Comparison of the learning during the relearning phase from the four groups.

A) The learning curves in the relearning phase of the four groups. B) Average learning rate, average learning extent, and average hand movement direction of the whole learning cycles for each group. Positive angle denotes CW direction. Error bars denote SEM.</p

Comparison of the learning during the counter-rotation phase for the four groups.

A) The learning curves in the counter rotation phase of the four groups. B) Average learning rate, average learning extent, and average hand movement direction of the whole learning cycles of each group. Note the opposite number of participants’ actual hand movement direction is calculated here. Positive angle denotes CW direction. Error bars denote SEM. *p < 0.05.</p

Experimental setup and designs.

A. Side view of the experimental setup. B. The illustration of the four possible targets and the perturbation of CCW visuomotor rotation. When the participant moves their hand to the top-right target (the dashed arrow), the cursor represented by the black circle was rotated 30° CCW to the hand position (the solid arrow). Then the hand gradually rotates clockwise over trials to bring the cursor to land on the target (the grey arrows). C. Eight phases of trials: baseline, initial rotation learning, initial no-vision, initial washout, counter-rotation, second washout, relearning, and second no-vision. The positive angle indicates CCW rotation. The dashed horizontal lines during no-vision phases indicate no visual feedback. The dashed and solid arrows denote the trajectory of hand and cursor movement, respectively. Shaded gray: participants received punishment (P), reward (R), combination of punishment and reward (PR) or random number (C) during initial rotation learning phase.</p

Learning data for all the 8 phases for the <i>Control</i> group.

The grey lines denote the perfect hand movement direction to counter the visual perturbation. The dashed lines denote no visual cursor feedback. Positive angle denotes CW direction. Error bars denote SEM.</p

Comparison of the learning during the initial rotation learning phase from four different groups.

A) The learning curves during the initial rotation learning phase of the four groups. Inset illustrates the score curves for the three motivational groups. B) Average learning rate, average learning extent, and average hand movement direction of the whole learning cycles of each group. Positive angle denotes CW direction. Error bars denote SEM. *p p < 0.01.</p

DataSheet1_Large-Scale Heterogeneous Computing for 3D Deterministic Particle Transport on Tianhe-2A Supercomputer.zip

Scalable parallel algorithm for particle transport is one of the main application fields in high-performance computing. Discrete ordinate method (Sn) is one of the most popular deterministic numerical methods for solving particle transport equations. In this paper, we introduce a new method of large-scale heterogeneous computing of one energy group time-independent deterministic discrete ordinates neutron transport in 3D Cartesian geometry (Sweep3D) on Tianhe-2A supercomputer. In heterogeneous programming, we use customized Basic Communication Library (BCL) and Accelerated Computing Library (ACL) to control and communicate between CPU and the Matrix2000 accelerator. We use OpenMP instructions to exploit the parallelism of threads based on Matrix 2000. The test results show that the optimization of applying OpenMP on particle transport algorithm modified by our method can get 11.3 times acceleration at most. On Tianhe-2A supercomputer, the parallel efficiency of 1.01 million cores compared with 170 thousand cores is 52%.</p

Isopiestic Determination of Unsaturated and NaNO₃-Saturated H₂O + NaNO₃ + Y(NO₃)₃ + La(NO₃)₃ Systems and Representation with the Pitzer Model, Zdanovskii–Stokes–Robinson Rule, and Ideal–Like Solution Model

Isopiestic osmotic coefficients were determined for the unsaturated and NaNO3-saturated H2O + NaNO3 + Y(NO3)3 + La(NO3)3 system up to the maximum ionic strength I = 22 mol·kg–1 at 298.15 K. The experimental results were represented by a modified Pitzer model (J. Phys. Chem. B 2007, 111, 3704). The isopiestic data were found to closely fit a modified Zdanovskii–Stokes– Robinson model for the unsaturated system and Wang’s ideal–like solution model (Ber. Bunsen–Ges. Phys. Chem. 1998, 102, 1045) for the NaNO3-saturated quaternary system, respectively, which indicate that there is nonzero interchange energy between NaNO3 and each rare earth nitrate and a zero interchange energy between the unlike rare earth nitrates. The isopiestic osmotic coefficient measurements and the Pitzer model representations for the NaNO3-saturated quaternary systems are in good agreement with the ideal–like solution model

DataSheet_1_Quantitative Acetylomics Revealed Acetylation-Mediated Molecular Pathway Network Changes in Human Nonfunctional Pituitary Neuroendocrine Tumors.zip

Acetylation at lysine residue in a protein mediates multiple cellular biological processes, including tumorigenesis. This study aimed to investigate the acetylated protein profile alterations and acetylation-mediated molecular pathway changes in human nonfunctional pituitary neuroendocrine tumors (NF-PitNETs). The anti-acetyl antibody-based label-free quantitative proteomics was used to analyze the acetylomes between NF-PitNETs (n = 4) and control pituitaries (n = 4). A total of 296 acetylated proteins with 517 acetylation sites was identified, and the majority of which were significantly down-acetylated in NF-PitNETs (p<0.05 or only be quantified in NF-PitNETs/controls). These acetylated proteins widely functioned in cellular biological processes and signaling pathways, including metabolism, translation, cell adhesion, and oxidative stress. The randomly selected acetylated phosphoglycerate kinase 1 (PGK1), which is involved in glycolysis and amino acid biosynthesis, was further confirmed with immunoprecipitation and western blot in NF-PitNETs and control pituitaries. Among these acetylated proteins, 15 lysine residues within 14 proteins were down-acetylated and simultaneously up-ubiquitinated in NF-PitNETs to demonstrate a direct competition relationship between acetylation and ubiquitination. Moreover, the potential effect of protein acetylation alterations on NF-PitNETs invasiveness was investigated. Overlapping analysis between acetylomics data in NF-PitNETs and transcriptomics data in invasive NF-PitNETs identified 26 overlapped molecules. These overlapped molecules were mainly involved in metabolism-associated pathways, which means that acetylation-mediated metabolic reprogramming might be the molecular mechanism to affect NF-PitNET invasiveness. This study provided the first acetylomic profiling and acetylation-mediated molecular pathways in human NF-PitNETs, and offered new clues to elucidate the biological functions of protein acetylation in NF-PitNETs and discover novel biomarkers for early diagnosis and targeted therapy of NF-PitNETs.</p

Additional file 1 of The association between schizophrenia and white blood cells count: a bidirectional two-sample Mendelian randomization study

Supplementary Material 1: Supplementary Tables 5–1

Effects of Lignins on Antioxidant Biodiesel Production in Supercritical Methanol

Effects of Lignins on Antioxidant Biodiesel Production in Supercritical Methano