RT (in ms, bars) and ACC (in %, line) for the effect of congruency task convergence, with 95% confidence interval. by Marcel F. Hinss (14675457)

Subjects:

Particle size distribution chart of 10-micron iron oxide particles. by Yang Li (7082)

Subjects:

Effect of the type of switch trial on performance. by Marcel F. Hinss (14675457)

Subjects:

Evolution of personal factors in the different categories in the FRM social sports schools and in the association football clubs. by Gema Ortega Vila (19870900)

Subjects:

Graph of temperature rise variation for test groups with different particle sizes at two concentrations. by Yang Li (7082)

Subjects:

Parameter diagram for pit features on the specimen surface (a) Volume (b) Surface Area (c) Depth (d) Cross-sectional area. by Yang Li (7082)

Subjects:

Tunel detection of myocardial apoptosis. by Qingqing Hao (5464070)

Subjects:

Cardiomyocyte apoptosis rate in the CCM group. by Qingqing Hao (5464070)

Subjects:

The primer sequences of the genes used in the RT-PCR. by Qingqing Hao (5464070)

Subjects:

Fig 2 - by Qingqing Hao (5464070)

Subjects:

Cardiomyocyte apoptosis rate in the Sham group. by Qingqing Hao (5464070)

Subjects:

Cardiomyocyte apoptosis rate in the three groups. by Qingqing Hao (5464070)

Subjects:

Changes in mRNA expression of Caspase-3, ALDH2, Bcl-2, Bax and Bcl-2/Bax in three groups. by Qingqing Hao (5464070)

Subjects:

Apoptosis ratio in three groups. by Qingqing Hao (5464070)

Subjects:

Comparison of myocardial LC3 immunofluorescence staining of three groups (×400, scale bar = 10μm). by Qingqing Hao (5464070)

Subjects:

S1 File - by Qingqing Hao (5464070)

Subjects:

Cardiomyocyte apoptosis rate in the HF group. by Qingqing Hao (5464070)

Subjects:

Comparison of Beclin1, P62 and LC3B(II/I) protein expression levels in three groups. by Qingqing Hao (5464070)

Subjects:

Fig 3 - by Qingqing Hao (5464070)

Subjects:

A Locally Linear Dynamic Strategy for Manifold Learning. by Weifan Wang (4669081)

“…For 10-30% noise, where the Hebbian network employs a local linear transform, learning selectively increases signal direction alignment (blue) while simultaneously decreasing noise direction alignment (orange). …”