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: Infectious diseases are a leading cause of death globally. Decisions surrounding how to control an infectious disease outbreak currently rely on a subjective process involving surveillance and expert opinion. However, there are many situations where neither may be available. Modeling can fill gaps in the decision making process by using available data to provide quantitative estimates of outbreak trajectories. Effective reduction of the spread of infectious diseases can be achieved through collaboration between the modeling community and public health policy community. However, such collaboration is rare, resulting in a lack of models that meet the needs of the public health community. Here we show a Susceptible-Infectious-Recovered (SIR) model modified to include control measures that allows parameter ranges, rather than parameter point estimates, and includes a web user interface for broad adoption. We apply the model to three diseases, measles, norovirus and influenza, to show the feasibility of its use and describe a research agenda to further promote interactions between decision makers and the modeling community. Despite substantial public health improvements in the last century, infectious diseases remain one of the leading causes of both morbidity and mortality 1,2 . When confronted with an infectious disease outbreak, public health officials typically work to control the outbreak by performing assessments, analyzing surveillance data, identifying resources and interacting with subject mater experts 2-4 . Control measures are then implemented based on the cumulative information collected. These approaches rely heavily on good surveillance systems, access to experts, and good intuition about which control measures to use. As such, they are largely subjective, time consuming, and the infrastructure required is often not present in high disease burden areas. Modeling is an attractive supplemental method because of the ability to estimate an outbreak's trajectory and the effects of possible control measures in a timely manner. Compartmental models are historically common; they divide individuals into categories based on their disease status. The most common variant is the SIR model, named after the categories used-"susceptible", "infectious" and "recovered". Models of this nature have small computational requirements, and are thus commonly used as first pass attempts to characterize outbreaks or infections quickly 5 . For example, after the sudden emergence of Severe Acute Respiratory Syndrome (SARS) in the early 2000s, researchers used modeling to characterize the virus' epidemiology. Several used compartmental models with control measures like quarantine or isolation in various settings (e.g., hospitals or cities) to describe effects of possible interventions 6-9 . Similar work exists for essentially all well known infectious diseases. For example, Mandal et al. provide a review of models used for malaria 10 and Bauch et al. explore model use with respect to SARS and other emerging infectious diseases 6 . Methods among these groups are often similar, but tend to focus on specific diseases and locations of interest. In contrast, agent-based models use a bottom-up approach where the agents (these are often people) interact with particular rules to simulate outbreaks 11 . This allows simulations at high resolutions, but requires large amounts of data to parameterize the models, as well as substantial computational power. It is thought that they may reflect real world scenarios more accurately, but the lack of available epidemiological data necessitates assumptions that are difficult or impossible to test 11 . These models further require computational resources inaccessible to an average health department. Both agent-based and compartmental models exhibit additional features that are problematic to wide-spread model adoption. The first is the focus on particular disease-location pairs. This emphasis precludes application to
Title: An approach to and web-based tool for infectious disease outbreak intervention analysis OPEN

A: False
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Q: Paragraph: Chitin is a linear polysaccharide of N-acetylglucosamine, which is highly abundant in nature and mainly produced by marine crustaceans. Chitosan is obtained by hydrolytic deacetylation. Both polysaccharides are renewable resources, simply and cost-effectively extracted from waste material of fish industry, mainly crab and shrimp shells. Research over the past five decades has revealed that chitosan, in particular, possesses unique and useful characteristics such as chemical versatility, polyelectrolyte properties, gel-and film-forming ability, high adsorption capacity, antimicrobial and antioxidative properties, low toxicity, and biocompatibility and biodegradability features. A plethora of chemical chitosan derivatives have been synthesized yielding improved materials with suggested or effective applications in water treatment, biosensor engineering, agriculture, food processing and storage, textile additives, cosmetics fabrication, and in veterinary and human medicine. The number of studies in this research field has exploded particularly during the last two decades. Here, we review recent advances in utilizing chitosan and chitosan derivatives in different technical, agricultural, and biomedical fields. A large number of chitosan-based composites were investigated for removal of metal ions from aqueous solutions. They include chitosan-polymer macromolecular complexes (as cellulose, cellulosic matrix like cotton fibers, alginate, polyvinyl alcohol, polyvinyl chloride), chitosan ceramics, as well as clay and silicate composites (bentonite, montmorillonite, perlite, and zeolite) (Wan Ngah et al. 2011) . Due to the vast number of scientific publications on chitosan-based adsorption that have been published, only a representative sample is depicted for Cr(VI) and Cu(II). Cognate composites were devised as adsorbents of other metal ions (Cd, As, Fe, Pb, Co, Pb, Hg, Ni, Zn, U) that can be found in the detailed reviews of Reddy and Lee (
Title: Chitin/Chitosan: Versatile Ecological, Industrial, and Biomedical Applications

A: False
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Q: Paragraph: Steady state alveolar macrophages (AM) are long-lived lung-resident macrophages with sentinel function. Evidence suggests that AM precursors originate during embryogenesis and populate lungs without replenishment by circulating leukocytes. However, their presence and persistence are unclear following human lung transplantation (LTx). Our goal was to examine donor AM longevity and evaluate whether AM of recipient origin seeds the transplanted lungs. Origin of AM was accessed using donor-recipient HLA mismatches. We demonstrate that 94-100% of AM present in bronchoalveolar lavage (BAL) were donor derived and importantly AM of recipient origin were not detected. Further, analysis of BAL cells up to 3.5 yrs post-LTx revealed that majority of AM (>87%) was donor derived. Elicitation of de novo donor specific antibody (DSA) is a major post-LTx complication and a risk factor for development of chronic rejection. The donor AM responded to anti-HLA framework Ab with secretion of inflammatory cytokines. Further, in an experimental murine model, we demonstrate that adoptive transfer of allogeneic AM stimulated humoral and cellular immune responses to alloantigen and lung-associated self-antigens and led to bronchiolar obstruction. Therefore, donor derived AM play an essential role in the DSA induced inflammatory cascade leading to obliterative airway disease of the transplanted lungs.
Title: Long-term persistence of donor alveolar macrophages in human lung transplant recipients that influences donor specific immune responses HHS Public Access

A:
True
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