Atropisomers have emerged as important structural scaffolds in natural products, drug design, and asymmetric synthesis. Recently, N−N biaryl atropisomers have drawn increasing interest due to their ...unique structure and relatively stable axes. However, its asymmetric synthesis remains scarce compared to its well‐developed C−C biaryl analogs. In this concept, we summarize the asymmetric synthesis of N−N biaryl atropisomers including N−N pyrrole−pyrrole, N−N pyrrole−indole, N−N indole−indole, and N−N indole−carbazole, during which a series synthetic strategies are highlighted. Also, a synthetic evolution is briefly reviewed and an outlook of N−N biaryl atropisomers synthesis is offered.
Although N−N Biaryl atropisomers has emerged into valuable scaffolds in natural products, drug design and asymmetric synthesis, its asymmetric synthesis is scare until recently. This concept will focus on the asymmetric synthesis of the divergent N−N biaryl atropisomers scaffolds including N−N bipyrroles atropisomers, N−N pyrrole−indole atropisomers, N−N bisindoles atropisomers, N−N indole−carbazole atropisomers.
The exceptional points (EPs) of non-Hermitian systems, where n different energy eigenstates merge into an identical one, have many intriguing properties that have no counterparts in Hermitian ...systems. In particular, the ϵ 1 n dependence of the energy level splitting on a perturbative parameter ϵ near an nth order EP stimulates the idea of metrology with arbitrarily high sensitivity, since the susceptibility dϵ1/n/dϵ diverges at the EP. Here we theoretically study the sensitivity of parameter estimation near the EPs, using the exact formalism of quantum Fisher information (QFI). The QFI formalism allows the highest sensitivity to be determined without specifying a specific measurement approach. We find that the EP bears no dramatic enhancement of the sensitivity. Instead, the coalescence of the eigenstates exactly counteracts the eigenvalue susceptibility divergence and makes the sensitivity a smooth function of the perturbative parameter.
Palladium‐catalyzed enantioselective dearomative arylalkynylation of N‐substituted indoles, through a Heck/Sonogashira sequence, was established using a new BINOL‐based phosphoramidite as the chiral ...ligand. A wide range of 2,3‐disubstituted indolines, bearing vicinal quaternary and tertiary stereocenters, were efficiently constructed in one step with excellent enantioselectivities (up to 97 % ee) and diastereoselectivities (>20:1).
Double the function: A highly enantioselective dearomative arylalkynylation of N‐substituted indoles with alkynes has been established by using palladium and a BINOL‐based phosphoramidite as the chiral ligand. A wide range of 2,3‐disubstituted indolines, bearing vicinal tertiary and quaternary stereocenters, were constructed in one step with excellent enantio‐ and diastereoselectivities.
Do Convolutional Neural Networks Learn Class Hierarchy? Bilal, Alsallakh; Jourabloo, Amin; Mao Ye ...
IEEE transactions on visualization and computer graphics,
2018-Jan., 2018-01-00, 2018-1-00, 20180101, Letnik:
24, Številka:
1
Journal Article
Recenzirano
Odprti dostop
Convolutional Neural Networks (CNNs) currently achieve state-of-the-art accuracy in image classification. With a growing number of classes, the accuracy usually drops as the possibilities of ...confusion increase. Interestingly, the class confusion patterns follow a hierarchical structure over the classes. We present visual-analytics methods to reveal and analyze this hierarchy of similar classes in relation with CNN-internal data. We found that this hierarchy not only dictates the confusion patterns between the classes, it furthermore dictates the learning behavior of CNNs. In particular, the early layers in these networks develop feature detectors that can separate high-level groups of classes quite well, even after a few training epochs. In contrast, the latter layers require substantially more epochs to develop specialized feature detectors that can separate individual classes. We demonstrate how these insights are key to significant improvement in accuracy by designing hierarchy-aware CNNs that accelerate model convergence and alleviate overfitting. We further demonstrate how our methods help in identifying various quality issues in the training data.
Quantum coherence control usually requires low temperature environments. Even for nitrogen-vacancy center spins in diamond, a remarkable exception, the coherence signal is limited to about 700 K due ...to the quench of the spin-dependent fluorescence at a higher temperature. Here we overcome this limit and demonstrate quantum coherence control of the electron spins of nitrogen-vacancy centers in nanodiamonds at temperatures near 1000 K. The scheme is based on initialization and readout of the spins at room temperature and control at high temperature, which is enabled by pulse laser heating and rapid diffusion cooling of nanodiamonds on amorphous carbon films. Using the diamond magnetometry based on optically detected magnetic resonance up to 800 K, we observe the magnetic phase transition of a single nickel nanoparticle at about 615 K. This work enables nano-thermometry and nano-magnetometry in the high-temperature regime.
Consider a multi-dimensional spatio-temporal (ST) dataset where each entry is a numerical measure defined by the corresponding temporal, spatial and other domain-specific dimensions. A typical ...approach to explore such data utilizes interactive visualizations with multiple coordinated views. Each view displays the aggregated measures along one or two dimensions. By brushing on the views, analysts can obtain detailed information. However, this approach often cannot provide sufficient guidance for analysts to identify patterns hidden within subsets of data. Without a priori hypotheses, analysts need to manually select and iterate through different slices to search for patterns, which can be a tedious and lengthy process. In this work, we model multidimensional ST data as tensors and propose a novel piecewise rank-one tensor decomposition algorithm which supports automatically slicing the data into homogeneous partitions and extracting the latent patterns in each partition for comparison and visual summarization. The algorithm optimizes a quantitative measure about how faithfully the extracted patterns visually represent the original data. Based on the algorithm we further propose a visual analytics framework that supports a top-down, progressive partitioning workflow for level-of-detail multidimensional ST data exploration. We demonstrate the general applicability and effectiveness of our technique on three datasets from different application domains: regional sales trend analysis, customer traffic analysis in department stores, and taxi trip analysis with origin-destination (OD) data. We further interview domain experts to verify the usability of the prototype.
Abstract An acylative fluorination of two different alkenes is developed, assisted by the interaction of silver catalyst and Selectflour. Various α‐ketonic acids can be decarboxylated to form acyl ...radicals at 35 °C, sequentially add to the electron‐deficient and electron‐ rich alkenes to provide the benzyl fluorinated compounds containing diversified functional groups.
Phosphoenolpyruvate carboxykinase (PEPCK or PCK) catalyzes the first rate-limiting step in hepatic gluconeogenesis pathway to maintain blood glucose levels. Mammalian cells express two PCK genes, ...encoding for a cytoplasmic (PCPEK-C or PCK1) and a mitochondrial (PEPCK-M or PCK2) isoforms, respectively. Increased expressions of both PCK genes are found in cancer of several organs, including colon, lung, and skin, and linked to increased anabolic metabolism and cell proliferation. Here, we report that the expressions of both PCK1 and PCK2 genes are downregulated in primary hepatocellular carcinoma (HCC) and low PCK expression was associated with poor prognosis in patients with HCC. Forced expression of either PCK1 or PCK2 in liver cancer cell lines results in severe apoptosis under the condition of glucose deprivation and suppressed liver tumorigenesis in mice. Mechanistically, we show that the pro-apoptotic effect of PCK1 requires its catalytic activity. We demonstrate that forced PCK1 expression in glucose-starved liver cancer cells induced TCA cataplerosis, leading to energy crisis and oxidative stress. Replenishing TCA intermediate α-ketoglutarate or inhibition of reactive oxygen species production blocked the cell death caused by PCK expression. Taken together, our data reveal that PCK1 is detrimental to malignant hepatocytes and suggest activating PCK1 expression as a potential treatment strategy for patients with HCC.
N−N Atropisomers are a common motif in natural products and represent a significant dimension for exploration in modern pharmaceutical and medicinal chemistry. However, the catalytic atroposelective ...synthesis of such molecules remains challenging, hampering meaningful development. In particular, an enantioselective synthesis of N−N bisindole atropisomers is unprecedented. Herein, the first enantioselective synthesis of N−N bisindole atropisomers via the palladium‐catalyzed de novo construction of one indole skeleton is presented. A wide variety of N−N axially chiral bisindoles were generated in good yields with excellent enantioselectivities via a cascade condensation/N‐arylation reaction. Structurally diverse indole‐pyrrole, indole‐carbazole, and non‐biaryl‐indole atropisomers possessing a chiral N−N axis were accessed using this protocol. Moreover, investigations using density functional theory (DFT) calculations provided insight into the reaction mechanism and enantiocontrol.
An enantioselective synthesis of N−N bisindole atropisomers based on the de novo construction of one indole skeleton is presented. A wide variety of N−N axially chiral bisindoles were obtained in good yields with excellent enantioselectivities. Structurally diverse indole‐pyrrole, indole‐carbazole and non‐biaryl‐indole atropisomers possessing a chiral N−N axis were accessed using this protocol.
Event sequences analysis plays an important role in many application domains such as customer behavior analysis, electronic health record analysis and vehicle fault diagnosis. Real-world event ...sequence data is often noisy and complex with high event cardinality, making it a challenging task to construct concise yet comprehensive overviews for such data. In this paper, we propose a novel visualization technique based on the minimum description length (MDL) principle to construct a coarse-level overview of event sequence data while balancing the information loss in it. The method addresses a fundamental trade-off in visualization design: reducing visual clutter vs. increasing the information content in a visualization. The method enables simultaneous sequence clustering and pattern extraction and is highly tolerant to noises such as missing or additional events in the data. Based on this approach we propose a visual analytics framework with multiple levels-of-detail to facilitate interactive data exploration. We demonstrate the usability and effectiveness of our approach through case studies with two real-world datasets. One dataset showcases a new application domain for event sequence visualization, i.e., fault development path analysis in vehicles for predictive maintenance. We also discuss the strengths and limitations of the proposed method based on user feedback.
PDF
