Multi-Modal CLIP-Informed Protein Editing.

Proteins govern most biological functions essential for life, and achieving controllable protein editing has made great advances in probing natural systems, creating therapeutic conjugates, and generating novel protein constructs. Recently, machine learning-assisted protein editing (MLPE) has shown promise in accelerating optimization cycles and reducing experimental workloads. However, current methods struggle with the vast combinatorial space of potential protein edits and cannot explicitly conduct protein editing using biotext instructions, limiting their interactivity with human feedback.

The neural correlates of value hierarchies: a prospective typology based on personal value profiles of emerging adults.

Introduction: Value hierarchies, as motivational goals anchored in the self-schema, may be correlated with spontaneous activity in the resting brain, especially those involving self-relevance. This study aims to investigate the neural correlates of value hierarchies from the perspective of typology.

Methods: A total of 610 Chinese college students (30.

The welfare effects of impoverished rural areas: Review and research prospects.

The relationship between rural poverty and welfare effects is a significant social issue, as poor areas face challenges like fragile livelihoods, nutritional imbalances, and inadequate policy regulation. Studying welfare effects in impoverished rural areas is vital for addressing capability poverty and achieving the United Nations SDGs. This study examines three decades of research, using a quantitative literature analysis and traditional literature review.

The mediating role of personal values between COVID-19-related posttraumatic growth and life satisfaction among Chinese college students: A two-wave longitudinal study.

Despite considerable disruption of social order caused by the COVID-19 pandemic, it has also been said to contribute to positive psychological changes and influence on the perception of public life satisfaction. The present study aimed to explore the association between the COVID-19 related posttraumatic growth and life satisfaction and the mediating role of personal values. A two-wave longitudinal design was used.

Parameter estimation of the incubation period of COVID-19 based on the doubly interval-censored data model.

With the spread of the novel coronavirus disease 2019 (COVID-19) around the world, the estimation of the incubation period of COVID-19 has become a hot issue. Based on the doubly interval-censored data model, we assume that the incubation period follows lognormal and Gamma distribution, and estimate the parameters of the incubation period of COVID-19 by adopting the maximum likelihood estimation, expectation maximization algorithm and a newly proposed algorithm (expectation mostly conditional maximization algorithm, referred as ECIMM). The main innovation of this paper lies in two aspects: Firstly, we regard the sample data of the incubation period as the doubly interval-censored data without unnecessary data simplification to improve the accuracy and credibility of the results; secondly, our new ECIMM algorithm enjoys better convergence and universality compared with others.