cssi/SciSciGPT-SciSciNet huggingface dataset:
Spatiotemporal prediction of wildfire size extremes with Bayesian finite sample maxima

Wildfires are becoming more frequent in parts of the globe, but predicting where and when wildfires occur remains difficult. To predict wildfire extremes across the contiguous United States, we integrate a 30-yr wildfire record with meteorological and housing data in spatiotemporal Bayesian statistical models with spatially varying nonlinear effects. We compared different distributions for the number and sizes of large fires to generate a posterior predictive distribution based on finite sample maxima for extreme events (the largest fires over bounded spatiotemporal domains). A zero-inflated negative binomial model for fire counts and a lognormal model for burned areas provided the best performance. This model attains 99% interval coverage for the number of fires and 93% coverage for fire sizes over a six year withheld data set. Dryness and air temperature strongly predict extreme wildfire probabilities. Housing density has a hump-shaped relationship with fire occurrence, with more fires occurring at intermediate housing densities. Statistically, these drivers affect the chance of an extreme wildfire in two ways: by altering fire size distributions, and by altering fire frequency, which influences sampling from the tails of fire size distributions. We conclude that recent extremes should not be surprising, and that the contiguous United States may be on the verge of even larger wildfire extremes.
CD23 expression in mantle cell lymphoma is associated with CD200 expression, leukemic non-nodal form, and a better prognosis

Summary Mantle cell lymphoma (MCL) is usually CD23 negative, a feature helpful in distinguishing MCL from chronic lymphocytic leukemia/small lymphocytic lymphoma. However, a subset of MCL cases can be CD23+. Limited data are available regarding the clinicopathological features and prognosis of patients with CD23+ MCL. In this study, we reviewed 798 cases of MCL and identified 103 (13%) that were CD23+ by flow cytometry, all of which were positive for cyclin D1 and/or associated with CCND1/IGH. In all cases of CD23+ MCL, CD23 expression was dim partial or dim, unlike moderate to bright CD23 expression observed in chronic lymphocytic leukemia/small lymphocytic lymphoma. The clinicopathological features and outcome of patients with CD23+ MCL were compared with 240 patients with typical MCL negative for CD23. Patients with CD23+ MCL more often had an elevated leukocyte count (33% versus 18%, P = .009), bone marrow involvement (89% versus 78%, P = .02), stage 4 disease (87% versus 77%, P = .03), and a leukemic presentation (42% versus 11%, P = .0001). CD23+ MCL was also more often positive for CD200 (17% versus. 4.6%, P = .0005) and less commonly positive for SOX11 (55% versus. 74%, P = .027). All other clinicopathological features were similar. With similar treatment regimens and observation times, patients with CD23+ MCL had a significant better overall survival (P = .02) and progression-free survival (P = .029). In conclusion, CD23 expression was observed in 13% of MCL cases and is associated with a better prognosis in patients with MCL. CD23 is associated with leukocytosis, a leukemic presentation, bone marrow involvement, CD200 expression, and a lower frequency of SOX11 positivity.
Stand-in Labor and the Rising Economy of Self

Ghostwriters represent a form of labor aimed at producing someone else’s self, or what we label “stand-in labor.” This growing workforce sits at the intersection of critical developments in today’s neoliberal economy: the rise in selfbranding, the growth in outsourcing of the self, and mounting income inequality. This article explores the experience of stand-in workers and its implication on the economy of self. Relying on 72 interviews with ghostwriters and publishing industry insiders, we show that ghostwriters face recognition estrangement because they are often asked to stay out of public view for the crafted selves to prove “authentic.” As creative workers with a high degree of investment in their work, ghostwriters are quite sensitive to this form of estrangement. They manage this tension in a unique way: they claim a professional need to disappear in order to properly put forth a subject’s “true” voice, yet emphasize their active contribution to the crafting of a subject’s public self that differs from the subject’s “true” self. In doing so, ghostwriters alter the subjects they impersonate by creating a distance between the subjects’ crafted and “actual” selves. Our study therefore uncovers a paradoxical dynamic — namely, taking professional pride in disappearing, yet reappearing in the act of altering others’ selves — that we posit might prove inherent to the performance of stand-in labor. More broadly, we suggest that many stand-in workers engaged in this growing economy of self might alter the people they impersonate, thus leading to a situation where calls for authenticity breed adulteration.
Organic- and molecule-based magnets

Magnets have been known for millennia and are strongly associated with metals (e.g. Fe, Co, Ni, Gd), intermetallics (e.g. Co 17 Sm 2 , Nd 2 Fe 14 B), or their oxides (e.g. CrO 2 , Fe 3 O 4 ). The development of new magnetic materials has led to ubiquitous uses for electricity generation, memory storage media, and devices such as electric motors, microphones, telephones and computers. These magnets are fabricated via energy demanding metallurgical methods and are frequently brittle, chemically reactive, and possess elements in limited supply. The end of the last millennium has seen a surge in using organic, molecular, and polymeric materials as substitutes for metal and ceramic materials in many applications. Also, in the past few decades organic and molecule-based materials have been shown to magnetically order with examples having ordering temperatures exceeding room temperature, higher-than-iron saturation magnetizations, large coercive fields, etc. An overview of organic-based, and more generally molecule-based magnetic materials that exhibit unusual magnetic properties ranging from ferromagnets to synthetic antiferromagnets with emphasis on magnetic ordering using examples possessing organic nitriles ( CN) or inorganic cyanide (CN − ) is described.
Heterochronic developmental shifts underlie floral diversity within Jaltomata (Solanaceae)

Heterochronic shifts during mid- to late stages of organismal development have been proposed as key mechanisms generating phenotypic diversity. To determine whether late heterochronic shifts underlie derived floral morphologies within Jaltomata (Solanaceae)—a genus whose species have extensive and recently evolved floral diversity—we compared floral development of four diverse species (including an ambiguously ancestral or secondarily derived rotate, two putatively independently evolved campanulate, and a tubular morph) to the ancestral rotate floral form, as well as to an outgroup that shares this ancestral floral morphology. We determined that early floral development ( 1 mm diameter) due to differential growth acceleration of corolla traits. Floral ontogeny among similar mature rotate forms remains comparable until late stages, while somewhat different patterns of organ growth are found between species with similar campanulate forms. Our data suggest shared floral patterning during early-stage development, but that different heterochronic shifts during mid- and late-stage development contribute to divergent floral traits. Heterochrony thus appears to have been important in the rapid and repeated diversification of Jaltomata flowers.
One-pot synthesis of 3-triazolyl-2-iminochromenes via a catalytic three component cascade reaction.

A variety of 3-triazolyl-2-iminochromenes were synthesized in a one-pot, catalytic, three component condensation. In this event, a Cu(I)-catalyzed cycloaddition between 2-azidoacetonitrile and an a...
Synthesis of 6,8-Diarylimino-7H-Pyrano[3,2-c:5,6-c’]Dicoumarins; Chemoselective Hydrolysis of the Ether- and Imino-Functions:

POCl3-induced dehydration of 3,3'-methylenedi(2-arylamino-4H-chromen-4-ones) gives 6,8-diarylimino-7H-pyrano[3,2-c:5,6-c’]dicoumarins, which undergo chemoselective hydrolysis of the imino function ...
Performance Advantages of Deep Neural Networks for Angle of Arrival Estimation

The problem of estimating the number of sources and their angles of arrival from a single antenna array observation has been an active area of research in the signal processing community for the last few decades. When the number of sources is large, the maximum likelihood estimator is intractable due to its very high complexity, and therefore alternative signal processing methods have been developed with some performance loss. In this paper, we apply a deep neural network (DNN) approach to the problem and analyze its advantages with respect to signal processing algorithms. We show that an appropriate designed network can attain the maximum likelihood performance with feasible complexity and outperform other feasible signal processing estimation methods over various signal to noise ratios and array response inaccuracies.
Total synthesis of aspeverin via an iodine(III)-mediated oxidative cyclization.

The first total synthesis of aspeverin, a prenylated indole alkaloid isolated from Aspergillus versicolor in 2013, is described. Key steps utilized to assemble the core structure of the target include a highly diastereoselective Diels–Alder reaction, a Curtius rearrangement, and a unique strategy for installation of the geminal dimethyl group. A novel iodine(III)-initiated cyclization was then used to install the bicyclic urethane linkage distinctive to the natural product.
The MicroRNA, miR-18a, Regulates NeuroD and Photoreceptor Differentiation in the Retina of Zebrafish

During embryonic retinal development, six types of retinal neurons are generated from multipotent progenitors in a strict spatiotemporal pattern. This pattern requires cell cycle exit (i.e. neurogenesis) and differentiation to be precisely regulated in a lineage-specific manner. In zebrafish, the bHLH transcription factor NeuroD governs photoreceptor genesis through Notch signaling but also governs photoreceptor differentiation though distinct mechanisms that are currently unknown. Also unknown are the mechanisms that regulate NeuroD and the spatiotemporal pattern of photoreceptor development. Members of the miR-17-92 microRNA cluster regulate CNS neurogenesis, and a member of this cluster, miR-18a, is predicted to target neuroD mRNA. The purpose of this study was to determine if, in the developing zebrafish retina, miR-18a regulates NeuroD and if it plays a role in photoreceptor development. Quantitative RT-PCR showed that, of the three miR-18 family members (miR-18a, b, and c), miR-18a expression most closely parallels neuroD expression. Morpholino oligonucleotides and CRISPR/Cas9 gene editing were used for miR-18a loss-of-function (LOF) and both resulted in larvae with more mature photoreceptors at 70 hpf without affecting cell proliferation. Western blot showed that miR-18a LOF increases NeuroD protein levels and in vitro dual luciferase assay showed that miR-18a directly interacts with the 3' UTR of neuroD. Finally, tgif1 mutants have increased miR-18a expression, less NeuroD protein and fewer mature photoreceptors, and the photoreceptor deficiency is rescued by miR-18a knockdown. Together, these results show that, independent of neurogenesis, miR-18a regulates the timing of photoreceptor differentiation and indicate that this occurs through post-transcriptional regulation of NeuroD.
Evidence for an Intense Neutrino Flux during r-Process Nucleosynthesis?

We investigate the possibility that neutrino capture on heavy nuclei competes with beta decay in the environment where the r-process elements are synthesized. We find that such neutrino capture is not excluded by existing abundance determinations. We show that inclusion of significant neutrino capture on the neutron number N = 82 waiting-point nuclei can allow the inferred abundances of these species to provide a good fit to steady weak (beta decay plus neutrino capture) flow equilibrium. In fact, for particular choices of neutrino flux conditions, this fit is an improvement over the case in which nuclei change their charge by beta decay alone. However, this improved fit can be realized only if neutrino capture plays a negligible role in nuclear decay back toward stability. We discuss the implications of these considerations for currently proposed sites and models of r-process nucleosynthesis.
Induction of AMPK activation by N,N'-diarylurea FND-4b decreases growth and increases apoptosis in triple negative and estrogen-receptor positive breast cancers.

Purpose Triple negative breast cancer (TNBC) is the most lethal and aggressive subtype of breast cancer. AMP-activated protein kinase (AMPK) is a major energy regulator that suppresses tumor growth, and 1-(3-chloro-4-((trifluoromethyl)thio)phenyl)-3-(4-(trifluoromethoxy)phenyl)urea (FND-4b) is a novel AMPK activator that inhibits growth and induces apoptosis in colon cancer. The purpose of this project was to test the effects of FND-4b on AMPK activation, proliferation, and apoptosis in breast cancer with a particular emphasis on TNBC. Materials and methods (i) Estrogen-receptor positive breast cancer (ER+BC; MCF-7, and T-47D), TNBC (MDA-MB-231 and HCC-1806), and breast cancer stem cells were treated with FND-4b for 24h. Immunoblot analysis assessed AMPK, acetyl-CoA carboxylase (ACC), ribosomal protein S6, cyclin D1, and cleaved PARP. (ii) Sulforhodamine B growth assays were performed after treating ER+BC and TNBC cells with FND-4b for 72h. Proliferation was also assessed by counting cells after 72h of FND-4b treatment. (iii) Cell death ELISA assays were performed after treating ER+BC and TNBC cells with FND-4b for 72h. Results (i) FND-4b increased AMPK activation with concomitant decreases in ACC activity, phosphorylated S6, and cyclin D1 in all subtypes. (ii) FND-4b decreased proliferation in all cells, while dose-dependent growth decreases were found in ER+BC and TNBC. (iii) Increases in apoptosis were observed in ER+BC and the MDA-MB-231 cell line with FND-4b treatment. Conclusions Our findings indicate that FND-4b decreases proliferation for a variety of breast cancers by activating AMPK and has notable effects on TNBC. The growth reductions were mediated through decreases in fatty acid synthesis (ACC), mTOR signaling (S6), and cell cycle flux (cyclin D1). ER+BC cells were more susceptible to FND-4b-induced apoptosis, but MDA-MB-231 cells still underwent apoptosis with higher dose treatment. Further development of FND compounds could result in a novel therapeutic for TNBC.
Novel syntheses of β-halo-α,β-unsaturated ketones

Abstract Novel methods have been developed for the transformation of unsymmetrical 1,3-diketones to β-halo-α,β-unsaturated ketones. These new methods complement known syntheses of this functional group, allowing efficient access to a previously unattainable regioisomer.
Iodine(III)-mediated bicyclic diazenium salt formation

Abstract The hypervalent iodine(III) reagent PhI(OTf) 2 has been shown to be an effective oxidant for the conversion of linear aryl-hydrazones bearing a pendant alkene into bicyclic diazenium salts. This oxidative cyclization presumably occurs by the iodine(III) mediated formation of a 1-aza-2-azoniaallene salt intermediate that undergoes a subsequent intramolecular 1,3-dipolar cycloaddition with the pendant alkene.
Elemental Fluorine to 8-Fluoropurines in One Step

An efficient regiocontrolled approach to the synthesis of 8-fluoropurines by direct fluorination of purines with dilute elemental fluorine is described. The one-step procedure produced regiospecific substitution of the C(8)-hydrogen of purine derivatives in isolated yields close to 30% with protected purines in CHCl3. Fluorination yields with unprotected purines in EtOH were reduced to less than 10%. The electrophilic fluorination procedure has a broad scope of applicability and permits a ready and easy access to 8-fluoropurine derivatives, for the first time, for evaluation of their biochemical and pharmacological properties.
Reactions of Saturated and Unsaturated Tertiary Alkyl Halides and Saturated Secondary Alkyl Iodides with Lithium Aluminum Deuteride. Convincing Evidence for a Single-Electron-Transfer Pathway

Reactions of saturated secondary and tertiary alkyl halides with LiAlH4 (LAH) and LiAlD4 (LAD) have been carried out, and convincing evidence for a single-electron-transfer (SET) pathway has been obtained. Reactions involving saturated alkyl halides with LAD provide a model system in which a halogen-atom radical chain process is not possible, and therefore, the observation of large quantities (in some cases >90%) of protium in the reduction product provides strong evidence for a radical intermediate and a SET pathway. Specifically, the reaction of 2-iodooctane (10) with LAD produced octane with a deuterium content as low as 21%. Also, the reaction of the tertiary halide 2-iodo-2-methylheptane (15) with LAD produced 2-methylheptane (16) with a deuterium content as low as 8%. The effect of stoichiometry, halogen type, and reaction vessel surface on these reactions was studied. Reaction of the unsaturated tertiary halide 6-iodo-6-methyl-1-heptene (25) with LAD was also studied and was found to proceed predom...
Co(III)-alkylperoxo complexes: syntheses, structure-reactivity correlations, and use in the oxidation of hydrocarbons.

Crystalline [LCoIII−OOR] complexes with strong-field ligands, L, afford ROO• and RO• radicals upon mild heating in solution. This fact allows oxidation of hydrocarbons by these complexes under mild conditions. The extent of hydrocarbon oxidation by discrete [LCoIII−OOR] complexes depends on the nature of L, the solvent, the temperature, and the presence of other M(II) ions. Such systems are catalytic in the presence of excess ROOH.
Primary alanes and alanates: useful synthetic reagents in aluminum chemistry

Abstract Primary alanes [RAlH2]2 can be stabilized kinetically by employment of very bulky alkyl or aryl substituents. They are easily prepared by reacting the appropriate lithium trihydroalanate precursor with organic halides, anhydrous hydrogen halides or halogens. Reactions of these aluminum hydrides with a wide variety of substrates ranging from protic reagents such as water, alcohols, amines, phosphines or thiols over ketones, nitriles or isonitriles to silylated species such as siloxanes or silyl halides are presented. Primary alanes were shown to be unique starting materials for a number of interesting compounds that were otherwise not accessible, or only available in low yields. In addition, postulated intermediates of aluminum hydride reductions of organic substrates such as ketones or nitriles can be isolated when using bulky primary alanes.
Incremental Conversion of Outer-Membrane Permeabilizers into Potent Antibiotics for Gram-Negative Bacteria

Cholic acid derivatives appended with amine groups have been prepared for use as permeabilizers of the outer membranes of Gram-negative bacteria. These compounds interact synergistically with antibiotics such as erythromycin and novobiocin to inhibit growth of Gram-negative bacteria. When a hydrophobic chain is included on the permeabilizers, they can be converted into potent antibiotics. The role of the hydrophobic chain is to facilitate self-promoted transport of the cholic acid derivatives across the outer membrane of Gram-negative bacteria. These compounds share activities found with polymyxin B and derivatives.
Boymaw, Overexpressed in Brains With Major Psychiatric Disorders, May Encode a Small Protein to Inhibit Mitochondrial Function and Protein Translation

The t(1,11) chromosome translocation co-segregates with major psychiatric disorders in a large Scottish family. The translocation disrupts the DISC1and Boymaw (DISC1FP1) genes on chromosomes 1 and 11, respectively. After translocation, two fusion genes are generated. Our recent studies found that the DISC1-Boymaw fusion protein is localized in mitochondria and inhibits oxidoreductase activity, rRNA expression, and protein translation. Mice carrying the DISC1-Boymaw fusion genes display intermediate behavioral phenotypes related to major psychiatric disorders. Here, we report that the Boymaw gene may encode a small protein predominantly localized in mitochondria. The Boymaw protein inhibits oxidoreductase activity, rRNA expression, and protein translation in the same way as the DISC1-Boymaw fusion protein. Interestingly, Boymaw expression is up-regulated by different stressors at RNA and/or protein translational levels. In addition, we found that Boymaw RNA expression is significantly increased in the postmortem brains of patients with major psychiatric disorders. Our studies therefore suggest that the Boymaw gene could potentially be a susceptibility gene for major psychiatric disorders in both the Scottish t(1,11) family and the general population of patients.
Proteomic Analysis of Urine from California Sea Lions ( Zalophus californianus): A Resource for Urinary Biomarker Discovery.

Urinary markers for the assessment of kidney diseases in wild animals are limited, in part, due to the lack of urinary proteome data, especially for marine mammals. One of the most prevalent kidney diseases in marine mammals is caused by Leptospira interrogans, which is the second most common etiology linked to stranding of California sea lions (Zalophus californianus). Urine proteins from 11 sea lions with leptospirosis kidney disease and eight sea lions without leptospirosis or kidney disease were analyzed using shotgun proteomics. In total, 2694 protein groups were identified, and 316 were differentially abundant between groups. Major urine proteins in sea lions were similar to major urine proteins in dogs and humans except for the preponderance of resistin, lysozyme C, and PDZ domain containing 1, which appear to be over-represented. Previously reported urine protein markers of kidney injury in humans and animals were also identified. Notably, neutrophil gelatinase-associated lipocalin, osteopontin, a...
A facile chemoselective deprotection of the p-methoxybenzyl group

Abstract The p-methoxybenzyl (PMB) group can be chemoselectively cleaved at low temperature in the presence of SnCl4 and thiophenol. This method is especially useful in the cases where oxidative reagents such as DDQ and CAN need to be avoided.
Submodular Observation Selection and Information Gathering for Quadratic Models

We study the problem of selecting most informative subset of a large observation set to enable accurate estimation of unknown parameters. This problem arises in a variety of settings in machine learning and signal processing including feature selection, phase retrieval, and target localization. Since for quadratic measurement models the moment matrix of the optimal estimator is generally unknown, majority of prior work resorts to approximation techniques such as linearization of the observation model to optimize the alphabetical optimality criteria of an approximate moment matrix. Conversely, by exploiting a connection to the classical Van Trees' inequality, we derive new alphabetical optimality criteria without distorting the relational structure of the observation model. We further show that under certain conditions on parameters of the problem these optimality criteria are monotone and (weak) submodular set functions. These results enable us to develop an efficient greedy observation selection algorithm uniquely tailored for quadratic models, and provide theoretical bounds on its achievable utility.
Synthesis of 3-Indolyl-2,5-dihydroxybenzoquinones

3-Indolylquinones can be efficiently prepared by the acid-catalyzed condensation of indoles with 2,5-dichlorobenzoquinone, followed by DDQ oxidation. The resulting dichloroquinones are hydrolyzed to the 3-indolyldihydroxybenzoquinones. The 3-indolylquinone substructure is of interest because of its presence in natural products that modulate biological processes through protein−protein interactions, including the asterriquinones.
Position effects influencing intrachromosomal repair of a double-strand break in budding yeast

Repair of a double-strand break (DSB) by an ectopic homologous donor sequence is subject to the three-dimensional arrangement of chromosomes in the nucleus of haploid budding yeast. The data for interchromosomal recombination suggest that searching for homology is accomplished by a random collision process, strongly influenced by the contact probability of the donor and recipient sequences. Here we explore how recombination occurs on the same chromosome and whether there are additional constraints imposed on repair. Specifically, we examined how intrachromosomal repair is affected by the location of the donor sequence along the 813-kb chromosome 2 (Chr2), with a site-specific DSB created on the right arm (position 625 kb). Repair correlates well with contact frequencies determined by chromosome conformation capture-based studies (r = 0.85). Moreover, there is a profound constraint imposed by the anchoring of the centromere (CEN2, position 238 kb) to the spindle pole body. Sequences at the same distance on either side of CEN2 are equivalently constrained in recombining with a DSB located more distally on one arm, suggesting that sequences on the opposite arm from the DSB are not otherwise constrained in their interaction with the DSB. The centromere constraint can be partially relieved by inducing transcription through the centromere to inactivate CEN2 tethering. In diploid cells, repair of a DSB via its allelic donor is strongly influenced by the presence and the position of an ectopic intrachromosomal donor.
Hydrothermal synthesis, structure, and magnetic properties of the mixed-valent Np(IV)/Np(V) Selenite Np(NpO2)2(SeO3)3.

The reaction of NpO{sub 2} with SeO{sub 2} in the presence of CsCl at 180 {sup o}C results in the formation of Np(NpO{sub 2}){sub 2}(SeO{sub 3}){sub 3} (1). The structure of 1 consists of three crystallographically unique Np centers with three different coordination environments in two different oxidation states. Np(1) is found in a neptunyl(V), ONpO{sup +}, unit that is further ligated in the equatorial plane by three chelating SeO{sub 3}{sup 2-} anions to create a hexagonal bipyramidal NpO{sub 8} unit. A second neptunyl(V) cation also occurs for Np(2); it is bound by four bridging selenite anions and by the oxo atom from the Np(1) neptunyl cation to form a pentagonal bipyramidal, NpO{sub 7}, unit. The third neptunium center, Np(3), which contains Np(IV), is found in a distorted NpO{sub 8} dodecahedron. Np(3) is bound by five bridging selenite anions and by three neptunyl units via cation-cation interactions. The NpO{sub 7} pentagonal bipyramids and NpO{sub 8} hexagonal bipyramids share both corners and edges. Both of these polyhedra share corners via cation-cation interactions with the NpO{sub 8} dodecahedra creating a three-dimensional structure with small channels that house the stereochemically active lone pair of electrons on the selenite anions. Magnetic susceptibility data followmore » Curie-Weiss behavior over the entire temperature range measured (5 {<=} T {<=} 320 K). The effective moment, {mu}{sub eff} = 2.28 {mu}{sub B}, which represents an average over the three crystallographically inequivalent Np atoms, is within the expected range of values. There is no evidence of long-range ordering of the Np moments at temperatures down to 5 K, consistent with the negligible Weiss constant determined from fitting the susceptibility data. Crystallographic data: 1, orthorhombic, space group Pbca, a = 10.6216(5), b = 11.9695(6), and c = 17.8084(8) {angstrom} and Z = 8 (T = 193 K).« less
SYNTHESIS OF 2,3-DIHYDROBENZOFURANS BY MN(OAC)3-BASED OXIDATIVE CYCLOADDITION OF 2-CYCLOHEXENONES WITH ALKENES. SYNTHESIS OF ()-CONOCARPAN

Oxidative cycloaddition of a 2-cyclohexenone or α-tetralone and an alkene with dried Mn(OAc)3 in benzene at 80−140 °C provides a general route to dihydrobenzofurans 15 and dihydronaphthofurans 17. Although the yields are modest, this one-pot reaction provides simple access to these compounds, which have previously been prepared by multistep routes. Oxidative cycloaddition of 2-cyclohexenones with β-methylstyrenes provides a new route to benzofuranoid neolignans, which was applied to the synthesis of conocarpan (22). The formation of 2-acetoxyhexanedioic acids 27 and 47 from acetoxylation of 2-cyclohexenones in HOAc, but not in benzene, opens up a new class of Mn(OAc)3 reactions and explains Watt and Demir's discovery that much higher yields of α‘-acetoxy enones are obtained in benzene than in HOAc.
Isocorannulenofuran: a versatile building block for the synthesis of large buckybowls.

Isocorannulenofuran, synthesized in two steps from accessible bromocorannulene, gives Diels−Alder adducts with benzynes which can be deoxygenated to produce large polycyclic aromatic hydrocarbons (PAHs) combining the bowl-shaped corannulene subunit with planar fragments.
The Effects of Traditional Cigarette and E-Cigarette Taxes on Adult Tobacco Product Use

We study the effects of traditional cigarette and e-cigarette taxes on use of these products among adults in the United States. Data are drawn from the Behavioral Risk Factor Surveillance System and National Health Interview Survey over the period 2011 to 2018. Using two-way fixed effects models, we find evidence that higher traditional cigarette tax rates reduce adult traditional cigarette use and increase adult e-cigarette use. Similarly, we find that higher e-cigarette tax rates increase traditional cigarette use and reduce e-cigarette use. Cross-tax effects imply that the products are economic substitutes. Our results suggest that a proposed national e-cigarette tax of $1.65 per milliliter of vaping liquid would raise the proportion of adults who smoke cigarettes daily by approximately one percentage point, translating to 2.5 million extra adult daily smokers compared to the counterfactual of not having the tax.
The CspC pseudoprotease regulates germination of Clostridioides difficile spores in response to multiple environmental signals.

The gastrointestinal pathogen, Clostridioides difficile, initiates infection when its metabolically dormant spore form germinates in the mammalian gut. While most spore-forming bacteria use transmembrane germinant receptors to sense nutrient germinants, C. difficile is thought to use the soluble pseudoprotease, CspC, to detect bile acid germinants. To gain insight into CspC’s unique mechanism of action, we solved its crystal structure. Guided by this structure, we identified CspC mutations that confer either hypo- or hyper-sensitivity to bile acid germinant. Surprisingly, hyper-sensitive CspC variants exhibited bile acid-independent germination as well as increased sensitivity to amino acid and/or calcium co-germinants. Since mutations in specific residues altered CspC’s responsiveness to these different signals, CspC plays a critical role in regulating C. difficile spore germination in response to multiple environmental signals. Taken together, these studies implicate CspC as being intimately involved in the detection of distinct classes of co-germinants in addition to bile acids and thus raises the possibility that CspC functions as a signaling node rather than a ligand-binding receptor.
On Quadratic Distinction of Automorphic Sheaves

We prove a geometric version of a classical result on the characterization of an irreducible cuspidal automorphic representation of GLn(AE ) being the base change of a stable cuspidal representation of the quasi-split unitary group associated to the quadratic extension E/F , via the nonvanishing of certain period integrals, called being distinguished. We show that certain cohomology of an automorphic sheaf of GLn,X′ is nonvanishing if and only if the corresponding local system E on X′ is conjugate selfdual with respect to an etale double cover X′/X of curves, which directly relates to the base change from the associated unitary group. In particular, the geometric setting makes sense over any base field.
Algorithms for Estimating Trends in Global Temperature Volatility

Trends in terrestrial temperature variability are perhaps more relevant for species viability than trends in mean temperature. In this paper, we develop methodology for estimating such trends using multi-resolution climate data from polar orbiting weather satellites. We derive two novel algorithms for computation that are tailored for dense, gridded observations over both space and time. We evaluate our methods with a simulation that mimics these data’s features and on a large, publicly available, global temperature dataset with the eventual goal of tracking trends in cloud reflectance temperature variability.
Anchoring ceria nanoparticles on reduced graphene oxide and their electronic transport properties

We report a simple scheme of anchoring crystalline ceria nanoparticles (CNPs) onto reduced graphene oxide (RGO) sheets. Two types of CNPs, consisting of predominantly either Ce3+ or Ce4+ valence states, were mixed with GO suspended in water, with simultaneous reduction using hydrazine to yield CNP/RGO composite. Structural and surface characterizations reveal a strong electrostatic interaction between the CNPs and the RGO. Electrical characterizations show that with increased oxygen vacancies from Ce4+ to Ce3+ states the predominantly ambipolar RGO transforms to n-type CNP/RGO composites due to the electrostatic interaction between the localized electrons in oxygen vacancy sites of CNPs and mobile holes in RGO.
Minimax Learning for Remote Prediction

The classical problem of supervised learning is to infer an accurate predictor of a target variable $Y$ from a measured variable $X$ by using a finite number of labeled training samples. Motivated by the increasingly distributed nature of data and decision making, in this paper we consider a variation of this classical problem in which the prediction is performed remotely based on a rate-constrained description $M$ of X. Upon receiving M, the remote node computes an estimate Y of Y. We follow the recent minimax approach to study this learning problem and show that it corresponds to a one-shot minimax noisy source coding problem. We then establish information theoretic bounds on the risk-rate Lagrangian cost and a general method to design a near-optimal descriptor-estimator pair, which can be viewed as a rate-constrained analog to the maximum conditional entropy principle used in the classical minimax learning problem. Our results show that a naive estimate-compress scheme for rate-constrained prediction is not in general optimal.
On variance reduction in stochastic gradient descent and its asynchronous variants

We study optimization algorithms based on variance reduction for stochastic gradient descent (SGD). Remarkable recent progress has been made in this direction through development of algorithms like SAG, SVRG, SAGA. These algorithms have been shown to outperform SGD, both theoretically and empirically. However, asynchronous versions of these algorithms—a crucial requirement for modern large-scale applications—have not been studied. We bridge this gap by presenting a unifying framework for many variance reduction techniques. Subsequently, we propose an asynchronous algorithm grounded in our framework, and prove its fast convergence. An important consequence of our general approach is that it yields asynchronous versions of variance reduction algorithms such as SVRG and SAGA as a byproduct. Our method achieves near linear speedup in sparse settings common to machine learning. We demonstrate the empirical performance of our method through a concrete realization of asynchronous SVRG.
How well do reduced models capture the dynamics in models of interacting neurons

This paper introduces a class of stochastic models of interacting neurons with emergent dynamics similar to those seen in local cortical populations. Rigorous results on existence and uniqueness of nonequilibrium steady states are proved. These network models are then compared to very simple reduced models driven by the same mean excitatory and inhibitory currents. Discrepancies in firing rates between network and reduced models are investigated and explained by correlations in spiking, or partial synchronization, working in concert with “nonlinearities” in the time evolution of membrane potentials. The use of simple random walks and their first passage times to simulate fluctuations in neuronal membrane potentials and interspike times is also considered.
Stabilization of the Khovanov Homotopy Type of Torus Links

The structure of the Khovanov homology of $(n,m)$ torus links has been extensively studied. In particular, Marko Stosic proved that the homology groups stabilize as $m\rightarrow\infty$. We show that the Khovanov homotopy types of $(n,m)$ torus links, as constructed by Robert Lipshitz and Sucharit Sarkar, also become stably homotopy equivalent as $m\rightarrow\infty$. We provide an explicit bound on values of $m$ beyond which the stabilization begins. As an application, we give new examples of torus links with non-trivial $Sq^2$ action.
Characterizing and Learning Equivalence Classes of Causal DAGs under Interventions

We consider the problem of learning causal DAGs in the setting where both observational and interventional data is available. This setting is common in biology, where gene regulatory networks can be intervened on using chemical reagents or gene deletions. Hauser and Buhlmann (2012) previously characterized the identifiability of causal DAGs under perfect interventions, which eliminate dependencies between targeted variables and their direct causes. In this paper, we extend these identifiability results to general interventions, which may modify the dependencies between targeted variables and their causes without eliminating them. We define and characterize the interventional Markov equivalence class that can be identified from general (not necessarily perfect) intervention experiments. We also propose the first provably consistent algorithm for learning DAGs in this setting and evaluate our algorithm on simulated and biological datasets.
Alchemist: An Apache Spark ⇔ MPI interface

The Apache Spark framework for distributed computation is popular in the data analytics community due to its ease of use, but its MapReduce-style programming model can incur significant overheads when performing computations that do not map directly onto this model. One way to mitigate these costs is to off-load computations onto MPI codes. In recent work, we introduced Alchemist, a system for the analysis of large-scale data sets. Alchemist calls MPI-based libraries from within Spark applications, and it has minimal coding, communication, and memory overheads. In particular, Alchemist allows users to retain the productivity benefits of working within the Spark software ecosystem without sacrificing performance efficiency in linear algebra, machine learning, and other related computations. In this paper, we discuss the motivation behind the development of Alchemist, and we provide a detailed overview its design and usage. We also demonstrate the efficiency of our approach on medium-to-large data sets, using some standard linear algebra operations, namely matrix multiplication and the truncated singular value decomposition of a dense matrix, and we compare the performance of Spark with that of Spark+Alchemist. These computations are run on the NERSC supercomputer Cori Phase 1, a Cray XC40.
Prediction-Correction Interior-Point Method for Time-Varying Convex Optimization

In this paper, we develop an interior-point method for solving a class of convex optimization problems with time-varying objective and constraint functions. Using log-barrier penalty functions, we propose a continuous-time dynamical system for tracking the (time-varying) optimal solution with an asymptotically vanishing error. This dynamical system is composed of two terms: a correction term consisting of a continuous-time version of Newton's method, and a prediction term able to track the drift of the optimal solution by taking into account the time-varying nature of the objective and constraint functions. Using appropriately chosen time-varying slack and barrier parameters, we ensure that the solution to this dynamical system globally asymptotically converges to the optimal solution at an exponential rate. We illustrate the applicability of the proposed method in two applications: a sparsity promoting least squares problem and a collision-free robot navigation problem.
K-homology and Fredholm operators I: Dirac Operators

Abstract This expository paper proves the Atiyah–Singer index theorem for Dirac operators as a corollary of Bott periodicity.
Attacking Visual Language Grounding with Adversarial Examples: A Case Study on Neural Image Captioning

Visual language grounding is widely studied in modern neural image captioning systems, which typically adopts an encoder-decoder framework consisting of two principal components: a convolutional neural network (CNN) for image feature extraction and a recurrent neural network (RNN) for language caption generation. To study the robustness of language grounding to adversarial perturbations in machine vision and perception, we propose Show-and-Fool, a novel algorithm for crafting adversarial examples in neural image captioning. The proposed algorithm provides two evaluation approaches, which check if we can mislead neural image captioning systems to output some randomly chosen captions or keywords. Our extensive experiments show that our algorithm can successfully craft visually-similar adversarial examples with randomly targeted captions or keywords, and the adversarial examples can be made highly transferable to other image captioning systems. Consequently, our approach leads to new robustness implications of neural image captioning and novel insights in visual language grounding.
Sensor-Based Reactive Symbolic Planning in Partially Known Environments

This paper considers the problem of completing assemblies of passive objects in nonconvex environments, cluttered with convex obstacles of unknown position, shape and size that satisfy a specific separation assumption. A differential drive robot equipped with a gripper and a LIDAR sensor, capable of perceiving its environment only locally, is used to position the passive objects in a desired configuration. The method combines the virtues of a deliberative planner generating high-level, symbolic commands, with the formal guarantees of convergence and obstacle avoidance of a reactive planner that requires little onboard computation and is used online. The validity of the proposed method is verified both with formal proofs and numerical simulations.
A Kunz-type characterization of regular rings via alterations

Abstract We prove that a local domain R, essentially of finite type over a field, is regular if and only if for every regular alteration π : X → Spec R , we have that R π ⁎ O X has finite (equivalently zero in characteristic zero) projective dimension.
Minimal initial data for potential Navier–Stokes singularities

Abstract Assuming some initial data u 0 ∈ H ˙ 1 / 2 ( R 3 ) lead to a singularity for the 3d Navier–Stokes equations, we show that there are also initial data with the minimal H ˙ 1 / 2 -norm which will produce a singularity.
Finiteness of Lagrangian fibrations with fixed invariants

Abstract We prove finiteness of the deformation classes of hyperkahler Lagrangian fibrations in any fixed dimension with fixed Fujiki constant and discriminant of the Beauville–Bogomolov–Fujiki lattice. We also prove there are only finitely many deformation classes of hyperkahler Lagrangian fibrations with an ample line bundle of a given degree on the general fibre of the fibration.
Period doubling, entropy, and renormalization

We show that in any family of stunted sawtooth maps, the set of maps whose set of periods is the set of all powers of 2 has no interior point, i.e., the combinatorial description of the boundary of chaos coincides with the topological description. We also show that, under mild assumptions, smooth multimodal maps whose set of periods is the set of all powers of 2 are infinitely renormalizable.
Quasi-trivial quandles and biquandles, cocycle enhancements and link-homotopy of pretzel links

We investigate some algebraic structures called quasi-trivial quandles and we use them to study link-homotopy of pretzel links. Precisely, a necessary and sufficient condition for a pretzel link with at least two components being trivial under link-homotopy is given. We also generalize the quasi-trivial quandle idea to the case of biquandles and consider enhancement of the quasi-trivial biquandle cocycle counting invariant by quasi-trivial biquandle cocycles, obtaining invariants of link-homotopy type of links analogous to the quasi-trivial quandle cocycle invariants in Inoue’s paper [A. Inoue, Quasi-triviality of quandles for link-homotopy, J. Knot Theory Ramifications 22(6) (2013) 1350026, doi:10.1142/S0218216513500260, MR3070837].
Geometric Inference on Kernel Density Estimates

We show that geometric inference of a point cloud can be calculated by examining its kernel density estimate with a Gaussian kernel. This allows one to consider kernel density estimates, which are robust to spatial noise, subsampling, and approximate computation in comparison to raw point sets. This is achieved by examining the sublevel sets of the kernel distance, which isomorphically map to superlevel sets of the kernel density estimate. We prove new properties about the kernel distance, demonstrating stability results and allowing it to inherit reconstruction results from recent advances in distance-based topological reconstruction. Moreover, we provide an algorithm to estimate its topology using weighted Vietoris-Rips complexes.
Model of the Songbird Nucleus HVC as a Network of Central Pattern Generators

Building on the observations by Hahnloser et al. of a remarkable sparse command center for sculpting avian song production, and accounting for significant input from the New York University laborat...
Learning Graphical Models Using Multiplicative Weights

We give a simple, multiplicative-weight update algorithm for learning undirected graphical models or Markov random fields (MRFs). The approach is new, and for the well-studied case of Ising models or Boltzmann machines we obtain an algorithm that uses a nearlyoptimal number of samples and has running time O(n^2) (where n is the dimension), subsuming and improving on all prior work. Additionally, we give the first efficient algorithm for learning Ising models over non-binary alphabets.Our main application is an algorithm for learning the structure of t-wise MRFs with nearly-optimal sample complexity (up to polynomial losses in necessary terms that depend on the weights) and running time that is n^t. In addition, given n^t samples, we can also learn the parameters of the model and generate a hypothesis that is close in statistical distance to the true MRF. All prior work runs in time n^d for graphs of bounded degree d and does not generate a hypothesis close in statistical distance even for t = 3. We observe that our runtime has the correct dependence on n and t assuming the hardness of learning sparse parities with noise.Our algorithm&#x2013; the Sparsitron&#x2013; is easy to implement (has only one parameter) and holds in the on-line setting. Its analysis applies a regret bound from Freund and Schapires classic Hedge algorithm. It also gives the first solution to the problem of learning sparse Generalized Linear Models (GLMs).