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.

Example Input: This paper discusses actions aimed at sustainable management of healthcare wastes (HCW) in China, taking into account the current national situation in this field, as well as the requirements deriving from the Stockholm Convention on Persistent Organic Pollutants and the WHO recommendations. By the end of 2005, there were 149 low-standard HCW disposal facilities in operation in China, distributed throughout different areas. According to the National Hazardous Waste and Healthcare Waste Disposal Facility Construction Plan, 331 modern, high-standard, centralized facilities will be built up in China in municipal level cities. Although incineration is still the main technical option for HCW disposal in China, it is expected that, especially for medium and small size facilities, non-incineration technologies will develop quickly and will soon become the main technical option. The basic management needs -both from the point of view of pollution control and final disposal -have been defined, and a system of technical and environmental standards has been formulated and implemented; however, there are still some shortages. This is particularly true when considering the best available techniques and best environmental practices developed under the Stockholm Convention, with which the present technological and managing situations are not completely compliant. In this framework, the lifecycle (from generation to final disposal of wastes) of HCW and holistic approaches (technology verification, facilities operation, environmental supervision, environmental monitoring, training system, financial mechanism, etc.) towards HCW management are the most important criteria for the sustainable and reliable management of HCW in China.
Example Output: Sustainable management measures for healthcare waste in China

Example Input: medRxiv preprint Interpretation Parameters that successfully reproduce the observed number of cases indicate that both R 0 and the prevalence of the virus might be underestimated. This is in concordance with the newest research on undocumented COVID-19 cases. Consequently, the actual mortality rate is putatively lower than estimated. Confirmation of the pandemic characteristic by further refinement of the model and screening tests is crucial for developing an effective strategy for the global epidemiological crisis. 1 Balcan D, Gonçalves B, Hu H, Ramasco JJ, Colizza V, Vespignani A. Modeling the spatial spread of infectious diseases: the GLobal Epidemic and Mobility computational model. J Comput Sci 2010; 1 : 132-45. 2 Van den Broeck W, Gioannini C, Gonçalves B, Quaggiotto M, Colizza V, Vespignani A. The GLEaMviz computational tool, a publicly available software to explore realistic epidemic spreading scenarios at the global scale. BMC Infect Dis 2011; 11 : 37. 3 Tizzoni M, Bajardi P, Poletto C, et al. Real-time numerical forecast of global epidemic spreading: case study of 2009 A/H1N1pdm. BMC Med 2012;
Example Output: From a single host to global spread. The global mobility based modelling of the COVID-19 pandemic implies higher infection and lower detection rates than current estimates

Example Input: Influenza virus infection is a prevalent disease in humans. Antibodies against hemagglutinin have been shown to prevent infection and hence hemagglutinin is the major constituent of current vaccines. Antibodies directed against the highly conserved extracellular domain of M2 have also been shown to mediate protection against Influenza A infection in various animal models. Active vaccination is generally considered the best approach to combat viral diseases. However, passive immunization is an attractive alternative, particularly in acutely exposed or immune compromized individuals, young children and the elderly. We recently described a novel method for the rapid isolation of natural human antibodies by mammalian cell display. Here we used this approach to isolate human monoclonal antibodies directed against the highly conserved extracellular domain of the Influenza A M2 protein. The identified antibodies bound M2 peptide with high affinities, recognized native cell-surface expressed M2 and protected mice from a lethal influenza virus challenge. Moreover, therapeutic treatment up to 2 days after infection was effective, suggesting that M2-specific monoclonals have a great potential as immunotherapeutic agents against Influenza infection.
Example Output:
Virology Journal Prophylactic and therapeutic activity of fully human monoclonal antibodies directed against Influenza A M2 protein