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Over the past decade, the rapid development of DNA synthesis and sequencing technologies has enabled preliminary use of DNA molecules for digital data storage, overcoming the capacity and persistence bottlenecks of silicon-based storage media. DNA storage has now been fully accomplished in the laboratory through existing biotechnology, which again demonstrates the viability of carbon-based storage media. However, the high cost and latency of data reconstruction pose challenges that hinder the practical implementation of DNA storage beyond the laboratory. In this article, we review existing advanced DNA storage methods, analyze the characteristics and performance of biotechnological approaches at various stages of data writing and reading, and discuss potential factors influencing DNA storage from the perspective of data reconstruction. [Display omitted] Cao et al. summarize advanced DNA storage methods and explore the possible factors affecting DNA storage from the perspective of data reconstruction. They also analyze data reconstruction performance in terms of sequencing, clustering, and assembly and advocate paying more attention to data access efficiency and data security. [ABSTRACT FROM AUTHOR]

[Display omitted] 7-substituted tetrahydroisoquinolines derivatives were designed, synthesized, and evaluated for neuroprotective properties. We summarized the preliminary structure activity relationships (SAR). Compound 3i was screened as a hit compound and its antidepressant activity was evaluated by employing the forced swimming test, tail suspension test. Additionally, ADMET profile (absorption, distribution, metabolism, excretion and toxicity properties) of the compound 3i was predicted in order to evaluate their lead-like properties and safety. The interaction of compound 3i bound to MAO-A was explored using molecular docking and molecular dynamics simulation. Results of biological studies revealed that the compound 3i exhibited almost equal antidepressant activity compared with magnoflorine. Compound 3i is predicted to possess good drug like properties and safety based on ADMET profile predictions. This work provides ideas for the drugs discovery of antidepressant agents. [ABSTRACT FROM AUTHOR]

Highlights • Kiwifruit water loss was spatial movement of water from interior tissues to outwards. • Vibration caused excess water loss although there was an undamaged fruit surface. • Vibration accelerated water loss process due to intracellular damage in kiwifruit. Abstract Fruit usually suffers from water loss after transportation and storage, which largely blemishes the quality characteristics including appearance, saleable weight and texture. This study was conducted to interpret the potential relations between fruit water loss and transport vibration. Kiwifruit were subjected to vibration using an electrodynamic shaker followed by storing at 25 °C and 75% RH (relative humidity) in dark for 12 d. Fruit weight loss and water content in the epidermis (EP), outer pericarp (OP), inner pericarp (IP) and core tissues were determined. Shrinkage of EP cells and water movement were evaluated using laser scanning confocal microscopy and magnetic resonance imaging, respectively. Cell damage was investigated by observing the ultrastructure and electrolyte leakage. The results showed that fruit water loss was accompanied with the spatial movement of water from interior IP, OP and external EP. Vibration damaged the fruit cells with plasmolysis, membrane contracting and increased electrolyte leakage, which accelerated movement of water from the tissues to outward resulting in severe water loss of fruit. However, the electrolyte leakage and water content in the core were little changed in both control and vibrated fruit. Shrinkage of EP cells coupled with fruit shrivel appeared by 4 d of storage after vibration. However, the symptom in control fruit was not observed until 8 d of storage. It could be concluded that the simulated transport vibration caused intracellular damage in fruit tissues, which accelerated the water loss and shriveling process. [ABSTRACT FROM AUTHOR]

The heat intolerance and retrogradation behavior of native wheat starch (WS) are undesirable for starch-based gel foods, therefore the combinations of WS and hydrocolloids have attracted extensive attentions. The objectives of this study were to investigate the effects of konjac glucomannan (KGM) with different degree of deacetylation (DD) on the pasting, rheological and retrogradation properties of WS. Results showed that deacetyl-konjac glucomannan (DKGM) increased the peak viscosity (PV), trough viscosity (TV) and final viscosity (FV), while decreased the breakdown (BD) values of WS, suggesting the enhancement of the viscosity and thermal stability of WS paste. The raised storage modulus (G′) of WS gels with DKGM1 (DD, 48.23%) demonstrated that the partial removal of acetyl groups from KGM chains effectively promoted the formation of gel network, accompanied by increased elasticity. After storing at 4 °C for 7 days, the hardness of gels increased up 369%, while supplement with DKGM significantly (p < 0.05) decreased the hardness. These data demonstrated that DKGM delayed the process of starch retrogradation, which was further verified by LF-NMR analysis. Besides, the addition of DKGM reduced the retrogradation rate, relative crystallinity and the orderliness of WS-DKGM gels with the prolonging of storage at 4 °C, all validating the hindrance of starch retrogradation by DKGM. Therefore, these data suggested that partial deacetylation of KGM could effectively improve the pasting, rheological characteristics and impede the retrogradation of WS. [Display omitted] • Deacetyl-konjac glucomannan (DKGM) increased the pasting viscosity of wheat starch. • Wheat starch-DKGM gels exhibited non-Newtonian fluid properties and higher elasticity. • DKGM improved the hardness of wheat starch gels after refrigerated storage. • DKGM delayed starch retrogradation via inhibiting water mobility and recrystallization. [ABSTRACT FROM AUTHOR]

• AchLOX3 and AchOPR3 were involved in JA biosynthesis of kiwifruit. • ABA-induced AchABF1-1 was a nucleus-localized transcription factor. • AchABF1-1 activated AchLOX3 and AchOPR3 expression by binding to their promoters. • ABA promoted SPP formation by the induction of JA biosynthesis. Mechanical damage is a central limiting factor in the maintenance of the postharvest fruit quality during harvest, transportation, and processing. In this study, wounded kiwifruit (Actinidia chinensis cv. Xuxiang) were respectively treated with abscisic acid (ABA), fluridone (FLD, an inhibitor of ABA biosynthesis), methyl jasmonate (MeJA), diethyldithiocarbamic acid (DIECA, an inhibitor of JA biosynthesis), and ABA+DIECA to investigate the potential interaction between ABA and JA in the process of wound healing. The results showed that blocking JA biosynthesis significantly reduced the positive effect of ABA on the accumulation of suberin polyphenolic (SPP). Besides, transiently overexpressed the AchLOX3 and AchOPR3 in tobacco (Nicotiana benthamiana) leaves confirmed that these two genes respectively encoded lipoxygenase and 12-oxo-phytodienoic acid reductase involved in JA biosynthesis. Notably, the positive regulation of transcription factor (TF) AchABF1-1 on AchLOX3 and AchOPR3 was identified. ABA-induced AchABF-1 located in the nucleus and activated the transcriptional expression of AchLOX3 and AchOPR3 through binding to their promoters. These results were further confirmed in the tobacco leaves overexpressing AchABF1-1 in which AchABF1-1 promoted NbLOX and NbOPR expression with the increases of JA content. In addition, exogenous ABA increased endogenous JA content, and enhanced LOX and OPR activities as well as their related gene expression, while FLD reduced these indices. These results suggested that the promotion effect of JA on the SPP accumulation was enhanced through the promotion of JA biosynthesis by ABA-responsive transcription factor AchABF1-1 during the wound healing process of kiwifruit. [ABSTRACT FROM AUTHOR]

Abstract: A novel couple images encryption algorithm based on DNA subsequence operation and chaotic system is presented. Different from the traditional DNA encryption methods, our algorithm is not use complex biological operation, but just uses the idea of DNA subsequence operation (such as elongation operation, truncation operation, and deletion operation). And then, do the DNA addition operation under the Chen's Hyper-chaotic map in this image cipher. The simulation experimental results and security analysis show that our algorithm not only has good encryption effect, but also has the ability of resisting exhaustive attack and statistical attack. [Copyright &y& Elsevier]

Abstract: In recent years, the studies of chaos-based image encryption have become an important aspect of the security of image transmission. So far, a large amount of chaotic maps have been used in image encryption with the permutation–diffusion architecture, such as logistic map, cat map, tent map and so on. In this paper, a defect of designing an image cryptosystem based on logistic map is proposed. According to the cryptanalysis of the defect, the initial value of logistic which is used to encrypt plain-image can be deduced by the decreased key space, when the parameter of logistic map is given. Finally, the theoretical analysis and numerical experimental results show that the defect could be used to break the image cryptosystem based on logistic map. [Copyright &y& Elsevier]

Abstract: In order to improve the conversion efficiency of grid-connected PV system, a new method to realize maximum power point tracking - recursive Calculation were proposed. This method is the direct calculation of the maximum power point, and its hardware uses a DC/DC boosted circuit to regulate PWM duty cycle. Only through a sampling, the voltage of the maximum power point and the duty cycle value can be calculated directly. By adjusting the value of duty cycle, the values of voltage and current can be got recursively, and then determine whether the derivative that power divide voltage equals to zero. If zero, it indicates the maximum power point has been reached. By DSP2812 this method has been verified that it shows rapid computing speed, high accuracy, and high stability of the system. [Copyright &y& Elsevier]

Abstract: In this paper, a novel approach is presented for the motion retrieval based on the similarity of the motion data. For each sequence in the database, the Independent Component Analysis (ICA) algorithm is used to extract features, the reference vector''s distribution is estimated instead of the original data.The reference vector is clustered using Iterative Self-organizing Data Analysis Techniques Algorithm (ISODATA). Finally the similarity between the query example and motion sequence in the database is measured using the Mahalanobis distance. Experimental results on the CMU databaase demonstrate that the proposed approach achieves good performance. [Copyright &y& Elsevier]

Abstract: In this paper, we obtain some sufficient conditions for determining the asymptotic stability of discrete-time non-autonomous delayed Hopfield neural networks by utilizing the Lyapunov functional method. An example is given to show the validity of the results. [Copyright &y& Elsevier]

Abstract: Precise pupil center detection is an important factor for gaze tracking in video-oculography (VOG) systems. Existing methods perform well to extract the features when the area of pupil in eye image is clear, whereas, interferences, such as eyelashes, corneal reflection etc., will lead to a low success rate. One main reason is the closure of eyelids. In this paper, a systemic 3D transformation algorithm is proposed to accurately ascertain the pupil center, in spite of the complicating factors mentioned above. Experiments show the good performance of our method. And the pupil center could be extracted accurately, even though only 25% of the pupil is visible. [Copyright &y& Elsevier]

Abstract: By constructing suitable Lyapunov functionals and combining with matrix inequality technique, a new sufficient condition is presented for the global asymptotic stability of delayed neural networks. The condition contains and improves some of the previous results in the earlier references. [Copyright &y& Elsevier]

Abstract: In this paper, by utilizing the Lyapunov functional method and combining with the linear matrix inequality approach, we analyze the global asymptotic stability of delayed Hopfield neural networks (HNNs). A new sufficient condition ensuring the global stability of the unique equilibrium point of delayed HNNs is obtained, which is dependent on the size of delays. This condition is less restrictive and conservative than that given in the earlier references. In addition, an example is also provided to illustrate the applicability of the result. [Copyright &y& Elsevier]

Abstract: In this Letter, by utilizing Lyapunov functional method and Halanay inequalities, we analyze global exponential stability of nonautonomous cellular neural networks with delay. Several new sufficient conditions ensuring global exponential stability of the network are obtained. The results given here extend and improve the earlier publications. An example is given to demonstrate the effectiveness of the obtained results. [Copyright &y& Elsevier]

A new sufficient condition has been presented ensuring the global exponential stability of cellular neural networks with time-varying delays by using an approach based on delay differential inequality combining with Young inequality. The results established here extend those earlier given in the literature. Compared with the method of Lyapunov functionals as in most previous studies, our method is simpler and more effective for stability analysis. [Copyright &y& Elsevier]

Abstract: This paper provides a new sufficient condition for the complete stability of the delayed cellular neural networks. This condition imposes constraints on the parameters of the networks and the size of time delay. The linear matrix inequality approach plays an important role in the proof. Our result recovers the known results in the earlier literature as special cases. Finally, we give an example to illustrate the applicability of our main result. [Copyright &y& Elsevier]

• AchnCYP86A1 and AchnFAR were involved in wound suberinzation of kiwifruit. • AcnMYB4 repressed AchnCYP86A1 and AchnFAR expression by binding to gene promoter. • ABA induced the AchnCYP86A1 and AchnFAR expression by inhibition of AchnMYB4. Suberin biosynthesis involves a large number of genes, and many of them are induced by abscisic acid (ABA). However, the regulation of transcription factor (TF) in response to ABA on suberin biosynthetic genes in kiwifruit has been unexplored. In this study, two genes, AchnCYP86A1 and AchnFAR respectively encoding a fatty acid ω-hydroxylase and fatty acyl-CoA reductase involved in suberin monomer biosynthesis were demonstrated in transient overexpressed tobacco (Nicotiana benthamiana). Notably, the negative regulation of AchnMYB4 on AchnCYP86A1 and AchnFAR was identified. AchnMYB4 could repress AchnCYP86A1 and AchnFAR transcript by directly binding to the gene promoter in yeast one-hybrid and dual-luciferase assays. These results were further confirmed in transient overexpressed tobacco leaves in that AchnMYB4 significantly down-regulated suberin biosynthetic genes including CYP86A1 , FAR2 and FAR3 , and reduced accumulation of ω-hydroxyacids and primary alcohols. Moreover, exogenous ABA could induce the expression of AchnCYP86A1 and AchnFAR , and the accumulation of corresponding suberin monomers by inhibition of AchnMYB4 in wound-tissue of kiwifruit. However, fluridone (an inhibitor of ABA biosynthesis) was found to counter the inductive effects of ABA. Taken together, the results suggest that ABA activates AchnCYP86A1 and AchnFAR to promote suberin monomers biosynthesis by inhibiting AchnMYB4. [ABSTRACT FROM AUTHOR]

Identifying the abnormal samples from a data set and determining their type are two key tasks of anomaly detection. However, the existing anomaly detection algorithms are generally faced with the defects of weak generalization ability and insufficient interpretation, the core reason of which is that they cannot mine specific features for different abnormal types. In this paper, a new anomaly detection algorithm aiming at feature selection for different abnormal types is developed. Inspired by self-supervised learning, we take the stationarity of variance changes of abnormal score similarity as a pretext task and combine it with wrapped search method. Then, the features and the corresponding parameters for different abnormal types can be screened to apply to the downstream task of anomaly integration detection. To verify the efficiency of the new algorithm, we conduct two sets of experiments to compare the new algorithm with 11 classical anomaly detection and 3 clustering anomaly detection algorithms on the data sets WDBC, WPBC and Wilt from DAMI database with the evaluation measures P@n , Adj- P@n , AP, Adj-AP and AUC. The experiment results show that, both in the identification and classification on abnormal samples, all performance measures of the new algorithm are explicitly better than that of the contrastive algorithms. Also, we apply the new algorithm to the Chinese auto insurance market, and find that the results can help managers to identify the main patterns of fraudulent claims and to summarize the feature combinations of fraud behaviors. In general, the new algorithm developed in this paper has the following advantages compared with traditional algorithms: 1) It can directly capture abnormal features and realize effective recognition of abnormal types, which effectively bridge the gap between abnormal judgement and feature screening. 2) Automatic screening of abnormal features can be completed under the condition of self-updating learning optimal strategy. 3) Only a few features are extracted from all features to reveal the abnormal characteristics, which significantly improves the interpretability and generalization ability of the algorithm and its results. In a word, through the novel self-supervised design method, feature screening is skillfully integrated into the anomaly detection task, which may provide a new way for anomaly detection research. [ABSTRACT FROM AUTHOR]