cssi/SciSciGPT-SciSciNet huggingface dataset:
Time-to-surgery and overall survival after breast cancer diagnosis in a universal health system.

It is unclear whether time between breast cancer diagnosis and surgery is associated with survival and whether this relationship is affected by access to care. We evaluated the association between time-to-surgery and overall survival among women in the universal-access U.S. Military Health System (MHS). Women aged 18–79 who received surgical treatment for stages I–III breast cancer between 1998 and 2010 were identified in linked cancer registry and administrative databases with follow-up through 2015. Multivariable Cox regression models were used to estimate risk of all-cause death associated with time-to-surgery intervals. The study included 9669 women with 93.1% survival during the study period. The hazards ratios (95% confidence intervals) of all-cause death associated with time-to-surgery were 1.15 (0.93, 1.42) for 0 days, 1.00 (reference) for 1–21 days, 0.97 (0.78, 1.21) for 22–35 days, and 1.30 (1.04, 1.61) for ≥ 36 days. The higher risk of mortality associated with time-to-surgery ≥ 36 days tended to be consistent when analyzed by surgery type, age at diagnosis, and tumor stage. In the MHS, longer time-to-surgery for breast cancer was associated with poorer overall survival, suggesting the importance of timeliness in receiving surgical treatment for breast cancer in relation to overall survival.
Large Genus Asymptotics for Siegel–Veech Constants

In this paper we consider the large genus asymptotics for two classes of Siegel–Veech constants associated with an arbitrary connected stratum $$\mathcal {H} (\alpha )$$ of Abelian differentials. The first is the saddle connection Siegel–Veech constant $$c_{\mathrm{sc}}^{m_i, m_j} \big ( \mathcal {H} (\alpha ) \big )$$ counting saddle connections between two distinct, fixed zeros of prescribed orders $$m_i$$ and $$m_j$$ , and the second is the area Siegel–Veech constant $$c_{\mathrm{area}} \big ( \mathcal {H}(\alpha ) \big )$$ counting maximal cylinders weighted by area. By combining a combinatorial analysis of explicit formulas of Eskin–Masur–Zorich that express these constants in terms of Masur–Veech strata volumes, with a recent result for the large genus asymptotics of these volumes, we show that $$c_{\mathrm{sc}}^{m_i, m_j} \big ( \mathcal {H} (\alpha ) \big ) = (m_i + 1) (m_j + 1) \big ( 1 + o(1) \big )$$ and $$c_{\mathrm{area}} \big ( \mathcal {H}(\alpha ) \big ) = \frac{1}{2} + o(1)$$ , both as $$|\alpha | = 2g - 2$$ tends to $$\infty $$ . The former result confirms a prediction of Zorich and the latter confirms one of Eskin–Zorich in the case of connected strata.
Disentangling neural mechanisms for perceptual grouping

Forming perceptual groups and individuating objects in visual scenes is an essential step towards visual intelligence. This ability is thought to arise in the brain from computations implemented by bottom-up, horizontal, and top-down connections between neurons. However, the relative contributions of these connections to perceptual grouping are poorly understood. We address this question by systematically evaluating neural network architectures featuring combinations of these connections on two synthetic visual tasks, which stress low-level "Gestalt" vs. high-level object cues for perceptual grouping. We show that increasing the difficulty of either task strains learning for networks that rely solely on bottom-up processing. Horizontal connections resolve this limitation on tasks with Gestalt cues by supporting incremental spatial propagation of activities, whereas top-down connections rescue learning on tasks with high-level object cues by modifying coarse predictions about the position of the target object. Our findings dissociate the computational roles of bottom-up, horizontal and top-down connectivity, and demonstrate how a model featuring all of these interactions can more flexibly learn to form perceptual groups.
Anisotropic Hydrolysis Susceptibility in Deformed Polydimethylsiloxanes.

Chemical reactions involving the polydimethylsiloxane (PDMS) backbone can induce significant network rearrangements and ultimately degrade macro-scale mechanical properties of silicone components. ...
On the Robustness of Information-Theoretic Privacy Measures and Mechanisms

Consider a data publishing setting for a dataset composed by both private and non-private features. The publisher uses an empirical distribution, estimated from $n$ i.i.d. samples, to design a privacy mechanism which is applied to new fresh samples afterward. In this paper, we study the discrepancy between the privacy-utility guarantees for the empirical distribution, used to design the privacy mechanism, and those for the true distribution, experienced by the privacy mechanism in practice. We first show that, for any privacy mechanism, these discrepancies vanish at speed $O(1/\sqrt {n})$ with high probability. These bounds follow from our main technical results regarding the Lipschitz continuity of the considered information leakage measures. Then we prove that the optimal privacy mechanisms for the empirical distribution approach the corresponding mechanisms for the true distribution as the sample size $n$ increases, thereby establishing the statistical consistency of the optimal privacy mechanisms. Finally, we introduce and study uniform privacy mechanisms which, by construction, provide privacy to all the distributions within a neighborhood of the estimated distribution and, thereby, guarantee privacy for the true distribution with high probability.
Finite degree clones are undecidable

Abstract A clone of functions on a finite domain determines and is determined by its system of invariant relations (=predicates). When a clone is determined by a finite number of relations, we say that the clone is of finite degree. For each Minsky machine M we associate a finitely generated clone C such that C has finite degree if and only if M halts, thus proving that deciding whether a given clone has finite degree is impossible.
“What Do Your Friends Think?”: Efficient Polling Methods for Networks Using Friendship Paradox

This paper deals with randomized polling of a social network. In the case of forecasting the outcome of an election between two candidates A and B, classical intent polling asks randomly sampled individuals: who will you vote for? Expectation polling asks: who do you think will win? In this paper, we propose a novel neighborhood expectation polling (NEP) strategy that asks randomly sampled individuals: what is your estimate of the fraction of votes for A? Therefore, in NEP, sampled individuals will naturally look at their neighbors (defined by the underlying social network graph) when answering this question. Hence, the mean squared error (MSE) of NEP methods rely on selecting the optimal set of samples from the network. To this end, we propose two NEP algorithms for the following cases: (i) the social network graph is not known but, random walks (sequential exploration) can be performed on the graph, and (ii) the social network graph is unknown but, uniformly sampled nodes from the network are available. For both cases, algorithms based on a graph theoretic consequence called friendship paradox are proposed. Theoretical results on the dependence of the MSE of the algorithms on the properties of the network are established. Numerical results on real and synthetic data sets are provided to illustrate the performance of the algorithms.
Hydrogen exchange of chemoreceptors in functional complexes suggests protein stabilization mediates long-range allosteric coupling

Bacterial chemotaxis receptors form extended hexagonal arrays that integrate and amplify signals to control swimming behavior. Transmembrane signaling begins with a 2-A ligand-induced displacement of an α helix in the periplasmic and transmembrane domains, but it is unknown how the cytoplasmic domain propagates the signal an additional 200 A to control the kinase CheA bound to the membrane-distal tip of the receptor. The receptor cytoplasmic domain has previously been shown to be highly dynamic as both a cytoplasmic fragment (CF) and within the intact chemoreceptor; modulation of its dynamics is thought to play a key role in signal propagation. This hydrogen deuterium exchange-MS (HDX-MS) study of functional complexes of CF, CheA, and CheW bound to vesicles in native-like arrays reveals that the CF is well-ordered only in its protein interaction region where it binds CheA and CheW. We observe rapid exchange throughout the rest of the CF, with both uncorrelated (EX2) and correlated (EX1) exchange patterns, suggesting the receptor cytoplasmic domain retains disorder even within functional complexes. HDX rates are increased by inputs that favor the kinase-off state. We propose that chemoreceptors achieve long-range allosteric control of the kinase through a coupled equilibrium: CheA binding in a kinase-on conformation stabilizes the cytoplasmic domain, and signaling inputs that destabilize this domain (ligand binding and demethylation) disfavor CheA binding such that it loses key contacts and reverts to a kinase-off state. This study reveals the mechanistic role of an intrinsically disordered region of a transmembrane receptor in long-range allostery.
Joint Models for Time-to-Event Data and Longitudinal Biomarkers of High Dimension

Joint models for longitudinal biomarkers and time-to-event data are widely used in longitudinal studies. Many joint modeling approaches have been proposed to handle different types of longitudinal biomarkers and survival outcomes. However, most existing joint modeling methods cannot deal with a large number of longitudinal biomarkers simultaneously, such as the longitudinally collected gene expression profiles. In this article, we propose a new joint modeling method under the Bayesian framework, which is able to analyze longitudinal biomarkers of high dimension. Specifically, we assume that only a few unobserved latent variables are related to the survival outcome and the latent variables are inferred using a factor analysis model, which greatly reduces the dimensionality of the biomarkers and also accounts for the high correlations among the biomarkers. Through extensive simulation studies, we show that our proposed method has improved prediction accuracy over other joint modeling methods. We illustrate the usefulness of our method on a dataset of idiopathic pulmonary fibrosis patients in which we are interested in predicting the patients' time-to-death using their gene expression profiles.
Stochastic Vertex Corrections: Linear Scaling Methods for Accurate Quasiparticle Energies

New stochastic approaches for the computation of electronic excitations are developed within the many-body perturbation theory. Three approximations to the electronic self-energy are considered: G0W0, G0W0tc, and G0W0tcΓX. All three methods are formulated in the time domain, and the latter two incorporate nonlocal vertex corrections. In the case of G0W0tcΓX, the vertex corrections are included both in the screened Coulomb interaction and in the expression for the self-energy. The implementation of the three approximations is verified by comparison to deterministic results for a set of small molecules. The performance of the fully stochastic implementation is tested on acene molecules, C60 and PC60BM. The vertex correction appears crucial for the description of unoccupied states. Unlike conventional (deterministic) approaches, all three stochastic methods scale linearly with the number of electrons.
On 2-knots and connected sums with projective planes

In this paper, we generalize a result of Satoh to show that for any odd natural n, the connected sum of the n-twist spun sphere of a knot K and an unknotted projective plane in the 4-sphere is equivalent to the same unknotted projective plane. We additionally provide a fix to a small error in Satoh’s proof of the case that K is a 2-bridge knot.
CAMR: Coded Aggregated MapReduce

Many big data algorithms executed on MapReduce-like systems have a shuffle phase that often dominates the overall job execution time. Recent work has demonstrated schemes where the communication load in the shuffle phase can be traded off for the computation load in the map phase. In this work, we focus on a class of distributed algorithms, broadly used in deep learning, where intermediate computations of the same task can be combined. Even though prior techniques reduce the communication load significantly, they require a number of jobs that grows exponentially in the system parameters. This limitation is crucial and may diminish the load gains as the algorithm scales. We propose a new scheme which achieves the same load as the state-of-the-art while ensuring that the number of jobs as well as the number of subfiles that the data set needs to be split into remain small.
Adaptive nonlinear multigrid inversion with applications to Bayesian optical diffusion tomography

We previously proposed a general framework for nonlinear multi-grid inversion applicable to any inverse problem in which the forward model can be naturally represented at differing resolutions. The method has the potential for very large computational savings and robust convergence. In this paper, multigrid inversion is further extended to adaptively allocate computation to the scale at which the algorithm can best reduce the cost. We applied the proposed method to solve the problem of optical diffusion tomography in a Bayesian framework, and our simulation results indicate that the adaptive scheme can improve computational efficiency in this application.
Detecting Kidney Stones Using Twinkling Artifacts: Survey of Kidney Stones with Varying Composition and Size.

Abstract In recent years, work has been done to understand the mechanisms of Doppler ultrasound twinkling artifacts (TAs) and why they appear over kidney stones. In the work described here, twinkling artifacts were evaluated as a possible method of locating and characterizing kidney stones. Doppler ultrasound scanning was used to evaluate 47 stones of different types and sizes in the range 1.31–55.76 mm2 in cross-sectional area (average = 9.65 mm2). An isolated stone study was used to understand the behavior of the TAs. An ex vivo kidney study was conducted to determine if the renal tissue impeded localization of the TAs to the stones. An ex vivo study of randomly placed stones was used to evaluate the robustness of the method for detecting stones that were placed by an independent party. The TAs were found to be qualitatively consistent in appearance across stone types, sizes and scanning parameters in the isolated stone study. Quantitative assessment of TA amplitude for isolated stones was also found to be consistent for each class of stones across multiple days. The TAs were also found to be isolated to the stone when placed in an ex vivo kidney. The study of randomly placed stones revealed that this method could find all 47 stones used in a clinical situation with only two false positives. A few limitations to this method were noted involving accurate sizing of stones and the specificity of characterizing the stones. Further work will be done to overcome limitations by improving the Doppler acquisition and processing code, as well as by evaluating the use of TAs in human studies.
Legal Moralism, Overinclusive Offenses, and the Problem of Wrongfulness Conflation

In the Realm of Criminal Law, Antony Duff seeks to defend the view (termed “legal moralism”) that we should criminalize conduct only if it is wrongful. Skeptics of legal moralism argue that this occurs all the time in supposedly overinclusive offenses whose definitions capture not only the kind of conduct that constitutes the target wrong, but also a wider class of conduct that is not wrongful prior to prohibition. An example is statutory rape. Duff, in response, contends that such offenses need not violate the requirements of legal moralism. Having exploitative sex with juveniles is obviously wrong even prior to its legal regulation (these wrongs are mala in se). But having non-exploitative sex with juveniles is also potentially wrong, inasmuch as it involves a violation of a prohibition that society has decided is justified for instrumental reasons (such wrongs are mala prohibita). While Duff’s analysis offers an ingenious explanation for why offenses like statutory rape need not violate the bare minimum requirements of legal moralism, it simultaneously exposes separate, largely unacknowledged, problems of fair labeling and proportionality. By combining in a single offense wrongs that are primarily malum in se with ones that are primarily malum prohibitum—a process referred to as “wrongfulness conflation”—we risk treating unlike wrongs alike, imposing disproportionate punishments, and blurring offense labels. And such problems occur not just in the context of statutory rape, but also with respect to a host of other supposedly overinclusive offenses, including various forms of sexual assault.
Cooperativity between the 3' untranslated region microRNA binding sites is critical for the virulence of eastern equine encephalitis virus.

Eastern equine encephalitis virus (EEEV), a mosquito-borne RNA virus, is one of the most acutely virulent viruses endemic to the Americas, causing between 30% and 70% mortality in symptomatic human cases. A major factor in the virulence of EEEV is the presence of four binding sites for the hematopoietic cell-specific microRNA, miR-142-3p, in the 3’ untranslated region (3’ UTR) of the virus. Three of the sites are “canonical” with all 7 seed sequence residues complimentary to miR-142-3p while one is “non-canonical” and has a seed sequence mismatch. Interaction of the EEEV genome with miR-142-3p limits virus replication in myeloid cells and suppresses the systemic innate immune response, greatly exacerbating EEEV neurovirulence. The presence of the miRNA binding sequences is also required for efficient EEEV replication in mosquitoes and, therefore, essential for transmission of the virus. In the current studies, we have examined the role of each binding site by point mutagenesis of the seed sequences in all combinations of sites followed by infection of mammalian myeloid cells, mosquito cells and mice. The resulting data indicate that both canonical and non-canonical sites contribute to cell infection and animal virulence, however, surprisingly, all sites are rapidly deleted from EEEV genomes shortly after infection of myeloid cells or mice. Finally, we show that the virulence of a related encephalitis virus, western equine encephalitis virus, is also dependent upon miR-142-3p binding sites.
Adhesion of arbitrary-shaped thin-film microstructures

We develop, implement in a finite element environment, and experimentally validate an approach to model adhesion of a class of arbitrary-shaped thin-film microstructures commonly used in microsystems technology. The modeling approach adopts principles of three-dimensional linear elastic fracture mechanics and extends them to thin-film plate-like microstructures. A companion experimental effort is carried out to measure adhesion energy of polysilicon microcantilevers using interferometry, and then to study the adhesion behavior of a suite of circular and square plates. The finite element approach is validated by comparison with relevant analytical results. It is then applied to the circular and square plate microstructures and good agreement between measurements and predictions is obtained.
Effect of Pressure on Magnetic Structure in Heavy Fermion CeRhIn5

Abstract : The effect of hydrostatic pressure on the in-commensurate antiferromagnetic structure of CeRhIn5 is investigated with neutron diffraction using a He pressure cell. At 3.8 kbar, the staggered magnetic moment is 0.37(4) micro-B per Ce at 1.6 K, which is the same as the ambient-pressure value. The Neel temperature TN = 3.8(1) K is also the same as the ambient-pressure one, although the curve of order parameter has changed by pressure. The incommensurability delta of the magnetic wave vector qM = (1/2,1/2, delta) has reduced from delta = 0.297 at ambient pressure to delta = 0.294(1) at 3.8 kbar.
Single cell census of human kidney organoids shows reproducibility and diminished off-target cells after transplantation.

Human iPSC-derived kidney organoids have the potential to revolutionize discovery, but assessing their consistency and reproducibility across iPSC lines, and reducing the generation of off-target cells remain an open challenge. Here, we profile four human iPSC lines for a total of 450,118 single cells to show how organoid composition and development are comparable to human fetal and adult kidneys. Although cell classes are largely reproducible across time points, protocols, and replicates, we detect variability in cell proportions between different iPSC lines, largely due to off-target cells. To address this, we analyze organoids transplanted under the mouse kidney capsule and find diminished off-target cells. Our work shows how single cell RNA-seq (scRNA-seq) can score organoids for reproducibility, faithfulness and quality, that kidney organoids derived from different iPSC lines are comparable surrogates for human kidney, and that transplantation enhances their formation by diminishing off-target cells. How reproducible human kidney organoids derived from different iPSC lines are, and how faithful they are to human kidney tissue remain unclear. Here, the authors use four human iPSC lines to derive kidney organoids and show how organoid composition is reproducible, comparable to human tissue and of improved quality after transplantation.
In-Place Zero-Space Memory Protection for CNN

Convolutional Neural Networks (CNN) are being actively explored for safety-critical applications such as autonomous vehicles and aerospace, where it is essential to ensure the reliability of inference results in the presence of possible memory faults. Traditional methods such as error correction codes (ECC) and Triple Modular Redundancy (TMR) are CNN-oblivious and incur substantial memory overhead and energy cost. This paper introduces in-place zero-space ECC assisted with a new training scheme weight distribution-oriented training. The new method provides the first known zero space cost memory protection for CNNs without compromising the reliability offered by traditional ECC.
On the Traffic Impacts of Optimally Controlled Connected and Automated Vehicles

The implementation of connected and automated vehicle (CAV) technologies enables a novel computational framework for real-time control actions aimed at optimizing energy consumption and associated benefits. Several research efforts reported in the literature to date have proposed decentralized control algorithms to coordinate CAVs in various traffic scenarios, e.g., highway on-ramps, intersections, and roundabouts. However, the impact of optimally coordinating CAVs on the performance of a transportation network has not been thoroughly analyzed yet. In this paper, we apply a decentralized optimal control framework in a transportation network and compare its performance to a baseline scenario consisting of human-driven vehicles. We show that introducing of CAVs yields radically improved roadway capacity and network performance.
Three Faces of Restitution

During the first half of the 20th century, three mainstays of the required first-year law school curriculum were Contracts, Torts, and Restitution. Today Restitution has disappeared as a separate course and is offered, if at all, only as part of an optional Remedies course. This disappearance is particularly ironic to Michiganders, as the two leading mid-20th-century Restitution scholars were from our state. The purpose of this paper is to re-introduce Restitution by illustrating three of its principal advantages: as an alternative to Tort remedies, as an alternative to Contract remedies, and as a remedy in cases where neither body of law provides relief. It has been said, “The lawyer who doesn’t know remedies is like a physician without a cure.” To provide complete relief, lawyers need to know the benefits of Restitution. Welcome to a look into three faces of Restitution.
Implementation of Bayesian multiple comparison correction in the second-level analysis of fMRI data: With pilot analyses of simulation and real fMRI datasets based on voxelwise inference

We developed and tested the Bayesian multiple comparison correction method for Bayesian voxelwise second-level fMRI analysis with R. The performance of the developed method was tested with simulation and real image datasets. First, we compared false alarm and hit rates, which were used as proxies for selectivity and sensitivity, respectively, between Bayesian and classical inference methods. For the comparison, we created simulated images, added noise to the created images, and analyzed the noise-added images while applying Bayesian and classical multiple comparison correction methods. Second, we analyzed five real image datasets to examine how our Bayesian method worked in realistic settings. When the performance assessment was conducted, the Bayesian correction method demonstrated good sensitivity (hit rate ≥ 75%) and acceptable selectivity (false alarm rate < 10%) when N ≥ 8. Furthermore, the Bayesian correction method showed better sensitivity compared with the classical correction method while maintaining the aforementioned acceptable selectivity.
CaSpER identifies and visualizes CNV events by integrative analysis of single-cell or bulk RNA-sequencing data.

RNA sequencing experiments generate large amounts of information about expression levels of genes. Although they are mainly used for quantifying expression levels, they contain much more biologically important information such as copy number variants (CNVs). Here, we present CaSpER, a signal processing approach for identification, visualization, and integrative analysis of focal and large-scale CNV events in multiscale resolution using either bulk or single-cell RNA sequencing data. CaSpER integrates the multiscale smoothing of expression signal and allelic shift signals for CNV calling. The allelic shift signal measures the loss-of-heterozygosity (LOH) which is valuable for CNV identification. CaSpER employs an efficient methodology for the generation of a genome-wide B-allele frequency (BAF) signal profile from the reads and utilizes it for correction of CNVs calls. CaSpER increases the utility of RNA-sequencing datasets and complements other tools for complete characterization and visualization of the genomic and transcriptomic landscape of single cell and bulk RNA sequencing data. RNA-sequencing is mostly used to assess gene expression; however, it can also give information about genetic variants. Here, the authors present CaSpER, a statistical framework that utilises RNA-sequencing reads to identify and visualise CNV events by integrating transcriptome-wide expression and allelic shift profiles.
Learning 2D Temporal Adjacent Networks for Moment Localization with Natural Language.

We address the problem of retrieving a specific moment from an untrimmed video by a query sentence. This is a challenging problem because a target moment may take place in relations to other temporal moments in the untrimmed video. Existing methods cannot tackle this challenge well since they consider temporal moments individually and neglect the temporal dependencies. In this paper, we model the temporal relations between video moments by a two-dimensional map, where one dimension indicates the starting time of a moment and the other indicates the end time. This 2D temporal map can cover diverse video moments with different lengths, while representing their adjacent relations. Based on the 2D map, we propose a Temporal Adjacent Network (2D-TAN), a single-shot framework for moment localization. It is capable of encoding the adjacent temporal relation, while learning discriminative features for matching video moments with referring expressions. We evaluate the proposed 2D-TAN on three challenging benchmarks, i.e., Charades-STA, ActivityNet Captions, and TACoS, where our 2D-TAN outperforms the state-of-the-art.
Mesolimbic dopamine D2 receptors and neural representations of subjective value

The process by which the value of delayed rewards is discounted varies from person to person. It has been suggested that these individual differences in subjective valuation of delayed rewards are supported by mesolimbic dopamine D2-like receptors (D2Rs) in the ventral striatum. However, no study to date has documented an association between direct measures of dopamine receptors and neural representations of subjective value in humans. Here, we examined whether individual differences in D2R availability were related to neural subjective value signals during decision making. Human participants completed a monetary delay discounting task during an fMRI scan and on a separate visit completed a PET scan with the high affinity D2R tracer [18 F]fallypride. Region-of-interest analyses revealed that D2R availability in the ventral striatum was positively correlated with subjective value-related activity in the ventromedial prefrontal cortex and midbrain but not with choice behavior. Whole-brain analyses revealed a positive correlation between ventral striatum D2R availability and subjective value-related activity in the left inferior frontal gyrus and superior insula. These findings identify a link between a direct measure of mesolimbic dopamine function and subjective value representation in humans and suggest a mechanism by which individuals vary in neural representation of discounted subjective value.
The Mermin Fixed Point

The most efficient known method for solving certain computational problems is to construct an iterated map whose fixed points are by design the problem's solution. Although the origins of this idea go back at least to Newton, the clearest expression of its logical basis is an example due to Mermin. A contemporary application in image recovery demonstrates the power of the method.
The Scientific Capabilities of the James Webb Space Telescope

The scientific capabilities of the James Webb Space Telescope fall into four themes. The End of the Dark Ages: First Light and Reionization theme seeks to identify the first luminous sources to form and to determine the ionization history of the universe. The Assembly of Galaxies theme seeks to determine how galaxies and dark matter, gas, stars, metals morphological structures, and active nuclei within them evolved from the epoch of reionization to the present. The Birth of Stars and Protoplanetary Systems and the Origins of Life theme seeks to determine the physical and chemical properties of planetary systems around nearby stars and of our own, and investigate the potential for life in those systems. A comprehensive, top-level review of JWST sciences was published in the journal Space Science Reviews (Gardner et al. 2006, SSR, 123, 485). That paper gives details of the 4 JWST science themes, and describes the design of the observatory and ground system. Since that paper was published, the JWST Science Working Group, working with members of the astronomical community, has continued to develop the science case for JWST, giving more details in a series of white papers. In this poster, the main science themes and white papers are reviewed.
The effects of polydisperse crowders on the compaction of the Escherichia coli nucleoid

DNA binding proteins, supercoiling, macromolecular crowders, and transient DNA attachments to the cell membrane have all been implicated in the organization of the bacterial chromosome. However, it is unclear what role these factors play in compacting the bacterial DNA into a distinct organelle-like entity, the nucleoid. By analyzing the effects of osmotic shock and mechanical squeezing on Escherichia coli, we show that macromolecular crowders play a dominant role in the compaction of the DNA into the nucleoid. We find that a 30% increase in the crowder concentration from physiological levels leads to a three-fold decrease in the nucleoid's volume. The compaction is anisotropic, being higher along the long axes of the cell at low crowding levels. At higher crowding levels, the nucleoid becomes spherical, and its compressibility decreases significantly. Furthermore, we find that the compressibility of the nucleoid is not significantly affected by cell growth rates and by prior treatment with rifampicin. The latter results point out that in addition to poly ribosomes, soluble cytoplasmic proteins have a significant contribution in determining the size of the nucleoid. The contribution of poly ribosomes dominates at faster and soluble proteins at slower growth rates.
County-level analysis reveals a rapidly shifting landscape of insecticide hazard to honey bees ( Apis mellifera ) on US farmland

Each year, millions of kilograms of insecticides are applied to crops in the US. While insecticide use supports food, fuel, and fiber production, it can also threaten non-target organisms, a concern underscored by mounting evidence of widespread decline of pollinator populations. Here, we integrate several public datasets to generate county-level annual estimates of total 'bee toxic load' (honey bee lethal doses) for insecticides applied in the US between 1997-2012, calculated separately for oral and contact toxicity. To explore the underlying components of the observed changes, we divide bee toxic load into extent (area treated) and intensity (application rate x potency). We show that while contact-based bee toxic load remained relatively steady, oral-based bee toxic load increased roughly 9-fold, with reductions in application rate outweighed by disproportionate increases in potency (toxicity/kg) and extent. This pattern varied markedly by region, with the greatest increase seen in Heartland (121-fold increase), likely driven by use of neonicotinoid seed treatments in corn and soybean. In this "potency paradox", farmland in the central US has become more hazardous to bees despite lower volumes of insecticides applied, raising concerns about insect conservation and highlighting the importance of integrative approaches to pesticide use monitoring.
Near-optimal approximate discrete and continuous submodular function minimization

In this paper we provide improved running times and oracle complexities for approximately minimizing a submodular function. Our main result is a randomized algorithm, which given any submodular function defined on n-elements with range [−1, 1], computes an e-additive approximate minimizer in O(n/e2) oracle evaluations with high probability. This improves over the O(n5/3/e2) oracle evaluation algorithm of Chakrabarty et al. (STOC 2017) and the O(n3/2/e2) oracle evaluation algorithm of Hamoudi et al.. Further, we leverage a generalization of this result to obtain efficient algorithms for minimizing a broad class of nonconvex functions. For any function f with domain [0, 1]n that satisfies [MATH HERE] for all i ≠ j and is L-Lipschitz with respect to the L∞-norm we give an algorithm that computes an e-additive approximate minimizer with O(n · poly(L/e)) function evaluation with high probability.
Towards Optimal Separations between Quantum and Randomized Query Complexities

The query model offers a concrete setting where quantum algorithms are provably superior to randomized algorithms. Beautiful results by Bernstein-Vazirani, Simon, Aaronson, and others presented partial Boolean functions that can be computed by quantum algorithms making much fewer queries compared to their randomized analogs. To date, separations of $O(1)$ vs. $\sqrt{N}$ between quantum and randomized query complexities remain the state-of-the-art (where $N$ is the input length), leaving open the question of whether $O(1)$ vs. $N^{1/2+\Omega(1)}$ separations are possible? We answer this question in the affirmative. Our separating problem is a variant of the Aaronson-Ambainis k-fold Forrelation problem. We show that our variant: 1)Can be solved by a quantum algorithm making $2^{O(k)}$ queries to the inputs. 2)Requires at least $\widetilde{\Omega}(N^{2(k-1)/(3k-1)})$ queries for any randomized algorithm. For any constant $\epsilon > 0$ , this gives a $O(1)$ vs. $N^{1/2-\epsilon}$ separation between the quantum and randomized query complexities of partial Boolean functions. Our proof is Fourier analytical and uses new bounds on the Fourier spectrum of classical decision trees, which could be of independent interest. Looking forward, we conjecture that the Fourier bounds could be further improved in a precise manner, and show that such conjectured bounds imply optimal $O(1)$ vs. $N^{1-\epsilon}$ separations between the quantum and randomized query complexities of partial Boolean functions.
"How do I fool you?": Manipulating User Trust via Misleading Black Box Explanations

As machine learning black boxes are increasingly being deployed in critical domains such as healthcare and criminal justice, there has been a growing emphasis on developing techniques for explaining these black boxes in a human interpretable manner. There has been recent concern that a high-fidelity explanation of a black box ML model may not accurately reflect the biases in the black box. As a consequence, explanations have the potential to mislead human users into trusting a problematic black box. In this work, we rigorously explore the notion of misleading explanations and how they influence user trust in black box models. Specifically, we propose a novel theoretical framework for understanding and generating misleading explanations, and carry out a user study with domain experts to demonstrate how these explanations can be used to mislead users. Our work is the first to empirically establish how user trust in black box models can be manipulated via misleading explanations.
Residential noise exposure and health: Evidence from aviation noise and birth outcomes

Abstract Utilizing information on exact home addresses on birth records, we exploit arguably exogenous variation in noise exposure triggered by a new Federal Aviation Administration policy called NextGen, which unintentionally increased noise levels in communities experiencing concentrated flight patterns. We examine the fetal health impact of exposure to noise levels in excess of the EPA and the WHO recommended threshold of 55 dB. We find that the likelihood of having low birth weight (LBW) babies increases by 1.6 percentage points among mothers who live close to the airport, in the direction of the runway, exposed to noise levels over the 55 dB threshold, and during the period when NextGen was more actively implemented at the airport. Our finding has important policy implications for the trade-off between flight pattern optimization and human health in light of the long-term impact of LBW on later life outcomes.
Interpreting West Ashcom: Drones, Artifacts, and Archives

Archaeology from St. Mary’s College of Maryland began looking for the former homestead of West Ashcom in the Spring of 2012. West Ashcom was established on the south bank of the Patuxent River in what is now St. Mary’s County, MD by John Ashcom in 1651. At its height in the early eighteenth century it contained a manor house, kitchen, dairy, orchard, port, haberdashery, and various other barns and dependencies. Using traditional sources such as archives and methods like pedestrian surveys and surface collections, a late seventeenth/early eighteenth-century site was identified in a plowed field. Since then, archaeologists from SMCM have employed a range of sources, field methods, and mapping techniques to define the parameters of the site, past structures, and identify activity areas in a largely compromised area. This paper summarizes the results of more traditional uses of GIS mapping paired with experimental drone data to demonstrate the benefit of mixing old and new technologies when interpreting sites subject to continuous plowing and planting.
Asymmetric Lattice Disorder Induced at Oxide Interfaces

Control of order-disorder phase transitions is a fundamental materials science challenge, underpinning the development of energy storage technologies such as solid oxide fuel cells and batteries, ultra-high temperature ceramics, and durable nuclear waste forms. At present, the development of promising complex oxides for these applications is hindered by a poor understanding of how interfaces affect lattice disordering processes and defect transport. Here we explore the evolution of local disorder in ion-irradiated La$_2$Ti$_2$O$_7$ / SrTiO$_3$ thin film heterostructures using a combination of high-resolution scanning transmission electron microscopy (STEM), position-averaged convergent beam electron diffraction (PACBED), electron energy loss spectroscopy (STEM-EELS), and \textit{ab initio} theory calculations. We observe highly non-uniform lattice disordering driven by asymmetric oxygen vacancy formation across the interface. Our calculations indicate that this asymmetry results from differences in the polyhedral connectivity and vacancy formation energies of the two interface components, suggesting ways to manipulate lattice disorder in functional oxide heterostructures.
Convex integration and phenomenologies in turbulence

In this review article we discuss a number of recent results concerning wild weak solutions of the incompressible Euler and Navier-Stokes equations. These results build on the groundbreaking works of De Lellis and Szekelyhidi Jr., who extended Nash's fundamental ideas on $C^1$ flexible isometric embeddings, into the realm of fluid dynamics. These techniques, which go under the umbrella name convex integration, have fundamental analogies the phenomenological theories of hydrodynamic turbulence. Mathematical problems arising in turbulence (such as the Onsager conjecture) have not only sparked new interest in convex integration, but certain experimentally observed features of turbulent flows (such as intermittency) have also informed new convex integration constructions. First, we give an elementary construction of nonconservative $C^{0+}_{x,t}$ weak solutions of the Euler equations, first proven by De Lellis-Szekelyhidi Jr.. Second, we present Isett's recent resolution of the flexible side of the Onsager conjecture. Here, we in fact follow the joint work of De Lellis-Szekelyhidi Jr. and the authors of this paper, in which weak solutions of the Euler equations in the regularity class $C^{\frac 13-}_{x,t}$ are constructed, attaining any energy profile. Third, we give a concise proof of the authors' recent result, which proves the existence of infinitely many weak solutions of the Navier-Stokes in the regularity class $C^0_t L^{2+}_x \cap C^0_t W^{1,1+}_x$. We conclude the article by mentioning a number of open problems at the intersection of convex integration and hydrodynamic turbulence.
Linear representations of finite geometries and associated LDPC codes

Abstract The linear representation of a subset of a finite projective space is an incidence system of affine points and lines determined by the subset. In this paper we use character theory to show that the rank of the incidence matrix has a direct geometric interpretation in terms of certain hyperplanes. We consider the LDPC codes defined by taking the incidence matrix and its transpose as parity-check matrices, and in the former case prove a conjecture of Vandendriessche that the code is generated by words of minimum weight called plane words. In the latter case we compute the minimum weight in several cases and provide explicit constructions of minimum weight codewords.
De Novo Clustering of Long-Read Transcriptome Data Using a Greedy, Quality Value-Based Algorithm.

Long-read sequencing of transcripts with PacBio Iso-Seq and Oxford Nanopore Technologies has proven to be central to the study of complex isoform landscapes in many organisms. However, current de novo transcript reconstruction algorithms from long-read data are limited, leaving the potential of these technologies unfulfilled. A common bottleneck is the dearth of scalable and accurate algorithms for clustering long reads according to their gene family of origin. To address this challenge, we develop isONclust, a clustering algorithm that is greedy (in order to scale) and makes use of quality values (in order to handle variable error rates). We test isONclust on three simulated and five biological datasets, across a breadth of organisms, technologies, and read depths. Our results demonstrate that isONclust is a substantial improvement over previous approaches, both in terms of overall accuracy and/or scalability to large datasets. Our tool is available at https://github.com/ksahlin/isONclust.
"Red is not the only color of a rainbow": The making and resistance of the "MSM" subject among gay men in China.

Abstract Public health scholars classify gay men as “men who have sex with men (MSM)” in their studies and interventions. Debates have been raised about the MSM classification for decades. However, we know little about how people who are classified as MSM perceive and respond to this classification, particularly in the authoritarian context where the biopower interacts with the repressive state power. Drawing upon Ian Hacking's dynamic nominalism theory, this study tries to fill these gaps with interviews of 40 gay men in three Chinese cities about their interactions with public health education materials. I examined their perceptions of MSM knowledge and discourses associated with the classification, as well as their identifications to the MSM subject. I found that, on the one hand, many gay men had internalized the MSM subjectivity and considered themselves essentially at high risk of HIV infection. This compliance was constructed through various biopower techniques with the support of the state's repressive power, as the Chinese state censored almost all public representations of gay men except the HIV/AIDS subject MSM. On the other hand, some of my interviewees were resistant to be part of the MSM classification. I showed how this failure is an unintended consequence of the hegemonic MSM discourse and the authoritarian regime's institutional exclusion of the gay men's community's engagement in the expertise network that develops intervention materials and strategies. At last, I proposed to move beyond the debate around the name and representational character of the MSM by moving toward a more reflexive public health.
Measuring populism worldwide

Populism studies have rapidly burgeoned but systematic global empirical evidence about this phenomenon has lagged behind. How can party values be measured in consistent, valid, and reliable ways, f...
Finite strain constitutive modeling for shape memory alloys considering transformation-induced plasticity and two-way shape memory effect

Abstract This work presents a three-dimensional constitutive model for shape memory alloys considering the TRansformation-Induced Plasticity (TRIP) as well as the Two-Way Shape Memory Effect (TWSME) through a large deformation framework. The presented logarithmic strain based model is able to capture the large strains and rotations exhibited by SMAs under general thermomechanical cycling. By using the martensitic volume fraction, transformation strain, internal stress, and TRIP strain tensors as internal state variables, the model is capable to capture the stress-dependent TRIP generation when SMAs are subjected to a multiaxial stress state, as well as the TWSME for thermomechanically trained SMAs under load-free conditions. A detailed implementation procedure of the proposed model is presented through a user-defined material subroutine within a finite element framework allowing for solving different Boundary Value Problems (BVPs). Comprehensive instruction on calibrating the model parameters as well as the derivation of continuum tangent stiffness matrix are also provided. In the end, the simulated cyclic pseudoelastic and actuation responses by the presented model for a wide range of SMA material systems under both uniaxial and multiaxial stress states are compared against experimental results to validate the proposed modeling capabilities.
On the Cauchy problem for stochastic integro-differential equations with radially O-regularly varying Lévy measure

Parabolic integro-differential nondegenerate Cauchy problem is considered in the scale of $$L_{p}$$ spaces of functions whose regularity is defined by a Levy measure with O-regularly varying radial profile. Existence and uniqueness of a solution is proved by deriving apriori estimates. Some probability density function estimates of the associated Levy process are used as well.