Encoding Individual Source Sequences for the Wiretap Channel

We consider the problem of encoding a deterministic source sequence (i.e., individual sequence) for the degraded wiretap channel by means of an encoder and decoder that can both be implemented as finite-state machines. Our first main result is a necessary condition for both reliable and secure transmission in terms of the given source sequence, the bandwidth expansion factor, the secrecy capacity, the number of states of the encoder and the number of states of the decoder. Equivalently, this necessary condition can be presented as a converse bound (i.e., a lower bound) on the smallest achievable bandwidth expansion factor. The bound is asymptotically achievable by Lempel–Ziv compression followed by good channel coding for the wiretap channel. Given that the lower bound is saturated, we also derive a lower bound on the minimum necessary rate of purely random bits needed for local randomness at the encoder in order to meet the security constraint. This bound too is achieved by the same achievability scheme. Finally, we extend the main results to the case where the legitimate decoder has access to a side information sequence, which is another individual sequence that may be related to the source sequence, and a noisy version of the side information sequence leaks to the wiretapper.

In silico mutational analysis in RNA polymerase β subunit (rpoB) gene of rifampicin-resistant in Mycobacterium tuberculosis from Malaysia

Tuberculosis (TB) is mainly caused by Mycobacterium tuberculosis (MTB) and remains as a key public health problem worldwide. Most of MTB clinical strains are resistant to rifampicin (RIF), the first-line anti-tuberculosis drug. RIF resistance to MTB is due to mutations that mainly found in RIF resistance-determining region (RRDR) in drug target gene, RNA polymerase β subunit (rpoB). Therefore, the aim of the study is to extend the identification of variants in rpoB gene and to elucidate the effect of variants to the RIF resistance. Four of the strains, MTBR1/09, MTBR2/09, MTBR3/09 and MTB221/11 were subjected to drug susceptibility test (DST). All of the strains sequenced and submitted to the National Center for Biotechnology Information Sequence Read Archive were analyzed to identify the variants in the rpoB gene. The identified new variants were then subjected to docking to examine the drug-protein interactions. DST analysis revealed MTBR1/09, MTBR2/09 and MTBR3/09 were resistant to the RIF drug, while MTB221/11 was a presumptive susceptible strain. Two new variants were observed, the deletion (Phe433_Met434delinsLeu in MTBR1/09) and missense (Lys37Arg in MTBR3/09) variants. Meanwhile, the His445Leu, Ser450Leu, Asp103Asp, Ala1075Ala were reported variants. Docking of RIF to MTBR1/09 and MTBR3/09 mutant models revealed the RIF bound to the RIF binding site at different binding affinity and conformation. Concurrently, the new variants caused the RIF to bind to the different active site and neighboring residues. Findings from DST and docking analyses indicate that new variants potentially disturb the RIF inhibition in RpoB mutant proteins, and thus might be responsible to cause the RIF resistance.

Reinforcement Learning for Bit-Flipping Decoding of Polar Codes

A traditional successive cancellation (SC) decoding algorithm produces error propagation in the decoding process. In order to improve the SC decoding performance, it is important to solve the error propagation. In this paper, we propose a new algorithm combining reinforcement learning and SC flip (SCF) decoding of polar codes, which is called a Q-learning-assisted SCF (QLSCF) decoding algorithm. The proposed QLSCF decoding algorithm uses reinforcement learning technology to select candidate bits for the SC flipping decoding. We establish a reinforcement learning model for selecting candidate bits, and the agent selects candidate bits to decode the information sequence. In our scheme, the decoding delay caused by the metric ordering can be removed during the decoding process. Simulation results demonstrate that the decoding delay of the proposed algorithm is reduced compared with the SCF decoding algorithm, based on critical set without loss of performance.

72-h diurnal RNA-seq analysis of fully expanded third leaves from maize, sorghum, and foxtail millet at 3-h resolution

Objectives The purpose of this data set is to capture the complete diurnal (i.e., daily) transcriptome of fully expanded third leaves from the C4 panacoid grasses sorghum (Sorghum bicolor), maize (Zea mays), and foxtail millet (Setaria italica) with RNA-seq transcriptome profiling. These data are the cornerstone of a larger project that examined the conservation and divergence of gene expression networks within these crop plants. This data set focuses on temporal changes in gene expression to identify the network architecture responsible for daily regulation of plant growth and metabolic activities. The power of this data set is fine temporal resolution combined with continuous sampling over multiple days. Data description The data set is 72 individual RNA-seq samples representing 24 time course samples each for sorghum, maize, and foxtail millet plants cultivated in a growth chamber under equal intervals of light and darkness. The 24 samples are separated by 3-h intervals so that the data set is a fine scale 72-h analysis of gene expression in the leaves of each plant type. FASTQ files from Illumina sequencing are available at the National Center for Biotechnology Information Sequence Read Archive.

Does the Order of Information Affect Investors' Investment Decisions? Experimental Investigation

Research aims: This study examines the order of information’s effect according to the Belief Adjustment Model. In particular, this study investigates the effect of the direction of the order and the pattern of presenting information in making investment decisions.Design/Methodology/Approach: The research applied an experimental method with web-based instruments using a 2x2 factorial design between subjects, involving 65 investors.Research findings: The investors’ investment valuation who received negative to positive information sequence direction was higher than the investors who received positive to negative information direction. Furthermore, there was an order effect in the form of recency on investors who received a partial presentation pattern. Meanwhile, investors who received a simultaneous pattern did not show an order effect in their assessment. These findings underline that the simultaneous pattern could reduce the order effect, so that investors need to generalize the information as a whole to avoid this bias.Theoretical contribution/Originality: This study extends the investigation of investment decisions using a long sequence of information perspectives and more varied types of information (e.g., financial information, corporate governance, and industry sectoral information that has an impact on company conditions) in making investment decisions on the belief adjustment model.Practitioner/Policy implication: Companies must maintain the direction of the order and the presentation patterns when issuing company information to maintain the quality of investors' decisions and avoid the risk of volatility in company shares.Research limitation/Implication: Participants who joined this research were active investors but had not yet had a comprehensive experience.

A joint design method of frame synchronization code and LDPC code

Frame synchronization word (FSW) is an important basis in signal synchronization detection. In our work, the joint design of frame synchronization words and error correcting code are proposed which through regularly distributing the frame synchronization words among the information bits to improve the decoding performance of the LDPC. Frame synchronization word should be added to the information sequence corresponding to the position with the check matrix larger column weight which can guarantee that more Frame synchronization words are received by the check node in the decoding iteration. The frame synchronization word is known to the receiver which play an important role in decoding iteration. The results of simulation show that the algorithm makes an obvious improvement in decoding performance when the signal-noise ratio (SNR) is lower than 1 dB.

Performance Analysis of CRC-Polar Concatenated Codes

Polar code has been proven to obtain Shannon capacity for Binary Input Discrete Memoryless Channel (BIDMC) and its use has been proposed as the channel coding in 5G technology. However, its performance is limited in finite block length, compared to Turbo or LDPC codes. This research proposes the use of various CRC codes to complement Polar codes with finite block length and analyses the performance based on Block Error Rate (BLER) to Es/N0 (dB). The CRC codes used are of degrees 11 and 24, with 3 different polynomial generators for each degree. The number of bits in the information sequence is 32. The list sizes used are 1, 2, 4, and 8. Simulation results show that the concatenation of CRC and Polar codes will yield good BLER vs Es/N0 performance for short blocks of codeword, with rates 32/864 and 54/864. Concatenating CRC codes with Polar codes will yield a BLER performance of 10-2 with Es/N0 values of -9.1 to -7.5 dB when CRC codes of degree 11 is used, depending on the SC list used. The use of CRC codes of degree 24 enables a BLER performance of 10-2 with Es/N0 values of -7 to -6 dB when the SC list used is 1 or 2. The use of CRC codes of degree 24 combined with SC list with sizes 4 or 8 will improve the BLER performance to 10-2 with Es/N0 values of -8 to -7.5 dB

Encryption algorithm for network communication information based on binary logistic regression

In order to overcome the problems of long encrypting time, low information availability, low information integrity and low encrypting efficiency when using the current method to encrypt the communication information in the network without constructing the sequence of communication information. This paper proposes a network communication information encryption algorithm based on binary logistic regression, analyses the development of computer architecture, builds a network communication model, layers the main body of information exchange, and realizes the information synchronization of device objects at all levels. Based on the binary Logistic regression model, network communication information sequence is generated, and the fusion tree is constructed by network communication information sequence. The network communication information is encrypted through system initialization stage, data preparation stage, data fusion stage and data validation stage. The experimental results show that the information availability of the proposed algorithm is high, and the maximum usability can reach 97.7%. The encryption efficiency is high, and the shortest encryption time is only 1.9 s, which fully shows that the proposed algorithm has high encryption performance.

DOPPLER FREQUENCY SHIFT ESTIMATION BASED ON THE FIRST- AND SECOND-ORDER DIFFERENCE PHASES

Рассмотрена задача оценки доплеровского смещения несущей частоты информационного одночастотного фа- зоманипулированного сигнала, если информационная последовательность неизвестна. Приведено описание метода оценки с использованием разности фаз первого и второго порядков. Представлены результаты численного моделирования. The problem of Doppler frequency shift estimation of the single-tone information signal with phase-shiftkeying modulation under conditions when the information sequence is unknown is considered. The description of the estimation method using the firstand second-order phase difference is given. The results of the numerical simulation are presented.