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".

Input: Consider Input: Paragraph: Background: Although the mini-clinical evaluation (mini-CEX) exercise has been adapted to a broad range of clinical situations, limited studies of the mini-CEX for postgraduate residency training in emergency medicine (EM) have been documented. Aim: The purpose of this study is to analyze the results of implementing the mini-CEX into the one-month postgraduate residency training in EM. Materials and methods: This study is a retrospective review of mini-CEXs completed by ED faculty members from August 2009 to December 2010. All PGY-1 residents enrolled in this study rotated through the one-month EM training. Each PGY-1 resident received one week of trauma training and three weeks of non-trauma training. The clinical competencies of each PGY-1 resident were evaluated with mini-CEXs, rated by a trauma surgeon and three emergency physicians (EPs). We analyzed the validity of weekly mini-CEX and the impact of seniority and specialty training of ED faculties on observation time, feedback time and rating scores. Results: Fifty-seven ED faculty members (42 EPs and 15 trauma surgeons) evaluated 183 PGY-1 residents during the 17 months of EM training. ED faculties with different specialty training provided similar assessment processes. Most competencies were rated significantly higher by trauma surgeons than by EPs. On the computerized mini-CEX rating, no data was missed and junior EPs rated all competencies significantly higher. The evaluators and PGY-1 residents were generally satisfied with the computerized format. As compared to the first assessment, only some competencies of PGY-1 residents were rated significantly higher in subsequent evaluations. Conclusion: The seniority and specialty training of ED faculty affected the mini-CEX ratings. The computer-based mini-CEX facilitated complete data gathering but showed differences for ED faculty with different levels of seniority. Further studies of the reliability and validity of the mini-CEX for PGY-1 EM training are needed.
Title: Implementation of the mini-clinical evaluation exercise in postgraduate Year 1 residency training in emergency medicine: Clinical experience at Chang Gung Memorial Hospital ScienceDirect

Output: False

Input: Consider Input: Paragraph: Previously developed Asn-Gly-Arg (NGR) peptide-modified multifunctional poly(ethyleneimine)-poly(ethylene glycol) (PEI-PEG)-based nanoparticles (TPIC) have been considered to be promising carriers for the co-delivery of DNA and doxorubicin (DOX). As a continued effort, the aim of the present study was to further evaluate the interaction between TPIC and human umbilical vein endothelial cells (HUVEC) to better understand the cellular entry mechanism. In the present investigation, experiments relevant to co-localization, endocytosis inhibitors and factors influencing the internalization were performed. Without any treatment, there was no co-localization between aminopeptidase N/CD13 (APN/CD13) and caveolin 1 (CAV1). However, co-localization between CD13 and CAV1 was observed when cells were incubated with an anti-CD13 antibody or TPIC. As compared with antibody treatment, TPIC accelerated the speed and enhanced the degree of co-localization. TPIC entered HUVEC not only together with CD13 but also together with CAV1. However, this internalization was not dependent on the enzyme activity of CD13 but could be inhibited by methyl--eyclodextfin (MCD), further identifying the involvement of caveolae-mediated endocytosis (CvME). This conclusion was also verified by endocytosis inhibitor experiments.
Title: A preliminary study on the interaction between Asn-Gly-Arg (NGR)-modified multifunctional nanoparticles and vascular epithelial cells-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Output: False

Input: Consider Input: Paragraph: Individual-based epidemiology models are used to study the effects of public health interventions and changes in individual behavior to the dynamics of infectious diseases [1] . A detailed description of the individual-based model used in simulating the outbreaks in this study is presented in [2] . The individual-based model is made up of a dynamic social contact network and a disease transmission model. The social contact network which is a synthetic representation of a particular geographical region is generated using United States Census data. The structure of the underlying network is important since interactions between agents influences how disease propagates during epidemic simulations. In this initial study, neither changes in individual behavior nor intervention strategies are explored. However, in later studies to better understand the implications of specific intervention strategies, we would forecast disease dynamics given that effective measures have been introduced to control the spread of an outbreak. The construction of the dynamic social contact network requires two steps. In step 1 a synthetic population is created. Individuals in the synthetic population are tagged to realistic demographics while preserving the confidentiality of the original data sets. Each individual is assigned to a household using a decision tree based on demographic information (such as number of people in a household, number of children etc.) from data provided in SF3 and PUMA (Public Use Microdata Area) census files. Households are placed in realistic geographical regions. The synthetic population is statistically identical to the census aggregated at the block level. More information can be found in [3], [4] and [5]. Step 2 assigns a daily activity list with specified durations (start and end times) to each household based on several thousand responses to an activity or time-use survey. The activity templates which vary by region given factors such as the geographical location and age composition of the population, are created based on the National
Title: A Simulation Optimization Approach to Epidemic Forecasting Supporting Information Individual-based Model
Output: False