Strain Gradient Solutions of Eshelby-Type Problems for Polygonal and Polyhedral Inclusions

The Eshelby-type problems of an arbitrary-shape polygonal or polyhedral inclusion embedded in an infinite homogeneous isotropic elastic material are analytically solved using a simplified strain gradient elasticity theory (SSGET) that contains a material length scale parameter. The Eshelby tensors for a plane strain inclusion with an arbitrary polygonal cross section and for an arbitrary-shape polyhedral inclusion are analytically derived in general forms in terms of three potential functions. These potential functions, as area integrals over the polygonal cross section and volume integrals over the polyhedral inclusion, are evaluated. For the polygonal inclusion problem, the three area integrals are first transformed to three line integrals using the Green's theorem, which are then evaluated analytically by direct integration. In the polyhedral inclusion case, each of the three volume integrals is first transformed to a surface integral by applying the divergence theorem, which is then transformed to a contour (line) integral based on Stokes' theorem and using an inverse approach. In addition, the Eshelby tensor for an anti-plane strain inclusion with an arbitrary polygonal cross section embedded in an infinite homogeneous isotropic elastic material is analytically solved. Each of the newly derived Eshelby tensors is separated into a classical part and a gradient part. The latter includes the material length scale parameter additionally, thereby enabling the interpretation of the inclusion size effect. For homogenization applications, the area or volume average of each newly derived Eshelby tensor over the polygonal cross section or the polyhedral inclusion domain is also provided in a general form. To illustrate the newly obtained Eshelby tensors and their area or volume averages, different types of polygonal and polyhedral inclusions are quantitatively studied by directly using the general formulas derived. The numerical results show that the components of the each SSGET-based Eshelby tensor for all inclusion shapes considered vary with both the position and the inclusion size. It is also observed that the components of each averaged Eshelby tensor based on the SSGET change with the inclusion size

Does enterprise risk management benefit manufacturing firms? Evidence from China

It is observed that Enterprise risk management (ERM) framework has been adopted by some manufacturing firms in China in the past years. To investigate the effectiveness of ERM, data of A-share listed manufacturing firms in Shanghai and Shenzhen stock exchange during 2010-2019 are adopted from Wind database and CSMAR database, two large domestic databases, to examine the impact of ERM on value of manufacturing firms. Treatment effects model and genenralised method of moments (GMM) are employed to derive the empirical results. Our results show that adoption of ERM can add value to the firms, and firms benefitmore from high-quality ERM program. Furthermore, the impact of ERM seems to be more significant among the manufacturing firms with smaller scale, or stronger institutional shareholding, or international business. Our findings encourage the manufacturing firms to implement ERM program and improve the program to achieve its targets

Product Demand Forecasting and Dynamic Pricing considering Consumers' Mental Accounting and Peak-End Reference Effects

We introduce a demand forecasting model for a monopolistic company selling products to consumers with double-entry mental accounting, which means consumers experience pleasure when consuming goods or service and feel pains when paying for them. Moreover, as the monopolist changes prices, consumers form a reference price that adjusts an anchoring standard based on the lowest price that they perceived, namely, the peak-end anchoring. We obtain the steady state prices under three different payment schemes for two-and infinite-period. We also analyze the relationship between these steady prices and maximal profit and compare the steady state prices of different payment schemes by changing the double-entry mental accounting's parameters through numerical examples. The proposed model is computationally tractable for demand forecasting of realistic size

Product Demand Forecasting and Dynamic Pricing considering Consumers’ Mental Accounting and Peak-End Reference Effects

We introduce a demand forecasting model for a monopolistic company selling products to consumers with double-entry mental accounting, which means consumers experience pleasure when consuming goods or service and feel pains when paying for them. Moreover, as the monopolist changes prices, consumers form a reference price that adjusts an anchoring standard based on the lowest price that they perceived, namely, the peak-end anchoring. We obtain the steady state prices under three different payment schemes for two- and infinite-period. We also analyze the relationship between these steady prices and maximal profit and compare the steady state prices of different payment schemes by changing the double-entry mental accounting’s parameters through numerical examples. The proposed model is computationally tractable for demand forecasting of realistic size

Coordination in the Decentralized Assembly System with Dual Supply Modes

This paper investigates a decentralized assembly system that consists of one assembler and two independent suppliers; wherein one supplier is perfectly reliable for the production, while the other generates yield uncertainty. Facing the random market demand, the assembler has to order the components from one supplier in advance and meanwhile requires the other supplier to deliver the components under VMI mode. We construct a Nash game between the supplier and the assembler so as to derive their equilibrium procurement/production strategies. The results show that the channel’s performance is highly undermined by the decentralization between players and also the combination of two supply modes. Compared to the centralized system, we propose an advance payment contract to perfectly coordinate the supply chain performance. The numerical examples indicate some management implications on the supply mode comparison and sensitivity analysis

Optimal allocation of distributed generation and electric vehicle charging stations based on intelligent algorithm and bi‐level programming

To facilitate the development of active distribution networks with high penetration of large‐scale distributed generation (DG) and electric vehicles (EVs), active management strategies should be considered at the planning stage to implement the coordinated optimal allocations of DG and electric vehicle charging stations (EVCSs). In this article, EV charging load curves are obtained by the Monte Carlo simulation method. This article reduces the number of photovoltaic outputs and load scenarios by the K‐means++ clustering algorithm to obtain a typical scenario set. Additionally, we propose a bi‐level programming model for the coordinated DG and EVCSs planning problem. The maximisation of annual overall profit for the power supply company is taken as the objective function for the upper planning level. Then, each scenario is optimised at the lower level by using active management strategies. The improved harmonic particle swarm optimisation algorithm is used to solve the bi‐level model. The validation results for the IEEE‐33 node, PG&E‐69 node test system and an actual regional 30‐node distribution network show that the bi‐level programming model proposed in this article can improve the planning capacity of DG and EVCSs, and effectively increase the annual overall profit of the power supply company, while improving environmental and social welfare, and reducing system power losses and voltage shifts. The study provides a new perspective on the distribution network planning problem.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155928/1/etep12366.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155928/2/etep12366_am.pd

The value of IGF-1 and IGFBP-1 in patients with heart failure with reduced, mid-range, and preserved ejection fraction

Background: Previous studies have reported inconsistent results regarding the implications of deranged insulin-like growth factor 1 (IGF-1)/insulin-like growth factor-binding protein 1 (IGFBP-1) axis in patients with heart failure (HF). This study evaluates the roles of IGF1/IGFBP-1 axis in patients with HF with reduced ejection fraction (HFrEF), mid-range ejection fraction (HFmrEF), or preserved ejection fraction (HFpEF). Methods: Consecutive patients with HFrEF, HFmrEF, and HFpEF who underwent comprehensive cardiac assessment were included. The primary endpoint was the composite endpoint of all-cause death and HF rehospitalization at one year. Results: A total of 151 patients with HF (HFrEF: n = 51; HFmrEF: n = 30; HFpEF: n = 70) and 50 control subjects were included. The concentrations of IGFBP-1 (p < 0.001) and IGFBP-1/IGF-1 ratio (p < 0.001) were significantly lower in patients with HF compared to controls and can readily distinguish patients with and without HF (IGFBP-1: areas under the curve (AUC): 0.725, p < 0.001; IGFBP-1/IGF-1 ratio: AUC:0.755, p < 0.001; respectively). The concentrations of IGF-1, IGFBP-1, and IGFBP-1/IGF-1 ratio were similar among HFpEF, HFmrEF, and HFrEF patients. IGFBP-1 and IGFBP-1/IGF-1 ratio positively correlated with N-terminal probrain natriuretic peptide (NT-proBNP) levels (r = 0.255, p = 0.002; r = 0.224, p = 0.007, respectively). IGF-1, IGFBP-1, and IGFBP-1/IGF-1 ratio did not predict the primary endpoint at 1 year for the whole patients with HF and HF subtypes on both univariable and multivariable Cox regression. Conclusion: The concentrations of plasma IGFBP-1 and IGFBP-1/IGF-1 ratio can distinguish patients with and without HF. In HF, IGFBP-1 and IGFBP-1/IGF-1 ratio positively correlated with NT-proBNP levels