cssi/SciSciGPT-SciSciNet huggingface dataset:
Catalytic enantioselective oxidation of sulfides and disulfides by a chiral complex of bis-hydroxamic acid and molybdenum

Abstract A chiral bis-hydroxamic acid (BHA)-molybdenum complex was used for the catalytic asymmetric oxidation of sulfides and disulfides utilizing one equivalent of alkyl peroxide with yields up to 83% and ee up to 86%. An extension of our methodology combines the asymmetric oxidation with kinetic resolution providing excellent enantioselectivity (ee 92–99%).
A new approach for the synthesis of (±)-trans-10,11-dihydroxy-5,6,6a,7,8,12b-hexahydrobenzo[a]phenanthridine (dihydrexidine)

Abstract A novel method is reported for the synthesis of (±)-trans-10,11-dihydroxy-5,6,6a,7,8,12b-hexahydrobenzo[a]phenanthridine (dihydrexidine, 6b ) employing as a key step the cyclization of the acid chloride of 3b , via decarbonylation, to the hexahydrobenzo[a]phenanthridine 4b .
Vanadium-catalyzed selective aerobic alcohol oxidation in ionic liquid [bmim]PF6

Abstract A selective aerobic oxidation of alcohols into the corresponding aldehydes or ketones was developed by using two-component system VO(acac)2/DABCO in the ionic liquid [bmim]PF6, and the catalysts can be recycled and reused for three runs without any significant loss of catalytic activity.
Magnetic Resonance Study of a Series of Phosphorus-Containing Zintl Compounds: Ca14AlP11, Ca14MnP11, and Eu14MnP11

The compounds Ca14AlP11, Ca14MnP11, and Eu14MnP11 have been synthesized and are isostructural to the Zintl compound, Ca14AlSb11. Eu14MnP11 is a ferromagnet showing colossal magnetoresistance at TC = 52 K, Ca14MnP11 shows paramagnetic behavior down to 5 K, and Ca14AlP11 is nonmagnetic. The formula unit for these Zintl compounds is A14MPn11 and comprises 14 A cations, a MPn4 tetrahedron, four isolated Pn anions, and a Pn3 linear unit. The central Pn of the Pn3 unit is believed to be positionally disordered, and it has been speculated that the disorder is static rather than dynamic. To address this issue, 31P solid-state NMR was applied to these new compounds to provide insight into the magnetic ordering and structural changes. The NMR chemical shift anisotropy and the dipolar coupling for the 31P nuclei as well as the quadrupolar coupling for the 27Al nucleus in the diamagnetic compound Ca14AlP11 provide structural details consistent with the Zintl structure. Wide-line 31P NMR and EPR were applied to the pa...
Intramolecular photocyclizations of amino ketones to form fused and bridged bicyclic amines

Abstract The irradiation of cyclic aminoketones produces bicyclic amines derived from intramolecular electron transfer followed by cyclization.
Phosphine-catalyzed asymmetric synthesis of β-lactones from disubstituted ketenes and aldehydes.

In this article we describe a general catalytic procedure for the formation of β-lactones bearing two stereogenic centers, from disubstituted ketenes and achiral aldehydes. BINAPHANE was found to display excellent enantioselectivity (≥90% ee for eight examples) and good diastereoselectivity (≥90:10 for 13 examples) in catalyzing the formation of β-lactones bearing two stereogenic centers from achiral aldehydes (both aromatic and aliphatic) and alkylarylketenes or dialkylketenes. A preference for formation of the trans diastereomer was observed in these reactions. For those reactions where BINAPHANE failed as a catalyst, tri-n-butylphosphine was found to be an effective achiral nucleophilic catalyst, effecting good yield and diastereoselectivity in racemic β-lactone formation. Evidence for the involvement of phosphonium enolate intermediates in the reaction mechanism was obtained through reaction monitoring by 31P NMR spectroscopy and by comparison with previously characterized intermediates observed in th...
Capn5 Expression in the Healthy and Regenerating Zebrafish Retina.

Purpose Autosomal dominant neovascular inflammatory vitreoretinopathy (ADNIV) is a devastating inherited autoimmune disease of the eye that displays features commonly seen in other eye diseases, such as retinitis pigmentosa and diabetic retinopathy. ADNIV is caused by a gain-of-function mutation in Calpain-5 (CAPN5), a calcium-dependent cysteine protease. Very little is known about the normal function of CAPN5 in the adult retina, and there are conflicting results regarding its role during mammalian embryonic development. The zebrafish (Danio rerio) is an excellent animal model for studying vertebrate development and tissue regeneration, and represents a novel model to explore the function of Capn5 in the eye. Methods We characterized the expression of Capn5 in the developing zebrafish central nervous system (CNS) and retina, in the adult zebrafish retina, and in response to photoreceptor degeneration and regeneration using whole-mount in situ hybridization, FISH, and immunohistochemistry. Results In zebrafish, capn5 is strongly expressed in the developing embryonic brain, early optic vesicles, and in newly differentiated retinal photoreceptors. We found that expression of capn5 colocalized with cone-specific markers in the adult zebrafish retina. We observed an increase in expression of Capn5 in a zebrafish model of chronic rod photoreceptor degeneration and regeneration. Acute light damage to the zebrafish retina was accompanied by an increase in expression of Capn5 in the surviving cones and in a subset of Muller glia. Conclusions These studies suggest that Capn5 may play a role in CNS development, photoreceptor maintenance, and photoreceptor regeneration.
Structure-activity relationships among 2-substituted 5,6-dichloro-, 4,6-dichloro-, and 4,5-dichloro-1-[(2-hydroxyethoxy) methyl]- and -1-[(1,3-dihydroxy-2-propoxy) methyl]benzimidazoles.

The sodium salt of 2,5,6-trichlorobenzimidazole (8a) was condensed with [2-(benzyloxy)ethoxy]-methyl chloride (9) and [1,3-bis(benzyloxy)-2-propoxy]methyl chloride (18) to provide the corresponding protected acyclic nucleosides 10a and 19a, which on debenzylation afforded 2,5,6-trichloro-1-[(2-hydroxyethoxy)methyl]benzimidazole (11a) and 2,5,6-trichloro-1-[(1,3-dihydroxy-2-propoxy)methyl] benzimidazole (20a), respectively. A similar condensation of 2,4,6-trichlorobenzimidazole (2a) and 2,4,5-trichlorobenzimidazole (7a) followed by debenzylation yielded 11b, 20b, 11c, and 20c, respectively. A nucleophilic displacement of the 2-chloro group of 11a-c and 20a-c with liquid ammonia, methylamine, dimethylamine, and thiourea furnished several interesting 2-substituted compounds in good yields, e.g., 12-14(a-e), 21-23(a-e), 15-17, and 24-26. Alkylation of the 2-thio analogs 15-17 and 24-26 with benzyl chloride furnished the 2-alkylthio acyclic nucleosides 12d-14d and 21d-23d. Desulfurization of 15 and 24 with Raney Ni furnished 5,6-dichloro-1[(2-hydroxyethoxy)methyl]benzimidazole (12e) and 5,6-dichloro-1-[1,3-dihydroxy-2-propoxy)methyl]benzimidazole (21e), respectively (acyclic analog of 5,6-dichloro-1-beta-D-ribofuranosylbenzimidazole). Similarly the dihalo compounds 13e, 14e, and 23e were prepared in moderate yields from the 2-thio analogs 16,17, and 26. Treatment of 2-bromo-5,6-dichlorobenzimidazole (8b) with 27 and 30 gave the protected acyclic compounds 28a and 31a, which on deacetylation with sodium carbonate and potassium cyanide yielded 2-bromo-5,6-dichloro-1-[(2-hydroxyethoxy)methyl]benzimidazole (29a) and 2-bromo-5,6-dichloro-1-[(1,3-dihydroxy-2-propoxy)methyl]benzimidazole (32a), respectively, in moderate yields. The 2-bromo-4,6-dichlorobenzimidazole and 2-bromo-,5-dichlorbenzimidazole analogs 29b,c and 32b,c were prepared in a similar manner. Compounds were tested for activity against human cytomegalovirus (HCMV) and herpes simplex virus type 1 (HSV-1) and for cytotoxicity. In marked contrast to the ribosylbenzimidazoles, none of the acyclic analogs were specific and potent inhibitors of HCMV. Only the 2-thiobenzyl analogs 12d, 13d, 14d, and 23d and the 2-Br analogs 32a,b were active, but activity was not well separated from cytotoxicity. The lack of specific and potent antiviral activity strongly suggests that these acyclic nucleoside analogs are not phosphorylated by HCMV or HSV-1 gene products and that the ribosylbenzimidazoles do not require phosphorylation for antiviral activity.
An efficient method for the N-debenzylation of aromatic heterocycles

Abstract The treatment of N -benzylated heterocycles with potassium tert -butoxide/DMSO and oxygen at room temperature cleanly affords N -debenzylated products in high yield. This procedure can be utilized on a variety of functionalized nitrogen-containing heterocycles such as imidazoles, benzimidazoles, pyrazoles, indazoles, carbazoles, and indoles.
Synthesis and Selective Coronary Vasodilatory Activity of 3,4-Dihydro-2,2-bis(methoxymethyl)-2H-1-benzopyran-3-ol Derivatives: Novel Potassium Channel Openers

A variety of compounds having a benzopyran such as levcromakalim generally exhibit potent antihypertensive activity. During extensive investigations aimed toward identifying K+ channel openers having selective coronary vasodilation without potent hypotensive and tachycardiac effects, we synthesized a series of 3,4-dihydro-2H-1-benzopyran-3-ol derivatives modified at positions 2, 4, and 6 in the benzopyran ring. Initially, compounds having two methoxymethyl groups at position 2 were found to show a selective effect on coronary blood flow (CoBF) relative to mean arterial pressure (MAP) in anesthetized dogs. To find more potent vasodilators, various benzopyran derivatives modified at position 4 were synthesized and structure-activity relationships were examined by evaluation of the extent and duration of the increase in CoBF in anesthetized dogs. As a result, compounds having a (1,6-dihydro-6-oxopyridazin-3-yl)amino group at position 4, in addition to the two methoxymethyl groups at position 2, were found to be more potent and to have an improved duration of action. Among these compounds, JTV-506, (-)-(3S,4R)-6-cyano-3,4-dihydro-4-[(1,6-dihydro-1-methyl-6-oxopyridaz in-3-yl)amino]-2,2-bis(methoxymethyl)-2H-1-benzopyran-3-ol, exhibited good selectivity for its effect. Administration of this compound (0.03 mg/kg, p.o.) elicited an increase of CoBF without a change of systemic blood pressure and heart rate (HR) in conscious dogs. Further evaluation was performed with respect to (i) the selectivity of its action on the coronary artery versus the aorta and (ii) its effects on MAP, HR, and electrocardiographic ST elevation. As a result, JTV-506 was selected as a potent and selective coronary vasodilator with various pharmacological features favoring clinical development.
BORON TRICHLORIDE MEDIATED ALKYNE-ALDEHYDE COUPLING REACTIONS

The boron trichloride mediated reaction of aryl aldehydes and alkynes can be used to selectively generate either (Z,Z)- or (Z,E)-1,5-dichloro-1,4-dienes as major products, depending on the reaction conditions employed. To investigate the mechanism of this important carbon-carbon bond forming reaction, the boron trichloride mediated reaction of phenylacetylene with p-bromobenzaldehyde was chosen as the model system. Interestingly, when the coupling reactions are carried out below ―60 °C, (E,E)-1,5-dichloro-1,4-dienes are also formed. The ratios of (Z,Z)-, (Z,E)-, and (E,E)-1,5-dichloro-1,4-dienes were correlated to the reaction conditions using gas chromatography-mass spectrometry. The results of the investigation can be used to explain why the ratio of (Z,E)-, (Z,Z)-, and (E,E)-1,5-dichloro-1,4-pentadiene products change very dramatically when changes are made in either the sequence of addition of the reagents or the reaction temperature.
A Synthetic Approach to 15-D2c-Isoprostane Ethyl Ester

The preparation of ketone 10 is described. Oxidation of 10 to the sulfoxide followed by sigmatropic rearrangement gave not the expected 15-D2c-isoprostane ethyl ester (4), but the trans diastereomer 11. A 13C NMR method for establishment of the relative configuration of the cyclopentane rings of the isoprostanes and prostaglandins is also reported.
AA′2Rh6O12: A New Family of Rhodium Oxides Exhibiting High Thermopower Coupled with High Electrical Conductivity

A new family of rhodium oxides with the SrCa 2 Sc 6 O 12 structure has been discovered. The new compounds prepared are SrMg 2 Rh 6 O 12 , La 1-x Mg 2-y Rh 6 O 12 , Bi 0.8 Li 2 Rh 6 O 12 , Pb 0.78 Li 2 Rh 6 O 12 , Bi 0.75 Sc 1.10 -(Rh 4.92 Sc 1.08 )O 12 , SrBe 2 RhO 12 , and Bi 0.68 Be 2 RhO 12 . All compounds can be considered Rh 3+ /Rh 4+ mixed-valence compounds with the highest average oxidation being +3.4. Structural analyses based on single-crystal X-ray diffraction data were performed for four of the compounds, and triangular coordination for Be was found in the case of Bi 0.68 Be 2 Rh 6 O 12 . All the compounds are good electrical conductors, and a Seebeck coefficient of 200μV/K was found for Bi 0.88 Li 2 RhO 12 and SrMg 2 RhO 12 . The magnetic properties of Pb 0.78 Li 2 Rh 6 O 12 , Bi 0.78 Li 2 Rh 6 O 12 and Bi 0.68 Be 2 Rh 6 O 12 are discussed.
A new and efficient route toward the preparation of diazo ketones using cyanuric chloride and diazomethane

Abstract A new method for the preparation of diazo ketones has been developed. 2,4,6-Trichloro-1,3,5-triazine (cyanuric chloride) has been found to be an excellent coupling reagent allowing for the efficient transfer of diazomethane to a carboxylic acid. Preparation of diazo ketones using carboxylic acids and triazine reagents is considerably more convenient than classical diazo transfer protocols because water does not have to be stringently removed and the entire procedure can be carried out in one-pot. Electron deficient and neutral aryl carboxylic acids were found to give better results than electron rich or aliphatic carboxylic acids.
An Improved Synthesis of β-Nicotyrine from the Dehydrogenation of Nicotine: Comparison of Conventional and Microwave-Assisted Reactions

Abstract β-Nicotyrine, a minor tobacco alkaloid, can be rapidly prepared in good yield from the dehydrogenation of S-(-)-nicotine over MnO2 with microwave irradiation. This method is superior to dehydrogenation reactions that utilize S-(-)-nicotine and MnO2 in a variety of solvents under reflux.
Leveraging biological insight and environmental variation to improve phenotypic prediction: Integrating crop growth models (CGM) with whole genome prediction (WGP)

Abstract A successful strategy for prediction of crop yield that accounts for the effects of genotype, environment and their interactions with management will create many opportunities for enhancing the productivity of agricultural systems. Crop growth models (CGMs) have a history of application for crop management decision support. Recently, whole genome prediction (WGP) methodologies have been developed and applied in breeding to enable prediction of crop traits for new genotypes, and thus increased the size of plant breeding programs without expanding expensive field testing. The integration of a CGM into the algorithm for WGP, referred to as CGM-WGP, has opened up the potential for prediction of G × E × M interactions for breeding and product placement applications. The main objectives of this study were to extend CGM-WGP methodology to train models using data from multiple environments, and to evaluate, using both synthetic and experimental data from a maize drought breeding program, whether CGM-WGP methodology can enable improved phenotypic prediction when G × E interactions are an important determinant of performance. The CGM-WGP methodology was improved by 1) reformulating the model as a Bayesian generalized linear hierarchical model, and 2) by sampling the posterior distribution using a Metropolis-within-Gibbs sampling algorithm. The increased efficiency of the algorithm enabled the use of multiple environments and larger populations than those used in previous studies. Synthetic datasets included three environments and an empirical dataset included two environments contrasting for drought stress pattern and intensity. The empirical dataset included four double haploid populations expressing different levels of G × E interaction. Collectively, the prediction accuracy results for the empirical study indicate there were realized advantages in prediction accuracy for yield, in both the water limited and the not water limited environments, from the modeling of the G × E interactions by the CGM-WGP methodology relative to the reference method BayesA. Similarly, the difference in CGM-WGP accuracy relative to BayesA increased with decreasing similarity between the environment types utilized for training and evaluating the predictions. The synthesis provided in this work that encompasses crop physiology and modeling, quantitative genetics, genomic prediction and breeding, should stimulate a cross disciplinary dialogue towards building the next generation of prediction methodologies.
Unexpected copper-catalyzed aminohalogenation reaction of olefins using N-halo-N-metallo-sulfonamide as the nitrogen and halogen sources

N-Chloro-N-sodium-sulfonamide was found to react with olefins in the presence of copper catalyst to give vicinal haloamine derivatives instead of aziridines. The resulting regio and stereochemistry indicates that this unexpected reaction could proceed through the formation of unprecedented N-chloro-N-copper-2-nitrobenzenesulfonyl aziridinium intermediates, which can increase the successful chance to render the asymmetric version of the aminohalogenation reaction. In addition, this finding provides a more convenient protocol by the use of solely pure NsNClNa for the aminohalogenation reaction as compared to the mixed nitrogen and chlorine sources consisting of NsNCl2 and NsNHNa as previously reported by us. Two new simple olefin substrates, trans-stilbene and styrene, were also found to be effective for this new reaction system.
Optimal Structure of Metaplasticity for Adaptive Learning

Learning from reward feedback in a changing environment requires a high degree of adaptability, yet the precise estimation of reward information demands slow updates. In the framework of estimating reward probability, here we investigated how this tradeoff between adaptability and precision can be mitigated via metaplasticity, i.e. synaptic changes that do not always alter synaptic efficacy. Using the mean-field and Monte Carlo simulations we identified 'superior' metaplastic models that can substantially overcome the adaptability-precision tradeoff. These models can achieve both adaptability and precision by forming two separate sets of meta-states: reservoirs and buffers. Synapses in reservoir meta-states do not change their efficacy upon reward feedback, whereas those in buffer meta-states can change their efficacy. Rapid changes in efficacy are limited to synapses occupying buffers, creating a bottleneck that reduces noise without significantly decreasing adaptability. In contrast, more-populated reservoirs can generate a strong signal without manifesting any observable plasticity. By comparing the behavior of our model and a few competing models during a dynamic probability estimation task, we found that superior metaplastic models perform close to optimally for a wider range of model parameters. Finally, we found that metaplastic models are robust to changes in model parameters and that metaplastic transitions are crucial for adaptive learning since replacing them with graded plastic transitions (transitions that change synaptic efficacy) reduces the ability to overcome the adaptability-precision tradeoff. Overall, our results suggest that ubiquitous unreliability of synaptic changes evinces metaplasticity that can provide a robust mechanism for mitigating the tradeoff between adaptability and precision and thus adaptive learning.
Synaptic and Gene Regulatory Mechanisms in Schizophrenia, Autism, and 22q11.2 Copy Number Variant-Mediated Risk for Neuropsychiatric Disorders.

Abstract Background 22q11.2 copy number variants are among the most highly penetrant genetic risk variants for developmental neuropsychiatric disorders such as schizophrenia (SCZ) and autism spectrum disorder (ASD). However, the specific mechanisms through which they confer risk remain unclear. Methods Using a functional genomics approach, we integrated transcriptomic data from the developing human brain, genome-wide association findings for SCZ and ASD, protein interaction data, and gene expression signatures from SCZ and ASD postmortem cortex to 1) organize genes into the developmental cellular and molecular systems within which they operate, 2) identify neurodevelopmental processes associated with polygenic risk for SCZ and ASD across the allelic frequency spectrum, and 3) elucidate pathways and individual genes through which 22q11.2 copy number variants may confer risk for each disorder. Results Polygenic risk for SCZ and ASD converged on partially overlapping neurodevelopmental modules involved in synaptic function and transcriptional regulation, with ASD risk variants additionally enriched for modules involved in neuronal differentiation during fetal development. The 22q11.2 locus formed a large protein network during development that disproportionately affected SCZ-associated and ASD-associated neurodevelopmental modules, including loading highly onto synaptic and gene regulatory pathways. SEPT5, PI4KA, and SNAP29 genes are candidate drivers of 22q11.2 synaptic pathology relevant to SCZ and ASD, and DGCR8 and HIRA are candidate drivers of disease-relevant alterations in gene regulation. Conclusions This approach offers a powerful framework to identify neurodevelopmental processes affected by diverse risk variants for SCZ and ASD and elucidate mechanisms through which highly penetrant, multigene copy number variants contribute to disease risk.
Layer-Tunable Third-Harmonic Generation in Multilayer Black Phosphorus

Black phosphorus has been the subject of growing interest due to its unique band structure that is both layer dependent and anisotropic. While many have studied the linear optical response of black phosphorus, the nonlinear response has remained relatively unexplored. Here we report on the observation of third-harmonic generation in black phosphorus using an ultrafast near-IR laser and measure χ(3) experimentally for the first time. It was found that the third-harmonic emission is highly anisotropic, dependent on the incident polarization, and varies strongly with the number of layers present due to signal depletion and phase-matching conditions.
Rigid Components of Random Graphs

We study the emergence of rigid components in an Erd} os-R enyi random graph G (n;p), using the parameterization p = c=n for a xed constant c > 0. We show that for all c > 0, almost surely all rigid components have size 2, 3 or ( n); for c > 4, we show that almost surely there is a rigid component of size at least n=10.
Incomplete Dot Products for Dynamic Computation Scaling in Neural Network Inference

We propose the use of incomplete dot products (IDP) to dynamically adjust the number of input channels used in each layer of a convolutional neural network during feedforward inference. IDP adds monotonically non-increasing coefficients, referred to as a “profile”, to the channels during training. The profile orders the contribution of each channel in non-increasing order. At inference time, the number of channels used can be dynamically adjusted to trade off accuracy for lowered power consumption and reduced latency by selecting only a beginning subset of channels. This approach allows for a single network to dynamically scale over a computation range, as opposed to training and deploying multiple networks to support different levels of computation scaling. Additionally, we extend the notion to multiple profiles, each optimized for some specific range of computation scaling. We present experiments on the computation and accuracy trade-offs of IDP for popular image classification models and datasets. We demonstrate that, for MNIST and CIFAR-10, IDP reduces computation significantly, e.g., by 75%, without significantly compromising accuracy. We argue that IDP provides a convenient and effective means for devices to lower computation costs dynamically to reflect the current computation budget of the system. For example, VGG-16 with 50% IDP (using only the first 50% of channels) achieves 70% in accuracy on the CIFAR-10 dataset compared to the standard network which achieves only 35% accuracy when using the reduced channel set.
Improvement of Mixing Function for Modified Upwinding Compact Scheme

The compact scheme has high order accuracy and high resolution, but cannot be used to capture the shock. WENO is a great scheme for shock capturing, but is too dissipative for turbulence and small length scales. We developed a modified upwinding compact scheme which uses an effective shock detector to block compact scheme to cross the shock and a control function to mix the flux with WENO scheme near the shock. The new scheme makes the original compact scheme able to capture the shock sharply and, more important, keep high order accuracy and high resolution in the smooth area, which is particularly important for shock boundary layer and shock acoustic interactions. This work is a continuation to modify the control function for the modified up-winding compact scheme (MUCS). Numerical results show the scheme is successful for 2-D Euler.
Divisorial Strata of Abelian Differentials

We compute a closed formula for the class of the closure of the locus of curves in $\overline{\mathcal{M}}_g$ that admit an abelian differential of signature $\kappa=(k_1,...,k_{g-2})$.
Streaming End-to-end Speech Recognition for Mobile Devices

End-to-end (E2E) models, which directly predict output character sequences given input speech, are good candidates for on-device speech recognition. E2E models, however, present numerous challenges: In order to be truly useful, such models must decode speech utterances in a streaming fashion, in real time; they must be robust to the long tail of use cases; they must be able to leverage user-specific context (e.g., contact lists); and above all, they must be extremely accurate. In this work, we describe our efforts at building an E2E speech recog-nizer using a recurrent neural network transducer. In experimental evaluations, we find that the proposed approach can outperform a conventional CTC-based model in terms of both latency and accuracy in a number of evaluation categories.
Whom are you going to call? determinants of @-mentions in Github discussions

Open Source Software (OSS) project success relies on crowd contributions. When an issue arises in pull-request based systems, @-mentions are used to call on people to task; previous studies have shown that @-mentions in discussions are associated with faster issue resolution. In most projects there may be many developers who could technically handle a variety of tasks. But OSS supports dynamic teams distributed across a wide variety of social and geographic backgrounds, as well as levels of involvement. It is, then, important to know whom to call on, i.e., who can be relied or trusted with important task-related duties, and why. In this paper, we sought to understand which observable socio-technical attributes of developers can be used to build good models of them being future @-mentioned in GitHub issues and pull request discussions. We built overall and project-specific predictive models of future @-mentions, in order to capture the determinants of @-mentions in each of two hundred GitHub projects, and to understand if and how those determinants differ between projects. We found that visibility, expertise, and productivity are associated with an increase in @-mentions, while responsiveness is not, in the presence of a number of control variables. Also, we find that though project-specific differences exist, the overall model can be used for cross-project prediction, indicating its GitHub-wide utility.
Periodicity and ergodicity in the trihexagonal tiling

We consider the dynamics of light rays in the trihexagonal tiling where triangles and hexagons are transparent and have equal but opposite indices of refraction. We find that almost every ray of light is dense in a region of a particular form: the regions have infinite area and consist of the plane with a periodic family of triangles removed. We also completely describe initial conditions for periodic and drift-periodic light rays.
Nash Social Welfare, Matrix Permanent, and Stable Polynomials.

We study the problem of allocating m items to n agents subject to maximizing the Nash social welfare (NSW) objective. We write a novel convex programming relaxation for this problem, and we show that a simple randomized rounding algorithm gives a 1/e approximation factor of the objective, breaking the 1/2e^(1/e) approximation factor of Cole and Gkatzelis. Our main technical contribution is an extension of Gurvits's lower bound on the coefficient of the square-free monomial of a degree m-homogeneous stable polynomial on m variables to all homogeneous polynomials. We use this extension to analyze the expected welfare of the allocation returned by our randomized rounding algorithm.
On the projective normality of double coverings over a rational surface

Abstract We study the projective normality of a minimal surface X which is a ramified double covering over a rational surface S with dim ⁡ | − K S | ≥ 1 . In particular Horikawa surfaces, the minimal surfaces of general type with K X 2 = 2 p g ( X ) − 4 , are of this type, up to resolution of singularities. Let π be the covering map from X to S . We show that the Z 2 -invariant adjoint divisors K X + r π ⁎ A are normally generated, where the integer r ≥ 3 and A is an ample divisor on S .
A filtration of unoriented cobordism

Abstract We give a filtration of BO that recovers the polynomial generators of H ⁎ BO one at a time, and that the corresponding Thom spectra filter the unoriented cobordism ring π ⁎ ( MO ) and recovers the polynomial generators of this ring one at a time.
On Decomposing Betti Tables and O-Sequences

The Boij–Soderberg characterization decomposes a Betti table into a unique positive integral linear combination of pure diagrams. Given a module with a pure resolution, we describe explicit formulae for computing the decomposition of the Betti table of the module given the decomposition of the truncation of the Betti table, and vice versa.Nagel and Sturgeon described the decomposition of Betti tables of ideals with d-linear resolutions; indeed, the coefficients are precisely finite O-sequences. Using the extension formulae, we provide an explicit description of the coefficients of the decomposition of the Betti table of the quotient ring of such an ideal. Following from this, we describe the closed convex simplicial cone of O-sequences.
Compact multi-class boosted trees

Gradient boosted decision trees are a popular machine learning technique, in part because of their ability to give good accuracy with small models. We describe two extensions to the standard tree boosting algorithm designed to increase this advantage. The first improvement extends the boosting formalism from scalar-valued trees to vector-valued trees. This allows individual trees to be used as multiclass classifiers, rather than requiring one tree per class, and drastically reduces the model size required for multiclass problems. We also show that some other popular vector-valued gradient boosted trees modifications fit into this formulation and can be easily obtained in our implementation. The second extension, layer-by-layer boosting, takes smaller steps in function space, which is empirically shown to lead to a faster convergence and to a more compact ensemble. We have added both improvements to the open-source TensorFlow Boosted trees (TFBT) package, and we demonstrate their efficacy on a variety of multiclass datasets. We expect these extensions will be of particular interest to boosted tree applications that require small models, such as embedded devices, applications requiring fast inference, or applications desiring more interpretable models.
Link cobordisms and absolute gradings on link Floer homology

We show that the link cobordism maps defined by the author are graded and satisfy a grading change formula. Using the grading change formula, we prove a new bound for $\Upsilon_K(t)$ for knot cobordisms in negative definite 4-manifolds. As another application, we show that the link cobordism maps associated to a connected, closed surface in $S^4$ are determined by the genus of the surface. We also prove a new adjunction relation and adjunction inequality for the link cobordism maps. Along the way, we see how many known results in Heegaard Floer homology can be proven using basic properties of the link cobordism maps, together with the grading change formula.
Logarithmic fluctuations for internal DLA

Let each of n particles starting at the origin in Z 2 perform simple random walk until reaching a site with no other particles. Lawler, Bramson, and Griffeath proved that the resulting random set A(n) of n occupied sites is (with high probability) close to a disk Br of radius r = p n= . We show that the discrepancy between A(n) and the disk is at most logarithmic in the radius: i.e., there is an absolute constant C such that with probability 1, Br C log r A(r 2 ) Br+C log r for all suciently large r:
Graphene Klein tunnel transistors for high speed analog RF applications.

We propose Graphene Klein tunnel transistors (GKTFET) as a way to enforce current saturation while maintaining large mobility for high speed radio frequency (RF) applications. The GKTFET consists of a sequence of angled graphene p-n junctions (GPNJs). Klein tunneling creates a collimation of electrons across each GPNJ, so that the lack of substantial overlap between transmission lobes across successive junctions creates a gate-tunable transport gap without significantly compromising the on-current. Electron scattering at the device edge tends to bleed parasitic states into the gap, but the resulting pseudogap is still sufficient to create a saturated output (I D –V D ) characteristic and a high output resistance. The modulated density of states generates a higher transconductance (g m ) and unity current gain cut-off frequency (f T ) than GFETs. More significantly the high output resistance makes the unity power gain cut-off frequency (f max ) of GKTFETs considerably larger than GFETs, making analog GKTFET potentially useful for RF electronics. Our estimation shows the f T /f max of a GKTFET with 1 μm channel reaches 33 GHz/17 GHz, and scale up to 350 GHz/53 GHz for 100 nm channel (assuming a single, scalable trapezoidal gate). The f max of a GKTFET is 10 times higher than a GFET with the same channel length.
Privacy leakages in approximate adders

Approximate computing has recently emerged as a promising method to meet the low power requirements of digital designs. The erroneous outputs produced in approximate computing can be partially a function of each chip's process variation. We show that, in such schemes, the erroneous outputs produced on each chip instance can reveal the identity of the chip that performed the computation, possibly jeopardizing user privacy. In this work, we perform simulation experiments on 32-bit Ripple Carry Adders, Carry Lookahead Adders, and Han-Carlson Adders running at over-scaled operating points. Our results show that identification is possible, we contrast the identifiability of each type of adder, and we quantify how success of identification varies with the extent of over-scaling and noise. Our results are the first to show that approximate digital computations may compromise privacy. Designers of future approximate computing systems should be aware of the possible privacy leakages and decide whether mitigation is warranted in their application.
Phonons and thermal transport in graphene and graphene-based materials

A discovery of the unusual thermal properties of graphene stimulated experimental, theoretical and computational research directed at understanding phonon transport and thermal conduction in two-dimensional material systems. We provide a critical review of recent results in the graphene thermal field focusing on phonon dispersion, specific heat, thermal conductivity, and comparison of different models and computational approaches. The correlation between the phonon spectrum in graphene-based materials and the heat conduction properties is analyzed in details. The effects of the atomic plane rotations in bilayer graphene, isotope engineering, and relative contributions of different phonon dispersion branches are discussed. For readers' convenience, the summaries of main experimental and theoretical results on thermal conductivity as well as phonon mode contributions to thermal transport are provided in the form of comprehensive annotated tables.
Bayesian inference for Gaussian graphical models beyond decomposable graphs

Bayesian inference for graphical models has received much attention in the literature in recent years. It is well known that, when the graph G is decomposable, Bayesian inference is significantly more tractable than in the general non‐decomposable setting. Penalized likelihood inference in contrast has made tremendous gains in the past few years in terms of scalability and tractability. Bayesian inference, however, has not had the same level of success, though a scalable Bayesian approach has its strengths, especially in terms of quantifying uncertainty. To address this gap, we propose a scalable and flexible novel Bayesian approach for estimation and model selection in Gaussian undirected graphical models. We first develop a class of generalized G‐Wishart distributions with multiple shape parameters for an arbitrary underlying graph. This class contains the G‐Wishart distribution as a special case. We then introduce the class of generalized Bartlett graphs and derive an efficient Gibbs sampling algorithm to obtain posterior draws from generalized G‐Wishart distributions corresponding to a generalized Bartlett graph. The class of generalized Bartlett graphs contains the class of decomposable graphs as a special case but is substantially larger than the class of decomposable graphs. We proceed to derive theoretical properties of the proposed Gibbs sampler. We then demonstrate that the proposed Gibbs sampler is scalable to significantly higher dimensional problems compared with using an accept–reject or a Metropolis–Hasting algorithm. Finally, we show the efficacy of the proposed approach on simulated and real data. In particular, we demonstrate that our generalized Bartlett methodology can be used for efficient model selection by reducing the graph search space by using penalized likelihood and pseudolikelihood methods.
A subspace method for array covariance matrix estimation

This paper introduces a subspace method for the estimation of an array covariance matrix. When the received signals are uncorrelated, it is shown that the array covariance matrices lie in a special subspace defined through all possible correlation vectors of the received signals and whose dimension is typically much smaller than the ambient dimension. Based on this observation, a subspace-based covariance matrix estimator is proposed as a solution to a semi-definite convex optimization problem. While the optimization problem has no closed-form solution, a nearly optimal closed-form solution that is easily implementable is proposed. The proposed approach is shown to yield higher estimation accuracy than conventional approaches since it eliminates the estimation error that does not lie in the subspace of the true covariance matrices. The numerical examples demonstrate that the proposed estimator can significantly improve the estimation quality of the covariance matrix.
Hybrid Planning and Control for Multiple Fixed-Wing Aircraft under Input Constraints

This paper presents a novel hybrid control protocol for de-conflicting multiple vehicles with constraints on control inputs. We consider turning rate and linear speed constraints to represent fixed-wing or car-like vehicles. A set of state-feedback controllers along with a state-dependent switching logic are synthesized in a hybrid system to generate collision-free trajectories that converge to the desired destinations of the vehicles. The switching law is designed so that the safety can be guaranteed while no Zeno behavior can occur. A novel temporary goal assignment technique is also designed to guarantee convergence. We analyze the individual modes for safety and the closed-loop hybrid system for convergence. The theoretical developments are demonstrated via simulation results.
The Externalities of Exploration and How Data Diversity Helps Exploitation.

Online learning algorithms, widely used to power search and content optimization on the web, must balance exploration and exploitation, potentially sacrificing the experience of current users for information that will lead to better decisions in the future. Recently, concerns have been raised about whether the process of exploration could be viewed as unfair, placing too much burden on certain individuals or groups. Motivated by these concerns, we initiate the study of the externalities of exploration – the undesirable side effects that the presence of one party may impose on another – under the linear contextual bandits model. We introduce the notion of a group externality, measuring the extent to which the presence of one population of users impacts the rewards of another. We show that this impact can in some cases be negative, and that, in a certain sense, no algorithm can avoid it. We then study externalities at the individual level, interpreting the act of exploration as an externality imposed on the current user of a system by future users. This drives us to ask under what conditions inherent diversity in the data makes explicit exploration unnecessary. We build on a recent line of work on the smoothed analysis of the greedy algorithm that always chooses the action that currently looks optimal, improving on prior results to show that a greedy approach almost matches the best possible Bayesian regret rate of any other algorithm on the same problem instance whenever the diversity conditions hold, and that this regret is at most O~(T1/3)
Hierarchically-Attentive RNN for Album Summarization and Storytelling

We address the problem of end-to-end visual storytelling. Given a photo album, our model first selects the most representative (summary) photos, and then composes a natural language story for the album. For this task, we make use of the Visual Storytelling dataset and a model composed of three hierarchically-attentive Recurrent Neural Nets (RNNs) to: encode the album photos, select representative (summary) photos, and compose the story. Automatic and human evaluations show our model achieves better performance on selection, generation, and retrieval than baselines.
Rigidity of equality of Lyapunov exponents for geodesic flows

We study the relationship between the Lyapunov exponents of the geodesic flow of a closed negatively curved manifold and the geometry of the manifold. We show that if each periodic orbit of the geodesic flow has exactly one Lyapunov exponent on the unstable bundle then the manifold has constant negative curvature. We also show under a curvature pinching condition that equality of all Lyapunov exponents with respect to volume on the unstable bundle also implies that the manifold has constant negative curvature. We then study the degree to which one can emulate these rigidity theorems for the hyperbolic spaces of nonconstant negative curvature when the Lyapunov exponents with respect to volume match those of the appropriate symmetric space and obtain rigidity results under additional technical assumptions. The proofs use new results from hyperbolic dynamics including the nonlinear invariance principle of Avila and Viana and the approximation of Lyapunov exponents of invariant measures by Lyapunov exponents associated to periodic orbits which was developed by Kalinin in his proof of the Livsic theorem for matrix cocycles. We also employ rigidity results of Capogna and Pansu on quasiconformal mappings of certain nilpotent Lie groups.
Semi-Automated Annotation of Discrete States in Large Video Datasets

We propose a framework for semi-automated annotation of video frames where the video is of an object that at any point in time can be labeled as being in one of a finite number of discrete states. A Hidden Markov Model (HMM) is used to model (1) the behavior of the underlying object and (2) the noisy observation of its state through an image processing algorithm. The key insight of this approach is that the annotation of frame-by-frame video can be reduced from a problem of labeling every single image to a problem of detecting a transition between states of the underlying objected being recording on video. The performance of the framework is evaluated on a driver gaze classification dataset composed of 16,000,000 images that were fully annotated over 6,000 hours of direct manual annotation labor. On this dataset, we achieve a 13x reduction in manual annotation for an average accuracy of 99.1% and a 84x reduction for an average accuracy of 91.2%.
The hyperbolic lattice point count in infinite volume with applications to sieves

We develop novel techniques using abstract operator theory to obtain asymptotic formulae for lattice counting problems on infinite-volume hyperbolic manifolds, with error terms that are uniform as the lattice moves through “congruence” subgroups. We give the following application to the theory of affine linear sieves. In the spirit of Fermat, consider the problem of primes in the sum of two squares, f(c,d)=c2+d2, but restrict (c,d) to the orbit O=(0,1)Γ, where Γ is an infinite-index, nonelementary, finitely generated subgroup of SL(2,Z). Assume that the Reimann surface Γ\H has a cusp at infinity. We show that the set of values f(O) contains infinitely many integers having at most R prime factors for any R>4/(δ-θ), where θ>1/2 is the spectral gap and δ 149/150, then we can take θ=5/6, giving R=25. The limit of this method is R=9 for δ-θ>4/9. This is the same number of prime factors as attained in Brun's original attack on the twin prime conjecture
Norm convergence of partial sums of $H^1$ functions

A classical observation of Riesz says that truncations of a general ∑n=0∞a nzn in the Hardy space H1 do not converge in H1. A substitute positive result is proved: these partial sums always converge in the Bergman norm A1. The result is extended to complete Reinhardt domains in ℂn. A new proof of the failure of H1 convergence is also given.
Bayesian multicategory support vector machines

We show that the multi-class support vector machine (MSVM) proposed by Lee et al. (2004) can be viewed as a MAP estimation procedure under an appropriate probabilistic interpretation of the classifier. We also show that this interpretation can be extended to a hierarchical Bayesian architecture and to a fully-Bayesian inference procedure for multi-class classification based on data augmentation. We present empirical results that show that the advantages of the Bayesian formalism are obtained without a loss in classification accuracy.
Edge-exchangeable graphs and sparsity

Many popular network models rely on the assumption of (vertex) exchangeability, in which the distribution of the graph is invariant to relabelings of the vertices. However, the Aldous-Hoover theorem guarantees that these graphs are dense or empty with probability one, whereas many real-world graphs are sparse. We present an alternative notion of exchangeability for random graphs, which we call edge exchangeability, in which the distribution of a graph sequence is invariant to the order of the edges. We demonstrate that edge-exchangeable models, unlike models that are traditionally vertex exchangeable, can exhibit sparsity. To do so, we outline a general framework for graph generative models; by contrast to the pioneering work of Caron and Fox (2015), models within our framework are stationary across steps of the graph sequence. In particular, our model grows the graph by instantiating more latent atoms of a single random measure as the dataset size increases, rather than adding new atoms to the measure.