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".

Example Input: Paragraph: Meliacine (MA), an antiviral principle present in partially purified leaf extracts of Melia azedarach L., prevents the development of herpetic stromal keratitis (HSK) in mice by diminishing the viral load in the eye and the severity of lesions caused by a virus-induced immunopathological reaction. The tetranortriterpenoid 1-cinnamoyl-3,11-dihydroxymeliacarpin (CDM), obtained from MA purification, displays anti-herpetic activity and impedes nuclear factor B (NF-B) activation in HSV-1 infected conjunctival cells. To extend our understanding about CDM biological properties, we investigated its anti-HSV-1 activity as well as the effect on NF-B activation and cytokine secretion induced by viral (HSV-1) and no-viral (LPS) stimuli, in corneal cells and macrophages. CDM exerted a potent anti-HSV-1 effect on corneal cells and inhibited NF-B translocation to the nucleus, leading to a decrease in IL-6 production. Besides, CDM seemed to modulate IL-6 and TNF-␣ responses in macrophages, whether they were infected with HSV-1 or stimulated with LPS. However, CDM did not affect NF-B activation in these cells, suggesting that an alternative NF-B cell signaling pathway would be involved in the modulation of cytokine production. We conclude that, in addition to its antiviral effect, CDM would be acting as an immunomodulating compound which would be responsible for the improvement of murine HSK already reported. 
 Title: A natural tetranortriterpenoid with immunomodulating properties as a potential anti-HSV agent
Example Output: False

Example Input: Paragraph: Among the causes for pregnancy loss, viruses and non-infectious factors are among the most important. In both dogs and cats, research and clinical evidence provide proof that there is an increasing incidence of pregnancy loss associated with infectious diseases like herpesvirus, as well as the presence of toxicants or chemicals in the animal's diet and environment. Endocrine causes must be taken into consideration when dealing with pregnancy loss. This review will cover the most recent knowledge regarding viral and non-infectious of pregnancy losses in the dog and cat. # 
 Title: Canine and feline pregnancy loss due to viral and non-infectious causes: A review
Example Output: True

Example Input: Paragraph: The rapid growth of the tourism and hospitality industries serves as the major driving force for academic researchers to investigate the accurate forecasting of lodging demand in tourist destinations. For instance, Tsai et al. (2006) studied the relationship between hotel room demand/supply functions and room rate using a simultaneous equations model for determinants of room demand/supply in Las Vegas. In terms of optimal hotel rates, Pan (2007) proposed an optimal room rate model to set pricing strategies at peak or low seasons. Recently, Slattery (2009) suggested employing the Otus theory to study the relationships between economic structure and demand/ supply of hotel rooms. In this paper, a novel time series model is presented which models multivariate time series data. The advantage of this model is that the discovered factors are mutually independent and a univariate time series model can be applied to these factors without considering the factors' interdependence. The next section introduces the methodologies of independent component analysis. On the basis of this model, empirical studies on Hong Kong hotel occupancy rates are analyzed. The most dominant factor of infectious diseases is subsequently detected. At last, managerial implications and concluding remarks are provided. Independent component analysis (ICA) is a statistical technique that aims to capture observed data in terms of a linear combination of underlying latent variables. These latent variables are assumed to be non-Gaussian and mutually independent. A typical ICA model for an N-dimensional multivariate time series {x 1 =(x it , . . ., x Nt ) 0 }: t = 1, . . ., T) is where s t is a vector of statistically independent latent variables called independent components (ICs). A is an unknown constant mixing matrix, and T is the number of observations of the time series. The task of ICA is to identify both the ICs and the matrix A. Various algorithms for parameter estimation have been developed for ICA. Among them, a widely used one is the FastICA algorithm, which was proposed by Hyvä rinen et al. (2001). Since traditional ICA algorithms lack the ranking of ICs, Wu et al. (2006) proposed an ordering algorithm for independent components based on the minimizing mean squared errors (MSE) criterion. Based on this ordering method, ICs are sorted in a way such that modeling errors are minimized and dominant ICs are identified. Modifying the approach of Wu et al. (2006) , the major steps of modeling hotel occupancy rate using ICA are presented as follows: 1. Import the multivariate dataset (X) with number of N time series, each time series has T observations. 2. Use the FastICA algorithm to find the independent components (S) and the mixing matrix (A). 3. Use the independent component (IC) ordering method to order the ICs to find 1st IC, 2nd IC, 3rd IC, and so on. The recent global outbreak of Influenza A (H1N1), or the more commonly known as swine flu, has negatively affected the tourism and hospitality industries in many countries. This article reports a study that applied independent component analysis, a novel statistical technique, to separate the dominant factors which determine the levels of hotel occupancy rates in Hong Kong. Empirical findings would provide useful insights on how the dynamic lodging demand reacts to epidemics based on the severity and duration of the events. ß 
 Title: The impact of infectious diseases on hotel occupancy rate based on independent component analysis
Example Output:
True