cssi/SciSciGPT-SciSciNet huggingface dataset:
Toll-like receptor signaling in hematopoietic stem and progenitor cells.

Purpose of review The innate immune system is essential in the protection against microbial infection and facilitating tissue repair mechanisms. During these stresses, the maintenance of innate immune cell numbers through stress-induced or emergency hematopoiesis is key for our survival. One major mechanism to recognize danger signals is through the activation of Toll-like receptors (TLRs) on the surface of hematopoietic cells, including hematopoietic stem cell (HSC) and hematopoietic progenitor cell (HPC), and nonhematopoietic cells, which recognize pathogen-derived or damaged-induced compounds and can influence the emergency hematopoietic response. This review explores how direct pathogen-sensing by HSC/HPC regulates hematopoiesis, and the positive and negative consequences of these signals. Recent findings Recent studies have highlighted new roles for TLRs in regulating HSC and HPC differentiation to innate immune cells of both myeloid and lymphoid origin and augmenting HSC and HPC migration capabilities. Most interestingly, new insights as to how acute versus chronic stimulation of TLR signaling regulates HSC and HPC function has been explored. Summary Recent evidence suggests that TLRs may play an important role in many inflammation-associated diseases. This suggests a possible use for TLR agonists or antagonists as potential therapeutics. Understanding the direct effects of TLR signaling by HSC and HPC may help regulate inflammatory/danger signal-driven emergency hematopoiesis.
Energy Cost Pass-Through in U.S. Manufacturing: Estimates and Implications for Carbon Taxes

We study how changes in energy input costs for U.S. manufacturers affect the relative welfare of manufacturing producers and consumers (i.e., incidence). We also develop a methodology to estimate the incidence of input taxes which accounts for incomplete pass-through, imperfect competition, and substitution amongst inputs. For the several industries we study, 70 percent of energy price-driven changes in input costs get passed through to consumers in the short- to medium-run. The share of the welfare cost that consumers bear is 25-75 percent smaller (and the share producers bear is larger) than models featuring complete pass-through and perfect competition would suggest.
Responsible Data Science

Data science is an emerging discipline that offers both promise and peril. Responsible data science refers to efforts that address both the technical and societal issues in emerging data-driven technologies. How can machine learning and AI systems reason effectively about complex dependencies and uncertainty? Furthermore, how do we understand the ethical and societal issues involved in data-driven decision-making? There is a pressing need to integrate algorithmic and statistical principles, social science theories, and basic humanist concepts so that we can think critically and constructively about the socio-technical systems we are building. In this talk, I will overview this emerging area.
Laser frequency upconversion in plasmas with finite ionization rates

Laser frequency can be upconverted in a plasma undergoing ionization. For finite ionization rates, the laser pulse energy is partitioned into a pair of counterpropagating waves and static transverse currents. The wave amplitudes are determined by the ionization rates and the input pulse duration. The strongest output waves can be obtained when the plasma is fully ionized in a time that is shorter than the pulse duration. The static transverse current can induce a static magnetic field with instant ionization, but it dissipates as heat if the ionization time is longer than a few laser periods. This picture comports with experimental data, providing a description of both laser frequency upconverters and other laser-plasma interaction with evolving plasma densities.Laser frequency can be upconverted in a plasma undergoing ionization. For finite ionization rates, the laser pulse energy is partitioned into a pair of counterpropagating waves and static transverse currents. The wave amplitudes are determined by the ionization rates and the input pulse duration. The strongest output waves can be obtained when the plasma is fully ionized in a time that is shorter than the pulse duration. The static transverse current can induce a static magnetic field with instant ionization, but it dissipates as heat if the ionization time is longer than a few laser periods. This picture comports with experimental data, providing a description of both laser frequency upconverters and other laser-plasma interaction with evolving plasma densities.
Structural transformation and embrittlement during lithiation and delithiation cycles in an amorphous silicon electrode

Abstract Silicon shows potential as an anode material in lithium ion batteries due to its high specific capacity, yet its considerable volume expansion during lithiation leads to fracture and pulverization. Unfortunately, neither the atomic-level structural evolution, nor the mechanical behavior of the anode during lithiation and delithiation cycles is well understood. Interestingly, the lithiation process of a-Si provides an interesting continuum from open-structured network glass to densely-packed atomic glass, which could be used to obtain useful insights regarding commonalities in glasses. Here atomic level simulation has been used to investigate one cycle of lithiation and delithiation of amorphous silicon electrode, using Grand Canonical Monte Carlo (GCMC) and molecular dynamics (MD) simulations. The atomic level structural transformation and damage accumulation of the anode during cycling has been systematically analyzed, as well as their mechanical responses in compact tension tests. There appears to be a ductile-brittle-ductile transition for the amorphous silicon anode during both the lithiation and delithiation cycle. In other words, amorphous silicon is particularly vulnerable at intermediate lithiation. The fracture behavior of lithiated silicon was found to correlate to the Poisson's ratio, due to variations in bond covalency and structural disorder.
ET-Lasso: A New Efficient Tuning of Lasso-type Regularization for High-Dimensional Data

The $L_1 $ regularization (Lasso) has proven to be a versatile tool to select relevant features and estimate the model coefficients simultaneously and has been widely used in many research areas such as genomes studies, finance, and biomedical imaging. Despite its popularity, it is very challenging to guarantee the feature selection consistency of Lasso especially when the dimension of the data is huge. One way to improve the feature selection consistency is to select an ideal tuning parameter. Traditional tuning criteria mainly focus on minimizing the estimated prediction error or maximizing the posterior model probability, such as cross-validation and BIC, which may either be time-consuming or fail to control the false discovery rate (FDR) when the number of features is extremely large. The other way is to introduce pseudo-features to learn the importance of the original ones. Recently, the Knockoff filter is proposed to control the FDR when performing feature selection. However, its performance is sensitive to the choice of the expected FDR threshold. Motivated by these ideas, we propose a new method using pseudo-features to obtain an ideal tuning parameter. In particular, we present the E fficient T uning of Lasso (ET-Lasso ) to separate active and inactive features by adding permuted features as pseudo-features in linear models. The pseudo-features are constructed to be inactive by nature, which can be used to obtain a cutoff to select the tuning parameter that separates active and inactive features. Experimental studies on both simulations and real-world data applications are provided to show that ET-Lasso can effectively and efficiently select active features under a wide range of scenarios.
Stereoselective synthesis of 4-alkylidene pyrrolidinones and pyrrolizidinones

Abstract α-Aminoalkylcuprates prepared from tert-butoxycarbonyl protected amines undergo a conjugate addition reaction with α,β-β,γ-allenyl esters to afford the corresponding β,γ-unsaturated esters with high degree of stereoselectivity. Treatment of the unsaturated esters with PhOH TMSCl or catechol boron bromide effects amine deprotection and lactamization to afford a 4-alkylidene-2-pyrrolidinone ring with preservation of the original olefin stereochemistry. The method can be used to prepare 4-alkylidene 2-pyrrolidinones and 2-pyrrolizidinones
Synthesis of the Hexasaccharide Fragment of Landomycin A: Application of Glycosyl Tetrazoles and Phosphites in the Synthesis of a Deoxyoligosaccharide

The synthesis of the hexasaccharide fragment of the antitumor antibiotic landomycin A (1) (aka. NSC 639187) is described. The stereocontrolled introduction of key glycoside linkages relies on the combined application of glycosyl tetrazoles and phosphites to establish α and β glycosidic linkages, respectively. Spectral comparison of landomycin A octaacetate (2) and hexasaccharide pentaacetate (3) serves to corroborate the assigned structure of 1 within the oligosaccharide domain.
Myths and Legends of the Baldwin Effect

This position paper argues that the Baldwin effect is widely misunderstood by the evolutionary computation community. The misunderstandings appear to fall into two general categories. Firstly, it is commonly believed that the Baldwin effect is concerned with the synergy that results when there is an evolving population of learning individuals. This is only half of the story. The full story is more complicated and more interesting. The Baldwin effect is concerned with the costs and benefits of lifetime learning by individuals in an evolving population. Several researchers have focussed exclusively on the benefits, but there is much to be gained from attention to the costs. This paper explains the two sides of the story and enumerates ten of the costs and benefits of lifetime learning by individuals in an evolving population. Secondly, there is a cluster of misunderstandings about the relationship between the Baldwin effect and Lamarckian inheritance of acquired characteristics. The Baldwin effect is not Lamarckian. A Lamarckian algorithm is not better for most evolutionary computing problems than a Baldwinian algorithm. Finally, Lamarckian inheritance is not a better model of memetic (cultural) evolution than the Baldwin effect.
Paradigms and Paradoxes: The Solubility of AgCl in Water: Some Thermochemical Issues of Aqueous Ag+ Ion

It is well established in the pedagogical literature that AgCl is insoluble in water while NaCl and KCl are soluble: applications of this difference are made in elementary studies of both qualitative and quantitative analysis. What is usually left unsaid, however, is why AgCl is so much less soluble than NaCl or KCl. This brief note addresses this issue in terms of the thermochemistry of these three metal chlorides and constituent ions as found in their solid salts, aqueous solutions and gaseous diatomic molecules.
N-(trans-1-Propenyl)carbazole: an excellent dienophile for cation radical Diels–Alder cycloadditions

Abstract The efficient, regiospecific, and periselective Diels–Alder cycloadditions of N -( trans -1-propenyl)carbazole, a highly electron rich dienophile, to both acyclic and cyclic conjugated dienes is found to be induced by tris(4-bromophenyl)aminium hexachloroantimonate.
Host-guest interactions of cyclodextrins and metalloporphyrins: supramolecular building blocks toward artificial heme proteins

Cyclodextrins are versatile building blocks for a variety of macromolecules due to the inclusion complexes that are formed with hydrophobic organic molecules. Cyclodextrin-porphyrin interactions are of particular interest since cyclodextrins can serve as a non-covalent binding pocket while metalloporphyrins could serve as the heme analogs in the construction of heme protein model compounds. Various approaches to the design and assembly of biomimetic porphyrin constructs are compared and contrasted in this minireview with a particular emphasis on self-assembled and porphyrin-cyclodextrin systems. Several recent advances from our laboratories are described in this context. A sensitive fluorescent binding probe, 6A-N-dansyl-permethylated-β-cyclodextrin (Dan-NH-TMCD), was found to form 2:1 complexes with the meso-tetraphenylporphyrins Mn(III)TCPP, Mn(III)TPPS and Mn(III)TF4TMAP with high binding constants. A perPEGylated cyclodextrin, heptakis(2,3,6-tri-O-2-(2-(2-methoxyethoxy)ethoxy)ethyl)-β-cyclodextrin (TP...
Responses to mechanically and visually cued water waves in the nervous system of the medicinal leech

Sensitivity to water waves is a key modality by which aquatic predators can detect and localize their prey. For one such predator – the medicinal leech, Hirudo verbana – behavioral responses to visual and mechanical cues from water waves are well documented. Here, we quantitatively characterized the response patterns of a multisensory interneuron, the S cell, to mechanically and visually cued water waves. As a function of frequency, the response profile of the S cell replicated key features of the behavioral prey localization profile in both visual and mechanical modalities. In terms of overall firing rate, the S cell response was not direction selective, and although the direction of spike propagation within the S cell system did follow the direction of wave propagation under certain circumstances, it is unlikely that downstream neuronal targets can use this information. Accordingly, we propose a role for the S cell in the detection of waves but not in the localization of their source. We demonstrated that neither the head brain nor the tail brain are required for the S cell to respond to visually cued water waves.
A View at the Millennium: the Efficiency of Enzymatic Catalysis

Binding TS in preference to S and increasing TΔS‡ by freezing out motions in E·S and E·TS have been accepted as the driving forces in enzymatic catalysis; however, the smaller value of ΔG‡ for a on...
Crystallographic and kinetic analyses of human IPMK reveal disordered domains modulate ATP binding and kinase activity.

Inositol polyphosphate multikinase (IPMK) is a member of the IPK-superfamily of kinases, catalyzing phosphorylation of several soluble inositols and the signaling phospholipid PI(4,5)P2 (PIP2). IPMK also has critical non-catalytic roles in p53, mTOR/Raptor, TRAF6 and AMPK signaling mediated partly by two disordered domains. Although IPMK non-catalytic functions are well established, it is less clear if the disordered domains are important for IPMK kinase activity or ATP binding. Here, kinetic and structural analyses of an engineered human IPMK lacking all disordered domains (ΔIPMK) are presented. Although the KM for PIP2 is identical between ΔIPMK and wild type, ΔIPMK has a 1.8-fold increase in kcat for PIP2, indicating the native IPMK disordered domains decrease IPMK activity in vitro. The 2.5 A crystal structure of ΔIPMK is reported, confirming the conserved ATP-grasp fold. A comparison with other IPK-superfamily structures revealed a putative “ATP-clamp” in the disordered N-terminus, we predicted would stabilize ATP binding. Consistent with this observation, removal of the ATP clamp sequence increases the KM for ATP 4.9-fold, indicating the N-terminus enhances ATP binding to IPMK. Together, these structural and kinetic studies suggest in addition to mediating protein-protein interactions, the disordered domains of IPMK impart modulatory capacity to IPMK kinase activity through multiple kinetic mechanisms.
An Improved Synthesis of Canthin-6-one

Abstract An improved route has been devised which provides canthin-6-one in the highest yield from tryptamine to date. Tryptamine is converted to Nb -benzyltryptamine via reaction with benzoylchlor...
Antiferromagnetic order in Ce3Ni2+xSi8−x (x≈1)

Abstract The structural, magnetic, thermodynamic and electrical properties of Ce3Ni2+xSi8−x ( x ≈ 1 ) were investigated by means of X-ray diffraction, magnetic susceptibility, specific heat and resistivity measurements. Structure determination by means of single-crystal X-ray diffraction, supported by elemental analysis revealed that Ce3Ni3.1(1)Si6.9(1) and its La-analogue La3Ni3.01(2)Si6.99(2) crystallize in the orthorhombic space group C m m m (No. 65) with unit cell parameters of a = 4 . 0935 ( 4 ) A, b = 25 . 984 ( 2 ) A, c = 4 . 1746 ( 4 ) A; and a = 4 . 1257 ( 3 ) A, b = 26 . 167 ( 2 ) A and c = 4 . 2186 ( 3 ) A, respectively. The comprehensive property measurements performed on single crystals indicate the existence of an onset of antiferromagnetic order in Ce3Ni2+xSi8−x ( x ≈ 1 ) at T N = 4 K and a Kondo-like resistivity with a Kondo temperature of T * = 75 K. These results suggest a very light heavy-fermion behavior in the title compound with corresponding Sommerfeld-coefficient γ = 51 mJ/mol Ce K.
The conversion of benzothiazines to 2-alkenyl anilines

Abstract Upon treatment with excess potassium dimsylate in DMSO benzothiazines 1a-1j undergo an elimination of the sulfoximine functional group to give 2-alkenylsulfinanilides nonstereoselectively in good to excellent yield. These are easily converted to the corresponding anilines with ethanolic potassium hydroxide. Mechanistic studies indicate that the elimination reaction takes place via an Elcb mechanism.
Mixed 1,1-Bisphosphorus Compounds: Synthesis, Alkylation, and Horner—Wadsworth—Emmons Olefination Reactions

Mixed 1,1-bisphosphorus compounds were prepared by the reaction between a phosphonate diester anion and a P(III) chlorophosphine, or its P(V) borane complex. After deprotonation either in situ or in a separate step, the resulting products can be alkylated or reacted with carbonyl compounds. A variety of olefination products were obtained, generally with high E-stereoselectivity. The reaction is competitive with other methods for the synthesis of alkenyl phosphorus compounds, and in the case of trisubstituted alkenes, regio- and stereocontrolled olefination provides products not easily accessible via any other process. The deprotection of phosphine−borane adducts was also demonstrated. Overall, a variety of novel organophosphorus reagents and products were synthesized easily and in good yields.
Persuasion in Networks: Public Signals and k-Cores

We consider a setting where agents in a social network take binary actions, which exhibit local strategic complementarities. In particular, the payoff of each agent depends on the number of her neighbors who take action 1, as well as an underlying state of the world. The agents are a priori uninformed about the state, which belongs to an interval of the real line. An information designer (sender) can commit to a public signaling mechanism, which once the state is realized reveals a public signal to all the agents. Agents update their posterior about the state using the realization of the public signal, and possibly change their actions. The objective of the information designer is to maximize the expected activity level, i.e., the expected total number of agents who take action 1. How should the information information designer choose her public signaling mechanism to achieve this objective? This is the first paper to study the design of public signaling mechanisms in social networks, and its main contribution is to provide an answer this question.
Convenient preparation of 1-amidoindenes.

Lewis acid-catalyzed α-amidoalkylation of enolizable aldehydes with N-(α-benzotriazolyl-α-arylalkyl)amides followed by intramolecular Friedel−Crafts cyclization provides a convenient route to 2-substituted 1-amidoindenes.
One-pot conversion of glycals to cis-1,2-isopropylidene-α-glycosides

Described is a general method for the conversion of glycals to the corresponding 1,2-cis-isopropylidene-alpha-glycosides. Epoxidation of glycals with dimethyldioxirane followed by ZnCl(2)-catalyzed addition of acetone converted a variety of protected glycals into 1,2-cis-isopropylidene-alpha-glycosides in good yield. The reaction is compatible with a range of protecting groups, including esters, benzyl ethers, and silyl ethers, as well as free hydroxyl groups. This method has been applied to develop a synthesis of protected glucuronic acid 1, a key intermediate in the synthesis of glycosaminoglycans. Compound 1 was produced in seven steps and 32% overall yield.
1-Cyano-3-(1H)-1,2-benziodoxols: stable cyanoiodinanes and efficient reagents for direct N-alkyl cyanation of N,N-dialkylarylamines

Abstract Cyanobenziodoxols 2 and 4 can be prepared from benziodoxols 1 or 3 and cyanotrimethylsilane in the form of stable, crystalline compounds. Cyanobenziodoxol 2 reacts with N,N-dimethylary lamines under mild conditions to afford N-(cyanomethyl)-N-methylarylamines 6 in excellent yields.
Macrocyclic Ligands with Partially Fluorinated Sidearms: Synthesis and Metal Ion Complexation

Abstract Derivatives of aza-12-crown-4, aza-15-crown-5, aza-18-crown-6, 1,10-diaza-18-crown-6 and 1,4,8,12-tetraazacyclopentadecane with partially fluorinated substituents attached to nitrogen are prepared. Their efficiencies and selectivities in alkali metal and silver picrate extractions from aqueous solutions into chloroform are determined and compared with those of appropriate model compounds. Ionophores with longer spacers of –CH 2 OCH 2 CH 2 – and –CH 2 CH 2 OCH 2 CH 2 – between the nitrogen atom(s) of the macroring and the perfluoroalkyl group(s) exhibit greater extraction efficiencies than do analogues with shorter spacers consisting of one or two methylene groups.
The First Examples of Ring-Closing Olefin Metathesis of Vinyl Chlorides

Ring-closing metathesis (RCM) of olefinic vinyl chlorides can be effected by using the second generation Grubbs catalyst (10 mol %, PhH, 65 °C) to produce a variety of carbocyclic and heterocyclic five-, six-, and seven-membered rings in excellent yields.
One-pot synthesis of aldehydes or ketones from carboxylic acids via in situ generation of Weinreb amides using the Deoxo-Fluor reagent

A one-pot, high yield conversion of carboxylic acids to the corresponding aldehydes and ketones is described. The highlight of this methodology is the in situ generation of Weinreb amides with the Deoxo-Fluor reagent, which undergo nucleophilic reaction with DIBAL-H and Grignard reagents.
Palladium-catalyzed dehydrative allylation of hypophosphorous acid with allylic alcohols.

A novel palladium-catalyzed allylation of H3PO2 with allylic alcohols is described. The phosphorus−carbon bond-forming reaction produces allylic-H-phosphinic acids and water, in the absence of additives. Primary H-phosphinic acids are obtained in excellent yields, whereas secondary H-phosphinic acids react sluggishly. A reusable polymer-supported catalyst is also described. The reaction provides an environmentally sound approach to H-phosphinic acids.
Generation of aryltropylium ions by photoinduced and thermal electron transfer

Abstract The two step oxidation of colourless arylcycloheptatrienes to the corresponding coloured aryltropylium salts occurs either via the initiation by photoexcited electron acceptors or thermally by tetracyanoquinodimethane (TCNQ). In each case not a hydride ion is transferred but the oxidation follows the electron - proton - electron sequence
Pulmonary Metagenomic Sequencing Suggests Missed Infections in Immunocompromised Children

Author(s): Zinter, Matt S; Dvorak, Christopher C; Mayday, Madeline Y; Iwanaga, Kensho; Ly, Ngoc P; McGarry, Meghan E; Church, Gwynne D; Faricy, Lauren E; Rowan, Courtney M; Hume, Janet R; Steiner, Marie E; Crawford, Emily D; Langelier, Charles; Kalantar, Katrina; Chow, Eric D; Miller, Steve; Shimano, Kristen; Melton, Alexis; Yanik, Gregory A; Sapru, Anil; DeRisi, Joseph L | Abstract: BackgroundDespite improved diagnostics, pulmonary pathogens in immunocompromised children frequently evade detection, leading to significant mortality. Therefore, we aimed to develop a highly sensitive metagenomic next-generation sequencing (mNGS) assay capable of evaluating the pulmonary microbiome and identifying diverse pathogens in the lungs of immunocompromised children.MethodsWe collected 41 lower respiratory specimens from 34 immunocompromised children undergoing evaluation for pulmonary disease at 3 children's hospitals from 2014-2016. Samples underwent mechanical homogenization, parallel RNA/DNA extraction, and metagenomic sequencing. Sequencing reads were aligned to the National Center for Biotechnology Information nucleotide reference database to determine taxonomic identities. Statistical outliers were determined based on abundance within each sample and relative to other samples in the cohort.ResultsWe identified a rich cross-domain pulmonary microbiome that contained bacteria, fungi, RNA viruses, and DNA viruses in each patient. Potentially pathogenic bacteria were ubiquitous among samples but could be distinguished as possible causes of disease by parsing for outlier organisms. Samples with bacterial outliers had significantly depressed alpha-diversity (median, 0.61; interquartile range [IQR], 0.33-0.72 vs median, 0.96; IQR, 0.94-0.96; P l .001). Potential pathogens were detected in half of samples previously negative by clinical diagnostics, demonstrating increased sensitivity for missed pulmonary pathogens (P l .001).ConclusionsAn optimized mNGS assay for pulmonary microbes demonstrates significant inoculation of the lower airways of immunocompromised children with diverse bacteria, fungi, and viruses. Potential pathogens can be identified based on absolute and relative abundance. Ongoing investigation is needed to determine the pathogenic significance of outlier microbes in the lungs of immunocompromised children with pulmonary disease.
Restoration of susceptibility to amikacin by 8-hydroxyquinoline analogs complexed to zinc.

Gram-negative pathogens resistant to amikacin and other aminoglycosides of clinical relevance usually harbor the 6’-N-acetyltransferase type Ib [AAC(6')-Ib], an enzyme that catalyzes inactivation of the antibiotic by acetylation using acetyl-CoA as donor substrate. Inhibition of the acetylating reaction could be a way to induce phenotypic conversion to susceptibility in these bacteria. We have previously observed that Zn2+ acts as an inhibitor of the enzymatic acetylation of aminoglycosides by AAC(6')-Ib, and in complex with ionophores it effectively reduced the levels of resistance in cellulo. We compared the activity of 8-hydroxyquinoline, three halogenated derivatives, and 5-[N-Methyl-N-Propargylaminomethyl]-8-Hydroxyquinoline in complex with Zn2+ to inhibit growth of amikacin-resistant Acinetobacter baumannii in the presence of the antibiotic. Two of the compounds, clioquinol (5-chloro-7-iodo-8-hydroxyquinoline) and 5,7-diiodo-8-hydroxyquinoline, showed robust inhibition of growth of the two A. baumannii clinical isolates that produce AAC(6')-Ib. However, none of the combinations had any activity on another amikacin-resistant A. baumannii strain that possesses a different, still unknown mechanism of resistance. Time-kill assays showed that the combination of clioquinol or 5,7-diiodo-8-hydroxyquinoline with Zn2+ and amikacin was bactericidal. Addition of 8-hydroxyquinoline, clioquinol, or 5,7-diiodo-8-hydroxyquinoline, alone or in combination with Zn2+, and amikacin to HEK293 cells did not result in significant toxicity. These results indicate that ionophores in complex with Zn2+ could be developed into potent adjuvants to be used in combination with aminoglycosides to treat Gram-negative pathogens in which resistance is mediated by AAC(6')-Ib and most probably other related aminoglycoside modifying enzymes.
Generation of allyl Grignard reagents via titanocene-catalyzed activation of allyl halides

Abstract A protocol for the generation of allyl Grignard reagents via the catalytic activation of allyl halides is described herein. Subsequent nucleophilic addition to carbonyl derivatives provided the desired homo allylic alcohols in excellent yields (84–99%). Evidence suggests that titanocene dichloride catalyzes the formation of an allyl Grignard species which reacts solely with the carbonyl electrophile as evidenced by the complete absence of Wurtz coupling. This methodology will have wide-ranging applicability in the generation of highly reactive organometallic reagents.
Direct modulation of aberrant brain network connectivity through real-time NeuroFeedback

Even when we are at rest, our brains are always active. For example, areas of the brain involved in vision remain active in complete darkness. Different brain regions that connect together to perform a given task often show coordinated activity at rest. Past studies have shown that these resting connections are different in people with conditions such as autism. Some brain regions are more weakly connected while others are more strongly connected in people with autism spectrum disorder compared to those without. Furthermore, people with more severe symptoms seem to have more abnormal connections. “Neurofeedback training” is a method of changing the resting connections between different brain regions. Scientists measure a brain signal – the connection between different brain regions – from a person in real time. They then provide positive feedback to the person if this signal improves. For example, if a connection that is too weak becomes stronger, the scientists might reinforce this by providing feedback on the success. Previous work has shown that neurofeedback training may even change people’s behaviour. However, it has not yet been explored as a method of treating the abnormal connections seen in people with autism when their brains are at rest. To address this, Ramot et al. used a technique known as “functional magnetic resonance imaging” (or fMRI for short) to measure brain activity in young men with autism. First, certain brain regions were identified as having abnormal resting connections with each other. The participants were then asked to look at a blank screen and to try to reveal a picture hidden underneath. Whenever the connections between the chosen brain regions improved, part of the picture was revealed on the screen, accompanied by an upbeat sound. The participants were unaware that it was their brain signals causing this positive feedback. This form of neurofeedback training successfully changed the abnormal brain connections in most of the participants with autism, making their connections more similar to those seen in the wider population. These effects lasted up to a year after training. Early results also suggest that these changes were related to improvements in symptoms, although further work is needed to see if doctors could reliably use this method as a therapy. These findings show that neurofeedback training could potentially help treat not only autism spectrum disorder, but a range of other disorders that involve abnormal brain connections, including depression and schizophrenia.
Synthesis of N,N'-bis(acrylamido)acetic acid-based T-antigen glycodendrimers and their mouse monoclonal IgG antibody binding properties.

Novel glycodendrimers based on N,N'-bis(acrylamido)acetic acid core with valencies between two and six were synthesized. The breast cancer-associated T-antigen carbohydrate marker, (β-Gal-(1-3)-α-GalNAc-OR), was then conjugated by (i) 1,4-conjugate addition of thiolated T-antigen to the N-acrylamido dendritic cores and by (ii) amide bond formation between an acid derivative of the T-antigen and the polyamino dendrimers. The protein-binding ability of these new glycodendrimers was fully demonstrated by turbidimetric analysis and by enzyme-linked immunosorbent assay (ELISA) using peanut lectin from Arachis hypogaea and a mouse monoclonal antibody (MAb) FAA-J11 (IgG3). When tested as inhibitors of binding between MAb and a polymeric form of the T-antigen (T-antigen-co-polyacrylamide) used as a coating antigen, di- (17), tetra- (20), hexa- (21), and tetravalent (22) dendrimers showed IC50 values of 174, 19, 48, and 18 nM, respectively. Two tetramers showed 120- to ∼128-fold increased inhibitory properties ove...
NaCu(Ta1−yNby)4O11 solid solution: A tunable band gap spanning the visible-light wavelengths

The new solid-solution NaCu(Ta{sub 1-y}Nb{sub y}){sub 4}O{sub 11} (0{<=}y{<=}0.7) was synthesized by solid-state methods in the form of bulk powders that ranged from light-yellow to brown colored and were characterized by powder X-ray diffraction techniques (Space group R-3c (no. 167); Z=6; a=6.214(1)-6.218(1) Angstrom-Sign and c=36.86(1)-36.94(1) Angstrom-Sign ). Full-profile Rietveld refinements confirmed a site-differentiated ordering of the Cu(I) and Na cations, i.e., occupying the 12c (linear environment) and 18d (seven-coordinate environment) crystallographic sites respectively. Conversely, a statistical mixture of Ta(V) and Nb(V) cations occurred over the 6b (octahedral environment) or the 18e (pentagonal-bipyramidal environment) crystallographic sites, without any preferential segregation. The UV-Vis diffuse reflectance spectra showed a significant red-shift of the optical bandgap size (indirect) from {approx}2.70 eV to {approx}1.80 eV across the solid solution with increasing Nb(V) content. Electronic-structure calculations using the tight-binding linear-muffin-tin-orbital approach showed that the reduction in bandgap size arises from the introduction of the lower-energy Nb 4d{sup 0} orbitals into the conduction band and consequently a lower energy of the conduction band edge. The lowest-energy bandgap transitions were found to be derived from electronic transitions between the filled Cu(I) and the empty Nb(V) d-orbitals, with a small amount of mixing with the O 2p orbitals. Themore » resulting conduction and valence band energies are found to approximately bracket the redox potentials for water reduction and oxidation, and meeting the thermodynamic requirements for photocatalytic water-splitting reactions. - Graphical Abstract: The NaCu(Ta{sub 1-y}Nb{sub y}){sub 4}O{sub 11} (0{<=}y{<=}0.7) solid solution shows a statistical occupancy of the Ta(V) and Nb(V) cations in both octahedral and pentagonal bipyramidal environments. An increasing Nb(V) content also causes a significant red-shift of the bandgap size from {approx}2.70 eV to {approx}1.80 eV. Highlights: Black-Right-Pointing-Pointer Double solid-solution of M(I) (=Cu, Na) and M(V) (=Nb, Ta) crystallographic sites. Black-Right-Pointing-Pointer Increasing Nb content leads to tunable bandgap size from {approx}2.70 eV to {approx}1.80 eV across the solid solution. Black-Right-Pointing-Pointer Layers of MO{sub 7} (M=Ta, Nb) pentagonal bipyramids and isolated MO{sub 6} octahedra.« less
The expendable male hypothesis.

Matriliny is a system of kinship in which descent and inheritance are conferred along the female line. The theoretically influential concept of the matrilineal puzzle posits that matriliny poses sp...
Dual fans and mirror symmetry

Abstract We show that the mirror constructions of Greene–Plesser, Berglund–Hubsch, Batyrev, Batyrev–Borisov, Givental and Hori–Vafa can be expressed in terms of what we call dual fans. To do this, we associate to a pair of dual fans a pair of toric Landau–Ginzburg models, and we describe a process by which each of the mirror constructions listed also produces a pair of toric Landau–Ginzburg models. Replacing mirror pairs by toric Landau–Ginzburg models is reversible, and our main result is that the dual fan models and the mirror pairs models coincide.
Neural Variational Inference and Learning in Undirected Graphical Models

Many problems in machine learning are naturally expressed in the language of undirected graphical models. Here, we propose black-box learning and inference algorithms for undirected models that optimize a variational approximation to the log-likelihood of the model. Central to our approach is an upper bound on the log-partition function parametrized by a function q that we express as a flexible neural network. Our bound makes it possible to track the partition function during learning, to speed-up sampling, and to train a broad class of hybrid directed/undirected models via a unified variational inference framework. We empirically demonstrate the effectiveness of our method on several popular generative modeling datasets.
Measurement of nonlinear piezoelectric coefficients using a micromechanical resonator

We describe and demonstrate a method by which the nonlinear piezoelectric properties of a piezoelectric material may be measured by detecting the force that it applies on a suspended micromechanical resonator at one of its mechanical resonance frequencies. Resonators are used in countless applications; this method could provide a means for better-characterizing material behaviors within real MEMS devices. Further, special devices can be designed to probe this nonlinear behavior at specific frequencies with enhanced signal sizes. The resonators used for this experiment are actuated using a 1-μm-thick layer of aluminum nitride. When driven at large amplitudes, the piezoelectric layer generates harmonics, which are measurable in the response of the resonator. In this experiment, we measured the second-order piezoelectric coefficient of aluminum nitride to be − ( 23.1 ± 14.1 ) × 10 − 22 m / V 2.
Curvature-aided incremental aggregated gradient method

We propose a new algorithm for finite sum optimization which we call the curvature-aided incremental aggregated gradient (CIAG) method. Motivated by the problem of training a classifier for a d-dimensional problem, where the number of training data is m and m ≫ d ≫ 1, the CIAG method seeks to accelerate incremental aggregated gradient (IAG) methods using aids from the curvature (or Hessian) information, while avoiding the evaluation of matrix inverses required by the incremental Newton (IN) method. Specifically, our idea is to exploit the incrementally aggregated Hessian matrix to trace the full gradient vector at every incremental step, therefore achieving an improved linear convergence rate over the state-of-the-art IAG methods. For strongly convex problems, the fast linear convergence rate requires the objective function to be close to quadratic, or the initial point to be close to optimal solution. Importantly, we show that running one iteration of the CIAG method yields the same improvement to the optimality gap as running one iteration of the full gradient method, while the complexity is O(d2) for CIAG and O(md) for the full gradient. Overall, the CIAG method strikes a balance between the high computation complexity incremental Newtontype methods and the slow IAG method. Our numerical results support the theoretical findings and show that the CIAG method often converges with much fewer iterations than IAG, and requires much shorter running time than IN when the problem dimension is high.
Batch Policy Learning under Constraints

When learning policies for real-world domains, two important questions arise: (i) how to efficiently use pre-collected off-policy, non-optimal behavior data; and (ii) how to mediate among different competing objectives and constraints. We thus study the problem of batch policy learning under multiple constraints, and offer a systematic solution. We first propose a flexible meta-algorithm that admits any batch reinforcement learning and online learning procedure as subroutines. We then present a specific algorithmic instantiation and provide performance guarantees for the main objective and all constraints. To certify constraint satisfaction, we propose a new and simple method for off-policy policy evaluation (OPE) and derive PAC-style bounds. Our algorithm achieves strong empirical results in different domains, including in a challenging problem of simulated car driving subject to multiple constraints such as lane keeping and smooth driving. We also show experimentally that our OPE method outperforms other popular OPE techniques on a standalone basis, especially in a high-dimensional setting.
Data-Driven Approach to Simulating Realistic Human Joint Constraints

Modeling realistic human joint limits is important for applications involving physical human-robot interaction. However, setting appropriate human joint limits is challenging because it is pose-dependent: the range of joint motion varies depending on the positions of other bones. The paper introduces a new technique to accurately simulate human joint limits in physics simulation. We propose to learn an implicit equation to represent the boundary of valid human joint configurations from real human data. The function in the implicit equation is represented by a fully connected neural network whose gradients can be efficiently computed via back-propagation. Using gradients, we can efficiently enforce realistic human joint limits through constraint forces in a physics engine or as constraints in an optimization problem.
Perfect dyadic operators: Weighted T(1) theorem and two weight estimates

Abstract Perfect dyadic operators were first introduced in [1] , where a local T ( b ) theorem was proved for such operators. In [3] it was shown that for every singular integral operator T with locally bounded kernel on R n × R n there exists a perfect dyadic operator T such that T − T is bounded on L p ( d x ) for all 1 p ∞ . In this paper we show a decomposition of perfect dyadic operators on real line into four well known operators: two selfadjoint operators, paraproduct and its adjoint. Based on this decomposition we prove a sharp weighted version of the T ( 1 ) theorem for such operators, which implies A 2 conjecture for such operators with constant which only depends on ‖ T ( 1 ) ‖ BMO d , ‖ T ⁎ ( 1 ) ‖ BMO d and the constant in testing conditions for T. Moreover, the constant depends on these parameters at most linearly. In this paper we also obtain sufficient conditions for the two weight boundedness for a perfect dyadic operator and simplify these conditions under additional assumptions that weights are in the Muckenhoupt class A ∞ d .
Noise-adaptive margin-based active learning and lower bounds under Tsybakov noise condition

We present a simple noise-robust margin-based active learning algorithm to find homogeneous (passing the origin) linear separators and analyze its error convergence when labels are corrupted by noise. We show that when the imposed noise satisfies the Tsybakov low noise condition (Mammen, Tsybakov, and others 1999; Tsybakov 2004) the algorithm is able to adapt to unknown level of noise and achieves optimal statistical rate up to polylogarithmic factors. We also derive lower bounds for margin based active learning algorithms under Tsybakov noise conditions (TNC) for the membership query synthesis scenario (Angluin 1988). Our result implies lower bounds for the stream based selective sampling scenario (Cohn 1990) under TNC for some fairly simple data distributions. Quite surprisingly, we show that the sample complexity cannot be improved even if the underlying data distribution is as simple as the uniform distribution on the unit ball. Our proof involves the construction of a well-separated hypothesis set on the d-dimensional unit ball along with carefully designed label distributions for the Tsybakov noise condition. Our analysis might provide insights for other forms of lower bounds as well.
Ultra-Fine Entity Typing

We introduce a new entity typing task: given a sentence with an entity mention, the goal is to predict a set of free-form phrases (e.g. skyscraper, songwriter, or criminal) that describe appropriate types for the target entity. This formulation allows us to use a new type of distant supervision at large scale: head words, which indicate the type of the noun phrases they appear in. We show that these ultra-fine types can be crowd-sourced, and introduce new evaluation sets that are much more diverse and fine-grained than existing benchmarks. We present a model that can predict ultra-fine types, and is trained using a multitask objective that pools our new head-word supervision with prior supervision from entity linking. Experimental results demonstrate that our model is effective in predicting entity types at varying granularity; it achieves state of the art performance on an existing fine-grained entity typing benchmark, and sets baselines for our newly-introduced datasets.
White matter hyperintensity segmentation from T1 and FLAIR images using fully convolutional neural networks enhanced with residual connections

Segmentation and quantification of white matter hyperintensities (WMHs) are of great importance in studying and understanding various neurological and geriatric disorders. Although automatic methods have been proposed for WMH segmentation on magnetic resonance imaging (MRI), manual corrections are often necessary to achieve clinically practical results. Major challenges for WMH segmentation stem from their inhomogeneous MRI intensities, random location and size distributions, and MRI noise. The presence of other brain anatomies or diseases with enhanced intensities adds further difficulties. To cope with these challenges, we present a specifically designed fully convolutional neural network (FCN) with residual connections to segment WMHs by using combined T1 and fluid-attenuated inversion recovery (FLAIR) images. Our customized FCN is designed to be straightforward and generalizable, providing efficient end-to-end training due to its enhanced information propagation. We tested our method on the open WMH Segmentation Challenge MICCAI2017 dataset, and, despite our method's relative simplicity, results show that it performs amongst the leading techniques across five metrics. More importantly, our method achieves the best score for Hausdorff distance and average volume difference in testing datasets from two MRI scanners that were not included in training, demonstrating better generalization ability of our proposed method over its competitors.
On Invariants of $\text{C}^*$-algebras with the ideal property

In this paper, we consider $\text{C}^*$-algebras with the ideal property (the ideal property unifies the simple and real rank zero cases). We define two categories related the invariants of the $\text{C}^*$-algebras with the ideal property. And we showed that these two categories are in fact isomorphic. As a consequence, the Elliott's Invariant and the Stevens' Invariant are isomorphic for $\text{C}^*$-algebras with the ideal property.
Optimally-tuned nonparametric linear equalization for massive MU-MIMO systems

This paper deals with linear equalization in massive multi-user multiple-input multiple-output (MU-MIMO) wireless systems. We first provide simple conditions on the antenna configuration for which the well-known linear minimum mean-square error (L-MMSE) equalizer provides near-optimal spectral efficiency, and we analyze its performance in the presence of parameter mismatches in the signal and/or noise powers. We then propose a novel, optimally-tuned NOnParametric Equalizer (NOPE) for massive MU-MIMO systems, which avoids knowledge of the transmit signal and noise powers altogether. We show that NOPE achieves the same performance as that of the L-MMSE equalizer in the large-antenna limit, and we demonstrate its efficacy in realistic, finite-dimensional systems. From a practical perspective, NOPE is computationally efficient and avoids dedicated training that is typically required for parameter estimation.
Inferring Narrative Causality between Event Pairs in Films.

To understand narrative, humans draw inferences about the underlying relations between narrative events. Cognitive theories of narrative understanding define these inferences as four different types of causality, that include pairs of events A, B where A physically causes B (X drop, X break), to pairs of events where A causes emotional state B (Y saw X, Y felt fear). Previous work on learning narrative relations from text has either focused on “strict” physical causality, or has been vague about what relation is being learned. This paper learns pairs of causal events from a corpus of film scene descriptions which are action rich and tend to be told in chronological order. We show that event pairs induced using our methods are of high quality and are judged to have a stronger causal relation than event pairs from Rel-Grams.