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 Q]: a b s t r a c t H1N1 is an infectious virus which, when spread affects a large volume of the population. It is an airborne disease that spreads easily and has a high death rate. Development of healthcare support systems using cloud computing is emerging as an effective solution with the benefits of better quality of service, reduced costs and flexibility. In this paper, an effective cloud computing architecture is proposed which predicts H1N1 infected patients and provides preventions to control infection rate. It consists of four processing components along with secure cloud storage medical database. The random decision tree is used to initially assess the infection in any patient depending on his/her symptoms. Social Network Analysis (SNA) is used to present the state of the outbreak. The proposed architecture is tested on synthetic data generated for two million users. The system provided 94% accuracy for the classification and around 81% of the resource utilization on Amazon EC2 cloud. The key point of the paper is the use of SNA graphs to calculate role of an infected user in spreading the outbreak known as Outbreak Role Index (ORI). It will help government agencies and healthcare departments to present, analyze and prevent outbreak effectively.
[EX A]: Smart monitoring and controlling of Pandemic Influenza A (H1N1) using Social Network Analysis and cloud computing

[EX Q]: In this paper, we analyze a delayed SEIR epidemic model in which the latent and infected states are infective. The model has a globally asymptotically stable disease-free equilibrium whenever a certain epidemiological threshold, known as the basic reproduction number R 0 , is less than or equal to unity. We investigate the effect of the time delay on the stability of endemic equilibrium when R 0 > 1. We give criteria that ensure that endemic equilibrium is asymptotically stable for all time delays and a Hopf bifurcation occurs as time delay exceeds the critical value. We give formulae for the direction of Hopf bifurcations and the stability of bifurcated periodic solutions by applying the normal form theory and the center manifold reduction for functional differential equations. Numerical simulations are presented to illustrate the analytical results.
[EX A]: Hopf bifurcation analysis of a delayed SEIR epidemic model with infectious force in latent and infected period

[EX Q]: The power of forward genetics in yeast is the foundation on which the field of autophagy research firmly stands. Complementary work on autophagy in higher eukaryotes has revealed both the deep conservation of this process, as well as novel mechanisms by which autophagy is regulated in the context of development, immunity, and neuronal homeostasis. The recent emergence of new clustered regularly interspaced palindromic repeats/ CRISPR-associated protein 9 (CRISPR/Cas9)-based technologies has begun facilitating efforts to define novel autophagy factors and pathways by forward genetic screening in mammalian cells. Here, we set out to develop an expanded toolkit of autophagy reporters amenable to CRISPR/Cas9 screening. Genome-wide screening of our reporters in mammalian cells recovered virtually all known autophagy-related (ATG) factors as well as previously uncharacterized factors, including vacuolar protein sorting 37 homolog A (VPS37A), transmembrane protein 251 (TMEM251), amyotrophic lateral sclerosis 2 (ALS2), and TMEM41B. To validate this data set, we used quantitative microscopy and biochemical analyses to show that 1 novel hit, TMEM41B, is required for phagophore maturation. TMEM41B is an integral endoplasmic reticulum (ER) membrane protein distantly related to the established autophagy factor vacuole membrane protein 1 (VMP1), and our data show that these two factors play related, albeit not fully overlapping, roles in autophagosome biogenesis. In sum, our work uncovers new ATG factors, reveals a malleable network of autophagy receptor genetic interactions, and provides a valuable resource (http://crispr.deniclab.com) for further mining of novel autophagy mechanisms. Eukaryotic cells use autophagy to eliminate unwanted structures-such as protein aggregates, intracellular pathogens, and damaged organelles-that are too large to be handled PLOS Biology | https://doi.Citation: Shoemaker CJ, Huang TQ, Weir NR, Polyakov NJ, Schultz SW, Denic V (2019) CRISPR screening using an expanded toolkit of autophagy reporters identifies TMEM41B as a novel autophagy factor. PLoS Biol 17(4): e2007044. by the proteasome. This unusual vesicle transport pathway begins with packaging of cytoplasmic targets into a double-membrane vesicle (autophagosome) and ends with their degradation in the lysosome. A deeper understanding of autophagy as a regulated mechanism for protein turnover has the potential to provide new therapies for diverse human pathologies, including neurodegenerative disease, cardiometabolic disease, and cancer. Here, we set out to build new reporters for studying mammalian autophagy by genetic screening. This approach allowed us to carry out pooled genome-wide clustered regularly interspaced palindromic repeats (CRISPR) knockout screens and recover virtually all known mammalian autophagy-related (ATG) factors. In addition, we uncovered several uncharacterized proteins, including the endoplasmic reticulum (ER) transmembrane protein 41B (TMEM41B), which we went on to show is required for normal growth of autophagosome precursor membranes around their targets. More broadly, our data set provides a comprehensive resource of genes that affect autophagosome trafficking to the lysosome for further hypothesis testing. Defining the genetic landscape of mammalian autophagy PLOS Biology | https://doi.
[EX A]:
CRISPR screening using an expanded toolkit of autophagy reporters identifies TMEM41B as a novel autophagy factor