The GTK+ Drag-And-Drop Mechanism
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In Silico Docking Analysis of CCL28 (CC Motif Chemokine Ligand
F1000Research 2019, 8:313 Last updated: 21 SEP 2021 RESEARCH ARTICLE In silico docking analysis of CCL28 (C-C motif chemokine ligand 28) and astragalin as the potential inhibitor of rheumatoid arthritis [version 1; peer review: 1 approved, 1 approved with reservations] Sadaf Noor, Syeda Tahira Qousain, Syed Aun Muhammad Institute of Molecular Biology and Biotechnology, Bahauddin Zakariya University, Multan, Punjab, 60800, Pakistan v1 First published: 20 Mar 2019, 8:313 Open Peer Review https://doi.org/10.12688/f1000research.18541.1 Latest published: 20 Mar 2019, 8:313 https://doi.org/10.12688/f1000research.18541.1 Reviewer Status Invited Reviewers Abstract Background: Rheumatoid arthritis is an inflammatory and chronic 1 2 disease of the joints affecting 1% of the world’s population. Women are three times more likely to be affected than men. Many drugs are version 1 being used for the treatment of rheumatoid arthritis but they often 20 Mar 2019 report report have severe side effects. C-C motif chemokine ligand 28 (CCL28) recruits leukocytes and other proinflammatory factors to the site of 1. Ihsan Ul Haq, Quaid-i-Azam University, joint inflammation. The purpose of the present research is the computational evaluation of astragalin, a natural flavonoid extracted Islamabad, Pakistan from black tea, as an inhibitor of CCL28 by in silico docking. 2. Sagarika Biswas, Institute of Genomics and Methods: The three-dimensional structure of CCL28 to act as a molecular target was obtained from the Protein Data Bank (PDB ID: Integrative Biology, New Delhi, India 6CWS). The quality of the CCL28 structure was assessed using Phyre2 and Molecular Operating Environment (MOE) software was used for Any reports and responses or comments on the binding affinity analysis. -
Google Docs Reference
Google Drive Quick Reference Guide Google Drive Homepage Overview 1. Search Drive: Enter your search text and click on the Search icon to find your files. Select the folder first if you would like to search within a specific folder. 2. New & Upload: Click New and choose from the list of documents, presentations, etc. that you can create or upload using Google Drive. 3. My Drive: The section of Google Drive on the web that syncs to your computer. Any time you modify a file or folder in My Drive, these changes will be mirrored in the local version of your Google Drive folder. 4. Navigation Panel: Links to your starred items and trash. Shared with me lets you view files, folders, and Google Docs that others have shared with you. 5. Download Google Drive (under settings in new drive): Download and install the Google Drive Client for your Mac/PC to sync files from your computer to Google Drive on the web. (won’t work on SBCSC computers) 6. Details Pane: Here you can see a preview of the select- ed file, the time of your last view, when it was last modi- fied, and by whom. You can also view and update the file’s sharing settings and organize it into folders. (right click (i) view details-or (i) on top menu top open pane) Upload Files and Folders into Google Drive You can upload and convert the following file types into Google Drive for online editing and sharing. • Documents: Microsoft Word, OpenOffice, StarOffice, RTF (.rtf), HTML, or plain text (.txt). -
IP Log for Eclipse.Platform Release 4.0, July 2010 Licenses
IP Log for eclipse.platform Release 4.0, July 2010 Licenses • Eclipse Public License v1.0 Third-Party Code CQ Third-Party Code License Use ICU4J (core and extended ICU4J License (X License, 1065 function) and ICU4J MIT Style) Replacement plug-in Version: 3.6 ICU4J License (X License, 1116 ICU4J Version: 3.4.5.20061213 MIT Style) 1153 JSch 0.1.31 Version: 0.1.31 New BSD license Apache Lucene Version: 1.9.1 243 (Core+Contrib Analyzers Apache License, 2.0 Analysis Src) 257 APT Version: 1 New BSD license Mozilla Public License 1.1 (MPL), MIT Style with No 262 Cairo Version: 1.0.2 Endorsement Clause, Historical Permissive Notice & Disclaimer ICU4J License (X License, 280 ICU4J Version: 3.4 MIT Style) ICU4J License (X License, 281 ICU4J Version: 3.4.3 MIT Style) 293 jsch Version: 0.1.28 New BSD license 308 PNG unload Version: 1 MIT license 1232 Apache Ant Version: 1.7.0 Apache License, 2.0 ICU4J and ICU4J Replacement ICU4J License (X License, 1367 Version: 3.6.1 MIT Style) Olsen time zone data Version: 1368 Public Domain 2007e Work derived from IJG JPEG 1596 IJG License Version: Release 6b,337 unmodified 1826 JSch 0.1.35 New BSD license source & binary ICU4J and ICU4J replacement MIT License with "no unmodified 1919 Version: 3.8.1 edorsement" clause source & binary unmodified 2014 jsch Version: 0.1.37 New BSD license source & binary XHTML DTDs Version: unmodified 2044 W3C Document License Versions 1.0 and 1.1 (PB CQ331) source org.apache.ant Version: 1.6.5 2404 (ATO CQ1013) (using Orbit Apache License, 2.0 CQ2209) org.apache.lucene Version: 1.4.3 2405 (Core Source Only) (ATO Apache License, 2.0 CQ1014) (using Orbit CQ2210) Junit Version: 3.8.2 (ATO 2406 Common Public License 1.0 CQ299) (using Orbit CQ2206) Historical support for Java SSH modified 2410 Applet + Blowfish Version - v. -
The GNOME Desktop Environment
The GNOME desktop environment Miguel de Icaza ([email protected]) Instituto de Ciencias Nucleares, UNAM Elliot Lee ([email protected]) Federico Mena ([email protected]) Instituto de Ciencias Nucleares, UNAM Tom Tromey ([email protected]) April 27, 1998 Abstract We present an overview of the free GNU Network Object Model Environment (GNOME). GNOME is a suite of X11 GUI applications that provides joy to users and hackers alike. It has been designed for extensibility and automation by using CORBA and scripting languages throughout the code. GNOME is licensed under the terms of the GNU GPL and the GNU LGPL and has been developed on the Internet by a loosely-coupled team of programmers. 1 Motivation Free operating systems1 are excellent at providing server-class services, and so are often the ideal choice for a server machine. However, the lack of a consistent user interface and of consumer-targeted applications has prevented free operating systems from reaching the vast majority of users — the desktop users. As such, the benefits of free software have only been enjoyed by the technically savvy computer user community. Most users are still locked into proprietary solutions for their desktop environments. By using GNOME, free operating systems will have a complete, user-friendly desktop which will provide users with powerful and easy-to-use graphical applications. Many people have suggested that the cause for the lack of free user-oriented appli- cations is that these do not provide enough excitement to hackers, as opposed to system- level programming. Since most of the GNOME code had to be written by hackers, we kept them happy: the magic recipe here is to design GNOME around an adrenaline response by trying to use exciting models and ideas in the applications. -
SEED™ Assessment Guide for Family Planning Programming
SEED™ Assessment Guide for Family Planning Programming SEED™ Assessment Guide for Family Planning Programming © 2011 EngenderHealth EngenderHealth 440 Ninth Avenue New York, NY 10001 U.S.A. Telephone: 212-561-8000 Fax: 212-561-8067 e-mail: [email protected] www.engenderhealth.org This publication was made possible through support provided by the F.M. Kirby Foundation. The opinions expressed herein are those of the publisher and do not necessarily reflect the views of the foundation. Cover design, graphic design, and typesetting: Weronika Murray and Tor de Vries Printing: Automated Graphic Systems ISBN 978-1-885063-97-7 Printed in the United States of America. Printed on recycled paper. Suggested citation: EngenderHealth. 2011. The SEED assessment guide for family planning programming. New York. Photo credits: M. Tuschman/EngenderHealth, A. Fiorente/EngenderHealth, C. Svingen/EngenderHealth. ii ContEntS Acknowledgments .................................................................................................................................. iv Acronyms and Abbreviations ................................................................................................................... v Introduction ................................................................................................................................. 2 EngenderHealth’s SEED Programming Model .......................................................................................... 3 How to Use This Assessment Guide........................................................................................................ -
A Highly Interactive Expert System for Outside Plant Engineering
From: IAAI-93 Proceedings. Copyright © 1993, AAAI (www.aaai.org). All rights reserved. OPERA: A Highly Interactive Expert System for Outside Plant Engineering Gary Lazarus, Lien ‘Ihn and Marty Baade Expert Systems Laboratory NYNEX Science & Technology 500 Westchester Avenue White Plains, NY 10604 [email protected] Abstract system that contains more engineering expertise than OPERA is an expert system developed at the Expert any single engineer in the telephone companies. Systems Laboratory at NYNEX Science & Technology to As is the case in most high technology fields, assist outside plant telecommunications engineers in the outside plant engineers routinely see new products, or planning and implementation of sophisticated electronic refinements and enhancements to existing ones. The equipment. The engineer communicates with the system via underlying first order principles of engineering are intelligent documents that are schematic in their design and complex and not necessarily fully understood by all dynamic in their operation to facilitate the conveyance of necessary and sufficient information. Expertise from the top engineers charged with the responsibility of turning up experts in the company was culled and built into the system working systems. Engineers who immerse themselves in to create an expert system that surpasses the engineering the latest technology can perform very well. But, the knowledge of any single engineer in the company. The effort required to maintain that ability is significant. domain and project objectives are discussed, the system OPERA (Outside Plant Engineering and Resource architecture and development, testing, deployment and Administration), therefore, must provide a reasoning maintenance issues are presented and the use of artificial mechanism that emulates the best engineers and be intelligence techniques is justified. -
Drag-And-Guess: Drag-And-Drop with Prediction
Drag-and-Guess: Drag-and-Drop with Prediction Takeshi Nishida Takeo Igarashi Department of Computer Science, Department of Computer Science, The University of Tokyo The University of Tokyo / PREST JST [email protected] [email protected] ABSTRACT is presented to the user as an animation; the user can start the Drag-and-guess is an extension of drag-and-drop that uses next operation before the animation terminates. predictions. As the user starts dragging an object, the system predicts the drop target and presents the result. If the target is hidden in a closed folder or beneath other windows, the system makes it temporarily visible to free the user from manual preparation. The user can accept the prediction by releasing the mouse button and the object flies to the target, or reject it by continuing the dragging operation, thereby switching to traditional drag-and-drop seamlessly. Keywords: Drag-and-drop, Drag-and-guess, Prediction INTRODUCTION We demonstrate an extension of traditional drag-and-drop Figure 1 Drag-and-guess in action. that uses predictions, called drag-and-guess (DnG) (Figure 1). As the user starts dragging an object, the system predicts the drop target and responds by revealing the predicted result. If the target is not visible (e.g., hidden in nested hierarchical folders or outside the area visible on the screen), -The user starts dragging the system automatically makes the target location -The system checks the situation temporarily visible. If the prediction is correct, the user can System : confident System : unconfident accept it by releasing the mouse button, when the object Task : difficult Task : easy automatically drops on the target. -
Seed Modules Reference Manual
Seed Modules Reference Manual May 20, 2009 Seed Modules Reference Manual ii Contents 1 readline module. 1 1.1 API Reference . .1 1.2 Examples . .1 2 SQLite module. 3 2.1 API Reference . .3 2.2 Examples . .3 3 GtkBuilder module. 5 3.1 API Reference . .5 3.2 Examples . .5 4 Sandbox module. 7 4.1 API Reference . .7 4.2 Examples . .7 iii Chapter 1 readline module. Robert Carr 1.1 API Reference The readline module allows for basic usage of the GNU readline library, in Seed. More advanced fea- tures may be added a a later time. In order to use the readline module it must be first imported. readline= imports.readline; readline.readline (prompt) Prompts for one line of input on standard input using prompt as the prompt. prompt A string to use as the readline prompt Returns A string entered on standard input. readline.bind (key, function) Binds key to function causing the function to be invokved when- ever key is pressed key A string specifying the key to bind function The function to invoke when key is pressed readline.done () Indicates that readline should finish the current line, and return from readline- .readline. Can be used in callbacks to implement features like multiline editing readline.buffer() Retrieve the current readline buffer Returns The current readline buffer readline.insert (string) Inserts string in to the current readline buffer string The string to insert 1.2 Examples Below are several examples of using the Seed readline module. For additional resources, consult the examples/ folder of the Seed source 1 CHAPTER 1. -
Pick-And-Drop: a Direct Manipulation Technique for Multiple Computer
Pick-and-Drop: A Direct Manipulation Technique for Multiple Computer Environments tun ekimoto ony gomputer iene v ortory snF QEIREIQ rigshigotndD hingwEkuD okyo IRI tpn CVIEQESRRUERQVH rekimotodslFsonyFoFjp httpXGGwwwFslFsonyFoFjpGp ersonGrekimotoFhtml ABSTRACT This paper proposes a new field of user interfaces called multi-computer direct manipulation and presents a pen-based direct manipulation technique that can be used for data transfer between different computers as well as within the same computer. The proposed Pick-and-Drop allows a user to pick up an object on a display and drop it on another display as if he/she were manipulating a physical object. Even though the pen itself does not have storage capabilities, a combination of Pen-ID and the pen manager on the network provides the illusion that the pen can physically pick up and move a computer object. Based on this concept, we have built several experimental applications using palm-sized, desk- top, and wall-sized pen computers. We also considered the importance of physical artifacts in designing user interfaces in a future computing environment. KEYWORDS: direct manipulation, graphical user inter- Figure 1: A typical ªmouse jungleº in a multi-computer faces, input devices, stylus interfaces, pen interfaces, drag- environment and-drop, multi-computer user interfaces, ubiquitous com- puting, computer augmented environments writing a program on a UNIX while editing a diagram on a INTRODUCTION Mac). In a ubiquitous computing (UbiComp) environment [18], we no longer use a single computer to perform tasks. Instead, However, using multiple computers without considering the many of our daily activities including discussion, documen- user-interface introduces several problems. -
Testing X/Motif Applications
TTeessttiinngg XX//MMoottiiff AApppplliiccaattiioonnss Achieving Quality Goals Through Automated GUI Testing Integrated Computer Solutions Incorporated The User Interface Company™ Phone: 617.621.0060 Email: [email protected] www.ics.com Automated Testing of X-Window Applications Choosing the Ideal Tool for Automated GUI Testing Table of Contents Overview............................................................................................................................. 3 The importance of GUI testing ........................................................................................... 3 Exploratory testing.......................................................................................................... 3 Regression testing ........................................................................................................... 3 Boundary testing ............................................................................................................. 4 Stress testing ................................................................................................................... 4 GUI Testing Tools .............................................................................................................. 4 Developing initial GUI tests ............................................................................................... 5 Using a GUI test tool during exploration............................................................................ 6 Basic scripting.................................................................................................................... -
Decwindows Motif for Openvms Installation Guide
VSI OpenVMS DECwindows Motif for OpenVMS Installation Guide Document Number: DO-DDWINS-01A Publication Date: October 2019 Revision Update Information: This is a new manual. Operating System and Version: VSI OpenVMS Integrity Version 8.4-1H1 VSI OpenVMS Alpha Version 8.4-2L1 Software Version: DECwindows Motif for OpenVMS Version 1.7F VMS Software, Inc., (VSI) Bolton, Massachusetts, USA DECwindows Motif for OpenVMS Installation Guide Copyright © 2019 VMS Software, Inc. (VSI), Bolton, Massachusetts, USA Legal Notice Confidential computer software. Valid license from VSI required for possession, use or copying. Consistent with FAR 12.211 and 12.212, Commercial Computer Software, Computer Software Documentation, and Technical Data for Commercial Items are licensed to the U.S. Government under vendor's standard commercial license. The information contained herein is subject to change without notice. The only warranties for VSI products and services are set forth in the express warranty statements accompanying such products and services. Nothing herein should be construed as constituting an additional warranty. VSI shall not be liable for technical or editorial errors or omissions contained herein. HPE, HPE Integrity, HPE Alpha, and HPE Proliant are trademarks or registered trademarks of Hewlett Packard Enterprise. The VSI OpenVMS documentation set is available on DVD. ii DECwindows Motif for OpenVMS Installation Guide Preface .................................................................................................................................... -
Skyfire: Data-Driven Seed Generation for Fuzzing
Skyfire: Data-Driven Seed Generation for Fuzzing Junjie Wang, Bihuan Chen†, Lei Wei, and Yang Liu Nanyang Technological University, Singapore {wang1043, bhchen, l.wei, yangliu}@ntu.edu.sg †Corresponding Author Abstract—Programs that take highly-structured files as inputs Syntax Semantic normally process inputs in stages: syntax parsing, semantic check- Features Rules ing, and application execution. Deep bugs are often hidden in the <?xml version="1.0" application execution stage, and it is non-trivial to automatically encoding="utf- pass pass pass 8"?><xsl:stylesheet version="1.0" Syntax Semantic Application xmlns:xsl="http://www.w3 .org/1999/XSL/Transform" generate test inputs to trigger them. Mutation-based fuzzing gen- ><xsl:output xsl:use- √ attribute- Parsing Checking Execution erates test inputs by modifying well-formed seed inputs randomly sets=""/></xsl:stylesheet> Parsing Semantic or heuristically. Most inputs are rejected at the early syntax pars- Inputs Crashes ing stage. Differently, generation-based fuzzing generates inputs Errors Violations from a specification (e.g., grammar). They can quickly carry the ! ! X fuzzing beyond the syntax parsing stage. However, most inputs fail to pass the semantic checking (e.g., violating semantic rules), Fig. 1: Stages of Processing Highly-Structured Inputs which restricts their capability of discovering deep bugs. In this paper, we propose a novel data-driven seed generation approach, named Skyfire, which leverages the knowledge in the analysis [8, 9] that identifies those interesting bytes to mutate, vast amount of existing samples to generate well-distributed seed symbolic execution [10, 11, 12] that relies on constraint solving inputs for fuzzing programs that process highly-structured inputs.