A general binomial mixture model is proposed for the species accumulation function based on presence–absence (incidence) of species in a sample of quadrats or other sampling units. The model covers interpolation between zero and the observed number of samples, as well as extrapolation beyond the observed sample set. For interpolation (sample‐based rarefaction), easily calculated, closed‐form expressions for both expected richness and its confidence limits are developed (using the method of moments) that completely eliminate the need for resampling methods and permit direct statistical comparison of richness between sample sets. An incidence‐based form of the Coleman (random‐placement) model is developed and compared with the moment‐based interpolation method. For extrapolation beyond the empirical sample set (and simultaneously, as an alternative method of interpolation), a likelihood‐based estimator with a bootstrap confidence interval is described that relies on a sequential, AIC‐guided algorithm to fit the mixture model parameters. Both the moment‐based and likelihood‐based estimators are illustrated with data sets for temperate birds and tropical seeds, ants, and trees. The moment‐based estimator is confidently recommended for interpolation (sample‐based rarefaction). For extrapolation, the likelihood‐based estimator performs well for doubling or tripling the number of empirical samples, but it is not reliable for estimating the richness asymptote. The sensitivity of individual‐based and sample‐based rarefaction to spatial (or temporal) patchiness is discussed.

Owing to their high affinities and specificities, rabbit monoclonal antibodies (mAbs) have demonstrated value and potential primarily as basic research and diagnostic reagents, but in some cases also as therapeutics. To accelerate access to rabbit mAbs bypassing immunization, we generated a large naïve rabbit antibody repertoire represented by a phage display library encompassing >10 billion independent antibodies in chimeric rabbit/human Fab format and validated it by next-generation sequencing. Panels of rabbit mAbs selected from this library against two emerging cancer targets, ROR1 and ROR2, revealed high diversity, affinity, and specificity. Moreover, ROR1− and ROR2-targeting rabbit mAbs demonstrated therapeutic utility as components of chimeric antigen receptor-engineered T cells, further corroborating the value of the naïve rabbit antibody library as a rich and virtually unlimited source of rabbit mAbs.

We studied the magnetostratigraphy and sedimentary facies of a 550-m-long drill core from the Jiudong Basin in the NE Tibetan Plateau. Our aims were to reconstruct the late Cenozoic sedimentary evolution of this foreland basin, and to determine the spatiotemporal pattern of growth of the Qilian Shan. The magnetostratigraphy indicates that the sedimentary sequence was deposited during ca. 7–0 Ma. From ca. 6.7–3.0 Ma, the sediment accumulation rate increased gradually from ∼30 mm/k.y. to 120 mm/k.y., which was associated with the gradual evolution of sedimentary facies from a shallow lake/delta front to braided rivers. The progradation of the depositional system from 7 Ma to 3 Ma probably reflects the growth of the relief of the Qilian Shan caused by tectonic uplift. The occurrence of a continuous braided river environment from 3 Ma to the present suggests that the high relief of the Qilian Shan developed before 3 Ma. An abrupt decrease of the sedimentation rate to ∼46 mm/k.y. during 3.0–1.8 Ma, and the deposition of coarse-grained sediments, indicates the uplift of the basin center. We interpret this to reflect the propagation of the thrust system of the Qilian Shan into the basin along a southward-dipping décollement from ca. 3 Ma. Climatic changes may have influenced the sedimentary sequence by introducing long-distance-transported thin coarse sand/gravel layers which are sandwiched within the sequence, and likely were a response to cooling events or climatic transitions. The widespread occurrence of deformation within the basin region in the NE Tibetan Plateau at ca. 3 Ma indicates that this date marks the basinward growth of the deformation system.

Chemical-looping combustion (CLC) is a promising technology to combine the energy-use situation in China and CO 2 zero emission in situ, which allows for CO 2 sequestration by efficient ways and without nitrogen oxide (NO x ) formation. An oxygen carrier with good performance is one of the key issues of the CLC process. Calcium sulfate has proven to be a kind of new oxygen carrier with sufficient reactivities in reduction and oxidation reactions, with enough ability for carrying oxygen and no secondary pollution. The decomposition mechanism of calcium sulfate with an average particle size of 8.934 µm in a different simulated atmosphere in CLC is investigated using a simultaneous thermal analyzer at five different heating rates. In an inert atmosphere, the relationship between activation energy and conversion fraction of calcium sulfate is obtained without the introduction of the reaction mechanism function. The values of activation energy, frequency factor, and linear factor corresponding to 5 different heating rates and 30 different common reaction mechanism functions, respectively, are calculated using an accurate kinetics integral expression and a temperature integral approximation with high precision. Kinetic parameters of the decomposition reaction without any disturbance of other reactions, including E βf0 and ln A βf0 , are determined by extrapolating the heating rate to zero. Additionally, the relationship between the activation energy of decomposition and conversion rate is found using the double-extrapolated method. The activation energy at the start of the decomposition reaction, E Rf0 , is also evaluated by extrapolating the conversion rate to zero. Whe E βf0 and E Rf0 are compared, the most likely mechanism function in the decomposition process is characterized by the Avrami-Erofeev equation and the reaction is dominated by the nucleation rate. The Avrami-Erofeev equation is also evaluated on the basis of the most likely mechanism function by the Popescu method.

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