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The article developed a method for automated penetration testing using deep machine learning technology. The main purpose of the development is to improve the security of computer systems. To achieve this goal, the analysis of existing penetration testing methods was carried out and their main disadvantages were identified. They are mainly related to the subjectivity of assessments in the case of manual testing. In cases of automated testing, most authors confirm the fact that there is no unified effective solution for the procedures used. This contradiction is resolved using intelligent methods of analysis. It is proposed that the developed method be based on deep reinforcement learning technology. To achieve the main goal, a study was carried out of the Shadov system's ability to collect factual data for designing attack trees, as well as the Mulval platform for generating attack trees. A method for forming a matrix of cyber intrusions using the Mulval tool has been developed. The Deep Q - Lerning Network method has been improved for analyzing the cyber intrusion matrix and finding the optimal attack trajectory. In the study, according to the deep reinforcement learning method, the reward scores assigned to each node, according to the CVSS rating, were used. This made it possible to shrink the attack trees and identify an attack with a greater likelihood of occurring. A comparative study of the automated penetration testing method was carried out. The practical possibility of using the developed method to improve the security of a computer system has been revealed.

Testing process for penetration into computer systems mathematical model was developed in the article. The proposed model differs from the known by computer systems specialized information platforms security testing capabilities, which made it possible to estimate the penetration test algorithm execution time falling within a given interval probability. The proposed testing process for penetration into computer systems mathematical model was further developed (modified). Modified model distinctive feature is the Erlang distribution as the main one in the state transition processes mathematical formalization. This made it possible on the one hand to unify the mathematical model and present the testing process at a higher level of the testing hierarchy, on the other hand to simplify it 1.7 times. A security testing mathematical model was developed in order to estimate the simulation results accuracy, based on the known GERT-networks simplification and modification approach. Testing algorithms execution time value mathematical expectation values are obtained and estimated. Comparative modeling results investigations have shown the study values comparability for all three approaches of security testing process mathematical formalization. This confirmed the hypothesis that it is advisable to use a unified mathematical formalization approach, which was implemented in a penetration testing process modified mathematical model.

The functions of long noncoding (lnc) RNA in the response of maize to infection by rice black streaked dwarf virus (RBSDV) is poorly understood, and therefore, a comprehensive disease‐responding lncRNA profile in maize infected with RBSDV was investigated. A total of 38,511 mRNAs and 2717 lncRNAs were identified by performing transcriptomic analysis of maize leaves infected with the virus, including 558 and 8276 differentially expressed lncRNAs (DElncRs) and mRNAs (DEmRs). Functional enrichment analysis of DEmRs showed that multiple immune‐related pathways were significantly enriched (p < 0.05), such as "plant hormone signal transduction", "phenylpropanoid biosynthesis", and "plant–pathogen interaction". There were 248 DElncR‐DEmR pairs, including 169 DElncRs and 236 target DEmRs generated by combining location information and differentially expressed transcripts in this work. In addition, we found that the promoter of lncRNA MSTRG.17772.1 that responds to RBSDV contains abscisic acid (ABA)‐ and methyl jasmonate (MeJA)‐responsive regions, and these two hormones can increase the level of MSTRG.17772.1 and corresponding target mRNA Zm00001d049643_T003, suggesting that ABA and MeJA may respond to RBSDV infection through MSTRG.17772.1–Zm00001d049643_T003 in maize. Our findings revealed the expression of RBSDV‐responsive lncRNAs in maize and provide novel insights into the connection between lncRNAs and ABA and MeJA in the regulation of plant disease resistance. [ABSTRACT FROM AUTHOR]

Long non-coding RNA (lncRNA) is a crucial regulatory mechanism in the plant response to biotic and abiotic stress. However, their roles in potato (Solanum tuberosum L.) resistance to Phytophthora infestans (P. infestans) largely remain unknown. In this study, we identify 2857 lncRNAs and 33,150 mRNAs of the potato from large-scale published RNA sequencing data. Characteristic analysis indicates a similar distribution pattern of lncRNAs and mRNAs on the potato chromosomes, and the mRNAs were longer and had more exons than lncRNAs. Identification of alternative splicing (AS) shows that there were a total of 2491 lncRNAs generated from AS and the highest frequency (46.49%) of alternative acceptors (AA). We performed R package TCseq to cluster 133 specific differentially expressed lncRNAs from resistance lines and found that the lncRNAs of cluster 2 were upregulated. The lncRNA targets were subject to KEGG pathway enrichment analysis, and the interactive network between lncRNAs and mRNAs was constructed by using GENIE3, a random forest machine learning algorithm. Transient overexpression of StLNC0004 in Nicotiana benthamiana significantly suppresses P. infestans growth compared with a control, and the expression of extensin (NbEXT), the ortholog of the StLNC0004 target gene, was significantly upregulated in the overexpression line. Together, these results suggest that lncRNAs play potential functional roles in the potato response to P. infestans infection. [ABSTRACT FROM AUTHOR]

Nonspecific lipidtransfer proteins (nsLTPs), which are small, cysteine‐rich proteins, belong to the pathogenesis‐related protein family, and several of them act as positive regulators during plant disease resistance. However, the underlying molecular mechanisms of these proteins in plant immune responses are unclear. In this study, a typical nsLTP gene, StLTP10, was identified and functionally analysed in potato. StLTP10 expression was significantly induced by Phytophthora infestans, which causes late blight in potato, and defence‐related phytohormones, including abscisic acid (ABA), salicylic acid, and jasmonic acid. Characterization of StLTP10‐overexpressing and knockdown lines indicated that StLTP10 positively regulates plant resistance to P. infestans. This resistance was coupled with enhanced expression of reactive oxygen species scavenging‐ and defence‐related genes. Furthermore, we identified that StLTP10 physically interacts with ABA receptor PYL4 and affects its subcellular localization. These two proteins work together to regulate stomatal closure during pathogen infection. Interestingly, we also found that wound‐induced protein kinase interacts with StLTP10 and positively regulates its protein abundance. Taken together, our results provide insight into the role of StLTP10 in resistance to P. infestans and suggest candidates to enhance broad‐spectrum resistance to pathogens in potato. [ABSTRACT FROM AUTHOR]

Phytophthora infestans causes the severe late blight disease of potato. During its infection process, P. infestans delivers hundreds of RXLR (Arg-x-Leu-Arg, x behalf of any one amino acid) effectors to manipulate processes in its hosts, creating a suitable environment for invasion and proliferation. Several effectors interact with host proteins to suppress host immunity and inhibit plant growth. However, little is known about how P. infestans regulates the host transcriptome. Here, we identified an RXLR effector, PITG_15718.2, which is upregulated and maintains a high expression level throughout the infection. Stable transgenic potato (Solanum tuberosum) lines expressing PITG_15718.2 show enhanced leaf colonization by P. infestans and reduced vegetative growth. We further investigated the transcriptional changes between three PITG_15718.2 transgenic lines and the wild type Désirée by using RNA sequencing (RNA-Seq). Compared with Désirée, 190 differentially expressed genes (DEGs) were identified, including 158 upregulated genes and 32 downregulated genes in PITG_15718.2 transgenic lines. Eight upregulated and nine downregulated DEGs were validated by real-time RT-PCR, which showed a high correlation with the expression level identified by RNA-Seq. These DEGs will help to explore the mechanism of PITG_15718.2-mediated immunity and growth inhibition in the future. [ABSTRACT FROM AUTHOR]

Based on density evolution analysis of the existing belief propagation (BP) algorithm, the Turbo Decoding Message Passing (TDMP) algorithm was analyzed from the perspective of density evolution and Gaussian approximation, and the theoretical analysis process of TDMP algorithm was given. When calculating the prior message of each layer of the TDMP algorithm, the check message of the previous iteration should be subtracted. Therefore, the result will not be convergent, if the TDMP algorithm is directly analyzed based on density evolution and Gaussian approximation. We researched the TDMP algorithm based on the symmetry conditions to obtain the convergent result. When using density evolution (DE) and Gaussian approximation to analyze the decoding convergence of the TDMP algorithm, we can provide a theoretical basis for proving the superiority of the algorithm. Then, based on the DE theory, we calculated the probability density function (PDF) of the check-to-variable information of TDMP and its simplified algorithm, and then gave it a calculation based on the process of the normalization factor. Simulation results show that the decoding convergence speed of the TDMP algorithm was faster and the iterations were smaller compared to the BP algorithm under the same conditions. [ABSTRACT FROM AUTHOR]

Late blight, caused by Phytophthora infestans , is one of the most serious diseases affecting potatoes ( Solanum tuberosum L.). Long non-coding RNAs (lncRNAs) are transcripts with a length of more than 200 nucleotides that have no protein-coding potential. Few studies have been conducted on lncRNAs related to plant immune regulation in plants, and the molecular mechanisms involved in this regulation require further investigation. We identified and screened an lncRNA that specifically responds to P. infestans infection, namely, StlncRNA13558 . P. infestans infection activates the abscisic acid (ABA) pathway, and ABA induces StlncRNA13558 to enhance potato resistance to P. infestans . StlncRNA13558 positively regulates the expression of its co-expressed PR-related gene StPRL . StPRL promotes the accumulation of reactive oxygen species and transmits a resistance response by affecting the salicylic acid hormone pathway, thereby enhancing potato resistance to P. infestans . In summary, we identified the potato late blight resistance lncRNA StlncRNA13558 and revealed its upstream and downstream regulatory relationship of StlncRNA13558 . These results improve our understanding of plant-pathogen interactions' immune mechanism and elucidate the response mechanism of lncRNA-target genes regulating potato resistance to P. infestans infection., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Shang, Wang, Cao, Wang, Wang, Shi, Liu, Zhou, Zhu and Zhu.)

The performance of solid-state laser is limited by the thermal effects in the gain medium. In this study, we investigated the implementation of an efficient short-cavity continuous-wave 1064 nm Nd:YAG solid-state laser by using a rotatory pumping scheme to alleviate the thermal accumulation in the gain medium. With this method, the laser power reached 25.7 W with a slope efficiency of 41.5% at a 10.0-mm pump rotation radius and an optimum rotation rate of 2300 rpm. The influence of rotatory pumping radius and rotation rates was analyzed, and the results indicated that the rotatory pumping would be promising technique for the power scaling of solid-state lasers.