Optimal Structure Research Articles

Growing evolutional deep echo state network

Deep echo state network (Deep ESN) is a powerful method for time-series prediction, but developing the optimal structure of Deep ESN remains challenging. A novel generative framework, growing evolutional Deep ESN (GE Deep ESN) is proposed, where networks are generated through alternating growth and evolution. A model compression method is implemented during the evolution phase to optimize the inner structure of the reservoirs, and to automatically determine reservoir size. A simple termination criterion of growth is introduced to determine network depth. The feasibility and superiority of GE Deep ESN were validated experimentally with two benchmark prediction tasks. For real-time trajectory prediction in photoelectric tracking systems, an iterative learning model based on GE Deep ESN is proposed, the real time prediction result showed that network evolution enhances the model’s suitability for this task, and improves prediction precision.

Improving gas separation performance by boron nitride nanotubes

The performance of boron nitride nanotubes (BNNTs) and carbon nanotubes (CNTs) in multiple gas separation systems was systematically compared using molecular simulation methods. Findings reveal that under conditions of 298 K and 2 MPa, BNNTs generally show higher adsorption selectivities than CNTs for CH4/N2, CO2/CH4, and CO2/N2 mixtures. Notably, in the CO2/CH4 system, BNNTs exhibit a selectivity of up to 350 at a radius of 0.48 nm, significantly surpassing the 14 observed for CNTs; in the CO2/N2 system, selectivity can reach as high as 969 for BNNTs, contrasting with the 69 for CNTs. Furthermore, BNNTs achieve saturation adsorption for CF4 at 0.04 MPa with a capacity of 2.7 mmol/g, while CNTs show a higher adsorption capacity for N2, reflecting the superior selective adsorption capability of BNNTs for specific gases. Analysis of nanotubes with different chiral configurations led to the recommendation of (11,11) and (7,7) chiralities as optimal structures for efficient gas separation. Fluctuations in energy contributions from fluid-wall interactions in BNNTs, are closely related to their selectivity fluctuations. The results demonstrate that BNNTs, due to their unique structural characteristics, possess significant potential in the field of gas adsorption and separation, particularly in enhancing the selective adsorption of CO2 and CF4.

Torque ripple reduction and increasing of torque per volume for hybrid electrical vehicle

Hybrid electrical vehicles (HEV) should be designed somehow torque is smooth. Because torque ripple not only reduces control precision but also increases elements vibration that causes acoustic noise, mechanical instability and early aging parts. Furthermore, torque per volume should be maximized and heat removal should be accomplished without torque weakening. It is proposed the volume and internal dimensions are determined due to the thermal considerations and maximize torque per volume. The mentioned application is neglected heat removal so volume is constant. Therefore, HEV is manufactured by two objective functions: either minimum fluctuations or maximum average torque. In this paper series hybrid excitation synchronous machine (SHESM) is utilized as HEV. Two-objective optimization problems are solved by MOEA/D, NSGA II, PESA II and SPEA II algorithms based on a two-dimensional (2-D) model. The performance indices of optimal structure are evaluated by 2-D and confirmed by numerical method.

Computational Analysis of Dinucleoside Monophosphates: Comparing Structural Properties of Analogous Strands of Deoxyribonucleic Acids and Ribonucleic Acids Using Quantum Density Functional Calculations

The objective of this experiment was to determine the relative stabilities of dinucleoside monophosphates using density functional theory calculations. The calculations performed used Gaussian16 density functionals (Frisch et al., 2014) and Schrödinger’s equation to determine the optimal structure of single strands of two-base long deoxyribonucleic acids and their analogous ribonucleic acids. The strands looked at were composed of, respectively, deoxyadenosine-deoxycytidine, and deoxyguanosine-deoxythymidine for the DNA strands. The RNA strands were composed of, respectively, adenosine-cytosine, guanine-uracil, and guanine-thymine. The Hartree-Fock energies of the DNA AC and GT strands as well as those of the RNA AC, GT, and GU strands respectively were of -9.5672 x10-15 J, -1.0153 x10-14 J, -1.0223 x10-14 J, -1.0809 x10-14 J, and -1.0638 x10-14 J. Each of these were determined using Gaussian16 with the wB97X-D/6-31+G(d,p) model and tabulated using AIMAll (AIMSum, 2019). These values show that the RNA strands are more stable than the DNA strands with the adenosine-containing strands being the least stable in both the DNA and RNA forms respectively.

Shape optimization with level set-based method using a reaction diffusion equation for 2D sound barrier

A level set-based method using a reaction diffusion equation is applied for optimization problems of two dimensional (2D) sound barriers. The level set method is employed to implicitly represent the sound barrier structure, which distinguishes the material and void domains by the value of the level set function. The boundary element method is employed to solve acoustic problems governed by Helmholtz equation. Topological derivatives are computed by the boundary integral equation combined with the adjoint variable method. The distribution of level set function is iteratively updated based on the reaction diffusion equation to find the optimal structure. For the existent floating scatterers in the optimization process and the sharp and narrow parts on the surface of the sound barrier, we propose a filtering algorithm to remove floating scatterers and develop a method to achieve a smooth surface of the sound barrier. The shape optimization of sound barriers is achieved using these techniques, integrating the level set-based topology optimization method. Numerical tests are provided to demonstrate the validity and effectiveness of the proposed methods.

A comprehensive review on the fundamental principles, innovative designs, and multidisciplinary applications of micromixers

This paper comprehensively reviews the fundamental principles, innovative designs, and multidisciplinary applications of micromixers. First, it introduces the fundamental principles of fluid mixing in micromixers, including passive and active mixing mechanisms, and the flow characteristics of fluids at the microscale. Subsequently, it focuses on the innovative design of passive micromixers, covering a variety of designs, such as obstacle structures, curved serpentine structures, groove structures, separation and recombination structures, topology optimization structures, and baffle structures, and analyzes the effects of different structures on mixing efficiency and pressure drop. In addition, it also studies the innovative design of active micromixers, including magnetic field assistance, electric field assistance, surface acoustic wave assistance, and thermal effect assistance, and analyzes the effects of different driving modes on mixing efficiency. Finally, it outlines the multidisciplinary applications of micromixers in the fields of biomedicine, chemical analysis, environmental monitoring and control, and new energy. This review aims to provide a comprehensive reference for the research and application of micromixers and promote their application in more fields.

Optimization of co-linear-type pulsed electric field treatment chamber for milk pasteurization

Pulsed electric fields (PEFs) are increasingly employed industrially as pasteurization methods for liquid foods. However, some issues regarding heat-sensitive, high-protein liquid foods remain unresolved. The efficacy of PEFs during continuous processing depends on the structural characteristics of the processing chamber. This study presents the optimal structure of our originally developed colinear-type PEF treatment chamber, determined through a combination of experimental and numerical calculations. Our pasteurization system, with a flow rate of 10 L/h, involved an optimized PEF treatment and a moderate heat treatment at 60 °C. Our system inactivates Listeria innocua in sterilized milk by more than seven orders of magnitude. In a durability test, the system was successfully operated continuously for more than 1 h under pasteurized conditions without any damage or component adhesion on the stainless-steel electrodes. This study provides guidelines for the high-flow pasteurization of high-protein liquid foods.

Dynamic Gradient Boosted Metaheuristic approach for efficient reinforced concrete structure optimization

Structural optimization remains a time-consuming and challenging task, particularly for reinforced concrete structures. Surrogate modeling, a subset of machine learning, has emerged as a promising approach to mitigate the computational burden of structural analysis. However, the use of surrogate modeling also introduces additional challenges, especially the risk of prediction errors due to a small training database. This paper introduces a novel framework, Dynamic Gradient Boosted Metaheuristic Method (DGBM), to address this challenge and enhance optimization efficiency. DGBM integrates Light Gradient Boosted Machine (LightGBM) as a surrogate model for structural analysis, along with a modified Symbiotic Organisms Search (SOS) algorithm, effectively exploring the search space to discover optimal solutions. Its innovative features include LightGBM screening, dynamic training, design modifications, adaptive correction mechanisms, and integration with ETABS. The current study aims to leverage the strengths of machine learning and metaheuristics to significantly reduce the computational cost associated with traditional optimization methods while minimizing the impact of prediction errors. These enhancements refine and expedite the optimization process, making it more applicable to real-world design scenarios. The effectiveness of DGBM is evaluated through case studies on practical reinforced concrete structures, the proposed framework consistently achieves the target cost and delivers results 42.5 % faster in case 1, 57.1 % faster in case 2, and 25 % faster in case 3 compared to the next best method. This advantage translates to faster design iterations and increased efficiency for engineers, empowering them to explore a broader range of design options and achieve optimal solutions for complex structures in a shorter timeframe.

A Practical Study of Knowledge Mapping Empowering the Construction of Engineering Costing Software Application Courses in Undergraduate Colleges and Universities

Relying on the talent cultivation program of Chongqing Institute of Engineering, this paper combines the characteristics of the Engineering Costing Software Application course with its current status quo, analyzes the existing problems and teaching pain points, and introduces knowledge mapping. The course construction is carried out in terms of the combing of knowledge points, the optimization of the course structure, the innovation of the teaching method, and the evaluation and feedback of the teaching in order to improve the systematicity and structural nature of the teaching content, enhance students’ learning experience, and enhance their learning effect. It is conducive to the formation of students’ knowledge systems and provides a basis for discussion and reference for improving the quality of teaching and cultivating application-oriented talents who meet the market demand.

Energy redistribution in railway transition zones by geometric optimisation of a novel transition structure

Railway transition zones are critical regions in railway infrastructure that are subjected to excessive operation-driven degradation due to energy concentration within these zones. This work presents a heuristic approach to optimise the geometry of the transition structure and investigate its influence on the strain energy distribution in the railway transition zones (RTZs), with a specific focus on embankment-bridge transitions equipped with a newly proposed ’Safe Hull-Inspired Energy Limiting Design (SHIELD)’ transition structure. For this purpose, a number of three-dimensional finite element models are used to analyze different geometric profiles of SHIELD in a systematic manner. By altering SHIELD’s geometry across longitudinal, transversal, and vertical directions, the influence of the different geometric profiles on the total strain energy distribution across the trackbed layers (ballast, embankment, and subgrade) is studied in terms of spatial and temporal variations. The results establish the contribution of geometry to energy redistribution in all three directions and present an optimum geometry for the type of transition under study. It is found that among all the profiles, the longitudinal geometric profile of SHIELD has the most significant impact on the strain energy distribution, while the transversal profile primarily influences the ballast layer, and the alteration of vertical profiles enhance the local redistribution of strain energy in the vicinity of the transition interface. The preliminary optimisation (heuristic approach) presented in this work provides the starting point for full-scale optimisation to obtain tailored shapes of transition structures such that there is neither a concentration of energy nor an obstruction in the flow of energy in RTZs.

FINANCIAL MANAGEMENT PRACTICES ON GROWTH OF BUSINESS ENTERPRISES IN MBINGA DISTRICT, TANZANIA

A robust financial management system forms the foundation for business growth and long-term survival. However, there is limited information on the financial management practices that contribute to business growth in the Mbinga district. This study examined financial management and working capital management practices. A semi quasi-experimental research design was employed, utilizing questionnaires distributed to a sample of 62 business owners. Descriptive statistics were analyzed using the SPSS package. The results indicated that 41.9% of business enterprises employed working capital management practices, while 24% used capital structure management practices. Financial management practices were found to enhance management efficiency with a mean score of 3.74, increase the availability of capital with a mean score of 3.61, and improve operational margins with a mean score of 3.56. The study concluded that financial management practices are crucial for business growth and recommended their implementation. The study also found that capital structure management practices were applied to a lesser extent, although businesses showed an understanding of balancing debt and equity for financial sustainability. These findings suggest that the effective implementation of financial management practices is crucial for the growth and performance of businesses in the district. The study concludes that the integration of sound financial management practices contributes to better financial decision-making, risk mitigation, and resource optimization, leading to business expansion and sustainability. From a policy perspective, the study recommends that regulators and stakeholders encourage firms to leverage debt financing due to its associated tax benefits and advantages for financial sustainability. Theoretically, the findings underscore the relevance of agency theory in understanding the dynamics between managers and shareholders, and the principle of optimal capital structure in maximizing firm value. These insights provide a foundation for future research and practical interventions aimed at improving financial management practices in similar contexts.

Research on the Impact of Digital Financial Technology on the Business Model Transformation of Commercial Banks

This paper explores in depth the broad impact of digital financial technologies on the business models of commercial banks and analyzes in detail the transformation strategies that commercial banks should adopt in response to these changes. With the rapid development of cutting-edge technologies such as big data, cloud computing, artificial intelligence, and blockchain, digital finance has become an irreversible trend in the financial industry, which has not only changed the way financial services are provided, but also reshaped the market competition pattern of commercial banks. This paper first expounds the impact of digital financial technology on the traditional business model of commercial banks, including the reduction of market entry threshold, the change of competition focus and the innovation of risk management model. Then, the paper focuses on the specific strategies of commercial bank business model transformation, including technological innovation, organizational structure optimization, process management improvement, talent training and introduction, and strengthening cooperation and win-win situation. Through the introduction of the actual case analysis, it shows the successful practice and lessons of commercial banks in the business model transformation. Finally, this paper concludes that the key to the successful transformation of commercial banks' business model lies in the deep integration of technology and business, as well as the ability to flexibly respond to market changes and customer needs. Only in this way can commercial banks remain competitive and achieve sustainable development in the era of digital finance.

Rock exfoliation in the unstable formations during underground mine working driving and selection of efficient adhesive compositions for strengthening

Purpose is to identify factors favouring rock exfoliation in roof of underground mine workings while operating Akbakay deposit and determine optimum structure of adhesive reagents for the rock strengthening taking into consideration mineralogical composition of the formation. Methods. The research was carried out in a lab environment. Chemical and ultimate composition of the rock mass samples was determined through x-ray diffraction method; the x-ray phase identification approach helped define their mineralogical composition. The optimum composition of adhesive reagents has been determined based upon the ambient temperature and hardening time. Viscosity durability of the adhesive compounds was assessed using a technique of uniaxial crack of the immovable samples. Statistical data processing involved determination of the required number of the samples to achieve the preset accuracy degree. Findings. Exfoliation of the fragments of both fractured and unstable rocks from Akbakai deposit depends upon availabi-lity of such chemically and mechanically unstable salts as dolomite, albite, and mirror stone. Epoxide reagent in 9 to 1 ratio with polyethylenepolyamine catalyzer has been identified as the most effective adhesive compound. Epoxy adhesives have demonstrated higher cohesive resistance to compare with polyurethane analogues, and better compliance with requirements as for viscosity and hardening time. Originality. Use of epoxy to strengthen both fissured and unstable rocks of Akbakai deposit containing mineral salts, helps increase tensile properties up to three times. Moreover, epoxies also demonstrate high adhesive characteristics; and they are resistant to moisture and temperature attacks being typical for mine environment. New logarithmic dependencies have been identified describing rock mass stability while applying the modified polyurethane with polyethylenepolyamine catalyzer in 9 to 1 ratio. Practical implications. Various types of reagents have been considered for safe and effective strengthening of underground mine workings in the fractured rock masses having a tendency to caving. The proposed adhesive reagents resist efficiently the external share loads and stresses increasing structural stability and safety of rock masses.

Chitosan/La catalyzed synthesis of novel ferrocenated spiropyrrolizidines: Green synthesis, crystallographic, DFT and Hirshfeld surface studies

A novel polymeric catalytic system, utilizing chitosan-bounded lanthanum (chitosan/La), facilitated the formation of spiropyrrolizidine hybrids in higher yield. These hybrids were synthesized via one-pot three component 1,3-dipolar cycloaddition reaction involving ferrocenated chalcones, and azomethine ylides. The chemical structures were elucidated using various spectroscopic techniques and further confirmed via X-ray crystallography of a compound 3. Density functional theory (DFT) calculations executed followed by Gaussian 09 and GaussView 5.0 software provided insights into the optimal structure of molecular compounds. The computational analysis employed the 6–311G++ (d,p) higher-order basis set and the B3LYP method. Additionally, Hirshfeld surface analysis was utilized to predict crystallographic shapes, revealing van der Waals interaction contributing to crystal stabilization.

Sealing Characteristics Analysis of New Subsea Wellhead Sealing Device

Subsea wellhead systems are the crucial equipment for the development of oil and gas resources offshore, while the sealing device plays a vital role as the main component of the wellhead system. Once the seal fails, it is necessary to retrieve the original wellhead system and either repair the sealing device or reinstall a new one. This will result in a delay in normal production and an increase in development costs. Therefore, a novel subsea wellhead sealing device is designed. A finite element analysis model is developed to study the underwater wellhead sealing mechanism regarding the equivalent stress and contact stress. The research results show that as the driving block gradually increases from 4 mm to 12 mm, the stress of the 12 convex parts on the sealing body also increases. The maximum equivalent stress reaches 3.5 times the yield limit, indicating that it has entered the yield stage and can achieve a more effective seal. The analysis of the contact stress of the sealing body reveals that the contact stress of the driving block increases, leading to plastic deformation of the sealing body while driving it to achieve a complete seal. In general, the finite element simulation results are consistent with the engineering practice. By analyzing the sealing characteristics, it can serve as the foundation for designing and providing theoretical support for the optimization of the metal-sealing structure.

Combinatorial optimization of the hybrid cellulase complex structure designed from modular libraries.

Cellulase selectively recognizes cellulose surfaces and cleaves their β-1,4-glycosidic bonds. Combining hydrolysis using cellulase and fermentation can produce alternative fuels and chemical products. However, anaerobic bacteria produce only low levels of highly active cellulase complexes so-called cellulosomes. Therefore, we designed hybrid cellulase complexes from 49 biotinylated catalytic domain (CD) and 30 biotinylated cellulose-binding domain (CBD) libraries on streptavidin-conjugated nanoparticles to enhance cellulose hydrolysis by mimicking the cellulosome structure. The hybrid cellulase complex, incorporating both native CD and CBD, significantly improved reducing sugar production from cellulose compared to free native modular enzymes. The optimal CBD for each hybrid cellulase complex differed from that of the native enzyme. The most effective hybrid cellulase complex was observed with the combination of CD6-4 from Thermobifida fusca YX and CBD46 from the Bacillus halodurans C-125. The hybrid cellulase complex/CD6-4-CBD46 and -CD6-4-CBD2-5 combinations showed increased reducing sugar production. Similar results were also observed in microcrystalline cellulose degradation. Furthermore, clustering on nanoparticles enhanced enzyme thermostability. Our results demonstrate that hybrid cellulase complex structures improve enzyme function through synergistic effects and extend the lifespan of the enzyme.

Study on energy absorption of paper honeycomb sandwich tube filled by polyethylene foam under axial loading

This work proposed an approach to multi-component non-metallic materials, namely regular polygonal paper honeycomb sandwich tubes filled with polyethylene (PE) foam, and focused on the influence of drop impact parameters and structural parameters on the deformation characteristics and energy absorption of the filled tubes. Axial drop impact tests were employed to exert drop impact loading on cross-sections of the specimens with a square drop weight. The results showed that the X-direction filled tube (X-DFT) had a higher crushing strength and yield strength than that of the Y-direction filled tube (Y-DFT). As the tubular cross-section edge number of the filled tube increased, the specific energy absorption (SEA) and specific total efficiency (STE) decreased. Under the same axial drop impact loading conditions, the SEA and STE of the X-DFT were superior to those of the Y-DFT. As the edge number of the tubular cross-section or the tubular length ratio increased, the SEA and STE of the filled honeycomb tube decreased significantly. While the impact energy increased, the SEA and STE of the filled tubes increased approximately linearly. This work investigated the influence of drop-impact and structural parameters on deformation characteristics and energy absorption. It is expected to provide supplementary documentation for the advancement of cushion protection technology and the optimization of product structure.

Accelerating decarbonized economic growth through net-zero entrepreneurship: Low-carbon economic development perspective

Net-zero entrepreneurship is a novel concept introduced in the context of carbon neutrality, and exploring whether it can catalyze decarbonized economic growth is a worthy pursuit. This study constructs a comprehensive, low-carbon endogenous economic growth model to scrutinize the intricate nexus between net-zero entrepreneurship and decarbonized economic growth. Empirical validation employs a series of multiple regression models to rigorously test the hypotheses derived from the theoretical framework using an extensive dataset spanning Chinese provinces. The results reveal a nuanced landscape. (i) Net-zero entrepreneurship plays a remarkable role in promoting decarbonization growth, with considerable regional heterogeneity. (ii) Green technology progress exhibits a notable mediating effect. (iii) Environmental regulation and industrial structure optimization have positive moderating effects. (iv) The results passed alternative dependent variable and one-phase lag regression robustness tests. In a distinct contribution to entrepreneurship literature, this study augments the discourse on strategies to steer low-carbon transitions. The research findings indicate that net-zero entrepreneurship can accelerate the global decarbonization process, and green technology progress is a significant driving mechanism in this process. Additionally, it is essential to strengthen environmental agencies’ regulatory oversight and optimize industrial structures to pave the way for transformative sustainable growth. In the future, more entrepreneurs should be encouraged to engage in green technology and business model innovation to contribute to global decarbonization efforts.

Spatial Simulation and Optimization of Cropping Structure Under Climate and Land Use Change Conditions Considering Synergistic Economic Benefits and Carbon Reduction in Crop Growth Processes

AbstractThe climate and land use changes caused by the natural environment and socioeconomic development have potential impacts on the green and sustainable development of agriculture. To accommodate agricultural production under multiple scenarios of future climate and land‐use change, this study proposes a “simulation–optimization” modeling approach based on a crop growth model with a synergistic “carbon emission–economic benefit” approach. This approach is based on climate change conditions and it accurately simulates future land use changes and crop growth processes, establishes a carbon emission intensity optimization model, and generates a spatial planting structure optimization and regulation scheme based on intelligent optimization algorithms under changing scenarios. The results of the model application show that the planting structure option in the future scenario can increase economic benefit by up to 14.8% compared to the current scenario while simultaneously reducing total greenhouse gas emissions by 6.77%. Correlation analysis of planting area, irrigation water volume, carbon intensity value and unilateral water use efficiency can be used to obtain the coordination level of each county under different regulation scenarios. This “simulation–optimization” modeling approach provides an effective approach to achieve synergistic and coordinated development of regional agricultural benefits and carbon reduction by fine‐tuning the planting structure, which promotes low‐carbon and high‐quality development of regional agriculture.

The Employment Outlook of Urban Youth under Consumption Downgrading

This paper uses participant observation and semi-structured interviews to examine the presentation of urban youth’s employment outlook in the context of consumer downgrading, and explores the shaping factors behind it to provide rational explanations. Through the classification and analysis of employment attitudes and expectations, it is found that the employment expectations of urban youths tend to be de-employerization and career digitization, lifelong learning and compound talents, embracing new industries and engaging in new occupations as amphibious youths and slash-and-burn youths, and presenting attitudes of pursuing the fulfillment of self-worth, and attaching equal importance to responsibilities and ideals. The emergence of employment attitudes and expectations is related to the acceleration of modernity and pressurized survival, as well as the awakening of self-consciousness among urban youth. In this regard, society at large should respect and adjust to their new employment mentality and expectations, so that they can firmly hold on to their ideals, which is also of great significance in promoting the in-depth optimization of the human resources structure.