Independent Branches Research Articles

Study on combustion characteristics of swirl premixed combustor

Taking a certain type of combustion chamber as the research object, the numerical simulation is carried out by using RANS (Reynolds averaged Navier-stokes) and LES (large eddy simulation), and the simulation results of the two numerical methods are compared and analyzed. The research results show that the RANS calculation results can reflect the main flow field characteristics in the combustion field, and have certain engineering significance. LES can reproduce specific flow field details such as the weak axial flow region, accurately simulate the location and strength of the shear layer, simulate the dynamic development process of flame, and capture the dynamic characteristics of the combustion flow field. Compared with RANS, LES has more obvious advantages in numerical simulation of the combustion flow field. Through calculation, the precessing vortex core under this working condition is composed of three relatively independent spiral vortex branches, which excites periodic velocity pulsation and pressure pulsation in the combustion chamber. LES captures the dominant frequency with the precession vortex core of 156 Hz.

MFB-LANN: A lightweight and updatable myocardial infarction diagnosis system based on convolutional neural networks and active learning

Background and objectives: 12 leads electrocardiogram (ECG) are widely used to diagnose myocardial infarction (MI). Generally, the symptoms of MI can be reflected by waveforms in the heartbeat, and the contribution of different ECG leads to different types of MI is different. Therefore, it is significant to use the heartbeat waveform features and the lead relationship features for multi-category MI diagnosis. Moreover, the challenge of individual differences and lightweight algorithms also need to be further resolved and explored in the ECG automatic diagnosis system.Methods: This paper presents a lightweight MI diagnosis system named multi-feature-branch lead attention neural network (MFB-LANN) via 12 leads ECG signals. It is designed based on the characteristics of the ECG lead. Specifically, 12 independent feature branches correspond to different leads, and each branch contains different convolutional layers to extract features in the heartbeat, then a novel attention module is developed named lead attention mechanism (LAM) to assign different weights to each feature branch. Finally all the weighted feature branches are fused for classification. Furthermore, to overcome individual differences, patient-specific scheme and active learning (AL) are used to train and update the model iteratively.Results: Experimental results based on Physikalisch-Technische Bundesanstalt (PTB) database shows that the MFB-LANN achieved satisfactory results with accuracy of 99.63% based on 5-fold cross validation under the intra-patient scheme. The patient-specific experiment yielded an average accuracy of 96.99% compared to the state-of-the-art. By contrast, the model achieved acceptable results on the hybrid database (PTB and PTB-XL), especially achieving 94.19% accuracy after the update. Moreover, the system can complete the update process and real-time diagnosis on the ARM Cortex-A72 platform.Conclusions: Experiments show that the proposed method for MI diagnosis has more obvious advantages compared to other recent methods, and it has great potential to be applied to the mobile medical field.

Parallel Business Processes Modeling

The article considers a new section of the modern theory of business processes dedicated to their parallel processing. The relevance of the work is due to the need to reorganize business processes in order to improve a number of their key indicators, such as speed, cost, etc. It should be noted that the well-known models and methods of the modern theory of business processes practically do not address the issues of parallelism in them, although this direction occupies a significant place in the general theory of processes and, in addition to the actual methods of description, analysis and verification of parallel structures, also includes methods of parallelization of sequential structures. The paper proposes a classification of parallel business processes based on the types of parallel computing systems and completely covering the subject area under consideration. Examples of parallel business processes of each type are given. For each of the selected classes of business processes, a brief overview of the current state of affairs in terms of parallelism is given; the directions of relevant work are identified and analyzed. Brief descriptions of models and methods of pipelined and synchronous parallelism are given. In terms of asynchronous parallelism, a model and language tools for organizing parallel independent branches (processes) are proposed. A mixed graph containing nodes and branches of various types is used as the corresponding model. The scenario of executing a parallel business process is formalized. To estimate the execution time of a parallel business process, the basic theorems of the theory of computational processes are adapted in order to focus them on business processes, recommendations are given on the rules for building parallel business processes. The requirements for the language tools for describing asynchronous parallel business processes are formulated. Next, the methods of parallelization of business processes related to its linear sections and cycles are considered. The definitions of the linear section and the cycle in the business process are introduced. For their parallelization, the key task is to identify information dependencies between the functions of the business process. Attention is drawn to the sequence of definitions/uses of information objects, manifested through incoming and outgoing information flows for functional objects of the corresponding visual modeling language. In terms of the above-mentioned business process graph, the concepts of information dependence of various types are formalized. The proposed work is one of the first attempts to build a formal basis for the organization of parallelism in business processes, which plays an important role in improving the key indicators of business processes in the tasks of their reorganization.

Self-Supervised Representation Learning for Evolutionary Neural Architecture Search

Recently proposed neural architecture search (NAS) algorithms adopt neural predictors to accelerate architecture search. The capability of neural predictors to accurately predict the performance metrics of the neural architecture is critical to NAS, but obtaining training datasets for neural predictors is often time-consuming. How to obtain a neural predictor with high prediction accuracy using a small amount of training data is a central problem to neural predictor-based NAS. Here, a new architecture encoding scheme is first devised to calculate the graph edit distance of neural architectures, which overcomes the drawbacks of existing vector-based architecture encoding schemes. To enhance the predictive performance of neural predictors, two self-supervised learning methods are proposed to pre-train the architecture embedding part of neural predictors to generate a meaningful representation of neural architectures. The first method designs a graph neural network-based model with two independent branches and utilizes the graph edit distance of two different neural architectures as a supervision to force the model to generate meaningful architecture representations. Inspired by contrastive learning, the second method presents a new contrastive learning algorithm that utilizes a central feature vector as a proxy to contrast positive pairs against negative pairs. Experimental results illustrate that the pre-trained neural predictors can achieve comparable or superior performance compared with their supervised counterparts using only half of the training samples. The effectiveness of the proposed methods is further validated by integrating the pre-trained neural predictors into a neural predictor guided evolutionary neural architecture search (NPENAS) algorithm, which achieves stateof-the-art performance on NASBench-101, NASBench-201, and DARTS benchmarks

Nocardioides dongkuii sp. nov. and Nocardioides lijunqiniae sp. nov., isolated from faeces of Tibetan antelope (Pantholops hodgsonii) and leaves of dandelion (Taraxacum officinale), respectively, on the Qinghai-Tibet Plateau.

In the present study, four bacterial strains, two (S-713T and 406) isolated from faecal samples of Tibetan antelopes and the other two (S-531T and 1598) from leaves of dandelion collected on the Qinghai-Tibet Plateau of PR China, were analysed using a polyphasic approach. All four isolates were aerobic, rod-shaped, non-motile, oxidase-negative, Gram-stain-positive and catalase-positive. According to four phylogenetic trees, strain pairs S-713T/406 and S-531T/1598 form two independent branches belonging to the genus Nocardioides, and are closest to Nocardioides lianchengensis, Nocardioides dokdonensis, Nocardioides salarius, Nocardioides marinisabuli, Nocardioides psychrotolerans and Nocardioides szechwanensis. Although sharing MK8-(H4) as their major isoprenoid quinone, strains S-713T and S-531T contained C18 : 1 ω9c (24.64 and 16.34 %) and iso-C16 : 0 (9.74 and 29.38 %), respectively, as their main fatty acids, with remarkable differences in their biochemical profiles but only slight ones in their optimal growth conditions. The chromosomes of strains S-713T and S-531T were 4 207 844 bp (G+C content, 73.0 mol%) and 4 809 817 bp (G+C content, 72.5 mol%), respectively. Collectively, the two strain pairs represent two separate novel species of the genus Nocardioides, for which the names Nocardioides dongkuii sp. nov. and Nocardioides lijunqiniae sp. nov. are proposed, with S-713T (=JCM 33698T=CGMCC 4.7660T) and S-531T (=JCM 33468T=CGMCC 4.7659T) as the respective type strains.

Linking adolescent and adult narcissism research: A contribution by the narcissistic admiration and rivalry concept

To date, adolescent and adult narcissism research are independent research branches with almost no cross-talk. In the current paper, we argue that it is possible to merge them. The study was completed by adolescents (N = 269) three times during one year period and we compared their scores with adult population (N = 351). Further, we evaluated whether the two-dimensional model of narcissism fits the data from adolescents and whether is invariant in comparison to the adults. Third, we analysed whether narcissism in adolescence is stable. Finally, we scrutinized whether the pathways underlying the link of narcissistic personality to being liked are the same in adolescent as reported in adult narcissism. We have found support for linking adolescent and adult narcissism.

PUBLIC - POLITICAL LIFE OF THE KYRGYZ REPUBLIC

1991year entered world history as the collapse of the USSR and the emergence of new independent states on its wreckage. In August 31, 1991, Kyrgyzstan adopted the Declaration on State independence. The transition to democratization began in difficult condition. The political, economic, social crisis set the stage for new reforms in the country. Changes in the political system of society were enshrined in the adopted first Constitution of 1993. The principle of separation of powers was enshrined: legislative, executive and judicial bodies were defined as independent branches of government. The political life of society depends on the type of political regime, public opinion, the influence of ideology and religion, as well as the decency of the media. Constitutional, political and economic reforms in Kyrgyzstan upset the balance government. The instability of democratic institutions and the establishment of authoritarian rule led to the March events of 2005.

SMG5-SMG7 authorize nonsense-mediated mRNA decay by enabling SMG6 endonucleolytic activity

Eukaryotic gene expression is constantly controlled by the translation-coupled nonsense-mediated mRNA decay (NMD) pathway. Aberrant translation termination leads to NMD activation, resulting in phosphorylation of the central NMD factor UPF1 and robust clearance of NMD targets via two seemingly independent and redundant mRNA degradation branches. Here, we uncover that the loss of the first SMG5-SMG7-dependent pathway also inactivates the second SMG6-dependent branch, indicating an unexpected functional connection between the final NMD steps. Transcriptome-wide analyses of SMG5-SMG7-depleted cells confirm exhaustive NMD inhibition resulting in massive transcriptomic alterations. Intriguingly, we find that the functionally underestimated SMG5 can substitute the role of SMG7 and individually activate NMD. Furthermore, the presence of either SMG5 or SMG7 is sufficient to support SMG6-mediated endonucleolysis of NMD targets. Our data support an improved model for NMD execution that features two-factor authentication involving UPF1 phosphorylation and SMG5-SMG7 recruitment to access SMG6 activity.

Multi-Scale Convolutional Gated Recurrent Unit Networks for Tool Wear Prediction in Smart Manufacturing

As an integrated application of modern information technologies and artificial intelligence, Prognostic and Health Management (PHM) is important for machine health monitoring. Prediction of tool wear is one of the symbolic applications of PHM technology in modern manufacturing systems and industry. In this paper, a multi-scale Convolutional Gated Recurrent Unit network (MCGRU) is proposed to address raw sensory data for tool wear prediction. At the bottom of MCGRU, six parallel and independent branches with different kernel sizes are designed to form a multi-scale convolutional neural network, which augments the adaptability to features of different time scales. These features of different scales extracted from raw data are then fed into a Deep Gated Recurrent Unit network to capture long-term dependencies and learn significant representations. At the top of the MCGRU, a fully connected layer and a regression layer are built for cutting tool wear prediction. Two case studies are performed to verify the capability and effectiveness of the proposed MCGRU network and results show that MCGRU outperforms several state-of-the-art baseline models.

Facial Expression Recognition With Two-Branch Disentangled Generative Adversarial Network

Facial Expression Recognition (FER) is a challenging task in computer vision as features extracted from expressional images are usually entangled with other facial attributes, e.g., poses or appearance variations, which are adverse to FER. To achieve a better FER performance, we propose a model named Two-branch Disentangled Generative Adversarial Network (TDGAN) for discriminative expression representation learning. Different from previous methods, TDGAN learns to disentangle expressional information from other unrelated facial attributes. To this end, we build the framework with two independent branches, which are specific for facial and expressional information processing respectively. Correspondingly, two discriminators are introduced to conduct identity and expression classification. By adversarial learning, TDGAN is able to transfer an expression to a given face. It simultaneously learns a discriminative representation that is disentangled from other facial attributes for each expression image, which is more effective for FER task. In addition, a self-supervised mechanism is proposed to improve representation learning, which enhances the power of disentangling. Quantitative and qualitative results in both in-the-lab and in-the-wild datasets demonstrate that TDGAN is competitive to the state-of-the-art methods.

Visual detection of construction and demolition waste using multi-sensor fusion

In construction and demolition waste (CDW), there are materials that are difficult to separate by density and magnetic characteristics alone. To realise a finer separation of these difficult-to-separate materials, a multi-sensor fusion method for the visual detection of CDW is proposed. This method consists of a red–green–blue–depth (RGBD) data collection method with high precision in the height direction and a multimodal data processing algorithm. To obtain comprehensive features accurately and efficiently, the proposed method uses two independent MobileNet branches to extract colour visual features and geometric features separately, and an encoder is used to control the frequency of the two models in real time to better match the two data types. The proposed method makes full use of the height data to filter out the background of the conveyor belt and the invalid areas generated by the region proposal networks to improve its robustness. Experiments show that the accuracy of the proposed visual detection method is over 90%. Additionally, computational efficiency reaches 1.67 frames per second (fps) on a central processing unit (CPU) and 30 fps on a graphics processing unit. The detection efficiency when running on the CPU could reach 25 000 CDW items per hour.

THE HISTORIA AVGVSTA BEFORE MS PAL. LAT. 899: LOST MANUSCRIPTS AND SCRIBAL MEDIATION

AbstractThis article re-evaluates the role of the manuscript tradition of the Historia Augusta in debates over the original contents and authorship of the text. Evidence for physical disruptions to the text before our oldest surviving manuscripts points to an earlier manuscript distributed across multiple codices. A multi-volume archetype eliminates critical arguments against the author's claims about lives missing before the Life of Hadrian as well as in the lacuna for the years a.d. 244–260. Other multi-volume codices of the eighth and ninth centuries show that loss of an initial volume would have disrupted the textual tradition for the index, titles and authorial attributions. Comparison of our most complete early witness, Pal. lat. 899, to the independent branches of the textual tradition shows discrepancies between these paratextual elements as expected in a disrupted tradition. Ultimately, this article concludes that the current debates on authorship and the original scope of the Historia Augusta rest on paratextual elements from a single branch of the manuscript tradition, raising doubts about the centrality of these controversies to understanding the work.

Inhella proteolytica sp. nov. and Inhella gelatinilytica sp. nov., two novel species of the genus Inhella isolated from aquaculture water.

The two novel bacterial strains designated 1Y17T and 4Y10T from aquaculture water were characterized using a polyphasic taxonomic approach. Phylogenetic analysis of 16S rRNA gene sequences revealed that strains 1Y17T and 4Y10T belonged to the genus Inhella and were close to Inhella crocodyli CCP-18T, Inhella inkyongensis IMCC1713T and Inhella fonticola TNR-25T. Strains 1Y17T and 4Y10T shared 98.6% identity with each other and less than 99.0% identity with their relatives above. The phylogenomic analysis indicated that the two strains formed two independent branches distinct from their relatives. The digital DNA-DNA hybridization (dDDH) and average nucleotide identity (ANI) values between the two strains were 21.3 and 80.9% below the two thresholds of 70% dDDH and 95-96% ANI for species definition; those between the two novel strains and their relatives were far below thresholds for species definition, implying that they represent two novel genospecies. The predominant fatty acids of the two strains were summed feature 3 (C16:1 ω7c and/or C16:1 ω6c) and C16:0; the major polar lipids were diphosphatidylglycerol, phosphatidylethanolamine and phosphatidylglycerol; the major quinone and polyamine were Q-8 and putrescine. Their genomic DNA G + C contents were 69.3 and 65.0%. The two novel strains can produce poly-β-hydroxybutyrate, matching with the presence of the three synthetic related genes of the phaC-phaA-phaB in their genomes. Based on the genotypic and phenotypic characteristics such as aesculin and gelatin hydrolysis, strains 1Y17T and 4Y10T are concluded to represent two novel species of the genus Inhella, for which the names Inhella proteolytica sp. nov. (type strain 1Y17T = GDMCC 1.1830T = KACC 21948T) and Inhella gelatinilytica sp. (type strain 4Y10T = GDMCC 1.1829T = KCTC 82338T) are proposed.

The Rule of Abd аl-Fattah al-Sisi: Politics, Economics and International Relations of Egypt in the 2010s.

The article is devoted to the history of coming to power and the analysis of the domestic and foreign policy of the President of the Arab Republic of Egypt (ARE), Field Marshal Abd-аl Fattah al-Sisi. The author notes that the new leader of the country chose a tough internal political course aimed at strengthening his own power and suppressing the opposition, fi rst of all, the Muslim Brotherhood (the organization’s activities are prohibited on the territory of the Russian Federation), and the 2014 Constitution and its 2019 amendments led to the virtual disappearance of the independent branches of power and its concentration in the hands of the president, as well as the consolidation in the Basic Law of provisions on the special role of the military in the life of society. Thus, the head of state and the Supreme Council of the Armed Forces determine the political processes in the country, controlling civil institutions. Unlike the traditional ARE course, Abd-al Fattah al-Sisi is building a tougher and more uncompromising policy, demonstrating a readiness to use force, primarily in Libya, narrowing his scope for diplomatic maneuver.

Inverse Artificial Neural Network for Multiobjective Antenna Design

To improve the convenience and efficiency of antenna design, in this article, a novel inverse artificial neural network (ANN) model is proposed in which antenna performance indexes are set as the input and corresponding geometrical variables are set as the output. To solve the multiobjective problem of antenna modeling, the first part of the ANN model involves three parallel and independent branches for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</i> -parameter, gain, and radiation pattern, and the second part outputs a final predicted result. Once the training is completed, the proposed inverse model can provide antenna geometries directly without being repetitively called by an optimization algorithm. Compared with the inverse extreme learning machine and five state-of-art forward models, the proposed model uses a small number of training samples and directly obtains the satisfying values of geometrical variables without any optimization process.

Comparative genomic analysis of the genus Novosphingobium and the description of two novel species Novosphingobium aerophilum sp. nov. and Novosphingobium jiangmenense sp. nov

Members of the genus Novosphingobium are well known for their metabolically versatile and great application potential in pollution elimination. The three novel bacterial strains, designated 4Y4T, 4Y9, and 1Y9AT, were isolated from aquaculture water and characterized by using a polyphasic taxonomic approach. The 16S rRNA gene sequences phylogenetic analysis revealed that the three strains belonged to the genus Novosphingobium. The phylogenomic analysis indicated that the three strains formed two independent and robust branches distinct from all reference strains. The analyses of dDDH values and ANIs between the three strains and their relatives further demonstrated that the three strains represented two different novel genospecies. Comparative genomic analysis of the three isolates and 32 type strains of the genus Novosphingobium showed that the most important central metabolic pathways of these strains appeared to be similar, while specific and specialized metabolic pathways were flexible and variable among these strains. Chemotaxonomic characterization exhibited that the predominant cellular fatty acids were summed feature 8, summed feature 3, and C14:0 2OH; the major polar lipids were diphosphatidylglycerol, phosphatidylethanolamine, phosphatidyldimethylethanolamine, phosphatidylglycerol, and sphingoglycolipid; the major respiratory quinone and polyamine were Q-10 and spermidine. The DNA G + C contents were 67.6 and 64.7 %. Based on the genotypic and phenotypic characteristics, strains 4Y4T and 1Y9AT are concluded to represent two novel species of the genus Novosphingobium, for which the names Novosphingobium aerophilum sp. nov. (type strain 4Y4T = GDMCC 1.1828 T = KACC 21946 T) and Novosphingobium jiangmenense sp. nov. (type strain 1Y9AT = GDMCC 1.1936 T = KACC 22085 T) are proposed.

Calcineurin Immune Signaling in Response to Zinc Challenge in the Naked Carp Gymnocypris eckloni

Zinc pollution impairs neural processes and protein function and also effects calcium-related transcriptional regulation and enzyme activity. In this study, we investigated pathways that potentially respond to calcium signaling under Zn2+ stress. Specifically we measured relative expressions of GeCNAα, GeCNB, GeMT, GeTNF-α, GeIL-1β, and GeHsp90 in gills, livers, and kidneys of the indicator species Gymnocypris eckloni and found wide variation in their expression between tissues during the course of Zn2+ exposure. Notably, GeCNAα, GeCNB, GeTNF-α, GeIL-1β, and GeMT were rapidly and strongly up-regulated in gills; GeIL-1β and GeHsp90 transcription was quickly induced in kidneys; and GeCNB, GeTNF-α, GeIL-1β, and GeHsp90 were most rapidly up-regulated in livers. GeCNAα and GeMT showed a contrasting late transcriptional up-regulation. These results suggest independent branches for chelation and immune responses during self-protection against Zn2+ toxicity, and the immune response appears to be faster than metal chelation.

Evaluation of the strategic potential of the latest technologies in industrial fungi farming

The continuous process of improving technologies for the production of cultivated fungi has led to a significant increase in global production and opened the possibility of cultivating a wide range of new types of edible fungi. Industrial fungi farming as an economic activity in developed European countries has become one of the main independent branches of agricultural production. In the Russian Federation, there is a positive growth in the volume of production of edible fungi. Assessing the strategic potential of the latest technologies in industrial fungi farming is a top priority for the country. Due to the introduction of the latest technology of three-phase preparation of the substrate, the intensification of the production cycle of growing fruit bodies of fungi has increased by 1.5 times.

The complementarity of sociology and psychology and their general scientific significance

The nature of sociology and psychology is clarified accounting for the achievements of modern philosophy of science. The general scientific significance of these sciences is determined in accordance with said clarification. Any scientific theory functions, in particular, in the form of group and individual theories. In this connection, the general scientific significance of sociology and psychology becomes evident. The status of sociology is primarily determined by the study of group theories that have general scientific significance. The status of psychology is determined by individual theories. Its priority in this area is also indisputable. Therefore, same as sociology, psychology presents a science of auxiliary nature. Auxiliary sciences are necessary for the development of the content of the independent sciences. Unfortunately, the mainstream tendency is that both sociology and psychology are considered independent branches of science. In this regard, the status of sociology is determined by a certain class of social phenomena, and the status of psychology is determined by mental processes.

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The article considers the method for describing program modeling where predicates are used to create a model in the form of a nondeterministic finite automaton. A format of the description of predicates with the division of their semantic and conditional parts is offered in the paper. Arithmetic operators, parentheses, standard functions, as well as temporal logic operators U and N should be used to describe the content of the predicate. For the logical part of predicates, in addition to their logical functions, it is proposed to use relation operations, arithmetic operators, parentheses and standard functions. The formation of the description of each state of the pro-gram automaton model should be completed by dividing into different branches of the model. To describe the models of parallel programs, the following special states have been introduced: a state-monitor for the access of various processes to shared resources and a state-protocol for the description of independent parallel branches. The model is created in the process of its de-scription, so it does not require further verification. If the description of the model is performed correctly and the optimal algorithm of the future program is selected, such model will fully cor-respond to its description. Unlike MODEL CHECKING technology, which requires verification, it eliminates the need for model verification. The graph of the obtained model is processed by its sequential traversal on all branches with returns to the previous states and subsequent soft-ware implementation. Consecutive traversing should be performed for each branch of the model either to its final state or to the state that has already been processed during the traversal. Model processing includes transmission of the model description into an internal representation for subsequent conversion into a program in the target procedural programming language. In this case all actions in the substantive parts of the predicates, as well as the conditions of the branches in the process of transmission are converted into an internal representation of the pro-gram. This technology provides a direct conversion of the description of the program model in-to the program itself.