cssi/SciSciGPT-SciSciNet huggingface dataset:
In Situ Monitoring of Composition and Sensitivity to Growth Parameters of Pulsed Laser Deposition

Complex oxides with perovskite structure have been widely studied for their diverse functional properties. When dimensionally reduced to epitaxial thin films and heterostructures, these properties ...
A Non-Geometrodynamic Quantum Yang-Mills Theory of Gravity Based on the Homogeneous Lorentz Group

In this paper, we present a non-geometrodynamic quantum Yang–Mills theory of gravity based on the homogeneous Lorentz group within the general framework of the Poincare gauge theories. The obstacles of this treatment are that first, on the one hand, the gauge group that is available for this purpose is non-compact. On the other hand, Yang–Mills theories with non-compact groups are rarely healthy, and only a few instances exist in the literature. Second, it is not clear how the direct observations of space–time waves can be explained when space–time has no dynamics. We show that the theory is unitary and is renormalizable to the one-loop perturbation. Although in our proposal, gravity is not associated with any elementary particle analogous to the graviton, classical helicity-two space–time waves are explained. Five essential exact solutions to the field equations of our proposal are presented as well. We also discuss a few experimental tests that can falsify the presented Yang–Mills theory.
Shellability of face posets of electrical networks and the CW poset property

Abstract We prove a conjecture of Thomas Lam that the face posets of stratified spaces of planar resistor networks are shellable. These posets are called uncrossing partial orders. This shellability result combines with Lam's previous result that these same posets are Eulerian to imply that they are CW posets, namely that they are face posets of regular CW complexes. Certain subposets of uncrossing partial orders are shown to be isomorphic to type A Bruhat order intervals; our shelling is shown to coincide on these intervals with a Bruhat order shelling which was constructed by Matthew Dyer using a reflection order. Our shelling for uncrossing posets also yields an explicit shelling for each interval in the face posets of the edge product spaces of phylogenetic trees, namely in the Tuffley posets, by virtue of each interval in a Tuffley poset being isomorphic to an interval in an uncrossing poset. This yields a more explicit proof of the result of Gill, Linusson, Moulton and Steel that the CW decomposition of Moulton and Steel for the edge product space of phylogenetic trees is a regular CW decomposition.
The Effects of Prefilled Tax Returns on Taxpayer Compliance

This study uses two online experiments to examine the potential consequences of a recent U.S. Senate proposal to prefill federal income tax returns on behalf of individuals. Consistent with omission theory, we find that prefilled returns lower compliance compared to self-completed returns when the prefilled returns do not estimate undocumented sources of income (e.g., cash tips). However, our results show that including estimates of undocumented income increases taxpayer compliance relative to self-completed returns. We also find evidence suggesting that prefilled returns eliminate the often-replicated differences in reporting behavior between taxpayers in refund versus tax due settlement positions, suggesting that prefilled returns changed individuals’ reference points. These findings suggest the implementation of a prefilled return policy could have economically important effects on taxpayer decisions.
Shifting Opinions in a Social Network Through Leader Selection

We study the French–DeGroot opinion dynamics in a social network with two polarizing parties. We consider a network in which the leaders of one party are given, and we pose the problem of selecting the leader set of the opposing party so as to shift the average opinion to a desired value. When each party has only one leader, we express the average opinion in terms of the transition matrix and the stationary distribution of random walks in the network. The analysis shows the balance of influence between the two leader nodes. We show that the problem of selecting at most $k$ absolute leaders to shift the average opinion is NP-hard. Then, we reduce the problem to a problem of submodular maximization with a submodular knapsack constraint and an additional cardinality constraint, and propose a greedy algorithm with upper bound search to approximate the optimum solution. We also conduct experiments in random networks and real-world networks to show the effectiveness of the algorithm.
Gender gaps in education: The long view

Many countries remain far from achieving gender equality in the classroom. Using data from 126 countries, we characterize the evolution of gender gaps in low- and middle-income countries between 1960 and 2010. We document five facts. First, women are more educated today than 50 years ago in every country in the world. Second, they remain less educated than men in the vast majority of countries. Third, in many countries with low levels of education for both men and women in 1960, gender gaps widened as more boys went to school, then narrowed as girls enrolled; thus, gender gaps got worse before they got better. Fourth, gender gaps rarely persist in countries where boys attain high levels of education. Most countries with large, current gender gaps in educational attainment have low levels of male educational attainment, and many also perform poorly on other measures of development such as life expectancy and GDP per capita. Fifth, in the youngest cohorts, women have more education than men in some regions of the world. Although gender gaps in educational attainment are diminishing in most countries, the empirical evidence does not support the hypothesis that reducing the gender gap in schooling consistently leads to smaller gender gaps in labor force participation.
Chiral self-sorting of active semiflexible filaments with intrinsic curvature

Many-body interactions in systems of active matter can cause particles to move collectively and self-organize into dynamic structures with long-range order. In cells, the self-assembly of cytoskeletal filaments is critical for cellular motility, structure, intracellular transport, and division. Semiflexible cytoskeletal filaments driven by polymerization or motor-protein interactions on a two-dimensional substrate, such as the cell cortex, can induce filament bending and curvature leading to interesting collective behavior. For example, the bacterial cell-division filament FtsZ is known to have intrinsic curvature that causes it to self-organize into rings and vortices, and recent experiments reconstituting the collective motion of microtubules driven by motor proteins on a surface have observed chiral symmetry breaking of the collective behavior due to motor-induced curvature of the filaments. Previous work on the self-organization of driven filament systems have not studied the effects of curvature and filament structure on collective behavior. In this work, we present Brownian dynamics simulation results of driven semiflexible filaments with intrinsic curvature and investigate how the interplay between filament rigidity and radius of curvature can tune the self-organization behavior in homochiral systems and heterochiral mixtures. We find a curvature-induced reorganization from polar flocks to self-sorted chiral clusters, which is modified by filament flexibility. This transition changes filament transport from ballistic to diffusive at long timescales.
Constructing a Tower of Babble: An Examination of Purpose in Establishment Clause Jurisprudence

“Purpose” is a key component of modern Establishment Clause jurisprudence. While the Supreme Court has expanded the role purpose plays in various areas of constitutional analysis over the last half-century, the Court seemingly continues to muddy the waters as to purpose’s proper place in Establishment Clause cases. This Comment focuses on the function and operation of purpose in Establishment Clause cases in order to probe the complications and obstacles inherent to this area of constitutional law. By constructing and applying an analytical framework that examines modern Establishment Clause cases through the lenses of “conceptions of purpose,” “evidence of purpose,” and “indicia of impermissible purpose,” this Comment provides critical takeaways about the development and current state of the Establishment Clause—as well as potential future outcomes in these cases. Ultimately, the dispositive consideration in Establishment Clause cases is the utilization and weight given by individual Justices in any given case to the factors discussed in this Comment’s analytical framework. This conclusion demonstrates the judge-dependent nature of these cases and the value certain Justices place on the institutional legitimacy of the Supreme Court and the judicial branch as a whole.
VCNet and Functional Targeted Regularization For Learning Causal Effects of Continuous Treatments.

Motivated by the rising abundance of observational data with continuous treatments, we investigate the problem of estimating the average dose-response curve (ADRF). Available parametric methods are limited in their model space, and previous attempts in leveraging neural network to enhance model expressiveness relied on partitioning continuous treatment into blocks and using separate heads for each block; this however produces in practice discontinuous ADRFs. Therefore, the question of how to adapt the structure and training of neural network to estimate ADRFs remains open. This paper makes two important contributions. First, we propose a novel varying coefficient neural network (VCNet) that improves model expressiveness while preserving continuity of the estimated ADRF. Second, to improve finite sample performance, we generalize targeted regularization to obtain a doubly robust estimator of the whole ADRF curve.
Affordable Care Act Medicaid expansions and the nurse labor market

Shortages in healthcare labor markets were a major concern voiced by critics of the 2010 Patient Protection and Affordable Care Act. Using a difference-in-differences strategy, I find the 2014 Medicaid expansions increased the average workweek by 30 minutes for registered nurses and 50 minutes for licensed practical nurses, driven by an increase in full-time work. Registered nurses and licensed practical nurses were 3 and 5 percentage points, respectively, more likely to work full-time due to the Medicaid expansions. Effects are larger in the long-term care, home healthcare, and social services sector and in rural areas where the expansions likely had the largest impact on utilization. I do not find effects on nurse labor supply, suggesting the expansion of Medicaid led to a small increase in demand for nurses.
Charged lepton flavor violation at the EIC

We present a comprehensive analysis of the potential sensitivity of the Electron-Ion Collider (EIC) to charged lepton flavor violation (CLFV) in the channel ep → τX, within the model-independent framework of the Standard Model Effective Field Theory (SMEFT). We compute the relevant cross sections to leading order in QCD and electroweak corrections and perform simulations of signal and SM background events in various τ decay channels, suggesting simple cuts to enhance the associated estimated efficiencies. To assess the discovery potential of the EIC in τ-e transitions, we study the sensitivity of other probes of this physics across a broad range of energy scales, from pp → eτX at the Large Hadron Collider to decays of B mesons and τ leptons, such as τ → eγ, τ → el+l−, and crucially the hadronic modes τ → eY with Y ∈ {π, K, ππ, Kπ, …}. We find that electroweak dipole and four-fermion semi-leptonic operators involving light quarks are already strongly constrained by τ decays, while operators involving the c and b quarks present more promising discovery potential for the EIC. An analysis of three models of leptoquarks confirms the expectations based on the SMEFT results. We also identify future directions needed to maximize the reach of the EIC in CLFV searches: these include an optimization of the τ tagger in hadronic channels, an exploration of background suppression through tagging b and c jets in the final state, and a global fit by turning on all SMEFT couplings, which will likely reveal new discovery windows for the EIC.
Inequality and giving

Abstract In a laboratory experiment, we incentivize participants to make donations to a real-world charity. By randomizing the income distribution, we identify a causal effect of inequality on giving behavior. On both the intensive and extensive margins, donations fall when inequality is higher. Our results conflict with theories that predict greater inequality increases charitable giving, but are consistent with other empirical evidence that charitable giving is lower when inequality increases. We present a model where the income distribution directly affects the marginal utility of charitable giving, making a negative inequality-giving relationship possible.
Exploration of characteristic temperature contributions to metallic glass forming ability

author Various combinations of characteristic temperatures, such as the glass transition temperature, liquidus temperature, and crystallization temperature, have been proposed as predictions of the glass forming ability of metal alloys. We have used statistical approaches from machine learning to systematically explore a wide range of possible characteristic temperature functions for predicting glass forming ability in the form of critical casting diameter, D max . Both linear and non-linear models were used to learn on the largest database of D max values to date consisting of 747 compositions. We find that no combination of temperatures for features offers a better prediction of D max in a machine learning model than the temperatures themselves, and that regression models suffer from poor performance on standard machine learning metrics like root mean square error (minimum value of 3.3 ± 0.1 mm for data with a standard deviation of 4.8 mm). Examination of the errors vs. database size suggest that a larger database may improve results, although a database significantly larger than that used here would likely be required. Shifting a focus from regression to categorization models learning from characteristic temperatures can be used to weakly distinguish glasses likely to be above vs. below our database’s median D max value of 4.0 mm, with a mean F1 score of 0.77 ± 0.02 for this categorization. The overall weak results on predicting D max suggests that critical cooling rate might be a better target for machine learning model prediction.
Deference or Abdication: A Comparison of the Supreme Courts of Israel and the United States in Cases Involving Real or Perceived Threats to National Security

The Supreme Courts of Israel and the United States treat cases involving national security radically differently, or so it appears on the surface. The fact that the two courts make very different use of justiciability doctrines dramatically affects their willingness to decide "war on terrorism" cases that challenge aspects of national security programs as violative of individual rights. On the surface, the approaches of the two courts thus appear to be radically different, and indeed they are, at least with respect to their willingness to hear and decide cases in "real time" and in terms of their willingness to embrace and apply justiciability doctrines to cases involving national security. However, a more probing analysis of actual decisions and their impact on coordinate branches of government reveals surprising similarities. This Article compares the United States and Israeli Supreme Courts' very different use of justiciability doctrines and then moves beyond those doctrines to explore the impact of actual decisions on policies undertaken in the name of national security. Part II describes the articulated philosophies of the two courts regarding the role of judicial review in cases involving national security. This part explores three justiciability doctrines -- the political question doctrine, standing requirements, and the state secrets privilege -- and compares the two courts' declared positions with respect to those doctrines in cases dealing with foreign affairs. It also analyzes the two courts' articulated philosophies regarding the scope of judicial review in cases implicating military decisions. Part III of the article moves away from the courts' rhetorical stances on questions of justiciability and judicial review and examines and compares decisions of the two courts in cases that pit national security against individual liberties. This part looks at cases challenging practices including targeted killings, torture, administrative detention, and other actions undertaken in the name of national security. Part IV concludes that (a) the two courts have the institutional capability to resolve challenges to national security policies; (b) adherence to non-justiciability doctrines like the political question doctrine amounts to an abdication of the judicial role; and (c) the availability of judicial review has an actual effect on governmental policy and military practice.
Feature Detection and Curve Fitting Using Fast Walsh Transforms for Shock Tracking: Applications

Walsh functions form an orthonormal basis set consisting of square waves. Square waves make the system well suited for detecting and representing functions with discontinuities. Given a uniform distribution of 2p cells on a one-dimensional element, it has been proven that the inner product of the Walsh Root function for group p with every polynomial of degree < or = (p - 1) across the element is identically zero. It has also been proven that the magnitude and location of a discontinuous jump, as represented by a Heaviside function, are explicitly identified by its Fast Walsh Transform (FWT) coefficients. These two proofs enable an algorithm that quickly provides a Weighted Least Squares fit to distributions across the element that include a discontinuity. The detection of a discontinuity enables analytic relations to locally describe its evolution and provide increased accuracy. Time accurate examples are provided for advection, Burgers equation, and Riemann problems (diaphragm burst) in closed tubes and de Laval nozzles. New algorithms to detect up to two C0 and/or C1 discontinuities within a single element are developed for application to the Riemann problem, in which a contact discontinuity and shock wave form after the diaphragm bursts.
Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering

Many Question-Answering (QA) datasets contain unanswerable questions, but their treatment in QA systems remains primitive. Our analysis of the Natural Questions (Kwiatkowski et al. 2019) dataset reveals that a substantial portion of unanswerable questions (~21%) can be explained based on the presence of unverifiable presuppositions. Through a user preference study, we demonstrate that the oracle behavior of our proposed system—which provides responses based on presupposition failure—is preferred over the oracle behavior of existing QA systems. Then, we present a novel framework for implementing such a system in three steps: presupposition generation, presupposition verification, and explanation generation, reporting progress on each. Finally, we show that a simple modification of adding presuppositions and their verifiability to the input of a competitive end-to-end QA system yields modest gains in QA performance and unanswerability detection, demonstrating the promise of our approach.
Snapshot-free, transparent, and robust memory reclamation for lock-free data structures

We present a family of safe memory reclamation schemes, Hyaline, which are fast, scalable, and transparent to the underlying lock-free data structures. Hyaline is based on reference counting -- considered impractical for memory reclamation in the past due to high overheads. Hyaline uses reference counters only during reclamation, but not while accessing individual objects, which reduces overheads for object accesses. Since with reference counters, an arbitrary thread ends up freeing memory, Hyaline's reclamation workload is (almost) balanced across all threads, unlike most prior reclamation schemes such as epoch-based reclamation (EBR) or hazard pointers (HP). Hyaline often yields (excellent) EBR-grade performance with (good) HP-grade memory efficiency, which is a challenging trade-off with all existing schemes. Hyaline schemes offer: (i) high performance; (ii) good memory efficiency; (iii) robustness: bounding memory usage even in the presence of stalled threads, a well-known problem with EBR; (iv) transparency: supporting virtually unbounded number of threads (or concurrent entities) that can be created and deleted dynamically, and effortlessly join existent workload; (v) autonomy: avoiding special OS mechanisms and being non-intrusive to runtime or compiler environments; (vi) simplicity: enabling easy integration into unmanaged C/C++ code; and (vii) generality: supporting many data structures. All existing schemes lack one or more properties. We have implemented and tested Hyaline on x86(-64), ARM32/64, PowerPC, and MIPS. The general approach requires LL/SC or double-width CAS, while a specialized version also works with single-width CAS. Our evaluation reveals that Hyaline's throughput is very high -- it steadily outperforms EBR by 10% in one test and yields 2x gains in oversubscribed scenarios. Hyaline's superior memory efficiency is especially evident in read-dominated workloads.
Constitutional Courts and Consolidated Power

Many new democracies exhibit a disturbing lack of electoral competition. All too often, the first party to hold office creates a network of power and patronage that chokes off meaningful political challenge. These strong party democracies, with power often being held by the inheritors of the political mantle of those that led the opposition to prior authoritarian rule, exhibit a tendency toward the three “C’s” of associated with the lack of accountability: clientelism, cronyism, and corruption. Such strong-party regimes and their associated pathologies present relatively new constitutional courts with a distinct set of controversies that necessarily bring the judiciary into conflict with consolidating political power. This article explores the form that judicial responses to the excesses of political dominance might take. Three courts are selected as exemplars of such responses. In the first instance, the Colombian Constitutional Court repudiated the attempt of President Uribe to * Reiss Professor of Constitutional Law, NYU School of Law. amend the constitution to permit a third term in office, despite the lack of reasoning to support the rejection of a largely procedurally proper constitutional amendment. In the second, the South African Constitutional Court has scrupulously avoided any frontal confrontation with the current African National Congress government, instead casting its repeated rejection of government efforts to insulate itself from accountability in narrow procedural rulings or in rulings based on other, non-politically charged sources of law. Finally, there is the Thai Constitutional Court which, while providing the strongest jurisprudential defense of its intervention, appears an active ally of one partisan camp as the country hovers on the brink of civil
Methodology to simulate parasitic reflection and birefringence in optical pickup units and sensors

ABSTRACT A novel technique is presented for the computation of the polarization transfer function of optical assemblies with finite reflection coefficients, birefringence, and other parasitic imperfections. The methodology is directly applicable to optical data storage modeling, such as CD/DVD recording optics and the physical recording process. Keywords: Optical data storage, optical system design 1. Introduction Jones calculus [1] is a powerful tool for the modeling of optical assemblies of all types and has been particularly useful for the modeling of the optical pickup unit (OPU) in optical data storage drives [2] and optical sensors [3]. For this type of calculation, Jones matrices, which represent the optical elements, are matrix-multiplied to represent the overall optical train in a unidirectional manner. Bidirectional propagation is often handled by unfolding the optical train, i.e. topologically mapping a bidirectional problem into a unidirectional, albeit less compact problem. However, the transfer-matrix approach has limitations when solving for optical systems that have re-entrant (loop) topologies. This would include optical systems with closely packed optical elements having less than perfect antireflection coatings such as an OPU. In the case of interferometers, and optical systems with partially coherent light in general, finite reflections along with the forward and backwards propagation make all but the simplest systems challenging to reduce to tractable equations. In this paper, a methodology is introduced which is a powerful technique that permits the straightforward calculation of the polarization transfer function including the recursive mathematics that arise from the physics of multiple reflections. Although this is a generally applicable tool, is most valuable to provide a means to do tradeoff analyses for realistic components. For cost reduction, molded-optics without AR coatings may be employed in low cost OPUs, which increases the need to understand how parasitic effects will manifest themselves. Evaluation of system sensitivity to thickness, reflectivity, and birefringence variations in the media, as a function of OPU component and assembly tolerances may also be performed in a straightforward manner.
Neurexin1α Differentially Regulates Synaptic Efficacy within Striatal Circuits

Mutations in genes essential for shared aspects of synaptic function throughout the CNS, such as the presynaptic adhesion molecule Neurexin1α (Nrxn1α), are strongly implicated in neuropsychiatric pathophysiology. As the input nucleus of the basal ganglia, the striatum integrates diverse excitatory projections governing cognitive and motor control, and its functional impairment underlies neuropsychiatric disorders. While prior work has emphasized Neurexins’ contributions to synaptic transmission in hippocampus and brainstem, their function in striatal circuits remains unstudied. As Nrxn1α is highly expressed at striatal inputs, we employed optogenetic-mediated afferent recruitment of dorsal prefrontal cortex-dorsomedial striatal (DMS) connections, uncovering a decrease in net synaptic strength specifically onto indirect pathway spiny neurons in both Nrxn1α+/- and Nrxn1α-/- mice, driven by reductions in transmitter release probability. In contrast, thalamic excitatory inputs to DMS demonstrated relatively normal excitatory synaptic strength. These findings suggest that dysregulation of Nrxn1α modulates striatal function in an input and target-specific manner.
Interaction of micropatterned topographical and biochemical cues to direct neurite growth from spiral ganglion neurons.

Abstract Functional outcomes with neural prosthetic devices, such as cochlear implants, are limited in part due to physical separation between the stimulating elements and the neurons they stimulate. One strategy to close this gap aims to precisely guide neurite regeneration to position the neurites in closer proximity to electrode arrays. Here, we explore the ability of micropatterned biochemical and topographic guidance cues, singly and in combination, to direct the growth of spiral ganglion neuron (SGN) neurites, the neurons targeted by cochlear implants. Photopolymerization of methacrylate monomers was used to form unidirectional topographical features of ridges and grooves in addition to multidirectional patterns with 90o angle turns. Microcontact printing was also used to create similar uni- and multi-directional patterns of peptides on polymer surfaces. Biochemical cues included peptides that facilitate (laminin, LN) or repel (EphA4-Fc) neurite growth. On flat surfaces, SGN neurites preferentially grew on LN-coated stripes and avoided EphA4-Fc-coated stripes. LN or EphA4-Fc was selectively adsorbed onto the ridges or grooves to test the neurite response to a combination of topographical and biochemical cues. Coating the ridges with EphA4-Fc and grooves with LN lead to enhanced SGN alignment to topographical patterns. Conversely, EphA4-Fc coating on the grooves or LN coating on the ridges tended to disrupt alignment to topographical patterns. SGN neurites respond to combinations of topographical and biochemical cues and surface patterning that leverages both cues enhance guided neurite growth.
Regularity of a transmission problem and periodic homogenization

Abstract This paper is concerned with the regularity theory of a transmission problem arising in composite materials. We give a new self-contained proof for the C k , α estimates on both sides of the interface under the minimal assumptions on the interface and data. Moreover, we prove the uniform Lipschitz estimate across a C 1 , α interface when the coefficients on both sides of the interface are periodic with independent structures and oscillating at different microscopic scales. The proofs rely on the notion of “piecewise linear solutions” which captures the essential structure of the transmission problem.
Stable characters from permutation patterns

For a fixed permutation σ∈Sk, let Nσ denote the function which counts occurrences of σ as a pattern in permutations from Sn. We study the expected value (and dth moments) of Nσ on conjugacy classes of Sn and prove that the irreducible character support of these class functions stabilizes as n grows. This says that there is a single polynomial in the variables n,m1,…,mdk which computes these moments on any conjugacy class (of cycle type 1m12m2⋯) of any symmetric group. This result generalizes results of Hultman (Adv Appl Math 54:1–10, 2014) and of Gill (The k-assignment polytope, phylogenetic trees, and permutation patterns, Ph.D. Thesis at Linkoping University, pp 103–125, 2013), who proved the cases (d,k)=(1,2) and (1, 3) using ad hoc methods. Our proof is, to our knowledge, the first application of partition algebras to the study of permutation patterns.
The Party Structure of Mutual Funds

We investigate the structure of mutual funds’ corporate governance preferences as revealed by how they vote their shares in portfolio companies. We apply unsupervised learning tools from the machine learning literature to analyze a comprehensive dataset of mutual funds’ votes and find that a parsimonious two-dimensional model can explain the bulk of mutual fund voting. The two dimensions capture competing visions of corporate governance and are closely related to the recommendations of the leading proxy advisors. Model-based cluster analysis shows that mutual funds are organized into three ‘parties’—the Traditional Governance Party, the Shareholder Reform Party, and the Shareholder Protest Party—that follow distinctive philosophies of corporate governance and shareholders’ role. Our preference measures for mutual funds generate a range of insights about the broader system of corporate governance.
Envisioning Communities: A Participatory Approach Towards AI for Social Good

Research in artificial intelligence (AI) for social good presupposes some definition of social good, but potential definitions have been seldom suggested and never agreed upon. The normative question of what AI for social good research should be "for" is not thoughtfully elaborated, or is frequently addressed with a utilitarian outlook that prioritizes the needs of the majority over those who have been historically marginalized, brushing aside realities of injustice and inequity. We argue that AI for social good ought to be assessed by the communities that the AI system will impact, using as a guide the capabilities approach, a framework to measure the ability of different policies to improve human welfare equity. Furthermore, we lay out how AI research has the potential to catalyze social progress by expanding and equalizing capabilities. We show how the capabilities approach aligns with a participatory approach for the design and implementation of AI for social good research in a framework we introduce called PACT, in which community members affected should be brought in as partners and their input prioritized throughout the project. We conclude by providing an incomplete set of guiding questions for carrying out such participatory AI research in a way that elicits and respects a community's own definition of social good.
Meissner-London Susceptibility of Superconducting Right Circular Cylinders in an Axial Magnetic Field

Analysis of magnetic susceptibility of nonellipsoidal samples is a long-standing problem in experimental studies of magnetism and superconductivity. Here the quantitative description of the Meissner-London response (no Abrikosov vortices) of right circular cylinders in an axial magnetic field is given. Three-dimensional adaptive finite-element modeling is used to calculate the total magnetic moment ($m$) in a wide range of London penetration depth ($\ensuremath{\lambda}$) to sample size ($a$) ratios, $\ensuremath{\lambda}/a$. By fitting numerical solutions, the closed-form empirical magnetic susceptibility is obtained involving only sample dimensions and $\ensuremath{\lambda}$, thus providing a recipe for determining the London penetration depth from the precision measurements of the magnetic susceptibility. Detailed protocols of the experimental data analysis using the developed approach are given. The results can be readily extended to the most frequently used cuboid-shaped samples.
Social Media Polarization and Echo Chambers in the Context of COVID-19: Case Study.

Background Social media chatter in 2020 has been largely dominated by the COVID-19 pandemic. Existing research shows that COVID-19 discourse is highly politicized, with political preferences linked to beliefs and disbeliefs about the virus. As it happens with topics that become politicized, people may fall into echo chambers, which is the idea that one is only presented with information they already agree with, thereby reinforcing one's confirmation bias. Understanding the relationship between information dissemination and political preference is crucial for effective public health communication. Objective We aimed to study the extent of polarization and examine the structure of echo chambers related to COVID-19 discourse on Twitter in the United States. Methods First, we presented Retweet-BERT, a scalable and highly accurate model for estimating user polarity by leveraging language features and network structures. Then, by analyzing the user polarity predicted by Retweet-BERT, we provided new insights into the characterization of partisan users. Results We observed that right-leaning users were noticeably more vocal and active in the production and consumption of COVID-19 information. We also found that most of the highly influential users were partisan, which may contribute to further polarization. Importantly, while echo chambers exist in both the right- and left-leaning communities, the right-leaning community was by far more densely connected within their echo chamber and isolated from the rest. Conclusions We provided empirical evidence that political echo chambers are prevalent, especially in the right-leaning community, which can exacerbate the exposure to information in line with pre-existing users' views. Our findings have broader implications in developing effective public health campaigns and promoting the circulation of factual information online.
A unique GCN5 histone acetyltransferase complex controls erythrocyte invasion and virulence in the malaria parasite Plasmodium falciparum

The histone acetyltransferase GCN5-associated SAGA complex is evolutionarily conserved from yeast to human and functions as a general transcription co-activator in global gene regulation. In this study, we identified a divergent GCN5 complex in Plasmodium falciparum, which contains two plant homeodomain (PHD) proteins (PfPHD1 and PfPHD2) and a plant apetela2 (AP2)-domain transcription factor (PfAP2-LT). To dissect the functions of the PfGCN5 complex, we generated parasite lines with either the bromodomain in PfGCN5 or the PHD domain in PfPHD1 deleted. The two deletion mutants closely phenocopied each other, exhibiting significantly reduced merozoite invasion of erythrocytes and elevated sexual conversion. These domain deletions caused dramatic decreases not only in histone H3K9 acetylation but also in H3K4 trimethylation, indicating synergistic crosstalk between the two euchromatin marks. Domain deletion in either PfGCN5 or PfPHD1 profoundly disturbed the global transcription pattern, causing altered expression of more than 60% of the genes. At the schizont stage, these domain deletions were linked to specific down-regulation of merozoite genes involved in erythrocyte invasion, many of which contain the AP2-LT binding motif and are also regulated by AP2-I and BDP1, suggesting targeted recruitment of the PfGCN5 complex to the invasion genes by these specific factors. Conversely, at the ring stage, PfGCN5 or PfPHD1 domain deletions disrupted the mutually exclusive expression pattern of the entire var gene family, which encodes the virulent factor PfEMP1. Correlation analysis between the chromatin state and alteration of gene expression demonstrated that up- and down-regulated genes in these mutants are highly correlated with the silent and active chromatin states in the wild-type parasite, respectively. Collectively, the PfGCN5 complex represents a novel HAT complex with a unique subunit composition including an AP2 transcription factor, which signifies a new paradigm for targeting the co-activator complex to regulate general and parasite-specific cellular processes in this low-branching parasitic protist.
Automatic Server to Circuit Mapping with The Red Pills

As fine grained power monitoring becomes crucial in data centers, a challenge raises on how to correctly map server identities to power circuits. Power provisioning, power capping, and power tracking all depend on accurately accounting which server consumes power from which circuit. Manual survey is cumbersome and error prone. We describe a solution, called Red Pill, that can systematically and automatically identify the mapping. The idea is to generate a power consumption pattern (a.k.a. a signature) by controlling CPU utilization, and to reliably detect it from circuit-level power measurements. We describe our implementation of the Red Pill system and evaluate it with real data traces
Jamming and arrest of cell motion in biological tissues.

Abstract Collective cell motility is crucial to many biological processes including morphogenesis, wound healing, and cancer invasion. Recently, the biology and biophysics communities have begun to use the term ‘cell jamming’ to describe the collective arrest of cell motion in tissues. Although this term is widely used, the underlying mechanisms are varied. In this review, we highlight three independent mechanisms that can potentially drive arrest of cell motion — crowding, tension-driven rigidity, and reduction of fluctuations — and propose a framework that connects all three. Because multiple mechanisms may be operating simultaneously, this emphasizes that experiments should strive to identify which mechanism dominates in a given situation. We also discuss how specific cell-scale and molecular-scale biological processes, such as cell–cell and cell-substrate interactions, control aspects of these underlying physical mechanisms.
Ultra-low memory seismic inversion with randomized trace estimation

Inspired by recent work on extended image volumes that lays the ground for randomized probing of extremely large seismic wavefield matrices, we present a memory frugal and computationally efficient inversion methodology that uses techniques from randomized linear algebra. By means of a carefully selected realistic synthetic example, we demonstrate that we are capable of achieving competitive inversion results at a fraction of the memory cost of conventional full-waveform inversion with limited computational overhead. By exchanging memory for negligible computational overhead, we open with the presented technology the door towards the use of low-memory accelerators such as GPUs.
Spin networks and anyonic topological computing II

We review the q-deformed spin network approach to Topological Quantum Field Theory and apply these methods to produce unitary representations of the braid groups that are dense in the unitary groups. The simplest case of these models is the Fibonacci model, itself universal for quantum computation. We here formulate these braid group representations in a form suitable for computation and algebraic work.
Distributed Gradient Flow: Nonsmoothness, Nonconvexity, and Saddle Point Evasion

The paper considers distributed gradient flow (DGF) for multi-agent nonconvex optimization. DGF is a continuous-time approximation of distributed gradient descent that is often easier to study than its discrete-time counterpart. The paper has two main contributions. First, the paper considers optimization of nonsmooth, nonconvex objective functions. It is shown that DGF converges to critical points in this setting. The paper then considers the problem of avoiding saddle points. It is shown that if agents' objective functions are assumed to be smooth and nonconvex, then DGF can only converge to a saddle point from a zero-measure set of initial conditions. To establish this result, the paper proves a stable manifold theorem for DGF, which is a fundamental contribution of independent interest. In a companion paper, analogous results are derived for discrete-time algorithms.
A Simple Framework for 3D Lensless Imaging with Programmable Masks

Author(s): Zheng, Yucheng; Hua, Yi; Sankaranarayanan, Aswin C; Asif, M Salman | Abstract: Lensless cameras provide a framework to build thin imaging systems by replacing the lens in a conventional camera with an amplitude or phase mask near the sensor. Existing methods for lensless imaging can recover the depth and intensity of the scene, but they require solving computationally-expensive inverse problems. Furthermore, existing methods struggle to recover dense scenes with large depth variations. In this paper, we propose a lensless imaging system that captures a small number of measurements using different patterns on a programmable mask. In this context, we make three contributions. First, we present a fast recovery algorithm to recover textures on a fixed number of depth planes in the scene. Second, we consider the mask design problem, for programmable lensless cameras, and provide a design template for optimizing the mask patterns with the goal of improving depth estimation. Third, we use a refinement network as a post-processing step to identify and remove artifacts in the reconstruction. These modifications are evaluated extensively with experimental results on a lensless camera prototype to showcase the performance benefits of the optimized masks and recovery algorithms over the state of the art.
The Graphs of Stably Matchable Pairs

We study the graphs formed from instances of the stable matching problem by connecting pairs of elements with an edge when there exists a stable matching in which they are matched. Our results include the NP-completeness of recognizing these graphs, a recognition algorithm that is singly exponential in the number of edges of the given graph, and an algorithm whose time is linear in the number of vertices of the graph but exponential in a polynomial of its carving width.
On a Characterization of Convergence in Banach Spaces with a Schauder Basis

“The method in the present paper is abstract and is phrased in terms of Banach spaces, linear operators, and so on. This has the advantage of greater simplicity in proof and greater generality in applications.” Jacob T. Schwartz
Attacks on Visualization-Based Malware Detection: Balancing Effectiveness and Executability.

With the rapid development of machine learning for image classification, researchers have found new applications of visualization techniques in malware detection. By converting binary code into images, researchers have shown satisfactory results in applying machine learning to extract features that are difficult to discover manually. Such visualization-based malware detection methods can capture malware patterns from many different malware families and improve malware detection speed. On the other hand, recent research has also shown adversarial attacks against such visualization-based malware detection. Attackers can generate adversarial examples by perturbing the malware binary in non-reachable regions, such as padding at the end of the binary. Alternatively, attackers can perturb the malware image embedding and then verify the executability of the malware post-transformation. One major limitation of the first attack scenario is that a simple pre-processing step can remove the perturbations before classification. For the second attack scenario, it is hard to maintain the original malware’s executability and functionality. In this work, we provide literature review on existing malware visualization techniques and attacks against them. We summarize the limitation of the previous work, and design a new adversarial example attack against visualization-based malware detection that can evade pre-processing filtering and maintain the original malware functionality. We test our attack on a public malware dataset and achieve a 98% success rate.
Social Influence Leads to the Formation of Diverse Local Trends

How does the visual design of digital platforms impact user behavior and the resulting environment? A body of work suggests that introducing social signals to content can increase both the inequality and unpredictability of its success, but has only been shown in the context of music listening. To further examine the effect of social influence on media popularity, we extend this research to the context of algorithmically-generated images by re-adapting Salganik et al's Music Lab experiment. On a digital platform where participants discover and curate AI-generated hybrid animals, we randomly assign both the knowledge of other participants' behavior and the visual presentation of the information. We successfully replicate the Music Lab's findings in the context of images, whereby social influence leads to an unpredictable winner-take-all market. However, we also find that social influence can lead to the emergence of local cultural trends that diverge from the status quo and are ultimately more diverse. We discuss the implications of these results for platform designers and animal conservation efforts.
Neutron detection efficiency of the Neutron dEtector with Xn Tracking (NEXT)

Abstract An efficient neutron detection system with good energy resolution is required to correctly characterize decays of neutron-rich nuclei where β − delayed neutron emission is a dominant decay mode. The Neutron dEtector with Xn Tracking (NEXT) has been designed to measure β -delayed neutron emitters. By segmenting the detector along the neutron flight path, NEXT reduces the associated uncertainties in neutron time-of-flight measurements, improving energy resolution while maintaining detection efficiency. Detector prototypes are comprised of optically separated segments of a neutron-gamma discriminating plastic scintillator coupled to position-sensitive photomultiplier tubes. The first performance studies of this detector showed that high intrinsic neutron detection efficiency could be achieved while retaining good energy resolution. The results from the efficiency measurements using neutrons from direct reactions are presented.