Various sudden shifts in financial market conditions over the past decades have demonstrated the significant impact of market structural breaks on firms' credit behavior. To characterize such effect quantitatively, we develop a continuous-time modulated Markov model for firms' credit rating transitions with the possibility of market structural breaks. The model takes a semi-parametric multiplicative regression form, in which the effects of firms' observable covariates and macroeconomic variables are represented parametrically and nonparametrically, respectively, and the frailty effects of unobserved firm-specific and market-wide variables are incorporated via the integration form of the model assumption. We further develop a mixtured-estimating-equation approach to make inference on the effect of market variations, baseline intensities of all firms' credit rating transitions, and rating transition intensities for each individual firm. We then use the developed model and inference procedure to analyze the monthly credit rating of U.S. firms from January 1986 to December 2012, and study the effect of market structural breaks on firms' credit rating transitions.

Inflammation is known to be risk factors for metabolic diseases. The purpose of this study was to develop a Food-based Index of Dietary Inflammatory Potential (FBDI) and conduct its validation assessment. This study analyzed raw data from Korean Genome and Epidemiology Study 2012–2014 data of 17,771 people. We carried out the correlation analysis between 51 food groups and hs-CRP. The FBDI was developed by multiple regression method with hs-CRP and selected 17 food group. For the validation of FBDI, 7795 people in the 6th Korea National Health and Nutrition Examination Survey (KNHAES) was used. Binary logistic regression analysis was used for risk analysis of metabolic syndrome and FBDI. The FBDI model included that 7 were composed of anti-inflammatory food groups and 3 of inflammatory food groups. The FBDI was calculated by multiplying the intake of food group by β coefficients. KNHAES were included in the validation of FBDI. The risk of metabolic syndrome was found to be 2.152 times higher in the group with the highest FBDI than in the group with the lowest one (95% Cl:1.458–3.178, p for trend = 0.000). This study developed FBDI reflecting food intake for Koreans, which showed a significant relationship with the risk of metabolic syndrome.

This work aims to describe the dielectric behaviours of four main tissues in the human forearm using mathematical modelling, including fat, muscle, blood, and bone. Determining the electrical response of multiple tissues can help develop physiological monitoring of an organ or a body’s section by filtering out the impedance contributions from the surrounding tissues to blood flow-induced impedance variations. Multi-frequency bioimpedance analysis (MF-BIA) was initially performed using the finite element method (FEM) with a 3D forearm model followed by a pilot study to characterise the response of actual forearm tissues from 1 kHz to 349 kHz. Both the simulation and experimental results were fitted to a single-dispersion Cole model (SDCM) and a multi-dispersion Cole model (MDCM) to determine the Cole parameters for each tissue. The correlation analysis and Bland-Altman plot indicated a good fit between raw and fitted impedance values using both SDCM and MDCM. Overall, MDCM exhibited better performance in fitting and estimation of the Cole parameters with correlation coefficient (R2) of 0.99 and 0.97, root mean squared error (RMSE) of 0.09 Ω and 0.14 Ω, and mean difference (mean±standard deviation) of 0.00±0.09 Ω and -0.03±0.14 Ω for the real part and imaginary part of impedance, respectively.

In this present study, 3-pentadecyl-phenol was selected as a modifier to prepare a foamable phenolic resin with excellent performance, which was successfully prepared by in-situ modification. Fourier transform infrared spectroscopy (FT-IR) and nuclear magnetic resonance (¹H NMR, ¹³C-NMR) were used to test and characterize the molecular structure of the modified resin. The results showed that 3-pentadecyl-phenol successfully modified the molecular structure of phenolic resin with a reduction in resin gel time. The effect of changing the added amount of 3-pentadecyl-phenol on the mechanical properties, microstructure and flame retardancy of the modified foam was investigated. The results showed that when the amount of added 3-pentadecyl-phenol was 15% of the total amount of phenol, this resulted in the best toughness of the modified foam, which could be increased to 300% compared to the bending deflection of the unmodified phenolic foam. The cell structure showed that the modified phenolic foam formed a more regular and dense network structure and the closed cell ratio was high. Furthermore, the compressive strength, bending strength, and limited oxygen index were improved, while the water absorption rate was lowered. However, the foam density could be kept below 40 mg/cm³, which does not affect the load.

Abstract：Commuting of residents in big city often brings tidal traffic pressure or congestions. Understanding the causes behind this phenomenon is of great significance for urban space optimization. Various spatial big data make possible the fine description of urban residents travel behaviors, and bring new approaches to related studies. The present study focuses on two aspects: one is to obtain relatively accurate features of commuting behaviors by using mobile phone data, and the other is to simulate commuting behaviors of residents through the agent-based model and inducing backward the causes of congestion. Taking the Baishazhou area of Wuhan, a local area of a mega city in China, as a case study, travel behaviors of commuters are simulated: the spatial context of the model is set up using the existing urban road network and by dividing the area into travel units; then using the mobile phone call detail records (CDR) of a month, statistics of residents' travel during the four time slots in working day mornings are acquired and then used to generated the OD matrix of travels at different time slots; and then the data are imported into the model for simulation. By the preset rules of congestion, the agent-based model can effectively simulate the traffic conditions of each traffic intersection, and can also induce backward the causes of traffic congestion using the simulation results and the OD matrix. Finally, the model is used for the evaluation of road network optimization, which shows evident effects of the optimizing measures adopted in relieving congestion, and thus also proves the value of this method in urban studies.

In recent years, the use of solid waste fillers to partially replace natural fillers in asphalt mixtures to produce high-performance asphalt mixtures has received widespread attention. However, differences in the material properties of solid waste fillers remain a problem for this recycling method. To address this issue, limestone powder in asphalt mixtures was replaced by three solid waste fillers (steel slag powder, tailings powder and calcium carbide slag powder) in this study. The chemical composition of the fillers was first characterized to assess the homogeneity of the material. Then, AC and SMA asphalt mixtures were designed and produced and characterized for wet stability. The results showed that asphalt mixtures with solid waste fillers were superior to LP asphalt mixtures in terms of resistance to water damage, and steel slag powder showed the best improvement in moisture stability of asphalt mixtures. The optimum substitution of solid waste filler for limestone filler was 25%. In addition, the moisture stability of asphalt mixture with limestone filler was significantly improved with the addition of anti-stripping agents. In contrast, the moisture stability of asphalt mixtures with solid waste filler was slightly improved. Solid waste fillers could be used in asphalt mixtures and have a similar function as the anti-stripping agent. In summary, the use of solid waste fillers to replace mineral fillers in asphalt mixtures is a reliable, value-added, recycling option.

Wastes from social economic activities had great impact on water quality thereby limiting water usability for domestic purposes. Sewages discharge from people activities, usually consist of undesirable concentrations of soluble chemicals that infiltrate into the surrounding surface and underground water, and then constitute health risk to the populace. In order to investigate the concentration characteristics and health risk for the local residents in Nandong Underground River Watershed (NURW), eleven common heavy metals in the water body analysis were conducted. Health risk assessment (HRA) was taken to analyze eleven heavy metals of 84 water samples from surface and underground waters in NURW: 36 samples underground water and 48 samples surface water. Our results showed that the heavy metals concentration order is that of Fe > Al > Mn > Zn > As > Cd > Pb > Cr > Ni > Cu > Hg. Correlation analysis indicates that these eleven metal elements have certain similarity on material source and migration transformation. The health risks for local residents exposed to metal elements in the water of NURW mainly from carcinogenic risk (10−6～10−4 a−1) through drinking way, and the health risk of heavy metals exposed to children through drinking way was much higher than adults. The maximum exposing health risks of Cr in both underground and surface water were higher than the recommendation standard (5.0×10-5 a-1) from ICRP, and all the values over the standard (5.0×10-6 a-1) recommended by the Swedish Environmental Protection Agency and the Dutch Ministry of Construction and Environment and the British Royal Society. The results of health risk assessment shows that Cr in the water of NURW was the mainly source of carcinogenic risk for the local residents, following by Cd and As. Consequently, it is necessary to control the three carcinogenic metals when the water was used as drinking water source.

With the global warming and the frequent occurrences of harsh environments, mooring line failures are frequent. Response analysis of the platform structure and its residual mooring system under multiple mooring line failures is needed. Therefore, it is necessary to investigate the change law of platform motion response after mooring line failure to find out the reasons for the change. Studies for different failure combinations of mooring lines show that the variation of the steady-state equilibrium position of the platform is closely related to the stiffness, with a clear functional. The duration and amplitude of the transient response are mainly influenced by the Morison drag force. And it was found that the suspended mooring line reduced the motion responses. It is also found that the mooring line failure increased the effective tension and suspension length of the riser. Based on the improved Dezert-Smarandache theory (DSmT), it is calculated that mooring line failure has little effect on the failure probability in different zones of the riser.

Glucagon-like peptide-1 (GLP-1) is an incretin hormone that acts on the pancreas to increase insulin and decrease glucagon secretion. Albuminuria is the pivotal marker for diabetic nephropathy, which is the leading microvascular complication of diabetes mellitus. Most of the previous studies mainly focused on the clinical trials of the therapeutic renal protective effect after administration of GLP-1 receptor agonists (GLP-1 RAs), not prior to administration. Therefore, this study aimed to investigate the association between fasting plasma GLP-1 levels and albuminuria before GLP-1 RA administration. A cross-sectional study was designed to evaluate the association between fasting plasma GLP-1 levels and albuminuria in patients with type 2 diabetes mellitus (T2DM). A total of 68 T2DM participants were analyzed from the data at Wonkwang University Hospital in Iksan, Korea. Logistic regression analysis was performed to evaluate the odds ratio (OR) and 95% confidence interval (CI) of the incidence of albuminuria between the GLP-1 low group (Group L) and the high group (Group H). The OR (95% CI) for the incidence of albuminuria comparing the Group L with the Group H of fasting plasma GLP-1 levels was 3.410 (1.160-10.023), p = 0.026 after adjustment for age, gender, fasting plasma glucose, HbA1c, C-peptide, the use of ACE inhibitors or ARBs, SGLT-2 inhibitors, and DPP-4 inhibitors. As a continuous variable, the OR (95% CI) for the incidence of albuminuria associated with the reduction of each 1 pmol/L in fasting plasma GLP-1 levels was 1.673 (1.173-1.870), p = 0.018, after full adjustment. This study showed the negative association between fasting plasma GLP-1 levels and the incidence of albuminuria in Korean patients with T2DM, before GLP-1 RA administration. This result suggests that endogenous GLP-1 may play a role in attenuating albuminuria.

Background/Aim: microRNAs (miRNAs) are key regulators of both physiological and pathophysiological mechanisms in diabetes and gastrointestinal (GI) dysmotility. Our previous studies have demonstrated the therapeutic potential of miR-10a-5p mimic and miR-10b-5p mimic (miR-10a/b mimics) in rescuing diabetes and GI dysmotility in murine models of diabetes. In this study, we elucidated the safety profile of a long-term treatment with miR-10a/b mimics in diabetic mice. Methods: Male C57BL6 mice were fed a high-fat, high-sucrose diet (HFHSD) to induce diabetes and treated by five subcutaneous injections of miR-10a/b mimics for a 5-month period. We examined the long-term effect of the miRNA mimics on diabetes and GI dysmotility, including an assessment of cancer risk as well as liver and colon inflammation using cancer and inflammatory biomarkers. Results: HFHSD-induced diabetic mice subcutaneously injected with miR-10a/b mimics monthly for 5 months exhibited a marked reduction in fasting blood glucose levels with restoration of insulin and significant weight loss, improved glucose and insulin intolerance, and restored GI transit time. In addition, the miR-10a/b mimic treated diabetic mice showed no indication of risk for cancer development and inflammation induction in the liver, colon, and blood for the 5 months post injections. Conclusion: This longitudinal study demonstrates that miR-10a/b mimics, when subcutaneously administered in diabetic mice, effectively alleviate diabetes and GI dysmotility for 5 months with no discernible risk for cancer or inflammation in the liver and colon. The sustained efficacy and favorable safety profiles position miR-10a/b mimics as promising candidates in miRNA-based therapeutics for diabetes and GI dysmotility.

Biological neural network (BNN) is the core brain for creature to accomplish its intelligent behaviors through unique network structure and mechanisms. It also inspires controlling human-designed autonomous agents including robots to generate more advanced intelligent behaviors by mimicking the neural control mechanism of creatures at a deeper and more interactive level. Here, we constructed a whole-brain neural network model of Caenorhabditis elegans (C. elegans), which characterizes the electrochemical processes at the level of cellular synapse. The neural network simulation integrates computational programming and visualization of neurons and synapse connections of C. elegans, containing the specific controllable circuits summarization with their dynamic characteristics within the whole network. To illustrate its particular intelligent control capability in terms of robotics, we introduce the first innovative methodology for applying the BNN model to a 12-legged robot’s movement control based on the established numerical simulation platforms. We accomplished and designed two methods and corresponding encoding processes, one involving orientation control and the other involving locomotion generation, to demonstrate the intelligent control performance of BNN. Both simulation and experiment results indicate that the robot exhibits stronger autonomy and more intelligent moving performance under the control of BNN. We then summarized the contributions for digitalizing the C. elegans’ whole-brain neural network in real-time and utilizing it to control robot in a closed loop to validate its advanced intelligence control ability in terms of a scientific robot.