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Simple Summary: Any abnormalities in the physical properties of an egg can decrease the hatching rate. The embryos of oviparous reptiles obtain Ca from the eggshell. This motivated us to analyze the microstructure and Ca in the eggshells of Chinese alligators. We found that the shells of the eggs with high hatching rates were thicker than those of the eggs with low hatching rates. There were also fewer erosion-crater pores on the surfaces of the eggs with high hatching rates than on the surfaces of the eggs with low hatching rates. Moreover, the shells' Ca contents were significantly higher in the eggs with high hatching rates than in the eggs with low hatching rates. Cluster modeling indicated that the highest hatching rate occurred when the eggshell thickness was 200–380 µm and there were 1–12 pores. These results suggest that eggs with adequate Ca contents, thicker shells, and less air permeability are more likely to hatch. Furthermore, our findings can inform future studies. The Chinese alligator (Alligator sinensis), found only in a small region in southeastern Anhui Province, is listed as critically endangered (CR) by the International Union for Conservation of Nature (IUCN) due to its current declining population trend. Any abnormalities in the physical properties of an egg can decrease the hatching rate. In particular, eggshells play an essential role in embryo development, motivating us to analyze the microstructures of the eggshells of Chinese alligators. In this study, we categorized the eggshells into two groups, based on the hatching rates, and analyzed the relationship between the eggshell parameters (eggshell thickness, calcium content, and number of pores in erosion craters) and the hatching rate, as well as the relationships between the eggshell parameters. We found that the shells of the eggs with high hatching rates were thicker than those of the eggs with low hatching rates. There were also fewer erosion-crater pores on the surfaces of the eggs with high hatching rates than on the surfaces of the eggs with low hatching rates. Moreover, the shell Ca content was significantly higher in the eggs with high hatching rates than in the eggs with low hatching rates. Cluster modeling indicated that the highest hatching rate occurred when the eggshell thickness was 200–380 µm and there were 1–12 pores. These results suggest that eggs with adequate Ca contents, thicker shells, and less air permeability are more likely to hatch. Furthermore, our findings can inform future studies, which will be vital for the survival of the critically endangered Chinese alligator species. [ABSTRACT FROM AUTHOR]

Tensor computations are increasingly prevalent numerical techniques in data science, but pose unique challenges for high-performance implementation. We provide novel algorithms and systems infrastructure which enable efficient parallel implementation of algorithms for tensor completion with generalized loss functions. Specifically, we consider alternating minimization, coordinate minimization, and a quasi-Newton (generalized Gauss-Newton) method. By extending the Cyclops library, we implement all of these methods in high-level Python syntax. To make possible tensor completion for very sparse tensors, we introduce new multi-tensor primitives, for which we provide specialized parallel implementations. We compare these routines to pairwise contraction of sparse tensors by reduction to hypersparse matrix formats, and find that the multi-tensor routines are more efficient in theoretical cost and execution time in experiments. We provide microbenchmarking results on the Stampede2 supercomputer to demonstrate the efficiency of the new primitives and Cyclops functionality. We then study the performance of the tensor completion methods for a synthetic tensor with 10 billion nonzeros and the Netflix dataset, considering both least squares and Poisson loss functions. • Novel algorithms that use second information for generalized tensor completion. • Novel formulation of quasi-Newton algorithm for generalized tensor completion. • New programming abstractions in Python for sparse tensor kernels. • First parallel implementation of generalized tensor completion algorithms. [ABSTRACT FROM AUTHOR]

With the development of a sustainable lifestyle, people are paying more and more attention to the comfort of their own living environment, including public space lighting, which is immediately accessible to residents. The demand on its quality and comfort has thus gained attention recently. However, there is still a lack of related research on public space lighting comfort evaluation models that combine nighttime light remote sensing data and field measurement data, and link lighting attributes with the comfort of residents. This research uses nighttime light remote sensing data to select typical test areas, measures the lighting data of the survey points on the spot, develops an intelligent WeChat applet that collects public perception data, analyzes different lighting parameters, and builds a public space lighting comfort model based on the structural equation model analysis method. The results show that the factor that the areas with high light intensity are more comfortable than the areas with low light intensity. In areas with high light intensity, people pay more attention to the uniformity, security and comfort of the light, while in areas with low light intensity or high blue light, people's perception of glare will be more obvious. This research can provide a basis for the intelligent optimization of public space lighting from the perspective of public preference. [ABSTRACT FROM AUTHOR]