Unified Website Accessibility Assessment Framework

In this chapter, a unified web accessibility assessment (UWAA) framework and its software has been proposed. UWAA framework was developed by considering Web Content Accessibility Guideline 2.0 to evaluate accessibility of web sites by integrating more than one evaluation approach. Achecker tool as an automated evaluation approach and barrier walkthrough (BW) as an expert-based evaluation approach were integrated in the UWAA framework. The framework also provides suggestions to recover from the problems determined to the evaluators. The websites of three universities were evaluated to determine the framework's accuracy and consistency. It was revealed that the results obtained from automated and expert-based evaluation methods were consistent and complementary with each other. Furthermore, it has been demonstrated that problems which cannot be determined by an automated tool but which can be detected by an expert can be identified by BW method.

Electronic case report forms generation from pathology reports by ARGO, automatic record generator for onco-hematology

The unstructured nature of Real-World (RW) data from onco-hematological patients and the scarce accessibility to integrated systems restrain the use of RW information for research purposes. Natural Language Processing (NLP) might help in transposing unstructured reports into standardized electronic health records. We exploited NLP to develop an automated tool, named ARGO (Automatic Record Generator for Onco-hematology) to recognize information from pathology reports and populate electronic case report forms (eCRFs) pre-implemented by REDCap. ARGO was applied to hemo-lymphopathology reports of diffuse large B-cell, follicular, and mantle cell lymphomas, and assessed for accuracy (A), precision (P), recall (R) and F1-score (F) on internal (n = 239) and external (n = 93) report series. 326 (98.2%) reports were converted into corresponding eCRFs. Overall, ARGO showed high performance in capturing (1) identification report number (all metrics > 90%), (2) biopsy date (all metrics > 90% in both series), (3) specimen type (86.6% and 91.4% of A, 98.5% and 100.0% of P, 92.5% and 95.5% of F, and 87.2% and 91.4% of R for internal and external series, respectively), (4) diagnosis (100% of P with A, R and F of 90% in both series). We developed and validated a generalizable tool that generates structured eCRFs from real-life pathology reports.

A new automated tool to quantify nucleoid distribution within mitochondrial networks

Mitochondrial DNA (mtDNA) maintenance is essential to sustain a functionally healthy population of mitochondria within cells. Proper mtDNA replication and distribution within mitochondrial networks are essential to maintain mitochondrial homeostasis. However, the fundamental basis of mtDNA segregation and distribution within mitochondrial networks is still unclear. To address these questions, we developed an algorithm, Mitomate tracker to unravel the global distribution of nucleoids within mitochondria. Using this tool, we decipher the semi-regular spacing of nucleoids across mitochondrial networks. Furthermore, we show that mitochondrial fission actively regulates mtDNA distribution by controlling the distribution of nucleoids within mitochondrial networks. Specifically, we found that primary cells bearing disease-associated mutations in the fission proteins DRP1 and MYH14 show altered nucleoid distribution, and acute enrichment of enlarged nucleoids near the nucleus. Further analysis suggests that the altered nucleoid distribution observed in the fission mutants is the result of both changes in network structure and nucleoid density. Thus, our study provides novel insights into the role of mitochondria fission in nucleoid distribution and the understanding of diseases caused by fission defects.

Determining the Image Base of ARM Firmware by Matching Function Addresses

Firmware is software embedded in a device and acts as the most fundamental work of a system. Disassembly is a necessary step to understand the operational mechanism or detect the vulnerabilities of the firmware. When disassembling a firmware, it should first obtain the processor type of running environment and the image base of firmware. In general, the processor type can be obtained by tearing down the device or consulting the product manual. However, at present, there is still no automated tool that can be used to obtain the image base of all types of firmware. In this paper, we focus on firmware in ARM and propose an automated method to determine the image base address. Firstly, by studying the storage rule and loading mode of the function address, we can obtain the function offset and the function address loaded by LDR instruction, respectively. Then, with this information, we propose an algorithm, named Determining image Base by Matching Function Addresses (DBMFA), to determine the image base. The experimental results indicate that the proposed method can successfully determine the image base of firmware which uses LDR instruction to load function address.

GapMind for Carbon Sources: Automated annotations of catabolic pathways

GapMind for carbon sources is an automated tool for annotating catabolic pathways in bacterial and archaeal genomes. GapMind includes 62 compounds and identifies potential transporters and enzymes by their similarity to experimentally-characterized proteins. To improve GapMind's coverage, we used high-throughput genetic data from 29 bacteria and systematically examined the gaps. We identified novel pathways or enzymes for the utilization of glucosamine, citrulline, myo-inositol, lactose, and phenylacetate, and we annotated 299 diverged enzymes and transporters. We also curated 125 proteins from published reports. For the 29 bacteria with genetic data, GapMind finds high-confidence paths for 85% of utilized carbon sources. In diverse bacteria and archaea, 38% of utilized carbon sources have high-confidence paths, which was improved from 27% by incorporating the fitness-based annotations and our curation. GapMind for carbon sources is available as a web server (http://papers.genomics.lbl.gov/carbon) and takes just 30 seconds for the typical genome.