{% extends 'base/base.html' %} {% block content %}
Whether you're craving apple, chocolate, pecan, strawberry or pumpkin pie, we have best pie recipes with tips, photos and videos to help make it right--even the crust!


Home
Listings
Contact
Schedule a Consultation
Name:
Email:
Phone:
Help Needed With:
Buying my First Home
Buying a New Home
Selling my Home
Details About Your Needs:
How Did You Get Here?
Word-of-Mouth
Facebook
Instagram
Pinterest
Twitter
SEND


(This recipe makes more pastry than you will need. The extra can be kept in the fridge for up to a week.)
For the pastry, combine the flour and salt on a work surface add the butter and work the dough with your fingertips until the mixture has a texture like sand or resembles breadcrumbs.
Make a well in the mixture, place the egg yolks and water in the centre and mix using one hand starting from the centre of the well.
Bring the dough together into a smooth ball.
Let it rest in the refrigerator, covered in plastic wrap, for 30 minutes before using. (It will keep in the refrigerator for one week covered in plastic wrap.)
In a heavy-based frying pan, gently fry the squid, celery, onion and garlic in three quarters of the olive oil for 2-3 minutes without colouring the squid.  Cook over a low heat for one hour (the mixture needs to stew together well). Allow to cool and season to taste with salt and freshly ground black pepper.
Combine the paprika with the remaining olive oil and set aside.
Preheat the oven to 180C/350F/Gas 4 and line a baking tray with baking paper.
From the pastry roll out two circles about 20cm/8in wide and about 3mm/1/8 inch thick. Put one piece of pastry on the prepared tray. Spread the squid mixture over the pastry, leaving a 1cm/½in border all around. Glaze the edges with the egg yolk. Cover with the second piece of pastry and seal the two rounds of pastry dough together by pinching the edges, and then roll them inward so they stick together.
Brush the tielle with the paprika oil and bake for 30 minutes.
For the fennel and mint salad, place the sliced fennel and mint leaves in a bowl.
Put the lemon zest and juice in a small glass bowl along with the oil and whisk.
Pour the dressing over the fennel and mint and mix together.
To serve, place the tielle sétoise on a serving board and pile the salad next to it.


Guide¶
1. Data collection and documentation¶
1.1 What data will you collect, observe, generate or re-use?¶
SNSF [SNSF2017]
Questions you might want to consider:
- What type, format and volume of data will you collect, observe, generate or reuse?
- Which existing data (yours or third-party) will you reuse?
Briefly describe the data you will collect, observe or generate. Also mention any existing data that will be (re)used. The descriptions should include the type, format and content of each dataset. Furthermore, provide an estimation of the volume of the generated datasets.
(This relates to the FAIR Data Principles F2, I3, R1 & R1.2)
Instructions¶
- Identify each dataset
- (or collection of datasets that have the same characteristics with respect to content-type, source, format, etc.) and consider to introduce an abbreviation for each one.
- For pre-existing datasets,
- briefly describe the content, role in the project, and the source.
- For datasets to be produced in this project,
- briefly describe their content, role in the project, and how they will be collected, observed or generated.
- For all datasets,
- mention the general data type (e.g., text,
tabular data, images, movies, audio files, device-specific
binary data, geospatial data, census data, …) along with
the their file-formats (as created by the device(s) used, by the
simulation software, or as downloaded), e.g.,
CSV
,netCDF
,JPEG
,PNG
,MPEG-4
,PDF
,Shapefile
,VCF
,SMILES
, … For datasets for which you have options to choose a file-format, please refer to Appendix A: File format recommendations.
- For all datasets,
- give an estimate of the total volume and the number of files, if a large number of them is to be expected. Orders of magnitude are sufficient.
Note
Make sure to not only consider the “raw” data, but also datasets that will be expected at the end of the analysis chain and directly underlie the resulting publications.
Example snippets¶
Example 1 [UGLA2015-1]¶
The data produced from this research project will fall into two categories:
- The various reaction parameters required for optimization of the chemical transformation.
- The spectroscopic and general characterization data of all compounds produced during the work.
All data is tabular. Data in category 1 will be documented in [file_format]. Spectroscopic data in category 2 will be produced as [file_format] and converted to [file format] for further use. Other characterization data in this category will be collected in [file_format].
We anticipate that the data produced in category 1 will amount to approximately 10 MB and the data produced in category 2 will be in the range of 4 - 5 GB.
Example 2 [UGLA2015-2]¶
This project will work with and generate four main types of raw data:
- Images from transmitted-light microscopy of giemsa-stained squashed larval brains.
- Images from confocal microscopy of immunostained whole-mounted larval brains.
- Western blot data.
- Results from LC/MS analyses of larval brains
All data will be stored either in the format in which it was originally generated (i.e. Metamorph files for confocal images; Spectrum Mill files for mass spectra with results of mass spectra analyses stored in CSV files; TIFF files for transmitted-light microscopy), or will be converted into a digital form via scanning to create TIFF or JPEG files (e.g. western blots or other types of results).
Measurements and quantification of the images will be recorded in Excel files. For long term preservation, they will be converted to CSV files. Micrograph data is expected to total between 100 GB and 1 TB over the course of the project. Scanned images of western blots are expected to total around 1GB over the course of the project. Other derived data (measurements and quantification) are not expected to exceed 10 MB.
Example 3 (modified from [EPFL2017])¶
The data are tabular health records generated by users of the application X, which is deployed to 2 million users by company Y, who will also collect the data from all users to provide us with the complete dataset.
All fields contain user observations and are entered manually, except for temperature, which is measured by a Bluetooth connected thermometer. Data recording will take place over the course of three months.
Data fields per user: User identifier, Age, Weight, Size.
Six data fields per users per day of observation, which include one numerical value (temperature), five values on a nominal scale, e.g. “cervical fluid quality”, and one free-text field.
Data will be received in CSV format and has a total volume of about 15 GB.
Example 4 (from real Eawag DMP)¶
There will be two categories of data: NEW data from this project and EXISTING data from the FOEN Lake Monitoring program. The NEW data will consist of several file types, all CSV real number format, which are all organized along the same principle: matrixes of times series with various channels, each corresponding to a sensor (number of sensors varies from 1 to10) and very different length, as the sampling frequency varies by several orders-of-magnitudes. (i) 6 files of CO2, DO, PAR and temperature (24 files at a time; Figure 2), each file only 1 sensor (Delta = 10 min; continuous), (ii) Thetis profiles corresponding to time series (equivalent to depth series) of 10 sensors (Delta = 1 s; 5-10 times per day). (iii) 5 files of CO2 time series for short-term surface flux measurements (several files, one per month), (iv) meteodata file (eight sensors; continuous), (v) T-Microstructure profiles files (6 sensors at 512 Hz; several files, once per month) and (vi) excel files for individual chemical samples (such as alkalinity, sediment trap estimates, ect; sporadic). The EXISTING data is already available (CIPAIS, CIPEL) in excel sheets with matrices for the individual samplings and a variable number of parameters (~10 to ~25). The EXISTING data will not be modified and remains with the organizations. We will keep a copy on our computers during the project. We anticipate the data produced in category 1 to amount to several hundred MB for the moored and profiled sensor files and ~100 GB for the T-microstructure profiles; the EXISTING data in category 2 is in the range of ~20 MB.
1.2 How will the data be collected, observed or generated?¶
SNSF [SNSF2017]
Questions you might want to consider:
- What standards, methodologies or quality assurance processes will you use?
- How will you organize your files and handle versioning?
Explain how the data will be collected, observed or generated. Describe how you plan to control and document the consistency and quality of the collected data: calibration processes, repeated measurements, data recording standards, usage of controlled vocabularies, data entry validation, data peer review, etc.
Discuss how the data management will be handled during the project, mentioning for example naming conventions, version control and folder structures. (This relates to the FAIR Data Principle R1)
Instructions¶
This section actually has two parts, 1. Quality Control and 2. Organization.
1. Quality assurance¶
For each dataset, mention standards, methodologies and processes that serve to ensure that the data meets the expected quality. This might for example include:
- The use of core facility services (specify their certifications, if any)
- Codes of good research practice that are being followed.
- Quality control procedures such as plausibility checks, range check, double data entry, statistical or visual outlier detection, instrument verification tests, etc., that you plan to apply.
- The method to record data quality (e.g. quality flags for data points), if applicable.
- Arrangements to assign responsibilities for quality control.
- Training activities.
2. Data Organization¶
Briefly describe how the data will be organized. That might be a folder-structure together with a file naming convention, a local SQL or NoSQL database, a cloud-based collaboration platform, a version-control system such as git, an Electronic LaboratoryNotebook / Laboratory Information System (ELN/LIMS), etc.
Consider how the chosen organization schema supports version-control (if necessary), collaboration (if necessary) and is suited for the expected data volume and data structure.
Example snippets¶
Example 1 (modified from [UGLA2015-1])¶
The reaction conditions will be recorded and collated using a spreadsheet application. The resulting files will be saved in directory, one for each scientist, with appropriately set file permissions. A filename convention that encodes reaction, reaction generation and date will be applied.
These directories will be mirrored to SWITCHDrive to for collaboration.
The various experimental procedures and associated compound characterization will be written up using the Royal Society of Chemistry standard formatting in a Word document, each Word document will also be exported to PDF-A. The associated NMR spectra will be collated in chronological order in a PDF-A document.
Example 2 (modified from [UGLA2015-2])¶
All samples on which data are collected will be prepared according to published standard protocols in the field [cite reference]. Files will be named according to a pre-agreed convention. The dataset will be accompanied by a README file which will describe the directory hierarchy. Each directory will contain an INFO.txt file describing the experimental protocol used in that experiment. It will also record any deviations from the protocol and other useful contextual information.
The format used for microscope images captures and stores a range of metadata (field size, magnification, lens phase, …) with each image. We will use a Python script that automatically extracts these metadata and stores them together with the respective filenames in a SQLite database.
Example 3 (from a real Eawag DMP)¶
The data from the moored sensors is sensor-internally stored and recovered every two months, when sensors will be cleaned and recalibrated if data indicates quality loss. The CO2 sensors will be cross calibrated against atmospheric pressure. The DO and PAR sensors in the mooring will be compared to profiled sensors and deviations detected. Temperature sensors are extremely stable and are only calibrated before and after the two years using the laboratory temperature bath which is calibrated agaist the Office of Metrology in Bern every few years to 0.001 oC. The Thesis sensor data is transmitted when surfacing via GSM communication system directly to the lab where sensors deterioration is weekly checked. The instrument will be retrieved every month and sensors cleaned. The optical sensors will be calibrated according the manual every six months. The T-microstructure sensors do not need calibration as the data is matched to (very accurate) CTD temperature. Small T shifts are irreverent, as only the spectra matter. The sensors deterioration (or frequency loss) will visually be checked and is seen in the quality of the Batchelor spectra. The very simple structure of the CSV files holding the raw data will be documented in a plain text README file. This file, and all raw data files as they become available, will be uploaded to the Eawag Research Data Institutional Collection into one “data package”, which is annotated with general metadata. Copies of the raw data files as well as set of calibrated, quality-controlled files stored on the group computers at EPFL will be organized in a folder structure that is also documented in a README file. At the end of the project, the entire set of calibrated, quality-controlled files will be annotated and stored on the Eawag institutional repository as well.
Example 4 [EPFL2017]¶
All experimental data will be automatically imported into the institutional electronic Laboratory Information System (LIMS) from the measurement device. Methods and materials will be recorded using the institutional Electronic Lab Notebook (ELN).
Example 5¶
The sensor data are being fed into a Postgresql database running on an institutional server. The database implements rules for basic validity checks (range-checks, plausibility checks). The R scripts for data analysis are stored in the institutional Git repository for version control and collaboration.
1.3 What documentation and metadata will you provide with the data?¶
SNSF [SNSF2017]
Questions you might want to consider:
- What information is required for users (computer or human) to read and interpret the data in the future?
- How will you generate this documentation?
- What community standards (if any) will be used to annotate the (meta)data?
Describe all types of documentation (README files, metadata, etc.) you will provide to help secondary users to understand and reuse your data. Metadata should at least include basic details allowing other users (computer or human) to find the data. This includes at least a name and a persistent identifier for each file, the name of the person who collected or contributed to the data, the date of collection and the conditions to access the data.
Furthermore, the documentation may include details on the methodology used, information about the performed processing and analytical steps, variable definitions, references to vocabularies used, as well as units of measurement. Wherever possible, the documentation should follow existing community standards and guidelines. Explain how you will prepare and share this information. (This relates to the FAIR Data Principles I1, I2, I3, R1, R1.2 & R1.3)
Instructions¶
Conceptualize two types of metadata: 1. Scientific metadata and 2. General metadata:
1. Scientific metadata¶
Scientific metadata provides all necessary information to correctly understand, interpret, assess, replicate (within limits), build upon, and generally use your data. This metadata might be compiled “free-form” into one or several README-file(s) that accompany the data.
Certain fields have formally defined established metadata standards, e.g. the Ecological Metadata Language (EML), the Open Microscopy Environment Schemas or WaterML. Mention it, if you use such a standard. Have a look at The RDA metadata directory for an overview of existing standards.
This metadata could contain for example:
- A description of the organization and relationships of the files or database tables and other supporting materials.
- Information about the naming convention (if applicable).
- A mapping of data files to the corresponding section of the associated publication, if applicable.
- Information about units of measurements, variable definitions, columns headings and abbreviations (if not present in the data-files proper).
- Information about the software (name, version, system environment). used to produce and read the data (if the software is not included as data).
- Information about which files were used in what way at what stage of the work.
- Suggestions for how to best reuse the data.
- Any information suited to decrease the chances that a future user of the data needs to contact you with questions.
Describe, as detailed as possible, what will comprise the scientific metadata. Make sure to mention all information, or information categories, that a future user of your data will need to read and interpret the data.
Describe how this metadata will be managed, i.e. who or what will generate it when, in what form it is stored in which location, and how it is associated with the respective experiment, measurement, or observation. Describe technical aspects of the metadata management, e.g. the use of database software, and the protocol or mechanism to handle updates and version control, if applicable.
2. General metadata¶
This type of metadata serves to make your data findable. It consists of general attributes that help to search, sort, index, access and propagate the dataset or collection of datasets. At Eawag, capture, storage, formatting and dissemination of this metadata is handled by the institutional research data repository. You might use the Eawag standard snippet “metadata in ERIC”.
Examples for 1. Scientific metadata¶
Example 1 [DataONE2011]¶
We will first document our metadata by taking careful notes in the laboratory notebook that refer to specific data files and describe all columns, units, abbreviations, and missing value identifiers. These notes will be transcribed into a .txt document that will be stored with the data file. After all of the data are collected, we will then use EML (Ecological Metadata Language) to digitize our metadata. EML is one of the accepted formats used in ecology, and works well for the types of data we will be producing. We will create these metadata using Morpho software, available through KNB (http://knb.ecoinformatics.org/morphoportal.jsp). The metadata will fully describe the data files and the context of the measurements.
Example 2 [UGLA2015-1]¶
The data will be accompanied by the following contextual documentation, according to standard practice for synthetic methodology projects:
- spreadsheet documents which detail the reaction conditions.
- text files which detail the experimental procedures and compound characterization.
Files and folders will be named according to a pre-agreed convention. The final dataset as deposited in the institutional data repository will also be accompanied by a README file listing the contents of the other files and outlining the file-naming convention used.
Example 3 (from a real Eawag DMP)¶
For every data stream (sequences of identical data files) over the entire 2-year period of data acquisition a README File will be generated which contains: (a) the sensors used (product, type, serial number), (b) the temporal sequence of the sensors (time and location, sampling interval), (c) the observations made during maintenance and repairs, and (d) details on the physical units, as well as the calibration procedure and format. This is a standard procedure which we have used in the past.
Standard snippet for 2. General metadata¶
Eawag standard snippet “metadata in ERIC”
The completed dataset will be uploaded to the Eawag Research Data Institutional Collection (ERIC). This repository collects (upon upload) the metadata according to the DataCite metadata schema 4.0, an accepted state-of-the-art standard. In addition to the mandatory fields of the DataCite schema, ERIC collects several metadata fields such as time-range, spatial extent, geographical names, measured variables, chemical substances and taxonomic information. ERIC provides search functionality and assigns a persistent URL to each dataset.
2. Ethics, legal and security issues¶
2.1 How will ethical issues be addressed and handled?¶
SNSF [SNSF2017]
Questions you might want to consider:
- What is the relevant protection standard for your data? Are you bound by a confidentiality agreement?
- Do you have the necessary permission to obtain, process, preserve and share the data? Have the people whose data you are using been informed or did they give their consent?
- What methods will you use to ensure the protection of personal or other sensitive data?
Ethical issues in research projects demand for an adaptation of research data management practices, e.g. how data is stored, who can access/reuse the data and how long the data is stored. Methods to manage ethical concerns may include: anonymization of data; gain approval by ethics committees; formal consent agreements. You should outline that all ethical issues in your project have been identified, including the corresponding measures in data management. (This relates to the FAIR Data Principle A1)
Instructions¶
- Make sure you have a good idea what personal data means in the context of Swiss data protection law: Personal data refers to any information that relates to a particular person. Next to items such as physical- or email-address, health record, or age, it also includes for example photographs, videos recordings or genetic information. If in doubt, consult the Eawag Compliance Guide (page 18) and references therein.
- Check whether your project involves the collection, storage or processing of personal data.
- Check whether your project involves other types of sensitive information, e.g. otherwise not easily obtainable information about vulnerabilities of water infrastructure or locations of rare and protected species.
- Check whether your work involves data that you obtain under a non-disclosure agreement or any kind of contract that would restrict its usage or dissemination, or includes other special requirements relevant for data handling.
- If your project requires the assessment of an ethical review board (or similar), or requires permission from third parties such as a cantonal office, check whether any imposed requirements are related to data collection, processing or dissemination.
If the your project is free from any of the above issues, you might copy & paste Eawag standard snippet “no issues”.
Otherwise:
Specify all data that are affected by any of the above points. Specify
the special requirements regarding data collection, handling and
dissemination.
The collection of personal data most likely requires informed consent. Describe consent-form content and ancillary measures to ensure informedness, if applicable.
Mention relevant approvals and permissions obtained from third parties and reference their requirements.
If you anonymize personal data, describe the anonymization method (e.g. pseudonymization or removal of personal information).
If you use encryption and/or if you put in place special access restrictions, just mention that here and refer to Section 2.2, where you give the details.
Mention non-technical procedures that ensure data protection, such as scheduled deletion of data or training activities. For technical implementation details or purely technical measures reference Section 2.2.
Standard snippet¶
Eawag standard snippet “no issues”
There are no ethical, legal or security issues regarding data collection, processing, storage and dissemination in this project. We neither obtain nor generate sensitive data and do not sign a confidentiality agreement.
Examples¶
Example 1¶
Dataset X was obtained from the BAFU and is subject to a confidentiality agreement to keep information about the sampling locations secret. We are allowed to share this information among researchers involved in the project. The dataset is being stored in a location to which only project member have access. Please refer to Section 2.2 for technical details about access restrictions. All project members will be informed about sensitivity of this data and agree not to copy it to other places. This dataset and intermediate datasets containing the sampling locations will be excluded from the data package published along with the final report and replaced with instructions about how to obtain them from the BAFU.
Example 2 [ESRC2013]¶
A letter explaining the purpose, approach and dissemination strategy (including plans to share data) of the research, and an accompanying consent form (including to share data) will be prepared and translated into the relevant languages. A clear verbal explanation will also be provided to each interviewee and focus group participant. Commitments to ensure confidentiality will be maintained by ensuring recordings are not shared; that transcripts are anonymized and details that can be used to identify participants are removed from transcripts or concealed in write-ups. Please refer to Section 2.2 for technical details regarding anonymization method and techincal measures.
Example 3¶
The raw data from our metabolite measurements could, in concert with other data, potentially be used to associate individual households with drug-use profiles. We therefore regard the sampling locations as sensitive data. In all published data, the sampling locations will be replaced with numerical codes. The respective correspondence table will be stored encrypted, please refer to Section 2.2 for technical details.
2.2 How will data access and security be managed?¶
SNSF [SNSF2017]
Questions you might want to consider:
- What are the main concerns regarding data security, what are the levels of risk and what measures are in place to handle security risks?
- How will you regulate data access rights/permissions to ensure the security of the data?
- How will personal or other sensitive data be handled to ensure safe data storage and transfer?
If you work with personal or other sensitive data you should outline the security measures in order to protect the data. Please list formal standards which will be adopted in your study. An example is ISO 27001 - Information security management. Furthermore, describe the main processes or facilities for storage and processing of personal or other sensitive data. (This relates to the FAIR Data Principle A1)
Instructions¶
Briefly mention the datasets that require special protection (reference Section 2.1) and use an adverb to indicate the “level of risk” (e.g. “high”, “medium”, “low”).
To document proper handling of sensitive data consider the following points and recommendations:
- Storage location(s)
- Do not store sensitive data “in the cloud”, unless the service provider is bound by Swiss privacy law. If you have to, encrypt it (see Note on encryption). Mention any considerations in that regard, if applicable.
- Secure transmission
- Encrypt sensitive data before transmission over a network and mention it if you do that. Public key encryption is the recommended method (see Note on encryption).
- Access restrictions
- Describe who has access to the data at what stage and how you implement access restrictions (e.g. by permissions on the file system).
- IT Infrastructure
- Describe the IT infrastructure used with regard to data security. You might use Eawag standard snippet “Eawag file services - access”, if applicable.
Note on encryption
Consider encrypting sensitive information. In that case, name the encryption method, at what stage the data is encrypted, and how the encryption key is managed. In particular, consider using full-disk encryption for field notebooks, and public-key encryption for exchanging sensitive information (e.g. in emails or email-attachments, or when using untrusted file-sharing services such as Dropbox. GnuPG is the recommended software for that purpose.
Standard snippet¶
Eawag standard snippet “Eawag file services - access”
All data will be stored on Eawag’s central shared Fileservices. Data security and confidentiality are protected by using Microsoft Active Directory authentication. The shared filesystem can only be accessed from inside the Eawag network and remote access is possible by establishing a Virtual Private Network (VPN) that is secured by 2-factor authentication.
Examples¶
Example 1 [Leeds2013]¶
Access to electronic data is controlled by Active Directory (AD) Group membership. The Faculty IT Manager will set up a dedicated folder for this research project and create read-only and read-write AD groups. The PI will decide which users require read-only and read-write access. Off-campus access is via the Citrix portal. External users who need access to the data will apply for a University username and then be assigned to the appropriate AD group.
Example 2 (modified from [NEH2015])¶
Research records will be kept confidential, and access will be limited to the PI, primary research team members, and project participants. Data will be housed on a local server controlled by the PI, and will be accessible via SSH and VPN. Data containing identifiable information, or information covered by an NDA, will be held in an encrypted format (symmetric, AES256, key on local server, passphrase only know to PI and primary research team members).
Example 3 (from a real Eawag DMP)¶
The data we are generating, processing and storing in this project does not pose a particular data security risk. Day-to-day work is conducted on standard-issue workstations in the EPFL-environment with standard enterprise-grade access control. The EPFL network is a secured system following the best practices in terms of identity management and central storage facility has redundancy, mirroring and is monitored. At different stages, data will be stored in the Eawag Institutional Collection (see section 1.3). This system is accessible only from within the Eawag network and is comprised of several virtualized Linux systems that receive real-time security patches. Access control is handled according to recognized best practices of server administration.
2.3 How will you handle copyright and Intellectual Property Rights issues?¶
SNSF [SNSF2017]
Questions you might want to consider:
- Who will be the owner of the data?
- Which licenses will be applied to the data?
- What restrictions apply to the reuse of third-party data?
Outline the owners of the copyright and Intellectual Property Right (IPR) of all data that will be collected and generated, including the licence(s). For consortia, an IPR ownership agreement might be necessary. You should comply with relevant funder, institutional, departmental or group policies on copyright or IPR. Furthermore, clarify what permissions are required should third-party data be re-used. (This relates to the FAIR Data Principles I3 & R1.1)
Instructions¶
If your work involves data that you obtain under a non-disclosure agreement or any kind of contract that would restrict its usage or dissemination (see Section 2.1), consider how that impacts your right to disseminate derived data and your results and elaborate.
In case your data or source code might be commercially exploitable (e.g. patentable), please consult the Technology Transfer Office at Empa.
Results from work of Eawag employees is generally “owned” by Eawag. If your project involves groups from other institutions, make sure that there is an agreement about a common policy on the dissemination of results. Mention such an agreement or state that Eawag has the sole authority to disseminate the data.
After having established who owns / will own the rights on all data, software and other creative works that will be produced or used in or by the project, consider the Note on licenses below. If you can release all relevant data, software and other creative works relevant for the project into the public domain, you might use the Eawag standard snippet “default licensing” and move on.
Otherwise state for all data, source code and other output under what terms it will be made available at the end of the project, and why it can’t be released into the public domain, if applicable. If parts of the output or pre-existing data can not be made available at all, state that here and give the reason.
If the reasons for not releasing the data, or releasing it under terms that restrict re-use, are related to the presence of “sensitive data” in the sense of Section 2.1, reference Section 4.2, where you explain the details.
Note on licenses
- 1. Pure data,
- “facts about nature”, are not subject to copyright law in Switzerland. However, to make clear to potential users that they can re-use it, explicitly place it in the public domain by applying the CC0 Public Domain Dedication.
- 2. Source code
falls sui generis under copyright law and you need to explicitly waive the copyright to enable unrestricted re-use. Apply the CC0 - Public Domain Dedication.
If you want to have the option to sue people who don’t credit you when using your code, apply the MIT License.
If you like to force people who build on your code to open source their changes and improvements as well, apply the GNU Affero General Public License.
If your code builds on third-party code, check whether the respective license restricts your choice of license (e.g., if you build on code licensed under the GNU General Public License, GPL, you need to publish your derived code under a compatible license, or not publish it at all). If you have trouble to sort out your license-entanglements, get in touch with the Eawag Research Data Management Project<EMAIL_ADDRESS>for help.
- 3. Other creative output
such as text, images, video also falls sui generis under copyright law and you need to explicitly waive the copyright to enable unrestricted re-use. Apply the CC0 Public Domain Dedication.
If you want to have the option to sue people who don’t credit you when re-using your work, apply the Ceative Commons Attribution 4.0 International License.
In case you derived such a work from a pre-existing source, check whether restrictions imposed by the license of the original exist and publish your derivative work under a compatible license, if possible.
Standard snippet¶
Eawag standard snippet “default licensing”
All software, datasets and other creative works from this project will be placed in the public domain by applying the Creative Commons Public Domain Dedication (CC0 1.0). Eawag has either unrestricted authority over the dissemination of the data and works to be published, or we have established an agreement to that effect with our collaborators.
Examples¶
Example 1¶
The source code for analysis will most likely utilize the GNU Scientific Library (GSL), which is licensed under the GNU General Public License (GPL). Therefore we will make our analysis software available under the GPL as well.
Example 2¶
Our collaborators at X University in Germany will contribute significantly to produce the extensive database of species distributions, which, in Germany, falls under copyright law. University X would like to retain the copyright on the database and therefore it will be published without a license that could facilitate re-use.
Example 3 (modified from [EPFL2017])¶
This project is being carried out in collaboration with an industrial partner. The intellectual property rights are set out in the collaboration agreement. The intellectual property generated from this project will be fully exploited with help from the institutional Technology Transfer Office. The aim is to patent the final procedure and then publish the work in a research journal and to publish the supporting data under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.
3. Data storage and preservation¶
3.1 How will your data be stored and backed-up during the research?¶
SNSF [SNSF2017]
Questions you might want to consider:
- What are [sic] your storage capacity and where will the data be stored?
- What are the back-up procedures?
Please mention what the needs are in terms of data storage and where the data will be stored. Please consider that data storage on laptops or hard drives, for example, is risky. Storage through IT teams is safer. If external services are asked for, it is important that this does not conflict with the policy of each entity involved in the project, especially concerning the issue of sensitive data. Please specify your back-up procedure (frequency of updates, responsibilities, automatic/manual process, security measures, etc.)
Instructions¶
Describe storage location and backup procedure during all phases of research, e.g. a), during data collection / generation, and b), during analysis.
At stages where data can not be stored on Eawag infrastructure (e.g. fieled campaign involving dataloggers and laptops), take care to implement a backup protocol that should
- be as automatic as possible,
- frequent enough,
- duplicate the data onto another storage medium, which
- is kept at a different location and
- ideally includes (automatic) checks for the success of each backup.
From copying data from the field-laptop to a flash drive that is kept by another person to automatic synchronization with SWITCHDrive, there are many options to do this reliably and comfortably. Consult your IT department if you need help, or just to assess you strategy. Describe this backup strategy.
At a stage where you have access to the Eawag shared filesystem, store your data there. Make sure you know which directories of your workstation are mapped to backed-up server storage (see IT documentation - Backup). Check with IT whether you have access to the required storage capacity and arrange an increase of the quota, if necessary. Copy & paste the text-snippet below (Eawag standard snippet “file services - backup”) to account for this stage.
In case you plan to use other servers, e.g. for doing bioinformatics at the Genetic Diversity Centre, inquire about their backup procedure and briefly describe it here. In case you need to set up a backup-solution by yourself, consider getting advice from the IT department.
In case you plan to use cloud storage for collaboration (e.g. SWITCHDrive), make sure a replica of that data is kept on Eawag infrastructure at any time. Encrypt sensitive that is being stored by third parties. Mention such a setup here.
Check whether you have the necessary storage capacity at all storage locations you plan to use. Mention that here (if not already covered by Eawag standard snippet “file services - backup”.
Standard snippet¶
Eawag standard snippet “file services - backup”
Data will be stored on back-upped servers in the Eawag local network. For file services and virtual server farm, Eawag shares a server/storage platform (Netapp Metrocluster, Cisco UCS Server, VMWare) with Empa. The backup procedure is fully automatic. Snapshots of files are taken at least three times during a working day. All data are mirrored synchronously between the two server sites on the Empa-Eawag campus in Dübendorf. Additionally, backups (to disk) are taken from the Metrocluster at a third location on the campus. Backups are kept for three months. We have arranged to have access to the required storage-capacity.
Examples¶
Example 1¶
Data will be downloaded from the dataloggers diurnally to the field-laptop, and immediately copied to a flash-drive, which is stored in a physically secure location in the field office. Success of the download is checked immediately. The laptop is brought to Dübendorf campus (no network link on-site) on the same day and the data is copied to a backed-up server in the Eawag local network. [copy text from Eawag standard snippet “file services - backup”]
Example 2¶
The simulations will be carried at supercomputing facility X, where
backup is not available. On the local workstation runs a script that
periodically calls rsync
to mirror the remote directory, where
the simulation results are written, to a backed-up share on Eawag
infrastructure (which is mounted on the local workstation). [copy text
from Eawag standard snippet “file services - backup”]
Example 3¶
Our team stores the data to be analyzed along with the results using Eawag file services. [copy text from Eawag standard snippet “file services - backup”] To easily share data with our collaborators in Fribourg, we synchronize those data with a folder on SWITCHdrive. Since this is sensitive personal data, the folder being synchronized contains encrypted files (public key encryption, key-pairs specifically created for this project).
3.2 What is your data preservation plan?¶
SNSF [SNSF2017]
Questions you might want to consider:
- What procedures would be used to select data to be preserved?
- What file formats will be used for preservation?
Please specify which data will be retained, shared and archived after the completion of the project and the corresponding data selection procedure (e.g. long-term value, potential value for reuse, obligations to destroy some data, etc.). Please outline a long-term preservation plan for the datasets beyond the lifetime of the project. In particular, comment on the choice of file formats and the use of community standards. (This relates to the FAIR Data Principles F2 & R1.3)
Instructions¶
It is Eawag policy to generally preserve all relevant data generated or used by research projects in the Eawag Research Data Institutional Collection. Refer to internally communicated guidelines or contact the Eawag Research Data Management Project<EMAIL_ADDRESS>for help. You can copy & paste the standard text-snippet below (Eawag standard snippet “preservation”). Note that this does not necessarily means that all this data will be publicly shared. Data that will not be shared should be mentioned in Section 4.2.
Check whether there are reasons not to preserve a part of the data and mention if there are any. That could apply for example to data that
- is subject to a contractual or legal obligation to destroy data after a certain amount of time, or
- simulation data that can be re-created through computation, or
- high-volume data that can be downloaded any time from a reliable external long-term repository, e.g. climate model output.
If there are no exceptions, follow Eawag standard procedure and copy & paste the Eawag standard snippet “preservation”.
Check whether you consider any of the data eligible for Long Term Storage. Mention those datasets and adapt the standard text-snippet below (Eawag standard snippet “long-term storage”).
This applies to data of long-term institutional or societal value. Long Term Storage tries to ensure re-usability of the data at a time when the creators of the data, the current custodians, the current storage platform, or the currently responsible institution (Eawag) are not available anymore. Such data is of high quality and consists primarily of unique observations of the environment or experimental results. Data flagged as Long Term Storage in the institutional repository will be reviewed with regard to file-formats and documentation.
List the file-formats that you are going to upload to the institutional repository. (see Appendix A: File format recommendations).
Standard snippets¶
Eawag standard snippet “preservation”
It is Eawag policy to generally preserve all relevant data generated or used by research projects in the Eawag Research Data Institutional Collection. This includes all raw data, all processed data that directly underlies the reported results, and all ancillary information necessary to understand, evaluate, interpret and re-use the results of the study. Data from intermediate steps of the analysis that can be re-created from preserved information does not need not to be stored.
Eawag standard snippet “long-term storage”
The dataset X and Y will be flagged for Long Term Storage upon submission to the Eawag institutional collection because they represent unique and non-reproducible information about the state of the environment and we expect them to be of high quality and of great utility for future researchers. Datasets flagged for Long Term Storage will be subjected to specific measures to preserve data integrity and data safety, such as additional backups, regular re-writes to new storage media and redundant storage in third-party repositories. Additionally, data flagged in this way will be stored in file-formats that minimize the chance for format obsolescence.
4. Data sharing and reuse¶
4.2 Are there any necessary limitations to protect sensitive data?¶
SNSF [SNSF2017]
Questions you might want to consider:
- Under which conditions will the data be made available (timing of data release, reason for delay if applicable)?
Data have to be shared as soon as possible, but at the latest at the time of publication of the respective scientific output. Restrictions may be only due to legal, ethical, copyright, confidentiality or other clauses. Consider whether a non-disclosure agreement would give sufficient protection for confidential data. (This relates to the FAIR Data Principles A1 & R1.1)
Instructions¶
- If you can publish all data at the time of publication just state that.
- If parts of the data will not be made available at all, state the reason(s).
- If you intend to publish part of the data before the related publication is finished, you might state this here.
- In general, the optimal point in time to publish data that underpins a publication is right after the publication has been accepted. In case you are not able to publish the data latest at the time of publication of the respective output, state the reason(s) for that delay. State explicitly when exactly you plan to publish it though.
- If you are confident that you can make all relevant data public in time, you might use the Eawag standard snippet “publishing OK below.
Note
The SNSF description seems to imply that delayed or forgone publication of data is only acceptable for sensitive data as described in Section 2.1. We believe there are other valid reasons and suggest you wait until this problem actually materializes at the end of the project, describe the issue in the final DMP, and hope that the SNSF will accept that.
Possible reasons for delayed publication (accepted by SNSF) could for example include:
- The time necessary to anonymize personal data.
- The need to keep patentable information secret until patent protection applies.
Possible reasons for delayed publication, which are currently not accepted by SNSF, include for example:
- The intent to synchronize the publication of the data with other publications (e.g. project report, paper, press release) to maximize visibility and impact.
- The intent to base follow-up publications on the data, after the project has finished.
- The intent to couple re-use of the data by other groups to an offer for collaboration.
Standard snippet¶
Eawag standard snippet “publishing OK”
We expect no limitations with respect to publishing the data. It will be made available to the public in full, latest at the time of publication of the project report.
Examples¶
Example 1¶
Our data will include meteorological observations obtained from MeteoSwiss who prohibit any further distribution of the data. Therefore we will have to exclude these data from publication.
Example 3¶
The extensive household survey about water-born diseases poses severe challenges with regard to anonymization, since simple pseudonymization might not be sufficient to guard against the identification of individual households by an inference attack that uses other available information.
Therefore we will be only able to publish summary statistics together with the associated article. If a sufficiently anonymized dataset turns out to still hold scientific value, we will publish it no later than one year after completion of the project.
Example 4¶
We expect that the the sampling campaign will yield useful data that cannot be completely exploited within the frame of this project. We therefore anticipate a follow-up project based on these data and might therefore delay the the publication of the full dataset for two years.
4.3 I will choose digital repositories that are conform to the FAIR Data Principles. [checkbox
]¶
SNSF [SNSF2017]
The SNSF requires that repositories are conform to the FAIR Data Principles (Section 5 of the guidelines for researchers, SNSF’s explanation of the FAIR Data Principles). If there are no repositories complying with these requirements in your research field, please deposit a copy of your data on a generic platform (see examples). If no data can be shared, this is a statement of principles.
Instructions¶
Just check the box:4.4 I will choose digital repositories maintained by a non-profit organisation. [radio-button yes/no
]¶
SNSF [SNSF2017]
-> If the answer is no: “Explain why you cannot share your data on a non-commercial digital repository.”
The SNSF supports the use of non-commercial repositories for data sharing. Costs related to data upload are only covered for non-commercial repositories.


ItemModelScatterDataProxy QML Type
Proxy class for presenting data in item models with Scatter3D. More...
| Import Statement: | import QtDataVisualization 1.2 |
| Since: | QtDataVisualization 1.0 |
| Instantiates: | QItemModelScatterDataProxy |
| Inherits: |
Properties
- itemModel : model
- rotationRole : string
- rotationRolePattern : regExp
- rotationRoleReplace : string
- xPosRole : string
- xPosRolePattern : regExp
- xPosRoleReplace : string
- yPosRole : string
- yPosRolePattern : regExp
- yPosRoleReplace : string
- zPosRole : string
- zPosRolePattern : regExp
- zPosRoleReplace : string
Detailed Description
This type allows you to use AbstractItemModel derived models as a data source for Scatter3D.
The data is resolved asynchronously whenever the mapping or the model changes. QScatterDataProxy::arrayReset() is emitted when the data has been resolved.
For more details, see QItemModelScatterDataProxy documentation.
Usage example:
ItemModelScatterDataProxy { itemModel: model // E.g. a list model defined elsewhere containing point coordinates. // Mapping model roles to scatter series item coordinates. xPosRole: "xPos" yPosRole: "yPos" zPosRole: "zPos" }
See also ScatterDataProxy and Qt Data Visualization Data Handling.
Property Documentation
The item model to use as a data source for Scatter3D.
The item model role to map into item rotation. The model may supply the value for rotation as either variant that is directly convertible to quaternion, or as one of the string representations: "scalar,x,y,z"
or "@angle,x,y,z"
. The first format will construct the quaternion directly with given values, and the second one will construct the quaternion using QQuaternion::fromAxisAndAngle() method.
When set, a search and replace is done on the value mapped by the rotation role before it is used as item rotation. This property specifies the regular expression to find the portion of the mapped value to replace and rotationRoleReplace property contains the replacement string.
See also rotationRole and rotationRoleReplace.
This property defines the replace content to be used in conjunction with rotationRolePattern. Defaults to an empty string. For more information on how the search and replace using regular expressions works, see QString::replace(const QRegExp &rx, const QString &after) function documentation.
See also rotationRole and rotationRolePattern.
When set, a search and replace is done on the value mapped by the x position role before it is used as an item position value. This property specifies the regular expression to find the portion of the mapped value to replace and xPosRoleReplace property contains the replacement string.
See also xPosRole and xPosRoleReplace.
This property defines the replace content to be used in conjunction with xPosRolePattern. Defaults to an empty string. For more information on how the search and replace using regular expressions works, see QString::replace(const QRegExp &rx, const QString &after) function documentation.
See also xPosRole and xPosRolePattern.
When set, a search and replace is done on the value mapped by the y position role before it is used as an item position value. This property specifies the regular expression to find the portion of the mapped value to replace and yPosRoleReplace property contains the replacement string.
See also yPosRole and yPosRoleReplace.
This property defines the replace content to be used in conjunction with yPosRolePattern. Defaults to an empty string. For more information on how the search and replace using regular expressions works, see QString::replace(const QRegExp &rx, const QString &after) function documentation.
See also yPosRole and yPosRolePattern.
When set, a search and replace is done on the value mapped by the z position role before it is used as an item position value. This property specifies the regular expression to find the portion of the mapped value to replace and zPosRoleReplace property contains the replacement string.
See also zPosRole and zPosRoleReplace.
This property defines the replace content to be used in conjunction with zPosRolePattern. Defaults to an empty string. For more information on how the search and replace using regular expressions works, see QString::replace(const QRegExp &rx, const QString &after) function documentation.
See also zPosRole and zPosRolePattern.


Preparation time
30 mins to 1 hour
Cooking time
30 mins to 1 hour
Serves
Makes 1 x 23cm/9in tart
Dietary
Tropical fruits replace the more traditional raspberry jam in this custard tart. Serve it cold with whipped cream.
Preheat the oven to 220C/425F/Gas 7. Grease and line a 23cm/9in tart tin.
For the pastry, put the flour and icing sugar in the bowl of a food processor and pulse briefly to mix. Add the butter and pulse until the mixture resembles fine breadcrumbs.
Tip the mixture out into a large mixing bowl and add the egg yolks and two tablespoons of cold water. Mix with your hands until the mixture comes together.
On a lightly floured work surface, briefly knead the dough to bring the pastry together. Flatten to a thick circle, wrap in cling film and chill in the fridge for 20 minutes.

Line the tart tin with the pastry, using a rolling pin to help you lift the pastry. Gently push the pastry into the edges and leave any excess overhanging the tin. Place the tart tin on a baking tray.
Prick the base of the pastry all over with a fork. Rest the pastry case in the fridge for 10 minutes.
When the pastry is chilled, line it with four sheets of cling film or a scrunched up piece of baking parchment. Completely fill with baking beans (or dry pulses) and blind bake for 20 minutes on the middle shelf of the oven.
Remove from oven and lift out the baking beans using the cling film or baking parchment. Brush the pastry case with egg wash.
Return to the oven for eight minutes, or until the pastry looks dry and golden-brown.
Lower the oven temperature to 140C/275F/Gas 1.
For the filling, in a large heatproof bowl add the eggs, orange zest, lime zest and 150g/5½oz of the caster sugar. Stir gently until the sugar is dissolved - try to avoid getting too much air into the mixture.
In a food processor, blend half of the mango to a purée. Pass through a sieve to remove any fibres and measure out 50g/1¾oz of purée (any leftover purée can be stored in the fridge for 2-3 days and used in smoothies, sorbets or as a sauce for desserts).
Cut the passionfruits in half and pass the pulp through a sieve into a measuring jug. Add orange juice to make 100ml/3½fl oz of passionfruit and juice combined. Pour into the egg mixture along with the rum, mango purée and double cream. Stir gently until well mixed. Set aside.
For the pastry, trim the excess pastry from the sides using a sharp knife.
Meanwhile, place the bowl of filling over a pan of gently simmering water (do not let the water touch the bowl). Stir continuously until the mixture reaches 55C/130F on a cook’s thermometer.
Pour the filling in the warmed tart case and bake for 25 minutes, until just set but with a wobble in the centre. (When cooked, the filling should be 70C/160F in the centre.)
Remove from the oven and set aside to cool for 10 minutes. Remove the tin and place the tart on a cooling rack. When it is completely cool, put the tart on a serving plate.
For the decoration, scatter the desiccated coconut in a pattern in the middle of the tart. Neatly slice the remaining mango and arrange the slices around the edge of the tart. Finish with the physalis placed evenly around the tart.


State:
California
Massachussets
Virginia
New York
Collarado
Intuit Employee:
Intuit Employee:
Method of Commute:
Car:
Carpool:
First Name


Android 10 Is Rolling Out To The HONOR 20, 20 Pro & View 20
We have some good news for HONOR flagship users. Android 10 is now rolling out to the HONOR 20, 20 Pro, and View 20. Those three devices are the very latest flagship offerings from Huawei's subsidiary.
Android 10 coming to the HONOR 20, 20 Pro & View 20 with Magic UI 3.0
Android 10 is coming with Magic UI 3.0 on those three smartphones. This is a global variant of Android 10 that we're talking about here, by the way.
The update has begun rolling out to those three devices globally, but it may take a while before all of you get it. The rollout is going out in phases, so it has not been pushed out for every single device just yet. If everything goes according to plan, though, it will reach all phones within a week or two.
Advertisement
This update weighs 4.63GB, in case you're wondering, so it's a hefty one. That's not that surprising, though, considering that a brand new iteration of Android is coming, along with HONOR's additions.
The global variant of this update was spotted with a build number <IP_ADDRESS> (C431E9R3P7). Your update may come with a different build number, though, as we're sure that more than one variant is rolling out.
Your phone can be updated via the HiCare app, or the system updater. The phone will notify you once the OTA update is available for your device, though you can always check manually as well.
Advertisement
Android 10 update brings quite a few changes to the HONOR 20, 20 Pro, and the View 20. You will get Android 10's brand new privacy controls, along with some design changes inspired by Google's latest Android version.
Your UI will look considerably different than the stock one, though. HONOR's phones come with Magic UI pre-installed, and Magic UI 3.0 brings a number of changes compared to v2.0.
The update includes a 'Magazine Design', dynamic animations, and more
You'll get a new Magazine Design with this update, along with a Morandi color scheme. Dynamic animations are also included in the package, by the way.
Advertisement
HONOR will also deliver a number of improvements to the GPU Turbo feature, while the Phone Clone feature will also be included.
Media playback-related improvements are also rolling out as we speak, along with a number of additional changes that you can check out it the included image.
This global update arrived to the HONOR 20, 20 Pro, and View 20 sooner than we expected. The P30 and P30 Pro also started receiving Android 10 a couple of days ago, and HONOR seems to have been just as fast this time around.
Advertisement


Copyright © Bristol CND All rights reserved.
<EMAIL_ADDRESS>http://www.bristolcnd.org.uk/


The new firmware was updated and the device will be restarted in a few seconds. Take a look at the serial output for details.


Sentence Splitting, Tokenization, Lemmatization, Part-of-speech Tagging, Dependency Parsing and Named Entity Recognition for more than 50 languages
During the PARSEME Shared Task we experimented with a new architecture and algorithm for identifying expression. You can read the paper here.
We started working on integrating this technique into NLP-Cube and we are almost done. During our experiments we tested the unmodified GBG on Named Entity Recognition. We used the CONLL2003 corpus and got some pretty interesting results. According to the ACL Wiki, the best performing system is that of Huang et al. (2015) with a 90.1% F-Score. Our system achieved an F-Score of 95.12% for token-based evaluation (which is the same score used in the previously mentioned evaluation) and 93.40% strict F-Score (where we only counted NERs that are fully recognized and we discard partial matches).
Full evaluation output (using the PARSEME evaluation script):
## Global evaluation * MWE-based: P=5369/5849=0.9179 R=5369/5648=0.9506 F=0.9340 * Tok-based: P=7884/8465=0.9314 R=7884/8112=0.9719 F=0.9512 ## Per-category evaluation (partition of Global) * LOC: MWE-proportion: gold=1668/5648=30% pred=1580/5849=27% * LOC: MWE-based: P=1472/1580=0.9316 R=1472/1668=0.8825 F=0.9064 * LOC: Tok-based: P=1675/1797=0.9321 R=1675/1925=0.8701 F=0.9001 * MISC: MWE-proportion: gold=702/5648=12% pred=743/5849=13% * MISC: MWE-based: P=567/743=0.7631 R=567/702=0.8077 F=0.7848 * MISC: Tok-based: P=743/998=0.7445 R=743/918=0.8094 F=0.7756 * ORG: MWE-proportion: gold=1661/5648=29% pred=1835/5849=31% * ORG: MWE-based: P=1469/1835=0.8005 R=1469/1661=0.8844 F=0.8404 * ORG: Tok-based: P=2250/2738=0.8218 R=2250/2496=0.9014 F=0.8598 * PER: MWE-proportion: gold=1617/5648=29% pred=1691/5849=29% * PER: MWE-based: P=1527/1691=0.9030 R=1527/1617=0.9443 F=0.9232 * PER: Tok-based: P=2677/2932=0.9130 R=2677/2773=0.9654 F=0.9385 ## MWE continuity (partition of Global) * Continuous: MWE-proportion: gold=5648/5648=100% pred=5755/5849=98% * Continuous: MWE-based: P=5369/5755=0.9329 R=5369/5648=0.9506 F=0.9417 * Discontinuous: MWE-proportion: gold=0/5648=0% pred=94/5849=2% * Discontinuous: MWE-based: P=0/94=0.0000 R=0/0=0.0000 F=0.0000 ## Number of tokens (partition of Global) * Multi-token: MWE-proportion: gold=2074/5648=37% pred=2209/5849=38% * Multi-token: MWE-based: P=1941/2209=0.8787 R=1941/2074=0.9359 F=0.9064 * Single-token: MWE-proportion: gold=3574/5648=63% pred=3640/5849=62% * Single-token: MWE-based: P=3428/3640=0.9418 R=3428/3574=0.9591 F=0.9504 ## Whether seen in train (partition of Global) * Seen-in-train: MWE-proportion: gold=3021/5648=53% pred=3011/5849=51% * Seen-in-train: MWE-based: P=2941/3011=0.9768 R=2941/3021=0.9735 F=0.9751 * Unseen-in-train: MWE-proportion: gold=2627/5648=47% pred=2838/5849=49% * Unseen-in-train: MWE-based: P=2428/2838=0.8555 R=2428/2627=0.9242 F=0.8886 ## Whether identical to train (partition of Seen-in-train) * Variant-of-train: MWE-proportion: gold=10/3021=0% pred=14/3011=0% * Variant-of-train: MWE-based: P=7/14=0.5000 R=7/10=0.7000 F=0.5833 * Identical-to-train: MWE-proportion: gold=3011/3021=100% pred=2997/3011=100% * Identical-to-train: MWE-based: P=2934/2997=0.9790 R=2934/3011=0.9744 F=0.9767


[gecode-users] allocated() virtual member function?
Joseph Scott
joseph.scott at it.uu.se
Tue Nov 4 15:46:56 CET 2014
Hello,
I have a quick question about a propagator with heap-allocated memory. I understand that it needs to be registered for disposal, via AP_DISPOSE. But I’m a little confused by the “Reporting allocated memory” paragraph in MPG (Section 30.2, p. 361), which states that any propagator allocating non-space memory “must implement the virtual member function allocated()”.
I’ve looked, but it seems like the allocated() member function has been removed (maybe as part of the change to peak memory tracking in 4.2?). Is it safe to assume this paragraph no longer applies? Or do I need to report the propagator’s allocated size somewhere else?
Thanks!
Joe
More information about the users
mailing list


Before Change
def train(self, training_corpus, feature_set):
self.global_feature_set = feature_set
self.allowed_features_keys = {fkey for edge in training_corpus.edges() for fkey in edge.features.keys()}
self.final_allowed_key_mapping = {}
num_feat = 0
for allowed_feat_key in self.allowed_features_keys:
After Change
def train(self, training_corpus, feature_set):
self.global_feature_set = feature_set
self.allowed_features_keys, self.final_allowed_key_mapping = \
__class__._gen_allowed_and_final_mapping_features_keys(training_corpus)
X, y = __class__._convert_edges_to_SVC_instances(training_corpus, self.final_allowed_key_mapping, self.preprocess)


NIMASA remits N16 billion revenue in 2019
by Chidinma NwagbaraThe Director-General of the Nigerian Maritime Administration and Safety Agency (NIMASA), Hon. Dakuku Peterside, on Tuesday, disclosed that the total sum of N16 billion has been remitted into the Consolidated Revenue Fund in 2019.
According to Punch, Peterside said N110.84 billion was the targeted revenue for 2019, out of which N83.49 billion, representing 74%, was realised while N20 billion had been spent out of the N28 billion allocated for the mandatory Maritime Fund.
Breakdown of the expenses for the 2019 budget: Peterside said N20 billion was budgeted for personnel cost, out of which N15.2 billion had been spent, while overhead got N24 billion allocation with N12 billion spent out of it.
He added that the agency also released N2.5 billion to the Nigerian Maritime University, Okerenkoko, Delta State.
“As of October 31, we had contributed N16 billion into the Consolidated Revenue Fund. We have since increased our contribution and in that contribution, we have exceeded our budget target.”
Speaking at the sideline of the budget defence, Hon Peterside affirmed that the Agency had achieved tremendous success towards improving ease of doing business by reducing the number of agencies at the port.
[READ MORE: Six firms face LIRS sanction over non-remittance of N42.68 million Income Tax]
According to him, “I don’t think we have issues with port congestion, the problem is the access roads to our various ports and Federal Government is taking it as a priority programme. That is what I can say. The issue ab-initio is not port congestion, it is that access roads to ports are bad and we were not able to evacuate cargoes from the port early enough. If the access roads were in order, then it will be easier for us to evacuate cargoes.
“In addition to that, if you notice the new programme, we are connecting all ports by rail to the hinterland that will also help in evacuating cargoes from the port to hinterland. And of course, you are aware of the dry port programme being pursued by the Nigerian Shippers Council. So all of that would help in alleviating what you called congestion of ports.”
Speaking further, Peterside stated that NIMASA was working to ensure the review of existing maritime laws in the country to meet up contemporary demands of the industry.


TABLE OF INTERACTIONS WITH
RACECADOTRIL
From the French ANSM drug interactions document of September 2016, p. 187
RACECADOTRIL RxNorm: 16738 ATC: A07XA04 |
ANGIOTENSIN CONVERTING ENZYME INHIBITORS (ACE INHIBITORS) CLASS CODE: C09AA |
Risk of increase of the undesirable effects of the angioedema type. |
Contraindication -in case of previous angioedema while taking ACE inhibitors Not recommended --in the absence of previous angioedema with ACE inhibitors. |


Cultural Blog - Compassion
What are your thoughts about the compassion training?
The meditation exercise seemed like an interesting variation on the earlier ones. Once again it's easy enough to envisage goodness in most people but when I get to the last section it's very hard to do this for the most difficult that I have met! (But maybe that's the point of all this! Or maybe it's them that needs the training!!) I do agree that the most effective business leaders that I have met are those who you can like and respect.
Give a short summary of each of the components of the SCARF model of social behaviour
Status - We act to increase or preserve our social status.
Certainty - We act to increase certainty and decrease uncertainty.
Autonomy - We act to increase autonomy.
Relatedness - We are less likely to feel threatened by those who we think of as being related to us in some way.
Fairness - We will not accept rewards if we feel that the situation is unfair to us.
Difficult conversations and mindful emailing ( or slacking! ) are highly important at EDA. Is there an example in your life where you applied/didn't apply these concepts?
A while ago I needed to have a difficult conversation with a loved one. I agonized about this for a long time but finally I formulated a plan in my mind. As it happens it was very similar to the method described in this chapter. A key point was to try to see the situation from the other's point of view. This allowed me to preempt any difficult responses and to create acceptible solutions for them.
How did you feel about it?
Great. It was eventually worth the agony!


(Defined in: jpgraph_canvas.php : 20)
Class usage and Overview
If you for some reason just want plain canvas to draw on using the direct drawing method you can create a new canvas with this class.
The canvas is meant to be manipulated through the Image class which can be found as an instance variable ($graph->img) in the canvas class.
Please remeber taht using the drawing methods in the Image class assumes screen (pixels) coordinates.
See also related classes:
Graph
Class Methods
Strokes plot area and margin
Description:
Calling this method will fill the margin (with the margin color) and fill the plot area with the plot color. You should call this method before stroking anything else to the canvas as otherwise what you have stroken will be overwritten.
// Setup a basic canvas we can work
$g = new CanvasGraph(400,200,'auto');
$g->SetMargin(5,11,6,11);
$g->SetShadow();
$g->SetMarginColor("teal");
// We need to stroke the plotarea and margin before we add the
// text since we otherwise would overwrite the text.
$g->InitFrame();
// Draw a text box in the middle
$txt="This\nis\na TEXT!!!";
$t = new Text($txt,200,10);
$t->SetFont(FF_ARIAL,FS_BOLD,40);
// Stroke the text
$t->Stroke($g->img);
// Stroke the graph
$g->Stroke();
Stroke graph to browser or file
| Argument | Default | Description |
|
$aStrokeFileName
|
""
| Filename to stroke to |
Description:
Stroke a file to browser or file. See Graph::Stroke() for more details.
See also:
$canvas->Stroke();
Construct a new Cnavas graph
| Argument | Default | Description |
|
$aWidth
|
300
| Width of graph |
|
$aHeight
|
200
| Height of graph |
|
$aCachedName
|
""
| Cache file name |
|
$timeout
|
0
| Cache timeout |
|
$inline
|
1
| Inline or not |
Description:
See Graph::Graph() for description, this method is identical.
See also:
// Create a new canvas and draw a line from top left to
// bottom right
$canvas = new CanvasGraph(300,200);
$canvas->img->SetColor(black*);
$canvas->img->Line(0,0,300,200);
$canvas->Stroke();


--- layout: post status: publish published: true title: Minor Update to PipelineTesting author: display_name: Tomas Restrepo login: tomasr email<EMAIL_ADDRESS>url: http://winterdom.com/ author_login: tomasr author_email<EMAIL_ADDRESS>author_url: http://winterdom.com/ wordpress_id: 54 wordpress_url: http://winterdom.com/2007/12/minorupdatetopipelinetesting date: '2007-12-17 05:57:17 +0000' date_gmt: '2007-12-17 05:57:17 +0000' categories: - BizTalk tags: [] comments: [] ---
I've uploaded a new update to my PipelineTesting library, a tool for creating automated tests for BizTalk Server 2006 pipelines and custom pipeline components. Read more about PipelineTesting, and download the code here.
The only change on this version is that the IPipelineContext.GetEventStream() method now returns a stub implementation BAM EventStream instead of returning null as previous versions did. This makes it easier to execute pipelines that require access to BAM.


This page describes how to package your extension.
As the Overview explains,
extensions are packaged as signed ZIP files
with the file extension "crx"—for example,
myextension.crx
.
Note:
You do not need to package your own extension.
If you publish your extension using the
Chrome Developer Dashboard,
then the only reason to create your own .crx
file
would be to distribute a non-public version—for example,
to alpha testers.
You can find information on publishing extensions and apps in the
Chrome Web Store getting started tutorial, starting at
Step 5: Zip up your app.
When you package an extension, the extension is assigned a unique key pair. The extension's ID is based on a hash of the public key. The private key is used to sign each version of the extension and must be secured from public access. Be careful not to include your private key within your extensions!
To package an extension:
chrome://extensions
C:\myext
.
(Ignore the other field;
you don't specify a private key file
the first time you package a particular extension.)
.crx
file,
which is the actual extension that can be installed,
and a .pem
file,
which contains the private key.
Do not lose the private key!
Keep the .pem
file secret and in a safe place.
You'll need it later if you want to do any of the following:
If the extension is successfully packaged, you'll see a dialog like this
that tells you where to find
the .crx
and .pem
files:
To create an updated version of your extension:
manifest.json
.
C:\myext
.
.pem
file for this extension—for
example, C:\myext.pem
.
If the updated extension is successfully packaged, you'll see a dialog like this:
You can use the Chrome Developer Dashboard to upload an extension that you've previously packaged yourself. However, unless you take special steps, the extension's ID in the Chrome Web Store will be different from its ID in the package you created. This different ID might be a problem if you've distributed your extension package, because it allows users to install multiple versions of your extension, each with its own local data.
If you want to keep the extension ID the same, follow these steps:
.crx
file to key.pem
. key.pem
in the top directory
of your extension.
Another way to package extensions
is by invoking chrome.exe
at the command line.
Use the --pack-extension
flag
to specify the location of the extension's folder.
Use --pack-extension-key
to specify the location of the extension's private key file.
For example:
chrome.exe --pack-extension=C:\myext --pack-extension-key=C:\myext.pem
For more information on the format, as well as pointers to scripts you can use
to create .crx
files, see CRX Package Format.


public abstract class TwoFingerGestureDetector extends BaseGestureDetector
| Modifier and Type | Field and Description |
|---|---|
protected float |
deltaPixelFingerX0 |
protected float |
deltaPixelFingerX1 |
protected float |
deltaPixelFingerY0 |
protected float |
deltaPixelFingerY1 |
protected float |
density |
protected float |
mCurrFingerDiffX |
protected float |
mCurrFingerDiffY |
protected float |
mPrevFingerDiffX |
protected float |
mPrevFingerDiffY |
mContext, mCurrEvent, mCurrPressure, mGestureInProgress, mPrevEvent, mPrevPressure, mTimeDelta, PRESSURE_THRESHOLD
| Constructor and Description |
|---|
TwoFingerGestureDetector(android.content.Context context) |
| Modifier and Type | Method and Description |
|---|---|
float |
getCurrentSpan()
Return the current distance between the two pointers forming the
gesture in progress.
|
float |
getPreviousSpan()
Return the previous distance between the two pointers forming the
gesture in progress.
|
protected static float |
getRawX(android.view.MotionEvent event,
int pointerIndex)
MotionEvent has no getRawX(int) method; simulate it pending future API approval.
|
protected static float |
getRawY(android.view.MotionEvent event,
int pointerIndex)
MotionEvent has no getRawY(int) method; simulate it pending future API approval.
|
protected abstract void |
handleInProgressEvent(int actionCode,
android.view.MotionEvent event)
Called when the current event occurred when a gesture IS in progress.
|
protected abstract void |
handleStartProgressEvent(int actionCode,
android.view.MotionEvent event)
Called when the current event occurred when NO gesture is in progress
yet.
|
protected boolean |
isSloppyGesture(android.view.MotionEvent event)
Check if we have a sloppy gesture.
|
protected void |
resetDistanceFinger() |
protected void |
updateDistanceFingerByEvent(android.view.MotionEvent currEvent) |
protected void |
updateStateByEvent(android.view.MotionEvent curr) |
getEventTime, getTimeDelta, isInProgress, onTouchEvent, resetState
protected float mPrevFingerDiffX
protected float mPrevFingerDiffY
protected float mCurrFingerDiffX
protected float mCurrFingerDiffY
protected float deltaPixelFingerX0
protected float deltaPixelFingerX1
protected float deltaPixelFingerY0
protected float deltaPixelFingerY1
protected float density
public TwoFingerGestureDetector(android.content.Context context)
protected abstract void handleStartProgressEvent(int actionCode, android.view.MotionEvent event)
BaseGestureDetector
handleStartProgressEvent
in class BaseGestureDetector
protected abstract void handleInProgressEvent(int actionCode, android.view.MotionEvent event)
BaseGestureDetector
handleInProgressEvent
in class BaseGestureDetector
protected void resetDistanceFinger()
protected void updateStateByEvent(android.view.MotionEvent curr)
updateStateByEvent
in class BaseGestureDetector
protected void updateDistanceFingerByEvent(android.view.MotionEvent currEvent)
public float getCurrentSpan()
public float getPreviousSpan()
protected static float getRawX(android.view.MotionEvent event, int pointerIndex)
event
- pointerIndex
- protected static float getRawY(android.view.MotionEvent event, int pointerIndex)
event
- pointerIndex
- protected boolean isSloppyGesture(android.view.MotionEvent event)
event
-


Home
ABOUT
Contact
SOMETHING AWESOME COMING SOON
We'r currently working on new website We'll be launching soon.
visit now
www.tenantverify.in


|
| string | GetAttribute (string name) |
| | Returns an attribute value by name . More...
|
| |
| bool | SetAttribute (string name, string value) |
| | Adds a new attribute. If an attribute with that name is already present in the element, its value is changed to be that of the value parameter. More...
|
| |
| void | RemoveAttribute (string name) |
| | Removes an attribute specified by name . More...
|
| |
| bool | HasAttribute (string name) |
| | Returns true when an attribute with a given name is specified on this element or has a default value, false otherwise. More...
|
| |
| bool | SetInnerHTML (string html) |
| | Replaces inner HTML of the current element with specified html. More...
|
| |
| bool | SetInnerText (string text) |
| | Replaces inner text of the current element with specified html. More...
|
| |
| void | Focus () |
| | Give focus to the current element More...
|
| |
| void | Blur () |
| | Remove focus from the current element More...
|
| |
| List< DOMNode > | GetElementsByTagName (string tagName) |
| | Returns a list of DOM nodes with specific tagName . More...
|
| |
| List< DOMNode > | GetElementsByName (string name) |
| | Returns a list of DOM nodes whose name attribute is given by name . More...
|
| |
| List< DOMNode > | GetElementsByClassName (string className) |
| | Returns a list of DOM nodes whose class attribute is given by className . More...
|
| |
| void | Click () |
| | Simulates click on the current Node. More...
|
| |
| DOMNode | QuerySelector (string selectors) |
| | Returns the first DOM node from children of the current node, that match any selector within selectors string. More...
|
| |
| List< DOMNode > | QuerySelectorAll (string selectors) |
| | Returns a list of DOM nodes from children of the current node, that match any selector within selectors string. More...
|
| |
| bool | InsertChild (DOMNode node, DOMNode beforeNode) |
| | Inserts a new node before an existing beforeNode. The new node could be an existing node in the document, or you can create and insert a new node. If the node is existing node, it will be moved to new location in the document. More...
|
| |
| bool | ReplaceChild (DOMNode newNode, DOMNode oldNode) |
| | Replaces existing child node with a new node. The new node could be an existing node in the document, or you can create a new node. If the newNode is existing node, it will be moved to new location in the document. The old node could be used for inserting/appending it into the document later. More...
|
| |
| bool | RemoveChild (DOMNode childNode) |
| | Removes a child node and notifies whether child node was removed from the current node successfully or not. More...
|
| |
| bool | AppendChild (DOMNode childNode) |
| | Appends a node as the last child of the current node. The new node could be an existing node in the document, or you can create a new node. If the childNode is existing node, it will be moved to new location in the document. More...
|
| |
| void | AddEventListener (DOMEventType eventType, DOMEventHandler handler, bool useCapture) |
| | This method allows the registration of event listeners on the event target. If an DOMEventHandler is added to an DOMEventTarget while it is processing an event, it will not be triggered by the current actions but may be triggered during a later stage of event flow, such as the bubbling phase.
If multiple identical DOMEventHandlers are registered on the same DOMEventTarget with the same parameters the duplicate instances are discarded. They do not cause the DOMEventHandler to be called twice and since they are discarded they do not need to be removed with the RemoveEventListener method. More...
|
| |
| void | AddEventListener (DOMEvent domEvent, DOMEventHandler handler, bool useCapture) |
| | This method allows the registration of event listeners on the event target. If an DOMEventHandler is added to an DOMEventTarget while it is processing an event, it will not be triggered by the current actions but may be triggered during a later stage of event flow, such as the bubbling phase.
If multiple identical DOMEventHandlers are registered on the same DOMEventTarget with the same parameters the duplicate instances are discarded. They do not cause the DOMEventHandler to be called twice and since they are discarded they do not need to be removed with the RemoveEventListener method. More...
|
| |
| void | RemoveEventListener (DOMEventType eventType, DOMEventHandler handler, bool useCapture) |
| | This method allows the removal of event listeners from the event target. If an DOMEventHandler is removed from an DOMEventTarget while it is processing an event, it will not be triggered by the current actions. DOMEventHandlers can never be invoked after being removed.
Calling RemoveEventListener with arguments which do not identify any currently registered DOMEventHandler on the DOMEventTarget has no effect. More...
|
| |
| void | RemoveEventListener (DOMEvent domEvent, DOMEventHandler handler, bool useCapture) |
| | This method allows the removal of event listeners from the event target. If an DOMEventHandler is removed from an DOMEventTarget while it is processing an event, it will not be triggered by the current actions. DOMEventHandlers can never be invoked after being removed.
Calling RemoveEventListener with arguments which do not identify any currently registered DOMEventHandler on the DOMEventTarget has no effect. More...
|
| |
| List< DOMEventHandler > | GetEventListeners (DOMEventType eventType) |
| | Returns a list of registered DOMEventHandler's for specific eventType. More...
|
| |
| List< DOMEventHandler > | GetEventListeners (DOMEvent domEvent) |
| | Returns a list of registered DOMEventHandler's for specific custom event. More...
|
| |
| bool | DispatchEvent (DOMEvent domEvent) |
| | Sends an event to the current element. More...
|
| |
| DOMElement | GetElementByTagName (string tagName) |
| | Finds first DOM element in the current document or element with the given tagName . Returns null if element wasn't found using given find method. More...
|
| |
| DOMElement | GetElementByName (string name) |
| | Finds first DOM element in the current document or element with the given name . Returns null if element wasn't found using given find method. More...
|
| |
| DOMElement | GetElementByClassName (string className) |
| | Finds first DOM element in the current document or element with the given className . Returns null if element wasn't found using given find method. More...
|
| |
| XPathResult | Evaluate (string expression) |
| | Evaluates an XPath expression for the document element with XPathResultType.ANY_TYPE and returns the result. Equivalent of: More...
|
| |
| XPathResult | Evaluate (string expression, XPathResultType type) |
| | Returns an XPathResult based on an XPath expression and other given parameters. More...
|
| |
|
| Dictionary< string, string > | Attributes [get] |
| | Returns a dictionary that contains attributes of the current element. More...
|
| |
| string | InnerHTML [get] |
| | Returns a string that represents inner HTML of the current element. More...
|
| |
| string | InnerText [get] |
| | Returns a string that represents inner text of the current element. More...
|
| |
| int | OffsetLeft [get] |
| | Gets the horizontal offset position of the current element More...
|
| |
| int | OffsetTop [get] |
| | Gets the vertical offset position of the current element More...
|
| |
| int | OffsetWidth [get] |
| | Gets the width of the current element, including padding, border and scrollbar More...
|
| |
| int | OffsetHeight [get] |
| | Gets the height of the current element, including padding, border and scrollbar More...
|
| |
| int | ClientLeft [get] |
| | Gets the width of the left border of the current element More...
|
| |
| int | ClientTop [get] |
| | Gets the width of the top border of the current element More...
|
| |
| int | ClientWidth [get] |
| | Gets the width of the current element, including padding More...
|
| |
| int | ClientHeight [get] |
| | Gets the height of the current element, including padding More...
|
| |
| double | ScrollLeft [get, set] |
| | Gets or sets the number of pixels an element's content is scrolled horizontally More...
|
| |
| double | ScrollTop [get, set] |
| | Gets or sets the number of pixels an element's content is scrolled vertically More...
|
| |
| int | ScrollWidth [get] |
| | Gets the entire width of the current element, including padding More...
|
| |
| int | ScrollHeight [get] |
| | Gets the entire height of the current element, including padding More...
|
| |
| Rectangle | BoundingClientRect [get] |
| | Returns bounds of the element and its position relative to the top-left of the viewport of the current document. More...
|
| |
| string | NodeName [get] |
| | Gets the name of this node, depending on its DOMNodeType. More...
|
| |
| string | NodeValue [get, set] |
| | Gets or sets the value of this node, depending on its DOMNodeType. More...
|
| |
| DOMNodeType | NodeType [get] |
| | Gets the type of this node. More...
|
| |
| DOMNode | Parent [get] |
| | Gets parent node or null if there's no parent. More...
|
| |
| List< DOMNode > | Children [get] |
| | Gets a list of child node of this node. More...
|
| |
| string | XPath [get] |
| | Gets the xpath of this node More...
|
| |
| string | TextContent [get, set] |
| | Gets or sets text content of the node and its descendants. More...
|
| |
| DOMNode | NextSibling [get] |
| | Gets the node immediately following this one in its parent's children list, or null if this node is the last node in the list. More...
|
| |
| DOMNode | PreviousSibling [get] |
| | Gets the node immediately preceding this one in its parent's children list, or null if this node is the first node in that list. More...
|
| |
Represents DOM HTML element.


Settings
Name
Username
Tel
Remember me
Log In
NightCrawler
Nav
From current position?