An Exact Bayesian Model for Meta-Analysis of the Standardized Mean Difference with Its Simultaneous Credible Intervals.

While Bayesian methodology is increasingly favored in behavioral research for its clear probabilistic inference and model structure, its widespread acceptance as a standard meta-analysis approach remains limited. Although some conventional Bayesian hierarchical models are frequently used for analysis, their performance has not been thoroughly examined. This study evaluates two commonly used Bayesian models for meta-analysis of standardized mean difference and identifies significant issues with these models. In response, we introduce a new Bayesian model equipped with novel features that address existing model concerns and a broader limitation of the current Bayesian meta-analysis. Furthermore, we introduce a simple computational approach to construct simultaneous credible intervals for the summary effect and between-study heterogeneity, based on their joint posterior samples. This fully captures the joint uncertainty in these parameters, a task that is challenging or impractical with frequentist models. Through simulation studies rooted in a joint Bayesian/frequentist paradigm, we compare our model's performance against existing ones under conditions that mirror realistic research scenarios. The results reveal that our new model outperforms others and shows enhanced statistical properties. We also demonstrate the practicality of our models using real-world examples, highlighting how our approach strengthens the robustness of inferences regarding the summary effect.

Study on protective performance and gradient optimization of helmet foam liner under bullet impact.

Protective equipment in war plays a vital role in the safety of soldiers, the threat to soldiers from brain damage caused by deformation at the back of the helmet cannot be ignored, so research on reduce blunt post-cranial injury has great significance and value. This study first conducted gunshot experiments, used rifle bullets impact bulletproof plate and different density liner foam to record the incident process and internal response of craniocerebral model. After verifying the accuracy of finite element model through experimental data, optimization model is established based on response surface method to optimize the structure of gradient foam, analyze the cranial strain and energy absorption to select the best density and thickness distribution of each foam layer. Optimization results show that liner foam which designed to have lower density and thicker thickness for impact and brace layers, higher density and thinner thickness for middle layer can significantly improve the energy absorption efficiency. Compared to the 40.65 J of energy absorption before optimization, the optimized gradient foam can absorb 109.3 J of energy, with a 169% increase in the absorption ratio. The skull strain in the craniocerebral model was reduced from 1.260 × 10-2 to 1.034 × 10-2, with a reduction of about 22%. This study provides references for the design and development of protective equipment and plays an important role in ensuring the safety of soldiers in the battlefield environment.

Spillover effects of food recalls: A milk recall scenario experiment in China.

Food recall is a major ingredient in food safety with existing literature focusing mainly on its direct impacts. Few studies focus on possible spillover effects. It is hypothesized that food recalls have a spillover effect on the recalled brand and purchase channel. As a test of this hypothesis, a 2-purchase channel by 3-recall strategy scenario experiment was conducted on spillover effects of a milk recall in Beijing, China. The results indicate that food-safety scares have significant negative impacts on consumers' purchase intention on the recalled brand and purchase channel, and the impacts are more significant for online than offline marketing. However, voluntary recalls by online firms help mitigate these negative effects and restore consumers' purchase intention more than offline voluntary recalls. An online food incident creates an issue of trust toward general online platforms. Online vendors should take greater care in guaranteeing food safety and actively take restorative actions such as voluntary recalls after a food safety incident. Results provide empirical evidence for industry organizations and governments to stipulate a strict food safety and incident resolution system for e-commerce.

Does the COVID-19 Pandemic Change Consumers' Food Consumption and Willingness-to-Pay? The Case of China.

Since COVID-19 was first detected in China in 2019, governments around the world have imposed strict measures to curb the spread of the coronavirus, which substantially impacted people's life. Consumers' food consumption behavior has also changed accordingly with reduced grocery shopping frequency, replaced in-person grocery shopping with online shopping, and increased valuation on food. In this paper, we aim to investigate the change in Chinese consumers' food consumption and their willingness to pay (WTP) for vegetables and meat, using a dataset with 1206 online samples collected between February and March 2020. Consumers' WTP for vegetables and meat is estimated using a double-bounded dichotomous contingent valuation design, and factors affecting their WTPs are also investigated. Results show that consumers have a higher WTP for these food products during the pandemic, and their WTP is positively affected by their anticipated duration of the COVID-19, their online shopping shares, their direct exposure to infected patients, their gender, and their income. These results imply that the food industry shall try to develop online market channels as consumers are willing to share the costs, while lower-income consumers may not be able to meet their food needs with prices increased beyond their WTP and thus may call for the government's support.