What a relief! In 1955 the principle of strain release was put forward to explain the differing reactivity of axial and equitorial alcohols during oxidation. Our findings suggest that this same rationale may account for the differing rates of activation between axial and equitorial C-H bonds in C-H activation processes. In conjunction with steric and electronic considerations, strain-release can be used to qualitatively predict relative rates and site specificity of C-H activation in complex settings. Keywords natural products; C-H functionalization; conformational analysisThe field of C-H activation and the logic that underlies its use in complex molecule synthesis are developing at a rapid pace.[1] This is due, in part, to the great potential that such transformations could have on the various "economies" of synthesis. total syntheses that utilize one or multiple C-H activation steps, a profound understanding of even the subtlest reactivity trends is needed. In particular, it has been observed on multiple occasions that equatorial C-H bonds react more rapidly than those oriented axially (Figure 1).[4] This curious axial-equatorial rate ratio appears to be independent of the reagent system employed and in some cases can be exploited to achieve site-specific C-H activation.[4c,4f, 5] So far, explanations for these "orphan" observations have remained ambigouous. In this Communication, a reactivity factor that apparently has been ignored thus far in this context is proposed, one that we suspect, besides steric hindrance to reagent approach and C-H bond nucleophilicity,[6] to be co-responsible for the more rapid activation of equatorial vs. axial C-H bonds in these tertiary settings.In 1955, one of us proposed strain release ( Figure 2A) to explain the relative rates of reactions in which an equatorial hydrogen is also removed more rapidly than its axial counterpart, namely, in the oxidation of steroidal secondary alcohols with chromic acid (see Supporting Information for an English translation of this paper).[7] The rate acceleration in these reactions is attributed to a release of strain (1,3-diaxial interactions) in the transition state of going from an sp 3 to an sp 2 carbon. At the time, this work convincingly contradicted and corrected the theory [8] according to which the difference in oxidation rate of axial and equatorial alcohols was due to steric hindrance to proton abstraction by a base. In a later paper, the strain-release hypothesis was corroborated in collaboration with F. A key step in the total synthesis of eudesmane terpenes[5] caused us to revisit this principle, one that has so far mainly been used to explain differences in the rates of alcohol oxidation [7,9a,9b] and solvolysis [10]. As shown in Figure 2B, the power of the Curci (TFDO) oxidation [4c] was vividly demonstrated by the conversion of 1 to 2. Among five tertiary centers present in 1, H 1 was selectively activated, leading the corresponding alcohol 2 in 82% isolated yield on a gram scale. Purely electronic considerations mi...

The Pacific white shrimp Litopenaeus vannamei is a euryhaline penaeid species that shows ontogenetic adaptations to salinity, with its larvae inhabiting oceanic environments and postlarvae and juveniles inhabiting estuaries and lagoons. Ontogenetic adaptations to salinity manifest in L. vannamei through strong hyper-osmoregulatory and hypo-osmoregulatory patterns and an ability to tolerate extremely low salinity levels. To understand this adaptive mechanism to salinity stress, RNA-seq was used to compare the transcriptomic response of L. vannamei to changes in salinity from 30 (control) to 3 practical salinity units (psu) for 8 weeks. In total, 26,034 genes were obtained from the hepatopancreas tissue of L. vannamei using the Illumina HiSeq 2000 system, and 855 genes showed significant changes in expression under salinity stress. Eighteen top Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were significantly involved in physiological responses, particularly in lipid metabolism, including fatty-acid biosynthesis, arachidonic acid metabolism and glycosphingolipid and glycosaminoglycan metabolism. Lipids or fatty acids can reduce osmotic stress in L. vannamei by providing additional energy or changing the membrane structure to allow osmoregulation in relevant organs, such as the gills. Steroid hormone biosynthesis and the phosphonate and phosphinate metabolism pathways were also involved in the adaptation of L. vannamei to low salinity, and the differential expression patterns of 20 randomly selected genes were validated by quantitative real-time PCR (qPCR). This study is the first report on the long-term adaptive transcriptomic response of L. vannamei to low salinity, and the results will further our understanding of the mechanisms underlying osmoregulation in euryhaline crustaceans.

Abstract-In this paper, the problem of multi-view embedding from different visual cues and modalities is considered. We propose a unified solution for subspace learning methods using the Rayleigh quotient, which is extensible for multiple views, supervised learning, and non-linear embeddings. Numerous methods including Canonical Correlation Analysis, Partial Least Square regression and Linear Discriminant Analysis are studied using specific intrinsic and penalty graphs within the same framework. Non-linear extensions based on kernels and (deep) neural networks are derived, achieving better performance than the linear ones. Moreover, a novel Multi-view Modular Discriminant Analysis (MvMDA) is proposed by taking the view difference into consideration. We demonstrate the effectiveness of the proposed multi-view embedding methods on visual object recognition and cross-modal image retrieval, and obtain superior results in both applications compared to related methods.

No abstract

Due to their weak interlayer bonding, van der Waals (vdW) solids are very sensitive to external stimuli such as strain. Experimental studies of strain tuning of thermal properties in vdW solids have not yet been reported. Under ~9% cross-plane compressive strain created by hydrostatic pressure in a diamond anvil cell, we observed an increase of cross-plane thermal conductivity in bulk MoS 2 from 3.5 Wm-1 K-1 to about 25 Wm-1 K-1 , measured with a picosecond transient thermoreflectance technique. First-principles calculations and coherent phonon spectroscopy experiments reveal that this drastic change arises from the strain-enhanced interlayer interaction, heavily modified phonon dispersions, and decrease in phonon lifetimes due to unbundling effect along cross-plane direction. The contribution from the change of electronic thermal conductivity is negligible. Our results suggest possible parallel tuning of structural, thermal and electrical properties of vdW solids with strain in multi-physics devices. Main Text Strain is an effective tool to tune physical properties in a wide range of materials [1-4]. In transition metal dichalcogenides (TMDs), a family of two-dimensional (2D) van der Waals (vdW) solids, strain can alter the interlayer distance, as well as bond strength, length and angle between the transition metal and chalcogen atoms, modifying the interatomic orbital coupling, interlayer wavefunction overlap and valence band splitting [5-7]. Changes in these physical parameters can modulate electronic and phononic properties to a great extent. For example, the electronic band gap and phonon Raman peaks in TMDs have been shown experimentally very sensitive to strain, with an A 1g phonon Raman shift as large as ~5-6 cm-1 /% [8-13]. In traditional mechanical bending/stretching experiments, the 2D materials sit on a flexible substrate and strain is determined

This paper seeks to predict the performance of the side channel pump by considering the influences of different wrapping angles. Firstly, three pump cases 1, 2 and 3 are modeled with wrapping angles 15°, 30° and 45°, respectively. Secondly, different physical parameters comprising exchanged mass flow, pressure and velocity distributions are plotted at the best efficiency point (QBEP) to analyze the internal flow characteristics. Since the flow exchange times depend on the size of the wrapping angle, the size of the wrapping angle has significant effects on the pump head performance. Case 1 with the smallest wrapping angle recorded the largest head improvement at all operating conditions compared to case 2 and case 3. Case 1 at QBEP attained a head coefficient increase of about 9.8% and 38.6% compared to that of case 2 and case 3, respectively. However, the size of the wrapping angle had a slight effect on the pump efficiency; thus, case 1 still predicted a marginal increase in efficiency compared to case 2 and case 3 at all operating conditions. Lastly, the numerical simulations were validated with experimental data after manufacturing pump case 2.

Abstract-Successful fine-grained image classification methods learn subtle details between visually similar (sub-)classes, but the problem becomes significantly more challenging if the details are missing due to low resolution. Encouraged by the recent success of Convolutional Neural Network (CNN) architectures in image classification, we propose a novel resolution-aware deep model which combines convolutional image super-resolution and convolutional fine-grained classification into a single model in an end-to-end manner. Extensive experiments on multiple benchmarks demonstrate that the proposed model consistently performs better than conventional convolutional networks on classifying fine-grained object classes in low-resolution images. The problem of image classification is to categorise images according to their semantic content (e.g. person, plane). Finegrained image classification further divides classes to their "sub-categories" such as the models of cars [1], the species of birds [2], the categories of flowers [3] and the breeds of dogs [4]. Fine-grained categorisation is a difficult task due to small inter-class variance between visually similar subclasses. The problem becomes even more challenging when available images are low-resolution (LR) images where many details are missing as compared to their high-resolution (HR) counterparts.Since the rise of Convolutional Neural Network (CNN) architectures in image classification [5], the accuracy of finegrained image classification has dramatically improved and many CNN-based extensions have been proposed [6] Deng et al. [19] we propose a unique end-to-end deep learning framework that combines CNN super-resolution and CNN fine-grained classification -a resolution-aware Convolutional Neural Network (RACNN) for fine-grained object categorisation in low-resolution images. To our best knowledge, our work is the first end-to-end learning model for low-resolution fine-grained object classification.Our main principle is simple: the higher image resolution, the easier for classification. Our research questions are: Can computational super-resolution recover some of the important details required for fine-grained image classification and can super-resolution improves fine-grained classification and SRbased fine-grained classification can be designed into a supervised end-to-end learning framework, as depicted in Figure 1 illustrating the difference between RACNN and conventional CNN. I. RELATED WORKFine-Grained Image Categorisation -Recent algorithms for discriminating fine-grained classes (such as animal species arXiv:1703.05393v3 [cs.CV]

No abstract