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".

Q: Paragraph: To provide optimal cut-off values of anti-Middle East respiratory syndrome coronavirus (MERS-CoV) serologic tests, we evaluated performance of ELISA IgG, ELISA IgA, IFA IgM, and IFA IgG using 138 serum samples of 49 MERS-CoV-infected patients and 219 serum samples of 219 rRT-PCR-negative MERS-CoV-exposed healthcare personnel and patients. The performance analysis was conducted for two different purposes: (1) prediction of neutralization activity in MERS-CoV-infected patients, and (2) epidemiologic surveillance of MERS-CoV infections among MERS-CoV-exposed individuals. To evaluate performance according to serum collection time, we used 'days post onset of illness (dpoi)' and 'days post exposure (dpex)' assessing neutralization activity and infection diagnosis, respectively. Performance of serologic tests improved with delayed sampling time, being maximized after a seroconversion period. In predicting neutralization activity, ELISA IgG tests showed optimal performance using sera collected after 21 dpoi at cut-off values of OD ratio 0.4 (sensitivity 100% and specificity 100%), and ELISA IgA showed optimal performance using sera collected after 14 dpoi at cut-off value of OD ratio 0.2 (sensitivity 85.2% and specificity 100%). In diagnosis of MERS-CoV infection, ELISA IgG exhibited optimal performance using sera collected after 28 dpex, at a cut-off value of OD ratio 0.2 (sensitivity 97.3% and specificity 92.9%). These new breakpoints are markedly lower than previously suggested values (ELISA IgG OD ratio 1.1, sensitivity 34.8% and specificity 100% in the present data set), and the performance data help serologic tests to be practically used in the field of MERS management. 
 Title: Suggested new breakpoints of anti-MERS-CoV antibody ELISA titers: performance analysis of serologic tests

A: True
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Q: Paragraph: Background: Health care planning for pandemic influenza is a challenging task which requires predictive models by which the impact of different response strategies can be evaluated. However, current preparedness plans and simulations exercises, as well as freely available simulation models previously made for policy makers, do not explicitly address the availability of health care resources or determine the impact of shortages on public health. Nevertheless, the feasibility of health systems to implement response measures or interventions described in plans and trained in exercises depends on the available resource capacity. As part of the AsiaFluCap project, we developed a comprehensive and flexible resource modelling tool to support public health officials in understanding and preparing for surges in resource demand during future pandemics. Results: The AsiaFluCap Simulator is a combination of a resource model containing 28 health care resources and an epidemiological model. The tool was built in MS Excel© and contains a user-friendly interface which allows users to select mild or severe pandemic scenarios, change resource parameters and run simulations for one or multiple regions. Besides epidemiological estimations, the simulator provides indications on resource gaps or surpluses, and the impact of shortages on public health for each selected region. It allows for a comparative analysis of the effects of resource availability and consequences of different strategies of resource use, which can provide guidance on resource prioritising and/or mobilisation. Simulation results are displayed in various tables and graphs, and can also be easily exported to GIS software to create maps for geographical analysis of the distribution of resources. The AsiaFluCap Simulator is freely available software (www.cdprg.org) which can be used by policy makers, policy advisors, donors and other stakeholders involved in preparedness for providing evidence based and illustrative information on health care resource capacities during future pandemics. The tool can inform both preparedness plans and simulation exercises and can help increase the general understanding of dynamics in resource capacities during a pandemic. The combination of a mathematical model with multiple resources and the linkage to GIS for creating maps makes the tool unique compared to other available software. 
 Title: Development of a resource modelling tool to support decision makers in pandemic influenza preparedness: The AsiaFluCap Simulator

A: True
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Q: Paragraph: β-keto esters are used as precursors for the synthesis of β-amino acids, which are building blocks for some classes of pharmaceuticals. Here we describe the comparison of screening procedures for hydrolases to be used for the hydrolysis of β-keto esters, the first step in the preparation of β-amino acids. Two of the tested high throughput screening (HTS) assays depend on coupled enzymatic reactions which detect the alcohol released during ester hydrolysis by luminescence or absorption. The third assay detects the pH shift due to acid formation using an indicator dye. To choose the most efficient approach for screening, we assessed these assays with different statistical methods-namely, the classical Z'-factor, standardized mean difference (SSMD), the Kolmogorov-Smirnov-test, and t-statistics. This revealed that all three assays are suitable for HTS, the pH assay performing best. Based on our data we discuss the explanatory power of different statistical measures. Finally, we successfully employed the pH assay to identify a very fast hydrolase in an enzyme-substrate screening. 
 Title: Statistical Evaluation of HTS Assays for Enzymatic Hydrolysis of β-Keto Esters

A:
True
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