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Malicious code threatens the safety of computer systems. Researching malicious code design techniques and mastering code behavior patterns are the basic work of network security prevention. With the game of network offense and defense, malicious code shows the characteristics of invisibility, polymorphism, and multi-dismutation. How to correctly and effectively understand malicious code and extract the key malicious features is the main goal of malicious code detection technology. As an important method of program understanding, program slicing is used to analyze the program code by using the idea of “decomposition”, and then extract the code fragments that the analyst is interested in. In recent years, data mining and machine learning techniques have been applied to the field of malicious code detection. The reason why it has become the focus of research is that it can use data mining to dig out meaningful patterns from a large amount of existing code data. Machine learning can It helps to summarize the identification knowledge of known malicious code, so as to conduct similarity search and help find unknown malicious code. The machine learning heuristic malicious code detection method firstly needs to automatically or manually extract the structure, function and behavior characteristics of the malicious code, so we can first slice the malicious code and then perform the detection. Through the improvement of the classic program slicing algorithm, this paper effectively improves the slicing problem between binary code processes. At the same time, it implements a malicious code detection system. The machine code byte sequence variable-length N-gram is used as the feature extraction method to further prove that the efficiency and accuracy of malicious code detection technology based on data mining and machine learning. &nbsp

To solve the problem of large carbon emissions in rural area, this paper conducts field research in rural areas of Shandong and embarks on supply-demand bilateral energy structure optimization which combines local resource endowments, the latest rural energy application technologies and energy consumption preference. The study uses long-range energy alternatives planning (LEAP) model to analyze the trend of energy consumption and CO2 emission from 2020 to 2050 under four different scenarios. The results of Tanzhuang show that residents in rural areas still rely on traditional biomass for energy consumption, especially for winter heating. Energy structure optimization has a significant impact on energy saving and emission reduction. Energy consumption and generation are projected steadily up to 2050 under all scenarios while the carbon emissions show a downward trend with a rapid decline from 2021 to 2030 and a relatively stable state for the next 20 years. Combining policy advancement and marginal carbon abatement cost (MACC) of different energy technologies, energy structure optimization-low cost (ESO-LOW) scenario shows a higher emission reduction benefits than the others. Six other villages in Shandong are analyzed in order to demonstrate the effectiveness of supply-demand bilateral energy structure optimization, sensitivity results show that the optimization is significant to the carbon neutrality target and carbon emission reduction.

Background The mitochondrial voltage-dependent anion channel (VDAC) is increasingly implicated in the control of apoptosis. We have studied the effects the mitochondrial DNA (mtDNA) tRNAIle mutation on VDAC expression, localization, and apoptosis. Methods Lymphoblastoid cell lines were derived from 3 symptomatic and 1 asymptomatic members of a family with hypertension associated with the A4263G tRNAIle mutation as well as from control subjects. Mitochondrial potential (ΔΨm) and apoptosis were measured by flow cytometry; co-localization of VDAC and Bax was evaluated by confocal microscopy. Results Expression of VDAC and Bax in mtDNA cell lines was found to be increased compared to controls, while expression of the small conductance calcium-dependant potassium channel (sKCa) was unchanged. Confocal imaging revealed co-localization of VDAC/Bax on the outer mitochondrial membrane of A4263G cell lines but not from controls. Flow cytometry indicated that the mitochondrial potential was decreased by 32% in mutated cells versus controls while rates of apoptosis were increased (P < 0.05). The difference was attenuated by Cyclosporin A (CsA, 2 μM), a blocker of VDAC. Conclusion We conclude that increased expression of mitochondrial VDAC and subcellular co-localization of VDAC/Bax increases mitochondrial permeability and apoptosis in cell lines carrying the mtDNA tRNAIle A4263G mutation.

Power load forecasting is a key element for power system management and planning. However, it has been proven to be a hard task due to various unstable factors. This paper presents a forecasting methodology based on this particular type of neural network. The scope of this study presents a solution for short-term load forecasting based on a three-stage model which starts with pattern recognition via self-organizing map (SOM), a clustering of the previous partition by K-means algorithm, and finally demand forecasting for each cluster with back propagation neural network (BPNN) improved by additional momentum and variable learning rate methods. The effectiveness of SOM-K-BPNN model has been verified by the final simulation which shows that the proposed model outperforms the BPNN model with default parameters and Grey System GM (1, 1); therefore, empirical results show that the proposed SOM-K-BPNN model is feasible and can fulfil the short-term load forecasting requirements of China.

Objective To find a novel mitochondrial DNA point mutation A4263G, we characterised clinically and evaluated hereditarily a large Chinese family with the characteristics of maternally inherited hypertension. Methods The mitochondrial DNA point mutation A4263G was detected by sequence analysis of mitochondrial DNA from enrolled patients with essential hypertension. Then we collected and did statistic analyses on the clinical data of this family. Results All the members with mitochondrial DNA point mutation A4263G were maternal members, a finding consistent with the maternal inherited characteristics. The morbidity of hypertension in the maternal members is up to 53.8%, while that in the nonmaternal members is only 11.8% (p Conclusions By far all findings, including the same mitochondrial DNA point mutation in all maternal individuals and clear pattern of maternal inheritance, suggested mitochondrial DNA point mutation may be associated with hypertension and play an important role in onset of hypertension.

Presents the MS results. (PDF 8620 kb)

showing supplementary results. (PDF 10332 kb)

showing supplementary results. (PDF 10332 kb)

Presents the MS results. (PDF 8620 kb)