Ectopic cervical thymoma in a patient with Myasthenia gravis

Ectopic cervical thymoma is rare and is often misdiagnosed as a thyroid tumor or other malignancy. Ectopic thymic tissue can be found along the entire thymic descent path during embryogenesis. However, a thymoma arising from such ectopic thymic tissue is extremely rare. Herein we report a patient with ectopic cervical thymoma and myasthenia gravis (MG) and discuss the management

EFFECTS ON POSTURAL CONSTRAINTS ON OVERARM THROWING

This study explored the effects of postural constraints on overarm throwing. 10 participants were required to perform an overarm throwing movement by 3 tasks which under postural constraints. Tasks were including trunk-fixed, sitting, and standing. 10 pieces of 3D motion capture system were used to record the maximum velocity of body segments as data and one-way repeated measures ANOVA (a=.05) with HSD post-hoc tests was conducted to analysis the data. Therefore, the results indicated that the performance of overarm throwing by 3 tasks were different significantly, which proved the kinetic chain formed by links connected in series gave body segments more velocities. Moreover, it meat trunk and lower limbs played the roles to transport velocity as performing overarm throwing

Are AlphaZero-like Agents Robust to Adversarial Perturbations?

The success of AlphaZero (AZ) has demonstrated that neural-network-based Go AIs can surpass human performance by a large margin. Given that the state space of Go is extremely large and a human player can play the game from any legal state, we ask whether adversarial states exist for Go AIs that may lead them to play surprisingly wrong actions. In this paper, we first extend the concept of adversarial examples to the game of Go: we generate perturbed states that are ``semantically'' equivalent to the original state by adding meaningless moves to the game, and an adversarial state is a perturbed state leading to an undoubtedly inferior action that is obvious even for Go beginners. However, searching the adversarial state is challenging due to the large, discrete, and non-differentiable search space. To tackle this challenge, we develop the first adversarial attack on Go AIs that can efficiently search for adversarial states by strategically reducing the search space. This method can also be extended to other board games such as NoGo. Experimentally, we show that the actions taken by both Policy-Value neural network (PV-NN) and Monte Carlo tree search (MCTS) can be misled by adding one or two meaningless stones; for example, on 58\% of the AlphaGo Zero self-play games, our method can make the widely used KataGo agent with 50 simulations of MCTS plays a losing action by adding two meaningless stones. We additionally evaluated the adversarial examples found by our algorithm with amateur human Go players and 90\% of examples indeed lead the Go agent to play an obviously inferior action. Our code is available at \url{https://PaperCode.cc/GoAttack}.Comment: Accepted by Neurips 202

MiniZero: Comparative Analysis of AlphaZero and MuZero on Go, Othello, and Atari Games

This paper presents MiniZero, a zero-knowledge learning framework that supports four state-of-the-art algorithms, including AlphaZero, MuZero, Gumbel AlphaZero, and Gumbel MuZero. While these algorithms have demonstrated super-human performance in many games, it remains unclear which among them is most suitable or efficient for specific tasks. Through MiniZero, we systematically evaluate the performance of each algorithm in two board games, 9x9 Go and 8x8 Othello, as well as 57 Atari games. For two board games, using more simulations generally results in higher performance. However, the choice of AlphaZero and MuZero may differ based on game properties. For Atari games, both MuZero and Gumbel MuZero are worth considering. Since each game has unique characteristics, different algorithms and simulations yield varying results. In addition, we introduce an approach, called progressive simulation, which progressively increases the simulation budget during training to allocate computation more efficiently. Our empirical results demonstrate that progressive simulation achieves significantly superior performance in two board games. By making our framework and trained models publicly available, this paper contributes a benchmark for future research on zero-knowledge learning algorithms, assisting researchers in algorithm selection and comparison against these zero-knowledge learning baselines. Our code and data are available at https://rlg.iis.sinica.edu.tw/papers/minizero.Comment: Submitted to IEEE Transactions on Games, under revie

Preoperative treatment with 5α-reductase inhibitors and the risk of hemorrhagic events in patients undergoing transurethral resection of the prostate – A population-based cohort study

OBJECTIVES: To assess the associations between preoperative treatment with 5-alpha reductase inhibitors and the risks of blood transfusion during transurethral resection of the prostate and blood clot evacuation or emergency department visits for hematuria within 1 month after surgery. METHODS: We used data from the Taiwan National Health Insurance Research Database in this population-based cohort study. A total of 3,126 patients who underwent first-time transurethral resection of the prostate from 2004 to 2013 were identified. Adjusted odds ratios estimated by multiple logistic regression models were used to assess the independent effects of the preoperative use of 5-alpha reductase inhibitors on the risks of perioperative hemorrhagic events after adjustment for potential confounders. RESULTS: Two hundred and ninety-seven (9.4%) patients were treated with 5-alpha reductase inhibitors fo

Prophylactic Cavotricuspid Isthmus Ablation in Atrial Fibrillation without Documented Typical Atrial Flutter: A Systematic Review and Meta-analysis

Background: The advantage of prophylactic cavotricuspid isthmus (CTI) ablation for AF patients without documented atrial flutter is still unclear. The present study aimed to evaluate the role of prophylactic CTI ablation in this population. Methods: A systematic review and meta-analysis study was conducted. The overall effects estimation was conducted using random effects models. The pooled effects were presented as the risk difference and standardised mean difference for dichotomous and continuous outcomes, respectively. Results: A total of 1,476 patients from four studies were included. The risk of atrial tachyarrhythmias following a successful catheter ablation procedure was greater in the pulmonary vein isolation + CTI ablation group than pulmonary vein isolation alone group (34.8% versus 28.2%; risk difference 0.08; 95% CI [0.00–0.17]; p=0.04). Prophylactic CTI ablation was associated with a higher recurrent AF rate (33.8% versus 27.1%; risk difference 0.07; 95% CI [0.01–0.13]; p=0.02). Additional prophylactic CTI ablation to pulmonary vein isolation significantly increased the radio frequency application time (standardised mean difference 0.52; 95% CI [0.04–1.01]; p=0.03). Conclusion: This study suggested that prophylactic CTI ablation was an ineffective and inefficient approach in AF without documented typical atrial flutter patients