cssi/SciSciGPT-SciSciNet huggingface dataset:
Robust Linear Temporal Logic

Although it is widely accepted that every system should be robust, in the sense that "small" violations of environment assumptions should lead to "small" violations of system guarantees, it is less clear how to make this intuitive notion of robustness mathematically precise. In this paper, we address the problem of how to specify robustness in temporal logic. Our solution consists of a robust version of the Linear Temporal Logic (LTL) fragment that only contains the always and eventually temporal operators.
Fast Multivariate Log-Concave Density Estimation

Abstract A novel computational approach to log-concave density estimation is proposed. Previous approaches utilize the piecewise-affine parametrization of the density induced by the given sample set. The number of parameters as well as non-smooth subgradient-based convex optimization for determining the maximum likelihood density estimate cause long runtimes for dimensions d ≥ 2 and large sample sets. The presented approach is based on mildly non-convex smooth approximations of the objective function and sparse, adaptive piecewise-affine density parametrization. Established memory-efficient numerical optimization techniques enable to process larger data sets for dimensions d ≥ 2 . While there is no guarantee that the algorithm returns the maximum likelihood estimate for every problem instance, we provide comprehensive numerical evidence that it does yield near-optimal results after significantly shorter runtimes. For example, 10000 samples in R 2 are processed in two seconds, rather than in ≈ 14 hours required by the previous approach to terminate. For higher dimensions, density estimation becomes tractable as well: Processing 10000 samples in R 6 requires 35 min. The software is publicly available as CRAN R package fmlogcondens .
Temporal Event Knowledge Acquisition via Identifying Narratives.

Inspired by the double temporality characteristic of narrative texts, we propose a novel approach for acquiring rich temporal “before/after” event knowledge across sentences in narrative stories. The double temporality states that a narrative story often describes a sequence of events following the chronological order and therefore, the temporal order of events matches with their textual order. We explored narratology principles and built a weakly supervised approach that identifies 287k narrative paragraphs from three large corpora. We then extracted rich temporal event knowledge from these narrative paragraphs. Such event knowledge is shown useful to improve temporal relation classification and outperforms several recent neural network models on the narrative cloze task.
A new perspective on CP and T violation

It is shown that the results of CP and T violation experiments can be interpreted using a very general framework that does not require a Hilbert space of states or linear operators to represent the symmetries or dynamics. Analysis within this general framework brings out the aspects of quantum mechanics that are essential for this interpretation. More importantly, should quantum mechanics be eventually replaced by a new paradigm, this framework could still be used to establish violation of CP and T invariance from the already known experimental results. This work arose as a ‘formal response’ to a talk Three Merry Roads to T-Violation by Dr. Bryan Roberts [1]. Both talks were given at a Workshop on Cosmology and Time held at Penn State in April 2013, which brought together physicists and philosophers of science.
Pattern Formation without Favored Local Interactions

Individual cellular automata rules are attractive models for a range of biological and physical self-assembling systems. While coexpression and coevolution are common in such systems, ensembles of cellular automata rules remain poorly understood. Here we report the first known analysis of the equally weighted ensemble of all elementary cellular automata (ECA) rules. Ensembledynamicsrevealpersistent, localized, non-interactingpatterns, rather than homogenization. The patterns are strongly correlated by velocity and have a quasi-linear dependence on initial conditions. Dispersion from a single initial site generates peaks traveling at low-denominator fractional velocities, some of which are not discernible in individual rules, suggesting collective excitation. Further analysis of the time-evolved rule space shows the 256 ECArules can be represented by only approximately 111 principal components. These results suggest the rather surprising conclusion that rich self-assembly is possible without favoring particular local interactions.
What made you do this? Understanding black-box decisions with sufficient input subsets

Local explanation frameworks aim to rationalize particular decisions made by a black-box prediction model. Existing techniques are often restricted to a specific type of predictor or based on input saliency, which may be undesirably sensitive to factors unrelated to the model’s decision making process. We instead propose sufficient input subsets that identify minimal subsets of features whose observed values alone suffice for the same decision to be reached, even if all other input feature values are missing. General principles that globally govern a model’s decision-making can also be revealed by searching for clusters of such input patterns across many data points. Our approach is conceptually straightforward, entirely model-agnostic, simply implemented using instance-wise backward selection, and able to produce more concise rationales than existing techniques. We demonstrate the utility of our interpretation method on various neural network models trained on text, image, and genomic data.
Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change

Understanding how words change their meanings over time is key to models of language and cultural evolution, but historical data on meaning is scarce, making theories hard to develop and test. Word embeddings show promise as a diachronic tool, but have not been carefully evaluated. We develop a robust methodology for quantifying semantic change by evaluating word embeddings (PPMI, SVD, word2vec) against known historical changes. We then use this methodology to reveal statistical laws of semantic evolution. Using six historical corpora spanning four languages and two centuries, we propose two quantitative laws of semantic change: (i) the law of conformity---the rate of semantic change scales with an inverse power-law of word frequency; (ii) the law of innovation---independent of frequency, words that are more polysemous have higher rates of semantic change.
Communication-efficient algorithms for decentralized and stochastic optimization

We present a new class of decentralized first-order methods for nonsmooth and stochastic optimization problems defined over multiagent networks. Considering that communication is a major bottleneck in decentralized optimization, our main goal in this paper is to develop algorithmic frameworks which can significantly reduce the number of inter-node communications. Our major contribution is to present a new class of decentralized primal–dual type algorithms, namely the decentralized communication sliding (DCS) methods, which can skip the inter-node communications while agents solve the primal subproblems iteratively through linearizations of their local objective functions. By employing DCS, agents can find an $$\epsilon $$-solution both in terms of functional optimality gap and feasibility residual in $${{\mathcal {O}}}(1/\epsilon )$$ (resp., $${{\mathcal {O}}}(1/\sqrt{\epsilon })$$) communication rounds for general convex functions (resp., strongly convex functions), while maintaining the $${{\mathcal {O}}}(1/\epsilon ^2)$$ (resp., $$\mathcal{O}(1/\epsilon )$$) bound on the total number of intra-node subgradient evaluations. We also present a stochastic counterpart for these algorithms, denoted by SDCS, for solving stochastic optimization problems whose objective function cannot be evaluated exactly. In comparison with existing results for decentralized nonsmooth and stochastic optimization, we can reduce the total number of inter-node communication rounds by orders of magnitude while still maintaining the optimal complexity bounds on intra-node stochastic subgradient evaluations. The bounds on the (stochastic) subgradient evaluations are actually comparable to those required for centralized nonsmooth and stochastic optimization under certain conditions on the target accuracy.
Novel approach for cybersecurity workforce development: A course in secure design

Training the future cybersecurity workforce to respond to emerging threats requires introduction of novel educational interventions into the cybersecurity curriculum. To be effective, these interventions have to incorporate trending knowledge from cybersecurity and other related domains while allowing for experiential learning through hands-on experimentation. To date, the traditional interdisciplinary approach for cybersecurity training has infused political science, law, economics or linguistics knowledge into the cybersecurity curriculum, allowing for limited experimentation. Cybersecurity students were left with little opportunity to acquire knowledge, skills, and abilities in domains outside of these. Also, students in outside majors had no options to get into cybersecurity. With this in mind, we developed an interdisciplinary course for experiential learning in the fields of cybersecurity and interaction design. The inaugural course teaches students from cybersecurity, user interaction design, and visual design the principles of designing for secure use — or secure design — and allows them to apply them for prototyping of Internet-of-Things (IoT) products for smart homes. This paper elaborates on the concepts of secure design and how our approach enhances the training of the future cybersecurity workforce.
An Occluded Stacked Hourglass Approach to Facial Landmark Localization and Occlusion Estimation

A key step to driver safety is to observe the driver's activities with the face being a key step in this process to extracting information such as head pose, blink rate, yawns, talking to passenger which can then help derive higher level information, such as distraction, drowsiness, intent, and where they are looking. In the context of driving safety, it is important for the system perform robust estimation under harsh lighting and occlusion but also be able to detect when the occlusion occurs so that information predicted from occluded parts of the face can be taken into account properly. This paper introduces the Occluded Stacked Hourglass, based on the work of original Stacked Hourglass network for body pose joint estimation, which is retrained to process a detected face window and output 68 occlusion heat maps, each corresponding to a facial landmark. Landmark location, occlusion levels and a refined face detection score, to reject false positives, are extracted from these heat maps. Using the facial landmark locations, features such as head pose and eye/mouth openness can be extracted to derive driver attention and activity. The system is evaluated for face detection, head pose, and occlusion estimation on various datasets in the wild, both quantitatively and qualitatively, and shows state-of-the-art results.
On the mean square of the remainder for the Euclidean lattice point counting problem

We give asymptotic formulas for the average and mean square bounds for the remainder in the lattice point counting problem, counting the number of lattice points in a large ball in R d , when averaged over families of shears of the lattice.
The minimal length of a Lagrangian cobordism between Legendrians

To investigate the rigidity and flexibility of Lagrangian cobordisms between Legendrian submanifolds, we study the minimal length of such a cobordism, which is a 1-dimensional measurement of the non-cylindrical portion of the cobordism. Our primary tool is a set of real-valued capacities for a Legendrian submanifold, which are derived from a filtered version of Legendrian contact homology. Relationships between capacities of Legendrians at the ends of a Lagrangian cobordism yield lower bounds on the length of the cobordism. We apply the capacities to Lagrangian cobordisms realizing vertical dilations (which may be arbitrarily short) and contractions (whose lengths are bounded below). We also study the interaction between length and the linking of multiple cobordisms as well as the lengths of cobordisms derived from non-trivial loops of Legendrian isotopies.
The phase transition in random regular exact cover

A k-uniform, d-regular instance of Exact Cover is a family of m sets Fn,d,k = {Sj ⊆ {1, . . . , n}}, where each subset has size k and each 1 ≤ i ≤ n is contained in d of the Sj . It is satisfiable if there is a subset T ⊆ {1, . . . , n} such that |T ∩ Sj | = 1 for all j. Alternately, we can consider it a d-regular instance of Positive 1-in-k SAT, i.e., a Boolean formula with m clauses and n variables where each clause contains k variables and demands that exactly one of them is true. We determine the satisfiability threshold for random instances of this type with k > 2. Letting d = ln k (k − 1)(− ln(1− 1/k)) + 1 , we show that Fn,d,k is satisfiable with high probability if d d. We do this with a simple application of the first and second moment methods, boosting the probability of satisfiability below d to 1− o(1) using the small subgraph conditioning method.
Efficient Algorithms with Asymmetric Read and Write Costs

In several emerging technologies for computer memory (main memory), the cost of reading is significantly cheaper than the cost of writing. Such asymmetry in memory costs poses a fundamentally different model from the RAM for algorithm design. In this paper we study lower and upper bounds for various problems under such asymmetric read and write costs. We consider both the case in which all but O(1) memory has asymmetric cost, and the case of a small cache of symmetric memory. We model both cases using the (M,omega)-ARAM, in which there is a small (symmetric) memory of size M and a large unbounded (asymmetric) memory, both random access, and where reading from the large memory has unit cost, but writing has cost omega >> 1. For FFT and sorting networks we show a lower bound cost of Omega(omega*n*log_{omega*M}(n)), which indicates that it is not possible to achieve asymptotic improvements with cheaper reads when omega is bounded by a polynomial in M. Moreover, there is an asymptotic gap (of min(omega,log(n)/log(omega*M)) between the cost of sorting networks and comparison sorting in the model. This contrasts with the RAM, and most other models, in which the asymptotic costs are the same. We also show a lower bound for computations on an n*n diamond DAG of Omega(omega*n^2/M) cost, which indicates no asymptotic improvement is achievable with fast reads. However, we show that for the minimum edit distance problem (and related problems), which would seem to be a diamond DAG, we can beat this lower bound with an algorithm with only O(omega*n^2/(M*min(omega^{1/3},M^{1/2}))) cost. To achieve this we make use of a "path sketch" technique that is forbidden in a strict DAG computation. Finally, we show several interesting upper bounds for shortest path problems, minimum spanning trees, and other problems. A common theme in many of the upper bounds is that they require redundant computation and a tradeoff between reads and writes.
Khovanov–Rozansky homology and directed cycles

We determine the cycle packing number of a directed graph using elementary projective algebraic geometry. Our idea is rooted in the Khovanov–Rozansky theory. In fact, using the Khovanov–Rozansky homology of a graph, we also obtain algebraic methods of detecting directed and undirected cycles containing a particular vertex or edge.
Empirical and Strong Coordination via Soft Covering With Polar Codes

We design polar codes for empirical coordination and strong coordination in two-node networks. Our constructions hinge on the fact that polar codes enable explicit low-complexity schemes for soft covering. We leverage this property to propose explicit and low-complexity coding schemes that achieve the capacity regions of both empirical coordination and strong coordination for sequences of actions taking value in an alphabet of prime cardinality. Our results improve previously known polar coding schemes, which (i) were restricted to uniform distributions and to actions obtained via binary symmetric channels for strong coordination, (ii) required a non-negligible amount of common randomness for empirical coordination, and (iii) assumed that the simulation of discrete memoryless channels could be perfectly implemented. As a by-product of our results, we obtain a polar coding scheme that achieves channel resolvability for an arbitrary discrete memoryless channel whose input alphabet has prime cardinality.
Unification nets: canonical proof net quantifiers

Proof nets for MLL (unit-free Multiplicative Linear Logic) are concise graphical representations of proofs which are canonical in the sense that they abstract away syntactic redundancy such as the order of non-interacting rules. We argue that Girard's extension to MLL1 (first-order MLL) fails to be canonical because of redundant existential witnesses, and present canonical MLL1 proof nets called unification nets without them. For example, while there are infinitely many cut-free Girard nets ∀x Px v ∃x Px, one per arbitrary witness for ∃x, there is a unique cut-free unification net, with no specified witness.Cut elimination for unification nets is local and linear time, while Girard's is non-local and exponential time. Since some unification nets are exponentially smaller than corresponding Girard nets and sequent proofs, technical delicacy is required to ensure correctness is polynomial-time (quadratic).These results transcend MLL1 via a methodological insight: for canonical quantifiers, the standard parallel/sequential dichotomy of proof nets is insufficient; an implicit/explicit witness dichotomy is needed. Current work extends unification nets to additives and uses them to extend combinatorial proofs [Proofs without syntax, Annals of Mathematics, 2006] to classical first-order logic.
Symmetric matrices, Catalan paths, and correlations

Kenyon and Pemantle (2014) gave a formula for the entries of a square matrix in terms of connected principal and almost-principal minors. Each entry is an explicit Laurent polynomial whose terms are the weights of domino tilings of a half Aztec diamond. They conjectured an analogue of this parametrization for symmetric matrices, where the Laurent monomials are indexed by Catalan paths. In this paper we prove the Kenyon-Pemantle conjecture, and relate this to a statistics problem pioneered by Joe (2006). Correlation matrices are represented by an explicit bijection from the cube to the elliptope.
Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study

Several recent papers investigate Active Learning (AL) for mitigating the data dependence of deep learning for natural language processing. However, the applicability of AL to real-world problems remains an open question. While in supervised learning, practitioners can try many different methods, evaluating each against a validation set before selecting a model, AL affords no such luxury. Over the course of one AL run, an agent annotates its dataset exhausting its labeling budget. Thus, given a new task, we have no opportunity to compare models and acquisition functions. This paper provides a large-scale empirical study of deep active learning, addressing multiple tasks and, for each, multiple datasets, multiple models, and a full suite of acquisition functions. We find that across all settings, Bayesian active learning by disagreement, using uncertainty estimates provided either by Dropout or Bayes-by-Backprop significantly improves over i.i.d. baselines and usually outperforms classic uncertainty sampling.
Explicit Heegner points: Kolyvagin's conjecture and non-trivial elements in the Shafarevich–Tate group

Abstract Kolyvagin used Heegner points to associate a system of cohomology classes to an elliptic curve over Q and conjectured that the system contains a non-trivial class. His conjecture has profound implications on the structure of Selmer groups. We provide new computational and theoretical evidence for Kolyvagin's conjecture. More precisely, we explicitly approximate Heegner points over ring class fields and use these points to give evidence for the conjecture for specific elliptic curves of rank two. We explain how Kolyvagin's conjecture implies that if the analytic rank of an elliptic curve is at least two then the Z p -corank of the corresponding Selmer group is at least two as well. We also use explicitly computed Heegner points to produce non-trivial classes in the Shafarevich–Tate group.
The S. pombe adaptor protein Bbc1 regulates localization of Wsp1 and Vrp1 during endocytic actin patch assembly.

ABSTRACT Arp2/3 complex-nucleated branched actin networks provide the key force necessary for endocytosis. The Arp2/3 complex is activated by nucleation-promoting factors including the Schizosaccharomyces pombe Wiskott–Aldrich syndrome protein (Wsp1) and myosin-1 (Myo1). There are >40 known yeast endocytic proteins with distinct spatial and temporal localizations and functions; however, it is still unclear how these proteins work together to drive endocytosis. Here, we used quantitative live-cell imaging to determine the function of the uncharacterized S. pombe protein Bbc1. We discovered that Myo1 interacts with and recruits Bbc1 to sites of endocytosis. Bbc1 competes with the verprolin Vrp1 for localization to patches and association with Myo1, thus releasing Vrp1 and its binding partner Wsp1 from Myo1. Normally Myo1 remains at the base of the endocytic invagination and Vrp1–Wsp1 internalizes with the endocytic vesicle. However, in the absence of Bbc1, a portion of Vrp1–Wsp1 remains with Myo1 at the base of the invagination, and endocytic structures internalize twice as far. We propose that Bbc1 disrupts a transient interaction of Myo1 with Vrp1 and Wsp1 and thereby limits Arp2/3 complex-mediated nucleation of actin branches at the plasma membrane. This article has an associated First Person interview with the first author of the paper.
Is your function low dimensional

We study the problem of testing if a function depends on a small number of linear directions of its input data. We call a function $f$ a linear $k$-junta if it is completely determined by some $k$-dimensional subspace of the input space. In this paper, we study the problem of testing whether a given $n$ variable function $f : \mathbb{R}^n \to \{0,1\}$, is a linear $k$-junta or $\epsilon$-far from all linear $k$-juntas, where the closeness is measured with respect to the Gaussian measure on $\mathbb{R}^n$. Linear $k$-juntas are a common generalization of two fundamental classes from Boolean function analysis (both of which have been studied in property testing) $\textbf{1.}$ $k$- juntas which are functions on the Boolean cube which depend on at most k of the variables and $\textbf{2.}$ intersection of $k$ halfspaces, a fundamental geometric concept class. We show that the class of linear $k$-juntas is not testable, but adding a surface area constraint makes it testable: we give a $\mathsf{poly}(k \cdot s/\epsilon)$-query non-adaptive tester for linear $k$-juntas with surface area at most $s$. We show that the polynomial dependence on $s$ is necessary. Moreover, we show that if the function is a linear $k$-junta with surface area at most $s$, we give a $(s \cdot k)^{O(k)}$-query non-adaptive algorithm to learn the function up to a rotation of the basis. In particular, this implies that we can test the class of intersections of $k$ halfspaces in $\mathbb{R}^n$ with query complexity independent of $n$.
Beauty Learning and Counterfactual Inference

This work showcases a new approach for causal discovery by leveraging user experiments and recent advances in photo-realistic image editing, demonstrating a potential of identifying causal factors and understanding complex systems counterfactually. We introduce the beauty learning problem as an example, which has been discussed metaphysically for centuries and been proved exists, is quantifiable, and can be learned by deep models in our recent paper, where we utilize a natural image generator coupled with user studies to infer causal effects from facial semantics to beauty outcomes, the results of which also align with existing empirical studies. We expect the proposed framework for a broader application in causal inference.
Proximity RNA Labeling by APEX-Seq Reveals the Organization of Translation Initiation Complexes and Repressive RNA Granules

Diverse ribonucleoprotein complexes control mRNA processing, translation, and decay. Transcripts in these complexes localize to specific regions of the cell and can condense into non-membrane-bound structures such as stress granules. It has proven challenging to map the RNA composition of these large and dynamic structures, however. We therefore developed an RNA proximity labeling technique, APEX-seq, which uses the ascorbate peroxidase APEX2 to probe the spatial organization of the transcriptome. We show that APEX-seq can resolve the localization of RNAs within the cell and determine their enrichment or depletion near key RNA-binding proteins. Matching the spatial transcriptome, as revealed by APEX-seq, with the spatial proteome determined by APEX-mass spectrometry (APEX-MS), obtained precisely in parallel, provides new insights into the organization of translation initiation complexes on active mRNAs and unanticipated complexity in stress granule composition. Our novel technique allows a powerful and general approach to explore the spatial environment of macromolecules.
Conceptualization and operationalization: utility of communication privacy management theory

Communication Privacy Management (CPM) theory explains one of the most important, yet challenging social processes in everyday life, that is, managing disclosing and protecting private information. The CPM privacy management system offers researchers, students, and the public a comprehensive approach to the complex and fluid character of privacy management in action. Following an overview of Communication Privacy Management framework, this review focuses on recent research utilizing CPM concepts that cross a growing number of contexts and illustrates the way people navigate privacy in action. Researchers operationalize the use of privacy rules and other core concepts that help describe and explain the ups and downs of privacy management people encounter.
Blockchain meets database: design and implementation of a blockchain relational database

In this paper, we design and implement the first-ever decentralized replicated relational database with blockchain properties that we term blockchain relational database. We highlight several similarities between features provided by blockchain platforms and a replicated relational database, although they are conceptually different, primarily in their trust model. Motivated by this, we leverage the rich features, decades of research and optimization, and available tooling in relational databases to build a blockchain relational database. We consider a permissioned blockchain model of known, but mutually distrustful organizations each operating their own database instance that are replicas of one another. The replicas execute transactions independently and engage in decentralized consensus to determine the commit order for transactions. We design two approaches, the first where the commit order for transactions is agreed upon prior to executing them, and the second where transactions are executed without prior knowledge of the commit order while the ordering happens in parallel. We leverage serializable snapshot isolation (SSI) to guarantee that the replicas across nodes remain consistent and respect the ordering determined by consensus, and devise a new variant of SSI based on block height for the latter approach. We implement our system on PostgreSQL and present detailed performance experiments analyzing both approaches.
Effects of persistent sodium current blockade in respiratory circuits depend on the pharmacological mechanism of action and network dynamics.

The mechanism(s) of action of most commonly used pharmacological blockers of voltage-gated ion channels are well understood; however, this knowledge is rarely considered when interpreting experimental data. Effects of blockade are often assumed to be equivalent, regardless of the mechanism of the blocker involved. Using computer simulations, we demonstrate that this assumption may not always be correct. We simulate the blockade of a persistent sodium current (INaP), proposed to underlie rhythm generation in pre-Botzinger complex (pre-BotC) respiratory neurons, via two distinct pharmacological mechanisms: (1) pore obstruction mediated by tetrodotoxin and (2) altered inactivation dynamics mediated by riluzole. The reported effects of experimental application of tetrodotoxin and riluzole in respiratory circuits are diverse and seemingly contradictory and have led to considerable debate within the field as to the specific role of INaP in respiratory circuits. The results of our simulations match a wide array of experimental data spanning from the level of isolated pre-BotC neurons to the level of the intact respiratory network and also generate a series of experimentally testable predictions. Specifically, in this study we: (1) provide a mechanistic explanation for seemingly contradictory experimental results from in vitro studies of INaP block, (2) show that the effects of INaP block in in vitro preparations are not necessarily equivalent to those in more intact preparations, (3) demonstrate and explain why riluzole application may fail to effectively block INaP in the intact respiratory network, and (4) derive the prediction that effective block of INaP by low concentration tetrodotoxin will stop respiratory rhythm generation in the intact respiratory network. These simulations support a critical role for INaP in respiratory rhythmogenesis in vivo and illustrate the importance of considering mechanism when interpreting and simulating data relating to pharmacological blockade.
MNL-Bandit: A Dynamic Learning Approach to Assortment Selection

We consider a dynamic assortment selection problem where in every round the retailer offers a subset (assortment) of N substitutable products to a consumer, who selects one of these products accord...
Simple and Efficient Truncation of Virtual Spaces in Embedded Wave Functions via Concentric Localization

We present a strategy to generate "concentrically local orbitals" for the purpose of decreasing the computational cost of wave function-in-density functional theory (WF-in-DFT) embedding. The concentric localization is performed for the virtual orbitals by first projecting the virtual space onto atomic orbitals centered on the embedded atoms. Using a one-particle operator, these projected orbitals are then taken as a starting point to iteratively span the virtual space, recursively creating virtual orbital "shells" with consecutively decreasing correlation energy recovery at each iteration. This process can be repeated to convergence, allowing for tunable accuracy. Assessment of the proposed scheme is performed by application to the potential energy diagram of the Menshutkin reaction of chloromethane and ammonia inside a segment of a carbon nanotube and the torsional potential of a simplified version of the retinal chromophore.
Nonparametric identification in index models of link formation

Abstract We consider a dyadic link formation model with a homophily effect index and a degree heterogeneity index. We provide nonparametric identification results for the potentially nonparametric homophily effect function, the realizations of unobserved individual fixed effects and the unknown distribution of idiosyncratic shocks, up to normalization. We propose a novel form of scale normalization on an arbitrary interquantile range, which is not only theoretically general but also proves particularly convenient for the identification analysis. We then use an inductive “in-fill and out-expansion” algorithm to establish our main results.
Heritage Language Learners and Spanish for Specific Purposes: Bridging the Gap through Community Service Learning

The growth in the number of Spanish heritage language learners in languages for specific purposes classes has been accompanied by an increase in the number and types of community service learning programs in which these students can participate to better prepare them for future employment opportunities. In spite of the increase in the number of Spanish heritage language learners in the languages for specific purposes classroom, few studies have looked at these students in this setting and even fewer have looked at the role that community service learning can play in developing these learners’ domain-specific abilities. Through an analysis of research in the areas of heritage language learners, Spanish for specific purposes, and community service learning, this article discusses strategies to effectively teach Spanish heritage language learners in language for specific purposes classes and to develop their language and cultural knowledge through community service learning. In addition, we address many of the challenges that arise when connecting Spanish heritage language learners with community partners as well as the obstacles to the integration of community service learning into the Spanish for specific purposes curriculum. The article concludes providing suggestions on how community service can be used to help Spanish heritage language learners not only see the benefits of language for specific purposes courses but also transfer their skills to other fields of study.
Awareness of Sex Offender Registration Policies and Self-Reported Sexual Offending in a Community Sample of Adolescents

Sex offender registration laws are widely implemented, increasingly restrictive, and intended to serve both specific and general deterrent functions. Most states have some form of policy mechanism to place adolescents on sex offender registries, yet it remains unclear whether adolescents possess the requisite policy awareness to be deterred from sexual offending. This study examined awareness of sex offender registration as a potential sanction and its cross-sectional association with engagement in several registrable sexual behaviors (sexting, indecent exposure, sexual solicitation, and forcible touching) in a community sample of 144 adolescents. Results revealed that many adolescents were unaware that these behaviors could result in sex offender registration. Moreover, over one-third of adolescents who incorrectly believed that youth cannot be registered were highly confident in their answers. Notably, nearly half the sample had engaged in at least one of the four registrable behaviors we assessed, and policy-aware youth were just as likely as others to have engaged in those registrable sexual behaviors. Our findings cast doubt on arguments that juvenile sex offender registration serves as a general deterrent, adding to a growing body of literature suggesting that the policy is ineffective and in need of reform.
Do Detail and Its Verifiability Serve as Indicators of Strategy Effectiveness and as Sources of Credibility in Voluntary Qualitative Disclosure

This article examines whether detail and its verifiability serve as indicators of strategy effectiveness and provide sources of credibility in voluntary qualitative disclosure. In an archival study...
Communication Profiling and Characterization of Deep-Learning Workloads on Clusters With High-Performance Interconnects

Heterogeneous high-performance computing systems with GPUs are equipped with high-performance interconnects like InfiniBand, Omni-Path, PCIe, and NVLink. However, little exists in the literature that captures the performance impact of these interconnects on distributed deep learning (DL). In this article, we choose Horovod, a distributed training middleware, to analyze and profile various DNN training workloads using TensorFlow and PyTorch in addition to standard MPI microbenchmarks. We use a wide variety of systems with CPUs like Intel Xeon and IBM POWER9, GPUs like Volta V100, and various interconnects to analyze the following metrics: 1) message-size with Horovod's tensor-fusion; 2) message-size without tensor-fusion; 3) number of MPI/NCCL calls; and 4) time taken by each MPI/NCCL call. We observed extreme performance variations for non-power-of-two message sizes on different platforms. To address this, we design a message-padding scheme for Horovod, illustrate significantly smoother allreduce latency profiles, and report cases where we observed improvement for end-to-end training.
Hippocampal theta codes for distances in semantic and temporal spaces

The medial temporal lobe (MTL) is known to support episodic memory and spatial navigation, raising the possibility that its true function is to form “cognitive maps” of any kind of information. Studies in humans and animals support the idea that the hippocampal theta rhythm (4 to 8 Hz) is key to this mapping function, as it has been repeatedly observed during spatial navigation tasks. If episodic memory and spatial navigation are 2 sides of the same coin, we hypothesized that theta oscillations might reflect relations between explicitly nonspatial items, such as words. We asked 189 neurosurgical patients to perform a verbal free-recall task, of which 96 had indwelling electrodes placed in the MTL. Subjects were instructed to remember short lists of sequentially presented nouns. We found that hippocampal theta power and connectivity during item retrieval coded for semantic distances between words, as measured using word2vec-derived subspaces. Additionally, hippocampal theta indexed temporal distances between words after filtering lists on recall performance, to ensure adequate dynamic range in time. Theta effects were noted only for semantic subspaces of 1 dimension, indicating a substantial compression of the possible semantic feature space. These results lend further support to our growing confidence that the MTL forms cognitive maps of arbitrary representational spaces, helping to reconcile longstanding differences between the spatial and episodic memory literatures.
Parasites and sexual selection

Parasites may impose heavy energetic costs on their hosts, and it may often benefit animals to choose mates that are relatively free of parasites. According to the Hamilton–Zuk hypothesis, choosing mates on the basis of parasite resistance may be particularly beneficial if such resistance is heritable, and sexual signals may have evolved in part to convey information about parasite resistance. As evidence for this, females in species ranging from jungle fowl to crickets seem to prefer males that have fewer parasites and/or a stronger immune response. Testosterone may provide a mechanistic link between parasite resistance and sexual signaling in vertebrates, as it both enhances the signal and depresses the immune system. Further work in the field should address such questions as the degree to which the evolution and development of sexual signals depends on parasites and how this may influence differences between the sexes.
Endoscopic management of large ileocecal valve lesions over an 18-year interval.

Background and study aims Ileocecal valve (ICV) lesions are challenging to remove endoscopically. Patients and methods This was a retrospective cohort study, performed at an academic tertiary US hospital. Sessile polyps or flat ICV lesions ≥ 20 mm in size referred for endoscopic mucosal resection (EMR) were included. Successful resection rates, complication rates and recurrence were compared to lesions ≥ 20 mm in size not located on the ICV. Results During an 18-year interval, there were 118 ICV lesions ≥ 20 mm with mean size 28.6 mm (44.9 % females; mean age 71.6 years), comprising 9.03 % of all referred polyps. Ninety ICV lesions (76.3 %) were resected endoscopically, compared to 91.3 % of non-ICV lesions (P Conclusions Large ICV polyps are a common source of tertiary referrals. Over an 18-year experience, risk of EMR for ICV polyps was numerically lower, and risk of recurrence was numerically higher at first follow and significantly higher at second follow-up compared to non-ICV polyps.
Inferring reaction network structure from single-cell, multiplex data, using toric systems theory

The goal of many single-cell studies on eukaryotic cells is to gain insight into the biochemical reactions that control cell fate and state. In this paper we introduce the concept of Effective Stoichiometric Spaces (ESS) to guide the reconstruction of biochemical networks from multiplexed, fixed time-point, single-cell data. In contrast to methods based solely on statistical models of data, the ESS method leverages the power of the geometric theory of toric varieties to begin unraveling the structure of chemical reaction networks (CRN). This application of toric theory enables a data-driven mapping of covariance relationships in single-cell measurements into stoichiometric information, one in which each cell subpopulation has its associated ESS interpreted in terms of CRN theory. In the development of ESS we reframe certain aspects of the theory of CRN to better match data analysis. As an application of our approach we process cytomery- and image-based single-cell datasets and identify differences in cells treated with kinase inhibitors. Our approach is directly applicable to data acquired using readily accessible experimental methods such as Fluorescence Activated Cell Sorting (FACS) and multiplex immunofluorescence.
New Physical Insights about Tidal Disruption Events from a Comprehensive Observational Inventory at X-Ray Wavelengths

We perform a comprehensive study of the X-ray emission from 70 transient sources which have been classified as a tidal disruption event (TDE) in the literature. We explore the properties of these candidates using nearly three decades of X-ray observations to quantify the properties and characteristics of X-ray TDEs observationally. We find that the emission from X-ray TDEs increase by two to four orders of magnitude compared to pre-flare constraints, which evolves significantly with time and decays with powerlaw indices that are typically shallower than the canonical $t^{-5/3}$ decay law, implying that X-ray TDEs are viscously delayed. These events exhibit enhanced column densities relative to Galactic and are quite soft in nature, with no strong correlation between the amount of detected soft and hard emission. At peak, jetted events have an X-ray to optical ratio $\gg$1, while non-jetted events have a ratio $\sim$1, which suggests that these events undergo reprocessing at different rates. X-ray TDEs have long $T_{90}$ values consistent with that expected from a viscously-driven accretion disk formed by the disruption of a main-sequence star by a black hole with a mass $<$$10^{7}M_{\odot}$. The isotropic luminosities of X-ray TDEs is bimodal such that jetted and non-jetted events are separated by a "reprocessing valley" which we suggest is naturally populated by optical/UV TDEs that most likely produce X-rays, but due to reprocessing this emission is "veiled" from observations. Our results suggest that non-jetted X-ray TDEs likely originate from partial disruptions and/or disruptions of low mass stars.
Algebraic filling inequalities and cohomological width

In his work on singularities, expanders and topology of maps, Gromov showed, using isoperimetric inequalities in graded algebras, that every real-valued map on the n–torus admits a fibre whose homological size is bounded below by some universal constant depending on n. He obtained similar estimates for maps with values in finite-dimensional complexes, by a Lusternik–Schnirelmann-type argument. We describe a new homological filling technique which enables us to derive sharp lower bounds in these theorems in certain situations. This partly realises a programme envisaged by Gromov. In contrast to previous approaches, our methods imply similar lower bounds for maps defined on products of higher-dimensional spheres.
Twelve years of IUE spectra of the interacting binary VV Cephei

All well-exposed high-resolution IUE spectra obtained of the eclipsing binary system VV Cephei (M2Iabep + B) are examined. High-temperature absorption features attributable to the hot companion were detected, indicating that the companion (or the inner regions of its accretion disk) are not as hot as a B1-B2 star. Doubling of Fe II (UV 1) lines, with an additional narrow component redshifted by about 60 km/sec, occurs only when the B star is behind the plane of the sky containing the M supergiant, suggesting the existence of mass transfer from the red to the blue star. Absorption features from neutral elements weaken dramatically during egress, while those from ionized elements remain at nearly constant strength. During egress from primary eclipse, the Mg II resonance doublet shows asymmetric double-peaked emission indicative of formation in an expanding chromosphere. It is concluded that the outer atmosphere of the M supergiant is highly clumped.
Computing Equilibria in Binary Networked Public Goods Games

Public goods games study the incentives of individuals to contribute to a public good and their behaviors in equilibria. In this paper, we examine a specific type of public goods game where players are networked and each has binary actions, and focus on the algorithmic aspects of such games. First, we show that checking the existence of a pure-strategy Nash equilibrium is NP-complete. We then identify tractable instances based on restrictions of either utility functions or of the underlying graphical structure. In certain cases, we also show that we can efficiently compute a socially optimal Nash equilibrium. Finally, we propose a heuristic approach for computing approximate equilibria in general binary networked public goods games, and experimentally demonstrate its effectiveness. Due to space limitation, some proofs are deferred to the extended version1.
Tumor downstaging in muscle invasive bladder cancer with neoadjuvant systemic therapy—does it lead to prolonged survival?

It has been firmly established that cisplatin-based chemotherapy in the neoadjuvant setting prior to radical cystectomy improves overall survival in patients with muscle invasive bladder cancer (1). This study demonstrates and argues that improvement in overall survival with neoadjuvant chemotherapy (NACT) is not only related to a complete clinical response (pT0N0), but also to any pathologic downstaging, whether complete or a partial response from the initial clinical stage at diagnosis (2). Both the Retrospective International Study of Cancer of the Urothelial Tract (RISC) and National Cancer Database (NCDB) were queried in this study to identify a cohort of patients that had complete pathologic response or downstaging with NACT. Multivariable Cox proportional hazard models were used to demonstrate the effect of downstaging and complete pathologic response on overall survival in the data set. The analysis ultimately found that any pathologic response is associated with improved overall survival, but a couple caveats should be noted.