Research on the Tournament Incentive Mechanism of the Safety Behavior for Construction Workers: Considering Multiple Heterogeneity.

The unsafe behavior of construction workers is one of the most important and direct causes of safety accidents. Managers usually develop effective incentives aimed at regulating worker safety behavior. Due to the large number of workers in construction projects, there are multiple differences in fairness preference, risk preference and ability level, which will lead to the complex effect of the traditional mechanism to regulate workers' safety behavior. In order to improve the effectiveness of incentive measures for worker safety behavior, this paper takes into account the multiple differences of individual workers' fairness preference, risk preference and ability level, based on the tournament mechanism to construct a competition incentive model. By designing a tournament reward and salary distribution for heterogeneous workers, the occurrence of unsafe behaviors can be reduced. The study found that in terms of the optimal level of safety investment, workers with risk aversion attitude generally invest higher than that of workers with risk preference, no matter whether they have a strong fairness preference or not; In terms of the distribution of tournament rewards, workers with a risk aversion attitude and a higher level of fairness preference need to be given higher incentives.

[Physiological and enrichment characteristics of Paulownia fortunei seedlings under zinc, cadmium and their combined stress].

The hydroponic culture test method was used to study the physiological and biochemical responses of Paulownia fortunei seedlings under Zn stress, Cd stress, and combined Zn and Cd stress as well as changes in the enrichment and transfer characteristics of heavy metals. Under single and combined heavy metal stress, the biomass, plant height, and peroxidase (POD) activity of P. fortunei decreased as the treatment concentration increased. Combined Zn and Cd affected adversely plant height and biomass. As the concentration of Zn increased when applied alone, the chlorophyll content and catalase (CAT) activity of P. fortunei first increased and then decreased, the superoxide dismutase (SOD) activity increased, and the aboveground malondialdehyde (MDA) content first decreased and then increased. As the concentration of Cd increased when applied alone, chlorophyll content and CAT activity increased, and SOD activity and aboveground MDA content first increased and then decreased. Under both Cd and Zn, the physiological response was more complex. Cd in the seedlings of P. fortunei was concentrated in the root. In contrast, Zn was concentrated in the upper part of the ground, and its transfer coefficient was greater than 1.00. Thus, the addition of Zn promotes the transfer of heavy metals to the above-ground portions of plants. Generally, P. fortunei can effectively promote ecological restoration under complex forms of heavy metal pollution.

Adaptive genetic differentiation in Pterocarya stenoptera (Juglandaceae) driven by multiple environmental variables were revealed by landscape genomics.

BACKGROUND: The investigation of the genetic basis of local adaptation in non-model species is an interesting focus of evolutionary biologists and molecular ecologists. Identifying these adaptive genetic variabilities on the genome responsible can provide insight into the genetic mechanism of local adaptation. RESULTS: We investigated the spatial distribution of genetic variation in 22 natural populations of Pterocarya stenoptera across its distribution area in China to provide insights into the complex interplay between multiple environmental variables and adaptive genetic differentiation. The Bayesian analysis of population structure showed that the 22 populations of P. stenoptera were subdivided into two groups. Redundancy analysis demonstrated that this genetic differentiation was caused by the divergent selection of environmental difference. A total of 44 outlier loci were mutually identified by Arlequin and BayeScan, 43 of which were environment-associated loci (EAL). The results of latent factor mixed model analysis showed that solar radiation in June (Sr6), minimum temperature of the coldest month (Bio6), temperature seasonality (Bio4), and water vapor pressure in January (Wvp1) were associated with the highest numbers of EAL. Sr6 was associated with the ecological habitat of "prefered light", and Bio6 and Wvp1 were associated with the ecological habitat of "warm and humid environment". CONCLUSIONS: Our results provided empirical evidence that environmental variables related to the ecological habitats of species play key roles in driving adaptive differentiation of species genome.