Ahmed Ryan (pizzahair9)

This dataset is related to the article entitled "Left Common Carotid Artery Biomechanical Properties in Individuals over 80 years Women Have Stiffer Vessels" published in Annals of Vascular Surgery in August 2020 [1].Meta-analysis, a systematic statistical examination that combines the results of several independent studies, has the potential of obtaining problem- and implementation-independent knowledge and understanding of metaheuristic algorithms, but has not yet been applied in the domain of operations research. To illustrate the procedure, we carried out a meta-analysis of the adaptive layer in adaptive large neighborhood search (ALNS). Although ALNS has been widely used to solve a broad range of problems, it has not yet been established whether or not adaptiveness actually contributes to the performance of an ALNS algorithm. A total of 134 studies were identified through Google Scholar or personal e-mail correspondence with researchers in the domain, 63 of which fit a set of predefined eligibility criteria. The results for 25 different implementations of ALNS solving a variety of problems were collected and analyzed using a random effects model. This dataset contains a detailed comparison of ALNS with the non-adaptive variant per study and per instance, together with the meta-analysis summary results. The data enable to replicate the analysis, to evaluate the algorithms using other metrics, to revisit the importance of ALNS adaptive layer if results from more studies become available, or to simply consult the ready-to-use formulas in the summary file to carry out a meta-analysis of any research question. The individual studies, the meta-analysis and its results are described and interpreted in detail in Renata Turkeš, Kenneth Sörensen, Lars Magnus Hvattum, Meta-analysis of Metaheuristics Quantifying the Effect of Adaptiveness in Adaptive Large Neighborhood Search, in the European Journal of Operational Research.Serum, urine and tissue from a rat model of chronic kidney disease (CKD) were analysed using nuclear magnetic resonance (NMR) spectroscopy-based metabolomics methods, and compared with samples from sham operated rats. Both urine and serum were sampled at multiple timepoints, and the results have been reported elsewhere (https//doi.org/10.1007/s11306-019-1569-3[1]). The data could be useful to researchers working with human CKD or rat models of the disease. In addition, several different types of NMR spectra were recorded, including 1D NOESY, CPMG, and 2D J-resolved spectra, and the data could be useful for method comparison and algorithm development, both in terms of NMR spectroscopy and multivariate analysis.The global crisis prevailing in the wake of the spread of COVID-19 has raised several speculations about the impact of the lockdown on the mental health of people. The dataset presented here is the assessment of the psychological distress experienced by people in India following the implementation of lockdown as a measure to curtail the spread of the coronavirus. The data was collected through a survey conducted by employing an online questionnaire assessing the socio-demographic information (9-items) as well as the administration of the short version of the General Health Questionnaire (GHQ-12 items) originally developed by Goldberg (1972). The period of data collection is between 9th April 2020 and 20th April 2020 where a total of 1,894 responses were obtained. The Google forms containing the questionnaire of the study were shared publicly through emails and via the social media forum like WhatsApp and Facebook. Thereby, those who took the initiative to fill-up the responses were included as the survey participants. Thus, the final sample had participants representing 17 states and Union territories of India. The entire dataset is stored in a Microsoft Excel Worksheet (.xls) and the questionnaire is attached as a supplementary file. The data is beneficial for the timely assessment of the nature and degree