cssi/SciSciGPT-SciSciNet huggingface dataset:
On to the next chapter for crop breeding: Convergence with data science

Crop breeding is as ancient as the invention of cultivation. In essence, the objective of crop breeding is to improve plant fitness under human cultivation conditions, making crops more productive while maintaining consistency in life cycle and quality. Predictive breeding has been demonstrated in the agricultural industry and in public breeding programs for over a decade. The massive stores of data that have been generated by industry, farmers, and scholars through several decades have finally been recognized as a potential asset that can be brought to bear on specific breeding decisions. A wide range of analytical methods that were initially developed for various other quantitative disciplines, such as machine learning, deep learning, and artificial intelligence, are now being adapted for application in crop breeding to support analytics and decision making processes. This convergence between data science and crop breeding analytics is expected to address long-standing gaps in crop breeding analytics, and realize the potential of applying advanced analytics to multidimensional data such as geospatial variables, a multitude of phenotypic responses, and genetic information. Here, we summarize the few existing examples followed by perspectives on where else these technologies would have applications to accelerate operational aspects of crop breeding and agricultural product development efforts.
CLINICAL PREDICTORS OF SYMPTOM RESOLUTION FOR CHILDREN AND ADOLESCENTS WITH SPORT-RELATED CONCUSSION:

Background:Early prognosis of expected recovery duration after a sport-related concussion is a challenging task for sports medicine clinicians, as various pre-morbid, injury characteristic, and fun...
Improved visible to IR image transformation using synthetic data augmentation with cycle-consistent adversarial networks

Infrared (IR) images are essential to improve the visibility of dark or camouflaged objects. Object recognition and segmentation based on a neural network using IR images provide more accuracy and insight than color visible images. But the bottleneck is the amount of relevant IR images for training. It is difficult to collect real-world IR images for special purposes, including space exploration, military and fire-fighting applications. To solve this problem, we created color visible and IR images using a Unity-based 3D game editor. These synthetically generated color visible and IR images were used to train cycle consistent adversarial networks (CycleGAN) to convert visible images to IR images. CycleGAN has the advantage that it does not require precisely matching visible and IR pairs for transformation training. In this study, we discovered that additional synthetic data can help improve CycleGAN performance. Neural network training using real data (N = 20) performed more accurate transformations than training using real (N = 10) and synthetic (N = 10) data combinations. The result indicates that the synthetic data cannot exceed the quality of the real data. Neural network training using real (N = 10) and synthetic (N = 100) data combinations showed almost the same performance as training using real data (N = 20). At least 10 times more synthetic data than real data is required to achieve the same performance. In summary, CycleGAN is used with synthetic data to improve the IR image conversion performance of visible images.
Design of a Tapered Slot Waveguide Dielectric Laser Accelerator for Sub-Relativistic Electrons

We design and analyze a tapered slot waveguide structure for sub-relativistic electron acceleration. The tapering scheme can be designed, through the eikonal approximation’ to achieve phase synchronization with the accelerated electrons. © 2019 The Author(s)
Comprehensive analysis of lymphocyte loss kinetics in patients treated with focal fractionated radiation therapy.

e14191Background: Radiation (RT)-induced lymphopenia (RIL) is associated with worse survival in patients with solid tumors as well as lower response rates to checkpoint inhibitors. This analysis ai...
The estimation of the aromaticity of five-membered and benzo fused five-membered rings by the hybrid DFT computed magnetic properties

The structures of thiophene, pyrrole, furan, and their benzo derivatives were generated with the hybrid B3LYP density functional theory (DFT) methods employing a 6-31G* basis set. Their magnetic susceptibility anisotropics were calculated on these geometries with a continuous set of gauge transformations. The aromaticity of the heterocycles was discussed in light of their structural uniformity and magnetic susceptibility. The computed structural parameters, order of aromaticity, stability, and reactivity is in excellent agreement with the experimental results. The usefulness of this approach to determine the reactivity is discussed.
Highly Efficient Cpf1-Mediated Gene Targeting in Mice Following High Concentration Pronuclear Injection

Cpf1 has emerged as an alternative to the Cas9 RNA-guided nuclease. Here we show that gene targeting rates in mice using Cpf1 can meet, or even surpass, Cas9 targeting rates (approaching 100% targeting), but require higher concentrations of mRNA and guide. We also demonstrate that coinjecting two guides with close targeting sites can result in synergistic genomic cutting, even if one of the guides has minimal cutting activity.
A novel diacetylenic bilirubin

An etiobilirubin-IIβ analog with the central C(10) CH2 group replaced by a diacetylene unit (1) was synthesized by base-catalyzed condensation of bis-[3-methyl-4-ethyl-5-formylpyrrol-2-yl]-diacetylene (3) with 3-methyl-4-ethyl-5-p-toluenesulfonyl-2-pyrrolinone (10). Diacetylenic rubin 1 is a dark red solid, giving orange solutions with uv-visible absorption maxima near 460 nm.
Evolution of a synthetic approach to CP-263,114.

Three different approaches to the carbocyclic core of CP-263,114 are presented that illustrate a strategic evolution from an oxy-Cope rearrangement to variants of the Wharton fragmentation.
Positive cardiac inotrope omecamtiv mecarbil activates muscle despite suppressing the myosin working stroke

Omecamtiv mecarbil (OM) is a positive cardiac inotrope in phase-3 clinical trials for treatment of heart failure. Although initially described as a direct myosin activator, subsequent studies are at odds with this description and do not explain OM-mediated increases in cardiac performance. Here we show, via single-molecule, biophysical experiments on cardiac myosin, that OM suppresses myosin’s working stroke and prolongs actomyosin attachment 5-fold, which explains inhibitory actions of the drug observed in vitro. OM also causes the actin-detachment rate to become independent of both applied load and ATP concentration. Surprisingly, increased myocardial force output in the presence of OM can be explained by cooperative thin-filament activation by OM-inhibited myosin molecules. Selective suppression of myosin is an unanticipated route to muscle activation that may guide future development of therapeutic drugs.
Asymmetric allylic alkylation catalyzed by palladium complexes with new chiral ligands

Abstract A potential chiral tridentate ligand based on 2,6-disubstituted pyridine has been prepared and its palladium complexes have been used in asymmetric allylic alkylation. Up to 75 % ee is achieved in the reaction between 1,3-diphenyl-2-propenyl acetate and dimethyl malonate. A control experiment with a similar ligand without pyridine suggests that the bidentate diphosphine coordination is responsible for the asymmetric reaction with this potential tridentate ligand.
Catalytic asymmetric Simmons–Smith cyclopropanation of unfunctionalized olefins

Abstract This paper describes a catalytic asymmetric cyclopropanation system for unfunctionalized olefins using readily available dipeptide N-Boc- l -Val- l -Pro-OMe (1) as ligand.
Aspirin treatment does not increase microhemorrhage size in young or aged mice.

Microhemorrhages are common in the aging brain and are thought to contribute to cognitive decline and the development of neurodegenerative diseases, such as Alzheimer’s disease. Chronic aspirin therapy is widespread in older individuals and decreases the risk of coronary artery occlusions and stroke. There remains a concern that such aspirin usage may prolong bleeding after a vessel rupture in the brain, leading to larger bleeds that cause more damage to the surrounding tissue. Here, we aimed to understand the influence of aspirin usage on the size of cortical microhemorrhages and explored the impact of age. We used femtosecond laser ablation to rupture arterioles in the cortex of both young (2–5 months old) and aged (18–29 months old) mice dosed on aspirin in their drinking water and measured the extent of penetration of both red blood cells and blood plasma into the surrounding tissue. We found no difference in microhemorrhage size for both young and aged mice dosed on aspirin, as compared to controls (hematoma diameter = 104 +/- 39 (97 +/- 38) μm in controls and 109 +/- 25 (101 +/- 28) μm in aspirin-treated young (aged) mice; mean +/- SD). In contrast, young mice treated with intravenous heparin had an increased hematoma diameter of 136 +/- 44 μm. These data suggest that aspirin does not increase the size of microhemorrhages, supporting the safety of aspirin usage.
Salinamides, Antiinflammatory Depsipeptides from a Marine Streptomycete

In addition to the previously reported antiinflammatory agents salinamides A and B from the marine isolate Streptomyces sp. CNB-091, three minor peptides are described. Their total structures were established using a combination of spectral and chemical techniques. Revised structures are presented for the bicyclic depsipeptides salinamides A and B on the basis of the analysis of the dansylated salinamide A hydrolysate by chiral capillary electrophoresis. The fermentation yield of salinamide D, which contains a d-valine residue in place of the d-isoleucine moiety in salinamide A, can be dramatically increased 30-fold by supplementing the growth media with l-valine. Salinamides C and E are monocyclic depsipeptides that are likely methylated byproducts of salinamide A biosynthetic intermediates.
The Mismatch in Distributions of Vertebrates and the Plants that they Disperse

Little is known about how mutualistic interactions affect the distribution of species richness on broad geographic scales. It has been predicted that the richness of species involved in obligate mutualisms should be positively associated across their range. Whereas, if mutualisms are facilitative, the distribution of mutualists should be correlated with other factors. This study is the first study to compare the co-distribution of mutualist species in general and seed dispersal mutualisms specifically. We used geographic distributions of plant and animal mutualists to investigate the co-distribution and patterns of seed dispersal mutualisms. We found the mutualism between dispersers and plants does not account for the distribution of either group. In fact, there is a mismatch of richness between plants and the animals that disperse their seeds. Environmental factors are better predictors of both animal distribution and seed dispersal mutualisms across North America.
Total Synthesis of (+)-Polyoxin J.

Stereoselective total synthesis of (+)-polyoxin J is described. The synthesis was achieved in a convergent manner by coupling protected thymine polyoxin C (19) and 5-O-carbamoyl polyoxamic acid 27 and subsequent removal of the protecting groups. The key steps of the synthesis of protected thymine polyoxin C involved the stereoselective electrophilic epoxidation of E-allyl alcohol 7 derived from isopropylidene d-ribose derivative 5, followed by regioselective epoxide opening of 8 and conversion of resulting azido diol 9 to protected thymine polyoxin C (19). Protected polyoxamic acid 27 was synthesized stereoselectively by utilizing Sharpless epoxidation of tartrate-derived allylic alcohol 20 followed by a regioselective epoxide ring opening with diisopropoxytitanium diazide.
Alternating poly(pyridyl vinylene phenylene vinylene)s: synthesis and solid state organizations

Abstract Poly(pyridyl vinylene phenylene vinylenes) were synthesized by Heck coupling procedures. These materials display large red shifts in their optical absorption which upon protonation or alkylation of the pyridyl nitrogen. Some of the polymers were found to be liquid crystalline. The protonated or alkylated versions exhibit highly organized structures due to charge-transfer interactions between polymer chains.
A mild and efficient method for the synthesis of vinylogous carbamates from alkyl azides

A mild and efficient one-pot method for the synthesis of vinylogous carbamates is reported starting from alkyl azides under a hydrogen atmosphere using 10% Pd/C. The resulting products are useful intermediates for the synthesis of heterocyclic compounds, natural products, and in peptidomimetics.
A radical prototype to steroids: Synthesis of d,l-5α-D-homoandrostane-4α-methyl-3,17a-dione

Abstract An intramolecular radical methodology is described as an approach to D-homoandrostanes. The angular C-8 cyano group in tetracycle 7 derived from radical cyclization of polyene 6 serves as a latent functional group for elaboration to the C-8 βH in d,l-homoandrostane 11.
Incorporation of A2Q into HgQ and dimensional reduction to A2Hg3Q4 and A2Hg6Q7 (A = K, Rb, Cs; Q = S, Se). Access of Li ions in A2Hg6Q7 through topotactic ion-exchange

The synthesis of the one-dimensional K2Hg3Q4 (Q = S, Se) and Cs2Hg3Se4 and the three-dimensional A2Hg6S7 (A = K, Rb, Cs), and A2Hg6Se7 (A = Rb, Cs) in reactive A2Qx fluxes is reported. Pale yellow,...
A highly parallel strategy for storage of digital information in living cells

Encoding arbitrary digital information in DNA has attracted attention as a potential avenue for large scale and long term data storage. However, in order to enable DNA data storage technologies there needs to be improvements in data storage fidelity (tolerance to mutation), the facility of writing and reading the data (biases and systematic error arising from synthesis and sequencing), and overall scalability. To this end, we have developed and implemented an encoding scheme that is suitable for detecting and correcting errors that may arise during storage, writing, and reading, such as those arising from nucleotide substitutions, insertions, and deletions. We propose a scheme for parallelized long term storage of encoded sequences that relies on overlaps rather than the address blocks found in previously published work. Using computer simulations, we illustrate the encoding, sequencing, decoding, and recovery of encoded information, ultimately demonstrating the possibility of a successful round-trip read/write. These demonstrations show that in theory a precise control over error tolerance is possible. Even after simulated degradation of DNA, recovery of original data is possible owing to the error correction capabilities built into the encoding strategy. A secondary advantage of our method is that the statistical characteristics (such as repetitiveness and GC-composition) of encoded sequences can also be tailored without sacrificing the overall ability to store large amounts of data. Finally, the combination of the overlap-based partitioning of data with the LZMA compression that is integral to encoding means that the entire sequence must be present for successful decoding. This feature enables inordinately strong encryptions. As a potential application, an encrypted pathogen genome could be distributed and carried by cells without danger of being expressed, and could not even be read out in the absence of the entire DNA consortium. We have developed a method for DNA encoding, using a significantly different fundamental approach from existing work, which often performs better than alternatives and allows for a great deal of freedom and flexibility of application.
Ring Attractor Dynamics Emerge from a Spiking Model of the Entire Protocerebral Bridge.

Animal navigation is accomplished by a combination of landmark-following and dead reckoning based on estimates of self motion. Both of these approaches require the encoding of heading information, which can be represented as an allocentric or egocentric azimuthal angle. Recently, Ca2+ correlates of landmark position and heading direction, in egocentric coordinates, were observed in the ellipsoid body (EB), a ring-shaped processing unit in the fly central complex (Seelig and Jayaraman, 2015). These correlates displayed key dynamics of so-called ring attractors, namely: 1) responsiveness to the position of external stimuli, 2) persistence in the absence of external stimuli, 3) locking onto a single external stimulus when presented with two competitors, 4) stochastically switching between competitors with low probability, and 5) sliding or jumping between positions when an external stimulus moves. We hypothesized that ring attractor-like activity in the EB arises from reciprocal neuronal connections to a related structure, the protocerebral bridge (PB). Using recent light-microscopy resolution catalogues of neuronal cell types in the PB (Wolff et al., 2015; Lin et al., 2013), we determined a connectivity matrix for the PB-EB circuit. When activity in this network was simulated using a leaky-integrate-and-fire model, we observed patterns of activity that closely resemble the reported Ca2+ phenomena. All qualitative ring attractor behaviors were recapitulated in our model, allowing us to predict failure modes of the putative PB-EB ring attractor and the circuit dynamics phenotypes of thermogenetic or optogenetic manipulations. Ring attractor dynamics emerged under a wide variety of parameter configurations, even including non-spiking leaky-integrator implementations. This suggests that the ring-attractor computation is a robust output of this circuit, apparently arising from its high-level network properties (topological configuration, local excitation and long-range inhibition) rather than fine-scale biological detail.
ALKYLATION OF ALDEHYDE (ARENESULFONYL)HYDRAZONES WITH TRIALKYLBORANES

(Arenesulfonyl)hydrazone derivatives of aryl aldehydes are readily alkylated by trialkylboranes in the presence of base to generate new organoboranes that may be converted to the corresponding substituted alkanes or alcohols depending upon the reaction conditions chosen. Both tosyl- and trisylhydrazone derivatives can be utilized in the reaction, which tolerates a variety of functional groups, making it a versatile alternative to both the Grignard and Suzuki-coupling reactions.
Candida albicans Elicits Pro-Inflammatory Differential Gene Expression in Intestinal Peyer's Patches.

The details of how gut-associated lymphoid tissues such as Peyer’s patches (PPs) in the small intestine play a role in immune surveillance, microbial differentiation and the mucosal barrier protection in response to fungal organisms such as Candida albicans are still unclear. We particularly focus on PPs as they are the immune sensors and inductive sites of the gut that influence inflammation and tolerance. We have previously demonstrated that CD11c+ phagocytes that include dendritic cells and macrophages are located in the sub-epithelial dome within PPs sample C. albicans. To gain insight on how specific cells within PPs sense and respond to the sampling of fungi, we gavaged naive mice with C. albicans strains ATCC 18804 and SC5314 as well as Saccharomyces cerevisiae. We measured the differential gene expression of sorted CD45+ B220+ B-cells, CD3+ T-cells and CD11c+ DCs within the first 24 h post-gavage using nanostring nCounter® technology. The results reveal that at 24 h, PP phagocytes were the cell type that displayed differential gene expression. These phagocytes were able to sample C. albicans and discriminate between strains. In particular, strain ATCC 18804 upregulated fungal-specific pro-inflammatory genes pertaining to innate and adaptive immune responses. Interestingly, PP CD11c+ phagocytes also differentially expressed genes in response to C. albicans that were important in the protection of the mucosal barrier. These results highlight that the mucosal barrier not only responds to C. albicans, but also aids in the protection of the host.
Practical preparation of potentially anesthetic fluorinated ethyl methyl ethers by means of bromine trifluoride and other methods

Abstract Synthetic methods, especially those that use bromine trifluoride as a fluorinating agent, are described for the preparation of a number of fluorinated ethyl methyl ethers in good yield and high purity. In all cases, medium-scale syntheses (8–22 g) of potentially anesthetic compounds have been accomplished. The compounds are of sufficient purity (>99%) for biological evaluation.
Robust Nonparametric Descriptors for Clustering Quantification in Single-Molecule Localization Microscopy

Single-molecule localization microscopy (SMLM) has been utilized broadly in imaging biological molecules in various biological systems, allowing quantitative analyses on the spatial organizations and patterns of these molecules. However, parameters are needed in many of the currently available methods or algorithms, likely introducing subjective bias in the analyses. Here, we report a robust nonparametric descriptor, J'(r) , for quantifying the spatial organization of molecules in single-molecule localization microscopy. J'(r) , based on nearest neighbor distribution functions, does not require any parameter as an input for analyzing point patterns. We show that it displays a valley shape in the presence of clusters of molecules, and the characteristics of the valley reliably report the clustering features in the data. More importantly, the position of the J'(r) valley (rJ'm) depends exclusively on the density of clustering molecules. Therefore, it is ideal for direct measurements of clustering density of molecules in single-molecule localization microscopy.
Preparation of O-(Silyl)benzyl Alcohols

Abstract Abstract: γ-Hydroxysilanes 4 can be easily prepared from bromosilyl ethers 3 by a reaction involving 1,4-migration of the silicon group from oxygen to carbon.
Dissection of molecular assembly dynamics by tracking orientation and position of single molecules in live cells

Regulation of order, such as orientation and conformation, drives the function of most molecular assemblies in living cells but remains difficult to measure accurately through space and time. We built an instantaneous fluorescence polarization microscope, which simultaneously images position and orientation of fluorophores in living cells with single-molecule sensitivity and a time resolution of 100 ms. We developed image acquisition and analysis methods to track single particles that interact with higher-order assemblies of molecules. We tracked the fluctuations in position and orientation of molecules from the level of an ensemble of fluorophores down to single fluorophores. We tested our system in vitro using fluorescently labeled DNA and F-actin, in which the ensemble orientation of polarized fluorescence is known. We then tracked the orientation of sparsely labeled F-actin network at the leading edge of migrating human keratinocytes, revealing the anisotropic distribution of actin filaments relative to the local retrograde flow of the F-actin network. Additionally, we analyzed the position and orientation of septin-GFP molecules incorporated in septin bundles in growing hyphae of a filamentous fungus. Our data indicate that septin-GFP molecules undergo positional fluctuations within ∼350 nm of the binding site and angular fluctuations within ∼30° of the central orientation of the bundle. By reporting position and orientation of molecules while they form dynamic higher-order structures, our approach can provide insights into how micrometer-scale ordered assemblies emerge from nanoscale molecules in living cells.
E3: Entailment-driven Extracting and Editing for Conversational Machine Reading.

Conversational machine reading systems help users answer high-level questions (e.g. determine if they qualify for particular government benefits) when they do not know the exact rules by which the determination is made (e.g. whether they need certain income levels or veteran status). The key challenge is that these rules are only provided in the form of a procedural text (e.g. guidelines from government website) which the system must read to figure out what to ask the user. We present a new conversational machine reading model that jointly extracts a set of decision rules from the procedural text while reasoning about which are entailed by the conversational history and which still need to be edited to create questions for the user. On the recently introduced ShARC conversational machine reading dataset, our Entailment-driven Extract and Edit network (E3) achieves a new state-of-the-art, outperforming existing systems as well as a new BERT-based baseline. In addition, by explicitly highlighting which information still needs to be gathered, E3 provides a more explainable alternative to prior work. We release source code for our models and experiments at https://github.com/vzhong/e3.
Designing fecal microbiota transplant trials that account for differences in donor stool efficacy

Fecal microbiota transplantation is a highly effective intervention for patients suffering from recurrent Clostridium difficile, a common hospital-acquired infection. Fecal microbiota transplantation's success as a therapy for C. difficile has inspired interest in performing clinical trials that experiment with fecal microbiota transplantation as a therapy for other conditions like inflammatory bowel disease, obesity, diabetes, and Parkinson's disease. Results from clinical trials that use fecal microbiota transplantation to treat inflammatory bowel disease suggest that, for at least one condition beyond C. difficile, most fecal microbiota transplantation donors produce stool that is not efficacious. The optimal strategies for identifying and using efficacious donors have not been investigated. We therefore examined the optimal Bayesian response-adaptive strategy for allocating patients to donors and formulated a computationally tractable myopic heuristic. This heuristic computes the probability that a donor is efficacious by updating prior expectations about the efficacy of fecal microbiota transplantation, the placebo rate, and the fraction of donors that produce efficacious stool. In simulations designed to mimic a recent fecal microbiota transplantation clinical trial, for which traditional power calculations predict [Formula: see text] statistical power, we found that accounting for differences in donor stool efficacy reduced the predicted statistical power to [Formula: see text]. For these simulations, using the heuristic Bayesian allocation strategy more than quadrupled the statistical power to [Formula: see text]. We use the results of similar simulations to make recommendations about the number of patients, the number of donors, and the choice of clinical endpoint that clinical trials should use to optimize their ability to detect if fecal microbiota transplantation is effective for treating a condition.
Synthesis of Alkylidenecyclopentenones and Dialkylidenecyclopentenones via the Coupling of Propargylic Alcohol and 2-Alkyne-1,4-diol Derivatives with Cyclopropylcarbene–Chromium Complexes

Abstract The coupling of propargylic alcohols and their derivatives with cyclopropylcarbene–chromium complexes has been investigated. The coupling reaction leads to alkylidenecyclopentenones or alkoxyalkyl-cyclopentenones, depending on the leaving group ability of the propargyl substituent. A mechanism involving formation of a cyclopentadienone, followed by reduction and β-elimination is proposed. Coupling of cyclopropylcarbene complexes with 2-alkyne-1,4-diol derivatives leads to dialkylidenecyclopentenone derivatives via a double elimination process.
Estimating the social cost of congestion using the bottleneck model

Abstract This paper uses the bottleneck model of Vickrey (1969) to empirically measure the social cost of traffic congestion in the US. Using a detailed trip-level data, we estimate extra travel time over and above hypothetical free-flow travel time, which we call “queuing time”, for each average commute trip. The estimated individual queuing time implies that the annual cost of congestion borne by all US commuters is about 29 billion dollars. We find that a higher level of congestion in a city may be attributed to a smaller per capita road stock in the city. This paper also empirically quantifies a toll that depends both on the commuter's arrival time and trip distance.
Catalytic macrocyclizations of thietanes and thiiranes by metal carbonyl complexes.

This Account summarizes our recent studies of the catalytic transformations of thietanes and thiiranes by metal carbonyl complexes of the third row of the transition elements. The goal of the work has been to prepare polythioether macrocycles (thiacrowns) catalytically. This has been achieved with high success for certain thietane reactions. Thiiranes, on the other hand, tend to yield macrocyclic polydisulfides, but it has recently been found that these reactions can be redirected toward the thiacrown products by using certain alkyne carboxylates as cocatalysts. Vinylthiiranes are transformed into 3,6-dihydro-1,2-dithiins catalytically in excellent yield via W(CO)5(vinylthiirane) complexes.
Two novel acentric borate fluorides: M3B6O11F2 (M = Sr, Ba).

Two novel, noncentrosymmetric borate fluorides, Sr(3)B(6)O(11)F(2) and Ba(3)B(6)O(11)F(2), have been synthesized hydrothermally and their structures determined. The compounds are isostructural, crystallizing in space group P2(1), having lattice parameters of a = 6.4093 (13) A, b = 8.2898 (17) A, c = 9.3656 (19) A, and β = 101.51 (3)° for Sr(3)B(6)O(11)F(2) and a = 6.5572 (13) A, b = 8.5107 (17) A, c = 9.6726 (19) A, and β = 101.21 (3)° for Ba(3)B(6)O(11)F(2). The structure consists of a complex triple-ring borate framework having aligned triangular [BO(3)] groups that impart polarity. Fluorine atoms are bound only to the alkaline-earth metals and are not part of the borate framework, resulting in a vastly different structure from those of the hydrated borates Sr(3)B(6)O(11)(OH)(2) and Ba(3)B(6)O(11)(OH)(2) with similar formulas. The title compounds are transparent to nearly 200 nm, making them potentially useful for deep-ultraviolet nonlinear-optical applications.
Iodine(III)-Mediated Cyclization of Unsaturated O-Alkyl Hydroxamates: Silyl-Assisted Access to α-Vinyl and α-(2-Silylvinyl) Lactams

The embodiment of lactam rings within a wealth of physiologically active natural products and pharmaceutical agents ensures that the development of synthetic methods, which facilitate the preparation of these saturated N-heterocycles, is of critical importance. Herein the development of a versatile method for the synthesis of 4 to 8-membered α-vinyl and α-(2-silylvinyl) lactams involving the iodine(III)-mediated oxidative cyclization of unsaturated O-alkyl hydroxamates, which encompass an allylsilane, is reported. Importantly, the outcome of this transformation can be effectively controlled through variation of the substitution pattern at the silicon center. While allyltrimethylsilanes undergo ring closure with desilylation to form α-vinyl lactams, the corresponding triisopropyl and triphenylsilanes cyclize without loss of the larger silyl group to form E-vinylsilanes with excellent stereoselectivity. From a mechanistic standpoint, it is proposed that this reaction proceeds via concerted alkene addition of a singlet nitrenium ion (or its equivalent) to form a bicyclic N-acyl-N-alkoxyaziridinium ion, which undergoes eliminative ring opening.
N 3 LO predictions for the decay of the Higgs boson to bottom quarks

We present a fully-differential calculation of the $$ H\to b\overline{b} $$ decay at next-to-next-to-next-to-leading order (N3LO) accuracy. Our calculation considers diagrams in which the Higgs boson couples directly to the bottom quarks, i.e. the perturbative order we consider is $$ \mathcal{O}\left({\alpha}_s^3{y}_b^2\right) $$ . In order to regulate the infrared divergences present at this order we use the Projection-to-Born technique coupled with N -jettiness slicing. After validating our methodology at next-to-next-to-leading order (NNLO) we present exclusive jet rates and differential distributions for jet observables at N3LO accuracy using the Durham jet algorithm in the Higgs rest frame.
Sparse Approximation via Generating Point Sets

For a set P of n points in the unit ball b⊆ Rd, consider the problem of finding a small subset T⊆ P such that its convex-hull e-approximates the convex-hull of the original set. Specifically, the Hausdorff distance between the convex hull of T and the convex hull of P should be at most e. We present an efficient algorithm to compute such an e′-approximation of size kalg, where e ′ is a function of e and kalg is a function of the minimum size kopt of such an e-approximation. Surprisingly, there is no dependence on the dimension d in either of the bounds. Furthermore, every point of P can be e-approximated by a convex-combination of points of T that is O(1/e2)-sparse.Our result can be viewed as a method for sparse, convex autoencoding: approximately representing the data in a compact way using sparse combinations of a small subset T of the original data. The new algorithm can be kernelized, and it preserves sparsity in the original input.
Pressure-Induced Cation Migration and Volume Expansion in the Defect Pyrochlores ANbWO6 (A = NH4+, Rb+, H+, K+)

The structural and compositional evolution of four members of the ANbWO6 (A = NH4+, Rb+, H+, K+) defect pyrochlore family have been studied as a function of pressure up to 7 GPa, using a diamond an...
CATALYTIC GENERATION AND TRAPPING OF ACYLMETALS CONTAINING NI AND CU WITH ENOLATES

Abstract Carbonylative cyclization of iodoarenes and iodoalkenes containing a proximal enolate precursor can selectively provide either cyclic ketones or lactones in the presence of Ni or Cu catalysts via trapping of putative acylmetal derivatives with C - or O -enolates, respectively; the ring size and regioselectivity of the reaction may be predicted based on two generalizations derived from the recently developed corresponding Pd-catalyzed reaction.
Implications of EMU for Exchange Rate Policy in Central and Eastern Europe

In view of the requirements of Stage 2 of European Monetary Union (EMU) for accession to the European Union, this paper examines the desirability for, and the ability of, the lead candidates in Central and Eastern Europe to participate in the new exchange rate mechanism (ERM2) and eventually in EMU. For most of these countries the benefits are likely to outweigh the cost of participation. After successfully meeting the basic conditions (wage flexibility, prudent fiscal and monetary stance, financial system soundness) for ERM2, each candidate should be able to shadow the euro, with sufficient flexibility around the central rate, prior to formal participation. The paper concludes with a discussion of two policy dilemmas.
Cost/Performance in Modern Data Stores: How Data Caching Systems Succeed

Data in traditional "caching" data systems resides on secondary storage, and is read into main memory only when operated on. This limits system performance. Main memory data stores with data always in main memory are much faster. But this performance comes at a cost. In this paper, we analyze the costs of both in-memory operations and secondary storage operations where data is not "in cache". We study the performance impact of cache misses on caching system performance. The analysis considers both execution and storage costs. Based on our analysis, we derive cost/performance results for a data caching system [Deuteronomy and its Bw-tree] and a main memory system [MassTree] to understand where each demonstrates the best cost per operation, what is driving the cost differences, and the scale of the differences. This analysis (1) provides insight into why data caching systems continue to dominate the market; (2) points to higher performance that does not rely on simply increasing main memory cache size; and (3) suggests a path to lower costs and hence better cost/performance.
A fundamental improvement to Ericksen-Leslie kinematics

We demonstrate theory and computations for finite-energy line defect solutions in an improvement of Ericksen-Leslie liquid crystal theory. Planar director fields are considered in two and three space dimensions, and we demonstrate straight as well as loop disclination solutions. The possibility of static balance of forces in the presence of a disclination and in the absence of flow and body forces is discussed. The work exploits an implicit conceptual connection between the Weingarten-Volterra characterization of possible jumps in certain potential fields and the Stokes-Helmholtz resolution of vector fields. The theoretical basis of our work is compared and contrasted with the theory of Volterra disclinations in elasticity. Physical reasoning precluding a gauge-invariant structure for the model is also presented.
Noisin: Unbiased Regularization for Recurrent Neural Networks

Recurrent neural networks (RNNs) are powerful models of sequential data. They have been successfully used in domains such as text and speech. However, RNNs are susceptible to overfitting; regularization is important. In this paper we develop Noisin, a new method for regularizing RNNs. Noisin injects random noise into the hidden states of the RNN and then maximizes the corresponding marginal likelihood of the data. We show how Noisin applies to any RNN and we study many different types of noise. Noisin is unbiased--it preserves the underlying RNN on average. We characterize how Noisin regularizes its RNN both theoretically and empirically. On language modeling benchmarks, Noisin improves over dropout by as much as 12.2% on the Penn Treebank and 9.4% on the Wikitext-2 dataset. We also compared the state-of-the-art language model of Yang et al. 2017, both with and without Noisin. On the Penn Treebank, the method with Noisin more quickly reaches state-of-the-art performance.
Scalable Motif-aware Graph Clustering

We develop new methods based on graph motifs for graph clustering, allowing more efficient detection of communities within networks. We focus on triangles within graphs, but our techniques extend to other clique motifs as well. Our intuition, which has been suggested but not formalized similarly in previous works, is that triangles are a better signature of community than edges. We therefore generalize the notion of conductance for a graph to triangle conductance, where the edges are weighted according to the number of triangles containing the edge. This methodology allows us to develop variations of several existing clustering techniques, including spectral clustering, that minimize triangles split by the cluster instead of edges cut by the cluster. We provide theoretical results in a planted partition model to demonstrate the potential for triangle conductance in clustering problems. We then show experimentally the effectiveness of our methods to multiple applications in machine learning and graph mining.
Rethinking interphase representations for modeling viscoelastic properties for polymer nanocomposites

Abstract Numerical modeling of viscoelastic properties is critical to developing the structure-property relationship of polymer nanocomposites. While it is recognized that the altered polymer region near filler particles, the interphase, significantly contributes to enhancements of composite properties, the spatial distribution of interphase properties is rarely considered due to lack of local property measurements. In recent years, the Atomic Force Microscopy (AFM) technique has begun to make local property measurements of the interphase available. In the light of the increasing availability of AFM data, in this work a new interphase representation for modeling the viscoelastic properties of polymer nanocomposites is proposed. The proposed interphase representation disentangles the interphase behavior by two separate components – single-body interphase gradient and multi-body compound effect, whose functional forms are learned via data mining. The proposed interphase representation is integrated into a Finite Element model, and the effects of each component of the interphase representations are numerically studied. In addition, the advantages of the proposed interphase representation are demonstrated by comparison to a prior simulation work in which only a uniform effective property of the interphase is considered. Moreover, the proposed interphase representation is utilized to solve the inverse problem of inferring spatial distribution of local properties using Bayesian optimization-based inference on experimental data.
Tight lower bound on the probability of a binomial exceeding its expectation

Abstract We give the proof of a tight lower bound on the probability that a binomial random variable exceeds its expected value. The inequality plays an important role in a variety of contexts, including the analysis of relative deviation bounds in learning theory and generalization bounds for unbounded loss functions.
Locality in Network Optimization

In probability theory and statistics notions of correlation among random variables, decay of correlation and bias–variance tradeoff are fundamental. In this work, we introduce analogous notions in optimization and show their usefulness in a concrete setting. We propose a general notion of correlation among variables in optimization procedures that is based on the sensitivity of optimal points upon (possibly finite) perturbations. We present a canonical instance in network optimization (the min-cost network flow problem) that exhibits locality, i.e., a setting where the correlation decays as a function of the graph-theoretical distance in the network. In the case of warm-start reoptimization, we develop a general approach to localize a given optimization routine in order to exploit locality. We show that the localization mechanism is responsible for introducing a bias in the original algorithm, and that the bias–variance tradeoff that emerges can be exploited to minimize the computational complexity required to reach a prescribed level of error accuracy. We provide numerical evidence to support our claims.
Improving Viterbi is Hard: Better Runtimes Imply Faster Clique Algorithms

The classic algorithm of Viterbi computes the most likely path in a Hidden Markov Model (HMM) that results in a given sequence of observations. It runs in time $O(Tn^2)$ given a sequence of $T$ observations from a HMM with $n$ states. Despite significant interest in the problem and prolonged effort by different communities, no known algorithm achieves more than a polylogarithmic speedup. In this paper, we explain this difficulty by providing matching conditional lower bounds. We show that the Viterbi algorithm runtime is optimal up to subpolynomial factors even when the number of distinct observations is small. Our lower bounds are based on assumptions that the best known algorithms for the All-Pairs Shortest Paths problem (APSP) and for the Max-Weight $k$-Clique problem in edge-weighted graphs are essentially tight. Finally, using a recent algorithm by Green Larsen and Williams for online Boolean matrix-vector multiplication, we get a $2^{\Omega(\sqrt {\log n})}$ speedup for the Viterbi algorithm when there are few distinct transition probabilities in the HMM.
Increasing the action gap: new operators for reinforcement learning

This paper introduces new optimality-preserving operators on Q-functions. We first describe an operator for tabular representations, the consistent Bellman operator, which incorporates a notion of local policy consistency. We show that this local consistency leads to an increase in the action gap at each state; increasing this gap, we argue, mitigates the undesirable effects of approximation and estimation errors on the induced greedy policies. This operator can also be applied to discretized continuous space and time problems, and we provide empirical results evidencing superior performance in this context. Extending the idea of a locally consistent operator, we then derive sufficient conditions for an operator to preserve optimality, leading to a family of operators which includes our consistent Bellman operator. As corollaries we provide a proof of optimality for Baird's advantage learning algorithm and derive other gap-increasing operators with interesting properties. We conclude with an empirical study on 60 Atari 2600 games illustrating the strong potential of these new operators.
Robust power system state estimation for the nonlinear AC flow model

An important monitoring task for power systems is accurate estimation of the system operation state. Under the nonlinear AC power flow model, the state estimation (SE) problem is inherently nonconvex giving rise to many local optima. In addition to nonconvexity, SE is challenged by data integrity and cyber-security issues. Unfortunately, existing robust (R-) SE schemes employed routinely in practice rely on iterative solvers, which are sensitive to initialization and cannot ensure global optimality. A novel R-SE approach is formulated here by capitalizing on the sparsity of an overcomplete outlier vector model. Observability and identifiability issues of this model are investigated, and neat links are established between R-SE and error control coding. The convex semidefinite relaxation (SDR) technique is further pursued to render the nonconvex R-SE problem efficiently solvable. The resultant algorithm markedly out-performs existing iterative alternatives, as corroborated through numerical tests on the standard IEEE 30-bus system.
Learning Patient Representations from Text

Mining electronic health records for patients who satisfy a set of predefined criteria is known in medical informatics as phenotyping. Phenotyping has numerous applications such as outcome prediction, clinical trial recruitment, and retrospective studies. Supervised machine learning for phenotyping typically relies on sparse patient representations such as bag-of-words. We consider an alternative that involves learning patient representations. We develop a neural network model for learning patient representations and show that the learned representations are general enough to obtain state-of-the-art performance on a standard comorbidity detection task.
Estimating the distribution of Galaxy Morphologies on a continuous space

The incredible variety of galaxy shapes cannot be summarized by human defined discrete classes of shapes without causing a possibly large loss of information. Dictionary learning and sparse coding allow us to reduce the high dimensional space of shapes into a manageable low dimensional continuous vector space. Statistical inference can be done in the reduced space via probability distribution estimation and manifold estimation.
Irrationality proofs à la Hermite

In [1] Niven used the integral to give a well-known proof of the irrationality of π. Recently Zhou and Markov [2] used a recurrence relation satisfied by this integral to present an alternative proof which may be more direct than Niven's. Niven did not cite any references in [1] and thus the origin or H n seems rather mysterious and ingenious. However if we heed Abel's advice to ‘study the masters’, we find that Hn emerged much more naturally from the great works of Lambert [3] and Hermite [4].
A search for a spectral technique to solve nonlinear fractional differential equations

Abstract A spectral decomposition method is used to obtain solutions to a class of nonlinear differential equations. We extend this approach to the analysis of the fractional form of these equations and demonstrate the method by applying it to the fractional Riccati equation, the fractional logistic equation and a fractional cubic equation. The solutions reduce to those of the ordinary nonlinear differential equations, when the order of the fractional derivative is α = 1 . The exact analytic solutions to the fractional nonlinear differential equations had not been previously known, so we evaluate how well the derived solutions satisfy the corresponding fractional dynamic equations. In the three cases we find a small, apparently generic, systematic error that we are not able to fully interpret.