Optimized Decimation of Tensor Networks with Super-orthogonalization for Two-Dimensional Quantum Lattice Models

A novel algorithm based on the optimized decimation of tensor networks with super-orthogonalization (ODTNS) that can be applied to simulate efficiently and accurately not only the thermodynamic but also the ground state properties of two-dimensional (2D) quantum lattice models is proposed. By transforming the 2D quantum model into a three-dimensional (3D) closed tensor network (TN) comprised of the tensor product density operator and a 3D brick-wall TN, the free energy of the system can be calculated with the imaginary time evolution, in which the network Tucker decomposition is suggested for the first time to obtain the optimal lower-dimensional approximation on the bond space by transforming the TN into a super-orthogonal form. The efficiency and accuracy of this algorithm are testified, which are fairly comparable with the quantum Monte Carlo calculations. Besides, the present ODTNS scheme can also be applicable to the 2D frustrated quantum spin models with nice efficiency

Forgiveness from Emotion Fit: Emotional Frame, Consumer Emotion, and Feeling-Right in Consumer Decision to Forgive

Three studies examine an emotion fit effect in the crisis communication, namely, the interaction between emotional frames of guilt and shame and consumer emotions of anger and fear on consumer forgiveness. Guilt-framing communication results in higher forgiveness than shame-framing for angry consumers, whereas shame-framing communication results in higher forgiveness than guilt-framing for fearful consumers. These effects are driven by consumers’ accessible regulatory foci associated with anger/fear and guilt/shame. Specifically, feelings of anger activate a promotion focus that is represented by guilt frames, while feelings of fear activate a prevention focus that is enacted by shame frames. Compared with emotion nonfit (i.e., anger to shame and fear to guilt), emotion fit (i.e., anger to guilt and fear to shame) facilitates greater feeling-right and consumer forgiveness. The findings offer novel insights for extant literature on emotion, crisis communication, and regulatory focus theory, as well as practical suggestions regarding the emotional frames

Comparative proteomic profiling reveals molecular characteristics associated with oogenesis and oocyte maturation during ovarian development of Bactrocera dorsalis (Hendel)

Time-dependent expression of proteins in ovary is important to understand oogenesis in insects. Here, we profiled the proteomes of developing ovaries from Bactrocera dorsalis (Hendel) to obtain information about ovarian development with particular emphasis on differentially expressed proteins (DEPs) involved in oogenesis. A total of 4838 proteins were identified with an average peptide number of 8.15 and sequence coverage of 20.79%. Quantitative proteomic analysis showed that a total of 612 and 196 proteins were differentially expressed in developing and mature ovaries, respectively. Furthermore, 153, 196 and 59 potential target proteins were highly expressed in early, vitellogenic and mature ovaries and most tested DEPs had the similar trends consistent with the respective transcriptional profiles. These proteins were abundantly expressed in pre-vitellogenic and vitellogenic stages, including tropomyosin, vitellogenin, eukaryotic translation initiation factor, heat shock protein, importin protein, vitelline membrane protein, and chorion protein. Several hormone and signal pathway related proteins were also identified during ovarian development including piRNA, notch, insulin, juvenile, and ecdysone hormone signal pathways. This is the first report of a global ovary proteome of a tephritid fruit fly, and may contribute to understanding the complicate processes of ovarian development and exploring the potentially novel pest control targets