Kinetics of chain collapse in dilute polymer solutions: Molecular weight and solvent dependences

The molecular weight and solvent dependences of the characteristic time of chain collapse were studied for poly(methyl methacrylate) (PMMA) of the molecular weight Mw =6.4× 106 and 1.14× 107 in pure acetonitrile (AcN) and in the mixed solvent of AcN+water (10 vol %). The size of PMMA chains was measured as a function of the time after the quench by static light scattering and the chain collapse processes were expressed by the plot of the expansion factor α2 vs ln t. The chain collapse in the mixed solvent AcN+water (10 vol %) was found to occur much faster than that in pure AcN, though the measurement of the former collapse process required several hours. In order to make a comparison between the rates of chain collapses, the fast chain collapse process was superposed on the slow one by scaling the time of the fast process as γt. The scale factor γ was determined by comparing the chain collapse processes of nearly the same equilibrium expansion factor with each other. Accordingly, the superposition of the collapse for Mw =6.4× 106 on that for Mw =1.14× 107 yielded γm =4.0±0.6 for the process in AcN+water and 5.5±0.6 in AcN. The superposition of the chain collapse process in AcN+water on that in AcN yielded γs =9.5±1.4 for Mw =6.4× 106 and 12.0±1.8 for Mw =1.14× 107. This analysis suggests that γm and γs are constant independent of each other. Thus, by assuming the molecular weight dependence of γm ∼ Mz, the characteristic time τexp of chain collapse was conjectured as τexp ∼κ Mz, where κ reflects the nature of solvent species. The ratio of κ for PMMA in AcN to that in AcN+water is given by γs. The exponent was estimated to be z=2.4±0.7 for AcN+water and 3.0±0.7 for AcN. These values are compatible with the theoretical prediction z=3 based on a phenomenological model, though the observed characteristic times are longer by several orders of magnitude than those of the theoretical prediction

Revisiting a kNN-based Image Classification System with High-capacity Storage

In existing image classification systems that use deep neural networks, the knowledge needed for image classification is implicitly stored in model parameters. If users want to update this knowledge, then they need to fine-tune the model parameters. Moreover, users cannot verify the validity of inference results or evaluate the contribution of knowledge to the results. In this paper, we investigate a system that stores knowledge for image classification, such as image feature maps, labels, and original images, not in model parameters but in external high-capacity storage. Our system refers to the storage like a database when classifying input images. To increase knowledge, our system updates the database instead of fine-tuning model parameters, which avoids catastrophic forgetting in incremental learning scenarios. We revisit a kNN (k-Nearest Neighbor) classifier and employ it in our system. By analyzing the neighborhood samples referred by the kNN algorithm, we can interpret how knowledge learned in the past is used for inference results. Our system achieves 79.8% top-1 accuracy on the ImageNet dataset without fine-tuning model parameters after pretraining, and 90.8% accuracy on the Split CIFAR-100 dataset in the task incremental learning setting.Comment: 16 pages, 7 figures, 6 table

Auto-tracking camera for dry-box laparoscopic training

While laparoscopic surgery is less invasive than open surgery and is now common in various medical fields, laparoscopic surgery often requires more time for the operator to achieve mastery. Dry box training is one of the most important methods for developing laparoscopic skill. However, the camera is usually fixed to a particular point, which is different from practical surgery, during which the operational field is constantly adjusted by an assistant. Therefore, we introduced a camera for dry box training that can be moved by surgeons as desired by using computer vision. By detecting the ArUco marker, the camera attached onto the servomotor successfully tracked the forceps automatically. This system could easily be modified and become operable by a foot switch or voice, and collaborations between surgeons and medical engineers are expected

Subaru Deep Survey V. A Census of Lyman Break Galaxies at z=4 and 5 in the Subaru Deep Fields: Photometric Properties

(abridged) We investigate photometric properties of Lyman Break Galaxies (LBGs) at z=3.5-5.2 based on large samples of 2,600 LBGs detected in deep (i'~27) and wide-field (1,200 arcmin^2) images taken in the Subaru Deep Field (SDF) and the Subaru/XMM Deep Field (SXDF). The selection criteria for the LBG samples are examined with 85 spectroscopically identified objects and by Monte Carlo simulations. We find in the luminosity functions of LBGs (i) that the number density of bright galaxies (M_{1700}<-22; corresponding to SFR_{corr}>100 Msolar yr^{-1}) decreases significantly from z=4 to 5 and (ii) that the faint-end slope of the luminosity function may become steeper towards higher redshifts. We estimate dust extinction of z=4 LBGs with M<M^* from UV slopes, and obtain E(B-V)=0.15+/-0.03 as the mean value. The dust extinction remains constant with apparent luminosity, but increases with intrinsic luminosity. We find no evolution in dust extinction between LBGs at z=3 and 4. We investigate the evolution of UV-luminosity density at 1700A, rho, and find that rho does not significantly change from z=3 to z=5, i.e., rho(z=4)/rho(z=3)=1.0+/-0.2 and rho(z=5)/rho(z=3)=0.8+/-0.4, thus the cosmic star-formation rate (SFR) density remains constant. We find that the stellar mass density estimated from the cosmic SFR is consistent with those derived directly from the stellar mass function at z=0-1, but exceeds those at z~3 by a factor of 3. We find that the ratio of the UV-luminosity density of Ly-a emitters (LAEs) to that of LBGs is ~60% at z=5, and thus about a half of the star formation at z=5 probably occurs in LAEs. We obtain a constraint on the escape fraction of UV-ionizing photons produced by LBGs, f_{esc}>~0.13.Comment: 41 pages, 22 figures, ApJ in press. Paper with high resolution figures is available at http://hikari.astron.s.u-tokyo.ac.jp/~ouchi/work/astroph/SDS_V_VI/SDS_V.pdf (PDF

Social problems in daily life of patients with dementia

AIM: Most patients with dementia frequently encounter various problems in their daily lives. Those troubles embarrass both the patients and their families, and cause problems for society. However, there have been few scientific reports on the difficulties in the daily life of patients with dementia. Therefore, we tried to clarify the frequency and characteristics of troubles experienced by patients with dementia. METHODS: Seven medical centers treating dementia patients in Okayama Prefecture, Japan, participated in this survey. A total of 737 patients were placed in one of the three groups: a dementia group (n = 478), a mild cognitive impairment group (n = 199) and a control group (n = 60). The frequency of 13 difficulties was scored for each patient. RESULTS: Among normal participants, no person caused these problems once a year or more frequently. "Massive, recurrent buying" and "acts that risk causing a fire" were reported once a year or more for >10% of mild cognitive impairment patients. "Troubles with wealth management" and "troubles with money management" were the most frequent problems of dementia patients. CONCLUSIONS: Several problems are already sometimes encountered in patients with mild cognitive impairment. It would be useful to know which social difficulties are often seen in dementia patients in order to protect the safety of the patients. It is always difficult to balance respecting the autonomy of dementia patients and ensuring their safely

Cosmic shear statistics in the Suprime-Cam 2.1 sq deg field: Constraints on Omega_m and sigma_8

We present measurements of the cosmic shear correlation in the shapes of galaxies in the Suprime-Cam 2.1 deg^2 R_c-band imaging data. As an estimator of the shear correlation originated from the gravitational lensing, we adopt the aperture mass variance. We detect a non-zero E mode variance on scales between 2 and 40arcmin. We also detect a small but non-zero B mode variance on scales larger than 5arcmin. We compare the measured E mode variance to the model predictions in CDM cosmologies using maximum likelihood analysis. A four-dimensional space is explored, which examines sigma_8, Omega_m, Gamma and zs (a mean redshift of galaxies). We include three possible sources of error: statistical noise, the cosmic variance estimated using numerical experiments, and a residual systematic effect estimated from the B mode variance. We derive joint constraints on two parameters by marginalizing over the two remaining parameters. We obtain an upper limit of Gamma0.9 (68% confidence). For a prior Gamma\in[0.1,0.4] and zs\in[0.6,1.4], we find sigma_8=(0.50_{-0.16}^{+0.35})Omega_m^{-0.37} for flat cosmologies and sigma_8=(0.51_{-0.16}^{+0.29})Omega_m^{-0.34}$ for open cosmologies (95% confidence). If we take the currently popular LCDM model, we obtain a one-dimensional confidence interval on sigma_8 for the 95.4% level, 0.62<\sigma_8<1.32 for zs\in[0.6,1.4]. Information on the redshift distribution of galaxies is key to obtaining a correct cosmological constraint. An independent constraint on Gamma from other observations is useful to tighten the constraint.Comment: 12 pages, 12 figures, accepted for publication in Ap