Target highlights in CASP14 : Analysis of models by structure providers

Abstract The biological and functional significance of selected CASP14 targets are described by the authors of the structures. The authors highlight the most relevant features of the target proteins and discuss how well these features were reproduced in the respective submitted predictions. The overall ability to predict three-dimensional structures of proteins has improved remarkably in CASP14, and many difficult targets were modelled with impressive accuracy. For the first time in the history of CASP, the experimentalists not only highlighted that computational models can accurately reproduce the most critical structural features observed in their targets, but also envisaged that models could serve as a guidance for further studies of biologically-relevant properties of proteins. This article is protected by copyright. All rights reserved.Peer reviewe

Robust kernel distance multivariate control chart using support vector principles

It is important to monitor manufacturing processes in order to improve product quality and reduce production cost. Statistical Process Control (SPC) is the most commonly used method for process monitoring, in particular making distinctions between variations attributed to normal process variability to those caused by ‘special causes’. Most SPC and multivariate SPC (MSPC) methods are parametric in that they make assumptions about the distributional properties and autocorrelation structure of in-control process parameters, and, if satisfied, are effective in managing false alarms/-positives and false- negatives. However, when processes do not satisfy these assumptions, the effectiveness of SPC methods is compromised. Several non-parametric control charts based on sequential ranks of data depth measures have been proposed in the literature, but their development and implementation have been rather slow in industrial process control. Several non-parametric control charts based on machine learning principles have also been proposed in the literature to overcome some of these limitations. However, unlike conventional SPC methods, these non-parametric methods require event data from each out-of-control process state for effective model building. The paper presents a new non-parametric multivariate control chart based on kernel distance that overcomes these limitations by employing the notion of one-class classification based on support vector principles. The chart is non-parametric in that it makes no assumptions regarding the data probability density and only requires ‘normal’ or in-control data for effective representation of an in-control process. It does, however, make an explicit provision to incorporate any available data from out-of-control process states. Experimental evaluation on a variety of benchmarking datasets suggests that the proposed chart is effective for process mo

Design and synthesis of polycyclic indoles under green conditions via Fischer indolization

A simple and useful synthetic route to aza-polyquinane derivatives involving Fischer indolization under green conditions has been demonstrated. Selenium dioxide is found to be useful for oxidizing some of these indole derivatives

Exploiting location and contextual information to develop a comprehensive framework for proactive handover in heterogeneous environments

The development and deployment of several wireless and cellular networks mean that users will demand to be always connected as they move around. Mobile nodes will therefore have several interfaces and connections will be seamlessly switched among available networks using vertical handover techniques. Proactive handover mechanisms can be combined with the deployment of a number of location-based systems that provide location information to a very high degree of accuracy in different contexts. Furthermore, this new environment will also allow contextual information such as user profiles as well as the availability of local services to be combined to provide optimal communications for mobile users. The goal of this paper is therefore to explore the development of a comprehensive framework for achieving optimal communication in heterogeneous wireless environments using location and contextual information to provide efficient handover mechanisms. Using location-based techniques, it is possible to demonstrate that the Time Before Vertical Handover as well as the Network Dwell Time can be accurately estimated. These techniques are dependent on accurately estimating the handover radius. This paper investigates how location and context awareness can be used to estimate the best handover radius. The paper also explores how such techniques may be integrated into the Y-Comm architecture which is being used to explore the development of future mobile networks. Finally, the paper highlights the use of ontological techniques as a mechanism for specifying and prototyping such systems

Bulk-Phase Ion Conduction in Cocrystalline LiCl·<i>N</i>,<i>N</i>‑Dimethylformamide: A New Paradigm for Solid Electrolytes Based upon the Pearson Hard–Soft Acid–Base Concept

Bulk-Phase Ion Conduction in Cocrystalline LiCl·<i>N</i>,<i>N</i>‑Dimethylformamide: A New Paradigm for Solid Electrolytes Based upon the Pearson Hard–Soft Acid–Base Concep

Bulk-Phase Ion Conduction in Cocrystalline LiCl·<i>N</i>,<i>N</i>‑Dimethylformamide: A New Paradigm for Solid Electrolytes Based upon the Pearson Hard–Soft Acid–Base Concept

Bulk-Phase Ion Conduction in Cocrystalline LiCl·<i>N</i>,<i>N</i>‑Dimethylformamide: A New Paradigm for Solid Electrolytes Based upon the Pearson Hard–Soft Acid–Base Concep

Design, docking, MD simulation and in-silco ADMET prediction studies of novel indole-based benzamides targeting estrogen receptor alfa positive for effective breast cancer therapy

Breast cancer is one of the most common malignancies in women, afflicting millions of lives each year. Our current study suggests that the development of the most promising 7-substituted -1-(4-(piperidine-1-yl methoxy)benzyl)-1H-indole-3-carboxamide derivatives results in potent anticancer agents through in-silico investigations. The molecular docking was performed against estrogen receptor alpha (ER-α) positive (PDB ID: 3UUD) of breast cancer cells to anticipate the binding modes of the designed compounds and the likely mode of action. The interactions between the ligands and amino acid residues were thoroughly elucidated. The stability of the docked protein-ligand complexes was further confirmed by 100 ns molecular simulations methods. From in-silico studies, indole-based benzamides exhibited satisfactory physicochemical, drug-likeness and toxicity properties. To conclude, the most promising substituted benzamide analogs on the indole ring could serve as a possible modulator against ER-α positive breast cancer

The Role of the Intertropical Discontinuity Region and the Heat Low in Dust Emission and Transport Over the Thar Desert, India: A Premonsoon Case Study

International audienceA severe dust storm occurred over north India during 12–16 June 2018 is analyzed using satellite observations, reanalysis, ground-based measurements, and model (Meso-NH) simulations focusing on the dynamic processes that caused the dust-storm generation, uplift, and propagation as well as its impacts on air quality. The initial dust emission was triggered by strong near-surface southwesterlies (~15–20 m s−1) associated with the monsoon flow advancing northward, in response to the deepening of the thermal low over the Thar desert. The convergence between the northwesterlies and the monsoon flow along the Intertropical Discontinuity region caused high dust accumulation over northwest India in an area of weak winds. Convective mixing during daytime favors the vertical transport of dust to higher altitudes above the monsoon flow, but the towering Himalayas and the associated return northerly flow aloft play a blocking role leading to dust accumulation at heights between 1 and 3 km over northwest India. The prevailed northwesterlies in the middle troposphere favor the eastward transport of the dust plumes along the Ganges valley, helping to evacuate the dust toward east India. Based on Meso-NH model simulations, the dust storm was associated with dust loads higher than 30 gm−2 and AODs higher than 3, in agreement with MODIS observations. The impact of the dust storm on the spatial-temporal evolution of the PM10 and PM2.5 mass concentrations is studied using data from 23 air-quality stations over northern India, indicating daily PM10 peaks reaching at ~900 μg m−3, implying a severe degradation of air quality