观点: 作为拥有研发背景的认知观点, 作者每次发现了一些理论和创造性思维, 便开始工程设计, 在真实的场景中应用, 进行论证, 确定它的社会价值: 改变生产力, 创造新的生产力, 优化和归纳生产资料, 最后适应生产环境并进行有效的从局部到整体的修复, 优化, 改善, 改变, 创造新的更好的环境的过程. 作者认为 一个命题论点必须经过严谨的推导论证, 确定它的真实性和有效性. 这篇著作于是形成了骨架.
OUTLOOK: Due to the cognitically researching background, the Author always prepare more and more real world software projects where supporting the proof in truly way: Emancipate the productive forces, Create new productivity, Optimize existing production tools to better adapt to the production environment and Better assists Human-oid in where understanding, adaptation and transformation of the environment, there for, thurs proofs and factors where could be garthered to the parts of backbone in catalytic computing of the humanoid DNA.
Keywords: Chromosome, PDC, PDW, TVM, PDE, PDE-Code, Eternal-tons, L-Pyrimidine, Discrete
关键词: 染色体, 生命词根库, 象契文字典, 肽虚拟机器, 磁基肽展公式, 非对称肽加密, 永生苷, 变嘧啶, 离散定律
前言: 自从罗瑶光先生发现了类人 DNA 与 神经元基于催化算子映射编码方式后, 于是开始进行多种具体工程应用论证实现, 这个过程一次又一次的改变作者的思维, 特别是生命染色体配对后聚合方式, 形成了具体的生命词根库, 然后组成象契文字典, 逐渐形成肽虚拟机模拟, 进而优化推导出肽展公式, 非对称肽加密, 永生苷, 变嘧啶 作为DNA离散定律的补充, 于是归纳成一个完整的系统思想, 正如这篇文章, 对于AOPM VECS IDUQ 肽元基编码计算与它的应用, 永生只是开始~
Since Mr.Yaoguang Luo AND Mr.Rongwu luo found out the ‘The INITONS Catalytic Reflection Between Humanoid DNA and Nero Cell(DNA encoding 1.2.2)’ see 1.2.2 Chinese full style: NCAC, CN2020Z11L0333706. English short style: EI ACM, A2050-ICITEE2020, then did alot of proofs in DETA web big data projects, such like (Deta OSS…). Always, Those proofs have been pushing Mr.Yaoguang who always jumping out the way of his mind for thinking in depthly… for the instances PDC, PDW, TVM, PDE, PDE-Code, Eternal-tons and L-Pyrimidine, the Author will prepare more and more logic caculation proofs about implementing the ‘AOPM-VECS-IDUQ Catalytic INITONS PDE LAW and Its Application’ in sequency flowchat as below.
I DETA INITONS classify/ 德塔元基 分类
Figure 1 见文件地址: github https://github.com/yaoguangluo/Deta_Resource/blob/master/CN_DT_pdn_computing1_2_2.pdf
Figure 1 见文件地址: gitee https://gitee.com/DetaChina/collection-of-papers-by-deta/blob/master/CN_DT_pdn_computing1_2_2.pdf
选个切入点说起, 自从作者在上一篇著作DNA编码规范中发现了类DNA的编码元 AOPM VPCS IDUC 后进行了简单的去重生成 AOPM VECS IDUQ, 于是开始女娲计划设计如Figure 1, 现在按照主谓宾, 定状补的语法组成形式设计3元词根如: 单元基 AOPM VECS IDUQ. 双元基 AA… AO… AP… AM … OA…OO… OP… OM… 三元基 AAA… AAO… AAP… AAM… 通过编码, 发现 仅仅1维词根便包含上千的逻辑含义, 如果2维词根如 …AAA.AAO… 便瞬间膨胀到(1000+) * (1000+)= 100万+, 这个意识远远大于人类现在的最高学术水平, 于是惊叹, 如何合理的应用这种知识结构? 似乎有点远, 先从养疗经上做元initons分类实验. 如下FIGURE 1-1
Since the latest document paper “The INITONS Catalytic Reflection Between Humanoid DNA and Nero Cell” finished, the Author changes the name of AOPM-VPCS-IDUC initons into AOPM-VECS-IDUQ due to the duplication of the same chars P and C. then starts the NUWA plan, please see at Figure 1, similar with the Human’s grammar, could format the initons as three types, one for Single-tons A, O, P, M, V, E, C, S, I, D, U, Q; two for Double-tons AA, AO, AP, AM, … …OA, OP, OM… AND Triper-tons AAA, AAO, AAP, AAM… Then we could find out more than 1800 Triper initons word’s root. if it’s root words appear in 2 dimension or more dimension root links… It could happen and detail out the conbination features of more than one millon real world verbal’s, so let’s talking about the ‘YANGLIAOJING’ software on a researching way as FIGURE 1-1.
Figure 1-1 见文件地址: github https://github.com/yaoguangluo/Deta_Resource/blob/master/CN_DT_pdn_computing1_2_2.pdf
Figure 1-1 见文件地址: gitee https://gitee.com/DetaChina/collection-of-papers-by-deta/blob/master/CN_DT_pdn_computing1_2_2.pdf
一开始养疗经的ETL 节点 通过插件的方式扩充, 作者想设计成肽化插件形式, 通过TVM 肽化虚拟机来添加jar包,这样 jar包也可以设计成肽文件编码. 既可以加密保存又可以作为肽节点拓展. 于是作者开始验证可行性, 先按简单的分类和聚类索引模式, 按 A, AO, AOP, 进行节点归类. 研究发现, 一个肽索引世界展现在眼前, 原来这种染色体化的结构数不尽, 于是开始按主谓宾的方式开始模拟明显特征规范的 3元染色体层, 结果发现也有24对, 如Figure 2
Base through the DETA Unicorn Nodes in ETL OSGI plug-in way, the Author try to code the ETL node files where transpoting into a PDN files by using DNA catalytic 1.2.2 INITONS encoding technonogy, At that time, Author thinks It could be used in Data encoding domain. Let’s proving, for example the first, using classify method, define the A, AO, AOP… did the PDN files name’s statistic in an observer view upon the classify model. then get a true answear of the main features of triper-tons classify where similar with 24 basic types. as Figure 2 shows.
Figure 2 见文件地址: github https://github.com/yaoguangluo/Deta_Resource/blob/master/CN_DT_pdn_computing1_2_2.pdf
Figure 2 见文件地址: gitee https://gitee.com/DetaChina/collection-of-papers-by-deta/blob/master/CN_DT_pdn_computing1_2_2.pdf
如下文字. 如图先将12个元基initons AOPM VECS IDUQ进行root 根拓展, 发现生成 AOPM- VECS 和AOPM-IDUQ 显隐模式于是发现了 24 类组, 正如figure 2 这些类组一开始作者的思路是染色体索引, 后来思考 如果这种索引能进行功能化, 那么就是一个个函数的主要功能区, 于是按DNA 编码规范1.2.2开始定义词根, 发现了很多惊讶和有趣的研究结果如 Figure4 词根的发现.
let’s proving that the root extension of the initons AOPM-VECS-IDUQ, we could see there have 2 types initon section-extensions per each same initon section. For example we can find AOPM has AOPM-VECS and AOPM-IDUQ, the author named dominant chromosome and recessive chromosome, after named, it proofs the software’s function also could be extended to the PDN funtion Observer model. then following ‘The INITONS Catalytic Reflection Between Humanoid DNA and Nero Cell 1.2.2’ Author began to make a definition of the PDN’s word (PDW) by using PDN root initon chars(PDC), and those PDCs where could build a extension linklist model in the PDN files (PDE). see Figure 4(PDC)
II I DETA INITONS PDN words root/ 德塔元基分类 词根
分类组成词根 代表 动词, 名词和形容词, 动词 IDUC-前缀根, 名词 VPCS-前缀根, 形容词 AOPM-前缀根, 形成DNA 语言的 有效元染色体, 如图4, 按照编码规范, 2元词根有明确逻辑价值的组合竟然也是24个组, 作者开始专注思考. 这24组的功能进行深入研究…
After the classification of the PDC and into the 4-pars-chromosome model, it proofs the IDUC-PDC root where similar with the humanoid Verb definition; the VPCS-PDC root similar with the humanoid Noun definition; and the AOPM-PDC root similar with the humanoid Adj definition. See the Figure 4, by following DNA encoding 1.2.2 researching, then got 24 types useful 4-pars-chromosome model, let’s continuring proving as below…
Figure 4 见文件地址: github https://github.com/yaoguangluo/Deta_Resource/blob/master/CN_DT_pdn_computing1_2_2.pdf
Figure 4 见文件地址: gitee https://gitee.com/DetaChina/collection-of-papers-by-deta/blob/master/CN_DT_pdn_computing1_2_2.pdf
III DETA INITONS PDN words/ 德塔元基分类 词典
词根开始各种组合形成世界首个象契文字DNA语言, 按照罗瑶光先生的思维逻辑进行人类语言和象契语言转换 如 动词, 名词, 形容词… 于是我归纳了下 AOPM 体现了养疗经的智慧高级功能形态, VECS 体现了养疗经的多样化特征, IDUQ 体现了养疗经的生物应激活性, 这个归纳和总结, 用人类的认知的语义理解方式, 作者按照罗瑶光先生的思考方式进行词汇提炼, 确定了软件工程AOPM属于生命周期的系统分类,是一种高级形态, 具有可描述的智慧性, VPCS 因为涉及到控制执行, 插件扩展和静态属性, 作者认为是具有逻辑特征的多样性. 最后IDUQ因为涉及到增删改查, 都是运动方式, 作者定义为应激性表达. 于是再次归纳为Figure 5, 作者开始思考, dna的肽 竟然可以形成一篇具有阅读性的文章, 这篇文章竟然还有思维活性, 应激活性和智慧活性, 于是再次切入实际的论证 将java语言进行翻译成肽语言…
After researching, It proofs that DNA language is a hieroglyph-sphenogram word which has intently hieroglyph details and sphenogram formats. then next proof, the Author changes his thinking and mind reading ways into the hieroglyph-sphenogram word sentences, for example changes the human’s verb, noun and adj into DNA PDC roots PDW linklist. then find out that AOPM-VECS INITONS, wisdom dominant chromosome pair determines the way of wisdom association; AOPM-IDUQ INITONS, wisdom recessive chromosome pair determines the way of wisdom expression; VECS-AOPM INITONS, diversity dominant chromosome pairs, determine the diversity of consciousness characteristic; VECS-IDUQ INITONS, diversified recessive chromosome pairs to determine diversified motion characteristics; IDUQ-AOPM INITONS, stress dominant chromosome pair to determine the functional aspects of stress; IDUQ-VECS INITONS, stress recessive chromosome pairs to determine the expression object of stress. please see Figure 5, it proofs that DNA PDW could be a artical paper, and this paper could become to a life. it reflections as three instances: AOPM the diversity of consciousness characteristic, VECS wisdom association and IDUQ diversified motion characteristics. let’s proving in a real wold project ‘YANGLIAOJING’: Change the Java file into the PDE file.
Figure 5 见文件地址: github https://github.com/yaoguangluo/Deta_Resource/blob/master/CN_DT_pdn_computing1_2_2.pdf
Figure 5 见文件地址: gitee https://gitee.com/DetaChina/collection-of-papers-by-deta/blob/master/CN_DT_pdn_computing1_2_2.pdf
IV DETA TVM/ 德塔词典肽翻译虚拟机
于是开始将一个养疗经java文件翻译成肽文, 这个过程可以细分为几个细节, 如 Figure6, 先简单转成java行格式 肽文有利于区分. 有理观测. 然后再进行肽链化, 这时候作者发现了一些细节问题, 其中最主要的问题是怎么将AOPM 和 VECS向 IDUQ 层展开. 于是开始设计肽展函数. 我一直在思考一种可行的虚拟机形式, 如果我不设计而是依赖一种编程语言, 会出现平台移植困难, 于是先从肽翻译机开始.
After beginning of the PDE translation, the duration of operations could be parsed in a small details as Figure 6, first into TVM file, then into TVM-PDN list file. finally into a TVM-PDN-PDE IDUQ list file. This real operation needs a logic extension formular collection of PDE AOPM <-SWAP-> VECS <-SWAP->IDUQ ASAP. the Author thought JVM could embedded into other OS platform, TVM PDW needs inherit JVM this fomation: TVM could embedded into other programming languages environment(c/c++, QT, RUBY, C# .ETC…). let’s continuring proving TVM’s application.
Figure 6 见文件地址: github https://github.com/yaoguangluo/Deta_Resource/blob/master/CN_DT_pdn_computing1_2_2.pdf
Figure 6 见文件地址: gitee https://gitee.com/DetaChina/collection-of-papers-by-deta/blob/master/CN_DT_pdn_computing1_2_2.pdf
V DETA TVM applications/ 德塔 肽翻译虚拟机应用技术
首先想到的是加密应用, 比如我最近10年常用MD5加密, 筛子加密, 单握手非对称加密, DNA加密的效果因为有规则词库和规则概率钥匙, 然后丝化不饱和肽展失真, 所以加密无规律可循, 甚至越解越乱. 是很好的非对称加密方式.
The first real world imagination of application is Asymmetrically Communications Encryption, Such likes MD5 and Dice communication, DNA Encryption Includes the probabily extension and statistic method, lets the probabily extension build a key, and statistic method for indexing, its very hard to rollback without personal PDE laws, therefore, the level of the safe is pending highly. let’s proving.
Figure 7 见文件地址: github https://github.com/yaoguangluo/Deta_Resource/blob/master/CN_DT_pdn_computing1_2_2.pdf
Figure 7 见文件地址: gitee https://gitee.com/DetaChina/collection-of-papers-by-deta/blob/master/CN_DT_pdn_computing1_2_2.pdf
Figure 8 见文件地址: github https://github.com/yaoguangluo/Deta_Resource/blob/master/CN_DT_pdn_computing1_2_2.pdf
Figure 8 见文件地址: gitee https://gitee.com/DetaChina/collection-of-papers-by-deta/blob/master/CN_DT_pdn_computing1_2_2.pdf
我选了一个比较简洁的插件源码进行肽化, 这个源码首先短小, 词汇量少, 所以肽化的过程实现快, 比较好观测中间过程, 拓展我的研发思维. 通过intions词根进行语义编码后, 如Figure8, 因为空格和回车等符号没有intion词根转码, 保留了一些程序的特征. 这种文可以作为虚拟机文, 方便以后词库优化.
Initly, the Author choose a short Java file for PDN extending. because of short, its easy to understand how does TVM working for the translation. after observation of the duration, please see figure 8, without the simbol ENTER and TAB, TVM and JAVA all include the programming features. By following John Von Neumann’s flow chat, in order to optimiz to a PDE file in the next step, now save this programming features is sufficency and necessery.
VI DETA TVM PDC/ 虚拟机应用优化
Figure 9 见文件地址: github https://github.com/yaoguangluo/Deta_Resource/blob/master/CN_DT_pdn_computing1_2_2.pdf
Figure 9 见文件地址: gitee https://gitee.com/DetaChina/collection-of-papers-by-deta/blob/master/CN_DT_pdn_computing1_2_2.pdf
加密后于是开始 设计非词汇的符号, 如空格和回车等. 更好的将TVM肽虚拟机密文对比肽展文是因为在肽展公式论证中, 推导出概率变化 如 S = I, S =Q , (D=DD之后用于丝化计算), 如图Figure9虚拟机文在全部肽化后会惊奇的发现 整个文件 好比一个很长的链条. 这个链条有明确的序列和意思. 通过肽展的变换, 作者根据自身的对词汇的理解概括发现了.
After the DNA PDE Encryption, It proofs alot of PDE Law in Figure 9, we get alot of basic PDE formular like S = I, S = Q, (D = DD for PDE comp’s caculation, proof laterly), then proofs the Java or PDE file could be a PDE IDUQ initons linklist, this list has an absolutly hieroglyph-grammar in sphenogram-sequency. in Author’s collections, means from Human verbal list into a DNA verbal list by uing PDE Formular. let’s continuring proving as below…
I-INCREMENT/ADD D-DECREMENT/FILTER U-UPDATE C/Q-QUERY/CHECK
V-VITIONARY/FEEL P/E-EXECUTE C-CONTROL S-SET/STATIC
A-ANALYSIS O-OPERATION P-PROCESS M-MANAGEMENT
A分析 = V 感知 + S 静态 = U 改变 + Q 查询 + I 可增加 + Q 可查询 = U + Q + I = V + I…
A analysis = V visionary + S static sets = U update + Q query + I increment + Q query = U update + Q query+ I increment = V visionary + I increment…
O= E + S = I + U + I + Q = I + U + Q = E + Q…
P= E + C = I + U + I + D = I + U + D = E + D…
M= C + S = I + D + I + Q = I + D + Q = C + Q…
这些比较简单的分类, 为了决定它的有效性, 于是开始论证, 用作者的话语便是从语文词汇上的语义的概括到离散数学公式的变换过程展开式.于是开始各种模拟推导.
Then Author proofs that makes alot of real word POS words into PDW by using PDE logic classify method, in order to find more and more PDE formular LAW ASAP with a highly quality.
VII DETA TVM PDE/ 德塔肽翻译推导
完美的单链化后 开始思考怎么还原 迫切需要论证一些编码解码公式
After the linklist modulation, then need roll back the IDUQ into a highly style likes VECS and AOPM, so it seems Mr.Yaoguang need proof more, then continuring proving.
=>通过推导发现有些肽展过程是可以可逆变换的. (后来论证得到准确答案这是不严谨的)
=>After the perfect single chain, let’s started to think about how to rollback or restore it. It is urgent to demonstrate some encoding and decoding formulas.
A = S - I = I - S =…
O = S - Q = Q - S =…
P = C - D = D - S =…
M = S - Q = Q - S =…
=> 关于减法运算,作者想到计算汇编指令计算的反码和补码思路, 于是想到 可肽增方式. 于是停止了, 研究, 因为减法其实也是加法的一种形式.于是跟进论证优先级降低.
= >Regarding the subtraction of operation, the author thought of how to calculate the complement and implement increments of the calculation of the assembly instruction, so he thought of the PDE increase method. After research researching, because that subtraction almost actually a form of addition. So the priority of the follow-up argument is reduced down.
有价值的推导和假设如下
The valuable derivations and assumptions are as follows
V + S = V + I => S = I 联想/Imagination~ A = U
E + S = E + Q => S = Q 联想/Imagination~ A = T
E + C = E + D => C = D 联想/Imagination~ G = C
C + S = C + Q => S = Q 联想/Imagination~ A = T
=> 联想: 竟然和人类的ACGTU 腺吻合! 论证下~
假设 S 已经彻底解码为 A 腺嘌呤, 假设A 腺嘌呤在dna中属于原生静态物质, 于是得到可持续假设论证如下.
VECS-S 为 A-腺嘌呤 在 dna 函数中属于原生活性物质
IDUQ-Q 为 T-胸腺嘧啶 在 dna 函数中属于感应活性物质
IDUQ-I 为 U-尿嘧啶 在 dna 函数中属于增生活性物质
VECS-C 为 G-鸟嘌呤 在 dna 函数中属于控制活性物质
IDUQ-D 为 C-胞嘧啶 在 dna 函数中属于降解活性物质
=> Lenovo: It actually coincides with the human ACGTU gland! Under the argument~
Assuming that S has been completely decoded as A adenine, and assuming that A adenine is a primitive static substance in DNA, the sustainable hypothesis is demonstrated as follows.
VECS-S is A-adenine initon, which is the original active substance in DNA function
IDUQ-Q is T-thymine initon, which is an active substance in the DNA function
IDUQ-I is U-uracil initon is a life-enhancing substance in the DNA function
VECS-C is G-guanine initon which is a controlling active substance in DNA function
IDUQ-D is C-cytosine initon which is a degradation active substance in DNA function
=> 可持续论证如下. 嘌呤 生物多样化特征 属于VPCS INTIONS肽， 嘧啶 生物应激性特征 属于IDUQ INTIONS肽．
=> The sustainable proof is as follows. Purine and its biological diversity characteristics where belong to VPCS INTIONS peptides, and pyrimidine and its biological stress characteristics where belong to IDUQ INTIONS peptides.
最后通过推导公式归纳了下: V = U + Q, E = I + U, C = I + D, S = I + Q, I = !D, U = !Q
Then we find: V = U + Q, E = I + U, C = I + D, S = I + Q, I = !D, U = !Q
罗瑶光, 2020年10月25日 6:00 AM D8+ 我得到严谨的语义假设公式 推导论证结果:
Luo Yaoguang, October 25, 2020 6:00 AM D8+ got the rigorous semantic hypothesis formula deduction result:
A 分析 O 操作 P 处理 M 管理
V 感知 E 执行 C 控制(G 鸟嘌呤) S 静态(A 腺嘌呤)
I 增加(U 尿嘧啶) D 减少(C 胞嘧啶) U 改变 Q 查找(T 胸腺嘧啶)
A analysis O operation P process M management
V vitionary E execute C control(G Guanine initon) S static(A Adenine initon)
I increment(U uracil initon) D decrement(C cytosine initon) U update Q query(T thymine initon)
可以推断:(因为一开始作者没有定AOPM的名称方式,于是先统一高级元INITON用嘌呤名称)
A 分析(TA 变感腺嘌呤) O 操作(UA 增变腺嘌呤) P 处理(UG 增变鸟嘌呤) M 管理(GA 鸟腺嘌呤)
V 感知(T 变感嘌呤) E 执行(U 增变嘌呤) C 控制(G 鸟嘌呤) S 静态(A 腺嘌呤)
I 增加(U 尿嘧啶) D 减少(C 胞嘧啶) U 改变(变嘧啶) Q 感应(T 胸腺嘧啶)
Then proof:(in the first Mr.Yaoguang didn’t name the AOPM initons then using Purine initons(PI) instead.
A analysis(LTA -Adenine-PI) O operation(ULA -Adenine-PI) P process(UG －Guanine－PI) M management (GA－PI)
V vitionary(LT yaoguang-T-PI) E execute(UL -yaoguang-PI) C control(G Guanine initon) S static(A Adenine initon)
I increment(U uracil initon) D decrement(C cytosine initon) U update(L yaoguang initons) Q query(T thymine initon)
U 改变(变嘧啶) Named by Yaoguang.Luo 20201025
U UPDATE(L yaoguang initons) Named by Yaoguang.Luo 20201025
VIII DETA TVM PDC functions/ 德塔肽推导函数化
于是通过罗瑶光先生的认知思维与 模拟最简单的几个小词汇 组合, 有了这些小词汇, 于是开始降元推理, 进行统计观测, 作者开启了意识肽展公式推导体系如下:
书写: …OVQ.OEQ.MVQ.OSU…
物体: …AVQ.ASQ…
桌子: …OVQ.OEQ.MVQ.OSU…AVQ.ASQ…
教育: …AVQ.OEQ.PVU.PSU.MSU.MSQ…OVQ.OEQ.MVQ.OSU…
Mr.Luo monit the human words into PDW by using his real word cognitions, then begin to make a logic proof of PDE caculations.
HAND WRITE: …OVQ.OEQ.MVQ.OSU…
OBJECT: …AVQ.ASQ…
TABLE: _ …OVQ.OEQ.MVQ.OSU_ …AVQ.ASQ…
EDUCATION: …AVQ.OEQ.PVU.PSU.MSU.MSQ …OVQ.OEQ.MVQ.OSU…
IX DETA TVM PDC function optimization and PDE/ 德塔肽推导函数逻辑优化
于是开始这些组合的有理合理性演化推理. //SORT 20201025 19:47 AM D8+ 继续持续绝对专注论证肽增公式1.0 BY USING ENGLISH FOR - 4 BITS DIUQ WAY 通过已有逻辑公式
Proof !-> MASK, ~-> COMPS :
THEN WE FIND? 于是我们推导发现了一些新的肽展变换定律 (PDE SWAP NEW LAW: D = DD)
在如下公式中 符号解释 !-> 为反码, ~-> 为补码
Proof !-> MASK, ~-> COMPS :
V 感知 -> U + Q !-> QU ~-> QQ !-> UU ~-> UQ = V
E 执行 -> I + U !-> DQ ~-> DDD !-> III ~-> IIU = I + E (肽增/PDE INCREMENT)
C 控制 -> I + D !-> DI ~-> DU !-> IQ ~-> UDD = U + D (肽展/PDE) = U + D + D (肽增/PDE INCREMENT)
THEN WE FIND 我们发现 补码变换计算中间态生成两个公式 U = E, I = U
V vitionary -> U + Q !-> QU ~-> QQ !-> UU ~-> UQ = V
E execute -> I + U !-> DQ ~-> DDD !-> III ~-> IIU = I + E (肽增/PDINCREMENT)
C control -> I + D !-> DI ~-> DU !-> IQ ~-> UDD = U + D (肽展/PDE) = U + D + D (肽增/PDE INCREMENT)
THEN WE FIND two formulars in comp’s duration: U = E, I = U
第一种方法 饱和4元子肽展 /first way 4 bits proof
A = V + S = U + Q + I + Q = UQIQ !-> QUDU ~-> QUDQ !-> UQIU ~-> UQIQ = A
O = E + S = I + U + I + Q = IUIQ !-> DQDU ~-> DQDQ !-> IUIU ~-> IUIQ = O
P = E + C = I + U + I + D = IUID !-> DQDI ~-> DQDU !-> IUIQ ~-> IUIDD = P + D (肽增/PDE INCREMENT)
M = C + S = I + D + I + Q = IDIQ !-> DIDU ~-> DIDQ !-> IDIU ~-> IDIQ = M
第二种方法不饱和3元子肽展 /second way 3 bits proof
A = V + S = U + Q + I + Q = UQI !-> QUD ~-> QUI !-> UQD ~-> UQI = A
O = E + S = I + U + I + Q = IUQ !-> DQU ~-> DQQ !-> IUU ~-> IUQ = O
P = E + C = I + U + I + D = IUD !-> DQI ~-> DQU !-> IUQ ~-> IUDD = P + D (肽增/PDE INCREMENT)
M = C + S = I + D + I + Q = IDQ !-> DIU ~-> DIQ !-> IDU ~-> IDQ = M
结论, 看起来似乎是很好的方式 这里描述下为什么我会4bit 计算, 因为一开始用3bit也能很好的论证, 为了找到伪命题, 我思考, VECS如果进行增元倍增,最好是倍数4bit, 于是觉得有必要推导论证
In conclusion, it proofs 4bits discrete caculation is a better way. then Author makes an arrangement as below.the Author thought from VPCS to IDUQ is 2 bits, so that from AOPM to IDUQ may need 4 bit, will be better for the observation.
于是开始整理, 归纳为下面肽展公式.
Figure 11-1 见文件地址: https://github.com/yaoguangluo/Deta_Resource/blob/master/CN_DT_pdn_computing1_2_2.pdf
PDE MASK LAW/ 离散反码定理
I = D!
D = I!
U = Q!
Q = U!
PDE COMP’S LAW/ 离散补码定理
DD = ++Q
I = ++D
U = ++I
Q = ++U
PDE (肽减/PDE DECREMENT) LAW
C = D (肽减/PDE DECREMENT)
S = I (肽减/PDE DECREMENT)
S = Q (肽减/PDE DECREMENT)
PDE (肽增/PDE INCREMENT) LAW
D = DD (肽增/PDE INCREMENT)
U = E (肽增/PDE INCREMENT)
I = U (肽增/PDE INCREMENT)
E = I + E (肽增/PDE INCREMENT)
P = P + D (肽增/PDE INCREMENT)
C = U + D + D(肽增/PDE INCREMENT)
PDE (肽展/PDE) LAW
A = V + S (肽展/PDE)
A = U + Q + I (不饱和／错误肽展/UNSAFE PDE)
O = E + S (肽展/PDE)
O = I + U + Q (不饱和／错误肽展/UNSAFE PDE)
P = E + C (肽展/PDE)
P = I + U + D (不饱和／错误肽展/UNSAFE PDE)
M = C + S (肽展)
M = I + D + Q (不饱和／错误肽展/UNSAFE PDE)
V = U + Q (肽展/PDE)
E = I + U (肽展/PDE)
E = D + U (肽展/PDE)
C = I + D (肽展/PDE)
S = I + Q (肽展/PDE)
X DETA TVM PDE Logic/ 德塔肽推导函数逻辑优化成肽展公式化
于是发现了一些简单的推导公式 和 不饱和公式, 于是找到了很多东西 如 L变嘧啶
FLASH A NEW NAME 可以得到联想假设推断:
A 分析(LTA 变胸腺腺苷) O 操作(UCLA 尿胞变腺苷) P 处理(UCLG 尿胞变鸟苷) M 管理(GA 鸟腺苷)
V 感知(LT 变胸腺嘌呤) E 执行(UCL 尿胞变嘌呤) C 控制(G 鸟嘌呤) S 静态(A 腺嘌呤)
I 增加(U 尿嘧啶) D 减少(C 胞嘧啶) U 改变(L 变嘧啶) Q 感应(T 胸腺嘧啶)
U 改变(L 变嘧啶)定义为 L(L-Pyrimidine) the first char of luo YG and liang BY, Named by yaoguangluo 20201025 END 2020-10-25 21:30 PM, D8+, YAOGUANGLUO LIUYANG
A analysis(LTA -Glycoside) O operation(UCLA -Glycoside) P process(UCLG －Glycoside) M management (GA－Glycoside)
V vitionary(LT yaoguang-T-PI) E execute(UL -yaoguang-PI) C control(G Guanine initon) S static(A Adenine initon)
I increment(U uracil initon) D decrement(C cytosine initon) U update(L yaoguang initons) Q query(T thymine initon)
U update(L update-Pyrimidine)定义为 L(L-Pyrimidine) the first char of luo YG and liang BY, Named by yaoguangluo 20201025 END 2020-10-25 21:30 PM, D8+, YAOGUANGLUO LIUYANG
今天发现 A = U + Q + I (肽展) 与 O = I + U + Q (肽展) 出现逆对称 引起了我的注意 为了避免定义为误差变换, 于是现在我增加 4BIT LAW 演化如下,
Today find out that (paper time) A = U + Q + I (PDE) 与 O = I + U + Q (PDE) will cause a Direction Inverse Symmetry, Then makes more attension that increments 4 formulars of 4 bits PDE Law as below
A = U + Q + I + Q ,
O = I + U + I + Q ,
P = I + U + I + D ,
M = I + D + I + Q
XI DETA TVM PDE and its application/ 德塔肽展公式应用论证技术
于是想到文件加密, DNA, 有丝分裂等. 于是开始从文件加密上论证, 肽展函数模拟酸碱 控制 概率丝化 方式 S= I, S= Q, E= IU, E= DU… 等
TVM PDE and its application where not only could used in document encoding, DNA moniter, humanoid cognitions or other domains, and also for the probability real word issues by using PDE LAW. for example S= I, S= Q, E= IU, E= DU… etc.
FIGURE 12 见文件地址: https://github.com/yaoguangluo/Deta_Resource/blob/master/CN_DT_pdn_computing1_2_2.pdf
XII TVM humanoid life Research/ 应用在类人生命进化中
发现有重大价值后, 开始高级应用, 模拟新冠和永生等词汇推导
Moniter COVID-19 verbal AND Immortal life verbal
A 分析(LTA 变胸腺腺苷) O 操作(UCLA 尿胞变腺苷) P 处理(UCLG 尿胞变鸟苷) M 管理(GA 鸟腺苷)
V 感知(LT 变胸腺嘌呤) E 执行(UCL 尿胞变嘌呤) C 控制(G 鸟嘌呤) S 静态(A 腺嘌呤)
I 增加(U 尿嘧啶) D 减少(C 胞嘧啶) U 改变(L 变嘧啶) Q 感应(T 胸腺嘧啶)
A analysis(LTA -Glycoside)O operation(UCLA -Glycoside)P process(UCLG －Glycoside)M management (GA－Glycoside)
V vitionary(LT yaoguang-T-PI) E execute(UL -yaoguang-PI) C control(G Guanine initon) S static(A Adenine initon)
I increment(U uracil initon) D decrement(C cytosine initon) U update(L yaoguang initons) Q query(T thymine initon)
1 新冠语义解释模拟/Moniter COVID-19
…MSI.OCU.OCI.PCU.PCI… 罗瑶光按照人类的理解方式认为 管理静态增加, 操作控制增加处理控制增加
…MSI.OCU.OCI.PCU.PCI… in yaoguangluo’s cognitive way is manage set increment, operat control increment ,process control increment…
作者认为可以用在OSGI插件肽化上. /Author thought it could be used in A OSGI plug-in PDN way.
…GAAU.UCLAGL.UCLAGU.UCLGGL.UCLGGU…一种核酸抑制新冠苷糖
…鸟腺苷-腺嘌呤-尿嘧啶.尿胞变腺苷-鸟嘌呤-变嘧啶.尿胞变腺苷-鸟嘌呤-尿嘧啶.尿胞变鸟苷-鸟嘌呤-变嘧啶.尿胞变鸟苷-鸟嘌呤-尿嘧啶…
．．．Guanosine-adenine-uracil. Cytarabine-guanine-pyrimidine. Cytarabine-guanine-uracil. Cytidine-guanine-pyrimidine… . cytidine-guanine-uracil… PDN INITONS MONITER.
…MSI.OCU.OCI.PCU.PCI…
仅仅做不饱和分解聚合的肽展计算为:let’s proving by using Yaoguang’s PDE law
…M.S.I.O.C.U.O.C.I.P.C.U.P.C.I…
…CS.S.I.ES.C.U.ES.C.I.EC.C.U.EC.C.I…
1 E=IU
…CS.S.I.IUS.C.U.IUS.C.I.IUC.C.U.IUC.C.I…
1.1 S=I probability
…CI.I.I.IUI.C.U.IUI.C.I.IUC.C.U.IUC.C.I…
…C.I.I.I.I.U.I.C.U.I.U.I.C.I.I.U.C.C.U.I.U.C.C.I…
…I.D.I.I.I.I.U.I.I.D.U.I.U.I.I.D.I.I.U.I.D.I.D.U.I.U.I.D.I.D.I…
…C.I.I.I.E.I.I.E.I.U.I.C.I.E.C.I.E.E.C.C.I…
…C.I.I.I.E.I.I.E.I.U.I.C.I.P.I.E.P.C.I…
…CI.I.IE.I.IEI.UIC.IPI.EPC.I…
生成人体饮食难以形成的染色体 同元基 IEI IPI 物质 Initon语义翻译做用就是dna 执行钥匙
Could be extended into a PDE-initons where includs IEI(add an execute’s increment) IPI(add a processor’s increment), such like the execute key of DNA languages.
1.2 S=Q probability
…CQ.Q.I.IUQ.C.U.IUQ.C.I.IUC.C.U.IUC.C.I…
1.3 第一个S=I 第二个S=Q, 这是一个概率问题. 停止论证.之后可以设计成证书或者概率钥匙
Following the PDE formulars, we know s equals to i or q which is an unforeseeable probability issues, so stop, guess could build it into a probability key certificate for the software encryption conmmunications.
2 E=DU
…CS.S.I.DUS.C.U.DUS.C.I.DUC.C.U.DUC.C.I…
2.1 S=Q probability
…CQ.Q.I.DUQ.C.U.DUQ.C.I.DUC.C.U.DUC.C.I…
…I.D.Q.Q.I.D.U.Q.I.D.U.D.U.Q.I.D.I.D.U.I.D.I.D.U.D.U.I.D.I.D.I…
…I.D.Q.Q.I.D.U.Q.I.D.U.D.U.Q.I.D.I.E.C.I.E.E.C.C.I…
…C.Q.Q.C.V.I.E.D.V.I.D.I.E.C.I.E.E.C.C.I…
…CQQ.CVI.EDV.IDI.ECI.EEC.CI…
生成人体饮食难以形成的染色体EDV 执行胞嘧啶的查看增加, EEC .CI 同连元基 执行控制的增加钥匙.
Could be extended into a PDE-initons where includs EDV(executing the decrement’s vitionaries), EEC(executing the execute’s controller) and CI(control the increment) to find the free D initons, such likes the controller key of DNA languages.
2.2 如1.3/ 2.2 same with 1.3
实验推导证明: 补充均衡营养, 多运动, 多喝水, 远离脏乱环境( 因为脏乱的环境有增加不饱和肽展几率 ) 提高免疫力可以有效的预防新冠.
另外过程可模拟 酸碱化, 磁化等概率论 来控制 合成趋势. 作者准备在编码的非对称钥匙证书中广泛应用. Then proving: with in a sufficency nutritions, do more sports, drink more water and get away from the dirty environment( dirty environment will cause an unsaturated PDN extentions which bad for human heathy) where in order to raise up the body energy to avoid the COVID-19, the Authors thought this processing durations where could be controlled by Biology, magnition and probability domains. so let’s proving as below in a way of probability
论证人 罗瑶光 2020-10-28 23:17 PM D8+
…概率论证很多,这里不一一例举./etc
2 永生语义解释模拟/ The real world words of the Eternel initons about nuclease as below.
永生有关 核酸成分 …MCI.MSI.OSU.OSI.SDI…
罗瑶光按照人类的理解方式认为 管理控制增加, 管理静态增加,操作静态的 胞嘧啶增加可以补充核酸链的胞嘧啶. 作者同样认为可以用在OSGI函数插件过滤的肽化上.
Mr.yaoguangluo thought it could arrangment likes managing a controller’s increment, managing set’s increment, operate the static sets, operate to add the set and decrements …
-> …GAGU.GAAU.UCLAA.UCLAAU.LACU… , 一种核酸永生苷糖, 肿瘤增生苷糖
-> …鸟腺苷-鸟嘌呤-尿嘧啶.鸟腺苷-腺嘌呤-尿嘧啶.尿胞变腺苷-腺嘌呤-变嘧啶.尿胞变腺苷-腺嘌呤-尿嘧啶.腺嘌呤-胞嘧啶-尿嘧啶… 根据肽展公式1.2.2 分解为 为
-> …Guanosine-guanine-uracil. Guanosine-adenine-uracil. UCLA-Glycoside-adenine-L-pyrimidine.UCLA-Glycoside-adenine-URACIL… ADENINE-CYTOSINE-URACIL…
=…MCI.MSI.OSU.OSI.SDI…
=…IDQ-ID-I.IDQ-IQ-I.IUQ-IQ-U.IUQ-IQ-I.IQ-D-I…
=…I.D.Q.I.D.I.I.D.Q.I.Q.I.I.U.Q.I.Q.U.I.U.Q.I.Q.I.I.Q.D.I… 根据肽增公式1.2.2 聚合为/ PDN conbination
=…C.Q.C.I.C.Q.S.I.I.U.Q.S.U.I.U.Q.S.I.S.D.I…
=…C.Q.C.I.C.Q.S.I.P.S.U.P.S.I.S.D.I…
=…CQ.CI.CQ.SI.PSU.PSI.SDI… 完美变换过程 全程透明
论证结果:永生苷糖, 肿瘤增生苷糖核酸成分 可以转换为 控制执行 静态胞嘧啶增加 (SDI) 论证人: 罗瑶光 2020-10-27 11:37 AM
It proofs eternal initons and Tumor Hyperplasia initons could swap into CP(control the process) to let the static decrements incremented. where means SDI, yaoguangluo, 2020-10-27 11:37 AM.
A 分析(LTA 变胸腺腺苷) O 操作(UCLA 尿胞变腺苷) P 处理(UCLG 尿胞变鸟苷) M 管理(GA 鸟腺苷)
V 感知(LT 变胸腺嘌呤) E 执行(UCL 尿胞变嘌呤) C 控制(G 鸟嘌呤) S 静态(A 腺嘌呤)
I 增加(U 尿嘧啶) D 减少(C 胞嘧啶) U 改变(L 变嘧啶) Q 感应(T 胸腺嘧啶)
A analysis(LTA -Glycoside)O operation(UCLA -Glycoside)P process(UCLG －Glycoside)M management (GA－Glycoside)
V vitionary(LT yaoguang-T-PI) E execute(UL -yaoguang-PI) C control(G Guanine initon) S static(A Adenine initon)
I increment(U uracil initon) D decrement(C cytosine initon) U update(L yaoguang initons) Q query(T thymine initon)
//same delete… //… //…
then 2 = …CS-ID-I.CS-IQ-I.ES-IQ-U.ES-IQ-I.IQ-D-I…
then E= DU =2 …CS-ID-I.CS-IQ-I.DUS-IQ-U.DUS-IQ-I.IQ-D-I…
then S= IQ =2.1 …IDIQ-ID-I.IDIQ-IQ-I.DUIQ-IQ-U.DUIQ-IQ-I.IQ-D-I… =略.
then S= I =2.2 …IDI-ID-I.IDI-IQ-I.DUI-IQ-U.DUI-IQ-I.IQ-D-I…
= 2.2 …I.D.I.I.D.I.I.D.I.I.Q.I.D.U.I.I.Q.U.D.U.I.I.Q.I.I.Q.D.I…
= 2.2 …ID.I.ID.I.ID.I.IQ.ID.U.I.IQ.U.D.U.I.IQ.I.IQ.D.I…
= 2.2 …C.I.C.I.C.I.S.C.U.I.S.U.D.U.I.S.I.S.D.I…
= 2.2 …CI.CI.CIS.CUI.SUD.UIS.ISD.I…
= ISD 增加静态删除, I代谢/ add a static set’s decrement.
分解S= Q =2.3 …IDQ-ID-I.IDQ-IQ-I.DUQ-IQ-U.DUQ-IQ-I.IQ-D-I…
= 2.3 …I.D.Q.I.D.I.I.D.Q.I.Q.I.D.U.Q.I.Q.U.D.U.Q.I.Q.I.I.Q.D.I…
= 2.3 …ID.Q.ID.I.ID.Q.IQ.ID.UQ.IQ.U.D.UQ.IQ.I.IQ.D.I…
= 2.3 …C.Q.C.I.C.Q.S.C.V.S.U.D.V.S.I.S.D.I…
= 2.3 …C.Q.C.I.C.Q.S.C.VS.U.D.VS.I.S.D.I…
= 2.3 …C.Q.C.I.C.Q.S.C.A.U.D.A.I.S.D.I…
= 2.3 …CQ.CI.CQ.SCA.UDA.ISD.I…
= SCA UDA 变胸腺腺苷代谢,ISD生成静态嘧胞啶, I代谢 根据肽增公式1.2.2 聚合为 完美变换过程 全程透明
= SCA(Static controller’s analysis) UDA( update the decrement’s analysis) mean check the D initons and I.SD.I(ADD MORE STATIC DECREMENTS-cytosine initon)
论证结果:永生苷糖, 肿瘤增生苷糖核酸成分 可以转换为 变嘧啶控制执行 静态胞嘧啶增加 (SDI)
It proof Eternal initons word could update the decrement’s analysis how many D-initons need be incremented.
论证人: 罗瑶光 2020-10-27 11:37 AM 过程可 酸碱 化 控制 合成趋势.
Yaoguang 2020-10-27 11:37 AM this trending durations could be controlled by the ratio of ACID or Alkali.
XIII Eternal Research/ 应用在类人生命永生探索领域
于是找到了很多 新东西, 如 核酸 执行钥匙 …IEI.IPI.EPC.I … 应用如
永生之匙类 族重要肽丝 激素注射液 1.0
…CI.I.IE.I.IEI.UIC.IPI.EPC.I…IEI.IPI.EPC.I. DNA control absorb E KEY
…CI.CI.CI.SI.EI.SU.EI.SI.SDI…IEI.IPI.EPC.I… DNA execute absorb E KEY
…CQ.CI.CQ.SI.IAU.IA.ISI.D…IEI.IPI.EPC.I… => 同元基 增补 钥匙
…IAI.IOI.IPI.IMI…IEI.IPI.EPC.I…
…IVI.IEI.ICI.ISI…IEI.IPI.EPC.I…
…CQQ.CVI…EVV.IDI.ECI.EEC.CI… DNA check V KEY
…CQQ.CPI…EPV.IDI.ECI.EEC.CI… DNA check P/E(VPCS-VECS) KEY
…CQQ.CCI…ECV.IDI.ECI.EEC.CI… DNA check C KEY
…CQQ.CSI…ESV.IDI.ECI.EEC.CI… DNA check S KEY
=> 罗瑶光于2020-10-20 命名为 <大同连元基鸟胸腺苷肽丝碱 1.1> 永生活性钥匙组合 如下:
…CQQ.CEI.EEV.IDI…ECI.EEC.CI… DNA check E KEY
…CII.IEI.IEI.UIC.IPI.EPC.I…IEI.IPI.EPC.I… DNA control absorb E KEY
…CIC.ICI.SIE.ISU.EIS.ISD.I…IEI.IPI.EPC.I… DNA execute absorb E KEY
…CQQ.CVI.EVV.IDI…ECI.EEC.CI… DNA check V KEY
…CII.IVI.IVI.UIC.IPI.EPC.I…IEI.IPI.EPC.I… DNA control absorb V KEY
…CIC.ICI.SIE.ISU.EIS.ISD.I…IEI.IPI.EPC.I… DNA execute absorb V KEY
…CQQ.COI.EOV.IDI…ECI.EEC.CI… DNA check O KEY
…CII.IOI.IOI.UIC.IPI.EPC.I…IEI.IPI.EPC.I… DNA control absorb O KEY
…CIC.ICI.SIE.ISU.EIS.ISD.I…IEI.IPI.EPC.I… DNA execute absorb O KEY
…CQQ.CMI.EMV.IDI…ECI.EEC.CI… DNA check M KEY
…CII.IMI.IMI.UIC.IPI.EPC.I…IEI.IPI.EPC.I… DNA control absorb M KEY
…CIC.ICI.SIE.ISU.EIS.ISD.I…IEI.IPI.EPC.I… DNA execute absorb M KEY
…CQQ.CPI.EPV.IDI…ECI.EEC.CI… DNA check P KEY
…CII.IPI.IPI.UIC.IPI.EPC.I…IEI.IPI.EPC.I… DNA control absorb P KEY
…CIC.ICI.SIE.ISU.EIS.ISD.I…IEI.IPI.EPC.I… DNA execute absorb P KEY
警告!!
1 禁止科学家 实验取材于 智慧生物. 必将 受到 所在国和联合国的 相关法律制裁 !
2 作者提出警示 这类物质含有癌变, 肿瘤增生等功能, 呼吁禁止在生物(特别是有智慧的生物)上尝试研究…
3 现在的纳米技术人工可以低廉合成. 这些成分在植物中都普遍存在,不要用为伪科学方法提炼.
4 由于医学人员没有变嘧啶，不要在生物(特别是有智慧的生物)上尝试研究…
FATAR WARNNING!!!
1 Dangrous! Under The National Law in Biology!
2 Unsafe! Will Cause The Tumor Growth or Canceration.
3 Reasearching Must Under The Sufficency and Sciency Logic Proofs.
4 Forbidden the research with the object of Bio-humanoid-intellgence. Because the U(L-pyrimidine INITONS) is unforeseeably.
XIV Not the End/ 似乎刚刚开始…
FIGURE 13 见文件地址: https://github.com/yaoguangluo/Deta_Resource/blob/master/CN_DT_pdn_computing1_2_2.pdf
人类要做的事情太多了…如图13, 养疗经繁衍以后肯定会遇到这个问题. 是一个课题.
这篇文章通过大量的模拟论证和概率丝化推导, 作者得到具体论证结果:
1 软件具备生命肽化特征. 可以实现软件的进化.
2 增删改查中改 L-变嘧啶(L-Pyrimidine) 的存在性 如 I = U. 在很多语义肽化计算中起到基础催化算子计算的作用
3 AOPM VECS IDUQ肽展公式Figure 11-1完整的推导过程具备离散数学严谨性.
4 DNA 的编码方式和生命词库可以实现非对称加密. 并可以进行概率化钥匙生成.
5 人类历史首次论证 DNA的执行钥匙是一种同连元基(…CII… … …IEI.IPI.EPC.I…)… 肽丝组合.
6 世界首个象契文字典DNA initon生命字典 具有巨大应用价值.
7 TVM做为函数的肽化虚拟机可以进行 肽文和代码间的自由变换. 也为下一步肽函数执行逻辑做铺垫.
8 人类历史首次发现 肽展公式 确定DNA的唯一进化方式, 途径执行方式.
还有很多启发点 因为科学的严谨性, 没有丰富的持续论证, 所以没有一一在此列举.
SEE FIGURE 13, THE Inherit Way of YANGLIAOJING will cause a lot of problems, need proving.
in conclution about this article, the Author did alot proofs as below:
1 Yaoguangluo proofs Software could be a Life. definitly Software could born a Life.
2 Yaoguangluo proofs out the L-Pyrimidine initon and swap formular: I = U. in data increment, decrement, update and query, which is very usful in the data catalytic caculations.
3 Yaoguangluo proofs AOPM VECS IDUQ PDE Law see at Figure 11-1 is very usful in the DNA data encoding.
4 Yaoguangluo proofs AOPM VECS IDUQ PDE Law could use in the data Asymmertry cryption. and intion key store Certs.
5 Yaoguangluo proofs (…CII… … …IEI.IPI.EPC.I…)… is a format PDE key
6 Yaoguangluo named the world first hieroglyph-sphenogram dictionary DNA initon PDW.
7 Yaoguangluo named TVM where do a swap between programming file and PDN file.
8 Yaoguangluo find out the world first PDE Formular List, where can translate the humanoid cognitive words into DNA PDN encoding.
ETC…
XV Refer/ 引用
- 非对称加密, https://baike.sogou.com/v7480386.htm?fromTitle=%E9%9D%9E%E5%AF%B9%E7%A7%B0%E5%8A%A0%E5%AF%86
- 嘧啶, https://baike.sogou.com/v5478759.htm?fromTitle=%E5%98%A7%E5%95%B6
- 嘌呤, https://baike.sogou.com/v5478759.htm?fromTitle=嘌呤
- 苷, https://baike.sogou.com/v3272184.htm?fromTitle=%E8%8B%B7
- 新冠, https://baike.sogou.com/v184764825.htm?fromTitle=%E6%96%B0%E5%86%A0%E7%97%85%E6%AF%92
- Github VPCS, YAOGUANG. Luo, https://github.com/yaoguangluo/Deta_Resource/blob/master/VPCS-Method_V1.1.pdf, last accessed 2020/10/23.
6.1 Gitee, https://gitee.com/DetaChina/Deta_Resource/blob/master/VPCS-Method_V1.1.pdf - Github AOPM, https://github.com/YAOGUANGluo/DETA_Resource/blob/master/AOPM[10]%20System%20On%20VPCS.pdf, last accessed 2020/10/23.
7.1. Gitee, https://gitee.com/DetaChina/Deta_Resource/blob/master/AOPM%20System%20On%20VPCS.pdf - 象契文字, 象形的明确意识 加 契形的格式符号.
8.1. 象形文字, https://baike.sogou.com/v74567.htm?fromTitle=%E8%B1%A1%E5%BD%A2%E6%96%87%E5%AD%97
8.2. 契形文字, https://baike.sogou.com/v416426.htm?fromTitle=楔形文字
9 YAOGUANG LUO, DETA ETL, National Copyright Administration of China, CN4240558, (2019). - YANGLIAOJING, http://tinos.qicp.vip/DETA_HUARUIJI[12].html, last accessed 2020/10/23.
- DNA, https://baike.baidu.com/item/%E8%84%B1%E6%B0%A7%E6%A0%B8%E7%B3%96%E6%A0%B8%E9%85%B8/78250?fromtitle =DNA[14]&fromid=98123&fr=aladdin, last accessed 2020/10/23.
- UNICORN AI, https://github.com/YAOGUANGluo/ETL_Unicorn, last accessed 2020/10/23.
- PDN LINK, https://baike.baidu.com/item/%E8%82%BD%E9%93%BE/8625112?fr=aladdin, last accessed 2020/10/23.
- Yaoguangluo, Rongwuluo, The INITONS Catalytic Reflection Between Humanoid DNA and Nero Cell 1.2.2, CN2020Z11L0333706’
github, https://github.com/yaoguangluo/Deta_Resource/blob/master/DNA%20%E7%BC%96%E7%A0%81%E6%96%B9%E5%BC%8F1.2.2%20%E4%B8%AD%E8%AF%91%E8%8B%B1%E6%B7%B7%E5%90%88%E7%89%88.pdf
gitee, https://gitee.com/DetaChina/collection-of-papers-by-deta/blob/master/DNA%20%E7%BC%96%E7%A0%81%E6%96%B9%E5%BC%8F1.2.2%20%E4%B8%AD%E8%AF%91%E8%8B%B1%E6%B7%B7%E5%90%88%E7%89%88.pdf
Thanks
感谢父亲在医学上提供了许多可借鉴的研究思维经验, 比如医学的严谨性和可扩展性, 为DNA非对称方法模拟丰富了作者的联想, 因为这篇文章主要是离散数学公式推导论证, 于是署名为独立作者, 在此感谢. 感谢 md 格式 规范, 方便我美观编辑.
罗瑶光 浏阳 准备翻译英文版本前规范化文章.
2020-10-30 已向华夏 知识产权提交个人著作中文版本申请: 文件地址: https://github.com/yaoguangluo/Deta_Resource/blob/master/CN_DT_pdn_computing1_2_2.pdf
发布受干扰, 20201102报警, 国家公安备案 按git 时间戳 增量模式 确定的 保留的 中英 混合版本(肽展定理的推导过程一字不变):
https://gitee.com/DetaChina/collection-of-papers-by-deta/blob/master/著作权版本PDE_Formular_1_2_2.pdf
https://github.com/yaoguangluo/Deta_Resource/blob/master/著作权版本PDE_Formular_1_2_2.pdf ()
新增疑问２０２０－１０－３１：
罗瑶光．浏阳
