Host-guest Interaction at Molecular Interfaces: Binding of Cucurbit[7]uril on Ferrocenyl Self-assembled Monolayers on Gold

Ferrocene (Fc) encapsulated cucurbit[7]uril (CB[7]) supramolecular host-guest complex  (Fc@CB[7]) as a synthetic recognition pair has been widely adapted for coupling biomolecules and nanomaterials due to its ultra-high binding affinity. In this paper, we have explored the binding of CB[7] on binary ferrocenylundecanethiolate/octanethiolate self-assembled monolayer on gold  (FcC11S-/C8S-Au), a model system to deepen our understanding of host-guest chemistry at molecular interfaces. It has been shown that upon incubation with CB[7] solution, the redox behavior FcC11S-/C8S-Au changes remarkably, i.e., a new pair of peaks appeared at more positive potential with narrowed widths. The ease of quantitation of surface bound-redox species (Fc+/Fc and  Fc+@CB[7]/ Fc@CB[7]) enabled us to determine the thermodynamic formation constant of  Fc@CB[7] at FcC11S-/C8S-Au (7.3±1.8 × 104 M-1). With time-dependent redox responses, we were able to, for the first time, deduce both the binding and dissociation rate constants, 2.8±0.3 × 103  M-1s-1 and 0.08±0.01 s-1, respectively. These results showed substantial differences both thermodynamically and kinetically for the formation of host-guest inclusion complex at molecular interfaces with respect to solution-diffused, homogenous environments

Stability Analysis of Delayed Genetic Regulatory Networks via a Relaxed Double Integral Inequality

Time delay arising in a genetic regulatory network may cause the instability. This paper is concerned with the stability analysis of genetic regulatory networks with interval time-varying delays. Firstly, a relaxed double integral inequality, named as Wirtinger-type double integral inequality (WTDII), is established to estimate the double integral term appearing in the derivative of Lyapunov-Krasovskii functional with a triple integral term. And it is proved theoretically that the proposed WTDII is tighter than the widely used Jensen-based double inequality and the recently developed Wiringter-based double inequality. Then, by applying the WTDII to the stability analysis of a delayed genetic regulatory network, together with the usage of useful information of regulatory functions, several delay-range- and delay-rate-dependent (or delay-rate-independent) criteria are derived in terms of linear matrix inequalities. Finally, an example is carried out to verify the effectiveness of the proposed method and also to show the advantages of the established stability criteria through the comparison with some literature

Generalized Magneto-thermo-microstretch Response of a Half-space with Temperature-dependent Properties During Thermal Shock

Abstract The generalized magneto-thermoelastic problem of an infinite homogeneous isotropic microstretch half-space with temperature

Being Comes from Not-being: Open-vocabulary Text-to-Motion Generation with Wordless Training

Text-to-motion generation is an emerging and challenging problem, which aims to synthesize motion with the same semantics as the input text. However, due to the lack of diverse labeled training data, most approaches either limit to specific types of text annotations or require online optimizations to cater to the texts during inference at the cost of efficiency and stability. In this paper, we investigate offline open-vocabulary text-to-motion generation in a zero-shot learning manner that neither requires paired training data nor extra online optimization to adapt for unseen texts. Inspired by the prompt learning in NLP, we pretrain a motion generator that learns to reconstruct the full motion from the masked motion. During inference, instead of changing the motion generator, our method reformulates the input text into a masked motion as the prompt for the motion generator to ``reconstruct'' the motion. In constructing the prompt, the unmasked poses of the prompt are synthesized by a text-to-pose generator. To supervise the optimization of the text-to-pose generator, we propose the first text-pose alignment model for measuring the alignment between texts and 3D poses. And to prevent the pose generator from overfitting to limited training texts, we further propose a novel wordless training mechanism that optimizes the text-to-pose generator without any training texts. The comprehensive experimental results show that our method obtains a significant improvement against the baseline methods. The code is available at https://github.com/junfanlin/oohmg