Controlling keywords and their positions in text generation

One of the challenges in text generation is to control generation as intended by a user. Previous studies have proposed to specify the keywords that should be included in the generated text. However, this is insufficient to generate text which reflect the user intent. For example, placing the important keyword beginning of the text would helps attract the reader's attention, but existing methods do not enable such flexible control. In this paper, we tackle a novel task of controlling not only keywords but also the position of each keyword in the text generation. To this end, we show that a method using special tokens can control the relative position of keywords. Experimental results on summarization and story generation tasks show that the proposed method can control keywords and their positions. We also demonstrate that controlling the keyword positions can generate summary texts that are closer to the user's intent than baseline. We release our code

Surgical productivity recovery after the COVID-19 pandemic in Japan

IntroductionPrevious studies demonstrated that the surgical productivity regressed in 2020. This study therefore explored whether the COVID-19 pandemic had any significant lasting effect of reducing the surgical productivity in Japan. This is a retrospective observational study which is an extension of the previous ones.MethodsThe authors analyzed 18,805 surgical procedures performed during the study period from April 1 through September 30 in 2016–22. A non-radial and non-oriented Malmquist model under the variable returns-to-scale assumptions was employed. The decision-making unit (DMU) was defined as a surgical specialty department. Inputs were defined as (1) the number of assistants, and (2) the surgical duration. The output was defined as the surgical fee. The study period was divided into 42 one-month periods. The authors added all the inputs and outputs for each DMU during these study periods, and computed its Malmquist index, efficiency change and technical change. The outcome measures were its annual productivity, efficiency, and technical changes between the same months in each year.ResultsThere was no statistically significant difference in annual productivity, efficiency, and technical changes between pre-pandemic and post-pandemic periods.DiscussionNo evidence was found to suggest that the COVID-19 pandemic has any significant lasting effect of reducing the surgical productivity

Detecting System Failures with GPUs and LLVM

Since system failures cause a huge financial loss, they should be detected as early and accurately as possible and then be recovered rapidly. To detect system failures, there are mainly two methods: black-box and white-box monitoring. However, external black-box monitoring cannot obtain detailed information on system failures, while internal white-box one is largely affected by system failures. This paper proposes GPUSentinel for more reliable white-box monitoring using general-purpose GPUs. In GPUSentinel, system monitors running in a GPU analyze main memory and indirectly obtain the state of the target system. Since GPUs are isolated from the target system, system monitors are not easily affected by system failures. For easy development of system monitors, GPUSentinel provides a development environment including program transformation with LLVM. In addition, it also provides reliable notification mechanisms to remote hosts. We have implemented GPUSentinel using CUDA and the Linux kernel and confirmed that GPUSentinel could detect three types of system failures.10th ACM SIGOPS Asia-Pacific Workshop on Systems (APSys 2019), August 19 - 20, 2019 , Hangzhou, Chin

Safety and Efficacy of the Surgical Management of Hemodialysis Patients with Gastric Cancer

This retrospective study evaluated the short- and long-term outcomes after surgical management for gastric cancer in hemodialysis patients compared to non-dialysis patients. Twelve hemodialysis patients were compared with a propensity score-matched cohort of 39 gastric cancer patients who had not undergone hemodialysis. Short- and long-term outcomes along with scores estimating physiological ability and surgical stress were evaluated in both groups. The incidence of postoperative morbidity according to the Clavien-Dindo classification was higher in the hemodialysis gastric cancer group than in the non-dialysis gastric cancer group. The 5-year overall survival rate in the non-dialysis group was 69.2% after surgical resection for gastric cancer and 22.2% in the hemodialysis group. Patients with preoperative risk scores≥0.48 had significantly poorer survival outcomes compared to those with preoperative risk scores<0.48 (5-year survival rate, 83.3% vs. 39.4%, respectively). Our analyses suggest that hemodialysis patients undergoing surgery for gastric cancer have a significantly poorer postoperative prognosis and an elevated risk of postoperative complications