Balance Transformer Research Articles

Ecological Translatology in the Translation of Ancient Chinese Poetry: A Case Study of The Departure from Baidicheng in the Morning

The paper explores the translation of Li Bai’s poem The Departure from Baidicheng in the Morning. Applying the Eco-translatology theory, it aims to analyze how different English translations—by Xu Yuanchong, Yang Xianyi and Dai Naidie, and Weng Xianliang—reflect the adaptation of language, culture, and communication in the translation process. Given “Adaptation and Selection” Idea as well as “Three-D” Theory, the paper compares the linguistic, cultural, and communicative strategies employed by these translators. The findings suggest that each translation demonstrates varying degrees of adaptation, with Xu Yuanchong’s version achieving the most balanced ecological transformation. It is also found that Eco-translatology provides valuable insights into enhancing the accuracy and cultural transmission of Chinese poetry in translation.

Risk Analysis of Regional Carbon Imbalance Based on Carbon Budget Pattern and Its Transformation Trend

Carbon budget accounting and identification of carbon imbalance risks contribute to revealing the impact mechanism and extent of human activity on the regional carbon budget. It is of great significance to conduct regional differentiated carbon governance and promote regional collaborative emission reduction. As a result, this study first constructed a research framework for regional carbon imbalance risk assessment based on carbon budget. Then, the carbon budget was calculated at a grid and county scale taking Henan Province as an example, and its spatio-temporal pattern was discussed. Finally, the regional carbon imbalance risk index was constructed to reveal the temporal and spatial evolution characteristics of carbon imbalance risk in Henan Province. The results showed： ① From 2001 to 2020, the carbon emissions in Henan Province increased from 232 million tons to 586 million tons. Spatially, it exhibited a gradually decreasing distribution pattern from the central areas to the periphery of each city. Carbon absorption showed a slight fluctuating increase trend （117 million-153 million） with a distribution feature of "higher in the west, lower in the east； higher in the south, lower in the north." ② The carbon source/sink ratio in Henan Province showed a characteristic of rapid growth followed by a gradual decline, reaching a peak of 5.14 in 2013. The carbon source/sink value in economically developed areas was significantly higher than that in economically underdeveloped areas. The regional differences in carbon balance transformation were evident, showing an overall "imbalance-neutralization-imbalance" trend. ③ During the study period, carbon imbalance risks in Henan Province gradually stabilized, and the number of districts and counties with a carbon imbalance risk index higher than 0.6 was 107 （68.2%） during 2016-2020. The high-risk areas of carbon imbalance mainly expanded from the Zhengzhou metropolitan area to the periphery along major transportation routes. ④ Future efforts should focus on establishing land spatial optimization and differentiated governance strategies, considering varying carbon imbalance risks across regions. This includes enhancing county-level cross-compensation mechanisms based on carbon imbalance risk assessments； mitigating regional carbon imbalances； and advancing regional collaborative emission reductions, carbon sequestration, and carbon neutrality goals.

Novel imbalanced fault diagnosis method based on generative adversarial networks with balancing serial CNN and Transformer (BCTGAN)

In industrial production engineering, machines cannot sustain faults for extended periods, resulting in limited fault data collection. This scarcity of data impedes the advancement of accurate fault diagnosis models, particularly in the context of small-sample, extremely imbalanced fault modeling, which poses a significant and challenging problem. In this paper, we introduce an innovative data augmentation approach for addressing the small-sample imbalanced problem: the balanced conditioning CNN (Convolutional Neural Networks)-Transformer architecture based Generative Adversarial Network (BCTGAN). Firstly, we employ a serial CNN and Transformer architecture as the foundation of the generator. Secondly, we introduce micro-enhancement and SMOTE (Synthetic Minority Oversampling Technique) enhancement of samples to facilitate model training. Micro-enhancement simply augments the sample size, while SMOTE enhancement enhances diversity. Together, these techniques balance the training process by introducing new loss function terms. Finally, outlier samples are mitigated through a designed multi-domain feature screening method. Despite the added time cost and computational complexity, results from three instances demonstrate that the proposed method holds superior diagnostic results with great potential compared to traditional and general GAN-based fault diagnosis methods. Our work provides theoretical and practical insights for modeling the field of small-sample blended disequilibrium fault diagnosis.

Investments in Fixed Capital of the Oil and Gas Region as an Indicator of Its Readiness for the Financial Embargo and Transformation of the Global Energy Balance

The financial embargo has a special impact on the economic systems of oil and gas regions. This is explained by the increased foreign trade turnover of oil and gas regions, as well as the high capital intensity of the oil and gas industry, a long period of return on financial investments, and the high profitability of innovative investments. Thepurposeof the study is to identify various aspects of the problem of investing in fixed assets in oil and gas regions, find ways, forms and methods of investment stimulation of their innovative production development and assess the possibilities of transitioning to new technological structures in the conditions of a financial embargo and the transformation of the global energy balance.Methodsof regression analysis of the structure and dynamics of investment in fixed capital of organizations in the oil and gas regions of the Volga Federal District were used and polynomial trend lines were constructed until 2030. An economic analysis of the structure of investment in fixed capital of oil and gas regions was made by sources of financing, types of fixed assets, forms of ownership, types of economic activity, as well as a regression analysis of the dynamics and forecast of the balance (receipt minus withdrawal) of foreign direct investment in oil and gas regions according to the balance of payments of the Russian Federation. Theresultof the study was the development and justification of a system of priority factors for creating a favorable investment climate in oil and gas regions to increase their resistance to the conditions of the financial embargo and the economic transformation of the global energy balance.

Dynamic–quadratic balancing: A computational approach to balancing and model reduction for affine nonlinear systems

AbstractIn this paper, we discuss a new approach to balancing (known as dynamic–quadratic balancing) and model reduction for affine nonlinear system. We give a fresh look to balancing in terms of the dynamics of the system, rather than simply a structural property. With this perspective, we also develop a new approach to obtaining the balancing transformation in one step, instead of a three‐step process as proposed in earlier methods. Further, we explore the relationship between quadratic balancing and input–output stability. In addition, we also develop a computational approach for obtaining the balancing transformation by solving a coupled system of PDEs or inequalities (Lyapunov/Hamilton–Jacobi type). After that, model reduction can be carried out in the conventional way using Hankel singular‐value functions or using a new criterion. Finally, we present some examples to clarify the results.

An adaptive controller for power quality control in high speed railway with electric locomotives with asynchronous traction motors

Introduction. Power quality in an electric railway system pertains to the dependability, consistency, and purity of the electrical power provided to different components and systems within the railway infrastructure. Assessing power quality offers considerable opportunities to improve the efficiency of railway systems. Problem. Managing the flow of active and reactive power effectively, decreasing harmonic currents, and addressing the negative sequence component are all critical parts of improving power quality for electrified rail systems. As a result, flexible AC transmission systems are the major means of minimizing or decreasing these difficulties. Purpose. This study describes a half-bridge reactive power railway power conditioner (HB-RPC) with a novel Ynev balancing transformer. HB-RPC is made up of four switching devices and two DC capacitors and the compensator’s stability is determined by the operating voltage of the DC-link. Any variations or imbalances in the DC voltage might cause the compensator to operate in an unstable manner. Novelty. Of a novel balanced transformer with HB-RPC in a high-speed railway system with two scenarios. Methods. The study utilized MATLAB/Simulink software for simulation purposes. The system integrates a fuzzy logic controller (FLC) and a PI controller to optimize DC voltage, ensuring its constancy and balance, with the objective of improving the overall stability of the system. Results. The simulation outcomes illustrate the efficacy of the control approach. Through a comparison of results between scenarios (two and four trains) with the PI-based-HB-RPC and the FLC-based-HB-RPC, the system exhibits enhanced stability for the proposed railway system when employing the FLC-based-HB-RPC, compared to a controller based on PI. Practical value. The proposed configuration elucidates its role in enhancing both the dynamic performance of the system and the power quality of the three-phase rail traction chain.

Balanced transformer: efficient classification of glioblastoma and primary central nervous system lymphoma

Objective. Primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM) are malignant primary brain tumors with different biological characteristics. Great differences exist between the treatment strategies of PCNSL and GBM. Thus, accurately distinguishing between PCNSL and GBM before surgery is very important for guiding neurosurgery. At present, the spinal fluid of patients is commonly extracted to find tumor markers for diagnosis. However, this method not only causes secondary injury to patients, but also easily delays treatment. Although diagnosis using radiology images is non-invasive, the morphological features and texture features of the two in magnetic resonance imaging (MRI) are quite similar, making distinction with human eyes and image diagnosis very difficult. In order to solve the problem of insufficient number of samples and sample imbalance, we used data augmentation and balanced sample sampling methods. Conventional Transformer networks use patch segmentation operations to divide images into small patches, but the lack of communication between patches leads to unbalanced data layers. Approach. To address this problem, we propose a balanced patch embedding approach that extracts high-level semantic information by reducing the feature dimensionality and maintaining the geometric variation invariance of the features. This approach balances the interactions between the information and improves the representativeness of the data. To further address the imbalance problem, the balanced patch partition method is proposed to increase the receptive field by sampling the four corners of the sliding window and introducing a linear encoding component without increasing the computational effort, and designed a new balanced loss function. Main results. Benefiting from the overall balance design, we conducted an experiment using Balanced Transformer and obtained an accuracy of 99.89%, sensitivity of 99.74%, specificity of 99.73% and AUC of 99.19%, which is far higher than the previous results (accuracy of 89.6% ∼ 96.8%, sensitivity of 74.3% ∼ 91.3%, specificity of 88.9% ∼ 96.02% and AUC of 87.8% ∼ 94.9%). Significance. This study can accurately distinguish PCNSL and GBM before surgery. Because GBM is a common type of malignant tumor, the 1% improvement in accuracy has saved many patients and reduced treatment times considerably. Thus, it can provide doctors with a good basis for auxiliary diagnosis.

Isolated Bidirectional DC–DC Converter for SuperCapacitor Applications

This paper proposes a new bidirectional DC/DC converter for supercapacitor applications. The proposed converter has a parallel structure in supercapacitor side (where voltage is low and current is high) and a series structure in the other side. This structure increases efficiency of the converter. For current sharing in the parallel side of the proposed converter, two different methods are recommended and compared in this paper: Current balancing transformer (CBT) and two separate inductors (TSI). Simulation and experimental results show performance of the proposed converter.

ТРАНСФОРМАЦИЯ РОССИЙСКОГО ЭНЕРГОБАЛАНСА В КОНТЕКСТЕ ВКЛЮЧЕНИЯ ВОДОРОДА В МИРОВОЙ ЭНЕРГОБАЛАНС

The purpose of the article is to analyze the prospects for the development of hydrogen energy in Russia in the context of the transformation of the global energy balance. The article examines the current state of the Russian energy balance and the factors influencing its development directions, analyzes hydrogen production projects, and describes the investment component of the optimal scenario for the transformation of the energy balance in the Russian Federation in connection with the development of hydrogen energy. It is determined that the development of hydrogen energy in the Russian Federation is conditioned by the need to ensure energy security and national technological sovereignty. In addition, the development of low-carbon energy sources contributes to the diversification of the country’s fuel energy balance and the reduction of its carbon footprint in the global economy. In the conclusions of the article, proposals are formulated for the transformation of the energy balance of the Russian Federation, taking into account the possible inclusion of hydrogen in the global energy balance.

MAIN ASPECTS OF THE TRANSFORMATION OF WORLD TRADE REGIMES AT THE PRESENT STAGE

The article is devoted to the analysis of key aspects of the transformation of world trade regimes at the current stage, such as digital commerce, regional trade agreements, protectionism, trade exchange of services, global supply chains and protection of innovative technologies for international economic stability. It is proved that the study of modern trends and transformations of the world economy is an actual theoretical and applied task, which involves the systematic consolidation of methods and mechanisms of interdisciplinary research. Important factor in modern conditions of globalization of trade relations is the use of information technologies, they become the determining factors of victory in the competitive struggle, it allows you to break traditional supply chains and move to the future. Implementation of digital technologies contributes to significant improvement of business results and significantly accelerates strategic changes in the development of world trade. It is summarized that until recently globalization processes were characterized as stable, mostly positive. But at the current stage, it became clear that the processes of transformation are linear in nature and largely depend on the geopolitical situation in the world, the cyclical nature of global economic development, the geographical location and structure of the economy of the countries of the world. The transformation of the management trade balance changes the form and content of world trade regimes .Accordingly, predicting the future, we understand that we cannot give even approximate calculations or make a more or less accurate analysis. The economic interdependence of different countries should be a guarantee of financial success, but in recent decades it has increasingly transformed and turned into something unusual in world trade. The main focus is on the discussion of forecasts for the current year 2024 of international organizations such as the World Trade Organization (WTO) and the World Trade Organization (WTO), which play a key role in regulating trade relations at this stage.

Learnable Leakage and Onset-Spiking Self-Attention in SNNs with Local Error Signals.

Spiking neural networks (SNNs) have garnered significant attention due to their computational patterns resembling biological neural networks. However, when it comes to deep SNNs, how to focus on critical information effectively and achieve a balanced feature transformation both temporally and spatially becomes a critical challenge. To address these challenges, our research is centered around two aspects: structure and strategy. Structurally, we optimize the leaky integrate-and-fire (LIF) neuron to enable the leakage coefficient to be learnable, thus making it better suited for contemporary applications. Furthermore, the self-attention mechanism is introduced at the initial time step to ensure improved focus and processing. Strategically, we propose a new normalization method anchored on the learnable leakage coefficient (LLC) and introduce a local loss signal strategy to enhance the SNN's training efficiency and adaptability. The effectiveness and performance of our proposed methods are validated on the MNIST, FashionMNIST, and CIFAR-10 datasets. Experimental results show that our model presents a superior, high-accuracy performance in just eight time steps. In summary, our research provides fresh insights into the structure and strategy of SNNs, paving the way for their efficient and robust application in practical scenarios.

Design of An Agricultural Extension Schedule Management System

Based on the strategic plan of the Ministry of Agriculture for 2015-2019, development in the agricultural sector will refer to the Agriculture for Development Paradigm which positions the agricultural sector as a driver of balanced and comprehensive development transformation including demographic, economic, intersectoral, spatial, institutional and development governance. With such great potential, the Pasuruan Regency Food and Agriculture Security Service has problems in the availability of human resources in quantity, especially agricultural instructors. For this reason, there is a need for a system that can optimize existing human resources. The system development method used is the waterfall method, the waterfall method is a method that works sequentially, the development of the agricultural extension schedule management system has been going well. So that it can help the work management process of agricultural instructors in distributing agricultural extension at the village level. This agricultural extension schedule management system is implemented using a MySQL database and the PHP programming language. This system is easy to use so it helps related parties in schedule management and recording extension activities.

Experimental linear parameter-varying model identification of an elastic kinetic roof structure

Elastic kinetic structures are a recent approach to design transformable lightweight structures. Their transformation is based on elastic bending, exploiting the compliant material behavior of the structural members. This enables transformable structures with a stable transformation process. However, due to their lightweight and flexible design, elastic kinetic structures are highly sensitive to static and dynamic disturbances. Moreover, such transformable structures exhibit a transformation state dependent dynamic behavior, due to geometric nonlinearities. Nevertheless, most of current research focuses on the principles of elastic kinetic transformation than on effective disturbance mitigation. The latter is usually designed based on low-order control-oriented models. This paper describes a system identification methodology, suitable to identify low-order models for the transformation state dependent dynamics of elastic kinetic structures. The system identification is carried out using a local approach in the linear parameter-varying (LPV) framework. For the identification of local linear time-invariant (LTI) models, the system realization using the information matrix (SRIM) method is applied. The collection of local LTI models is internally balanced using a balancing transformation, in order to represent the locally estimated models with respect to a common state–space basis. Via linear interpolation, an LPV system in grid-based representation is derived. This methodology is experimentally validated with data from an active hybrid roof structure prototype.

A Novel Co-phase Traction Power Supply System in Electrified Railway

The electrified railway has power quality problems such as three phases seriously unbalanced, large harmonics, and reactive power. In addition, the neutral section exists at each power supply section, which restricts the development of the high-speed and heavy-haul railway. This paper proposes a novel co-phase traction power supply system (TPSS) based on a YNvd balanced transformer, which can not only solve the above problems but also save one single-phase coupling step-down transformer, thus reducing the cost and space of the whole system. In addition, the voltage level of the converter switching device can be reduced by the rational design of the transformer tap position, which enhances the reliability and feasibility of the system. The compensation principle and control strategy of the co-phase TPSS based on the novel YNvd balanced transformer are analyzed in detail in this paper, and the compensation current detection and integrated power flow controller (IPFC) control methods are given. Simulation and analysis show that the proposed topology structure and control method are correct and feasible.

Food and Beverage Management: Trends, Innovations, and Challenges

This paper is woven with dynamic trends, pioneering innovations, and formidable challenges, explored in the study of food and beverage management: trends, innovations, and challenges. Through an extensive literature review, the research traces F&B Management's evolution within the connection of culinary arts, hospitality, and business acumen, establishing a comprehensive foundation for understanding core concepts. Employing a mixed-methods approach, the study captures insights from professionals and discerning consumers, unveiling trends like sustainability and experiential dining, where 72% and 65% of respondents, respectively, emphasize preferences for locally sourced ingredients and immersive dining. Technological innovations play a pivotal role, with 42% of respondents favoring AI-driven personalized menu recommendations, and 58% desiring tech-enhanced customer convenience. Amid challenges such as labor shortages and health regulations, the industry exhibits adaptability and resilience, embracing mentorship and technology-driven solutions. It offers a panoramic view of an industry balancing tradition and transformation, guiding practitioners, researchers, and stakeholders through an ever-evolving landscape.

Essential and substantive features of balanced spatial development of rural areas: national and global aspects

The article examines theoretical and conceptual approaches to understanding the balanced spatial development of rural areas in the context of transformational economic processes in the agricultural sector of Ukraine and global environmental challenges. The purpose of the study is to further form a systematic view of balanced sustainable development of rural areas with an emphasis on the specifics of agrarian natural resource management. The essence of the economic space of rural areas is revealed through the peculiarities of balanced agricultural management, as well as the use of natural resource potential, in particular, land and resource potential. A system of socio-ecological, economic and institutional directions of management of a conceptual nature has been formed in order to intensify the balanced and continuous transformation of the economic space of rural areas. The developed conceptual directions are a prerequisite for ensuring the economisation and ecologisation of the territorial-spatial organisation of the rational use and reproduction of agricultural potential (in particular, land and resource, natural resource). Particular attention is paid to the issues of determining the structural and functional construction of the space of rural areas on the basis of balanced agricultural management. The proposed structuring of the economic space of agriculture by various criteria is a generalised characteristic of the balanced spatial development of rural areas. The characteristics by means of which the economic space of rural areas receives its qualitative definition (capacity, saturation, density, development, connectivity, tension) are given.

A VHF Circularly Polarized Turnstile Antenna with Balun for Meteor Radar

This paper presents a circularly polarized turnstile antenna for a meteor radar system. The antenna employs a pair of turnstile radiators, a 1:2 power divider and a 90° phase shifter. After a series of simulations and optimizations, the maximum circularly polarized gain at 39 MHz is 5.9 dBic with 96° 3 dB beam width. The simulated axial ratio below 3 dB is from −39° to 39° within the band of interest. Then, the proposed antenna is fabricated and applied to a meteor radar system. Two tests are carried out for radiation characteristics demonstration. In the first test, the VSWR of the proposed antenna is below 1.2 at 38.5–39.5 MHz and keeps good agreement with simulation results. However, the meteor azimuth distribution is illogical when the output results are compared with the Australian meteor detection radar (ATRAD) meteor detection. To address the problem, baluns are investigated and introduced for balanced feeding. The 1:1 unbalance–balance transformer has been used to improve the radiation characteristics of the designed antenna. The final test results show that the meteor radar system with the improved antenna achieves better performances in meteor counts and meteor azimuth distribution.

Franco-Russian Great Power Rivalry in the Sahara-Sahel Region

The confrontation between Paris and Moscow, which commenced at the end of last decade in the Sahara-Sahel region, is largely a consequence of the weaknesses of the French foreign policy in the region, which Russia strives to exploit to its political and economic benefit. The hotspots of this confrontation are Libya and Mali, where the Franco-Russian rivalry has led to the global securitization of the conflict (in both countries), transformation of the regional balance of power (in Libya), and the aggravation of existing security problems (in Mali). Overall, the Franco-Russian rivalry in the Sahara-Sahel region is a phenomenon of the upcoming age of multipolarity and a new Scramble for Africa.

АНАЛИЗ СТРАТЕГИЙ ЦИФРОВОЙ ТРАНСФОРМАЦИИ РЕГИОНОВ РОССИИ В КОНТЕКСТЕ ДОСТИЖЕНИЯ НАЦИОНАЛЬНЫХ ЦЕЛЕЙ

The article analyzes the planned estimates of digital maturity indicators from 2022 to 2024 for 82 Russian regions, which are calculated on the basis of regional digital transformation strategies. The indicators are determined by the methodology of the Ministry of Digital Development, Communications and Mass Media of the Russian Federation. Based on these indicators, a planned index of digital maturity was determined for five key industries in each of the regions of Russia under consideration: education, healthcare, public administration, public transport and urban economy. It is shown that the expected rate of digital transformation in different industries will vary significantly. In the regions, there have been identified advanced, medium-high, medium-low and lagging regions in the field of digital transformation for the planned period. Based on the results of the study, the authors recommend creating a comprehensive federal program to help increase the digital maturity index in lagging industries, which will solve the problem of digital transformation imbalance and the problem of lagging regions. For three regions from each category ways are proposed for redistributing resources and capacities to increase the rate of digital transformation in lagging industries from the standpoint of balanced digital transformation, taking into account growth dynamics from 2022 to 2024.

Обоснование необходимости реинжиниринга бизнес-процессов на предприятиях российского ТЭК

The article considers the application of the process approach in the management of enterprises of the fuel and energy complex. In conditions when the fuel and energy sector plays a key role in the economy of a country like Russia, with increased uncertainty and complexity of forecasting changes in the external environment, it is necessary to develop new approaches to managing business processes in this area. The rapid transformation of the global balance in the energy market, the redistribution of forces and gravity points taking place at the moment, set new development goals for the entire industry as a whole and for individual companies. We should not lose sight of the sanctions pressure caused by the escalated political confrontation between Russia and Western countries.
 It is proposed to identify key business processes at fuel and energy complex enterprises and to justify methodological approaches to their reengineering, taking into account the specifics of the industry and the need for a qualitative change in the behavior model of fuel and energy complex enterprises in new macroeconomic conditions.