Development Of System Research Articles

Intensification of Trade Interactions between the Regions of China and Russia

The article identifies the Chinese provinces that are the points of growth of the Russian imports. Their main supply channels to the Chinese market are concentrated in the eastern coastal regions of China, being traditionally more developed. Russian imports are growing faster through the Chinese pilot free trade zones. However, geographical and product diversification is still slow. The supply structure of Russian products is still dominated by raw materials, while imports of high value added products are growing rapidly in some regions of China. The rapid growth of Russian imports is observed in some regions of the Yangtze River Economic Belt, which creates additional opportunities for the intensification of trade interactions with the Russian regions within the project «Volga-Yangtze». The connection of the export sectors of the economy of the Volga Federal District with the import of China is considered in more detail in the article as a potential for further intensification of trade interactions. The regions with a high level of economic diversification (the Nizhny Novgorod and the Samara regions) have the greatest opportunities for developing trade interactions. Current conditions indicate that prospects for the further intensification of Russian exports to China are determined by the expansion of production (in the regions with a high share of exports to China and other friendly countries), development of transport and logistics system, adaptation of Russian products to the needs of the Chinese consumer. One way to increase exports of Rus-sian high-value-added products is to reduce barriers to the supply of such products in China’s free-trade zones. In a limited international market, Russian regions may have to compete more for Chinese consumers as the domestic market becomes saturated.

Reform of the Preliminary Ruling Procedure in the EU Court System

In 2022, the Court of Justice of the European Union announced a new stage of reform of its system. In the face of an increase in the number of cases under consideration it is designed to maintain a professional and thorough approach to disputes resolution while reducing the time of legal proceedings. The changes are based on the new competence of the General Court to deal with requests under preliminary ruling procedure and certain other categories of disputes, as well as obtaining more freedom in matters of internal organization and the establishment of a permanent position of Advocate General. Taking into account the scientific and educational literature already published in Russia on the basics of the Court of Justice of the EU, the authors focused their attention on current issues and prospects for the development of the EU judicial system. The purpose of the article is a doctrinal study of the reasons that led to this reform, an analysis of the final text of the agreed draft regulation, as well as an overview of the measures that were implemented by the European Court of Justice at earlier stages and the reasons why they were insufficient. The authors consider new categories of cases, procedural guarantees to maintain uniformity of judicial practice and the stages of discussion of the draft regulation, which took place in 2023 in the EU institutions responsible for the adoption of the new legislation.

Determining Resident Status for Taxation in the USA

This paper examines international taxation practices, in particular focusing on the taxation of individuals as well as tax tools used in industrialized countries to optimize tax collection and stimulate economic development. It is also directly relevant for representatives of ministries and departments involved in managing the state budget. The experience of the United States, with its developed and comprehensive tax control system, could be useful in organizing more effective taxation of foreign individuals, including migrant workers residing on the territory of the Russian Federation.

Governing authority through bureaucracy: conflicts over bureaucratic cadres and the rise of authoritarianism in the late Ottoman Empire (1908–1913)

ABSTRACT This article presents a historical analysis of how internal power struggles and conflicts among state actors can foster the development of authoritarian systems, particularly when a political network gains exclusive control over the bureaucratic apparatus through its authority over appointments and dismissals. Focusing on the intricate power struggles and factional rivalries surrounding gubernatorial appointments between 1908 and 1913, this article aims to provide an alternative approach to understanding how the Committee of Union and Progress (CUP) became the dominant governing force within the state apparatus, enabling it to pursue an authoritarian agenda.

Development of a Portable Ozone Generation System for Calibration of Online Ozone Water Analyzers

ABSTRACT Ozone water, serving as a disinfectant, plays a significant role in the production of medical, food, and sanitation sectors. However, due to the instability of ozone water, it needs to be produced and used simultaneously in practical applications. It leads to a series of technical challenges. They include the lack of standard ozone water solutions. To address them, this study designs and constructs a new calibration system for online ozone water analyzers with controllable concentrations. This system has been successfully applied to the calibration of online ozone water analyzers from different manufacturers and models available. The concentration values of ozone water were verified using the chemical iodometric method. Calibration results showed that the indication error of the online ozone water analyzers ranged from 0.04 mg/L to 0.07 mg/L, the repeatability was between 0.0% and 4.1%, and the stability ranged from 2% to 9%. This study not only provides an effective solution for the calibration of online ozone water analyzers but also contributes to the standardization and quality control in related fields through the design and implementation of the system.

Slovak database of speech affected by neurodegenerative diseases

A new Slovak speech database EWA-DB was created for research purposes aimed at early detection of neurodegenerative diseases from speech. It contains 1649 speakers performing various speech and language tasks, such as sustained vowel phonation, diadochokinesis, naming and picture description. The sample of speakers consists of individuals with Alzheimer’s disease, mild cognitive impairment, Parkinson’s disease, and healthy controls. In this article we describe the EWA-DB development process, the language and speech task selection, patient and healthy control recruitment, as well as the testing and recording protocol. The structure and content of the database and file formats are described in detail. We assume that the presented database could be suitable for the development of automatic systems predicting the diagnoses of Alzheimer’s disease, mild cognitive impairment, and Parkinson’s disease from language and speech features.

Development of funnel-type fluidized bed reactor system using microcarriers for cultures of adherent cells

Development of funnel-type fluidized bed reactor system using microcarriers for cultures of adherent cells

How Accurate Are QM/MM Models?

Despite the success and widespread use of QM/MM methods in modeling (bio)chemically important processes, their accuracy is still not well understood. A key reason is because these methods are ultimately approximations to direct QM calculations of very large systems, which are impractical to perform in most cases. We highlight recent progress toward the development of realistic model systems where it is possible to obtain full QM reference data to directly and systematically evaluate the effectiveness of different QM/MM generation schemes. These model systems are highly flexible and can be tailored to probe the sensitivity of a QM/MM model to different reaction types and simulation parameters such as pairing of QM and MM potentials, QM region size, and composition. It is envisaged that this strategy could be used to directly validate different QM/MM generation schemes and spur the development of more robust models in the future.

An advanced retrieval-augmented generation system for manufacturing quality control

The rise of Large Language Models (LLMs) with generative artificial intelligence has revolutionized the development of knowledge-based systems, enabling intuitive interactions through natural language. This paper explores the implementation of an advanced Retrieval-Augmented Generation (RAG) system, designed to improve manufacturing quality control by utilizing the capabilities of LLMs, particularly OpenAI’s GPT models. We focus on the ceramic tile manufacturing process, where the system retrieves and analyzes specialized bibliographic sources to diagnose defects and propose solutions. In addition to core RAG functionalities, the system incorporates tailored pre-processing and post-processing mechanisms to optimize document retrieval and response generation. The system’s effectiveness in solving quality issues is demonstrated through its application in identifying defect causes and generating actionable solutions, significantly improving non-conformities management. This approach not only streamlines troubleshooting but also enhances the quality control system, providing a comprehensive, scalable tool for manufacturers.

Development of an oral cancer detection system through deep learning

ObjectiveWe aimed to develop an AI-based model that uses a portable electronic oral endoscope to capture intraoral images of patients for the detection of oral cancer.Subjects and methodsFrom September 2019 to October 2023, 205 high-quality annotated images of oral cancer were collected using a portable oral electronic endoscope at the Chinese PLA General Hospital for this study. The U-Net and ResNet-34 deep learning models were employed for oral cancer detection. The performance of these models was evaluated using several metrics: Dice coefficient, Intersection over Union (IoU), Loss, Precision, Recall, and F1 Score.ResultsDuring the algorithm model training phase, the Dice values were approximately 0.8, the Loss values were close to 0, and the IoU values were around 0.7. In the validation phase, the highest Dice values ranged between 0.4 and 0.5, while the Loss values increased, and the training loss began to decrease gradually. In the test phase, the model achieved a maximum Precision of 0.96 with a confidence threshold of 0.990. Additionally, with a confidence threshold of 0.010, the highest F1 score reached was 0.58.ConclusionThis study provides an initial demonstration of the potential of deep learning models in identifying oral cancer.

The genetic landscape of autism spectrum disorder in an ancestrally diverse cohort

Autism spectrum disorder (ASD) comprises neurodevelopmental disorders with wide variability in genetic causes and phenotypes, making it challenging to pinpoint causal genes. We performed whole exome sequencing on a modest, ancestrally diverse cohort of 195 families, including 754 individuals (222 with ASD), and identified 38,834 novel private variants. In 68 individuals with ASD (~30%), we identified 92 potentially pathogenic variants in 73 known genes, including BCORL1, CDKL5, CHAMP1, KAT6A, MECP2, and SETD1B. Additionally, we identified 158 potentially pathogenic variants in 120 candidate genes, including DLG3, GABRQ, KALRN, KCTD16, and SLC8A3. We also found 34 copy number variants in 31 individuals overlapping known ASD loci. Our work expands the catalog of ASD genetics by identifying hundreds of variants across diverse ancestral backgrounds, highlighting convergence on nervous system development and signal transduction. These findings provide insights into the genetic underpinnings of ASD and inform molecular diagnosis and potential therapeutic targets.

Coupling-Coordination Analysis of Water Resources–Social Economy–Ecological Environment in the Yellow River Golden Triangle Area

Water resources, the social economy, and the ecological environment are interrelated and interacting complex systems, and the relationship among them affects the sustainable development of a region. To explore the interactive relationship and driving factors between water resources, the social economy, and the ecological environment, the Yellow River Golden Triangle region is taken as the research object in this paper. By constructing a coupling-coordination evaluation index system of water resources, the social economy, and the ecological environment system, the coupling-coordination development of this region from 2011 to 2021 is studied using the coupling-coordination degree model, and the influencing factors of coupling-coordination development are identified by gray relational analysis. The results show that from 2011 to 2021, the comprehensive evaluation index of the water resources, social economy, and ecological environment in the Yellow River Golden Triangle region shows a trend of steady development followed by a gradual increase. The water-resources subsystem restricts the development of the coupling system. The coupling-coordination degree increased from a barely coordinated stage in 2011 to a well-coordinated stage in 2021. The social economy subsystem and water-resources subsystem are the main factors affecting the coordinated development of the coupling system.

Regulation of the physicochemical properties of nutrient solution in hydroponic system based on the CatBoost model

Too high or low nutrient solution concentrations adversely affect hydroponic vegetables’ growth and yield performance. In addition, the temperature of the solution and the dissolved oxygen (DO) content of the water are critical factors. A real-time regulation model for nutrient solutions based on the CatBoost model was developed to address the issues of low automation and accuracy of nutrient solution configuration and management. The pH, electric conductivity (EC) and DO of the nutrient solution, and the corresponding water temperature of 96 groups of hydroponic lettuce nutrient solutions (KNO3, MgSO4, Ca(NO3)2, KH2PO4, NH4H2PO4, and microfertilizer) were measured using a gradient combination test designed according to the formula of hydroponic lettuce nutrient solution. A prediction model of the nutrient solution index was constructed using a gradient-enhanced decision tree algorithm and the accuracies of the random forest, XGBoost, and CatBoost algorithms were compared. The results show that the root mean square error (RMSE), mean absolute error (MAE) and coefficient of determination (R2) of the simulated and measured values of the EC prediction model established by the CatBoost model were 248.28 µS/cm, 203.19 µS/cm and 0.946, respectively. At the same time, it was found that the hydroponic variable fertilization control system, composed of four modules–data acquisition, data decision, field control, and manual control–could predict the EC and pH value changes of the nutrient solution and timely add compounds for control. The application of nutrients based on the developed system was good and the weight of the cream lettuce (Flandria RZ) grown using the system was more than 200 g, which meets the requirement for high-quality cream lettuce production. Therefore, the CatBoost model system can be used to improve the hydroponic production system of vegetables by managing nutrients effectively.

Affinity purification of the outer hair cell motor protein prestin using His-tag

ObjectiveThe high sensitivity and broad frequency selectivity of mammalian hearing are associated with the somatic motility of outer hair cells (OHCs) in the cochlea. This motility is considered to be induced by conformational changes of the motor protein prestin expressing in the lateral plasma membrane of OHCs. Since its identification in 2000, prestin has been actively investigated and its structure and function have gradually been elucidated. These successes are partly due to the development of efficient expression and purification system of the membrane proteins including prestin. To obtain further understandings of prestin, the development of various types of such systems will be essential. However, recent study protocols on membrane proteins have often employed HEK293 cells and have become complexed with expression genes carrying several proteins and peptides for stabilization and purification of the expressed proteins. In the present study, a simple expression and purification system using Chinese hamster ovary (CHO) cells and Hi-tag was developed. MethodsFull length gerbil prestin was transfected into modified mammalian expression vectors with C-terminal 6 × His-tag. After drug selection with G418 for 4 weeks, single colonies were isolated by limiting dilution method. Cell lines highly expressing prestin were selected (named 3D5, 4D7 and 3C8). These cells were gently disrupted using a Dounce tissue grinder. Membrane fractions were extracted by ultracentrifugation and affinity chromatography was performed. The efficiency of the purification process was evaluated by quantitative Western blotting using a standard protein. ResultsAmong the cell lines constructed, Western blotting analysis showed bands at around 100 kDa and the highest intensity was confirmed from the 3C8 cell line, indicating that this cell line has the highest expression of prestin molecules. The membrane fraction was therefore extracted from this cell line and subjected to the following purification procedure. It was found that 78.7 μg of prestin was purified from 2.0 × 109 CHO cells. ConclusionIn the present study, 78.7 μg of prestin was purified from 2.0 × 109 CHO cells, which stably expressing 6 × His-tagged prestin, by extracting cell membrane fractions and standard affinity chromatography for His-tag.

Experimental and numerical investigation of a novel inlet for boundary layer ingesting propulsion systems

Boundary Layer Ingestion (BLI) propulsion systems have the potential to significantly enhance aircraft performance, particularly by improving fuel efficiency and reducing emissions. However, the high total pressure losses and distortions at the outlet of the BLI inlet normally restricts the development of BLI propulsion systems. This paper introduces and investigates a high-performance dual-sided BLI inlet configuration suitable for a large amount of boundary layer ingesting through a combination of computational and experimental methods. The dual-sided BLI inlet has two air entrances located at the top and bottom of the aircraft's rear fuselage, with the two ducts from the upper and lower inlets deflecting towards each other and converging at the same annular outlet. Simulation results indicate that the dual-sided BLI inlet prevents the concentration of low-energy flow observed with single-sided inlets, thereby reducing outlet distortion. Additionally, high-speed wind tunnel tests were conducted to validate the design's feasibility. The test results indicate that the dual-sided BLI inlet demonstrates good performance at the design point (Mfar=0.75, MAIP=0.50, δ/h≈45 %). The total pressure recovery coefficient σfar=0.907 and σin=0.995, the outlet total pressure distortion index DC60=0.24, and the outlet swirl intensity is minor. In conclusion, the novel BLI inlet maintains robust performance under designed conditions, fulfilling the engine's stability requirements.

How different levels of semantic segmentation affect human perception of driving scenes

As automated vehicles continue to advance, teleoperation has emerged as a critical support system for navigating complex and unpredictable environments that exceed the vehicles' current autonomous capabilities. A main issue in the implementation of teleoperation is latency caused by the high bandwidth required to transmit the video feed from the vehicle to the remote teleoperation station. A possible approach for addressing the latency problem is the transfer of lower-resolution or compressed videos between the vehicle and the teleoperation station. When applying semantic segmentation on the video feed, many pixels are mapped to a limited set of possible colors according to the types of objects that they represent. This concept has been commonly used in autonomous driving algorithms and has the potential to enable the transferring of smaller-sized videos thus reducing bandwidth. In this study, we examine how presenting semantically segmented driving scenes to humans affects their perception of the scene, and specifically, how it affects their hazard perception and situation awareness. We conducted two user studies comparing the effects of using different levels and types of semantic segmentation. Our results indicate that viewing partly segmented scenes, such that only a selected set of object types are colored, commonly achieves the same effect, and sometimes even outperforms a realistic view. Our study and its insights may pave the way for future research, development, and design of teleoperation systems of automated vehicles.

Time-division multiplexing cascaded active phase-locking method for an all-fiber coherent beam combining system

Coherent beam combining (CBC) is an effective approach to exceed the power limitation of fiber lasers by combining multiple laser sources. Phase-locking is one of the important steps in an active CBC system. Many phase-locking methods have already been developed and have effectively achieved phase control. Generally, the phase control bandwidth decreases accordingly as the number of combined lasers increases. This will hamper the development of CBC systems to larger scales. At the same time, the structure of traditional tiled-aperture CBC systems is also a potential limiting factor in the aspect of feedback configuration. An all-fiber CBC structure based on active phase control can avoid physical size limitations on traditional structures and greatly expand the scale of tiled-aperture CBC arrays to over tens of thousands of sub-beams. In such a large array scale, existing phase control methods will inevitably encounter the problem of bandwidth reduction. To solve this problem, we propose a time-division multiplexing cascaded (TDMC) active phase-locking method in this paper. Simulation studies on phase control of over 10,000 laser beams are conducted. The method shows huge bandwidth enhancement in control phases of a large number of lasers. This will lay the technological foundation for further expanding the number of an all-fiber tiled-aperture array.

A Critical Look at the Evolution of Flow Analysis

The inception of flow analysis (FA) is closely related to the need for a better understanding of chemical reactions. At the beginning of the last century, these reactions were intensively investigated, and the main involved parameters were the reactant amounts and the available reaction time.¹ It was soon realized that solution mixing and detection were often time-dependent, so they were better accomplished on a fluidic basis.² This stimulated the development of simple flow-based instruments³ that allowed chemical reactions to be more efficiently investigated. The availability of commercial colorimetric detectors in the 1930s4 increased the demand for chemical analysis and, thus, the laboratory workload. This motivated the proposal of the AutoAnalyzer®, the first commercial air-segmented flow analyzer.5 It was intensively used for large-scale assays, persisted for several decades, and involved only a few manufacturing companies. As the implementation of official, recommended, or tentative methods was preferred, the AutoAnalyzer underwent a relatively slow evolution yet an amazing worldwide acceptance. Later on, flow analyzers without segmentation were proposed.6 An example is the flow injection analyzer, which involves precise sample insertion, controlled dispersion, and reproducible timing. Exploitation of these features improved the simplicity, versatility, and flexibility of the analyzer. Further evolution led to the emergence of the sequential injection analyzer and derived ones, which occasionally involved segmented and unsegmented streams. Nowadays, flow analysis is approaching maturity, as evidenced by the number of applications, books, book chapters, tutorials, thesis, academic courses, workshops, scientific articles, events, seminars, commercially available instruments (some of them specially designed for educational purposes), patents, etc. Intensive development of expert flow systems,7 usually exploiting manifold programming,8 is underway. Micro-flow analyzers are also being proposed, especially for large-scale assays under laboratory, in-situ and in-vivo conditions. Compliance with the principles of Green9 and White10 Analytical Chemistry has always been a positive factor for FA development. For a FA healthy evolution, inertia or setback should be avoided, and synergy rather than divergence should be ensured. To this end, flashback and consensus are relevant. Flashback permits the evaluation a particular situation in the past, whereas consensus is more related to future developments.

Follow-up supportive policies and risk perception influence livelihood adaptation of anti-poverty relocated households in ethnic mountains of southwest China

The poverty alleviation relocation program (PAR) is a milestone project in breaking spatial poverty traps in ethnic mountainous regions and provides a key solution for eradicating global absolute poverty. As direct participants in the restructuring of environmental and livelihood systems, the livelihood adaptation of relocated households is fundamental to the sustainable development of human-land systems in resettlement sites and the consolidation of the success of poverty alleviation. This research constructs an adaptive integration analysis framework of “external disturbance-adaptation process-adaptation outcome”, by utilizing questionnaire data from relocated households in the Liangshan Yi minority area of Southwest China, and employing a formative structural equation model to investigate the transmission mechanisms and heterogeneous effects of PAR on livelihood adaptation across different resettlement characteristics. The results indicate that: (1) External disturbance of PAR facilitates positive adaptation outcomes, with follow-up supportive policy as the most significant determinant, which contributes directly to adaptation outcomes and indirectly through improved learning and self-organization capacity. Conversely, risk perception has a negative impact on adaptation outcomes and further exacerbates adverse impacts by reducing buffering capacity. (2) The pathways influencing subjective and objective adaptation outcomes demonstrate heterogeneity. PAR has a positive impact on subjective adaptation, but a non-significant effect on objective adaptation, self-organization capacity and buffering capacity are the most important direct drivers and mediating variables affecting both, respectively. (3) Resettlement characteristics exert a moderating effect on livelihood adaptation. The positive effect of follow-up supportive policy on learning capacity and the marginal contribution of learning capacity to adaptative strategies being greater in mid-to-long-term resettlements. Buffering capacity of village resettlements and subjective adaptation of town resettlements are more beneficial from follow-up supportive policy.

The Design of a Good Data Processing App Applying QR Code

Designing a good data processing application using QR Codes aims to increase efficiency and accuracy in data management. QR codes are a fast and easy technology for storing and scanning data, allowing users to quickly access information without entering data manually. This application is designed for various purposes, such as inventory, time and attendance management, and document tracking. The application design process includes user needs analysis, interface design, back-end development, and integration with QR code technology. The prototype method is used during the system development stage. The programming language used is a hypertext preprocessor with a MySQL database, and a framework is used to ensure that the application behaves as expected and can provide effective solutions in data processing. The results of this design are expected to significantly contribute to operational efficiency, reduce human error in data entry, and increase the speed of accessing and managing information. Apart from that, implementing QR codes in data processing applications is hoped to be widely used in various industries and business fields.