(Color online) <i>AUC</i>_<i>s</i> and <i>τ</i> of the EigenRank algorithm, IBeta method and Vote Aggregation method for the synthetic networks: (a, b) in the random rating attack case when |<i>E</i>| = 7.2 × 10⁵; (c, d) in the malicious rating attack case when |<i>E</i>| = 7.2 × 10⁵; (e, f) in the random rating attack case when |<i>E</i>| = 1.08 × 10⁶; (g, h) in the malicious rating attack case when |<i>E</i>| = 1.08 × 10⁶.

The parameter ρ denotes the ratio of random/malicious ratings. It can be seen that both the AUCs and τ of the EigenRank algorithm exceed their counterparts in the IBeta method and Vote Aggregation method with different ρ and |E|. The results are averaged over 50 independent realizations. The error bars are the corresponding standard deviations.</p

Descriptor table of letters used in this paper.

Descriptor table of letters used in this paper.</p

(Color online) The effectiveness of the EigenRank algorithm under random rating attack for the MovieLens data set: (a) the AUC values <i>AUC</i>_<i>e</i>; (b-c) Δ<i>AUC</i>_<i>e</i>, the comparison of <i>AUC</i>_<i>e</i> between EigenRank algorithm and IBeta method (b), Vote Aggregation method (c); (d) the recall <i>R</i>_<i>c</i>(<i>L</i>); (e-f) Δ<i>R</i>_<i>c</i>(<i>L</i>), the comparison of recall between EigenRank algorithm and IBeta method (e), Vote Aggregation method (f).

The parameters q and p denote the ratio and the activity of spammers, respectively. q ranges from 0.025 to 0.5 in increments of 0.025 and p ranges from 0.01 to 0.2 in increments of 0.01. One observes both the AUCe and Rc(L) of the EigenRank algorithm exceed the ones obtained by the IBeta method and Vote Aggregation method for different (p, q).</p

S1 Appendix -

(PDF)</p

(Color online) The effectiveness of the EigenRank algorithm under random rating attack for the Netflix data set: (a) the AUC values <i>AUC</i>_<i>e</i>; (b-c) Δ<i>AUC</i>_<i>e</i>, the comparison of <i>AUC</i>_<i>e</i> between EigenRank algorithm and IBeta method (b), Vote Aggregation method (c); (d) the recall <i>R</i>_<i>c</i>(<i>L</i>); (e-f) Δ<i>R</i>_<i>c</i>(<i>L</i>), the comparison of recall between EigenRank algorithm and IBeta method (e), Vote Aggregation method (f).

The parameters q and p denote the ratio and the activity of spammers, respectively and L = q|U|. q ranges from 0.015 to 0.3 in increments of 0.015 and p ranges from 0.005 to 0.1 in increments of 0.005. One observes that both the AUCe and Rc(L) of the EigenRank algorithm exceed those of the IBeta method and Vote Aggregation method for different (p, q).</p

Anisotropic Paramagnetic Properties of Metallofullerene Confined in a Metal–Organic Framework

Paramagnetic metallofullerenes have a spherical molecular structure and stable unpaired spin protected by a fullerene cage and have potential applications in quantum information processing, etc. For endohedral azafullerene Y₂@C₇₉N, the N atom on the cage endows the molecule with unpaired spin and is proposed to induce the molecule orientation within the MOF pore via host–guest interaction. Angular-dependent EPR spectroscopy was employed on the Y₂@C₇₉N⊂MOF-177 complex to detect the anisotropic paramagnetic properties. These results experimentally confirmed the trend of molecule orientation of Y₂@C₇₉N within MOF-177 under certain conditions, which also induces the presence of several conformers of Y₂@C₇₉N. The additional EPR splittings in Y₂@C₇₉N⊂MOF-177 are proposed to originate from partially disordered molecules as well as the N-coupling of Y₂@C₇₉N upon implanting it into the MOF-177 pore. The N-defect on the fullerene cage of Y₂@C₇₉N is expected to be utilized as an anchor to build a three-dimensional spin array within MOF matrix

Natural light intensity at the bottom of the tanks during the diel cycle (N = 3, mean ± SE).

<p>Natural light intensity at the bottom of the tanks during the diel cycle (N = 3, mean ± SE).</p

PCR primers used in the study.

<p>PCR primers used in the study.</p

Effect of covering behavior on relative expression of <i>PAX 6</i> in <i>Strongylocentrotus intermedius</i> under photic and aphotic conditions.

<p>Y: covering material present. N: covering material not present. (N = 4, mean ± SE).</p

BCN Nanotubes as Highly Sensitive Torsional Electromechanical Transducers

Owing to their mechanically tunable electronic properties, carbon nanotubes (CNTs) have been widely studied as potential components for nanoelectromechanical systems (NEMS); however, the mechanical properties of multiwall CNTs are often limited by the weak shear interactions between the graphitic layers. Boron nitride nanotubes (BNNTs) exhibit a strong interlayer mechanical coupling, but their high electrical resistance limits their use as electromechanical transducers. Can the outstanding mechanical properties of BNNTs be combined with the electromechanical properties of CNTs in one hybrid structure? Here, we report the first experimental study of boron carbonitride nanotube (BCNNT) mechanics and electromechanics. We found that the hybrid BCNNTs are up to five times torsionally stiffer and stronger than CNTs, thereby retaining to a large extent the ultrahigh torsional stiffness of BNNTs. At the same time, we show that the electrical response of BCNNTs to torsion is 1 to 2 orders of magnitude higher than that of CNTs. These results demonstrate that BCNNTs could be especially attractive building blocks for NEMS