In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

Q: Estimating temporal changes in a target population from phylogenetic or count data is an important problem in ecology and epidemiology. Reliable estimates can provide key insights into the climatic and biological drivers influencing the diversity or structure of that population and evidence hypotheses concerning its future growth or decline. In infectious disease applications, the individuals infected across an epidemic form the target population. The renewal model estimates the effective reproduction number, R, of the epidemic from counts of its observed cases. The skyline model infers the effective population size, N, underlying a phylogeny of sequences sampled from that epidemic. Practically, R measures ongoing epidemic growth while N informs on historical caseload. While both models solve distinct problems, the reliability of their estimates depends on p-dimensional piecewise-constant functions. If p is misspecified, the model might underfit significant changes or overfit noise and promote a spurious understanding of the epidemic, which might misguide intervention policies or misinform forecasts. Surprisingly, no transparent yet principled approach for optimising p exists. Usually, p is heuristically set, or obscurely controlled via complex algorithms. We present a computable and interpretable p-selection method based on the minimum description length (MDL) formalism of information theory. Unlike many standard model selection techniques, MDL accounts for the additional statistical complexity induced by how parameters interact. As a result, our method optimises p so that R and N estimates properly adapt to the available data. It also outperforms comparable Akaike and Bayesian information criteria on several classification problems. Our approach requires some knowledge of the parameter space and exposes the similarities between renewal and skyline models.

A: Adaptive Estimation for Epidemic Renewal and Phylogenetic Skyline Models
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Q: . The role of interferon in spontaneous cell-mediated cytotoxicity in pigs. Vet. Microbiol., I i : 69 -77. Specific release of StCr and the production of interferon (IFN) increased in parallel in a spontaneous cell-mediated cytotoxicity (SCMC) assay in which uninfected PK-15 cells or PK-15 cells persistently infected with transmissible gastroenteritis virus (PK-15-TGE cells) were used as targets, and peripheral blood lymphocytes (PBL) from a young adult pig were used as effector cells. Higher levels of both specific S~Cr release and IFN were obtained in the assays containing PK-15-TGE cells. Co-cultivation of PBL from newborn piglets with PK-15-TGE cells yielded similar levels of IFN to those produced by co-cultivation of adult PBL and PK-15-TGE cells, but lower levels of IFN were produced by co-cultivation with uninfected PK-15 cells. Pretreatment of adult PBL with IFN augmented their SCMC effector activity for both PK-15 and PK-15-TGE cells in the S~Cr release assay. Pretreatment of the PK-15-TGE target cells with IFN did not affect their release of S*Cr in the SCMC reaction, while IFN pretreatment of PK-15 targets protected them against SCMC. In a single cell cytotoxicity assay the effects of IFN pretreatment on the effector adult PBL and on the PK-15 and PK-15-TGE target cells were confirmed, and SCMC incompetent PBL from neonatal piglets were rendered cytotoxic by pretreatment with IFN. PBL from newborn piglets bound to either target cell with the same frequency as PBL from SCMC competent adult pigs, and IFN pretreatment of either effector or target cells had no effect on target-binding frequency.

A: THE ROLE OF INTERFERON IN SPONTANEOUS CELL-MEDIATED CYTOTOXICITY IN PIGS
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Q: The fourth outbreak of the Coronaviruses, known as the 2019-nCoV, has occurred in Wuhan city of Hubei province in China in December 2019. We propose a timevarying sparse vector autoregressive (VAR) model to retrospectively analyze and visualize the dyamic transmission routes of this outbreak in mainland China over January 31 -February 19, 2020. Our results demonstrate that the influential interprovince routes from Hubei have become unidentifiable since February 4, whereas the self-transmission in each province was accelerating over February 4-15. From February 16, all routes became less detectable, and no influential transmissions could be identified on February 18 and 19. Such evidence supports the effectiveness of government interventions, including the travel restrictions in Hubei. Implications of our results suggest that in addition to the origin of the outbreak, virus preventions are of crucial importance in provinces with the largest migrant workers percentages (e.g., Jiangxi, Henan and Anhui) to controlling the spread of 2019-nCoV.

A:
How does the outbreak of 2019-nCoV spread in mainland China? A retrospective analysis of the dynamic transmission routes *
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