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

Cross-Speaker Emotion Transfer for Low-Resource Text-to-Speech Using Non-Parallel Voice Conversion with Pitch-Shift Data Augmentation

Data augmentation via voice conversion (VC) has been successfully applied to low-resource expressive text-to-speech (TTS) when only neutral data for the target speaker are available. Although the quality of VC is crucial for this approach, it is challenging to learn a stable VC model because the amount of data is limited in low-resource scenarios, and highly expressive speech has large acoustic variety. To address this issue, we propose a novel data augmentation method that combines pitch-shifting and VC techniques. Because pitch-shift data augmentation enables the coverage of a variety of pitch dynamics, it greatly stabilizes training for both VC and TTS models, even when only 1,000 utterances of the target speaker's neutral data are available. Subjective test results showed that a FastSpeech 2-based emotional TTS system with the proposed method improved naturalness and emotional similarity compared with conventional methods.Comment: Submitted to Interspeech 202

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

Restoration of the Ellipsoid Zone and Visual Prognosis at 1 Year after Surgical Macular Hole Closure

Purpose. To evaluate the restoration of the ellipsoid zone (EZ) and its influence on visual prognosis 1 year after surgical macular hole (MH) closure. Method. Subjects were patients with stage 2, 3, or 4 idiopathic MH who underwent primary vitrectomy that resulted in successful hole closure. Nineteen eyes with both EZ disruption with foveal detachment and a continuous external limiting membrane on optical coherence tomography during the early postoperative period were included in this study. Result. EZ disruption was restored in 10 eyes (53%, Group A) and remained in 9 eyes (47%, Group B) at 1 year after surgery. In Group B, the diameter of the residual EZ disruption was 54.7±33.1 μm. LogMAR visual acuity (VA) 1 year after surgery was significantly better than preoperative VA in each group (Group A: -0.007±0.102; P<0.001; Group B: 0.051±0.148; P<0.001), but there was no significant difference between the 2 groups (P=0.332). There was no significant correlation between logMAR VA and EZ disruption diameter at 1 year after surgery. Conclusion. EZ was restored in 53% of eyes at 1 year after surgical closure of idiopathic MH. Mean residual EZ disruption diameter was 54.7±33.1 μm. Neither resolved nor residual EZ disruption influenced postoperative VA

Neural networks for a quick access to a digital twin of scanning physical properties measurements

For performing successful measurements within limited experimental time, efficient use of preliminary data plays a crucial role. This work shows that a simple feedforward type neural networks approach for learning preliminary experimental data can provide quick access to simulate the experiment within the learned range. The approach is especially beneficial for physical properties measurements with scanning on multiple axes, where derivative or integration of data are required to obtain the objective quantity. Due to its simplicity, the learning process is fast enough for the users to perform learning and simulation on-the-fly by using a combination of open-source optimization techniques and deep-learning libraries. Here such a tool for augmenting the experimental data is proposed, aiming to help researchers to decide the most suitable experimental conditions before performing costly experiments in real. Furthermore, this tool can also be used from the perspective of taking advantage of reutilizing and repurposing previously published data, accelerating data-driven exploration of functional materials.Comment: 19 pages, 5 figures + 7 pages of Supporting Informatio

Lattice Anharmonicity in BiS2-Based Layered Superconductor RE(O,F)BiS2 (RE = La, Ce, Pr, Nd)

We studied Gr\"uneisen parameter ({\gamma}G) to investigate lattice anharmonicity in a layered BiS2-based superconductor system REO1-xFxBiS2 (RE = La, Ce, Pr, Nd), where in-plane chemical pressure was tuned by substituting the RE elements. With increasing in-plane chemical pressure, bulk modulus remarkably increases, and a high {\gamma}G is observed for RE = Nd. The dependence of {\gamma}G on in-plane chemical pressure exhibits a good correlation with Tc, and a higher Tc is achieved when {\gamma}G is large for RE = Nd. In addition, {\gamma}G shows a slight decrease by a decrease of F concentration (x) in REO1-xFxBiS2. Our results show that the anharmonic vibration of Bi along the c-axis is present in REO1-xFxBiS2, and the enhancement of the anharmonicity is positively linked to superconducting Tc and pairing mechanisms.Comment: 15 pages, 5 figure