The Status and Prospects of the Licensed Pharmacist Qualification System in China

The Licensed Pharmacist Qualification System refers to a series of systems of Licensed Pharmacist management. The establishment and development of the Licensed Pharmacist Qualification System plays an unparallel role in the improvement of pharmaceutical care and the training of pharmaceutical professionals. This article generally describes the Licensed Pharmacist Qualification System in China, makes a comparison study between Chinese and American Licensed Pharmacist Qualification System and discusses about the future development of the Licensed Pharmacist Qualification System. Key words:licensed qualification; licensed pharmacist; pharmaceutical car

A Workflow Management System Guide

A workflow describes the entirety of processing steps in an analysis, such as employed in many fields of physics. Workflow management makes the dependencies between individual steps of a workflow and their computational requirements explicit, such that entire workflows can be executed in a stand-alone manner. Though the use of workflow management is widely recommended in the interest of transparency, reproducibility and data preservation, choosing among the large variety of available workflow management tools can be overwhelming. We compare selected workflow management tools concerning all relevant criteria and make recommendations for different use cases

Improved selective background Monte Carlo simulation at Belle II with graph attention networks and weighted events

When measuring rare processes at Belle II, a huge luminosity is required, which means a large number of simulations are necessary to determine signal efficiencies and background contributions. However, this process demands high computation costs while most of the simulated data, in particular in case of background, are discarded by the event selection. Thus, filters using graph neural networks are introduced at an early stage to save the resources for the detector simulation and reconstruction of events discarded at analysis level. In our work, we improved the performance of the filters using graph attention and investigated statistical methods including sampling and reweighting to deal with the biases introduced by the filtering.Comment: to be published in ACAT 2022 proceedings in the Journal Of Physics: Conference Serie

Latent-Optimized Adversarial Neural Transfer for Sarcasm Detection

The existence of multiple datasets for sarcasm detection prompts us to apply transfer learning to exploit their commonality. The adversarial neural transfer (ANT) framework utilizes multiple loss terms that encourage the source-domain and the target-domain feature distributions to be similar while optimizing for domain-specific performance. However, these objectives may be in conflict, which can lead to optimization difficulties and sometimes diminished transfer. We propose a generalized latent optimization strategy that allows different losses to accommodate each other and improves training dynamics. The proposed method outperforms transfer learning and meta-learning baselines. In particular, we achieve 10.02% absolute performance gain over the previous state of the art on the iSarcasm dataset.Comment: 14 pages, 5 figures, published at NAACL-HLT 2021 conference, see https://www.aclweb.org/anthology/2021.naacl-main.425