LFTOP: An LF based approach to domain specific reasoning

Specialized vocabulary, notations and inference rules tailored for the description, analysis and reasoning of a domain is very important for the domain. For domain-specific issues researchers focus mainly on the design and implementation of domain-specific languages (DSL) and pay little attention to the reasoning aspects. We believe that domain-specific reasoning is very important to help the proofs of some properties of the domains and should be more concise, more reusable and more believable. It deserves to be investigated in an engineering way. Type theory provides good support for generic reasoning and verification. Many type theorists want to extend uses of type theory to more domains, and believe that the methods, ideas, and technology of type theory can have a beneficial effect for computer assisted reasoning in many domains. Proof assistants based on type theory are well known as effective tools to support reasoning. But these proof assistants have focused primarily on generic notations for representation of problems and are oriented towards helping expert type theorists build proofs efficiently. They are successful in this goal, but they are less suitable for use by non-specialists. In other words, one of the big barriers to limit the use of type theory and proof assistant in domain-specific areas is that it requires significant expertise to use it effectively. We present LFTOP ― a new approach to domain-specific reasoning that is based on a type-theoretic logical framework (LP) but does not require the user to be an expert in type theory. In this approach, users work on a domain-specific interface that is familiar to them. The interface presents a reasoning system of the domain through a user-oriented syntax. A middle layer provides translation between the user syntax and LF， and allows additional support for reasoning (e.g. model checking). Thus, the complexity of the logical framework is hidden but we also retain the benefits of using type theory and its related tools, such as precision and machine-checkable proofs. The approach is being investigated through a number of case studies. In each case study, the relevant domain-specific specification languages and logic are formalized in Plastic. The relevant reasoning system is designed and customized for the users of the corresponding specific domain. The corresponding lemmas are proved in Plastic. We analyze the advantages and shortcomings of this approach, define some new concepts related to the approach, especially discuss issues arising from the translation between the different levels. A prototype implementation is developed. We illustrate the approach through many concrete examples in the prototype implementation. The study of this thesis shows that the approach is feasible and promising, the relevant methods and technologies are useful and effective

A Migration Method of MPI Program Combining Local Library Replacement and Instruction Translation

Binary translation acts as a main method used to solve software compatibility among different instruction set architectures (ISAs), yet the main objects that the binary translator deals with are serial programs but not parallel programs. We propose a hybrid method combining local library replacement and instruction translation based on a formal model built to describe the equivalent when migrating MPI programs between different clusters. The shared codes in a MPI program (MPI library function call) are treated by executing local libraries, and the other parts are done by dynamic binary translation. Also, during the course of dealing with local library functions, we propose a method of program flow redirection by designing two algorithms along with hierarchically encapsulating local libraries. A framework called MPI-QEMU is designed to implement migrating MPI program of 64 bits from X86-64/Linux platform to the domestic SW platform which is verified by experiment

PO-077 Hypoxia exercise improves glucose metabolism in the overweight and obese women

Objective With the increase of social pressure and the unreasonable diet structure, the proportion of the overweight and obese people is increasing. Obesity is an important factor causing many chronic diseases, such as type II diabetes, atherosclerosis, hypertension, hyperlipidemia and so on. Epidemiological studies show that the proportion of obese people in China is still high. It has seriously hindered the further development of the Chinese health. The combination of diet and exercise is effective for reducing the weight. However, this method isn’t effective for overweight and obese people. Therefore, the way to reduce weight has become a central issue for many researchers. Studies have shown that the exposure of hypoxia condition can decrease weight and exercise can promote energy consumption. Exercises in a hypoxic environment provide a new way of thinking for the prevention and treatment of obesity and national fitness, and which are also a research hotspot for weight loss. Methods The study enrolled 40 young women with overweight/obese subjects, aged 18-47 years, with no abnormal physical examination. The criterion for overweight is BMI ≥ 24 and the criterion for obesity is BMI ≥ 28. All subjects were paired according to their body weight, divided into hypoxia group and normoxia group and they exercised for 6 weeks, 3 times a week, every other day. The content of the exercise intervention includes 30 minutes strength training and 30minutes endurance training. Strength training is in front and endurance training is in the back. There are 5 minutes of warm-up and finishing activities before and after training. Strength training uses dumbbells, chooses 12RM weight, exercise with 8 actions, which are dead lift, upright row, squat, shoulder press, calf Jump, advance junge, biceps curl and triceps extension, each action 2 Group, rest between groups for 30s. Endurance training uses a treadmill with a slope of 0°, and the speed is adjusted according to the target heart rate interval. The calculation method of the target heart rate interval is (220-age)×60%～(220-age)×70%. Meanwhile, the hypoxia group wears inhaled atmospheric hypoxia equipment and they exercised in a low-oxygen condition. The oxygen content of the inhaled mixed gas is 16%; the normoxia group exercises under the normal oxygen condition. Nutritional education was given to all subjects prior to the start of exercise intervention and the personal diet was controlled as much as possible, but diet was not restricted during the intervention. Body weight was measured before and after intervention. Fasting venous blood was taken. Blood glucose (GLU), insulin (INS) and glycated hemoglobin (GHb) were measured. Insulin resistance index (HOMA-IR) was calculated. All test results were expressed as mean ± standard deviation, non-parametric Mann-Whitney U test was used for comparison between groups, and non-parametric Wilcoxon matching was used for symbol level test. The significance level was P<0.05, the level of very significant was P<0.01. Results  After intervention, the fasting blood glucose level of the hypoxia group and normoxia group decreased and the hypoxia group decreased more, but there was no significant difference compared with before intervention (P>0.05). There was no significant difference between the rate and the normoxia group (P>0.05). After intervention, the GHb levels in the hypoxia group and the normoxia group decreased, but there was a significant difference between the hypoxia group and the hypoxia group (P<0.05). The difference between the normoxia group was not significant (P>0.05). There was no significant difference in the rate of GHb change between the oxygen exercise group and the normoxia group (P>0.05). After intervention, the fasting INS levels in the hypoxia group and the normoxia group decreased, but there was a significant difference between the hypoxia group and the hypoxia group (P<0.05), and the difference between the normoxia group was not significant (P>0.05). There was no significant difference in the rate of fasting INS between the hypoxia group and the normoxia group (P>0.05). The HOMA-IR of the hypoxia group and the normoxia group decreased after intervention, but there was significant difference between the hypoxia group and the hypoxia group (P<0.05) and the difference between the normoxia group was not significant (P>0.05). The HOMA-IR rate of hypoxia exercise was not significantly different from that of normoxia group (P>0.05). Conclusions Compared with the normoxia group, the hypoxia group has a more improved glycosylated hemoglobin and insulin resistance index. It suggests that the exercise intervention of the hypoxia condition may be more effective in treating obesity and preventing chronic diseases

Human Papillomavirus Type 18 E6 and E7 Genes Integrate into Human Hepatoma Derived Cell Line Hep G2

Background and Objectives: Human papillomaviruses have been linked causally to some human cancers such as cervical carcinoma, but there is very little research addressing the effect of HPV infection on human liver cells. We chose the human hepatoma derived cell line Hep G2 to investigate whether HPV gene integration took place in liver cells as well. Methods: We applied PCR to detect the possible integration of HPV genes in Hep G2 cells. We also investigated the expression of the integrated E6 and E7 genes by using RT-PCR and Western blotting. Then, we silenced E6 and E7 expression and checked the cell proliferation and apoptosis in Hep G2 cells. Furthermore, we analyzed the potential genes involved in cell cycle and apoptosis regulatory pathways. Finally, we used in situ hybridization to detect HPV 16/18 in hepatocellular carcinoma samples. Results: Hep G2 cell line contains integrated HPV 18 DNA, leading to the expression of the E6 and E7 oncogenic proteins. Knockdown of the E7 and E6 genes expression reduced cell proliferation, caused the cell cycle arrest at the S phase, and increased apoptosis. The human cell cycle and apoptosis real-time PCR arrays analysis demonstrated E6 and E7-mediated regulation of some genes such as Cyclin H, UBA1, E2F4, p53, p107, FASLG, NOL3 and CASP14. HPV16/18 was found in only 9% (9/100) of patients with hepatocellular carcinoma. Conclusion: Our investigations showed that HPV 18 E6 and E7 genes can be integrated into the Hep G2, and we observed a low prevalence of HPV 16/18 in hepatocellular carcinoma samples. However, the precise risk of HPV as causative agent of hepatocellular carcinoma needs further study

LFTOP : an LF-based approach to domain-specific reasoning

A new approach to domain-specific reasoning is presented that is based on a type-theoretic logical framework (LF) but does not require the user to be an expert in type theory. The concepts of the domain and its related reasoning systems are formalized in LF, but the user works with the system through a syntax and interface appropriate to his/her work. A middle layer provides translation between the user syntax and LF, and allows additional support for reasoning (e.g., model checking). Thus, the complexity of the logical framework is hidden but the benefits of using type theory and its related tools are retained, such as precision and machine-checkable proofs. This approach is investigated through a number of case studies: here, the authors consider the verification of properties of concurrency. The authors have formalized a specification language (CCS) and logic (μ--calculus) in LF, together with useful lemmas, and a user-oriented syntax has been designed. The authors demonstrate the approach with simple examples. However, applying lemmas to objects introduced by the user may result in framework-level objects which cannot be translated back to the user level.The authors discuss this problem, define a notion of adequacy, and prove that in this case study, translation can always be reversed

A Method of Short Text Representation Fusion with Weighted Word Embeddings and Extended Topic Information

Short text representation is one of the basic and key tasks of NLP. The traditional method is to simply merge the bag-of-words model and the topic model, which may lead to the problem of ambiguity in semantic information, and leave topic information sparse. We propose an unsupervised text representation method that involves fusing word embeddings and extended topic information. Following this, two fusion strategies of weighted word embeddings and extended topic information are designed: static linear fusion and dynamic fusion. This method can highlight important semantic information, flexibly fuse topic information, and improve the capabilities of short text representation. We use classification and prediction tasks to verify the effectiveness of the method. The testing results show that the method is valid

Automatic Benchmark Generation Framework for Malware Detection

To address emerging security threats, various malware detection methods have been proposed every year. Therefore, a small but representative set of malware samples are usually needed for detection model, especially for machine-learning-based malware detection models. However, current manual selection of representative samples from large unknown file collection is labor intensive and not scalable. In this paper, we firstly propose a framework that can automatically generate a small data set for malware detection. With this framework, we extract behavior features from a large initial data set and then use a hierarchical clustering technique to identify different types of malware. An improved genetic algorithm based on roulette wheel sampling is implemented to generate final test data set. The final data set is only one-eighteenth the volume of the initial data set, and evaluations show that the data set selected by the proposed framework is much smaller than the original one but does not lose nearly any semantics