NeuroSynt: A Neuro-symbolic Portfolio Solver for Reactive Synthesis

We introduce NeuroSynt, a neuro-symbolic portfolio solver framework for reactive synthesis. At the core of the solver lies a seamless integration of neural and symbolic approaches to solving the reactive synthesis problem. To ensure soundness, the neural engine is coupled with model checkers verifying the predictions of the underlying neural models. The open-source implementation of NeuroSynt provides an integration framework for reactive synthesis in which new neural and state-of-the-art symbolic approaches can be seamlessly integrated. Extensive experiments demonstrate its efficacy in handling challenging specifications, enhancing the state-of-the-art reactive synthesis solvers, with NeuroSynt contributing novel solves in the current SYNTCOMP benchmarks

Integration of new biological and physical retrospective dosimetry methods into EU emergency response plans : joint RENEB and EURADOS inter-laboratory comparisons

Purpose: RENEB, 'Realising the European Network of Biodosimetry and Physical Retrospective Dosimetry,' is a network for research and emergency response mutual assistance in biodosimetry within the EU. Within this extremely active network, a number of new dosimetry methods have recently been proposed or developed. There is a requirement to test and/or validate these candidate techniques and inter-comparison exercises are a well-established method for such validation. Materials and methods: The authors present details of inter-comparisons of four such new methods: dicentric chromosome analysis including telomere and centromere staining; the gene expression assay carried out in whole blood; Raman spectroscopy on blood lymphocytes, and detection of radiation induced thermoluminescent signals in glass screens taken from mobile phones. Results: In general the results show good agreement between the laboratories and methods within the expected levels of uncertainty, and thus demonstrate that there is a lot of potential for each of the candidate techniques. Conclusions: Further work is required before the new methods can be included within the suite of reliable dosimetry methods for use by RENEB partners and others in routine and emergency response scenarios

Iterative Circuit Repair Against Formal Specifications

We present a deep learning approach for repairing sequential circuits against formal specifications given in linear-time temporal logic (LTL). Given a defective circuit and its formal specification, we train Transformer models to output circuits that satisfy the corresponding specification. We propose a separated hierarchical Transformer for multimodal representation learning of the formal specification and the circuit. We introduce a data generation algorithm that enables generalization to more complex specifications and out-of-distribution datasets. In addition, our proposed repair mechanism significantly improves the automated synthesis of circuits from LTL specifications with Transformers. It improves the state-of-the-art by 6.8 percentage points on held-out instances and 11.8 percentage points on an out-of-distribution dataset from the annual reactive synthesis competition

nl2spec: Interactively Translating Unstructured Natural Language to Temporal Logics with Large Language Models

A rigorous formalization of desired system requirements is indispensable when performing any verification task. This often limits the application of verification techniques, as writing formal specifications is an error-prone and time-consuming manual task. To facilitate this, we present nl2spec, a framework for applying Large Language Models (LLMs) to derive formal specifications (in temporal logics) from unstructured natural language. In particular, we introduce a new methodology to detect and resolve the inherent ambiguity of system requirements in natural language: we utilize LLMs to map subformulas of the formalization back to the corresponding natural language fragments of the input. Users iteratively add, delete, and edit these sub-translations to amend erroneous formalizations, which is easier than manually redrafting the entire formalization. The framework is agnostic to specific application domains and can be extended to similar specification languages and new neural models. We perform a user study to obtain a challenging dataset, which we use to run experiments on the quality of translations. We provide an open-source implementation, including a web-based frontend

The Abrasion Question. Some Factors in the Deterioration of Rubber When Exposed to Frictional Contacts with Other Materials

Abstract If we accept the proposal that the fundamental effect produced by the machines diagrammed in Fig. 1 is that of dragging a series of saw-toothed paddles across the surface of rubber specimens, we must accept as fact the theorem that the results recorded by these types of machines is a summarization of values rather than a fundamental value. If we accept the evidence that relations cannot be varied on any type of present abrasion testers to duplicate the conditions existing in all situations where rubber is exposed to frictional contacts with other materials, we must accept the fact that some fundamental factor is absent, or is over- or under-emphasized as these relations are varied. Whether these missing reactions can be supplied by evaluating other characteristics which will properly modify the results obtained on any given abrasion tester is an open question. It can be safely stated, however, that results obtained from any type of tester discussed can only be considered as evaluating rubber compositions at or near the point of optimum cure under one particular set of wear conditions. With one exception these conditions may safely be considered as approximating the conditions obtaining between a tire tread and the road under normal operating conditions. The Sproul-Evans tester may safely be considered as more closely approximating sand-blast hose conditions than tire-road conditions. It is the thought of the author that the most promising field of future endeavor lies in the direction of studying the possibility of reproducing more fundamental effects, rather than attempting to add more reactions to the already complex set of conditions present in the known types of abrasion testers. The suggestion is also offered that a most promising field of study lies in the direction of studying the modifying effect of distortion upon the fundamental characteristics of rubber, and attempting to establish the extent of distortion present when rubber is exposed to frictional disintegration in actual service conditions.</jats:p

Global Health Impact: A Model to Alleviate the Burden and Expand Access to Treatment of Neglected Tropical Diseases

Neglected tropical diseases (NTDs) receive relatively little research and development but have a tremendous impact on lifespan and livelihood. Here, we use existing data on the need for drugs, their efficacy, and their treatment percentages to estimate the impacts of various regimens on the global burden of several NTDs: schistosomiasis, onchocerciasis, lymphatic filariasis, and three soil-transmitted helminths (STHs) over time. For an interactive visualization of our models’ results, see https://www.global-health-impact.org/. In 2015, our NTD models estimate that treatment averted 2,778,131.78 disability-adjusted life years (DALYs). Together, treatments targeting STHs together averted 51.05% of the DALYs averted from all NTD treatments, whereas schistosomiasis, lymphatic filariasis, and onchocerciasis medicines averted 40.21%, 7.56%, and 1.18%, respectively. Our models highlight the importance of focusing not just on the burden of these diseases but also on their alleviation in the effort to expand access to treatment.</jats:p