Towards Strengthening Deep Learning-based Side Channel Attacks with Mixup

In recent years, various deep learning techniques have been exploited in side channel attacks, with the anticipation of obtaining more appreciable attack results. Most of them concentrate on improving network architectures or putting forward novel algorithms, assuming that there are adequate profiling traces available to train an appropriate neural network. However, in practical scenarios, profiling traces are probably insufficient, which makes the network learn deficiently and compromises attack performance. In this paper, we investigate a kind of data augmentation technique, called mixup, and first propose to exploit it in deep-learning based side channel attacks, for the purpose of expanding the profiling set and facilitating the chances of mounting a successful attack. We perform Correlation Power Analysis for generated traces and original traces, and discover that there exists consistency between them regarding leakage information. Our experiments show that mixup is truly capable of enhancing attack performance especially for insufficient profiling traces. Specifically, when the size of the training set is decreased to 30% of the original set, mixup can significantly reduce acquired attacking traces. We test three mixup parameter values and conclude that generally all of them can bring about improvements. Besides, we compare three leakage models and unexpectedly find that least significant bit model, which is less frequently used in previous works, actually surpasses prevalent identity model and hamming weight model in terms of attack results

Water-Soluble Electrospun Nanofibers as a Method for On-Chip Reagent Storage

This work demonstrates the ability to electrospin reagents into water-soluble nanofibers resulting in a stable on-chip enzyme storage format. Polyvinylpyrrolidone (PVP) nanofibers were spun with incorporation of the enzyme horseradish peroxidase (HRP). Scanning electron microscopy (SEM) of the spun nanofibers was used to confirm the non-woven structure which had an average diameter of 155 ± 34 nm. The HRP containing fibers were tested for their change in activity following electrospinning and during storage. A colorimetric assay was used to characterize the activity of HRP by reaction with the nanofiber mats in a microtiter plate and monitoring the change in absorption over time. Immediately following electrospinning, the activity peak for the HRP decreased by approximately 20%. After a storage study over 280 days, 40% of the activity remained. In addition to activity, the fibers were observed to solubilize in the microfluidic chamber. The chromogenic 3,3′,5,5′-tetramethylbenzidine solution reacted immediately with the fibers as they passed through a microfluidic channel. The ability to store enzymes and other reagents on-chip in a rapidly dispersible format could reduce the assay steps required of an operator to perform

Photovoltaic generator model for power system dynamic studies

Photovoltaic (PV) power generation has developed very rapidly worldwide in the recent years. There is a possibility that the PV power generation will switch from an auxiliary power supply, as of today, to a main power source in many power grids in the future. Naturally, dynamic studies on power grids with a high penetration of PV generators have become increasingly important, and thus have attracted major attentions from both the power industry and the academia. Consequently, dynamic modeling of PV generators has been investigated widely. However, among various proposed models, there is a confusion on the model applicability and a lack of the clarification on the required level of details on the modeling work, which severely limit the real industrial applications of the developed models. This paper reviews the state-of-the-art PV generator dynamic modeling work, with a focus on the modeling principles of PV generator for the power system dynamic studies. The paper presents the detailed modeling process for the recommended PV generator dynamic model, and clarifies the assumptions and simplifications made in the modeling process, thus raises the discussion on the model applicability. Studies that require further attentions on developing the dynamic models of PV generators for power system dynamic studies are identified and presented in the paper. However, this work does not intend to conclude the research work in this important field, instead, it aims to provoke more discussions on developing guidelines on building or selecting the appropriate models to fit into the purpose of the targeted dynamic studies

Operation characteristics of DC transmission system with large-scale renewable energy integration

Marked with flexible interconnection and control, the high-voltage direct current (HVDC) gird has captured much attention of industries and academics. Hybrid dual-infeed or multi-infeed HVDC composed of line-commutated-converter HVDC (LCC-HVDC) and voltage source converter HVDC (VSC-HVDC) will form the main pattern in a further power grid; meanwhile, the new gird pattern will bring new opportunities and challenges to security and stability control in the power system. First, research works on the control strategies and operation performances of LCC-HVDC and VSC-HVDC are stated in this paper; then, a model of wind power integration into a dual-infeed DC transmission system is established in PowerFactory, and case studies are conducted in both steady and transient states. On this basis, a new control strategy for variable-speed constant-frequency wind power generators to promote voltage characteristics of the DC network is designed in this paper, and two additional active power control segments are designed in the traditional control system; thus, DC voltage stability can be improved by fast regulation of active power output due to quick power adjustment of wind power generators; simulations are implemented and the results will lay a foundation for safe and stable operation in the DC transmission system with renewable energy integration

Structure–activity characteristics of phenylalanine analogs selectively transported by L-type amino acid transporter 1 (LAT1)

Abstract L-type amino acid transporter 1 (LAT1) is a transmembrane protein responsible for transporting large neutral amino acids. While numerous LAT1-targeted compound delivery for the brain and tumors have been investigated, their LAT1 selectivity often remains ambiguous despite high LAT1 affinity. This study assessed the LAT1 selectivity of phenylalanine (Phe) analogs, focusing on their structure–activity characteristics. We discovered that 2-iodo-l-phenylalanine (2-I-Phe), with an iodine substituent at position 2 in the benzene ring, markedly improves LAT1 affinity and selectivity compared to parent amino acid Phe, albeit at the cost of reduced transport velocity. l-Phenylglycine (Phg), one carbon shorter than Phe, was found to be a substrate for LAT1 with a lower affinity, exhibiting a low level of selectivity for LAT1 equivalent to Phe. Notably, (R)-2-amino-1,2,3,4-tetrahydro-2-naphthoic acid (bicyclic-Phe), with an α-methylene moiety akin to the α-methyl group in α-methyl-l-phenylalanine (α-methyl-Phe), a known LAT1-selective compound, showed similar LAT1 transport maximal velocity to α-methyl-Phe, but with higher LAT1 affinity and selectivity. In vivo studies revealed tumor-specific accumulation of bicyclic-Phe, underscoring the importance of LAT1-selectivity in targeted delivery. These findings emphasize the potential of bicyclic-Phe as a promising LAT1-selective component, providing a basis for the development of LAT1-targeting compounds based on its structural framework

Construction of an example system for AC/DC hybrid power grid with high-proportion renewable energy

Large-scale wind and solar power generations have got rapid development in recent years in China and abroad. They always connect to load centres through high-voltage direct current (HVDC) transmission or ultra HVDC (UHVDC) transmission lines. Such systems are so large and it is necessary to make appropriate equivalence according to the purpose of different research. At present, the analysis model of this kind of real system is few, and simplified single-machine infinite-bus system or IEEE example system is adopted most of the time, which may affect the accuracy of analysis results. Here, the UHVDC project from a practical renewable energy base to load centres in China is chosen as an example, the actual structure and parameters are used to establish a typical example system for AC/DC hybrid power grid with high-proportion renewable energy. The new-generation synchronous condenser with large capacity and the supporting synchronous generators are all considered. First, the installed power generation, power grid structure, and load configuration of example system are introduced. Then the load flow distribution and transient stability characteristics are analysed by using DIgSILENT PowerFactory software. Finally, the feasibility of the proposed example system is shown by simulation results

Identification of phytochemical compounds of Fagopyrum dibotrys and their targets by metabolomics, network pharmacology and molecular docking studies

Acute lung injury (ALI) is a clinically severe lung illness with high incidence rate and mortality. Especially, coronavirus disease 2019 (COVID-19) poses a serious threat to world wide governmental fitness. It has distributed to almost from corner to corner of the universe, and the situation in the prevention and control of COVID-19 remains grave. Traditional Chinese medicine plays a vital role in the precaution and therapy of sicknesses. At present, there is a lack of drugs for treating these diseases, so it is necessary to develop drugs for treating COVID-19 related ALI. Fagopyrum dibotrys (D. Don) Hara is an annual plant of the Polygonaceae family and one of the long-history used traditional medicine in China. In recent years, its rhizomes (medicinal parts) have attracted the attention of scholars at home and abroad due to their significant anti-inflammatory, antibacterial and anticancer activities. It can work on SARS-COV-2 with numerous components, targets, and pathways, and has a certain effect on coronavirus disease 2019 (COVID-19) related acute lung injury (ALI). However, there are few systematic studies on its aerial parts (including stems and leaves) and its potential therapeutic mechanism has not been studied. The phytochemical constituents of rhizome of F. dibotrys were collected using TCMSP database. And metabolites of F. dibotrys' s aerial parts were detected by metabonomics. The phytochemical targets of F. dibotrys were predicted by the PharmMapper website tool. COVID-19 and ALI-related genes were retrieved from GeneCards. Cross targets and active phytochemicals of COVID-19 and ALI related genes in F. dibotrys were enriched by gene ontology (GO) and KEGG by metscape bioinformatics tools. The interplay network entre active phytochemicals and anti COVID-19 and ALI targets was established and broke down using Cytoscape software. Discovery Studio (version 2019) was used to perform molecular docking of crux active plant chemicals with anti COVID-19 and ALI targets. We identified 1136 chemicals from the aerial parts of F. dibotrys, among which 47 were active flavonoids and phenolic chemicals. A total of 61 chemicals were searched from the rhizome of F. dibotrys, and 15 of them were active chemicals. So there are 6 commonly key active chemicals at the aerial parts and the rhizome of F. dibotrys, 89 these phytochemicals's potential targets, and 211 COVID-19 and ALI related genes. GO enrichment bespoken that F. dibotrys might be involved in influencing gene targets contained numerous biological processes, for instance, negative regulation of megakaryocyte differentiation, regulation of DNA metabolic process, which could be put down to its anti COVID-19 associated ALI effects. KEGG pathway indicated that viral carcinogenesis, spliceosome, salmonella infection, coronavirus disease - COVID-19, legionellosis and human immunodeficiency virus 1 infection pathway are the primary pathways obsessed in the anti COVID-19 associated ALI effects of F. dibotrys. Molecular docking confirmed that the 6 critical active phytochemicals of F. dibotrys, such as luteolin, (+) -epicatechin, quercetin, isorhamnetin, (+) -catechin, and (−) -catechin gallate, can combine with kernel therapeutic targets NEDD8, SRPK1, DCUN1D1, and PARP1. In vitro activity experiments showed that the total antioxidant capacity of the aerial parts and rhizomes of F. dibotrys increased with the increase of concentration in a certain range. In addition, as a whole, the antioxidant capacity of the aerial part of F. dibotrys was stronger than that of the rhizome. Our research afford cues for farther exploration of the anti COVID-19 associated ALI chemical compositions and mechanisms of F. dibotrys and afford scientific foundation for progressing modern anti COVID-19 associated ALI drugs based on phytochemicals in F. dibotrys. We also fully developed the medicinal value of F. dibotrys' s aerial parts, which can effectively avoid the waste of resources. Meanwhile, our work provides a new strategy for integrating metabonomics, network pharmacology, and molecular docking techniques which was an efficient way for recognizing effective constituents and mechanisms valid to the pharmacologic actions of traditional Chinese medicine

Association between MMP1 -1607 1G>2G polymorphism and head and neck cancer risk: a meta-analysis.

BACKGROUND: MMP1 is an important member of the MMP endopeptidase family that plays a critical role in the development of head and neck cancer (HNC). Several studies have investigated the association between the MMP1 -1607 1G>2G polymorphism and risk of HNC, but their results have been inconsistent. Here, we conducted a meta-analysis to further explore the role of the MMP1 -1607 1G>2G polymorphism in HNC development. METHODS: We identified all eligible studies in the electronic databases of PubMed, ISI Web of Knowledge, MEDLINE, Embase, and Google Scholar (from January 2000 to June 2012). A meta-analysis was performed to evaluate the association between the MMP1 -1607 1G>2G polymorphism and risk of HNC by calculating odds ratios (OR) and 95% confidence interval (CIs). RESULTS: Twelve studies were included in this meta-analysis. In overall comparison, significant associations were found using the recessive and allelic contrast models (OR, 1.38; 95% CI, 1.07-1.79 and OR, 1.27; 95% CI, 1.05-1.53, respectively), but no association was detected using the dominant model. In the stratified analyses by several variables, significant associations were observed using the recessive, dominant, and allelic contrast models in the Asian population (OR, 1.64; 95% CI, 1.29-2.08; OR, 1.39; 95% CI, 1.06-1.82; and OR, 1.41; 95% CI, 1.21-1.65, respectively), European population (OR, 0.58; 95% CI, 0.40-0.84; OR, 0.64; 95% CI, 0.44-0.92; and OR, 0.68; 95% CI, 0.54-0.85, respectively), and population-based subgroup (OR, 1.24; 95% CI,1.05-1.47; OR,1.48; 95% CI,1.04-2.12; and OR, 1.22; 95% CI, 1.07-1.38, respectively). Furthermore, significant associations were detected in oral cavity cancer and nasopharyngeal cancer under the recessive model. CONCLUSION: Our results suggest that the MMP1 -1607 1G>2G polymorphism is associated with risk of HNC and that it plays different roles in Asian and European populations. Further studies with large sample size are needed to validate our findings