Detecting Floating-Point Errors via Atomic Conditions

This paper tackles the important, difficult problem of detecting program inputs that trigger large floating-point errors in numerical code. It introduces a novel, principled dynamic analysis that leverages the mathematically rigorously analyzed condition numbers for atomic numerical operations, which we call atomic conditions, to effectively guide the search for large floating-point errors. Compared with existing approaches, our work based on atomic conditions has several distinctive benefits: (1) it does not rely on high-precision implementations to act as approximate oracles, which are difficult to obtain in general and computationally costly; and (2) atomic conditions provide accurate, modular search guidance. These benefits in combination lead to a highly effective approach that detects more significant errors in real-world code (e.g., widely-used numerical library functions) and achieves several orders of speedups over the state-of-the-art, thus making error analysis significantly more practical. We expect the methodology and principles behind our approach to benefit other floating-point program analysis tasks such as debugging, repair and synthesis. To facilitate the reproduction of our work, we have made our implementation, evaluation data and results publicly available on GitHub at https://github.com/FP-Analysis/atomic-condition.ISSN:2475-142

Theoretical Guidance on Evacuation Decisions after a Big Nuclear Accident under the Assumption That Evacuation Is Desirable

The development of nuclear power is a major measure for implementing energy-saving and emission reduction strategies all over the world. For a long time, the hazards of nuclear accidents have been obstacles to the development of nuclear power. Temporary evacuation is the fastest and most effective emergency measure to ensure the safety of residents in a short period of time after a nuclear accident. Numerous nuclear accident emergency management personnel make judgments based on personal work experience and subjective awareness when formulating a nuclear accident emergency evacuation plan. How to make a scientific and reasonable decision on the emergency evacuation of nuclear accidents in the shortest time is a common problem faced by many emergency departments when a nuclear accident occurs. In a complex and ever-changing radiation environment, how to maximize the use of limited information and make decisions quickly in an uncertain environment is a core issue that effectively reduces the risk of nuclear accidents. This paper constructs a set of assessment system of nuclear accident emergency evacuation plan selection based on the characteristics of nuclear accident emergencies under uncertain environmental conditions. It uses triangular fuzzy language to describe nuclear accident emergency evacuation decision plans and the weighting of relevant factors. Additionally, the K-means clustering method is used to calculate the weight of experts, which reduces the influence of subjective factors considered by decision makers. Finally, a decision model for emergency evacuation of nuclear accidents is constructed based on the TOPSIS decision model

Nutritional and Medicinal Use of Cactus Pear (Opuntia Spp.) Cladodes and Fruits

Natural products and health foods have recently received a lot of attention both by health professionals and the common population for improving overall well-being, as well as in the prevention of diseases including cancer. In this line, all types of fruits and vegetables have been reevaluated and recognized as valuable sources of nutraceuticals. The great number of potentially active nutrients and their multifunctional properties make cactus pear (Opuntia spp.) fruits and cladodes perfect candidates for the production of health-promoting food and food supplements. Although traditionally appreciated for its pharmacological properties by the Native Americans, cactus pear is still hardly recognized because of insufficient scientific information. However, recent studies on Opuntia spp. have demonstrated cactus pear fruit and vegetative cladodes to be excellent candidates for the development of healthy food. Therefore, this review summarizes current knowledge on the chemical composition of Opuntia cacti with particular emphasis in its use as food and medicine

Optimization Design of Pressure Hull for Long-Range Underwater Glider Based on Energy Consumption Constraints

Underwater gliders are a class of ocean observation equipment driven by buoyancy, and their energy consumption source is mainly generated by the active regulation of buoyancy. The periodic elastic deformation of the pressure hull during the upward and downward movement of the underwater glider can have a large impact on its driving buoyancy. This paper relates the optimization problem of the pressure hull with the energy consumption of underwater glider, and the energy improvement factor is taken as the optimization objective. Based on the mechanical theory, the theoretical optimization model and constraint model are derived. A hybrid genetic simulated annealing algorithm (HGSAA) is adopted to optimize the pressure hull of the underwater glider developed by Huazhong University of Science and Technology (HUST). Additionally, the effectiveness of the optimized mathematical model and optimization results were verified by the tests. The sea trial results show that after the pressure hull optimization, the energy consumption of the buoyancy regulation unit decreased by 21.9%, and the total energy carried increased by 12.4%

Oracle-free repair synthesis for floating-point programs

The floating-point representation provides widely-used data types (such as “float” and “double”) for modern numerical software. Numerical errors are inherent due to floating-point’s approximate nature, and pose an important, well-known challenge. It is nontrivial to fix/repair numerical code to reduce numerical errors — it requires either numerical expertise (for manual fixing) or high-precision oracles (for automatic repair); both are difficult requirements. To tackle this challenge, this paper introduces a principled dynamic approach that is fully automated and oracle-free for effectively repairing floating-point errors. The key of our approach is the novel notion of micro-structure that characterizes structural patterns of floating-point errors. We leverage micro-structures’ statistical information on floating-point errors to effectively guide repair synthesis and validation. Compared with existing state-of-the-art repair approaches, our work is fully automatic and has the distinctive benefit of not relying on the difficult to obtain high-precision oracles. Evaluation results on 36 commonly-used numerical programs show that our approach is highly efficient and effective: (1) it is able to synthesize repairs instantaneously, and (2) versus the original programs, the repaired programs have orders of magnitude smaller floating-point errors, while having faster runtime performance.ISSN:2475-142

A Genetic Algorithm for Detecting Significant Floating-Point Inaccuracies

It is well-known that using floating-point numbers may inevitably result in inaccurate results and sometimes even cause serious software failures. Safety-critical software often has strict requirements on the upper bound of inaccuracy, and a crucial task in testing is to check whether significant inaccuracies may be produced. The main existing approach to the floating-point inaccuracy problem is error analysis, which produces an upper bound of inaccuracies that may occur. However, a high upper bound does not guarantee the existence of inaccuracy defects, nor does it give developers any concrete test inputs for debugging. In this paper, we propose the first metaheuristic search-based approach to automatically generating test inputs that aim to trigger significant inaccuracies in floating-point programs. Our approach is based on the following two insights: (1) with FPDebug, a recently proposed dynamic analysis approach, we can build a reliable fitness function to guide the search; (2) two main factors - the scales of exponents and the bit formations of significands - may have significant impact on the accuracy of the output, but in largely different ways. We have implemented and evaluated our approach over 154 real-world floating-point functions. The results show that our approach can detect significant inaccuracies in the subjects.EICPCI-S(ISTP)[email protected]; [email protected]; [email protected]; [email protected]; [email protected]; [email protected]

Evaluation of microalgae on preventing bone loss in C57BL/6J mice induced by hindlimb suspension

Abstract Bone loss caused by microgravity severely damages the health of astronauts; however, no effective countermeasures exist. Microalgae are microscopic algae rich in protein, polysaccharide, and other nutrients, which can provide astronauts with safe food and oxygen supply in the space ecosystem. Recent studies have demonstrated that microalgae can potentially reduce bone loss in primary osteoporosis. Here, a hindlimb suspension (HLS) mouse (C57BL/6J) model was used to investigate the potential effects of five different microalgae in preventing microgravity‐induced bone loss. The results showed that long‐term administration of 300 mg/kg body weight/day Spirulina platensis (SP) significantly reduced bone loss and increased trabecular number and bone strength. In addition, mice in the HLS group also exhibited disordered gut microbiota with increased Firmicutes/Bacteroidetes, decreased fecal short‐chain fatty acids levels, and increased levels of colonic proinflammatory cytokines interleukin‐6 and tumor necrosis factor‐α. To a certain extent, SP reduced these changes and maintained homeostasis of the intestinal environment. These results suggest that SP has a potential enhancing effect on resistance to bone loss in HLS mice