Solving Math Word Problems by Combining Language Models With Symbolic Solvers

Automatically generating high-quality step-by-step solutions to math word problems has many applications in education. Recently, combining large language models (LLMs) with external tools to perform complex reasoning and calculation has emerged as a promising direction for solving math word problems, but prior approaches such as Program-Aided Language model (PAL) are biased towards simple procedural problems and less effective for problems that require declarative reasoning. We propose an approach that combines an LLM that can incrementally formalize word problems as a set of variables and equations with an external symbolic solver that can solve the equations. Our approach achieves comparable accuracy to the original PAL on the GSM8K benchmark of math word problems and outperforms PAL by an absolute 20% on ALGEBRA, a new dataset of more challenging word problems extracted from Algebra textbooks. Our work highlights the benefits of using declarative and incremental representations when interfacing with an external tool for solving complex math word problems. Our data and prompts are publicly available at https://github.com/joyheyueya/declarative-math-word-problem

Reconstruction of metabolic networks from high-throughput metabolite profiling data: in silico analysis of red blood cell metabolism

We investigate the ability of algorithms developed for reverse engineering of transcriptional regulatory networks to reconstruct metabolic networks from high-throughput metabolite profiling data. For this, we generate synthetic metabolic profiles for benchmarking purposes based on a well-established model for red blood cell metabolism. A variety of data sets is generated, accounting for different properties of real metabolic networks, such as experimental noise, metabolite correlations, and temporal dynamics. These data sets are made available online. We apply ARACNE, a mainstream transcriptional networks reverse engineering algorithm, to these data sets and observe performance comparable to that obtained in the transcriptional domain, for which the algorithm was originally designed.Comment: 14 pages, 3 figures. Presented at the DIMACS Workshop on Dialogue on Reverse Engineering Assessment and Methods (DREAM), Sep 200

How do cities approach policy innovation and policy learning? A study of 30 policies in Northern Europe and North America

This paper reports on a study of current practice in policy transfer, and ways in which its effectiveness can be increased. A literature review identifies important factors in examining the transfer of policies. Results of interviews in eleven cities in Northern Europe and North America investigate these factors further. The principal motivations for policy transfer were strategic need and curiosity. Local officials and politicians dominated the process of initiating policy transfer, and local officials were also the leading players in transferring experience. A range of information sources are used in the search process but human interaction was the most important source of learning for two main reasons. First, there is too much information available through the Internet and the search techniques are not seen to be wholly effective in identifying the necessary information. Secondly, the information available on websites, portals and even good practice guides is not seen to be of mixed quality with risks of focussing only on successful implementation and therefore subject to some bias. Officials therefore rely on their trusted networks of peers for lessons as here they can access the ‘real implementation’ story and the unwritten lessons. Organisations which have a culture that is supportive of learning from elsewhere had strong and broad networks of external contacts and resourced their development whilst others are more insular or inward looking and reluctant to invest in policy lessons from elsewhere. Solutions to the problems identified in the evidence base are proposed

X-ray Astronomy in the Laboratory with a Miniature Compact Object Produced by Laser-Driven Implosion

Laboratory spectroscopy of non-thermal equilibrium plasmas photoionized by intense radiation is a key to understanding compact objects, such as black holes, based on astronomical observations. This paper describes an experiment to study photoionizing plasmas in laboratory under well-defined and genuine conditions. Photoionized plasma is here generated using a 0.5-keV Planckian x-ray source created by means of a laser-driven implosion. The measured x-ray spectrum from the photoionized silicon plasma resembles those observed from the binary stars Cygnus X-3 and Vela X-1 with the Chandra x-ray satellite. This demonstrates that an extreme radiation field was produced in the laboratory, however, the theoretical interpretation of the laboratory spectrum significantly contradicts the generally accepted explanations in x-ray astronomy. This model experiment offers a novel test bed for validation and verification of computational codes used in x-ray astronomy.Comment: 5 pages, 4 figures are included. This is the original submitted version of the manuscript to be published in Nature Physic

Combating pan-coronavirus infection by indomethacin through simultaneously inhibiting viral replication and inflammatory response

Severe infections with coronaviruses are often accompanied with hyperinflammation, requiring therapeutic strategies to simultaneously tackle the virus and inflammation. By screening a safe-in-human broad-spectrum antiviral agents library, we identified that indomethacin can inhibit pan-coronavirus infection in human cell and airway organoids models. Combining indomethacin with oral antiviral drugs authorized for treating COVID-19 results in synergistic anti-coronavirus activity. Coincidentally, screening a library of FDA-approved drugs identified indomethacin as the most potent potentiator of interferon response through increasing STAT1 phosphorylation. Combining indomethacin with interferon-alpha exerted synergistic antiviral effects against multiple coronaviruses. The anti-coronavirus activity of indomethacin is associated with activating interferon response. In a co-culture system of lung epithelial cells with macrophages, indomethacin inhibited both viral replication and inflammatory response. Collectively, indomethacin is a pan-coronavirus inhibitor that can simultaneously inhibit virus-triggered inflammatory response. The therapeutic potential of indomethacin can be further augmented by combining it with oral antiviral drugs or interferon-alpha.</p

Design Study of a Novel Positron Emission Tomography System for Plant Imaging

Positron Emission Tomography is a non-disruptive and high-sensitive digital imaging technique which allows to measure in-vivo and non invasively the changes of metabolic and transport mechanisms in plants. When it comes to the early assessment of stress-induced alterations of plant functions, plant PET has the potential of a major breakthrough. The development of dedicated plant PET systems faces a series of technological and experimental difficulties, which make conventional clinical and preclinical PET systems not fully suitable to agronomy. First, the functional and metabolic mechanisms of plants depend on environmental conditions, which can be controlled during the experiment if the scanner is transported into the growing chamber. Second, plants need to be imaged vertically, thus requiring a proper Field Of View. Third, the transverse Field of View needs to adapt to the different plant shapes, according to the species and the experimental protocols. In this paper, we perform a simulation study, proposing a novel design of dedicated plant PET scanners specifically conceived to address these agronomic issues. We estimate their expected sensitivity, count rate performance and spatial resolution, and we identify these specific features, which need to be investigated when realizing a plant PET scanner. Finally, we propose a novel approach to the measurement and verification of the performance of plant PET systems, including the design of dedicated plant phantoms, in order to provide a standard evaluation procedure for this emerging digital imaging agronomic technology

Why growth equals power - and why it shouldn't : constructing visions of China

When discussing the success of China's transition from socialism, there is a tendency to focus on growth figures as an indication of performance. Whilst these figures are indeed impressive, we should not confuse growth with development and assume that the former necessarily automatically generates the latter. Much has been done to reduce poverty in China, but the task is not as complete as some observers would suggest; particularly in terms of access to health, education and welfare, and also in dealing with relative (rather than absolute) depravation and poverty. Visions of China have been constructed that exaggerate Chinese development and power in the global system partly to serve political interests, but partly due to the failure to consider the relationship between growth and development, partly due to the failure to disaggregate who gets what in China, and partly due to the persistence of inter-national conceptions of globalised production, trade, and financial flows

Electromigration-Induced Propagation of Nonlinear Surface Waves

Due to the effects of surface electromigration, waves can propagate over the free surface of a current-carrying metallic or semiconducting film of thickness h_0. In this paper, waves of finite amplitude, and slow modulations of these waves, are studied. Periodic wave trains of finite amplitude are found, as well as their dispersion relation. If the film material is isotropic, a wave train with wavelength lambda is unstable if lambda/h_0 < 3.9027..., and is otherwise marginally stable. The equation of motion for slow modulations of a finite amplitude, periodic wave train is shown to be the nonlinear Schrodinger equation. As a result, envelope solitons can travel over the film's surface.Comment: 13 pages, 2 figures. To appear in Phys. Rev.