The parity-violating energy difference (PVED) between two enantiomers of a chiral molecule is caused by the weak interaction. Because of the smallness of the PVED, nonzero PVED is yet to be discovered in experimental searches. To detect the PVED, the search for molecules with large PVED values is important. Previously, one of the authors proposed that the PVED may be significantly enhanced in ionized or excited states. The significant enhancement of the PVED in some electronic excited states is proven in this study using H 2 X 2 (X = O, S, Se, Te) molecules as examples. The maximum enhancement was an about 360-fold increase for H 2 Se 2 . For the PVED calculation, we employ the finite-field perturbation theory (FFPT) within the equation-of-motion coupledcluster theory based on the exact two-component molecular mean-field Hamiltonian. The relation between the enhancement of the PVED and the contribution to the PVED from the highest occupied molecular orbital is also examined. The effects of computational elements, such as parameters related to the electron correlation and FFPT on PVED values in excited states of H 2 X 2 molecules, are studied.

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This paper proposes fragility curves for asset damage based on questionnaire replies from companies that were affected by floods after the heavy rain event of July 2018 in Japan. Fragility curves are a probabilistic method for analyzing structural vulnerability and production facility of companies. Although a fragility curve is a basic model of disaster damage assumption, there has been no case of estimating the asset damage rate at the time of flood damage. In this study, the expected values of the damage rate and the damage cost obtained by the probability distribution of the asset damage rate are smaller than the estimation results in the Manual for Economic Evaluation of Flood Control Investments. These results may reflect the progress of the flood control and the Business Continuity Plan (BCP) of companies; thus, it is important to verify the validity of the evaluation model while continuously updating it.

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