(1)    'Figure3 raw data_SABOR-HSRL1_UC12_20140723_F2_R2.h5' is the raw High Spectral Resolution Lidar (HSRL) profile data for the track shown in Figure 3. (2)    'Figure3 result_IOP profile.mat' is the derived along-track vertical profile results of absorption, scattering, and beam attenuation coefficients for the study area in Figure 3.(3)    'Figure4-5 raw HSRL data' folder stores all HSRL raw flight data collected during the SABOR campaign. These h5 files are used to derive absorption, scattering, and beam attenuation coefficient. (4)    'Figure4-5 validation_insitu data' folder stores in-situ absorption, scattering, and attenuation coefficient profiles form SeaBASS, used for validation in Figures 4-5.(5)    'Figure4-5 result_matchups.mat' consists of 14 matchups between the derived results (absorption, scattering, and beam attenuation coefficients) and cast in-situ measurements, used for comparison in Figures 4-5.

(1)    'Figure3 raw data_SABOR-HSRL1_UC12_20140723_F2_R2.h5' is the raw High Spectral Resolution Lidar (HSRL) profile data for the track shown in Figure 3. (2)    'Figure3 result_IOP profile.mat' is the derived along-track vertical profile results of absorption, scattering, and beam attenuation coefficients for the study area in Figure 3.(3)    'Figure4-5 raw HSRL data' folder stores all HSRL raw flight data collected during the SABOR campaign. These h5 files are used to derive absorption, scattering, and beam attenuation coefficient. (4)    'Figure4-5 validation_insitu data' folder stores in-situ absorption, scattering, and attenuation coefficient profiles form SeaBASS, used for validation in Figures 4-5.(5)    'Figure4-5 result_matchups.mat' consists of 14 matchups between the derived results (absorption, scattering, and beam attenuation coefficients) and cast in-situ measurements, used for comparison in Figures 4-5.

(1)  'SABOR-HSRL1_UC12_20140723_F2_R2.h5' is HSRL raw profile data from NASA (Figure 3).(2)  'Figure 3 result a b c.mat' is  the derived IOP profile results in a track (Figure 3).(2)  'Figure 4-5 raw HSRL data' folder stores the HSRL raw flight data from the SABOR experiment (Figure 4-5).(3)  'Figure 4-5 validation-insitu data' folder stores raw  in-situ absorption coefficient , scattering coefficient and attenuation coefficient  data (Figure 4-5).(5)  'Figure 4-5 result data sabor_cell.mat'  is the 14 matchups between the  derived IOP results and cast in situ measurements (Figure 4-5)

A high-quality reference genome coupled with resequencing data is becoming a promising strategy to address issues in conservation genomics, which has greatly enhanced the development of conservation plans for endangered species. Pangolins are fascinating animals with a range of distinctive features, but unfortunately, they are the world's most trafficked wild animals. Here, we report a haplotype-resolved and chromosome-scale genome for the Chinese pangolin (Manis pentadactyla), the most representative reference genome for pangolin species. We assembled 20 chromosome-scale pseudomolecules for MP. The diploid genome sizes assembled for MP were ~2.64 Gb, and represented 92.48% of the estimated genome size. The contig and scaffold NG50 of the MP were 456.16 Mb and 140.71 Mb.

A high-quality reference genome coupled with resequencing data is becoming a promising strategy to address issues in conservation genomics, which has greatly enhanced the development of conservation plans for endangered species. Pangolins are fascinating animals with a range of distinctive features, but unfortunately, they are the world's most trafficked wild animals. Here, we report a haplotype-resolved and chromosome-scale genome for each of the Chinese pangolin and Malayan pangolin, the most representative reference genome for pangolin species. We found a greater improvement in evaluation of genetic diversity and inbreeding based on high-quality genomes and obtained different results in detecting genome-wide extinction risks being compared with short read assembled genomes. Moderate inbreeding and genetic diversity were verified again in these two pangolin species except for one Malayan pangolin population with the high inbreeding and low genetic diversity, which we recommend to pay special attention to the conservation and protection of this population. Additionally, our study is the first to detect relative mild genetic purging in pangolin populations that were analyzed. These two high quality reference genomes will provide valuable genomic resource for future studies on the protection and conservation for pangolins.

A high-quality reference genome coupled with resequencing data is becoming a promising strategy to address issues in conservation genomics, which has greatly enhanced the development of conservation plans for endangered species. Pangolins are fascinating animals with a range of distinctive features, but unfortunately, they are the world's most trafficked wild animals. We assembled 19 chromosome-scale pseudomolecules for Malayan pangolin (Manis javanica). The diploid genome sizes assembled for MJ were ~2.56 Gb, and represented 96.78% of the estimated genome size. The contig and scaffold NG50 of the MJ were 46.22Mb and 141.80 Mb.

No description available

Snakes are one of the most important wildlife resources and are widely distributed. Bungarus multicinctus is a highly venomous snake and is distributed in central and southern China. In recent years, venomous snake bites have gradually increased. Genomic resources are significant for understanding the evolution of a species and the molecular mechanisms of toxin production. So far, the genomic resources of snakes are a rarity. In 2021 we collected a snake sample in Beiliu Longgukeng, Guangxi, which was identified as Bungarus multicinctus by morphological identification. Here, we present a highly contiguous B. multicinctus genome with a genome size of 1.51Gb. The repeat content in the genome is 40.15%, and the total length is more than 620Mb. A total of 24,869 functional genes were annotated. This study is of great significance for understanding the evolution of B. multicinctus, and also provides a molecular basis for the genes of the venom glands.

Understanding how collaborative groups accomplish their work is a complex undertaking, because group problem-solving is a dynamic process, affected by interactions among many factors including the team’s tasks and goals, the prior skills and capabilities of its individual members, the communication and social dynamics between members, and other aspects of the task and the working environment. In educational contexts an additional crucial question arises: What is the relationship of group performance to individual learning outcomes, and how do group process mechanisms determine that relationship? Also, a critical task variable, discussed in the literature but little studied, is the demonstrability of the correct solution (Shaw, 1963); we investigate its role in moderating learning and performance outcomes. To investigate these questions, we propose a model of how group process facilitates individual learning and task performance in groups, and adopt a simulation approach employing agent-based modeling to assess the importance of and interactions among factors hypothesized to affect group problem-solving process, performance outcomes, and individual learning. Our simulation incorporates a simple cognitively diagnostic measurement model relating prior knowledge and learned skills to performance, a framework that offers conceptual advantages in modeling prior task-relevant knowledge, the demonstrability of correct solutions, individual learning, and process gains from the group work.

Understanding how collaborative groups accomplish their work is a complex undertaking, because group problem-solving is a dynamic process, affected by interactions among many factors including the team’s tasks and goals, the prior skills and capabilities of its individual members, the communication and social dynamics between members, and other aspects of the task and the working environment. In educational contexts an additional crucial question arises: What is the relationship of group performance to individual learning outcomes, and how do group process mechanisms determine that relationship? Also, a critical task variable, discussed in the literature but little studied, is the demonstrability of the correct solution (Shaw, 1963); we investigate its role in moderating learning and performance outcomes. To investigate these questions, we propose a model of how group process facilitates individual learning and task performance in groups, and adopt a simulation approach employing agent-based modeling to assess the importance of and interactions among factors hypothesized to affect group problem-solving process, performance outcomes, and individual learning. Our simulation incorporates a simple cognitively diagnostic measurement model relating prior knowledge and learned skills to performance, a framework that offers conceptual advantages in modeling prior task-relevant knowledge, the demonstrability of correct solutions, individual learning, and process gains from the group work.