogs graphon games. Existence and uniqueness results are provided as well as convergence of the finite-player network game opti...
Gaussian Regularization of the Pseudospectrum and Davies' Conjecture

A matrix $A\in\mathbb{C}^{n\times n}$ is diagonalizable if it has a basis of linearly independent eigenvectors. Since the set of nondiagonalizable matrices has measure zero, every $A\in \mathbb{C}^{n\times n}$ is the limit of diagonalizable matrices. We prove a quantitative version of this fact conjectured by E.B. Davies: for each $\delta\in (0,1)$, every matrix $A\in \mathbb{C}^{n\times n}$ is at least $\delta\|A\|$-close to one whose eigenvectors have condition number at worst $c_n/\delta$, for some constants $c_n$ dependent only on $n$. Our proof uses tools from random matrix theory to show that the pseudospectrum of $A$ can be regularized with the addition of a complex Gaussian perturbation. Along the way, we explain how a variant of a theorem of Śniady implies a conjecture of Sankar, Spielman and Teng on the optimal constant for smoothed analysis of condition numbers.
Order-Preserving Encryption Revisited: Improved Security Analysis and Alternative Solutions.

We further the study of order-preserving symmetric encryption (OPE), a primitive for allowing ecient range queries on encrypted data, recently initiated (from a cryptographic perspective) by Boldyreva et al. (Eurocrypt ’09). First, we address the open problem of characterizing what encryption via a random order-preserving function (ROPF) leaks about underlying data (ROPF being the \ideal object" in the security denition, POPF, satised by their scheme.) In particular, we show that, for a database of randomly distributed plaintexts and appropriate choice of parameters, ROPF encryption leaks neither the precise value of any plaintext nor the precise distance between any two of them. The analysis here introduces useful new techniques. On the other hand, we show that ROPF encryption leaks approximate value of any plaintext as well as approximate distance between any two plaintexts, each to an accuracy of about square root of the domain size. We then study schemes that are not order-preserving, but which nevertheless allow ecient range queries and achieve security notions stronger than POPF. In a setting where the entire database is known in advance of key-generation (considered in several prior works), we show that recent constructions of \monotone minimal perfect hash functions" allow to eciently
Contemporary Rates of Inferior Vena Cava Filter Thrombosis and Risk Factors

Abstract Objective Inferior vena cava thrombosis is an uncommon complication associated with inferior vena cava filters (IVCF), with literature citing rates ranging from 1% to 31%. Few observational studies describe risk factors associated with IVCF thrombosis, despite the significant clinical sequelae such as post-thrombotic syndrome, venous claudication, and venous ulceration. To better describe IVCF thrombosis and risk factors, data were queried from VQI-participating centers. Methods IVCF data were obtained through the international VQI database from 2013 – 2019. Patients included in this analysis had two-year follow-up. Baseline demographics, medical comorbidities, medication, procedural, anatomical, and post-operative variables were assessed using Kaplan-Meier survival curves with log-rank tests, Student’s t-tests, or Mann-Whitney U tests for IVCF thrombosis at two years. Cox regression analyses identified independent predictors of IVCF thrombosis. A subgroup analysis of those who presented with a venous thromboembolism (VTE) was also performed. Results There were 62 US and Canadian VQI-participating centers, including 12,874 cases of IVCF placement. There 78 cases (1.3%) of IVCF thrombosis identified out of a total of 5,780 cases with two-year follow up. Those who experienced IVCF thrombosis had significantly lower rates of diabetes, coronary artery disease, pre-operative antiplatelet medications, pre-operative statins, as well as lower rates of discharge and follow up antiplatelet medications. On univariable analysis, cases of IVCF thrombosis also had higher rates of pulmonary emboli (PE) and VTE on admission, internal jugular venous access (versus femoral vein access), temporary IVCF use, follow up anticoagulation, follow up IVCF complication, follow up access site thrombosis, and rates of new or propagated DVT at follow up, and longer post-operative hospital stays. Multivariable analysis demonstrated independent predictors of IVCF thrombosis included new or propagated DVT at follow up (hazard ratio [HR]=16.3, 95% confident interval (CI) = 9.8 – 27.3, P Conclusion The rate of IVCF thrombosis remained low in a contemporary international database. This study of over 5,000 patients with IVCFs suggests that antiplatelet therapy should be administered after IVCF placement to decreased risk of IVCF thrombosis.
Transferred-Arc Cleaning of Tungsten

Abstract Transferred-arc cleaning is being investigated as a solvent-free cleaning method for various metallic substrates. With the recent increase in attention given the hazards involved in the storage, use and disposal of organic solvents, cleaning methods which promise comparable cleaning effectiveness with reduced hazards are being sought. Transferred-arc cleaning of tungsten substrates has been studied to identify the effect of processing conditions on cleaning and roughening characteristics. A Box-Behnken response surface designed experiment varying the chamber pressure, substrate standoff distance and plasma torch arc current while observing the transferred-arc voltage, current, surface cleanliness and surface roughness was performed. The results of the analysis show the effect of the various independent variables on the measured responses. Particular difficulties in roughening tungsten are due to its exceptionally high arc voltage for metal arc attachment. The results presented here provide an enhanced understanding of the arcing properties of various cathode materials. Such information is useful in obtaining the desired cleaning and/or roughening of the substrate.
Age and sex effects on advanced white matter microstructure measures in 15,628 older adults: A UK biobank study

A comprehensive characterization of the brain’s white matter is critical for improving our understanding of healthy and diseased aging. Here we used diffusion-weighted magnetic resonance imaging (dMRI) to estimate age and sex effects on white matter microstructure in a cross-sectional sample of 15,628 adults aged 45–80 years old (47.6% male, 52.4% female). Microstructure was assessed using the following four models: a conventional single-shell model, diffusion tensor imaging (DTI); a more advanced single-shell model, the tensor distribution function (TDF); an advanced multi-shell model, neurite orientation dispersion and density imaging (NODDI); and another advanced multi-shell model, mean apparent propagator MRI (MAPMRI). Age was modeled using a data-driven statistical approach, and normative centile curves were created to provide sex-stratified white matter reference charts. Participant age and sex substantially impacted many aspects of white matter microstructure across the brain, with the advanced dMRI models TDF and NODDI detecting such effects the most sensitively. These findings and the normative reference curves provide an important foundation for the study of healthy and diseased brain aging.
Differentiable thermodynamic modeling

Abstract A new framework of thermodynamic modeling is proposed by introducing the concept of differentiable programming, where all the thermodynamic observables including both thermochemical quantities and phase equilibria can be differentiated with respect to the underlying model parameters, thus allowing the models learned by gradient-based optimization. It is shown that thermodynamic modeling and deep learning can be seamlessly integrated and unified within this framework. A preliminary successful application is demonstrated for the Cu-Rh system. It is expected that thermodynamic modeling in a deep learning style can increase prediction power of models, and provide more effective guidance for design, synthesis and optimization of multi-component materials with complex chemistry via learning various types of data.
Determining Aircraft Moments of Inertia from Flight Test Data

Flight test maneuvers and dynamic modeling techniques were developed for determining aircraft moments of inertia from flight test data. Full nonlinear rigid-body rotational equations of motion were...
Radio Observations of an Ordinary Outflow from the Tidal Disruption Event AT2019dsg

We present detailed radio observations of the tidal disruption event (TDE) AT2019dsg, obtained with the Very Large Array (VLA) and the Atacama Large Millimeter/submillimeter Array (ALMA), and spanning $55-560$ days post-disruption. We find that the peak brightness of the radio emission increases until ~200 days and subsequently begins to decrease steadily. Using the standard equipartition analysis, including the effects of synchrotron cooling as determined by the joint VLA-ALMA spectral energy distributions, we find that the outflow powering the radio emission is in roughly free expansion with a velocity of $\approx 0.07c$, while its kinetic energy increases by a factor of about 5 from 55 to 200 days and plateaus at $\approx 5\times 10^{48}$ erg thereafter. The ambient density traced by the outflow declines as $\approx R^{-1.6}$ on a scale of $\approx (1-4)\times 10^{16}$ cm ($\approx 6300-25000$ $R_s$), followed by a steeper decline to $\approx 6\times 10^{16}$ cm ($\approx 37500$ $R_s$). Allowing for a collimated geometry, we find that to reach even mildly relativistic velocities ($\Gamma=2$) the outflow requires an opening angle of $\theta_j\approx 2^\circ$, which is narrow even by the standards of GRB jets; a truly relativistic outflow requires an unphysically narrow jet. The outflow velocity and kinetic energy in AT2019dsg are typical of previous non-relativistic TDEs, and comparable to those from Type Ib/c supernovae, raising doubts about the claimed association with a high-energy neutrino event.
Topological stars, black holes and generalized charged Weyl solutions

We construct smooth static bubble solutions, denoted as topological stars, in five-dimensional Einstein-Maxwell theories which are asymptotic to $\mathbb{R}^{1,3}\times$S$^1$. The bubbles are supported by allowing electromagnetic fluxes to wrap smooth topological cycles. The solutions live in the same regime as non-extremal static charged black strings, that reduce to black holes in four dimensions. We generalize to multi-body configurations on a line by constructing closed-form generalized charged Weyl solutions in the same theory. Generic solutions consist of topological stars and black strings stacked on a line, that are wrapped by electromagnetic fluxes. We embed the solutions in type IIB String Theory on S$^1\times$T$^4$. In this framework, the charged Weyl solutions provide a novel class in String Theory of multiple charged objects in the non-supersymmetric and non-extremal black hole regime.
Dyadic Carleson embedding and sparse domination of weighted composition operators on strictly pseudoconvex domains

Abstract In this paper, we study the behavior of the weighted composition operators acting on Bergman spaces defined on strictly pseudoconvex domains via the sparse domination technique from harmonic analysis. As a byproduct, we also prove a weighted type estimate for the weighted composition operators which is adapted to Sawyer-testing conditions. Our results extend the work by the first author, Li, Shi and Wick under a much more general setting.
Preference-Based Learning for User-Guided HZD Gait Generation on Bipedal Walking Robots

This paper presents a framework that leverages both control theory and machine learning to obtain stable and robust bipedal locomotion without the need for manual parameter tuning. Traditionally, gaits are generated through trajectory optimization methods and then realized experimentally — a process that often requires extensive tuning due to differences between the models and hardware. In this work, the process of gait realization via hybrid zero dynamics (HZD) based optimization is formally combined with preference-based learning to systematically realize dynamically stable walking. Importantly, this learning approach does not require a carefully constructed reward function, but instead utilizes human pairwise preferences. The power of the proposed approach is demonstrated through two experiments on a planar biped AMBER-3M: the first with rigid point-feet, and the second with induced model uncertainty through the addition of springs where the added compliance was not accounted for in the gait generation or in the controller. In both experiments, the framework achieves stable, robust, efficient, and natural walking in fewer than 50 iterations with no reliance on a simulation environment. These results demonstrate a promising step in the unification of control theory and learning.
Designing Composites with Target Effective Young’s Modulus using Reinforcement Learning

Advancements in additive manufacturing have enabled design and fabrication of materials and structures not previously realizable. In particular, the design space of composite materials and structures has vastly expanded, and the resulting size and complexity has challenged traditional design methodologies, such as brute force exploration and one factor at a time (OFAT) exploration, to find optimum or tailored designs. To address this challenge, supervised machine learning approaches have emerged to model the design space using curated training data; however, the selection of the training data is often determined by the user. In this work, we develop and utilize a Reinforcement learning (RL)-based framework for the design of composite structures which avoids the need for user-selected training data. For a 5 × 5 composite design space comprised of soft and compliant blocks of constituent material, we find that using this approach, the model can be trained using 2.78% of the total design space consists of 225 design possibilities. Additionally, the developed RL-based framework is capable of finding designs at a success rate exceeding 90%. The success of this approach motivates future learning frameworks to utilize RL for the design of composites and other material systems.
Enabling microbiome research on personal devices

Microbiome studies have recently transitioned from experimental designs with a few hundred samples to designs spanning tens of thousands of samples. Modern studies such as the Earth Microbiome Project (EMP) afford the statistics crucial for untangling the many factors that influence microbial community composition. Analyzing those data used to require access to a compute cluster, making it both expensive and inconvenient. We show that recent improvements in both hardware and software now allow to compute key bioinformatics tasks on EMP-sized data in minutes using a gaming-class laptop, enabling much faster and broader microbiome science insights.
A Graph Approach to Simulate Twitter Activities with Hawkes Processes

The rapid growth of social media has been witnessed during recent years as a result of the prevalence of the internet. This trend brings an increasing interest in simulating social media which can provide valuable insights to both academic researchers and businesses. In this paper, we present a step-by-step approach of using Hawkes process, a self-activating stochastic process, to simulate Twitter activities and demonstrate how this model can be utilized to evaluate the chance of extremely rare web crises. Another goal of this research is to introduce a new strategy that implements Hawkes process on graph structures. Overall, we intend to extend the current Hawkes process to a wider range of scenarios and, in particular, create a more realistic simulation of Twitter activities by incorporating the actual user status and following-follower interactions between users.
The Game of Poker Chips, Dominoes and Survival

The Game of Poker Chips, Dominoes and Survival was created to foster cohesion in a group setting. Given two colored poker chips, each player needs to secure a domino before time is called in order to `survive', and can make exchanges according to two simple rules. Analysis reveals that the group will be forced to cooperate at a high level in order to succeed, and a simple time complexity computation shows how the game coordinator can choose the initial distribution of poker chips to the players in order to fine tune the game's difficulty. A simple criteria is given for determining if the game is `solvable' for any given initial chip distribution, that is, if all players can survive if given sufficient time to make exchanges. The best strategies for group survival, that is, those taking the least amount of time, are provided as consequences of simple complexity arguments. In addition to being a lively game to play in management training or classroom settings, the analysis of the game after play can make for an engaging exercise in any basic discrete mathematics course to give a basic introduction to elements of game theory, logical reasoning, induction, recursion, number theory and the computation of algorithmic complexities.
Fairness in Ranking under Uncertainty

Fairness has emerged as an important consideration in algorithmic decision-making. Unfairness occurs when an agent with higher merit obtains a worse outcome than an agent with lower merit. Our central point is that a primary cause of unfairness is uncertainty. A principal or algorithm making decisions never has access to the agents' true merit, and instead uses proxy features that only imperfectly predict merit (e.g., GPA, star ratings, recommendation letters). None of these ever fully capture an agent's merit; yet existing approaches have mostly been defining fairness notions directly based on observed features and outcomes. Our primary point is that it is more principled to acknowledge and model the uncertainty explicitly. The role of observed features is to give rise to a posterior distribution of the agents' merits. We use this viewpoint to define a notion of approximate fairness in ranking. We call an algorithm $\phi$-fair (for $\phi \in [0,1]$) if it has the following property for all agents $x$ and all $k$: if agent $x$ is among the top $k$ agents with respect to merit with probability at least $\rho$ (according to the posterior merit distribution), then the algorithm places the agent among the top $k$ agents in its ranking with probability at least $\phi \rho$. We show how to compute rankings that optimally trade off approximate fairness against utility to the principal. In addition to the theoretical characterization, we present an empirical analysis of the potential impact of the approach in simulation studies. For real-world validation, we applied the approach in the context of a paper recommendation system that we built and fielded at a large conference.
Frizzled3 inhibits Vangl2-Prickle3 association to establish planar cell polarity in the vertebrate neural plate.

The orientation of epithelial cells in the plane of the tissue, known as planar cell polarity (PCP), is regulated by interactions of asymmetrically localized PCP protein complexes. In the Xenopus neural plate, Van Gogh-like2 (Vangl2) and Prickle3 (Pk3) proteins form a complex at the anterior cell boundaries, but how this complex is regulated in vivo remains largely unknown. Here we use proximity biotinylation and crosslinking approaches to show that Vangl2-Pk3 association is inhibited by Frizzled3 (Fz3), a core PCP protein that is specifically expressed in the neuroectoderm and is essential for the establishment of PCP in this tissue. This inhibition required Fz3-dependent Vangl2 phosphorylaton. Consistent with our observations, the complex of Pk3 with nonphosphorylatable Vangl2 did not polarize in the neural plate. These findings provide evidence for in vivo regulation of Vangl2-Pk3 complex formation and localization by a Frizzled receptor.
Estimating the natural indirect effect and the mediation proportion via the product method

BACKGROUND The natural indirect effect (NIE) and mediation proportion (MP) are two measures of primary interest in mediation analysis. The standard approach for mediation analysis is through the product method, which involves a model for the outcome conditional on the mediator and exposure and another model describing the exposure-mediator relationship. The purpose of this article is to comprehensively develop and investigate the finite-sample performance of NIE and MP estimators via the product method. METHODS With four common data types with a continuous/binary outcome and a continuous/binary mediator, we propose closed-form interval estimators for NIE and MP via the theory of multivariate delta method, and evaluate its empirical performance relative to the bootstrap approach. In addition, we have observed that the rare outcome assumption is frequently invoked to approximate the NIE and MP with a binary outcome, although this approximation may lead to non-negligible bias when the outcome is common. We therefore introduce the exact expressions for NIE and MP with a binary outcome without the rare outcome assumption and compare its performance with the approximate estimators. RESULTS Simulation studies suggest that the proposed interval estimator provides satisfactory coverage when the sample size ≥500 for the scenarios with a continuous outcome and sample size ≥20,000 and number of cases ≥500 for the scenarios with a binary outcome. In the binary outcome scenarios, the approximate estimators based on the rare outcome assumption worked well when outcome prevalence less than 5% but could lead to substantial bias when the outcome is common; in contrast, the exact estimators always perform well under all outcome prevalences considered. CONCLUSIONS Under samples sizes commonly encountered in epidemiology and public health research, the proposed interval estimator is valid for constructing confidence interval. For a binary outcome, the exact estimator without the rare outcome assumption is more robust and stable to estimate NIE and MP. An R package mediateP is developed to implement the methods for point and variance estimation discussed in this paper.
Materials and technologies for rechargeable lithium–sulfur batteries

Lithium–sulfur (Li–S) batteries are one of the most promising energy storage systems being developed as an alternative to conventional intercalation-type lithium-ion batteries. This chapter first discusses the fundamental chemistry and existing issues associated with Li–S system. It then consolidates significant advances in the Li–S battery, including the development of sulfur composite cathodes, binders, and electrolytes, as well as several notable new concepts in materials and cell design.
Topological Neighborhoods for Spline Curves: Practice & Theory

The unresolved subtleties of floating point computations in geometric modeling become considerably more difficult in animations and scientific visualizations. Some emerging solutions based upon topological considerations for curves will be presented. A novel geometric seeding algorithm for Newton's method was used in experiments to determine feasible support for these visualization applications.
La epidemia del sida en Cuba

Cuba's response to tbe Human Immunodeficiency Virus (HIV) epidemic has been to conduct mass testing of tbe population to ascertain leroprevalence, to enforce mandatory relative quarantine of persons testing positivc:, and to implement educational interventions using media and sehool-based programs. Results reported to date show a low seroprevalence rate without evidence of a widespread· epidemic. Possible advantages of Cuba's poliey inelude rapid reduction in the risk of HIV .transmission by infected blood products, an opportunity for focused education and secondary prevention, and limitation of new infections. Possible disadvantages inelude the restrietion of individuals' freedom who are not guilty of any ilegal act, quarantine ofpenons with falle positive HIV tests,and ongoing transmission because of the incomplete nature of the quarantine, Cuba's HIV polierl. expenalve,may displace other public health priorities, and emphaai2el government regulatlon Instead of personal responsability for behavioraI c:hange.The quarantine poliey may paradoxicalIy permit most Cubans to feeI that they a~ personaIly invulnerable to the HIV epidemie. Ke-y fIIords: Cuba, AIDS, HIV preventlon, quarantine.
The Illusion of Fairness Through Special Committees in Management Buyouts

This essay will explore these deficiencies and argue for real, and not illusory, safeguards against directors' self-dealing in management buyouts. Part II provides an overview of corporation law regarding the decisionmaking authority of the board. Part III discusses self-dealing transactions as exceptions to the normal judicial deference accorded board decisions. Part IV discusses the flaws in the use of the special committee to address conflict of interest problems. Part V provides an analysis of the case introducing this essay and Part VI offers conclusions and suggestions for reform.
THE CYTOCHROME C OXIDASE COMPONENTS. VI. EFFECT OF BOROHYDRIDE ON PRESUMED "OXYGENATED COMPLEX".

Abstract A study of the effect of borohydride on the so-called “oxygen complex” of Okunuki has been made. The evidence that borohydride will not reduce oxidized cytochrome c oxidase but will reduce “the oxygenated complex” is questioned. It is suggested that borohydride can reduce cytochrome c oxidase because of its ability to reduce oxidation products of dithionite.
Wide-bandwidth Identification of small-signal dq impedances of ac power systems via single-phase series voltage injection

The injection of single-phase wide-bandwidth signals into three-phase ac power systems significantly reduces measurement time using the hardware with minimized number of components. Interleaved transformer-less H-bridge converter is optimized to operate as a series voltage injector, increasing the low frequency injection range by avoiding transformer saturation problems. The decoupling control is implemented, providing the effective way to balance dc capacitor voltages and regulate the series injection voltage. The modular and scalable single-phase impedance measurement unit (IMU) is designed and constructed to inject chirp, multi-tone and sinusoidal signals in series with the three-phase ac power systems. The measurement system is designed to inject all three types of signals in the full frequency range, offering a trade-off between measurement time, identification process precision, and number of identification points. The effectiveness of the proposed identification approach is verified with the online estimation of source and load impedances of actively controlled programmable voltage source and a three-phase resistive load.
Use of Patient-Centered Function and Symptom Rating Systems in Spinal Disorders

The criteria for assessing patients with disorders of the lumbar spine have historically been subjective and variable. This situation has led to uncertainty about diagnostic criteria, operative indications, and surgical outcome. In an effort to improve the evaluation process, various patient-centered function and symptom rating systems, including questionnaires and functional tests, have recently been developed. This report reviews several of these rating systems and their role in the assessment of patients with back-related symptoms.
Biomechanical characteristics of hemi-hamate reconstruction versus volar plate arthroplasty in the treatment of dorsal fracture dislocations of the proximal interphalangeal joint.

Purpose To compare stability and range of motion after hemi-hamate reconstruction versus volar plate arthroplasty in a biomechanical proximal interphalangeal (PIP) joint fracture-dislocation model. Methods Eighteen digits from 6 cadaver hands were tested. We created defects of 40%, 60%, and 80% in the palmar base of each digit's middle phalanx, simulating an acute PIP joint fracture-dislocation. Each defect scenario was reconstructed with a hemi-hamate arthroplasty followed by a volar plate arthroplasty. A computer-controlled mechanism was used to bring each digit's PIP joint from full extension to full flexion via the digital tendons in each testing state, and in the intact state. During each testing scenario we collected PIP joint cinedata in a true lateral projection using mini-fluoroscopy. A digital radiography program was used to measure the amount of middle phalanx dorsal translation (subluxation) in full PIP joint extension. We recorded the angle at which subluxation, if present, occurred during each testing scenario. Results Average dorsal displacement of the middle phalanx in relation to the proximal phalanx was 0.01 mm for the hemi-hamate reconstructed joints and –0.03 mm for the volar plate arthroplasty, compared with the intact state. Flexion contractures were noted in each of the specimens reconstructed with volar plate arthroplasty. Degree of contracture was directly correlated with defect size, averaging 20° for 40% defects, 35° for 60% defects, and 60° for 80% defects. We observed no flexion contractures in the hemi-hamate reconstructions. Conclusions Surgeons can use both hemi-hamate and volar plate arthroplasty to restore PIP joint stability following a fracture dislocation with a large middle phalanx palmar base defect. Use of volar plate arthroplasty led to an increasing flexion contracture as the middle phalanx palmar base defect increased. Clinical relevance Clinicians can use the information from this study to help with surgical decision-making and patient education.
Lag Periods During the Self-Assembly of {Mo72Fe30} Macroions: Connection to the Virus Capsid Formation Process

The kinetic properties of the self-assembly of hydrophilic Keplerate-type polyoxometalate (POM) {Mo72Fe30} macroanions into single-layer, vesicle-like blackberry structures in solutions were monitored by the static and dynamic laser light scattering techniques. In the presence of additional electrolytes, an obvious lag period at the initial stage of self-assembly was observed, followed by a fast increase of the scattered intensity. The whole kinetic curve is sigmoidal with a lag phase. A two-step nucleation−growth mechanism is proposed to explain this lag phase: the {Mo72Fe30} macroanions slowly associate into oligomers (mostly dimers), which are the thermodynamically unfavorable intermediates, at the initial stage; once the oligomers reach a critical concentration, the blackberry formation process is accelerated. Analytical ultracentrifugation (AUC) was used to confirm the oligomeric state in {Mo72Fe30} solution during the lag period. The length of the lag period is dependent on temperature, ionic streng...