How are small ions involved in the compaction of DNA molecules?

DNA is a genetic material found in all life on Earth. DNA is composed of four types of nucleotide subunits, and forms a double-helical one-dimensional polyelectrolyte chain. If we focus on the microscopic molecular structure, DNA is a rigid rod-like molecule. On the other hand, with coarse graining, a long-chain DNA exhibits fluctuating behavior over the whole molecule due to thermal fluctuation. Owe to its semiflexible nature, individual giant DNA molecule undergoes a large discrete transition in the higher-order structure. In this folding transition into a compact state, small ions in the solution have a critical effect, since DNA is highly charged. In the present article, we interpret the characteristic features of DNA compaction while paying special attention to the role of small ions, in relation to a variety of single-chain morphologies generated as a result of compaction

Effect of Dy substitution in the giant magnetocaloric properties of HoB2_{2}

Recently, a massive magnetocaloric effect near the liquefaction temperature of hydrogen has been reported in the ferromagnetic material HoB$_{2}$. Here we investigate the effects of Dy substitution in the magnetocaloric properties of Ho$_{1-x}$Dy$_{x}$B$_{2}$ alloys ($\textit{x}$ = 0, 0.3, 0.5, 0.7, 1.0). We find that the Curie temperature ($\textit{T}$$_{C}$) gradually increases upon Dy substitution, while the magnitude of the magnetic entropy change |$\Delta \textit{S}_{M}$| at $\textit{T}$ = $\textit{T}_{C}$ decreases from 0.35 to 0.15 J cm$^{-3}$ K$^{-1}$ for a field change of 5 T. Due to the presence of two magnetic transitions in these alloys, despite the change in the peak magnitude of |$\Delta \textit{S}_{M}$|, the refrigerant capacity ($\textit{RC}$) and refrigerant cooling power ($\textit{RCP}$) remains almost constant in all doping range, which as large as 5.5 J cm$^{-3}$ and 7.0 J cm$^{-3}$ for a field change of 5 T. These results imply that this series of alloys could be an exciting candidate for magnetic refrigeration in the temperature range between 10-50 K.Comment: 19 pages, 5 figures, 2 table

Playing for Data: Ground Truth from Computer Games

Recent progress in computer vision has been driven by high-capacity models trained on large datasets. Unfortunately, creating large datasets with pixel-level labels has been extremely costly due to the amount of human effort required. In this paper, we present an approach to rapidly creating pixel-accurate semantic label maps for images extracted from modern computer games. Although the source code and the internal operation of commercial games are inaccessible, we show that associations between image patches can be reconstructed from the communication between the game and the graphics hardware. This enables rapid propagation of semantic labels within and across images synthesized by the game, with no access to the source code or the content. We validate the presented approach by producing dense pixel-level semantic annotations for 25 thousand images synthesized by a photorealistic open-world computer game. Experiments on semantic segmentation datasets show that using the acquired data to supplement real-world images significantly increases accuracy and that the acquired data enables reducing the amount of hand-labeled real-world data: models trained with game data and just 1/3 of the CamVid training set outperform models trained on the complete CamVid training set.Comment: Accepted to the 14th European Conference on Computer Vision (ECCV 2016

Experimental exploration of ErB2_2 and SHAP analysis on a machine-learned model of magnetocaloric materials for materials design

Stimulated by a recent report of a giant magnetocaloric effect in HoB$_2$ found via machine-learning predictions, we have explored the magnetocaloric properties of a related compound ErB$_2$, that has remained the last ferromagnetic material among the rare-earth diboride (REB$_2$) family with unreported magnetic entropy change |{\Delta}SM|. The evaluated $|\Delta S_M|$ at field change of 5 T in ErB$_2$ turned out to be as high as 26.1 (J kg$^{-1}$ K$^{-1}$) around the ferromagnetic transition (${T_C}$) of 14 K. In this series, HoB$_2$ is found to be the material with the largest $|\Delta S_M|$ as the model predicted, while the predicted values showed a deviation with a systematic error compared to the experimental values. Through a coalition analysis using SHAP, we explore how this rare-earth dependence and the deviation in the prediction are deduced in the model. We further discuss how SHAP analysis can be useful in clarifying favorable combinations of constituent atoms through the machine-learned model with compositional descriptors. This analysis helps us to perform materials design with aid of machine learning of materials data.Comment: 9 pages, 10 figures. Accepted manuscript. Published by Taylor & Francis in STAM:Methods, available at https://doi.org/10.1080/27660400.2023.221747

High Jc_{c} and low anisotropy of hydrogen doped NdFeAsO superconducting thin film

The recent realisations of hydrogen doped LnFeAsO (Ln = Nd and Sm) superconducting epitaxial thin films call for further investigation of their structural and electrical transport properties. Here, we report on the microstructure of a NdFeAs(O,H) epitaxial thin film and its temperature, field, and orientation dependencies of the resistivity and the critical current density J$_{c}$. The superconducting transition temperature T$_{c}$ is comparable to NdFeAs(O,F). Transmission electron microscopy investigation supported that hydrogen is homogenously substituted for oxygen. A high self-field J$_{c}$ of over 10 MA/cm$^{2}$ was recorded at 5 K, which is likely to be caused by a short London penetration depth. The anisotropic Ginzburg–Landau scaling for the angle dependence of J$_{c}$ yielded temperature-dependent scaling parameters γ$_{J}$ that decreased from 1.6 at 30 K to 1.3 at 5 K. This is opposite to the behaviour of NdFeAs(O,F). Additionally, γ$_{J}$ of NdFeAs(O,H) is smaller than that of NdFeAs(O,F). Our results indicate that heavily electron doping by means of hydrogen substitution for oxygen in LnFeAsO is highly beneficial for achieving high J$_{c}$ with low anisotropy without compromising T$_{c}$, which is favourable for high-field magnet applications

High HbA1c levels correlate with reduced plaque regression during statin treatment in patients with stable coronary artery disease: Results of the coronary atherosclerosis study measuring effects of rosuvastatin using intravascular ultrasound in Japanese subjects (COSMOS)

Abstract Background The incidence of cardiac events is higher in patients with diabetes than in people without diabetes. The Coronary Atherosclerosis Study Measuring Effects of Rosuvastatin Using Intravascular Ultrasound in Japanese Subjects (COSMOS) demonstrated significant plaque regression in Japanese patients with chronic coronary disease after 76 weeks of rosuvastatin (2.5 mg once daily, up-titrated to a maximum of 20 mg/day to achieve LDL cholesterol Methods In this subanalysis of COSMOS, we examined the association between HbA1c and plaque regression in 40 patients with HbA1c ≥6.5% (high group) and 86 patients with HbA1c Results In multivariate analyses, HbA1c and plaque volume at baseline were major determinants of plaque regression. LDL cholesterol decreased by 37% and 39% in the high and low groups, respectively, while HDL cholesterol increased by 16% and 22%, respectively. The reduction in plaque volume was significantly (p = 0.04) greater in the low group (from 71.0 ± 39.9 to 64.7 ± 34.7 mm3) than in the high group (from 74.3 ± 34.2 to 71.4 ± 32.3 mm3). Vessel volume increased in the high group but not in the low group (change from baseline: +4.2% vs −0.8%, p = 0.02). Change in plaque volume was significantly correlated with baseline HbA1c. Conclusions Despite similar improvements in lipid levels, plaque regression was less pronounced in patients with high HbA1c levels compared with those with low levels. Tight glucose control during statin therapy may enhance plaque regression in patients with stable coronary disease. Trial registration ClinicalTrials.gov, Identifier NCT00329160</p