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Flowering time and photoperiod sensitivity are fundamental traits that determine soybean adaptation to a given region or a wide range of geographic environments. The General Regulatory Factors (GRFs), also known as 14-3-3 family, are involved in protein–protein interactions in a phosphorylation-dependent manner, thus regulating ubiquitous biological processes, such as photoperiodic flowering, plant immunity and stress response. In this study, 20 soybean GmSGF14 genes were identified and divided into two categories according to phylogenetic relationships and structural characteristics. Real-time quantitative PCR analysis revealed that GmSGF14g, GmSGF14i, GmSGF14j, GmSGF14k, GmSGF14m and GmSGF14s were highly expressed in all tissues compared to other GmSGF14 genes. In addition, we found that the transcript levels of GmSGF14 family genes in leaves varied significantly under different photoperiodic conditions, indicating that their expression responds to photoperiod. To explore the role of GmSGF14 in the regulation of soybean flowering, the geographical distribution of major haplotypes and their association with flowering time in six environments among 207 soybean germplasms were studied. Haplotype analysis confirmed that the GmSGF14mH4 harboring a frameshift mutation in the 14-3-3 domain was associated with later flowering. Geographical distribution analysis demonstrated that the haplotypes related to early flowering were frequently found in high-latitude regions, while the haplotypes associated with late flowering were mostly distributed in low-latitude regions of China. Taken together, our results reveal that the GmSGF14 family genes play essential roles in photoperiodic flowering and geographical adaptation of soybean, providing theoretical support for further exploring the function of specific genes in this family and varietal improvement for wide adaptability. [ABSTRACT FROM AUTHOR]

With the rapid development of China's economy, people are eager for an effective way to relieve work pressure and strengthen their health at the same time. Outdoor sport is one of the best choices for people. However, the amount of recommended data on the network is very large. As a result, when people understand outdoor sports through the network, they cannot effectively obtain the information they want. This is the problem of "information overload," and personalized recommendation system can effectively alleviate this problem. In order to effectively recommend outdoor sports to users, a useful attempt was made in the personalized recommendation system for outdoor sports in this paper. The specific work of this paper is as follows: firstly, the current situation of outdoor sports in China was summarized, and the related technologies of the recommendation system were studied, including user modeling technology, recommendation target modeling technology, and recommendation algorithm. In order to obtain better recommendation effect, this paper proposes to mix user-based collaborative filtering recommendation algorithm, project-based collaborative filtering recommendation algorithm, and content-based recommendation algorithm. The hybrid algorithm adopts the way of feature expansion and weighted combination. Firstly, the hybrid model (model 1) of user-based collaborative filtering recommendation and content-based recommendation is obtained. Secondly, the hybrid model (model 2) based on project collaborative filtering recommendation and content-based recommendation was obtained. Finally, model 1 and model 2 were combined together to get a hybrid model with better final recommendation effect. For the common cold start problem in the recommendation system, the system adopts content-based recommendation algorithm to solve it. [ABSTRACT FROM AUTHOR]

Changes in land use and landscapes have a direct impact on the regional eco-environment. It is of great importance to understand the change pattern of land use, landscapes, and their mechanism on the ecological quality, especially ecologically fragile areas. The northern sand-prevention belt (NSPB) is an important ecologically fragile area in China, which has a large influence on the ecological security of the entire country. Based on the land use data of the NSPB in 2000, 2010, and 2018, we studied the spatio-temporal characteristics of land-use change and change in landscape patterns. The ecological quality represented by the remote sensing-based desertification index (RSDI) was calculated using satellite images. The effects of land use and landscape patterns on RSDI were analyzed by geographic detector and geographically weighted regression. Important results include the following: (1) Land-use change in the study area was high during 2000–2010 but slower in 2010–2018. Grassland was the largest land-use type in the NSPB, and varied greatly in terms of total change and spatial location. The major change was the conversion between dense and moderate grass, with 64,860 km2 of dense grass turning into moderate grass, and 48,505 km2 changing the other way. (2) Among the four landscape metrics, patch density, area-weighted mean fractal dimension, and edge density increased, whereas the aggregation index decreased, which indicated that the landscape was developing towards heterogeneity, fragmentation, complexity, and aggregation. Spatially, the landscape metrics presented a strip distribution in the east of the NSPB. (3) The effects of various land-use types on ecological quality, from high to low, were unused land, woodland, dense grass, cropland, moderate grass, built-up land, sparse grass, and waterbody. The areas where the ecological quality was greatly affected by the landscape patterns were concentrated in the agro-pastoral ecotone and the forest-steppe ecotone. The results of this study reveal the trends of land use and landscape patterns in the NSPB over 18 years and can help to understand their mechanism on ecological quality, which is of significance for the management of this area. • LUC in the NSPB was active from 2000 to 2010 and weakened from 2010 to 2018. • The landscape was developing towards heterogeneity, fragmentation, complexity, and aggregation. • The effects of land use and landscape on ecological quality were studied by GD and GWR. [ABSTRACT FROM AUTHOR]

Temperature and precipitation are considered to be the most important indicators affecting the green-up date. Sensitivity of the green-up date to temperature and precipitation is considered to be one of the key indicators to characterize the response of terrestrial ecosystems to climate change. We selected the main grassland types for analysis, including temperate steppe, temperate meadow steppe, upland meadow, and lowland meadow. This study investigates the variation in key meteorological indicators (daily maximum temperature (Tmax), daily minimum temperature (Tmin), and precipitation) between 2001 and 2018. We then examined the partial correlation and sensitivity of green-up date (GUD) to Tmax, Tmin, and precipitation. Our analysis indicated that the average GUD across the whole area was DOY 113. The mean GUD trend was −3.1 days/decade and the 25% region advanced significantly. Tmax and Tmin mainly showed a decreasing trend in winter (p > 0.05). In spring, Tmax mainly showed an increasing trend (p > 0.05) and Tmin a decreasing trend (p > 0.05). Precipitation showed no significant (p > 0.05) change trend and the trend range was ±10 mm/decade. For temperate steppe, the increase in Tmin in March promotes green-up (27.3%, the proportion of significant pixels), with a sensitivity of −0.17 days/°C. In addition, precipitation in April also promotes green-up (21.7%), with a sensitivity of −0.32 days/mm. The GUDs of temperate meadow steppe (73.9%), lowland meadow (65.9%), and upland meadow (22.1%) were mainly affected by Tmin in March, with sensitivities of −0.15 days/°C, −0.13 days/°C, and −0.14 days/°C, respectively. The results of this study reveal the response of vegetation to climate warming and contribute to improving the prediction of ecological changes as temperatures increase in the future. [ABSTRACT FROM AUTHOR]

• Erguna Block contains a crystalline basement at least in Paleoproterozoic ages. • The Neoproterozoic intrusive rocks define two stages magmatism. • Two stages magmatism corresponds to the assembly and break-up of the Rodinia supercontinent. • The Central Mongolia-Erguna Block has a tectonic affinity to the Tarim Craton. The Central Asian Orogenic Belt is sandwiched between the Siberian, East European (Baltica), Tarim, and North China cratons, which contain several Precambrian micro-continental blocks, such as the Kazakhstan-Yili-Central Tianshan blocks, the Junggar Block and the Amuria Block. The tectonic nature and positions of these micro-continental blocks are unclear and disputed in many supercontinent reconstructions. In particular, the position of the Amuria Block in the eastern Central Asian Orogenic Belt, which is important for the reconstructions of the Precambrian Rodinia supercontinent, remains unknown because of the lack of late Palaeoproterozoic to Neoproterozoic geological and geochronological data. The Erguna Block, a part of the Amuria Block in NE China, has been considered as a constituent block of the Rodinia supercontinent. However, the late Palaeoproterozoic to Neoproterozoic tectonic evolution of the Erguna Block with respect to the assembly and break-up of Rodinia remains poorly understood. Here we present zircon U–Pb–Hf–O isotopic data and whole-rock elemental data of the newly discovered late Palaeoproterozoic and Neoproterozoic records in the northern Erguna Block. The gneissic granites have protolith and metamorphic ages of 1839 ± 24 and 497 ± 6 Ma, respectively, and relatively uniform two-stage Hf model ages (T DM1) of 2.67–1.26 Ga, indicating that the Erguna Block has a Palaeoproterozoic crystalline basement. The zircon U–Pb ages for the Neoproterozoic intrusive rocks define two stages of magmatism in early Neoproterozoic (Stage 1; i.e., ca. 946 Ma) and middle Neoproterozoic (Stage 2; i.e., 833–737 Ma), respectively, implying that the Erguna Block had switched to an intra-continental extensional setting (833–737 Ma) after the early Neoproterozoic (ca. 946 Ma) convergence–accretion. A comparison of data from the Erguna Block and its adjacent units reveals that the Erguna and Central Mongolia blocks were likely in a single crustal entity with the Tarim Craton associated with the Rodinia assembly at ca. 900 Ma. This composite block then detached from the Tarim Craton at ca. 800 Ma following the break-up of Rodinia, and drifted southwards to the vicinity of the Siberia Craton during the Cambrian. [ABSTRACT FROM AUTHOR]