The role of information industry convergence in energy transition.

To cope with global climate risks, promoting energy transformation has become a global consensus. China issued a reform policy in 2010 to promote the convergence of the three major information industries, namely broadcasting and television networks, telecommunications networks and the Internet (TPR policy). However, is the convergence of information industries able to promote energy transition? This study constructs a quasi-natural experimental framework using China's TPR policy as a representative case of industrial convergence. Using city-level panel data between 2003 and 2016 in China and a multi-period difference-in-differences model, this study examines the impact of TPR policy on energy transition. The results show that TPR policy positively contributes to energy transition at a 1% significance level. Extensive robustness tests support this finding. This positive effect is particularly evident in regions with less developed communications infrastructure and stricter environmental regulations. Mechanism analysis suggests that TPR policy promotes energy transition by improving the level of information networks, promoting technological innovation, and optimizing industrial structure. The findings of this paper emphasize the importance of information industry convergence in facilitating energy transformation.

Urban public services and fertility intentions of internal migrants in China.

As China continues to implement its progressive fertility promotion policy, there has been a drastic decline in the fertility rate. Given that the migrant population constitutes more than a quarter of China's total population, enhancing the willingness of this demographic to have additional children through policy-guided urban public services is pivotal for optimizing China's population development strategy. This study analyzes the influence of urban public services on the reproductive intentions of the migrant population, utilizing data from 110,667 migrant families with one child, drawn from China's Migrant Population Dynamic Monitoring data in 2016 and 2018. The data analysis reveals several key findings: (1) Urban public services, overall, exhibit a notable positive effect on the willingness of the migrant population to have more children, albeit with limitations and a declining trend. (2) Among urban public services, primary basic education significantly impacts the willingness of the migrant population to expand their families. (3) Large cities have created a 'reverse screening' effect on the migrant population, leading to differential access to public services. This scenario caters effectively to the high human capital migrant individuals while reducing accessibility to livelihood public services for the low human capital migrant population. This paper critically evaluates China's progressively adjusted fertility policy from the perspective of the migrant population. It underscores the necessity of establishing a comprehensive fertility support policy system across China.

Bifunctional Mo2N Nanoparticles with Nanozyme and SERS Activity: A Versatile Platform for Sensitive Detection of Biomarkers in Serum Samples.

The combined application of nanozymes and surface-enhanced Raman scattering (SERS) provides a promising approach to obtain label-free detection. However, developing nanomaterials with both highly efficient enzyme-like activity and excellent SERS sensitivity remains a huge challenge. Herein, we proposed one-step synthesis of Mo2N nanoparticles (NPs) as a "two-in-one" substrate, which exhibits both excellent peroxidase (POD)-like activity and high SERS activity. Its mimetic POD activity can catalyze the 3,3',5,5'-tetramethylbenzidine (TMB) molecule to SERS-active oxidized TMB (ox-TMB) with high efficiency. Furthermore, combining experimental profiling with theory, the mechanism of POD-like activity and SERS enhancement of Mo2N NPs was explored in depth. Benefiting from the outstanding properties of Mo2N NPs, a versatile platform for indirect SERS detection of biomarkers was developed based on the Mo2N NPs-catalyzed product ox-TMB, which acts as the SERS signal readout. The feasibility of this platform was validated using glutathione (GSH) and target antigens alpha-fetoprotein antigen (AFP) and carcinoembryonic antigen (CEA) as representatives of small molecules with a hydroxyl radical (·OH) scavenging effect and proteins with a low Raman scattering cross-section, respectively. The limits of detection of GSH, AFP, and CEA were as low as 0.1 µmol/L, 89.1, and 74.6 pg/mL, respectively. Significantly, it also showed application in human serum samples with recoveries ranging from 96.0 to 101%. The acquired values based on this platform were compared with the standard electrochemiluminescence method, and the relative error was less than ±7.3. This work not only provides a strategy for developing highly active bifunctional nanomaterials but also manifests their widespread application for multiple biomarkers analysis.

Simplified Methods for Modelling Dependent Parameters in Health Economic Evaluations: A Tutorial.

BACKGROUND: In health economic evaluations, model parameters are often dependent on other model parameters. Although methods exist to simulate multivariate normal (MVN) distribution data and estimate transition probabilities in Markov models while considering competing risks, they are technically challenging for health economic modellers to implement. This tutorial introduces easily implementable applications for handling dependent parameters in modelling. METHODS: Analytical proofs and proposed simplified methods for handling dependent parameters in typical health economic modelling scenarios are provided, and implementation of these methods are illustrated in seven examples along with the SAS and R code. RESULTS: Methods to quantify the covariance and correlation coefficients of correlated variables based on published summary statistics and generation of MVN distribution data are demonstrated using examples of physician visits data and cost component data. The use of univariate normal distribution data instead of MVN distribution data to capture population heterogeneity is illustrated based on the results from multiple regression models with linear predictors, and two examples are provided (linear fixed-effects model and Cox proportional hazards model). A conditional probability method is introduced to handle two or more state transitions in a single Markov model cycle and applied in examples of one- and two-way state transitions. CONCLUSIONS: This tutorial proposes an extension of routinely used methods along with several examples. These simplified methods may be easily applied by health economic modellers with varied statistical backgrounds.

Effect modification of time spent outdoors on the association between early childhood overweight and myopia: a one-year follow-up study.

BACKGROUND: This study examined the moderating role of outdoor time on the relationship between overweight and myopia. METHODS: The data for this study was obtained from a prospective study in Shanghai, where non-myopic children wore wristwear and were followed up for 1 year. Eye examinations were performed at each visit. The modification effect was assessed on the additive scale using multivariable logistic regression, and relative excess risk due to interaction was used to calculate the modification effect. RESULTS: A total of 4683 non-myopic children were included with 32.20% being overweight at baseline. Following a 1-year period, 17.42% of children had myopia. When compared to those who spent <90 minutes outdoors, children who spent >120 had a relative risk of myopia onset that was reduced to 0.61. As time spent outdoors decreased, more risks of myopia onset were identified among overweight children than among normal children, the modification effect on the additive scale was -0.007, with ~70% of this effect attributed to the modifying influence of outdoor time. CONCLUSIONS: Increasing outdoor time can reduce myopia more among overweight children than normal. Future interventions should focus on outdoor activities among overweight children to reduce myopia risks.

MCT1-governed pyruvate metabolism is essential for antibody class-switch recombination through H3K27 acetylation.

Monocarboxylate transporter 1 (MCT1) exhibits essential roles in cellular metabolism and energy supply. Although MCT1 is highly expressed in activated B cells, it is not clear how MCT1-governed monocarboxylates transportation is functionally coupled to antibody production during the glucose metabolism. Here, we report that B cell-lineage deficiency of MCT1 significantly influences the class-switch recombination (CSR), rendering impaired IgG antibody responses in Mct1f/fMb1Cre mice after immunization. Metabolic flux reveals that glucose metabolism is significantly reprogrammed from glycolysis to oxidative phosphorylation in Mct1-deficient B cells upon activation. Consistently, activation-induced cytidine deaminase (AID), is severely suppressed in Mct1-deficient B cells due to the decreased level of pyruvate metabolite. Mechanistically, MCT1 is required to maintain the optimal concentration of pyruvate to secure the sufficient acetylation of H3K27 for the elevated transcription of AID in activated B cells. Clinically, we found that MCT1 expression levels are significantly upregulated in systemic lupus erythematosus patients, and Mct1 deficiency can alleviate the symptoms of bm12-induced murine lupus model. Collectively, these results demonstrate that MCT1-mediated pyruvate metabolism is required for IgG antibody CSR through an epigenetic dependent AID transcription, revealing MCT1 as a potential target for vaccine development and SLE disease treatment.

Combining with domiphen bromide restores colistin efficacy against colistin-resistant Gram-negative bacteria in vitro and in vivo.

Today, colistin is considered a last-resort antibiotic for treating multidrug-resistant (MDR) Gram-negative bacteria (GNB). However, the increased and improper use of colistin has led to the emergence of colistin-resistant (Col-R) GNB. Thus, it is urgent to develop new drugs and therapies in response to the ongoing emergence of colistin resistance. In this study, we investigated the antibacterial and antibiofilm activities of the quaternary ammonium compound domiphen bromide (DB) in combination with colistin against clinical Col-R GNB both in vitro and in vivo. Checkerboard assay and time-kill analysis demonstrated significant synergistic antibacterial effects of the colistin/DB combination. The synergistic antibiofilm activity was confirmed through crystal violet staining and scanning electron microscopy (SEM). Furthermore, the colistin/DB combination exhibited increased survival rates in infected larvae and reduced bacterial loads in a mouse thigh infection model. The cytotoxicity measurement and hemolysis test showed that the combination did not adversely affect cell viability at synergistic concentrations. The alkaline phosphatase (ALP) leak test and propidium iodide (PI) staining analysis further revealed that the colistin/DB combination enhanced the therapeutic effect of colistin by altering bacterial membrane permeability. The ROS assays revealed that the combination induced the accumulation of bacterial ROS, leading to bacterial death. In conclusion, our study is the first to identify DB as a colistin potentiator, effectively restoring the sensitivity of bacteria to colistin. It provides a promising alternative approach for combating Col-R GNB infections.

Temperature and salinity sensing characteristics of embedded core optical fiber based on surface plasmon resonance.

An embedded core fiber sensor based on surface plasmon resonance (SPR) principle is developed. In the structure of optical fiber, the middle of the optical fiber cladding is hollowed out. The hollowed-out part is then filled with a temperature-sensitive layer. For the temperature sensitive layer, polydimethylsiloxane(PDMS) is chosen. A metal layer is placed outside the cladding of the optical fiber to detect changes in the external environment and stimulate the SPR effect.The gold metal(Au) layer is also placed between the cladding and the PDMS to stimulate the SPR effect.The refractive index of seawater varies with salinity and temperature through COMSOL Multiphysics finite element simulation. We can measure the two parameters of salinity and temperature at the same time based on the SPR principle. The sensitivity of salinity and temperature calculated by this sensor is 0.193 nm/%, 0.397 nm/°C. Fiber optic sensors use the SPR principle to detect dynamic, real-time, continuous processes. The measurement range is very wide, and the brightness is also very high.Compared with single-channel measurement of single parameter, this sensor can greatly improve the efficiency of two-parameter measurement. The sensor has the advantages of simple structure, low production cost and high sensitivity, which can realize the simultaneous measurement of two parameters and avoid the crosstalk between parameters. It has great research significance.

The Properties of Linezolid, Rifampicin, and Vancomycin, as Well as the Mechanism of Action of Pentamidine, Determine Their Synergy against Gram-Negative Bacteria.

Combining pentamidine with Gram-positive-targeting antibiotics has been proven to be a promising strategy for treating infections from Gram-negative bacteria (GNB). However, which antibiotics pentamidine can and cannot synergize with and the reasons for the differences are unclear. This study aimed to identify the possible mechanisms for the differences in the synergy of pentamidine with rifampicin, linezolid, tetracycline, erythromycin, and vancomycin against GNB. Checkerboard assays were used to detect the synergy of pentamidine and the different antibiotics. To determine the mechanism of pentamidine, fluorescent labeling assays were used to measure membrane permeability, membrane potential, efflux pump activity, and reactive oxygen species (ROS); the LPS neutralization assay was used to evaluate the target site; and quantitative PCR was used to measure changes in efflux pump gene expression. Our results revealed that pentamidine strongly synergized with rifampicin, linezolid, and tetracycline and moderately synergized with erythromycin, but did not synergize with vancomycin against E. coli, K. pneumoniae, E. cloacae, and A. baumannii. Pentamidine increased the outer membrane permeability but did not demolish the outer and inner membranes, which exclusively permits the passage of hydrophobic, small-molecule antibiotics while hindering the entry of hydrophilic, large-molecule vancomycin. It dissipated the membrane proton motive force and inactivated the efflux pump, allowing the intracellular accumulation of antimicrobials that function as substrates of the efflux pump, such as linezolid. These processes resulted in metabolic perturbation and ROS production which ultimately was able to destroy the bacteria. These mechanisms of action of pentamidine on GNB indicate that it is prone to potentiating hydrophobic, small-molecule antibiotics, such as rifampicin, linezolid, and tetracycline, but not hydrophilic, large-molecule antibiotics like vancomycin against GNB. Collectively, our results highlight the importance of the physicochemical properties of antibiotics and the specific mechanisms of action of pentamidine for the synergy of pentamidine-antibiotic combinations. Pentamidine engages in various pathways in its interactions with GNB, but these mechanisms determine its specific synergistic effects with certain antibiotics against GNB. Pentamidine is a promising adjuvant, and we can optimize drug compatibility by considering its functional mechanisms.

What determines the performance of low-carbon cities in China? Analysis of the grouping based on the technology-Organization-Environment framework.

BACKGROUND AND OBJECTIVES: Addressing climate change and reducing greenhouse gas emissions have emerged as shared global objectives. Enhancing the development performance of low-carbon cities has become an urgent and widely acknowledged concern for both government policy-making departments and academics. Drawing upon the complex grouping perspective and resource allocation theory, this study investigates how varying conditions related to technology, organization, and environment in Chinese low-carbon pilot cities can effectively allocate resources to shape the governance performance of low-carbon cities. METHODS AND DATA: This paper employs a comprehensive grouping analysis perspective, treating the research object as a combination of various ways between condition variables. It integrates the advantages of case studies and variable studies, and investigates the collective relationships between elemental groupings and outcomes using the fsQCA analysis method. This approach facilitates the understanding of multiple concurrent causal relationships within the technology-organization-environment (TOE) framework, accounting for different performance levels in Chinese low-carbon pilot cities, as well as addressing complex causal issues such as asymmetry and multiple scenario equivalence. Data from 30 representative low-carbon pilot cities in China were employed to validate the TOE theoretical framework. CONCLUSION: No single element alone can be considered a necessary condition for low-carbon city governance performance. However, environmental enhancement plays a more prominent role in the governance performance of low-carbon cities. Additionally, the presence of "multiple concurrent" technical, organizational, and environmental conditions leads to a diverse range of governance performance in Chinese low-carbon pilot cities. In other words, the driving paths of low-carbon city performance exhibit distinct pathways. CONTRIBUTION: The findings of this study can assist low-carbon pilot city managers in generating effective governance ideas, facilitating the successful implementation of low-carbon city pilot projects, and drawing valuable lessons from the experience of low-carbon city development in China.

Imaging PIP2 and BCR microclusters in B cell immunological synapse.

The humoral immune response is dependent on B cell activation and differentiation, which is typically triggered by the formation of immunological synapses at the interface between B cells and the antigen presenting surfaces. However, due to the highly dynamic and transient feature of immunological synapses, it has been difficult to capture and investigate the molecular events that occur within them. The planar lipids bilayer (PLB) supported antigen presenting surface combined with high-resolution high-speed total internal reflection fluorescence microscope (TIRFM) live cell imaging system has been proved to be a powerful tool that allows us to visualize the dynamic events in immunological synapse. In addition, the phospholipid phosphatidylinositol-(4,5)-biphosphate (PIP2) plays a unique role in B cell activation, and it is difficult to investigate the synaptic dynamics of PIP2 molecules. Hence, we describe here the general procedures for the utilization of a PLB based antigen presenting system combining TIRFM based imaging methods to visualize the spatial-temporal co-distribution of PIP2 and BCR microcluster within the B cell immunological synapse.

Nitric oxide-loaded nano- and microparticle platforms serving as potential new antifungal therapeutics.

Fungal diseases are a leading threat to human health, especially in individuals with compromised immunity. Although there have been recent important advances in antifungal drug development, antifungal resistance, drug-drug interactions and difficulties in delivery remain major challenges. Among its pleiotropic actions, nitric oxide (NO) is a key molecule in host defense. We have developed a flexible nanoparticle platform that delivers sustained release of NO and have demonstrated the platform's efficacy against diverse bacteria as well as some fungal species. In this work, we investigate the effects of two NO-releasing particles against a panel of important human yeast. Our results demonstrate that the compounds are both effective against diverse yeast, including ascomycota and basidiomycota species, and that NO-releasing particles may be a potent addition to our armamentarium for the treatment of focal and disseminated mycoses.

Prediction of prognosis in COVID-19 patients using machine learning: A systematic review and meta-analysis.

BACKGROUND: Accurate prediction of prognostic outcomes in patients with COVID-19 could facilitate clinical decision-making and medical resource allocation. However, little is known about the ability of machine learning (ML) to predict prognosis in COVID-19 patients. OBJECTIVE: This study aimed to systematically examine the prognostic value of ML in patients with COVID-19. METHODS: A systematic search was conducted in PubMed, Web of Science, Embase, Cochrane Library, and IEEE Xplore up to December 15, 2021. Studies predicting the prognostic outcomes of COVID-19 patients using ML were eligible for inclusion. Risk of bias was evaluated by a tailored checklist based on Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Pooled sensitivity, specificity, and area under the receiver operating curve (AUC) were calculated to evaluate model performance. RESULTS: A total of 33 studies that described 35 models were eligible for inclusion, with 27 models presenting mortality, four intensive care unit (ICU) admission, and four use of ventilation. For predicting mortality, ML gave a pooled sensitivity of 0.86 (95% CI, 0.79-0.90), a specificity of 0.87 (95% CI, 0.80-0.92), and an AUC of 0.93 (95% CI, 0.90-0.95). For the prediction of ICU admission, ML had a sensitivity of 0.86 (95% CI, 0.78-0.92), a specificity of 0.81 (95% CI, 0.66-0.91), and an AUC of 0.91 (95% CI, 0.88-0.93). For the prediction of ventilation, ML had a sensitivity of 0.81 (95% CI, 0.68-0.90), a specificity of 0.78 (95% CI, 0.66-0.87), and an AUC of 0.87 (95% CI, 0.83-0.89). Meta-regression analyses indicated that algorithm, population, study design, and source of dataset influenced the pooled estimate. CONCLUSION: This meta-analysis demonstrated the satisfactory performance of ML in predicting prognostic outcomes in patients with COVID-19, suggesting the potential value of ML to support clinical decision-making. However, improvements to methodology and validation are still necessary before its application in routine clinical practice.

Structure sensitivity reaction of chloroform hydrodechlorination to light olefins using Pd catalysts supported on carbon nanotubes and carbon nanofibers.

The upgrading of wasted chloroform in hydrodechlorination for the production of olefins such as ethylene and propylene is studied by employing four catalysts (PdCl/CNT, PdCl/CNF, PdN/CNT, and PdN/CNF) prepared by different precursors (PdCl2 and Pd(NO3)2) supported on carbon nanotubes (CNT) or carbon nanofibers (CNF). TEM and EXAFS-XANES results confirm that Pd nanoparticle size increases in the order: PdCl/CNT < PdCl/CNF âˆ¼ PdN/CNT < PdN/CNF, descending the electron density of Pd nanoparticles in the same order. It illustrates that PdCl-based catalysts show donation of electrons from support to Pd nanoparticles, which is not observed in PdN-based catalysts. Moreover, this effect is more evident in CNT. The smallest and well-dispersed Pd nanoparticles (NPs) on PdCl/CNT with high electron density favor an excellent and stable activity and a remarkable selectivity to olefins. In contrast, the other three catalysts show lower selectivity to olefins and lower activities which suffer strong deactivation due to the formation of Pd carbides on their larger Pd nanoparticles with lower electron density, compared to PdCl/CNT.

Constructing A Solar Evaporator by Stacking Exhausted Wood Sponges for Freshwater Generation and Fertilizer Recovery.

Solar water evaporation is an efficient and sustainable technology. To reduce energy consumption and improve cost efficiency, the surface modification of wood sponge by polypyrrole-glutathione (PGWS) was achieved using an in-situ synthetic method. The PGWS exhibits excellent adsorption efficiency for Hg(II) ions with adsorption capacity of 330.8 mg g-1 at 25 °C. Following Hg(II) absorption, the PGWS could be upcycled for solar steam generation. A stackable device was constructed by placing two wood sponges under a Hg(II) saturated PGWS [PGWS-Hg(II)], this system exhibited the highest water evaporation rate of 2.14 kg m-2 h-1 under 1 kW m-2 . Moreover, collecting paper was inserted between the stacked PGWS-Hg(II) and wood sponge for the collection of salts. As such salt can be successfully collected from simulated fertilizer plant effluent and then used as a nutrient for growing plants using a hydroponic system. The facile design of stackable evaporation provides an opportunity for wastewater utilization by harvesting solar energy.

Fatal Case of Heartland Virus Disease Acquired in the Mid-Atlantic Region, United States.

Heartland virus (HRTV) disease is an emerging tickborne illness in the midwestern and southern United States. We describe a reported fatal case of HRTV infection in the Maryland and Virginia region, states not widely recognized to have human HRTV disease cases. The range of HRTV could be expanding in the United States.

Pathway of Effects of Socioeconomic Status on Rural Left-behind Children to Receive Oral Health Services: A Structural Equation Modeling.

In a rural area with a high proportion of left-behind children (LBC), we aimed to identify the pathway of influence of socioeconomic status (SES) on LBCs to receive oral health services after individualized advice. Between September and October 2020, in a rural area of Yunnan, a survey of 238 LBC and 210 non-left-behind children (NLBC) showed that 91.9% and 94.2% had primary teeth caries, respectively. Their caregivers were advised on (1) dental care: bringing the children to seek professional dental care; and (2) self-care: supervising the children's oral health behaviors. Two to three months later, the children and their caregivers were visited to assess the compliance with these items of advice. Structural equation modeling (SEM) was used to handle the association between SES and compliance with the advice. A heatmap was used to visualize the data of reasons for seeking dental care or not. A total of 183 (87.1%) NLBCs and 206 (86.6%) LBCs were given the above advice; 32.9% of caregivers complied with dental care advice without a statistical difference between the LBC and NLBC group; 69.9% of caregivers of NLBCs complied with self-care advice, statistically more than those LBCs (59.2%). The education of caregivers was significantly associated with compliance with both advice items in univariate analysis. SES had a direct effect on the children being left behind and the level of oral health knowledge and awareness of the caregivers. Being left behind did not have an independent effect on receiving oral health services for children. "Dental disease was not severe" and "having no pain" were the main reasons for not seeking dental care. There was no clear grouping of participants with different background information based on the reasons given for seeking or not seeking dental care. Our study pointed to the importance of SES level. Being left behind alone may not be a risk factor for missing oral health services among rural children.

Many-Objective Job-Shop Scheduling: A Multiple Populations for Multiple Objectives-Based Genetic Algorithm Approach.

The job-shop scheduling problem (JSSP) is a challenging scheduling and optimization problem in the industry and engineering, which relates to the work efficiency and operational costs of factories. The completion time of all jobs is the most commonly considered optimization objective in the existing work. However, factories focus on both time and cost objectives, including completion time, total tardiness, advance time, production cost, and machine loss. Therefore, this article first time proposes a many-objective JSSP that considers all these five objectives to make the model more practical to reflect the various demands of factories. To optimize these five objectives simultaneously, a novel multiple populations for multiple objectives (MPMO) framework-based genetic algorithm (GA) approach, called MPMOGA, is proposed. First, MPMOGA employs five populations to optimize the five objectives, respectively. Second, to avoid each population only focusing on its corresponding single objective, an archive sharing technique (AST) is proposed to store the elite solutions collected from the five populations so that the populations can obtain optimization information about the other objectives from the archive. This way, MPMOGA can approximate different parts of the entire Pareto front (PF). Third, an archive update strategy (AUS) is proposed to further improve the quality of the solutions in the archive. The test instances in the widely used test sets are adopted to evaluate the performance of MPMOGA. The experimental results show that MPMOGA outperforms the compared state-of-the-art algorithms on most of the test instances.

Understanding bias in probabilistic analysis in model-based health economic evaluation.

Guidelines of economic evaluations suggest that probabilistic analysis (using probability distributions as inputs) provides less biased estimates than deterministic analysis (using point estimates) owing to the non-linear relationship of model inputs and model outputs. However, other factors can also impact the magnitude of bias for model results. We evaluate bias in probabilistic analysis and deterministic analysis through three simulation studies. The simulation studies illustrate that in some cases, compared with deterministic analyses, probabilistic analyses may be associated with greater biases in model inputs (risk ratios and mean cost estimates using the smearing estimator), as well as model outputs (life-years in a Markov model). Point estimates often represent the most likely value of the parameter in the population, given the observed data. When model parameters have wide, asymmetric confidence intervals, model inputs with larger likelihoods (e.g., point estimates) may result in less bias in model outputs (e.g., costs and life-years) than inputs with lower likelihoods (e.g., probability distributions). Further, when the variance of a parameter is large, simulations from probabilistic analyses may yield extreme values that tend to bias the results of some non-linear models. Deterministic analysis can avoid extreme values that probabilistic analysis may encounter. We conclude that there is no definitive answer on which analytical approach (probabilistic or deterministic) is associated with a less-biased estimate in non-linear models. Health economists should consider the bias of probabilistic analysis and select the most suitable approach for their analyses.

The joint influence of subjective social status and life skill level on adolescent health risk behaviors / 中国学校卫生

Abstract@#Subjective social status and life skill level are important influencing factors of adolescent health risk behaviors, and they interact with each other and jointly act on adolescent health risk behaviors, which make the mechanism of adolescent health risk behaviors become more diverse and complex. The current paper reviews the correlations among subjective social status, life skill level and adolescent health risk behaviors, in order to explore the joint influence of subjective social status and life skill level on adolescent health risk behaviors, then provides future directions for exploring possible mechanisms, and proposes recommendations for effective prevention strategies of adolescent health risk behaviors.