AMIDA : a Sequence Diagram Extraction Toolkit Supporting Automatic Phase Detection

ICSE Companion '08: Companion of the 30th international conference on Software engineeringLeipzig, GermanyMay 10 - 18, 200

Semiclassical analysis of the bifundamental QCD on R2×T2\mathbb{R}^2\times T^2 with 't Hooft flux

We study the phase structure of bifundamental quantum chromodynamics (QCD(BF)), which is the $4$-dimensional $SU(N) \times SU(N)$ gauge theory coupled with the bifundamental fermion. Firstly, we refine constraints on its phase diagram from 't Hooft anomalies and global inconsistencies, and we find more severe constraints than those in previous literature about QCD(BF). Secondly, we employ the recently-proposed semiclassical approach for confining vacua to investigate this model concretely, and this is made possible via anomaly-preserving $T^2$ compactification. For sufficiently small $T^2$ with the 't Hooft flux, the dilute gas approximation of center vortices gives reliable semiclassical computations, and we determine the phase diagram as a function of the fermion mass $m$, two strong scales $\Lambda_{1},\Lambda_2$, and two vacuum angles, $\theta_1, \theta_2$. In particular, we find that the QCD(BF) vacuum respects the $\mathbb{Z}_2$ exchange symmetry of two gauge groups. Under the assumption of the adiabatic continuity, our result successfully explains one of the conjectured phase diagrams in the previous literature and also gives positive support for the nonperturbative validity of the large-$N$ orbifold equivalence between QCD(BF) and $\mathcal{N}=1$ $SU(2N)$ supersymmetric Yang-Mills theory. We also comment on problems of domain walls.Comment: 33 pages, 5 figures, small discussion adde

DPHuBERT: Joint Distillation and Pruning of Self-Supervised Speech Models

Self-supervised learning (SSL) has achieved notable success in many speech processing tasks, but the large model size and heavy computational cost hinder the deployment. Knowledge distillation trains a small student model to mimic the behavior of a large teacher model. However, the student architecture usually needs to be manually designed and will remain fixed during training, which requires prior knowledge and can lead to suboptimal performance. Inspired by recent success of task-specific structured pruning, we propose DPHuBERT, a novel task-agnostic compression method for speech SSL based on joint distillation and pruning. Experiments on SUPERB show that DPHuBERT outperforms pure distillation methods in almost all tasks. Moreover, DPHuBERT requires little training time and performs well with limited training data, making it suitable for resource-constrained applications. Our method can also be applied to various speech SSL models. Our code and models will be publicly available.Comment: Accepted at INTERSPEECH 2023. Code will be available at: https://github.com/pyf98/DPHuBER

Visualizing an Execution Trace as a Compact Sequence Diagram Using Dominance Algorithms

Visualizing an execution trace of an object-oriented system as sequence diagrams is effective to understand the behavior of the system. However, sequence diagrams extracted from an execution trace are too large for developers to inspect since a trace involves a large number of objects and method calls. To support developers to understand extracted sequence diagrams, it is necessary to remove the less important details of the diagrams. In this paper, we apply a dominance algorithm to a dynamic call graph among objects in order to detect and remove local objects contributing to internal behavior of dominator objects. The case study shows our approach automatically removed about 40 percent of the objects from execution traces on average.4th International Workshop on Program Comprehension through Dynamic Analysis(PCODA'08)co-located with the 15th International Working Conference on Reverse Engineering (WCRE’08)October 16th, 2008 – Antwerp, BelgiumAndy Zaidman, Abdelwahab Hamou-Lhadj, Orla Greevy, David Röthlisberger(editors)刊行年月日は会議開催日を参考にし

4D ASR: Joint modeling of CTC, Attention, Transducer, and Mask-Predict decoders

The network architecture of end-to-end (E2E) automatic speech recognition (ASR) can be classified into several models, including connectionist temporal classification (CTC), recurrent neural network transducer (RNN-T), attention mechanism, and non-autoregressive mask-predict models. Since each of these network architectures has pros and cons, a typical use case is to switch these separate models depending on the application requirement, resulting in the increased overhead of maintaining all models. Several methods for integrating two of these complementary models to mitigate the overhead issue have been proposed; however, if we integrate more models, we will further benefit from these complementary models and realize broader applications with a single system. This paper proposes four-decoder joint modeling (4D) of CTC, attention, RNN-T, and mask-predict, which has the following three advantages: 1) The four decoders are jointly trained so that they can be easily switched depending on the application scenarios. 2) Joint training may bring model regularization and improve the model robustness thanks to their complementary properties. 3) Novel one-pass joint decoding methods using CTC, attention, and RNN-T further improves the performance. The experimental results showed that the proposed model consistently reduced the WER.Comment: Accepted by INTERRSPEECH202

Indocyanine green-laden poly(ethylene glycol)-block-polylactide (PEG-b-PLA) nanocapsules incorporating reverse micelles: Effects of PEG-b-PLA composition on the nanocapsule diameter and encapsulation efficiency

Reverse micelles are thermodynamically stable systems, with a capacity to encapsulate hydrophilic molecules in their nanosized core, which is smaller than the core generally obtained with water-in-oil-emulsion droplets. Herein, we present a simple technique for the preparation of poly(ethylene glycol)-block-polylactide (PEG-b-PLA) nanocapsules encapsulating a hydrophilic photosensitizer (indocyanine green, ICG), which exploits reverse micelle formation and subsequent emulsion-solvent diffusion. We establish the effect of the PEG-b-PLA composition and the co-surfactant volume on the diameter and water content of the reverse micelles. We demonstrate that the composition of PEG-b-PLA affects also the diameter and encapsulation efficiency of the resulting nanocapsules. We show that the ICG-laden nanocapsules fabricated under the most optimal conditions have a diameter of approximately 100 nm and an ICG encapsulation efficiency of 58%. We believe that the method proposed here is a promising step towards the preparation of hydrophilic drug-laden polymer nanocapsules with a small diameter and therefore suitable for use in drug delivery applications based on enhanced permeability and retention (EPR) effect-driven passive targeting

Successful low-energy cardioversion using a novel biodegradable gel pad: Feasibility of treating postoperative atrial fibrillation in animals

ObjectivePostoperative atrial fibrillation is one of the most frequent complications of cardiac surgery. We developed a novel biodegradable gel pad consisting of biopolymers that directly attach to the myocardium by electrostatic interaction. The present study examines the feasibility and effectiveness of low-energy internal cardioversion using these pads.MethodsThe hearts of 6 pigs were exposed through a median sternotomy under general anesthesia, and 2 monopolar pacing wires were placed on the left pulmonary veins (chest open group). Two biodegradable cardioversion gel pads were placed on the right appendage and the left atria without suturing. All wires were extruded through the skin and secured with a suture. Sustained atrial fibrillation was induced by burst-pacing from the pulmonary veins in continuous 20-ms cycles. Shock intensity started at 0.5 J, and the energy level was increased in 0.5-J increments until cardioversion occurred. This protocol was repeated 5 times per pig. In a second group of 6 pigs (chest closed group), the epicardial cardioversion electrode gel pads and pacing wire electrodes were positioned as described above. Shock intensity was started at 0.5 J. If the shock was unsuccessful, the energy level was increased in 0.5-J increments until 2 consecutive cardioversions were achieved at a single energy level. At postoperative days 1, 3, 5, and 7, the defibrillation threshold was determined with the chest closed. At postoperative day 10, the cardioversion wires were removed. At predetermined time intervals, the heart was reexposed and the extent of degradation in vivo was visually evaluated and histologically assessed after sacrifice.ResultsAll pigs with induced atrial fibrillation were cardioverted to sinus rhythm on the determined postoperative day. The mean energy and lead impedance in the chest open group were 0.65 ± 0.23 J and 97.6 ± 5.52 Ω, respectively, and the overall values of mean energy and lead impedance in the chest closed group were 1.67 ± 1.00 J and 75.9 ± 13.3Ω, respectively. No complications were observed after wire removal. The gel pads became degraded and decreased in thickness, and signs of mild inflammation were evident on the gel pad. However, the gel pads did not elicit significant severe inflammatory reactions according to both gross and histologic assessments at 1 month after the surgery.ConclusionAtrial cardioversion using novel biodegradable gel pads that are easily affixed may afford a straightforward and effective treatment for atrial fibrillation after cardiac surgery