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.

Ex Input:
Emerging and re-emerging pathogens and bioterror threats require an organized and coherent response from the worldwide research community to maximize available resources and competencies with the primary goals to understand the pathogen and enable intervention. In 2001, the Structural Proteomics In Europe project prototyped the pan-viral structural genomic approach, and the SARS outbreak in 2003 accelerated the concept of structural characterization of all proteins from a viral proteome and the interaction with their host partners. Following that approach, in 2004 the center for Functional and Structural Proteomics for SARS-CoV related proteins was initiated as part of the US NIH NIAID proteomics resource centers. Across worldwide efforts in Asia, Europe and America, the international research teams working on SARS-CoV have now determined experimental structural information for 45% of the SARS-CoV proteins and 53% of all its soluble proteins. This data is fully available to the scientific community and is providing an unprecedented level of insight to this class of RNA viruses. The efforts and results by the international scientific community to the SARS outbreak are serving as an example and roadmap of a rapid response using modern research methods.

Ex Output:
International Research Networks in Viral Structural Proteomics: again, lessons from SARS

Ex Input:
. 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.

Ex Output:
THE ROLE OF INTERFERON IN SPONTANEOUS CELL-MEDIATED CYTOTOXICITY IN PIGS

Ex Input:
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 Hyva 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.

Ex Output:
The impact of infectious diseases on hotel occupancy rate based on independent component analysis