Dielectric properties of TbMnO3 ceramics doped with Bi and Fe ions

AbstractThe ceramic composites of TbMnO3, Tb0.95Bi0.05MnO3, Tb0.9Bi0.1MnO3 and Tb0.9Bi0.1Mn0.95Fe0.05O3 were compounded by conventional solid-state reaction. Both dielectric constants (ɛ′) and loss tangent (tanδ) of composites have been measured and studied as a function of the temperature from 80 to 400K and the frequency from 100Hz to 1MHz. Interestingly, doping Bi makes dielectric constant decrease and the dielectric dissipation peaks disappear in the high temperature range. But the dielectric constant becomes larger and the dielectric dissipation peaks appear again in the high temperature range after Fe doping appropriately. Analysis indicates that the perovskite structures gradually vary with the increase of Bi replacing Tb, thus the dielectric properties could be enhanced with the small amount of Mn replacement with Fe

Representations for the Drazin inverse of the sum P+Q+R+S and its applications

AbstractLet P, Q, R and S be complex square matrices and M=P+Q+R+S. A quadruple (P,Q,R,S) is called a pseudo-block decomposition of M ifPQ=QP=0PS=SQ=QR=RP=0andRD=SD=0,where RD and SD are the Drazin inverses of R and S, respectively. We investigate the problem of finding formulae for the Drazin inverse of M. The explicit representations for the Drazin inverses of M and P+Q+R are developed, under some assumptions. As its application, some representations are presented for 2×2 block matricesAB0CandABDC, where the blocks A and C are square matrices. Several results of this paper extend the well known representation for the Drazin inverse ofAB0Cgiven by Hartwig and Shoaf, Meyer and Rose in 1977. An illustrative example is given to verify our new representations

On disjoint range operators in a Hilbert space

AbstractFor a bounded linear operator M in a Hilbert space H, various relations among the ranges R(M),R(M∗), R(M+M∗) and the null spaces N(M),N(M∗) are considered from the point of view of their relations to the known classes of operators, such as EP, co-EP, weak-EP, GP, DR, or SR. Particular attention is paid to the range projectors of the operators M, M∗ and some further characteristics of these projectors are derived as well

Round-Bale Silage Preparation of Rice Straw

Rice straw is an important feed resource for ruminants. In Japan, rice straw cannot be fully dried due to the usually humid autumn season, which leads to about 70% of the production being ploughed back or incinerated. Therefore, the development of techniques to enhance the long-term preservation and quality of rice straw is of great importance. In this work, a new lactic acid bacterium was used as a silage inoculant, and its effect on round-bale silage preparation from fresh rice straw was examined

ContrasInver: Voxel-wise Contrastive Semi-supervised Learning for Seismic Inversion

Recent studies have shown that learning theories have been very successful in hydrocarbon exploration. Inversion of seismic into various attributes through the relationship of 1D well-logs and 3D seismic is an essential step in reservoir description, among which, acoustic impedance is one of the most critical attributes, and although current deep learningbased impedance inversion obtains promising results, it relies on a large number of logs (1D labels, typically more than 30 well-logs are required per inversion), which is unacceptable in many practical explorations. In this work, we define acoustic impedance inversion as a regression task for learning sparse 1D labels from 3D volume data and propose a voxel-wise semisupervised contrastive learning framework, ContrasInver, for regression tasks under sparse labels. ConstraInver consists of several key components, including a novel pre-training method for 3D seismic data inversion, a contrastive semi-supervised strategy for diffusing well-log information to the global, and a continuous-value vectorized characterization method for a contrastive learning-based regression task, and also designed the distance TopK sampling method for improving the training efficiency. We performed a complete ablation study on SEAM Phase I synthetic data to verify the effectiveness of each component and compared our approach with the current mainstream methods on this data, and our approach demonstrated very significant advantages. In this data we achieved an SSIM of 0.92 and an MSE of 0.079 with only four well-logs. ConstraInver is the first purely data-driven approach to invert two classic field data, F3 Netherlands (only four well-logs) and Delft (only three well-logs) and achieves very reasonable and reliable results.Comment: This work has been submitted to journal for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Unified-Width Adaptive Dynamic Network for All-In-One Image Restoration

In contrast to traditional image restoration methods, all-in-one image restoration techniques are gaining increased attention for their ability to restore images affected by diverse and unknown corruption types and levels. However, contemporary all-in-one image restoration methods omit task-wise difficulties and employ the same networks to reconstruct images afflicted by diverse degradations. This practice leads to an underestimation of the task correlations and suboptimal allocation of computational resources. To elucidate task-wise complexities, we introduce a novel concept positing that intricate image degradation can be represented in terms of elementary degradation. Building upon this foundation, we propose an innovative approach, termed the Unified-Width Adaptive Dynamic Network (U-WADN), consisting of two pivotal components: a Width Adaptive Backbone (WAB) and a Width Selector (WS). The WAB incorporates several nested sub-networks with varying widths, which facilitates the selection of the most apt computations tailored to each task, thereby striking a balance between accuracy and computational efficiency during runtime. For different inputs, the WS automatically selects the most appropriate sub-network width, taking into account both task-specific and sample-specific complexities. Extensive experiments across a variety of image restoration tasks demonstrate that the proposed U-WADN achieves better performance while simultaneously reducing up to 32.3\% of FLOPs and providing approximately 15.7\% real-time acceleration. The code has been made available at \url{https://github.com/xuyimin0926/U-WADN}