Supply interruption supply chain network model with uncertain demand: an application of chance-constrained programming with fuzzy parameters

The downstream supply interruption of manufacturers is a disaster for the company when the demand is uncertain in the market; a fuzzy programming with fuzzy parameters model of supply interruption supply chain network is established by simulating market operation rules. The aim of the current study is to build a fuzzy chance-constrained programming method which is developed for supporting the uncertainty of demand. This method ensured that the fuzzy constraints can be satisfied at specified confidence levels, leading to cost-effective solutions under acceptable risk magnitudes. Finally, through the case of the electronic product manufacturing enterprise, the feasibility and effectiveness of the proposed model are verified by adopting a sensitivity analysis of capacity loss level and minimizing objective function. Numerical simulation shows that selecting two manufacturing centers can effectively reduce the supply chain cost and maintain business continuity

System dynamics model based on evolutionary game theory for quality supervision among construction stakeholders

To address the gap, that is, few studies have explored the influence of the participants’ interactions with one another during construction quality supervision, this paper proposes a system dynamics model based on evolutionary game theory to describe the complex and dynamic interactions among tripartite stakeholders in China, including the project owner (PO), construction supervising engineer (CSE), and construction contractor (CC). First, the replicated dynamic equation set is established in terms of expense targets. Second, the equilibrium solutions of the equation set are obtained to test strategy options. The trends of system fluctuations caused by penalty and reward changes are also analyzed. Finally, the stability of the proposed model is improved by integrating a dynamic penalty–reward scenario into the evolutionary strategy of the PO. Simulation results show that: 1) the evolutionary stable strategy does not exist in initial interactions, 2) the degrees of penalty and reward considerably affect the CC’s rate variable, and 3) the dynamic penalty–reward scenario could effectively improve the stability of the proposed model. The unsteadiness of the quality supervision system and the stability control scenario could help in understanding the impact of interactions among stakeholders and provide suggestions for optimizing quality supervision procedures

Identifying risk factors affecting exercise behavior among overweight or obese individuals in China

BackgroundThe disease burden caused by obesity has increased significantly in China. Less than 30% of those who are obese meet the weekly physical activity standards recommended by the WHO. Risk factors that influence exercise behavior in people with obesity remain unclear.MethodsBased on the survey from the Chinese General Social Survey program (CGSS) in 2017, 3,331 subjects were identified and enrolled in the univariate and multiple probit regression models. We aimed to identify the association between SRH and the exercise behavior of obese people and further explore the influencing factors of active physical activity in this group of people.ResultsThe proportion of active physical activity in obese people was 25%. Groups with better SRH, higher education and income were more likely to participate in sports. Obese people who lived in rural areas, were unmarried or divorced, or fell within the age range of 35–40 had a significantly lower percentage of engagement in active physical activity.ConclusionsThe proportion of people with obesity who meet the WHO recommendation for physical activity in China is not ideal. Health promotion programs for those who are obese need to be further strengthened and targeted, especially for rural areas, low-income families, and middle-aged obese people

A real-time control approach based on intelligent video surveillance for violations by construction workers

The unsafe behavior of workers is the main object of construction safety management, in which violations require increased attention due to their pernicious consequences. However, existing studies have merely discussed violations separately from unsafe behaviors. To respond quickly to workers’ violations on site, this study proposes a real-time control approach based on intelligent video surveillance. First, scenes reflecting unsafe behaviors are automatically acquired through camera-based behavior analysis technology. Meanwhile, the time corresponding to the construction phase is recorded. Second, the temporal association rule model of worker’s unsafe behavior is constructed, and the rule “construction phase→unsafe behavior” is determined by the Apriori algorithm to identify target behaviors necessary for critical control in different construction phases. Finally, statistical process control is used to find the trends of violations with frequency and mass characteristics through the dynamic monitoring of target behavior. In addition, real-time alerts of these unsafe acts are produced simultaneously. A pilot study is conducted on the cross-river tunnel project in Wuhan city, Hubei, China, and the violations related to construction machineries is proven to be controllable. Thus, the proposed approach promotes behavioral safety management on construction since it effectively controls workers’ violations by real-time monitoring and analysis

A Comprehensive RNA Expression Signature for Cervical Squamous Cell Carcinoma Prognosis

Clinicopathological characteristics alone are not enough to predict the survival of patients with cervical squamous cell carcinoma (CESC) due to clinical heterogeneity. In recent years, many genes and non-coding RNAs have been shown to be oncogenes or tumor-suppressors in CESC cells. This study aimed to develop a comprehensive transcriptomic signature for CESC patient prognosis. Univariate, multivariate, and Least Absolute Shrinkage and Selection Operator penalized Cox regression were used to identify prognostic signatures for CESC patients from transcriptomic data of The Cancer Genome Atlas. A normalized prognostic index (NPI) was formulated as a synthetical index for CESC prognosis. Time-dependent receiver operating characteristic curve analysis was used to compare prognostic signatures. A prognostic transcriptomic signature was identified, including 1 microRNA, 1 long non-coding RNA, and 6 messenger RNAs. Decreased survival was associated with CESC patients being in the high-risk group stratified by NPI. The NPI was an independent predictor for CESC patient prognosis and it outperformed the known clinicopathological characteristics, microRNA-only signature, gene-only signature, and previously identified microRNA and gene signatures. Function and pathway enrichment analysis revealed that the identified prognostic RNAs were mainly involved in angiogenesis. In conclusion, we proposed a transcriptomic signature for CESC prognosis and it may be useful for effective clinical risk management of CESC patients. Moreover, RNAs in the transcriptomic signature provided clues for downstream experimental validation and mechanism exploration

Properties and Asteroseismological analysis of a new ZZ ceti discovered by TMTS

Tsinghua university-Ma Huateng Telescope for Survey (TMTS) aims to discover rapidly evolving transients by monitoring the northern sky. The TMTS catalog is cross-matched with the white dwarf (WD) catalog of Gaia EDR3, and light curves of more than a thousand WD candidates are obtained so far. Among them, the WD TMTS J23450729+5813146 (hereafter J2345) is one interesting common source. Based on the light curves from the TMTS and follow-up photometric observations, periods of 967.113 s, 973.734 s, 881.525 s, 843.458 s, 806.916 s and 678.273 s are identified. In addition, the TESS observations suggest a 3.39 h period but this can be attributed to the rotation of a comoving M dwarf located within 3". The spectroscopic observation indicates that this WD is DA type with Teff = 11778+/-617K,log g = 8.38+/-0.31,mass=0.84+/-0.20Msun and age=0.704+/-0.377 Gyrs. Asteroseismological analysis reveals a global best-fit solution of Teff =12110+/-10K and mass=0.760+/-0.005Msun,consistent with the spectral fitting results, and Oxygen and Carbon abundances in the core center are 0.73 and 0.27, respectively. The distance derived from the intrinsic luminosity given by asteroseismology is 93 parsec, which is in agreement with the distance of 98 parsec from Gaia DR3. Additionally, kinematic study shows that this WD is likely a thick disk star. The mass of its zero-age main-sequence mass is estimated to be 3.08 Msun and has a main-sequence plus cooling age of roughly 900 Myrs.Comment: 10 pages, 10 figures, accepted for publication in MNRA

Chronic exposure to low-level lipopolysaccharide dampens influenza-mediated inflammatory response via A20 and PPAR network

Influenza A virus (IAV) infection leads to severe inflammation, and while epithelial-driven inflammatory responses occur via activation of NF-κB, the factors that modulate inflammation, particularly the negative regulators are less well-defined. In this study we show that A20 is a crucial molecular switch that dampens IAV-induced inflammatory responses. Chronic exposure to low-dose LPS environment can restrict this excessive inflammation. The mechanisms that this environment provides to suppress inflammation remain elusive. Here, our evidences show that chronic exposure to low-dose LPS suppressed IAV infection or LPS stimulation-induced inflammation in vitro and in vivo. Chronic low-dose LPS environment increases A20 expression, which in turn positively regulates PPAR-α and -γ, thus dampens the NF-κB signaling pathway and NLRP3 inflammasome activation. Knockout of A20 abolished the inhibitory effect on inflammation. Thus, A20 and its induced PPAR-α and -γ play a key role in suppressing excessive inflammatory responses in the chronic low-dose LPS environment