In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".

Paragraph: In this paper, we propose and discuss a stochastic SIRS epidemic model with non-monotone incidence rate under regime-switching. First of all, we show that there is a unique positive solution, which is a prerequisite for analyzing the long-term behavior of the stochastic model. Then, a threshold dynamic determined by the basic reproduction number R s 0 is established: the disease can be eradicated almost surely if R s 0 < 1 and under mild extra conditions, whereas if R s 0 > 1 , the densities of the distributions of the solution can converge in L 1 to an invariant density by using the Markov semigroups theory. Finally, based on realistic parameters obtained from previous literatures, numerical simulations have been performed to verify our analytical results. 
 Title: A stochastic SIRS epidemic model with non-monotone incidence rate under regime-switching
True

Paragraph: The APETALA2 (AP2) genes represent the AP2 group within a large group of DNA-binding proteins called AP2/EREBP. The AP2 gene is functional and necessary for flower development, stem cell maintenance, and seed development, whereas the other members of AP2 group redundantly affect flowering time. Here we study the phylogeny of AP2 group genes in spermatophytes. Spermatophyte AP2 group genes can be classified into AP2 and TOE types, six clades, and we found that the AP2 group homologs in gymnosperms belong to the AP2 type, whereas TOE types are absent, which indicates the AP2 type gene are more ancient and TOE type was split out of AP2 type and losing the major function. In Brassicaceae, the expansion of AP2 and TOE type lead to the gene number of AP2 group were up to six. Purifying selection appears to have been the primary driving force of spermatophyte AP2 group evolution, although positive selection occurred in the AP2 clade. The transition from exon to intron of AtAP2 in Arabidopsis mutant leads to the loss of gene function and the same situation was found in AtTOE2. Combining this evolutionary analysis and published research, the results suggest that typical AP2 group genes may first appear in gymnosperms and diverged in angiosperms, following expansion of group members and functional differentiation. In angiosperms, AP2 genes (AP2 clade) inherited key functions from ancestors and other genes of AP2 group lost most function but just remained flowering time controlling in gene formation. In this study, the phylogenies of AP2 group genes in spermatophytes was analyzed, which supported the evidence for the research of gene functional evolution of AP2 group. 
 Title: Expansion and Functional Divergence of AP2 Group Genes in Spermatophytes Determined by Molecular Evolution and Arabidopsis Mutant Analysis
True

Paragraph: The novel Coronavirus SARS-CoV-2 (CoV) has induced a world-wide pandemic and subsequent non-pharmaceutical interventions (NPI) in order to control the spreading of the virus. NPIs are considered to be critical in order to at least delay the peak number of infected individuals and to prevent the health care system becoming overwhelmed by the number of patients to treat in hospitals or in intensive care units (ICUs). However, there is also increasing concern that the NPIs in place would increase mortality because of other diseases, increase the frequency of suicide and increase the risk of an economic recession with unforeseeable implications. It is therefore instrumental to evaluate the necessity of NPIs and to monitor the progress of containment of the virus spreading. We used a data-driven estimation of the evolution of the reproduction number for viral spreading in Germany as well as in all its federal states. Based on an extended infectionepidemic model, parameterized with data from the Robert Koch-Institute and, alternatively, with parameters stemming from a fit to the initial phase of CoV spreading in different regions of Italy, we consistently found that the reproduction number was turned down to a range near 1 in all federal states. We used the latest reproduction number as a starting point for the simulation of epidemic progression and varied the reproduction number, mimicking either release or strengthening of NPIs. Germany is currently, April 3rd, 2020, at the border line of a reproduction number between the scenarios of major immunisation of the population or eradication of the virus. We strongly recommend to keep all NPIs in place and suggest to even strengthen the measures in order to accelerate reaching the state of full control, thus, also limiting collateral damage of the NPIs in time. : medRxiv preprint 1 day, although the range varies between 0 -3 days (IQR) depending on age. The time span spent during hospitalization to admission in ICU is likely shorter as the patients get older. For Germany where the majority of reported infections are in middle-aged groups, we assume the median value of 1/R7 ~ 2.5 days. We have varied 1/R7 within a range of 1 -3.5 days. The inverse of R8 depicts the time span spent in ICU before discharge. Here, we assume that patients who are recovering in ICU do not spend much time in general hospital care. 1/R8 is also presumably dependent on age, with more severe courses and thus prolonged ICU admission needed for high risk individuals, such as aged patients. WHO-China joint mission on COVID-19 outbreak (WHO-China 2020) reports that the total duration of being in hospital for the severely ill patients can be around 3 to 6 weeks. This gives us a range of possible values because: . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not peer-reviewed) The copyright holder for this preprint . 
 Title: Estimate of the development of the epidemic reproduction number Rt from Coronavirus SARS-CoV-2 case data and implications for political measures based on prognostics

False