Implications for Ediacaran biological evolution from the ca. 602 Ma Lantian biota in China

The morphologically differentiated benthic macrofossils of algae and putative animal affinities of the Lantian biota in China represents the oldest known Ediacaran macroscopic eukaryotic assemblage. Although the biota provides remarkable insights into the early evolution of complex macroeukaryotes in the Ediacaran, the uncertainty in its age has hampered any robust biological evaluation. We resolve this issue by applying a petrographic-guided rhenium-osmium (Re-Os) organic-bearing sedimentary unit study on the Lantian biota. This work confines a minimum age for the first appearance of the Lantian biota to 602 ± 7 Ma (2σ, including decay constant uncertainty). This new Re-Os date confirms that the Lantian biota is of early–mid Ediacaran age and temporally distinct from the typical Ediacaran macrobiotas. Our results indicate that the differentiation and radiation of macroscopic eukaryotes, and the evolution of the primitive, erect epibenthic ecosystem, occurred in the early–mid Ediacaran and were associated with highly fluctuating oceanic redox conditions. The radiogenic initial 187Os/188Os ratios derived from the Lantian (1.14 ± 0.02) and other Ediacaran shales invoke oxidative weathering of upper continental crust in the early–middle Ediacaran, which may have stimulated the evolution of life and oceanic-atmospheric oxygenation. Integrated with published Ediacaran chronological and geochemical data, our new Re-Os geochemical study of the Lantian black shale provides a refined, time-calibrated record of environment and eukaryote evolution during the Ediacaran

Lattice study on ηc2\eta_{c2} and X(3872)

Properties of $2^{-+}$ charmonium $\eta_{c2}$ are investigated in quenched lattice QCD. The mass of $\eta_{c2}$ is determined to be 3.80(3) GeV, which is close to the mass of $D$-wave charmonium $\psi(3770)$ and in agreement with quark model predictions. The transition width of $\eta_{c2}\to \gamma J/\psi$ is also obtained with a value $\Gamma=3.8(9)$ keV. Since the possible $2^{-+}$ assignment to X(3872) has not been ruled out by experiments, our results help to clarify the nature of X(3872).Comment: 15 pages, 8 figures. typos, grammatical errors and some references corrected, redundant discussions deleted, conclusion does not change. published versio

Low-Level Laser-Accelerated Peripheral Nerve Regeneration within a Reinforced Nerve Conduit across a Large Gap of the Transected Sciatic Nerve in Rats

This study proposed a novel combination of neural regeneration techniques for the repair of damaged peripheral nerves. A biodegradable nerve conduit containing genipin-cross-linked gelatin was annexed using beta-tricalcium phosphate (TCP) ceramic particles (genipin-gelatin-TCP, GGT) to bridge the transection of a 15 mm sciatic nerve in rats. Two trigger points were irradiated transcutaneously using 660 nm of gallium-aluminum arsenide phosphide (GaAlAsP) via laser diodes for 2 min daily over 10 consecutive days. Walking track analysis showed a significant improvement in sciatic functional index (SFI) (P<0.01) and pronounced improvement in the toe spreading ability of rats undergoing laser stimulation. Electrophysiological measurements (peak amplitude and area) illustrated by compound muscle action potential (CMAP) curves demonstrated that laser stimulation significantly improved nerve function and reduced muscular atrophy. Histomorphometric assessments revealed that laser stimulation accelerated nerve regeneration over a larger area of neural tissue, resulting in axons of greater diameter and myelin sheaths of greater thickness than that observed in rats treated with nerve conduits alone. Motor function, electrophysiological reactions, muscular reinnervation, and histomorphometric assessments all demonstrate that the proposed therapy accelerated the repair of transected peripheral nerves bridged using a GGT nerve conduit

Capturing Delayed Feedback in Conversion Rate Prediction via Elapsed-Time Sampling

Conversion rate (CVR) prediction is one of the most critical tasks for digital display advertising. Commercial systems often require to update models in an online learning manner to catch up with the evolving data distribution. However, conversions usually do not happen immediately after a user click. This may result in inaccurate labeling, which is called delayed feedback problem. In previous studies, delayed feedback problem is handled either by waiting positive label for a long period of time, or by consuming the negative sample on its arrival and then insert a positive duplicate when a conversion happens later. Indeed, there is a trade-off between waiting for more accurate labels and utilizing fresh data, which is not considered in existing works. To strike a balance in this trade-off, we propose Elapsed-Time Sampling Delayed Feedback Model (ES-DFM), which models the relationship between the observed conversion distribution and the true conversion distribution. Then we optimize the expectation of true conversion distribution via importance sampling under the elapsed-time sampling distribution. We further estimate the importance weight for each instance, which is used as the weight of loss function in CVR prediction. To demonstrate the effectiveness of ES-DFM, we conduct extensive experiments on a public data and a private industrial dataset. Experimental results confirm that our method consistently outperforms the previous state-of-the-art results.Comment: This paper has been accepted by AAAI 202