Charge-parity (CP) violation in the tau-charm energy region is a promising area for sensitive tests of Standard Model (SM) predictions and searches for new, beyond the SM physics. A future Tau-Charm Facility that operates at center-of-mass energies between 2.0 and 7.0 GeV, with a peak luminosity of 0.5×1035 cm−2 s−1, would provide huge numbers of hadrons and tau (τ) leptons that are produced in low-background environments and with well understood kinematic properties. In this report, prospects for unique studies of CP violation in the decay of charmed hadrons, and in the production and decay of hyperons and τ leptons at a next-generation tau-charm facility are discussed. In addition, opportunities for improved tests of CPT invariance test in K0−K̄0 mixing are presented.
Inverse data envelopment analysis (DEA) and meta-frontier analysis framework have been widely used to measure performance of banks. However, there are few studies on introducing meta-frontier framework into inverse DEA, which leads to the advantages of meta-frontier in measuring technical gap and technical bias that cannot be applied to the target setting of inverse DEA. Therefore, this paper develops a meta-frontier inverse DEA analysis framework considering responsibility allocation. Firstly, we introduce the concept of “responsibility”, defined as the efficiency maintenance requirement for each output of a decision-making unit (DMU) when inputs are augmented. Then, we further propose the concept of “responsibility allocation”, which refers to the distribution of total responsibility across different outputs, ensuring the rationality and fairness of the allocation process. Secondly, the responsibility allocation is further extended to multi-scenarios for discussion, and then we give an algorithm to obtain a unique, optimal solution. Moreover, this paper quantifies the influence of responsibility allocation on inefficient behavior and technology gap. Finally, by comparing the existing technical bias analysis methods, this paper proposes a technical bias analysis method considering responsibility allocation, and determines the final responsibility allocation, so as to identify the technical improvement direction of target setting. The resulting technical improvement direction is compared with the classical method. To illustrate the usefulness and applicability of the proposed approach we applied it to a real application of 42 commercial banks around the world.
Let \cal F F be a family of sets in \mathbb{R}^d R d . A set M \subset \mathbb{R}^d M ⊂ R d is called \cal F F -convex if for any points x,y\in M x , y ∈ M there is a set F\in \cal F F ∈ F such that x,y\in F x , y ∈ F and F\subset M F ⊂ M . A function f: \mathbb{R}\rightarrow \mathbb{R} f : R → R is called \cal F F -convex if its epigraph is \cal F F -convex. In this paper we investigate various \cal F F -convexities for real functions
In this paper, we investigate biphoton generation via spontaneous four-wave mixing in Doppler-broadened atomic vapors. Thermal motion breaks the zero-temperature symmetry between copropagating and counterpropagating geometries and introduces competition between the biphoton generation rate and propagation loss. A temperature-dependent pump-detuning scheme restores an approximate mirror symmetry between the frequency-resolved responses of the two geometries, yielding nearly identical biphoton generation rates and correlation strengths over a broad temperature range. We find that increasing atomic thermal velocity drives the temporal correlation function from damped oscillations at low temperatures to a purely exponential decay at higher temperatures by enhancing decoherence and pushing the effective Rabi frequency into the imaginary regime. This behavior is captured analytically through the temperature-dependent modification of the poles governing the oscillatory correlations. The generated biphotons retain strong nonclassical character, accompanied by spectral narrowing and temperature-induced temporal broadening. Numerical simulations incorporating Doppler averaging validate these predictions, quantify the model's accuracy, and confirm that the same qualitative trends persist at higher optical depths. These results identify a simple and tunable route to narrowband biphoton generation in warm vapors, with direct relevance to quantum memories and long-distance quantum communication.
Self-derivation through memory integration is the process of integrating two or more separate but related episodes into new knowledge. The present study examined how emotional valence influences adolescents' self-derivation in classroom settings across two experiments. In Experiment 1, adolescents (N = 159, M age = 13.48) viewed emotional video clips aiming to induce different emotional valences (positive, negative, and neutral), followed by a self-derivation through integration task. In Experiment 2, adolescents (N = 454, M age = 13.49) viewed the emotional video clip at various phases of memory integration (before-learning, between-stem, before-test). A delayed test one week later assessed the retention of self-derived knowledge. Across both experiments, positive emotion most effectively enhanced self-derivation through integration. Specifically, Experiment 2 revealed that inducing positive emotion prior to learning enhanced self-derivation. The overall retention of self-derivation significantly improved after one week. These findings underscore the importance of fostering positive emotional valences before learning to promote adolescents' effective knowledge integration and self-derivation.
