Simultaneous coupling of phototaxis and electrotaxis in Volvox algae

In nature, living creatures are affected by several stimuli simultaneously. The response of living creatures to stimuli is called taxis. In order to reveal the principles of taxis behavior in response to complex stimuli, we simultaneously applied photostimulation and electric stimulation perpendicularly to a Volvox algae solution. The probability distribution of the swimming direction showed that a large population of swimming cells moved in a direction that was the result of the composition of phototaxis and electrotaxis. More surprisingly, we uncovered the coupling of signs of taxis, i.e., coupling of phototaxis and electrotaxis induced positive electrotaxis, which did not emerge in the single stimulation experiments. We qualitatively explained the coupling of taxis based on the polarization of the swimming cells induced by the simultaneous photo- and electric stimulation

Role of hydrophobic interaction in hapten-antibody binding

The precipitation reaction of bovine serum albumin coupled with p-azophenylleucine with homologous antibody was inhibited by several structurally related haptens. The isobutyl group substituent on alpha-carbon atom of the leucine residue contributed more than -5.8 Kcal/mol to the free energy of binding. This value was consistent with the free energy change expected from the transfer of n-butane from an aqueous environment to liquid n-butane. The observed contribution was explained, in terms of the hydrophobic interaction of the isobutyl group with the antigen binding site of the antibody molecule. These results were also compared with other hapten-antibody systems.</p

Cosmic Star Formation Activity at z=2.2 Probed by H-alpha Emission Line Galaxies

We present a pilot narrow-band survey of H-alpha emitters at z=2.2 in the Great Observatories Origins Deep Survey North (GOODS-N) field with MOIRCS instrument on the Subaru telescope. The survey reached a 3 sigma limiting magnitude of 23.6 (NB209) which corresponds to a 3 sigma limiting line flux of 2.5 x 10^-17 erg s^-1 cm^-2 over a 56 arcmnin^2 contiguous area (excluding a shallower area). From this survey, we have identified 11 H-alpha emitters and one AGN at z=2.2 on the basis of narrow-band excesses and photometric redshifts. We obtained spectra for seven new objects among them, including one AGN, and an emission line above 3 sigma is detected from all of them. We have estimated star formation rates (SFR) and stellar masses (M_star) for individual galaxies. The average SFR and M_star is 27.8M_solar yr^-1 and 4.0 x 10^10M_solar, respectivly. Their specific star formation rates are inversely correlated with their stellar masses. Fitting to a Schechter function yields the H-alpha luminosity function with log L = 42.82, log phi = -2.78 and alpha = -1.37. The average star formation rate density in the survey volume is estimated to be 0.31M_solar yr^-1Mpc^-3 according to the Kennicutt relation between H-alpha luminosity and star formation rate. We compare our H-alpha emitters at z=2.2 in GOODS-N with narrow-band line emitters in other field and clusters to see their time evolution and environmental dependence. We find that the star formation activity is reduced rapidly from z=2.5 to z=0.8 in the cluster environment, while it is only moderately changed in the field environment. This result suggests that the timescale of galaxy formation is different among different environments, and the star forming activities in high density regions eventually overtake those in lower density regions as a consequence of "galaxy formation bias" at high redshifts.Comment: Accepted for publication in PASJ Subaru Special Issue, 11 pages, 10 figure

Think Globally, Embed Locally - Locally Linear Meta-embedding of Words

Distributed word embeddings have shown superior performances in numerous Natural Language Processing (NLP) tasks. However, their performances vary significantly across different tasks, implying that the word embeddings learnt by those methods capture complementary aspects of lexical semantics. Therefore, we believe that it is important to combine the existing word embeddings to produce more accurate and complete \emph{meta-embeddings} of words. For this purpose, we propose an unsupervised locally linear meta-embedding learning method that takes pre-trained word embeddings as the input, and produces more accurate meta embeddings. Unlike previously proposed meta-embedding learning methods that learn a global projection over all words in a vocabulary, our proposed method is sensitive to the differences in local neighbourhoods of the individual source word embeddings. Moreover, we show that vector concatenation, a previously proposed highly competitive baseline approach for integrating word embeddings, can be derived as a special case of the proposed method. Experimental results on semantic similarity, word analogy, relation classification, and short-text classification tasks show that our meta-embeddings to significantly outperform prior methods in several benchmark datasets, establishing a new state of the art for meta-embeddings

Learning Linear Transformations between Counting-based and Prediction-based Word Embeddings

Despite the growing interest in prediction-based word embedding learning methods, it remains unclear as to how the vector spaces learnt by the prediction-based methods differ from that of the counting-based methods, or whether one can be transformed into the other. To study the relationship between counting-based and prediction-based embeddings, we propose a method for learning a linear transformation between two given sets of word embeddings. Our proposal contributes to the word embedding learning research in three ways: (a) we propose an efficient method to learn a linear transformation between two sets of word embeddings, (b) using the transformation learnt in (a), we empirically show that it is possible to predict distributed word embeddings for novel unseen words, and (c) empirically it is possible to linearly transform counting-based embeddings to prediction-based embeddings, for frequent words, different POS categories, and varying degrees of ambiguities

Thermospermine suppresses auxin-inducible xylem differentiation in Arabidopsis thaliana

Thermospermine, a structural isomer of spermine, is synthesized by a thermospermine synthase designated ACAULIS5 (ACL5). Thermospermine-deficient acl5 mutant of Arabidopsis thaliana shows severe dwarfism and excessive xylem differentiation. By screening for compounds that affect xylem differentiation in the acl5 mutant, we identified auxin analogs that remarkably enhanced xylem vessel differentiation in the acl5 mutant but not in the wild type. The xylem-inducing effect of auxin analogs was clearly suppressed by thermospermine, indicating that auxin-inducible xylem differentiation is normally limited by thermospermine. Here, we further characterized xylem-inducing effect of auxin analogs in various organs. Auxin analogs promoted protoxylem differentiation in roots and cotyledons in the acl5 mutant. Our results indicate that the opposite action between thermospermine and auxin in xylem differentiation is common in different organs and also suggest that thermospermine might be required for the suppression of protoxylem differentiation