Based on the collective forest with common use rights, the social-ecological system analysis framework and autonomous governance theory proposed by Elinor Ostrom are introduced in the forest eco-economic system to analyze the interaction logic among the first-level subsystems and the secondary variables of the forest eco-economic system and the variables related to the autonomous governance of the system to explore the synergistic mechanisms affecting the forest eco-economic system. The results show that: in the case of information asymmetry, collective actions of governmental and non-governmental organizations will aggravate the dilemma of forest eco-economic synergistic development; actors extract forest resource units from the forest resource system to achieve economic benefits; and renewable resources of forest ecosystems can be sustained in the long term when the average extraction rate of humans from forest ecosystems does not exceed the average replenishment rate.

In view of the fact that the convolution neural network segmentation method lacks to capture the global dependency of infected areas in COVID-19 images, which is not conducive to the complete segmentation of scattered lesion areas, this paper proposes a COVID-19 lesion segmentation method UniUNet based on UniFormer with its strong ability to capture global dependency. Firstly, a U-shaped encoder-decoder structure based on UniFormer is designed, which can enhance the cooperation ability of local and global relations. Secondly, Swin spatial pyramid pooling module is introduced to compensate the influence of spatial resolution reduction in the encoder process and generate multi-scale representation. Multi-scale attention gate is introduced at the skip connection to suppress redundant features and enhance important features. Experiment results show that, compared with the other four methods, the proposed model achieves better results in Dice, loU and Recall on COVID-19-CT-Seg and CC-CCIII dataset, and achieves a more complete segmentation of the lesion area.

A total of 25 SSR primers were screened on 37 putative F₁s derived from the five different crosses. Identified cross specific highly informative SSRs primers, i.e., 14 for the first cross, 10 for the second, 12 for the third and 6 each for fourth and fifth crosses. For the first cross Bhagwa × Daru 17, four primers (HvSSRT_375, NRCP_SSR9, NRCP_SSR12 and NRCP_SSR92) were found to be highly informative with higher 100% hybrid purity index (HPI), PIC (~0.52), and observed heterozygosity (Ho, range 0.87–0.93) values, and two F₁s namely H₁ and H₂ were found to be highly heterotic with a heterozygosity index (HI) of 92.85%. Similarly, for Bhagwa × Nana, three primers (HvSSRT_375, HvSSRT_605 and NRCP_SSR19) had higher HPI (70%–100%), PIC (0.52–0.69), and Ho (0.75–0.33) values, and three F₁s H₁, H₂, and H₄ had 70% (HI). For Bhagwa × IC318712, four SSRs (HvSSRT_254, HvSSRT_348, HvSSRT_826 and NRCP_SSR95) had higher Ho (~0.83), HPI (100%) and PIC (~0.52) values, and four F₁s H₂, H₇, H₉, and H₁₀ showed 91.66% (HI). For Bhagwa × Nayana, HvSSRT_605, HvSSRT_826, and HvSSRT_432, and for Ganesh × Nayana, HVSSRT_375, HVSSRT_605, and HvSSRT_826 were found informative. These markers will be highly useful in developing maps of populations.

The study examined the socio-demographic factors affecting access to and utilization of social welfare services in Yenagoa Local Government Area of Bayelsa State, Nigeria. Quantitative and qualitative approaches were adopted to select 570 respondents from the study area. Probability and non-probability sampling techniques were adopted in the selection of communities, and respondents. The quantitative data were analyzed using frequency distribution tables and percentages, while chi-square statistic was used to determine the relationship between socio-demographic variables and access to and utilization of social welfare services. The qualitative data were analyzed in themes as a complement to the quantitative data. This study reveals that although all the respondents reported knowing available social welfare services, 44.3% reported not having access to existing social services due to factors connected to serendipity variables, such as terrain condition, ethnicity and knowing someone in government. Therefore, the study recommends that the government and other stakeholders should push for the massive delivery of much-needed social welfare services to address the issue of welfare service deficit across the nation, irrespective of the ethnic group and whether the community is connected to the government of the day or not, primarily in rural areas.