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With rapid developments of the Internet of Things (IoT) applications in recent years, their use to facilitate day-to-day activities in various domains for enhancing the quality of human life has significantly increased. Fog computing has been developed to overcome the limitations of cloud-based networks and to address the challenges posed by the massive growth of IoT devices. This paradigm can provide better Quality of Service (QoS) in terms of low energy consumption and fast response, and cope with latency and bandwidth limitations. Since IoT applications are offered in the form of multiple IoT services with different QoS requirements, it is essential to develop an efficient IoT service deployment mechanism in a fog environment with distributed fog nodes and centralized fog servers. This is referred to as the Fog Services Placement (FSP) problem. Hence, we propose a QoS-aware IoT services placement policy with different objectives as a multi-objective optimization problem. Given the proven effectiveness of meta-heuristic techniques in solving optimization problems, we have used the Open-source Development Model Algorithm (ODMA) to deploy IoT services on fog nodes called FSP-ODMA. FSP-ODMA uses the service cost, energy consumption, response time, latency, and fog resource utilization as objective functions to find the optimal IoT service placement plan. In addition, we propose a three-layer conceptual computing framework (i.e., cloud-fog-IoT) to describe the interactions between system components and the FSP problem-solving policy. The simulation results obtained demonstrate that the proposed solution increases the resource usage and service acceptance ratio and reduces the service delay and the energy consumption compared with the other metaheuristic-based mechanisms. [ABSTRACT FROM AUTHOR]

Due to the unique low rigidity of thin-walled parts, significant machining deformation may occur in the milling process. A deformation prediction model is presented in this paper while considering the effect of the removed material on the global stiffness matrix. Aiming at reducing the scale of the global stiffness matrix, the super-element method is firstly used and the scale of the stiffness matrix is significantly reduced about 30%. And then, the stiffness matrix of the in-process workpiece (IPW) is directly obtained by eliminating the contribution of the removed nodes in the global stiffness matrix. This method can avoid re-building the geometric model or re-meshing the finite element (FE) model in the machining process. To improve the inverse calculation efficiency of the stiffness matrix, a novel nodes re-sorting method is proposed based on the calculation order of the matrix blocks in LU decomposition and inverse calculation. Furthermore, the optimal stiffness direction is discussed and applying the cutting force in this direction can minimize the machining deformation. The simulation results verified the existence of the optimal stiffness direction. Finally, the simulation and experiment are carried out to validate the accuracy of the proposed model. [ABSTRACT FROM AUTHOR]

This study aims to explore the relationships between electricity consumption and per capita GDP, urbanization rate, and the proportion of tertiary industry in China during 2005–2018. The results demonstrate that electricity consumption and its determinants are cointegrated. Then fully modified ordinary least square (FMOLS) and fixed effect with varying coefficients and intercept techniques are used to explore the relationships. The empirical results show that all three factors positively affect electricity consumption, per capita GDP has exerted positive impacts on electricity consumption in the 28 provinces, urbanization rate also contributes a positive influence on electricity consumption in 29 provinces, while the positive effect of the proportion of tertiary industry emerges only in 10 provinces. Meanwhile, the urbanization rate makes the most considerable contribution to electricity consumption, while the proportion of the tertiary industry is the least essential determinant. The panel causality results reveal that per capita GDP and urbanization rate cause electricity consumption in the short run and per capita GDP and electricity consumption Granger cause each other in the long run. Finally, we propose policy implications including enhancing the security and reliability of power supply and optimizing the structure of electricity consumption in different industries in China. [ABSTRACT FROM AUTHOR]

The growing share of renewable energy has an increasingly significant impact on the electricity market. Locational marginal price (LMP), as a sensitive price signal, has a potential but considerable correlation with renewable energy generation. In this context, this paper focuses on the joint fluctuation laws between LMP and renewables consumed to generate electricity. At first, LMP and renewables consumption data from Independent System Operator New England (ISO‐NE) are collected and preprocessed. Then, through highly comparative time‐series analysis (hctsa), it is found that discrete symbolization features have effective description ability. Therefore, a coarse‐grained method is conducted to convert the real matrix data into a symbol vector based on numerical distribution analysis. Next, joint fluctuation complex networks are constructed according to the symbol vector. From a global perspective, the joint fluctuation network follows an exponential distribution and exhibits hierarchical modularity. From a local perspective, the joint fluctuation network follows a power‐law distribution. The research results of this paper provide a new perspective to understand the evolution of the electricity market with large‐scale renewable energy and have reference value for identifying the valuable joint fluctuation patterns and improving the LMP forecast results. [ABSTRACT FROM AUTHOR]

To identify a new regimen to optimize treatment for patients with newly diagnosed type 2 diabetes (T2DM) by short-term continuous subcutaneous insulin infusion (CSII) alone. Methods. 60 patients with newly diagnosed T2DM were randomized into two groups (n=30 each) and treated for 2 weeks with CSII alone (CSII group) or with CSII plus sitagliptin (CSII + Sig group). The glycemic variability of the patients was measured using a continuous glucose monitoring system (CGMS) for the last 72 hours. A standard meal test was performed before and after the interventions, and the levels of glycated albumin, fasting glucose, fasting C-peptide, postprandial 2 h blood glucose, and postprandial 2 h C-peptide were examined. Results. Compared with the CSII group, the indicators of glycemic variability, such as the mean amplitude of glycemic excursion (MAGE) and the standard deviation of blood glucose (SDBG), were decreased significantly in the CSII + Sig group. The changes before and after treatment in the C-peptide reactivity index (ΔCPI) and the secretory unit of islet in transplantation index (ΔSUIT) indicated a significant improvement in the CSII + Sig group. Conclusions. Add-on therapy with sitagliptin may be an optimized treatment for patients with newly diagnosed T2DM compared with short-term CSII alone. [ABSTRACT FROM AUTHOR]

To identify a new regimen to optimize treatment for patients with newly diagnosed type 2 diabetes (T2DM) by short-term continuous subcutaneous insulin infusion (CSII) alone. Methods. 60 patients with newly diagnosed T2DM were randomized into two groups (n=30 each) and treated for 2 weeks with CSII alone (CSII group) or with CSII plus sitagliptin (CSII + Sig group). The glycemic variability of the patients was measured using a continuous glucose monitoring system (CGMS) for the last 72 hours. A standard meal test was performed before and after the interventions, and the levels of glycated albumin, fasting glucose, fasting C-peptide, postprandial 2 h blood glucose, and postprandial 2 h C-peptide were examined. Results. Compared with the CSII group, the indicators of glycemic variability, such as the mean amplitude of glycemic excursion (MAGE) and the standard deviation of blood glucose (SDBG), were decreased significantly in the CSII + Sig group. The changes before and after treatment in the C-peptide reactivity index (ΔCPI) and the secretory unit of islet in transplantation index (ΔSUIT) indicated a significant improvement in the CSII + Sig group. Conclusions. Add-on therapy with sitagliptin may be an optimized treatment for patients with newly diagnosed T2DM compared with short-term CSII alone. [ABSTRACT FROM AUTHOR]

To determine serum cytokine profiles in Graves’ disease (GD) patients with or without active and inactive thyroid associated ophthalmopathy (TAO), we recruited 65 subjects: 10 GD only (without TAO), 25 GD + active TAO, 20 GD + TAO, and 10 healthy controls. Liquid chip assay was used to measure serum Th1/Th2/Th17 cytokines including IFN-γ (interferon-gamma), TNF-α (tumor necrosis factor-alpha), IL-1α (interleukin-1 alpha), IL-1Ra (IL-1 receptor antagonist), IL-2, IL-4, IL-6, and IL-17 and two chemokines: RANTES (regulated upon activation, normal T cell expressed and secreted) and IP-10 (IFN-γ-induced protein 10). Serum levels of TSH (thyroid stimulating hormone) receptor autoantibodies (TRAb) were measured using an enzyme linked immunosorbent assay. Compared with healthy controls, TAO patients showed significantly elevated serum levels of IFN-γ, TNF-α, IL-1α, IL-4, IL-6, IL-17, and IP-10. Comparing active and inactive TAO, serum Th1 cytokines IFN-γ and TNF-α were elevated in active TAO, while serum Th2 cytokine IL-4 was elevated in inactive TAO. Serum Th17 cytokine IL-17 was elevated in GD but reduced in both active and inactive TAO. A positive correlation was found between TRAb and IFN-γ, TNF-α, IL-1α, IL-2, IL-4, and IL-6. Taken together, serum Th1/Th2/Th17 cytokines and chemokines reflect TAO disease activity and may be implicated in TAO pathogenesis. [ABSTRACT FROM AUTHOR]