杉木GRF和GIF基因家族鉴定、表达与互作分析

生长调节因子(GRF)和GRF相互作用因子(GIF)在植物的生长发育和逆境胁迫响应中发挥重要作用。为研究GRF和GIF基因在杉木生长发育和逆境胁迫响应中的功能,本研究基于杉木全长转录组数据,利用生物信息学手段共鉴定获得5个ClGRFs基因和2个ClGIFs基因。分析结果显示,ClGRFs氨基酸残基数目范围为386(ClGRF4)~723 aa(ClGRF3),等电点为7.07(ClGRF4)~9.26(ClGRF5);2个ClGIFs蛋白氨基酸数目分别为242和258 aa,等电点均在6左右,蛋白质分子质量分别为25.64和27.96 kDa。保守结构域和基序分析发现ClGRFs蛋白均含QLQ和WRC结构域,ClGIFs蛋白均含SSXT结构域,且高度保守。进一步分析结果显示,ClGRFs分别属于进化枝Ⅲ和进化枝Ⅵ,且均受miR396调控。表达分析结果表明,ClGRFs基因的表达具有一定的组织特异性,而ClGIFs在不同组织呈组成性表达,且ClGRFs和ClGIFs基因均能响应赤霉素(GA3)和水杨酸(SA)的处理。酵母双杂交结果表明5个ClGRFs蛋白和2个ClGIFs蛋白均存在互作关系。本研究结果为进一步研究杉木GRF和GIF基因的功能提供了理论基础。

A Linked List Encryption Scheme for Image Steganography without Embedding

Information steganography has received more and more attention from scholars nowadays,especially in the area of image steganography,which uses image content to transmit information and makes the existence of secret information undetectable.To enhance concealment and security,the Steganography without Embedding(SWE)method has proven effective in avoiding image distortion resulting from cover modification.In this paper,a novel encrypted communication scheme for image SWE is proposed.It reconstructs the image into a multi-linked list structure consisting of numerous nodes,where each pixel is transformed into a single node with data and pointer domains.By employing a special addressing algorithm,the optimal linked list corresponding to the secret information can be identified.The receiver can restore the secretmessage fromthe received image using only the list header position information.The scheme is based on the concept of coverless steganography,eliminating the need for any modifications to the cover image.It boasts high concealment and security,along with a complete message restoration rate,making it resistant to steganalysis.Furthermore,this paper proposes linked-list construction schemeswithin theproposedframework,which caneffectively resist a variety of attacks,includingnoise attacks and image compression,demonstrating a certain degree of robustness.To validate the proposed framework,practical tests and comparisons are conducted using multiple datasets.The results affirm the framework’s commendable performance in terms of message reduction rate,hidden writing capacity,and robustness against diverse attacks.

基于对比学习和GIF标记的多模态对话回复检索

社交媒体网站上使用GIF(Graphics Interchange Format)作为消息的回复相当普遍。但目前大多方法针对问题“如何选择一个合适的GIF回复消息”,没有很好地利用社交媒体上的GIF附属标记信息。为此,提出基于对比学习和GIF标记的多模态对话回复检索(CoTa-MMD)方法,将标记信息整合到检索过程中。具体来说就是使用标记作为中间变量,文本→GIF的检索就被转换为文本→GIF标记→GIF的检索,采用对比学习算法学习模态表示,并利用全概率公式计算检索概率。与直接的文本图像检索相比,引入的过渡标记降低了不同模态的异质性导致的检索难度。实验结果表明,CoTa-MMD模型相较于深度监督的跨模态检索(DSCMR)模型,在PEPE-56多模态对话数据集和Taiwan多模态对话数据集上文本图像检索任务的召回率之和分别提升了0.33个百分点和4.21个百分点。

A Review on the Recent Trends of Image Steganography for VANET Applications

Image steganography is a technique of concealing confidential information within an image without dramatically changing its outside look.Whereas vehicular ad hoc networks(VANETs),which enable vehicles to communicate with one another and with roadside infrastructure to enhance safety and traffic flow provide a range of value-added services,as they are an essential component of modern smart transportation systems.VANETs steganography has been suggested by many authors for secure,reliable message transfer between terminal/hope to terminal/hope and also to secure it from attack for privacy protection.This paper aims to determine whether using steganography is possible to improve data security and secrecy in VANET applications and to analyze effective steganography techniques for incorporating data into images while minimizing visual quality loss.According to simulations in literature and real-world studies,Image steganography proved to be an effectivemethod for secure communication on VANETs,even in difficult network conditions.In this research,we also explore a variety of steganography approaches for vehicular ad-hoc network transportation systems like vector embedding,statistics,spatial domain(SD),transform domain(TD),distortion,masking,and filtering.This study possibly shall help researchers to improve vehicle networks’ability to communicate securely and lay the door for innovative steganography methods.

A Shuffling-Steganography Algorithm to Protect Data of Drone Applications

In Saudi Arabia,drones are increasingly used in different sensitive domains like military,health,and agriculture to name a few.Typically,drone cameras capture aerial images of objects and convert them into crucial data,alongside collecting data from distributed sensors supplemented by location data.The interception of the data sent from the drone to the station can lead to substantial threats.To address this issue,highly confidential protection methods must be employed.This paper introduces a novel steganography approach called the Shuffling Steganography Approach(SSA).SSA encompasses five fundamental stages and three proposed algorithms,designed to enhance security through strategic encryption and data hiding techniques.Notably,this method introduces advanced resistance to brute force attacks by employing predefined patterns across a wide array of images,complicating unauthorized access.The initial stage involves encryption,dividing,and disassembling the encrypted data.A small portion of the encrypted data is concealed within the text(Algorithm 1)in the third stage.Subsequently,the parts are merged and mixed(Algorithm 2),and finally,the composed text is hidden within an image(Algorithm 3).Through meticulous investigation and comparative analysis with existing methodologies,the proposed approach demonstrates superiority across various pertinent criteria,including robustness,secret message size capacity,resistance to multiple attacks,and multilingual support.

A Single-Sized Metasurface for Image Steganography and Multi-Key Information Encryption

With the escalating flow of information and digital communication,information security has become an increasingly important issue.Traditional cryptographic methods are being threatened by advancing progress in computing,while physical encryption methods are favored as a viable and compelling avenue.Metasurfaces,which are known for their extraordinary ability to manipulate optical parameters at the nanoscale,exhibit significant potential for the revolution of optical devices,making them a highly promising candidate for optical encryption applications.Here,a single-sized metasurface with four independent channels is proposed for conducting steganography and multi-key information encryption.More specifically,plaintext is transformed into a ciphertext image,which is encoded into a metasurface,while the decryption key is discretely integrated into another channel within the same metasurface.Two different keys for steganographic image unveiling are also encoded into the metasurface and can be retrieved with different channels and spatial positions.This distributed multi-key encryption approach can enhance security,while strategically distributing images across distinct spatial zones serves as an additional measure to reduce the risk of information leakage.This minimalist designed metasurface,with its advantages of high information density and robust security,holds promise across applications including portable encryption,high-camouflaged image display,and high-density optical storage.

A Dynamic YOLO-Based Sequence-Matching Model for Efficient Coverless Image Steganography

Many existing coverless steganography methods establish a mapping relationship between cover images and hidden data.One issue with these methods is that as the steganographic capacity increases,the number of images stored in the database grows exponentially.This makes it challenging to build and manage a large image database.To improve the image library utilization and anti-attack capability of the steganography system,we propose an efficient coverless scheme based on dynamically matched substrings.We utilize You Only Look Once(YOLO)for selecting optimal objects and create a mapping dictionary between these objects and scrambling factors.Using this dictionary,each image is effectively assigned to a specific scrambling factor,which is then used to scramble the receiver’s sequence key.To achieve sufficient steganography capability with a limited image library,all substrings of the scrambled sequences have the potential to hide data.After matching the secret information,the ideal number of stego images will be obtained from the database.According to experimental results,this technology outperforms most previous works in terms of data load,transmission security,and hiding capacity.It can recover an average of 79.85%of secret information under typical geometric attacks,and only approximately 200 random images are needed to achieve a capacity of 19 bits per image.

An Improved Image Steganography Security and Capacity Using Ant Colony Algorithm Optimization

This advanced paper presents a new approach to improving image steganography using the Ant Colony Optimization(ACO)algorithm.Image steganography,a technique of embedding hidden information in digital photographs,should ideally achieve the dual purposes of maximum data hiding and maintenance of the integrity of the cover media so that it is least suspect.The contemporary methods of steganography are at best a compromise between these two.In this paper,we present our approach,entitled Ant Colony Optimization(ACO)-Least Significant Bit(LSB),which attempts to optimize the capacity in steganographic embedding.The approach makes use of a grayscale cover image to hide the confidential data with an additional bit pair per byte,both for integrity verification and the file checksumof the secret data.This approach encodes confidential information into four pairs of bits and embeds it within uncompressed grayscale images.The ACO algorithm uses adaptive exploration to select some pixels,maximizing the capacity of data embedding whileminimizing the degradation of visual quality.Pheromone evaporation is introduced through iterations to avoid stagnation in solution refinement.The levels of pheromone are modified to reinforce successful pixel choices.Experimental results obtained through the ACO-LSB method reveal that it clearly improves image steganography capabilities by providing an increase of up to 30%in the embedding capacity compared with traditional approaches;the average Peak Signal to Noise Ratio(PSNR)is 40.5 dB with a Structural Index Similarity(SSIM)of 0.98.The approach also demonstrates very high resistance to detection,cutting down the rate by 20%.Implemented in MATLAB R2023a,the model was tested against one thousand publicly available grayscale images,thus providing robust evidence of its effectiveness.

Randomization Strategies in Image Steganography Techniques:A Review

Image steganography is one of the prominent technologies in data hiding standards.Steganographic system performance mostly depends on the embedding strategy.Its goal is to embed strictly confidential information into images without causing perceptible changes in the original image.The randomization strategies in data embedding techniques may utilize random domains,pixels,or region-of-interest for concealing secrets into a cover image,preventing information from being discovered by an attacker.The implementation of an appropriate embedding technique can achieve a fair balance between embedding capability and stego image imperceptibility,but it is challenging.A systematic approach is used with a standard methodology to carry out this study.This review concentrates on the critical examination of several embedding strategies,incorporating experimental results with state-of-the-art methods emphasizing the robustness,security,payload capacity,and visual quality metrics of the stego images.The fundamental ideas of steganography are presented in this work,along with a unique viewpoint that sets it apart from previous works by highlighting research gaps,important problems,and difficulties.Additionally,it offers a discussion of suggested directions for future study to advance and investigate uncharted territory in image steganography.

Image Steganography by Pixel-Value Differencing Using General Quantization Ranges

A new steganographic method by pixel-value differencing(PVD)using general quantization ranges of pixel pairs’difference values is proposed.The objective of this method is to provide a data embedding technique with a range table with range widths not limited to powers of 2,extending PVD-based methods to enhance their flexibility and data-embedding rates without changing their capabilities to resist security attacks.Specifically,the conventional PVD technique partitions a grayscale image into 1×2 non-overlapping blocks.The entire range[0,255]of all possible absolute values of the pixel pairs’grayscale differences in the blocks is divided into multiple quantization ranges.The width of each quantization range is a power of two to facilitate the direct embedding of the bit information with high embedding rates.Without using power-of-two range widths,the embedding rates can drop using conventional embedding techniques.In contrast,the proposed method uses general quantization range widths,and a multiple-based number conversion mechanism is employed skillfully to implement the use of nonpower-of-two range widths,with each pixel pair being employed to embed a digit in the multiple-based number.All the message bits are converted into a big multiple-based number whose digits can be embedded into the pixel pairs with a higher embedding rate.Good experimental results showed the feasibility of the proposed method and its resistance to security attacks.In addition,implementation examples are provided,where the proposed method adopts non-power-of-two range widths and employsmultiple-based number conversion to expand the data-hiding and steganalysis-resisting capabilities of other PVD methods.

A Review of Image Steganography Based on Multiple Hashing Algorithm

Steganography is a technique for hiding secret messages while sending and receiving communications through a cover item.From ancient times to the present,the security of secret or vital information has always been a significant problem.The development of secure communication methods that keep recipient-only data transmissions secret has always been an area of interest.Therefore,several approaches,including steganography,have been developed by researchers over time to enable safe data transit.In this review,we have discussed image steganography based on Discrete Cosine Transform(DCT)algorithm,etc.We have also discussed image steganography based on multiple hashing algorithms like the Rivest–Shamir–Adleman(RSA)method,the Blowfish technique,and the hash-least significant bit(LSB)approach.In this review,a novel method of hiding information in images has been developed with minimal variance in image bits,making our method secure and effective.A cryptography mechanism was also used in this strategy.Before encoding the data and embedding it into a carry image,this review verifies that it has been encrypted.Usually,embedded text in photos conveys crucial signals about the content.This review employs hash table encryption on the message before hiding it within the picture to provide a more secure method of data transport.If the message is ever intercepted by a third party,there are several ways to stop this operation.A second level of security process implementation involves encrypting and decrypting steganography images using different hashing algorithms.

High-Secured Image LSB Steganography Using AVL-Tree with Random RGB Channel Substitution

Random pixel selection is one of the image steganography methods that has achieved significant success in enhancing the robustness of hidden data.This property makes it difficult for steganalysts’powerful data extraction tools to detect the hidden data and ensures high-quality stego image generation.However,using a seed key to generate non-repeated sequential numbers takes a long time because it requires specific mathematical equations.In addition,these numbers may cluster in certain ranges.The hidden data in these clustered pixels will reduce the image quality,which steganalysis tools can detect.Therefore,this paper proposes a data structure that safeguards the steganographic model data and maintains the quality of the stego image.This paper employs the AdelsonVelsky and Landis(AVL)tree data structure algorithm to implement the randomization pixel selection technique for data concealment.The AVL tree algorithm provides several advantages for image steganography.Firstly,it ensures balanced tree structures,which leads to efficient data retrieval and insertion operations.Secondly,the self-balancing nature of AVL trees minimizes clustering by maintaining an even distribution of pixels,thereby preserving the stego image quality.The data structure employs the pixel indicator technique for Red,Green,and Blue(RGB)channel extraction.The green channel serves as the foundation for building a balanced binary tree.First,the sender identifies the colored cover image and secret data.The sender will use the two least significant bits(2-LSB)of RGB channels to conceal the data’s size and associated information.The next step is to create a balanced binary tree based on the green channel.Utilizing the channel pixel indicator on the LSB of the green channel,we can conceal bits in the 2-LSB of the red or blue channel.The first four levels of the data structure tree will mask the data size,while subsequent levels will conceal the remaining digits of secret data.After embedding the bits in the binary tree level by level,the model restores the AVL tree to create the stego image.Ultimately,the receiver receives this stego image through the public channel,enabling secret data recovery without stego or crypto keys.This method ensures that the stego image appears unsuspicious to potential attackers.Without an extraction algorithm,a third party cannot extract the original secret information from an intercepted stego image.Experimental results showed high levels of imperceptibility and security.

Elevating Image Steganography:A Fusion of MSB Matching and LSB Substitution for Enhanced Concealment Capabilities

In today’s rapidly evolving landscape of communication technologies,ensuring the secure delivery of sensitive data has become an essential priority.To overcome these difficulties,different steganography and data encryption methods have been proposed by researchers to secure communications.Most of the proposed steganography techniques achieve higher embedding capacities without compromising visual imperceptibility using LSB substitution.In this work,we have an approach that utilizes a combinationofMost SignificantBit(MSB)matching andLeast Significant Bit(LSB)substitution.The proposed algorithm divides confidential messages into pairs of bits and connects them with the MSBs of individual pixels using pair matching,enabling the storage of 6 bits in one pixel by modifying a maximum of three bits.The proposed technique is evaluated using embedding capacity and Peak Signal-to-Noise Ratio(PSNR)score,we compared our work with the Zakariya scheme the results showed a significant increase in data concealment capacity.The achieved results of ourwork showthat our algorithmdemonstrates an improvement in hiding capacity from11%to 22%for different data samples while maintaining a minimumPeak Signal-to-Noise Ratio(PSNR)of 37 dB.These findings highlight the effectiveness and trustworthiness of the proposed algorithm in securing the communication process and maintaining visual integrity.

A Novel LSB Steganography Technique for Enhancing Cloud Security

Steganography is a technique that is frequently used to hide hidden information in multimedia artifacts including music, video, and images. In order to protect data saved in the cloud, this paper presents a steganography method for encrypting sound utilizing LSB-based computation. By using the least significant bit (LSB) of a byte to represent a message and then substituting each LSB bit with a binary message and encrypting a significant quantity of data. The proposed system uses the LSB technique of picture steganography, Multi-Level Encryption Algorithm (MLEA) and Two-Level Encryption Algorithm (TLEA) data encryption to give the highest level of cloud security. Compared to other current schemes, the performance of the suggested method is 1.732125% better on average.

GIF教学模式在高中英语读后续写教学中的实践

以支架理论和互动协同理论为理论基础,从读后续写的问题出发,试构建GIF教学模式探究完整的续写策略,明确学生写作思路。GIF教学模式旨在从语言和思维两方面搭建续写支架,按照“主旨阅读(Gist reading)-推理判断(Inference)-情节构建(Formulation)”三路径实施支架教学,激活学生结构、内容与语言图式,增强协同效应,并引入师生合作评价促进人际互动,以期最大化激发学生的内生表达动力,提升续写成效。

基于GeoGebra和GIF图形的复变函数点集绘制

采用Geo Gebra6制作复变函数中的点集绘图,并解复数方程把复数根可视化,使学生通过简单的软件操作掌握抽象函数的几何意义。使用Geo Gebra5软件制作割圆术的GIF图形,让抽象的内容更生动,提升课堂的可视化效果。近年来,随着有关可视化教学的研究逐步开展,其在提升教学效果方面的作用日益受到重视[1]。而复变函数课程中研究不等式所确定的区域或非区域,连通或不连通,通过一个抽象表达式,一般很难判定。

An Animated GIF Steganography Using Variable Block Partition Scheme

The paper presents a novel Graphics Interchange Format (GIF) Steganography system. The algorithm uses an animated (GIF) file format video to applyon, a secured and variable image partition scheme for data embedding. The secretdata could be any character text, any image, an audio file, or a video file;that isconverted in the form of bits. The proposed method uses a variable partitionscheme structure for data embedding in the (GIF) file format video. The algorithmestimates the capacity of the cover (GIF) image frames to embed data bits. Ourmethod built variable partition blocks in an empty frame separately and incorporate it with randomly selected (GIF) frames. This way the (GIF) frame is dividedinto variable block same as in the empty frame. Then algorithm embeds secretdata on appropriate pixel of the (GIF) frame. Each selected partition block for dataembedding, can store a different number of data bits based on block size. Intruders could never come to know exact position of the secrete data in this stegoframe. All the (GIF) frames are rebuild to make animated stego (GIF) video.The performance of the proposed (GIF) algorithm has experimented andevaluated based on different input parameters, like Mean Square Error (MSE)and Peak Signal-to-Noise Ratio (PSNR) values. The results are compared withsome existing methods and found that our method has promising results.

黑麦GIF基因家族全基因组鉴定及其表达分析

生长调节互作因子(GRF-interacting factor,GIF)是植物体内一类转录共激活因子,在植物生长发育过程中起重要作用。为挖掘和利用黑麦GIF家族基因,利用同源比对方法对黑麦GIF基因家族进行了鉴定,并系统分析了黑麦与其他禾本科植物及模式植物拟南芥GIF基因的系统发育关系、蛋白结构域、基因结构和共线性关系。结果显示,在黑麦基因组中共鉴定到3个GIF基因家族成员,分布在4R和5R染色体上;系统进化分析发现,黑麦GIF基因家族成员与小麦和大麦的亲缘关系更近。蛋白结构域和基因结构分析发现,GIF基因家族成员在黑麦及其他禾本科植物中的蛋白结构域和基因结构相对保守,均含有4个外显子。共线性分析发现,黑麦ScGIF1基因与其他禾本科植物GIF基因间均存在共线性关系,其中与小麦间共线基因数最多。Ka/Ks分析发现,黑麦GIF基因家族成员在进化中受到纯化选择。此外,在黑麦穗部鉴定到一个特异性高表达的GIF基因(ScGIF1),其编码的蛋白含有多个磷酸化位点,推测ScGIF1蛋白可能是通过磷酸化来调控黑麦麦穗的发育和粒型的。

GIF动图的著作权问题研究

GIF动图作为一种典型的用户生成内容,无论是从对素材的选择角度,还是从对画面的选择和编排角度来看,其都满足了著作权法意义上的独创性标准。因此,在现行实定法框架内GIF动图可以被认定为视听作品。在用户制作和传播GIF动图的过程中,可能会涉及对原作品权利人的复制权、信息网络传播权、表演权以及放映权的侵犯。基于解释论立场,通常情况下制作GIF动图虽然会利用他人在先作品,但仍然不妨碍构成对原作品的合理使用,这一结论也可依据四要素标准从学理上得以检验。同时,GIF动图分享平台在处理有关GIF动图所引发的纠纷时,需要遵循公私法二分的处理方式,即对于有关GIF动图私法方面的争议,应当遵循被动审查的原则;而在面对有关公法方面的争议时,原则上应以接到投诉作为其采取措施的义务来源,但对于特殊内容仍应主动履行必要的审查义务。

Improved Video Steganography with Dual Cover Medium,DNA and Complex Frames

The most valuable resource on the planet is no longer oil,but data.The transmission of this data securely over the internet is another challenge that comes with its ever-increasing value.In order to transmit sensitive information securely,researchers are combining robust cryptography and steganographic approaches.The objective of this research is to introduce a more secure method of video steganography by using Deoxyribonucleic acid(DNA)for embedding encrypted data and an intelligent frame selection algorithm to improve video imperceptibility.In the previous approach,DNA was used only for frame selection.If this DNA is compromised,then our frames with the hidden and unencrypted data will be exposed.Moreover the frame selected in this way were random frames,and no consideration was made to the contents of frames.Hiding data in this way introduces visible artifacts in video.In the proposed approach rather than using DNA for frame selection we have created a fakeDNA out of our data and then embedded it in a video file on intelligently selected frames called the complex frames.Using chaotic maps and linear congruential generators,a unique pixel set is selected each time only from the identified complex frames,and encrypted data is embedded in these random locations.Experimental results demonstrate that the proposed technique shows minimum degradation of the stenographic video hence reducing the very first chances of visual surveillance.Further,the selection of complex frames for embedding and creation of a fake DNA as proposed in this research have higher peak signal-to-noise ratio(PSNR)and reduced mean squared error(MSE)values that indicate improved results.The proposed methodology has been implemented in Matlab.