Constrained Update Projection Approach to Safe Policy Optimization

Safe reinforcement learning (RL) studies problems where an intelligent agent has to not only maximize reward but also avoid exploring unsafe areas. In this study, we propose CUP, a novel policy optimization method based on Constrained Update Projection framework that enjoys rigorous safety guarantee. Central to our CUP development is the newly proposed surrogate functions along with the performance bound. Compared to previous safe RL methods, CUP enjoys the benefits of 1) CUP generalizes the surrogate functions to generalized advantage estimator (GAE), leading to strong empirical performance. 2) CUP unifies performance bounds, providing a better understanding and interpretability for some existing algorithms; 3) CUP provides a non-convex implementation via only first-order optimizers, which does not require any strong approximation on the convexity of the objectives. To validate our CUP method, we compared CUP against a comprehensive list of safe RL baselines on a wide range of tasks. Experiments show the effectiveness of CUP both in terms of reward and safety constraint satisfaction. We have opened the source code of CUP at this link https://github.com/zmsn-2077/ CUP-safe-rl.Comment: Accepted by NeurIPS2022. arXiv admin note: substantial text overlap with arXiv:2202.0756

Global Profiling of DNA Replication Timing and Efficiency Reveals that Efficient Replication/Firing Occurs Late during S-Phase in S. pombe

10.1371/journal.pone.0000722PLoS ONE2

Baichuan 2: Open Large-scale Language Models

Large language models (LLMs) have demonstrated remarkable performance on a variety of natural language tasks based on just a few examples of natural language instructions, reducing the need for extensive feature engineering. However, most powerful LLMs are closed-source or limited in their capability for languages other than English. In this technical report, we present Baichuan 2, a series of large-scale multilingual language models containing 7 billion and 13 billion parameters, trained from scratch, on 2.6 trillion tokens. Baichuan 2 matches or outperforms other open-source models of similar size on public benchmarks like MMLU, CMMLU, GSM8K, and HumanEval. Furthermore, Baichuan 2 excels in vertical domains such as medicine and law. We will release all pre-training model checkpoints to benefit the research community in better understanding the training dynamics of Baichuan 2.Comment: Baichuan 2 technical report. Github: https://github.com/baichuan-inc/Baichuan

Laparoscopic cholecystectomy for acute cholecystitis: clinical analysis of 216 cases

ObjectiveTo investigate the clinical experience of laparoscopic cholecystectomy (LC) for acute cholecystitis. MethodsA retrospective analysis was performed on the clinical records of 216 patients with acute cholecystitis who underwent LC in Qingpu Branch of Zhongshan Hospital, Fudan University from January 2010 to January 2013. LC was performed under intubation general anaesthesia, with three holes conventionally and four holes if necessary. After operation, the drainage tube was placed for 1-3 d, and antibiotics were administered for 3-5 d. The time of operation, length of postoperative hospital stay, and incidence of postoperative complications were determined. All patients were followed up for at least 0.5 year after operation. ResultsLC was successfully performed in 188 (87.0%) of all patients; 28 (13.0%) of all patients were converted to open surgery. The mean time of operation was 62.00±11.27 min; the mean length of hospital stay was 4.60±2.16 d; the incidence of postoperative complications was 2.3%(5/216). All patients were cured and discharged. During follow-up, no patients developed other complications and all recovered well. ConclusionLC is safe and feasible in the treatment of acute cholecystitis. Correct manipulation of the Calot's triangle and proper abdominal drainage are the key to successful operation

Violence Towards Gay Men: An Examination Among Straight Men

This study investigated the effect of video content on straight men’s homosexual judgment. Straight male participants (N = 115) were randomly assigned to one of three conditions: heterosexual video condition in which they viewed male-female sexual activities, homosexual video condition in which they viewed male-male sexual activities, and landscape video condition in which they viewed landscape scenery. Main effects of video content on animalistic dehumanization of gay men and hurting intention towards gay men were found. Animalistic dehumanization mediated the relationship between sexual arousal and hurting intention in the heterosexual video condition, and mediated the relationship between disgust and hurting intention in the heterosexual video condition and the homosexual video condition. Results imply that sexual arousal and disgust can foster straight men’s negative attitudes of gay men even when the sexual arousal and disgust are not elicited by gay-related stimuli. Implications and future directions were discussed

#NotAllWhites: Liberal-leaning Whites Racially Disidentify in Response to Trump-Related Group-Image Threat

Thesis (Master's)--University of Washington, 2020Donald Trump won the 2016 presidential election, in large part, due to support from White Americans. This win created a new socio-political reality in which White Americans as a group became associated with Trump and his anti-egalitarianism. Four studies (N=3245) explored how liberal-leaning Whites negotiate their racial identity to contend with group-image threat arising from the association between their racial ingroup and Trump. Trump-related group-image threat (i.e., Whites’ agreement with Trump’s anti-egalitarianism or disapproval of his impeachment) led liberal-leaning Whites to disidentify from their racial ingroup. In turn, racial disidentification predicted greater signaling of egalitarian beliefs (i.e., expressing intentions to advocate for racial equity and supporting policies designed to benefit racially minoritized groups) and behaviors (i.e., donating money to racial equity-focused organizations). These results suggest that the process of negotiating Trump-related group-image threat has implications for both White Americans’ racial identities and ongoing efforts to achieve racial equity

The ever-changing face of social groups: Psychological and behavioral responses to group-image threat

Thesis (Ph.D.)--University of Washington, 2023Images of a social group are socially constructed, fluctuate across time and context, and have the power not only to inform group members about their group’s position within social hierarchies but also to shape how others perceive, relate to, and subsequently act toward members of this group. Hence, negative group images diminish a group’s social standing and promote interpersonal and intergroup discrimination against this group, which clashes with people’s basic needs to maintain a positive sense of self and gives rise to group-image threats. Across three papers, I examine group-image threats facing three different groups (East Asian people, White Americans, and Native Peoples), which emerged during three unique socio-cultural-political contexts (the COVID-19 pandemic, Donald Trump’s presidency, and the 2020 U.S. Presidential Election night). I focus on group-image threats’ sources and psychological outcomes, and how group members respond to these threats. Paper 1 demonstrates that the image that blamed East Asian people for causing and spreading COVID-19 increased anxious expectations of discrimination among East Asian individuals and, in turn, predicted greater sleep difficulties, suggesting that negative group images have detrimental implications for group members’ mental and physical well-being. Paper 2 reveals that the image depicting White Americans as anti-egalitarian Trump supporters led liberal-leaning Whites to psychologically and behaviorally disidentify from their racial group, suggesting that high-status group members are also susceptible to group-image threats and that people have the capacity to manage their identities in response to threats to their positive sense of self. Finally, Paper 3 leverages an incident on the 2020 U.S. Presidential Election night that renders Native Peoples invisible to explore how the absence of group images shapes Native Peoples’ understandings of their group’s social standing and how they contended with this image (or lack thereof), suggesting that disadvantaged social group members are active agents who push back against negative group images. By providing insights into the antecedents and ramifications of ever-changing group images, this dissertation demonstrates that negative group images can either hinder or advance the efforts to create a more equitable and inclusive future