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".

Ex Input:
Paragraph: Similarity in time series is an important feature of dynamical systems such as financial systems, with potential use for clustering of series in system. Here, we mainly introduce a novel method: the reconstructed phase space information clustering method to analyze the financial markets. The method is used to examine the similarity of different sequences by calculating the distances between them, which the main difference from previous method is the way to map the original time series to symbolic sequences. Here we make use of the state space reconstruction to construct the symbolic sequences and quantify the similarity of different stock markets and exchange rate markets considering the chaotic behavior between the complex time series. And we compare the results of similarity of artificial and real data using the modified method, information categorization method and system clustering method. We conclude that the reconstructed phase space information clustering method is effective to research the close relationship in time series and for short time series especially. Besides, we report the results of similarity of different exchange rate time series in different periods and find the effect of the exchange rate regime in 2008 on the time series. Also we acquire some characteristics of exchange rate time
Title: The similarity analysis of financial stocks based on information clustering

Ex Output:
False

Ex Input:
Paragraph: The new era in systems pharmacology has revolutionized the human biology. Its applicability, precise treatment, adequate response and safety measures fit into all the paradigm of medical/clinical practice. The importance of mathematical models in understanding the disease pathology and epideomology is now being realized. The advent of high-throughput technologies and the emergence of systems biology have resulted in the creation of systems pharmacogenomics and the focus is now on personalized medicine. However, there are some regulatory issues that need to be addresssed; are we ready for this universal adoption? This article details some of the infectious disease pharmacogenomics to the developments in this area.
Title: System pharmacogenomics application in infectious diseases

Ex Output:
True

Ex Input:
Paragraph: The initial step of retrovirus entry-the interaction between the virus envelope glycoprotein trimer and a cellular receptor-is complex, involving multiple, noncontiguous determinants in both proteins that specify receptor choice, binding affinity and the ability to trigger conformational changes in the viral glycoproteins. Despite the complexity of this interaction, retroviruses have the ability to evolve the structure of their envelope glycoproteins to use a different cellular protein as receptors. The highly homologous subgroup A to E Avian Sarcoma and Leukosis Virus (ASLV) glycoproteins belong to the group of class 1 viral fusion proteins with a two-step triggering mechanism that allows experimental access to intermediate structures during the fusion process. We and others have taken advantage of replication-competent ASLVs and exploited genetic selection strategies to force the ASLVs to naturally evolve and acquire envelope glycoprotein mutations to escape the pressure on virus entry and still yield a functional replicating virus. This approach allows for the simultaneous selection of multiple mutations in multiple functional domains of the envelope glycoprotein that may be required to yield a functional virus. Here, we review the ASLV family and experimental system and the reverse engineering approaches used to understand the evolution of ASLV receptor usage.
Title: viruses Reverse Engineering Provides Insights on the Evolution of Subgroups A to E Avian Sarcoma and Leukosis Virus Receptor Specificity

Ex Output:
False