We used a constant comparative and iterative approach, in which we compared preliminary categories with the research findings, raw data excerpts, and co-investigators' interpretations of the studies.
In this report, we present the results of the MOODINFLAME study, in which we compared euthymic BD patients with HC.
We used a murine (C57Bl/6 mice) ischemic hind limb model in which we compared LDPI with the clinically used 99mTc-sestamibi SPECT perfusion imaging (n = 7).
We designed six experiments in which we compared the amplitudes of anticipatory, express and regular saccades, for various conditions of target eccentricities, target direction, and predictability.
We show the effectiveness of these principles via a significant-scale user study in which we compared an interface developed based on these principles with a traditional one.
We conducted a prospective observational study in which we compared the use of US versus conventional chest radiograph (CCR) in patients receiving a CVC for the detection of post insertion complications and to confirm proper CVC position.
Thus, we present a study in which we compared a set of commercialised smartphone launchers with an adapted UI and ATs for older adults by means of heuristic evaluation.
In the third case, in which we compared the β-lactalbumin and hen egg-white lysozyme protein homologues, we successfully eliminated differences between the folding kinetics of the two systems by suppressing electrostatic interactions, supporting previously reported findings.
First, we conducted a field experiment in which we compared recruitment of epibiota to concrete plates with either C. gigas, wild-stock S. glomerata, selectively bred S. glomerata or glue (control).
In this paper we describe the results of an end-user study in which we compared two basic interface designs for the layout of multiple options: a simple hierarchy and a single layer grid.
We carried out concordance analysis in which we compared the mRNA-seq data to expression data from the same samples obtained using the NanoString cancer reference gene set data (see below).
