cssi/SciSciGPT-SciSciNet huggingface dataset:
Synthetic Studies Aimed at (−)-Cochleamycin A. Evaluation of Late-Stage Macrocyclization Alternatives

An efficient route to the fully functionalized ABC ring systems of the unnatural enantiomer of cochleamycin A was developed. L-(-)-Malic and L-(-)-ascorbic acids served well as starting materials for the two building blocks used to construct an (E,Z,E)-1,6,8-nonatriene intermediate. The AB part structure was assembled by way of a stereocontrolled intramolecular Diels-Alder cycloaddition via adoption of an endo transition state. From this vantage point, two general pathways were subsequently explored as to their suitability for elaboration of the CD rings. Initially examined was a protocol involving 10-membered carbocycle construction. When this approach was demonstrated not to be workable, attention was directed to 10-membered macrolactonization as an alternative tactic. Although assembly of the C-ring in this manner was easily achieved, ultimate closure of the six-membered ring to form ring D remains an unsolved problem.
Novel cyclization reactions of mono- and dichloroazodienes. A new synthesis of substituted pyridazines†

Cyclization of the in—situ generated chloroazodienes with a variety of enamines was found to give chloro-substituted tetrahydropyridazines which could be aromatized to pyridazines by base treatment. This sequence appears to be a formal 4 + 2 hetero Diels-Alder reaction with a high degree of regio and stereo control and constitutes a new synthesis of substituted pyridazines. However, cyclization of the corresponding dichloroazodienes with acyclic enamines gave not only the expected pyridazine product, but also gave an N-aminopyrrole product. Combination of the dichloroazodiene with cyclic enamines gave bicyclic dihy-dropyridazines, bicyclic pyridazines, and acyclic enamines which could be forced to close to the bicyclic dihydropyridazines upon further heating. These results would indicate a stepwise mechanism. The scope and mechanistic speculations on these reactions will be presented. While exploring the novel cyclization reactions of 4-chloroazodienes with electron rich olefins we developed a new and general synthesis of substituted 3-phenypyridazines. A number of these analogs were found to exhibit bleaching herbicidal activity (phytoene desaturase inhibition). Further methodology development coupled with analog synthesis led to the preparation of 3-heteroaryloxy and 3-aryloxypyridazines with increased unit activity and selectivity as well as good environmental properties. These compounds were found to be more active than current commercial standards on a number of important weed species with selectivity in corn in the US and small grains in Europe. Greenhouse activity of the most active analogs ranged from 17–140 g/hectare on important narrow-leaf species.
Synthesis, structure and physical properties of GdCu4Al and GdCu4Ga

Abstract Two non-stoichiometric Gd compounds, GdCu5−xTrx (Tr=Al, Ga) have been synthesized from the corresponding elements by high temperature reactions in sealed tantalum containers. They crystallize in the hexagonal CaCu5-type (Pearson's symbol hP6, space group P6/mmm, No. 191) with lattice parameters determined from single-crystal X-ray diffraction at room temperature as follows: a=5.0831(10) A; c=4.156(2) A for GdCu3.98(4)Al1.02(4), and a=5.1025(10) A; c=4.155(2) A for GdCu3.9(1)Ga1.1(1), respectively. Structure refinements from single crystal X-ray diffraction data reveal that substitution of Cu for Al or Ga takes place preferably on one of the two transition metal sites with site symmetry mmm (3g). Both compounds order antiferromagnetically below ∼40 K and ∼36 K, respectively, as determined from temperature dependent dc-magnetization, resistivity and heat-capacity measurements.
The acetolysis of 2‐acetoxyalkyltellurium trihalides

The reaction of six 2-acetoxyalkyltellurium trihalides in refluxing dry acetic acid yields haloacetates in addition to the previously observed diacetates. The haloacetates are formed either through direct cleavage of the carbon–tellurium bond with retention of configuration or through initial formation of a neighboring group intermediate that is subsequently attacked by halide ion. Added lithium acetate leads to an increase in SN2 attack on the tellurium carbon. © 1998 John Wiley & Sons, Inc. Heteroatom Chem 9:85–93, 1998
Electronic Structure of Tantalum Oxynitride Perovskite Photocatalysts

The tantalum oxynitride perovskites ATaO2N (A = Ca, Sr, and Ba) and PrTaON2 are promising candidates for the photocatalytic splitting of water under illumination with visible light. A combination o...
Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport

Classical supervised learning produces unreliable models when training and target distributions differ, with most existing solutions requiring samples from the target domain. We propose a proactive approach which learns a relationship in the training domain that will generalize to the target domain by incorporating prior knowledge of aspects of the data generating process that are expected to differ as expressed in a causal selection diagram. Specifically, we remove variables generated by unstable mechanisms from the joint factorization to yield the Surgery Estimator---an interventional distribution that is invariant to the differences across environments. We prove that the surgery estimator finds stable relationships in strictly more scenarios than previous approaches which only consider conditional relationships, and demonstrate this in simulated experiments. We also evaluate on real world data for which the true causal diagram is unknown, performing competitively against entirely data-driven approaches.
Total synthesis of cystothiazoles A and C.

An efficient pathway culminating in the enantiocontrolled preparation of cystothiazoles A and C has been described. The cystothiazoles demonstrate potent antifungal activity and function as novel inhibitors of mitochondrial oxidation at a specific site on the cytochrome bc1 complex. These studies outline a general and flexible plan that can be readily adapted for the synthesis of a variety of related five-membered heterocyclic systems and for biological investigations of structure−activity relationships. The core [2,4‘]bisthiazole component 8 was prepared in six steps, and the use of the Horner−Emmons olefination to yield the α,β-unsaturated ester 10 set the stage for an asymmetric Evans aldol process, which established the required C4/C5 stereochemistry. Finally the cystothiazoles A and C were prepared via a stereocontrolled O-alkylation of the precursor β-keto esters 22a and 22b.
Synthesis and Regioselective Ribosylation of 6,7-Dichloroimidazo[4,5-b]quinolin-2-one

The polyhalogenated benzimidazole nucleosides 2,5,6-trichloro-1-(β-d-ribofuranosyl)benzimidazole (TCRB) and the 2-bromo analogue (BDCRB) were synthesized in our laboratory and established as potent and selective antiviral agents against human cytomegalovirus (HCMV) with a novel mode of action. In an effort to study the behavior of the key substructure of these analogues in a dimensionally stretched-out manner and probe the spatial limitation of the target enzyme(s), a series of N1- and N3-ribonucleosides of imidazo[4,5-b]quinolines were designed as linear dimensional analogues. The nucleosides 6,7-dichloro-1-(β-d-ribofuranosyl)imidazo[4,5-b]quinolin-2-one and 6,7-dichloro-3-(β-d-ribofuranosyl)imidazo[4,5-b]quinolin-2-one were selected and prepared as the key intermediates in this study. During this study, a novel photoassisted annulation was developed for the synthesis of 6,7-dichloroimidazo[4,5-b]quinolin-2-one, which overcame several problems that were encountered with the literature annulation method. ...
Reading Profiles in Multi-Site Data With Missingness

Children with reading disability exhibit varied deficits in reading and cognitive abilities that contribute to their reading comprehension problems. Some children exhibit primary deficits in phonological processing, while others can exhibit deficits in oral language and executive functions that affect comprehension. This behavioral heterogeneity is problematic when missing data prevent the characterization of different reading profiles, which often occurs in retrospective data sharing initiatives without coordinated data collection. Here we show that reading profiles can be reliably identified based on Random Forest classification of incomplete behavioral datasets, after the missForest method is used to multiply impute missing values. Results from simulation analyses showed that reading profiles could be accurately classified across degrees of missingness (e.g., ~5% classification error for 30% missingness across the sample). The application of missForest to a real multi-site dataset (n = 924) showed that reading disability profiles significantly and consistently differed in reading and cognitive abilities for cases with and without missing data. The results of validation analyses indicated that the reading profiles (cases with and without missing data) exhibited significant differences for an independent set of behavioral variables that were not used to classify reading profiles. Together, the results show how multiple imputation can be applied to the classification of cases with missing data and can increase the integrity of results from multi-site open access datasets.
Microwave-assisted cyclocondensation of hydrazine derivatives with alkyl dihalides or ditosylates in aqueous media: syntheses of pyrazole, pyrazolidine and phthalazine derivatives

Abstract Direct syntheses of 4,5-dihydro-pyrazole, pyrazolidine, and 1,2-dihydro-phthalazine derivatives via double-alkylation of hydrazines by alkyl dihalides or ditosylates were accomplished in aqueous media under microwave irradiation conditions; the environmentally friendlier chemical transformation occurred in a single step and eliminated the use of expensive metal catalysts in building two C–N bonds.
Experimental Investigation of Direct Contact Baseplate Cooling for Electric Vehicle Power Electronics

An experimental setup has been built to investigate the thermo-hydraulic performance of the direct contact baseplate cooling technique for power electronics in electric vehicles, to improve the design and to validate the modelling of this technique. The setup consists of an electrical heater to emulate the heat dissipation of the power electronics and which is cooled by a 60/40% mixture by mass of water-glycol. It is equipped with a flow rate sensor, absolute and differential pressure sensors and temperature measurements at the inlet, outlet and baseplate over the channel length, to determine the performance parameters used in the comparison: thermal resistance and pumping power. Three fluid inlet temperatures, four power levels and four flow rates have been tested for three channel heights (1.5mm, 3mm and 7.6mm). Increasing the fluid temperature and/or heating power, results in a lower thermal resistance and pumping power, due to a lower viscosity of the fluid. The performance of the 1.5mm and 7.6mm channel was found to be quite similar, while the 3mm channel results on average in a 5.8% lower thermal resistance compared to the other two channel heights. The heat transfer in terms of the Nusselt number was also evaluated in function of the Reynolds number. By analyzing the hydraulic and thermal entrance lengths it could be concluded that the flow in all measurements is simultaneously developing. A comparison with two correlations from scientific literature for simultaneously developing flow did not show a good agreement, possibly due to the specific inlet and outlet effect, which is more pronounced for a bigger channel height than a smaller channel height.
Satisficing in Multi-Armed Bandit Problems

Satisficing is a relaxation of maximizing and allows for less risky decision making in the face of uncertainty. We propose two sets of satisficing objectives for the multi-armed bandit problem, where the objective is to achieve reward-based decision-making performance above a given threshold. We show that these new problems are equivalent to various standard multi-armed bandit problems with maximizing objectives and use the equivalence to find bounds on performance. The different objectives can result in qualitatively different behavior; for example, agents explore their options continually in one case and only a finite number of times in another. For the case of Gaussian rewards we show an additional equivalence between the two sets of satisficing objectives that allows algorithms developed for one set to be applied to the other. We then develop variants of the Upper Credible Limit (UCL) algorithm that solve the problems with satisficing objectives and show that these modified UCL algorithms achieve efficient satisficing performance.
Tailored porous electrode resistance for controlling electrolyte depletion and improving charging response in electrochemical systems

Abstract The rapid charging and/or discharging of electrochemical cells can lead to localized depletion of electrolyte concentration. This depletion can significantly impact the system's time dependent resistance. For systems with porous electrodes, electrolyte depletion can limit the rate of charging and increase energy dissipation. Here we propose a theory to control and avoid electrolyte depletion by tailoring the value and spatial distribution of resistance in a porous electrode. We explore the somewhat counterintuitive idea that increasing local spatial resistances of the solid electrode itself leads to improved charging rate and minimal change in energy loss. We analytically derive a simple expression for an electrode matrix resistance profile that leads to highly uniform electrolyte depletion. We use numerical simulations to explore this theory and simulate spatiotemporal dynamics of electrolyte concentration in the case of a supercapacitor with various tailored electrode matrix resistance profiles which avoid localized depletion. This increases charging rate up to ∼ 2 -fold with minimal effect on overall dissipated energy in the system.
Cohomology of flag varieties and the Brylinski–Kostant filtration

Let G be a reductive algebraic group over C and let N be a G-module. For any subspace M of N, the Brylinski–Kostant filtration on M is defined through the action of a principal nilpotent element in LieG. This filtration is related to a q-analog of weight multiplicity due to Lusztig. We generalize this filtration to other nilpotent elements and show that this generalized filtration is related to “parabolic” versions of Lusztig's q-analog of weight multiplicity. Along the way we also generalize results of Broer on cohomology vanishing of bundles on cotangent bundles of partial flag varieties. We conclude by computing some explicit examples.
The neural hawkes process: a neurally self-modulating multivariate point process

Many events occur in the world. Some event types are stochastically excited or inhibitedߞin the sense of having their probabilities elevated or decreasedߞby patterns in the sequence of previous events. Discovering such patterns can help us predict which type of event will happen next and when. We model streams of discrete events in continuous time, by constructing a neurally self-modulating multivariate point process in which the intensities of multiple event types evolve according to a novel continuous-time LSTM. This generative model allows past events to influence the future in complex and realistic ways, by conditioning future event intensities on the hidden state of a recurrent neural network that has consumed the stream of past events. Our model has desirable qualitative properties. It achieves competitive likelihood and predictive accuracy on real and synthetic datasets, including under missing-data conditions.
An asymptotic equipartition property for measures on model spaces

Let $G$ be a sofic group, and let $\Sigma = (\sigma_n)_{n\geq 1}$ be a sofic approximation to it. For a probability-preserving $G$-system, a variant of the sofic entropy relative to $\Sigma$ has recently been defined in terms of sequences of measures on its model spaces that `converge' to the system in a certain sense. Here we prove that, in order to study this notion, one may restrict attention to those sequences that have the asymptotic equipartition property. This may be seen as a relative of the Shannon--McMillan theorem in the sofic setting. We also give some first applications of this result, including a new formula for the sofic entropy of a $(G\times H)$-system obtained by co-induction from a $G$-system, where $H$ is any other infinite sofic group.
Articulated pose estimation using hierarchical exemplar-based models

Exemplar-based models have achieved great success on localizing the parts of semi-rigid objects. However, their efficacy on highly articulated objects such as humans is yet to be explored. Inspired by hierarchical object representation and recent application of Deep Convolutional Neural Networks (DCNNs) on human pose estimation, we propose a novel formulation that incorporates both hierarchical exemplar-based models and DCNNs in the spatial terms. Specifically, we obtain more expressive spatial models by assuming independence between exemplars at different levels in the hierarchy; we also obtain stronger spatial constraints by inferring the spatial relations between parts at the same level. As our method strikes a good balance between expressiveness and strength of spatial models, it is both effective and generalizable, achieving state-of-the-art results on different benchmarks: Leeds Sports Dataset and CUB-200-2011.
Gravitational waves and their memory in general relativity

General relativity explains gravitational radiation from binary black hole or neutron star mergers, from core-collapse supernovae and even from the inflation period in cosmology. These waves exhibit a unique effect called memory or Christodoulou effect, which in a detector like LIGO or LISA shows as a permanent displacement of test masses and in radio telescopes like NANOGrav as a change in the frequency of pulsars' pulses. It was shown that electromagnetic fields and neutrino radiation enlarge the memory. Recently it has been understood that the two types of memory addressed in the literature as `linear' and `nonlinear' are in fact two different phenomena. The former is due to fields that do not and the latter is due to fields that do reach null infinity.
Approximate hierarchical clustering via sparsest cut and spreading metrics

Dasgupta recently introduced a cost function for the hierarchical clustering of a set of points given pairwise similarities between them. He showed that this function is NP-hard to optimize, but a top-down recursive partitioning heuristic based on an αn-approximation algorithm for uniform sparsest cut gives an approximation of O(αn log n) (the current best algorithm has [EQUATION]. We show that the aforementioned sparsest cut heuristic in fact obtains an O(αn)-approximation. The algorithm also applies to a generalized cost function studied by Dasgupta. Moreover, we obtain a strong inapproximability result, showing that the Hierarchical Clustering objective is hard to approximate to within any constant factor assuming the Small-Set Expansion (SSE) Hypothesis. Finally, we discuss approximation algorithms based on convex relaxations. We present a spreading metric SDP relaxation for the problem and show that it has integrality gap at most [EQUATION]. The advantage of the SDP relative to the sparsest cut heuristic is that it provides an explicit lower bound on the optimal solution and could potentially yield an even better approximation for hierarchical clustering. In fact our analysis of this SDP served as the inspiration for our improved analysis of the sparsest cut heuristic. We also show that a spreading metric LP relaxation gives an O(log n)-approximation.
Automatic Annotation of Structured Facts in Images

Motivated by the application of fact-level image understanding, we present an automatic method for data collection of structured visual facts from images with captions. Example structured facts include attributed objects (e.g., ), actions (e.g., ), interactions (e.g., ), and positional information (e.g., ). The collected annotations are in the form of fact-image pairs (e.g., and an image region containing this fact). With a language approach, the proposed method is able to collect hundreds of thousands of visual fact annotations with accuracy of 83% according to human judgment. Our method automatically collected more than 380,000 visual fact annotations and more than 110,000 unique visual facts from images with captions and localized them in images in less than one day of processing time on standard CPU platforms. We will make the data publically available.
Uniqueness of gradient Ricci solitons

We show that a three-dimensional steady gradient Ricci soliton which is asymptotic to the Bryant soliton in a suitable sense must be isometric to the Bryant soliton.
Global solutions of the gravity-capillary water-wave system in three dimensions

In this paper we prove global regularity for the full water-wave system in three dimensions for small data, under the influence of both gravity and surface tension. This problem presents essential difficulties which were absent in all of the earlier global regularity results for other water-wave models. To construct global solutions, we use a combination of energy estimates and matching dispersive estimates. There is a significant new difficulty in proving energy estimates in our problem, namely the combination of slow pointwise decay of solutions (no better than ${\lvert t \rvert}^{- 5/6}$) and the presence of a large, codimension-$1$, set of quadratic time-resonances. To deal with such a situation, we propose here a new mechanism, which exploits a non-degeneracy property of the time-resonant hypersurfaces and some special structure of the quadratic part of the non-linearity, connected to the conserved energy of the system. The dispersive estimates rely on analysis of the Duhamel formula in the Fourier space. The main contributions come from the set of space-time resonances, which is a large set of dimension $1$. To control the corresponding bilinear interactions, we use harmonic analysis techniques, such as orthogonality arguments in the Fourier space and atomic decompositions of functions. Most importantly, we construct and use a refined norm which is well adapted to the geometry of the problem.
Local Algorithms for Block Models with Side Information

There has been a recent interest in understanding the power of local algorithms for optimization and inference problems on sparse graphs. Gamarnik and Sudan (2014) showed that local algorithms are weaker than global algorithms for finding large independent sets in sparse random regular graphs thus refuting a conjecture by Hatami, Lovasz, and Szegedy (2012). Montanari (2015) showed that local algorithms are suboptimal for finding a community with high connectivityin the sparse Erdos-Renyi random graphs. For the symmetric planted partition problem (also named community detection for the block models) on sparse graphs, a simple observation is that local algorithms cannot have non-trivial performance.In this work we consider the effect of side information on local algorithms for community detection under the binary symmetric stochastic block model. In the block model with side information each of the n vertices is labeled + or - independently and uniformly at random; each pair of vertices is connected independently with probability a/n if both of them have the same label or b/n otherwise. The goal is to estimate the underlying vertex labeling given 1) the graph structure and 2) side information in the form of a vertex labeling positively correlated with the true one. Assuming that the ratio between in and out degree a/b is θ(1) and the average degree (a+b) / 2 = n{o(1), we show that a local algorithm, namely, belief propagation run on the local neighborhoods, maximizes the expected fraction of vertices labeled correctly in the following three regimes: |a--b| C (a+b) for some constant C and all 0
On Atkin and Swinnerton-Dyer congruence relations (3)

It is now well known that Hecke operators defined classically act trivially on genuine cuspforms for noncongruence subgroups of SL2(Z). Atkin and Swinnerton-Dyer speculated the existence of p-adic Hecke operators so that the Fourier coefficients of their eigenfunctions satisfy three-term congruence recursions. In the previous two papers with the same title ([W.C. Li, L. Long, Z. Yang, On Atkin and Swinnerton-Dyer congruence relations, J. Number Theory 113 (1) (2005) 117–148] by W.C. Li, L. Long, Z. Yang and [A.O.L. Atkin, W.C. Li, L. Long, On Atkin and Swinnerton-Dyer congruence relations (2), Math. Ann. 340 (2) (2008) 335–358] by A.O.L. Atkin, W.C. Li, L. Long), the authors have studied two exceptional spaces of noncongruence cuspforms where almost all p-adic Hecke operators can be diagonalized simultaneously or semi-simultaneously. Moreover, it is shown that the l-adic Scholl representations attached to these spaces are modular in the sense that they are isomorphic, up to semisimplification, to the l-adic representations arising from classical automorphic forms. In this paper, we study an infinite family of spaces of noncongruence cuspforms (which includes the cases in [W.C. Li, L. Long, Z. Yang, On Atkin and Swinnerton-Dyer congruence relations, J. Number Theory 113 (1) (2005) 117–148; A.O.L. Atkin, W.C. Li, L. Long, On Atkin and Swinnerton-Dyer congruence relations (2), Math. Ann. 340 (2) (2008) 335–358]) under a general setting. It is shown that for each space in this family there exists a fixed basis so that the Fourier coefficients of each basis element satisfy certain weaker three-term congruence recursions. For a new case in this family, we will exhibit that the attached l-adic Scholl representations are modular and the p-adic Hecke operators can be diagonalized semi-simultaneously.
One-Shot Learning for Semantic Segmentation

Low-shot learning methods for image classification support learning from sparse data. We extend these techniques to support dense semantic image segmentation. Specifically, we train a network that, given a small set of annotated images, produces parameters for a Fully Convolutional Network (FCN). We use this FCN to perform dense pixel-level prediction on a test image for the new semantic class. Our architecture shows a 25% relative meanIoU improvement compared to the best baseline methods for one-shot segmentation on unseen classes in the PASCAL VOC 2012 dataset and is at least 3 times faster.
Number Variance of Random Zeros on Complex Manifolds, II: Smooth Statistics

We consider the zero sets $Z_N$ of systems of $m$ random polynomials of degree $N$ in $m$ complex variables, and we give asymptotic formulas for the random variables given by summing a smooth test function over $Z_N$. Our asymptotic formulas show that the variances for these smooth statistics have the growth $N^{m-2}$. We also prove analogues for the integrals of smooth test forms over the subvarieties defined by $k<m$ random polynomials. Such linear statistics of random zero sets are smooth analogues of the random variables given by counting the number of zeros in an open set, which we proved elsewhere to have variances of order $N^{m-1/2}$. We use the variance asymptotics and off-diagonal estimates of Szego kernels to extend an asymptotic normality result of Sodin-Tsirelson to the case of smooth linear statistics for zero sets of codimension one in any dimension $m$.
Exact prior‐free probabilistic inference in a class of non‐regular models

Standard statistical methods, such as maximum likelihood, are often justified based on their asymptotic properties. For suitably regular models, this theory is standard, but when the model is non-regular, for example, the support depends on the parameter, these asymptotic properties may be difficult to assess. Recently, an inferential model (IM) framework has been developed that provides valid prior-free probabilistic inference without the need for asymptotic justification. In this paper, we construct an IM for a class of highly non-regular models with parameter-dependent support. This construction requires conditioning, which is facilitated through solving a particular differential equation. We prove that the plausibility intervals derived from this IM are exact, and we demonstrate, via simulations, that their exactness does not come at the cost of loss of efficiency. Copyright © 2016 John Wiley & Sons, Ltd.
A general framework for pairs trading with a control-theoretic point of view

Pairs trading is a market-neutral strategy that exploits historical correlation between stocks to achieve statistical arbitrage. Existing pairs-trading algorithms in the literature require rather restrictive assumptions on the underlying stochastic stock-price processes and the so-called spread function. In contrast to existing literature, we consider an algorithm for pairs trading which requires less restrictive assumptions than heretofore considered. Since our point of view is control-theoretic in nature, the analysis and results are straightforward to follow by a non-expert in finance. To this end, we describe a general pairs-trading algorithm which allows the user to define a rather arbitrary spread function which is used in a feedback context to modify the investment levels dynamically over time. When this function, in combination with the price process, satisfies a certain mean-reversion condition, we deem the stocks to be a tradeable pair. For such a case, we prove that our control-inspired trading algorithm results in positive expected growth in account value. Finally, we describe tests of our algorithm on historical trading data by fitting stock price pairs to a popular spread function used in literature. Simulation results from these tests demonstrate robust growth while avoiding huge drawdowns.
Recovering a tree from the lengths of subtrees spanned by a randomly chosen sequence of leaves

Given an edge-weighted tree T with n leaves, sample the leaves uniformly at random without replacement and let Wk , 2 ≤ k ≤ n, be the length of the subtree spanned by the first k leaves. We consider the question, "Can T be identified (up to isomorphism) by the joint probability distribution of the random vector (W2, …, Wn )?" We show that if T is known a priori to belong to one of various families of edge-weighted trees, then the answer is, "Yes." These families include the edge-weighted trees with edge-weights in general position, the ultrametric edge-weighted trees, and certain families with equal weights on all edges such as (k + 1)-valent and rooted k-ary trees for k ≥ 2 and caterpillars.
Synthesizing Training Data for Object Detection in Indoor Scenes.

Detection of objects in cluttered indoor environments is one of the key enabling functionalities for service robots. The best performing object detection approaches in computer vision exploit deep Convolutional Neural Networks (CNN) to simultaneously detect and categorize the objects of interest in cluttered scenes. Training of such models typically requires large amounts of annotated training data which is time consuming and costly to obtain. In this work we explore the ability of using synthetically generated composite images for training state-of-the-art object detectors, especially for object instance detection. We superimpose 2D images of textured object models into images of real environments at variety of locations and scales. Our experiments evaluate different superimposition strategies ranging from purely image-based blending all the way to depth and semantics informed positioning of the object models into real scenes. We demonstrate the effectiveness of these object detector training strategies on two publicly available datasets, the GMU-Kitchens and the Washington RGB-D Scenes v2. As one observation, augmenting some hand-labeled training data with synthetic examples carefully composed onto scenes yields object detectors with comparable performance to using much more hand-labeled data. Broadly, this work charts new opportunities for training detectors for new objects by exploiting existing object model repositories in either a purely automatic fashion or with only a very small number of human-annotated examples.
Some minimal rings related to 2-primal rings

In a paper on the taxonomy of 2-primal rings, examples of various types of rings that are related to commutativity such as reduced, symmetric, duo, reversible and PS I were given in order t...
Pragmatically Informative Image Captioning with Character-Level Inference

We combine a neural image captioner with a Rational Speech Acts (RSA) model to make a system that is pragmatically informative: its objective is to produce captions that are not merely true but also distinguish their inputs from similar images. Previous attempts to combine RSA with neural image captioning require an inference which normalizes over the entire set of possible utterances. This poses a serious problem of efficiency, previously solved by sampling a small subset of possible utterances. We instead solve this problem by implementing a version of RSA which operates at the level of characters (“a”, “b”, “c”, ...) during the unrolling of the caption. We find that the utterance-level effect of referential captions can be obtained with only character-level decisions. Finally, we introduce an automatic method for testing the performance of pragmatic speaker models, and show that our model outperforms a non-pragmatic baseline as well as a word-level RSA captioner.
An investigation on partitions with equal products

An ordered triple (s,p,n) is called admissible if there exist two different multisets X = {x1,x2,…,xn} and Y = {y1,y2,…,yn} such that X and Y share the same sum s, the same product p, and the same ...
Hardy inequalities for fractional integrals on general domains

Abstract We prove a sharp Hardy inequality for fractional integrals for functions that are supported in a general domain. The constant is the same as the one for the half-space and hence our result settles a recent conjecture of Bogdan and Dyda.
Dynamic matrix factorization with social influence

Matrix factorization is a key component of collaborative filtering-based recommendation systems because it allows us to complete sparse user-by-item ratings matrices under a low-rank assumption that encodes the belief that similar users give similar ratings and that similar items garner similar ratings. This paradigm has had immeasurable practical success, but it is not the complete story for understanding and inferring the preferences of people. First, peoples' preferences and their observable manifestations as ratings evolve over time along general patterns of trajectories. Second, an individual person's preferences evolve over time through influence of their social connections. In this paper, we develop a unified process model for both types of dynamics within a state space approach, together with an efficient optimization scheme for estimation within that model. The model combines elements from recent developments in dynamic matrix factorization, opinion dynamics and social learning, and trust-based recommendation. The estimation builds upon recent advances in numerical nonlinear optimization. Empirical results on a large-scale data set from the Epinions website demonstrate consistent reduction in root mean squared error by consideration of the two types of dynamics.
Analysis of CSAT Performance in Wi-Fi and LTE-U Coexistence

In this paper, we study energy-based Carrier Sense Adaptive Transmission (CSAT) for use with LTE-U and investigate the performance in Wi-Fi/LTE-U coexistence using theoretical analysis and experimental verification using NI USRPs. According to the LTE-U forum specification, if an LTE-U base station (BS) finds a vacant channel, it can transmit for up to 20 ms and turn OFF its transmission for only 1 ms, resulting in a maximum duty cycle of 95%. In a dense deployment of LTE-U and Wi-Fi, it is very likely that a Wi-Fi access point (AP) will wish to use the same channel. It will start transmission by trying to transmit association packets (using carrier sense multiple access with collision avoidance (CSMA/CA)) through the 1 ms LTE-U OFF duration. Since this duration is very small, it leads to increased association packet drops and thus delays the Wi-Fi association process. Once LTE-U, using CSAT, detects Wi-Fi, it should scale back the duty cycle to 50%. We demonstrate in this paper, using an experimental platform as well as theoretical analysis, that if LTE-U is using a 95% duty cycle, energy based CSAT will take a much longer time to scale back the duty cycle due to the beacon drops and delays in the reception. Hence, in order to maintain association fairness with Wi-Fi, we propose that a LTE-U BS should not transmit at maximum duty cycles (95%), even if the channel is sensed to be vacant.
Nonstandard braid relations and Chebyshev polynomials

Abstract A fundamental open problem in algebraic combinatorics is to find a positive combinatorial formula for Kronecker coefficients, which are multiplicities of the decomposition of the tensor product of two S r -irreducibles into irreducibles. Mulmuley and Sohoni attempt to solve this problem using canonical basis theory, by first constructing a nonstandard Hecke algebra B r , which, though not a Hopf algebra, is a u-analogue of the Hopf algebra C S r in some sense (where u is the Hecke algebra parameter). For r = 3 , we study this Hopf-like structure in detail. We define a nonstandard Hecke algebra H ˇ 3 ( k ) ⊆ H 3 ⊗ k , determine its irreducible representations over Q ( u ) , and show that it has a presentation with a nonstandard braid relation that involves Chebyshev polynomials evaluated at 1 u + u − 1 . We generalize this to Hecke algebras of dihedral groups. We go on to show that these nonstandard Hecke algebras have bases similar to the Kazhdan–Lusztig basis of H 3 and are cellular algebras in the sense of Graham and Lehrer.
Filtered models for reacting gas–particle flows

Using the kinetic-theory-based two-fluid models as a starting point, we develop filtered two-fluid models for a gas–particle flow in the presence of an isothermal, first-order, solid-catalyzed reaction of a gaseous species. As a consequence of the filtering procedure, terms describing the filtered reaction rate and filtered reactant dispersion need to be constituted in order to close the filtered species balance equation. In this work, a constitutive relation for filtered reaction rate is developed by performing fine-grid, two-fluid model simulations of an isothermal, solid-catalyzed, first-order reaction in a periodic domain. It is observed that the cluster-scale effectiveness factor, defined as the ratio between the reaction rate observed in a fine-grid simulation to that observed in a coarse-grid simulation, can be substantially smaller than unity, and it manifests an inverted bell shape dependence on filtered particle volume fraction in all simulation cases. Moreover, the magnitude of the deviation in the cluster-scale effectiveness factor from unity is a strong function of the meso-scale Thiele modulus and dimensionless filter size. Thus coarse-grid simulations of a reacting gas–particle flow will over-estimate the reaction rate if the cluster-scale effectiveness factor is not accounted for.
A Deterministic Protocol for Sequential Asymptotic Learning

In the classic herding model, agents receive private signals about an underlying binary state of nature, and act sequentially to choose one of two possible actions, after observing the actions of their predecessors. We investigate what types of behaviors lead to asymptotic learning, where agents will eventually converge to the right action in probability. It is known that for rational agents and bounded signals, there will not be asymptotic learning. Does it help if the agents can be cooperative rather than act selfishly? This is simple to achieve if the agents are allowed to use randomized protocols. In this paper, we provide the first deterministic protocol under which asymptotic learning occurs. In addition, our protocol has the advantage of being much simpler than previous protocols.
The motivic fundamental group of the punctured projective line

We describe a construction of an object associated to the fundamental group of the projective line minus three points in the Bloch-Kriz category of mixed Tate motives. This description involves Massey products of Steinberg symbols in the motivic cohomology of the ground field.
Learning Simplicial Complexes from Persistence Diagrams.

Topological Data Analysis (TDA) studies the shape of data. A common topological descriptor is the persistence diagram, which encodes topological features in a topological space at different scales. Turner, Mukeherjee, and Boyer showed that one can reconstruct a simplicial complex embedded in R^3 using persistence diagrams generated from all possible height filtrations (an uncountably infinite number of directions). In this paper, we present an algorithm for reconstructing plane graphs K=(V,E) in R^2 , i.e., a planar graph with vertices in general position and a straight-line embedding, from a quadratic number height filtrations and their respective persistence diagrams.
A fast amortized algorithm for computing quadratic Dirichlet L-functions

An algorithm to compute Dirichlet $L$-functions for many quadratic characters is derived. The algorithm is optimal (up to logarithmic factors) provided that the conductors of the characters under consideration span a dyadic window.
A short proof of the Kac–Ward formula

We present a new short proof of the Kac-Ward formula for the partition function of the Ising model on planar graphs.
Good formal structures for flat meromorphic connections, II: Excellent schemes

Given a flat meromorphic connection on an excellent scheme over a field of characteristic zero, we prove existence of good formal structures after blowing up; this extends a theorem of Mochizuki for algebraic varieties. The argument combines a numerical criterion for good formal structures from a previous paper, with an analysis based on the geometry of an associated valuation space (Riemann-Zariski space). We obtain a similar result over the formal completion of an excellent scheme along a closed subscheme. If we replace the excellent scheme by a complex analytic variety, we obtain a similar but weaker result in which the blowup can only be constructed in a small neighborhood of a prescribed point.
Experimental Demonstration of Efficient Spin–Orbit Torque Switching of an MTJ With Sub-100 ns Pulses

Efficient generation of spin currents from charge currents is of high importance for memory and logic applications of spintronics. In particular, generation of spin currents from charge currents in high spin–orbit coupling metals has the potential to provide a scalable solution for embedded memory. We demonstrate a net reduction in the critical charge current for spin torque-driven magnetization reversal via using spin–orbit mediated spin current generation. We scaled the dimensions of the spin–orbit electrode to 400 nm and the nanomagnet to 270 nm $\times68$ nm in a three-terminal spin–orbit torque, magnetic tunnel junction (SOT-MTJ) geometry. Our estimated effective spin Hall angle is 0.15–0.20 using the ratio of zero-temperature critical current from spin Hall switching and estimated spin current density for switching the magnet. We show bidirectional transient switching using spin–orbit generated spin torque at 100 ns switching pulses reliably followed by transient read operations. We finally compare the static and dynamic response of the SOT-MTJ with transient spin circuit modeling showing the performance of scaled SOT-MTJs to enable nanosecond class non-volatile MTJs.
Polynomial bounds for decoupling, with applications

Let f(x) = f(x1, ..., xn) = Σ|S|≤k aS IIi∈S xi be an n-variate real multilinear polynomial of degree at most k, where S ⊆ [n] = {1, 2, ..., n}. For its one-block decoupled version. [EQUATION] we show tail-bound comparisons of the form [EQUATION] Our constants Ck, Dk are significantly better than those known for "full decoupling". For example, when x, y, z are independent Gaussians we obtain Ck = Dk = O(k); when x, y, z are ±1 random variables we obtain Ck = O(k2), Dk = kO(k). By contrast, for full decoupling only Ck = Dk = kO(k) is known in these settings. We describe consequences of these results for query complexity (related to conjectures of Aaronson and Ambainis) and for analysis of Boolean functions (including an optimal sharpening of the DFKO Inequality).
Performance and programming effort trade-offs of android persistence frameworks

Abstract A fundamental building block of a mobile application is the ability to persist program data between different invocations. Referred to as persistence, this functionality is commonly implemented by means of persistence frameworks. Without a clear understanding of the energy consumption, execution time, and programming effort of popular Android persistence frameworks, mobile developers lack guidelines for selecting frameworks for their applications. To bridge this knowledge gap, we report on the results of a systematic study of the performance and programming effort trade-offs of eight Android persistence frameworks, and provide practical recommendations for mobile application developers.
Social Systems: Can we Do More Than Just Poke Friends?

Social sites have become extremely popular among users but have they attracted equal attention from the research community? Are they good only for simple tasks, such as tagging and poking friends? Do they present any new or interesting research challenges? In this paper, we describe the insights we have obtained implementing CourseRank, a course evaluation and planning social system. We argue that more attention should be given to social sites like ours and that there are many challenges (though not the traditional DBMS ones) that should be addressed by our community.
An Axiomatic Study of Scoring Rule Markets

Prediction markets are well-studied in the case where predictions are probabilities or expectations of future random variables. In 2008, Lambert, et al. proposed a generalization, which we call "scoring rule markets" (SRMs), in which traders predict the value of arbitrary statistics of the random variables, provided these statistics can be elicited by a scoring rule. Surprisingly, despite active recent work on prediction markets, there has not yet been any investigation into more general SRMs. To initiate such a study, we ask the following question: in what sense are SRMs "markets"? We classify SRMs according to several axioms that capture potentially desirable qualities of a market, such as the ability to freely exchange goods (contracts) for money. Not all SRMs satisfy our axioms: once a contract is purchased in any market for prediction the median of some variable, there will not necessarily be any way to sell that contract back, even in a very weak sense. Our main result is a characterization showing that slight generalizations of cost-function-based markets are the only markets to satisfy all of our axioms for finite-outcome random variables. Nonetheless, we find that several SRMs satisfy weaker versions of our axioms, including a novel share-based market mechanism for ratios of expected values.
Preserving Randomness for Adaptive Algorithms

Suppose Est is a randomized estimation algorithm that uses n random bits and outputs values in R^d. We show how to execute Est on k adaptively chosen inputs using only n + O(k log(d + 1)) random bits instead of the trivial nk (at the cost of mild increases in the error and failure probability). Our algorithm combines a variant of the INW pseudorandom generator [Impagliazzo et al., 1994] with a new scheme for shifting and rounding the outputs of Est. We prove that modifying the outputs of Est is necessary in this setting, and furthermore, our algorithm's randomness complexity is near-optimal in the case d {-1, 1} using O(n log n) * poly(1/theta) queries to F and O(n) random bits (independent of theta), improving previous work by Bshouty et al. [Bshouty et al., 2004].