Ordered Context-Free Grammars Revisited

We continue our study of ordered context-free grammars, a grammar formalism that places an order on the parse trees produced by the corresponding context-free grammar. In particular, we simplify our previous definition of a derivation of a string for a given ordered context-free grammar, and present a parsing algorithm, using shared packed parse forests, with time complexity O(n^4), where n is the length of the input string being parsed.Comment: In Proceedings NCMA 2023, arXiv:2309.0733

Analyzing Catastrophic Backtracking Behavior in Practical Regular Expression Matching

We develop a formal perspective on how regular expression matching works in Java, a popular representative of the category of regex-directed matching engines. In particular, we define an automata model which captures all the aspects needed to study such matching engines in a formal way. Based on this, we propose two types of static analysis, which take a regular expression and tell whether there exists a family of strings which makes Java-style matching run in exponential time.Comment: In Proceedings AFL 2014, arXiv:1405.527

Formalizing BPE Tokenization

In this paper, we formalize practical byte pair encoding tokenization as it is used in large language models and other NLP systems, in particular we formally define and investigate the semantics of the SentencePiece and HuggingFace tokenizers, in particular how they relate to each other, depending on how the tokenization rules are constructed. Beyond this we consider how tokenization can be performed in an incremental fashion, as well as doing it left-to-right using an amount of memory constant in the length of the string, enabling e.g. using a finite state string-to-string transducer.Comment: In Proceedings NCMA 2023, arXiv:2309.0733

Generation of Library Models for Verification of Android Applications

Android applications are difficult to verify and test since they have many external dependencies. To overcome this problem, environment generation can be used to create a model of the environment to simulate the behavior of these external dependencies. Creating this environment model manually is a tedious process and although there are many techniques available to generate models, the key lies in identifying how these techniques can be applied to a specific domain. In this paper we discuss two static analysis tools OCSEGen and Modgen and how they can be applied to the Android domain to generate models for specific parts of the environment

Environment Modeling Using Runtime Values for JPF-Android

Software applications are developed to be executed in a specific environment. This environment includes external native libraries to add functionality to the application and drivers to fire the application execution. For testing and verification, the environment of an application is simplified abstracted using models or stubs. Empty stubs, returning default values, are simple to generate automatically, but they do not perform well when the application expects specific return values. Symbolic execution is used to find input parameters for drivers and return values for library stubs, but it struggles to detect the values of complex objects. In this work-in-progress paper, we explore an approach to generate drivers and stubs based on values collected during runtime instead of using default values. Entry-points and methods that need to be modeled are instrumented to log their parameters and return values. The instrumented applications are then executed using a driver and instrumented libraries. The values collected during runtime are used to generate driver and stub values on- the-fly that improve coverage during verification by enabling the execution of code that previously crashed or was missed. We are implementing this approach to improve the environment model of JPF-Android, our model checking and analysis tool for Android applications

The Near-Ring of Lipschitz Functions on a Metric Space

This paper treats near-rings of zero-preserving Lipschitz functions on metric spaces that are also abelian groups, using pointwise addition of functions as addition and composition of functions as multiplication. We identify a condition on the metric ensuring that the set of all such Lipschitz functions is a near-ring, and we investigate the complications that arise from the lack of left distributivity in the resulting right near-ring. We study the behavior of the set of invertible Lipschitz functions, and we initiate an investigation into the ideal structure of normed near-rings of Lipschitz functions. Examples are given to illustrate the results and to demonstrate the limits of the theory

Sodium valproate poisoning. A case report

CITATION: Van der Merwe, A. C. et al. 1985. Sodium valproate poisoning. A case report. South African Medical Journal, 67:735-736.The original publication is available at http://www.samj.org.zaA case of a severe overdose of sodium valproate (more than 10 times the therapeutic requirement) is discussed. The patient presented with central nervous, respiratory and cardiovascular depression and was treated with supportive therapy and haemoperfusion. However, on available data it would appear that haemoperfusion did not make a significant contribution towards the patient's recovery.Publisher’s versio

Automatic assignment of diagnosis codes to free-form text medical note

International Classification of Disease (ICD) coding plays a significant role in classify-ing morbidity and mortality rates. Currently, ICD codes are assigned to a patient’s medical record by hand by medical practitioners or specialist clinical coders. This practice is prone to errors, and training skilled clinical coders requires time and human resources. Automatic prediction of ICD codes can help alleviate this burden. In this paper, we propose a transformer-based architecture with label-wise attention for predicting ICD codes on a medical dataset. The transformer model is first pre-trained from scratch on a medical dataset. Once this is done, the pre-trained model is used to generate representations of the tokens in the clinical documents, which are fed into the label-wise attention layer. Finally, the outputs from the label-wise attention layer are fed into a feed-forward neural network to predict appropriate ICD codes for the input document. We evaluate our model using hospital discharge summaries and their corresponding ICD-9 codes from the MIMIC-III dataset. Our experimental results show that our transformer model outperforms all previous models in terms of micro-F1 for the full label set from the MIMIC-III dataset. This is also the first successful application of a pre-trained transformer architecture to the auto-coding problem on the full MIMIC-III dataset

Long-term follow-up of R403W MYH7 and R92W TNNT2 HCM families : mutations determine left ventricular dimensions but not wall thickness during disease progression

The original publication is available at http://www.cvja.co.za/CVJA holds the copyrightThe clinical profile and prognosis of patients with hypertrophic cardiomyopathy, a primary cardiac muscle disease caused mostly by mutations in sarcomeric protein-encoding genes, have been linked to particular disease-causing mutations in the past. However, such associations are often based on cross-sectional observations, as longitudinal studies of the progression of the disease in genotypically defined patients are sparse. Most importantly, the relative contribution of age, gender and genetic cause to disease profile and progression has not yet been reported, and the question remains whether one or more of these factors could mask the effect of the other(s). Methods: We previously described cross-sectional family studies of two hypertrophic cardiomyopathy (HCM)-causing mutations, R92WTNNT2 and R403WMYH7, both associated with minimal hypertrophy, but with widely different life expectancies. We re-investigated 22 and 26 R92WTNNT2 and R403WMYH7 mutation carriers in these and additional South African R92WTNNT2 families after a mean 11.08 ± 2.79 years, and compared the influence of the two mutations, in the context of age and gender, on disease progression. Results: We demonstrated a positive correlation between age and interventricular septal thickness for both mutations, with more than a third of all mutation carriers developing clinically recognised hypertrophy only after the age of 35 years. This period of hypertrophically silent HCM also coincided with the years in which most sudden cardiac deaths occurred, particularly in male R92WTNNT2 carriers. Statistical analyses indicated that the particular mutation was the strongest determinant of left ventricular remodelling; particularly, LVESD increased and EF reduction was noted in the majority of R403WMYH7 carriers, which may require clinical follow-up over the longer term. Conclusions: Statistical modelling of follow-up data suggests that an interplay between unidentified, possibly genderassociated factors, and the causal mutation are the determinants of eventual cardiac function and survival, but not of the extent of hypertrophy, and emphasises the need for long-term follow-up even in individuals with apparently mild disease.Publishers' Versio

Genetic variation in angiotensin II type 2 receptor gene influences extent of left ventricular hypertrophy in hypertrophic cardiomyopathy independent of blood pressure

Introduction. Hypertrophic cardiomyopathy (HCM), an inherited primary cardiac disorder mostly caused by defective sarcomeric proteins, serves as a model to investigate left ventricular hypertrophy (LVH). HCM manifests extreme variability in the degree and distribution of LVH, even in patients with the same causal mutation. Genes coding for renin—angiotensin—aldosterone system components have been studied as hypertrophy modifiers in HCM, with emphasis on the angiotensin (Ang) II type 1 receptor (AT1R). However, Ang II binding to Ang II type 2 receptors (AT2R) also has hypertrophy-modulating effects. Methods. We investigated the effect of the functional +1675 G/A polymorphism (rs1403543) and additional single nucleotide polymorphisms in the 3' untranslated region of the AT2R gene ( AGTR2) on a heritable composite hypertrophy score in an HCM family cohort in which HCM founder mutations segregate. Results. We find significant association between rs1403543 and hypertrophy, with each A allele decreasing the average wall thickness by ~0.5 mm, independent of the effects of the primary HCM causal mutation, blood pressure and other hypertrophy covariates ( p = 0.020). Conclusion. This study therefore confirms a hypertrophy-modulating effect for AT2R also in HCM and implies that +1675 G/A could potentially be used in a panel of markers that profile a genetic predisposition to LVH in HCM