Automatic Sequencing Research Articles

The role of motor cortex in motor sequence execution depends on demands for flexibility.

The role of the motor cortex in executing motor sequences is widely debated, with studies supporting disparate views. Here we probe the degree to which the motor cortex's engagement depends on task demands, specifically whether its role differs for highly practiced, or 'automatic', sequences versus flexible sequences informed by external cues. To test this, we trained rats to generate three-element motor sequences either by overtraining them on a single sequence or by having them follow instructive visual cues. Lesioning motor cortex showed that it is necessary for flexible cue-driven motor sequences but dispensable for single automatic behaviors trained in isolation. However, when an automatic motor sequence was practiced alongside the flexible task, it became motor cortex dependent, suggesting that an automatic motor sequence fails to consolidate subcortically when the same sequence is produced also in a flexible context. A simple neural network model recapitulated these results and offered a circuit-level explanation. Our results critically delineate the role of the motor cortex in motor sequence execution, describing the conditions under which it is engaged and the functions it fulfills, thus reconciling seemingly conflicting views about motor cortex's role in motor sequence generation.

Microstructural Investigation and Mechanical Properties of Resistance Spot Welding Joints of Mild Steel Sheets

Due to its high productivity, low cost, and increased work efficiency, resistance spot welding (RSW) can instantly join two or more steel sheets and it is widely used in the automotive industry and lately in the manufacturing of thin-walled cold-formed steel constructions. However, the RSW of zinc-coated mild steel sheets presents metallurgical challenges, especially when different thickness combinations are used. Therefore, in the present paper a resistance welding machine was used which uses direct current (MFDC) inverter technology combined with SMART AUTOSET technology to weld S250 GD and S350 GD galvanised mild steel sheets with different thicknesses. It is well known that, due to the elevated temperature that occurs during the welding process, followed by rapid cooling, defects such as cracking, porosity, lack of fusion, and an increased amount of brittle phases affect the welding quality. Therefore, the influence of the RSW process parameters established by an automatic sequence on the nugget geometry, microstructure, and mechanical properties was investigated. The phase transformations that took place during the heating-cooling cycle were analysed in detail through metallographic studies. The results showed that the microstructure of the weld nuggets was similar, characterised by columnar grains elongated in the direction of heat evacuation. Nevertheless, there were differences in terms of phase dispersion, defects and mechanical properties that have been linked to the RSW process parameters.

Automatic setting optimization for robotic upper-extremity rehabilitation in patients with stroke using ReoGo-J: a cross-sectional clinical trial

Stroke-induced upper-extremity paralysis affects a substantial portion of the population, necessitating effective rehabilitation strategies. This study aimed to develop an automated program, incorporating the item response theory, for rehabilitation in patients with post-stroke upper-extremity paralysis, focusing on the ReoGo-J device, and to identify suitable robot parameters for robotic rehabilitation. ReoGo-J, a training device for upper-extremity disorders including 71 items, was administered to over 300 patients with varying degrees of post-stroke upper-extremity paralysis. Each item was rated on a three-point scale (0, very difficult; 1, adequate; 2, very easy). The results were analyzed using the graded response model, an extension of the two-parameter logistic model within the framework of the item response theory, to grade the training items based on ability of the patients. The relationship between the predicted ability, an indicator of the predicted ability the paralyzed upper-extremity to perform an item in the item response theory analysis (higher numbers indicate higher ability, lower numbers indicate lower ability), and the items in the Fugl–Meyer assessment (FMA), which indicate the degree of paralysis, was analyzed using Pearson’s correlation coefficient. This study included 312 patients with post-stroke upper-extremity paralysis. The predicted ability (θ) of the tasks included in the original ReoGo-J test for forward reaching, reaching for mouth, rotational reaching, radial reaching (2D), abduction reaching, reaching in eight directions, radial reach (3D), and reaching for head ranged from − 2.0 to − 0.8, − 1.3 to − 0.8, − 1.0 to − 0.1, − 0.7 to 0.3, − 0.2 to 0.4, − 0.4 to 0.6, − 0.1 to 0.6, and 0.5 to 0.6, respectively. Significantly high correlations (r = 0.80) were observed between the predicted ability of all patients and the upper-extremity items of shoulder-elbow-forearm in the FMA. We have introduced an automated program based on item response theory and determined the order of difficulty of the 71 training items in ReoGo-J. The strong correlation between the predicted ability and the shoulder-elbow-forearm items in FMA may be used to ameliorate post-stroke upper-extremity paralysis. Notably, the program allows for estimation of appropriate ReoGo-J tasks, enhancing clinical efficiency.Trial registration: https://www.umin.ac.jp/ctr/index-j.htm (UMIN000040127).

Genotyping Apolipoprotein E (APOE) Isoforms with Sequence-Specific-Primer (SSP)-PCR in Early‑Onset Alzheimer’s Disease Patients: A Rapid and Revised Methodology

Alzheimer's disease (AD) is a neurodegenerative disorder that causes progressive damage to brain cells, leading to impairment in cognitive functions. The Apolipoprotein E (APOE) variants play a significant role in the genetic basis of AD, especially late-onset AD (LOAD), and increase the disease risk at an earlier age. Although controversial, some studies reveal the association between APOE genotype and early-onset AD (EOAD) regardless of family history. Therefore, diagnostic laboratories widely perform routine tests to determine the APOE genotype. In the present study, we implemented a revised methodology for the Sequence-Specific-Primer-PCR (SSP-PCR) test for rapid APOE genotyping in 67 EOAD patients. Then, the findings were validated using automatic sequencing with newly designed primers for the related region of the APOE. We state clearly that the applicability of the SSP-PCR method was improved when the primer concentrations of control genes were increased 2-fold, as we reported. All data obtained from SSP-PCR were consistent with Sanger sequencing confirmations. Based on the genotyping results, the four different APOE genotypes were detected: E2/E4, E3/E3, E3/E4, and E4/E4. The frequencies were 1.5% (n=1) for E2/E4, 76.1% (n=51) for E3/E3, 16.4% (n=11) for E3/E4, and 6% (n=4) for E4/E4. In the study group, 23.9% (n=16) of the patients had homozygous or heterozygous APOE E4. However, we detected no significant association between the clinical features and the APOE genotype. As a result, this method is reliable, cost-effective, and rapid for performing genotyping analysis of the APOE for routine tests and research studies with larger EOAD cohorts.

AUTOMATIC MACHINE TOOL ALIGNMENT ON ITS FOUNDATION

This article deals with the issue of the automatic setting of machines on their base. The focus is on machines with a self-supporting frame, freestanding, on more than three supports. The alignment uses the previously presented method of precise and repeatable machine placement on the foundation. As a result, the machine has the necessary parameters in terms of its geometry, and at the same time a defined weight distribution on the individual building elements is guaranteed. The paper presents a new method for automatic machine alignment using so-called “smart feet”. Due to this, the process of machine alignment is clearly defined, repeatable and does not depend on the experience of the personnel performing the alignment. The presented algorithm makes it possible to automate the entire machine-setting process. The article includes the presentation of a machine placement on its base, which is used for testing and verification of the functionality of the alignment algorithm.

Low-Thrust Fuel-Optimal Guidance with Automatic Control Sequence Detection and Separation

This paper develops a novel fuel-optimal guidance scheme using differential algebraic techniques that is capable of handling changes in the optimal thrust sequence, in addition to a large domain of uncertainty. Taylor polynomials of the solution flow exhibit large approximation errors when the control sequence changes within the domain of operation. This property is leveraged through automatic domain splitting, a technique that tracks the approximation error and splits the domain into smaller subdomains when high errors are observed. After multiple splits, the domain is autonomously separated along the boundaries between different optimal control sequences. Crucially, each resulting subdomain encompasses only a single control sequence, ensuring that any guidance updates obtained from the final polynomial map provide the corresponding optimal control sequence. To ensure high accuracy of the guidance updates, this work also develops an efficient and iterative-less differential-algebra-based refinement algorithm, which is applied to the outputs of the polynomial map. The overall guidance scheme provides highly accurate guidance updates in response to large trajectory deviations, including new optimal control sequences, as demonstrated in an Earth–Psyche transfer.

An optimal goose lithium-ion batteries accurate and rapid RUL prediction method with automatic initial hyperparameters settings

Abstract Machine learning has emerged as a highly effective tool for addressing complex data problems, garnering significant attention in the field of equipment degradation and remaining service life prediction. Existing prediction models typically exhibit two primary shortcomings: on the one hand, the accuracy of life prediction reaches the desired level of precision while failing to achieve a sufficiently fast prediction speed, and on the other hand, generalization is not guaranteed while requiring the model to be robust. These two aspects present a significant challenge to the field of machine learning. In light of the aforementioned issues, we propose a prediction model based on the goose algorithm. Initially, we set the goose algorithm using adaptive initialization of the goose population to guarantee that the goose population is set at the appropriate interval, and we incorporate it into the extreme learning machine model through the improved goose algorithm. goose algorithm is used to predict the service life. Finally, we utilize different types of lithium batteries with varying operational conditions to conduct pertinent case studies to validate the proposed prediction model. The results demonstrated that the average accuracy was above 98% in all validated datasets. The shortest computation time was 0.19 s.

82 Linear mixed models for dissecting social and direct genetic effects of automatic feeder visit sequences

Abstract In this study, we delved into the feeding behaviors of 548 swine, using 114,263 records from FIRE feeders to uncover the direct and social genetic effects of feeding duration. We aimed at dissecting direct and social effects and genetics and environmental components of feeding duration using linear mixed-effects models (LMMs). To accomplish this, we fit and compared several models. The full model included direct and social genetic effects and permanent environmental effects or the social effects or both sets of effects. All models included the effect of the social group. This model facilitates a comprehensive understanding of the determinants of feeding times as it related to social interaction sequences. A novel aspect of our study is the use of sequence of feeder visits as a proxy to social interaction at the feeder, so separate social genetic and social permanent environmental effects of an individual from the ‘Social Group’ effect. The analysis reveals that the full model offers the best fit to the data, as indicated by the smallest Akaike Information Criterion (AIC). However, comparisons with reduced models suggest a partial confounding between additive genetic and permanent environmental effects at both additive and social levels. Notably, the variance explained by the social group remains consistent across models, implying minimal confounding with this factor and underscoring the distinct impact of social dynamics. The observation that social direct genetic effects do not significantly overlap (e.g., M1 vs M2) is promising, suggesting the potential to address the confounding between additive genetic (A) and permanent environmental (PE) effects by incorporating a more detailed pedigree analysis. By presenting variance components and model fit indices (Table 1), our research illuminates the intricate interactions among genetic, environmental, and social factors affecting swine behavior. The use of mixed-effects modeling in this study advances our understanding of the temporal dynamics of animal social behavior, emphasizing the importance of detailed statistical analysis in behavioral research.

String Attractors of Some Simple-Parry Automatic Sequences

String Attractors of Some Simple-Parry Automatic Sequences

Design and Development of an Automatic Layout Algorithm for Laser GNSS RTK.

At the current stage, the automation level of GNSS RTK equipment is low, and manual operation leads to decreased accuracy and efficiency in setting out. To address these issues, this paper has designed an algorithm for automatic setting out that resolves the common problem of reduced accuracy in conventional RTK. First, the calculation of the laser rotation center is conducted using relevant parameters to calibrate the instrument's posture and angle. Then, by analyzing the posture information, the relative position and direction of the instrument to the point to be set out are determined, and the rotation angles in the horizontal and vertical directions are calculated. Following this, the data results are analyzed, and the obtained rotation angles are output to achieve automatic control of the instrument. Finally, a rotating laser composed of servo motors and laser modules is used to control the GNSS RTK equipment to locate the set-out point, thereby determining its position on the ground and displaying it in real-time. Compared to traditional GNSS RTK equipment, the proposed automatic setting out algorithm and the developed GNSS laser RTK equipment reduce the setting out error from 15 mm to 10.3 mm. This reduces the barrier to using GNSS RTK equipment, minimizes human influence, enhances the work efficiency of setting out measurements, and ensures high efficiency and stability under complex conditions.

195: A simple in silico model as a support in the clinical practice: automatic setting of a VA-ECMO system.

195: A simple in silico model as a support in the clinical practice: automatic setting of a VA-ECMO system.

Terminal sequence consistency verification method for small diameter abreast optical fibers based on computer vision

In a kind of precision industrial equipment, small diameter abreast optical fibers are used for high-speed communication among functional nodes. The arrangement order at both terminals of the abreast optical fibers need to comply with communication protocols. In this paper, we propose an automatic terminal sequence consistency verification method based on computer vision. The Hue Saturation Value (HSV) color space is used for improving the image feature extraction capability. An abreast optical fiber sequence dictionary which converts the protocol logic into an input-output mapping table is provided to follow protocol confidentiality and improve inspecting speed. A light control baffle position adaptive algorithm is designed for improving the accuracy of optical fiber incident light control. The experimental results show that the method can achieve the conductivity inspection of 1 optical fiber every 50 seconds, and the inspection accuracy is over 96.5%, which generally improves the inspection efficiency by 45% compared with manual inspection.

Dyck Words, Pattern Avoidance, and Automatic Sequences

Dyck Words, Pattern Avoidance, and Automatic Sequences

Repetition Factorization of Automatic Sequences

Following Inoue et al., we define a word to be a repetition if it is a (fractional) power of exponent at least [Formula: see text]. A word has a repetition factorization if it is the product of repetitions. We study repetition factorizations in several (generalized) automatic sequences, including the infinite Fibonacci word, the Thue-Morse word, paperfolding words, and the Rudin-Shapiro sequence.

Analysis of the genetic structure of populations of the terrestrial mollusk <i>Caucasotachea vindobonensis</i> (Helicidae) in conditions at the eastern border of the range using microsatellite markers

BACKGROUND: Assessing the genetic structure of populations of rare and vulnerable species provides useful information for developing conservation strategies. AIM: The aim of the study was to study the genetic structure of Caucasotachea vindobonensis populations in the south of the Central Russian Upland using SSR markers. MATERIALS AND METHODS: Genetic structure of the populations was studied using eight microsatellite markers, first identified by the authors for the species under study. Fragment analysis of PCR products was carried out on an automatic capillary DNA sequencer Nanophore 05 (Russia). A total of 498 individuals from 24 populations were studied. RESULTS: A total of 59 alleles were isolated in the eight studied SSR loci, of which 21 (36%) turned out to be private. At the same time, private alleles were found in eleven studied populations, which is 46% of their total number. According to the data obtained, the effective number of alleles (Ae) averaged 1.6 ± 0.06, the Shannon index (I) was 0.45 ± 0.03, and the level of expected heterozygosity (He) was 0.27 ± 0.021. A high level of spatial subdivision of population gene pools was noted (Fst = 0.47 ± 0.08) with a fairly low level of gene flow (Nm = 1.15 ± 0.91). PCA analysis showed that the populations of the central and eastern parts of the south of the Central Russian Upland form a closely related group, different from other populations of the region. Calculation of the effective abundance using the LD method showed that Ne varies in different groups of snails from 0.6 to infinity. CONCLUSIONS: Populations of C. vindobonensis in the south of the Central Russian Upland live in conditions of significant isolation, as evidenced by the high degree of differentiation of the studied groups. The analysis of principal components based on genetic distances according to Nei and Wright’s F-statistics indicate a pronounced division of populations in the study area into two clusters, which is probably associated with the historical features of landscape formation. Calculation of effective numbers indicates the high viability of the majority of the studied populations. At the same time, some groups of snails are clearly in a depressed state, which is reflected in low levels of genetic diversity and their effective size.

Ichthyosis Follicularis, Atrichia, and Photophobia (IFAP) Syndrome, Type 2: Clinical Case

Background. Ichthyosis follicularis with atrichia and photophobia (IFAP syndrome), type 2 is a rare hereditary disease from the group of syndromic forms of ichthyosis. It is clinically characterized by triad of non-inflammatory follicular ichthyosis, total or subtotal alopecia at birth or shortly after, and photophobia of different severity. There is no etiotropic therapy for IFAP syndrome, while symptomatic treatment (emollients, keratolytics, retinoids) is aimed on stabilizing the patient’s condition and maintaining the optimal quality of life. About 60 cases of IFAP syndrome have been described worldwide by 2023, and none in Russia.Clinical case description. The girl, 2 years 3 months old, had signs of xeroderma, follicular hyperkeratosis, photophobia with lacrimation, and alopecia. The diagnosis of “ichthyosis follicularis with atrichia and photophobia (IFAP syndrome), type 2, autosomal dominant” was established according to anamnesis, clinical signs, and results of whole-exome sequencing, followed by validation of the identified nucleotide variant chr17:17720597G>A, p.1669C>T (p.Arg557Cys NM_001005291.2) in exon 9 of the SREBF1 gene via direct automatic sequencing in the patient and both parents (not revealed in her parents).Conclusion. Molecular genetic testing is crucial to establish IFAP syndrome as clinical signs of the disease are similar to other dermatoses. However, physicians need to have clinical suspicion when identifying cases of follicular ichthyosis in combination with alopecia and photophobia at or shortly after birth to timely diagnose IFAP syndrome and thus prevent any treatment delays.

Niemann-Pick Disease, Type A: Clinical Case of 5 Months Old Patient

Background. Niemann-Pick disease, type A is a rare hereditary disease from the group of lysosomal storage diseases, it is characterized by early onset and progressive course. Description of this disease’s clinical cases is crucial for early diagnosis and adequate management due to its rarity, rapid progression, and the development of new pathogenetic therapy methods.Clinical case description. The disease manifested on the second month of the patient’s life with poor weight gain, frequent pneumonia, hepatosplenomegaly, diffuse muscular hypotonia, delayed motor development, and progressive neurological symptoms. Laboratory testing has revealed significant decrease in sphingomyelinase activity in blood. The heterozygous deletion c.996del in exon 2 of the SMPD1 gene has been revealed via direct automatic sequencing; it leads to frameshifting p.F333Sfs*52 (inherited from mother). Moreover, the previously described pathogenic nucleotide variant c.1252C>T (heterozygous) has been revealed in exon 3 of the SMPD1 gene; it leads to translation arrest p.Arg418* (inherited from father). Cherry-red spots were diagnosed at fundospcopy. The diagnosis of Niemann-Pick disease, type А was established according to clinical signs and molecular genetic testing results.Conclusion. The detection of physical and motor development delay, diffuse muscular hypotonia, hepatosplenomegaly, cherry-red spots at ophthalmological examination, lung involvement, recurrent pneumonia, and progressive neurological symptoms in a child during the first months of life indicates that this patient has Niemann-Pick disease, type А. Early molecular genetic testing is crucial for timely choosing the management approach and further genetic counselling of the family.

Discourse Analysis: Adjacency Pairs in Selected Korean Englishman YouTube Video

This research focuses to analyze adjacency pairs in the selected Korean Englishman YouTube Video titled “K-Pop Idol NCT Johnny fed us luxury Korean Beef BBQ!” using Yule’s (1996) theory. This study is using the qualitative descriptive method to analyze the data. From the conversation uttered by speakers, there are some patterns that they automatically produced, called adjacency pairs. The adjacency pairs occur when two or more people talk and respond to each other’s questions. Based on the analysis, there are 25 adjacency pairs; (15) Question–Answer, (1) Command–Compliance, (1) Request–Acceptance, (1) Offer–Acceptance, (5) Assessment–Agreement, (2) Suggestion–Acceptance that were found in the conversation between Johnny, Josh, and Ollie in the Korean Englishman YouTube video titled “K-Pop Idol NCT Johnny fed us luxury Korean Beef BBQ!”. From all the data found in this study, the functions of utterances are in accordance with each type of adjacency pair thus conclude that adjacency pairs are automatic sequences of two utterances produced by two speakers with the second utterances conversing about the first utterance. Key Words: Adjacency Pairs, Conversation Analysis, Discourse Analysis

Enhancing healthcare in the digital era: A secure e-health system for heart disease prediction and cloud security

In the modern world, due to changing lifestyles, more people are infected by deadly diseases, especially heart disorders. An early prognosis is the only possible way of increasing survival rate. One of the key elements of this context is the healthcare digitalization that is carried out through Internet of Things (IoTs) and cloud computing. However, main issue in cloud with IoT is false diagnosis, which leads to cause a major impact on patient’s life. Moreover, data communication through cloud servers can be compromised by attackers due to security issues. Therefore, to overcome these issues, this paper proposes a novel secure e-healthcare system with dual objectives- accurate disease prediction and improved cloud security. A novel diagnosis approach ‘Hybrid Binary Particle Firefly Optimized Extreme Learning Machine classifier (HybBPF-ELM)’ to predict HD is designed, that recognize the subject with HD abnormality from the normal ones. The prediction accuracy and time efficiency of training process are improved by the adoption of a Hybrid Binary Particle Firefly Optimizer (HBPFO) through fine-tuning weight and bias of Extreme Learning Machine (ELM) classifier. Additionally, a new intelligent encryption and decryption framework ‘IEDF’ is introduced for cloud security. It combines four encryption algorithms, including Advanced Encryption Standard (AES), Data Encryption Standard (DES), Rivest- Shamir-Adleman (RSA), and Modified Blow Fish (MBF) to enhance cryptographic strength and key security. Along with this, an Automatic Sequence Encryption (ASC) for data block encryption is employed to ensure strong security and network performance. The integration of HD prediction module and cloud security framework within e-healthcare system assists healthcare experts in securely storing and transferring data for advanced diagnosis. The results show that our proposed system achieves an overall prediction accuracy of 99.36 % and less processing time for encryption and decryption of 127.55 s and 452.01 s at 2.2 GB file size respectively.

High Wideband Digital Oscilloscope Design

In most test applications, acquisition and analysis involving simultaneous processing of analog and digital signals. However, the bandwidth of most mainstream digital oscilloscopes is limited to 100 MHz, which is unable to meet the testing needs of high-frequency signals in complex electronic systems [1], and therefore, high-bandwidth digital oscilloscopes have emerged. Based on this background, this paper designs a digital oscilloscope hardware platform with high bandwidth by integrating FPGA and ARM technologies, aiming to meet the rigorous testing requirements of modern electronic systems. The FPGA module is based on the xc7s75fgga676 chip, which is mainly responsible for ADC control, data processing and frequency measurement functions. AM5708 is selected as the ARM module to realize the trigger, time base, amplitude and automatic setting functions of the oscilloscope. In order to ensure the accuracy and fidelity of waveform changes, the Sinc function interpolation method is used. This design further improves the acquisition bandwidth and processing speed on the basis of traditional MSO (Mixed Signal Oscilloscope) oscilloscopes, which is of great significance for the acquisition and processing of high-speed signals.