Doctor Voldritch's Experiment Mac OS

Today we are happy to present MonetDBLite for R, a fully embedded version of MonetDB that installs like any other R package. The database runs within the R process itself (like its namesake SQLite), greatly improving efficiency of data transfers. The package is available for Linux, Mac OS X and Windows (64 bit).

R and MonetDB fit together well, with statistical programming performed in R and data wrangling handled by MonetDB. For years, we have had the MonetDB.R R package, which allows to connect to a running MonetDB server, send queries and retrieve results. Due to the inefficiencies of shipping data around, MonetDB also supports User-Defined Functions implemented in R. However, both approaches require users to set up and maintain a separate MonetDB server. There have been numerous requests to simplify this process.

Experiment Log 614-1a Researcher: Dr. Opus Date: Description: Over the course of about 20 days, a series of tests were run to check the accuracy of SCP-614 regarding future torrents. A string was randomly generated and searched for in SCP-614, and a note was made if a previously generated dummy file was found. Spider-Man 2 is a 2004 action-adventure game, based on the film of the same name, while incorporating additional material from the comic books.Published by Activision, the console versions were developed by Treyarch, while the others had different developers. Item #: SCP-3082 Object Class: Euclid Special Containment Procedures: The suburban locale surrounding SCP-3082 and the private property associated with the anomaly itself are to remain in the Foundation's ownership, functioning as a Site-11 satellite facility. In order to more easily preserve the appearance of an unremarkable neighborhood, it is recommended that Foundation personnel inhabit.

Installation of MonetDBLite is straightforward:

This will install MonetDBLite and the latest version of the MonetDB.R client package, which contains the DBI and dplyr backends. Here is a usage example with MonetDBLite:

Note that MonetDBLite will store the 'mtcars' table on disk in the specified directory (a temporary one here). A later R session does not need to repeat writing the data to the database and can directly work with the stored persistent tables. This considerably reduces the startup time of analyses, especially as tables get large.

To showcase the power of MonetDBLite, we compared its performance against MonetDB with the socket-based R client and RSQLite. As a real-world benchmark, we use Anthony Damico's scripts to analyse the 'Home Mortgage Disclosure Act (HMDA)' dataset . These scripts generate SQL queries to accurately reproduce statistics found in Federal Financial Institutions Examination Council (FFIEC) publications. The used data from 2006 to 2011 contains 128 Million rows of data with 71 fields each. In CSV format, the full dataset occupies 56 GB of disk space. In addition, we have produced smaller versions of the dataset with 6M and 60M tuples by way of random sampling. We ran three experiments: CSV loading, querying and full table transfer into R.

All experiments report wall clock time and were run on a Linux desktop machine with 16GB of main memory and a 3.40GHz Intel i7-2600K CPU. The query and conversion timings are from 'hot' runs. The following figure illustrate the outcome of the CSV loading experiment:

Doctor Voldritch's Experiment Mac Os Update

We can see how MonetDBLite and MonetDB.R are almost equal, which is of no surprise since they use the same CSV loader code. SQLite performs well except for the large dataset, where the operating system was forced to swap out virtual memory frequently.

Timings from running the HMDA queries are plotted in the following figure:

Since the query results only contain a few tuples, the socket overhead is small and the timings of MonetDBLite and MonetDB.R are again comparable. SQLite cannot benefit from the columnar storage model and performs significantly worse.

Finally, another common use case is to retrieve an entire table from the database into a R data.frame. The next figure shows timings for reading the entire 'hmda_11' table into R.

The socket-based MonetDB.R client is not able to perform well here. The client needs to convert the row-based wire protocol back to the colummnar format of data.frame objects and needs to perform extensive string parsing as well. Due to limitations in R, it did not finish (DNF) for the two larger data sets. MonetDBLite on the other hand shows stellar performance here, only taking 94 seconds to transfer 14M rows with 71 fields into R. This is largely due to their compatible columnar data representations. SQLite takes 13 times longer.

All scripts and data files used to produce these plots are available online..

We invite the interested public to try out MonetDBLite. If any issues arise, please report back to hannes@cwi.nl .

Update: MonetDBLite has been accepted to CRAN.

Update II: MonetDBLite is now on GitHub.

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All Dissertations

Title

Author

Date of Award

August 2020

Document Type

Dissertation

Doctor Voldritch's Experiment Mac Os Download

Degree Name

Doctor Voldritch's Experiment Mac Os Pro

Doctor of Philosophy (PhD)

Department

Food Technology

Committee Member

Doctor Voldritch's Experiment Mac Os 7

William Scott Whiteside

Committee Member

Ron Thomas

Committee Member

Hojae Bae

Committee Member

Kyle Dunno

Abstract

This research studied is about development of seaweed biodegradable nanocomposite films reinforced with cellulose nanocrystals (CNCs) from seaweed biomass and investigating the properties of the films. Study was conducted to isolate CNCs from seaweed biomass and these isolated CNCs are applied to developed seaweed biopolymer films. At last, degradability of these films was evaluated with a weight loss method in soil burial and lake water immersion systems.

Doctor Voldritch

CNCs were extracted from seaweed biomass of brown, red, and green by four steps process of depolymerization, bleaching, acid hydrolysis, and mechanical dispersion. Physicochemical and thermal properties were determined for each seaweed group and compared. Among the seaweeds, Sargassum fluitans (brown seaweed) was used to isolate CNCs and applied to alginate nanocomposite (Alg/CNCs) films. Alg/CNCs films showed gradual decreasing of water absorption/solubility, water vapor permeability (WVP), oxygen permeability (OP), and light transmittance with increasing addition of CNCs. Also, addition of CNCs enhanced the tensile strength but elongation of Alg/CNCs films did not show the tendency due to its shrinkage. Scanning electron microscopy (SEM) results indicated that CNCs layers can be formed in the alginate polymer matrix, and the Fourier-transform infrared spectroscopy (FTIR) spectra showed the chemical interaction between alginate polymer matrix and CNCs. Thermal stability test with thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) data suggested the addition of CNCs can improve the thermal properties of Alg/CNCs films.

Seaweed nanocomposite films were also developed with brown seaweeds crude extracts; kombu (Laminaria japonica) and sargassum (Sargassum natans). Obtained supernatant after acid-base pretreatment was used for film forming solution. Seaweed biopolymer films were formed by casting-evaporation method. CNCs were isolated from residues with acid-base pretreatment and applied to seaweed biopolymer film for developing bionanocomposite film. Kombu nanocomposite film was prepared with 5% CNCs (KNF-5), and sargassum nanocomposite film was formed with 5% and 25% CNCs (SNF-5 and SNF-25, respectively). Without addition of CNCs, kombu film (KF) appeared as a dark brown color and sargassum film (SF) as a light brown color. CNCs did not affect the color of the films. Through the SEM observation, holes and cracks were found in surface and cross section of KF and SF but they were covered up with CNCs. Chemical structure changes indicated the molecular strength was increased when CNCs were added to the KF and SF. Also, higher crystallinity index was obtained after CNCs addition. These changings led to improving not only the physicochemical characteristics but also mechanical, barrier, and thermal properties. Total phenolic contents, DPPH radical scavenging effect, and reducing power assay indicated that kombu film showed higher antioxidant properties than sargassum film but not significantly related to the CNCs addition.

Developed bionanocomposite films were conducted to degradation test for evaluating their biodegradability. It was performed under indoor soil burial and lake water immersion systems for 35 days and degradation rate was determined by weight loss. In both conditions, degradation results varied in the order as followed: Alginate nanocomposite film (ANF-5) > alginate film (AF) > KNF-5 > SNF-25, SNF-5 > KF > SF. Alginate-based films degraded up to 35% in soil and 53% in lake water for 35 days. In the case of seaweed films, they were eliminated by soil in 28 days and lake water in 7 days. Morphological observation showed wrinkles, pores, and cracks on their surface in the later days of the experiment. Besides, chemical structure changes revealed molecular bonding in polymer matrix diminished at the last stage of the process compared to before the test. Thermal stabilities also decreased due to reduction of the bonding strength after a certain period of days in both soil burial and lake water immersion systems.

Recommended Citation

Doh, Hansol, 'Development of Seaweed Biodegradable Nanocomposite Films Reinforced with Cellulose Nanocrystals for Food Packaging' (2020). All Dissertations. 2663.
https://tigerprints.clemson.edu/all_dissertations/2663

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