Automatic Sequencing Research Articles

Role of the basal ganglia in innate and learned behavioural sequences.

Integrating individual actions into coherent, organised behavioural units, a process called chunking, is a fundamental, evolutionarily conserved process that renders actions automatic. In vertebrates, evidence points to the basal ganglia- a complex network believed to be involved in action selection- as a key component of action sequence encoding, although the underlying mechanisms are only just beginning to be understood. Central pattern generators control many innate automatic behavioural sequences that form some of the most basic behaviours in an animal's repertoire, and in vertebrates, brainstem and spinal pattern generators are under the control of higher order structures such as the basal ganglia. Evidence suggests that the basal ganglia play a crucial role in the concatenation of simpler behaviours into more complex chunks, in the context of innate behavioural sequences such as chain grooming in rats, as well as sequences in which innate capabilities and learning interact such as birdsong, and sequences that are learned from scratch, such as lever press sequences in operant behaviour. It has been proposed that the role of the striatum, the largest input structure of the basal ganglia, might lie in selecting and allowing the relevant central pattern generators to gain access to the motor system in the correct order, while inhibiting other behaviours. As behaviours become more complex and flexible, the pattern generators seem to become more dependent on descending signals. Indeed, during learning, the striatum itself may adopt the functional characteristics of a higher order pattern generator, facilitated at the microcircuit level by striatal neuropeptides.

Algebraic Automatic Continued Fractions in Characteristic 2

Abstract We present two families of automatic sequences that define algebraic continued fractions in characteristic $2$. The period-doubling sequence belongs to the first family $\mathcal {P}$, and its sum modulo $2$, the Thue–Morse sequence, belongs to the second family $\mathcal {G}$. The family $\mathcal {G}$ contains all the iterated sums of sequences from the $\mathcal {P}$ and more.

Metadata-independent classification of MRI sequences using convolutional neural networks: Successful application to prostate MRI

PurposeThe ever-increasing volume of medical imaging data and interest in Big Data research brings challenges to data organization, categorization, and retrieval. Although the radiological value chain is almost entirely digital, data structuring has been widely performed pragmatically, but with insufficient naming and metadata standards for the stringent needs of image analysis. To enable automated data management independent of naming and metadata, this study focused on developing a convolutional neural network (CNN) that classifies medical images based solely on voxel data. MethodA 3D CNN (3D-ResNet18) was trained using a dataset of 31,602 prostate MRI volumes with 10 different sequence types of 1243 patients. A five-fold cross-validation approach with patient-based splits was chosen for training and testing. Training was repeated with a gradual reduction in training data assessing classification accuracies to determine the minimum training data required for sufficient performance. The trained model and developed method were tested on three external datasets. ResultsThe model achieved an overall accuracy of 99.88 % ± 0.13 % in classifying typical prostate MRI sequence types. When being trained with approximately 10 % of the original cohort (112 patients), the CNN still achieved an accuracy of 97.43 % ± 2.10 %. In external testing the model achieved sensitivities of > 90 % for 10/15 tested sequence types. ConclusionsThe herein developed CNN enabled automatic and reliable sequence identification in prostate MRI. Ultimately, such CNN models for voxel-based sequence identification could substantially enhance the management of medical imaging data, improve workflow efficiency and data quality, and allow for robust clinical AI workflows.

First Report of Bidens Mottle Virus Causing Mild mottle and Leaf Distortion in Stachytarpheta jamaicensis in Taiwan.

Stachytarpheta jamaicensis, a traditional herbal pharmacological plant in the Family Verbenaceae that produces purplish-blue flowers, is mainly used as a garden plant in tropical and subtropical areas, including Taiwan. A begomovirus, stachytarpheta leaf curl virus (StaLCV) that caused disease on S. jamaicensis, has been reported (Xiong et al. 2005). In 2021, five symptomatic plants with mild mottle and leaf distortion (Fig. S1A, B) and three asymptomatic plants were collected in Taichung City, Taiwan. Polymerase chain reaction (PCR) and reverse transcription (RT)-PCR assays using degenerate primer pairs with expected amplicon sizes of 1.2-1.3 kb (PAL1v1978/PAR1c715; Rojas et al. 1993), 312 bp (dTospo-F2/dTospo-R2; Huang et al. 2018), and 600-750 kb (Hrp5/Pot1; Chen et al. 2006, Colinet and Kummert 1993) for Begomovirus, Orthotospovirus, and Potyvirus, respectively were performed using total DNA and total RNA plant extracts. Results showed the expected fragments were only amplified from the 5 symptomatic plants using Potyvirus degenerate primers. Three out of five randomly picked amplicons, coding the 3'-end of nuclear inclusion b protein (NIb) and 5'-end coat protein (CP) genes, were cloned and sequenced with the ABI3730 automatic sequencer (Applied Biosystems, Hammonton, NJ, USA) in Biotechnology Centre DNA-sequencing facility at National Chung Hsing University (NCHU). After NCBI BLASTN analysis, the sequences were shown to be most closely related to bidens mottle virus (BiMoV). The nucleotide sequence identities analyzed using the CLUSTAL W Methods of MegAlign program (DNASTAR, Inc., Madison, WI, USA), showed the three amplicons shared 95.8-99.8% to each other and 94.3-97.1% with 18 BiMoV isolates available in NCBI GenBank. Further RT-PCR with a specific primer (FJJ2021-278) designed from the CP of previously amplified amplicons, paired with oligo d(T) primer, were used for amplification of the 3'-CP gene and 3'-untranslated region (UTR) from total RNAs purified from symptomatic plants. The full-length CPs (804-nt and 268-aa) of the BiMoV isolates described here (Acc. Nos. OM406329 and OM406330; designated as isolate Stachy3 and Stachy7, respectively) shared 96.5-98.5% nucleotide and 97.8-99.3% amino acid identity to other BiMoV isolates. The isolate used for back-inoculation to S. jamaicensis was selected after the completion of triple single chlorotic local lesion isolation in Chenopodium quinoa. Two mechanically-inoculated S. jamaicensis plants exhibited symptoms 14-16 days post-inoculation similar to those observed in field plants and tested positive in RT-PCR using BiMoV-specific primers. In transmission electron microscopy, crude sap extracted from mechanically-inoculated C. quinoa and stained with uranyl acetate (UA) revealed flexuous filamentous virions of approximately 720 × 12 nm (Fig. S1C). A western blot assay using BiMoV antiserum (Chen and Lee 2012) revealed bands of about 34 KDa only from the mechanically-inoculated C. quinoa and the five symptomatic S. jamaicensis plants collected from the field. Taken together, we believe this is the first report of BiMoV infecting and causing mild chlorotic mottle and leaf distortion on S. jamaicensis. S. jamaicensis may serve as a new alternative host of BiMoV that can spread the disease, and consequently may directly impact the producers of horticultural or economical crops, such as lettuce, calendula, sunflower, lisianthus, and garland chrysanthemum in Taiwan.

Digitalization of Accounting: Implementation Features and Efficiency Assessment

The digitalization of accounting processes offers significant benefits, including increased efficiency and reduced errors in accounting data. However, the successful implementation of new and modernization of existing computer programs in the accounting system requires consideration of cost, technical, professional, and managerial factors. This study aims to provide a comprehensive analysis of qualitative and quantitative parameters that can form the basis for making decisions on the integration of automated accounting data processing, robotic process automation, artificial intelligence, blockchain, or their combinations into existing systems for the full digitalization of accounting. The integration of software robots and artificial intelligence into accounting systems offers various benefits related to the creation of a non-standard environment where the generation, transfer, and exchange of traditional accounting information is accelerated and improved through the integration of data from other management systems and databases. These improvements contribute to the efficiency and reliability of the automated accounting system. The introduction of software components such as robotic process automation and artificial intelligence helps to free accounting staff from the routine of repetitive operations and ensures automatic prioritization and sequencing of accounting registration in the digital space. Integration of bots into an automated accounting system also facilitates document sharing and provides remote automated monitoring. This increases interaction between departments and improves control over operations that require additional attention from managers.To assess the effectiveness of such software solutions, the authors critically evaluate existing approaches to determining the qualitative indicators that are expected to be obtained after the introduction of software innovations and propose to supplement the performance criteria with quantitative indicators, among which are the time-saving ratio in document processing, the error rate and the resource-saving ratio. In conclusion, this study substantiates the need to consider quantitative parameters and coefficients that can be used to assess the effectiveness of implementing software solutions in automated accounting systems for the digitalization of financial information. The results emphasize the need for a holistic approach to assessing the effectiveness, reliability, and security of these solutions. Improved technical knowledge and training of accounting professionals in security assessment are crucial for the successful implementation and use of digitalization of accounting systems.

THE PREVALENCE OF INTEGRON CLASS I AND II AMONG MULTI-DRUG RESISTANCE PRODUCING KLEBSIELLA pneumonia

This study aimed to determine antibiotic resistance profiles and the distribution of Integron I, Integron II, and genes among uropathogenic Klebsiella pneumoniae isolated from patients suffering from urinary tract infection. The results revealed that one hundred and thirty-seven (91%) out of 150 clinical specimens were Klebsiella pneumoniae. The isolates (137 isolates) were given a higher percentage of resistance against Piperacillin (94.89%)and Rifampicin (93.43%) and the lowest resistance was with Meropenem (40.87%). According to PCR amplification for 15 isolates showed the proportion of class I (intl1) and class II (intl2) integrons were investigated. What are 100% (n=15) and 45% (n=7) of isolates had intl1 and intl2 genes, respectively. PCR products for (Five)isolates were subjected to direct sequencing, and both strands of PCR products were sequenced with an automatic sequencer. These sequences were analyzed for the presence of variance of these genes and the detection of the differences in the nucleotides.

THE PREVALENCE OF INTEGRON CLASS I AND II AMONG MULTI-DRUG RESISTANCE PRODUCING KLEBSIELLA pneumonia

This study aimed to determine antibiotic resistance profiles and the distribution of Integron I, Integron II, and genes among uropathogenic Klebsiella pneumoniae isolated from patients suffering from urinary tract infection. The results revealed that one hundred and thirty-seven (91%) out of 150 clinical specimens were Klebsiella pneumoniae. The isolates (137 isolates) were given a higher percentage of resistance against Piperacillin (94.89%)and Rifampicin (93.43%) and the lowest resistance was with Meropenem (40.87%). According to PCR amplification for 15 isolates showed the proportion of class I (intl1) and class II (intl2) integrons were investigated. What are 100% (n=15) and 45% (n=7) of isolates had intl1 and intl2 genes, respectively. PCR products for (Five)isolates were subjected to direct sequencing, and both strands of PCR products were sequenced with an automatic sequencer. These sequences were analyzed for the presence of variance of these genes and the detection of the differences in the nucleotides.

Criteria for prioritizing selection of Mexican maize landrace accessions for conservation in situ or ex situ based on phylogenetic analysis

IntroductionA combination of factors including migration, climate change and the encroachment of growing cities are associated with the extinction of species and a reduction in biodiversity. In Mexico maize landraces are an important source of germplasm that could be invaluable for future breeding programs in response a changing environment. Efforts to develop conservation strategies are hampered by the costs of housing and maintaining large germplasm collections. Effective criteria are therefore needed to identify rare genotypes that are in danger of being lost and to define minimal cost-effective core collections.MethodsA large-scale genotyping analysis of Mexican maize landraces was carried out using 14 SSR markers spread across the 10 maize chromosomes. DNA was extracted from 30 individual plants of each accession and 3 bulks containing 220ng of DNA from each of 10 individual plants were prepared. Amplification reactions were carried out individually on each bulk sample and SSRs were detected using an automatic sequencer. Binary scores were used to produce phylogenies and a rareness index Ri was developed to identify a minimal collection of accessions.ResultsA total of 40,140 individual plants from accessions obtained in 14 different Mexican states and covering 47 maize races were analyzed. Accessions from Northern and Central-Southern states could be distinguished based on genotype and accessions from Michoacán state were found to be distinct to all other accessions. A minimal collection of 56 accessions that covered all identified alleles and included rare allele combinations was determined.DiscussionThe strategy employed successfully distinguished accessions from different regions of Mexico and identified rare germplasm and offers a cost effective method to determine minimal germplasm collections for conservation in situ or ex situ. The strategy could easily be adapted for use in other native crop species such as common bean, chili pepper and tomato among others.

Digital microfluidics-engaged automated enzymatic degradation and synthesis of oligosaccharides.

Glycans are an important group of natural biopolymers, which not only play the role of a major biological energy resource but also as signaling molecules. As a result, structural characterization or sequencing of glycans, as well as targeted synthesis of glycans, is of great interest for understanding their structure-function relationship. However, this generally involves tedious manual operations and high reagent consumptions, which are the main technical bottlenecks retarding the advances of both automatic glycan sequencing and synthesis. Until now, automated enzymatic glycan sequencers or synthesizers are still not available on the market. In this study, to promote the development of automation in glycan sequencing or synthesis, first, programmed degradation and synthesis of glycans catalyzed by enzymes were successfully conducted on a digital microfluidic (DMF) device by using microdroplets as microreactors. In order to develop automatic glycan synthesizers and sequencers, a strategy integrating enzymatic oligosaccharide degradation or synthesis and magnetic manipulation to realize the separation and purification process after enzymatic reactions was designed and performed on DMF. An automatic process for enzymatic degradation of tetra-N-acetyl chitotetraose was achieved. Furthermore, the two-step enzymatic synthesis of lacto-N-tetraose was successfully and efficiently completed on the DMF platform. This work demonstrated here would open the door to further develop automatic enzymatic glycan synthesizers or sequencers based on DMF.

Tourism composite spatial indicators through variography and geographically weighted principal components analysis

AbstractThe definition of an index to synthesize the tourism appeal of a holiday destination is complex due to the effect of different aspects, such as the economic, socio-demographic, cultural, geographical ones regarding both demand and supply-side. In this paper, several spatially-referenced factors, related to the tourism attractiveness, are analyzed through the geographically weighted principal components analysis (GWPCA). However, the automatic setting of its kernel bandwidth, often used in practice, provides sometimes a not satisfactory result, since it is too small, with possible abrupt variation in the spatial domain, or too large, disregarding the spatial dependence. For this reason, a new approach, based on variography and minimum spatial correlation distance characterizing the covariates, is proposed for the GWPCA. A comparison with respect to the outputs of the GWPCA, based on automatic fitting, is discussed. Moreover, tourism composite spatial indicators are developed in order to support the policy makers in planning possible actions to boost tourism over the region of interest.

An automatic purse-seine set type classification algorithm to inform tropical tuna management

Management of large-scale tuna purse-seine fisheries often involves consideration of set type because the different set types yield different target species and bycatch species compositions, and may therefore impact those populations differently. Using the ensemble method random forests for classification, annual set type classification algorithms were developed based on a suite of operational characteristics, and catch and bycatch information, collected by onboard observers for the tropical tuna purse-seine fishery in the eastern Pacific Ocean (EPO) during 2010–2019. Two types of algorithms were built for each year: 1) a 2-class algorithm for sets on unassociated tuna schools (NOA) and sets on floating-object-associated tuna (OBJ); and, 2) a 3-class algorithm for all three types of sets that occur in the EPO, which includes sets on marine mammal-associated tuna (DEL). Results indicated that such data can be used to reliably distinguish between purse-seine sets types, highlighting inherent operational and ecological differences among them in the EPO. For the 2-class algorithms, the average misclassification error rates were 3.3% for NOA sets and 4.5% for OBJ sets. For the 3-class algorithms, the average misclassification error rates were 2% for DEL sets, 10.6% for NOA sets and 4.6% for OBJ sets. Comparison of results for NOA sets from the 2-class and 3-class algorithms suggests that the higher NOA-set misclassification error rate for the 3-class algorithm is due to a difficulty in distinguishing NOA sets from DEL sets with the predictors used in this analysis. The most useful bycatch information for predicting set type included amounts of dorado, wahoo, small fish species, such as triggerfishes, and silky sharks, illustrating the importance of bycatch data collection by observers, even for species of no commercial value. In the case of the 2-class algorithms, the annual misclassification error rates for NOA and OBJ sets were not only small, but also fairly stable over the 10-year period, even in the presence of the strong 2015 – 2016 El Niño event. This suggests that the methodology is robust and could be used to validate set type determinations based on other criteria, such as distance to a floating object (or a fish aggregating device), and to verify data quality, more generally.

On Structured Random Matrices Defined by Matrix Substitutions

The structure of the random matrices introduced in this work is given by deterministic matrices—the skeletons of the random matrices—built with an algorithm of matrix substitutions with entries in a finite field of integers modulo some prime number, akin to the algorithm of one dimensional automatic sequences. A random matrix has the structure of a given skeleton if to the same number of an entry of the skeleton, in the finite field, it corresponds a random variable having, at least, as its expected value the correspondent value of the number in the finite field. Affine matrix substitutions are introduced and fixed point theorems are proven that allow the consideration of steady states of the structure which are essential for an efficient observation. For some more restricted classes of structured random matrices the parameter estimation of the entries is addressed, as well as the convergence in law and also some aspects of the spectral analysis of the random operators associated with the random matrix. Finally, aiming at possible applications, it is shown that there is a procedure to associate a canonical random surface to every random structured matrix of a certain class.

An Improved Technique for Genotyping the ABCB1 Gene Variant of Exon 21.

The Multidrug Resistance protein (ABCB1, MDR1) is involved in the transport of xenobiotics and antiretroviral drugs. Some variants of the ABCB1 gene are of clinical importance; among them, exon 12 (c.1236C>T, rs1128503), 21 (c.2677G>T/A, rs2032582), and 26 (c.3435C>T, rs1045642) have a high incidence in Caucasians. Several protocols have been used for genotyping the exon 21 variants, such as allele-specific PCR-RFLP using adapted primer to generate a digestion site for several enzymes and automatic sequencing to detect the SNVs, TaqMan Allele Discrimination assay and High-Resolution Melter analysis (HRMA). The aim was to describe a new approach to genotype the three variants c.2677G>T/A for the exon 21 doing only one PCR with the corresponding primers and the digestion of the PCR product with two restriction enzymes: BrsI to identify A allele and BseYI to differentiate between G or T. An improvement of this methodology was also described. The proposal technique here described is demonstrated to be very efficient, easy, fast, reproducible, and cost-effective.

Coronary Computed Tomography Angiography with Deep Learning Image Reconstruction: A Preliminary Study to Evaluate Radiation Exposure Reduction.

Coronary computed tomography angiography (CCTA) is a medical imaging technique that produces detailed images of the coronary arteries. Our work focuses on the optimization of the prospectively ECG-triggered scan technique, which delivers the radiation efficiently only during a fraction of the R-R interval, matching the aim of reducing radiation dose in this increasingly used radiological examination. In this work, we analyzed how the median DLP (Dose-Length Product) values for CCTA of our Center decreased significantly in recent times mainly due to a notable change in the technology used. We passed from a median DLP value of 1158 mGy·cm to 221 mGy·cm for the whole exam and from a value of 1140 mGy·cm to 204 mGy·cm if considering CCTA scanning only. The result was obtained through the association of important factors during the dose imaging optimization: technological improvement, acquisition technique, and image reconstruction algorithm intervention. The combination of these three factors allows us to perform a faster and more accurate prospective CCTA with a lower radiation dose. Our future aim is to tune the image quality through a detectability-based study, combining algorithm strength with automatic dose settings.

Intelligent Island detection method of DC microgrid based on Adaboost algorithm

Aiming at the problems of large detection blind areas and difficult threshold settings in traditional passive islanding detection methods, this paper proposes an intelligent passive islanding detection method based on the adaptive boosting (Adaboost) algorithm. This method first uses feature screening technology to obtain the key feature electrical quantities of DC microgrid islands and form a sample set, and then rely on the Adaboost algorithm to generate a high-precision island classification model to realize the detection and classification of DC microgrid operation status. It has the advantages of automatic setting threshold, small detection blind area, and high accuracy. In addition, aiming at the problem that the classification results of the intelligent islanding detection algorithm based on machine learning cannot be directly used as the islanding discrimination results, an islanding criterion method based on the sliding window algorithm is added on the basis of the classification algorithm. This method realizes the accurate detection of the DC microgrid islanding operation state by the secondary analysis and judgment of the classification results of the islanding classification model. Finally, a DC microgrid model is built to simulate and verify the proposed method. The results show that the method can quickly and accurately complete the islanding detection of the DC microgrid.

Optimal dual-energy computed tomography scan parameters to detect small-sized urinary stones and their composition

To investigate the optimal scanning parameters of dual-energy computed tomography (DECT), which can accurately determine sensitivity (the detectability of urinary stones) and accuracy (the composition matching of urinary stones), and to apply them to clinical trials. Fifteen urinary stones were chemically analyzed, and their chemical compositions were considered a reference standard with which we compared the uric acid (UA) and non-UA compositions determined using DECT. The urinary stones were placed inside a bolus and scanned with a dual-source CT scanner under various selected dual-energy conditions (A to X) using various solid water phantom thicknesses. These datasets were analyzed using the Siemens syngo.via software tool (integrated into the CT system) for matching the sensitivity and accuracy assessments. This study showed that 80% of the highest sensitivity (detection of urinary stones) and 92% of the highest accuracy (composition matching of urinary stones) were achieved under condition A (a collimation beam width setting of 2 × 32× 0.6mm, an automatic exposure control setting of 80/sn140 peak kilovoltage, and a slice thickness of 0.5/0.5mm) (P < 0.05). Application of the DECT energy parameters presented in the study will help identify the sensitivity and accuracy of UA and non-UA stone analysis, even in patients with small-sized urinary stones and in conditions difficult for analysis.

On a family of 2-automatic sequences generating algebraic continued fractions in characteristic 2

We present family of automatic sequences that define algebraic continued fractions in characteristic 2. This family is constructed from ultimately period words and contains the period-doubling sequence.

Time-Series Analysis of Ship Movements Using Community Detection and Functional Data Analysis across the East Coast of the Republic of Korea

Kim, G.; Jeong, M.-H.; Jeon, S.-B., and Khan, M.S., 2023. Time-series analysis of ship movements using community detection and functional data analysis across the east coast of the Republic of Korea. Journal of Coastal Research, 39(2), 360–365. Charlotte (North Carolina), ISSN 0749-0208. Because of the recent climate change caused by air pollution in ports, global interest in marine spatial planning (MSP) has increased to achieve cost-effective navigation, economic development goals, logistics, and energy transportation. Accordingly, research on ship traffic, the main cause of air pollution in ports, is attracting attention. This study aims to investigate the temporal characteristics of the port network on the east coast of the Republic of Korea using the automatic identification system data set. This study used the Louvain model, a community detection technique for complex networks, and functional data analysis (FDA). The results of the Louvain model showed that the port network of the Republic of Korea has a hub-and-spoke structure in which ports that are close to each other are regionally clustered around the main ports in the community. The FDA results showed seasonal changes in port arrival volume and detection of abnormal ports in Korea's east-coast ports. The results of this study are expected to provide a baseline for policy makers to establish an effective MSP for port management, cost-effective route development, and prediction of the number of operations.

Requirements for Dental CAD Software: A Survey of Korean Dental Personnel

This study aimed to evaluate the needs of dentists, dental technicians, dental hygienists, and dental-related workers in terms of dental computer-aided design (CAD) software and artificial intelligence (AI). Based on a factor analysis, 57 survey items were assigned to six categories: (a) considerations when purchasing dental CAD software; (b) prosthesis design process; (c) dental CAD function; (d) use of AI dental CAD crown and denture design; (e) impact of AI; and (f) improvements in AI features. Overall, 93 participants were included in the study, and the reliability of the resultant survey data was estimated using Cronbach’s alpha coefficient. Statistically significant factors in each category were identified using one-way analysis of variance and Tukey’s honestly significant difference test (α = 0.05). The results revealed that design quality, design convenience and reproducibility, margin line setting, and automatic margin setting were considered most important in their respective categories (p &lt; 0.05). There were also significant differences in the importance of certain items, such as branding importance and functional diversity, among different dental personnel groups (p &lt; 0.05). Design speed and convenience were also found to be more important to dentists and dental hygienists compared to other dental personnel (p &lt; 0.05). The importance of specific survey items varied significantly based on age, dental personnel, and work experience groups. Dental personnel, such as dentists and dental technicians, assigned greater importance to certain factors, such as branding, functional diversity, design speed, and compatibility with CAM equipment, compared to other occupational groups.

Solutions of the Yang–Baxter Equation and Automaticity Related to Kronecker Modules

The Kronecker algebra K is the path algebra induced by the quiver with two parallel arrows, one source and one sink (i.e., a quiver with two vertices and two arrows going in the same direction). Modules over K are said to be Kronecker modules. The classification of these modules can be obtained by solving a well-known tame matrix problem. Such a classification deals with solving systems of differential equations of the form Ax=Bx′, where A and B are m×n, F-matrices with F an algebraically closed field. On the other hand, researching the Yang–Baxter equation (YBE) is a topic of great interest in several science fields. It has allowed advances in physics, knot theory, quantum computing, cryptography, quantum groups, non-associative algebras, Hopf algebras, etc. It is worth noting that giving a complete classification of the YBE solutions is still an open problem. This paper proves that some indecomposable modules over K called pre-injective Kronecker modules give rise to some algebraic structures called skew braces which allow the solutions of the YBE. Since preprojective Kronecker modules categorize some integer sequences via some appropriated snake graphs, we prove that such modules are automatic and that they induce the automatic sequences of continued fractions.