Filter Results
2725892 results
Raw data for mitochondrial respiration and enzymatic activity experiments involving red blood cells from zebra finches.
Data Types:
  • Tabular Data
  • Dataset
Table S1 List of macro-benthic species returned to the study area, indicating their presence (+) in the three periods considered: Pre-Industrial (Pre-IND; 1850-1910); Industrial (IND; 1911-1991) and Post-Industrial (post-IND; 1992-current). Table S2. References list of the literature from which the species in the check-list have been documented in the studied area.
Data Types:
  • Tabular Data
  • Dataset
  • Document
Physical properties and group compositions, n-alkanes and isoprenoids, tricyclic terpanes, pentacyclic terpanes and steranes of the sapmles.
Data Types:
  • Tabular Data
  • Dataset
Pore structure parameters from MICP tests and core routine analysis including helium porosity, air permeability and density.
Data Types:
  • Tabular Data
  • Dataset
The file Research Data includes the hydrogeological data, CBM production data, PCA data, cluster analysis data, NMR data, and gas-water two-phase permeability data of coal samples.
Data Types:
  • Tabular Data
  • Dataset
Data used for preparation of figures in the manuscript and a particular rate constants calculated from kinetic runs.
Data Types:
  • Tabular Data
  • Dataset
An introduction of the sediments used for the determination of absolute diatom abundance and the ADA estimates of these sediment subsamples are provided here.
Data Types:
  • Tabular Data
  • Dataset
Total 200 participants, 100 male and 100 female were enrolled according to inclusion and exclusion criteria. The Inclusion criteria were: apparently healthy males and females, age between 19 to 30 years old and agree to participate. Exclusion criteria were: pregnancy, lactation, patients with chronic diseases as arthritis, CVD, T2DM, hypothyroidism, hypertension, and intake of drugs that can affect weight e.g. corticosteroids, anti-depressive medications and insulin. A convenient sample was chosen for selection of enrolled participants, mainly from Taibah University as well as, graduated students in addition to students’ relatives and friends. The questionnaire concerned with demographic data, family history of obesity, physical activity level, and the age of introduction of olive oil in the dietary pattern was filled by face to face interview. Anthropometric measurements were obtained by trained team based on a standardized procedure. Using the World Health Organization (WHO) criteria to define BMI categories (WHO, 1999). A BMI result of less than 18.5kg/m2 is considered underweight, 18.5-24.9 kg/m2 is normal, 25-29.9kg/m2 is overweight, while 30kg/m2 and above is obese. Waist circumference was measured using flexible measuring tape. The Waist circumference cut-offs based on ethnic specific values for European, Sub-Saharan African, Eastern Mediterranean and Middle Eastern (Arab) which is >94 centimeters for men and >80 centimeters for women. Standardized methods were used for measurements. The weight was measured using electronic weight scale, while the height was measured using a stadiometer. Regarding Waist circumference measure, participants were asked to stand with back straight. Heavy clothing was removed from the waist line. The tape was aligned at the top of the hip bone (iliac crest) parallel with the edge of the last palpable rib (nearly 2 centimeters above the navel). The waist measure was taken at the end of a normal expiration and approximated to the nearest 0.5 cm. In accordance to WC definition, exclusion was done for obese and underweight participants (WHO, 2008). Detailed 24-hours recall were taken for two days and the mean level was calculated. Describing dietary intake with a special emphasis on olive oil consumption. Total olive oil consumption per day included green and black olives intake. Each three olives contain one gram of olive oil according to Diet Organizer analysis. Nutritional supplement intake was considered in the diet analysis. References: WHO. (1999). WHO consultation on obesity Obesity : preventing and managing the global epidemic : report of a WHO consultation. Retrieved from Geneva, Switzerland: http://apps.who.int/bmi/index.jsp?introPage=intro_3.html WHO. (2008). Waist circumference and waist-hip ratio: report of a WHO expert consultation. Retrieved from https://www.who.int/nutrition/publications/obesity/WHO_report_waistcircumference_and_waisthip_ratio/en/
Data Types:
  • Tabular Data
  • Dataset
Objective: Intra-articular corticosteroid (IAS) injections are often used for the immediate relief of pain and inflammation in the joint of psoriatic arthritis (PsA) patients. However, studies identifying factors that can predict response to IAS injections are lacking. We aimed to assess the usefulness of serine proteinase activity measurements in PsA synovial fluid (SF) samples obtained at the time of injection in predicting clinical response. Methods: PsA patients with available SF samples from the knee joint were identified from the University of Toronto PsA cohort. Clinical response was defined as an absence of tenderness or swelling in the injected joint at the first post-injection visit, at either 3 or 6 months. Proteinase activity was determined by measuring cleavage of fluorogenic tri-peptide substrates for trypsin-like (VPR-AMC and VLK-AMC) and chymotrypsin-like (AAPF-AMC) serine proteinases. Generalized estimating equation (GEE) models were used to investigate which factors were associated with response. Results: A total of 32 patients with 60 injected joints and data available for follow-up at 3 or 6 months were included in the analysis, with 25 (41.7%) injected joints resulting in clinical response. Age, sex, active joint count, medications and serine proteinase activity at the time of injection were included as covariates. Only treatment with biologics was significantly associated with response at 3 or 6 months in the multivariate reduced model (OR 3.02, p = 0.027). Conclusion: We could not demonstrate an association between SF serine proteinase activity and response to IAS injection. Biologic agents significantly improve the likelihood of achieving clinical response.
Data Types:
  • Tabular Data
  • Dataset
The datasets are part of the study titled "A web-based Delphi multi-criteria group decision-making framework for renewable energy project development processes." The study aims to outline and implement the web-based Delphi Multi-criteria Group Decision Making (Delphi-MGDM) Framework, which is intended to facilitate top-level group decision-making for renewable energy project development and long-term strategic direction setting. The datasets include: (1) the weights of criteria obtained from judgments of the experts, (2) the summary of criteria scores, (3) the comparison table dataset, and (4) the full report of the Visual PROMETHEE. “Criteria Weighing Dataset” is obtained from the judgment of experts using the AHP-Online System created by Klaus D. Goepel (available at https://bpmsg.com/ahp/ahp.php). On a pairwise comparison basis, we asked the experts to make their opinion on four (4) criteria and then the sixteen (16) sub-criteria in three rounds. The group weights after the third round are considered the final weights of criteria and sub-criteria. To rank RES using MCDA, we used the data from the literature and the Philippines’ DOE for all ten quantitative sub-criteria. However, there are six qualitative sub-criteria, so we asked the opinion of experts on how solar, wind, biomass, and hydropower are performing in each criterion based on their knowledge and expertise. This time, we used a self-derived questionnaire and as a summary of this process, we produced the “Scoring of Options Dataset.” We got the average, minimum and maximum values of the scores to make data for the ranking in three cases (realistic, pessimistic, and optimistic). "Comparison table" dataset is composed of comparison tables for the three cases. Table A reflects the data for realistic case in which we use the averages of the qualitative inputs from experts, the averages of quantitative data obtained in ranges, and the actual value of data not given in ranges. Table B reflects the data for the optimistic case. For qualitative data, we used the minimum value of the sub-criteria to be minimized and maximum value for sub-criteria to maximized. For quantitative data in ranges, we used the minimum value of cost sub-criteria and maximum value of benefit sub-criteria. We estimated fictitious data for some quantitative data not given in ranges. Table C reflects the data for the pessimistic case. We used the same concept with Table B, but with opposite choices. For instance, we used the maximum value of cost sub-criteria and minimum value of benefit sub-criteria for quantitative data. Finally, we used Visual PROMETHEE (available at http://www.promethee-gaia.net/vpa.html) to rank renewable energy sources. The "Visual PROMETHEE Full Report" dataset is the actual report exported from the Visual PROMETHEE application – containing a partial and complete ranking of RES.
Data Types:
  • Tabular Data
  • Dataset
  • Document