Prema: A Tool for Precise Requirements Editing, Modeling and Analysis

We present Prema, a tool for Precise Requirement Editing, Modeling and Analysis. It can be used in various fields for describing precise requirements using formal notations and performing rigorous analysis. By parsing the requirements written in formal modeling language, Prema is able to get a model which aptly depicts the requirements. It also provides different rigorous verification and validation techniques to check whether the requirements meet users' expectation and find potential errors. We show that our tool can provide a unified environment for writing and verifying requirements without using tools that are not well inter-related. For experimental demonstration, we use the requirements of the automatic train protection (ATP) system of CASCO signal co. LTD., the largest railway signal control system manufacturer of China. The code of the tool cannot be released here because the project is commercially confidential. However, a demonstration video of the tool is available at https://youtu.be/BX0yv8pRMWs.Comment: accepted by ASE2019 demonstration trac

ALA: Naturalness-aware Adversarial Lightness Attack

Most researchers have tried to enhance the robustness of DNNs by revealing and repairing the vulnerability of DNNs with specialized adversarial examples. Parts of the attack examples have imperceptible perturbations restricted by Lp norm. However, due to their high-frequency property, the adversarial examples can be defended by denoising methods and are hard to realize in the physical world. To avoid the defects, some works have proposed unrestricted attacks to gain better robustness and practicality. It is disappointing that these examples usually look unnatural and can alert the guards. In this paper, we propose Adversarial Lightness Attack (ALA), a white-box unrestricted adversarial attack that focuses on modifying the lightness of the images. The shape and color of the samples, which are crucial to human perception, are barely influenced. To obtain adversarial examples with a high attack success rate, we propose unconstrained enhancement in terms of the light and shade relationship in images. To enhance the naturalness of images, we craft the naturalness-aware regularization according to the range and distribution of light. The effectiveness of ALA is verified on two popular datasets for different tasks (i.e., ImageNet for image classification and Places-365 for scene recognition).Comment: 9 page

FREPA: An Automated and Formal Approach to Requirement Modeling and Analysis in Aircraft Control Domain

Formal methods are promising for modeling and analyzing system requirements. However, applying formal methods to large-scale industrial projects is a remaining challenge. The industrial engineers are suffering from the lack of automated engineering methodologies to effectively conduct precise requirement models, and rigorously validate and verify (V&V) the generated models. To tackle this challenge, in this paper, we present a systematic engineering approach, named Formal Requirement Engineering Platform in Aircraft (FREPA), for formal requirement modeling and V\&V in the aerospace and aviation control domains. FREPA is an outcome of the seamless collaboration between the academy and industry over the last eight years. The main contributions of this paper include 1) an automated and systematic engineering approach FREPA to construct requirement models, validate and verify systems in the aerospace and aviation control domain, 2) a domain-specific modeling language AASRDL to describe the formal specification, and 3) a practical FREPA-based tool AeroReq which has been used by our industry partners. We have successfully adopted FREPA to seven real aerospace gesture control and two aviation engine control systems. The experimental results show that FREPA and the corresponding tool AeroReq significantly facilitate formal modeling and V&V in the industry. Moreover, we also discuss the experiences and lessons gained from using FREPA in aerospace and aviation projects.Comment: 12 pages, Published by FSE 202

Value of deep learning models based on ultrasonic dynamic videos for distinguishing thyroid nodules

ObjectiveThis study was designed to distinguish benign and malignant thyroid nodules by using deep learning(DL) models based on ultrasound dynamic videos.MethodsUltrasound dynamic videos of 1018 thyroid nodules were retrospectively collected from 657 patients in Zhejiang Cancer Hospital from January 2020 to December 2020 for the tests with 5 DL models.ResultsIn the internal test set, the area under the receiver operating characteristic curve (AUROC) was 0.929(95% CI: 0.888,0.970) for the best-performing model LSTM Two radiologists interpreted the dynamic video with AUROC values of 0.760 (95% CI: 0.653, 0.867) and 0.815 (95% CI: 0.778, 0.853). In the external test set, the best-performing DL model had AUROC values of 0.896(95% CI: 0.847,0.945), and two ultrasound radiologist had AUROC values of 0.754 (95% CI: 0.649,0.850) and 0.833 (95% CI: 0.797,0.869).ConclusionThis study demonstrates that the DL model based on ultrasound dynamic videos performs better than the ultrasound radiologists in distinguishing thyroid nodules

Visualization balloon occlusion-assisted technique in the treatment of large or giant paraclinoid aneurysms: A study of 17 cases series

ObjectiveAlthough balloon-assisted techniques are valuable in aneurysm clipping, repeated angiography and fluoroscopy are required to understand the location and shape of the balloon. This study investigated the value of visualization balloon occlusion-assisted techniques in aneurysm hybridization procedures.MethodsWe propose a visualization balloon technique that injects methylene blue into the balloon, allowing it to be well visualized under a microscope without repeated angiography. This study retrospects the medical records of 17 large or giant paraclinoid aneurysms treated by a visualization balloon occlusion-assisted technique in a hybrid operating room. Intraoperative surgical techniques, postoperative complications, and immediate and long-term angiographic findings are highlighted.ResultsAll 17 patients had safe and successful aneurysm clipping surgery with complete angiographic occlusion. Under the microscope, the balloon injected with methylene blue is visible through the arterial wall. The position and shape of the balloon can be monitored in real time without repeated angiography and fluoroscopic guidance. Two cases of intraoperative visualization balloon shift and slip into the aneurysm cavity were detected in time, and there were no cases of balloon misclipping or difficult removal. Of 17 patients, four patients (23.5%) experienced short-term complications, including pulmonary infection (11.8%), abducens nerve paralysis (5.9%), and thalamus hemorrhage (5.9%). The rate of vision recovery among patients with previous visual deficits was 70% (7 of 10 patients). The mean follow-up duration was 32.76 months. No aneurysms or neurological deficits recurred among all patients who completed the follow-up.ConclusionOur study indicates that microsurgical clipping with the visualization balloon occlusion-assisted technique seems to be a safe and effective method for patients with large or giant paraclinoid aneurysms to reduce the surgical difficulty and simplify the operation process of microsurgical treatment alone

Characteristics and operation outcomes of neuro-oncology patients after COVID-19 pandemic — A case series

Background: COVID-19 has been spreading worldwide at hitherto unknown speed, and the treatment of neuro-oncology patients without COVID-19 has been greatly affected. Methods: To compare the medical records and surgical results of surgical patients before and after the pandemic. We collected a total of 80 patients form April 2020 to May 2020 after pandemic and from April 2019 to May 2019 before pandemic. The patient's demographics, past medical history, comorbidities, imaging, pathology, laboratory teat, and Karnofsky Performance Score (KPS) were analyzed. Results: The most common presenting symptom was intracranial hypertension and neurological deficit. Hypertension and diabetes were the most common comorbid diseases. The pre-operation KPS were 83.21 ± 15.60, 80 ± 14.77, 78.57 ± 12.83 and 74.14 ± 12.72, respectively. The post-operation KPS were 94.64 ± 8.65, 95.45 ± 6.56, 91.43 ± 10.82 and 84.21 ± 22.55, respectively. The tumor volume was larger and the midline shift distance was greater after the pandemic than before. For pathological grade, meningiomas were mostly grade I, while gliomas were mainly grade III and IV. Conclusion: Although affected by the COVID-19 pandemic, patients with glioma should be operated as soon as possible to obtain better surgical results, however, for patients with meningiomas, their operation can be postponed slightly when the patients are tolerable

Comparative Proteomic Profiling of Human Bile Reveals SSP411 as a Novel Biomarker of Cholangiocarcinoma

<div><h3>Background</h3><p>Cholangiocarcinoma (CC) is an intractable cancer, arising from biliary epithelial cells, which has a poor prognosis and is increasing in incidence. Early diagnosis of CC is essential as surgical resection remains the only effective therapy. The purpose of this study was to identify improved biomarkers to facilitate early diagnosis and prognostication in CC.</p> <h3>Methods</h3><p>A comparative expression profile of human bile samples from patients with cholangitis and CC was constructed using a classic 2D/MS/MS strategy and the expression of selected proteins was confirmed by Western blotting. Immunohistochemistry was performed to determine the expression levels of selected candidate biomarkers in CC and matched normal tissues. Finally, spermatogenesis associated 20 (SSP411; also named SPATA20) was quantified in serum samples using an ELISA.</p> <h3>Results</h3><p>We identified 97 differentially expressed protein spots, corresponding to 49 different genes, of which 38 were upregulated in bile from CC patients. Western blotting confirmed that phosphoglycerate mutase 1 (brain) (PGAM-1), protein disulfide isomerase family A, member 3 (PDIA3), heat shock 60 kDa protein 1 (chaperonin) (HSPD1) and SSP411 were significantly upregulated in individual bile samples from CC patients. Immunohistochemistry demonstrated these proteins were also overexpressed in CC, relative to normal tissues. SSP411 displayed value as a potential serum diagnostic biomarker for CC, with a sensitivity of 90.0% and specificity of 83.3% at a cutoff value of 0.63.</p> <h3>Conclusions</h3><p>We successfully constructed a proteomic profile of CC bile proteins, providing a valuable pool novel of candidate biomarkers. SSP411 has potential as a biomarker for the diagnosis of CC.</p> </div

2-DE gels of pooled human bile samples.

<p>(A, B) 2-DE maps of pooled bile samples from cholangiocarcinoma patients (A; n = 5 each) and pooled samples from cholangitis patients (B; n = 3 or 4 each). The proteins were separated by 2D-PAGE and visualized by silver staining. The differentially expressed proteins selected as potential biomarkers are marked.</p

Western blot validation of four candidate cholangiocarcinoma biomarkers in individual bile samples.

<p>Western blotting (top) and quantification (bottom) of candidate biomarker expression in equal volumes of individual bile samples from 10 cholangitis patients (benign) and 19 cholangiocarcinoma (CC) patients. (A) PGAM-1; (B) PDIA3; (C) HSPD1 (D) and SSP411.</p

Validation of the diagnostic value of SSP411 in serum samples using an ELISA.

<p>(A). Distribution of the serum OD value in cholangiocarcinoma (CC) patients, patients with benign disease and healthy individuals. (B). Receiver operating characteristic (ROC) analysis for the optimal cut-off point for discrimination between between different groups (CC vs. benign; CC vs. benign+normal; benign vs. normal). (C). Distribution of the serum OD values in hepatocellular carcinoma (HCC) patients, patients with liver cirrhosis and healthy individuals. (D). ROC analysis of SSP411 for HCC. (E). ROC analysis results between different CC and HCC groups.</p