2,360 research outputs found
Tandem ring-closing metathesis reaction with a ruthenium catalyst containing a N-heterocyclic ligand
The highly active catalyst 2 was used in tandem RCM to make molecules with various ring systems containing α,β-unsaturated carbonyl compounds
Ring Expansion via Olefin Metathesis
Various macrocycles were prepared in one step by a novel ring-expansion method using olefin metathesis
Olefin Metathesis Involving Ruthenium Enoic Carbene Complexes
Olefin metathesis has become a valuable reaction in organic synthesis, as has been demonstrated by its frequent use as the key bond constructions for total syntheses of many natural products. With the recent discovery of highly active catalyst 1, trisubstituted and functionalized alkenes have been synthesized efficiently by cross-metathesis (CM), further expanding the substrate scope for this reaction. With these successes in hand, unprecedented metathesis reactions were explored. There have been no previous reports of the dimerization of α,β-unsaturated carbonyl compounds by a metathesis mechanism. Molybdenum- and tungsten-based catalysts form metallocyclobutane with acrylates, but they are inactive due to carbonyl oxygen chelation. Our group reported the synthesis of ester carbene 4 by a nonmetathesis route and showed that 4 was extremely reactive. In fact, ester carbene 4 was the first carbene to ring-open cyclohexene but did not react in a catalytic fashion.4 The nontrivial synthesis, lack of stability, and the ineffective catalytic activity of ester carbene 4 has limited its uses in organic synthesis
IDENTIFYING CRITICAL KINEMATIC PARAMETERS FOR BETTER GOLF PUTTING
In modern golf competition, putting is one of the crucial parts of the game. It has been reported that putting accounts for about 40% of all golf shot played in tournaments (Gwyn & Patch, 1993). Wiren (1992) also indicated that, on average, putting constitutes 38% of all golf strokes in competition and improving putting skills is th e fastest way to lower the score. However, it is also true that most recreational golfers neglect the putting and seldom practice it hard. Despite this revealing statistics and the obvious
importance of competent putting, much of the pedagogical literature is based on the observations and anecdotal evidence provided by top players and coaches (Paradisis & Rees, 2004). Therefore, the purpose of this study was to identify critical kinematic parameters of a putt by comparing putts performed by elite and novice golifers, and nongolfers. The findings might provide valuable information for improving putting performance
Ru-Catalyzed, cis-Selective Living Ring-Opening Metathesis Polymerization of Various Monomers, Including a Dendronized Macromonomer, and Implications to Enhanced Shear Stability
An unsaturated polymer’s cis/trans-olefin content has a significant influence on its properties. For polymers obtained by ring-opening metathesis polymerization (ROMP), the cis/trans-olefin content can be tuned by using specific catalysts. However, cis-selective ROMP has suffered from narrow monomer scope and lack of control over the polymerization (giving polymers with broad molecular weight distributions and prohibiting the synthesis of block copolymers). Herein, we report the versatile cis-selective controlled living ROMP of various endo-tricyclo[4.2.2.0^(2,5)]deca-3,9-diene and various norbornene derivatives using a fast-initiating dithiolate-chelated Ru catalyst. Polymers with cis-olefin content as high as 99% could be obtained with high molecular weight (up to M_n of 105.1 kDa) and narrow dispersity (<1.4). The living nature of the polymerization was also exploited to prepare block copolymers with high cis-olefin content for the first time. Furthermore, owing to the successful control over the stereochemistry and narrow dispersity, we could compare cis- and trans-rich polynorbornene and found the former to have enhanced resistance to shear degradation
Automatic Network Adaptation for Ultra-Low Uniform-Precision Quantization
Uniform-precision neural network quantization has gained popularity since it
simplifies densely packed arithmetic unit for high computing capability.
However, it ignores heterogeneous sensitivity to the impact of quantization
errors across the layers, resulting in sub-optimal inference accuracy. This
work proposes a novel neural architecture search called neural channel
expansion that adjusts the network structure to alleviate accuracy degradation
from ultra-low uniform-precision quantization. The proposed method selectively
expands channels for the quantization sensitive layers while satisfying
hardware constraints (e.g., FLOPs, PARAMs). Based on in-depth analysis and
experiments, we demonstrate that the proposed method can adapt several popular
networks channels to achieve superior 2-bit quantization accuracy on CIFAR10
and ImageNet. In particular, we achieve the best-to-date Top-1/Top-5 accuracy
for 2-bit ResNet50 with smaller FLOPs and the parameter size.Comment: Accepted as a full paper by the TinyML Research Symposium 202
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