A Cross-project Defect Prediction Model Using Feature Transfer and Ensemble Learning

Cross-project defect prediction (CPDP) trains the prediction models with existing data from other projects (the source projects) and uses the trained model to predict the target projects. To solve two major problems in CPDP, namely, variability in data distribution and class imbalance, in this paper we raise a CPDP model combining feature transfer and ensemble learning, with two stages of feature transfer and the classification. The feature transfer method is based on Pearson correlation coefficient, which reduces the dimension of feature space and the difference of feature distribution between items. The class imbalance is solved by SMOTE and Voting on both algorithm and data levels. The experimental results on 20 source-target projects show that our method can yield significant improvement on CPDP

Diversity and soil chemical properties jointly explained the basal area in karst forest

IntroductionPlant diversity and soil chemical properties are important factors affecting the plant growth. We sought to compare the explanatory rates of diversity and soil chemical properties in explaining the variation of basal area in karst forests, and also sought to compare the relative importance of the niche complementarity and mass ratio hypotheses.MethodsOn the basis of linear regression and structural equation modelling, we examined the correlation between the basal area of plant communities and species diversity, functional diversity, phylogenetic diversity, the community-weighted mean (CWM) of traits, and soil chemical properties, using data obtained from 35 monitoring plots in southwest China.ResultsSpecies, functional, and phylogenetic diversities were all significantly correlated with the basal area of the plant community, among the indices of which, Faith’s phylogenetic diversity was found to have the greatest explanatory power for basal area. These plant diversity indices can better explain the variation in basal area than the CWM of traits, suggesting the niche complementarity hypothesis is more applicable than the mass ratio hypothesis. Moreover, soil chemical properties also have an equal important impact. Different chemical properties were found to show significant positive correlations with basal area, and their total effects on basal area were shown to be greater than the CWM of traits.DiscussionAttention should be paid to diversity and soil chemical properties. This study provides theoretical guidance for understanding biodiversity maintenance mechanisms and protecting karst forests

Habitat associations of woody plant species in evergreen–deciduous broadleaf karst forests in southwest China

The effects of habitat filtering on community assembly have been extensively researched, and topography has been identified as a critical factor influencing the spatial distribution of trees. In this study, a 25-ha plot was established in karst evergreen–deciduous broadleaf forests in southwestern China. Eight topographical factors were used to divide plots into four habitat types, i.e., hilltop, steep slope, gentle slope, and depression, using a multivariate regression tree. A total of 85 evergreen and deciduous tree species were recorded in these four habitats and classified into three life stages, the differentiation of which was assessed using torus-translation tests. A total of 65 species significantly positively associated with at least one habitat and 79 species significantly negatively associated with at least one habitat were identified. Most species, whether evergreen or deciduous, exhibited a positive correlation with steep slopes, whereas relatively few species were adapted to depressions. Moreover, the percentage of evergreen species positively associated with hilltops and steep slopes was higher than that of deciduous species. Both evergreen and deciduous species showed an increasing percentage of positive correlation with hilltops from the sapling stage to the mature stage. However, more evergreen species grew on steep slopes in the sapling stage, whereas deciduous species grew in the mature stage. Canonical correspondence was used to analyze the relationship between species and the eight topographical factors. Regardless of life form or life stage, results showed that species distribution was significantly affected by topography. Furthermore, the distribution of evergreen species on sapling-stage trees was found to be more influenced by topography, whereas deciduous species were more influenced by topography in the mature stage. Finally, elevation was identified as the most crucial topographical factor affecting species distribution

A prospective multicenter clinical research study validating the effectiveness and safety of a chest X-ray-based pulmonary tuberculosis screening software JF CXR-1 built on a convolutional neural network algorithm

BackgroundChest radiography (chest X-ray or CXR) plays an important role in the early detection of active pulmonary tuberculosis (TB). In areas with a high TB burden that require urgent screening, there is often a shortage of radiologists available to interpret the X-ray results. Computer-aided detection (CAD) software employed with artificial intelligence (AI) systems may have the potential to solve this problem.ObjectiveWe validated the effectiveness and safety of pulmonary tuberculosis imaging screening software that is based on a convolutional neural network algorithm.MethodsWe conducted prospective multicenter clinical research to validate the performance of pulmonary tuberculosis imaging screening software (JF CXR-1). Volunteers under the age of 15 years, both with or without suspicion of pulmonary tuberculosis, were recruited for CXR photography. The software reported a probability score of TB for each participant. The results were compared with those reported by radiologists. We measured sensitivity, specificity, consistency rate, and the area under the receiver operating characteristic curves (AUC) for the diagnosis of tuberculosis. Besides, adverse events (AE) and severe adverse events (SAE) were also evaluated.ResultsThe clinical research was conducted in six general infectious disease hospitals across China. A total of 1,165 participants were enrolled, and 1,161 were enrolled in the full analysis set (FAS). Men accounted for 60.0% (697/1,161). Compared to the results from radiologists on the board, the software showed a sensitivity of 94.2% (95% CI: 92.0–95.8%) and a specificity of 91.2% (95% CI: 88.5–93.2%). The consistency rate was 92.7% (91.1–94.1%), with a Kappa value of 0.854 (P = 0.000). The AUC was 0.98. In the safety set (SS), which consisted of 1,161 participants, 0.3% (3/1,161) had AEs that were not related to the software, and no severe AEs were observed.ConclusionThe software for tuberculosis screening based on a convolutional neural network algorithm is effective and safe. It is a potential candidate for solving tuberculosis screening problems in areas lacking radiologists with a high TB burden

Highly efficient enzymatic preparation of isomalto-oligosaccharides from starch using an enzyme cocktail

Background: Current commercial production of isomalto-oligosaccharides (IMOs) commonly involves a lengthy multistage process with low yields. Results: To improve the process efficiency for production of IMOs,we developed a simple and efficient method by using enzyme cocktails composed of the recombinant Bacillus naganoensis pullulanase produced by Bacillus licheniformis , \u3b1-amylase from Bacillus amyloliquefaciens , barley bran \u3b2-amylase, and \u3b1-transglucosidase from Aspergillus niger to perform simultaneous saccharification and transglycosylation to process the liquefied starch. After 13 h of reacting time, 49.09% IMOs (calculated from the total amount of isomaltose, isomaltotriose, and panose) were produced. Conclusions: Our method of using an enzyme cocktail for the efficient production of IMOs offers an attractive alternative to the process presently in use

Metagenomic Profiling of the Bacterial Community Changes from Koji to Mash Stage in the Brewing of Soy Sauce

The improvement of soy sauce fermentation is restricted by the insufficient information on bacterial community. In this study, bacterial communities in the koji and mash stage were compared based on next-generation sequencing technology. A total of 29 genera were identi­fied in the koji stage, while 34 in the mash stage. After koji stage, 7 genera disappeared and 12 new genera appeared in the mash stage. The dominant bacteria were Kurthia, Weissella and Staphylococcus in the koji stage and Staphylococcus, Kurthia, Enterococcus and Leuconostoc in the mash stage. The results provided insights into the microbial communities involved in soy sauce fermentation

Seasonal Changes and Vertical Distribution of Fine Root Biomass During Vegetation Restoration in a Karst Area, Southwest China

In karst ecosystems, plants absorbing smaller amounts of nutrients, owing to shallow soil, show limited growth. In addition, fine roots (diameter < 2 mm) contribute to the regulation of nutrient cycles in terrestrial ecosystems. However, the spatial and temporal variations of fine root biomass in different vegetation types of the karst region remains poorly understood. In this study, we investigated the seasonal and vertical variation in biomass, necromass, and total mass of fine roots using sequential soil coring under different stages of vegetation restoration (grassland, shrubland, secondary forest, and primary forest) in Southwest China. The results showed that the fine root biomass and necromass ranged from 136.99 to 216.18 g m−2 and 47.34 to 86.94 g m−2, respectively. The total mass of fine roots and their production ranged from 187.00 to 303.11 g m−2 and 55.74 to 100.84 g m−2 year−1, respectively. They showed a single peak across the vegetation restoration gradient. The fine root biomass and total fine root mass also showed a single peak with seasonal change. In autumn, the fine root biomass was high, whereas the necromass was low. Most of the fine roots were concentrated in the surface soil layer (0–10 cm), which accounted more than 57% root biomass, and decreased with increasing soil depth. In addition, fine root production showed a similar vertical pattern of variation with biomass. Overall, our results suggested that fine roots show clear seasonal and vertical changes with vegetation succession. Moreover, there was a higher seasonal fluctuation and a greater vertical decreasing trend in late-successional stages than in the early-successional stages. The conversion of degraded land to forest could improve the productivity of underground ecosystems and vegetation restoration projects in the fragile karst region should, therefore, continue