cssi/SciSciGPT-SciSciNet huggingface dataset:
Electronic Structure Modeling of Electrochemical Reactions at Electrode/Electrolyte Interfaces in Lithium Ion Batteries

We review recent ab initio molecular dynamics studies of electrode/electrolyte interfaces in lithium ion batteries. Our goals are to introduce experimentalists to simulation techniques applicable to models which are arguably most faithful to experimental conditions so far, and to emphasize to theorists that the inherently interdisciplinary nature of this subject requires bridging the gap between solid and liquid state perspectives. We consider liquid ethylene carbonate (EC) decomposition on lithium intercalated graphite, lithium metal, oxide-coated graphite, and spinel manganese oxide surfaces. These calculations are put in the context of more widely studied water–solid interfaces. Our main themes include kinetically controlled two-electron-induced reactions, the breaking of a previously much neglected chemical bond in EC, and electron tunneling. Future work on modeling batteries at atomic length scales requires capabilities beyond state-of-the-art, which emphasizes that applied battery research can and s...
Stereospecific Transformation of Terpinen-4-ol to Dihydropinol

Abstract A simple transformation of terpinen-4-ol (1) to dihydropinol (4) is described. S-Terpinen-4-ol was stereospecifically oxidized with vanadyl diacac to cis-terpinen-4-ol-epoxide (2). Reduction with LiAlD4 afforded the unexpected 1R-deutero-2S,4S-dihydroxy menthane (3) which was cyclized in acid to 4.
Implications of solar and atmospheric neutrinos

Abstract The importance of non-zero neutrino mass as a probe of particle physics, astrophysics, and cosmology is emphasized. The present status and future prospects for the solar and atmospheric neutrinos are reviewed, and the implications for neutrino mass and mixing in 2, 3, and 4-neutrino schemes are discussed. The possibilities for significant mixing between ordinary and light sterile neutrinos are described.
Ru-BICP-Catalyzed Asymmetric Hydrogenation of Aromatic Ketones.

The design and synthesis of effective enantioselective catalysts for hydrogenation of simple ketones remains a challenging problem.1 Recently, Noyori2 disclosed a ternary catalyst system consisting of Ru-BINAP-chiral diamine-KOH, which is highly efficient in the asymmetric hydrogenation of a variety of simple ketones lacking a secondary coordinating functional group. We have developed rhodium complexes with a conformationally rigid, electron-rich bidentate phosphine ligand (PennPhos)3 as highly enantioselective catalysts for hydrogenation of both aryl alkyl and dialkyl ketones. In a related study, we have designed and synthesized a new conformationally rigid 1,4-bisphosphine, (2R,2′R)-bis(diphenylphosphino)-(1R,1′R)-dicyclopentane (BICP). Rh-BICP gives excellent enantioselectivity upon asymmetric hydrogenation of 2-(acylamino)acrylic acids.4 Prompted by these encouraging results, we were interested in exploring the Ru-BICP-catalyzed hydrogenation of simple ketones using Noyori’s protocol (Scheme 1). Our experimental results on a Ru-BICP catalytic system indicate an important finding of possible multipoint interactions between a chiral chelating diamine and acetylthiophene derivatives.
Network analysis to evaluate the impact of research funding on research community consolidation

In 2004, the Alfred P. Sloan Foundation launched a new program focused on incubating a new field, "Microbiology of the Built Environment" (MoBE). By the end of 2017, the program had supported the publication of hundreds of scholarly works, but it was unclear to what extent it had stimulated the development of a new research community. We identified 307 works funded by the MoBE program, as well as a comparison set of 698 authors who published in the same journals during the same period of time but were not part of the Sloan Foundation-funded collaboration. Our analysis of collaboration networks for both groups of authors suggests that the Sloan Foundation's program resulted in a more consolidated community of researchers, specifically in terms of number of components, diameter, density, and transitivity of the coauthor networks. In addition to highlighting the success of this particular program, our method could be applied to other fields to examine the impact of funding programs and other large-scale initiatives on the formation of research communities.
On Obfuscating Point Functions.

We study the problem of obfuscation in the context of point functions (also known as delta functions). A point function is a Boolean function that assumes the value 1 at exactly one point. Our main results are as follows: 1. We provide a simple construction of efficient obfuscators for point functions for a slightly relaxed notion of obfuscation wherein the size of the simulator has an inverse polynomial dependency on the distinguishing probability which is nonetheless impossible for general circuits. This is the first known construction of obfuscators for a non-trivial family of functions under general computational assumptions. Our obfuscator is based on a probabilistic hash function constructed from a very strong one-way permutation, and does not require any set-up assumptions. Our construction also yields an obfuscator for point functions with multi-bit output. 2. We show that such a strong one-way permutation wherein any polynomial-sized circuit inverts the permutation on at most a polynomial number of inputs can be realized using a random permutation oracle. We prove the result by improving on the counting argument used in [GT00]; this result may be of independent interest. It follows that our construction yields obfuscators for point functions in the non-programmable random permutation oracle model (in the sense of [N02]). Furthermore, we prove that an assumption like the one we used is necessary for our obfuscator construction. 3. Finally, we establish two impossibility results on obfuscating point functions which indicate that the limitations on our construction (in simulating only adversaries with single-bit output and in using non-uniform advice in our simulator) are in some sense inherent. The first of the two results is a consequence of a simple characterization of functions that can be obfuscated against general adversaries with multi-bit output as the class of functions that are efficiently and exactly learnable using membership queries. We stress that prior to this work, what is known about obfuscation are negative results for the general class of circuits [BGI+01] and positive results in the random oracle model [LPS04] or under non-standard number-theoretic assumptions [C97]. This work represents the first effort to bridge the gap between the two for a natural class of functionalities. ∗hoeteck@cs.berkeley.edu. Work supported by US-Israel BSF Grant 2002246.
Ultra-accurate complex disorder prediction: Case study of neurodevelopmental disorders

Early prediction of complex disorders (e.g., autism and other neurodevelopmental disorders) is one of the fundamental goals of precision medicine and personalized genomics. An early prediction of complex disorders can have a significant impact on increasing the effectiveness of interventions and treatments in improving the prognosis and, in many cases, enhancing the quality of life in the affected patients. Considering the genetic heritability of neurodevelopmental disorders, we are proposing a novel framework for utilizing rare coding variation for early prediction of these disorders. We provide a novel formulation for the Ultra-Accurate Disorder Prediction (UADP) problem and develop a novel combinatorial framework for solving this problem. The primary goal of this novel framework, denoted as Odin (Oracle for DIsorder predictioN), is to make an accurate prediction for a subset of affected cases while having virtually zero false positive predictions for unaffected samples. Note that in the Odin framework we will take advantage of the available functional information (e.g., pairwise coexpression of genes during brain development) to increase the prediction power beyond genes with recurrent variants. Application of our method accurately recovers an additional 8% of autism cases without known recurrent mutated genes in the training set and with a less than 0.5% false positive prediction based on our analysis of unaffected controls. Furthermore, Odin predicted a set of 391 genes that severe variants in these genes can cause autism or other developmental delay disorders.
Oxazoline formation via a palladium-catalyzed cyclization: A direct, stereoselective approach to cis-5-amino-2-cyclopenten-1-ol derivatives

Abstract Alanyl substituted 4-amino-2-cyclopenten-1-yl acetates were obtained optically pure in three steps from cyclopentadiene. The Pd 0 catalyzed cyclization of these allylic acetates was studied using protected and unprotected derivatives. A novel oxazoline synthesis was developed and its utility was demonstrated by the preparation of a cis -5-amino-2-cyclopenten-1-ol derivative.
Chirally enshrouded 2,6-diarylbenzoic acids with two-fold symmetry

Abstract The synthesis and characterization of a new design of W-shaped chiral clefts with C 2 symmetry is presented. The molecules are based on the 2,6-diarylbenzoic acid motif. A series of syn/anti isomers are discussed with respect to their symmetry, configurational stability, and suitability for the development of chiral materials.
EWS-FLI-1 creates a cell surface microenvironment conducive to IGF signaling by inducing pappalysin-1

Ewing sarcoma is an aggressive cancer of bone and soft tissue in children with poor prognosis. It is characterized by the chromosomal translocation between EWS and an Ets family transcription factor, most commonly FLI-1. EWS-FLI-1 fusion accounts for 85% of Ewing sarcoma cases. EWS-FLI-1 regulates the expression of a number of genes important for sarcomagenesis, can transform NIH3T3 and C3H10T1/2 cells, and is necessary for proliferation and tumorigenicity of Ewing sarcoma cells, suggesting that EWS-FLI-1 is the causative oncoprotein. Here we report that EWS-FLI-1 induces the expression of pappalysin-1 (PAPPA), a cell surface protease that degrades IGF binding proteins (IGFBPs) and increases the bioavailability of IGF. EWS-FLI-1 binds to the pappalysin-1 gene promoter and stimulates the expression of pappalysin-1, leading to degradation of IGFBPs and enhanced IGF signaling. Silencing of pappalysin-1 strongly inhibited anchorage-dependent and anchorage-independent growth as well as xenograft tumorigenicity of Ewing sarcoma cells. These results suggest that EWS-FLI-1 creates a cell surface microenvironment conducive to IGF signaling by inducing pappalysin-1, which emerged as a novel target to inhibit IGF signaling in Ewing sarcoma.
New polar intermetallic phases RE2Zn5Tt (RE = La-Nd; Tt = Sn and Pb): synthesis, structure, chemical bonding, and magnetic properties

Reported are the synthesis, crystal structure, electronic structure, and magnetic properties of a series of zinc-rich ternary phases with formulas RE2Zn5Tt (RE = La-Nd; Tt = Sn and Pb). The structures of these compounds have been established by single-crystal and powder X-ray diffraction. They crystallize in the orthorhombic space group Cmcm (No. 63, LaRhSn2 structure type, Pearson symbol oC32). The most prominent structural feature is the trigonal-planar coordination of the Sn(Pb) atoms; the latter interconnect layers of Zn atoms to comprise a complex [Zn5Tt] polyanionic framework. The structural relationships between the structure of the title compounds and the EuIn4, La3Al11, and YIrGe2 structure types are highlighted. Temperature-dependent DC magnetization measurements indicate Pauli-like paramagnetism for La2Zn5Sn, while Ce2Zn5Sn, Pr2Zn5Sn, and Nd2Zn5Sn display Curie-Weiss behavior in the high-temperature regime. At cryogenic temperatures, the magnetic responses of Ce2Zn5Sn, Pr2Zn5Sn, and Nd2Zn5Sn appear to deviate from the Curie-Weiss law; however, no magnetic orderings could be observed down to 5 K. Theoretical considerations of the electronic structure on the basis of the tight-binding linear muffin-tin orbital (TB-LMTO-ASA) method are also presented and discussed.
Acid catalyzed nitrile thiolysis of 3-amino-acrylonitriles, toward the synthesis of 3,4-substituted-5-amino-isothiazoles

Abstract Application of an acid-catalyzed thioamidation of β-amino-acrylonitriles to the corresponding β-amino-thioacrylamides toward the synthesis of 3,4-substituted-5-amino-isothiazoles is described. The greatest yields were observed for examples with electron rich aromatic systems. This method uses inexpensive and easily handled reagents.
Synthesis and cytotoxicity of 2-acetyl-4,8-dihydrobenzodithiophene-4, 8-dione derivatives.

2-Acetyl-4,8-dihydrobenzo[1,2-b:4,5-b']dithiophene-4,8-dione (9) and 2-acetyl-4,8-dihydrobenzo-[1,2-b:5,4-b']dithiophene-4,8-dione (19), together with 10 related mono- and disubstituted derivatives, were synthesized and evaluated in vitro by NC against eight cancer types. All compounds showed significant activity against melanoma, HL-60 leukemia, NCI-H23 non-small-cell lung cancer, OVCAR-3 ovarian cancer, and MDA-MB-435 and MDA-N breast cancer cell lines. Compound 11, 2-(1'-acetoxyethyl)-4,8-dihydrobenzo[1,2-b:4,5-b']dithiophene-4,8-dione, showed the highest overall potency (mean GI 50 = 40 nM).
Tandem multicomponent/click reactions : synthesis of functionalized oxazoles and tetrazoles from acyl cyanides

The combination of multicomponent condensations with post-condensation dipolar cycloaddition reactions provides a useful route to densely functionalized oxazoles and tetrazoles in just two synthetic steps.
Serum extracellular vesicle depletion processes affect release and infectivity of HIV-1 in culture.

Extracellular vesicles (EVs) are involved in intercellular communication and affect processes including immune and antiviral responses. Blood serum, a common cell culture medium component, is replete with EVs and must be depleted prior to EV-related experiments. The extent to which depletion processes deplete non-EV particles is incompletely understood, but depleted serum is associated with reduced viability and growth in cell culture. Here, we examined whether serum depleted by two methods affected HIV-1 replication. In cell lines, including HIV-1 latency models, increased HIV-1 production was observed, along with changes in cell behavior and viability. Add-back of ultracentrifuge pellets (enriched in EVs but possibly other particles) rescued baseline HIV-1 production. Primary cells were less sensitive to serum depletion processes. Virus produced under processed serum conditions was more infectious. Finally, changes in cellular metabolism, surface markers, and gene expression, but not miRNA profiles, were associated with depleted serum culture. In conclusion, depleted serum conditions have a substantial effect on HIV-1 production and infectivity. Dependence of cell cultures on “whole serum” must be examined carefully along with other experimental variables, keeping in mind that the effects of EVs may be accompanied by or confused with those of closely associated or physically similar particles.
Facile Enantioselective Synthesis of Two New Bicyclic Chiral Templates

Abstract Optically active bicyclic dienes, 4 and 5 have been enantioselectively prepared in three and four steps, respectively. Mixtures of predominantly either the R or S enantiomer were obtained via an asymmetric alkylation of a chiral cnamine.
Re-evaluating evolution in the HIV reservoir

Despite antiretroviral therapy (ART), a latent reservoir of replication-competent HIV-1 persists in resting memory CD4+ T-cells and precludes cure. Lorenzo-Redondo et al. [Nature 530:51-56, 2016] analyzed HIV-1 sequences collected from three individuals during the first six months of ART, discovered specific patterns of sequence evolution, and concluded that viral replication persists during therapy. We believe these evolutionary patterns are artifacts of rapidly decaying viral subpopulations present during the first months of therapy and are not characteristic of the long-lived reservoir. The study therefore provides no evidence that ongoing replication is an additional barrier to cure for treated individuals who consistently maintain low viral loads.
Palladium-catalyzed carbene insertion into benzyl bromides

Abstract Palladium can catalyze the insertion of ethyl diazoacetate into benzyl bromides. The key step in the catalytic cycle is the migratory insertion of a carbene, derived from ethyl diazoacetate, into a Pd–C bond.
Diet Influences Early Microbiota Development in Dairy Calves without Long-Term Impacts on Milk Production.

ABSTRACT Gastrointestinal tract (GIT) microorganisms play important roles in the health of ruminant livestock and affect the production of agriculturally relevant products, including milk and meat. Despite this link, interventions to alter the adult microbiota to improve production have proven ineffective, as established microbial communities are resilient to change. In contrast, developing communities in young animals may be more easily altered but are less well studied. Here, we measured the GIT-associated microbiota of 45 Holstein dairy cows from 2 weeks to the first lactation cycle, using Illumina amplicon sequencing of bacterial (16S rRNA V4), archaeal (16S rRNA V6 to V8), and fungal (internal transcribed region 1 [ITS1]) communities. Fecal and ruminal microbiota of cows raised on calf starter grains and/or corn silage were correlated to lifetime growth as well as milk production during the first lactation cycle, in order to determine whether early-life diets have long-term impacts. Significant diet-associated differences in total microbial communities and specific taxa were observed by weaning (8 weeks), but all animals reached an adult-like composition between weaning and 1 year. While some calf-diet-driven differences were apparent in the microbiota of adult cows, these dissimilarities did not correlate with animal growth or milk production. This finding suggests that initial microbial community establishment is affected by early-life diet but postweaning factors have a greater influence on adult communities and production outcomes. IMPORTANCE The gut microbiota is essential for the survival of many organisms, including ruminants that rely on microorganisms for nutrient acquisition from dietary inputs for the production of products such as milk and meat. While alteration of the adult ruminant microbiota to improve production is possible, changes are often unstable and fail to persist. In contrast, the early-life microbiota may be more amenable to sustained modification. However, few studies have determined the impact of early-life interventions on downstream production. Here, we investigated the impact of agriculturally relevant calf diets, including calf starter and corn silage, on gut microbial communities, growth, and production through the first lactation cycle. Thus, this work serves to further our understanding of early-life microbiota acquisition, as well as informing future practices in livestock management.
The Curtin−Hammett Principle in Mass Spectrometry

The Curtin−Hammett principle (CHP) is an important concept in physical organic chemistry and is often utilized in the investigation of reaction mechanisms. Two reactants, A and B, in rapid equilibrium, react to form products PA and PB with rates kA and kB, respectively. If the reaction is under kinetic control and the rate of equilibration between the two reactants is much faster than the reactions to form products, then the branching ratio of products PA and PB depends solely on the difference in barrier heights for the two product channels. The CHP is based on the fact that the ratio of products formed is not determined by the reactant population ratio. However, the CHP also applies to studies in other areas of chemistry, including mass spectrometry. This Account describes work from our groups in which the results must be interpreted in light of the CHP. These studies illustrate two important implications of the CHP. First, they demonstrate how product distributions cannot be used to assess reactant str...
Complestatin synthetic studies; the effect of the amino acid configuration on peptide backbone conformation in the common western BCD macrocycle.

The synthesis and structural analysis, involving X-ray crystallographic, nuclear magnetic resonance, and computational studies of four diastereomers of the common western BCD diarylether macrocycle of the complestatins, a family of HIV entry inhibitors, has been achieved exploiting a ruthenium-promoted intramolecular S N Ar reaction. The stereogenicity of the individual phenylglycines (residues C and D) results in remarkable effects on the backbone conformation.
Syntheses of Birnessites Using Alcohols as Reducing Reagents: Effects of Synthesis Parameters on the Formation of Birnessites

This study shows that synthetic birnessite, an octahedral layered manganese oxide material called OL-1 can be synthesized with Na+, K+, Na+/Mg2+, or K+/Mg2+ ions as interlayer cations by redox reactions between permanganate and alcohols in a strong basic media. The synthesis processes were followed by powder X-ray diffraction (XRD) studies. OL-1 samples have been characterized by XRD, chemical analysis, average oxidation states measurements, and scanning electron microscopy studies. Results show that all OL-1 samples have an interlayer spacing of ∼7.0 A. The average oxidation states of manganese fall in a range of 3.60−3.70. The chemical compositions for typical Na−OL-1 and K−OL-1 are Na4.7Mn14O27.7·8.7H2O and K4.6Mn14O27.9·6.6H2O, respectively. α-MnO(OH) coexists with Na−OL-1 in the synthesis where NaMnO4 aqueous solution is added to the solution containing ethanol, water, and sodium hydroxide. When Mg(MnO4)2 was used as the oxidant, more Mg2+ ions were accommodated in OL-1 than in previous reports. The ...
Molecular Clusters of Binary and Ternary Mercury Chalcogenides: Colloidal Synthesis, Characterization, and Optical Spectra

A series of binary (HgSe) and ternary (HgSe1-xSx) mercury chalcogenide clusters are synthesized utilizing a colloidal technique involving the phase separation of metal and chalcogen precursors in the presence of strong Hg(II) coordinating ligands. The clusters vary in size between 2 and 3 nm and possess the cubic zinc blende structure of the bulk. Energy-dispersive X-ray measurements show that the composition of the ternary material can be varied throughout the entire composition range from HgS to HgSe. In all cases, the linear absorption of these binary and ternary species is narrow with well-resolved transitions at both the band edge and at higher energies. Complementary band edge emission is also observed with no apparent deep trap emission. Size- and composition (x)-dependent optical properties of these clusters are investigated using photoluminescence (PL) and photoluminescence excitation (PLE) spectra. In the case of HgSe clusters, the size-dependent behavior of up to four excited states is followed...
CoxCu1–xCr2S4 Nanocrystals: Synthesis, Magnetism, and Band Structure Calculations

Spin-based transport in semiconductor systems has been proposed as the foundation of a new class of spintronic devices. For the practical realization of such devices, it is important to identify new magnetic systems operating at room temperature that can be readily integrated with standard semiconductors. A promising class of materials for this purpose is magnetic chromium-based chalcogenides that have the spinel structure. Nanocrystals of CoxCu1–xCr2S4 have been synthesized over the entire composition range by a facile solution-based method. While CuCr2S4 is a ferromagnetic metal, CoCr2S4 is known to be a ferrimagnetic semiconductor. Systematic changes in the lattice parameter, size, and magnetic properties of the nanocrystals are observed with composition. The nanocrystals are magnetic over the entire range, with a decrease in the magnetic transition temperature with increasing Co content. Band structure calculations have been carried out to determine the electronic and magnetic structure as a function ...
Azidocarbonyl‐substituted cubanoureas

Despite the angular strain associated with the assembly of small rings, 1,2-diisocyanatocubane reacts with trimethylsilyl azide under mild conditions to form a hexacyclic ring assembly that contains an imidazolidone ring fused to one edge of cubane. This compound was identified as an azidocarbonyl-substituted cubanourea by means of X-ray crystal structure analysis of the nitro-derivative, the energetic compound N-azidocarbonyl-N1-nitrocubanourea.
Molecular nanowires of 1 nm diameter from capillary filling of single-walled carbon nanotubes

Molecular nanowires inside single-walled carbon nanotubes are produced by capillary filling. Bismuth was drawn into single-walled carbon nanotubes, where it formed single-crystal nanowires of nanometer dimensions. Metal was introduced in its gas, solution, and solid phases, with the solution phase process the most efficient and versatile method of filling. The majority of fillings are one-dimensional nanowires with high length to diameter ratios. The strong capillary effect in single-walled carbon nanotubes should allow these materials to host a wide variety of nanoscale materials.
Selective addition of amines to 5-trifluoromethyl-2,4-dichloropyrimidine induced by Lewis acids

Abstract A variety of 2,4-diamino-pyrimidine systems can be prepared from the corresponding 2,4-dichloro-pyrimidine by sequential addition of two amines, the first adding selectively to the 4-position. In contrast it was found that 2,4-dichloro-5-trifluoromethyl-pyrimidine yields a 1:1 mixture of the two possible isomers. Lewis acids were employed to increase the ratio of isomers to >10:1 in favor of the 2-addition product. Optimization of the effect of Lewis acid additives on this and other dichloropyrimidine systems will be discussed.
Total Synthesis of the Diterpenoid Alkaloid Arcutinidine Using a Strategy Inspired by Chemical Network Analysis

Arcutinidine and other arcutinidine-type diterpenoid alkaloids feature an intricate polycyclic, bridged framework with unusual connectivity. A chemical network analysis approach to the arcutane ske...
Competing Fluid Forces Control Endothelial Sprouting in a 3-D Microfluidic Vessel Bifurcation Model.

Sprouting angiogenesis—the infiltration and extension of endothelial cells from pre-existing blood vessels—helps orchestrate vascular growth and remodeling. It is now agreed that fluid forces, such as laminar shear stress due to unidirectional flow in straight vessel segments, are important regulators of angiogenesis. However, regulation of angiogenesis by the different flow dynamics that arise due to vessel branching, such as impinging flow stagnation at the base of a bifurcating vessel, are not well understood. Here we used a recently developed 3-D microfluidic model to investigate the role of the flow conditions that occur due to vessel bifurcations on endothelial sprouting. We observed that bifurcating fluid flow located at the vessel bifurcation point suppresses the formation of angiogenic sprouts. Similarly, laminar shear stress at a magnitude of ~3 dyn/cm2 applied in the branched vessels downstream of the bifurcation point, inhibited the formation of angiogenic sprouts. In contrast, co-application of ~1 µm/s average transvascular flow across the endothelial monolayer with laminar shear stress induced the formation of angiogenic sprouts. These results suggest that transvascular flow imparts a competing effect against bifurcating fluid flow and laminar shear stress in regulating endothelial sprouting. To our knowledge, these findings are the first report on the stabilizing role of bifurcating fluid flow on endothelial sprouting. These results also demonstrate the importance of local flow dynamics due to branched vessel geometry in determining the location of sprouting angiogenesis.
CALCULATING WELFARE COSTS OF INFLATION IN A SEARCH MODEL WITH PREFERENCE HETEROGENEITY: A CALIBRATION EXERCISE

Using US cross-sectional data, this paper calculates the welfare cost of a 10 percent inflation for different individuals and finds that the difference in cost between the poorest 20 percent, measured by their net worth, and the richest 20 percent is in the order of 102 percent. That is, a poor person is on average willing to forgive 102 percent more of their total consumption in order to have inflation reduced from 10 percent to 0. In absolute terms this represents a cost of 0.461 percent of consumption for the poorest and 0.228 percent for the richest. I accomplish this by introducing preference heterogeneity in a monetary search model first developed by Lagos and Wright, and calibrate the model to match each agent's type of cash holdings, approximated by their holdings in transactional accounts that bear almost no interest, as a fraction of their net worth using data from the Survey of Consumer Finances. I also show that this welfare difference increases to 130 percent (2.28 percent for the poorest 20 percent and 0.992 percent for the richest 20 percent) whenever frictions in the use of money are imposed (holdup problem). This distributional effect is further augmented if more frictions in the terms of trade are present. The ability to explicitly model these frictions is the advantage of using this model. Hence, inflation in this framework, as other studies have shown, acts as a regressive consumption tax; and this regressiveness is augmented with the holdup problem.
A collider observable QCD axion

We present a model where the QCD axion is at the TeV scale and visible at a collider via its decays. Conformal dynamics and strong CP considerations account for the axion coupling strongly enough to the standard model to be produced as well as the coincidence between the weak scale and the axion mass. The model predicts additional pseudoscalar color octets whose properties are completely determined by the axion properties rendering the theory testable.
Inexact Successive quadratic approximation for regularized optimization

Successive quadratic approximations, or second-order proximal methods, are useful for minimizing functions that are a sum of a smooth part and a convex, possibly nonsmooth part that promotes regularization. Most analyses of iteration complexity focus on the special case of proximal gradient method, or accelerated variants thereof. There have been only a few studies of methods that use a second-order approximation to the smooth part, due in part to the difficulty of obtaining closed-form solutions to the subproblems at each iteration. In fact, iterative algorithms may need to be used to find inexact solutions to these subproblems. In this work, we present global analysis of the iteration complexity of inexact successive quadratic approximation methods, showing that an inexact solution of the subproblem that is within a fixed multiplicative precision of optimality suffices to guarantee the same order of convergence rate as the exact version, with complexity related in an intuitive way to the measure of inexactness. Our result allows flexible choices of the second-order term, including Newton and quasi-Newton choices, and does not necessarily require increasing precision of the subproblem solution on later iterations. For problems exhibiting a property related to strong convexity, the algorithms converge at global linear rates. For general convex problems, the convergence rate is linear in early stages, while the overall rate is O(1 / k). For nonconvex problems, a first-order optimality criterion converges to zero at a rate of $$O(1/\sqrt{k})$$ .
OBSTRUCTIONS TO THE EXISTENCE AND SQUEEZING OF LAGRANGIAN COBORDISMS

Capacities that provide both qualitative and quantitative obstructions to the existence of a Lagrangian cobordism between two (n - 1)-dimensional submanifolds in parallel hyperplanes of ℝ2n are defined using the theory of generating families. Qualitatively, these capacities show that, for example, in ℝ4 there is no Lagrangian cobordism between two ∞-shaped curves with a negative crossing when the lower end is "smaller". Quantitatively, when the boundary of a Lagrangian ball lies in a hyperplane of ℝ2n, the capacity of the boundary gives a restriction on the size of a rectangular cylinder into which the Lagrangian ball can be squeezed.
Fairness in learning: classic and contextual bandits

We introduce the study of fairness in multi-armed bandit problems. Our fairness definition demands that, given a pool of applicants, a worse applicant is never favored over a better one, despite a learning algorithm's uncertainty over the true payoffs. In the classic stochastic bandits problem we provide a provably fair algorithm based on "chained" confidence intervals, and prove a cumulative regret bound with a cubic dependence on the number of arms. We further show that any fair algorithm must have such a dependence, providing a strong separation between fair and unfair learning that extends to the general contextual case. In the general contextual case, we prove a tight connection between fairness and the KWIK (Knows What It Knows) learning model: a KWIK algorithm for a class of functions can be transformed into a provably fair contextual bandit algorithm and vice versa. This tight connection allows us to provide a provably fair algorithm for the linear contextual bandit problem with a polynomial dependence on the dimension, and to show (for a different class of functions) a worst-case exponential gap in regret between fair and non-fair learning algorithms.
On the Small Ball Inequality in all dimensions

Abstract Let h R denote an L ∞ normalized Haar function adapted to a dyadic rectangle R ⊂ [ 0 , 1 ] d . We show that for choices of coefficients α ( R ) , we have the following lower bound on the L ∞ norms of the sums of such functions, where the sum is over rectangles of a fixed volume: n d − 1 2 − η ‖ ∑ | R | = 2 − n α ( R ) h R ( x ) ‖ L ∞ ( [ 0 , 1 ] d ) ≳ 2 − n ∑ | R | = 2 − n | α ( R ) | , for some 0 η 1 2 . The point of interest is the dependence upon the logarithm of the volume of the rectangles. With n ( d − 1 ) / 2 on the left above, the inequality is trivial, while it is conjectured that the inequality holds with n ( d − 2 ) / 2 . This is known in the case of d = 2 [Michel Talagrand, The small ball problem for the Brownian sheet, Ann. Probab. 22 (3) (1994) 1331–1354, MR 95k:60049], and a recent paper of two of the authors [Dmitriy Bilyk, Michael T. Lacey, On the Small Ball Inequality in three dimensions, Duke Math. J., (2006), in press, arXiv: math.CA/0609815 ] proves a partial result towards the conjecture in three dimensions. In this paper, we show that the argument of [Dmitriy Bilyk, Michael T. Lacey, On the Small Ball Inequality in three dimensions, Duke Math. J., (2006), in press, arXiv: math.CA/0609815 ] can be extended to arbitrary dimension. We also prove related results in the subjects of the irregularity of distribution, and approximation theory. The authors are unaware of any prior results on these questions in any dimension d ⩾ 4 .
Deep Information Propagation

We study the behavior of untrained neural networks whose weights and biases are randomly distributed using mean field theory. We show the existence of depth scales that naturally limit the maximum depth of signal propagation through these random networks. Our main practical result is to show that random networks may be trained precisely when information can travel through them. Thus, the depth scales that we identify provide bounds on how deep a network may be trained for a specific choice of hyperparameters. As a corollary to this, we argue that in networks at the edge of chaos, one of these depth scales diverges. Thus arbitrarily deep networks may be trained only sufficiently close to criticality. We show that the presence of dropout destroys the order-to-chaos critical point and therefore strongly limits the maximum trainable depth for random networks. Finally, we develop a mean field theory for backpropagation and we show that the ordered and chaotic phases correspond to regions of vanishing and exploding gradient respectively.
CANTOR POLYNOMIALS FOR SEMIGROUP SECTORS

A packing function on a set Ω in Rn is a one-to-one correspondence between the set of lattice points in Ω and the set N0 of non-negative integers. It is proved that if r and s are relatively prime positive integers such that r divides s - 1, then there exist two distinct quadratic packing polynomials on the sector {(x, y) ∈ R2 : 0 ≤ y ≤ rx/s}. For the rational numbers 1/s, these are the unique quadratic packing polynomials. Moreover, quadratic quasi-polynomial packing functions are constructed for all rational sectors.
On Data-Dependent Random Features for Improved Generalization in Supervised Learning

The randomized-feature approach has been successfully employed in large-scale kernel approximation and supervised learning. The distribution from which the random features are drawn impacts the number of features required to efficiently perform a learning task. Recently, it has been shown that employing data-dependent randomization improves the performance in terms of the required number of random features. In this paper, we are concerned with the randomized-feature approach in supervised learning for good generalizability. We propose the Energy-based Exploration of Random Features (EERF) algorithm based on a data-dependent score function that explores the set of possible features and exploits the promising regions. We prove that the proposed score function with high probability recovers the spectrum of the best fit within the model class. Our empirical results on several benchmark datasets further verify that our method requires smaller number of random features to achieve a certain generalization error compared to the state-of-the-art while introducing negligible pre-processing overhead. EERF can be implemented in a few lines of code and requires no additional tuning parameters.
Personalized Automatic Estimation of Self-Reported Pain Intensity from Facial Expressions

Pain is a personal, subjective experience that is commonly evaluated through visual analog scales (VAS). While this is often convenient and useful, automatic pain detection systems can reduce pain score acquisition efforts in large-scale studies by estimating it directly from the partictipants' facial expressions. In this paper, we propose a novel two-stage learning approach for VAS estimation: first, our algorithm employs Recurrent Neural Networks (RNNs) to automatically estimate Prkachin and Solomon Pain Intensity (PSPI) levels from face images. The estimated scores are then fed into the personalized Hidden Conditional Random Fields (HCRFs), used to estimate the VAS, provided by each person. Personalization of the model is performed using a newly introduced facial expressiveness score, unique for each person. To the best of our knowledge, this is the first approach to automatically estimate VAS from face images. We show the benefits of the proposed personalized over traditional non-personalized approach on a benchmark dataset for pain analysis from face images.
Numerical proof of stability of viscous shock profiles

We carry out the first rigorous numerical proof based on Evans function computations of stability of viscous shock profiles, for the system of isentropic gas dynamics with monatomic equation of state. We treat a selection of shock strengths ranging from the lower stability boundary of Mach number ≈1.86, below which profiles are known by energy estimates to be stable, to the upper stability boundary of ≈1669, above which profiles are expected to be provable by rigorous asymptotic analysis to be stable. These results open the possibilities of: (i) automatic rigorous verification of stability or instability of individual shocks of general systems, and (ii) rigorous proof of stability of all shocks of particular systems.
Fairness Under Composition

Algorithmic fairness, and in particular the fairness of scoring and classification algorithms, has become a topic of increasing social concern and has recently witnessed an explosion of research in theoretical computer science, machine learning, statistics, the social sciences, and law. Much of the literature considers the case of a single classifier (or scoring function) used once, in isolation. In this work, we initiate the study of the fairness properties of systems composed of algorithms that are fair in isolation; that is, we study fairness under composition. We identify pitfalls of naive composition and give general constructions for fair composition, demonstrating both that classifiers that are fair in isolation do not necessarily compose into fair systems and also that seemingly unfair components may be carefully combined to construct fair systems. We focus primarily on the individual fairness setting proposed in [Dwork, Hardt, Pitassi, Reingold, Zemel, 2011], but also extend our results to a large class of group fairness definitions popular in the recent literature, exhibiting several cases in which group fairness definitions give misleading signals under composition.
Parisi formula for the ground state energy in the mixed $p$-spin model

We show that the thermodynamic limit of the ground state energy in the mixed pp-spin model can be identified as a variational problem. This gives a natural generalization of the Parisi formula at zero temperature.
Juggling card sequences

Juggling patterns can be described by a sequence of cards which keep track of the relative order of the balls at each step. This interpretation has many algebraic and combinatorial properties, with connections to Stirling numbers, Dyck paths, Narayana numbers, boson normal ordering, arc-labeled digraphs, and more. Some of these connections are investigated with a particular focus on enumerating juggling patterns satisfying certain ordering constraints, including where the number of crossings is fixed.
On the Prior Sensitivity of Thompson Sampling

The empirically successful Thompson Sampling algorithm for stochastic bandits has drawn much interest in understanding its theoretical properties. One important benefit of the algorithm is that it allows domain knowledge to be conveniently encoded as a prior distribution to balance exploration and exploitation more effectively. While it is generally believed that the algorithm’s regret is low (high) when the prior is good (bad), little is known about the exact dependence. This paper is a first step towards answering this important question: focusing on a special yet representative case, we fully characterize the algorithm’s worst-case dependence of regret on the choice of prior. As a corollary, these results also provide useful insights into the general sensitivity of the algorithm to the choice of priors, when no structural assumptions are made. In particular, with p being the prior probability mass of the true reward-generating model, we prove \(O(\sqrt{T/p})\) and \(O(\sqrt{(1-p)T})\) regret upper bounds for the poor- and good-prior cases, respectively, as well as matching lower bounds. Our proofs rely on a fundamental property of Thompson Sampling and make heavy use of martingale theory, both of which appear novel in the Thompson-Sampling literature and may be useful for studying other behavior of the algorithm.
Calabi energies of extremal toric surfaces

We derive a formula for the L^2 norm of the scalar curvature of any extremal Kaehler metric on a compact toric manifold, stated purely in terms of the geometry of the corresponding moment polytope. The main interest of this formula pertains to the case of complex dimension 2, where it plays a key role in construction of Bach-flat metrics on appropriate 4-manifolds.
Efficient Globally Convergent Stochastic Optimization for Canonical Correlation Analysis

We study the stochastic optimization of canonical correlation analysis (CCA), whose objective is nonconvex and does not decouple over training samples. Although several stochastic gradient based optimization algorithms have been recently proposed to solve this problem, no global convergence guarantee was provided by any of them. Inspired by the alternating least squares/power iterations formulation of CCA, and the shift-and-invert preconditioning method for PCA, we propose two globally convergent meta-algorithms for CCA, both of which transform the original problem into sequences of least squares problems that need only be solved approximately. We instantiate the meta-algorithms with state-of-the-art SGD methods and obtain time complexities that significantly improve upon that of previous work. Experimental results demonstrate their superior performance.
Cascade Adversarial Machine Learning Regularized with a Unified Embedding

Injecting adversarial examples during training, known as adversarial training, can improve robustness against one-step attacks, but not for unknown iterative attacks. To address this challenge, we first show iteratively generated adversarial images easily transfer between networks trained with the same strategy. Inspired by this observation, we propose cascade adversarial training, which transfers the knowledge of the end results of adversarial training. We train a network from scratch by injecting iteratively generated adversarial images crafted from already defended networks in addition to one-step adversarial images from the network being trained. We also propose to utilize embedding space for both classification and low-level (pixel-level) similarity learning to ignore unknown pixel level perturbation. During training, we inject adversarial images without replacing their corresponding clean images and penalize the distance between the two embeddings (clean and adversarial). Experimental results show that cascade adversarial training together with our proposed low-level similarity learning efficiently enhances the robustness against iterative attacks, but at the expense of decreased robustness against one-step attacks. We show that combining those two techniques can also improve robustness under the worst case black box attack scenario.
Fast and Efficient Distributed Computation of Hamiltonian Cycles in Random Graphs

We present fast and efficient randomized distributed algorithms to find Hamiltonian cycles in random graphs. In particular, we present a randomized distributed algorithm for the G(n, p) random graph model, with number of nodes n and p = c ln n/n^δ (for any constant 0 0), that finds a Hamiltonian cycle with high probability in O(n^δ) rounds. Our algorithm works in the (synchronous) CONGEST model (i.e., only O(log n)-sized messages are communicated per edge per round) and its computational cost per node is sublinear (in n) per round and is fully-distributed (each node uses only o(n) memory and all nodes' computations are essentially balanced). Our algorithm improves over the previous best known result in terms of both the running time as well as the edge sparsity of the graphs where it can succeed; in particular, the denser the random graph, the smaller is the running time.
Algorithms and error bounds for noisy phase retrieval with low-redundancy frames

Abstract The main objective of this paper is to find algorithms accompanied by explicit error bounds for phase retrieval from noisy magnitudes of frame coefficients when the underlying frame has a low redundancy. We achieve these goals with frames consisting of N = 6 d − 3 vectors spanning a d-dimensional complex Hilbert space. The two algorithms we use, phase propagation or the kernel method, are polynomial time in the dimension d. To ensure a successful approximate recovery, we assume that the noise is sufficiently small compared to the squared norm of the vector to be recovered. In this regime, we derive an explicit error bound that is inverse proportional to the signal-to-noise ratio, with a constant of proportionality that depends only on the dimension d. Properties of the reproducing kernel space of complex polynomials and of trigonometric polynomials are central in our error estimates.