cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5517/ccdc.csd.cc24vvf9
title: CCDC 1992011: Experimental Crystal Structure Determination

description: Related Article: Richa, Sunil Kumar, Jayant Sindhu, Poonam Choudhary, Sundeep Jaglan, Ennio Zangrando, Rakesh Kumar, Subash C. Sahoo, Vinod Kumar, Surinder K. Mehta, Ramesh Kataria|2020|J.Mol.Struct.|1228|129460|doi:10.1016/j.molstruc.2020.129460
DOI: 10.5517/ccdc.csd.cc24vvmh
title: CCDC 1992017: Experimental Crystal Structure Determination

description: Related Article: Richa, Sunil Kumar, Jayant Sindhu, Poonam Choudhary, Sundeep Jaglan, Ennio Zangrando, Rakesh Kumar, Subash C. Sahoo, Vinod Kumar, Surinder K. Mehta, Ramesh Kataria|2020|J.Mol.Struct.|1228|129460|doi:10.1016/j.molstruc.2020.129460
DOI: 10.5517/ccdc.csd.cc24vvgb
title: CCDC 1992012: Experimental Crystal Structure Determination

description: Related Article: Richa, Sunil Kumar, Jayant Sindhu, Poonam Choudhary, Sundeep Jaglan, Ennio Zangrando, Rakesh Kumar, Subash C. Sahoo, Vinod Kumar, Surinder K. Mehta, Ramesh Kataria|2020|J.Mol.Struct.|1228|129460|doi:10.1016/j.molstruc.2020.129460
DOI: 10.5517/ccdc.csd.cc24vv95
title: CCDC 1992007: Experimental Crystal Structure Determination

description: Related Article: Richa, Sunil Kumar, Jayant Sindhu, Poonam Choudhary, Sundeep Jaglan, Ennio Zangrando, Rakesh Kumar, Subash C. Sahoo, Vinod Kumar, Surinder K. Mehta, Ramesh Kataria|2020|J.Mol.Struct.|1228|129460|doi:10.1016/j.molstruc.2020.129460
DOI: 10.5517/ccdc.csd.cc24vvd8
title: CCDC 1992010: Experimental Crystal Structure Determination

description: Related Article: Richa, Sunil Kumar, Jayant Sindhu, Poonam Choudhary, Sundeep Jaglan, Ennio Zangrando, Rakesh Kumar, Subash C. Sahoo, Vinod Kumar, Surinder K. Mehta, Ramesh Kataria|2020|J.Mol.Struct.|1228|129460|doi:10.1016/j.molstruc.2020.129460
DOI: 10.5517/ccdc.csd.cc24vvhc
title: CCDC 1992013: Experimental Crystal Structure Determination

description: Related Article: Richa, Sunil Kumar, Jayant Sindhu, Poonam Choudhary, Sundeep Jaglan, Ennio Zangrando, Rakesh Kumar, Subash C. Sahoo, Vinod Kumar, Surinder K. Mehta, Ramesh Kataria|2020|J.Mol.Struct.|1228|129460|doi:10.1016/j.molstruc.2020.129460
DOI: 10.5517/ccdc.csd.cc24vvql
title: CCDC 1992020: Experimental Crystal Structure Determination

description: Related Article: Richa, Sunil Kumar, Jayant Sindhu, Poonam Choudhary, Sundeep Jaglan, Ennio Zangrando, Rakesh Kumar, Subash C. Sahoo, Vinod Kumar, Surinder K. Mehta, Ramesh Kataria|2020|J.Mol.Struct.|1228|129460|doi:10.1016/j.molstruc.2020.129460
DOI: 10.5517/ccdc.csd.cc256lgg
title: CCDC 2002335: Experimental Crystal Structure Determination

description: Related Article: Semra Daşgın, Yetkin Gök, Duygu Barut Celepci, Parham Taslimi, Merve İzmirli, Aydın Aktaş, İlhami Gulcin|2020|J.Mol.Struct.|1228|129442|doi:10.1016/j.molstruc.2020.129442
DOI: 10.5517/ccdc.csd.cc25tz33
title: CCDC 2020955: Experimental Crystal Structure Determination

description: Related Article: Maryam Aghaee, Khosro Mohammadi, Payam Hayati, Sara Ahmadi, Fatemeh Yazdian, Angel Gutierrez, Shamila Rouhani, Titus A.M. Msagati|2020|J.Mol.Struct.|1228|129434|doi:10.1016/j.molstruc.2020.129434
DOI: 10.5517/ccdc.csd.cc25v518
title: CCDC 2021139: Experimental Crystal Structure Determination

description: Related Article: Hemat M. Dardeer, Mohamed Y. Mahgoub, João Ferreira da Silva, Elghareeb E. Elboray|2020|J.Mol.Struct.|1228|129458|doi:10.1016/j.molstruc.2020.129458
DOI: 10.5517/ccdc.csd.cc25v529
title: CCDC 2021140: Experimental Crystal Structure Determination

description: Related Article: Hemat M. Dardeer, Mohamed Y. Mahgoub, João Ferreira da Silva, Elghareeb E. Elboray|2020|J.Mol.Struct.|1228|129458|doi:10.1016/j.molstruc.2020.129458
DOI: 10.5517/ccdc.csd.cc25v53b
title: CCDC 2021141: Experimental Crystal Structure Determination

description: Related Article: Hemat M. Dardeer, Mohamed Y. Mahgoub, João Ferreira da Silva, Elghareeb E. Elboray|2020|J.Mol.Struct.|1228|129458|doi:10.1016/j.molstruc.2020.129458
DOI: 10.5517/ccdc.csd.cc25v54c
title: CCDC 2021142: Experimental Crystal Structure Determination

description: Related Article: Hemat M. Dardeer, Mohamed Y. Mahgoub, João Ferreira da Silva, Elghareeb E. Elboray|2020|J.Mol.Struct.|1228|129458|doi:10.1016/j.molstruc.2020.129458
DOI: 10.5517/ccdc.csd.cc25v55d
title: CCDC 2021143: Experimental Crystal Structure Determination

description: Related Article: Hemat M. Dardeer, Mohamed Y. Mahgoub, João Ferreira da Silva, Elghareeb E. Elboray|2020|J.Mol.Struct.|1228|129458|doi:10.1016/j.molstruc.2020.129458
DOI: 10.5517/ccdc.csd.cc21v1b9
title: CCDC 1901860: Experimental Crystal Structure Determination

description: Related Article: G. Kavitha, A. Dhandapani, B. Gunasekaran, M. Suresh|2020|J.Mol.Struct.|1228|129484|doi:10.1016/j.molstruc.2020.129484
DOI: 10.5517/ccdc.csd.cc25jfrx
title: CCDC 2011799: Experimental Crystal Structure Determination

description: Related Article: Luca Catalano, Luzia S. Germann, Patrick A. Julien, Mihails Arhangelskis, Ivan Halasz, Krunoslav Užarević, Martin Etter, Robert E. Dinnebier, Maurizio Ursini, Massimo Cametti, Javier Martí-Rujas, Tomislav Friščić, Pierangelo Metrangolo, Giuseppe Resnati, Giancarlo Terraneo|2020|Cell Press: Chem|7|146|doi:10.1016/j.chempr.2020.10.022
DOI: 10.5517/ccdc.csd.cc26116j
title: CCDC 2026786: Experimental Crystal Structure Determination

description: Related Article: Türkan Kutlu, Işıl Yıldırım, Hande Karabıyık, Ayten Kılınçlı, İbrahim Tekedereli, Yetkin Gök, Miriş Dikmen, Aydın Aktaş|2020|J.Mol.Struct.|1228|129462|doi:10.1016/j.molstruc.2020.129462
DOI: 10.5517/ccdc.csd.cc25jfsy
title: CCDC 2011800: Experimental Crystal Structure Determination

description: Related Article: Luca Catalano, Luzia S. Germann, Patrick A. Julien, Mihails Arhangelskis, Ivan Halasz, Krunoslav Užarević, Martin Etter, Robert E. Dinnebier, Maurizio Ursini, Massimo Cametti, Javier Martí-Rujas, Tomislav Friščić, Pierangelo Metrangolo, Giuseppe Resnati, Giancarlo Terraneo|2020|Cell Press: Chem|7|146|doi:10.1016/j.chempr.2020.10.022
DOI: 10.5517/ccdc.csd.cc25jftz
title: CCDC 2011801: Experimental Crystal Structure Determination

description: Related Article: Luca Catalano, Luzia S. Germann, Patrick A. Julien, Mihails Arhangelskis, Ivan Halasz, Krunoslav Užarević, Martin Etter, Robert E. Dinnebier, Maurizio Ursini, Massimo Cametti, Javier Martí-Rujas, Tomislav Friščić, Pierangelo Metrangolo, Giuseppe Resnati, Giancarlo Terraneo|2020|Cell Press: Chem|7|146|doi:10.1016/j.chempr.2020.10.022
DOI: 10.5517/ccdc.csd.cc2620lx
title: CCDC 2027728: Experimental Crystal Structure Determination

description: Related Article: Semra Daşgın, Yetkin Gök, Duygu Barut Celepci, Parham Taslimi, Merve İzmirli, Aydın Aktaş, İlhami Gulcin|2020|J.Mol.Struct.|1228|129442|doi:10.1016/j.molstruc.2020.129442
DOI: 10.5517/ccdc.csd.cc25s639
title: CCDC 2019250: Experimental Crystal Structure Determination

description: Related Article: Semra Daşgın, Yetkin Gök, Duygu Barut Celepci, Parham Taslimi, Merve İzmirli, Aydın Aktaş, İlhami Gulcin|2020|J.Mol.Struct.|1228|129442|doi:10.1016/j.molstruc.2020.129442
DOI: 10.5517/ccdc.csd.cc25zt99
title: CCDC 2025611: Experimental Crystal Structure Determination

description: Related Article: Benjamin H. Wilson, Cameron S. Vojvodin, Ghazale Gholami, Louae M. Abdulla, Christopher A. O’Keefe, Robert W. Schurko, Stephen J. Loeb|2020|Cell Press: Chem|7|202|doi:10.1016/j.chempr.2020.11.009
DOI: 10.7295/w9cil53353
title: CIL:53353, Drosophila melanogaster, Entire Organism
DOI: 10.7295/w9cil53354
title: CIL:53354, Drosophila melanogaster, Entire Organism
DOI: 10.7295/w9cil53355
title: CIL:53355, Drosophila melanogaster, Entire Organism
DOI: 10.7295/w9cil53356
title: CIL:53356, Drosophila melanogaster, Entire Organism
DOI: 10.7295/w9cil53357
title: CIL:53357, Drosophila melanogaster, Entire Organism
DOI: 10.7295/w9cil53358
title: CIL:53358, Drosophila melanogaster, Entire Organism
DOI: 10.7295/w9cil53359
title: CIL:53359, Drosophila melanogaster, Entire Organism
DOI: 10.7295/w9cil53360
title: CIL:53360, Drosophila melanogaster, Entire Organism
DOI: 10.7295/w9cil53361
title: CIL:53361, Drosophila melanogaster, Entire Organism
DOI: 10.21227/pwc1-ab92
title: WIDAR3.0: WiFi-based Activity Recognition Dataset

description: This repository hosts the data and code for paper "Zero-Effort Cross-Domain Gesture Recognition with Wi-Fi" published in ACM MobiSys 2019.This dataset includes the Channel State Information (CSI) data collected from commodity Wi-Fi devices for gestures and Body-coordinate Velocity Profile (BVP) data calculated by the algorithms from the above mentioned paper.Also included in this repository is the data for paper "GaitID: Robust WiFi Based Gait Recognition" published in Springer WASA 2020.Please stay tuned for further updates.Due to technical issues, please access our dataset homepage for download links: http://tns.thss.tsinghua.edu.cn/widar3.0/
DOI: 10.6084/m9.figshare.13096241.v1
title: Look_up_tables.zip

description: This dataset can be used to calculate the direct radiative effects of BC with fractal morphologies.
DOI: 10.6084/m9.figshare.13096241
title: Look_up_tables.zip

description: This dataset can be used to calculate the direct radiative effects of BC with fractal morphologies.
DOI: 10.6084/m9.figshare.12827327.v1
title: Database or optical properties of coated black carbon aggregates

description: Database or optical properties of coated black carbon aggregates
DOI: 10.6084/m9.figshare.12827327
title: Database or optical properties of coated black carbon aggregates

description: Database or optical properties of coated black carbon aggregates
DOI: 10.21227/hf67-qt35
title: WIDAR3.0: WiFi-based Activity Recognition Dataset

description: This repository hosts the data and code for paper "Zero-Effort Cross-Domain Gesture Recognition with Wi-Fi" published in ACM MobiSys 2019.This dataset includes the Channel State Information (CSI) data collected from commodity Wi-Fi devices for gestures and Body-coordinate Velocity Profile (BVP) data calculated by the algorithms from the above mentioned paper.Also included in this repository is the data for paper "GaitID: Robust WiFi Based Gait Recognition" published in Springer WASA 2020.Please stay tuned for further updates.Due to technical issues, please access our dataset homepage for download links: http://tns.thss.tsinghua.edu.cn/widar3.0/
DOI: 10.17632/24rdgtycdr.1
title: Data for: Performance Degradation and Wearing of Electrical Submersible Pump (ESP) with Gas-Liquid-Solid Flow: Experiments and Mechanistic Modeling

description: MTESP mapping 80bpd
DOI: 10.5281/zenodo.4435033
title: NEXUS file describing the taxonomic relationships of the 466 species for which genome sequencing was underway at Tree of Life, Wellcome Sanger Institute, at 31 December 2020

description: This NEXUS file shows the taxonomic relationships of 466 species of eukaryote. The taxonomy derives from the NCBI TaxonomyDB. The species are those for which genome sequencing is underway at the Tree of Life programme, Wellcome Sanger Institute, as of 31st Decemnber 2020. The NEXUS file includes a figtree block generated in FigTree [<strong>https://github.com/rambaut/figtree] </strong>that informs display of the data as a circular tree with species coloured by taxonomic Family, and Families with more than one species represented as triangles. The figure is used in publications and presentations describing the activities of the Tree of Life programme and the projects in which Tree of Life is involved, especially the Darwin Tree of Life project [https://darwintreeoflife.org].
DOI: 10.5281/zenodo.4435032
title: NEXUS file describing the taxonomic relationships of the 466 species for which genome sequencing was underway at Tree of Life, Wellcome Sanger Institute, at 31 December 2020

description: This NEXUS file shows the taxonomic relationships of 466 species of eukaryote. The taxonomy derives from the NCBI TaxonomyDB. The species are those for which genome sequencing is underway at the Tree of Life programme, Wellcome Sanger Institute, as of 31st Decemnber 2020. The NEXUS file includes a figtree block generated in FigTree [<strong>https://github.com/rambaut/figtree] </strong>that informs display of the data as a circular tree with species coloured by taxonomic Family, and Families with more than one species represented as triangles. The figure is used in publications and presentations describing the activities of the Tree of Life programme and the projects in which Tree of Life is involved, especially the Darwin Tree of Life project [https://darwintreeoflife.org].
DOI: 10.5519/qd.18froozm
title: Query on the Natural History Museum Data Portal (data.nhm.ac.uk) (353 records)
DOI: 10.21227/styn-ez53
title: WIDAR3.0: WiFi-based Activity Recognition Dataset

description: This repository hosts the data and code for paper "Zero-Effort Cross-Domain Gesture Recognition with Wi-Fi" published in ACM MobiSys 2019.This dataset includes the Channel State Information (CSI) data collected from commodity Wi-Fi devices for gestures and Body-coordinate Velocity Profile (BVP) data calculated by the algorithms from the above mentioned paper.Also included in this repository is the data for paper "GaitID: Robust WiFi Based Gait Recognition" published in Springer WASA 2020.Please stay tuned for further updates.Due to technical issues, please access our dataset homepage for download links: http://tns.thss.tsinghua.edu.cn/widar3.0/
DOI: 10.5281/zenodo.4435795
title: EAGLE Media Wiki RDF data from Wikibase

description: This is a dump of the triples entered with the Wikibase Extension into the EAGLE Media Wiki for translations. https://wiki.eagle-network.eu/wiki/Main_Page The same data is accessible via the Mediawiki API. It is part of the EAGLE project https://www.eagle-network.eu/. Contributors of the translations are in the data.
DOI: 10.5281/zenodo.4435794
title: EAGLE Media Wiki RDF data from Wikibase

description: This is a dump of the triples entered with the Wikibase Extension into the EAGLE Media Wiki for translations. https://wiki.eagle-network.eu/wiki/Main_Page The same data is accessible via the Mediawiki API. It is part of the EAGLE project https://www.eagle-network.eu/. Contributors of the translations are in the data.
DOI: 10.5281/zenodo.4027947
title: Dataset for English Health-Related Advice Directed to the General Public on Twitter During the Early Spread of COVID-19 [Dataset]

description: Health-related advice directed to the public on twitterprovides insight into the use of social media duringa pandemic. This paper describes our data collection, sampling, and analysis of 44 million tweets in English in March 2020. We make reference to a parallel dataset and analysis of tweets in Arabic during thesame period. The contribution of this paper is a description of our dataset, our coding process to indicate tweets with health related advice, and our analysis and comparisons of the characteristics of the tweets with and without health-related advice. These contributions providethe basis for future research on semi-automated classifiers for health-related advice and efforts to reduce thespread of harmful health advice.
DOI: 10.5281/zenodo.4027946
title: Dataset for English Health-Related Advice Directed to the General Public on Twitter During the Early Spread of COVID-19 [Dataset]

description: Health-related advice directed to the public on twitterprovides insight into the use of social media duringa pandemic. This paper describes our data collection, sampling, and analysis of 44 million tweets in English in March 2020. We make reference to a parallel dataset and analysis of tweets in Arabic during thesame period. The contribution of this paper is a description of our dataset, our coding process to indicate tweets with health related advice, and our analysis and comparisons of the characteristics of the tweets with and without health-related advice. These contributions providethe basis for future research on semi-automated classifiers for health-related advice and efforts to reduce thespread of harmful health advice.
DOI: 10.5281/zenodo.4023275
title: AraHealth: A Dataset for Arabic Health-Related Advice Directed to the General Public on Twitter During the Early Spread of COVID-19 [Dataset]

description: Health-related advice directed to the general public on Twitter provides insight into the use of social media during health emergencies. This paper describes our data collection, sampling, and analysis of 24 million tweets in Arabic in March and early April 2020. We make reference to a parallel dataset and analysis of tweets in English during the same period. The contribution of this paper is a description of our dataset, our coding process to indiciate tweets with health related advice, and our analysis and comparisons of the characteristics of the tweets with and without health-related advice. These contributions provide the basis for future research on semi-automated classifiers for health-related advice and efforts to reduce the spread of harmful health advice.
DOI: 10.5281/zenodo.4023274
title: AraHealth: A Dataset for Arabic Health-Related Advice Directed to the General Public on Twitter During the Early Spread of COVID-19 [Dataset]

description: Health-related advice directed to the general public on Twitter provides insight into the use of social media during health emergencies. This paper describes our data collection, sampling, and analysis of 24 million tweets in Arabic in March and early April 2020. We make reference to a parallel dataset and analysis of tweets in English during the same period. The contribution of this paper is a description of our dataset, our coding process to indiciate tweets with health related advice, and our analysis and comparisons of the characteristics of the tweets with and without health-related advice. These contributions provide the basis for future research on semi-automated classifiers for health-related advice and efforts to reduce the spread of harmful health advice.
DOI: 10.6084/m9.figshare.13363580.v1
title: plastid phylogenetic analysis of mosses

description: concatenated dataset of plastid 81 protein-coding-gene dataset of 28 moss species
DOI: 10.6084/m9.figshare.13502223.v1
title: ASPECT input files (parameters and initial and boundary conditions)

description: # ----------------------------------------------------------------------# Sungho Lee# SEISMOLOGICAL LABORATORY, Seoul National University, South Korea# sungho91@snu.ac.kr or sungho91123@gmail.com# Thses input files were used for aspect in my reasearch project# The publication title is "Origin of seismicty in the Korean Peninsula and implication for intraplate earthqaukes" (in preparation, Dec./2020)# ----------------------------------------------------------------------<br>#### ASPECT input files ##### Case1-1.prm, crustal thikcness variation with laterally uniform temperature# Case1-2.prm, crustal thikcness variation with laterally uniform temperature with traction boundary condition on the western side wall (50 MPa)# Case1-3.prm, crustal thikcness variation with laterally uniform temperature with traction boundary condition on the western side wall (100 MPa)# Case2-1.prm, lithospheric thickness variation with laterally non-uniform temperature (0 - 200 km)# Case2-2.prm, lithospheric thickness variation with laterally non-uniform temperature (0 - 200 km) with traction boundary condition on the western side wall (50 MPa)# Case2-3.prm, lithospheric thickness variation with laterally non-uniform temperature (0 - 200 km) with traction boundary condition on the western side wall (100 MPa)# Case3-1.prm, Full upper mantle structures with laterally non-uniform temperature (0 - 660 km)# Case3-2.prm, Full upper mantle structures with laterally non-uniform temperature (0 - 660 km) with traction boundary condition on the western side wall (50 MPa)# Case3-3.prm, Full upper mantle structures with laterally non-uniform temperature (0 - 660 km) with traction boundary condition on the western side wall (100 MPa)<br>#### data dir. ##### crustal_isostacy.txt, intial guess for topography resulted from Case 1-1. The guess was used Case 1-2 to Case 3-3 for reducing simulation time# initial_material_1.txt, composition model for upper and lower cursts and mantle which is from CRUST1.0 data# initial_temperature_Vs_cr.txt, initial temperature for Case 1-1 to Case 1-3# initial_temperature_Vs_litho.txt, initial temperature for Case 2-1 to Case 2-3# initial_temperature_Vs_FWEA18.txt, initial temperature for Case 3-1 to Case 3-3<br>#### traction dir. ##### traction_case1_50.txt, traction data for Case 1-2# traction_case1_100.txt, traction data for Case 1-3# traction_case2_50.txt, traction data for Case 2-2# traction_case2_100.txt, traction data for Case 2-3# traction_case3_50.txt, traction data for Case 3-2# traction_case3_100.txt, traction data for Case 3-3
DOI: 10.17632/xkz8rfyvdp.1
title: Supplemental Data - van Straalen et al. JAAD; 2021.

description: Supplemental Data - van Straalen et al. The efficacy and tolerability of tetracyclines and clindamycin plus rifampicin for the treatment of hidradenitis suppurativa; results of a prospective European cohort study. JAAD; 2021.
DOI: 10.17632/jvv88yhfmm.1
title: Tithonia rotundifolia as a protein source in New Zealand/Chinchilla weaner rabbit production

description: Proximate analysis of Tithonia rotundifolia was conducted at Fertilizer, Farm Feeds and Remedies Institute laboratory, under the Department of Research and Specialist Services in Harare. The proximate analysis was done on a dry matter basis and the data from the analysis was incorporated in FeedWin for feed formulation. The main aspects considered in proximate analysis being the dry matter content (DM), crude protein content (CP), crude fibre content (CF), ether extract content (EE), nitrogen-free extract content (NFE), calcium content (Ca) and phosphorous content (P), which are important for the diet formulation. The samples were analysed using the procedures of Association of Official Analytical Chemists (A.O.A.C. 2005). For other feed ingredients, the researcher used the standard nutritional composition on FeedWin feed formulation software. FeedWin Interactive v1.01 software was used to formulate the diet. This software ensures the use of nutrient composition in formulating diets. The Tithonia meal was used as an inclusion in the feed, mixed with other ingredients which are maize meal, soybean meal, salt, limestone and mono-calcium-phosphate. These ingredients were used to formulate three diets with 0 %, 10 % and 20 % inclusion levels of the Tithonia meal. The inclusion of Tithonia meal in the diet formulation caused the percentage variation of other ingredients. Thus, becoming a source of variation.Data collected was daily feed intake and weekly weight gain. This data was fed into Microsoft Excel and used to calculate feed conversion efficiency. Before the commencement of the experiment, the weights of the rabbits were taken, using a digital scale for weighing. After this, the rabbits were weighed weekly for weight gain changes. Since the animals were given a predetermined amount of feed, the left-over feed was measured every morning during the feeding trial so as to calculate the feed intake. The feed conversion efficiency was then calculated after the feeding trial. Feed intake was calculated by subtracting the refusals from the feed given. The feed conversion efficiency was then calculated by dividing total feed intake with total weight gain.Statistical Package for Social Sciences (SPSS) also known as Statistical Product and Service Solutions (SPSS) version 20 was used to analyse the data on feed intake, weight gain and feed conversion efficiency. The data was subjected to GLM repeated measures ANOVA for RCBD. Boniferroni’s test was used to separate means. Descriptive statistics were also generated which were presented in form of tables and graphs. Equality of variances was tested using Levene’s test. Wilk’s Lambda’s test was used to assess whether or not there was effect of time or interaction between time and diet.