Collaborative Evolution Mechanism and Simulation of Construction Waste Recycling Stakeholders Based on Social Network

With the continuous advancement of urbanization, a huge amount of construction waste is generated in large-scale construction activities, which has aggravated the problems of environmental pollution, waste of resources and destruction of city appearance. Construction waste recycling can effectively solve these problems. However, the recycling rate of construction waste is low in China. Therefore, this paper, firstly through the way of literature analysis and questionnaire investigation, analyzes the factors that influence construction waste resource utilization, determines the key influence factors and the stakeholders in the process of construction waste resource utilization, and uses social network analysis method to identify core stakeholders. On this basis, this paper selects construction enterprises and recycling enterprises as the game subjects, and the government and the public as the external environment to explore the influence of the external environment on the cooperation behavior of the two stakeholders, and uses Matlab simulation to analyze the influence of external variables on the decision-making behavior evolution of the two stakeholders. The research results show that the government, construction enterprises, recycling enterprises and the public are the four core stakeholders of the construction waste recycling system, which have the power to control the information transmission among other stakeholders and play a great supporting role in the smooth implementation of the construction waste recycling project. Among them, the construction enterprise and recycling enterprise are the construction waste recycling system’s two stakeholders playing the pivotal role, and the government and the public are the external environment of the construction waste recycling system’s incentive and regulatory effect. The difference between the benefits and costs of the two stakeholders and the effect intensity of the external environment determines the stable state of the system, that is, the stronger the effect of the external environment and the larger the difference, the more the behavior of the two tends toward the recycling, on-site recycling strategy. Government penalties and rewards can effectively reduce the illegal dumping of construction waste, while excessive penalties and rewards have limitations in controlling illegal dumping. Public participation can effectively improve the efficiency of government supervision. The research results help to deeply understand the behavior, needs and cooperation of stakeholders in the construction waste recycling market, improve the efficiency of cooperation between construction enterprises and recycling enterprises, and provide management inspiration for the construction waste recycling practice

Serum CXCL16 as a novel marker of renal injury in type 2 diabetes mellitus.

BACKGROUND: Soluble C-X-C chemokine ligand 16 (CXCL16), a scavenger receptor for oxidized low density lipoprotein, has been shown to promote atherogenic effects in vivo and to predict long-term mortality in acute coronary syndrome. The aim of this study was to explore the association of circulating CXCL16 levels with diabetic subjects with and without renal disease. METHODOLOGY/PRINCIPAL FINDINGS: One hundred twenty Chinese subjects, which included patients with type 2 diabetes mellitus (T2DM), diabetic nephropathy (DN), and CKD, as well as healthy controls, were enrolled in this study. Serum CXCL16 levels were examined by immunoassay and other clinical biochemical parameters were tested based on standard methods. Our results indicated that, HDL and LDL cholesterol levels are significantly different in DN but not in T2D patients in comparison with healthy subjects. On the other hand, Serum CXCL16 levels were significantly increased in DN subjects compared with age and gender matched healthy and T2DM subjects (p<0.05 respectively). However, no significant changes in serum CXCL16 levels were found between T2DM and healthy subjects. Furthermore, serum CXCL16 concentration negatively correlated with estimated glomerular filtrate rate, creatinine clearance rate and blood albumin, and positively with 24 h proteinuria, blood urea nitrogen (BUN), creatinine, and uric acid after adjusting for age, gender and BMI in subjects with DN. Multiple stepwise regression analyses indicated that serum CXCL16 levels were independently associated with serum 24 h proteinuria, and BUN (p<0.05 respectively). CONCLUSION: Serum CXCL16 may be an indicator of renal injury in subjects with T2DM. Understanding the exact mechanism of elevated CXCL16 in subjects with DN requires further study

Multiple stepwise regression analysis showing variables independently associated with serum CXCL16 level.

<p>Multiple stepwise regression analysis showing variables independently associated with serum CXCL16 level.</p

Serum concentration of CXCL16 (A), creatinine (B), BUN (C), and uric acid (D) among T2DM, DN, CKD, and healthy subjects.

<p>*, p<0.05; **, p<0.01; ***, p<0.001.</p

Correlation of serum CXCL16 levels with CCR (A), eGFR (B), creatinine (C), BUN (D), 24 h proteinuria (E), and blood albumin (F) in subjects with DN.

<p>Correlation of serum CXCL16 levels with CCR (A), eGFR (B), creatinine (C), BUN (D), 24 h proteinuria (E), and blood albumin (F) in subjects with DN.</p

Serum concentration of total cholesterol(A), HDL (B), LDL (C), and triglycerides (D) among T2DM, DN, CKD, and healthy subjects.

<p>*, p<0.05.</p

Anthropometric parameters and biochemical index among subjects with T2DM, DN, CKD and healthy.

<p>NS: not significant. Results are expressed as frequencies, mean±SD, or median (interquartile range) as appropriate. ^a, p<0.05 <i>vs</i>. Healthy; ^b, p<0.01 <i>vs</i>. Healthy; ^c, p<0.001 <i>vs</i>. Healthy; ^†, p<0.05 <i>vs</i>. DN; ^††, p<0.05 <i>vs</i>. DN; ^†††, p<0.05 <i>vs</i>. DN.</p

Correlation of serum CXCL16 levels with anthropometric parameters, biochemical indexes and other relevant factors in subjects with DN (n = 30).

*<p>Adjusted for age, gender, and BMI. NS: not significant.</p