Observations of Shock Waves in Cloud Cavitation

This paper describes an investigation of the dynamics and acoustics of cloud cavitation, the structures which are often formed by the periodic breakup and collapse of a sheet or vortex cavity. This form of cavitation frequently causes severe noise and damage, though the precise mechanism responsible for the enhancement of these adverse effects is not fully understood. In this paper, we investigate the large impulsive surface pressures generated by this type of cavitation and correlate these with the images from high-speed motion pictures. This reveals that several types of propagating structures (shock waves) are formed in a collapsing cloud and dictate the dynamics and acoustics of collapse. One type of shock wave structure is associated with the coherent collapse of a well-defined and separate cloud when it is convected into a region of higher pressure. This type of global structure causes the largest impulsive pressures and radiated noise. But two other types of structure, termed 'crescent-shaped regions' and 'leading-edge structures' occur during the less-coherent collapse of clouds. These local events are smaller and therefore produce less radiated noise but the interior pressure pulse magnitudes are almost as large as those produced by the global events. The ubiquity and severity of these propagating shock wave structures provides a new perspective on the mechanisms reponsible for noise and damage in cavitating flows involving clouds of bubbles. It would appear that shock wave dynamics rather than the collapse dynamics of single bubbles determine the damage and noise in many cavitating flows

A Concise Total Synthesis of (--)-Maoecrystal Z

The first total synthesis of (--)-maoecrystal Z is described. The key steps of the synthesis include a diastereoselective Ti^(III)-mediated reductive epoxide coupling reaction and a diastereoselective Sm^(II)-mediated reductive cascade cyclization reaction. These transformations enabled the preparation of (--)-maoecrystal Z in only 12 steps from (--)-γ-cyclogeraniol

Relationship between hyperuricemia with deposition and sexual dysfunction in males and females

Purpose The association between gout, the most common crystal arthropathy, and sexual dysfunctions has often been investigated by studies in the last decades. Despite the presence of shared risk factors and comorbidities and the possible effects on sexual health of long-term gout complications, awareness of this association is severely lacking and the pathogenetic mechanisms have only partially been identified. In the present review, we aimed to investigate the current evidence regarding the potential mechanisms linking sexual dysfunctions and gout. Methods A comprehensive literature search within PubMed was performed to provide a summary of currently available evidence regarding the association between gout and sexual dysfunctions. Results Gout and sexual dysfunctions share several risk factors, including diabesity, chronic kidney disease, hypertension, metabolic syndrome, and peripheral vascular disease. Gout flares triggered by intense inflammatory responses feature severe pain and disability, resulting in worse sexual function, and some, but not all, treatments can also impair sexual health. Long-term gout complications can result in persistent pain and disability due to joint deformity, fractures, or nerve compression, with negative bearing on sexual function. The presence of low-grade inflammation impairs both sex steroids synthesis and endothelial function, further advancing sexual dysfunctions. The psychological burden of gout is another issue negatively affecting sexual health. Conclusions According to currently available evidence, several biological and psychological mechanisms link sexual dysfunctions and gout. Addressing risk factors and providing adequate treatment could potentially have beneficial effects on both conditions. Appropriate clinical evaluation and multidisciplinary approach are recommended to improve patient care

Shock Waves in Cloud Cavitation

Thie paper described experimental and computational investigations of the dynamics of clouds of cavitation bubbles. Recent studies have confirmed that the interactions between bubbles as they are manifest in the dynamics of bubble clouds lead to generation of very large impulsive pressures which, in turn, cause substantial enhancement of the radiated noise and the material damage which results from this form of cavitation. The experimental program focuses on cloud cavitation formed on the suction surface of a hydrofoil, both static and oscillating. Piezo-electric transducers mounted at a series of locations on the suction surface measured very large positive pressure pulses with amplitudesx of the order of tens of atmospheres and with durations of the order of tenths of milliseconds. Two distinct types of pressure pulse were identified from high-speed films: "local pulses" which are registered by individual transducers and appear to be associated with the propagation of localized bubbly shocks and "global pulses" which result from larger scale, coherent collapses of bubble clouds. The experiments investigate the effects of reduced frequency, cavitation number and tunnel velocity on the magnitude of these pressure pulses. The computational component continues the earlier work of Wang and Brennen (1, 2), which presented numerical solutions of the growth and collapse of a spherical cloud of bubbles. This confirmed the idea put forward by Morch and his co-workers who speculated that collapse of the cloud involved the formation of a bubbly shock wave on the surface of the cloud and that inward propagation and geometric focussing of this shock would lead to very large localized pressure pulses. Here we review how the radiated acoustic pulses depend on the governing parameters such as the bubble population density, the cavitation number and the ratio of the bubble size to the cloud size. Understanding such bubbly flow and shock wave processes is important because these flow structures propagate the noise and produce the impulsive loads on nearby solid surfaces in a cavitating flow. How these shocks are formed and propagate in the much more complex cloud geometry associated with cavitating foils, propeller or pump blades is not presently clear. However, by combining the computational and experimental observations, we suggest some specific mechanisms which may be active in the dynamics and acoustics of these more complex flows

Synthesis and Biological Evaluation of Pyrroloindolines as Positive Allosteric Modulators of the α1β2γ2 GABA_A Receptor

γ-Aminobutyric acid type A (GABA_A) receptors are key mediators of central inhibitory neurotransmission and have been implicated in several disorders of the central nervous system. Some positive allosteric modulators (PAMs) of this receptor provide great therapeutic benefits to patients. However, adverse effects remain a challenge. Selective targeting of GABA_A receptors could mitigate this problem. Here, we describe the synthesis and functional evaluation of a novel series of pyrroloin-dolines that display significant modulation of the GABA_A receptor, acting as PAMs. We found that halogen incorporation at the C5 position greatly increased the PAM potency relative to the parent ligand, while substitutions at other positions generally decreased potency. Mutagenesis studies suggest that the binding site lies at the top of the transmembrane domain

Multilabel Classification Models for the Prediction of Cross-Coupling Reaction Conditions

Machine-learned ranking models have been developed for the prediction of substrate-specific cross-coupling reaction conditions. Data sets of published reactions were curated for Suzuki, Negishi, and C–N couplings, as well as Pauson–Khand reactions. String, descriptor, and graph encodings were tested as input representations, and models were trained to predict the set of conditions used in a reaction as a binary vector. Unique reagent dictionaries categorized by expert-crafted reaction roles were constructed for each data set, leading to context-aware predictions. We find that relational graph convolutional networks and gradient-boosting machines are very effective for this learning task, and we disclose a novel reaction-level graph attention operation in the top-performing model

Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions

We present a systematic investigation using graph neural networks (GNNs) to model organic chemical reactions. To do so, we prepared a dataset collection of four ubiquitous reactions from the organic chemistry literature. We evaluate seven different GNN architectures for classification tasks pertaining to the identification of experimental reagents and conditions. We find that models are able to identify specific graph features that affect reaction conditions and lead to accurate predictions. The results herein show great promise in advancing molecular machine learning

Graph Neural Networks for the Prediction of Substrate-Specific Organic Reaction Conditions

We present a systematic investigation using graph neural networks (GNNs) to model organic chemical reactions. To do so, we prepared a dataset collection of four ubiquitous reactions from the organic chemistry literature. We evaluate seven different GNN architectures for classification tasks pertaining to the identification of experimental reagents and conditions. We find that models are able to identify specific graph features that affect reaction conditions and lead to accurate predictions. The results herein show great promise in advancing molecular machine learning.Comment: 23 pages, 10 tables, 13 figures, to appear in the ICML 2020 Workshop on Graph Representation Learning and Beyond (GRLB