Expansion Problem Research Articles

Engineered cell-laden thermosensitive poly(N-isopropylacrylamide)-immobilized gelatin microspheres as 3D cell carriers for regenerative medicine.

Several studies have focused on using cell carriers to solve the problem of mesenchymal stem cell expansion on regenerative medicine. However, the disadvantages of using prolonged enzymatic treatment and low cell harvest efficiency still trouble researchers. In this study, PNIPAAm-immobilized gelatin microspheres (abbreviated as GNMS) were synthesized using a simple power-driven flow-focusing microinjection system. The developed thermosensitive GNMS can allow easier harvesting of cells from the microspheres, requiring only 10 ​min of low-temperature treatment and 5 ​min of trypsin treatment. The developed GNMS was characterized by Fourier-transform infrared spectroscopy, optical microscopy, and scanning electron microscopy. Further, live/dead staining, F-actin staining, and PrestoBlue cell viability assays were used to evaluate cytotoxicity, cell morphology, cell proliferation, and harvest efficiency. The gene expression of stem cell markers was determined by real-time quantitative PCR (Q-PCR) analysis to investigate the stemness and phenotypic changes in Wharton's jelly-derived mesenchymal stem cells. The results showed that the engineered cell-laden thermosensitive GNMS could significantly increase the cell harvest rate with over 99% cell survival rate and no change in the cell phenotype. Thus, the described strategy GNMS could be the suitable 3D cell carriers in the therapeutic application and opens new avenues for regenerative medicine.

Implementation of entrepreneurship acceleration services in the federal project: the problem of comprehensiveness and expansion of the approach

Implementation of entrepreneurship acceleration services in the federal project: the problem of comprehensiveness and expansion of the approach

An efficient XOR-based visual cryptography scheme with lossless reconfigurable algorithms

This article proposes an efficient XOR-based visual cryptography scheme with lossless reconfigurable algorithms, which includes an encryption and a decryption schemes for gray-scale and color secret images. The encryption scheme aims to encrypt secret images by mapping them to several shared images that do not suffer any pixel expansion problem and do not reveal any information of the secret images by considering a random column selection algorithm based on the 0-mapping and 1-mapping matrices, where the two matrices are dynamically generated in the encryption scheme. Moreover, the proposed decryption scheme can reconstruct the secret images with only a series of XOR operations. The reconstructed images do not suffer any contrast distortion and pixel expansion problems comparing with their original secret images. Finally, the proposed two schemes are illustrated with the practical examples.

Assessing the role of fluctuating renewables in energy transition: Methodologies and tools

Due to the environmental impacts brought by current energy schemes, the energy transition, a new paradigm shift from fossil fuels to renewable energy, has been widely accepted and is being realized through collective international, regional, and local efforts. Electricity, as the most direct and effective use of renewable energy sources (RES), plays a key role in the energy transition. In this paper, we first discuss a viable pathway to energy transition through the electricity triangle, highlighting the role of RES in electricity generation. Further, we propose methodologies for the planning of wind and solar PV, as well as how to address their uncertainty in generation expansion problems. Finally, by using a web-based tool, “RES-PLAT”11https://res-plat.est.polito.it., we demonstrate the scheme in a case study in Egypt, which evaluates the impacts and benefits of a large-scale RES expansion.22The short version of the paper was presented at Applied Energy Symposium: MIT A+ B, August 13–14, Boston. This paper is a substantial extension of the short version of the conference paper.

Assessments of linear power flow and transmission loss approximations in coordinated capacity expansion problems

With rising shares of renewables and the need to properly assess trade-offs between transmission, storage and sectoral integration as balancing options, building a bridge between energy system models and detailed power flow studies becomes increasingly important, but is computationally challenging.Here, we compare approximations for two nonlinear phenomena, power flow and transmission losses, in linear capacity expansion problems that co-optimise investments in generation, storage and transmission infrastructure. We evaluate different flow representations discussing differences in investment decisions, nodal prices, the deviation of optimised flows and losses from simulated AC power flows, and the computational performance. By using the open European power system model PyPSA-Eur, we obtain detailed and reproducible results aiming at facilitating the selection of a suitable power flow model.Given the differences in complexity, the optimal choice depends on the application, the user’s available computational resources, and the level of spatial detail considered. Although the commonly used transport model can already identify key features of a cost-efficient system while being quick to solve, severe deficiencies under high loading conditions arise due to the lack of a physical grid representation. Moreover, disregarding transmission losses overestimates optimal grid expansion by 20%. Adding a convex relaxation of quadratic losses with three tangents to the linearised power flow and accounting for changing line impedances as the network is reinforced suffices to represent power flows and losses adequately in design studies. We show that the obtained investment and dispatch decisions are then sufficiently physical to be used in more detailed nonlinear simulations of AC power flow evaluating their technical feasibility.

Recycling of paper/wood industry waste for hydromechanical stability of expansive soils: A novel approach

This article presents a sustainable solution to repurpose paper/wood industry waste as a geotechnical construction material. A novel lignosulphonate (LS)-based composite admixture (CA) was used in this study to cope with construction problems pertaining to expansive soils. Surface water infiltration in terms of rainfall and surface water irrigation are the prime factors that cause volumetric change behavior and a drastic reduction in shear strength due to loss in suction that eventually causes failure in expansive soils. Such failures are comprised of complex hydromechanical phenomena and their remediation requires special attention. In this context, this study for the first time deals with the use of LS-based CA as a remedy to such failures in expansive soils considering the hydromechanical properties. To better understand the hydraulic response, the specially designed soil-column model tests (SCMTs) were conducted. Besides, different geotechnical experiments and microstructural analyses were carried out to analyze the hydromechanical behavior of CA treatment against the varying degree of saturation (Sr). The results showed that LS-based CA treatment increases the water holding capacity over a suction range of 78.4 kPa and air entry value (AEV) by 33%. Also, the SCMT showed that the wetting-front depth (WFD) at full saturation in CA treated expansive soil was 4–10% quicker than untreated expansive soil. In addition, for the increase in Sr from optimum to 100%, the decrease in cohesion (c) value for untreated and treated soil was found to be 88% and 39.8%, and the increase in compressibility was 37% and 17%, respectively, highlighting better resistance against Sr. Whereas, the swelling potential was completely eradicated with a significant reduction in volumetric shrinkage by 43% compared to untreated soil. The microstructural analyses showed the development of apparent aggregation with the Sr in untreated expansive soil, whereas the CA treatment-induced better structure with bigger size particles with disrupted inter and intra assemblage pore spaces. The results showed that LS-based CA manifests substantial hydromechanical stability against variation in Sr. Overall, this study provides the scientific basis to the practitioners for the pragmatic use of LS-based CA in treating expansive soil problems.

Derivation and generation of path-based valid inequalities for transmission expansion planning

This paper seeks to solve the long-term transmission expansion planning problem in power systems more effectively by reducing the solution search space and the computational effort. The proposed methodology finds and adds cutting planes based on structural insights about bus angle differences along paths. Two lemmas and a theorem are proposed which formally establish the validity of these cutting planes onto the underlying mathematical formulations. These path-based bus angle difference constraints, which tighten the relaxed feasible region, are used in combination with branch-and-bound to find lower bounds on the optimal investment of the transmission expansion planning problem. This work also creates an algorithm that automates the process of finding and applying the most effective valid inequalities, resulting in significantly reduced testing and computational time. The algorithm is implemented in Python, using Gurobi to add constraints and solve the exact DCOPF-based transmission expansion problem. This paper uses two different-sized systems to illustrate the effectiveness of the proposed framework: the GOC 500-bus system and a modified Polish 2383-bus system.

A Nested Cross Decomposition Algorithm for Power System Capacity Expansion with Multiscale Uncertainties

Modern electric power systems have witnessed rapidly increasing penetration of renewable energy, storage, electrical vehicles, and various demand response resources. The electric infrastructure planning is thus facing more challenges as a result of the variability and uncertainties arising from the diverse new resources. This study aims to develop a multistage and multiscale stochastic mixed integer programming (MM-SMIP) model to capture both the coarse-temporal-scale uncertainties, such as investment cost and long-run demand stochasticity, and fine-temporal-scale uncertainties, such as hourly renewable energy output and electricity demand uncertainties, for the power system capacity expansion problem. To be applied to a real power system, the resulting model will lead to extremely large-scale mixed integer programming problems, which suffer not only the well-known curse of dimensionality but also computational difficulties with a vast number of integer variables at each stage. In addressing such challenges associated with the MM-SMIP model, we propose a nested cross decomposition algorithm that consists of two layers of decomposition—that is, the Dantzig–Wolfe decomposition and L-shaped decomposition. The algorithm exhibits promising computational performance under our numerical study and is especially amenable to parallel computing, which will also be demonstrated through the computational results.

Cavity expansion analysis of normal indention of rocks with lateral confinement

Indentation of rocks with lateral confinement is strongly related to rock fragmentation in drilling, mechanized tunnelling, and mining. Yet, the interpretation of the results and its transfer to use in practice is complicated by both the limited specimen size and boundary conditions associated with the application of lateral confinement. In this study, a new semi-analytical solution for the problem of a finite-cavity expansion in rock specimens of finite radial extent is present for the analysis of rock indentation with lateral confinement. To account for possible strain hardening/softening effect, an extended linear strain hardening/softening, i.e. constant plastic tangential modulus, Drucker-Prager model with non-associated flow rule is used to describe the stress-strain behavior of rocks. The model predictions, valid up to crack initiation, agree well with experimental observations that peak indentation pressure increases with lateral confinement, indicating that for a correct interpretation of results, the ratio between specimen size and the tip width of a truncated indenter as well as the boundary conditions shall be considered. The results point to the need for further development of the cavity expansion model by incorporating more features to model the realistic rock behavior and for more experimental studies with lateral confinement using advanced testing technique to monitor the failure process.

Research on Guidance and Control Method of Hypersonic UAV Capture Segment Based on Overload

With the implementation of China’s high supersonic aircraft science and technology engineering and the key basic scientific problems of near space vehicles major research programs.In this context, China is also vigorously developing high-speed high-mobility, long range and recyclable aircraft. In view of the tracking problem of a hypersonic vehicle when it reaches the capture segment, a mathod based on overload guidance law is proposed. The relationship between force and head-on angle can be deduced from the relationship between overload and head-on angle, thus transforming the overload control problem into the head-on control problem. Inversion controller design method is adopted for its parameter uncertainty rigid body model, and the derivative of virtual control amount is obtained by dynamic surface method to avoid the problem of differential expansion. Based on the secound-order tracking-differential, a nonlinear interference observer is designed to estimate and compensate for model uncertainties. The simulation results show that the controller can achieve stable tracking of the angle and high reference instructions, and has a strong robustness to the uncertainty effect of the model.

A one-for-all strategy of polyimide coating layer for resolving the comprehensive issues of phosphorus anode

Phosphorus is a promising anode with high capacity (2596 mAh g−1 and 6075 ∼ 6924 mAh cm−3), low lithium-ion diffusion barrier (0.08 eV), and appropriate lithiation potential (∼0.7 V vs Li+/Li). However, it faces the problems of huge volume expansion (∼300%), low electronic conductivity (10-14 ∼ 102 S cm−1), soluble intermediates (lithium polyphosphides, LixPs), degradation in air, and low thermal stability. In this work, phosphorus/carbon nanotube composites were coated with a polyimide layer, which plays the roles of a buffer layer to relieve the volume expansion of phosphorus, an obstruct layer to confine LixPs, an inert layer to prevent the degradation of phosphorus in air, a heat resistant layer to improve the thermal stability of the anode. The resulting composites (P/CNT@PI) display high capacity retention of 798.1 mAh g−1 after 150 cycles at 1 A g−1, achieving 17 times as much as the control sample (P/CNT).

Editors’ Note

Editors’ Note

Expansion of the Two-particle Dirac Equation in Powers of 1/c to Higher Orders

Using an extension of the Foldy–Wouthuysen transformation to two-particle wave equations, we consider the problem of expansion of the two-body Dirac Hamiltonian in powers of 1/c up to the fourth order. The transformed Hamiltonian in an even-even form toorder 1/c4 is obtained. It is shown that the extra terms which can be eliminated by additional unitary transformations appear in the expansion in higher orders. As an example, the Breit equation for Coulomb particles is considered, and all the terms of order 1/c4 in its reduction are calculated. The obtained results can be used for the expansion of relativistic and quasirelativistic two-particle wave equations to higher orders.

An analysis of zonal electricity pricing from a long-term perspective

In an era of energy transition, it is crucial to ensure that the design of the short-term electricity market provides sufficient cash flows to producers so as to allow the investment of the right technology at the right location. In this paper, we revisit the question of capacity allocation in zonal markets from a long-term perspective. We model the capacity expansion problem in zonal markets in which inter-zonal transmission capacity allocation is organized through flow-based market coupling, which is an approximation of power flow equations in aggregate networks that is employed in European market design. We demonstrate that the classical result of equivalence between centralized and decentralized formulations in transmission-constrained markets ceases to hold in this case. We propose a model of the decentralized capacity expansion problem with flow-based market coupling as a generalized Nash equilibrium that we formulate as a linear complementarity problem. We then perform simulations of the capacity expansion problem with nodal pricing and three variations of zonal pricing on a realistic instance of the Central Western European network and comment on the impacts of flow-based market coupling on investment.

Disturbance-Observer-Based Adaptive Fuzzy Control for Islanded Distributed Energy Resource Systems

With the aim to improve the antidisturbance ability of the islanded distributed energy resource (DER) systems, a disturbance-observer-based adaptive fuzzy sliding mode control (DAFSC) voltage controller is designed based on indirect vector control, which implements the voltage tracking and improves the self-regulation ability of the islanded DER systems. Firstly, the circuit diagram and the mathematical model of the DER system are presented. Then, the second-order sliding mode differentiator is designed to solve the problem of calculation expansion in the backstepping control method. To solve the influence of lumped disturbance on the system, a disturbance-observer is proposed to observe the unknown disturbance and compensate the controller feed-forward. Moreover, fuzzy control is proposed to reduce the dependence of the control effect on model accuracy. Finally, the stability of the controller is verified by Lyapunov stability theory, and the hardware in the loop results is given to verify that the control effect of the proposed DAFC controller has better dynamic performance compared with proportion-integral (PI) and the backstepping control strategy.

CAR-macrophage: An extensive immune enhancer to fight cancer.

CAR-macrophage: An extensive immune enhancer to fight cancer.

Cavity expansion in cohesive-frictional soils with limited dilation

The problem of cavity expansion from zero radius has no characteristic length and therefore possesses a similarity solution, in which the cavity pressure remains constant and the continuing deformation is geometrically self-similar. In this case, the incremental velocity approach first used by R. Hill in 1950 to analyse cavity expansion in Tresca materials can be extended to derive a solution for the limiting pressure of cavity expansion in other types of material. In this paper, a rigorous semi-analytical solution is derived, following Hill's incremental velocity method, for the expansion of cavities from zero initial radius in cohesive-frictional soils with limited dilation. In particular, the radius of the elastic–plastic interface c is used in this paper as the timescale and the solution for the limit pressure has been presented. Solutions are evaluated for a number of cases representative of a range of cohesive-frictional and dilatant soils. A comparison is also made between the solutions presented here and previous solutions for cohesive-frictional soils that have unlimited (on-going) plastic dilation. In particular, the influence of limited plastic dilation on the cavity limit pressure is identified and discussed.

A flexible system design approach for multi-facility capacity expansion problems with risk aversion

This article studies a model for risk aversion when designing a flexible capacity expansion plan for a multi-facility system. In this setting, the decision maker can dynamically expand the capacity of each facility given observations of uncertain demand. We model this situation as a multi-stage stochastic programming problem, and we express risk aversion through the Conditional Value-at-Risk (CVaR) and a mean-CVaR objective. We optimize the multi-stage problem over a tractable family of if–then decision rules using a decomposition algorithm. This algorithm decomposes the stochastic program over scenarios and updates the solutions via the subgradients of the function of cumulative future costs. To illustrate the practical effectiveness of this method, we present a numerical study of a decentralized waste-to-energy system in Singapore. The simulation results show that the risk-averse model can improve the tail risk of investment losses by adjusting the weight factors of the mean-CVaR objective. The simulations also demonstrate that the proposed algorithm can converge to high-performance policies within a reasonable time, and that it is also more scalable than existing flexible design approaches.

Class Highlight Generative Adversarial Networks for Strip Steel Defect Classification

In order to solve the problem of dataset expansion in deep learning tasks such as image classification, this paper proposed an image generation model called Class Highlight Generative Adversarial Networks (CH-GANs). In order to highlight image categories, accelerate the convergence speed of the model and generate true-to-life images with clear categories, first, the image category labels were deconvoluted and integrated into the generator through [Formula: see text] convolution. Second, a novel discriminator that cannot only judge the authenticity of the image but also the image category was designed. Finally, in order to quickly and accurately classify strip steel defects, the lightweight image classification network GhostNet was appropriately improved by modifying the number of network layers and the number of network channels, adding SE modules, etc., and was trained on the dataset expanded by CH-GAN. In the comparative experiments, the average FID of CH-GAN is 7.59; the accuracy of the improved GhostNet is 95.67% with 0.19[Formula: see text]M parameters. The experimental results prove the effectiveness and superiority of the methods proposed in this paper in the generation and classification of strip steel defect images.

Capacity Expansion Planning with Stochastic Rolling Horizon Dispatch

Variable renewable energy sources introduce significant amounts of short-term uncertainty that should be considered when making investment decisions. In this work, we present a method for representing stochastic power system operation in day-ahead and balancing electricity markets within a capacity expansion model. We use Benders cuts and a stochastic rolling horizon dispatch to represent operational costs in the capacity expansion problem (CEP) and investigate different formulations for the cuts. We test the model on a two-bus case study with wind power, energy storage and a constrained transmission line. The case study shows that cuts created from the day-ahead problem gives the lowest expected total cost for the stochastic CEP. The stochastic CEP results in 3% lower expected total cost compared to the deterministic CEP capacities evaluated under uncertain operation. The number of required stochastic iterations is efficiently reduced by introducing a deterministic lower bound, while extending the horizon of the operational problem by persistence forecasting leads to reduced operational costs.